WorldWideScience

Sample records for global monthly precipitation

  1. The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present)

    Science.gov (United States)

    Adler, Robert F.; Huffman, George J.; Chang, Alfred; Ferraro, Ralph; Xie, Ping-Ping; Janowiak, John; Rudolf, Bruno; Schneider, Udo; Curtis, Scott; Bolvin, David

    2003-01-01

    The Global Precipitation Climatology Project (GPCP) Version 2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5 degrees x 2.5 degrees latitude-longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit-satellite infrared data, and rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The data set is extended back into the premicrowave era (before 1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the raingauge analysis. This monthly analysis is the foundation for the GPCP suite of products including those at finer temporal resolution, satellite estimate, and error estimates for each field. The 23-year GPCP climatology is characterized, along with time and space variations of precipitation.

  2. Global Precipitation Analyses at Time Scales of Monthly to 3-Hourly

    Science.gov (United States)

    Adler, Robert F.; Huffman, George; Curtis, Scott; Bolvin, David; Nelkin, Eric; Einaudi, Franco (Technical Monitor)

    2002-01-01

    Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM (Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the Goodyear data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the Goodyear period. Monthly anomalies of precipitation are related to ENRON variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1 degree latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is described. Finally, a TRMM-based Based analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous OR observations and merges the various calibrated observations into a final, Baehr resolution map. This TRMM standard product will be available for the entire TRMM period (January Represent). A real-time version of this merged product is being produced and is available at 0.25 degree latitude-longitude resolution over the latitude range from 50 deg. N -50 deg. S. Examples will be shown, including its use in monitoring flood conditions.

  3. Global Precipitation Climatology Project (GPCP) Climate Data Record (CDR), Version 2.3 (Monthly)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Precipitation Climatology Project (GPCP) consists of monthly satellite-gauge and associated precipitation error estimates and covers the period January...

  4. The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset

    Science.gov (United States)

    Huffman, George J.; Adler, Robert F.; Arkin, Philip; Chang, Alfred; Ferraro, Ralph; Gruber, Arnold; Janowiak, John; McNab, Alan; Rudolf, Bruno; Schneider, Udo

    1997-01-01

    The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global, monthly precipitation dataset covering the period July 1987 through December 1995. The primary product in the dataset is a merged analysis incorporating precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit -satellite infrared data, and rain gauge observations. The dataset also contains the individual input fields, a combination of the microwave and infrared satellite estimates, and error estimates for each field. The data are provided on 2.5 deg x 2.5 deg latitude-longitude global grids. Preliminary analyses show general agreement with prior studies of global precipitation and extends prior studies of El Nino-Southern Oscillation precipitation patterns. At the regional scale there are systematic differences with standard climatologies.

  5. The global historical climatology network: Long-term monthly temperature, precipitation, and pressure data

    International Nuclear Information System (INIS)

    Vose, R.S.; Schmoyer, R.L.; Peterson, T.C.; Steurer, P.M.; Heim, R.R. Jr.; Karl, T.R.; Eischeid, J.K.

    1992-01-01

    Interest in global climate change has risen dramatically during the past several decades. In a similar fashion, the number of data sets available to study global change has also increased. Unfortunately, many different organizations and researchers have compiled these data sets, making it confusing and time consuming for individuals to acquire the most comprehensive data. In response to this rapid growth in the number of global data sets, DOE's Carbon Dioxide Information Analysis Center (CDIAC) and NOAA's National Climatic Data Center (NCDC) established the Global Historical Climatology Network (GHCN) project. The purpose of this project is to compile an improved data set of long-term monthly mean temperature, precipitation, sea level pressure, and station pressure for as dense a network of global stations as possible. Specifically, the GHCN project seeks to consolidate the numerous preexisting national-, regional-, and global-scale data sets into a single global data base; to subject the data to rigorous quality control; and to update, enhance, and distribute the data set at regular intervals. The purpose of this paper is to describe the compilation and contents of the GHCN data base (i.e., GHCN Version 1.0)

  6. Probability of occurrence of monthly and seasonal winter precipitation over Northwest India based on antecedent-monthly precipitation

    Science.gov (United States)

    Nageswararao, M. M.; Mohanty, U. C.; Dimri, A. P.; Osuri, Krishna K.

    2018-05-01

    Winter (December, January, and February (DJF)) precipitation over northwest India (NWI) is mainly associated with the eastward moving mid-latitude synoptic systems, western disturbances (WDs), embedded within the subtropical westerly jet (SWJ), and is crucial for Rabi (DJF) crops. In this study, the role of winter precipitation at seasonal and monthly scale over NWI and its nine meteorological subdivisions has been analyzed. High-resolution (0.25° × 0.25°) gridded precipitation data set of India Meteorological Department (IMD) for the period of 1901-2013 is used. Results indicated that the seasonal precipitation over NWI is below (above) the long-term mean in most of the years, when precipitation in any of the month (December/January/February) is in deficit (excess). The contribution of December precipitation (15-20%) to the seasonal (DJF) precipitation is lesser than January (35-40%) and February (35-50%) over all the subdivisions. December (0.60), January (0.57), and February (0.69) precipitation is in-phase (correlation) with the corresponding winter season precipitation. However, January precipitation is not in-phase with the corresponding December (0.083) and February (-0.03) precipitation, while December is in-phase with the February (0.21). When monthly precipitation (December or January or December-January or February) at subdivision level over NWI is excess (deficit); then, the probability of occurrence of seasonal excess (deficit) precipitation is high (almost nil). When antecedent-monthly precipitation is a deficit or excess, the probability of monthly (January or February or January + February) precipitation to be a normal category is >60% over all the subdivisions. This study concludes that the December precipitation is a good indicator to estimate the performance of January, February, January-February, and the seasonal (DJF) precipitation.

  7. Climate Prediction Center (CPC)Monthly Precipitation Reconstruction (PREC) Spatial Resolution of 2.5 degree

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This global monthly precipitation analysis is called the Climate Prediction Center (CPC) Precipitation Reconstruction (PREC). This analysis consists of two...

  8. Climate Prediction Center (CPC)Monthly Precipitation Reconstruction (PREC) at Spatial Resolution of 1 degree.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This global monthly precipitation analysis is called the Climate Prediction Center (CPC) Precipitation Reconstruction (PREC). This analysis consists of two...

  9. Climate Prediction Center(CPC) Monthly Precipitation Reconstruction (PREC)at Spatial Resolution of 0.5 degree.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This global monthly precipitation analysis is called the Climate Prediction Center (CPC) Precipitation Reconstruction (PREC). This analysis consists of two...

  10. A global satellite assisted precipitation climatology

    Science.gov (United States)

    Funk, Christopher C.; Verdin, Andrew P.; Michaelsen, Joel C.; Pedreros, Diego; Husak, Gregory J.; Peterson, P.

    2015-01-01

    Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05°) global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate

  11. Global Precipitation Responses to Land Hydrological Processes

    Science.gov (United States)

    Lo, M.; Famiglietti, J. S.

    2012-12-01

    Several studies have established that soil moisture increases after adding a groundwater component in land surface models due to the additional supply of subsurface water. However, impacts of groundwater on the spatial-temporal variability of precipitation have received little attention. Through the coupled groundwater-land-atmosphere model (NCAR Community Atmosphere Model + Community Land Model) simulations, this study explores how groundwater representation in the model alters the precipitation spatiotemporal distributions. Results indicate that the effect of groundwater on the amount of precipitation is not globally homogeneous. Lower tropospheric water vapor increases due to the presence of groundwater in the model. The increased water vapor destabilizes the atmosphere and enhances the vertical upward velocity and precipitation in tropical convective regions. Precipitation, therefore, is inhibited in the descending branch of convection. As a result, an asymmetric dipole is produced over tropical land regions along the equator during the summer. This is analogous to the "rich-get-richer" mechanism proposed by previous studies. Moreover, groundwater also increased short-term (seasonal) and long-term (interannual) memory of precipitation for some regions with suitable groundwater table depth and found to be a function of water table depth. Based on the spatial distributions of the one-month-lag autocorrelation coefficients as well as Hurst coefficients, air-land interaction can occur from short (several months) to long (several years) time scales. This study indicates the importance of land hydrological processes in the climate system and the necessity of including the subsurface processes in the global climate models.

  12. Climate Prediction Center (CPC) Monthly Precipitation Reconstruction of Ocean(PRECO)at Spatial Resolution of 2.5 degree.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This global monthly precipitation analysis is called the Climate Prediction Center (CPC) Precipitation Reconstruction (PREC). This analysis consists of two...

  13. A Global Precipitation Perspective on Persistent Extratropical Flow Anomalies

    Science.gov (United States)

    Huffman, George J.; Adler, Robert F.; Bolvin, David T.

    1999-01-01

    Two globally-complete, observation-only precipitation datasets have recently been developed for the Global Precipitation Climatology Project (GPCP). Both depend heavily on a variety of satellite input, as well as gauge data over land. The first, Version 2 x 79, provides monthly estimates on a 2.5 deg x 2.5 deg lat/long grid for the period 1979 through late 1999 (by the time of the conference). The second, the One-Degree Daily (1DD), provides daily estimates on a 1 deg x 1 deg grid for the period 1997 through late 1999 (by the time of the conference). Both are in beta test preparatory to release as official GPCP products. These datasets provide a unique perspective on the hydrological effects of the various atmospheric flow anomalies that have been identified by meteorologists. In this paper we discuss the regional precipitation effects that result from persistent extratropical flow anomalies. We will focus on the Pacific-North America (PNA) and North Atlantic Oscillation (NAO) patterns. Each characteristically becomes established on synoptic time scales, but then persists for periods that can exceed a month. The onset phase of each appears to have systematic mobile features, while the mature phase tend to be more stationary. Accordingly, composites of monthly data for outstanding positive and negative events (separately) contained in the 20-year record reveal the climatological structure of the precipitation during the mature phase. The climatological anomalies of the positive, negative, and (positive-negative) composites show the expected storm-track-related shifts in precipitation, and provide the advantage of putting the known precipitation effects over land in the context of the total pattern over land and ocean. As well, this global perspective points out some unexpected areas of correlation. Day-by-day composites of daily data anchored to the onset date demonstrate the systematic features during the onset. Although the 1DD has a fairly short record, some

  14. Statistical significance of trends in monthly heavy precipitation over the US

    KAUST Repository

    Mahajan, Salil

    2011-05-11

    Trends in monthly heavy precipitation, defined by a return period of one year, are assessed for statistical significance in observations and Global Climate Model (GCM) simulations over the contiguous United States using Monte Carlo non-parametric and parametric bootstrapping techniques. The results from the two Monte Carlo approaches are found to be similar to each other, and also to the traditional non-parametric Kendall\\'s τ test, implying the robustness of the approach. Two different observational data-sets are employed to test for trends in monthly heavy precipitation and are found to exhibit consistent results. Both data-sets demonstrate upward trends, one of which is found to be statistically significant at the 95% confidence level. Upward trends similar to observations are observed in some climate model simulations of the twentieth century, but their statistical significance is marginal. For projections of the twenty-first century, a statistically significant upwards trend is observed in most of the climate models analyzed. The change in the simulated precipitation variance appears to be more important in the twenty-first century projections than changes in the mean precipitation. Stochastic fluctuations of the climate-system are found to be dominate monthly heavy precipitation as some GCM simulations show a downwards trend even in the twenty-first century projections when the greenhouse gas forcings are strong. © 2011 Springer-Verlag.

  15. Climatology and Interannual Variability of Quasi-Global Intense Precipitation Using Satellite Observations

    Science.gov (United States)

    Ricko, Martina; Adler, Robert F.; Huffman, George J.

    2016-01-01

    Climatology and variations of recent mean and intense precipitation over a near-global (50 deg. S 50 deg. N) domain on a monthly and annual time scale are analyzed. Data used to derive daily precipitation to examine the effects of spatial and temporal coverage of intense precipitation are from the current Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 version 7 precipitation product, with high spatial and temporal resolution during 1998 - 2013. Intense precipitation is defined by several different parameters, such as a 95th percentile threshold of daily precipitation, a mean precipitation that exceeds that percentile, or a fixed threshold of daily precipitation value [e.g., 25 and 50 mm day(exp -1)]. All parameters are used to identify the main characteristics of spatial and temporal variation of intense precipitation. High correlations between examined parameters are observed, especially between climatological monthly mean precipitation and intense precipitation, over both tropical land and ocean. Among the various parameters examined, the one best characterizing intense rainfall is a fraction of daily precipitation Great than or equal to 25 mm day(exp. -1), defined as a ratio between the intense precipitation above the used threshold and mean precipitation. Regions that experience an increase in mean precipitation likely experience a similar increase in intense precipitation, especially during the El Nino Southern Oscillation (ENSO) events. Improved knowledge of this intense precipitation regime and its strong connection to mean precipitation given by the fraction parameter can be used for monitoring of intense rainfall and its intensity on a global to regional scale.

  16. Global warming without global mean precipitation increase?

    Science.gov (United States)

    Salzmann, Marc

    2016-06-01

    Global climate models simulate a robust increase of global mean precipitation of about 1.5 to 2% per kelvin surface warming in response to greenhouse gas (GHG) forcing. Here, it is shown that the sensitivity to aerosol cooling is robust as well, albeit roughly twice as large. This larger sensitivity is consistent with energy budget arguments. At the same time, it is still considerably lower than the 6.5 to 7% K(-1) decrease of the water vapor concentration with cooling from anthropogenic aerosol because the water vapor radiative feedback lowers the hydrological sensitivity to anthropogenic forcings. When GHG and aerosol forcings are combined, the climate models with a realistic 20th century warming indicate that the global mean precipitation increase due to GHG warming has, until recently, been completely masked by aerosol drying. This explains the apparent lack of sensitivity of the global mean precipitation to the net global warming recently found in observations. As the importance of GHG warming increases in the future, a clear signal will emerge.

  17. The Global Precipitation Patterns Associated with Short-Term Extratropical Climate Fluctuations

    Science.gov (United States)

    Huffman, George J.; Adler, Robert F.; Bolvin, David T.

    1999-01-01

    Two globally-complete, observation-only precipitation datasets have recently been developed for the Global Precipitation Climatology Project (GPCP). Both depend heavily on a variety of satellite input, as well as gauge data over land. The first, Version 2x79, provides monthly estimates on a 2.5 deg. x 2.5 deg. lat/long grid for the period 1979 through late 1999 (by the time of the conference). The second, the One-Degree Daily (1DD), provides daily estimates on a 1 deg. x l deg. grid for the period 1997 through late 1999 (by the time of the conference). Both are in beta test preparatory to release as official GPCP products. These datasets provide a unique perspective on the hydrological effects of the various atmospheric flow anomalies that have been identified by meteorologists. In this paper we discuss the regional precipitation effects that result from persistent extratropical flow anomalies. We will focus on the Pacific-North America (PNA) and North Atlantic Oscillation (NAO) patterns. Each characteristically becomes established on synoptic time scales, but then persists for periods that can exceed a month. The onset phase of each appears to have systematic mobile features, while the mature phase tend to be more stationary. Accordingly, composites of monthly data for outstanding positive and negative events (separately) contained in the 20-year record reveal the climatological structure of the precipitation during the mature phase. The climatological anomalies of the positive, negative, and (positive-negative) composites show the expected storm-track-related shifts in precipitation, and provide the advantage of putting the known precipitation effects over land in the context of the total pattern over land and ocean. As well, this global perspective points out some unexpected areas of correlation. Day-by-day composites of daily data anchored to the onset date demonstrate the systematic features during the onset. Although the 1DD has a fairly short record, some

  18. Effective Assimilation of Global Precipitation

    Science.gov (United States)

    Lien, G.; Kalnay, E.; Miyoshi, T.; Huffman, G. J.

    2012-12-01

    Assimilating precipitation observations by modifying the moisture and sometimes temperature profiles has been shown successful in forcing the model precipitation to be close to the observed precipitation, but only while the assimilation is taking place. After the forecast start, the model tends to "forget" the assimilation changes and lose their extra skill after few forecast hours. This suggests that this approach is not an efficient way to modify the potential vorticity field, since this is the variable that the model would remember. In this study, the ensemble Kalman filter (EnKF) method is used to effectively change the potential vorticity field by allowing ensemble members with better precipitation to receive higher weights. In addition to using an EnKF, two other changes in the precipitation assimilation process are proposed to solve the problems related to the highly non-Gaussian nature of the precipitation variable: a) transform precipitation into a Gaussian distribution based on its climatological distribution, and b) only assimilate precipitation at the location where some ensemble members have positive precipitation. The idea is first tested by the observing system simulation experiments (OSSEs) using SPEEDY, a simplified but realistic general circulation model. When the global precipitation is assimilated in addition to conventional rawinsonde observations, both the analyses and the medium range forecasts are significantly improved as compared to only having rawinsonde observations. The improvement is much reduced when only modifying the moisture field with the same approach, which shows the importance of the error covariance between precipitation and all other model variables. The effect of precipitation assimilation is larger in the Southern Hemisphere than that in the Northern Hemisphere because the Northern Hemisphere analyses are already accurate as a result of denser rawinsonde stations. Assimilation of precipitation using a more comprehensive

  19. Global Precipitation Measurement Poster

    Science.gov (United States)

    Azarbarzin, Art

    2010-01-01

    This poster presents an overview of the Global Precipitation Measurement (GPM) constellation of satellites which are designed to measure the Earth's precipitation. It includes the schedule of launches for the various satellites in the constellation, and the coverage of the constellation, It also reviews the mission capabilities, and the mission science objectives.

  20. Variations and Trends in Global and Regional Precipitation Based on the 22-year GPCP (Global Precipitation Climatology Project) and Three-year TRMM (Tropical Rainfall Measuring Mission) Data Sets

    Science.gov (United States)

    Adler, R.; Curtis, S.; Huffman, G.; Bolvin, D.; Nelkin, E.

    2001-05-01

    This paper gives an overview of the analysis of global precipitation over the last few decades and the impact of the new TRMM precipitation observations. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to study global and regional variations and trends and is compared to the much shorter TRMM(Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in global precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. The global trend analysis must be interpreted carefully, however, because the inhomogeneity of the data set makes detecting a small signal very difficult, especially over this relatively short period. The relation of global (and tropical) total precipitation and ENSO events is quantified with no significant signal when land and ocean are combined. Identifying regional trends in precipitation may be more practical. From 1979 to 2000 the tropics have pattern of regional rainfall trends that has an ENSO-like pattern with features of both the El Nino and La Nina. This feature is related to a possible trend in the frequency of ENSO events (either El Nino or La Nina) over the past 20 years. Monthly anomalies of precipitation are related to ENSO variations with clear signals extending into middle and high latitudes of both hemispheres. The El Nino and La Nina mean anomalies are near mirror images of each other and when combined produce an ENSO signal with significant spatial continuity over large distances. A number of the features are shown to extend into high latitudes. Positive anomalies extend in the Southern Hemisphere (S.H.) from the Pacific southeastward across Chile and Argentina into the south Atlantic Ocean. In the Northern Hemisphere (N.H.) the counterpart feature extends across the southern U.S. and Atlantic Ocean into Europe

  1. Repeated and random components in Oklahoma's monthly precipitation record

    Science.gov (United States)

    Precipitation across Oklahoma exhibits a high degree of spatial and temporal variability and creates numerous water resources management challenges. The monthly precipitation record of the Central Oklahoma climate division was evaluated in a proof-of-concept to establish whether a simple monthly pre...

  2. A globally calibrated scheme for generating daily meteorology from monthly statistics: Global-WGEN (GWGEN) v1.0

    Science.gov (United States)

    Sommer, Philipp S.; Kaplan, Jed O.

    2017-10-01

    While a wide range of Earth system processes occur at daily and even subdaily timescales, many global vegetation and other terrestrial dynamics models historically used monthly meteorological forcing both to reduce computational demand and because global datasets were lacking. Recently, dynamic land surface modeling has moved towards resolving daily and subdaily processes, and global datasets containing daily and subdaily meteorology have become available. These meteorological datasets, however, cover only the instrumental era of the last approximately 120 years at best, are subject to considerable uncertainty, and represent extremely large data files with associated computational costs of data input/output and file transfer. For periods before the recent past or in the future, global meteorological forcing can be provided by climate model output, but the quality of these data at high temporal resolution is low, particularly for daily precipitation frequency and amount. Here, we present GWGEN, a globally applicable statistical weather generator for the temporal downscaling of monthly climatology to daily meteorology. Our weather generator is parameterized using a global meteorological database and simulates daily values of five common variables: minimum and maximum temperature, precipitation, cloud cover, and wind speed. GWGEN is lightweight, modular, and requires a minimal set of monthly mean variables as input. The weather generator may be used in a range of applications, for example, in global vegetation, crop, soil erosion, or hydrological models. While GWGEN does not currently perform spatially autocorrelated multi-point downscaling of daily weather, this additional functionality could be implemented in future versions.

  3. Global Precipitation Measurement (GPM) L-6

    Science.gov (United States)

    Neeck, Steven P.; Kakar, Ramesh K.; Azarbarzin, Ardeshir A.; Hou, Arthur Y.

    2013-10-01

    The Global Precipitation Measurement (GPM) mission will advance the measurement of global precipitation, making possible high spatial resolution precipitation measurements. GPM will provide the first opportunity to calibrate measurements of global precipitation across tropical, mid-latitude, and polar regions. The GPM mission has the following scientific objectives: (1) Advance precipitation measurement capability from space through combined use of active and passive remote-sensing techniques; (2) Advance understanding of global water/energy cycle variability and fresh water availability; (3) Improve climate prediction by providing the foundation for better understanding of surface water fluxes, soil moisture storage, cloud/precipitation microphysics and latent heat release in the Earth's atmosphere; (4) Advance Numerical Weather Prediction (NWP) skills through more accurate and frequent measurements of instantaneous rain rates; and (5) Improve high impact natural hazard (flood/drought, landslide, and hurricane hazard) prediction capabilities. The GPM mission centers on the deployment of a Core Observatory carrying an advanced radar / radiometer system to measure precipitation from space and serve as a reference standard to unify precipitation measurements from a constellation of research and operational satellites. GPM, jointly led with the Japan Aerospace Exploration Agency (JAXA), involves a partnership with other international space agencies including the French Centre National d'Études Spatiales (CNES), the Indian Space Research Organisation (ISRO), the U.S. National Oceanic and Atmospheric Administration (NOAA), the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), and others. The GPM Core Observatory is currently being prepared for shipment to Japan for launch. Launch is scheduled for February 2014 from JAXA's Tanegashima Space Center on an H-IIA 202 launch vehicle.

  4. A precipitation database of station-based daily and monthly measurements for West Africa: Overview, quality control and harmonization

    Science.gov (United States)

    Bliefernicht, Jan; Waongo, Moussa; Annor, Thompson; Laux, Patrick; Lorenz, Manuel; Salack, Seyni; Kunstmann, Harald

    2017-04-01

    West Africa is a data sparse region. High quality and long-term precipitation data are often not readily available for applications in hydrology, agriculture, meteorology and other needs. To close this gap, we use multiple data sources to develop a precipitation database with long-term daily and monthly time series. This database was compiled from 16 archives including global databases e.g. from the Global Historical Climatology Network (GHCN), databases from research projects (e.g. the AMMA database) and databases of the national meteorological services of some West African countries. The collection consists of more than 2000 precipitation gauges with measurements dating from 1850 to 2015. Due to erroneous measurements (e.g. temporal offsets, unit conversion errors), missing values and inconsistent meta-data, the merging of this precipitation dataset is not straightforward and requires a thorough quality control and harmonization. To this end, we developed geostatistical-based algorithms for quality control of individual databases and harmonization to a joint database. The algorithms are based on a pairwise comparison of the correspondence of precipitation time series in dependence to the distance between stations. They were tested for precipitation time series from gages located in a rectangular domain covering Burkina Faso, Ghana, Benin and Togo. This harmonized and quality controlled precipitation database was recently used for several applications such as the validation of a high resolution regional climate model and the bias correction of precipitation projections provided the Coordinated Regional Climate Downscaling Experiment (CORDEX). In this presentation, we will give an overview of the novel daily and monthly precipitation database and the algorithms used for quality control and harmonization. We will also highlight the quality of global and regional archives (e.g. GHCN, GSOD, AMMA database) in comparison to the precipitation databases provided by the

  5. Global Precipitation Climatology Project (GPCP) Climate Data Record (CDR), Version 1.3 (Daily)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The GPCP Daily analysis is a companion to the GPCP Monthly analysis, and provides globally complete precipitation estimates at a spatial resolution of one degree...

  6. Global daily precipitation fields from bias-corrected rain gauge and satellite observations. Pt. 1. Design and development

    Energy Technology Data Exchange (ETDEWEB)

    Kottek, M.; Rubel, F. [Univ. of Veterinary Medicine, Vienna (Austria). Biometeorology Group

    2007-10-15

    Global daily precipitation analyses are mainly based on satellite estimates, often calibrated with monthly ground analyses or merged with model predictions. We argue here that an essential improvement of their accuracy is only possible by incorporation of daily ground measurements. In this work we apply geostatistical methods to compile a global precipitation product based on daily rain gauge measurements. The raw ground measurements, disseminated via Global Telecommunication System (GTS), are corrected for their systematic measurement errors and interpolated onto a global 1 degree grid. For interpolation ordinary block kriging is applied, with precalculated spatial auto-correlation functions (ACFs). This technique allows to incorporate additional climate information. First, monthly ACFs are calculated from the daily data; second, they are regionalised according to the five main climatic zones of the Koeppen-Geiger climate classification. The interpolation error, a by-product of kriging, is used to flag grid points as missing if the error is above a predefined threshold. But for many applications missing values constitute a problem. Due to a combination of the ground analyses with the daily multi-satellite product of the Global Precipitation Climatology Project (GPCP-1DD) not only these missing values are replaced but also the spatial structure of the satellite estimates is considered. As merging method bivariate ordinary co-kriging is applied. The ACFs necessary for the gauge and the satellite fields as well as the corresponding spatial cross-correlation functions (CCFs) are again precalculated for each of the five main climatic zones and for each individual month. As a result two new global daily data sets for the period 1996 up to today will be available on the Internet (www.gmes-geoland.info): A precipitation product over land, analysed from ground measurements; and a global precipitation product merged from this and the GPCP-1DD multi-satellite product. (orig.)

  7. Substantial proportion of global streamflow less than three months old

    Science.gov (United States)

    Jasechko, Scott; Kirchner, James W.; Welker, Jeffrey M.; McDonnell, Jeffrey J.

    2016-02-01

    Biogeochemical cycles, contaminant transport and chemical weathering are regulated by the speed at which precipitation travels through landscapes and reaches streams. Streamflow is a mixture of young and old precipitation, but the global proportions of these young and old components are not known. Here we analyse seasonal cycles of oxygen isotope ratios in rain, snow and streamflow compiled from 254 watersheds around the world, and calculate the fraction of streamflow that is derived from precipitation that fell within the past two or three months. This young streamflow accounts for about a third of global river discharge, and comprises at least 5% of discharge in about 90% of the catchments we investigated. We conclude that, although typical catchments have mean transit times of years or even decades, they nonetheless can rapidly transmit substantial fractions of soluble contaminant inputs to streams. Young streamflow is less prevalent in steeper landscapes, which suggests they are characterized by deeper vertical infiltration. Because young streamflow is derived from less than 0.1% of global groundwater storage, we conclude that this thin veneer of aquifer storage will have a disproportionate influence on stream water quality.

  8. Statistical evaluation of the performance of gridded monthly precipitation products from reanalysis data, satellite estimates, and merged analyses over China

    Science.gov (United States)

    Deng, Xueliang; Nie, Suping; Deng, Weitao; Cao, Weihua

    2018-04-01

    In this study, we compared the following four different gridded monthly precipitation products: the National Centers for Environmental Prediction version 2 (NCEP-2) reanalysis data, the satellite-based Climate Prediction Center Morphing technique (CMORPH) data, the merged satellite-gauge Global Precipitation Climatology Project (GPCP) data, and the merged satellite-gauge-model data from the Beijing Climate Center Merged Estimation of Precipitation (BMEP). We evaluated the performances of these products using monthly precipitation observations spanning the period of January 2003 to December 2013 from a dense, national, rain gauge network in China. Our assessment involved several statistical techniques, including spatial pattern, temporal variation, bias, root-mean-square error (RMSE), and correlation coefficient (CC) analysis. The results show that NCEP-2, GPCP, and BMEP generally overestimate monthly precipitation at the national scale and CMORPH underestimates it. However, all of the datasets successfully characterized the northwest to southeast increase in the monthly precipitation over China. Because they include precipitation gauge information from the Global Telecommunication System (GTS) network, GPCP and BMEP have much smaller biases, lower RMSEs, and higher CCs than NCEP-2 and CMORPH. When the seasonal and regional variations are considered, NCEP-2 has a larger error over southern China during the summer. CMORPH poorly reproduces the magnitude of the precipitation over southeastern China and the temporal correlation over western and northwestern China during all seasons. BMEP has a lower RMSE and higher CC than GPCP over eastern and southern China, where the station network is dense. In contrast, BMEP has a lower CC than GPCP over western and northwestern China, where the gauge network is relatively sparse.

  9. The assessment of Global Precipitation Measurement estimates over the Indian subcontinent

    Science.gov (United States)

    Murali Krishna, U. V.; Das, Subrata Kumar; Deshpande, Sachin M.; Doiphode, S. L.; Pandithurai, G.

    2017-08-01

    Accurate and real-time precipitation estimation is a challenging task for current and future spaceborne measurements, which is essential to understand the global hydrological cycle. Recently, the Global Precipitation Measurement (GPM) satellites were launched as a next-generation rainfall mission for observing the global precipitation characteristics. The purpose of the GPM is to enhance the spatiotemporal resolution of global precipitation. The main objective of the present study is to assess the rainfall products from the GPM, especially the Integrated Multi-satellitE Retrievals for the GPM (IMERG) data by comparing with the ground-based observations. The multitemporal scale evaluations of rainfall involving subdaily, diurnal, monthly, and seasonal scales were performed over the Indian subcontinent. The comparison shows that the IMERG performed better than the Tropical Rainfall Measuring Mission (TRMM)-3B42, although both rainfall products underestimated the observed rainfall compared to the ground-based measurements. The analyses also reveal that the TRMM-3B42 and IMERG data sets are able to represent the large-scale monsoon rainfall spatial features but are having region-specific biases. The IMERG shows significant improvement in low rainfall estimates compared to the TRMM-3B42 for selected regions. In the spatial distribution, the IMERG shows higher rain rates compared to the TRMM-3B42, due to its enhanced spatial and temporal resolutions. Apart from this, the characteristics of raindrop size distribution (DSD) obtained from the GPM mission dual-frequency precipitation radar is assessed over the complex mountain terrain site in the Western Ghats, India, using the DSD measured by a Joss-Waldvogel disdrometer.

  10. Evaluation of IMERG and TRMM 3B43 Monthly Precipitation Products over Mainland China

    Directory of Open Access Journals (Sweden)

    Fengrui Chen

    2016-06-01

    Full Text Available As the successor of the Tropical Rainfall Measuring Mission (TRMM, the Global Precipitation Measurement (GPM mission significantly improves the spatial resolution of precipitation estimates from 0.25° to 0.1°. The present study analyzed the error structures of Integrated Multisatellite Retrievals for GPM (IMERG monthly precipitation products over Mainland China from March 2014 to February 2015 using gauge measurements at multiple spatiotemporal scales. Moreover, IMERG products were also compared with TRMM 3B43 products. The results show that: (1 overall, IMERG can capture the spatial patterns of precipitation over China well. It performs a little better than TRMM 3B43 at seasonal and monthly scales; (2 the performance of IMERG varies greatly spatially and temporally. IMERG performs better at low latitudes than at middle latitudes, and shows worse performance in winter than at other times; (3 compared with TRMM 3B43, IMERG significantly improves the estimation accuracy of precipitation over the Xinjiang region and the Qinghai-Tibetan Plateau, especially over the former where IMERG increases Pearson correlation coefficient by 0.18 and decreases root-mean-square error by 54.47 mm for annual precipitation estimates. However, most IMERG products over these areas are unreliable; and (4 IMERG shows poor performance in winter as TRMM 3B43 even if GPM improved its ability to sense frozen precipitation. Most of them over North China are unreliable during this period.

  11. Monthly Mean Precipitation Sums at Russian Arctic Stations, 1966-1990

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains monthly mean precipitation sums from Russian arctic stations. Precipitation measurements were acquired using a Tretyakov precipitation gauge....

  12. The linkage between geopotential height and monthly precipitation in Iran

    Science.gov (United States)

    Shirvani, Amin; Fadaei, Amir Sabetan; Landman, Willem A.

    2018-04-01

    This paper investigates the linkage between large-scale atmospheric circulation and monthly precipitation during November to April over Iran. Canonical correlation analysis (CCA) is used to set up the statistical linkage between the 850 hPa geopotential height large-scale circulation and monthly precipitation over Iran for the period 1968-2010. The monthly precipitation dataset for 50 synoptic stations distributed in different climate regions of Iran is considered as the response variable in the CCA. The monthly geopotential height reanalysis dataset over an area between 10° N and 60° N and from 20° E to 80° E is utilized as the explanatory variable in the CCA. Principal component analysis (PCA) as a pre-filter is used for data reduction for both explanatory and response variables before applying CCA. The optimal number of principal components and canonical variables to be retained in the CCA equations is determined using the highest average cross-validated Kendall's tau value. The 850 hPa geopotential height pattern over the Red Sea, Saudi Arabia, and Persian Gulf is found to be the major pattern related to Iranian monthly precipitation. The Pearson correlation between the area averaged of the observed and predicted precipitation over the study area for Jan, Feb, March, April, November, and December months are statistically significant at the 5% significance level and are 0.78, 0.80, 0.82, 0.74, 0.79, and 0.61, respectively. The relative operating characteristic (ROC) indicates that the highest scores for the above- and below-normal precipitation categories are, respectively, for February and April and the lowest scores found for December.

  13. Cluster Analysis of Monthly Precipitation over the Western Maritime Continent under Climate Change

    Directory of Open Access Journals (Sweden)

    Saurabh K Singh

    2017-11-01

    Full Text Available Changes in climate because of global warming during the 20th and 21st centuries have a direct impact on the hydrological cycle as driven by precipitation. However, studying precipitation over the Western Maritime Continent (WMC is a great challenge, as the WMC has a complex topography and weather system. Understanding changes in precipitation patterns and their groupings is an important aspect of planning mitigation measures to minimize flood and drought risk as well as of understanding the redistribution of precipitation arising from climate change. This paper employs Ward’s hierarchical clustering on regional climate model (RCM-simulated monthly precipitation gridded data over 42 approximately evenly distributed grid stations from the years 2030 to 2060. The aim was to investigate spatial and temporal groupings over the four major landmasses in the WMC and to compare these with historical precipitation groupings. The results showed that the four large-scale islands of Java, Sumatra, Peninsular Malaysia and Borneo would experience a significant spatial redistribution of precipitation over the years 2030 to 2060, as compared to historical patterns from 1980 to 2005. The spatial groups were also compared for two future forcing scenarios, representative concentration pathways (RCPs 4.5 and 8.5, and different groupings over the Borneo region were observed.

  14. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015

    Science.gov (United States)

    Abatzoglou, John T.; Dobrowski, Solomon Z.; Parks, Sean A.; Hegewisch, Katherine C.

    2018-01-01

    We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958-2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.

  15. Identifying external influences on global precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Marvel, K.; Bonfils, C.

    2013-11-11

    Changes in global (ocean and land) precipitation are among the most important and least well-understood consequences of climate change. Increasing greenhouse gas concentrations are thought to affect the zonal-mean distribution of precipitation through two basic mechanisms. First, increasing temperatures will lead to an intensification of the hydrological cycle (“thermodynamic” changes). Second, changes in atmospheric circulation patterns will lead to poleward displacement of the storm tracks and subtropical dry zones and to a widening of the tropical belt (“dynamic” changes). We demonstrate that both these changes are occurring simultaneously in global precipitation, that this behavior cannot be explained by internal variability alone, and that external influences are responsible for the observed precipitation changes. Whereas existing model experiments are not of sufficient length to differentiate between natural and anthropogenic forcing terms at the 95% confidence level, we present evidence that the observed trends result from human activities.

  16. The Relationships between Tropical Pacific and Atlantic SST and Northeast Brazil Monthly Precipitation.

    Science.gov (United States)

    Bertacchi Uvo, Cintia; Repelli, Carlos A.; Zebiak, Stephen E.; Kushnir, Yochanan

    1998-04-01

    The monthly patterns of northeast Brazil (NEB) precipitation are analyzed in relation to sea surface temperature (SST) in the tropical Pacific and Atlantic Oceans, using singular value decomposition. It is found that the relationships between precipitation and SST in both basins vary considerably throughout the rainy season (February-May). In January, equatorial Pacific SST is weakly correlated with precipitation in small areas of southern NEB, but Atlantic SST shows no significant correlation with regional precipitation. In February, Pacific SST is not well related to precipitation, but south equatorial Atlantic SST is positively correlated with precipitation over the northern Nordeste, the latter most likely reflecting an anomalously early (or late) southward migration of the ITCZ precipitation zone. During March, equatorial Pacific SST is negatively correlated with Nordeste precipitation, but no consistent relationship between precipitation and Atlantic SST is found. Atlantic SST-precipitation correlations for April and May are the strongest found among all months or either ocean. Precipitation in the Nordeste is positively correlated with SST in the south tropical Atlantic and negatively correlated with SST in the north tropical Atlantic. These relationships are strong enough to determine the structure of the seasonal mean SST-precipitation correlations, even though the corresponding patterns for the earlier months of the season are quite different. Pacific SST-precipitation correlations for April and May are similar to those for March. Extreme wet (dry) years for the Nordeste occur when both Pacific and Atlantic SST patterns for April and May occur simultaneously. A separate analysis reinforces previous findings in showing that SST in the tropical Pacific and the northern tropical Atlantic are positively correlated and that tropical Pacific-south Atlantic correlations are negligible.Time-lagged analyses show the potential for forecasting either seasonal mean

  17. Climate Prediction Center (CPC) Global Precipitation Time Series

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global precipitation time series provides time series charts showing observations of daily precipitation as well as accumulated precipitation compared to normal...

  18. A global gridded dataset of daily precipitation going back to 1950, ideal for analysing precipitation extremes

    Science.gov (United States)

    Contractor, S.; Donat, M.; Alexander, L. V.

    2017-12-01

    Reliable observations of precipitation are necessary to determine past changes in precipitation and validate models, allowing for reliable future projections. Existing gauge based gridded datasets of daily precipitation and satellite based observations contain artefacts and have a short length of record, making them unsuitable to analyse precipitation extremes. The largest limiting factor for the gauge based datasets is a dense and reliable station network. Currently, there are two major data archives of global in situ daily rainfall data, first is Global Historical Station Network (GHCN-Daily) hosted by National Oceanic and Atmospheric Administration (NOAA) and the other by Global Precipitation Climatology Centre (GPCC) part of the Deutsche Wetterdienst (DWD). We combine the two data archives and use automated quality control techniques to create a reliable long term network of raw station data, which we then interpolate using block kriging to create a global gridded dataset of daily precipitation going back to 1950. We compare our interpolated dataset with existing global gridded data of daily precipitation: NOAA Climate Prediction Centre (CPC) Global V1.0 and GPCC Full Data Daily Version 1.0, as well as various regional datasets. We find that our raw station density is much higher than other datasets. To avoid artefacts due to station network variability, we provide multiple versions of our dataset based on various completeness criteria, as well as provide the standard deviation, kriging error and number of stations for each grid cell and timestep to encourage responsible use of our dataset. Despite our efforts to increase the raw data density, the in situ station network remains sparse in India after the 1960s and in Africa throughout the timespan of the dataset. Our dataset would allow for more reliable global analyses of rainfall including its extremes and pave the way for better global precipitation observations with lower and more transparent uncertainties.

  19. Responses of Seasonal Precipitation Intensity to Global Warming

    Science.gov (United States)

    Lan, Chia-Wei; Lo, Min-Hui; Chou, Chia

    2016-04-01

    Under global warming, the water vapor increases with rising temperature at the rate of 7%/K. Most previous studies focus on the spatial differences of precipitation and suggest that wet regions become wetter and dry regions become drier. Our recent studies show a temporal disparity of global precipitation, which the wet season becomes wetter and dry season becomes drier; therefore, the annual range increases. However, such changes in the annual range are not homogeneous globally, and in fact, the drier trend over the ocean is much larger than that over the land, where the dry season does not become drier. Such precipitation change over land is likely because of decreased omega at 500hPa (more upward motion) in the reanalysis datasets from 1980 to 2013. The trends of vertical velocity and moist static energy profile over the increased precipitation regions become more unstable. The instability is most likely attributed to the change in specific humility below 400hPa. Further, we will use Coupled Model Intercomparison Project Phase 5 (CMIP5) archives to investigate whether the precipitation responses in dry season are different between the ocean and land under global warming.

  20. Estimating Climatological Bias Errors for the Global Precipitation Climatology Project (GPCP)

    Science.gov (United States)

    Adler, Robert; Gu, Guojun; Huffman, George

    2012-01-01

    A procedure is described to estimate bias errors for mean precipitation by using multiple estimates from different algorithms, satellite sources, and merged products. The Global Precipitation Climatology Project (GPCP) monthly product is used as a base precipitation estimate, with other input products included when they are within +/- 50% of the GPCP estimates on a zonal-mean basis (ocean and land separately). The standard deviation s of the included products is then taken to be the estimated systematic, or bias, error. The results allow one to examine monthly climatologies and the annual climatology, producing maps of estimated bias errors, zonal-mean errors, and estimated errors over large areas such as ocean and land for both the tropics and the globe. For ocean areas, where there is the largest question as to absolute magnitude of precipitation, the analysis shows spatial variations in the estimated bias errors, indicating areas where one should have more or less confidence in the mean precipitation estimates. In the tropics, relative bias error estimates (s/m, where m is the mean precipitation) over the eastern Pacific Ocean are as large as 20%, as compared with 10%-15% in the western Pacific part of the ITCZ. An examination of latitudinal differences over ocean clearly shows an increase in estimated bias error at higher latitudes, reaching up to 50%. Over land, the error estimates also locate regions of potential problems in the tropics and larger cold-season errors at high latitudes that are due to snow. An empirical technique to area average the gridded errors (s) is described that allows one to make error estimates for arbitrary areas and for the tropics and the globe (land and ocean separately, and combined). Over the tropics this calculation leads to a relative error estimate for tropical land and ocean combined of 7%, which is considered to be an upper bound because of the lack of sign-of-the-error canceling when integrating over different areas with a

  1. Online Assessment of Satellite-Derived Global Precipitation Products

    Science.gov (United States)

    Liu, Zhong; Ostrenga, D.; Teng, W.; Kempler, S.

    2012-01-01

    inter-comparing both versions of TRMM products in their areas of interest. Making this service available to users will help them to better understand associated changes. We plan to implement this inter-comparison in TRMM standard monthly products with the IPWG algorithms. The plans outlined above will complement and accelerate the existing and ongoing validation activities in the community as well as enhance data services for TRMM and the future Global Precipitation Mission (GPM).

  2. Simulations of monthly mean nitrate concentrations in precipitation over East Asia

    International Nuclear Information System (INIS)

    Junling An; Xinjin Cheng; Ueda, Hiromasa; Kajino, Mizuo

    2002-01-01

    Monthly mean nitrate concentrations in precipitation over East Asia (10-55 o N, 75-155 o E) in April, July, September, and December of 1999 were simulated by using a regional air quality Eulerian model (RAQM) with meteorological fields four times per day taken from National Centers for Environmental Prediction. The distribution of the nitrate concentration in precipitation depends significantly on the emission patterns of nitrogen oxides (NO x =NO+NO 2 ) and volatile organic compound (VOC) and seasonal precipitation variability. The downward trend is also revealed, particularly on July and December. Highest concentrations are found in the industrialized regions, i.e., the coastal area of the Mainland of China, the Bay of the Huanghai Sea and the Bohai Sea, Korea, and Southern Japan. Long-range transport may cause elevated concentrations in remote areas downwind of the industrialized regions under favorable meteorological conditions, e.g., low precipitation. Comparison of observation and simulations indicates that the RAQM model reasonably predicts synoptic-scale changes in different months (seasons) and simulated nitrate levels in 4 months fit observed data with the discrepancy within a factor of 2. Exclusion of liquid chemistry within clouds is feasible for regional (1 o x1 o ) and long-term (monthly) nitrate simulations. The uncertainty originates mainly from that of the emission data and modeled precipitation amounts and initial and boundary conditions. (author)

  3. Are climate-related changes to the character of global-mean precipitation predictable?

    International Nuclear Information System (INIS)

    Stephens, Graeme L; Hu, Yongxiang

    2010-01-01

    The physical basis for the change in global-mean precipitation projected to occur with the warming associated with increased greenhouse gases is discussed. The expected increases to column water vapor W control the rate of increase of global precipitation accumulation through its affect on the planet's energy balance. The key role played by changes to downward longwave radiation controlled by this changing water vapor is emphasized. The basic properties of molecular absorption by water vapor dictate that the fractional rate of increase of global-mean precipitation must be significantly less that the fractional rate of increase in water vapor and it is further argued that this reduced rate of precipitation increase implies that the timescale for water re-cycling is increased in the global mean. This further implies less frequent precipitation over a fixed period of time, and the intensity of these less frequent precipitating events must subsequently increase in the mean to realize the increased global accumulation. These changes to the character of global-mean precipitation, predictable consequences of equally predictable changes to W, apply only to the global-mean state and not to the regional or local scale changes in precipitation.

  4. The Mediterranean Moisture Contribution to Climatological and Extreme Monthly Continental Precipitation

    Directory of Open Access Journals (Sweden)

    Danica Ciric

    2018-04-01

    Full Text Available Moisture transport from its sources to surrounding continents is one of the most relevant topics in hydrology, and its role in extreme events is crucial for understanding several processes such as intense precipitation and flooding. In this study, we considered the Mediterranean Sea as the main water source and estimated its contribution to the monthly climatological and extreme precipitation events over the surrounding continental areas. To assess the effect of the Mediterranean Sea on precipitation, we used the Multi-Source Weighted-Ensemble Precipitation (MSWEP database to characterize precipitation. The Lagrangian dispersion model known as FLEXPART was used to estimate the moisture contribution of this source. This contribution was estimated by tracking particles that leave the Mediterranean basin monthly and then calculating water loss (E − P < 0 over the continental region, which was modelled by FLEXPART. The analysis was conducted using data from 1980 to 2015 with a spatial resolution of 0.25°. The results showed that, in general, the spatial pattern of the Mediterranean source’s contribution to precipitation, unlike climatology, is similar during extreme precipitation years in the regions under study. However, while the Mediterranean Sea is usually not an important source of climatological precipitation for some European regions, it is a significant source during extreme precipitation years.

  5. Global precipitations and climate change. Proceedings

    International Nuclear Information System (INIS)

    Desbois, M.; Desalmand, F.

    1994-01-01

    The workshop reviewed the present status of knowledge concerning the past and present evolution of the distribution of precipitations at global scale, related to climate evolution at different time scales. This review was intended to assess the availability and quality of data which could help, through validation and initialization of model studies, to improve our understanding of the processes determining these precipitation changes. On another hand, the modelling specialists presented their actual use of precipitation data. Exchanges of views between the modelling and observing communities were thus made possible, leading to a set of recommendations for future studies. Sessions were then devoted to specific themes: 1) Paleoclimatology, 2) data collection, history and statistics, programmes, 3) methodologies and accuracy of large scale estimation of precipitation from conventional data, 4) estimation of precipitation from satellite data, 5) modelling studies. (orig.)

  6. Global Precipitation Measurement. Report 7; Bridging from TRMM to GPM to 3-Hourly Precipitation Estimates

    Science.gov (United States)

    Shepherd, J. Marshall; Smith, Eric A.; Adams, W. James (Editor)

    2002-01-01

    Historically, multi-decadal measurements of precipitation from surface-based rain gauges have been available over continents. However oceans remained largely unobserved prior to the beginning of the satellite era. Only after the launch of the first Defense Meteorological Satellite Program (DMSP) satellite in 1987 carrying a well-calibrated and multi-frequency passive microwave radiometer called Special Sensor Microwave/Imager (SSM/I) have systematic and accurate precipitation measurements over oceans become available on a regular basis; see Smith et al. (1994, 1998). Recognizing that satellite-based data are a foremost tool for measuring precipitation, NASA initiated a new research program to measure precipitation from space under its Mission to Planet Earth program in the 1990s. As a result, the Tropical Rainfall Measuring Mission (TRMM), a collaborative mission between NASA and NASDA, was launched in 1997 to measure tropical and subtropical rain. See Simpson et al. (1996) and Kummerow et al. (2000). Motivated by the success of TRMM, and recognizing the need for more comprehensive global precipitation measurements, NASA and NASDA have now planned a new mission, i.e., the Global Precipitation Measurement (GPM) mission. The primary goal of GPM is to extend TRMM's rainfall time series while making substantial improvements in precipitation observations, specifically in terms of measurement accuracy, sampling frequency, Earth coverage, and spatial resolution. This report addresses four fundamental questions related to the transition from current to future global precipitation observations as denoted by the TRMM and GPM eras, respectively.

  7. The physical drivers of historical and 21st century global precipitation changes

    International Nuclear Information System (INIS)

    Thorpe, Livia; Andrews, Timothy

    2014-01-01

    Historical and 21st century global precipitation changes are investigated using data from the fifth Coupled Model Intercomparison Project (CMIP5) Atmosphere-Ocean-General-Circulation-Models (AOGCMs) and a simple energy-balance model. In the simple model, precipitation change in response to a given top-of-atmosphere radiative forcing is calculated as the sum of a response to the surface warming and a direct ‘adjustment’ response to the atmospheric radiative forcing. This simple model allows the adjustment in global mean precipitation to atmospheric radiative forcing from different forcing agents to be examined separately and emulates the AOGCMs well. During the historical period the AOGCMs simulate little global precipitation change despite an increase in global temperature—at the end of the historical period, global multi-model mean precipitation has increased by about 0.03 mm day −1 , while the global multi-model mean surface temperature has warmed by about 1 K, both relative to the pre-industrial control means. This is because there is a large direct effect from CO 2 and black carbon atmospheric forcing that opposes the increase in precipitation from surface warming. In the 21st century scenarios, the opposing effect from black carbon declines and the increase in global precipitation due to surface warming dominates. The cause of the spread between models in the global precipitation projections (which can be up to 0.25 mm day −1 ) is examined and found to come mainly from uncertainty in the climate sensitivity. The spatial distribution of precipitation change is found to be dominated by the response to surface warming. It is concluded that AOGCM global precipitation projections are in line with expectations based on our understanding of how the energy and water cycles are physically linked. (letters)

  8. High resolution reconstruction of monthly precipitation of Iberian Peninsula using circulation weather types

    Science.gov (United States)

    Cortesi, N.; Trigo, R.; Gonzalez-Hidalgo, J. C.; Ramos, A. M.

    2012-06-01

    Precipitation over the Iberian Peninsula (IP) is highly variable and shows large spatial contrasts between wet mountainous regions, to the north, and dry regions in the inland plains and southern areas. In this work, a high-density monthly precipitation dataset for the IP was coupled with a set of 26 atmospheric circulation weather types (Trigo and DaCamara, 2000) to reconstruct Iberian monthly precipitation from October to May with a very high resolution of 3030 precipitation series (overall mean density one station each 200 km2). A stepwise linear regression model with forward selection was used to develop monthly reconstructed precipitation series calibrated and validated over 1948-2003 period. Validation was conducted by means of a leave-one-out cross-validation over the calibration period. The results show a good model performance for selected months, with a mean coefficient of variation (CV) around 0.6 for validation period, being particularly robust over the western and central sectors of IP, while the predicted values in the Mediterranean and northern coastal areas are less acute. We show for three long stations (Lisbon, Madrid and Valencia) the comparison between model and original data as an example to how these models can be used in order to obtain monthly precipitation fields since the 1850s over most of IP for this very high density network.

  9. Incorporation of a Cuban radiological station to the global net of isotopes in precipitations

    International Nuclear Information System (INIS)

    Dominguez L, O.; Ramos V, E.O.; Prendes A, M.; Alonso A, D.; Caveda R, C.A.

    2006-01-01

    From March, 2002 the West station of the National Net of Environmental Radiological Surveillance located in the Center of Protection and Hygiene of the Radiations, belongs to the Global Net of Isotopes in Precipitations. The obtained isotopic information of the analysis of the samples of monthly monitored precipitations (oxygen-18, deuterium and tritium) its are stored in a database, which is available through Internet. For the acceptance in the Global Net, it was necessary the incorporation to the monitoring of the station the meteorological surface variables. Also it was developed a software for the calculation of the tension of the water steam starting from the values of humidity and temperature. The obtained results in 2002 and published recently, its are inside the range of values reported for these isotopes in the Caribbean area. (Author)

  10. The forcing of monthly precipitation variability over Southwest Asia during the Boreal cold season

    Science.gov (United States)

    Hoell, Andrew; Shukla, Shraddhanand; Barlow, Mathew; Cannon, Forest; Kelley, Colin; Funk, Christopher C.

    2015-01-01

    Southwest Asia, deemed as the region containing the countries of Afghanistan, Iran, Iraq and Pakistan, is water scarce and receives nearly 75% of its annual rainfall during8 the boreal cold season of November-April. The forcing of Southwest Asia precipitation has been previously examined for the entire boreal cold season from the perspective of climate variability originating over the Atlantic and tropical Indo-Pacific Oceans. Here, we examine the inter-monthly differences in precipitation variability over Southwest Asia and the atmospheric conditions directly responsible in forcing monthly November-April precipitation. Seasonally averaged November-April precipitation over Southwest Asia is significantly correlated with sea surface temperature (SST) patterns consistent with Pacific Decadal Variability (PDV), the El Nino-Southern Oscillation (ENSO) and the warming trend of SST (Trend). On the contrary, the precipitation variability during individual months of November-April are unrelated and are correlated with SST signatures that include PDV, ENSO and Trend in different combinations. Despite strong inter-monthly differences in precipitation variability during November- April over Southwest Asia, similar atmospheric circulations, highlighted by a stationary equivalent barotropic Rossby wave centered over Iraq, force the monthly spatial distributions of precipitation. Tropospheric waves on the eastern side of the equivalent barotropic Rossby wave modifies the flux of moisture and advects the mean temperature gradient, resulting in temperature advection that is balanced by vertical motions over Southwest Asia. The forcing of monthly Southwest Asia precipitation by equivalent barotropic Rossby waves is different than the forcing by baroclinic Rossby waves associated with tropically-forced-only modes of climate variability.

  11. Supporting Hydrometeorological Research and Applications with Global Precipitation Measurement (GPM) Products and Services

    Science.gov (United States)

    Liu, Zhong; Ostrenga, D.; Vollmer, B.; Deshong, B.; MacRitchie, K.; Greene, M.; Kempler, S.

    2016-01-01

    Precipitation is an important dataset in hydrometeorological research and applications such as flood modeling, drought monitoring, etc. On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data. The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). GPM products currently available include the following:1. Level-1 GPM Microwave Imager (GMI) and partner radiometer products2. Goddard Profiling Algorithm (GPROF) GMI and partner products (Level-2 and Level-3)3. GPM dual-frequency precipitation radar and their combined products (Level-2 and Level-3)4. Integrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final run)GPM data can be accessed through a number of data services (e.g., Simple Subset Wizard, OPeNDAP, WMS, WCS, ftp, etc.). A newly released Unified User Interface or UUI is a single interface to provide users seamless access to data, information and services. For example, a search for precipitation products will not only return TRMM and GPM products, but also other global precipitation products such as MERRA (Modern Era Retrospective-Analysis for Research and Applications), GLDAS (Global Land Data Assimilation Systems), etc.New features and capabilities have been recently added in GIOVANNI to allow exploring and inter-comparing GPM IMERG (Integrated Multi-satelliE Retrievals for GPM) half-hourly and monthly precipitation

  12. Increasing importance of precipitation variability on global livestock grazing lands

    Science.gov (United States)

    Sloat, Lindsey L.; Gerber, James S.; Samberg, Leah H.; Smith, William K.; Herrero, Mario; Ferreira, Laerte G.; Godde, Cécile M.; West, Paul C.

    2018-03-01

    Pastures and rangelands underpin global meat and milk production and are a critical resource for millions of people dependent on livestock for food security1,2. Forage growth, which is highly climate dependent3,4, is potentially vulnerable to climate change, although precisely where and to what extent remains relatively unexplored. In this study, we assess climate-based threats to global pastures, with a specific focus on changes in within- and between-year precipitation variability (precipitation concentration index (PCI) and coefficient of variation of precipitation (CVP), respectively). Relating global satellite measures of vegetation greenness (such as the Normalized Difference Vegetation Index; NDVI) to key climatic factors reveals that CVP is a significant, yet often overlooked, constraint on vegetation productivity across global pastures. Using independent stocking data, we found that areas with high CVP support lower livestock densities than less-variable regions. Globally, pastures experience about a 25% greater year-to-year precipitation variation (CVP = 0.27) than the average global land surface area (0.21). Over the past century, CVP has generally increased across pasture areas, although both positive (49% of pasture area) and negative (31% of pasture area) trends exist. We identify regions in which livestock grazing is important for local food access and economies, and discuss the potential for pasture intensification in the context of long-term regional trends in precipitation variability.

  13. Application of Observed Precipitation in NCEP Global and Regional Data Assimilation Systems, Including Reanalysis and Land Data Assimilation

    Science.gov (United States)

    Mitchell, K. E.

    2006-12-01

    The Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) applies several different analyses of observed precipitation in both the data assimilation and validation components of NCEP's global and regional numerical weather and climate prediction/analysis systems (including in NCEP global and regional reanalysis). This invited talk will survey these data assimilation and validation applications and methodologies, as well as the temporal frequency, spatial domains, spatial resolution, data sources, data density and data quality control in the precipitation analyses that are applied. Some of the precipitation analyses applied by EMC are produced by NCEP's Climate Prediction Center (CPC), while others are produced by the River Forecast Centers (RFCs) of the National Weather Service (NWS), or by automated algorithms of the NWS WSR-88D Radar Product Generator (RPG). Depending on the specific type of application in data assimilation or model forecast validation, the temporal resolution of the precipitation analyses may be hourly, daily, or pentad (5-day) and the domain may be global, continental U.S. (CONUS), or Mexico. The data sources for precipitation include ground-based gauge observations, radar-based estimates, and satellite-based estimates. The precipitation analyses over the CONUS are analyses of either hourly, daily or monthly totals of precipitation, and they are of two distinct types: gauge-only or primarily radar-estimated. The gauge-only CONUS analysis of daily precipitation utilizes an orographic-adjustment technique (based on the well-known PRISM precipitation climatology of Oregon State University) developed by the NWS Office of Hydrologic Development (OHD). The primary NCEP global precipitation analysis is the pentad CPC Merged Analysis of Precipitation (CMAP), which blends both gauge observations and satellite estimates. The presentation will include a brief comparison between the CMAP analysis and other global

  14. Using Multiple Monthly Water Balance Models to Evaluate Gridded Precipitation Products over Peninsular Spain

    Directory of Open Access Journals (Sweden)

    Javier Senent-Aparicio

    2018-06-01

    Full Text Available The availability of precipitation data is the key driver in the application of hydrological models when simulating streamflow. Ground weather stations are regularly used to measure precipitation. However, spatial coverage is often limited in low-population areas and mountain areas. To overcome this limitation, gridded datasets from remote sensing have been widely used. This study evaluates four widely used global precipitation datasets (GPDs: The Tropical Rainfall Measuring Mission (TRMM 3B43, the Climate Forecast System Reanalysis (CFSR, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, and the Multi-Source Weighted-Ensemble Precipitation (MSWEP, against point gauge and gridded dataset observations using multiple monthly water balance models (MWBMs in four different meso-scale basins that cover the main climatic zones of Peninsular Spain. The volumes of precipitation obtained from the GPDs tend to be smaller than those from the gauged data. Results underscore the superiority of the national gridded dataset, although the TRMM provides satisfactory results in simulating streamflow, reaching similar Nash-Sutcliffe values, between 0.70 and 0.95, and an average total volume error of 12% when using the GR2M model. The performance of GPDs highly depends on the climate, so that the more humid the watershed is, the better results can be achieved. The procedures used can be applied in regions with similar case studies to more accurately assess the resources within a system in which there is scarcity of recorded data available.

  15. Advances in Global Water Cycle Science Made Possible by Global Precipitation Mission (GPM)

    Science.gov (United States)

    Smith, Eric A.; Starr, David OC. (Technical Monitor)

    2001-01-01

    Within this decade the internationally sponsored Global Precipitation Mission (GPM) will take an important step in creating a global precipitation observing system from space. One perspective for understanding the nature of GPM is that it will be a hierarchical system of datastreams from very high caliber combined dual frequency radar/passive microwave (PMW) rain-radiometer retrievals, to high caliber PMW rain-radiometer only retrievals, and on to blends of the former datastreams with other less-high caliber PMW-based and IR-based rain retrievals. Within the context of NASA's role in global water cycle science and its own Global Water & Energy Cycle (GWEC) program, GPM is the centerpiece mission for improving our understanding of the global water cycle from a space-based measurement perspective. One of the salient problems within our current understanding of the global water and energy cycle is determining whether a change in the rate of the water cycle is accompanying changes in global temperature. As there are a number of ways in which to define a rate-change of the global water cycle, it is not entirely clear as to what constitutes such a determination, This paper presents an overview of the Global Precipitation Mission and how its datasets can be used in a set of quantitative tests within the framework of the oceanic and continental water budget equations to determine comprehensively whether substantive rate changes do accompany perturbations in global temperatures and how such rate changes manifest themselves in both water storage and water flux transport processes.

  16. Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

    Science.gov (United States)

    Qi, W.; Zhang, C.; Fu, G.; Sweetapple, C.; Zhou, H.

    2016-02-01

    The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash-Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A

  17. Monthly Total Precipitation Observation for Climate Prediction Center (CPC)Forecast Divisions

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This ASCII dataset contains monthly total precipitation for 102 Forecast Divisions within the conterminous U.S. It is derived from the monthly NCDC climate division...

  18. Improving Global Precipitation Product Access at the GES DISC

    Science.gov (United States)

    Liu, Z.; Vollmer, B.; Savtchenko, A.; Ostrenga, D.; DeShong, B.; Fang, F.; Albayrak, R,; Sherman, E.; Greene, M.; Li, A.; hide

    2018-01-01

    The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been actively and continually engaged in improving the access to and use of Global Precipitation Measurement (GPM), Tropical Precipitation Measuring Mission (TRMM), and other precipitation data, including the following new services and Ongoing development activities: Updates on GPM products and data services, New features in Giovanni, Ongoing development activities; and Precipitation product and service outreach activities.

  19. Global Precipitation Measurement (GPM) Mission: Overview and Status

    Science.gov (United States)

    Hou, Arthur Y.

    2012-01-01

    The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. NASA and JAXA will deploy a Core Observatory in 2014 to serve as a reference satellite to unify precipitation measurements from the constellation of sensors. The GPM Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Radiometer (GMI). The DPR will be the first dual-frequency radar in space to provide not only measurements of 3-D precipitation structures but also quantitative information on microphysical properties of precipitating particles. The DPR and GMI measurements will together provide a database that relates vertical hydrometeor profiles to multi-frequency microwave radiances over a variety of environmental conditions across the globe. This combined database will be used as a common transfer standard for improving the accuracy and consistency of precipitation retrievals from all constellation radiometers. For global coverage, GPM relies on existing satellite programs and new mission opportunities from a consortium of partners through bilateral agreements with either NASA or JAXA. Each constellation member may have its unique scientific or operational objectives but contributes microwave observations to GPM for the generation and dissemination of unified global precipitation data products. In addition to the DPR and GMI on the Core Observatory, the baseline GPM constellation consists of the following sensors: (1) Special Sensor Microwave Imager/Sounder (SSMIS) instruments on the U.S. Defense Meteorological Satellite Program (DMSP) satellites, (2) the Advanced Microwave Scanning Radiometer-2 (AMSR-2) on the GCOM-W1 satellite of JAXA, (3) the Multi-Frequency Microwave Scanning Radiometer (MADRAS) and the multi-channel microwave humidity sounder

  20. Successes with the Global Precipitation Measurement (GPM) Mission

    Science.gov (United States)

    Skofronick-Jackson, Gail; Huffman, George; Stocker, Erich; Petersen, Walter

    2016-01-01

    Water is essential to our planet Earth. Knowing when, where and how precipitation falls is crucial for understanding the linkages between the Earth's water and energy cycles and is extraordinarily important for sustaining life on our planet during climate change. The Global Precipitation Measurement (GPM) Core Observatory spacecraft launched February 27, 2014, is the anchor to the GPM international satellite mission to unify and advance precipitation measurements from a constellation of research and operational sensors to provide "next-generation" precipitation products. GPM is currently a partnership between NASA and the Japan Aerospace Exploration Agency (JAXA). Status and successes in terms of spacecraft, instruments, retrieval products, validation, and impacts for science and society will be presented. Precipitation, microwave, satellite

  1. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015

    OpenAIRE

    Abatzoglou, John T.; Dobrowski, Solomon Z.; Parks, Sean A.; Hegewisch, Katherine C.

    2018-01-01

    We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and sol...

  2. High resolution reconstruction of monthly autumn and winter precipitation of Iberian Peninsula for last 150 years.

    Science.gov (United States)

    Cortesi, N.; Trigo, R.; González-Hidalgo, J. C.; Ramos, A.

    2012-04-01

    Precipitation over Iberian Peninsula (IP) presents large values of interannual variability and large spatial contrasts between wet mountainous regions in the north and dry regions in the southern plains. Unlike other European regions, IP was poorly monitored for precipitation during 19th century. Here we present a new approach to fill this gap. A set of 26 atmospheric circulation weather types (Trigo R.M. and DaCamara C.C., 2000) derived from a recent SLP dataset, the EMULATE (European and North Atlantic daily to multidecadal climate variability) Project, was used to reconstruct Iberian monthly precipitation from October to March during 1851-1947. Principal Component Regression Analysis was chosen to develop monthly precipitation reconstruction back to 1851 and calibrated over 1948-2003 period for 3030 monthly precipitation series of high-density homogenized MOPREDAS (Monthly Precipitation Database for Spain and Portugal) database. Validation was conducted over 1920-1947 at 15 key site locations. Results show high model performance for selected months, with a mean coefficient of variation (CV) around 0.6 during validation period. Lower CV values were achieved in western area of IP. Trigo, R. M., and DaCamara, C.C., 2000: "Circulation weather types and their impact on the precipitation regime in Portugal". Int. J. Climatol., 20, 1559-1581.

  3. Comparison of TRMM and Global Precipitation Climatology Project (GPCP) Precipitation Analyses

    Science.gov (United States)

    Adler, Robert F.; Huffman, George J.; Bolvin, David; Nelkin, Eric; Curtis, Scott

    1999-01-01

    This paper describes recent results of using Tropical Rainfall Measuring Mission (TRMM) (launched in November 1997) information as the key calibration tool in a merged analysis on a 1 x 1' latitude/longitude monthly scale based on multiple satellite sources and raingauge analyses. The TRMM-based product is compared with the community-based Global Precipitation Climatology Project (GPCP) results. The long-term GPCP analysis is compared to the new TRMM-based analysis which uses the most accurate TRMM information to calibrate the estimates from the Special Sensor Microwave/Imager (SSM/I) and geosynchronous IR observations and merges those estimates together with the TRMM and gauge information to produce accurate rainfall estimates with the increased sampling provided by the combined satellite information. The comparison with TRMM results on a month-to-month basis should clarify the strengths and weaknesses of the long-term GPCP product in the tropics and point to how to improve the monitoring analysis. Preliminary results from the TRMM merged satellite analysis indicates fairly close agreement with the GPCP estimates. The GPCP analysis is done at 2.5 degree latitude/longitude resolution and interpolated to a 1 degree grid for comparison with the TRMM analysis. As expected the same features are evident in both panels, but there are subtle differences in the magnitudes. Focusing on the Pacific Ocean Inter-Tropical Convergence Zone (ITCZ) one can see the TRMM-based estimates having higher peak values and lower values in the ITCZ periphery. These attributes also show up in the statistics, where GPCP>TRMM at low values (below 10 mm/d) and TRMM>GPCP at high values (greater than 15 mm/d). The area in the Indian Ocean which shows consistently higher values of TRMM over GPCP needs to be examined carefully to determine if the lack of geosynchronous data has led to a difference in the two analyses. By the time of the meeting over a year of TRMM products will be available for

  4. A possible constraint on regional precipitation intensity changes under global warming

    DEFF Research Database (Denmark)

    Gutowski, William J.; Kozak, K. A.; Arritt, R. W.

    2007-01-01

    Changes in daily precipitation versus intensity under a global warming scenario in two regional climate simulations of the United States show a well-recognized feature of more intense precipitation. More important, by resolving the precipitation intensity spectrum, the changes show a relatively...

  5. Global estimate of lichen and bryophyte contributions to forest precipitation interception

    Science.gov (United States)

    Van Stan, John; Porada, Philipp; Kleidon, Axel

    2017-04-01

    Interception of precipitation by forest canopies plays an important role in its partitioning to evaporation, transpiration and runoff. Field observations show arboreal lichens and bryophytes can substantially enhance forests' precipitation storage and evaporation. However, representations of canopy interception in global land surface models currently ignore arboreal lichen and bryophyte contributions. This study uses the lichen and bryophyte model (LiBry) to provide the first process-based modelling approach estimating these organisms' contributions to canopy water storage and evaporation. The global mean value of forest water storage capacity increased significantly from 0.87 mm to 1.33 mm by the inclusion of arboreal poikilohydric organisms. Global forest canopy evaporation of intercepted precipitation was also greatly enhanced by 44%. Ratio of total versus bare canopy global evaporation exceeded 2 in many forested regions. This altered global patterns in canopy water storage, evaporation, and ultimately the proportion of rainfall evaporated. A sensitivity analysis was also performed. Results indicate rainfall interception is of larger magnitude than previously reported by global land surface modelling work because of the important role of lichen and bryophytes in rainfall interception.

  6. Orographic precipitation at global and regional scales: Observational uncertainty and evaluation of 25-km global model simulations

    Science.gov (United States)

    Schiemann, Reinhard; Roberts, Charles J.; Bush, Stephanie; Demory, Marie-Estelle; Strachan, Jane; Vidale, Pier Luigi; Mizielinski, Matthew S.; Roberts, Malcolm J.

    2015-04-01

    Precipitation over land exhibits a high degree of variability due to the complex interaction of the precipitation generating atmospheric processes with coastlines, the heterogeneous land surface, and orography. Global general circulation models (GCMs) have traditionally had very limited ability to capture this variability on the mesoscale (here ~50-500 km) due to their low resolution. This has changed with recent investments in resolution and ensembles of multidecadal climate simulations of atmospheric GCMs (AGCMs) with ~25 km grid spacing are becoming increasingly available. Here, we evaluate the mesoscale precipitation distribution in one such set of simulations obtained in the UPSCALE (UK on PrACE - weather-resolving Simulations of Climate for globAL Environmental risk) modelling campaign with the HadGEM-GA3 AGCM. Increased model resolution also poses new challenges to the observational datasets used to evaluate models. Global gridded data products such as those provided by the Global Precipitation Climatology Project (GPCP) are invaluable for assessing large-scale features of the precipitation distribution but may not sufficiently resolve mesoscale structures. In the absence of independent estimates, the intercomparison of different observational datasets may be the only way to get some insight into the uncertainties associated with these observations. Here, we focus on mid-latitude continental regions where observations based on higher-density gauge networks are available in addition to the global data sets: Europe/the Alps, South and East Asia, and the continental US. The ability of GCMs to represent mesoscale variability is of interest in its own right, as climate information on this scale is required by impact studies. An additional motivation for the research proposed here arises from continuing efforts to quantify the components of the global radiation budget and water cycle. Recent estimates based on radiation measurements suggest that the global mean

  7. Advances in Understanding Global Water Cycle with Advent of Global Precipitation Measurement (GPM) Mission

    Science.gov (United States)

    Smith, Eric A.; Starr, David (Technical Monitor)

    2002-01-01

    Within this decade the internationally organized Global Precipitation Measurement (GPM) Mission will take an important step in creating a global precipitation observing system from space. One perspective for understanding the nature of GPM is that it will be a hierarchical system of datastreams beginning with very high caliber combined dual frequency radar/passive microwave (PMW) rain-radiometer retrievals, to high caliber PMW rain-radiometer only retrievals, and then on to blends of the former datastreams with additional lower-caliber PMW-based and IR-based rain retrievals. Within the context of the now emerging global water & energy cycle (GWEC) programs of a number of research agencies throughout the world, GPM serves as a centerpiece space mission for improving our understanding of the global water cycle from a global measurement perspective. One of the salient problems within our current understanding of the global water and energy cycle is determining whether a change in the rate of the water cycle is accompanying changes in climate, e.g., climate warming. As there are a number of ways in which to define a rate-change of the global water cycle, it is not entirely clear as to what constitutes such a determination. This paper presents an overview of the GPM Mission and how its observations can be used within the framework of the oceanic and continental water budget equations to determine whether a given perturbation in precipitation is indicative of an actual rate change in the global water cycle, consistent with required responses in water storage and/or water flux transport processes, or whether it is the natural variability of a fixed rate cycle.

  8. Precipitation Reconstruction over Land (PREC/L)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The monthly data set consists files of 3 resolutions of monthly averaged precipitation totals. The global analyses are defined by interpolation of gauge observations...

  9. Monitoring Global Precipitation through UCI CHRS's RainMapper App on Mobile Devices

    Science.gov (United States)

    Nguyen, P.; Huynh, P.; Braithwaite, D.; Hsu, K. L.; Sorooshian, S.

    2014-12-01

    The Water and Development Information for Arid Lands-a Global Network (G-WADI) Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks—Cloud Classification System (PERSIANN-CCS) GeoServer has been developed through a collaboration between the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California, Irvine (UCI) and the UNESCO's International Hydrological Program (IHP). G-WADI PERSIANN-CCS GeoServer provides near real-time high resolution (0.04o, approx 4km) global (60oN - 60oS) satellite precipitation estimated by the PERSIANN-CCS algorithm developed by the scientists at CHRS. The G-WADI PERSIANN-CCS GeoServer utilizes the open-source MapServer software from the University of Minnesota to provide a user-friendly web-based mapping and visualization of satellite precipitation data. Recent efforts have been made by the scientists at CHRS to provide free on-the-go access to the PERSIANN-CCS precipitation data through an application named RainMapper for mobile devices. RainMapper provides visualization of global satellite precipitation of the most recent 3, 6, 12, 24, 48 and 72-hour periods overlaid with various basemaps. RainMapper uses the Google maps application programing interface (API) and embedded global positioning system (GPS) access to better monitor the global precipitation data on mobile devices. Functionalities include using geographical searching with voice recognition technologies make it easy for the user to explore near real-time precipitation in a certain location. RainMapper also allows for conveniently sharing the precipitation information and visualizations with the public through social networks such as Facebook and Twitter. RainMapper is available for iOS and Android devices and can be downloaded (free) from the App Store and Google Play. The usefulness of RainMapper was demonstrated through an application in tracking the evolution of the recent Rammasun Typhoon over the

  10. Effective assimilation of global precipitation: simulation experiments

    Directory of Open Access Journals (Sweden)

    Guo-Yuan Lien

    2013-07-01

    Full Text Available Past attempts to assimilate precipitation by nudging or variational methods have succeeded in forcing the model precipitation to be close to the observed values. However, the model forecasts tend to lose their additional skill after a few forecast hours. In this study, a local ensemble transform Kalman filter (LETKF is used to effectively assimilate precipitation by allowing ensemble members with better precipitation to receive higher weights in the analysis. In addition, two other changes in the precipitation assimilation process are found to alleviate the problems related to the non-Gaussianity of the precipitation variable: (a transform the precipitation variable into a Gaussian distribution based on its climatological distribution (an approach that could also be used in the assimilation of other non-Gaussian observations and (b only assimilate precipitation at the location where at least some ensemble members have precipitation. Unlike many current approaches, both positive and zero rain observations are assimilated effectively. Observing system simulation experiments (OSSEs are conducted using the Simplified Parametrisations, primitivE-Equation DYnamics (SPEEDY model, a simplified but realistic general circulation model. When uniformly and globally distributed observations of precipitation are assimilated in addition to rawinsonde observations, both the analyses and the medium-range forecasts of all model variables, including precipitation, are significantly improved as compared to only assimilating rawinsonde observations. The effect of precipitation assimilation on the analyses is retained on the medium-range forecasts and is larger in the Southern Hemisphere (SH than that in the Northern Hemisphere (NH because the NH analyses are already made more accurate by the denser rawinsonde stations. These improvements are much reduced when only the moisture field is modified by the precipitation observations. Both the Gaussian transformation and

  11. Japanese Global Precipitation Measurement (GPM) mission status and application of satellite-based global rainfall map

    Science.gov (United States)

    Kachi, Misako; Shimizu, Shuji; Kubota, Takuji; Yoshida, Naofumi; Oki, Riko; Kojima, Masahiro; Iguchi, Toshio; Nakamura, Kenji

    2010-05-01

    As accuracy of satellite precipitation estimates improves and observation frequency increases, application of those data to societal benefit areas, such as weather forecasts and flood predictions, is expected, in addition to research of precipitation climatology to analyze precipitation systems. There is, however, limitation on single satellite observation in coverage and frequency. Currently, the Global Precipitation Measurement (GPM) mission is scheduled under international collaboration to fulfill various user requirements that cannot be achieved by the single satellite, like the Tropical Rainfall Measurement Mission (TRMM). The GPM mission is an international mission to achieve high-accurate and high-frequent rainfall observation over a global area. GPM is composed of a TRMM-like non-sun-synchronous orbit satellite (GPM core satellite) and constellation of satellites carrying microwave radiometer instruments. The GPM core satellite carries the Dual-frequency Precipitation Radar (DPR), which is being developed by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT), and microwave radiometer provided by the National Aeronautics and Space Administration (NASA). Development of DPR instrument is in good progress for scheduled launch in 2013, and DPR Critical Design Review has completed in July - September 2009. Constellation satellites, which carry a microwave imager and/or sounder, are planned to be launched around 2013 by each partner agency for its own purpose, and will contribute to extending coverage and increasing frequency. JAXA's future mission, the Global Change Observation Mission (GCOM) - Water (GCOM-W) satellite will be one of constellation satellites. The first generation of GCOM-W satellite is scheduled to be launched in 2011, and it carries the Advanced Microwave Scanning Radiometer 2 (AMSR2), which is being developed based on the experience of the AMSR-E on EOS Aqua satellite

  12. Predictability of monthly temperature and precipitation using automatic time series forecasting methods

    Science.gov (United States)

    Papacharalampous, Georgia; Tyralis, Hristos; Koutsoyiannis, Demetris

    2018-02-01

    We investigate the predictability of monthly temperature and precipitation by applying automatic univariate time series forecasting methods to a sample of 985 40-year-long monthly temperature and 1552 40-year-long monthly precipitation time series. The methods include a naïve one based on the monthly values of the last year, as well as the random walk (with drift), AutoRegressive Fractionally Integrated Moving Average (ARFIMA), exponential smoothing state-space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components (BATS), simple exponential smoothing, Theta and Prophet methods. Prophet is a recently introduced model inspired by the nature of time series forecasted at Facebook and has not been applied to hydrometeorological time series before, while the use of random walk, BATS, simple exponential smoothing and Theta is rare in hydrology. The methods are tested in performing multi-step ahead forecasts for the last 48 months of the data. We further investigate how different choices of handling the seasonality and non-normality affect the performance of the models. The results indicate that: (a) all the examined methods apart from the naïve and random walk ones are accurate enough to be used in long-term applications; (b) monthly temperature and precipitation can be forecasted to a level of accuracy which can barely be improved using other methods; (c) the externally applied classical seasonal decomposition results mostly in better forecasts compared to the automatic seasonal decomposition used by the BATS and Prophet methods; and (d) Prophet is competitive, especially when it is combined with externally applied classical seasonal decomposition.

  13. Evaluation of globally available precipitation data products as input for water balance models

    Science.gov (United States)

    Lebrenz, H.; Bárdossy, A.

    2009-04-01

    Subject of this study is the evaluation of globally available precipitation data products, which are intended to be used as input variables for water balance models in ungauged basins. The selected data sources are a) the Global Precipitation Climatology Centre (GPCC), b) the Global Precipitation Climatology Project (GPCP) and c) the Climate Research Unit (CRU), resulting into twelve globally available data products. The data products imply different data bases, different derivation routines and varying resolutions in time and space. For validation purposes, the ground data from South Africa were screened on homogeneity and consistency by various tests and an outlier detection using multi-linear regression was performed. External Drift Kriging was subsequently applied on the ground data and the resulting precipitation arrays were compared to the different products with respect to quantity and variance.

  14. Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR upon TRMM Precipitation Radar (PR in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

    Directory of Open Access Journals (Sweden)

    Jinyu Gao

    2017-11-01

    Full Text Available Spaceborne precipitation radars are powerful tools used to acquire adequate and high-quality precipitation estimates with high spatial resolution for a variety of applications in hydrological research. The Global Precipitation Measurement (GPM mission, which deployed the first spaceborne Ka- and Ku-dual frequency radar (DPR, was launched in February 2014 as the upgraded successor of the Tropical Rainfall Measuring Mission (TRMM. This study matches the swath data of TRMM PR and GPM DPR Level 2 products during their overlapping periods at the global scale to investigate their similarities and DPR’s improvements concerning precipitation amount estimation and type classification of GPM DPR over TRMM PR. Results show that PR and DPR agree very well with each other in the global distribution of precipitation, while DPR improves the detectability of precipitation events significantly, particularly for light precipitation. The occurrences of total precipitation and the light precipitation (rain rates < 1 mm/h detected by GPM DPR are ~1.7 and ~2.53 times more than that of PR. With regard to type classification, the dual-frequency (Ka/Ku and single frequency (Ku methods performed similarly. In both inner (the central 25 beams and outer swaths (1–12 beams and 38–49 beams of DPR, the results are consistent. GPM DPR improves precipitation type classification remarkably, reducing the misclassification of clouds and noise signals as precipitation type “other” from 10.14% of TRMM PR to 0.5%. Generally, GPM DPR exhibits the same type division for around 82.89% (71.02% of stratiform (convective precipitation events recognized by TRMM PR. With regard to the freezing level height and bright band (BB height, both radars correspond with each other very well, contributing to the consistency in stratiform precipitation classification. Both heights show clear latitudinal dependence. Results in this study shall contribute to future development of spaceborne

  15. Atmospheric Simulations Using OGCM-Assimilation SST: Influence of the Wintertime Japan Sea on Monthly Precipitation

    Directory of Open Access Journals (Sweden)

    Masaru Yamamoto Naoki Hirose

    2010-01-01

    Full Text Available Temperature data for the Japan Sea obtained from ocean data assimilation modeling is applied to atmospheric simulations of monthly precipitation for January 2005. Because the volume of flow of the Tsushima Warm Current was large during the winter season, the sea surface temperature (SST and coastal precipitation were higher in comparison with those in 2003. In order to evaluate influence of SST on monthly precipitation, we use surface temperatures of the Japan Sea in 2003 and 2005 for comparative simulations of precipitation for January 2005. The precipitation in experiment C (using cool SST data in 2003 is smaller than that in experiment W (using warm SST data in 2005 in a large part of the sea area, since the small evaporation results from the low SST over the upstream area of northwesterly winter monsoon. In the domain of 33.67 - 45.82°N and 125.89 - 142.9°E, the averaged evaporation and precipitation in experiment C are 10% and 13% smaller than those in experiment W, respectively. About half of the difference between the precipitations observed for January 2003 and 2005 in a heavy snow area is equal to the difference between the two simulations. Our results show that the mesoscale SST difference between 2003 and 2005 is related to the local difference of monthly precipitation.

  16. Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

    Science.gov (United States)

    Sommer, Philipp; Kaplan, Jed

    2016-04-01

    Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.

  17. Occurrence Probabilities of Wet and Dry Periods in Southern Italy through the SPI Evaluated on Synthetic Monthly Precipitation Series

    Directory of Open Access Journals (Sweden)

    Tommaso Caloiero

    2018-03-01

    Full Text Available The present article investigates dry and wet periods in a large area of the Mediterranean basin. First, a stochastic model was applied to a homogeneous database of monthly precipitation values of 46 rain gauges in five regions of southern Italy. In particular, after estimating the model parameters, a set of 104 years of monthly precipitation for each rain gauge was generated by means of a Monte Carlo technique. Then, dry and wet periods were analyzed through the application of the standardized precipitation index (SPI over 3-month and 6-month timespan (short-term and 12-month and 24-month period (long-term. As a result of the SPI application on the generated monthly precipitation series, higher occurrence probabilities of dry conditions than wet conditions have been detected, especially when long-term precipitation scales are considered.

  18. Precipitation Reconstruction (PREC)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The PREC data set is an analysis of monthly precipitation constructed on a 2.5(o)lat/lon grid over the global for the period from 1948 to the present. The land...

  19. First evaluation of the utility of GPM precipitation in global flood monitoring

    Science.gov (United States)

    Wu, H.; Yan, Y.; Gao, Z.

    2017-12-01

    The Global Flood Monitoring System (GFMS) has been developed and used to provide real-time flood detection and streamflow estimates over the last few years with significant success shown by validation against global flood event data sets and observed streamflow variations (Wu et al., 2014). It has become a tool for various national and international organizations to appraise flood conditions in various areas, including where rainfall and hydrology information is limited. The GFMS has been using the TRMM Multi-satellite Precipitation Analysis (TMPA) as its main rainfall input. Now, with the advent of the Global Precipitation Measurement (GPM) mission there is an opportunity to significantly improve global flood monitoring and forecasting. GPM's Integrated Multi-satellitE Retrievals for GPM (IMERG) multi-satellite product is designed to take advantage of various technical advances in the field and combine that with an efficient processing system producing "early" (4 hrs) and "late" (12 hrs) products for operational use. Specifically, this study is focused on (1) understanding the difference between the new IMERG products and other existing satellite precipitation products, e.g., TMPA, CMORPH, and ground observations; (2) addressing the challenge in the usage of the IMERG for flood monitoring through hydrologic models, given that only a short period of precipitation data record has been accumulated since the lunch of GPM in 2014; and (3) comparing the statistics of flood simulation based on the DRIVE model with IMERG, TMPA, CMORPH etc. as precipitation inputs respectively. Derivation of a global threshold map is a necessary step to define flood events out of modelling results, which requires a relatively longer historic information. A set of sensitivity tests are conducted by adjusting IMERG's light, moderate, heavy rain to existing precipitation products with long-term records separately, to optimize the strategy of PDF matching. Other aspects are also examined

  20. Climate Prediction Center(CPC) Monthly U.S. Precipitation and Temperature Summary

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly U.S. minimum and maximum temperatures in whole degrees Fahrenheit and reported and estimated precipitation amounts in hundredths of inches(ex 100 is 1.00...

  1. Access NASA Satellite Global Precipitation Data Visualization on YouTube

    Science.gov (United States)

    Liu, Z.; Su, J.; Acker, J. G.; Huffman, G. J.; Vollmer, B.; Wei, J.; Meyer, D. J.

    2017-12-01

    Since the satellite era began, NASA has collected a large volume of Earth science observations for research and applications around the world. Satellite data at 12 NASA data centers can also be used for STEM activities such as disaster events, climate change, etc. However, accessing satellite data can be a daunting task for non-professional users such as teachers and students because of unfamiliarity of terminology, disciplines, data formats, data structures, computing resources, processing software, programing languages, etc. Over the years, many efforts have been developed to improve satellite data access, but barriers still exist for non-professionals. In this presentation, we will present our latest activity that uses the popular online video sharing web site, YouTube, to access visualization of global precipitation datasets at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC). With YouTube, users can access and visualize a large volume of satellite data without necessity to learn new software or download data. The dataset in this activity is the 3-hourly TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Analysis (TMPA). The video consists of over 50,000 data files collected since 1998 onwards, covering a zone between 50°N-S. The YouTube video will last 36 minutes for the entire dataset record (over 19 years). Since the time stamp is on each frame of the video, users can begin at any time by dragging the time progress bar. This precipitation animation will allow viewing precipitation events and processes (e.g., hurricanes, fronts, atmospheric rivers, etc.) on a global scale. The next plan is to develop a similar animation for the GPM (Global Precipitation Measurement) Integrated Multi-satellitE Retrievals for GPM (IMERG). The IMERG provides precipitation on a near-global (60°N-S) coverage at half-hourly time interval, showing more details on precipitation processes and development, compared to the 3

  2. Climate Prediction Center (CPC) Monthly U.S. Selected Cities Precipitation Summary

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly U.S. reported precipitation amounts in hundredths of inches (ex 100 is 1.00 inches) generated from the GTS metar(hourly) and synoptic(6-hourly)observations...

  3. Downscaling global precipitation for local applications - a case for the Rhine basin

    Science.gov (United States)

    Sperna Weiland, Frederiek; van Verseveld, Willem; Schellekens, Jaap

    2017-04-01

    Within the EU FP7 project eartH2Observe a global Water Resources Re-analysis (WRR) is being developed. This re-analysis consists of meteorological and hydrological water balance variables with global coverage, spanning the period 1979-2014 at 0.25 degrees resolution (Schellekens et al., 2016). The dataset can be of special interest in regions with limited in-situ data availability, yet for local scale analysis particularly in mountainous regions, a resolution of 0.25 degrees may be too coarse and downscaling the data to a higher resolution may be required. A downscaling toolbox has been made that includes spatial downscaling of precipitation based on the global WorldClim dataset that is available at 1 km resolution as a monthly climatology (Hijmans et al., 2005). The input of the down-scaling tool are either the global eartH2Observe WRR1 and WRR2 datasets based on the WFDEI correction methodology (Weedon et al., 2014) or the global Multi-Source Weighted-Ensemble Precipitation (MSWEP) dataset (Beck et al., 2016). Here we present a validation of the datasets over the Rhine catchment by means of a distributed hydrological model (wflow, Schellekens et al., 2014) using a number of precipitation scenarios. (1) We start by running the model using the local reference dataset derived by spatial interpolation of gauge observations. Furthermore we use (2) the MSWEP dataset at the native 0.25-degree resolution followed by (3) MSWEP downscaled with the WorldClim dataset and final (4) MSWEP downscaled with the local reference dataset. The validation will be based on comparison of the modeled river discharges as well as rainfall statistics. We expect that down-scaling the MSWEP dataset with the WorldClim data to higher resolution will increase its performance. To test the performance of the down-scaling routine we have added a run with MSWEP data down-scaled with the local dataset and compare this with the run based on the local dataset itself. - Beck, H. E. et al., 2016. MSWEP

  4. The Global Climatology Network Precipitation data

    International Nuclear Information System (INIS)

    Peterson, T.C.; Easterling, D.R.; Eischeid, J.K.

    1993-01-01

    Several years ago, in response to growing concern about global climate change, the US National Climatic Data Center and the Carbon Dioxide Information Analysis Center undertook an effort to create a baseline global land surface climate data set called the Global Historical Climatology Network (GHCN, Vose et al., 1992). GHCN was created by merging several large existing climate data sets into one data base. Fifteen separate data sets went into the creation of the GHCN version 1.0. GHCN version 1.0 was released in 1992. It has 7,533 precipitation stations, but the number of stations varies with time. A slight majority (55%) have records in excess of 50 years, and a significant proportion (13%) have records in excess of 100 years. The longest period of record for any given station is 291 years (1697--1987 for Kew, United Kingdom)

  5. Prime mission results of the dual-frequency precipitation radar on the global precipitation measurement core spacecraft and the version 5 GPM standard products

    Science.gov (United States)

    Furukawa, K.; Nio, T.; Oki, R.; Kubota, T.; Iguchi, T.

    2017-09-01

    The Dual-frequency Precipitation Radar (DPR) on the Global Precipitation Measurement (GPM) core satellite was developed by Japan Aerospace Exploration Agency (JAXA) and National Institute of Information and Communications Technology (NICT). The objective of the GPM mission is to observe global precipitation more frequently and accurately. The GPM core satellite is a joint product of National Aeronautics and Space Administration (NASA), JAXA and NICT. NASA developed the satellite bus and the GPM Microwave Imager (GMI), and JAXA and NICT developed the DPR. The inclination of the GPM core satellite is 65 degrees, and the nominal flight altitude is 407 km. The non-sunsynchronous circular orbit is necessary for measuring the diurnal change of rainfall. The DPR consists of two radars, which are Ku-band precipitation radar (KuPR) and Ka-band precipitation radar (KaPR). GPM core observatory was successfully launched by H2A launch vehicle on Feb. 28, 2014. DPR orbital check out was completed in May 2014. DPR products were released to the public on Sep. 2, 2014 and Normal Observation Operation period was started. JAXA is continuing DPR trend monitoring, calibration and validation operations to confirm that DPR keeps its function and performance on orbit. The results of DPR trend monitoring, calibration and validation show that DPR kept its function and performance on orbit during the 3 years and 2 months prime mission period. The DPR Prime mission period was completed in May 2017. The version 5 GPM products were released to the public in 2017. JAXA confirmed that GPM/DPR total system performance and the GPM version 5 products achieved the success criteria and the performance indicators that were defined for the JAXA GPM/DPR mission.

  6. California Wintertime Precipitation in Regional and Global Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Caldwell, P M

    2009-04-27

    In this paper, wintertime precipitation from a variety of observational datasets, regional climate models (RCMs), and general circulation models (GCMs) is averaged over the state of California (CA) and compared. Several averaging methodologies are considered and all are found to give similar values when model grid spacing is less than 3{sup o}. This suggests that CA is a reasonable size for regional intercomparisons using modern GCMs. Results show that reanalysis-forced RCMs tend to significantly overpredict CA precipitation. This appears to be due mainly to overprediction of extreme events; RCM precipitation frequency is generally underpredicted. Overprediction is also reflected in wintertime precipitation variability, which tends to be too high for RCMs on both daily and interannual scales. Wintertime precipitation in most (but not all) GCMs is underestimated. This is in contrast to previous studies based on global blended gauge/satellite observations which are shown here to underestimate precipitation relative to higher-resolution gauge-only datasets. Several GCMs provide reasonable daily precipitation distributions, a trait which doesn't seem tied to model resolution. GCM daily and interannual variability is generally underpredicted.

  7. Improving weapons fallout time series on a global basis using precipitation data

    International Nuclear Information System (INIS)

    Palsson, S.E.; Howard, B.J.; Aoyama, M.

    2004-01-01

    The fallout from the atmospheric weapons tests in the late fifties and early sixties forms the main source of man made radionuclides in the terrestrial environment. It is important to be able to distinguish global fallout from other sources of man-made radioactivity, and therefore to have good methods of quantifying the level of global fallout in areas where it has not previously been measured. Because global fallout was deposited over many years, model validation can require knowledge about deposition time series which are not available through direct measurements. This can be especially important for sparsely populated areas with vulnerable ecosystems, where high transfer of radionuclides, particularly radiocaesium, may occur. The UNSCEAR reports describe the global data and show how the deposition was dependent on latitude. Others have successfully used a model assuming a proportional relationship between deposition and precipitation (e.g. on a regional scale within the AMAP project and on a local scale in some countries, such as Iceland and Sweden). This paper describes a study where different data sets were combined to test, at a local scale to a global scale, how well the proportional relationship between precipitation and deposition holds and to what degree other effects (e.g. dependence on latitude as in the UNSCEAR model) need to be taken into account. It makes use of the Integrated Global Fallout Database of the Meteorological Research Institute of Japan which has been used previously to demonstrate the relationship between precipitation and deposition and subsequently to make an estimate of the total fallout amount of 137 Cs in the mid latitudes of the Northern Hemisphere. The study described in this paper provides a fuller description of global deposition than the latitude or precipitation based studies alone. Applied in a simple model as presented here, this enable better deposition estimation (including time dependency), especially if precipitation

  8. Incorporation of a Cuban radiological station to the global net of isotopes in precipitations; Incorporacion de una estacion radiologica cubana a la red global de isotopos en precipitaciones

    Energy Technology Data Exchange (ETDEWEB)

    Dominguez L, O.; Ramos V, E.O.; Prendes A, M.; Alonso A, D.; Caveda R, C.A. [CPHR, Calle 20 No. 4113 e/41 y 47, Playa, C.P. 11300, A.P. 6195, C.P. 10600 La Habana (Cuba)]. e-mail: orlando@cphr.edu.cu

    2006-07-01

    From March, 2002 the West station of the National Net of Environmental Radiological Surveillance located in the Center of Protection and Hygiene of the Radiations, belongs to the Global Net of Isotopes in Precipitations. The obtained isotopic information of the analysis of the samples of monthly monitored precipitations (oxygen-18, deuterium and tritium) its are stored in a database, which is available through Internet. For the acceptance in the Global Net, it was necessary the incorporation to the monitoring of the station the meteorological surface variables. Also it was developed a software for the calculation of the tension of the water steam starting from the values of humidity and temperature. The obtained results in 2002 and published recently, its are inside the range of values reported for these isotopes in the Caribbean area. (Author)

  9. Climate change and precipitation: Detecting changes Climate change and precipitation: Detecting changes

    International Nuclear Information System (INIS)

    Van Boxel, John H

    2001-01-01

    Precipitation is one of the most, if not the most important climate parameter In most studies on climate change the emphasis is on temperature and sea level rise. Often too little attention is given to precipitation. For a large part this is due to the large spatial en temporal variability of precipitation, which makes the detection of changes difficult. This paper describes methods to detect changes in precipitation. In order to arrive at statistically significant changes one must use long time series and spatial averages containing the information from several stations. In the Netherlands the average yearly precipitation increased by 11% during the 20th century .In the temperate latitudes on the Northern Hemisphere (40-60QN) the average increase was about 7% over the 20th century and the globally averaged precipitation increased by about 3%. During the 20th century 38% of the land surface of the earth became wetter, 42% experienced little change (less than 5% change) and 20% became dryer. More important than the average precipitation is the occurrence of extremes. In the Netherlands there is a tendency to more extreme precipitations, whereas the occurrence of relatively dry months has not changed. Also in many other countries increases in heavy precipitation events are observed. All climate models predict a further increase of mean global precipitation if the carbon dioxide concentration doubles. Nevertheless some areas get dryer, others have little change and consequently there are also areas where the increase is much more than the global average. On a regional scale however there are large differences between the models. Climate models do not yet provide adequate information on changes in extreme precipitations

  10. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, 1997-present, Evaporation Minus Precipitation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Evaporation Minus Precipitation data from the TAO/TRITON (Pacific Ocean, https://www.pmel.noaa.gov/gtmba/ ), RAMA (Indian Ocean,...

  11. Global Precipitation Measurement (GPM) Core Observatory Falling Snow Estimates

    Science.gov (United States)

    Skofronick Jackson, G.; Kulie, M.; Milani, L.; Munchak, S. J.; Wood, N.; Levizzani, V.

    2017-12-01

    Retrievals of falling snow from space represent an important data set for understanding and linking the Earth's atmospheric, hydrological, and energy cycles. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. This work focuses on comparing the first stable falling snow retrieval products (released May 2017) for the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO), which was launched February 2014, and carries both an active dual frequency (Ku- and Ka-band) precipitation radar (DPR) and a passive microwave radiometer (GPM Microwave Imager-GMI). Five separate GPM-CO falling snow retrieval algorithm products are analyzed including those from DPR Matched (Ka+Ku) Scan, DPR Normal Scan (Ku), DPR High Sensitivity Scan (Ka), combined DPR+GMI, and GMI. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new, the different on-orbit instruments don't capture all snow rates equally, and retrieval algorithms differ. Thus a detailed comparison among the GPM-CO products elucidates advantages and disadvantages of the retrievals. GPM and CloudSat global snowfall evaluation exercises are natural investigative pathways to explore, but caution must be undertaken when analyzing these datasets for comparative purposes. This work includes outlining the challenges associated with comparing GPM-CO to CloudSat satellite snow estimates due to the different sampling, algorithms, and instrument capabilities. We will highlight some factors and assumptions that can be altered or statistically normalized and applied in an effort to make comparisons between GPM and CloudSat global satellite falling snow products as equitable as possible.

  12. Global warming precipitation accumulation increases above the current-climate cutoff scale.

    Science.gov (United States)

    Neelin, J David; Sahany, Sandeep; Stechmann, Samuel N; Bernstein, Diana N

    2017-02-07

    Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff.

  13. Global warming precipitation accumulation increases above the current-climate cutoff scale

    Science.gov (United States)

    Sahany, Sandeep; Stechmann, Samuel N.; Bernstein, Diana N.

    2017-01-01

    Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff. PMID:28115693

  14. Regional climate change: Precipitation variability in mountainous part of Bulgaria

    Directory of Open Access Journals (Sweden)

    Nikolova Nina

    2007-01-01

    Full Text Available The aim of paper is to analyze temporal and spatial changes in monthly precipitation as well as extremely dry and wet months in mountainous part of Bulgaria. Study precipitation variability in mountainous part is very important because this part is the region where the rivers take its source from. Extreme values of monthly precipitation are important information for better understanding of the whole variability and trends in precipitation time series. The mean investigated period is 1951-2005 and the reference period is so called temporary climate - 1961- 1990. Extreme dry precipitation months are defined as a month whose monthly precipitation is lower than 10% of gamma distribution in the reference period 1961-1990. Extreme wet months are determined with respect to 90% percentiles of gamma distribution (monthly precipitation is higher than 90%. The result of the research show that in mountainous part of Bulgaria during 1950s and 1960s number of extremely wet months is higher than number of dry months. Decreasing of monthly precipitation is a feature for 1980s. This dry period continues till 2004. The years 2000 makes impression as driest year in high mountains with about 7 extremely dry months. The second dry year is 1993. The negative precipitation anomaly is most clearly determined during last decade at study area. The present research points out that fluctuation of precipitation in mountainous part of Bulgaria are coinciding with regional and global climate trends.

  15. Global Precipitation Climatology Project (GPCP) - Daily, Version 1.2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Precipitation Climatology Project (GPCP) comprises a total of 27 products. The Version 1.2 Daily product covers the period October 1998 to the present,...

  16. Global Precipitation Climatology Project (GPCP) - Pentad, Version 2.2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Precipitation Climatology Project (GPCP) comprises a total of 27 products. The Version 2.2 Pentad product covers the period January 1979 to the present,...

  17. Developing Information Services and Tools to Access and Evaluate Data Quality in Global Satellite-based Precipitation Products

    Science.gov (United States)

    Liu, Z.; Shie, C. L.; Meyer, D. J.

    2017-12-01

    Global satellite-based precipitation products have been widely used in research and applications around the world. Compared to ground-based observations, satellite-based measurements provide precipitation data on a global scale, especially in remote continents and over oceans. Over the years, satellite-based precipitation products have evolved from single sensor and single algorithm to multi-sensors and multi-algorithms. As a result, many satellite-based precipitation products have been enhanced such as spatial and temporal coverages. With inclusion of ground-based measurements, biases of satellite-based precipitation products have been significantly reduced. However, data quality issues still exist and can be caused by many factors such as observations, satellite platform anomaly, algorithms, production, calibration, validation, data services, etc. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to NASA global precipitation product archives including the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), as well as other global and regional precipitation products. Precipitation is one of the top downloaded and accessed parameters in the GES DISC data archive. Meanwhile, users want to easily locate and obtain data quality information at regional and global scales to better understand how precipitation products perform and how reliable they are. As data service providers, it is necessary to provide an easy access to data quality information, however, such information normally is not available, and when it is available, it is not in one place and difficult to locate. In this presentation, we will present challenges and activities at the GES DISC to address precipitation data quality issues.

  18. Tritium Level in Romanian Precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Varlam, C.; Stefanescu, I.; Faurescu, I.; Bogdan, D.; Soare, A. [Institute for Cryogenic and Isotope Technologies, Rm. Valcea (Romania); Duliu, O. G. [Faculty of Physics, University of Bucharest, Magurele (Romania)

    2013-07-15

    Romania is one of the countries that has no station included in GNIP (Global Network of Isotopes in Precipitation) on its territory. This paper presents results regarding the tritium concentration in precipitation for the period 1999-2009. The precipitation fell at the Institute for cryogenic and Isotope technologies (geographical coordinates: altitude 237 m, latitude 45{sup o}02'07' N, longitude 24{sup o}17'03' E) an was collected both individually and as a composite average of each month. It was individually measured and the average was calculated and compared with the tritium concentration measured in the composite sample. tritium concentration levels ranged from 9.9 {+-} 2.1 TU for 2004 and 13.7 {+-} 2.2 TU for 2009. Comparing the arithmetic mean values with the weighted mean for the period of observation, it was noticed that the higher absolute values of the weighted means were constant. It was found that for the calculated monthly average for the period of observation (1999-2009), the months with the maximum tritium concentration are the same as the months with the maximum amount of precipitation. This behaviour is typical for the monitored location. (author)

  19. Climate Prediction Center (CPC) One Month Probabilistic Precipitation Outlook for the Contiguous United States and Alaska

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center (CPC) issues a probabilistic one-month precipitation outlook for the United States twice a month. CPC issues an initial monthly outlook...

  20. Global Precipitation Measurement Mission: Architecture and Mission Concept

    Science.gov (United States)

    Bundas, David

    2005-01-01

    The Global Precipitation Measurement (GPM) Mission is a collaboration between the National Aeronautics and Space Administration (NASA) and the Japanese Aerospace Exploration Agency (JAXA), and other partners, with the goal of monitoring the diurnal and seasonal variations in precipitation over the surface of the earth. These measurements will be used to improve current climate models and weather forecasting, and enable improved storm and flood warnings. This paper gives an overview of the mission architecture and addresses some of the key trades that have been completed, including the selection of the Core Observatory s orbit, orbit maintenance trades, and design issues related to meeting orbital debris requirements.

  1. The nonstationary impact of local temperature changes and ENSO on extreme precipitation at the global scale

    Science.gov (United States)

    Sun, Qiaohong; Miao, Chiyuan; Qiao, Yuanyuan; Duan, Qingyun

    2017-12-01

    The El Niño-Southern Oscillation (ENSO) and local temperature are important drivers of extreme precipitation. Understanding the impact of ENSO and temperature on the risk of extreme precipitation over global land will provide a foundation for risk assessment and climate-adaptive design of infrastructure in a changing climate. In this study, nonstationary generalized extreme value distributions were used to model extreme precipitation over global land for the period 1979-2015, with ENSO indicator and temperature as covariates. Risk factors were estimated to quantify the contrast between the influence of different ENSO phases and temperature. The results show that extreme precipitation is dominated by ENSO over 22% of global land and by temperature over 26% of global land. With a warming climate, the risk of high-intensity daily extreme precipitation increases at high latitudes but decreases in tropical regions. For ENSO, large parts of North America, southern South America, and southeastern and northeastern China are shown to suffer greater risk in El Niño years, with more than double the chance of intense extreme precipitation in El Niño years compared with La Niña years. Moreover, regions with more intense precipitation are more sensitive to ENSO. Global climate models were used to investigate the changing relationship between extreme precipitation and the covariates. The risk of extreme, high-intensity precipitation increases across high latitudes of the Northern Hemisphere but decreases in middle and lower latitudes under a warming climate scenario, and will likely trigger increases in severe flooding and droughts across the globe. However, there is some uncertainties associated with the influence of ENSO on predictions of future extreme precipitation, with the spatial extent and risk varying among the different models.

  2. Monthly, global emissions of carbon dioxide from fossil fuel consumption

    Energy Technology Data Exchange (ETDEWEB)

    Andres, R. J.; Marland, G.; Boden, T. A. (Environmental Sciences Div., Oak Ridge National Laboratory, Oak Ridge, TN (United States)), e-mail: andresrj@ornl.gov; Gregg, J. S. (Risoe DTU National Laboratory for Sustainable Energy, Roskilde (Denmark)); Losey, L. (Dept. of Space Studies, Univ. of North Dakota, Grand Forks, ND (United States))

    2011-07-15

    This paper examines available data, develops a strategy and presents a monthly, global time series of fossil-fuel carbon dioxide emissions for the years 1950-2006. This monthly time series was constructed from detailed study of monthly data from the 21 countries that account for approximately 80% of global total emissions. These data were then used in a Monte Carlo approach to proxy for all remaining countries. The proportional-proxy methodology estimates by fuel group the fraction of annual emissions emitted in each country and month. Emissions from solid, liquid and gas fuels are explicitly modelled by the proportional-proxy method. The primary conclusion from this study is the global monthly time series is statistically significantly different from a uniform distribution throughout the year. Uncertainty analysis of the data presented show that the proportional-proxy method used faithfully reproduces monthly patterns in the data and the global monthly pattern of emissions is relatively insensitive to the exact proxy assignments used. The data and results presented here should lead to a better understanding of global and regional carbon cycles, especially when the mass data are combined with the stable carbon isotope data in atmospheric transport models

  3. Calibration Plans for the Global Precipitation Measurement (GPM)

    Science.gov (United States)

    Bidwell, S. W.; Flaming, G. M.; Adams, W. J.; Everett, D. F.; Mendelsohn, C. R.; Smith, E. A.; Turk, J.

    2002-01-01

    The Global Precipitation Measurement (GPM) is an international effort led by the National Aeronautics and Space Administration (NASA) of the U.S.A. and the National Space Development Agency of Japan (NASDA) for the purpose of improving research into the global water and energy cycle. GPM will improve climate, weather, and hydrological forecasts through more frequent and more accurate measurement of precipitation world-wide. Comprised of U.S. domestic and international partners, GPM will incorporate and assimilate data streams from many spacecraft with varied orbital characteristics and instrument capabilities. Two of the satellites will be provided directly by GPM, the core satellite and a constellation member. The core satellite, at the heart of GPM, is scheduled for launch in November 2007. The core will carry a conical scanning microwave radiometer, the GPM Microwave Imager (GMI), and a two-frequency cross-track-scanning radar, the Dual-frequency Precipitation Radar (DPR). The passive microwave channels and the two radar frequencies of the core are carefully chosen for investigating the varying character of precipitation over ocean and land, and from the tropics to the high-latitudes. The DPR will enable microphysical characterization and three-dimensional profiling of precipitation. The GPM-provided constellation spacecraft will carry a GMI radiometer identical to that on the core spacecraft. This paper presents calibration plans for the GPM, including on-board instrument calibration, external calibration methods, and the role of ground validation. Particular emphasis is on plans for inter-satellite calibration of the GPM constellation. With its Unique instrument capabilities, the core spacecraft will serve as a calibration transfer standard to the GPM constellation. In particular the Dual-frequency Precipitation Radar aboard the core will check the accuracy of retrievals from the GMI radiometer and will enable improvement of the radiometer retrievals

  4. Changes in precipitation extremes projected by a 20-km mesh global atmospheric model

    Directory of Open Access Journals (Sweden)

    Akio Kitoh

    2016-03-01

    Full Text Available High-resolution modeling is necessary to project weather and climate extremes and their future changes under global warming. A global high-resolution atmospheric general circulation model with grid size about 20 km is able to reproduce climate fields as well as regional-scale phenomena such as monsoonal rainfall, tropical and extratropical cyclones, and heavy precipitation. This 20-km mesh model is applied to project future changes in weather and climate extremes at the end of the 21st century with four different spatial patterns in sea surface temperature (SST changes: one with the mean SST changes by the 28 models of the Coupled Model Intercomparison Project Phase 5 (CMIP5 under the Representative Concentration Pathways (RCP-8.5 scenario, and the other three obtained from a cluster analysis, in which tropical SST anomalies derived from the 28 CMIP5 models were grouped. Here we focus on future changes in regional precipitation and its extremes. Various precipitation indices averaged over the Twenty-two regional land domains are calculated. Heavy precipitation indices (maximum 5-day precipitation total and maximum 1-day precipitation total increase in all regional domains, even where mean precipitation decrease (Southern Africa, South Europe/Mediterranean, Central America. South Asia is the domain of the largest extreme precipitation increase. In some domains, different SST patterns result in large precipitation changes, possibly related to changes in large-scale circulations in the tropical Pacific.

  5. New Global Precipitation Products and Data Service Updates at the NASA GES DISC

    Science.gov (United States)

    Liu, Z.; Ostrenga, D.; Savtchenko, A.; DeShong, B.; Greene, M.; Vollmer, B.; Kempler, S.

    2016-01-01

    This poster describes recent updates of the ongoing GPM data service activities at the NASA Goddard Earth Sciences (GES) Data and Information Services Center(DISC) to facilitate access and exploration of GPM, TRMM and other NASA precipitation datasets for the global community. The poster contains -Updates on GPM products and data services -New features in Giovanni for precipitation data visualization -Precipitation data and service outreach activities.

  6. Applying Advances in GPM Radiometer Intercalibration and Algorithm Development to a Long-Term TRMM/GPM Global Precipitation Dataset

    Science.gov (United States)

    Berg, W. K.

    2016-12-01

    The Global Precipitation Mission (GPM) Core Observatory, which was launched in February of 2014, provides a number of advances for satellite monitoring of precipitation including a dual-frequency radar, high frequency channels on the GPM Microwave Imager (GMI), and coverage over middle and high latitudes. The GPM concept, however, is about producing unified precipitation retrievals from a constellation of microwave radiometers to provide approximately 3-hourly global sampling. This involves intercalibration of the input brightness temperatures from the constellation radiometers, development of an apriori precipitation database using observations from the state-of-the-art GPM radiometer and radars, and accounting for sensor differences in the retrieval algorithm in a physically-consistent way. Efforts by the GPM inter-satellite calibration working group, or XCAL team, and the radiometer algorithm team to create unified precipitation retrievals from the GPM radiometer constellation were fully implemented into the current version 4 GPM precipitation products. These include precipitation estimates from a total of seven conical-scanning and six cross-track scanning radiometers as well as high spatial and temporal resolution global level 3 gridded products. Work is now underway to extend this unified constellation-based approach to the combined TRMM/GPM data record starting in late 1997. The goal is to create a long-term global precipitation dataset employing these state-of-the-art calibration and retrieval algorithm approaches. This new long-term global precipitation dataset will incorporate the physics provided by the combined GPM GMI and DPR sensors into the apriori database, extend prior TRMM constellation observations to high latitudes, and expand the available TRMM precipitation data to the full constellation of available conical and cross-track scanning radiometers. This combined TRMM/GPM precipitation data record will thus provide a high-quality high

  7. Detecting quasi-oscillations in the monthly precipitation regimes of the Iberian Peninsula

    Directory of Open Access Journals (Sweden)

    L. Morala

    2003-03-01

    Full Text Available A spectral analysis of the time series corresponding to the main monthly precipitation regimes of the Iberian Peninsula was performed using two methods, the Multi-Taper Method and Monte Carlo Singular Spectrum Analysis. The Multi-Taper Method gave a preliminary view of the presence of signals in some of the time series. Monte Carlo Singular Spectrum Analysis discriminated between potential oscillations and noise. From the results of the two methods it is concluded that there exist three significant quasi-oscillations at the 95% level of confidence: a 5.0 year quasi-oscillation and a long-term trend in the Atlantic pattern of March, a 3.2 year quasi-oscillation in the Cantabrian pattern of January, and a 4.0 year quasi-oscillation in the Catalonian pattern of February. These quasi-oscillations might be related to climatic variations with similar periodicities over the North Atlantic Ocean. The possible simultaneity of high values of precipitation generated by the significant quasi-oscillations and high sea–level pressures was studied by means of composite maps. It was found that high values of precipitation generated by the oscillations of the Atlantic patterns of January and March exist simultaneously with a specific high pressure structure over the North Atlantic Ocean, that allow cyclonic perturbations to cross the Iberian Peninsula. During the non-wet years, this high pressure structure moves northwards, keeping the track of the low pressure centers to the north, far from the Iberian Peninsula. On the other hand, high values of precipitation generated by the oscillation of the Cantabrian pattern of January exist simultaneously with a high pressure structure over the Galicia region and the Cantabrian Sea, that allow a northerly flow over the region. Also, a positive trend in the NAO index for March has been found, starting in the sixties, which is not evident for other winter months. This trend agrees with the decreasing trend found in the

  8. Global warming and South Indian monsoon rainfall-lessons from the Mid-Miocene.

    Science.gov (United States)

    Reuter, Markus; Kern, Andrea K; Harzhauser, Mathias; Kroh, Andreas; Piller, Werner E

    2013-04-01

    Precipitation over India is driven by the Indian monsoon. Although changes in this atmospheric circulation are caused by the differential seasonal diabatic heating of Asia and the Indo-Pacific Ocean, it is so far unknown how global warming influences the monsoon rainfalls regionally. Herein, we present a Miocene pollen flora as the first direct proxy for monsoon over southern India during the Middle Miocene Climate Optimum. To identify climatic key parameters, such as mean annual temperature, warmest month temperature, coldest month temperature, mean annual precipitation, mean precipitation during the driest month, mean precipitation during the wettest month and mean precipitation during the warmest month the Coexistence Approach is applied. Irrespective of a ~ 3-4 °C higher global temperature during the Middle Miocene Climate Optimum, the results indicate a modern-like monsoonal precipitation pattern contrasting marine proxies which point to a strong decline of Indian monsoon in the Himalaya at this time. Therefore, the strength of monsoon rainfall in tropical India appears neither to be related to global warming nor to be linked with the atmospheric conditions over the Tibetan Plateau. For the future it implies that increased global warming does not necessarily entail changes in the South Indian monsoon rainfall.

  9. Next-Generation Satellite Precipitation Products for Understanding Global and Regional Water Variability

    Science.gov (United States)

    Hou, Arthur Y.

    2011-01-01

    A major challenge in understanding the space-time variability of continental water fluxes is the lack of accurate precipitation estimates over complex terrains. While satellite precipitation observations can be used to complement ground-based data to obtain improved estimates, space-based and ground-based estimates come with their own sets of uncertainties, which must be understood and characterized. Quantitative estimation of uncertainties in these products also provides a necessary foundation for merging satellite and ground-based precipitation measurements within a rigorous statistical framework. Global Precipitation Measurement (GPM) is an international satellite mission that will provide next-generation global precipitation data products for research and applications. It consists of a constellation of microwave sensors provided by NASA, JAXA, CNES, ISRO, EUMETSAT, DOD, NOAA, NPP, and JPSS. At the heart of the mission is the GPM Core Observatory provided by NASA and JAXA to be launched in 2013. The GPM Core, which will carry the first space-borne dual-frequency radar and a state-of-the-art multi-frequency radiometer, is designed to set new reference standards for precipitation measurements from space, which can then be used to unify and refine precipitation retrievals from all constellation sensors. The next-generation constellation-based satellite precipitation estimates will be characterized by intercalibrated radiometric measurements and physical-based retrievals using a common observation-derived hydrometeor database. For pre-launch algorithm development and post-launch product evaluation, NASA supports an extensive ground validation (GV) program in cooperation with domestic and international partners to improve (1) physics of remote-sensing algorithms through a series of focused field campaigns, (2) characterization of uncertainties in satellite and ground-based precipitation products over selected GV testbeds, and (3) modeling of atmospheric processes and

  10. Classification and global distribution of ocean precipitation types based on satellite passive microwave signatures

    Science.gov (United States)

    Gautam, Nitin

    The main objectives of this thesis are to develop a robust statistical method for the classification of ocean precipitation based on physical properties to which the SSM/I is sensitive and to examine how these properties vary globally and seasonally. A two step approach is adopted for the classification of oceanic precipitation classes from multispectral SSM/I data: (1)we subjectively define precipitation classes using a priori information about the precipitating system and its possible distinct signature on SSM/I data such as scattering by ice particles aloft in the precipitating cloud, emission by liquid rain water below freezing level, the difference of polarization at 19 GHz-an indirect measure of optical depth, etc.; (2)we then develop an objective classification scheme which is found to reproduce the subjective classification with high accuracy. This hybrid strategy allows us to use the characteristics of the data to define and encode classes and helps retain the physical interpretation of classes. The classification methods based on k-nearest neighbor and neural network are developed to objectively classify six precipitation classes. It is found that the classification method based neural network yields high accuracy for all precipitation classes. An inversion method based on minimum variance approach was used to retrieve gross microphysical properties of these precipitation classes such as column integrated liquid water path, column integrated ice water path, and column integrated min water path. This classification method is then applied to 2 years (1991-92) of SSM/I data to examine and document the seasonal and global distribution of precipitation frequency corresponding to each of these objectively defined six classes. The characteristics of the distribution are found to be consistent with assumptions used in defining these six precipitation classes and also with well known climatological patterns of precipitation regions. The seasonal and global

  11. The Global Precipitation Measurement (GPM) Mission: Overview and U.S. Status

    Science.gov (United States)

    Hou, Arthur Y.; Azarbarzin, Ardeshir A.; Kakar, Ramesh K.; Neeck, Steven

    2011-01-01

    The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. The cornerstone of the GPM mission is the deployment of a Core Observatory in a 65 deg non-Sun-synchronous orbit to serve as a physics observatory and a transfer standard for inter-calibration of constellation radiometers. The GPM Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Radiometer (GMI). The first space-borne dual-frequency radar will provide not only measurements of 3-D precipitation structures but also quantitative information on microphysical properties of precipitating particles needed for improving precipitation retrievals from passive microwave sensors. The combined use of DPR and GMI measurements will place greater constraints on radiometer retrievals to improve the accuracy and consistency of precipitation estimates from all constellation radiometers. The GPM constellation is envisioned to comprise five or more conical-scanning microwave radiometers and four or more cross-track microwave sounders on operational satellites. NASA and the Japan Aerospace Exploration Agency (JAXA) plan to launch the GPM Core in July 2013. NASA will provide a second radiometer to be flown on a partner-provided GPM Low-Inclination Observatory (L10) to improve near real-time monitoring of hurricanes and mid-latitude storms. NASA and the Brazilian Space Program (AEB/IPNE) are currently engaged in a one-year study on potential L10 partnership. JAXA will contribute to GPM data from the Global Change Observation Mission-Water (GCOM-W) satellite. Additional partnerships are under development to include microwave radiometers on the French-Indian Megha-Tropiques satellite and U.S. Defense Meteorological Satellite Program (DMSP) satellites, as well as cross

  12. Implications of a decrease in the precipitation area for the past and the future

    Science.gov (United States)

    Benestad, Rasmus E.

    2018-04-01

    The total area with 24 hrs precipitation has shrunk by 7% between 50°S–50°N over the period 1998–2016, according to the satellite-based Tropical Rain Measurement Mission data. A decrease in the daily precipitation area is an indication of profound changes in the hydrological cycle, where the global rate of precipitation is balanced by the global rate of evaporation. This decrease was accompanied by increases in total precipitation, evaporation, and wet-day mean precipitation. If these trends are real, then they suggest increased drought frequencies and more intense rainfall. Satellite records, however, may be inhomogeneous because they are synthesised from a number of individual missions with improved technology over time. A linear dependency was also found between the global mean temperature and the 50°S–50°N daily precipitation area with a slope value of ‑17 × 106 km 2/°C. This dependency was used with climate model simulations to make future projections which suggested a continued decrease that will strengthen in the future. The precipitation area evolves differently when the precipitation is accumulated over short and long time scales, however, and there has been a slight increase in the monthly precipitation area while the daily precipitation area decreased. An increase on monthly scale may indicate more pronounced variations in the rainfall patterns due to migrating rain-producing phenomena.

  13. Global monthly water stress: II. Water demand and severity of water

    NARCIS (Netherlands)

    Wada, Y.; Beek, L.P.H. van; Viviroli, D.; Dürr, H.H.; Weingartner, R.; Bierkens, M.F.P.

    2011-01-01

    This paper assesses global water stress at a finer temporal scale compared to conventional assessments. To calculate time series of global water stress at a monthly time scale, global water availability, as obtained from simulations of monthly river discharge from the companion paper, is confronted

  14. Flood triggering in Switzerland: the role of daily to monthly preceding precipitation

    Science.gov (United States)

    Froidevaux, P.; Schwanbeck, J.; Weingartner, R.; Chevalier, C.; Martius, O.

    2015-09-01

    Determining the role of different precipitation periods for peak discharge generation is crucial for both projecting future changes in flood probability and for short- and medium-range flood forecasting. In this study, catchment-averaged daily precipitation time series are analyzed prior to annual peak discharge events (floods) in Switzerland. The high number of floods considered - more than 4000 events from 101 catchments have been analyzed - allows to derive significant information about the role of antecedent precipitation for peak discharge generation. Based on the analysis of precipitation times series, a new separation of flood-related precipitation periods is proposed: (i) the period 0 to 1 day before flood days, when the maximum flood-triggering precipitation rates are generally observed, (ii) the period 2 to 3 days before flood days, when longer-lasting synoptic situations generate "significantly higher than normal" precipitation amounts, and (iii) the period from 4 days to 1 month before flood days when previous wet episodes may have already preconditioned the catchment. The novelty of this study lies in the separation of antecedent precipitation into the precursor antecedent precipitation (4 days before floods or earlier, called PRE-AP) and the short range precipitation (0 to 3 days before floods, a period when precipitation is often driven by one persistent weather situation like e.g., a stationary low-pressure system). A precise separation of "antecedent" and "peak-triggering" precipitation is not attempted. Instead, the strict definition of antecedent precipitation periods permits a direct comparison of all catchments. The precipitation accumulating 0 to 3 days before an event is the most relevant for floods in Switzerland. PRE-AP precipitation has only a weak and region-specific influence on flood probability. Floods were significantly more frequent after wet PRE-AP periods only in the Jura Mountains, in the western and eastern Swiss plateau, and at

  15. Global monsoon precipitation responses to large volcanic eruptions.

    Science.gov (United States)

    Liu, Fei; Chai, Jing; Wang, Bin; Liu, Jian; Zhang, Xiao; Wang, Zhiyuan

    2016-04-11

    Climate variation of global monsoon (GM) precipitation involves both internal feedback and external forcing. Here, we focus on strong volcanic forcing since large eruptions are known to be a dominant mechanism in natural climate change. It is not known whether large volcanoes erupted at different latitudes have distinctive effects on the monsoon in the Northern Hemisphere (NH) and the Southern Hemisphere (SH). We address this issue using a 1500-year volcanic sensitivity simulation by the Community Earth System Model version 1.0 (CESM1). Volcanoes are classified into three types based on their meridional aerosol distributions: NH volcanoes, SH volcanoes and equatorial volcanoes. Using the model simulation, we discover that the GM precipitation in one hemisphere is enhanced significantly by the remote volcanic forcing occurring in the other hemisphere. This remote volcanic forcing-induced intensification is mainly through circulation change rather than moisture content change. In addition, the NH volcanic eruptions are more efficient in reducing the NH monsoon precipitation than the equatorial ones, and so do the SH eruptions in weakening the SH monsoon, because the equatorial eruptions, despite reducing moisture content, have weaker effects in weakening the off-equatorial monsoon circulation than the subtropical-extratropical volcanoes do.

  16. Performance evaluation of latest integrated multi-satellite retrievals for Global Precipitation Measurement (IMERG) over the northern highlands of Pakistan

    Science.gov (United States)

    Anjum, Muhammad Naveed; Ding, Yongjian; Shangguan, Donghui; Ahmad, Ijaz; Ijaz, Muhammad Wajid; Farid, Hafiz Umar; Yagoub, Yousif Elnour; Zaman, Muhammad; Adnan, Muhammad

    2018-06-01

    Recently, the Global Precipitation Measurement (GPM) mission has released the Integrated Multi-satellite Retrievals for GPM (IMERG) at a fine spatial (0.1° × 0.1°) and temporal (half hourly) resolutions. A comprehensive evaluation of this newly launched precipitation product is very important for satellite-based precipitation data users as well as for algorithm developers. The objective of this study was to provide a preliminary and timely performance evaluation of the IMERG product over the northern high lands of Pakistan. For comparison reference, the real-time and post real-time Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products were also evaluated parallel to the IMERG. All of the selected precipitation products were evaluated at annual, monthly, seasonal and daily time scales using reference gauges data from April 2014 to December 2016. The results showed that: (1) the precipitation estimates from IMERG, 3B42V7 and 3B42RT products correlated well with the reference gauges observations at monthly time scale (CC = 0.93, 0.91, 0.88, respectively), whereas moderately at the daily time scale (CC = 0.67, 0.61, and 0.58, respectively); (2) Compared to the 3B42V7 and 3B42RT, the precipitation estimates from IMERG were more reliable in all seasons particularly in the winter season with lowest relative bias (2.61%) and highest CC (0.87); (3) IMERG showed a clear superiority over 3B42V7 and 3B42RT products in order to capture spatial distribution of precipitation over the northern Pakistan; (4) Relative to the 3B42V7 and 3B42RT, daily precipitation estimates from IMEREG showed lowest relative bias (9.20% vs. 21.40% and 26.10%, respectively) and RMSE (2.05 mm/day vs. 2.49 mm/day and 2.88 mm/day, respectively); and (5) Light precipitation events (0-1 mm/day) were usually overestimated by all said satellite-based precipitation products. In contrast moderate (1-20 mm/day) to heavy (>20 mm/day) precipitation events were

  17. Validation of a homogeneous 41-year (1961-2001) winter precipitation hindcasted dataset over the Iberian Peninsula: assessment of the regional improvement of global reanalysis

    Energy Technology Data Exchange (ETDEWEB)

    Sotillo, M.G. [Area de Medio Fisico, Puertos del Estado, Madrid (Spain); Martin, M.L. [Universidad de Valladolid, Dpto. Matematica Aplicada, Escuela Universitaria de Informatica, Campus de Segovia, Segovia (Spain); Valero, F. [Universidad Complutense de Madrid, Dpto. Astrofisica y CC. de la Atmosfera, Facultad de CC Fisicas, Madrid (Spain); Luna, M.Y. [Instituto Nacional de Meteorologia, Madrid (Spain)

    2006-11-15

    A 44-year (1958-2001) homogeneous, Mediterranean, high-resolution atmospheric database was generated through dynamical downscaling within the HIPOCAS (Hindcast of Dynamic Processes of the Ocean and Coastal Areas of Europe) Project framework. This work attempts to provide a validation of the monthly winter HIPOCAS precipitation over the Iberian Peninsula and the Balearic Islands and to evaluate the potential improvement of these new hindcasted data versus global reanalysis datasets. The validation was performed through the comparative analysis with a precipitation database derived from 4,617 in situ stations located over Iberia and the Balearics. The statistical comparative analysis between the observed and the HIPOCAS fields highlights their very good agreement not only in terms of spatial and time distribution, but also in terms of total amount of precipitation. A principal component analysis is carried out, showing that the patterns derived from the HIPOCAS data largely capture the main characteristics of the observed field. Moreover, it is worth to note that the HIPOCAS patterns reproduce accurately the observed regional characteristics linked to the main orographic features of the study domain. The existence of high correlations between the hindcasted and observed principal component time series gives a measure of the model performance ability. An additional comparative study of the HIPOCAS winter precipitation with global reanalysis data (NCEP and ERA) is performed. This study reveals the important regional improvement in the characterization of the observed precipitation introduced by the HIPOCAS hindcast relative to the above global reanalyses. Such improvement is effective not only in terms of total amount values, but also in the spatial distribution, the observed field being much more realistically reproduced by HIPOCAS than by the global reanalysis data. (orig.)

  18. Systematical estimation of GPM-based global satellite mapping of precipitation products over China

    Science.gov (United States)

    Zhao, Haigen; Yang, Bogang; Yang, Shengtian; Huang, Yingchun; Dong, Guotao; Bai, Juan; Wang, Zhiwei

    2018-03-01

    As the Global Precipitation Measurement (GPM) Core Observatory satellite continues its mission, new version 6 products for Global Satellite Mapping of Precipitation (GSMaP) have been released. However, few studies have systematically evaluated the GSMaP products over mainland China. This study quantitatively evaluated three GPM-based GSMaP version 6 precipitation products for China and eight subregions referring to the Chinese daily Precipitation Analysis Product (CPAP). The GSMaP products included near-real-time (GSMaP_NRT), microwave-infrared reanalyzed (GSMaP_MVK), and gauge-adjusted (GSMaP_Gau) data. Additionally, the gauge-adjusted Integrated Multi-Satellite Retrievals for Global Precipitation Measurement Mission (IMERG_Gau) was also assessed and compared with GSMaP_Gau. The analyses of the selected daily products were carried out at spatiotemporal resolutions of 1/4° for the period of March 2014 to December 2015 in consideration of the resolution of CPAP and the consistency of the coverage periods of the satellite products. The results indicated that GSMaP_MVK and GSMaP_NRT performed comparably and underdetected light rainfall events (Pearson linear correlation coefficient (CC), fractional standard error (FSE), and root-mean-square error (RMSE) metrics during the summer. Compared with GSMaP_NRT and GSMaP_MVK, GSMaP_Gau possessed significantly improved metrics over mainland China and the eight subregions and performed better in terms of CC, RMSE, and FSE but underestimated precipitation to a greater degree than IMERG_Gau. As a quantitative assessment of the GPM-era GSMaP products, these validation results will supply helpful references for both end users and algorithm developers. However, the study findings need to be confirmed over a longer future study period when the longer-period IMERG retrospectively-processed data are available.

  19. The Climate Hazards group InfraRed Precipitation (CHIRP) with Stations (CHIRPS): Development and Validation

    Science.gov (United States)

    Peterson, P.; Funk, C. C.; Husak, G. J.; Pedreros, D. H.; Landsfeld, M.; Verdin, J. P.; Shukla, S.

    2013-12-01

    CHIRP and CHIRPS are new quasi-global precipitation products with daily to seasonal time scales, a 0.05° resolution, and a 1981 to near real-time period of record. Developed by the Climate Hazards Group at UCSB and scientists at the U.S. Geological Survey Earth Resources Observation and Science Center specifically for drought early warning and environmental monitoring, CHIRPS provides moderate latency precipitation estimates that place observed hydrologic extremes in their historic context. Three main types of information are used in the CHIRPS: (1) global 0.05° precipitation climatologies, (2) time-varying grids of satellite-based precipitation estimates, and (3) in situ precipitation observations. CHIRP: The global grids of long-term (1980-2009) average precipitation were estimated for each month based on station data, averaged satellite observations, and physiographic parameters. 1981-present time-varying grids of satellite precipitation were derived from spatially varying regression models based on pentadal cold cloud duration (CCD) values and TRMM V7 training data. The CCD time-series were derived from the CPC and NOAA B1 datasets. Pentadal CCD-percent anomaly values were multiplied by pentadal climatology fields to produce low bias pentadal precipitation estimates. CHIRPS: The CHG station blending procedure uses the satellite-observed spatial covariance structure to assign relative weights to neighboring stations and the CHIRP values. The CHIRPS blending procedure is based on the expected correlation between precipitation at a given target location and precipitation at the locations of the neighboring observation stations. These correlations are estimated using the CHIRP fields. The CHG has developed an extensive archive of in situ daily, pentadal and monthly precipitation totals. The CHG database has over half a billion daily rainfall observations since 1980 and another half billion before 1980. Most of these observations come from four sets of global

  20. The Global Network of Isotopes in Precipitation after 55 years: assessing past, present and future developments

    Science.gov (United States)

    Terzer, Stefan; Araguas-Araguas, Luis; Wassenaar, Leonard I.; Aggarwal, Pradeep K.

    2015-04-01

    The Global Network of Isotopes in Precipitation (GNIP) is a global observation programme operated by the International Atomic Energy Agency (IAEA), in cooperation with the World Meteorological Organization (WMO) and more than 100 contributing institutions worldwide. GNIP has been the primary repository for baseline stable (δ18O, δ2H) and radioactive (3H) isotope data since its foundation in 1960. The impetus for GNIP was the monitoring of radioactive fallout from atmospheric thermonuclear testing and resulting tritium levels of precipitation, but tritium together with stable isotopes was recognized as a key to understanding hydrological processes. Later, new applications were developed focusing on hydrometeorology and paleoclimatic research. Increasingly, GNIP data are being used more widely in ecological and forensic investigations, e.g. for tracking of migratory animals. The GNIP database comprises more than 135,000 isotopic records (δ18O: 63,000; δ2H: 55,000; 3H: 63,000) of monthly composite precipitation samples from more than 1,000 stations worldwide. About 300 stations are currently active for stable isotopes and ca. 100 for tritium. Data for most of the active stations is available up to 2013. Several national isotopic observation networks (e.g. in Austria, Australia, China or the United States of America) exist besides GNIP, complementing precipitation isotope data at national levels. The spatially and temporally discrete nature of the GNIP dataset induces coverage gaps. Recently, highly-resolved gridded datasets were established to help overcome this deficiency through geostatistical prediction models. These 'isoscape' (isotopic landscapes) are based on combinations of multiple regression and interpolation methods, with a range of parameterization available at regional and global levels. Attempts to bridge the gap between 'one-size-fits-all' global parameterization and improved predictions at regional and local levels led to the establishment of a

  1. Global Precipitation Measurement (GPM) Mission: Precipitation Processing System (PPS) GPM Mission Gridded Text Products Provide Surface Precipitation Retrievals

    Science.gov (United States)

    Stocker, Erich Franz; Kelley, O.; Kummerow, C.; Huffman, G.; Olson, W.; Kwiatkowski, J.

    2015-01-01

    In February 2015, the Global Precipitation Measurement (GPM) mission core satellite will complete its first year in space. The core satellite carries a conically scanning microwave imager called the GPM Microwave Imager (GMI), which also has 166 GHz and 183 GHz frequency channels. The GPM core satellite also carries a dual frequency radar (DPR) which operates at Ku frequency, similar to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar, and a new Ka frequency. The precipitation processing system (PPS) is producing swath-based instantaneous precipitation retrievals from GMI, both radars including a dual-frequency product, and a combined GMIDPR precipitation retrieval. These level 2 products are written in the HDF5 format and have many additional parameters beyond surface precipitation that are organized into appropriate groups. While these retrieval algorithms were developed prior to launch and are not optimal, these algorithms are producing very creditable retrievals. It is appropriate for a wide group of users to have access to the GPM retrievals. However, for researchers requiring only surface precipitation, these L2 swath products can appear to be very intimidating and they certainly do contain many more variables than the average researcher needs. Some researchers desire only surface retrievals stored in a simple easily accessible format. In response, PPS has begun to produce gridded text based products that contain just the most widely used variables for each instrument (surface rainfall rate, fraction liquid, fraction convective) in a single line for each grid box that contains one or more observations.This paper will describe the gridded data products that are being produced and provide an overview of their content. Currently two types of gridded products are being produced: (1) surface precipitation retrievals from the core satellite instruments GMI, DPR, and combined GMIDPR (2) surface precipitation retrievals for the partner constellation

  2. Quantifying the temperature-independent effect of stratospheric aerosol geoengineering on global-mean precipitation in a multi-model ensemble

    International Nuclear Information System (INIS)

    Ferraro, Angus J; Griffiths, Hannah G

    2016-01-01

    The reduction in global-mean precipitation when stratospheric aerosol geoengineering is used to counterbalance global warming from increasing carbon dioxide (CO 2 ) concentrations has been mainly attributed to the temperature-independent effect of CO 2 on atmospheric radiative cooling. We demonstrate here that stratospheric sulphate aerosol itself also acts to reduce global-mean precipitation independent of its effects on temperature. The temperature-independent effect of stratospheric aerosol geoenginering on global-mean precipitation is calculated by removing temperature-dependent effects from climate model simulations of the Geoengineering Model Intercomparison Project (GeoMIP). When sulphate aerosol is injected into the stratosphere at a rate of 5 Tg SO 2 per year the aerosol reduces global-mean precipitation by approximately 0.2 %, though multiple ensemble members are required to separate this effect from internal variability. For comparison, the precipitation reduction from the temperature-independent effect of increasing CO 2 concentrations under the RCP4.5 scenario of the future is approximately 0.5 %. The temperature-independent effect of stratospheric sulphate aerosol arises from the aerosol’s effect on tropospheric radiative cooling. Radiative transfer calculations show this is mainly due to increasing downward emission of infrared radiation by the aerosol, but there is also a contribution from the stratospheric warming the aerosol causes. Our results suggest climate model simulations of solar dimming can capture the main features of the global-mean precipitation response to stratospheric aerosol geoengineering. (letter)

  3. Performance of the Falling Snow Retrieval Algorithms for the Global Precipitation Measurement (GPM) Mission

    Science.gov (United States)

    Skofronick-Jackson, Gail; Munchak, Stephen J.; Ringerud, Sarah

    2016-01-01

    Retrievals of falling snow from space represent an important data set for understanding the Earth's atmospheric, hydrological, and energy cycles, especially during climate change. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new and retrievals are still undergoing development with challenges remaining). This work reports on the development and testing of retrieval algorithms for the Global Precipitation Measurement (GPM) mission Core Satellite, launched February 2014.

  4. GPM, GMI Level 3 Monthly GPROF Profiling V03

    Data.gov (United States)

    National Aeronautics and Space Administration — 3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are...

  5. Validation and Error Characterization for the Global Precipitation Measurement

    Science.gov (United States)

    Bidwell, Steven W.; Adams, W. J.; Everett, D. F.; Smith, E. A.; Yuter, S. E.

    2003-01-01

    The Global Precipitation Measurement (GPM) is an international effort to increase scientific knowledge on the global water cycle with specific goals of improving the understanding and the predictions of climate, weather, and hydrology. These goals will be achieved through several satellites specifically dedicated to GPM along with the integration of numerous meteorological satellite data streams from international and domestic partners. The GPM effort is led by the National Aeronautics and Space Administration (NASA) of the United States and the National Space Development Agency (NASDA) of Japan. In addition to the spaceborne assets, international and domestic partners will provide ground-based resources for validating the satellite observations and retrievals. This paper describes the validation effort of Global Precipitation Measurement to provide quantitative estimates on the errors of the GPM satellite retrievals. The GPM validation approach will build upon the research experience of the Tropical Rainfall Measuring Mission (TRMM) retrieval comparisons and its validation program. The GPM ground validation program will employ instrumentation, physical infrastructure, and research capabilities at Supersites located in important meteorological regimes of the globe. NASA will provide two Supersites, one in a tropical oceanic and the other in a mid-latitude continental regime. GPM international partners will provide Supersites for other important regimes. Those objectives or regimes not addressed by Supersites will be covered through focused field experiments. This paper describes the specific errors that GPM ground validation will address, quantify, and relate to the GPM satellite physical retrievals. GPM will attempt to identify the source of errors within retrievals including those of instrument calibration, retrieval physical assumptions, and algorithm applicability. With the identification of error sources, improvements will be made to the respective calibration

  6. Mapping global precipitation with satellite borne microwave radiometer and infrared radiometer using Kalman filter

    International Nuclear Information System (INIS)

    Noda, S.; Sasashige, K.; Katagami, D.; Ushio, T.; Kubota, T.; Okamoto, K.; Iida, Y.; Kida, S.; Shige, S.; Shimomura, S.; Aonashi, K.; Inoue, T.; Morimoto, T.; Kawasaki, Z.

    2007-01-01

    Estimates of precipitation at a high time and space resolution are required for many important applications. In this paper, a new global precipitation map with high spatial (0.1 degree) and temporal (1 hour) resolution using Kalman filter technique is presented and evaluated. Infrared radiometer data, which are available globally nearly everywhere and nearly all the time from geostationary orbit, are used with the several microwave radiometers aboard the LEO satellites. IR data is used as a means to move the precipitation estimates from microwave observation during periods when microwave data are not available at a given location. Moving vector is produced by computing correlations on successive images of IR data. When precipitation is moved, the Kalman filter is applied for improving the moving technique in this research. The new approach showed a better score than the technique without Kalman filter. The correlation coefficient was 0.1 better than without the Kalman filter about 6 hours after the last microwave overpasses, and the RMS error was improved about 0.1 mm/h with the Kalman filter technique. This approach is unique in that 1) the precipitation estimates from the microwave radiometer is mainly used, 2) the IR temperature in every hour is also used for the precipitation estimates based on the Kalman filter theory

  7. Global Precipitation Measurement (GPM) Mission Core Spacecraft Systems Engineering Challenges

    Science.gov (United States)

    Bundas, David J.; ONeill, Deborah; Field, Thomas; Meadows, Gary; Patterson, Peter

    2006-01-01

    The Global Precipitation Measurement (GPM) Mission is a collaboration between the National Aeronautics and Space Administration (NASA) and the Japanese Aerospace Exploration Agency (JAXA), and other US and international partners, with the goal of monitoring the diurnal and seasonal variations in precipitation over the surface of the earth. These measurements will be used to improve current climate models and weather forecasting, and enable improved storm and flood warnings. This paper gives an overview of the mission architecture and addresses the status of some key trade studies, including the geolocation budgeting, design considerations for spacecraft charging, and design issues related to the mitigation of orbital debris.

  8. Ground-Based Global Positioning System (GPS) Meteorology Integrated Precipitable Water Vapor (IPW)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Ground-Based Global Positioning System (GPS) Meteorology Integrated Precipitable Water Vapor (IPW) data set measures atmospheric water vapor using ground-based...

  9. Global Analysis of Ecosystem Evapotranspiration Response to Precipitation Deficits

    Science.gov (United States)

    He, Bin; Wang, Haiyan; Guo, Lanlan; Liu, Junjie

    2017-12-01

    Changes in ecosystem evapotranspiration (ET) due to precipitation deficits (PD) can relieve or aggravate soil moisture shortages, thus impacting drought severity. Previous findings have conflicted with regard to response of ET to PD. The present study relies on a global land ET synthesis data set (ETsyn) and observations from eddy-covariance towers (ETobs) to thoroughly examine the sensitivity of ET to PD, which is represented by the standardized precipitation index. There was a contrast in the response to PD between arid and humid ecosystems. ETsyn of arid ecosystems was typically reduced promptly in response to a reduction of precipitation, while ETsyn in humid ecosystems experienced a two-staged change: First, there was an enhancement, and then a reduction associated with persisting PD. Compared with ETsyn, ETobs suggests the occurrence of a more significant ET transition in response to PD. In arid ecosystems, ET typically negatively correlated with low PD, but this was limited by a large PD. Findings from this study are crucial for understanding the role of ET in drought evolution.

  10. Rand Corporation Mean Monthly Global Snow Depth

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — All available monthly snow depth climatologies were integrated by the Rand Corporation, in the early 1980s, into one global (excluding Africa and South America)...

  11. Assessment of global precipitation measurement satellite products over Saudi Arabia

    Science.gov (United States)

    Mahmoud, Mohammed T.; Al-Zahrani, Muhammad A.; Sharif, Hatim O.

    2018-04-01

    Most hydrological analysis and modeling studies require reliable and accurate precipitation data for successful simulations. However, precipitation measurements should be more representative of the true precipitation distribution. Many approaches and techniques are used to collect precipitation data. Recently, hydrometeorological and climatological applications of satellite precipitation products have experienced a significant improvement with the emergence of the latest satellite products, namely, the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) products, which can be utilized to estimate and analyze precipitation data. This study focuses on the validation of the IMERG early, late and final run rainfall products using ground-based rain gauge observations throughout Saudi Arabia for the period from October 2015 to April 2016. The accuracy of each IMERG product is assessed using six statistical performance measures to conduct three main evaluations, namely, regional, event-based and station-based evaluations. The results indicate that the early run product performed well in the middle and eastern parts as well as some of the western parts of the country; meanwhile, the satellite estimates for the other parts fluctuated between an overestimation and an underestimation. The late run product showed an improved accuracy over the southern and western parts; however, over the northern and middle parts, it showed relatively high errors. The final run product revealed significantly improved precipitation estimations and successfully obtained higher accuracies over most parts of the country. This study provides an early assessment of the performance of the GPM satellite products over the Middle East. The study findings can be used as a beneficial reference for the future development of the IMERG algorithms.

  12. Using GRACE to constrain precipitation amount over cold mountainous basins

    Science.gov (United States)

    Behrangi, Ali; Gardner, Alex S.; Reager, John T.; Fisher, Joshua B.

    2017-01-01

    Despite the importance for hydrology and climate-change studies, current quantitative knowledge on the amount and distribution of precipitation in mountainous and high-elevation regions is limited due to instrumental and retrieval shortcomings. Here by focusing on two large endorheic basins in High Mountain Asia, we show that satellite gravimetry (Gravity Recovery and Climate Experiment (GRACE)) can be used to provide an independent estimate of monthly accumulated precipitation using mass balance equation. Results showed that the GRACE-based precipitation estimate has the highest agreement with most of the commonly used precipitation products in summer, but it deviates from them in cold months, when the other products are expected to have larger errors. It was found that most of the products capture about or less than 50% of the total precipitation estimated using GRACE in winter. Overall, Global Precipitation Climatology Project (GPCP) showed better agreement with GRACE estimate than other products. Yet on average GRACE showed 30% more annual precipitation than GPCP in the study basins. In basins of appropriate size with an absence of dense ground measurements, as is a typical case in cold mountainous regions, we find GRACE can be a viable alternative to constrain monthly and seasonal precipitation estimates from other remotely sensed precipitation products that show large bias.

  13. Global monsoon precipitation responses to large volcanic eruptions

    Science.gov (United States)

    Liu, Fei; Chai, Jing; Wang, Bin; Liu, Jian; Zhang, Xiao; Wang, Zhiyuan

    2016-01-01

    Climate variation of global monsoon (GM) precipitation involves both internal feedback and external forcing. Here, we focus on strong volcanic forcing since large eruptions are known to be a dominant mechanism in natural climate change. It is not known whether large volcanoes erupted at different latitudes have distinctive effects on the monsoon in the Northern Hemisphere (NH) and the Southern Hemisphere (SH). We address this issue using a 1500-year volcanic sensitivity simulation by the Community Earth System Model version 1.0 (CESM1). Volcanoes are classified into three types based on their meridional aerosol distributions: NH volcanoes, SH volcanoes and equatorial volcanoes. Using the model simulation, we discover that the GM precipitation in one hemisphere is enhanced significantly by the remote volcanic forcing occurring in the other hemisphere. This remote volcanic forcing-induced intensification is mainly through circulation change rather than moisture content change. In addition, the NH volcanic eruptions are more efficient in reducing the NH monsoon precipitation than the equatorial ones, and so do the SH eruptions in weakening the SH monsoon, because the equatorial eruptions, despite reducing moisture content, have weaker effects in weakening the off-equatorial monsoon circulation than the subtropical-extratropical volcanoes do. PMID:27063141

  14. Monthly, global emissions of carbon dioxide from fossil fuel consumption

    DEFF Research Database (Denmark)

    Andres, R.J.; Gregg, Jay Sterling; Losey, L.

    2011-01-01

    This paper examines available data, develops a strategy and presents a monthly, global time series of fossil-fuel carbon dioxide emissions for the years 1950–2006. This monthly time series was constructed from detailed study of monthly data from the 21 countries that account for approximately 80......% of global total emissions. These data were then used in a Monte Carlo approach to proxy for all remaining countries. The proportional-proxy methodology estimates by fuel group the fraction of annual emissions emitted in each country and month. Emissions from solid, liquid and gas fuels are explicitly...

  15. An evaluation of temperature and precipitation from global and regional climate models over Scandinavia

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2012-07-01

    Precipitation and temperature from global (GCMs) and regional (RCMs) climate models are compared with reanalysis and observations over Scandinavia. Also projections for the next 50-100 years are considered. The climate development is visualised as moving averages (1920-2100). Box plots are used to illuminate how well GCM runs capture the observed seasonal cycle. Maps show the seasonal difference between results from control runs (RCM) and observations (E-OBS dataset) for the reference period 1981-2000. Plots illustrate the RCM-representation of seasonal temperature and precipitations cycle for five locations in Norway and Sweden: Oslo, Bergen, Trondheim, Tromsoe and Oestersund. The results show rather large differences between control runs and observations, demonstrating the need for bias correction of results from climate models. To get an indicator of which GC M-RCM-combination give the best representation of present climate over Scandinavia, a model ranking is provided. The performance measure used is the root-mean-square deviation of mean monthly and seasonal values. The data is compared both in an area-weighted spatial average of the whole domain as well as for the selected locations. The results indicate that the regional models RACMO2 and RCA show the smallest deviations from observed climate. Among the top ranking GCM-RCM combinations, most were driven by the global model ECHAM5 and some by a version of HadCM3. These two GCMs are also present among the worst performing GCM-RCM combinations indicating that selection of RCMs is crucial. (Author)

  16. What controls deuterium excess in global precipitation?

    Directory of Open Access Journals (Sweden)

    S. Pfahl

    2014-04-01

    Full Text Available The deuterium excess (d of precipitation is widely used in the reconstruction of past climatic changes from ice cores. However, its most common interpretation as moisture source temperature cannot directly be inferred from present-day water isotope observations. Here, we use a new empirical relation between d and near-surface relative humidity (RH together with reanalysis data to globally predict d of surface evaporation from the ocean. The very good quantitative agreement of the predicted hemispherically averaged seasonal cycle with observed d in precipitation indicates that moisture source relative humidity, and not sea surface temperature, is the main driver of d variability on seasonal timescales. Furthermore, we review arguments for an interpretation of long-term palaeoclimatic d changes in terms of moisture source temperature, and we conclude that there remains no sufficient evidence that would justify to neglect the influence of RH on such palaeoclimatic d variations. Hence, we suggest that either the interpretation of d variations in palaeorecords should be adapted to reflect climatic influences on RH during evaporation, in particular atmospheric circulation changes, or new arguments for an interpretation in terms of moisture source temperature will have to be provided based on future research.

  17. The Advantage of Using International Multimodel Ensemble for Seasonal Precipitation Forecast over Israel

    Directory of Open Access Journals (Sweden)

    Amir Givati

    2017-01-01

    Full Text Available This study analyzes the results of monthly and seasonal precipitation forecasting from seven different global climate forecast models for major basins in Israel within October–April 1982–2010. The six National Multimodel Ensemble (NMME models and the ECMWF seasonal model were used to calculate an International Multimodel Ensemble (IMME. The study presents the performance of both monthly and seasonal predictions of precipitation accumulated over three months, with respect to different lead times for the ensemble mean values, one per individual model. Additionally, we analyzed the performance of different combinations of models. We present verification of seasonal forecasting using real forecasts, focusing on a small domain characterized by complex terrain, high annual precipitation variability, and a sharp precipitation gradient from west to east as well as from south to north. The results in this study show that, in general, the monthly analysis does not provide very accurate results, even when using the IMME for one-month lead time. We found that the IMME outperformed any single model prediction. Our analysis indicates that the optimal combinations with the high correlation values contain at least three models. Moreover, prediction with larger number of models in the ensemble produces more robust predictions. The results obtained in this study highlight the advantages of using an ensemble of global models over single models for small domain.

  18. Climate Prediction Center (CPC) NCEP-Global Forecast System (GFS) Precipitation Forecast Product

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Forecast System (GFS) forecast precipitation data at 37.5km resolution is created at the NOAA Climate Prediction Center for the purpose of near real-time...

  19. MSWEP : 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data

    NARCIS (Netherlands)

    Beck, Hylke E.; Van Dijk, Albert I.J.M.; Levizzani, Vincenzo; Schellekens, Jaap; Miralles, Diego G.; Martens, Brecht; De Roo, Ad

    2017-01-01

    Current global precipitation (P) datasets do not take full advantage of the complementary nature of satellite and reanalysis data. Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) version 1.1, a global P dataset for the period 1979-2015 with a 3-hourly temporal and 0.25° spatial

  20. Estimation of monthly-mean daily global solar radiation based on MODIS and TRMM products

    International Nuclear Information System (INIS)

    Qin, Jun; Chen, Zhuoqi; Yang, Kun; Liang, Shunlin; Tang, Wenjun

    2011-01-01

    Global solar radiation (GSR) is required in a large number of fields. Many parameterization schemes are developed to estimate it using routinely measured meteorological variables, since GSR is directly measured at a limited number of stations. Even so, meteorological stations are sparse, especially, in remote areas. Satellite signals (radiance at the top of atmosphere in most cases) can be used to estimate continuous GSR in space. However, many existing remote sensing products have a relatively coarse spatial resolution and these inversion algorithms are too complicated to be mastered by experts in other research fields. In this study, the artificial neural network (ANN) is utilized to build the mathematical relationship between measured monthly-mean daily GSR and several high-level remote sensing products available for the public, including Moderate Resolution Imaging Spectroradiometer (MODIS) monthly averaged land surface temperature (LST), the number of days in which the LST retrieval is performed in 1 month, MODIS enhanced vegetation index, Tropical Rainfall Measuring Mission satellite (TRMM) monthly precipitation. After training, GSR estimates from this ANN are verified against ground measurements at 12 radiation stations. Then, comparisons are performed among three GSR estimates, including the one presented in this study, a surface data-based estimate, and a remote sensing product by Japan Aerospace Exploration Agency (JAXA). Validation results indicate that the ANN-based method presented in this study can estimate monthly-mean daily GSR at a spatial resolution of about 5 km with high accuracy.

  1. Verification of the Global Precipitation Measurement (GPM) Satellite by the Olympic Mountains Experiment (OLYMPEX)

    Science.gov (United States)

    McMurdie, L. A.; Houze, R.

    2017-12-01

    Measurements of global precipitation are critical for monitoring Earth's water resources and hydrological processes, including flooding and snowpack accumulation. As such, the Global Precipitation Measurement (GPM) Mission `Core' satellite detects precipitation ranging from light snow to heavy downpours in a wide range locations including remote mountainous regions. The Olympic Mountains Experiment (OLYMPEX) during the 2015-2016 fall-winter season in the mountainous Olympic Peninsula of Washington State provide physical and hydrological validation for GPM precipitation algorithms and insight into the modification of midlatitude storms by passage over mountains. The instrumentation included ground-based dual-polarization Doppler radars on the windward and leeward sides of the Olympic Mountains, surface stations that measured precipitation rates, particle size distributions and fall velocities at various altitudes, research aircraft equipped with cloud microphysics probes, radars, lidar, and passive radiometers, supplemental rawinsondes and dropsondes, and autonomous recording cameras that monitored snowpack accumulation. Results based on dropsize distributions (DSDs) and cross-sections of radar reflectivity over the ocean and windward slopes have revealed important considerations for GPM algorithm development. During periods of great precipitation accumulation and enhancement by the mountains on windward slopes, both warm rain and ice-phase processes are present, implying that it is important for GPM retrievals be sensitive to both types of precipitation mechanisms and to represent accurately the concentration of precipitation at the lowest possible altitudes. OLYMPEX data revealed that a given rain rate could be associated with a variety of DSDs, which presents a challenge for GPM precipitation retrievals in extratropical cyclones passing over mountains. Some of the DSD regimes measured during OLYMPEX stratiform periods have the same characteristics found in prior

  2. Climate Prediction Center (CPC) Three Month Probabilistic Precipitation Outlook for the Contiguous United States and Alaska

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center (CPC) issues a series of thirteen probabilistic three-month precipitation outlooks for the United States. CPC issues the thirteen...

  3. The Day-1 GPM Combined Precipitation Algorithm: IMERG

    Science.gov (United States)

    Huffman, G. J.; Bolvin, D. T.; Braithwaite, D.; Hsu, K.; Joyce, R.; Kidd, C.; Sorooshian, S.; Xie, P.

    2012-12-01

    The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) algorithm will provide the at-launch combined-sensor precipitation dataset being produced by the U.S. GPM Science Team. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in three current U.S. algorithms: - the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; - the CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following storm motion; and - the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS), which provides a neural-network-based scheme for generating microwave-calibrated precipitation estimates from geosynchronous infrared brightness temperatures, and filters out some non-raining cold clouds. The goal is to provide a long-term, fine-scale record of global precipitation from the entire constellation of precipitation-relevant satellite sensors, with input from surface precipitation gauges. The record will begin January 1998 at the start of the Tropical Rainfall Measuring Mission (TRMM) and extend as GPM records additional data. Although homogeneity is considered desirable, the use of diverse and evolving data sources works against the strict long-term homogeneity that characterizes a Climate Data Record (CDR). This talk will briefly review the design requirements for IMERG, including multiple runs at different latencies (most likely around 4 hours, 12 hours, and 2 months after observation time), various intermediate data fields as part of the IMERG data file, and the plans to bring up IMERG with calibration by TRMM initially, transitioning to GPM when its individual-sensor precipitation algorithms are fully functional

  4. Precipitation from Space: Advancing Earth System Science

    Science.gov (United States)

    Kucera, Paul A.; Ebert, Elizabeth E.; Turk, F. Joseph; Levizzani, Vicenzo; Kirschbaum, Dalia; Tapiador, Francisco J.; Loew, Alexander; Borsche, M.

    2012-01-01

    Of the three primary sources of spatially contiguous precipitation observations (surface networks, ground-based radar, and satellite-based radar/radiometers), only the last is a viable source over ocean and much of the Earth's land. As recently as 15 years ago, users needing quantitative detail of precipitation on anything under a monthly time scale relied upon products derived from geostationary satellite thermal infrared (IR) indices. The Special Sensor Microwave Imager (SSMI) passive microwave (PMW) imagers originated in 1987 and continue today with the SSMI sounder (SSMIS) sensor. The fortunate longevity of the joint National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) Tropical Rainfall Measuring Mission (TRMM) is providing the environmental science community a nearly unbroken data record (as of April 2012, over 14 years) of tropical and sub-tropical precipitation processes. TRMM was originally conceived in the mid-1980s as a climate mission with relatively modest goals, including monthly averaged precipitation. TRMM data were quickly exploited for model data assimilation and, beginning in 1999 with the availability of near real time data, for tropical cyclone warnings. To overcome the intermittently spaced revisit from these and other low Earth-orbiting satellites, many methods to merge PMW-based precipitation data and geostationary satellite observations have been developed, such as the TRMM Multisatellite Precipitation Product and the Climate Prediction Center (CPC) morphing method (CMORPH. The purpose of this article is not to provide a survey or assessment of these and other satellite-based precipitation datasets, which are well summarized in several recent articles. Rather, the intent is to demonstrate how the availability and continuity of satellite-based precipitation data records is transforming the ways that scientific and societal issues related to precipitation are addressed, in ways that would not be

  5. A Global Model for Circumgalactic and Cluster-core Precipitation

    Science.gov (United States)

    Voit, G. Mark; Meece, Greg; Li, Yuan; O'Shea, Brian W.; Bryan, Greg L.; Donahue, Megan

    2017-08-01

    We provide an analytic framework for interpreting observations of multiphase circumgalactic gas that is heavily informed by recent numerical simulations of thermal instability and precipitation in cool-core galaxy clusters. We start by considering the local conditions required for the formation of multiphase gas via two different modes: (1) uplift of ambient gas by galactic outflows, and (2) condensation in a stratified stationary medium in which thermal balance is explicitly maintained. Analytic exploration of these two modes provides insights into the relationships between the local ratio of the cooling and freefall timescales (I.e., {t}{cool}/{t}{ff}), the large-scale gradient of specific entropy, and the development of precipitation and multiphase media in circumgalactic gas. We then use these analytic findings to interpret recent simulations of circumgalactic gas in which global thermal balance is maintained. We show that long-lasting configurations of gas with 5≲ \\min ({t}{cool}/{t}{ff})≲ 20 and radial entropy profiles similar to observations of cool cores in galaxy clusters are a natural outcome of precipitation-regulated feedback. We conclude with some observational predictions that follow from these models. This work focuses primarily on precipitation and AGN feedback in galaxy-cluster cores, because that is where the observations of multiphase gas around galaxies are most complete. However, many of the physical principles that govern condensation in those environments apply to circumgalactic gas around galaxies of all masses.

  6. GPM, TRMM, GMI,TMI Level 3 Monthly GPROF Profiling V03

    Data.gov (United States)

    National Aeronautics and Space Administration — 3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are...

  7. The global precipitation response to volcanic eruptions in the CMIP5 models

    International Nuclear Information System (INIS)

    Iles, Carley E; Hegerl, Gabriele C

    2014-01-01

    We examine the precipitation response to volcanic eruptions in the Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations compared to three observational datasets, including one with ocean coverage. Global precipitation decreases significantly following eruptions in CMIP5 models, with the largest decrease in wet tropical regions. This also occurs in observational land data, and ocean data in the boreal cold season. Monsoon rainfall decreases following eruptions in both models and observations. In response to individual eruptions, the ITCZ shifts away from the hemisphere with the greater concentration of aerosols in CMIP5. Models undergo a longer-lasting ocean precipitation response than over land, but the response in the short satellite record is too noisy to confirm this. We detect the influence of volcanism on precipitation in all three datasets in the cold season, although the models underestimate the size of the response. In the warm season the volcanic influence is only marginally detectable. (letter)

  8. Global Precipitation Measurement. Report 1; Summary of the First GPM Partners Planning Workshop

    Science.gov (United States)

    Shepherd, J. Marshall; Mehta, Amita; Smith, Eric A. (Editor); Adams, W. James (Editor)

    2002-01-01

    This report provides a synopsis of the proceedings of the First Global Precipitation Measurement (GPM) Partners Planning Workshop held at the University of Maryland, College Park, from May 16 to 18, 2001. GPM consists of a multi-member global satellite constellation (i.e., an international set of satellite missions) and the accompanying scientific research program, with the main goal of providing frequent, accurate, and globally distributed precipitation measurements essential in understanding several fundamental issues associated with the global water and energy cycle (GWEC). The exchange of scientific and technical information at this and subsequent GPM workshops between representatives from around the world represents a key step in the formulation phase of GPM mission development. The U.S. National Aeronautics and Space Agency (NASA), the National Space Development Agency of Japan (NASDA), and other interested agencies from nations around the world seek to observe, understand, and model the Earth system to learn how it is changing and what consequences these changes have on life, particularly as they pertain to hydrological processes and the availability of fresh water resources. GWEN processes are central to a broader understanding of the Earth system.

  9. Statistical downscaling based on dynamically downscaled predictors: Application to monthly precipitation in Sweden

    Science.gov (United States)

    Hellström, Cecilia; Chen, Deliang

    2003-11-01

    A prerequisite of a successful statistical downscaling is that large-scale predictors simulated by the General Circulation Model (GCM) must be realistic. It is assumed here that features smaller than the GCM resolution are important in determining the realism of the large-scale predictors. It is tested whether a three-step method can improve conventional one-step statistical downscaling. The method uses predictors that are upscaled from a dynamical downscaling instead of predictors taken directly from a GCM simulation. The method is applied to downscaling of monthly precipitation in Sweden. The statistical model used is a multiple regression model that uses indices of large-scale atmospheric circulation and 850-hPa specific humidity as predictors. Data from two GCMs (HadCM2 and ECHAM4) and two RCM experiments of the Rossby Centre model (RCA1) driven by the GCMs are used. It is found that upscaled RCA1 predictors capture the seasonal cycle better than those from the GCMs, and hence increase the reliability of the downscaled precipitation. However, there are only slight improvements in the simulation of the seasonal cycle of downscaled precipitation. Due to the cost of the method and the limited improvements in the downscaling results, the three-step method is not justified to replace the one-step method for downscaling of Swedish precipitation.

  10. On the effects of wildfires on precipitation in Southern Africa

    Science.gov (United States)

    De Sales, Fernando; Okin, Gregory S.; Xue, Yongkang; Dintwe, Kebonye

    2018-03-01

    This study investigates the impact of wildfire on the climate of Southern Africa. Moderate resolution imaging spectroradiometer derived burned area fraction data was implemented in a set of simulations to assess primarily the role of wildfire-induced surface changes on monthly precipitation. Two post-fire scenarios are examined namely non-recovering and recovering vegetation scenarios. In the former, burned vegetation fraction remains burned until the end of the simulations, whereas in the latter it is allowed to regrow following a recovery period. Control simulations revealed that the model can dependably capture the monthly precipitation and surface temperature averages in Southern Africa thus providing a reasonable basis against which to assess the impacts of wildfire. In general, both wildfire scenarios have a negative impact on springtime precipitation. September and October were the only months with statistically significant precipitation changes. During these months, precipitation in the region decreases by approximately 13 and 9% in the non-recovering vegetation scenario, and by about 10 and 6% in the recovering vegetation wildfire scenario, respectively. The primary cause of precipitation deficit is the decrease in evapotranspiration resulting from a reduction in surface net radiation. Areas impacted by the precipitation reduction includes the Luanda, Kinshasa, and Brazzaville metropolitan areas, The Angolan Highlands, which are the source of the Okavango Rive, and the Okavango Delta region. This study suggests that a probable intensification in wildfire frequency and extent resulting from projected population increase and global warming in Southern Africa could potentially exacerbate the impacts of wildfires in the region's seasonal precipitation.

  11. Global Summary of the Month, version 1.0

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global summaries data set contains a monthly (GSOM) resolution of meteorological elements (max temp, snow, etc) from 1763 to present with updates weekly. The...

  12. Global auroral conductance distribution due to electron and proton precipitation from IMAGE-FUV observations

    Directory of Open Access Journals (Sweden)

    V. Coumans

    2004-04-01

    Full Text Available The Far Ultraviolet (FUV imaging system on board the IMAGE satellite provides a global view of the north auroral region in three spectral channels, including the SI12 camera sensitive to Doppler shifted Lyman-α emission. FUV images are used to produce instantaneous maps of electron mean energy and energy fluxes for precipitated protons and electrons. We describe a method to calculate ionospheric Hall and Pedersen conductivities induced by auroral proton and electron ionization based on a model of interaction of auroral particles with the atmosphere. Different assumptions on the energy spectral distribution for electrons and protons are compared. Global maps of ionospheric conductances due to instantaneous observation of precipitating protons are calculated. The contribution of auroral protons in the total conductance induced by both types of auroral particles is also evaluated and the importance of proton precipitation is evaluated. This method is well adapted to analyze the time evolution of ionospheric conductances due to precipitating particles over the auroral region or in particular sectors. Results are illustrated with conductance maps of the north polar region obtained during four periods with different activity levels. It is found that the proton contribution to conductance is relatively higher during quiet periods than during substorms. The proton contribution is higher in the period before the onset and strongly decreases during the expansion phase of substorms. During a substorm which occurred on 28 April 2001, a region of strong proton precipitation is observed with SI12 around 14:00MLT at ~75° MLAT. Calculation of conductances in this sector shows that neglecting the protons contribution would produce a large error. We discuss possible effects of the proton precipitation on electron precipitation in auroral arcs. The increase in the ionospheric conductivity, induced by a former proton precipitation can reduce the potential drop

  13. Global auroral conductance distribution due to electron and proton precipitation from IMAGE-FUV observations

    Directory of Open Access Journals (Sweden)

    V. Coumans

    2004-04-01

    Full Text Available The Far Ultraviolet (FUV imaging system on board the IMAGE satellite provides a global view of the north auroral region in three spectral channels, including the SI12 camera sensitive to Doppler shifted Lyman-α emission. FUV images are used to produce instantaneous maps of electron mean energy and energy fluxes for precipitated protons and electrons. We describe a method to calculate ionospheric Hall and Pedersen conductivities induced by auroral proton and electron ionization based on a model of interaction of auroral particles with the atmosphere. Different assumptions on the energy spectral distribution for electrons and protons are compared. Global maps of ionospheric conductances due to instantaneous observation of precipitating protons are calculated. The contribution of auroral protons in the total conductance induced by both types of auroral particles is also evaluated and the importance of proton precipitation is evaluated. This method is well adapted to analyze the time evolution of ionospheric conductances due to precipitating particles over the auroral region or in particular sectors. Results are illustrated with conductance maps of the north polar region obtained during four periods with different activity levels. It is found that the proton contribution to conductance is relatively higher during quiet periods than during substorms. The proton contribution is higher in the period before the onset and strongly decreases during the expansion phase of substorms. During a substorm which occurred on 28 April 2001, a region of strong proton precipitation is observed with SI12 around 14:00MLT at ~75° MLAT. Calculation of conductances in this sector shows that neglecting the protons contribution would produce a large error. We discuss possible effects of the proton precipitation on electron precipitation in auroral arcs. The increase in the ionospheric conductivity, induced by a former proton precipitation can reduce the potential drop

  14. An ensemble-based dynamic Bayesian averaging approach for discharge simulations using multiple global precipitation products and hydrological models

    Science.gov (United States)

    Qi, Wei; Liu, Junguo; Yang, Hong; Sweetapple, Chris

    2018-03-01

    Global precipitation products are very important datasets in flow simulations, especially in poorly gauged regions. Uncertainties resulting from precipitation products, hydrological models and their combinations vary with time and data magnitude, and undermine their application to flow simulations. However, previous studies have not quantified these uncertainties individually and explicitly. This study developed an ensemble-based dynamic Bayesian averaging approach (e-Bay) for deterministic discharge simulations using multiple global precipitation products and hydrological models. In this approach, the joint probability of precipitation products and hydrological models being correct is quantified based on uncertainties in maximum and mean estimation, posterior probability is quantified as functions of the magnitude and timing of discharges, and the law of total probability is implemented to calculate expected discharges. Six global fine-resolution precipitation products and two hydrological models of different complexities are included in an illustrative application. e-Bay can effectively quantify uncertainties and therefore generate better deterministic discharges than traditional approaches (weighted average methods with equal and varying weights and maximum likelihood approach). The mean Nash-Sutcliffe Efficiency values of e-Bay are up to 0.97 and 0.85 in training and validation periods respectively, which are at least 0.06 and 0.13 higher than traditional approaches. In addition, with increased training data, assessment criteria values of e-Bay show smaller fluctuations than traditional approaches and its performance becomes outstanding. The proposed e-Bay approach bridges the gap between global precipitation products and their pragmatic applications to discharge simulations, and is beneficial to water resources management in ungauged or poorly gauged regions across the world.

  15. High-resolution Monthly Satellite Precipitation Product over the Conterminous United States

    Science.gov (United States)

    Hashemi, H.; Fayne, J.; Knight, R. J.; Lakshmi, V.

    2017-12-01

    We present a data set that enhanced the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) monthly product 3B43 in its accuracy and spatial resolution. For this, we developed a correction function to improve the accuracy of TRMM 3B43, spatial resolution of 25 km, by estimating and removing the bias in the satellite data using a ground-based precipitation data set. We observed a strong relationship between the bias and land surface elevation; TRMM 3B43 tends to underestimate the ground-based product at elevations above 1500 m above mean sea level (m.amsl) over the conterminous United States. A relationship was developed between satellite bias and elevation. We then resampled TRMM 3B43 to the Digital Elevation Model (DEM) data set at a spatial resolution of 30 arc second ( 1 km on the ground). The produced high-resolution satellite-based data set was corrected using the developed correction function based on the bias-elevation relationship. Assuming that each rain gauge represents an area of 1 km2, we verified our product against 9,200 rain gauges across the conterminous United States. The new product was compared with the gauges, which have 50, 60, 70, 80, 90, and 100% temporal coverage within the TRMM period of 1998 to 2015. Comparisons between the high-resolution corrected satellite-based data and gauges showed an excellent agreement. The new product captured more detail in the changes in precipitation over the mountainous region than the original TRMM 3B43.

  16. Understanding the Global Water and Energy Cycle Through Assimilation of Precipitation-Related Observations: Lessons from TRMM and Prospects for GPM

    Science.gov (United States)

    Hou, Arthur; Zhang, Sara; daSilva, Arlindo; Li, Frank; Atlas, Robert (Technical Monitor)

    2002-01-01

    Understanding the Earth's climate and how it responds to climate perturbations relies on what we know about how atmospheric moisture, clouds, latent heating, and the large-scale circulation vary with changing climatic conditions. The physical process that links these key climate elements is precipitation. Improving the fidelity of precipitation-related fields in global analyses is essential for gaining a better understanding of the global water and energy cycle. In recent years, research and operational use of precipitation observations derived from microwave sensors such as the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and Special Sensor Microwave/Imager (SSM/I) have shown the tremendous potential of using these data to improve global modeling, data assimilation, and numerical weather prediction. We will give an overview of the benefits of assimilating TRMM and SSM/I rain rates and discuss developmental strategies for using space-based rainfall and rainfall-related observations to improve forecast models and climate datasets in preparation for the proposed multi-national Global Precipitation Mission (GPM).

  17. GPM, METOP-A, GMI,MHS Level 3 Monthly GPROF Profiling V03

    Data.gov (United States)

    National Aeronautics and Space Administration — 3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are...

  18. GPM, METOP-B, GMI,MHS Level 3 Monthly GPROF Profiling V03

    Data.gov (United States)

    National Aeronautics and Space Administration — 3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are...

  19. GPM, F16,GMI,SSMI Level 3 Monthly GPROF Profiling V03

    Data.gov (United States)

    National Aeronautics and Space Administration — 3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are...

  20. GPM, F17,GMI,SSMI Level 3 Monthly GPROF Profiling V03

    Data.gov (United States)

    National Aeronautics and Space Administration — 3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are...

  1. GPM, F18,GMI,SSMI Level 3 Monthly GPROF Profiling V03

    Data.gov (United States)

    National Aeronautics and Space Administration — 3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are...

  2. GPM, NOAA18, GMI,MHS Level 3 Monthly GPROF Profiling V03

    Data.gov (United States)

    National Aeronautics and Space Administration — 3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are...

  3. GPM, TRMM, GMI,TMI Level 3 Monthly GPROF Profiling VV03B

    Data.gov (United States)

    National Aeronautics and Space Administration — 3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are...

  4. Air pollution or global warming: Attribution of extreme precipitation changes in eastern China—Comments on "Trends of extreme precipitation in Eastern China and their possible causes"

    Science.gov (United States)

    Wang, Yuan

    2015-10-01

    The recent study "Trends of Extreme Precipitation in Eastern China and Their Possible Causes" attributed the observed decrease/increase of light/heavy precipitation in eastern China to global warming rather than the regional aerosol effects. However, there exist compelling evidence from previous long-term observations and numerical modeling studies, suggesting that anthropogenic pollution is closely linked to the recent changes in precipitation intensity because of considerably modulated cloud physical properties by aerosols in eastern China. Clearly, a quantitative assessment of the aerosol and greenhouse effects on the regional scale is required to identify the primary cause for the extreme precipitation changes.

  5. Correlation and SVD Analysis of Anomalous Spring Precipitation in Northwest China and Sea Surface Temperature in Key Region in Recent 50 Years

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    [Objective] The aim was to study the relationship between spring precipitation anomaly in Northwest China and sea surface temperature anomaly (SSTA) in Key region in recent 50 years. [Method] Based on monthly average precipitation in Northwest China and global monthly sea surface temperature (SST) grid data, the effects of SSTA in equatorial central and eastern Pacific on spring precipitation in Northwest China were discussed by means of correlation and SVD analysis. [Result] For spring precipitation in Nor...

  6. Future changes in extreme precipitation in the Rhine basin based on global and regional climate model simulations

    NARCIS (Netherlands)

    Pelt, van S.C.; Beersma, J.J.; Buishand, T.A.; Hurk, van den B.J.J.M.; Kabat, P.

    2012-01-01

    Probability estimates of the future change of extreme precipitation events are usually based on a limited number of available global climate model (GCM) or regional climate model (RCM) simulations. Since floods are related to heavy precipitation events, this restricts the assessment of flood risks.

  7. Climate dynamics: a network-based approach for the analysis of global precipitation.

    Science.gov (United States)

    Scarsoglio, Stefania; Laio, Francesco; Ridolfi, Luca

    2013-01-01

    Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can

  8. Climate dynamics: a network-based approach for the analysis of global precipitation.

    Directory of Open Access Journals (Sweden)

    Stefania Scarsoglio

    Full Text Available Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010. The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that

  9. Exploring the effects of climatic variables on monthly precipitation variation using a continuous wavelet-based multiscale entropy approach.

    Science.gov (United States)

    Roushangar, Kiyoumars; Alizadeh, Farhad; Adamowski, Jan

    2018-08-01

    Understanding precipitation on a regional basis is an important component of water resources planning and management. The present study outlines a methodology based on continuous wavelet transform (CWT) and multiscale entropy (CWME), combined with self-organizing map (SOM) and k-means clustering techniques, to measure and analyze the complexity of precipitation. Historical monthly precipitation data from 1960 to 2010 at 31 rain gauges across Iran were preprocessed by CWT. The multi-resolution CWT approach segregated the major features of the original precipitation series by unfolding the structure of the time series which was often ambiguous. The entropy concept was then applied to components obtained from CWT to measure dispersion, uncertainty, disorder, and diversification of subcomponents. Based on different validity indices, k-means clustering captured homogenous areas more accurately, and additional analysis was performed based on the outcome of this approach. The 31 rain gauges in this study were clustered into 6 groups, each one having a unique CWME pattern across different time scales. The results of clustering showed that hydrologic similarity (multiscale variation of precipitation) was not based on geographic contiguity. According to the pattern of entropy across the scales, each cluster was assigned an entropy signature that provided an estimation of the entropy pattern of precipitation data in each cluster. Based on the pattern of mean CWME for each cluster, a characteristic signature was assigned, which provided an estimation of the CWME of a cluster across scales of 1-2, 3-8, and 9-13 months relative to other stations. The validity of the homogeneous clusters demonstrated the usefulness of the proposed approach to regionalize precipitation. Further analysis based on wavelet coherence (WTC) was performed by selecting central rain gauges in each cluster and analyzing against temperature, wind, Multivariate ENSO index (MEI), and East Atlantic (EA) and

  10. GPM, F17,GMI,SSMI Level 3 Monthly GPROF Profiling VV03B

    Data.gov (United States)

    National Aeronautics and Space Administration — 3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are...

  11. GPM, NOAA19, GMI,MHS Level 3 Monthly GPROF Profiling VV03B

    Data.gov (United States)

    National Aeronautics and Space Administration — 3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are...

  12. Variability and trends in global drought

    Science.gov (United States)

    McCabe, Gregory J.; Wolock, David M.

    2015-01-01

    Monthly precipitation (P) and potential evapotranspiration (PET) from the CRUTS3.1 data set are used to compute monthly P minus PET (PMPE) for the land areas of the globe. The percent of the global land area with annual sums of PMPE less than zero are used as an index of global drought (%drought) for 1901 through 2009. Results indicate that for the past century %drought has not changed, even though global PET and temperature (T) have increased. Although annual global PET and T have increased, annual global P also has increased and has mitigated the effects of increased PET on %drought.

  13. Consultants' meeting on operational aspects of the global network ''isotopes in precipitation''

    International Nuclear Information System (INIS)

    1995-01-01

    The Consultant's meeting on ''Operational Aspects of the Global Network - Isotopes in Precipitation'' was organized by the International Atomic Energy Agency (IAEA) in co-operation with the World Meteorological Organization (WMO), the Past Global Changes Project (PAGES) of the International Geosphere-Biosphere Programme (IGBP), the World Health Organization (WHO) and the International Association of Hydrological Sciences (IAHS). It was agreed to transfer the responsibility of running the GNIP and the collection of isotope data in precipitation to a Steering Committee, which will consist of representatives of the following organizations: IAEA, WMO, IGBP-PAGES, WHO, UNESCO and IAHS. The responsibilities of the International Atomic Energy Agency (IAEA) in the Steering Committee are as follows: Co-ordination of the sample analysis: Arrangements for and participation in the measuring programme. Monitoring analytical aspects of sample collection, storage, etc. Arrangements for interlaboratory comparison exercises; collection of isotope and meteorological data, maintenance of the GNIP database and data distribution to interested users; promotion of full use and wider application of GNIP data in practical hydrological applications. Figs, tabs

  14. Investigating precipitation changes of anthropic origin: data and methodological issues

    Science.gov (United States)

    de Lima, Isabel; Lovejoy, Shaun

    2017-04-01

    from about a month to ≈30 years. We illustrate this using local gauge data and three qualitatively different global scale precipitation products (from gauges, reanalyses and a satellite and gauge hybrid) that allow to investigate precipitation from monthly to centennial scales and in space from planetary down to 5°x5° scales. By systematically characterizing precipitation variability across wide ranges of time and space scales, we show that the anthropogenic signal only exceeded the natural variability at time scales larger than ≈20 years, so that the disagreement in the trends can be traced to these low frequencies.

  15. The Impact of Desert Dust Aerosol Radiative Forcing on Global and West African Precipitation

    Science.gov (United States)

    Jordan, A.; Zaitchik, B. F.; Gnanadesikan, A.; Dezfuli, A. K.

    2015-12-01

    Desert dust aerosols exert a radiative forcing on the atmosphere, influencing atmospheric temperature structure and modifying radiative fluxes at the top of the atmosphere (TOA) and surface. As dust aerosols perturb radiative fluxes, the atmosphere responds by altering both energy and moisture dynamics, with potentially significant impacts on regional and global precipitation. Global Climate Model (GCM) experiments designed to characterize these processes have yielded a wide range of results, owing to both the complex nature of the system and diverse differences across models. Most model results show a general decrease in global precipitation, but regional results vary. Here, we compare simulations from GFDL's CM2Mc GCM with multiple other model experiments from the literature in order to investigate mechanisms of radiative impact and reasons for GCM differences on a global and regional scale. We focus on West Africa, a region of high interannual rainfall variability that is a source of dust and that neighbors major Sahara Desert dust sources. As such, changes in West African climate due to radiative forcing of desert dust aerosol have serious implications for desertification feedbacks. Our CM2Mc results show net cooling of the planet at TOA and surface, net warming of the atmosphere, and significant increases in precipitation over West Africa during the summer rainy season. These results differ from some previous GCM studies, prompting comparative analysis of desert dust parameters across models. This presentation will offer quantitative analysis of differences in dust aerosol parameters, aerosol optical properties, and overall particle burden across GCMs, and will characterize the contribution of model differences to the uncertainty of forcing and climate response affecting West Africa.

  16. Application study of monthly precipitation forecast in Northeast China based on the cold vortex persistence activity index

    Science.gov (United States)

    Gang, Liu; Meihui, Qu; Guolin, Feng; Qucheng, Chu; Jing, Cao; Jie, Yang; Ling, Cao; Yao, Feng

    2018-03-01

    This paper introduces three quantitative indicators to conduct research for characterizing Northeast China cold vortex persistence activity: cold vortex persistence, generalized "cold vortex," and cold vortex precipitation. As discussed in the first part of paper, a hindcast is performed by multiple regressions using Northeast China precipitation from 2012 to 2014 combination with the previous winter 144 air-sea system factors. The results show that the mentioned three cold vortex index series can reflect the spatial and temporal distributions of observational precipitation in 2012-2014 and obtain results. The cold vortex factors are then added to the Forecast System on Dynamical and Analogy Skills (FODAS) to carry out dynamic statistical hindcast of precipitation in Northeast China from 2003 to 2012. Based on the characteristics and significance of each index, precipitation hindcast is carried out for Northeast China in May, June, July, August, May-June, and July-August. It turns out that the Northeast Cold Vortex Index Series, as defined in this paper, can make positive corrections to the FODAS forecast system, and most of the index correction results are higher than the system's own correction value. This study provides quantitative index products and supplies a solid technical foundation and support for monthly precipitation forecast in Northeast China.

  17. Study of variations of stable isotopes in precipitation: case of Antananarivo

    International Nuclear Information System (INIS)

    Randrianarivola, M.

    2014-01-01

    The isotopic signature of precipitation is the input signal in any study of hydrological cycle. The scientific objective of this work is to better understand the isotopic variations in precipitation and identify their processes. We used the network of measurement GNIP (Global Network of Isotopes in Precipitation) in which data is acquired by the International Atomic Energy Agency through isotope hydrology laboratory at INSTN-Madagascar. Analyzes stable isotopes ( 18O and 2 H), were performed at a monthly time step. We were able to confirm the relative importance of different mechanisms governing the isotopic composition of precipitation. The spatial distribution of abundance ratios of Antananarivo rain is in fact dictated by the temperature which follow indirectly from the effects of altitude and seasonal variations. At the monthly scale, local meteoric water line δ 2 H versus δ 18 O shows the specificity of Antananarivo (deuterium excess of 17.5‰ ). Additionally, seasonal variations in precipitation is related to the temperature such that in summer (d=15‰) and winter (d=18‰) [fr

  18. Assessment of the Latest GPM-Era High-Resolution Satellite Precipitation Products by Comparison with Observation Gauge Data over the Chinese Mainland

    Directory of Open Access Journals (Sweden)

    Shaowei Ning

    2016-10-01

    Full Text Available The Global Precipitation Mission (GPM Core Observatory that was launched on 27 February 2014 ushered in a new era for estimating precipitation from satellites. Based on their high spatial–temporal resolution and near global coverage, satellite-based precipitation products have been applied in many research fields. The goal of this study was to quantitatively compare two of the latest GPM-era satellite precipitation products (GPM IMERG and GSMap-Gauge Ver. 6 with a network of 840 precipitation gauges over the Chinese mainland. Direct comparisons of satellite-based precipitation products with rain gauge observations over a 20 month period from April 2014 to November 2015 at 0.1° and daily/monthly resolutions showed the following results: Both of the products were capable of capturing the overall spatial pattern of the 20 month mean daily precipitation, which was characterized by a decreasing trend from the southeast to the northwest. GPM IMERG overestimated precipitation by approximately 0.09 mm/day while GSMap-Gauge Ver. 6 underestimated precipitation by −0.04 mm/day. The two satellite-based precipitation products performed better over wet southern regions than over dry northern regions. They also showed better performance in summer than in winter. In terms of mean error, root mean square error, correlation coefficient, and probability of detection, GSMap-Gauge was better able to estimate precipitation and had more stable quality results than GPM IMERG on both daily and monthly scales. GPM IMERG was more sensitive to conditions of no rain or light rainfall and demonstrated good capability of capturing the behavior of extreme precipitation events. Overall, the results revealed some limitations of these two latest satellite-based precipitation products when used over the Chinese mainland, helping to characterize some of the error features in these datasets for potential users.

  19. How much might additional half a degree from a global warming of 1.5°C affects the extreme precipitation change in China?

    Science.gov (United States)

    Li, W.; Jiang, Z.

    2017-12-01

    In order to strengthen the global respond to the dangerous of global warming, Paris Agreement sets out two long-term warming goals: limiting global warming to well below 2˚C and purse effort to below 1.5˚C above pre-industrial levels. However, future climate change risks in those two warming targets show significant regional differences. This article aims to study the intensity and frequency of extreme precipitation change over China under those two global warming targets by using CMIP5 models under RCP4.5 and RCP8.5 scenario. Focus is put on the effects of the additional half degree in changing the extreme precipitation. Results show that the changes of extreme precipitation are independent of the RCP scenarios when global warming reaches the same threshold. Intensity of extreme precipitation averaged over China increase by around 6% and 11% when global warming reaches 1.5˚C and 2˚C, respectively. The additional half a degree increase makes the intensity of extreme precipitation averaged over China to increase by 4.5%, which translates to an increase close to the Clausius-Clapeyron scaling. Return period decreases by 5 years for the extra half degree warming when the 20-year return values are considered at the reference level.

  20. Large differences in regional precipitation change between a first and second 2 K of global warming

    Science.gov (United States)

    Good, Peter; Booth, Ben B. B.; Chadwick, Robin; Hawkins, Ed; Jonko, Alexandra; Lowe, Jason A.

    2016-12-01

    For adaptation and mitigation planning, stakeholders need reliable information about regional precipitation changes under different emissions scenarios and for different time periods. A significant amount of current planning effort assumes that each K of global warming produces roughly the same regional climate change. Here using 25 climate models, we compare precipitation responses with three 2 K intervals of global ensemble mean warming: a fast and a slower route to a first 2 K above pre-industrial levels, and the end-of-century difference between high-emission and mitigation scenarios. We show that, although the two routes to a first 2 K give very similar precipitation changes, a second 2 K produces quite a different response. In particular, the balance of physical mechanisms responsible for climate model uncertainty is different for a first and a second 2 K of warming. The results are consistent with a significant influence from nonlinear physical mechanisms, but aerosol and land-use effects may be important regionally.

  1. Precipitation and total power consumption in the ionosphere: Global MHD simulation results compared with Polar and SNOE observations

    Directory of Open Access Journals (Sweden)

    M. Palmroth

    2006-05-01

    Full Text Available We compare the ionospheric electron precipitation morphology and power from a global MHD simulation (GUMICS-4 with direct measurements of auroral energy flux during a pair of substorms on 28-29 March 1998. The electron precipitation power is computed directly from global images of auroral light observed by the Polar satellite ultraviolet imager (UVI. Independent of the Polar UVI measurements, the electron precipitation energy is determined from SNOE satellite observations on the thermospheric nitric oxide (NO density. We find that the GUMICS-4 simulation reproduces the spatial variation of the global aurora rather reliably in the sense that the onset of the substorm is shown in GUMICS-4 simulation as enhanced precipitation in the right location at the right time. The total integrated precipitation power in the GUMICS-4 simulation is in quantitative agreement with the observations during quiet times, i.e., before the two substorm intensifications. We find that during active times the GUMICS-4 integrated precipitation is a factor of 5 lower than the observations indicate. However, we also find factor of 2-3 differences in the precipitation power among the three different UVI processing methods tested here. The findings of this paper are used to complete an earlier objective, in which the total ionospheric power deposition in the simulation is forecasted from a mathematical expression, which is a function of solar wind density, velocity and magnetic field. We find that during this event, the correlation coefficient between the outcome of the forecasting expression and the simulation results is 0.83. During the event, the simulation result on the total ionospheric power deposition agrees with observations (correlation coefficient 0.8 and the AE index (0.85.

  2. Vegetation anomalies caused by antecedent precipitation in most of the world

    Science.gov (United States)

    Papagiannopoulou, C.; Miralles, D. G.; Dorigo, W. A.; Verhoest, N. E. C.; Depoorter, M.; Waegeman, W.

    2017-07-01

    Quantifying environmental controls on vegetation is critical to predict the net effect of climate change on global ecosystems and the subsequent feedback on climate. Following a non-linear Granger causality framework based on a random forest predictive model, we exploit the current wealth of multi-decadal satellite data records to uncover the main drivers of monthly vegetation variability at the global scale. Results indicate that water availability is the most dominant factor driving vegetation globally: about 61% of the vegetated surface was primarily water-limited during 1981-2010. This included semiarid climates but also transitional ecoregions. Intra-annually, temperature controls Northern Hemisphere deciduous forests during the growing season, while antecedent precipitation largely dominates vegetation dynamics during the senescence period. The uncovered dependency of global vegetation on water availability is substantially larger than previously reported. This is owed to the ability of the framework to (1) disentangle the co-linearities between radiation/temperature and precipitation, and (2) quantify non-linear impacts of climate on vegetation. Our results reveal a prolonged effect of precipitation anomalies in dry regions: due to the long memory of soil moisture and the cumulative, non-linear, response of vegetation, water-limited regions show sensitivity to the values of precipitation occurring three months earlier. Meanwhile, the impacts of temperature and radiation anomalies are more immediate and dissipate shortly, pointing to a higher resilience of vegetation to these anomalies. Despite being infrequent by definition, hydro-climatic extremes are responsible for up to 10% of the vegetation variability during the 1981-2010 period in certain areas, particularly in water-limited ecosystems. Our approach is a first step towards a quantitative comparison of the resistance and resilience signature of different ecosystems, and can be used to benchmark Earth

  3. Climatic driving forces in inter-annual variation of global FPAR

    Science.gov (United States)

    Peng, Dailiang; Liu, Liangyun; Yang, Xiaohua; Zhou, Bin

    2012-09-01

    Fraction of Absorbed Photosynthetically Active Radiation (FPAR) characterizes vegetation canopy functioning and its energy absorption capacity. In this paper, we focus on climatic driving forces in inter-annual variation of global FPAR from 1982 to 2006 by Global Historical Climatology Network (GHCN-Monthly) data. Using FPAR-Simple Ratio Vegetation Index (SR) relationship, Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) was used to estimate FPAR at the global scale. The correlation between inter-annual variation of FPAR and temperature, precipitation derived from GHCN-Monthly was examined, during the periods of March-May (MAM), June-August (JJA), September-November (SON), and December-February (DJF) over from 1982 to 2006. The analysis of climatic influence on global FPAR revealed the significant correlation with temperature and precipitation in some meteorological stations area, and a more significant correlation with precipitation was found than which with temperature. Some stations in the regions between 30° N and 60° N and around 30° S in South America, where the annual FPAR variation showed a significant positive correlation with temperature (P forest of Africa and Amazon during the dry season of JJA and SON.

  4. Changes in equatorial zonal circulations and precipitation in the context of the global warming and natural modes

    Science.gov (United States)

    Kim, B. H.; Ha, K. J.

    2017-12-01

    The strengthening and westward shift of Pacific Walker Circulation (PWC) is observed during the recent decades. However, the relative roles of global warming and natural variability on the change in PWC unclearly remain. By conducting numerical atmospheric general circulation model (AGCM) experiments using the spatial SST patterns in the global warming and natural modes which are obtained by the multi-variate EOF analysis from three variables including precipitation, sea surface temperature (SST), and divergent zonal wind, we indicated that the westward shift and strengthening of PWC are caused by the global warming SST pattern in the global warming mode and the negative Interdecadal Pacific Oscillation-like SST pattern in the natural mode. The SST distribution of the Pacific Ocean (PO) has more influence on the changes in equatorial zonal circulations and tropical precipitation than that of the Indian Ocean (IO) and Atlantic Ocean (AO). The change in precipitation is also related to the equatorial zonal circulations variation through the upward and downward motions of the circulations. The IO and AO SST anomalies in the global warming mode can affect on the changes in equatorial zonal circulations, but the influence of PO SST disturbs the Indian Walker circulation and Atlantic Walker circulation changes by the IO and AO. The zonal shift of PWC is found to be highly associated with a zonal gradient of SST over the PO through the idealized numerical AGCM experiments and predictions of CMIP5 models.

  5. A Robust Response of Precipitation to Global Warming from CMIP5 Models

    Science.gov (United States)

    Lau, K. -M.; Wu, H. -T.; Kim, K. -M.

    2012-01-01

    How precipitation responds to global warming is a major concern to society and a challenge to climate change research. Based on analyses of rainfall probability distribution functions of 14 state-of-the-art climate models, we find a robust, canonical global rainfall response to a triple CO2 warming scenario, featuring 100 250% more heavy rain, 5-10% less moderate rain, and 10-15% more very light or no-rain events. Regionally, a majority of the models project a consistent response with more heavy rain events over climatologically wet regions of the deep tropics, and more dry events over subtropical and tropical land areas. Results suggest that increased CO2 emissions induce basic structural changes in global rain systems, increasing risks of severe floods and droughts in preferred geographic locations worldwide.

  6. Precipitation and Carbon-Water Coupling Jointly Control the Interannual Variability of Global Land Gross Primary Production

    Science.gov (United States)

    Zhang, Yao; Xiao, Xiangming; Guanter, Luis; Zhou, Sha; Ciais, Philippe; Joiner, Joanna; Sitch, Stephen; Wu, Xiaocui; Nabel, Julian; Dong, Jinwei; hide

    2016-01-01

    Carbon uptake by terrestrial ecosystems is increasing along with the rising of atmospheric CO2 concentration. Embedded in this trend, recent studies suggested that the interannual variability (IAV) of global carbon fluxes may be dominated by semi-arid ecosystems, but the underlying mechanisms of this high variability in these specific regions are not well known. Here we derive an ensemble of gross primary production (GPP) estimates using the average of three data-driven models and eleven process-based models. These models are weighted by their spatial representativeness of the satellite-based solar-induced chlorophyll fluorescence (SIF). We then use this weighted GPP ensemble to investigate the GPP variability for different aridity regimes. We show that semi-arid regions contribute to 57% of the detrended IAV of global GPP. Moreover, in regions with higher GPP variability, GPP fluctuations are mostly controlled by precipitation and strongly coupled with evapotranspiration (ET). This higher GPP IAV in semi-arid regions is co-limited by supply (precipitation)-induced ET variability and GPP-ET coupling strength. Our results demonstrate the importance of semi-arid regions to the global terrestrial carbon cycle and posit that there will be larger GPP and ET variations in the future with changes in precipitation patterns and dryland expansion.

  7. Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

    Science.gov (United States)

    Hong, Yang; Adler, Robert F.; Huffman, George J.; Pierce, Harold

    2008-01-01

    Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

  8. Evaluating the Global Precipitation Measurement mission with NOAA/NSSL Multi-Radar Multisensor: current status and future directions.

    Science.gov (United States)

    Kirstetter, P. E.; Petersen, W. A.; Gourley, J. J.; Kummerow, C.; Huffman, G. J.; Turk, J.; Tanelli, S.; Maggioni, V.; Anagnostou, E. N.; Hong, Y.; Schwaller, M.

    2017-12-01

    Accurate characterization of uncertainties in space-borne precipitation estimates is critical for many applications including water budget studies or prediction of natural hazards at the global scale. The GPM precipitation Level II (active and passive) and Level III (IMERG) estimates are compared to the high quality and high resolution NEXRAD-based precipitation estimates derived from the NOAA/NSSL's Multi-Radar, Multi-Sensor (MRMS) platform. A surface reference is derived from the MRMS suite of products to be accurate with known uncertainty bounds and measured at a resolution below the pixel sizes of any GPM estimate, providing great flexibility in matching to grid scales or footprints. It provides an independent and consistent reference research framework for directly evaluating GPM precipitation products across a large number of meteorological regimes as a function of resolution, accuracy and sample size. The consistency of the ground and space-based sensors in term of precipitation detection, typology and quantification are systematically evaluated. Satellite precipitation retrievals are further investigated in terms of precipitation distributions, systematic biases and random errors, influence of precipitation sub-pixel variability and comparison between satellite products. Prognostic analysis directly provides feedback to algorithm developers on how to improve the satellite estimates. Specific factors for passive (e.g. surface conditions for GMI) and active (e.g. non uniform beam filling for DPR) sensors are investigated. This cross products characterization acts as a bridge to intercalibrate microwave measurements from the GPM constellation satellites and propagate to the combined and global precipitation estimates. Precipitation features previously used to analyze Level II satellite estimates under various precipitation processes are now intoduced for Level III to test several assumptions in the IMERG algorithm. Specifically, the contribution of Level II is

  9. Controls on the meridional extent of tropical precipitation and its contraction under global warming

    Science.gov (United States)

    Donohoe, A.

    2017-12-01

    A method for decomposing changes and variability in the spatial structure of tropical precipitation into shifting (meridional translation), contracting, and intensifying modes of variability is introduced. We demonstrate that the shifting mode of tropical precipitation explains very little (20%) more of the tropical precipitation changes and variability. Furthermore, the contraction of tropical precipitation is highly correlated (R2 > 0.95) with an intensification of the precipitation in both the observations and forced modeled simulations. These results suggest that the simultaneous contraction and intensification of tropical precipitation is the dominant mode of variability and changes under external forcing. We speculate that tropical surface temperature controls this concurrent variability. Indeed, models robustly predict that tropical precipitation increases and meridionally contracts in response to increased CO2 and is reduced and meridionally expanded under glacial forcing and boundary conditions. In contrast, the directionality of the tropical precipitation shift is both ambiguous and small in magnitude in response to increased CO2. Furthermore, the ratio of the contraction/expansion to intensification/reduction is consistent in the continuum of climate states from the glacial climate to a modern climate to a 4XCO2 climate suggesting that the intensification and contraction are linked together via a single mechanism. We examine two mechanisms responsible for the contraction of the precipitation under global warming : i. the reduction of the seasonal cycle of energy input to the atmosphere due to sea ice retreat that results in the tropical precipitation remaining closer to the equator during the solsticial seasons and; ii. the increased gross moist stability of the tropical atmosphere as the surface warms resulting in a weaker cross-equatorial Hadley circulation during the solsticial seasons.

  10. Evaluation of satellite-retrieved extreme precipitation using gauge observations

    Science.gov (United States)

    Lockhoff, M.; Zolina, O.; Simmer, C.; Schulz, J.

    2012-04-01

    Precipitation extremes have already been intensively studied employing rain gauge datasets. Their main advantage is that they represent a direct measurement with a relatively high temporal coverage. Their main limitation however is their poor spatial coverage and thus a low representativeness in many parts of the world. In contrast, satellites can provide global coverage and there are meanwhile data sets available that are on one hand long enough to be used for extreme value analysis and that have on the other hand the necessary spatial and temporal resolution to capture extremes. However, satellite observations provide only an indirect mean to determine precipitation and there are many potential observational and methodological weaknesses in particular over land surfaces that may constitute doubts concerning their usability for the analysis of precipitation extremes. By comparing basic climatological metrics of precipitation (totals, intensities, number of wet days) as well as respective characteristics of PDFs, absolute and relative extremes of satellite and observational data this paper aims at assessing to which extent satellite products are suitable for analysing extreme precipitation events. In a first step the assessment focuses on Europe taking into consideration various satellite products available, e.g. data sets provided by the Global Precipitation Climatology Project (GPCP). First results indicate that satellite-based estimates do not only represent the monthly averaged precipitation very similar to rain gauge estimates but they also capture the day-to-day occurrence fairly well. Larger differences can be found though when looking at the corresponding intensities.

  11. Precipitation data in a mountainous catchment in Honduras: quality assessment and spatiotemporal characteristics

    Science.gov (United States)

    Westerberg, I.; Walther, A.; Guerrero, J.-L.; Coello, Z.; Halldin, S.; Xu, C.-Y.; Chen, D.; Lundin, L.-C.

    2010-08-01

    An accurate description of temporal and spatial precipitation variability in Central America is important for local farming, water supply and flood management. Data quality problems and lack of consistent precipitation data impede hydrometeorological analysis in the 7,500 km2 Choluteca River basin in central Honduras, encompassing the capital Tegucigalpa. We used precipitation data from 60 daily and 13 monthly stations in 1913-2006 from five local authorities and NOAA's Global Historical Climatology Network. Quality control routines were developed to tackle the specific data quality problems. The quality-controlled data were characterised spatially and temporally, and compared with regional and larger-scale studies. Two gap-filling methods for daily data and three interpolation methods for monthly and mean annual precipitation were compared. The coefficient-of-correlation-weighting method provided the best results for gap-filling and the universal kriging method for spatial interpolation. In-homogeneity in the time series was the main quality problem, and 22% of the daily precipitation data were too poor to be used. Spatial autocorrelation for monthly precipitation was low during the dry season, and correlation increased markedly when data were temporally aggregated from a daily time scale to 4-5 days. The analysis manifested the high spatial and temporal variability caused by the diverse precipitation-generating mechanisms and the need for an improved monitoring network.

  12. Global Precipitation Measurement (GPM) Spacecraft Lithium Ion Battery Micro-Cycling Investigation

    Science.gov (United States)

    Dakermanji, George; Lee, Leonine; Spitzer, Thomas

    2016-01-01

    The Global Precipitation Measurement (GPM) spacecraft was jointly developed by NASA and JAXA. It is a Low Earth Orbit (LEO) spacecraft launched on February 27, 2014. The power system is a Direct Energy Transfer (DET) system designed to support 1950 watts orbit average power. The batteries use SONY 18650HC cells and consist of three 8s by 84p batteries operated in parallel as a single battery. During instrument integration with the spacecraft, large current transients were observed in the battery. Investigation into the matter traced the cause to the Dual-Frequency Precipitation Radar (DPR) phased array radar which generates cyclical high rate current transients on the spacecraft power bus. The power system electronics interaction with these transients resulted in the current transients in the battery. An accelerated test program was developed to bound the effect, and to assess the impact to the mission.

  13. Data Visualization and Analysis Tools for the Global Precipitation Measurement (GPM) Validation Network

    Science.gov (United States)

    Morris, Kenneth R.; Schwaller, Mathew

    2010-01-01

    The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) Mission compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR) to similar measurements from U.S. and international operational weather radars. This prototype is a major component of the GPM Ground Validation System (GVS). The VN provides a means for the precipitation measurement community to identify and resolve significant discrepancies between the ground radar (GR) observations and similar satellite observations. The VN prototype is based on research results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller (2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for the comparisons. This paper describes software tools that have been developed for visualization and statistical analysis of the original and volume matched PR and GR data.

  14. Regional scaling of annual mean precipitation and water availability with global temperature change

    Science.gov (United States)

    Greve, Peter; Gudmundsson, Lukas; Seneviratne, Sonia I.

    2018-03-01

    Changes in regional water availability belong to the most crucial potential impacts of anthropogenic climate change, but are highly uncertain. It is thus of key importance for stakeholders to assess the possible implications of different global temperature thresholds on these quantities. Using a subset of climate model simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), we derive here the sensitivity of regional changes in precipitation and in precipitation minus evapotranspiration to global temperature changes. The simulations span the full range of available emission scenarios, and the sensitivities are derived using a modified pattern scaling approach. The applied approach assumes linear relationships on global temperature changes while thoroughly addressing associated uncertainties via resampling methods. This allows us to assess the full distribution of the simulations in a probabilistic sense. Northern high-latitude regions display robust responses towards wetting, while subtropical regions display a tendency towards drying but with a large range of responses. Even though both internal variability and the scenario choice play an important role in the overall spread of the simulations, the uncertainty stemming from the climate model choice usually accounts for about half of the total uncertainty in most regions. We additionally assess the implications of limiting global mean temperature warming to values below (i) 2 K or (ii) 1.5 K (as stated within the 2015 Paris Agreement). We show that opting for the 1.5 K target might just slightly influence the mean response, but could substantially reduce the risk of experiencing extreme changes in regional water availability.

  15. Precipitation isoscapes for New Zealand: enhanced temporal detail using precipitation-weighted daily climatology.

    Science.gov (United States)

    Baisden, W Troy; Keller, Elizabeth D; Van Hale, Robert; Frew, Russell D; Wassenaar, Leonard I

    2016-01-01

    Predictive understanding of precipitation δ(2)H and δ(18)O in New Zealand faces unique challenges, including high spatial variability in precipitation amounts, alternation between subtropical and sub-Antarctic precipitation sources, and a compressed latitudinal range of 34 to 47 °S. To map the precipitation isotope ratios across New Zealand, three years of integrated monthly precipitation samples were acquired from >50 stations. Conventional mean-annual precipitation δ(2)H and δ(18)O maps were produced by regressions using geographic and annual climate variables. Incomplete data and short-term variation in climate and precipitation sources limited the utility of this approach. We overcome these difficulties by calculating precipitation-weighted monthly climate parameters using national 5-km-gridded daily climate data. This data plus geographic variables were regressed to predict δ(2)H, δ(18)O, and d-excess at all sites. The procedure yields statistically-valid predictions of the isotope composition of precipitation (long-term average root mean square error (RMSE) for δ(18)O = 0.6 ‰; δ(2)H = 5.5 ‰); and monthly RMSE δ(18)O = 1.9 ‰, δ(2)H = 16 ‰. This approach has substantial benefits for studies that require the isotope composition of precipitation during specific time intervals, and may be further improved by comparison to daily and event-based precipitation samples as well as the use of back-trajectory calculations.

  16. Response of precipitation extremes to idealized global warming in an aqua-planet climate model: Towards robust projection across different horizontal resolutions

    Energy Technology Data Exchange (ETDEWEB)

    Li, F.; Collins, W.D.; Wehner, M.F.; Williamson, D.L.; Olson, J.G.

    2011-04-15

    Current climate models produce quite heterogeneous projections for the responses of precipitation extremes to future climate change. To help understand the range of projections from multimodel ensembles, a series of idealized 'aquaplanet' Atmospheric General Circulation Model (AGCM) runs have been performed with the Community Atmosphere Model CAM3. These runs have been analysed to identify the effects of horizontal resolution on precipitation extreme projections under two simple global warming scenarios. We adopt the aquaplanet framework for our simulations to remove any sensitivity to the spatial resolution of external inputs and to focus on the roles of model physics and dynamics. Results show that a uniform increase of sea surface temperature (SST) and an increase of low-to-high latitude SST gradient both lead to increase of precipitation and precipitation extremes for most latitudes. The perturbed SSTs generally have stronger impacts on precipitation extremes than on mean precipitation. Horizontal model resolution strongly affects the global warming signals in the extreme precipitation in tropical and subtropical regions but not in high latitude regions. This study illustrates that the effects of horizontal resolution have to be taken into account to develop more robust projections of precipitation extremes.

  17. Global distribution of moisture, evaporation-precipitation, and diabatic heating rates

    Science.gov (United States)

    Christy, John R.

    1989-01-01

    Global archives were established for ECMWF 12-hour, multilevel analysis beginning 1 January 1985; day and night IR temperatures, and solar incoming and solar absorbed. Routines were written to access these data conveniently from NASA/MSFC MASSTOR facility for diagnostic analysis. Calculations of diabatic heating rates were performed from the ECMWF data using 4-day intervals. Calculations of precipitable water (W) from 1 May 1985 were carried out using the ECMWF data. Because a major operational change on 1 May 1985 had a significant impact on the moisture field, values prior to that date are incompatible with subsequent analyses.

  18. Projections of the Ganges-Brahmaputra precipitation: downscaled from GCM predictors

    Science.gov (United States)

    Pervez, Md Shahriar; Henebry, Geoffrey M.

    2014-01-01

    Downscaling Global Climate Model (GCM) projections of future climate is critical for impact studies. Downscaling enables use of GCM experiments for regional scale impact studies by generating regionally specific forecasts connecting global scale predictions and regional scale dynamics. We employed the Statistical Downscaling Model (SDSM) to downscale 21st century precipitation for two data-sparse hydrologically challenging river basins in South Asia—the Ganges and the Brahmaputra. We used CGCM3.1 by Canadian Center for Climate Modeling and Analysis version 3.1 predictors in downscaling the precipitation. Downscaling was performed on the basis of established relationships between historical Global Summary of Day observed precipitation records from 43 stations and National Center for Environmental Prediction re-analysis large scale atmospheric predictors. Although the selection of predictors was challenging during the set-up of SDSM, they were found to be indicative of important physical forcings in the basins. The precipitation of both basins was largely influenced by geopotential height: the Ganges precipitation was modulated by the U component of the wind and specific humidity at 500 and 1000 h Pa pressure levels; whereas, the Brahmaputra precipitation was modulated by the V component of the wind at 850 and 1000 h Pa pressure levels. The evaluation of the SDSM performance indicated that model accuracy for reproducing precipitation at the monthly scale was acceptable, but at the daily scale the model inadequately simulated some daily extreme precipitation events. Therefore, while the downscaled precipitation may not be the suitable input to analyze future extreme flooding or drought events, it could be adequate for analysis of future freshwater availability. Analysis of the CGCM3.1 downscaled precipitation projection with respect to observed precipitation reveals that the precipitation regime in each basin may be significantly impacted by climate change

  19. Century-scale variability in global annual runoff examined using a water balance model

    Science.gov (United States)

    McCabe, G.J.; Wolock, D.M.

    2011-01-01

    A monthly water balance model (WB model) is used with CRUTS2.1 monthly temperature and precipitation data to generate time series of monthly runoff for all land areas of the globe for the period 1905 through 2002. Even though annual precipitation accounts for most of the temporal and spatial variability in annual runoff, increases in temperature have had an increasingly negative effect on annual runoff after 1980. Although the effects of increasing temperature on runoff became more apparent after 1980, the relative magnitude of these effects are small compared to the effects of precipitation on global runoff. ?? 2010 Royal Meteorological Society.

  20. Impacts of global warming of 1.5 °C and 2.0 °C on precipitation patterns in China by regional climate model (COSMO-CLM)

    Science.gov (United States)

    Sun, Hemin; Wang, Anqian; Zhai, Jianqing; Huang, Jinlong; Wang, Yanjun; Wen, Shanshan; Zeng, Xiaofan; Su, Buda

    2018-05-01

    Regional precipitation patterns may change in a warmer climate, thereby increasing flood and drought risks. In this paper, annual, annual maximum, intense, heavy, moderate, light, and trace precipitation are employed as indicators to assess changes in precipitation patterns under two scenarios in which the global mean temperature increases by 1.5 °C and 2.0 °C relative to pre-industrial levels using the regional climate model COSMO-CLM (CCLM). The results show that annual precipitation in China will be approximately 2.5% higher under 1.5 °C warming relative to the present-day baseline (1980-2009), although it will decrease by approximately 4.0% under an additional 0.5 °C increase in global mean temperature. This trend is spatially consistent for regions with annual precipitation of 400-800 mm, which has experienced a drying trend during the past half century; thus, limiting global warming to 1.5 °C may mitigate these drying conditions. The annual maximum precipitation continues to increase from present day levels to the 2.0 °C warming scenario. Relative to the baseline period, the frequency of trace and light precipitation days exhibits a negative trend, while that of moderate, heavy, and intense precipitation days has a positive trend under the 1.5 °C warming scenario. For the 2.0 °C warming world, the frequency of days is projected to decrease for all precipitation categories, although the intensity of intense precipitation increases. Spatially, a decrease in the number of precipitation days is expected to continue in central and northern China, where a drying trend has persisted over the past half century. Southeastern China, which already suffers greatly from flooding, is expected to face more heavy and intense precipitation with an additional 0.5 °C increase in global mean temperature. Meanwhile, the intensity of intense precipitation is expected to increase in northern China, and the contribution of light and moderate precipitation to the annual

  1. Terrestrial precipitation and soil moisture: A case study over southern Arizona and data development

    Science.gov (United States)

    Stillman, Susan

    reanalyses. We show that while WGEW is small compared to the grid size of many of the evaluated products, unlike scaling from point to area, the effect of scaling from smaller to larger area is small. Finally, we focus on global precipitation. Global monthly gauge based precipitation data has become widely available in recent years and is necessary for analyzing the climatological and anomaly precipitation fields as well as for calibrating and evaluating other gridded products such as satellite-based and modeled precipitation. However, frequency and intensity of precipitation are also important in the partitioning of water and energy fluxes. Therefore, because daily and sub-daily observed precipitation is limited to recent years, the number of raining days per month (N) is needed. We show that the only currently available long-term N product, developed by the Climate Research Unit (CRU), is deficient in certain areas, particularly where CRU gauge data is sparse. We then develop a new global 110-year N product, which shows significant improvement over CRU using three regional daily precipitation products with far more gauges than are used in CRU.

  2. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 3 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Land Surface Temperature Databank contains monthly timescale mean, maximum, and minimum temperature for approximately 40,000 stations globally. It was...

  3. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 2 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  4. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 1 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  5. Calibration and combination of monthly near-surface temperature and precipitation predictions over Europe

    Science.gov (United States)

    Rodrigues, Luis R. L.; Doblas-Reyes, Francisco J.; Coelho, Caio A. S.

    2018-02-01

    A Bayesian method known as the Forecast Assimilation (FA) was used to calibrate and combine monthly near-surface temperature and precipitation outputs from seasonal dynamical forecast systems. The simple multimodel (SMM), a method that combines predictions with equal weights, was used as a benchmark. This research focuses on Europe and adjacent regions for predictions initialized in May and November, covering the boreal summer and winter months. The forecast quality of the FA and SMM as well as the single seasonal dynamical forecast systems was assessed using deterministic and probabilistic measures. A non-parametric bootstrap method was used to account for the sampling uncertainty of the forecast quality measures. We show that the FA performs as well as or better than the SMM in regions where the dynamical forecast systems were able to represent the main modes of climate covariability. An illustration with the near-surface temperature over North Atlantic, the Mediterranean Sea and Middle-East in summer months associated with the well predicted first mode of climate covariability is offered. However, the main modes of climate covariability are not well represented in most situations discussed in this study as the seasonal dynamical forecast systems have limited skill when predicting the European climate. In these situations, the SMM performs better more often.

  6. Large differences in regional precipitation change between a first and second 2 K of global warming

    Science.gov (United States)

    Good, Peter; Booth, Ben B. B.; Chadwick, Robin; Hawkins, Ed; Jonko, Alexandra; Lowe, Jason A.

    2016-01-01

    For adaptation and mitigation planning, stakeholders need reliable information about regional precipitation changes under different emissions scenarios and for different time periods. A significant amount of current planning effort assumes that each K of global warming produces roughly the same regional climate change. Here using 25 climate models, we compare precipitation responses with three 2 K intervals of global ensemble mean warming: a fast and a slower route to a first 2 K above pre-industrial levels, and the end-of-century difference between high-emission and mitigation scenarios. We show that, although the two routes to a first 2 K give very similar precipitation changes, a second 2 K produces quite a different response. In particular, the balance of physical mechanisms responsible for climate model uncertainty is different for a first and a second 2 K of warming. The results are consistent with a significant influence from nonlinear physical mechanisms, but aerosol and land-use effects may be important regionally. PMID:27922014

  7. Precipitable water: Its linear retrieval using leaps and bounds procedure and its global distribution from SEASAT SMMR data

    Science.gov (United States)

    Pandey, P. C.

    1982-01-01

    Eight subsets using two to five frequencies of the SEASAT scanning multichannel microwave radiometer are examined to determine their potential in the retrieval of atmospheric water vapor content. Analysis indicates that the information concerning the 18 and 21 GHz channels are optimum for water vapor retrieval. A comparison with radiosonde observations gave an rms accuracy of approximately 0.40 g sq cm. The rms accuracy of precipitable water using different subsets was within 10 percent. Global maps of precipitable water over oceans using two and five channel retrieval (average of two and five channel retrieval) are given. Study of these maps reveals the possibility of global moisture distribution associated with oceanic currents and large scale general circulation in the atmosphere. A stable feature of the large scale circulation is noticed. The precipitable water is maximum over the Bay of Bengal and in the North Pacific over the Kuroshio current and shows a general latitudinal pattern.

  8. HOMPRA Europe - A gridded precipitation data set from European homogenized time series

    Science.gov (United States)

    Rustemeier, Elke; Kapala, Alice; Meyer-Christoffer, Anja; Finger, Peter; Schneider, Udo; Venema, Victor; Ziese, Markus; Simmer, Clemens; Becker, Andreas

    2017-04-01

    Reliable monitoring data are essential for robust analyses of climate variability and, in particular, long-term trends. In this regard, a gridded, homogenized data set of monthly precipitation totals - HOMPRA Europe (HOMogenized PRecipitation Analysis of European in-situ data)- is presented. The data base consists of 5373 homogenized monthly time series, a carefully selected subset held by the Global Precipitation Climatology Centre (GPCC). The chosen series cover the period 1951-2005 and contain less than 10% missing values. Due to the large number of data, an automatic algorithm had to be developed for the homogenization of these precipitation series. In principal, the algorithm is based on three steps: * Selection of overlapping station networks in the same precipitation regime, based on rank correlation and Ward's method of minimal variance. Since the underlying time series should be as homogeneous as possible, the station selection is carried out by deterministic first derivation in order to reduce artificial influences. * The natural variability and trends were temporally removed by means of highly correlated neighboring time series to detect artificial break-points in the annual totals. This ensures that only artificial changes can be detected. The method is based on the algorithm of Caussinus and Mestre (2004). * In the last step, the detected breaks are corrected monthly by means of a multiple linear regression (Mestre, 2003). Due to the automation of the homogenization, the validation of the algorithm is essential. Therefore, the method was tested on artificial data sets. Additionally the sensitivity of the method was tested by varying the neighborhood series. If available in digitized form, the station history was also used to search for systematic errors in the jump detection. Finally, the actual HOMPRA Europe product is produced by interpolation of the homogenized series onto a 1° grid using one of the interpolation schems operationally at GPCC

  9. Recent change of the global monsoon precipitation (1979-2008)

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Bin [University of Hawaii at Manoa, Department of Meteorology, Honolulu, HI (United States); University of Hawaii at Manoa, International Pacific Research Center, Honolulu, HI (United States); Liu, Jian [Chinese Academy of Sciences, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Nanjing (China); Kim, Hyung-Jin [Japan Agency for Marine-Earth Science and Technology, Research Institute for Global Change, Yokohama, Kanagawa (Japan); Webster, Peter J. [Georgia Institute of Technology, School of Earth and Atmospheric Sciences, Atlanta, GA (United States); Yim, So-Young [University of Hawaii at Manoa, International Pacific Research Center, Honolulu, HI (United States)

    2012-09-15

    The global monsoon (GM) is a defining feature of the annual variation of Earth's climate system. Quantifying and understanding the present-day monsoon precipitation change are crucial for prediction of its future and reflection of its past. Here we show that regional monsoons are coordinated not only by external solar forcing but also by internal feedback processes such as El Nino-Southern Oscillation (ENSO). From one monsoon year (May to the next April) to the next, most continental monsoon regions, separated by vast areas of arid trade winds and deserts, vary in a cohesive manner driven by ENSO. The ENSO has tighter regulation on the northern hemisphere summer monsoon (NHSM) than on the southern hemisphere summer monsoon (SHSM). More notably, the GM precipitation (GMP) has intensified over the past three decades mainly due to the significant upward trend in NHSM. The intensification of the GMP originates primarily from an enhanced east-west thermal contrast in the Pacific Ocean, which is coupled with a rising pressure in the subtropical eastern Pacific and decreasing pressure over the Indo-Pacific warm pool. While this mechanism tends to amplify both the NHSM and SHSM, the stronger (weaker) warming trend in the NH (SH) creates a hemispheric thermal contrast, which favors intensification of the NHSM but weakens the SHSM. The enhanced Pacific zonal thermal contrast is largely a result of natural variability, whilst the enhanced hemispherical thermal contrast is likely due to anthropogenic forcing. We found that the enhanced global summer monsoon not only amplifies the annual cycle of tropical climate but also promotes directly a ''wet-gets-wetter'' trend pattern and indirectly a ''dry-gets-drier'' trend pattern through coupling with deserts and trade winds. The mechanisms recognized in this study suggest a way forward for understanding past and future changes of the GM in terms of its driven mechanisms. (orig.)

  10. A comparison of monthly precipitation point estimates at 6 locations in Iran using integration of soft computing methods and GARCH time series model

    Science.gov (United States)

    Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

    2017-11-01

    Precipitation plays an important role in determining the climate of a region. Precise estimation of precipitation is required to manage and plan water resources, as well as other related applications such as hydrology, climatology, meteorology and agriculture. Time series of hydrologic variables such as precipitation are composed of deterministic and stochastic parts. Despite this fact, the stochastic part of the precipitation data is not usually considered in modeling of precipitation process. As an innovation, the present study introduces three new hybrid models by integrating soft computing methods including multivariate adaptive regression splines (MARS), Bayesian networks (BN) and gene expression programming (GEP) with a time series model, namely generalized autoregressive conditional heteroscedasticity (GARCH) for modeling of the monthly precipitation. For this purpose, the deterministic (obtained by soft computing methods) and stochastic (obtained by GARCH time series model) parts are combined with each other. To carry out this research, monthly precipitation data of Babolsar, Bandar Anzali, Gorgan, Ramsar, Tehran and Urmia stations with different climates in Iran were used during the period of 1965-2014. Root mean square error (RMSE), relative root mean square error (RRMSE), mean absolute error (MAE) and determination coefficient (R2) were employed to evaluate the performance of conventional/single MARS, BN and GEP, as well as the proposed MARS-GARCH, BN-GARCH and GEP-GARCH hybrid models. It was found that the proposed novel models are more precise than single MARS, BN and GEP models. Overall, MARS-GARCH and BN-GARCH models yielded better accuracy than GEP-GARCH. The results of the present study confirmed the suitability of proposed methodology for precise modeling of precipitation.

  11. Uncertainty of global summer precipitation in the CMIP5 models: a comparison between high-resolution and low-resolution models

    Science.gov (United States)

    Huang, Danqing; Yan, Peiwen; Zhu, Jian; Zhang, Yaocun; Kuang, Xueyuan; Cheng, Jing

    2018-04-01

    The uncertainty of global summer precipitation simulated by the 23 CMIP5 CGCMs and the possible impacts of model resolutions are investigated in this study. Large uncertainties exist over the tropical and subtropical regions, which can be mainly attributed to convective precipitation simulation. High-resolution models (HRMs) and low-resolution models (LRMs) are further investigated to demonstrate their different contributions to the uncertainties of the ensemble mean. It shows that the high-resolution model ensemble means (HMME) and low-resolution model ensemble mean (LMME) mitigate the biases between the MME and observation over most continents and oceans, respectively. The HMME simulates more precipitation than the LMME over most oceans, but less precipitation over some continents. The dominant precipitation category in the HRMs (LRMs) is the heavy precipitation (moderate precipitation) over the tropic regions. The combinations of convective and stratiform precipitation are also quite different: the HMME has much higher ratio of stratiform precipitation while the LMME has more convective precipitation. Finally, differences in precipitation between the HMME and LMME can be traced to their differences in the SST simulations via the local and remote air-sea interaction.

  12. Adjusted monthly temperature and precipitation values for Guinea Conakry (1941-2010) using HOMER.

    Science.gov (United States)

    Aguilar, Enric; Aziz Barry, Abdoul; Mestre, Olivier

    2013-04-01

    Africa is a data sparse region and there are very few studies presenting homogenized monthly records. In this work, we introduce a dataset consisting of 12 stations spread over Guinea Conakry containing daily values of maximum and minimum temperature and accumulated rainfall for the period 1941-2010. The daily values have been quality controlled using R-Climdex routines, plus other interactive quality control applications, coded by the authors. After applying the different tests, more than 200 daily values were flagged as doubtful and carefully checked against the statistical distribution of the series and the rest of the dataset. Finally, 40 values were modified or set to missing and the rest were validated. The quality controlled daily dataset was used to produce monthly means and homogenized with HOMER, a new R-pacakge which includes the relative methods that performed better in the experiments conducted in the framework of the COST-HOME action. A total number of 38 inhomogeneities were found for temperature. As a total of 788 years of data were analyzed, the average ratio was one break every 20.7 years. The station with a larger number of inhomogeneities was Conakry (5 breaks) and one station, Kissidougou, was identified as homogeneous. The average number of breaks/station was 3.2. The mean value of the monthly factors applied to maximum (minimum) temperature was 0.17 °C (-1.08 °C) . For precipitation, due to the demand of a denser network to correctly homogenize this variable, only two major inhomogeneities in Conakry (1941-1961, -12%) and Kindia (1941-1976, -10%) were corrected. The adjusted dataset was used to compute regional series for the three variables and trends for the 1941-2010 period. The regional mean has been computed by simply averaging anomalies to 1971-2000 of the 12 time series. Two different versions have been obtained: a first one (A) makes use of the missing values interpolation made by HOMER (so all annual values in the regional series

  13. Monthly Summaries of the Global Historical Climatology Network - Daily (GHCN-D)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly Summaries of Global Historical Climatology Network (GHCN)-Daily is a dataset derived from GHCN-Daily. The data are produced by computing simple averages or...

  14. Negative soil moisture-precipitation feedback in dry and wet regions.

    Science.gov (United States)

    Yang, Lingbin; Sun, Guoqing; Zhi, Lu; Zhao, Jianjun

    2018-03-05

    Soil moisture-precipitation (SM-P) feedback significantly influences the terrestrial water and energy cycles. However, the sign of the feedback and the associated physical mechanism have been debated, leaving a research gap regarding global water and climate changes. Based on Koster's framework, we estimate SM-P feedback using satellite remote sensing and ground observation data sets. Methodologically, the sign of the feedback is identified by the correlation between monthly soil moisture and next-month precipitation. The physical mechanism is investigated through coupling precipitation and soil moisture (P-SM), soil moisture ad evapotranspiration (SM-E) and evapotranspiration and precipitation (E-P) correlations. Our results demonstrate that although positive SM-P feedback is predominant over land, non-negligible negative feedback occurs in dry and wet regions. Specifically, 43.75% and 40.16% of the negative feedback occurs in the arid and humid climate zones. Physically, negative SM-P feedback depends on the SM-E correlation. In dry regions, evapotranspiration change is soil moisture limited. In wet regions, evapotranspiration change is energy limited. We conclude that the complex SM-E correlation results in negative SM-P feedback in dry and wet regions, and the cause varies based on the environmental and climatic conditions.

  15. Amazon River Basin Precipitation, 1972-1992

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: The precipitation data is 0.2 degree gridded monthly precipitation data based upon monthly rain data from Peru and Bolivia and daily rain data from Brazil....

  16. Impact of Precipitating Ice Hydrometeors on Longwave Radiative Effect Estimated by a Global Cloud-System Resolving Model

    Science.gov (United States)

    Chen, Ying-Wen; Seiki, Tatsuya; Kodama, Chihiro; Satoh, Masaki; Noda, Akira T.

    2018-02-01

    Satellite observation and general circulation model (GCM) studies suggest that precipitating ice makes nonnegligible contributions to the radiation balance of the Earth. However, in most GCMs, precipitating ice is diagnosed and its radiative effects are not taken into account. Here we examine the longwave radiative impact of precipitating ice using a global nonhydrostatic atmospheric model with a double-moment cloud microphysics scheme. An off-line radiation model is employed to determine cloud radiative effects according to the amount and altitude of each type of ice hydrometeor. Results show that the snow radiative effect reaches 2 W m-2 in the tropics, which is about half the value estimated by previous studies. This effect is strongly dependent on the vertical separation of ice categories and is partially generated by differences in terminal velocities, which are not represented in GCMs with diagnostic precipitating ice. Results from sensitivity experiments that artificially change the categories and altitudes of precipitating ice show that the simulated longwave heating profile and longwave radiation field are sensitive to the treatment of precipitating ice in models. This study emphasizes the importance of incorporating appropriate treatments for the radiative effects of precipitating ice in cloud and radiation schemes in GCMs in order to capture the cloud radiative effects of upper level clouds.

  17. A CloudSat-CALIPSO View of Cloud and Precipitation Properties Across Cold Fronts over the Global Oceans

    Science.gov (United States)

    Naud, Catherine M.; Posselt, Derek J.; van den Heever, Susan C.

    2015-01-01

    The distribution of cloud and precipitation properties across oceanic extratropical cyclone cold fronts is examined using four years of combined CloudSat radar and CALIPSO lidar retrievals. The global annual mean cloud and precipitation distributions show that low-level clouds are ubiquitous in the post frontal zone while higher-level cloud frequency and precipitation peak in the warm sector along the surface front. Increases in temperature and moisture within the cold front region are associated with larger high-level but lower mid-/low level cloud frequencies and precipitation decreases in the cold sector. This behavior seems to be related to a shift from stratiform to convective clouds and precipitation. Stronger ascent in the warm conveyor belt tends to enhance cloudiness and precipitation across the cold front. A strong temperature contrast between the warm and cold sectors also encourages greater post-cold-frontal cloud occurrence. While the seasonal contrasts in environmental temperature, moisture, and ascent strength are enough to explain most of the variations in cloud and precipitation across cold fronts in both hemispheres, they do not fully explain the differences between Northern and Southern Hemisphere cold fronts. These differences are better explained when the impact of the contrast in temperature across the cold front is also considered. In addition, these large-scale parameters do not explain the relatively large frequency in springtime post frontal precipitation.

  18. Climate Prediction Center (CPC) Global Monthly Leaky Bucket Soil Moisture Analysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly global soil moisture, runoff, and evaporation data sets produced by the Leaky Bucket model at 0.5? ? 0.5? resolution for the period from 1948 to the present....

  19. Environmental isotope data no.1: World survey of isotope concentration in precipitation (1953-1963)

    International Nuclear Information System (INIS)

    1969-01-01

    This volume reports environmental isotope (tritium, deuterium and oxygen-18) concentrations in monthly samples of precipitation taken by a global network of 155 stations in the period 1953-1963. Selected meteorological data (amount of precipitation, vapour pressure and temperature) are presented to aid the user in hydrological and hydrometerological studies. The collection of the precipitation samples is carried out by the meteorological services of 65 countries and territories. Analyses of the network samples are done in co-operating laboratories in Canada, Denmark, India, Israel, New Zealand, Sweden and the United States of America and in the IAEA laboratory in Vienna. 4 refs, 2 figs

  20. Satellite-Based Precipitation Datasets

    Science.gov (United States)

    Munchak, S. J.; Huffman, G. J.

    2017-12-01

    Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

  1. Implementing a Global Tool for Mercy Corps Based on Spatially Continuous Precipitation Analysis for Resiliency Monitoring and Measuring at the Community-Scale

    Science.gov (United States)

    Tomlin, J. N.; El-Behaedi, R.; McCartney, S.; Lingo, R.; Thieme, A.

    2017-12-01

    Global water resources are important for societies, economies, and the environment. In Niger, limited water resources restrict the expansion of agriculture and communities. Mercy Corps currently works in over 40 countries around the world to address a variety of stresses which include water resources and building long-term food resilience. As Mercy Corps seeks to integrate the use of Earth observations, NASA has established a partnership to help facilitate this effort incorporating Tropical Rainfall Measuring Mission (TRMM), Global Precipitation Measurement (GPM), and Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data to create a standardized precipitation index that highlights low and high rainfall from 1981 - 2016. The team created a Google Earth Engine tool that combines precipitation data with other metrics of stress in Niger. The system is designed to be able to incorporate groundwater storage data as it becomes available. This tool allows for near real-time updates of trends in precipitation and improves Mercy Corps' ability to spatially evaluate changes in resiliency by monitoring shocks and stressors.

  2. Precipitation variability increases in a warmer climate.

    Science.gov (United States)

    Pendergrass, Angeline G; Knutti, Reto; Lehner, Flavio; Deser, Clara; Sanderson, Benjamin M

    2017-12-21

    Understanding changes in precipitation variability is essential for a complete explanation of the hydrologic cycle's response to warming and its impacts. While changes in mean and extreme precipitation have been studied intensively, precipitation variability has received less attention, despite its theoretical and practical importance. Here, we show that precipitation variability in most climate models increases over a majority of global land area in response to warming (66% of land has a robust increase in variability of seasonal-mean precipitation). Comparing recent decades to RCP8.5 projections for the end of the 21 st century, we find that in the global, multi-model mean, precipitation variability increases 3-4% K -1 globally, 4-5% K -1 over land and 2-4% K -1 over ocean, and is remarkably robust on a range of timescales from daily to decadal. Precipitation variability increases by at least as much as mean precipitation and less than moisture and extreme precipitation for most models, regions, and timescales. We interpret this as being related to an increase in moisture which is partially mitigated by weakening circulation. We show that changes in observed daily variability in station data are consistent with increased variability.

  3. UC Irvine CHRS Real-time Global Satellite Precipitation Monitoring System (G-WADI PERSIANN-CCS GeoServer) for Hydrometeorological Applications

    Science.gov (United States)

    Sorooshian, S.; Hsu, K. L.; Gao, X.; Imam, B.; Nguyen, P.; Braithwaite, D.; Logan, W. S.; Mishra, A.

    2015-12-01

    The G-WADI Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) GeoServer has been successfully developed by the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California Irvine in collaboration with the UNESCO's International Hydrological Programme (IHP) and a number of its international centers. The system employs state-of-the-art technologies in remote sensing and artificial intelligence to estimate precipitation globally from satellite imagery in real-time and high spatiotemporal resolution (4km, hourly). It offers graphical tools and data service to help the user in emergency planning and management for natural disasters related to hydrological processes. The G-WADI PERSIANN-CCS GeoServer has been upgraded with new user-friendly functionalities. The precipitation data generated by the GeoServer is disseminated to the user community through support provided by ICIWaRM (The International Center for Integrated Water Resources Management), UNESCO and UC Irvine. Recently a number of new applications for mobile devices have been developed by our students. The RainMapper has been available on App Store and Google Play for the real-time PERSIANN-CCS observations. A global crowd sourced rainfall reporting system named iRain has also been developed to engage the public globally to provide qualitative information about real-time precipitation in their location which will be useful in improving the quality of the PERSIANN-CCS data. A number of recent examples of the application and use of the G-WADI PERSIANN-CCS GeoServer information will also be presented.

  4. Prediction of monthly average global solar radiation based on statistical distribution of clearness index

    International Nuclear Information System (INIS)

    Ayodele, T.R.; Ogunjuyigbe, A.S.O.

    2015-01-01

    In this paper, probability distribution of clearness index is proposed for the prediction of global solar radiation. First, the clearness index is obtained from the past data of global solar radiation, then, the parameters of the appropriate distribution that best fit the clearness index are determined. The global solar radiation is thereafter predicted from the clearness index using inverse transformation of the cumulative distribution function. To validate the proposed method, eight years global solar radiation data (2000–2007) of Ibadan, Nigeria are used to determine the parameters of appropriate probability distribution for clearness index. The calculated parameters are then used to predict the future monthly average global solar radiation for the following year (2008). The predicted values are compared with the measured values using four statistical tests: the Root Mean Square Error (RMSE), MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error) and the coefficient of determination (R"2). The proposed method is also compared to the existing regression models. The results show that logistic distribution provides the best fit for clearness index of Ibadan and the proposed method is effective in predicting the monthly average global solar radiation with overall RMSE of 0.383 MJ/m"2/day, MAE of 0.295 MJ/m"2/day, MAPE of 2% and R"2 of 0.967. - Highlights: • Distribution of clearnes index is proposed for prediction of global solar radiation. • The clearness index is obtained from the past data of global solar radiation. • The parameters of distribution that best fit the clearness index are determined. • Solar radiation is predicted from the clearness index using inverse transformation. • The method is effective in predicting the monthly average global solar radiation.

  5. Soil response to long-term projections of extreme temperature and precipitation in the southern La Plata Basin

    Science.gov (United States)

    Pántano, Vanesa C.; Penalba, Olga C.

    2017-12-01

    Projected changes were estimated considering the main variables which take part in soil-atmosphere interaction. The analysis was focused on the potential impact of these changes on soil hydric condition under extreme precipitation and evapotranspiration, using the combination of Global Climate Models (GCMs) and observational data. The region of study is the southern La Plata Basin that covers part of Argentine territory, where rainfed agriculture production is one of the most important economic activities. Monthly precipitation and maximum and minimum temperatures were used from high quality-controlled observed data from 46 meteorological stations and the ensemble of seven CMIP5 GCMs in two periods: 1970-2005 and 2065-2100. Projected changes in monthly effective temperature and precipitation were analysed. These changes were combined with observed series for each probabilistic interval. The result was used as input variables for the water balance model in order to obtain consequent soil hydric condition (deficit or excess). Effective temperature and precipitation are expected to increase according to the projections of GCMs, with few exceptions. The analysis revealed increase (decrease) in the prevalence of evapotranspiration over precipitation, during spring (winter). Projections for autumn months show precipitation higher than potential evapotranspiration more frequently. Under dry extremes, the analysis revealed higher projected deficit conditions, impacting on crop development. On the other hand, under wet extremes, excess would reach higher values only in particular months. During December, projected increase in temperatures reduces the impact of extreme high precipitation but favours deficit conditions, affecting flower-fructification stage of summer crops.

  6. Modelled Precipitation Over Greenland

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the annual total precipitation from 1985 to 1999 and monthly total precipitation from January 1985 to December 1999. The data is derived from...

  7. United States Historical Climatology Network (US HCN) monthly temperature and precipitation data

    Energy Technology Data Exchange (ETDEWEB)

    Daniels, R.C. [ed.] [Univ. of Tennessee, Knoxville, TN (United States). Energy, Environment and Resources Center; Boden, T.A. [ed.] [Oak Ridge National Lab., TN (United States); Easterling, D.R.; Karl, T.R.; Mason, E.H.; Hughes, P.Y.; Bowman, D.P. [National Climatic Data Center, Asheville, NC (United States)

    1996-01-11

    This document describes a database containing monthly temperature and precipitation data for 1221 stations in the contiguous United States. This network of stations, known as the United States Historical Climatology Network (US HCN), and the resulting database were compiled by the National Climatic Data Center, Asheville, North Carolina. These data represent the best available data from the United States for analyzing long-term climate trends on a regional scale. The data for most stations extend through December 31, 1994, and a majority of the station records are serially complete for at least 80 years. Unlike many data sets that have been used in past climate studies, these data have been adjusted to remove biases introduced by station moves, instrument changes, time-of-observation differences, and urbanization effects. These monthly data are available free of charge as a numeric data package (NDP) from the Carbon Dioxide Information Analysis Center. The NDP includes this document and 27 machine-readable data files consisting of supporting data files, a descriptive file, and computer access codes. This document describes how the stations in the US HCN were selected and how the data were processed, defines limitations and restrictions of the data, describes the format and contents of the magnetic media, and provides reprints of literature that discuss the editing and adjustment techniques used in the US HCN.

  8. Precipitation regime classification for the Mojave Desert: Implications for fire occurrence

    Science.gov (United States)

    Tagestad, Jerry; Brooks, Matthew L.; Cullinan, Valerie; Downs, Janelle; McKinley, Randy

    2016-01-01

    Long periods of drought or above-average precipitation affect Mojave Desert vegetation condition, biomass and susceptibility to fire. Changes in the seasonality of precipitation alter the likelihood of lightning, a key ignition source for fires. The objectives of this study were to characterize the relationship between recent, historic, and future precipitation patterns and fire. Classifying monthly precipitation data from 1971 to 2010 reveals four precipitation regimes: low winter/low summer, moderate winter/moderate summer, high winter/low summer and high winter/high summer. Two regimes with summer monsoonal precipitation covered only 40% of the Mojave Desert ecoregion but contain 88% of the area burned and 95% of the repeat burn area. Classifying historic precipitation for early-century (wet) and mid-century (drought) periods reveals distinct shifts in regime boundaries. Early-century results are similar to current, while the mid-century results show a sizeable reduction in area of regimes with a strong monsoonal component. Such a shift would suggest that fires during the mid-century period would be minimal and anecdotal records confirm this. Predicted precipitation patterns from downscaled global climate models indicate numerous epochs of high winter precipitation, inferring higher fire potential for many multi-decade periods during the next century.

  9. Global Changes of the Water Cycle Intensity

    Science.gov (United States)

    Bosilovich, Michael G.; Schubert, Siegfried D.; Walker, Gregory K.

    2003-01-01

    In this study, we evaluate numerical simulations of the twentieth century climate, focusing on the changes in the intensity of the global water cycle. A new diagnostic of atmospheric water vapor cycling rate is developed and employed, that relies on constituent tracers predicted at the model time step. This diagnostic is compared to a simplified traditional calculation of cycling rate, based on monthly averages of precipitation and total water content. The mean sensitivity of both diagnostics to variations in climate forcing is comparable. However, the new diagnostic produces systematically larger values and more variability than the traditional average approach. Climate simulations were performed using SSTs of the early (1902-1921) and late (1979- 1998) twentieth century along with the appropriate C02 forcing. In general, the increase of global precipitation with the increases in SST that occurred between the early and late twentieth century is small. However, an increase of atmospheric temperature leads to a systematic increase in total precipitable water. As a result, the residence time of water in the atmosphere increased, indicating a reduction of the global cycling rate. This result was explored further using a number of 50-year climate simulations from different models forced with observed SST. The anomalies and trends in the cycling rate and hydrologic variables of different GCMs are remarkably similar. The global annual anomalies of precipitation show a significant upward trend related to the upward trend of surface temperature, during the latter half of the twentieth century. While this implies an increase in the hydrologic cycle intensity, a concomitant increase of total precipitable water again leads to a decrease in the calculated global cycling rate. An analysis of the land/sea differences shows that the simulated precipitation over land has a decreasing trend while the oceanic precipitation has an upward trend consistent with previous studies and the

  10. Analysis of a global database containing tritium in precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Buckley, R. L. [Savannah River Site (SRS), Aiken, SC (United States); Rabun, R. L. [Savannah River Site (SRS), Aiken, SC (United States); Heath, M. [Savannah River Site (SRS), Aiken, SC (United States)

    2016-02-17

    The International Atomic Energy Agency (IAEA) directed the collection of tritium in water samples from the mid-1950s to 2009. The Global Network of Isotopes in Precipitation (GNIP) data examined the airborne movement of isotope releases to the environment, with an objective of collecting spatial data on the isotope content of precipitation across the globe. The initial motivation was to monitor atmospheric thermonuclear test fallout through tritium, deuterium, and oxygen isotope concentrations, but after the 1970s the focus changed to being an observation network of stable hydrogen and oxygen isotope data for hydrologic studies. The GNIP database provides a wealth of tritium data collections over a long period of time. The work performed here primarily examined data features in the past 30 years (after much of the effects of above-ground nuclear testing in the late 1950s to early 1960s decayed away), revealing potentially unknown tritium sources. The available data at GNIP were reorganized to allow for evaluation of trends in the data both temporally and spatially. Several interesting cases were revealed, including relatively high measured concentrations in the Atlantic and Indian Oceans, Russia, Norway, as well as an increase in background concentration at a collector in South Korea after 2004. Recent data from stations in the southeastern United States nearest to the Savannah River Site do not indicate any high values. Meteorological impacts have not been considered in this study. Further research to assess the likely source location of interesting cases using transport simulations and/or literature searches is warranted.

  11. Homogenization of monthly precipitation time series in Croatia

    Czech Academy of Sciences Publication Activity Database

    Zahradníček, Pavel; Rasol, D.; Cindric, K.; Štěpánek, Petr

    2014-01-01

    Roč. 34, č. 14 (2014), s. 3671-3682 ISSN 0899-8418 R&D Projects: GA MŠk(CZ) EE2.3.20.0248; GA MŠk(CZ) EE2.4.31.0056 Institutional support: RVO:67179843 Keywords : homogenization * Croatia * precipitation * inhomogeneities * break points Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 3.157, year: 2014

  12. Correlation between δ18O in precipitation and surface air temperature on different time-scale in China

    International Nuclear Information System (INIS)

    Zhang Lin; Chen Zongyu; Nie Zhenlong; Liu Fuliang; Jia Yankun; Zhang Xiangyang

    2008-01-01

    The relation between isotopic compositions of precipitation and surface air temperature provides a unique tool for paleoclimate studies, among which the relation between long term changes in δ 18 O of precipitation and surface air temperature at different stations or in a given location seems to be the most appropriate to paleoclimatic reconstructions. Analysis was conducted on monthly and annual mean δ 18 O content of precipitation and surface air temperature at spatial and fixed locations by using the data of China (1985-2002) in Global Network of Isotopes in Precipitation (GNIP) Database. This study shows that there is a positive correlation between δ 18 O of precipitation and surface air temperature for stations located in north of 34 degree-36 degree N latitudes. The seasonal δ 18 O-temperature gradient derived from the monthly data of 12 stations in northern China is about 0.034% degree C -1 . The δ 18 O-temperature gradient, however, derived from the long term annual mean data of 13 stations, is about 0.052% degree C -1 , which is substantially larger than the seasonal gradient. (authors)

  13. Significant uncertainty in global scale hydrological modeling from precipitation data errors

    Science.gov (United States)

    Sperna Weiland, Frederiek C.; Vrugt, Jasper A.; van Beek, Rens (L.) P. H.; Weerts, Albrecht H.; Bierkens, Marc F. P.

    2015-10-01

    In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we focus on large-scale hydrologic modeling and analyze the effect of parameter and rainfall data uncertainty on simulated discharge dynamics with the global hydrologic model PCR-GLOBWB. We use three rainfall data products; the CFSR reanalysis, the ERA-Interim reanalysis, and a combined ERA-40 reanalysis and CRU dataset. Parameter uncertainty is derived from Latin Hypercube Sampling (LHS) using monthly discharge data from five of the largest river systems in the world. Our results demonstrate that the default parameterization of PCR-GLOBWB, derived from global datasets, can be improved by calibrating the model against monthly discharge observations. Yet, it is difficult to find a single parameterization of PCR-GLOBWB that works well for all of the five river basins considered herein and shows consistent performance during both the calibration and evaluation period. Still there may be possibilities for regionalization based on catchment similarities. Our simulations illustrate that parameter uncertainty constitutes only a minor part of predictive uncertainty. Thus, the apparent dichotomy between simulations of global-scale hydrologic behavior and actual data cannot be resolved by simply increasing the model complexity of PCR-GLOBWB and resolving sub-grid processes. Instead, it would be more productive to improve the characterization of global rainfall amounts at spatial resolutions of 0.5° and smaller.

  14. Self-organizing map network-based precipitation regionalization for the Tibetan Plateau and regional precipitation variability

    Science.gov (United States)

    Wang, Nini; Yin, Jianchuan

    2017-12-01

    A precipitation-based regionalization for the Tibetan Plateau (TP) was investigated for regional precipitation trend analysis and frequency analysis using data from 1113 grid points covering the period 1900-2014. The results utilizing self-organizing map (SOM) network suggest that four clusters of precipitation coherent zones can be identified, including the southwestern edge, the southern edge, the southeastern region, and the north central region. Regionalization results of the SOM network satisfactorily represent the influences of the atmospheric circulation systems such as the East Asian summer monsoon, the south Asian summer monsoon, and the mid-latitude westerlies. Regionalization results also well display the direct impacts of physical geographical features of the TP such as orography, topography, and land-sea distribution. Regional-scale annual precipitation trend as well as regional differences of annual and seasonal total precipitation were investigated by precipitation index such as precipitation concentration index (PCI) and Standardized Anomaly Index (SAI). Results demonstrate significant negative long-term linear trends in southeastern TP and the north central part of the TP, indicating arid and semi-arid regions in the TP are getting drier. The empirical mode decomposition (EMD) method shows an evolution of the main cycle with 4 and 12 months for all the representative grids of four sub-regions. The cross-wavelet analysis suggests that predominant and effective period of Indian Ocean Dipole (IOD) on monthly precipitation is around ˜12 months, except for the representative grid of the northwestern region.

  15. Detecting Climate Signals in Precipitation Extremes from TRMM (1998-2013) - Increasing Contrast Between Wet and Dry Extremes During the "Global Warming Hiatus"

    Science.gov (United States)

    Wu, Huey-Tzu Jenny; Lau, William K.-M.

    2016-01-01

    We investigate changes in daily precipitation extremes using Tropical Rainfall Measuring Mission (TRMM) data (1998-2013), which coincides with the "global warming hiatus." Results show a change in probability distribution functions of local precipitation events (LPEs) during this period consistent with previous global warming studies, indicating increasing contrast between wet and dry extremes, with more intense LPE, less moderate LPE, and more dry (no rain) days globally. Analyses for land and ocean separately reveal more complex and nuanced changes over land, characterized by a strong positive trend (+12.0% per decade, 99% confidence level (c.l.)) in frequency of extreme LPEs over the Northern Hemisphere extratropics during the wet season but a negative global trend (-6.6% per decade, 95% c.l.) during the dry season. A significant global drying trend (3.2% per decade, 99% c.l.) over land is also found during the dry season. Regions of pronounced increased dry events include western and central U.S., northeastern Asia, and Southern Europe/Mediterranean.

  16. Monthly Rainfall Erosivity Assessment for Switzerland

    Science.gov (United States)

    Schmidt, Simon; Meusburger, Katrin; Alewell, Christine

    2016-04-01

    Water erosion is crucially controlled by rainfall erosivity, which is quantified out of the kinetic energy of raindrop impact and associated surface runoff. Rainfall erosivity is often expressed as the R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). Just like precipitation, the rainfall erosivity of Switzerland has a characteristic seasonal dynamic throughout the year. This inter-annual variability is to be assessed by a monthly and seasonal modelling approach. We used a network of 86 precipitation gauging stations with a 10-minute temporal resolution to calculate long-term average monthly R-factors. Stepwise regression and Monte Carlo Cross Validation (MCCV) was used to select spatial covariates to explain the spatial pattern of R-factor for each month across Switzerland. The regionalized monthly R-factor is mapped by its individual regression equation and the ordinary kriging interpolation of its residuals (Regression-Kriging). As covariates, a variety of precipitation indicator data has been included like snow height, a combination of hourly gauging measurements and radar observations (CombiPrecip), mean monthly alpine precipitation (EURO4M-APGD) and monthly precipitation sums (Rhires). Topographic parameters were also significant explanatory variables for single months. The comparison of all 12 monthly rainfall erosivity maps showed seasonality with highest rainfall erosivity in summer (June, July, and August) and lowest rainfall erosivity in winter months. Besides the inter-annual temporal regime, a seasonal spatial variability was detectable. Spatial maps of monthly rainfall erosivity are presented for the first time for Switzerland. The assessment of the spatial and temporal dynamic behaviour of the R-factor is valuable for the identification of more susceptible seasons and regions as well as for the application of selective erosion control measures. A combination with monthly vegetation

  17. On the long-range dependence properties of annual precipitation using a global network of instrumental measurements

    Science.gov (United States)

    Tyralis, Hristos; Dimitriadis, Panayiotis; Koutsoyiannis, Demetris; O'Connell, Patrick Enda; Tzouka, Katerina; Iliopoulou, Theano

    2018-01-01

    The long-range dependence (LRD) is considered an inherent property of geophysical processes, whose presence increases uncertainty. Here we examine the spatial behaviour of LRD in precipitation by regressing the Hurst parameter estimate of mean annual precipitation instrumental data which span from 1916-2015 and cover a big area of the earth's surface on location characteristics of the instrumental data stations. Furthermore, we apply the Mann-Kendall test under the LRD assumption (MKt-LRD) to reassess the significance of observed trends. To summarize the results, the LRD is spatially clustered, it seems to depend mostly on the location of the stations, while the predictive value of the regression model is good. Thus when investigating for LRD properties we recommend that the local characteristics should be considered. The application of the MKt-LRD suggests that no significant monotonic trend appears in global precipitation, excluding the climate type D (snow) regions in which positive significant trends appear.

  18. Using Extreme Tropical Precipitation Statistics to Constrain Future Climate States

    Science.gov (United States)

    Igel, M.; Biello, J. A.

    2017-12-01

    Tropical precipitation is characterized by a rapid growth in mean intensity as the column humidity increases. This behavior is examined in both a cloud resolving model and with high-resolution observations of precipitation and column humidity from CloudSat and AIRS, respectively. The model and the observations exhibit remarkable consistency and suggest a new paradigm for extreme precipitation. We show that the total precipitation can be decomposed into a product of contributions from a mean intensity, a probability of precipitation, and a global PDF of column humidity values. We use the modeling and observational results to suggest simple, analytic forms for each of these functions. The analytic representations are then used to construct a simple expression for the global accumulated precipitation as a function of the parameters of each of the component functions. As the climate warms, extreme precipitation intensity and global precipitation are expected to increase, though at different rates. When these predictions are incorporated into the new analytic expression for total precipitation, predictions for changes due to global warming to the probability of precipitation and the PDF of column humidity can be made. We show that strong constraints can be imposed on the future shape of the PDF of column humidity but that only weak constraints can be set on the probability of precipitation. These are largely imposed by the intensification of extreme precipitation. This result suggests that understanding precisely how extreme precipitation responds to climate warming is critical to predicting other impactful properties of global hydrology. The new framework can also be used to confirm and discount existing theories for shifting precipitation.

  19. Intercomparison of PERSIANN-CDR and TRMM-3B42V7 precipitation estimates at monthly and daily time scales

    Science.gov (United States)

    Katiraie-Boroujerdy, Pari-Sima; Akbari Asanjan, Ata; Hsu, Kuo-lin; Sorooshian, Soroosh

    2017-09-01

    In the first part of this paper, monthly precipitation data from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission 3B42 algorithm Version 7 (TRMM-3B42V7) are evaluated over Iran using the Generalized Three-Cornered Hat (GTCH) method which is self-sufficient of reference data as input. Climate Data Unit (CRU) is added to the GTCH evaluations as an independent gauge-based dataset thus, the minimum requirement of three datasets for the model is satisfied. To ensure consistency of all datasets, the two satellite products were aggregated to 0.5° spatial resolution, which is the minimum resolution of CRU. The results show that the PERSIANN-CDR has higher Signal to Noise Ratio (SNR) than TRMM-3B42V7 for the monthly rainfall estimation, especially in the northern half of the country. All datasets showed low SNR in the mountainous area of southwestern Iran, as well as the arid parts in the southeast region of the country. Additionally, in order to evaluate the efficacy of PERSIANN-CDR and TRMM-3B42V7 in capturing extreme daily-precipitation amounts, an in-situ rain-gauge dataset collected by the Islamic Republic of the Iran Meteorological Organization (IRIMO) was employed. Given the sparsity of the rain gauges, only 0.25° pixels containing three or more gauges were used for this evaluation. There were 228 such pixels where daily and extreme rainfall from PERSIANN-CDR and TRMM-3B42V7 could be compared. However, TRMM-3B42V7 overestimates most of the intensity indices (correlation coefficients; R between 0.7648-0.8311, Root Mean Square Error; RMSE between 3.29mm/day-21.2mm/5day); PERSIANN-CDR underestimates these extremes (R between 0.6349-0.7791 and RMSE between 3.59mm/day-30.56mm/5day). Both satellite products show higher correlation coefficients and lower RMSEs for the annual mean of consecutive dry spells than wet spells. The results show that TRMM-3B42V7

  20. On the Precipitation and Precipitation Change in Alaska

    Directory of Open Access Journals (Sweden)

    Gerd Wendler

    2017-12-01

    Full Text Available Alaska observes very large differences in precipitation throughout the state; southeast Alaska experiences consistently wet conditions, while northern Arctic Alaska observes very dry conditions. The maximum mean annual precipitation of 5727 mm is observed in the southeastern panhandle at Little Port Arthur, while the minimum of 92 mm occurs on the North Slope at Kuparuk. Besides explaining these large differences due to geographic and orographic location, we discuss the changes in precipitation with time. Analyzing the 18 first-order National Weather Service stations, we found that the total average precipitation in the state increased by 17% over the last 67 years. The observed changes in precipitation are furthermore discussed as a function of the observed temperature increase of 2.1 °C, the mean temperature change of the 18 stations over the same period. This observed warming of Alaska is about three times the magnitude of the mean global warming and allows the air to hold more water vapor. Furthermore, we discuss the effect of the Pacific Decadal Oscillation (PDO, which has a strong influence on both the temperature and precipitation in Alaska.

  1. Evaluating Satellite Products for Precipitation Estimation in Mountain Regions: A Case Study for Nepal

    Directory of Open Access Journals (Sweden)

    Tarendra Lakhankar

    2013-08-01

    Full Text Available Precipitation in mountain regions is often highly variable and poorly observed, limiting abilities to manage water resource challenges. Here, we evaluate remote sensing and ground station-based gridded precipitation products over Nepal against weather station precipitation observations on a monthly timescale. We find that the Tropical Rainfall Measuring Mission (TRMM 3B-43 precipitation product exhibits little mean bias and reasonable skill in giving precipitation over Nepal. Compared to station observations, the TRMM precipitation product showed an overall Nash-Sutcliffe efficiency of 0.49, which is similar to the skill of the gridded station-based product Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE. The other satellite precipitation products considered (Global Satellite Mapping of Precipitation (GSMaP, the Climate Prediction Center Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS were less skillful, as judged by Nash-Sutcliffe efficiency, and, on average, substantially underestimated precipitation compared to station observations, despite their, in some cases, higher nominal spatial resolution compared to TRMM. None of the products fully captured the dependence of mean precipitation on elevation seen in the station observations. Overall, the TRMM product is promising for use in water resources applications.

  2. Properties of Extreme Precipitation and Their Uncertainties in 3-year GPM Precipitation Radar Data

    Science.gov (United States)

    Liu, N.; Liu, C.

    2017-12-01

    Extreme high precipitation rates are often related to flash floods and have devastating impacts on human society and the environments. To better understand these rare events, 3-year Precipitation Features (PFs) are defined by grouping the contiguous areas with nonzero near-surface precipitation derived using Global Precipitation Measurement (GPM) Ku band Precipitation Radar (KuPR). The properties of PFs with extreme precipitation rates greater than 20, 50, 100 mm/hr, such as the geographical distribution, volumetric precipitation contribution, seasonal and diurnal variations, are examined. In addition to the large seasonal and regional variations, the rare extreme precipitation rates often have a larger contribution to the local total precipitation. Extreme precipitation rates occur more often over land than over ocean. The challenges in the retrieval of extreme precipitation might be from the attenuation correction and large uncertainties in the Z-R relationships from near-surface radar reflectivity to precipitation rates. These potential uncertainties are examined by using collocated ground based radar reflectivity and precipitation retrievals.

  3. Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

    Science.gov (United States)

    Zeng, Fanwei; Collatz, George James; Pinzon, Jorge E.; Ivanoff, Alvaro

    2013-01-01

    Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

  4. The effect of ambient air temperature and precipitation on monthly counts of salmonellosis in four regions of Kazakhstan, Central Asia, in 2000-2010.

    Science.gov (United States)

    Grjibovski, A M; Kosbayeva, A; Menne, B

    2014-03-01

    We studied associations between monthly counts of laboratory-confirmed cases of salmonellosis, ambient air temperature and precipitation in four settings in Kazakhstan. We observed a linear association between the number of cases of salmonellosis and mean monthly temperature during the same months only in Astana: an increase of 1°C was associated with a 5·5% [95% confidence interval (CI) 2·2-8·8] increase in the number of cases. A similar association, although not reaching the level of significance was observed in the Southern Kazakhstan region (3·5%, 95% CI -2·1 to 9·1). Positive association with precipitation with lag 2 was found in Astana: an increase of 1 mm was associated with a 0·5% (95% CI 0·1-1·0) increase in the number of cases. A similar association, but with lag 0 was observed in Southern Kazakhstan region (0·6%, 95% CI 0·1-1·1). The results may have implications for the future patterns of salmonellosis in Kazakhstan with regard to climate change.

  5. Impact of Precipitation Fluctuation on Desert-Grassland ANPP

    Directory of Open Access Journals (Sweden)

    Liangxu Liu

    2016-11-01

    Full Text Available Precipitation change has significantly influenced annual net primary productivity (ANPP at either annual or seasonal scales in desert steppes in arid and semi-arid regions. In order to reveal the process of precipitation driving ANPP at different time scales, responses of different ANPP levels to the inter-annual and intra-annual precipitation fluctuations were analyzed. ANPP was reversed by building a ground reflectance spectrum model, from 2000 to 2015, using the normalized differential vegetation index of the Moderate-Resolution Imaging Spectroradiometer (MODIS-NDVI data at 250 m × 250 m spatial resolution. Since the description of the differently expressing forms of precipitation are not sufficient in former studies in order to overcome the deficiency of former studies, in this study, intra-annual precipitation fluctuations were analyzed not only with precipitation of May–August, June–August, July–August, and August, respectively, which have direct influence on vegetation productivity within the year, but quantitative description, vector precipitation (R, concentration ratio (Cd, and concentration period (D, were also used to describe the overall characteristics of intra-annual precipitation fluctuations. The concentration ratio and the maximum precipitation period of the intra-annual precipitation were represented by using monthly precipitation. The results showed that: (1 in the period from 1971 to 2015, the maximum annual precipitation is 3.76 times that of the minimum in the Urat desert steppe; (2 vector precipitation is more significantly related to ANPP (r = 0.7724, p = 0.000 compared to meteorological annual precipitation and real annual precipitation influence; and (3 annual precipitation is almost concentrated in 5–8 months and monthly precipitation accumulation has significantly effected ANPP, especially in the period of June–August, since the vegetation composition in the study area was mainly sub-shrubs and perennial

  6. Regionalizing Africa: Patterns of Precipitation Variability in Observations and Global Climate Models

    Science.gov (United States)

    Badr, Hamada S.; Dezfuli, Amin K.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.

    2016-01-01

    Many studies have documented dramatic climatic and environmental changes that have affected Africa over different time scales. These studies often raise questions regarding the spatial extent and regional connectivity of changes inferred from observations and proxies and/or derived from climate models. Objective regionalization offers a tool for addressing these questions. To demonstrate this potential, applications of hierarchical climate regionalizations of Africa using observations and GCM historical simulations and future projections are presented. First, Africa is regionalized based on interannual precipitation variability using Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data for the period 19812014. A number of data processing techniques and clustering algorithms are tested to ensure a robust definition of climate regions. These regionalization results highlight the seasonal and even month-to-month specificity of regional climate associations across the continent, emphasizing the need to consider time of year as well as research question when defining a coherent region for climate analysis. CHIRPS regions are then compared to those of five GCMs for the historic period, with a focus on boreal summer. Results show that some GCMs capture the climatic coherence of the Sahel and associated teleconnections in a manner that is similar to observations, while other models break the Sahel into uncorrelated subregions or produce a Sahel-like region of variability that is spatially displaced from observations. Finally, shifts in climate regions under projected twenty-first-century climate change for different GCMs and emissions pathways are examined. A projected change is found in the coherence of the Sahel, in which the western and eastern Sahel become distinct regions with different teleconnections. This pattern is most pronounced in high-emissions scenarios.

  7. Connecting Satellite-Based Precipitation Estimates to Users

    Science.gov (United States)

    Huffman, George J.; Bolvin, David T.; Nelkin, Eric

    2018-01-01

    Beginning in 1997, the Merged Precipitation Group at NASA Goddard has distributed gridded global precipitation products built by combining satellite and surface gauge data. This started with the Global Precipitation Climatology Project (GPCP), then the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), and recently the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG). This 20+-year (and on-going) activity has yielded an important set of insights and lessons learned for making state-of-the-art precipitation data accessible to the diverse communities of users. Merged-data products critically depend on the input sensors and the retrieval algorithms providing accurate, reliable estimates, but it is also important to provide ancillary information that helps users determine suitability for their application. We typically provide fields of estimated random error, and recently reintroduced the quality index concept at user request. Also at user request we have added a (diagnostic) field of estimated precipitation phase. Over time, increasingly more ancillary fields have been introduced for intermediate products that give expert users insight into the detailed performance of the combination algorithm, such as individual merged microwave and microwave-calibrated infrared estimates, the contributing microwave sensor types, and the relative influence of the infrared estimate.

  8. Beyond Precipitation: Physiographic Gradients Dictate the Relative Importance of Environmental Drivers on Savanna Vegetation

    Science.gov (United States)

    Campo-Bescós, Miguel A.; Muñoz-Carpena, Rafael; Kaplan, David A.; Southworth, Jane; Zhu, Likai; Waylen, Peter R.

    2013-01-01

    Background Understanding the drivers of large-scale vegetation change is critical to managing landscapes and key to predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to improve our understanding of the role, magnitude and spatial distribution of the key environmental factors driving vegetation change in southern African savanna, and how they vary across physiographic gradients. Methodology/Principal Findings We applied Dynamic Factor Analysis (DFA), a multivariate times series dimension reduction technique to ten years of monthly remote sensing data (MODIS-derived normalized difference vegetation index, NDVI) and a suite of environmental covariates: precipitation, mean and maximum temperature, soil moisture, relative humidity, fire and potential evapotranspiration. Monthly NDVI was described by cyclic seasonal variation with distinct spatiotemporal patterns in different physiographic regions. Results support existing work emphasizing the importance of precipitation, soil moisture and fire on NDVI, but also reveal overlooked effects of temperature and evapotranspiration, particularly in regions with higher mean annual precipitation. Critically, spatial distributions of the weights of environmental covariates point to a transition in the importance of precipitation and soil moisture (strongest in grass-dominated regions with precipitation950 mm). Conclusions/Significance We quantified the combined spatiotemporal effects of an available suite of environmental drivers on NDVI across a large and diverse savanna region. The analysis supports known drivers of savanna vegetation but also uncovers important roles of temperature and evapotranspiration. Results highlight the utility of applying the DFA approach to remote sensing products for regional analyses of landscape change in the context of global environmental change. With the dramatic increase in global change research, this methodology augurs well for

  9. Intercomparison of spaceborne precipitation radars and its applications in examining precipitation-topography relationships in the Tibetan Plateau

    Science.gov (United States)

    Tang, G.; Gao, J.; Long, D.

    2017-12-01

    Precipitation is one of the most important components in the water and energy cycles. Spaceborne radars are considered the most direct technology for observing precipitation from space since 1998. This study compares and evaluates the only three existing spaceborne precipitation radars, i.e., the Ku-band precipitation radar (TRMM PR), the W-band Cloud Profiling Radar (CloudSat CPR), and the Ku/Ka-band Dual-frequency Precipitation Radar (GPM DPR). In addition, TRMM PR and GPM DPR are evaluated against hourly rain gauge data in Mainland China. The Tibetan Plateau (TP) is known as the Earth's third pole where precipitation is affected profoundly by topography. However, ground gauges are extremely sparse in the TP, and spaceborne radars can provide valuable data with relatively high accuracy. The relationships between precipitation and topography over the TP are investigated using 17-year TRMM PR data and 2-year GPM DPR data, in combination with rain gauge data. Results indicate that: (1) DPR and PR agree with each other and correlate very well with gauges in Mainland China. DPR improves light precipitation detectability significantly compared with PR. However, DPR high sensitivity scans (HS) deviates from DPR normal and matched scans (NS and MS) and PR in the comparison based on global coincident events and rain gauges in China; (2) CPR outperforms the other two radars in terms of light precipitation detection. In terms of global snowfall estimation, DPR and CPR show very different global snowfall distributions originating from different frequencies, retrieval algorithms, and sampling characteristics; and (3) Precipitation generally decreases exponentially with increasing elevation in the TP. The precipitation-topography relationships are regressed using exponential fitting in seventeen river basins in the TP with good coefficients of determination. Due to the short time span of GPM DPR, the relationships based on GPM DPR data are less robust than those derived from

  10. Tritium time series in precipitation of Rm. Valcea, Romania.

    Science.gov (United States)

    Varlam, Carmen; Duliu, Octavian G; Faurescu, Ionut; Vagner, Irina; Faurescu, Denisa

    2016-01-01

    Following tritium concentration records in precipitation for the period 1999-2013 and tritium concentration behaviour during this period for the Ramnicu Valcea (Rm. Valcea) location, the tritium level of individual precipitations of the late spring and summer for the 2009-2013 period was investigated. Despite good correlation between monthly mean tritium concentrations and monthly mean precipitations over the 15-year period of observations (Pearson coefficient 0.87), the individual precipitations had no linear correlation between the tritium concentration and the amount of precipitation.

  11. Calculation of probability density functions for temperature and precipitation change under global warming

    International Nuclear Information System (INIS)

    Watterson, Ian G.

    2007-01-01

    Full text: he IPCC Fourth Assessment Report (Meehl ef al. 2007) presents multi-model means of the CMIP3 simulations as projections of the global climate change over the 21st century under several SRES emission scenarios. To assess the possible range of change for Australia based on the CMIP3 ensemble, we can follow Whetton etal. (2005) and use the 'pattern scaling' approach, which separates the uncertainty in the global mean warming from that in the local change per degree of warming. This study presents several ways of representing these two factors as probability density functions (PDFs). The beta distribution, a smooth, bounded, function allowing skewness, is found to provide a useful representation of the range of CMIP3 results. A weighting of models based on their skill in simulating seasonal means in the present climate over Australia is included. Dessai ef al. (2005) and others have used Monte-Carlo sampling to recombine such global warming and scaled change factors into values of net change. Here, we use a direct integration of the product across the joint probability space defined by the two PDFs. The result is a cumulative distribution function (CDF) for change, for each variable, location, and season. The median of this distribution provides a best estimate of change, while the 10th and 90th percentiles represent a likely range. The probability of exceeding a specified threshold can also be extracted from the CDF. The presentation focuses on changes in Australian temperature and precipitation at 2070 under the A1B scenario. However, the assumption of linearity behind pattern scaling allows results for different scenarios and times to be simply obtained. In the case of precipitation, which must remain non-negative, a simple modification of the calculations (based on decreases being exponential with warming) is used to avoid unrealistic results. These approaches are currently being used for the new CSIRO/ Bureau of Meteorology climate projections

  12. Consequences of 1.5 °C and 2 °C global warming levels for temperature and precipitation changes over Central Africa

    Science.gov (United States)

    Pokam Mba, Wilfried; Longandjo, Georges-Noel T.; Moufouma-Okia, Wilfran; Bell, Jean-Pierre; James, Rachel; Vondou, Derbetini A.; Haensler, Andreas; Fotso-Nguemo, Thierry C.; Merlin Guenang, Guy; Djiotang Tchotchou, Angennes Lucie; Kamsu-Tamo, Pierre H.; Takong, Ridick R.; Nikulin, Grigory; Lennard, Christopher J.; Dosio, Alessandro

    2018-05-01

    Discriminating climate impacts between 1.5 °C and 2 °C warming levels is particularly important for Central Africa, a vulnerable region where multiple biophysical, political, and socioeconomic stresses interact to constrain the region’s adaptive capacity. This study uses an ensemble of 25 transient Regional Climate Model (RCM) simulations from the CORDEX initiative, forced with the Representative Concentration Pathway (RCP) 8.5, to investigate the potential temperature and precipitation changes in Central Africa corresponding to 1.5 °C and 2 °C global warming levels. Global climate model simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5) are used to drive the RCMs and determine timing of the targeted global warming levels. The regional warming differs over Central Africa between 1.5 °C and 2 °C global warming levels. Whilst there are large uncertainties associated with projections at 1.5 °C and 2 °C, the 0.5 °C increase in global temperature is associated with larger regional warming response. Compared to changes in temperature, changes in precipitation are more heterogeneous and climate model simulations indicate a lack of consensus across the region, though there is a tendency towards decreasing seasonal precipitation in March–May, and a reduction of consecutive wet days. As a drought indicator, a significant increase in consecutive dry days was found. Consistent changes of maximum 5 day rainfall are also detected between 1.5 °C vs. 2 °C global warming levels.

  13. A Global Assessment of Runoff Sensitivity to Changes in Precipitation, Potential Evaporation, and Other Factors

    OpenAIRE

    Berghuijs, Wouter; Larsen, Joshua; van Emmerik, Tim; Woods, Ross

    2017-01-01

    Precipitation (P) and potential evaporation (Ep) are commonly studied drivers of changing freshwater availability, as aridity (Ep/P) explains ∼90% of the spatial differences in mean runoff across the globe. However, it is unclear if changes in aridity over time are also the most important cause for temporal changes in mean runoff and how this degree of importance varies regionally. We show that previous global assessments that address these questions do not properly account for changes due to...

  14. Global observed long-term changes in temperature and precipitation extremes: A review of progress and limitations in IPCC assessments and beyond

    OpenAIRE

    Lisa V. Alexander

    2016-01-01

    The Intergovernmental Panel on Climate Change (IPCC) first attempted a global assessment of long-term changes in temperature and precipitation extremes in its Third Assessment Report in 2001. While data quality and coverage were limited, the report still concluded that heavy precipitation events had increased and that there had been, very likely, a reduction in the frequency of extreme low temperatures and increases in the frequency of extreme high temperatures. That overall assessment had ch...

  15. Precipitation estimates and comparison of satellite rainfall data to in situ rain gauge observations to further develop the watershed-modeling capabilities for the Lower Mekong River Basin

    Science.gov (United States)

    Dandridge, C.; Lakshmi, V.; Sutton, J. R. P.; Bolten, J. D.

    2017-12-01

    This study focuses on the lower region of the Mekong River Basin (MRB), an area including Burma, Cambodia, Vietnam, Laos, and Thailand. This region is home to expansive agriculture that relies heavily on annual precipitation over the basin for its prosperity. Annual precipitation amounts are regulated by the global monsoon system and therefore vary throughout the year. This research will lead to improved prediction of floods and management of floodwaters for the MRB. We compare different satellite estimates of precipitation to each other and to in-situ precipitation estimates for the Mekong River Basin. These comparisons will help us determine which satellite precipitation estimates are better at predicting precipitation in the MRB and will help further our understanding of watershed-modeling capabilities for the basin. In this study we use: 1) NOAA's PERSIANN daily 0.25° precipitation estimate Climate Data Record (CDR), 2) NASA's Tropical Rainfall Measuring Mission (TRMM) daily 0.25° estimate, and 3) NASA's Global Precipitation Measurement (GPM) daily 0.1 estimate and 4) 488 in-situ stations located in the lower MRB provide daily precipitation estimates. The PERSIANN CDR precipitation estimate was able to provide the longest data record because it is available from 1983 to present. The TRMM precipitation estimate is available from 2000 to present and the GPM precipitation estimates are available from 2015 to present. It is for this reason that we provide several comparisons between our precipitation estimates. Comparisons were done between each satellite product and the in-situ precipitation estimates based on geographical location and date using the entire available data record for each satellite product for daily, monthly, and yearly precipitation estimates. We found that monthly PERSIANN precipitation estimates were able to explain up to 90% of the variability in station precipitation depending on station location.

  16. Precipitation Climatology on Titan-like Exomoons.

    Science.gov (United States)

    Tokano, Tetsuya

    2015-06-01

    The availability of liquid water on the surface on Earth's continents in part relies on the precipitation of water. This implies that the habitability of exomoons has to consider not only the surface temperature and atmospheric pressure for the presence of liquid water, but also the global precipitation climatology. This study explores the sensitivity of the precipitation climatology of Titan-like exomoons to these moons' orbital configuration using a global climate model. The precipitation rate primarily depends on latitude and is sensitive to the planet's obliquity and the moon's rotation rate. On slowly rotating moons the precipitation shifts to higher latitudes as obliquity is increased, whereas on quickly rotating moons the latitudinal distribution does not strongly depend on obliquity. Stellar eclipse can cause a longitudinal variation in the mean surface temperature and surface pressure between the subplanetary and antiplanetary side if the planet's obliquity and the moon's orbital distance are small. In this particular condition the antiplanetary side generally receives more precipitation than the subplanetary side. However, precipitation on exomoons with dense atmospheres generally occurs at any longitude in contrast to tidally locked exoplanets.

  17. Evaluation of Uncertainty in Precipitation Datasets for New Mexico, USA

    Science.gov (United States)

    Besha, A. A.; Steele, C. M.; Fernald, A.

    2014-12-01

    Climate change, population growth and other factors are endangering water availability and sustainability in semiarid/arid areas particularly in the southwestern United States. Wide coverage of spatial and temporal measurements of precipitation are key for regional water budget analysis and hydrological operations which themselves are valuable tool for water resource planning and management. Rain gauge measurements are usually reliable and accurate at a point. They measure rainfall continuously, but spatial sampling is limited. Ground based radar and satellite remotely sensed precipitation have wide spatial and temporal coverage. However, these measurements are indirect and subject to errors because of equipment, meteorological variability, the heterogeneity of the land surface itself and lack of regular recording. This study seeks to understand precipitation uncertainty and in doing so, lessen uncertainty propagation into hydrological applications and operations. We reviewed, compared and evaluated the TRMM (Tropical Rainfall Measuring Mission) precipitation products, NOAA's (National Oceanic and Atmospheric Administration) Global Precipitation Climatology Centre (GPCC) monthly precipitation dataset, PRISM (Parameter elevation Regression on Independent Slopes Model) data and data from individual climate stations including Cooperative Observer Program (COOP), Remote Automated Weather Stations (RAWS), Soil Climate Analysis Network (SCAN) and Snowpack Telemetry (SNOTEL) stations. Though not yet finalized, this study finds that the uncertainty within precipitation estimates datasets is influenced by regional topography, season, climate and precipitation rate. Ongoing work aims to further evaluate precipitation datasets based on the relative influence of these phenomena so that we can identify the optimum datasets for input to statewide water budget analysis.

  18. Fluctuations in the large-scale atmospheric circulation and ocean conditions associated with the dominant modes of wintertime precipitation variability for the contiguous United States

    International Nuclear Information System (INIS)

    Mitchell, T.P.; Blier, W.

    1994-01-01

    The historical Climatic Division record of monthly- and seasonal-mean wintertime precipitation totals are analyzed to document the dominant patterns of precipitation variability for the contiguous United States. The analysis technique employed is the Rotated Principal Component analysis. Time series for the leading patterns are related to global sea-surface temperatures (SSTs), and to gridded surface and upper-air analyses for the Northern Hemisphere

  19. Evaluation of the Potential of NASA Multi-satellite Precipitation Analysis in Global Landslide Hazard Assessment

    Science.gov (United States)

    Hong, Yang; Adler, Robert F.; Huffman, George J.

    2007-01-01

    Landslides are one of the most widespread natural hazards on Earth, responsible for thousands of deaths and billions of dollars in property damage every year. In the U.S. alone landslides occur in every state, causing an estimated $2 billion in damage and 25- 50 deaths each year. Annual average loss of life from landslide hazards in Japan is 170. The situation is much worse in developing countries and remote mountainous regions due to lack of financial resources and inadequate disaster management ability. Recently, a landslide buried an entire village on the Philippines Island of Leyte on Feb 17,2006, with at least 1800 reported deaths and only 3 houses left standing of the original 300. Intense storms with high-intensity , long-duration rainfall have great potential to trigger rapidly moving landslides, resulting in casualties and property damage across the world. In recent years, through the availability of remotely sensed datasets, it has become possible to conduct global-scale landslide hazard assessment. This paper evaluates the potential of the real-time NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA) system to advance our understanding of and predictive ability for rainfall-triggered landslides. Early results show that the landslide occurrences are closely associated with the spatial patterns and temporal distribution of rainfall characteristics. Particularly, the number of landslide occurrences and the relative importance of rainfall in triggering landslides rely on the influence of rainfall attributes [e.g. rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms). TMPA precipitation data are available in both real-time and post-real-time versions, which are useful to assess the location and timing of rainfall-triggered landslide hazards by monitoring landslide-prone areas while receiving heavy rainfall. For the purpose of identifying rainfall-triggered landslides, an empirical global rainfall intensity

  20. Observed and simulated precipitation responses in wet and dry regions 1850–2100

    International Nuclear Information System (INIS)

    Liu Chunlei; Allan, Richard P

    2013-01-01

    Global warming is expected to enhance fluxes of fresh water between the surface and atmosphere, causing wet regions to become wetter and dry regions drier, with serious implications for water resource management. Defining the wet and dry regions as the upper 30% and lower 70% of the precipitation totals across the tropics (30° S–30° N) each month we combine observations and climate model simulations to understand changes in the wet and dry regions over the period 1850–2100. Observed decreases in precipitation over dry tropical land (1950–2010) are also simulated by coupled atmosphere–ocean climate models (−0.3%/decade) with trends projected to continue into the 21st century. Discrepancies between observations and simulations over wet land regions since 1950 exist, relating to decadal fluctuations in El Niño southern oscillation, the timing of which is not represented by the coupled simulations. When atmosphere-only simulations are instead driven by observed sea surface temperature they are able to adequately represent this variability over land. Global distributions of precipitation trends are dominated by spatial changes in atmospheric circulation. However, the tendency for already wet regions to become wetter (precipitation increases with warming by 3% K −1 over wet tropical oceans) and the driest regions drier (precipitation decreases of −2% K −1 over dry tropical land regions) emerges over the 21st century in response to the substantial surface warming. (letter)

  1. Recent Trends of the Tropical Hydrological Cycle Inferred from Global Precipitation Climatology Project and International Satellite Cloud Climatology Project data

    Science.gov (United States)

    Zhou, Y. P.; Xu, Kuan-Man; Sud, Y. C.; Betts, A. K.

    2011-01-01

    Scores of modeling studies have shown that increasing greenhouse gases in the atmosphere impact the global hydrologic cycle; however, disagreements on regional scales are large, and thus the simulated trends of such impacts, even for regions as large as the tropics, remain uncertain. The present investigation attempts to examine such trends in the observations using satellite data products comprising Global Precipitation Climatology Project precipitation and International Satellite Cloud Climatology Project cloud and radiation. Specifically, evolving trends of the tropical hydrological cycle over the last 20-30 years were identified and analyzed. The results show (1) intensification of tropical precipitation in the rising regions of the Walker and Hadley circulations and weakening over the sinking regions of the associated overturning circulation; (2) poleward shift of the subtropical dry zones (up to 2deg/decade in June-July-August (JJA) in the Northern Hemisphere and 0.3-0.7deg/decade in June-July-August and September-October-November in the Southern Hemisphere) consistent with an overall broadening of the Hadley circulation; and (3) significant poleward migration (0.9-1.7deg/decade) of cloud boundaries of Hadley cell and plausible narrowing of the high cloudiness in the Intertropical Convergence Zone region in some seasons. These results support findings of some of the previous studies that showed strengthening of the tropical hydrological cycle and expansion of the Hadley cell that are potentially related to the recent global warming trends.

  2. Precipitation Dynamical Downscaling Over the Great Plains

    Science.gov (United States)

    Hu, Xiao-Ming; Xue, Ming; McPherson, Renee A.; Martin, Elinor; Rosendahl, Derek H.; Qiao, Lei

    2018-02-01

    Detailed, regional climate projections, particularly for precipitation, are critical for many applications. Accurate precipitation downscaling in the United States Great Plains remains a great challenge for most Regional Climate Models, particularly for warm months. Most previous dynamic downscaling simulations significantly underestimate warm-season precipitation in the region. This study aims to achieve a better precipitation downscaling in the Great Plains with the Weather Research and Forecast (WRF) model. To this end, WRF simulations with different physics schemes and nudging strategies are first conducted for a representative warm season. Results show that different cumulus schemes lead to more pronounced difference in simulated precipitation than other tested physics schemes. Simply choosing different physics schemes is not enough to alleviate the dry bias over the southern Great Plains, which is related to an anticyclonic circulation anomaly over the central and western parts of continental U.S. in the simulations. Spectral nudging emerges as an effective solution for alleviating the precipitation bias. Spectral nudging ensures that large and synoptic-scale circulations are faithfully reproduced while still allowing WRF to develop small-scale dynamics, thus effectively suppressing the large-scale circulation anomaly in the downscaling. As a result, a better precipitation downscaling is achieved. With the carefully validated configurations, WRF downscaling is conducted for 1980-2015. The downscaling captures well the spatial distribution of monthly climatology precipitation and the monthly/yearly variability, showing improvement over at least two previously published precipitation downscaling studies. With the improved precipitation downscaling, a better hydrological simulation over the trans-state Oologah watershed is also achieved.

  3. Does extreme precipitation intensity depend on the emissions scenario?

    Science.gov (United States)

    Pendergrass, Angeline; Lehner, Flavio; Sanderson, Benjamin; Xu, Yangyang

    2016-04-01

    The rate of increase of global-mean precipitation per degree surface temperature increase differs for greenhouse gas and aerosol forcings, and therefore depends on the change in composition of the emissions scenario used to drive climate model simulations for the remainder of the century. We investigate whether or not this is also the case for extreme precipitation simulated by a multi-model ensemble driven by four realistic emissions scenarios. In most models, the rate of increase of maximum annual daily rainfall per degree global warming in the multi-model ensemble is statistically indistinguishable across the four scenarios, whether this extreme precipitation is calculated globally, over all land, or over extra-tropical land. These results indicate that, in most models, extreme precipitation depends on the total amount of warming and does not depend on emissions scenario, in contrast to mean precipitation.

  4. Global land carbon sink response to temperature and precipitation varies with ENSO phase

    Energy Technology Data Exchange (ETDEWEB)

    Fang, Yuanyuan; Michalak, Anna M.; Schwalm, Christopher R.; Huntzinger, Deborah N.; Berry, Joseph A.; Ciais, Philippe; Piao, Shilong; Poulter, Benjamin; Fisher, Joshua B.; Cook, Robert B.; Hayes, Daniel; Huang, Maoyi; Ito, Akihiko; Jain, Atul; Lei, Huimin; Lu, Chaoqun; Mao, Jiafu; Parazoo, Nicholas C.; Peng, Shushi; Ricciuto, Daniel M.; Shi, Xiaoying; Tao, Bo; Tian, Hanqin; Wang, Weile; Wei, Yaxing; Yang, Jia

    2017-05-01

    Climate variability associated with the El Niño-Southern Oscillation (ENSO) and its consequent impacts on land carbon sink interannual variability have been used as a basis for investigating carbon cycle responses to climate variability more broadly, and to inform the sensitivity of the tropical carbon budget to climate change. Past studies have presented opposing views about whether temperature or precipitation is the primary factor driving the response of the land carbon sink to ENSO. Here, we show that the dominant driver varies with ENSO phase. Whereas tropical temperature explains sink dynamics following El Niño conditions (rTG,P=0.59, p<0.01), the post La Niña sink is driven largely by tropical precipitation (rPG,T=-0.46, p=0.04). This finding points to an ENSO-phase-dependent interplay between water availability and temperature in controlling the carbon uptake response to climate variations in tropical ecosystems. We further find that none of a suite of ten contemporary terrestrial biosphere models captures these ENSO-phase-dependent responses, highlighting a key uncertainty in modeling climate impacts on the future of the global land carbon sink.

  5. Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI)

    Science.gov (United States)

    Asadi Zarch, Mohammad Amin; Sivakumar, Bellie; Sharma, Ashish

    2015-07-01

    Both drought and aridity indicate imbalance in water availability. While drought is a natural temporal hazard, aridity is a constant climatic feature. This paper investigates the changes in drought characteristics across different aridity zones with and without consideration of potential evapotranspiration (PET), as a means to better assess drought in a warming climate. Two drought indexes are employed: (1) Standardized precipitation index (SPI), which is solely based on precipitation; and (2) Reconnaissance drought index (RDI), which, in addition to precipitation, takes PET into account. The two indexes are first employed to observed precipitation and PET data for the period 1960-2009 from the CRU (Climate Research Unit, University of East Anglia) TS 3.1 database. The results indicate that although all the aridity zones experience both downward and upward drought trends, no significant trend is found over large parts of the zones. However, the agreement between SPI and RDI reduces from the hyper-arid zone on one extreme toward the humid zone on the other. In the three more humid zones (i.e. semi-arid, sub-humid, and humid), the indexes exhibit different trends, with RDI showing more decreasing trends (i.e. becoming drier). While SPI generally shows more drought prone areas than RDI for the pre-1998 period, the opposite is observed for the post-1998 period. Given the known changes to PET in observed records, and also expected increases as global warming intensifies, these results suggest that RDI will be consistently different to the SPI as global warming intensifies. This hypothesis is further tested for historic and future climate projections from the CSIRO (Commonwealth Scientific and Industrial Research Organisation, Australia) Mk3.6 global climate model (GCM), with use of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and RCP8.5 (Representative Concentration Pathways). In this case, PET is calculated using FAO56-PM model for assessment of

  6. Acidity of Scandinavian precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Barrett, E; Bordin, G

    1955-01-01

    Data on the pH of the total monthly precipitation at stations of a Swedish network for sampling and chemical analysis of precipitation and atmospheric aerosols during the year July 1953 to June 1954 are presented and discussed, together with the pH data from the first two months of operation of a large pan-Scandinavian net. It is found that well-defined regions of acidity and alkalinity relative to the pH of water in equilibrium with atmospheric carbon dioxide exist, and that these regions persist to such an extent that the monthly deviations from the pattern of the annual mean pH at stations unaffected by local pollution show persistently high acidity, while inland northern stations show equally persistent alkalinity. Some possible reasons for the observed distributions are considered.

  7. "Cool" vs. "warm" winter precipitation and its effect on streamflow in California

    OpenAIRE

    Cayan, Daniel R.

    1991-01-01

    Precipitation is a difficult variable to understand and predict. In this study, monthly precipitation in California is divided into two classes according to the monthly temperature to better diagnose the atmospheric circulation that causes precipitation, and to illustrate how temperature compounds the precipitation to runoff process.

  8. Precipitation Sedimentation and Advection in GFS

    Science.gov (United States)

    Sun, R.; Tallapragada, V.

    2016-12-01

    Zhao and Carr microphysics scheme as implemented in the NCEP Global Forecasting System (GFS) predicts only the total cloud condensate (cloud water or ice). The precipitation generated in the column fall to the ground instantly. This mean precipitation sedimentation and advection are not considered. As resolution increases the lack of the two physical processes creates problems. The slowly falling precipitation (snow) falls to the wrong surface grid box, which may have led to the observed spotty-precipitation pattern. To solve the problem two prognositic variables, snow and rain, are added. Addition of the two precipitation variable allows their advection. The corresponding sedimentation process are also added. In this study we examine the effect of precipitation advection and sedimentation on the precipitation pattern, associated precipitation skills and clouds.

  9. Towards combined global monthly gravity field solutions

    Science.gov (United States)

    Jaeggi, Adrian; Meyer, Ulrich; Beutler, Gerhard; Weigelt, Matthias; van Dam, Tonie; Mayer-Gürr, Torsten; Flury, Jakob; Flechtner, Frank; Dahle, Christoph; Lemoine, Jean-Michel; Bruinsma, Sean

    2014-05-01

    Currently, official GRACE Science Data System (SDS) monthly gravity field solutions are generated independently by the Centre for Space Research (CSR) and the German Research Centre for Geosciences (GFZ). Additional GRACE SDS monthly fields are provided by the Jet Propulsion Laboratory (JPL) for validation and outside the SDS by a number of other institutions worldwide. Although the adopted background models and processing standards have been harmonized more and more by the various processing centers during the past years, notable differences still exist and the users are more or less left alone with a decision which model to choose for their individual applications. This procedure seriously limits the accessibility of these valuable data. Combinations are well established in the area of other space geodetic techniques, such as the Global Navigation Satellite Systems (GNSS), Satellite Laser Ranging (SLR), and Very Long Baseline Interferometry (VLBI). Regularly comparing and combining space-geodetic products has tremendously increased the usefulness of the products in a wide range of disciplines and scientific applications. Therefore, we propose in a first step to mutually compare the large variety of available monthly GRACE gravity field solutions, e.g., by assessing the signal content over selected regions, by estimating the noise over the oceans, and by performing significance tests. We make the attempt to assign different solution characteristics to different processing strategies in order to identify subsets of solutions, which are based on similar processing strategies. Using these subsets we will in a second step explore ways to generate combined solutions, e.g., based on a weighted average of the individual solutions using empirical weights derived from pair-wise comparisons. We will also assess the quality of such a combined solution and discuss the potential benefits for the GRACE and GRACE-FO user community, but also address minimum processing

  10. Can the variability in precipitation simulations across GCMs be reduced through sensible bias correction?

    Science.gov (United States)

    Nguyen, Ha; Mehrotra, Rajeshwar; Sharma, Ashish

    2017-11-01

    This work investigates the performance of four bias correction alternatives for representing persistence characteristics of precipitation across 37 General Circulation Models (GCMs) from the CMIP5 data archive. The first three correction approaches are the Simple Monthly Bias Correction (SMBC), Equidistance Quantile Mapping (EQM), and Nested Bias Correction (NBC), all of which operate in the time domain, with a focus on representing distributional and moment attributes in the observed precipitation record. The fourth approach corrects for the biases in high- and low-frequency variability or persistence of the GCM time series in the frequency domain and is named as Frequency-based Bias Correction (FBC). The Climatic Research Unit (CRU) gridded precipitation data covering the global land surface is used as a reference dataset. The assessment focusses on current and future means, variability, and drought-related characteristics at different temporal and spatial scales. For the current climate, all bias correction approaches perform reasonably well at the global scale by reproducing the observed precipitation statistics. For the future climate, focus is drawn on the agreement of the attributes across the GCMs considered. The inter-model difference/spread of each attribute across the GCMs is used as a measure of this agreement. Our results indicate that out of the four bias correction approaches used, FBC provides the lowest inter-model spreads, specifically for persistence attributes, over most regions/ parts over the global land surface. This has significant implications for most hydrological studies where the effect of low-frequency variability is of considerable importance.

  11. Environmental isotope data no. 10: World survey of isotope concentration in precipitation (1988-1991). Report from a network

    International Nuclear Information System (INIS)

    1994-01-01

    This is the tenth volume of the publication Environmental Isotope Data: World Survey of Isotope Concentration in Precipitation. This volume is primarily concerned with the concentration of the environmental isotopes (tritium, deuterium and oxygen-18) in monthly samples of precipitation taken by a global network of 169 stations in the period 1988 to 1991. Selected meteorological data, such as the amount of precipitation, mean water vapour pressure and surface air temperature, are also presented. Data before 1988 which were unavailable at the time of the earlier issues have also been included in the latter part of this volume as late reports. The data are being widely used in hydrological, hydrometeorological and climatological studies. 9 refs, 2 figs

  12. Forecasting droughts in West Africa: Operational practice and refined seasonal precipitation forecasts

    Science.gov (United States)

    Bliefernicht, Jan; Siegmund, Jonatan; Seidel, Jochen; Arnold, Hanna; Waongo, Moussa; Laux, Patrick; Kunstmann, Harald

    2016-04-01

    Precipitation forecasts for the upcoming rainy seasons are one of the most important sources of information for an early warning of droughts and water scarcity in West Africa. The meteorological services in West Africa perform seasonal precipitation forecasts within the framework of PRESAO (the West African climate outlook forum) since the end of the 1990s. Various sources of information and statistical techniques are used by the individual services to provide a harmonized seasonal precipitation forecasts for decision makers in West Africa. In this study, we present a detailed overview of the operational practice in West Africa including a first statistical assessment of the performance of the precipitation forecasts for drought situations for the past 18 years (1998 to 2015). In addition, a long-term hindcasts (1982 to 2009) and a semi-operational experiment for the rainy season 2013 using statistical and/or dynamical downscaling are performed to refine the precipitation forecasts from the Climate Forecast System Version 2 (CFSv2), a global ensemble prediction system. This information is post-processed to provide user-oriented precipitation indices such as the onset of the rainy season for supporting water and land use management for rain-fed agriculture. The evaluation of the individual techniques is performed focusing on water-scarce regions of the Volta basin in Burkina Faso and Ghana. The forecasts of the individual techniques are compared to state-of-the-art global observed precipitation products and a novel precipitation database based on long-term daily rain-gage measurements provided by the national meteorological services. The statistical assessment of the PRESAO forecasts indicates skillful seasonal precipitation forecasts for many locations in the Volta basin, particularly for years with water deficits. The operational experiment for the rainy season 2013 illustrates the high potential of a physically-based downscaling for this region but still shows

  13. CMORPH 8 Km: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A new technique is presented in which half-hourly global precipitation estimates derived from passive microwave satellite scans are propagated by motion vectors...

  14. Precipitation variability assessment of northeast China: Songhua ...

    Indian Academy of Sciences (India)

    Variability in precipitation is critical for the management of water resources. ... applied on precipitation data on a monthly, seasonally, annually, decade scale and the number of rainy ... 2015). As a result, such irregularities in precipitation,. i.e., droughts and floods can affect the ... (January–December), years and decades.

  15. Inter-Comparison and Evaluation of Remote Sensing Precipitation Products over China from 2005 to 2013

    Directory of Open Access Journals (Sweden)

    Qiaolin Zeng

    2018-01-01

    Full Text Available Precipitation is a key aspect of the climate system. In this paper, the dependability of five satellite precipitation products (TRMM [Tropical Rainfall Measuring Mission] 3BV42, PERSIANN [Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks] CDR, GSMaP [Global Satellite Mapping of Precipitation] RENALYSIS, CMORPH [Climate Prediction Center’s morphing technique] BLD and CMORPH_RAW were compared with in situ measurements over China for the period of 2005 to 2013. To completely evaluate these precipitation products, the annual, seasonal and monthly precipitation averages were calculated. Overall, the Huaihe River and Qinlin mountains are shown to have heavy precipitation to the southeast and lighter precipitation to the northwest. The comparison results indicate that Gauge correction (CMORPH_BLD improves the quality of the original satellite products (CMORPH_RAW, resulting in the higher correlation coefficient (CC, the low relative bias (BIAS and root mean square error (RMSE. Over China, the GSMaP_RENALYSIS outperforms other products and shows the highest CC (0.91 and lowest RMSE (0.85 mm/day and all products except for PERSIANN_CDR exhibit underestimation. GSMaP_RENALYSIS gives the highest of probability of detection (81%, critical success index (63% and lowest false alarm ratio (36% while TRMM3BV42 gives the highest of frequency bias index (1.00. Over Tibetan Plateau, CMORPH_RAW demonstrates the poorest performance with the biggest BIAS (4.2 mm/month and lowest CC (0.22 in December 2013. GSMaP_RENALYSIS displays quite consistent with in situ measurements in summer. However, GSMaP_RENALYSIS and CMORPH_RAW underestimate precipitation over South China. CMORPH_BLD and TRMM3BV42 show consistent with high CC (>0.8 but relatively large RMSE in summer.

  16. Indirect downscaling of global circulation model data based on atmospheric circulation and temperature for projections of future precipitation in hourly resolution

    Science.gov (United States)

    Beck, F.; Bárdossy, A.

    2013-07-01

    Many hydraulic applications like the design of urban sewage systems require projections of future precipitation in high temporal resolution. We developed a method to predict the regional distribution of hourly precipitation sums based on daily mean sea level pressure and temperature data from a Global Circulation Model. It is an indirect downscaling method avoiding uncertain precipitation data from the model. It is based on a fuzzy-logic classification of atmospheric circulation patterns (CPs) that is further subdivided by means of the average daily temperature. The observed empirical distributions at 30 rain gauges to each CP-temperature class are assumed as constant and used for projections of the hourly precipitation sums in the future. The method was applied to the CP-temperature sequence derived from the 20th century run and the scenario A1B run of ECHAM5. According to ECHAM5, the summers in southwest Germany will become progressively drier. Nevertheless, the frequency of the highest hourly precipitation sums will increase. According to the predictions, estival water stress and the risk of extreme hourly precipitation will both increase simultaneously during the next decades.

  17. Artificial neural network optimisation for monthly average daily global solar radiation prediction

    International Nuclear Information System (INIS)

    Alsina, Emanuel Federico; Bortolini, Marco; Gamberi, Mauro; Regattieri, Alberto

    2016-01-01

    Highlights: • Prediction of the monthly average daily global solar radiation over Italy. • Multi-location Artificial Neural Network (ANN) model: 45 locations considered. • Optimal ANN configuration with 7 input climatologic/geographical parameters. • Statistical indicators: MAPE, NRMSE, MPBE. - Abstract: The availability of reliable climatologic data is essential for multiple purposes in a wide set of anthropic activities and operative sectors. Frequently direct measures present spatial and temporal lacks so that predictive approaches become of interest. This paper focuses on the prediction of the Monthly Average Daily Global Solar Radiation (MADGSR) over Italy using Artificial Neural Networks (ANNs). Data from 45 locations compose the multi-location ANN training and testing sets. For each location, 13 input parameters are considered, including the geographical coordinates and the monthly values for the most frequently adopted climatologic parameters. A subset of 17 locations is used for ANN training, while the testing step is against data from the remaining 28 locations. Furthermore, the Automatic Relevance Determination method (ARD) is used to point out the most relevant input for the accurate MADGSR prediction. The ANN best configuration includes 7 parameters, only, i.e. Top of Atmosphere (TOA) radiation, day length, number of rainy days and average rainfall, latitude and altitude. The correlation performances, expressed through statistical indicators as the Mean Absolute Percentage Error (MAPE), range between 1.67% and 4.25%, depending on the number and type of the chosen input, representing a good solution compared to the current standards.

  18. Assessing water resources in Azerbaijan using a local distributed model forced and constrained with global data

    Science.gov (United States)

    Bouaziz, Laurène; Hegnauer, Mark; Schellekens, Jaap; Sperna Weiland, Frederiek; ten Velden, Corine

    2017-04-01

    In many countries, data is scarce, incomplete and often not easily shared. In these cases, global satellite and reanalysis data provide an alternative to assess water resources. To assess water resources in Azerbaijan, a completely distributed and physically based hydrological wflow-sbm model was set-up for the entire Kura basin. We used SRTM elevation data, a locally available river map and one from OpenStreetMap to derive the drainage direction network at the model resolution of approximately 1x1 km. OpenStreetMap data was also used to derive the fraction of paved area per cell to account for the reduced infiltration capacity (c.f. Schellekens et al. 2014). We used the results of a global study to derive root zone capacity based on climate data (Wang-Erlandsson et al., 2016). To account for the variation in vegetation cover over the year, monthly averages of Leaf Area Index, based on MODIS data, were used. For the soil-related parameters, we used global estimates as provided by Dai et al. (2013). This enabled the rapid derivation of a first estimate of parameter values for our hydrological model. Digitized local meteorological observations were scarce and available only for limited time period. Therefore several sources of global meteorological data were evaluated: (1) EU-WATCH global precipitation, temperature and derived potential evaporation for the period 1958-2001 (Harding et al., 2011), (2) WFDEI precipitation, temperature and derived potential evaporation for the period 1979-2014 (by Weedon et al., 2014), (3) MSWEP precipitation (Beck et al., 2016) and (4) local precipitation data from more than 200 stations in the Kura basin were available from the NOAA website for a period up to 1991. The latter, together with data archives from Azerbaijan, were used as a benchmark to evaluate the global precipitation datasets for the overlapping period 1958-1991. By comparing the datasets, we found that monthly mean precipitation of EU-WATCH and WFDEI coincided well

  19. Global Precipitation Measurement (GPM) and International Space Station (ISS) Coordination for CubeSat Deployments to Minimize Collision Risk

    Science.gov (United States)

    Pawloski, James H.; Aviles, Jorge; Myers, Ralph; Parris, Joshua; Corley, Bryan; Hehn, Garrett; Pascucci, Joseph

    2016-01-01

    The Global Precipitation Measurement Mission (GPM) is a joint U.S. and Japan mission to observe global precipitation, extending the Tropical Rainfall Measuring Mission (TRMM), which was launched by H-IIA from Tanegashima in Japan on February 28TH, 2014 directly into its 407km operational orbit. The International Space Station (ISS) is an international human research facility operated jointly by Russia and the USA from NASA's Johnson Space Center (JSC) in Houston Texas. Mission priorities lowered the operating altitude of ISS from 415km to 400km in early 2105, effectively placing both vehicles into the same orbital regime. The ISS has begun a program of deployments of cost effective CubeSats from the ISS that allow testing and validation of new technologies. With a major new asset flying at the same effective altitude as the ISS, CubeSat deployments became a serious threat to GPM and therefore a significant indirect threat to the ISS. This paper describes the specific problem of collision threat to GPM and risk to ISS CubeSat deployment and the process that was implemented to keep both missions safe from collision and maximize their project goals.

  20. Global peak flux profile of proton precipitation in the equatorial zone

    International Nuclear Information System (INIS)

    Miah, M.A.

    1991-01-01

    Particle precipitation near the equator within ± 30deg geomagnetic latitude was investigated by the Phoenix-1 instrumentation on board the S81-1 mission. The monitor telescope on board the mission was sensitive to protons in the energy range 0.6-9.1 MeV, to alpha particles in the energy range 0.4-80 MeV/nucleon and Z→3 particles ( 12 C) of energy greater than 0.7 MeV/nucleon. The peak efficiency of the telescope was for particles of ∼88deg pitch angles at the line of minimum magnetic field. Careful separation of the magnetically quiet time equatorial particle data from global data coverage and subsequent analysis shows that the ML detector on board the mission detected mostly protons. The proton peak flux profile follows the line of minimum magnetic field. The full width at half maximum (FWHM) of the equatorial zone is ∼ 13deg, which is well within the EUV emission zone. (author). 14 refs., 9 figs

  1. Lessons learned from oxygen isotopes in modern precipitation applied to interpretation of speleothem records of paleoclimate from eastern Asia

    Science.gov (United States)

    Dayem, Katherine E.; Molnar, Peter; Battisti, David S.; Roe, Gerard H.

    2010-06-01

    Variability in oxygen isotope ratios collected from speleothems in Chinese caves is often interpreted as a proxy for variability of precipitation, summer precipitation, seasonality of precipitation, and/or the proportion of 18O to 16O of annual total rainfall that is related to a strengthening or weakening of the East Asian monsoon and, in some cases, to the Indian monsoon. We use modern reanalysis and station data to test whether precipitation and temperature variability over China can be related to changes in climate in these distant locales. We find that annual and rainy season precipitation totals in each of central China, south China, and east India have correlation length scales of ∼ 500 km, shorter than the distance between many speleothem records that share similar long-term time variations in δ18O values. Thus the short distances of correlation do not support, though by themselves cannot refute, the idea that apparently synchronous variations in δ18O values at widely spaced (> 500 km) caves in China are due to variations in annual precipitation amounts. We also evaluate connections between climate variables and δ18O values using available instrumental measurements of δ18O values in precipitation. These data, from stations in the Global Network of Isotopes in Precipitation (GNIP), show that monthly δ18O values generally do not correlate well with either local precipitation amount or local temperature, and the degree to which monthly δ18O values do correlate with them varies from station to station. For the few locations that do show significant correlations between δ18O values and precipitation amount, we estimate the differences in precipitation amount that would be required to account for peak-to-peak differences in δ18O values in the speleothems from Hulu and Dongge caves, assuming that δ18O scales with the monthly amount of precipitation or with seasonal differences in precipitation. Insofar as the present-day relationship between δ18O

  2. Estimation of the impact of climate change-induced extreme precipitation events on floods

    Science.gov (United States)

    Hlavčová, Kamila; Lapin, Milan; Valent, Peter; Szolgay, Ján; Kohnová, Silvia; Rončák, Peter

    2015-09-01

    In order to estimate possible changes in the flood regime in the mountainous regions of Slovakia, a simple physically-based concept for climate change-induced changes in extreme 5-day precipitation totals is proposed in the paper. It utilizes regionally downscaled scenarios of the long-term monthly means of the air temperature, specific air humidity and precipitation projected for Central Slovakia by two regional (RCM) and two global circulation models (GCM). A simplified physically-based model for the calculation of short-term precipitation totals over the course of changing air temperatures, which is used to drive a conceptual rainfall-runoff model, was proposed. In the paper a case study of this approach in the upper Hron river basin in Central Slovakia is presented. From the 1981-2010 period, 20 events of the basin's most extreme average of 5-day precipitation totals were selected. Only events with continual precipitation during 5 days were considered. These 5-day precipitation totals were modified according to the RCM and GCM-based scenarios for the future time horizons of 2025, 2050 and 2075. For modelling runoff under changed 5-day precipitation totals, a conceptual rainfall-runoff model developed at the Slovak University of Technology was used. Changes in extreme mean daily discharges due to climate change were compared with the original flood events and discussed.

  3. Study of sea-surface slope distribution and its effect on radar backscatter based on Global Precipitation Measurement Ku-band precipitation radar measurements

    Science.gov (United States)

    Yan, Qiushuang; Zhang, Jie; Fan, Chenqing; Wang, Jing; Meng, Junmin

    2018-01-01

    The collocated normalized radar backscattering cross-section measurements from the Global Precipitation Measurement (GPM) Ku-band precipitation radar (KuPR) and the winds from the moored buoys are used to study the effect of different sea-surface slope probability density functions (PDFs), including the Gaussian PDF, the Gram-Charlier PDF, and the Liu PDF, on the geometrical optics (GO) model predictions of the radar backscatter at low incidence angles (0 deg to 18 deg) at different sea states. First, the peakedness coefficient in the Liu distribution is determined using the collocations at the normal incidence angle, and the results indicate that the peakedness coefficient is a nonlinear function of the wind speed. Then, the performance of the modified Liu distribution, i.e., Liu distribution using the obtained peakedness coefficient estimate; the Gaussian distribution; and the Gram-Charlier distribution is analyzed. The results show that the GO model predictions with the modified Liu distribution agree best with the KuPR measurements, followed by the predictions with the Gaussian distribution, while the predictions with the Gram-Charlier distribution have larger differences as the total or the slick filtered, not the radar filtered, probability density is included in the distribution. The best-performing distribution changes with incidence angle and changes with wind speed.

  4. Average monthly and annual climate maps for Bolivia

    KAUST Repository

    Vicente-Serrano, Sergio M.

    2015-02-24

    This study presents monthly and annual climate maps for relevant hydroclimatic variables in Bolivia. We used the most complete network of precipitation and temperature stations available in Bolivia, which passed a careful quality control and temporal homogenization procedure. Monthly average maps at the spatial resolution of 1 km were modeled by means of a regression-based approach using topographic and geographic variables as predictors. The monthly average maximum and minimum temperatures, precipitation and potential exoatmospheric solar radiation under clear sky conditions are used to estimate the monthly average atmospheric evaporative demand by means of the Hargreaves model. Finally, the average water balance is estimated on a monthly and annual scale for each 1 km cell by means of the difference between precipitation and atmospheric evaporative demand. The digital layers used to create the maps are available in the digital repository of the Spanish National Research Council.

  5. Historic and future increase in the global land area affected by monthly heat extremes

    International Nuclear Information System (INIS)

    Coumou, Dim; Robinson, Alexander

    2013-01-01

    Climatic warming of about 0.5 ° C in the global mean since the 1970s has strongly increased the occurrence-probability of heat extremes on monthly to seasonal time scales. For the 21st century, climate models predict more substantial warming. Here we show that the multi-model mean of the CMIP5 (Coupled Model Intercomparison Project) climate models accurately reproduces the evolution over time and spatial patterns of the historically observed increase in monthly heat extremes. For the near-term (i.e., by 2040), the models predict a robust, several-fold increase in the frequency of such heat extremes, irrespective of the emission scenario. However, mitigation can strongly reduce the number of heat extremes by the second half of the 21st century. Unmitigated climate change causes most (>50%) continental regions to move to a new climatic regime with the coldest summer months by the end of the century substantially hotter than the hottest experienced today. We show that the land fraction experiencing extreme heat as a function of global mean temperature follows a simple cumulative distribution function, which depends only on natural variability and the level of spatial heterogeneity in the warming. (letter)

  6. Comparison of GPM IMERG, TMPA 3B42 and PERSIANN-CDR satellite precipitation products over Malaysia

    Science.gov (United States)

    Tan, Mou Leong; Santo, Harrif

    2018-04-01

    The launch of the Global Precipitation Measurement (GPM) mission has prompted the assessment of the newly released satellite precipitation products (SPPs) in different parts of the world. This study performed an initial comparison of three GPM IMERG products (IMERG_E, IMERG_L and IMERG_F) with its predecessor, the TMPA 3B42 and 3B42RT products, and a long-term PERSIANN-CDR product over Malaysia. The performance of six SPPs was evaluated using 501 precipitation gauges from 12 March 2014 to 29 February 2016. The annual, seasonal, monthly and daily precipitation measurements were validated using three widely used statistical metrics (CC, RMSE and RB). The precipitation detection capability (POD, FAR and CSI), probability density function (PDF) and the 2014-2015 flood event analysis were also considered in this assessment. The results show that all the SPPs perform well in annual and monthly precipitation measurements. The spatial variability of the total annual precipitation in 2015 is well captured by all six SPPs, with high precipitation amount in southern East Malaysia, and low precipitation amount in the middle part of Peninsular Malaysia. In contrast, all the SPPs show moderate correlation at daily precipitation estimations, with better performance during the northeast monsoon season. The performance of all the SPPs is better in eastern Peninsular Malaysia, but poorer in northern Peninsular Malaysia. All the SPPs have good precipitation detection ability, except the PERSIANN-CDR. All the SPPs underestimate the light (0-1 mm/day) and violent (> 50 mm/day) precipitation classes, but overestimate moderate and heavy (1-50 mm/day) precipitation classes. The IMERG is shown to have a better capability in detecting light precipitation (0-1 mm/day) compared to the other SPPs. The PERSIANN-CDR has the worst performance in capturing all the precipitation classes, with significant underestimation of light precipitation (0-1 mm/day) class and overestimation of moderate and

  7. TRMM Version 7 Level 3 Gridded Monthly Accumulations of GPROF Precipitation Retrievals

    Science.gov (United States)

    Stocker, E. F.; Kelley, O. A.

    2012-01-01

    In July 2011, improved versions of the retrieval algorithms were approved for TRMM. All data starting with June 2011 are produced only with the version 7 code. At the same time, version 7 reprocessing of all TRMM mission data was started. By the end of August 2011, the 14+ years of the reprocessed mission data became available online to users. This reprocessing provided the opportunity to redo and enhance upon an analysis of V7 impacts on L3 data accumulations that was presented at the 2010 EGU General Assembly. This paper will discuss the impact of algorithm changes made in th GPROF retrieval on the Level 2 swath products. Perhaps the most important change in that retrieval was to replacement of a model based a priori database with one created from Precipitation Radar (PR) and TMI brightness temperature (Tb) data. The radar pays a major role in the V7 GPROF (GPROF2010) in determining existence of rain. The level 2 retrieval algorithm also introduced a field providing the probability of rain. This combined use of the PR has some impact on the retrievals and created areas, particularly over ocean, where many areas of low-probability precipitation are retrieved whereas in version 6, these areas contained zero rain rates. This paper will discuss how these impacts get translated to the space/time averaged monthly products that use the GPROF retrievals. The level 3 products discussed are the gridded text product 3G68 and the standard 3A12 and 3B31 products. The paper provides an overview of the changes and explanation of how the level 3 products dealt with the change in the retrieval approach. Using the .25 deg x .25 degree grid, the paper will show that agreement between the swath product and the level 3 remains very high. It will also present comparisons of V6 and V7 GPROF retrievals as seen both at the swath level and the level 3 time/space gridded accumulations. It will show that the various L3 products based on GPROF level 2 retrievals are in close agreement. The

  8. Regionalization of monthly rainfall erosivity patternsin Switzerland

    Science.gov (United States)

    Schmidt, Simon; Alewell, Christine; Panagos, Panos; Meusburger, Katrin

    2016-10-01

    One major controlling factor of water erosion is rainfall erosivity, which is quantified as the product of total storm energy and a maximum 30 min intensity (I30). Rainfall erosivity is often expressed as R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). As rainfall erosivity is closely correlated with rainfall amount and intensity, the rainfall erosivity of Switzerland can be expected to have a regional characteristic and seasonal dynamic throughout the year. This intra-annual variability was mapped by a monthly modeling approach to assess simultaneously spatial and monthly patterns of rainfall erosivity. So far only national seasonal means and regional annual means exist for Switzerland. We used a network of 87 precipitation gauging stations with a 10 min temporal resolution to calculate long-term monthly mean R-factors. Stepwise generalized linear regression (GLM) and leave-one-out cross-validation (LOOCV) were used to select spatial covariates which explain the spatial and temporal patterns of the R-factor for each month across Switzerland. The monthly R-factor is mapped by summarizing the predicted R-factor of the regression equation and the corresponding residues of the regression, which are interpolated by ordinary kriging (regression-kriging). As spatial covariates, a variety of precipitation indicator data has been included such as snow depths, a combination product of hourly precipitation measurements and radar observations (CombiPrecip), daily Alpine precipitation (EURO4M-APGD), and monthly precipitation sums (RhiresM). Topographic parameters (elevation, slope) were also significant explanatory variables for single months. The comparison of the 12 monthly rainfall erosivity maps showed a distinct seasonality with the highest rainfall erosivity in summer (June, July, and August) influenced by intense rainfall events. Winter months have the lowest rainfall erosivity. A proportion of 62 % of

  9. Impact of precipitation and land biophysical variables on the simulated discharge of European and Mediterranean rivers

    Science.gov (United States)

    Szczypta, C.; Decharme, B.; Carrer, D.; Calvet, J.-C.; Lafont, S.; Somot, S.; Faroux, S.; Martin, E.

    2012-09-01

    This study investigates the impact on river discharge simulations of errors in the precipitation forcing, together with changes in the representation of vegetation variables and of plant transpiration. The most recent European Centre for Medium-Range Weather Forecasts reanalysis (ERA-Interim) is used to drive the Interactions between Soil, Biosphere, and Atmosphere-Total Runoff Integrating Pathways (ISBA-TRIP) continental hydrological system over Europe and the Mediterranean basin over the 1991-2008 period. As ERA-Interim tends to underestimate precipitation, a number of precipitation corrections are proposed. In particular, the monthly Global Precipitation Climatology Centre (GPCC) precipitation product is used to bias-correct the 3-hourly ERA-Interim estimates. This correction markedly improves the match between the ISBA-TRIP simulations and the river discharge observations from the Global Runoff Data Centre (GRDC), at 150 gauging stations. The impact on TRIP river discharge simulations of various representations of the evapotranspiration in the ISBA land surface model is investigated as well: ISBA is used together with its upgraded carbon flux version (ISBA-A-gs). The latter is either driven by the satellite-derived climatology of the Leaf Area Index (LAI) used by ISBA, or performs prognostic LAI simulations. The ISBA-A-gs model, with or without dynamically simulated LAI, allows a better representation of river discharge at low water levels. On the other hand, ISBA-A-gs does not perform as well as the original ISBA model at springtime.

  10. Evaluation of the WRF model for precipitation downscaling on orographic complex islands

    Science.gov (United States)

    Díaz, Juan P.; González, Albano; Expósito, Francisco; Pérez, Juan C.

    2010-05-01

    General Circulation Models (GCMs) have proven to be an effective tool to simulate many aspects of large-scale and global climate. However, their applicability to climate impact studies is limited by their capabilities to resolve regional scale situations. In this sense, dynamical downscaling techniques are an appropriate alternative to estimate high resolution regional climatologies. In this work, the Weather Research and Forecasting model (WRF) has been used to simulate precipitations over the Canary Islands region during 2009. The precipitation patterns over Canary Islands, located at North Atlantic region, show large gradients over a relatively small geographical area due to large scale factors such as Trade Winds regime predominant in the area and mesoscale factors mainly due to the complex terrain. Sensitivity study of simulated WRF precipitations to variations in model setup and parameterizations was carried out. Thus, WRF experiments were performed using two way nesting at 3 km horizontal grid spacing and 28 vertical levels in the Canaries inner domain. The initial and lateral and lower boundary conditions for the outer domain were provided at 6 hourly intervals by NCEP FNL (Final) Operational Global Analysis data on 1.0x1.0 degree resolution interpolated onto the WRF model grid. Numerous model options have been tested, including different microphysics schemes, cumulus parameterizations and nudging configuration Positive-definite moisture advection condition was also checked. Two integration approaches were analyzed: a 1-year continuous long-term integration and a consecutive short-term monthly reinitialized integration. To assess the accuracy of our simulations, model results are compared against observational datasets obtained from a network of meteorological stations in the region. In general, we can observe that the regional model is able to reproduce the spatial distribution of precipitation, but overestimates rainfall, mainly during strong

  11. Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

    Science.gov (United States)

    Potter, C. S.

    1997-01-01

    This study describes the use of satellite data to calibrate a new climate-vegetation greenness function for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes of the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980s in order to refine our empirical understanding of intraannual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global l(sup o) gridded data sets suggest that three climate indexes: growing degree days, annual precipitation total, and an annual moisture index together can account to 70-80 percent of the variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same climate index values from the previous year explained no significant additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes was closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from l(sup o) grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes were not accurately predicted are mainly high latitude ecosystems and other remote locations where climate station data are sparse.

  12. The Interdecadal Variability of Summer Precipitation over the South of China and its Response to Asian Monsoon at the Turning Points of Global Warming

    Science.gov (United States)

    Wang, Huan; Li, Dongliang

    2017-04-01

    Under the background of global warming, decadal variability of the summer precipitation in the South of China and the Asian monsoon experienced mutations at around the end of 1970s, the beginning of 1990s and 21st century. We examined the external and internal forcings which may cause the mutations and diagnosed the mechanism. Human emission of CO2 has always been the fatal reason for global warming, and it is also the primary reason for the precipitation increasing over Yangtze-Huai river basin at the end of the 1970s. The Yangtze-Huai river basin and South China demonstrated more summer rainfall after 1993. This can be explained by the weakening of the Asian summer monsoon caused by the positive anomaly of summer SST over northwest Pacific Ocean and Indian Ocean. A significant trend in the enhancement of sensible heat over the TP has exerted some considerable influence on the reinforce of the EASM, accompanied by the northward migration of the summer precipitation belt shifting northward at the beginning of 21st century.

  13. Identification of relationships between climate indices and long-term precipitation in South Korea using ensemble empirical mode decomposition

    Science.gov (United States)

    Kim, Taereem; Shin, Ju-Young; Kim, Sunghun; Heo, Jun-Haeng

    2018-02-01

    Climate indices characterize climate systems and may identify important indicators for long-term precipitation, which are driven by climate interactions in atmosphere-ocean circulation. In this study, we investigated the climate indices that are effective indicators of long-term precipitation in South Korea, and examined their relationships based on statistical methods. Monthly total precipitation was collected from a total of 60 meteorological stations, and they were decomposed by ensemble empirical mode decomposition (EEMD) to identify the inherent oscillating patterns or cycles. Cross-correlation analysis and stepwise variable selection were employed to select the significant climate indices at each station. The climate indices that affect the monthly precipitation in South Korea were identified based on the selection frequencies of the selected indices at all stations. The NINO12 indices with four- and ten-month lags and AMO index with no lag were identified as indicators of monthly precipitation in South Korea. Moreover, they indicate meaningful physical information (e.g. periodic oscillations and long-term trend) inherent in the monthly precipitation. The NINO12 indices with four- and ten- month lags was a strong indicator representing periodic oscillations in monthly precipitation. In addition, the long-term trend of the monthly precipitation could be explained by the AMO index. A multiple linear regression model was constructed to investigate the influences of the identified climate indices on the prediction of monthly precipitation. Three identified climate indices successfully explained the monthly precipitation in the winter dry season. Compared to the monthly precipitation in coastal areas, the monthly precipitation in inland areas showed stronger correlation to the identified climate indices.

  14. Global drought outlook by means of seasonal forecasts

    Science.gov (United States)

    Ziese, Markus; Fröhlich, Kristina; Rustemeier, Elke; Becker, Andreas

    2017-04-01

    Droughts are naturally occurring phenomena which are caused by a shortage of available water due to lower than normal precipitation and/or above normal evaporation. Depending on the length of the droughts, several sectors are affected starting with agriculture, then river and ground water levels and finally socio-economic losses at the long end of the spectrum of drought persistence. Droughts are extreme events that affect much larger areas and last much longer than floods, but are less geared towards media than floods being more short-scale in persistence and impacts. Finally the slow onset of droughts make the detection and early warning of their beginning difficult and time is lost for preparatory measures. Drought indices are developed to detect and classify droughts based on (meteorological) observations and possible additional information tailored to specific user needs, e.g. in agriculture, hydrology and other sectors. Not all drought indices can be utilized for global applications as not all input parameters are available at this scale. Therefore the Global Precipitation Climatology Centre (GPCC) developed a drought index as combination of the Standardized Drought Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), the GPCC-DI. The GPCC-DI is applied to drought monitoring and retrospective analyses on a global scale. As the Deutscher Wetterdienst (DWD) operates a seasonal forecast system in cooperation with Max-Planck-Institute for Meteorology Hamburg and University of Hamburg, these data are also used for an outlook of drought conditions by means of the GPCC-DI. The reliability of seasonal precipitation forecasts is limited, so the drought outlook is available only for forecast months two to four. Based on the GPCC-DI, DWD provides a retrospective analysis, near-real-time monitoring and outlook of drought conditions on a global scale and regular basis.

  15. Changes in Intense Precipitation Events in West Africa and the central U.S. under Global Warming

    Energy Technology Data Exchange (ETDEWEB)

    Cook, Kerry H. [Univ. of Texas, Austin, TX (United States); Vizy, Edward [Univ. of Texas, Austin, TX (United States)

    2016-02-08

    The purpose of the proposed project is to improve our understanding of the physical processes and large-scale connectivity of changes in intense precipitation events (high rainfall rates) under global warming in West Africa and the central U.S., including relationships with low-frequency modes of variability. This is in response to the requested subject area #2 “simulation of climate extremes under a changing climate … to better quantify the frequency, duration, and intensity of extreme events under climate change and elucidate the role of low frequency climate variability in modulating extremes.” We will use a regional climate model and emphasize an understanding of the physical processes that lead to an intensification of rainfall. The project objectives are as follows: 1. Understand the processes responsible for simulated changes in warm-season rainfall intensity and frequency over West Africa and the Central U.S. associated with greenhouse gas-induced global warming 2. Understand the relationship between changes in warm-season rainfall intensity and frequency, which generally occur on regional space scales, and the larger-scale global warming signal by considering modifications of low-frequency modes of variability. 3. Relate changes simulated on regional space scales to global-scale theories of how and why atmospheric moisture levels and rainfall should change as climate warms.

  16. Comparison of global observations and trends of total precipitable water derived from microwave radiometers and COSMIC radio occultation from 2006 to 2013

    Science.gov (United States)

    Ho, Shu-Peng; Peng, Liang; Mears, Carl; Anthes, Richard A.

    2018-01-01

    We compare atmospheric total precipitable water (TPW) derived from the SSM/I (Special Sensor Microwave Imager) and SSMIS (Special Sensor Microwave Imager/Sounder) radiometers and WindSat to collocated TPW estimates derived from COSMIC (Constellation System for Meteorology, Ionosphere, and Climate) radio occultation (RO) under clear and cloudy conditions over the oceans from June 2006 to December 2013. Results show that the mean microwave (MW) radiometer - COSMIC TPW differences range from 0.06 to 0.18 mm for clear skies, from 0.79 to 0.96 mm for cloudy skies, from 0.46 to 0.49 mm for cloudy but non-precipitating conditions, and from 1.64 to 1.88 mm for precipitating conditions. Because RO measurements are not significantly affected by clouds and precipitation, the biases mainly result from MW retrieval uncertainties under cloudy and precipitating conditions. All COSMIC and MW radiometers detect a positive TPW trend over these 8 years. The trend using all COSMIC observations collocated with MW pixels for this data set is 1.79 mm decade-1, with a 95 % confidence interval of (0.96, 2.63), which is in close agreement with the trend estimated by the collocated MW observations (1.78 mm decade-1 with a 95 % confidence interval of 0.94, 2.62). The sample of MW and RO pairs used in this study is highly biased toward middle latitudes (40-60° N and 40-65° S), and thus these trends are not representative of global average trends. However, they are representative of the latitudes of extratropical storm tracks and the trend values are approximately 4 to 6 times the global average trends, which are approximately 0.3 mm decade-1. In addition, the close agreement of these two trends from independent observations, which represent an increase in TPW in our data set of about 6.9 %, are a strong indication of the positive water vapor-temperature feedback on a warming planet in regions where precipitation from extratropical storms is already large.

  17. A Space-Based Perspective of the 2017 Hurricane Season from the Global Precipitation Measurement (GPM) Mission

    Science.gov (United States)

    Skofronick Jackson, G.; Petersen, W. A.; Huffman, G. J.; Kirschbaum, D.; Wolff, D. B.; Tan, J.; Zavodsky, B.

    2017-12-01

    The Global Precipitation Measurement (GPM) mission collected unique, near real time 3-D satellite-based views of hurricanes in 2017 together with estimated precipitation accumulation using merged satellite data for scientific studies and societal applications. Central to GPM is the NASA-JAXA GPM Core Observatory (CO). The GPM-CO carries an advanced dual-frequency precipitation radar (DPR) and a well-calibrated, multi-frequency passive microwave radiometer that together serve as an on orbit reference for precipitation measurements made by the international GPM satellite constellation. GPM-CO overpasses of major Hurricanes such as Harvey, Irma, Maria, and Ophelia revealed intense convective structures in DPR radar reflectivity together with deep ice-phase microphysics in both the eyewalls and outer rain bands. Of considerable scientific interest, and yet to be determined, will be DPR-diagnosed characteristics of the rain drop size distribution as a function of convective structure, intensity and microphysics. The GPM-CO active/passive suite also provided important decision support information. For example, the National Hurricane Center used GPM-CO observations as a tool to inform track and intensity estimates in their forecast briefings. Near-real-time rainfall accumulation from the Integrated Multi-satellitE Retrievals for GPM (IMERG) was also provided via the NASA SPoRT team to Puerto Rico following Hurricane Maria when ground-based radar systems on the island failed. Comparisons between IMERG, NOAA Multi-Radar Multi-Sensor data, and rain gauge rainfall accumulations near Houston, Texas during Hurricane Harvey revealed spatial biases between ground and IMERG satellite estimates, and a general underestimation of IMERG rain accumulations associated with infrared observations, collectively illustrating the difficulty of measuring rainfall in hurricanes.GPM data continue to advance scientific research on tropical cyclone intensification and structure, and contribute to

  18. Reassessing the role of temperature in precipitation oxygen isotopes across the eastern and central United States through weekly precipitation-day data

    Science.gov (United States)

    Akers, Pete D.; Welker, Jeffrey M.; Brook, George A.

    2017-09-01

    Air temperature is correlated with precipitation oxygen isotope (δ18Oprcp) variability for much of the eastern and central United States, but the nature of this δ18Oprcp-temperature relationship is largely based on data coarsely aggregated at a monthly resolution. We constructed a database of 6177 weeks of isotope and precipitation-day air temperature data from 25 sites to determine how more precise data change our understanding of this classic relationship. Because the δ18Oprcp-temperature relationship is not perfectly linear, trends in the regression residuals suggest the influence of additional environmental factors such as moisture recycling and extratropical cyclone interactions. Additionally, the temporal relationships between δ18Oprcp and temperature observed in the weekly data at individual sites can explain broader spatial patterns observed across the study region. For 20 of 25 sites, the δ18Oprcp-temperature relationship slope is higher for colder precipitation than for warmer precipitation. Accordingly, northern and western sites with relatively more cold precipitation events have steeper overall relationships with higher slope values than southeastern sites that have more warm precipitation events. Although the magnitude of δ18Oprcp variability increases to the north and west, the fraction of δ18Oprcp variability explained by temperature increases due to wider annual temperature ranges, producing stronger relationships in these regions. When our δ18Oprcp-temperature data are grouped by month, we observe significant variations in the relationship from month to month. This argues against a principal causative role for temperature and suggests the existence of an alternative environmental control on δ18Oprcp values that simply covaries seasonally with temperature.

  19. Consequences of Global Warming of 1.5 °C and 2 °C for Regional Temperature and Precipitation Changes in the Contiguous United States.

    Science.gov (United States)

    Karmalkar, Ambarish V; Bradley, Raymond S

    2017-01-01

    The differential warming of land and ocean leads to many continental regions in the Northern Hemisphere warming at rates higher than the global mean temperature. Adaptation and conservation efforts will, therefore, benefit from understanding regional consequences of limiting the global mean temperature increase to well below 2°C above pre-industrial levels, a limit agreed upon at the United Nations Climate Summit in Paris in December 2015. Here, we analyze climate model simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to determine the timing and magnitude of regional temperature and precipitation changes across the contiguous United States (US) for global warming of 1.5 and 2°C and highlight consensus and uncertainties in model projections and their implications for making decisions. The regional warming rates differ considerably across the contiguous US, but all regions are projected to reach 2°C about 10-20 years before the global mean temperature. Although there is uncertainty in the timing of exactly when the 1.5 and 2°C thresholds will be crossed regionally, over 80% of the models project at least 2°C warming by 2050 for all regions for the high emissions scenario. This threshold-based approach also highlights regional variations in the rate of warming across the US. The fastest warming region in the contiguous US is the Northeast, which is projected to warm by 3°C when global warming reaches 2°C. The signal-to-noise ratio calculations indicate that the regional warming estimates remain outside the envelope of uncertainty throughout the twenty-first century, making them potentially useful to planners. The regional precipitation projections for global warming of 1.5°C and 2°C are uncertain, but the eastern US is projected to experience wetter winters and the Great Plains and the Northwest US are projected to experience drier summers in the future. The impact of different scenarios on regional precipitation projections is

  20. Assessing Changes in Precipitation and Impacts on Groundwater in Southeastern Brazil using Regional Hydroclimate Reconstruction

    Science.gov (United States)

    Nunes, A.; Fernandes, M.; Silva, G. C., Jr.

    2017-12-01

    Aquifers can be key players in regional water resources. Precipitation infiltration is the most relevant process in recharging the aquifers. In that regard, understanding precipitation changes and impacts on the hydrological cycle helps in the assessment of groundwater availability from the aquifers. Regional modeling systems can provide precipitation, near-surface air temperature, together with soil moisture at different ground levels from coupled land-surface schemes. More accurate those variables are better the evaluation of the precipitation impact on the groundwater. Downscaling of global reanalysis very often employs regional modeling systems, in order to give more detailed information for impact assessment studies at regional scales. In particular, the regional modeling system, Satellite-enhanced Regional Downscaling for Applied Studies (SRDAS), might improve the accuracy of hydrometeorological variables in regions with spatial and temporal scarcity of in-situ observations. SRDAS combines assimilation of precipitation estimates from gauge-corrected satellite-based products with spectral nudging technique. The SRDAS hourly outputs provide monthly means of atmospheric and land-surface variables, including precipitation, used in the calculations of the hydrological budget terms. Results show the impact of changes in precipitation on groundwater in the aquifer located near the southeastern coastline of Brazil, through the assessment of the water-cycle terms, using a hydrological model during dry and rainy periods found in the 15-year numerical integration of SRDAS.

  1. A novel convective-scale regional reanalysis COSMO-REA2: Improving the representation of precipitation

    Directory of Open Access Journals (Sweden)

    Sabrina Wahl

    2017-10-01

    Full Text Available Atmospheric reanalyses are a state-of-the-art tool to generate consistent and realistic state estimates of the atmospheric system. They provide a synthesis of various heterogeneous observational systems and model simulations using a physical model together with a data assimilation scheme. Current reanalyses are mainly global, while regional reanalyses are emerging for North America, the polar region, and most recently for Europe. However, deep convection is still parameterized even in the regional reanalyses. A novel convective-scale regional reanalysis system for Central Europe (COSMO-REA2 has been developed by the Hans-Ertel Center for Weather Research – Climate Monitoring Branch. The system is based on the COSMO model and uses observational nudging for regional data assimilation. In addition to conventional observations, radar-derived rain rates are assimilated using latent heat nudging. With a horizontal grid-spacing of 2 km, the model runs without parameterization of deep moist convection. COSMO-REA2 produces horizontal wind fields that represent a realistic energy spectrum for horizontal scales above 14 km. COSMO-REA2 is currently available for seven years from 2007 to 2013.This study illustrates the improved representation of local precipitation over Germany by the convective-scale reanalysis COSMO-REA2 compared to coarser gridded European and global reanalyses. A systematic verification using rain gauge data reveals the added value of high-resolution regional atmospheric reanalyses on different time scales. On monthly to annual time scales, regional reanalyses yield better estimates of the spatial variability of precipitation patterns which can not be provided by coarser gridded global models. On hourly to daily time scales, the convective-scale reanalysis substantially improves the representation of local precipitation in two ways. On the one hand, COSMO-REA2 shows an enhanced representation of observed frequencies of local

  2. Historic and future increase in the global land area affected by monthly heat extremes

    NARCIS (Netherlands)

    Coumou, Dim; Robinson, Alexander

    2013-01-01

    Climatic warming of about 0.5 ° C in the global mean since the 1970s has strongly increased the occurrence-probability of heat extremes on monthly to seasonal time scales. For the 21st century, climate models predict more substantial warming. Here we show that the multi-model mean of the CMIP5

  3. Global modeling of land water and energy balances. Part III: Interannual variability

    Science.gov (United States)

    Shmakin, A.B.; Milly, P.C.D.; Dunne, K.A.

    2002-01-01

    The Land Dynamics (LaD) model is tested by comparison with observations of interannual variations in discharge from 44 large river basins for which relatively accurate time series of monthly precipitation (a primary model input) have recently been computed. When results are pooled across all basins, the model explains 67% of the interannual variance of annual runoff ratio anomalies (i.e., anomalies of annual discharge volume, normalized by long-term mean precipitation volume). The new estimates of basin precipitation appear to offer an improvement over those from a state-of-the-art analysis of global precipitation (the Climate Prediction Center Merged Analysis of Precipitation, CMAP), judging from comparisons of parallel model runs and of analyses of precipitation-discharge correlations. When the new precipitation estimates are used, the performance of the LaD model is comparable to, but not significantly better than, that of a simple, semiempirical water-balance relation that uses only annual totals of surface net radiation and precipitation. This implies that the LaD simulations of interannual runoff variability do not benefit substantially from information on geographical variability of land parameters or seasonal structure of interannual variability of precipitation. The aforementioned analyses necessitated the development of a method for downscaling of long-term monthly precipitation data to the relatively short timescales necessary for running the model. The method merges the long-term data with a reference dataset of 1-yr duration, having high temporal resolution. The success of the method, for the model and data considered here, was demonstrated in a series of model-model comparisons and in the comparisons of modeled and observed interannual variations of basin discharge.

  4. The tritium content of precipitation and surface water in Austria in 1984

    International Nuclear Information System (INIS)

    Rank, D.; Rajner, V.; Lust, G.

    1985-01-01

    This report includes weighted monthly 3 H-means from 23 precipitation sampling stations, 3 H-concentrations of daily precipitation samples from the station Wien-Arsenal, and 3 H-concentrations of monthly samples from 17 surface water sampling stations. (Author)

  5. Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

    Science.gov (United States)

    Robertson, F. R.; Bosilovich, M. G.; Roberts, J. B.; Reichle, R. H.; Adler, R.; Ricciardulli, L.; Berg, W.; Huffman, G. J.

    2013-01-01

    Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal

  6. Asymmetric responses of primary productivity to precipitation extremes: A synthesis of grassland precipitation manipulation experiments.

    Science.gov (United States)

    Wilcox, Kevin R; Shi, Zheng; Gherardi, Laureano A; Lemoine, Nathan P; Koerner, Sally E; Hoover, David L; Bork, Edward; Byrne, Kerry M; Cahill, James; Collins, Scott L; Evans, Sarah; Gilgen, Anna K; Holub, Petr; Jiang, Lifen; Knapp, Alan K; LeCain, Daniel; Liang, Junyi; Garcia-Palacios, Pablo; Peñuelas, Josep; Pockman, William T; Smith, Melinda D; Sun, Shanghua; White, Shannon R; Yahdjian, Laura; Zhu, Kai; Luo, Yiqi

    2017-10-01

    Climatic changes are altering Earth's hydrological cycle, resulting in altered precipitation amounts, increased interannual variability of precipitation, and more frequent extreme precipitation events. These trends will likely continue into the future, having substantial impacts on net primary productivity (NPP) and associated ecosystem services such as food production and carbon sequestration. Frequently, experimental manipulations of precipitation have linked altered precipitation regimes to changes in NPP. Yet, findings have been diverse and substantial uncertainty still surrounds generalities describing patterns of ecosystem sensitivity to altered precipitation. Additionally, we do not know whether previously observed correlations between NPP and precipitation remain accurate when precipitation changes become extreme. We synthesized results from 83 case studies of experimental precipitation manipulations in grasslands worldwide. We used meta-analytical techniques to search for generalities and asymmetries of aboveground NPP (ANPP) and belowground NPP (BNPP) responses to both the direction and magnitude of precipitation change. Sensitivity (i.e., productivity response standardized by the amount of precipitation change) of BNPP was similar under precipitation additions and reductions, but ANPP was more sensitive to precipitation additions than reductions; this was especially evident in drier ecosystems. Additionally, overall relationships between the magnitude of productivity responses and the magnitude of precipitation change were saturating in form. The saturating form of this relationship was likely driven by ANPP responses to very extreme precipitation increases, although there were limited studies imposing extreme precipitation change, and there was considerable variation among experiments. This highlights the importance of incorporating gradients of manipulations, ranging from extreme drought to extreme precipitation increases into future climate change

  7. Precipitation projections under GCMs perspective and Turkish Water Foundation (TWF) statistical downscaling model procedures

    Science.gov (United States)

    Dabanlı, İsmail; Şen, Zekai

    2018-04-01

    The statistical climate downscaling model by the Turkish Water Foundation (TWF) is further developed and applied to a set of monthly precipitation records. The model is structured by two phases as spatial (regional) and temporal downscaling of global circulation model (GCM) scenarios. The TWF model takes into consideration the regional dependence function (RDF) for spatial structure and Markov whitening process (MWP) for temporal characteristics of the records to set projections. The impact of climate change on monthly precipitations is studied by downscaling Intergovernmental Panel on Climate Change-Special Report on Emission Scenarios (IPCC-SRES) A2 and B2 emission scenarios from Max Plank Institute (EH40PYC) and Hadley Center (HadCM3). The main purposes are to explain the TWF statistical climate downscaling model procedures and to expose the validation tests, which are rewarded in same specifications as "very good" for all stations except one (Suhut) station in the Akarcay basin that is in the west central part of Turkey. Eventhough, the validation score is just a bit lower at the Suhut station, the results are "satisfactory." It is, therefore, possible to say that the TWF model has reasonably acceptable skill for highly accurate estimation regarding standard deviation ratio (SDR), Nash-Sutcliffe efficiency (NSE), and percent bias (PBIAS) criteria. Based on the validated model, precipitation predictions are generated from 2011 to 2100 by using 30-year reference observation period (1981-2010). Precipitation arithmetic average and standard deviation have less than 5% error for EH40PYC and HadCM3 SRES (A2 and B2) scenarios.

  8. Assessment of climate change scenarios for Saudi Arabia using data from global climate models

    International Nuclear Information System (INIS)

    Husain, T.; Chowdhury, S.

    2009-01-01

    This study assesses available scientific information and data to predict changes in the climatic parameters in Saudi Arabia for understanding the impacts for mitigation and/or adaptation. Meteorological data from 26 synoptic stations were analyzed in this study. Various climatic change scenarios were reviewed and A 2 and B 2 climatic scenario families were selected. In order to assess long-term global impact, global climatic models were used to simulate changes in temperature, precipitation, relative humidity, solar radiation, and wind circulation. Using global climate model (GCM), monthly time series data was retrieved for Longitude 15 o N to 35 o N and 32.5 o E to 60 o E covering the Kingdom of Saudi Arabia from 1970 to 2100 for all grids. Taking averages of 1970 to 2003 as baseline, change in temperature, relative humidity and precipitation were estimated for the base period. A comparative evaluation was performed for predictive capabilities of these models for temperature, precipitation and relative humidity. Available meteorological data from 1970 to 2003 was used to determine trends. This paper discusses the inconsistency in these parameters for decision-making and recommends future studies by linking global climate models with a suitable regional climate modeling tool. (author)

  9. Analysis of Roanoke Region Weather Patterns Under Global Teleconnections

    OpenAIRE

    LaRocque, Eric John

    2006-01-01

    This work attempts to relate global teleconnections, through physical phenomena such as the El Nino-Southern Oscillation (ENSO), Artic Oscillation (AO), North Atlantic Oscillation (NAO), and the Pacific North American (PNA) pattern to synoptic-scale weather patterns and precipitation in the Roanoke, Virginia region. The first chapter describes the behavior of the El Nino-Southern Oscillation (ENSO) by implementing non-homogeneous and homogeneous Markov Chain models on a monthly time series o...

  10. Radar-Derived Quantitative Precipitation Estimation Based on Precipitation Classification

    Directory of Open Access Journals (Sweden)

    Lili Yang

    2016-01-01

    Full Text Available A method for improving radar-derived quantitative precipitation estimation is proposed. Tropical vertical profiles of reflectivity (VPRs are first determined from multiple VPRs. Upon identifying a tropical VPR, the event can be further classified as either tropical-stratiform or tropical-convective rainfall by a fuzzy logic (FL algorithm. Based on the precipitation-type fields, the reflectivity values are converted into rainfall rate using a Z-R relationship. In order to evaluate the performance of this rainfall classification scheme, three experiments were conducted using three months of data and two study cases. In Experiment I, the Weather Surveillance Radar-1988 Doppler (WSR-88D default Z-R relationship was applied. In Experiment II, the precipitation regime was separated into convective and stratiform rainfall using the FL algorithm, and corresponding Z-R relationships were used. In Experiment III, the precipitation regime was separated into convective, stratiform, and tropical rainfall, and the corresponding Z-R relationships were applied. The results show that the rainfall rates obtained from all three experiments match closely with the gauge observations, although Experiment II could solve the underestimation, when compared to Experiment I. Experiment III significantly reduced this underestimation and generated the most accurate radar estimates of rain rate among the three experiments.

  11. Altered Precipitation and Flow Patterns in the Dunajec River Basin

    Directory of Open Access Journals (Sweden)

    Mariola Kędra

    2017-01-01

    Full Text Available This study analyzes changes in long-term patterns of precipitation and river flow, as well as changes in their variability over the most recent 60 years (1956–2015. The study area is situated in the mountain basin of the Dunajec River, encompassing streams draining the Tatra Mountains in southern Poland. The focus of the study was to evaluate how regional warming translates into precipitation changes in the studied mountain region, and how changes in climate affect sub-regional hydrology. Monthly time series of precipitation measured at several sites were compared for two 30-year periods (1986–2015 versus 1956–1985. The significance of the difference between the periods in question was evaluated by means of the Wilcoxon signed rank test with the Bonferroni correction. The identified shifts in precipitation for 6 months are statistically significant and largely consistent with the revealed changes in river flow patterns. Moreover, significant differences in precipitation variability were noted in the study area, resulting in a significant decrease in the repeatability of precipitation over the most recent 30 years (1986–2015. Changes in the variability of the river flow studied were less visible in this particular mountain region (while significant for two months; however, the overall repeatability of river flow decreased significantly at the same rate as for precipitation.

  12. Improved correlation of monthly mean daily and hourly diffuse radiation with the corresponding global radiation for Indian stations

    International Nuclear Information System (INIS)

    Garg, H.P.; Garg, S.N.

    1985-12-01

    Several existing correlations between radiation monthly mean ratios of global to extraterrestrial and diffuse to global were tried for four Indian stations and found inadequate. New correlations were established for these stations and it was shown that these correlations are highly climate dependent. Classical equation of Liu and Jordon was tried to find hourly diffuse and global radiation from daily sums of diffuse and global radiation respectively. It was suitably modified to suit the Indian data. Equations developed by Collares-Pereira and Rabl have shown excellent agreement with the observed values

  13. Evaluation of CMIP5 continental precipitation simulations relative to satellite-based gauge-adjusted observations

    Science.gov (United States)

    Mehran, A.; AghaKouchak, A.; Phillips, T. J.

    2014-02-01

    The objective of this study is to cross-validate 34 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of precipitation against the Global Precipitation Climatology Project (GPCP) data, quantifying model pattern discrepancies, and biases for both entire distributions and their upper tails. The results of the volumetric hit index (VHI) analysis of the total monthly precipitation amounts show that most CMIP5 simulations are in good agreement with GPCP patterns in many areas but that their replication of observed precipitation over arid regions and certain subcontinental regions (e.g., northern Eurasia, eastern Russia, and central Australia) is problematical. Overall, the VHI of the multimodel ensemble mean and median also are superior to that of the individual CMIP5 models. However, at high quantiles of reference data (75th and 90th percentiles), all climate models display low skill in simulating precipitation, except over North America, the Amazon, and Central Africa. Analyses of total bias (B) in CMIP5 simulations reveal that most models overestimate precipitation over regions of complex topography (e.g., western North and South America and southern Africa and Asia), while underestimating it over arid regions. Also, while most climate model simulations show low biases over Europe, intermodel variations in bias over Australia and Amazonia are considerable. The quantile bias analyses indicate that CMIP5 simulations are even more biased at high quantiles of precipitation. It is found that a simple mean field bias removal improves the overall B and VHI values but does not make a significant improvement at high quantiles of precipitation.

  14. MODIS/Terra Aerosol Cloud Water Vapor Ozone Monthly L3 Global 1Deg CMG V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Aerosol Cloud Water Vapor Ozone Monthly L3 Global 1Deg CMG (MOD08_M3). MODIS was launched aboard the Terra satellite on December 18, 1999 (10:30 am...

  15. Comparison of global observations and trends of total precipitable water derived from microwave radiometers and COSMIC radio occultation from 2006 to 2013

    Directory of Open Access Journals (Sweden)

    S.-P. Ho

    2018-01-01

    Full Text Available We compare atmospheric total precipitable water (TPW derived from the SSM/I (Special Sensor Microwave Imager and SSMIS (Special Sensor Microwave Imager/Sounder radiometers and WindSat to collocated TPW estimates derived from COSMIC (Constellation System for Meteorology, Ionosphere, and Climate radio occultation (RO under clear and cloudy conditions over the oceans from June 2006 to December 2013. Results show that the mean microwave (MW radiometer – COSMIC TPW differences range from 0.06 to 0.18 mm for clear skies, from 0.79 to 0.96 mm for cloudy skies, from 0.46 to 0.49 mm for cloudy but non-precipitating conditions, and from 1.64 to 1.88 mm for precipitating conditions. Because RO measurements are not significantly affected by clouds and precipitation, the biases mainly result from MW retrieval uncertainties under cloudy and precipitating conditions. All COSMIC and MW radiometers detect a positive TPW trend over these 8 years. The trend using all COSMIC observations collocated with MW pixels for this data set is 1.79 mm decade−1, with a 95 % confidence interval of (0.96, 2.63, which is in close agreement with the trend estimated by the collocated MW observations (1.78 mm decade−1 with a 95 % confidence interval of 0.94, 2.62. The sample of MW and RO pairs used in this study is highly biased toward middle latitudes (40–60° N and 40–65° S, and thus these trends are not representative of global average trends. However, they are representative of the latitudes of extratropical storm tracks and the trend values are approximately 4 to 6 times the global average trends, which are approximately 0.3 mm decade−1. In addition, the close agreement of these two trends from independent observations, which represent an increase in TPW in our data set of about 6.9 %, are a strong indication of the positive water vapor–temperature feedback on a warming planet in regions where precipitation from extratropical

  16. Evaluation of Satellite and Model Precipitation Products Over Turkey

    Science.gov (United States)

    Yilmaz, M. T.; Amjad, M.

    2017-12-01

    Satellite-based remote sensing, gauge stations, and models are the three major platforms to acquire precipitation dataset. Among them satellites and models have the advantage of retrieving spatially and temporally continuous and consistent datasets, while the uncertainty estimates of these retrievals are often required for many hydrological studies to understand the source and the magnitude of the uncertainty in hydrological response parameters. In this study, satellite and model precipitation data products are validated over various temporal scales (daily, 3-daily, 7-daily, 10-daily and monthly) using in-situ measured precipitation observations from a network of 733 gauges from all over the Turkey. Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 version 7 and European Center of Medium-Range Weather Forecast (ECMWF) model estimates (daily, 3-daily, 7-daily and 10-daily accumulated forecast) are used in this study. Retrievals are evaluated for their mean and standard deviation and their accuracies are evaluated via bias, root mean square error, error standard deviation and correlation coefficient statistics. Intensity vs frequency analysis and some contingency table statistics like percent correct, probability of detection, false alarm ratio and critical success index are determined using daily time-series. Both ECMWF forecasts and TRMM observations, on average, overestimate the precipitation compared to gauge estimates; wet biases are 10.26 mm/month and 8.65 mm/month, respectively for ECMWF and TRMM. RMSE values of ECMWF forecasts and TRMM estimates are 39.69 mm/month and 41.55 mm/month, respectively. Monthly correlations between Gauges-ECMWF, Gauges-TRMM and ECMWF-TRMM are 0.76, 0.73 and 0.81, respectively. The model and the satellite error statistics are further compared against the gauges error statistics based on inverse distance weighting (IWD) analysis. Both the model and satellite data have less IWD errors (14

  17. Recent and future extreme precipitation over Ukraine

    Science.gov (United States)

    Vyshkvarkova, Olena; Voskresenskaya, Elena

    2014-05-01

    The aim of study is to analyze the parameters of precipitation extremes and inequality over Ukraine in recent climate epoch and their possible changes in the future. Data of observations from 28 hydrometeorological stations over Ukraine and output of GFDL-CM3 model (CMIP5) for XXI century were used in the study. The methods of concentration index (J. Martin-Vide, 2004) for the study of precipitation inequality while the extreme precipitation indices recommended by the ETCCDI - for the frequency of events. Results. Precipitation inequality on the annual and seasonal scales was studied using estimated CI series for 1951-2005. It was found that annual CI ranges vary from 0.58 to 0.64. They increase southward from the north-west (forest zone) and the north-east (forest steppe zone) of Ukraine. CI maxima are located in the coastal regions of the Black Sea and the Sea of Azov. Annual CI spatial distribution indicates that the contribution of extreme precipitation into annual totals is most significant at the boundary zone between steppe and marine regions. At the same time precipitation pattern at the foothill of Carpathian Mountains is more homogenous. The CI minima (0.54) are typical for the winter season in foothill of Ukrainian Carpathians. The CI maxima reach 0.71 in spring at the steppe zone closed to the Black Sea coast. It should be noted that the greatest ranges of CI maximum and CI minimum deviation are typical for spring. It is associated with patterns of cyclone trajectories in that season. The most territory is characterized by tendency to decrease the contribution of extreme precipitation into the total amount (CI linear trends are predominantly negative in all seasons). Decadal and interdecadal variability of precipitation inequality associated with global processes in ocean-atmosphere system are also studied. It was shown that precipitation inequality over Ukraine on 10 - 15 % stronger in negative phase of Pacific Decadal Oscillation and in positive phase

  18. Observed precipitation trends in the Yangtze river catchment from 1951 to 2002

    Institute of Scientific and Technical Information of China (English)

    SUBuda; JIANGTong; SHIYafeng; StefanBECKER; MracoGEMMER

    2004-01-01

    The monthly, seasonal, and annual precipitation trends in the Yangtze river catchment have been detected through analysis of 51 meteorological stations' data between 1950-2002 provided by National Meteorological Administration. Results reveal that: 1) Summer precipitation in the Yangtze river catchment shows significant increasing tendency. The Poyanghu lake basin, Dongtinghu lake basin and Taihu lake basin in the middle and lower reaches are the places showing significant positive trends. Summer precipitation in the middle and lower reaches experienced an abrupt change in the year 1992; 2) The monthly precipitation in months just adjoining to summer shows decreasing tendency in the Yangtze river catchment. The upper and middle reaches in Jialingjiang river basin and Hanshui river basin are the places showing significant negative trends; 3) Extreme precipitation events show an increasing tendency in most places, especially in the middle and lower reaches of the Yangtze river catchment.

  19. Regional improvement of global reanalyses by means of a new long-term Mediterranean hindcasted precipitation dataset: a first study over the Iberian Peninsula

    Directory of Open Access Journals (Sweden)

    M. G. Sotillo

    2006-01-01

    Full Text Available Generation of a Mediterranean long-term (1958-2001 homogeneous high resolution environmental database constituted the main objective whitin the HIPOCAS Project. The high number of parameters included in this database allows a complete characterization of Mediterranean storms. In this paper, the HIPOCAS precipitation reliability over the Iberian Peninsula and the Balearic Islands is evaluated against long-term in-situ observations from Iberia. In order to provide a more complete study, comparisons of the HIPOCAS field with NCEP/NCAR and ERA global reanalysis show the important improvement in the characterisation of the observed precipitation introduced by the HIPOCAS hindcast.

  20. The tritium content of precipitation and surface water in Austria in 1986

    International Nuclear Information System (INIS)

    Rank, D.; Rajner, V.; Lust, G.

    1987-01-01

    This report includes weighted monthly 3 H-means for 23 precipitation sampling stations, 3 H-concentrations of daily precipitation samples from the station Wien-Arsenal, and 3 H-concentrations of monthly samples from 17 surface water sampling stations. 2 refs., 3 tabs., 18 figs. (Author)

  1. Dynamical response of Mediterranean precipitation to greenhouse gases and aerosols

    Directory of Open Access Journals (Sweden)

    T. Tang

    2018-06-01

    Full Text Available Atmospheric aerosols and greenhouse gases affect cloud properties, radiative balance and, thus, the hydrological cycle. Observations show that precipitation has decreased in the Mediterranean since the beginning of the 20th century, and many studies have investigated possible mechanisms. So far, however, the effects of aerosol forcing on Mediterranean precipitation remain largely unknown. Here we compare the modeled dynamical response of Mediterranean precipitation to individual forcing agents in a set of global climate models (GCMs. Our analyses show that both greenhouse gases and aerosols can cause drying in the Mediterranean and that precipitation is more sensitive to black carbon (BC forcing than to well-mixed greenhouse gases (WMGHGs or sulfate aerosol. In addition to local heating, BC appears to reduce precipitation by causing an enhanced positive sea level pressure (SLP pattern similar to the North Atlantic Oscillation–Arctic Oscillation, characterized by higher SLP at midlatitudes and lower SLP at high latitudes. WMGHGs cause a similar SLP change, and both are associated with a northward diversion of the jet stream and storm tracks, reducing precipitation in the Mediterranean while increasing precipitation in northern Europe. Though the applied forcings were much larger, if forcings are scaled to those of the historical period of 1901–2010, roughly one-third (31±17 % of the precipitation decrease would be attributable to global BC forcing with the remainder largely attributable to WMGHGs, whereas global scattering sulfate aerosols would have negligible impacts. Aerosol–cloud interactions appear to have minimal impacts on Mediterranean precipitation in these models, at least in part because many simulations did not fully include such processes; these merit further study. The findings from this study suggest that future BC and WMGHG emissions may significantly affect regional water resources, agricultural practices, ecosystems and

  2. A review of the PERSIANN family global satellite precipitation data products

    Science.gov (United States)

    Nguyen, P.; Ombadi, M.; Ashouri, H.; Thorstensen, A.; Hsu, K. L.; Braithwaite, D.; Sorooshian, S.; William, L.

    2017-12-01

    Precipitation is an integral part of the hydrologic cycle and plays an important role in the water and energy balance of the Earth. Careful and consistent observation of precipitation is important for several reasons. Over the last two decades, the PERSIANN system of precipitation products have been developed at the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California, Irvine in collaboration with NASA, NOAA and the UNESCO G-WADI program. The PERSIANN family includes three main satellite-based precipitation estimation products namely PERSIANN, PERSIANN-CCS, and PERSIANN-CDR. They are accessible through several web-based interfaces maintained by CHRS to serve the needs of researchers, professionals and general public. These interfaces are CHRS iRain, Data Portal and RainSphere, which can be accessed at http://irain.eng.uci.edu, http://chrsdata.eng.uci.edu, and http://rainsphere.eng.uci.edu respectively and can be used for visualization, analysis or download of the data. The main objective of this presentation is to provide a concise and clear summary of the similarities and differences between the three products in terms of attributes and algorithm structure. Moreover, the presentation aims to provide an evaluation of the performance of the products over the Contiguous United States (CONUS) using Climate Prediction Center (CPC) precipitation dataset as a baseline of comparison. Also, an assessment of the behavior of PERSIANN family products over the globe (60°S - 60°N) is performed.

  3. A Global Rapid Integrated Monitoring System for Water Cycle and Water Resource Assessment (Global-RIMS)

    Science.gov (United States)

    Roads, John; Voeroesmarty, Charles

    2005-01-01

    The main focus of our work was to solidify underlying data sets, the data processing tools and the modeling environment needed to perform a series of long-term global and regional hydrological simulations leading eventually to routine hydrometeorological predictions. A water and energy budget synthesis was developed for the Mississippi River Basin (Roads et al. 2003), in order to understand better what kinds of errors exist in current hydrometeorological data sets. This study is now being extended globally with a larger number of observations and model based data sets under the new NASA NEWS program. A global comparison of a number of precipitation data sets was subsequently carried out (Fekete et al. 2004) in which it was further shown that reanalysis precipitation has substantial problems, which subsequently led us to the development of a precipitation assimilation effort (Nunes and Roads 2005). We believe that with current levels of model skill in predicting precipitation that precipitation assimilation is necessary to get the appropriate land surface forcing.

  4. Consequences of Global Warming of 1.5 °C and 2 °C for Regional Temperature and Precipitation Changes in the Contiguous United States.

    Directory of Open Access Journals (Sweden)

    Ambarish V Karmalkar

    Full Text Available The differential warming of land and ocean leads to many continental regions in the Northern Hemisphere warming at rates higher than the global mean temperature. Adaptation and conservation efforts will, therefore, benefit from understanding regional consequences of limiting the global mean temperature increase to well below 2°C above pre-industrial levels, a limit agreed upon at the United Nations Climate Summit in Paris in December 2015. Here, we analyze climate model simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5 to determine the timing and magnitude of regional temperature and precipitation changes across the contiguous United States (US for global warming of 1.5 and 2°C and highlight consensus and uncertainties in model projections and their implications for making decisions. The regional warming rates differ considerably across the contiguous US, but all regions are projected to reach 2°C about 10-20 years before the global mean temperature. Although there is uncertainty in the timing of exactly when the 1.5 and 2°C thresholds will be crossed regionally, over 80% of the models project at least 2°C warming by 2050 for all regions for the high emissions scenario. This threshold-based approach also highlights regional variations in the rate of warming across the US. The fastest warming region in the contiguous US is the Northeast, which is projected to warm by 3°C when global warming reaches 2°C. The signal-to-noise ratio calculations indicate that the regional warming estimates remain outside the envelope of uncertainty throughout the twenty-first century, making them potentially useful to planners. The regional precipitation projections for global warming of 1.5°C and 2°C are uncertain, but the eastern US is projected to experience wetter winters and the Great Plains and the Northwest US are projected to experience drier summers in the future. The impact of different scenarios on regional precipitation

  5. The Global Precipitation Measurement (GPM) Spacecraft Power System Design and Orbital Performance

    Science.gov (United States)

    Dakermanji, George; Burns, Michael; Lee, Leonine; Lyons, John; Kim, David; Spitzer, Thomas; Kercheval, Bradford

    2016-01-01

    The Global Precipitation Measurement (GPM) spacecraft was jointly developed by National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA). It is a Low Earth Orbit (LEO) spacecraft launched on February 27, 2014. The spacecraft is in a circular 400 Km altitude, 65 degrees inclination nadir pointing orbit with a three year basic mission life. The solar array consists of two sun tracking wings with cable wraps. The panels are populated with triple junction cells of nominal 29.5% efficiency. One axis is canted by 52 degrees to provide power to the spacecraft at high beta angles. The power system is a Direct Energy Transfer (DET) system designed to support 1950 Watts orbit average power. The batteries use SONY 18650HC cells and consist of three 8s x 84p batteries operated in parallel as a single battery. The paper describes the power system design details, its performance to date and the lithium ion battery model that was developed for use in the energy balance analysis and is being used to predict the on-orbit health of the battery.

  6. Optimizing Orbit-Instrument Configuration for Global Precipitation Mission (GPM) Satellite Fleet

    Science.gov (United States)

    Smith, Eric A.; Adams, James; Baptista, Pedro; Haddad, Ziad; Iguchi, Toshio; Im, Eastwood; Kummerow, Christian; Einaudi, Franco (Technical Monitor)

    2001-01-01

    Following the scientific success of the Tropical Rainfall Measuring Mission (TRMM) spearheaded by a group of NASA and NASDA scientists, their external scientific collaborators, and additional investigators within the European Union's TRMM Research Program (EUROTRMM), there has been substantial progress towards the development of a new internationally organized, global scale, and satellite-based precipitation measuring mission. The highlights of this newly developing mission are a greatly expanded scope of measuring capability and a more diversified set of science objectives. The mission is called the Global Precipitation Mission (GPM). Notionally, GPM will be a constellation-type mission involving a fleet of nine satellites. In this fleet, one member is referred to as the "core" spacecraft flown in an approximately 70 degree inclined non-sun-synchronous orbit, somewhat similar to TRMM in that it carries both a multi-channel polarized passive microwave radiometer (PMW) and a radar system, but in this case it will be a dual frequency Ku-Ka band radar system enabling explicit measurements of microphysical DSD properties. The remainder of fleet members are eight orbit-synchronized, sun-synchronous "constellation" spacecraft each carrying some type of multi-channel PMW radiometer, enabling no worse than 3-hour diurnal sampling over the entire globe. In this configuration the "core" spacecraft serves as a high quality reference platform for training and calibrating the PMW rain retrieval algorithms used with the "constellation" radiometers. Within NASA, GPM has advanced to the pre-formulation phase which has enabled the initiation of a set of science and technology studies which will help lead to the final mission design some time in the 2003 period. This presentation first provides an overview of the notional GPM program and mission design, including its organizational and programmatic concepts, scientific agenda, expected instrument package, and basic flight

  7. Benchmarking monthly homogenization algorithms

    Science.gov (United States)

    Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.

    2011-08-01

    The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random break-type inhomogeneities were added to the simulated datasets modeled as a Poisson process with normally distributed breakpoint sizes. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including (i) the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii) the error in linear trend estimates and (iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data

  8. Recent advances in precipitation-bias correction and application

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Significant progresses have been made in recent years in precipitation data analyses at regional to global scales. This paper re-views and synthesizes recent advances in precipitation-bias corrections and applications in many countries and over the cold re-gions. The main objective of this review is to identify and examine gaps in regional and national precipitation-error analyses. This paper also discusses and recommends future research needs and directions. More effort and coordination are necessary in the determinations of precipitation biases on large regions across national borders. It is important to emphasize that bias cor-rections of precipitation measurements affect both water budget and energy balance calculations, particularly over the cold regions.

  9. Spatio-Temporal Analysis of the Accuracy of Tropical Multisatellite Precipitation Analysis 3B42 Precipitation Data in Mid-High Latitudes of China

    Science.gov (United States)

    Cai, Yancong; Jin, Changjie; Wang, Anzhi; Guan, Dexin; Wu, Jiabing; Yuan, Fenghui; Xu, Leilei

    2015-01-01

    Satellite-based precipitation data have contributed greatly to quantitatively forecasting precipitation, and provides a potential alternative source for precipitation data allowing researchers to better understand patterns of precipitation over ungauged basins. However, the absence of calibration satellite data creates considerable uncertainties for The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 product over high latitude areas beyond the TRMM satellites latitude band (38°NS). This study attempts to statistically assess TMPA V7 data over the region beyond 40°NS using data obtained from numerous weather stations in 1998–2012. Comparative analysis at three timescales (daily, monthly and annual scale) indicates that adoption of a monthly adjustment significantly improved correlation at a larger timescale increasing from 0.63 to 0.95; TMPA data always exhibits a slight overestimation that is most serious at a daily scale (the absolute bias is 103.54%). Moreover, the performance of TMPA data varies across all seasons. Generally, TMPA data performs best in summer, but worst in winter, which is likely to be associated with the effects of snow/ice-covered surfaces and shortcomings of precipitation retrieval algorithms. Temporal and spatial analysis of accuracy indices suggest that the performance of TMPA data has gradually improved and has benefited from upgrades; the data are more reliable in humid areas than in arid regions. Special attention should be paid to its application in arid areas and in winter with poor scores of accuracy indices. Also, it is clear that the calibration can significantly improve precipitation estimates, the overestimation by TMPA in TRMM-covered area is about a third as much as that in no-TRMM area for monthly and annual precipitation. The systematic evaluation of TMPA over mid-high latitudes provides a broader understanding of satellite-based precipitation estimates, and these data are

  10. Spatio-temporal analysis of the accuracy of tropical multisatellite precipitation analysis 3B42 precipitation data in mid-high latitudes of China.

    Directory of Open Access Journals (Sweden)

    Yancong Cai

    Full Text Available Satellite-based precipitation data have contributed greatly to quantitatively forecasting precipitation, and provides a potential alternative source for precipitation data allowing researchers to better understand patterns of precipitation over ungauged basins. However, the absence of calibration satellite data creates considerable uncertainties for The Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis (TMPA 3B42 product over high latitude areas beyond the TRMM satellites latitude band (38°NS. This study attempts to statistically assess TMPA V7 data over the region beyond 40°NS using data obtained from numerous weather stations in 1998-2012. Comparative analysis at three timescales (daily, monthly and annual scale indicates that adoption of a monthly adjustment significantly improved correlation at a larger timescale increasing from 0.63 to 0.95; TMPA data always exhibits a slight overestimation that is most serious at a daily scale (the absolute bias is 103.54%. Moreover, the performance of TMPA data varies across all seasons. Generally, TMPA data performs best in summer, but worst in winter, which is likely to be associated with the effects of snow/ice-covered surfaces and shortcomings of precipitation retrieval algorithms. Temporal and spatial analysis of accuracy indices suggest that the performance of TMPA data has gradually improved and has benefited from upgrades; the data are more reliable in humid areas than in arid regions. Special attention should be paid to its application in arid areas and in winter with poor scores of accuracy indices. Also, it is clear that the calibration can significantly improve precipitation estimates, the overestimation by TMPA in TRMM-covered area is about a third as much as that in no-TRMM area for monthly and annual precipitation. The systematic evaluation of TMPA over mid-high latitudes provides a broader understanding of satellite-based precipitation estimates, and these

  11. Pareto-Optimal Estimates of California Precipitation Change

    Science.gov (United States)

    Langenbrunner, Baird; Neelin, J. David

    2017-12-01

    In seeking constraints on global climate model projections under global warming, one commonly finds that different subsets of models perform well under different objective functions, and these trade-offs are difficult to weigh. Here a multiobjective approach is applied to a large set of subensembles generated from the Climate Model Intercomparison Project phase 5 ensemble. We use observations and reanalyses to constrain tropical Pacific sea surface temperatures, upper level zonal winds in the midlatitude Pacific, and California precipitation. An evolutionary algorithm identifies the set of Pareto-optimal subensembles across these three measures, and these subensembles are used to constrain end-of-century California wet season precipitation change. This methodology narrows the range of projections throughout California, increasing confidence in estimates of positive mean precipitation change. Finally, we show how this technique complements and generalizes emergent constraint approaches for restricting uncertainty in end-of-century projections within multimodel ensembles using multiple criteria for observational constraints.

  12. Global ice volume variations through the last glacial cycle simulated by a 3-D ice-dynamical model

    NARCIS (Netherlands)

    Bintanja, R.; Wal, R.S.W. van de; Oerlemans, J.

    2002-01-01

    A coupled ice sheet—ice shelf—bedrock model was run at 20km resolution to simulate the evolution of global ice cover during the last glacial cycle. The mass balance model uses monthly mean temperature and precipitation as input and incorporates the albedo—mass balance feedback. The model is forced

  13. Error threshold inference from Global Precipitation Measurement (GPM) satellite rainfall data and interpolated ground-based rainfall measurements in Metro Manila

    Science.gov (United States)

    Ampil, L. J. Y.; Yao, J. G.; Lagrosas, N.; Lorenzo, G. R. H.; Simpas, J.

    2017-12-01

    The Global Precipitation Measurement (GPM) mission is a group of satellites that provides global observations of precipitation. Satellite-based observations act as an alternative if ground-based measurements are inadequate or unavailable. Data provided by satellites however must be validated for this data to be reliable and used effectively. In this study, the Integrated Multisatellite Retrievals for GPM (IMERG) Final Run v3 half-hourly product is validated by comparing against interpolated ground measurements derived from sixteen ground stations in Metro Manila. The area considered in this study is the region 14.4° - 14.8° latitude and 120.9° - 121.2° longitude, subdivided into twelve 0.1° x 0.1° grid squares. Satellite data from June 1 - August 31, 2014 with the data aggregated to 1-day temporal resolution are used in this study. The satellite data is directly compared to measurements from individual ground stations to determine the effect of the interpolation by contrast against the comparison of satellite data and interpolated measurements. The comparisons are calculated by taking a fractional root-mean-square error (F-RMSE) between two datasets. The results show that interpolation improves errors compared to using raw station data except during days with very small amounts of rainfall. F-RMSE reaches extreme values of up to 654 without a rainfall threshold. A rainfall threshold is inferred to remove extreme error values and make the distribution of F-RMSE more consistent. Results show that the rainfall threshold varies slightly per month. The threshold for June is inferred to be 0.5 mm, reducing the maximum F-RMSE to 9.78, while the threshold for July and August is inferred to be 0.1 mm, reducing the maximum F-RMSE to 4.8 and 10.7, respectively. The maximum F-RMSE is reduced further as the threshold is increased. Maximum F-RMSE is reduced to 3.06 when a rainfall threshold of 10 mm is applied over the entire duration of JJA. These results indicate that

  14. Short-Term Effects of Changing Precipitation Patterns on Shrub-Steppe Grasslands: Seasonal Watering Is More Important than Frequency of Watering Events.

    Science.gov (United States)

    Densmore-McCulloch, Justine A; Thompson, Donald L; Fraser, Lauchlan H

    2016-01-01

    Climate change is expected to alter precipitation patterns. Droughts may become longer and more frequent, and the timing and intensity of precipitation may change. We tested how shifting precipitation patterns, both seasonally and by frequency of events, affects soil nitrogen availability, plant biomass and diversity in a shrub-steppe temperate grassland along a natural productivity gradient in Lac du Bois Grasslands Protected Area near Kamloops, British Columbia, Canada. We manipulated seasonal watering patterns by either exclusively watering in the spring or the fall. To simulate spring precipitation we restricted precipitation inputs in the fall, then added 50% more water than the long term average in the spring, and vice-versa for the fall precipitation treatment. Overall, the amount of precipitation remained roughly the same. We manipulated the frequency of rainfall events by either applying water weekly (frequent) or monthly (intensive). After 2 years, changes in the seasonality of watering had greater effects on plant biomass and diversity than changes in the frequency of watering. Fall watering reduced biomass and increased species diversity, while spring watering had little effect. The reduction in biomass in fall watered treatments was due to a decline in grasses, but not forbs. Plant available N, measured by Plant Root Simulator (PRS)-probes, increased from spring to summer to fall, and was higher in fall watered treatments compared to spring watered treatments when measured in the fall. The only effect observed due to frequency of watering events was greater extractable soil N in monthly applied treatments compared to weekly watering treatments. Understanding the effects of changing precipitation patterns on grasslands will allow improved grassland conservation and management in the face of global climatic change, and here we show that if precipitation is more abundant in the fall, compared to the spring, grassland primary productivity will likely be

  15. Seasonal Cycle in German Daily Precipitation Extremes

    Directory of Open Access Journals (Sweden)

    Madlen Fischer

    2018-01-01

    Full Text Available The seasonal cycle of extreme precipitation in Germany is investigated by fitting statistical models to monthly maxima of daily precipitation sums for 2,865 rain gauges. The basis is a non-stationary generalized extreme value (GEV distribution variation of location and scale parameters. The negative log-likelihood serves as the forecast error for a cross validation to select adequate orders of the harmonic functions for each station. For nearly all gauges considered, the seasonal model is more appropriate to estimate return levels on a monthly scale than a stationary GEV used for individual months. The 100-year return-levels show the influence of cyclones in the western, and convective events in the eastern part of Germany. In addition to resolving the seasonality, we use a simulation study to show that annual return levels can be estimated more precisely from a monthly-resolved seasonal model than from a stationary model based on annual maxima.

  16. Dissolved organic carbon in the precipitation of Seoul, Korea: Implications for global wet depositional flux of fossil-fuel derived organic carbon

    Science.gov (United States)

    Yan, Ge; Kim, Guebuem

    2012-11-01

    Precipitation was sampled in Seoul over a one-year period from 2009 to 2010 to investigate the sources and fluxes of atmospheric dissolved organic carbon (DOC). The concentrations of DOC varied from 15 μM to 780 μM, with a volume-weighted average of 94 μM. On the basis of correlation analysis using the commonly acknowledged tracers, such as vanadium, the combustion of fossil-fuels was recognized to be the dominant source. With the aid of air mass backward trajectory analyses, we concluded that the primary fraction of DOC in our precipitation samples originated locally in Korea, albeit the frequent long-range transport from eastern and northeastern China might contribute substantially. In light of the relatively invariant organic carbon to sulfur mass ratios in precipitation over Seoul and other urban regions around the world, the global magnitude of wet depositional DOC originating from fossil-fuels was calculated to be 36 ± 10 Tg C yr-1. Our study further underscores the potentially significant environmental impacts that might be brought about by this anthropogenically derived component of organic carbon in the atmosphere.

  17. Future increases in Arctic precipitation linked to local evaporation and sea-ice retreat.

    Science.gov (United States)

    Bintanja, R; Selten, F M

    2014-05-22

    Precipitation changes projected for the end of the twenty-first century show an increase of more than 50 per cent in the Arctic regions. This marked increase, which is among the highest globally, has previously been attributed primarily to enhanced poleward moisture transport from lower latitudes. Here we use state-of-the-art global climate models to show that the projected increases in Arctic precipitation over the twenty-first century, which peak in late autumn and winter, are instead due mainly to strongly intensified local surface evaporation (maximum in winter), and only to a lesser degree due to enhanced moisture inflow from lower latitudes (maximum in late summer and autumn). Moreover, we show that the enhanced surface evaporation results mainly from retreating winter sea ice, signalling an amplified Arctic hydrological cycle. This demonstrates that increases in Arctic precipitation are firmly linked to Arctic warming and sea-ice decline. As a result, the Arctic mean precipitation sensitivity (4.5 per cent increase per degree of temperature warming) is much larger than the global value (1.6 to 1.9 per cent per kelvin). The associated seasonally varying increase in Arctic precipitation is likely to increase river discharge and snowfall over ice sheets (thereby affecting global sea level), and could even affect global climate through freshening of the Arctic Ocean and subsequent modulations of the Atlantic meridional overturning circulation.

  18. Climatological Modeling of Monthly Air Temperature and Precipitation in Egypt through GIS Techniques

    Science.gov (United States)

    El Kenawy, A.

    2009-09-01

    This paper describes a method for modeling and mapping four climatic variables (maximum temperature, minimum temperature, mean temperature and total precipitation) in Egypt using a multiple regression approach implemented in a GIS environment. In this model, a set of variables including latitude, longitude, elevation within a distance of 5, 10 and 15 km, slope, aspect, distance to the Mediterranean Sea, distance to the Red Sea, distance to the Nile, ratio between land and water masses within a radius of 5, 10, 15 km, the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI), the Normalized Difference Temperature Index (NDTI) and reflectance are included as independent variables. These variables were integrated as raster layers in MiraMon software at a spatial resolution of 1 km. Climatic variables were considered as dependent variables and averaged from quality controlled and homogenized 39 series distributing across the entire country during the period of (1957-2006). For each climatic variable, digital and objective maps were finally obtained using the multiple regression coefficients at monthly, seasonal and annual timescale. The accuracy of these maps were assessed through cross-validation between predicted and observed values using a set of statistics including coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), mean bias Error (MBE) and D Willmott statistic. These maps are valuable in the sense of spatial resolution as well as the number of observatories involved in the current analysis.

  19. Constraining precipitation amount and distribution over cold regions using GRACE

    Science.gov (United States)

    Behrangi, A.; Reager, J. T., II; Gardner, A. S.; Fisher, J.

    2017-12-01

    Current quantitative knowledge on the amount and distribution of precipitation in high-elevation and high latitude regions is limited due to instrumental and retrieval shortcomings. Here we demonstrate how that satellite gravimetry (Gravity Recovery and Climate Experiment, GRACE) can be used to provide an independent estimate of monthly accumulated precipitation using mass balance. Results showed that the GRACE-based precipitation estimate has the highest agreement with most of the commonly used precipitation products in summer, but it deviates from them in cold months, when the other products are expected to have larger error. We also observed that as near surface temperature decreases products tend to underestimate accumulated precipitation retrieved from GRACE. The analysis performed using various products such as GPCP, GPCC, TRMM, and gridded station data over vast regions in high latitudes and two large endorheic basins in High Mountain Asia. Based on the analysis over High Mountain Asia it was found that most of the products capture about or less than 50% of the total precipitation estimated using GRACE in winter. Overall, GPCP showed better agreement with GRACE estimate than other products. Yet on average GRACE showed 30% more annual precipitation than GPCP in the study basin.

  20. An Evaluation of the Predictability of Austral Summer Season Precipitation over South America.

    Science.gov (United States)

    Misra, Vasubandhu

    2004-03-01

    In this study predictability of austral summer seasonal precipitation over South America is investigated using a 12-yr set of a 3.5-month range (seasonal) and a 17-yr range (continuous multiannual) five-member ensemble integrations of the Center for Ocean Land Atmosphere Studies (COLA) atmospheric general circulation model (AGCM). These integrations were performed with prescribed observed sea surface temperature (SST); therefore, skill attained represents an estimate of the upper bound of the skill achievable by COLA AGCM with predicted SST. The seasonal runs outperform the multiannual model integrations both in deterministic and probabilistic skill. The simulation of the January February March (JFM) seasonal climatology of precipitation is vastly superior in the seasonal runs except over the Nordeste region where the multiannual runs show a marginal improvement. The teleconnection of the ensemble mean JFM precipitation over tropical South America with global contemporaneous observed sea surface temperature in the seasonal runs conforms more closely to observations than in the multiannual runs. Both the sets of runs clearly beat persistence in predicting the interannual precipitation anomalies over the Amazon River basin, Nordeste, South Atlantic convergence zone, and subtropical South America. However, both types of runs display poorer simulations over subtropical regions than the tropical areas of South America. The examination of probabilistic skill of precipitation supports the conclusions from deterministic skill analysis that the seasonal runs yield superior simulations than the multiannual-type runs.

  1. Inorganic nitrogen in precipitation and atmospheric sediments

    Energy Technology Data Exchange (ETDEWEB)

    Matheson, D H

    1951-01-01

    In an investigation covering 18 months, daily determinations were made of the inorganic nitrogen contained in precipitation and atmospheric sediments collected at Hamilton, Ont. The nitrogen fall for the whole period averaged 5.8 lb. N per acre per year. Sixty-one per cent of the total nitrogen was collected on 25% of the days when precipitation occurred. The balance, occurring on days without precipitation, is attributable solely to the sedimentation of dust. Ammonia nitrogen averaged 56% of the total, but the proportion for individual days varied widely.

  2. Spatial and temporal variability of precipitation in Serbia for the period 1961-2010

    Science.gov (United States)

    Milovanović, Boško; Schuster, Phillip; Radovanović, Milan; Vakanjac, Vesna Ristić; Schneider, Christoph

    2017-10-01

    Monthly, seasonal and annual sums of precipitation in Serbia were analysed in this paper for the period 1961-2010. Latitude, longitude and altitude of 421 precipitation stations and terrain features in their close environment (slope and aspect of terrain within a radius of 10 km around the station) were used to develop a regression model on which spatial distribution of precipitation was calculated. The spatial distribution of annual, June (maximum values for almost all of the stations) and February (minimum values for almost all of the stations) precipitation is presented. Annual precipitation amounts ranged from 500 to 600 mm to over 1100 mm. June precipitation ranged from 60 to 140 mm and February precipitation from 30 to 100 mm. The validation results expressed as root mean square error (RMSE) for monthly sums ranged from 3.9 mm in October (7.5% of the average precipitation for this month) to 6.2 mm in April (10.4%). For seasonal sums, RMSE ranged from 10.4 mm during autumn (6.1% of the average precipitation for this season) to 20.5 mm during winter (13.4%). On the annual scale, RMSE was 68 mm (9.5% of the average amount of precipitation). We further analysed precipitation trends using Sen's estimation, while the Mann-Kendall test was used for testing the statistical significance of the trends. For most parts of Serbia, the mean annual precipitation trends fell between -5 and +5 and +5 and +15 mm/decade. June precipitation trends were mainly between -8 and +8 mm/decade. February precipitation trends generally ranged from -3 to +3 mm/decade.

  3. Analysis of Precipitation and Drought Data in Hexi Corridor, Northwest China

    Directory of Open Access Journals (Sweden)

    Xinyang Yu

    2017-05-01

    Full Text Available Precipitation data from nine meteorological stations in arid oases of Hexi Corridor, northwest China during 1970–2012 were analyzed to detect trends in precipitation and Standardized Precipitation Index (SPI at multiple time scales using linear regression, Mann–Kendall and Spearman’s Rho tests. The results found that annual precipitation in the observed stations was rare and fell into the arid region category according to the aridity index analysis. The monthly analysis of precipitation found that three stations showed significant increasing trends in different months, while on the annual level, only Yongchang station had a significant increasing trend. The analysis of SPI-12 found three main drought intervals, i.e., 1984–1987, 1991–1992 and 2008–2011, and an extremely dry year among the stations was recorded in 1986; the southeast and middle portions of the study area are expected to have more precipitation and less dry conditions.

  4. Increased Kawasaki Disease Incidence Associated With Higher Precipitation and Lower Temperatures, Japan, 1991-2004.

    Science.gov (United States)

    Abrams, Joseph Y; Blase, Jennifer L; Belay, Ermias D; Uehara, Ritei; Maddox, Ryan A; Schonberger, Lawrence B; Nakamura, Yosikazu

    2018-06-01

    Kawasaki disease (KD) is an acute febrile vasculitis, which primarily affects children. The etiology of KD is unknown; while certain characteristics of the disease suggest an infectious origin, genetic or environmental factors may also be important. Seasonal patterns of KD incidence are well documented, but it is unclear whether these patterns are caused by changes in climate or by other unknown seasonal effects. The relationship between KD incidence and deviations from expected temperature and precipitation were analyzed using KD incidence data from Japanese nationwide epidemiologic surveys (1991-2004) and climate data from 136 weather stations of the Japan Meteorological Agency. Seven separate Poisson-distributed generalized linear regression models were run to examine the effects of temperature and precipitation on KD incidence in the same month as KD onset and the previous 1, 2, 3, 4, 5 and 6 months, controlling for geography as well as seasonal and long-term trends in KD incidence. KD incidence was negatively associated with temperature in the previous 2, 3, 4 and 5 months and positively associated with precipitation in the previous 1 and 2 months. The model that best predicted variations in KD incidence used climate data from the previous 2 months. An increase in total monthly precipitation by 100 mm was associated with increased KD incidence (rate ratio [RR] 1.012, 95% confidence interval [CI]: 1.005-1.019), and an increase of monthly mean temperature by 1°C was associated with decreased KD incidence (RR 0.984, 95% CI: 0.978-0.990). KD incidence was significantly affected by temperature and precipitation in previous months independent of other unknown seasonal factors. Climate data from the previous 2 months best predicted the variations in KD incidence. Although fairly minor, the effect of temperature and precipitation independent of season may provide additional clues to the etiology of KD.

  5. Regime-dependent forecast uncertainty of convective precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Keil, Christian; Craig, George C. [Muenchen Univ. (Germany). Meteorologisches Inst.

    2011-04-15

    Forecast uncertainty of convective precipitation is influenced by all scales, but in different ways in different meteorological situations. Forecasts of the high resolution ensemble prediction system COSMO-DE-EPS of Deutscher Wetterdienst (DWD) are used to examine the dominant sources of uncertainty of convective precipitation. A validation with radar data using traditional as well as spatial verification measures highlights differences in precipitation forecast performance in differing weather regimes. When the forecast uncertainty can primarily be associated with local, small-scale processes individual members run with the same variation of the physical parameterisation driven by different global models outperform all other ensemble members. In contrast when the precipitation is governed by the large-scale flow all ensemble members perform similarly. Application of the convective adjustment time scale confirms this separation and shows a regime-dependent forecast uncertainty of convective precipitation. (orig.)

  6. Harmonic analysis of the precipitation in Greece

    Science.gov (United States)

    Nastos, P. T.; Zerefos, C. S.

    2009-04-01

    Greece is a country with a big variety of climates due to its geographical position, to the many mountain ranges and also to the multifarious and long coastline. The mountainous volumes are of such orientation that influences the distribution of the precipitation, having as a result, Western Greece to present great differentiations from Central and Eastern Greece. The application of harmonic analysis to the annual variability of precipitation is the goal of this study, so that the components, which compose the annual variability, be elicited. For this purpose, the mean monthly precipitation data from 30 meteorological stations of National Meteorological Service were used for the time period 1950-2000. The initial target is to reduce the number of variables and to detect structure in the relationships between variables. The most commonly used technique for this purpose is the application of Factor Analysis to a table having as columns the meteorological stations-variables and rows the monthly mean precipitation, so that 2 main factors were calculated, which explain the 98% of total variability of precipitation in Greece. Factor 1, representing the so-called uniform field and interpreting the most of the total variance, refers in fact to the Mediterranean depressions, affecting mainly the West of Greece and also the East Aegean and the Asia Minor coasts. In the process, the Fourier Analysis was applied to the factor scores extracted from the Factor Analysis, so that 2 harmonic components are resulted, which explain above the 98% of the total variability of each main factor, and are due to different synoptic and thermodynamic processes associated with Greece's precipitation construction. Finally, the calculation of the time of occurrence of the maximum precipitation, for each harmonic component of each one of the two main factors, gives the spatial distribution of appearance of the maximum precipitation in the Hellenic region.

  7. Comparison of five gridded precipitation products at climatological scales over West Africa

    Science.gov (United States)

    Akinsanola, A. A.; Ogunjobi, K. O.; Ajayi, V. O.; Adefisan, E. A.; Omotosho, J. A.; Sanogo, S.

    2017-12-01

    The paper aimed at assessing the capabilities and limitations of five different precipitation products to describe rainfall over West Africa. Five gridded precipitation datasets of the Tropical Rainfall Measurement Mission (TRMM) Multi-Platform Analysis (TMPA 3B43v7); University of Delaware (UDEL version 3.01); Climatic Research Unit (CRU version 3.1); Global Precipitation Climatology Centre (GPCC version 7) and African Rainfall Climatology (ARC version 2) were compared and validated with reference ground observation data from 81 stations spanning a 19-year period, from January 1990 to December 2008. Spatial investigation of the precipitation datasets was performed, and their capability to replicate the inter-annual and intra-seasonal variability was also assessed. The ability of the products to capture the El Nino and La Nina events were also assessed. Results show that all the five datasets depicted similar spatial distribution of mean rainfall climatology, although differences exist in the total rainfall amount for each precipitation dataset. Further analysis shows that the three distinct phases of the mean annual cycle of the West Africa Monsoon precipitation were well captured by the datasets. However, CRU, GPCC and UDEL failed to capture the little dry season in the month of August while UDEL and GPCC underestimated rainfall amount in the Sahel region. Results of the inter-annual precipitation anomalies shows that ARC2 fail to capture about 46% of the observed variability while the other four datasets exhibits a greater performance ( r > 0.9). All the precipitation dataset except ARC2 were consistent with the ground observation in capturing the dry and wet conditions associated with El Nino and La Nina events, respectively. ARC2 tends to overestimate the El Nino event and failed to capture the La Nina event in all the years considered. In general GPCC, CRU and TRMM were found to be the most outstanding datasets and can, therefore, be used for precipitation

  8. Global resistance and resilience of primary production following extreme drought are predicted by mean annual precipitation

    Science.gov (United States)

    Stuart-Haëntjens, E. J.; De Boeck, H. J.; Lemoine, N. P.; Gough, C. M.; Kröel-Dulay, G.; Mänd, P.; Jentsch, A.; Schmidt, I. K.; Bahn, M.; Lloret, F.; Kreyling, J.; Wohlgemuth, T.; Stampfli, A.; Anderegg, W.; Classen, A. T.; Smith, M. D.

    2017-12-01

    Extreme drought is increasing globally in frequency and intensity, with uncertain consequences for the resistance and resilience of key ecosystem functions, including primary production. Primary production resistance, the capacity of an ecosystem to withstand change in primary production following extreme climate, and resilience, the degree to which primary production recovers, vary among and within ecosystem types, obscuring global patterns of resistance and resilience to extreme drought. Past syntheses on resistance have focused climatic gradients or individual ecosystem types, without assessing interactions between the two. Theory and many empirical studies suggest that forest production is more resistant but less resilient than grassland production to extreme drought, though some empirical studies reveal that these trends are not universal. Here, we conducted a global meta-analysis of sixty-four grassland and forest sites, finding that primary production resistance to extreme drought is predicted by a common continuum of mean annual precipitation (MAP). However, grasslands and forests exhibit divergent production resilience relationships with MAP. We discuss the likely mechanisms underlying the mixed production resistance and resilience patterns of forests and grasslands, including different plant species turnover times and drought adaptive strategies. These findings demonstrate the primary production responses of forests and grasslands to extreme drought are mixed, with far-reaching implications for Earth System Models, ecosystem management, and future studies of extreme drought resistance and resilience.

  9. Gridded Mean Monthly Temperature and Precipitation Data for Alaska, British Columbia, and Yukon

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — To aid in better understanding the temperature and precipitation data of the spatially variable climate of Alaska and Northwest Canada, this dataset was created via...

  10. Hydrological modeling of the Peruvian–Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset

    Directory of Open Access Journals (Sweden)

    R. Zubieta

    2017-07-01

    Full Text Available In the last two decades, rainfall estimates provided by the Tropical Rainfall Measurement Mission (TRMM have proven applicable in hydrological studies. The Global Precipitation Measurement (GPM mission, which provides the new generation of rainfall estimates, is now considered a global successor to TRMM. The usefulness of GPM data in hydrological applications, however, has not yet been evaluated over the Andean and Amazonian regions. This study uses GPM data provided by the Integrated Multi-satellite Retrievals (IMERG (product/final run as input to a distributed hydrological model for the Amazon Basin of Peru and Ecuador for a 16-month period (from March 2014 to June 2015 when all datasets are available. TRMM products (TMPA V7 and TMPA RT datasets and a gridded precipitation dataset processed from observed rainfall are used for comparison. The results indicate that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, compared to observed rainfall (by 11.1 and 15.7 %, respectively. In general, GPM-IMERG, TMPA V7 and TMPA RT correlate with observed rainfall, with a similar number of rain events correctly detected ( ∼  20 %. Statistical analysis of modeled streamflows indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets in southern regions (Ucayali Basin. GPM-IMERG, TMPA V7 and TMPA RT do not properly simulate streamflows in northern regions (Marañón and Napo basins, probably because of the lack of adequate rainfall estimates in northern Peru and the Ecuadorian Amazon.

  11. Data Descriptor: TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015

    Science.gov (United States)

    John T. Abatzoglou; Solomon Z. Dobrowski; Sean A. Parks; Katherine C. Hegewisch

    2018-01-01

    We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from...

  12. Seasonal fluctuations of organophosphate concentrations in precipitation and storm water runoff.

    Science.gov (United States)

    Regnery, Julia; Püttmann, Wilhelm

    2010-02-01

    To investigate seasonal fluctuations and trends of organophosphate (flame retardants, plasticizers) concentrations in rain and snow, precipitation samples were collected in 2007-2009 period at a densely populated urban sampling site and two sparsely populated rural sampling sites in middle Germany. In addition, storm water runoff was sampled from May 2008 to April 2009 at an urban storm water holding tank (SWHT). Samples were analyzed for tris(2-chloroethyl) phosphate (TCEP), tris(2-chloro-1-methylethyl) phosphate (TCPP), tris(1,3-dichloro-2-propyl) phosphate (TDCP), tris(2-butoxyethyl) phosphate (TBEP), tri-iso-butyl phosphate (TiBP), and tri-n-butyl phosphate (TnBP) by gas chromatography-mass spectrometry after solid phase extraction. Among the six analyzed organophosphates (OPs), TCPP dominated in all precipitation and SWHT water samples with maximum concentrations exceeding 1000ngL(-1). For all analytes, no seasonal trends were observed at the urban precipitation sampling site, although atmospheric photooxidation was expected to reduce particularly concentrations of non-chlorinated OPs during transport from urban to remote areas in summer months with higher global irradiation. In the SWHT a seasonal trend with decreasing concentrations in summer/autumn is evident for the non-chlorinated OPs due to in-lake degradation but not for the chlorinated OPs. Furthermore, an accumulation of OPs deposited in SWHTs was observed with concentrations often exceeding those observed in wet precipitation. Median concentrations of TCPP (880ngL(-1)), TDCP (13ngL(-1)) and TBEP (77ngL(-1)) at the SWHT were more than twice as high as median concentrations measured at the urban precipitation sampling site (403ngL(-1), 5ngL(-1), and 21ngL(-1) respectively).

  13. ASSESSING GLOBAL CLIMATE VARIABILITY UNDER COLDEST AND WARMEST PERIODS AT DIFFERENT LATITUDINAL REGIONS

    Directory of Open Access Journals (Sweden)

    Eleonora Runtunuwu

    2016-10-01

    Full Text Available Effect of climate change on water balance will play a key role in the biosphere system. To study the global climate change impact on water balance during 95-year period (1901-1995, long-term grid climatic data including global mean monthly temperature and precipitation at 0.5 x 0.5 degree resolution were analysed. The trend and variation of climate change, the time series of monthly air temperature and precipitation data were aggregated into annual arithmetic means for two extreme periods (1901-1920 and 1990-1995. The potential evapotranspiration (Eo was calculated using Thornthwaite method.The changes in mean annual value were obtained by subtracting the maximum period data from 1990 to 1995 (Max with the minimum period data from 1901 to 1920 (Min. The results revealed that over 95-year period, mean global air temperature increased by 0.57oC. The temperature increase varied greatly in Asia, with more than 3.0oC, especially at 45-70oN, as well over the northern part of America (60-65oN and Europe (55- 75oN. In low latitude across Asia, Africa, and South America, the variation was less than 1.5oC. In 80-85ºN region, the variation was relatively small and at higher latitudes it increasedsignificantly. Precipitation varied temporally and spatially. In the 40-45ºN and 40-45ºS regions, increasing precipitation of more than 100 mm occurred during the June-August andSeptember-November, especially in the northern hemisphere. The Eo increase of 2000 mm during 95 years occurred in the tropical northern America, middle Africa, and South-East Asia. A grid in Central Java of Indonesia showed that the Eo increase of 2500 mm during 95 years resulted in the decrease of growing period by 100 days. In coping with climate change, adjustment of cropping calendar is imperative.

  14. CHARACTERISTICS OF MEI-YU PRECIPITATION AND SVD ANALYSIS OF PRECIPITATION OVER THE YANGTZE-HUAIHE RIVERS VALLEYS AND THE SEA SURFACE TEMPERATURE IN THE NORTHERN PACIFIC OCEAN

    Institute of Scientific and Technical Information of China (English)

    MAO Wen-shu; WANG Qian-qian; PENG Jun; LI Yong-hua

    2008-01-01

    Based on the precipitation data of Meiyu at 37 stations in the valleys of Yangtze and Huaihe Rivers from 1954 to 2001, the temporal-spatial characteristics of Meiyu precipitation and their relationships with the sea surface temperature in northern Pacific are investigated using such methods as harmonic analysis, empirical orthogonal function (EOF), composite analysis and singular value decomposition (SVD). The results show that the temporal evolution and spatial distribution of Meiyu precipitation are not homogeneous in the Yangtze-Huaihe Rivers basins but with prominent inter-annual and inter-decadal variabilities. The key region between the anomalies of Meiyu precipitation and the monthly sea surface temperature anomalies (SSTA) lies in the west wind drift of North Pacific, which influences the precipitation anomaly of Meiyu precipitation over a key period of time from January to March in the same year. When the SST in the North Pacific west wind drift is warmer (colder) than average during these months, Meiyu precipitation anomalously increases (decreases) in the concurrent year. Results of SVD are consistent with those of composite analysis which pass the significance test of Monte-Carlo at 0.05.

  15. Monthly Climatic Data for the World

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Publication of monthly mean temperature, pressure, precipitation, vapor pressure, and hours of sunshine for approximately 2,000 surface data collection stations...

  16. Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

    Science.gov (United States)

    Zhou, C.; Zhang, X.; Gong, S.; Wang, Y.; Xue, M.

    2016-01-01

    A comprehensive aerosol-cloud-precipitation interaction (ACI) scheme has been developed under a China Meteorological Administration (CMA) chemical weather modeling system, GRAPES/CUACE (Global/Regional Assimilation and PrEdiction System, CMA Unified Atmospheric Chemistry Environment). Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN) are interactively fed online into a two-moment cloud scheme (WRF Double-Moment 6-class scheme - WDM6) and a convective parameterization to drive cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred.The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.

  17. Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

    Directory of Open Access Journals (Sweden)

    C. Zhou

    2016-01-01

    Full Text Available A comprehensive aerosol–cloud–precipitation interaction (ACI scheme has been developed under a China Meteorological Administration (CMA chemical weather modeling system, GRAPES/CUACE (Global/Regional Assimilation and PrEdiction System, CMA Unified Atmospheric Chemistry Environment. Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN are interactively fed online into a two-moment cloud scheme (WRF Double-Moment 6-class scheme – WDM6 and a convective parameterization to drive cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred.The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.

  18. Local and global effects of climate on dengue transmission in Puerto Rico.

    Directory of Open Access Journals (Sweden)

    Michael A Johansson

    Full Text Available The four dengue viruses, the agents of dengue fever and dengue hemorrhagic fever in humans, are transmitted predominantly by the mosquito Aedes aegypti. The abundance and the transmission potential of Ae. aegypti are influenced by temperature and precipitation. While there is strong biological evidence for these effects, empirical studies of the relationship between climate and dengue incidence in human populations are potentially confounded by seasonal covariation and spatial heterogeneity. Using 20 years of data and a statistical approach to control for seasonality, we show a positive and statistically significant association between monthly changes in temperature and precipitation and monthly changes in dengue transmission in Puerto Rico. We also found that the strength of this association varies spatially, that this variation is associated with differences in local climate, and that this relationship is consistent with laboratory studies of the impacts of these factors on vector survival and viral replication. These results suggest the importance of temperature and precipitation in the transmission of dengue viruses and suggest a reason for their spatial heterogeneity. Thus, while dengue transmission may have a general system, its manifestation on a local scale may differ from global expectations.

  19. Monthly hydroclimatology of the continental United States

    Science.gov (United States)

    Petersen, Thomas; Devineni, Naresh; Sankarasubramanian, A.

    2018-04-01

    Physical/semi-empirical models that do not require any calibration are of paramount need for estimating hydrological fluxes for ungauged sites. We develop semi-empirical models for estimating the mean and variance of the monthly streamflow based on Taylor Series approximation of a lumped physically based water balance model. The proposed models require mean and variance of monthly precipitation and potential evapotranspiration, co-variability of precipitation and potential evapotranspiration and regionally calibrated catchment retention sensitivity, atmospheric moisture uptake sensitivity, groundwater-partitioning factor, and the maximum soil moisture holding capacity parameters. Estimates of mean and variance of monthly streamflow using the semi-empirical equations are compared with the observed estimates for 1373 catchments in the continental United States. Analyses show that the proposed models explain the spatial variability in monthly moments for basins in lower elevations. A regionalization of parameters for each water resources region show good agreement between observed moments and model estimated moments during January, February, March and April for mean and all months except May and June for variance. Thus, the proposed relationships could be employed for understanding and estimating the monthly hydroclimatology of ungauged basins using regional parameters.

  20. Precipitation response to the current ENSO variability in a warming world

    Science.gov (United States)

    Bonfils, C.; Santer, B. D.; Phillips, T. J.; Marvel, K.; Leung, L.

    2013-12-01

    The major triggers of past and recent droughts include large modes of variability, such as ENSO, as well as specific and persistent patterns of sea surface temperature anomalies (SSTAs; Hoerling and Kumar, 2003, Shin et al. 2010, Schubert et al. 2009). However, alternative drought initiators are also anticipated in response to increasing greenhouse gases, potentially changing the relative contribution of ocean variability as drought initiator. They include the intensification of the current zonal wet-dry patterns (the thermodynamic mechanism, Held and Soden, 2006), a latitudinal redistribution of global precipitation (the dynamical mechanism, Seager et al. 2007, Seidel et al. 2008, Scheff and Frierson 2008) and a reduction of local soil moisture and precipitation recycling (the land-atmosphere argument). Our ultimate goal is to investigate whether the relative contribution of those mechanisms change over time in response to global warming. In this study, we first perform an EOF analysis of the 1900-1999 time series of observed global SST field and identify a simple ENSO-like (ENSOL) mode of SST variability. We show that this mode is well spatially and temporally correlated with observed worldwide regional precipitation and drought variability. We then develop concise metrics to examine the fidelity with which the CMIP5 coupled global climate models (CGCMs) capture this particular ENSO-like mode in the current climate, and their ability to replicate the observed teleconnections with precipitation. Based on the CMIP5 model projections of future climate change, we finally analyze the potential temporal variations in ENSOL to be anticipated under further global warming, as well as their associated teleconnections with precipitation (pattern, amplitude, and total response). Overall, our approach allows us to determine what will be the effect of the current ENSO-like variability (i.e., as measured with instrumental observations) on precipitation in a warming world. This

  1. Monthly Sea Surface Salinity and Freshwater Flux Monitoring

    Science.gov (United States)

    Ren, L.; Xie, P.; Wu, S.

    2017-12-01

    Taking advantages of the complementary nature of the Sea Surface Salinity (SSS) measurements from the in-situ (CTDs, shipboard, Argo floats, etc.) and satellite retrievals from Soil Moisture Ocean Salinity (SMOS) satellite of the European Space Agency (ESA), the Aquarius of a joint venture between US and Argentina, and the Soil Moisture Active Passive (SMAP) of national Aeronautics and Space Administration (NASA), a technique is developed at NOAA/NCEP/CPC to construct an analysis of monthly SSS, called the NOAA Blended Analysis of Sea-Surface Salinity (BASS). The algorithm is a two-steps approach, i.e. to remove the bias in the satellite data through Probability Density Function (PDF) matching against co-located in situ measurements; and then to combine the bias-corrected satellite data with the in situ measurements through the Optimal Interpolation (OI) method. The BASS SSS product is on a 1° by 1° grid over the global ocean for a 7-year period from 2010. Combined with the NOAA/NCEP/CPC CMORPH satellite precipitation (P) estimates and the Climate Forecast System Reanalysis (CFSR) evaporation (E) fields, a suite of monthly package of the SSS and oceanic freshwater flux (E and P) was developed to monitor the global oceanic water cycle and SSS on a monthly basis. The SSS in BASS product is a suite of long-term SSS and fresh water flux data sets with temporal homogeneity and inter-component consistency better suited for the examination of the long-term changes and monitoring. It presents complete spatial coverage and improved resolution and accuracy, which facilitates the diagnostic analysis of the relationship and co-variability among SSS, freshwater flux, mixed layer processes, oceanic circulation, and assimilation of SSS into global models. At the AGU meeting, we will provide more details on the CPC salinity and fresh water flux data package and its applications in the monitoring and analysis of SSS variations in association with the ENSO and other major climate

  2. Spatial and temporal variability of precipitation and drought in Portugal

    Directory of Open Access Journals (Sweden)

    D. S. Martins

    2012-05-01

    Full Text Available The spatial variability of precipitation and drought are investigated for Portugal using monthly precipitation from 74 stations and minimum and maximum temperature from 27 stations, covering the common period of 1941–2006. Seasonal precipitation and the corresponding percentages in the year, as well as the precipitation concentration index (PCI, was computed for all 74 stations and then used as an input matrix for an R-mode principal component analysis to identify the precipitation patterns. The standardized precipitation index at 3 and 12 month time scales were computed for all stations, whereas the Palmer Drought Severity Index (PDSI and the modified PDSI for Mediterranean conditions (MedPDSI were computed for the stations with temperature data. The spatial patterns of drought over Portugal were identified by applying the S-mode principal component analysis coupled with varimax rotation to the drought indices matrices. The result revealed two distinct sub-regions in the country relative to both precipitation regimes and drought variability. The analysis of time variability of the PC scores of all drought indices allowed verifying that there is no linear trend indicating drought aggravation or decrease. In addition, the analysis shows that results for SPI-3, SPI-12, PDSI and MedPDSI are coherent among them.

  3. Seasonal analysis of precipitation, drought and Vegetation index in Indonesian paddy field based on remote sensing data

    International Nuclear Information System (INIS)

    Darmawan, S; Takeuchi, W; Shofiyati, R; Sari, D K; Wikantika, K

    2014-01-01

    Paddy field is important agriculture crop in Indonesia. Rice is a food staple for 237,6 million Indonesian people. Paddy field growth is strongly influenced by water, but the amount of precipitation is unpredictable. Annual and interannual climate variability in Indonesia is unusual. In recent years remote sensing data has been used for measurement and monitoring of precipitation, drought and Vegetation index such as Global Satellite Mapping of Precipitation (GSMaP), Multi-purpose Transmission SATellite (MTSAT) and Moderate Resolution Imaging Spectroradiometer (MODIS). The objective of this research is to investigate seasonal variability of precipitation, drought and Vegetation index in Indonesian paddy field based on remote sensing data. The methodology consists of collecting of enhanced vegetation index (EVI) from MODIS data, mosaicking of image, collecting of region of interest of paddy field, collecting of precipitation and drought index based on Keetch Bryam Drought Index (KBDI) from GSMaP and MTSAT, and seasonal analysis. The result of this research has showed seasonal variability of precipitation, KBDI and EVI on Indonesia paddy field from 2007 until 2012. Precipitation begins from January until May and October until December, and KBDI begins to increase from June and peak in September only in South Sumatera precipitation almost in all month. Seasonal analysis has showed precipitation and KBDI affect on EVI that can indicate variety phenology of Indonesian paddy field. Peak of EVI occurs before peak of KBDI occurs and increasing of KBDI followed by decreasing of EVI. In 2010 all province got higher precipitation and smaller KBDI so EVI has three peaks such as in West Java that can indicated increasing of rice production

  4. Projected Changes in the Annual Cycle of Precipitation over Central Asia by CMIP5 Models

    Science.gov (United States)

    Yu, X.; Zhao, Y.

    2017-12-01

    Future changes in the annual cycle of the precipitation in central Asia (CA) were estimated based on the historical and Representative Concentration Pathway 8.5 (RCP8.5) experiments from 25 models of the Coupled Model Intercomparison Project phase 5 (CMIP5). Compared with the Global Precipitation Climatology Project (GPCP) observations, the historical (1979-1999) experiments showed that most models can capture the migration of rainfall centers, but remarkable discrepancies exist in the location and intensity of rainfall centers between simulations and observations. Considering the skill scores of precipitation and pattern correlations of circulations, which are closely related to the precipitation for each month, for the 25 models, the four best models (e.g., CanESM2, CMCC-CMS, MIROC5 and MPI-ESM-LR) with relatively good performance were selected. The four models' ensemble mean indicated that the migration and location of the precipitation centers were better reproduced, except the intensity of the centers was overestimated, compared with the result that only considered precipitation. Based on the four best models' ensemble mean under RCP8.5 scenarios, precipitation was projected to increase dramatically over most of the CA region in the boreal cold seasons (November, December, January, February, March, April and May) with the maximum in December in the end of twenty-first century (2079-2099), and several positive centers were located in the Pamirs Plateau and the Tianshan Mountains. By contrast, the precipitation changes were weak in the boreal warm seasons (June, July, August, September and October), with a wet center located in the northern Himalayas. Furthermore, there remain some uncertainties in the projected precipitation regions and periods obtained by comparing models' ensemble results of this paper and the results of previous studies. These uncertainties should be investigated in future work.

  5. Global observed long-term changes in temperature and precipitation extremes: A review of progress and limitations in IPCC assessments and beyond

    Directory of Open Access Journals (Sweden)

    Lisa V. Alexander

    2016-03-01

    Full Text Available The Intergovernmental Panel on Climate Change (IPCC first attempted a global assessment of long-term changes in temperature and precipitation extremes in its Third Assessment Report in 2001. While data quality and coverage were limited, the report still concluded that heavy precipitation events had increased and that there had been, very likely, a reduction in the frequency of extreme low temperatures and increases in the frequency of extreme high temperatures. That overall assessment had changed little by the time of the IPCC Special Report on Extremes (SREX in 2012 and the IPCC Fifth Assessment Report (AR5 in 2013, but firmer statements could be added and more regional detail was possible. Despite some substantial progress throughout the IPCC Assessments in terms of temperature and precipitation extremes analyses, there remain major gaps particularly regarding data quality and availability, our ability to monitor these events consistently and our ability to apply the complex statistical methods required. Therefore this article focuses on the substantial progress that has taken place in the last decade, in addition to reviewing the new progress since IPCC AR5 while also addressing the challenges that still lie ahead.

  6. Large-scale atmospheric circulation biases and changes in global climate model simulations and their importance for climate change in Central Europe

    Directory of Open Access Journals (Sweden)

    A. P. van Ulden

    2006-01-01

    Full Text Available The quality of global sea level pressure patterns has been assessed for simulations by 23 coupled climate models. Most models showed high pattern correlations. With respect to the explained spatial variance, many models showed serious large-scale deficiencies, especially at mid-latitudes. Five models performed well at all latitudes and for each month of the year. Three models had a reasonable skill. We selected the five models with the best pressure patterns for a more detailed assessment of their simulations of the climate in Central Europe. We analysed observations and simulations of monthly mean geostrophic flow indices and of monthly mean temperature and precipitation. We used three geostrophic flow indices: the west component and south component of the geostrophic wind at the surface and the geostrophic vorticity. We found that circulation biases were important, and affected precipitation in particular. Apart from these circulation biases, the models showed other biases in temperature and precipitation, which were for some models larger than the circulation induced biases. For the 21st century the five models simulated quite different changes in circulation, precipitation and temperature. Precipitation changes appear to be primarily caused by circulation changes. Since the models show widely different circulation changes, especially in late summer, precipitation changes vary widely between the models as well. Some models simulate severe drying in late summer, while one model simulates significant precipitation increases in late summer. With respect to the mean temperature the circulation changes were important, but not dominant. However, changes in the distribution of monthly mean temperatures, do show large indirect influences of circulation changes. Especially in late summer, two models simulate very strong warming of warm months, which can be attributed to severe summer drying in the simulations by these models. The models differ also

  7. Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

    Science.gov (United States)

    Hussain, Ijaz; Spöck, Gunter; Pilz, Jürgen; Yu, Hwa-Lung

    2010-08-01

    Spatio-temporal estimation of precipitation over a region is essential to the modeling of hydrologic processes for water resources management. The changes of magnitude and space-time heterogeneity of rainfall observations make space-time estimation of precipitation a challenging task. In this paper we propose a Box-Cox transformed hierarchical Bayesian multivariate spatio-temporal interpolation method for the skewed response variable. The proposed method is applied to estimate space-time monthly precipitation in the monsoon periods during 1974-2000, and 27-year monthly average precipitation data are obtained from 51 stations in Pakistan. The results of transformed hierarchical Bayesian multivariate spatio-temporal interpolation are compared to those of non-transformed hierarchical Bayesian interpolation by using cross-validation. The software developed by [11] is used for Bayesian non-stationary multivariate space-time interpolation. It is observed that the transformed hierarchical Bayesian method provides more accuracy than the non-transformed hierarchical Bayesian method.

  8. Oxygen and Hydrogen Isotopes of Precipitation in a Rocky Mountainous Area of Beijing to Distinguish and Estimate Spring Recharge

    Directory of Open Access Journals (Sweden)

    Ziqiang Liu

    2018-05-01

    Full Text Available Stable isotopes of oxygen and hydrogen were used to estimate seasonal contributions of precipitation to natural spring recharge in Beijing’s mountainous area. Isotopic compositions were shown to be more positive in the dry season and more negative in the wet season, due to the seasonal patterns in the amount of precipitation. The local meteoric water line (LMWL was δ2H = 7.0 δ18O − 2.3 for the dry season and δ2H = 5.9 δ18O − 10.4 for the wet season. LMWL in the two seasons had a lower slope and intercept than the Global Meteoric Water Line (p < 0.01. The slope and intercept of the LMWL in the wet season were lower than that in the dry season because of the effect of precipitation amount during the wet season (p < 0.01. The mean precipitation effects of −15‰ and −2‰ per 100 mm change in the amount of precipitation for δ2H and δ18O, respectively, were obtained from the monthly total precipitation and its average isotopic value. The isotopic composition of precipitation decreased when precipitation duration increased. Little changes in the isotopic composition of the natural spring were found. By employing isotope conservation of mass, it could be derived that, on average, approximately 7.2% of the natural spring came from the dry season precipitation and the rest of 92.8% came from the wet season precipitation.

  9. Assessment of the potential forecasting skill of a global hydrological model in reproducing the occurrence of monthly flow extremes

    Directory of Open Access Journals (Sweden)

    N. Candogan Yossef

    2012-11-01

    Full Text Available As an initial step in assessing the prospect of using global hydrological models (GHMs for hydrological forecasting, this study investigates the skill of the GHM PCR-GLOBWB in reproducing the occurrence of past extremes in monthly discharge on a global scale. Global terrestrial hydrology from 1958 until 2001 is simulated by forcing PCR-GLOBWB with daily meteorological data obtained by downscaling the CRU dataset to daily fields using the ERA-40 reanalysis. Simulated discharge values are compared with observed monthly streamflow records for a selection of 20 large river basins that represent all continents and a wide range of climatic zones.

    We assess model skill in three ways all of which contribute different information on the potential forecasting skill of a GHM. First, the general skill of the model in reproducing hydrographs is evaluated. Second, model skill in reproducing significantly higher and lower flows than the monthly normals is assessed in terms of skill scores used for forecasts of categorical events. Third, model skill in reproducing flood and drought events is assessed by constructing binary contingency tables for floods and droughts for each basin. The skill is then compared to that of a simple estimation of discharge from the water balance (PE.

    The results show that the model has skill in all three types of assessments. After bias correction the model skill in simulating hydrographs is improved considerably. For most basins it is higher than that of the climatology. The skill is highest in reproducing monthly anomalies. The model also has skill in reproducing floods and droughts, with a markedly higher skill in floods. The model skill far exceeds that of the water balance estimate. We conclude that the prospect for using PCR-GLOBWB for monthly and seasonal forecasting of the occurrence of hydrological extremes is positive. We argue that this conclusion applies equally to other similar GHMs and

  10. Enhancing Global Land Surface Hydrology Estimates from the NASA MERRA Reanalysis Using Precipitation Observations and Model Parameter Adjustments

    Science.gov (United States)

    Reichle, Rolf; Koster, Randal; DeLannoy, Gabrielle; Forman, Barton; Liu, Qing; Mahanama, Sarith; Toure, Ally

    2011-01-01

    The Modern-Era Retrospective analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis that provides. in addition to atmospheric fields. global estimates of soil moisture, latent heat flux. snow. and runoff for J 979-present. This study introduces a supplemental and improved set of land surface hydrological fields ('MERRA-Land') generated by replaying a revised version of the land component of the MERRA system. Specifically. the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameters in the rainfall interception model, changes that effectively correct for known limitations in the MERRA land surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ERA-Interim reanalysis. MERRA-Land and ERA-Interim root zone soil moisture skills (against in situ observations at 85 US stations) are comparable and significantly greater than that of MERRA. Throughout the northern hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 15 basins in the western US) of MERRA and MERRA-Land is typically higher than that of ERA-Interim. With a few exceptions. the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using '\\-tERRA output for land surface hydrological studies.

  11. Microphysical Properties of Frozen Particles Inferred from Global Precipitation Measurement (GPM) Microwave Imager (GMI) Polarimetric Measurements

    Science.gov (United States)

    Gong, Jie; Wu, Dongliang

    2017-01-01

    Scattering differences induced by frozen particle microphysical properties are investigated, using the vertically (V) and horizontally (H) polarized radiances from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) 89 and 166GHz channels. It is the first study on global frozen particle microphysical properties that uses the dual-frequency microwave polarimetric signals. From the ice cloud scenes identified by the 183.3 3GHz channel brightness temperature (TB), we find that the scatterings of frozen particles are highly polarized with V-H polarimetric differences (PD) being positive throughout the tropics and the winter hemisphere mid-latitude jet regions, including PDs from the GMI 89 and 166GHz TBs, as well as the PD at 640GHz from the ER-2 Compact Scanning Submillimeter-wave Imaging Radiometer (CoSSIR) during the TC4 campaign. Large polarization dominantly occurs mostly near convective outflow region (i.e., anvils or stratiform precipitation), while the polarization signal is small inside deep convective cores as well as at the remote cirrus region. Neglecting the polarimetric signal would result in as large as 30 error in ice water path retrievals. There is a universal bell-curve in the PD TB relationship, where the PD amplitude peaks at 10K for all three channels in the tropics and increases slightly with latitude. Moreover, the 166GHz PD tends to increase in the case where a melting layer is beneath the frozen particles aloft in the atmosphere, while 89GHz PD is less sensitive than 166GHz to the melting layer. This property creates a unique PD feature for the identification of the melting layer and stratiform rain with passive sensors. Horizontally oriented non-spherical frozen particles are thought to produce the observed PD because of different ice scattering properties in the V and H polarizations. On the other hand, changes in the ice microphysical habitats or orientation due to turbulence mixing can also lead to a reduced PD in the deep

  12. Precipitation reconstruction using ring-width chronology

    Indian Academy of Sciences (India)

    ring samples of two adjacent homogeneous sites, has been used to reconstruct precipitation for the non-monsoon months (previous year October to concurrent May) back to AD 1171. This provides the first record of hydrological conditions for the ...

  13. Quantitative precipitation climatology over the Himalayas by using Precipitation Radar on Tropical Rainfall Measuring Mission (TRMM) and a dense network of rain-gauges

    Science.gov (United States)

    Yatagai, A.

    2010-09-01

    Quantified grid observation data at a reasonable resolution are indispensable for environmental monitoring as well as for predicting future change of mountain environment. However quantified datasets have not been available for the Himalayan region. Hence we evaluate climatological precipitation data around the Himalayas by using Precipitation Radar (PR) data acquired by the Tropical Rainfall Measuring Mission (TRMM) over 10 years of observation. To validate and adjust these patterns, we used a dense network of rain gauges collected by the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE Water Resources) project (http://www.chikyu.ac.jp/precip/). We used more than 2600 stations which have more than 10-year monthly precipitation over the Himalayan region (75E-105E, 20-36N) including country data of Nepal, Bangladesh, Bhutan, Pakistan, India, Myanmar, and China. The region we studied is so topographically complicated that horizontal patterns are not uniform. Therefore, every path data of PR2A25 (near-surface rain) was averaged in a 0.05-degree grid and a 10-year monthly average was computed (hereafter we call PR). On the other hand, for rain-gauge, we first computed cell averages if each 0.05-degree grid cell has 10 years observation or more. Here we refer to the 0.05-degree rain-gauge climatology data as RG data. On the basis of comparisons between the RG and PR composite values, we defined the parameters of the regressions to correct the monthly climatology value based on the rain gauge observations. Compared with the RG, the PR systematically underestimated precipitation by 28-38% in summer (July-September). Significant correlation between TRMM/PR and rain-gauge data was found for all months, but the correlation is relatively low in winter. The relationship is investigated for different elevation zones, and the PR was found to underestimate RG data in most zones, except for certain zones in

  14. African aerosol and large-scale precipitation variability over West Africa

    International Nuclear Information System (INIS)

    Huang Jingfeng; Zhang Chidong; Prospero, Joseph M

    2009-01-01

    We investigated the large-scale connection between African aerosol and precipitation in the West African Monsoon (WAM) region using 8-year (2000-2007) monthly and daily Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products (aerosol optical depth, fine mode fraction) and Tropical Rainfall Measuring Mission (TRMM) precipitation and rain type. These high-quality data further confirmed our previous results that the large-scale link between aerosol and precipitation in this region undergoes distinct seasonal and spatial variability. Previously detected suppression of precipitation during months of high aerosol concentration occurs in both convective and stratiform rain, but not systematically in shallow rain. This suggests the suppression of deep convection due to the aerosol. Based on the seasonal cycle of dust and smoke and their geographical distribution, our data suggest that both dust (coarse mode aerosol) and smoke (fine mode aerosol) contribute to the precipitation suppression. However, the dust effect is evident over the Gulf of Guinea while the smoke effect is evident over both land and ocean. A back trajectory analysis further demonstrates that the precipitation reduction is statistically linked to the upwind aerosol concentration. This study suggests that African aerosol outbreaks in the WAM region can influence precipitation in the local monsoon system which has direct societal impact on the local community. It calls for more systematic investigations to determine the modulating mechanisms using both observational and modeling approaches.

  15. Flood modelling with global precipitation measurement (GPM) satellite rainfall data: a case study of Dehradun, Uttarakhand, India

    Science.gov (United States)

    Sai Krishna, V. V.; Dikshit, Anil Kumar; Pandey, Kamal

    2016-05-01

    Urban expansion, water bodies and climate change are inextricably linked with each other. The macro and micro level climate changes are leading to extreme precipitation events which have severe consequences on flooding in urban areas. Flood simulations shall be helpful in demarcation of flooded areas and effective flood planning and preparedness. The temporal availability of satellite rainfall data at varying spatial scale of 0.10 to 0.50 is helpful in near real time flood simulations. The present research aims at analysing stream flow and runoff to monitor flood condition using satellite rainfall data in a hydrologic model. The satellite rainfall data used in the research was NASA's Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG), which is available at 30 minutes temporal resolution. Landsat data was used for mapping the water bodies in the study area. Land use land cover (LULC) data was prepared using Landsat 8 data with maximum likelihood technique that was provided as an input to the HEC-HMS hydrological model. The research was applied to one of the urbanized cities of India, viz. Dehradun, which is the capital of Uttarakhand State. The research helped in identifying the flood vulnerability at the basin level on the basis of the runoff and various socio economic parameters using multi criteria analysis.

  16. Future Projections of Precipitation Characteristics in East Asia Simulated by the MRI CGCM2

    Institute of Scientific and Technical Information of China (English)

    Akio KITOH; Masahiro HOSAKA; Yukimasa ADACHI; Kenji KAMIGUCHI

    2005-01-01

    Projected changes in precipitation characteristics around the mid-21st century and end-of-the-century are analyzed using the daily precipitation output of the 3-member ensemble Meteorological Research Institute global ocean-atmosphere coupled general circulation model (MRI-CGCM2) simulations under the Special Report on Emissions Scenarios (SRES) A2 and B2 scenarios. It is found that both the frequency and intensity increase in about 40% of the globe, while both the frequency and intensity decrease in about 20% of the globe. These numbers differ only a few percent from decade to decade of the 21st century and between the A2 and B2 scenarios. Over the rest of the globe (about one third), the precipitation frequency decreases but its intensity increases, suggesting a shift of precipitation distribution toward more intense events by global warming. South China is such a region where the summertime wet-day frequency decreases but the precipitation intensity increases. This is related to increased atmospheric moisture content due to global warming and an intensified and more westwardly extended North Pacific subtropical anticyclone,which may be related with an El Ni(n)o-like mean sea surface temperature change. On the other hand, a decrease in summer precipitation is noted in North China, thus augmenting a south-to-north precipit ation contrast more in the future.

  17. Mapping Monthly Water Scarcity in Global Transboundary Basins at Country-Basin Mesh Based Spatial Resolution.

    Science.gov (United States)

    Degefu, Dagmawi Mulugeta; Weijun, He; Zaiyi, Liao; Liang, Yuan; Zhengwei, Huang; Min, An

    2018-02-01

    Currently fresh water scarcity is an issue with huge socio-economic and environmental impacts. Transboundary river and lake basins are among the sources of fresh water facing this challenge. Previous studies measured blue water scarcity at different spatial and temporal resolutions. But there is no global water availability and footprint assessment done at country-basin mesh based spatial and monthly temporal resolutions. In this study we assessed water scarcity at these spatial and temporal resolutions. Our results showed that around 1.6 billion people living within the 328 country-basin units out of the 560 we assessed in this study endures severe water scarcity at least for a month within the year. In addition, 175 country-basin units goes through severe water scarcity for 3-12 months in the year. These sub-basins include nearly a billion people. Generally, the results of this study provide insights regarding the number of people and country-basin units experiencing low, moderate, significant and severe water scarcity at a monthly temporal resolution. These insights might help these basins' sharing countries to design and implement sustainable water management and sharing schemes.

  18. The Effect of Hurricanes on Annual Precipitation in Maryland and the Connection to Global Climate Change

    Science.gov (United States)

    Liu, Jackie; Liu, Zhong

    2015-01-01

    Precipitation is a vital aspect of our lives droughts, floods and other related disasters that involve precipitation can cause costly damage in the economic system and general society. Purpose of this project is to determine what, if any effect do hurricanes have on annual precipitation in Maryland Research will be conducted on Marylands terrain, climatology, annual precipitation, and precipitation contributed from hurricanes Possible connections to climate change

  19. Role of α precipitates in flux pinning in a superconducting Ti-Nb-Ta-Zr quaternary alloy

    International Nuclear Information System (INIS)

    Osamura, K.; Tsunekawa, H.; Monju, Y.; Horiuchi, T.

    1984-01-01

    The precipitation behaviour of the α phase in a Ti-27 at.% Nb-6 at% Ta-6 at% Zr alloy has been investigated mainly by means of small-angle X-ray scattering measurements, by which the average size and number density of α precipitates were determined. The alloy was isothermally aged at 643 K after cold-rolling to various thicknesses. During ageing the average size of α precipitates increased but the number density decreased. The effect of cold-rolling was to increase the volume fraction of α precipitates. The superconducting critical current density was measured for the same specimens after the metallographical investigation. The specific pinning force produced by α precipitates, which corresponds to the global pinning force density divided by the number density of precipitates, was found to be proportional to the cube of the particle radius. It was found that the global pinning force density can be described using a scaling rule in terms of the volume fraction of α precipitates and the reduced magnetic field. The dominant global pinning force in the present foil specimens, as well as in commercial multifilamentary wires, is attributed to α precipitates. Dislocations and their secondary substructure introduced by cold-working also contributed to flux pinning, and could offer nucleation sites for the α phase. (author)

  20. Improving the Regional Applicability of Satellite Precipitation Products by Ensemble Algorithm

    Directory of Open Access Journals (Sweden)

    Waseem Muhammad

    2018-04-01

    Full Text Available Satellite-based precipitation products (e.g., Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG and its predecessor, Tropical Rainfall Measuring Mission (TRMM are a critical source of precipitation estimation, particularly for a region with less, or no, hydrometric networking. However, the inconsistency in the performance of these products has been observed in different climatic and topographic diverse regions, timescales, and precipitation intensities and there is still room for improvement. Hence, using a projected ensemble algorithm, the regional precipitation estimate (RP is introduced here. The RP concept is mainly based on the regional performance weights derived from the Mean Square Error (MSE and the precipitation estimate from the TRMM product, that is, TRMM 3B42 (TR, real-time (late (IT and the research (post-real-time (IR products of IMERG. The overall results of the selected contingency table (e.g., Probability of detection (POD and statistical indices (e.g., Correlation Coefficient (CC signposted that the proposed RP product has shown an overall better potential to capture the gauge observations compared with the TR, IR, and IT in five different climatic regions of Pakistan from January 2015 to December 2016, at a diurnal time scale. The current study could be the first research providing preliminary feedback from Pakistan for global precipitation measurement researchers by highlighting the need for refinement in the IMERG.

  1. Diurnal Variation of Tropical Ice Cloud Microphysics inferred from Global Precipitation Measurement Microwave Imager (GPM-GMI)'s Polarimetric Measurement

    Science.gov (United States)

    Gong, J.; Zeng, X.; Wu, D. L.; Li, X.

    2017-12-01

    Diurnal variation of tropical ice cloud has been well observed and examined in terms of the area of coverage, occurring frequency, and total mass, but rarely on ice microphysical parameters (habit, size, orientation, etc.) because of lack of direct measurements of ice microphysics on a high temporal and spatial resolutions. This accounts for a great portion of the uncertainty in evaluating ice cloud's role on global radiation and hydrological budgets. The design of Global Precipitation Measurement (GPM) mission's procession orbit gives us an unprecedented opportunity to study the diurnal variation of ice microphysics on the global scale for the first time. Dominated by cloud ice scattering, high-frequency microwave polarimetric difference (PD, namely the brightness temperature difference between vertically- and horizontally-polarized paired channel measurements) from the GPM Microwave Imager (GMI) has been proven by our previous study to be very valuable to infer cloud ice microphysical properties. Using one year of PD measurements at 166 GHz, we found that cloud PD exhibits a strong diurnal cycle in the tropics (25S-25N). The peak PD amplitude varies as much as 35% over land, compared to only 6% over ocean. The diurnal cycle of the peak PD value is strongly anti-correlated with local ice cloud occurring frequency and the total ice mass with a leading period of 3 hours for the maximum correlation. The observed PD diurnal cycle can be explained by the change of ice crystal axial ratio. Using a radiative transfer model, we can simulate the observed 166 GHz PD-brightness temperature curve as well as its diurnal variation using different axial ratio values, which can be caused by the diurnal variation of ice microphysical properties including particle size, percentage of horizontally-aligned non-spherical particles, and ice habit. The leading of the change of PD ahead of ice cloud mass and occurring frequency implies the important role microphysics play in the

  2. Global Precipitation Climatology Project (GPCP) - Monthly, Version 2.2 (Version Superseded)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Version 2.2 of the dataset has been superseded by a newer version. Users should not use version 2.2 except in rare cases (e.g., when reproducing previous studies...

  3. Enabling Global Observations of Clouds and Precipitation on Fine Spatio-Temporal Scales from CubeSat Constellations: Temporal Experiment for Storms and Tropical Systems Technology Demonstration (TEMPEST-D)

    Science.gov (United States)

    Reising, S. C.; Todd, G.; Padmanabhan, S.; Lim, B.; Heneghan, C.; Kummerow, C.; Chandra, C. V.; Berg, W. K.; Brown, S. T.; Pallas, M.; Radhakrishnan, C.

    2017-12-01

    The Temporal Experiment for Storms and Tropical Systems (TEMPEST) mission concept consists of a constellation of 5 identical 6U-Class satellites observing storms at 5 millimeter-wave frequencies with 5-10 minute temporal sampling to observe the time evolution of clouds and their transition to precipitation. Such a small satellite mission would enable the first global measurements of clouds and precipitation on the time scale of tens of minutes and the corresponding spatial scale of a few km. TEMPEST is designed to improve the understanding of cloud processes by providing critical information on temporal signatures of precipitation and helping to constrain one of the largest sources of uncertainty in cloud models. TEMPEST millimeter-wave radiometers are able to perform remote observations of the cloud interior to observe microphysical changes as the cloud begins to precipitate or ice accumulates inside the storm. The TEMPEST technology demonstration (TEMPEST-D) mission is in progress to raise the TRL of the instrument and spacecraft systems from 6 to 9 as well as to demonstrate radiometer measurement and differential drag capabilities required to deploy a constellation of 6U-Class satellites in a single orbital plane. The TEMPEST-D millimeter-wave radiometer instrument provides observations at 89, 165, 176, 180 and 182 GHz using a single compact instrument designed for 6U-Class satellites. The direct-detection topology of the radiometer receiver substantially reduces both its power consumption and design complexity compared to heterodyne receivers. The TEMPEST-D instrument performs precise, end-to-end calibration using a cross-track scanning reflector to view an ambient blackbody calibration target and cosmic microwave background every scan period. The TEMPEST-D radiometer instrument has been fabricated and successfully tested under environmental conditions (vibration, thermal cycling and vacuum) expected in low-Earth orbit. TEMPEST-D began in Aug. 2015, with a

  4. Interdecadal variability of winter precipitation in Southeast China

    OpenAIRE

    Zhang, L.; Zhu, X.; Fraedrich, K.; Sielmann, F.; Zhi, X.

    2014-01-01

    Interdecadal variability of observed winter precipitation in Southeast China (1961–2010) is characterized by the first empirical orthogonal function of the three-monthly Standardized Precipitation Index (SPI) subjected to a 9-year running mean. For interdecadal time scales the dominating spatial modes represent monopole features involving the Arctic Oscillation (AO) and the sea surface temperature (SST) anomalies. Dynamic composite analysis (based on NCEP/NCAR reanalyzes) reveals the followin...

  5. Establishing the Global Fresh Water Sensor Web

    Science.gov (United States)

    Hildebrand, Peter H.

    2005-01-01

    This paper presents an approach to measuring the major components of the water cycle from space using the concept of a sensor-web of satellites that are linked to a data assimilation system. This topic is of increasing importance, due to the need for fresh water to support the growing human population, coupled with climate variability and change. The net effect is that water is an increasingly valuable commodity. The distribution of fresh water is highly uneven over the Earth, with both strong latitudinal distributions due to the atmospheric general circulation, and even larger variability due to landforms and the interaction of land with global weather systems. The annual global fresh water budget is largely a balance between evaporation, atmospheric transport, precipitation and runoff. Although the available volume of fresh water on land is small, the short residence time of water in these fresh water reservoirs causes the flux of fresh water - through evaporation, atmospheric transport, precipitation and runoff - to be large. With a total atmospheric water store of approx. 13 x 10(exp 12)cu m, and an annual flux of approx. 460 x 10(exp 12)cu m/y, the mean atmospheric residence time of water is approx. 10 days. River residence times are similar, biological are approx. 1 week, soil moisture is approx. 2 months, and lakes and aquifers are highly variable, extending from weeks to years. The hypothesized potential for redistribution and acceleration of the global hydrological cycle is therefore of concern. This hypothesized speed-up - thought to be associated with global warming - adds to the pressure placed upon water resources by the burgeoning human population, the variability of weather and climate, and concerns about anthropogenic impacts on global fresh water availability.

  6. Minimizing the Standard Deviation of Spatially Averaged Surface Cross-Sectional Data from the Dual-Frequency Precipitation Radar

    Science.gov (United States)

    Meneghini, Robert; Kim, Hyokyung

    2016-01-01

    For an airborne or spaceborne radar, the precipitation-induced path attenuation can be estimated from the measurements of the normalized surface cross section, sigma 0, in the presence and absence of precipitation. In one implementation, the mean rain-free estimate and its variability are found from a lookup table (LUT) derived from previously measured data. For the dual-frequency precipitation radar aboard the global precipitation measurement satellite, the nominal table consists of the statistics of the rain-free 0 over a 0.5 deg x 0.5 deg latitude-longitude grid using a three-month set of input data. However, a problem with the LUT is an insufficient number of samples in many cells. An alternative table is constructed by a stepwise procedure that begins with the statistics over a 0.25 deg x 0.25 deg grid. If the number of samples at a cell is too few, the area is expanded, cell by cell, choosing at each step that cell that minimizes the variance of the data. The question arises, however, as to whether the selected region corresponds to the smallest variance. To address this question, a second type of variable-averaging grid is constructed using all possible spatial configurations and computing the variance of the data within each region. Comparisons of the standard deviations for the fixed and variable-averaged grids are given as a function of incidence angle and surface type using a three-month set of data. The advantage of variable spatial averaging is that the average standard deviation can be reduced relative to the fixed grid while satisfying the minimum sample requirement.

  7. Impact of the surface wind flow on precipitation characteristics over the southern Himalayas: GPM observations

    Science.gov (United States)

    Zhang, Aoqi; Fu, Yunfei; Chen, Yilun; Liu, Guosheng; Zhang, Xiangdong

    2018-04-01

    The distribution and influence of precipitation over the southern Himalayas have been investigated on regional and global scales. However, previous studies have been limited by the insufficient emphasis on the precipitation triggers or the lack of droplet size distribution (DSD) data. Here, precipitating systems were identified using Global Precipitation Mission dual-frequency radar data, and then categorized into five classes according to surface flow from the European Centre for Medium-Range Weather Forecast Interim data. The surface flow is introduced to indicate the precipitation triggers, which is validated in this study. Using case and statistical analysis, we show that the precipitating systems with different surface flow had different precipitation characteristics, including spatio-temporal features, reflectivity profile, DSD, and rainfall intensity. Furthermore, the results show that the source of the surface flow influences the intensity and DSD of precipitation. The terrain exerts different impacts on the precipitating systems of five categories, leading to various distributions of precipitation characteristics over the southern Himalayas. Our results suggest that the introduction of surface flow and DSD for precipitating systems provides insight into the complex precipitation of the southern Himalayas. The different characteristics of precipitating systems may be caused by the surface flow. Therefore, future study on the orographic precipitations should take account the impact of the surface flow and its relevant dynamic mechanism.

  8. STAMMEX high resolution gridded daily precipitation dataset over Germany: a new potential for regional precipitation climate research

    Science.gov (United States)

    Zolina, Olga; Simmer, Clemens; Kapala, Alice; Mächel, Hermann; Gulev, Sergey; Groisman, Pavel

    2014-05-01

    We present new high resolution precipitation daily grids developed at Meteorological Institute, University of Bonn and German Weather Service (DWD) under the STAMMEX project (Spatial and Temporal Scales and Mechanisms of Extreme Precipitation Events over Central Europe). Daily precipitation grids have been developed from the daily-observing precipitation network of DWD, which runs one of the World's densest rain gauge networks comprising more than 7500 stations. Several quality-controlled daily gridded products with homogenized sampling were developed covering the periods 1931-onwards (with 0.5 degree resolution), 1951-onwards (0.25 degree and 0.5 degree), and 1971-2000 (0.1 degree). Different methods were tested to select the best gridding methodology that minimizes errors of integral grid estimates over hilly terrain. Besides daily precipitation values with uncertainty estimates (which include standard estimates of the kriging uncertainty as well as error estimates derived by a bootstrapping algorithm), the STAMMEX data sets include a variety of statistics that characterize temporal and spatial dynamics of the precipitation distribution (quantiles, extremes, wet/dry spells, etc.). Comparisons with existing continental-scale daily precipitation grids (e.g., CRU, ECA E-OBS, GCOS) which include considerably less observations compared to those used in STAMMEX, demonstrate the added value of high-resolution grids for extreme rainfall analyses. These data exhibit spatial variability pattern and trends in precipitation extremes, which are missed or incorrectly reproduced over Central Europe from coarser resolution grids based on sparser networks. The STAMMEX dataset can be used for high-quality climate diagnostics of precipitation variability, as a reference for reanalyses and remotely-sensed precipitation products (including the upcoming Global Precipitation Mission products), and for input into regional climate and operational weather forecast models. We will present

  9. Global Precipitation Measurement. Report 2; Benefits of Partnering with GPM Mission

    Science.gov (United States)

    Stocker, Erich F.; Smith, Eric A. (Editor); Adams, W. James (Editor); Starr, David OC. (Technical Monitor)

    2002-01-01

    An important goal of the Global Precipitation Measurement (GPM) mission is to maximize participation by non-NASA partners both domestic and international. A consequence of this objective is the provision for NASA to provide sufficient incentives to achieve partner buy-in and commitment to the program. NASA has identified seven specific areas in which substantive incentives will be offered: (1) partners will be offered participation in governance of GPM mission science affairs including definition of data products; (2) partners will be offered use of NASA's TDRSS capability for uplink and downlink of commands and data in regards to partner provided spacecraft; (3) partners will be offered launch support for placing partner provided spacecraft in orbit conditional upon mutually agreeable co-manifest arrangements; (4) partners will be offered direct data access at the NASA-GPM server level rather than through standard data distribution channels; (5) partners will be offered the opportunity to serve as regional data archive and distribution centers for standard GPM data products; and (6) partners will be offered the option to insert their own specialized filtering and extraction software into the GPM data processing stream or to obtain specialized subsets and products over specific areas of interest (7) partners will be offered GPM developed software tools that can be run on their platforms. Each of these incentives, either individually or in combination, represents a significant advantage to partners who may wish to participate in the GPM mission.

  10. A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor

    Science.gov (United States)

    Huang, Liangke; Jiang, Weiping; Liu, Lilong; Chen, Hua; Ye, Shirong

    2018-05-01

    In ground-based global positioning system (GPS) meteorology, atmospheric weighted mean temperature, T_m , plays a very important role in the progress of retrieving precipitable water vapor (PWV) from the zenith wet delay of the GPS. Generally, most of the existing T_m models only take either latitude or altitude into account in modeling. However, a great number of studies have shown that T_m is highly correlated with both latitude and altitude. In this study, a new global grid empirical T_m model, named as GGTm, was established by a sliding window algorithm using global gridded T_m data over an 8-year period from 2007 to 2014 provided by TU Vienna, where both latitude and altitude variations are considered in modeling. And the performance of GGTm was assessed by comparing with the Bevis formula and the GPT2w model, where the high-precision global gridded T_m data as provided by TU Vienna and the radiosonde data from 2015 are used as reference values. The results show the significant performance of the new GGTm model against other models when compared with gridded T_m data and radiosonde data, especially in the areas with great undulating terrain. Additionally, GGTm has the global mean RMS_{PWV} and RMS_{PWV} /PWV values of 0.26 mm and 1.28%, respectively. The GGTm model, fed only by the day of the year and the station coordinates, could provide a reliable and accurate T_m value, which shows the possible potential application in real-time GPS meteorology, especially for the application of low-latitude areas and western China.

  11. An Experimental System for a Global Flood Prediction: From Satellite Precipitation Data to a Flood Inundation Map

    Science.gov (United States)

    Adler, Robert

    2007-01-01

    Floods impact more people globally than any other type of natural disaster. It has been established by experience that the most effective means to reduce the property damage and life loss caused by floods is the development of flood early warning systems. However, advances for such a system have been constrained by the difficulty in estimating rainfall continuously over space (catchment-. national-, continental-. or even global-scale areas) and time (hourly to daily). Particularly, insufficient in situ data, long delay in data transmission and absence of real-time data sharing agreements in many trans-boundary basins hamper the development of a real-time system at the regional to global scale. In many countries around the world, particularly in the tropics where rainfall and flooding co-exist in abundance, satellite-based precipitation estimation may be the best source of rainfall data for those data scarce (ungauged) areas and trans-boundary basins. Satellite remote sensing data acquired and processed in real time can now provide the space-time information on rainfall fluxes needed to monitor severe flood events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models, which can be parameterized by a tailored geospatial database. An example that is a key to this progress is NASA's contribution to the Tropical Rainfall Measuring Mission (TRMM), launched in November 1997. Hence, in an effort to evolve toward a more hydrologically-relevant flood alert system, this talk articulates a module-structured framework for quasi-global flood potential naming, that is 'up to date' with the state of the art on satellite rainfall estimation and the improved geospatial datasets. The system is modular in design with the flexibility that permits changes in the model structure and in the choice of components. Four major components included in the system are: 1) multi-satellite precipitation estimation; 2) characterization of

  12. Sensitivity of Sahelian Precipitation to Desert Dust under ENSO variability: a regional modeling study

    Science.gov (United States)

    Jordan, A.; Zaitchik, B. F.; Gnanadesikan, A.

    2016-12-01

    Mineral dust is estimated to comprise over half the total global aerosol burden, with a majority coming from the Sahara and Sahel region. Bounded by the Sahara Desert to the north and the Sahelian Savannah to the south, the Sahel experiences high interannual rainfall variability and a short rainy season during the boreal summer months. Observation-based data for the past three decades indicates a reduced dust emission trend, together with an increase in greening and surface roughness within the Sahel. Climate models used to study regional precipitation changes due to Saharan dust yield varied results, both in sign convention and magnitude. Inconsistency of model estimates drives future climate projections for the region that are highly varied and uncertain. We use the NASA-Unified Weather Research and Forecasting (NU-WRF) model to quantify the interaction and feedback between desert dust aerosol and Sahelian precipitation. Using nested domains at fine spatial resolution we resolve changes to mesoscale atmospheric circulation patterns due to dust, for representative phases of El Niño-Southern Oscillation (ENSO). The NU-WRF regional earth system model offers both advanced land surface data and resolvable detail of the mechanisms of the impact of Saharan dust. Results are compared to our previous work assessed over the Western Sahel using the Geophysical Fluid Dynamics Laboratory (GFDL) CM2Mc global climate model, and to other previous regional climate model studies. This prompts further research to help explain the dust-precipitation relationship and recent North African dust emission trends. This presentation will offer a quantitative analysis of differences in radiation budget, energy and moisture fluxes, and atmospheric dynamics due to desert dust aerosol over the Sahel.

  13. The Impact of Global Warming on Precipitation Patterns in Ilorin and the Hydrological Balance of the Awun Basin

    Science.gov (United States)

    Ayanshola, Ayanniyi; Olofintoye, Oluwatosin; Obadofin, Ebenezer

    2018-03-01

    This study presents the impact of global warming on precipitation patterns in Ilorin, Nigeria, and its implications on the hydrological balance of the Awun basin under the prevailing climate conditions. The study analyzes 39 years of rainfall and temperature data of relevant stations within the study areas. Simulated data from the Coupled Global Climate model for historical and future datasets were investigated under the A2 emission scenario. Statistical regression and a Mann-Kendall analysis were performed to determine the nature of the trends in the hydrological variables and their significance levels, while a Soil and Water Assessment Tool (SWAT) was used to estimate the water balance and derive the stream flow and yield of the Awun basin. The study revealed that while minimum and maximum temperatures in Ilorin are increasing, rainfall is generally decreasing. The assessment of the trends in the water balance parameters in the basin indicates that there is no improvement in the water yield as the population increases. This may result in major stresses to the water supply in the near future.

  14. Precipitation Estimation Using Combined Radar/Radiometer Measurements Within the GPM Framework

    Science.gov (United States)

    Hou, Arthur

    2012-01-01

    The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. The GPM mission centers upon the deployment of a Core Observatory in a 65o non-Sun-synchronous orbit to serve as a physics observatory and a transfer standard for intersatellite calibration of constellation radiometers. The GPM Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Radiometer (GMI). The DPR will be the first dual-frequency radar in space to provide not only measurements of 3-D precipitation structures but also quantitative information on microphysical properties of precipitating particles needed for improving precipitation retrievals from microwave sensors. The DPR and GMI measurements will together provide a database that relates vertical hydrometeor profiles to multi-frequency microwave radiances over a variety of environmental conditions across the globe. This combined database will be used as a common transfer standard for improving the accuracy and consistency of precipitation retrievals from all constellation radiometers. For global coverage, GPM relies on existing satellite programs and new mission opportunities from a consortium of partners through bilateral agreements with either NASA or JAXA. Each constellation member may have its unique scientific or operational objectives but contributes microwave observations to GPM for the generation and dissemination of unified global precipitation data products. In addition to the DPR and GMI on the Core Observatory, the baseline GPM constellation consists of the following sensors: (1) Special Sensor Microwave Imager/Sounder (SSMIS) instruments on the U.S. Defense Meteorological Satellite Program (DMSP) satellites, (2) the Advanced Microwave Scanning Radiometer-2 (AMSR-2) on the GCOM-W1

  15. Atmospheric precipitable water in Jos, Nigeria | Utah | Nigerian ...

    African Journals Online (AJOL)

    ... the atmosphere of Jos in the month of August has a value of 4.44±0.47cm, while the minimum of 1.54±0.47cm was found in the month of February. The regression models have been presented and discussed. Keywords: Precipitable water vapour, dew-point temperature, relative humidity. Nigerian Journal of Physics Vol.

  16. Benchmarking homogenization algorithms for monthly data

    Directory of Open Access Journals (Sweden)

    V. K. C. Venema

    2012-01-01

    Full Text Available The COST (European Cooperation in Science and Technology Action ES0601: advances in homogenization methods of climate series: an integrated approach (HOME has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative. The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random independent break-type inhomogeneities with normally distributed breakpoint sizes were added to the simulated datasets. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide trend was added.

    Participants provided 25 separate homogenized contributions as part of the blind study. After the deadline at which details of the imposed inhomogeneities were revealed, 22 additional solutions were submitted. These homogenized datasets were assessed by a number of performance metrics including (i the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii the error in linear trend estimates and (iii traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve

  17. Future changes in summer mean and extreme precipitation frequency in Japan by d4PDF regional climate simulations

    Science.gov (United States)

    Okada, Y.; Ishii, M.; Endo, H.; Kawase, H.; Sasaki, H.; Takayabu, I.; Watanabe, S.; Fujita, M.; Sugimoto, S.; Kawazoe, S.

    2017-12-01

    Precipitation in summer plays a vital role in sustaining life across East Asia, but the heavy rain that is often generated during this period can also cause serious damage. Developing a better understanding of the features and occurrence frequency of this heavy rain is an important element of disaster prevention. We investigated future changes in summer mean and extreme precipitation frequency in Japan using large ensemble dataset which simulated by the Non-Hydrostatic Regional Climate Model with a horizontal resolution of 20km (NHRCM20). This dataset called database for Policy Decision making for Future climate changes (d4PDF), which is intended to be utilized for the impact assessment studies and adaptation planning to global warming. The future climate experiments assume the global mean surface air temperature rise 2K and 4K from the pre-industrial period. We investigated using this dataset future changes of precipitation in summer over the Japanese archipelago based on observational locations. For mean precipitation in the present-day climate, the bias of the rainfall for each month is within 25% even considering all members (30 members). The bias at each location is found to increase by over 50% on the Pacific Ocean side of eastern part of Japan and interior locations of western part of Japan. The result in western part of Japan depends on the effect of the elevations in this model. The future changes in mean precipitation show a contrast between northern and southern Japan, with the north showing a slight increase but the south a decrease. The future changes in the frequency of extreme precipitation in the national average of Japan increase at 2K and 4K simulations compared with the present-day climate, respectively. The authors were supported by the Social Implementation Program on Climate Change Adaptation Technology (SI-CAT), the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan.

  18. Isotopic composition of precipitation at the station Ljubljana (Reaktor, Slovenia – period 2007–2010

    Directory of Open Access Journals (Sweden)

    Polona Vreča

    2014-12-01

    Full Text Available The stable isotopic composition of hydrogen and oxygen (δ2H and δ18O and the tritium activity (A were monitored in monthly collected precipitation at Ljubljana (Reaktor during the period 2007–2010. Monthly and yearly isotope variations are discussed and compared with those observed over the period 1981–2006 and with the basic meteorological parameters for Ljubljana (Bežigrad and Ljubljana (Hrastje stations for the period 2007−2010. The mean values for δ2H and δ18O, weighted by precipitation amount at Ljubljana (Reaktor, are –59.4 ‰ and –8.71 ‰. The reduced major axis local meteoric water line (LMWLRMA is δ2H = (8.19 ± 0.22×δ18O + (11.52 ± 1.97, while the precipitation weighted least square regression results in LMWLPWLSR-Re δ2H = (7.94 ± 0.21×δ18O + (9.76 ± 1.93. The lack of significant difference in the LMWL slopes indicates a relatively homogeneous distribution of monthly precipitation as well as the small number of low-amount monthly precipitation events with low deuterium excess. The deuterium excess weighted mean value is 10.3 ‰ which indicates the prevailing influence of the Atlantic air masses. The temperature coefficient of δ18O is 0.30 ‰/°C. Tritium activity in monthly precipitation shows typical seasonal variations, with a weighted mean tritium activity in this period of 8.5 TU. No decrease of mean annual activity is observed.

  19. Sea surface salinity and temperature-based predictive modeling of southwestern US winter precipitation: improvements, errors, and potential mechanisms

    Science.gov (United States)

    Liu, T.; Schmitt, R. W.; Li, L.

    2017-12-01

    Using 69 years of historical data from 1948-2017, we developed a method to globally search for sea surface salinity (SSS) and temperature (SST) predictors of regional terrestrial precipitation. We then applied this method to build an autumn (SON) SSS and SST-based 3-month lead predictive model of winter (DJF) precipitation in southwestern United States. We also find that SSS-only models perform better than SST-only models. We previously used an arbitrary correlation coefficient (r) threshold, |r| > 0.25, to define SSS and SST predictor polygons for best subset regression of southwestern US winter precipitation; from preliminary sensitivity tests, we find that |r| > 0.18 yields the best models. The observed below-average precipitation (0.69 mm/day) in winter 2015-2016 falls within the 95% confidence interval of the prediction model. However, the model underestimates the anomalous high precipitation (1.78 mm/day) in winter 2016-2017 by more than three-fold. Moisture transport mainly attributed to "pineapple express" atmospheric rivers (ARs) in winter 2016-2017 suggests that the model falls short on a sub-seasonal scale, in which case storms from ARs contribute a significant portion of seasonal terrestrial precipitation. Further, we identify a potential mechanism for long-range SSS and precipitation teleconnections: standing Rossby waves. The heat applied to the atmosphere from anomalous tropical rainfall can generate standing Rossby waves that propagate to higher latitudes. SSS anomalies may be indicative of anomalous tropical rainfall, and by extension, standing Rossby waves that provide the long-range teleconnections.

  20. A global dataset of sub-daily rainfall indices

    Science.gov (United States)

    Fowler, H. J.; Lewis, E.; Blenkinsop, S.; Guerreiro, S.; Li, X.; Barbero, R.; Chan, S.; Lenderink, G.; Westra, S.

    2017-12-01

    It is still uncertain how hydrological extremes will change with global warming as we do not fully understand the processes that cause extreme precipitation under current climate variability. The INTENSE project is using a novel and fully-integrated data-modelling approach to provide a step-change in our understanding of the nature and drivers of global precipitation extremes and change on societally relevant timescales, leading to improved high-resolution climate model representation of extreme rainfall processes. The INTENSE project is in conjunction with the World Climate Research Programme (WCRP)'s Grand Challenge on 'Understanding and Predicting Weather and Climate Extremes' and the Global Water and Energy Exchanges Project (GEWEX) Science questions. A new global sub-daily precipitation dataset has been constructed (data collection is ongoing). Metadata for each station has been calculated, detailing record lengths, missing data, station locations. A set of global hydroclimatic indices have been produced based upon stakeholder recommendations including indices that describe maximum rainfall totals and timing, the intensity, duration and frequency of storms, frequency of storms above specific thresholds and information about the diurnal cycle. This will provide a unique global data resource on sub-daily precipitation whose derived indices will be freely available to the wider scientific community.

  1. Multiresolution comparison of precipitation datasets for large-scale models

    Science.gov (United States)

    Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

    2014-12-01

    Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

  2. Soil moisture memory at sub-monthly time scales

    Science.gov (United States)

    Mccoll, K. A.; Entekhabi, D.

    2017-12-01

    For soil moisture-climate feedbacks to occur, the soil moisture storage must have `memory' of past atmospheric anomalies. Quantifying soil moisture memory is, therefore, essential for mapping and characterizing land-atmosphere interactions globally. Most previous studies estimate soil moisture memory using metrics based on the autocorrelation function of the soil moisture time series (e.g., the e-folding autocorrelation time scale). This approach was first justified by Delworth and Manabe (1988) on the assumption that monthly soil moisture time series can be modelled as red noise. While this is a reasonable model for monthly soil moisture averages, at sub-monthly scales, the model is insufficient due to the highly non-Gaussian behavior of the precipitation forcing. Recent studies have shown that significant soil moisture-climate feedbacks appear to occur at sub-monthly time scales. Therefore, alternative metrics are required for defining and estimating soil moisture memory at these shorter time scales. In this study, we introduce metrics, based on the positive and negative increments of the soil moisture time series, that can be used to estimate soil moisture memory at sub-monthly time scales. The positive increments metric corresponds to a rapid drainage time scale. The negative increments metric represents a slower drying time scale that is most relevant to the study of land-atmosphere interactions. We show that autocorrelation-based metrics mix the two time scales, confounding physical interpretation. The new metrics are used to estimate soil moisture memory at sub-monthly scales from in-situ and satellite observations of soil moisture. Reference: Delworth, Thomas L., and Syukuro Manabe. "The Influence of Potential Evaporation on the Variabilities of Simulated Soil Wetness and Climate." Journal of Climate 1, no. 5 (May 1, 1988): 523-47. doi:10.1175/1520-0442(1988)0012.0.CO;2.

  3. Characteristics of Spatial Structural Patterns and Temporal Variability of Annual Precipitation in Ningxia

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    [Objective] The aim was to study the characteristics of the spatial structural patterns and temporal variability of annual precipitation in Ningxia.[Method] Using rotated empirical orthogonal function,the precipitation concentration index,wavelet analysis and Mann-Kendall rank statistic method,the characteristics of precipitation on the spatial-temporal variability and trend were analyzed by the monthly precipitation series in Ningxia during 1951-2008.[Result] In Ningxia,the spatial structural patterns of a...

  4. Towards a probabilistic regional reanalysis system for Europe: evaluation of precipitation from experiments

    Directory of Open Access Journals (Sweden)

    Liselotte Bach

    2016-11-01

    Full Text Available A new development in the field of reanalyses is the incorporation of uncertainty estimation capabilities. We have developed a probabilistic regional reanalysis system for the CORDEX-EUR11 domain that is based on the numerical weather prediction model COSMO at a 12-km grid spacing. The lateral boundary conditions of all ensemble members are provided by the global reanalysis ERA-Interim. In the basic implementation of the system, uncertainties due to observation errors are estimated. Atmospheric assimilation of conventional observations perturbed by means of random samples of observation error yields estimates of the reanalysis uncertainty conditioned to observation errors. The data assimilation employed is a new scheme based on observation nudging that we denote ensemble nudging. The lower boundary of the atmosphere is regularly updated by external snow depth, sea surface temperature and soil moisture analyses. One of the most important purposes of reanalyses is the estimation of so-called essential climate variables. For regional reanalyses, precipitation has been identified as one of the essential climate variables that are potentially better represented than in other climate data sets. For that reason, we assess the representation of precipitation in our system in a pilot study. Based on two experiments, each of which extends over one month, we conduct a preliminary comparison to the global reanalysis ERA-Interim, a dynamical downscaling of the latter and the high-resolution regional reanalysis COSMO-REA6. In a next step, we assess our reanalysis system's probabilistic capabilities versus the ECMWF-EPS in terms of six-hourly precipitation sums. The added value of our probabilistic regional reanalysis system motivates the current production of a 5-year-long test reanalysis COSMO-EN-REA12 in the framework of the FP7-funded project Uncertainties in Ensembles of Regional Re-Analyses (UERRA.

  5. Observed changes in extreme precipitation in Poland: 1991-2015 versus 1961-1990

    Science.gov (United States)

    Pińskwar, Iwona; Choryński, Adam; Graczyk, Dariusz; Kundzewicz, Zbigniew W.

    2018-01-01

    Several episodes of extreme precipitation excess and extreme precipitation deficit, with considerable economic and social impacts, have occurred in Europe and in Poland in the last decades. However, the changes of related indices exhibit complex variability. This paper analyses changes in indices related to observed abundance and deficit of precipitated water in Poland. Among studied indices are maximum seasonal 24-h precipitation for the winter half-year (Oct.-March) and the summer half-year (Apr.-Sept.), maximum 5-day precipitation, maximum monthly precipitation and number of days with intense or very intense precipitation (respectively, in excess of 10 mm or 20 mm per day). Also, the warm-seasonal maximum number of consecutive dry days (longest period with daily precipitation below 1 mm) was examined. Analysis of precipitation extremes showed that daily maximum precipitation for the summer half-year increased for many stations, and increases during the summer half-year are more numerous than those in the winter half-year. Also, analysis of 5-day and monthly precipitation sums show increases for many stations. Number of days with intense precipitation increases especially in the north-western part of Poland. The number of consecutive dry days is getting higher for many stations in the summer half-year. Comparison of these two periods: colder 1961-1990 and warmer 1991-2015, revealed that during last 25 years most of statistical indices, such as 25th and 75th percentiles, median, mean and maximum are higher. However, many changes discussed in this paper are weak and statistically insignificant. The findings reported in this paper challenge results based on earlier data that do not include 2007-2015.

  6. Standardized precipitation index zones for Mexico

    Energy Technology Data Exchange (ETDEWEB)

    Giddings, L.; Soto, M. [Instituto de Ecologia, A.C., Xalapa, Veracruz (Mexico); Rutherford, B.M.; Maarouf, A. [Faculty of Environmental Studies, York University, Toronto, Ontario (Canada)

    2005-01-01

    Precipitation zone systems exists for Mexico based on seasonality, quantity of precipitation, climates and geographical divisions, but none are convenient for the study of the relation of precipitation with phenomena such as El nino. An empirical set of seven exclusively Mexican and six shared zones was derived from three series of Standardized Precipitation Index (SPI) images, from 1940 through 1989: a whole year series (SPI-12) of 582 monthly images, a six month series (SPI-6) of 50 images for winter months (November through April), and a six month series (SPI-6) of 50 images for summer months (May through October). By examination of principal component and unsupervised classification images, it was found that all three series had similar zones. A set of basic training fields chosen from the principal component images was used to classify all three series. The resulting thirteen zones, presented in this article, were found to be approximately similar, varying principally at zones edges. A set of simple zones defined by just a few vertices can be used for practical operations. In general the SPI zones are homogeneous, with almost no mixture of zones and few outliers of one zone in the area of others. They are compared with a previously published map of climatic regions. Potential applications for SPI zones are discussed. [Spanish] Existen varios sistemas de zonificacion de Mexico basados en la estacionalidad, cantidad de precipitacion, climas y divisiones geograficas, pero ninguno es conveniente para el estudio de la relacion de la precipitacion con fenomenos tales como El Nino. En este trabajo se presenta un conjunto de siete zonas empiricas exclusivamente mexicanas y seis compartidas, derivadas de tres series de imagenes de SPI (Indice Estandarizado de la Precipitacion), desde 1940 a 1989: una serie de 582 imagenes mensuales (SPI-12), una series de 50 imagenes (SPI-6) de meses de invierno (noviembre a abril), y otra de 50 imagenes (SPI-6) de meses de verano

  7. The U.S. Geological Survey Monthly Water Balance Model Futures Portal

    Science.gov (United States)

    Bock, Andrew R.; Hay, Lauren E.; Markstrom, Steven L.; Emmerich, Christopher; Talbert, Marian

    2017-05-03

    The U.S. Geological Survey Monthly Water Balance Model Futures Portal (https://my.usgs.gov/mows/) is a user-friendly interface that summarizes monthly historical and simulated future conditions for seven hydrologic and meteorological variables (actual evapotranspiration, potential evapotranspiration, precipitation, runoff, snow water equivalent, atmospheric temperature, and streamflow) at locations across the conterminous United States (CONUS).The estimates of these hydrologic and meteorological variables were derived using a Monthly Water Balance Model (MWBM), a modular system that simulates monthly estimates of components of the hydrologic cycle using monthly precipitation and atmospheric temperature inputs. Precipitation and atmospheric temperature from 222 climate datasets spanning historical conditions (1952 through 2005) and simulated future conditions (2020 through 2099) were summarized for hydrographic features and used to drive the MWBM for the CONUS. The MWBM input and output variables were organized into an open-access database. An Open Geospatial Consortium, Inc., Web Feature Service allows the querying and identification of hydrographic features across the CONUS. To connect the Web Feature Service to the open-access database, a user interface—the Monthly Water Balance Model Futures Portal—was developed to allow the dynamic generation of summary files and plots  based on plot type, geographic location, specific climate datasets, period of record, MWBM variable, and other options. Both the plots and the data files are made available to the user for download 

  8. Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC)

    Science.gov (United States)

    Liu, Zhong; Ostrenga, D.; Vollmer, B.; Deshong, B.; Greene, M.; Teng, W.; Kempler, S. J.

    2015-01-01

    On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following: 1. Level-1 GPM Microwave Imager (GMI) and partner radiometer products. 2. Goddard Profiling Algorithm (GPROF) GMI and partner products. 3. Integrated Multi-satellitE Retrievals for GPM (IMERG) products. (early, late, and final)A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http:disc.sci.gsfc.nasa.govgpm). Data services that are currently and to-be available include Google-like Mirador (http:mirador.gsfc.nasa.gov) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http:giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data

  9. Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC)

    Science.gov (United States)

    Ostrenga, D.; Liu, Z.; Vollmer, B.; Teng, W. L.; Kempler, S. J.

    2014-12-01

    On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http://pmm.nasa.gov/GPM). The GPM mission consists of an international network of satellites in which a GPM "Core Observatory" satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following: Level-1 GPM Microwave Imager (GMI) and partner radiometer products Goddard Profiling Algorithm (GPROF) GMI and partner products Integrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final) A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http://disc.sci.gsfc.nasa.gov/gpm). Data services that are currently and to-be available include Google-like Mirador (http://mirador.gsfc.nasa.gov/) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http://giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding

  10. Statistically extrapolated nowcasting of summertime precipitation over the Eastern Alps

    Science.gov (United States)

    Chen, Min; Bica, Benedikt; Tüchler, Lukas; Kann, Alexander; Wang, Yong

    2017-07-01

    This paper presents a new multiple linear regression (MLR) approach to updating the hourly, extrapolated precipitation forecasts generated by the INCA (Integrated Nowcasting through Comprehensive Analysis) system for the Eastern Alps. The generalized form of the model approximates the updated precipitation forecast as a linear response to combinations of predictors selected through a backward elimination algorithm from a pool of predictors. The predictors comprise the raw output of the extrapolated precipitation forecast, the latest radar observations, the convective analysis, and the precipitation analysis. For every MLR model, bias and distribution correction procedures are designed to further correct the systematic regression errors. Applications of the MLR models to a verification dataset containing two months of qualified samples, and to one-month gridded data, are performed and evaluated. Generally, MLR yields slight, but definite, improvements in the intensity accuracy of forecasts during the late evening to morning period, and significantly improves the forecasts for large thresholds. The structure-amplitude-location scores, used to evaluate the performance of the MLR approach, based on its simulation of morphological features, indicate that MLR typically reduces the overestimation of amplitudes and generates similar horizontal structures in precipitation patterns and slightly degraded location forecasts, when compared with the extrapolated nowcasting.

  11. Variability of Evaporation and Precipitation over the Ocean from Satellite Data

    Science.gov (United States)

    Malinin, V. N.; Gordeeva, S. M.

    2017-12-01

    HOAPS-3 and PMWC satellite archives for 1988-2008 are used to estimate moisture-exchange components between the ocean and atmosphere (evaporation, precipitation, and the difference between them or effective evaporation). Moisture-exchange components for the entire World Ocean and for the North Atlantic Ocean within 30°-60° N are calculated. A strong overestimation of the global values of effective evaporation by HOAPS data (mainly caused by a decrease in precipitation) is shown. In the interannual variability of effective evaporation, there is clearly an overestimated positive trend, which contradicts the real increase in the Global Sea Level. Large systematic errors in moisture-exchange components are revealed for the North Atlantic water area. According to HOAPS data, there is a significant underestimation of evaporation and effective evaporation. According to PMWC data, the amount of precipitation is significantly overestimated and evaporation is underestimated. As a consequence, effective evaporation becomes negative, which is impossible. Low accuracy in the estimation of moisture-exchange components and the need to improve old estimates and develop new evaporation and precipitation databases based on satellite data are noted.

  12. Effect of precipitation bias correction on water budget calculation in Upper Yellow River, China

    International Nuclear Information System (INIS)

    Ye Baisheng; Yang Daqing; Ma Lijuan

    2012-01-01

    This study quantifies the effect of precipitation bias corrections on basin water balance calculations for the Yellow River Source region (YRS). We analyse long-term (1959–2001) monthly and yearly data of precipitation, runoff, and ERA-40 water budget variables and define a water balance regime. Basin precipitation, evapotranspiration and runoff are high in summer and low in winter. The basin water storage change is positive in summer and negative in winter. Monthly precipitation bias corrections, ranging from 2 to 16 mm, do not significantly alter the pattern of the seasonal water budget. The annual bias correction of precipitation is about 98 mm (19%); this increase leads to the same amount of evapotranspiration increase, since yearly runoff remains unchanged and the long-term storage change is assumed to be zero. Annual runoff and evapotranspiration coefficients change, due to precipitation bias corrections, from 0.33 and 0.67 to 0.28 and 0.72, respectively. These changes will impact the parameterization and calibration of land surface and hydrological models. The bias corrections of precipitation data also improve the relationship between annual precipitation and runoff. (letter)

  13. The use of normalized climatological anomalies to rank precipitation events in the Iberian Peninsula

    Science.gov (United States)

    Ramos, Alexandre M.; Trigo, Ricardo M.; Liberato, Margarida L. R.

    2013-04-01

    Extreme precipitation events in the Iberian Peninsula during winter months have major socio-economic impacts such as flooding, landslides, extensive property damage and life losses, and are usually associated to deep low pressure systems with Atlantic origin, although some extreme events in summer/autumn months are fed by the Mediterranean. Quite often these events are evaluated on a casuistic base and with relatively few stations. An objective method for ranking daily precipitation events is presented based on the extensive use of the most comprehensive database of daily precipitation available for the Iberian Peninsula (IB02) and spanning from 1950 to 2003, with a resolution of 0.2° (approximately 16 x 22 km at latitude 40°N), for a total of 1673 pixels. This database is based on a dense network of rain gauges, combining two national data sets, 'Spain02' for peninsular Spain and Balearic islands (Herrera et al., 2012), and 'PT02' for mainland Portugal (Belo-Pereira et al., 2011), with a total of more than two thousand stations over Spain and four hundred stations over Portugal, all quality-controlled and homogenized. The daily precipitation data from 1950 to 2003 are compared with a 30-year (1961-90) precipitation climatology to achieve a daily normalized departure from the climatology. The magnitude of an event is given daily by an index that is obtained after multiplying 1) the area (in percentage) that has precipitation anomalies above two standard deviations by 2) the mean values of these anomalies over this area. With this criterion we are able to evaluate not only the spatial extent of the precipitation events but also their spatially integrated intensity. In addition, to stress out the hydrological responses to precipitation, rankings taking into account the sum of the normalized anomalies over different time periods (3 days, 5 days and 10 days) were also computed. Here different precipitation rankings will be presented considering the entire Iberian

  14. GPS-based PWV for precipitation forecasting and its application to a typhoon event

    Science.gov (United States)

    Zhao, Qingzhi; Yao, Yibin; Yao, Wanqiang

    2018-01-01

    The temporal variability of precipitable water vapour (PWV) derived from Global Navigation Satellite System (GNSS) observations can be used to forecast precipitation events. A number of case studies of precipitation events have been analysed in Zhejiang Province, and a forecasting method for precipitation events was proposed. The PWV time series retrieved from the Global Positioning System (GPS) observations was processed by using a least-squares fitting method, so as to obtain the line tendency of ascents and descents over PWV. The increment of PWV for a short time (two to six hours) and PWV slope for a longer time (a few hours to more than ten hours) during the PWV ascending period are considered as predictive factors with which to forecast the precipitation event. The numerical results show that about 80%-90% of precipitation events and more than 90% of heavy rain events can be forecasted two to six hours in advance of the precipitation event based on the proposed method. 5-minute PWV data derived from GPS observations based on real-time precise point positioning (RT-PPP) were used for the typhoon event that passed over Zhejiang Province between 10 and 12 July, 2015. A good result was acquired using the proposed method and about 74% of precipitation events were predicted at some ten to thirty minutes earlier than their onset with a false alarm rate of 18%. This study shows that the GPS-based PWV was promising for short-term and now-casting precipitation forecasting.

  15. Black carbon and West African Monsoon precipitation. Observations and simulations

    International Nuclear Information System (INIS)

    Huang, J.; Adams, A.; Zhang, C.; Wang, C.

    2009-01-01

    We have recently investigated large-scale co-variability between aerosol and precipitation and other meteorological variables in the West African Monsoon (WAM) region using long term satellite observations and reanalysis data. In this study we compared the observational results to a global model simulation including only direct radiative forcing of black carbon (BC). From both observations and model simulations we found that in boreal cold seasons anomalously high African aerosols are associated with significant reductions in cloud amount, cloud top height, and surface precipitation. These results suggest that the observed precipitation reduction in the WAM region is caused by radiative effect of BC. The result also suggests that the BC effect on precipitation is nonlinear. (orig.)

  16. A new mechanism for warm-season precipitation response to global warming based on convection-permitting simulations

    Science.gov (United States)

    Dai, Aiguo; Rasmussen, Roy M.; Liu, Changhai; Ikeda, Kyoko; Prein, Andreas F.

    2017-08-01

    Climate models project increasing precipitation intensity but decreasing frequency as greenhouse gases increase. However, the exact mechanism for the frequency decrease remains unclear. Here we investigate this by analyzing hourly data from regional climate change simulations with 4 km grid spacing covering most of North America using the Weather Research and Forecasting model. The model was forced with present and future boundary conditions, with the latter being derived by adding the CMIP5 19-model ensemble mean changes to the ERA-interim reanalysis. The model reproduces well the observed seasonal and spatial variations in precipitation frequency and histograms, and the dry interval between rain events over the contiguous US. Results show that overall precipitation frequency indeed decreases during the warm season mainly due to fewer light-moderate precipitation (0.1 2.0 mm/h) events, while heavy (2 10 mm/h) events increase. Dry spells become longer and more frequent, together with a reduction in time-mean relative humidity (RH) in the lower troposphere during the warm season. The increased dry hours and decreased RH lead to a reduction in overall precipitation frequency and also for light-moderate precipitation events, while water vapor-induced increases in precipitation intensity and the positive latent heating feedback in intense storms may be responsible for the large increase in intense precipitation. The size of intense storms increases while their number decreases in the future climate, which helps explain the increase in local frequency of heavy precipitation. The results generally support a new hypothesis for future warm-season precipitation: each rainstorm removes ≥7% more moisture from the air per 1 K local warming, and surface evaporation and moisture advection take slightly longer than currently to replenish the depleted moisture before the next storm forms, leading to longer dry spells and a reduction in precipitation frequency, as well as

  17. Daily precipitation statistics in regional climate models

    DEFF Research Database (Denmark)

    Frei, Christoph; Christensen, Jens Hesselbjerg; Déqué, Michel

    2003-01-01

    An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km...

  18. Spatial variations of summer precipitation trends in South Korea, 1973-2005

    International Nuclear Information System (INIS)

    Chang, Heejun; Kwon, Won-Tae

    2007-01-01

    We have investigated the spatial patterns of trends in summer precipitation amount, intensity, and heavy precipitation for South Korea between 1973 and 2005. All stations show increasing trends in precipitation amount during the summer months, with the highest percentage of significant increase in June precipitation for the northern and central western part of South Korea. There is a significant increase in August precipitation for stations in the southeastern part of South Korea. Only a few stations exhibited significant upward trends in September precipitation. There is a weak to moderate spatial autocorrelation with the highest Moran's I value in June precipitation amount and August precipitation intensity. The number of days with daily precipitation exceeding 50 and 30 mm during the summer has increased at all stations. Observed trends are likely to be associated with changes in large-scale atmospheric circulation, sea surface temperature anomalies, and orography, but detailed causes of these trends need further investigation

  19. Chemical and environmental isotopes study of precipitation in Syria

    International Nuclear Information System (INIS)

    Al-Charideh, A.; Abou Zakhem, B.

    2009-02-01

    Chemical and isotopic compositions of monthly precipitation were monitored at 12 stations distributed over the entire region in Syria for a period of 4 years from December 1999 to April 2003. Amount of precipitation and mean air temperature of rain monthly were also recorded. The conductivity of rain waters varies between 35 μ/cm in the mountainous stations and 336 μ/cm at Deir Az-Zor station. Excepted Tartous station, the mean value of Cl in the rainfall in all station is 3.8 mg/l. The seasonal variations in δ 18 O are smaller at west stations than to the east stations due to low seasonal temperature variations. All stations are characterized by water lines with slopes significantly lower than GMWL, except Bloudan, suggesting the influence of local factors on the isotopic composition of the precipitation. d-excess values decrease from 19% in the western part to 13% in the eastern part of Syria, indicating the influence of the precipitation generated by the air masses coming from the Mediterranean Sea over Syria. A reliable altitude effect represent by depletion of heavy stable isotopes of about -0.21, and -1.47, per 100 m elevation of 18 O and δ 2 H, respectively. Monthly tritium activity and seasonal variations pattern are low in the west stations than at the east stations. The weighted mean tritium values are between 3 to 9 TU during 2000-2003, and it is increasing with distance from the Syrian coast by 1 TU /100 Km. (author)

  20. 21st Century Changes in Precipitation Extremes Based on Resolved Atmospheric Patterns

    Science.gov (United States)

    Gao, X.; Schlosser, C. A.; O'Gorman, P. A.; Monier, E.

    2014-12-01

    Global warming is expected to alter the frequency and/or magnitude of extreme precipitation events. Such changes could have substantial ecological, economic, and sociological consequences. However, climate models in general do not correctly reproduce the frequency distribution of precipitation, especially at the regional scale. In this study, a validated analogue method is employed to diagnose the potential future shifts in the probability of extreme precipitation over the United States under global warming. The method is based on the use of the resolved large-scale meteorological conditions (i.e. flow features, moisture supply) to detect the occurrence of extreme precipitation. The CMIP5 multi-model projections have been compiled for two radiative forcing scenarios (Representative Concentration Pathways 4.5 and 8.5). We further analyze the accompanying circulation features and their changes that may be responsible for shifts in extreme precipitation in response to changed climate. The application of such analogue method to detect other types of hazard events, i.e. landslides is also explored. The results from this study may guide hazardous weather watches and help society develop adaptive strategies for preventing catastrophic losses.

  1. The impact of Arctic and North Atlantic oscillation on temperature and precipitation anomalies in Serbia

    Directory of Open Access Journals (Sweden)

    Pavlović-Berdon Nada

    2012-01-01

    Full Text Available The impact of the Arctic Oscillations (AO and the North Atlantic Oscillations (NAO is considered as the most prominent of atmospheric oscillations in the area of the northern hemisphere from the United States to Siberia and from the Arctic to the subtropical Atlantic. The aim of this study was to determine how these fluctuations affect the temperature and precipitation in Serbia. This paper explores the impact for the period of 50 years (1958-2007 by months and in 20 synoptic stations. The influence of the AO on temperature anomalies in Serbia can be seen by the correlation coefficient, the largest in the month of January, while its impact on precipitation is the largest in the month of February. After the test of linear correlation between the NAO index and temperature anomalies for the base period 1971-2000 for 20 synoptic stations in Serbia, it has been found that the highest correlation is in the month of January. The correlation between the NAO and the precipitation anomalies for the stations mentioned above is the highest in the month of February. Spatial patterns of the AO and the NAO influence on temperature in January and on precipitation in February were obtained by applying principal component analysis.

  2. Spatial and seasonal responses of precipitation in the Ganges and Brahmaputra river basins to ENSO and Indian Ocean dipole modes: implications for flooding and drought

    Science.gov (United States)

    Pervez, M. S.; Henebry, G. M.

    2014-02-01

    We evaluated the spatial and temporal responses of precipitation in the basins as modulated by the El Niño Southern Oscillation (ENSO) and Indian Ocean (IO) dipole modes using observed precipitation records at 43 stations across the Ganges and Brahmaputra basins from 1982 to 2010. Daily observed precipitation records were extracted from Global Surface Summary of the Day dataset and spatial and monthly anomalies were computed. The anomalies were averaged for the years influenced by climate modes combinations. Occurrences of El Niño alone significantly reduced (60% and 88% of baseline in the Ganges and Brahmaputra basins, respectively) precipitation during the monsoon months in the northwestern and central Ganges basin and across the Brahmaputra basin. In contrast, co-occurrence of La Niña and a positive IO dipole mode significantly enhanced (135% and 160% of baseline, respectively) precipitation across both basins. During the co-occurrence of neutral phases in both climate modes (occurring 13 out of 28 yr), precipitation remained below average to average in the agriculturally extensive areas of Haryana, Uttar Pradesh, Bihar, eastern Nepal, and the Rajshahi district in Bangladesh in the Ganges basin and northern Bangladesh, Meghalaya, Assam, and Arunachal Pradesh in the Brahmaputra basin. This pattern implies that a regular water deficit is likely in these areas with implications for the agriculture sector due to its reliance on consistent rainfall for successful production. Major flooding and drought occurred as a consequence of the interactive effects of the ENSO and IO dipole modes, with the sole exception of extreme precipitation and flooding during El Niño events. This observational analysis will facilitate well informed decision making in minimizing natural hazard risks and climate impacts on agriculture, and supports development of strategies ensuring optimized use of water resources in best management practice under changing climate.

  3. Storms over the METER--ORNL Precipitation Network: the first six months

    International Nuclear Information System (INIS)

    Miller, R.L.; Patrinos, A.A.N.; Saylor, R.E.

    1979-06-01

    This report presents the first set of data collected by the METER--ORNL Precipitation Network. This network of 49 recording raingages and 5 recording windsets was installed in February 1978, around the Bowen Electric Generating Plant in northwest Georgia for the purpose of investigating the potential effect of the plant's cooling towers on rainfall. This study is conducted on behalf of the DOE Program on Meteorological Effects of Thermal Energy Releases (METER). Included in this report are the complete descriptions of 98 rainfall events which occurred over the METER--ORNL network during the period February 22--August 31, 1978. These descriptions are augmented by information and data supplied by the National Weather Service (NWS). Several stratifications of the rainfall events are performed for reference purposes

  4. TOMS/Earth Probe UV Aerosol Index Monthly L3 Global 1x1.25 deg Lat/Lon Grid V008

    Data.gov (United States)

    National Aeronautics and Space Administration — This data product contains TOMS/Earth Probe UV Aerosol Index Monthly L3 Global 1x1.25 deg Lat/Lon Grid Version 8 data in ASCII format. (The shortname for this...

  5. TOMS/Nimbus-7 UV Aerosol Index Monthly L3 Global 1x1.25 deg Lat/Lon Grid V008

    Data.gov (United States)

    National Aeronautics and Space Administration — This data product contains TOMS/Nimbus-7 UV Aerosol Index Monthly L3 Global 1x1.25 deg Lat/Lon Grid Version 8 data in ASCII format. The Total Ozone Mapping...

  6. TOMS/Nimbus-7 Total Column Ozone Monthly L3 Global 1x1.25 deg Lat/Lon Grid V008

    Data.gov (United States)

    National Aeronautics and Space Administration — This data product contains TOMS/Nimbus-7 Total Column Ozone Monthly L3 Global 1x1.25 deg Lat/Lon Grid Version 8 data in ASCII format. The Total Ozone Mapping...

  7. Groundwater level responses to precipitation variability in Mediterranean insular aquifers

    Science.gov (United States)

    Lorenzo-Lacruz, Jorge; Garcia, Celso; Morán-Tejeda, Enrique

    2017-09-01

    Groundwater is one of the largest and most important sources of fresh water on many regions under Mediterranean climate conditions, which are exposed to large precipitation variability that includes frequent meteorological drought episodes, and present high evapotranspiration rates and water demand during the dry season. The dependence on groundwater increases in those areas with predominant permeable lithologies, contributing to aquifer recharge and the abundance of ephemeral streams. The increasing pressure of tourism on water resources in many Mediterranean coastal areas, and uncertainty related to future precipitation and water availability, make it urgent to understand the spatio-temporal response of groundwater bodies to precipitation variability, if sustainable use of the resource is to be achieved. We present an assessment of the response of aquifers to precipitation variability based on correlations between the Standardized Precipitation Index (SPI) at various time scales and the Standardized Groundwater Index (SGI) across a Mediterranean island. We detected three main responses of aquifers to accumulated precipitation anomalies: (i) at short time scales of the SPI (24 months). The differing responses were mainly explained by differences in lithology and the percentage of highly permeable rock strata in the aquifer recharge areas. We also identified differences in the months and seasons when aquifer storages are more dependent on precipitation; these were related to climate seasonality and the degree of aquifer exploitation or underground water extraction. The recharge of some aquifers, especially in mountainous areas, is related to precipitation variability within a limited spatial extent, whereas for aquifers located in the plains, precipitation variability influence much larger areas; the topography and geological structure of the island explain these differences. Results indicate large spatial variability in the response of aquifers to precipitation in

  8. Variability and trends of wet season temperature in the Sudano-Sahelian zone and relationships with precipitation

    Science.gov (United States)

    Oueslati, Boutheina; Camberlin, Pierre; Zoungrana, Joël; Roucou, Pascal; Diallo, Saliou

    2018-02-01

    The relationships between precipitation and temperature in the central Sudano-Sahelian belt are investigated by analyzing 50 years (1959-2008) of observed temperature (Tx and Tn) and rainfall variations. At daily time-scale, both Tx and Tn show a marked decrease as a response to rainfall occurrence, with a strongest departure from normal 1 day after the rainfall event (-0.5 to -2.5 °C depending on the month). The cooling is slightly larger when heavy rainfall events (>5 mm) are considered. The temperature anomalies weaken after the rainfall event, but are still significant several days later. The physical mechanisms accounting for the temperature response to precipitation are analysed. The Tx drop is accounted for by reduced incoming solar radiation associated with increased cloud cover and increased surface evaporation following surface moistening. The effect of evaporation becomes dominant a few days after the rainfall event. The reduced daytime heat storage and the subsequent sensible heat flux result in a later negative Tn anomaly. The effect of rainfall variations on temperature is significant for long-term warming trends. The rainfall decrease experienced between 1959 and 2008 accounts for a rainy season Tx increase of 0.15 to 0.3 °C, out of a total Tx increase of 1.3 to 1.5 °C. These results have strong implications on the assessment of future temperature changes. The dampening or amplifying effects of precipitation are determined by the sign of future precipitation trends. Confidence on temperature changes under global warming partly depend on the robustness of precipitation projections.

  9. Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

    Science.gov (United States)

    Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

    2017-12-01

    Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

  10. Data Analysis of GPM Constellation Satellites-IMERG and ERA-Interim precipitation products over West of Iran

    Science.gov (United States)

    Sharifi, Ehsan; Steinacker, Reinhold; Saghafian, Bahram

    2016-04-01

    Precipitation is a critical component of the Earth's hydrological cycle. The primary requirement in precipitation measurement is to know where and how much precipitation is falling at any given time. Especially in data sparse regions with insufficient radar coverage, satellite information can provide a spatial and temporal context. Nonetheless, evaluation of satellite precipitation is essential prior to operational use. This is why many previous studies are devoted to the validation of satellite estimation. Accurate quantitative precipitation estimation over mountainous basins is of great importance because of their susceptibility to hazards. In situ observations over mountainous areas are mostly limited, but currently available satellite precipitation products can potentially provide the precipitation estimation needed for meteorological and hydrological applications. One of the newest and blended methods that use multi-satellites and multi-sensors has been developed for estimating global precipitation. The considered data set known as Integrated Multi-satellitE Retrievals (IMERG) for GPM (Global Precipitation Measurement) is routinely produced by the GPM constellation satellites. Moreover, recent efforts have been put into the improvement of the precipitation products derived from reanalysis systems, which has led to significant progress. One of the best and a worldwide used model is developed by the European Centre for Medium Range Weather Forecasts (ECMWF). They have produced global reanalysis daily precipitation, known as ERA-Interim. This study has evaluated one year of precipitation data from the GPM-IMERG and ERA-Interim reanalysis daily time series over West of Iran. IMERG and ERA-Interim yield underestimate the observed values while IMERG underestimated slightly and performed better when precipitation is greater than 10mm. Furthermore, with respect to evaluation of probability of detection (POD), threat score (TS), false alarm ratio (FAR) and probability

  11. Responses of Mean and Extreme Precipitation to Deforestation in the Maritime Continent

    Science.gov (United States)

    Chen, C. C.; Lo, M. H.; Yu, J. Y.

    2017-12-01

    Anthropogenic land use and land cover change, including tropical deforestation, could have substantial effects on local surface energy and water budgets, and thus on the atmospheric stability which may result in changes in precipitation. Maritime Continent has undergone severe deforestation in recent decades but has received less attention than Amazon or Congo rainforests. Therefore, this study is to decipher the precipitation response to deforestation in the Maritime Continent. We conduct deforestation experiments using Community Earth System Model (CESM) and through converting the tropical rainforest into grassland. The results show that deforestation in Maritime Continent leads to an increase in both mean temperature and mean precipitation. Moisture budget analysis indicates that the increase in precipitation is associated with the vertically integrated vertical moisture advection, especially the dynamic component (changes in convection). In addition, through moist static energy (MSE) budget analysis, we find the atmosphere among deforested areas become unstable owing to the combined effects of positive specific humidity anomalies at around 850 hPa and anomalous warming extended from the surface to 750 hPa. This instability will induce anomalous ascending motion, which could enhance the low-level moisture convergence, providing water vapor from the surrounding warm ocean. To further evaluate the precipitation response to deforestation, we examine the precipitation changes under La Niña events and global warming scenario using CESM Atmospheric Model Intercomparison Project (AMIP) simulations and Representative Concentration Pathway (RCP) 8.5 simulations. We find that the precipitation increase caused by deforestation in Maritime Continent is comparable in magnitude to that generated by either natural variability or global warming forcing. Besides the changes in mean precipitation, preliminary results show the extreme precipitation also increases. We will further

  12. Stable Isotopic Composition of Precipitation from 2015-2016 Central Texas Rainfall Events

    Science.gov (United States)

    Maupin, C. R.; McChesney, C. L.; Roark, B.; Gorman, M. K.; Housson, A. L.

    2016-12-01

    Central Texas lies within the Southern Great Plains, a region where rainfall is of tremendous agricultural and associated socioeconomic importance. Paleoclimate records from speleothems in central Texas caves may assist in placing historical and recent drought and pluvial events in the context of natural variability. Effective interpretation of such records requires the nature and origin of variations in the meteoric δ18O signal transmitted from cloud to speleothem to be understood. Here we present a record of meteoric δ18O and δD from each individual precipitation event (δ18Op and δDp), collected by rain gauge in Austin, Texas, USA, from April 2015 through 2016. Backwards hybrid single-particle Lagrangian integrated trajectories (HYSPLITs) indicate the broader moisture source for each precipitation event during this time was the Gulf of Mexico. The local meteoric water line is within error of the global meteoric water line, suggesting minimal sourcing of evaporated continental vapor for precipitation. Total monthly rainfall followed the climatological pattern of a dual boreal spring and fall maximum, with highly variable event δ18Op and δDp values. Surface temperature during precipitation often exerts control over continental and mid latitude δ18Op values, but is not significantly correlated to study site δ18Op (p>0.10). Amount of rain falling during each precipitation event ("amount effect") explains a significant 18% of variance in δ18Op. We hypothesize that this relationship can be attributed to the following: 1) minimal recycling of continental water vapor during the study period; 2) the presence of synoptic conditions favoring intense boreal spring and fall precipitation, driven by a developing, and subsequently in-place, strong ENSO event coupled with a southerly flow from the open Gulf of Mexico; and 3) the meteorological nature of the predominant precipitating events over Texas during this time, mesoscale convective systems, which are known to

  13. Assessment of GPM and TRMM Multi-Satellite Precipitation Products in Streamflow Simulations in a Data-Sparse Mountainous Watershed in Myanmar

    Directory of Open Access Journals (Sweden)

    Fei Yuan

    2017-03-01

    Full Text Available Satellite precipitation products from the Global Precipitation Measurement (GPM mission and its predecessor the Tropical Rainfall Measuring Mission (TRMM are a critical data source for hydrological applications in ungauged basins. This study conducted an initial and early evaluation of the performance of the Integrated Multi-satellite Retrievals for GPM (IMERG final run and the TRMM Multi-satellite Precipitation Analysis 3B42V7 precipitation products, and their feasibility in streamflow simulations in the Chindwin River basin, Myanmar, from April 2014 to December 2015 was also assessed. Results show that, although IMERG and 3B42V7 can potentially capture the spatiotemporal patterns of historical precipitation, the two products contain considerable errors. Compared with 3B42V7, no significant improvements were found in IMERG. Moreover, 3B42V7 outperformed IMERG at daily and monthly scales and in heavy rain detections at four out of five gauges. The large errors in IMERG and 3B42V7 distinctly propagated to streamflow simulations via the Xinanjiang hydrological model, with a significant underestimation of total runoff and high flows. The bias correction of the satellite precipitation effectively improved the streamflow simulations. The 3B42V7-based streamflow simulations performed better than the gauge-based simulations. In general, IMERG and 3B42V7 are feasible for use in streamflow simulations in the study area, although 3B42V7 is better suited than IMERG.

  14. Precipitation characteristics in tropical Africa using satellite and in situ observations

    Science.gov (United States)

    Dezfuli, A. K.; Ichoku, I.; Huffman, G. J.; Mohr, K. I.

    2017-12-01

    Tropical Africa receives nearly all its precipitation as a result of convection. The characteristics of rain-producing systems in this region have not been well-understood, despite their crucial role in regional and global circulation. This is mainly due to the lack of in situ observations. Here, we have used precipitation records from the Trans-African Hydro-Meteorological Observatory (TAHMO) ground-based gauge network to improve our knowledge about the rainfall systems in the region, and to validate the recently-released IMERG precipitation product based on satellite observations from the Global Precipitation Measurement (GPM) constellation. The high temporal resolution of the gauge data has allowed us to identify three classes of rain events based on their duration and intensity. The contribution of each class to the total rainfall and the favorable surface atmospheric conditions for each class have been examined. As IMERG aims to continue the legacy of its predecessor, TRMM Multi-Satellite Precipitation Analysis (TMPA), and provide higher resolution data, continent-wide comparisons are made between these two products. Due to its improved temporal resolution, IMERG shows some advantages over TMPA in capturing the diurnal cycle and propagation of the meso-scale convective systems. However, the performance of the two satellite-based products varies by season, region and the evaluation statistics. The results of this study serve as a basis for our ongoing work on the impacts of biomass burning on precipitation processes in Africa.

  15. Isotopic composition of past precipitation

    International Nuclear Information System (INIS)

    Edwards, T.W.D.

    1998-01-01

    The distribution of stable isotopes in precipitation provides critical quantitative information about the global water cycle. The first PAGES/IAEA ISOMAP workshop was held at the IAEA headquarters in Vienna, 24-26 August 1998, which gathered 32 participants. The presentation and discussions demonstrated that a high level of sophistication already exists in the development of transfer functions between measured parameters and precipitation, as a result of the extensive use of water isotope tracers in paleo-environmental investigations, but a major challenge facing both producers and users of paleo-isotope data is the effective management of data and meta-data, to permit ready retrieval of raw and inferred data for comparison and reinterpretation. This will be in important goal of future ISOMAP activities. The critical need for more paleo-data from low latitudes was clearly recognized

  16. Analysis on Climatic Characteristics of the Precipitation Anomaly in Southwest China in Recent 60 Years

    Institute of Scientific and Technical Information of China (English)

    ZHANG; Rong; PANG; Jing; QIN; Jun

    2012-01-01

    [Objective]The research aimed to analyze temporal-spatial distribution characteristics of the precipitation anomaly in southwest China from 1951 to 2010. [Method] Based on monthly precipitation data at 44 stations of southwest China and 160 stations of China from 1951 to 2010, by using EOF analysis, wavelet analysis and composite analysis, monthly and seasonal change rules of the precipitation in southwest China were analyzed. Corresponding spatial-temporal distribution characteristics of the precipitation in drought and flood years were studied. Temporal-spatial distribution characteristics of the precipitation anomaly in southwest China in recent 60 years were revealed. [Result]Seasonal distribution of the precipitation in southwest China was uneven and was typical single-peak type. Precipitation concentrated from May to September, and peak appeared in July. In recent years, rainfall in autumn significantly became less, while that in other seasons had no obvious change. Precipitation in summer had the cycle of 14 years, another for 6 years and 3-4 years of periodic oscillations. In wet years, precipitation in southwest China had same phase with that in southern China, and anti-phase with that in the junction of Qinghai, Gansu, Xinjiang and Tibet. In dry years, precipitation in southwest China had same phase with that in the eastern part of northwest China and northern China. [Conclusion]The research provided reference basis for prediction and pre-warning of the precipitation in the zone.

  17. Global change and biological soil crusts: Effects of ultraviolet augmentation under altered precipitation regimes and nitrogen additions

    Science.gov (United States)

    Belnap, J.; Phillips, S.L.; Flint, S.; Money, J.; Caldwell, M.

    2008-01-01

    Biological soil crusts (BSCs), a consortium of cyanobacteria, lichens, and mosses, are essential in most dryland ecosystems. As these organisms are relatively immobile and occur on the soil surface, they are exposed to high levels of ultraviolet (UV) radiation and atmospheric nitrogen (N) deposition, rising temperatures, and alterations in precipitation patterns. In this study, we applied treatments to three types of BSCs (early, medium, and late successional) over three time periods (spring, summer, and spring-fall). In the first year, we augmented UV and altered precipitation patterns, and in the second year, we augmented UV and N. In the first year, with average air temperatures, we saw little response to our treatments except quantum yield, which was reduced in dark BSCs during one of three sample times and in Collema BSCs two of three sample times. There was more response to UV augmentation the second year when air temperatures were above average. Declines were seen in 21% of the measured variables, including quantum yield, chlorophyll a, UV-protective pigments, nitrogenase activity, and extracellular polysaccharides. N additions had some negative effects on light and dark BSCs, including the reduction of quantum yield, ??-carotene, nitrogenase activity, scytonemin, and xanthophylls. N addition had no effects on the Collema BSCs. When N was added to samples that had received augmented UV, there were only limited effects relative to samples that received UV without N. These results indicate that the negative effect of UV and altered precipitation on BSCs will be heightened as global temperatures increase, and that as their ability to produce UV-protective pigments is compromised, physiological functioning will be impaired. N deposition will only ameliorate UV impacts in a limited number of cases. Overall, increases in UV will likely lead to lowered productivity and increased mortality in BSCs through time, which, in turn, will reduce their ability to contribute

  18. Fuzzy-logic-based power control system for multifield electrostatic precipitators

    Energy Technology Data Exchange (ETDEWEB)

    Grass, N. [Siemens AG, Erlangen (Germany)

    2002-10-01

    The power consumption of large precipitators can be in the range of 1 MW and above. Depending on the dust load properties, the electrical power may be reduced by up to 50% by applying fuzzy logic, without significantly increasing the dust emissions. The new approach uses fuzzy logic for optimization of existing electrostatic precipitators. The software runs on a standard personal computer platform under the, Windows NT operating system. The controllers of the electrostatic precipitator power supplies are linked to the personal computer via an industrial network (e.g., PROFIBUS). The system determines online the differentials of emission versus electrical power of each field. This measurement is difficult because of overlaid events in the other zones, and process changes. The long response time of the resultant dust emission due to electrical power changes in the precipitator is an additional complication. Rules were defined for a coarse, but fast-response power adaptation of all zones. Fine tuning the running system after the coarse optimization increased the accuracy and reliability. When installed on a 4 x 5 zone precipitator in a power station, significant results were obtained. The power savings over three months of operation were in the range of 40%-60% depending on the load and fuel characteristics. Data were recorded over the test period of three months. The results are presented.

  19. Magnetospheric Response Associated With Multiple Atmospheric Reflections of Precipitated Electrons in Aurora.

    Science.gov (United States)

    Khazanov, G. V.; Merkin, V. G.; Zesta, E.; Sibeck, D. G.; Grubbs, G. A., II; Chu, M.; Wiltberger, M. J.

    2017-12-01

    The magnetosphere and ionosphere are strongly coupled by precipitating electrons during storm times. Therefore, first principle simulations of precipitating electron fluxes are required to understand storm time variations of ionospheric conductances and related electric fields. As has been discussed by Khazanov et al. [2015 - 2017], the first step in such simulations is initiation of electron precipitation from the Earth's plasma sheet via wave particle interaction processes into both magnetically conjugate points, and the step 2 is the follow up of multiple atmospheric reflections of electron fluxes formed at the boundary between the ionosphere and magnetosphere of two magnetically conjugate points. To demonstrate this effect on the global magnetospheric response the Lyon-Fedder-Mobarry global magnetosphere model coupled with the Rice Convection Model of the inner magnetosphere has been used and run for the geomagnetic storm of 17 March 2013.

  20. Local biomass burning is a dominant cause of the observed precipitation reduction in southern Africa

    Science.gov (United States)

    Hodnebrog, Øivind; Myhre, Gunnar; Forster, Piers M.; Sillmann, Jana; Samset, Bjørn H.

    2016-01-01

    Observations indicate a precipitation decline over large parts of southern Africa since the 1950s. Concurrently, atmospheric concentrations of greenhouse gases and aerosols have increased due to anthropogenic activities. Here we show that local black carbon and organic carbon aerosol emissions from biomass burning activities are a main cause of the observed decline in southern African dry season precipitation over the last century. Near the main biomass burning regions, global and regional modelling indicates precipitation decreases of 20–30%, with large spatial variability. Increasing global CO2 concentrations further contribute to precipitation reductions, somewhat less in magnitude but covering a larger area. Whereas precipitation changes from increased CO2 are driven by large-scale circulation changes, the increase in biomass burning aerosols causes local drying of the atmosphere. This study illustrates that reducing local biomass burning aerosol emissions may be a useful way to mitigate reduced rainfall in the region. PMID:27068129

  1. Average monthly and annual climate maps for Bolivia

    KAUST Repository

    Vicente-Serrano, Sergio M.; El Kenawy, Ahmed M.; Azorin-Molina, Cesar; Chura, O.; Trujillo, F.; Aguilar, Enric; Martí n-Herná ndez, Natalia; Ló pez-Moreno, Juan Ignacio; Sanchez-Lorenzo, Arturo; Morá n-Tejeda, Enrique; Revuelto, Jesú s; Ycaza, P.; Friend, F.

    2015-01-01

    This study presents monthly and annual climate maps for relevant hydroclimatic variables in Bolivia. We used the most complete network of precipitation and temperature stations available in Bolivia, which passed a careful quality control

  2. Study on the Variation Characteristic of Precipitation in Liaoning Province in Recent 48 Years

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    [Objective] The aim was to study the variation characteristic of precipitation in Liaoning Province in recent 48 years. [Method] According to monthly precipitation data from meteorological observation station in Liaoning Province from 1961 to 2008, the variation characteristic of precipitation in Liaoning was analyzed by means of one-dimensional linear estimation, 5-year moving average and wavelet transform method in our paper. [Result] Annual mean precipitation in Liaoning from 1961 to 2008 showed decrease...

  3. Spatiotemporal Variability and Covariability of Temperature, Precipitation, Soil Moisture, and Vegetation in North America for Regional Climate Model Applications

    Science.gov (United States)

    Castro, C. L.; Beltran-Przekurat, A. B.; Pielke, R. A.

    2007-05-01

    Previous work has established that the dominant modes of Pacific SSTs influence the summer climate of North America through large-scale forcing, and this effect is most pronounced during the early part of the season. It is hypothesized, then, that land surface influences become more dominant in the latter part of the season as remote teleconnection influences diminish. As a first step toward investigation of this hypothesis in a regional climate model (RCM) framework, the statistically signficant spatiotemporal patterns of variability and covariability in North American precipitation (specified by the standardized precipitation index, or SPI), soil moisture, and vegetation are determined for timescales from a month to six months. To specify these respective data we use: CPC gauge- derived precipitation (1950-2000), Variable Infiltration Capacity (VIC) Model and NOAH Model NLDAS soil moisture and temperature, and the Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (GIMMS-NDVI). The principal statistical tool used is multiple taper frequency singular value decomposition (MTM-SVD), and this is supplemented by wavelet analysis for specific areas of interest. The significant interannual variability in all of these data occur at a timescale of about 7 to 9 years and appears to be the integrated effect of remote SST forcing from the Pacific. Considering the entire year, the spatial pattern for precipitation resembles the typical ENSO winter signature. If the summer season is considered seperately, the out of phase relationship between precipitation anomalies in the central U.S. and core monsoon region is apparent. The largest soil moisture anomalies occur in the central U.S., since precipitation in this region has a consistent relationship to Pacific SSTs for the entire year. This helps to explain the approximately 20 year periodicity in drought conditions there. Unlike soil moisture, the largest anomalies in vegetation occur in the

  4. The intensity of precipitation during extratropical cyclones in global warming simulations: a link to cyclone intensity?

    Energy Technology Data Exchange (ETDEWEB)

    Watterson, I.G. [CSIRO Atmospheric Research, Aspendale (Australia)

    2006-01-01

    Simulations of global warming over the coming century from two CSIRO GCMs are analysed to assess changes in the intensity of extratropical cyclones, and the potential role of increased latent heating associated with precipitation during cyclones. A simple surface cyclone detection scheme is applied to a four-member ensemble of simulations from the Mark 2 GCM, under rising greenhouse gas concentrations. The seasonal distribution of cyclones appears broadly realistic during 1961-1990. By 2071-2100, with 3 K global warming, numbers over 20 deg N to 70 deg N decrease by 6% in winter and 2% annually, with similar results for the south. The average intensity of cyclones, from relative central pressure and other measures, is largely unchanged however. 30-yr extremes of dynamic intensity also show little clear change, including values averaged over continents. Mean rain rates at cyclone centres are typically at least double rates from all days. Rates during cyclones increase by an average 14% in the northern winter under global warming. Rates over adjacent grid squares and during the previous day increase similarly, as do extreme rates. Results from simulations of the higher-resolution (1.8 deg grid) Mark 3 GCM are similar, with widespread increases in rain rates but not in cyclone intensity. The analyses suggest that latent heating during storms increases, as anticipated due to the increased moisture capacity of the warmer atmosphere. However, any role for enhanced heating in storm development in the GCMs is apparently masked by other factors. An exception is a 5% increase in extreme intensity around 55 deg S in Mark 3, despite decreased numbers of lows, a factor assessed using extreme value theory. Further studies with yet higher-resolution models may be needed to examine the potential realism of these results, particularly with regard to extremes at smaller scale.

  5. Socio-hydrological approach to the evaluation of global fertilizer substitution by sustainable struvite precipitants from wastewater

    Science.gov (United States)

    Kok, Dirk-Jan; Pande, Saket; Renata Cordeiro Ortigara, Angela; Savenije, Hubert; Uhlenbrook, Stefan

    2017-04-01

    Phosphorus is an element necessary for the development of organic tissue as it forms a key, structural component of DNA and RNA. Currently, much of this unrenewable resource is being wasted to the ocean through the discharge of untreated or partially treated wastewater from urban areas and livestock industries. Analysing the potential phosphorus production of these two sectors in possibly meeting the partial demand of the agricultural sector, will be an important tool in tackling both phosphorus depletion from natural sources as well as phosphorus pollution of water sources . In this study, a global overview is provided where a selection of P-production nodes and P-consumption nodes have been determined using global spatial data. Distances, investment costs and associated carbon footprints are then considered in modelling a simple, alternative trade network of struvite precipitant, phosphorus flows. The network is then optimized to maximum trade flow after which an international, free-market P-commodity price is determined. Carrot-stick policy measures such as subsidies and carbon taxes are evaluated in their benefits to supporting sustainable phosphorus consumption over the non-sustainable counterpart. Preliminary results have revealed that there exists a total anthropogenic production potential of 3.3 MtP for 2005. Very crudely, but in accordance to results by Milhelcic et al. (2011) who reported 22%, approximately 20% of the reported global fertilizer consumption could then be satisfied by recovering urban phosphorus. Phosphorus recovery from wastewater for secondary utilization will prove an important step in creating sustainable communities through closed circle economic development. It is also a step towards prolonging our phosphate rock reserves, granting more time to revise our current phosphorus throughput cycle before the depletion of the remaining reserves.

  6. A global empirical system for probabilistic seasonal climate prediction

    Science.gov (United States)

    Eden, J. M.; van Oldenborgh, G. J.; Hawkins, E.; Suckling, E. B.

    2015-12-01

    Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961-2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño-Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

  7. Prediction of Monthly Summer Monsoon Rainfall Using Global Climate Models Through Artificial Neural Network Technique

    Science.gov (United States)

    Nair, Archana; Singh, Gurjeet; Mohanty, U. C.

    2018-01-01

    The monthly prediction of summer monsoon rainfall is very challenging because of its complex and chaotic nature. In this study, a non-linear technique known as Artificial Neural Network (ANN) has been employed on the outputs of Global Climate Models (GCMs) to bring out the vagaries inherent in monthly rainfall prediction. The GCMs that are considered in the study are from the International Research Institute (IRI) (2-tier CCM3v6) and the National Centre for Environmental Prediction (Coupled-CFSv2). The ANN technique is applied on different ensemble members of the individual GCMs to obtain monthly scale prediction over India as a whole and over its spatial grid points. In the present study, a double-cross-validation and simple randomization technique was used to avoid the over-fitting during training process of the ANN model. The performance of the ANN-predicted rainfall from GCMs is judged by analysing the absolute error, box plots, percentile and difference in linear error in probability space. Results suggest that there is significant improvement in prediction skill of these GCMs after applying the ANN technique. The performance analysis reveals that the ANN model is able to capture the year to year variations in monsoon months with fairly good accuracy in extreme years as well. ANN model is also able to simulate the correct signs of rainfall anomalies over different spatial points of the Indian domain.

  8. Characterization of increased persistence and intensity of precipitation in the northeastern United States

    Science.gov (United States)

    Guilbert, Justin; Betts, Alan K.; Rizzo, Donna M.; Beckage, Brian; Bomblies, Arne

    2015-03-01

    We present evidence of increasing persistence in daily precipitation in the northeastern United States that suggests that global circulation changes are affecting regional precipitation patterns. Meteorological data from 222 stations in 10 northeastern states are analyzed using Markov chain parameter estimates to demonstrate that a significant mode of precipitation variability is the persistence of precipitation events. We find that the largest region-wide trend in wet persistence (i.e., the probability of precipitation in 1 day and given precipitation in the preceding day) occurs in June (+0.9% probability per decade over all stations). We also find that the study region is experiencing an increase in the magnitude of high-intensity precipitation events. The largest increases in the 95th percentile of daily precipitation occurred in April with a trend of +0.7 mm/d/decade. We discuss the implications of the observed precipitation signals for watershed hydrology and flood risk.

  9. Key drivers of precipitation isotopes in Windhoek, Namibia (2012-2016)

    Science.gov (United States)

    Kaseke, K. F.; Wang, L.; Wanke, H.

    2017-12-01

    Southern African climate is characterized by large variability with precipitation model estimates varying by as much as 70% during summer. This difference between model estimates is partly because most models associate precipitation over Southern Africa with moisture inputs from the Indian Ocean while excluding inputs from the Atlantic Ocean. However, growing evidence suggests that the Atlantic Ocean may also contribute significant amounts of moisture to the region. This four-year (2012-2016) study investigates the isotopic composition (δ18O, δ2H and δ17O) of event-scale precipitation events, the key drivers of isotope variations and the origins of precipitation experienced in Windhoek, Namibia. Results indicate large storm-to-storm isotopic variability δ18O (25‰), δ2H (180‰) and δ17O (13‰) over the study period. Univariate analysis showed significant correlations between event precipitation isotopes and local meteorological parameters; lifted condensation level, relative humidity (RH), precipitation amount, average wind speed, surface and air temperature (p < 0.05). The number of significant correlations between local meteorological parameters and monthly isotopes was much lower suggesting loss of information through data aggregation. Nonetheless, the most significant isotope driver at both event and monthly scales was RH, consistent with the semi-arid classification of the site. Multiple linear regression analysis suggested RH, precipitation amount and air temperature were the most significant local drivers of precipitation isotopes accounting for about 50% of the variation implying that about 50% could be attributed to source origins. HYSLPIT trajectories indicated that 78% of precipitation originated from the Indian Ocean while 21% originated from the Atlantic Ocean. Given that three of the four study years were droughts while two of the three drought years were El Niño related, our data also suggests that δ'17O-δ'18O could be a useful tool to

  10. Precipitation Estimation Using L-Band and C-Band Soil Moisture Retrievals

    Science.gov (United States)

    Koster, Randal D.; Brocca, Luca; Crow, Wade T.; Burgin, Mariko S.; De Lannoy, Gabrielle J. M.

    2016-01-01

    An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterometer (ASCAT) mission. The precipitation estimates so obtained are evaluated against in situ (gauge-based) precipitation observations from across the globe. The precipitation estimation skill achieved using the L-band SMAP and SMOS data sets is higher than that obtained with the C-band product, as might be expected given that L-band is sensitive to a thicker layer of soil and thereby provides more information on the response of soil moisture to precipitation. The square of the correlation coefficient between the SMAP-based precipitation estimates and the observations (for aggregations to approximately100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions specifically designed to monitor soil moisture thus do provide significant information on precipitation variability, information that could contribute to efforts in global precipitation estimation.

  11. Exploring Database Improvements for GPM Constellation Precipitation Retrievals

    Science.gov (United States)

    Ringerud, S.; Kidd, C.; Skofronick Jackson, G.

    2017-12-01

    The Global Precipitation Measurement Mission (GPM) offers an unprecedented opportunity for understanding and mapping of liquid and frozen precipitation on a global scale. GPM mission development of physically based retrieval algorithms, for application consistently across the constellation radiometers, relies on combined active-passive retrievals from the GPM core satellite as a transfer standard. Radiative transfer modeling is then utilized to compute a priori databases at the frequency and footprint geometry of each individual radiometer. The Goddard Profiling Algorithm (GPROF) performs constellation retrievals across the GPM databases in a Bayesian framework, constraining searches using model data on a pixel-by-pixel basis. This work explores how the retrieval might be enhanced with additional information available within the brightness temperature observations themselves. In order to better exploit available information content, model water vapor is replaced with retrieved water vapor. Rather than treating each footprint as a 1D profile alone in space, information regarding Tb variability in the horizontal is added as well as variability in the time dimension. This additional information is tested and evaluated for retrieval improvement in the context of the Bayesian retrieval scheme. Retrieval differences are presented as a function of precipitation and surface type for evaluation of where the added information proves most effective.

  12. Long-term variability of precipitation in Republic of Macedonia

    International Nuclear Information System (INIS)

    Slavov, Nikola; Marinova, Tania; Ristevski, Pece

    2004-01-01

    During the last century a great attention has been spared to the water resources of the territories of different countries in the world. In the last decades investigations were directed towards the long-term variability of precipitation in the basic regions of agricultural production. Among these investigations the results that indicate decreasing of precipitation amounts during the potential crop-growing season are of especially great interest because precipitation decreasing affects harmfully crop production and population feeding. The purpose of the present work is to study the long-term variability of monthly precipitation sums for 5 representative meteorological stations in Republic of Macedonia: Skopje, Bitola, Prilep, Stip and Demir Kapija for the period 1925-2000. The duration and periodicity of precipitation variations are analyzed on the base of 5-years smooth values for different seasons, warm and cold half-year and for year. The tendencies of trend for the period 1925-2000 are found out.(Author)

  13. Chemical and isotopic composition of precipitations in Syria

    International Nuclear Information System (INIS)

    Abou Zakhem, B.; Hafez, R.

    2008-01-01

    13 meteoric stations were selected in syria for cumulative monthly rainfall sampling during two hydrological cycles; 1991-1992 and 1992-1993. The chemical and isotopic compositions of monthly precipitation were studied. The winter and spring rainfall isotopic characteristics were determined, in addition to the syrian or local meteoric line (SMWL) was estimated with a slope of 6.63 and that of both syria and Jordan of 6.73. The effect of climatic factors as temperature and relative air humidity on oxygen-18, deuterium and d-excess were studied and it was found that the relationship between temperature and oxygen-18 and deuterium is a positive linear correlation; however, it is a negative correlation with d-excess. The mean seasonal variation amplitude was determined by 6%, and the amount effect on isotopic content of precipitation was studied. The geographic factors and its affect on isotopic contents of precipitation such as altitude were considered, furthermore, the isotopic gradient with altitude was determined for both oxygen-18 and deuterium (-0.14% and - 0.84%/100 m elevation respectively). The spatial variability of oxygen-18, deuterium, tritium and d-excess indicted the effect of mountain chains and gaps between mountains on the isotopic content of precipitation, the continental effect on tritium build-up by about 33% per 100 Km from the coast. The increase of d-excess values towards the south west proves the eastern mediterranean climate type over this region. (author)

  14. Application of physical scaling towards downscaling climate model precipitation data

    Science.gov (United States)

    Gaur, Abhishek; Simonovic, Slobodan P.

    2018-04-01

    Physical scaling (SP) method downscales climate model data to local or regional scales taking into consideration physical characteristics of the area under analysis. In this study, multiple SP method based models are tested for their effectiveness towards downscaling North American regional reanalysis (NARR) daily precipitation data. Model performance is compared with two state-of-the-art downscaling methods: statistical downscaling model (SDSM) and generalized linear modeling (GLM). The downscaled precipitation is evaluated with reference to recorded precipitation at 57 gauging stations located within the study region. The spatial and temporal robustness of the downscaling methods is evaluated using seven precipitation based indices. Results indicate that SP method-based models perform best in downscaling precipitation followed by GLM, followed by the SDSM model. Best performing models are thereafter used to downscale future precipitations made by three global circulation models (GCMs) following two emission scenarios: representative concentration pathway (RCP) 2.6 and RCP 8.5 over the twenty-first century. The downscaled future precipitation projections indicate an increase in mean and maximum precipitation intensity as well as a decrease in the total number of dry days. Further an increase in the frequency of short (1-day), moderately long (2-4 day), and long (more than 5-day) precipitation events is projected.

  15. Satellite precipitation estimation over the Tibetan Plateau

    Science.gov (United States)

    Porcu, F.; Gjoka, U.

    2012-04-01

    Precipitation characteristics over the Tibetan Plateau are very little known, given the scarcity of reliable and widely distributed ground observation, thus the satellite approach is a valuable choice for large scale precipitation analysis and hydrological cycle studies. However,the satellite perspective undergoes various shortcomings at the different wavelengths used in atmospheric remote sensing. In the microwave spectrum often the high soil emissivity masks or hides the atmospheric signal upwelling from light-moderate precipitation layers, while low and relatively thin precipitating clouds are not well detected in the visible-infrared, because of their low contrast with cold and bright (if snow covered) background. In this work an IR-based, statistical rainfall estimation technique is trained and applied over the Tibetan Plateau hydrological basin to retrive precipitation intensity at different spatial and temporal scales. The technique is based on a simple artificial neural network scheme trained with two supervised training sets assembled for monsoon season and for the rest of the year. For the monsoon season (estimated from June to September), the ground radar precipitation data for few case studies are used to build the training set: four days in summer 2009 are considered. For the rest of the year, CloudSat-CPR derived snowfall rate has been used as reference precipitation data, following the Kulie and Bennartz (2009) algorithm. METEOSAT-7 infrared channels radiance (at 6.7 and 11 micometers) and derived local variability features (such as local standard deviation and local average) are used as input and the actual rainrate is obtained as output for each satellite slot, every 30 minutes on the satellite grid. The satellite rainrate maps for three years (2008-2010) are computed and compared with available global precipitation products (such as C-MORPH and TMPA products) and with other techniques applied to the Plateau area: similarities and differences are

  16. Analysis of precipitation teleconnections in CMIP models as a measure of model fidelity in simulating precipitation

    Science.gov (United States)

    Langenbrunner, B.; Neelin, J.; Meyerson, J.

    2011-12-01

    The accurate representation of precipitation is a recurring issue in global climate models, especially in the tropics. Poor skill in modeling the variability and climate teleconnections associated with El Niño/Southern Oscillation (ENSO) also persisted in the latest Climate Model Intercomparison Project (CMIP) campaigns. Observed ENSO precipitation teleconnections provide a standard by which we can judge a given model's ability to reproduce precipitation and dynamic feedback processes originating in the tropical Pacific. Using CMIP3 Atmospheric Model Intercomparison Project (AMIP) runs as a baseline, we compare precipitation teleconnections between models and observations, and we evaluate these results against available CMIP5 historical and AMIP runs. Using AMIP simulations restricts evaluation to the atmospheric response, as sea surface temperatures (SSTs) in AMIP are prescribed by observations. We use a rank correlation between ENSO SST indices and precipitation to define teleconnections, since this method is robust to outliers and appropriate for non-Gaussian data. Spatial correlations of the modeled and observed teleconnections are then evaluated. We look at these correlations in regions of strong precipitation teleconnections, including equatorial S. America, the "horseshoe" region in the western tropical Pacific, and southern N. America. For each region and season, we create a "normalized projection" of a given model's teleconnection pattern onto that of the observations, a metric that assesses the quality of regional pattern simulations while rewarding signals of correct sign over the region. Comparing this to an area-averaged (i.e., more generous) metric suggests models do better when restrictions on exact spatial dependence are loosened and conservation constraints apply. Model fidelity in regional measures remains far from perfect, suggesting intrinsic issues with the models' regional sensitivities in moist processes.

  17. Characterization of precipitation features over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2013-12-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, surface observations, and models to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets of TMPA 3B42, CMORPH, and PERSIANN. The satellite based QPEs are compared over the concurrent period with the NCEP Stage IV product, which is a near real time product providing precipitation data at the hourly temporal scale gridded at a nominal 4-km spatial resolution. In addition, remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model), which provides gridded precipitation estimates that are used as a baseline for multi-sensor QPE products comparison. The comparisons are performed at the annual, seasonal, monthly, and daily scales with focus on selected river basins (Southeastern US, Pacific Northwest, Great Plains). While, unconditional annual rain rates present a satisfying agreement between all products, results suggest that satellite QPE datasets exhibit important biases in particular at higher rain rates (≥4 mm/day). Conversely, on seasonal scales differences between remotely sensed data and ground surface observations can be greater than 50% and up to 90% for low daily accumulation (≤1 mm/day) such as in the Western US (summer) and Central US (winter). The conditional analysis performed using different daily rainfall accumulation thresholds (from low rainfall intensity to intense precipitation) shows that while intense events measured at the ground are infrequent (around 2% for daily accumulation above 2 inches/day), remotely sensed products displayed differences from 20-50% and up to 90-100%. A discussion on the impact of differing spatial and temporal resolutions with respect to the datasets ability to capture extreme

  18. Pushing precipitation to the extremes in distributed experiments: Recommendations for simulating wet and dry years

    Science.gov (United States)

    Knapp, Alan K.; Avolio, Meghan L.; Beier, Claus; Carroll, Charles J.W.; Collins, Scott L.; Dukes, Jeffrey S.; Fraser, Lauchlan H.; Griffin-Nolan, Robert J.; Hoover, David L.; Jentsch, Anke; Loik, Michael E.; Phillips, Richard P.; Post, Alison K.; Sala, Osvaldo E.; Slette, Ingrid J.; Yahdjian, Laura; Smith, Melinda D.

    2017-01-01

    Intensification of the global hydrological cycle, ranging from larger individual precipitation events to more extreme multiyear droughts, has the potential to cause widespread alterations in ecosystem structure and function. With evidence that the incidence of extreme precipitation years (defined statistically from historical precipitation records) is increasing, there is a clear need to identify ecosystems that are most vulnerable to these changes and understand why some ecosystems are more sensitive to extremes than others. To date, opportunistic studies of naturally occurring extreme precipitation years, combined with results from a relatively small number of experiments, have provided limited mechanistic understanding of differences in ecosystem sensitivity, suggesting that new approaches are needed. Coordinated distributed experiments (CDEs) arrayed across multiple ecosystem types and focused on water can enhance our understanding of differential ecosystem sensitivity to precipitation extremes, but there are many design challenges to overcome (e.g., cost, comparability, standardization). Here, we evaluate contemporary experimental approaches for manipulating precipitation under field conditions to inform the design of ‘Drought-Net’, a relatively low-cost CDE that simulates extreme precipitation years. A common method for imposing both dry and wet years is to alter each ambient precipitation event. We endorse this approach for imposing extreme precipitation years because it simultaneously alters other precipitation characteristics (i.e., event size) consistent with natural precipitation patterns. However, we do not advocate applying identical treatment levels at all sites – a common approach to standardization in CDEs. This is because precipitation variability varies >fivefold globally resulting in a wide range of ecosystem-specific thresholds for defining extreme precipitation years. For CDEs focused on precipitation extremes, treatments should be based

  19. Global Historical Climatology Network - Monthly (GHCN-M), Version 3

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Please note, GHCN-Monthly provides climatological observations for four elements; monthly mean maximum temperature, minimum temperature, mean temperature, and...

  20. Seasonal and ENSO Influences on the Stable Isotopic Composition of Galápagos Precipitation

    Science.gov (United States)

    Martin, N. J.; Conroy, J. L.; Noone, D.; Cobb, K. M.; Konecky, B. L.; Rea, S.

    2018-01-01

    The origin of stable isotopic variability in precipitation over time and space is critical to the interpretation of stable isotope-based paleoclimate proxies. In the eastern equatorial Pacific, modern stable isotope measurements in precipitation (δ18Op and δDp) are sparse and largely unevaluated in the literature, although insights from such analyses would benefit the interpretations of several regional isotope-based paleoclimate records. Here we present a new 3.5 year record of daily-resolved δ18Op and δDp from Santa Cruz, Galápagos. With a prior 13 year record of monthly δ18Op and δDp from the island, these new data reveal controls on the stable isotopic composition of regional precipitation on event to interannual time scales. Overall, we find Galápagos δ18Op is significantly correlated with precipitation amount on daily and monthly time scales. The majority of Galápagos rain events are drizzle, or garúa, derived from local marine boundary layer vapor, with corresponding high δ18Op values due to the local source and increased evaporation and equilibration of smaller drops with boundary layer vapor. On monthly time scales, only precipitation in very strong, warm season El Niño months has substantially lower δ18Op values, as the sea surface temperature threshold for deep convection (28°C) is only surpassed at these times. The 2015/2016 El Niño event did not produce strong precipitation or δ18Op anomalies due to the short period of warm SST anomalies, which did not extend into the peak of the warm season. Eastern Pacific proxy isotope records may be biased toward periods of high rainfall during strong to very strong El Niño events.

  1. Forecasting Precipitation over the MENA Region: A Data Mining and Remote Sensing Based Approach

    Science.gov (United States)

    Elkadiri, R.; Sultan, M.; Elbayoumi, T.; Chouinard, K.

    2015-12-01

    We developed and applied an integrated approach to construct predictive tools with lead times of 1 to 12 months to forecast precipitation amounts over the Middle East and North Africa (MENA) region. The following steps were conducted: (1) acquire and analyze temporal remote sensing-based precipitation datasets (i.e. Tropical Rainfall Measuring Mission [TRMM]) over five main water source regions in the MENA area (i.e. Atlas Mountains in Morocco, Southern Sudan, Red Sea Hills of Yemen, and Blue Nile and White Nile source areas) throughout the investigation period (1998 to 2015), (2) acquire and extract monthly values for all of the climatic indices that are likely to influence the climatic patterns over the MENA region (e.g., Northern Atlantic Oscillation [NOI], Southern Oscillation Index [SOI], and Tropical North Atlantic Index [TNA]); and (3) apply data mining methods to extract relationships between the observed precipitation and the controlling factors (climatic indices) and use predictive tools to forecast monthly precipitation over each of the identified pilot study areas. Preliminary results indicate that by using the period from January 1998 until August 2012 for model training and the period from September 2012 to January 2015 for testing, precipitation can be successfully predicted with a three-months lead over South West Yemen, Atlas Mountains in Morocco, Southern Sudan, Blue Nile sources and White Nile sources with confidence (Pearson correlation coefficient: 0.911, 0.823, 0.807, 0.801 and 0.895 respectively). Future work will focus on applying this technique for prediction of precipitation over each of the climatically contiguous areas of the MENA region. If our efforts are successful, our findings will lead the way to the development and implementation of sound water management scenarios for the MENA countries.

  2. A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

    Science.gov (United States)

    Tao, W. K.

    2017-12-01

    In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

  3. Does GPM-based multi-satellite precipitation enhance rainfall estimates over Pakistan and Bolivia arid regions?

    Science.gov (United States)

    Hussain, Y.; Satgé, F.; Bonnet, M. P.; Pillco, R.; Molina, J.; Timouk, F.; Roig, H.; Martinez-Carvajal, H., Sr.; Gulraiz, A.

    2016-12-01

    Arid regions are sensitive to rainfall variations which are expressed in the form of flooding and droughts. Unfortunately, those regions are poorly monitored and high quality rainfall estimates are still needed. The Global Precipitation Measurement (GPM) mission released two new satellite rainfall products named Integrated Multisatellite Retrievals GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) bringing the possibility of accurate rainfall monitoring over these countries. This study assessed both products at monthly scale over Pakistan considering dry and wet season over the 4 main climatic zones from 2014 to 2016. With similar climatic conditions, the Altiplano region of Bolivia is considered to quantify the influence of big lakes (Titicaca and Poopó) in rainfall estimates. For comparison, the widely used TRMM-Multisatellite Precipitation Analysis 3B43 (TMPA-3B43) version 7 is also involved in the analysis to observe the potential enhancement in rainfall estimate brought by GPM products. Rainfall estimates derived from 110 rain-gauges are used as reference to compare IMERG, GSMaP-v6 and TMPA-3B43 at the 0.1° and 0.25° spatial resolution. Over both regions, IMERG and GSMaP-v6 capture the spatial pattern of precipitation as well as TMPA-3B43. All products tend to over estimates rainfall over very arid regions. This feature is even more marked during dry season. However, during this season, both reference and estimated rainfall remain very low and do not impact seasonal water budget computation. On a general way, IMERG slightly outperforms TMPA-3B43 and GSMaP-v6 which provides the less accurate rainfall estimate. The TMPA-3B43 rainfall underestimation previously found over Lake Titicaca is still observed in IMERG estimates. However, GSMaP-v6 considerably decreases the underestimation providing the most accurate rainfall estimate over the lake. MOD11C3 Land Surface Temperature (LST) and ASTER Global Emissivity Dataset reveal strong

  4. Modulation of precipitation by conditional symmetric instability release

    Science.gov (United States)

    Glinton, Michael R.; Gray, Suzanne L.; Chagnon, Jeffrey M.; Morcrette, Cyril J.

    2017-03-01

    Although many theoretical and observational studies have investigated the mechanism of conditional symmetric instability (CSI) release and associated it with mesoscale atmospheric phenomena such as frontal precipitation bands, cloud heads in rapidly developing extratropical cyclones and sting jets, its climatology and contribution to precipitation have not been extensively documented. The aim of this paper is to quantify the contribution of CSI release, yielding slantwise convection, to climatological precipitation accumulations for the North Atlantic and western Europe. Case studies reveal that CSI release could be common along cold fronts of mature extratropical cyclones and the North Atlantic storm track is found to be a region with large CSI according to two independent CSI metrics. Correlations of CSI with accumulated precipitation are also large in this region and CSI release is inferred to be occurring about 20% of the total time over depths of over 1 km. We conclude that the inability of current global weather forecast and climate prediction models to represent CSI release (due to insufficient resolution yet lack of subgrid parametrization schemes) may lead to errors in precipitation distributions, particularly in the region of the North Atlantic storm track.

  5. Generation of a stochastic precipitation model for the tropical climate

    Science.gov (United States)

    Ng, Jing Lin; Abd Aziz, Samsuzana; Huang, Yuk Feng; Wayayok, Aimrun; Rowshon, MK

    2017-06-01

    A tropical country like Malaysia is characterized by intense localized precipitation with temperatures remaining relatively constant throughout the year. A stochastic modeling of precipitation in the flood-prone Kelantan River Basin is particularly challenging due to the high intermittency of precipitation events of the northeast monsoons. There is an urgent need to have long series of precipitation in modeling the hydrological responses. A single-site stochastic precipitation model that includes precipitation occurrence and an intensity model was developed, calibrated, and validated for the Kelantan River Basin. The simulation process was carried out separately for each station without considering the spatial correlation of precipitation. The Markov chains up to the fifth-order and six distributions were considered. The daily precipitation data of 17 rainfall stations for the study period of 1954-2013 were selected. The results suggested that second- and third-order Markov chains were suitable for simulating monthly and yearly precipitation occurrences, respectively. The fifth-order Markov chain resulted in overestimation of precipitation occurrences. For the mean, distribution, and standard deviation of precipitation amounts, the exponential, gamma, log-normal, skew normal, mixed exponential, and generalized Pareto distributions performed superiorly. However, for the extremes of precipitation, the exponential and log-normal distributions were better while the skew normal and generalized Pareto distributions tend to show underestimations. The log-normal distribution was chosen as the best distribution to simulate precipitation amounts. Overall, the stochastic precipitation model developed is considered a convenient tool to simulate the characteristics of precipitation in the Kelantan River Basin.

  6. Assessment of Observational Uncertainty in Extreme Precipitation Events over the Continental United States

    Science.gov (United States)

    Slinskey, E. A.; Loikith, P. C.; Waliser, D. E.; Goodman, A.

    2017-12-01

    Extreme precipitation events are associated with numerous societal and environmental impacts. Furthermore, anthropogenic climate change is projected to alter precipitation intensity across portions of the Continental United States (CONUS). Therefore, a spatial understanding and intuitive means of monitoring extreme precipitation over time is critical. Towards this end, we apply an event-based indicator, developed as a part of NASA's support of the ongoing efforts of the US National Climate Assessment, which assigns categories to extreme precipitation events based on 3-day storm totals as a basis for dataset intercomparison. To assess observational uncertainty across a wide range of historical precipitation measurement approaches, we intercompare in situ station data from the Global Historical Climatology Network (GHCN), satellite-derived precipitation data from NASA's Tropical Rainfall Measuring Mission (TRMM), gridded in situ station data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM), global reanalysis from NASA's Modern Era Retrospective-Analysis version 2 (MERRA 2), and regional reanalysis with gauge data assimilation from NCEP's North American Regional Reanalysis (NARR). Results suggest considerable variability across the five-dataset suite in the frequency, spatial extent, and magnitude of extreme precipitation events. Consistent with expectations, higher resolution datasets were found to resemble station data best and capture a greater frequency of high-end extreme events relative to lower spatial resolution datasets. The degree of dataset agreement varies regionally, however all datasets successfully capture the seasonal cycle of precipitation extremes across the CONUS. These intercomparison results provide additional insight about observational uncertainty and the ability of a range of precipitation measurement and analysis products to capture extreme precipitation event climatology. While the event category threshold is fixed

  7. Evaluation of Real-Time Convection-Permitting Precipitation Forecasts in China During the 2013-2014 Summer Season

    Science.gov (United States)

    Zhu, Kefeng; Xue, Ming; Zhou, Bowen; Zhao, Kun; Sun, Zhengqi; Fu, Peiling; Zheng, Yongguang; Zhang, Xiaoling; Meng, Qingtao

    2018-01-01

    Forecasts at a 4 km convection-permitting resolution over China during the summer season have been produced with the Weather Research and Forecasting model at Nanjing University since 2013. Precipitation forecasts from 2013 to 2014 are evaluated with dense rain gauge observations and compared with operational global model forecasts. Overall, the 4 km forecasts show very good agreement with observations over most parts of China, outperforming global forecasts in terms of spatial distribution, intensity, and diurnal variation. Quantitative evaluations with the Gilbert skill score further confirm the better performance of the 4 km forecasts over global forecasts for heavy precipitation, especially for the thresholds of 100 and 150 mm d-1. Besides bulk characteristics, the representations of some unique features of summer precipitation in China under the influence of the East Asian summer monsoon are further evaluated. These include the northward progression and southward retreat of the main rainband through the summer season, the diurnal variations of precipitation, and the meridional and zonal propagation of precipitation episodes associated with background synoptic flow and the embedded mesoscale convective systems. The 4 km forecast is able to faithfully reproduce most of the features while overprediction of afternoon convection near the southern China coast is found to be a main deficiency that requires further investigations.

  8. Global Climatic Indices Influence on Rainfall Spatiotemporal Distribution : A Case Study from Morocco

    Science.gov (United States)

    Elkadiri, R.; Zemzami, M.; Phillips, J.

    2017-12-01

    The climate of Morocco is affected by the Mediterranean Sea, the Atlantic Ocean the Sahara and the Atlas mountains, creating a highly variable spatial and temporal distribution. In this study, we aim to decompose the rainfall in Morocco into global and local signals and understand the contribution of the climatic indices (CIs) on rainfall. These analyses will contribute in understanding the Moroccan climate that is typical of other Mediterranean and North African climatic zones. In addition, it will contribute in a long-term prediction of climate. The constructed database ranges from 1950 to 2013 and consists of monthly data from 147 rainfall stations and 37 CIs data provided mostly by the NOAA Climate Prediction Center. The next general steps were followed: (1) the study area was divided into 9 homogenous climatic regions and weighted precipitation was calculated for each region to reduce the local effects. (2) Each CI was decomposed into nine components of different frequencies (D1 to D9) using wavelet multiresolution analysis. The four lowest frequencies of each CI were selected. (3) Each of the original and resulting signals were shifted from one to six months to account for the effect of the global patterns. The application of steps two and three resulted in the creation of 1225 variables from the original 37 CIs. (4) The final 1225 variables were used to identify links between the global and regional CIs and precipitation in each of the nine homogenous regions using stepwise regression and decision tree. The preliminary analyses and results were focused on the north Atlantic zone and have shown that the North Atlantic Oscillation (PC-based) from NCAR (NAOPC), the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the Western Mediterranean Oscillation (WMO) and the Extreme Eastern Tropical Pacific Sea Surface Temperature (NINO12) have the highest correlation with rainfall (33%, 30%, 27%, 21% and -20%, respectively). In addition the 4-months lagged

  9. The full annual carbon balance of a subtropical coniferous plantation is highly sensitive to autumn precipitation.

    Science.gov (United States)

    Xu, Mingjie; Wang, Huimin; Wen, Xuefa; Zhang, Tao; Di, Yuebao; Wang, Yidong; Wang, Jianlei; Cheng, Chuanpeng; Zhang, Wenjiang

    2017-08-30

    Deep understanding of the effects of precipitation on carbon budgets is essential to assess the carbon balance accurately and can help predict potential variation within the global change context. Therefore, we addressed this issue by analyzing twelve years (2003-2014) of observations of carbon fluxes and their corresponding temperature and precipitation data in a subtropical coniferous plantation at the Qianyanzhou (QYZ) site, southern China. During the observation years, this coniferous ecosystem experienced four cold springs whose effects on the carbon budgets were relatively clear based on previous studies. To unravel the effects of temperature and precipitation, the effects of autumn precipitation were examined by grouping the data into two pools based on whether the years experienced cold springs. The results indicated that precipitation in autumn can accelerate the gross primary productivity (GPP) of the following year. Meanwhile, divergent effects of precipitation on ecosystem respiration (Re) were found. Autumn precipitation was found to enhance Re in normal years but the same regulation was not found in the cold-spring years. These results suggested that for long-term predictions of carbon balance in global climate change projections, the effects of precipitation must be considered to better constrain the uncertainties associated with the estimation.

  10. Global Historical Climatology Network - Monthly Temperature, Version 4 (BETA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Only available as BETA release. The GHCN-Monthly Temperature Version 4 dataset consists of monthly mean temperature - both raw and bias corrected data. A full...

  11. Seasonality of runoff and precipitation regimes along transects in Peru and Austria

    OpenAIRE

    Gaudry Maria M. Cárdenas; Gutknecht Dieter; Parajka Juraj; Perdigão Rui A.P.; Blöschl Günter

    2017-01-01

    The aim of this study is to understand the seasonalities of runoff and precipitation and their controls along two transects in Peru and one transect in Austria. The analysis is based on daily precipitation data at 111 and 61 stations in Peru and Austria, respectively, and daily discharge data at 51 and 110 stations. The maximum Pardé coefficient is used to quantify the strength of the seasonalities of monthly precipitation and runoff. Circular statistics are used to quantify the seasonalities...

  12. Future changes of precipitation characteristics in China

    Science.gov (United States)

    Wu, S.; Wu, Y.; Wen, J.

    2017-12-01

    Global warming has the potential to alter the hydrological cycle, with significant impacts on the human society, the environment and ecosystems. This study provides a detailed assessment of potential changes in precipitation characteristics in China using a suite of 12 high-resolution CMIP5 climate models under a medium and a high Representative Concentration Pathways: RCP4.5 and RCP8.5. We examine future changes over the entire distribution of precipitation, and identify any shift in the shape and/or scale of the distribution. In addition, we use extreme-value theory to evaluate the change in probability and magnitude for extreme precipitation events. Overall, China is going to experience an increase in total precipitation (by 8% under RCP4.5 and 12% under RCP8.5). This increase is uneven spatially, with more increase in the west and less increase in the east. Precipitation frequency is projected to increase in the west and decrease in the east. Under RCP4.5, the overall precipitation frequency for the entire China remains largely unchanged (0.08%). However, RCP8.5 projects a more significant decrease in frequency for large part of China, resulting in an overall decrease of 2.08%. Precipitation intensity is likely increase more uniformly, with an overall increase of 11% for RCP4.5 and 19% for RCP8.5. Precipitation increases for all parts of the distribution, but the increase is more for higher quantiles, i.e. strong events. The relative contribution of small quantiles is likely to decrease, whereas contribution from heavy events is likely to increase. Extreme precipitation increase at much higher rates than average precipitation, and high rates of increase are expected for more extreme events. 1-year events are likely to increase by 15%, but 20-year events are going to increase by 21% under RCP4.5, 26% and 40% respectively under RCP8.5. The increase of extreme events is likely to be more spatially uniform.

  13. Precipitation in a warming world: Assessing projected hydro-climate changes in California and other Mediterranean climate regions.

    Science.gov (United States)

    Polade, Suraj D; Gershunov, Alexander; Cayan, Daniel R; Dettinger, Michael D; Pierce, David W

    2017-09-07

    In most Mediterranean climate (MedClim) regions around the world, global climate models (GCMs) consistently project drier futures. In California, however, projections of changes in annual precipitation are inconsistent. Analysis of daily precipitation in 30 GCMs reveals patterns in projected hydrometeorology over each of the five MedClm regions globally and helps disentangle their causes. MedClim regions, except California, are expected to dry via decreased frequency of winter precipitation. Frequencies of extreme precipitation, however, are projected to increase over the two MedClim regions of the Northern Hemisphere where projected warming is strongest. The increase in heavy and extreme precipitation is particularly robust over California, where it is only partially offset by projected decreases in low-medium intensity precipitation. Over the Mediterranean Basin, however, losses from decreasing frequency of low-medium-intensity precipitation are projected to dominate gains from intensifying projected extreme precipitation. MedClim regions are projected to become more sub-tropical, i.e. made dryer via pole-ward expanding subtropical subsidence. California's more nuanced hydrological future reflects a precarious balance between the expanding subtropical high from the south and the south-eastward extending Aleutian low from the north-west. These dynamical mechanisms and thermodynamic moistening of the warming atmosphere result in increased horizontal water vapor transport, bolstering extreme precipitation events.

  14. TEMPERATURE AND PRECIPITATION CHANGES IN TÂRGU-MURES (ROMANIA FROM PERIOD 1951-2010

    Directory of Open Access Journals (Sweden)

    O.Rusz

    2012-03-01

    Full Text Available Temperature and precipitation changes in Târgu Mures (Romania from period 1951-2010. The analysis was made based upon meteorological data collected at Târgu Mures meteorological station (Romania, Mures county, lat. 46°32’N, lon. 24°32’E, elevation 308 m, between 1951 and 2010. Several climatic parameters were studied (for instance, annual and monthly mean temperature, maximum precipitation in 24 hours, number of summer days, etc. Detected inhomogeneities are not related to instrumental causes or geographical relocation. Positive and statistical significant trends (Mann-Kendall test are indicated for: mean annual temperatures, mean temperatures of warm months, average of the maximum and minimum temperatures (annual and warm months data, number of days with mean temperature between 20.1-25.0 °C, number of days with precipitation ≥0 mm, and for all parameters of precipitation of September. The sequential version of Mann-Kendall test show a beginning of a trend in 1956 in the case of mean temperature (at same, the two and three parts regression denote this year like a moment of change, years 1965 and 1992 in the case of annual amount of precipitation. CUSUM charts indicate occurs of changes points at 1988, 2005, 2009 (mean temperature respectively at 1989, 2004 (precipitation, and at 1968, 1992 (daily temperature range. Tendencies of overlapped time series reveal a more important increase at the end of period (mainly for mean temperature. The analysis with RClimDex show for 5 extreme climate indices a significant trend: positive for summer days, warm nights, warm spell duration indicator and negative for cold nights and cold days.

  15. Long-Term Precipitation Analysis and Estimation of Precipitation Concentration Index Using Three Support Vector Machine Methods

    Directory of Open Access Journals (Sweden)

    Milan Gocic

    2016-01-01

    Full Text Available The monthly precipitation data from 29 stations in Serbia during the period of 1946–2012 were considered. Precipitation trends were calculated using linear regression method. Three CLINO periods (1961–1990, 1971–2000, and 1981–2010 in three subregions were analysed. The CLINO 1981–2010 period had a significant increasing trend. Spatial pattern of the precipitation concentration index (PCI was presented. For the purpose of PCI prediction, three Support Vector Machine (SVM models, namely, SVM coupled with the discrete wavelet transform (SVM-Wavelet, the firefly algorithm (SVM-FFA, and using the radial basis function (SVM-RBF, were developed and used. The estimation and prediction results of these models were compared with each other using three statistical indicators, that is, root mean square error, coefficient of determination, and coefficient of efficiency. The experimental results showed that an improvement in predictive accuracy and capability of generalization can be achieved by the SVM-Wavelet approach. Moreover, the results indicated the proposed SVM-Wavelet model can adequately predict the PCI.

  16. Global water cycle

    Science.gov (United States)

    Robertson, Franklin; Goodman, Steven J.; Christy, John R.; Fitzjarrald, Daniel E.; Chou, Shi-Hung; Crosson, William; Wang, Shouping; Ramirez, Jorge

    1993-01-01

    This research is the MSFC component of a joint MSFC/Pennsylvania State University Eos Interdisciplinary Investigation on the global water cycle extension across the earth sciences. The primary long-term objective of this investigation is to determine the scope and interactions of the global water cycle with all components of the Earth system and to understand how it stimulates and regulates change on both global and regional scales. Significant accomplishments in the past year are presented and include the following: (1) water vapor variability; (2) multi-phase water analysis; (3) global modeling; and (4) optimal precipitation and stream flow analysis and hydrologic processes.

  17. Investigation on the Patterns of Global Vegetation Change Using a Satellite-Sensed Vegetation Index

    Directory of Open Access Journals (Sweden)

    Ainong Li

    2010-06-01

    Full Text Available The pattern of vegetation change in response to global change still remains a controversial issue. A Normalized Difference Vegetation Index (NDVI dataset compiled by the Global Inventory Modeling and Mapping Studies (GIMMS was used for analysis. For the period 1982–2006, GIMMS-NDVI analysis indicated that monthly NDVI changes show homogenous trends in middle and high latitude areas in the northern hemisphere and within, or near, the Tropic of Cancer and Capricorn; with obvious spatio-temporal heterogeneity on a global scale over the past two decades. The former areas featured increasing vegetation activity during growth seasons, and the latter areas experienced an even greater amplitude in places where precipitation is adequate. The discussion suggests that one should be cautious of using the NDVI time-series to analyze local vegetation dynamics because of its coarse resolution and uncertainties.

  18. Temporal and spatial variability of global water balance

    Science.gov (United States)

    McCabe, Gregory J.; Wolock, David M.

    2013-01-01

    An analysis of simulated global water-balance components (precipitation [P], actual evapotranspiration [AET], runoff [R], and potential evapotranspiration [PET]) for the past century indicates that P has been the primary driver of variability in R. Additionally, since about 2000, there have been increases in P, AET, R, and PET for most of the globe. The increases in R during 2000 through 2009 have occurred despite unprecedented increases in PET. The increases in R are the result of substantial increases in P during the cool Northern Hemisphere months (i.e. October through March) when PET increases were relatively small; the largest PET increases occurred during the warm Northern Hemisphere months (April through September). Additionally, for the 2000 through 2009 period, the latitudinal distribution of P departures appears to co-vary with the mean P departures from 16 climate model projections of the latitudinal response of P to warming, except in the high latitudes. Finally, changes in water-balance variables appear large from the perspective of departures from the long-term means. However, when put into the context of the magnitudes of the raw water balance variable values, there appears to have been little change in any of the water-balance variables over the past century on a global or hemispheric scale.

  19. Monthly Climate Data for Selected USGS HCDN Sites, 1951-1990

    Data.gov (United States)

    National Aeronautics and Space Administration — Time series of monthly minimum and maximum temperature, precipitation and potential evapotranspiration were derived for 1337 watersheds in the conterminous United...

  20. Monthly Climate Data for Selected USGS HCDN Sites, 1951-1990

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: Time series of monthly minimum and maximum temperature, precipitation and potential evapotranspiration were derived for 1337 watersheds in the conterminous...

  1. Advances in Understanding the Role of Frozen Precipitation in High Latitude Hydrology

    Science.gov (United States)

    L'Ecuyer, T. S.; Wood, N.; Smalley, M.; McIlhattan, E.; Kulie, M.

    2017-12-01

    Satellite-based millimeter wavelength radar observations provide a unique perspective on the global character of frozen precipitation that has been difficult to detect using conventional spaceborne precipitation sensors. This presentation will describe the methodology underpinning the ten-year CloudSat global snowfall product and discuss the results of a number of complementary approaches that have been adopted to quantify its uncertainties. These datasets are shedding new light on the distribution, character, and impacts of frozen precipitation on high latitude hydrology. Inferred regional snowfall accumulations, for example, provide valuable constraints on projected changes in precipitation and mass balance on the Antarctic ice sheet in climate models. When placed in the broader context of complementary observations from other A-Train sensors, instantaneous snowfall estimates also hint at the large-scale processes that influence snow formation including air-sea interactions associated with cold-air outbreaks, lake-effect snows, and orographic enhancement. Simultaneous CloudSat and CALIPSO observations further emphasize the important role snowfall plays in the lifetime of super-cooled liquid containing clouds in the Arctic and highlight a model deficiency with important implications for surface energy and mass balance on the Greenland ice sheet.

  2. Retrieval of precipitable water using near infrared channels of Global Imager/Advanced Earth Observing Satellite-II (GLI/ADEOS-II)

    International Nuclear Information System (INIS)

    Kuji, M.; Uchiyama, A.

    2002-01-01

    Retrieval of precipitable water (vertically integrated water vapor amount) is proposed using near infrared channels og Global Imager onboard Advanced Earth Observing Satellite-II (GLI/ADEOS-II). The principle of retrieval algorithm is based upon that adopted with Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Earth Observing System (EOS) satellite series. Simulations were carried out with GLI Signal Simulator (GSS) to calculate the radiance ratio between water vapor absorbing bands and non-absorbing bands. As a result, it is found that for the case of high spectral reflectance background (a bright target) such as the land surface, the calibration curves are sensitive to the precipitable water variation. For the case of low albedo background (a dark target) such as the ocean surface, on the contrary, the calibration curve is not very sensitive to its variation under conditions of the large water vapor amount. It turns out that aerosol loading has little influence on the retrieval over a bright target for the aerosol optical thickness less than about 1.0 at 500nm. It is also anticipated that simultaneous retrieval of the water vapor amount using GLI data along with other channels will lead to improved accuracy of the determination of surface geophysical properties, such as vegetation, ocean color, and snow and ice, through the better atmospheric correction

  3. Anticipated Improvements in Precipitation Physics and Understanding of Water Cycle from GPM Mission

    Science.gov (United States)

    Smith, Eric A.

    2003-01-01

    The GPM mission is currently planned for start in the late-2007 to early-2008 time frame. Its main scientific goal is to help answer pressing scientific problems arising within the context of global and regional water cycles. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood/draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like core satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe -- continuously. The constellation s orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. GPM is organized internationally, involving existing, pending, projected, and under-study partnerships which will link NASA and NOAA in the US, NASDA in Japan, ESA in Europe, ISRO in India, CNES in France, and possibly AS1 in Italy, KARI in South Korea, CSA in Canada, and AEB in Brazil. Additionally, the program is actively pursuing agreements with other international collaborators and

  4. Evaluation of the Performance of Three Satellite Precipitation Products over Africa

    Directory of Open Access Journals (Sweden)

    Aleix Serrat-Capdevila

    2016-10-01

    Full Text Available We present an evaluation of daily estimates from three near real-time quasi-global Satellite Precipitation Products—Tropical Rainfall Measuring Mission (TRMM Multi-satellite Precipitation Analysis (TMPA, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, and Climate Prediction Center (CPC Morphing Technique (CMORPH—over the African continent, using the Global Precipitation Climatology Project one Degree Day (GPCP-1dd as a reference dataset for years 2001 to 2013. Different types of errors are characterized for each season as a function of spatial classifications (latitudinal bands, climatic zones and topography and in relationship with the main rain-producing mechanisms in the continent: the Intertropical Convergence Zone (ITCZ and the East African Monsoon. A bias correction of the satellite estimates is applied using a probability density function (pdf matching approach, with a bias analysis as a function of rain intensity, season and latitude. The effects of bias correction on different error terms are analyzed, showing an almost elimination of the mean and variance terms in most of the cases. While raw estimates of TMPA show higher efficiency, all products have similar efficiencies after bias correction. PERSIANN consistently shows the smallest median errors when it correctly detects precipitation events. The areas with smallest relative errors and other performance measures follow the position of the ITCZ oscillating seasonally over the equator, illustrating the close relationship between satellite estimates and rainfall regime.

  5. Intensification of extreme European summer precipitation in a warmer climate

    DEFF Research Database (Denmark)

    Christensen, O. B.; Christensen, J. H.

    2004-01-01

    Heavy and/or extended precipitation episodes with subsequent surface runoff can inflict catastrophic property damage and loss of human life. Thus, it is important to determine how the character of such events could change in response to greenhouse gas-induced global warming. Impacts of climate...... warming on severe precipitation events in Europe on a diurnal time scale were investigated with a high-resolution regional climate model for two of the greenhouse gas emission scenarios constructed by the Intergovernmental Panel on Climate Change (IPCC; Nakicenovic, N., et al., 2000, IPCC special report...... models both originating from fully transient climate change simulations. Here, we show that although the summer time precipitation decreases over a substantial part of Europe in the scenarios analysed, an increase in the amount of precipitation exceeding the present-day 99th and in most cases even the 95...

  6. Global Drought Monitoring and Forecasting based on Satellite Data and Land Surface Modeling

    Science.gov (United States)

    Sheffield, J.; Lobell, D. B.; Wood, E. F.

    2010-12-01

    objective quantification and tracking of their spatial-temporal characteristics. Further we present strategies for merging various sources of information, including bias correction of satellite precipitation and assimilation of remotely sensed soil moisture, which can augment the monitoring in regions where satellite precipitation is most uncertain. Ongoing work is adding a drought forecast component based on a successful implementation over the U.S. and agricultural productivity estimates based on output from crop yield models. The forecast component uses seasonal global climate forecasts from the NCEP Climate Forecast System (CFS). These are merged with observed climatology in a Bayesian framework to produce ensemble atmospheric forcings that better capture the uncertainties. At the same time, the system bias corrects and downscales the monthly CFS data. We show some initial seasonal (up to 6-month lead) hydrologic forecast results for the African system. Agricultural monitoring is based on the precipitation, temperature and soil moisture from the system to force statistical and process based crop yield models. We demonstrate the feasibility of monitoring major crop types across the world and show a strategy for providing predictions of yields within our drought forecast mode.

  7. Long-Term Precipitation Isotope Ratios (δ18O, δ2H, d-excess) in the Northeast US Reflect Atlantic Ocean Warming and Shifts in Moisture Sources

    Science.gov (United States)

    Puntsag, T.; Welker, J. M.; Mitchell, M. J.; Klein, E. S.; Campbell, J. L.; Likens, G.

    2014-12-01

    The global water cycle is exhibiting dramatic changes as global temperatures increase resulting in increases in: drought extremes, flooding, alterations in storm track patterns with protracted winter storms, and greater precipitation variability. The mechanisms driving these changes can be difficult to assess, but the spatial and temporal patterns of precipitation water isotopes (δ18O, δ2H, d-excess) provide a means to help understand these water cycle changes. However, extended temporal records of isotope ratios in precipitation are infrequent, especially in the US. In our study we analyzed precipitation isotope ratio data from the Hubbard Brook Experimental Forest in New Hampshire that has the longest US precipitation isotope record, to determine: 1) the monthly composited averages and trends from 1967 to 2012 (45 years); ; 2) the relationships between abiotic properties such as local temperatures, precipitation type, storm tracks and isotope ratio changes; and 3) the influence of regional shifts in moisture sources and/or changes in N Atlantic Ocean water conditions on isotope values. The seasonal variability of Hubbard Brook precipitation isotope ratios is consistent with other studies, as average δ18O values are ~ -15‰ in January and ~ -5 ‰ in July. However, over the 45 year record there is a depletion trend in the δ 18O values (becoming isotopically lighter with a greater proportion of 16O), which coupled with less change in δ 2H leads to increases in d-excess values from ~ -10‰ around 1970 to greater than 10‰ in 2009. These changes occurred during a period of warming as opposed to cooling local temperatures indicating other processes besides temperature are controlling long-term water isotope traits in this region. We have evidence that these changes in precipitation isotope traits are controlled in large part by an increases in moisture being sourced from a warming N Atlantic Ocean that is providing evaporated, isotopically

  8. High-resolution precipitation database for the last two centuries in Italy: climatologies and anomalies

    Science.gov (United States)

    Crespi, Alice; Brunetti, Michele; Maugeri, Maurizio

    2017-04-01

    The availability of gridded high-resolution spatial climatologies and corresponding secular records has acquired an increasing importance in the recent years both to research purposes and as decision-support tools in the management of natural resources and economical activities. High-resolution monthly precipitation climatologies for Italy were computed by gridding on a 30-arc-second-resolution Digital Elevation Model (DEM) the precipitation normals (1961-1990) obtained from a quality-controlled dataset of about 6200 stations covering the Italian surface and part of the Northern neighbouring regions. Starting from the assumption that the precipitation distribution is strongly influenced by orography, especially elevation, a local weighted linear regression (LWLR) of precipitation versus elevation was performed at each DEM cell. The regression coefficients for each cell were estimated by selecting the stations with the highest weights in which the distances and the level of similarity between the station cells and the considered grid cell, in terms of orographic features, are taken into account. An optimisation procedure was then set up in order to define, for each month and for each grid cell, the most suitable decreasing coefficients for the weighting factors which enter in the LWLR scheme. The model was validated by the comparison with the results provided by inverse distance weighting (IDW) applied both to station normals and to the residuals of a global regression of station normals versus elevation. In both cases, the LWLR leave-one-out reconstructions show the best agreement with the observed station normals, especially when considering specific station clusters (high elevation sites for example). After producing the high-resolution precipitation climatological field, the temporal component on the high-resolution grid was obtained by following the anomaly method. It is based on the assumption that the spatio-temporal structure of the signal of a

  9. Modes of winter precipitation variability in the North Atlantic

    Energy Technology Data Exchange (ETDEWEB)

    Zorita, E. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Hydrophysik; Saenz, J.; Fernandez, J.; Zubillaga, J. [Bilbao Univ. (Spain)

    2001-07-01

    The modes of variability of winter precipitation in the North Atlantic sector are identified by Empirical Orthogonal Functions Analysis in the NCEP/NCAR global reanalysis data sets. These modes are also present in a gridded precipitation data set over the Western Europe. The large-scale fields of atmospheric seasonal mean circulation, baroclinic activity, evaporation and humidity transport that are connected to the rainfall modes have been also analyzed in order to investigate the physical mechanisms that are causally linked to the rainfall modes. The results indicate that the leading rainfall mode is associated to the North Atlantic oscillation and represents a meridional redistribution of precipitation in the North Atlantic through displacements of the storm tracks. The second mode is related to evaporation anomalies in the Eastern Atlantic that precipitate almost entirely in the Western Atlantic. The third mode seems to be associated to meridional transport of water vapor from the Tropical Atlantic. (orig.)

  10. An aftereffect of global warming on tropical Pacific decadal variability

    Science.gov (United States)

    Zheng, Jian; Liu, Qinyu; Wang, Chuanyang

    2018-03-01

    Studies have shown that global warming over the past six decades can weaken the tropical Pacific Walker circulation and maintain the positive phase of the Interdecadal Pacific Oscillation (IPO). Based on observations and model simulations, another aftereffect of global warming on IPO is found. After removing linear trends (global warming signals) from observations, however, the tropical Pacific climate still exhibited some obvious differences between two IPO negative phases. The boreal winter (DJF) equatorial central-eastern Pacific sea surface temperature (SST) was colder during the 1999-2014 period (P2) than that during 1961-1976 (P1). This difference may have been a result of global warming nonlinear modulation of precipitation; i.e., in the climatological rainy region, the core area of the tropical Indo-western Pacific warm pool receives more precipitation through the "wet-get-wetter" mechanism. Positive precipitation anomalies in the warm pool during P2 are much stronger than those during P1, even after subtracting the linear trend. Corresponding to the differences of precipitation, the Pacific Walker circulation is stronger in P2 than in P1. Consequent easterly winds over the equatorial Pacific led to a colder equatorial eastern-central Pacific during P2. Therefore, tropical Pacific climate differences between the two negative IPO phases are aftereffects of global warming. These aftereffects are supported by the results of coupled climate model experiments, with and without global warming.

  11. Factors controlling stable isotope composition of European precipitation

    International Nuclear Information System (INIS)

    Rozanski, K.; Sonntag, C.; Muennich, K.O.

    1982-01-01

    The seasonal and spatial variations of stable isotope ratios in present day European precipitation are simulated with a simple multibox model of the mean west-east horizontal transport of the atmospheric water vapour across the European continent. Isotope fractionation during the formation of precipitation leads to an increasing depletion of heavy isotopes in the residual air moisture as it moves towards the centre of the continent. This isotopic depletion is partly compensated, particularly in summer, by evapotranspiration, which is assumed to transfer soil water into the atmosphere without isotope fractionation. The model estimates are based on horizontal water vapour flux data, varying seasonally between 88 and 130 kg m -1 s -1 for the Atlantic coast region, and on the monthly precipitation, evapotranspiration and surface air temperature data available for various locations in Europe. Both continental and seasonal temperature effects observed in the stable isotope composition of European precipitation are fairly well reproduced by the model. The calculations show that the isotopic composition of local precipitation is primarily controlled by regional scale processes, i.e. by the water vapour transport patterns into the continent, and by the average precipitation-evapotranspiration history of the air masses precipitating at a given place. Local parameters such as the surface and/or cloud base temperature or the amount of precipitation modify the isotope ratios only slightly. Implications of the model predictions for the interpretation of stable isotope ratios in earlier periods as they are preserved in ice cores and in groundwater are also discussed. (Auth.)

  12. Missing data analysis and homogeneity test for Turkish precipitation ...

    Indian Academy of Sciences (India)

    the monthly and annual total precipitation records at stations operated by Turkish ... used in regional studies; the number of stations representing the area and the quality of the data are also very ..... Water Resources Management 22: 823–841.

  13. Effects on Storm-Water Management for Three Major US Cities Using Location Specific Extreme Precipitation Dynamical Downscaling

    Science.gov (United States)

    Pelle, A.; Allen, M.; Fu, J. S.

    2013-12-01

    With rising population and increasing urban density, it is of pivotal importance for urban planners to plan for increasing extreme precipitation events. Climate models indicate that an increase in global mean temperature will lead to increased frequency and intensity of storms of a variety of types. Analysis of results from the Coupled Model Intercomparison Project, Phase 5 (CMIP5) has demonstrated that global climate models severely underestimate precipitation, however. Preliminary results from dynamical downscaling indicate that Philadelphia, Pennsylvania is expected to experience the greatest increase of precipitation due to an increase in annual extreme events in the US. New York City, New York and Chicago, Illinois are anticipated to have similarly large increases in annual extreme precipitation events. In order to produce more accurate results, we downscale Philadelphia, Chicago, and New York City using the Weather Research and Forecasting model (WRF). We analyze historical precipitation data and WRF output utilizing a Log Pearson Type III (LP3) distribution for frequency of extreme precipitation events. This study aims to determine the likelihood of extreme precipitation in future years and its effect on the of cost of stormwater management for these three cities.

  14. Using Climate Regionalization to Understand Climate Forecast System Version 2 (CFSv2) Precipitation Performance for the Conterminous United States (CONUS)

    Science.gov (United States)

    Regonda, Satish K.; Zaitchik, Benjamin F.; Badr, Hamada S.; Rodell, Matthew

    2016-01-01

    Dynamically based seasonal forecasts are prone to systematic spatial biases due to imperfections in the underlying global climate model (GCM). This can result in low-forecast skill when the GCM misplaces teleconnections or fails to resolve geographic barriers, even if the prediction of large-scale dynamics is accurate. To characterize and address this issue, this study applies objective climate regionalization to identify discrepancies between the Climate Forecast SystemVersion 2 (CFSv2) and precipitation observations across the Contiguous United States (CONUS). Regionalization shows that CFSv2 1 month forecasts capture the general spatial character of warm season precipitation variability but that forecast regions systematically differ from observation in some transition zones. CFSv2 predictive skill for these misclassified areas is systematically reduced relative to correctly regionalized areas and CONUS as a whole. In these incorrectly regionalized areas, higher skill can be obtained by using a regional-scale forecast in place of the local grid cell prediction.

  15. Mid-latitude afforestation shifts general circulation and tropical precipitation.

    Science.gov (United States)

    Swann, Abigail L S; Fung, Inez Y; Chiang, John C H

    2012-01-17

    We show in climate model experiments that large-scale afforestation in northern mid-latitudes warms the Northern Hemisphere and alters global circulation patterns. An expansion of dark forests increases the absorption of solar energy and increases surface temperature, particularly in regions where the land surface is unable to compensate with latent heat flux due to water limitation. Atmospheric circulation redistributes the anomalous energy absorbed in the northern hemisphere, in particular toward the south, through altering the Hadley circulation, resulting in the northward displacement of the tropical rain bands. Precipitation decreases over parts of the Amazon basin affecting productivity and increases over the Sahel and Sahara regions in Africa. We find that the response of climate to afforestation in mid-latitudes is determined by the amount of soil moisture available to plants with the greatest warming found in water-limited regions. Mid-latitude afforestation is found to have a small impact on modeled global temperatures and on global CO(2), but regional heating from the increase in forest cover is capable of driving unintended changes in circulation and precipitation. The ability of vegetation to affect remote circulation has implications for strategies for climate mitigation.

  16. Comparing the Palmer Drought Index and the Standardized Precipitation Index for Zagreb-Gric Observatory

    Science.gov (United States)

    Pandzic, Kreso

    2016-04-01

    Conventional Palmer Drought Index (PDSI) and recent Standardized Precipitation Index (SPI) are compared for Zagreb-Gric weather station. Historical time series of PDSI and SPI are compared. For that purpose monthly precipitation, air temperature and air humidity data for Zagreb-Gric Observatory and period 1862-2012 are used. The results indicate that SPI is simpler for interpretation than PDSI. On the other side, lack of temperature within SPI, make impossible use of it on climate change applications. A comparison of PDSI and SPI for the periods from 1 to 24 months indicate the best agreement between PDSI and SPI for the periods from 6 to 12 months. In addition, correlation coefficients of determination between annual corn crop per hectare and SPI 9- months time scale and PDSI from May to October are shown as significant.

  17. Modeling of present and Eemian stable water isotopes in precipitation

    DEFF Research Database (Denmark)

    Sjolte, Jesper

    The subject of this thesis is the modeling of the isotopic temperature proxies d18O, dD and deuterium excess in precipitation. Two modeling studies were carried out, one using the regional climate model, and one using a global climate model. In the regional study the model was run for the period ...... the modeled isotopes do not agree with ice core data. The discrepancy between the model output and the ice core data is attributed to the boundary conditions, where changes in ice sheets and vegetation have not been accounted for.......The subject of this thesis is the modeling of the isotopic temperature proxies d18O, dD and deuterium excess in precipitation. Two modeling studies were carried out, one using the regional climate model, and one using a global climate model. In the regional study the model was run for the period...... 1959 to 2001 using meteorological data and a domain including Greenland and the surrounding North Atlantic. The model was found to reproduce the observed seasonal variability of temperature and precipitation well. In comparison with ice core data from Greenland and observations from coastal stations...

  18. Validation of satellite based precipitation over diverse topography of Pakistan

    Science.gov (United States)

    Iqbal, Muhammad Farooq; Athar, H.

    2018-03-01

    This study evaluates the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) product data with 0.25° × 0.25° spatial and post-real-time 3 h temporal resolution using point-based Surface Precipitation Gauge (SPG) data from 40 stations, for the period 1998-2013, and using gridded Asian Precipitation ˗ Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) data abbreviated as APH data with 0.25° × 0.25° spatial and daily temporal resolution for the period 1998-2007, over vulnerable and data sparse regions of Pakistan (24-37° N and 62-75° E). To evaluate the performance of TMPA relative to SPG and APH, four commonly used statistical indicator metrics including Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Correlation Coefficient (CC) are employed on daily, monthly, seasonal as well as on annual timescales. The TMPA slightly overestimated both SPG and APH at daily, monthly, and annual timescales, however close results were obtained between TMPA and SPG as compared to those between TMPA and APH, on the same timescale. The TMPA overestimated both SPG and APH during the Pre-Monsoon and Monsoon seasons, whereas it underestimated during the Post-Monsoon and Winter seasons, with different magnitudes. Agreement between TMPA and SPG was good in plain and medium elevation regions, whereas TMPA overestimated APH in 31 stations. The magnitudes of MAE and RMSE were high at daily timescale as compared to monthly and annual timescales. Relatively large MAE was observed in stations located over high elevation regions, whereas minor MAE was recorded in plain area stations at daily, monthly, and annual timescales. A strong positive linear relationship between TMPA and SPG was established at monthly (0.98), seasonal (0.93 to 0.98) and annual (0.97) timescales. Precipitation increased with the increase of elevation, and not only elevation but latitude also affected the

  19. Potential relationships between the river discharge and the precipitation in the Jinsha River basin, China

    Science.gov (United States)

    Wang, Gaoxu; Zeng, Xiaofan; Zhao, Na; He, Qifang; Bai, Yiran; Zhang, Ruoyu

    2018-02-01

    The relationships between the river discharge and the precipitation in the Jinsha River basin are discussed in this study. In addition, the future precipitation trend from 2011-2050 and its potential influence on the river discharge are analysed by applying the CCLM-modelled precipitation. According to the observed river discharge and precipitation, the annual river discharge at the two main hydrological stations displays good correlations with the annual precipitation in the Jinsha River basin. The predicted future precipitation tends to change similarly as the change that occurred during the observation period, whereas the monthly distributions over a year could be more uneven, which is unfavourable for water resources management.

  20. Quantifying recycled moisture fraction in precipitation of an arid region using deuterium excess

    Directory of Open Access Journals (Sweden)

    Yanlong Kong

    2013-01-01

    Full Text Available Terrestrial moisture recycling by evapotranspiration has recently been recognised as an important source of precipitation that can be characterised by its isotopic composition. Up to now, this isotope technique has mainly been applied to moisture recycling in some humid regions, including Brazil, Great Lakes in North America and the European Alps. In arid and semi-arid regions, the contribution of transpiration by plants to local moisture recycling can be small, so that evaporation by bare soil and surface water bodies dominates. Recognising that the deuterium excess (d-excess of evaporated moisture is significantly different from that of the original water, we made an attempt to use this isotopic parameter for estimating moisture recycling in the semi-arid region of Eastern Tianshan, China. We measured the d-excess of samples taken from individual precipitation events during a hydrological year from 2003 to 2004 at two Tianshan mountain stations, and we used long-term monthly average values of the d-excess for the station Urumqi, which are available from the International Atomic Energy Agency–World Meteorological Organization (IAEA–WMO Global Network of Isotopes in Precipitation (GNIP. Since apart from recycling of moisture from the ground, sub-cloud evaporation of falling raindrops also affects the d-excess of precipitation, the measured values had to be corrected for this evaporation effect. For the selected stations, the sub-cloud evaporation was found to change between 0.1 and 3.8%, and the d-excess decreased linearly with increasing sub-cloud evaporation at about 1.1‰ per 1% change of sub-cloud evaporation. Assuming simple mixing between advected and recycled moisture, the recycled fraction in precipitation has been estimated to be less than 2.0±0.6% for the Tianshan mountain stations and reach values up to 15.0±0.7% in the Urumqi region. The article includes a discussion of these findings in the context of water cycling in the