Relationships between High Impact Tropical Rainfall Events and Environmental Conditions

Science.gov (United States)

Painter, C.; Varble, A.; Zipser, E. J.

2017-12-01

While rainfall increases as moisture and vertical motion increase, relationships between regional environmental conditions and rainfall event characteristics remain more uncertain. Of particular importance are long duration, heavy rain rate, and significant accumulation events that contribute sizable fractions of overall precipitation over short time periods. This study seeks to establish relationships between observed rainfall event properties and environmental conditions. Event duration, rain rate, and rainfall accumulation are derived using the Tropical Rainfall Measuring Mission (TRMM) 3B42 3-hourly, 0.25° resolution rainfall retrieval from 2002-2013 between 10°N and 10°S. Events are accumulated into 2.5° grid boxes and matched to monthly mean total column water vapor (TCWV) and 500-hPa vertical motion (omega) in each 2.5° grid box, retrieved from ERA-interim reanalysis. Only months with greater than 3 mm/day rainfall are included to ensure sufficient sampling. 90th and 99th percentile oceanic events last more than 20% longer and have rain rates more than 20% lower than those over land for a given TCWV-omega condition. Event duration and accumulation are more sensitive to omega than TCWV over oceans, but more sensitive to TCWV than omega over land, suggesting system size, propagation speed, and/or forcing mechanism differences for land and ocean regions. Sensitivities of duration, rain rate, and accumulation to TCWV and omega increase with increasing event extremity. For 3B42 and ERA-Interim relationships, the 90th percentile oceanic event accumulation increases by 0.93 mm for every 1 Pa/min change in rising motion, but this increases to 3.7 mm for every 1 Pa/min for the 99th percentile. Over land, the 90th percentile event accumulation increases by 0.55 mm for every 1 mm increase in TCWV, whereas the 99th percentile increases by 0.90 mm for every 1 mm increase in TCWV. These changes in event accumulation are highly correlated with changes in event

Assessment of probabilistic areal reduction factors of precipitations for the entire French territory with gridded rainfall data.

Science.gov (United States)

Fouchier, Catherine; Maire, Alexis; Arnaud, Patrick; Cantet, Philippe; Odry, Jean

2016-04-01

high-resolution atmospheric reanalysis over France with the SAFRAN-gauge-based analysis system (Vidal et al., 2010). We have then built samples of maximal rainfalls for each cell location (the "point" rainfalls) and for different areas centered on each cell location (the areal rainfalls) of these gridded data. To compute rainfall quantiles, we have fitted a Gumbel law, with the L-moment method, on each of these samples. Our daily and hourly ARF have then shown four main trends: i) a sensitivity to the return period, with ARF values decreasing when the return period increases; ii) a sensitivity to the rainfall duration, with ARF values decreasing when the rainfall duration decreases; iii) a sensitivity to the season, with ARF values smaller for the summer period than for the winter period; iv) a sensitivity to the geographical location, with low ARF values in the French Mediterranean area and ARF values close to 1 for the climatic zones of Northern and Western France (oceanic to semi-continental climate). The results of this data-intensive study led for the first time on the whole French territory are in agreement with studies led abroad (e.g. Allen and DeGaetano 2005, Overeem et al. 2010) and confirm and widen the results of previous studies that were carried out in France on smaller areas and with fewer rainfall durations (e.g. Ramos et al., 2006, Neppel et al., 2003). References Allen R. J. and DeGaetano A. T. (2005). Areal reduction factors for two eastern United States regions with high rain-gauge density. Journal of Hydrologic Engineering 10(4): 327-335. Arnaud P., Fine J.-A. and Lavabre J. (2007). An hourly rainfall generation model applicable to all types of climate. Atmospheric Research 85(2): 230-242. Cantet, P. and Arnaud, P. (2014). Extreme rainfall analysis by a stochastic model: impact of the copula choice on the sub-daily rainfall generation, Stochastic Environmental Research and Risk Assessment, Springer Berlin Heidelberg, 28(6), 1479-1492. Neppel L

Relationships between Indian summer monsoon rainfall and ice cover over selected oceanic regions

Digital Repository Service at National Institute of Oceanography (India)

Gopinathan, C.K.

The variations in oceanic ice cover at selected polar regions during 1973 to 1987 have been analysed in relation to the seasonal Indian summer monsoon rainfall. The ice cover over the Arctic regions in June has negative relationship (correlation...

The Role of Indian Ocean SST Anomalies in Modulating Regional Rainfall Variability and Long-term Change

Science.gov (United States)

Ummenhofer, C. C.; Sen Gupta, A.; England, M. H.

2008-12-01

In a series of atmospheric general circulation model simulations, the potential impact of Indian Ocean sea surface temperature (SST) anomalies in modulating low- to mid-latitude precipitation around the Indian Ocean rim countries is explored. The relative importance of various characteristic tropical and subtropical Indian Ocean SST poles, both individually and in combination, to regional precipitation changes is quantified. A mechanism for the rainfall modulation is proposed, by which the SST anomalies induce changes in the thermal properties of the atmosphere, resulting in a reorganization of the large-scale atmospheric circulation across the Indian Ocean basin. Across western and southern regions of Australia, rainfall anomalies are found to be due to modulations in the meridional thickness gradient, thermal wind, and baroclinicity, leading to changes in the moisture flux onto the continent. The pattern of large-scale circulation changes over the tropical Indian Ocean and adjacent land masses is consistent with an anomalous strengthening of the Walker cell, leading to variations in precipitation of opposite sign across western and eastern regions of the basin. Links between long-term changes in Indian Ocean surface properties and regional precipitation changes in Indian Ocean rim countries are also discussed in a broader context with implications for water management and seasonal forecasting.

Estimation of Rainfall Associated with Typhoons over the Ocean Using TRMM/TMI and Numerical Models

Directory of Open Access Journals (Sweden)

Nan-Ching Yeh

2015-11-01

Full Text Available This study quantitatively estimated the precipitation associated with a typhoon in the northwestern Pacific Ocean by using a physical algorithm which included the Weather Research and Forecasting model, Radiative Transfer for TIROS Operational Vertical Sounder model, and data from the Tropical Rainfall Measuring Mission (TRMM/TRMM Microwave Imager (TMI and TRMM/Precipitation Radar (PR. First, a prior probability distribution function (PDF was constructed using over three million rain rate retrievals from the TRMM/PR data for the period 2002–2010 over the northwestern Pacific Ocean. Subsequently, brightness temperatures for 15 typhoons that occurred over the northwestern Pacific Ocean were simulated using a microwave radiative transfer model and a conditional PDF was obtained for these typhoons. The aforementioned physical algorithm involved using a posterior PDF. A posterior PDF was obtained by combining the prior and conditional PDFs. Finally, the rain rate associated with a typhoon was estimated by inputting the observations of the TMI (attenuation indices at 10, 19, 37 GHz into the posterior PDF (lookup table. Results based on rain rate retrievals indicated that rainband locations with the heaviest rainfall showed qualitatively similar horizontal distributions. The correlation coefficient and root-mean-square error of the rain rate estimation were 0.63 and 4.45 mm·h−1, respectively. Furthermore, the correlation coefficient and root-mean-square error for convective rainfall were 0.78 and 7.25 mm·h−1, respectively, and those for stratiform rainfall were 0.58 and 9.60 mm·h−1, respectively. The main contribution of this study is introducing an approach to quickly and accurately estimate the typhoon precipitation, and remove the need for complex calculations.

Contrasting the co-variability of daytime cloud and precipitation over tropical land and ocean

Science.gov (United States)

Jin, Daeho; Oreopoulos, Lazaros; Lee, Dongmin; Cho, Nayeong; Tan, Jackson

2018-03-01

The co-variability of cloud and precipitation in the extended tropics (35° N-35° S) is investigated using contemporaneous data sets for a 13-year period. The goal is to quantify potential relationships between cloud type fractions and precipitation events of particular strength. Particular attention is paid to whether the relationships exhibit different characteristics over tropical land and ocean. A primary analysis metric is the correlation coefficient between fractions of individual cloud types and frequencies within precipitation histogram bins that have been matched in time and space. The cloud type fractions are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) joint histograms of cloud top pressure and cloud optical thickness in 1° grid cells, and the precipitation frequencies come from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) data set aggregated to the same grid.It is found that the strongest coupling (positive correlation) between clouds and precipitation occurs over ocean for cumulonimbus clouds and the heaviest rainfall. While the same cloud type and rainfall bin are also best correlated over land compared to other combinations, the correlation magnitude is weaker than over ocean. The difference is attributed to the greater size of convective systems over ocean. It is also found that both over ocean and land the anti-correlation of strong precipitation with weak (i.e., thin and/or low) cloud types is of greater absolute strength than positive correlations between weak cloud types and weak precipitation. Cloud type co-occurrence relationships explain some of the cloud-precipitation anti-correlations. Weak correlations between weaker rainfall and clouds indicate poor predictability for precipitation when cloud types are known, and this is even more true over land than over ocean.

Seasonal Variation of Diurnal Cycle of Rainfall in the Eastern Equatorial Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

RameshKumar, M.R.; Pednekar, S.; Katsumata, M.; Antony, M.K.; Kuroda, Y.; Unnikrishnan, A.S.

The diurnal cycle of rainfall over the eastern equatorial Indian Ocean is studied for the period 23rd October 2001 to 31st October 2003 using the hourly data from the Triton buoy positioned at 1.5°S and 90°E. An analysis of the active and weak...

Desert locust populations, rainfall and climate change: insights from phenomenological models using gridded monthly data

OpenAIRE

Tratalos, Jamie A.; Cheke, Robert A.; Healey, Richard G.; Stenseth, Nils Chr.

2010-01-01

Using autocorrelation analysis and autoregressive integrated moving average (ARIMA)modelling, we analysed a time series of the monthly number of 1° grid squares infested with desert locust Schistocerca gregaria swarms throughout the geographical range of the species from 1930–1987. Statistically significant first- and higher-order autocorrelations were found in the series. Although endogenous components captured much of the variance, adding rainfall data improved endogenous ARIMA models and r...

South African mid-summer seasonal rainfall prediction performance by a coupled ocean-atmosphere model

CSIR Research Space (South Africa)

Landman, WA

2011-01-01

Full Text Available . 2000; Goddard and Mason, 2002). Such a so-called two-tiered procedure to predict the outcome of the rainfall season has been employed in South Africa for a number of years already (e.g., Landman et al., 2001). The advent of fully coupled ocean...

Heavy Rainfall Episodes in the Eastern Northeast Brazil Linked to Large-Scale Ocean-Atmosphere Conditions in the Tropical Atlantic

Directory of Open Access Journals (Sweden)

Yves K. Kouadio

2012-01-01

Full Text Available Relationships between simultaneous occurrences of distinctive atmospheric easterly wave (EW signatures that cross the south-equatorial Atlantic, intense mesoscale convective systems (lifespan > 2 hour that propagate westward over the western south-equatorial Atlantic, and subsequent strong rainfall episodes (anomaly > 10 mm·day−1 that occur in eastern Northeast Brazil (ENEB are investigated. Using a simple diagnostic analysis, twelve cases with EW lifespan ranging between 3 and 8 days and a mean velocity of 8 m·s−1 were selected and documented during each rainy season of 2004, 2005, and 2006. These cases, which represent 50% of the total number of strong rainfall episodes and 60% of the rainfall amount over the ENEB, were concomitant with an acceleration of the trade winds over the south-equatorial Atlantic, an excess of moisture transported westward from Africa to America, and a strengthening of the convective activity in the oceanic region close to Brazil. Most of these episodes occurred during positive sea surface temperature anomaly patterns over the entire south-equatorial Atlantic and low-frequency warm conditions within the oceanic mixing layer. A real-time monitoring and the simulation of this ocean-atmosphere relationship could help in forecasting such dramatic rainfall events.

Uganda rainfall variability and prediction

Science.gov (United States)

Jury, Mark R.

2018-05-01

This study analyzes large-scale controls on Uganda's rainfall. Unlike past work, here, a May-October season is used because of the year-round nature of agricultural production, vegetation sensitivity to rainfall, and disease transmission. The Uganda rainfall record exhibits steady oscillations of ˜3 and 6 years over 1950-2013. Correlation maps at two-season lead time resolve the subtropical ridge over global oceans as an important feature. Multi-variate environmental predictors include Dec-May south Indian Ocean sea surface temperature, east African upper zonal wind, and South Atlantic wind streamfunction, providing a 33% fit to May-Oct rainfall time series. Composite analysis indicates that cool-phase El Niño Southern Oscillation supports increased May-Oct Uganda rainfall via a zonal overturning lower westerly/upper easterly atmospheric circulation. Sea temperature anomalies are positive in the east Atlantic and negative in the west Indian Ocean in respect of wet seasons. The northern Hadley Cell plays a role in limiting the northward march of the equatorial trough from May to October. An analysis of early season floods found that moist inflow from the west Indian Ocean converges over Uganda, generating diurnal thunderstorm clusters that drift southwestward producing high runoff.

Direct AC–AC grid interface converter for ocean wave energy system

International Nuclear Information System (INIS)

Tsang, K.M.; Chan, W.L.

2015-01-01

Highlights: • Novel power grid interface converter for ocean wave energy system. • Unlike conventional approach, generator output is directly converted into fixed frequency AC for synchronous connection. • High conversion efficient and power quality could be achieved. - Abstract: Ocean wave energy is very promising. However, existing systems are using rectifying circuits to convert variable voltage and variable frequency output of electric generator into DC voltage and then use grid-tied inverter to connect to the power grid. Such arrangement will not only reduce the overall efficient but also increase the cost of the system. A direct AC–AC converter is a desirable solution. In this paper, a six-switch AC–AC converter has been proposed as a single phase grid-connected interface. New switching scheme has been derived for the converter such that the virtual input AC–DC conversion and the output DC–AC conversion can be decoupled. State-space averaging model and pulse width modulation scheme have been derived for the converter. As the input and the output operations can be decoupled, two independent controllers have been designed to handle the input AC–DC regulation and the output DC–AC regulation. The proposed scheme demands for two separate duty ratios and novel switching scheme has been derived to realize the combined duty ratios in one switching cycle. Power regulation, harmonics elimination and power factor correction control algorithms have also been derived for the converter when it is connected to the supply grid. Experimental results of a small scale model are included to demonstrate the effectiveness of the proposed switching and control schemes

On the generation of coastline-following grids for ocean models—trade-off between orthogonality and alignment to coastlines

Science.gov (United States)

Liu, Xiaonan; Ma, Jialiang; Xu, Shiming; Wang, Bin

2017-08-01

Regional ocean models usually utilize orthogonal curvilinear grids that are fit to the coastline of the modeled regions. While the orthogonality of the grid is required from the perspective of the numerical algorithms, the alignment to the irregular coastlines improves the characterization of the land-sea distribution and the ocean simulation. In this article, we carry out fractal analysis of two representative coastal regions and discuss the trade-offs between the orthogonality and coastline alignment during the grid generation of these regions. A new grid generation method based on Schwarz-Christoffel conformal mappings is proposed, with automatic coastal boundary retrieval algorithm that generates resolution dependent boundary for grid generation and alleviates the human efforts involved in traditional methods. We show that for the southeastern Pacific region, the coastline is smooth with low fractal dimension and there exists effective trade-off with a coastline boundary that adjusts to the desired grid resolution. On the contrary, there is no effective trade-off for southeast China seas where the coastline is of higher fractal dimension, and a coarser coastline boundary is recommended for better orthogonality with little loss in coastline alignment. Further numerical study of coastal trapped Kelvin waves for the typical regions demonstrate that the new coastline-fitting grids achieve smaller error in numerical dispersion and higher accuracy. Through analysis, we conclude that for grid generation for regional ocean modeling, modelers should bring into consideration of the multi-scale fractal characteristics of the coastline.

Influence of the sea surface temperature anomaly over the Indian Ocean in March on the summer rainfall in Xinjiang

Science.gov (United States)

Zhou, Yang; Huang, Anning; Zhao, Yong; Yang, Qing; Jiang, Jing; La, Mengke

2015-02-01

This study explores the relationship between the sea surface temperature over the Indian Ocean (IOSST) in March and the summer rainfall in Xinjiang. In the observations, the IOSST in March significantly correlates with the summer rainfall in Xinjiang with a correlation coefficient of about 0.49 during 1961-2007. This relationship is independent from the El Niño Southern Oscillation (ENSO), with a partial correlation coefficient of about 0.40-0.48 controlling for the ENSO indices from December to March. In addition to the observations, three sets of numerical sensitivity experiments are conducted with a regional climate model (RegCM4.3). The model results show that warm IOSST can excite a negative anomaly of geopotential height at 500 hPa over the Indian Ocean in March. This anomaly stays over the tropical Indian Ocean, and then propagates north to central Asia in June. Consequently, the anomalous wind associated with this geopotential height anomaly transports moisture from the Persian Gulf and the coast of Iran to Xinjiang, passing over Pakistan and the Tibetan Plateau. Therefore, the warm (cold) IOSST in March tends to cause the increase (decrease) of the summer rainfall over Xinjiang, especially in the Tian Shan and Kunlun Mountains.

Rainfall Effects on the Kuroshio Current East of Taiwan

Science.gov (United States)

Hsu, Po-Chun; Lin, Chen-Chih; Ho, Chung-Ru

2017-04-01

Changes of sea surface salinity (SSS) in the open oceans are related to precipitation and evaporation. SSS has been an indicator of water cycle. It may be related to the global change. The Kuroshio Current, a western boundary current originating from the North Equatorial Current, transfers warm and higher salinity to higher latitudes. It flows northward along the east coasts of Luzon Island and Taiwan Island to Japan. In this study, effects of heavy rainfall on the Kuroshio surface salinity east of Taiwan are investigated. Sea surface salinity (SSS) data taken by conductivity temperature depth (CTD) sensor on R/V Ocean Researcher I cruises, conductivity sensor on eight glider cruises, and Aquarius satellite data are used in this study. The rain rate data derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are also employed. A glider is a kind of autonomous underwater vehicle, which uses small changes in its buoyancy in conjunction with wings to convert vertical motion to horizontal in the underwater without requiring input from an operator. It can take sensors to measure salinity, temperature, and pressure. The TRMM/TMI data from remote sensing system are daily and are mapped to 0.25-degree grid. The results show a good correlation between the rain rate and SSS with a correlation coefficient of 0.86. The rainfall causes SSS of the Kuroshio surface water drops 0.176 PSU per 1 mm/hr rain rate.

RSS SSMIS OCEAN PRODUCT GRIDS DAILY FROM DMSP F17 NETCDF V7

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National Aeronautics and Space Administration — The RSS SSMIS Ocean Product Grids Daily from DMSP F17 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSMIS OCEAN PRODUCT GRIDS DAILY FROM DMSP F16 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSMIS Ocean Product Grids Daily from DMSP F16 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

The numerics of hydrostatic structured-grid coastal ocean models: State of the art and future perspectives

Science.gov (United States)

Klingbeil, Knut; Lemarié, Florian; Debreu, Laurent; Burchard, Hans

2018-05-01

The state of the art of the numerics of hydrostatic structured-grid coastal ocean models is reviewed here. First, some fundamental differences in the hydrodynamics of the coastal ocean, such as the large surface elevation variation compared to the mean water depth, are contrasted against large scale ocean dynamics. Then the hydrodynamic equations as they are used in coastal ocean models as well as in large scale ocean models are presented, including parameterisations for turbulent transports. As steps towards discretisation, coordinate transformations and spatial discretisations based on a finite-volume approach are discussed with focus on the specific requirements for coastal ocean models. As in large scale ocean models, splitting of internal and external modes is essential also for coastal ocean models, but specific care is needed when drying & flooding of intertidal flats is included. As one obvious characteristic of coastal ocean models, open boundaries occur and need to be treated in a way that correct model forcing from outside is transmitted to the model domain without reflecting waves from the inside. Here, also new developments in two-way nesting are presented. Single processes such as internal inertia-gravity waves, advection and turbulence closure models are discussed with focus on the coastal scales. Some overview on existing hydrostatic structured-grid coastal ocean models is given, including their extensions towards non-hydrostatic models. Finally, an outlook on future perspectives is made.

New spatial and temporal indices of Indian summer monsoon rainfall

Science.gov (United States)

Dwivedi, Sanjeev; Uma, R.; Lakshmi Kumar, T. V.; Narayanan, M. S.; Pokhrel, Samir; Kripalani, R. H.

2018-02-01

The overall yearly seasonal performance of Indian southwest monsoon rainfall (ISMR) for the whole Indian land mass is presently expressed by the India Meteorological Department (IMD) by a single number, the total quantum of rainfall. Any particular year is declared as excess/deficit or normal monsoon rainfall year on the basis of this single number. It is well known that monsoon rainfall also has high interannual variability in spatial and temporal scales. To account for these aspects in ISMR, we propose two new spatial and temporal indices. These indices have been calculated using the 115 years of IMD daily 0.25° × 0.25° gridded rainfall data. Both indices seem to go in tandem with the in vogue seasonal quantum index. The anomaly analysis indicates that the indices during excess monsoon years behave randomly, while for deficit monsoon years the phase of all the three indices is the same. Evaluation of these indices is also studied with respect to the existing dynamical indices based on large-scale circulation. It is found that the new temporal indices have better link with circulation indices as compared to the new spatial indices. El Nino and Southern Oscillation (ENSO) especially over the equatorial Pacific Ocean still have the largest influence in both the new indices. However, temporal indices have much better remote influence as compared to that of spatial indices. Linkages over the Indian Ocean regions are very different in both the spatial and temporal indices. Continuous wavelet transform (CWT) analysis indicates that the complete spectrum of oscillation of the QI is shared in the lower oscillation band by the spatial index and in the higher oscillation band by the temporal index. These new indices may give some extra dimension to study Indian summer monsoon variability.

Automatic Extraction of High-Resolution Rainfall Series from Rainfall Strip Charts

Science.gov (United States)

Saa-Requejo, Antonio; Valencia, Jose Luis; Garrido, Alberto; Tarquis, Ana M.

2015-04-01

Soil erosion is a complex phenomenon involving the detachment and transport of soil particles, storage and runoff of rainwater, and infiltration. The relative magnitude and importance of these processes depends on a host of factors, including climate, soil, topography, cropping and land management practices among others. Most models for soil erosion or hydrological processes need an accurate storm characterization. However, this data are not always available and in some cases indirect models are generated to fill this gap. In Spain, the rain intensity data known for time periods less than 24 hours back to 1924 and many studies are limited by it. In many cases this data is stored in rainfall strip charts in the meteorological stations but haven't been transfer in a numerical form. To overcome this deficiency in the raw data a process of information extraction from large amounts of rainfall strip charts is implemented by means of computer software. The method has been developed that largely automates the intensive-labour extraction work based on van Piggelen et al. (2011). The method consists of the following five basic steps: 1) scanning the charts to high-resolution digital images, 2) manually and visually registering relevant meta information from charts and pre-processing, 3) applying automatic curve extraction software in a batch process to determine the coordinates of cumulative rainfall lines on the images (main step), 4) post processing the curves that were not correctly determined in step 3, and 5) aggregating the cumulative rainfall in pixel coordinates to the desired time resolution. A colour detection procedure is introduced that automatically separates the background of the charts and rolls from the grid and subsequently the rainfall curve. The rainfall curve is detected by minimization of a cost function. Some utilities have been added to improve the previous work and automates some auxiliary processes: readjust the bands properly, merge bands when

RSS SSM/I OCEAN PRODUCT GRIDS DAILY FROM DMSP F14 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids Daily from DMSP F14 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSM/I OCEAN PRODUCT GRIDS DAILY FROM DMSP F11 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids Daily from DMSP F11 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSM/I OCEAN PRODUCT GRIDS DAILY FROM DMSP F13 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids Daily from DMSP F13 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

Gridded rainfall estimation for distributed modeling in western mountainous areas

Science.gov (United States)

Moreda, F.; Cong, S.; Schaake, J.; Smith, M.

2006-05-01

Estimation of precipitation in mountainous areas continues to be problematic. It is well known that radar-based methods are limited due to beam blockage. In these areas, in order to run a distributed model that accounts for spatially variable precipitation, we have generated hourly gridded rainfall estimates from gauge observations. These estimates will be used as basic data sets to support the second phase of the NWS-sponsored Distributed Hydrologic Model Intercomparison Project (DMIP 2). One of the major foci of DMIP 2 is to better understand the modeling and data issues in western mountainous areas in order to provide better water resources products and services to the Nation. We derive precipitation estimates using three data sources for the period of 1987-2002: 1) hourly cooperative observer (coop) gauges, 2) daily total coop gauges and 3) SNOw pack TELemetry (SNOTEL) daily gauges. The daily values are disaggregated using the hourly gauge values and then interpolated to approximately 4km grids using an inverse-distance method. Following this, the estimates are adjusted to match monthly mean values from the Parameter-elevation Regressions on Independent Slopes Model (PRISM). Several analyses are performed to evaluate the gridded estimates for DMIP 2 experiments. These gridded inputs are used to generate mean areal precipitation (MAPX) time series for comparison to the traditional mean areal precipitation (MAP) time series derived by the NWS' California-Nevada River Forecast Center for model calibration. We use two of the DMIP 2 basins in California and Nevada: the North Fork of the American River (catchment area 885 sq. km) and the East Fork of the Carson River (catchment area 922 sq. km) as test areas. The basins are sub-divided into elevation zones. The North Fork American basin is divided into two zones above and below an elevation threshold. Likewise, the Carson River basin is subdivided in to four zones. For each zone, the analyses include: a) overall

Comparison of random forests and support vector machine for real-time radar-derived rainfall forecasting

Science.gov (United States)

Yu, Pao-Shan; Yang, Tao-Chang; Chen, Szu-Yin; Kuo, Chen-Min; Tseng, Hung-Wei

2017-09-01

This study aims to compare two machine learning techniques, random forests (RF) and support vector machine (SVM), for real-time radar-derived rainfall forecasting. The real-time radar-derived rainfall forecasting models use the present grid-based radar-derived rainfall as the output variable and use antecedent grid-based radar-derived rainfall, grid position (longitude and latitude) and elevation as the input variables to forecast 1- to 3-h ahead rainfalls for all grids in a catchment. Grid-based radar-derived rainfalls of six typhoon events during 2012-2015 in three reservoir catchments of Taiwan are collected for model training and verifying. Two kinds of forecasting models are constructed and compared, which are single-mode forecasting model (SMFM) and multiple-mode forecasting model (MMFM) based on RF and SVM. The SMFM uses the same model for 1- to 3-h ahead rainfall forecasting; the MMFM uses three different models for 1- to 3-h ahead forecasting. According to forecasting performances, it reveals that the SMFMs give better performances than MMFMs and both SVM-based and RF-based SMFMs show satisfactory performances for 1-h ahead forecasting. However, for 2- and 3-h ahead forecasting, it is found that the RF-based SMFM underestimates the observed radar-derived rainfalls in most cases and the SVM-based SMFM can give better performances than RF-based SMFM.

GHRSST L2P Gridded Global Subskin Sea Surface Temperature from the Tropical Rainfall Mapping Mission (TRMM) Microwave Imager (TMI) (GDS version 1)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is a well calibrated passive microwave radiometer, similar to SSM/I, that contains lower...

Comparative Study of Monsoon Rainfall Variability over India and the Odisha State

Directory of Open Access Journals (Sweden)

K C Gouda

2017-10-01

Full Text Available Indian summer monsoon (ISM plays an important role in the weather and climate system over India. The rainfall during monsoon season controls many sectors from agriculture, food, energy, and water, to the management of disasters. Being a coastal province on the eastern side of India, Odisha is one of the most important states affected by the monsoon rainfall and associated hydro-meteorological systems. The variability of monsoon rainfall is highly unpredictable at multiple scales both in space and time. In this study, the monsoon variability over the state of Odisha is studied using the daily gridded rainfall data from India Meteorological Department (IMD. A comparative analysis of the behaviour of monsoon rainfall at a larger scale (India, regional scale (Odisha, and sub-regional scale (zones of Odisha is carried out in terms of the seasonal cycle of monsoon rainfall and its interannual variability. It is seen that there is no synchronization in the seasonal monsoon category (normal/excess/deficit when analysed over large (India and regional (Odisha scales. The impact of El Niño, La Niña, and the Indian Ocean Dipole (IOD on the monsoon rainfall at both scales (large scale and regional scale is analysed and compared. The results show that the impact is much more for rainfall over India, but it has no such relation with the rainfall over Odisha. It is also observed that there is a positive (negative relation of the IOD with the seasonal monsoon rainfall variability over Odisha (India. The correlation between the IAV of monsoon rainfall between the large scale and regional scale was found to be 0.46 with a phase synchronization of 63%. IAV on a sub-regional scale is also presented.

RSS SSM/I OCEAN PRODUCT GRIDS MONTHLY AVERAGE FROM DMSP F15 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids Monthly Average from DMSP F15 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special...

Statistical and dynamical assessment of land-ocean-atmosphere interactions across North Africa

Science.gov (United States)

Yu, Yan

impacts is evaluated through ensembles of fully coupled CESM dynamical experiments, with modified leaf area index (LAI) and soil moisture across the Sahel or West African Monsoon (WAM) region. The atmospheric responses to oceanic and terrestrial forcings are generally consistent between the dynamical experiments and statistical GEFA, confirming GEFA's capability of isolating the individual impacts of oceanic and terrestrial forcings on North African climate. Furthermore, with the incorporation of stepwise selection, GEFA can now provide reliable estimates of the oceanic and terrestrial impacts on the North African climate with the typical length of observational datasets, thereby enhancing the method's applicability. After the successful validation of GEFA, the key observed oceanic and terrestrial drivers of North African climate are identified through the application of GEFA to gridded observations, remote sensing products, and reanalyses. According to GEFA, oceanic drivers dominate over terrestrial drivers in terms of their observed impacts on North African climate in most seasons. Terrestrial impacts are comparable to, or more important than, oceanic impacts on rainfall during the post-monsoon across the Sahel and WAM region, and after the short rain across the Horn of Africa (HOA). The key ocean basins that regulate North African rainfall are typically located in the tropics. While the observed impacts of SST variability across the tropical Pacific and tropical Atlantic Oceans on the Sahel rainfall are largely consistent with previous model-based findings, minimal impacts from tropical Indian Ocean variability on Sahel rainfall are identified in observations, in contrast to previous modeling studies. The current observational analysis verifies model-hypothesized positive vegetation-rainfall feedback across the Sahel and HOA, which is confined to the post-monsoon and post-short rains season, respectively. However, the observed positive vegetation feedback to rainfall

RSS SSM/I OCEAN PRODUCT GRIDS WEEKLY AVERAGE FROM DMSP F15 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids Weekly Average from DMSP F15 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSMIS OCEAN PRODUCT GRIDS 3-DAY AVERAGE FROM DMSP F16 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSMIS Ocean Product Grids 3-Day Average from DMSP F16 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSM/I OCEAN PRODUCT GRIDS WEEKLY AVERAGE FROM DMSP F10 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids Weekly Average from DMSP F10 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSM/I OCEAN PRODUCT GRIDS WEEKLY AVERAGE FROM DMSP F8 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Products Grid Weekly Average from DMSP F8 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

Long range forecasting of summer monsoon rainfall from SST in the central equatorial Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Sadhuram, Y; Murthy, T.V.R.

of summer monsoon rainfall from SST in the central equatorial Indian ocean Y. Sadhuram and T. V. Ramana Murthy National Institute of Oceanography, Regional Centre, 176, Lawson's Bay Colony, . Visakhapatnam-530017 ABSTRACT Severalprediction tedmiques have... and droughts associated with strong and weak monsoons greatly influence the economy of the country. Most of the droughts and floods are associated with EI-Nino and La- Nina respectively (Webster andYang3 and krishna Kumar et al\\. The relationship between ENSO...

Long term spatial and temporal rainfall trends and homogeneity analysis in Wainganga basin, Central India

Directory of Open Access Journals (Sweden)

Arun Kumar Taxak

2014-08-01

Full Text Available Gridded rainfall data of 0.5×0.5° resolution (CRU TS 3.21 was analysed to study long term spatial and temporal trends on annual and seasonal scales in Wainganga river basin located in Central India during 1901–2012. After testing the presence of autocorrelation, Mann–Kendall (Modified Mann–Kendall test was applied to non-auto correlated (auto correlated series to detect the trends in rainfall data. Theil and Sen׳s slope estimator test was used for finding the magnitude of change over a time period. For detecting the most probable change year, Pettitt–Mann–Whitney test was applied. The Rainfall series was then divided into two partial duration series for finding changes in trends before and after the change year. Arc GIS was used to explore spatial patterns of the trends over the entire basin. Though most of the grid points shows a decreasing trend in annual rainfall, only seven grids has a significant decreasing trend during 1901–2012. On the basis of seasonal trend analysis, non-significant increasing trend is observed only in post monsoon season while seven grid points show significant decreasing trend in monsoon rainfall and non-significant in pre-monsoon and winter rainfall over the last 112 years. During the study period, overall a 8.45% decrease in annual rainfall is estimated. The most probable year of change was found to be 1948 in annual and monsoonal rainfall. There is an increasing rainfall trend in the basin during the period 1901–1948, which is reversed during the period 1949–2012 resulting in decreasing rainfall trend in the basin. Homogeneous trends in annual and seasonal rainfall over a grid points is exhibited in the basin by van Belle and Hughes׳ homogeneity trend test.

Role of Ocean Initial Conditions to Diminish Dry Bias in the Seasonal Prediction of Indian Summer Monsoon Rainfall: A Case Study Using Climate Forecast System

Science.gov (United States)

Koul, Vimal; Parekh, Anant; Srinivas, G.; Kakatkar, Rashmi; Chowdary, Jasti S.; Gnanaseelan, C.

2018-03-01

Coupled models tend to underestimate Indian summer monsoon (ISM) rainfall over most of the Indian subcontinent. Present study demonstrates that a part of dry bias is arising from the discrepancies in Oceanic Initial Conditions (OICs). Two hindcast experiments are carried out using Climate Forecast System (CFSv2) for summer monsoons of 2012-2014 in which two different OICs are utilized. With respect to first experiment (CTRL), second experiment (AcSAL) differs by two aspects: usage of high-resolution atmospheric forcing and assimilation of only ARGO observed temperature and salinity profiles for OICs. Assessment of OICs indicates that the quality of OICs is enhanced due to assimilation of actual salinity profiles. Analysis reveals that AcSAL experiment showed 10% reduction in the dry bias over the Indian land region during the ISM compared to CTRL. This improvement is consistently apparent in each month and is highest for June. The better representation of upper ocean thermal structure of tropical oceans at initial stage supports realistic upper ocean stability and mixing. Which in fact reduced the dominant cold bias over the ocean, feedback to air-sea interactions and land sea thermal contrast resulting better representation of monsoon circulation and moisture transport. This reduced bias of tropospheric moisture and temperature over the Indian land mass and also produced better tropospheric temperature gradient over land as well as ocean. These feedback processes reduced the dry bias in the ISM rainfall. Study concludes that initializing the coupled models with realistic OICs can reduce the underestimation of ISM rainfall prediction.

RSS SSM/I OCEAN PRODUCT GRIDS 3-DAY AVERAGE FROM DMSP F14 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids 3-Day Average from DMSP F14 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSM/I OCEAN PRODUCT GRIDS 3-DAY AVERAGE FROM DMSP F10 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids 3-Day Average from DMSP F10 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

Simulation of Tropical Rainfall Variability

Science.gov (United States)

Bader, J.; Latif, M.

2002-12-01

The impact of sea surface temperature (SST) - especially the role of the tropical Atlantic meridional SST gradient and the El Nino-Southern Oscillation - on precipitation is investigated with the atmospheric general circulation model ECHAM4/T42. Ensemble experiments - driven with observed SST - show that Atlantic SST has a significant influence on precipitation over West Africa and northeast Brazil. SST sensitivity experiments were performed in which the climatological SST was enhanced or decreased by one Kelvin in certain ocean areas. Changing SST in the eastern tropical Atlantic caused only significant changes along the Guinea Coast, with a positive anomaly (SSTA) increasing rainfall and a negative SSTA reducing it. The response was nearly linear. Changing SST in other ocean areas caused significant changes over West Africa, especially in the Sahel area. The response is found to be non linear, with only negative SSTA leading to significant reduction in Sahel rainfall. Also, the impact of the SSTAs from the different ocean regions was not additive with respect to the rainfall. The influence of SST on precipitation over northeast Brazil (Nordeste) was also investigated. Three experiments were performed in which the climatological SST was enhanced/decreased or decreased/enhanced by one Kelvin in the North/South Atlantic and increased by two Kelvin in the Nino3 ocean area. All experiments caused significant changes over Nordeste, with an enhanced/reduced SST gradient in the Atlantic increasing/reducing rainfall. The response was nearly linear. The main effect of the Atlantic SST gradient was a shift of the ITCZ, caused by trade wind changes. The ''El Nino'' event generates a significant reduction in Nordeste rainfall. A significant positive SLP anomaly occurs in northeast Brazil which may be associated with the descending branch of the Walker circulation. Also a significant positive SLP over the Atlantic from 30S to 10N north occurs. This results in a reduced SLP

Predictability of Seasonal Rainfall over the Greater Horn of Africa

Science.gov (United States)

Ngaina, J. N.

2016-12-01

The El Nino-Southern Oscillation (ENSO) is a primary mode of climate variability in the Greater of Africa (GHA). The expected impacts of climate variability and change on water, agriculture, and food resources in GHA underscore the importance of reliable and accurate seasonal climate predictions. The study evaluated different model selection criteria which included the Coefficient of determination (R2), Akaike's Information Criterion (AIC), Bayesian Information Criterion (BIC), and the Fisher information approximation (FIA). A forecast scheme based on the optimal model was developed to predict the October-November-December (OND) and March-April-May (MAM) rainfall. The predictability of GHA rainfall based on ENSO was quantified based on composite analysis, correlations and contingency tables. A test for field-significance considering the properties of finiteness and interdependence of the spatial grid was applied to avoid correlations by chance. The study identified FIA as the optimal model selection criterion. However, complex model selection criteria (FIA followed by BIC) performed better compared to simple approach (R2 and AIC). Notably, operational seasonal rainfall predictions over the GHA makes of simple model selection procedures e.g. R2. Rainfall is modestly predictable based on ENSO during OND and MAM seasons. El Nino typically leads to wetter conditions during OND and drier conditions during MAM. The correlations of ENSO indices with rainfall are statistically significant for OND and MAM seasons. Analysis based on contingency tables shows higher predictability of OND rainfall with the use of ENSO indices derived from the Pacific and Indian Oceans sea surfaces showing significant improvement during OND season. The predictability based on ENSO for OND rainfall is robust on a decadal scale compared to MAM. An ENSO-based scheme based on an optimal model selection criterion can thus provide skillful rainfall predictions over GHA. This study concludes that the

Accuracy of rainfall measurement for scales of hydrological interest

Directory of Open Access Journals (Sweden)

S. J. Wood

2000-01-01

Full Text Available The dense network of 49 raingauges over the 135 km2 Brue catchment in Somerset, England is used to examine the accuracy of rainfall estimates obtained from raingauges and from weather radar. Methods for data quality control and classification of precipitation types are first described. A super-dense network comprising eight gauges within a 2 km grid square is employed to obtain a 'true value' of rainfall against which the 2 km radar grid and a single 'typical gauge' estimate can be compared. Accuracy is assessed as a function of rainfall intensity, for different periods of time-integration (15 minutes, 1 hour and 1 day and for two 8-gauge networks in areas of low and high relief. In a similar way, the catchment gauge network is used to provide the 'true catchment rainfall' and the accuracy of a radar estimate (an area-weighted average of radar pixel values and a single 'typical gauge' estimate of catchment rainfall evaluated as a function of rainfall intensity. A single gauge gives a standard error of estimate for rainfall in a 2 km square and over the catchment of 33% and 65% respectively, at rain rates of 4 mm in 15 minutes. Radar data at 2 km resolution give corresponding errors of 50% and 55%. This illustrates the benefit of using radar when estimating catchment scale rainfall. A companion paper (Wood et al., 2000 considers the accuracy of rainfall estimates obtained using raingauge and radar in combination. Keywords: rainfall, accuracy, raingauge, radar

The sensitivity of catchment runoff models to rainfall data at different spatial scales

Directory of Open Access Journals (Sweden)

V. A. Bell

2000-01-01

Full Text Available The sensitivity of catchment runoff models to rainfall is investigated at a variety of spatial scales using data from a dense raingauge network and weather radar. These data form part of the HYREX (HYdrological Radar EXperiment dataset. They encompass records from 49 raingauges over the 135 km2 Brue catchment in south-west England together with 2 and 5 km grid-square radar data. Separate rainfall time-series for the radar and raingauge data are constructed on 2, 5 and 10 km grids, and as catchment average values, at a 15 minute time-step. The sensitivity of the catchment runoff models to these grid scales of input data is evaluated on selected convective and stratiform rainfall events. Each rainfall time-series is used to produce an ensemble of modelled hydrographs in order to investigate this sensitivity. The distributed model is shown to be sensitive to the locations of the raingauges within the catchment and hence to the spatial variability of rainfall over the catchment. Runoff sensitivity is strongest during convective rainfall when a broader spread of modelled hydrographs results, with twice the variability of that arising from stratiform rain. Sensitivity to rainfall data and model resolution is explored and, surprisingly, best performance is obtained using a lower resolution of rainfall data and model. Results from the distributed catchment model, the Simple Grid Model, are compared with those obtained from a lumped model, the PDM. Performance from the distributed model is found to be only marginally better during stratiform rain (R2 of 0.922 compared to 0.911 but significantly better during convective rain (R2 of 0.953 compared to 0.909. The improved performance from the distributed model can, in part, be accredited to the excellence of the dense raingauge network which would not be the norm for operational flood warning systems. In the final part of the paper, the effect of rainfall resolution on the performance of the 2 km distributed

Oceanic and atmospheric conditions associated with the pentad rainfall over the southeastern peninsular India during the North-East Indian Monsoon season

Science.gov (United States)

Shanmugasundaram, Jothiganesh; Lee, Eungul

2018-03-01

The association of North-East Indian Monsoon rainfall (NEIMR) over the southeastern peninsular India with the oceanic and atmospheric conditions over the adjacent ocean regions at pentad time step (five days period) was investigated during the months of October to December for the period 1985-2014. The non-parametric correlation and composite analyses were carried out for the simultaneous and lagged time steps (up to four lags) of oceanic and atmospheric variables with pentad NEIMR. The results indicated that NEIMR was significantly correlated: 1) positively with both sea surface temperature (SST) led by 1-4 pentads (lag 1-4 time steps) and latent heat flux (LHF) during the simultaneous, lag 1 and 2 time steps over the equatorial western Indian Ocean, 2) positively with SST but negatively with LHF (less heat flux from ocean to atmosphere) during the same and all the lagged time steps over the Bay of Bengal. Consistently, during the wet NEIMR pentads over the southeastern peninsular India, SST significantly increased over the Bay of Bengal during all the time steps and the equatorial western Indian Ocean during the lag 2-4 time steps, while the LHF decreased over the Bay of Bengal (all time steps) and increased over the Indian Ocean (same, lag 1 and 2). The investigation on ocean-atmospheric interaction revealed that the enhanced LHF over the equatorial western Indian Ocean was related to increased atmospheric moisture demand and increased wind speed, whereas the reduced LHF over the Bay of Bengal was associated with decreased atmospheric moisture demand and decreased wind speed. The vertically integrated moisture flux and moisture transport vectors from 1000 to 850 hPa exhibited that the moisture was carried away from the equatorial western Indian Ocean to the strong moisture convergence regions of the Bay of Bengal during the same and lag 1 time steps of wet NEIMR pentads. Further, the moisture over the Bay of Bengal was transported to the southeastern peninsular

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

OpenAIRE

Carolien Toté; Domingos Patricio; Hendrik Boogaard; Raymond van der Wijngaart; Elena Tarnavsky; Chris Funk

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Cl...

Simulating multi-scale oceanic processes around Taiwan on unstructured grids

Science.gov (United States)

Yu, Hao-Cheng; Zhang, Yinglong J.; Yu, Jason C. S.; Terng, C.; Sun, Weiling; Ye, Fei; Wang, Harry V.; Wang, Zhengui; Huang, Hai

2017-11-01

We validate a 3D unstructured-grid (UG) model for simulating multi-scale processes as occurred in Northwestern Pacific around Taiwan using recently developed new techniques (Zhang et al., Ocean Modeling, 102, 64-81, 2016) that require no bathymetry smoothing even for this region with prevalent steep bottom slopes and many islands. The focus is on short-term forecast for several months instead of long-term variability. Compared with satellite products, the errors for the simulated Sea-surface Height (SSH) and Sea-surface Temperature (SST) are similar to a reference data-assimilated global model. In the nearshore region, comparison with 34 tide gauges located around Taiwan indicates an average RMSE of 13 cm for the tidal elevation. The average RMSE for SST at 6 coastal buoys is 1.2 °C. The mean transport and eddy kinetic energy compare reasonably with previously published values and the reference model used to provide boundary and initial conditions. The model suggests ∼2-day interruption of Kuroshio east of Taiwan during a typhoon period. The effect of tidal mixing is shown to be significant nearshore. The multi-scale model is easily extendable to target regions of interest due to its UG framework and a flexible vertical gridding system, which is shown to be superior to terrain-following coordinates.

Analysis of rainfall distribution in Kelantan river basin, Malaysia

Science.gov (United States)

Che Ros, Faizah; Tosaka, Hiroyuki

2018-03-01

Using rainfall gauge on its own as input carries great uncertainties regarding runoff estimation, especially when the area is large and the rainfall is measured and recorded at irregular spaced gauging stations. Hence spatial interpolation is the key to obtain continuous and orderly rainfall distribution at unknown points to be the input to the rainfall runoff processes for distributed and semi-distributed numerical modelling. It is crucial to study and predict the behaviour of rainfall and river runoff to reduce flood damages of the affected area along the Kelantan river. Thus, a good knowledge on rainfall distribution is essential in early flood prediction studies. Forty six rainfall stations and their daily time-series were used to interpolate gridded rainfall surfaces using inverse-distance weighting (IDW), inverse-distance and elevation weighting (IDEW) methods and average rainfall distribution. Sensitivity analysis for distance and elevation parameters were conducted to see the variation produced. The accuracy of these interpolated datasets was examined using cross-validation assessment.

GHRSST Level 2P Regional Subskin Sea Surface Temperature from the Tropical Rainfall Mapping Mission (TRMM) Microwave Imager (TMI) for the Atlantic Ocean (GDS version 1)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is a well calibrated passive microwave radiometer, similar to SSM/I, that contains lower...

Predictability of rainfall and teleconnections patterns influencing on Southwest Europe from sea surfaces temperatures

Science.gov (United States)

Lorenzo, M. N.; Iglesias, I.; Taboada, J. J.; Gómez-Gesteira, M.; Ramos, A. M.

2009-04-01

This work assesses the possibility of doing a forecast of rainfall and the main teleconnections patterns that influences climate in Southwest Europe by using sea surface temperature anomalies (SSTA). The area under study is located in the NW Iberian Peninsula. This region has a great oceanic influence on its climate and has an important dependency of the water resources. In this way if the different SST patterns are known, the different rainfall situations can be predicted. On the other hand, the teleconnection patterns, which have strong weight on rainfall, are influenced by the SSTA of different areas. In the light of this, the aim of this study is to explore the relationship between global SSTAs, rainfall and the main teleconnection patterns influencing on Europe. The SST data with a 2.0 degree resolution was provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA. A monthly averaged data from 1 January 1951 through December 2006 was considered. The monthly precipitation data from 1951-2006 were obtained from the database CLIMA of the University of Santiago de Compostela with data from the Meteorological State Agency (AEMET) and the Regional Government of Galicia. The teleconnection indices were taken of the Climate Prediction Center of the NOAA between 1950 and 2006. A monthly and seasonal study was analysed considering up to three months of delay in the first case and up to four seasons of delay in the second case. The Pearson product-moment correlation coefficient r was considered to quantify linear associations between SSTA and precipitation and/or SSTA and teleconnection indices. A test for field-significance was applied considering the properties of finiteness and interdependence of the spatial grid to avoid spurious correlations. Analysing the results obtained with the global SSTA and the teleconnection indices, a great number of ocean regions with high correlations can be found. The spatial patterns show very high correlations with Indian Ocean waters

An Optimization Method for Virtual Globe Ocean Surface Dynamic Visualization

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HUANG Wumeng

2016-12-01

Full Text Available The existing visualization method in the virtual globe mainly uses the projection grid to organize the ocean grid. This special grid organization has the defects in reflecting the difference characteristics of different ocean areas. The method of global ocean visualization based on global discrete grid can make up the defect of the projection grid method by matching with the discrete space of the virtual globe, so it is more suitable for the virtual ocean surface simulation application.But the available global discrete grids method has many problems which limiting its application such as the low efficiency of rendering and loading, the need of repairing grid crevices. To this point, we propose an optimization for the global discrete grids method. At first, a GPU-oriented multi-scale grid model of ocean surface which develops on the foundation of global discrete grids was designed to organize and manage the ocean surface grids. Then, in order to achieve the wind-drive wave dynamic rendering, this paper proposes a dynamic wave rendering method based on the multi-scale ocean surface grid model to support real-time wind field updating. At the same time, considering the effect of repairing grid crevices on the system efficiency, this paper presents an efficient method for repairing ocean surface grid crevices based on the characteristics of ocean grid and GPU technology. At last, the feasibility and validity of the method are verified by the comparison experiment. The experimental results show that the proposed method is efficient, stable and fast, and can compensate for the lack of function of the existing methods, so the application range is more extensive.

RainyDay: An Online, Open-Source Tool for Physically-based Rainfall and Flood Frequency Analysis

Science.gov (United States)

Wright, D.; Yu, G.; Holman, K. D.

2017-12-01

Flood frequency analysis in ungaged or changing watersheds typically requires rainfall intensity-duration-frequency (IDF) curves combined with hydrologic models. IDF curves only depict point-scale rainfall depth, while true rainstorms exhibit complex spatial and temporal structures. Floods result from these rainfall structures interacting with watershed features such as land cover, soils, and variable antecedent conditions as well as river channel processes. Thus, IDF curves are traditionally combined with a variety of "design storm" assumptions such as area reduction factors and idealized rainfall space-time distributions to translate rainfall depths into inputs that are suitable for flood hydrologic modeling. The impacts of such assumptions are relatively poorly understood. Meanwhile, modern precipitation estimates from gridded weather radar, grid-interpolated rain gages, satellites, and numerical weather models provide more realistic depictions of rainfall space-time structure. Usage of such datasets for rainfall and flood frequency analysis, however, are hindered by relatively short record lengths. We present RainyDay, an open-source stochastic storm transposition (SST) framework for generating large numbers of realistic rainfall "scenarios." SST "lengthens" the rainfall record by temporal resampling and geospatial transposition of observed storms to extract space-time information from regional gridded rainfall data. Relatively short (10-15 year) records of bias-corrected radar rainfall data are sufficient to estimate rainfall and flood events with much longer recurrence intervals including 100-year and 500-year events. We describe the SST methodology as implemented in RainyDay and compare rainfall IDF results from RainyDay to conventional estimates from NOAA Atlas 14. Then, we demonstrate some of the flood frequency analysis properties that are possible when RainyDay is integrated with a distributed hydrologic model, including robust estimation of flood

Combined effect of MJO, ENSO and IOD on the intraseasonal variability of northeast monsoon rainfall over south peninsular India

Science.gov (United States)

Sreekala, P. P.; Rao, S. Vijaya Bhaskara; Rajeevan, K.; Arunachalam, M. S.

2018-02-01

The present study has examined the combined effect of MJO, ENSO and IOD on the intraseasonal and interannual variability of northeast monsoon rainfall over south peninsular India. The study has revealed that the intraseasonal variation of daily rainfall over south peninsular India during NEM season is associated with various phases of eastward propagating MJO life cycle. Positive rainfall anomaly over south peninsular India and surrounding Indian Ocean (IO) is observed during the strong MJO phases 2, 3 and 4; and negative rainfall anomaly during the strong MJO phases 5,6,7,8 and 1. Above normal (below normal) convection over south peninsular India and suppressed convection over east Indian and West Pacific Ocean, high pressure (low pressure) anomaly over West Pacific Ocean, Positive (negative) SST anomalies over equatorial East and Central Pacific Ocean and easterly wind anomaly (westerly anomaly) over equatorial Indian Ocean are the observed features during the first three MJO (5, 6, 7) phases and all these features are observed in the excess (drought) NEMR composite. This suggests that a similar mode of physical mechanism is responsible for the intraseasonal and interannual variability of northeast monsoon rainfall. The number of days during the first three phases (last four phases) of MJO, where the enhanced convection and positive rainfall anomaly is over Indian Ocean (East Indian ocean and West Pacific Ocean), is more (less) during El Nino and IOD years and less during La Nina and NIOD years and vice versa. The observed excess (deficit) rainfall anomaly over west IO and south peninsular India and deficit (excess) rainfall anomaly over east IO including Bay of Bengal and West Pacific Ocean suggest that the more (less) number of first three phases during El Nino and IOD (La Nina and Negative IOD) is due to the interaction between eastward moving MJO and strong easterlies over equatorial IO present during El Nino and IOD years. This interaction would inhibit the

Analysis of Rainfall Variations and Trends in Coastal Tanzania

African Journals Online (AJOL)

Ocean Dipole, Pacific Decadal Oscillation ... island of Mafia receives the highest amount of rainfall (1879 mm p.a.) while Kilwa. Masoko receives the ... However, the effects of the Pacific .... an important role in terrestrial and marine .... and ENSO, the largest coefficient being .... rainfall on the small islands of Southeast Asia.

Madagascar corals reveal a multidecadal signature of rainfall and river runoff since 1708

Directory of Open Access Journals (Sweden)

C. A. Grove

2013-03-01

Full Text Available Pacific Ocean sea surface temperatures (SST influence rainfall variability on multidecadal and interdecadal timescales in concert with the Pacific Decadal Oscillation (PDO and Interdecadal Pacific Oscillation (IPO. Rainfall variations in locations such as Australia and North America are therefore linked to phase changes in the PDO. Furthermore, studies have suggested teleconnections exist between the western Indian Ocean and Pacific Decadal Variability (PDV, similar to those observed on interannual timescales related to the El Niño Southern Oscillation (ENSO. However, as instrumental records of rainfall are too short and sparse to confidently assess multidecadal climatic teleconnections, here we present four coral climate archives from Madagascar spanning up to the past 300 yr (1708–2008 to assess such decadal variability. Using spectral luminescence scanning to reconstruct past changes in river runoff, we identify significant multidecadal and interdecadal frequencies in the coral records, which before 1900 are coherent with Asian-based PDO reconstructions. This multidecadal relationship with the Asian-based PDO reconstructions points to an unidentified teleconnection mechanism that affects Madagascar rainfall/runoff, most likely triggered by multidecadal changes in North Pacific SST, influencing the Asian Monsoon circulation. In the 20th century we decouple human deforestation effects from rainfall-induced soil erosion by pairing luminescence with coral geochemistry. Positive PDO phases are associated with increased Indian Ocean temperatures and runoff/rainfall in eastern Madagascar, while precipitation in southern Africa and eastern Australia declines. Consequently, the negative PDO phase that started in 1998 may contribute to reduced rainfall over eastern Madagascar and increased precipitation in southern Africa and eastern Australia. We conclude that multidecadal rainfall variability in Madagascar and the western Indian Ocean needs to be

An Assessment of Satellite-Derived Rainfall Products Relative to Ground Observations over East Africa

Directory of Open Access Journals (Sweden)

Margaret Wambui Kimani

2017-05-01

Full Text Available Accurate and consistent rainfall observations are vital for climatological studies in support of better agricultural and water management decision-making and planning. In East Africa, accurate rainfall estimation with an adequate spatial distribution is limited due to sparse rain gauge networks. Satellite rainfall products can potentially play a role in increasing the spatial coverage of rainfall estimates; however, their performance needs to be understood across space–time scales and factors relating to their errors. This study assesses the performance of seven satellite products: Tropical Applications of Meteorology using Satellite and ground-based observations (TAMSAT, African Rainfall Climatology And Time series (TARCAT, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS, Tropical Rainfall Measuring Mission (TRMM-3B43, Climate Prediction Centre (CPC Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR, CPC Merged Analysis of Precipitation (CMAP, and Global Precipitation Climatology Project (GPCP, using locally developed gridded (0.05° rainfall data for 15 years (1998–2012 over East Africa. The products’ assessments were done at monthly and yearly timescales and were remapped to the gridded rain gauge data spatial scale during the March to May (MAM and October to December (OND rainy seasons. A grid-based statistical comparison between the two datasets was used, but only pixel values located at the rainfall stations were considered for validation. Additionally, the impact of topography on the performance of the products was assessed by analyzing the pixels in areas of highest negative bias. All the products could substantially replicate rainfall patterns, but their differences are mainly based on retrieving high rainfall amounts, especially of localized orographic types. The products exhibited systematic errors, which

Interannual rainfall variability in the Amazon basin and sea-surface temperatures in the equatorial Pacific and the tropical Atlantic Oceans

Science.gov (United States)

Ronchail, Josyane; Cochonneau, Gérard; Molinier, Michel; Guyot, Jean-Loup; Chaves, Adriana Goretti De Miranda; Guimarães, Valdemar; de Oliveira, Eurides

2002-11-01

Rainfall variability in the Amazon basin is studied in relation to sea-surface temperatures (SSTs) in the equatorial Pacific and the northern and southern tropical Atlantic during the 1977-99 period, using the HiBAm original rainfall data set and complementary cluster and composite analyses.The northeastern part of the basin, north of 5 °S and east of 60 °W, is significantly related with tropical SSTs: a rainier wet season is observed when the equatorial Pacific and the northern (southern) tropical Atlantic are anomalously cold (warm). A shorter and drier wet season is observed during El Niño events and negative rainfall anomalies are also significantly associated with a warm northern Atlantic in the austral autumn and a cold southern Atlantic in the spring. The northeastern Amazon rainfall anomalies are closely related with El Niño-southern oscillation during the whole year, whereas the relationships with the tropical Atlantic SST anomalies are mainly observed during the autumn. A time-space continuity is observed between El Niño-related rainfall anomalies in the northeastern Amazon, those in the northern Amazon and south-eastern Amazon, and those in northern South America and in the Nordeste of Brazil.A reinforcement of certain rainfall anomalies is observed when specific oceanic events combine. For instance, when El Niño and cold SSTs in the southern Atlantic are associated, very strong negative anomalies are observed in the whole northern Amazon basin. Nonetheless, the comparison of the cluster and the composite analyses results shows that the rainfall anomalies in the northeastern Amazon are not always associated with tropical SST anomalies.In the southern and western Amazon, significant tropical SST-related rainfall anomalies are very few and spatially variable. The precipitation origins differ from those of the northeastern Amazon: land temperature variability, extratropical perturbations and moisture advection are important rainfall factors, as well

Asian Summer Monsoon Rainfall associated with ENSO and its Predictability

Science.gov (United States)

Shin, C. S.; Huang, B.; Zhu, J.; Marx, L.; Kinter, J. L.; Shukla, J.

2015-12-01

The leading modes of the Asian summer monsoon (ASM) rainfall variability and their seasonal predictability are investigated using the CFSv2 hindcasts initialized from multiple ocean analyses over the period of 1979-2008 and observation-based analyses. It is shown that the two leading empirical orthogonal function (EOF) modes of the observed ASM rainfall anomalies, which together account for about 34% of total variance, largely correspond to the ASM responses to the ENSO influences during the summers of the developing and decaying years of a Pacific anomalous event, respectively. These two ASM modes are then designated as the contemporary and delayed ENSO responses, respectively. It is demonstrated that the CFSv2 is capable of predicting these two dominant ASM modes up to the lead of 5 months. More importantly, the predictability of the ASM rainfall are much higher with respect to the delayed ENSO mode than the contemporary one, with the predicted principal component time series of the former maintaining high correlation skill and small ensemble spread with all lead months whereas the latter shows significant degradation in both measures with lead-time. A composite analysis for the ASM rainfall anomalies of all warm ENSO events in this period substantiates the finding that the ASM is more predictable following an ENSO event. The enhanced predictability mainly comes from the evolution of the warm SST anomalies over the Indian Ocean in the spring of the ENSO maturing phases and the persistence of the anomalous high sea surface pressure over the western Pacific in the subsequent summer, which the hindcasts are able to capture reasonably well. The results also show that the ensemble initialization with multiple ocean analyses improves the CFSv2's prediction skill of both ENSO and ASM rainfall. In fact, the skills of the ensemble mean hindcasts initialized from the four different ocean analyses are always equivalent to the best ones initialized from any individual ocean

First results from comparison of rainfall estimations by GPM IMERG with rainfall measurements from the WegenerNet high density network

Science.gov (United States)

Oo, Sungmin; Foelsche, Ulrich; Kirchengast, Gottfried; Fuchsberger, Jürgen

2016-04-01

The research level products of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG "Final" run datasets) were compared with rainfall measurements from the WegenerNet high density network as part of ground validation (GV) projects of GPM missions. The WegenerNet network comprises 151 ground level weather stations in an area of 15 km × 20 km in south-eastern Austria (Feldbach region, ˜46.93° N, ˜15.90° E) designed to serve as a long-term monitoring and validation facility for weather and climate research and applications. While the IMERG provides rainfall estimations every half hour at 0.1° resolution, the WegenerNet network measures rainfall every 5 minutes at around 2 km2 resolution and produces 200 m × 200 m gridded datasets. The study was conducted on the domain of the WegenerNet network; eight IMERG grids are overlapped with the network, two of which are entirely covered by the WegenerNet (40 and 39 stations in each grid). We investigated data from April to September of the years 2014 to 2015; the date of first two years after the launch of the GPM Core Observatory. Since the network has a flexibility to work with various spatial and temporal scales, the comparison could be conducted on average-points to pixel basis at both sub-daily and daily timescales. This presentation will summarize the first results of the comparison and future plans to explore the characteristics of errors in the IMERG datasets.

10 Characterisation of Seasonal Rainfall.cdr

African Journals Online (AJOL)

Administrator

El Nino-South Oscillation (ENSO) phenomenon occurs in the Equatorial Eastern Pacific Ocean and has been noted to ... of crops. There is need for more research attention on the onset of rainfall and ... impacts of adverse weather conditions or.

Long-range forecast of monthly rainfall over India during summer monsoon season using SST in the north Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Sadhuram, Y.

only SS T. Utilizing the rainfall data of Pa r tha - sarathy et al. 6 and SSTA data (5 ? 5 d e- gree grids) of Kaplan et al. 8 , it is found that the SSTA over the AS du r ing winter (DJF ? 1/0 year) in the region 15 ? 20 ?N; 60 ? 70 ?E... and b ). The corr e lations are almost zero du r ing April and May, which is not shown. SSTA during fall in the CEIO is strongly and positively corr e lated with the seasonal and monthly rai n fall. It is w eak during other months (Figure 1 c...

Weather model performance on extreme rainfall events simulation's over Western Iberian Peninsula

Science.gov (United States)

Pereira, S. C.; Carvalho, A. C.; Ferreira, J.; Nunes, J. P.; Kaiser, J. J.; Rocha, A.

2012-08-01

This study evaluates the performance of the WRF-ARW numerical weather model in simulating the spatial and temporal patterns of an extreme rainfall period over a complex orographic region in north-central Portugal. The analysis was performed for the December month of 2009, during the Portugal Mainland rainy season. The heavy rainfall to extreme heavy rainfall periods were due to several low surface pressure's systems associated with frontal surfaces. The total amount of precipitation for December exceeded, in average, the climatological mean for the 1971-2000 time period in +89 mm, varying from 190 mm (south part of the country) to 1175 mm (north part of the country). Three model runs were conducted to assess possible improvements in model performance: (1) the WRF-ARW is forced with the initial fields from a global domain model (RunRef); (2) data assimilation for a specific location (RunObsN) is included; (3) nudging is used to adjust the analysis field (RunGridN). Model performance was evaluated against an observed hourly precipitation dataset of 15 rainfall stations using several statistical parameters. The WRF-ARW model reproduced well the temporal rainfall patterns but tended to overestimate precipitation amounts. The RunGridN simulation provided the best results but model performance of the other two runs was good too, so that the selected extreme rainfall episode was successfully reproduced.

The added value of stochastic spatial disaggregation for short-term rainfall forecasts currently available in Canada

Science.gov (United States)

Gagnon, Patrick; Rousseau, Alain N.; Charron, Dominique; Fortin, Vincent; Audet, René

2017-11-01

Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada's (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Québec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.

Tropical Rainfall Measuring Mission (TRMM) and the Future of Rainfall Estimation from Space

Science.gov (United States)

Kakar, Ramesh; Adler, Robert; Smith, Eric; Starr, David OC. (Technical Monitor)

2001-01-01

Tropical rainfall is important in the hydrological cycle and to the lives and welfare of humans. Three-fourths of the energy that drives the atmospheric wind circulation comes from the latent heat released by tropical precipitation. Recognizing the importance of rain in the tropics, NASA for the U.S.A. and NASDA for Japan have partnered in the design, construction and flight of a satellite mission to measure tropical rainfall and calculate the associated latent heat release. The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on November 27, 1997, and data from all the instruments first became available approximately 30 days after launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms and applications of these results to areas such as Data Assimilation and model initialization. TRMM has reduced the uncertainty of climatological rainfall in tropics by over a factor of two, therefore establishing a standard for comparison with previous data sets and climatologies. It has documented the diurnal variation of precipitation over the oceans, showing a distinct early morning peak and this satellite mission has shown the utility of precipitation information for the improvement of numerical weather forecasts and climate modeling. This paper discusses some promising applications using TRMM data and introduces a measurement concept being discussed by NASA/NASDA and ESA for the future of rainfall estimation from space.

2 minute Southcentral Alaska Elevation Grid

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The 2-minute Southcentral Alaska Elevation Grid provides bathymetric data in ASCII raster format of 2-minute resolution in geographic coordinates. This grid is...

Prediction of monsoon rainfall with a nested grid mesoscale limited ...

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

At the India Meteorological Department (IMD), New Delhi, a 12-level limited area ... namurti et al (1995, 1998) noted that the Florida .... intensifies into monsoon depression giving rise to .... available to us on rainfall over the sea is the INSAT.

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.

U.S. Isostatic Residual Gravity Grid

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — isores.bin - standard grid containing isostatic residual gravity map for U.S. Grid interval = 4 km. Projection is Albers (central meridian = 96 degrees West; base...

An Atlantic influence on Amazon rainfall

Energy Technology Data Exchange (ETDEWEB)

Yoon, Jin-Ho [University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States); Zeng, Ning [University of Maryland, Earth System Science Interdisciplinary Center, College Park, MD (United States); University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States)

2010-02-15

Rainfall variability over the Amazon basin has often been linked to variations in Pacific sea surface temperature (SST), and in particular, to the El Nino/Southern Oscillation (ENSO). However, only a fraction of Amazon rainfall variability can be explained by ENSO. Building upon the recent work of Zeng (Environ Res Lett 3:014002, 2008), here we provide further evidence for an influence on Amazon rainfall from the tropical Atlantic Ocean. The strength of the North Atlantic influence is found to be comparable to the better-known Pacific ENSO connection. The tropical South Atlantic Ocean also shows some influence during the wet-to-dry season transition period. The Atlantic influence is through changes in the north-south divergent circulation and the movement of the ITCZ following warm SST. Therefore, it is strongest in the southern part of the Amazon basin during the Amazon's dry season (July-October). In contrast, the ENSO related teleconnection is through anomalous east-west Walker circulation with largely concentrated in the eastern (lower) Amazon. This ENSO connection is seasonally locked to boreal winter. A complication due to the influence of ENSO on Atlantic SST causes an apparent North Atlantic SST lag of Amazon rainfall. Removing ENSO from North Atlantic SST via linear regression resolves this causality problem in that the residual Atlantic variability correlates well and is in phase with the Amazon rainfall. A strong Atlantic influence during boreal summer and autumn is particularly significant in terms of the impact on the hydro-ecosystem which is most vulnerable during the dry season, as highlighted by the severe 2005 Amazon drought. Such findings have implications for both seasonal-interannual climate prediction and understanding the longer-term changes of the Amazon rainforest. (orig.)

Indian Ocean and Indian summer monsoon: relationships without ENSO in ocean-atmosphere coupled simulations

Science.gov (United States)

Crétat, Julien; Terray, Pascal; Masson, Sébastien; Sooraj, K. P.; Roxy, Mathew Koll

2017-08-01

The relationship between the Indian Ocean and the Indian summer monsoon (ISM) and their respective influence over the Indo-Western North Pacific (WNP) region are examined in the absence of El Niño Southern Oscillation (ENSO) in two partially decoupled global experiments. ENSO is removed by nudging the tropical Pacific simulated sea surface temperature (SST) toward SST climatology from either observations or a fully coupled control run. The control reasonably captures the observed relationships between ENSO, ISM and the Indian Ocean Dipole (IOD). Despite weaker amplitude, IODs do exist in the absence of ENSO and are triggered by a boreal spring ocean-atmosphere coupled mode over the South-East Indian Ocean similar to that found in the presence of ENSO. These pure IODs significantly affect the tropical Indian Ocean throughout boreal summer, inducing a significant modulation of both the local Walker and Hadley cells. This meridional circulation is masked in the presence of ENSO. However, these pure IODs do not significantly influence the Indian subcontinent rainfall despite overestimated SST variability in the eastern equatorial Indian Ocean compared to observations. On the other hand, they promote a late summer cross-equatorial quadrupole rainfall pattern linking the tropical Indian Ocean with the WNP, inducing important zonal shifts of the Walker circulation despite the absence of ENSO. Surprisingly, the interannual ISM rainfall variability is barely modified and the Indian Ocean does not force the monsoon circulation when ENSO is removed. On the contrary, the monsoon circulation significantly forces the Arabian Sea and Bay of Bengal SSTs, while its connection with the western tropical Indian Ocean is clearly driven by ENSO in our numerical framework. Convection and diabatic heating associated with above-normal ISM induce a strong response over the WNP, even in the absence of ENSO, favoring moisture convergence over India.

World Ocean Atlas 2013 (NCEI Accession 0114815)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — World Ocean Atlas 2013 (WOA13) is a set of objectively analyzed (1 degree grid and 1/4 degree grid) climatological fields of in situ temperature, salinity, dissolved...

Rainfall erosivity in the Fukushima Prefecture: implications for radiocesium mobilization and migration

Science.gov (United States)

Laceby, J. Patrick; Chartin, Caroline; Degan, Francesca; Onda, Yuichi; Evrard, Olivier; Cerdan, Olivier; Ayrault, Sophie

2015-04-01

The Fukushima Dai-ichi nuclear power plant (FDNPP) accident in March 2011 led to the fallout of predominantly radiocesium (137Cs and 134Cs) on soils of the Fukushima Prefecture. This radiocesium was primarily fixated to fine soil particles. Subsequently, rainfall and snow melt run-off events result in significant quantities of radiocesium being eroded and transported throughout the coastal catchments and ultimately exported to the Pacific Ocean. Erosion models, such as the Universal Soil Loss Equation (USLE), relate rainfall directly to soil erosion in that an increase in rainfall one month will directly result in a proportional increase in sediment generation. Understanding the rainfall regime of the region is therefore fundamental to modelling and predicting long-term radiocesium export. Here, we analyze rainfall data for ~40 stations within a 100 km radius of the FDNPP. First we present general information on the rainfall regime in the region based on monthly and annual rainfall totals. Second we present general information on rainfall erosivity, the R-factor of the USLE equation and its relationship to the general rainfall data. Third we examine rainfall trends over the last 100 years at several of the rainfall stations to understand temporal trends and whether ~20 years of data is sufficient to calculate the R-factor for USLE models. Fourth we present monthly R-factor maps for the Fukushima coastal catchments impacted by the FDNPP accident. The variability of the rainfall in the region, particularly during the typhoon season, is likely resulting in a similar variability in the transfer and migration of radiocesium throughout the coastal catchments of the Fukushima Prefecture. Characterizing the region's rainfall variability is fundamental to modelling sediment and the concomitant radiocesium migration and transfer throughout these catchments and ultimately to the Pacific Ocean.

Bathymetric Position Index (BPI) Structures 20 m grid derived from gridded bathymetry of Brooks Banks, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (20 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Brooks Banks, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of Kure Atoll, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Zones 20 m grid derived from gridded bathymetry of Brooks Banks, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (20 m cell size) multibeam bathymetry, collected aboard NOAA...

An Overview of Rainfall-Runoff Model Types

Science.gov (United States)

This report explores rainfall-runoff models, their generation methods, and the categories under which they fall. Runoff plays an important role in the hydrological cycle by returning excess precipitation to the oceans and controlling how much water flows into stream systems. Mode...

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Kure Atoll, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard R/V...

Validation of satellite daily rainfall estimates in complex terrain of Bali Island, Indonesia

Science.gov (United States)

Rahmawati, Novi; Lubczynski, Maciek W.

2017-11-01

Satellite rainfall products have different performances in different geographic regions under different physical and climatological conditions. In this study, the objective was to select the most reliable and accurate satellite rainfall products for specific, environmental conditions of Bali Island. The performances of four spatio-temporal satellite rainfall products, i.e., CMORPH25, CMORPH8, TRMM, and PERSIANN, were evaluated at the island, zonation (applying elevation and climatology as constraints), and pixel scales, using (i) descriptive statistics and (ii) categorical statistics, including bias decomposition. The results showed that all the satellite products had low accuracy because of spatial scale effect, daily resolution and the island complexity. That accuracy was relatively lower in (i) dry seasons and dry climatic zones than in wet seasons and wet climatic zones; (ii) pixels jointly covered by sea and mountainous land than in pixels covered by land or by sea only; and (iii) topographically diverse than uniform terrains. CMORPH25, CMORPH8, and TRMM underestimated and PERSIANN overestimated rainfall when comparing them to gauged rain. The CMORPH25 had relatively the best performance and the PERSIANN had the worst performance in the Bali Island. The CMORPH25 had the lowest statistical errors, the lowest miss, and the highest hit rainfall events; it also had the lowest miss rainfall bias and was relatively the most accurate in detecting, frequent in Bali, ≤ 20 mm day-1 rain events. Lastly, the CMORPH25 coarse grid better represented rainfall events from coastal to inlands areas than other satellite products, including finer grid CMORPH8.

2.5-min gravity grid of N. America

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The dgrav gridded data set was produced by NGDC by regridding the Decade of North American (DNAG) 6-km gravity grid of N. America. A grid cell dimension of 2.5...

Impacts of the ENSO Modoki and other Tropical Indo-Pacific Climate-Drivers on African Rainfall.

Science.gov (United States)

Preethi, B; Sabin, T P; Adedoyin, J A; Ashok, K

2015-11-16

The study diagnoses the relative impacts of the four known tropical Indo-Pacific drivers, namely, El Niño Southern Oscillation (ENSO), ENSO Modoki, Indian Ocean Dipole (IOD), and Indian Ocean Basin-wide mode (IOBM) on African seasonal rainfall variability. The canonical El Niño and El Niño Modoki are in general associated with anomalous reduction (enhancement) of rainfall in southern (northern) hemispheric regions during March-May season. However, both the El Niño flavours anomalously reduce the northern hemispheric rainfall during June-September. Interestingly, during boreal spring and summer, in many regions, the Indian Ocean drivers have influences opposite to those from tropical Pacific drivers. On the other hand, during the October-December season, the canonical El Niño and/or positive IOD are associated with an anomalous enhancement of rainfall in the Eastern Africa, while the El Niño Modoki events are associated with an opposite impact. In addition to the Walker circulation changes, the Indo-Pacific drivers influence the African rainfall through modulating jet streams. During boreal summer, the El Niño Modoki and canonical El Niño (positive IOD) tend to weaken (strengthen) the tropical easterly jet, and result in strengthening (weakening) and southward shift of African easterly jet. This anomalously reduces (enhances) rainfall in the tropical north, including Sahelian Africa.

Evaluation of different gridded rainfall datasets for rainfed wheat yield prediction in an arid environment

Science.gov (United States)

Lashkari, A.; Salehnia, N.; Asadi, S.; Paymard, P.; Zare, H.; Bannayan, M.

2018-05-01

The accuracy of daily output of satellite and reanalysis data is quite crucial for crop yield prediction. This study has evaluated the performance of APHRODITE (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation), PERSIANN (Rainfall Estimation from Remotely Sensed Information using Artificial Neural Networks), TRMM (Tropical Rainfall Measuring Mission), and AgMERRA (The Modern-Era Retrospective Analysis for Research and Applications) precipitation products to apply as input data for CSM-CERES-Wheat crop growth simulation model to predict rainfed wheat yield. Daily precipitation output from various sources for 7 years (2000-2007) was obtained and compared with corresponding ground-observed precipitation data for 16 ground stations across the northeast of Iran. Comparisons of ground-observed daily precipitation with corresponding data recorded by different sources of datasets showed a root mean square error (RMSE) of less than 3.5 for all data. AgMERRA and APHRODITE showed the highest correlation (0.68 and 0.87) and index of agreement (d) values (0.79 and 0.89) with ground-observed data. When daily precipitation data were aggregated over periods of 10 days, the RMSE values, r, and d values increased (30, 0.8, and 0.7) for AgMERRA, APHRODITE, PERSIANN, and TRMM precipitation data sources. The simulations of rainfed wheat leaf area index (LAI) and dry matter using various precipitation data, coupled with solar radiation and temperature data from observed ones, illustrated typical LAI and dry matter shape across all stations. The average values of LAImax were 0.78, 0.77, 0.74, 0.70, and 0.69 using PERSIANN, AgMERRA, ground-observed precipitation data, APHRODITE, and TRMM. Rainfed wheat grain yield simulated by using AgMERRA and APHRODITE daily precipitation data was highly correlated (r 2 ≥ 70) with those simulated using observed precipitation data. Therefore, gridded data have high potential to be used to supply lack of data and

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Wake Island, West Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of Ni'ihau Island, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Zones 60 m grid derived from gridded bathymetry of Rota Island, Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (60 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Structures 60 m grid derived from gridded bathymetry of Wake Island, West Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (60 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of French Frigate Shoals, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Ni'ihau Island, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of French Frigate Shoals, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Zones 60 m grid derived from gridded bathymetry of Wake Island, West Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (60 m cell size) multibeam bathymetry, collected aboard R/V...

Development of a gridded meteorological dataset over Java island, Indonesia 1985-2014.

Science.gov (United States)

Yanto; Livneh, Ben; Rajagopalan, Balaji

2017-05-23

We describe a gridded daily meteorology dataset consisting of precipitation, minimum and maximum temperature over Java Island, Indonesia at 0.125°×0.125° (~14 km) resolution spanning 30 years from 1985-2014. Importantly, this data set represents a marked improvement from existing gridded data sets over Java with higher spatial resolution, derived exclusively from ground-based observations unlike existing satellite or reanalysis-based products. Gap-infilling and gridding were performed via the Inverse Distance Weighting (IDW) interpolation method (radius, r, of 25 km and power of influence, α, of 3 as optimal parameters) restricted to only those stations including at least 3,650 days (~10 years) of valid data. We employed MSWEP and CHIRPS rainfall products in the cross-validation. It shows that the gridded rainfall presented here produces the most reasonable performance. Visual inspection reveals an increasing performance of gridded precipitation from grid, watershed to island scale. The data set, stored in a network common data form (NetCDF), is intended to support watershed-scale and island-scale studies of short-term and long-term climate, hydrology and ecology.

Rainfall Distributions in Sri Lanka in Time and Space: An Analysis Based on Daily Rainfall Data

Directory of Open Access Journals (Sweden)

T. P. Burt

2014-09-01

Full Text Available Daily rainfall totals are analyzed for the main agro-climatic zones of Sri Lanka for the period 1976–2006. The emphasis is on daily rainfall rather than on longer-period totals, in particular the number of daily falls exceeding given threshold totals. For one station (Mapalana, where a complete daily series is available from 1950, a longer-term perspective on changes over half a century is provided. The focus here is particularly on rainfall in March and April, given the sensitivity of agricultural decisions to early southwest monsoon rainfall at the beginning of the Yala cultivation season but other seasons are also considered, in particular the northeast monsoon. Rainfall across Sri Lanka over three decades is investigated in relation to the main atmospheric drivers known to affect climate in the region: sea surface temperatures in the Pacific and Indian Oceans, of which the former are shown to be more important. The strong influence of El Niño and La Niña phases on various aspects of the daily rainfall distribution in Sri Lanka is confirmed: positive correlations with Pacific sea-surface temperatures during the north east monsoon and negative correlations at other times. It is emphasized in the discussion that Sri Lanka must be placed in its regional context and it is important to draw on regional-scale research across the Indian subcontinent and the Bay of Bengal.

Regions Subject to Rainfall Oscillation in the 5–10 Year Band

Directory of Open Access Journals (Sweden)

Jean-Louis Pinault

2018-01-01

Full Text Available The decadal oscillation of rainfall in Europe that has been observed since the end of the 20th century is a phenomenon well known to climatologists. Consequences are considerable because the succession of wet or dry years produces floods or, inversely, droughts. Moreover, much research has tried to answer the question about the possible link between the frequency and the intensity of extra-tropical cyclones, which are particularly devastating, and global warming. This work aims at providing an exhaustive description of the rainfall oscillation in the 5–10 year band during one century on a planetary scale. It is shown that the rainfall oscillation results from baroclinic instabilities over the oceans. For that, a joint analysis of the amplitude and the phase of sea surface temperature anomalies and rainfall anomalies is performed, which discloses the mechanisms leading to the alternation of high and low atmospheric pressure systems. For a prospective purpose, some milestones are suggested on a possible link with very long-period Rossby waves in the oceans.

Determination of mean rainfall from the Special Sensor Microwave/Imager (SSM/I) using a mixed lognormal distribution

Science.gov (United States)

Berg, Wesley; Chase, Robert

1992-01-01

Global estimates of monthly, seasonal, and annual oceanic rainfall are computed for a period of one year using data from the Special Sensor Microwave/Imager (SSM/I). Instantaneous rainfall estimates are derived from brightness temperature values obtained from the satellite data using the Hughes D-matrix algorithm. The instantaneous rainfall estimates are stored in 1 deg square bins over the global oceans for each month. A mixed probability distribution combining a lognormal distribution describing the positive rainfall values and a spike at zero describing the observations indicating no rainfall is used to compute mean values. The resulting data for the period of interest are fitted to a lognormal distribution by using a maximum-likelihood. Mean values are computed for the mixed distribution and qualitative comparisons with published historical results as well as quantitative comparisons with corresponding in situ raingage data are performed.

Bathymetric Position Index (BPI) Zones 60 m grid derived from gridded bathymetry of the U.S. Territory of Guam.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (60 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of Pearl and Hermes Atoll, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Contribution of Tropical Cyclones to the North Pacific Climatological Rainfall as Observed from Satellites.

Science.gov (United States)

Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.

2000-10-01

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations for an 11-yr period. These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and interannual distribution of the North Pacific Ocean total rainfall during June-November when tropical cyclones are most important.To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from passive microwave satellite observations within 444-km radius of the center of those North Pacific tropical cyclones that reached storm stage and greater. These rain-rate observations are converted to monthly rainfall amounts and then compared with those for nontropical cyclone systems.The main results of this study indicate that 1) tropical cyclones contribute 7% of the rainfall to the entire domain of the North Pacific during the tropical cyclone season and 12%, 3%, and 4% when the study area is limited to, respectively, the western, central, and eastern third of the ocean; 2) the maximum tropical cyclone rainfall is poleward (5°-10° latitude depending on longitude) of the maximum nontropical cyclone rainfall; 3) tropical cyclones contribute a maximum of 30% northeast of the Philippine Islands and 40% off the lower Baja California coast; 4) in the western North Pacific, the tropical cyclone rainfall lags the total rainfall by approximately two months and shows seasonal latitudinal variation following the Intertropical Convergence Zone; and 5) in general, tropical cyclone rainfall is enhanced during the El Niño years by warm SSTs in the eastern North Pacific and by the monsoon trough in the western and central North Pacific.

Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

Science.gov (United States)

Chawla, Ila; Osuri, Krishna K.; Mujumdar, Pradeep P.; Niyogi, Dev

2018-02-01

Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15-18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor-Yamada-Janjic PBL and Betts-Miller-Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation

Origins and interrelationship of Intraseasonal rainfall variations around the Maritime Continent during boreal winter

Science.gov (United States)

Cao, Xi; Wu, Renguang

2018-04-01

Large intraseasonal rainfall variations are identified over the southern South China Sea (SSCS), tropical southeastern Indian Ocean (SEIO), and east coast of the Philippines (EPHI) in boreal winter. The present study contrasts origins and propagations and investigates interrelations of intraseasonal rainfall variations on the 10-20- and 30-60-day time scales in these regions. Different origins are identified for intraseasonal rainfall anomalies over the SSCS, SEIO, and EPHI on both time scales. On the 10-20-day time scale, strong northerly or northeasterly wind anomalies related to the East Asian winter monsoon (EAWM) play a major role in intraseasonal rainfall variations over the SSCS and EPHI. On the 30-60-day time scale, both the intraseasonal signal from the tropical Indian Ocean and the EAWM-related wind anomalies contribute to intraseasonal rainfall variations over the SSCS, whereas the EAWM-related wind anomalies have a major contribution to the intraseasonal rainfall variations over the EPHI. No relation is detected between the intraseasonal rainfall variations over the SEIO and the EAWM on both the 10-20-day and 30-60-day time scales. The anomalies associated with intraseasonal rainfall variations over the SSCS and EPHI propagate northwestward and northeastward, respectively, on the 10-20- and 30-60-day time scales. The intraseasonal rainfall anomalies display northwestward and northward propagation over the Bay of Bengal, respectively, on the 10-20- and 30-60-day time scales.

Ocean eddies and climate predictability.

Science.gov (United States)

Kirtman, Ben P; Perlin, Natalie; Siqueira, Leo

2017-12-01

A suite of coupled climate model simulations and experiments are used to examine how resolved mesoscale ocean features affect aspects of climate variability, air-sea interactions, and predictability. In combination with control simulations, experiments with the interactive ensemble coupling strategy are used to further amplify the role of the oceanic mesoscale field and the associated air-sea feedbacks and predictability. The basic intent of the interactive ensemble coupling strategy is to reduce the atmospheric noise at the air-sea interface, allowing an assessment of how noise affects the variability, and in this case, it is also used to diagnose predictability from the perspective of signal-to-noise ratios. The climate variability is assessed from the perspective of sea surface temperature (SST) variance ratios, and it is shown that, unsurprisingly, mesoscale variability significantly increases SST variance. Perhaps surprising is the fact that the presence of mesoscale ocean features even further enhances the SST variance in the interactive ensemble simulation beyond what would be expected from simple linear arguments. Changes in the air-sea coupling between simulations are assessed using pointwise convective rainfall-SST and convective rainfall-SST tendency correlations and again emphasize how the oceanic mesoscale alters the local association between convective rainfall and SST. Understanding the possible relationships between the SST-forced signal and the weather noise is critically important in climate predictability. We use the interactive ensemble simulations to diagnose this relationship, and we find that the presence of mesoscale ocean features significantly enhances this link particularly in ocean eddy rich regions. Finally, we use signal-to-noise ratios to show that the ocean mesoscale activity increases model estimated predictability in terms of convective precipitation and atmospheric upper tropospheric circulation.

Rugosity grid derived from gridded bathymetry of Kure Atoll, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, and IKONOS derived depths using the Benthic...

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Pearl and Hermes Atoll, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard R/V...

Gridded bathymetry of Penguin Bank, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry (5 m cell size) of Penguin Bank, Hawaii, USA. The netCDF grid and ArcGIS ASCII file include multibeam bathymetry from the Simrad EM3002d, and...

Characterisation of Seasonal Rainfall for Cropping Schedules ...

African Journals Online (AJOL)

El Nino-South Oscillation (ENSO) phenomenon occurs in the Equatorial Eastern Pacific Ocean and has been noted to account significantly for rainfall variability in many parts of the world, particularly tropical regions. This variability is very important in rainfed crop production and needs to be well understood. Thirty years of ...

Underwater Acoustic Measurements to Estimate Wind and Rainfall in the Mediterranean Sea

Directory of Open Access Journals (Sweden)

Sara Pensieri

2015-01-01

Full Text Available Oceanic ambient noise measurements can be analyzed to obtain qualitative and quantitative information about wind and rainfall phenomena over the ocean filling the existing gap of reliable meteorological observations at sea. The Ligurian Sea Acoustic Experiment was designed to collect long-term synergistic observations from a passive acoustic recorder and surface sensors (i.e., buoy mounted rain gauge and anemometer and weather radar to support error analysis of rainfall rate and wind speed quantification techniques developed in past studies. The study period included combination of high and low wind and rainfall episodes and two storm events that caused two floods in the vicinity of La Spezia and in the city of Genoa in 2011. The availability of high resolution in situ meteorological data allows improving data processing technique to detect and especially to provide effective estimates of wind and rainfall at sea. Results show a very good correspondence between estimates provided by passive acoustic recorder algorithm and in situ observations for both rainfall and wind phenomena and demonstrate the potential of using measurements provided by passive acoustic instruments in open sea for early warning of approaching coastal storms, which for the Mediterranean coastal areas constitutes one of the main causes of recurrent floods.

Location-Based Rainfall Nowcasting Service for Public

Science.gov (United States)

Woo, Wang-chun

2013-04-01

The Hong Kong Observatory has developed the "Short-range Warning of Intense Rainstorms in Localized Systems (SWIRLS)", a radar-based rainfall nowcasting system originally to support forecasters in rainstorm warning and severe weather forecasting such as hail, lightning and strong wind gusts in Hong Kong. The system has since been extended to provide rainfall nowcast service direct for the public in recent years. Following the launch of "Rainfall Nowcast for the Pearl River Delta Region" service provided via a Geographical Information System (GIS) platform in 2008, a location-based rainfall nowcast service served through "MyObservatory", a smartphone app for iOS and Android developed by the Observatory, debuted in September 2012. The new service takes advantage of the capability of smartphones to detect own locations and utilizes the quantitative precipitation forecast (QPF) from SWIRLS to provide location-based rainfall nowcast to the public. The conversion of radar reflectivity data (at 2 or 3 km above ground) to rainfall in SWIRLS is based on the Z-R relationship (Z=aRb) with dynamical calibration of the coefficients a and b determined using real-time rain gauge data. Adopting the "Multi-scale Optical-flow by Variational Analysis (MOVA)" scheme to track the movement of radar echoes and Semi-Lagrangian Advection (SLA) scheme to extrapolate their movement, the system is capable of producing QPF for the next six hours in a grid of 480 x 480 that covers a domain of 256 km x 256 km once every 6 minutes. Referencing the closest point in a resampled 2-km grid over the territory of Hong Kong, a prediction as to whether there will be rainfall exceeding 0.5 mm in every 30 minute intervals for the next two hours at users' own or designated locations are made available to the users in both textual and graphical format. For those users who have opted to receive notifications, a message would pop up on the user's phone whenever rain is predicted in the next two hours in a user

Final Report for DOE grant DE-FG02-07ER64432 "New Grid and Discretization Technologies for Ocean and Ice Simulations"

Energy Technology Data Exchange (ETDEWEB)

Gunzburger, Max

2013-03-12

The work reported is in pursuit of these goals: high-quality unstructured, non-uniform Voronoi and Delaunay grids; improved finite element and finite volume discretization schemes; and improved finite element and finite volume discretization schemes. These are sought for application to spherical and three-dimensional applications suitable for ocean, atmosphere, ice-sheet, and other climate modeling applications.

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Tau Island, Territory of American Samoa, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard R/V...

Rugosity grid derived from gridded bathymetry of Ni'ihau Island, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA ship Hi'ialakai and R/V AHI using the Benthic Terrain Modeler with...

Rugosity grid derived from gridded bathymetry of French Frigate Shoals, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Sensitivity of Horn of Africa Rainfall to Regional Sea Surface Temperature Forcing

Directory of Open Access Journals (Sweden)

Zewdu T. Segele

2015-05-01

Full Text Available The Abdus Salam International Center for Theoretical Physics (ICTP version 4.4 Regional Climate Model (RegCM4 is used to investigate the rainfall response to cooler/warmer sea surface temperature anomaly (SSTA forcing in the Indian and Atlantic Oceans. The effect of SSTA forcing in a specific ocean basin is identified by ensemble, averaging 10 individual simulations in which a constant or linearly zonally varying SSTA is prescribed in individual basins while specifying the 1971–2000 monthly varying climatological sea surface temperature (SST across the remaining model domain. The nonlinear rainfall response to SSTA amplitude also is investigated by separately specifying +1K, +2K, and +4K SSTA forcing in the Atlantic and Indian Oceans. The simulation results show that warm SSTs over the entire Indian Ocean produce drier conditions across the larger Blue Nile catchment, whereas warming ≥ +2K generates large positive rainfall anomalies exceeding 10 mm·day−1 over drought prone regions of Northeastern Ethiopia. However, the June–September rainy season tends to be wetter (drier when the SST warming (cooling is limited to either the Northern or Southern Indian Ocean. Wet rainy seasons generally are characterized by deepening of the monsoon trough, east of 40°E, intensification of the Mascarene high, strengthening of the Somali low level jet and the tropical easterly jet, enhanced zonal and meridional vertically integrated moisture fluxes, and steeply vertically decreasing moist static energy. The opposite conditions hold for dry monsoon seasons.

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Rose Atoll, Territory of American Samoa, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard R/V AHI...

Mosaic of gridded multibeam bathymetry, gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tinian Island, Commonwealth of the Northern Marianas Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size)...

5-minute Gridded Global Relief Data (ETOPO5)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Earth topography five minute grid (ETOPO5) is a gridded data base of worldwide elevations derived from several sources at a resolution of 5 minutes of latitude and...

U.S. Topographic Grid

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — isotop.bin - topographic data for conterminous U.S. projected on an 8 km grid. Projection is Albers, central meridian = 96 degrees West, base latitude = 0 degrees...

Rugosity grid derived from gridded bathymetry of Apra Harbor, Guam U.S. Territory

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (1 m cell size) multibeam bathymetry, collected aboard the Survey Vessel Swamp Fox using the Terrain Modeler with rugosity methods...

Bathymetric Position Index (BPI) Structures 40 m grid derived from gridded bathymetry of Howland Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (40 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 20 m grid derived from gridded bathymetry of Johnston Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (20 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 20 m grid derived from gridded bathymetry of Baker Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (20 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of Ta'u Island, Territory of American Samoa, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Topographic relationships for design rainfalls over Australia

Science.gov (United States)

Johnson, F.; Hutchinson, M. F.; The, C.; Beesley, C.; Green, J.

2016-02-01

for most of the Australian continent, extreme rainfall is closely aligned with elevation, but in areas with high topographic relief the impacts of topography on rainfall extremes are more complex. The interpolated extreme rainfall statistics, using no data transformation, have been used by the Australian Bureau of Meteorology to produce new IDF data for the Australian continent. The comprehensive methods presented for the evaluation of gridded design rainfall statistics will be useful for similar studies, in particular the importance of balancing the need for a continentally-optimum solution that maintains sufficient definition at the local scale.

Spatio-temporal trends of rainfall across Indian river basins

Science.gov (United States)

Bisht, Deepak Singh; Chatterjee, Chandranath; Raghuwanshi, Narendra Singh; Sridhar, Venkataramana

2018-04-01

Daily gridded high-resolution rainfall data of India Meteorological Department at 0.25° spatial resolution (1901-2015) was analyzed to detect the trend in seasonal, annual, and maximum cumulative rainfall for 1, 2, 3, and 5 days. The present study was carried out for 85 river basins of India during 1901-2015 and pre- and post-urbanization era, i.e., 1901-1970 and 1971-2015, respectively. Mann-Kendall ( α = 0.05) and Theil-Sen's tests were employed for detecting the trend and percentage of change over the period of time, respectively. Daily extreme rainfall events, above 95 and 99 percentile threshold, were also analyzed to detect any trend in their magnitude and number of occurrences. The upward trend was found for the majority of the sub-basins for 1-, 2-, 3-, and 5-day maximum cumulative rainfall during the post-urbanization era. The magnitude of extreme threshold events is also found to be increasing in the majority of the river basins during the post-urbanization era. A 30-year moving window analysis further revealed a widespread upward trend in a number of extreme threshold rainfall events possibly due to urbanization and climatic factors. Overall trends studied against intra-basin trend across Ganga basin reveal the mixed pattern of trends due to inherent spatial heterogeneity of rainfall, therefore, highlighting the importance of scale for such studies.

Aragonite saturation state gridded to 1x1 degree latitude and longitude at depth levels of 0, 50, 100, 200, 500, 1000, 2000, 3000, and 4000 meters in the global oceans (NCEI Accession 0139360)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This archival package contains gridded data of aragonite saturation state across the global oceans (spatial distributions with a resolution of 1x1 degree latitude...

Slope grid derived from gridded bathymetry of Apra Harbor, Guam U.S. Territory

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (1 m cell size) multibeam bathymetry, collected aboard the Survey Vessel Swamp Fox. Cell values reflect the maximum rate of change (in...

Slope grid (5 m) derived from gridded bathymetry of US Territory of Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (5 m cell size) bathymetry from four sources: Multibeam bathymetry collected by Coral Reef Ecosystem Division aboard NOAA R/V AHI, and...

Rugosity 5m grid derived from gridded bathymetry of Brooks Banks, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA ship Hi'ialakai and R/V AHI using the Benthic Terrain Modeler with...

Model simulations of rainfall over southern Africa and its eastern ...

African Journals Online (AJOL)

2016-01-01

Jan 1, 2016 ... Rainfall simulations over southern and tropical Africa in the form of low-resolution Atmospheric Model ..... provision of sea-surface temperatures and sea-ice fields of a host ...... with variability of the Atlantic Ocean. Bull.

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

KAUST Repository

Konda, Gopinadh; Chowdary, Jasti S.; Srinivas, G; Gnanaseelan, C; Parekh, Anant; Attada, Raju; Rama Krishna, S S V S

2018-01-01

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

Science.gov (United States)

Konda, Gopinadh; Chowdary, J. S.; Srinivas, G.; Gnanaseelan, C.; Parekh, Anant; Attada, Raju; Rama Krishna, S. S. V. S.

2018-06-01

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

KAUST Repository

Konda, Gopinadh

2018-05-22

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

NOAA Climate Data Record (CDR) of Gridded Satellite Data from ISCCP B1 (GridSat-B1) Infrared Channel Brightness Temperature, Version 2

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Gridded Satellite (GridSat-B1) data provides a uniform set of quality controlled geostationary satellite observations for the visible, infrared window and...

An Updated TRMM Composite Climatology of Tropical Rainfall and Its Validation

Science.gov (United States)

Wang, Jian-Jian; Adler, Robert F.; Huffman, George; Bolvin, David

2013-01-01

An updated 15-yr Tropical Rainfall Measuring Mission (TRMM) composite climatology (TCC) is presented and evaluated. This climatology is based on a combination of individual rainfall estimates made with data from the primaryTRMMinstruments: theTRMM Microwave Imager (TMI) and the precipitation radar (PR). This combination climatology of passive microwave retrievals, radar-based retrievals, and an algorithm using both instruments simultaneously provides a consensus TRMM-based estimate of mean precipitation. The dispersion of the three estimates, as indicated by the standard deviation sigma among the estimates, is presented as a measure of confidence in the final estimate and as an estimate of the uncertainty thereof. The procedures utilized by the compositing technique, including adjustments and quality-control measures, are described. The results give a mean value of the TCC of 4.3mm day(exp -1) for the deep tropical ocean beltbetween 10 deg N and 10 deg S, with lower values outside that band. In general, the TCC values confirm ocean estimates from the Global Precipitation Climatology Project (GPCP) analysis, which is based on passive microwave results adjusted for sampling by infrared-based estimates. The pattern of uncertainty estimates shown by sigma is seen to be useful to indicate variations in confidence. Examples include differences between the eastern and western portions of the Pacific Ocean and high values in coastal and mountainous areas. Comparison of the TCC values (and the input products) to gauge analyses over land indicates the value of the radar-based estimates (small biases) and the limitations of the passive microwave algorithm (relatively large biases). Comparison with surface gauge information from western Pacific Ocean atolls shows a negative bias (16%) for all the TRMM products, although the representativeness of the atoll gauges of open-ocean rainfall is still in question.

Gridded Data in the Arctic; Benefits and Perils of Publicly Available Grids

Science.gov (United States)

Coakley, B.; Forsberg, R.; Gabbert, R.; Beale, J.; Kenyon, S. C.

2015-12-01

Our understanding of the Arctic Ocean has been hugely advanced by release of gridded bathymetry and potential field anomaly grids. The Arctic Gravity Project grid achieves excellent, near-isotropic coverage of the earth north of 64˚N by combining land, satellite, airborne, submarine, surface ship and ice set-out measurements of gravity anomalies. Since the release of the V 2.0 grid in 2008, there has been extensive icebreaker activity across the Amerasia Basin due to mapping of the Arctic coastal nation's Extended Continental Shelves (ECS). While grid resolution has been steadily improving over time, addition of higher resolution and better navigated data highlights some distortions in the grid that may influence interpretation. In addition to the new ECS data sets, gravity anomaly data has been collected from other vessels; notably the Korean Icebreaker Araon, the Japanese icebreaker Mirai and the German icebreaker Polarstern. Also the GRAV-D project of the US National Geodetic Survey has flown airborne surveys over much of Alaska. These data will be Included in the new AGP grid, which will result in a much improved product when version 3.0 is released in 2015. To make use of these measurements, it is necessary to compile them into a continuous spatial representation. Compilation is complicated by differences in survey parameters, gravimeter sensitivity and reduction methods. Cross-over errors are the classic means to assess repeatability of track measurements. Prior to the introduction of near-universal GPS positioning, positional uncertainty was evaluated by cross-over analysis. GPS positions can be treated as more or less true, enabling evaluation of differences due to contrasting sensitivity, reference and reduction techniques. For the most part, cross-over errors for racks of gravity anomaly data collected since 2008 are less than 0.5 mGals, supporting the compilation of these data with only slight adjustments. Given the different platforms used for various

Bathymetric Position Index (BPI) Zones 10 m grid derived from gridded bathymetry of Sarigan Island, Commonwealth of the Northern Mariana Islands, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Zones 10 m grid derived from gridded bathymetry of Maug Island, Commonwealth of the Northern Mariana Islands, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Zones 10 m grid derived from gridded bathymetry of Asuncion Island, Commonwealth of the Northern Mariana Islands, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry collected aboard NOAA...

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Rota Island, Commonwealth of the Northern Mariana Islands, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Zones 10 m grid derived from gridded bathymetry of Agrihan Island, Commonwealth of the Northern Mariana Islands, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of Ofu and Olosega Islands, Territory of American Samoa, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

World Ocean Atlas 2005, Salinity

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — World Ocean Atlas 2005 (WOA05) is a set of objectively analyzed (1° grid) climatological fields of in situ temperature, salinity, dissolved oxygen, Apparent Oxygen...

World Ocean Atlas 2005, Temperature

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — World Ocean Atlas 2005 (WOA05) is a set of objectively analyzed (1° grid) climatological fields of in situ temperature, salinity, dissolved oxygen, Apparent Oxygen...

Slope 20 m grid derived from gridded bathymetry of Brooks Banks, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (20 m cell size) multibeam bathymetry, collected aboard NOAA ship Hi'ialakai and R/V AHI. Cell values reflect the maximum rate of...

Rugosity grid derived from gridded bathymetry of Pearl and Hermes Atoll, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, and IKONOS derived depths using the Benthic...

Network-derived inhomogeneity in monthly rainfall analyses over western Tasmania

International Nuclear Information System (INIS)

Fawcett, Robert; Trewin, Blair; Barnes-Keoghan, Ian

2010-01-01

Monthly rainfall in the wetter western half of Tasmania was relatively poorly observed in the early to middle parts of the 20th century, and this causes a marked inhomogeneity in the operational gridded monthly rainfall analyses generated by the Australian Bureau of Meteorology up until the end of 2009. These monthly rainfall analyses were generated for the period 1900 to 2009 in two forms; a national analysis at 0.25 0 latitude-longitude resolution, and a southeastern Australia regional analysis at 0.1 0 resolution. For any given month, they used all the monthly data from the standard Bureau rainfall gauge network available in the Australian Data Archive for Meteorology. Since this network has changed markedly since Federation (1901), there is obvious scope for network-derived inhomogeneities in the analyses. In this study, we show that the topography-resolving techniques of the new Australian Water Availability Project analyses, adopted as the official operational analyses from the start of 2010, substantially diminish those inhomogeneities, while using largely the same observation network. One result is an improved characterisation of recent rainfall declines across Tasmania. The new analyses are available at two resolutions, 0.25 0 and 0.05 0 .

Regional frequency analysis of short duration rainfall extremes using gridded daily rainfall data as co-variate

DEFF Research Database (Denmark)

Madsen, H.; Gregersen, Ida Bülow; Rosbjerg, Dan

2017-01-01

with daily measurements. The Poisson rate is positively correlated to the mean annual precipitation for all durations considered (1 min to 48 hours). The mean intensity can be assumed constant over Denmark for durations up to 1 hour. For durations larger than 1 hour the mean intensity is significantly...... correlated to the mean extreme daily precipitation. A Generalised Pareto distribution with a regional constant shape parameter is adopted. Compared to previous regional studies in Denmark a general increase in extreme rainfall intensity for durations up to 1 hour is found, whereas for larger durations both...

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Ofu and Olosega Islands, Territory of American Samoa, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard R/V...

Rain-shadow: An area harboring "Gray Ocean" clouds

Science.gov (United States)

Padmakumari, B.; Maheskumar, R. S.; Harikishan, G.; Morwal, S. B.; Kulkarni, J. R.

2018-06-01

The characteristics of monsoon convective clouds over the rain-shadow region of north peninsular India have been investigated using in situ aircraft cloud microphysical observations collected during Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX). The parameters considered for characterization are: liquid water content (LWC), cloud vertical motion (updraft, downdraft: w), cloud droplet number concentration (CDNC) and effective radius (Re). The results are based on 15 research flights which were conducted from the base station Hyderabad during summer monsoon season. The clouds studied were developing congestus. The clouds have low CDNC and low updraft values resembling the oceanic convective clouds. The super-saturation in clouds is found to be low (≤0.2%) due to low updrafts. The land surface behaves like ocean surface during monsoon as deduced from Bowen ratio. Microphysically the clouds showed oceanic characteristics. However, these clouds yield low rainfall due to their low efficiency (mean 14%). The cloud parameters showed a large variability; hence their characteristic values are reported in terms of median values. These values will serve the numerical models for rainfall simulations over the region and also will be useful as a scientific basis for cloud seeding operations to increase the rainfall efficiency. The study revealed that monsoon convective clouds over the rain-shadow region are of oceanic type over the gray land, and therefore we christen them as "Gray Ocean" clouds.

Evaluating the Impact of Localized GCM Grid Refinement on Regional Tropical Cyclone Climatology and Synoptic Variability using Variable-Resolution CAM-SE

Science.gov (United States)

Zarzycki, C.; Jablonowski, C.

2013-12-01

Using General Circulation Models (GCMs) to resolve sub-synoptic features in climate simulations has traditionally been difficult due to a multitude of atmospheric processes operating at subgrid scales requiring significant parameterization. For example, at traditional GCM horizontal grid resolutions of 50-300 km, tropical cyclones are generally under-resolved. This paper explores a novel variable-resolution global modeling approach that allows for high spatial resolutions in areas of interest, such as low-latitude ocean basins where tropical cyclogenesis occurs. Such multi-resolution GCM designs allow for targeted use of computing resources at the regional level while maintaining a globally-continuous model domain and may serve to bridge the gap between GCMs with uniform grids and boundary-forced limited area models. A statically-nested, variable-resolution option has recently been introduced into the Community Atmosphere Model's (CAM) Spectral Element (SE) dynamical core. A 110 km CAM-SE grid with a 28 km nest over the Atlantic Ocean has been coupled to land, ocean, and ice components within the Community Earth System Model (CESM). We present the results of a multi-decadal climate simulation using Atmospheric Model Intercomparison Project (AMIP) protocols, which force the model with historical sea surface temperatures and airborne chemical species. To investigate whether refinement improves the representation of tropical cyclones, we compare Atlantic storm statistics to observations with specific focus paid to intensity profiles and track densities. The resolution dependance of both cyclone structure and objective detection between refined and unrefined basins is explored. In addition, we discuss the potential impact of using variable-resolution grids on the large-scale synoptic interannual variability by comparing refined grid simulations to reanalysis data as well as an unrefined, globally-uniform CAM-SE simulation with identical forcing. We also evaluate the

Rugosity grid (5 m) derived from gridded bathymetry of the US Territory of Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) bathymetry from four sources: Multibeam bathymetry collected by Coral Reef Ecosystem Division aboard NOAA R/V AHI,...

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Supply Reef, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Maug Island, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Alamagan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of Rota Island, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Guguan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Pagan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Asuncion Island, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry...

60 m Rugosity grid derived from gridded bathymetry of Wake Island, West Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (60 m cell size) multibeam bathymetry, collected aboard NOAA ship Hi'ialakai and R/V AHI using the Benthic Terrain Modeler with...

CRED Rugosity grid derived from gridded bathymetry of Tutuila Island, American Samoa, South Pacific

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Rugosity 60 m grid derived from gridded bathymetry of Rota Island, Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (60 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Tropical intraseasonal rainfall variability in the CFSR

Energy Technology Data Exchange (ETDEWEB)

Wang, Jiande [I.M. System Group Inc. at NOAA/NCEP/EMC, Camp Springs, MD (United States); Wang, Wanqiu [NOAA/NCEP/CPC, Camp Springs, MD (United States); Fu, Xiouhua [University of Hawaii at Manoa, IPRC, SOEST, Honolulu, HI (United States); Seo, Kyong-Hwan [Pusan National University, Department of Atmospheric Sciences, Busan (Korea, Republic of)

2012-06-15

While large-scale circulation fields from atmospheric reanalyses have been widely used to study the tropical intraseasonal variability, rainfall variations from the reanalyses are less focused. Because of the sparseness of in situ observations available in the tropics and strong coupling between convection and large-scale circulation, the accuracy of tropical rainfall from the reanalyses not only measures the quality of reanalysis rainfall but is also to some extent indicative of the accuracy of the circulations fields. This study analyzes tropical intraseasonal rainfall variability in the recently completed NCEP Climate Forecast System Reanalysis (CFSR) and its comparison with the widely used NCEP/NCAR reanalysis (R1) and NCEP/DOE reanalysis (R2). The R1 produces too weak rainfall variability while the R2 generates too strong westward propagation. Compared with the R1 and R2, the CFSR produces greatly improved tropical intraseasonal rainfall variability with the dominance of eastward propagation and more realistic amplitude. An analysis of the relationship between rainfall and large-scale fields using composites based on Madden-Julian Oscillation (MJO) events shows that, in all three NCEP reanalyses, the moisture convergence leading the rainfall maximum is near the surface in the western Pacific but is above 925 hPa in the eastern Indian Ocean. However, the CFSR produces the strongest large-scale convergence and the rainfall from CFSR lags the column integrated precipitable water by 1 or 2 days while R1 and R2 rainfall tends to lead the respective precipitable water. Diabatic heating related to the MJO variability in the CFSR is analyzed and compared with that derived from large-scale fields. It is found that the amplitude of CFSR-produced total heating anomalies is smaller than that of the derived. Rainfall variability from the other two recently produced reanalyses, the ECMWF Re-Analysis Interim (ERAI), and the Modern Era Retrospective-analysis for Research and

Projections of West African summer monsoon rainfall extremes from two CORDEX models

Science.gov (United States)

Akinsanola, A. A.; Zhou, Wen

2018-05-01

Global warming has a profound impact on the vulnerable environment of West Africa; hence, robust climate projection, especially of rainfall extremes, is quite important. Based on two representative concentration pathway (RCP) scenarios, projected changes in extreme summer rainfall events over West Africa were investigated using data from the Coordinated Regional Climate Downscaling Experiment models. Eight (8) extreme rainfall indices (CDD, CWD, r10mm, r20mm, PRCPTOT, R95pTOT, rx5day, and sdii) defined by the Expert Team on Climate Change Detection and Indices were used in the study. The performance of the regional climate model (RCM) simulations was validated by comparing with GPCP and TRMM observation data sets. Results show that the RCMs reasonably reproduced the observed pattern of extreme rainfall over the region and further added significant value to the driven GCMs over some grids. Compared to the baseline period 1976-2005, future changes (2070-2099) in summer rainfall extremes under the RCP4.5 and RCP8.5 scenarios show statistically significant decreasing total rainfall (PRCPTOT), while consecutive dry days and extreme rainfall events (R95pTOT) are projected to increase significantly. There are obvious indications that simple rainfall intensity (sdii) will increase in the future. This does not amount to an increase in total rainfall but suggests a likelihood of greater intensity of rainfall events. Overall, our results project that West Africa may suffer more natural disasters such as droughts and floods in the future.

Observational evidence for the relationship between spring soil moisture and June rainfall over the Indian region

Science.gov (United States)

KanthaRao, B.; Rakesh, V.

2018-05-01

Understanding the relationship between gradually varying soil moisture (SM) conditions and monsoon rainfall anomalies is crucial for seasonal prediction. Though it is an important issue, very few studies in the past attempted to diagnose the linkages between the antecedent SM and Indian summer monsoon rainfall. This study examined the relationship between spring (April-May) SM and June rainfall using observed data during the period 1979-2010. The Empirical Orthogonal Function (EOF) analyses showed that the spring SM plays a significant role in June rainfall over the Central India (CI), South India (SI), and North East India (NEI) regions. The composite anomaly of the spring SM and June rainfall showed that excess (deficit) June rainfall over the CI was preceded by wet (dry) spring SM. The anomalies in surface-specific humidity, air temperature, and surface radiation fluxes also supported the existence of a positive SM-precipitation feedback over the CI. On the contrary, excess (deficit) June rainfall over the SI and NEI region were preceded by dry (wet) spring SM. The abnormal wet (dry) SM over the SI and NEI decreased (increased) the 2-m air temperature and increased (decreased) the surface pressure compared to the surrounding oceans which resulted in less (more) moisture transport from oceans to land (negative SM-precipitation feedback over the Indian monsoon region).

Interpolation of daily rainfall using spatiotemporal models and clustering

KAUST Repository

Militino, A. F.

2014-06-11

Accumulated daily rainfall in non-observed locations on a particular day is frequently required as input to decision-making tools in precision agriculture or for hydrological or meteorological studies. Various solutions and estimation procedures have been proposed in the literature depending on the auxiliary information and the availability of data, but most such solutions are oriented to interpolating spatial data without incorporating temporal dependence. When data are available in space and time, spatiotemporal models usually provide better solutions. Here, we analyse the performance of three spatiotemporal models fitted to the whole sampled set and to clusters within the sampled set. The data consists of daily observations collected from 87 manual rainfall gauges from 1990 to 2010 in Navarre, Spain. The accuracy and precision of the interpolated data are compared with real data from 33 automated rainfall gauges in the same region, but placed in different locations than the manual rainfall gauges. Root mean squared error by months and by year are also provided. To illustrate these models, we also map interpolated daily precipitations and standard errors on a 1km2 grid in the whole region. © 2014 Royal Meteorological Society.

Interpolation of daily rainfall using spatiotemporal models and clustering

KAUST Repository

Militino, A. F.; Ugarte, M. D.; Goicoa, T.; Genton, Marc G.

2014-01-01

Accumulated daily rainfall in non-observed locations on a particular day is frequently required as input to decision-making tools in precision agriculture or for hydrological or meteorological studies. Various solutions and estimation procedures have been proposed in the literature depending on the auxiliary information and the availability of data, but most such solutions are oriented to interpolating spatial data without incorporating temporal dependence. When data are available in space and time, spatiotemporal models usually provide better solutions. Here, we analyse the performance of three spatiotemporal models fitted to the whole sampled set and to clusters within the sampled set. The data consists of daily observations collected from 87 manual rainfall gauges from 1990 to 2010 in Navarre, Spain. The accuracy and precision of the interpolated data are compared with real data from 33 automated rainfall gauges in the same region, but placed in different locations than the manual rainfall gauges. Root mean squared error by months and by year are also provided. To illustrate these models, we also map interpolated daily precipitations and standard errors on a 1km2 grid in the whole region. © 2014 Royal Meteorological Society.

Nevada Isostatic Gravity Grid

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A 2 kilometer Isostatic anomaly grid for the state of Nevada. Number of columns is 269 and number of rows is 394. The order of the data is from the lower left to the...

Maine Bouguer Gravity Grid

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A 2 kilometer Bouguer anomaly grid for the state of Maine. Number of columns is 197 and number of rows is 292. The order of the data is from the lower left to the...

Minnesota Bouguer Anomaly Grid

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A 1.5 kilometer Bouguer anomaly grid for the state of Minnesota. Number of columns is 404 and number of rows is 463. The order of the data is from the lower left to...

Bolivian Bouguer Anomaly Grid

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A 1 kilometer Bouguer anomaly grid for the country of Bolivia.Number of columns is 550 and number of rows is 900. The order of the data is from the lower left to the...

Slope 60 m grid derived from gridded bathymetry of Guam Island, Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (60 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI. Cell values reflect the maximum rate of...

Slope 60 m grid derived from gridded bathymetry of Rota Island, Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (60 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI. Cell values reflect the maximum rate of...

Predicting monsoon rainfall and pressure indices from sea surface temperature

Digital Repository Service at National Institute of Oceanography (India)

Sadhuram, Y.

The relationship between the sea surface temperature (SST) in the Indian Ocean and monsoon rainfall has been examined by using 21 years data set (1967-87) of MOHSST.6 (Met. Office Historical Sea Surface Temperature data set, obtained from U.K. Met...

Application of Artificial Neural Networks to Rainfall Forecasting in Queensland, Australia

Institute of Scientific and Technical Information of China (English)

John ABBOT; Jennifer MAROHASY

2012-01-01

In this study,the application of artificial intelligence to monthly and seasonal rainfall forecasting in Queensland,Australia,was assessed by inputting recognized climate indices,monthly historical rainfall data,and atmospheric temperatures into a prototype stand-alone,dynamic,recurrent,time-delay,artificial neural network.Outputs,as monthly rainfall forecasts 3 months in advance for the period 1993 to 2009,were compared with observed rainfall data using time-series plots,root mean squared error (RMSE),and Pearson correlation coefficients.A comparison of RMSE values with forecasts generated by the Australian Bureau of Meteorology's Predictive Ocean Atmosphere Model for Australia (POAMA)-1.5 general circulation model (GCM) indicated that the prototype achieved a lower RMSE for 16 of the 17 sites compared.The application of artificial neural networks to rainfall forecasting was reviewed.The prototype design is considered preliminary,with potential for significant improvement such as inclusion of output from GCMs and experimentation with other input attributes.

Predicting extreme rainfall over eastern Asia by using complex networks

International Nuclear Information System (INIS)

He Su-Hong; Gong Yan-Chun; Huang Yan-Hua; Wu Cheng-Guo; Feng Tai-Chen; Gong Zhi-Qiang

2014-01-01

A climate network of extreme rainfall over eastern Asia is constructed for the period of 1971–2000, employing the tools of complex networks and a measure of nonlinear correlation called event synchronization (ES). Using this network, we predict the extreme rainfall for several cases without delay and with n-day delay (1 ≤ n ≤ 10). The prediction accuracy can reach 58% without delay, 21% with 1-day delay, and 12% with n-day delay (2 ≤ n ≤ 10). The results reveal that the prediction accuracy is low in years of a weak east Asia summer monsoon (EASM) or 1 year later and high in years of a strong EASM or 1 year later. Furthermore, the prediction accuracy is higher due to the many more links that represent correlations between different grid points and a higher extreme rainfall rate during strong EASM years. (geophysics, astronomy, and astrophysics)

Mosaic of gridded multibeam and lidar bathymetry of the US Territory of Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded lidar bathymetry. Gridded (5 m cell size) multibeam bathymetry were collected aboard NOAA Ship Hiialaka'i and...

Utah Bouguer Gravity Grid

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A 2.5 kilometer Bouguer anomaly grid for the state of Utah. Number of columns is 196 and number of rows is 245. The order of the data is from the lower left to the...

Regimes of Diurnal Variation of Summer Rainfall over Subtropical East Asia

Energy Technology Data Exchange (ETDEWEB)

Yuan W.; Lin W.; Yu, R.; Zhang, M.; Chen, H.; Li, J.

2012-05-01

Using hourly rain gauge records and Tropical Rainfall Measuring Mission 3B42 from 1998 to 2006, the authors present an analysis of the diurnal characteristics of summer rainfall over subtropical East Asia. The study shows that there are four different regimes of distinct diurnal variation of rainfall in both the rain gauge and the satellite data. They are located over the Tibetan Plateau with late-afternoon and midnight peaks, in the western China plain with midnight to early-morning peaks, in the eastern China plain with double peaks in late afternoon and early morning, and over the East China Sea with an early-morning peak. No propagation of diurnal phases is found from the land to the ocean across the coastlines. The different diurnal regimes are highly correlated with the inhomogeneous underlying surface, such as the plateau, plain, and ocean, with physical mechanisms consistent with the large-scale 'mountain-valley' and 'land-sea' breezes and convective instability. These diurnal characteristics over subtropical East Asia can be used as diagnostic metrics to evaluate the physical parameterization and hydrological cycle of climate models over East Asia.

Prediction of East African Seasonal Rainfall Using Simplex Canonical Correlation Analysis.

Science.gov (United States)

Ntale, Henry K.; Yew Gan, Thian; Mwale, Davison

2003-06-01

A linear statistical model, canonical correlation analysis (CCA), was driven by the Nelder-Mead simplex optimization algorithm (called CCA-NMS) to predict the standardized seasonal rainfall totals of East Africa at 3-month lead time using SLP and SST anomaly fields of the Indian and Atlantic Oceans combined together by 24 simplex optimized weights, and then `reduced' by the principal component analysis. Applying the optimized weights to the predictor fields produced better March-April-May (MAM) and September-October-November (SON) seasonal rain forecasts than a direct application of the same, unweighted predictor fields to CCA at both calibration and validation stages. Northeastern Tanzania and south-central Kenya had the best SON prediction results with both validation correlation and Hanssen-Kuipers skill scores exceeding +0.3. The MAM season was better predicted in the western parts of East Africa. The CCA correlation maps showed that low SON rainfall in East Africa is associated with cold SSTs off the Somali coast and the Benguela (Angola) coast, and low MAM rainfall is associated with a buildup of low SSTs in the Indian Ocean adjacent to East Africa and the Gulf of Guinea.

Analysis of aggregation and disaggregation effects for grid-based hydrological models and the development of improved precipitation disaggregation procedures for GCMs

Directory of Open Access Journals (Sweden)

H. S. Wheater

1999-01-01

Full Text Available Appropriate representation of hydrological processes within atmospheric General Circulation Models (GCMs is important with respect to internal model dynamics (e.g. surface feedback effects on atmospheric fluxes, continental runoff production and to simulation of terrestrial impacts of climate change. However, at the scale of a GCM grid-square, several methodological problems arise. Spatial disaggregation of grid-square average climatological parameters is required in particular to produce appropriate point intensities from average precipitation. Conversely, aggregation of land surface heterogeneity is necessary for grid-scale or catchment scale application. The performance of grid-based hydrological models is evaluated for two large (104km2 UK catchments. Simple schemes, using sub-grid average of individual land use at 40 km scale and with no calibration, perform well at the annual time-scale and, with the addition of a (calibrated routing component, at the daily and monthly time-scale. Decoupling of hillslope and channel routing does not necessarily improve performance or identifiability. Scale dependence is investigated through application of distribution functions for rainfall and soil moisture at 100 km scale. The results depend on climate, but show interdependence of the representation of sub-grid rainfall and soil moisture distribution. Rainfall distribution is analysed directly using radar rainfall data from the UK and the Arkansas Red River, USA. Among other properties, the scale dependence of spatial coverage upon radar pixel resolution and GCM grid-scale, as well as the serial correlation of coverages are investigated. This leads to a revised methodology for GCM application, as a simple extension of current procedures. A new location-based approach using an image processing technique is then presented, to allow for the preservation of the spatial memory of the process.

A Statistical Model for Seasonal Rainfall Forecasting over the ...

African Journals Online (AJOL)

In a preliminary step, in order to identify the most influential rainfall predictor, a correlation matrix and step-wise regression of 10 predictors with different lags were analysed. The influence of the southern Indian Ocean Sea Surface Temperature was identified as the most influential predictor for the highland of Eritrea.

Gridded multibeam bathymetry of Apra Harbor, Guam U.S. Territory

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry from Apra Harbor, Guam U.S. Territory. The netCDF and Arc ASCII grids include multibeam bathymetry from the Reson SeaBat 8125 multibeam sonar...

Tropical Indian Ocean Variability Driving Southeast Australian Droughts

Science.gov (United States)

Ummenhofer, C. C.; England, M. H.; McIntosh, P. C.; Meyers, G. A.; Pook, M. J.; Risbey, J. S.; Sen Gupta, A.; Taschetto, A. S.

2009-04-01

Variability in the tropical Indian Ocean has widespread effects on rainfall in surrounding countries, including East Africa, India and Indonesia. The leading mode of tropical Indian Ocean variability, the Indian Ocean Dipole (IOD), is a coupled ocean-atmosphere mode characterized by sea surface temperature (SST) anomalies of opposite sign in the east and west of the basin with an associated large-scale atmospheric re-organisation. Earlier work has often focused on the positive phase of the IOD. However, we show here that the negative IOD phase is an important driver of regional rainfall variability and multi-year droughts. For southeastern Australia, we show that it is actually a lack of the negative IOD phase, rather than the positive IOD phase or Pacific variability, that provides the most robust explanation for recent drought conditions. Since 1995, a large region of Australia has been gripped by the most severe drought in living memory, the so-called "Big Dry". The ramifications for affected regions are dire, with acute water shortages for rural and metropolitan areas, record agricultural losses, the drying-out of two of Australia's major river systems and far-reaching ecosystem damage. Yet the drought's origins have remained elusive. For Southeast Australia, we show that the "Big Dry" and other iconic 20th Century droughts, including the Federation Drought (1895-1902) and World War II drought (1937-1945), are driven by tropical Indian Ocean variability, not Pacific Ocean conditions as traditionally assumed. Specifically, a conspicuous absence of characteristic Indian Ocean temperature conditions that are conducive to enhanced tropical moisture transport has deprived southeastern Australia of its normal rainfall quota. In the case of the "Big Dry", its unprecedented intensity is also related to recent above-average temperatures. Implications of recent non-uniform warming trends in the Indian Ocean and how that might affect ocean characteristics and climate in

Rugosity grid derived from gridded bathymetry of Howland Island, Pacific Remote Island Areas, Central Pacific

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (40 m cell size) multibeam bathymetry, collected aboard R/V AHI and NOAA ship Hi'ialakai. Cell values reflect the (surface area) /...

Slope grid derived from gridded bathymetry of Ofu and Olosega Islands, Territory of American Samoa, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard R/V AHI, and bathymetry derived from multispectral IKONOS satellite imagery....

Slope grid derived from gridded bathymetry of Johnston Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (20 m cell size) multibeam bathymetry, collected aboard R/V AHI, and NOAA ship Hi'ialakai. Cell values reflect the maximum rate of...

Slope grid derived from gridded bathymetry of Howland Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (40 m cell size) multibeam bathymetry, collected aboard R/V AHI, and NOAA ship Hi'ialakai. Cell values reflect the maximum rate of...

Slope grid derived from gridded bathymetry of Baker Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (20 m cell size) multibeam bathymetry, collected aboard R/V AHI, and NOAA ship Hi'ialakai. Cell values reflect the maximum rate of...

Linking Vital Rates of Landbirds on a Tropical Island to Rainfall and Vegetation Greenness.

Directory of Open Access Journals (Sweden)

James F Saracco

Full Text Available Remote tropical oceanic islands are of high conservation priority, and they are exemplified by range-restricted species with small global populations. Spatial and temporal patterns in rainfall and plant productivity may be important in driving dynamics of these species. Yet, little is known about environmental influences on population dynamics for most islands and species. Here we leveraged avian capture-recapture, rainfall, and remote-sensed habitat data (enhanced vegetation index [EVI] to assess relationships between rainfall, vegetation greenness, and demographic rates (productivity, adult apparent survival of three native bird species on Saipan, Northern Mariana Islands: rufous fantail (Rhipidura rufifrons, bridled white-eye (Zosterops conspicillatus, and golden white-eye (Cleptornis marchei. Rainfall was positively related to vegetation greenness at all but the highest rainfall levels. Temporal variation in greenness affected the productivity of each bird species in unique ways. Predicted productivity of rufous fantail was highest when dry and wet season greenness values were high relative to site-specific 5-year seasonal mean values (i.e., relative greenness; while the white-eye species had highest predicted productivity when relative greenness contrasted between wet and dry seasons. Survival of rufous fantail and bridled white eye was positively related to relative dry-season greenness and negatively related to relative wet-season greenness. Bridled white-eye survival also showed evidence of a positive response to overall greenness. Our results highlight the potentially important role of rainfall regimes in affecting population dynamics of species on oceanic tropical islands. Understanding linkages between rainfall, vegetation, and animal population dynamics will be critical for developing effective conservation strategies in this and other regions where the seasonal timing, extent, and variability of rainfall is expected to change in the

2.5-min Isostatic Gravity Grid for the United States

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The 2.5-min isostatic gravity data set was produced by regridding the 4-km residual isostatic gravity grid of the U.S. The isostatic residual gravity grid was...

Annual and interannual variation of precipitation over the tropical Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

RameshKumar, M.R.; Prasad, T.G.

/month, and the lowest amplitudes are found in the western Indian Ocean, especially off the Arabian and east African coasts. The INSAT and GEOS Precipitation Index (GPI) rainfall estimates correlated reasonably well with the island rainfall data, with correlation...

TELLUS_OCEAN_GIF_CSR_RL05:1

Data.gov (United States)

National Aeronautics and Space Administration — The images were generated from the monthly ocean mass grids, which contain ocean water mass given as equivalent water thickness derived from the Center of Space...

Spatial and temporal variability of rainfall in the Tocantins-Araguaia hydrographic region

Directory of Open Access Journals (Sweden)

Glauber Epifanio Loureiro

2015-01-01

Full Text Available Current paper examines the space-time dynamics of yearly rainfall of the Tocantins-Araguaia Hydrographic Region (TAHR, foregrounded on rainfall volume from isohyet maps and interpolated by Kriging geo-statistical method.  Rainfall space dynamics was undertaken by the analysis of descriptive statistics, Index of Meteorological Irregularity (IMI and Variation Coefficient. Temporal dynamics was analyzed through the distribution of total annual volume precipitation for each TAHR sub-basin by the Standardized Anomaly Index, trend and magnitude test provided by Mann-Kendall and Sen Tests. Results correlated with meteorological anomalies of the Atlantic (Dipole and Pacific (ENOS Oceans show a highly heterogeneous rainfall behavior with temporal variability. Or rather, a decrease of rainfall extensiveness during years of intense meteorological anomaly with a rainfall increase south of the High Tocantins and Araguaia sub-basins and a decrease of rainfall in the Lower Tocantins sub-basin, with El Niño features. Although the Mann-Kendall test does not show statistically a significant trend for rainfall in the TAHR region, Sen’s estimator reveals a decrease in rainfall in the High Tocantins (-1.24 km³ year-1 and Araguaia (-1.13 km³ year-1 sub-basins and a rainfall increase in the Lower Tocantins sub-basin (0.53 km³ year-1 and in the TAHR region (-1.5 km³ year-1.

Rugosity grid (5 m) derived from gridded bathymetry of Saipan Island, Commonwealth of the Northern Marianas

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) bathymetry from two sources: Multibeam bathymetry collected by Coral Reef Ecosystem Division aboard NOAA R/V AHI,...

Coverage map of gridded multibeam and lidar bathymetry of the US Territory of Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded lidar bathymetry. Gridded (5 m cell size) multibeam bathymetry were collected aboard NOAA Ship Hiialaka'i and...

Rugosity grid derived from gridded bathymetry of of Baker Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (20 m cell size) multibeam bathymetry, collected aboard R/V AHI and NOAA ship Hi'ialakai. Cell values reflect the (surface area) /...

Rugosity grid derived from gridded bathymetry of of Johnston Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (20 m cell size) multibeam bathymetry, collected aboard R/V AHI and NOAA ship Hi'ialakai. Cell values reflect the (surface area) /...

Gridded 5km GHCN-Daily Temperature and Precipitation Dataset, Version 1

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Gridded 5km GHCN-Daily Temperature and Precipitation Dataset (nClimGrid) consists of four climate variables derived from the GHCN-D dataset: maximum temperature,...

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

Directory of Open Access Journals (Sweden)

Carolien Toté

2015-02-01

Full Text Available Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT v2.0, Famine Early Warning System NETwork (FEWS NET Rainfall Estimate (RFE v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS are compared to independent gauge data (2001–2012. This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

Science.gov (United States)

Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Arctic and Southern Ocean Sea Ice Concentrations

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Monthly sea ice concentration for Arctic (1901 to 1995) and Southern oceans (1973 to 1990) were digitized on a standard 1-degree grid (cylindrical projection) to...

Multi-decadal classification of synoptic weather types, observed trends and links to rainfall characteristics over Saudi Arabia

KAUST Repository

El Kenawy, Ahmed M.

2014-09-15

An automated version of the Lamb weather type classification scheme was employed to characterize daily circulation conditions in Saudi Arabia from 1960 to 2005. Daily gridded fields of sea level pressure (SLP) from both the NCEP/NCAR and the European Center for Medium-Range Weather Forecast (ECMWF) reanalysis data (ERA40) were used as input data for this classification. The output catalog included 10 basic types, which describe the direction and vorticity of airflow in the region (i.e., cyclonic, anti-cyclonic, and directional). In general, our findings indicate that cyclonic (C) days represent the most frequent type among all days, with 69.2% of the annual count of days from 1960 to 2005, followed by SE directional flows (21%). It was also determined that airflows originating from the Indian Ocean (i.e., S, SE, and E) are more frequent than those from the Mediterranean and Red Seas (i.e., W, NW, and SW). The defined weather types were assessed for the presence of inter-annual and intra-annual trends using the Mann–Kendall tau statistic. The trend analysis suggests statistically significant changes in the frequencies of a majority of the weather types from 1960 to 2005. The relationship between the daily occurrence of rainfall and the frequency of individual weather types was also described using daily rainfall data from a network of 87 weather observatories. Results demonstrate that increasing frequencies of weather types connected to easterly inflows support higher precipitation amounts over the study domain. Characterizing the association between atmospheric circulation patterns and rainfall in Saudi Arabia is important for understanding potential impacts related to climate variability and also for developing circulation-based downscaling methods.

Validation of Satellite Estimates (Tropical Rainfall Measuring Mission, TRMM for Rainfall Variability over the Pacific Slope and Coast of Ecuador

Directory of Open Access Journals (Sweden)

Bolívar Erazo

2018-02-01

Full Text Available A dense rain-gauge network within continental Ecuador was used to evaluate the quality of various products of rainfall data over the Pacific slope and coast of Ecuador (EPSC. A cokriging interpolation method is applied to the rain-gauge data yielding a gridded product at 5-km resolution covering the period 1965–2015. This product is compared with the Global Precipitation Climatology Centre (GPCC dataset, the Climatic Research Unit–University of East Anglia (CRU dataset, the Tropical Rainfall Measuring Mission (TRMM/TMPA 3B43 Version 7 dataset and the ERA-Interim Reanalysis. The analysis reveals that TRMM data show the most realistic features. The relative bias index (Rbias indicates that TRMM data is closer to the observations, mainly over lowlands (mean Rbias of 7% but have more limitations in reproducing the rainfall variability over the Andes (mean Rbias of −28%. The average RMSE and Rbias of 68.7 and −2.8% of TRMM are comparable with the GPCC (69.8 and 5.7% and CRU (102.3 and −2.3% products. This study also focuses on the rainfall inter-annual variability over the study region which experiences floods that have caused high economic losses during extreme El Niño events. Finally, our analysis evaluates the ability of TRMM data to reproduce rainfall events during El Niño years over the study area and the large basins of Esmeraldas and Guayas rivers. The results show that TRMM estimates report reasonable levels of heavy rainfall detection (for the extreme 1998 El Niño event over the EPSC and specifically towards the center-south of the EPSC (Guayas basin but present underestimations for the moderate El Niño of 2002–2003 event and the weak 2009–2010 event. Generally, the rainfall seasonal features, quantity and long-term climatology patterns are relatively well estimated by TRMM.

Distributed modelling of shallow landslides triggered by intense rainfall

Directory of Open Access Journals (Sweden)

G. B. Crosta

2003-01-01

Full Text Available Hazard assessment of shallow landslides represents an important aspect of land management in mountainous areas. Among all the methods proposed in the literature, physically based methods are the only ones that explicitly includes the dynamic factors that control landslide triggering (rainfall pattern, land-use. For this reason, they allow forecasting both the temporal and the spatial distribution of shallow landslides. Physically based methods for shallow landslides are based on the coupling of the infinite slope stability analysis with hydrological models. Three different grid-based distributed hydrological models are presented in this paper: a steady state model, a transient "piston-flow" wetting front model, and a transient diffusive model. A comparative test of these models was performed to simulate landslide occurred during a rainfall event (27–28 June 1997 that triggered hundreds of shallow landslides within Lecco province (central Southern Alps, Italy. In order to test the potential for a completely distributed model for rainfall-triggered landslides, radar detected rainfall intensity has been used. A new procedure for quantitative evaluation of distributed model performance is presented and used in this paper. The diffusive model results in the best model for the simulation of shallow landslide triggering after a rainfall event like the one that we have analysed. Finally, radar data available for the June 1997 event permitted greatly improving the simulation. In particular, radar data allowed to explain the non-uniform distribution of landslides within the study area.

Rainfall characteristics and thresholds for periglacial debris flows in the Parlung Zangbo Basin, southeast Tibetan Plateau

Science.gov (United States)

Deng, Mingfeng; Chen, Ningsheng; Ding, Haitao

2018-02-01

The Parlung Zangbo Basin in the southeastern Tibet Plateau is affected by the summer monsoon from the Indian Ocean, which produces large rainfall gradients in the basin. Rainfall data during 2012-2015 from five new meteorological stations are used to analyse the rainfall characteristics. The daily rainfall, rainfall duration, mean rainfall intensity, and peak rainfall intensity are consistent, but sometimes contrasting. For example, these values decrease with increasing altitude, and the gradient is large downstream and small upstream, respectively. Moreover, the rainfall intensity peaks between 01:00 and 06:00 and increases during the afternoon. Based on the analysis of 14 debris flow cases in the basin, differences in the rainfall threshold differ depending on the location as sediment varieties. The sediment in the middle portions of the basin is wet and well structured; thus, long-duration, high-intensity rainfall is required to generate debris flows. Ravels in the upstream area are arid and not well structured, and short-duration rainfall is required to trigger debris flows. Between the above two locations, either long-duration, low-intensity rainfall or short-duration, high-intensity rainfall could provoke debris flows. Clearly, differences in rainfall characteristics and rainfall thresholds that are associated with the location must be considered in debris flow monitoring and warnings.

Improving a spatial rainfall product using a data-mining approach and its effect on the hydrological response of a meso-scale catchment.

Science.gov (United States)

Oriani, F.; Stisen, S.; Demirel, C.

2017-12-01

The spatial representation of rainfall is of primary importance to correctly study the uncertainty of basin recharge and its propagation to the surface and underground circulation. We consider here the daily grid rainfall product provided by the Danish Meteorological Institute as input to the National Water Resources Model of Denmark. Due to a drastic reduction in the rain gauge network (from approximately 500 stations in the period 1996-2006, to 250 in the period 2007-2014), the grid rainfall product, based on the interpolation of these data, is much less reliable. The research is focused on the Skjern catchment (1,050 km2 western Jutland), where we can dispose of the complete rain-gauge database from the Danish Hydrological Observatory and compute the distributed hydrological response at the 1-km scale.To give a better estimation of the gridded rainfall input, we start from ground measurements by simulating the missing data with a stochastic data-mining approach, then we compute again the grid interpolation. To maximize the predictive power of the technique, combinations of station time-series that are the most informative to each other are selected on the basis of their correlation and available historical data. Then, the missing data inside these time-series are simulated together using the direct sampling technique (DS) [1, 2]. DS simulates a datum by sampling the historical record of the same stations where a similar data pattern occurs, preserving their complex statistical relation. The simulated data are reinjected in the whole dataset and used as well as conditioning data to progressively fill up the gaps in other stations.The results show that the proposed methodology, tested on the period 1995-2012, can increase the realism of the grid rainfall product by regenerating the missing ground measurements. The hydrological response is analyzed considering the observations at 5 hydrological stations. The presented methodology can be used in many regions to

Future changes in rainfall associated with ENSO, IOD and changes in the mean state over Eastern Africa

Science.gov (United States)

Endris, Hussen Seid; Lennard, Christopher; Hewitson, Bruce; Dosio, Alessandro; Nikulin, Grigory; Artan, Guleid A.

2018-05-01

This study examines the projected changes in the characteristics of the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) in terms of mean state, intensity and frequency, and associated rainfall anomalies over eastern Africa. Two regional climate models driven by the same four global climate models (GCMs) and the corresponding GCM simulations are used to investigate projected changes in teleconnection patterns and East African rainfall. The period 1976-2005 is taken as the reference for present climate and the far-future climate (2070-2099) under Representative Concentration Pathway 8.5 (RCP8.5) is analyzed for projected change. Analyses of projections based on GCMs indicate an El Niño-like (positive IOD-like) warming pattern over the tropical Pacific (Indian) Ocean. However, large uncertainties remain in the projected future changes in ENSO/IOD frequency and intensity with some GCMs show increase of ENSO/IOD frequency and intensity, and others a decrease or no/small change. Projected changes in mean rainfall over eastern Africa based on the GCM and RCM data indicate a decrease in rainfall over most parts of the region during JJAS and MAM seasons, and an increase in rainfall over equatorial and southern part of the region during OND, with the greatest changes in equatorial region. During ENSO and IOD years, important changes in the strength of the teleconnections are found. During JJAS, when ENSO is an important driver of rainfall variability over the region, both GCM and RCM projections show an enhanced La Niña-related rainfall anomaly compared to the present period. Although the long rains (MAM) have little association with ENSO in the reference period, both GCMs and RCMs project stronger ENSO teleconnections in the future. On the other hand, during the short rains (OND), a dipole future change in rainfall teleconnection associated with ENSO and IOD is found, with a stronger ENSO/IOD related rainfall anomaly over the eastern part of the domain

Rugosity grid derived from gridded bathymetry of Ta'u Island of the Manu'a Island group, American Samoa

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard R/V AHI, and bathymetry derived from multispectral IKONOS satellite imagery...

Rugosity grid derived from gridded bathymetry Ofu and Olosega Islands of the Manu'a Island group, American Samoa

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard R/V AHI, and bathymetry derived from multispectral IKONOS satellite imagery...

Prevention through policy: Urban macroplastic leakages to the marine environment during extreme rainfall events

OpenAIRE

Axelsson, Charles; van Sebille, Erik

2017-01-01

The leakage of large plastic litter (macroplastics) into the ocean is a major environmental problem. A significant fraction of this leakage originates from coastal cities, particularly during extreme rainfall events. As coastal cities continue to grow, finding ways to reduce this macroplastic leakage is extremely pertinent. Here, we explore why and how coastal cities can reduce macroplastic leakages during extreme rainfall events. Using nine global cities as a basis, we establish that while c...

CRED Gridded Bathymetry near Northampton Seamounts (100-004), Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-004b is a 60-m ASCII grid of depth data collected near Northampton Seamounts in the Northwestern Hawaiian Islands as of May 2003. This grid has been...

A TRMM-Calibrated Infrared Rainfall Algorithm Applied Over Brazil

Science.gov (United States)

Negri, A. J.; Xu, L.; Adler, R. F.; Einaudi, Franco (Technical Monitor)

2000-01-01

The development of a satellite infrared technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall in Amazonia are presented. The Convective-Stratiform. Technique, calibrated by coincident, physically retrieved rain rates from the Tropical Rain Measuring Mission (TRMM) Microwave Imager (TMI), is applied during January to April 1999 over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. Results compare well (a one-hour lag) with the diurnal cycle derived from Tropical Ocean-Global Atmosphere (TOGA) radar-estimated rainfall in Rondonia. The satellite estimates reveal that the convective rain constitutes, in the mean, 24% of the rain area while accounting for 67% of the rain volume. The effects of geography (rivers, lakes, coasts) and topography on the diurnal cycle of convection are examined. In particular, the Amazon River, downstream of Manaus, is shown to both enhance early morning rainfall and inhibit afternoon convection. Monthly estimates from this technique, dubbed CST/TMI, are verified over a dense rain gage network in the state of Ceara, in northeast Brazil. The CST/TMI showed a high bias equal to +33% of the gage mean, indicating that possibly the TMI estimates alone are also high. The root mean square difference (after removal of the bias) equaled 36.6% of the gage mean. The correlation coefficient was 0.77 based on 72 station-months.

The capacity of radar, crowdsourced personal weather stations and commercial microwave links to monitor small scale urban rainfall

Science.gov (United States)

Uijlenhoet, R.; de Vos, L. W.; Leijnse, H.; Overeem, A.; Raupach, T. H.; Berne, A.

2017-12-01

For the purpose of urban rainfall monitoring high resolution rainfall measurements are desirable. Typically C-band radar can provide rainfall intensities at km grid cells every 5 minutes. Opportunistic sensing with commercial microwave links yields rainfall intensities over link paths within cities. Additionally, recent developments have made it possible to obtain large amounts of urban in situ measurements from weather amateurs in near real-time. With a known high resolution simulated rainfall event the accuracy of these three techniques is evaluated, taking into account their respective existing layouts and sampling methods. Under ideal measurement conditions, the weather station networks proves to be most promising. For accurate estimation with radar, an appropriate choice for Z-R relationship is vital. Though both the microwave links and the weather station networks are quite dense, both techniques will underestimate rainfall if not at least one link path / station captures the high intensity rainfall peak. The accuracy of each technique improves when considering rainfall at larger scales, especially by increasing time intervals, with the steepest improvements found in microwave links.

CRED Gridded Bathymetry near Laysan Island (100-006), Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-006b is a 60-m ASCII grid of depth data collected near Laysan Island in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced as...

CRED Gridded Bathymetry near Lisianski Island (100-001), Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-001b is a 60-m ASCII grid of depth data collected near Lisianski Island in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced as...

2-minute Gridded Global Relief Data (ETOPO2) v2

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Two-minute gridded global relief for both ocean and land areas are available in the ETOPO2v2 (2006) database. ETOPO2v2 replaced ETOPO2 (2001). The historic 2-minute...

Vertical Motion Changes Related to North-East Brazil Rainfall Variability: a GCM Simulation

Science.gov (United States)

Roucou, Pascal; Oribe Rocha de Aragão, José; Harzallah, Ali; Fontaine, Bernard; Janicot, Serge

1996-08-01

The atmospheric structure over north-east Brazil during anomalous rainfall years is studied in the 11 levels of the outputs of the Laboratoire de Météorologie Dynamique atmospheric general circulation model (LMD AGCM). Seven 19-year simulations were performed using observed sea-surface temperature (SST) corresponding to the period 1970- 1988. The ensemble mean is calculated for each month of the period, leading to an ensemble-averaged simulation. The simulated March-April rainfall is in good agreement with observations. Correlations of simulated rainfall and three SST indices relative to the equatorial Pacific and northern and southern parts of the Atlantic Ocean exhibit stronger relationships in the simulation than in the observations. This is particularly true with the SST gradient in the Atlantic (Atlantic dipole). Analyses on 200 ;hPa velocity potential, vertical velocity, and vertical integral of the zonal component of mass flux are performed for years of abnormal rainfall and positive/negative SST anomalies in the Pacific and Atlantic oceans in March-April during the rainy season over the Nordeste region. The results at 200 hPa show a convergence anomaly over Nordeste and a divergence anomaly over the Pacific concomitant with dry seasons associated with warm SST anomalies in the Pacific and warm (cold) waters in the North (South) Atlantic. During drought years convection inside the ITCZ indicated by the vertical velocity exhibits a displacement of the convection zone corresponding to a northward migration of the ITCZ. The east-west circulation depicted by the zonal divergent mass flux shows subsiding motion over Nordeste and ascending motion over the Pacific in drought years, accompanied by warm waters in the eastern Pacific and warm/cold waters in northern/southern Atlantic. Rainfall variability of the Nordeste rainfall is linked mainly to vertical motion and SST variability through the migration of the ITCZ and the east-west circulation.

Yakutat Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Yakutat, Alaska Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Assessing the Regional Frequency, Intensity, and Spatial Extent of Tropical Cyclone Rainfall

Science.gov (United States)

Bosma, C.; Wright, D.; Nguyen, P.

2017-12-01

While the strength of a hurricane is generally classified based on its wind speed, the unprecedented rainfall-driven flooding experienced in southeastern Texas during Hurricane Harvey clearly highlights the need for better understanding of the hazards associated with extreme rainfall from hurricanes and other tropical systems. In this study, we seek to develop a framework for describing the joint probabilistic and spatio-temporal properties of extreme rainfall from hurricanes and other tropical systems. Furthermore, we argue that commonly-used terminology - such as the "500-year storm" - fail to convey the true properties of tropical cyclone rainfall occurrences in the United States. To quantify the magnitude and spatial extent of these storms, a database consisting of hundreds of unique rainfall volumetric shapes (or "voxels") was created. Each voxel is a four-dimensional object, created by connecting, in both space and time, gridded rainfall observations from the daily, gauge-based NOAA CPC-Unified precipitation dataset. Individual voxels were then associated with concurrent tropical cyclone tracks from NOAA's HURDAT-2 archive, to create distinct representations of the rainfall associated with every Atlantic tropical system making landfall over (or passing near) the United States since 1948. Using these voxels, a series of threshold-excess extreme value models were created to estimate the recurrence intervals of extreme tropical cyclone rainfall, both nationally and locally, for single and multi-day timescales. This voxel database also allows for the "indexing" of past events, placing recent extremes - such as the 50+ inches of rain observed during Hurricane Harvey - into a national context and emphasizing how rainfall totals that are rare at the point scale may be more frequent from a regional perspective.

Gridded multibeam bathymetry of Howland Island, Pacific Remote Island Areas, Central Pacific

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry at 40m resolution surrounding Howland Island, within the Pacific Remote Island Areas - Central Pacific Ocean. Bottom coverage was achieved in...

TRMM Precipitation Radar (PR) Gridded Rainfall Product (TRMM Product 3A25) V6

Data.gov (United States)

National Aeronautics and Space Administration — The primary objective of algorithm 3A25 is to compute various rainfall statistics over a month from the level 2 PR products. The statistics are derived at two...

TRMM Precipitation Radar (PR) Gridded Rainfall Product (TRMM Product 3A25) V7

Data.gov (United States)

National Aeronautics and Space Administration — The primary objective of algorithm 3A25 is to compute various rainfall statistics over a month from the level 2 PR products. The statistics are derived at two...

Bermuda Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Bermuda Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is a...

Analysis of trend in temperature and rainfall time series of an Indian arid region: comparative evaluation of salient techniques

Science.gov (United States)

Machiwal, Deepesh; Gupta, Ankit; Jha, Madan Kumar; Kamble, Trupti

2018-04-01

This study investigated trends in 35 years (1979-2013) temperature (maximum, Tmax and minimum, Tmin) and rainfall at annual and seasonal (pre-monsoon, monsoon, post-monsoon, and winter) scales for 31 grid points in a coastal arid region of India. Box-whisker plots of annual temperature and rainfall time series depict systematic spatial gradients. Trends were examined by applying eight tests, such as Kendall rank correlation (KRC), Spearman rank order correlation (SROC), Mann-Kendall (MK), four modified MK tests, and innovative trend analysis (ITA). Trend magnitudes were quantified by Sen's slope estimator, and a new method was adopted to assess the significance of linear trends in MK-test statistics. It was found that the significant serial correlation is prominent in the annual and post-monsoon Tmax and Tmin, and pre-monsoon Tmin. The KRC and MK tests yielded similar results in close resemblance with the SROC test. The performance of two modified MK tests considering variance-correction approaches was found superior to the KRC, MK, modified MK with pre-whitening, and ITA tests. The performance of original MK test is poor due to the presence of serial correlation, whereas the ITA method is over-sensitive in identifying trends. Significantly increasing trends are more prominent in Tmin than Tmax. Further, both the annual and monsoon rainfall time series have a significantly increasing trend of 9 mm year-1. The sequential significance of linear trend in MK test-statistics is very strong (R 2 ≥ 0.90) in the annual and pre-monsoon Tmin (90% grid points), and strong (R 2 ≥ 0.75) in monsoon Tmax (68% grid points), monsoon, post-monsoon, and winter Tmin (respectively 65, 55, and 48% grid points), as well as in the annual and monsoon rainfalls (respectively 68 and 61% grid points). Finally, this study recommends use of variance-corrected MK test for the precise identification of trends. It is emphasized that the rising Tmax may hamper crop growth due to enhanced

CRED Gridded Bathymetry near Midway Atoll (100-102), Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-102b is a 60-m ASCII grid of depth data collected near Midway Atoll in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced as part...

CRED Gridded Bathymetry near Maro Reef (100-007), Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-007b is a 60-m ASCII grid of depth data collected near Maro Reef in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced as part of...

Idaho Batholith Study Area Density Grid

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A 2 kilometer terrace-density grid for the Idaho batholith study area. Number of columns is 331 and number of rows is 285. The order of the data is from the lower...

Gridded multibeam bathymetry of Baker Island, Pacific Remote Island Areas, Central Pacific

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry at 40m resolution surrounding Baker Island, within the Pacific Remote Island Areas - Central Pacific Ocean. Bottom coverage was achieved in depths...

Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

Science.gov (United States)

Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

2018-04-01

The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of the US Territory of Guam.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from a focal mean analysis on bathymetry and slope. The bathymetry grid (5 m cell size) is derived from bathymetry from four sources:...

Midway Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Midway Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is a suite...

A Comparative Frequency Analysis of Maximum Daily Rainfall for a SE Asian Region under Current and Future Climate Conditions

Directory of Open Access Journals (Sweden)

Velautham Daksiya

2017-01-01

Full Text Available The impact of changing climate on the frequency of daily rainfall extremes in Jakarta, Indonesia, is analysed and quantified. The study used three different models to assess the changes in rainfall characteristics. The first method involves the use of the weather generator LARS-WG to quantify changes between historical and future daily rainfall maxima. The second approach consists of statistically downscaling general circulation model (GCM output based on historical empirical relationships between GCM output and station rainfall. Lastly, the study employed recent statistically downscaled global gridded rainfall projections to characterize climate change impact rainfall structure. Both annual and seasonal rainfall extremes are studied. The results show significant changes in annual maximum daily rainfall, with an average increase as high as 20% in the 100-year return period daily rainfall. The uncertainty arising from the use of different GCMs was found to be much larger than the uncertainty from the emission scenarios. Furthermore, the annual and wet seasonal analyses exhibit similar behaviors with increased future rainfall, but the dry season is not consistent across the models. The GCM uncertainty is larger in the dry season compared to annual and wet season.

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of the US Territory of Guam.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The bathymetry grid (5 m cell size) is derived from bathymetry from four sources: Multibeam...

Observation-Based Estimates of Surface Cooling Inhibition by Heavy Rainfall under Tropical Cyclones

Digital Repository Service at National Institute of Oceanography (India)

Jourdain, N; Lengaigne, M.; Vialard, J.; Madec, G.; Menkes, C.E.; Vincent, E.M.; Jullien, E.; Barnier, B.

Tropical cyclones drive intense ocean vertical mixing that explains most of the surface cooling observed in their wake (the "cold wake"). The influence of cyclonic rainfall on the cold wake at a global scale over the 2002-09 period is investigated...

Comparison of Satellite Rainfall Estimates and Rain Gauge Measurements in Italy, and Impact on Landslide Modeling

Directory of Open Access Journals (Sweden)

Mauro Rossi

2017-12-01

Full Text Available Landslides can be triggered by intense or prolonged rainfall. Rain gauge measurements are commonly used to predict landslides even if satellite rainfall estimates are available. Recent research focuses on the comparison of satellite estimates and gauge measurements. The rain gauge data from the Italian network (collected in the system database “Verifica Rischio Frana”, VRF are compared with the National Aeronautics and Space Administration (NASA Tropical Rainfall Measuring Mission (TRMM products. For the purpose, we couple point gauge and satellite rainfall estimates at individual grid cells, evaluating the correlation between gauge and satellite data in different morpho-climatological conditions. We then analyze the statistical distributions of both rainfall data types and the rainfall events derived from them. Results show that satellite data underestimates ground data, with the largest differences in mountainous areas. Power-law models, are more appropriate to correlate gauge and satellite data. The gauge and satellite-based products exhibit different statistical distributions and the rainfall events derived from them differ. In conclusion, satellite rainfall cannot be directly compared with ground data, requiring local investigation to account for specific morpho-climatological settings. Results suggest that satellite data can be used for forecasting landslides, only performing a local scaling between satellite and ground data.

Evolution of ENSO-related rainfall anomalies in Southeast Asia region and its relationship with atmosphere-ocean variations in Indo-Pacific sector

Energy Technology Data Exchange (ETDEWEB)

Juneng, Liew; Tangang, Fredolin T. [Technology National University of Malaysia, Marine Science Program, School of Environmental and Natural Resource Sciences, Bangi Selangor (Malaysia)

2005-09-01

The Southeast Asia rainfall (SEAR) anomalies depend strongly on phases of El Nino (La Nina). Using an extended empirical orthogonal function (EEOF) analysis, it is shown that the dominant EEOF mode of SEAR anomalies evolves northeastward throughout a period from the summer when El Nino develops to spring the following year when the event weakens. This evolution is consistent with northeastward migration of the ENSO-related anomalous out going radiation field. During boreal summer (winter), the strong ENSO-related anomaly tends to reside in regions south (north) of the equator. The evolution of dominant mode of SEAR anomalies is in tandem with the evolution of ENSO-related sea surface temperature (SST) anomalies. The strengthening and weakening of ''boomerang-shaped'' SST in western Pacific, the changing sign of anomalous SST in Java Sea and the warming in Indian Ocean and South China Sea are all part of ENSO-related changes and all are linked to SEAR anomaly. The anomalous low-level circulation associated with ENSO-related SEAR anomaly indicates the strengthening and weakening of two off-equatorial anticyclones, one over the Southern Indian Ocean and the other over the western North Pacific. Together with patterns of El Nino minus La Nina composites of various fields, it is proposed that the northeastward evolution of SEAR anomaly is basically part of the large-scale eastward evolution of ENSO-related signal in the Indo-Pacific sector. The atmosphere-ocean interaction plays an important role in this evolution. (orig.)

Gridded multibeam bathymetry and SHOALS LIDAR bathymetry of Penguin Bank, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry (5 m cell size) of Penguin Bank, Hawaii, USA. The netCDF grid and ArcGIS ASCII file include multibeam bathymetry from the Simrad EM3002d, and...

Nantucket, Massachusetts Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Nantucket, Massachusetts Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Diurnal circulations and their multi-scale interaction leading to rainfall over the South China Sea upstream of the Philippines during intraseasonal monsoon westerly wind bursts

Energy Technology Data Exchange (ETDEWEB)

Park, Myung-Sook; Elsberry, Russell L. [Naval Postgraduate School, Department of Meteorology, Monterey, CA (United States); Ho, Chang-Hoi [Seoul National University, School of Earth and Environmental Sciences, Seoul (Korea, Republic of); Kim, Jinwon [University of California in Los Angeles, Department of Meteorology, Berkeley, CA (United States)

2011-10-15

The morning diurnal precipitation maximum over the coastal sea upstream of the Philippines during intraseasonal westerly wind bursts is examined from observations and numerical model simulations. A well-defined case of precipitation and large-scale circulation over the coastal sea west of the Philippines during 17-27 June 2004 is selected as a representative case. The hypothesis is that the mesoscale diurnal circulation over the Philippines and a large-scale diurnal circulation that is induced by large-scale differential heating over Asian continent and the surrounding ocean interact to produce the offshore precipitation maximum during the morning. Three-hourly combined satellite microwave and infrared rainfall retrievals define the morning rainfall peak during this period, and then later the stratiform rain area extends toward the open sea. A control numerical simulation in which a grid-nudging four-dimensional data assimilation (FDDA) is applied to force the large-scale diurnal circulation represents reasonably well the morning rainfall maximum. An enhanced low-level convergence similar to observations is simulated due to the interaction of the local- and large-scale diurnal circulations. The essential role of the local-scale diurnal circulation is illustrated in a sensitivity test in which the solar zenith angle is fixed at 7 am to suppress this diurnal circulation. The implication for climate diagnosis or modeling of such upstream coastal sea precipitation maxima is that the diurnal variations of both the local- and the large-scale circulations must be taken into consideration. (orig.)

Horizontal Residual Mean Circulation: Evaluation of Spatial Correlations in Coarse Resolution Ocean Models

Science.gov (United States)

Li, Y.; McDougall, T. J.

2016-02-01

Coarse resolution ocean models lack knowledge of spatial correlations between variables on scales smaller than the grid scale. Some researchers have shown that these spatial correlations play a role in the poleward heat flux. In order to evaluate the poleward transport induced by the spatial correlations at a fixed horizontal position, an equation is obtained to calculate the approximate transport from velocity gradients. The equation involves two terms that can be added to the quasi-Stokes streamfunction (based on temporal correlations) to incorporate the contribution of spatial correlations. Moreover, these new terms do not need to be parameterized and is ready to be evaluated by using model data directly. In this study, data from a high resolution ocean model have been used to estimate the accuracy of this HRM approach for improving the horizontal property fluxes in coarse-resolution ocean models. A coarse grid is formed by sub-sampling and box-car averaging the fine grid scale. The transport calculated on the coarse grid is then compared to the transport on original high resolution grid scale accumulated over a corresponding number of grid boxes. The preliminary results have shown that the estimate on coarse resolution grids roughly match the corresponding transports on high resolution grids.

Influence of southern oscillation on autumn rainfall in Iran (1951-2011)

Science.gov (United States)

Roghani, Rabbaneh; Soltani, Saeid; Bashari, Hossein

2016-04-01

This study aimed to investigate the relationships between southern oscillation and autumn (October-December) rainfall in Iran. It also sought to identify the possible physical mechanisms involved in the mentioned relationships by analyzing observational atmospheric data. Analyses were based on monthly rainfall data from 50 synoptic stations with at least 35 years of records up to the end of 2011. Autumn rainfall time series were grouped by the average Southern Oscillation Index (SOI) and SOI phase methods. Significant differences between rainfall groups in each method were assessed by Kruskal-Wallis and Kolmogorov-Smirnov non-parametric tests. Their relationships were also validated using the linear error in probability space (LEPS) test. The results showed that average SOI and SOI phases during July-September were related with autumn rainfall in some regions located in the west and northwest of Iran, west coasts of the Caspian Sea and southern Alborz Mountains. The El Niño (negative) and La Niña (positive) phases were associated with increased and decreased autumn rainfall, respectively. Our findings also demonstrated the persistence of Southern Pacific Ocean's pressure signals on autumn rainfall in Iran. Geopotential height patterns were totally different in the selected El Niño and La Niña years over Iran. During the El Niño years, a cyclone was formed over the north of Iran and an anticyclone existed over the Mediterranean Sea. During La Niña years, the cyclone shifted towards the Mediterranean Sea and an anticyclone developed over Iran. While these El Niño conditions increased autumn rainfall in Iran, the opposite conditions during the La Niña phase decreased rainfall in the country. In conclusion, development of rainfall prediction models based on the SOI can facilitate agricultural and water resources management in Iran.

Rugosity 10 m grid derived from gridded bathymetry of Alamagan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hi'ialakai and R/V AHI, using the Benthic Terrain Modeler with...

Rugosity 10 m grid derived from gridded bathymetry of Pagan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Rugosity 10 m grid derived from gridded bathymetry of Agrihan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Rugosity 10 m grid derived from gridded bathymetry of Maug Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Rugosity 10 m grid derived from gridded bathymetry of Asuncion Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (10 m cell size) multibeam bathymetry collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Rugosity 10 m grid derived from gridded bathymetry of Guguan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Changing character of rainfall in eastern China, 1951–2007

Science.gov (United States)

Day, Jesse A.; Fung, Inez; Liu, Weihan

2018-03-01

The topography and continental configuration of East Asia favor the year-round existence of storm tracks that extend thousands of kilometers from China into the northwestern Pacific Ocean, producing zonally elongated patterns of rainfall that we call “frontal rain events.” In spring and early summer (known as “Meiyu Season”), frontal rainfall intensifies and shifts northward during a series of stages collectively known as the East Asian summer monsoon. Using a technique called the Frontal Rain Event Detection Algorithm, we create a daily catalog of all frontal rain events in east China during 1951–2007, quantify their attributes, and classify all rainfall on each day as either frontal, resulting from large-scale convergence, or nonfrontal, produced by local buoyancy, topography, or typhoons. Our climatology shows that the East Asian summer monsoon consists of a series of coupled changes in frontal rain event frequency, latitude, and daily accumulation. Furthermore, decadal changes in the amount and distribution of rainfall in east China are overwhelmingly due to changes in frontal rainfall. We attribute the “South Flood–North Drought” pattern observed beginning in the 1980s to changes in the frequency of frontal rain events, while the years 1994–2007 witnessed an uptick in event daily accumulation relative to the rest of the study years. This particular signature may reflect the relative impacts of global warming, aerosol loading, and natural variability on regional rainfall, potentially via shifting the East Asian jet stream.

Westport, Washington Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Westport, Washington Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Nawiliwili, Hawaii Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Nawiliwili, Hawaii Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Virginia Beach Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Virginia Beach, Virginia Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Monterey, California Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Monterey, California Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Tropical Atlantic Contributions to Strong Rainfall Variability Along the Northeast Brazilian Coast

Directory of Open Access Journals (Sweden)

G. A. Hounsou-gbo

2015-01-01

Full Text Available Tropical Atlantic (TA Ocean-atmosphere interactions and their contributions to strong variability of rainfall along the Northeast Brazilian (NEB coast were investigated for the years 1974–2008. The core rainy seasons of March-April and June-July were identified for Fortaleza (northern NEB; NNEB and Recife (eastern NEB; ENEB, respectively. Lagged linear regressions between sea surface temperature (SST and pseudo wind stress (PWS anomalies over the entire TA and strong rainfall anomalies at Fortaleza and Recife show that the rainfall variability of these regions is differentially influenced by the dynamics of the TA. When the Intertropical Convergence Zone is abnormally displaced southward a few months prior to the NNEB rainy season, the associated meridional mode increases humidity and precipitation during the rainy season. Additionally, this study shows predictive effect of SST, meridional PWS, and barrier layer thickness, in the Northwestern equatorial Atlantic, on the NNEB rainfall. The dynamical influence of the TA on the June-July ENEB rainfall variability shows a northwestward-propagating area of strong, positively correlated SST from the southeastern TA to the southwestern Atlantic warm pool (SAWP offshore of Brazil. Our results also show predictive effect of SST, zonal PWS, and mixed layer depth, in the SAWP, on the ENEB rainfall.

Grid-cell-based crop water accounting for the famine early warning system

Science.gov (United States)

Verdin, James; Klaver, Robert

2002-06-01

Rainfall monitoring is a regular activity of food security analysts for sub-Saharan Africa due to the potentially disastrous impact of drought. Crop water accounting schemes are used to track rainfall timing and amounts relative to phenological requirements, to infer water limitation impacts on yield. Unfortunately, many rain gauge reports are available only after significant delays, and the gauge locations leave large gaps in coverage. As an alternative, a grid-cell-based formulation for the water requirement satisfaction index (WRSI) was tested for maize in Southern Africa. Grids of input variables were obtained from remote sensing estimates of rainfall, meteorological models, and digital soil maps. The spatial WRSI was computed for the 1996-97 and 1997-98 growing seasons. Maize yields were estimated by regression and compared with a limited number of reports from the field for the 1996-97 season in Zimbabwe. Agreement at a useful level (r = 0·80) was observed. This is comparable to results from traditional analysis with station data. The findings demonstrate the complementary role that remote sensing, modelling, and geospatial analysis can play in an era when field data collection in sub-Saharan Africa is suffering an unfortunate decline. Published in 2002 by John Wiley & Sons, Ltd.

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

Evaluation of TRIGRS (transient rainfall infiltration and grid-based regional slope-stability analysis)'s predictive skill for hurricane-triggered landslides: A case study in Macon County, North Carolina

Science.gov (United States)

Liao, Z.; Hong, Y.; Kirschbaum, D.; Adler, R.F.; Gourley, J.J.; Wooten, R.

2011-01-01

The key to advancing the predictability of rainfall-triggered landslides is to use physically based slope-stability models that simulate the transient dynamical response of the subsurface moisture to spatiotemporal variability of rainfall in complex terrains. TRIGRS (transient rainfall infiltration and grid-based regional slope-stability analysis) is a USGS landslide prediction model, coded in Fortran, that accounts for the influences of hydrology, topography, and soil physics on slope stability. In this study, we quantitatively evaluate the spatiotemporal predictability of a Matlab version of TRIGRS (MaTRIGRS) in the Blue Ridge Mountains of Macon County, North Carolina where Hurricanes Ivan triggered widespread landslides in the 2004 hurricane season. High resolution digital elevation model (DEM) data (6-m LiDAR), USGS STATSGO soil database, and NOAA/NWS combined radar and gauge precipitation are used as inputs to the model. A local landslide inventory database from North Carolina Geological Survey is used to evaluate the MaTRIGRS' predictive skill for the landslide locations and timing, identifying predictions within a 120-m radius of observed landslides over the 30-h period of Hurricane Ivan's passage in September 2004. Results show that within a radius of 24 m from the landslide location about 67% of the landslide, observations could be successfully predicted but with a high false alarm ratio (90%). If the radius of observation is extended to 120 m, 98% of the landslides are detected with an 18% false alarm ratio. This study shows that MaTRIGRS demonstrates acceptable spatiotemporal predictive skill for landslide occurrences within a 120-m radius in space and a hurricane-event-duration (h) in time, offering the potential to serve as a landslide warning system in areas where accurate rainfall forecasts and detailed field data are available. The validation can be further improved with additional landslide information including the exact time of failure for each

Slope 10 m grid derived from gridded bathymetry of Agrihan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI. Cell values reflect the maximum rate of...

Slope 10 m grid derived from gridded bathymetry of Pagan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI. Cell values reflect the maximum rate of...

Slope 10 m grid derived from gridded bathymetry of Guguan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI. Cell values reflect the maximum rate of...

Slope 10 m grid derived from gridded bathymetry of Maug Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI. Cell values reflect the maximum rate of...

Slope 10 m grid derived from gridded bathymetry of Sarigan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI. Cell values reflect the maximum rate of...

Slope 10 m grid derived from gridded bathymetry of Supply Reef, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI. Cell values reflect the maximum rate of...

Impacts of the leading modes of tropical Indian Ocean sea surface temperature anomaly on sub-seasonal evolution of the circulation and rainfall over East Asia during boreal spring and summer

Science.gov (United States)

Liu, Senfeng; Duan, Anmin

2017-02-01

The two leading modes of the interannual variability of the tropical Indian Ocean (TIO) sea surface temperature (SST) anomaly are the Indian Ocean basin mode (IOBM) and the Indian Ocean dipole mode (IODM) from March to August. In this paper, the relationship between the TIO SST anomaly and the sub-seasonal evolution of the circulation and rainfall over East Asia during boreal spring and summer is investigated by using correlation analysis and composite analysis based on multi-source observation data from 1979 to 2013, together with numerical simulations from an atmospheric general circulation model. The results indicate that the impacts of the IOBM on the circulation and rainfall over East Asia vary remarkably from spring to summer. The anomalous anticyclone over the tropical Northwest Pacific induced by the warm IOBM is closely linked with the Pacific-Japan or East Asia-Pacific teleconnection pattern, which persists from March to August. In the upper troposphere over East Asia, the warm phase of the IOBM generates a significant anticyclonic response from March to May. In June and July, however, the circulation response is characterized by enhanced subtropical westerly flow. A distinct anomalous cyclone is found in August. Overall, the IOBM can exert significant influence on the western North Pacific subtropical high, the South Asian high, and the East Asian jet, which collectively modulate the precipitation anomaly over East Asia. In contrast, the effects of the IODM on the climate anomaly over East Asia are relatively weak in boreal spring and summer. Therefore, studying the impacts of the TIO SST anomaly on the climate anomaly in East Asia should take full account of the different sub-seasonal response during boreal spring and summer.

North-East monsoon rainfall extremes over the southern peninsular India and their association with El Niño

Science.gov (United States)

Singh, Prem; Gnanaseelan, C.; Chowdary, J. S.

2017-12-01

The present study investigates the relationship between extreme north-east (NE) monsoon rainfall (NEMR) over the Indian peninsula region and El Niño forcing. This turns out to be a critical science issue especially after the 2015 Chennai flood. The puzzle being while most El Niños favour good NE monsoon, some don't. In fact some El Niño years witnessed deficit NE monsoon. Therefore two different cases (or classes) of El Niños are considered for analysis based on standardized NEMR index and Niño 3.4 index with case-1 being both Niño-3.4 and NEMR indices greater than +1 and case-2 being Niño-3.4 index greater than +1 and NEMR index less than -1. Composite analysis suggests that SST anomalies in the central and eastern Pacific are strong in both cases but large differences are noted in the spatial distribution of SST over the Indo-western Pacific region. This questions our understanding of NEMR as mirror image of El Niño conditions in the Pacific. It is noted that the favourable excess NEMR in case-1 is due to anomalous moisture transport from Bay of Bengal and equatorial Indian Ocean to southern peninsular India. Strong SST gradient between warm western Indian Ocean (and Bay of Bengal) and cool western Pacific induced strong easterly wind anomalies during NE monsoon season favour moisture transport towards the core NE monsoon region. Further anomalous moisture convergence and convection over the core NE monsoon region supported positive rainfall anomalies in case-1. While in case-2, weak SST gradients over the Indo-western Pacific and absence of local low level convergence over NE monsoon region are mainly responsible for deficit rainfall. The ocean dynamics in the Indian Ocean displayed large differences during case-1 and case-2, suggesting the key role of Rossby wave dynamics in the Indian Ocean on NE monsoon extremes. Apart from the large scale circulation differences the number of cyclonic systems land fall for case-1 and case-2 have also contributed for

Florence, Oregon Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Florence, Oregon Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Lahaina, Hawaii Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Lahaina, Hawaii Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Newport, Oregon Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Newport, Oregon Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Garibaldi, Oregon Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Garibaldi, Oregon Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Keauhou, Hawaii Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Keauhou, Hawaii Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Hanalei, Hawaii Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Hanalei, Hawaii Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Seaside, Oregon Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Seaside, Oregon Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Nikolski, Alaska Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Nikolski, Alaska Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Kahului, Hawaii Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Kahului, Hawaii Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Haleiwa, Hawaii Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Haleiwa, Hawaii Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Savannah, Georgia Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Savannah, Georgia Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Characteristics of coupled atmosphere-ocean CO2 sensitivity experiments with different ocean formulations

International Nuclear Information System (INIS)

Washington, W.M.; Meehl, G.A.

1990-01-01

The Community Climate Model at the National Center for Atmospheric Research has been coupled to a simple mixed-layer ocean model and to a coarse-grid ocean general circulation model (OGCM). This paper compares the responses of simulated climate to increases of atmospheric carbon dioxide (CO 2 ) in these two coupled models. Three types of simulations were run: (1) control runs with both ocean models, with CO 2 held constant at present-day concentrations, (2) instantaneous doubling of atmospheric CO 2 (from 330 to 660 ppm) with both ocean models, and (3) a gradually increasing (transient) CO 2 concentration starting at 330 ppm and increasing linearly at 1% per year, with the OGCM. The mixed-layer and OGCM cases exhibit increases of 3.5 C and 1.6 C, respectively, in globally averaged surface air temperature for the instantaneous doubling cases. The transient-forcing case warms 0.7 C by the end of 30 years. The mixed-layer ocean yields warmer-than-observed tropical temperatures and colder-than-observed temperatures in the higher latitudes. The coarse-grid OGCM simulates lower-than-observed sea surface temperatures (SSTs) in the tropics and higher-than-observed SSTs and reduced sea-ice extent at higher latitudes. Sensitivity in the OGCM after 30 years is much lower than in simulations with the same atmosphere coupled to a 50-m slab-ocean mixed layer. The OGCM simulates a weaker thermohaline circulation with doubled CO 2 as the high-latitude ocean-surface layer warms and freshens and the westerly wind stress decreases. Convective overturning in the OGCM decreases substantially with CO 2 warming

Characteristics of coupled atmosphere-ocean CO2 sensitivity experiments with different ocean formulations

International Nuclear Information System (INIS)

Washington, W.M.; Meehl, G.A.

1991-01-01

The Community Climate Model at the National Center for Atmospheric Research has been coupled to a simple mixed-layer ocean model and to a coarse-grid ocean general circulation model (OGCM). This paper compares the responses of simulated climate to increases of atmospheric carbon dioxide (CO 2 ) in these two coupled models. Three types of simulations were run: (1) control runs with both ocean models, with CO 2 held constant at present-day concentrations, (2) instantaneous doubling of atmospheric CO 2 (from 330 to 660 ppm) with both ocean models, and (3) a gradually increasing (transient) CO 2 concentration starting at 330 ppm and increasing linearly at 1% per year, with the OGCM. The mixed-layer and OGCM cases exhibit increases of 3.5 C and 1.6 C, respectively, in globally averaged surface air temperature for the instantaneous doubling cases. The transient-forcing case warms 0.7 C by the end of 30 years. The mixed-layer ocean yields warmer-than-observed tropical temperatures and colder-than-observed temperatures in the higher latitudes. The coarse-grid OGCM simulates lower-than-observed sea surface temperatures (SSTs) in the tropics and higher-than-observed SSTs and reduced sea-ice extent at higher latitudes. Sensitivity in the OGCM after 30 years is much lower than in simulations with the same atmosphere coupled to a 50-m slab-ocean mixed layer. The OGCM simulates a weaker thermohaline circulation with doubled CO 2 as the high-latitude ocean-surface layer warms and freshens and the westerly wind stress decreases. Convective overturning in the OGCM decreases substantially with CO 2 warming. 46 refs.; 20 figs.; 1 tab

First evaluation of MyOcean altimetric data in the Arctic Ocean

DEFF Research Database (Denmark)

Cheng, Yongcun; Andersen, Ole Baltazar; Knudsen, Per

2012-01-01

The MyOcean V2 preliminary (V2p) data set of weekly gridded sea level anomaly (SLA) maps from 1993 to 2009 over the Arctic region is evaluated against existing altimetric data sets and tide gauge data. Compared with DUACS V3.0.0 (Data Unification and Altimeter Combination System) data set, MyOcean...... V2p data set improves spatial coverage and quality as well as maximum temporal correlation coefficient between altimetry and tide gauge data. The estimated amplitude of sea level annual signal and linear sea level trend from MyOcean data set are evaluated against altimetry from DUACS and RADS (Radar...... Altimeter Database System), the SODA (Simple Ocean Data Assimilation) ocean reanalysis and tide gauge data sets from PSMSL (Permanent Service for Mean Sea Level). The results show that the MyOcean data set fits in-situ measurements better than DUACS data set with respect to amplitude of annual signal...

Slope 10 m grid derived from gridded bathymetry of Asuncion Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (10 m cell size) multibeam bathymetry collected aboard NOAA Ship Hiialaka'i and R/V AHI. Cell values reflect the maximum rate of change...

Slope 5 m grid derived from gridded bathymetry of Rota Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI. Cell values reflect the maximum rate of change...

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

Science.gov (United States)

Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

2016-01-01

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW’s) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. PMID:27314363

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data.

Science.gov (United States)

Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

2016-06-15

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

Directory of Open Access Journals (Sweden)

Haris Akram Bhatti

2016-06-01

Full Text Available With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA Climate Prediction Centre (CPC morphing technique (CMORPH satellite rainfall product (CMORPH in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW sizes and for sequential windows (SW’s of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE. To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r and standard deviation (SD. Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

Shemya, Alaska Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Shemya, Alaska Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is...

Kodiak, Alaska Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Kodiak, Alaska Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is...

Sitka, Alaska Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Sitka, Alaska Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is...

Homer, Alaska Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Homer, Alaska Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is...

Eureka, California Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Eureka, California Forecast Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is a...

Seward, Alaska Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Seward, Alaska Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is...

Kihei, Hawaii Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Kihei, Hawaii Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is...

Unalaska, Alaska Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Unalaska, Alaska Forecast Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is a...

Cordova, Alaska Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Cordova, Alaska Forecast Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is a...

Chignik, Alaska Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Chignik, Alaska Forecast Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is a...

Genetic Programming for the Downscaling of Extreme Rainfall Events on the East Coast of Peninsular Malaysia

Directory of Open Access Journals (Sweden)

Sahar Hadi Pour

2014-11-01

Full Text Available A genetic programming (GP-based logistic regression method is proposed in the present study for the downscaling of extreme rainfall indices on the east coast of Peninsular Malaysia, which is considered one of the zones in Malaysia most vulnerable to climate change. A National Centre for Environmental Prediction reanalysis dataset at 42 grid points surrounding the study area was used to select the predictors. GP models were developed for the downscaling of three extreme rainfall indices: days with larger than or equal to the 90th percentile of rainfall during the north-east monsoon; consecutive wet days; and consecutive dry days in a year. Daily rainfall data for the time periods 1961–1990 and 1991–2000 were used for the calibration and validation of models, respectively. The results are compared with those obtained using the multilayer perceptron neural network (ANN and linear regression-based statistical downscaling model (SDSM. It was found that models derived using GP can predict both annual and seasonal extreme rainfall indices more accurately compared to ANN and SDSM.

A comparison of extreme rainfall characteristics in the Brazilian Amazon derived from two gridded data sets and a national rain gauge network

Science.gov (United States)

Clarke, Robin T.; Bulhoes Mendes, Carlos Andre; Costa Buarque, Diogo

2010-07-01

Two issues of particular importance for the Amazon watershed are: whether annual maxima obtained from reanalysis and raingauge records agree well enough for the former to be useful in extending records of the latter; and whether reported trends in Amazon annual rainfall are reflected in the behavior of annual extremes in precipitation estimated from reanalyses and raingauge records. To explore these issues, three sets of daily precipitation data (1979-2001) from the Brazilian Amazon were analyzed (NCEP/NCAR and ERA-40 reanalyses, and records from the raingauge network of the Brazilian water resources agency - ANA), using the following variables: (1) mean annual maximum precipitation totals, accumulated over one, two, three and five days; (2) linear trends in these variables; (3) mean length of longest within-year "dry" spell; (4) linear trends in these variables. Comparisons between variables obtained from all three data sources showed that reanalyses underestimated time-trends and mean annual maximum precipitation (over durations of one to five days), and the correlations between reanalysis and spatially-interpolated raingauge estimates were small for these two variables. Both reanalyses over-estimated mean lengths of dry period relative to the mean length recorded by the raingauge network. Correlations between the trends calculated from all three data sources were small. Time-trends averaged over the reanalysis grid-squares, and spatially-interpolated time trends from raingauge data, were all clustered around zero. In conclusion, although the NCEP/NCAR and ERA-40 gridded data-sets may be valuable for studies of inter-annual variability in precipitation totals, they were found to be inappropriate for analysis of precipitation extremes.

A new parallelization algorithm of ocean model with explicit scheme

Science.gov (United States)

Fu, X. D.

2017-08-01

This paper will focus on the parallelization of ocean model with explicit scheme which is one of the most commonly used schemes in the discretization of governing equation of ocean model. The characteristic of explicit schema is that calculation is simple, and that the value of the given grid point of ocean model depends on the grid point at the previous time step, which means that one doesn’t need to solve sparse linear equations in the process of solving the governing equation of the ocean model. Aiming at characteristics of the explicit scheme, this paper designs a parallel algorithm named halo cells update with tiny modification of original ocean model and little change of space step and time step of the original ocean model, which can parallelize ocean model by designing transmission module between sub-domains. This paper takes the GRGO for an example to implement the parallelization of GRGO (Global Reduced Gravity Ocean model) with halo update. The result demonstrates that the higher speedup can be achieved at different problem size.

Evaluation of GPM IMERG Early, Late, and Final rainfall estimates using WegenerNet gauge data in southeastern Austria

Directory of Open Access Journals (Sweden)

S. O

2017-12-01

Full Text Available The Global Precipitation Measurement (GPM Integrated Multi-satellite Retrievals for GPM (IMERG products provide quasi-global (60° N–60° S precipitation estimates, beginning March 2014, from the combined use of passive microwave (PMW and infrared (IR satellites comprising the GPM constellation. The IMERG products are available in the form of near-real-time data, i.e., IMERG Early and Late, and in the form of post-real-time research data, i.e., IMERG Final, after monthly rain gauge analysis is received and taken into account. In this study, IMERG version 3 Early, Late, and Final (IMERG-E,IMERG-L, and IMERG-F half-hourly rainfall estimates are compared with gauge-based gridded rainfall data from the WegenerNet Feldbach region (WEGN high-density climate station network in southeastern Austria. The comparison is conducted over two IMERG 0.1°  ×  0.1° grid cells, entirely covered by 40 and 39 WEGN stations each, using data from the extended summer season (April–October for the first two years of the GPM mission. The entire data are divided into two rainfall intensity ranges (low and high and two seasons (warm and hot, and we evaluate the performance of IMERG, using both statistical and graphical methods. Results show that IMERG-F rainfall estimates are in the best overall agreement with the WEGN data, followed by IMERG-L and IMERG-E estimates, particularly for the hot season. We also illustrate, through rainfall event cases, how insufficient PMW sources and errors in motion vectors can lead to wide discrepancies in the IMERG estimates. Finally, by applying the method of Villarini and Krajewski (2007, we find that IMERG-F half-hourly rainfall estimates can be regarded as a 25 min gauge accumulation, with an offset of +40 min relative to its nominal time.

Evaluation of GPM IMERG Early, Late, and Final rainfall estimates using WegenerNet gauge data in southeastern Austria

Science.gov (United States)

O, Sungmin; Foelsche, Ulrich; Kirchengast, Gottfried; Fuchsberger, Juergen; Tan, Jackson; Petersen, Walter A.

2017-12-01

The Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) products provide quasi-global (60° N-60° S) precipitation estimates, beginning March 2014, from the combined use of passive microwave (PMW) and infrared (IR) satellites comprising the GPM constellation. The IMERG products are available in the form of near-real-time data, i.e., IMERG Early and Late, and in the form of post-real-time research data, i.e., IMERG Final, after monthly rain gauge analysis is received and taken into account. In this study, IMERG version 3 Early, Late, and Final (IMERG-E,IMERG-L, and IMERG-F) half-hourly rainfall estimates are compared with gauge-based gridded rainfall data from the WegenerNet Feldbach region (WEGN) high-density climate station network in southeastern Austria. The comparison is conducted over two IMERG 0.1° × 0.1° grid cells, entirely covered by 40 and 39 WEGN stations each, using data from the extended summer season (April-October) for the first two years of the GPM mission. The entire data are divided into two rainfall intensity ranges (low and high) and two seasons (warm and hot), and we evaluate the performance of IMERG, using both statistical and graphical methods. Results show that IMERG-F rainfall estimates are in the best overall agreement with the WEGN data, followed by IMERG-L and IMERG-E estimates, particularly for the hot season. We also illustrate, through rainfall event cases, how insufficient PMW sources and errors in motion vectors can lead to wide discrepancies in the IMERG estimates. Finally, by applying the method of Villarini and Krajewski (2007), we find that IMERG-F half-hourly rainfall estimates can be regarded as a 25 min gauge accumulation, with an offset of +40 min relative to its nominal time.

The Green Ocean Amazon Experiment (GoAmazon2014/5) Observes Pollution Affecting Gases, Aerosols, Clouds, and Rainfall over the Rain Forest

Energy Technology Data Exchange (ETDEWEB)

Martin, S. T. [Harvard University, Cambridge, Massachusetts; Artaxo, P. [University of São Paulo, São Paulo, Brazil; Machado, L. [National Institute for Space Research, São José dos Campos, Brazil; Manzi, A. O. [National Institute of Amazonian Research, Manaus, Amazonas, Brazil; Souza, R. A. F. [Amazonas State University, Amazonas, Brazil; Schumacher, C. [Texas A& amp,M University, College Station, Texas; Wang, J. [Brookhaven National Laboratory, Upton, New York; Biscaro, T. [National Institute for Space Research, São José dos Campos, Brazil; Brito, J. [University of São Paulo, São Paulo, Brazil; Calheiros, A. [National Institute for Space Research, São José dos Campos, Brazil; Jardine, K. [Lawrence Berkeley National Lab, Berkeley, California; Medeiros, A. [Amazonas State University, Amazonas, Brazil; Portela, B. [National Institute of Amazonian Research, Manaus, Amazonas, Brazil; de Sá, S. S. [Harvard University, Cambridge, Massachusetts; Adachi, K. [Meteorological Research Institute, Tsukuba, Ibaraki, Japan; Aiken, A. C. [Los Alamos National Laboratory, Los Alamos, New Mexico; Albrecht, R. [University of São Paulo, São Paulo, Brazil; Alexander, L. [Pacific Northwest National Laboratory, Richland, Washington; Andreae, M. O. [Max Planck Institute for Chemistry, Mainz, Germany; Barbosa, H. M. J. [University of São Paulo, São Paulo, Brazil; Buseck, P. [Arizona State University, Tempe, Arizona; Chand, D. [Pacific Northwest National Laboratory, Richland, Washington; Comstock, J. M. [Pacific Northwest National Laboratory, Richland, Washington; Day, D. A. [University of Colorado Boulder, Boulder, Colorado; Dubey, M. [Los Alamos National Laboratory, Los Alamos, New Mexico; Fan, J. [Pacific Northwest National Laboratory, Richland, Washington; Fast, J. [Pacific Northwest National Laboratory, Richland, Washington; Fisch, G. [Aeronautic and Space Institute, São José dos Campos, Brazil; Fortner, E. [Aerodyne, Inc., Billerica, Massachusetts; Giangrande, S. [Brookhaven National Laboratory, Upton, New York; Gilles, M. [Lawrence Berkeley National Lab, Berkeley, California; Goldstein, A. H. [University of California, Berkeley, Berkeley, California; Guenther, A. [University of California, Irvine, Irvine, California; Hubbe, J. [Pacific Northwest National Laboratory, Richland, Washington; Jensen, M. [Brookhaven National Laboratory, Upton, New York; Jimenez, J. L. [University of Colorado Boulder, Boulder, Colorado; Keutsch, F. N. [Harvard University, Cambridge, Massachusetts; Kim, S. [University of California, Irvine, Irvine, California; Kuang, C. [Brookhaven National Laboratory, Upton, New York; Laskin, A. [Pacific Northwest National Laboratory, Richland, Washington; McKinney, K. [Harvard University, Cambridge, Massachusetts; Mei, F. [Pacific Northwest National Laboratory, Richland, Washington; Miller, M. [Rutgers, The State University of New Jersey, New Brunswick, New Jersey; Nascimento, R. [Amazonas State University, Amazonas, Brazil; Pauliquevis, T. [Federal University of São Paulo, São Paulo, Brazil; Pekour, M. [Pacific Northwest National Laboratory, Richland, Washington; Peres, J. [University of São Paulo, São Paulo, Brazil; Petäjä, T. [University of Helsinki, Helsinki, Finland; Pöhlker, C. [Max Planck Institute for Chemistry, Mainz, Germany; Pöschl, U. [Max Planck Institute for Chemistry, Mainz, Germany; Rizzo, L. [Federal University of São Paulo, São Paulo, Brazil; Schmid, B. [Pacific Northwest National Laboratory, Richland, Washington; Shilling, J. E. [Pacific Northwest National Laboratory, Richland, Washington; Dias, M. A. Silva [University of São Paulo, São Paulo, Brazil; Smith, J. N. [University of California, Irvine, Irvine, California; Tomlinson, J. M. [Pacific Northwest National Laboratory, Richland, Washington; Tóta, J. [Federal University of West Para, Santarém, Pará, Brazil; Wendisch, M. [University of Leipzig, Leipzig, Germany

2017-05-01

The Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) experiment took place around the urban region of Manaus in central Amazonia across two years. The urban pollution plume was used to study the susceptibility of gases, aerosols, clouds, and rainfall to human activities in a tropical environment. Many aspects of air quality, weather, terrestrial ecosystems, and climate work differently in the tropics than in the more thoroughly studied USA, employed an unparalleled suite of measurements at nine ground sites and onboard two aircraft to investigate the flow of background air into Manaus, the emissions into the air over the city, and the advection of the pollution downwind of the city. Herein, to visualize this train of processes and its effects, observations aboard a low-flying aircraft are presented. Comparative measurements within and adjacent to the plume followed the emissions of biogenic volatile organic carbon compounds (BVOCs) from the tropical forest, their transformations by the atmospheric oxidant cycle, alterations of this cycle by the influence of the pollutants, transformations of the chemical products into aerosol particles, the relationship of these particles to cloud condensation nuclei (CCN) activity, and the differences in cloud properties and rainfall for background compared to polluted conditions. The observations of the GoAmazon2014/5 experiment illustrate how the hydrologic cycle, radiation balance, and carbon recycling may be affected by present-day as well as future economic development and pollution over the Amazonian tropical forest.

A Canonical Response in Rainfall Characteristics to Global Warming: Projections by IPCC CMIP5 Models

Science.gov (United States)

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

2012-01-01

Changes in rainfall characteristics induced by global warming are examined based on probability distribution function (PDF) analysis, from outputs of 14 IPCC (Intergovernmental Panel on Climate Change), CMIP (5th Coupled Model Intercomparison Project) models under various scenarios of increased CO2 emissions. Results show that collectively CMIP5 models project a robust and consistent global and regional rainfall response to CO2 warming. Globally, the models show a 1-3% increase in rainfall per degree rise in temperature, with a canonical response featuring large increase (100-250 %) in frequency of occurrence of very heavy rain, a reduction (5-10%) of moderate rain, and an increase (10-15%) of light rain events. Regionally, even though details vary among models, a majority of the models (>10 out of 14) project a consistent large scale response with more heavy rain events in climatologically wet regions, most pronounced in the Pacific ITCZ and the Asian monsoon. Moderate rain events are found to decrease over extensive regions of the subtropical and extratropical oceans, but increases over the extratropical land regions, and the Southern Oceans. The spatial distribution of light rain resembles that of moderate rain, but mostly with opposite polarity. The majority of the models also show increase in the number of dry events (absence or only trace amount of rain) over subtropical and tropical land regions in both hemispheres. These results suggest that rainfall characteristics are changing and that increased extreme rainfall events and droughts occurrences are connected, as a consequent of a global adjustment of the large scale circulation to global warming.

Rugosity grid derived from gridded bathymetry of Thirty-Five Fathom Bank and Thirty-Seven Fathom Bank, Commonwealth of the Northern Marianas.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, aboard NOAA Ship Oscar Elton Sette. Cell values reflect the (surface area) / (planimetric...

Bathymetric Position Index (BPI) Structures 5m grid derived from gridded bathymetry of Saipan Island, Commonwealth of the Northern Marianas

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from a focal mean analysis on bathymetry and slope. The bathymetry grid (5 m cell size) is derived from two sources: Multibeam bathymetry...

Idaho Batholith Study Area Isostatic Gravity Grid

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A 2 kilometer isostatic gravity grid for the Idaho batholith study area. Number of columns is 331 and number of rows is 285. The order of the data is from the lower...

Idaho Batholith Study Area Bouguer Gravity Grid

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A 2 kilometer Bouguer gravity anomaly grid for the Idaho batholith study area. Number of columns is 331 and number of rows is 285. The order of the data is from the...

Gamma-ray dose rate increase at rainfall events and their air-mass origins

International Nuclear Information System (INIS)

Iyogi, Takashi; Hisamatsu, Shun'ichi; Inaba, Jiro

2007-01-01

The environmental γ-ray dose rate and precipitation rates were measured at our institute, in Rokkasho, Aomori, Japan. We analyzed 425 rainfall events in which the precipitation rate was over 0.5 mm from April through November during the years 2003 to 2005. Backward trajectories for 5 d starting from 1000 m above Rokkasho at the time of the maximum dose rate in a rainfall event, were calculated by using the HYSPLIT model of the NOAA Air Resources Laboratory. The trajectories for 5 d were classified by visual inspection according to the passage areas; Pacific Ocean, Asian Continent and Japan Islands. The increase of cumulative environmental γ-ray dose during a rainfall event was plotted against the precipitation in the event, and their relationship was separately examined according to the air-mass passage area, i.e. origin of the air-mass. Our results showed that the origin of air-mass was an important factor affecting the increase of environmental γ-ray dose rate by rainfall. (author)

Wake Island Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Wake Island Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is a...

Adak, Alaska Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Adak, Alaska Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is a...

Gridded bathymetry of Barbers Point, Oahu Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry (1m) of Barbers Point ship grounding site, Oahu, Hawaii, USA. The data include multibeam bathymetry from the Reson 8101 multibeam sonar collected...

Hilo, Hawaii Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Hilo, Hawaii Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is a...

Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

Science.gov (United States)

Kashid, Satishkumar S.; Maity, Rajib

2012-08-01

SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different

Vertical Profiles of Latent Heat Release over the Global Tropics using TRMM rainfall products from December 1997 to November 2001

Science.gov (United States)

Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.

2002-01-01

NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2001. Rainfall, latent heating and radar reflectivity structures between El Nino (DE 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs. west Pacific, Africa vs. S. America) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in strtaiform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. The Goddard Cumulus Ensemble Model is being used to simulate various mesoscale convective systems that developed in different geographic locations. Specifically, the model estimated rainfall, radar reflectivity and latent heating profiles will be compared to observational data collected from TRMM field campaigns over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and the central Pacific in 1999 (KWAJEX). Sounding diagnosed heating budgets and radar reflectivity from these experiments can provide the means to validate (heating product) as well as improve the GCE model.

CRED Gridded Bathymetry of Necker Island (100-021) in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-021b is a 60-m ASCII grid of depth data collected near Necker Island in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced as...

Bathymetric Position Index (BPI) Zones 5m grid derived from gridded bathymetry of Saipan Island, Commonwealth of the Northern Marianas

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The bathymetry grid (5 m cell size) is derived from bathymetry from two sources: Multibeam...

Synoptic monthly gridded Global Temperature and Salinity Profile Programme (GTSPP) water temperature and salinity from January 1990 to December 2009 (NCEI Accession 0138647)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The synoptic gridded Global Temperature and Salinity Profile Programme (SG-GTSPP) provides world ocean 3D gridded temperature and salinity data in monthly increment...

Rainy Day: A Remote Sensing-Driven Extreme Rainfall Simulation Approach for Hazard Assessment

Science.gov (United States)

Wright, Daniel; Yatheendradas, Soni; Peters-Lidard, Christa; Kirschbaum, Dalia; Ayalew, Tibebu; Mantilla, Ricardo; Krajewski, Witold

2015-04-01

Progress on the assessment of rainfall-driven hazards such as floods and landslides has been hampered by the challenge of characterizing the frequency, intensity, and structure of extreme rainfall at the watershed or hillslope scale. Conventional approaches rely on simplifying assumptions and are strongly dependent on the location, the availability of long-term rain gage measurements, and the subjectivity of the analyst. Regional and global-scale rainfall remote sensing products provide an alternative, but are limited by relatively short (~15-year) observational records. To overcome this, we have coupled these remote sensing products with a space-time resampling framework known as stochastic storm transposition (SST). SST "lengthens" the rainfall record by resampling from a catalog of observed storms from a user-defined region, effectively recreating the regional extreme rainfall hydroclimate. This coupling has been codified in Rainy Day, a Python-based platform for quickly generating large numbers of probabilistic extreme rainfall "scenarios" at any point on the globe. Rainy Day is readily compatible with any gridded rainfall dataset. The user can optionally incorporate regional rain gage or weather radar measurements for bias correction using the Precipitation Uncertainties for Satellite Hydrology (PUSH) framework. Results from Rainy Day using the CMORPH satellite precipitation product are compared with local observations in two examples. The first example is peak discharge estimation in a medium-sized (~4000 square km) watershed in the central United States performed using CUENCAS, a parsimonious physically-based distributed hydrologic model. The second example is rainfall frequency analysis for Saint Lucia, a small volcanic island in the eastern Caribbean that is prone to landslides and flash floods. The distinct rainfall hydroclimates of the two example sites illustrate the flexibility of the approach and its usefulness for hazard analysis in data-poor regions.

Prevention through policy : Urban macroplastic leakages to the marine environment during extreme rainfall events

NARCIS (Netherlands)

Axelsson, Charles; van Sebille, Erik

2017-01-01

The leakage of large plastic litter (macroplastics) into the ocean is a major environmental problem. A significant fraction of this leakage originates from coastal cities, particularly during extreme rainfall events. As coastal cities continue to grow, finding ways to reduce this macroplastic

Spatiotemporal Scaling Effect on Rainfall Network Design Using Entropy

Directory of Open Access Journals (Sweden)

Chiang Wei

2014-08-01

Full Text Available Because of high variation in mountainous areas, rainfall data at different spatiotemporal scales may yield potential uncertainty for network design. However, few studies focus on the scaling effect on both the spatial and the temporal scale. By calculating the maximum joint entropy of hourly typhoon events, monthly, six dry and wet months and annual rainfall between 1992 and 2012 for 1-, 3-, and 5-km grids, the relocated candidate rain gauges in the National Taiwan University Experimental Forest of Central Taiwan are prioritized. The results show: (1 the network exhibits different locations for first prioritized candidate rain gauges for different spatiotemporal scales; (2 the effect of spatial scales is insignificant compared to temporal scales; and (3 a smaller number and a lower percentage of required stations (PRS reach stable joint entropy for a long duration at finer spatial scale. Prioritized candidate rain gauges provide key reference points for adjusting the network to capture more accurate information and minimize redundancy.

CRED Gridded Bathymetry of Nihoa Island (100-025) in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-025b is a 60-m ASCII grid of depth data collected near Nihoa Island in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced as part...

CRED Gridded Bathymetry of Raita Bank (100-009), in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-009b is a 60-m ASCII grid of depth data collected near Raita Bank in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced as part...

Simulation of an extreme heavy rainfall event over Chennai, India using WRF: Sensitivity to grid resolution and boundary layer physics

KAUST Repository

Srinivas, C.V.

2018-05-04

In this study, the heavy precipitation event on 01 December 2015 over Chennai located on the southeast coast of India was simulated using the Weather Research and Forecast (WRF) model. A series of simulations were conducted using explicit convection and varying the planetary boundary layer (PBL) parameterization schemes. The model results were compared with available surface, satellite and Doppler Weather Radar observations. Simulations indicate strong, sustained moist convection associated with development of a mesoscale upper air cyclonic circulation, during the passage of a synoptic scale low-pressure trough caused heavy rainfall over Chennai and its surroundings. Results suggest that veering of wind with height associated with strong wind shear in the layer 800–400 hPa together with dry air advection facilitated development of instability and initiation of convection. The 1-km domain using explicit convection improved the prediction of rainfall intensity of about 450 mm and its distribution. The PBL physics strongly influenced the rainfall prediction by changing the location of upper air circulation, energy transport, moisture convergence and intensity of convection in the schemes YSU, MYJ and MYNN. All the simulations underestimated the first spell of the heavy rainfall. While YSU and MYJ schemes grossly underestimated the rainfall and dislocated the area of maximum rainfall, the higher order MYNN scheme simulated the rainfall pattern in better agreement with observations. The MYNN showed lesser mixing and simulated more humid boundary layer, higher convective available potential energy (CAPE) and stronger winds at mid-troposphere than did the other schemes. The MYNN also realistically simulated the location of upper air cyclonic flow and various dynamic and thermodynamic features. Consequently it simulated stronger moisture convergence and higher precipitation.

Simulation of an extreme heavy rainfall event over Chennai, India using WRF: Sensitivity to grid resolution and boundary layer physics

KAUST Repository

Srinivas, C.V.; Yesubabu, V.; Hari Prasad, D.; Hari Prasad, K.B.R.R.; Greeshma, M.M.; Baskaran, R.; Venkatraman, B.

2018-01-01

In this study, the heavy precipitation event on 01 December 2015 over Chennai located on the southeast coast of India was simulated using the Weather Research and Forecast (WRF) model. A series of simulations were conducted using explicit convection and varying the planetary boundary layer (PBL) parameterization schemes. The model results were compared with available surface, satellite and Doppler Weather Radar observations. Simulations indicate strong, sustained moist convection associated with development of a mesoscale upper air cyclonic circulation, during the passage of a synoptic scale low-pressure trough caused heavy rainfall over Chennai and its surroundings. Results suggest that veering of wind with height associated with strong wind shear in the layer 800–400 hPa together with dry air advection facilitated development of instability and initiation of convection. The 1-km domain using explicit convection improved the prediction of rainfall intensity of about 450 mm and its distribution. The PBL physics strongly influenced the rainfall prediction by changing the location of upper air circulation, energy transport, moisture convergence and intensity of convection in the schemes YSU, MYJ and MYNN. All the simulations underestimated the first spell of the heavy rainfall. While YSU and MYJ schemes grossly underestimated the rainfall and dislocated the area of maximum rainfall, the higher order MYNN scheme simulated the rainfall pattern in better agreement with observations. The MYNN showed lesser mixing and simulated more humid boundary layer, higher convective available potential energy (CAPE) and stronger winds at mid-troposphere than did the other schemes. The MYNN also realistically simulated the location of upper air cyclonic flow and various dynamic and thermodynamic features. Consequently it simulated stronger moisture convergence and higher precipitation.

Simulating the characteristics of tropical cyclones over the South West Indian Ocean using a Stretched-Grid Global Climate Model

Science.gov (United States)

Maoyi, Molulaqhooa L.; Abiodun, Babatunde J.; Prusa, Joseph M.; Veitch, Jennifer J.

2018-03-01

Tropical cyclones (TCs) are one of the most devastating natural phenomena. This study examines the capability of a global climate model with grid stretching (CAM-EULAG, hereafter CEU) in simulating the characteristics of TCs over the South West Indian Ocean (SWIO). In the study, CEU is applied with a variable increment global grid that has a fine horizontal grid resolution (0.5° × 0.5°) over the SWIO and coarser resolution (1° × 1°—2° × 2.25°) over the rest of the globe. The simulation is performed for the 11 years (1999-2010) and validated against the Joint Typhoon Warning Center (JTWC) best track data, global precipitation climatology project (GPCP) satellite data, and ERA-Interim (ERAINT) reanalysis. CEU gives a realistic simulation of the SWIO climate and shows some skill in simulating the spatial distribution of TC genesis locations and tracks over the basin. However, there are some discrepancies between the observed and simulated climatic features over the Mozambique channel (MC). Over MC, CEU simulates a substantial cyclonic feature that produces a higher number of TC than observed. The dynamical structure and intensities of the CEU TCs compare well with observation, though the model struggles to produce TCs with a deep pressure centre as low as the observed. The reanalysis has the same problem. The model captures the monthly variation of TC occurrence well but struggles to reproduce the interannual variation. The results of this study have application in improving and adopting CEU for seasonal forecasting over the SWIO.

Port Angeles, Washington Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Port Angeles, Washington Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Los Angeles, California Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Los Angeles, California Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Crescent City, California Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Crescent City, California Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Christiansted, Virgin Islands Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Christiansted, Virgin Islands Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Santa Barbara, California Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Santa Barbara, California Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Point Reyes, California Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Point Reyes, California Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

San Francisco, California Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The San Francisco, California Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

British Columbia, Canada Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The British Columbia, Canada Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Interannual Rainfall Variability in North-East Brazil: Observation and Model Simulation

Science.gov (United States)

Harzallah, A.; Rocha de Aragão, J. O.; Sadourny, R.

1996-08-01

The relationship between interannual variability of rainfall in north-east Brazil and tropical sea-surface temperature is studied using observations and model simulations. The simulated precipitation is the average of seven independent realizations performed using the Laboratoire de Météorologie Dynamique atmospheric general model forced by the 1970-1988 observed sea-surface temperature. The model reproduces very well the rainfall anomalies (correlation of 091 between observed and modelled anomalies). The study confirms that precipitation in north-east Brazil is highly correlated to the sea-surface temperature in the tropical Atlantic and Pacific oceans. Using the singular value decomposition method, we find that Nordeste rainfall is modulated by two independent oscillations, both governed by the Atlantic dipole, but one involving only the Pacific, the other one having a period of about 10 years. Correlations between precipitation in north-east Brazil during February-May and the sea-surface temperature 6 months earlier indicate that both modes are essential to estimate the quality of the rainy season.

Fajardo, Puerto Rico Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Fajardo, Puerto Rico Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Ponce, Puerto Rico Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Ponce, Puerto Rico Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Daytona Beach, Florida Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Daytona Beach, Florida Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Sand Point, Alaska Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Sand Point, Alaska Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Arena Cove, California Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Arena Cove, California Forecast Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Neah Bay, Washington Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Neah Bay, Washington Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Toke Point, Washington Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Toke Point, Washington Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Palm Beach, Florida Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Palm Beach, Florida Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Pearl Harbor, Hawaii Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Pearl Harbor, Hawaii Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Arecibo, Puerto Rico Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Arecibo, Puerto Rico Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Port Orford, Oregon Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Port Orford, Oregon Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Kailua-Kona, Hawaii Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Kailua-Kona, Hawaii Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Port Alexander, Alaska Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Port Alexander, Alaska Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

La Push, Washington Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The La Push, Washington Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

Derivation and Error Analysis of the Earth Magnetic Anomaly Grid at 2 arc min Resolution Version 3 (EMAG2v3)

Science.gov (United States)

Meyer, B.; Chulliat, A.; Saltus, R.

2017-12-01

The Earth Magnetic Anomaly Grid at 2 arc min resolution version 3, EMAG2v3, combines marine and airborne trackline observations, satellite data, and magnetic observatory data to map the location, intensity, and extent of lithospheric magnetic anomalies. EMAG2v3 includes over 50 million new data points added to NCEI's Geophysical Database System (GEODAS) in recent years. The new grid relies only on observed data, and does not utilize a priori geologic structure or ocean-age information. Comparing this grid to other global magnetic anomaly compilations (e.g., EMAG2 and WDMAM), we can see that the inclusion of a priori ocean-age patterns forces an artificial linear pattern to the grid; the data-only approach allows for greater complexity in representing the evolution along oceanic spreading ridges and continental margins. EMAG2v3 also makes use of the satellite-derived lithospheric field model MF7 in order to accurately represent anomalies with wavelengths greater than 300 km and to create smooth grid merging boundaries. The heterogeneous distribution of errors in the observations used in compiling the EMAG2v3 was explored, and is reported in the final distributed grid. This grid is delivered at both 4 km continuous altitude above WGS84, as well as at sea level for all oceanic and coastal regions.

CRED Gridded Bathymetry of French Frigate Shoals (100-019) in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-019b is a 60-m ASCII grid of depth data collected near French Frigate Shoals in the Northwestern Hawaiian Islands as of May 2003. This grid has been...

CRED Gridded Bathymetry of East Gardner Pinnacles (100-016) in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-016b is a 60-m ASCII grid of depth data collected near E Gardner Pinnacles in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced...

CRED Gridded Bathymetry of Northeast Gardner Pinnacles (100-013) in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-013b is a 60-m ASCII grid of depth data collected near NE Gardner Pinnacles in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced...

CRED Gridded Bathymetry of East Necker Seamount (100-023) in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-023b is a 60-m ASCII grid of depth data collected near E. Necker Seamount in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced...

CRED Gridded Bathymetry of Southwest Gardner Pinnacles (100-012) in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-012b is a 60-m ASCII grid of depth data collected near SW Gardner Pinnacles in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced...

CRED Gridded Bathymetry near Lisianski Island and Pioneer Bank (100-002), Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-002b is a 60-m ASCII grid of depth data collected near Lisianski Island and Pioneer Bank in the Northwestern Hawaiian Islands as of May 2003. This grid has...

Key West, Florida Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Key West, Florida Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Montauk, New York Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Montauk, New York Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

24 arc-second Kenai Peninsula Bororugh Alaska Elevation Grid

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The 24 arc-second Kenai Peninsula Bororugh Alaska Elevation Grid provides bathymetric data in ASCII raster format of 24 second resolution in geographic coordinates....

Bar Harbor, ME Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Bar Harbor, Maine Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

Apra Harbor, Guam Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Apra Harbor, Guam Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

GPM Mission Gridded Text Products Providing Surface Precipitation Retrievals

Science.gov (United States)

Stocker, Erich Franz; Kelley, Owen; Huffman, George; Kummerow, Christian

2015-04-01

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 GMI/DPR 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 reseachers 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 GMI/DPR (2) surface precipitation retrievals for the partner

Vertical Profiles of Latent Heat Release over the Global Tropics using TRMM Rainfall Products from December 1997 to November 2002

Science.gov (United States)

Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.

2003-01-01

NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2000. Rainfall, latent heating and radar reflectivity structures between El Nino (DJF 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs west Pacific, Africa vs. S. America ) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in stratiform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. The Goddard Cumulus Ensemble Model is being used to simulate various mesoscale convective systems that developed in different geographic locations. Specifically, the model estimated rainfall, radar reflectivity and latent heating profiles will be compared to observational data collected from TRMM field campaigns over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and the central Pacific in 1999 (KWAJEX). Sounding diagnosed heating budgets and radar reflectivity from these experiments can provide the means to validate (heating product) as well as improve the GCE model. Review of other latent heating algorithms will be discussed in the workshop.

Changing On Diurnal Cycle Of Rainfall In Northern Coastal Of West Java

Science.gov (United States)

Yulihastin, E.; Hadi, T. W.; Ningsih, N. S.

2017-12-01

The floods event in the north of Java was largely due to persistent of rainfall that occurred in the morning which indicated of deviation of diurnal pattern of rainfall. The shift of the phase of diurnal rainfall cycle using TRMM satellite hourly data of 3B41RT on the rainy period of 2000-2016 exhibits over land from Late Afternoon-Early Midnight (LA-EM) to morning. The peak of the cycle changes from diurnal to semidiurnal with a peak occurring in LA-EM and morning. Location of rainfall which usually occurs in the oceans shifted into near coastal area. The classification of diurnal rainfall cycles based on composite analysis shows four types: Normal (N) Type (45.6%) with one peak rainfall occurring in the afternoon until night, Diurnal (D) Type (26%) with one peak and phase opposite to normal type, Semidiurnal (SD) Type (6.5 %) with two peaks and the main peak occurring in the afternoon until night, Third Diurnal (TD) Type (21.7%) with three peaks and the main peak occurs in the morning. The classification was confirmed using the objective method of Empirical Mode Decomposition (EMD) and obtained three IMFs representing three diurnal cycle modes of Type TD (67.8%) with the main rain peak taking place in the afternoon, Type D with rain peak occurring in the early hours (18.9%), and SD type (9.9%) with the first peak occurred in the afternoon. For D Type, the results also prove that the diurnal cycle with significant deviations in amplitude occurred in February 2002, 2004, 2008, 2014, wich is the maximum rainfall occurs in the EM. It also seems that in those years, rainfall intensity is concentrated on the northern coast of West Java while in the Java Sea rainfall was minimum.

Rugosity 10 m grid derived from gridded bathymetry of Farallon de Pajaros (Uracas) Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Elfin Cove, Alaska Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Elfin Cove, Alaska Forecast Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is a...

CRED Gridded Bathymetry of Northwest Gardner Pinnacles (100-011) in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-011b is a 60-m ASCII grid of depth data collected near Kure Atoll in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced as part...

CRED Gridded Bathymetry of Southeast Maro Reef (100-010) in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-010b is a 60-m ASCII grid of depth data collected near SE Maro Reef in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced as part...

Prediction of early summer rainfall over South China by a physical-empirical model

Science.gov (United States)

Yim, So-Young; Wang, Bin; Xing, Wen

2014-10-01

In early summer (May-June, MJ) the strongest rainfall belt of the northern hemisphere occurs over the East Asian (EA) subtropical front. During this period the South China (SC) rainfall reaches its annual peak and represents the maximum rainfall variability over EA. Hence we establish an SC rainfall index, which is the MJ mean precipitation averaged over 72 stations over SC (south of 28°N and east of 110°E) and represents superbly the leading empirical orthogonal function mode of MJ precipitation variability over EA. In order to predict SC rainfall, we established a physical-empirical model. Analysis of 34-year observations (1979-2012) reveals three physically consequential predictors. A plentiful SC rainfall is preceded in the previous winter by (a) a dipole sea surface temperature (SST) tendency in the Indo-Pacific warm pool, (b) a tripolar SST tendency in North Atlantic Ocean, and (c) a warming tendency in northern Asia. These precursors foreshadow enhanced Philippine Sea subtropical High and Okhotsk High in early summer, which are controlling factors for enhanced subtropical frontal rainfall. The physical empirical model built on these predictors achieves a cross-validated forecast correlation skill of 0.75 for 1979-2012. Surprisingly, this skill is substantially higher than four-dynamical models' ensemble prediction for 1979-2010 period (0.15). The results here suggest that the low prediction skill of current dynamical models is largely due to models' deficiency and the dynamical prediction has large room to improve.

Total Sediment Thickness of the World's Oceans & Marginal Seas, Version 2

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NGDC's global ocean sediment thickness grid (Divins, 2003) has been updated for the Australian-Antarctic region (60?? -155?? E, 30?? -70?? S). New seismic reflection...

Slope 10 m grid derived from gridded bathymetry of Farallon de Pajaros (Uracas) Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI. Cell values reflect the maximum rate of...

Medium Range Forecast (MRF) and Nested Grid Model (NGM)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Nested Grid Model (NGM) and Medium Range Forecast (MRF) Archive is historical digital data set DSI-6140, archived at the NOAA National Centers for Environmental...

Enhanced Orographic Tropical Rainfall: An Study of the Colombia's rainfall

Science.gov (United States)

Peñaranda, V. M.; Hoyos Ortiz, C. D.; Mesa, O. J.

2015-12-01

Convection in tropical regions may be enhanced by orographic barriers. The orographic enhancement is an intensification of rain rates caused by the forced lifting of air over a mountainous structure. Orographic heavy rainfall events, occasionally, comes along by flooding, debris flow and substantial amount of looses, either economics or human lives. Most of the heavy convective rainfall events, occurred in Colombia, have left a lot of victims and material damages by flash flooding. An urgent action is required by either scientific communities or society, helping to find preventive solutions against these kind of events. Various scientific literature reports address the feedback process between the convection and the local orographic structures. The orographic enhancement could arise by several physical mechanism: precipitation transport on leeward side, convection triggered by the forcing of air over topography, the seeder-feeder mechanism, among others. The identification of the physical mechanisms for orographic enhancement of rainfall has not been studied over Colombia. As far as we know, orographic convective tropical rainfall is just the main factor for the altitudinal belt of maximum precipitation, but the lack of detailed hydro-meteorological measurements have precluded a complete understanding of the tropical rainfall in Colombia and its complex terrain. The emergence of the multifractal theory for rainfall has opened a field of research which builds a framework for parsimonious modeling of physical process. Studies about the scaling behavior of orographic rainfall have found some modulating functions between the rainfall intensity probability distribution and the terrain elevation. The overall objective is to advance in the understanding of the orographic influence over the Colombian tropical rainfall based on observations and scaling-analysis techniques. We use rainfall maps, weather radars scans and ground-based rainfall data. The research strategy is

Empirical studies of the microwave radiometric response to rainfall in the tropics and midlatitudes

Science.gov (United States)

Petty, Grant W.; Katsaros, Kristina B.

1989-01-01

Results are presented from quantitative comparisons between satellite microwave radiometer observations and digital radar observations of equatorial convective cloud clusters and midlatitude frontal precipitation. Simultaneous data from the Winter Monsoon Experiment digital radar and the SMMR for December 1978 are analyzed. It is found that the most important differences between the microwave response to rainfall in the equatorial tropics and to stratiform rain in oceanic midlatitude fronts is caused by the different spatial characteristics of stratiform and convective rainfall and by the different background brightness temperature fields associated with tropical and midlatitude levels of atmospheric water vapor.

Mesoscale and Local Scale Evaluations of Quantitative Precipitation Estimates by Weather Radar Products during a Heavy Rainfall Event

Directory of Open Access Journals (Sweden)

Basile Pauthier

2016-01-01

Full Text Available A 24-hour heavy rainfall event occurred in northeastern France from November 3 to 4, 2014. The accuracy of the quantitative precipitation estimation (QPE by PANTHERE and ANTILOPE radar-based gridded products during this particular event, is examined at both mesoscale and local scale, in comparison with two reference rain-gauge networks. Mesoscale accuracy was assessed for the total rainfall accumulated during the 24-hour event, using the Météo France operational rain-gauge network. Local scale accuracy was assessed for both total event rainfall and hourly rainfall accumulations, using the recently developed HydraVitis high-resolution rain gauge network Evaluation shows that (1 PANTHERE radar-based QPE underestimates rainfall fields at mesoscale and local scale; (2 both PANTHERE and ANTILOPE successfully reproduced the spatial variability of rainfall at local scale; (3 PANTHERE underestimates can be significantly improved at local scale by merging these data with rain gauge data interpolation (i.e., ANTILOPE. This study provides a preliminary evaluation of radar-based QPE at local scale, suggesting that merged products are invaluable for applications at very high resolution. The results obtained underline the importance of using high-density rain-gauge networks to obtain information at high spatial and temporal resolution, for better understanding of local rainfall variation, to calibrate remotely sensed rainfall products.

Satellite rainfall monitoring over Africa for food security, using multi-channel MSG data

Science.gov (United States)

Chadwick, R.; Grimes, D.; Saunders, R.; Blackmore, T.; Francis, P.

2009-04-01

Near real-time rainfall estimates are crucial in sub-Saharan Africa for a variety of humanitarian and agricultural purposes. However, for economic and infrastructural reasons, regularly reporting rain-gauges are sparse and precipitation radar networks extremely rare. Satellite rainfall estimates, particularly from geostationary satellites such as Meteosat Second Generation (MSG), present one method of filling this information gap, as they produce data at high temporal and spatial resolution. An algorithm has been developed to produce rainfall estimates for Africa from multi-channel MSG data. The algorithm is calibrated using precipitation radar data collected in Niamey, Niger as part of the African Monsoon Multidisciplinary Analyses (AMMA) project in 2006, and is based on an algorithm used operationally over Europe by the UK Met Office. Contingency tables are used to establish a statistical relationship between multi-channel MSG data and probability of rainfall at several different rain-rate magnitudes as sensed by the radar. Rain-rate estimates can then be produced at a variety of spatial and temporal scales, with MSG scan length (15 minutes) and pixel size (3-4km) as the lower limit. Results will be presented of a validation of this algorithm over the Sahel region of Africa. Rainfall estimates from this algorithm, processed for 2004, will be validated against gridded rain-gauge data at a 0.5 degree and 10 day timescale suitable for drought monitoring purposes. A comparison will also be made against rainfall estimates from the TAMSAT algorithm, which uses single channel IR data from MSG, and has been shown to perform well in the Sahel region.

Bathymetric Bathymetric Position Index (BPI) Zones 20 m grid derived from gridded bathymetry of Baker Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from gridded (20 m cell size) multibeam bathymetry, collected aboard R/V AHI and NOAA ship Hi'ialakai. BPI Zones was created using the Benthic...

Bathymetric Bathymetric Position Index (BPI) Zones 20 m grid derived from gridded bathymetry of Johnston Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from gridded (20 m cell size) multibeam bathymetry, collected aboard R/V AHI and NOAA ship Hi'ialakai. BPI Zones was created using the Benthic...

Bathymetric Bathymetric Position Index (BPI) Zones 40 m grid derived from gridded bathymetry of Howland Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from gridded (40 m cell size) multibeam bathymetry, collected aboard R/V AHI and NOAA ship Hi'ialakai. BPI Zones was created using the Benthic...

Month-to-month variability of Indian summer monsoon rainfall in 2016: role of the Indo-Pacific climatic conditions

Science.gov (United States)

Chowdary, Jasti S.; Srinivas, G.; Du, Yan; Gopinath, K.; Gnanaseelan, C.; Parekh, Anant; Singh, Prem

2018-03-01

Indian summer monsoon (ISM) rainfall during 2016 exhibited a prominent month-to-month fluctuations over India, with below normal rainfall in June and August and above normal rainfall in July. The factors determining the month-to-month fluctuations in ISM rainfall during 2016 are investigated with main focus on the Indo-Pacific climatic anomalies. Warm sea surface temperature (SST) anomalies associated with super El Niño 2015 disappeared by early summer 2016 over the central and eastern Pacific. On the other hand, negative Indian Ocean dipole (IOD) like SST anomaly pattern over the equatorial Indian Ocean and anomalous anticyclonic circulation over the western North Pacific (WNP) are reported in summer 2016 concurrently with decaying El Niño/developing La Niña phase. Observations revealed that the low rainfall over central north India in June is due to moisture divergence caused by the westward extension of ridge corresponding to WNP anticyclone and subsidence induced by local Hadley cell partly related to negative IOD. Low level convergence of southeasterly wind from Bay of Bengal associated with weak WNP anticyclone and northwesterly wind corresponding to anticyclonic circulation over the northwest India remarkably contributed to positive rainfall in July over most of the Indian subcontinent. While reduced rainfall over the Indian subcontinent in August 2016 is associated with the anomalous moisture transport from ISM region to WNP region, in contrast to July, due to local cyclogenesis corroborated by number of tropical cyclones in the WNP. In addition to this, subsidence related to strong convection supported by cyclonic circulation over the WNP also resulted in low rainfall over the ISM region. Coupled General Circulation model sensitivity experiments confirmed that strong convective activities associated with cyclonic circulation over the WNP is primarily responsible for the observed negative ISM rainfall anomalies in August 2016. It is noted that the Indo

Charlotte Amalie, Virgin Islands Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Charlotte Amalie, Virgin Islands Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami...

Stochastically-forced Decadal Variability in Australian Rainfall

Science.gov (United States)

Taschetto, A.

2015-12-01

Iconic Australian dry and wet periods were driven by anomalous conditions in the tropical oceans, such as the worst short-term drought in the southeast in 1982 associated with the strong El Niño and the widespread "Big Wet" in 1974 linked with a La Niña event. The association with oceanic conditions makes droughts predictable to some extent. However, prediction can be difficult when there is no clear external forcing such as El Niños. Can dry spells be triggered and maintained with no ocean memory? In this study, we investigate the potential role of internal multi-century atmospheric variability in controlling the frequency, duration and intensity of long-term dry and wet spells over Australia. Two multi-century-scale simulations were performed with the NCAR CESM: (1) a fully-coupled simulation (CPLD) and (2) an atmospheric simulation forced by a seasonal SST climatology derived from the coupled experiment (ACGM). Results reveal that droughts and wet spells can indeed be generated by internal variability of the atmosphere. Those internally generated events are less severe than those forced by oceanic variability, however the duration of dry and wet spells longer than 3 years is comparable with and without the ocean memory. Large-scale ocean modes of variability seem to play an important role in producing continental-scale rainfall impacts over Australia. While the Pacific Decadal Oscillation plays an important role in generating droughts in the fully coupled model, perturbations of monsoonal winds seem to be the main trigger of dry spells in the AGCM case. Droughts in the mid-latitude regions such as Tasmania can be driven by perturbations in the Southern Annular Mode, not necessarily linked to oceanic conditions even in the fully-coupled model. The mechanisms behind internally-driven mega-droughts and mega-wets will be discussed.

Combined TRMM Microwave Imager (TMI) and Precipitation Radar (PR) Gridded Orbital Data Set (G2B31) V6

Data.gov (United States)

National Aeronautics and Space Administration — Combined TRMM Microwave Imager (TMI) and Precipitation Radar (PR) gridded orbital rainfall data, is a special product derived from the TRMM standard product (2B-31)...

Warning Model for Shallow Landslides Induced by Extreme Rainfall

Directory of Open Access Journals (Sweden)

Lien-Kwei Chien

2015-08-01

Full Text Available In this study, the geophysical properties of the landslide-prone catchment of the Gaoping River in Taiwan were investigated using zones based on landslide history in conjunction with landslide analysis using a deterministic approach based on the TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-Stability model. Typhoon Morakot in 2009 was selected as a simulation scenario to calibrate the combination of geophysical parameters in each zone before analyzing changes in the factor of safety (FS. Considering the amount of response time required for typhoons, suitable FS thresholds for landslide warnings are proposed for each town in the catchment area. Typhoon Fanapi of 2010 was used as a test scenario to verify the applicability of the FS as well as the efficacy of the cumulative rainfall thresholds derived in this study. Finally, the amount of response time provided by the FS thresholds in cases of yellow and red alerts was determined. All five of the landslide events reported by the Soil and Water Conservation Bureau were listed among the unstable sites identified in the proposed model, thereby demonstrating its effectiveness and accuracy in determining unstable areas and areas that require evacuation. These cumulative rainfall thresholds provide a valuable reference to guide disaster prevention authorities in the issuance of yellow and red alerts with the ability to reduce losses and save lives.

5 m Gridded multibeam bathymetry of Rota Island, Commonwealth of the Northern Mariana Islands (CNMI)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rota Island, CNMI. Bottom coverage was achieved in depths between 0 and -1905 meters; this 5-m grid has data only to -400 m. The netCDF and Arc ASCII grids include...

Basin and Range Province, Western US, USGS Grids #2

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These grid files were used to produce gravity and basin depth maps of the Basin and Range Province, western United States. The maps show gravity values and modeled...

Basin and Range Province, Western US, USGS Grids, #1

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These grid files were used to produce gravity and basin depth maps of the Basin and Range Province, western United States. The maps show gravity values and modeled...

Basin and Range Province, Western US, USGS Grids #3

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These grid files were used to produce gravity and basin depth maps of the Basin and Range Province, western United States. The maps show gravity values and modeled...

Basin and Range Province, Western US, USGS Grids #5

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These grid files were used to produce gravity and basin depth maps of the Basin and Range Province, western United States. The maps show gravity values and modeled...

Basin and Range Province, Western US, USGS Grids #4

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These grid files were used to produce gravity and basin depth maps of the Basin and Range Province, western United States. The maps show gravity values and modeled...

Prediction of summer monsoon rainfall over India using the NCEP climate forecast system

Energy Technology Data Exchange (ETDEWEB)

Pattanaik, D.R. [India Meteorological Department (IMD), New Delhi (India); Kumar, Arun [Climate Prediction Center, National Centre for Environmental Prediction (NCEP)/NWS/NOAA, Camp Springs, MD (United States)

2010-03-15

The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction's (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS's hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50 E-110 E and 10 S-35 N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon

Myrtle Beach, South Carolina Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Myrtle Beach, South Carolina Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Pago Pago, American Samoa Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Pago Pago, American Samoa Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Morehead City, North Carolina Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Morehead City, North Carolina Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Atlantic City, New Jersey Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Atlantic City, New Jersey Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Cape Hatteras, North Carolina Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Cape Hatteras, North Carolina Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Port San Luis, California Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Port San Luis, California Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

Heterogeneity of Dutch rainfall

NARCIS (Netherlands)

Witter, J.V.

1984-01-01

Rainfall data for the Netherlands have been used in this study to investigate aspects of heterogeneity of rainfall, in particular local differences in rainfall levels, time trends in rainfall, and local differences in rainfall trend. The possible effect of urbanization and industrialization on the

Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes

Science.gov (United States)

Ghosh, Subimal; Vittal, H.; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K. S.; Dhanesh, Y.; Sudheer, K. P.; Gunthe, S. S.

2016-01-01

India’s agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins. PMID:27463092

Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes.

Directory of Open Access Journals (Sweden)

Subimal Ghosh

Full Text Available India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins.

San Juan, Puerto Rico Tsunami Forecast Grids for MOST Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The San Juan, Puerto Rico Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

CRED Gridded Bathymetry near Northampton Seamounts to West Laysan Island (100-005) Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-005b is a 60-m ASCII grid of depth data collected near Kure Atoll in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced as part...

CRED Gridded Bathymetry of West St. Rogatien Bank (100-017) in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-017b is a 60-m ASCII grid of depth data collected near Kure Atoll in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced as part...

On the dust load and rainfall relationship in South Asia: an analysis from CMIP5

Science.gov (United States)

Singh, Charu; Ganguly, Dilip; Dash, S. K.

2018-01-01

This study is aimed at examining the consistency of the relationship between load of dust and rainfall simulated by different climate models and its implication for the Indian summer monsoon system. Monthly mean outputs of 12 climate models, obtained from the archive of the Coupled Model Intercomparison Project phase 5 (CMIP5) for the period 1951-2004, are analyzed to investigate the relationship between dust and rainfall. Comparative analysis of the model simulated precipitation with the India Meteorological Department (IMD) gridded rainfall, CRU TS3.21 and GPCP version 2.2 data sets show significant differences between the spatial patterns of JJAS rainfall as well as annual cycle of rainfall simulated by various models and observations. Similarly, significant inter-model differences are also noted in the simulation of load of dust, nevertheless it is further noted that most of the CMIP5 models are able to capture the major dust sources across the study region. Although the scatter plot analysis and the lead-lag pattern correlation between the dust load and the rainfall show strong relationship between the dust load over distant sources and the rainfall in the South Asian region in individual models, the temporal scale of this association indicates large differences amongst the models. Our results caution that it would be pre-mature to draw any robust conclusions on the time scale of the relationship between dust and the rainfall in the South Asian region based on either CMIP5 results or limited number of previous studies. Hence, we would like to emphasize upon the fact that any conclusions drawn on the relationship between the dust load and the South Asian rainfall using model simulation is highly dependent on the degree of complexity incorporated in those models such as the representation of aerosol life cycle, their interaction with clouds, precipitation and other components of the climate system.

Combined TRMM Microwave Imager (TMI) and Precipitation Radar (PR) Gridded Orbital Data Set (G2A12) V6

Data.gov (United States)

National Aeronautics and Space Administration — The TRMM Microwave Imager (TMI) Gridded Orbital rainfall data, a special product derived from the TRMM standard product, TMI rain profile (2A-12), and mapped to a...

Comparison of publically available Moho depth and crustal thickness grids with newly derived grids by 3D gravity inversion for the High Arctic region.

Science.gov (United States)

Lebedeva-Ivanova, Nina; Gaina, Carmen; Minakov, Alexander; Kashubin, Sergey

2016-04-01

We derived Moho depth and crustal thickness for the High Arctic region by 3D forward and inverse gravity modelling method in the spectral domain (Minakov et al. 2012) using lithosphere thermal gravity anomaly correction (Alvey et al., 2008); a vertical density variation for the sedimentary layer and lateral crustal variation density. Recently updated grids of bathymetry (Jakobsson et al., 2012), gravity anomaly (Gaina et al, 2011) and dynamic topography (Spasojevic & Gurnis, 2012) were used as input data for the algorithm. TeMAr sedimentary thickness grid (Petrov et al., 2013) was modified according to the most recently published seismic data, and was re-gridded and utilized as input data. Other input parameters for the algorithm were calibrated using seismic crustal scale profiles. The results are numerically compared with publically available grids of the Moho depth and crustal thickness for the High Arctic region (CRUST 1 and GEMMA global grids; the deep Arctic Ocean grids by Glebovsky et al., 2013) and seismic crustal scale profiles. The global grids provide coarser resolution of 0.5-1.0 geographic degrees and not focused on the High Arctic region. Our grids better capture all main features of the region and show smaller error in relation to the seismic crustal profiles compare to CRUST 1 and GEMMA grids. Results of 3D gravity modelling by Glebovsky et al. (2013) with separated geostructures approach show also good fit with seismic profiles; however these grids cover the deep part of the Arctic Ocean only. Alvey A, Gaina C, Kusznir NJ, Torsvik TH (2008). Integrated crustal thickness mapping and plate recon-structions for the high Arctic. Earth Planet Sci Lett 274:310-321. Gaina C, Werner SC, Saltus R, Maus S (2011). Circum-Arctic mapping project: new magnetic and gravity anomaly maps of the Arctic. Geol Soc Lond Mem 35, 39-48. Glebovsky V.Yu., Astafurova E.G., Chernykh A.A., Korneva M.A., Kaminsky V.D., Poselov V.A. (2013). Thickness of the Earth's crust in the

Rainfall Erosivity in Europe

DEFF Research Database (Denmark)

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale

2015-01-01

Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the Rfactor in the USLE model and its revised version, RUSLE. At national...... and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based...

Surface Ocean CO₂ Atlas (SOCAT) gridded data products

Digital Repository Service at National Institute of Oceanography (India)

Sabine, C.L.; Hankin, S.; Koyuk, H.; Bakker, D.C.E.; Pfeil, B.; Olsen, A; Metzl, N.; Kozyr, A; Fassbender, A; Manke, A; Malczyk, J.; Akl, J.; Alin, S.R.; Bellerby, R.G.J.; Borges, A; Boutin, J.; Brown, P.J.; Cai, W.-J.; Chavez, F.P.; Chen, A.; Cosca, C.; Feely, R.A.; Gonzalez-Davila, M.; Goyet, C.; Hardman-Mountford, N.; Heinze, C.; Hoppema, M.; Hunt, C.W.; Hydes, D.; Ishii, M.; Johannessen, T.; Key, R.M.; Kortzinger, A.; Landschutzer, P.; Lauvset, S.K.; Lefevre, N.; Lenton, A.; Lourantou, A.; Merlivat, L.; Midorikawa, T.; Mintrop, L.; Miyazaki, C.; Murata, A.; Nakadate, A.; Nakano, Y.; Nakaoka, S.; Nojiri, Y.; Omar, A.M.; Padin, X.A.; Park, G.-H.; Paterson, K.; Perez, F.F.; Pierrot, D.; Poisson, A.; Rios, A.F.; Salisbury, J.; Santana-Casiano, J.M.; Sarma, V.V.S.S.; et al.

As a response to public demand for a well-documented, quality controlled, publically available, global surface ocean carbon dioxide (CO₂) data set, the international marine carbon science community developed the Surface Ocean CO_2...

Enhancement of vegetation-rainfall feedbacks on the Australian summer monsoon by the Madden-Julian Oscillation

Science.gov (United States)

Notaro, Michael

2018-01-01

A regional climate modeling analysis of the Australian monsoon system reveals a substantial modulation of vegetation-rainfall feedbacks by the Madden Julian Oscillation (MJO), both of which operate at similar sub-seasonal time scales, as evidence that the intensity of land-atmosphere interactions is sensitive to the background atmospheric state. Based on ensemble experiments with imposed modification of northern Australian leaf area index (LAI), the atmospheric responses to LAI anomalies are composited for negative and positive modes of the propagating MJO. In the regional climate model (RCM), northern Australian vegetation feedbacks are characterized by evapotranspiration (ET)-driven rainfall responses, with the moisture feedback mechanism dominating over albedo and roughness feedback mechanisms. During November-April, both Tropical Rainfall Measuring Mission and RCM data reveal MJO's pronounced influence on rainfall patterns across northern Australia, tropical Indian Ocean, Timor Sea, Arafura Sea, and Gulf of Carpentaria, with the MJO dominating over vegetation feedbacks in terms of regulating monsoon rainfall variability. Convectively-active MJO phases support an enhancement of positive vegetation feedbacks on monsoon rainfall. While the MJO imposes minimal regulation of ET responses to LAI anomalies, the vegetation feedback-induced responses in precipitable water, cloud water, and rainfall are greatly enhanced during convectively-active MJO phases over northern Australia, which are characterized by intense low-level convergence and efficient precipitable water conversion. The sub-seasonal response of vegetation-rainfall feedback intensity to the MJO is complex, with significant enhancement of rainfall responses to LAI anomalies in February during convectively-active MJO phases compared to minimal modulation by the MJO during prior and subsequent calendar months.

International Comprehensive Ocean-Atmosphere Data Set (ICOADS)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Surface marine observational records from ships, buoys, and other platform types are processed and binned creating monthly global and regional grids of the...

Acquisition Of Rainfall Dataset And The Application For The Automatic Harvester In The Chesapeake Bay Region

Science.gov (United States)

Choi, Y.; Piasecki, M.

2008-12-01

The objective of this study is the preparation and indexing of rainfall data products for ingestion into the Chesapeake Bay Environmental Observatory (CBEO) node of the CUAHSI/WATERs network. Rainfall products (which are obtained and then processed based on the WSR-88D NEXRAD network) are obtained from the NOAA/NWS Advanced Hydrologic Prediction Service that combines the Multi-sensor Precipitation Estimate (MPE) data generated by the Regional River Forecast Centers and Hydro-NEXRAD rainfall data generated as a service by the University of Iowa. The former is collected on 4*4 km grid (HRAP) with a daily average temporal resolution and the latter on a 1minute*1minute degree grid with hourly values. We have generated a cut-out for the Chesapeake Bay Basin that contains about 9,300 nodes (sites) for the MPE data and about 300,000 nodes (sites) for the Hydro-NEXRAD product. Automated harvesting services have been implemented for both data products. The MPE data is harvested from its download site using ArcGIS which in turn is used to extract the data for the Chesapeake Bay watershed before a scripting program is used to scatter the data into the ODM. The Hydro-NEXRAD is downloaded from a web-based system at the University of Iowa which permits downloads for large scale watersheds organized by Hydraulic Unit Codes (HUC). The resulting ASCII is then automatically parsed and the information stored alongside the MPE data. The two data products stored side-by-side then allows a comparison between them addressing the accuracy and agreement between the methods used to arrive at rainfall data as both use the raw reflectivity data from the WSD-88D system.

Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin

Science.gov (United States)

Shrestha, M.S.; Artan, Guleid A.; Bajracharya, S.R.; Sharma, R. R.

2008-01-01

In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.

EMAG2: Earth Magnetic Anomaly Grid (2-arc-minute resolution)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — EMAG2 is a global Earth Magnetic Anomaly Grid compiled from satellite, ship, and airborne magnetic measurements. It is a significant update of our previous candidate...

Daily disaggregation of simulated monthly flows using different rainfall datasets in southern Africa

Directory of Open Access Journals (Sweden)

D.A. Hughes

2015-09-01

New hydrological insights for the region: There are substantial regional differences in the success of the monthly hydrological model, which inevitably affects the success of the daily disaggregation results. There are also regional differences in the success of using global rainfall data sets (Climatic Research Unit (CRU datasets for monthly, National Oceanic and Atmospheric Administration African Rainfall Climatology, version 2 (ARC2 satellite data for daily. The overall conclusion is that the disaggregation method presents a parsimonious approach to generating daily flow simulations from existing monthly simulations and that these daily flows are likely to be useful for some purposes (e.g. water quality modelling, but less so for others (e.g. peak flow analysis.

Enhanced marine sulphur emissions offset global warming and impact rainfall.

Science.gov (United States)

Grandey, B S; Wang, C

2015-08-21

Artificial fertilisation of the ocean has been proposed as a possible geoengineering method for removing carbon dioxide from the atmosphere. The associated increase in marine primary productivity may lead to an increase in emissions of dimethyl sulphide (DMS), the primary source of sulphate aerosol over remote ocean regions, potentially causing direct and cloud-related indirect aerosol effects on climate. This pathway from ocean fertilisation to aerosol induced cooling of the climate may provide a basis for solar radiation management (SRM) geoengineering. In this study, we investigate the transient climate impacts of two emissions scenarios: an RCP4.5 (Representative Concentration Pathway 4.5) control; and an idealised scenario, based on RCP4.5, in which DMS emissions are substantially enhanced over ocean areas. We use mini-ensembles of a coupled atmosphere-ocean configuration of CESM1(CAM5) (Community Earth System Model version 1, with the Community Atmosphere Model version 5). We find that the cooling effect associated with enhanced DMS emissions beneficially offsets greenhouse gas induced warming across most of the world. However, the rainfall response may adversely affect water resources, potentially impacting human livelihoods. These results demonstrate that changes in marine phytoplankton activity may lead to a mixture of positive and negative impacts on the climate.

Spatiotemporal Interpolation of Rainfall by Combining BME Theory and Satellite Rainfall Estimates

Directory of Open Access Journals (Sweden)

Tingting Shi

2015-09-01

Full Text Available The accurate assessment of spatiotemporal rainfall variability is a crucial and challenging task in many hydrological applications, mainly due to the lack of a sufficient number of rain gauges. The purpose of the present study is to investigate the spatiotemporal variations of annual and monthly rainfall over Fujian province in China by combining the Bayesian maximum entropy (BME method and satellite rainfall estimates. Specifically, based on annual and monthly rainfall data at 20 meteorological stations from 2000 to 2012, (1 the BME method with Tropical Rainfall Measuring Mission (TRMM estimates considered as soft data, (2 ordinary kriging (OK and (3 cokriging (CK were employed to model the spatiotemporal variations of rainfall in Fujian province. Subsequently, the performance of these methods was evaluated using cross-validation statistics. The results demonstrated that BME with TRMM as soft data (BME-TRMM performed better than the other two methods, generating rainfall maps that represented the local rainfall disparities in a more realistic manner. Of the three interpolation (mapping methods, the mean absolute error (MAE and root mean square error (RMSE values of the BME-TRMM method were the smallest. In conclusion, the BME-TRMM method improved spatiotemporal rainfall modeling and mapping by integrating hard data and soft information. Lastly, the study identified new opportunities concerning the application of TRMM rainfall estimates.

The Indian summer monsoon rainfall: interplay of coupled dynamics, radiation and cloud microphysics

Directory of Open Access Journals (Sweden)

P. K. Patra

2005-01-01

Full Text Available The Indian summer monsoon rainfall (ISMR, which has a strong connection to agricultural food production, has been less predictable by conventional models in recent times. Two distinct years 2002 and 2003 with lower and higher July rainfall, respectively, are selected to help understand the natural and anthropogenic influences on ISMR. We show that heating gradients along the meridional monsoon circulation are reduced due to aerosol radiative forcing and the Indian Ocean Dipole in 2002. An increase in the dust and biomass-burning component of the aerosols through the zonal monsoon circulation resulted in reduction of cloud droplet growth in July 2002. These conditions were opposite to those in July 2003 which led to an above average ISMR. In this study, we have utilized NCEP/NCAR reanalyses for meteorological data (e.g. sea-surface temperature, horizontal winds, and precipitable water, NOAA interpolated outgoing long-wave radiation, IITM constructed all-India rainfall amounts, aerosol parameters as observed from the TOMS and MODIS satellites, and ATSR fire count maps. Based on this analysis, we suggest that monsoon rainfall prediction models should include synoptic as well as interannual variability in both atmospheric dynamics and chemical composition.

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tutuila Island, American Samoa, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Rose Atoll, American Samoa, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry were...

GIS-based two-dimensional numerical simulation of rainfall-induced debris flow

Directory of Open Access Journals (Sweden)

C. Wang

2008-02-01

Full Text Available This paper aims to present a useful numerical method to simulate the propagation and deposition of debris flow across the three dimensional complex terrain. A depth-averaged two-dimensional numerical model is developed, in which the debris and water mixture is assumed to be continuous, incompressible, unsteady flow. The model is based on the continuity equations and Navier-Stokes equations. Raster grid networks of digital elevation model in GIS provide a uniform grid system to describe complex topography. As the raster grid can be used as the finite difference mesh, the continuity and momentum equations are solved numerically using the finite difference method. The numerical model is applied to simulate the rainfall-induced debris flow occurred in 20 July 2003, in Minamata City of southern Kyushu, Japan. The simulation reproduces the propagation and deposition and the results are in good agreement with the field investigation. The synthesis of numerical method and GIS makes possible the solution of debris flow over a realistic terrain, and can be used to estimate the flow range, and to define potentially hazardous areas for homes and road section.

Bathymetric Position Index (BPI) Structures 5m grid derived from gridded bathymetry of Tinian Island, Aguijan Island and Tatsumi Bank, Commonwealth of the Northern Marianas

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from a focal mean analysis on bathymetry and slope. The bathymetry grid (5 m cell size) is derived from bathymetry from three sources:...

Bathymetric Position Index (BPI) Zones 5m grid derived from gridded bathymetry of Tinian Island, Aguijan Island and Tatsumi Bank, Commonwealth of the Northern Marianas

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The bathymetry grid (5 m cell size) is derived from bathymetry from three sources:...

CRED Gridded Bathymetry along a transit to Nihoa Island (100-027) in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-027b is a 60-m ASCII grid of depth data collected near Transit to Nihoa in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced as...

Influence of the balance of the intertropical front on seasonal variations of the isotopic composition in rainfall at Kisiba Masoko (Rungwe Volcanic Province, SW, Tanzania).

Science.gov (United States)

Nivet, Fantine; Bergonzini, Laurent; Mathé, Pierre-Etienne; Noret, Aurélie; Monvoisin, Gaël; Majule, Amos; Williamson, David

2018-08-01

Tropical rainfall isotopic composition results from complex processes. The climatological and environmental variability in East Africa increases this complexity. Long rainfall isotope datasets are needed to fill the lack of observations in this region. At Kisiba Masoko, Tanzania, rainfall and rain isotopic composition have been monitored during 6 years. Mean year profiles allow to analyse the seasonal variations. The mean annual rainfall is 2099 mm with a rain-weighted mean composition of -3.2 ‰ for δ 18 O and -11.7 ‰ for δ 2 H. The results are consistent with available data although they present their own specificity. Thus, if the local meteoric water line is δ 2 H = 8.6 δ 18 O + 14.8, two seasonal lines are observed. The seasonality of the isotopic composition in rain and deuterium excess has been compared with precipitating air masses backtracking trajectories to characterize a simple scheme of vapour histories. The three major oceanic sources have two moisture signatures with their own trajectory histories: one originated from the tropical Indian Ocean at the beginning of the rainy season and one from the Austral Ocean at its end. The presented isotopic seasonality depends on the balance of the intertropical front and provides a useful dataset to improve the knowledge about local processes.

Shallow and Deep Latent Heating Modes Over Tropical Oceans Observed with TRMM PR Spectral Latent Heating Data

Science.gov (United States)

Takayabu, Yukari N.; Shige, Shoichi; Tao, Wei-Kuo; Hirota, Nagio

2010-01-01

The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of its formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the Tropics. Associated with this rainfall is a vast amount of heat, which is known as latent heat. It arises mainly due to the phase change of water vapor condensing into liquid droplets; three-fourths of the total heat energy available to the Earth's atmosphere comes from tropical rainfall. In addition, fresh water provided by tropical rainfall and its variability exerts a large impact upon the structure and motions of the upper ocean layer. Three-dimensional distributions of latent heating estimated from Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR)utilizing the Spectral Latent Heating (SLH) algorithm are analyzed. Mass-weighted and vertically integrated latent heating averaged over the tropical oceans is estimated as approx.72.6 J/s (approx.2.51 mm/day), and that over tropical land is approx.73.7 J/s (approx.2.55 mm/day), for 30degN-30degS. It is shown that non-drizzle precipitation over tropical and subtropical oceans consists of two dominant modes of rainfall systems, deep systems and congestus. A rough estimate of shallow mode contribution against the total heating is about 46.7 % for the average tropical oceans, which is substantially larger than 23.7 % over tropical land. While cumulus congestus heating linearly correlates with the SST, deep mode is dynamically bounded by large-scale subsidence. It is notable that substantial amount of rain, as large as 2.38 mm day-1 in average, is brought from congestus clouds under the large-scale subsiding circulation. It is also notable that even in the region with SST warmer than 28 oC, large-scale subsidence effectively suppresses the deep convection, remaining the heating by congestus clouds. Our results support that the entrainment of mid-to-lower-tropospheric dry air, which accompanies the large

Rainfall and Extratropical Transition of Tropical Cyclones: Simulation, Prediction, and Projection

Science.gov (United States)

Liu, Maofeng

Rainfall and associated flood hazards are one of the major threats of tropical cyclones (TCs) to coastal and inland regions. The interaction of TCs with extratropical systems can lead to enhanced precipitation over enlarged areas through extratropical transition (ET). To achieve a comprehensive understanding of rainfall and ET associated with TCs, this thesis conducts weather-scale analyses by focusing on individual storms and climate-scale analyses by focusing on seasonal predictability and changing properties of climatology under global warming. The temporal and spatial rainfall evolution of individual storms, including Hurricane Irene (2011), Hurricane Hanna (2008), and Hurricane Sandy (2012), is explored using the Weather Research and Forecast (WRF) model and a variety of hydrometeorological datasets. ET and Orographic mechanism are two key players in the rainfall distribution of Irene over regions experiencing most severe flooding. The change of TC rainfall under global warming is explored with the Forecast-oriented Low Ocean Resolution (FLOR) climate model under representative concentration pathway (RCP) 4.5 scenario. Despite decreased TC frequency, FLOR projects increased landfalling TC rainfall over most regions of eastern United States, highlighting the risk of increased flood hazards. Increased storm rain rate is an important player of increased landfalling TC rainfall. A higher atmospheric resolution version of FLOR (HiFLOR) model projects increased TC rainfall at global scales. The increase of TC intensity and environmental water vapor content scaled by the Clausius-Clapeyron relation are two key factors that explain the projected increase of TC rainfall. Analyses on the simulation, prediction, and projection of the ET activity with FLOR are conducted in the North Atlantic. FLOR model exhibits good skills in simulating many aspects of present-day ET climatology. The 21st-century-projection under RCP4.5 scenario demonstrates the dominant role of ET

Gridded bathymetry of 35 fthm Bank, and 37 fthm Bank, north of Farallon de Medinilla, CNMI, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry (5m) of the bank environment of 35-fthm Bank and 37 fthm Bank,CNMI USA. These netCDF and ASCII grids include multibeam bathymetry from the Reson...

A Southern Ocean variability study using the Argo-based Model for Investigation of the Global Ocean (AMIGO)

Science.gov (United States)

Lebedev, Konstantin

2017-04-01

The era of satellite observations of the ocean surface that started at the end of the 20th century and the development of the Argo project in the first years of the 21st century, designed to collect information of the upper 2000 m of the ocean using satellites, provides unique opportunities for continuous monitoring of the Global Ocean state. Starting from 2005, measurements with the Argo floats have been performed over the majority of the World Ocean. In November 2007, the Argo program reached coverage of 3000 simultaneously operating floats (one float in a three-degree square) planned during the development of the program. Currently, 4000 Argo floats autonomously profile the upper 2000-m water column of the ocean from Antarctica to Spitsbergen increasing World Ocean temperature and salinity databases by 12000 profiles per month. This makes it possible to solve problems on reconstructing and monitoring the ocean state on an almost real-time basis, study the ocean dynamics, obtain reasonable estimates of the climatic state of the ocean in the last decade and estimate existing intraclimatic trends. We present the newly developed Argo-Based Model for Investigation of the Global Ocean (AMIGO), which consists of a block for variational interpolation of the profiles of drifting Argo floats to a regular grid and a block for model hydrodynamic adjustment of variationally interpolated fields. Such a method makes it possible to obtain a full set of oceanographic characteristics - temperature, salinity, density, and current velocity - using irregularly located Argo measurements (the principle of the variational interpolation technique entails minimization of the misfit between the interpolated fields defined on the regular grid and irregularly distributed data; hence the optimal solution passes as close to the data as possible). The simulations were performed for the entire globe limited in the north by 85.5° N using 1° grid spacing in both longitude and latitude. At the

Oceanic influence on extreme rainfall trends in the north central coast of Venezuela: present and future climate assessments

Directory of Open Access Journals (Sweden)

Lelys Guenni

2013-10-01

Full Text Available Extreme events are an important part of climate variability and their intensity and persistence are often modulated by large scale climatic patterns which might act as forcing drivers affecting their probability of occurrence. When the North Tropical Atlantic (NTA and the Equatorial Pacific (Ni\\~no 3 region sea surface temperature (SST anomalies are of opposite signs and the first one is positive while the second one is negative, the rainfall response is stronger in the northern coast of Venezuela as well as in the Pacific coast of Central America during the Nov-Feb period. The difference between these two SST anomaly time series (NTA-Ni\\~no3 is used in this analysis and it is called the Atlantic-Pacific Index or API. By fitting a dynamic generalized extreme value (GEV model to station based daily rainfall at different locations and to the Xie and Arkin dataset for the Vargas state, we found the API index to be an adequate index to explain the probabilistic nature of rainfall extremes in the northern Venezuelan coast for the months Nov-Feb. Dependence between the Atlantic-Pacific index and the probabilistic behavior of extreme rainfall was also explored for simulations from two global coupled General Circulation Models for the 20th century climate (20C3M experiment and the 21st century climate (SRES A2 experiment: the Echam5 model and the HadCM3 model. A significant dependence of extreme rainfall on the Atlantic-Pacific index is well described by the GEV dynamic model for the Echam5 20C3M experiment model outputs. When looking at future climates under the SRES A2 experiment, the dependence of extreme rainfall from the API index is still significant for the middle part of the 21st century (2046-2064, while this dependence fades off for the latest part of the century (2081-2099

Relationships between southeastern Australian rainfall and sea surface temperatures examined using a climate model

Science.gov (United States)

Watterson, I. G.

2010-05-01

Rainfall in southeastern Australia has declined in recent years, particularly during austral autumn over the state of Victoria. A recent study suggests that sea surface temperature (SST) variations in both the Indonesian Throughflow (ITF) region and in a meridional dipole in the central Indian Ocean have influenced Victorian late autumn rainfall since 1950. However, it remains unclear to what extent SSTs in these and other regions force such a teleconnection. Analysis of a 1080 year simulation by the climate model CSIRO Mk3.5 shows that the model Victorian rainfall is correlated rather realistically with SSTs but that part of the above relationships is due to the model ENSO. Furthermore, the remote patterns of pressure, rainfall, and land temperature greatly diminish when the data are lagged by 1 month, suggesting that the true forcing by the persisting SSTs is weak. In a series of simulations of the atmospheric Mk3.5 with idealized SST anomalies, raised SSTs to the east of Indonesia lower the simulated Australian rainfall, while those to the west raise it. A positive ITF anomaly lowers pressure over Australia, but with little effect on Victorian rainfall. The meridional dipole and SSTs to the west and southeast of Australia have little direct effect on southeastern Australia in the model. The results suggest that tropical SSTs predominate as an influence on Victorian rainfall. However, the SST indices appear to explain only a fraction of the observed trend, which in the case of decadal means remains within the range of unforced variability simulated by Mk3.5.

Rainfall simulation in education

Science.gov (United States)

Peters, Piet; Baartman, Jantiene; Gooren, Harm; Keesstra, Saskia

2016-04-01

Rainfall simulation has become an important method for the assessment of soil erosion and soil hydrological processes. For students, rainfall simulation offers an year-round, attractive and active way of experiencing water erosion, while not being dependent on (outdoors) weather conditions. Moreover, using rainfall simulation devices, they can play around with different conditions, including rainfall duration, intensity, soil type, soil cover, soil and water conservation measures, etc. and evaluate their effect on erosion and sediment transport. Rainfall simulators differ in design and scale. At Wageningen University, both BSc and MSc student of the curriculum 'International Land and Water Management' work with different types of rainfall simulation devices in three courses: - A mini rainfall simulator (0.0625m2) is used in the BSc level course 'Introduction to Land Degradation and Remediation'. Groups of students take the mini rainfall simulator with them to a nearby field location and test it for different soil types, varying from clay to more sandy, slope angles and vegetation or litter cover. The groups decide among themselves which factors they want to test and they compare their results and discuss advantage and disadvantage of the mini-rainfall simulator. - A medium sized rainfall simulator (0.238 m2) is used in the MSc level course 'Sustainable Land and Water Management', which is a field practical in Eastern Spain. In this course, a group of students has to develop their own research project and design their field measurement campaign using the transportable rainfall simulator. - Wageningen University has its own large rainfall simulation laboratory, in which a 15 m2 rainfall simulation facility is available for research. In the BSc level course 'Land and Water Engineering' Student groups will build slopes in the rainfall simulator in specially prepared containers. Aim is to experience the behaviour of different soil types or slope angles when (heavy) rain

Rainfall: State of the Science

Science.gov (United States)

Testik, Firat Y.; Gebremichael, Mekonnen

Rainfall: State of the Science offers the most up-to-date knowledge on the fundamental and practical aspects of rainfall. Each chapter, self-contained and written by prominent scientists in their respective fields, provides three forms of information: fundamental principles, detailed overview of current knowledge and description of existing methods, and emerging techniques and future research directions. The book discusses • Rainfall microphysics: raindrop morphodynamics, interactions, size distribution, and evolution • Rainfall measurement and estimation: ground-based direct measurement (disdrometer and rain gauge), weather radar rainfall estimation, polarimetric radar rainfall estimation, and satellite rainfall estimation • Statistical analyses: intensity-duration-frequency curves, frequency analysis of extreme events, spatial analyses, simulation and disaggregation, ensemble approach for radar rainfall uncertainty, and uncertainty analysis of satellite rainfall products The book is tailored to be an indispensable reference for researchers, practitioners, and graduate students who study any aspect of rainfall or utilize rainfall information in various science and engineering disciplines.

Trends in rainfall and rainfall-related extremes in the east coast of peninsular Malaysia

Science.gov (United States)

Mayowa, Olaniya Olusegun; Pour, Sahar Hadi; Shahid, Shamsuddin; Mohsenipour, Morteza; Harun, Sobri Bin; Heryansyah, Arien; Ismail, Tarmizi

2015-12-01

The coastlines have been identified as the most vulnerable regions with respect to hydrological hazards as a result of climate change and variability. The east of peninsular Malaysia is not an exception for this, considering the evidence of heavy rainfall resulting in floods as an annual phenomenon and also water scarcity due to long dry spells in the region. This study examines recent trends in rainfall and rainfall- related extremes such as, maximum daily rainfall, number of rainy days, average rainfall intensity, heavy rainfall days, extreme rainfall days, and precipitation concentration index in the east coast of peninsular Malaysia. Recent 40 years (1971-2010) rainfall records from 54 stations along the east coast of peninsular Malaysia have been analyzed using the non-parametric Mann-Kendall test and the Sen's slope method. The Monte Carlo simulation technique has been used to determine the field significance of the regional trends. The results showed that there was a substantial increase in the annual rainfall as well as the rainfall during the monsoon period. Also, there was an increase in the number of heavy rainfall days during the past four decades.

Warming of the Indian Ocean Threatens Eastern and Southern Africa, but could be Mitigated by Agricultural Development

Science.gov (United States)

Funk, Chris; Dettinger, Michael D.; Brown, Molly E.; Michaelsen, Joel C.; Verdin, James P.; Barlow, Mathew; Howell, Andrew

2008-01-01

Since 1980, the number of undernourished people in eastern and southern Africa has more than doubled. Rural development stalled and rural poverty expanded during the 1990s. Population growth remains very high and declining per capita agricultural capacity retards progress towards Millennium Development goals. Analyses of in situ station data and satellite observations of precipitation identify another problematic trend. Main growing season rainfall receipts have diminished by approximately 15% in food insecure countries clustered along the western rim of the Indian Ocean. Occurring during the main growing seasons in poor countries dependent on rain fed agriculture, these declines are societally dangerous. Will they persist or intensify? Tracing moisture deficits upstream to an anthropogenically warming Indian Ocean leads us to conclude that further rainfall declines are likely. We present analyses suggesting that warming in the central Indian Ocean disrupts onshore moisture transports, reducing continental rainfall. Thus late 20th century anthropogenic Indian Ocean warming has probably already produced societally dangerous climate change by creating drought and social disruption in some of the world's most fragile food economies. We quantify the potential impacts of the observed precipitation and agricultural capacity trends by modeling millions of undernourished people as a function of rainfall, population, cultivated area, seed and fertilizer use. Persistence of current tendencies may result in a 50% increase in undernourished people. On the other hand, modest increases in per capita agricultural productivity could more than offset the observed precipitation declines. Investing in agricultural development can help mitigate climate change while decreasing rural poverty and vulnerability.

CRED Gridded Bathymetry of Twin Banks and Northwest Nihoa Island (100-024) in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-024b is a 60-m ASCII grid of depth data collected near Twin Banks NW Nihoa in the Northwestern Hawaiian Islands as of May 2003. This grid has been produced...

Modeling regional initiation of rainfall-induced shallow landslides in the eastern Umbria Region of central Italy

Science.gov (United States)

Salciarini, D.; Godt, J.W.; Savage, W.Z.; Conversini, P.; Baum, R.L.; Michael, J.A.

2006-01-01

We model the rainfall-induced initiation of shallow landslides over a broad region using a deterministic approach, the Transient Rainfall Infiltration and Grid-based Slope-stability (TRIGRS) model that couples an infinite-slope stability analysis with a one-dimensional analytical solution for transient pore pressure response to rainfall infiltration. This model permits the evaluation of regional shallow landslide susceptibility in a Geographic Information System framework, and we use it to analyze susceptibility to shallow landslides in an area in the eastern Umbria Region of central Italy. As shown on a landslide inventory map produced by the Italian National Research Council, the area has been affected in the past by shallow landslides, many of which have transformed into debris flows. Input data for the TRIGRS model include time-varying rainfall, topographic slope, colluvial thickness, initial water table depth, and material strength and hydraulic properties. Because of a paucity of input data, we focus on parametric analyses to calibrate and test the model and show the effect of variation in material properties and initial water table conditions on the distribution of simulated instability in the study area in response to realistic rainfall. Comparing the results with the shallow landslide inventory map, we find more than 80% agreement between predicted shallow landslide susceptibility and the inventory, despite the paucity of input data.

Prevention through policy: Urban macroplastic leakages to the marine environment during extreme rainfall events.

Science.gov (United States)

Axelsson, Charles; van Sebille, Erik

2017-11-15

The leakage of large plastic litter (macroplastics) into the ocean is a major environmental problem. A significant fraction of this leakage originates from coastal cities, particularly during extreme rainfall events. As coastal cities continue to grow, finding ways to reduce this macroplastic leakage is extremely pertinent. Here, we explore why and how coastal cities can reduce macroplastic leakages during extreme rainfall events. Using nine global cities as a basis, we establish that while cities actively create policies that reduce plastic leakages, more needs to be done. Nonetheless, these policies are economically, socially and environmentally cobeneficial to the city environment. While the lack of political engagement and economic concerns limit these policies, lacking social motivation and engagement is the largest limitation towards implementing policy. We recommend cities to incentivize citizen and municipal engagement with responsible usage of plastics, cleaning the environment and preparing for future extreme rainfall events. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Dynamics of changing impacts of tropical Indo-Pacific variability on Indian and Australian rainfall

Science.gov (United States)

Li, Ziguang; Cai, Wenju; Lin, Xiaopei

2016-08-01

A positive Indian Ocean Dipole (IOD) and a warm phase of the El Niño-Southern Oscillation (ENSO) reduce rainfall over the Indian subcontinent and southern Australia. However, since the 1980s, El Niño’s influence has been decreasing, accompanied by a strengthening in the IOD’s influence on southern Australia but a reversal in the IOD’s influence on the Indian subcontinent. The dynamics are not fully understood. Here we show that a post-1980 weakening in the ENSO-IOD coherence plays a key role. During the pre-1980 high coherence, ENSO drives both the IOD and regional rainfall, and the IOD’s influence cannot manifest itself. During the post-1980 weak coherence, a positive IOD leads to increased Indian rainfall, offsetting the impact from El Niño. Likewise, the post-1980 weak ENSO-IOD coherence means that El Niño’s pathway for influencing southern Australia cannot fully operate, and as positive IOD becomes more independent and more frequent during this period, its influence on southern Australia rainfall strengthens. There is no evidence to support that greenhouse warming plays a part in these decadal fluctuations.

A variable resolution right TIN approach for gridded oceanographic data

Science.gov (United States)

Marks, David; Elmore, Paul; Blain, Cheryl Ann; Bourgeois, Brian; Petry, Frederick; Ferrini, Vicki

2017-12-01

Many oceanographic applications require multi resolution representation of gridded data such as for bathymetric data. Although triangular irregular networks (TINs) allow for variable resolution, they do not provide a gridded structure. Right TINs (RTINs) are compatible with a gridded structure. We explored the use of two approaches for RTINs termed top-down and bottom-up implementations. We illustrate why the latter is most appropriate for gridded data and describe for this technique how the data can be thinned. While both the top-down and bottom-up approaches accurately preserve the surface morphology of any given region, the top-down method of vertex placement can fail to match the actual vertex locations of the underlying grid in many instances, resulting in obscured topology/bathymetry. Finally we describe the use of the bottom-up approach and data thinning in two applications. The first is to provide thinned, variable resolution bathymetry data for tests of storm surge and inundation modeling, in particular hurricane Katrina. Secondly we consider the use of the approach for an application to an oceanographic data grid of 3-D ocean temperature.

Subgrid Parameterization of the Soil Moisture Storage Capacity for a Distributed Rainfall-Runoff Model

Directory of Open Access Journals (Sweden)

Weijian Guo

2015-05-01

Full Text Available Spatial variability plays an important role in nonlinear hydrologic processes. Due to the limitation of computational efficiency and data resolution, subgrid variability is usually assumed to be uniform for most grid-based rainfall-runoff models, which leads to the scale-dependence of model performances. In this paper, the scale effect on the Grid-Xinanjiang model was examined. The bias of the estimation of precipitation, runoff, evapotranspiration and soil moisture at the different grid scales, along with the scale-dependence of the effective parameters, highlights the importance of well representing the subgrid variability. This paper presents a subgrid parameterization method to incorporate the subgrid variability of the soil storage capacity, which is a key variable that controls runoff generation and partitioning in the Grid-Xinanjiang model. In light of the similar spatial pattern and physical basis, the soil storage capacity is correlated with the topographic index, whose spatial distribution can more readily be measured. A beta distribution is introduced to represent the spatial distribution of the soil storage capacity within the grid. The results derived from the Yanduhe Basin show that the proposed subgrid parameterization method can effectively correct the watershed soil storage capacity curve. Compared to the original Grid-Xinanjiang model, the model performances are quite consistent at the different grid scales when the subgrid variability is incorporated. This subgrid parameterization method reduces the recalibration necessity when the Digital Elevation Model (DEM resolution is changed. Moreover, it improves the potential for the application of the distributed model in the ungauged basin.

Significant influences of global mean temperature and ENSO on extreme rainfall over Southeast Asia

Science.gov (United States)

Villafuerte, Marcelino, II; Matsumoto, Jun

2014-05-01

Along with the increasing concerns on the consequences of global warming, and the accumulating records of disaster related to heavy rainfall events in Southeast Asia, this study investigates whether a direct link can be detected between the rising global mean temperature, as well as the El Niño-Southern Oscillation (ENSO), and extreme rainfall over the region. The maximum likelihood modeling that allows incorporating covariates on the location parameter of the generalized extreme value (GEV) distribution is employed. The GEV model is fitted to annual and seasonal rainfall extremes, which were taken from a high-resolution gauge-based gridded daily precipitation data covering a span of 57 years (1951-2007). Nonstationarities in extreme rainfall are detected over the central parts of Indochina Peninsula, eastern coasts of central Vietnam, northwest of the Sumatra Island, inland portions of Borneo Island, and on the northeastern and southwestern coasts of the Philippines. These nonstationarities in extreme rainfall are directly linked to near-surface global mean temperature and ENSO. In particular, the study reveals that a kelvin increase in global mean temperature anomaly can lead to an increase of 30% to even greater than 45% in annual maximum 1-day rainfall, which were observed pronouncedly over central Vietnam, southern coast of Myanmar, northwestern sections of Thailand, northwestern tip of Sumatra, central portions of Malaysia, and the Visayas island in central Philippines. Furthermore, a pronounced ENSO influence manifested on the seasonal maximum 1-day rainfall; a northward progression of 10%-15% drier condition over Southeast Asia as the El Niño develops from summer to winter is revealed. It is important therefore, to consider the results obtained here for water resources management as well as for adaptation planning to minimize the potential adverse impact of global warming, particularly on extreme rainfall and its associated flood risk over the region

[Effects of rainfall intensity on rainfall infiltration and redistribution in soil on Loess slope land].

Science.gov (United States)

Li, Yi; Shao, Ming'an

2006-12-01

With simulation test, this paper studied the patterns of rainfall infiltration and redistribution in soil on typical Loess slope land, and analyzed the quantitative relations between the infiltration and redistribution and the movement of soil water and mass, with rainfall intensity as the main affecting factor. The results showed that rainfall intensity had significant effects on the rainfall infiltration and water redistribution in soil, and the microcosmic movement of soil water. The larger the rainfall intensity, the deeper the wetting front of rainfall infiltration and redistribution was, and the wetting front of soil water redistribution had a slower increase velocity than that of rainfall infiltration. The power function of the wetting front with time, and also with rainfall intensity, was fitted well. There was also a quantitative relation between the wetting front of rainfall redistribution and the duration of rainfall. The larger the rainfall intensity, the higher the initial and steady infiltration rates were, and the cumulative infiltration increased faster with time. Moreover, the larger the rainfall intensity, the smaller the wetting front difference was at the top and the end of the slope. With the larger rainfall intensity, both the difference of soil water content and its descending trend between soil layers became more obvious during the redistribution process on slope land.

Tropical influence on Euro-Asian autumn rainfall variability

Energy Technology Data Exchange (ETDEWEB)

Mariotti, A. [University of Maryland, College Park, MD (United States); ENEA, Rome (Italy); Ballabrera-Poy, J. [University of Maryland, ESSIC, College Park, MD (United States); Zeng, N. [University of Maryland, ESSIC, College Park, MD (United States); University of Maryland, Department of Meteorology,, College Park, MD (United States)

2005-04-01

The connection between autumn rainfall variability in the Euro-Asian domain and tropical climate is documented using state-of-the-art global observational datasets and re-analyses. Results suggest a robust statistical relationship between the El Nino Southern Oscillation (ENSO) and autumn rainfall in parts of southwest Europe, northern Africa and southwest Asia. The correlation between area-mean anomalies over this region (P{sub ea}) and the NINO3.4 index is 0.68, stationary over the last 50 years. Global ENSO-like tropical climate anomalies are observed in conjunction with P{sub ea} anomalies confirming the relationship found with the NINO3.4 index. Overall, the connection with Indo-Pacific variability is stronger than that with the eastern Pacific.While rainfall anomalies in southwest Europe and southwest Asia appear to largely co-vary as one pattern under the influence of ENSO, our results suggest that different mechanisms may be contributing to the observed anomalies. In the North Atlantic/European region, it is speculated that while a PNA-like mode maybe the prevailing teleconnection mechanism for high P{sub ea}, for low P{sub ea} tropical Atlantic ENSO related SST anomalies may be playing a more relevant role forcing northeastward propagating Rossby waves. Over southwest Asia, a more direct connection to the Indo-Pacific region is suggested by the upper air anomaly observed over southern Asia, possibly the Rossby wave response to enhanced heating in the Indian Ocean. (orig.)

Karst springs as 'natural' pluviometers: Constraints on the isotopic composition of rainfall in the Apennines of central Italy

International Nuclear Information System (INIS)

Minissale, A.; Vaselli, O.

2011-01-01

Highlights: → Isotopic compositions of karstic springs in central Italy have been reviewed. → Isotopic gradients of rainfalls for elevations have been evaluated in an Alpine valley. → Karstic drops have been calculated by using isotopic compositions of springs. → Isotopic compositions of rainfalls in central Italy have been re-calculated using the isotopic compositions of karstic springs. - Abstract: This paper describes an indirect method to calculate the isotopic composition of rainfall by using the isotopic composition of karst springs fed by waters circulating in the most important regional aquifer of central Italy, i.e. the Mesozoic limestone sequence that forms the backbone of the Apennines. By using δ 18 O and δD data and the δ 18 O (and/or δD) average gradient for elevation, evaluated through the use of literature rainfall data and new measurements from a typical Alpine valley in northern Italy, the altitude of precipitation of their parent water has been re-calculated. Vertical descents of more than 2000 m, from recharge to discharge, have been assessed in some high flow-rate cold springs in the morphologically steep Adriatic sector of central Italy. A clear correlation between the vertical descents and more negative isotopic compositions at their relative emergence elevations is highlighted. In contrast, in the Tyrrhenian sector lower karstic drops (generally lower than 500 m) correlate with less negative isotopic composition of recharge areas. The δ 18 O iso-contour map of the 'recalculated' parent rainfall in central Italy is more detailed than any possible isotopic map of rainfall made using pluviometers, unless large number of rainfall collectors were deployed on mountaintops. The data also show that the isotopic composition of rainfall depends on the source of the storm water. In particular, precipitation is isotopically heavier when originating in the Mediterranean Sea, and lighter when formed in the Atlantic Ocean. Consequently, the

Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

Science.gov (United States)

Bell, Thomas L.; Kundu, Prasun K.; Einaudi, Franco (Technical Monitor)

2000-01-01

Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

Estimation of Rainfall Erosivity via 1-Minute to Hourly Rainfall Data from Taipei, Taiwan

Science.gov (United States)

Huang, Ting-Yin; Yang, Ssu-Yao; Jan, Chyan-Deng

2017-04-01

Soil erosion is a natural process on hillslopes that threats people's life and properties, having a considerable environmental and economic implications for soil degradation, agricultural activity and water quality. The rainfall erosivity factor (R-factor) in the Universal Soil Loss Equation (USLE), composed of total kinetic energy (E) and the maximum 30-min rainfall intensity (I30), is widely used as an indicator to measure the potential risks of soil loss caused by rainfall at a regional scale. This R factor can represent the detachment and entrainment involved in climate conditions on hillslopes, but lack of 30-min rainfall intensity data usually lead to apply this factor more difficult in many regions. In recent years, fixed-interval, hourly rainfall data is readily available and widely used due to the development of automatic weather stations. Here we assess the estimations of R, E, and I30 based on 1-, 5-, 10-, 15-, 30-, 60-minute rainfall data, and hourly rainfall data obtained from Taipei weather station during 2004 to 2010. Results show that there is a strong correlation among R-factors estimated from different interval rainfall data. Moreover, the shorter time-interval rainfall data (e.g., 1-min) yields larger value of R-factor. The conversion factors of rainfall erosivity (ratio of values estimated from the resolution lower than 30-min rainfall data to those estimated from 60-min and hourly rainfall data, respectively) range from 1.85 to 1.40 (resp. from 1.89 to 1.02) for 60-min (resp. hourly) rainfall data as the time resolution increasing from 30-min to 1-min. This paper provides useful information on estimating R-factor when hourly rainfall data is only available.

Potential Predictability and Prediction Skill for Southern Peru Summertime Rainfall

Science.gov (United States)

WU, S.; Notaro, M.; Vavrus, S. J.; Mortensen, E.; Block, P. J.; Montgomery, R. J.; De Pierola, J. N.; Sanchez, C.

2016-12-01

The central Andes receive over 50% of annual climatological rainfall during the short period of January-March. This summertime rainfall exhibits strong interannual and decadal variability, including severe drought events that incur devastating societal impacts and cause agricultural communities and mining facilities to compete for limited water resources. An improved seasonal prediction skill of summertime rainfall would aid in water resource planning and allocation across the water-limited southern Peru. While various underlying mechanisms have been proposed by past studies for the drivers of interannual variability in summertime rainfall across southern Peru, such as the El Niño-Southern Oscillation (ENSO), Madden Julian Oscillation (MJO), and extratropical forcings, operational forecasts continue to be largely based on rudimentary ENSO-based indices, such as NINO3.4, justifying further exploration of predictive skill. In order to bridge this gap between the understanding of driving mechanisms and the operational forecast, we performed systematic studies on the predictability and prediction skill of southern Peru summertime rainfall by constructing statistical forecast models using best available weather station and reanalysis datasets. At first, by assuming the first two empirical orthogonal functions (EOFs) of summertime rainfall are predictable, the potential predictability skill was evaluated for southern Peru. Then, we constructed a simple regression model, based on the time series of tropical Pacific sea-surface temperatures (SSTs), and a more advanced Linear Inverse Model (LIM), based on the EOFs of tropical ocean SSTs and large-scale atmosphere variables from reanalysis. Our results show that the LIM model consistently outperforms the more rudimentary regression models on the forecast skill of domain averaged precipitation index and individual station indices. The improvement of forecast correlation skill ranges from 10% to over 200% for different

CRED Gridded Bathymetry of Bank 66 and east French Frigate Shoals (100-020) in the Northwestern Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — File 100-020b is a 60-m ASCII grid of depth data collected near Bank 66, East French Frigate Shoals in the Northwestern Hawaiian Islands as of May 2003. This grid...