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...

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

Science.gov (United States)

Tesfaye Ayehu, Getachew; Tadesse, Tsegaye; Gessesse, Berhan; Dinku, Tufa

2018-04-01

Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3) and the African Rainfall Climatology (ARC 2) products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days) and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD = 0.99, 1.00) and measure of volumetric rainfall (VHI = 1.00, 1.00), the highest correlation coefficients (r = 0.81, 0.88), better bias values (0.96, 0.96), and the lowest RMSE (28.45 mm dekad-1, 59.03 mm month-1) than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale), although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance underestimating rain gauge observed rainfall by

Development of Deep Learning Based Data Fusion Approach for Accurate Rainfall Estimation Using Ground Radar and Satellite Precipitation Products

Science.gov (United States)

Chen, H.; Chandra, C. V.; Tan, H.; Cifelli, R.; Xie, P.

2016-12-01

Rainfall estimation based on onboard satellite measurements has been an important topic in satellite meteorology for decades. A number of precipitation products at multiple time and space scales have been developed based upon satellite observations. For example, NOAA Climate Prediction Center has developed a morphing technique (i.e., CMORPH) to produce global precipitation products by combining existing space based rainfall estimates. The CMORPH products are essentially derived based on geostationary satellite IR brightness temperature information and retrievals from passive microwave measurements (Joyce et al. 2004). Although the space-based precipitation products provide an excellent tool for regional and global hydrologic and climate studies as well as improved situational awareness for operational forecasts, its accuracy is limited due to the sampling limitations, particularly for extreme events such as very light and/or heavy rain. On the other hand, ground-based radar is more mature science for quantitative precipitation estimation (QPE), especially after the implementation of dual-polarization technique and further enhanced by urban scale radar networks. Therefore, ground radars are often critical for providing local scale rainfall estimation and a "heads-up" for operational forecasters to issue watches and warnings as well as validation of various space measurements and products. The CASA DFW QPE system, which is based on dual-polarization X-band CASA radars and a local S-band WSR-88DP radar, has demonstrated its excellent performance during several years of operation in a variety of precipitation regimes. The real-time CASA DFW QPE products are used extensively for localized hydrometeorological applications such as urban flash flood forecasting. In this paper, a neural network based data fusion mechanism is introduced to improve the satellite-based CMORPH precipitation product by taking into account the ground radar measurements. A deep learning system is

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

Directory of Open Access Journals (Sweden)

G. T. Ayehu

2018-04-01

Full Text Available Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor ground observations or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3 and the African Rainfall Climatology (ARC 2 products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD  =  0.99, 1.00 and measure of volumetric rainfall (VHI  =  1.00, 1.00, the highest correlation coefficients (r =  0.81, 0.88, better bias values (0.96, 0.96, and the lowest RMSE (28.45 mm dekad−1, 59.03 mm month−1 than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale, although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance

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.

The Tropical Rainfall Measuring Mission and Vern Suomi 's Vital Role

Science.gov (United States)

Simpson, Joanne; Kummerow, Christian

1999-01-01

The Tropical Rainfall Measuring Mission was a new concept of measuring rainfall over the global tropics using a combination of instruments, including the first weather radar to be flown in space. An important objective of the mission was to obtain profiles of latent heat in order to initialize large-scale circulation models and to understand the relationship between short-term climate changes in relation to rainfall variability. The idea originated in the early 1980's from scientists at the Goddard Space Flight Center/NASA who had been involved with attempts to measure rain with a passive microwave instrument on Nimbus 5 and had compared its results with rain falling in the area covered by the GATE1 radar ships. Using an imaginary satellite flying over the GATE ships, scientists showed that a satellite with an inclined orbit of 30-35 degrees could obtain monthly rainfalls with a sampling error of less than 10 percent over 5 degree by 5 degree areas. The Japanese proposed that they could build a nadir-scanning rain radar for the satellite. Vern Suomi was excited by this mission from the outset, since he recognized the great importance of adequate rainfall measurements over the tropical oceans. He was a charter member of the Science Steering Team and prepared a large part of the Report. While the mission attracted strong support in the science community, it was opposed by some of the high-level NASA management who feared its competition for funds with some much larger Earth Science satellites. Vern was able to overcome this opposition and to generate Congressional support, so that the Project finally got underway on both sides of the Pacific in 1991. The paper will discuss the design of the satellite, its data system and ground validation program. TP.NM was successfully launched in late 1997. Early results will be described. 1 GATE stands for GARP Atlantic Tropical Experiment and GARP stands for Global Atmospheric Research Program.

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.

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

Application of seasonal rainfall forecasts and satellite rainfall observations to crop yield forecasting for Africa

Science.gov (United States)

Greatrex, H. L.; Grimes, D. I. F.; Wheeler, T. R.

2009-04-01

Rain-fed agriculture is of utmost importance in sub-Saharan Africa; the FAO estimates that over 90% of food consumed in the region is grown in rain-fed farming systems. As the climate in sub-Saharan Africa has a high interannual variability, this dependence on rainfall can leave communities extremely vulnerable to food shortages, especially when coupled with a lack of crop management options. The ability to make a regional forecast of crop yield on a timescale of months would be of enormous benefit; it would enable both governmental and non-governmental organisations to be alerted in advance to crop failure and could facilitate national and regional economic planning. Such a system would also enable individual communities to make more informed crop management decisions, increasing their resilience to climate variability and change. It should be noted that the majority of crops in the region are rainfall limited, therefore the ability to create a seasonal crop forecast depends on the ability to forecast rainfall at a monthly or seasonal timescale and to temporally downscale this to a daily time-series of rainfall. The aim of this project is to develop a regional-scale seasonal forecast for sub-Saharan crops, utilising the General Large Area Model for annual crops (GLAM). GLAM would initially be driven using both dynamical and statistical seasonal rainfall forecasts to provide an initial estimate of crop yield. The system would then be continuously updated throughout the season by replacing the seasonal rainfall forecast with daily weather observations. TAMSAT satellite rainfall estimates are used rather than rain-gauge data due to the scarcity of ground based observations. An important feature of the system is the use of the geo-statistical method of sequential simulation to create an ensemble of daily weather inputs from both the statistical seasonal rainfall forecasts and the satellite rainfall estimates. This allows a range of possible yield outputs to be

Comparing Satellite Rainfall Estimates with Rain-Gauge Data: Optimal Strategies Suggested by a Spectral Model

Science.gov (United States)

Bell, Thomas L.; Kundu, Prasun K.; Lau, William K. M. (Technical Monitor)

2002-01-01

Validation of satellite remote-sensing methods for estimating rainfall against rain-gauge data is attractive because of the direct nature of the rain-gauge measurements. Comparisons of satellite estimates to rain-gauge data are difficult, however, because of the extreme variability of rain and the fact that satellites view large areas over a short time while rain gauges monitor small areas continuously. In this paper, a statistical model of rainfall variability developed for studies of sampling error in averages of satellite data is used to examine the impact of spatial and temporal averaging of satellite and gauge data on intercomparison results. The model parameters were derived from radar observations of rain, but the model appears to capture many of the characteristics of rain-gauge data as well. The model predicts that many months of data from areas containing a few gauges are required to validate satellite estimates over the areas, and that the areas should be of the order of several hundred km in diameter. Over gauge arrays of sufficiently high density, the optimal areas and averaging times are reduced. The possibility of using time-weighted averages of gauge data is explored.

Assessment of satellite rainfall products over the Andean plateau

Science.gov (United States)

Satgé, Frédéric; Bonnet, Marie-Paule; Gosset, Marielle; Molina, Jorge; Hernan Yuque Lima, Wilson; Pillco Zolá, Ramiro; Timouk, Franck; Garnier, Jérémie

2016-01-01

Nine satellite rainfall estimations (SREs) were evaluated for the first time over the South American Andean plateau watershed by comparison with rain gauge data acquired between 2005 and 2007. The comparisons were carried out at the annual, monthly and daily time steps. All SREs reproduce the salient pattern of the annual rain field, with a marked north-south gradient and a lighter east-west gradient. However, the intensity of the gradient differs among SREs: it is well marked in the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 (TMPA-3B42), Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Global Satellite Mapping of Precipitation (GSMaP) products, and it is smoothed out in the Climate prediction center MORPHing (CMORPH) products. Another interesting difference among products is the contrast in rainfall amounts between the water surfaces (Lake Titicaca) and the surrounding land. Some products (TMPA-3B42, PERSIANN and GSMaP) show a contradictory rainfall deficit over Lake Titicaca, which may be due to the emissivity contrast between the lake and the surrounding lands and warm rain cloud processes. An analysis differentiating coastal Lake Titicaca from inland pixels confirmed this trend. The raw or Real Time (RT) products have strong biases over the study region. These biases are strongly positive for PERSIANN (above 90%), moderately positive for TMPA-3B42 (28%), strongly negative for CMORPH (- 42%) and moderately negative for GSMaP (- 18%). The biases are associated with a deformation of the rain rate frequency distribution: GSMaP underestimates the proportion of rainfall events for all rain rates; CMORPH overestimates the proportion of rain rates below 2 mm day- 1; and the other products tend to overestimate the proportion of moderate to high rain rates. These biases are greatly reduced by the gauge adjustment in the TMPA-3B42, PERSIANN and CMORPH products, whereas a

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.

Cross-validation Methodology between Ground and GPM Satellite-based Radar Rainfall Product over Dallas-Fort Worth (DFW) Metroplex

Science.gov (United States)

Chen, H.; Chandrasekar, V.; Biswas, S.

2015-12-01

Over the past two decades, a large number of rainfall products have been developed based on satellite, radar, and/or rain gauge observations. However, to produce optimal rainfall estimation for a given region is still challenging due to the space time variability of rainfall at many scales and the spatial and temporal sampling difference of different rainfall instruments. In order to produce high-resolution rainfall products for urban flash flood applications and improve the weather sensing capability in urban environment, the center for Collaborative Adaptive Sensing of the Atmosphere (CASA), in collaboration with National Weather Service (NWS) and North Central Texas Council of Governments (NCTCOG), has developed an urban radar remote sensing network in DFW Metroplex. DFW is the largest inland metropolitan area in the U.S., that experiences a wide range of natural weather hazards such as flash flood and hailstorms. The DFW urban remote sensing network, centered by the deployment of eight dual-polarization X-band radars and a NWS WSR-88DP radar, is expected to provide impacts-based warning and forecasts for benefit of the public safety and economy. High-resolution quantitative precipitation estimation (QPE) is one of the major goals of the development of this urban test bed. In addition to ground radar-based rainfall estimation, satellite-based rainfall products for this area are also of interest for this study. Typical example is the rainfall rate product produced by the Dual-frequency Precipitation Radar (DPR) onboard Global Precipitation Measurement (GPM) Core Observatory satellite. Therefore, cross-comparison between ground and space-based rainfall estimation is critical to building an optimal regional rainfall system, which can take advantages of the sampling differences of different sensors. This paper presents the real-time high-resolution QPE system developed for DFW urban radar network, which is based upon the combination of S-band WSR-88DP and X

Rainfall frequency analysis for ungauged sites using satellite precipitation products

Science.gov (United States)

Gado, Tamer A.; Hsu, Kuolin; Sorooshian, Soroosh

2017-11-01

The occurrence of extreme rainfall events and their impacts on hydrologic systems and society are critical considerations in the design and management of a large number of water resources projects. As precipitation records are often limited or unavailable at many sites, it is essential to develop better methods for regional estimation of extreme rainfall at these partially-gauged or ungauged sites. In this study, an innovative method for regional rainfall frequency analysis for ungauged sites is presented. The new method (hereafter, this is called the RRFA-S) is based on corrected annual maximum series obtained from a satellite precipitation product (e.g., PERSIANN-CDR). The probability matching method (PMM) is used here for bias correction to match the CDF of satellite-based precipitation data with the gauged data. The RRFA-S method was assessed through a comparative study with the traditional index flood method using the available annual maximum series of daily rainfall in two different regions in USA (11 sites in Colorado and 18 sites in California). The leave-one-out cross-validation technique was used to represent the ungauged site condition. Results of this numerical application have found that the quantile estimates obtained from the new approach are more accurate and more robust than those given by the traditional index flood method.

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.

The Variation of Tropical Cyclone Rainfall within the North Atlantic and Pacific as Observed from Satellites

Science.gov (United States)

Rodgers, Edward; Pierce, Harold; Adler, Robert

1999-01-01

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations in the North Atlantic and in three equal geographical regions of the North Pacific (i.e., Western, Central, and Eastern North Pacific). These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the 1987-1989, 1991-1998 North Atlantic and Pacific rainfall during June-November when tropical cyclones are most abundant. To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from the Defence Meteorological Satellite Program (DMSP) Special Sensor Microwave/ Radiometer (SSM/I) observations within 444 km radius of the center of those North Atlantic and Pacific tropical cyclones that reached storm stage and greater. These rain rate observations are then multiplied by the number of hours in a given month. Mean monthly rainfall amounts are also constructed for all the other North Atlantic and Pacific raining systems during this eleven year period for the purpose of estimating the geographical distribution and intensity of rainfall contributed by non-tropical cyclone systems. Further, the combination of the non-tropical cyclone and tropical cyclone (i.e., total) rainfall is constructed to delineate the fractional amount that tropical cyclones contributed to the total North Pacific rainfall.

On the Characterization of Rainfall Associated with U.S. Landfalling North Atlantic Tropical Cyclones Based on Satellite Data and Numerical Weather Prediction Outputs

Science.gov (United States)

Luitel, B. N.; Villarini, G.; Vecchi, G. A.

2014-12-01

When we talk about tropical cyclones (TCs), the first things that come to mind are strong winds and storm surge affecting the coastal areas. However, according to the Federal Emergency Management Agency (FEMA) 59% of the deaths caused by TCs since 1970 is due to fresh water flooding. Heavy rainfall associated with TCs accounts for 13% of heavy rainfall events nationwide for the June-October months, with this percentage being much higher if the focus is on the eastern and southern United States. This study focuses on the evaluation of precipitation associated with the North Atlantic TCs that affected the continental United States over the period 2007 - 2012. We evaluate the rainfall associated with these TCs using four satellite based rainfall products: Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA; both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); Climate Prediction Center (CPC) MORPHing technique (CMORPH). As a reference data we use gridded rainfall provided by CPC (Daily US Unified Gauge-Based Analysis of Precipitation). Rainfall fields from each of these satellite products are compared to the reference data, providing valuable information about the realism of these products in reproducing the rainfall associated with TCs affecting the continental United States. In addition to the satellite products, we evaluate the forecasted rainfall produced by five state-of-the-art numerical weather prediction (NWP) models: European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC). The skill of these models in reproducing TC rainfall is quantified for different lead times, and discussed in light of the performance of the satellite products.

Satellite observations of rainfall effect on sea surface salinity in the waters adjacent to Taiwan

Science.gov (United States)

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

2017-10-01

Changes of oceanic salinity are highly related to the variations of evaporation and precipitation. To understand the influence of rainfall on the sea surface salinity (SSS) in the waters adjacent to Taiwan, satellite remote sensing data from the year of 2012 to 2014 are employed in this study. The daily rain rate data obtained from Special Sensor Microwave Imager (SSM/I), Tropical Rainfall Measuring Mission's Microwave Imager (TRMM/TMI), Advanced Microwave Scanning Radiometer (AMSR), and WindSat Polarimetric Radiometer. The SSS data was derived from the measurements of radiometer instruments onboard the Aquarius satellite. The results show the average values of SSS in east of Taiwan, east of Luzon and South China Sea are 33.83 psu, 34.05 psu, and 32.84 psu, respectively, in the condition of daily rain rate higher than 1 mm/hr. In contrast to the rainfall condition, the average values of SSS are 34.07 psu, 34.26 psu, and 33.09 psu in the three areas, respectively at no rain condition (rain rate less than 1 mm/hr). During the cases of heavy rainfall caused by spiral rain bands of typhoon, the SSS is diluted with an average value of -0.78 psu when the average rain rate is higher than 4 mm/hr. However, the SSS was increased after temporarily decreased during the typhoon cases. A possible reason to explain this phenomenon is that the heavy rainfall caused by the spiral rain bands of typhoon may dilute the sea surface water, but the strong winds can uplift the higher salinity of subsurface water to the sea surface.

Contributions of Tropical Cyclones to the North Atlantic Climatological Rainfall as Observed from Satellites

Science.gov (United States)

Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.; Einaudi, Franco (Technical Monitor)

2000-01-01

The tropical cyclone rainfall climatology study that was performed for the North Pacific was extended to the North Atlantic. Similar to the North Pacific tropical cyclone study, mean monthly rainfall within 444 km of the center of the North Atlantic tropical cyclones (i.e., that reached storm stage and greater) was estimated from passive microwave satellite observations during, an eleven year period. These satellite-observed rainfall estimates were used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the North Atlantic total rainfall during, June-November when tropical cyclones were most abundant. The main results from this study indicate: 1) that tropical cyclones contribute, respectively, 4%, 3%, and 4% to the western, eastern, and entire North Atlantic; 2) similar to that observed in the North Pacific, the maximum in North Atlantic tropical cyclone rainfall is approximately 5 - 10 deg poleward (depending on longitude) of the maximum non-tropical cyclone rainfall; 3) tropical cyclones contribute regionally a maximum of 30% of the total rainfall 'northeast of Puerto Rico, within a region near 15 deg N 55 deg W, and off the west coast of Africa; 4) there is no lag between the months with maximum tropical cyclone rainfall and non-tropical cyclone rainfall in the western North Atlantic, while in the eastern North Atlantic, maximum tropical cyclone rainfall precedes maximum non-tropical cyclone rainfall; 5) like the North Pacific, North Atlantic tropical cyclones Of hurricane intensity generate the greatest amount of rainfall in the higher latitudes; and 6) warm ENSO events inhibit tropical cyclone rainfall.

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

OpenAIRE

Kimani, M.W.; Hoedjes, Johannes Cornelis Bernardus; Su, Z.

2017-01-01

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...

Sensitivity of Distributed Hydrologic Simulations to Ground and Satellite Based Rainfall Products

Directory of Open Access Journals (Sweden)

Singaiah Chintalapudi

2014-05-01

Full Text Available In this study, seven precipitation products (rain gauges, NEXRAD MPE, PERSIANN 0.25 degree, PERSIANN CCS-3hr, PERSIANN CCS-1hr, TRMM 3B42V7, and CMORPH were used to force a physically-based distributed hydrologic model. The model was driven by these products to simulate the hydrologic response of a 1232 km2 watershed in the Guadalupe River basin, Texas. Storm events in 2007 were used to analyze the precipitation products. Comparison with rain gauge observations reveals that there were significant biases in the satellite rainfall products and large variations in the estimated amounts. The radar basin average precipitation compared very well with the rain gauge product while the gauge-adjusted TRMM 3B42V7 precipitation compared best with observed rainfall among all satellite precipitation products. The NEXRAD MPE simulated streamflows matched the observed ones the best yielding the highest Nash-Sutcliffe Efficiency correlation coefficient values for both the July and August 2007 events. Simulations driven by TRMM 3B42V7 matched the observed streamflow better than other satellite products for both events. The PERSIANN coarse resolution product yielded better runoff results than the higher resolution product. The study reveals that satellite rainfall products are viable alternatives when rain gauge or ground radar observations are sparse or non-existent.

Rainfall Imprint on Sea Surface Salinity in the ITCZ: new satellite perspectives

Science.gov (United States)

Boutin, J.; Viltard, N.; Supply, A.; Martin, N.; Vergely, J. L.; Hénocq, C.; Reverdin, G. P.

2016-02-01

The European Soil Moisture and Ocean Salinity (SMOS) satellite mission monitors sea surface salinity (SSS) over the global ocean for more than 5 years since 2010. The MADRAS microwave radiometer carried by the French (CNES) Indian (ISRO) satellite mission Megha-Tropiques sampled the 30° N-30° S region end of 2011 and in 2012, very complementary to other Global Precipitation Measurement(GPM) missions. In tropical regions, SMOS SSS contains a large imprint of atmospheric rainfall, but is also likely affected by oceanographic processes (advection and diffusion). At local and short time scales, Boutin et al. (2013, 2014) have shown that the spatio-temporal variability of SSS is dominated by rainfall as detected by satellite microwave radiometers and have demonstrated a close to linear relationship between SMOS SSS freshening under rain cells and satellite rain rate. The order of magnitude is in remarkable agreement with the theoretical renewal model of Schlussel et al. (1997) and compatible with AQUARIUS SSS observations, as well as with in situ drifters observations although the latter are local and taken at 45cm depth while satellite L-band SSS roughly correspond to the top 1cm depth and are spatially integrated over 43-150km. It is thus expected that the combined information of satellite rain rates and satellite SSS brings new constraints on the precipitation budget. We first look at the consistency between the spatial structures of SMOS SSS decrease and of rain rates derived either from the MADRAS microwave radiometer or from the CMORPH combined products that do not use MADRAS rain rates. This provides an indirect validation of the rain rates estimates. We then investigate the impact of rain history and of wind speed on the observed SMOS freshening. Based on these results, we discuss the precision on various precipitation estimates over 2012 in the ITCZ region and the major sources of uncertainties that the SPURS2 campaign could help to resolve.

Satellite-based estimation of rainfall erosivity for Africa

NARCIS (Netherlands)

Vrieling, A.; Sterk, G.; Jong, S.M. de

2010-01-01

Rainfall erosivity is a measure for the erosive force of rainfall. Rainfall kinetic energy determines the erosivity and is in turn greatly dependent on rainfall intensity. Attempts for its large-scale mapping are rare. Most are based on interpolation of erosivity values derived from rain gauge

Does GPM-based multi-satellite precipitation enhance rainfall estimates over Pakistan and Bolivia arid regions?

Science.gov (United States)

Hussain, Y.; Satgé, F.; Bonnet, M. P.; Pillco, R.; Molina, J.; Timouk, F.; Roig, H.; Martinez-Carvajal, H., Sr.; Gulraiz, A.

2016-12-01

Arid regions are sensitive to rainfall variations which are expressed in the form of flooding and droughts. Unfortunately, those regions are poorly monitored and high quality rainfall estimates are still needed. The Global Precipitation Measurement (GPM) mission released two new satellite rainfall products named Integrated Multisatellite Retrievals GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) bringing the possibility of accurate rainfall monitoring over these countries. This study assessed both products at monthly scale over Pakistan considering dry and wet season over the 4 main climatic zones from 2014 to 2016. With similar climatic conditions, the Altiplano region of Bolivia is considered to quantify the influence of big lakes (Titicaca and Poopó) in rainfall estimates. For comparison, the widely used TRMM-Multisatellite Precipitation Analysis 3B43 (TMPA-3B43) version 7 is also involved in the analysis to observe the potential enhancement in rainfall estimate brought by GPM products. Rainfall estimates derived from 110 rain-gauges are used as reference to compare IMERG, GSMaP-v6 and TMPA-3B43 at the 0.1° and 0.25° spatial resolution. Over both regions, IMERG and GSMaP-v6 capture the spatial pattern of precipitation as well as TMPA-3B43. All products tend to over estimates rainfall over very arid regions. This feature is even more marked during dry season. However, during this season, both reference and estimated rainfall remain very low and do not impact seasonal water budget computation. On a general way, IMERG slightly outperforms TMPA-3B43 and GSMaP-v6 which provides the less accurate rainfall estimate. The TMPA-3B43 rainfall underestimation previously found over Lake Titicaca is still observed in IMERG estimates. However, GSMaP-v6 considerably decreases the underestimation providing the most accurate rainfall estimate over the lake. MOD11C3 Land Surface Temperature (LST) and ASTER Global Emissivity Dataset reveal strong

Assessment on spatiotemporal relationship between rainfall and cloud top temperature from new generation weather satellite imagery

Science.gov (United States)

Wei, Chiang; Yeh, Hui-Chung; Chen, Yen-Chang

2017-04-01

This study addressed the relationship between rainfall and cloud top temperature (CCT) from new generation satellite Himawari-8 imagery at different spatiotemporal scale. This satellite provides higher band, more bits for data format, spatial and temporal resolution compared with previous GMS series. The multi-infrared channels with 10-minute and 1-2 km resolution make it possible for rainfall estimating/forecasting in small/medium watershed. The preliminary result investigated at Chenyulan watershed (443.6 square kilometer) of Central Taiwan in 2016 Typhoon Megi shows the regression coefficient fitted by negative exponential equation of largest rainfall vs. CCT (B8 band) at pixel scale increases as time scales enlarges and reach 0.462 for 120-minute accumulative rainfall; the value (CTT of B15 band) decreases from 0.635 for 10-minute to 0.423 for 120-minute accumulative rainfall at basin-wide scale. More rainfall events for different regime are yet to evaluate to get solid results.

Does the GPM mission improve the systematic error component in satellite rainfall estimates over TRMM? An evaluation at a pan-India scale

Science.gov (United States)

Beria, Harsh; Nanda, Trushnamayee; Singh Bisht, Deepak; Chatterjee, Chandranath

2017-12-01

The last couple of decades have seen the outburst of a number of satellite-based precipitation products with Tropical Rainfall Measuring Mission (TRMM) as the most widely used for hydrologic applications. Transition of TRMM into the Global Precipitation Measurement (GPM) promises enhanced spatio-temporal resolution along with upgrades to sensors and rainfall estimation techniques. The dependence of systematic error components in rainfall estimates of the Integrated Multi-satellitE Retrievals for GPM (IMERG), and their variation with climatology and topography, was evaluated over 86 basins in India for year 2014 and compared with the corresponding (2014) and retrospective (1998-2013) TRMM estimates. IMERG outperformed TRMM for all rainfall intensities across a majority of Indian basins, with significant improvement in low rainfall estimates showing smaller negative biases in 75 out of 86 basins. Low rainfall estimates in TRMM showed a systematic dependence on basin climatology, with significant overprediction in semi-arid basins, which gradually improved in the higher rainfall basins. Medium and high rainfall estimates of TRMM exhibited a strong dependence on basin topography, with declining skill in higher elevation basins. The systematic dependence of error components on basin climatology and topography was reduced in IMERG, especially in terms of topography. Rainfall-runoff modeling using the Variable Infiltration Capacity (VIC) model over two flood-prone basins (Mahanadi and Wainganga) revealed that improvement in rainfall estimates in IMERG did not translate into improvement in runoff simulations. More studies are required over basins in different hydroclimatic zones to evaluate the hydrologic significance of IMERG.

Does the GPM mission improve the systematic error component in satellite rainfall estimates over TRMM? An evaluation at a pan-India scale

Directory of Open Access Journals (Sweden)

H. Beria

2017-12-01

Full Text Available The last couple of decades have seen the outburst of a number of satellite-based precipitation products with Tropical Rainfall Measuring Mission (TRMM as the most widely used for hydrologic applications. Transition of TRMM into the Global Precipitation Measurement (GPM promises enhanced spatio-temporal resolution along with upgrades to sensors and rainfall estimation techniques. The dependence of systematic error components in rainfall estimates of the Integrated Multi-satellitE Retrievals for GPM (IMERG, and their variation with climatology and topography, was evaluated over 86 basins in India for year 2014 and compared with the corresponding (2014 and retrospective (1998–2013 TRMM estimates. IMERG outperformed TRMM for all rainfall intensities across a majority of Indian basins, with significant improvement in low rainfall estimates showing smaller negative biases in 75 out of 86 basins. Low rainfall estimates in TRMM showed a systematic dependence on basin climatology, with significant overprediction in semi-arid basins, which gradually improved in the higher rainfall basins. Medium and high rainfall estimates of TRMM exhibited a strong dependence on basin topography, with declining skill in higher elevation basins. The systematic dependence of error components on basin climatology and topography was reduced in IMERG, especially in terms of topography. Rainfall-runoff modeling using the Variable Infiltration Capacity (VIC model over two flood-prone basins (Mahanadi and Wainganga revealed that improvement in rainfall estimates in IMERG did not translate into improvement in runoff simulations. More studies are required over basins in different hydroclimatic zones to evaluate the hydrologic significance of IMERG.

Developments in radar and remote-sensing methods for measuring and forecasting rainfall.

Science.gov (United States)

Collier, C G

2002-07-15

Over the last 25 years or so, weather-radar networks have become an integral part of operational meteorological observing systems. While measurements of rainfall made using radar systems have been used qualitatively by weather forecasters, and by some operational hydrologists, acceptance has been limited as a consequence of uncertainties in the quality of the data. Nevertheless, new algorithms for improving the accuracy of radar measurements of rainfall have been developed, including the potential to calibrate radars using the measurements of attenuation on microwave telecommunications links. Likewise, ways of assimilating these data into both meteorological and hydrological models are being developed. In this paper we review the current accuracy of radar estimates of rainfall, pointing out those approaches to the improvement of accuracy which are likely to be most successful operationally. Comment is made on the usefulness of satellite data for estimating rainfall in a flood-forecasting context. Finally, problems in coping with the error characteristics of all these data using both simple schemes and more complex four-dimensional variational analysis are being addressed, and are discussed briefly in this paper.

Feasibility Study on the Satellite Rainfall Data for Prediction of Sediment- Related Disaster by the Japanese Prediction Methodology

Science.gov (United States)

Shimizu, Y.; Ishizuka, T.; Osanai, N.; Okazumi, T.

2014-12-01

In this study, the sediment-related disaster prediction method which based ground gauged rainfall-data, currently practiced in Japan was coupled with satellite rainfall data and applied to domestic large-scale sediment-related disasters. The study confirmed the feasibility of this integrated method. In Asia, large-scale sediment-related disasters which can sweep away an entire settlement occur frequently. Leyte Island suffered from a huge landslide in 2004, and Typhoon Molakot in 2009 caused huge landslides in Taiwan. In the event of these sediment-related disasters, immediate responses by central and local governments are crucial in crisis management. In general, there are not enough rainfall gauge stations in developing countries. Therefore national and local governments have little information to determine the risk level of water induced disasters in their service areas. In the Japanese methodology, a criterion is set by combining two indices: the short-term rainfall index and long-term rainfall index. The short-term rainfall index is defined as the 60-minute total rainfall; the long-term rainfall index as the soil-water index, which is an estimation of the retention status of fallen rainfall in soil. In July 2009, a high-density sediment related disaster, or a debris flow, occurred in Hofu City of Yamaguchi Prefecture, in the western region of Japan. This event was calculated by the Japanese standard methodology, and then analyzed for its feasibility. Hourly satellite based rainfall has underestimates compared with ground based rainfall data. Long-term index correlates with each other. Therefore, this study confirmed that it is possible to deliver information on the risk level of sediment-related disasters such as shallow landslides and debris flows. The prediction method tested in this study is expected to assist for timely emergency responses to rainfall-induced natural disasters in sparsely gauged areas. As the Global Precipitation Measurement (GPM) Plan

Detecting Climate Variability in Tropical Rainfall

Science.gov (United States)

Berg, W.

2004-05-01

El Niño is substantially smaller due to decreased rainfall in the west Pacific partially canceling increases in the central and east Pacific. These differences are not limited to the long-term merged rainfall products using infrared data, but are also exist in state-of-the-art rainfall retrievals from the active and passive microwave sensors on board the Tropical Rainfall Measuring Mission (TRMM). For example, large differences exist in the response of tropical mean rainfall retrieved from the TRMM microwave imager (TMI) 2A12 algorithm and the precipitation radar (PR) 2A25 algorithm to the 1997/98 El Niño. To assist scientists attempting to wade through the vast array of climate rainfall products currently available, and to help them determine whether systematic biases in these rainfall products impact the conclusions of a given study, we have developed a Climate Rainfall Data Center (CRDC). The CRDC web site (rain.atmos.colostate.edu/CRDC) provides climate researchers information on the various rainfall datasets available as well as access to experts in the field of satellite rainfall retrievals to assist them in the appropriate selection and use of climate 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.

Assimilating satellite soil moisture into rainfall-runoff modelling: towards a systematic study

Science.gov (United States)

Massari, Christian; Tarpanelli, Angelica; Brocca, Luca; Moramarco, Tommaso

2015-04-01

Soil moisture is the main factor for the repartition of the mass and energy fluxes between the land surface and the atmosphere thus playing a fundamental role in the hydrological cycle. Indeed, soil moisture represents the initial condition of rainfall-runoff modelling that determines the flood response of a catchment. Different initial soil moisture conditions can discriminate between catastrophic and minor effects of a given rainfall event. Therefore, improving the estimation of initial soil moisture conditions will reduce uncertainties in early warning flood forecasting models addressing the mitigation of flood hazard. In recent years, satellite soil moisture products have become available with fine spatial-temporal resolution and a good accuracy. Therefore, a number of studies have been published in which the impact of the assimilation of satellite soil moisture data into rainfall-runoff modelling is investigated. Unfortunately, data assimilation involves a series of assumptions and choices that significantly affect the final result. Given a satellite soil moisture observation, a rainfall-runoff model and a data assimilation technique, an improvement or a deterioration of discharge predictions can be obtained depending on the choices made in the data assimilation procedure. Consequently, large discrepancies have been obtained in the studies published so far likely due to the differences in the implementation of the data assimilation technique. On this basis, a comprehensive and robust procedure for the assimilation of satellite soil moisture data into rainfall-runoff modelling is developed here and applied to six subcatchment of the Upper Tiber River Basin for which high-quality hydrometeorological hourly observations are available in the period 1989-2013. The satellite soil moisture product used in this study is obtained from the Advanced SCATterometer (ASCAT) onboard Metop-A satellite and it is available since 2007. The MISDc ("Modello Idrologico Semi

A Decadal Historical Satellite Data and Rainfall Trend Analysis (2001–2016 for Flood Hazard Mapping in Sri Lanka

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Niranga Alahacoon

2018-03-01

Full Text Available Critical information on a flood-affected area is needed in a short time frame to initiate rapid response operations and develop long-term flood management strategies. This study combined rainfall trend analysis using Asian Precipitation—Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE gridded rainfall data with flood maps derived from Synthetic Aperture Radar (SAR and multispectral satellite to arrive at holistic spatio-temporal patterns of floods in Sri Lanka. Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR data were used to map flood extents for emergency relief operations while eight-day Moderate Resolution Imaging Spectroradiometer (MODIS surface reflectance data for the time period from 2001 to 2016 were used to map long term flood-affected areas. The inundation maps produced for rapid response were published within three hours upon the availability of satellite imagery in web platforms, with the aim of supporting a wide range of stakeholders in emergency response and flood relief operations. The aggregated time series of flood extents mapped using MODIS data were used to develop a flood occurrence map (2001–2016 for Sri Lanka. Flood hotpots identified using both optical and synthetic aperture average of 325 km2 for the years 2006–2015 and exceptional flooding in 2016 with inundation extent of approximately 1400 km2. The time series rainfall data explains increasing trend in the extreme rainfall indices with similar observation derived from satellite imagery. The results demonstrate the feasibility of using multi-sensor flood mapping approaches, which will aid Disaster Management Center (DMC and other multi-lateral agencies involved in managing rapid response operations and preparing mitigation measures.

Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals

Science.gov (United States)

Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas

2016-03-01

Machine learning (ML) algorithms have successfully been demonstrated to be valuable tools in satellite-based rainfall retrievals which show the practicability of using ML algorithms when faced with high dimensional and complex data. Moreover, recent developments in parallel computing with ML present new possibilities for training and prediction speed and therefore make their usage in real-time systems feasible. This study compares four ML algorithms - random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) - for rainfall area detection and rainfall rate assignment using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path serve as predictor variables. The results indicate an overestimation of rainfall area delineation regardless of the ML algorithm (averaged bias = 1.8) but a high probability of detection ranging from 81% (SVM) to 85% (NNET). On a 24-hour basis, the performance of the rainfall rate assignment yielded R2 values between 0.39 (SVM) and 0.44 (AVNNET). Though the differences in the algorithms' performance were rather small, NNET and AVNNET were identified as the most suitable algorithms. On average, they demonstrated the best performance in rainfall area delineation as well as in rainfall rate assignment. NNET's computational speed is an additional advantage in work with large datasets such as in remote sensing based rainfall retrievals. However, since no single algorithm performed considerably better than the others we conclude that further research in providing suitable predictors for rainfall is of greater necessity than an optimization through the choice of the ML algorithm.

Extension of the TAMSAT satellite-based rainfall monitoring over Africa and from 1983 to present

OpenAIRE

Tarnavsky, Elena; Grimes, David; Maidment, Ross; Black, Emily; Allan, Richard; Stringer, Marc; Chadwick, Robin; Kayitakire, Francois

2014-01-01

Tropical Applications of Meteorology Using Satellite Data and Ground-Based Observations (TAMSAT) rainfall monitoring products have been extended to provide spatially contiguous rainfall estimates across Africa. This has been achieved through a new, climatology-based calibration, which varies in both space and time. As a result, cumulative estimates of rainfall are now issued at the end of each 10-day period (dekad) at 4-km spatial resolution with pan-African coverage. The utility of the produ...

Rainfall measurement from the opportunistic use of an Earth–space link in the Ku band

Directory of Open Access Journals (Sweden)

L. Barthès

2013-08-01

Full Text Available The present study deals with the development of a low-cost microwave device devoted to the measurement of average rain rates observed along Earth–satellite links, the latter being characterized by a tropospheric path length of a few kilometres. The ground-based power measurements, which are made using the Ku-band television transmissions from several different geostationary satellites, are based on the principle that the atmospheric attenuation produced by rain encountered along each transmission path can be used to determine the path-averaged rain rate. This kind of device could be very useful in hilly areas where radar data are not available or in urban areas where such devices could be directly placed in homes by using residential TV antenna. The major difficulty encountered with this technique is that of retrieving rainfall characteristics in the presence of many other causes of received signal fluctuation, produced by atmospheric scintillation, variations in atmospheric composition (water vapour concentration, cloud water content or satellite transmission parameters (variations in emitted power, satellite pointing. In order to conduct a feasibility study with such a device, a measurement campaign was carried out over a period of five months close to Paris. The present paper proposes an algorithm based on an artificial neural network, used to identify dry and rainy periods and to model received signal variability resulting from effects not related to rain. When the altitude of the rain layer is taken into account, the rain attenuation can be inverted to obtain the path-averaged rain rate. The rainfall rates obtained from this process are compared with co-located rain gauges and radar measurements taken throughout the full duration of the campaign, and the most significant rainfall events are analysed.

Rainfall measurement from the opportunistic use of an Earth-space link in the Ku band

Science.gov (United States)

Barthès, L.; Mallet, C.

2013-08-01

The present study deals with the development of a low-cost microwave device devoted to the measurement of average rain rates observed along Earth-satellite links, the latter being characterized by a tropospheric path length of a few kilometres. The ground-based power measurements, which are made using the Ku-band television transmissions from several different geostationary satellites, are based on the principle that the atmospheric attenuation produced by rain encountered along each transmission path can be used to determine the path-averaged rain rate. This kind of device could be very useful in hilly areas where radar data are not available or in urban areas where such devices could be directly placed in homes by using residential TV antenna. The major difficulty encountered with this technique is that of retrieving rainfall characteristics in the presence of many other causes of received signal fluctuation, produced by atmospheric scintillation, variations in atmospheric composition (water vapour concentration, cloud water content) or satellite transmission parameters (variations in emitted power, satellite pointing). In order to conduct a feasibility study with such a device, a measurement campaign was carried out over a period of five months close to Paris. The present paper proposes an algorithm based on an artificial neural network, used to identify dry and rainy periods and to model received signal variability resulting from effects not related to rain. When the altitude of the rain layer is taken into account, the rain attenuation can be inverted to obtain the path-averaged rain rate. The rainfall rates obtained from this process are compared with co-located rain gauges and radar measurements taken throughout the full duration of the campaign, and the most significant rainfall events are analysed.

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

NARCIS (Netherlands)

Tote, C.; Patricio, D.; Boogaard, H.L.; Wijngaart, van der R.; Tarnavsky, E.; Funk, 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

Estimating Typhoon Rainfall over Sea from SSM/I Satellite Data Using an Improved Genetic Programming

Science.gov (United States)

Yeh, K.; Wei, H.; Chen, L.; Liu, G.

2010-12-01

Estimating Typhoon Rainfall over Sea from SSM/I Satellite Data Using an Improved Genetic Programming Keh-Chia Yeha, Hsiao-Ping Weia,d, Li Chenb, and Gin-Rong Liuc a Department of Civil Engineering, National Chiao Tung University, Hsinchu, Taiwan, 300, R.O.C. b Department of Civil Engineering and Engineering Informatics, Chung Hua University, Hsinchu, Taiwan, 300, R.O.C. c Center for Space and Remote Sensing Research, National Central University, Tao-Yuan, Taiwan, 320, R.O.C. d National Science and Technology Center for Disaster Reduction, Taipei County, Taiwan, 231, R.O.C. Abstract This paper proposes an improved multi-run genetic programming (GP) and applies it to predict the rainfall using meteorological satellite data. GP is a well-known evolutionary programming and data mining method, used to automatically discover the complex relationships among nonlinear systems. The main advantage of GP is to optimize appropriate types of function and their associated coefficients simultaneously. This study makes an improvement to enhance escape ability from local optimums during the optimization procedure. The GP continuously runs several times by replacing the terminal nodes at the next run with the best solution at the current run. The current novel model improves GP, obtaining a highly nonlinear mathematical equation to estimate the rainfall. In the case study, this improved GP described above combining with SSM/I satellite data is employed to establish a suitable method for estimating rainfall at sea surface during typhoon periods. These estimated rainfalls are then verified with the data from four rainfall stations located at Peng-Jia-Yu, Don-Gji-Dao, Lan-Yu, and Green Island, which are four small islands around Taiwan. From the results, the improved GP can generate sophisticated and accurate nonlinear mathematical equation through two-run learning procedures which outperforms the traditional multiple linear regression, empirical equations and back-propagated network

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.

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.

The Use of Satellite Microwave Rainfall Measurements to Predict Eastern North Pacific Tropical Cyclone Intensity

National Research Council Canada - National Science Library

West, Derek

1998-01-01

.... Relationships between parameters obtained from an operational SSM/I based rainfall measuring algorithm and current intensity and ensuing 12, 24, 36, 48, 60, and 72 hour intensity changes from best...

Accuracy of CHIRPS Satellite-Rainfall Products over Mainland China

Directory of Open Access Journals (Sweden)

Lei Bai

2018-02-01

Full Text Available Precipitation is the main component of global water cycle. At present, satellite quantitative precipitation estimates (QPEs are widely applied in the scientific community. However, the evaluations of satellite QPEs have some limitations in terms of the deficiency in observation, evaluation methodology, the selection of time windows for evaluation and short periods for evaluation. The objective of this work is to make some improvements by evaluating the spatio-temporal pattern of the long-terms Climate Hazard Group InfraRed Precipitation Satellite’s (CHIRPS’s QPEs over mainland China. In this study, we compared the daily precipitation estimates from CHIRPS with 2480 rain gauges across China and gridded observation using several statistical metrics in the long-term period of 1981–2014. The results show that there is significant difference between point evaluation and grid evaluation for CHIRPS. CHIRPS has better performance for a large amount of precipitation than it does for arid and semi-arid land. The change in good performance zones has strong relationship with monsoon’s movement. Therefore, CHIRPS performs better in river basins of southern China and exhibits poor performance in river basins in northwestern and northern China. Moreover, CHIRPS exhibits better in warm season than in Winter, owing to its limited ability to detect snowfall. Nevertheless, CHIRPS is moderately sensitive to the precipitation from typhoon weather systems. The limitations for CHIRPS result from the Tropical Rainfall Measuring Mission (TRMM 3B42 estimates’ accuracy and valid spatial coverage.

Rainfall variability over southern Africa: an overview of current research using satellite and climate model data

Science.gov (United States)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, satellite-derived rainfall data are used as a basis for undertaking model experiments using a state-of-the-art climate model, run at both high and low spatial resolution. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, a brief overview is given of the authors' research to date, pertaining to southern African rainfall. This covers (i) a description of present-day rainfall variability over southern Africa; (ii) a comparison of model simulated daily rainfall with the satellite-derived dataset; (iii) results from sensitivity testing of the model's domain size; and (iv) results from the idealised SST experiments.

From TRMM to GPM: How well can heavy rainfall be detected from space?

Science.gov (United States)

Prakash, Satya; Mitra, Ashis K.; Pai, D. S.; AghaKouchak, Amir

2016-02-01

In this study, we investigate the capabilities of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and the recently released Integrated Multi-satellitE Retrievals for GPM (IMERG) in detecting and estimating heavy rainfall across India. First, the study analyzes TMPA data products over a 17-year period (1998-2014). While TMPA and reference gauge-based observations show similar mean monthly variations of conditional heavy rainfall events, the multi-satellite product systematically overestimates its inter-annual variations. Categorical as well as volumetric skill scores reveal that TMPA over-detects heavy rainfall events (above 75th percentile of reference data), but it shows reasonable performance in capturing the volume of heavy rain across the country. An initial assessment of the GPM-based multi-satellite IMERG precipitation estimates for the southwest monsoon season shows notable improvements over TMPA in capturing heavy rainfall over India. The recently released IMERG shows promising results to help improve modeling of hydrological extremes (e.g., floods and landslides) using satellite observations.

Rainfall measurement using cell phone links: classification of wet and dry periods using geostationary satellites

NARCIS (Netherlands)

van Delden, A.J.; van het Schip, T.I.; Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko; Meirink, J.F.

2017-01-01

Commercial cellular telecommunication networks can be used for rainfall estimation by measur- ing the attenuation of electromagnetic signals transmitted between antennas from microwave links. However, as the received link signal may also decrease during dry periods, a method to separate wet and dry

Adequacy of TRMM satellite rainfall data in driving the SWAT modeling of Tiaoxi catchment (Taihu lake basin, China)

Science.gov (United States)

Li, Dan; Christakos, George; Ding, Xinxin; Wu, Jiaping

2018-01-01

Spatial rainfall data is an essential input to Distributed Hydrological Models (DHM), and a significant contributor to hydrological model uncertainty. Model uncertainty is higher when rain gauges are sparse, as is often the case in practice. Currently, satellite-based precipitation products increasingly provide an alternative means to ground-based rainfall estimates, in which case a rigorous product assessment is required before implementation. Accordingly, the twofold objective of this work paper was the real-world assessment of both (a) the Tropical Rainfall Measuring Mission (TRMM) rainfall product using gauge data, and (b) the TRMM product's role in forcing data for hydrologic simulations in the area of the Tiaoxi catchment (Taihu lake basin, China). The TRMM rainfall products used in this study are the Version-7 real-time 3B42RT and the post-real-time 3B42. It was found that the TRMM rainfall data showed a superior performance at the monthly and annual scales, fitting well with surface observation-based frequency rainfall distributions. The Nash-Sutcliffe Coefficient of Efficiency (NSCE) and the relative bias ratio (BIAS) were used to evaluate hydrologic model performance. The satisfactory performance of the monthly runoff simulations in the Tiaoxi study supports the view that the implementation of real-time 3B42RT allows considerable room for improvement. At the same time, post-real-time 3B42 can be a valuable tool of hydrologic modeling, water balance analysis, and basin water resource management, especially in developing countries or at remote locations in which rainfall gauges are scarce.

Tropical Rainfall Analysis Using TRMM in Combination With Other Satellite Gauge Data: Comparison with Global Precipitation Climatology Project (GPCP) Results

Science.gov (United States)

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

1999-01-01

This paper describes recent results of using Tropical Rainfall Measuring Mission (TRMM) information as the key calibration tool in a merged analysis on a 1 deg x 1 deg latitude/longitude monthly scale based on multiple satellite sources and raingauge analysis. The procedure used to produce the GPCP data set is a stepwise approach which first combines the satellite low-orbit microwave and geosynchronous IR observations into a "multi-satellite" product and than merges that result with the raingauge analysis. Preliminary results produced with the still-stabilizing TRMM algorithms indicate that TRMM shows tighter spatial gradients in tropical rain maxima with higher peaks in the center of the maxima. The TRMM analyses will be used to evaluate the evolution of the 1998 ENSO variations, again in comparison with the GPCP analyses.

Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness

Science.gov (United States)

Kirschbaum, Dalia; Stanley, Thomas

2018-03-01

Determining the time, location, and severity of natural disaster impacts is fundamental to formulating mitigation strategies, appropriate and timely responses, and robust recovery plans. A Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed to indicate potential landslide activity in near real-time. LHASA combines satellite-based precipitation estimates with a landslide susceptibility map derived from information on slope, geology, road networks, fault zones, and forest loss. Precipitation data from the Global Precipitation Measurement (GPM) mission are used to identify rainfall conditions from the past 7 days. When rainfall is considered to be extreme and susceptibility values are moderate to very high, a "nowcast" is issued to indicate the times and places where landslides are more probable. When LHASA nowcasts were evaluated with a Global Landslide Catalog, the probability of detection (POD) ranged from 8% to 60%, depending on the evaluation period, precipitation product used, and the size of the spatial and temporal window considered around each landslide point. Applications of the LHASA system are also discussed, including how LHASA is used to estimate long-term trends in potential landslide activity at a nearly global scale and how it can be used as a tool to support disaster risk assessment. LHASA is intended to provide situational awareness of landslide hazards in near real-time, providing a flexible, open-source framework that can be adapted to other spatial and temporal scales based on data availability.

The all-year rainfall region of South Africa: Satellite rainfall-estimate perspective

CSIR Research Space (South Africa)

Engelbrecht, CJ

2012-09-01

Full Text Available Climate predictability and variability studies over South Africa typically focus on the summer rainfall region and to a lesser extent on the winter rainfall region. The all-year rainfall region of South Africa, a narrow strip located along the Cape...

Coupling rainfall observations and satellite soil moisture for predicting event soil loss in Central Italy

Science.gov (United States)

Todisco, Francesca; Brocca, Luca; Termite, Loris Francesco; Wagner, Wolfgang

2015-04-01

The accuracy of water soil loss prediction depends on the ability of the model to account for effects of the physical phenomena causing the output and the accuracy by which the parameters have been determined. The process based models require considerable effort to obtain appropriate parameter values and their failure to produce better results than achieved using the USLE/RUSLE model, encourages the use of the USLE/RUSLE model in roles of which it was not designed. In particular it is widely used in watershed models even at the event temporal scale. At hillslope scale, spatial variability in soil and vegetation result in spatial variations in soil moisture and consequently in runoff within the area for which soil loss estimation is required, so the modeling approach required to produce those estimates needs to be sensitive to those spatial variations in runoff. Some models include explicit consideration of runoff in determining the erosive stresses but this increases the uncertainty of the prediction due to the difficulty in parameterising the models also because the direct measures of surface runoff are rare. The same remarks are effective also for the USLE/RUSLE models including direct consideration of runoff in the erosivity factor (i.e. USLE-M by Kinnell and Risse, 1998, and USLE-MM by Bagarello et al., 2008). Moreover actually most of the rainfall-runoff models are based on the knowledge of the pre-event soil moisture that is a fundamental variable in the rainfall-runoff transformation. In addiction soil moisture is a readily available datum being possible to have easily direct pre-event measures of soil moisture using in situ sensors or satellite observations at larger spatial scale; it is also possible to derive the antecedent water content with soil moisture simulation models. The attempt made in the study is to use the pre-event soil moisture to account for the spatial variation in runoff within the area for which the soil loss estimates are required. More

Evaluation of sub daily satellite rainfall estimates through flash flood modelling in the Lower Middle Zambezi Basin

Directory of Open Access Journals (Sweden)

T. Matingo

2018-05-01

Full Text Available Flash floods are experienced almost annually in the ungauged Mbire District of the Middle Zambezi Basin. Studies related to hydrological modelling (rainfall-runoff and flood forecasting require major inputs such as precipitation which, due to shortage of observed data, are increasingly using indirect methods for estimating precipitation. This study therefore evaluated performance of CMORPH and TRMM satellite rainfall estimates (SREs for 30 min, 1 h, 3 h and daily intensities through hydrologic and flash flood modelling in the Lower Middle Zambezi Basin for the period 2013–2016. On a daily timestep, uncorrected CMORPH and TRMM show Probability of Detection (POD of 61 and 59 %, respectively, when compared to rain gauge observations. The best performance using Correlation Coefficient (CC was 70 and 60 % on daily timesteps for CMORPH and TRMM, respectively. The best RMSE for CMORPH was 0.81 % for 30 min timestep and for TRMM was 2, 11 % on 3 h timestep. For the year 2014 to 2015, the HEC-HMS (Hydrological Engineering Centre-Hydrological Modelling System daily model calibration Nash Sutcliffe efficiency (NSE for Musengezi sub catchment was 59 % whilst for Angwa it was 55 %. Angwa sub-catchment daily NSE results for the period 2015–2016 was 61 %. HEC-RAS flash flood modeling at 100, 50 and 25 year return periods for Angwa sub catchment, inundated 811 and 867 ha for TRMM rainfall simulated discharge at 3 h and daily timesteps, respectively. For CMORPH generated rainfall, the inundation was 818, 876, 890 and 891 ha at daily, 3 h, 1 h and 30 min timesteps. The 30 min time step for CMORPH effectively captures flash floods with the measure of agreement between simulated flood extent and ground control points of 69 %. For TRMM, the 3 h timestep effectively captures flash floods with coefficient of 67 %. The study therefore concludes that satellite products are most effective in capturing localized

Effect of Bias Correction of Satellite-Rainfall Estimates on Runoff Simulations at the Source of the Upper Blue Nile

Directory of Open Access Journals (Sweden)

Emad Habib

2014-07-01

Full Text Available Results of numerous evaluation studies indicated that satellite-rainfall products are contaminated with significant systematic and random errors. Therefore, such products may require refinement and correction before being used for hydrologic applications. In the present study, we explore a rainfall-runoff modeling application using the Climate Prediction Center-MORPHing (CMORPH satellite rainfall product. The study area is the Gilgel Abbay catchment situated at the source basin of the Upper Blue Nile basin in Ethiopia, Eastern Africa. Rain gauge networks in such area are typically sparse. We examine different bias correction schemes applied locally to the CMORPH product. These schemes vary in the degree to which spatial and temporal variability in the CMORPH bias fields are accounted for. Three schemes are tested: space and time-invariant, time-variant and spatially invariant, and space and time variant. Bias-corrected CMORPH products were used to calibrate and drive the Hydrologiska Byråns Vattenbalansavdelning (HBV rainfall-runoff model. Applying the space and time-fixed bias correction scheme resulted in slight improvement of the CMORPH-driven runoff simulations, but in some instances caused deterioration. Accounting for temporal variation in the bias reduced the rainfall bias by up to 50%. Additional improvements were observed when both the spatial and temporal variability in the bias was accounted for. The rainfall bias was found to have a pronounced effect on model calibration. The calibrated model parameters changed significantly when using rainfall input from gauges alone, uncorrected, and bias-corrected CMORPH estimates. Changes of up to 81% were obtained for model parameters controlling the stream flow volume.

Rainfall simulators - innovations seeking rainfall uniformity and automatic flow rate measurements

Science.gov (United States)

Bauer, Miroslav; Kavka, Petr; Strouhal, Luděk; Dostál, Tomáš; Krása, Josef

2016-04-01

Field rainfall simulators are used worldwide for many experimental purposes, such as runoff generation and soil erosion research. At CTU in Prague a laboratory simulator with swinging nozzles VeeJet has been operated since 2001. Since 2012 an additional terrain simulator is being used with 4 fixed FullJet 40WSQ nozzles with 2,4 m spacing and operating over two simultaneously sprinkled experimental plots sizing 8x2 and 1x1 m. In parallel to other research projects a specific problem was solved: improving rainfall spatial uniformity and overall intensity and surface runoff measurements. These fundamental variables significantly affect investigated processes as well as resulting water balance of the plot, therefore they need to be determined as accurately as possible. Although the original nozzles setting produced (commonly used) Christiansen uniformity index CU over 80 %, detailed measurements proved this index insufficient and showed many unrequired rainfall extremes within the plot. Moreover the number of rainfall intensity scenarios was limited and some of them required problematic multi-pressure operation of the water distribution system. Therefore the simulator was subjected to many substantial changes in 2015. Innovations ranged from pump intensification to control unit upgrade. As essential change was considered increase in number of nozzles to 9 in total and reducing their spacing to 1,2 m. However new uniformity measurements did not bring any significant improvement. Tested scenarios showed equal standard deviations of interpolated intensity rasters and equal or slightly lower CU index. Imperfections of sprinkling nozzles were found to be the limiting factor. Still many other benefits were brought with the new setup. Whole experimental plot 10x2 m is better covered with the rainfall while the water consumption is retained. Nozzles are triggered in triplets, which enables more rainfall intensity scenarios. Water distribution system is more stable due to

Topography and Data Mining Based Methods for Improving Satellite Precipitation in Mountainous Areas of China

Directory of Open Access Journals (Sweden)

Ting Xia

2015-07-01

Full Text Available Topography is a significant factor influencing the spatial distribution of precipitation. This study developed a new methodology to evaluate and calibrate the Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA products by merging geographic and topographic information. In the proposed method, firstly, the consistency rule was introduced to evaluate the fitness of satellite rainfall with measurements on the grids with and without ground gauges. Secondly, in order to improve the consistency rate of satellite rainfall, genetic programming was introduced to mine the relationship between the gauge rainfall and location, elevation and TMPA rainfall. The proof experiment and analysis for the mean annual satellite precipitation from 2001–2012, 3B43 (V7 of TMPA rainfall product, was carried out in eight mountainous areas of China. The result shows that the proposed method is significant and efficient both for the assessment and improvement of satellite precipitation. It is found that the satellite rainfall consistency rates in the gauged and ungauged grids are different in the study area. In addition, the mined correlation of location-elevation-TMPA rainfall can noticeably improve the satellite precipitation, both in the context of the new criterion of the consistency rate and the existing criteria such as Bias and RMSD. The proposed method is also efficient for correcting the monthly and mean monthly rainfall of 3B43 and 3B42RT.

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.

Evaluation of Version-7 TRMM Multi-Satellite Precipitation Analysis Product during the Beijing Extreme Heavy Rainfall Event of 21 July 2012

Directory of Open Access Journals (Sweden)

Yong Huang

2013-12-01

Full Text Available The latest Version-7 (V7 Tropical Rainfall Measuring Mission (TRMM Multi-satellite Precipitation Analysis (TMPA products were released by the National Aeronautics and Space Administration (NASA in December of 2012. Their performance on different climatology, locations, and precipitation types is of great interest to the satellite-based precipitation community. This paper presents a study of TMPA precipitation products (3B42RT and 3B42V7 for an extreme precipitation event in Beijing and its adjacent regions (from 00:00 UTC 21 July 2012 to 00:00 UTC 22 July 2012. Measurements from a dense rain gauge network were used as the ground truth to evaluate the latest TMPA products. Results are summarized as follows. Compared to rain gauge measurements, both 3B42RT and 3B42V7 generally captured the rainfall spatial and temporal pattern, having a moderate spatial correlation coefficient (CC, 0.6 and high CC values (0.88 over the broader Hebei, Beijing and Tianjin (HBT regions, but the rainfall peak is 6 h ahead of gauge observations. Overall, 3B42RT showed higher estimation than 3B42V7 over both HBT and Beijing. At the storm center, both 3B42RT and 3B42V7 presented a relatively large deviation from the temporal variation of rainfall and underestimated the storm by 29.02% and 36.07%, respectively. The current study suggests that the latest TMPA products still have limitations in terms of resolution and accuracy, especially for this type of extreme event within a latitude area on the edge of coverage of TRMM precipitation radar and microwave imager. Therefore, TMPA users should be cautious when 3B42RT and 3B42V7 are used to model, monitor, and forecast both flooding hazards in the Beijing urban area and landslides in the mountainous west and north of Beijing.

Propagation of Satelite Rainfall Products uncertainties in hydrological applications : Examples in West-Africa in the framework of the Megha-Tropiques Satellite Mission

Science.gov (United States)

Casse, C.; Gosset, M.; Peugeot, C.; Boone, A.; Pedinotti, V.

2013-12-01

The use of satellite based rainfall in research or operational Hydrological application is becoming more and more frequent. This is specially true in the Tropics where ground based gauge (or radar) network are generally scarce and often degrading. Member of the GPM constellation, the new French-Indian satellite Mission Megha-Tropiques (MT) dedicated to the water and energy budget in the tropical atmosphere contributes to a better monitoring of rainfall in the inter-tropical zone. As part of this mission, research is developed on the use of MT rainfall products for hydrological research or operational application such as flood monitoring. A key issue for such applications is how to account for rainfall products biases and uncertainties, and how to propagate them in the end user models ? Another important question is how to choose the best space-time resolution for the rainfall forcing, given that both model performances and rain-product uncertainties are resolution dependent. This talk will present on going investigations and perspectives on this subject, with examples from the Megha_tropiques Ground validation sites in West Africa. The CNRM model Surfex-ISBA/TRIP has been set up to simulate the hydrological behavior of the Niger River. This modeling set up is being used to study the predictability of Niger Floods events in the city of Niamey and the performances of satellite rainfall products as forcing for such predictions. One of the interesting feature of the Niger outflow in Niamey is its double peak : a first peak attributed to 'local' rainfall falling in small to medium size basins situated in the region of Niamey, and a second peak linked to the rainfall falling in the upper par of the river, and slowly propagating through the river towards Niamey. The performances of rainfall products are found to differ between the wetter/upper part of the basin, and the local/sahelian areas. Both academic tests with artificially biased or 'perturbed' rainfield and actual

Large-scale assessment of soil erosion in Africa: satellites help to jointly account for dynamic rainfall and vegetation cover

Science.gov (United States)

Vrieling, Anton; Hoedjes, Joost C. B.; van der Velde, Marijn

2015-04-01

Efforts to map and monitor soil erosion need to account for the erratic nature of the soil erosion process. Soil erosion by water occurs on sloped terrain when erosive rainfall and consequent surface runoff impact soils that are not well-protected by vegetation or other soil protective measures. Both rainfall erosivity and vegetation cover are highly variable through space and time. Due to data paucity and the relative ease of spatially overlaying geographical data layers into existing models like USLE (Universal Soil Loss Equation), many studies and mapping efforts merely use average annual values for erosivity and vegetation cover as input. We first show that rainfall erosivity can be estimated from satellite precipitation data. We obtained average annual erosivity estimates from 15 yr of 3-hourly TRMM Multi-satellite Precipitation Analysis (TMPA) data (1998-2012) using intensity-erosivity relationships. Our estimates showed a positive correlation (r = 0.84) with long-term annual erosivity values of 37 stations obtained from literature. Using these TMPA erosivity retrievals, we demonstrate the large interannual variability, with maximum annual erosivity often exceeding two to three times the mean value, especially in semi-arid areas. We then calculate erosivity at a 10-daily time-step and combine this with vegetation cover development for selected locations in Africa using NDVI - normalized difference vegetation index - time series from SPOT VEGETATION. Although we do not integrate the data at this point, the joint analysis of both variables stresses the need for joint accounting for erosivity and vegetation cover for large-scale erosion assessment and monitoring.

The Impact of Amazonian Deforestation on Dry-Season Rainfall

Science.gov (United States)

Negri, Andrew J.; Adler, Robert F.; Xu, Li-Ming; Surratt, Jason; Starr, David OC. (Technical Monitor)

2002-01-01

Many modeling studies have concluded that widespread deforestation of Amazonia would lead to decreased rainfall. We analyze geosynchronous infrared satellite data with respect percent cloudiness, and analyze rain estimates from microwave sensors aboard the Tropical Rainfall Measuring Mission satellite. We conclude that in the dry-season, when the effects of the surface are not overwhelmed by synoptic-scale weather disturbances, deep convective cloudiness, as well as rainfall occurrence, all increase over the deforested and non-forested (savanna) regions. This is in response to a local circulation initiated by the differential heating of the region's varying forestation. Analysis of the diurnal cycle of cloudiness reveals a shift toward afternoon hours in the deforested and savanna regions, compared to the forested regions. Analysis of 14 years of data from the Special Sensor Microwave/Imager data revealed that only in August did rainfall amounts increase over the deforested region.

Validation of a global satellite rainfall product for real time monitoring of meteorological extremes

Science.gov (United States)

Cánovas-García, Fulgencio; García-Galiano, Sandra; Karbalaee, Negar

2017-10-01

The real time monitoring of storms is important for the management and prevention of flood risks. However, in the southeast of Spain, it seems that the density of the rain gauge network may not be sufficient to adequately characterize the rainfall spatial distribution or the high rainfall intensities that are reached during storms. Satellite precipitation products such as PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Cloud Classification System) could be used to complement the automatic rain gauge networks and so help solve this problem. However, the PERSIANN-CCS product has only recently become available, so its operational validity for areas such as south-eastern Spain is not yet known. In this work, a methodology for the hourly validation of PERSIANN-CCS is presented. We used the rain gauge stations of the SIAM (Sistema de Información Agraria de Murcia) network to study three storms with a very high return period. These storms hit the east and southeast of the Iberian Peninsula and resulted in the loss of human life, major damage to agricultural crops and a strong impact on many different types of infrastructure. The study area is the province of Murcia (Region of Murcia), located in the southeast of the Iberian Peninsula, covering an area of more than 11,000 km2 and with a population of almost 1.5 million. In order to validate the PERSIANN-CCS product for these three storms, contrasts were made with the hyetographs registered by the automatic rain gauges, analyzing statistics such as bias, mean square difference and Pearson's correlation coefficient. Although in some cases the temporal distribution of rainfall was well captured by PERSIANN-CCS, in several rain gauges high intensities were not properly represented. The differences were strongly correlated with the rain gauge precipitation, but not with satellite-obtained rainfall. The main conclusion concerns the need for specific local calibration

Rainfall measurement based on in-situ storm drainage flow sensors

DEFF Research Database (Denmark)

Ahm, Malte; Rasmussen, Michael Robdrup

2017-01-01

Data for adjustment of weather radar rainfall estimations are mostly obtained from rain gauge observations. However, the density of rain gauges is often very low. Yet in many urban catchments, runoff sensors are typically available which can measure the rainfall indirectly. By utilising these sen......Data for adjustment of weather radar rainfall estimations are mostly obtained from rain gauge observations. However, the density of rain gauges is often very low. Yet in many urban catchments, runoff sensors are typically available which can measure the rainfall indirectly. By utilising...... these sensors, it may be possible to improve the ground rainfall estimate, and thereby improve the quantitative precipitation estimation from weather radars for urban drainage applications. To test the hypothesis, this paper presents a rainfall measurement method based on flow rate measurements from well......-defined urban surfaces. This principle was used to design a runoff measurement system in a parking structure in Aalborg, Denmark, where it was evaluated against rain gauges. The measurements show that runoff measurements from well-defined urban surfaces perform just as well as rain gauges. This opens up...

Evaluating the MSG satellite Multi-Sensor Precipitation Estimate for extreme rainfall monitoring over northern Tunisia

Directory of Open Access Journals (Sweden)

Saoussen Dhib

2017-06-01

Full Text Available Knowledge and evaluation of extreme precipitation is important for water resources and flood risk management, soil and land degradation, and other environmental issues. Due to the high potential threat to local infrastructure, such as buildings, roads and power supplies, heavy precipitation can have an important social and economic impact on society. At present, satellite derived precipitation estimates are becoming more readily available. This paper aims to investigate the potential use of the Meteosat Second Generation (MSG Multi-Sensor Precipitation Estimate (MPE for extreme rainfall assessment in Tunisia. The MSGMPE data combine microwave rain rate estimations with SEVIRI thermal infrared channel data, using an EUMETSAT production chain in near real time mode. The MPE data can therefore be used in a now-casting mode, and are potentially useful for extreme weather early warning and monitoring. Daily precipitation observed across an in situ gauge network in the north of Tunisia were used during the period 2007–2009 for validation of the MPE extreme event data. As a first test of the MSGMPE product's performance, very light to moderate rainfall classes, occurring between January and October 2007, were evaluated. Extreme rainfall events were then selected, using a threshold criterion for large rainfall depth (>50 mm/day occurring at least at one ground station. Spatial interpolation methods were applied to generate rainfall maps for the drier summer season (from May to October and the wet winter season (from November to April. Interpolated gauge rainfall maps were then compared to MSGMPE data available from the EUMETSAT UMARF archive or from the GEONETCast direct dissemination system. The summation of the MPE data at 5 and/or 15 min time intervals over a 24 h period, provided a basis for comparison. The MSGMPE product was not very effective in the detection of very light and light rain events. Better results were obtained for the slightly

Hydrological Evaluation of TRMM Rainfall over the Upper Senegal River Basin

Directory of Open Access Journals (Sweden)

Ansoumana Bodian

2016-04-01

Full Text Available The availability of climatic data, especially on a daily time step, has become very rare in West Africa over the last few years due to the high costs of climate data monitoring. This scarcity of climatic data is a huge obstacle to conduct hydrological studies over some watersheds. In this context, our study aimed to evaluate the capacity of Tropical Rainfall Measuring Mission (TRMM satellite data to simulate the observed runoffs over the Bafing (the main important tributary of the Senegal River before their potential integration in hydrological studies. The conceptual hydrological model GR4J (modèle du Génie Rural (Agricultural Engineering Model à 4 paramètres Journalier (4 parameters Daily has been used, calibrated and validated over the 1961–1997 period with rainfall and Potential Evapotranspiration (PET as inputs. Then, the parameters that best reflect the rainfall-runoff relation, obtained during the cross-calibration-validation phase, were used to simulate runoff over the 1998–2004 period using observed and TRMM rainfalls. The findings of this study show that there is a high consistency between satellite-based estimates and ground-based observations of rainfall. Over the 1998–2004 simulation period, the two rainfall data series show quite satisfactorily results. The output hydrographs from satellite-based estimates and ground-based observations of rainfall coincide quite well with the shape of observed hydrographs with Nash-Sutcliffe Efficiency coefficient (NSE of 0.88 and 0.80 for observed rainfalls and TRMM rainfalls, respectively.

Rainfall recharge estimation on a nation-wide scale using satellite information in New Zealand

Science.gov (United States)

Westerhoff, Rogier; White, Paul; Moore, Catherine

2015-04-01

Models of rainfall recharge to groundwater are challenged by the need to combine uncertain estimates of rainfall, evapotranspiration, terrain slope, and unsaturated zone parameters (e.g., soil drainage and hydraulic conductivity of the subsurface). Therefore, rainfall recharge is easiest to estimate on a local scale in well-drained plains, where it is known that rainfall directly recharges groundwater. In New Zealand, this simplified approach works in the policy framework of regional councils, who manage water allocation at the aquifer and sub-catchment scales. However, a consistent overview of rainfall recharge is difficult to obtain at catchment and national scale: in addition to data uncertainties, data formats are inconsistent between catchments; the density of ground observations, where these exist, differs across regions; each region typically uses different local models for estimating recharge components; and different methods and ground observations are used for calibration and validation of these models. The research described in this paper therefore presents a nation-wide approach to estimate rainfall recharge in New Zealand. The method used is a soil water balance approach, with input data from national rainfall and soil and geology databases. Satellite data (i.e., evapotranspiration, soil moisture, and terrain) aid in the improved calculation of rainfall recharge, especially in data-sparse areas. A first version of the model has been implemented on a 1 km x 1 km and monthly scale between 2000 and 2013. A further version will include a quantification of recharge estimate uncertainty: with both "top down" input error propagation methods and catchment-wide "bottom up" assessments of integrated uncertainty being adopted. Using one nation-wide methodology opens up new possibilities: it can, for example, help in more consistent estimation of water budgets, groundwater fluxes, or other hydrological parameters. Since recharge is estimated for the entire land

Assessment of the use of remotely sensed rainfall products for runoff ...

African Journals Online (AJOL)

The main objective of this research is to compare the performance of SWAT model using rainfall input data from remotely sensed and ground measured data for Gilgel abbay catchment. Based on the results obtained, it can be said that SWAT model yields good results for the satellite rainfall input data when compared to in ...

Development of Radar-Satellite Blended QPF (Quantitative Precipitation Forecast) Technique for heavy rainfall

Science.gov (United States)

Jang, Sangmin; Yoon, Sunkwon; Rhee, Jinyoung; Park, Kyungwon

2016-04-01

Due to the recent extreme weather and climate change, a frequency and size of localized heavy rainfall increases and it may bring various hazards including sediment-related disasters, flooding and inundation. To prevent and mitigate damage from such disasters, very short range forecasting and nowcasting of precipitation amounts are very important. Weather radar data very useful in monitoring and forecasting because weather radar has high resolution in spatial and temporal. Generally, extrapolation based on the motion vector is the best method of precipitation forecasting using radar rainfall data for a time frame within a few hours from the present. However, there is a need for improvement due to the radar rainfall being less accurate than rain-gauge on surface. To improve the radar rainfall and to take advantage of the COMS (Communication, Ocean and Meteorological Satellite) data, a technique to blend the different data types for very short range forecasting purposes was developed in the present study. The motion vector of precipitation systems are estimated using 1.5km CAPPI (Constant Altitude Plan Position Indicator) reflectivity by pattern matching method, which indicates the systems' direction and speed of movement and blended radar-COMS rain field is used for initial data. Since the original horizontal resolution of COMS is 4 km while that of radar is about 1 km, spatial downscaling technique is used to downscale the COMS data from 4 to 1 km pixels in order to match with the radar data. The accuracies of rainfall forecasting data were verified utilizing AWS (Automatic Weather System) observed data for an extreme rainfall occurred in the southern part of Korean Peninsula on 25 August 2014. The results of this study will be used as input data for an urban stream real-time flood early warning system and a prediction model of landslide. Acknowledgement This research was supported by a grant (13SCIPS04) from Smart Civil Infrastructure Research Program funded by

Validation of the TRMM Multi Satellite Rainfall Product 3B42 and estimation of scavenging coefficients for (131)I and (137)Cs using TRMM 3B42 rainfall data.

Science.gov (United States)

Shrivastava, R; Dash, S K; Hegde, M N; Pradeepkumar, K S; Sharma, D N

2014-12-01

The TRMM rainfall product 3B42 is compared with rain gauge observations for Kaiga, India on monthly and seasonal time scales. This comparison is carried out for the years 2004-2007 spanning four monsoon seasons. A good correlation is obtained between the two data sets however; magnitude wise, the cumulative precipitation of the satellite product on monthly and seasonal time scales is deficient by almost 33-40% as compared to the rain gauge data. The satellite product is also compared with APHRODITE's Monsoon Asia data set on the same time scales. This comparison indicates a much better agreement since both these data sets represent an average precipitation over the same area. The scavenging coefficients for (131)I and (137)Cs are estimated using TRMM 3B42, rain gauge and APHRODITE data. The values obtained using TRMM 3B42 rainfall data compare very well with those obtained using rain gauge and APHRODITE data. Copyright © 2014 Elsevier Ltd. All rights reserved.

Critical Phenomena of Rainfall in Ecuador

Science.gov (United States)

Serrano, Sh.; Vasquez, N.; Jacome, P.; Basile, L.

2014-02-01

Self-organized criticality (SOC) is characterized by a power law behavior over complex systems like earthquakes and avalanches. We study rainfall using data of one day, 3 hours and 10 min temporal resolution from INAMHI (Instituto Nacional de Meteorologia e Hidrologia) station at Izobamba, DMQ (Metropolitan District of Quito), satellite data over Ecuador from Tropical Rainfall Measure Mission (TRMM,) and REMMAQ (Red Metropolitana de Monitoreo Atmosferico de Quito) meteorological stations over, respectively. Our results show a power law behavior of the number of rain events versus mm of rainfall measured for the high resolution case (10 min), and as the resolution decreases this behavior gets lost. This statistical property is the fingerprint of a self-organized critical process (Peter and Christensen, 2002) and may serve as a benchmark for models of precipitation based in phase transitions between water vapor and precipitation (Peter and Neeling, 2006).

Assessment of global precipitation measurement satellite products over Saudi Arabia

Science.gov (United States)

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

2018-04-01

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

Performance of bias corrected MPEG rainfall estimate for rainfall-runoff simulation in the upper Blue Nile Basin, Ethiopia

Science.gov (United States)

Worqlul, Abeyou W.; Ayana, Essayas K.; Maathuis, Ben H. P.; MacAlister, Charlotte; Philpot, William D.; Osorio Leyton, Javier M.; Steenhuis, Tammo S.

2018-01-01

In many developing countries and remote areas of important ecosystems, good quality precipitation data are neither available nor readily accessible. Satellite observations and processing algorithms are being extensively used to produce satellite rainfall products (SREs). Nevertheless, these products are prone to systematic errors and need extensive validation before to be usable for streamflow simulations. In this study, we investigated and corrected the bias of Multi-Sensor Precipitation Estimate-Geostationary (MPEG) data. The corrected MPEG dataset was used as input to a semi-distributed hydrological model Hydrologiska Byråns Vattenbalansavdelning (HBV) for simulation of discharge of the Gilgel Abay and Gumara watersheds in the Upper Blue Nile basin, Ethiopia. The result indicated that the MPEG satellite rainfall captured 81% and 78% of the gauged rainfall variability with a consistent bias of underestimating the gauged rainfall by 60%. A linear bias correction applied significantly reduced the bias while maintaining the coefficient of correlation. The simulated flow using bias corrected MPEG SRE resulted in a simulated flow comparable to the gauge rainfall for both watersheds. The study indicated the potential of MPEG SRE in water budget studies after applying a linear bias correction.

Analytical solutions to sampling effects in drop size distribution measurements during stationary rainfall: Estimation of bulk rainfall variables

NARCIS (Netherlands)

Uijlenhoet, R.; Porrà, J.M.; Sempere Torres, D.; Creutin, J.D.

2006-01-01

A stochastic model of the microstructure of rainfall is used to derive explicit expressions for the magnitude of the sampling fluctuations in rainfall properties estimated from raindrop size measurements in stationary rainfall. The model is a marked point process, in which the points represent the

The Impact of a Amazonian Deforestation on Dry-Season Rainfall

Science.gov (United States)

Negri, Andrew J.; Adler, Robert F.; Xu, Liming; Surratt, Jason

2003-01-01

Many modeling studies have concluded that widespread deforestation of Amazonia would lead to decreased rainfall. We analyze geosynchronous infrared satellite data with respect to percent cloudiness, and analyze rain estimates from microwave sensors aboard the Tropical Rainfall Measuring Mission satellite. We conclude that in the dry-season, when the effects of the surface are not overwhelmed by synoptic-scale weather disturbances, shallow cumulus cloudiness, deep convective cloudiness, and rainfall occurrence all are larger over the deforested and non-forested (savanna) regions than over areas of dense jungle. This difference is in response to a local circulation initiated by the differential heating of the region s varying forestation. Analysis of the diurnal cycle of cloudiness reveals a shift in the onset of convection toward afternoon hours in the deforested and towards the morning hours in the savanna regions when compared to the neighboring forested regions. Analysis of 14 years of monthly estimates from the Special Sensor Microwave/Imager data revealed that in only in August was there a pattern of higher monthly rainfall amounts over the deforested region.

Predicting extreme rainfall events over Jeddah, Saudi Arabia: Impact of data assimilation with conventional and satellite observations

KAUST Repository

Viswanadhapalli, Yesubabu

2015-08-20

The impact of variational data assimilation for predicting two heavy rainfall events that caused devastating floods in Jeddah, Saudi Arabia is studied using the Weather Research and Forecasting (WRF) model. On 25 November 2009 and 26 January 2011, the city was deluged with more than double the annual rainfall amount caused by convective storms. We used a high resolution, two-way nested domain WRF model to simulate the two rainfall episodes. Simulations include control runs initialized with National Center for Environmental Prediction (NCEP) Global Forecasting System (GFS) data and 3-Dimensional Variational (3DVAR) data assimilation experiments conducted by assimilating NCEP prepbufr and radiance observations. Observations from Automated Weather Stations (AWS), synoptic charts, radar reflectivity and satellite pictures from the Presidency of Meteorology and Environment (PME), Jeddah, Saudi Arabia are used to assess the forecasting results. To evaluate the impact of the different assimilated observational datasets on the simulation of the major flooding event of 2009, we conducted 3DVAR experiments assimilating individual sources and a combination of all data sets. Results suggest that while the control run had a tendency to predict the storm earlier than observed, the assimilation of profile observations greatly improved the model\\'s thermodynamic structure and lead to better representation of simulated rainfall both in timing and amount. The experiment with assimilation of all available observations compared best with observed rainfall in terms of timing of the storm and rainfall distribution, demonstrating the importance of assimilating different types of observations. Retrospective experiments with and without data assimilation, for three different model lead times (48, 72 and 96-h), were performed to examine the skill of WRF model to predict the heavy rainfall events. Quantitative rainfall analysis of these simulations suggests that 48-h lead time runs with

Engineering of an Extreme Rainfall Detection System using Grid Computing

Directory of Open Access Journals (Sweden)

Olivier Terzo

2012-10-01

Full Text Available This paper describes a new approach for intensive rainfall data analysis. ITHACA's Extreme Rainfall Detection System (ERDS is conceived to provide near real-time alerts related to potential exceptional rainfalls worldwide, which can be used by WFP or other humanitarian assistance organizations to evaluate the event and understand the potentially floodable areas where their assistance is needed. This system is based on precipitation analysis and it uses rainfall data from satellite at worldwide extent. This project uses the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis dataset, a NASA-delivered near real-time product for current rainfall condition monitoring over the world. Considering the great deal of data to process, this paper presents an architectural solution based on Grid Computing techniques. Our focus is on the advantages of using a distributed architecture in terms of performances for this specific purpose.

Extreme flood event analysis in Indonesia based on rainfall intensity and recharge capacity

Science.gov (United States)

Narulita, Ida; Ningrum, Widya

2018-02-01

Indonesia is very vulnerable to flood disaster because it has high rainfall events throughout the year. Flood is categorized as the most important hazard disaster because it is causing social, economic and human losses. The purpose of this study is to analyze extreme flood event based on satellite rainfall dataset to understand the rainfall characteristic (rainfall intensity, rainfall pattern, etc.) that happened before flood disaster in the area for monsoonal, equatorial and local rainfall types. Recharge capacity will be analyzed using land cover and soil distribution. The data used in this study are CHIRPS rainfall satellite data on 0.05 ° spatial resolution and daily temporal resolution, and GSMap satellite rainfall dataset operated by JAXA on 1-hour temporal resolution and 0.1 ° spatial resolution, land use and soil distribution map for recharge capacity analysis. The rainfall characteristic before flooding, and recharge capacity analysis are expected to become the important information for flood mitigation in Indonesia.

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.

TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms

Directory of Open Access Journals (Sweden)

Patrick Marina

2017-01-01

Full Text Available On-site measurements from rain gauge provide important information for the design, construction, and operation of water resources engineering projects, groundwater potentials, and the water supply and irrigation systems. A dense gauging network is needed to accurately characterize the variation of rainfall over a region, unfitting for conditions with limited networks, such as in Sarawak, Malaysia. Hence, satellite-based algorithm estimates are introduced as an innovative solution to these challenges. With accessibility to dataset retrievals from public domain websites, it has become a useful source to measure rainfall for a wider coverage area at finer temporal resolution. This paper aims to investigate the rainfall estimates prepared by Tropical Rainfall Measuring Mission (TRMM to explain whether it is suitable to represent the distribution of extreme rainfall in Sungai Sarawak Basin. Based on the findings, more uniform correlations for the investigated storms can be observed for low to medium altitude (>40 MASL. It is found for the investigated events of Jan 05-11, 2009: the normalized root mean square error (NRMSE = 36.7 %; and good correlation (CC = 0.9. These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall.

Real-Time Rain Rate Evaluation via Satellite Downlink Signal Attenuation Measurement.

Science.gov (United States)

Giannetti, Filippo; Reggiannini, Ruggero; Moretti, Marco; Adirosi, Elisa; Baldini, Luca; Facheris, Luca; Antonini, Andrea; Melani, Samantha; Bacci, Giacomo; Petrolino, Antonio; Vaccaro, Attilio

2017-08-12

We present the NEFOCAST project (named by the contraction of "Nefele", which is the Italian spelling for the mythological cloud nymph Nephele, and "forecast"), funded by the Tuscany Region, about the feasibility of a system for the detection and monitoring of precipitation fields over the regional territory based on the use of a widespread network of new-generation Eutelsat "SmartLNB" (smart low-noise block converter) domestic terminals. Though primarily intended for interactive satellite services, these devices can also be used as weather sensors, as they have the capability of measuring the rain-induced attenuation incurred by the downlink signal and relaying it on an auxiliary return channel. We illustrate the NEFOCAST system architecture, consisting of the network of ground sensor terminals, the space segment, and the service center, which has the task of processing the information relayed by the terminals for generating rain field maps. We discuss a few methods that allow the conversion of a rain attenuation measurement into an instantaneous rainfall rate. Specifically, we discuss an exponential model relating the specific rain attenuation to the rainfall rate, whose coefficients were obtained from extensive experimental data. The above model permits the inferring of the rainfall rate from the total signal attenuation provided by the SmartLNB and from the link geometry knowledge. Some preliminary results obtained from a SmartLNB installed in Pisa are presented and compared with the output of a conventional tipping bucket rain gauge. It is shown that the NEFOCAST sensor is able to track the fast-varying rainfall rate accurately with no delay, as opposed to a conventional gauge.

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

Science.gov (United States)

Wright, Daniel B.; Mantilla, Ricardo; Peters-Lidard, Christa D.

2018-01-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, RainyDay can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, RainyDay can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. RainyDay can be useful for hazard modeling under nonstationary conditions. PMID:29657544

TRMM and Other Sources Rainfall Product (TRMM Product 3B43) V7

Data.gov (United States)

National Aeronautics and Space Administration — The Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its...

Comparison of Two Methods for Estimating the Sampling-Related Uncertainty of Satellite Rainfall Averages Based on a Large Radar Data Set

Science.gov (United States)

Lau, William K. M. (Technical Monitor); Bell, Thomas L.; Steiner, Matthias; Zhang, Yu; Wood, Eric F.

2002-01-01

The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.

Rainfall measurement using cell phone links

NARCIS (Netherlands)

Schip, van het T.I.; Overeem, A.; Leijnse, H.; Uijlenhoet, R.; Meirink, J.F.; Delden, van A.J.

2017-01-01

Commercial cellular telecommunication networks can be used for rainfall estimation by measuring the attenuation of electromagnetic signals transmitted between antennas from microwave links. However, as the received link signal may also decrease during dry periods, a method to separate wet and dry

Rainfall assimilation in RAMS by means of the Kuo parameterisation inversion: method and preliminary results

Science.gov (United States)

Orlandi, A.; Ortolani, A.; Meneguzzo, F.; Levizzani, V.; Torricella, F.; Turk, F. J.

2004-03-01

In order to improve high-resolution forecasts, a specific method for assimilating rainfall rates into the Regional Atmospheric Modelling System model has been developed. It is based on the inversion of the Kuo convective parameterisation scheme. A nudging technique is applied to 'gently' increase with time the weight of the estimated precipitation in the assimilation process. A rough but manageable technique is explained to estimate the partition of convective precipitation from stratiform one, without requiring any ancillary measurement. The method is general purpose, but it is tuned for geostationary satellite rainfall estimation assimilation. Preliminary results are presented and discussed, both through totally simulated experiments and through experiments assimilating real satellite-based precipitation observations. For every case study, Rainfall data are computed with a rapid update satellite precipitation estimation algorithm based on IR and MW satellite observations. This research was carried out in the framework of the EURAINSAT project (an EC research project co-funded by the Energy, Environment and Sustainable Development Programme within the topic 'Development of generic Earth observation technologies', Contract number EVG1-2000-00030).

Transitioning from CRD to CDRD in Bayesian retrieval of rainfall from satellite passive microwave measurements: Part 3 – Identification of optimal meteorological tags

Directory of Open Access Journals (Sweden)

E. A. Smith

2013-05-01

Full Text Available In the first two parts of this study we have presented a performance analysis of our new Cloud Dynamics and Radiation Database (CDRD satellite precipitation retrieval algorithm on various convective and stratiform rainfall case studies verified with precision radar ground truth data, and an exposition of the algorithm's detailed design in conjunction with a proof-of-concept analysis vis-à-vis its theoretical underpinnings. In this third part of the study, we present the underlying analysis used to identify what we refer to as the optimal metrological and geophysical tags, which are the optimally effective atmospheric and geographic parameters that are used to refine the selection of candidate microphysical profiles used for the Bayesian retrieval. These tags enable extending beyond the conventional Cloud Radiation Database (CRD algorithm by invoking meteorological-geophysical guidance, drawn from a simulated database, which affect and are in congruence with the observed precipitation states. This is guidance beyond the restrictive control provided by only simulated radiative transfer equation (RTE model-derived database brightness temperature (TB vector proximity information in seeking to relate physically consistent precipitation profile solutions to individual satellite-observed TB vectors. The first two parts of the study have rigorously demonstrated that the optimal tags effectively mitigate against solution ambiguity, where use of only a CRD framework (TB guidance only leads to pervasive non-uniqueness problems in finding rainfall solutions. Alternatively, a CDRD framework (TB + tag guidance mitigates against non-uniqueness problems through improved constraints. It remains to show how these optimal tags are identified. By use of three statistical analysis procedures applied to a database from 120 North American atmospheric simulations of precipitating storms (independent of the 60 simulations for the European-Mediterranean basin region

Daily TRMM and Others Rainfall Estimate (3B42 V7 derived) V7

Data.gov (United States)

National Aeronautics and Space Administration — The Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its...

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.

TRMM 3-Hourly 0.25 deg. TRMM and Other-GPI Calibration Rainfall Data V7

Data.gov (United States)

National Aeronautics and Space Administration — The Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its...

Assessment of satellite-based precipitation estimates over Paraguay

Science.gov (United States)

Oreggioni Weiberlen, Fiorella; Báez Benítez, Julián

2018-04-01

Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R 2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.

Improving rainfall representation for large-scale hydrological modelling of tropical mountain basins

Science.gov (United States)

Zulkafli, Zed; Buytaert, Wouter; Onof, Christian; Lavado, Waldo; Guyot, Jean-Loup

2013-04-01

Errors in the forcing data are sometimes overlooked in hydrological studies even when they could be the most important source of uncertainty. The latter particularly holds true in tropical countries with short historical records of rainfall monitoring and remote areas with sparse rain gauge network. In such instances, alternative data such as the remotely sensed precipitation from the TRMM (Tropical Rainfall Measuring Mission) satellite have been used. These provide a good spatial representation of rainfall processes but have been established in the literature to contain volumetric biases that may impair the results of hydrological modelling or worse, are compensated during model calibration. In this study, we analysed precipitation time series from the TMPA (TRMM Multiple Precipitation Algorithm, version 6) against measurements from over 300 gauges in the Andes and Amazon regions of Peru and Ecuador. We found moderately good monthly correlation between the pixel and gauge pairs but a severe underestimation of rainfall amounts and wet days. The discrepancy between the time series pairs is particularly visible over the east side of the Andes and may be attributed to localized and orographic-driven high intensity rainfall, which the satellite product may have limited skills at capturing due to technical and scale issues. This consequently results in a low bias in the simulated streamflow volumes further downstream. In comparison, with the recently released TMPA, version 7, the biases reduce. This work further explores several approaches to merge the two sources of rainfall measurements, each of a different spatial and temporal support, with the objective of improving the representation of rainfall in hydrological simulations. The methods used are (1) mean bias correction (2) data assimilation using Kalman filter Bayesian updating. The results are evaluated by means of (1) a comparison of runoff ratios (the ratio of the total runoff and the total precipitation over an

Hydrological real-time modelling in the Zambezi river basin using satellite-based soil moisture and rainfall data

Directory of Open Access Journals (Sweden)

P. Meier

2011-03-01

Full Text Available Reliable real-time forecasts of the discharge can provide valuable information for the management of a river basin system. For the management of ecological releases even discharge forecasts with moderate accuracy can be beneficial. Sequential data assimilation using the Ensemble Kalman Filter provides a tool that is both efficient and robust for a real-time modelling framework. One key parameter in a hydrological system is the soil moisture, which recently can be characterized by satellite based measurements. A forecasting framework for the prediction of discharges is developed and applied to three different sub-basins of the Zambezi River Basin. The model is solely based on remote sensing data providing soil moisture and rainfall estimates. The soil moisture product used is based on the back-scattering intensity of a radar signal measured by a radar scatterometer. These soil moisture data correlate well with the measured discharge of the corresponding watershed if the data are shifted by a time lag which is dependent on the size and the dominant runoff process in the catchment. This time lag is the basis for the applicability of the soil moisture data for hydrological forecasts. The conceptual model developed is based on two storage compartments. The processes modeled include evaporation losses, infiltration and percolation. The application of this model in a real-time modelling framework yields good results in watersheds where soil storage is an important factor. The lead time of the forecast is dependent on the size and the retention capacity of the watershed. For the largest watershed a forecast over 40 days can be provided. However, the quality of the forecast increases significantly with decreasing prediction time. In a watershed with little soil storage and a quick response to rainfall events, the performance is relatively poor and the lead time is as short as 10 days only.

Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

Science.gov (United States)

Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye; Lillo-Saavedra, Mario; Lagos, Octavio

2017-04-01

Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and for the case of the two long-term products the applicability for agricultural drought were evaluated when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in situ rainfall measurements across Chile were initially compared to the satellite data. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite products, and nine statistics were used to evaluate their performance to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze

Probabilistic clustering of rainfall condition for landslide triggering

Science.gov (United States)

Rossi, Mauro; Luciani, Silvia; Cesare Mondini, Alessandro; Kirschbaum, Dalia; Valigi, Daniela; Guzzetti, Fausto

2013-04-01

Landslides are widespread natural and man made phenomena. They are triggered by earthquakes, rapid snow melting, human activities, but mostly by typhoons and intense or prolonged rainfall precipitations. In Italy mostly they are triggered by intense precipitation. The prediction of landslide triggered by rainfall precipitations over large areas is commonly based on the exploitation of empirical models. Empirical landslide rainfall thresholds are used to identify rainfall conditions for the possible landslide initiation. It's common practice to define rainfall thresholds by assuming a power law lower boundary in the rainfall intensity-duration or cumulative rainfall-duration space above which landslide can occur. The boundary is defined considering rainfall conditions associated to landslide phenomena using heuristic approaches, and doesn't consider rainfall events not causing landslides. Here we present a new fully automatic method to identify the probability of landslide occurrence associated to rainfall conditions characterized by measures of intensity or cumulative rainfall and rainfall duration. The method splits the rainfall events of the past in two groups: a group of events causing landslides and its complementary, then estimate their probabilistic distributions. Next, the probabilistic membership of the new event to one of the two clusters is estimated. The method doesn't assume a priori any threshold model, but simple exploits the real empirical distribution of rainfall events. The approach was applied in the Umbria region, Central Italy, where a catalogue of landslide timing, were obtained through the search of chronicles, blogs and other source of information in the period 2002-2012. The approach was tested using rain gauge measures and satellite rainfall estimates (NASA TRMM-v6), allowing in both cases the identification of the rainfall condition triggering landslides in the region. Compared to the other existing threshold definition methods, the prosed

Sediment plume model-a comparison between use of measured turbidity data and satellite images for model calibration.

Science.gov (United States)

Sadeghian, Amir; Hudson, Jeff; Wheater, Howard; Lindenschmidt, Karl-Erich

2017-08-01

In this study, we built a two-dimensional sediment transport model of Lake Diefenbaker, Saskatchewan, Canada. It was calibrated by using measured turbidity data from stations along the reservoir and satellite images based on a flood event in 2013. In June 2013, there was heavy rainfall for two consecutive days on the frozen and snow-covered ground in the higher elevations of western Alberta, Canada. The runoff from the rainfall and the melted snow caused one of the largest recorded inflows to the headwaters of the South Saskatchewan River and Lake Diefenbaker downstream. An estimated discharge peak of over 5200 m 3 /s arrived at the reservoir inlet with a thick sediment front within a few days. The sediment plume moved quickly through the entire reservoir and remained visible from satellite images for over 2 weeks along most of the reservoir, leading to concerns regarding water quality. The aims of this study are to compare, quantitatively and qualitatively, the efficacy of using turbidity data and satellite images for sediment transport model calibration and to determine how accurately a sediment transport model can simulate sediment transport based on each of them. Both turbidity data and satellite images were very useful for calibrating the sediment transport model quantitatively and qualitatively. Model predictions and turbidity measurements show that the flood water and suspended sediments entered upstream fairly well mixed and moved downstream as overflow with a sharp gradient at the plume front. The model results suggest that the settling and resuspension rates of sediment are directly proportional to flow characteristics and that the use of constant coefficients leads to model underestimation or overestimation unless more data on sediment formation become available. Hence, this study reiterates the significance of the availability of data on sediment distribution and characteristics for building a robust and reliable sediment transport model.

Merging Satellite Precipitation Products for Improved Streamflow Simulations

Science.gov (United States)

Maggioni, V.; Massari, C.; Barbetta, S.; Camici, S.; Brocca, L.

2017-12-01

Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. Therefore, we propose to merge SM2RAIN and the widely used TMPA 3B42RT product across Italy for a 6-year period (2010-2015) at daily/0.25deg temporal/spatial scale. Two conceptually different merging techniques are compared to each other and evaluated in terms of different statistical metrics, including hit bias, threat score, false alarm rates, and missed rainfall volumes. The first is based on the maximization of the temporal correlation with a reference dataset, while the second is based on a Bayesian approach, which provides a probabilistic satellite precipitation estimate derived from the joint probability distribution of observations and satellite estimates. The merged precipitation products show a better performance with respect to the parental satellite-based products in terms of categorical

Measuring urban rainfall using microwave links from commercial cellular communication networks

NARCIS (Netherlands)

Overeem, A.; Leijnse, H.; Uijlenhoet, R.

2011-01-01

The estimation of rainfall using commercial microwave links is a new and promising measurement technique. Commercial link networks cover large parts of the land surface of the earth and have a high density, particularly in urban areas. Rainfall attenuates the electromagnetic signals transmitted

Hydrological similarity approach and rainfall satellite utilization for mini hydro power dam basic design (case study on the ungauged catchment at West Borneo, Indonesia)

Science.gov (United States)

Prakoso, W. G.; Murtilaksono, K.; Tarigan, S. D.; Purwanto, Y. J.

2018-05-01

An approach on flow duration and flood design estimation on the ungauged catchment with no rainfall and discharge data availability was been being develop with hydrological modelling including rainfall run off model implemented with watershed characteristic dataset. Near real time Rainfall data from multi satellite platform e.g. TRMM can be utilized for regionalization approach on the ungauged catchment. Watershed hydrologically similarity analysis were conducted including all of the major watershed in Borneo which was predicted to be similar with the Nanga Raun Watershed. It was found that a satisfactory hydrological model calibration could be achieved using catchment weighted time series of TRMM daily rainfall data, performed on nearby catchment deemed to be sufficiently similar to Nanga Raun catchment in hydrological terms. Based on this calibration, rainfall runoff parameters were then transferred to a model. Relatively reliable flow duration curve and extreme discharge value estimation were produced with reasonable several limitation. Further approach may be performed in order to deal with the primary limitations inherent in the hydrological and statistical analysis, especially to give prolongation to the availability of the rainfall and climate data with some novel approach like downscaling of global climate model.

Internationally coordinated multi-mission planning is now critical to sustain the space-based rainfall observations needed for managing floods globally

International Nuclear Information System (INIS)

Reed, Patrick M; Herman, Jonathan D; Chaney, Nathaniel W; Wood, Eric F; Ferringer, Matthew P

2015-01-01

At present 4 of 10 dedicated rainfall observing satellite systems have exceeded their design life, some by more than a decade. Here, we show operational implications for flood management of a ‘collapse’ of space-based rainfall observing infrastructure as well as the high-value opportunities for a globally coordinated portfolio of satellite missions and data services. Results show that the current portfolio of rainfall missions fails to meet operational data needs for flood management, even when assuming a perfectly coordinated data product from all current rainfall-focused missions (i.e., the full portfolio). In the full portfolio, satellite-based rainfall data deficits vary across the globe and may preclude climate adaptation in locations vulnerable to increasing flood risks. Moreover, removing satellites that are currently beyond their design life (i.e., the reduced portfolio) dramatically increases data deficits globally and could cause entire high intensity flood events to be unobserved. Recovery from the reduced portfolio is possible with internationally coordinated replenishment of as few as 2 of the 4 satellite systems beyond their design life, yielding rainfall data coverages that outperform the current full portfolio (i.e., an optimized portfolio of eight satellites can outperform ten satellites). This work demonstrates the potential for internationally coordinated satellite replenishment and data services to substantially enhance the cost-effectiveness, sustainability and operational value of space-based rainfall observations in managing evolving flood risks. (letter)

Characteristics and Diurnal Cycle of GPM Rainfall Estimates over the Central Amazon Region

Directory of Open Access Journals (Sweden)

Rômulo Oliveira

2016-06-01

Full Text Available Studies that investigate and evaluate the quality, limitations and uncertainties of satellite rainfall estimates are fundamental to assure the correct and successful use of these products in applications, such as climate studies, hydrological modeling and natural hazard monitoring. Over regions of the globe that lack in situ observations, such studies are only possible through intensive field measurement campaigns, which provide a range of high quality ground measurements, e.g., CHUVA (Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GlobAl Precipitation Measurement and GoAmazon (Observations and Modeling of the Green Ocean Amazon over the Brazilian Amazon during 2014/2015. This study aims to assess the characteristics of Global Precipitation Measurement (GPM satellite-based precipitation estimates in representing the diurnal cycle over the Brazilian Amazon. The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG and the Goddard Profiling Algorithm—Version 2014 (GPROF2014 algorithms are evaluated against ground-based radar observations. Specifically, the S-band weather radar from the Amazon Protection National System (SIPAM, is first validated against the X-band CHUVA radar and then used as a reference to evaluate GPM precipitation. Results showed satisfactory agreement between S-band SIPAM radar and both IMERG and GPROF2014 algorithms. However, during the wet season, IMERG, which uses the GPROF2014 rainfall retrieval from the GPM Microwave Imager (GMI sensor, significantly overestimates the frequency of heavy rainfall volumes around 00:00–04:00 UTC and 15:00–18:00 UTC. This overestimation is particularly evident over the Negro, Solimões and Amazon rivers due to the poorly-calibrated algorithm over water surfaces. On the other hand, during the dry season, the IMERG product underestimates mean precipitation in comparison to the S-band SIPAM

Deforestation and rainfall recycling in Brazil: Is decreased forest cover connectivity associated with decreased rainfall connectivity?

Science.gov (United States)

Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

2017-12-01

In the Brazilian rainforest-savanna transition zone, deforestation has the potential to significantly affect rainfall by disrupting rainfall recycling, the process by which regional evapotranspiration contributes to regional rainfall. Understanding rainfall recycling in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching, agriculture, hydropower generation, and drinking water management. Simulations in previous studies suggest complex, scale-dependent interactions between forest cover connectivity and rainfall. For example, the size and distribution of deforested patches has been found to affect rainfall quantity and spatial distribution. Here we take an empirical approach, using the spatial connectivity of rainfall as an indicator of rainfall recycling, to ask: as forest cover connectivity decreased from 1981 - 2015, how did the spatial connectivity of rainfall change in the Brazilian rainforest-savanna transition zone? We use satellite forest cover and rainfall data covering this period of intensive forest cover loss in the region (forest cover from the Hansen Global Forest Change dataset; rainfall from the Climate Hazards Infrared Precipitation with Stations dataset). Rainfall spatial connectivity is quantified using transfer entropy, a metric from information theory, and summarized using network statistics. Networks of connectivity are quantified for paired deforested and non-deforested regions before deforestation (1981-1995) and during/after deforestation (2001-2015). Analyses reveal a decline in spatial connectivity networks of rainfall following deforestation.

Remote sensing entropy to assess the sustainability of rainfall in tropical catchment

Science.gov (United States)

Mahmud, M. R.; Reba, M. N. M.; Wei, J. S.; Razak, N. H. Abdul

2018-02-01

This study demonstrated the utility of entropy computation using the satellite precipitation remote sensing data to assess the sustainability of rainfall in tropical catchments. There were two major issues need to be anticipated in monitoring the tropical catchments; first is the frequent monitoring of the rainfall and second is the appropriate indicator that sensitive to rainfall pattern changes or disorder. For the first issue, the use of satellite remote sensing precipitation data is suggested. Meanwhile for the second issue, the utilization of entropy concept in interpreting the disorder of temporal rainfall can be used to assess the sustain ability had been successfully adopted in some studies. Therefore, we hypothesized that the use of satellite precipitation as main data to compute entropy can be a novel tool in anticipating the above-mentioned conflict earlier. The remote sensing entropy results and in-situ river level showed good agreement indicating its reliability. 72% of the catchment has moderate to good rainfall supply during normal or non-drought condition. However, our result showed that the catchments were highly sensitive to drought especially in the west coast and southern part of the Peninsular Malaysia. High resiliency was identified in the east coast. We summarized that the proposed entropy-quantity scheme was a useful tool for cost-effective, quick, and operational sustainability assessment This study demonstrated the utility of entropy computation using the satellite precipitation remote sensing data to assess the sustainability of rainfall in tropical catchments.

Improved rainfall estimation over the Indian monsoon region by synergistic use of Kalpana-1 and rain gauge data

OpenAIRE

Gairola, R. M.; Prakash, Satya; Pal, P. K.

2015-01-01

In this paper, an attempt has been made to estimate rainfall over the Indian monsoon region by the synergistic use of the geostationary Kalpana-1 satellite-derived INSAT Multispectral Rainfall Algorithm (IMSRA) rainfall estimates and rain gauge data, using a successive correction method in order to further refine the operational IMSRA rainfall estimates. The successive correction method benefits from high spatial and temporal resolutions of the Kalpana-1 satellite and accurate rainfall estima...

Inter-comparison of Rainfall Estimation from Radar and Satellite During 2016 June 23 Yancheng Tornado Event over Eastern China

Science.gov (United States)

Huang, C.; Chen, S.; Liang, Z.; Hu, B.

2017-12-01

ABSTRACT: On the afternoon of June 23, 2016, Yancheng city in eastern China was hit by a severe thunderstorm that produced a devastating tornado. This tornado was ranked as an EF4 on the Enhanced Fujita scale by China Meteorological Administration, and killed at least 99 people and injured 846 others (152 seriously). This study evaluates rainfall estimates from ground radar network and four satellite algorithms with a relatively dense rain gauge network over eastern China including Jiangsu province and its adjacent regions for the Yancheng June 23 Tornado extreme convective storm in different spatiotemporal scales (from 0.04° to 0.1° and hourly to event total accumulation). The radar network is composed of about 6 S-band Doppler weather radars. Satellite precipitation products include Integrated Multi-satellitE Retrievals for GPM (IMERG), Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), and Global Satellite Mapping of Precipitation (GSMap). Relative Bias (RB), Root-Mean-Squared Error (RMSE), Correlation Coefficient (CC), Probability Of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) are used to quantify the performance of these precipitation products.

Evaluating a slope-stability model for shallow rain-induced landslides using gage and satellite data

Science.gov (United States)

Yatheendradas, S.; Kirschbaum, D.; Baum, Rex L.; Godt, Jonathan W.

2014-01-01

Improving prediction of landslide early warning systems requires accurate estimation of the conditions that trigger slope failures. This study tested a slope-stability model for shallow rainfall-induced landslides by utilizing rainfall information from gauge and satellite records. We used the TRIGRS model (Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis) for simulating the evolution of the factor of safety due to rainfall infiltration. Using a spatial subset of a well-characterized digital landscape from an earlier study, we considered shallow failure on a slope adjoining an urban transportation roadway near the Seattle area in Washington, USA.We ran the TRIGRS model using high-quality rain gage and satellite-based rainfall data from the Tropical Rainfall Measuring Mission (TRMM). Preliminary results with parameterized soil depth values suggest that the steeper slope values in this spatial domain have factor of safety values that are extremely close to the failure limit within an extremely narrow range of values, providing multiple false alarms. When the soil depths were constrained using a back analysis procedure to ensure that slopes were stable under initial condtions, the model accurately predicted the timing and location of the landslide observation without false alarms over time for gage rain data. The TRMM satellite rainfall data did not show adequately retreived rainfall peak magnitudes and accumulation over the study period, and as a result failed to predict the landslide event. These preliminary results indicate that more accurate and higher-resolution rain data (e.g., the upcoming Global Precipitation Measurement (GPM) mission) are required to provide accurate and reliable landslide predictions in ungaged basins.

Impact of Uncertainty Characterization of Satellite Rainfall Inputs and Model Parameters on Hydrological Data Assimilation with the Ensemble Kalman Filter for Flood Prediction

Science.gov (United States)

Vergara, H. J.; Kirstetter, P.; Hong, Y.; Gourley, J. J.; Wang, X.

2013-12-01

the sensitivities of the EnKF is revealed examining the impact of uncertainty representation on the assimilation process and subsequent forecasts. The methodology is tested on the hydrologic modeling of a basin subject to recurrent flooding events triggered by landfalling tropical systems. An ensemble framework for flood forecasting is employed to simulate the hydrologic processes using different levels of model structural complexity. Tropical Rainfall Measuring Mission (TRMM)-based QPE are used to force the hydrologic modeling system. A radar-based QPE product is utilized as a reference to estimate errors in satellite rainfall estimates and to characterize the uncertainty in model inputs. This set-up contributes to the development of methodologies to understand and characterize the error in satellite rainfall in a hydrologic modeling framework. Consequently, the results from this study will provide guidance for the integration of other remote-sensing observations through data assimilation for a more complete picture of the hydrometeorological phenomena of interest.

Impact of Satellite Remote Sensing Data on Simulations of Coastal Circulation and Hypoxia on the Louisiana Continental Shelf

OpenAIRE

Dong S. Ko; Richard W. Gould; Bradley Penta; John C. Lehrter

2016-01-01

We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS) near the annual hypoxic zone. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM) were used for the salinity flux, and the diffuse attenuation coefficient (Kd) from Moderate Resolution Imaging Spectroradiometer...

Sensitivity of Rainfall Extremes Under Warming Climate in Urban India

Science.gov (United States)

Ali, H.; Mishra, V.

2017-12-01

Extreme rainfall events in urban India halted transportation, damaged infrastructure, and affected human lives. Rainfall extremes are projected to increase under the future climate. We evaluated the relationship (scaling) between rainfall extremes at different temporal resolutions (daily, 3-hourly, and 30 minutes), daily dewpoint temperature (DPT) and daily air temperature at 850 hPa (T850) for 23 urban areas in India. Daily rainfall extremes obtained from Global Surface Summary of Day Data (GSOD) showed positive regression slopes for most of the cities with median of 14%/K for the period of 1979-2013 for DPT and T850, which is higher than Clausius-Clapeyron (C-C) rate ( 7%). Moreover, sub-daily rainfall extremes are more sensitive to both DPT and T850. For instance, 3-hourly rainfall extremes obtained from Tropical Rainfall Measurement Mission (TRMM 3B42 V7) showed regression slopes more than 16%/K aginst DPT and T850 for the period of 1998-2015. Half-hourly rainfall extremes from the Integrated Multi-satellitE Retrievals (IMERGE) of Global precipitation mission (GPM) also showed higher sensitivity against changes in DPT and T850. The super scaling of rainfall extremes against changes in DPT and T850 can be attributed to convective nature of precipitation in India. Our results show that urban India may witness non-stationary rainfall extremes, which, in turn will affect stromwater designs and frequency and magniture of urban flooding.

Using satellite-based rainfall data to support the implementation of ...

African Journals Online (AJOL)

The methods currently available in South Africa to implement environmental flows are based on real-time rainfall-runoff models (which require accurate inputs of rainfall data) or the use of flow gauges. Both methods are useful but have limitations which must be fully understood. The main limitation of the latter approach is ...

TRMM Applications for Rainfall-Induced Landslide Early Warning

Science.gov (United States)

Dok, A.; Fukuoka, H.; Hong, Y.

2012-04-01

Early warning system (EWS) is the most effective method in saving lives and reducing property damages resulted from the catastrophic landslides if properly implemented in populated areas of landslide-prone nations. For predicting the occurrence of landslides, it requires examination of empirical relationship between rainfall characteristics and past landslide occurrence. In developed countries like Japan and the US, precipitation is monitored by rain radars and ground-based rain gauge matrix. However, in developing regions like Southeast Asian countries, very limited number of rain gauges is available, and there is no implemented methodology for issuing effective warming of landslides yet. Correspondingly, satellite precipitation monitoring could be therefore a possible and promising solution for launching landslide quasi-real-time early warning system in those countries. It is due to the fact that TMPA (TRMM Multi-satellite Precipitation Analysis) can provides a globally calibration-based sequential scheme for combining precipitation estimates from multiple satellites, and gauge analyses where feasible, at fine scales (3-hourly with 0.25°x0.25° spatial resolution). It is available both after and in quasi-real time, calibrated by TRMM Combined Instrument and TRMM Microwave Imager precipitation product. However, validation of ground based rain gauge and TRMM satellite data in the vulnerable regions is still not yet operative. Snake-line/Critical-line and Soil Water Index (SWI) are used for issuing warning of landslide occurrence in Japan; whereas, Caine criterion is preferable in Europe and western nations. Herewith, it presents rainfall behavior which took place in Beichuan city (located on the 2008 Chinese Wenchuan earthquake fault), Hofu and Shobara cities in Japan where localized heavy rainfall attacked in 2009 and 2010, respectively, from TRMM 3B42RT correlated with ground based rain gauge data. The 1-day rainfall intensity and 15-day cumulative rainfall

Comparison between Pludix and impact/optical disdrometers during rainfall measurement campaigns

Science.gov (United States)

Caracciolo, Clelia; Prodi, Franco; Uijlenhoet, Remko

2006-11-01

The performances of two couples of disdrometers based on different measuring principles are compared: a classical Joss-Waldvogel disdrometer and a recently developed device, called the Pludix tested in Ferrara, Italy, and Pludix and the two-dimensional video disdrometer (2DVD) tested in Cabauw, The Netherlands. First, the measuring principles of the different instruments are presented and compared. Secondly, the performances of the two pairs of disdrometers are analysed by comparing their rain amounts with nearby tipping bucket rain gauges and the inferred drop size distributions. The most important rainfall integral parameters (e.g. rain rate and radar reflectivity) and drop size distribution parameters are also analysed and compared. The data set for Ferrara comprises 13 rainfall events, with a total of 20 mm of rainfall and a maximum rain rate of 4 mm h - 1 . The data set for Cabauw consists of 9 events, with 25-50 mm of rainfall and a maximum rain rate of 20-40 mm h - 1 . The Pludix tends to underestimate slightly the bulk rainfall variables in less intense events, whereas it tends to overestimate with respect to the other instruments in heavier events. The correspondence of the inferred drop size distributions with those measured by the other disdrometers is reasonable, particularly with the Joss-Waldvogel disdrometer. Considering that the Pludix is still in a calibration and testing phase, the reported results are encouraging. A new signal inversion algorithm, which will allow the detection of rain drops throughout the entire diameter interval between 0.3 and 7.0 mm, is under development.

A Merging Framework for Rainfall Estimation at High Spatiotemporal Resolution for Distributed Hydrological Modeling in a Data-Scarce Area

Directory of Open Access Journals (Sweden)

Yinping Long

2016-07-01

Full Text Available Merging satellite and rain gauge data by combining accurate quantitative rainfall from stations with spatial continuous information from remote sensing observations provides a practical method of estimating rainfall. However, generating high spatiotemporal rainfall fields for catchment-distributed hydrological modeling is a problem when only a sparse rain gauge network and coarse spatial resolution of satellite data are available. The objective of the study is to present a satellite and rain gauge data-merging framework adapting for coarse resolution and data-sparse designs. In the framework, a statistical spatial downscaling method based on the relationships among precipitation, topographical features, and weather conditions was used to downscale the 0.25° daily rainfall field derived from the Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis (TMPA precipitation product version 7. The nonparametric merging technique of double kernel smoothing, adapting for data-sparse design, was combined with the global optimization method of shuffled complex evolution, to merge the downscaled TRMM and gauged rainfall with minimum cross-validation error. An indicator field representing the presence and absence of rainfall was generated using the indicator kriging technique and applied to the previously merged result to consider the spatial intermittency of daily rainfall. The framework was applied to estimate daily precipitation at a 1 km resolution in the Qinghai Lake Basin, a data-scarce area in the northeast of the Qinghai-Tibet Plateau. The final estimates not only captured the spatial pattern of daily and annual precipitation with a relatively small estimation error, but also performed very well in stream flow simulation when applied to force the geomorphology-based hydrological model (GBHM. The proposed framework thus appears feasible for rainfall estimation at high spatiotemporal resolution in data-scarce areas.

Deformation responses of slow moving landslides to seasonal rainfall in the Northern Apennines, measured by InSAR

Science.gov (United States)

Bayer, Benedikt; Simoni, Alessandro; Mulas, Marco; Corsini, Alessandro; Schmidt, David

2018-05-01

Slow moving landslides are widespread geomorphological features in the Northern Apennines of Italy where they represent one of the main landscape forming processes. The lithology of the Northern Apennines fold and thrust belt is characterized by alternations of sandstone, siltstone and clayshales, also known as flysch, and clay shales with a chaotic block in matrix fabric, which are often interpreted as tectonic or sedimentary mélanges. While flysch rocks with a high pelitic fraction host earthslides that occasionally evolve into flow like movements, earthflows are the dominant landslide type in chaotic clay shales. In the present work, we document the kinematic response to rainfall of landslides in these different lithologies using radar interferometry. The study area includes three river catchments in the Northern Apennines. Here, the Mediterranean climate is characterized by two wet seasons during autumn and spring respectively, separated by dry summers and winters with moderate precipitation. We use SAR imagery from the X-band satellite COSMO SkyMed and from the C-band satellite Sentinel 1 to retrieve spatial displacement measurements between 2009 and 2016 for 25 landslides in our area of interest. We also document detailed temporal and spatial deformation signals for eight representative landslides, although the InSAR derived deformation signal is only well constrained by our dataset during the years 2013 and 2015. In spring 2013, long enduring rainfalls struck the study area and numerous landslide reactivations were documented by the regional authorities. During 2013, we measured higher displacement rates on the landslides in pelitic flysch formations compared to the earthflows in the clay shales. Slower mean velocities were measured on most landslides during 2015. We analyse the temporal deformation signal of our eight representative landslides and compare the temporal response to precipitation. We show that earthslides in pelitic flysch formations

SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture

Science.gov (United States)

Ciabatta, Luca; Massari, Christian; Brocca, Luca; Gruber, Alexander; Reimer, Christoph; Hahn, Sebastian; Paulik, Christoph; Dorigo, Wouter; Kidd, Richard; Wagner, Wolfgang

2018-02-01

Accurate and long-term rainfall estimates are the main inputs for several applications, from crop modeling to climate analysis. In this study, we present a new rainfall data set (SM2RAIN-CCI) obtained from the inversion of the satellite soil moisture (SM) observations derived from the ESA Climate Change Initiative (CCI) via SM2RAIN (Brocca et al., 2014). Daily rainfall estimates are generated for an 18-year long period (1998-2015), with a spatial sampling of 0.25° on a global scale, and are based on the integration of the ACTIVE and the PASSIVE ESA CCI SM data sets.The quality of the SM2RAIN-CCI rainfall data set is evaluated by comparing it with two state-of-the-art rainfall satellite products, i.e. the Tropical Measurement Mission Multi-satellite Precipitation Analysis 3B42 real-time product (TMPA 3B42RT) and the Climate Prediction Center Morphing Technique (CMORPH), and one modeled data set (ERA-Interim). A quality check is carried out on a global scale at 1° of spatial sampling and 5 days of temporal sampling by comparing these products with the gauge-based Global Precipitation Climatology Centre Full Data Daily (GPCC-FDD) product. SM2RAIN-CCI shows relatively good results in terms of correlation coefficient (median value > 0.56), root mean square difference (RMSD, median value test the capabilities of the data set to correctly identify rainfall events under different climate and precipitation regimes.The SM2RAIN-CCI rainfall data set is freely available at https://doi.org/10.5281/zenodo.846259.

Rainfall Modification by Urban Areas: New Perspectives from TRMM

Science.gov (United States)

Shepherd, J. Marshall; Pierce, Harold F.; Negri, Andrew

2002-01-01

Data from the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of -28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48% - 116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. Future work is extending the investigation to Phoenix, Arizona, an arid U.S. city, and several international cities like Mexico City, Johannesburg, and Brasilia. The study establishes the possibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

Precipitation Characteristics in West and East Africa from Satellite and in Situ Observations

Science.gov (United States)

Dezfuli, Amin K.; Ichoku, Charles M.; Mohr, Karen I.; Huffman, George J.

2017-01-01

Using in situ data, three precipitation classes are identified for rainy seasons of West and East Africa: weak convective rainfall (WCR), strong convective rainfall (SCR), and mesoscale convective systems (MCSs).Nearly 75% of the total seasonal precipitation is produced by the SCR and MCSs, even though they represent only 8% of the rain events. Rain events in East Africa tend to have a longer duration and lower intensity than in West Africa, reflecting different characteristics of the SCR and MCS events in these two regions. Surface heating seems to be the primary convection trigger for the SCR, particularly in East Africa, whereas the WCR requires a dynamical trigger such as low-level convergence. The data are used to evaluate the performance of the recently launched Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG)project. The IMERG-based precipitation shows significant improvement over its predecessor, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), particularly in capturing the MCSs, due to its improved temporal resolution.

Impact of Satellite Remote Sensing Data on Simulations of ...

Science.gov (United States)

We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS) near the annual hypoxic zone. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM) were used for the salinity flux, and the diffuse attenuation coefficient (Kd) from Moderate Resolution Imaging Spectroradiometer (MODIS) were used for solar penetration. Improvements in the model results in comparison with in situ observations occurred when the two types of satellite data were included. Without inclusion of the satellite-derived surface salinity flux, realistic monthly variability in the model salinity fields was observed, but important inter-annual variability wasmissed. Without inclusion of the satellite-derived light attenuation, model bottom water temperatures were too high nearshore due to excessive penetration of solar irradiance. In general, these salinity and temperature errors led to model stratification that was too weak, and the model failed to capture observed spatial and temporal variability in water-column vertical stratification. Inclusion of the satellite data improved temperature and salinity predictions and the vertical stratification was strengthened, which improved prediction of bottom-water dissolved oxygen. The model-predicted area of bottom-water hypoxia on the

Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

NARCIS (Netherlands)

Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

2016-01-01

Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide (≈ 35 500 km²) 15 min rainfall maps can

Rain detection over land surfaces using passive microwave satellite data

NARCIS (Netherlands)

Bauer, P.; Burose, D.; Schulz, J.

2002-01-01

An algorithm is presented for the detection of surface rainfall using passive microwave measurements by satellite radiometers. The technique consists of a two-stage approach to distinguish precipitation signatures from other effects: (1) Contributions from slowly varying parameters (surface type and

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

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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.

Precipitation measurements for earth-space communications: Accuracy requirements and ground-truth techniques

Science.gov (United States)

Ippolito, L. J.; Kaul, R.

1981-01-01

Rainfall which is regarded as one of the more important observations for the measurements of this most variable parameter was made continuously, across large areas and over the sea. Ships could not provide the needed resolution nor could available radars provide the needed breadth of coverage. Microwave observations from the Nimbus-5 satellite offered some hope. Another possibility was suggested by the results of many comparisons between rainfall and the clouds seen in satellite pictures. Sequences of pictures from the first geostationary satellites were employed and a general correspondence between rain and the convective clouds visible in satellite pictures was found. It was demonstrated that the agreement was best for growing clouds. The development methods to infer GATE rainfall from geostationary satellite images are examined.

The use of geostationary satellite based rainfall estimation and rainfall-runoff modelling for regional flash flood assessment

OpenAIRE

Suseno, Dwi Prabowo Yuga

2013-01-01

The availability of rainfall triggered hazard information such as flash flood is crucial in the flood disaster management and mitigation. However, providing that information is mainly hampered by the shortage of data because of the sparse, uneven or absence the hydrological or meteorological observation. Remote sensing techniques that make frequent observations with continuous spatial coverage provide useful information for detecting the hydrometeorological phenomena such as rainfall and floo...

An assessment of the performance of global rainfall estimates without ground-based observations

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C. Massari

2017-09-01

Full Text Available Satellite-based rainfall estimates over land have great potential for a wide range of applications, but their validation is challenging due to the scarcity of ground-based observations of rainfall in many areas of the planet. Recent studies have suggested the use of triple collocation (TC to characterize uncertainties associated with rainfall estimates by using three collocated rainfall products. However, TC requires the simultaneous availability of three products with mutually uncorrelated errors, a requirement which is difficult to satisfy with current global precipitation data sets. In this study, a recently developed method for rainfall estimation from soil moisture observations, SM2RAIN, is demonstrated to facilitate the accurate application of TC within triplets containing two state-of-the-art satellite rainfall estimates and a reanalysis product. The validity of different TC assumptions are indirectly tested via a high-quality ground rainfall product over the contiguous United States (CONUS, showing that SM2RAIN can provide a truly independent source of rainfall accumulation information which uniquely satisfies the assumptions underlying TC. On this basis, TC is applied with SM2RAIN on a global scale in an optimal configuration to calculate, for the first time, reliable global correlations (vs. an unknown truth of the aforementioned products without using a ground benchmark data set. The analysis is carried out during the period 2007–2012 using daily rainfall accumulation products obtained at 1° × 1° spatial resolution. Results convey the relatively high performance of the satellite rainfall estimates in eastern North and South America, southern Africa, southern and eastern Asia, eastern Australia, and southern Europe, as well as complementary performances between the reanalysis product and SM2RAIN, with the first performing reasonably well in the Northern Hemisphere and the second providing very good performance in the Southern

Ground-truth measurement systems

Science.gov (United States)

Serafin, R.; Seliga, T. A.; Lhermitte, R. M.; Nystuen, J. A.; Cherry, S.; Bringi, V. N.; Blackmer, R.; Heymsfield, G. M.

1981-01-01

Ground-truth measurements of precipitation and related weather events are an essential component of any satellite system designed for monitoring rainfall from space. Such measurements are required for testing, evaluation, and operations; they provide detailed information on the actual weather events, which can then be compared with satellite observations intended to provide both quantitative and qualitative information about them. Also, very comprehensive ground-truth observations should lead to a better understanding of precipitation fields and their relationships to satellite data. This process serves two very important functions: (a) aiding in the development and interpretation of schemes of analyzing satellite data, and (b) providing a continuing method for verifying satellite measurements.

Determination of Areas Susceptible to Landsliding Using Spatial Patterns of Rainfall from Tropical Rainfall Measuring Mission Data, Rio de Janeiro, Brazil

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Renato Fontes Guimarães

2017-10-01

Full Text Available Spatial patterns of shallow landslide initiation reflect both spatial patterns of heavy rainfall and areas susceptible to mass movements. We determine the areas most susceptible to shallow landslide occurrence through the calculation of critical soil cohesion and spatial patterns of rainfall derived from TRMM (Tropical Rainfall Measuring Mission data for Paraty County, State of Rio de Janeiro, Brazil. Our methodology involved: (a creating the digital elevation model (DEM and deriving attributes such as slope and contributing area; (b incorporating spatial patterns of rainfall derived from TRMM into the shallow slope stability model SHALSTAB; and (c quantitative assessment of the correspondence of mapped landslide scars to areas predicted to be most prone to shallow landsliding. We found that around 70% of the landslide scars occurred in less than 10% of the study area identified as potentially unstable. The greatest concentration of landslides occurred in areas where the root strength of vegetation is an important contribution to slope stability in regions of orographically-enhanced rainfall on the coastal topographic flank. This approach helps quantify landslide hazards in areas with similar geomorphological characteristics, but different spatial patterns of rainfall.

Improved spatial mapping of rainfall events with spaceborne SAR imagery

Science.gov (United States)

Ulaby, F. T.; Brisco, B.; Dobson, C.

1983-01-01

The Seasat satellite acquired the first spaceborne synthetic-aperture radar (SAR) images of the earth's surface, in 1978, at a frequency of 1.275 GHz (L-band) in a like-polarization mode at incidence angles of 23 + or - 3 deg. Although this may not be the optimum system configuration for radar remote sensing of soil moisture, interpretation of two Seasat images of Iowa demonstrates the sensitivity of microwave backscatter to soil moisture content. In both scenes, increased image brightness, which represents more radar backscatter, can be related to previous rainfall activity in the two areas. Comparison of these images with ground-based rainfall observations illustrates the increased spatial coverage of the rainfall event that can be obtained from the satellite SAR data. These data can then be color-enhanced by a digital computer to produce aesthetically pleasing output products for the user community.

Using Convective Stratiform Technique (CST) method to estimate rainfall (case study in Bali, December 14th 2016)

Science.gov (United States)

Vista Wulandari, Ayu; Rizki Pratama, Khafid; Ismail, Prayoga

2018-05-01

Accurate and realtime data in wide spatial space at this time is still a problem because of the unavailability of observation of rainfall in each region. Weather satellites have a very wide range of observations and can be used to determine rainfall variability with better resolution compared with a limited direct observation. Utilization of Himawari-8 satellite data in estimating rainfall using Convective Stratiform Technique (CST) method. The CST method is performed by separating convective and stratiform cloud components using infrared channel satellite data. Cloud components are classified by slope because the physical and dynamic growth processes are very different. This research was conducted in Bali area on December 14, 2016 by verifying the result of CST process with rainfall data from Ngurah Rai Meteorology Station Bali. It is found that CST method result had simililar value with data observation in Ngurah Rai meteorological station, so it assumed that CST method can be used for rainfall estimation in Bali region.

On the Tropical Rainfall Measuring Mission (TRMM): Bringing NASA's Earth System Science Program to the Classroom

Science.gov (United States)

Shepherd, J. Marshall

1998-01-01

The Tropical Rainfall Measuring Mission is the first mission dedicated to measuring tropical and subtropical rainfall using a variety of remote sensing instrumentation, including the first spaceborne rain-measuring radar. Since the energy released when tropical rainfall occurs is a primary "fuel" supply for the weather and climate "engine"; improvements in computer models which predict future weather and climate states may depend on better measurements of global tropical rainfall and its energy. In support of the STANYS conference theme of Education and Space, this presentation focuses on one aspect of NASA's Earth Systems Science Program. We seek to present an overview of the TRMM mission. This overview will discuss the scientific motivation for TRMM, the TRMM instrument package, and recent images from tropical rainfall systems and hurricanes. The presentation also targets educational components of the TRMM mission in the areas of weather, mathematics, technology, and geography that can be used by secondary school/high school educators in the classroom.

Measurement accuracy of weighing and tipping-bucket rainfall intensity gauges under dynamic laboratory testing

Science.gov (United States)

Colli, M.; Lanza, L. G.; La Barbera, P.; Chan, P. W.

2014-07-01

The contribution of any single uncertainty factor in the resulting performance of infield rain gauge measurements still has to be comprehensively assessed due to the high number of real world error sources involved, such as the intrinsic variability of rainfall intensity (RI), wind effects, wetting losses, the ambient temperature, etc. In recent years the World Meteorological Organization (WMO) addressed these issues by fostering dedicated investigations, which revealed further difficulties in assessing the actual reference rainfall intensity in the field. This work reports on an extensive assessment of the OTT Pluvio2 weighing gauge accuracy when measuring rainfall intensity under laboratory dynamic conditions (time varying reference flow rates). The results obtained from the weighing rain gauge (WG) were also compared with a MTX tipping-bucket rain gauge (TBR) under the same test conditions. Tests were carried out by simulating various artificial precipitation events, with unsteady rainfall intensity, using a suitable dynamic rainfall generator. Real world rainfall data measured by an Ogawa catching-type drop counter at a field test site located within the Hong Kong International Airport (HKIA) were used as a reference for the artificial rain generation system. Results demonstrate that the differences observed between the laboratory and field performance of catching-type gauges are only partially attributable to the weather and operational conditions in the field. The dynamics of real world precipitation events is responsible for a large part of the measurement errors, which can be accurately assessed in the laboratory under controlled environmental conditions. This allows for new testing methodologies and the development of instruments with enhanced performance in the field.

The consecutive dry days to trigger rainfall over West Africa

Science.gov (United States)

Lee, J. H.

2018-01-01

In order to resolve contradictions in addressing a soil moisture-precipitation feedback mechanism over West Africa and to clarify the impact of antecedent soil moisture on subsequent rainfall evolution, we first validated various data sets (SMOS satellite soil moisture observations, NOAH land surface model, TRMM rainfall, CMORPH rainfall and HadGEM climate models) with the Analyses Multidisciplinaires de la Mousson Africaine (AMMA) field campaign data. Based on this analysis, it was suggested that biases of data sets might cause contradictions in studying mechanisms. Thus, by taking into account uncertainties in data, it was found that the approach of consecutive dry days (i.e. a relative comparison of time-series) showed consistency across various data sets, while the direct comparison approach for soil moisture state and rainfall did not. Thus, it was discussed that it may be difficult to directly relate rain with soil moisture as the absolute value, however, it may be reasonable to compare a temporal progress of the variables. Based upon the results consistently showing a positive relationship between the consecutive dry days and rainfall, this study supports a negative feedback often neglected by climate model structure. This approach is less sensitive to interpretation errors arising from systematic errors in data sets, as this measures a temporal gradient of soil moisture state.

GHRSST Level 2P Global Subskin Sea Surface Temperature from TRMM Microwave Imager (TMI) onboard Tropical Rainfall Measurement Mission (TRMM) satellite (GDS versions 1 and 2)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — GDS2 Version -The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is a well calibrated passive microwave radiometer, similar to the Special Sensor...

INTEGRATION OF SATELLITE RAINFALL DATA AND CURVE NUMBER METHOD FOR RUNOFF ESTIMATION UNDER SEMI-ARID WADI SYSTEM

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E. O. Adam

2017-11-01

Full Text Available The arid and semi-arid catchments in dry lands in general require a special effective management as the scarcity of resources and information which is needed to leverage studies and investigations is the common characteristic. Hydrology is one of the most important elements in the management of resources. Deep understanding of hydrological responses is the key towards better planning and land management. Surface runoff quantification of such ungauged semi-arid catchments considered among the important challenges. A 7586 km2 catchment under investigation is located in semi-arid region in central Sudan where mean annual rainfall is around 250 mm and represent the ultimate source for water supply. The objective is to parameterize hydrological characteristics of the catchment and estimate surface runoff using suitable methods and hydrological models that suit the nature of such ungauged catchments with scarce geospatial information. In order to produce spatial runoff estimations, satellite rainfall was used. Remote sensing and GIS were incorporated in the investigations and the generation of landcover and soil information. Five days rainfall event (50.2 mm was used for the SCS CN model which is considered the suitable for this catchment, as SCS curve number (CN method is widely used for estimating infiltration characteristics depending on the landcover and soil property. Runoff depths of 3.6, 15.7 and 29.7 mm were estimated for the three different Antecedent Moisture Conditions (AMC-I, AMC-II and AMC-III. The estimated runoff depths of AMCII and AMCIII indicate the possibility of having small artificial surface reservoirs that could provide water for domestic and small household agricultural use.

Rainfall Product Evaluation for the TRMM Ground Validation Program

Science.gov (United States)

Amitai, E.; Wolff, D. B.; Robinson, M.; Silberstein, D. S.; Marks, D. A.; Kulie, M. S.; Fisher, B.; Einaudi, Franco (Technical Monitor)

2000-01-01

Evaluation of the Tropical Rainfall Measuring Mission (TRMM) satellite observations is conducted through a comprehensive Ground Validation (GV) Program. Standardized instantaneous and monthly rainfall products are routinely generated using quality-controlled ground based radar data from four primary GV sites. As part of the TRMM GV program, effort is being made to evaluate these GV products and to determine the uncertainties of the rainfall estimates. The evaluation effort is based on comparison to rain gauge data. The variance between the gauge measurement and the true averaged rain amount within the radar pixel is a limiting factor in the evaluation process. While monthly estimates are relatively simple to evaluate, the evaluation of the instantaneous products are much more of a challenge. Scattegrams of point comparisons between radar and rain gauges are extremely noisy for several reasons (e.g. sample volume discrepancies, timing and navigation mismatches, variability of Z(sub e)-R relationships), and therefore useless for evaluating the estimates. Several alternative methods, such as the analysis of the distribution of rain volume by rain rate as derived from gauge intensities and from reflectivities above the gauge network will be presented. Alternative procedures to increase the accuracy of the estimates and to reduce their uncertainties also will be discussed.

Comparisons of Satellite Soil Moisture, an Energy Balance Model Driven by LST Data and Point Measurements

Science.gov (United States)

Laiolo, Paola; Gabellani, Simone; Rudari, Roberto; Boni, Giorgio; Puca, Silvia

2013-04-01

Soil moisture plays a fundamental role in the partitioning of mass and energy fluxes between land surface and atmosphere, thereby influencing climate and weather, and it is important in determining the rainfall-runoff response of catchments; moreover, in hydrological modelling and flood forecasting, a correct definition of moisture conditions is a key factor for accurate predictions. Different sources of information for the estimation of the soil moisture state are currently available: satellite data, point measurements and model predictions. All are affected by intrinsic uncertainty. Among different satellite sensors that can be used for soil moisture estimation three major groups can be distinguished: passive microwave sensors (e.g., SSMI), active sensors (e.g. SAR, Scatterometers), and optical sensors (e.g. Spectroradiometers). The last two families, mainly because of their temporal and spatial resolution seem the most suitable for hydrological applications In this work soil moisture point measurements from 10 sensors in the Italian territory are compared of with the satellite products both from the HSAF project SM-OBS-2, derived from the ASCAT scatterometer, and from ACHAB, an operative energy balance model that assimilate LST data derived from MSG and furnishes daily an evaporative fraction index related to soil moisture content for all the Italian region. Distributed comparison of the ACHAB and SM-OBS-2 on the whole Italian territory are performed too.

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

ASSESSMENT OF SATELLITE PRECIPITATION PRODUCTS IN THE PHILIPPINE ARCHIPELAGO

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M. D. Ramos

2016-06-01

Full Text Available Precipitation is the most important weather parameter in the Philippines. Made up of more than 7100 islands, the Philippine archipelago is an agricultural country that depends on rain-fed crops. Located in the western rim of the North West Pacific Ocean, this tropical island country is very vulnerable to tropical cyclones that lead to severe flooding events. Recently, satellite-based precipitation estimates have improved significantly and can serve as alternatives to ground-based observations. These data can be used to fill data gaps not only for climatic studies, but can also be utilized for disaster risk reduction and management activities. This study characterized the statistical errors of daily precipitation from four satellite-based rainfall products from (1 the Tropical Rainfall Measuring Mission (TRMM, (2 the CPC Morphing technique (CMORPH of NOAA and (3 the Global Satellite Mapping of Precipitation (GSMAP and (4 Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks (PERSIANN. Precipitation data were compared to 52 synoptic weather stations located all over the Philippines. Results show GSMAP to have over all lower bias and CMORPH with lowest Mean Absolute Error (MAE and Root Mean Square Error (RMSE. In addition, a dichotomous rainfall test reveals GSMAP and CMORPH have low Proportion Correct (PC for convective and stratiform rainclouds, respectively. TRMM consistently showed high PC for almost all raincloud types. Moreover, all four satellite precipitation showed high Correct Negatives (CN values for the north-western part of the country during the North-East monsoon and spring monsoonal transition periods.

Assessment of Satellite Precipitation Products in the Philippine Archipelago

Science.gov (United States)

Ramos, M. D.; Tendencia, E.; Espana, K.; Sabido, J.; Bagtasa, G.

2016-06-01

Precipitation is the most important weather parameter in the Philippines. Made up of more than 7100 islands, the Philippine archipelago is an agricultural country that depends on rain-fed crops. Located in the western rim of the North West Pacific Ocean, this tropical island country is very vulnerable to tropical cyclones that lead to severe flooding events. Recently, satellite-based precipitation estimates have improved significantly and can serve as alternatives to ground-based observations. These data can be used to fill data gaps not only for climatic studies, but can also be utilized for disaster risk reduction and management activities. This study characterized the statistical errors of daily precipitation from four satellite-based rainfall products from (1) the Tropical Rainfall Measuring Mission (TRMM), (2) the CPC Morphing technique (CMORPH) of NOAA and (3) the Global Satellite Mapping of Precipitation (GSMAP) and (4) Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks (PERSIANN). Precipitation data were compared to 52 synoptic weather stations located all over the Philippines. Results show GSMAP to have over all lower bias and CMORPH with lowest Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). In addition, a dichotomous rainfall test reveals GSMAP and CMORPH have low Proportion Correct (PC) for convective and stratiform rainclouds, respectively. TRMM consistently showed high PC for almost all raincloud types. Moreover, all four satellite precipitation showed high Correct Negatives (CN) values for the north-western part of the country during the North-East monsoon and spring monsoonal transition periods.

Verification of the skill of numerical weather prediction models in forecasting rainfall from U.S. landfalling tropical cyclones

Science.gov (United States)

Luitel, Beda; Villarini, Gabriele; Vecchi, Gabriel A.

2018-01-01

The goal of this study is the evaluation of the skill of five state-of-the-art numerical weather prediction (NWP) systems [European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC)] in forecasting rainfall from North Atlantic tropical cyclones (TCs). Analyses focus on 15 North Atlantic TCs that made landfall along the U.S. coast over the 2007-2012 period. As reference data we use gridded rainfall provided by the Climate Prediction Center (CPC). We consider forecast lead-times up to five days. To benchmark the skill of these models, we consider rainfall estimates from one radar-based (Stage IV) and four satellite-based [Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA, both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); the CPC MORPHing Technique (CMORPH)] rainfall products. Daily and storm total rainfall fields from each of these remote sensing products are compared to the reference data to obtain information about the range of errors we can expect from "observational data." The skill of the NWP models is quantified: (1) by visual examination of the distribution of the errors in storm total rainfall for the different lead-times, and numerical examination of the first three moments of the error distribution; (2) relative to climatology at the daily scale. Considering these skill metrics, we conclude that the NWP models can provide skillful forecasts of TC rainfall with lead-times up to 48 h, without a consistently best or worst NWP model.

Diurnal Variation of Rainfall Associated with Tropical Depression in South China and its Relationship to Land-Sea Contrast and Topography

Directory of Open Access Journals (Sweden)

Yuchun Zhao

2013-12-01

Full Text Available Convective precipitation associated with tropical depression (TD is one primary type of post-flooding season rainfall in South China (SC. Observations of the Tropical Rainfall Measuring Mission (TRMM satellite have shown specific diurnal features of convective rainfall in South China, which is somewhat different from that in other seasons or regions of China. Convective precipitation is usually organized into a rainfall band along the southeastern coast of South China in the early morning hours. The rainfall band develops and intensifies quickly in the morning, then moves inland in the afternoon and, finally, diminishes at night. The daily convective rainfall along the coast is much more than that in the inland region, and heavy rainfall is often found along the coast. A long-duration heavy rainfall event associated with tropical depression “Fitow” during the period from 28 August to 6 September 2001, is selected in this study to explore the diurnal feature of convective rainfall and its formation mechanism. Modeling results of the 10-day heavy rainfall event are compared with both rain-gauge observation and satellite-retrieved rainfall. Total precipitation and its spatial distribution, as well as diurnal variations are reasonably simulated and agree well with observations. Further analysis reveals that the development and movement of convective precipitation is mainly related to the land and sea breezes. The anomalous height-latitudinal circulation in the morning-to-noon hours is completely reversed in the afternoon-to-late-evening hours, with the convective rainfall swinging back and forth, following its updraft branch. Sensitivity experiments show that the afternoon convective rainfall in the inland region of SC is caused by the diurnal variation of solar radiation forcing. The mountain range along the coast and the complex topography in the inland region of SC plays a critical role in the enhancement of diurnal convective rainfall

Performance of high-resolution X-band radar for rainfall measurement in The Netherlands

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C. Z. van de Beek

2010-02-01

Full Text Available This study presents an analysis of 195 rainfall events gathered with the X-band weather radar SOLIDAR and a tipping bucket rain gauge network near Delft, The Netherlands, between May 1993 and April 1994. The aim of this paper is to present a thorough analysis of a climatological dataset using a high spatial (120 m and temporal (16 s resolution X-band radar. This makes it a study of the potential for high-resolution rainfall measurements with non-polarimetric X-band radar over flat terrain. An appropriate radar reflectivity – rain rate relation is derived from measurements of raindrop size distributions and compared with radar – rain gauge data. The radar calibration is assessed using a long-term comparison of rain gauge measurements with corresponding radar reflectivities as well as by analyzing the evolution of the stability of ground clutter areas over time. Three different methods for ground clutter correction as well as the effectiveness of forward and backward attenuation correction algorithms have been studied. Five individual rainfall events are discussed in detail to illustrate the strengths and weaknesses of high-resolution X-band radar and the effectiveness of the presented correction methods. X-band radar is found to be able to measure the space-time variation of rainfall at high resolution, far greater than what can be achieved by rain gauge networks or a typical operational C-band weather radar. On the other hand, SOLIDAR can suffer from receiver saturation, wet radome attenuation as well as signal loss along the path. During very strong convective situations the signal can even be lost completely. In combination with several rain gauges for quality control, high resolution X-band radar is considered to be suitable for rainfall monitoring over relatively small (urban catchments. These results offer great prospects for the new high resolution polarimetric doppler X-band radar IDRA.

Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

Science.gov (United States)

Atencia, A.; Llasat, M. C.; Garrote, L.; Mediero, L.

2010-10-01

The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.

Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

Science.gov (United States)

Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann

2016-10-01

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches

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

Using naive Bayes classifier for classification of convective rainfall ...

Indian Academy of Sciences (India)

the rainfall intensity in the convective clouds is evaluated using weather radar over the northern Algeria. The results indicate an ... tropical and extratropical regions, are dominated .... MSG is a new series of European geostationary satellites ...

Infiltration and Runoff Measurements on Steep Burned Hillslopes Using a Rainfall Simulator with Variable Rain Intensities

Science.gov (United States)

Kinner, David A.; Moody, John A.

2008-01-01

Multiple rainfall intensities were used in rainfall-simulation experiments designed to investigate the infiltration and runoff from 1-square-meter plots on burned hillslopes covered by an ash layer of varying thickness. The 1-square-meter plots were on north- and south-facing hillslopes in an area burned by the Overland fire northwest of Boulder near Jamestown on the Front Range of Colorado. A single-nozzle, wide-angle, multi-intensity rain simulator was developed to investigate the infiltration and runoff on steep (30- to 40-percent gradient) burned hillslopes covered with ash. The simulated rainfall was evaluated for spatial variability, drop size, and kinetic energy. Fourteen rainfall simulations, at three intensities (about 20 millimeters per hour [mm/h], 35 mm/h, and 50 mm/h), were conducted on four plots. Measurements during and after the simulations included runoff, rainfall, suspended-sediment concentrations, surface ash layer thickness, soil moisture, soil grain size, soil lost on ignition, and plot topography. Runoff discharge reached a steady state within 7 to 26 minutes. Steady infiltration rates with the 50-mm/h application rainfall intensity approached 20?35 mm/h. If these rates are projected to rainfall application intensities used in many studies of burned area runoff production (about 80 mm/h), the steady discharge rates are on the lower end of measurements from other studies. Experiments using multiple rainfall intensities (three) suggest that runoff begins at rainfall intensities around 20 mm/h at the 1-square-meter scale, an observation consistent with a 10-mm/h rainfall intensity threshold needed for runoff initiation that has been reported in the literature.

A scattering-based over-land rainfall retrieval algorithm for South Korea using GCOM-W1/AMSR-2 data

Science.gov (United States)

Kwon, Young-Joo; Shin, Hayan; Ban, Hyunju; Lee, Yang-Won; Park, Kyung-Ae; Cho, Jaeil; Park, No-Wook; Hong, Sungwook

2017-08-01

Heavy summer rainfall is a primary natural disaster affecting lives and properties in the Korean Peninsula. This study presents a satellite-based rainfall rate retrieval algorithm for the South Korea combining polarization-corrected temperature ( PCT) and scattering index ( SI) data from the 36.5 and 89.0 GHz channels of the Advanced microwave Scanning Radiometer 2 (AMSR-2) onboard the Global Change Observation Mission (GCOM)-W1 satellite. The coefficients for the algorithm were obtained from spatial and temporal collocation data from the AMSR-2 and groundbased automatic weather station rain gauges from 1 July - 30 August during the years, 2012-2015. There were time delays of about 25 minutes between the AMSR-2 observations and the ground raingauge measurements. A new linearly-combined rainfall retrieval algorithm focused on heavy rain for the PCT and SI was validated using ground-based rainfall observations for the South Korea from 1 July - 30 August, 2016. The validation presented PCT and SI methods showed slightly improved results for rainfall > 5 mm h-1 compared to the current ASMR-2 level 2 data. The best bias and root mean square error (RMSE) for the PCT method at AMSR-2 36.5 GHz were 2.09 mm h-1 and 7.29 mm h-1, respectively, while the current official AMSR-2 rainfall rates show a larger bias and RMSE (4.80 mm h-1 and 9.35 mm h-1, respectively). This study provides a scatteringbased over-land rainfall retrieval algorithm for South Korea affected by stationary front rain and typhoons with the advantages of the previous PCT and SI methods to be applied to a variety of spaceborne passive microwave radiometers.

Assessment of Precipitation Data Generated by GPM and TRMM Satellites

Directory of Open Access Journals (Sweden)

Luísa Carolina Silva Lelis

Full Text Available Abstract This study aimed to verify the performance of the information produced by the GPM (Global Precipitation Measurement mission and TRMM (Tropical Rainfall Measurement Mission on the eastern region of São Paulo state, based on a comparison of rainfall data from DAEE (Department of Waters and Electric Energy of São Paulo State. The comparison was done by comparing spatially aggregated information from both sources. In order to analyze the results, we measured: (1 Relative Difference, (2 BIAS and (3 Root Mean Square Error (RMSE. It was found that the relative differences were in the range of -20% to 20% for both missions. Analyzing the BIAS for both satellites it was observed that 68% of the measurements were overestimated. The highest agreement was obtained for the mesoregion of Campinas and the lowest for Araraquara. In the TRMM, the lowest RMSE values were found in the Araraquara mesoregion and the highest in Piracicaba. In the GPM the closest measured values were observed in the Piracicaba mesoregion, while the most distant values were identified in Araraquara. All the analyzes of this work demonstrated similarity between the errors generated by both satellites. New comparison studies are needed to better understand the products.

Evaluation of TRMM 3B42 V7 Rainfall Product over the Oum Er Rbia Watershed in Morocco

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Hamza Ouatiki

2017-01-01

Full Text Available In arid and semi-arid areas, rainfall is often characterized by a strong spatial and temporal variability. These environmental factors, combined with the sparsity of the measurement networks in developing countries, constitute real constraints for water resources management. In recent years, several spatial rainfall measurement sources have become available, such as TRMM data (Tropical Rainfall Measurement Mission. In this study, the TRMM 3B42 Version 7 product was evaluated using rain gauges measurements from 19 stations in the Oum-Er-Bia (OER basin located in the center of Morocco. The relevance of the TRMM product was tested by direct comparison with observations at different time scales (daily, monthly, and annual between 1998 and 2010. Results show that the satellite product provides poor estimations of rainfall at the daily time scale giving an average Pearson correlation coefficient (r of 0.2 and average Root Mean Square Error (RMSE of 10 mm. However, the accuracy of TRMM rainfall is improved when temporally averaged to monthly time scale (r of 0.8 and RMSE of 28 mm or annual time scale (r of 0.71 and RMSE of 157 mm. Moreover, improved correlation with observed data was obtained for data spatially averaged at the watershed scale. Therefore, at the monthly and annual time scales, TRMM data can be a useful source of rainfall data for water resources monitoring and management in ungauged basins in semi-arid regions.

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

Science.gov (United States)

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

2017-12-01

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

The assessment of Global Precipitation Measurement estimates over the Indian subcontinent

Science.gov (United States)

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

2017-08-01

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

Measurements of effective non-rainfall in soil with the use of time-domain reflectometry technique

Science.gov (United States)

Nakonieczna, Anna; Kafarski, Marcin; Wilczek, Andrzej; Szypłowska, Agnieszka; Skierucha, Wojciech

2014-05-01

The non-rainfall vectors are fog, dew, hoarfrost and vapour adsorption directly from the atmosphere. The measurements of the amount of water supplied to the soil due to their temporary existence are essential, because in dry areas such water uptake can exceed that of rainfall. Although several devices and methods were proposed for estimating the effective non-rainfall input into the soil, the measurement standard has not yet been established. This is mainly due to obstacles in measuring small water additions to the medium, problems with taking readings in actual soil samples and atmospheric disturbances during their course in natural environment. There still exists the need for automated devices capable of measuring water deposition on real-world soil surfaces, whose resolution is high enough to measure the non-rainfall intensity and increase rate, which are usually very low. In order to achieve the desirable resolution and accuracy of the effective non-rainfall measurements the time-domain reflectometry (TDR) technique was employed. The TDR sensor designed and made especially for the purpose was an untypical waveguide. It consisted of a base made of laminate covered with copper, which served as a bottom of a cuboidal open container in which the examined materials were placed, and a copper signal wire placed on the top of the container. The wire adhered along its entire length to the tested material in order to eliminate the formation of air gaps between the two, what enhanced the accuracy of the measurements. The tested porous materials were glass beads, rinsed sand and three soil samples, which were collected in south-eastern Poland. The diameter ranges of their constituent particles were measured with the use of the laser diffraction technique. The sensor filled with the wetted material was placed on a scale and connected to the TDR meter. The automated readings of mass and TDR time were collected simultaneously every minute. The TDR time was correlated with the

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan.

Science.gov (United States)

Tsai, Kuang-Jung; Chiang, Jie-Lun; Lee, Ming-Hsi; Chen, Yie-Ruey

2017-04-01

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan. Kuang-Jung Tsai 1, Jie-Lun Chiang 2,Ming-Hsi Lee 2, Yie-Ruey Chen 1, 1Department of Land Management and Development, Chang Jung Christian Universityt, Tainan, Taiwan. 2Department of Soil and Water Conservation, National Pingtung University of Science and Technology, Pingtung, Taiwan. ABSTRACT The accumulated rainfall amount was recorded more than 2,900mm that were brought by Morakot typhoon in August, 2009 within continuous 3 days. Very serious landslides, and sediment related disasters were induced by this heavy rainfall event. The satellite image analysis project conducted by Soil and Water Conservation Bureau after Morakot event indicated that more than 10,904 sites of landslide with total sliding area of 18,113ha were found by this project. At the same time, all severe sediment related disaster areas are also characterized based on their disaster type, scale, topography, major bedrock formations and geologic structures during the period of extremely heavy rainfall events occurred at the southern Taiwan. Characteristics and mechanism of large scale landslide are collected on the basis of the field investigation technology integrated with GPS/GIS/RS technique. In order to decrease the risk of large scale landslides on slope land, the strategy of slope land conservation, and critical rainfall database should be set up and executed as soon as possible. Meanwhile, study on the establishment of critical rainfall value used for predicting large scale landslides induced by heavy rainfall become an important issue which was seriously concerned by the government and all people live in Taiwan. The mechanism of large scale landslide, rainfall frequency analysis ,sediment budge estimation and river hydraulic analysis under the condition of extremely climate change during the past 10 years would be seriously concerned and recognized as a required issue by this

Incorporation of Satellite Data and Uncertainty in a Nationwide Groundwater Recharge Model in New Zealand

Directory of Open Access Journals (Sweden)

Rogier Westerhoff

2018-01-01

collaborative research associated with the NGRM model include: improvement of rainfall-runoff models, establishment of snowmelt and river recharge modules, further improvement of estimates of rainfall and AET, and satellite-derived AET in irrigated areas. Importantly, the quantification of uncertainty, which should be associated with all future models, should give further impetus to field measurements of rainfall recharge for the purpose of model calibration.

Initial results of centralized autonomous orbit determination of the new-generation BDS satellites with inter-satellite link measurements

Science.gov (United States)

Tang, Chengpan; Hu, Xiaogong; Zhou, Shanshi; Liu, Li; Pan, Junyang; Chen, Liucheng; Guo, Rui; Zhu, Lingfeng; Hu, Guangming; Li, Xiaojie; He, Feng; Chang, Zhiqiao

2018-01-01

Autonomous orbit determination is the ability of navigation satellites to estimate the orbit parameters on-board using inter-satellite link (ISL) measurements. This study mainly focuses on data processing of the ISL measurements as a new measurement type and its application on the centralized autonomous orbit determination of the new-generation Beidou navigation satellite system satellites for the first time. The ISL measurements are dual one-way measurements that follow a time division multiple access (TDMA) structure. The ranging error of the ISL measurements is less than 0.25 ns. This paper proposes a derivation approach to the satellite clock offsets and the geometric distances from TDMA dual one-way measurements without a loss of accuracy. The derived clock offsets are used for time synchronization, and the derived geometry distances are used for autonomous orbit determination. The clock offsets from the ISL measurements are consistent with the L-band two-way satellite, and time-frequency transfer clock measurements and the detrended residuals vary within 0.5 ns. The centralized autonomous orbit determination is conducted in a batch mode on a ground-capable server for the feasibility study. Constant hardware delays are present in the geometric distances and become the largest source of error in the autonomous orbit determination. Therefore, the hardware delays are estimated simultaneously with the satellite orbits. To avoid uncertainties in the constellation orientation, a ground anchor station that "observes" the satellites with on-board ISL payloads is introduced into the orbit determination. The root-mean-square values of orbit determination residuals are within 10.0 cm, and the standard deviation of the estimated ISL hardware delays is within 0.2 ns. The accuracy of the autonomous orbits is evaluated by analysis of overlap comparison and the satellite laser ranging (SLR) residuals and is compared with the accuracy of the L-band orbits. The results indicate

An Experimental System for a Global Flood Prediction: From Satellite Precipitation Data to a Flood Inundation Map

Science.gov (United States)

Adler, Robert

2007-01-01

Floods impact more people globally than any other type of natural disaster. It has been established by experience that the most effective means to reduce the property damage and life loss caused by floods is the development of flood early warning systems. However, advances for such a system have been constrained by the difficulty in estimating rainfall continuously over space (catchment-. national-, continental-. or even global-scale areas) and time (hourly to daily). Particularly, insufficient in situ data, long delay in data transmission and absence of real-time data sharing agreements in many trans-boundary basins hamper the development of a real-time system at the regional to global scale. In many countries around the world, particularly in the tropics where rainfall and flooding co-exist in abundance, satellite-based precipitation estimation may be the best source of rainfall data for those data scarce (ungauged) areas and trans-boundary basins. Satellite remote sensing data acquired and processed in real time can now provide the space-time information on rainfall fluxes needed to monitor severe flood events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models, which can be parameterized by a tailored geospatial database. An example that is a key to this progress is NASA's contribution to the Tropical Rainfall Measuring Mission (TRMM), launched in November 1997. Hence, in an effort to evolve toward a more hydrologically-relevant flood alert system, this talk articulates a module-structured framework for quasi-global flood potential naming, that is 'up to date' with the state of the art on satellite rainfall estimation and the improved geospatial datasets. The system is modular in design with the flexibility that permits changes in the model structure and in the choice of components. Four major components included in the system are: 1) multi-satellite precipitation estimation; 2) characterization of

Urban Run-off Volumes Dependency on Rainfall Measurement Method

DEFF Research Database (Denmark)

Pedersen, L.; Jensen, N. E.; Rasmussen, Michael R.

2005-01-01

Urban run-off is characterized with fast response since the large surface run-off in the catchments responds immediately to variations in the rainfall. Modeling such type of catchments is most often done with the input from very few rain gauges, but the large variation in rainfall over small areas...... resolutions and single gauge rainfall was fed to a MOUSE run-off model. The flow and total volume over the event is evaluated....

Evaluation of the Performance of Three Satellite Precipitation Products over Africa

Directory of Open Access Journals (Sweden)

Aleix Serrat-Capdevila

2016-10-01

Full Text Available We present an evaluation of daily estimates from three near real-time quasi-global Satellite Precipitation Products—Tropical Rainfall Measuring Mission (TRMM Multi-satellite Precipitation Analysis (TMPA, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, and Climate Prediction Center (CPC Morphing Technique (CMORPH—over the African continent, using the Global Precipitation Climatology Project one Degree Day (GPCP-1dd as a reference dataset for years 2001 to 2013. Different types of errors are characterized for each season as a function of spatial classifications (latitudinal bands, climatic zones and topography and in relationship with the main rain-producing mechanisms in the continent: the Intertropical Convergence Zone (ITCZ and the East African Monsoon. A bias correction of the satellite estimates is applied using a probability density function (pdf matching approach, with a bias analysis as a function of rain intensity, season and latitude. The effects of bias correction on different error terms are analyzed, showing an almost elimination of the mean and variance terms in most of the cases. While raw estimates of TMPA show higher efficiency, all products have similar efficiencies after bias correction. PERSIANN consistently shows the smallest median errors when it correctly detects precipitation events. The areas with smallest relative errors and other performance measures follow the position of the ITCZ oscillating seasonally over the equator, illustrating the close relationship between satellite estimates and rainfall regime.

Entropy of stable seasonal rainfall distribution in Kelantan

Science.gov (United States)

Azman, Muhammad Az-zuhri; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Radi, Noor Fadhilah Ahmad

2017-05-01

Investigating the rainfall variability is vital for any planning and management in many fields related to water resources. Climate change can gives an impact of water availability and may aggravate water scarcity in the future. Two statistics measurements which have been used by many researchers to measure the rainfall variability are variance and coefficient of variation. However, these two measurements are insufficient since rainfall distribution in Malaysia especially in the East Coast of Peninsular Malaysia is not symmetric instead it is positively skewed. In this study, the entropy concept is used as a tool to measure the seasonal rainfall variability in Kelantan and ten rainfall stations were selected. In previous studies, entropy of stable rainfall (ESR) and apportionment entropy (AE) were used to describe the rainfall amount variability during years for Australian rainfall data. In this study, the entropy of stable seasonal rainfall (ESSR) is suggested to model rainfall amount variability during northeast monsoon (NEM) and southwest monsoon (SWM) seasons in Kelantan. The ESSR is defined to measure the long-term average seasonal rainfall amount variability within a given year (1960-2012). On the other hand, the AE measures the rainfall amounts variability across the months. The results of ESSR and AE values show that stations in east coastline are more variable as compared to other stations inland for Kelantan rainfall. The contour maps of ESSR for Kelantan rainfall stations are also presented.

Aerosol and rainfall variability over the Indian monsoon region: distributions, trends and coupling

Directory of Open Access Journals (Sweden)

R. Gautam

2009-09-01

Full Text Available Aerosol solar absorption over the Indian monsoon region has a potential role of modulating the monsoon circulation and rainfall distribution as suggested by recent studies based on model simulations. Prior to the onset of the monsoon, northern India is influenced by significant dust transport that constitutes the bulk of the regional aerosol loading over the Gangetic-Himalayan region. In this paper, a multi-sensor characterization of the increasing pre-monsoon aerosol loading over northern India, in terms of their spatial, temporal and vertical distribution is presented. Aerosol transport from the northwestern arid regions into the Indo-Gangetic Plains and over the foothills of the Himalayas is found to be vertically extended to elevated altitudes (up to 5 km as observed from the space-borne lidar measurements (CALIPSO. In relation with the enhanced pre-monsoon aerosol loading and the associated solar absorption effects on tropospheric temperature anomalies, this paper investigates the monsoon rainfall variability over India in recent past decades from an observational viewpoint. It is found that the early summer monsoon rainfall over India is on the rise since 1950s, as indicated by historical rainfall data, with over 20% increase for the period 1950–2004. This large sustained increase in the early summer rainfall is led by the observed strengthening of the pre-monsoon tropospheric land-sea thermal gradient over the Indian monsoon region as indicated by microwave satellite measurements (MSU of tropospheric temperatures from 1979–2007. Combined analysis of changes in tropospheric temperatures and summer monsoon rainfall in the past three decades, suggest a future possibility of an emerging rainfall pattern of a wetter monsoon over South Asia in early summer followed by a drier period.

A laboratory assessment of the measurement accuracy of weighing type rainfall intensity gauges

Science.gov (United States)

Colli, M.; Chan, P. W.; Lanza, L. G.; La Barbera, P.

2012-04-01

In recent years the WMO Commission for Instruments and Methods of Observation (CIMO) fostered noticeable advancements in the accuracy of precipitation measurement issue by providing recommendations on the standardization of equipment and exposure, instrument calibration and data correction as a consequence of various comparative campaigns involving manufacturers and national meteorological services from the participating countries (Lanza et al., 2005; Vuerich et al., 2009). Extreme events analysis is proven to be highly affected by the on-site RI measurement accuracy (see e.g. Molini et al., 2004) and the time resolution of the available RI series certainly constitutes another key-factor in constructing hyetographs that are representative of real rain events. The OTT Pluvio2 weighing gauge (WG) and the GEONOR T-200 vibrating-wire precipitation gauge demonstrated very good performance under previous constant flow rate calibration efforts (Lanza et al., 2005). Although WGs do provide better performance than more traditional Tipping Bucket Rain gauges (TBR) under continuous and constant reference intensity, dynamic effects seem to affect the accuracy of WG measurements under real world/time varying rainfall conditions (Vuerich et al., 2009). The most relevant is due to the response time of the acquisition system and the derived systematic delay of the instrument in assessing the exact weight of the bin containing cumulated precipitation. This delay assumes a relevant role in case high resolution rain intensity time series are sought from the instrument, as is the case of many hydrologic and meteo-climatic applications. This work reports the laboratory evaluation of Pluvio2 and T-200 rainfall intensity measurements accuracy. Tests are carried out by simulating different artificial precipitation events, namely non-stationary rainfall intensity, using a highly accurate dynamic rainfall generator. Time series measured by an Ogawa drop counter (DC) at a field test site

The wildgeographer avatar shows how to measure soil erosion rates by means of a rainfall simulator

Science.gov (United States)

Cerdà, Artemi; González Pelayo, Óscar; Pereira, Paulo; Novara, Agata; Iserloh, Thomas; Prosdocimi, Massimo

2015-04-01

This contribution to the immersed worlds wish to develop the avatar that will teach the students and other scientists how to develop measurements of soil erosion, surface runoff and wetting fronts by means of simulated rainfall experiments. Rainfall simulation is a well established and knows methodology to measure the soil erosion rates and soil hydrology under controlled conditions (Cerdà 1998a; Cerdà, 1998b; Cerdà and Jurgensen, 2011; Dunkerley, 2012; Iserloh et al., 2012; Iserloh et al., 2013; Ziadat and Taimeh, 2013; Butzen et al., 2014). However, is a method that requires a long training and expertise to avoid mismanagement and mistaken. To use and avatar can help in the teaching of the technique and the dissemination of the findings. This contribution will show to other avatars how to develop an experiment with simulated rainfall and will help to take the right decision in the design of the experiments. Following the main parts of the experiments and measurements the Wildgeographer avatar must develop: 1. Determine the objectives and decide which rainfall intensity and distribution, and which plot size to be used. Choose between a laboratory or a field rainfall simulation. 2. Design of the rainfall simulator to achieve the objectives: type of rainfall simulator (sprayer or drop former) and calibrate. 3. The experiments are carried out. 4. The results are show. Acknowledgements To the "Ministerio de Economía and Competitividad" of Spanish Government for finance the POSTFIRE project (CGL2013- 47862-C2-1-R). The research projects GL2008-02879/BTE, LEDDRA 243857 and PREVENTING AND REMEDIATING DEGRADATION OF SOILS IN EUROPE THROUGH LAND CARE (RECARE)FP7-ENV-2013- supported this research. References Butzen, V., Seeger, M., Wirtz, S., Huemann, M., Mueller, C., Casper, M., Ries, J. B. 2014. Quantification of Hortonian overland flow generation and soil erosion in a Central European low mountain range using rainfall experiments. Catena, 113, 202-212. Cerdà, A

Weekend Effect" in Summertime U.S. Rainfall: Evidence for Midweek Intensification of Storms by Pollution

Science.gov (United States)

Bell, Thomas L.; Rosenfeld, Daniel; Kim, Kyu-Myong; Hahnenberger, Maura

2006-01-01

Persistent and strong dependence of rain rate on the day of the week has been found in Tropical Rainfall Measuring Mission (TRMM) satellite estimates of summer afternoon rainfall over the southeast U.S. and the nearby Atlantic from 1998 to 2005. Midweek (Tue-Thu) rain rates and rain area appear to increase over land, and this increase is accompanied by a corresponding diminution of rainfall over nearby waters. Reanalysis data from atmospheric models, suggest that there is a corresponding weekly variation in atmospheric winds consistent with the changes in rainfall. These variations are almost certainly caused by weekly variations in human activity. The most likely cause of the observed changes in rainfall is the well documented weekly variation in atmospheric pollution. Particulate pollution is highest in the middle of the week. Considerable observational and modeling evidence has accumulated concerning the effects of aerosols on precipitation. Most of this evidence relates to the suppression of precipitation by aerosols, but it has been argued that storms in highly unstable moist environments can be invigorated by aerosols, and some modeling studies seem to confirm this. The strong weekly cycle in rainfall observed over the southeast U.S. along with what appears to be dynamical suppression of rainfall over the nearby Atlantic, and the lack of an observable cycle over the southwest U.S., are consistent with this theory.

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.

Satellite-Based Precipitation Datasets

Science.gov (United States)

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

2017-12-01

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

Positive response of Indian summer rainfall to Middle East dust

KAUST Repository

Jin, Qinjian

2014-06-02

Using observational and reanalyses data, we investigated the impact of dust aerosols over the Middle East and the Arabian Sea (AS) on the Indian summer monsoon (ISM) rainfall. Satellite and aerosol reanalysis data show extremely heavy aerosol loading, mainly mineral dust, over the Middle East and AS during the ISM season. Multivariate empirical orthogonal function analyses suggest an aerosol-monsoon connection. This connection may be attributed to dust-induced atmospheric heating centered over the Iranian Plateau (IP), which enhances the meridional thermal contrast and strengthens the ISM circulation and rainfall. The enhanced circulation further transports more dust to the AS and IP, heating the atmosphere (positive feedback). The aerosols over the AS and the Arabian Peninsula have a significant correlation with rainfall over central and eastern India about 2 weeks later. This finding highlights the nonlocal radiative effect of dust on the ISM circulation and rainfall and may improve ISM rainfall forecasts. © 2014. American Geophysical Union. All Rights Reserved.

Congo Basin rainfall climatology: can we believe the climate models?

Science.gov (United States)

Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M; Moufouma-Okia, Wilfran

2013-01-01

The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models.

Positive response of Indian summer rainfall to Middle East dust

KAUST Repository

Jin, Qinjian; Wei, Jiangfeng; Yang, Zong-Liang

2014-01-01

Using observational and reanalyses data, we investigated the impact of dust aerosols over the Middle East and the Arabian Sea (AS) on the Indian summer monsoon (ISM) rainfall. Satellite and aerosol reanalysis data show extremely heavy aerosol loading, mainly mineral dust, over the Middle East and AS during the ISM season. Multivariate empirical orthogonal function analyses suggest an aerosol-monsoon connection. This connection may be attributed to dust-induced atmospheric heating centered over the Iranian Plateau (IP), which enhances the meridional thermal contrast and strengthens the ISM circulation and rainfall. The enhanced circulation further transports more dust to the AS and IP, heating the atmosphere (positive feedback). The aerosols over the AS and the Arabian Peninsula have a significant correlation with rainfall over central and eastern India about 2 weeks later. This finding highlights the nonlocal radiative effect of dust on the ISM circulation and rainfall and may improve ISM rainfall forecasts. © 2014. American Geophysical Union. All Rights Reserved.

Monsoon onset over Kerala and pre monsoon rainfall peak

Digital Repository Service at National Institute of Oceanography (India)

RameshKumar, M.R.; Shenoi, S.S.C.; Shankar, D.

and the monsoon onset date over Kerala was found to be 0.72, which was statistically significant. Thus, as is felt that the pre monsoon rainfall estimate from the satellite data can be used for predicting the monsoon onset over Kerala coast. The results...

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

NARCIS (Netherlands)

Kimani, M.W.; Hoedjes, Johannes Cornelis Bernardus; Su, Z.

2017-01-01

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.

Performance and efficiency of geotextile-supported erosion control measures during simulated rainfall events

Science.gov (United States)

Obriejetan, Michael; Rauch, Hans Peter; Florineth, Florin

2013-04-01

Erosion control systems consisting of technical and biological components are widely accepted and proven to work well if installed properly with regard to site-specific parameters. A wide range of implementation measures for this specific protection purpose is existent and new, in particular technical solutions are constantly introduced into the market. Nevertheless, especially vegetation aspects of erosion control measures are frequently disregarded and should be considered enhanced against the backdrop of the development and realization of adaptation strategies in an altering environment due to climate change associated effects. Technical auxiliaries such as geotextiles typically used for slope protection (nettings, blankets, turf reinforcement mats etc.) address specific features and due to structural and material diversity, differing effects on sediment yield, surface runoff and vegetational development seem evident. Nevertheless there is a knowledge gap concerning the mutual interaction processes between technical and biological components respectively specific comparable data on erosion-reducing effects of technical-biological erosion protection systems are insufficient. In this context, an experimental arrangement was set up to study the correlated influences of geotextiles and vegetation and determine its (combined) effects on surface runoff and soil loss during simulated heavy rainfall events. Sowing vessels serve as testing facilities which are filled with top soil under application of various organic and synthetic geotextiles and by using a reliable drought resistant seed mixture. Regular vegetational monitoring as well as two rainfall simulation runs with four repetitions of each variant were conducted. Therefore a portable rainfall simulator with standardized rainfall intensity of 240 mm h-1 and three minute rainfall duration was used to stress these systems on different stages of plant development at an inclination of 30 degrees. First results show

Multiple data fusion for rainfall estimation using a NARX-based recurrent neural network – the development of the REIINN model

International Nuclear Information System (INIS)

Ang, M R C O; Gonzalez, R M; Castro, P P M

2014-01-01

Rainfall, one of the important elements of the hydrologic cycle, is also the most difficult to model. Thus, accurate rainfall estimation is necessary especially in localized catchment areas where variability of rainfall is extremely high. Moreover, early warning of severe rainfall through timely and accurate estimation and forecasting could help prevent disasters from flooding. This paper presents the development of two rainfall estimation models that utilize a NARX-based neural network architecture namely: REIINN 1 and REIINN 2. These REIINN models, or Rainfall Estimation by Information Integration using Neural Networks, were trained using MTSAT cloud-top temperature (CTT) images and rainfall rates from the combined rain gauge and TMPA 3B40RT datasets. Model performance was assessed using two metrics – root mean square error (RMSE) and correlation coefficient (R). REIINN 1 yielded an RMSE of 8.1423 mm/3h and an overall R of 0.74652 while REIINN 2 yielded an RMSE of 5.2303 and an overall R of 0.90373. The results, especially that of REIINN 2, are very promising for satellite-based rainfall estimation in a catchment scale. It is believed that model performance and accuracy will greatly improve with a denser and more spatially distributed in-situ rainfall measurements to calibrate the model with. The models proved the viability of using remote sensing images, with their good spatial coverage, near real time availability, and relatively inexpensive to acquire, as an alternative source for rainfall estimation to complement existing ground-based measurements

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.

Dry/Wet Conditions Monitoring Based on TRMM Rainfall Data and Its Reliability Validation over Poyang Lake Basin, China

Directory of Open Access Journals (Sweden)

Xianghu Li

2013-11-01

Full Text Available Local dry/wet conditions are of great concern in regional water resource and floods/droughts disaster risk management. Satellite-based precipitation products have greatly improved their accuracy and applicability and are expected to offer an alternative to ground rain gauges data. This paper investigated the capability of Tropical Rainfall Measuring Mission (TRMM rainfall data for monitoring the temporal and spatial variation of dry/wet conditions in Poyang Lake basin during 1998–2010, and validated its reliability with rain gauges data from 14 national meteorological stations in the basin. The results show that: (1 the daily TRMM rainfall data does not describe the occurrence and contribution rates of precipitation accurately, but monthly TRMM data have a good linear relationship with rain gauges rainfall data; (2 both the Z index and Standardized Precipitation Index (SPI based on monthly TRMM rainfall data oscillate around zero and show a consistent interannual variability as compared with rain gauges data; (3 the spatial pattern of moisture status, either in dry months or wet months, based on both the Z index and SPI using TRMM data, agree with the observed rainfall. In conclusion, the monthly TRMM rainfall data can be used for monitoring the variation and spatial distribution of dry/wet conditions in Poyang Lake basin.

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 Study of a Super Low Altitude Satellite

Science.gov (United States)

Noda, Atsushi; Homma, Masanori; Utashima, Masayoshi

This paper reports the result of a study for super low altitude satellite. The altitude of this satellite's orbit is lower than ever. The altitude of a conventional earth observing satellite is generally around from 600km to 900km. The lowest altitude of earth observing satellite launched in Japan was 350km; the Tropical Rainfall Measuring Mission (TRMM). By comparison, the satellite reported in this paper is much lower than that and it is planned to orbit below 200km. Furthermore, the duration of the flight planned is more than two years. Any satellite in the world has not achieved to keep such a low altitude that long term. The satellite in such a low orbit drops quickly because of the strong air drag. Our satellite will cancel the air drag effect by ion engine thrust. To realize this idea, a drag-free system will be applied. This usually leads a complicated and expensive satellite system. We, however, succeeded in finding a robust control law for a simple system even under the unpredictable change of air drag. When the altitude of the satellite is lowered successfully, the spatial resolution of an optical sensor can be highly improved. If a SAR is equipped with the satellite, it enables the drastic reduction of electric power consumption and the fabulous spatial resolution improvement at the same time.

Feasibility of High-Resolution Soil Erosion Measurements by Means of Rainfall Simulations and SfM Photogrammetry

Directory of Open Access Journals (Sweden)

Phoebe Hänsel

2016-11-01

Full Text Available The silty soils of the intensively used agricultural landscape of the Saxon loess province, eastern Germany, are very prone to soil erosion, mainly caused by water erosion. Rainfall simulations, and also increasingly structure-from-motion (SfM photogrammetry, are used as methods in soil erosion research not only to assess soil erosion by water, but also to quantify soil loss. This study aims to validate SfM photogrammetry determined soil loss estimations with rainfall simulations measurements. Rainfall simulations were performed at three agricultural sites in central Saxony. Besides the measured data runoff and soil loss by sampling (in mm, terrestrial images were taken from the plots with digital cameras before and after the rainfall simulation. Subsequently, SfM photogrammetry was used to reconstruct soil surface changes due to soil erosion in terms of high resolution digital elevation models (DEMs for the pre- and post-event (resolution 1 × 1 mm. By multi-temporal change detection, the digital elevation model of difference (DoD and an averaged soil loss (in mm is received, which was compared to the soil loss by sampling. Soil loss by DoD was higher than soil loss by sampling. The method of SfM photogrammetry-determined soil loss estimations also include a comparison of three different ground control point (GCP approaches, revealing that the most complex one delivers the most reliable soil loss by DoD. Additionally, soil bulk density changes and splash erosion beyond the plot were measured during the rainfall simulation experiments in order to separate these processes and associated surface changes from the soil loss by DoD. Furthermore, splash was negligibly small, whereas higher soil densities after the rainfall simulations indicated soil compaction. By means of calculated soil surface changes due to soil compaction, the soil loss by DoD achieved approximately the same value as the soil loss by rainfall simulation.

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

Online Visualization and Analysis of Global Half-Hourly Infrared Satellite Data

Science.gov (United States)

Liu, Zhong; Ostrenga, Dana; Leptoukh, Gregory

2011-01-01

nfrared (IR) images (approximately 11-micron channel) recorded by satellite sensors have been widely used in weather forecasting, research, and classroom education since the Nimbus program. Unlike visible images, IR imagery can reveal cloud features without sunlight illumination; therefore, they can be used to monitor weather phenomena day and night. With geostationary satellites deployed around the globe, it is possible to monitor weather events 24/7 at a temporal resolution that polar-orbiting satellites cannot achieve at the present time. When IR data from multiple geostationary satellites are merged to form a single product--also known as a merged product--it allows for observing weather on a global scale. Its high temporal resolution (e.g., every half hour) also makes it an ideal ancillary dataset for supporting other satellite missions, such as the Tropical Rainfall Measuring Mission (TRMM), etc., by providing additional background information about weather system evolution.

Evidence of Urban Precipitation Anomalies from Satellite and Ground-Based Measurements

Science.gov (United States)

Shepherd, J. Marshall; Manyin, M.; Negri, Andrew

2004-01-01

Urbanization is one of the extreme cases of land use change. Most of world's population has moved to urban areas. Although currently only 1.2% of the land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in the near future. It is estimated that by the year 2025, 60% of the world's population will live in cities. Human activity in urban environments also alters weather and climate processes. However, our understanding of urbanization on the total Earth-weather-climate system is incomplete. Recent literature continues to provide evidence that anomalies in precipitation exist over and downwind of major cities. Current and future research efforts are actively seeking to verify these literature findings and understand potential cause-effect relationships. The novelty of this study is that it utilizes rainfall data from multiple satellite data sources (e.g. TRMM precipitation radar, TRMM-geosynchronous-rain gauge merged product, and SSM/I) and ground-based measurements to identify spatial anomalies and temporal trends in precipitation for cities around the world. Early results will be presented and placed within the context of weather prediction, climate assessment, and societal applications.

Remote sensing-based characterization of rainfall during atmospheric rivers over the central United States

Science.gov (United States)

Nayak, Munir A.; Villarini, Gabriele

2018-01-01

Atmospheric rivers (ARs) play a central role in the hydrology and hydroclimatology of the central United States. More than 25% of the annual rainfall is associated with ARs over much of this region, with many large flood events tied to their occurrence. Despite the relevance of these storms for flood hydrology and water budget, the characteristics of rainfall associated with ARs over the central United has not been investigated thus far. This study fills this major scientific gap by describing the rainfall during ARs over the central United States using five remote sensing-based precipitation products over a 12-year study period. The products we consider are: Stage IV, Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA, both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); the CPC MORPHing Technique (CMORPH). As part of the study, we evaluate these products against a rain gauge-based dataset using both graphical- and metrics-based diagnostics. Based on our analyses, Stage IV is found to better reproduce the reference data. Hence, we use it for the characterization of rainfall in ARs. Most of the AR-rainfall is located in a narrow region within ∼150 km on both sides of the AR major axis. In this region, rainfall has a pronounced positive relationship with the magnitude of the water vapor transport. Moreover, we have also identified a consistent increase in rainfall intensity with duration (or persistence) of AR conditions. However, there is not a strong indication of diurnal variability in AR rainfall. These results can be directly used in developing flood protection strategies during ARs. Further, weather prediction agencies can benefit from the results of this study to achieve higher skill of resolving precipitation processes in their models.

Toward Continental-scale Rainfall Monitoring Using Commercial Microwave Links From Cellular Communication Networks

Science.gov (United States)

Uijlenhoet, R.; Leijnse, H.; Overeem, A.

2017-12-01

Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal's attenuation between transmitter and receiver. We have previously shown how one such a network can be used to retrieve the space-time dynamics of rainfall for an entire country (The Netherlands, ˜35,500 km2), based on an unprecedented number of links (˜2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrated the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. The presentation will focus on the potential for upscaling this technique to continental-scale rainfall monitoring in Europe. In addition, several examples of recent applications of this technique on other continents (South America, Africa, Asia and Australia) will be given.

The Impact of Model and Rainfall Forcing Errors on Characterizing Soil Moisture Uncertainty in Land Surface Modeling

Science.gov (United States)

Maggioni, V.; Anagnostou, E. N.; Reichle, R. H.

2013-01-01

The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.

Tropical Rainfall Measuring Mission: Monitoring the Global Tropics for 3 Years and Beyond. 1.1

Science.gov (United States)

Shepherd, Marshall; Starr, David OC. (Technical Monitor)

2001-01-01

The Tropical Rainfall Measuring Mission (TRMM) was launched in November 1997 as a joint U.S.-Japanese mission to advance understanding of the global energy and water cycle by providing distributions of rainfall and latent heating over the global tropics. As a part of NASA's Earth System Enterprise, TRMM seeks to understand the mechanisms through which changes in tropical rainfall influence global circulation. Additionally, a goal is to improve the ability to model these processes in order to predict global circulations and rainfall variability at monthly and longer time scales. Such understanding has implications for assessing climate processes related to El Nino/La Nina and Global Warming. TRMM has also provided unexpected and exciting new knowledge and applications in areas related to hurricane monitoring, lightning, pollution, hydrology, and other areas. This CD-ROM includes a self-contained PowerPoint presentation that provides an overview of TRMM and significant science results; a set of data movies or animation; and listings of current TRMM-related publications in the literature.

Land-mobile satellite excess path loss measurements

Science.gov (United States)

Hess, G. C.

1980-05-01

An experiment conducted with the ATS-6 satellite to determine the additional path loss over free-space loss experienced by land-mobile communication links is described. This excess path loss is measured as a function of 1) local environment, 2) vehicle heading, 3) link frequency, 4) satellite elevation angle, and 5) street side. A statistical description of excess loss developed from the data shows that the first two parameters dominate. Excess path loss on the order of 25 dB is typical in urban situations, but decreases to under 10 dB in suburban/rural areas. Spaced antenna selection diversity is found to provide only a slight decrease (4 dB, typically) in the urban excess path loss observed. Level crossing rates are depressed in satellite links relative to those of Rayleigh-faded terrestrial links, but increases in average fade durations tend to offset that advantage. The measurements show that the excess path loss difference between 860-MHz links and 1550-MHz links is generally negligible.

Global Lightning Climatology from the Tropical Rainfall Measuring Mission (TRMM), Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD)

Science.gov (United States)

Cecil, Daniel J.; Buechler, Dennis E.; Blakeslee, Richard J.

2015-01-01

The Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) has been collecting observations of total lightning in the global tropics and subtropics (roughly 38 deg S - 38 deg N) since December 1997. A similar instrument, the Optical Transient Detector, operated from 1995-2000 on another low earth orbit satellite that also saw high latitudes. Lightning data from these instruments have been used to create gridded climatologies and time series of lightning flash rate. These include a 0.5 deg resolution global annual climatology, and lower resolution products describing the annual cycle and the diurnal cycle. These products are updated annually. Results from the update through 2013 will be shown at the conference. The gridded products are publicly available for download. Descriptions of how each product can be used will be discussed, including strengths, weaknesses, and caveats about the smoothing and sampling used in various products.

Monitoring mass changes in the Volta River basin using GRACE satellite gravity and TRMM precipitation

Directory of Open Access Journals (Sweden)

Vagner G. Ferreira

Full Text Available GRACE satellite gravity data was used to estimate mass changes within the Volta River basin in West African for the period of January, 2005 to December, 2010. We also used the precipitation data from the Tropical Rainfall Measurement Mission (TRMM to determine relative contributions source to the seasonal hydrological balance within the Volta River basin. We found out that the seasonal mass change tends to be detected by GRACE for periods from 1 month in the south to 4 months in the north of the basin after the rainfall events. The results suggested a significant gain in water storage in the basin at reference epoch 2007.5 and a dominant annual cycle for the period under consideration for both in the mass changes and rainfall time series. However, there was a low correlation between mass changes and rainfall implying that there must be other processes which cause mass changes without rainfall in the upstream of the Volta River basin.

Pb-210 deposition measured in rainfall in Sao Paulo, SP-Brazil

Energy Technology Data Exchange (ETDEWEB)

Damatto, Sandra R.; Frujuele, Jonatan V.; Souza, Joseilton M.; Santos, Levi F., E-mail: damatto@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil). Lab. de Radiometria Ambiental

2013-07-01

Pb-210 (T{sub 1/2} = 22.3 y), a natural radionuclide from U-238 serie can be found in the atmosphere, as a product of {sup 222}Rn decay that emanates from the ground, where its atoms become rapidly fixed to aerosols and return to the earth as dry fallout or are washed out in the rain. This natural radionuclide has been widely used as an atmospheric tracer, to determine the aerosol residence time as well as chronometers in the environment. Pb-210 was measured during a period of two years, 2011 to 2013, in samples of rainfall in all the rainy events that occurred at the Instituto de Pesquisas Energeticas e Nucleares (IPEN) campus (23 deg 33’59.24” S - 46 deg 44’15.63” O at 760 m above sea level) which is located in the city of Sao Paulo, in the state of Sao Paulo, Brazil. Pb-210 concentration was measured in a total of 123 rainy events by beta gross counting in a low background gas flow proportional detector, after radiochemistry procedure. The results obtained were correlated to seasons and rainfall. The concentrations of {sup 210}Pb in rainfall varied from the minimum detectable activity, 4.9 mBq L{sup -1} to 1408± 43 mBq L{sup -1}. The highest concentrations were obtained in the months of winter and the lowest in summer. The monthly depositional flux of {sup 210}Pb, varied from 4.03 Bq m{sup -2} month{sup -1} to 46.4 Bq m{sup -2} month{sup -1}presenting a strong correlation with the amount of precipitation and hence showing seasonal trends. (author)

The possible direct use of satellite radiance measurements by the Atmospheric Radiation Measurement Program

International Nuclear Information System (INIS)

1993-03-01

The Atmospheric Radiation Measurement (ARM) Program is a major research program initiated by the Department of Energy to improve our understanding of radiative and cloud processes critical to predicting the Earth's climate and its changes. Central to this concept is the use of four to six intensively instrumented sites for long-term study and characterization of the processes of interest. The instrumentation suites will include ground-based, high-accuracy radiometers for measuring the short and longwave surface flux, as well as an extensive set of ground-and air-based instrumentation for characterizing the intervening atmospheric column. Satellite-based measurements are expected to play a very important role in providing top-of-the-atmosphere measurements. In this study, we examine the possibility of comparing ARM outputs directly with satellite measurements, thereby ensuring the independence of these two important data sets. Thus we focused on what do satellites really measure and how well do they measure it. On what can we do about the general lack of adequate visible channel calibration. On what is the best way for ARM to obtain near-real-time access to this unprocessed data. And on what is the optimum way for ARM to make use of satellite data

Study on the association of green house gas (CO2) with monsoon rainfall using AIRS and TRMM satellite observations

Science.gov (United States)

Singh, R. B.; Janmaijaya, M.; Dhaka, S. K.; Kumar, V.

Monsoon water cycle is the lifeline to over 60 per cent of the world's population. Throughout history, the monsoon-related calamities of droughts and floods have determined the life pattern of people. The association of Green House Gases (GHGs) particularly Carbon dioxide (CO2) with monsoon has been greatly debated amongst the scientific community in the past. The effect of CO2 on the monsoon rainfall over the Indian-Indonesian region (8-30°N, 65°-100°E) is being investigated using satellite data. The correlation coefficient (Rxy) between CO2 and monsoon is analysed. The Rxy is not significantly positive over a greater part of the study region, except a few regions. The inter-annual anomalies of CO2 is identified for playing a secondary role to influencing monsoon while other phenomenon like ENSO might be exerting a much greater influence.

Rainfall Downscaling Conditional on Upper-air Variables: Assessing Rainfall Statistics in a Changing Climate

Science.gov (United States)

Langousis, Andreas; Deidda, Roberto; Marrocu, Marino; Kaleris, Vassilios

2014-05-01

Due to its intermittent and highly variable character, and the modeling parameterizations used, precipitation is one of the least well reproduced hydrologic variables by both Global Climate Models (GCMs) and Regional Climate Models (RCMs). This is especially the case at a regional level (where hydrologic risks are assessed) and at small temporal scales (e.g. daily) used to run hydrologic models. In an effort to remedy those shortcomings and assess the effect of climate change on rainfall statistics at hydrologically relevant scales, Langousis and Kaleris (2013) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables. The developed downscaling scheme was tested using atmospheric data from the ERA-Interim archive (http://www.ecmwf.int/research/era/do/get/index), and daily rainfall measurements from western Greece, and was proved capable of reproducing several statistical properties of actual rainfall records, at both annual and seasonal levels. This was done solely by conditioning rainfall simulation on a vector of atmospheric predictors, properly selected to reflect the relative influence of upper-air variables on ground-level rainfall statistics. In this study, we apply the developed framework for conditional rainfall simulation using atmospheric data from different GCM/RCM combinations. This is done using atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com), and daily rainfall measurements for an intermediate-sized catchment in Italy; i.e. the Flumendosa catchment. Since GCM/RCM products are suited to reproduce the local climatology in a statistical sense (i.e. in terms of relative frequencies), rather than ensuring a one-to-one temporal correspondence between observed and simulated fields (i.e. as is the case for ERA-interim reanalysis data), we proceed in three steps: a) we use statistical tools to establish a linkage between ERA-Interim upper-air atmospheric forecasts and

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.

Variability of rainfall over small areas

Science.gov (United States)

Runnels, R. C.

1983-01-01

A preliminary investigation was made to determine estimates of the number of raingauges needed in order to measure the variability of rainfall in time and space over small areas (approximately 40 sq miles). The literature on rainfall variability was examined and the types of empirical relationships used to relate rainfall variations to meteorological and catchment-area characteristics were considered. Relations between the coefficient of variation and areal-mean rainfall and area have been used by several investigators. These parameters seemed reasonable ones to use in any future study of rainfall variations. From a knowledge of an appropriate coefficient of variation (determined by the above-mentioned relations) the number rain gauges needed for the precise determination of areal-mean rainfall may be calculated by statistical estimation theory. The number gauges needed to measure the coefficient of variation over a 40 sq miles area, with varying degrees of error, was found to range from 264 (10% error, mean precipitation = 0.1 in) to about 2 (100% error, mean precipitation = 0.1 in).

Investigation of Adaptive-threshold Approaches for Determining Area-Time Integrals from Satellite Infrared Data to Estimate Convective Rain Volumes

Science.gov (United States)

Smith, Paul L.; VonderHaar, Thomas H.

1996-01-01

The principal goal of this project is to establish relationships that would allow application of area-time integral (ATI) calculations based upon satellite data to estimate rainfall volumes. The research is being carried out as a collaborative effort between the two participating organizations, with the satellite data analysis to determine values for the ATIs being done primarily by the STC-METSAT scientists and the associated radar data analysis to determine the 'ground-truth' rainfall estimates being done primarily at the South Dakota School of Mines and Technology (SDSM&T). Synthesis of the two separate kinds of data and investigation of the resulting rainfall-versus-ATI relationships is then carried out jointly. The research has been pursued using two different approaches, which for convenience can be designated as the 'fixed-threshold approach' and the 'adaptive-threshold approach'. In the former, an attempt is made to determine a single temperature threshold in the satellite infrared data that would yield ATI values for identifiable cloud clusters which are closely related to the corresponding rainfall amounts as determined by radar. Work on the second, or 'adaptive-threshold', approach for determining the satellite ATI values has explored two avenues: (1) attempt involved choosing IR thresholds to match the satellite ATI values with ones separately calculated from the radar data on a case basis; and (2) an attempt involved a striaghtforward screening analysis to determine the (fixed) offset that would lead to the strongest correlation and lowest standard error of estimate in the relationship between the satellite ATI values and the corresponding rainfall volumes.

Satellite measurements of the earth's crustal magnetic field

Science.gov (United States)

Schnetzler, C. C.

1989-01-01

The literature associated with the Magsat mission has evaluated the capabilities and limitations of satellite measurements of the earth's crustal magnetic field, and demonstrated that there exists a 300-3000 km magnetic field, related to major features in the earth's crust, which is primarily caused by induction. Due to its scale and sensitivity, satellite data have been useful in the development of models for such large crustal features as subduction zones, submarine platforms, continental accretion boundaries, and rifts. Attention is presently given to the lack of agreement between laboratory and satellite estimates of lower crustal magnetization.

Validation of Satellite Derived Cloud Properties Over the Southeastern Pacific

Science.gov (United States)

Ayers, J.; Minnis, P.; Zuidema, P.; Sun-Mack, S.; Palikonda, R.; Nguyen, L.; Fairall, C.

2005-12-01

Satellite measurements of cloud properties and the radiation budget are essential for understanding meso- and large-scale processes that determine the variability in climate over the southeastern Pacific. Of particular interest in this region is the prevalent stratocumulus cloud deck. The stratocumulus albedos are directly related to cloud microphysical properties that need to be accurately characterized in Global Climate Models (GCMs) to properly estimate the Earth's radiation budget. Meteorological observations in this region are sparse causing large uncertainties in initialized model fields. Remote sensing from satellites can provide a wealth of information about the clouds in this region, but it is vital to validate the remotely sensed parameters and to understand their relationship to other parameters that are not directly observed by the satellites. The variety of measurements from the R/V Roger Revelle during the 2003 STRATUS cruise and from the R/V Ron Brown during EPIC 2001 and the 2004 STRATUS cruises are suitable for validating and improving the interpretation of the satellite derived cloud properties. In this study, satellite-derived cloud properties including coverage, height, optical depth, and liquid water path are compared with in situ measurements taken during the EPIC and STRATUS cruises. The remotely sensed values are derived from Geostationary Operational Environmental Satellite (GOES) imager data, Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellites, and from the Visible and Infrared Scanner (VIRS) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The products from this study will include regional monthly cloud climatologies derived from the GOES data for the 2003 and 2004 cruises as well as micro and macro physical cloud property retrievals centered over the ship tracks from MODIS and VIRS.

Temporal and spatial variability of rainfall distribution and ...

African Journals Online (AJOL)

Rainfall and evapotranspiration are the two major climatic factors affecting agricultural production. This study examined the extent and nature of rainfall variability from measured data while estimation of evapotranspiration was made from recorded weather data. Analysis of rainfall variability is made by the rainfall anomaly ...

A Modified Gash Model for Estimating Rainfall Interception Loss of Forest Using Remote Sensing Observations at Regional Scale

Directory of Open Access Journals (Sweden)

Yaokui Cui

2014-04-01

Full Text Available Rainfall interception loss of forest is an important component of water balance in a forested ecosystem. The Gash analytical model has been widely used to estimate the forest interception loss at field scale. In this study, we proposed a simple model to estimate rainfall interception loss of heterogeneous forest at regional scale with several reasonable assumptions using remote sensing observations. The model is a modified Gash analytical model using easily measured parameters of forest structure from satellite data and extends the original Gash model from point-scale to the regional scale. Preliminary results, using remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS products, field measured rainfall data, and meteorological data of the Automatic Weather Station (AWS over a picea crassifolia forest in the upper reaches of the Heihe River Basin in northwestern China, showed reasonable accuracy in estimating rainfall interception loss at both the Dayekou experimental site (R2 = 0.91, RMSE = 0.34 mm∙d −1 and the Pailugou experimental site (R2 = 0.82, RMSE = 0.6 mm∙d −1, compared with ground measurements based on per unit area of forest. The interception loss map of the study area was shown to be strongly heterogeneous. The modified model has robust physics and is insensitive to the input parameters, according to the sensitivity analysis using numerical simulations. The modified model appears to be stable and easy to be applied for operational estimation of interception loss over large areas.

Impact of Satellite Remote Sensing Data on Simulations of Coastal Circulation and Hypoxia on the Louisiana Continental Shelf

Directory of Open Access Journals (Sweden)

Dong S. Ko

2016-05-01

Full Text Available We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS near the annual hypoxic zone. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM were used for the salinity flux, and the diffuse attenuation coefficient (Kd from Moderate Resolution Imaging Spectroradiometer (MODIS were used for solar penetration. Improvements in the model results in comparison with in situ observations occurred when the two types of satellite data were included. Without inclusion of the satellite-derived surface salinity flux, realistic monthly variability in the model salinity fields was observed, but important inter-annual variability was missed. Without inclusion of the satellite-derived light attenuation, model bottom water temperatures were too high nearshore due to excessive penetration of solar irradiance. In general, these salinity and temperature errors led to model stratification that was too weak, and the model failed to capture observed spatial and temporal variability in water-column vertical stratification. Inclusion of the satellite data improved temperature and salinity predictions and the vertical stratification was strengthened, which improved prediction of bottom-water dissolved oxygen. The model-predicted area of bottom-water hypoxia on the Louisiana shelf, an important management metric, was substantially improved in comparison to observed hypoxic area by including the satellite data.

How Consistent are Recent Variations in the Tropical Energy and Water Cycle Resolved by Satellite Measurements?

Science.gov (United States)

Robertson, F. R.; Lu, H.-I.

2004-01-01

One notable aspect of Earth's climate is that although the planet appears to be very close to radiative balance at top-of-atmosphere (TOA), the atmosphere itself and underlying surface are not. Profound exchanges of energy between the atmosphere and oceans, land and cryosphere occur over a range of time scales. Recent evidence from broadband satellite measurements suggests that even these TOA fluxes contain some detectable variations. Our ability to measure and reconstruct radiative fluxes at the surface and at the top of atmosphere is improving rapidly. One question is 'How consistent, physically, are these diverse remotely-sensed data sets'? The answer is of crucial importance to understanding climate processes, improving physical models, and improving remote sensing algorithms. In this work we will evaluate two recently released estimates of radiative fluxes, focusing primarily on surface estimates. The International Satellite Cloud Climatology Project 'FD' radiative flux profiles are available from mid-1983 to near present and have been constructed by driving the radiative transfer physics from the Goddard Institute for Space Studies (GISS) global model with ISCCP clouds and TOVS (TIROS Operational Vertical Sounder)thermodynamic profiles. Full and clear sky SW and LW fluxes are produced. A similar product from the NASA/GEWEX Surface Radiation Budget Project using different radiative flux codes and thermodynamics from the NASA/Goddard Earth Observing System (GEOS-1) assimilation model makes a similar calculation of surface fluxes. However this data set currently extends only through 1995. We also employ precipitation measurements from the Global Precipitation Climatology Project (GPCP) and the Tropical Rainfall Measuring Mission (TRMM). Finally, ocean evaporation estimates from the Special Sensor Microwave Imager (SSM/I) are considered as well as derived evaporation from the NCAR/NCEP Reanalysis. Additional information is included in the original extended

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

Science.gov (United States)

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

2017-12-01

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

Connecting Satellite-Based Precipitation Estimates to Users

Science.gov (United States)

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

2018-01-01

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

A New Satellite System for Measuring BRDF from Space

Science.gov (United States)

Wiscombe, W.; Kaufman, Y.; Herman, J.

1999-01-01

Formation flying of satellites is at the beginning of an explosive growth curve. Spacecraft buses are shrinking to the point where we will soon be able to launch 10 micro-satellites or 100 nano-satellites on a single launch vehicle. Simultaneously, spectrometers are just beginning to be flown in space by both the U.S. and Europe. On-board programmable band aggregation will soon allow exactly the spectral bands desired to be returned to Earth. Further efforts are being devoted to radically shrink spectrometers both in size and weight. And GPS positioning and attitude determination, plus new technologies for attitude control, will allow fleets of satellites to all point at the same Earth target. All these advances, in combination, make possible for the first time the proper measurement of Bidirectional Reflectance Distribution (BRDF) form space. Previously space BDRF's were mere composites, built up over time by viewing different types of scenes at different times, then creating catalogs of BDRF functions whose use relied upon correct "scene identification" --the weak link. Formation-flying micro-satellites, carrying programmable spectrometers and precision-pointing at the same Earth target, can measure the full BDRF simultaneously, in real time. This talk will review these technological advances and discuss an actual proposed concept, based on these advances, to measure Earth-target BDRF's (clouds as well as surface) across the full solar spectrum in the 2010 timeframe. This concept is part of a larger concept called Leonardo for properly measuring the radiative forcing of Earth for climate purposes; lack of knowing of BDRF and of diurnal cycle are at present the two limiting factors preventing improved estimates of this forcing.

Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity: API and SURFEX

Science.gov (United States)

Real-time rainfall accumulation estimates at the global scale is useful for many applications. However, the real-time versions of satellite-based rainfall products are known to contain errors relative to real rainfall observed in situ. Recent studies have demonstrated how information about rainfall ...

Comparative measurements with seven rainfall simulators on uniform bare fallow land

NARCIS (Netherlands)

Iserloh, T.; Ries, J.B.; Cerda, A.; Echeverria, M.T.; Fister, W.; Geissler, C.; Kuhn, N.J.; Leon, F.J.; Peters, P.; Schindewolf, M.; Schmidt, J.; Scholten, T.; Seeger, K.M.

2013-01-01

To assess the influence of rainfall simulator type and plot dimensions on runoff and erosion, seven small portable rainfall simulators from Freiberg, Tubingen, Trier (all Germany), Valencia, Zaragoza (both Spain), Basel (Switzerland) and Wageningen (the Netherlands) were compared on a prepared bare

Topographic Correction of Wind-driven Rainfall for Landslide Analysis in Central Taiwan with Validation from Aerial and Satellite Optical Images

Directory of Open Access Journals (Sweden)

Jin-King Liu

2013-05-01

Full Text Available Rainfall intensity plays an important role in landslide prediction especially in mountain areas. However, the rainfall intensity of a location is usually interpolated from rainfall recorded at nearby gauges without considering any possible effects of topographic slopes. In order to obtain reliable rainfall intensity for disaster mitigation, this study proposes a rainfall-vector projection method for topographic-corrected rainfall. The topographic-corrected rainfall is derived from wind speed, terminal velocity of raindrops, and topographical factors from digital terrain model. In addition, scatter plot was used to present landslide distribution with two triggering factors and kernel density analysis is adopted to enhance the perception of the distribution. Numerical analysis is conducted for a historic event, typhoon Mindulle, which occurred in 2004, in a location in central Taiwan. The largest correction reaches 11%, which indicates that topographic correction is significant. The corrected rainfall distribution is then applied to the analysis of landslide triggering factors. The result with corrected rainfall distribution provides better agreement with the actual landslide occurrence than the result without correction.

Predicting rainfall erosivity by momentum and kinetic energy in Mediterranean environment

Science.gov (United States)

Carollo, Francesco G.; Ferro, Vito; Serio, Maria A.

2018-05-01

Rainfall erosivity is an index that describes the power of rainfall to cause soil erosion and it is used around the world for assessing and predicting soil loss on agricultural lands. Erosivity can be represented in terms of both rainfall momentum and kinetic energy, both calculated per unit time and area. Contrasting results on the representativeness of these two variables are available: some authors stated that momentum and kinetic energy are practically interchangeable in soil loss estimation while other found that kinetic energy is the most suitable expression of rainfall erosivity. The direct and continuous measurements of momentum and kinetic energy by a disdrometer allow also to establish a relationship with rainfall intensity at the study site. At first in this paper a comparison between the momentum-rainfall intensity relationships measured at Palermo and El Teularet by an optical disdrometer is presented. For a fixed rainfall intensity the measurements showed that the rainfall momentum values measured at the two experimental sites are not coincident. However both datasets presented a threshold value of rainfall intensity over which the rainfall momentum assumes a quasi-constant value. Then the reliability of a theoretically deduced relationship, linking momentum, rainfall intensity and median volume diameter, is positively verified using measured raindrop size distributions. An analysis to assess which variable, momentum or kinetic energy per unit area and time, is the best predictor of erosivity in Italy and Spain was also carried out. This investigation highlighted that the rainfall kinetic energy per unit area and time can be substituted by rainfall momentum as index for estimating the rainfall erosivity, and this result does not depend on the site where precipitation occurs. Finally, rainfall intensity measurements and soil loss data collected from the bare plots equipped at Sparacia experimental area were used to verify the reliability of some

Rainfall variation and child health: effect of rainfall on diarrhea among under 5 children in Rwanda, 2010.

Science.gov (United States)

Mukabutera, Assumpta; Thomson, Dana; Murray, Megan; Basinga, Paulin; Nyirazinyoye, Laetitia; Atwood, Sidney; Savage, Kevin P; Ngirimana, Aimable; Hedt-Gauthier, Bethany L

2016-08-05

Diarrhea among children under 5 years of age has long been a major public health concern. Previous studies have suggested an association between rainfall and diarrhea. Here, we examined the association between Rwandan rainfall patterns and childhood diarrhea and the impact of household sanitation variables on this relationship. We derived a series of rain-related variables in Rwanda based on daily rainfall measurements and hydrological models built from daily precipitation measurements collected between 2009 and 2011. Using these data and the 2010 Rwanda Demographic and Health Survey database, we measured the association between total monthly rainfall, monthly rainfall intensity, runoff water and anomalous rainfall and the occurrence of diarrhea in children under 5 years of age. Among the 8601 children under 5 years of age included in the survey, 13.2 % reported having diarrhea within the 2 weeks prior to the survey. We found that higher levels of runoff were protective against diarrhea compared to low levels among children who lived in households with unimproved toilet facilities (OR = 0.54, 95 % CI: [0.34, 0.87] for moderate runoff and OR = 0.50, 95 % CI: [0.29, 0.86] for high runoff) but had no impact among children in household with improved toilets. Our finding that children in households with unimproved toilets were less likely to report diarrhea during periods of high runoff highlights the vulnerabilities of those living without adequate sanitation to the negative health impacts of environmental events.

Drought Early Warning and Agro-Meteorological Risk Assessment using Earth Observation Rainfall Datasets and Crop Water Budget Modelling

Science.gov (United States)

Tarnavsky, E.

2016-12-01

The water resources satisfaction index (WRSI) model is widely used in drought early warning and food security analyses, as well as in agro-meteorological risk management through weather index-based insurance. Key driving data for the model is provided from satellite-based rainfall estimates such as ARC2 and TAMSAT over Africa and CHIRPS globally. We evaluate the performance of these rainfall datasets for detecting onset and cessation of rainfall and estimating crop production conditions for the WRSI model. We also examine the sensitivity of the WRSI model to different satellite-based rainfall products over maize growing regions in Tanzania. Our study considers planting scenarios for short-, medium-, and long-growing cycle maize, and we apply these for 'regular' and drought-resistant maize, as well as with two different methods for defining the start of season (SOS). Simulated maize production estimates are compared against available reported production figures at the national and sub-national (province) levels. Strengths and weaknesses of the driving rainfall data, insights into the role of the SOS definition method, and phenology-based crop yield coefficient and crop yield reduction functions are discussed in the context of space-time drought characteristics. We propose a way forward for selecting skilled rainfall datasets and discuss their implication for crop production monitoring and the design and structure of weather index-based insurance products as risk transfer mechanisms implemented across scales for smallholder farmers to national programmes.

Ground- and satellite-based evidence of the biophysical mechanisms behind the greening Sahel.

Science.gov (United States)

Brandt, Martin; Mbow, Cheikh; Diouf, Abdoul A; Verger, Aleixandre; Samimi, Cyrus; Fensholt, Rasmus

2015-04-01

After a dry period with prolonged droughts in the 1970s and 1980s, recent scientific outcome suggests that the decades of abnormally dry conditions in the Sahel have been reversed by positive anomalies in rainfall. Various remote sensing studies observed a positive trend in vegetation greenness over the last decades which is known as the re-greening of the Sahel. However, little investment has been made in including long-term ground-based data collections to evaluate and better understand the biophysical mechanisms behind these findings. Thus, deductions on a possible increment in biomass remain speculative. Our aim is to bridge these gaps and give specifics on the biophysical background factors of the re-greening Sahel. Therefore, a trend analysis was applied on long time series (1987-2013) of satellite-based vegetation and rainfall data, as well as on ground-observations of leaf biomass of woody species, herb biomass, and woody species abundance in different ecosystems located in the Sahel zone of Senegal. We found that the positive trend observed in satellite vegetation time series (+36%) is caused by an increment of in situ measured biomass (+34%), which is highly controlled by precipitation (+40%). Whereas herb biomass shows large inter-annual fluctuations rather than a clear trend, leaf biomass of woody species has doubled within 27 years (+103%). This increase in woody biomass did not reflect on biodiversity with 11 of 16 woody species declining in abundance over the period. We conclude that the observed greening in the Senegalese Sahel is primarily related to an increasing tree cover that caused satellite-driven vegetation indices to increase with rainfall reversal. © 2014 John Wiley & Sons Ltd.

Gross rainfall amount and maximum rainfall intensity in 60-minute influence on interception loss of shrubs: a 10-year observation in the Tengger Desert.

Science.gov (United States)

Zhang, Zhi-Shan; Zhao, Yang; Li, Xin-Rong; Huang, Lei; Tan, Hui-Juan

2016-05-17

In water-limited regions, rainfall interception is influenced by rainfall properties and crown characteristics. Rainfall properties, aside from gross rainfall amount and duration (GR and RD), maximum rainfall intensity and rainless gap (RG), within rain events may heavily affect throughfall and interception by plants. From 2004 to 2014 (except for 2007), individual shrubs of Caragana korshinskii and Artemisia ordosica were selected to measure throughfall during 210 rain events. Various rainfall properties were auto-measured and crown characteristics, i.e., height, branch and leaf area index, crown area and volume of two shrubs were also measured. The relative interceptions of C. korshinskii and A. ordosica were 29.1% and 17.1%, respectively. Rainfall properties have more contributions than crown characteristics to throughfall and interception of shrubs. Throughfall and interception of shrubs can be explained by GR, RI60 (maximum rainfall intensities during 60 min), RD and RG in deceasing importance. However, relative throughfall and interception of two shrubs have different responses to rainfall properties and crown characteristics, those of C. korshinskii were closely related to rainfall properties, while those of A. ordosica were more dependent on crown characteristics. We highlight long-term monitoring is very necessary to determine the relationships between throughfall and interception with crown characteristics.

Satellite measurements of aerosol mass and transport

Energy Technology Data Exchange (ETDEWEB)

Fraser, R.S.; Kaufman, Y.J.; Mahoney, R.L.

1984-01-01

The aerosol optical thickness over land is derived from satellite measurements of the radiance of scattered sunlight. These data are used to estimate the columnar mass density of particulate sulfur on a day with a large amount of sulfur. The horizontal transport of the particulate sulfur is calculated using wing vectors measured with rawins. 33 references, 7 figures, 1 table.

Tropical Rainfall Measuring Mission (TRMM) Precipitation Data and Services for Research and Applications

Science.gov (United States)

Liu, Zhong; Ostrenga, Dana; Teng, William; Kempler, Steven

2012-01-01

Precipitation is a critical component of the Earth's hydrological cycle. Launched on 27 November 1997, TRMM is a joint U.S.-Japan satellite mission to provide the first detailed and comprehensive data set of the four-dimensional distribution of rainfall and latent heating over vastly under-sampled tropical and subtropical oceans and continents (40 S - 40 N). Over the past 14 years, TRMM has been a major data source for meteorological, hydrological and other research and application activities around the world. The purpose of this short article is to inform that the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides TRMM archive and near-real-time precipitation data sets and services for research and applications. TRMM data consist of orbital data from TRMM instruments at the sensor s resolution, gridded data at a range of spatial and temporal resolutions, subsets, ground-based instrument data, and ancillary data. Data analysis, display, and delivery are facilitated by the following services: (1) Mirador (data search and access); (2) TOVAS (TRMM Online Visualization and Analysis System); (3) OPeNDAP (Open-source Project for a Network Data Access Protocol); (4) GrADS Data Server (GDS); and (5) Open Geospatial Consortium (OGC) Web Map Service (WMS) for the GIS community. Precipitation data application services are available to support a wide variety of applications around the world. Future plans include enhanced and new services to address data related issues from the user community. Meanwhile, the GES DISC is preparing for the Global Precipitation Measurement (GPM) mission which is scheduled for launch in 2014.

Geometric model of pseudo-distance measurement in satellite location systems

Science.gov (United States)

Panchuk, K. L.; Lyashkov, A. A.; Lyubchinov, E. V.

2018-04-01

The existing mathematical model of pseudo-distance measurement in satellite location systems does not provide a precise solution of the problem, but rather an approximate one. The existence of such inaccuracy, as well as bias in measurement of distance from satellite to receiver, results in inaccuracy level of several meters. Thereupon, relevance of refinement of the current mathematical model becomes obvious. The solution of the system of quadratic equations used in the current mathematical model is based on linearization. The objective of the paper is refinement of current mathematical model and derivation of analytical solution of the system of equations on its basis. In order to attain the objective, geometric analysis is performed; geometric interpretation of the equations is given. As a result, an equivalent system of equations, which allows analytical solution, is derived. An example of analytical solution implementation is presented. Application of analytical solution algorithm to the problem of pseudo-distance measurement in satellite location systems allows to improve the accuracy such measurements.

Re-assessing Rainwater Harvesting Volume by CHIRPS Satellite in Semarang Settlement Area

Science.gov (United States)

Prihanto, Yosef; Koestoer, Raldi H.; Sutjiningsih, Dwita

2017-12-01

Semarang City is one of the most influential coastal cities in Java Island. The city is facing increasingly-high water demand due to its development and water problems due to climate change. The spatial physiography and landscape of Semarang City are also exposed the city to water security problem. Hence, rainwater harvesting treatment is an urgent effort to meet the city’s water needs. However, planning, implementation and management of rainwater harvesting are highly depended on multitemporal rainfall data. It has not yet been fully compiled due to limited rain stations. This study aims to examine the extent to which CHIRPS satellite data can be utilized in estimating volume of rainwater harvesting 16 sub-districts in Semarang and determine the water security status. This study uses descriptive statistical method based on spatial analyses. Such method was developed through spatial modeling for rainfall using isohyetal model. The parameters used are rainfall, residential rooftop area, administrative area, population, physiographic and altitude units. Validation is carried out by using monthly 10 rain stations data. The results show level of validity by utilizing CHIRPS Satellite data and mapping rainfall distribution. This study also produces a potential map of distribution rainfall volume that can be harvested in 16 sub-districts of Semarang.

Rainfall interception of three trees in Oakland, California

Science.gov (United States)

Qingfu Xiao; E. Gregory McPherson

2011-01-01

A rainfall interception study was conducted in Oakland, California to determine the partitioning of rainfall and the chemical composition of precipitation, throughfall, and stemflow. Rainfall interception measurements were conducted on a gingko (Ginkgo biloba) (13.5 m tall deciduous tree), sweet gum (Liquidambar styraciflua) (8...

The analysis of the possibility of using 10-minute rainfall series to determine the maximum rainfall amount with 5 minutes duration

Science.gov (United States)

Kaźmierczak, Bartosz; Wartalska, Katarzyna; Wdowikowski, Marcin; Kotowski, Andrzej

2017-11-01

Modern scientific research in the area of heavy rainfall analysis regarding to the sewerage design indicates the need to develop and use probabilistic rain models. One of the issues that remains to be resolved is the length of the shortest amount of rain to be analyzed. It is commonly believed that the best time is 5 minutes, while the least rain duration measured by the national services is often 10 or even 15 minutes. Main aim of this paper is to present the difference between probabilistic rainfall models results given from rainfall time series including and excluding 5 minutes rainfall duration. Analysis were made for long-time period from 1961-2010 on polish meteorological station Legnica. To develop best fitted to measurement rainfall data probabilistic model 4 probabilistic distributions were used. Results clearly indicates that models including 5 minutes rainfall duration remains more appropriate to use.

Measurement of initial soil moisture conditions for purposes of rainfall simulation experiments

OpenAIRE

TEREZA, Davidová; VÁCLAV, David

2015-01-01

The research on rainfall-runoff processes has become even more important in recent decades with respect to both flood and drought events as well as to expected impacts of considered climate changes. It is researched in different ways and at different scales according to the purpose. The rainfall simulator developed at Department of Irrigation, Drainage and Landscape Engineering is being used for purposes of detail analysis of rainfall-runoff process in order to research infiltration process w...

Satellite passive microwave rain measurement techniques for land and ocean

Science.gov (United States)

Spencer, R. W.

1985-01-01

Multiseasonal rainfall was found to be measurable over land with satellite passive microwave data, based upon comparisons between Nimbus 7 Scanning Multichannel Microwave Radiometer (SMME) brightness temperatures (T sub B) and operational WSR-57 radar rain rates. All of the SMMR channels (bipolarized 37, 21, 18, 10.7, and 6.6. GHz T sub B) were compared to radar reflectivities for 25 SMMR passes and 234 radar scans over the U.S. during the spring, summer, and fall of 1979. It was found that the radar rain rates were closely related to the difference between 37 and 21 GHz T sub B. This result is due to the volume scattering effects of precipitation which cause emissivity decreases with frequency, as opposed to emissive surfaces (e.g., water) whose emissivities increase with frequency. Two frequencies also act to reduce the effects of thermometric temperature variations on T sub B to a miminum. During summer and fall, multiple correlation coefficients of 0.80 and 0.75 were obtained. These approach the limit of correlation that can be expected to exist between two very different data sources, especially in light of the errors attributable to manual digitization of PPI photographs of variable quality from various operational weather radar not calibrated for research purposes. During the spring, a significantly lower (0.63) correlation was found. This poorer performance was traced to cases of wet, unvegetated soil being sensed at the lower frequencies through light rain, partly negating the rain scattering signal.

Design and Performance of Tropical Rainfall Measuring Mission (TRMM) Super NiCd Batteries

Science.gov (United States)

Ahmad, Anisa J.; Rao, Gopalakrishna M.; Jallice, Doris E.; Moran Vickie E.

1999-01-01

The Tropical Rainfall Measuring Mission (TRMM) is a joint mission between NASA and the National Space Development Agency (NASDA) of Japan. The observatory is designed to monitor and study tropical rainfall and the associated release of energy that helps to power the global atmospheric circulation shaping both weather and climate around the globe. The spacecraft was launched from Japan on November 27,1997 via the NASDA H-2 launch vehicle. The TRMM Power Subsystem is a Peak Power Tracking system that can support the maximum TRMM load of 815 watts at the end of its three year life. The Power Subsystem consists of two 50 Ampere Hour Super NiCd batteries, Gallium Arsenide Solar Array and the Power System Electronics. This paper describes the TRMM Power Subsystem, battery design, cell and battery ground test performance, and in-orbit battery operations and performance.

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

Impacts of the seasonal distribution of rainfall on vegetation productivity across the Sahel

Science.gov (United States)

Zhang, Wenmin; Brandt, Martin; Tong, Xiaoye; Tian, Qingjiu; Fensholt, Rasmus

2018-01-01

Climate change in drylands has caused alterations in the seasonal distribution of rainfall including increased heavy-rainfall events, longer dry spells, and a shifted timing of the wet season. Yet the aboveground net primary productivity (ANPP) in drylands is usually explained by annual-rainfall sums, disregarding the influence of the seasonal distribution of rainfall. This study tested the importance of rainfall metrics in the wet season (onset and cessation of the wet season, number of rainy days, rainfall intensity, number of consecutive dry days, and heavy-rainfall events) for growing season ANPP. We focused on the Sahel and northern Sudanian region (100-800 mm yr-1) and applied daily satellite-based rainfall estimates (CHIRPS v2.0) and growing-season-integrated normalized difference vegetation index (NDVI; MODIS) as a proxy for ANPP over the study period: 2001-2015. Growing season ANPP in the arid zone (100-300 mm yr-1) was found to be rather insensitive to variations in the seasonal-rainfall metrics, whereas vegetation in the semi-arid zone (300-700 mm yr-1) was significantly impacted by most metrics, especially by the number of rainy days and timing (onset and cessation) of the wet season. We analysed critical breakpoints for all metrics to test if vegetation response to changes in a given rainfall metric surpasses a threshold beyond which vegetation functioning is significantly altered. It was shown that growing season ANPP was particularly negatively impacted after > 14 consecutive dry days and that a rainfall intensity of ˜ 13 mm day-1 was detected for optimum growing season ANPP. We conclude that the number of rainy days and the timing of the wet season are seasonal-rainfall metrics that are decisive for favourable vegetation growth in the semi-arid Sahel and need to be considered when modelling primary productivity from rainfall in the drylands of the Sahel and elsewhere.

Measurement-based perturbation theory and differential equation parameter estimation with applications to satellite gravimetry

Science.gov (United States)

Xu, Peiliang

2018-06-01

The numerical integration method has been routinely used by major institutions worldwide, for example, NASA Goddard Space Flight Center and German Research Center for Geosciences (GFZ), to produce global gravitational models from satellite tracking measurements of CHAMP and/or GRACE types. Such Earth's gravitational products have found widest possible multidisciplinary applications in Earth Sciences. The method is essentially implemented by solving the differential equations of the partial derivatives of the orbit of a satellite with respect to the unknown harmonic coefficients under the conditions of zero initial values. From the mathematical and statistical point of view, satellite gravimetry from satellite tracking is essentially the problem of estimating unknown parameters in the Newton's nonlinear differential equations from satellite tracking measurements. We prove that zero initial values for the partial derivatives are incorrect mathematically and not permitted physically. The numerical integration method, as currently implemented and used in mathematics and statistics, chemistry and physics, and satellite gravimetry, is groundless, mathematically and physically. Given the Newton's nonlinear governing differential equations of satellite motion with unknown equation parameters and unknown initial conditions, we develop three methods to derive new local solutions around a nominal reference orbit, which are linked to measurements to estimate the unknown corrections to approximate values of the unknown parameters and the unknown initial conditions. Bearing in mind that satellite orbits can now be tracked almost continuously at unprecedented accuracy, we propose the measurement-based perturbation theory and derive global uniformly convergent solutions to the Newton's nonlinear governing differential equations of satellite motion for the next generation of global gravitational models. Since the solutions are global uniformly convergent, theoretically speaking

Precipitation characteristics in tropical Africa using satellite and in situ observations

Science.gov (United States)

Dezfuli, A. K.; Ichoku, I.; Huffman, G. J.; Mohr, K. I.

2017-12-01

Tropical Africa receives nearly all its precipitation as a result of convection. The characteristics of rain-producing systems in this region have not been well-understood, despite their crucial role in regional and global circulation. This is mainly due to the lack of in situ observations. Here, we have used precipitation records from the Trans-African Hydro-Meteorological Observatory (TAHMO) ground-based gauge network to improve our knowledge about the rainfall systems in the region, and to validate the recently-released IMERG precipitation product based on satellite observations from the Global Precipitation Measurement (GPM) constellation. The high temporal resolution of the gauge data has allowed us to identify three classes of rain events based on their duration and intensity. The contribution of each class to the total rainfall and the favorable surface atmospheric conditions for each class have been examined. As IMERG aims to continue the legacy of its predecessor, TRMM Multi-Satellite Precipitation Analysis (TMPA), and provide higher resolution data, continent-wide comparisons are made between these two products. Due to its improved temporal resolution, IMERG shows some advantages over TMPA in capturing the diurnal cycle and propagation of the meso-scale convective systems. However, the performance of the two satellite-based products varies by season, region and the evaluation statistics. The results of this study serve as a basis for our ongoing work on the impacts of biomass burning on precipitation processes in Africa.

Rainfall variation and child health: effect of rainfall on diarrhea among under 5 children in Rwanda, 2010

Directory of Open Access Journals (Sweden)

Assumpta Mukabutera

2016-08-01

Full Text Available Abstract Background Diarrhea among children under 5 years of age has long been a major public health concern. Previous studies have suggested an association between rainfall and diarrhea. Here, we examined the association between Rwandan rainfall patterns and childhood diarrhea and the impact of household sanitation variables on this relationship. Methods We derived a series of rain-related variables in Rwanda based on daily rainfall measurements and hydrological models built from daily precipitation measurements collected between 2009 and 2011. Using these data and the 2010 Rwanda Demographic and Health Survey database, we measured the association between total monthly rainfall, monthly rainfall intensity, runoff water and anomalous rainfall and the occurrence of diarrhea in children under 5 years of age. Results Among the 8601 children under 5 years of age included in the survey, 13.2 % reported having diarrhea within the 2 weeks prior to the survey. We found that higher levels of runoff were protective against diarrhea compared to low levels among children who lived in households with unimproved toilet facilities (OR = 0.54, 95 % CI: [0.34, 0.87] for moderate runoff and OR = 0.50, 95 % CI: [0.29, 0.86] for high runoff but had no impact among children in household with improved toilets. Conclusion Our finding that children in households with unimproved toilets were less likely to report diarrhea during periods of high runoff highlights the vulnerabilities of those living without adequate sanitation to the negative health impacts of environmental events.

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.

Radioactive pollution in rainfall

International Nuclear Information System (INIS)

Jemtland, R.

1985-01-01

Routine measurements of radioactivity in rainfall are carried out at the National Institute for Radiation Hygiene, Norway. The report discusses why the method of ion exchange was selected and gives details on how the measurements are performed

Bias correction of satellite precipitation products for flood forecasting application at the Upper Mahanadi River Basin in Eastern India

Science.gov (United States)

Beria, H.; Nanda, T., Sr.; Chatterjee, C.

2015-12-01

High resolution satellite precipitation products such as Tropical Rainfall Measuring Mission (TRMM), Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts (ECMWF), etc., offer a promising alternative to flood forecasting in data scarce regions. At the current state-of-art, these products cannot be used in the raw form for flood forecasting, even at smaller lead times. In the current study, these precipitation products are bias corrected using statistical techniques, such as additive and multiplicative bias corrections, and wavelet multi-resolution analysis (MRA) with India Meteorological Department (IMD) gridded precipitation product,obtained from gauge-based rainfall estimates. Neural network based rainfall-runoff modeling using these bias corrected products provide encouraging results for flood forecasting upto 48 hours lead time. We will present various statistical and graphical interpretations of catchment response to high rainfall events using both the raw and bias corrected precipitation products at different lead times.

A Machine Learning-based Rainfall System for GPM Dual-frequency Radar

Science.gov (United States)

Tan, H.; Chandrasekar, V.; Chen, H.

2017-12-01

Precipitation measurement produced by the Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) plays an important role in researching the water circle and forecasting extreme weather event. Compare with its predecessor - Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), GRM DPR measures precipitation in two different frequencies (i.e., Ku and Ka band), which can provide detailed information on the microphysical properties of precipitation particles, quantify particle size distribution and quantitatively measure light rain and falling snow. This paper presents a novel Machine Learning system for ground-based and space borne radar rainfall estimation. The system first trains ground radar data for rainfall estimation using rainfall measurements from gauges and subsequently uses the ground radar based rainfall estimates to train GPM DPR data in order to get space based rainfall product. Therein, data alignment between space DPR and ground radar is conducted using the methodology proposed by Bolen and Chandrasekar (2013), which can minimize the effects of potential geometric distortion of GPM DPR observations. For demonstration purposes, rainfall measurements from three rain gauge networks near Melbourne, Florida, are used for training and validation purposes. These three gauge networks, which are located in Kennedy Space Center (KSC), South Florida Water Management District (SFL), and St. Johns Water Management District (STJ), include 33, 46, and 99 rain gauge stations, respectively. Collocated ground radar observations from the National Weather Service (NWS) Weather Surveillance Radar - 1988 Doppler (WSR-88D) in Melbourne (i.e., KMLB radar) are trained with the gauge measurements. The trained model is then used to derive KMLB radar based rainfall product, which is used to train GPM DPR data collected from coincident overpasses events. The machine learning based rainfall product is compared against the GPM standard products

Correlative studies of satellite ozone sensor measurements

International Nuclear Information System (INIS)

Lovill, J.E.; Ellis, J.S.

1983-01-01

Comparisons are made between total ozone measurements made by four satellite ozone sensors (TOMS, SBUV, TOVS and MFR). The comparisons were made during July 1979 when all sensors were operating simultaneously. The TOMS and SBUV sensors were observed to measure less total ozone than the MFR sensor, 10 and 15 Dobson units (DU) respectively. The MFR and TOMS sensors measured less ozone than the TOVS sensor, 19 an 28 DU, respectively. Latitudinal variability of the total ozone comparisons is discussed

Interpretation of Spectrometric Measurements of Active Geostationary Satellites

Science.gov (United States)

Bedard, D.; Wade, G.

2014-09-01

Over 5000 visible near-infrared (VNIR) spectrometric measurements of active geostationary satellites have been collected with the National Research Council (NRC) 1.8m Plaskett telescope located at the Dominion Astrophysical Observatory (DAO) in Victoria, Canada. The objective of this ongoing experiment is to study how reflectance spectroscopy can be used to reliably identify specific material types on the surface of artificial Earth-orbiting objects. Active geostationary satellites were selected as the main subjects for this experiment since their orientation is stable and can be estimated to a high-level of confidence throughout a night of observation. Furthermore, for most geostationary satellites, there is a wide variety of sources that can provide some level of information as to their external surface composition. Notwithstanding the high number of measurements that have been collected to date, it was assumed that the experimenters would have a much greater success rate in material identification given the choice experimental subjects. To date, only the presence of aluminum has been confidently identified in some of the reflectance spectra that have been collected. Two additional material types, namely photovoltaic cells and polyimide film, the first layer of multi-layer insulation (MLI), have also been possibly identified. However uncertainties in the reduced spectral measurements prevent any definitive conclusion with respect to these materials at this time. The surprising lack of results with respect to material identification have forced the experimenters to use other data interpretation methods to characterize the spectral scattering characteristics of the studied satellites. The results from this study have already led to improvements in the ways that reflectance spectra from spacecraft are collected and analysed. Equally important, the data interpretation techniques elaborated over the course of this experiment will also serve to increase the body of

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

Science.gov (United States)

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

2002-01-01

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

Use of geostationary meteorological satellite images in convective rain estimation for flash-flood forecasting

Science.gov (United States)

Wardah, T.; Abu Bakar, S. H.; Bardossy, A.; Maznorizan, M.

2008-07-01

SummaryFrequent flash-floods causing immense devastation in the Klang River Basin of Malaysia necessitate an improvement in the real-time forecasting systems being used. The use of meteorological satellite images in estimating rainfall has become an attractive option for improving the performance of flood forecasting-and-warning systems. In this study, a rainfall estimation algorithm using the infrared (IR) information from the Geostationary Meteorological Satellite-5 (GMS-5) is developed for potential input in a flood forecasting system. Data from the records of GMS-5 IR images have been retrieved for selected convective cells to be trained with the radar rain rate in a back-propagation neural network. The selected data as inputs to the neural network, are five parameters having a significant correlation with the radar rain rate: namely, the cloud-top brightness-temperature of the pixel of interest, the mean and the standard deviation of the temperatures of the surrounding five by five pixels, the rate of temperature change, and the sobel operator that indicates the temperature gradient. In addition, three numerical weather prediction (NWP) products, namely the precipitable water content, relative humidity, and vertical wind, are also included as inputs. The algorithm is applied for the areal rainfall estimation in the upper Klang River Basin and compared with another technique that uses power-law regression between the cloud-top brightness-temperature and radar rain rate. Results from both techniques are validated against previously recorded Thiessen areal-averaged rainfall values with coefficient correlation values of 0.77 and 0.91 for the power-law regression and the artificial neural network (ANN) technique, respectively. An extra lead time of around 2 h is gained when the satellite-based ANN rainfall estimation is coupled with a rainfall-runoff model to forecast a flash-flood event in the upper Klang River Basin.

Predicting watershed acidification under alternate rainfall conditions

International Nuclear Information System (INIS)

Huntington, T.G.

1996-01-01

The effect of alternate rainfall scenarios on acidification of a forested watershed subjected to chronic acidic deposition was assessed using the model of acidification of groundwater in catchments (MAGIC). The model was calibrated at the Panola Mountain Research Watershed, near Atlanta, Georgia, USA using measured soil properties, wet and dry deposition, and modeled hydrologic routing. Model forecast simulations were evaluated to compare alternate temporal averaging of rainfall inputs and variations in rainfall amount and seasonal distribution. Soil water alkalinity was predicted to decrease to substantially lower concentrations under lower rainfall compared with current or higher rainfall conditions. Soil water alkalinity was also predicted to decrease to lower levels when the majority of rainfall occurred during the growing season compared with other rainfall distributions. Changes in rainfall distribution that result in decreases in net soil water flux will temporarily delay acidification. Ultimately, however, decreased soilwater flux will result in larger increases in soil-adsorbed sulfur and soil-water sulfate concentrations and decreases in alkalinity when compared to higher water flux conditions. Potential climate change resulting in significant changes in rainfall amounts, seasonal distributions of rainfall, or evapotranspiration will change net soil water flux and, consequently, will affect the dynamics of the acidification response to continued sulfate loading. 29 refs., 7 figs., 4 tabs

Hydrological modeling of the Peruvian–Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset

Directory of Open Access Journals (Sweden)

R. Zubieta

2017-07-01

Full Text Available In the last two decades, rainfall estimates provided by the Tropical Rainfall Measurement Mission (TRMM have proven applicable in hydrological studies. The Global Precipitation Measurement (GPM mission, which provides the new generation of rainfall estimates, is now considered a global successor to TRMM. The usefulness of GPM data in hydrological applications, however, has not yet been evaluated over the Andean and Amazonian regions. This study uses GPM data provided by the Integrated Multi-satellite Retrievals (IMERG (product/final run as input to a distributed hydrological model for the Amazon Basin of Peru and Ecuador for a 16-month period (from March 2014 to June 2015 when all datasets are available. TRMM products (TMPA V7 and TMPA RT datasets and a gridded precipitation dataset processed from observed rainfall are used for comparison. The results indicate that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, compared to observed rainfall (by 11.1 and 15.7 %, respectively. In general, GPM-IMERG, TMPA V7 and TMPA RT correlate with observed rainfall, with a similar number of rain events correctly detected ( ∼  20 %. Statistical analysis of modeled streamflows indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets in southern regions (Ucayali Basin. GPM-IMERG, TMPA V7 and TMPA RT do not properly simulate streamflows in northern regions (Marañón and Napo basins, probably because of the lack of adequate rainfall estimates in northern Peru and the Ecuadorian Amazon.

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.

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.

Using satellite-based measurements to explore ...

Science.gov (United States)

New particle formation (NPF) can potentially alter regional climate by increasing aerosol particle (hereafter particle) number concentrations and ultimately cloud condensation nuclei. The large scales on which NPF is manifest indicate potential to use satellite-based (inherently spatially averaged) measurements of atmospheric conditions to diagnose the occurrence of NPF and NPF characteristics. We demonstrate the potential for using satellite-measurements of insolation (UV), trace gas concentrations (sulfur dioxide (SO2), nitrogen dioxide (NO2), ammonia (NH3), formaldehyde (HCHO), ozone (O3)), aerosol optical properties (aerosol optical depth (AOD), Ångström exponent (AE)), and a proxy of biogenic volatile organic compound emissions (leaf area index (LAI), temperature (T)) as predictors for NPF characteristics: formation rates, growth rates, survival probabilities, and ultrafine particle (UFP) concentrations at five locations across North America. NPF at all sites is most frequent in spring, exhibits a one-day autocorrelation, and is associated with low condensational sink (AOD×AE) and HCHO concentrations, and high UV. However, there are important site-to-site variations in NPF frequency and characteristics, and in which of the predictor variables (particularly gas concentrations) significantly contribute to the explanatory power of regression models built to predict those characteristics. This finding may provide a partial explanation for the reported spatia

Estimations of natural variability between satellite measurements of trace species concentrations

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Sheese, P.; Walker, K. A.; Boone, C. D.; Degenstein, D. A.; Kolonjari, F.; Plummer, D. A.; von Clarmann, T.

2017-12-01

In order to validate satellite measurements of atmospheric states, it is necessary to understand the range of random and systematic errors inherent in the measurements. On occasions where the measurements do not agree within those errors, a common "go-to" explanation is that the unexplained difference can be chalked up to "natural variability". However, the expected natural variability is often left ambiguous and rarely quantified. This study will look to quantify the expected natural variability of both O3 and NO2 between two satellite instruments: ACE-FTS (Atmospheric Chemistry Experiment - Fourier Transform Spectrometer) and OSIRIS (Optical Spectrograph and Infrared Imaging System). By sampling the CMAM30 (30-year specified dynamics simulation of the Canadian Middle Atmosphere Model) climate chemistry model throughout the upper troposphere and stratosphere at times and geolocations of coincident ACE-FTS and OSIRIS measurements at varying coincidence criteria, height-dependent expected values of O3 and NO2 variability will be estimated and reported on. The results could also be used to better optimize the coincidence criteria used in satellite measurement validation studies.

Overview of Boundary Layer Clouds Using Satellite and Ground-Based Measurements

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Xi, B.; Dong, X.; Wu, P.; Qiu, S.

2017-12-01

A comprehensive summary of boundary layer clouds properties based on our few recently studies will be presented. The analyses include the global cloud fractions and cloud macro/micro- physical properties based on satellite measurements using both CERES-MODIS and CloudSat/Caliposo data products,; the annual/seasonal/diurnal variations of stratocumulus clouds over different climate regions (mid-latitude land, mid-latitude ocean, and Arctic region) using DOE ARM ground-based measurements over Southern great plain (SGP), Azores (GRW), and North slope of Alaska (NSA) sites; the impact of environmental conditions to the formation and dissipation process of marine boundary layer clouds over Azores site; characterizing Arctice mixed-phase cloud structure and favorable environmental conditions for the formation/maintainess of mixed-phase clouds over NSA site. Though the presentation has widely spread topics, we will focus on the representation of the ground-based measurements over different climate regions; evaluation of satellite retrieved cloud properties using these ground-based measurements, and understanding the uncertainties of both satellite and ground-based retrievals and measurements.

Wageningen Urban Rainfall Experiment 2014 (WURex14): Experimental Setup and First Results

Science.gov (United States)

van Leth, Thomas; Uijlenhoet, Remko; Overeem, Aart; Leijnse, Hidde; Hazenberg, Pieter

2015-04-01

Microwave links from cellular communication networks have been shown to be able to provide valuable information concerning the space-time variability of rainfall. In particular over urban areas, where network densities are generally high, they have the potential to complement existing dedicated infrastructure to measure rainfall (gauges, radars). In addition, microwave links provide a great opportunity for ground-based rainfall measurement for those land surface areas of the world where gauges and radars are generally lacking, e.g. Africa, Latin America, and large parts of Asia. Such information is not only crucial for water management and agriculture, but also for instance for ground validation of space-borne rainfall estimates such as those provided by the recently launched core satellite of the GPM (Global Precipitation Measurement) mission. WURex14 is dedicated to address several errors and uncertainties associated with such quantitative precipitation estimates in detail. The core of the experiment is provided by two co-located microwave links installed between two major buildings on the Wageningen University campus, approximately 2 km apart: a 38 GHz commercial microwave link, kindly provided to us by T-Mobile NL, and a 38 GHz dual-polarization research microwave link from RAL. Transmitting and receiving antennas have been attached to masts installed on the roofs of the two buildings, about 30 m above the ground. This setup has been complemented with a Scintec infrared Large-Aperture Scintillometer, installed over the same path, as well as a Parsivel optical disdrometer, located close to the mast on the receiving end of the links. During the course of the experiment, a 26 GHz RAL research microwave link was added to the experimental setup. Temporal sampling of the received signals was performed at a rate of 20 Hz. In addition, two time-lapse cameras have been installed on either side of the path to monitor the wetness of the antennas as well as the state of

Water storage and evaporation as constituents of rainfall interception

NARCIS (Netherlands)

Klaassen, W; Bosveld, F; de Water, E

1998-01-01

Intercepted rainfall may be evaporated during or after the rain event. Intercepted rain is generally determined as the difference between rainfall measurements outside and inside the forest. Such measurements are often used to discriminate between water storage and evaporation during rain as well.

Comparison of Ground- and Space-based Radar Observations with Disdrometer Measurements During the PECAN Field Campaign

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Torres, A. D.; Rasmussen, K. L.; Bodine, D. J.; Dougherty, E.

2015-12-01

Plains Elevated Convection At Night (PECAN) was a large field campaign that studied nocturnal mesoscale convective systems (MCSs), convective initiation, bores, and low-level jets across the central plains in the United States. MCSs are responsible for over half of the warm-season precipitation across the central U.S. plains. The rainfall from deep convection of these systems over land have been observed to be underestimated by satellite radar rainfall-retrieval algorithms by as much as 40 percent. These algorithms have a strong dependence on the generally unmeasured rain drop-size distribution (DSD). During the campaign, our group measured rainfall DSDs, precipitation fall velocities, and total precipitation in the convective and stratiform regions of MCSs using Ott Parsivel optical laser disdrometers. The disdrometers were co-located with mobile pod units that measured temperature, wind, and relative humidity for quality control purposes. Data from the operational NEXRAD radar in LaCrosse, Wisconsin and space-based radar measurements from a Global Precipitation Measurement satellite overpass on July 13, 2015 were used for the analysis. The focus of this study is to compare DSD measurements from the disdrometers to radars in an effort to reduce errors in existing rainfall-retrieval algorithms. The error analysis consists of substituting measured DSDs into existing quantitative precipitation estimation techniques (e.g. Z-R relationships and dual-polarization rain estimates) and comparing these estimates to ground measurements of total precipitation. The results from this study will improve climatological estimates of total precipitation in continental convection that are used in hydrological studies, climate models, and other applications.

Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems

Science.gov (United States)

Verdin, Andrew; Funk, Christopher C.; Rajagopalan, Balaji; Kleiber, William

2016-01-01

Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.

Monthly Rainfall Erosivity Assessment for Switzerland

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Schmidt, Simon; Meusburger, Katrin; Alewell, Christine

2016-04-01

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

Utilization of satellite images to understand the dynamics of Pampas shallow lakes

Directory of Open Access Journals (Sweden)

V. S. Aliaga

2016-06-01

Full Text Available The aim of this study was to analyze satellite images of different spatial resolutions to interpret the morphometric behavior of six shallow lakes of the Pampas, Argentina. These are characterized by having different rainfall regimes. Morphometric response considering each location, site conditions and dry and wet extreme events is analyzed. Standardized Precipitation Index (IEP for determination of wet, dry and normal years was used. This analysis showed that the Pampas shallow lakes do not behave in the same way to the rainfall events. Its origin, socio-economic use and rainfall patterns affect their spatiotemporal variation and morphometric.

Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

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Wolff, David B.; Fisher, Brad L.

2011-01-01

Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25deg terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSR-E over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm/hr. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU

Climatic Analysis of Oceanic Water Vapor Transports Based on Satellite E-P Datasets

Science.gov (United States)

Smith, Eric A.; Sohn, Byung-Ju; Mehta, Vikram

2004-01-01

Understanding the climatically varying properties of water vapor transports from a robust observational perspective is an essential step in calibrating climate models. This is tantamount to measuring year-to-year changes of monthly- or seasonally-averaged, divergent water vapor transport distributions. This cannot be done effectively with conventional radiosonde data over ocean regions where sounding data are generally sparse. This talk describes how a methodology designed to derive atmospheric water vapor transports over the world oceans from satellite-retrieved precipitation (P) and evaporation (E) datasets circumvents the problem of inadequate sampling. Ultimately, the method is intended to take advantage of the relatively complete and consistent coverage, as well as continuity in sampling, associated with E and P datasets obtained from satellite measurements. Independent P and E retrievals from Special Sensor Microwave Imager (SSM/I) measurements, along with P retrievals from Tropical Rainfall Measuring Mission (TRMM) measurements, are used to obtain transports by solving a potential function for the divergence of water vapor transport as balanced by large scale E - P conditions.

Forecasting Andean rainfall and crop yield from the influence of El Nino on Pleiades visibility

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Orlove; Chiang; Cane

2000-01-06

Farmers in drought-prone regions of Andean South America have historically made observations of changes in the apparent brightness of stars in the Pleiades around the time of the southern winter solstice in order to forecast interannual variations in summer rainfall and in autumn harvests. They moderate the effect of reduced rainfall by adjusting the planting dates of potatoes, their most important crop. Here we use data on cloud cover and water vapour from satellite imagery, agronomic data from the Andean altiplano and an index of El Nino variability to analyse this forecasting method. We find that poor visibility of the Pleiades in June-caused by an increase in subvisual high cirrus clouds-is indicative of an El Nino year, which is usually linked to reduced rainfall during the growing season several months later. Our results suggest that this centuries-old method of seasonal rainfall forecasting may be based on a simple indicator of El Nino variability.

A method for combining passive microwave and infrared rainfall observations

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Kummerow, Christian; Giglio, Louis

1995-01-01

Because passive microwave instruments are confined to polar-orbiting satellites, rainfall estimates must interpolate across long time periods, during which no measurements are available. In this paper the authors discuss a technique that allows one to partially overcome the sampling limitations by using frequent infrared observations from geosynchronous platforms. To accomplish this, the technique compares all coincident microwave and infrared observations. From each coincident pair, the infrared temperature threshold is selected that corresponds to an area equal to the raining area observed in the microwave image. The mean conditional rainfall rate as determined from the microwave image is then assigned to pixels in the infrared image that are colder than the selected threshold. The calibration is also applied to a fixed threshold of 235 K for comparison with established infrared techniques. Once a calibration is determined, it is applied to all infrared images. Monthly accumulations for both methods are then obtained by summing rainfall from all available infrared images. Two examples are used to evaluate the performance of the technique. The first consists of a one-month period (February 1988) over Darwin, Australia, where good validation data are available from radar and rain gauges. For this case it was found that the technique approximately doubled the rain inferred by the microwave method alone and produced exceptional agreement with the validation data. The second example involved comparisons with atoll rain gauges in the western Pacific for June 1989. Results here are overshadowed by the fact that the hourly infrared estimates from established techniques, by themselves, produced very good correlations with the rain gauges. The calibration technique was not able to improve upon these results.

Heavy rainfall in Mediterranean cyclones. Part I: contribution of deep convection and warm conveyor belt

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Flaounas, Emmanouil; Kotroni, Vassiliki; Lagouvardos, Konstantinos; Gray, Suzanne L.; Rysman, Jean-François; Claud, Chantal

2018-04-01

In this study, we provide an insight to the role of deep convection (DC) and the warm conveyor belt (WCB) as leading processes to Mediterranean cyclones' heavy rainfall. To this end, we use reanalysis data, lighting and satellite observations to quantify the relative contribution of DC and the WCB to cyclone rainfall, as well as to analyse the spatial and temporal variability of these processes with respect to the cyclone centre and life cycle. Results for the period 2005-2015 show that the relationship between cyclone rainfall and intensity has high variability and demonstrate that even intense cyclones may produce low rainfall amounts. However, when considering rainfall averages for cyclone intensity bins, a linear relationship was found. We focus on the 500 most intense tracked cyclones (responsible for about 40-50% of the total 11-year Mediterranean rainfall) and distinguish between the ones producing high and low rainfall amounts. DC and the WCB are found to be the main cause of rainfall for the former (producing up to 70% of cyclone rainfall), while, for the latter, DC and the WCB play a secondary role (producing up to 50% of rainfall). Further analysis showed that rainfall due to DC tends to occur close to the cyclones' centre and to their eastern sides, while the WCBs tend to produce rainfall towards the northeast. In fact, about 30% of rainfall produced by DC overlaps with rainfall produced by WCBs but this represents only about 8% of rainfall produced by WCBs. This suggests that a considerable percentage of DC is associated with embedded convection in WCBs. Finally, DC was found to be able to produce higher rain rates than WCBs, exceeding 50 mm in 3-h accumulated rainfall compared to a maximum of the order of 40 mm for WCBs. Our results demonstrate in a climatological framework the relationship between cyclone intensity and processes that lead to heavy rainfall, one of the most prominent environmental risks in the Mediterranean. Therefore, we set

Hydrologic and Erosional Response to Natural Rainfall and Effects of Conservation and Rehabilitation Measures in a Degraded Dry Sub-Humid Watershed of the Ethiopian Highlands

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McHugh, O. V.; Liu, B. M.; Steenhuis, T. S.

2005-12-01

A good understanding of runoff and erosion under actual field conditions is essential for effective planning of land conservation in the Ethiopian highlands. Hydrologic and sediment yield response to natural rainfall was measured during 3 rainy seasons (2003-2004) at plot and catchment scales with and without conservation practices. Results show that as expected surface runoff generation and erosion rates are significantly influenced by rainfall intensity, land use, scale of measurement, land slope, and the presence or not of conservation measures. Seasonal runoff coefficient and sediment yield were significantly better correlated to number of storms with high 30-minute maximum rainfall intensity (I30 > 20 mm h-1) than to total seasonal rainfall depth. Under conventional management systems cropland on slopes greater than 3 % generated significantly more (over twice) surface runoff and sediment yield compared with shrub and open forest grazing land on steep slopes (34 %). Plot measured surface runoff coefficients (for crop and grazing land uses which cover over 90 % of the catchment area) exceeded total catchment streamflow discharge demonstrating a scale effect. The observed scale effect, a stronger correlation of runoff with maximum rainfall intensity than rainfall depth and average rainfall intensity, and observed significant increases in runoff with steeper land slopes indicate that Hortonian overland flow is the primary runoff generation mechanism in the study zone. Concerning slope effects, cropland on mild slopes produced relatively low seasonal sediment yields (hillside conservation (areas with bench terracing, planted tree seedlings, and small area closure from livestock grazing) resulted in significantly lower catchment peak streamflow discharge and longer duration streamflow compared to a catchment in the same watershed without these measures. Cropland tied ridge and no till conservation practices reduced surface runoff and soil loss during seasons with

Disaggregating radar-derived rainfall measurements in East Azarbaijan, Iran, using a spatial random-cascade model

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Fouladi Osgouei, Hojjatollah; Zarghami, Mahdi; Ashouri, Hamed

2017-07-01

The availability of spatial, high-resolution rainfall data is one of the most essential needs in the study of water resources. These data are extremely valuable in providing flood awareness for dense urban and industrial areas. The first part of this paper applies an optimization-based method to the calibration of radar data based on ground rainfall gauges. Then, the climatological Z-R relationship for the Sahand radar, located in the East Azarbaijan province of Iran, with the help of three adjacent rainfall stations, is obtained. The new climatological Z-R relationship with a power-law form shows acceptable statistical performance, making it suitable for radar-rainfall estimation by the Sahand radar outputs. The second part of the study develops a new heterogeneous random-cascade model for spatially disaggregating the rainfall data resulting from the power-law model. This model is applied to the radar-rainfall image data to disaggregate rainfall data with coverage area of 512 × 512 km2 to a resolution of 32 × 32 km2. Results show that the proposed model has a good ability to disaggregate rainfall data, which may lead to improvement in precipitation forecasting, and ultimately better water-resources management in this arid region, including Urmia Lake.

Application of Vision Metrology to In-Orbit Measurement of Large Reflector Onboard Communication Satellite for Next Generation Mobile Satellite Communication

Science.gov (United States)

Akioka, M.; Orikasa, T.; Satoh, M.; Miura, A.; Tsuji, H.; Toyoshima, M.; Fujino, Y.

2016-06-01

Satellite for next generation mobile satellite communication service with small personal terminal requires onboard antenna with very large aperture reflector larger than twenty meters diameter because small personal terminal with lower power consumption in ground base requires the large onboard reflector with high antenna gain. But, large deployable antenna will deform in orbit because the antenna is not a solid dish but the flexible structure with fine cable and mesh supported by truss. Deformation of reflector shape deteriorate the antenna performance and quality and stability of communication service. However, in case of digital beam forming antenna with phased array can modify the antenna beam performance due to adjustment of excitation amplitude and excitation phase. If we can measure the reflector shape precisely in orbit, beam pattern and antenna performance can be compensated with the updated excitation amplitude and excitation phase parameters optimized for the reflector shape measured every moment. Softbank Corporation and National Institute of Information and Communications Technology has started the project "R&D on dynamic beam control technique for next generation mobile communication satellite" as a contracted research project sponsored by Ministry of Internal Affairs and Communication of Japan. In this topic, one of the problem in vision metrology application is a strong constraints on geometry for camera arrangement on satellite bus with very limited space. On satellite in orbit, we cannot take many images from many different directions as ordinary vision metrology measurement and the available area for camera positioning is quite limited. Feasibility of vision metrology application and general methodology to apply to future mobile satellite communication satellite is to be found. Our approach is as follows: 1) Development of prototyping simulator to evaluate the expected precision for network design in zero order and first order 2) Trial

Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network

Directory of Open Access Journals (Sweden)

N. Peleg

2013-06-01

Full Text Available Runoff and flash flood generation are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires furthering our knowledge of the uncertainties of these data. In 2011, a new super-dense network of rain gauges containing 14 stations, each with two side-by-side gauges, was installed within a 4 km2 study area near Kibbutz Galed in northern Israel. This network was established for a detailed exploration of the uncertainties and errors regarding rainfall variability within a common pixel size of data obtained from remote sensing systems for timescales of 1 min to daily. In this paper, we present the analysis of the first year's record collected from this network and from the Shacham weather radar, located 63 km from the study area. The gauge–rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The nugget parameter of the inter-gauge rainfall correlations was high (0.92 on the 1 min scale and increased as the timescale increased. The variance reduction factor (VRF, representing the uncertainty from averaging a number of rain stations per pixel, ranged from 1.6% for the 1 min timescale to 0.07% for the daily scale. It was also found that at least three rain stations are needed to adequately represent the rainfall (VRF < 5% on a typical radar pixel scale. The difference between radar and rain gauge rainfall was mainly attributed to radar estimation errors, while the gauge sampling error contributed up to 20% to the total difference. The ratio of radar rainfall to gauge-areal-averaged rainfall, expressed by the error distribution scatter parameter, decreased from 5.27 dB for 3 min timescale to 3.21 dB for the daily scale. The analysis of the radar errors and uncertainties suggest that a temporal scale of at least 10 min should be used for

Defense meteorological satellite measurements of total ozone

International Nuclear Information System (INIS)

Lovill, J.E.; Ellis, J.S.; Luther, F.M.; Sullivan, R.J.; Weichel, R.L.

1992-01-01

A multichannel filter radiometer (MFR) on Defense Meteorological Satellites (DMS) that measured total ozone on a global-scale from March 1977 - February 1980 is described. The total ozone data measured by the MFR were compared with total ozone data taken by surfaced-based Dobson spectrophotometers. When comparisons were made for five months, the Dobson spectrophotometer measured 2-5% more total ozone than the MFR. Comparisons between the Dobson spectrophotometer and the MFR showed a reduced RMS difference as the comparisons were made at closer proximity. A Northern Hemisphere total ozone distribution obtained from MFR data is presented

A small single-nozzle rainfall simulator to measure erosion response on different burn severities in southern British Columbia, Canada

Science.gov (United States)

Covert, Ashley; Jordan, Peter

2010-05-01

To study the effects of wildfire burn severity on runoff generation and soil erosion from high intensity rainfall, we constructed an effective yet simple rainfall simulator that was inexpensive, portable and easily operated by two people on steep, forested slopes in southern British Columbia, Canada. The entire apparatus, including simulator, pumps, hoses, collapsible water bladders and sample bottles, was designed to fit into a single full-sized pick-up truck. The three-legged simulator extended to approximately 3.3 metres above ground on steep slopes and used a single Spraying Systems 1/2HH-30WSQ nozzle which can easily be interchanged for other sized nozzles. Rainfall characteristics were measured using a digital camera which took images of the raindrops against a grid. Median drop size and velocity 5 cm above ground were measured and found to be 3/4 of the size of natural rain drops of that diameter class, and fell 7% faster than terminal velocity. The simulator was used for experiments on runoff and erosion on sites burned in 2007 by two wildfires in southern British Columbia. Simulations were repeated one and two years after the fires. Rainfall was simulated at an average rate of 67 mm hr-1 over a 1 m2 plot for 20 minutes. This rainfall rate is similar to the 100 year return period rainfall intensity for this duration at a nearby weather station. Simulations were conducted on five replicate 1 m2 plots in each experimental unit including high burn severity, moderate burn severity, unburned, and unburned with forest floor removed. During the simulation a sample was collected for 30 seconds every minute, with two additional samples until runoff ceased, resulting in 22 samples per simulation. Runoff, overland flow coefficient, infiltration and sediment yield were compared between treatments. Additional simulations were conducted immediately after a 2009 wildfire to test different mulch treatments. Typical results showed that runoff on plots with high burn

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.

Assessing water availability over peninsular Malaysia using public domain satellite data products

International Nuclear Information System (INIS)

Ali, M I; Hashim, M; Zin, H S M

2014-01-01

Water availability monitoring is an essential task for water resource sustainability and security. In this paper, the assessment of satellite remote sensing technique for determining water availability is reported. The water-balance analysis is used to compute the spatio-temporal water availability with main inputs; the precipitation and actual evapotranspiration rate (AET), both fully derived from public-domain satellite products of Tropical Rainfall Measurement Mission (TRMM) and MODIS, respectively. Both these satellite products were first subjected to calibration to suit corresponding selected local precipitation and AET samples. Multi-temporal data sets acquired 2000-2010 were used in this study. The results of study, indicated strong agreement of monthly water availability with the basin flow rate (r 2 = 0.5, p < 0.001). Similar agreements were also noted between the estimated annual average water availability with the in-situ measurement. It is therefore concluded that the method devised in this study provide a new alternative for water availability mapping over large area, hence offers the only timely and cost-effective method apart from providing comprehensive spatio-temporal patterns, crucial in water resource planning to ensure water security

Impact of atmospheric circulation types on southwest Asian dust and Indian summer monsoon rainfall

Science.gov (United States)

Kaskaoutis, D. G.; Houssos, E. E.; Solmon, F.; Legrand, M.; Rashki, A.; Dumka, U. C.; Francois, P.; Gautam, R.; Singh, R. P.

2018-03-01

This study examines the meteorological feedback on dust aerosols and rainfall over the Arabian Sea and India during the summer monsoon using satellite data, re-analysis and a regional climate model. Based on days with excess aerosol loading over the central Ganges basin during May - September, two distinct atmospheric circulation types (weather clusters) are identified, which are associated with different dust-aerosol and rainfall distributions over south Asia, highlighting the role of meteorology on dust emissions and monsoon rainfall. Each cluster is characterized by different patterns of mean sea level pressure (MSLP), geopotential height at 700 hPa (Z700) and wind fields at 1000 hPa and at 700 hPa, thus modulating changes in dust-aerosol loading over the Arabian Sea. One cluster is associated with deepening of the Indian/Pakistan thermal low leading to (i) increased cyclonicity and thermal convection over northwestern India and Arabian Peninsula, (ii) intensification of the southwest monsoon off the Horn of Africa, iii) increase in dust emissions from Rub-Al-Khali and Somalian deserts, (iv) excess dust accumulation over the Arabian Sea and, (v) strengthening of the convergence of humid air masses and larger precipitation over Indian landmass compared to the other cluster. The RegCM4.4 model simulations for dust-aerosol and precipitation distributions support the meteorological fields and satellite observations, while the precipitation over India is positively correlated with the aerosol loading over the Arabian Sea on daily basis for both weather clusters. This study highlights the key role of meteorology and atmospheric dynamics on dust life cycle and rainfall over the monsoon-influenced south Asia.

Use of GOES, SSM/I, TRMM Satellite Measurements Estimating Water Budget Variations in Gulf of Mexico - Caribbean Sea Basins

Science.gov (United States)

Smith, Eric A.

2004-01-01

This study presents results from a multi-satellite/multi-sensor retrieval system designed to obtain the atmospheric water budget over the open ocean. A combination of 3ourly-sampled monthly datasets derived from the GOES-8 5-channel Imager, the TRMM TMI radiometer, and the DMSP 7-channel passive microwave radiometers (SSM/I) have been acquired for the combined Gulf of Mexico-Caribbean Sea basin. Whereas the methodology has been tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the TRMM and SSM/I passive microwave measurements in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, the intent is to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is validated by cross-checking all the algorithm components through multiple- algorithm retrieval intercomparisons. A further check on the validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithms to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin, although it is fair to say that these checks are more effective m identifying problems in estimating vapor transports from a leaky operational radiosonde network than in verifying

A multi-source satellite data approach for modelling Lake Turkana water level: calibration and validation using satellite altimetry data

Directory of Open Access Journals (Sweden)

N. M. Velpuri

2012-01-01

Full Text Available Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of inter- and intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellite-driven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE of 0.80 during the validation period (2004–2009. Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1–2 m. The lake level fluctuated in the range up to 4 m between the years 1998–2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated

Urban rainfall estimation employing commercial microwave links

Science.gov (United States)

Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko; ten Veldhuis, Marie-claire

2015-04-01

Urban areas often lack rainfall information. To increase the number of rainfall observations in cities, microwave links from operational cellular telecommunication networks may be employed. Although this new potential source of rainfall information has been shown to be promising, its quality needs to be demonstrated more extensively. In the Rain Sense kickstart project of the Amsterdam Institute for Advanced Metropolitan Solutions (AMS), sensors and citizens are preparing Amsterdam for future weather. Part of this project is rainfall estimation using new measurement techniques. Innovative sensing techniques will be utilized such as rainfall estimation from microwave links, umbrellas for weather sensing, low-cost sensors at lamp posts and in drainage pipes for water level observation. These will be combined with information provided by citizens in an active way through smartphone apps and in a passive way through social media posts (Twitter, Flickr etc.). Sensor information will be integrated, visualized and made accessible to citizens to help raise citizen awareness of urban water management challenges and promote resilience by providing information on how citizens can contribute in addressing these. Moreover, citizens and businesses can benefit from reliable weather information in planning their social and commercial activities. In the end city-wide high-resolution rainfall maps will be derived, blending rainfall information from microwave links and weather radars. This information will be used for urban water management. This presentation focuses on rainfall estimation from commercial microwave links. Received signal levels from tens of microwave links within the Amsterdam region (roughly 1 million inhabitants) in the Netherlands are utilized to estimate rainfall with high spatial and temporal resolution. Rainfall maps will be presented and compared to a gauge-adjusted radar rainfall data set. Rainfall time series from gauge(s), radars and links will be compared.

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.

The 1988-2003 Greenland ice sheet melt extent using passive microwave satellite data and a regional climate model

Energy Technology Data Exchange (ETDEWEB)

Fettweis, Xavier; Ypersele, Jean-Pascal van [Universite Catholique de Louvain, Institut d' Astronomie et de Geophysique de G. Lemaitre, Louvain-La-Neuve (Belgium); Gallee, Hubert [CNRS, Laboratoire de Glaciologie et Geophysique de l' Environnement, Grenoble (France); Lefebre, Filip [Vito-IMS (Flemish Institute for Technological Research-Integral Environmental Studies), Mol (Belgium)

2006-10-15

Measurements from ETH-Camp and JAR1 AWS (West Greenland) as well as coupled atmosphere-snow regional climate simulations have highlighted flaws in the cross-polarized gradient ratio (XPGR) technique used to identify melt from passive microwave satellite data. It was found that dense clouds (causing notably rainfall) on the ice sheet severely perturb the XPGR melt signal. Therefore, the original XPGR melt detection algorithm has been adapted to better incorporate atmospheric variability over the ice sheet and an updated melt trend for the 1988-2003 period has been calculated. Compared to the original algorithm, the melt zone area increase is eight times higher (from 0.2 to 1.7% year{sup -1}). The increase is higher with the improved XPGR technique because rainfall also increased during this period. It is correlated to higher atmospheric temperatures. Finally, the model shows that the total ice sheet runoff is directly proportional to the melt extent surface detected by satellites. These results are important for the understanding of the effect of Greenland melting on the stability of the thermohaline circulation. (orig.)

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

Global distribution of pauses observed with satellite measurements

Indian Academy of Sciences (India)

Here we study the commonality and differences observed in the variability of all the pauses. We also examined how good other datasets will represent these features among (and in between) different satellite measurements, re-analysis, and model data. Hemispheric differences observed in all the pauses are also reported.

Rainfall estimation for hydrology using volumetric weather radar

NARCIS (Netherlands)

Hazenberg, P.

2013-01-01

This thesis focuses specifically on weather radar rainfall measurements in strati form precipitation. In North-Western Europe this type of precipitation is most dominant in winter and leads to the largest hydro logical response of catchments. Unfortunately, the quality of uncorrected radar rainfall

Urban rainfall estimation employing commercial microwave links (poster)

NARCIS (Netherlands)

Overeem, A.; Leijnse, H.; Uijlenhoet, R.; Ten Veldhuis, J.A.E.

2015-01-01

In the Rain Sense kickstart project of the Amsterdam Institute for Advanced Metropolitan Solutions (AMS), sensors and citizens are preparing Amsterdam for future weather. Urban areas often lack rainfall information. Hence, new rainfall measurement techniques are important. E.g., the number of

Total ozone retrieval from satellite multichannel filter radiometer measurements

International Nuclear Information System (INIS)

Lovill, J.E.; Sullivan, T.J.; Weichel, R.L.; Ellis, J.S.; Huebel, J.G.; Korver, J.; Weidhaas, P.P.; Phelps, F.A.

1978-01-01

A total ozone retrieval model has been developed to process radiance data gathered by a satellite-mounted multichannel filter radiometer (MFR). Extensive effort went into theoretical radiative transfer modeling, a retrieval scheme was developed, and the technique was applied to the MFR radiance measurements. The high quality of the total ozone retrieval results was determined through comparisons with Dobson measurements. Included in the report are global total ozone maps for 20 days between May 12 and July 5, 1977. A comparison of MFR results for 13 days in June 1977 with Dobson spectrophotometer measurements of ozone for the same period showed good agreement: there was a root-mean-square difference of 6.2% (equivalent to 20.2 m.atm.cm). The estimated global total ozone value for June 1977 (296 m.atm.cm) was in good agreement with satellite backscatter ultraviolet data for June 1970 (304 m.atm.cm) and June 1971

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.

Coarse Initial Orbit Determination for a Geostationary Satellite Using Single-Epoch GPS Measurements

Directory of Open Access Journals (Sweden)

Ghangho Kim

2015-04-01

Full Text Available A practical algorithm is proposed for determining the orbit of a geostationary orbit (GEO satellite using single-epoch measurements from a Global Positioning System (GPS receiver under the sparse visibility of the GPS satellites. The algorithm uses three components of a state vector to determine the satellite’s state, even when it is impossible to apply the classical single-point solutions (SPS. Through consideration of the characteristics of the GEO orbital elements and GPS measurements, the components of the state vector are reduced to three. However, the algorithm remains sufficiently accurate for a GEO satellite. The developed algorithm was tested on simulated measurements from two or three GPS satellites, and the calculated maximum position error was found to be less than approximately 40 km or even several kilometers within the geometric range, even when the classical SPS solution was unattainable. In addition, extended Kalman filter (EKF tests of a GEO satellite with the estimated initial state were performed to validate the algorithm. In the EKF, a reliable dynamic model was adapted to reduce the probability of divergence that can be caused by large errors in the initial state.

Coarse Initial Orbit Determination for a Geostationary Satellite Using Single-Epoch GPS Measurements

Science.gov (United States)

Kim, Ghangho; Kim, Chongwon; Kee, Changdon

2015-01-01

A practical algorithm is proposed for determining the orbit of a geostationary orbit (GEO) satellite using single-epoch measurements from a Global Positioning System (GPS) receiver under the sparse visibility of the GPS satellites. The algorithm uses three components of a state vector to determine the satellite’s state, even when it is impossible to apply the classical single-point solutions (SPS). Through consideration of the characteristics of the GEO orbital elements and GPS measurements, the components of the state vector are reduced to three. However, the algorithm remains sufficiently accurate for a GEO satellite. The developed algorithm was tested on simulated measurements from two or three GPS satellites, and the calculated maximum position error was found to be less than approximately 40 km or even several kilometers within the geometric range, even when the classical SPS solution was unattainable. In addition, extended Kalman filter (EKF) tests of a GEO satellite with the estimated initial state were performed to validate the algorithm. In the EKF, a reliable dynamic model was adapted to reduce the probability of divergence that can be caused by large errors in the initial state. PMID:25835299

CDRD and PNPR satellite passive microwave precipitation retrieval algorithms: EuroTRMM/EURAINSAT origins and H-SAF operations

Science.gov (United States)

Mugnai, A.; Smith, E. A.; Tripoli, G. J.; Bizzarri, B.; Casella, D.; Dietrich, S.; Di Paola, F.; Panegrossi, G.; Sanò, P.

2013-04-01

Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) is a EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) program, designed to deliver satellite products of hydrological interest (precipitation, soil moisture and snow parameters) over the European and Mediterranean region to research and operations users worldwide. Six satellite precipitation algorithms and concomitant precipitation products are the responsibility of various agencies in Italy. Two of these algorithms have been designed for maximum accuracy by restricting their inputs to measurements from conical and cross-track scanning passive microwave (PMW) radiometers mounted on various low Earth orbiting satellites. They have been developed at the Italian National Research Council/Institute of Atmospheric Sciences and Climate in Rome (CNR/ISAC-Rome), and are providing operational retrievals of surface rain rate and its phase properties. Each of these algorithms is physically based, however, the first of these, referred to as the Cloud Dynamics and Radiation Database (CDRD) algorithm, uses a Bayesian-based solution solver, while the second, referred to as the PMW Neural-net Precipitation Retrieval (PNPR) algorithm, uses a neural network-based solution solver. Herein we first provide an overview of the two initial EU research and applications programs that motivated their initial development, EuroTRMM and EURAINSAT (European Satellite Rainfall Analysis and Monitoring at the Geostationary Scale), and the current H-SAF program that provides the framework for their operational use and continued development. We stress the relevance of the CDRD and PNPR algorithms and their precipitation products in helping secure the goals of H-SAF's scientific and operations agenda, the former helpful as a secondary calibration reference to other algorithms in H-SAF's complete mix of algorithms. Descriptions of the algorithms' designs are provided

CDRD and PNPR satellite passive microwave precipitation retrieval algorithms: EuroTRMM/EURAINSAT origins and H-SAF operations

Directory of Open Access Journals (Sweden)

A. Mugnai

2013-04-01

Full Text Available Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF is a EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites program, designed to deliver satellite products of hydrological interest (precipitation, soil moisture and snow parameters over the European and Mediterranean region to research and operations users worldwide. Six satellite precipitation algorithms and concomitant precipitation products are the responsibility of various agencies in Italy. Two of these algorithms have been designed for maximum accuracy by restricting their inputs to measurements from conical and cross-track scanning passive microwave (PMW radiometers mounted on various low Earth orbiting satellites. They have been developed at the Italian National Research Council/Institute of Atmospheric Sciences and Climate in Rome (CNR/ISAC-Rome, and are providing operational retrievals of surface rain rate and its phase properties. Each of these algorithms is physically based, however, the first of these, referred to as the Cloud Dynamics and Radiation Database (CDRD algorithm, uses a Bayesian-based solution solver, while the second, referred to as the PMW Neural-net Precipitation Retrieval (PNPR algorithm, uses a neural network-based solution solver. Herein we first provide an overview of the two initial EU research and applications programs that motivated their initial development, EuroTRMM and EURAINSAT (European Satellite Rainfall Analysis and Monitoring at the Geostationary Scale, and the current H-SAF program that provides the framework for their operational use and continued development. We stress the relevance of the CDRD and PNPR algorithms and their precipitation products in helping secure the goals of H-SAF's scientific and operations agenda, the former helpful as a secondary calibration reference to other algorithms in H-SAF's complete mix of algorithms. Descriptions of the algorithms' designs are

Added value of online satellite data transmission for flood forecasting: warning systems in medium-size catchments.

Science.gov (United States)

Ruch, C; Stadler, H

2009-01-01

The present paper deals with the implementation of online data transferred via LEO satellite communication in a flood forecasting system. Although the project is ongoing, it is already recognised that the information chain: "measurement-transmission-forecast-alert" can be shortened, i.e., the flood danger can be more rapidly communicated to the population at risk. This gain is particularly valuable for medium size catchments where the concentration time (basin time of response to rainfall) is short.

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...

Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi

Directory of Open Access Journals (Sweden)

D. Kneis

2014-07-01

Full Text Available The paper examines the quality of satellite-based precipitation estimates for the lower Mahanadi River basin (eastern India. The considered data sets known as 3B42 and 3B42-RT (version 7/7A are routinely produced by the tropical rainfall measuring mission (TRMM from passive microwave and infrared recordings. While the 3B42-RT data are disseminated in real time, the gauge-adjusted 3B42 data set is published with a delay of some months. The quality of the two products was assessed in a two-step procedure. First, the correspondence between the remotely sensed precipitation rates and rain gauge data was evaluated at the sub-basin scale. Second, the quality of the rainfall estimates was assessed by analysing their performance in the context of rainfall–runoff simulation. At sub-basin level (4000 to 16 000 km2 the satellite-based areal precipitation estimates were found to be moderately correlated with the gauge-based counterparts (R2 of 0.64–0.74 for 3B42 and 0.59–0.72 for 3B42-RT. Significant discrepancies between TRMM data and ground observations were identified at high-intensity levels. The rainfall depth derived from rain gauge data is often not reflected by the TRMM estimates (hit rate 80 mm day-1. At the same time, the remotely sensed rainfall rates frequently exceed the gauge-based equivalents (false alarm ratios of 0.2–0.6. In addition, the real-time product 3B42-RT was found to suffer from a spatially consistent negative bias. Since the regionalisation of rain gauge data is potentially associated with a number of errors, the above results are subject to uncertainty. Hence, a validation against independent information, such as stream flow, was essential. In this case study, the outcome of rainfall–runoff simulation experiments was consistent with the above-mentioned findings. The best fit between observed and simulated stream flow was obtained if rain gauge data were used as model input (Nash–Sutcliffe index of 0.76–0.88 at

Be-7 measured at ground air level and rainfall in the city of Sao Paulo

International Nuclear Information System (INIS)

Damatto, Sandra R.; Souza, Joseilton M.; Frujuele, Jonatan V.; Maduar, Marcelo F.; Leonardo, Lucio; Pecequilo, Brigitte R.S.

2013-01-01

The cosmogenic radionuclide 7 Be (T 1/2 = 53.3 d), produced in the upper atmosphere by cosmic ray spallation of oxygen and nitrogen, is one of the cosmogenic radionuclides that can be used as tracer for heavy metals and pollutants in the environment, tracer of soil erosion and sedimentation in lakes, among other examples. Their subsequent deposition to the land surface occurs as both wet and dry fallout, although it has been demonstrated that 7 Be fallout is primarily associated with precipitation. There is limited data on the concentration of 7 Be in rainfall and in particulate in the Southern Hemisphere and in Brazil, compared with data from the Northern Hemisphere. This paper presents the results obtained of 7 Be concentrations measured from April 2011 to June 2013, in samples of air at ground level, each fifteen days, and rainfall in all the rainy events that occurred at Instituto de Pesquisas Energeticas e Nucleares (IPEN), which has its campus located in the city of Sao Paulo, state of Sao Paulo, Brazil. The concentrations of 7 Be were measured by non-destructive gamma-ray spectrometry using an extended range closed-end coaxial Be-layer HPGe detector with 25% relative efficiency and associated electronic devices and live counting time varying from 100,000 s to 300,000 s. The results obtained of 7 Be in particulate and in rainfall were correlated to seasons, precipitation, temperature and sunspot number. The higher values obtained for the concentrations were in spring and summer time presenting good correlations with the amount of precipitation and sunspot number and a clear seasonal variation. (author)

Commercial application of rainfall simulation

Science.gov (United States)

Loch, Rob J.

2010-05-01

to rain; and • Regular calibration of all equipment. In general, typical errors when rainfall simulation is carried out by inexperienced researchers include: • Failure to accurately measure rainfall rates (the most common error); • Inappropriate initial conditions, including wetting treatments; • Use of inappropriately small plots - relating to our concern at the erosion processes considered be those of genuine field relevance; • Inappropriate rainfall kinetic energies; and • Failure to observe critical processes operating on the study plots, such as saturation excess or the presence of impeding layers at shallow depths. Landloch regularly uses erodibility data to design stable batter profiles for minesite waste dumps. Subsequent monitoring of designed dumps has confirmed that modelled erosion rates are consistent with those subsequently measured under field conditions.

Areal rainfall estimation using moving cars - computer experiments including hydrological modeling

Science.gov (United States)

Rabiei, Ehsan; Haberlandt, Uwe; Sester, Monika; Fitzner, Daniel; Wallner, Markus

2016-09-01

The need for high temporal and spatial resolution precipitation data for hydrological analyses has been discussed in several studies. Although rain gauges provide valuable information, a very dense rain gauge network is costly. As a result, several new ideas have emerged to help estimating areal rainfall with higher temporal and spatial resolution. Rabiei et al. (2013) observed that moving cars, called RainCars (RCs), can potentially be a new source of data for measuring rain rate. The optical sensors used in that study are designed for operating the windscreen wipers and showed promising results for rainfall measurement purposes. Their measurement accuracy has been quantified in laboratory experiments. Considering explicitly those errors, the main objective of this study is to investigate the benefit of using RCs for estimating areal rainfall. For that, computer experiments are carried out, where radar rainfall is considered as the reference and the other sources of data, i.e., RCs and rain gauges, are extracted from radar data. Comparing the quality of areal rainfall estimation by RCs with rain gauges and reference data helps to investigate the benefit of the RCs. The value of this additional source of data is not only assessed for areal rainfall estimation performance but also for use in hydrological modeling. Considering measurement errors derived from laboratory experiments, the result shows that the RCs provide useful additional information for areal rainfall estimation as well as for hydrological modeling. Moreover, by testing larger uncertainties for RCs, they observed to be useful up to a certain level for areal rainfall estimation and discharge simulation.

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

A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data

Science.gov (United States)

Velpuri, N.M.; Senay, G.B.; Asante, K.O.

2012-01-01

Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of interand intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellitedriven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE) of 0.80 during the validation period (2004-2009). Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1-2m. The lake level fluctuated in the range up to 4m between the years 1998-2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated satellite-driven water balance

High-frequency DOC and nitrate measurements provide new insights into their export and their relationships to rainfall-runoff processes

Science.gov (United States)

Schwab, Michael; Klaus, Julian; Pfister, Laurent; Weiler, Markus

2015-04-01

Over the past decades, stream sampling protocols for environmental tracers were often limited by logistical and technological constraints. Long-term sampling programs would typically rely on weekly sampling campaigns, while high-frequency sampling would remain restricted to a few days or hours at best. We stipulate that the currently predominant sampling protocols are too coarse to capture and understand the full amplitude of rainfall-runoff processes and its relation to water quality fluctuations. Weekly sampling protocols are not suited to get insights into the hydrological system during high flow conditions. Likewise, high frequency measurements of a few isolated events do not allow grasping inter-event variability in contributions and processes. Our working hypothesis is based on the potential of a new generation of field-deployable instruments for measuring environmental tracers at high temporal frequencies over an extended period. With this new generation of instruments we expect to gain new insights into rainfall-runoff dynamics, both at intra- and inter-event scales. Here, we present the results of one year of DOC and nitrate measurements with the field deployable UV-Vis spectrometer spectro::lyser (scan Messtechnik GmbH). The instrument measures the absorption spectrum from 220 to 720 nm in situ and at high frequencies and derives DOC and nitrate concentrations. The measurements were carried out at 15 minutes intervals in the Weierbach catchment (0.47 km2) in Luxemburg. This fully forested catchment is characterized by cambisol soils and fractured schist as underlying bedrock. The time series of DOC and nitrate give insights into the high frequency dynamics of stream water. Peaks in DOC concentrations are closely linked to discharge peaks that occur during or right after a rainfall event. Those first discharge peaks can be linked to fast near surface runoff processes and are responsible for a remarkable amount of DOC export. A special characterisation of

Exploring the Role of Soil Moisture Conditions for Rainfall Triggered Landslides on Catchment Scale: the case of the Ialomita Sub Carpathians, Romania

Science.gov (United States)

Chitu, Zenaida; Bogaard, Thom; Adler, Mary-Jeanne; Steele-Dunne, Susan; Hrachowitz, Markus; Busuioc, Aristita; Sandric, Ionut; Istrate, Alexandru

2014-05-01

Like in many parts of the world, landslides represent in Romania recurrent phenomena that produce numerous damages to the infrastructure every few years. The high frequency of landslide events over the world has resulted to the development of many early warning systems that are based on the definition of rainfall thresholds triggering landslides. In Romania in particular, recent studies exploring the temporal occurrence of landslides have revealed that rainfall represents the most important triggering factor for landslides. The presence of low permeability soils and gentle slope degrees in the Ialomita Subcarpathians of Romania makes that cumulated precipitation over variable time interval and the hydraulic response of the soil plays a key role in landslides triggering. In order to identify the slope responses to rainfall events in this particular area we investigate the variability of soil moisture and its relationship to landslide events in three Subcarpathians catchments (Cricovul Dulce, Bizididel and Vulcana) by combining in situ measurements, satellite-based radiometry and hydrological modelling. For the current study, hourly soil moisture measurements from six soil moisture monitoring stations that are fitted with volumetric soil moisture sensors, temperature soil sensors and rain gauges sensors are used. Pedotransfer functions will be applied in order to infer hydraulic soil properties from soil texture sampled from 50 soil profiles. The information about spatial and temporal variability of soil moisture content will be completed with the Level 2 soil moisture products from the Soil Moisture and Ocean Salinity (SMOS) mission. A time series analysis of soil moisture is planned to be integrated to landslide and rainfall time series in order to determine a preliminary rainfall threshold triggering landslides in Ialomita Subcarpathians.

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

Science.gov (United States)

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

2017-12-01

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

Influence of atmospheric rainfall to γ radiation Kerma rate in surface air

International Nuclear Information System (INIS)

Xu Zhe; Wan Jun; Yu Rongsheng

2009-01-01

Objective: To investigate the influence rule of the atmospheric Rainfall to the γ radiation Kerma rate in surface air in order to revise the result of its measurement during rainfall. Methods: The influence factors of rainfall to the measurement of the γ radiation Kerma rate in air were analyzed and then the differential equation of the correlation factors was established theoretically, and by resolving the equation, the mathematical model Was obtained. The model was discussed through several practical examples. Results: The mathematical model was coincided with the tendency of curve about the measured data on the influence rule of rainfall to the γ radiation Kerma rate in surface air. Conclusion: By using the theoretical formula in this article which is established to explain the relationship between the rainfall and the γ radiation Kerma rate in surface air, the influence of rainfall to the γ radiation Kerma rate in surface air could be correctly revised. (authors)

NEXRAD Rainfall Data: Eureka, California

Data.gov (United States)

National Aeronautics and Space Administration — Next-Generation Radar (NEXRAD) Weather Surveillance Radar 1988 (WSR-88D) measurements were used to support AMSR-E rainfall validation efforts in Eureka, California,...

Installing the earth station of Ka-band satellite frequency in Malaysia: conceptual framework for site decision

Science.gov (United States)

Mahmud, M. R.; Reba, M. N. M.; Jaw, S. W.; Arsyad, A.; Ibrahim, M. A. M.

2017-05-01

This paper developed a conceptual framework in determining the suitable location in installing the earth station for Ka-band satellite communication in Malaysia. This current evolution of high throughput satellites experienced major challenge due to Malaysian climate. Because Ka-band frequency is highly attenuated by the rainfall; it is an enormous challenge to define the most appropriate site for the static communication. Site diversity, a measure to anticipate this conflict by choosing less attenuated region and geographically change the transmission strategy on season basis require accurate spatio-temporal information on the geographical, environmental and hydro-climatology at local scale. Prior to that request, this study developed a conceptual framework to cater the needs. By using the digital spatial data, acquired from site measurement and remote sensing, the proposed framework applied a multiple criteria analysis to perform the tasks of site selection. With the advancement of high resolution remotely sensed data, site determination can be conducted as in Malaysia; accommodating a new, fast, and effective satellite communication. The output of this study is one of the pioneer contributions to create a high tech-society.

STEP-TRAMM - A modeling interface for simulating localized rainfall induced shallow landslides and debris flow runout pathways

Science.gov (United States)

Or, D.; von Ruette, J.; Lehmann, P.

2017-12-01

Landslides and subsequent debris-flows initiated by rainfall represent a common natural hazard in mountainous regions. We integrated a landslide hydro-mechanical triggering model with a simple model for debris flow runout pathways and developed a graphical user interface (GUI) to represent these natural hazards at catchment scale at any location. The STEP-TRAMM GUI provides process-based estimates of the initiation locations and sizes of landslides patterns based on digital elevation models (SRTM) linked with high resolution global soil maps (SoilGrids 250 m resolution) and satellite based information on rainfall statistics for the selected region. In the preprocessing phase the STEP-TRAMM model estimates soil depth distribution to supplement other soil information for delineating key hydrological and mechanical properties relevant to representing local soil failure. We will illustrate this publicly available GUI and modeling platform to simulate effects of deforestation on landslide hazards in several regions and compare model outcome with satellite based information.

RAINFALL ANALYSIS IN KLANG RIVER BASIN USING CONTINUOUS WAVELET TRANSFORM

Directory of Open Access Journals (Sweden)

Celso A. G. Santos

2016-01-01

Full Text Available The rainfall characteristics within Klang River basin is analyzed by the continuous wavelet transform using monthly rainfall data (1997–2009 from a raingauge and also using daily rainfall data (1998–2013 from the Tropical Rainfall Measuring Mission (TRMM. The wavelet power spectrum showed that some frequency components were presented within the rainfall time series, but the observed time series is short to provide accurate information, thus the daily TRMM rainfall data were used. In such analysis, two main frequency components, i.e., 6 and 12 months, showed to be present during the entire period of 16 years. Such semiannual and annual frequencies were confirmed by the global wavelet power spectra. Finally, the modulation in the 8–16-month and 256– 512-day bands were examined by an average of all scales between 8 and 16 months, and 256 and 512 days, respectively, giving a measure of the average monthly/daily variance versus time, where the periods with low or high variance could be identified.

Object-Based Assessment of Satellite Precipitation Products

Directory of Open Access Journals (Sweden)

Jingjing Li

2016-06-01

Full Text Available An object-based verification approach is employed to assess the performance of the commonly used high-resolution satellite precipitation products: Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, Climate Prediction center MORPHing technique (CMORPH, and Tropical Rainfall Measurement Mission (TRMM Multi-Satellite Precipitation Analysis (TMPA 3B42RT. The evaluation of the satellite precipitation products focuses on the skill of depicting the geometric features of the localized precipitation areas. Seasonal variability of the performances of these products against the ground observations is investigated through the examples of warm and cold seasons. It is found that PERSIANN is capable of depicting the orientation of the localized precipitation areas in both seasons. CMORPH has the ability to capture the sizes of the localized precipitation areas and performs the best in the overall assessment for both seasons. 3B42RT is capable of depicting the location of the precipitation areas for both seasons. In addition, all of the products perform better on capturing the sizes and centroids of precipitation areas in the warm season than in the cold season, while they perform better on depicting the intersection area and orientation in the cold season than in the warm season. These products are more skillful on correctly detecting the localized precipitation areas against the observations in the warm season than in the cold season.

Quantifying rainfall-runoff relationships on the Mieso Hypo Calcic ...

African Journals Online (AJOL)

The mean annual rainfall at Mieso is 738 mm. The soil is a Hypo Calcic Vertisol with a high clay and silt content and is very susceptible to crusting. To achieve the objective of the study, rainfall-runoff measurements were made during 2003 and 2004 on 2 m x 2 m plots provided with a runoff measuring system, and replicated ...

Rainfall Erosivity Database on the European Scale (REDES): A product of a high temporal resolution rainfall data collection in Europe

Science.gov (United States)

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine

2016-04-01

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 R-factor in the (R)USLE model. The R-factor is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minutes rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years) which are not readily available at European scale. The European Commission's Joint Research Centre(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland in order to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,541 rainfall stations in 2014 and has been updated with 134 additional stations in 2015. The interpolation of those point R-factor values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511, 801-815). The intra-annual variability of rainfall erosivity is crucial for modelling soil erosion on a monthly and seasonal basis. The monthly feature of rainfall erosivity has been added in 2015 as an advancement of REDES and the respective mean annual R-factor map. Almost 19,000 monthly R-factor values of REDES contributed to the seasonal and monthly assessments of rainfall erosivity in Europe. According to the first results, more than 50% of the total rainfall erosivity in Europe takes place in the period from June to September. The spatial patterns of rainfall erosivity have significant differences between Northern and Southern Europe as summer is the most erosive period in Central and Northern Europe and autumn in the

A technique to obtain a multiparameter radar rainfall algorithm using the probability matching procedure

International Nuclear Information System (INIS)

Gorgucci, E.; Scarchilli, G.

1997-01-01

The natural cumulative distributions of rainfall observed by a network of rain gauges and a multiparameter radar are matched to derive multiparameter radar algorithms for rainfall estimation. The use of multiparameter radar measurements in a statistical framework to estimate rainfall is resented in this paper, The techniques developed in this paper are applied to the radar and rain gauge measurement of rainfall observed in central Florida and central Italy. Conventional pointwise estimates of rainfall are also compared. The probability matching procedure, when applied to the radar and surface measurements, shows that multiparameter radar algorithms can match the probability distribution function better than the reflectivity-based algorithms. It is also shown that the multiparameter radar algorithm derived matching the cumulative distribution function of rainfall provides more accurate estimates of rainfall on the ground in comparison to any conventional reflectivity-based algorithm

Effect of monthly areal rainfall uncertainty on streamflow simulation

Science.gov (United States)

Ndiritu, J. G.; Mkhize, N.

2017-08-01

Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic

Rainfall estimation with TFR model using Ensemble Kalman filter

Science.gov (United States)

Asyiqotur Rohmah, Nabila; Apriliani, Erna

2018-03-01

Rainfall fluctuation can affect condition of other environment, correlated with economic activity and public health. The increasing of global average temperature is influenced by the increasing of CO2 in the atmosphere, which caused climate change. Meanwhile, the forests as carbon sinks that help keep the carbon cycle and climate change mitigation. Climate change caused by rainfall intensity deviations can affect the economy of a region, and even countries. It encourages research on rainfall associated with an area of forest. In this study, the mathematics model that used is a model which describes the global temperatures, forest cover, and seasonal rainfall called the TFR (temperature, forest cover, and rainfall) model. The model will be discretized first, and then it will be estimated by the method of Ensemble Kalman Filter (EnKF). The result shows that the more ensembles used in estimation, the better the result is. Also, the accurateness of simulation result is influenced by measurement variable. If a variable is measurement data, the result of simulation is better.

Monsoon Rainfall and Landslides in Nepal

Science.gov (United States)

Dahal, R. K.; Hasegawa, S.; Bhandary, N. P.; Yatabe, R.

2009-12-01

A large number of human settlements on the Nepal Himalayas are situated either on old landslide mass or on landslide-prone areas. As a result, a great number of people are affected by large- and small-scale landslides all over the Himalayas especially during monsoon periods. In Nepal, only in the half monsoon period (June 10 to August 15), 70, 50 and 68 people were killed from landslides in 2007, 2008 and 2009, respectively. In this context, this paper highlights monsoon rainfall and their implications in the Nepal Himalaya. In Nepal, monsoon is major source of rainfall in summer and approximately 80% of the annual total rainfall occurs from June to September. The measured values of mean annual precipitation in Nepal range from a low of approximately 250 mm at area north of the Himalaya to many areas exceeding 6,000 mm. The mean annual rainfall varying between 1500 mm and 2500 mm predominate over most of the country. In Nepal, the daily distribution of precipitation during rainy season is also uneven. Sometime 10% of the total annual precipitation can occur in a single day. Similarly, 50% total annual rainfall also can occur within 10 days of monsoon. This type of uneven distribution plays an important role in triggering many landslides in Nepal. When spatial distribution of landslides was evaluated from record of more than 650 landslides, it is found that more landslides events were concentrated at central Nepal in the area of high mean annual rainfall. When monsoon rainfall and landslide relationship was taken into consideration, it was noticed that a considerable number of landslides were triggered in the Himalaya by continuous rainfall of 3 to 90 days. It has been noticed that continuous rainfall of few days (5 days or 7 days or 10 days) are usually responsible for landsliding in the Nepal Himalaya. Monsoon rains usually fall with interruptions of 2-3 days and are generally characterized by low intensity and long duration. Thus, there is a strong role of

Assessment of runoff contributing catchment areas in rainfall runoff modelling

DEFF Research Database (Denmark)

Thorndahl, Søren; Johansen, C.; Schaarup-Jensen, Kjeld

2006-01-01

In numerical modelling of rainfall caused runoff in urban sewer systems an essential parameter is the hydrological reduction factor which defines the percentage of the impervious area contributing to the surface flow towards the sewer. As the hydrological processes during a rainfall are difficult...... to determine with significant precision the hydrological reduction factor is implemented to account all hydrological losses except the initial loss. This paper presents an inconsistency between calculations of the hydrological reduction factor, based on measurements of rainfall and runoff, and till now...... recommended literature values for residential areas. It is proven by comparing rainfall-runoff measurements from four different residential catchments that the literature values of the hydrological reduction factor are over-estimated for this type of catchment. In addition, different catchment descriptions...

Comprehensive Comparisons of Satellite Data, Signals, and Measurements between the BeiDou Navigation Satellite System and the Global Positioning System †

Science.gov (United States)

Jan, Shau-Shiun; Tao, An-Lin

2016-01-01

The Chinese BeiDou navigation satellite system (BDS) aims to provide global positioning service by 2020. The combined use of BDS and Global Positioning System (GPS) is proposed to provide navigation service with more stringent requirements. Actual satellite data, signals and measurements were collected for more than one month to analyze the positioning service qualities from both BDS and GPS. In addition to the conversions of coordinate and timing system, five data quality analysis (DQA) methods, three signal quality analysis (SQA) methods, and four measurement quality analysis (MQA) methods are proposed in this paper to improve the integrated positioning performance of BDS and GPS. As shown in the experiment results, issues related to BDS and GPS are resolved by the above proposed quality analysis methods. Thus, the anomalies in satellite data, signals and measurements can be detected by following the suggested resolutions to enhance the positioning performance of the combined use of BDS and GPS in the Asia Pacific region. PMID:27187403

Meteorology Assessment of Historic Rainfall for Los Alamos During September 2013

Energy Technology Data Exchange (ETDEWEB)

Bruggeman, David Alan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Dewart, Jean Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-02-12

DOE Order 420.1, Facility Safety, requires that site natural phenomena hazards be evaluated every 10 years to support the design of nuclear facilities. The evaluation requires calculating return period rainfall to determine roof loading requirements and flooding potential based on our on-site rainfall measurements. The return period rainfall calculations are done based on statistical techniques and not site-specific meteorology. This and future studies analyze the meteorological factors that produce the significant rainfall events. These studies provide the meteorology context of the return period rainfall events.

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.

Hydrological Utility and Uncertainty of Multi-Satellite Precipitation Products in the Mountainous Region of South Korea

Directory of Open Access Journals (Sweden)

Jong Pil Kim

2016-07-01

Full Text Available Satellite-derived precipitation can be a potential source of forcing data for assessing water availability and managing water supply in mountainous regions of East Asia. This study investigates the hydrological utility of satellite-derived precipitation and uncertainties attributed to error propagation of satellite products in hydrological modeling. To this end, four satellite precipitation products (tropical rainfall measuring mission (TRMM multi-satellite precipitation analysis (TMPA version 6 (TMPAv6 and version 7 (TMPAv7, the global satellite mapping of precipitation (GSMaP, and the climate prediction center (CPC morphing technique (CMORPH were integrated into a physically-based hydrologic model for the mountainous region of South Korea. The satellite precipitation products displayed different levels of accuracy when compared to the intra- and inter-annual variations of ground-gauged precipitation. As compared to the GSMaP and CMORPH products, superior performances were seen when the TMPA products were used within streamflow simulations. Significant dry (negative biases in the GSMaP and CMORPH products led to large underestimates of streamflow during wet-summer seasons. Although the TMPA products displayed a good level of performance for hydrologic modeling, there were some over/underestimates of precipitation by satellites during the winter season that were induced by snow accumulation and snowmelt processes. These differences resulted in streamflow simulation uncertainties during the winter and spring seasons. This study highlights the crucial need to understand hydrological uncertainties from satellite-derived precipitation for improved water resource management and planning in mountainous basins. Furthermore, it is suggested that a reliable snowfall detection algorithm is necessary for the new global precipitation measurement (GPM mission.

Spin motion determination of the Envisat satellite through laser ranging measurements from a single pass measured by a single station

Science.gov (United States)

Pittet, Jean-Noël; Šilha, Jiří; Schildknecht, Thomas

2018-02-01

The Satellite Laser Ranging (SLR) technology is used to accurately determine the position of space objects equipped with so-called retro-reflectors or retro-reflector arrays (RRA). This type of measurement allows to measure the range to the spacecraft with high precision, which leads to determination of very accurate orbits for these targets. Non-active spacecraft, which are not attitude controlled any longer, tend to start to spin or tumble under influence of the external and internal torques and forces. If the return signal is measured for a non-spherical non-active rotating object, the signal in the range residuals with respect to the reference orbit is more complex. For rotating objects the return signal shows an oscillating pattern or patterns caused by the RRA moving around the satellite's centre of mass. This behaviour is projected onto the radial component measured by the SLR. In our work, we demonstrate how the SLR ranging technique from one sensor to a satellite equipped with a RRA can be used to precisely determine its spin motion during one passage. Multiple SLR measurements of one target over time allow to accurately monitor spin motion changes which can be further used for attitude predictions. We show our solutions of the spin motion determined for the non-active ESA satellite Envisat obtained from measurements acquired during years 2013-2015 by the Zimmerwald SLR station, Switzerland. All the necessary parameters are defined for our own so-called point-like model which describes the motion of a point in space around the satellite centre of mass.

How is rainfall interception in urban area affected by meteorological parameters?

Science.gov (United States)

Zabret, Katarina; Rakovec, Jože; Mikoš, Matjaž; Šraj, Mojca

2017-04-01

Rainfall interception is part of the hydrological cycle. Precipitation, which hits vegetation, is retained on the leaves and branches, from which it eventually evaporates into the atmosphere (interception) or reaches the ground by dripping from the canopy, falling through the gaps (throughfall) and running down the stems (stemflow). The amount of rainfall reaching the ground depends on various meteorological and vegetation parameters. Rainfall, throughfall and stemflow have been measured in the city of Ljubljana, Slovenia since the beginning of 2014. Manual and automatic measurements are performed regularly under Betula pendula and Pinus nigra trees in urban area. In 2014, there were detected 178 rainfall events with total amount of 1672.1 mm. In average B. pendula intercepted 44% of rainfall and P. nigra intercepted 72% of rainfall. In 2015 we have detected 117 events with 1047.4 mm of rainfall, of which 37% was intercepted by B. pendula and 60% by P. nigra. The effect of various meteorological parameters on the rainfall interception was analysed in the study. The parameters included in the analysis were rainfall rate, rainfall duration, drop size distribution (average drop velocity and diameter), average wind speed, and average temperature. The results demonstrate decreasing rainfall interception with longer rainfall duration and higher rainfall intensity although the impact of the latter one is not statistically significant. In the case of very fast or very slow rainfall drops, the interception is higher than for the mean rain drop velocity values. In the case of P. nigra the impact of the rain drop diameter on interception is similar to the one of rain drop velocity while for B. pendula increasing of drop diameter also increases the interception. As expected, interception is higher for warmer events. This trend is more evident for P. nigra than for B. pendula. Furthermore, the amount of intercepted rainfall also increases with wind although it could be

Contribution of BeiDou satellite system for long baseline GNSS measurement in Indonesia

Science.gov (United States)

Gumilar, I.; Bramanto, B.; Kuntjoro, W.; Abidin, H. Z.; Trihantoro, N. F.

2018-05-01

The demand for more precise positioning method using GNSS (Global Navigation Satellite System) in Indonesia continue to rise. The accuracy of GNSS positioning depends on the length of baseline and the distribution of observed satellites. BeiDou Navigation Satellite System (BDS) is a positioning system owned by China that operating in Asia-Pacific region, including Indonesia. This research aims to find out the contribution of BDS in increasing the accuracy of long baseline static positioning in Indonesia. The contributions are assessed by comparing the accuracy of measurement using only GPS (Global Positioning System) and measurement using the combination of GPS and BDS. The data used is 5 days of GPS and BDS measurement data for baseline with 120 km in length. The software used is open-source RTKLIB and commercial software Compass Solution. This research will explain in detail the contribution of BDS to the accuracy of position in long baseline static GNSS measurement.

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

Science.gov (United States)

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

2018-06-01

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

Regionalization of monthly rainfall erosivity patternsin Switzerland

Science.gov (United States)

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

2016-10-01

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

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

Measurement of the Lense-Thirring drag on high-altitude, laser-ranged artificial satellites

International Nuclear Information System (INIS)

Ciufolini, I.

1986-01-01

We describe a new method of measuring the Lense-Thirring relativistic nodal drag using LAGEOS together with another high-altitude, laser-ranged, similar satellite with appropriately chosen orbital parameters. We propose, for this purpose, that a future satellite such as LAGEOS II have an inclination supplementary to that of LAGEOS. The experiment proposed here would provide a method for experimental verification of the general relativistic formulation of Mach's principle and measurement of the gravitomagnetic field

Transportable IOT measurement station for direct-broadcast satellites

Science.gov (United States)

Ulbricht, Michael

A transportable 11.7-12.5-GHz flux-density measurement facility for use in the in-orbit testing (IOT) of the FRG TV-Sat direct-broadcast satellites is described. Major components include a 1.2-m-diameter antenna, the fluxmeter, a radiometer to determine atmospheric attenuation, a weather station, and a control and data-processing computer; all of the components are mounted on a 5.10 x 2.35 x 2.70-m trailer. IOT performance parameters include gain/temperature ratio 15.9 dB/K, measurement range -97 to -117 dBW/sq m, measurement accuracy less than 0.5 dB rms, and measurement rate 250-650 msec. Photographs and a block diagram are provided.

[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.

Should seasonal rainfall forecasts be used for flood preparedness?

Directory of Open Access Journals (Sweden)

E. Coughlan de Perez

2017-09-01

Full Text Available In light of strong encouragement for disaster managers to use climate services for flood preparation, we question whether seasonal rainfall forecasts should indeed be used as indicators of the likelihood of flooding. Here, we investigate the primary indicators of flooding at the seasonal timescale across sub-Saharan Africa. Given the sparsity of hydrological observations, we input bias-corrected reanalysis rainfall into the Global Flood Awareness System to identify seasonal indicators of floodiness. Results demonstrate that in some regions of western, central, and eastern Africa with typically wet climates, even a perfect tercile forecast of seasonal total rainfall would provide little to no indication of the seasonal likelihood of flooding. The number of extreme events within a season shows the highest correlations with floodiness consistently across regions. Otherwise, results vary across climate regimes: floodiness in arid regions in southern and eastern Africa shows the strongest correlations with seasonal average soil moisture and seasonal total rainfall. Floodiness in wetter climates of western and central Africa and Madagascar shows the strongest relationship with measures of the intensity of seasonal rainfall. Measures of rainfall patterns, such as the length of dry spells, are least related to seasonal floodiness across the continent. Ultimately, identifying the drivers of seasonal flooding can be used to improve forecast information for flood preparedness and to avoid misleading decision-makers.

Adapting an existing visualization application for browser-based deployment: A case study from the Tropical Rainfall Measuring Mission

Science.gov (United States)

Kelley, Owen A.

2013-02-01

THOR, the Tool for High-resolution Observation Review, is a data viewer for the Tropical Rainfall Measuring Mission (TRMM) and the upcoming Global Precipitation Measurement (GPM) mission. THOR began as a desktop application, but now it can be accessed with a web browser, making THOR one of the first online tools for visualizing TRMM satellite data (http://pps.gsfc.nasa.gov/thor). In this effort, the reuse of the existing visualization code was maximized and the complexity of new code was minimized by avoiding unnecessary functionality, frameworks, or libraries. The simplicity of this approach makes it potentially attractive to researchers wishing to adapt their visualization applications for online deployment. To enable THOR to run within a web browser, three new pieces of code are written. First, the graphical user interface (GUI) of the desktop application is translated into HTML, JavaScript, and CSS. Second, a simple communication mechanism is developed over HTTP. Third, a virtual GUI is created on the server that interfaces with the image-generating routines of the existing desktop application so that these routines do not need to be modified for online use. While the basic functionality of THOR is now available online, prototyping is ongoing for enhanced 3D imaging and other aspects of both THOR Desktop and THOR Online. Because TRMM data products are complex and periodically reprocessed with improved algorithms, having a tool such as THOR is important to analysts at the Precipitation Processing System where the algorithms are tested and the products generated, stored, and distributed. Researchers also have found THOR useful for taking a first look at individual files before writing their own software to perform specialized calculations and analyses.

Pattern Analysis of El Nino and La Nina Phenomenon Based on Sea Surface Temperature (SST) and Rainfall Intensity using Oceanic Nino Index (ONI) in West Java Area

Science.gov (United States)

Prasetyo, Yudo; Nabilah, Farras

2017-12-01

Climate change occurs in 1998-2016 brings significant alteration in the earth surface. It is affects an extremely anomaly temperature such as El Nino and La Nina or mostly known as ENSO (El Nino Southern Oscillation). West Java is one of the regions in Indonesia that encounters the impact of this phenomenon. Climate change due to ENSO also affects food production and other commodities. In this research, processing data method is conducted using programming language to process SST data and rainfall data from 1998 to 2016. The data are sea surface temperature from NOAA satellite, SST Reynolds (Sea Surface Temperature) and daily rainfall temperature from TRMM satellite. Data examination is done using analysis of rainfall spatial pattern and sea surface temperature (SST) where is affected by El Nino and La Nina phenomenon. This research results distribution map of SST and rainfall for each season to find out the impacts of El Nino and La Nina around West Java. El Nino and La Nina in Java Sea are occurring every August to February. During El Nino, sea surface temperature is between 27°C - 28°C with average temperature on 27.71°C. Rainfall intensity is 1.0 mm/day - 2.0 mm/day and the average are 1.63 mm/day. During La Nina, sea surface temperature is between 29°C - 30°C with average temperature on 29.06°C. Rainfall intensity is 9.0 mm/day - 10 mm/day, and the average is 9.74 mm/day. The correlation between rainfall and SST is 0,413 which is expresses a fairly strong correlation between parameters. The conclusion is, during La Nina SST and rainfall increase. While during El Nino SST and rainfall decrease. Hopefully this research could be a guideline to plan disaster mitigation in West Java region that is related extreme climate change.

Inter-satellite calibration of FengYun 3 medium energy electron fluxes with POES electron measurements

Science.gov (United States)

Zhang, Yang; Ni, Binbin; Xiang, Zheng; Zhang, Xianguo; Zhang, Xiaoxin; Gu, Xudong; Fu, Song; Cao, Xing; Zou, Zhengyang

2018-05-01

We perform an L-shell dependent inter-satellite calibration of FengYun 3 medium energy electron measurements with POES measurements based on rough orbital conjunctions within 5 min × 0.1 L × 0.5 MLT. By comparing electron flux data between the U.S. Polar Orbiting Environmental Satellites (POES) and Chinese sun-synchronous satellites including FY-3B and FY-3C for a whole year of 2014, we attempt to remove less reliable data and evaluate systematic uncertainties associated with the FY-3B and FY-3C datasets, expecting to quantify the inter-satellite calibration factors for the 150-350 keV energy channel at L = 2-7. Compared to the POES data, the FY-3B and FY-3C data generally exhibit a similar trend of electron flux variations but more or less underestimate them within a factor of 5 for the medium electron energy 150-350 keV channel. Good consistency in the flux conjunctions after the inter-calibration procedures gives us certain confidence to generalize our method to calibrate electron flux measurements from various satellite instruments.

Darfur: rainfall and conflict

International Nuclear Information System (INIS)

Kevane, Michael; Gray, Leslie

2008-01-01

Data on rainfall patterns only weakly corroborate the claim that climate change explains the Darfur conflict that began in 2003 and has claimed more than 200 000 lives and displaced more than two million persons. Rainfall in Darfur did not decline significantly in the years prior to the eruption of major conflict in 2003; rainfall exhibited a flat trend in the thirty years preceding the conflict (1972-2002). The rainfall evidence suggests instead a break around 1971. Rainfall is basically stationary over the pre- and post-1971 sub-periods. The break is larger for the more northerly rainfall stations, and is less noticeable for En Nahud. Rainfall in Darfur did indeed decline, but the decline happened over 30 years before the conflict erupted. Preliminary analysis suggests little merit to the proposition that a structural break several decades earlier is a reasonable predictor of the outbreak of large-scale civil conflict in Africa

Darfur: rainfall and conflict

Science.gov (United States)

Kevane, Michael; Gray, Leslie

2008-07-01

Data on rainfall patterns only weakly corroborate the claim that climate change explains the Darfur conflict that began in 2003 and has claimed more than 200 000 lives and displaced more than two million persons. Rainfall in Darfur did not decline significantly in the years prior to the eruption of major conflict in 2003; rainfall exhibited a flat trend in the thirty years preceding the conflict (1972 2002). The rainfall evidence suggests instead a break around 1971. Rainfall is basically stationary over the pre- and post-1971 sub-periods. The break is larger for the more northerly rainfall stations, and is less noticeable for En Nahud. Rainfall in Darfur did indeed decline, but the decline happened over 30 years before the conflict erupted. Preliminary analysis suggests little merit to the proposition that a structural break several decades earlier is a reasonable predictor of the outbreak of large-scale civil conflict in Africa.

Historical analysis of interannual rainfall variability and trends in southeastern Brazil based on observational and remotely sensed data

Science.gov (United States)

Vásquez P., Isela L.; de Araujo, Lígia Maria Nascimento; Molion, Luiz Carlos Baldicero; de Araujo Abdalad, Mariana; Moreira, Daniel Medeiros; Sanchez, Arturo; Barbosa, Humberto Alves; Rotunno Filho, Otto Corrêa

2018-02-01

The Brazilian Southeast is considered a humid region. It is also prone to landslides and floods, a result of significant increases in rainfall during spring and summer caused by the South Atlantic Convergence Zone (SACZ). Recently, however, the region has faced a striking rainfall shortage, raising serious concerns regarding water availability. The present work endeavored to explain the meteorological drought that has led to hydrological imbalance and water scarcity in the region. Hodrick-Prescott smoothing and wavelet transform techniques were applied to long-term hydrologic and sea surface temperature (SST)—based climate indices monthly time series data in an attempt to detect cycles and trends that could help explain rainfall patterns and define a framework for improving the predictability of extreme events in the region. Historical observational hydrologic datasets available include monthly precipitation amounts gauged since 1888 and 1940 and stream flow measured since the 1930s. The spatial representativeness of rain gauges was tested against gridded rainfall satellite estimates from 2000 to 2015. The analyses revealed variability in four time scale domains—infra-annual, interannual, quasi-decadal and inter-decadal or multi-decadal. The strongest oscillations periods revealed were: for precipitation—8 months, 2, 8 and 32 years; for Pacific SST in the Niño-3.4 region—6 months, 2, 8 and 35.6 years, for North Atlantic SST variability—6 months, 2, 8 and 32 years and for Pacific Decadal Oscillation (PDO) index—6.19 months, 2.04, 8.35 and 27.31 years. Other periodicities less prominent but still statistically significant were also highlighted.

Using satellite data on meteorological and vegetation characteristics and soil surface humidity in the Land Surface Model for the vast territory of agricultural destination

Science.gov (United States)

Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Vasilenko, Eugene; Volkova, Elena; Kukharsky, Alexander

2017-04-01

vegetation cover (taken for vegetation temperature) Ta and efficient radiation temperature Ts.eff, as well as land surface emissivity E, normalized difference vegetation index NDVI, vegetation cover fraction B, and leaf area index LAI. The SEVIRI-based retrievals have included precipitation, LST Tls and Ta, E at daylight and nighttime, LAI (daily), and B. From the MSU-MR data there have been retrieved values of all the same characteristics as from the AVHRR data. The MSU-MR-based daily and monthly sums of precipitation have been calculated using the developed earlier and modified Multi Threshold Method (MTM) intended for the cloud detection and identification of its types around the clock as well as allocation of precipitation zones and determination of instantaneous maximum rainfall intensities for each pixel at that the transition from assessing rainfall intensity to estimating their daily values is a key element of the MTM. Measurement data from 3 IR MSU-MR channels (3.8, 11 i 12 μm) as well as their differences have been used in the MTM as predictors. Controlling the correctness of the MSU-MR-derived rainfall estimates has been carried out when comparing with analogous AVHRR- and SEVIRI-based retrievals and with precipitation amounts measured at the agricultural meteorological station of the study region. Probability of rainfall zones determination from the MSU-MR data, to match against the actual ones, has been 75-85% as well as for the AVHRR and SEVIRI data. The time behaviors of satellite-derived and ground-measured daily and monthly precipitation sums for vegetation season and yeaŗ correspondingly, have been in good agreement with each other although the first ones have been smoother than the latter. Discrepancies have existed for a number of local maxima for which satellite-derived precipitation estimates have been less than ground-measured values. It may be due to the different spatial scales of areal satellite-derived and point ground-based estimates. Some

Damaging Rainfall and Flooding. The Other Sahel Hazards

Energy Technology Data Exchange (ETDEWEB)

Tarhule, A. [Department of Geography, University of Oklahoma, 100 East Boyd Street, Norman, OK, 73079 (United States)

2005-10-01

Damaging rainfall and rain-induced flooding occur from time to time in the drought-prone Sahel savannah zone of Niger in West Africa but official records of these events and their socioeconomic impacts do not exist. This paper utilized newspaper accounts between 1970 and 2000 to survey and illustrate the range of these flood hazards in the Sahel. During the study interval, 53 newspaper articles reported 79 damaging rainfall and flood events in 47 different communities in the Sahel of Niger. Collectively, these events destroyed 5,580 houses and rendered 27,289 people homeless. Cash losses and damage to infrastructure in only three events exceeded $4 million. Sahel residents attribute these floods to five major causes including both natural and anthropogenic, but they view the flood problem as driven primarily by land use patterns. Despite such awareness, traditional coping strategies appear inadequate for dealing with the problems in part because of significant climatic variability. Analysis of several rainfall measures indicates that the cumulative rainfall in the days prior to a heavy rain event is an important factor influencing whether or not heavy rainfall results in flooding. Thus, despite some limitations, newspaper accounts of historical flooding are largely consistent with measured climatic variables. The study demonstrates that concerted effort is needed to improve the status of knowledge concerning flood impacts and indeed other natural and human hazards in the Sahel.

Cloud and Thermodynamic Parameters Retrieved from Satellite Ultraspectral Infrared Measurements

Science.gov (United States)

Zhou, Daniel K.; Smith, William L.; Larar, Allen M.; Liu, Xu; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Stephen A.

2008-01-01

Atmospheric-thermodynamic parameters and surface properties are basic meteorological parameters for weather forecasting. A physical geophysical parameter retrieval scheme dealing with cloudy and cloud-free radiance observed with satellite ultraspectral infrared sounders has been developed and applied to the Infrared Atmospheric Sounding Interferometer (IASI) and the Atmospheric InfraRed Sounder (AIRS). The retrieved parameters presented herein are from radiance data gathered during the Joint Airborne IASI Validation Experiment (JAIVEx). JAIVEx provided intensive aircraft observations obtained from airborne Fourier Transform Spectrometer (FTS) systems, in-situ measurements, and dedicated dropsonde and radiosonde measurements for the validation of the IASI products. Here, IASI atmospheric profile retrievals are compared with those obtained from dedicated dropsondes, radiosondes, and the airborne FTS system. The IASI examples presented here demonstrate the ability to retrieve fine-scale horizontal features with high vertical resolution from satellite ultraspectral sounder radiance spectra.

Rainfall simulators in hydrological and geomorphological sciences: benefits, applications and future research directions

Science.gov (United States)

Iserloh, Thomas; Cerdà, Artemi; Fister, Wolfgang; Seitz, Steffen; Keesstra, Saskia; Green, Daniel; Gabriels, Donald

2017-04-01

Rainfall simulators are used extensively within the hydrological and geomorphological sciences and provide a useful investigative tool to understand many processes, such as: (i) plot-scale runoff, infiltration and erosion; (ii) irrigation and crop management, and; (iii) investigations into flooding within a laboratory setting. Although natural rainfall is desirable as it represents actual conditions in a given geographic location, data acquisition relying on natural rainfall is often hindered by its unpredictable nature. Furthermore, rainfall characteristics such as the intensity, duration, drop size distribution and kinetic energy cannot be spatially or temporally regulated or repeated between experimentation. Rainfall simulators provide a suitable method to overcome the issues associated with depending on potentially erratic and unpredictable natural rainfall as they allow: (i) multiple measurements to be taken quickly without waiting for suitable natural rainfall conditions; (ii) the simulation of spatially and/or temporally controlled rainfall patterns over a given plot area, and; (iii) the creation of a closed environment, allowing simplified measurement of input and output conditions. There is no standardisation of rainfall simulation and as such, rainfall simulators differ in their design, rainfall characteristics and research application. Although this impedes drawing meaningful comparisons between studies, this allows researchers to create a bespoke and tailored rainfall simulator for the specific research application. This paper summarises the rainfall simulators used in European research institutions (Universities of Trier, Valencia, Basel, Tuebingen, Wageningen, Loughborough and Ghent) to investigate a number of hydrological and geomorphological issues and includes details on the design specifications (such as the extent and characteristics of simulated rainfall), as well as a discussion of the purpose and application of the rainfall simulator.

History of satellite missions and measurements of the Earth Radiation Budget (1957-1984)

Science.gov (United States)

House, F. B.; Gruber, A.; Hunt, G. E.; Mecherikunnel, A. T.

1986-01-01

The history of satellite missions and their measurements of the earth radiation budget from the beginning of the space age until the present time are reviewed. The survey emphasizes the early struggle to develop instrument systems to monitor reflected shortwave and emitted long-wave exitances from the earth, and the problems associated with the interpretation of these observations from space. In some instances, valuable data sets were developed from satellite measurements whose instruments were not specifically designed for earth radiation budget observations.

Apply data mining to analyze the rainfall of landslide

Directory of Open Access Journals (Sweden)

Lee Chou-Yuan

2018-01-01

Full Text Available Taiwan is listed as extremely dangerous country which suffers from many disasters. The disasters from the landslide result in the loss of agricultural productions, life and property and so on. Many researchers concern about the disasters of landslide, but there are few discussions for the threshold of rainfall for landslide. In this paper, data mining is applied to establish rules and the threshold of rainfall for landslide in Huafan University, Taiwan. These used variables include rainfall, insolation, insolation rate, averaged humidity, averaged temperature, wind speed, and the tilt of inclinometer. The inclinometer is an important instrument for measuring tilt, elevation or depression of an object with respect to gravity. There are 26 inclinometers in Talun mountain area of Huafan University. In this research, the used data were collected from January 2008 to July 2014. In the proposed approach, the regression analysis is used to predict rainfall first. Then, decision tree is used to obtain decision rules and set the threshold of rainfall for landslide. The output of this approach can provide more information for understanding the change of rainfall. The threshold of rainfall could also provide useful information to maintain the security for Huafan University.

Thermal Conductivity Measurements on Icy Satellite Analogs

Science.gov (United States)

Javeed, Aurya; Barmatz, Martin; Zhong, Fang; Choukroun, Mathieu

2012-01-01

With regard to planetary science, NASA aspires to: "Advance scientific knowledge of the origin and history of the solar system, the potential for life elsewhere, and the hazards and resources present as humans explore space". In pursuit of such an end, the Galileo and Cassini missions garnered spectral data of icy satellite surfaces implicative of the satellites' structure and material composition. The potential for geophysical modeling afforded by this information, coupled with the plausibility of life on icy satellites, has pushed Jupiter's Europa along with Saturn's Enceladus and Titan toward the fore of NASA's planetary focus. Understanding the evolution of, and the present processes at work on, the aforementioned satellites falls squarely in-line with NASA's cited goal.

Satellite data sets for the atmospheric radiation measurement (ARM) program

Energy Technology Data Exchange (ETDEWEB)

Shi, L.; Bernstein, R.L. [SeaSpace Corp., San Diego, CA (United States)

1996-04-01

This abstract describes the type of data obtained from satellite measurements in the Atmospheric Radiation Measurement (ARM) program. The data sets have been widely used by the ARM team to derive cloud-top altitude, cloud cover, snow and ice cover, surface temperature, water vapor, and wind, vertical profiles of temperature, and continuoous observations of weather needed to track and predict severe weather.

Access NASA Satellite Global Precipitation Data Visualization on YouTube

Science.gov (United States)

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

2017-12-01

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

Rainfall distribution and change detection across climatic zones in Nigeria

OpenAIRE

Stephen Bunmi Ogungbenro; Tobi Eniolu Morakinyo

2014-01-01

Nigerian agriculture is mainly rain-fed and basically dependent on the vagaries of weather especially rainfall. Nigeria today has about forty-four (44) weather observation stations which provide measurement of rainfall amount for different locations across the country. Hence, this study investigates change detection in rainfall pattern over each climatic zone of Nigeria. Data were collected for 90 years (1910–1999) period for all the weather observation stations in Nigeria, while a subdivisio...

Automated reconstruction of rainfall events responsible for shallow landslides

Science.gov (United States)

Vessia, G.; Parise, M.; Brunetti, M. T.; Peruccacci, S.; Rossi, M.; Vennari, C.; Guzzetti, F.

2014-04-01

Over the last 40 years, many contributions have been devoted to identifying the empirical rainfall thresholds (e.g. intensity vs. duration ID, cumulated rainfall vs. duration ED, cumulated rainfall vs. intensity EI) for the initiation of shallow landslides, based on local as well as worldwide inventories. Although different methods to trace the threshold curves have been proposed and discussed in literature, a systematic study to develop an automated procedure to select the rainfall event responsible for the landslide occurrence has rarely been addressed. Nonetheless, objective criteria for estimating the rainfall responsible for the landslide occurrence (effective rainfall) play a prominent role on the threshold values. In this paper, two criteria for the identification of the effective rainfall events are presented: (1) the first is based on the analysis of the time series of rainfall mean intensity values over one month preceding the landslide occurrence, and (2) the second on the analysis of the trend in the time function of the cumulated mean intensity series calculated from the rainfall records measured through rain gauges. The two criteria have been implemented in an automated procedure written in R language. A sample of 100 shallow landslides collected in Italy by the CNR-IRPI research group from 2002 to 2012 has been used to calibrate the proposed procedure. The cumulated rainfall E and duration D of rainfall events that triggered the documented landslides are calculated through the new procedure and are fitted with power law in the (D,E) diagram. The results are discussed by comparing the (D,E) pairs calculated by the automated procedure and the ones by the expert method.

Evaluation of Satellite-Based Precipitation Products from IMERG V04A and V03D, CMORPH and TMPA with Gauged Rainfall in Three Climatologic Zones in China

Directory of Open Access Journals (Sweden)

Guanghua Wei

2017-12-01

Full Text Available A critical evaluation of the newly released precipitation data set is very important for both the end users and data developers. Meanwhile, the evaluation may provide a benchmark for the product’s continued development and future improvement. To these ends, the four precipitation estimates including IMERG (the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement V04A, IMERG V03D, CMORPH (the Climate Prediction Center Morphing technique-CRT and TRMM (the Tropical Rainfall Measuring Mission 3B42 are systematically evaluated against the gauge precipitation estimates at multiple spatiotemporal scales from 1 June 2014 to 30 November 2015 over three different topographic and climatic watersheds in China. Meanwhile, the statistical methods are utilized to quantize the performance of the four satellite-based precipitation estimates. The results show that: (1 over the Tibetan Plateau cold region, among all products, IMERG V04A underestimates precipitation with the largest RB (−46.98% during the study period and the similar results are seen at the seasonal scale. However, IMERG V03D demonstrates the best performance according to RB (7.46%, RMSE (0.44 mm/day and RRMSE (28.37%. Except for in summer, TRMM 3B42 perform better than CMORPH according to RMSEs, RRMSEs and Rs; (2 within the semi-humid Huaihe River Basin, IMERG V04A has a slight advantage over the other three satellite-based precipitation products with the lowest RMSE (0.32 mm/day during the evaluation period and followed by IMERG V03D, TRMM 3B42 and CMORPH orderly; (3 over the arid/semi-arid Weihe River Basin, in comparison with the other three products, TRMM 3B42 demonstrates the best performance with the lowest RMSE (0.1 mm/day, RRMSE (8.44% and highest R (0.92 during the study period. Meanwhile, IMERG V03D perform better than IMERG V04A according all the statistical indicators; (4 in winter, IMERG V04A and IMERG V03D tend to underestimate the total precipitation

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

Determination of atmospheric aerosol properties over land using satellite measurements

NARCIS (Netherlands)

Kokhanovsky, A.A.; Leeuw, G. de

2009-01-01

Mostly, aerosol properties are poorly understood because the aerosol properties are very sparse. The first workshop on the determination of atmospheric aerosol properties over land using satellite measurements is convened in Bremen, Germany. In this workshop, the topics of discussions included a

Ground-based observations coordinated with Viking satellite measurements

International Nuclear Information System (INIS)

Opgenoorth, H.J.; Kirkwood, S.

1989-01-01

The instrumentation and the orbit of the Viking satellite made this first Swedish satellite mission ideally suited for coordinated observations with the dense network of ground-based stations in northern Scandinavia. Several arrays of complementing instruments such as magnetometers, all-sky cameras, riometers and doppler radars monitored on a routine basis the ionosphere under the magnetospheric region passed by Viking. For a large number of orbits the Viking passages close to Scandinavia were covered by the operation of specially designed programmes at the European incoherent-scatter facility (EISCAT). First results of coordinated observations on the ground and aboard Viking have shed new light on the most spectacular feature of substorm expansion, the westward-travelling surge. The end of a substorm and the associated decay of a westward-travelling surge have been analysed. EISCAT measurements of high spatial and temporal resolution indicate that the conductivities and electric fields associated with westward-travelling surges are not represented correctly by the existing models. (author)

Contribution of tropical cyclones to global rainfall

Science.gov (United States)

Khouakhi, Abdou; Villarini, Gabriele; Vecchi, Gabriel; Smith, James

2016-04-01

Rainfall associated with tropical cyclones (TCs) can have both devastating and beneficial impacts in different parts of the world. In this work, daily precipitation and historical six-hour best track TC datasets are used to quantify the contribution of TCs to global rainfall. We select 18607 rain gauge stations with at least 25 complete (at least 330 measurements per year) years between 1970 and 2014. We consider rainfall associated with TCs if the center of circulation of the storm passed within a given distance from the rain gauge and within a given time window. Spatial and temporal sensitivity analyses are performed with varying time windows (same day, ±1 day) and buffer radii (400 km and 500 km) around each rain gauge. Results highlight regional differences in TC-induced rainfall. The highest TC-induced precipitation totals (400 to 600+ mm/year) are prevalent along eastern Asia, western and northeastern Australia, and in the western Pacific islands. Stations along the southeast of the U.S. coast and surrounding the Gulf of Mexico receive up to 200 mm/year of TC rainfall. The highest annual fractional contributions of TCs to total rainfall (from 35 to 50%) are recorded in stations located in northwestern Australia, southeastern China, the northern Philippines and the southern Mexico peninsula. Seasonally, the highest proportions (40 to 50%) are recorded along eastern Australia and Mauritius in winter, and in eastern Asia and Mexico in summer and autumn. Analyses of the relative contribution of TCs to extreme rainfall using annual maximum (AM) and peaks-over-threshold (POT) approaches indicate notable differences among regions. The highest TC-AM rainfall proportions (45 to 60%) are found in stations located in Japan, eastern China, the Philippines, eastern and western Australia. Substantial contributions (25 to 40% of extreme rainfall) are also recorded in stations located along the U.S. East Coast, the Gulf of Mexico, and the Mexico peninsula. We find similar

Rainfall erosivity factor estimation in Republic of Moldova

Science.gov (United States)

Castraveš, Tudor; Kuhn, Nikolaus

2017-04-01

Rainfall erosivity represents a measure of the erosive force of rainfall. Typically, it is expressed as variable such as the R factor in the Universal Soil Loss Equation (USLE) (Wischmeier and Smith, 1965, 1978) or its derivates. The rainfall erosivity index for a rainfall event (EI30) is calculated from the total kinetic energy and maximum 30 minutes intensity of individual events. However, these data are often unavailable for wide regions and countries. Usually, there are three issues regarding precipitation data: low temporal resolution, low spatial density and limited access to the data. This is especially true for some of postsoviet countries from Eastern Europe, such as Republic of Moldova, where soil erosion is a real and persistent problem (Summer, 2003) and where soils represents the main natural resource of the country. Consequently, researching and managing soil erosion is particularly important. The purpose of this study is to develop a model based on commonly available rainfall data, such as event, daily or monthly amounts, to calculate rainfall erosivity for the territory of Republic of Moldova. Rainfall data collected during 1994-2015 period at 15 meteorological stations in the Republic of Moldova, with 10 minutes temporal resolution, were used to develop and calibrate a model to generate an erosivity map of Moldova. References 1. Summer, W., (2003). Soil erosion in the Republic of Moldova — the importance of institutional arrangements. Erosion Prediction in Ungauged Basins: Integrating Methods and Techniques (Proceedings of symposium HS01 held during IUGG2003 at Sapporo. July 2003). IAHS Publ. no. 279. 2. Wischmeier, W.H., and Smith, D.D. (1965). Predicting rainfall-erosion losses from cropland east of the Rocky Mountains. Agr. Handbook No. 282, U.S. Dept. Agr., Washington, DC 3. Wischmeier, W.H., and Smith, D.D. (1978). Predicting rainfall erosion losses. Agr. handbook No. 537, U.S. Dept. of Agr., Science and Education Administration.

Assessment of Rainfall-induced Landslide Potential and Spatial Distribution

Science.gov (United States)

Chen, Yie-Ruey; Tsai, Kuang-Jung; Chen, Jing-Wen; Chiang, Jie-Lun; Hsieh, Shun-Chieh; Chue, Yung-Sheng

2016-04-01

Recently, due to the global climate change, most of the time the rainfall in Taiwan is of short duration but with high intensity. Due to Taiwan's steep terrain, rainfall-induced landslides often occur and lead to human causalities and properties loss. Taiwan's government has invested huge reconstruction funds to the affected areas. However, after rehabilitation they still face the risk of secondary sediment disasters. Therefore, this study assesses rainfall-induced (secondary) landslide potential and spatial distribution in watershed of Southern Taiwan under extreme climate change. The study areas in this research are Baolai and Jianshan villages in the watershed of the Laonongxi River Basin in the Southern Taiwan. This study focused on the 3 years after Typhoon Morakot (2009 to 2011). During this period, the study area experienced six heavy rainfall events including five typhoons and one heavy rainfall. The genetic adaptive neural network, texture analysis and GIS were implemented in the analysis techniques for the interpretation of satellite images and to obtain surface information and hazard log data and to analyze land use change. A multivariate hazards evaluation method was applied to quantitatively analyze the weights of various natural environmental and slope development hazard factors. Furthermore, this study established a slope landslide potential assessment model and depicted a slope landslide potential diagram by using the GIS platform. The interaction between (secondary) landslide mechanism, scale, and location was analyzed using association analysis of landslide historical data and regional environmental characteristics. The results of image classification before and after six heavy rainfall events show that the values of coefficient of agreement are at medium-high level. By multivariate hazards evaluation method, geology and the effective accumulative rainfall (EAR) are the most important factors. Slope, distance from fault, aspect, land disturbance

Chemical and biological relationships relevant to the effect of acid rainfall on the soil-plant system

Science.gov (United States)

Marvin Nyborg

1976-01-01

This paper deals with problems of measuring acidity in rainfall and the interpretation of these measurements in terms of effects on the soil-plant system. Theoretical relationships of the carbon-dioxide-bicarbonate equalibria and its effect on rainfall acidity measurements are given. The relationship of a cation-anion balance model of acidity in rainfall to plant...

On the coordination of EISCAT measurements with rocket and satellite observations

International Nuclear Information System (INIS)

Hultqvist, B.

1977-01-01

The scientific interest of combining EISCAT measurements of the thermal ionospheric plasma with sounding rocket and/or satellite measurements of the hot plasma distribution function and other variables is discussed briefly. Some examples are presented where such coordinated measurements are of great interest. The importance of being able to launch rockets through, or at least quite close to, the radar beam is emphasized. (Auth.)

Total Discharge Estimation in the Korean Peninsula Using Multi-Satellite Products

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Jae Young Seo

2017-07-01

Full Text Available Estimation of total discharge is necessary to understand the hydrological cycle and to manage water resources efficiently. However, the task is problematic in an area where ground observations are limited. The North Korea region is one example. Here, the total discharge was estimated based on the water balance using multiple satellite products. They are the terrestrial water storage changes (TWSC derived from the Gravity Recovery and Climate Experiment (GRACE, precipitation from the Tropical Rainfall Measuring Mission (TRMM, and evapotranspiration from the Moderate Resolution Imaging Spectroradiometer (MODIS. The satellite-based discharge was compared with land surface model products of the Global Land Data Assimilation System (GLDAS, and a positive relationship between the results was obtained (r = 0.70–0.86; bias = −9.08–16.99 mm/month; RMSE = 36.90–62.56 mm/month; NSE = 0.01–0.62. Among the four land surface models of GLDAS (CLM, Mosaic, Noah, and VIC, CLM corresponded best with the satellite-based discharge, satellite-based discharge has a tendency to slightly overestimate compared to model-based discharge (CLM, Mosaic, Noah, and VIC in the dry season. Also, the total discharge data based on the Precipitation-Runoff Modeling System (PRMS and the in situ discharge for major five river basins in South Korea show comparable seasonality and high correlation with the satellite-based discharge. In spite of the relatively low spatial resolution of GRACE, and loss of information incurred during the process of integrating three different satellite products, the proposed methodology can be a practical tool to estimate the total discharge with reasonable accuracy, especially in a region with scarce hydrologic data.

Rainfall interception and the coupled surface water and energy balance

NARCIS (Netherlands)

Van Dijk, A.I.J.M.; et al., et al.; Moors, E.J.

2015-01-01

Evaporation from wet canopies (. E) can return up to half of incident rainfall back into the atmosphere and is a major cause of the difference in water use between forests and short vegetation. Canopy water budget measurements often suggest values of E during rainfall that are several times greater

Petascale Diagnostic Assessment of the Global Portfolio Rainfall Space Missions' Ability to Support Flood Forecasting

Science.gov (United States)

Reed, P. M.; Chaney, N.; Herman, J. D.; Wood, E. F.; Ferringer, M. P.

2015-12-01

This research represents a multi-institutional collaboration between Cornell University, The Aerospace Corporation, and Princeton University that has completed a Petascale diagnostic assessment of the current 10 satellite missions providing rainfall observations. Our diagnostic assessment has required four core tasks: (1) formally linking high-resolution astrodynamics design and coordination of space assets with their global hydrological impacts within a Petascale "many-objective" global optimization framework, (2) developing a baseline diagnostic evaluation of a 1-degree resolution global implementation of the Variable Infiltration Capacity (VIC) model to establish the required satellite observation frequencies and coverage to maintain acceptable global flood forecasts, (3) evaluating the limitations and vulnerabilities of the full suite of current satellite precipitation missions including the recently approved Global Precipitation Measurement (GPM) mission, and (4) conceptualizing the next generation spaced-based platforms for water cycle observation. Our team exploited over 100 Million hours of computing access on the 700,000+ core Blue Waters machine to radically advance our ability to discover and visualize key system tradeoffs and sensitivities. This project represents to our knowledge the first attempt to develop a 10,000 member Monte Carlo global hydrologic simulation at one degree resolution that characterizes the uncertain effects of changing the available frequencies of satellite precipitation on drought and flood forecasts. The simulation—optimization components of the work have set a theoretical baseline for the best possible frequencies and coverages for global precipitation given unlimited investment, broad international coordination in reconfiguring existing assets, and new satellite constellation design objectives informed directly by key global hydrologic forecasting requirements. Our research poses a step towards realizing the integrated

Establishing best practices for the validation of atmospheric composition measurements from satellites

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Lambert, Jean-Christopher

As a contribution to the implementation of the Global Earth Observation System of Systems (GEOSS), the Committee on Earth Observation Satellites (CEOS) is developing a data quality strategy for satellite measurements. To achieve GEOSS requirements of consistency and interoperability (e.g. for comparison and for integrated interpretation) of the measurements and their derived data products, proper uncertainty assessment is essential and needs to be continuously monitored and traceable to standards. Therefore, CEOS has undertaken the task to establish a set of best practices and guidelines for satellite validation, starting with current practices that could be improved with time. Best practices are not intended to be imposed as firm requirements, but rather to be suggested as a baseline for comparing against, which could be used by the widest community and provide guidance to newcomers. The present paper reviews the current development of best practices and guidelines for the validation of atmospheric composition satellites. Terminologies and general principles of validation are reminded. Going beyond elementary definitions of validation like the assessment of uncertainties, the specific GEOSS context calls also for validation of individual service components and against user requirements. This paper insists on two important aspects. First one, the question of the "collocation". Validation generally involves comparisons with "reference" measurements of the same quantities, and the question of what constitutes a valid comparison is not the least of the challenges faced. We present a tentative scheme for defining the validity of a comparison and of the necessary "collocation" criteria. Second focus of this paper: the information content of the data product. Validation against user requirements, or the verification of the "fitness for purpose" of both the data products and their validation, needs to identify what information, in the final product, is contributed really

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

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

2017-12-01

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

River catchment rainfall series analysis using additive Holt-Winters method

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Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui

2016-03-01

Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.

Integrating Global Satellite-Derived Data Products as a Pre-Analysis for Hydrological Modelling Studies: A Case Study for the Red River Basin

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Gijs Simons

2016-03-01

Full Text Available With changes in weather patterns and intensifying anthropogenic water use, there is an increasing need for spatio-temporal information on water fluxes and stocks in river basins. The assortment of satellite-derived open-access information sources on rainfall (P and land use/land cover (LULC is currently being expanded with the application of actual evapotranspiration (ETact algorithms on the global scale. We demonstrate how global remotely sensed P and ETact datasets can be merged to examine hydrological processes such as storage changes and streamflow prior to applying a numerical simulation model. The study area is the Red River Basin in China in Vietnam, a generally challenging basin for remotely sensed information due to frequent cloud cover. Over this region, several satellite-based P and ETact products are compared, and performance is evaluated using rain gauge records and longer-term averaged streamflow. A method is presented for fusing multiple satellite-derived ETact estimates to generate an ensemble product that may be less susceptible, on a global basis, to errors in individual modeling approaches. Subsequently, monthly satellite-derived rainfall and ETact are combined to assess the water balance for individual subcatchments and types of land use, defined using a global land use classification improved based on auxiliary satellite data. It was found that a combination of TRMM rainfall and the ensemble ETact product is consistent with streamflow records in both space and time. It is concluded that monthly storage changes, multi-annual streamflow and water yield per LULC type in the Red River Basin can be successfully assessed based on currently available global satellite-derived products.

The along track scanning radiometer - an analysis of coincident ship and satellite measurements

Science.gov (United States)

Barton, I. J.; Prata, A. J.; Llewellyn-Jones, D. T.

1993-05-01

Following the successful launch of the ERS-1 satellite in July 1991 we have undertaken several geophysical validation cruises in the Coral Sea. The prime aim of these cruises was to compare the sea surface temperature (SST) derived from the Along Track Scanning Radiometer (ATSR) with that measured using precision radiometers mounted on the ships. On most occasions when simultaneous satellite and ship measurements were taken we also launched a radiosonde from one of the research vessels. The results suggest that the ATSR is able to measure the ``skin'' temperature of the sea surface with an accuracy suitable for climate research applications. A case study comparison between the AVHRR and ATSR SST products will also be presented.

The spatial return level of aggregated hourly extreme rainfall in Peninsular Malaysia

Science.gov (United States)

Shaffie, Mardhiyyah; Eli, Annazirin; Wan Zin, Wan Zawiah; Jemain, Abdul Aziz

2015-07-01

This paper is intended to ascertain the spatial pattern of extreme rainfall distribution in Peninsular Malaysia at several short time intervals, i.e., on hourly basis. Motivation of this research is due to historical records of extreme rainfall in Peninsular Malaysia, whereby many hydrological disasters at this region occur within a short time period. The hourly periods considered are 1, 2, 3, 6, 12, and 24 h. Many previous hydrological studies dealt with daily rainfall data; thus, this study enables comparison to be made on the estimated performances between daily and hourly rainfall data analyses so as to identify the impact of extreme rainfall at a shorter time scale. Return levels based on the time aggregate considered are also computed. Parameter estimation using L-moment method for four probability distributions, namely, the generalized extreme value (GEV), generalized logistic (GLO), generalized Pareto (GPA), and Pearson type III (PE3) distributions were conducted. Aided with the L-moment diagram test and mean square error (MSE) test, GLO was found to be the most appropriate distribution to represent the extreme rainfall data. At most time intervals (10, 50, and 100 years), the spatial patterns revealed that the rainfall distribution across the peninsula differ for 1- and 24-h extreme rainfalls. The outcomes of this study would provide additional information regarding patterns of extreme rainfall in Malaysia which may not be detected when considering only a higher time scale such as daily; thus, appropriate measures for shorter time scales of extreme rainfall can be planned. The implementation of such measures would be beneficial to the authorities to reduce the impact of any disastrous natural event.

Evaluation of TRMM satellite-based precipitation indexes for flood forecasting over Riyadh City, Saudi Arabia

Science.gov (United States)

Tekeli, Ahmet Emre; Fouli, Hesham

2016-10-01

Floods are among the most common disasters harming humanity. In particular, flash floods cause hazards to life, property and any type of structures. Arid and semi-arid regions are equally prone to flash floods like regions with abundant rainfall. Despite rareness of intensive and frequent rainfall events over Kingdom of Saudi Arabia (KSA); an arid/semi-arid region, occasional flash floods occur and result in large amounts of damaging surface runoff. The flooding of 16 November, 2013 in Riyadh; the capital city of KSA, resulted in killing some people and led to much property damage. The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) Real Time (RT) data (3B42RT) are used herein for flash flood forecasting. 3B42RT detected high-intensity rainfall events matching with the distribution of observed floods over KSA. A flood early warning system based on exceedance of threshold limits on 3B42RT data is proposed for Riyadh. Three different indexes: Constant Threshold (CT), Cumulative Distribution Functions (CDF) and Riyadh Flood Precipitation Index (RFPI) are developed using 14-year 3B42RT data from 2000 to 2013. RFPI and CDF with 90% captured the three major flooding events that occurred in February 2005, May 2010 and November 2013 in Riyadh. CT with 3 mm/h intensity indicated the 2013 flooding, but missed those of 2005 and 2010. The methodology implemented herein is a first-step simple and accurate way for flash flood forecasting over Riyadh. The simplicity of the methodology enables its applicability for the TRMM follow-on missions like Global Precipitation Measurement (GPM) mission.

Effects of Rainfall Characteristics on the Stability of Tropical Residual Soil Slope

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Rahardjo Harianto

2016-01-01

Full Text Available Global climate change has a significant impact on rainfall characteristics, sea water level and groundwater table. Changes in rainfall characteristics may affect stability of slopes and have severe impacts on sustainable urban living. Information on the intensity, frequency and duration of rainfall is often required by geotechnical engineers for performing slope stability analyses. Many seepage analyses are commonly performed using the most extreme rainfall possible which is uneconomical in designing a slope repair or slope failure preventive measure. In this study, the historical rainfall data were analyzed and investigated to understand the characteristics of rainfall in Singapore. The frequency distribution method was used to estimate future rainfall characteristics in Singapore. New intensity-duration-frequency (IDF curves for rainfall in Singapore were developed for six different durations (10, 20, 30 min and 1, 2 and 24 h and six frequencies (2, 5, 10, 25, 50 and 100 years. The new IDF curves were used in the seepage and slope stability analyses to determine the variation of factor of safety of residual soil slopes under different rainfall intensities in Singapore.

Evaluation of Satellite and Model Precipitation Products Over Turkey

Science.gov (United States)

Yilmaz, M. T.; Amjad, M.

2017-12-01

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

Insight into the Global Carbon Cycle from Assimilation of Satellite CO2 measurements

Science.gov (United States)

Baker, D. F.

2017-12-01

A key goal of satellite CO2 measurements is to provide sufficient spatio-temporal coverage to constrain portions of the globe poorly observed by the in situ network, especially the tropical land regions. While systematic errors in both measurements and modeling remain a challenge, these satellite data are providing new insight into the functioning of the global carbon cycle, most notably across the recent 2015-16 En Niño. Here we interpret CO2 measurements from the GOSAT and OCO-2 satellites, as well as from the global in situ network (both surface sites and routine aircraft profiles), using a 4DVar-based global CO2 flux inversion across 2009-2017. The GOSAT data indicate that the tropical land regions are responsible for most of the observed global variability in CO2 across the last 8+ years. For the most recent couple of years where they overlap, the OCO-2 data give the same result, an +2 PgC/yr shift towards CO2 release in the ENSO warm phase, while disagreeing somewhat on the absolute value of the flux. The variability given by both these satellites disagrees with that given by an in situ-only inversion across the recent 2015-16 El Niño: the +2 PgC/yr shift from the satellites is double that given by the in situ data alone, suggesting that the more complete coverage is providing a more accurate view. For the current release of OCO-2 data (version 7), however, the flux results given by the OCO-2 land data (from both nadir- and glint-viewing modes) disagree significantly with those given by the ocean glint data; we examine the soon-to-be-released v8 data to assess whether these systematic retrieval errors have been reduced, and whether the corrected OCO-2 ocean data support the result from the land data. We discuss finer-scale features flux results given by the satellite data, and examine the importance of the flux prior, as well.

Nitrogen oxides in the troposphere – What have we learned from satellite measurements?

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Richter A.

2009-02-01

Full Text Available Nitrogen oxides are key species in the troposphere where they are linked to ozone formation and acid rain. The sources of nitrogen oxides are anthropogenic to large extend, mainly through combustion of fossil fuels. Satellite observations of NO2 provide global measurements of nitrogen oxides since summer 1995, and these data have been applied for many studies on the emission sources and strengths, the chemistry and the transport of NOx. In this paper, an overview will be given on satellite measurements of NO2 , some examples of typical applications and an outlook on future prospects.

Blending Satellite Observed, Model Simulated, and in Situ Measured Soil Moisture over Tibetan Plateau

Directory of Open Access Journals (Sweden)

Yijian Zeng

2016-03-01

Full Text Available The inter-comparison of different soil moisture (SM products over the Tibetan Plateau (TP reveals the inconsistency among different SM products, when compared to in situ measurement. It highlights the need to constrain the model simulated SM with the in situ measured data climatology. In this study, the in situ soil moisture networks, combined with the classification of climate zones over the TP, were used to produce the in situ measured SM climatology at the plateau scale. The generated TP scale in situ SM climatology was then used to scale the model-simulated SM data, which was subsequently used to scale the SM satellite observations. The climatology-scaled satellite and model-simulated SM were then blended objectively, by applying the triple collocation and least squares method. The final blended SM can replicate the SM dynamics across different climatic zones, from sub-humid regions to semi-arid and arid regions over the TP. This demonstrates the need to constrain the model-simulated SM estimates with the in situ measurements before their further applications in scaling climatology of SM satellite products.

Towards validation of ammonia (NH3) measurements from the IASI satellite

Science.gov (United States)

Van Damme, M.; Clarisse, L.; Dammers, E.; Liu, X.; Nowak, J. B.; Clerbaux, C.; Flechard, C. R.; Galy-Lacaux, C.; Xu, W.; Neuman, J. A.; Tang, Y. S.; Sutton, M. A.; Erisman, J. W.; Coheur, P. F.

2015-03-01

Limited availability of ammonia (NH3) observations is currently a barrier for effective monitoring of the nitrogen cycle. It prevents a full understanding of the atmospheric processes in which this trace gas is involved and therefore impedes determining its related budgets. Since the end of 2007, the Infrared Atmospheric Sounding Interferometer (IASI) satellite has been observing NH3 from space at a high spatio-temporal resolution. This valuable data set, already used by models, still needs validation. We present here a first attempt to validate IASI-NH3 measurements using existing independent ground-based and airborne data sets. The yearly distributions reveal similar patterns between ground-based and space-borne observations and highlight the scarcity of local NH3 measurements as well as their spatial heterogeneity and lack of representativity. By comparison with monthly resolved data sets in Europe, China and Africa, we show that IASI-NH3 observations are in fair agreement, but they are characterized by a smaller variation in concentrations. The use of hourly and airborne data sets to compare with IASI individual observations allows investigations of the impact of averaging as well as the representativity of independent observations for the satellite footprint. The importance of considering the latter and the added value of densely located airborne measurements at various altitudes to validate IASI-NH3 columns are discussed. Perspectives and guidelines for future validation work on NH3 satellite observations are presented.

EPSAT-SG: a satellite method for precipitation estimation; its concepts and implementation for the AMMA experiment

Directory of Open Access Journals (Sweden)

J. C. Bergès

2010-01-01

Full Text Available This paper presents a new rainfall estimation method, EPSAT-SG which is a frame for method design. The first implementation has been carried out to meet the requirement of the AMMA database on a West African domain. The rainfall estimation relies on two intermediate products: a rainfall probability and a rainfall potential intensity. The first one is computed from MSG/SEVIRI by a feed forward neural network. First evaluation results show better properties than direct precipitation intensity assessment by geostationary satellite infra-red sensors. The second product can be interpreted as a conditional rainfall intensity and, in the described implementation, it is extracted from GPCP-1dd. Various implementation options are discussed and comparison of this embedded product with 3B42 estimates demonstrates the importance of properly managing the temporal discontinuity. The resulting accumulated rainfall field can be presented as a GPCP downscaling. A validation based on ground data supplied by AGRHYMET (Niamey indicates that the estimation error has been reduced in this process. The described method could be easily adapted to other geographical area and operational environment.

Near-equatorial convective regimes over the Indian Ocean as revealed by synergistic analysis of satellite observations.

Digital Repository Service at National Institute of Oceanography (India)

Levy, G.; Geiss, A.; RameshKumar, M.R.

We examine the organization and temporal evolution of deep convection in relation to the low level flow over the Indian Ocean by a synergistic analysis of several satellite datasets for wind, rainfall, Outgoing Longwave Radiation (OLR) and cloud...

Comparison of cloud top heights derived from FY-2 meteorological satellites with heights derived from ground-based millimeter wavelength cloud radar

Science.gov (United States)

Wang, Zhe; Wang, Zhenhui; Cao, Xiaozhong; Tao, Fa

2018-01-01

Clouds are currently observed by both ground-based and satellite remote sensing techniques. Each technique has its own strengths and weaknesses depending on the observation method, instrument performance and the methods used for retrieval. It is important to study synergistic cloud measurements to improve the reliability of the observations and to verify the different techniques. The FY-2 geostationary orbiting meteorological satellites continuously observe the sky over China. Their cloud top temperature product can be processed to retrieve the cloud top height (CTH). The ground-based millimeter wavelength cloud radar can acquire information about the vertical structure of clouds-such as the cloud base height (CBH), CTH and the cloud thickness-and can continuously monitor changes in the vertical profiles of clouds. The CTHs were retrieved using both cloud top temperature data from the FY-2 satellites and the cloud radar reflectivity data for the same time period (June 2015 to May 2016) and the resulting datasets were compared in order to evaluate the accuracy of CTH retrievals using FY-2 satellites. The results show that the concordance rate of cloud detection between the two datasets was 78.1%. Higher consistencies were obtained for thicker clouds with larger echo intensity and for more continuous clouds. The average difference in the CTH between the two techniques was 1.46 km. The difference in CTH between low- and mid-level clouds was less than that for high-level clouds. An attenuation threshold of the cloud radar for rainfall was 0.2 mm/min; a rainfall intensity below this threshold had no effect on the CTH. The satellite CTH can be used to compensate for the attenuation error in the cloud radar data.

On Variability in Satellite Terrestrial Chlorophyll Fluorescence Measurements: Relationships with Phenology and Ecosystem-Atmosphere Carbon Exchange, Vegetation Structure, Clouds, and Sun-Satellite Geometry

Science.gov (United States)

Joiner, J.; Yoshida, Y.; Guanter, L.; Zhang, Y.; Vasilkov, A. P.; Schaefer, K. M.; Huemmrich, K. F.; Middleton, E.; Koehler, P.; Jung, M.; Tucker, C. J.; Lyapustin, A.; Wang, Y.; Frankenberg, C.; Berry, J. A.; Koster, R. D.; Reichle, R. H.; Lee, J. E.; Kawa, S. R.; Collatz, G. J.; Walker, G. K.; Van der Tol, C.

2014-12-01

Over the past several years, there have been several breakthroughs in our ability to detect the very small fluorescence emitted by chlorophyll in vegetation globally from space. There are now multiple instruments in space capable of measuring this signal at varying temporal and spatial resolutions. We will review the state-of-the-art with respect to these relatively new satellite measurements and ongoing studies that examine the relationships with photosynthesis. Now that we have a data record spanning more than seven years, we can examine variations due to seasonal carbon uptake, interannual variability, land-use changes, and water and temperature stress. In addition, we examine how clouds and satellite viewing geometry impact the signal. We compare and contrast these variations with those from popular vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), related to the potential photosynthesis as well as with measurements from flux tower gas exchange measurements and other model-based estimates of Global Primary Productivity (GPP). Vegetation fluorescence can be simulated in global vegetation models as well as with 1D canopy radiative transport models. We will describe how the satellite fluorescence data are being used to evaluate and potentially improve these models.

Development of a multi-sensor based urban discharge forecasting system using remotely sensed data: A case study of extreme rainfall in South Korea