The Potential Utilization of Satellite Derived Rainfall in a Data-Scarce Basin

2013 ◽  
Vol 726-731 ◽  
pp. 3531-3537
Author(s):  
Kwaku Amaning Adjei ◽  
Li Liang Ren ◽  
Emmanuel Kwame Appiah-Adjei ◽  
Samuel Nii Odai
Keyword(s):  
West Africa ◽  
Time Scales ◽  
Rain Gauge ◽  
Great Benefit ◽  
The Other ◽  
Its Analysis ◽  
Satellite Rainfall ◽  
Annual Time ◽  
Rainfall Estimates

This study assessed the potential for the use of satellite derived rainfall in a data-scarce basin like the Black Volta in West Africa. Using a point to pixel approach, accumulations of ground measurements on daily, monthly and annual time scales were compared with accumulations derived from 0.1° resolution daily gridded satellite Rainfall Estimates (RFE). The results from the analysis of the RFE data showed monthly correlations ranged from 0.76 to 0.92 when compared with the rain gauge measurements. These results obtained, indicate “good” to “very good” in terms of correlation (r) for the monthly and annual datasets. The study found that the use of satellite derived rainfall, like the RFE from FEWSNET, in the basin would be of great benefit considering the difficulties in accessing data both locally and from the other riparian countries; but its analysis and use should be on the monthly and annual scales.

scholarly journals Investigation of Discrepancies in Satellite Rainfall Estimates over Ethiopia

2014 ◽  
Vol 15 (6) ◽  
pp. 2347-2369 ◽  
Author(s):  
Matthew P. Young ◽  
Charles J. R. Williams ◽  
J. Christine Chiu ◽  
Ross I. Maidment ◽  
Shu-Hua Chen
Keyword(s):  
Daily Rainfall ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Rainfall Amount ◽  
Shallow Convection ◽  
Rain Gauges ◽  
The Mean ◽  
Satellite Rainfall ◽  
Convective Cells ◽  
Rainfall Estimates

Abstract Tropical Applications of Meteorology Using Satellite and Ground-Based Observations (TAMSAT) rainfall estimates are used extensively across Africa for operational rainfall monitoring and food security applications; thus, regional evaluations of TAMSAT are essential to ensure its reliability. This study assesses the performance of TAMSAT rainfall estimates, along with the African Rainfall Climatology (ARC), version 2; the Tropical Rainfall Measuring Mission (TRMM) 3B42 product; and the Climate Prediction Center morphing technique (CMORPH), against a dense rain gauge network over a mountainous region of Ethiopia. Overall, TAMSAT exhibits good skill in detecting rainy events but underestimates rainfall amount, while ARC underestimates both rainfall amount and rainy event frequency. Meanwhile, TRMM consistently performs best in detecting rainy events and capturing the mean rainfall and seasonal variability, while CMORPH tends to overdetect rainy events. Moreover, the mean difference in daily rainfall between the products and rain gauges shows increasing underestimation with increasing elevation. However, the distribution in satellite–gauge differences demonstrates that although 75% of retrievals underestimate rainfall, up to 25% overestimate rainfall over all elevations. Case studies using high-resolution simulations suggest underestimation in the satellite algorithms is likely due to shallow convection with warm cloud-top temperatures in addition to beam-filling effects in microwave-based retrievals from localized convective cells. The overestimation by IR-based algorithms is attributed to nonraining cirrus with cold cloud-top temperatures. These results stress the importance of understanding regional precipitation systems causing uncertainties in satellite rainfall estimates with a view toward using this knowledge to improve rainfall algorithms.

scholarly journals Evaluation of High-Resolution Satellite Rainfall Products through Streamflow Simulation in a Hydrological Modeling of a Small Mountainous Watershed in Ethiopia

2012 ◽  
Vol 13 (1) ◽  
pp. 338-350 ◽  
Author(s):  
Menberu M. Bitew ◽  
Mekonnen Gebremichael ◽  
Lula T. Ghebremichael ◽  
Yared A. Bayissa
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Bias Correction ◽  
Hydrological Modeling ◽  
Rain Gauge ◽  
Hydrologic Model ◽  
Model Simulations ◽  
Mountainous Watershed ◽  
Satellite Rainfall ◽  
Rainfall Estimates

Abstract This study focuses on evaluating four widely used global high-resolution satellite rainfall products [the Climate Prediction Center’s morphing technique (CMORPH) product, the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) near-real-time product (3B42RT), the TMPA method post-real-time research version product (3B42), and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) product] with a spatial resolution of 0.25° and temporal resolution of 3 h through their streamflow simulations in the Soil and Water Assessment Tool (SWAT) hydrologic model of a 299-km2 mountainous watershed in Ethiopia. Results show significant biases in the satellite rainfall estimates. The 3B42RT and CMORPH products perform better than the 3B42 and PERSIANN. The predictive ability of each of the satellite rainfall was examined using a SWAT model calibrated in two different approaches: with rain gauge rainfall as input, and with each of the satellite rainfall products as input. Significant improvements in model streamflow simulations are obtained when the model is calibrated with input-specific rainfall data than with rain gauge data. Calibrating SWAT with satellite rainfall estimates results in curve number values that are by far higher than the standard tabulated values, and therefore caution must be exercised when using standard tabulated parameter values with satellite rainfall inputs. The study also reveals that bias correction of satellite rainfall estimates significantly improves the model simulations. The best-performing model simulations based on satellite rainfall inputs are obtained after bias correction and model recalibration.

scholarly journals The TAMORA algorithm: satellite rainfall estimates over West Africa using multi-spectral SEVIRI data

2010 ◽  
Vol 25 ◽  
pp. 3-9 ◽  
Author(s):  
R. S. Chadwick ◽  
D. I. F. Grimes ◽  
R. W. Saunders ◽  
P. N. Francis ◽  
T. A. Blackmore
Keyword(s):  
West Africa ◽  
Estimation Algorithm ◽  
Radar Data ◽  
Local Calibration ◽  
Accumulated Rainfall ◽  
Satellite Rainfall ◽  
Sahel Region ◽  
Rain Rates ◽  
Improved Accuracy ◽  
Rainfall Estimates

Abstract. A multi-spectral rainfall estimation algorithm has been developed for the Sahel region of West Africa with the purpose of producing accumulated rainfall estimates for drought monitoring and food security. Radar data were used to calibrate multi-channel SEVIRI data from MSG, and a probability of rainfall at several different rain-rates was established for each combination of SEVIRI radiances. Radar calibrations from both Europe (the SatPrecip algorithm) and Niger (TAMORA algorithm) were used. 10 day estimates were accumulated from SatPrecip and TAMORA and compared with kriged gauge data and TAMSAT satellite rainfall estimates over West Africa. SatPrecip was found to produce large overestimates for the region, probably because of its non-local calibration. TAMORA was negatively biased for areas of West Africa with relatively high rainfall, but its skill was comparable to TAMSAT for the low-rainfall region climatologically similar to its calibration area around Niamey. These results confirm the high importance of local calibration for satellite-derived rainfall estimates. As TAMORA shows no improvement in skill over TAMSAT for dekadal estimates, the extra cloud-microphysical information provided by multi-spectral data may not be useful in determining rainfall accumulations at a ten day timescale. Work is ongoing to determine whether it shows improved accuracy at shorter timescales.

Validation of Satellite Rainfall Estimates over Equatorial East Africa

2021 ◽  
Author(s):  
Simon Ageet ◽  
Andreas Fink ◽  
Marlon Maranan
Keyword(s):  
East Africa ◽  
Extreme Values ◽  
Extreme Event ◽  
Weather Prediction ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Annual Rainfall ◽  
Extreme Rainfall Events ◽  
Satellite Rainfall ◽  
Rainfall Estimates

<p>The sparsity of rain gauge (RG) data over Africa is a known impediment to the assessments of hydro-meteorological risks and of the skill of numerical weather prediction (NWP) models. Satellite rainfall estimates (SREs) have been used as surrogate fields for a long time and are continuously replaced by more advanced algorithms.  Using a unique daily rainfall dataset from 36 stations across equatorial East Africa for the period 2001–2018, this study performs a multi-scale evaluation of gauge-calibrated SREs, namely, Integrated Multi-satellite Retrieval for Global Precipitation Measurement (GPM) (IMERG), Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and Multi-Source Weighted-Ensemble Precipitation (MSWEP). Skills were assessed from daily to annual timescales, for extreme daily precipitation, and for the TMPA and IMERG near real-time (NRT) products. Results show that: 1) the satellite products reproduce the annual rainfall pattern and seasonal rainfall cycle well, despite exhibiting biases of up to 9%; 2) IMERG is the best overall for shorter temporal scales (daily, pentadal and dekadal) while MSWEP and CHIRPS perform best at the monthly and annual timesteps, respectively; 3) the SREs’ performance, especially in MSWEP, shows high spatial variability likely due to the variation of weights assigned during gauge calibration; 4) all the SREs miss between 57% (IMERG NRT)  and 83 (CHIRPS) of daily extreme rainfall events recorded in the RGs; 5) IMERG NRT outperforms all the other products regarding extreme event detection and accuracy; and 6) for assessing return values of daily extreme values, IMERG and MSWEP are satisfactory while the use of CHIRPS cannot be recommended. The study highlights some improvements of IMERG over its predecessor TMPA and the potential of Multi-Source Weighted-Ensembles products such as MSWEP for flood risk assessment and validation of NWP rainfall forecasts over East Africa.</p>

scholarly journals Evaluation of Satellite Rainfall Estimates in the Pra Basin of Ghana

2016 ◽  
Author(s):  
Collins Owusu ◽  
Kwaku Amaning Adjei ◽  
Samuel Nii Odai
Keyword(s):  
Missing Data ◽  
Perfect Match ◽  
The Other ◽  
Ungauged Basins ◽  
Alternative Source ◽  
Precipitation Measurement ◽  
Verification Methods ◽  
Need To Evaluate ◽  
Satellite Rainfall ◽  
Rainfall Estimates

Satellite-based rainfall estimation products provide a vital alternative source of rainfall data in areas where conventional precipitation measurement is not readily available. In order to facilitate the use of these products there is the need to evaluate their accuracies. This study evaluated the accuracy of three satellite rainfall products; TMPA 3B42RT, TMPA 3B42 and CMORPH in the Pra basin (23,330 km2) of Ghana. The evaluation was through the point-to-pixel method by comparing 0.25°x 0.25° satellite grids to gauged rainfall based on gauge locations and analyzed statistically using correlation coefficient (r), bias and percent bias (pBias) as the performance verification methods. Seven (7) gauge stations with no missing data for the period of 2003-2008 was used in the evaluation. The analysis was based on daily, monthly, annual and seasonal timescales. Our results showed a good correlation between the TMPA products and the gauged data on all timescales considered. The CMORPH on the other hand showed huge overestimation at all gauge locations. The TMPA 3B42 was seen to be the best amongst the three products. The overall rainfall in the basin was well depicted by the TMPA 3B42 and 3B42RT. Although there wasn’t a perfect match between the 3B42RT and 3B42 products and the gauged rainfall, these products can be used to supplement gauged rainfall measurements in the basin and in estimation of rainfall in ungauged basins with similar characteristics.

scholarly journals Evaluation of satellite rainfall estimates over Ethiopian river basins

2011 ◽  
Vol 15 (5) ◽  
pp. 1505-1514 ◽  
Author(s):  
T. G. Romilly ◽  
M. Gebremichael
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
River Basins ◽  
Rain Gauge ◽  
Rainfall Regime ◽  
Humid Climate ◽  
Precipitation Estimation ◽  
Satellite Rainfall ◽  
Almost All ◽  
High Elevations ◽  
Rainfall Estimates

Abstract. High resolution satellite-based rainfall estimates (SREs) have enormous potential for use in hydrological applications, particularly in the developing world as an alternative to conventional rain gauges which are typically sparse. In this study, three SREs have been evaluated against collocated rain gauge measurements in Ethiopia across six river basins that represent different rainfall regimes and topography. The comparison is made using five-year (2003–2007) averages, and results are stratified by river basin, elevation and season. The SREs considered are: the Climate Prediction Center morphing method (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Neural Networks (PERSIANN) and the real-time version of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT. Overall, the microwave-based products TMPA 3B42RT and CMORPH outperform the infrared-based product PERSIANN: PERSIANN tends to underestimate rainfall by 43 %, while CMORPH tends to underestimate by 11 % and TMPA 3B42RT tends to overestimate by 5 %. The bias in the satellite rainfall estimates depends on the rainfall regime, and, in some regimes, the elevation. In the northwest region, which is characterized mainly by highland topography, a humid climate and a strong Intertropical Convergence Zone (ITCZ) effect, elevation has a strong influence on the accuracy of the SREs: TMPA 3B42RT and CMORPH tend to overestimate at low elevations but give reasonably accurate results at high elevations, whereas PERSIANN gives reasonably accurate values at low elevations but underestimates at high elevations. In the southeast region, which is characterized mainly by lowland topography, a semi-arid climate and southerly winds, elevation does not have a significant influence on the accuracy of the SREs, and all the SREs underestimate rainfall across almost all elevations.

scholarly journals River flow prediction in data scarce regions: soil moisture integrated satellite rainfall products outperform rain gauge observations in West Africa

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Luca Brocca ◽  
Christian Massari ◽  
Thierry Pellarin ◽  
Paolo Filippucci ◽  
Luca Ciabatta ◽  
...  
Keyword(s):  
Soil Moisture ◽  
West Africa ◽  
River Flow ◽  
Rain Gauge ◽  
Flow Prediction ◽  
Satellite Rainfall

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

2018 ◽  
Vol 378 ◽  
pp. 59-65 ◽  
Author(s):  
Thomas Matingo ◽  
Webster Gumindoga ◽  
Hodson Makurira
Keyword(s):  
Flash Flood ◽  
Daily Rainfall ◽  
Flash Floods ◽  
Rain Gauge ◽  
Hydrological Modelling ◽  
Probability Of Detection ◽  
Time Step ◽  
Flood Modelling ◽  
Satellite Rainfall ◽  
Rainfall Estimates

Abstract. 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 hydrological processes such as flash floods for sub-daily rainfall, because of improved spatial and temporal resolution.

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