Articles | Volume 22, issue 8
https://doi.org/10.5194/hess-22-4547-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-4547-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluation of multiple climate data sources for managing environmental resources in East Africa
Solomon Hailu Gebrechorkos
CORRESPONDING AUTHOR
United Nations University Institute for Integrated Management of
Material Fluxes and of Resources (UNU-FLORES), 01067 Dresden, Germany
Faculty of Environmental Sciences, Institute of Hydrology and
Meteorology, Technische Universität Dresden, 01062 Dresden,
Germany
Stephan Hülsmann
United Nations University Institute for Integrated Management of
Material Fluxes and of Resources (UNU-FLORES), 01067 Dresden, Germany
Christian Bernhofer
Faculty of Environmental Sciences, Institute of Hydrology and
Meteorology, Technische Universität Dresden, 01062 Dresden,
Germany
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Solomon H. Gebrechorkos, Julian Leyland, Simon J. Dadson, Sagy Cohen, Louise Slater, Michel Wortmann, Philip J. Ashworth, Georgina L. Bennett, Richard Boothroyd, Hannah Cloke, Pauline Delorme, Helen Griffith, Richard Hardy, Laurence Hawker, Stuart McLelland, Jeffrey Neal, Andrew Nicholas, Andrew J. Tatem, Ellie Vahidi, Yinxue Liu, Justin Sheffield, Daniel R. Parsons, and Stephen E. Darby
Hydrol. Earth Syst. Sci., 28, 3099–3118, https://doi.org/10.5194/hess-28-3099-2024, https://doi.org/10.5194/hess-28-3099-2024, 2024
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Drought is undeniably one of the most intricate and significant natural hazards with far-reaching consequences for the environment, economy, water resources, agriculture, and societies across the globe. In response to this challenge, we have devised high-resolution drought indices. These indices serve as invaluable indicators for assessing shifts in drought patterns and their associated impacts on a global, regional, and local level facilitating the development of tailored adaptation strategies.
Solomon H. Gebrechorkos, Julian Leyland, Simon J. Dadson, Sagy Cohen, Louise Slater, Michel Wortmann, Philip J. Ashworth, Georgina L. Bennett, Richard Boothroyd, Hannah Cloke, Pauline Delorme, Helen Griffith, Richard Hardy, Laurence Hawker, Stuart McLelland, Jeffrey Neal, Andrew Nicholas, Andrew J. Tatem, Ellie Vahidi, Yinxue Liu, Justin Sheffield, Daniel R. Parsons, and Stephen E. Darby
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Solomon H. Gebrechorkos, Jian Peng, Ellen Dyer, Diego G. Miralles, Sergio M. Vicente-Serrano, Chris Funk, Hylke E. Beck, Dagmawi T. Asfaw, Michael B. Singer, and Simon J. Dadson
Earth Syst. Sci. Data, 15, 5449–5466, https://doi.org/10.5194/essd-15-5449-2023, https://doi.org/10.5194/essd-15-5449-2023, 2023
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Geosci. Model Dev., 15, 7353–7370, https://doi.org/10.5194/gmd-15-7353-2022, https://doi.org/10.5194/gmd-15-7353-2022, 2022
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Hydrol. Earth Syst. Sci., 26, 3177–3239, https://doi.org/10.5194/hess-26-3177-2022, https://doi.org/10.5194/hess-26-3177-2022, 2022
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Judith Marie Pöschmann, Dongkyun Kim, Rico Kronenberg, and Christian Bernhofer
Nat. Hazards Earth Syst. Sci., 21, 1195–1207, https://doi.org/10.5194/nhess-21-1195-2021, https://doi.org/10.5194/nhess-21-1195-2021, 2021
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Uta Moderow, Stefanie Fischer, Thomas Grünwald, Ronald Queck, and Christian Bernhofer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-202, https://doi.org/10.5194/hess-2020-202, 2020
Preprint withdrawn
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We analyzed three different estimates of evapotranspiration (ET) for four different sites along an elevation gradient of a low mountain range over 11 years. We found similar dependencies on meteorological variables for all three different ET estimates. Based on our analyses we recommend using a distinct ET estimate. Analysis further suggests that water temporally stored on plant surfaces should receive more attention. Our results contribute to determining reliable ET estimates.
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Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-27, https://doi.org/10.5194/hess-2020-27, 2020
Preprint withdrawn
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Proc. IAHS, 381, 7–11, https://doi.org/10.5194/piahs-381-7-2019, https://doi.org/10.5194/piahs-381-7-2019, 2019
Chunjing Qiu, Dan Zhu, Philippe Ciais, Bertrand Guenet, Gerhard Krinner, Shushi Peng, Mika Aurela, Christian Bernhofer, Christian Brümmer, Syndonia Bret-Harte, Housen Chu, Jiquan Chen, Ankur R. Desai, Jiří Dušek, Eugénie S. Euskirchen, Krzysztof Fortuniak, Lawrence B. Flanagan, Thomas Friborg, Mateusz Grygoruk, Sébastien Gogo, Thomas Grünwald, Birger U. Hansen, David Holl, Elyn Humphreys, Miriam Hurkuck, Gerard Kiely, Janina Klatt, Lars Kutzbach, Chloé Largeron, Fatima Laggoun-Défarge, Magnus Lund, Peter M. Lafleur, Xuefei Li, Ivan Mammarella, Lutz Merbold, Mats B. Nilsson, Janusz Olejnik, Mikaell Ottosson-Löfvenius, Walter Oechel, Frans-Jan W. Parmentier, Matthias Peichl, Norbert Pirk, Olli Peltola, Włodzimierz Pawlak, Daniel Rasse, Janne Rinne, Gaius Shaver, Hans Peter Schmid, Matteo Sottocornola, Rainer Steinbrecher, Torsten Sachs, Marek Urbaniak, Donatella Zona, and Klaudia Ziemblinska
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X. Wu, N. Vuichard, P. Ciais, N. Viovy, N. de Noblet-Ducoudré, X. Wang, V. Magliulo, M. Wattenbach, L. Vitale, P. Di Tommasi, E. J. Moors, W. Jans, J. Elbers, E. Ceschia, T. Tallec, C. Bernhofer, T. Grünwald, C. Moureaux, T. Manise, A. Ligne, P. Cellier, B. Loubet, E. Larmanou, and D. Ripoche
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Hydrol. Earth Syst. Sci., 19, 3457–3474, https://doi.org/10.5194/hess-19-3457-2015, https://doi.org/10.5194/hess-19-3457-2015, 2015
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Predicting hydrological effects of land use change, e.g. enhanced cultivation of short rotation coppices, requires an adequate parameterisation. Measurements and modelling results show that leaf area index, stomatal resistance and in particular start and length of growing season are most sensitive to soil hydrological quantities, like ground water recharge (GWR). Only simulations over 30 years, reflecting long-term climate variability, show even zero GWR, especially in succeeding dry years.
M. Renner, K. Brust, K. Schwärzel, M. Volk, and C. Bernhofer
Hydrol. Earth Syst. Sci., 18, 389–405, https://doi.org/10.5194/hess-18-389-2014, https://doi.org/10.5194/hess-18-389-2014, 2014
D. Lisniak, J. Franke, and C. Bernhofer
Hydrol. Earth Syst. Sci., 17, 2487–2500, https://doi.org/10.5194/hess-17-2487-2013, https://doi.org/10.5194/hess-17-2487-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Remote Sensing and GIS
Extent of gross underestimation of precipitation in India
A D-vine copula-based quantile regression towards merging satellite precipitation products over rugged topography: a case study in the upper Tekeze–Atbara Basin
Improved soil evaporation remote sensing retrieval algorithms and associated uncertainty analysis on the Tibetan Plateau
SMPD: a soil moisture-based precipitation downscaling method for high-resolution daily satellite precipitation estimation
Evaluating the accuracy of gridded water resources reanalysis and evapotranspiration products for assessing water security in poorly gauged basins
Attribution of global evapotranspiration trends based on the Budyko framework
The influence of vegetation water dynamics on the ASCAT backscatter–incidence angle relationship in the Amazon
Extrapolating continuous vegetation water content to understand sub-daily backscatter variations
Comprehensive evaluation of satellite-based and reanalysis soil moisture products using in situ observations over China
Variations in surface roughness of heterogeneous surfaces in the Nagqu area of the Tibetan Plateau
Evapotranspiration in the Amazon: spatial patterns, seasonality, and recent trends in observations, reanalysis, and climate models
The benefit of brightness temperature assimilation for the SMAP Level-4 surface and root-zone soil moisture analysis
Evaluation of the dual-polarization weather radar quantitative precipitation estimation using long-term datasets
Validation of SMAP L2 passive-only soil moisture products using upscaled in situ measurements collected in Twente, the Netherlands
Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa
Data-driven estimates of evapotranspiration and its controls in the Congo Basin
Ability of an Australian reanalysis dataset to characterise sub-daily precipitation
A daily 25 km short-latency rainfall product for data-scarce regions based on the integration of the Global Precipitation Measurement mission rainfall and multiple-satellite soil moisture products
Evaluation of soil moisture from CCAM-CABLE simulation, satellite-based models estimates and satellite observations: a case study of Skukuza and Malopeni flux towers
Statistical characteristics of raindrop size distribution during rainy seasons in the Beijing urban area and implications for radar rainfall estimation
An evaluation of daily precipitation from a regional atmospheric reanalysis over Australia
Performance of bias-correction schemes for CMORPH rainfall estimates in the Zambezi River basin
The El Niño event of 2015–2016: climate anomalies and their impact on groundwater resources in East and Southern Africa
Consistency of satellite-based precipitation products in space and over time compared with gauge observations and snow- hydrological modelling in the Lake Titicaca region
Using phase lags to evaluate model biases in simulating the diurnal cycle of evapotranspiration: a case study in Luxembourg
Integrating multiple satellite observations into a coherent dataset to monitor the full water cycle – application to the Mediterranean region
An improved perspective in the spatial representation of soil moisture: potential added value of SMOS disaggregated 1 km resolution “all weather” product
Temporal- and spatial-scale and positional effects on rain erosivity derived from point-scale and contiguous rain data
The PERSIANN family of global satellite precipitation data: a review and evaluation of products
Exploring seasonal and regional relationships between the Evaporative Stress Index and surface weather and soil moisture anomalies across the United States
Development of soil moisture profiles through coupled microwave–thermal infrared observations in the southeastern United States
Precipitation downscaling using a probability-matching approach and geostationary infrared data: an evaluation over six climate regions
Regional co-variability of spatial and temporal soil moisture–precipitation coupling in North Africa: an observational perspective
Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US
Regional frequency analysis of extreme rainfall in Belgium based on radar estimates
An assessment of the performance of global rainfall estimates without ground-based observations
Water–food–energy nexus with changing agricultural scenarios in India during recent decades
Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean
The effect of satellite-derived surface soil moisture and leaf area index land data assimilation on streamflow simulations over France
Reservoir storage and hydrologic responses to droughts in the Paraná River basin, south-eastern Brazil
Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels
Comparison of satellite-based evapotranspiration estimates over the Tibetan Plateau
Evaluation of soil moisture downscaling using a simple thermal-based proxy – the REMEDHUS network (Spain) example
The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat
Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002–2012)
Scoping a field experiment: error diagnostics of TRMM precipitation radar estimates in complex terrain as a basis for IPHEx2014
Comparison of rainfall estimations by TRMM 3B42, MPEG and CFSR with ground-observed data for the Lake Tana basin in Ethiopia
Downscaling of seasonal soil moisture forecasts using satellite data
Long term soil moisture mapping over the Tibetan plateau using Special Sensor Microwave/Imager
Intercomparison of four remote-sensing-based energy balance methods to retrieve surface evapotranspiration and water stress of irrigated fields in semi-arid climate
Gopi Goteti and James Famiglietti
Hydrol. Earth Syst. Sci., 28, 3435–3455, https://doi.org/10.5194/hess-28-3435-2024, https://doi.org/10.5194/hess-28-3435-2024, 2024
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Underestimation of precipitation (UoP) in India is a substantial issue not just within gauge-based precipitation datasets but also within state-of-the-art satellite and reanalysis-based datasets. UoP is prevalent across most river basins of India, including those that have experienced catastrophic flooding in the recent past. This paper highlights not only a major limitation of existing precipitation products for India but also other data-related obstacles faced by the research community.
Mohammed Abdallah, Ke Zhang, Lijun Chao, Abubaker Omer, Khalid Hassaballah, Kidane Welde Reda, Linxin Liu, Tolossa Lemma Tola, and Omar M. Nour
Hydrol. Earth Syst. Sci., 28, 1147–1172, https://doi.org/10.5194/hess-28-1147-2024, https://doi.org/10.5194/hess-28-1147-2024, 2024
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A D-vine copula-based quantile regression (DVQR) model is used to merge satellite precipitation products. The performance of the DVQR model is compared with the simple model average and one-outlier-removed average methods. The nonlinear DVQR model outperforms the quantile-regression-based multivariate linear and Bayesian model averaging methods.
Jin Feng, Ke Zhang, Huijie Zhan, and Lijun Chao
Hydrol. Earth Syst. Sci., 27, 363–383, https://doi.org/10.5194/hess-27-363-2023, https://doi.org/10.5194/hess-27-363-2023, 2023
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Here we improved a satellite-driven evaporation algorithm by introducing the modified versions of the two constraint schemes. The two moisture constraint schemes largely improved the evaporation estimation on two barren-dominated basins of the Tibetan Plateau. Investigation of moisture constraint uncertainty showed that high-quality soil moisture can optimally represent moisture, and more accessible precipitation data generally help improve the estimation of barren evaporation.
Kunlong He, Wei Zhao, Luca Brocca, and Pere Quintana-Seguí
Hydrol. Earth Syst. Sci., 27, 169–190, https://doi.org/10.5194/hess-27-169-2023, https://doi.org/10.5194/hess-27-169-2023, 2023
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In this study, we developed a soil moisture-based precipitation downscaling (SMPD) method for spatially downscaling the GPM daily precipitation product by exploiting the connection between surface soil moisture and precipitation according to the soil water balance equation. Based on this physical method, the spatial resolution of the daily precipitation product was downscaled to 1 km and the SMPD method shows good potential for the development of the high-resolution precipitation product.
Elias Nkiaka, Robert G. Bryant, Joshua Ntajal, and Eliézer I. Biao
Hydrol. Earth Syst. Sci., 26, 5899–5916, https://doi.org/10.5194/hess-26-5899-2022, https://doi.org/10.5194/hess-26-5899-2022, 2022
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Achieving water security in poorly gauged regions is hindered by a lack of in situ hydrometeorological data. In this study, we validated nine existing gridded water resource reanalyses and eight evapotranspiration products in eight representative gauged basins in Central–West Africa. Our results show the strengths and and weaknesses of the existing products and that these products can be used to assess water security in ungauged basins. However, it is imperative to validate these products.
Shijie Li, Guojie Wang, Chenxia Zhu, Jiao Lu, Waheed Ullah, Daniel Fiifi Tawia Hagan, Giri Kattel, and Jian Peng
Hydrol. Earth Syst. Sci., 26, 3691–3707, https://doi.org/10.5194/hess-26-3691-2022, https://doi.org/10.5194/hess-26-3691-2022, 2022
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We found that the precipitation variability dominantly controls global evapotranspiration (ET) in dry climates, while the net radiation has substantial control over ET in the tropical regions, and vapor pressure deficit (VPD) impacts ET trends in boreal mid-latitude climate. The critical role of VPD in controlling ET trends is particularly emphasized due to its influence in controlling the carbon–water–energy cycle.
Ashwini Petchiappan, Susan C. Steele-Dunne, Mariette Vreugdenhil, Sebastian Hahn, Wolfgang Wagner, and Rafael Oliveira
Hydrol. Earth Syst. Sci., 26, 2997–3019, https://doi.org/10.5194/hess-26-2997-2022, https://doi.org/10.5194/hess-26-2997-2022, 2022
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This study investigates spatial and temporal patterns in the incidence angle dependence of backscatter from the ASCAT C-band scatterometer and relates those to precipitation, humidity, and radiation data and GRACE equivalent water thickness in ecoregions in the Amazon. The results show that the ASCAT data record offers a unique perspective on vegetation water dynamics exhibiting sensitivity to moisture availability and demand and phenological change at interannual, seasonal, and diurnal scales.
Paul C. Vermunt, Susan C. Steele-Dunne, Saeed Khabbazan, Jasmeet Judge, and Nick C. van de Giesen
Hydrol. Earth Syst. Sci., 26, 1223–1241, https://doi.org/10.5194/hess-26-1223-2022, https://doi.org/10.5194/hess-26-1223-2022, 2022
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This study investigates the use of hydrometeorological sensors to reconstruct variations in internal vegetation water content of corn and relates these variations to the sub-daily behaviour of polarimetric L-band backscatter. The results show significant sensitivity of backscatter to the daily cycles of vegetation water content and dew, particularly on dry days and for vertical and cross-polarizations, which demonstrates the potential for using radar for studies on vegetation water dynamics.
Xiaolu Ling, Ying Huang, Weidong Guo, Yixin Wang, Chaorong Chen, Bo Qiu, Jun Ge, Kai Qin, Yong Xue, and Jian Peng
Hydrol. Earth Syst. Sci., 25, 4209–4229, https://doi.org/10.5194/hess-25-4209-2021, https://doi.org/10.5194/hess-25-4209-2021, 2021
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Soil moisture (SM) plays a critical role in the water and energy cycles of the Earth system, for which a long-term SM product with high quality is urgently needed. In situ observations are generally treated as the true value to systematically evaluate five SM products, including one remote sensing product and four reanalysis data sets during 1981–2013. This long-term intercomparison study provides clues for SM product enhancement and further hydrological applications.
Maoshan Li, Xiaoran Liu, Lei Shu, Shucheng Yin, Lingzhi Wang, Wei Fu, Yaoming Ma, Yaoxian Yang, and Fanglin Sun
Hydrol. Earth Syst. Sci., 25, 2915–2930, https://doi.org/10.5194/hess-25-2915-2021, https://doi.org/10.5194/hess-25-2915-2021, 2021
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In this study, using MODIS satellite data and site atmospheric turbulence observation data in the Nagqu area of the northern Tibetan Plateau, with the Massman-retrieved model and a single height observation to determine aerodynamic surface roughness, temporal and spatial variation characteristics of the surface roughness were analyzed. The result is feasible, and it can be applied to improve the model parameters of the land surface model and the accuracy of model simulation in future work.
Jessica C. A. Baker, Luis Garcia-Carreras, Manuel Gloor, John H. Marsham, Wolfgang Buermann, Humberto R. da Rocha, Antonio D. Nobre, Alessandro Carioca de Araujo, and Dominick V. Spracklen
Hydrol. Earth Syst. Sci., 25, 2279–2300, https://doi.org/10.5194/hess-25-2279-2021, https://doi.org/10.5194/hess-25-2279-2021, 2021
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Evapotranspiration (ET) is a vital part of the Amazon water cycle, but it is difficult to measure over large areas. In this study, we compare spatial patterns, seasonality, and recent trends in Amazon ET from a water-budget analysis with estimates from satellites, reanalysis, and global climate models. We find large differences between products, showing that many widely used datasets and climate models may not provide a reliable representation of this crucial variable over the Amazon.
Jianxiu Qiu, Jianzhi Dong, Wade T. Crow, Xiaohu Zhang, Rolf H. Reichle, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 1569–1586, https://doi.org/10.5194/hess-25-1569-2021, https://doi.org/10.5194/hess-25-1569-2021, 2021
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The SMAP L4 dataset has been extensively used in hydrological applications. We innovatively use a machine learning method to analyze how the efficiency of the L4 data assimilation (DA) system is determined. It shows that DA efficiency is mainly related to Tb innovation, followed by error in precipitation forcing and microwave soil roughness. Since the L4 system can effectively filter out precipitation error, future development should focus on correctly specifying the SSM–RZSM coupling strength.
Tanel Voormansik, Roberto Cremonini, Piia Post, and Dmitri Moisseev
Hydrol. Earth Syst. Sci., 25, 1245–1258, https://doi.org/10.5194/hess-25-1245-2021, https://doi.org/10.5194/hess-25-1245-2021, 2021
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A long set of operational polarimetric weather radar rainfall accumulations from Estonia and Italy are generated and investigated. Results show that the combined product of specific differential phase and horizontal reflectivity yields the best results when compared to rain gauge measurements. The specific differential-phase-based product overestimates weak precipitation, and the horizontal-reflectivity-based product underestimates heavy rainfall in all analysed accumulation periods.
Rogier van der Velde, Andreas Colliander, Michiel Pezij, Harm-Jan F. Benninga, Rajat Bindlish, Steven K. Chan, Thomas J. Jackson, Dimmie M. D. Hendriks, Denie C. M. Augustijn, and Zhongbo Su
Hydrol. Earth Syst. Sci., 25, 473–495, https://doi.org/10.5194/hess-25-473-2021, https://doi.org/10.5194/hess-25-473-2021, 2021
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NASA’s SMAP satellite provides estimates of the amount of water in the soil. With measurements from a network of 20 monitoring stations, the accuracy of these estimates has been studied for a 4-year period. We found an agreement between satellite and in situ estimates in line with the mission requirements once the large mismatches associated with rapidly changing water contents, e.g. soil freezing and rainfall, are excluded.
Moctar Dembélé, Bettina Schaefli, Nick van de Giesen, and Grégoire Mariéthoz
Hydrol. Earth Syst. Sci., 24, 5379–5406, https://doi.org/10.5194/hess-24-5379-2020, https://doi.org/10.5194/hess-24-5379-2020, 2020
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This study evaluates 102 combinations of rainfall and temperature datasets from satellite and reanalysis sources as input to a fully distributed hydrological model. The model is recalibrated for each input dataset, and the outputs are evaluated with streamflow, evaporation, soil moisture and terrestrial water storage data. Results show that no single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes.
Michael W. Burnett, Gregory R. Quetin, and Alexandra G. Konings
Hydrol. Earth Syst. Sci., 24, 4189–4211, https://doi.org/10.5194/hess-24-4189-2020, https://doi.org/10.5194/hess-24-4189-2020, 2020
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Water that evaporates from Africa's tropical forests provides rainfall throughout the continent. However, there are few sources of meteorological data in central Africa, so we use observations from satellites to estimate evaporation from the Congo Basin at different times of the year. We find that existing evaporation estimates in tropical Africa do not accurately capture seasonal variations in evaporation and that fluctuations in soil moisture and solar radiation drive evaporation rates.
Suwash Chandra Acharya, Rory Nathan, Quan J. Wang, Chun-Hsu Su, and Nathan Eizenberg
Hydrol. Earth Syst. Sci., 24, 2951–2962, https://doi.org/10.5194/hess-24-2951-2020, https://doi.org/10.5194/hess-24-2951-2020, 2020
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BARRA is a high-resolution reanalysis dataset over the Oceania region. This study evaluates the performance of sub-daily BARRA precipitation at point and spatial scales over Australia. We find that the dataset reproduces some of the sub-daily characteristics of precipitation well, although it exhibits some spatial displacement errors, and it performs better in temperate than in tropical regions. The product is well suited to complement other estimates derived from remote sensing and rain gauges.
Christian Massari, Luca Brocca, Thierry Pellarin, Gab Abramowitz, Paolo Filippucci, Luca Ciabatta, Viviana Maggioni, Yann Kerr, and Diego Fernandez Prieto
Hydrol. Earth Syst. Sci., 24, 2687–2710, https://doi.org/10.5194/hess-24-2687-2020, https://doi.org/10.5194/hess-24-2687-2020, 2020
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Rain gauges are unevenly spaced around the world with extremely low gauge density over places like Africa and South America. Here, water-related problems like floods, drought and famine are particularly severe and able to cause fatalities, migration and diseases. We have developed a rainfall dataset that exploits the synergies between rainfall and soil moisture to provide accurate rainfall observations which can be used to face these problems.
Floyd Vukosi Khosa, Mohau Jacob Mateyisi, Martina Reynita van der Merwe, Gregor Timothy Feig, Francois Alwyn Engelbrecht, and Michael John Savage
Hydrol. Earth Syst. Sci., 24, 1587–1609, https://doi.org/10.5194/hess-24-1587-2020, https://doi.org/10.5194/hess-24-1587-2020, 2020
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The paper evaluates soil moisture outputs from three structurally distinct models against in situ data. Our goal is to find how representative the model outputs are for site and region. This is a question of interest as some of the models have a specific regional focus on their inceptions. Much focus is placed on how the models capture the soil moisture signal. We find that there is agreement on seasonal patterns between the models and observations with a tolerable level of model uncertainty.
Yu Ma, Guangheng Ni, Chandrasekar V. Chandra, Fuqiang Tian, and Haonan Chen
Hydrol. Earth Syst. Sci., 23, 4153–4170, https://doi.org/10.5194/hess-23-4153-2019, https://doi.org/10.5194/hess-23-4153-2019, 2019
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Raindrop size distribution (DSD) information is fundamental in understanding the precipitation microphysics and quantitative precipitation estimation. This study extensively investigates the DSD characteristics during rainy seasons in the Beijing urban area using 5-year DSD observations from a Parsivel2 disdrometer. The statistical distributions of DSD parameters are examined and the polarimetric radar rainfall algorithms are derived to support the ongoing development of an X-band radar network.
Suwash Chandra Acharya, Rory Nathan, Quan J. Wang, Chun-Hsu Su, and Nathan Eizenberg
Hydrol. Earth Syst. Sci., 23, 3387–3403, https://doi.org/10.5194/hess-23-3387-2019, https://doi.org/10.5194/hess-23-3387-2019, 2019
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BARRA is a novel regional reanalysis for Australia. Our research demonstrates that it is able to characterize a rich spatial variation in daily precipitation behaviour. In addition, its ability to represent large rainfalls is valuable for the analysis of extremes. It is a useful complement to existing precipitation datasets for Australia, especially in sparsely gauged regions.
Webster Gumindoga, Tom H. M. Rientjes, Alemseged Tamiru Haile, Hodson Makurira, and Paolo Reggiani
Hydrol. Earth Syst. Sci., 23, 2915–2938, https://doi.org/10.5194/hess-23-2915-2019, https://doi.org/10.5194/hess-23-2915-2019, 2019
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We evaluate the influence of elevation and distance from large-scale open water bodies on bias for CMORPH satellite rainfall in the Zambezi basin. Effects of distance > 10 km from water bodies are minimal, whereas the effects at shorter distances are indicated but are not conclusive for lack of rain gauges. Taylor diagrams show station elevation influencing CMORPH performance. The
spatio-temporaland newly developed
elevation zonebias schemes proved more effective in removing CMORPH bias.
Seshagiri Rao Kolusu, Mohammad Shamsudduha, Martin C. Todd, Richard G. Taylor, David Seddon, Japhet J. Kashaigili, Girma Y. Ebrahim, Mark O. Cuthbert, James P. R. Sorensen, Karen G. Villholth, Alan M. MacDonald, and Dave A. MacLeod
Hydrol. Earth Syst. Sci., 23, 1751–1762, https://doi.org/10.5194/hess-23-1751-2019, https://doi.org/10.5194/hess-23-1751-2019, 2019
Frédéric Satgé, Denis Ruelland, Marie-Paule Bonnet, Jorge Molina, and Ramiro Pillco
Hydrol. Earth Syst. Sci., 23, 595–619, https://doi.org/10.5194/hess-23-595-2019, https://doi.org/10.5194/hess-23-595-2019, 2019
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This paper assesses the potential of satellite precipitation estimates (SPEs) for precipitation measurement and hydrological and snow modelling. A total of 12 SPEs is considered to provide a global overview of available SPE accuracy for users interested in such datasets. Results show that, over poorly monitored regions, SPEs represent a very efficient alternative to traditional precipitation gauges to follow precipitation in time and space and for hydrological and snow modelling.
Maik Renner, Claire Brenner, Kaniska Mallick, Hans-Dieter Wizemann, Luigi Conte, Ivonne Trebs, Jianhui Wei, Volker Wulfmeyer, Karsten Schulz, and Axel Kleidon
Hydrol. Earth Syst. Sci., 23, 515–535, https://doi.org/10.5194/hess-23-515-2019, https://doi.org/10.5194/hess-23-515-2019, 2019
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We estimate the phase lag of surface states and heat fluxes to incoming solar radiation at the sub-daily timescale. While evapotranspiration reveals a minor phase lag, the vapor pressure deficit used as input by Penman–Monteith approaches shows a large phase lag. The surface-to-air temperature gradient used by energy balance residual approaches shows a small phase shift in agreement with the sensible heat flux and thus explains the better correlation of these models at the sub-daily timescale.
Victor Pellet, Filipe Aires, Simon Munier, Diego Fernández Prieto, Gabriel Jordá, Wouter Arnoud Dorigo, Jan Polcher, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 465–491, https://doi.org/10.5194/hess-23-465-2019, https://doi.org/10.5194/hess-23-465-2019, 2019
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This study is an effort for a better understanding and quantification of the water cycle and related processes in the Mediterranean region, by dealing with satellite products and their uncertainties. The aims of the paper are 3-fold: (1) developing methods with hydrological constraints to integrate all the datasets, (2) giving the full picture of the Mediterranean WC, and (3) building a model-independent database that can evaluate the numerous regional climate models (RCMs) for this region.
Samiro Khodayar, Amparo Coll, and Ernesto Lopez-Baeza
Hydrol. Earth Syst. Sci., 23, 255–275, https://doi.org/10.5194/hess-23-255-2019, https://doi.org/10.5194/hess-23-255-2019, 2019
Franziska K. Fischer, Tanja Winterrath, and Karl Auerswald
Hydrol. Earth Syst. Sci., 22, 6505–6518, https://doi.org/10.5194/hess-22-6505-2018, https://doi.org/10.5194/hess-22-6505-2018, 2018
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The potential of rain to cause soil erosion by runoff is called rain erosivity. Rain erosivity is highly variable in space and time even over distances of less than 1 km. Contiguously measured radar rain data depict for the first time this spatio-temporal variation, but scaling factors are required to account for differences in spatial and temporal resolution compared to rain gauge data. These scaling factors were obtained from more than 2 million erosive events.
Phu Nguyen, Mohammed Ombadi, Soroosh Sorooshian, Kuolin Hsu, Amir AghaKouchak, Dan Braithwaite, Hamed Ashouri, and Andrea Rose Thorstensen
Hydrol. Earth Syst. Sci., 22, 5801–5816, https://doi.org/10.5194/hess-22-5801-2018, https://doi.org/10.5194/hess-22-5801-2018, 2018
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The goal of this article is to first provide an overview of the available PERSIANN precipitation retrieval algorithms and their differences. We evaluate the products over CONUS at different spatial and temporal scales using CPC data. Daily scale is the finest temporal scale used for the evaluation over CONUS. We provide a comparison of the available products at a quasi-global scale. We highlight the strengths and limitations of the PERSIANN products.
Jason A. Otkin, Yafang Zhong, David Lorenz, Martha C. Anderson, and Christopher Hain
Hydrol. Earth Syst. Sci., 22, 5373–5386, https://doi.org/10.5194/hess-22-5373-2018, https://doi.org/10.5194/hess-22-5373-2018, 2018
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Correlation analyses were used to explore relationships between the Evaporative Stress Index (ESI) – which depicts anomalies in evapotranspiration (ET) – and various land and atmospheric variables that impact ET. The results revealed that the ESI is more strongly correlated to anomalies in soil moisture and near-surface vapor pressure deficit than to precipitation and temperature anomalies. Large regional and seasonal dependencies in the strengths of the correlations were also observed.
Vikalp Mishra, James F. Cruise, Christopher R. Hain, John R. Mecikalski, and Martha C. Anderson
Hydrol. Earth Syst. Sci., 22, 4935–4957, https://doi.org/10.5194/hess-22-4935-2018, https://doi.org/10.5194/hess-22-4935-2018, 2018
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Multiple satellite observations can be used for surface and subsurface soil moisture estimations. In this study, satellite observations along with a mathematical model were used to distribute and develop multiyear soil moisture profiles over the southeastern US. Such remotely sensed profiles become particularly useful at large spatiotemporal scales, can be a significant tool in data-scarce regions of the world, can complement various land and crop models, and can act as drought indicators etc.
Ruifang Guo, Yuanbo Liu, Han Zhou, and Yaqiao Zhu
Hydrol. Earth Syst. Sci., 22, 3685–3699, https://doi.org/10.5194/hess-22-3685-2018, https://doi.org/10.5194/hess-22-3685-2018, 2018
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Existing satellite products are often insufficient for use in small-scale (< 10 km) hydrological and meteorological studies. We propose a new approach based on the cumulative distribution of frequency to downscale satellite precipitation products with geostationary (GEO) data. This paper uses CMORPH and FY2-E GEO data to examine the approach in six different climate regions. The downscaled precipitation performed better for convective systems.
Irina Y. Petrova, Chiel C. van Heerwaarden, Cathy Hohenegger, and Françoise Guichard
Hydrol. Earth Syst. Sci., 22, 3275–3294, https://doi.org/10.5194/hess-22-3275-2018, https://doi.org/10.5194/hess-22-3275-2018, 2018
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In North Africa rain storms can be as vital as they are devastating. The present study uses multi-year satellite data to better understand how and where soil moisture conditions affect development of rainfall in the area. Our results reveal two major regions in the southwest and southeast, where drier soils show higher potential to cause rainfall development. This knowledge is essential for the hydrological sector, and can be further used by models to improve prediction of rainfall and droughts.
Nishan Bhattarai, Kaniska Mallick, Nathaniel A. Brunsell, Ge Sun, and Meha Jain
Hydrol. Earth Syst. Sci., 22, 2311–2341, https://doi.org/10.5194/hess-22-2311-2018, https://doi.org/10.5194/hess-22-2311-2018, 2018
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We report the first ever regional-scale implementation of the Surface Temperature Initiated Closure (STIC1.2) model for mapping evapotranspiration (ET) using MODIS land surface and gridded climate datasets to overcome the existing uncertainties in aerodynamic temperature and conductance estimation in global ET models. Validation and intercomparison with SEBS and MOD16 products across an aridity gradient in the US manifested better ET mapping potential of STIC1.2 in different climates and biomes.
Edouard Goudenhoofdt, Laurent Delobbe, and Patrick Willems
Hydrol. Earth Syst. Sci., 21, 5385–5399, https://doi.org/10.5194/hess-21-5385-2017, https://doi.org/10.5194/hess-21-5385-2017, 2017
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Knowing the characteristics of extreme precipitation is useful for flood management applications like sewer system design. The potential of a 12-year high-quality weather radar precipitation dataset is investigated by comparison with rain gauges. Despite known limitations, a good agreement is found between the radar and the rain gauges. Using the radar data allow us to reduce the uncertainty of the extreme value analysis, especially for short duration extremes related to thunderstorms.
Christian Massari, Wade Crow, and Luca Brocca
Hydrol. Earth Syst. Sci., 21, 4347–4361, https://doi.org/10.5194/hess-21-4347-2017, https://doi.org/10.5194/hess-21-4347-2017, 2017
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The paper explores a method for the assessment of the performance of global rainfall estimates without relying on ground-based observations. Thanks to this method, different global correlation maps are obtained (for the first time without relying on a benchmark dataset) for some of the most used globally available rainfall products. This is central for hydroclimatic studies within data-scarce regions, where ground observations are scarce to evaluate the relative quality of a rainfall product
Beas Barik, Subimal Ghosh, A. Saheer Sahana, Amey Pathak, and Muddu Sekhar
Hydrol. Earth Syst. Sci., 21, 3041–3060, https://doi.org/10.5194/hess-21-3041-2017, https://doi.org/10.5194/hess-21-3041-2017, 2017
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The article summarises changing patterns of the water-food-energy nexus in India during recent decades. The work first analyses satellite data of water storage with a validation using the observed well data. Northern India shows a declining trend of water storage and western-central India shows an increasing trend of the same. Major droughts result in a drop in water storage which is not recovered due to uncontrolled ground water irrigation for agricultural activities even in good monsoon years.
Francesco Marra, Efrat Morin, Nadav Peleg, Yiwen Mei, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 21, 2389–2404, https://doi.org/10.5194/hess-21-2389-2017, https://doi.org/10.5194/hess-21-2389-2017, 2017
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Rainfall frequency analyses from radar and satellite estimates over the eastern Mediterranean are compared examining different climatic conditions. Correlation between radar and satellite results is high for frequent events and decreases with return period. The uncertainty related to record length is larger for drier climates. The agreement between different sensors instills confidence on their use for rainfall frequency analysis in ungauged areas of the Earth.
David Fairbairn, Alina Lavinia Barbu, Adrien Napoly, Clément Albergel, Jean-François Mahfouf, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 2015–2033, https://doi.org/10.5194/hess-21-2015-2017, https://doi.org/10.5194/hess-21-2015-2017, 2017
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This study assesses the impact on river discharge simulations over France of assimilating ASCAT-derived surface soil moisture (SSM) and leaf area index (LAI) observations into the ISBA land surface model. Wintertime LAI has a notable impact on river discharge. SSM assimilation degrades river discharge simulations. This is caused by limitations in the simplified versions of the Kalman filter and ISBA model used in this study. Implementing an observation operator for ASCAT is needed.
Davi de C. D. Melo, Bridget R. Scanlon, Zizhan Zhang, Edson Wendland, and Lei Yin
Hydrol. Earth Syst. Sci., 20, 4673–4688, https://doi.org/10.5194/hess-20-4673-2016, https://doi.org/10.5194/hess-20-4673-2016, 2016
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Drought propagation from rainfall deficits to reservoir depletion was studied based on remote sensing, monitoring and modelling data. Regional droughts were shown by widespread depletion in total water storage that reduced soil moisture storage and runoff, greatly reducing reservoir storage. The multidisciplinary approach to drought assessment shows the linkages between meteorological and hydrological droughts that are essential for managing water resources subjected to climate extremes.
Zhi Qing Peng, Xiaozhou Xin, Jin Jun Jiao, Ti Zhou, and Qinhuo Liu
Hydrol. Earth Syst. Sci., 20, 4409–4438, https://doi.org/10.5194/hess-20-4409-2016, https://doi.org/10.5194/hess-20-4409-2016, 2016
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A remote sensing algorithm named temperature sharpening and flux aggregation (TSFA) was applied to HJ-1B satellite data to estimate evapotranspiration over heterogeneous surface considering landscape and statistical effects on mixed pixels. Footprint validation results showed TSFA was more accurate and less uncertain than other two upscaling methods. Additional analysis and comparison showed TSFA can capture land surface heterogeneities and integrate the effect of landscapes within mixed pixels.
Jian Peng, Alexander Loew, Xuelong Chen, Yaoming Ma, and Zhongbo Su
Hydrol. Earth Syst. Sci., 20, 3167–3182, https://doi.org/10.5194/hess-20-3167-2016, https://doi.org/10.5194/hess-20-3167-2016, 2016
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The Tibetan Plateau plays a major role in regional and global climate. The knowledge of latent heat flux can help to better describe the complex interactions between land and atmosphere. The purpose of this paper is to provide a detailed cross-comparison of existing latent heat flux products over the TP. The results highlight the recently developed latent heat product – High Resolution Land Surface Parameters from Space (HOLAPS).
J. Peng, J. Niesel, and A. Loew
Hydrol. Earth Syst. Sci., 19, 4765–4782, https://doi.org/10.5194/hess-19-4765-2015, https://doi.org/10.5194/hess-19-4765-2015, 2015
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This paper gives a comprehensive evaluation of a simple newly developed downscaling scheme using in situ measurements from REMEDHUS network, a first cross-comparison of the performance of the downscaled soil moisture from MODIS and MSG SEVIRI, an evaluation of the performance of the downscaled soil moisture at different spatial resolutions, and an exploration of the influence of LST, vegetation index, terrain, clouds, and land cover heterogeneity on the performance of VTCI.
G. Boulet, B. Mougenot, J.-P. Lhomme, P. Fanise, Z. Lili-Chabaane, A. Olioso, M. Bahir, V. Rivalland, L. Jarlan, O. Merlin, B. Coudert, S. Er-Raki, and J.-P. Lagouarde
Hydrol. Earth Syst. Sci., 19, 4653–4672, https://doi.org/10.5194/hess-19-4653-2015, https://doi.org/10.5194/hess-19-4653-2015, 2015
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The paper presents a new model (SPARSE) to estimate total evapotranspiration as well as its components (evaporation and transpiration) from remote-sensing data in the thermal infra-red domain. The limits of computing two unknowns (evaporation and transpiration) out of one piece of information (one surface temperature) are assessed theoretically. The model performance in retrieving the components as well as the water stress is assessed for two wheat crops (one irrigated and one rainfed).
O. P. Prat and B. R. Nelson
Hydrol. Earth Syst. Sci., 19, 2037–2056, https://doi.org/10.5194/hess-19-2037-2015, https://doi.org/10.5194/hess-19-2037-2015, 2015
Y. Duan, A. M. Wilson, and A. P. Barros
Hydrol. Earth Syst. Sci., 19, 1501–1520, https://doi.org/10.5194/hess-19-1501-2015, https://doi.org/10.5194/hess-19-1501-2015, 2015
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A diagnostic analysis of the space-time structure of error in quantitative precipitation estimates (QPEs) from the precipitation radar on the Tropical Rainfall Measurement Mission satellite is presented here in preparation for the Integrated Precipitation and Hydrology Experiment (IPHEx) in 2014. A high-density raingauge network over the southern Appalachians allows for direct comparison between ground-based measurements and satellite-based QPE (PR 2A25 Version 7 with 5 years of data 2008-2013).
A. W. Worqlul, B. Maathuis, A. A. Adem, S. S. Demissie, S. Langan, and T. S. Steenhuis
Hydrol. Earth Syst. Sci., 18, 4871–4881, https://doi.org/10.5194/hess-18-4871-2014, https://doi.org/10.5194/hess-18-4871-2014, 2014
S. Schneider, A. Jann, and T. Schellander-Gorgas
Hydrol. Earth Syst. Sci., 18, 2899–2905, https://doi.org/10.5194/hess-18-2899-2014, https://doi.org/10.5194/hess-18-2899-2014, 2014
R. van der Velde, M. S. Salama, T. Pellarin, M. Ofwono, Y. Ma, and Z. Su
Hydrol. Earth Syst. Sci., 18, 1323–1337, https://doi.org/10.5194/hess-18-1323-2014, https://doi.org/10.5194/hess-18-1323-2014, 2014
J. Chirouze, G. Boulet, L. Jarlan, R. Fieuzal, J. C. Rodriguez, J. Ezzahar, S. Er-Raki, G. Bigeard, O. Merlin, J. Garatuza-Payan, C. Watts, and G. Chehbouni
Hydrol. Earth Syst. Sci., 18, 1165–1188, https://doi.org/10.5194/hess-18-1165-2014, https://doi.org/10.5194/hess-18-1165-2014, 2014
Cited articles
Abiodun, B. J., Abba Omar, S., Lennard, C., and Jack, C.: Using regional
climate models to simulate extreme rainfall events in the Western Cape,
South Africa: Simulating Extreme Rainfall Events in Western Cape, Int. J.
Climatol., 36, 689–705, https://doi.org/10.1002/joc.4376, 2016.
Anyah, R. O. and Semazzi, F. H. M.: Climate variability over the Greater
Horn of Africa based on NCAR AGCM ensemble, Theor. Appl. Climatol., 86,
39–62, https://doi.org/10.1007/s00704-005-0203-7, 2006.
Anyah, R. O. and Semazzi, F. H. M.: Variability of East African rainfall
based on multiyear Regcm3 simulations, Int. J. Climatol., 27, 357–371,
https://doi.org/10.1002/joc.1401, 2007.
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M.,
and Reinhardt, T.: Operational Convective-Scale Numerical Weather Prediction
with the COSMO Model: Description and Sensitivities, Mon. Weather Rev.,
139, 3887–3905, https://doi.org/10.1175/MWR-D-10-05013.1, 2011.
Bayissa, Y., Tadesse, T., Demisse, G., and Shiferaw, A.: Evaluation of
Satellite-Based Rainfall Estimates and Application to Monitor Meteorological
Drought for the Upper Blue Nile Basin, Ethiopia, Remote Sens., 9, 669, https://doi.org/10.3390/rs9070669, 2017.
Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles,
D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25∘ global
gridded precipitation (1979–2015) by merging gauge, satellite, and
reanalysis data, Hydrol. Earth Syst. Sci., 21, 589–615,
https://doi.org/10.5194/hess-21-589-2017, 2017.
Cattani, E., Merino, A., and Levizzani, V.: Evaluation of Monthly
Satellite-Derived Precipitation Products over East Africa, J. Hydrometeorol.,
17, 2555–2573, https://doi.org/10.1175/JHM-D-15-0042.1, 2016.
Ceccherini, G., Ameztoy, I., Hernández, C., and Moreno, C.:
High-Resolution Precipitation Datasets in South America and West Africa based
on Satellite-Derived Rainfall, Enhanced Vegetation Index and Digital
Elevation Model, Remote Sens., 7, 6454–6488, https://doi.org/10.3390/rs70506454, 2015.
Chaney, N. W., Sheffield, J., Villarini, G., and Wood, E. F.: Development of
a High-Resolution Gridded Daily Meteorological Dataset over Sub-Saharan
Africa: Spatial Analysis of Trends in Climate Extremes, J. Climate, 27,
5815–5835, https://doi.org/10.1175/JCLI-D-13-00423.1, 2014.
Climate Hazards Group (CHG): Climate Hazards Group InfraRed Precipitation
(CHIRP): available at
ftp://ftp.chg.ucsb.edu/pub/org/chg/products/CHIRP/daily/, last access:
24 July 2017.
Cohen Liechti, T., Matos, J. P., Boillat, J.-L., and Schleiss, A. J.:
Comparison and evaluation of satellite derived precipitation products for
hydrological modeling of the Zambezi River Basin, Hydrol. Earth Syst. Sci.,
16, 489–500, https://doi.org/10.5194/hess-16-489-2012, 2012.
Daren Harmel, R. and Smith, P. K.: Consideration of measurement uncertainty
in the evaluation of goodness-of-fit in hydrologic and water quality
modeling, J. Hydrol., 337, 326–336, https://doi.org/10.1016/j.jhydrol.2007.01.043, 2007.
Deblauwe, V., Droissart, V., Bose, R., Sonké, B., Blach-Overgaard, A.,
Svenning, J.-C., Wieringa, J. J., Ramesh, B. R., Stévart, T., and
Couvreur, T. L. P.: Remotely sensed temperature and precipitation data
improve species distribution modelling in the tropics: Remotely sensed
climate data for tropical species distribution models, Global Ecol.
Biogeogr., 25, 443–454, https://doi.org/10.1111/geb.12426, 2016.
Demaria, E. M. C., Maurer, E. P., Sheffield, J., Bustos, E., Poblete, D.,
Vicuña, S., and Meza, F.: Using a Gridded Global Dataset to Characterize
Regional Hydroclimate in Central Chile, J. Hydrometeorol., 14, 251–265,
https://doi.org/10.1175/JHM-D-12-047.1, 2012.
Dembélé, M. and Zwart, S. J.: Evaluation and comparison of
satellite-based rainfall products in Burkina Faso, West Africa, Int. J.
Remote Sens., 37, 3995–4014, https://doi.org/10.1080/01431161.2016.1207258, 2016.
Dinku, T., Kinfe, H., Ross, M., Elena, T., and Stephen, C.: Combined use of
satellite estimates and rain gauge observations to generate high-quality
historical rainfall time series over Ethiopia, Int. J. Climatol., 34,
2489–2504, https://doi.org/10.1002/joc.3855, 2013.
Dinku, T., Block, P., Sharoff, J., Hailemariam, K., Osgood, D., Corral, J.
del, Cousin, R., and Thomson, M. C.: Bridging critical gaps in climate
services and applications in Africa, Earth Perspect., 1, 15,
https://doi.org/10.1186/2194-6434-1-15, 2014.
Diro, G. T., Grimes, D. I. F., and Black, E.: Teleconnections between
Ethiopian summer rainfall and sea surface temperature: part I – observation
and modelling, Clim. Dynam., 37, 103–119, https://doi.org/10.1007/s00382-010-0837-8,
2011.
Dixon, J., Gulliver, A., and Gibbon, D.: Farming systems and poverty, Food
and Agricultural Organization of the United Nations and World Bank, Rome and
Washington, DC, available at:
http://www.fao.org/docrep/003/y1860e/y1860e00.htm (last access: 3
August 2015), 2001.
Duan, Z., Liu, J., Tuo, Y., Chiogna, G., and Disse, M.: Evaluation of eight
high spatial resolution gridded precipitation products in Adige Basin (Italy)
at multiple temporal and spatial scales, Sci. Total Environ., 573,
1536–1553, https://doi.org/10.1016/j.scitotenv.2016.08.213, 2016.
Earth System Grid Federation (ESGF): Regional Climate Models (RCMs),
available at: https://esgf-index1.ceda.ac.uk/projects/esgf-ceda/, last
access: 16 November 2016.
Endris, H. S., Omondi, P., Jain, S., Lennard, C., Hewitson, B., Chang'a, L.,
Awange, J. L., Dosio, A., Ketiem, P., Nikulin, G., Panitz, H.-J.,
Büchner, M., Stordal, F., and Tazalika, L.: Assessment of the Performance
of CORDEX Regional Climate Models in Simulating East African Rainfall, J.
Climate, 26, 8453–8475, https://doi.org/10.1175/JCLI-D-12-00708.1, 2013.
Endris, H. S., Lennard, C., Hewitson, B., Dosio, A., Nikulin, G., and Panitz,
H.-J.: Teleconnection responses in multi-GCM driven CORDEX RCMs over Eastern
Africa, Clim. Dynam., 46, 2821–2846, https://doi.org/10.1007/s00382-015-2734-7, 2015.
FAO: Adapting to climate change through land and water management in Eastern
Africa, Food and Agricultural Organization of the United Nations and World
Bank, Rome, available at: http://www.fao.org/3/a-i3781e.pdf (last
access: 3 August 2015), 2014.
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S.,
Husak, G., Rowland, J., Harrison, L., Hoell, A., and Michaelsen, J.: The
climate hazards infrared precipitation with stations – a new environmental
record for monitoring extremes, Sci. Data, 2, 150066,
https://doi.org/10.1038/sdata.2015.66, 2015.
Gan, T. Y., Ito, M., Hülsmann, S., Qin, X., Lu, X. X., Liong, S. Y.,
Rutschman, P., Disse, M., and Koivusalo, H.: Possible climate
change/variability and human impacts, vulnerability of drought-prone regions,
water resources and capacity building for Africa, Hydrolog. Sci. J., 61,
1209–1226, https://doi.org/10.1080/02626667.2015.1057143, 2016.
Gebrechorkos, S. H., Hülsmann, S., and Bernhofer, C.: Changes in
temperature and precipitation extremes in Ethiopia, Kenya, and Tanzania, Int.
J. Climatol., 1–13, https://doi.org/10.1002/joc.5777, 2018.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs,
L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K.,
Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da
Silva, A. M., Gu, W., Kim, G.-K., Koster, R., Lucchesi, R., Merkova, D.,
Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert,
S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis
for Research and Applications, Version 2 (MERRA-2), J. Climate, 30,
5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F., Gu,
G., Hong, Y., Bowman, K. P., and Stocker, E. F.: The TRMM Multisatellite
Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor
Precipitation Estimates at Fine Scales, J. Hydrometeorol., 8,
38–55, https://doi.org/10.1175/JHM560.1, 2007.
Huffman, G. J., Adler, R. F., Bolvin, D. T., and Gu, G.: Improving the global
precipitation record: GPCP Version 2.1, Geophys. Res. Lett., 36, L17808,
https://doi.org/10.1029/2009GL040000, 2009.
IFPRI: Economywide Impacts of Climate Change on Agriculture in Sub-Saharan
Africa – climatechange-agriculture.pdf, available at:
http://www.indiaenvironmentportal.org.in/files/climatechange-agriculture.pdf
(last access: 3 August 2015), 2009.
IPCC: IPCC Third Assessment Report: Climate Change 2001 (TAR), Geneva
Switzerland, available at: http://www.ipcc.ch/ipccreports/tar/wg1/
(last access: 3 August 2015), 2001.
IPCC: Climate Change 2007: The Physical Science Basis: Contribution of
Working Group I to the Fourth Assessment Report of the of the IPCC, edited
by: Solomon, S. et al., CAmbridge University Press, available at:
https://www.ipcc.ch/publications_and_data/ar4/wg1/en/contents.html
(last access: 30 November 2016), 2007.
IPCC: AR5 IPCC Whats in it for Africa, available at:
https://cdkn.org/resource/highlights-africa-ar5/ (last access:
4 January 2017), 2014.
International Research Institute climate data library (IRI/LDE): Climate
Hazards Group InfraRed Precipitation with Station data (CHIRPS), available
at: https://iridl.ldeo.columbia.edu/SOURCES/.UCSB/.CHIRPS/, last
access: 12 May 2016.
International Research Institute climate data library (IRI/LDEO): Africa
Rainfall Climatology version 2 (ARC2), available at:
https://iridl.ldeo.columbia.edu/SOURCES/.NOAA/.NCEP/.CPC/.FEWS/.Africa/.DAILY/.ARC2/,
last access: 31 October 2016.
Jebari, S., Berndtsson, R., Olsson, J., and Bahri, A.: Soil erosion
estimation based on rainfall disaggregation, J. Hydrol., 436–437, 102–110,
https://doi.org/10.1016/j.jhydrol.2012.03.001, 2012.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A.,
Reynolds, R., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K.
C., Ropelewski, C., Wang, J., Jenne, R., and Joseph, D.: The NCEP/NCAR
40-Year Reanalysis Project, B. Am. Meteorol. Soc., 77, 437–471,
https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996.
Kimani, M. W., Hoedjes, J. C. B., and Su, Z.: An Assessment of
Satellite-Derived Rainfall Products Relative to Ground Observations over East
Africa, Remote Sens., 9, 430, https://doi.org/10.3390/rs9050430, 2017.
Kim, J., Waliser, D. E., Mattmann, C. A., Goodale, C. E., Hart, A. F.,
Zimdars, P. A., Crichton, D. J., Jones, C., Nikulin, G., Hewitson, B., Jack,
C., Lennard, C., and Favre, A.: Evaluation of the CORDEX-Africa multi-RCM
hindcast: systematic model errors, Clim. Dynam., 42, 1189–1202,
https://doi.org/10.1007/s00382-013-1751-7, 2014.
Lafon, T., Dadson, S., Buys, G., and Prudhomme, C.: Bias correction of daily
precipitation simulated by a regional climate model: a comparison of methods,
Int. J. Climatol., 33, 1367–1381, https://doi.org/10.1002/joc.3518, 2013.
Legates, D. R. and McCabe, G. J.: Evaluating the use of “goodness-of-fit”
Measures in hydrologic and hydroclimatic model validation, Water Resour.
Res., 35, 233–241, https://doi.org/10.1029/1998WR900018, 1999.
Maidment, R. I., Grimes, D., Allan, R. P., Tarnavsky, E., Stringer, M.,
Hewison, T., Roebeling, R., and Black, E.: The 30 year TAMSAT African
Rainfall Climatology And Time series (TARCAT) data set, J. Geophys.
Res.-Atmos., 119, JD021927, https://doi.org/10.1002/2014JD021927, 2014.
Maidment, R. I., Grimes, D., Black, E., Tarnavsky, E., Young, M., Greatrex,
H., Allan, R. P., Stein, T., Nkonde, E., Senkunda, S., and Alcántara, E.
M. U.: A new, long-term daily satellite-based rainfall dataset for
operational monitoring in Africa, Sci. Data, 4, 170063,
https://doi.org/10.1038/sdata.2017.63, 2017.
Malo, M., Jember, G., and Woodfine, A.: Strenghtening Capacity for Climate
Change Adaptation in the Agriculture Sector in Ethiopia, Proceedings from
National Workshop, Food and Agricultural Organization of the United Nations
and World Bank, Nazreth, Ethiopia, available at:
http://www.fao.org/docrep/014/i2155e/i2155e00.pdf (last access:
4 August 2015), 2012.
Maraun, D.: Bias Correction, Quantile Mapping, and Downscaling: Revisiting
the Inflation Issue, J. Climate, 26, 2137–2143,
https://doi.org/10.1175/JCLI-D-12-00821.1, 2013.
Moazami, S., Golian, S., Kavianpour, M. R., and Hong, Y.: Comparison of
PERSIANN and V7 TRMM Multi-satellite Precipitation Analysis (TMPA) products
with rain gauge data over Iran, Int. J. Remote Sens., 34, 8156–8171,
https://doi.org/10.1080/01431161.2013.833360, 2013.
Neitsch, S., Arnold, J., Kiniry, J., Williams, J., and King, K.: Soil and
Water Assement Tool Theoretical Documentation, available at:
https://swat.tamu.edu/media/1290/swat2000theory.pdf (last access:
23 May 2018), 2002.
Niang, I., Ruppel, O. C., Abdrabo, M. A., Essel, A., Lennard, C., Padgham,
J., and Urquhart, P.: Africa. In: Climate Change 2014: Impacts, Adaptation,
and Vulnerability. Part B: Regional Aspects, Contribution of Working Group II
to the Fifth Assessment Report of the Intergovernmental Panel on Climate
Change, edited by: Barros, V. R., Field, C. B., Dokken, D. J., Mastrandrea,
M. D., Mach, K. J., Bilir, T. E., Chatterjee, M., Ebi, K. L., Estrada, Y. O.,
Genova, R. C., Girma, B., Kissel, E. S., Levy, A. N., MacCracken, S.,
Mastrandrea, P. R., and White, L. L., Cambridge University Press, Cambridge,
United Kingdom and New York, NY, USA, 1199–1265, available at:
http://www.ipcc.ch/pdf/assessment-report/ar5/wg2/WGIIAR5-Chap22_
FINAL.pdf (last access: 4 January 2017), 2014.
Nikulin, G., Jones, C., Giorgi, F., Asrar, G., Buechner, M., Cerezo-Mota, R.,
Christensen, O. B., Deque, M., Fernandez, J., Haensler, A., van Meijgaard,
E., Samuelsson, P., Sylla, M. B., and Sushama, L.: Precipitation Climatology
in an Ensemble of CORDEX-Africa Regional Climate Simulations, J. Climate, 25,
6057–6078, https://doi.org/10.1175/JCLI-D-11-00375.1, 2012.
Novella, N. S., Thiaw, W. M., Novella, N. S., and Thiaw, W. M.: African
Rainfall Climatology Version 2 for Famine Early Warning Systems,
Httpdxdoiorg101175JAMC–11-02381, available at:
http://journals.ametsoc.org/doi/abs/10.1175/JAMC-D-11-0238.1 (last
access: 30 November 2016), 2013.
Pricope, N. G., Husak, G., Lopez-Carr, D., Funk, C., and Michaelsen, J.: The
climate-population nexus in the East African Horn: Emerging degradation
trends in rangeland and pastoral livelihood zones, Global Environ. Chang.,
23, 1525–1541, https://doi.org/10.1016/j.gloenvcha.2013.10.002, 2013.
Romilly, T. G. and Gebremichael, M.: Evaluation of satellite rainfall
estimates over Ethiopian river basins, Hydrol. Earth Syst. Sci., 15,
1505–1514, https://doi.org/10.5194/hess-15-1505-2011, 2011.
Saha, S., Moorthi, S., Pan, H.-L., Wu, X., Wang, J., Nadiga, S., Tripp, P.,
Kistler, R., Woollen, J., Behringer, D., Liu, H., Stokes, D., Grumbine, R.,
Gayno, G., Wang, J., Hou, Y.-T., Chuang, H., Juang, H.-M. H., Sela, J.,
Iredell, M., Treadon, R., Kleist, D., Van Delst, P., Keyser, D., Derber, J.,
Ek, M., Meng, J., Wei, H., Yang, R., Lord, S., van den Dool, H., Kumar, A.,
Wang, W., Long, C., Chelliah, M., Xue, Y., Huang, B., Schemm, J.-K.,
Ebisuzaki, W., Lin, R., Xie, P., Chen, M., Zhou, S., Higgins, W., Zou, C.-Z.,
Liu, Q., Chen, Y., Han, Y., Cucurull, L., Reynolds, R. W., Rutledge, G., and
Goldberg, M.: The NCEP Climate Forecast System Reanalysis, B. Am. Meteorol.
Soc., 91, 1015–1058, https://doi.org/10.1175/2010BAMS3001.1, 2010.
Samuelsson, P., Jones, C. G., WilléN, U., Ullerstig, A., Gollvik, S.,
Hansson, U., Jansson, C., KjellströM, E., Nikulin, G., and Wyser, K.: The
Rossby Centre Regional Climate model RCA3: model description and performance:
THE ROSSBY CENTRE REGIONAL CLIMATE MODEL RCA3, Tellus A, 63, 4–23,
https://doi.org/10.1111/j.1600-0870.2010.00478.x, 2011.
Sapiano, M. R. P. and Arkin, P. A.: An Intercomparison and Validation of
High-Resolution Satellite Precipitation Estimates with 3-Hourly Gauge Data,
J. Hydrometeorol., 10, 149–166, https://doi.org/10.1175/2008JHM1052.1, 2009.
Segele, Z. T., Leslie, L. M., and Lamb, P. J.: Evaluation and adaptation of a
regional climate model for the Horn of Africa: rainfall climatology and
interannual variability, Int. J. Climatol., 29, 47–65, https://doi.org/10.1002/joc.1681,
2009.
Sheffield, J., Goteti, G., Wood, E. F., Sheffield, J., Goteti, G., and Wood,
E. F.: Development of a 50-Year High-Resolution Global Dataset of
Meteorological Forcings for Land Surface Modeling,
https://doi.org/10.1175/JCLI3790.1, 2006.
Sheffield, J., Wood, E. F., Chaney, N., Guan, K., Sadri, S., Yuan, X., Olang,
L., Amani, A., Ali, A., Demuth, S., and Ogallo, L.: A Drought Monitoring and
Forecasting System for Sub-Sahara African Water Resources and Food Security,
B. Am. Meteorol. Soc., 95, 861–882, https://doi.org/10.1175/BAMS-D-12-00124.1, 2013.
Sheffield, J., Wood, E. F., Chaney, N., Guan, K., Sadri, S., Yuan, X., Olang,
L., Amani, A., Ali, A., Demuth, S., and Ogallo, L.: A Drought Monitoring and
Forecasting System for Sub-Sahara African Water Resources and Food Security,
B. Am. Meteorol. Soc., 95, 861–882, https://doi.org/10.1175/BAMS-D-12-00124.1, 2014.
Sun, L., Li, H., Zebiak, S. E., Moncunill, D. F., Filho, F. D. A. D. S., and
Moura, A. D.: An Operational Dynamical Downscaling Prediction System for
Nordeste Brazil and the 2002–04 Real-Time Forecast Evaluation, J. Climate,
19, 1990–2007, https://doi.org/10.1175/JCLI3715.1, 2006.
Sylla, M. B., Giorgi, F., Coppola, E., and Mariotti, L.: Uncertainties in
daily rainfall over Africa: assessment of gridded observation products and
evaluation of a regional climate model simulation, Int. J. Climatol., 33,
1805–1817, https://doi.org/10.1002/joc.3551, 2013.
Tarnavsky, E., Grimes, D., Maidment, R., Black, E., Allan, R. P., Stringer,
M., Chadwick, R., and Kayitakire, F.: Extension of the TAMSAT Satellite-Based
Rainfall Monitoring over Africa and from 1983 to Present, J. Appl. Meteorol.
Clim., 53, 2805–2822, https://doi.org/10.1175/JAMC-D-14-0016.1, 2014.
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res.-Atmos., 106, 7183–7192, https://doi.org/10.1029/2000JD900719,
2001.
Teng, J., Potter, N. J., Chiew, F. H. S., Zhang, L., Wang, B., Vaze, J., and
Evans, J. P.: How does bias correction of regional climate model
precipitation affect modelled runoff?, Hydrol. Earth Syst. Sci., 19,
711–728, https://doi.org/10.5194/hess-19-711-2015, 2015.
Terrestrial Hydrology Research Group Princeton University:
Observational-Reanalysis hybrid (ORH), available at:
http://hydrology.princeton.edu/data.php, last access: 12 May 2016.
Troy, T. J., Sheffield, J., and Wood, E. F.: Estimation of the Terrestrial
Water Budget over Northern Eurasia through the Use of Multiple Data Sources,
J. Climate, 24, 3272–3293, https://doi.org/10.1175/2011JCLI3936.1, 2011.
UNEP: The Democratic Republic of the Congo Post-Conflict Environmental
Assessment United Nations Environment Programme Synthesis for Policy Makers,
available at: http://postconflict.unep.ch/publications/UNEP_
DRC_PCEA_EN.pdf (last access: 30 November 2016), 2011.
Urama, K. and Ozor, N.: Impacts of climate change on water resources in
Africa?: the Role of Adaptation, African Technology Policy Studies Network
(ATPS), available at:
https://www.researchgate.net/publication/267218899_Impacts_of_climate_change_on_water_resources_in_Africa_the_role_of_adaptation
(last access: 5 August 2015), 2010.
Vernimmen, R. R. E., Hooijer, A., Mamenun, Aldrian, E., and van Dijk, A. I.
J. M.: Evaluation and bias correction of satellite rainfall data for drought
monitoring in Indonesia, Hydrol. Earth Syst. Sci., 16, 133–146,
https://doi.org/10.5194/hess-16-133-2012, 2012.
Wang, A., Lettenmaier, D. P., and Sheffield, J.: Soil Moisture Drought in
China, 1950–2006, J. Climate, 24, 3257–3271, https://doi.org/10.1175/2011JCLI3733.1,
2011.
Wang, J. and Wolff, D. B.: Evaluation of TRMM Ground-Validation Radar-Rain
Errors Using Rain Gauge Measurements, J. Appl. Meteorol. Clim., 49, 310–324,
https://doi.org/10.1175/2009JAMC2264.1, 2010.
Wilby, R. L. and Dawson, C. W.: sdsm – a decision support tool for the
assessment of regional climate change impacts, Environ. Modell. Softw., 17,
145–157, https://doi.org/10.1016/S1364-8152(01)00060-3, 2004.
Wilby, R. L. and Dawson, C. W.: SDSM 4.2 – A decision support tool for the
assessment of regional climate change impacts, United Kingdom, available at:
https://sdsm.org.uk/SDSMManual.pdf (last access: 11 January 2017),
2007.
Wilby, R. L. and Yu, D.: Rainfall and temperature estimation for a data
sparse region, Hydrol. Earth Syst. Sci., 17, 3937–3955,
https://doi.org/10.5194/hess-17-3937-2013, 2013.
Willmott, C. J.: On the Validation of Models, Phys. Geogr., 2, 184–194,
1981.
World Bank: Doing business in The East African Community, IFC/World Bank
Rep., 116 pp., available at:
http://www.tzdpg.or.tz/fileadmin/_migrated/content_uploads/DB12-EAC_01.pdf
(last access: 30 November 2016), 2012.
Xie, P. and Arkin, P. A.: Global Precipitation: A 17-Year Monthly Analysis
Based on Gauge Observations, Satellite Estimates, and Numerical Model
Outputs, B. Am. Meteorol. Soc., 78, 2539–2558,
https://doi.org/10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2, 1997.
Zambrano-Bigiarini, M., Nauditt, A., Birkel, C., Verbist, K., and Ribbe, L.:
Temporal and spatial evaluation of satellite-based rainfall estimates across
the complex topographical and climatic gradients of Chile, Hydrol. Earth
Syst. Sci., 21, 1295–1320, https://doi.org/10.5194/hess-21-1295-2017, 2017.
Short summary
In Africa field-based meteorological data are scarce; therefore global data sources based on remote sensing and climate models are often used as alternatives. To assess their suitability for a large and topographically complex area in East Africa, we evaluated multiple climate data products with available ground station data at multiple timescales over 21 regions. The comprehensive evaluation resulted in identification of preferential data sources to be used for climate and hydrological studies.
In Africa field-based meteorological data are scarce; therefore global data sources based on...