Abstract
The availability of satellite and reanalysis climate datasets and their applicability have been greatly promoted in hydro-climatic studies. However, such climatic products are still subject to considerable uncertainties and an evaluation of the products is necessary for applications in specific regions. This study aims to evaluate the reliability of nine gridded precipitation and temperature datasets against ground-based observations in the upper Tekeze River basin (UTB) of Ethiopia from 1982 to 2016. Precipitation, maximum temperature (Tmax), minimum temperature (Tmin), and mean temperature (Tmean) were evaluated at daily and monthly timescales. The results show that the best estimates of precipitation are from the EartH2Observe, WFDEI, and ERA-Interim reanalysis data Merged and Bias-corrected for the Inter-Sectoral Impact Model Intercomparison Project (EWEMBI), and the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) datasets. The percentage biases and correlation coefficients (CCs) are within ± 15% and > 0.5, respectively, for both EWEMBI and CHIRPS at the two timescales. All products underestimate the drought conditions indicated by the standardized precipitation index (SPI), while the EWEMBI and CHIRPS datasets show higher agreement with the observations than other datasets. The Tmean estimates produced by the ECMWF Re-Analysis version 5 (ERA5) and the Climate Hazards Group InfraRed Temperature with Station data (CHIRTS) are the closest to the observations, with CCs of 0.65 and 0.55, respectively, at the daily timescale. The CHIRTS and EWEMBI datasets show better representations of Tmax (Tmin), with CCs of 0.69 (0.72) and 0.62 (0.68), respectively, at the monthly timescale. The temperature extremes are better captured by the ERA5 (Tmean), CHIRTS (Tmax), and EWEMBI (Tmin) datasets. The findings of this study provide useful information to select the most appropriate dataset for hydrometeorological studies in the UTB and could help to improve the regional representation of global datasets.
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References
Abrha, A. Z., 2009: Assessment of spatial and temporal variability of river discharge, sediment yield and sediment-fixed nutrient export in Geba River catchment, northern Ethiopia. Ph.D. dissertation, Katholieke Universiteit Leuven, Belgium, 203 pp.
Agutu, N. O., J. L. Awange, A. Zerihun, et al., 2017: Assessing multi-satellite remote sensing, reanalysis, and land surface models’ products in characterizing agricultural drought in East Africa. Remote Sens. Environ., 194, 287–302, doi: https://doi.org/10.1016/j.rse.2017.03.041.
Aslami, F., A. Ghorbani, B. Sobhani, et al., 2019: Comprehensive comparison of daily IMERG and GSMaP satellite precipitation products in Ardabil Province, Iran. Int. J. Remote Sens., 40, 3139–3153, doi: https://doi.org/10.1080/01431161.2018.1539274.
Awange, J. L., K. X. Hu, and M. Khaki, 2019: The newly merged satellite remotely sensed, gauge and reanalysis-based Multi-Source Weighted-Ensemble Precipitation: Evaluation over Australia and Africa (1981–2016). Sci. Total Environ., 670, 448–465, doi: https://doi.org/10.1016/j.scitotenv.2019.03.148.
Ayoub, A. B., F. Tangang, L. Juneng, et al., 2020: Evaluation of gridded precipitation datasets in Malaysia. Remote Sens., 12, 613, doi: https://doi.org/10.3390/rs12040613.
Azimi, S., A. B. Dariane, S. Modanesi, et al., 2020: Assimilation of Sentinel 1 and SMAP-based satellite soil moisture retrievals into SWAT hydrological model: the impact of satellite revisit time and product spatial resolution on flood simulations in small basins. J. Hydrol., 581, 124367, doi: https://doi.org/10.1016/j.jhydrol.2019.124367.
Balsamo, G., C. Albergel, A. Beljaars, et al., 2015: ERA-Interim/Land: a global land surface reanalysis data set. Hydrol. Earth Syst. Sci., 19, 389–407, doi: https://doi.org/10.5194/hess-19-389-2015.
Bayissa, Y., T. Tadesse, G. Demisse, et al., 2017: Evaluation of satellite-based rainfall estimates and application to monitor meteorological drought for the Upper Blue Nile Basin, Ethiopia. Remote Sens., 9, 669, doi: https://doi.org/10.3390/rs9070669.
Boke, A. S., 2017: Comparative evaluation of spatial interpolation methods for estimation of missing meteorological variables over Ethiopia. J. Water Resour. Prot., 9, 945–959, doi: https://doi.org/10.4236/jwarp.2017.98063.
Climate Change Service (C3S), 2019: ERA5-Land reanalysis. Copernicus Climate Change Service. Available online at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels-monthly-means?tab=overview. Accessed on 20 March 2021.
Chai, T., and R. R. Draxler, 2014: Root mean square error (RMSE) or mean absolute error (MAE)? Arguments against avoiding RMSE in the literature. Geosci. Model Dev., 7, 1247–1250, doi: https://doi.org/10.5194/gmd-7-1247-2014.
Chen, M. Y., W. Shi, P. P. Xie, et al., 2008: Assessing objective techniques for gauge-based analyses of global daily precipitation. J. Geophys. Res. Atmos., 113, D04110, doi: https://doi.org/10.1029/2007JD009132.
Costa, R. L., G. M. de Mello Baptista, H. B. Gomes, et al., 2020: Analysis of climate extremes indices over northeast Brazil from 1961 to 2014. Wea. Climate Extremes, 28, 100,254, doi: https://doi.org/10.1016/j.wace.2020.100254.
Degefu, M. A., and W. Bewket., 2015: Trends and spatial patterns of drought incidence in the Omo-Ghibe River basin, Ethiopia. Geogr. Ann. Ser. A Phys. Geogr., 97, 395–414, doi: https://doi.org/10.1111/geoa.12080.
Dembélé, M., and S. J. Zwart, 2016: Evaluation and comparison of satellite-based rainfall products in Burkina Faso, West Africa. Int. J. Remote Sens., 37, 3995–4014, doi: https://doi.org/10.1080/01431161.2016.1207258.
Dinku, T., P. Ceccato, E. Grover-Kopec, et al., 2007: Validation of satellite rainfall products over East Africa’s complex topography. Int. J. Remote Sens., 28, 1503–1526, doi: https://doi.org/10.1080/01431160600954688.
Fang, J., W. T. Yang, Y. B. Luan, et al., 2019: Evaluation of the TRMM 3B42 and GPM IMERG products for extreme precipitation analysis over China. Atmos. Res., 223, 24–38, doi: https://doi.org/10.1016/j.atmosres.2019.03.001.
Fentaw, F., D. Hailu, A. Nigussie, et al., 2018: Climate change impact on the hydrology of Tekeze Basin, Ethiopia: Projection of rainfall-runoff for future water resources planning. Water Conserv. Sci. Eng., 3, 267–278, doi: https://doi.org/10.1007/s41101-018-0057-3.
Funk, C., P. Peterson, M. Landsfeld, et al., 2015: The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Sci. Data, 2, 150,066, doi: https://doi.org/10.1038/sdata.2015.66.
Funk, C., P. Peterson, S. Peterson, et al., 2019: A high-resolution 1983–2016 Tmax climate data record based on infrared temperatures and stations by the climate hazard center. J. Climate, 32, 5639–5658, doi: https://doi.org/10.1175/JCLI-D-18-0698.1.
Gebremicael, T. G., Y. A. Mohamed, P. van der Zaag, et al., 2019: Evaluation of multiple satellite rainfall products over the rugged topography of the Tekeze-Atbara basin in Ethiopia. Int. J. Remote Sens., 40, 4326–4345, doi: https://doi.org/10.1080/01431161.2018.1562585.
Gebremicael, T. G., Y. A. Mohamed, P. van der Zaag, et al., 2020: Change in low flows due to catchment management dynamics—Application of acomparative modelling approach. Hydrol. Process., 34, 2101–2116, doi: https://doi.org/10.1002/hyp.13715.
Gyasi-Agyei, Y., 2020: Identification of the optimum rain gauge network density for hydrological modelling based on radar rainfall analysis. Water, 12, 1906, doi: https://doi.org/10.3390/w12071906.
Haile, G. G., Q. H. Tang, G. Y. Leng, et al., 2020: Long-term spatiotemporal variation of drought patterns over the Greater Horn of Africa. Sci. Total Environ., 704, 135299, doi: https://doi.org/10.1016/j.scitotenv.2019.135299.
Harris, I., P. D. Jones, T. J. Osborn, et al., 2014: Updated high-resolution grids of monthly climatic observations—the CRU TS3.10 Dataset. Int. J. Climatol., 34, 623–642, doi: https://doi.org/10.1002/joc.3711.
Harris, I., T. J. Osborn, P. Jones, et al., 2020: Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Sci. Data, 7, 109, doi: https://doi.org/10.1038/s41597-020-0453-3.
Harrison, L., C. Funk, and P. Peterson, 2019: Identifying changing precipitation extremes in Sub-Saharan Africa with gauge and satellite products. Environ. Res. Lett., 14, 085007, doi: https://doi.org/10.1088/1748-9326/ab2cae.
Hu, S., H. J. Qiu, D. D. Yang, et al., 2017: Evaluation of the applicability of climate forecast system reanalysis weather data for hydrologic simulation: A case study in the Bahe River Basin of the Qinling Mountains, China. J. Geogr. Sci., 27, 546–564, doi: https://doi.org/10.1007/s11442-017-1392-6.
Islam, A., and N. Cartwright, 2020: Evaluation of climate reanalysis and space-borne precipitation products over Bangladesh. Hydrol. Sci. J., 65, 1112–1128, doi: https://doi.org/10.1080/02626667.2020.1730845.
Kanamitsu, M., W. Ebisuzaki, J. Woollen, et al., 2002: NCEP-DOE AMIP-II reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 1631–1644, doi: https://doi.org/10.1175/BAMS-83-11-1631.
Lakew, H. B., S. A. Moges, and D. H. Asfaw, 2017: Hydrological evaluation of satellite and reanalysis precipitation products in the Upper Blue Nile Basin: A case study of Gilgel Abbay. Hydrology, 4, 39, doi: https://doi.org/10.3390/hydrology4030039.
Lange, S., 2016: EartH2Observe, WFDEI and ERA-Interim data Merged and Bias-corrected for ISIMIP (EWEMBI). GFZ Data Services. Available online at https://dataservices.gfz-potsdam.de/pik/showshort.php?id=escidoc:1809891. Accessed on 20 March 2021.
Lange, S., 2018: Bias correction of surface downwelling longwave and shortwave radiation for the EWEMBI dataset. Earth Syst. Dyn., 9, 627–645, doi: https://doi.org/10.5194/esd-9-627-2018.
Lange, S., 2019. EartH2Observe, WFDEI and ERA-Interim data Merged and Bias-corrected for ISIMIP (EWEMBI). V. 1.1. GFZ Data Services. Available online at https://doi.org/10.5880/pik.2019.004, doi: https://doi.org/10.5880/pik.2019.004. Accessed on 20 March 2021.
Le Coz, C., and N. van de Giesen, 2020: Comparison of rainfall products over sub-Saharan Africa. J. Hydrometeor., 21, 553–596, doi: https://doi.org/10.1175/JHM-D-18-0256.1.
Lemma, E., S. Upadhyaya, and R. Ramsankaran, 2019: Investigating the performance of satellite and reanalysis rainfall products at monthly timescales across different rainfall regimes of Ethiopia. Int. J. Remote Sens., 40, 4019–1042, doi: https://doi.org/10.1080/01431161.2018.1558373.
Li, C. X., T. B. Zhao, C. X. Shi, et al., 2020: Evaluation of daily precipitation product in China from the CMA global atmospheric interim reanalysis. J. Meteor. Res., 34, 117–136, doi: https://doi.org/10.1007/s13351-020-8196-9.
Li, D., G. Christakos, X. X. Ding, et al., 2018: Adequacy of TRMM satellite rainfall data in driving the SWAT modeling of Tiaoxi catchment (Taihu Lake basin, China). J. Hydrol., 556, 1139–1152, doi: https://doi.org/10.1016/j.jhydrol.2017.01.006.
Liu, X. C., Z. X. Xu, and R. H. Yu, 2012: Spatiotemporal variability of drought and the potential climatological driving factors in the Liao River basin. Hydrol. Process., 26, 1–14, doi: https://doi.org/10.1002/hyp.8104.
Liu, X. C., Q. H. Tang, H. J. Cui, et al., 2017: Multimodel uncertainty changes in simulated river flows induced by human impact parameterizations. Environ. Res. Lett., 12, 025009, doi: https://doi.org/10.1088/1748-9326/aa5a3a.
Lockhoff, M., O. Zolina, C. Simmer, et al., 2019: Representation of precipitation characteristics and extremes in regional reanalyses and satellite- and gauge-based estimates over western and central Europe. J. Hydrometeor., 20, 1123–1145, doi: https://doi.org/10.1175/JHM-D-18-0200.1.
Mahmood, R., S. F. Jia, T. Mahmood, et al., 2020: Predicted and projected water resources changes in the Chari Catchment, the Lake Chad basin, Africa. J. Hydrometeor., 21, 73–91, doi: https://doi.org/10.1175/JHM-D-19-0105.1.
Maidment, R. I., D. I. F. Grimes, R. P. Allan, et al., 2013: Evaluation of satellite-based and model re-analysis rainfall estimates for Uganda. Meteorol. Appl., 20, 308–317, doi: https://doi.org/10.1002/met.1283.
Marques, C. A. F., A. Rocha, J. Corte-Real, et al., 2009: Global atmospheric energetics from NCEP-Reanalysis 2 and ECMWF-ERA40 Reanalysis. Int. J. Climatol., 29, 159–174, doi: https://doi.org/10.1002/joc.1704.
McKee, T. B., N. J. Doesken, and J. Kleist, 1995: Drought Monitoring with Multiple Time Scales. Proc. 9th Conference on Applied Climatology, American Meteorological Society, Dallas, TX, 233–236
Ministry of Water Resources (MoWR), 1998: Tekeze river basin integrated development master plan project. Sectoral Report. Vol. VII, Addis Ababa, Ethiopia. Available online at https://entrospace.nilebasin.org/handle/20.500.12351/383?show=full. Accessed on 20 March 2021.
Muller, J. C.-Y., 2014: Adapting to climate change and addressing drought-learning from the Red Cross Red Crescent experiences in the Horn of Africa. Wea. Clim. Extremes, 3, 31–36, doi: https://doi.org/10.1016/j.wace.2014.03.009.
Nechita, C., K. Čufar, I. Macovei, et al., 2019: Testing three climate datasets for dendroclimatological studies of oaks in the South Carpathians. Sci. Total Environ., 694, 133, 730, doi: https://doi.org/10.1016/j.scitotenv.2019.133730.
Nicholson, S. E., 2017: Climate and climatic variability of rainfall over eastern Africa. Rev. Geophys., 55, 590–635, doi: https://doi.org/10.1002/2016RG000544.
Peng, J., S. Dadson, F. Hirpa, et al., 2020: A pan-African high-resolution drought index dataset. Earth Syst. Sci. Data, 12, 753–769, doi: https://doi.org/10.5194/essd-12-753-2020.
Roy, A., P. K. Thakur, N. Pokhriyal, et al., 2018: Intercomparison of different rainfall products and validation of WRF modelled rainfall estimation in N-W Himalya during monsoon period. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-5, 351–358, doi: https://doi.org/10.5144/isprs-nnaals-IV-5-351-2018.
Saccenti, E., M. H. W. B. Hendriks, and A. K. Smilde, 2020: Corruption of the Pearson correlation coefficient by measurement error and its estimation, bias, and correction under different error models. Sci. Rep., 10, 438, doi: https://doi.org/10.1038/s41598-019-57247-4.
Sahlu, D., S. A. Moges,, E. I. Nikolopoulos, et al., 2017: Evaluation of high-resolution multisatellite and reanalysis rainfall products over East Africa. Adv. Meteor., 2017, 4957960, doi: https://doi.org/10.1155/2017/4957960.
Satgé, F., D. Defrance, B. Sultan, et al., 2020: Evaluation of 23 gridded precipitation datasets across West Africa. J. Hydrol., 581, 124412, doi: https://doi.org/10.1016/j.jhydrol.2019.124412.
Schamm, K., M. Ziese, A. Becker, et al., 2014: Global gridded precipitation over land: a description of the new GPCC First Guess Daily product. Earth Syst. Sci. Data, 6, 49–60, doi: https://doi.org/10.5194/essd-6-49-2014.
Tan, M. L., P. W. Gassman, and A. P. Cracknell, 2017: Assessment of three long-term gridded climate products for hydroclimatic simulations in tropical river basins. Water, 9, 229, doi: https://doi.org/10.3390/w9030229.
Tan, X. H., B. Yong, and L. L. Ren, 2018: Error features of the hourly GSMaP multi-satellite precipitation estimates over nine major basins of China. Hydrol. Res., 49, 761–779, doi: https://doi.org/10.2166/nh.2017.263.
Tefera, A. S., J. O. Ayoade, and N. J. Bello, 2019: Comparative analyses of SPI and SPEI as drought assessment tools in Tigray Region, Northern Ethiopia. SN Appl. Sci., 1, 1265, doi: https://doi.org/10.1007/s42452-019-1326-2.
Toté, C., D. Patricio, H. Boogaard, et al., 2015: Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique. Remote Sens., 7, 1758–1776, doi: https://doi.org/10.3390/rs70201758.
Wang, N., W. B. Liu, F. B. Sun, et al., 2020: Evaluating satellite-based and reanalysis precipitation datasets with gauge-observed data and hydrological modeling in the Xihe River basin, China. Atmos. Res., 234, 104, 746, doi: https://doi.org/10.1016/j.atmosres.2019.104746.
Weedon, G. P., G. Balsamo, N. Bellouin, et al., 2014: The WFDEI meteorological forcing data set: WATCH Forcing Data methodology applied to ERA-Interim reanalysis data. Water Resour. Res., 50, 7505–7514, doi: https://doi.org/10.1002/2014WR015638.
Weedon, G. P., G. Balsamo, N. Bellouin, et al., 2018: The WFDEI meteorological forcing data. Research data archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. Available online at doi: https://doi.org/10.5065/486N-8109. Accessed on 20 March 2021
Worqlul, A. W., B. Maathuis, A. A. Adem, et al., 2014: Comparison of rainfall estimations by TRMM 3B42, MPEG and CFSR with ground-observed data for the Lake Tana basin in Ethiopia. Hydrol. Earth Syst. Sci., 18, 4871–4881, doi: https://doi.org/10.5194/hess-18-4871-2014.
Zeng, Q., H. Chen, C. Y. Xu, et al., 2018: The effect of rain gauge density and distribution on runoff simulation using a lumped hydrological modelling approach. J. Hydrol., 563, 106–122, doi: https://doi.org/10.1016/j.jhydrol.2018.05.058.
Zhang, Y. S., and N. Ma, 2018: Spatiotemporal variability of snow cover and snow water equivalent in the last three decades over Eurasia. J. Hydrol., 559, 238–251, doi: https://doi.org/10.1016/j.jhydrol.2018.02.031.
Zhao, H. G., S. T. Yang, Z. W. Wang, et al., 2015: Evaluating the suitability of TRMM satellite rainfall data for hydrological simulation using a distributed hydrological model in the Weihe River catchment in China. J. Geogr. Sci., 25, 177–195, doi: https://doi.org/10.1007/s11442-015-1161-3.
Zhao, T. B., and C. B. Fu, 2006: Comparison of products from ERA-40, NCEP-2, and CRU with station data for summer precipitation over China. Adv. Atmos. Sci., 23, 593–604, doi: https://doi.org/10.1007/s00376-006-0593-1.
Zhao, T. B., W. D. Guo, and C. B. Fu, 2008: Calibrating and evaluating reanalysis surface temperature error by topographic correction. J. Climate, 21, 1440–1446, doi: https://doi.org/10.11175/2007JCLI1463.1.
Ziese, M., A. Rauthe-Schöch, A. Becker, et al., 2018: GPCC Full Data Daily Version.2018 at 1.0°: Daily Land-Surface Precipitation from Rain-Gauges builton GTS-based and Historic Data. Available online at https://opendata.dwd.de/climate_environment/GPCC/html/fulldata-daily_v2018_doi_download.html, doi: https://doi.org/10.5676/DWD_GPCC/FD_D_V2018_100. Accessed on 20 March 2021.
Acknowledgments
The first author was sponsored by the Chinese Academy of Sciences (CAS)—The World Academy of Sciences (TWAS) President’s Fellowship Programme for his PhD study at the University of Chinese Academy of Sciences. The authors appreciate the Ethiopian National Meteorological Agency for providing the weather data.
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Supported by the National Natural Science Foundation of China (41790424, 41730645, and 41877164), Strategic Priority Research Program of the Chinese Academy of Sciences (XDA20060402), and International Partnership Program of the Chinese Academy of Sciences (131A11KYSB20170113).
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Reda, K.W., Liu, X., Tang, Q. et al. Evaluation of Global Gridded Precipitation and Temperature Datasets against Gauged Observations over the Upper Tekeze River Basin, Ethiopia. J Meteorol Res 35, 673–689 (2021). https://doi.org/10.1007/s13351-021-0199-7
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DOI: https://doi.org/10.1007/s13351-021-0199-7