{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T20:20:58Z","timestamp":1783110058335,"version":"3.54.6"},"reference-count":38,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T00:00:00Z","timestamp":1530748800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"'NUFFIC","award":["CF9417"],"award-info":[{"award-number":["CF9417"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Advances in remote sensing have led to the use of satellite-derived rainfall products to complement the sparse rain gauge data. Although these products are globally and some regional bias corrected, they often show substantial differences relative to ground measurements attributed to local and external factors that require systematic consideration. A decreasing rain gauge network inhibits the continuous validation of these products. Our proposal to deal with this problem was to use a Bayesian approach to merge the existing historical rain gauge information to create consistent satellite rainfall data for long-term applications. Monthly bias correction was applied to Climate Hazards Group Infrared Precipitation with Stations (CHIRPS v2) using a corresponding gridded (0.05\u00b0) rain gauge data over East Africa for 33 years (1981\u20132013). The first 22 years were utilized to derive error fields which were then applied to independent CHIRPS data for 11 years for validation. Assessments of the approach\u2019s influence on the rainfall estimates spatially and temporally were explored. Results showed a significant spatial reduction of the underestimation and overestimation of systematic errors at both monthly and yearly scales. The reduced errors increased with increased rainfall amounts, hence was less so in the relatively drier months. The overall monthly reduction of Root Mean Square Difference (RMSD) was between 4% and 60%, and the Mean Absolute Error (MAE) was between 1% and 63%, while the correlations improved by up to 21%. Yearly, the RMSD was reduced between 17% and 49%, and the MAE between 13% and 48%, while the increase in correlations was between 9% and 17%. Decreased yearly bias correction corresponded with years of high rainfall associated with El Ni\u00f1o. Results for the assessments of the effectiveness of the Bayesian approach showed that it was more effective in reducing systematic errors related to rainfall magnitudes, but its performance decreased in areas of sparse rain gauge network that insufficiently represented rainfall variabilities. This affected areas of deep convection, leading to minimal overestimation reductions associated with the cirrus effect. Conversely, significant corrections were during years of low rainfall from shallow convections. The approach is suitable for long-term applications where consistencies of mean errors can be assumed.<\/jats:p>","DOI":"10.3390\/rs10071074","type":"journal-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T10:52:44Z","timestamp":1530787964000},"page":"1074","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Bayesian Bias Correction of Satellite Rainfall Estimates for Climate Studies"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3428-3523","authenticated-orcid":false,"given":"Margaret Wambui","family":"Kimani","sequence":"first","affiliation":[{"name":"Faculty of Geo-Information Science and Earth Observation, University of Twente, 217 7500 AE Enschede, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joost C. B.","family":"Hoedjes","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information Science and Earth Observation, University of Twente, 217 7500 AE Enschede, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhongbo","family":"Su","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information Science and Earth Observation, University of Twente, 217 7500 AE Enschede, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,7,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1175\/JHM-D-11-042.1","article-title":"Intercomparison of high-resolution precipitation products over northwest Europe","volume":"13","author":"Kidd","year":"2012","journal-title":"J. Hydrometeorol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1016\/j.advwatres.2008.04.007","article-title":"Empirically-based modeling of spatial sampling uncertainties associated with rainfall measurements by rain gauges","volume":"31","author":"Villarini","year":"2008","journal-title":"Adv. Water Resour."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3123","DOI":"10.1002\/hyp.6534","article-title":"Validation of hydrological models for climate scenario simulation: The case of Saguenay watershed in Quebec","volume":"21","author":"Dibike","year":"2007","journal-title":"Hydrol. Process."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2035","DOI":"10.1175\/1520-0477(2000)081<2035:EOPSSE>2.3.CO;2","article-title":"Evaluation of persiann system satellite-based estimates of tropical rainfall","volume":"81","author":"Sorooshian","year":"2000","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"5393","DOI":"10.1080\/01431160500273551","article-title":"Application of three satellite techniques in support of precipitation forecasts of a NWP model","volume":"26","author":"Feidas","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.1175\/1520-0450(2000)039<1071:IVOTGP>2.0.CO;2","article-title":"Initial validation of the global precipitation climatology project monthly rainfall over the United States","volume":"39","author":"Krajewski","year":"2000","journal-title":"J. Appl. Meteorol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1175\/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2","article-title":"The version 2 global precipitation climatology project (GPCP) monthly precipitation analysis","volume":"4","author":"Adler","year":"2003","journal-title":"J. Hydrometeorol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1175\/1520-0477(1994)075<0401:TGPCPF>2.0.CO;2","article-title":"The global precipitation climatology project\u20141st algorithm intercomparison project","volume":"75","author":"Arkin","year":"1994","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1002\/met.1283","article-title":"Evaluation of satellite-based and model re-analysis rainfall estimates for Uganda","volume":"20","author":"Maidment","year":"2013","journal-title":"Meteorol. Appl."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1758","DOI":"10.3390\/rs70201758","article-title":"Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique","volume":"7","author":"Tote","year":"2015","journal-title":"Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"AghaKouchak, A., Mehran, A., Norouzi, H., and Behrangi, A. (2012). Systematic and random error components in satellite precipitation data sets. Geophys. Res. Lett., 39.","DOI":"10.1029\/2012GL051592"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1016\/j.atmosres.2016.04.017","article-title":"Comparative evaluation of different satellite rainfall estimation products and bias correction in the Upper Blue Nile (UBN) basin","volume":"178","author":"Abera","year":"2016","journal-title":"Atmos. Res."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Kimani, M.W., Hoedjes, J.C.B., and Su, Z.B. (2017). An assessment of satellite-derived rainfall products relative to ground observations over East Africa. Remote Sens., 9.","DOI":"10.3390\/rs9050430"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"915","DOI":"10.5194\/hess-18-915-2014","article-title":"Bias correction can modify climate model simulated precipitation changes without adverse effect on the ensemble mean","volume":"18","author":"Maurer","year":"2014","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1080\/15481603.2016.1228161","article-title":"Assessment of two techniques to merge ground-based and trmm rainfall measurements: A case study about Brazilian Amazon rainforest","volume":"53","author":"Mateus","year":"2016","journal-title":"GISci. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1175\/2008JHM1048.1","article-title":"Statistical evaluation of combined daily gauge observations and rainfall satellite estimates over continental South America","volume":"10","author":"Vila","year":"2009","journal-title":"J. Hydrometeorol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.1175\/2010JHM1246.1","article-title":"Real-time bias reduction for satellite-based precipitation estimates","volume":"11","author":"Tian","year":"2010","journal-title":"J. Hydrometeorol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1199","DOI":"10.1126\/science.285.5431.1199","article-title":"Hydrology\u2014Scarcity of rain, stream gages threatens forecasts","volume":"285","author":"Stokstad","year":"1999","journal-title":"Science"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1503","DOI":"10.1080\/01431160600954688","article-title":"Validation of satellite rainfall products over East Africa\u2019s complex topography","volume":"28","author":"Dinku","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"191","DOI":"10.2151\/jmsj1965.75.1B_191","article-title":"Assimilation of observations, an introduction (gtspecial issueltdata assimilation in meteology and oceanography: Theory and practice)","volume":"75","author":"Talagrand","year":"1997","journal-title":"J. Meteorol. Soc. Jpn. Ser. II"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"95","DOI":"10.5194\/asr-6-95-2011","article-title":"National climate observing system of switzerland (GCOS Switzerland)","volume":"6","author":"Seiz","year":"2011","journal-title":"Adv. Sci. Res."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros, D.H., Verdin, J.P., Rowland, J.D., Romero, B.E., Husak, G.J., Michaelsen, J.C., and Verdin, A.P. (2014). A Quasi-Global Precipitation Time Series for Drought Monitoring, U.S. Geological Survey Data Series.","DOI":"10.3133\/ds832"},{"key":"ref_23","unstructured":"(2015, November 06). IGAD. Available online: http:\/\/www.Icpac.Net\/."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"150050","DOI":"10.1038\/sdata.2015.50","article-title":"The centennial trends greater horn of Africa precipitation dataset","volume":"2","author":"Funk","year":"2015","journal-title":"Sci. Data"},{"key":"ref_25","unstructured":"(2015, November 06). ICPAC. Available online: http:\/\/chg-wiki.geog.ucsb.edu\/wiki\/GeoCLIM."},{"key":"ref_26","unstructured":"(2018, July 05). SRTM 90m Digital Elevation Database v4.1. Available online: http:\/\/www.Cgiar-csi.Org\/data\/srtm-90m-digital-elevation-database-v4-1."},{"key":"ref_27","unstructured":"Carlin, B.P., and Louis, T.A. (1996). Bayes and Empirical Bayes Methods for Data Analysis, Chapman and Hall."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"023005","DOI":"10.1117\/1.2912053","article-title":"Nearest-neighbor and bilinear resampling factor estimation to detect blockiness or blurriness of an image","volume":"17","author":"Suwendi","year":"2008","journal-title":"J. Electron. Imaging"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/j.apgeog.2015.07.014","article-title":"Impacts of DEM resolution, source, and resampling technique on SWAT-simulated streamflow","volume":"63","author":"Tan","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"7183","DOI":"10.1029\/2000JD900719","article-title":"Summarizing multiple aspects of model performance in a single diagram","volume":"106","author":"Taylor","year":"2001","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2598","DOI":"10.1002\/joc.4515","article-title":"The turkana low-level jet: Mean climatology and association with regional aridity","volume":"36","author":"Nicholson","year":"2016","journal-title":"Int. J. Climatol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1722","DOI":"10.1175\/1520-0493(1982)110<1722:ANFJIN>2.0.CO;2","article-title":"A newly found jet in North Kenya (Turkana Channel)","volume":"110","author":"Kinuthia","year":"1982","journal-title":"Mon. Weather Rev."},{"key":"ref_33","first-page":"323","article-title":"Intercomparison of improved satellite rainfall estimation with chirps gridded product and rain gauge data over Venezuela","volume":"29","author":"Trejo","year":"2016","journal-title":"Atmosfera"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Sassen, K., Wang, Z., and Liu, D. (2009). Cirrus clouds and deep convection in the tropics: Insights from CALIPSO and CloudSat. J. Geophys. Res. Atmos., 114.","DOI":"10.1029\/2009JD011916"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1248","DOI":"10.1175\/1520-0450(1992)031<1248:HAVSOT>2.0.CO;2","article-title":"Horizontal and vertical structure of the lake Turkana jet","volume":"31","author":"Kinuthia","year":"1992","journal-title":"J. Appl. Meteorol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1002\/(SICI)1097-0088(200001)20:1<19::AID-JOC449>3.0.CO;2-0","article-title":"Enso signals in East African rainfall seasons","volume":"20","author":"Indeje","year":"2000","journal-title":"Int. J. Climatol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2347","DOI":"10.1175\/JHM-D-13-0111.1","article-title":"Investigation of discrepancies in satellite rainfall estimates over Ethiopia","volume":"15","author":"Young","year":"2014","journal-title":"J. Hydrometeorol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.jaridenv.2016.12.009","article-title":"Validating chirps-based satellite precipitation estimates in northeast Brazil","volume":"139","author":"Barbosa","year":"2017","journal-title":"J. Arid Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/7\/1074\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:11:27Z","timestamp":1760195487000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/7\/1074"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,5]]},"references-count":38,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2018,7]]}},"alternative-id":["rs10071074"],"URL":"https:\/\/doi.org\/10.3390\/rs10071074","relation":{"has-preprint":[{"id-type":"doi","id":"10.20944\/preprints201804.0225.v1","asserted-by":"object"}]},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,7,5]]}}}