{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T04:18:55Z","timestamp":1776745135051,"version":"3.51.2"},"reference-count":38,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2015,2,5]],"date-time":"2015-02-05T00:00:00Z","timestamp":1423094400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001\u20132012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.<\/jats:p>","DOI":"10.3390\/rs70201758","type":"journal-article","created":{"date-parts":[[2015,2,5]],"date-time":"2015-02-05T10:54:42Z","timestamp":1423133682000},"page":"1758-1776","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":338,"title":["Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique"],"prefix":"10.3390","volume":"7","author":[{"given":"Carolien","family":"Tot\u00e9","sequence":"first","affiliation":[{"name":"Flemish Institute for Technological Research (VITO), Remote Sensing Unit, Boeretang 200,  2400 Mol, Belgium"}]},{"given":"Domingos","family":"Patricio","sequence":"additional","affiliation":[{"name":"Instituto Nacional de Meteorologia (INAM), Rua de Mukumbura 164, C.P. 256, Maputo, Mozambique"}]},{"given":"Hendrik","family":"Boogaard","sequence":"additional","affiliation":[{"name":"Alterra, Wageningen University, PO Box 47, 3708PB Wageningen, The Netherlands"}]},{"given":"Raymond","family":"Van der Wijngaart","sequence":"additional","affiliation":[{"name":"Alterra, Wageningen University, PO Box 47, 3708PB Wageningen, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3403-0411","authenticated-orcid":false,"given":"Elena","family":"Tarnavsky","sequence":"additional","affiliation":[{"name":"Department of Meteorology, University of Reading, Earley Gate, PO Box 243, Reading RG6 6BB, UK"}]},{"given":"Chris","family":"Funk","sequence":"additional","affiliation":[{"name":"United States Geological Survey\/Earth Resources Observation and Science (EROS) Center and the Climate Hazard Group, Geography Department, University of California Santa Barbara,  Santa Barbara, CA 93106, USA"}]}],"member":"1968","published-online":{"date-parts":[[2015,2,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1355","DOI":"10.1175\/BAMS-87-10-1355","article-title":"African climate change: Taking the shorter route","volume":"87","author":"Washington","year":"2006","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_2","first-page":"10619","article-title":"The 30-year TAMSAT African Rainfall Climatology and Time-series (TARCAT) dataset","volume":"199","author":"Maidment","year":"2014","journal-title":"J. Geophys. Res.: Atmos."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2805","DOI":"10.1175\/JAMC-D-14-0016.1","article-title":"Extension of the TAMSAT satellite-based rainfall monitoring over Africa and from 1983 to present","volume":"53","author":"Tarnavsky","year":"2014","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1041","DOI":"10.1002\/joc.635","article-title":"Satellite rainfall climatology: A review","volume":"21","author":"Kidd","year":"2001","journal-title":"Int. J. Climatol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1951","DOI":"10.1080\/01431160118816","article-title":"Comparison of TAMSAT and CPC rainfall estimates with raingauges, for southern Africa","volume":"22","author":"Thorne","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"4097","DOI":"10.1080\/01431160701772526","article-title":"Validation of high resolution satellite rainfall products over complex terrain","volume":"29","author":"Dinku","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1175\/1520-0493(1987)115<0051:TRBLSC>2.0.CO;2","article-title":"The relationship between large-scale convective rainfall and cold cloud over the western hemisphere during 1982\u20131984","volume":"115","author":"Arkin","year":"1987","journal-title":"Mon. Wea. Rev."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1801","DOI":"10.1175\/1520-0450(2001)040<1801:TEOTGP>2.0.CO;2","article-title":"The evolution of the Goddard Profiling Algorithm (GPROF) for rainfall estimation from passive microwave sensors","volume":"40","author":"Kummerow","year":"2001","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1175\/1520-0450(1993)032<0335:EOMROJ>2.0.CO;2","article-title":"Estimation of rainfall over Japan and surrounding waters from a combination of low-orbit microwave and geosynchronous IR data","volume":"32","author":"Adler","year":"1993","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/S0022-1694(99)00092-X","article-title":"Optimal areal rainfall estimation using raingauges and satellite data","volume":"222","author":"Grimes","year":"1999","journal-title":"J. Hydrol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1284","DOI":"10.1175\/1520-0442(1995)008<1284:GPEBOA>2.0.CO;2","article-title":"Global precipitation estimates based on a technique for combining satellite-based estimates, rain gauge analysis, and NWP model precipitation information","volume":"8","author":"Huffman","year":"1995","journal-title":"J. Clim."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1175\/1520-0469(2001)058<0742:ACSIAP>2.0.CO;2","article-title":"A combined satellite infrared and passive microwave technique for estimation of small-scale rainfall","volume":"18","author":"Todd","year":"2001","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2353","DOI":"10.1080\/01431161003698286","article-title":"An intercomparison of 10-day satellite precipitation products during West African monsoon","volume":"32","author":"Jobard","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","unstructured":"Peterson, P., Funk, C., Husak, G., Pedreros, D., Landsfeld, M., Verdin, J., and Shukla, S. The Climate Hazards group InfraRed Precipitation (CHIRP) with Stations (CHIRPS): Development and Validation. Available online: http:\/\/adsabs.harvard.edu\/abs\/2013AGUFM.H33E1417P."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1016\/S0169-8095(98)00051-9","article-title":"Validation of satellite and ground-based estimates of precipitation over the Sahel","volume":"47\u201348","author":"Laurent","year":"1998","journal-title":"Atmos. Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1337","DOI":"10.1175\/1520-0450(2003)042<1337:VOTAOR>2.0.CO;2","article-title":"Validation of TRMM and other rainfall estimates with a high-density gauge dataset for West Africa. Part I: Validation of GPCC rainfall product and pre-TRMM satellite and blended products","volume":"42","author":"Nicholson","year":"2003","journal-title":"J. Appl. Meteorol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1175\/2007JAMC1586.1","article-title":"Comparison of gridded multisatellite rainfall estimates with gridded gauge rainfall over West Africa","volume":"47","author":"Lamptey","year":"2008","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1707","DOI":"10.1175\/JAM2305.1","article-title":"Rainfall estimation in the Sahel. Part II: Evaluation of rain gauge networks in the CILSS countries and objective intercomparison of rainfall products","volume":"44","author":"Ali","year":"2005","journal-title":"J. Appl. Meteorol."},{"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":"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_21","unstructured":"Hellmuth, M.E., Moorhead, A., Thomson, M., and Williams, J. (2007). Climate Risk Management in Africa: Learning from Practice, International Research Institute for Climate and Society."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Matyas, C.J. (2014). Tropical cyclone formation and motion in the Mozambique Channel. Int. J. Climatol., in press.","DOI":"10.1002\/joc.3985"},{"key":"ref_23","unstructured":"FAO FAOSTAT. Available online: http:\/\/faostat3.fao.org\/."},{"key":"ref_24","unstructured":"O\u2019Brien, K., and Vogel, C. (2003). Coping with Climate Variability\u2014The Use of Seasonal Climate Forecast in Southern Africa, Grower House."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/joc.2050","article-title":"ENSO and Indian Ocean sea surface temperatures and their relationships with tropical temperate troughs over Mozambique and the Southwest Indian Ocean","volume":"31","author":"Manhique","year":"2011","journal-title":"Int. J. Climatol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1504\/IJGW.2013.057291","article-title":"Loss and damage from the double blow of flood and drought in Mozambique","volume":"5","author":"Brida","year":"2013","journal-title":"Int. J. Glob. Warm."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"840","DOI":"10.1175\/1520-0442(1996)009<0840:AOGMPU>2.0.CO;2","article-title":"Analyses of global monthly precipitation using gauge observations, satellite estimates, and numerical model predictions","volume":"9","author":"Xie","year":"1996","journal-title":"J. Clim."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1175\/1520-0477(2001)082<0205:ARTGHH>2.3.CO;2","article-title":"A real-time global half-hourly pixel-resolution infrared dataset and its applications","volume":"82","author":"Janowiak","year":"2001","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"893","DOI":"10.1175\/2011BAMS3039.1","article-title":"Globally gridded satellite observations for climate studies","volume":"92","author":"Knapp","year":"2011","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_30","first-page":"1","article-title":"The NCEP climate forecast system reanalysis","volume":"1","author":"Saha","year":"2010","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_31","unstructured":"Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Rowland, J., Romero, B., Husak, G., Michaelsen, J., Verdin, A., and Pedreros, P. A Quasi-Global Precipitation Time Series for Drought Monitoring, Available online: pubs.usgs.gov\/ds\/832\/."},{"key":"ref_32","unstructured":"TAMSAT. Available online: www.met.reading.ac.uk\/~tamsat."},{"key":"ref_33","unstructured":"USGS FEWS NET Data Portal, Available online: earlywarning.usgs.gov\/fews."},{"key":"ref_34","unstructured":"Climate Hazards Group Available online: chg.geog.ucsb.edu\/data\/chirps."},{"key":"ref_35","unstructured":"WWRP\/WGNE Joint Working Group on Forecast Verification Research Forecast Verification: Issues, Methods and FAQ, Available online: http:\/\/www.cawcr.gov.au\/projects\/verification\/."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1080\/02626667.2011.637498","article-title":"Spatial disaggregation and intensity correction of TRMM-based rainfall time series for hydrological applications in dryland catchments","volume":"57","author":"Tarnavsky","year":"2012","journal-title":"Hydrol. Sci. J."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2147","DOI":"10.1080\/014311697217800","article-title":"Objectively determined 10-day African rainfall estimates created for famine early warning systems","volume":"18","author":"Herman","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"5702","DOI":"10.3390\/rs5115702","article-title":"Optimizing satellite-based precipitation estimation for nowcasting of rainfall and flash flood events over the South African domain","volume":"5","year":"2013","journal-title":"Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/2\/1758\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:42:23Z","timestamp":1760215343000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/2\/1758"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,2,5]]},"references-count":38,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2015,2]]}},"alternative-id":["rs70201758"],"URL":"https:\/\/doi.org\/10.3390\/rs70201758","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,2,5]]}}}