{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T14:00:26Z","timestamp":1769176826018,"version":"3.49.0"},"reference-count":80,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2021,5,19]],"date-time":"2021-05-19T00:00:00Z","timestamp":1621382400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This study presents a rain area detection scheme that uses a gradient based adaptive technique for daytime and nighttime rain area detection and correction from reflectance and infrared (IR) brightness temperatures data of the Meteosat Second Generation (MSG) satellite. First, multiple parametric rain detection models developed from MSG\u2019s reflectance and IR data were calibrated and validated with rainfall data from a dense network of rain gauge stations and investigated to determine the best model parameters. The models were based on a conceptual assumption that clouds characterised by the top properties, e.g., high optical thickness and effective radius, have high rain probabilities and intensities. Next, a gradient based adaptive correction technique that relies on rain area-specific parameters was developed to reduce the number and sizes of the detected rain areas. The daytime detection with optical (VIS0.6) and near IR (NIR1.6) reflectance data achieved the best detection skill. For nighttime, detection with thermal IR brightness temperature differences of IR3.9-IR10.8, IR3.9-WV73 and IR108-WV62 showed the best detection skill based on general categorical statistics. Compared to the Global Precipitation Measurement (GPM) Integrated Mult-isatellitE Retrievals for GPM (IMERG) and the gauge station data from the southwest of Kenya, the model showed good agreement in the spatial dynamics of the detected rain area and rain rate.<\/jats:p>","DOI":"10.3390\/s21103547","type":"journal-article","created":{"date-parts":[[2021,5,19]],"date-time":"2021-05-19T21:49:21Z","timestamp":1621460961000},"page":"3547","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Rain Area Detection in South-Western Kenya by Using Multispectral Satellite Data from Meteosat Second Generation"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6865-0665","authenticated-orcid":false,"given":"Kumah K.","family":"Kingsley","sequence":"first","affiliation":[{"name":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500 AE Enschede, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ben H. P.","family":"Maathuis","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500 AE Enschede, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joost C. B.","family":"Hoedjes","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500 AE Enschede, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Donald T.","family":"Rwasoka","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500 AE Enschede, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bas V.","family":"Retsios","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500 AE Enschede, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bob Z.","family":"Su","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500 AE Enschede, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Macharia, J.M., Ngetich, F.K., and Shisanya, C.A. (2020). Comparison of satellite remote sensing derived precipitation estimates and observed data in Kenya. Agric. For. Meteorol., 284.","DOI":"10.1016\/j.agrformet.2019.107875"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1007\/s11069-006-9106-x","article-title":"Flood and landslide applications of near real-time satellite rainfall products","volume":"43","author":"Hong","year":"2007","journal-title":"Nat. Hazards"},{"key":"ref_3","unstructured":"David, N., Gao, O., Kumah, K.K., Hoedjes, J.C.B., Su, Z., and Liu, Y. (2019, January 4\u20137). Microwave communication networks as a sustainable tool of rainfall monitoring for agriculture needs in Africa. Proceedings of the 16th International Conference on Environmental Science and Technology, Rhodes, Greece."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"David, N., Liu, Y., Kumah, K.K., Hoedjes, J.C.B., Su, B.Z., and Gao, H.O. (2021). On the Power of Microwave Communication Data to Monitor Rain for Agricultural Needs in Africa. Water, 13.","DOI":"10.3390\/w13050730"},{"key":"ref_5","first-page":"61","article-title":"Cloud Top Microphysics as a Tool for Precipitation Measurements","volume":"Volume 1","author":"Levizzani","year":"2007","journal-title":"Measuring Precipitation From Space"},{"key":"ref_6","unstructured":"Berg\u00e8s, J.C., Chopin, F., Bessat, F., and Based, S. (2005, January 5\u20137). Satellite based downscaling algorithm for rainfall estimation hal. Proceedings of the IV Col\u00f3quio Brasileiro de Ci\u00eancias Geod\u00e9sicas\u2014IV CBCG, Curitiba, Brazil."},{"key":"ref_7","unstructured":"Milford, J.R., McDougall, V.D., and Dugdale, G. (2021, March 15). Rainfall estimation from cold cloud duration: Experience of the Tamsat Group in West Africa. Niamey. Available online: https:\/\/horizon.documentation.ird.fr\/exl-doc\/pleins_textes\/pleins_textes_6\/colloques2\/010008087.pdf."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1175\/1520-0450(1988)027<0030:ASITTE>2.0.CO;2","article-title":"A Satellite Infrared Technique to Estimate Tropical Convective and Stratiform Rainfall","volume":"27","author":"Adler","year":"1988","journal-title":"J. Appl. Meteorol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1007\/s00704-010-0316-5","article-title":"Identifying precipitating clouds in Greece using multispectral infrared Meteosat Second Generation satellite data","volume":"104","author":"Feidas","year":"2011","journal-title":"Theor. Appl. Climatol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2457","DOI":"10.1175\/JAMC-D-14-0082.1","article-title":"Precipitation Estimates from MSG SEVIRI Daytime, Nighttime, and Twilight Data with Random Forests","volume":"53","author":"Kuhnlein","year":"2014","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_11","first-page":"10619","article-title":"The 30 year TAMSAT African Rainfall Climatology And Time series (TARCAT) data set","volume":"119","author":"Ross","year":"2014","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.pce.2019.02.008","article-title":"Evaluation of TAMSAT satellite rainfall estimates for southern Africa: A comparative approach","volume":"112","author":"Seyama","year":"2019","journal-title":"Phys. Chem. Earth"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2292","DOI":"10.1175\/1520-0450(2001)040<2292:ACOCAR>2.0.CO;2","article-title":"A Comparison of Cloud and Rainfall Information from Instantaneous Visible and Infrared Scanner and Precipitation Radar Observations over a Frontal Zone in East Asia during June 1998","volume":"39","author":"Inoue","year":"2000","journal-title":"J. Appl. Meteorol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1002\/met.56","article-title":"Discriminating raining from non-raining cloud areas at mid-latitudes using meteosat second generation SEVIRI night-time data","volume":"15","author":"Thies","year":"2008","journal-title":"Meteor. Appl."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Kumah, K.K., Hoedjes, J.C.B., David, N., Maathuis, B.H.P., Gao, H.O., and Su, B.Z. (2020). Combining MWL and MSG SEVIRI Satellite Signals for Rainfall Detection and Estimation. Atmosphere, 11.","DOI":"10.3390\/atmos11090884"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2341","DOI":"10.5194\/acp-8-2341-2008","article-title":"Discriminating raining from non-raining clouds at mid-latitudes using meteosat second generation daytime data","volume":"8","author":"Thies","year":"2008","journal-title":"Atmos. Chem. Phys."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"D23206","DOI":"10.1029\/2008JD010464","article-title":"Precipitation process and rainfall intensity differentiation using Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager data","volume":"113","author":"Thies","year":"2008","journal-title":"J. Geophys. Res.-Atmos."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1175\/BAMS-83-7-Schmetz-2","article-title":"An Introduction to Meteosat Second Generation (MSG)","volume":"83","author":"Schmetz","year":"2002","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1080\/2150704X.2018.1453174","article-title":"On the vertical accuracy of the ALOS world 3D-30m digital elevation model","volume":"9","author":"Caglar","year":"2018","journal-title":"Remote Sens. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1038\/nature13636","article-title":"Migrations and dynamics of the intertropical convergence zone","volume":"513","author":"Schneider","year":"2014","journal-title":"Nature"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"8155","DOI":"10.1002\/2015GL065765","article-title":"Recent observed and simulated changes in precipitation over Africa","volume":"42","author":"Maidment","year":"2015","journal-title":"Geophys. Res. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1002\/2016RG000544","article-title":"Climate and climatic variability of rainfall over eastern Africa","volume":"55","author":"Nicholson","year":"2017","journal-title":"Rev Geophys."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1645","DOI":"10.1007\/s00382-013-1991-6","article-title":"Indo-Pacific sea surface temperature influences on failed consecutive rainy seasons over eastern Africa","volume":"43","author":"Hoell","year":"2013","journal-title":"Clim. Dyn."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"8453","DOI":"10.1175\/JCLI-D-12-00708.1","article-title":"Assessment of the Performance of CORDEX Regional Climate Models in Simulating East African Rainfall","volume":"26","author":"Endris","year":"2013","journal-title":"J. Clim."},{"key":"ref_25","unstructured":"EUMETSAT (2021, February 18). Optimal Cloud Analysis: Product Guide. Available online: https:\/\/www.eumetsat.int\/media\/45999."},{"key":"ref_26","unstructured":"TAHMO (2021, January 12). Acquire African Weather Data. Available online: https:\/\/tahmo.org\/."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1002\/wat2.1034","article-title":"The Trans-African Hydro-Meteorological Observatory (TAHMO)","volume":"1","author":"Hut","year":"2014","journal-title":"Wiley Interdiscip. Rev. Water"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2817","DOI":"10.1175\/JHM-D-17-0139.1","article-title":"Validation of IMERG Precipitation in Africa","volume":"18","author":"Dezfuli","year":"2017","journal-title":"J. Hydrometeorol."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Gebremichael, M., and Hossain, F. (2010). The TRMM Multi-Satellite Precipitation Analysis (TMPA). Satellite Rainfall Applications for Surface Hydrology, Springer.","DOI":"10.1007\/978-90-481-2915-7"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2471","DOI":"10.1175\/JTECH-D-19-0114.1","article-title":"IMERG V06: Changes to the Morphing Algorithm","volume":"36","author":"Tan","year":"2019","journal-title":"J. Atmos. Ocean Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1175\/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2","article-title":"CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution","volume":"5","author":"Joyce","year":"2004","journal-title":"J. Hydrometeorol."},{"key":"ref_32","unstructured":"(2021, March 19). Integrated Multi-satellitE Retrievals for GPM (IMERG), Available online: https:\/\/gpm.nasa.gov\/data\/directory."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1218","DOI":"10.1175\/1520-0450(2003)042<1218:ANDAFI>2.0.CO;2","article-title":"A night-rain delineation algorithm for infrared satellite data based on microphysical considerations","volume":"42","author":"Lensky","year":"2003","journal-title":"J. Appl. Meteorol."},{"key":"ref_34","unstructured":"Kerkmann, J., Rosenfeld, D., Lutz, H.J., Prieto, J., and K\u00f6nig, M. (2021, March 17). Applications of Meteosat Second Generation (MSG): Meteorological Use of the Seviri ir3.9 Channel. Available online: https:\/\/www.eumetsat.int\/msg-interpretation-guide."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1016\/j.atmosres.2015.09.021","article-title":"Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals","volume":"169","author":"Meyer","year":"2016","journal-title":"Atmos. Res."},{"key":"ref_36","unstructured":"Eumetsat (2021, February 21). Cloud Mask Product: Product Guide. Available online: https:\/\/www-cdn.eumetsat.int\/files\/2020-04\/pdf_clm_pg.pdf."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1175\/2007JAMC1661.1","article-title":"Validation of cloud liquid water path retrievals from SEVIRI using one year of CloudNET observations","volume":"47","author":"Roebeling","year":"2008","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2005JD006990","article-title":"Cloud property retrievals for climate monitoring: Implications of differences between Spinning Enhanced Visible and Infrared Imager (SEVIRI) on METEOSAT-8 and Advanced Very High Resolution Radiometer (AVHRR) on NOAA-17","volume":"111","author":"Roebeling","year":"2006","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1477","DOI":"10.1175\/2010JAMC2284.1","article-title":"Rainfall-Rate Assignment Using MSG SEVIRI Data-A Promising Approach to Spaceborne Rainfall-Rate Retrieval for Midlatitudes","volume":"49","author":"Kuhnlein","year":"2010","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1007\/s00704-012-0802-z","article-title":"Classification of convective and stratiform rain based on the spectral and textural features of Meteosat Second Generation infrared data","volume":"113","author":"Giannakos","year":"2012","journal-title":"Theor. Appl. Climatol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"623","DOI":"10.2151\/jmsj.81.623","article-title":"Comparison of a split-window and a multi-spectral cloud classification for MODIS observations","volume":"81","author":"Lutz","year":"2003","journal-title":"J. Meteorol. Soc. Japan"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/S0273-1177(97)00051-3","article-title":"Monitoring deep convection and convective overshooting with METEOSAT","volume":"19","author":"Schmetz","year":"1997","journal-title":"Adv. Space Res."},{"key":"ref_43","unstructured":"Kidder, S.Q., Kankiewicz, J.A., and Eis, K.E. (2005). Meteosat Second Generation Cloud Algorithms for Use at AFWA, BACIMO. Available online: http:\/\/cat.cira.colostate.edu\/kidder\/BACIMO_2005.pdf."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"469","DOI":"10.2151\/jmsj1965.65.3_469","article-title":"An Instantaneous Delineation of Convective Rainfall Areas Using Split Window Data of Noaa-7 Avhrr","volume":"65","author":"Inoue","year":"1987","journal-title":"J. Meteorol. Soc. Jpn."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3991","DOI":"10.1029\/JD092iD04p03991","article-title":"A Cloud Type Classification with Noaa 7 Split-Window Measurements","volume":"92","author":"Inoue","year":"1987","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_46","unstructured":"Inoue, T., Wu, X., and Bessho, K. (2001, January 15\u201318). Life Cycle of Convective Activity in Terms of Cloud Type Observed By Split Window. Proceedings of the 11th Conference on Satellite Meteorology and Oceanography, Madison, WI, USA."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1175\/1520-0450(1994)033<0212:CPIFD>2.0.CO;2","article-title":"Cloud Properties inferred from 8\u201312-\u00b5m Data","volume":"33","author":"Strabala","year":"1994","journal-title":"J. Appl. Meteorol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"63","DOI":"10.5194\/adgeo-16-63-2008","article-title":"First results on a process-oriented rain area classification technique using Meteosat Second Generation SEVIRI nighttime data","volume":"16","author":"Thies","year":"2008","journal-title":"Adv. Geosci."},{"key":"ref_49","first-page":"17","article-title":"Statistical Patterns of Rainfall Variability in the Great Rift Valley of Kenya","volume":"5","author":"Wakachala","year":"2015","journal-title":"J. Environ. Agric. Sci. (JEAS)"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1175\/1520-0426(2002)019<0065:EOSGTD>2.0.CO;2","article-title":"Evaluation of some ground truth designs for satellite estimates of rain rate","volume":"19","author":"Ha","year":"2002","journal-title":"J. Atmos. Ocean Technol."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Moraux, A., Dewitte, S., Cornelis, B., and Munteanu, A. (2019). Deep Learning for Precipitation Estimation from Satellite and Rain Gauges Measurements. Remote. Sens., 11.","DOI":"10.3390\/rs11212463"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Kilavi, M., MacLeod, D., Ambani, M., Robbins, J., Dankers, R., Graham, R., Helen, T., Salih, A., and Todd, M. (2018). Extreme Rainfall and Flooding over Central Kenya Including Nairobi City during the Long-Rains Season 2018: Causes, Predictability, and Potential for Early Warning and Actions. Atmosphere, 9.","DOI":"10.3390\/atmos9120472"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"2179","DOI":"10.1175\/1520-0477(1997)078<2179:SPIROC>2.0.CO;2","article-title":"Stratiform Precipitation in Regions of Convection: A Meteorological Paradox?","volume":"78","author":"Houze","year":"1997","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"88","DOI":"10.2151\/jmsj1965.63.1_88","article-title":"On the Temperature and Effective Emissivity Determination of Semi-Transparent Cirrus Clouds by Bi-Spectral Measurements in the 10 Mu-M Window Region","volume":"63","author":"Inoue","year":"1985","journal-title":"J. Meteorol. Soc. Jpn."},{"key":"ref_55","unstructured":"Wilks, D.S. (2011). Statistical Methods in the Atmospheric Sciences, Elsevier."},{"key":"ref_56","unstructured":"Harold, B., Barb, B., Beth, E., Chris, F., Johannes, J., Ian, J., Tieh-Yong, K., Paul, R., and David, S. (2020, October 10). WWRP\/WGNE Joint Working Group on Forecast Verification Research, Available online: https:\/\/www.cawcr.gov.au\/projects\/verification\/."},{"key":"ref_57","unstructured":"Huffman, G.J., Bolvin, D.T., Nelkin, E.J., and Tan, J. (2021, January 17). Integrated Multi-Satellite Retrievals for GPM (IMERG) Technical Documentation, Available online: https:\/\/pmm.nasa.gov\/sites\/default\/files\/document_files\/IMERG_doc_180207.pdf."},{"key":"ref_58","unstructured":"Huffman, G.J., Stocker, E.F., Bolvin, D.T., Nelkin, E.J., and Tan, J. (2021, January 02). GPM IMERG Final Precipitation L3 Half Hourly 0.1 Degree \u00d7 0.1 Degree V06, Available online: https:\/\/disc.gsfc.nasa.gov\/datasets\/GPM_3IMERGHH_06\/summary."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Anjum, M.N., Ahmad, I., Ding, Y.J., Shangguan, D.H., Zaman, M., Ijaz, M.W., Sarwar, K., Han, H.D., and Yang, M. (2019). Assessment of IMERG-V06 Precipitation Product over Different Hydro-Climatic Regimes in the Tianshan Mountains, North-Western China. Remote. Sens., 11.","DOI":"10.3390\/rs11192314"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"125929","DOI":"10.1016\/j.jhydrol.2020.125929","article-title":"A comprehensive evaluation of GPM-IMERG V06 and MRMS with hourly ground-based precipitation observations across Canada","volume":"594","author":"Moazami","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1175\/JHM-D-19-0257.1","article-title":"A Process-Based Validation of GPM IMERG and Its Sources Using a Mesoscale Rain Gauge Network in the West African Forest Zone","volume":"21","author":"Maranan","year":"2020","journal-title":"J. Hydrometeorol."},{"key":"ref_62","unstructured":"Tan, J., George, H., David, B., and Eric, N. (2021, March 02). IMERG V06 Ground Validation Wishlist, Available online: https:\/\/gpm.nasa.gov\/sites\/default\/files\/document_files\/IMERG-Validation-Wishlist.pdf."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"621","DOI":"10.2151\/jmsj1965.67.4_621","article-title":"Features of Clouds over the Tropical Pacific during Northern Hemispheric Winter Derived from Split Window Measurements","volume":"67","author":"Inoue","year":"1989","journal-title":"J. Meteorol. Soc. Jpn."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"804","DOI":"10.1175\/JAM2236.1","article-title":"Daytime global cloud typing from AVHRR and VIIRS: Algorithm description, validation, and comparisons","volume":"44","author":"Pavolonis","year":"2005","journal-title":"J. Appl. Meteorol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"4145","DOI":"10.1175\/1520-0442(2003)016<4145:OTRSOP>2.0.CO;2","article-title":"On the ROC Score of Probability Forecasts","volume":"16","author":"Kharin","year":"2003","journal-title":"J. Clim."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1007\/s00704-011-0509-6","article-title":"Validation of high-resolution TRMM-3B43 precipitation product using rain gauge measurements over Kyrgyzstan","volume":"108","author":"Karaseva","year":"2011","journal-title":"Theor. Appl. Clim."},{"key":"ref_67","unstructured":"Heinemann, T., Latanzio, A., and Roveda, F. (2002, January 23\u201327). The Eumetsat multi-sensor precipitation estimate (MPE). Proceedings of the second International Precipitation Working Group (IPWG) meeting, Madrid, Spain."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.wace.2017.03.002","article-title":"Evaluating the MSG satellite Multi-Sensor Precipitation Estimate for extreme rainfall monitoring over northern Tunisia","volume":"16","author":"Dhib","year":"2017","journal-title":"Weather. Clim. Extremes"},{"key":"ref_69","unstructured":"Andreas, W., Thomas, K., and Higgins, M. (2021, March 24). RGB Colour Interpretation Guide. Available online: http:\/\/www.eumetrain.org\/rgb_quick_guides\/."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"1696","DOI":"10.1175\/2009JAMC2092.1","article-title":"Rainfall Variability over Mountainous and Adjacent Lake Areas: The Case of Lake Tana Basin at the Source of the Blue Nile River","volume":"48","author":"Haile","year":"2009","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Kimani, M.W., Hoedjes, J.C.B., and Su, Z. (2017). An assessment of satellite-derived rainfall products relative to ground observations over East Africa. Remote Sens., 9.","DOI":"10.3390\/rs9050430"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"12786","DOI":"10.1038\/ncomms12786","article-title":"Hazardous thunderstorm intensification over Lake Victoria","volume":"7","author":"Thiery","year":"2016","journal-title":"Nat. Commun."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Haskell, G., and Rycroft, M. (1998). The Use of Meteorological Satellite Data in Africa and Their Contribution Towards Economic Development. New Space Markets, Springer.","DOI":"10.1007\/978-94-011-5030-9"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2011JD015883","article-title":"Retrieval of two-layer cloud properties from multispectral observations using optimal estimation","volume":"116","author":"Watts","year":"2011","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1175\/1520-0450(1997)036<0234:EOPAAR>2.0.CO;2","article-title":"Estimation of Precipitation Area and Rain Intensity Based on the Microphysical Properties Retrieved from NOAA AVHRR Data","volume":"36","author":"Lensky","year":"1997","journal-title":"J. Appl. Meteorol."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"2951","DOI":"10.5194\/hess-24-2951-2020","article-title":"Ability of an Australian reanalysis dataset to characterise sub-daily precipitation","volume":"24","author":"Acharya","year":"2020","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Carlberg, B., Franz, K., and Gallus, W. (2020). A Method to Account for QPF Spatial Displacement Errors in Short-Term Ensemble Streamflow Forecasting. Water, 12.","DOI":"10.3390\/w12123505"},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Uijlenhoet, R., Overeem, A., and Leijnse, H. (2018). Opportunistic remote sensing of rainfall using microwave links from cellular communication networks. Wires. Water, 5.","DOI":"10.1002\/wat2.1289"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"e1337","DOI":"10.1002\/wat2.1337","article-title":"Commercial microwave link networks for rainfall observation: Assessment of the current status and future challenges","volume":"6","author":"Chwala","year":"2019","journal-title":"Wires. Water"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"4297","DOI":"10.5194\/acp-14-4297-2014","article-title":"CLAAS: The CM SAF cloud property data set using SEVIRI","volume":"14","author":"Stengel","year":"2014","journal-title":"Atmos. Chem. Phys."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/10\/3547\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:04:16Z","timestamp":1760162656000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/10\/3547"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,19]]},"references-count":80,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["s21103547"],"URL":"https:\/\/doi.org\/10.3390\/s21103547","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,19]]}}}