{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T18:23:30Z","timestamp":1779906210974,"version":"3.53.1"},"reference-count":68,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,2,2]],"date-time":"2021-02-02T00:00:00Z","timestamp":1612224000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41875094"],"award-info":[{"award-number":["41875094"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Drought severity still remains a serious concern across Sub-Saharan Africa (SSA) due to its destructive impact on multiple sectors of society. In this study, the interannual variability and trends in the changes of the self-calibrating Palmer Drought Severity Index (scPDSI) based on the Penman\u2013Monteith (scPDSIPM) and Thornthwaite (scPDSITH) methods for measuring potential evapotranspiration (PET), precipitation (P), normalized difference vegetation index (NDVI), and sea surface temperature (SST) anomalies were investigated through statistical analysis of modeled and remote sensing data. It was shown that scPDSIPM and scPDSITH differed in the representation of drought characteristics over SSA. The regional trend magnitudes of scPDSI in SSA were 0.69 (scPDSIPM) and 0.2 mm\/decade (scPDSITH), with a difference in values attributed to the choice of PET measuring method used. The scPDSI and remotely sensed-based anomalies of P and NDVI showed wetting and drying trends over the period 1980\u20132012 with coefficients of trend magnitudes of 0.12 mm\/decade (0.002 mm\/decade). The trend analysis showed increased drought events in the semi-arid and arid regions of SSA over the same period. A correlation analysis revealed a strong relationship between the choice of PET measuring method and both P and NDVI anomalies for monsoon and pre-monsoon seasons. The correlation analysis of the choice of PET measuring method with SST anomalies indicated significant positive and negative relationships. This study has demonstrated the applicability of multiple data sources for drought assessment and provides useful information for regional drought predictability and mitigation strategies.<\/jats:p>","DOI":"10.3390\/rs13030533","type":"journal-article","created":{"date-parts":[[2021,2,2]],"date-time":"2021-02-02T13:01:12Z","timestamp":1612270872000},"page":"533","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Spatiotemporal Characteristics and Trend Analysis of Two Evapotranspiration-Based Drought Products and Their Mechanisms in Sub-Saharan Africa"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6636-9554","authenticated-orcid":false,"given":"Isaac Kwesi","family":"Nooni","sequence":"first","affiliation":[{"name":"Binjiang College, Nanjing University of Information Science &amp; Technology, No.333 Xishan Road, Wuxi 214105, China"},{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Geographical Sciences, Nanjing University of Information Science &amp; Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3501-9783","authenticated-orcid":false,"given":"Daniel Fiifi T.","family":"Hagan","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Geographical Sciences, Nanjing University of Information Science &amp; Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8613-0003","authenticated-orcid":false,"given":"Guojie","family":"Wang","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Geographical Sciences, Nanjing University of Information Science &amp; Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0626-0650","authenticated-orcid":false,"given":"Waheed","family":"Ullah","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Geographical Sciences, Nanjing University of Information Science &amp; Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2419-9988","authenticated-orcid":false,"given":"Shijie","family":"Li","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Geographical Sciences, Nanjing University of Information Science &amp; Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiao","family":"Lu","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Geographical Sciences, Nanjing University of Information Science &amp; Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Asher Samuel","family":"Bhatti","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Geographical Sciences, Nanjing University of Information Science &amp; Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao","family":"Shi","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Geographical Sciences, Nanjing University of Information Science &amp; Technology, Nanjing 210044, China"},{"name":"Jiangsu Meteorological Bureau, Meteorological Services Center, Nanjing 210008, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Lou","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Geographical Sciences, Nanjing University of Information Science &amp; Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6938-8734","authenticated-orcid":false,"given":"Nana Agyemang","family":"Prempeh","sequence":"additional","affiliation":[{"name":"School of Geosciences, Department of Geographic Sciences, University of Energy and Natural Resources, P.O. 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C.","family":"Lim Kam Sian","sequence":"additional","affiliation":[{"name":"Binjiang College, Nanjing University of Information Science &amp; Technology, No.333 Xishan Road, Wuxi 214105, China"},{"name":"College of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6425-1034","authenticated-orcid":false,"given":"Mawuli","family":"Dzakpasu","sequence":"additional","affiliation":[{"name":"Key Lab of Northwest Water Resources, Environment and Ecology, School of Environmental and Municipal Engineering, Xi\u2019an University of Architecture and Technology, No.13 Yanta Road, Xi\u2019an 710055, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1074-3719","authenticated-orcid":false,"given":"Solomon Obiri Yeboah","family":"Amankwah","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Geographical Sciences, Nanjing University of Information Science &amp; Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenxia","family":"Zhu","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Geographical Sciences, Nanjing University of Information Science &amp; Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,2]]},"reference":[{"key":"ref_1","unstructured":"Barros, R.V., Field, C.B., Dokken, D.J., Mastrandrea, M.D., Mach, K.J., Bilir, T.E., Ebi, K.L., Estrada, Y.O., Genova, R.C., and Girma, B. (2014). Climate Change 2014: Impacts, Adaptation, and Vulnerability, Cambridge University Press."},{"key":"ref_2","unstructured":"Guha-Sapir, D., Below, R., and Hoyois, P. (2020, January 06). Emem-Dat: The International Disaster Database. Available online: https:\/\/www.emdat.be\/."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2589","DOI":"10.5194\/hess-20-2589-2016","article-title":"A quantitative analysis to objectively appraise drought indicators and model drought impacts","volume":"20","author":"Bachmair","year":"2016","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"034042","DOI":"10.1088\/1748-9326\/aaafda","article-title":"How well do meteorological indicators represent agricultural and forest drought across europe?","volume":"13","author":"Bachmair","year":"2018","journal-title":"Environ. Res. Lett."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.5194\/nhess-12-1481-2012","article-title":"Climate trends and behaviour of drought indices based on precipitation and evapotranspiration in portugal","volume":"12","author":"Paulo","year":"2012","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1175\/2012EI000434.1","article-title":"Performance of drought indices for ecological, agricultural, and hydrological applications","volume":"16","author":"Camarero","year":"2012","journal-title":"Earth Interact."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.jhydrol.2010.07.012","article-title":"A review of drought concepts","volume":"391","author":"Mishra","year":"2010","journal-title":"J. Hydrol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1038\/nclimate1633","article-title":"Increasing drought under global warming in observations and models","volume":"3","author":"Dai","year":"2013","journal-title":"Nat. Clim. Change"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1038\/nature11575","article-title":"Little change in global drought over the past 60 years","volume":"491","author":"Sheffield","year":"2012","journal-title":"Nature"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1038\/491338a","article-title":"Historical drought trends revisited","volume":"491","author":"Seneviratne","year":"2012","journal-title":"Nature"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1038\/nclimate2067","article-title":"Global warming and changes in drought","volume":"4","author":"Trenberth","year":"2014","journal-title":"Nat. Clim. Change"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.1175\/JHM-386.1","article-title":"A global dataset of palmer drought severity index for 1870\u20132002: Relationship with soil moisture and effects of surface warming","volume":"5","author":"Dai","year":"2004","journal-title":"J. Hydrometeorol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3885","DOI":"10.5194\/hess-17-3885-2013","article-title":"A global analysis of the impact of drought on net primary productivity","volume":"17","author":"Chen","year":"2013","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4228","DOI":"10.1002\/2016JD026168","article-title":"Robust drying and wetting trends found in regions over china based on k\u00f6ppen climate classifications","volume":"122","author":"Chen","year":"2017","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.1175\/1520-0477-83.8.1149","article-title":"A review of twentieth-century drought indices used in the united states","volume":"83","author":"Heim","year":"2002","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2954","DOI":"10.1002\/joc.5475","article-title":"On the long-term changes of drought over china (1948\u20132012) from different methods of potential evapotranspiration estimations","volume":"38","author":"Wang","year":"2018","journal-title":"Int. J. Climatol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1007\/s41748-020-00153-x","article-title":"Projected Drought Events over West Africa Using RCA4 Regional Climate Model","volume":"4","author":"Ajayi","year":"2020","journal-title":"Earth Syst. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1007\/s41748-019-00133-w","article-title":"Identification of Potential Drought Areas in West Africa Under Climate Change and Variability","volume":"3","author":"Quenum","year":"2019","journal-title":"Earth Syst. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1007\/s41748-020-00169-3","article-title":"Assessing Future Changes of Climate Extreme Events in the CORDEX-MENA Region Using Regional Climate Model ALADIN-Climate","volume":"4","author":"Driouech","year":"2020","journal-title":"Earth Syst. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1002\/2017RG000574","article-title":"A review of global precipitation data sets: Data sources, estimation, and intercomparisons","volume":"56","author":"Sun","year":"2018","journal-title":"Rev. Geophys."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3717","DOI":"10.1007\/s12665-014-3659-x","article-title":"Dynamic and dry\/wet variation of climate in the potential extent of desertification in china during 1981\u20132010","volume":"73","author":"Sun","year":"2015","journal-title":"Environ. Earth Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1080\/16742834.2017.1392825","article-title":"Comparison of trends and frequencies of drought in central north china and sub-saharan africa from 1901 to 2010","volume":"10","author":"Ma","year":"2017","journal-title":"Atmos. Ocean. Sci. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1175\/BAMS-D-12-00124.1","article-title":"A drought monitoring and forecasting system for sub-sahara african water resources and food security","volume":"95","author":"Sheffield","year":"2014","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_24","unstructured":"FAO (2016). The State of Food and Agriculture 2016, Food and Agriculture of the United Nations."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1002\/wat2.1085","article-title":"Hydrological drought explained","volume":"2","year":"2015","journal-title":"WIREs Water"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"389","DOI":"10.5194\/essd-9-389-2017","article-title":"A global water resources ensemble of hydrological models: The earth2observe tier-1 dataset","volume":"9","author":"Schellekens","year":"2017","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"180214","DOI":"10.1038\/sdata.2018.214","article-title":"Present and future k\u00f6ppen-geiger climate classification maps at 1-km resolution","volume":"5","author":"Beck","year":"2018","journal-title":"Sci. Data"},{"key":"ref_28","unstructured":"ESACCI (2019, November 10). European Space Agency Climate Change Initiative. Land Use Land Cover (Lulc) Map. Available online: https:\/\/www.esa-landcover-cci.org\/."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.1175\/1520-0442(2002)015<1002:TEAMMR>2.0.CO;2","article-title":"The east african march\u2013may rainy season: Associated atmospheric dynamics and predictability over the 1968\u201397 period","volume":"15","author":"Camberlin","year":"2002","journal-title":"J. Clim."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Ullah, W., Wang, G., Lou, D., Ullah, S., Bhatti, A.S., Ullah, S., Karim, A., Hagan, D.F.T., and Ali, G. (2021). Large-scale atmospheric circulation patterns associated with extreme monsoon precipitation in Pakistan during 1981\u20132018. Atmos. Res., 105489.","DOI":"10.1016\/j.atmosres.2021.105489"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1007\/s003820000087","article-title":"Comparison of rainfall structures between ncep\/ncar reanalyses and observed data over tropical africa","volume":"16","author":"Poccard","year":"2000","journal-title":"Clim. Dyn."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2509","DOI":"10.1175\/JCLI-D-13-00365.1","article-title":"Timing and patterns of the enso signal in africa over the last 30 years: Insights from normalized difference vegetation index data","volume":"27","author":"Philippon","year":"2014","journal-title":"J. Clim."},{"key":"ref_33","unstructured":"(2019, November 10). National Aeronautics and Space Administration (NASA) Shuttle Radar Topography Mission (SRTM) Home Page, Available online: https:\/\/lpdaac.usgs.gov\/products\/srtmgl1v003\/."},{"key":"ref_34","unstructured":"Palmer, W. (1965). Meteorological Drought, US Weather Bureau."},{"key":"ref_35","unstructured":"Terrestrial Hydrology Research Group (2019, November 10). A Global Dataset of Palmer Drought Severity Index and Potential Evaporation at 1.0-Degree, Monthly Resolution. Available online: http:\/\/hydrology.princeton.edu\/data\/pdsi\/updates_1948-2012\/."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3088","DOI":"10.1175\/JCLI3790.1","article-title":"Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling","volume":"19","author":"Sheffield","year":"2006","journal-title":"J. Clim."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"4485","DOI":"10.1080\/01431160500168686","article-title":"An extended avhrr 8-km ndvi dataset compatible with modis and spot vegetation NDVI data","volume":"26","author":"Tucker","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"5201","DOI":"10.1080\/01431160600567787","article-title":"Compared regimes of NDVI and rainfall in semi-arid regions of Africa","volume":"27","author":"Martiny","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"150066","DOI":"10.1038\/sdata.2015.66","article-title":"The climate hazards infrared precipitation with stations\u2014A new environmental record for monitoring extremes","volume":"2","author":"Funk","year":"2015","journal-title":"Sci. Data"},{"key":"ref_40","unstructured":"IRI\/LDE (2019, November 10). International Research Institute Climate Data Library. Available online: https:\/\/iri.columbia.edu\/topics\/data-library\/."},{"key":"ref_41","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, USGS.","DOI":"10.3133\/ds832"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/j.rse.2017.03.041","article-title":"Assessing multi-satellite remote sensing, reanalysis, and land surface models\u2019 products in characterizing agricultural drought in East Africa","volume":"194","author":"Agutu","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Ullah, W., Wang, G., Ali, G., Tawia Hagan, D.F., Bhatti, A.S., and Lou, D. (2019). Comparing multiple precipitation products against in-situ observations over different climate regions of Pakistan. Remote Sens., 11.","DOI":"10.3390\/rs11060628"},{"key":"ref_44","unstructured":"Climate Prediction Center (CPC) of the National Weather Service (2020, January 06). U.S.w, Available online: http:\/\/www.Cpc.Ncep.Noaa.Gov."},{"key":"ref_45","unstructured":"Climate Prediction Center (CPC) of the National Weather Service (2020, January 06). Database, Available online: http:\/\/www.cpc.ncep.noaa.gov\/data\/indices\/."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"2283","DOI":"10.1175\/2007JCLI2100.1","article-title":"Improvements to noaa\u2019s historical merged land\u2013ocean surface temperature analysis (1880\u20132006)","volume":"21","author":"Smith","year":"2008","journal-title":"J. Clim."},{"key":"ref_47","unstructured":"(2019, November 10). European Center for Medium-Range Weather Forecasts (ECMWF) Home Page. Available online: http:\/\/apps.ecmwf.int\/datasets\/data\/interim-full-daily\/levtype=sfc\/."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1080\/07038992.1979.10854986","article-title":"Geometric correction, registration, and resampling of landsat imagery","volume":"5","author":"Shlien","year":"1979","journal-title":"Can. J. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"4778","DOI":"10.1080\/01431161.2014.930201","article-title":"Support vector machine to map oil palm in a heterogeneous environment","volume":"35","author":"Nooni","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"245","DOI":"10.2307\/1907187","article-title":"Nonparametric tests against trend","volume":"13","author":"Mann","year":"1945","journal-title":"Econometrica"},{"key":"ref_51","unstructured":"Kendall, M.G. (1975). Rank Correlation Methods, Charles Griffin."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1080\/01621459.1968.10480934","article-title":"Estimates of the regression coefficient based on kendall\u2019s tau","volume":"63","author":"Sen","year":"1968","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Nooni, I.K., Wang, G., Hagan, D.F.T., Lu, J., Ullah, W., and Li, S. (2019). Evapotranspiration and its components in the nile river basin based on long-term satellite assimilation product. Water, 11.","DOI":"10.3390\/w11071400"},{"key":"ref_54","unstructured":"Klein Tank, A.M.G., Zwiers, F.W., and Zhang, X. (2012). Guidelines on Analysis of Extremes in a Changing Climate in Support of Informed Decisions for Adaptation, World Meteorological Organization. WMO-TD No. 1500."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1175\/2009JCLI2968.1","article-title":"Spatial variation and trends in PDSI and SPI indices and their relation to streamflow in 10 large regions of china","volume":"23","author":"Zhai","year":"2010","journal-title":"J. Clim."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"075005","DOI":"10.1088\/1748-9326\/ab2203","article-title":"On the use of satellite, gauge, and reanalysis precipitation products for drought studies","volume":"14","author":"Golian","year":"2019","journal-title":"Environ. Res. Lett."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1093\/treephys\/tpv029","article-title":"Drought-induced tree mortality: From discrete observations to comprehensive research","volume":"35","author":"Klein","year":"2015","journal-title":"Tree Physiol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1104\/pp.110.170704","article-title":"Mechanisms linking drought, hydraulics, carbon metabolism, and vegetation mortality","volume":"155","author":"McDowell","year":"2011","journal-title":"Plant Physiol."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1111\/j.1469-8137.2008.02436.x","article-title":"Mechanisms of plant survival and mortality during drought: Why do some plants survive while others succumb to drought?","volume":"178","author":"McDowell","year":"2008","journal-title":"New Phytol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"948","DOI":"10.1038\/s41558-019-0630-6","article-title":"Increasing impacts of extreme droughts on vegetation productivity under climate change","volume":"9","author":"Xu","year":"2019","journal-title":"Nat. Clim. Change"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1111\/gcb.12393","article-title":"Drought footprint on European ecosystems between 1999 and 2010 assessed by remotely sensed vegetation phenology and productivity","volume":"20","author":"Ivits","year":"2014","journal-title":"Glob. Change Biol."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"2835","DOI":"10.1080\/01431161.2014.890298","article-title":"Drought impact on vegetation productivity in the Lower Mekong Basin","volume":"35","author":"Zhang","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"064007","DOI":"10.1088\/1748-9326\/ab7fde","article-title":"A tale of two futures: Contrasting scenarios of future precipitation for West Africa from an ensemble of regional climate models","volume":"15","author":"Dosio","year":"2020","journal-title":"Environ. Res. Lett."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"2569","DOI":"10.1038\/s41598-018-20904-1","article-title":"Sahel rainfall strength and onset improvements due to more realistic Atlantic cold tongue development in a climate model","volume":"8","author":"Steinig","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_65","unstructured":"Barros, R.V., Field, C.B., Dokken, D.J., Mastrandrea, M.D., Mach, K.J., Bilir, T.E., Ebi, K.L., Estrada, Y.O., Genova, R.C., and Girma, B. (2014). 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; Cambridge University Press."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1847","DOI":"10.1080\/01431160010029156","article-title":"NDVI anomaly patterns over Africa during the 1997\/98 ENSO warm event","volume":"22","author":"Anyamba","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.agrformet.2016.04.009","article-title":"Seasonal and interannual changes in vegetation activity of tropical forests in Southeast Asia","volume":"224","author":"Zhang","year":"2016","journal-title":"Agric. For. Meteorol."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.gloplacha.2017.02.008","article-title":"Response of vegetation to different time-scales drought across China: Spatiotemporal patterns, causes and implications","volume":"152","author":"Zhang","year":"2017","journal-title":"Glob. Planet. 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