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|Title:||Monitoring drought conditions and their uncertainties in Africa using TRMM data|
|Authors:||NAUMANN GUSTAVO; BARBOSA FERREIRA Paulo; SAIOTE CARRÃO HUGO MIGUEL; SINGLETON ANDREW; VOGT Juergen|
|Citation:||JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY vol. 57 p. 1867–1874|
|Publisher:||AMER METEOROLOGICAL SOC|
|Type:||Articles in periodicals and books|
|Abstract:||The main objective of this study is to evaluate the uncertainties due to sample size associated with the estimation of the Standardized Precipitation Index (SPI) and their impact on the level of confidence in drought monitoring in Africa using high spatial resolution but short time series data. In order to do this, two different rainfall datasets, each available on a monthly basis, were analysed over four river basins in Africa (Oum er-Rbia, Limpopo, Niger, and Eastern Nile), as well as at continental level. The two precipitation datasets used were the Tropical Rainfall Measuring Mission (TRMM) satellite monthly rainfall product 3B43 and the Global Precipitation Climatology Centre (GPCC) full reanalysis gridded precipitation dataset. A non-parametric resampling bootstrap approach was used to compute the confidence bands associated with the SPI estimation, which are essential for making a qualified assessment of drought events. The comparative analysis of different datasets suggests that is feasible to use short time series of remote sensing precipitation data such as TRMM, that have a higher spatial resolution than other gridded precipitation data, for reliable drought monitoring over Africa. The proposed approach for drought monitoring has the potential to be used in support of decision making at both continental and sub-continental scales over Africa or over other regions that have a sparse distribution of rainfall measurement instruments.|
|JRC Directorate:||Sustainable Resources|
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