High-Resolution Precipitation Datasets in South America and West Africa based on Satellite-Derived Rainfall, Enhanced Vegetation Index and Digital Elevation Model

Abstract

Mean Annual Precipitation is one of the most important variables used in water resource management. However, quantifying Mean Annual Precipitation at high spatial resolution, needed for advanced hydrological analysis, is challenging in developing countries which often present a sparse gauge network and a highly variable climate. In this work, we present a methodology to quantify Mean Annual Precipitation at 1 km spatial resolution using different precipitation products from satellite estimates and gauge observations at coarse spatial resolution (i.e., ranging from 4 km to 25 km). Examples of this methodology are given for South America and West Africa. We develop a downscaling method that exploits the relationship among satellite-derived rainfall, Digital Elevation Model and Enhanced Vegetation Index. Finally, we validate its performance using rain gauge measurements: comparable annual precipitation estimates for both South America and West Africa are retrieved. Validation indicates that high resolution Mean Annual Precipitation downscaled from CHIRP (Climate Hazards Group Infrared Precipitation) and GPCC (Global Precipitation Climatology Centre) datasets present the best ensemble of performance statistics for both South America and West Africa. Results OPEN ACCESSRemote Sens. 2015, 7 6455 also highlight the potential of the presented technique to downscale satellite-derived rainfall worldwide.

Spatial Downscaling of GPM Annual and Monthly Precipitation Using Regression-Based Algorithms in a Mountainous Area

“…Brunsdont et al [31] put forward a local regression model called Geographically Weighted Regression (GWR) to handle the problem of spatial nonstationary. GWR-based satellite precipitation downscaling algorithm was found to perform better than the two global-regression-based algorithms over various regions on TRMM product, at both annual scale and monthly scale [15,30,32].…”

Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

“…Even though the continuous development of CHIRPS is mainly in support of drought-related issues in Africa (Climate Hazards Group, 2016), there are now other global applications available (e.g. http://ewx.chg.ucsb.edu:8080/EWX/index.html, http:// chg.geog.ucsb.edu/tools/geowrsi/index.html) and also papers that have looked at climate dynamics in South America (Ceccherini et al, 2015;Deblauwe et al, 2016).…”

Spatio-temporal vegetation dynamics and relationship with climate over East Africa

“…The CCD-derived estimates are then merged with World Meteorological Organization's Global Telecommunication System (GTS) gauged data using a 'smart interpolation' approach . Comparisons with other satellite precipitation estimates and observed rainguage data have shown that this data set provides useful long-term precipitation estimates for Africa (Ceccherini et al, 2015;Dembélé and Zwart, 2016;Toté et al, 2015). In addition, this dataset has been used in the East Africa region 15 previously to provide high resolution and combined gauge-satellite precipitation estimates (Ayana et al, 2016;Pricope et al, 2013).…”