Comparison of satellite remote sensing derived precipitation estimates and observed data in Kenya
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Date
2019
Authors
Macharia, Joseph M.
Ngetich, Felix K.
Shisanya, C.A.
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
This study evaluated the accuracy of four satellite remote sensing (SRS) based products in predicting rainfall
(amounts and spatial distribution) over Kenya between 1998 and 2013. The four SRS products used include; two
satellite products (Climate Hazards Group InfraRed Precipitation with Station (CHIRPS 2.0) and Tropical
Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA) 3B42 version 7 (TRMM)), one gaugeinterpolated
product (Global Precipitation Climatology Centre (GPCC)) and one re-analysis product (Modern-Era
Retrospective Analysis for Research and Application (MERRA)). The monthly precipitation data were evaluated
for completeness, converted to individual raster files, projected to the World Geodetic System (WGS) 1984 -
Universal Transverse Mercator (UTM) zone 37 N ensuring a similar processing extent, rescaled to a common
resolution and reclassified following defined uniform intervals for ease of comparison. Thereafter, they were
subjected to five different metrics based on eight agro-ecological zones (AEZs) of Kenya, in reference to observed
rainfall data obtained from Kenya meteorological department (KMD). Results show that all SRS products both
overestimated or underestimated rainfall amounts on a pixel to pixel comparison. Based on point to point
proportion of variance evaluation (r2), TRMM best-estimated rainfall in the tropical cool humid (r2 = 0.64),
tropical warm humid (r2 = 0.58) and tropical cool subhumid (r2 = 0.39) zones and can be used for agricultural
advisory services. The GPCC product best-estimated rainfall in the tropical warm semiarid (r2 =0.46) and warm
tropical sub-humid (r2 = 0.21), while CHIRPS 2.0 best-estimated rainfall in the tropical warm arid (r2 = 0.33)
and therefore the two products could be best used to predict rainfall in the ASALs and drought-related studies,
with potential for irrigation. The MERRA product best-estimated rainfall in tropical cool arid (r2 = 0.97) and
tropical cool semiarid (r2 = 0.53) and could, therefore, be best used for high elevation and drought-related
studies. These results demonstrate the promising potential of the satellite remote sensed data in complementing
the existing meteorological observed data which are often marred by inconsistency and scarcity, and hence
unreliable in the existing agricultural advisory and other climate-based applications in Kenya, and sub-Saharan
Africa at large. However, given the observed AEZ dependant variations in the satellite estimates, it is advisable to
choose the most suitable SRS product for specific activities per AEZ and calibrate before utilisation.
Description
Research Article
Keywords
Rainfall, Kenya, CHIRPS 2.0, TRMM-TMPA 3B42 V7, GPCC, MERRA
Citation
Agricultural and Forest Meteorology 284 (2020) 107875