Abstract
Rainfall information is essential for many applications in developing countries, and yet, continually updated information at fine temporal and spatial scales is lacking. In Africa, rainfall monitoring is particularly important given the close relationship between climate and livelihoods. To address this information gap, this paper describes two versions (v2.0 and v3.0) of the TAMSAT daily rainfall dataset based on high-resolution thermal-infrared observations, available from 1983 to the present. The datasets are based on the disaggregation of 10-day (v2.0) and 5-day (v3.0) total TAMSAT rainfall estimates to a daily time-step using daily cold cloud duration. This approach provides temporally consistent historic and near-real time daily rainfall information for all of Africa. The estimates have been evaluated using ground-based observations from five countries with contrasting rainfall climates (Mozambique, Niger, Nigeria, Uganda, and Zambia) and compared to other satellite-based rainfall estimates. The results indicate that both versions of the TAMSAT daily estimates reliably detects rainy days, but have less skill in capturing rainfall amount—results that are comparable to the other datasets.
Highlights
Background and SummaryHigh spatial and temporal rainfall variability is a major challenge when it comes to managing agricultural activities across Africa, as above or below average rainfall can lead to crop losses and failure[1]
TAMSAT-2 and TAMSAT-3 are based on the disaggregation of the TAMSAT version 2.0 dekadal[18] and TAMSAT version 3.0 pentadal rainfall estimates respectively, to a daily time-step using daily calibrated cold cloud duration (CCD) observations
Given that the daily rainfall estimates derived from TAMSAT v2.0 have been in the public domain for several years and are used by many users, this paper formally evaluates both TAMSAT-2 and TAMSAT-3
Summary
High spatial and temporal rainfall variability is a major challenge when it comes to managing agricultural activities across Africa, as above or below average rainfall can lead to crop losses and failure[1]. While there is an ever growing collection of satellite-based datasets capable of providing near-real time estimates (a selection of which are listed in Table 1 in Maidment et al.18), only a handful of publicly available high resolution satellite-based datasets providing historic data (at least 30 years) at the daily time-step and which are continually updated in real time or near-real time, exist for Africa These are the National Oceanic Atmospheric Administration (NOAA) African Rainfall Climatology version 2.0 (ARC19) and the Climate Hazards Group InfraRed Precipitation with Station data version 2.0 (CHIRPS20) and are described in the Technical Validation section. TAMSAT-2 and TAMSAT-3 are based on the disaggregation of the TAMSAT version 2.0 dekadal[18] and TAMSAT version 3.0 pentadal rainfall estimates respectively, to a daily time-step using daily calibrated cold cloud duration (CCD) observations (see Methods section for algorithm details)
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