Data di Pubblicazione:
2021
Abstract:
During recent decades East Africa (EA) and Southern Africa (SA) have experienced an
intensification of hydrological hazards, such as floods and droughts, which have dramatically affected
the population, making these areas two of the regions of the African continent most vulnerable to
these hazards. Thus, precipitation monitoring and the evaluation of its variability have become
fundamentally important actions through the analysis of long-term data records. In particular,
satellite-based precipitation products are often used because they counterbalance the sparsity of
the rain gauge networks which often characterize these areas. The aim of this work is to compare
and contrast the capabilities of three daily satellite-based products in EA and SA from 1983 to 2017.
The selected products are two daily rainfall datasets based on high-resolution thermal infrared
observations, TAMSAT version 3 and CHIRPS, and a relatively new global product, MSWEP version
2.2, which merges satellite-based, rain gauge and re-analysis precipitation data. The datasets have
been directly intercompared, avoiding the traditional rain gauge validation. This is done by means of
pairwise comparison statistics at 0.25 spatial resolution and daily time scale to assess rain-detection
and quantitative estimate capabilities. Monthly climatology and spatial distribution of seasonality
are analyzed as well. The time evolution of the statistical indexes has been evaluated in order to
analyze the stability of the rain detection and estimation performances. Considerable agreement
among the precipitation products emerged from the analysis, in spite of the differences occurring
in specific situations over complex terrain, such as mountainous and coastal regions and deserts.
Moreover, the temporal evolution of the statistical indices has demonstrated that the agreement
between the products improved over time, with more stable capabilities in identifying precipitating
days and estimating daily precipitation starting in the second half of the 1990s.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
remote sensing; satellite; precipitation; long-tem dataset; Africa
Elenco autori:
Cattani, Elsa; Levizzani, Vincenzo
Link alla scheda completa:
Pubblicato in: