An observational study of the variability of East African rainfall with respect to sea surface temperature and soil moisture

Abstract

Rainfall from the October–November–December (OND) short rains season over East Africa (EA, 5°S–20°N, 28–52°E) were analysed during the 1983–2010 period using state‐of‐the‐art observational datasets. Links among satellite‐derived rainfall (Climate Hazards group InfraRed Precipitation with Station data, CHIRPS), sea surface temperature (Hadley Centre Sea ice and Sea Surface Temperature, HadISST1‐SST), soil moisture (Climate Change Initiative, CCI‐SM), and dynamical variables (European Centre for Medium‐Range Weather Forecasts Re‐Analysis, ERA‐Interim) are investigated to disentangle their specific role in shaping the rainfall variability over the region. In general, interannual rainfall variability is highest in the area during OND. Empirical orthogonal function (EOF) analysis is applied to the rainfall dataset to extract the dominant spatial and temporal patterns of variability. Results show that the rainfall variability is directly influenced by the SST variability in the Indian Ocean (Indian Ocean Dipole, IOD) and in the Pacific Ocean (El Niño–Southern Oscillation, ENSO), and by the local SM. The strong positive correlation (0.78) between EA short rain index and the IOD index indicates that the positive‐phase IOD (IOD+) plays a dominant role in driving OND rainfall. Moreover, IOD+ usually coincides with El Niño events and becomes stronger as the intensity of El Niño increases for years of joint events, and the Walker circulation is shifted accordingly. Furthermore, El Niño alone brings a reduction of rainfall over EA. The physical mechanism explaining the IOD+ link to EA rainfall consists of a Gill‐type response to warm western Indian Ocean SST anomalies that induces anomalous low‐level easterlies over the IO and leads to moisture convergence over EA. In general, the response of rainfall is opposite during the negative phase of the events (IOD− and La Niña).

East Africa Rainfall Trends and Variability 1983–2015 Using Three Long-Term Satellite Products

“…Between 1979 and 2012, an SST increase of 0.48 • C over the western Indian Ocean and a decrease of 0.26 • C over the eastern part were observed. Considering the strong correlation between the OND rainfall and the IOD [6,24], the mentioned SST variations over the Indian Ocean support the observed increasing trends. The long-term variability of short rains and its connections to large-scale factors were analyzed also by Nicholson [59] for a time period of 139 years (1874-2012), considering the relationships among rainfall and zonal wind at the surface and 200 hPa over the central equatorial Indian Ocean, Niño 3.4, and IOD indices.…”

“…The tendency of a decrease in JF PRCPTOT over the whole EA during the last years is perceivable, considering the PRCPTOT anomaly time series (Figure 9). A first period from 1985 to 1998 is characterized by a predominance of increasing positive anomalies, culminating with the prominent 1998 anomaly, a year when EA precipitation was enhanced by the simultaneous presence of El Niño and the positive IOD, starting from late 1997 [24]. A general decrease in the positive anomalies of all rainfall products then follows in favor of a predominance of negative anomalies.…”

Assessing the Impact of ENSO on Agriculture Over Africa Using Earth Observation Data

“…Relative to the long rainfall, the short rainfall appears to have higher inter-annual variability and a close association with ENSO resulting in a weaker vegetation effect of ENSO during or shortly after the ENSO post-phase compared to the peak phase (Wenhaji Ndomeni et al, 2018).…”

Satellite Remote Sensing of Precipitation and the Terrestrial Water Cycle in a Changing Climate

“…Drier regions of the world, such as East Africa, are frequently affected by severe droughts that are strongly linked to the seasonal cycles, intraseasonal and interannual variability, and local geography [267]. Satellite precipitation products can significantly help in understanding trends and variability of rainfall in the area [268] and their links with SST and soil moisture [269]. Moreover, they are starting to contribute significantly to devising strategies for managing the increased demand of groundwater connected with drought episodes [270,271], and to identifying trends in Africa's freshwater resources.…”