Assessment of Dry and Wet Events in Togo (2001-2019) using the Standard Precipitation Index and their relationship with Ocean-Atmosphere Climate Variability Modes

Abstract

Togo's economy is based mainly on agriculture, which represents 40% of the country's GDP. Therefore, like most West African countries, Togo is highly vulnerable to extreme climate events, remarkably rainfall variability. In this study, dry and wet events in Togo at local and regional scales during the period 2001-2019, were assessed using the Standard Precipitation Index (SPI). Monthly rainfall dataset from the Integrated Multi-satellitE Retrievals for GPM (IMERG) rainfall estimation and rain-gauge measurement from 9 meteorological stations across Togo were used for this purpose. Previously, an intercomparison study between rain gauge monthly rainfall and IMERG estimation was performed. Furthermore, based on correlation analysis, the SPI relationship with the climate indices Nino 3.4 and SAODI was investigated in order to explore, respectively, the influence of ENSO and SAOD on Togo rainfall. The results demonstrated that IMERG rainfall could reproduce the main temporal and spatial features of precipitation across Togo. For instance, the seasonal precipitation distribution and also the interannual anomalies. Nevertheless, regarding the seasonal variability, essential deviations from rain gauge occurred in the coastal area, specifically at Lomé, and underestimation in the high elevation areas, especially at Kouma Konda. The SPI analysis using rain gauge measurement and IMERG rainfall at a local scale also showed that IMERG could capture the occurrence of significant wet and dry periods in Togo. Based on the SPI results, two major climate periods were identified, one dominated by wet events from 2008 to 2010 and a second marked by severe and extreme dry events from 2013 to 2015. Finally, based on the correlation analysis between regional SPI and Nino 3.4 and SAODI, the results showed : a) low to moderate positive correlation with SAODI across Togo regions, with the highest correlation for Maritime and Plateaux regions; b) those correlations are stronger during the West Africa Monsoon season; c) that the signature of SAODI was consistent with the severe lack of precipitation (negative phase) during the 2013, 2014 and 2015 years, and also with a large amount of precipitation (positive phase) observed in 2007, 2008 and 2009, during which Togo experienced the most recent severe flooding events; d) weak, negative and not statistically significant correlation between Nino 3.4 index and SPI for all Togo regions. In conclusion, IMERG reproduced consistently the main features of seasonal and spatial variation of rainfall and also was able to capture the majors dry and wet events over Togo for the study period.