Spatiotemporal Characteristics and Trend Analysis of Two Evapotranspiration-Based Drought Products and Their Mechanisms in Sub-Saharan Africa

Abstract

Drought severity still remains a serious concern across Sub-Saharan Africa (SSA) due to its destructive impact on multiple sectors of society. In this study, the interannual variability and trends in the changes of the self-calibrating Palmer Drought Severity Index (scPDSI) based on the Penman–Monteith (scPDSIPM) and Thornthwaite (scPDSITH) methods for measuring potential evapotranspiration (PET), precipitation (P), normalized difference vegetation index (NDVI), and sea surface temperature (SST) anomalies were investigated through statistical analysis of modeled and remote sensing data. It was shown that scPDSIPM and scPDSITH differed in the representation of drought characteristics over SSA. The regional trend magnitudes of scPDSI in SSA were 0.69 (scPDSIPM) and 0.2 mm/decade (scPDSITH), with a difference in values attributed to the choice of PET measuring method used. The scPDSI and remotely sensed-based anomalies of P and NDVI showed wetting and drying trends over the period 1980–2012 with coefficients of trend magnitudes of 0.12 mm/decade (0.002 mm/decade). The trend analysis showed increased drought events in the semi-arid and arid regions of SSA over the same period. A correlation analysis revealed a strong relationship between the choice of PET measuring method and both P and NDVI anomalies for monsoon and pre-monsoon seasons. The correlation analysis of the choice of PET measuring method with SST anomalies indicated significant positive and negative relationships. This study has demonstrated the applicability of multiple data sources for drought assessment and provides useful information for regional drought predictability and mitigation strategies.

Spatio-Temporal Analysis of Drought Variability in Myanmar Based on the Standardized Precipitation Evapotranspiration Index (SPEI) and Its Impact on Crop Production

“…To estimate PET, the Penman-Monteith and Thornthwaite models are the two most widely used models. The former provides a better estimate due to its more comprehensive physics [4,14] but it is data intensive and requires more input data that are not usually readily available. The latter is simple as it requires mean monthly temperatures.…”

“…In addition, to understand possible climate changes implications on crop production, we conducted two separate analyses; the composite and correlational analysis. Reasons for selecting these two analyses is well articulated in [4,77]. Here, the study explored how to combined historical observations of crop production and weather and climate variables to explains crop production.…”

“…As a result, drought has gained attention from academia and other stakeholders [2][3][4]. Drought is a natural disaster [2,[5][6][7] that results in a negative impact on several sectors of society, such as, water resources [8], agriculture [8], ecosystems [9,10] and socio-economic impacts [9].…”

Future Changes in Simulated Evapotranspiration across Continental Africa Based on CMIP6 CNRM-CM6

“…Continental Africa is a climatologically diverse region located geographically between 32 • 00 N and 35 • 00 S and 14 • 00 W and 52 • 00 E. The continent has a huge landmass area stretching to nearly 30.37 million km 2 . The continent straddles the equator and is boarded to the southeast by the Indian Ocean, to the northeast by the Mediterranean Sea, and to the west by the Atlantic Ocean [56].…”

Projections of precipitation extremes based on bias‐corrected Coupled Model Intercomparison Project phase 6 models ensemble over southern Africa

“…Thus, changes in mean PRE substantially impact their livelihood (Kilroy, 2015; UNFCCC, 2017; Ahmadalipour et al ., 2019). Many parts of the world are experiencing extreme events (IPCC, 2021), with recent floods and droughts being the most notable examples (Fischer et al ., 2021; Nooni et al ., 2021a; 2021b; Ossó et al ., 2021). Dry spells and very heavy PRE events destruct agriculture, causing food insecurity (IPCC, 2021), and enormous ecological losses.…”