Atmosphere (Feb 2023)

Climatic and Vegetation Response Patterns over South Africa during the 2010/2011 and 2015/2016 Strong ENSO Phases

  • Lerato Shikwambana,
  • Kanya Xongo,
  • Morwapula Mashalane,
  • Paidamwoyo Mhangara

DOI
https://doi.org/10.3390/atmos14020416
Journal volume & issue
Vol. 14, no. 2
p. 416

Abstract

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El Niño-Southern Oscillation (ENSO) is a significant climate phenomenon on Earth due to its ability to change the global atmospheric circulation which influences temperature and precipitation across the globe. In this study, we investigate the responses of climatic and vegetation parameters due to two strong ENSO phases, i.e., La Niña (2010/2011) and El Niño (2015/2016) in South Africa. The study aims to understand the influence of strong seasonal ENSO events on climatic and vegetation parameters over South Africa. Remote sensing data from the Global Precipitation Measurement (GPM), Moderate Resolution Imaging Spectroradiometer (MODIS), Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and Atmospheric Infrared Sounder (AIRS) was used. The relationship between precipitation, temperature, and Normalized Difference Vegetation Index (NDVI) were studied using Pearson’s correlation. Comparison between the La Niña, neutral year, and El Niño periods showed two interesting results: (1) higher precipitation from the south coast to the east coast of South Africa, with some low precipitation in the interior during the La Niña and El Niño periods, and (2) a drop in precipitation by ~46.6% was observed in the southwestern parts of South Africa during the La Niña and El Niño events. The study further showed that wind speed and wind direction were not impacted by strong ENSO events during the MAM, JJA and SON seasons, but the DJF season showed varying wind speeds, especially on the west coast, during both ENSO events. Overall, the Pearson’s correlation results clearly showed that the relationship between climatic parameters such as precipitation, temperature, and vegetation parameters such a NDVI is highly correlated while other parameters, such as wind speed and direction, are not. This study has provided new insights into the relationship between temperature, precipitation, and NDVI in South Africa; however, future work will include other climatic and vegetation parameters such as relative humidity and net longwave radiation.

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