Deriving Useful Information from Bimonthly Global-Scale Climate Analysis for Climate Change Adaptation Over East Africa
Implementation of appropriate climate change adaptation strategies is contingent on a good understanding of climate variability. Efforts to adapt to climate change impacts in East African societies have flourished. However, an area of research which has been neglected and could enhance adaptive capacity is bimonthly global-scale climate analysis in relationship to the long rains, during the climatologically prominent phase of El Niño Southern Oscillation (ENSO). Empirical analyses were carried out using nearly 60 years of standardized gridded rainfall, horizontal wind and sea surface temperature (SST) data, to gain predictive understanding of the region’s climate. This study has delineated SST and divergent circulation features related to three of the four rainfall modes. The modes responded differently to the Pacific ENSO, Atlantic and Indian Oceans. However, there was no clear relationship between the second mode and the global SST distributions. Having substantiated this with monthly and seasonal-scale SST analyses, it suggested that this atypical pattern warranted numerical modeling studies or should be verified using other high resolution datasets. The SST predictor features identified may be used to enhance operational seasonal climate prediction scheme. In this way, end users would be better prepared to select appropriate climate change adaption options.
KeywordsEast Africa Standardized global sea surface temperature anomalies Standardized upper level circulations anomalies Long rainfall modes
The authors wish to acknowledge the following data sources: NCEP/NCAR reanalysis, CRU gridded precipitation data, and NOAA ERSST.
- Akponikpè, P. B., Ge´rard, I. B., Michels, K., & Bielders. C. L. (2010) Use of the APSIM model in long term simulation to support decision making regarding nitrogen management for pearl millet in the Sahel. In Journal of European Agronomy, 32, 144–154.Google Scholar
- Funk, C. (2012). Exceptional warming in the Western Pacific-Indian Ocean Warm Pool has contributed to more frequent droughts in Eastern Africa. In Bulletin of American Meteorological Society, 7, 1049–1051.Google Scholar
- Johnson, R. A., & Wichern, D. W. (2007). Applied multivariate statistical analysis (6th ed.). New Jersey, USA: Pearson Education, INC.Google Scholar
- Marchant, R., Mumbi, C., Behera, S., & Yamagata, T. (2006). The Indian Ocean dipole—the unsung driver of climatic variability in East Africa. In African Journal of Ecology, 45, 4–16.Google Scholar
- Saji, N. H., Goswami, B. N., Vinayachandran, P. N., & Yamagata, T. (1999). A dipole mode in the tropical Indian Ocean. In Nature, 401, 360–363.Google Scholar
- Smith, K. A., & Semazzi, F. H. M. (2014). The role of the dominant modes of precipitation variability over Eastern Africa in modulating the hydrology of lake victoria. In Advances in Meteorology, 11. Article ID 516762, http://dx.doi.org/10.1155/2014/516762
- Tetteh, I. K. (2012). West African seasonal climate variability and predictability, PhD thesis, North Carolina State University.Google Scholar
- Washington, R., Harrison, M., Conway, D., Black, E., Challinor, A., Grimes, D., et al. (2006). African climate change—Taking the shorter route. In Bulletin of American Meteorological Society, 1355–1366.Google Scholar
- Wilks, D. S. (2006). Statistical methods in the atmospheric sciences (3rd ed.). New York, USA: Academic Press.Google Scholar