scholarly journals East African rainfall seasonality based on modulated annual cycle (MAC)

2012 ◽  
Vol 7 (24) ◽  
Author(s):  
Zablone Owiti
Keyword(s):  
Annual Cycle ◽  
East African ◽  
African Rainfall ◽  
Rainfall Seasonality ◽  
Modulated Annual Cycle

scholarly journals Biases in CMIP5 Sea Surface Temperature and the Annual Cycle of East African Rainfall

2020 ◽  
Vol 33 (19) ◽  
pp. 8209-8223
Author(s):  
Bradfield Lyon
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Annual Cycle ◽  
General Circulation ◽  
Regional Scale ◽  
Sea Surface ◽  
East African ◽  
Coupled Models ◽  
African Rainfall ◽  
Short Rains

AbstractIn much of East Africa, climatological rainfall follows a bimodal distribution characterized by the long rains (March–May) and short rains (October–December). Most CMIP5 coupled models fail to properly simulate this annual cycle, typically reversing the amplitudes of the short and long rains relative to observations. This study investigates how CMIP5 climatological sea surface temperature (SST) biases contribute to simulation errors in the annual cycle of East African rainfall. Monthly biases in CMIP5 climatological SSTs (50°S–50°N) are first identified in historical runs (1979–2005) from 31 models and examined for consistency. An atmospheric general circulation model (AGCM) is then forced with observed SSTs (1979–2005) generating a set of control runs and observed SSTs plus the monthly, multimodel mean SST biases generating a set of “bias” runs for the same period. The control runs generally capture the observed annual cycle of East African rainfall while the bias runs capture prominent CMIP5 annual cycle biases, including too little (much) precipitation during the long rains (short rains) and a 1-month lag in the peak of the long rains relative to observations. Diagnostics reveal the annual cycle biases are associated with seasonally varying north–south- and east–west-oriented SST bias patterns in Indian Ocean and regional-scale atmospheric circulation and stability changes, the latter primarily associated with changes in low-level moist static energy. Overall, the results indicate that CMIP5 climatological SST biases are the primary driver of the improper simulation of the annual cycle of East African rainfall. Some implications for climate change projections are discussed.

Seasonal prediction of East African rainfall

2014 ◽  
Vol 35 (10) ◽  
pp. 2698-2723 ◽  
Author(s):  
Chia-Jeng Chen ◽  
Aris P. Georgakakos
Keyword(s):  
Seasonal Prediction ◽  
East African ◽  
African Rainfall

scholarly journals Reconciling Theories for Human and Natural Attribution of Recent East Africa Drying

2017 ◽  
Vol 30 (6) ◽  
pp. 1939-1957 ◽  
Author(s):  
Andrew Hoell ◽  
Martin Hoerling ◽  
Jon Eischeid ◽  
Xiao-Wei Quan ◽  
Brant Liebmann
Keyword(s):  
Global Warming ◽  
East Africa ◽  
Decadal Variability ◽  
Coupled Model ◽  
Western Pacific ◽  
East African ◽  
Coupled Models ◽  
Central Pacific ◽  
Model Simulations ◽  
African Rainfall

Abstract Two theories for observed East Africa drying trends during March–May 1979–2013 are reconciled. Both hypothesize that variations in tropical sea surface temperatures (SSTs) caused East Africa drying. The first invokes a mainly human cause resulting from sensitivity to secular warming of Indo–western Pacific SSTs. The second invokes a mainly natural cause resulting from sensitivity to a strong articulation of ENSO-like Pacific decadal variability involving warming of the western Pacific and cooling of the central Pacific. Historical atmospheric model simulations indicate that observed SST variations contributed significantly to the East Africa drying trend during March–May 1979–2013. By contrast, historical coupled model simulations suggest that external radiative forcing alone, including the ocean’s response to that forcing, did not contribute significantly to East Africa drying. Recognizing that the observed SST variations involved a commingling of natural and anthropogenic effects, this study diagnosed how East African rainfall sensitivity was conditionally dependent on the interplay of those factors. East African rainfall trends in historical coupled models were intercompared between two composites of ENSO-like decadal variability, one operating in the early twentieth century before appreciable global warming and the other in the early twenty-first century of strong global warming. The authors find the coaction of global warming with ENSO-like decadal variability can significantly enhance 35-yr East Africa drying trends relative to when the natural mode of ocean variability acts alone. A human-induced change via its interplay with an extreme articulation of natural variability may thus have been key to Africa drying; however, these results are speculative owing to differences among two independent suites of coupled model ensembles.

The relationship between Indian Ocean sea–surface temperature and East African rainfall

2005 ◽  
Vol 363 (1826) ◽  
pp. 43-47 ◽  
Author(s):  
Emily Black
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Southern Oscillation ◽  
Sea Surface ◽  
East African ◽  
African Rainfall ◽  
The Pacific ◽  
The Indian Ocean ◽  
The Relationship

Knowledge of the processes that control East African rainfall is essential for the development of seasonal forecasting systems, which may mitigate the effects of flood and drought. This study uses observational data to unravel the relationship between the Indian Ocean Dipole (IOD), the El Niño Southern Oscillation (ENSO) and rainy autumns in East Africa. Analysis of sea–surface temperature data shows that strong East African rainfall is associated with warming in the Pacific and Western Indian Oceans and cooling in the Eastern Indian Ocean. The resemblance of this pattern to that which develops during IOD events implies a link between the IOD and strong East African rainfall. Further investigation suggests that the observed teleconnection between East African rainfall and ENSO is a manifestation of a link between ENSO and the IOD.

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