The hydroclimate of East Africa shows distinctive variabilities on seasonal to decadal time scales and poses a great challenge to climatologists attempting to project its response to anthropogenic emissions of greenhouse gases (GHGs). Increased frequency and intensity of droughts over East Africa in recent decades raise the question of whether the drying trend will continue into the future. To address this question, we first examine the decadal variability of the East African rainfall during March to May (MAM, the major rainy season in East Africa) and assess how well a series of models simulate the observed features. Observational results show that the drying trend during MAM is associated with decadal natural variability of sea surface temperature (SST) variations over the Pacific Ocean. The multimodel mean of the SST forced, Coupled Model Intercomparison Project Phase 5 (CMIP5) AMIP experiment models reproduces both the climatological annual cycle and the drying trend in recent decades. The fully coupled models from the CMIP5 historical experiment, however, have systematic errors in simulating the East African rainfall annual cycle by underestimating the MAM rainfall while overestimating the October to December (OND, the second rainy season in East Africa) rainfall. The multimodel mean of the historical coupled runs of the MAM rainfall anomalies, which is the best estimate of the radiatively forced change, shows a weak wetting trend associated with anthropogenic forcing. However, the SST anomaly pattern associated with the MAM rainfall has large discrepancies with the observations.
The errors in simulating the East African hydroclimate with coupled models raise questions about how reliable model projections of future East African climate are. This motivates a fundamental study of why East African climate is the way it is and why coupled models get it wrong. East African hydroclimate is characterized by a dry annual mean climatology compared to other deep tropical land areas and a bimodal annual cycle with the major rainy season during MAM (often called the ``long rains'' by local people) and the second during OND (the ``short rains''). To explore these distinctive features, we use the ERA Interim Re Analysis data to analyze the associated annual cycles of atmospheric convective stability, circulation and moisture budget. The atmosphere over East Africa is found to be convectively stable, in general, year round but with an annual cycle dominated by the surface moist static energy (MSE), which is in phase with the precipitation annual cycle. Throughout the year, the atmospheric circulation is dominated by a pattern of convergence near the surface, divergence in the lower troposphere and convergence again at upper levels. Consistently, the convergence of the vertically integrated moisture flux is mostly negative across the year, but becomes weakly positive in the two rainy seasons. It is suggested the semi-arid/arid climate in East Africa and its bimodal rainfall annual cycle can be explained by the ventilation mechanism, in which the atmospheric convective stability over East Africa is controlled by the import of low MSE air from the relatively cool Indian Ocean off the coast and the cold winter hemisphere. During the rainy seasons, however, the off coast SST increases (and is warmest during the long rains season) and the northerly or southerly weakens, and consequently the air imported into East Africa becomes less stable.
The MSE framework is then applied to study the coupling induced bias of the East African rainfall annual cycle often found in CMIP3/5 coupled models that overestimates the OND rainfall and underestimates the MAM rainfall, by comparing the historical (coupled) and the AMIP runs (SST forced) for each model. It is found that a warm north and cold south SST bias over the Indian Ocean induced in coupled models is responsible for the dry MAM rainfall bias over East Africa while the ocean dynamics induced warm west and cold east SST bias over the Indian Ocean contributes to the wet OND rainfall bias in East Africa.
Finally, to understand the East African regional climate in the context of the broader tropical climate and circulation, zonal momentum balance of the tropical atmospheric circulation during the global monsoon mature months (January and July) are analyzed in three dimensions based on the ERA-Interim Re-Analysis. It is found that the dominant terms in the balance of the atmospheric boundary layer (ABL) in both months are the pressure gradient force, the Coriolis force and friction. The nonlinear advection term plays a significant role only in the Asian summer monsoon regions including off East Africa. In the upper troposphere, the pressure gradient force, the Coriolis force and nonlinear advection are the dominant terms. The transient eddy force and the residual force (which can be explained as convective momentum transfer over open oceans) are secondary yet can not be neglected near the equator. Zonal mean equatorial upper troposphere easterlies are maintained by the absolute angular momentum advection associated with the cross equatorial Hadley circulation. Equatorial upper troposphere easterlies over the Asian monsoon regions are also controlled by the absolute angular momentum advection but are mainly maintained by the pressure gradient force in January. The equivalent linear Rayleigh friction, which is widely applied in simple tropical models, is calculated and the corresponding spatial distribution of local coefficient and damping time scale are estimated from the linear regression. It is found that the linear momentum model is in general capable of crudely describing the tropical atmospheric circulation dynamics yet the caveat should be kept in mind that the friction coefficient is not uniformly distributed and is even negative in some regions.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D8J96547 |
| Date | January 2015 |
| Creators | Yang, Wenchang |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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