22nd Conference on Climate Variability and Change

106

The effects of altered vegetation on local climate change with respect to glaciers atop Mt. Kilimanjaro

Sean Heuser, North Carolina State University, Raleigh, NC; and F. Semazzi

Tropical glaciers are an important indicator of climate change (Houghton et al., 2001; Oerlemans, 2001) and they feature prominently in the IPCC climate change studies (IPCC AR4). Perhaps the best recognized tropical glacier is the cap of Mount Kilimanjaro, located along the border of Kenya and Tanzania, which has exhibited dramatic recession during the recent decades. The amount of ice over the mountain has decreased by 82% compared to its volume in 1910 (Thompson, 2002). Studies of the Kilimanjaro glacier indicate that the temperature of the region has fluctuated only slightly on the annual timescale (Hastenrath, 1991) and the sharp decrease in precipitation is considered to be the main cause of the glacier recession (Kaser et al., 2004). Mt. Kilimanjaro is located approximately 370 km south of the equator and about the same distance west of the Indian Ocean along the Kenya-Tanzanian border (3°04'S, 37°21'E) (Mölg and Hardy, 2004). At 5893m, Kilimanjaro is the highest mountain in Africa, and its climate is dominated by the biannual passage of the Intertropical Convergence Zone (ITCZ) over the region. There are two distinct rainy seasons typically known as the ‘long rains‘ of March through May and the ‘short rains' which occur during the months of October through December. These two seasons account for more than 80% of the precipitation (Coutts, 1969; Basalirwa et al., 1999). Thermal homogeneity is observed on the mountain with temperature values varying less than 2°C annually (Hardy et al., 1998; Mölg and Hardy, 2004).

The objective of this study is to determine if changes in vegetation around the region of Mount Kilimanjaro enhance or inhibit the glaciers atop the mountain. Using the Weather Research and Forecasting Model (WRF) Advanced Research WRF (ARW) model, a series of simulations are run during the short rains of East Africa for the year 2000. Three simulations were performed with a default albedo, an albedo reduction from 0.22 to 0.18, and an albedo increase from 0.22 to 0.25. The changes show small impacts on the seasonal temperature values near the top of the mountain with temperatures decreasing in both cases (0.12% in the 0.25 scenario and 0.02% in the 0.18 scenario). However, precipitation changes are more significant with a 6.6% decrease in the 0.18 case and a 2.5% increase in the 0.25 case. The changes in precipitation are influenced significantly by the amount of shortwave radiation absorbed at the surface. The increase in shortwave radiation in the 0.25 case triggered more convection leading to more precipitation. The opposite effect is noticeable in the 0.18 scenario. These changes led to an increase in latent heat flux which we believe would tend to accelerate sublimation atop the mountain. Our modeling results support our hypothesis that the response of precipitation to land use change is significantly greater than that of temperature, and therefore a more likely factor for modulating the glacial volume over Kilimanjaro summit.

Initially we have focused on changes in albedo as a proxy for land use change. Future work will extend this preliminary investigation to include ensemble simulations, simulations of the seasons of the annual cycle, evapotranspiraton and surface effects of vegetation forcing, and the combined effect of all the three vegetation factors to infer the total effect of vegetation anomalies on glacier recession.

References

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Basalirwa, C.P.K., J.O. Odiyo, R.J. Mingodo, E.J. Mpeta, 1999. The climatological regions of Tanzania based on the rainfall characteristics. International Journal of Climatology. 19: 69-80.

Hardy, D.R., M. Vuille, C. Braun, F. Keimig, R.S. Bradley, 1998. Annual and daily meteorological cycles at high altitude on a tropical mountain. Bulletin of the American Meteorological Society 79: 1899-1913.

Poster Session , Seasonal to Interannual Variability: Observations and Predictions
Tuesday, 19 January 2010, 9:45 AM-11:00 AM

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