Application of self-organizing-maps technique in downscaling GCMs climate change projections for Same, Tanzania
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Date
2010
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Abstract
High resolution surface climate variables are required for end-users in climate change impact studies; however, information provided by Global Climate Models (GCMs) has a coarser resolution. Downscaling techniques such as that developed at the University of Cape Town, which is based on Self-Organizing Maps (SOMs) technique, can be used to downscale the coarse-scale GCM climate change projections into finer spatial resolutions; but that must be combined with verification. The SOM downscaling technique was employed to project rainfall and temperature changes for 2046-2065 and 2080-2100 periods for Same, Tanzania. This model was initially verified using downscaled NCEP reanalysis and observed climate data set between 1979 and 2004, and between NCEP reanalysis and GCM controls (1979 - 2000). After verification, the model was then used to downscale climate change projections of four GCMs for 2046-2065 (future-A) and 2080-2100 (future-B) periods. These projections were then used to compute changes in the climate variables by comparing future-A and B to the control period (1961-2000). Verification results indicated that the NCEP downscaled climate data compared well with the observed data. Also, comparison between NCEP downscaled and GCM downscaled showed that all the four GCM models (CGCM, CNRM, IPSL, and ECHAM) compared well with the NCEP downscaled temperature and rainfall data. Future projections (2046-2065) indicated 56 mm and 42 mm increase in seasonal total rainfall amounts for March-April-May (MAM) and October-November-December (OND) (23% and 26% increase), respectively; and a temperature increase of about 2°C for both seasons. Furthermore, it was found that during MAM there will be a decrease in dry spells by 2 days, and an increase in seasonal length by 8 days, while for OND, there will be also 2 days decrease in dry spells, and 40 days increase in the seasonal length. The results for future-B shows a 4°C rise in temperature, and 46.5% and 35.8% increase in rainfall for MAM and OND, respectively. The results imply a better climatic future for the area because of the increase in the amount of rainfall and decrease in dry spells. However, it is suggested that further investigations are required to see if the projected changes will have real positive effects in agricultural production and also identify better agronomic practices that will take advantage of the opportunities.
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Keywords
Climate change, Downscaling, Self Organizing Maps, GCMs