Potential Regions of Strong Land-atmosphere Coupling Based on the S2S Project Database: Implications for the Indian Summer Monsoon Rainfall Variability
Wednesday, 16 December 2015
Poster Hall (Moscone South)
Advancing the understanding of land-ocean-atmosphere coupled processes and improving the prediction on the sub-seasonal to seasonal (S2S) time scale is important for several sectors such as agriculture, health, disaster management etc. The multi-model S2S database provides an ideal test bed for inter-comparison of model performance in this time scale and improving the understanding of coupled processes. Soil moisture and snow cover have been recognized as potential sources of predictability for temperature and precipitation on this time scale. They can play a crucial role through better initialization and improved representation of land surface processes. In this study, we focus on the identification of potential regions of strong land-atmosphere coupling during March-April-May (MAM) and June-July-August (JJA). A quantification of the land-atmosphere coupling strength in the models is also made on the basis of several coupling indices. Comparison with earlier studies helps us identify the regions where biases in the terrestrial and/or atmospheric segments may affect the overall land-atmosphere coupling strength in individual models. Better representation of land surface processes and accurate initialization of the land surface states during MAM has important implications for variability of Indian summer monsoon rainfall on sub-seasonal time scales, which is also addressed in this study.