Evaluation of RCA & RCA GUESS and estimation of vegetation-climate feedbacks over India for present climate

English. Popular summary Changes in climate modify the terrestrial vegetation distribution that in turn affects the climate system by altering the balance of radiation, water, momentum, CO2 and other important atmospheric gases. This entire process is termed as vegetation-climate feedbacks. These feedbacks are studied by regional earth system model. In this study, RCA-GUESS, a regional earth system model, is applied over India to capture the influence of these feedbacks on the present climate. I also used a regional climate model, RCA and compared its results with RCA GUESS. However, before applying these regional models to a large area such as India, it is important to validate these models. Therefore, the aim of this study is to first assess the performance of RCA GUESS and RCA, a regional climate model, against some observation datasets for the period 1989-2005. Later, this study examines the influence of vegetation feedbacks on present climate of India. At the end, the future climate predictions will be made using RCA. The study found that RCA was not accurately simulating average surface temperature and precipitation for summer as well as for winter months. On the other hand, the regional earth system model, RCA GUESS also showed similar pattern of deviations but the irregularities in this model are explained to a certain extent over some regions by including dynamic vegetation and in some cases, the deviations were even amplified. It is suggested that both models require significant improvement in their structural design for correctly representing the climate and vegetation pattern for tropical region. The study also discussed the reasons of significant deviations present over mountainous regions which was also noticed when these models were applied over different regions such as Europe and South America. Since both models showed considerable uncertainty in predicting the present climate variables, therefore, it is very hard to deduce the actual impact of climate on vegetation pattern and vice versa. The study also found that India would experience overall warming of 1oC for the period 2031 to 2050 and the warming will be more pronounced over northern, western and central regions. The temperature of these regions rise as much as 1.5 to 2oC. These results are comparable with the findings of other studies. But, the major shift in the precipitation pattern is not properly captured.

English. Scientific summary There is a bidirectional relation between climate and vegetation distribution at local as well as global scale. Changes in climate pattern modify the terrestrial vegetation distribution that in turn affects the climate system by altering the balance of radiation, water, momentum, CO2 and other important atmospheric gases. The large-scale changes in vegetation structure and composition give rise to important climate relevant feedbacks (biophysical as well as biogeochemical). General circulation models that simulate future climate state do not take into account these interactions between land and atmosphere. Results from fairly recent studies bring forth the importance of including vegetation dynamics in order to predict the future climate more realistically. The physical changes in vegetation pattern such as changes in albedo, evapotranspiration, and surface roughness affect the climate pattern (i.e. through biophysical feedbacks) at regional scales, emphasizing the importance of coupling regional climate models with dynamic vegetation models. However, before applying the regional models to a large domain such as India, it is important to validate these models. Therefore, the aim of this study is to first assess the performance of RCA GUESS, a regional earth system model and RCA, a regional climate model, against observation datasets for the period 1989-2005. Later, the study examines the effect of vegetation feedbacks, more precisely biophysical feedbacks, on present climate of India. At the end, the future climate predictions will be made using RCA under IPCC’s future greenhouse gas scenario (SRES-A1B). The study found that RCA did not simulate average surface temperature and precipitation for summer as well as winter months quite reasonably. On the other hand, RCA GUESS also showed similar pattern of deviations but the biases in RCA GUESS are explained to a certain extent over some regions by including transient vegetation and in some cases the deviations were even amplified. This shows that Indian Climate is quite sensitive to vegetation change and it certainly plays a critical role in influencing the regional climate. However, still both models require significant improvement in their structural design for correctly representing the climate and vegetation pattern of tropical region. The study also discussed the reasons of significant biases present over mountainous region which was also noticed when these models are applied over different bioclimatic regions such as Europe and South America. Since both models showed considerable uncertainty in predicting the present climate variables, therefore, it is very hard to deduce the actual impact of climate on vegetation pattern and vice versa. However, the study also found that India would experience overall warming of 1oC under A1B scenario for the period 2031 to 2050 and the warming will be more pronounced over northern, western and central regions. The temperature of these regions rise as much as 1.5 to 2oC. These results are comparable with the findings of other studies. But, the major shift in the precipitation pattern is not properly captured. Overall, this study not only improved our current understanding of RCA and RCA GUESS performance over tropical country such as India but also form a basis for future studies using these models over that region.