How well can CMIP5 simulate precipitation and its controlling processes over tropical South America

摘要: Underestimated rainfall over Amazonia was a common problem for the Coupled Model Intercomparison Project phase 3 (CMIP3) models. We investigate whether it still exists in CMIP 5 (CMIP5) models and, if so, what causes these biases? Our evaluation of historical simulations shows that some underestimate Amazonia. During dry season, both convective and large-scale precipitation is underestimated most GFDL-ESM2M IPSL notably show more pentads with no rainfall. wet In transition seasons, realistic moisture convergence surface evapotranspiration generally have totals. models, overestimates are associated adjacent tropical eastern Pacific ITCZs. However, other too much net radiation resultant high Bowen ratio appears to cause underestimates low pre-seasonal latent heat, sensible flux, weaker influence cold air incursions contribute bias. About half can capture, but overestimate, influences teleconnection. Based on simple metric, HadGEM2-ES outperforms especially conditions atmospheric circulation. has strongest bias presumably due its overestimate divergence, induced by overestimated ITCZs oceans, reinforced positive feedbacks between reduced cloudiness, suppression during weak extratropical disturbances season.