Subseasonal convection variability over the Intra‐American Seas simulated by an AGCM and sensitivity to CMIP5 SST biases and projections

Abstract

AbstractThe influence of coupled model sea surface temperature (SST) climatological biases and SST projections on daily convection over the Intra‐American Seas (IAS) during the May–November rainy season are examined by clustering (k − means) daily OLR anomalies in ECHAM5 atmospheric global climate model (AGCM) experiments. The AGCM is first forced by 1980–2005 observed SSTs (GOGA), then with climatological, multi‐model mean monthly climatological SST bias from 31 CMIP5 coupled models (HIST) and projected SST changes for 2040–2059 (PROJ) and 2080–2099 (PROJ2) imposed on top of observed values. A typology of seven recurrent convection regimes is identified and consists of three dry and four wet regimes, including three regimes characterized by tropical‐midlatitude interactions between surface convection cells across the IAS and Rossby wave in the upper‐troposphere, and a regime of broad wettening typical of the ITCZ. Compared to an earlier observational study, all seven regimes are reasonably well reproduced in the HIST runs. However, the latter exhibit drier dry regimes, a less wet ITCZ‐like wet regime and a southeastward shift of convective anomalies developing across the IAS in the three other regimes, all result in a drier simulated IAS climate compared to GOGA. ECHAM5 projection runs for PROJ and PROJ2 are both characterized by the inhibition of the broad ITCZ‐like wet regime, indicating a significant trend towards more frequent dry weather. Meanwhile, convection anomalies related to tropical‐midlatitude interactions are shifted further east of the Caribbean as lead increases. These results suggest more frequent and intense extreme rainfall over the tropical Atlantic and the southeast US, while parts of the Caribbean are projected to experience drier climate. The projected drying, however, is of the same order of magnitude as results from historical SST biases, suggesting that the latter need to be considered in model projections, which might underestimate future IAS drying.