A complete hydro-climate model chain to investigate the influence of sea surface temperature on recent hydroclimatic variability in subtropical South America (Laguna Mar Chiquita, Argentina)

Abstract

During the 1970s, Laguna Mar Chiquita (Argentina) experienced a dramatic hydroclimatic anomaly, with a substantial rise in its level. Precipitations are the dominant driving factor in lake level fluctuations. The present study investigates the potential role of remote forcing through global sea surface temperature (SST) fields in modulating recent hydroclimatic variability in Southeastern South America and especially over the Laguna Mar Chiquita region. Daily precipitation and temperature are extracted from a multi-member LMDz atmospheric general circulation model (AGCM) ensemble of simulations forced by HadISST1 observed time-varying global SST and sea-ice boundary conditions from 1950 to 2005. The various members of the ensemble are only different in their atmospheric initial conditions. Statistical downscaling (SD) is used to adjust precipitation and temperature from LMDz ensemble mean at the station scale over the basin. A coupled basin-lake hydrological model (cpHM) is then using the LMDz-downscaled (LMDz-SD) climate variables as input to simulate the lake behavior. The results indicate that the long-term lake level trend is fairly well depicted by the LMDz-SD-cpHM simulations. The 1970s level rise and high-level conditions are generally well captured in timing and in magnitude when SST-forced AGCM-SD variables are used to drive the cpHM. As the LMDz simulations are forced solely with the observed sea surface conditions, the global SST seems to have an influence on the lake level variations of Laguna Mar Chiquita. As well, this study shows that the AGCM-SD-cpHM model chain is a useful approach for evaluating long-term lake level fluctuations in response to the projected climate changes.