On the Relationship between Mean Monsoon Precipitation and Low Pressure Systems in Climate Model Simulations

Abstract

AbstractThe north-northwest-propagating low pressure systems (LPS) are an important component of the Indian summer monsoon (ISM). The objective detection and tracking of LPS in reanalysis products and climate model simulations are challenging because of the weak structure of the LPS compared to tropical cyclones. Therefore, the skill of reanalyses and climate models in simulating the monsoon LPS is unknown. A robust method is presented here to objectively identify and track LPS, which mimics the conventional identification and tracking algorithm based on detecting closed isobars on surface pressure charts. The new LPS tracking technique allows a fair comparison between the observed and simulated LPS. The analysis based on the new tracking algorithm shows that the reanalyses from ERA-Interim and MERRA were able to reproduce the observed climatology and interannual variability of the monsoon LPS with a fair degree of accuracy. Further, the newly developed LPS detection and tracking algorithm is also applied to the climate model simulations of phase 5 of the Coupled Model Intercomparison Project (CMIP5). The CMIP5 models show considerable spread in terms of their skill in LPS simulation. About 60% of the observed total summer monsoon precipitation over east-central India is found to be associated with LPS activities, while in model simulations this ratio varies between 5% and 60%. Those models that simulate synoptic activity realistically are found to have better skill in simulating seasonal mean monsoon precipitation. The model-to-model variability in the simulated synoptic activity is found to be linked to the intermodel spread in zonal wind shear over the Indian region, which is further linked to inadequate representation of the tropical easterly jet in climate models. These findings elucidate the mechanisms behind the model simulation of ISM precipitation, synoptic activity, and their interdependence.