Atmospheric moisture fluxes associated with heavy rainfall in the Indian and Australian monsoons simulated by CMIP6 models <sup> </sup> — Australian Meteorological and Oceanographic Society

Atmospheric moisture fluxes associated with heavy rainfall in the Indian and Australian monsoons simulated by CMIP6 models   (#230)

Ian G Watterson 1
  1. CSIRO Oceans and Atmosphere, Aspendale, VIC, Australia

Heavy rainfall on the tropical continents is closely linked to horizontal moisture transport or flux in the atmosphere. Using data available from the new ERA5 reanalyses and eight climate models contributing to the CMIP6 international experiment, the Indian and Australian summer monsoons are studied. Each model simulates the basic features of the two monsoons, as represented in ERA5, with detail that can depend on model resolution. Further, in each the rainfall from the top decile of monthly amounts at each grid point is closely correlated with the convergence of the vertically-integrated moisture flux. The intensity of the rainfall over northern Australia is stronger in models whose mean flux extends further southward into the continent.

The changes in the monsoons associated with global warming are investigated using the CMIP6 simulations with CO2 rising at 1% per year. Changes between 20-year periods 130 years apart are standardized by the global mean warming. In all eight models the eastward flux into India intensifies and rainfall increases both on the west coast and on the Himalayas, by differing amounts. Over tropical Australia, the changes vary considerably across the small ensemble, both for rainfall, the fluxes and the convergence. Rainfall increases or decreases, largely depending on the change in flux across the northern coast. For both continents, the change in ensemble mean rainfall, especially for the top decile of months, closely matches that in the associated convergence. The flux changes provide insight into the mechanisms for the differing monsoonal rainfall changes in the models, with implications for the uncertainty in projections of future change.

#amos2020