Radiative forcing is a crucial metric in climate modeling, with most models, including general circulation models (GCMs), examining how different atmospheric factors affect it. However, uncertainties remain in satellite observations and multi-model simulations, particularly concerning atmospheric elements like clouds and precipitation.
Precipitating particles influence radiative forcing by affecting incoming shortwave and outgoing longwave radiations. Conventional GCMs in the Coupled Model Intercomparison Project Phase 6 (CMIP6) often treat precipitation diagnostically and exclude the radiative effects of precipitation (REP). This omission presents challenges in extracting the magnitude of REP due to complex atmosphere-ocean feedback and multi-model variabilities.
A study led by Associate Professor Takuro Michibata from Okayama University, published in *npj Climate and Atmospheric Science* on June 19, 2024, explored REP’s influence on radiative forcing at various geographical scales. Dr. Michibata used three sub-versions of the Japanese GCM, MIROC6, incorporating different precipitation and radiative treatments: diagnostic precipitation without REP (DIAG), prognostic precipitation without REP (PROG REP-OFF), and prognostic precipitation with REP (PROG REP-ON). This approach quantified the impact of precipitating particles on radiation budgets and hydrological cycles globally and regionally.
Using 34 climate models from the CMIP6 data archive, the study examined REP’s effect on seasonal variations of Arctic amplification. The findings revealed that REP alters atmospheric circulation, affecting local thermodynamic profiles and remote precipitation rates. Precipitating particles reduce net shortwave radiation (“parasol effect”) and increase net longwave radiation (“warming effect”), particularly in the Arctic. This leads to a reduction in atmospheric radiative cooling and a slowdown in the global hydrological cycle.
Surface warming is more pronounced in polar regions, with winter temperatures increasing by more than 1 K on average, over twice the summer warming. This winter warming is stronger in simulations with REP included (PROG REP-ON). In contrast, tropical and subtropical regions showed smaller temperature variations, with precipitation changes being the main effect of REP.
The study highlights REP’s significant influence on the radiation budget and hydrological cycle at both global and regional scales, providing insights into REP’s impact on temperature and precipitation changes. Including REP in GCMs could improve precipitation and temperature biases, enhancing the accuracy of climate simulations against observational data.
“Given that the Arctic climate is remotely linked to mid-latitude meteorology and weather, this study will contribute to improving climate models for more accurate predictions of future climate change and extreme weather events. Additionally, understanding REP at a process level will be useful for other modeling groups in future model development.”
