The contrasting effects of thermodynamic and dynamic processes on East Asian summer monsoon precipitation during the Last Glacial Maximum: a data-model comparison

The Last Glacial Maximum (LGM; 21 ka BP) was the most recent glacial period when the global ice sheet volume was at a maximum. Therefore, the LGM can be used to investigate atmospheric dynamics under a climate that differed significantly from the present. This study quantitatively compares pollen records of boreal summer (June–July–August) precipitation with the PMIP3 LGM simulations. The data-model comparison shows an overall agreement on a drier than pre-industrial East Asian summer monsoon (EASM) climate. Nevertheless, 17 out of 55 records show a regional precipitation increase that is also simulated over the additional land mass area due to sea level drop. The thermodynamic and dynamic responses are analyzed to explain a drier LGM EASM as a combination of these two antagonistic mechanisms. Relatively low atmospheric moisture content was the main thermodynamic control on the lower LGM (relative to pre-industrial levels) EASM precipitation amounts in both the reconstructions and the models. In contrast, two dynamic processes in relation to stationary eddy activity act to increase EASM precipitation regionally in records and simulations, respectively. Precipitation increase in records is explained by dynamic enhancement of the horizontal moisture transport, while dynamic enhancement of the vertical moisture transport leads to simulated precipitation increase over the specific region where landmass was exposed during LGM along continental coastlines of China due to significant drop in sea level (relative to pre-industrial levels). Overall, the opposing effects of thermodynamic and dynamic processes on precipitation during the LGM provide a means to reconcile the spatial heterogeneity of recorded precipitation changes in sign, although data-model comparison suggests that the simulated dynamic wetting mechanism is too weak relative to the thermodynamic drying mechanism over data-model disagreement regions.