In our world natural climate variability is more and more overprinted by effects of human activity. Some expected outcomes are rather obvious: increased temperatures will, sooner or later, lead to less ice in the climate system, directly impacting both high latitudes and mountain regions. Other effects of anthropogenic activity on future climate are on the other hand more difficult to predict. While precipitation will overall increase due to basic physical principles, it is less clear how this change will be shaped across regions and over time. 

For many humans, monsoons are a precipitation pattern of very high relevance. Shifts in monsoon extent, timing, intensity, and extremes in a changing climate define health and safety, integrity of infrastructure, food security, and living conditions. Being able to understand evolution of monsoon systems is therefore a precondition to identify possible worst-case scenarios and to plan for mitigation. 

Yet, how can we know characteristics of monsoon in a warmer climate? This question can be answered with climate models that quantify monsoon patterns in dependence of climate forcings. Assumptions about future human activity then allow us to create an envelope of uncertainty of future monsoon characteristics. 

A big problem in this respect is the “size” of this envelope of uncertainty. Due to structure and parameters climate models have intrinsic uncertainties, resulting in uncertain future projections. Observations are always a good benchmark for performance of climate models. Yet, there is no reason to assume that a model that performs well against observational data of today, must necessarily also perform well for warmer climates. We should therefore test climate models against model-independent data - not only to derive a more robust assessment of future monsoons, but also to improve monsoon dynamics in our climate models. 

Paleoclimate research opens this possibility and has certain advantages over modern observational data. The latter is often used in model development and is therefore not model-independent, hampering model verification. Furthermore, the current climate does not yet show all characteristics of a warmer future. In paleoclimate research we must address differences in the degree of equilibrium of past vs. current climate. These may lead to different transient climate patterns. Therefore, paleoclimate is best employed to gain an understanding of the physical processes that are involved in shaping a specific monsoon characteristic that is different from today. This knowledge can then be applied to refine our understanding of future monsoon characteristics. 

Sun et al. (2024) study East Asian Summer Monsoon (EASM) of the mid-Piacenzian Warm Period (MPWP) - the most recent time, about 3 million years ago, when Earth experienced greenhouse gas concentrations like today. We base our work on an ensemble of climate models from the second phase of the Pliocene Model Intercomparison Project (PlioMIP2) that, beyond providing a best candidate for Pliocene climate, also enables separation of contributions by carbon dioxide and geographic differences. To consider transient climate, thereby allowing a transfer of results from equilibrium MPWP climate to a (transient) future state, we include results from transient greenhouse gas driven simulations of the Coupled Model Intercomparison Project, Phase 6. We compare precipitation patterns simulated by models with pollen-based precipitation records. A novelty of our study is that we apply an analysis method that enables us to track the impact of different physical processes on monsoon anomalies.

We find that the multi-model mean suggests an overall wetter East Asia in the MPWP due to increased net-precipitation, which is consistent with earlier qualitative records. Individual model simulations, on the other hand, show diverging precipitation response, and the agreement with pollen-based precipitation reconstructions is imperfect as the latter provide a more diverse picture of precipitation changes than the more uniform precipitation increase inferred from the model ensemble. Therefore, an important question arises: how can models and proxies be reconciled? 

We find that across the model ensemble enhanced EASM precipitation is predominantly controlled by thermodynamics, this means enhanced vertical water vapor transport in a warmer climate. On the other hand, tropical and subtropical MPWP EASM precipitation are controlled by different processes and moisture sources. Subtropical EASM is more related to horizontal moisture transport sourced from the western Pacific subtropical high while tropical EASM is fed from the Bay of Bengal. Based on forcing separation we infer that monsoon precipitation in equilibrium with elevated carbon dioxide is mostly due to increase in vertical and horizontal moisture transport, while transient carbon dioxide forcing enhances vertical moisture transport. Dynamic processes tend to reduce precipitation in transient climate and increase it in equilibrium climate, the difference owing to the lack of an increase in horizontal moisture transport in a transient state. 

What do we learn from these results about the agreement between models and reconstructions and about future monsoon characteristics? We can reconcile model-data discord by showing that certain physical processes do align with the changes in recorded precipitation. Nevertheless, remaining model-data disagreements, and appreciable uncertainty in details of simulated spatial monsoon patterns that exist for both MPWP and transient future climate, highlight that model structural and parameter-related uncertainties in the simulation of monsoon circulation should be further examined. In other words, while an ensemble of models reproduces various aspects of reconstructed precipitation, individual models have potential for improvement. On the other hand, EASM in a past warm climate, that was predominantly driven by increased carbon dioxide, shows similarities to EASM in future projections, where heat is based on increased carbon dioxide of anthropogenic origin. These inferences inform us on future evolution of EASM while outlining regionality of physical processes that drive precipitation in a warmer world. 

Reference 
Sun, Y., Wu, H., Ding, L. et al. Decomposition of physical processes controlling EASM precipitation changes during the mid-Piacenzian: new insights into data–model integration. npj Clim Atmos Sci 7, 120 (2024). https://doi.org/10.1038/s41612-024-00668-4