PNNL

The Science                                

Global climate models have large uncertainty in projecting future precipitation changes. Researchers developed and used a simple Lagrangian parcel model to investigate the effects of global warming on mesoscale convective system (MCS) initiation and growth. The parcel model projects a decrease in average precipitation over the central U.S. and an increase in the east, which is in agreement with the Coupled Model Intercomparison Project 5 (CMIP5) model projections. The results show that bias in CMIP5 exaggerates the change in future average precipitation by 25%. The parcel model captures changes in convection, the movement of air due to temperature differences, including the reduced occurrence of weak-to-moderate convection and the increased frequency of strong convection. The parcel model also projects smaller mesoscale clusters under global warming.

The Impact

Because global climate models (GCMs) represent convection using simplified representations, they have large uncertainty in projecting future changes in convection and precipitation. Convection-permitting models explicitly resolve convection and may provide more robust future projections. However, their large computational demand limits their use. This study shows that simple parcel models can be used to diagnose the impacts of GCM model biases on future projections and reproduce features of convection changes projected by convection-permitting models. Simple parcel models can be used to understand the mechanisms of future changes in convection and precipitation to guide GCM development and inform analysis of convection permitting climate change simulations.

Summary

This study investigated the effect of global warming on the convective initiation and genesis of summertime MCSs over the U.S. based on a simple Lagrangian parcel model. The results highlight the key mechanisms responsible for MCS behavior changes during the convective initiation and MCS genesis stages in the future climate. By using the single-column model, researchers first explored changes in the average precipitation between the current and future climate under global warming and compared them with CMIP5 model projections. The simple model provides an analog testbed to illustrate how CMIP5 model biases in the current climate affect predictions of future mean precipitation. The research then examined the changes in the distribution of precipitation across convective events as well as their dependence on geographic location. A multi-column model was then used to identify potential changes of the MCS final state caused by several mechanistic processes under global warming. The simple model itself provides an efficient tool to evaluate environmental profiles to determine if they favor convection in both the current and future climate.3.53% and 4.19±2.28%, respectively in the raw ensemble-model projection to 7.03±2.59% and 4.63±1.71%. This constraint thus suggests a higher global mean precipitation increase and reduces the uncertainty by ~25%, providing valuable information for impact assessments.

PNNL Contact

L. Ruby Leung, Pacific Northwest National Laboratory, ruby.leung@pnnl.gov

Funding

All authors were supported by the Department of Energy’s Office of Science Biological and Environmental Research program’s Regional and Global Climate Model Analysis program area.