Constraint on regional land surface air temperature projections in CMIP6 multi-model ensemble

Abstract

The reliability of the near-land-surface air temperature (LSAT) projections from the state-of-the-art climate-system models that participated in the Coupled Model Intercomparison Project phase six (CMIP6) is debatable, particularly on regional scales. Here we introduce a new method of constructing a constrained multi-model-ensemble (CMME), based on rejecting models that fail to reproduce observed LSAT trends. We use the CMME to constrain future LSAT projections under the Shared Socioeconomic Pathways 5-8.5 (SSP5-8.5) in the 21st century; this scenario represents the high end of the range of future pathway uncertainty. In comparison with the “raw” (unconstrained) CMIP6 multi-model ensemble (MME) mean, the impact of the observation-based constraint is less than 0.1 oC/100years at global scale over the 21st century. However, the regional results show a wider range of positive and negative adjustments from -1.0oC/100years to 1 oC/100years. The ideal 1pctCO2 experiment suggests that the response of LSAT to carbon dioxide (CO2) forcing on regional scales is responsible for the MME biases in historical period, indicating the higher reliability of CMME in the 21st century projections. The advantage of CMME is that it goes beyond the idea of “model democracy” assumed in MME. The unconstrained CMIP6 MME may be overestimating the risks of future warming over North America, Europe, and North Africa, but underestimating the risks over Asia.

Surface Air Temperature Trend Over the Tibetan Plateau in CMIP6 and Its Constraint in Future Projection

“…Results in Zhang et al. (2023) indicate the relatively low capability of CMIP6 models in reproducing SAT trend over TP, which may be partly due to the relatively low resolution and uncertainty of the CRU data. Based on finer and more precise station observations in China, the constrained multi‐model ensemble method (CMME) introduced by Zhang et al.…”

“…However, in comparison with the Climatic Research Unit gridded data (CRU; Harris et al., 2020), Zhang et al. (2023) found that the CMIP6 MME has a relatively low capability in reproducing the SAT trend in the United States and Asia. Future projections in CMIP6 MME may overestimate the SAT‐rising risk over North America but underestimate the risk over Asia.…”

“…Based on finer and more precise station observations in China, the constrained multi‐model ensemble method (CMME) introduced by Zhang et al. (2023) will be used to calibrate future SAT trend projections over TP in this study. The observed SAT trend is calculated as the SAT trend in CN05.1 from 1961 to 2014 at each grid point over TP.…”

“…In this study, we evaluate the ability of the CMIP6 climate model in reproducing SAT over TP and try to calibrate its projections under different shared socio‐economic paths by a new ensemble averaging method (CMME) introduced in Zhang et al. (2023).…”