Evaluation of historical CMIP6 model simulations and future projections of temperature over the Pan-Third Pole region

Abstract

The Pan-Third Pole (PTP) region, which encompasses the Eurasian highlands and their surroundings, has experienced unprecedented, accelerated warming during the past decades. This study evaluates the performance of historical simulation runs of the Coupled Model Intercomparison Project (CMIP6) in capturing spatial patterns and temporal variations observed over the PTP region for mean and extreme temperatures. In addition, projected changes in temperatures under four Shared Socioeconomic Pathway (SSP) scenarios (SSP1‐2.6, SSP2‐4.5, SSP3-7.0, and SSP5‐8.5) are also reported. Four indices were used to characterize changes in temperature extremes: the annual maximum value of daily maximum temperature (TXx), the annual minimum value of daily minimum temperature (TNn), and indices for the percentage of warm days (TX90p) and warm nights (TN90p). Results indicate that most CMIP6 models generally capture the characteristics of the observed mean and extreme temperatures over the PTP region, but there still are slight cold biases in the Tibetan Plateau. Future changes of mean and extreme temperatures demonstrate that a strong increase will occur for the entire PTP region during the twenty-first century under all four SSP scenarios. Between 2015 and 2099, ensemble area-averaged annual mean temperatures are projected to increase by 1.24 °C/100 year, 3.28 °C/100 year, 5.57 °C/100 year, and 7.40 °C/100 year for the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. For TXx and TNn, the most intense warming is projected in Central Asia. The greatest number of projected TX90p and TN90p will occur in the Southeast Asia and Tibetan Plateau, respectively.

Quantification of The Performance of CMIP6 Models for Dynamic Downscaling in The North Pacific and Northwest Pacific Oceans

“…Similarly, the simulated trade winds are relatively weak, whereas the strength of the westerlies is well simulated compared with the reference. These results are consistent with those of previous studies that showed CMIP multi-model ensembles have positive or negative biases on a regional scale with respect to the surface and lateral boundary variables for the historical climate but reasonably reproduce their spatial distribution (e.g., Kim et al 2020;Zhang et al 2020;Fan et al 2022).…”

“…Numerous studies have examined the performance of CMIP6 models on global and regional scales (e.g., Eyring et al 2016;Kim et al 2020;Lee et al 2021;Planton et al 2021;Tang et al 2021;Xie et al 2022). CMIP6 models have been reported to realistically reproduce mean and extreme climates compared to observations, and their performances have improved compared to those of previous phase CMIP models (e.g., Kim et al 2020;Xie et al 2022;Fan et al 2022). These model evaluation studies have been mainly conducted in the atmospheric fields connected with the international regional-atmosphere climate model project known as the COordinated Regional climate Downscaling EXperiment (CORDEX; Oh et al 2014;Torres-Alavez et al 2021), and model performances have often been evaluated based on habitable land areas rather than the ocean region (e.g., Kim et al 2020;Xie et al 2022;Fan et al 2022).…”

Evaluation of CMIP6 Models and Multi-Model Ensemble for Extreme Precipitation over Arid Central Asia

“…In recent years, extensive studies have been conducted on evaluating and projecting extreme climate change over ACA. The prediction studies of temperature and temperature converge, with a significant warming trend expected for the 21st century [20,[35][36][37], while the simulation and prediction of extreme precipitation are more uncertain [9,38]. Li et al [27] showed that almost all models (HighResMIP) overestimated the precipitation frequency in CA, with a greater overestimation of the precipitation frequency and amount in mountainous areas.…”

Emergent Constraints on Future Projections of Tibetan Plateau Warming in Winter

“…Chen & Zhou, 2016;Sharmila et al, 2015). All models project that the TP surface temperature will continue to increase under future warming climate (e.g., Fan et al, 2022;Guo et al, 2016;F. Su et al, 2013), but consensus on its future warming magnitude remains lacking.…”

“…Climate models are widely used to study the future projections of climate change (e.g., Beniston et al., 2007; X. Chen & Zhou, 2016; Sharmila et al., 2015). All models project that the TP surface temperature will continue to increase under future warming climate (e.g., Fan et al., 2022; Guo et al., 2016; F. Su et al., 2013), but consensus on its future warming magnitude remains lacking. The magnitude of temperature increase could be influenced by emission scenarios (Tian et al., 2015; You, Cai, Wu, et al., 2021; M. Zhou et al., 2022), with the projected difference between the very high and very low emission scenarios reaching as much as 6°C by the end of the 21st century (Y. Peng et al., 2022).…”