Evaluation of events of extreme temperature change between neighboring days in CMIP6 models over China

Abstract

In the context of global warming, the frequency and intensity of extreme weather and climate events are increasing. However, the impact of these changes that is directly felt by people is the day-to-day temperature change. Extreme temperature changes between neighboring days (ETCNs) carry substantial disease risks and socioeconomic impacts. Evaluative studies of ETCN events with global circulation models (GCMs) remain unknown in China. This study quantitatively evaluates the performances of 36 GCMs and the multi-model ensemble (MME) of the Coupled Model Intercomparison Project 6 (CMIP6) in simulating the extreme cooling (EC) and extreme warming (EW) events of two consecutive days as defined by relative thresholds. Moreover, we select the optimal models in different regions at the seasonal and annual scales in China, providing theoretical support for the frequency projection and modeling improvement of ETCN events. The results showed that from 1981 to 2013, the annual average EW events and EC events in China showed increasing but not statistically significant trends, and the frequency of EW events was higher than that of EC events. EW events mostly occurred in spring, while EC events mostly occurred in autumn.Additionally, the performances of the CMIP6 models are quite different between EC and EW events.The simulations of EC events are generally more reliable than those of EW events, and the models can also capture the annual cycle of EC events well. Furthermore, the CMIP6 models overestimate the frequencies of EW and EC events but underestimate the frequency of EC events in autumn. The CMIP6 models exhibit poor performance in simulating the trend of and interannual variability in ETCN events and can only simulate the decreasing trend in autumn. Finally, according to the overall ranking of the CMIP6 models, GFDL-ESSM4 and EC-Earth3-Veg-LR achieve the best performance in simulating EW and EC events, respectively. The CMIP6 MME only effectively improved the capabilities of the models to simulate winter EC events in the WNW region. In terms of the trend of and interannual variability in ETCN events, individual models exhibited better performances than the CMIP6 ensemble.

Sources and paths of extreme cold surges over China and their associated atmospheric circulations

“…The ECS paths sourced near Scandinavia (labelled S‐type) were more complex and needed to be further classified according to the locations of entry. The S‐type ECSs entering China from the east (east of the 115°E), middle (95–115°E) and west (west of 95°E) were further divided into S1‐type, S2‐type and S3‐type ECSs (Ma et al, 2022a, 2022b; Song and Yan, 2022; Figure 2).…”

“…The ECS paths sourced near Scandinavia (labelled S-type) were more complex and needed to be further classified according to the locations of entry. The S-type ECSs entering China from the east (east of the 115 E), middle (95-115 E) and west (west of 95 E) were further divided into S1-type, S2-type and S3-type ECSs (Ma et al, 2022a(Ma et al, , 2022bSong and Yan, 2022; Figure 2). ECS is defined as the maximum value of the maximum daily temperature drop among all involved grid points from the start date to the end date of the ECS.…”

Effects of irrigation‐induced surface thermodynamics changes on wind speed in the Heihe River basin, Northwest China

“…It is provided by the National Meteorological Information Center of the China Meteorological Administration (CMA). The quality‐controlled and homogenized datasets have been widely applied to explore the changes in wind speed and evaluate the model simulation in China (Li et al, 2018; Song & Yan, 2022; Zhang et al, 2021). In the study area, there are 19 ground meteorology stations, among which 10 stations are surrounded by cropland and 9 stations are surrounded by non‐cropland (Figure 1c).…”

Observed changes in wet days and dry spells over the IGAD region of eastern Africa

“…These 10 models were chosen based on how well they performed across the IGAD region 52 . The selected 10 models and CHIRPS datasets were rescaled from original resolutions to ten-kilometer (0.1 deg) using the bilinear interpolation method 53 to overcome the challenges of differences in resolutions of CMIP6 models and CHRIPS satellite rainfall estimates. The full model description including the spatial resolution, member realization outputs, the institute(s) possessing the intellectual property rights, and the full description of abbreviation of the names and datasets used can be found in CMIP6 institution_id values ( http://wcrp-cmip.github.io ) website.…”