Abstract
The extreme temperature changes under a 0.5 °C global mean surface temperature warming increment is of great importance for climate change adaption and risk management on post-Paris-Agreement agenda. The impacts of the already happened 0.5 °C warming increment on extreme temperature can serve as essential references for the 1.5/2 °C projections. Quantifying the observed changes of climate extremes is hampered by the limitation of observational datasets in both spatial coverage and temporal continuity. The reanalysis datasets are hoped to be useful substitutes for the observations, but their performance over continental China remains unknown. In this study, we compare the extreme temperature changes associated with the past 0.5 °C warming derived from three reanalysis datasets including JRA-55, ERA and 20CR with the observation in China. Distinct increases (decreases) in warm (cold) extremes are detected in all three reanalyses in a spatially aggregated perspective as in the observation. On regional scales the reanalyses have evident spreads in regions with insufficient observational coverage such as the western China. JRA-55 shows good agreement with the observation in both spatial patterns and magnitudes of extreme temperature changes. Both ERA and 20CR show weaker consistency with the observation, particularly in western China, mainly due to less observational constraints in data assimilation. The different aerosol data used in reanalysis assimilation systems also influenced the data quality. Our results indicate that while the reanalyses can serve as useful substitutes to fill in the observational gaps, cautious should be taken in regions with sparse observations and large anthropogenic aerosol emissions.
Highlights
Climate extreme changes have more severe impacts on multiple aspects in human and natural systems compared to the mean climate changes (Seneviratne et al 2012)
The changes in seasonal mean temperature shows good linear relationship with the extreme temperature intensity changes (Fig. 2). This indicates that the seasonal mean TX and TN warming background mainly contributes to the corresponding extreme temperature change
While the extreme temperature changes under the 0.5 °C additional warming increment measured by observational datasets are hoped to be useful references for adaptation activities, the observational datasets have suffered from insufficient spatial consistency and temporal continuity in observational stations
Summary
Climate extreme changes have more severe impacts on multiple aspects in human and natural systems compared to the mean climate changes (Seneviratne et al 2012). The hottest day and night will increase by ~ 0.6 °C–0.7 °C, and the frequency of the warm days will be increased ~ 130% (Guo et al 2017; Kharin et al 2018; Shi et al 2018) While these different approaches qualitatively agree with each other in the general decreases of extreme temperature under 1.5 °C warming level compared to 2 °C, quantitative differences are seen due to the different modeling strategies and the limitations of climate models in the physical processes parameterization. Since the GMST has already witnessed a half-degree warming increment during the period of 1991–2010 compared to the period of 1960–1979 (Hansen et al 2010) This indicate that the observed changes in climate extremes under this historical 0.5 °C warming increment can be used as observational metrics to evaluate model performance, or even regarded as analogues for the future projections (Schleussner et al 2017). How to reliably quantify the observed changes is of central importance
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