Temperature Dependence of Hourly, Daily, and Event-based Precipitation Extremes Over China

Abstract

Theoretically, precipitation extremes will increase at a rate of 6–7% with temperature increasing, namely the Clausius-Clapeyron relationship. However, many gauge observations suggest a peak structure of the relationship between precipitation extremes and atmospheric temperature, deviating from the Clausius-Clapeyron relationship. In this study, a comprehensive investigation about the temperature dependence of precipitation extremes (hourly, daily, and event-based) across China is implemented. The results confirm the widespread existence of the peak structure for daily and hourly precipitation extremes and show that (1) there is a generally positive spatial correlation between the precipitation extremes at the peak and temperature at the peak, and this scaling rate is close to the C-C rate; (2) the scaling of event-based extremes for precipitation amount with temperature follows a similar pattern to the daily precipitation extremes while the event-based precipitation intensity does not show a peak structure; (3) the decrease of rain duration is the main cause for the peak structure of the rain amount scaling.

Scalability of future climate changes across Japan examined with large-ensemble simulations at + 1.5 K, +2 K, and + 4 K global warming levels

“…9b), and the increase rates are 7% K −1 , 6% K −1 , and 5% K −1 at d1.5, d2, and d4 respectively. These values agree with the theoretical values from the Clausius-Clapeyron (CC) relationship of 6 to 7% K −1 for strong precipitation (e.g., Wang et al 2017;Gao et al 2018).…”

The relationship of atmospheric air temperature and dew point temperature to extreme rainfall

“…Negative scaling contradicts observed historical increases in tropical rainfall extremes (Donat et al 2016, Guerreiro et al 2018. This has led to the explanation that, at higher temperatures, the relative humidity decreases, as there is no more moisture to be sourced (Hardwick Jones et al 2010) and evaporation limitations (Priestley 1965, Roderick et al 2019 result in a reversal from positive to negative scaling (Drobinski et al 2016, 2018, Gao et al 2018. Indeed the most negative scaling is found in regions with the largest humidity limitations .…”

A Comparison of Intra-Annual and Long-Term Trend Scaling of Extreme Precipitation with Temperature in a Large-Ensemble Regional Climate Simulation

“…Indeed, the identification of super-Clausius-Clapeyron scaling rates in areas with ample atmospheric moisture, whether via binning or trend scaling calculations, would necessarily indicate a change in precipitation efficiency (precipitation expressed as the fraction of precipitable water in the atmospheric column at the time of the event), and thus moisture convergence-a strong indication that circulation is at play, either at local scales via vertical motion induced by latent heat released during cloud condensation or at larger scales (Pfahl et al 2017;Tandon et al 2018;Norris et al 2019;Li et al 2019a). Studies of binning curves in specific regions that have attempted to understand the processes that underlie the hook shape that is often seen also tend to implicate circulation and temperature related moisture deficits (e.g., Chan et al 2016;Drobinski et al 2016;Gao et al 2018;Wang et al 2017). Whether the kind of circulation change that occurs within an epoch, and particularly, within individual annual cycles, is indicative of the circulation change that might occur between epochs at the time of year with the most intense precipitation events occur is not evident.…”

“…Note that Wasko and Sharma (2014) proposed a variant approach by using quantile regression to regress precipitation onto daily temperatures to obtain a description of how the conditional quantiles of precipitation vary with temperature. These two approaches have been used to study binning scaling rates for different regions, different seasons, and different precipitation types (e.g., Hardwick Jones et al 2010;Lenderink et al 2011;Utsumi et al 2011;Mishra et al 2012;Panthou et al 2014;Ali and Mishra 2017;Lochbihler et al 2017;Gao et al 2018;Wang et al 2018;Wasko et al 2018;Van de Vyver et al 2019;Zhang et al 2019). Note that binning rates may vary seasonally owing to seasonal changes in weather patterns and large-scale circulation (Berg et al 2009;Shaw et al 2011;Mishra et al 2012).…”