High-Resolution WRF Simulation of Extreme Heat Events in Eastern China: Large Sensitivity to Land Surface Schemes

Wenjian Hua,Haishan Chen,Liming Zhou,Xuan Dong,Shanlei Sun,Qingyuan Liu

doi:10.3389/feart.2021.770826

Abstract

Regional climate models with high-resolution simulation are particularly useful for providing a detailed representation of land surface processes, and for studying the relationship between land surface processes and heat events. However, large differences and uncertainties exist among different land surface schemes (LSSs). This study comprehensively assesses the sensitivity to different LSSs based on two extreme heat events in eastern China using the Weather Research and Forecasting (WRF) model. Among the five LSSs (i.e., 5TD, CLM4, Noah, Noah-MP and RUC), Noah is closest to observations in reproducing the temperatures and energy fluxes for both two heat events. The modeled warm biases result mainly from the underestimation of evapotranspirative cooling. Our results show that how each LSS partitions the evapotranspiration (ET) and sensible heat largely determines the relationship between the temperature and turbulent fluxes. Although the simulated two extreme heat events manifest similar biases in the temperatures and energy fluxes, the land surface responses (ET and soil moisture) are different.

Highlights

Extreme heat events, such as hot days, heat waves or multi-day heat events, have become more frequent over a large majority of global land areas under global warming (Hartmann et al, 2013), and have drawn an increasing amount of attention (e.g., Beniston, 2004; García-Herrera et al, 2010; Barriopedro et al, 2011; Trenberth and Fasullo, 2012)
Our results show that how each land surface schemes (LSSs) partitions the evapotranspiration (ET) and sensible heat largely determines the relationship between the temperature and turbulent fluxes
We focus on the areal mean of the study region over eastern China (Figure 2A), as the Clouds and the Earth’s Radiant Energy System (CERES) relatively has the lower spatial resolution compared to the model outputs

Summary

INTRODUCTION

Extreme heat events, such as hot days, heat waves or multi-day heat events, have become more frequent over a large majority of global land areas under global warming (Hartmann et al, 2013), and have drawn an increasing amount of attention (e.g., Beniston, 2004; García-Herrera et al, 2010; Barriopedro et al, 2011; Trenberth and Fasullo, 2012). Large scale systematic model biases exist in simulating heterogeneous land surface processes due to biases in lateral and lower boundary conditions derived from coarse resolution reanalysis data (Moalafhi et al, 2016). Using reference values computed over the inner domain (d03, Figure 1A) for the same time period establishes a baseline from which anomalies are calculated This effectively normalizes the data so they can be compared among the simulations from different LSMs and combined to more accurately represent the spatial patterns of fine-scale features. To examine the impacts of the two extreme heat events with regards to their land surface conditions using observed temperatures and GLEAM data from a longer time scales, we calculate the standardized anomalies of temperature, ET, soil moisture and energy fluxes for the summer of 2013 and 2017 following Xu et al (2011). The standardized anomalies are expressed as a (x−m)/s, where a is the standardized anomaly of a given variable (e.g., temperature, ET and soil moisture) in a specific year (2013 or 2017). x denotes the values in 2013 or 2017. m and s represent the long term mean and standard deviation over a reference period from 2003 to 2018, but excluding 2013 and 2017

RESULTS AND DISCUSSION

SUMMARY AND CONCLUSION

DATA AVAILABILITY STATEMENT