Sensitivity of simulated short-range high-temperature weather to land surface schemes by WRF

Abstract

The simulations of a heat wave occurring in southern Yangtze-Huaihe valley and southern China during late July, 2003 were conducted to examine the sensitivity of simulated surface air temperature (SAT) to different land surface schemes (LSSs) using the Weather Research and Forecasting Model (WRF) Version 2.2 in the short-range mode for 24-h integrations. Initial and boundary conditions employed a National Centers for Environmental Prediction (NCEP) analysis. The results showed that, overall, simulated high-temperature weather is sensitive to different LSSs. Large differences in simulated SAT intensity, threat score, and simulated error under different schemes are identified clearly. In addition, some systematic differences are also induced by the LSSs. In terms of threat score from the three LSSs, SLAB is the best, and RUC is better than NOAH. SLAB gives the lowest absolute error for area-averaged SAT, and tends to depict the western Pacific subtropical high with the easternmost position at low levels. The LSSs modify the simulated SAT, primarily via the transfer of sensible heat from the land surface to the atmosphere. The physical mechanism of the positive feedback between atmospheric circulation and the SAT is unimportant, with "negative" feedback over most of the simulated areas. This study emphasizes the importance of improving LSSs in SAT forecasting by numerical models.WRF, land surface scheme, high-temperature weather, sensitivity experiment. Citation:Zeng X M, Wu Z H, Xiong S Y, et al. Sensitivity of simulated short-range high-temperature weather to land surface schemes by WRF.

Feedback between surface air temperature and atmospheric circulation in high‐temperature weather in East China: a diurnal perspective

“…For example, over 0900–1400 LT, the 850‐ and 700‐hPa heights decrease with the SAT increase, which is consistent with the negative feedback in the lower troposphere (i.e. Zeng et al ., ; ZWZ14), and the 300‐hPa height increases, which also agrees well with the positive feedback in the upper troposphere (e.g. ZWZ14).…”

“…Following Zeng et al . () and ZWZ14, for the simulation period we chose the hottest phase of the summer, i.e. late July 2003, when extremely high temperatures occurred over the land of south‐eastern China (within area ‘D2’; Figure S1).…”

“…While for the short‐range (18 h) East China high‐temperature weather in late July 2003, a negative SAT–circulation feedback was found using different land surface schemes (LSSs) in Version 2.2 of the Advanced Research Weather Research and Forecasting model (WRF), or ARW (Skamarock et al ., ), i.e. higher surface temperature was induced by the increase in surface sensible heating, and it reduced the geopotential heights in the western Pacific subtropical high (WPSH) in the lower atmosphere (or higher surface temperature resulted in weakened low‐level circulation, and vice versa; Zeng et al ., ). Recently, this negative feedback was further confirmed by the ARW (Version 3.3; Skamarock et al ., ) 24‐h simulations using a specific LSS with various soil wetness; moreover, a positive SAT–circulation feedback was identified in the mid‐troposphere by ZWZ14.…”

Sensitivity of a regional climate model to land surface parameterization schemes for East Asian summer monsoon simulation

“…Sato and Xue (2013) found that different descriptions of land surface processes in various schemes are one major source of uncertainties for the EASM downscaling. Zeng et al (2011) evaluated the sensitivity of simulated shortrange high-temperature weather to LSP schemes by WRF. However, few studies have been done on the evaluation of RCM to multi-LSP schemes for long-term simulation of the EASM comprehensively.…”

The effect of deforestation on the regional temperature in Northeastern China

“…Weather Research and Forecasting (WRF) has been adapted for simulating regional climate in recent years. With the land surface model embedded in the model, it can show the meteorological features such as diurnal cycle of temperature (Zeng et al 2011) and precipitation, etc., as well as express the influences of regional issues in better resolution to give better understanding of the coupling relationship between land and atmosphere (Das et al 2011;Subin et al 2011).…”