Spatiotemporal distribution of near-surface air temperature lapse rate in China and its application in bias correction of NCEP temperature forecasts
The near-surface air temperature lapse rate(NTLR)is a crucial yet complex meteorological parameter that determines the rate at which air temperature decreases with increasing altitude.A uniform lapse rate across the troposphere cannot adequately capture the spatiotemporal variability of NTLR.Given the significant influences of topography,geographical location,seasonal cycles,diurnal variations,and human activities on NTLR,this study highlights the need for a spatiotemporally specific approach to accurately characterize these variations.The study has two primary objectives:first,to analyze the spatial and temporal variability of NTLR across different regions of China,and second,to assess the impact of these variations on the correction of temperature forecast biases in the NCEP model.According to comprehensive physical regionalization,China is divided into 33 sub-regions.Utili-zing a dataset of hourly temperature observations from 2 427 national-level meteorological stations in China,cov-ering the period from March 1,2013,to February 28,2022,the study calculates regional and seasonal NTLR val-ues for both day and night using a ternary linear regression model.This model accounts for altitude,latitude,and longitude,providing a detailed representation of the NTLR's relationship with geographical factors.The calculated NTLR values are then applied to correct elevation-based biases in the NCEP temperature forecasts from March 1,2022,to February 28,2023.The results indicate that:1)Significant spatiotemporal variations in NTLR exist across China,with differences occurring even within the same sub-region.The annual mean NTLR for China is 0.57 ℃/(100 m),with nighttime values slightly higher than daytime values.2)Seasonal and diurnal variations in NT-LR are substantial,with the highest rates observed in summer(average 0.63 ℃/(100 m))and the lowest in winter(average 0.47 ℃/(100 m)).The maximum day-night differences in NTLR are 0.22,0.29,0.28,and 0.50 ℃/(100 m)for spring,summer,autumn,and winter,respectively.3)Applying the statistically derived NT-LR to correct elevation-based biases in the NCEP temperature forecasts reduces the mean absolute error(MAE)across China for all forecast periods up to 360 h,with an average reduction of 0.56 ℃ and a maximum reduction of 1.20℃.The correction is most effective in summer and during the daytime across most sub-regions.However,in some areas,such as the central and northern Qinghai-Xizang Plateau,applying NTLR for bias correction has led to reduced forecast accuracy,indicating that NTLR application must be adapted to local conditions.Future research should explore the impact of varying altitude ranges,slope aspects,and other factors on NTLR within the context of comprehensive physical regionalization.
near-surface air temperature lapse ratespatiotemporal variabilityregional variationseasonal varia-tiondiurnal variation
万方数据
维普
