A Comparative Study on Four Methods of Boundary Layer Height Calculation in Autumn and Winter under Different PM2.5 Pollution Levels in Xi’an, China

Author:

Sun Haiyan12,Wang Jiaqi2,Sheng Li3,Jiang Qi4

Affiliation:

1. Guizhou Purelue Techinology Co., Ltd., Guiyang 550081, China

2. Department of Ecological Environment of Guizhou, Guiyang 550002, China

3. CMA Earth System Modeling and Prediction Centre (CEMC) & State Key Laboratory of Severe Weather of China Meteorological Administration (CMA), Beijing 100081, China

4. National Meteorological Center, Beijing 100081, China

Abstract

In this paper, L-band sounding and surface observation data are used to calculate the boundary layer height (BLH) and evaluated CMA (China Metrological Administration Numerical Forecast System) and ERA5 in Xi’an for 2017–2021 using the Richardson (Ri) and Nozaki methods. For different PM2.5 pollution levels, the correlation between the vertical profile of meteorological factors and BLH is explored. There is a certain negative correlation between BLH and PM2.5 concentration. The BLH mean values of Nozaki, Ri, ERA5, and CMA from high to low are ~980 m, ~640 m, ~410 m, and ~240 m, respectively. The highest correlation is between ERA5 and CMA BLH with r2 > 0.85 for all pollution processes, while it between other methods is significantly lower (r2 < 0.58). The observational BLH is generally higher than the model results. Nozaki has a good adaptability on the light pollution, while Ri is more applicable to the stable boundary layer. In moderate and higher pollution, the ERA5 has a slightly better performance than CMA in BLH, while in light pollution there is a significant underestimation for both. Overall, the correlation between any two BLH methods gradually increases with increasing pollution level. In this study, there is about ~30% probability of polluted weather when BLH < 200 m and only <7% probability when BLH > 2000 m. It is difficult to simulate the neutral boundary layer and inversion processes for CMA and ERA5, but ERA5 has higher forecasting skills than CMA. This study can provide the data and theoretical support for the development of haze numerical forecast.

Funder

Meteorological Decision-making Service Project of China Meteorological Administration

National Natural Science Foundation of China

National Key R&D Program of China

Publisher

MDPI AG

Subject

Atmospheric Science,Environmental Science (miscellaneous)

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