高级检索

基于大气外强迫因子的我国夏季近地面臭氧浓度的统计预测

Statistical prediction for near-surface ozone concentration during summer in China based on atmospheric external forcing factors

  • 摘要: 本研究利用观测和再分析数据,揭示影响2013-2020年间我国夏季近地面臭氧浓度长期演变的主要海温外强迫因子,并利用多元线性回归方程构建了统计预测模型,所得结论如下:(1)我国尤其是华东和华南地区的夏季臭氧浓度表现出一定的波动上升特征,分析发现影响我国夏季近地面臭氧浓度变化的大气外强迫因子包括海洋性大陆海温异常和北大西洋南北偶极子型海温分布;(2)海洋性大陆海温异常是通过调节局地环流从而影响我国臭氧浓度变化的,而北大西洋海温则是通过激发东传的Rossby波列来影响臭氧浓度变化;(3)利用臭氧的趋势因子及识别到的区域海温因子,本文构建出我国夏季近地面臭氧浓度变化的统计回归预测模型,该模型在回报试验期内能很好地预测出全国及不同子区域臭氧浓度变化及其空间分布。因此,本文研究成果对我国夏季近地面臭氧浓度具有明显的预测潜力和应用价值。

     

    Abstract: This study utilized observational and reanalysis data to reveal the main external forcing factors of sea surface temperature (SST) that influenced the long-term evolution of near-surface O3 concentration during summer in China from 2013 to 2020. Then, a statistical prediction model was further constructed using the multiple linear regression equations of summer O3. The conclusions drawn are as follows: (1) The near-surface O3 concentration during summer in China, especially in East China and South China, shows certain fluctuating upward characteristics. It is revealed that the atmospheric external forcing factors influencing the variation of O3 concentration during summer in China include the Maritime Continental SST anomalies and the North-South dipole-type SST anomalies over the North Atlantic. (2) The Maritime continental SST anomalies affect variations of O3 concentration in China by regulating local circulations, while those over the North Atlantic are by exciting the eastward Rossby wave train. (3) Using the trend factor of O3 concentration and the identified regional SST factors, we have constructed a statistical regression prediction model for variations of O3 concentration during summer in China. This prediction model can accurately predict the changes and spatial distribution of O3 concentration across the country and in different subregions during the hindcast period. Hence, the achievements of the study has certain predictive potential and application value.

     

/

返回文章
返回