Seasonal Characteristics of Forecasting Uncertainties in Surface PM_2.5 Concentration Associated with Forecast Lead Time over the Beijing-Tianjin-Hebei Region

Abstract

Forecasting uncertainties among meteorological fields have long been recognized as the main limitation on the accuracy and predictability of air quality forecasts. However, the particular impact of meteorological forecasting uncertainties on air quality forecasts specific to different seasons is still not well known. In this study, a series of forecasts with different forecast lead times for January, April, July, and October of 2018 are conducted over the Beijing-Tianjin-Hebei (BTH) region and the impacts of meteorological forecasting uncertainties on surface PM_2.5 concentration forecasts with each lead time are investigated. With increased lead time, the forecasted PM_2.5 concentrations significantly change and demonstrate obvious seasonal variations. In general, the forecasting uncertainties in monthly mean surface PM_2.5 concentrations in the BTH region due to lead time are the largest (80%) in spring, followed by autumn (~50%), summer (~40%), and winter (20%). In winter, the forecasting uncertainties in total surface PM_2.5 mass due to lead time are mainly due to the uncertainties in PBL heights and hence the PBL mixing of anthropogenic primary particles. In spring, the forecasting uncertainties are mainly from the impacts of lead time on lower-tropospheric northwesterly winds, thereby further enhancing the condensation production of anthropogenic secondary particles by the long-range transport of natural dust. In summer, the forecasting uncertainties result mainly from the decrease in dry and wet deposition rates, which are associated with the reduction of near-surface wind speed and precipitation rate. In autumn, the forecasting uncertainties arise mainly from the change in the transport of remote natural dust and anthropogenic particles, which is associated with changes in the large-scale circulation.

摘 要

气象要素预报的不确定性是长期以来学界公认的制约空气质量预报准确性和可预测性的主要因素。但目前气象预报的不确定性对不同季节空气质量预报影响的研究较为缺乏,且空气质量预报不确定性随预报时长延长增加的关键过程和机制也尚不明确。本研究通过对京津冀地区2018年1月、4月、7月和10月的2天至7天预报时长的数值预报实验,分析了气象预报不确定性对各预报时长近地面PM2.5浓度预报的影响。结果显示,随预报时长延长,PM2.5 的预报浓度有明显变化,并表现出显著的季节性变化特征:预报时长导致的京津冀地区PM2.5 月平均近地面浓度的预报不确定性在春季最大(80%),其次是秋季(约 50%)、夏季(约 40%)和冬季(20%)。通过分析PM2.5各化学组份近地面浓度和气象要素随预报时长的变化特征,本研究发现冬季预报时长导致的PM2.5近地面浓度预报不确定性主要是由于边界层高度预报随预报时长的升高增强了人为一次颗粒物的边界层混合。在春季,预报时长导致的不确定性则主要受对流层底西北风的影响。随预报时长不断增强的西北风加强了自然源沙尘气溶胶的远距离传输和人为二次气溶胶的凝结生成。在夏季,预报时长导致的不确定性主要是由于近地面风速和降水率随预报时长的减弱导致的干、湿沉积率的减弱。在秋季,预报时长导致的不确定性主要来自自然源沙尘的远距离传输和人为大气颗粒物传输随预报时长的增强,这与大尺度环流随预报时长的变化有关。