ABSTRACT
In the winters of 2012-2018, a total of 25 'ultra-long' (≥6 days), wide-ranging pollution events occurred in northern China. The results showed that the atmospheric circulation pattern corresponding to 62.5% of the persistent 'most serious' and 'more serious' air pollution events in northern China were the blocking structures, and that 43.75% of the 500-hPa atmospheric circulation anomalies in the middle and high latitudes of Eurasia were 'dual-blocking', 18.75% of them were 'single-blocking'. The abnormally stable blocking situation provided a special circulation background for the occurrence and maintenance of persistent heavy air pollution in northern China. The Okhotsk blocking is significantly positively correlated with the persistent 'most serious' air pollution events. 'Stagnation' of the blocking system and its dynamic effect play an important role in regulating atmospheric environmental capacity and accelerating the accumulation of aerosols during the persistent heavy pollution episodes. Due to the synergy between the weak wind effect of the leeward slope on the eastern side of the Loess Plateau in this region and the downward airflow of the large-scale blocking system, the effect of sustained suppression of atmospheric pollutant diffusion in northern China is more significant. The downward air flow along the eastern leeward slope of the Loess Plateau is very important for accumulation of air pollutants, which is controlled by the tropospheric blocking high. In addition, the 'subsidence (temperature) inversion' effect produced by the synergy between the downward airflow of the eastern leeward slope of the Loess Plateau and the large-scale blocking system creates a continuous and stable 'warm-cover' structure in the middle of the troposphere on the eastern of the Loess Plateau; this effect strengthens the radiation effect of aerosols in the atmospheric pollutants, as well as the 'two-way feedback' mechanism between adverse meteorological conditions in the boundary layer and atmospheric pollutants.
ABSTRACT
In this paper, we propose a remote sensing model based on a 1 × 1 km spatial resolution to estimate the spatio-temporal distribution of sunshine percentage (SSP) and sunshine duration (SD), taking into account terrain features and atmospheric factors. To account for the influence of topography and atmospheric conditions in the model, a digital elevation model (DEM) and cloud products from the moderate-resolution imaging spectroradiometer (MODIS) for 2010 were incorporated into the model and subsequently validated against in situ observation data. The annual and monthly average daily total SSP and SD have been estimated based on the proposed model. The error analysis results indicate that the proposed modelled SD is in good agreement with ground-based observations. The model performance is evaluated against two classical interpolation techniques (kriging and inverse distance weighting (IDW)) based on the mean absolute error (MAE), the mean relative error (MRE) and the root-mean-square error (RMSE). The results reveal that the SD obtained from the proposed model performs better than those obtained from the two classical interpolators. This results indicate that the proposed model can reliably reflect the contribution of terrain and cloud cover in SD estimation in Ghana, and the model performance is expected to perform well in similar environmental conditions.
