The paper presents a study of urban heat island (UHI) intensity and its impact on air quality by using the System of Air Quality Forecasting and Research (SAFAR) network observations over Delhi during the clear sky mo...The paper presents a study of urban heat island (UHI) intensity and its impact on air quality by using the System of Air Quality Forecasting and Research (SAFAR) network observations over Delhi during the clear sky month of December of 2013 and 2015. It is found that in the month of December 2013 and 2015 the UHI shows a peak in late evening around 20:00 hrs. The concentration of PM2.5 shows a bimodal peak in the month of December of both the years 2013 and 2015 which is due to the enhanced anthropogenic activity during the traffic hours. The formation of UHI during the late evening traffic hours is due to the enhancement in the concentration of PM2.5 due to the enhanced anthropogenic activity with higher ground heat flux and lower PBLH and wind speed which leads to both the years 2013 and 2015 during the month of December. It is also found that UHI intensity shows a positive correlation (r = 0.57) with PM2.5 concentration and a negative correlation (r = -0.40) with wind speed and the PM2.5 concentration also shows a negative correlation (r = -0.57) with wind speed during December 2013. Whereas during December 2015 it has found that UHI intensity has a positive correlation (r = 0.65) with PM2.5 concentration and a negative correlation (r = -0.45) with wind speed and the PM2.5 concentration also shows a negative correlation (r = -0.57) with wind speed.展开更多
Planetary boundary layer height(PBLH) is an important input parameter for any boundary layer study or model, either climate or atmospheric. The variation of the PBLH is also of great significance to the physical proce...Planetary boundary layer height(PBLH) is an important input parameter for any boundary layer study or model, either climate or atmospheric. The variation of the PBLH is also of great significance to the physical processes of numerical prediction, diagnosis of weather forecasting and monitoring urban pollutants. However, effective ways to monitor the PBLH continuously are lack. Wind profilers are commonly used in monitoring PBLH continuously because of its high temporal and spatial resolution, coupled with capability of continuous detection. In this paper, the covariance wavelet transform(CWT) is used to analyze the range-corrected signal-to-noise ratio(SNR) of the wind profiler to determine the PBLH, which is then compared with the results measured by the gradient method and the radiosonde. The conclusions are as follows:(1) The scaling parameter a and translation parameter b of the wavelet are critical in determination of the PBLH by applying the CWT as different values may get completely different results, which requires to select appropriate values in the calculation carefully.(2) Quality control is crucial in determining the PBLH because good quality control can help remove mutation points, which makes the determined PBLH more consistent with the actual situation.(3) In clear-air, the gradient method is not applicable if the boundary layer turbulence is inhomogeneous and the impact of noise is large for that it is easy to be impacted by the mutation of SNR caused by the atmosphere turbulence instability and other factors, which will cause large errors, while the CWT method as an improvement of the gradient method can determine the PBLH quite well.(4) Through quality control, the PBLHs determined by the CWT are consistent with those of radiosonde, and the correlation coefficient between them is 0.87.展开更多
文摘The paper presents a study of urban heat island (UHI) intensity and its impact on air quality by using the System of Air Quality Forecasting and Research (SAFAR) network observations over Delhi during the clear sky month of December of 2013 and 2015. It is found that in the month of December 2013 and 2015 the UHI shows a peak in late evening around 20:00 hrs. The concentration of PM2.5 shows a bimodal peak in the month of December of both the years 2013 and 2015 which is due to the enhanced anthropogenic activity during the traffic hours. The formation of UHI during the late evening traffic hours is due to the enhancement in the concentration of PM2.5 due to the enhanced anthropogenic activity with higher ground heat flux and lower PBLH and wind speed which leads to both the years 2013 and 2015 during the month of December. It is also found that UHI intensity shows a positive correlation (r = 0.57) with PM2.5 concentration and a negative correlation (r = -0.40) with wind speed and the PM2.5 concentration also shows a negative correlation (r = -0.57) with wind speed during December 2013. Whereas during December 2015 it has found that UHI intensity has a positive correlation (r = 0.65) with PM2.5 concentration and a negative correlation (r = -0.45) with wind speed and the PM2.5 concentration also shows a negative correlation (r = -0.57) with wind speed.
基金Foundation of Beijige for radar meteorology and sever weather in Nanjing(BJG201407)National Natural Science Foundation of China(41475019+1 种基金4130618741505016)
文摘Planetary boundary layer height(PBLH) is an important input parameter for any boundary layer study or model, either climate or atmospheric. The variation of the PBLH is also of great significance to the physical processes of numerical prediction, diagnosis of weather forecasting and monitoring urban pollutants. However, effective ways to monitor the PBLH continuously are lack. Wind profilers are commonly used in monitoring PBLH continuously because of its high temporal and spatial resolution, coupled with capability of continuous detection. In this paper, the covariance wavelet transform(CWT) is used to analyze the range-corrected signal-to-noise ratio(SNR) of the wind profiler to determine the PBLH, which is then compared with the results measured by the gradient method and the radiosonde. The conclusions are as follows:(1) The scaling parameter a and translation parameter b of the wavelet are critical in determination of the PBLH by applying the CWT as different values may get completely different results, which requires to select appropriate values in the calculation carefully.(2) Quality control is crucial in determining the PBLH because good quality control can help remove mutation points, which makes the determined PBLH more consistent with the actual situation.(3) In clear-air, the gradient method is not applicable if the boundary layer turbulence is inhomogeneous and the impact of noise is large for that it is easy to be impacted by the mutation of SNR caused by the atmosphere turbulence instability and other factors, which will cause large errors, while the CWT method as an improvement of the gradient method can determine the PBLH quite well.(4) Through quality control, the PBLHs determined by the CWT are consistent with those of radiosonde, and the correlation coefficient between them is 0.87.
文摘利用2013年9月—2014年11月广州地区激光雷达观测结果,使用小波分析反演边界层高度(PBLH),通过归一化后向散射信号(NRB)的小波分解对小波分析中直接影响PBLH识别的尺度因子a进行了选取.并以2014年1月发生的一次灰霾过程为例,对灰霾过程的PBLH等边界层特征进行了分析,并对边界层垂直结构进行了初步探究.同时,利用自组织映射神经网络(SOM)进行了天气分型,对整个观测时段激光雷达反演的PBLH与天气型之间的关系进行了统计.结果表明,通过对NRB廓线的小波分解,小波分析尺度因子a取300较为合适.灰霾过程中PBLH均存在日变化.从平均结果来看,PBLH最高值出现在13:00,为850 m;最低值出现在5:00,为483 m.灰霾过程PBLH与PM_(2.5)之间呈显著负相关(r=-0.62,p<0.01),风速与PM_(2.5)之间也呈显著负相关(r=-0.39,p<0.01).对流边界层平均高度约为稳定边界层的1.5倍,峰值高度约为稳定边界层的3倍.低压天气系统控制下灰霾天气出现的概率较低,对应的PBLH明显较高,峰值高度在1200～1600 m,日间边界层发展极为明显.而高压天气系统控制下边界层发展容易受到抑制,峰值高度均低于1000 m.
