Table of Content

01 May 2015, Volume 31 Issue 2 Previous Issue    Next Issue

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Verification of precipitation forecast using an operational numerical model during flooding season of 2013 in the middle area of China CHEN Chao-jun LI Jun WANG Ming-huan 2015, 31 (2):  1-8.  Abstract ( 580 )   PDF (1572KB) ( 750 )   Save  The meso-scale numerical weather prediction system in the middle region of China has been updated recently with WRF model. In order to evaluate the prediction performance of the updated forecasting system, 24 and 48 hours precipitation prediction during the flood season of 2013 were analyzed in terms of TS score, forecast accuracy rate, missing alarm rate, false alarm rate, bias and ETS score. The results show that for 24 hours forecast, the distribution of daily mean precipitation rate, precipitation intensity and center position are closer to those of observation, while those from the 48 hours forecasts are significantly overestimated. Precipitation verification during the flood season suggests that most precipitation forecasts are overestimated, and TS and ETS scores decrease gradually and ETS score is gradually close to TS score with the increase of precipitation grade. Monthly precipitation verification suggests that accuracy rate of rainy and shine weather forecast is in a positive correlation with rainy day rate. Verification of forecasts from two models (WRF and GRAPES_Meso) shows that both have good prediction scores. It is worth noting that forecast results by the WRF are getting better with the increase of precipitation grade. In general, precipitation prediction products of this model are of a certain references to the precipitation forecast. Related Articles | Metrics

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Characteristics of air pollution during a snowstorm process in Nanjing 2015, 31 (2):  9-14.  Abstract ( 416 )   PDF (682KB) ( 329 )   Save A short but intensive snowfall occurred in Nanjing on February 19, 2013. Based on meteorological and environmental monitoring data, the impact of this process on various pollution sources and concentrations of pollutants was analyzed. Correlations between different pollutants and meteorological factors were discussed by a Pearson correlation analysis method. The results indicate that this snowstorm has significant impact on area pollution sources in Nanjing. In particular, fugitive dust emissions are almost not found. Mobile sources are mainly influenced by the number of vehicle during morning and evening rush hour peaks. Very little impact is found for industrial point sources. After this process, the ambient air quality reaches the excellence grade. AQI on February 19 decreases by 35% compared with that on February 18 or 20, 2013. SO2 diurnal variation on February 19 remains to be a single peak, while PM and NO2 diurnal variation in this day is not bimodal pattern as usual. PM2.5 concentration has a significant positive correlation with concentrations of PM10, SO2, NO2 and CO, and corresponding correlation coefficients are 0.979, 0.663, 0.837, and 0.875 respectively, which means the similar sources of those pollutants emissions. Concentrations of pollutants are significant negative correlations with wind speed and relative humidity and positive correlations with air temperature and pressure. Related Articles | Metrics

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Study on atmospheric correction methods for FY-3 MERSI image over Pearl River Delta region ZHANG Yue-wei,HE Quan-jun,HUANG Jiang 2015, 31 (2):  15-20.  Abstract ( 379 )   PDF (991KB) ( 603 )   Save  Observed data from 86 weather stations in Guangdong province were used to provide parameters of a simplify method for atmospheric correction (SMAC) algorithm, and then the SMAC algorithm was employed to conduct atmospheric correction for 250 m resolution data from medium resolution spectral imager (MERSI). In order to validate effects of SMAC algorithm for MERSI data, the reflectance histogram of each band and the normalized difference vegetation index (NDVI) before and after atmospheric correction were compared, and the reflectivity distribution characteristics in each meteorological station were analyzed. The results show that the reflectance interval of each band becomes wider and the reflectivity in the meteorological station is closer to the observation after atmospheric correction. Also, the histograms of NDVI are smoother and the peaks are higher after atmospheric correction; the histograms of NDVI are more similar for the data with time closer. All these results suggest that this atmospheric correction method is reasonable. Related Articles | Metrics

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Characteristics of concentration of air pollutant and its relationship with meteorological conditions in Yinchuan YAN Xiao-yu,GOU Xiao-hui,LIU Yu-lan,DU Juan-juan 2015, 31 (2):  21-30.  Abstract ( 452 )   PDF (2410KB) ( 616 )   Save  Using the air pollutants’ concentration data at 6 monitoring points of Yinchuan and the corresponding meteorological data in 2013, characteristics of the air pollutants’ concentrations and its relationship with the meteorological conditions were analyzed. The results show that annual average PM10 and PM2.5 concentration are 0.7 times and 0.4 times greater than the standard value. Annual mean SO2 and NO2 concentrations both exceed in a certain degree, while CO and O3 do not exceed the standard values. Concentrations of SO2, NO2, PM10, PM2.5 and CO are high in January, February, November and December, while that of O3 is high in May and October. There are two high peaks a day for SO2, NO2, PM10, PM2.5 and CO concentrations in one day, i.e. from 09:00 to 12:00 and from 21:00 to 00:00. However, the maximum O3 concentration generally occurs at 15:00. All pollutants concentrations generally show a seasonal quasi 7-day cycle and a yearly quasi 30-day cycle. Frequency of air quality with good grade accounts for 56 %, while those with light pollution and excellent air quality are 26 % and 12 % respectively. The primary pollutants are PM10, PM2.5 and SO2. Wind speed has a significant negative correlation with SO2, NO2 and CO concentrations, while it has a significant positive correlation with O3 concentration. Effect of wind speed on PM10 and PM2.5 concentrations is complex. When wind speed is less than a certain value, it is beneficial to PM10 and PM2.5 diffusion. On the other hand, when wind speed reaches a certain level, it can lead to increase concentrations of PM10 and PM2.5. Precipitation has good cleanup effect for pollutants, especially for SO2, while it had a weak effect on O3. Related Articles | Metrics

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Characteristics of haze and clean weather and their influencing factors in Xi'an ZHANG Wen-jing HU Lin WU Su-liang WANG Qi TIAN Liang 2015, 31 (2):  31-36.  Abstract ( 385 )   PDF (1566KB) ( 409 )   Save  Using pollution data, hourly surface wind, humidity and visibility in Xi′an from 2006 to 2012, the number of haze days calculated by theoretical prediction and observation were compared. Characteristics of haze days and clean days were analyzed, and corresponding meteorological elements were discussed. The results show that frequency of haze days is high in dry season and low in wet season. Effect of the surface wind on the haze weather is significant, and average daily surface wind is below 1.5 m·s-1 in most haze weather. It is equal or less than 1.0 m·s-1 in dry season, and even less than 0.5 m·s-1 in an extreme case. The number of clean days is higher in dry season than in wet season, which is due to the strong wind speed and low humidity in dry season. Related Articles | Metrics

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Relationship between air quality and meteorological conditions from 2006 to 2012 in Qingdao HUANG Rong GUO Li-na MA Yan YU Su-bing 2015, 31 (2):  37-43.  Abstract ( 463 )   PDF (1781KB) ( 783 )   Save Based on atmospheric monitoring data including SO2, NO2 and PM10 from 2006 to 2012 in Qingdao, temporal and spatial distributions of three main air pollutants and their correlations with the simultaneous meteorological elements were analyzed. Variation of meteorological conditions in pollution days was discussed. The result shows that the number of annual mean air pollution days are 23-33 in Qingdao, most of which occurs in winter and spring. PM10 is the primary atmospheric pollutant in Qingdao. Air pollution above the median level in Qingdao is mainly from PM10, which is mostly caused by external floating dust. Pollutant concentration is a negative correlation with cloud cover, precipitation and air temperature and positive correlation with air pressure. Air quality worsens during foggy days in winter, while the sea fog from April to June improves the air quality in Qingdao. Air pollution is easily induced by the existence of weak surface pressure pattern with the temperature inversion layer near ground and prolonged smog or haze in Qingdao. Related Articles | Metrics

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Analysis of climate change characteristics of rainstorm during flood season from 1958 to 2012 in Hebei province HUANG He YANG Chao YU Lei LE Zhang-yan WANG Zhi-Chao MA Hong-Qing 2015, 31 (2):  44-50.  Abstract ( 449 )   PDF (1754KB) ( 575 )   Save Using daily precipitation data at 21 weather stations in Hebei province from 1958 to 2012, climatic characteristics, annual and inter-decadal variations of heavy rain events and their trends during flood seasons were analyzed. The results indicate that heavy rain events during flood season are higher in the east and south than in the northwest. The largest center of heavy rain is located in the east of Hebei province, Tangshan and Qinhuangdao regions. According to the analysis of the inter-annual and inter-decadal scale, rainfall, frequency and intensity of heavy rain have a 2-3-year cycle, and the first two have a 15-20-year cycle after 1980s. Rainfall and frequency of heavy rain during flood season are in a declining trend, especially after 21st century. However, change of heavy rain intensity is not significant. For spatial distribution of heavy rain, inter-decadal rainfall and frequency as well as intensity all decrease to east and to south, and three indexes are in a declining trend in the most weather stations. Related Articles | Metrics

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Analysis of climatic characteristics of rainstorm during flood season from 1961 to 2012 in Shandong province LI Rui MENG Ling-wang ZHU Yi-qing WANG Jian-lin 2015, 31 (2):  51-58.  Abstract ( 439 )   PDF (1759KB) ( 479 )   Save Based on daily precipitation data at 35 observation stations during flood season from 1961 to 2012 in Shandong province, temporal and spatial characteristics of rainstorm day and intensity were analyzed by a mathematical statistical method. Meanwhile, a mean generating function model was established in an experiment of rainstorm prediction and was used to predict rainstorm. The results show that the rainstorm day and intensity during flood season from 1961 to 2012 in Shandong province are in a decreasing trend, and both are not statistically significant at the 0.05 level. Annual mean rainstorm days during the flood season are 2.2 days from 1961 to 2012 in Shandong province, and there are two cycles of 3.4 years and 8.0 years. Annual mean rainstorm intensity is 67.8 mm·d-1, oscillating with cycles of 2.3 years, 3.3 years, 6.9 years and quasi-12 years. There are no abrupt changes for rainstorm day and intensity during the flood season from 1961 to 2012 in Shandong province. Particularly, the annual mean rainstorm day and intensity during the flood season all decrease from the mid-later 1970s to late 1980s. The rainstorm day and intensity all increase gradually from northwest to southeast in Shandong province. The high frequency and strong intensity rainstorm events and continuous rainstorm events usually occur in the south of Shandong province, the south and east of Shandong peninsula. Prediction of rainstorm suggests that the mean generating function model can correctly simulate climate trend of rainstorm during the flood season from 2003 to 2012 in Shandong province, and it also has a good ability in the rainstorm prediction. Related Articles | Metrics

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Refined simulation of urban surface temperature distribution in Shanghai LIU Dong-wei AO Xiang-yu TAN Jian-guo CUI Lin-li 2015, 31 (2):  59-68.  Abstract ( 393 )   PDF (2360KB) ( 988 )   Save A method to simulate complex urban surface temperature was introduced. This method can be used to calculate urban net radiation flux based on a net all-wave radiation parameterization (NARP), and storage heat flux was obtained by an objective hysteresis model (OHM). Surface temperature was then calculated by a force-restore method. Different surface cover fractions were obtained using high-resolution satellite data in Shanghai, and then the average surface temperature in a grid box was determined with weights of area fractions of each land-cover types within the grid. The surface temperature on August 12, 2013 was simulated in Shanghai. The results show that the urban surface temperature increases rapidly in a daytime compared with that of other surface cover types, while it decreases slowly in a nighttime. By comparing the simulation results between MODIS land surface temperature and ground observational data, the spatial distribution of simulated surface temperature is more refined and closer to the ground observed data. Related Articles | Metrics

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Effect of meteorological conditions on heatstroke in summer and its prediction in Beijing DANG Bing LIU Bo YIN Ling ZHOU Zhong-yu HE Shi-lin LI Tan-shi SHANG Ke-zheng WANG Shi-gong 2015, 31 (2):  67-72.  Abstract ( 462 )   PDF (535KB) ( 381 )   Save  Based on 467 heatstroke cases, daily meteorological data and 1-4 days’ accumulated meteorological elements before heatstroke day from 2009 to 2012 in Beijing (sum 45 meteorological factors), relationships between heatstroke incidence and meteorological factors were analyzed by a correlation method. Improved forecast models of heatstroke were established by methods of a multiple linear regression and a nonlinear fitting, and the better model was selected to back substitution and verification for number of heatstroke patients. Also, this model was compared with the current used model. The results show?that temperature is a dominant factor causing heatstroke in summer in Beijing. Cumulative effects of temperature, vapor pressure, air pressure and precipitation in two days have a greater impact on heatstroke. In addition, new models have better fitting and forecasting effect for heatstroke, so is the grades of heatstroke. Thus, the models are of indicative to forecast heatstroke grades and prevent heatstroke. Related Articles | Metrics