Table of Content

28 February 2016, Volume 32 Issue 1 Previous Issue    Next Issue

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Evaluation of summer near-surface meteorological fields simulated by WRF model in Ji'nan GU Shen-dan, YU Li-juan, YIN Cheng-mei, HE Jian-jun 2016, 32 (1):  1-8.  doi: 10.11927/j.issn.1673-503X.2016.01.001 Abstract ( 564 )   PDF (1755KB) ( 1161 )   Save The meso-scale meteorological model had different performance in different regions.Using a numerical simulation method and a statistical method, performance of Weather Research and Forecasting (WRF) model was assessed in Ji'nan area, and impacts of the topography and land use on the WRF simulation were comparatively discussed in order to provide scientific references for operational running of the WRF model.The results indicate that the WRF model can simulate near-surface meteorological fields and their temporal variation well.Based on the statistical analysis, the accurate rates of simulated temperature, specific humidity, wind speed and wind direction are 72.5%, 59.6%, 29.4% and 36.2% for the WRF model, respectively.In summer, the WRF model underestimates specific humidity and overestimates wind speed over the Ji'nan regions, and it has obvious systematic bias on wind speed simulation.The effect of underlying surface on the simulation results of WRF model is significant.Root mean square error (RMSE) of the simulated 10 m wind speed is significantly correlated with topography, slope, and terrain deviation between model grid point and observed station point, especially with slope, while RMSE of the simulated 2 m temperature is only significantly correlated with terrain deviation.It should consider the impact of terrain deviation in complex terrain area if temperature from model grid point is compared with that from weather stations. References | Related Articles | Metrics

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Verification and assessment of precipitation forecast by five numerical models in Langfang XU Min, CONG Bo, LIU Yan-jie, WANG Jie, ZHANG Shao-hui, TIAN Xiao-fei 2016, 32 (1):  9-15.  doi: 10.11927/j.issn.1673-503X.2016.01.002 Abstract ( 344 )   PDF (1054KB) ( 704 )   Save In order to improve the application of precipitation forecast products from numerical models, forecast results were tested using observed precipitation from 9 weather stations of Langfang and forecast products from five numerical models, namely, Japan, Germany, T639, GRAPES and MM 5 models.The results indicate that TS scores of Japan and Germany models for more than or equal to 10 mm and 25 mm precipitation are 10.0%-40.0% higher than those from the other models.The MM 5 model for more than or equal to 50 mm precipitation has better forecast results in summer.T639 and GRAPES models show better prediction ability for heavy rain or more grade and light snow, while Japan and Germany models are better for moderate and heavy snow.TS score of T639 for rainstorm reaches 33.3% and higher than those of the other models. References | Related Articles | Metrics

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Analysis of a typical air pollution event in Shanghai CAO Yu, MA Jing-hui, XU Jian-ming, GENG Fu-hai 2016, 32 (1):  16-24.  doi: 10.11927/j.issn.1673-503X.2016.01.003 Abstract ( 371 )   PDF (2939KB) ( 494 )   Save Based on monitoring data of main pollutants and the NCEP/NCAR FNL (Final Analysis) reanalysis data with resolution of 1°×1°, together with aerosol extinction coefficients data and a backward trajectory simulation method of airflow from HYSPLIT of NOAA, a serious pollution process on May 25 to 30, 2014 in Shanghai caused by sand dust and straw burning was analyzed.Pollution source, transport path, meteorological conditions and atmospheric boundary layer features during this process were discussed.The results indicate that PM2.5 is prevailing in this process.Duration of pollution is long because of common influence of sand dust and straw burning.The horizontal transportation in the middle-low troposphere (700-850 hPa), vertical wind distribution and atmospheric stratification change provide favorable conditions for this air pollution event.Echo intensity and aerosol extinction coefficients observed by a micro pulse lidar (MPL) truly reflect the air pollution event, and both have a positive correlation with PM2.5 concentration after they revised by squared distance of radar monitoring, which is indicative to pollution weather forecast in Shanghai. References | Related Articles | Metrics

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Comparative analysis of two continuous air pollution events in Chongqing HU Chun-mei, LIU De, CHEN Dao-jin 2016, 32 (1):  25-32.  doi: 10.11927/j.issn.1673-503X.2016.01.004 Abstract ( 308 )   PDF (2504KB) ( 584 )   Save Two continuous air pollution events on January 15 to 20, 2009 (called 0115) and on November 20 to 29, 2011 (called 1120) in Chongqing were compared.The results show that upper and lower situation with widespread descending current under 600 hPa is not favorable to precipitation when pollution intensity is stronger for the 0115 event.Atmosphere in boundary layer is in a static stability condition with multi-inversions in lower level under 1.5 km, and it is wet in upper level and dry in lower level for humidity vertical distribution.The surface is uniform pressure field;mean wind speed is 0.84 m·s-1;the static wind frequency reaches 31.3%;turbulent fluctuation is weak because of small diurnal temperature range of 2.83℃.The severe fog or haze events (the minimum visibility is about 0.6 km) often happen in such a suitable atmospheric environment and the air pollution becomes more and more serious.On the other hand, duration of pollution is long for the 1120 event, and there is not precipitation.The circulation field in middle and lower level is narrow descending current.There are multi-inversions in boundary layer.Humidity distribution is dry in upper level and wet in lower level.The surface wind speed is 1.23 m·s-1 and larger than that of 0115 event.The diurnal mean temperature range is 5.18℃ leading to stronger turbulent fluctuation in ground layer.Mean surface relative humidity is lower than 80.0%.It is mainly haze weather in this period.Duration of pollution is long, while concentrations of pollutants are relatively lower. References | Related Articles | Metrics

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Characteristics of a haze weather event and prediction during spring in Chengdu YAN Yu-qian, ZHU Ke-yun, ZHANG Jie, XU Cheng 2016, 32 (1):  33-39.  doi: 10.11927/j.issn.1673-503X.2016.01.005 Abstract ( 319 )   PDF (1147KB) ( 509 )   Save A serious haze weather event from February 25 to March 12, 2013 was selected in this paper.Based on the environmental data from monitoring stations of Chengdu, meteorological data from weather stations, 0.75°×0.75° reanalysis data of ERA and wind profile radar data in Chengdu University of Information Technology, meteorological characteristics and effect of different meteorological conditions on pollutants diffusion in this process were analyzed.A forecast equation of PM2.5 concentration was established.The results show that it is stable in upper level.Surface is controlled by the uniform pressure field or weak low pressure and no precipitation.These conditions are favorable to formation of pollution.However, there is low trough system in upper altitude.If low pressure enhances on surface, haze dissipation probability increases.Low wind speed and downdraft in vertical direction avail to product haze weather.Temperature inversion in boundary layer is another important feature.Strong ground temperature inversion exists from 0 m to 200 m, and its structure has inhibitory effect on convection current and in favor of accumulating vapor to form the mist, thus there are more chances to generate haze weather.When there is a haze weather event, the height of mixing layer is generally low.A PM2.5 concentration model is established using a stepwise regression method, and its back inspection is done.Another haze weather event in spring in Chengdu is forecasted using this model.Pollution grade can be accurately forecasted, and its prediction results are relatively satisfactory. References | Related Articles | Metrics

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Characteristics of persistent haze periods using large range sequence reconstruction in Hubei province WANG Kai, FANG Si-da, LI Lan 2016, 32 (1):  40-45.  doi: 10.11927/j.issn.1673-503X.2016.01.006 Abstract ( 252 )   PDF (930KB) ( 431 )   Save Based on daily weather phenomenon, relative humidity and visibility data at 76 weather stations from 1961 to 2013, daily haze sequence was rebuilt in Hubei province, and a grade evaluation model for a large scale persistent haze event and corresponding indexes were built.Temporal and spatial characteristics of haze day and large scale consecutive haze events in Hubei province were also analyzed.The results show that there are a few differences between raw and corrected data for interdecadal variation of temporal and spatial distribution, while both trends are contrary.Interdecadal characteristics of haze day are significant in the recent 50 years in Hubei province according to sequence reconstruction of haze day.It is in a significant increasing trend after 2000, and haze day often occurs in winter.The large scale consecutive haze events mainly appear in 1970s and the early 21st century, especially in 2013.Higher frequency haze day is in the eastern region of northwestern Hubei province, and the north-central region of eastern Hubei province.According the results, the use of the LSCHI index to evaluate the large scale persistent haze period produces a better result. References | Related Articles | Metrics

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Vertical distribution of atmospheric ozone over Beijing from GPSO3 in-situ measurements LIU Chuan-xi, LIU Yi, WANG Yong 2016, 32 (1):  46-52.  doi: 10.11927/j.issn.1673-503X.2016.01.007 Abstract ( 327 )   PDF (644KB) ( 760 )   Save GPSO3 ozonesondes have been used to characterize the vertical distribution of atmospheric ozone over Beijing.Based on the ozone sondes data from September of 2002 to December of 2012, seasonal ozone variation and variability near the tropopause level is highlighted.The results indicate that the ozone mixing ratio increases with the altitude through the troposphere in all seasons.Generally, the averaged ozone concentration is the highest in summer and lowest in winter through the troposphere, and it is almost same in spring and autumn.Ozone concentration has a few differences in different height ranges.Vertical distribution and average of ozone concentration in the upper troposphere and lower stratosphere (8-15 km) is strongly modulated by the location of the tropopause.Analysis of tropopause-based coordinate suggests that vertical distribution of ozone concentration in the altitudes of 1-3 km under the tropopause is similar to that in the tropopause, while seasonal ozone concentration increases significantly with the heights near the tropopause.Due to increase of ozone concentration with altitude in different seasons, seasonal variation of ozone concentration in the altitudes of 1-3 km above tropopause is quite different from that in the troposphere.Normalized standard deviation of ozone concentration suggests that ozone variability is the highest in winter, followed in autumn, spring and summer in the lower troposphere, while it is the highest in spring, followed in winter, autumn and summer near the tropopause.The strong ozone variability around the tropopause in spring and winter is very likely related to active atmospheric disturbances and tropopause height variation in these seasons. References | Related Articles | Metrics

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Variation of ozone concentration and prediction in surface layer in Ningbo JIANG Lu-lu, QIAN Yan-zhen, DU Kun, GU Xiao-li 2016, 32 (1):  53-59.  doi: 10.11927/j.issn.1673-503X.2016.01.008 Abstract ( 359 )   PDF (1555KB) ( 982 )   Save Using environmental observation data of ozone in the surface layer, the meteorological observation data and NCEP reanalysis data form 2010 to 2013, the ozone distribution and its relevance with various environmental elements were analyzed, and a forecast model of ozone concentration was established.The results show that daily ozone concentration curve is unimodal and the peak generally appears in the afternoon in Ningbo.Meanwhile, annual variation of ozone concentration curve is bimodal and the two peaks occur in May and October, respectively.The forecast model is established by choosing daily mean pressure, vapor pressure, temperature, NO2 concentration and SO2 concentration which has good correlations with ozone concentration as predictors.After the evaluation, the model prediction effect is relatively good.Statistics of weather types leading to excessive ozone levels suggest that ozone pollution easily happens in several weather types such as transformed cold high pressure, uniform pressure field, upper ridge, subtropical high and peripheral tropical cyclone, and their proportions are 22.1%, 9.5%, 24.4%, 31.4% and 8.7%, while other weather types only account for 3.9%.Weather situation of each type is showed by a synthetic analysis method. References | Related Articles | Metrics

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Forecast of hourly total solar radiation based on a wavelet back propagation neural network method in Hainan province HUANG Hai-jing, ZHANG Jing-hong, QIN Wen-na, ZHANG Ming-jie, XING Cai-ying 2016, 32 (1):  60-65.  doi: 10.11927/j.issn.1673-503X.2016.01.009 Abstract ( 301 )   PDF (688KB) ( 663 )   Save Hourly total solar radiation data has become the basic requirements of the meteorological service for multi-industry.However, radiation observation sites in China are sparse.Using hourly total solar radiation data in different seasons and corresponding meteorological data from 2003 to 2012 in Haikou weather station, an hourly total solar radiation prediction model based on a wavelet back propagation (BP) neural network method was developed.The model was tested using observed data in 2013 and compared with that based on a stepwise statistical regression model developed by the same data.The results indicate that the model based on the wavelet BP neural network method has higher accuracy, but the level of accuracy is different in different seasons.The accuracy is the highest in winter and lowest in summer.The index of weather type is favorable to enhance the forecast accuracy in different seasons.The root means squared error (RMSE) between predicted and observed total solar radiation for the wavelet BP neural network model with index of weather type are 0.32 MJ·m-2 in spring, 0.47 MJ·m-2 in summer, 0.35 MJ·m-2 in autumn and MJ·m-2 in winter, and its forecast accuracy increases by 28.8%, 16.3%, 17.9% and 20.4% respectively compared with that for the stepwise regression model.It suggests that the model based the wavelet BP neural network method is suitable in Hainan. References | Related Articles | Metrics

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Characteristics of extreme high temperature weather in Shanghai JIANG Rong, CHEN Liang, XIANG Wei-ning 2016, 32 (1):  66-74.  doi: 10.11927/j.issn.1673-503X.2016.01.010 Abstract ( 488 )   PDF (1213KB) ( 635 )   Save Based on daily maximum, minimum air temperature data and relative humidity data in Xuhui weather station of Shanghai from 1960 to 2013, and daily maximum, minimum air temperature data at 10 automatic weather stations of Shanghai from 2004 to 2014, trends of extreme high temperature were analyzed using daily maximum air temperature, number of high temperature day, number of warming night (WR) day, high temperature and heat wave index, number of hot day and generalized extreme value (GEV) distribution and so on.The results show that daily highest air temperature increases obviously in summer from 1960 to 2013 in Shanghai, so are the number of WR day and high temperature and heat wave index, especially in 2013.GEV distribution and the number of hot day have different trends before and after 1976.Extreme high temperature is significant in urban area of Shanghai, and not in Fengxian station, Jinshan station and Chongming station.In general, different indices of extreme high temperature can comprehensively reflect climatic change trend of extreme high temperature events. References | Related Articles | Metrics

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Characteristics of climate change from 1960 to 2013 in Baiyangdian wetland LI Xiang, SHOU Shao-wen, BAI Yan-hui, WU Yun-long 2016, 32 (1):  75-83.  doi: 10.11927/j.issn.1673-503X.2016.01.011 Abstract ( 295 )   PDF (2581KB) ( 609 )   Save Based on observed data at 11 weather stations around the Baiyangdian wetland from 1960 to 2013, variation of annual and seasonal temperature and precipitation was analyzed by methods of a linear equation, a Person coefficient, a rate analysis and a Morlet wavelet analysis.The results show that annual mean air temperature is in an increasing trend, so is winter and spring temperature.Mean air temperature in summer and autumn is in a decreasing trend.However, increasing and decreasing trends of air temperature are not significant.The amplitudes of air temperature fluctuation are obviously weaker in Baiyangdian than in the surrounding areas.It suggests that microclimate in the wetland significantly modulates climate change.On the other hand, precipitation is in an increasing trend in spring and autumn, while it is in a decreasing trend in winter and summer, so is annual precipitation.All trends are not significant, while annual precipitation is lower in Baiyangdian wetland than in the surrounding areas.Furthermore, there is a 3-year cycle for annual and seasonal air temperature from 1960s to 2000 in Baiyangdian wetland and a 5-year cycle for annual, spring and autumn air temperature.The cycle is 3 years for annual and seasonal precipitation in 1960s, and it is 4 years during 1980s to 1990s. References | Related Articles | Metrics

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Change of spring maize during growth periods and its impact on yield from 1980 to 2010 in western Liaoning province ZHAO Xian-li, LI Li-guang, WANG Hong-bo, ZHAO Zi-qi, CAI Fu, YU Wen-ying, ZHANG Xiao-yue, DING Kang-kang, LI Jing 2016, 32 (1):  84-88.  doi: 10.11927/j.issn.1673-503X.2016.01.012 Abstract ( 298 )   PDF (554KB) ( 389 )   Save Based on observed data at 6 agricultural meteorological stations and spring maize yield data in the western Liaoning province from 1980 to 2010, variation of spring maize during growth period and its impact on yield were analyzed using methods of a climate trend rate and a correlation analysis.The results indicate that variation of the number of days during tasseling to flowering stage and flowering to milky maturity stage for spring maize has same trends at six stations of the western Liaoning province, while it is not the same in the other stages.Variation of number of days during different stages for spring maize is significant in Jianchang and Suizhong stations.The number of days of whole growth stage for spring maize is in an increasing trend except in Fuxin station.The trend rate is 5.00 days per decade in Zhangwu station, 7.03 days per decade in Jianchang station and 6.57 days per decade in Suizhong station, and they all pass through a significance test of 0.01 level.Anomalies of days of whole growth stage for spring maize change obviously in all stations of the western Liaoning province, and they are different in different growth stages.Anomalies of days of various growth stages change from negative to positive during 1980 to 2010. References | Related Articles | Metrics

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Risk evaluation on maize cold damage and frost damage in Liaoning province CHEN Kai-qi, MI Na 2016, 32 (1):  89-94.  doi: 10.11927/j.issn.1673-503X.2016.01.013 Abstract ( 407 )   PDF (1448KB) ( 605 )   Save Maize is an important crop in Liaoning province with the largest planting area and highest yield comparing to the other grain crops.Studies of regularity and risk on maize cold damage and frost damage are of vital importance for defending the disasters related to temperature and insuring the maize production security.Based on the daily temperature, the minimum temperature, maize planting area, maize yield at 49 weather stations of Liaoning province, the evaluation indexes and its value of maize cool damage and frost damage were determined.Then the integrated analysis of maize cold damage and frost damage was conducted from the respect of disaster hazard, disaster exposure and disaster sensitivity.Finally, the risk assessment and regionalization of cold damage and frost damage were investigated.The results show that the high-risk region of maize cold damage is located in Xifeng and east of Changtu.The middle-risk region is in the north and east of Liaoning province and the other places are attributed to low-risk region.For maize frost damage, the high-risk region is located in Jianping, Xifeng, Qingyuan and Xinbin, while low-risk region is in coastal areas and south of Liaoning province.In conclusion, under the background of climate warming, the more attention is still required on maize cold damage and frost damage. References | Related Articles | Metrics

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Analysis of spring temperature anomaly and its impact factors in Qinghai plateau SHEN Hong-yan, MA Ming-liang, SHI Xing-he, DAI Sheng, MA Zhan-liang 2016, 32 (1):  95-102.  doi: 10.11927/j.issn.1673-503X.2016.01.014 Abstract ( 294 )   PDF (3259KB) ( 516 )   Save Using temperature data in Qinghai province, monthly mean NCEP reanalysis data and circulation index from 1961 to 2012, characteristic of the spring temperature anomaly and its impact factors were analyzed.The results show that the spring temperature is in a significant increasing trend and has significant interdecadal variation.There are three types for variation of spring temperature, i.e.regional consistence type, east-west antiphase type and north-south antiphase type.There is obvious interdecadal variation for the former two types, while annual variation is significant for the north-south antiphase type.The key areas influencing the spring temperature anomaly are located in the Western Europe, Ural mountain, Qinghai plateau and its eastern region.Ural pressure ridge and east Asian trough influence directly the spring temperatute in Qinghai plateau.Also, the subtropical high and polar vortex index in Northern Hemisphere, Plateau height field are also the main impact factors of the spring temperature.At the same time, it has good response to anomaly of SST in the Somalia, the Arabian Sea, the Bay of Bengal of North Indian Ocean, the Northwest pacific and the Equatorial Pacific.It will be cold (warm) spring in Qinghai plateau when the SST in the above areas is low (high). References | Related Articles | Metrics

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Spatial and temporal climatic characteristics of hail from 1974 to 2013 in Gansu province HUANG Wu-bin, WANG Yan-feng, HUANG Yu-xia, WANG Lin 2016, 32 (1):  103-107.  doi: 10.11927/j.issn.1673-503X.2016.01.015 Abstract ( 368 )   PDF (2971KB) ( 389 )   Save Using hail data at 80 weather stations in Gansu province during 1974-2013, spatial and temporal characteristics of hail days were analyzed.The results show that the large value centers of hail days are located in Maqu, Wushaoling, Huajialing, Subei and Mazongshan, which is similar to elevation change.Hail weather often occurs in Gannan Plateau, Linxia, Wuwei areas during April to October, especially in Minxian station in April and Maqu station during May to October.It is in a decreasing trend for hail days in the recent 40 years, especially in Hedong region, and two low value centers are in Minxian-Gannan Plateau and Mazongshan.Number of hail days is reduced significantly since 1995 and has a 3.3 years cycle. References | Related Articles | Metrics

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Analysis of air quality situation and pollution reasons in Liaocheng WANG Cheng-xiang, LIU Jia-zhen 2016, 32 (1):  108-112.  doi: 10.11927/j.issn.1673-503X.2016.01.016 Abstract ( 420 )   PDF (587KB) ( 430 )   Save Based on monitoring data of main pollutants in Liaocheng from October of 2013 to September of 2014, temporal and spatial characteristic of all pollutants and their contribution to air pollution were analyzed.Reasons of air pollution in Liaocheng were discussed.The results show that the number of days with light pollution level or above accounts for 70% of the whole year.Concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO) and particulate matter (PM) have a similar seasonal variation, and they are significantly higher in winter than in summer.The number of days with PM2.5 and PM10 as primary pollutants is the greatest in Liaocheng, followed SO2 in winter.8 hours O3 concentration as the primary pollutant often occurs in summer.The order of contribution rate for five pollutants is PM2.5> PM10> NO2> CO> SO2, and the contribution rates of PM2.5 and PM10 are much higher than those of the other pollutants.It suggests that inhalable particulate and fine particles are prevailing in Liaocheng.Correlation analysis shows that PM2.5 and PM10 are possible to have the same or similar pollution sources.The main reasons for PM2.5 and PM10 pollution are attributed to wind lifting dust and use of fossil fuel. References | Related Articles | Metrics