In this paper, Urumqi Airport time-lapse ground man-made observation data from November 2015 to February 2017, European fine grid (0.25 × 0.25) initial field (20 o’clock) and the forecast field within 24 hours w...In this paper, Urumqi Airport time-lapse ground man-made observation data from November 2015 to February 2017, European fine grid (0.25 × 0.25) initial field (20 o’clock) and the forecast field within 24 hours were utilized. From November 2015 to February 2016, the relevant materials were used as research samples (a total of 948 times), and from November 2016 to February 2017 as test samples (a total of 922 times), statistical methods were used to establish the scoring standards. And each relevant element was scored. After the score, the score level range was delineated, and the visibility forecast was performed according to the scope. The conclusions are as follows: 1) European fine grid forecast products are with good correspondence with the visibility of this field are 850 hPa and 2 m high temperature inversion, 850 hPa relative humidity and 850 hPa wind field over the field. 2) Through the statistical analysis of scores, it is defined that the score below 400 is level 4, the score above 1000 is level 1, the difference is significant, and the forecast indication is strong. Level 2 and level 3 are more evenly distributed, with no more concentrated fractions. 3) Applying the test sample to test the above indicators. The forecast accuracy of level 1 is 61.2%, and the forecast accuracy of level 4 is 97.2%, so level 1 and level 4 are expected to obtain better forecast results, which is of practical application value.展开更多
[Objective] The research aimed to analyze change characteristics and forecast factors of the fog in Beibei District of Chongqing from 1953 to 2010. [Method] By observation data of the fog in Beibei District from 1953 ...[Objective] The research aimed to analyze change characteristics and forecast factors of the fog in Beibei District of Chongqing from 1953 to 2010. [Method] By observation data of the fog in Beibei District from 1953 to 2010, interdeoadal, interannual, seasonal and monthly varia- tion characteristics of the fog days and formation-dispersion time of the fog were conducted statistical analysis. Meteorological conditions and fore- cast factors of the fog were also analyzed. [Result] Distribution of the fog days in Beibei District had obvious interdecadal characteristics. Fog days was at its maximum in the 1980s while minimum in the 1960s. Fog duration presented slow increase trend. Interannual characteristic of the fog days overall presented increase trend, and it had 9-year periodic oscillation characteristic. Fog mainly concentrated in autumn and winter. Fog was mainly formed at night （20：00 -08：00） and dispersed in the daytime （08：00 -13：00）. Meteorological conditions which affected heavy fog in Beibei District were water vapor and stratification, wind field, temperature, relative humidity and so on. [ Conclusion] The research provided theoretical basis for scientific predication and forecast of the fog in Beibei District.展开更多
[Objective] The study aimed to discuss the characteristics and forecasting methods of dense fog in Xuzhou City. [Method] Based on the data of dense fog in Xuzhou City from 1960 to 2009, the characteristics and forming...[Objective] The study aimed to discuss the characteristics and forecasting methods of dense fog in Xuzhou City. [Method] Based on the data of dense fog in Xuzhou City from 1960 to 2009, the characteristics and forming conditions of dense fog in the region were analyzed, and then its forecasting methods were introduced, finally corresponding disaster prevention measures were put forward. [ Result] Dense fog might ap- pear in each season, its frequency of occurrence was the highest in December, namely 16.4% ; it was the lowest in June （2.2%）, and the fog las- ted for a short time and was thin. Heavy fog occurred more frequently in winter half year than summer half year, and the frequency of occurrence from October to next February was about 66.7%. In addition, dense fog mostly generated from late midnight to morning, while it appeared less in the afternoon. It shows that dense fog in Xuzhou City is mainly radiation fog instead of advection fog, but the two kinds of fog appeared simultane- ously sometimes. [ Conclusion] The research could provide scientific forecasting methods for the precise prediction of dense fog in Xuzhou City.展开更多
By analyzing meteorological data during 2000 -2009, the characteristics of fog in Changzhi region and weather situation of fog weather occurrence were summarized, and forecast equation was established.
[ Objective] The research aimed to study weather typing and dissipation forecast of the fog in Haizhou Bay. [ Method] Based on the me- teorological observation data of three representative stations in Lianyungang, we ...[ Objective] The research aimed to study weather typing and dissipation forecast of the fog in Haizhou Bay. [ Method] Based on the me- teorological observation data of three representative stations in Lianyungang, we analyzed weather situation before fog occurrence as well as the meteorological elements of coastal fog in Haizhou Bay, and established dissipation rating forecast equation of the fog. [ Result] From the surface weather chart, the fog in Haizhou Bay was divided into four types： low-pressure inverted trough type, prefrontal warm-zone type, high-pressure rear type and high-pressure bottom type. FOg formation was closely related to stratification stability, temperature, relative humidity, wind direction and wind velocity. By using multiple linear regression method, dissipation rating prediction equation of the fog was established. Via test, prediction was correct basically, and it reached 77% that forecast rating error was below level 0.5.[Conclusion] The research could provide favorable reference for forecast and warninq of the fo_q in Haizhou Bay.展开更多
Based on conventional observation data and NCEP reanalysis data at 10 national basic stations and reference stations of Shaoyang City during 1951-2014,300 cases of typical regional dense fog process appeared in the hi...Based on conventional observation data and NCEP reanalysis data at 10 national basic stations and reference stations of Shaoyang City during 1951-2014,300 cases of typical regional dense fog process appeared in the history were selected. From meteorological factors and weather situation,temporal-spatial distribution characteristics and trend change characteristics of dense fog in Shaoyang were analyzed. The results showed that（ 1） temporal-spatial distribution of dense fog in Shaoyang region was uneven,and interannual variability of fog days had large volatility and bad periodicity; dense fog days in Shaoyang region was obviously more in winter half year and less in summer half year. Dense fog was the most in November and the least in July. Dense fog mostly concentrated during 03： 00-09： 00; appearance time mostly concentrated during 05： 00-07： 30,and dissipation time mostly appeared after 08： 30. Dense fog appeared early and dissipated late in winter half year,and vice verse in summer half year.（ 2） Seen from meteorological factors,ground and 850 h Pa of wind velocity was generally 0-3 m/s,which was all small. Moreover,there existed temperature inversion from ground to 850 h Pa. Relative humidity on dense fog day was larger,and precipitation or cloudy day mostly appeared in prior day.（ 3） There were four kinds of ground weather situation forming dense fog： uniform pressure field type,cold and high pressure bottom type,cold and high pressure rear type,frontal type. Based on grasping change characteristics,rule and formation reason of dense fog,some forecast focus was found.展开更多
By analyzing the NCEP 1°×1° reanalysis (2004–2008), a number of predictors (factors of variables) are established with the output from the GRAPES model and with reference to the sea fog data from obser...By analyzing the NCEP 1°×1° reanalysis (2004–2008), a number of predictors (factors of variables) are established with the output from the GRAPES model and with reference to the sea fog data from observational stations (2004–2008) and field observations (2006–2008). Based on the criteria and conditions for sea fog appearance at the stations of Zhanjiang, Zhuhai and Shantou, a Model Output Statistics (MOS) scheme for distinguishing and forecasting 24-h sea fog is established and put into use for three representative coastal areas of Guangdong. As shown in an assessment of the forecasts for Zhanjiang and Shantou (March of 2008) and Zhuhai (April of 2008), the scheme was quite capable of forecasting sea fog on the coast of the province, with the accuracy ranging from 84% to 90%, the threat score from 0.40 to 0.50 and the Heidke skill from 0.52 to 0.56.展开更多
In the South China Sea, sea fog brings severe disasters every year, but forecasters have yet to implement an effective seafog forecast. To address this issue, we test a liquid-water-content-only(LWC-only) operational ...In the South China Sea, sea fog brings severe disasters every year, but forecasters have yet to implement an effective seafog forecast. To address this issue, we test a liquid-water-content-only(LWC-only) operational sea-fog prediction method based on a regional mesoscale numerical model with a horizontal resolution of about 3 km, the Global and Regional Assimilation and Prediction System(GRAPES), hereafter GRAPES-3 km. GRAPES-3 km models the LWC over the sea, from which we infer the visibility that is then used to identify fog. We test the GRAPES-3 km here against measurements in 2016 and 2017 from coastal-station observations, as well as from buoy data, data from the Integrated Observation Platform for Marine Meteorology, and retrieved fog and cloud patterns from Himawari-8 satellite data. For two cases that we examine in detail, the forecast region of sea fog overlaps well with the multi-observational data within 72 h. Considering forecasting for0–24 h, GRAPES-3 km has a 2-year-average equitable threat score(ETS) of 0.20 and a Heidke skill score(HSS) of 0.335,which is about 5.6%(ETS) and 6.4%(HSS) better than our previous method(GRAPES-MOS). Moreover, the stations near the particularly foggy region around the Leizhou Peninsula have relatively high forecast scores compared to other sea areas.Overall, the results show that GRAPES-3 km can roughly predict the formation, evolution, and dissipation of sea fog on the southern China coast.展开更多
Fog has recently become a frequent high-impact weather phenomenon along the coastal regions of North China. Accurate fog forecasting remains challenging due to limited understanding of the predictability and mechanism...Fog has recently become a frequent high-impact weather phenomenon along the coastal regions of North China. Accurate fog forecasting remains challenging due to limited understanding of the predictability and mechanism of fog formation associated with synoptic-scale circulation. One frequent synoptic pattern of fog formation in this area is associated with cold front passage(cold-front synoptic pattern, CFSP). This paper explored the predictability of a typical CFSP fog event from the perspective of analyzing key characteristics of synoptic-scale circulation determining fog forecasting performance and the possible mechanism. The event was ensemble forecasted with the Weather Research and Forecasting model. Two groups of ensemble members with good and bad forecasting performance were selected and composited. Results showed that the predictability of this case was largely determined by the simulated strengths of the cold-front circulation(i.e., trough and ridge and the associated surface high). The bad-performing members tended to have a weaker ridge behind a stronger trough, and associated higher pressure over land and a weaker surface high over the sea, leading to an adverse impact on strength and direction of steering flows that inhibit warm moist advection and enhance cold dry advection transported to the focus region. Associated with this cold dry advection, adverse synoptic conditions of stratification and moisture for fog formation were produced, consequently causing failure of fog forecasting in the focus region. This study highlights the importance of accurate synoptic-scale information for improved CFSP fog forecasting, and enhances understanding of fog predictability from perspective of synoptic-scale circulation.展开更多
利用2017年至2019年山东半岛15个沿海气象站观测资料和欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)细网格模式预报数据,采用逐日预报准确率和逐月平均差值计算方法,对地面2 m温度进行了检验,针对...利用2017年至2019年山东半岛15个沿海气象站观测资料和欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)细网格模式预报数据,采用逐日预报准确率和逐月平均差值计算方法,对地面2 m温度进行了检验,针对威海地区冷空气、冷流降雪和海雾过程分别进行了预报性能检验。结果表明:24 h时效内预报误差≤2℃时,低温预报准确率为60%~95%,高温预报准确率为50%~89%。低温预报中,北部沿海和南部沿海在3月至9月逐月平均预报误差小于1℃。冷空气过程高温预报正负差值比率相当,低温预报正差值的占比较大,最高为96%;冷流降雪过程中,高、低温预报整体以正差值为主;浓雾出现区域,模式的低温预报偏高。模式结果可为3月至9月低温预报提供较好的参考依据。展开更多
文摘In this paper, Urumqi Airport time-lapse ground man-made observation data from November 2015 to February 2017, European fine grid (0.25 × 0.25) initial field (20 o’clock) and the forecast field within 24 hours were utilized. From November 2015 to February 2016, the relevant materials were used as research samples (a total of 948 times), and from November 2016 to February 2017 as test samples (a total of 922 times), statistical methods were used to establish the scoring standards. And each relevant element was scored. After the score, the score level range was delineated, and the visibility forecast was performed according to the scope. The conclusions are as follows: 1) European fine grid forecast products are with good correspondence with the visibility of this field are 850 hPa and 2 m high temperature inversion, 850 hPa relative humidity and 850 hPa wind field over the field. 2) Through the statistical analysis of scores, it is defined that the score below 400 is level 4, the score above 1000 is level 1, the difference is significant, and the forecast indication is strong. Level 2 and level 3 are more evenly distributed, with no more concentrated fractions. 3) Applying the test sample to test the above indicators. The forecast accuracy of level 1 is 61.2%, and the forecast accuracy of level 4 is 97.2%, so level 1 and level 4 are expected to obtain better forecast results, which is of practical application value.
文摘[Objective] The research aimed to analyze change characteristics and forecast factors of the fog in Beibei District of Chongqing from 1953 to 2010. [Method] By observation data of the fog in Beibei District from 1953 to 2010, interdeoadal, interannual, seasonal and monthly varia- tion characteristics of the fog days and formation-dispersion time of the fog were conducted statistical analysis. Meteorological conditions and fore- cast factors of the fog were also analyzed. [Result] Distribution of the fog days in Beibei District had obvious interdecadal characteristics. Fog days was at its maximum in the 1980s while minimum in the 1960s. Fog duration presented slow increase trend. Interannual characteristic of the fog days overall presented increase trend, and it had 9-year periodic oscillation characteristic. Fog mainly concentrated in autumn and winter. Fog was mainly formed at night （20：00 -08：00） and dispersed in the daytime （08：00 -13：00）. Meteorological conditions which affected heavy fog in Beibei District were water vapor and stratification, wind field, temperature, relative humidity and so on. [ Conclusion] The research provided theoretical basis for scientific predication and forecast of the fog in Beibei District.
基金Supported by Special Fund for Forecasters of Jiangsu Provincial Meteorological Bureau (Study on the Forecasting Model of Dense Fog in Xuzhou City Based on SVM Method)
文摘[Objective] The study aimed to discuss the characteristics and forecasting methods of dense fog in Xuzhou City. [Method] Based on the data of dense fog in Xuzhou City from 1960 to 2009, the characteristics and forming conditions of dense fog in the region were analyzed, and then its forecasting methods were introduced, finally corresponding disaster prevention measures were put forward. [ Result] Dense fog might ap- pear in each season, its frequency of occurrence was the highest in December, namely 16.4% ; it was the lowest in June （2.2%）, and the fog las- ted for a short time and was thin. Heavy fog occurred more frequently in winter half year than summer half year, and the frequency of occurrence from October to next February was about 66.7%. In addition, dense fog mostly generated from late midnight to morning, while it appeared less in the afternoon. It shows that dense fog in Xuzhou City is mainly radiation fog instead of advection fog, but the two kinds of fog appeared simultane- ously sometimes. [ Conclusion] The research could provide scientific forecasting methods for the precise prediction of dense fog in Xuzhou City.
文摘By analyzing meteorological data during 2000 -2009, the characteristics of fog in Changzhi region and weather situation of fog weather occurrence were summarized, and forecast equation was established.
基金Supported by Youth Science Research Fund in Jiangsu Meteorological Bureau,China(Q201007)Special Item of Forecaster in Jiangsu Province,China(201207)
文摘[ Objective] The research aimed to study weather typing and dissipation forecast of the fog in Haizhou Bay. [ Method] Based on the me- teorological observation data of three representative stations in Lianyungang, we analyzed weather situation before fog occurrence as well as the meteorological elements of coastal fog in Haizhou Bay, and established dissipation rating forecast equation of the fog. [ Result] From the surface weather chart, the fog in Haizhou Bay was divided into four types： low-pressure inverted trough type, prefrontal warm-zone type, high-pressure rear type and high-pressure bottom type. FOg formation was closely related to stratification stability, temperature, relative humidity, wind direction and wind velocity. By using multiple linear regression method, dissipation rating prediction equation of the fog was established. Via test, prediction was correct basically, and it reached 77% that forecast rating error was below level 0.5.[Conclusion] The research could provide favorable reference for forecast and warninq of the fo_q in Haizhou Bay.
文摘Based on conventional observation data and NCEP reanalysis data at 10 national basic stations and reference stations of Shaoyang City during 1951-2014,300 cases of typical regional dense fog process appeared in the history were selected. From meteorological factors and weather situation,temporal-spatial distribution characteristics and trend change characteristics of dense fog in Shaoyang were analyzed. The results showed that（ 1） temporal-spatial distribution of dense fog in Shaoyang region was uneven,and interannual variability of fog days had large volatility and bad periodicity; dense fog days in Shaoyang region was obviously more in winter half year and less in summer half year. Dense fog was the most in November and the least in July. Dense fog mostly concentrated during 03： 00-09： 00; appearance time mostly concentrated during 05： 00-07： 30,and dissipation time mostly appeared after 08： 30. Dense fog appeared early and dissipated late in winter half year,and vice verse in summer half year.（ 2） Seen from meteorological factors,ground and 850 h Pa of wind velocity was generally 0-3 m/s,which was all small. Moreover,there existed temperature inversion from ground to 850 h Pa. Relative humidity on dense fog day was larger,and precipitation or cloudy day mostly appeared in prior day.（ 3） There were four kinds of ground weather situation forming dense fog： uniform pressure field type,cold and high pressure bottom type,cold and high pressure rear type,frontal type. Based on grasping change characteristics,rule and formation reason of dense fog,some forecast focus was found.
基金Natural Science Foundation of China (40675013)Research on Techniques of Specialized Forecast of Sea Fog and Visibility at the Pearl River Mouth+2 种基金project of Science and Technology Program of Guangdong Province (2006B37202005)Research on System of Monitoring Sea Fog for the Pearl River Mouthproject of Meteorological Science of Guangdong Meteorological Bureau
文摘By analyzing the NCEP 1°×1° reanalysis (2004–2008), a number of predictors (factors of variables) are established with the output from the GRAPES model and with reference to the sea fog data from observational stations (2004–2008) and field observations (2006–2008). Based on the criteria and conditions for sea fog appearance at the stations of Zhanjiang, Zhuhai and Shantou, a Model Output Statistics (MOS) scheme for distinguishing and forecasting 24-h sea fog is established and put into use for three representative coastal areas of Guangdong. As shown in an assessment of the forecasts for Zhanjiang and Shantou (March of 2008) and Zhuhai (April of 2008), the scheme was quite capable of forecasting sea fog on the coast of the province, with the accuracy ranging from 84% to 90%, the threat score from 0.40 to 0.50 and the Heidke skill from 0.52 to 0.56.
基金supported jointly by the National Natural Science Foundation of China (Grant Nos. 41675021, 41605006 and 41675019)the Meteorological Sciences Research Project (Grant No. GRMC2017M04)the Innovation Team of Forecasting Technology for Typhoon and Marine Meteorology of the Weather Bureau of Guangdong Province
文摘In the South China Sea, sea fog brings severe disasters every year, but forecasters have yet to implement an effective seafog forecast. To address this issue, we test a liquid-water-content-only(LWC-only) operational sea-fog prediction method based on a regional mesoscale numerical model with a horizontal resolution of about 3 km, the Global and Regional Assimilation and Prediction System(GRAPES), hereafter GRAPES-3 km. GRAPES-3 km models the LWC over the sea, from which we infer the visibility that is then used to identify fog. We test the GRAPES-3 km here against measurements in 2016 and 2017 from coastal-station observations, as well as from buoy data, data from the Integrated Observation Platform for Marine Meteorology, and retrieved fog and cloud patterns from Himawari-8 satellite data. For two cases that we examine in detail, the forecast region of sea fog overlaps well with the multi-observational data within 72 h. Considering forecasting for0–24 h, GRAPES-3 km has a 2-year-average equitable threat score(ETS) of 0.20 and a Heidke skill score(HSS) of 0.335,which is about 5.6%(ETS) and 6.4%(HSS) better than our previous method(GRAPES-MOS). Moreover, the stations near the particularly foggy region around the Leizhou Peninsula have relatively high forecast scores compared to other sea areas.Overall, the results show that GRAPES-3 km can roughly predict the formation, evolution, and dissipation of sea fog on the southern China coast.
基金supported by the National Key R&D Program of China (Nos. 2017YFC1404100 and 2017YFC1404104)the National Natural Science Foundation of China (Nos. 41705081 and 41575067)the Global Change Research Program of China (No. 2015CB953904)
文摘Fog has recently become a frequent high-impact weather phenomenon along the coastal regions of North China. Accurate fog forecasting remains challenging due to limited understanding of the predictability and mechanism of fog formation associated with synoptic-scale circulation. One frequent synoptic pattern of fog formation in this area is associated with cold front passage(cold-front synoptic pattern, CFSP). This paper explored the predictability of a typical CFSP fog event from the perspective of analyzing key characteristics of synoptic-scale circulation determining fog forecasting performance and the possible mechanism. The event was ensemble forecasted with the Weather Research and Forecasting model. Two groups of ensemble members with good and bad forecasting performance were selected and composited. Results showed that the predictability of this case was largely determined by the simulated strengths of the cold-front circulation(i.e., trough and ridge and the associated surface high). The bad-performing members tended to have a weaker ridge behind a stronger trough, and associated higher pressure over land and a weaker surface high over the sea, leading to an adverse impact on strength and direction of steering flows that inhibit warm moist advection and enhance cold dry advection transported to the focus region. Associated with this cold dry advection, adverse synoptic conditions of stratification and moisture for fog formation were produced, consequently causing failure of fog forecasting in the focus region. This study highlights the importance of accurate synoptic-scale information for improved CFSP fog forecasting, and enhances understanding of fog predictability from perspective of synoptic-scale circulation.
文摘利用2017年至2019年山东半岛15个沿海气象站观测资料和欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)细网格模式预报数据,采用逐日预报准确率和逐月平均差值计算方法,对地面2 m温度进行了检验,针对威海地区冷空气、冷流降雪和海雾过程分别进行了预报性能检验。结果表明:24 h时效内预报误差≤2℃时,低温预报准确率为60%~95%,高温预报准确率为50%~89%。低温预报中,北部沿海和南部沿海在3月至9月逐月平均预报误差小于1℃。冷空气过程高温预报正负差值比率相当,低温预报正差值的占比较大,最高为96%;冷流降雪过程中,高、低温预报整体以正差值为主;浓雾出现区域,模式的低温预报偏高。模式结果可为3月至9月低温预报提供较好的参考依据。
