ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 39,Issue 3,2013 Table of Contents
2013, 39(3):265-280.
DOI: 10.7519/j.issn.1000-0526.2013.03.001
Abstract:
The large scale CINRAD operational network has been built in China. Using quite a lot of data from the network, this paper analyzed the detection capability of the radar network in monitoring the large scale weather systems including cold front, extratropical cyclone, Jianghuai shear line, low level jet stream and typhoon; the mesoscale weather systems such as squall line, gust front, hail and thunderstorm high in severe convective weathers as well as the Meiyu front rainstorm. In addition, the scanning strategy and parameter setting in the CINRAD operation model as well as the features and problems of its technical system were discussed. The progresses are as follows: (1) Improving the existing observation model: Adding clear air mode and RHI vertical scanning 〖JP2〗mode to strengthen the radar detecting capability to clear air echoes〖JP〗 and the refinement of vertical structure; setting high mountain observation mode to enhance the capability to the boundary layer. (2) Improving radar adaption parameter to solve the problem of range folding and velocity ambiguity. (3) Using pulse compression method to develop the detecting capability to weak echoes and keeping spatial resolution of radar data. (4) Making good use of radar networking technology to realize simultaneous observations in time and space on different scale disastrous systems. (5) Using dual polarization technology to improve the accuracy of quantitative precipitation estimation and identify the precipitation phase state. Based on the above five grogresses, a preliminary scheme of radar technology upgrading was proposed. Finally, an outlook for the development of future CINRAD was presented as well.
The large scale CINRAD operational network has been built in China. Using quite a lot of data from the network, this paper analyzed the detection capability of the radar network in monitoring the large scale weather systems including cold front, extratropical cyclone, Jianghuai shear line, low level jet stream and typhoon; the mesoscale weather systems such as squall line, gust front, hail and thunderstorm high in severe convective weathers as well as the Meiyu front rainstorm. In addition, the scanning strategy and parameter setting in the CINRAD operation model as well as the features and problems of its technical system were discussed. The progresses are as follows: (1) Improving the existing observation model: Adding clear air mode and RHI vertical scanning 〖JP2〗mode to strengthen the radar detecting capability to clear air echoes〖JP〗 and the refinement of vertical structure; setting high mountain observation mode to enhance the capability to the boundary layer. (2) Improving radar adaption parameter to solve the problem of range folding and velocity ambiguity. (3) Using pulse compression method to develop the detecting capability to weak echoes and keeping spatial resolution of radar data. (4) Making good use of radar networking technology to realize simultaneous observations in time and space on different scale disastrous systems. (5) Using dual polarization technology to improve the accuracy of quantitative precipitation estimation and identify the precipitation phase state. Based on the above five grogresses, a preliminary scheme of radar technology upgrading was proposed. Finally, an outlook for the development of future CINRAD was presented as well.
2013, 39(3):281-290.
DOI: 10.7519/j.issn.1000-0526.2013.03.002
Abstract:
By using conventional observation data and NCEP reanalysis data, diagnostic analysis is performed on a rainstorm process, which occurred on 22-25 July 2010 in the western part of Sichuan Basin. The result shows that the rainstorm was generated under the circulation background that low level southerly airflows had remained over the region from the South China Sea to Sichuan Basin, so this rainstorm was closely related to the evolution of the southerly wind speeds. The rainfall intensity increased as the south winds grew stronger. Speed convergence formed by the enhanced south winds and positive vorticity advections became main dynamic trigger factors for the rainstorm. Therefore, the rainstorm is pretty consistent with the low level convergence and the positive vorticity advection. In addition, the result of WRF numerical simulation further indicates that: the evolution of 3 h wind speed at 850 hPa has good indication for the development of mesoscale convective systems. On the leeward side of the 3 h wind speed increasing area, convective cloud clusters are to develop rapidly in the next 3 hours. Moreover, the topographic influence simulation tests suggest that the airflow convergence generated in the west of the Basin is closely related to the topography of plateau.
By using conventional observation data and NCEP reanalysis data, diagnostic analysis is performed on a rainstorm process, which occurred on 22-25 July 2010 in the western part of Sichuan Basin. The result shows that the rainstorm was generated under the circulation background that low level southerly airflows had remained over the region from the South China Sea to Sichuan Basin, so this rainstorm was closely related to the evolution of the southerly wind speeds. The rainfall intensity increased as the south winds grew stronger. Speed convergence formed by the enhanced south winds and positive vorticity advections became main dynamic trigger factors for the rainstorm. Therefore, the rainstorm is pretty consistent with the low level convergence and the positive vorticity advection. In addition, the result of WRF numerical simulation further indicates that: the evolution of 3 h wind speed at 850 hPa has good indication for the development of mesoscale convective systems. On the leeward side of the 3 h wind speed increasing area, convective cloud clusters are to develop rapidly in the next 3 hours. Moreover, the topographic influence simulation tests suggest that the airflow convergence generated in the west of the Basin is closely related to the topography of plateau.
2013, 39(3):291-301.
DOI: 10.7519/j.issn.1000-0526.2013.03.003
Abstract:
In autumn, the weak convection case covers more percentage in Huabei (North China). In order to improve the ability to diagnose the convection intensity, two linear cases are analyzed which develop in the similar synoptic background but in different strength. The result indicates that strong convection develops in the deep upward current (to 200 hPa). And the absolute humidity in the lower troposphere is higher. However, in the weak one, the ascending current exists below 500 hPa only. At the same time, the specific humidity in the BL (boundary layer) is just (5-7) g·kg-1 which is (2-5) g·kg-1 lower than that of the strong case. These lead to the convection in different strength mainly. The deep anaflow in the strong case is caused by convergence line, dewpoint front and upper level trough. Furthermore, a strong divergence appearing in the upper troposphere overlaps the convergence layer. As the result, upward current enhances and goes up further. But for weak case, the cold air invades to the mid troposphere and makes the ascending current which could reach to the upper levels. The thermodynamic background difference appears in the lower troposphere. When strong convection develops, the instable energy accumulates in the convective area and CAPE reaches 1087 J·kg-1. Besides, from the surface to 600 or 700 hPa, it is warm and moist and being instable also. In the weak case, CAPE is 68 J·kg-1. Above the BL, it is cold and dry comparatively. Therefore, the following items could be helpful in the diagnosis of the convection strength in autumn: the depth of the upward current, the absolute humidity in the lower troposphere, the thickness of a layer which is not only unstable but also warm and wet.
In autumn, the weak convection case covers more percentage in Huabei (North China). In order to improve the ability to diagnose the convection intensity, two linear cases are analyzed which develop in the similar synoptic background but in different strength. The result indicates that strong convection develops in the deep upward current (to 200 hPa). And the absolute humidity in the lower troposphere is higher. However, in the weak one, the ascending current exists below 500 hPa only. At the same time, the specific humidity in the BL (boundary layer) is just (5-7) g·kg-1 which is (2-5) g·kg-1 lower than that of the strong case. These lead to the convection in different strength mainly. The deep anaflow in the strong case is caused by convergence line, dewpoint front and upper level trough. Furthermore, a strong divergence appearing in the upper troposphere overlaps the convergence layer. As the result, upward current enhances and goes up further. But for weak case, the cold air invades to the mid troposphere and makes the ascending current which could reach to the upper levels. The thermodynamic background difference appears in the lower troposphere. When strong convection develops, the instable energy accumulates in the convective area and CAPE reaches 1087 J·kg-1. Besides, from the surface to 600 or 700 hPa, it is warm and moist and being instable also. In the weak case, CAPE is 68 J·kg-1. Above the BL, it is cold and dry comparatively. Therefore, the following items could be helpful in the diagnosis of the convection strength in autumn: the depth of the upward current, the absolute humidity in the lower troposphere, the thickness of a layer which is not only unstable but also warm and wet.
2013, 39(3):302-312.
DOI: 10.7519/j.issn.1000-0526.2013.03.004
Abstract:
Based on NCEP/NCAR 1°×1° reanalysis data, conventional observational data and the FY 2E satellite data, the physical mechanism of an emergent Yellow River cyclone which induced strong winds over Yellow and Bohai Seas during 26-27 April 2011 is analyzed. It is shown that this event occurred during the period of adjustment of Eurasia mid high latitude circulations, east moving and development of unstable short wave trough at high latitudes and rebuilding of East Asian major trough. A strongly developed Yellow River cyclone was the engenderer of the northerly gale winds. Vorticity advection was a key factor in the growth of the cyclone, and subsequently, temperature advection played an important role. The baroclinicity near cold front was important to the genesis and development of cyclone by transforming available potential energy into kinetic energy. As the cyclone moves, 〖WTHX〗Q〖WTBZ〗 vectors always matched well with divergence maxima, and dynamic and thermal conditions were favorable to accumulate potential energy as well as to enhance and maintain the cyclone. Our results indicate that the strongly development of Yellow River cyclone was associated with vertical coupling between the upper westerly and lower southerly jets, thermal forcing of low level moist warm flow, and subsequently, the ascending motion in lower layers. And the gale winds over Yellow and Bohai Seas resulted from the combined impact of isallobaric gradient, pressure gradient, downward propagation of upper level momentum and divergence of super low level jet.
Based on NCEP/NCAR 1°×1° reanalysis data, conventional observational data and the FY 2E satellite data, the physical mechanism of an emergent Yellow River cyclone which induced strong winds over Yellow and Bohai Seas during 26-27 April 2011 is analyzed. It is shown that this event occurred during the period of adjustment of Eurasia mid high latitude circulations, east moving and development of unstable short wave trough at high latitudes and rebuilding of East Asian major trough. A strongly developed Yellow River cyclone was the engenderer of the northerly gale winds. Vorticity advection was a key factor in the growth of the cyclone, and subsequently, temperature advection played an important role. The baroclinicity near cold front was important to the genesis and development of cyclone by transforming available potential energy into kinetic energy. As the cyclone moves, 〖WTHX〗Q〖WTBZ〗 vectors always matched well with divergence maxima, and dynamic and thermal conditions were favorable to accumulate potential energy as well as to enhance and maintain the cyclone. Our results indicate that the strongly development of Yellow River cyclone was associated with vertical coupling between the upper westerly and lower southerly jets, thermal forcing of low level moist warm flow, and subsequently, the ascending motion in lower layers. And the gale winds over Yellow and Bohai Seas resulted from the combined impact of isallobaric gradient, pressure gradient, downward propagation of upper level momentum and divergence of super low level jet.
2013, 39(3):313-323.
DOI: 10.7519/j.issn.1000-0526.2013.03.005
Abstract:
The daily precipitation records of 59 rain gauges over the Huaihe River Basin and the ensemble mean forecasts of 24 h cumulated precipitation of the reforecast data generated by Global Forecast System (GFS) during the period of 1 January 1981 to 31 December 2003 are employed to construct a probability forecast model which can produce ensemble forecast based on conditional meta Gaussian distribution. The experiment to show how well the model works is done in four catchments of Huaihe River Basin. The result shows that the root mean square error (RMSE) of the ensemble forecasts generated by the new method introduced here reduces remarkably for all catchments and seasons. Especially the RMSE reduces by 3.11 mm in the stream between Bengbu Station and Hongze Lake in June. The brier skill score (BSS) of the ensemble forecasts of four catchments is between 0.16 and 0.61, suggesting that the ensemble forecasts can be used throughout the whole year. The ensemble forecasts in summer of the stream between Dapoling and Xixian Station are always lower than the observations in varying degrees when the threshold of daily mean areal precipitation (MAP) is between 0.00 mm and 7.82 mm, but when the threshold is 18.12 mm, the ensemble forecast in summer shows better reliability. Known from the percentile comparison between the ensemble forecasts and the observations, the ensemble forecast can capture more precipitation events of small magnitude MAP but is weak in forecasting MAP of large magnitude over 30 mm.
The daily precipitation records of 59 rain gauges over the Huaihe River Basin and the ensemble mean forecasts of 24 h cumulated precipitation of the reforecast data generated by Global Forecast System (GFS) during the period of 1 January 1981 to 31 December 2003 are employed to construct a probability forecast model which can produce ensemble forecast based on conditional meta Gaussian distribution. The experiment to show how well the model works is done in four catchments of Huaihe River Basin. The result shows that the root mean square error (RMSE) of the ensemble forecasts generated by the new method introduced here reduces remarkably for all catchments and seasons. Especially the RMSE reduces by 3.11 mm in the stream between Bengbu Station and Hongze Lake in June. The brier skill score (BSS) of the ensemble forecasts of four catchments is between 0.16 and 0.61, suggesting that the ensemble forecasts can be used throughout the whole year. The ensemble forecasts in summer of the stream between Dapoling and Xixian Station are always lower than the observations in varying degrees when the threshold of daily mean areal precipitation (MAP) is between 0.00 mm and 7.82 mm, but when the threshold is 18.12 mm, the ensemble forecast in summer shows better reliability. Known from the percentile comparison between the ensemble forecasts and the observations, the ensemble forecast can capture more precipitation events of small magnitude MAP but is weak in forecasting MAP of large magnitude over 30 mm.
2013, 39(3):324-332.
DOI: 10.7519/j.issn.1000-0526.2013.03.006
Abstract:
The linear regression (LR) and artificial neural network (ANN) methods are compared with each other in forecasting precipitation types under the same conditions. The selected predictors are surface air temperature and dew point when and 6 hours before precipitation happens, and the types include rain, sleet and snow. The observation data from 756 weather stations of the National Meteorological Centre, CMA during 2001-2011 are used, of which the data of 2001-2010 are used to test the methods and the 2011 data are used to verify the forecasting effects. The results show that both of the LR and ANN methods have prediction capacity for the three precipitation types of snow, rain and sleet. The predictability of snow is the best, then is rain, and the worst is sleet. Forecasts for the rain and snow separatrix forcasted by the two methods in the North of China are better than that in the South of China. The forecasting effect of ANN method is superior to that of LR method under the same conditions. When the temperature and dew point are forecasted correctly, the ANN method can be used to predict the rain and snow separatrix in the North of China exactly.
The linear regression (LR) and artificial neural network (ANN) methods are compared with each other in forecasting precipitation types under the same conditions. The selected predictors are surface air temperature and dew point when and 6 hours before precipitation happens, and the types include rain, sleet and snow. The observation data from 756 weather stations of the National Meteorological Centre, CMA during 2001-2011 are used, of which the data of 2001-2010 are used to test the methods and the 2011 data are used to verify the forecasting effects. The results show that both of the LR and ANN methods have prediction capacity for the three precipitation types of snow, rain and sleet. The predictability of snow is the best, then is rain, and the worst is sleet. Forecasts for the rain and snow separatrix forcasted by the two methods in the North of China are better than that in the South of China. The forecasting effect of ANN method is superior to that of LR method under the same conditions. When the temperature and dew point are forecasted correctly, the ANN method can be used to predict the rain and snow separatrix in the North of China exactly.
2013, 39(3):333-339.
DOI: 10.7519/j.issn.1000-0526.2013.03.007
Abstract:
The neural network approach has been extensively studied in the past years. Especially, the artificial neural network based on error back propagation algorithm (BP ANN) has played an important role in weather forecasting. But there is a problem for the BP ANN training: With the same sample model, the same network structure and the same input parameters, the weight and the final error results from each training are always not the same. Some final error results are good, but some poorer. So in the use of the BP ANN modeling training, we hope to find out a local optimal solution of the predictor model, helping the models estabish better generalization ability. In order to improve the BP ANN modeling and forecasting capability in forecasting operations, two year (2009-2011, each year from May 15 to September 15) forecast data from T639 and the maximum observed temperature from four stations in Beijing are used for numerical simulation. It is found by fitting modeling trials on four model samples that by using three improved methods, BP ANN’s random weights have a Gaussian distribution or initial weights field are initialized repeatedly, and with hidden layer neurons using dynamic network structure, hit rate from BP ANN fitting of the sample has improved to some extent. The last but the most important, taking the data of 115 days (from 15 May to 15 September 2011) as a forecast test data, three improved methods are integrated in BP ANN. Compared with the BP ANN before improvement, the result is found to be: hit rate from validation sample using the improved BP ANN is higher than the non improved BP ANN, and the optimized BP ANN has better generalization ability.
The neural network approach has been extensively studied in the past years. Especially, the artificial neural network based on error back propagation algorithm (BP ANN) has played an important role in weather forecasting. But there is a problem for the BP ANN training: With the same sample model, the same network structure and the same input parameters, the weight and the final error results from each training are always not the same. Some final error results are good, but some poorer. So in the use of the BP ANN modeling training, we hope to find out a local optimal solution of the predictor model, helping the models estabish better generalization ability. In order to improve the BP ANN modeling and forecasting capability in forecasting operations, two year (2009-2011, each year from May 15 to September 15) forecast data from T639 and the maximum observed temperature from four stations in Beijing are used for numerical simulation. It is found by fitting modeling trials on four model samples that by using three improved methods, BP ANN’s random weights have a Gaussian distribution or initial weights field are initialized repeatedly, and with hidden layer neurons using dynamic network structure, hit rate from BP ANN fitting of the sample has improved to some extent. The last but the most important, taking the data of 115 days (from 15 May to 15 September 2011) as a forecast test data, three improved methods are integrated in BP ANN. Compared with the BP ANN before improvement, the result is found to be: hit rate from validation sample using the improved BP ANN is higher than the non improved BP ANN, and the optimized BP ANN has better generalization ability.
2013, 39(3):340-346.
DOI: 10.7519/j.issn.1000-0526.2013.03.008
Abstract:
Based on replacing the original USGS land use data with a new urban land use dataset, the 1 km gridpoint interval WRF model and its coupling Urban Canopy Model (UCM) were used to simulate an extreme rainfall event that occurred in Beijing City on 23 June 2011. The result of the sensitivity experiment more agrees with the reality than the control experiment. Difference in surface energy balance between urban and rural areas shows that in daytime urban area absorbs more solar radiation for the area exhibits lower values of albedo. Due to the lack of vegetation in the urban, which inhibits cooling by evapotranspiration, most part of the incoming energy is partitioned into sensible heat flux to heat the urban region. The urban expansion reduces natural vegetation cover, and then it can help to decrease ground evaporation and local water vapor supply, enlarge surface sensible heat flux, deepen PBL height and enhance the mixing of water vapor. Hence it is not conducive to the occurrence of the rainfall.
Based on replacing the original USGS land use data with a new urban land use dataset, the 1 km gridpoint interval WRF model and its coupling Urban Canopy Model (UCM) were used to simulate an extreme rainfall event that occurred in Beijing City on 23 June 2011. The result of the sensitivity experiment more agrees with the reality than the control experiment. Difference in surface energy balance between urban and rural areas shows that in daytime urban area absorbs more solar radiation for the area exhibits lower values of albedo. Due to the lack of vegetation in the urban, which inhibits cooling by evapotranspiration, most part of the incoming energy is partitioned into sensible heat flux to heat the urban region. The urban expansion reduces natural vegetation cover, and then it can help to decrease ground evaporation and local water vapor supply, enlarge surface sensible heat flux, deepen PBL height and enhance the mixing of water vapor. Hence it is not conducive to the occurrence of the rainfall.
2013, 39(3):347-354.
DOI: 10.7519/j.issn.1000-0526.2013.03.009
Abstract:
This paper presents an analysis of variation characteristics and long term trend of acid rain in Taishan Mountain area, using the observed data of Taishan Mountain Weather Station from 1992 to 2010 and the data of Tai’an Weather Station from 2007 to 2010. The two stations are located within a distance of 10 km, and the latter sits at the foot of Taishan Mountain. The annual average precipitation pH values of the Taishan Mountain Station are generally below 5.60 except the two values in 1999 and 2001, with a variation ranging from 4.31 to 6.47. These pH values reveal two different periods of variation: one is a fluctuation change with no significant trend during 1992-1999, and another is a steady decrease trend from 2000 to 2010 at the annual rate of -0.15 a-1. The monthly average precipitation pH values over these years at Taishan Mountain Station vary from 4.50 to 5.02 with higher values in March and July and lower values in August and September, having an irregular seasonal variation. The monthly average pH values of Tai’an Weather Station have similar features in seasonal variation with Taishan Mountain Station, except the irregular changes in a few months due to limited data. Compared with the acid rain data from other mountain weather stations in China, the precipitation acidity of Taishan Mountain Station is much stronger than that of the mountains in the Northwest of China, similar with that of mountains in the Southwest of China, but a little weaker than that of Dayao Mountain, which is located in Guangdong Province, South China. The comparison of precipitation pH values and NHCs between Taishan Mountain Station and Tai’an Station indicates that the pH values and average NHCs of Tai’an Station are higher than those of Taishan Mountain Station. The most ΔpH values and ΔNHCs, which means the differences of pH values and of NHCs between Tai’an Station and Taishan Mountain Station when the two sites see rains at the same time and it begins to rain in less than two hours, are positive. This is probably due to the different contributions of scavenging the below clouds of atmospheric pollutants like aerosols， SO2 and NOx to the chemical composition of the rainwater at the two stations.
This paper presents an analysis of variation characteristics and long term trend of acid rain in Taishan Mountain area, using the observed data of Taishan Mountain Weather Station from 1992 to 2010 and the data of Tai’an Weather Station from 2007 to 2010. The two stations are located within a distance of 10 km, and the latter sits at the foot of Taishan Mountain. The annual average precipitation pH values of the Taishan Mountain Station are generally below 5.60 except the two values in 1999 and 2001, with a variation ranging from 4.31 to 6.47. These pH values reveal two different periods of variation: one is a fluctuation change with no significant trend during 1992-1999, and another is a steady decrease trend from 2000 to 2010 at the annual rate of -0.15 a-1. The monthly average precipitation pH values over these years at Taishan Mountain Station vary from 4.50 to 5.02 with higher values in March and July and lower values in August and September, having an irregular seasonal variation. The monthly average pH values of Tai’an Weather Station have similar features in seasonal variation with Taishan Mountain Station, except the irregular changes in a few months due to limited data. Compared with the acid rain data from other mountain weather stations in China, the precipitation acidity of Taishan Mountain Station is much stronger than that of the mountains in the Northwest of China, similar with that of mountains in the Southwest of China, but a little weaker than that of Dayao Mountain, which is located in Guangdong Province, South China. The comparison of precipitation pH values and NHCs between Taishan Mountain Station and Tai’an Station indicates that the pH values and average NHCs of Tai’an Station are higher than those of Taishan Mountain Station. The most ΔpH values and ΔNHCs, which means the differences of pH values and of NHCs between Tai’an Station and Taishan Mountain Station when the two sites see rains at the same time and it begins to rain in less than two hours, are positive. This is probably due to the different contributions of scavenging the below clouds of atmospheric pollutants like aerosols， SO2 and NOx to the chemical composition of the rainwater at the two stations.
2013, 39(3):355-361.
DOI: 10.7519/j.issn.1000-0526.2013.03.010
Abstract:
This study uses daily observation data in Jinan and Qingdao, Shandong Province during 1999-2011, to reveal associations between the precipitation types and temperatures to determine potential changes of precipitation in cold seasons. The results show that precipitation types are firstly relative with synoptic systems. Jianghuai cyclone and backflow situation weather systems often produce different precipitation types. Cold fronts, Huanghe cyclone and low eddy shear line often lead to snowfalls directly. Pure snowfall occurs in low temperatures and has obvious thresholds below 850 hPa. Temperatures at 850 hPa and 925 hPa are weak clues for identifying rain, snow and sleet in mixed precipitations while temperature below 1000 hPa is very critical. It is better for precipitation type discrimination by combining the temperature in different levels under 925 hPa with surface temperature than the single level temperature. By comparison, ice pellets are highly dependent on the higher temperature in 700 hPa. The height of 0℃ level is good clue for predicting precipitation types. The 0℃ level is higher or near 925 hPa when it rains, but when it descends near 1000 hPa rain converts to snow. There is no pure sleet or ice pellets because they always appear in mixed precepitation types.
This study uses daily observation data in Jinan and Qingdao, Shandong Province during 1999-2011, to reveal associations between the precipitation types and temperatures to determine potential changes of precipitation in cold seasons. The results show that precipitation types are firstly relative with synoptic systems. Jianghuai cyclone and backflow situation weather systems often produce different precipitation types. Cold fronts, Huanghe cyclone and low eddy shear line often lead to snowfalls directly. Pure snowfall occurs in low temperatures and has obvious thresholds below 850 hPa. Temperatures at 850 hPa and 925 hPa are weak clues for identifying rain, snow and sleet in mixed precipitations while temperature below 1000 hPa is very critical. It is better for precipitation type discrimination by combining the temperature in different levels under 925 hPa with surface temperature than the single level temperature. By comparison, ice pellets are highly dependent on the higher temperature in 700 hPa. The height of 0℃ level is good clue for predicting precipitation types. The 0℃ level is higher or near 925 hPa when it rains, but when it descends near 1000 hPa rain converts to snow. There is no pure sleet or ice pellets because they always appear in mixed precepitation types.
2013, 39(3):362-369.
DOI: 10.7519/j.issn.1000-0526.2013.03.011
Abstract:
An intercomparison of two kinds of wire icing observed data in China is performed to analyze the differences in diameter, thickness, weight, standard thickness of the wire ice in this study. The difference in the two icing observations under different weather phenomena and meteorological conditions is also discussed. The results show that the two kinds of wire ice (north south and east west) diameter, thickness and standard thickness data, which were collected by majority of the stations in the country from January to May 2011, have no significant difference. However, the difference in weight between the two datasets is obvious, especially in the areas to the south of the Yangtze River. Further analysis shows that the differences in ice thickness and diameter between the two datasets under the rime and mixed icing conditions are more significant, while the difference in ice weight reaches the maximum when the wind force is from Grade 0 to 3, the temperature ranges between -5℃ and 0℃, and the glaze occurs.
An intercomparison of two kinds of wire icing observed data in China is performed to analyze the differences in diameter, thickness, weight, standard thickness of the wire ice in this study. The difference in the two icing observations under different weather phenomena and meteorological conditions is also discussed. The results show that the two kinds of wire ice (north south and east west) diameter, thickness and standard thickness data, which were collected by majority of the stations in the country from January to May 2011, have no significant difference. However, the difference in weight between the two datasets is obvious, especially in the areas to the south of the Yangtze River. Further analysis shows that the differences in ice thickness and diameter between the two datasets under the rime and mixed icing conditions are more significant, while the difference in ice weight reaches the maximum when the wind force is from Grade 0 to 3, the temperature ranges between -5℃ and 0℃, and the glaze occurs.
2013, 39(3):370-376.
DOI: 10.7519/j.issn.1000-0526.2013.03.012
Abstract:
This paper compares the wind data measured and obtained by two TWP3 and one LAP3000 wind profilers located in Jiading and Songjiang areas within Shanghai profiler network in the winter period from 28 October to 28 November 2010 and in the summer time from 1 to 3 July 31 2011 to those measured by Baoshan GFE(L) 1 sounding radar system during the corresponding periods. Furthermore, the wind data probed by two different types of profilers in Jiading area are also compared with each other. The amount of wind data samples obtained under the stable weather conditions for the comparisons between the two types of wind profilers are 71981 pairs, and the total samples comparison of two TWP3 and one LAP3000 profilers with the 〖JP2〗Baoshan GFE(L) 1 radar data are 6733, 7350 and 7013 pairs, respectively. The results indicate that the average wind speed standard deviations between the TWP3 and LAP3000 are 3.63 and 4.12 m·s-1 for the two correspording sampling periods above, respectively. The statistic average standard deviations of wind speed in the summer sampling period for Jiading TWP3, Songjiang TWP3, Jiading LAP3000 profilers compared separately to Baoshan GFE(L) 1 sounding radar data are 3.34, 3.37 and 4.03 m·s-1, sequentially. However, in the winter sampling time, those averaged values of the above said comparing events are 3.22, 3.22 and 3.42 m·s-1. According to the statistic curves, the standard deviation for the two TWP3 wind profilers is 2 to 4 m·s-1 when they are compared to Baoshan GFE(L) 1 sounding radar data. Obviously, the two TWP3 profilers have a better system performance than the LAP3000 profiler. A new concept of “efficient sounding height” related to wind profiler radars also is presented for the first time in the paper.
This paper compares the wind data measured and obtained by two TWP3 and one LAP3000 wind profilers located in Jiading and Songjiang areas within Shanghai profiler network in the winter period from 28 October to 28 November 2010 and in the summer time from 1 to 3 July 31 2011 to those measured by Baoshan GFE(L) 1 sounding radar system during the corresponding periods. Furthermore, the wind data probed by two different types of profilers in Jiading area are also compared with each other. The amount of wind data samples obtained under the stable weather conditions for the comparisons between the two types of wind profilers are 71981 pairs, and the total samples comparison of two TWP3 and one LAP3000 profilers with the 〖JP2〗Baoshan GFE(L) 1 radar data are 6733, 7350 and 7013 pairs, respectively. The results indicate that the average wind speed standard deviations between the TWP3 and LAP3000 are 3.63 and 4.12 m·s-1 for the two correspording sampling periods above, respectively. The statistic average standard deviations of wind speed in the summer sampling period for Jiading TWP3, Songjiang TWP3, Jiading LAP3000 profilers compared separately to Baoshan GFE(L) 1 sounding radar data are 3.34, 3.37 and 4.03 m·s-1, sequentially. However, in the winter sampling time, those averaged values of the above said comparing events are 3.22, 3.22 and 3.42 m·s-1. According to the statistic curves, the standard deviation for the two TWP3 wind profilers is 2 to 4 m·s-1 when they are compared to Baoshan GFE(L) 1 sounding radar data. Obviously, the two TWP3 profilers have a better system performance than the LAP3000 profiler. A new concept of “efficient sounding height” related to wind profiler radars also is presented for the first time in the paper.
2013, 39(3):377-382.
DOI: 10.7519/j.issn.1000-0526.2013.03.013
Abstract:
A neural network scheme to do a multivariate analysis for forecasting the occurrence of thunderstorm in Taiyuan is presented by using sounding data and lightning location system data. Well correlated sounding factors are selected as the predictors， then all the input factors are normalized， and output data are adopted to two stage category so that the BP network with double hidden layers has been established and the independent samples can be tested in it. The results indicate that, in the same condition， compared with single hidden layer BP network, the double hidden layer BP network shows its advantage on solving classification problem. Compared with multivariate statistics regression algorithm, the neural network algorithm obtains higher thunderstorm forecasting TS score and more reliable results, showing good nonlinear processing ability in the thunderstorm forecasts based on sounding data. And then the rules of thunderstorm forecast results are analyzed and discussed, showing that sounding factors have a close connection with the occurrence of thunderstorm.
A neural network scheme to do a multivariate analysis for forecasting the occurrence of thunderstorm in Taiyuan is presented by using sounding data and lightning location system data. Well correlated sounding factors are selected as the predictors， then all the input factors are normalized， and output data are adopted to two stage category so that the BP network with double hidden layers has been established and the independent samples can be tested in it. The results indicate that, in the same condition， compared with single hidden layer BP network, the double hidden layer BP network shows its advantage on solving classification problem. Compared with multivariate statistics regression algorithm, the neural network algorithm obtains higher thunderstorm forecasting TS score and more reliable results, showing good nonlinear processing ability in the thunderstorm forecasts based on sounding data. And then the rules of thunderstorm forecast results are analyzed and discussed, showing that sounding factors have a close connection with the occurrence of thunderstorm.
2013, 39(3):383-388.
DOI: 10.7519/j.issn.1000-0526.2013.03.014
Abstract:
This paper described the design and development of the weather modification operational platform based on MICAPS V 3.2 core framework. First of all, we recommend the major function, features of modular design and system interface of MICAPS V 3.2. Then presented the workflows, contents and major products of weather modification, furthermore, pointed out the interactive method of different types of data in this system. Finally, design menu and interface layout were given to accomplish the development of the system aiming at the characteristics of weather modification, and displayed the examples of weather modification work main products which have been completed. The successful development of this weather modification operational platform broadens the application field of MICAPS V 3.2 and it is worth promoting nationwide.
This paper described the design and development of the weather modification operational platform based on MICAPS V 3.2 core framework. First of all, we recommend the major function, features of modular design and system interface of MICAPS V 3.2. Then presented the workflows, contents and major products of weather modification, furthermore, pointed out the interactive method of different types of data in this system. Finally, design menu and interface layout were given to accomplish the development of the system aiming at the characteristics of weather modification, and displayed the examples of weather modification work main products which have been completed. The successful development of this weather modification operational platform broadens the application field of MICAPS V 3.2 and it is worth promoting nationwide.
2013, 39(3):389-393.
DOI: 10.7519/j.issn.1000-0526.2013.03.015
Abstract:
The precise using of the weather radar data and the using effect of the weather radar mosaic observation are based on the precise positioning of the radar antenna feed coordinates. At present, antenna feed coordinates of the new generation weather radar are measured basically by single point positioning method of the American GPS (Global Position System) which is one kind of the GNSS (Global Navigation Satellite System), and the measurement error is generally more than 30 m. In order to improve the positioning accuracy, a new method to measure the weather radar antenna feed coordinates is proposed in this article. The GPS precise positioning technology and total station measuring technology are combined in the method, which can improve the accuracy of measuring the altitude of the weather radar antenna feed, making the error less than 10 m. The new generation weather radar feed coordinates of the Beijing Meteorological Bureau are measured with this method, and the measurement accuracy meets the design requirements.
The precise using of the weather radar data and the using effect of the weather radar mosaic observation are based on the precise positioning of the radar antenna feed coordinates. At present, antenna feed coordinates of the new generation weather radar are measured basically by single point positioning method of the American GPS (Global Position System) which is one kind of the GNSS (Global Navigation Satellite System), and the measurement error is generally more than 30 m. In order to improve the positioning accuracy, a new method to measure the weather radar antenna feed coordinates is proposed in this article. The GPS precise positioning technology and total station measuring technology are combined in the method, which can improve the accuracy of measuring the altitude of the weather radar antenna feed, making the error less than 10 m. The new generation weather radar feed coordinates of the Beijing Meteorological Bureau are measured with this method, and the measurement accuracy meets the design requirements.
2013, 39(3):394-400.
DOI: 10.7519/j.issn.1000-0526.2013.03.016
Abstract:
The following are the main characteristics of the general atmospheric circulation in December 2012. There is one polar vortex center in the Northern Hemisphere, and the circulation presents meridional patterns in middle high latitudes, which is in favor of leading cold air southward. The south branch trough behaves actively and the subtropical high is stronger than normal years’. The monthly mean precipitation over China is 17.6 mm, 67.6% more than the corresponding month of normal years (10.5 mm). The monthly mean temperature is -4.4℃, 1.2℃ lower than the normal temperature at the same period, of which the mean temperature of Beijing breaks the lowest record in history (-3.2℃). There are five obvious cold air processes and four rainfall processes in the month. Many regions experience extreme cold and extreme day temperature dropping events, and part of northern China suffers snow disasters. Besides, large scale persisting rainy weather appears Jiangnan, South China and other places in southern China.
The following are the main characteristics of the general atmospheric circulation in December 2012. There is one polar vortex center in the Northern Hemisphere, and the circulation presents meridional patterns in middle high latitudes, which is in favor of leading cold air southward. The south branch trough behaves actively and the subtropical high is stronger than normal years’. The monthly mean precipitation over China is 17.6 mm, 67.6% more than the corresponding month of normal years (10.5 mm). The monthly mean temperature is -4.4℃, 1.2℃ lower than the normal temperature at the same period, of which the mean temperature of Beijing breaks the lowest record in history (-3.2℃). There are five obvious cold air processes and four rainfall processes in the month. Many regions experience extreme cold and extreme day temperature dropping events, and part of northern China suffers snow disasters. Besides, large scale persisting rainy weather appears Jiangnan, South China and other places in southern China.
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ISSN:1000-0526 CN:11-2282/P