ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 47,Issue 5,2021 Table of Contents
2021, 47(5):517-528.
DOI: 10.7519/j.issn.1000-0526.2021.05.001
Abstract:
Based on the climate impact assessment documents, significant weather reports, tornado disaster records from Jiangsu civil affairs department and other relevant data from 2006 to 2018, the spato-temporal distribution, strength distribution, weather background and storm morphology characteristics of the Jiangsu tornadoes are analyzed according to the “Enhanced Fujita Scale”. The main results show that there were 41 tornadoes recorded in 27 tornadic days during the 13 years (2006-2018) with an average annual tornado of 3.2 times, of which the tornado events at EF2 level occurred the most, accounting for 39%, while the EF4 tornado was only recorded once, referring to the 23 June (6·23) Funing severe tornado. Since the 21st Century, there has been no record of extreme tornado events of EF5 level in Jiangsu Province, while the weak tornadoes of EF0 and EF1 are likely to be ignored due to the weak disaster, so their statistical results may be significantly underestimated. Tornadoes mainly occur in the eastern coastal area, the central coastal area and the western area of the north of the Huaihe River. Compared with the past, the high-risk center of tornado in central Jiangsu has a trend of moving southward, while the high-risk center in the eastern coastal area shows a feature of northward movement. Yancheng, Xuzhou and Yangzhou are the high frequency cities of tornado, but no tornado has happened in Suqian, Lianyungang, Changzhou and Zhenjiang in recent years. Most tornadoes occur in spring and summer, 90% of which are seen in July and August. The onset of tornadoes is from 10:00 BT to 20:00 BT, and 78% of tornado genesises in the diurnal variation are between 15:00 BT and 20:00 BT. About 50% of the tornadoes occur during the Meiyu period, and 27% of them are typhoon tornadoes. Yancheng is the highest incidence area of tornadoes in Meiyu period, and the Yangzhou-Taizhou Region has high incidence of tornadoes in mid-summer. There is no obvious high-risk area of typhoon tornadoes in Jiangsu. More than 50% of tornadoes in Jiangsu are generated in supercell mesocyclone embedded in cluster convective morphology, and about 30% of tornadoes are produced in the quasi-linear convective system convective morphology. Contrast to high frequency of tornadoes produced by the discrete cells in the United States, the possibility of tornadoes generated from discrete cells in East China (mainly in Jiangsu Province) is the lowest, and only two tornadoes (less than 5%) were generated in discrete cells in the past 13 years.
Based on the climate impact assessment documents, significant weather reports, tornado disaster records from Jiangsu civil affairs department and other relevant data from 2006 to 2018, the spato-temporal distribution, strength distribution, weather background and storm morphology characteristics of the Jiangsu tornadoes are analyzed according to the “Enhanced Fujita Scale”. The main results show that there were 41 tornadoes recorded in 27 tornadic days during the 13 years (2006-2018) with an average annual tornado of 3.2 times, of which the tornado events at EF2 level occurred the most, accounting for 39%, while the EF4 tornado was only recorded once, referring to the 23 June (6·23) Funing severe tornado. Since the 21st Century, there has been no record of extreme tornado events of EF5 level in Jiangsu Province, while the weak tornadoes of EF0 and EF1 are likely to be ignored due to the weak disaster, so their statistical results may be significantly underestimated. Tornadoes mainly occur in the eastern coastal area, the central coastal area and the western area of the north of the Huaihe River. Compared with the past, the high-risk center of tornado in central Jiangsu has a trend of moving southward, while the high-risk center in the eastern coastal area shows a feature of northward movement. Yancheng, Xuzhou and Yangzhou are the high frequency cities of tornado, but no tornado has happened in Suqian, Lianyungang, Changzhou and Zhenjiang in recent years. Most tornadoes occur in spring and summer, 90% of which are seen in July and August. The onset of tornadoes is from 10:00 BT to 20:00 BT, and 78% of tornado genesises in the diurnal variation are between 15:00 BT and 20:00 BT. About 50% of the tornadoes occur during the Meiyu period, and 27% of them are typhoon tornadoes. Yancheng is the highest incidence area of tornadoes in Meiyu period, and the Yangzhou-Taizhou Region has high incidence of tornadoes in mid-summer. There is no obvious high-risk area of typhoon tornadoes in Jiangsu. More than 50% of tornadoes in Jiangsu are generated in supercell mesocyclone embedded in cluster convective morphology, and about 30% of tornadoes are produced in the quasi-linear convective system convective morphology. Contrast to high frequency of tornadoes produced by the discrete cells in the United States, the possibility of tornadoes generated from discrete cells in East China (mainly in Jiangsu Province) is the lowest, and only two tornadoes (less than 5%) were generated in discrete cells in the past 13 years.
2021, 47(5):529-538.
DOI: 10.7519/j.issn.1000-0526.2021.05.002
Abstract:
Based on the grided precipitation analysis data from April to August in 2018, and precipitation forecast data of four regional high-resolution models, percentile frequency matching is applied to calibrate the hourly precipitation frequency of each model. Based on the verification of key areas, the technology of dynamic weighted multi-model integration shows its application in probabilistic forecasting of short-time severe rainfall. The results demonstrate that percentile frequency matching displays positive effects in heavy rain precipitation, which can reduce the systematic forecast bias of the model and improve the accuracy of precipitation forecasting. In the nowcasting leadtime, the precipitation information of the upstream key areas is suggestive of the precipitation forecast in the downstream area. The dynamic weighted integration provides more skillful and stable performance in probabilistic forecasting than the equally weighted integration. The case also illustrates that the new technology performs well on the short-time severe precipitation forecasting and early warning within the nowcasting lead time.
Based on the grided precipitation analysis data from April to August in 2018, and precipitation forecast data of four regional high-resolution models, percentile frequency matching is applied to calibrate the hourly precipitation frequency of each model. Based on the verification of key areas, the technology of dynamic weighted multi-model integration shows its application in probabilistic forecasting of short-time severe rainfall. The results demonstrate that percentile frequency matching displays positive effects in heavy rain precipitation, which can reduce the systematic forecast bias of the model and improve the accuracy of precipitation forecasting. In the nowcasting leadtime, the precipitation information of the upstream key areas is suggestive of the precipitation forecast in the downstream area. The dynamic weighted integration provides more skillful and stable performance in probabilistic forecasting than the equally weighted integration. The case also illustrates that the new technology performs well on the short-time severe precipitation forecasting and early warning within the nowcasting lead time.
LUO Cong
,
ZHANG Hualong
,
ZENG Qin
,
HU Sheng
,
WU Naigeng
,
CHEN Binghong
,
SHI Yang
,
HUANG Xiaoying
,
TANG Siyu
2021, 47(5):539-549.
DOI: 10.7519/j.issn.1000-0526.2021.05.003
Abstract:
This study evaluates the performance of the ECMWF global ensemble prediction system, the short-term-forecast mesoscale model, and the rapid-updated nowcasting model for South China based on GRAPES, by analyzing the spatio-temporal characteristics of precipitation forecast under the local climate background of Guangdong Province. Based on the evaluation results, a hybrid method for multi-model post-processing is developed to produce high-resolution gridded quantitative precipitation forecast (GQPF). The results are as follows: Multi-scale model integration is a promising technique for objective model post-processing. The frequency-matching and optimal-percentile methods show the advantages in ensemble forecast interpretation at synoptic scale, while the spatial correction and clear-rainy elimination based on localized stratified verification can help further optimize the space distribution and intensity for specific weather scenarios. Temporal downscaling based on the characteristics of the mesoscale model in diurnal variation is beneficial to improve the hourly precipitation forecasting. Considering the interdependence and complementary advantages of different methods, the GQPF method for Guangdong is established with a sequential flow of “frequency-matching, optimal-percentile, spatial correction, clear-rainy elimination, time-downscaling”, which improves the accuracy of precipitation objective forecast.
This study evaluates the performance of the ECMWF global ensemble prediction system, the short-term-forecast mesoscale model, and the rapid-updated nowcasting model for South China based on GRAPES, by analyzing the spatio-temporal characteristics of precipitation forecast under the local climate background of Guangdong Province. Based on the evaluation results, a hybrid method for multi-model post-processing is developed to produce high-resolution gridded quantitative precipitation forecast (GQPF). The results are as follows: Multi-scale model integration is a promising technique for objective model post-processing. The frequency-matching and optimal-percentile methods show the advantages in ensemble forecast interpretation at synoptic scale, while the spatial correction and clear-rainy elimination based on localized stratified verification can help further optimize the space distribution and intensity for specific weather scenarios. Temporal downscaling based on the characteristics of the mesoscale model in diurnal variation is beneficial to improve the hourly precipitation forecasting. Considering the interdependence and complementary advantages of different methods, the GQPF method for Guangdong is established with a sequential flow of “frequency-matching, optimal-percentile, spatial correction, clear-rainy elimination, time-downscaling”, which improves the accuracy of precipitation objective forecast.
PAN Liujie
,
XUE Chunfang
,
ZHANG Hongfang
,
GAO Xingxing
,
LIANG Mian
,
WANG Jianpeng
,
LIU Jiahuimin
2021, 47(5):550-560.
DOI: 10.7519/j.issn.1000-0526.2021.05.004
Abstract:
Improving the accuracy of grid precipitation forecasting is an important direction for refined weather forecasting. This paper uses the precipitation grid reanalysis data as a reference to objectively evaluate the precipitation forecast of different numerical models and the forecast performance of the National Meteorological Centre’s grid precipitation guidance products. Based on the verification results, a precipitation forecast interpretation method is proposed which fuses various precipitation forecast products. The main conclusions are as follows. Under the same precipitation threshold, the forecast performance of different precipitation products is significantly different, and there are cases in which the precipitation products with good forecast performance are missed, while other precipitation products are obtained. For the deterministic single model, the greater the forecast precipitation exceeds the verified threshold, the lower the possibility of an false alarm is. Verify the 3 h precipitation forecast for the three products with a valid time of 72 hours， for sunny or rainy day forecast, the number of omission of precipitation is significantly lower than the number of false alarms, which can be used to eliminate weak precipitation. On the basis of the verification, we select a model forecast that performed well in the previous period as the background field, and use a high threshold to fuse heavy precipitation, and use a low threshold to eliminate false alarm of weak precipitation. The results show that the forecast performance of fused precipitation can be improved.
Improving the accuracy of grid precipitation forecasting is an important direction for refined weather forecasting. This paper uses the precipitation grid reanalysis data as a reference to objectively evaluate the precipitation forecast of different numerical models and the forecast performance of the National Meteorological Centre’s grid precipitation guidance products. Based on the verification results, a precipitation forecast interpretation method is proposed which fuses various precipitation forecast products. The main conclusions are as follows. Under the same precipitation threshold, the forecast performance of different precipitation products is significantly different, and there are cases in which the precipitation products with good forecast performance are missed, while other precipitation products are obtained. For the deterministic single model, the greater the forecast precipitation exceeds the verified threshold, the lower the possibility of an false alarm is. Verify the 3 h precipitation forecast for the three products with a valid time of 72 hours， for sunny or rainy day forecast, the number of omission of precipitation is significantly lower than the number of false alarms, which can be used to eliminate weak precipitation. On the basis of the verification, we select a model forecast that performed well in the previous period as the background field, and use a high threshold to fuse heavy precipitation, and use a low threshold to eliminate false alarm of weak precipitation. The results show that the forecast performance of fused precipitation can be improved.
2021, 47(5):561-572.
DOI: 10.7519/j.issn.1000-0526.2021.05.005
Abstract:
In order to improve the quality and application level of X-band dual polarization radar data, based on the dual polarization radar quality control (dpQC) scheme from National Multi-Radar and Multi-Sensor (MRMS) Quantitative Precipitation Estimation (QPE) System, a new quality control scheme (dpXQC) is designed for X-band dual polarization radar data. In this scheme, threshold discrimination of differential reflectivity is integrated and some algorithm parameters of the original scheme are adjusted locally. The main principles of the dpXQC scheme include the threshold distinguishing precipitation echo from non-precipitation echo is adjusted to 0.9 when correlation coefficient (CC) of radar echo is used and those less than 0.9 are judged as non-precipitation echoes based on the statistical data； hail and the non-uniform beam filling region are identified by calculating the radar echo top and the location of the powerful echo area; melting layer is distinguished through the feature of CC around 0℃ height of sounding data; radar echo whose absolute value of differential reflectivity is larger than 5 dB is judged as non-precipitation echoes. The scheme also includes the algorithm of spike filter, continuous check and speckle filter. The dpXQC quality control scheme is used to do the test on the 5 Beijing X-band dual polarization radars, and the identification effect of non-precipitation echo is evaluated. The results show that most non-precipitation echoes can be filtered by the CC threshold. The residual non-precipitation echoes with CC larger than 0.9 including the stripe clutter, 〖JP2〗scattered clutter and the small-area clutter, can be removed by spike filter, continuous check and differential reflectivity threshold discrimination. The precipitation echo with CC less than 0.9 in the hail, the non-uniform beam filling and the melting layer region can be protected from CC filter by dpXQC〖JP〗 scheme; the statistical result reveals that the hit rate of recognition of non-precipitation echoes of the dpXQC scheme is 91.8% while the false alarm rate is 20.8%， so it is better than dpQC scheme. There are two main reasons for the high false alarm rate: one is that some non-uniform beam filling regions far away from the radar are not identified by algorithm because of severe attenuation of X-band radar, and the other is that the location and thickness of melting layer are fixed in every azimuth in algorithm, which does not accord with the actual observation. These cause some precipitation echoes with CC less than 0.9 to be identified as non-precipitation echoes in the unrecognized region. Overall, the non-precipitation echoes can be filtered while most precipitation echoes could be returned so that some professional work about the quantitative application of X-band dual polarization radar can be ensured by the dpXQC quality control algorithm.
In order to improve the quality and application level of X-band dual polarization radar data, based on the dual polarization radar quality control (dpQC) scheme from National Multi-Radar and Multi-Sensor (MRMS) Quantitative Precipitation Estimation (QPE) System, a new quality control scheme (dpXQC) is designed for X-band dual polarization radar data. In this scheme, threshold discrimination of differential reflectivity is integrated and some algorithm parameters of the original scheme are adjusted locally. The main principles of the dpXQC scheme include the threshold distinguishing precipitation echo from non-precipitation echo is adjusted to 0.9 when correlation coefficient (CC) of radar echo is used and those less than 0.9 are judged as non-precipitation echoes based on the statistical data； hail and the non-uniform beam filling region are identified by calculating the radar echo top and the location of the powerful echo area; melting layer is distinguished through the feature of CC around 0℃ height of sounding data; radar echo whose absolute value of differential reflectivity is larger than 5 dB is judged as non-precipitation echoes. The scheme also includes the algorithm of spike filter, continuous check and speckle filter. The dpXQC quality control scheme is used to do the test on the 5 Beijing X-band dual polarization radars, and the identification effect of non-precipitation echo is evaluated. The results show that most non-precipitation echoes can be filtered by the CC threshold. The residual non-precipitation echoes with CC larger than 0.9 including the stripe clutter, 〖JP2〗scattered clutter and the small-area clutter, can be removed by spike filter, continuous check and differential reflectivity threshold discrimination. The precipitation echo with CC less than 0.9 in the hail, the non-uniform beam filling and the melting layer region can be protected from CC filter by dpXQC〖JP〗 scheme; the statistical result reveals that the hit rate of recognition of non-precipitation echoes of the dpXQC scheme is 91.8% while the false alarm rate is 20.8%， so it is better than dpQC scheme. There are two main reasons for the high false alarm rate: one is that some non-uniform beam filling regions far away from the radar are not identified by algorithm because of severe attenuation of X-band radar, and the other is that the location and thickness of melting layer are fixed in every azimuth in algorithm, which does not accord with the actual observation. These cause some precipitation echoes with CC less than 0.9 to be identified as non-precipitation echoes in the unrecognized region. Overall, the non-precipitation echoes can be filtered while most precipitation echoes could be returned so that some professional work about the quantitative application of X-band dual polarization radar can be ensured by the dpXQC quality control algorithm.
2021, 47(5):573-585.
DOI: 10.7519/j.issn.1000-0526.2021.05.006
Abstract:
This paper describes a quality control (QC) algorithm for hourly horizontal wind products of Chinese wind profilers. The QC algorithm is based on the complex QC system of NCEP， is designed for the requirements of CMA global atmospheric/land surface reanalysis product (CRA). The effectiveness of the QC algorithm is checked by comparing the correlation coefficient, average bias and root mean square error of wind profiler data and radiosonde data before and after QC procedures. The deviations from ERAInterim reanalysis data are calculated for both radiosonde and wind profiler data. Through comparing wind profiler deviations with radiosonde deviations, the overall quality conditions of Chinese wind profiler data before and after QC procedures are analyzed. The results show that the wind profiler data and the radiosonde data show better consistency after the QC by this QC algorithm, and the correlation coefficients of different radar types and different detection altitudes increase from the range 0.17-0.82 to the range 0.79-0.98. For different radar types and different vertical layers, all the biases of horizontal profiler wind data from ERAInterim exhibit a dramatic decrease after the QC procedures and are nearly equivalent to that of radiosonde data, except that the data from boundary layer wind profiler radar still has a deviation of uwind component about 5 m·s-1 above 300 hPa. The results prove that the QC algorithm has the ability to identify the highlevel gross error data, and can make effective use of the data above the maximum detection height.
This paper describes a quality control (QC) algorithm for hourly horizontal wind products of Chinese wind profilers. The QC algorithm is based on the complex QC system of NCEP， is designed for the requirements of CMA global atmospheric/land surface reanalysis product (CRA). The effectiveness of the QC algorithm is checked by comparing the correlation coefficient, average bias and root mean square error of wind profiler data and radiosonde data before and after QC procedures. The deviations from ERAInterim reanalysis data are calculated for both radiosonde and wind profiler data. Through comparing wind profiler deviations with radiosonde deviations, the overall quality conditions of Chinese wind profiler data before and after QC procedures are analyzed. The results show that the wind profiler data and the radiosonde data show better consistency after the QC by this QC algorithm, and the correlation coefficients of different radar types and different detection altitudes increase from the range 0.17-0.82 to the range 0.79-0.98. For different radar types and different vertical layers, all the biases of horizontal profiler wind data from ERAInterim exhibit a dramatic decrease after the QC procedures and are nearly equivalent to that of radiosonde data, except that the data from boundary layer wind profiler radar still has a deviation of uwind component about 5 m·s-1 above 300 hPa. The results prove that the QC algorithm has the ability to identify the highlevel gross error data, and can make effective use of the data above the maximum detection height.
2021, 47(5):586-600.
DOI: 10.7519/j.issn.1000-0526.2021.05.007
Abstract:
Based on the precipitation data of Sichuan meteorological stations and the hindcast data of eight models in the World Meteorological Organization (WMO) sub-seasonal to seasonal (S2S) forecasting project from 1995 to 2010, forecasting skills of the models for extreme precipitation events during the flood season in Sichuan Province are evaluated and analyzed with five methods. These methods are probability of detection (POD), false alarm ratio (FAR), Heidke’s skill score (HSS), mean error and absolute error. As the results show, the prediction skills of S2S models for extreme precipitation in Sichuan Province are overall low, showing a feature of “low hit rate, high false alarm rate, and the forecast value far less than the observation with large deviation”. The forecast capability of all models improves with the lead-time shortening and their prediction performances on the synoptic scale are better than that on the sub-seasonal scale. Spatially, the qualitative prediction skill of the models is the highest in the south of western Sichuan Plateau, and the lowest in the east of the basin or Panxi Region. Meanwhile, the prediction absolute error present the distribution of “the largest in the basin, the secondly largest in the Panxi Region, the smallest in the western Sichuan Plateau”, and the maximum absolute error appears along the mountains in the western part of the basin. The prediction skills are different in each month during the flood season. The qualitative prediction skills are higher in the main flood season, especially in midsummer than in other months. However the quantitative prediction skill is the lowest in midsummer. Under consideration of quantitate and qualitative forecast ability, among the eight models, models from the United Kingdom Met Office (UKMO) and the Institute of Atmospheric Sciences and Climate of the National Research Council (CNR-ISAC) perform better in forecasting the extreme precipitation in Sichuan Province on the synoptic and the sub-seasonal scale, respectively. The best prediction models for the basin and Panxi Region are consistent with that of the whole province. However, for western Sichuan Plateau, model from the Korea Meteorological Administration (KMA) is optimal on the synoptic scale while models from the Australian Bureau of Meteorology (BoM) and CNR-ISAC are the best forecasting models on the sub-seasonal scale.
Based on the precipitation data of Sichuan meteorological stations and the hindcast data of eight models in the World Meteorological Organization (WMO) sub-seasonal to seasonal (S2S) forecasting project from 1995 to 2010, forecasting skills of the models for extreme precipitation events during the flood season in Sichuan Province are evaluated and analyzed with five methods. These methods are probability of detection (POD), false alarm ratio (FAR), Heidke’s skill score (HSS), mean error and absolute error. As the results show, the prediction skills of S2S models for extreme precipitation in Sichuan Province are overall low, showing a feature of “low hit rate, high false alarm rate, and the forecast value far less than the observation with large deviation”. The forecast capability of all models improves with the lead-time shortening and their prediction performances on the synoptic scale are better than that on the sub-seasonal scale. Spatially, the qualitative prediction skill of the models is the highest in the south of western Sichuan Plateau, and the lowest in the east of the basin or Panxi Region. Meanwhile, the prediction absolute error present the distribution of “the largest in the basin, the secondly largest in the Panxi Region, the smallest in the western Sichuan Plateau”, and the maximum absolute error appears along the mountains in the western part of the basin. The prediction skills are different in each month during the flood season. The qualitative prediction skills are higher in the main flood season, especially in midsummer than in other months. However the quantitative prediction skill is the lowest in midsummer. Under consideration of quantitate and qualitative forecast ability, among the eight models, models from the United Kingdom Met Office (UKMO) and the Institute of Atmospheric Sciences and Climate of the National Research Council (CNR-ISAC) perform better in forecasting the extreme precipitation in Sichuan Province on the synoptic and the sub-seasonal scale, respectively. The best prediction models for the basin and Panxi Region are consistent with that of the whole province. However, for western Sichuan Plateau, model from the Korea Meteorological Administration (KMA) is optimal on the synoptic scale while models from the Australian Bureau of Meteorology (BoM) and CNR-ISAC are the best forecasting models on the sub-seasonal scale.
2021, 47(5):601-608.
DOI: 10.7519/j.issn.1000-0526.2021.05.008
Abstract:
Typhoon objective strength determination is an important supporting technique to improve the modernization level of typhoon forecasting operation. Deep learning can implicitly extract the deep complex features in the images through the learning of a large number of samples, and it has been increasingly applied to the meteorological field nowadays. In this paper, a ResNet deep learning model is used to study the satellite cloud images as samples by pre-training and transfer-learning. After studying the 2005-2018 typhoon images of the Northwest Pacific and South China Sea, we consturct an automatic and objective typhoon intensity estimation technique. By using the deep learning technique to analyze the typhoon satellite images in 2019, we find that this technique can be used to estimate the objective intensity of typhoon in different intensity and different developing stages, and the mean absolute error (MAE) and root mean square error (RMSE) of independent samples in 2019 are 4.3 m·s-1 and 5.5 m·s-1 respectively. The accuracy is better than that of the traditional objective intensity estimation method, so it has certain application values.
Typhoon objective strength determination is an important supporting technique to improve the modernization level of typhoon forecasting operation. Deep learning can implicitly extract the deep complex features in the images through the learning of a large number of samples, and it has been increasingly applied to the meteorological field nowadays. In this paper, a ResNet deep learning model is used to study the satellite cloud images as samples by pre-training and transfer-learning. After studying the 2005-2018 typhoon images of the Northwest Pacific and South China Sea, we consturct an automatic and objective typhoon intensity estimation technique. By using the deep learning technique to analyze the typhoon satellite images in 2019, we find that this technique can be used to estimate the objective intensity of typhoon in different intensity and different developing stages, and the mean absolute error (MAE) and root mean square error (RMSE) of independent samples in 2019 are 4.3 m·s-1 and 5.5 m·s-1 respectively. The accuracy is better than that of the traditional objective intensity estimation method, so it has certain application values.
2021, 47(5):609-618.
DOI: 10.7519/j.issn.1000-0526.2021.05.009
Abstract:
Based on the observation data of 360° occlusion elevation angle and cloud amount around the observation site, the influence of occlusion on the consistency of sunshine observation data is analyzed. From the relative relationship between the solar elevation angle and the occlusion elevation angle, and the correction of the cloud to the occlusion rate, the correction method of the occlusion sunshine hours by station under cloudy weather conditions is established. Take Wushan Station in Chongqing as an example. The calculation and correction of the sunshine hours during the period of severe occlusion from 2004 to 2013 is performed. Through the vertical comparison between the occlusion period and the two unoccluded periods before and after the occlusion and the same-period horizontal comparison of Jianshi Station in Hubei Province, which is similar to the terrain and climate conditions, the correction effect is tested. The results show that the obstructions around the observation site of Wushan Station affect the observation of sunshine hours， which makes the observation data inconsistent before and after the occlusion. During the period of 2004-2013, the average number of occluded sunshine hours was 218.0 h·a-1, and the occlusion ratio reached 13.1%. Due to the hedging effect of weather conditions, the influence of occlusion in summer half year may be higher than that in winter half year. From the indirect comparison between the vertical and horizontal aspects, the correction method established in this paper not only calculates the influence of the occluder itself, but also takes into account the correction of the occlusion ration under cloudy conditions. The correction results are basically reasonable, and can be relatively accurately restore the occluded sunshine hours.
Based on the observation data of 360° occlusion elevation angle and cloud amount around the observation site, the influence of occlusion on the consistency of sunshine observation data is analyzed. From the relative relationship between the solar elevation angle and the occlusion elevation angle, and the correction of the cloud to the occlusion rate, the correction method of the occlusion sunshine hours by station under cloudy weather conditions is established. Take Wushan Station in Chongqing as an example. The calculation and correction of the sunshine hours during the period of severe occlusion from 2004 to 2013 is performed. Through the vertical comparison between the occlusion period and the two unoccluded periods before and after the occlusion and the same-period horizontal comparison of Jianshi Station in Hubei Province, which is similar to the terrain and climate conditions, the correction effect is tested. The results show that the obstructions around the observation site of Wushan Station affect the observation of sunshine hours， which makes the observation data inconsistent before and after the occlusion. During the period of 2004-2013, the average number of occluded sunshine hours was 218.0 h·a-1, and the occlusion ratio reached 13.1%. Due to the hedging effect of weather conditions, the influence of occlusion in summer half year may be higher than that in winter half year. From the indirect comparison between the vertical and horizontal aspects, the correction method established in this paper not only calculates the influence of the occluder itself, but also takes into account the correction of the occlusion ration under cloudy conditions. The correction results are basically reasonable, and can be relatively accurately restore the occluded sunshine hours.
2021, 47(5):619-626.
DOI: 10.7519/j.issn.1000-0526.2021.05.010
Abstract:
Based on the daily meteorological observation data and maize observation data of 13 agrometeorological experimental stations from 2010 to 2017, the canopy rainfall interception and its variation of main maize production areas in China are studied by using the rainfall interception model for maize. The results show that under different climatic conditions and growth conditions, the interception of maize canopy is quite different. The average interception is 4.3-23.5 mm. When the precipitation from jointing to matur-ity is less than 70 mm, the interception is less than 8 mm. With the increase of precipitation, the interception is first affected by both precipitation and maximum leaf area index (LAImax) and then becomes more sensitive to LAImax. The average interception rate is 1.9%-11.6%, and the interception rate is relatively stable in Huang-Huai-Hai summer maize planting area. The interception rate exceedes 10% in areas with precipitation less than 120 mm in growing season. Furthermore, the average interception rate range is given according to the classification of main maize production area and climatic dryness and wetness. The canopy interception and interception rate in different areas can be estimated according to precipitation from joining to maturity, LAImax and the rule of interception change. The interception research based on the actual growth and natural rainfall provides scientific basis for effective precipitation assessment, drought index correction, and farmland water cycle, and so on.
Based on the daily meteorological observation data and maize observation data of 13 agrometeorological experimental stations from 2010 to 2017, the canopy rainfall interception and its variation of main maize production areas in China are studied by using the rainfall interception model for maize. The results show that under different climatic conditions and growth conditions, the interception of maize canopy is quite different. The average interception is 4.3-23.5 mm. When the precipitation from jointing to matur-ity is less than 70 mm, the interception is less than 8 mm. With the increase of precipitation, the interception is first affected by both precipitation and maximum leaf area index (LAImax) and then becomes more sensitive to LAImax. The average interception rate is 1.9%-11.6%, and the interception rate is relatively stable in Huang-Huai-Hai summer maize planting area. The interception rate exceedes 10% in areas with precipitation less than 120 mm in growing season. Furthermore, the average interception rate range is given according to the classification of main maize production area and climatic dryness and wetness. The canopy interception and interception rate in different areas can be estimated according to precipitation from joining to maturity, LAImax and the rule of interception change. The interception research based on the actual growth and natural rainfall provides scientific basis for effective precipitation assessment, drought index correction, and farmland water cycle, and so on.
WANG Qingping
,
ZHU Wenna
,
WANG Yong
,
CHEN Yangquan
,
HAN Lei
,
WANG Chunhong
,
TAN Yanmei
,
ZHANG Liping
2021, 47(5):627-637.
DOI: 10.7519/j.issn.1000-0526.2021.05.011
Abstract:
Using FY-4A images generated by advanced geosynchronous radiation imager (ARGI) and level 2 satellite cloud product data and surface observation data, this paper analyzes two dense fog weather events that happened in 25-26 January 2019 and in 17-18 March 2019 at Urumqi International Airport. The results show that we can use Channel 3 (BD0.83 μm), Channel 6 (BD2.2 μm) Channel 8 (BD3.725 μm) and Channel 12 (BD10.8 μm) to monitoring the range of dense fog and the cloud structure features of fog top and the temperature of fog area during the daytime. Dissipation of fog has a good reflection on satellite images. At night, the difference between BD10.8 μm and BD3.725 μm (BTD10.8 μm-3.725 μm) and images of BD10.8 μm can be combined to identify the night foggy area, and the greater the bright temperature difference in the BTD10.8 μm-3.725 μm channels, the denser the fog. FY-4A satellite cloud top height and cloud classification products have more meticulous features on microphysical characteristics of dense fog. It is very effective in monitoring night dense fog and it also can make up for the deficiency of visible channels such as from Channel 1 to Channel 3, Channel 6 and Channel 8, which can only be used in the daytime.
Using FY-4A images generated by advanced geosynchronous radiation imager (ARGI) and level 2 satellite cloud product data and surface observation data, this paper analyzes two dense fog weather events that happened in 25-26 January 2019 and in 17-18 March 2019 at Urumqi International Airport. The results show that we can use Channel 3 (BD0.83 μm), Channel 6 (BD2.2 μm) Channel 8 (BD3.725 μm) and Channel 12 (BD10.8 μm) to monitoring the range of dense fog and the cloud structure features of fog top and the temperature of fog area during the daytime. Dissipation of fog has a good reflection on satellite images. At night, the difference between BD10.8 μm and BD3.725 μm (BTD10.8 μm-3.725 μm) and images of BD10.8 μm can be combined to identify the night foggy area, and the greater the bright temperature difference in the BTD10.8 μm-3.725 μm channels, the denser the fog. FY-4A satellite cloud top height and cloud classification products have more meticulous features on microphysical characteristics of dense fog. It is very effective in monitoring night dense fog and it also can make up for the deficiency of visible channels such as from Channel 1 to Channel 3, Channel 6 and Channel 8, which can only be used in the daytime.
2021, 47(5):638-644.
DOI: 10.7519/j.issn.1000-0526.2021.05.012
Abstract:
The main characteristics of the general atmospheric circulation in February 2021 are as follows. There were two polar vortex centers in the Northern Hemisphere and they were weaker than normal. The general atmospheric circulation over mid-high latitudes of the Northern Hemisphere showed a four-wave pattern, and the circulation was of zonal type. The western Pacific subtropical high was stronger than normal but its impact range was small. Cold air processes in this month were weak with small influence scope in China. The monthly mean temperature was 1.2℃, higher than normal by 2.9℃, which is the highest in the same period since 1961. An extreme high temperature event occurred because the daily maximum temperatures at 618 national meteorological stations nationwide exceeded the historical extreme values in the same period in records. In February, the monthly mean precipitation was 19.6 mm, 9.5% higher than normal. In addition, in the middle of February, sustained heavy fog weather appeared in the central and eastern part of China, and a sand-dust event occurred across North China at the end of February.
The main characteristics of the general atmospheric circulation in February 2021 are as follows. There were two polar vortex centers in the Northern Hemisphere and they were weaker than normal. The general atmospheric circulation over mid-high latitudes of the Northern Hemisphere showed a four-wave pattern, and the circulation was of zonal type. The western Pacific subtropical high was stronger than normal but its impact range was small. Cold air processes in this month were weak with small influence scope in China. The monthly mean temperature was 1.2℃, higher than normal by 2.9℃, which is the highest in the same period since 1961. An extreme high temperature event occurred because the daily maximum temperatures at 618 national meteorological stations nationwide exceeded the historical extreme values in the same period in records. In February, the monthly mean precipitation was 19.6 mm, 9.5% higher than normal. In addition, in the middle of February, sustained heavy fog weather appeared in the central and eastern part of China, and a sand-dust event occurred across North China at the end of February.
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ISSN:1000-0526 CN:11-2282/P