Abstract:
keep_len="250">To meet the requirement of numerical weather prediction for local severe convective weather, especially disastrous weather and extreme weather events, based on GRAPES-MESO 10 km system, many works have been completed, which include improving the calculation accuracy and stability of the model dynamic framework, selecting and testing the physical parameterization schemes suitable for high-resolution model, establishing a national radar quality control preprocess system, applying the national (SA/SB/CB) three-dimensional network mosaic data through the cloud analysis system, establishing a convective resolvable assimilation system and land surface data assimilation system for small and medium-scale systems, implementing the assimilation and application of unconventional local dense data such as radar radial wind, wind profile radar, FY-4A imager emissivity, satellite cloud motion wind, satellite GNSSRO, surface precipitation and the near surface data, and developing the rapid cycle technology. By integrating all the jobs mentioned above, the nationwide rapid analysis and forecast system CMA-MESO (GRAPES-MESO 3 km)has been established and put into operational run since June 2020 with 3 km horizontal resolution and 3 h time interval. The operational verification results in flood season from June to September of 2020 show that the forecasts of near surface elements (precipitation, 2 m temperature and 10 m wind) of CMA-MESO forecast surpass the results of GRAPES-MESO 10 km system, and the threat score for 3 h accumulated precipitation forecast is outstanding. The threat score for 24 h accumulated precipitation of CMA-MESO is slightly worse than the result of ECMWF, but the threat score for 3 h accumulated precipitation forecast is significantly better. For the precipitation exceeding 10.0 mm, CMA-MESO performs better than ECMWF within all the lead times, and the advantages are more obvious with the increase of precipitation threshold. Compared to ECMWF, CMA-MESO shows more obvious advantages on daytime forecast. For 25 mm precipitation threshold, the improvement rate exceeds 50% in most of the daytime and reaches about 100% in the later stage of forecast. The spatial distribution of mean 24 h accumulated precipitation predicted by CMA-MESO and ECMWF models is close to the observation, but the amount predicted by CMA-MESO is slightly larger. The frequency and intensity of precipitation simulated by CMA-MESO, which can characterize the ability of model to predict the spatial-temporal fine characteristics of precipitation, are consistent with observation in terms of both horizontal distribution and magnitude. The comprehensive performance of CMA-MESO in flood season in China exceeds that of ECMWF fine grid model. To meet the requirement of numerical weather prediction for local severe convective weather, especially disastrous weather and extreme weather events, based on GRAPES-MESO 10 km system, many works have been completed, which include improving the calculation accuracy and stability of the model dynamic framework, selecting and testing the physical parameterization schemes suitable for high-resolution model, establishing a national radar quality control preprocess system, applying the national (SA/SB/CB) three-dimensional network mosaic data through the cloud analysis system, establishing a convective resolvable assimilation system and land surface data assimilation system for small and medium-scale systems, implementing the assimilation and application of unconventional local dense data such as radar radial wind, wind profile radar, FY-4A imager emissivity, satellite cloud motion wind, satellite GNSSRO, surface precipitation and the near surface data, and developing the rapid cycle technology. By integrating all the jobs mentioned above, the nationwide rapid analysis and forecast system CMA-MESO (GRAPES-MESO 3 km)has been established and put into operational run since June 2020 with 3 km horizontal resolution and 3 h time interval. The operational verification results in flood season from June to September of 2020 show that the forecasts of near surface elements (precipitation, 2 m temperature and 10 m wind) of CMA-MESO forecast surpass the results of GRAPES-MESO 10 km system, and the threat score for 3 h accumulated precipitation forecast is outstanding. The threat score for 24 h accumulated precipitation of CMA-MESO is slightly worse than the result of ECMWF, but the threat score for 3 h accumulated precipitation forecast is significantly better. For the precipitation exceeding 10.0 mm, CMA-MESO performs better than ECMWF within all the lead times, and the advantages are more obvious with the increase of precipitation threshold. Compared to ECMWF, CMA-MESO shows more obvious advantages on daytime forecast. For 25 mm precipitation threshold, the improvement rate exceeds 50% in most of the daytime and reaches about 100% in the later stage of forecast. The spatial distribution of mean 24 h accumulated precipitation predicted by CMA-MESO and ECMWF models is close to the observation, but the amount predicted by CMA-MESO is slightly larger. The frequency and intensity of precipitation simulated by CMA-MESO, which can characterize the ability of model to predict the spatial-temporal fine characteristics of precipitation, are consistent with observation in terms of both horizontal distribution and magnitude. The comprehensive performance of CMA-MESO in flood season in China exceeds that of ECMWF fine grid model.

Abstract:
keep_len="250">China Meteorological Administration Global Ensemble Prediction System (CMA-GEPS) adopts singular vector method to generate initial perturbations. CMA-GEPS currently uses the initial analysis field from CMA Global Forecast System (CMA-GFS) data assimilation to calculate singular vector (ANSV). With this dependency, in the operational running procedures of CMA numerical weather prediction systems, the singular vector calculation starts when CMA-GFS analysis job is finished. With the improvement of model resolution, especially the horizontal resolution, the computation time of data assimilation analysis and the ensemble forecasts would be lengthened. Given relatively limited high-performance computational resources, it would bring great challenge for delivering the ensemble forecast products on time. ECMWF uses the data assimilation background field to calculate singular vector (FCSV), which could be implemented earlier than the computation of ANSV in the operational flow and then optimize the computation time for ensemble prediction system (EPS), and it shows that the performance of FCSV ensemble is comparable to ANSV ensemble.Based on CMA-GFS background field and SV calculation module, the feasibility of applying FCSV in CMA-GEPS is investigated. First, the spatial structures of ANSV and FCSV and their similarity index are analyzed. And then, two ensembles based on ANSV and FCSV are conducted for 10 cases in summer and autumn. The forecasts from ANSV ensemble and FCSV ensemble are comprehensively evaluated in terms of the ensemble prediction skill of barometric surface variables, the probability prediction of 24 hours accumulated precipitation in China, tropical cyclone track ensemble prediction skill, and the forecast skill of the minimum sea level pressure at tropical cyclone center. The results show that for the dominant extra-tropical singular vector in CMA-GEPS, the ANSV and FCSV have similar horizontal and vertical structures, their general similarity index is 0.6-0.8, and two ensembles have the comparable forecast skill over extratropics. For tropical singular vector which are only calculated when tropical cyclones are observed, their similarity index between ANSV and FCSV is relatively lower than that in extratropics, and FCSV ensemble shows slightly smaller ensemble spread but comparable error for tropical cyclone tracks. For the precipitation forecast, two ensembles have similar forecast skills for moderate to heavy rain. For mean sea level pressure forecast of strong tropical cyclone case, two ensemble have members showing the skill in terms of structures and magnitude. Therefore, it is feasible to apply FCSV in CMA-GEPS, and it could be an option to construct singular vector-based initial perturbations for future high-resolution operational CMA-GEPS. China Meteorological Administration Global Ensemble Prediction System (CMA-GEPS) adopts singular vector method to generate initial perturbations. CMA-GEPS currently uses the initial analysis field from CMA Global Forecast System (CMA-GFS) data assimilation to calculate singular vector (ANSV). With this dependency, in the operational running procedures of CMA numerical weather prediction systems, the singular vector calculation starts when CMA-GFS analysis job is finished. With the improvement of model resolution, especially the horizontal resolution, the computation time of data assimilation analysis and the ensemble forecasts would be lengthened. Given relatively limited high-performance computational resources, it would bring great challenge for delivering the ensemble forecast products on time. ECMWF uses the data assimilation background field to calculate singular vector (FCSV), which could be implemented earlier than the computation of ANSV in the operational flow and then optimize the computation time for ensemble prediction system (EPS), and it shows that the performance of FCSV ensemble is comparable to ANSV ensemble.Based on CMA-GFS background field and SV calculation module, the feasibility of applying FCSV in CMA-GEPS is investigated. First, the spatial structures of ANSV and FCSV and their similarity index are analyzed. And then, two ensembles based on ANSV and FCSV are conducted for 10 cases in summer and autumn. The forecasts from ANSV ensemble and FCSV ensemble are comprehensively evaluated in terms of the ensemble prediction skill of barometric surface variables, the probability prediction of 24 hours accumulated precipitation in China, tropical cyclone track ensemble prediction skill, and the forecast skill of the minimum sea level pressure at tropical cyclone center. The results show that for the dominant extra-tropical singular vector in CMA-GEPS, the ANSV and FCSV have similar horizontal and vertical structures, their general similarity index is 0.6-0.8, and two ensembles have the comparable forecast skill over extratropics. For tropical singular vector which are only calculated when tropical cyclones are observed, their similarity index between ANSV and FCSV is relatively lower than that in extratropics, and FCSV ensemble shows slightly smaller ensemble spread but comparable error for tropical cyclone tracks. For the precipitation forecast, two ensembles have similar forecast skills for moderate to heavy rain. For mean sea level pressure forecast of strong tropical cyclone case, two ensemble have members showing the skill in terms of structures and magnitude. Therefore, it is feasible to apply FCSV in CMA-GEPS, and it could be an option to construct singular vector-based initial perturbations for future high-resolution operational CMA-GEPS.

Abstract:
keep_len="250">The extreme heavy rainfall event in Henan Province during 17-23 July 2021 with 1-hour rainfall intensity breaking historical record in the inland of China, ranks second among the top 10 weather and climate events in China in 2021. Previous studies have investigated the rain gauge observations collected by the meteorological ground stations to analyze the rainfall situation and count the extreme value of the "21·7" process. Considering the rainfall is uneven in space and time, the observations from a single source has great uncertainty which may miss the actual rainfall extreme value. By comparing the rainfall observations between meteorological and hydrological rain gauge stations, the objectivity and accuracy of the rainfall records from two business systems are analyzed for the "21·7" extreme heavy rainfall event. It is found that the observations exhibit good agreement in the accumulated rainfall distributions of various levels, and the temporal evolution of daily and hourly rainfall. However, the positions and values of accumulated rainfall and hourly rainfall intensity extremum are different in detail according to these two systems. The systematic deviation between the meteorological and hydrological observations is less than 1% in the heavy rainfall area (6-day accumulated rainfall more than 600 mm). These differences are related to the distinctness in the number, location, density of stations, and the accuracy of observation instruments. In addition, the inhomogeneous features of the rainfall in time and space also lead to the deviation of rainfall records between meteorological and hydrological observations.On the other hand, the meteorological and hydrological rainfall data in top 3 accumulated rainfall cities (Zhengzhou, Hebi and Xinxiang) are merged. The results show that merged rainfall data can present more detailed rainfall distributions and more objective rainfall evolution characteristics compared to single source data. Based on the merged rainfall data, the rainfall features in these three cities are summarized. The strongest rainfall period in Hebi and Xinxiang are about 26 hours and 28 hours later than that at Zhengzhou, respectively, while the rainfall events happened in these three cities are characterized by large accumulated amount, extremely strong hourly intensity, concentrated location and sudden increase of rainfall intensity. The extreme heavy rainfall event in Henan Province during 17-23 July 2021 with 1-hour rainfall intensity breaking historical record in the inland of China, ranks second among the top 10 weather and climate events in China in 2021. Previous studies have investigated the rain gauge observations collected by the meteorological ground stations to analyze the rainfall situation and count the extreme value of the "21·7" process. Considering the rainfall is uneven in space and time, the observations from a single source has great uncertainty which may miss the actual rainfall extreme value. By comparing the rainfall observations between meteorological and hydrological rain gauge stations, the objectivity and accuracy of the rainfall records from two business systems are analyzed for the "21·7" extreme heavy rainfall event. It is found that the observations exhibit good agreement in the accumulated rainfall distributions of various levels, and the temporal evolution of daily and hourly rainfall. However, the positions and values of accumulated rainfall and hourly rainfall intensity extremum are different in detail according to these two systems. The systematic deviation between the meteorological and hydrological observations is less than 1% in the heavy rainfall area (6-day accumulated rainfall more than 600 mm). These differences are related to the distinctness in the number, location, density of stations, and the accuracy of observation instruments. In addition, the inhomogeneous features of the rainfall in time and space also lead to the deviation of rainfall records between meteorological and hydrological observations.On the other hand, the meteorological and hydrological rainfall data in top 3 accumulated rainfall cities (Zhengzhou, Hebi and Xinxiang) are merged. The results show that merged rainfall data can present more detailed rainfall distributions and more objective rainfall evolution characteristics compared to single source data. Based on the merged rainfall data, the rainfall features in these three cities are summarized. The strongest rainfall period in Hebi and Xinxiang are about 26 hours and 28 hours later than that at Zhengzhou, respectively, while the rainfall events happened in these three cities are characterized by large accumulated amount, extremely strong hourly intensity, concentrated location and sudden increase of rainfall intensity.

Abstract:
keep_len="250">Meteorological satellites can provide more details of cloud, which can be used to analyze the development process of convective cloud in the rainstorm events. To investigate the "21·7" extreme heavy rainfall in Henan Province, satellite cloud image characteristics, the development and evolution process of precipitation clouds, macro structure and microphysical features are deeply analyzed by FY-4A satellite data, FY-3D satellite data, and ERA5 reanalysis data. Particularly, FY-4A satellite data are used to study the cloud microphysical features of this event for the first time. The boundary position and intensity of the water vapor dark area of continental high are relatively stable from 18 July to 22 July in 2021, and the subtropical high continues to extend westward. The stable saddle field is conductive to the long-term development and maintenance of the low vortex cloud system over Henan Province. Two streams of water vapor locate at the north central part of Henan Province, which is favorable for the occurrence of rainstorm at Zhengzhou on 20 July. The reorganization and adjustment of the convective system are due to the consolidation and development of several convective clouds over Henan Province on 20 July. From 1400 BT to 1600 BT, the boundary of cold cloud is over Zhengzhou, where the brightness temperature gradient value is large, indicating that the convection is in its development stage. Furthermore, the cloud optical thickness increases from 1200 BT to 1400 BT, and still maintains a large value at 1500 BT. It indicates that this period is critical for a large number of liquid particles to merge. The time when the cloud optical thickness reaches peak value is prior to that of the precipitation. The increasing trend and value of cloud optical thickness have great significance for the magnitude and occurrence time of heavy rainfall. The relations between cloud top temperature and particle effective radius(T-r_e relations) are analyzed by FY-4A data. The results show that the rain zone over Henan Province is the deepest at 1600 BT 20 July, and the effective radius of cloud particles at different heights maintain at 20-25 μm. It indicates that the updraft in the cloud is strong, which is conductive to the occurrence of heavy rainfall. Meteorological satellites can provide more details of cloud, which can be used to analyze the development process of convective cloud in the rainstorm events. To investigate the "21·7" extreme heavy rainfall in Henan Province, satellite cloud image characteristics, the development and evolution process of precipitation clouds, macro structure and microphysical features are deeply analyzed by FY-4A satellite data, FY-3D satellite data, and ERA5 reanalysis data. Particularly, FY-4A satellite data are used to study the cloud microphysical features of this event for the first time. The boundary position and intensity of the water vapor dark area of continental high are relatively stable from 18 July to 22 July in 2021, and the subtropical high continues to extend westward. The stable saddle field is conductive to the long-term development and maintenance of the low vortex cloud system over Henan Province. Two streams of water vapor locate at the north central part of Henan Province, which is favorable for the occurrence of rainstorm at Zhengzhou on 20 July. The reorganization and adjustment of the convective system are due to the consolidation and development of several convective clouds over Henan Province on 20 July. From 1400 BT to 1600 BT, the boundary of cold cloud is over Zhengzhou, where the brightness temperature gradient value is large, indicating that the convection is in its development stage. Furthermore, the cloud optical thickness increases from 1200 BT to 1400 BT, and still maintains a large value at 1500 BT. It indicates that this period is critical for a large number of liquid particles to merge. The time when the cloud optical thickness reaches peak value is prior to that of the precipitation. The increasing trend and value of cloud optical thickness have great significance for the magnitude and occurrence time of heavy rainfall. The relations between cloud top temperature and particle effective radius(T-r_e relations) are analyzed by FY-4A data. The results show that the rain zone over Henan Province is the deepest at 1600 BT 20 July, and the effective radius of cloud particles at different heights maintain at 20-25 μm. It indicates that the updraft in the cloud is strong, which is conductive to the occurrence of heavy rainfall.

Abstract:
keep_len="250">Using meteorological satellite data and the reanalysis dataset from European Centre for Medium Range Weather Forecasts(ERA5) and others, based on the accuracy evaluation of FY-3D/VASS temperature in North America, the climatic background, development and evolution of North America winter storm Uri in 2021, the triggering effects of polar vortex activities on Uri and the characteristics of atmospheric environment causing extreme low temperature and snowfall are studied. The results show that the average absolute error of FY-3D/VASS temperature at 100, 400 hPa and 850 hPa are 1.14℃, 1.44℃ and 2.63℃ respectively. It shows that FY-3D/VASS temperature can meet the demand of global extreme cold event monitoring, and it is an important data source in regions where conventional meteorological observation is insufficient. FY-3D/VASS temperature analysis shows that in February 2021, when winter storm Uri is active, the temperature in the western part of the key area of polar cold air activity in North America (50°-150°W, 50°-80°N) is 4-8℃ lower than climate mean. The cold air intensity is the strongest in the first ten days of February, and the maximum percentage of temperature anomaly is about 70%. Under the guidance of the warm high ridge in the northeast Pacific, the polar vortex intensifies and extends southward, and the cold air breaks out southward during the vertical rotation of the horizontal trough on the west side of the polar vortex center. The abnormal southward extension of the upper troposphere potential vorticity in high latitude provides upper-level dynamic forcing for the formation of Uri. The cold air in the low layer extends southward and intersects with the warm and humid airflow transported northward over the Gulf of Mexico along the west side of the subtropical high in southern United States. They trigger the low-level vortex of storm Uri and the rapid development of cloud system. The cloud causing strong snowfall of storm Uri shows convective characteristics, with the cloud top brightness temperature reaching lower than -40℃ and even lower than -52℃ in some areas. Lightning is also active in the storm cloud system which causes heavy snow. Using meteorological satellite data and the reanalysis dataset from European Centre for Medium Range Weather Forecasts(ERA5) and others, based on the accuracy evaluation of FY-3D/VASS temperature in North America, the climatic background, development and evolution of North America winter storm Uri in 2021, the triggering effects of polar vortex activities on Uri and the characteristics of atmospheric environment causing extreme low temperature and snowfall are studied. The results show that the average absolute error of FY-3D/VASS temperature at 100, 400 hPa and 850 hPa are 1.14℃, 1.44℃ and 2.63℃ respectively. It shows that FY-3D/VASS temperature can meet the demand of global extreme cold event monitoring, and it is an important data source in regions where conventional meteorological observation is insufficient. FY-3D/VASS temperature analysis shows that in February 2021, when winter storm Uri is active, the temperature in the western part of the key area of polar cold air activity in North America (50°-150°W, 50°-80°N) is 4-8℃ lower than climate mean. The cold air intensity is the strongest in the first ten days of February, and the maximum percentage of temperature anomaly is about 70%. Under the guidance of the warm high ridge in the northeast Pacific, the polar vortex intensifies and extends southward, and the cold air breaks out southward during the vertical rotation of the horizontal trough on the west side of the polar vortex center. The abnormal southward extension of the upper troposphere potential vorticity in high latitude provides upper-level dynamic forcing for the formation of Uri. The cold air in the low layer extends southward and intersects with the warm and humid airflow transported northward over the Gulf of Mexico along the west side of the subtropical high in southern United States. They trigger the low-level vortex of storm Uri and the rapid development of cloud system. The cloud causing strong snowfall of storm Uri shows convective characteristics, with the cloud top brightness temperature reaching lower than -40℃ and even lower than -52℃ in some areas. Lightning is also active in the storm cloud system which causes heavy snow.

Abstract:
keep_len="250">Two processes of mesoscale convection moving eastward into the Bohai Bay on 12 May and 13 Jul in 2018, which are weakened process and enhanced process respectively, are simulated and analyzed by using the ocean-atmosphere-wave coupling model and dynamic downscaling method. Both processes occur under the control of strong southwesterly at low level and warm tongue near surface, which bring abundant water vapor and heat. The results show that the coupling model can simulate the right trend of the weakened process, but the wrong trend of the enhanced process, and the simulated intensity is overall weak. The simulation effects are improved obviously after the spatial resolution of the model increasing by using dynamic downscaling method twice. Through the comparison of sensitivity experiments, it is indicated that the coupling model has certain advantages in providing better initial and boundary conditions for the dynamic downscaling, which is suitable for the simulation, compared with the general atmospheric WRF model. Through the diagnosis and analysis of the simulation results, it's concluded that before the convection systems entering the sea, the convective available potential energy (CAPE) is large in the Bohai Bay and coastal areas. As the convection systems moving eastward into the sea, the CAPE is gradually consumed, but the supplement of CAPE in the enhanced process is stronger than that in the weakened process. The 0-6 km vertical wind shear condition of the enhanced process is also stronger than that of the weakened process in the Bohai Bay before the convection systems entering the sea, which is another favorable factor for the development of the convection. In the weakened process, the cold pool effect is increasingly stronger with an obvious rear inflow, and there is an obvious wind velocity convergence in the front of the cold pool during the convection systems moving. In the enhanced process, however, the strength of the cold pool is weaker, but the range is larger compared with the weakened process, and there is an obvious wind direction convergence in the front of the cold pool. In the weakened process, the underlying surface of the ocean provide less water vapor and heat energy for the convection region, making the convection difficult to maintain or further develop, while in the enhanced process the sea surface provides mass water vapor and heat energy transfer to the convective region when the convection system moving over the sea. Two processes of mesoscale convection moving eastward into the Bohai Bay on 12 May and 13 Jul in 2018, which are weakened process and enhanced process respectively, are simulated and analyzed by using the ocean-atmosphere-wave coupling model and dynamic downscaling method. Both processes occur under the control of strong southwesterly at low level and warm tongue near surface, which bring abundant water vapor and heat. The results show that the coupling model can simulate the right trend of the weakened process, but the wrong trend of the enhanced process, and the simulated intensity is overall weak. The simulation effects are improved obviously after the spatial resolution of the model increasing by using dynamic downscaling method twice. Through the comparison of sensitivity experiments, it is indicated that the coupling model has certain advantages in providing better initial and boundary conditions for the dynamic downscaling, which is suitable for the simulation, compared with the general atmospheric WRF model. Through the diagnosis and analysis of the simulation results, it's concluded that before the convection systems entering the sea, the convective available potential energy (CAPE) is large in the Bohai Bay and coastal areas. As the convection systems moving eastward into the sea, the CAPE is gradually consumed, but the supplement of CAPE in the enhanced process is stronger than that in the weakened process. The 0-6 km vertical wind shear condition of the enhanced process is also stronger than that of the weakened process in the Bohai Bay before the convection systems entering the sea, which is another favorable factor for the development of the convection. In the weakened process, the cold pool effect is increasingly stronger with an obvious rear inflow, and there is an obvious wind velocity convergence in the front of the cold pool during the convection systems moving. In the enhanced process, however, the strength of the cold pool is weaker, but the range is larger compared with the weakened process, and there is an obvious wind direction convergence in the front of the cold pool. In the weakened process, the underlying surface of the ocean provide less water vapor and heat energy for the convection region, making the convection difficult to maintain or further develop, while in the enhanced process the sea surface provides mass water vapor and heat energy transfer to the convective region when the convection system moving over the sea.

Abstract:
keep_len="250">In China, the operational upgrade of dual polarimetric weather radar is being promoted. CINRAD/SAD dual polarimetric weather radar in some provinces such as Guangdong, Jiangsu, Shandong and Zhejiang has been upgraded in operation. By June of 2021, there are 69 dual polarimetric weather radars in national radar network, and it will increase to more than 100 in the future. The dual polarimetric radar is an important detection equipment for studying the microphysical process of precipitation, which can provide multiple polarizations including raindrop spectrum information, and thus better describe the microphysical characteristics of precipitation. The technical upgrade will bring revolutionary changes for data quality control, hydrogel classification and quantitative precipitation estimation. With the measurement parameters such as correlation coefficient or differential reflectivity, the dual-polarimetric weather radar can effectively remove non-precipitation echoes such as ground clutter, anomalous propagation, electromagnetic interference, sea waves, clear air clutter and so on. Based on the non-precipitation identification technique on S-band WSR-88D dual polarization weather radar, the distribution characteristics of correlation coefficient and differential reflectivity in precipitation echo and clutter are analyzed. The CINRAD/SAD dual-polarimetric weather radar data are used to test and improve the algorithm to adapt domestic weather radar, the differential reflectivity texture feature is added in the improved algorithm and the distribution characteristics of differential reflectivity horizontal texture on precipitation echo and clutter are analyzed, to better remove non-precipitation echo. During the evaluation of algorithm, several cases such as hail, melting layer, typhoon and different types of clutters during May-October in 2019 and 2020 are investigated. The results show that the improved algorithm can identify 95.2% of non-precipitation echoes, and the error rate of precipitation is 2.6%. For the large area clear air clutter, after adding the differential reflectivity texture feature, combining with the correlation coefficient texture feature, the accuracy of the algorithm is improved from 68.6% to 96.8% for one case, but the overall accuracy is less than 90% for many cases, and it needs to be improved by deep learning method in the future. Non-precipitation identification algorithm on CINRAD/SAD is applied in mosaic image, showing great application prospect in the future for precipitation classification and quantitative precipitation estimation. It can provide high quality data and play an important role in real-time operation. In China, the operational upgrade of dual polarimetric weather radar is being promoted. CINRAD/SAD dual polarimetric weather radar in some provinces such as Guangdong, Jiangsu, Shandong and Zhejiang has been upgraded in operation. By June of 2021, there are 69 dual polarimetric weather radars in national radar network, and it will increase to more than 100 in the future. The dual polarimetric radar is an important detection equipment for studying the microphysical process of precipitation, which can provide multiple polarizations including raindrop spectrum information, and thus better describe the microphysical characteristics of precipitation. The technical upgrade will bring revolutionary changes for data quality control, hydrogel classification and quantitative precipitation estimation. With the measurement parameters such as correlation coefficient or differential reflectivity, the dual-polarimetric weather radar can effectively remove non-precipitation echoes such as ground clutter, anomalous propagation, electromagnetic interference, sea waves, clear air clutter and so on. Based on the non-precipitation identification technique on S-band WSR-88D dual polarization weather radar, the distribution characteristics of correlation coefficient and differential reflectivity in precipitation echo and clutter are analyzed. The CINRAD/SAD dual-polarimetric weather radar data are used to test and improve the algorithm to adapt domestic weather radar, the differential reflectivity texture feature is added in the improved algorithm and the distribution characteristics of differential reflectivity horizontal texture on precipitation echo and clutter are analyzed, to better remove non-precipitation echo. During the evaluation of algorithm, several cases such as hail, melting layer, typhoon and different types of clutters during May-October in 2019 and 2020 are investigated. The results show that the improved algorithm can identify 95.2% of non-precipitation echoes, and the error rate of precipitation is 2.6%. For the large area clear air clutter, after adding the differential reflectivity texture feature, combining with the correlation coefficient texture feature, the accuracy of the algorithm is improved from 68.6% to 96.8% for one case, but the overall accuracy is less than 90% for many cases, and it needs to be improved by deep learning method in the future. Non-precipitation identification algorithm on CINRAD/SAD is applied in mosaic image, showing great application prospect in the future for precipitation classification and quantitative precipitation estimation. It can provide high quality data and play an important role in real-time operation.

Abstract:
keep_len="250">The climate data of 180 meteorological stations from 1991 to 2020 are analyzed, representing different flue-cured tobacco planting areas in north central subtropical zone of China. The latest growth period division method and the latest tobacco varieties are considered, and the key growth period indicators of high-quality flue-cured tobacco are obtained through field investigation. According to the climatic conditions affecting the growth and development of high-quality tobacco leaves, the characteristics of the main climatic factors such as temperature, sunshine duration and precipitation in the field period and each development periods including root extension period, vigorous growing period and mature period are statistically analyzed. The weight of climate factors is calculated with principal component analysis method. Based on the principle of climate similarity, the similarity analysis is carried out by using the improved Euclidean distance between the two major tobacco planting areas of Hubei Province and the surrounding tobacco planting areas. The clustering results are obtained by hierarchical cluster method. The results show that the climate factors such as temperature, precipitation and sunshine duration meet the climate conditions for the growth of high-quality tobacco in the planting areas of southwest Hubei, northwest Hubei, western Henan, southern Henan, central Henan, western Hunan and central Hunan, compared with other tobacco planting areas. The difference of other climatic elements in different development periods is the largest in the root extension period, then in vigorous growing period, and is the smallest in the mature period except for precipitation. The climate elements in different development periods of tobacco planting areas are moderate in northwest and southwest Hubei, which is suitable for the growth and development of high-quality tobacco. Among the climatic factors affecting the growth and development of tobacco leaves, the temperature maximum in the prosperous period has the greatest impact on the growth and development of tobacco leaves. By comparing and analyzing the climate similarity of high-quality flue-cured tobacco areas in north central subtropical zone of China with two methods, the consistent conclusion is drawn. The climate elements of the tobacco planting areas are the closest in northwest Hubei and southern Shaanxi, and the climate elements of the tobacco planting areas are highly similar in southwest Hubei and western Hunan and southeast Sichuan. The results provide theoretical basis to optimize the layout of flue-cured tobacco planting and develop exclusive high-quality tobacco. The climate data of 180 meteorological stations from 1991 to 2020 are analyzed, representing different flue-cured tobacco planting areas in north central subtropical zone of China. The latest growth period division method and the latest tobacco varieties are considered, and the key growth period indicators of high-quality flue-cured tobacco are obtained through field investigation. According to the climatic conditions affecting the growth and development of high-quality tobacco leaves, the characteristics of the main climatic factors such as temperature, sunshine duration and precipitation in the field period and each development periods including root extension period, vigorous growing period and mature period are statistically analyzed. The weight of climate factors is calculated with principal component analysis method. Based on the principle of climate similarity, the similarity analysis is carried out by using the improved Euclidean distance between the two major tobacco planting areas of Hubei Province and the surrounding tobacco planting areas. The clustering results are obtained by hierarchical cluster method. The results show that the climate factors such as temperature, precipitation and sunshine duration meet the climate conditions for the growth of high-quality tobacco in the planting areas of southwest Hubei, northwest Hubei, western Henan, southern Henan, central Henan, western Hunan and central Hunan, compared with other tobacco planting areas. The difference of other climatic elements in different development periods is the largest in the root extension period, then in vigorous growing period, and is the smallest in the mature period except for precipitation. The climate elements in different development periods of tobacco planting areas are moderate in northwest and southwest Hubei, which is suitable for the growth and development of high-quality tobacco. Among the climatic factors affecting the growth and development of tobacco leaves, the temperature maximum in the prosperous period has the greatest impact on the growth and development of tobacco leaves. By comparing and analyzing the climate similarity of high-quality flue-cured tobacco areas in north central subtropical zone of China with two methods, the consistent conclusion is drawn. The climate elements of the tobacco planting areas are the closest in northwest Hubei and southern Shaanxi, and the climate elements of the tobacco planting areas are highly similar in southwest Hubei and western Hunan and southeast Sichuan. The results provide theoretical basis to optimize the layout of flue-cured tobacco planting and develop exclusive high-quality tobacco.

Abstract:
keep_len="250">A field experiment is conducted in Jianghan Plain using static chamber-gas chromatography method to monitor greenhouse gas emissions from 5 different rice cropping systems:Early rice, late rice, middle rice, rice-crayfish coculture and ratooning rice systems. The emission characteristics of methane and nitrous oxide fluxes, global warming potential and greenhouse gas emission intensity in different rice patterns are analyzed, aiming to provide scientific references for accurate estimates of greenhouse gas emissions from rice paddy. The results show that methane emissions are concentrated in the early flooding stage of rice paddy, with a flux peak of (85.7 mg·m^-2·h^-1) for rice-crayfish system, which is higher than those of other patterns by 71.7%-191.5%. Nitrous oxide emissions are mainly observed during mid-season drainage or after nitrogen fertilization, and the highest flux peak is found for ratooning rice (1100.7 μg·m^-2·h^-1), which is 16.8%-654.9% higher than other patterns. The sequence of accumulated methane emission from largest to smallest is rice-crayfish (541.1 kg·hm^-2), ratooning rice (293.7 kg·hm^-2), early rice (177.2 kg·hm^-2), late rice (133.7 kg·hm^-2), and middle rice (115.3 kg·hm^-2). For nitrous oxide emission, the sequence is ratooning rice (5.1 kg·hm^-2), early rice (2.1 kg·hm^-2), late rice (1.0 kg·hm^-2), middle rice (0.6 kg·hm^-2), and rice-crayfish (0.4 kg·hm^-2). As for total emission calculated by global warming potential, the value of rice-crayfish is 13657.7 kg·hm^-2, followed by ratooning rice (8857.0 kg·hm^-2), early rice (5067.3 kg·hm^-2), late rice (3647.0 kg·hm^-2), and middle rice (3053.8 kg·hm^-2). Rice-crayfish is also accompanied by high greenhouse gas emission intensity reaching up to 1.4 kg·kg^-1, followed by early rice (0.79 kg·kg^-1), ratooning rice (0.57 kg·kg^-1), late rice (0.53 kg·kg^-1), and middle rice (0.34 kg·kg^-1). The total emission and intensity of middle rice is significantly smaller than those of rice-crayfish system by 77.6% and 75.7%. It is notable that methane emission accounts for 82.9%-99.0% of total emission among different rice cropping patterns, indicating that controlling methane is key for low-carbon production. Due to water flooding in rice paddy, nitrous oxide emission is small. The high emissions from rice-crayfish paddy are mainly attributed to the long duration of flooding, straw returning and large amount of fodder input, which has led to a long period of soil anaerobic condition, and plenty of carbon substrate for methane production. Thus, it is important to explore methane reduction practices and strategies in rice-crayfish paddy. The emission intensity of middle rice is the lowest due to paddy-upland rotation and can be considered as a low-carbon rice cultivation pattern. A field experiment is conducted in Jianghan Plain using static chamber-gas chromatography method to monitor greenhouse gas emissions from 5 different rice cropping systems:Early rice, late rice, middle rice, rice-crayfish coculture and ratooning rice systems. The emission characteristics of methane and nitrous oxide fluxes, global warming potential and greenhouse gas emission intensity in different rice patterns are analyzed, aiming to provide scientific references for accurate estimates of greenhouse gas emissions from rice paddy. The results show that methane emissions are concentrated in the early flooding stage of rice paddy, with a flux peak of (85.7 mg·m^-2·h^-1) for rice-crayfish system, which is higher than those of other patterns by 71.7%-191.5%. Nitrous oxide emissions are mainly observed during mid-season drainage or after nitrogen fertilization, and the highest flux peak is found for ratooning rice (1100.7 μg·m^-2·h^-1), which is 16.8%-654.9% higher than other patterns. The sequence of accumulated methane emission from largest to smallest is rice-crayfish (541.1 kg·hm^-2), ratooning rice (293.7 kg·hm^-2), early rice (177.2 kg·hm^-2), late rice (133.7 kg·hm^-2), and middle rice (115.3 kg·hm^-2). For nitrous oxide emission, the sequence is ratooning rice (5.1 kg·hm^-2), early rice (2.1 kg·hm^-2), late rice (1.0 kg·hm^-2), middle rice (0.6 kg·hm^-2), and rice-crayfish (0.4 kg·hm^-2). As for total emission calculated by global warming potential, the value of rice-crayfish is 13657.7 kg·hm^-2, followed by ratooning rice (8857.0 kg·hm^-2), early rice (5067.3 kg·hm^-2), late rice (3647.0 kg·hm^-2), and middle rice (3053.8 kg·hm^-2). Rice-crayfish is also accompanied by high greenhouse gas emission intensity reaching up to 1.4 kg·kg^-1, followed by early rice (0.79 kg·kg^-1), ratooning rice (0.57 kg·kg^-1), late rice (0.53 kg·kg^-1), and middle rice (0.34 kg·kg^-1). The total emission and intensity of middle rice is significantly smaller than those of rice-crayfish system by 77.6% and 75.7%. It is notable that methane emission accounts for 82.9%-99.0% of total emission among different rice cropping patterns, indicating that controlling methane is key for low-carbon production. Due to water flooding in rice paddy, nitrous oxide emission is small. The high emissions from rice-crayfish paddy are mainly attributed to the long duration of flooding, straw returning and large amount of fodder input, which has led to a long period of soil anaerobic condition, and plenty of carbon substrate for methane production. Thus, it is important to explore methane reduction practices and strategies in rice-crayfish paddy. The emission intensity of middle rice is the lowest due to paddy-upland rotation and can be considered as a low-carbon rice cultivation pattern.