Volume 52,Issue 2,2024 Table of Contents
2024, 52(2):151-162.
DOI: 10.19517/j.1671-6345.20230146
Abstract:
As the effective supplements to Lband radiosonde, both the Doppler wind lidar and wind profiling radar can provide atmospheric wind field information with high spatial and temporal resolution. However, due to the obvious differences between Doppler wind lidar and wind profiling radar in terms of working principles and applicable conditions, the two wind measuring instruments have their own advantages and disadvantages in detection performance, and the detection data of a single instrument can no longer satisfy the requirements of refined forecasting. In this study, Lband radiosonde data from the Nanjiao observation site in Beijing from January to May 2020 are used to evaluate the observational data quality of the Doppler wind lidar and wind profiling radar at the same site. The results show that the Doppler wind lidar has a high consistency with the Lband radiosonde. The correlation coefficients of U and V components of Doppler wind lidar and Lband radiosonde are 0.97 and 0.98, respectively, and the root mean square errors of U and V components of Doppler wind lidar and Lband radiosonde are 1.1 and 0.95 m·s-1, respectively. However, when the detection height is above 2 km, the data acquisition rate of Doppler wind lidar is low and the deviation is large. Compared to Doppler wind lidar, the consistency between the wind profiling radar and Lband radiosonde is slightly worse. The correlation coefficients of U and V components between the wind profiling radar and Lband radiosonde are 0.94 and 0.93, respectively, and the root mean square errors of U and V components between the wind profiling radar and Lband radiosonde are 2.94 and 2.91 m·s-1, respectively. Compared to Doppler wind lidar, wind profiling radar has a longer detection range but a lower temporal resolution, in addition to a larger measurement bias below 0.5 km and above 6 km. Considering the advantages and disadvantages of the doppler wind lidar and wind profiling radar at different detection heights, the horizontal wind measurements from the two wind measuring instruments are first spliced and fused, and then the segmented surface fitting method is used to correct the outliers and compensate for the missing values of the fused wind profiles. Two cases are selected to validate and analyse the effect of fusion. The results show that the consistency between the wind direction and wind speed of the fused wind profile and the Lband radiosonde is significantly improved compared to the measurements of the individual devices before the fusion process.
As the effective supplements to Lband radiosonde, both the Doppler wind lidar and wind profiling radar can provide atmospheric wind field information with high spatial and temporal resolution. However, due to the obvious differences between Doppler wind lidar and wind profiling radar in terms of working principles and applicable conditions, the two wind measuring instruments have their own advantages and disadvantages in detection performance, and the detection data of a single instrument can no longer satisfy the requirements of refined forecasting. In this study, Lband radiosonde data from the Nanjiao observation site in Beijing from January to May 2020 are used to evaluate the observational data quality of the Doppler wind lidar and wind profiling radar at the same site. The results show that the Doppler wind lidar has a high consistency with the Lband radiosonde. The correlation coefficients of U and V components of Doppler wind lidar and Lband radiosonde are 0.97 and 0.98, respectively, and the root mean square errors of U and V components of Doppler wind lidar and Lband radiosonde are 1.1 and 0.95 m·s-1, respectively. However, when the detection height is above 2 km, the data acquisition rate of Doppler wind lidar is low and the deviation is large. Compared to Doppler wind lidar, the consistency between the wind profiling radar and Lband radiosonde is slightly worse. The correlation coefficients of U and V components between the wind profiling radar and Lband radiosonde are 0.94 and 0.93, respectively, and the root mean square errors of U and V components between the wind profiling radar and Lband radiosonde are 2.94 and 2.91 m·s-1, respectively. Compared to Doppler wind lidar, wind profiling radar has a longer detection range but a lower temporal resolution, in addition to a larger measurement bias below 0.5 km and above 6 km. Considering the advantages and disadvantages of the doppler wind lidar and wind profiling radar at different detection heights, the horizontal wind measurements from the two wind measuring instruments are first spliced and fused, and then the segmented surface fitting method is used to correct the outliers and compensate for the missing values of the fused wind profiles. Two cases are selected to validate and analyse the effect of fusion. The results show that the consistency between the wind direction and wind speed of the fused wind profile and the Lband radiosonde is significantly improved compared to the measurements of the individual devices before the fusion process.
2024, 52(2):163-172.
DOI: 10.19517/j.1671-6345.20230053
Abstract:
The groundbased microwave radiometer is employing passive remote sensing techniques to achieve realtime retrieval of atmospheric temperature, humidity profiles and related parameters. It possesses advantages of high spatiotemporal resolution, unmanned operation, and continuous functionality, gradually emerging as a potent supplementary method for remote sensing of atmospheric temperature, humidity, and cloud liquid water profiles both domestically and internationally. However, the inversion methods of microwave radiometer data rely on local historical radiosonde data and are restricted by factors such as the distribution of radiosonde stations. Consequently, its utilisation in areas lacking radiosonde stations is limited. To investigate the application effectiveness of ERA5 reanalysis data in microwave radiometer data retrieval, two neural networks are trained separately using radiosonde and ERA5 data as training samples. These networks are used to invert the microwave radiometer observation data. Subsequently, utilising radiosonde data as a reference, the correlation coefficient, absolute deviation, and root mean square error of the data inverted based on radiosonde and ERA5 reanalysis data are computed to assess the application effectiveness of ERA5 reanalysis data in microwave radiometer data retrieval. The results are indicating that the temperature profile inversions based on ERA5 and radiosonde data are exhibiting correlation coefficients of 0.988 and 0.99, with absolute deviations of 2.402 ℃ and 2.607 ℃, respectively. The water vapour density inversions are showing correlation coefficients of 0.975 and 0.979, with absolute deviations of 0.412 g/m3 and 0.369 g/m3. The relative humidity inversions are exhibiting correlation coefficients of 0.663 and 0.696, with absolute deviations of 15.587% and 13.976%. Furthermore, the integrated water vapour total inversions are presenting correlation coefficients of 0.959 and 0.968, with absolute deviations of 0.258 cm and 0.227 cm. Comparison of the microwave radiometer inversions based on radiosonde and reanalysis data is revealing closely aligned temperature profiles and integrated water vapour statistics; however, noticeable overestimations are observed in relative humidity. Analysis of error distribution with altitude is indicating relatively minor changes in root mean square errors for both radiosonde and ERA5 data. Temperature and humidity profile errors from both radiosonde and ERA5 retrievaled are performing better at lower altitudes, gradually increasing with altitude. The temperature profile error derived from radiosonde retrievals is notably smaller compared to ERA5based inversions, exhibiting a distinct difference in the variation of relative humidity errors with altitude. This study is currently focusing solely on the application effectiveness of ERA5 data near the Changchun radiosonde station. To comprehensively validate the utility of ERA5 in microwave radiometer data retrieval, further research is essential in other radiosonde stations, including regions devoid of radiosonde data. Future research is necessary to investigate the application and correction methodologies of ERA5 data in microwave radiometer data retrieval in these areas.
The groundbased microwave radiometer is employing passive remote sensing techniques to achieve realtime retrieval of atmospheric temperature, humidity profiles and related parameters. It possesses advantages of high spatiotemporal resolution, unmanned operation, and continuous functionality, gradually emerging as a potent supplementary method for remote sensing of atmospheric temperature, humidity, and cloud liquid water profiles both domestically and internationally. However, the inversion methods of microwave radiometer data rely on local historical radiosonde data and are restricted by factors such as the distribution of radiosonde stations. Consequently, its utilisation in areas lacking radiosonde stations is limited. To investigate the application effectiveness of ERA5 reanalysis data in microwave radiometer data retrieval, two neural networks are trained separately using radiosonde and ERA5 data as training samples. These networks are used to invert the microwave radiometer observation data. Subsequently, utilising radiosonde data as a reference, the correlation coefficient, absolute deviation, and root mean square error of the data inverted based on radiosonde and ERA5 reanalysis data are computed to assess the application effectiveness of ERA5 reanalysis data in microwave radiometer data retrieval. The results are indicating that the temperature profile inversions based on ERA5 and radiosonde data are exhibiting correlation coefficients of 0.988 and 0.99, with absolute deviations of 2.402 ℃ and 2.607 ℃, respectively. The water vapour density inversions are showing correlation coefficients of 0.975 and 0.979, with absolute deviations of 0.412 g/m3 and 0.369 g/m3. The relative humidity inversions are exhibiting correlation coefficients of 0.663 and 0.696, with absolute deviations of 15.587% and 13.976%. Furthermore, the integrated water vapour total inversions are presenting correlation coefficients of 0.959 and 0.968, with absolute deviations of 0.258 cm and 0.227 cm. Comparison of the microwave radiometer inversions based on radiosonde and reanalysis data is revealing closely aligned temperature profiles and integrated water vapour statistics; however, noticeable overestimations are observed in relative humidity. Analysis of error distribution with altitude is indicating relatively minor changes in root mean square errors for both radiosonde and ERA5 data. Temperature and humidity profile errors from both radiosonde and ERA5 retrievaled are performing better at lower altitudes, gradually increasing with altitude. The temperature profile error derived from radiosonde retrievals is notably smaller compared to ERA5based inversions, exhibiting a distinct difference in the variation of relative humidity errors with altitude. This study is currently focusing solely on the application effectiveness of ERA5 data near the Changchun radiosonde station. To comprehensively validate the utility of ERA5 in microwave radiometer data retrieval, further research is essential in other radiosonde stations, including regions devoid of radiosonde data. Future research is necessary to investigate the application and correction methodologies of ERA5 data in microwave radiometer data retrieval in these areas.
2024, 52(2):173-185.
DOI: 10.19517/j.1671-6345.20230261
Abstract:
The Qingpu CINRAD/SAD radar and the Nanhui WSR88D radar, located in Shanghai, are of different models, and different dualpolarisation technology upgrade schemes are adopted, so there is a certain data deviation between the two radars in actual business operation. In order to quantitatively evaluate the detection performance of the radars, analyse the main sources of differences in radar data, and improve the application of the data of the two radars in business forecasting, algorithm research and other aspects, a total of 3933 times of data in 30 processes are selected in the common detection area from July to September 2022 and June 2023. The data set includes typical weather processes such as hail, typhoons, and plum rains. The data are divided into stable precipitation and convective precipitation, and are compared according to intensity classification. We mainly use the data space matching method based on radars at different positions, the horizontal structure of reflectivity (ZH), differential reflectivity (ZDR), correlation coefficient (CC) and differential phase shift (ΦDP) and their variation trend with azimuth, the variation trend of radar sensitivity with elevation and the quantitative statistics of ZH and ZDR deviation for evaluation. The results show that the ZH observations of the two radars are close to each other. The ZDR, CC and ΦDP of the Qingpu CINRAD/SAD radar are more affected by the ground features and lightning rods, and are unstable with the change of azimuth, meanwhile, the nonmeteorological echo filtering effect of the Qingpu CINRAD/SAD radar is worse than that of the Nanhui WSR88D radar in the lower layers. The Nanhui 88D radar utilises azimuth superresolution technology to obtain a more refined echo structure. The Nanhui 88D radar only installs a lightning rod on the top of the radome, which is basically not affected by the lightning rod. The radar parameters are more stable as the azimuth changes. The deviation of ZH and ZDR of the two radars is larger in the area where the ZH is greater than 40 dBz. For stable precipitation of 15-25 dBz, the deviations of the ZH and ZDR of the two radars are small. Through calculation, the average deviation of ZH is 0.9 dB and ZDR is -0.14 dB. Based on the data of typhoon, hail, shortduration heavy precipitation and Meiyu precipitation, we quantitatively evaluate the differences between the two Sband dual polarisation weather radars in Shanghai from different aspects, providing a reference for subsequent algorithm improvements and data correction.
The Qingpu CINRAD/SAD radar and the Nanhui WSR88D radar, located in Shanghai, are of different models, and different dualpolarisation technology upgrade schemes are adopted, so there is a certain data deviation between the two radars in actual business operation. In order to quantitatively evaluate the detection performance of the radars, analyse the main sources of differences in radar data, and improve the application of the data of the two radars in business forecasting, algorithm research and other aspects, a total of 3933 times of data in 30 processes are selected in the common detection area from July to September 2022 and June 2023. The data set includes typical weather processes such as hail, typhoons, and plum rains. The data are divided into stable precipitation and convective precipitation, and are compared according to intensity classification. We mainly use the data space matching method based on radars at different positions, the horizontal structure of reflectivity (ZH), differential reflectivity (ZDR), correlation coefficient (CC) and differential phase shift (ΦDP) and their variation trend with azimuth, the variation trend of radar sensitivity with elevation and the quantitative statistics of ZH and ZDR deviation for evaluation. The results show that the ZH observations of the two radars are close to each other. The ZDR, CC and ΦDP of the Qingpu CINRAD/SAD radar are more affected by the ground features and lightning rods, and are unstable with the change of azimuth, meanwhile, the nonmeteorological echo filtering effect of the Qingpu CINRAD/SAD radar is worse than that of the Nanhui WSR88D radar in the lower layers. The Nanhui 88D radar utilises azimuth superresolution technology to obtain a more refined echo structure. The Nanhui 88D radar only installs a lightning rod on the top of the radome, which is basically not affected by the lightning rod. The radar parameters are more stable as the azimuth changes. The deviation of ZH and ZDR of the two radars is larger in the area where the ZH is greater than 40 dBz. For stable precipitation of 15-25 dBz, the deviations of the ZH and ZDR of the two radars are small. Through calculation, the average deviation of ZH is 0.9 dB and ZDR is -0.14 dB. Based on the data of typhoon, hail, shortduration heavy precipitation and Meiyu precipitation, we quantitatively evaluate the differences between the two Sband dual polarisation weather radars in Shanghai from different aspects, providing a reference for subsequent algorithm improvements and data correction.
2024, 52(2):186-194.
DOI: 10.19517/j.1671-6345.20230062
Abstract:
The China Meteorological Administration Satellite Broadcasting System (CMACast) is one of the three major meteorological data satellite broadcast systems of GEONETCast, responsible for disseminating meteorological data in the Asia Pacific region under the framework of WIS (WMO Information System) and IGDDS (Integrated Satellite Data Dissemination System). Different types of meteorological data are being broadcasted in different channels of CMACast, and channel multiplex the total bandwidth of the system based on parameters such as channel guarantee bandwidth, maximum bandwidth and priority. The data dissemination efficiency of different channels depends on the channel bandwidth allocated by the system. The larger the allocated bandwidth, the higher the data dissemination timeliness. When the amount of data broadcast in the broadcasting system is small, the system bandwidth is sufficient, and the bandwidth obtained by all channels is sufficient to meet the requirements of channel data broadcast timeliness. With the development of meteorological services, the data volume of the broadcasting system has increased from 180 GB/day to 460 GB/day. In the case of limited broadcasting bandwidth resources and varying types and sizes of broadcasting data, the accuracy of channel bandwidth parameters is having an increasing impact on the timeliness of data broadcasting. However, system managers are finding it increasingly difficult to adjust the broadcasting channel parameters to the optimal state through experience to maintain the broadcasting efficiency and timeliness of the broadcasting data. This is causing a serious decrease in the timeliness of data dissemination in some channels, which cannot meet the business timeliness requirements. By quantitatively analysing the transmission characteristics of different meteorological data, refined data transmission samples of various types of data are obtained, and the transmission characteristics of each channel data in the time domain are obtained. Based on this, scientific and quantitative calculations are being carried out for various data broadcast channel parameters according to the time requirements of each channel. Through simulation and iterative optimisation, the optimised parameters such as guaranteed bandwidth and maximum bandwidth of each channel are obtained, which are applied to business systems. This significantly improves the broadcasting efficiency of key data, optimises the overall broadcasting efficiency of the system, and solves the problem of low system broadcasting efficiency and insufficient timeliness caused by inaccurate setting of various channel parameters in the broadcast system. Through the research, a quantitative and accurate calculation and optimisation method is provided for the setting and optimisation of channel parameters in broadcast systems, solving the problem of inaccurate and difficult optimisation of channel parameters in broadcast systems using manual settings. The application is showing significant good results in practical broadcasting services.
The China Meteorological Administration Satellite Broadcasting System (CMACast) is one of the three major meteorological data satellite broadcast systems of GEONETCast, responsible for disseminating meteorological data in the Asia Pacific region under the framework of WIS (WMO Information System) and IGDDS (Integrated Satellite Data Dissemination System). Different types of meteorological data are being broadcasted in different channels of CMACast, and channel multiplex the total bandwidth of the system based on parameters such as channel guarantee bandwidth, maximum bandwidth and priority. The data dissemination efficiency of different channels depends on the channel bandwidth allocated by the system. The larger the allocated bandwidth, the higher the data dissemination timeliness. When the amount of data broadcast in the broadcasting system is small, the system bandwidth is sufficient, and the bandwidth obtained by all channels is sufficient to meet the requirements of channel data broadcast timeliness. With the development of meteorological services, the data volume of the broadcasting system has increased from 180 GB/day to 460 GB/day. In the case of limited broadcasting bandwidth resources and varying types and sizes of broadcasting data, the accuracy of channel bandwidth parameters is having an increasing impact on the timeliness of data broadcasting. However, system managers are finding it increasingly difficult to adjust the broadcasting channel parameters to the optimal state through experience to maintain the broadcasting efficiency and timeliness of the broadcasting data. This is causing a serious decrease in the timeliness of data dissemination in some channels, which cannot meet the business timeliness requirements. By quantitatively analysing the transmission characteristics of different meteorological data, refined data transmission samples of various types of data are obtained, and the transmission characteristics of each channel data in the time domain are obtained. Based on this, scientific and quantitative calculations are being carried out for various data broadcast channel parameters according to the time requirements of each channel. Through simulation and iterative optimisation, the optimised parameters such as guaranteed bandwidth and maximum bandwidth of each channel are obtained, which are applied to business systems. This significantly improves the broadcasting efficiency of key data, optimises the overall broadcasting efficiency of the system, and solves the problem of low system broadcasting efficiency and insufficient timeliness caused by inaccurate setting of various channel parameters in the broadcast system. Through the research, a quantitative and accurate calculation and optimisation method is provided for the setting and optimisation of channel parameters in broadcast systems, solving the problem of inaccurate and difficult optimisation of channel parameters in broadcast systems using manual settings. The application is showing significant good results in practical broadcasting services.
2024, 52(2):195-204.
DOI: 10.19517/j.1671-6345.20230093
Abstract:
The current service recipients of the Xinjiang Meteorological Big Data Cloud Platform are mostly based on numerical forecasting models and multisource fusion analysis of meteorological intranet business systems. The integration with the mobile internet is not high, and most of the frontline observation data are directly extracted and processed without being visually displayed through media. The basic stations also lack the means to access the operational status of automatic stations and local refined forecasting and warning on mobile devices. Therefore, to enhance the quality of meteorological services and meet the mobile visualisation needs for meteorological disaster prevention and reduction, as well as to improve the monitoring and warning capabilities of small and mediumscale weather disasters at the basic level in Xinjiang, there is urgency to develop a professional meteorological service APP. The Tian Shan Weather APP breaks through the heterogeneous barriers between the Xinjiang meteorological intranet and the mobile internet at the network level, fully utilises the existing digital achievements of meteorological business in the “cloud + end” business model. It processes and displays meteorological data such as ground observations from automatic weather stations, gridbased actual conditions, radar echoes, and disaster warnings. The key technologies are as follows: using multisource data processing and storage technology to process and reprocess raw data and standardised storage products; using service interfaces that inherit the technical characteristics of the largescale data cloud platform and achieve millisecondlevel data calls; using the SSM development framework based on inversion of control to separate APP transaction management from main business logic; using a data interaction mode based on the Restful architecture style for crossplatform development. At present, the Tian Shan Weather APP can provide realtime weather conditions, refined forecasts, warning details, and radar mosaics based on the user’s location in Xinjiang according to the user’s needs. It can also customise the calculation and analysis products of ground actual condition elements and statistical value elements for meteorological research purposes. Through simulated testing of the data cloud platform service interface and the original CIMISS system interface, it is found that under 100 concurrent accesses, the data cloud platform interface is 5.7 times faster than the original CIMISS interface, and under 200 concurrent accesses, it is 5.3 times faster. This shows that the APP inherits the high carrying capacity of the data cloud platform service interface. The APP is being widely promoted and used by meteorological departments at the provincial, municipal, and county levels, as well as in related industries such as civil aviation and the air force in Xinjiang. It has been widely recognized and has achieved significant results in the emergency support of weather automatic stations and meteorological disaster prevention and reduction services throughout Xinjiang.
The current service recipients of the Xinjiang Meteorological Big Data Cloud Platform are mostly based on numerical forecasting models and multisource fusion analysis of meteorological intranet business systems. The integration with the mobile internet is not high, and most of the frontline observation data are directly extracted and processed without being visually displayed through media. The basic stations also lack the means to access the operational status of automatic stations and local refined forecasting and warning on mobile devices. Therefore, to enhance the quality of meteorological services and meet the mobile visualisation needs for meteorological disaster prevention and reduction, as well as to improve the monitoring and warning capabilities of small and mediumscale weather disasters at the basic level in Xinjiang, there is urgency to develop a professional meteorological service APP. The Tian Shan Weather APP breaks through the heterogeneous barriers between the Xinjiang meteorological intranet and the mobile internet at the network level, fully utilises the existing digital achievements of meteorological business in the “cloud + end” business model. It processes and displays meteorological data such as ground observations from automatic weather stations, gridbased actual conditions, radar echoes, and disaster warnings. The key technologies are as follows: using multisource data processing and storage technology to process and reprocess raw data and standardised storage products; using service interfaces that inherit the technical characteristics of the largescale data cloud platform and achieve millisecondlevel data calls; using the SSM development framework based on inversion of control to separate APP transaction management from main business logic; using a data interaction mode based on the Restful architecture style for crossplatform development. At present, the Tian Shan Weather APP can provide realtime weather conditions, refined forecasts, warning details, and radar mosaics based on the user’s location in Xinjiang according to the user’s needs. It can also customise the calculation and analysis products of ground actual condition elements and statistical value elements for meteorological research purposes. Through simulated testing of the data cloud platform service interface and the original CIMISS system interface, it is found that under 100 concurrent accesses, the data cloud platform interface is 5.7 times faster than the original CIMISS interface, and under 200 concurrent accesses, it is 5.3 times faster. This shows that the APP inherits the high carrying capacity of the data cloud platform service interface. The APP is being widely promoted and used by meteorological departments at the provincial, municipal, and county levels, as well as in related industries such as civil aviation and the air force in Xinjiang. It has been widely recognized and has achieved significant results in the emergency support of weather automatic stations and meteorological disaster prevention and reduction services throughout Xinjiang.
2024, 52(2):205-217.
DOI: 10.19517/j.1671-6345.20230100
Abstract:
In order to gain a deep understanding of the spread characteristics of two wildfires that occur simultaneously, as well as the impact of atmosphere, terrain, and other factors on different wildfire behaviours, and to provide scientific support for extinguishing multiple wildfires. Two wildfires that occurred in Fuling on August 17, 2022 are selected to analyse and study the behaviour of the two wildfires using highresolution geographic information, vegetation data, and meteorological observations. At the same time, numerical simulation is conducted using the wildfireatmosphere coupled WRFFire model (Weather Research and Forecasting Model with Fire Module). The research results are found as follows. (1) Under the control of deep and high pressure, the two wildfires break out under the background of continuous high temperature and dryness. Ten days before the wildfire, the daily average temperature is 5.2-8.8 ℃ higher than the same period as usual, the daily maximum temperature is 6.2-8.4 ℃ higher than the same period as usual, and the daily average relative humidity is 26.3% lower than the same period as usual. The drought meteorological level reaches severe drought, and the fire risk meteorological level is high or extremely high. (2) The test results show that the simulated wind direction and wind speed changes of the model are relatively consistent with the actual situation, basically reflecting the sudden changes in wind direction and wind speed of the fire site, indicating that the WRFFire can accurately reproduce the spread of multiple real fire sites at the same time. (3) The analysis of temporal and spatial changes in wildfires spread characteristics indicates that the wildfire development in Daliangshan can be divided into 6 stages during this simulation phase, and the wildfire in Beishanping can be divided into 4 stages. The main reason for the difference in the spread and development of the two fires with a linear distance of 4.4 km is the difference in local wind fields caused by differences in terrain. There is a southwestnortheast trumpetshaped terrain on the south side of the Daliangshan fire site. After passing through this terrain, southerly winds form a significant convergence on the northeast side. Therefore, during the northward spread and development of the fire site, the fire on the east side is greater than that on the west side. The terrain on the west side of the Beishanping fire site is higher than that on the east side. As the southerly wind advances northward, it forms convergence in front of the mountain. Therefore, during some periods, the fire is stronger on the west side of the fire site in front of the mountain.
In order to gain a deep understanding of the spread characteristics of two wildfires that occur simultaneously, as well as the impact of atmosphere, terrain, and other factors on different wildfire behaviours, and to provide scientific support for extinguishing multiple wildfires. Two wildfires that occurred in Fuling on August 17, 2022 are selected to analyse and study the behaviour of the two wildfires using highresolution geographic information, vegetation data, and meteorological observations. At the same time, numerical simulation is conducted using the wildfireatmosphere coupled WRFFire model (Weather Research and Forecasting Model with Fire Module). The research results are found as follows. (1) Under the control of deep and high pressure, the two wildfires break out under the background of continuous high temperature and dryness. Ten days before the wildfire, the daily average temperature is 5.2-8.8 ℃ higher than the same period as usual, the daily maximum temperature is 6.2-8.4 ℃ higher than the same period as usual, and the daily average relative humidity is 26.3% lower than the same period as usual. The drought meteorological level reaches severe drought, and the fire risk meteorological level is high or extremely high. (2) The test results show that the simulated wind direction and wind speed changes of the model are relatively consistent with the actual situation, basically reflecting the sudden changes in wind direction and wind speed of the fire site, indicating that the WRFFire can accurately reproduce the spread of multiple real fire sites at the same time. (3) The analysis of temporal and spatial changes in wildfires spread characteristics indicates that the wildfire development in Daliangshan can be divided into 6 stages during this simulation phase, and the wildfire in Beishanping can be divided into 4 stages. The main reason for the difference in the spread and development of the two fires with a linear distance of 4.4 km is the difference in local wind fields caused by differences in terrain. There is a southwestnortheast trumpetshaped terrain on the south side of the Daliangshan fire site. After passing through this terrain, southerly winds form a significant convergence on the northeast side. Therefore, during the northward spread and development of the fire site, the fire on the east side is greater than that on the west side. The terrain on the west side of the Beishanping fire site is higher than that on the east side. As the southerly wind advances northward, it forms convergence in front of the mountain. Therefore, during some periods, the fire is stronger on the west side of the fire site in front of the mountain.
2024, 52(2):218-227.
DOI: 10.19517/j.1671-6345.20230114
Abstract:
The Method for ObjectBased Diagnostic Evaluation (MODE) has been widely applied in spatial evaluation in recent years. MODE is affected by many parameters such as precipitation critical value, convolution radius and attribute weight; the application effect of MODE depends on reasonable selection of convolution radius and accurate characterisation of spatial similarity between forecast and observation fields. Taking the CMPA as observation, MODE and FSS (Fractions Skill Score) are used to test the CMAGD 24 h daily precipitation forecast based on 54 precipitation cases in Guizhou in this paper. The number of objects extracted by MODE falls with convolution radius; too small convolution radius easily results in too many precipitation objects extracted; if the convolution radius is too large, local precipitation information will be lost and precipitation objects cannot be extracted from the precipitation field. Therefore, an appropriate convolution radius should be adopted to extract precipitation objects with MODE. It is found that the MMI (the Median Maximum Interest Value) of MODE is very sensitive to the convolution radius change and even has a mutation, so it cannot stably represent the overall spatial similarity of precipitation fields. Based on the MMI, the area weight is introduced to construct the AMMI (the Area Mean of Maximum Interest Value) to distinguish the contribution of different objects. The AMMI is more reasonable to characterise the overall similarity of the forecast and observation precipitation fields, and is unaffected by the number of precipitation objects, which is more stable than the MMI. In general, AMMI is larger than FSS, and the difference in the change of AMMI and FSS with spatial scale is due to the different calculation basis. According to the change of object’s total area with the convolution radius, precipitation can be divided into largearea precipitation and local precipitation. The average total area of largescale precipitation grows with the convolution radius, while AMMI has little change. As the convolution radius goes up, the average total area and AMMI of local precipitation go down. Taking the maximum convolution radius which makes the total area change not exceeding 10% in the observation field as the critical radius, there is a large difference between the probability of the critical radius of largescale precipitation and local precipitation from 0.05° to 0.4°. Local precipitation is sensitive to the selection of convolution radius and determining the convolution radius with critical radius is helpful to retain most of the information of the precipitation field.
The Method for ObjectBased Diagnostic Evaluation (MODE) has been widely applied in spatial evaluation in recent years. MODE is affected by many parameters such as precipitation critical value, convolution radius and attribute weight; the application effect of MODE depends on reasonable selection of convolution radius and accurate characterisation of spatial similarity between forecast and observation fields. Taking the CMPA as observation, MODE and FSS (Fractions Skill Score) are used to test the CMAGD 24 h daily precipitation forecast based on 54 precipitation cases in Guizhou in this paper. The number of objects extracted by MODE falls with convolution radius; too small convolution radius easily results in too many precipitation objects extracted; if the convolution radius is too large, local precipitation information will be lost and precipitation objects cannot be extracted from the precipitation field. Therefore, an appropriate convolution radius should be adopted to extract precipitation objects with MODE. It is found that the MMI (the Median Maximum Interest Value) of MODE is very sensitive to the convolution radius change and even has a mutation, so it cannot stably represent the overall spatial similarity of precipitation fields. Based on the MMI, the area weight is introduced to construct the AMMI (the Area Mean of Maximum Interest Value) to distinguish the contribution of different objects. The AMMI is more reasonable to characterise the overall similarity of the forecast and observation precipitation fields, and is unaffected by the number of precipitation objects, which is more stable than the MMI. In general, AMMI is larger than FSS, and the difference in the change of AMMI and FSS with spatial scale is due to the different calculation basis. According to the change of object’s total area with the convolution radius, precipitation can be divided into largearea precipitation and local precipitation. The average total area of largescale precipitation grows with the convolution radius, while AMMI has little change. As the convolution radius goes up, the average total area and AMMI of local precipitation go down. Taking the maximum convolution radius which makes the total area change not exceeding 10% in the observation field as the critical radius, there is a large difference between the probability of the critical radius of largescale precipitation and local precipitation from 0.05° to 0.4°. Local precipitation is sensitive to the selection of convolution radius and determining the convolution radius with critical radius is helpful to retain most of the information of the precipitation field.
8 Comparative Analysis of Regional Freezing Rain Events with Different Intensities in Guizhou Province
2024, 52(2):228-242.
DOI: 10.19517/j.1671-6345.20230005
Abstract:
Using the percentile method, the regional freezing process intensity is divided into four levels: extremely strong, strong, general strong, and general. Based on the daily observation data from 84 stations in Guizhou Province and reanalysis data, the cooling amplitude, number of affected stations, duration, altitude field, wind field, and temperature field are being analysed in a comparative way on 12 regional freezing Processes which are selected from four different intensities. The conclusions are as follows. The common features of the four freezing events with different intensities are: in the height field at 500 hPa, a distribution of “positivenegative” anomalies or a cutoff low is being exhibited over the East Asia region in the middle and high latitudes, with meridional circulation dominating from Lake Baikal to northern China; in the wind field at 850 hPa, the southern part of Yunnan Province is being controlled by southerly and southwestern winds, and there is a southwestern or westerly jet stream from Jiangnan to southern China. For the regional freezing rain events with strong intensity, a “two trough and one ridge” or “one trough and one ridge” distribution in the height field at 500 hPa is shown over the middle and high latitude regions. In the wind field at 850 hPa, there is a pattern of warm air advection aloft and cold air advection near the surface, with northeasterly winds return at 850 hPa and a southwestern jet stream at 700 hPa, while a stable lowlevel shear line is formed at 850 hPa. In the temperature field, a sandwich structure of coldwarmcold is observed, with the 0 ℃ isotherm below 900 hPa in the nearsurface layer. However, for the regional freezing rain events with moderate intensity, multiple troughs and ridges are distributed at 500 hPa. There are no common features for the northeasterly winds advection and lowlevel shear line in the wind field, as well as the coldwarmcold sandwich structure and the position of the nearsurface 0 ℃ isotherm in the temperature field. On the temperature profile, the period with the lowest position of the nearsurface 0 ℃ isotherm or the occurrence of the coldwarmcold sandwich structure corresponds to the time when the freezing rain events have the extensive impact and result in the most severe disaster. In the prediction of the freezing process, predict experiments can be conducted based on the position of the 0 ℃ line near the ground level and the strength of the temperature inversion layer.
Using the percentile method, the regional freezing process intensity is divided into four levels: extremely strong, strong, general strong, and general. Based on the daily observation data from 84 stations in Guizhou Province and reanalysis data, the cooling amplitude, number of affected stations, duration, altitude field, wind field, and temperature field are being analysed in a comparative way on 12 regional freezing Processes which are selected from four different intensities. The conclusions are as follows. The common features of the four freezing events with different intensities are: in the height field at 500 hPa, a distribution of “positivenegative” anomalies or a cutoff low is being exhibited over the East Asia region in the middle and high latitudes, with meridional circulation dominating from Lake Baikal to northern China; in the wind field at 850 hPa, the southern part of Yunnan Province is being controlled by southerly and southwestern winds, and there is a southwestern or westerly jet stream from Jiangnan to southern China. For the regional freezing rain events with strong intensity, a “two trough and one ridge” or “one trough and one ridge” distribution in the height field at 500 hPa is shown over the middle and high latitude regions. In the wind field at 850 hPa, there is a pattern of warm air advection aloft and cold air advection near the surface, with northeasterly winds return at 850 hPa and a southwestern jet stream at 700 hPa, while a stable lowlevel shear line is formed at 850 hPa. In the temperature field, a sandwich structure of coldwarmcold is observed, with the 0 ℃ isotherm below 900 hPa in the nearsurface layer. However, for the regional freezing rain events with moderate intensity, multiple troughs and ridges are distributed at 500 hPa. There are no common features for the northeasterly winds advection and lowlevel shear line in the wind field, as well as the coldwarmcold sandwich structure and the position of the nearsurface 0 ℃ isotherm in the temperature field. On the temperature profile, the period with the lowest position of the nearsurface 0 ℃ isotherm or the occurrence of the coldwarmcold sandwich structure corresponds to the time when the freezing rain events have the extensive impact and result in the most severe disaster. In the prediction of the freezing process, predict experiments can be conducted based on the position of the 0 ℃ line near the ground level and the strength of the temperature inversion layer.
9 Characteristics and Model Error Analysis of Persistent Extreme Heat of Sichuan Basin in August 2022
2024, 52(2):243-251.
DOI: 10.19517/j.1671-6345.20230155
Abstract:
Based on the hourly 2 m temperature and precipitation data of 104 stations in the Sichuan Basin in August 2022 and the historical data of the same period from 1971 to 2021, and the 2 m temperature forecast data of the EC, CMAGFS, and CMAMESO models, the temporal and spatial distribution characteristics and mode prediction deviation of this extreme heat weather process are analysed by statistical correlation method. The results show that: (1) In August 2022, the extreme heat weather process in the Sichuan Basin has a wide range, strong intensity, and long duration. There are 87.5% of stations in the basin that have broken the extreme value in the same period, and the peak period of the high temperature is obviously delayed compared with the same period in history. (2) The distribution of the maximum temperature in August 2022 is higher in the east and lower in the west, and the distribution of the difference between the maximum temperature and the extreme value in the same period is opposite, in which the maximum temperature decreases with the increase of the altitude of the station, while the extreme value difference first increases and then decreases with the altitude of the station. In addition, affected by the heat island effect, the stations with large extreme difference are mainly concentrated near the Longquan Mountain range. (3) During the high temperature period, the average temperature of the maximum and minimum are high, and the anomaly is large. In addition, the cumulative precipitation and rainy days are also far lower than the historical period. (4) In comparison, the prediction advantage of the EC model is mainly in the low elevation area of the basin, while the average absolute error of the CMAMESO model is smaller in the steep terrain area around the basin. In addition, the EC model predicts the peak temperature time closer to the reality, while the CMAMESO model predicts the number of hot days closer to the reality.
Based on the hourly 2 m temperature and precipitation data of 104 stations in the Sichuan Basin in August 2022 and the historical data of the same period from 1971 to 2021, and the 2 m temperature forecast data of the EC, CMAGFS, and CMAMESO models, the temporal and spatial distribution characteristics and mode prediction deviation of this extreme heat weather process are analysed by statistical correlation method. The results show that: (1) In August 2022, the extreme heat weather process in the Sichuan Basin has a wide range, strong intensity, and long duration. There are 87.5% of stations in the basin that have broken the extreme value in the same period, and the peak period of the high temperature is obviously delayed compared with the same period in history. (2) The distribution of the maximum temperature in August 2022 is higher in the east and lower in the west, and the distribution of the difference between the maximum temperature and the extreme value in the same period is opposite, in which the maximum temperature decreases with the increase of the altitude of the station, while the extreme value difference first increases and then decreases with the altitude of the station. In addition, affected by the heat island effect, the stations with large extreme difference are mainly concentrated near the Longquan Mountain range. (3) During the high temperature period, the average temperature of the maximum and minimum are high, and the anomaly is large. In addition, the cumulative precipitation and rainy days are also far lower than the historical period. (4) In comparison, the prediction advantage of the EC model is mainly in the low elevation area of the basin, while the average absolute error of the CMAMESO model is smaller in the steep terrain area around the basin. In addition, the EC model predicts the peak temperature time closer to the reality, while the CMAMESO model predicts the number of hot days closer to the reality.
2024, 52(2):252-264.
DOI: 10.19517/j.1671-6345.20230037
Abstract:
Based on the data of CFL03 atmospheric boundary layer wind profiler radar and the automatic weather observation data of Guiyang Airport from January 2019 to June 2022, this paper verifies the availability of WPR data and analyses horizontal wind field, vertical wind speed, echo intensity, atmospheric refractive index structure constant and other physical quantities in detail according to the typical snowfall and freezing rain process; at the same time, the differences of WPR data between different intensity snowfalls and freezing rains are compared. Finally, the WPR data of snowfall and freezing rain in recent three years are statistically analysed. The results show that: (1) The horizontal wind field of WPR reflects that the thickness and intensity of cold air during snowfall exceed that freezing rain, the middle and lower layers are controlled by cold advection during snowfall, while they are warm advection during freezing rain. (2) The greater the central value of C2n, the higher the upward development height of the large value area, and the stronger the snowfall intensity; and the increase/decrease of highlevel C2n is ahead of the increase/decrease of snowfall, which can reflect the intensity change of snowfall. (3) The radar reflectivity of snowfall leans to the left in the vertical direction, so the change of radar reflectivity in highlevel layers is an indicative of the change of snowfall intensity, the radar reflectivity of freezing rain presents a “strongweakstrong” distribution in the vertical direction, which is consistent with the “coldwarmcold” stratification distribution of temperature field in the vertical direction. (4) In freezing rain, the falling speed of particles is slower than that of snowfall, and the precipitation particles almost only fall in the cold air area below 1500 m with the speed of 0.2 to 1.0 m/s; while in sleet, the falling speed is faster than that of pure snow, and the falling speed of light snow is the slowest.
Based on the data of CFL03 atmospheric boundary layer wind profiler radar and the automatic weather observation data of Guiyang Airport from January 2019 to June 2022, this paper verifies the availability of WPR data and analyses horizontal wind field, vertical wind speed, echo intensity, atmospheric refractive index structure constant and other physical quantities in detail according to the typical snowfall and freezing rain process; at the same time, the differences of WPR data between different intensity snowfalls and freezing rains are compared. Finally, the WPR data of snowfall and freezing rain in recent three years are statistically analysed. The results show that: (1) The horizontal wind field of WPR reflects that the thickness and intensity of cold air during snowfall exceed that freezing rain, the middle and lower layers are controlled by cold advection during snowfall, while they are warm advection during freezing rain. (2) The greater the central value of C2n, the higher the upward development height of the large value area, and the stronger the snowfall intensity; and the increase/decrease of highlevel C2n is ahead of the increase/decrease of snowfall, which can reflect the intensity change of snowfall. (3) The radar reflectivity of snowfall leans to the left in the vertical direction, so the change of radar reflectivity in highlevel layers is an indicative of the change of snowfall intensity, the radar reflectivity of freezing rain presents a “strongweakstrong” distribution in the vertical direction, which is consistent with the “coldwarmcold” stratification distribution of temperature field in the vertical direction. (4) In freezing rain, the falling speed of particles is slower than that of snowfall, and the precipitation particles almost only fall in the cold air area below 1500 m with the speed of 0.2 to 1.0 m/s; while in sleet, the falling speed is faster than that of pure snow, and the falling speed of light snow is the slowest.
2024, 52(2):265-276.
DOI: 10.19517/j.1671-6345.20230225
Abstract:
In recent years, the problem of urban waterlogging is becoming increasingly serious, and urban waterlogging risk assessment is becoming one of the hotspots and challenges in urban waterlogging disaster research. This article takes the main urban area of Chengdu as an example. Meteorological data, geographic information data, socioeconomic statistical data, and waterlogging disaster information are used. The optimal function for estimating precipitation during the return period is selected by comparing multiple commonly used distribution functions. The hourly rainfall pattern in the study area is calculated with the Pilgrim & Cordery method. Then, an improved FloodArea waterlogging model is developed to simulate waterlogging scenarios with a 24hour rainfall period of 20, 30, 50, and 100 years. Based on the revised risk level standards for waterlogging highways and the revised loss curves for property, the levels of waterlogging traffic risk and the risk of indoor property loss for residents are discussed under the 100year return period precipitation scenario. The results show that: (1) The GEV (Generalized Extreme Value) distribution function is the optimal function for estimating precipitation at the return period in the main urban area of Chengdu. The 24hour hourly rainfall pattern in the main urban area of Chengdu presents a bimodal pattern, and the peak appears at the front of the precipitation process. (2) Based on the FloodArea model, the spatial distribution of urban waterlogging can be well simulated by improving the input data or parameters. The simulation results of various precipitation scenarios show that the proportion of waterlogging inundation areas in Gaoxin South Zone, Gaoxin West Zone, and Qingyang District is higher than in other areas. (3) The 24hour 100year rainfall scenario of waterlogging can cause 86.1% of the road length in the main urban area of Chengdu to be difficult to travel. Among them, the length of first level risk roads accounts for 10.5%, and the length of second and third level risk roads accounts for 27.5% and 28.4% respectively, with the highest risk of waterlogging roads in Chenghua District. (4) The potential loss of indoor property caused by waterlogging during a 24hour 100year rainfall scenario accounts for approximately 0.8% of the GDP (Gross Domestic Product) of the main urban area. Wuhou District has the highest risk of property loss, with potential losses accounting for 1.6% of its GDP. The evaluation results can provide support for the prevention and reduction of waterlogging disasters in Chengdu, and the established methods can provide technical reference for urban waterlogging risk assessment.
In recent years, the problem of urban waterlogging is becoming increasingly serious, and urban waterlogging risk assessment is becoming one of the hotspots and challenges in urban waterlogging disaster research. This article takes the main urban area of Chengdu as an example. Meteorological data, geographic information data, socioeconomic statistical data, and waterlogging disaster information are used. The optimal function for estimating precipitation during the return period is selected by comparing multiple commonly used distribution functions. The hourly rainfall pattern in the study area is calculated with the Pilgrim & Cordery method. Then, an improved FloodArea waterlogging model is developed to simulate waterlogging scenarios with a 24hour rainfall period of 20, 30, 50, and 100 years. Based on the revised risk level standards for waterlogging highways and the revised loss curves for property, the levels of waterlogging traffic risk and the risk of indoor property loss for residents are discussed under the 100year return period precipitation scenario. The results show that: (1) The GEV (Generalized Extreme Value) distribution function is the optimal function for estimating precipitation at the return period in the main urban area of Chengdu. The 24hour hourly rainfall pattern in the main urban area of Chengdu presents a bimodal pattern, and the peak appears at the front of the precipitation process. (2) Based on the FloodArea model, the spatial distribution of urban waterlogging can be well simulated by improving the input data or parameters. The simulation results of various precipitation scenarios show that the proportion of waterlogging inundation areas in Gaoxin South Zone, Gaoxin West Zone, and Qingyang District is higher than in other areas. (3) The 24hour 100year rainfall scenario of waterlogging can cause 86.1% of the road length in the main urban area of Chengdu to be difficult to travel. Among them, the length of first level risk roads accounts for 10.5%, and the length of second and third level risk roads accounts for 27.5% and 28.4% respectively, with the highest risk of waterlogging roads in Chenghua District. (4) The potential loss of indoor property caused by waterlogging during a 24hour 100year rainfall scenario accounts for approximately 0.8% of the GDP (Gross Domestic Product) of the main urban area. Wuhou District has the highest risk of property loss, with potential losses accounting for 1.6% of its GDP. The evaluation results can provide support for the prevention and reduction of waterlogging disasters in Chengdu, and the established methods can provide technical reference for urban waterlogging risk assessment.
2024, 52(2):277-287.
DOI: 10.19517/j.1671-6345.20230103
Abstract:
By using the electric rainproof shed at Gucheng Station in Hebei Province, which is located in the littlerainfall and arid regions of the main winter wheat production region of North China, natural precipitation is covered and irrigation is artificially controlled to form soil waterlogging, high humidity, drought, and control. The grain filling process, aboveground biomass, and yield components of winter wheat are measured after flowering. The stress effects of soil waterlogging on the grain filling rate and yield of winter wheat are analysed without the influence of rain and lowtemperature stress. The results show that the grain filling rate of winter wheat decreases and the duration of grain filling days shortens with the decrease of soil water; drought and waterlogging stress affect the dry matter distribution among organs and the sourcesink matching relationship of grain filling in winter wheat. With the decrease of soil water content, the dry matter distribution in the ear decreases, and the stem and leaf weight increases, that is, the biological yield (straw) increases, and the economic yield (grain) decreases. Under the condition of sufficient soil water, the photosynthetic efficiency of green organs such as leaves is high, the transport of photosynthetic products is dominant, and the dry matter of preanthesis vegetative organs has a small contribution rate to the formation and transport of grains; drought stress significantly weakens the photosynthetic capacity of leaves, reduces photosynthetic products and reduces dry matter transport, but the contribution rate of dry matter storage in preanthesis vegetative organs increases. Drought stress affects photosynthesis, grain filling, dry matter accumulation, transport, and distribution of winter wheat plants; during the grain filling period, high soil moisture has a yieldincreasing effect, with a theoretical yield increase of 5.87%. Soil waterlogging shows a decrease in yield, with a theoretical yield decrease of 1.50%; the harvest indices of high humidity and waterlogging are slightly higher than the control 0.5226. Under drought stress, the harvest index significantly decreases, with moderate drought and severe drought being which is 0.1130 to 0.1633 lower than the control. The results show that irrigation in the northern arid region can relieve the stress of climate drought on crop water demand, and when the good weather is full of sunshine, and the daily temperature range is large, the warm and hot conditions are more suitable, and the crop yield and quality are improved. Soil moisture is the key limiting factor affecting the potential of light and temperature production and the increase of yield per unit area of winter wheat in the northern region. The results of this study have certain reference significance for coping with the impact of extreme precipitation events caused by climate change on agricultural production, especially for scientific assessment of the impact of drought and flood disasters on crops in northern arid regions.
By using the electric rainproof shed at Gucheng Station in Hebei Province, which is located in the littlerainfall and arid regions of the main winter wheat production region of North China, natural precipitation is covered and irrigation is artificially controlled to form soil waterlogging, high humidity, drought, and control. The grain filling process, aboveground biomass, and yield components of winter wheat are measured after flowering. The stress effects of soil waterlogging on the grain filling rate and yield of winter wheat are analysed without the influence of rain and lowtemperature stress. The results show that the grain filling rate of winter wheat decreases and the duration of grain filling days shortens with the decrease of soil water; drought and waterlogging stress affect the dry matter distribution among organs and the sourcesink matching relationship of grain filling in winter wheat. With the decrease of soil water content, the dry matter distribution in the ear decreases, and the stem and leaf weight increases, that is, the biological yield (straw) increases, and the economic yield (grain) decreases. Under the condition of sufficient soil water, the photosynthetic efficiency of green organs such as leaves is high, the transport of photosynthetic products is dominant, and the dry matter of preanthesis vegetative organs has a small contribution rate to the formation and transport of grains; drought stress significantly weakens the photosynthetic capacity of leaves, reduces photosynthetic products and reduces dry matter transport, but the contribution rate of dry matter storage in preanthesis vegetative organs increases. Drought stress affects photosynthesis, grain filling, dry matter accumulation, transport, and distribution of winter wheat plants; during the grain filling period, high soil moisture has a yieldincreasing effect, with a theoretical yield increase of 5.87%. Soil waterlogging shows a decrease in yield, with a theoretical yield decrease of 1.50%; the harvest indices of high humidity and waterlogging are slightly higher than the control 0.5226. Under drought stress, the harvest index significantly decreases, with moderate drought and severe drought being which is 0.1130 to 0.1633 lower than the control. The results show that irrigation in the northern arid region can relieve the stress of climate drought on crop water demand, and when the good weather is full of sunshine, and the daily temperature range is large, the warm and hot conditions are more suitable, and the crop yield and quality are improved. Soil moisture is the key limiting factor affecting the potential of light and temperature production and the increase of yield per unit area of winter wheat in the northern region. The results of this study have certain reference significance for coping with the impact of extreme precipitation events caused by climate change on agricultural production, especially for scientific assessment of the impact of drought and flood disasters on crops in northern arid regions.
2024, 52(2):288-296.
DOI: 10.19517/j.1671-6345.20230027
Abstract:
Hightemperature heat damage is one of the main meteorological disasters in the Yangtze River Basin, and scientific assessment of heat damage risk is the basis for disaster prevention and reduction. This study is utilising meteorological observation data from the past 60 years to analyse the spatiotemporal distribution characteristics of hightemperature heat damage in Hubei. Based on the basic theory of natural disaster risk, a hightemperature heat damage risk assessment model is established, which includes factors such as the heat damage intensity that affects the critical period of rice seed setting rate, the actual exposure of the disaster bearing body during the disaster occurrence, and the vulnerability of the disaster. Risk analysis and zoning are conducted. The results show that the period with a high probability of hightemperature weather occurrence is late July, with the 6th pentad in July being the highest. From the perspective of the hightemperature heat damage risk index, the heat damage risk of rice heading and flowering in the third pentad of July is the highest, and thereafter, the heat damage risk decreases over time. The current heading and flowering period of one season mid season rice in Hubei is at a highrisk period, and delaying it for 5 days can reduce its heat damage risk index by about 20%; delaying for more than 15 days reduces the heat hazard risk index by more than 50%. The southeastern and northwestern regions of Hubei are highrisk areas for hightemperature heat damage. For the southeastern region of Hubei, it is recommended to postpone the sowing period by about 15 days or choose more heatresistant varietals to reduce the impact of hightemperature heat damage. Heat resistant varieties should be selected in the northwest of Hubei to reduce the risk of hightemperature and heat damage, and it is not advisable to postpone the sowing date to avoid the impact of autumn rain in western China on the rice harvest period. Due to the inferior water resource conditions compared to the Jianghan Plain in northern Hubei, and the frequent occurrence of hightemperatures accompanied by drought, it is recommended to choose heatresistant varieties and moderately control the rice planting area in the northern Hubei rice region. Regenerated rice should try to choose some heatresistant varieties and strengthen farmland management to cope with hightemperature and heat damage.
Hightemperature heat damage is one of the main meteorological disasters in the Yangtze River Basin, and scientific assessment of heat damage risk is the basis for disaster prevention and reduction. This study is utilising meteorological observation data from the past 60 years to analyse the spatiotemporal distribution characteristics of hightemperature heat damage in Hubei. Based on the basic theory of natural disaster risk, a hightemperature heat damage risk assessment model is established, which includes factors such as the heat damage intensity that affects the critical period of rice seed setting rate, the actual exposure of the disaster bearing body during the disaster occurrence, and the vulnerability of the disaster. Risk analysis and zoning are conducted. The results show that the period with a high probability of hightemperature weather occurrence is late July, with the 6th pentad in July being the highest. From the perspective of the hightemperature heat damage risk index, the heat damage risk of rice heading and flowering in the third pentad of July is the highest, and thereafter, the heat damage risk decreases over time. The current heading and flowering period of one season mid season rice in Hubei is at a highrisk period, and delaying it for 5 days can reduce its heat damage risk index by about 20%; delaying for more than 15 days reduces the heat hazard risk index by more than 50%. The southeastern and northwestern regions of Hubei are highrisk areas for hightemperature heat damage. For the southeastern region of Hubei, it is recommended to postpone the sowing period by about 15 days or choose more heatresistant varietals to reduce the impact of hightemperature heat damage. Heat resistant varieties should be selected in the northwest of Hubei to reduce the risk of hightemperature and heat damage, and it is not advisable to postpone the sowing date to avoid the impact of autumn rain in western China on the rice harvest period. Due to the inferior water resource conditions compared to the Jianghan Plain in northern Hubei, and the frequent occurrence of hightemperatures accompanied by drought, it is recommended to choose heatresistant varieties and moderately control the rice planting area in the northern Hubei rice region. Regenerated rice should try to choose some heatresistant varieties and strengthen farmland management to cope with hightemperature and heat damage.
2024, 52(2):297-308.
DOI: 10.19517/j.1671-6345.20230014
Abstract:
Liaoning Province is a major province for blueberry cultivation. Research on suitable areas for blueberries can provide a certain theoretical basis for the development planning of the blueberry industry, strengthening the utilisation of local agricultural climate resources, improving the yield and quality of blueberries, and increasing economic benefits. In this study, the northern high bush blueberry is the main research object. Based on its biological characteristics and environmental requirements, an evaluation index system for potential suitable areas for blueberries in Liaoning Province is being established, which includes 11 indicators from three aspects: terrain, soil and climate. The Analytic Hierarchy Process, Geographic Information System spatial analysis technology and systematic cluster analysis are used to study the potential suitability of blueberry regionalising in Liaoning Province. The results are as follows: (1) The suitable planting areas for blueberries based on terrain, soil and climate account for 81.68%, 60.86% and 78.16% of the total area of Liaoning Province, respectively. Soil conditions have an obvious limiting effect on the potential distribution of blueberries, mainly due to the high soil pH and low suitability level of EC value in some areas, which make soil improvement difficult. (2) From the comprehensive regionalising point of view, the suitable area for blueberries in Liaoning Province is about 7.628×104 km2, accounting for 51.54% of the total area of Liaoning Province, which is primarily distributed in the Liaodong Peninsula, the Liaohe Plain and the western coastal area of the Liaodong Bay, among which the most suitable area is primarily distributed in the middle of Liaohe Plain, the southern part of the Liaodong Peninsula and a few coastal areas in the western part of the Liaodong Bay. It should be noted that as the main grainproducing area, Liaohe Plain is not recommended for largescale development of the blueberry industry, so it is suggested that the Liaodong Peninsula and western coastal areas of the Liaodong Bay should be the key areas for the development of the blueberry industry in Liaoning Province. (3) The 59 counties (cities) in Liaoning Province are divided into three subregions with potential suitability and two subregions with nonsuitability. The first subregion of potential suitability has apparent planting advantages in terms of natural conditions and the other conditions are more suitable except for slightly lower winter low temperature; the planting conditions for blueberries in Subregion 2 of nonsuitable areas are the least ideal, and the main restriction factors are high soil pH or low winter temperature, so it is not recommended to develop the blueberry industry. (4) In practical application, the results of comprehensive regionalization and secondary regionalization of suitable areas should be combined to determine the overall suitability of each county (city) district based on secondary regionalization of suitable areas, and then conduct a detailed investigation of each county (city) district based on comprehensive regionalization to analyse and judge the planting advantages and constraints of each region before making scientific decisions. The regionalization results are in good agreement with the existing blueberry growing areas, which can provide a scientific basis for blueberry industry planning in Liaoning Province.
Liaoning Province is a major province for blueberry cultivation. Research on suitable areas for blueberries can provide a certain theoretical basis for the development planning of the blueberry industry, strengthening the utilisation of local agricultural climate resources, improving the yield and quality of blueberries, and increasing economic benefits. In this study, the northern high bush blueberry is the main research object. Based on its biological characteristics and environmental requirements, an evaluation index system for potential suitable areas for blueberries in Liaoning Province is being established, which includes 11 indicators from three aspects: terrain, soil and climate. The Analytic Hierarchy Process, Geographic Information System spatial analysis technology and systematic cluster analysis are used to study the potential suitability of blueberry regionalising in Liaoning Province. The results are as follows: (1) The suitable planting areas for blueberries based on terrain, soil and climate account for 81.68%, 60.86% and 78.16% of the total area of Liaoning Province, respectively. Soil conditions have an obvious limiting effect on the potential distribution of blueberries, mainly due to the high soil pH and low suitability level of EC value in some areas, which make soil improvement difficult. (2) From the comprehensive regionalising point of view, the suitable area for blueberries in Liaoning Province is about 7.628×104 km2, accounting for 51.54% of the total area of Liaoning Province, which is primarily distributed in the Liaodong Peninsula, the Liaohe Plain and the western coastal area of the Liaodong Bay, among which the most suitable area is primarily distributed in the middle of Liaohe Plain, the southern part of the Liaodong Peninsula and a few coastal areas in the western part of the Liaodong Bay. It should be noted that as the main grainproducing area, Liaohe Plain is not recommended for largescale development of the blueberry industry, so it is suggested that the Liaodong Peninsula and western coastal areas of the Liaodong Bay should be the key areas for the development of the blueberry industry in Liaoning Province. (3) The 59 counties (cities) in Liaoning Province are divided into three subregions with potential suitability and two subregions with nonsuitability. The first subregion of potential suitability has apparent planting advantages in terms of natural conditions and the other conditions are more suitable except for slightly lower winter low temperature; the planting conditions for blueberries in Subregion 2 of nonsuitable areas are the least ideal, and the main restriction factors are high soil pH or low winter temperature, so it is not recommended to develop the blueberry industry. (4) In practical application, the results of comprehensive regionalization and secondary regionalization of suitable areas should be combined to determine the overall suitability of each county (city) district based on secondary regionalization of suitable areas, and then conduct a detailed investigation of each county (city) district based on comprehensive regionalization to analyse and judge the planting advantages and constraints of each region before making scientific decisions. The regionalization results are in good agreement with the existing blueberry growing areas, which can provide a scientific basis for blueberry industry planning in Liaoning Province.
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