Volume 53,Issue 4,2025 Table of Contents
WANG Gaili
,
YANG Liangliang
,
CHEN Pei
,
FAN Mengqi
,
MA Li
,
HAO Yong
,
QIN Shengguang
,
WANG Qichao
2025, 53(4):457-467.
DOI: 10.19517/j.1671-6345.20240346
Abstract:
Global climate warming leads to an increase in the frequency and intensity of forest and grassland fires. During the rescue process of forest and grassland fires, wind is the most important meteorological factor affecting the spread of the fire. It determines not only the speed of the fire’s spread but also the area and direction of the fire’s spread. Moreover, the changeable wind field information under complex terrain conditions further increases the risks for firefighting efforts and the safety guarantee of rescue workers. The wind lidar, which has the capabilities of high spatial and temporal resolution and non-contact measurement, is of great significance for the prevention and control of forest fires and the on-site rescue command. However, the detection range of the existing wind lidar is difficult to meet the demand for long-distance wind field monitoring at the forest and grassland fire site, which restricts the precise monitoring and early warning of secondary disasters at the forest fire rescue site. Therefore, The study conducts research from two aspects: high-power laser emission technology and clear-sky weak signal algorithm, and comprehensively improves the detection range from both hardware technology and data processing aspects. The high-power laser emission technology mainly includes low-noise narrow linewidth technology, multi-stage pump source amplification technology, and Brillouin scattering suppression technology, so as to achieve high-power output as a whole and ensure the measurement accuracy, sensitivity, and reliability of the lidar system. In terms of data processing, the maximum likelihood discrete spectrum peak estimation algorithm and the optimised power spectrum frequency shift estimation algorithm are used to improve the detection ability of the lidar for weak signals. The research results show that after adopting the above technologies and algorithms, the wind lidar achieves large-scale wind field measurement over a range of 15 km. The data acquisition rate exceeds 90% at 12,600 metres, reaches more than 80% at 14,400 metres, and is above 75% at 15,000 metres, with a significant improvement in detection ability. In terms of detection accuracy, there is a high degree of consistency when compared with the data from the wind measurement tower. The determination coefficients of the horizontal wind speed and wind direction at the two heights of 77 metres and 103 metres between the wind lidar and the wind measurement tower are all above 0.99, the deviation of the linear regression fitting degree is all below 0.005, the average deviation of the wind speed is below 0.05 m/s, and the average deviation of the wind direction is below 2 degrees.
Global climate warming leads to an increase in the frequency and intensity of forest and grassland fires. During the rescue process of forest and grassland fires, wind is the most important meteorological factor affecting the spread of the fire. It determines not only the speed of the fire’s spread but also the area and direction of the fire’s spread. Moreover, the changeable wind field information under complex terrain conditions further increases the risks for firefighting efforts and the safety guarantee of rescue workers. The wind lidar, which has the capabilities of high spatial and temporal resolution and non-contact measurement, is of great significance for the prevention and control of forest fires and the on-site rescue command. However, the detection range of the existing wind lidar is difficult to meet the demand for long-distance wind field monitoring at the forest and grassland fire site, which restricts the precise monitoring and early warning of secondary disasters at the forest fire rescue site. Therefore, The study conducts research from two aspects: high-power laser emission technology and clear-sky weak signal algorithm, and comprehensively improves the detection range from both hardware technology and data processing aspects. The high-power laser emission technology mainly includes low-noise narrow linewidth technology, multi-stage pump source amplification technology, and Brillouin scattering suppression technology, so as to achieve high-power output as a whole and ensure the measurement accuracy, sensitivity, and reliability of the lidar system. In terms of data processing, the maximum likelihood discrete spectrum peak estimation algorithm and the optimised power spectrum frequency shift estimation algorithm are used to improve the detection ability of the lidar for weak signals. The research results show that after adopting the above technologies and algorithms, the wind lidar achieves large-scale wind field measurement over a range of 15 km. The data acquisition rate exceeds 90% at 12,600 metres, reaches more than 80% at 14,400 metres, and is above 75% at 15,000 metres, with a significant improvement in detection ability. In terms of detection accuracy, there is a high degree of consistency when compared with the data from the wind measurement tower. The determination coefficients of the horizontal wind speed and wind direction at the two heights of 77 metres and 103 metres between the wind lidar and the wind measurement tower are all above 0.99, the deviation of the linear regression fitting degree is all below 0.005, the average deviation of the wind speed is below 0.05 m/s, and the average deviation of the wind direction is below 2 degrees.
2025, 53(4):468-478.
DOI: 10.19517/j.1671-6345.20240339
Abstract:
The deep learning-based radar echo extrapolation method is widely applied to the challenging task of short-term precipitation forecasting. However, existing methods still face issues with prediction accuracy, and when dealing with high-resolution and long-time sequence data, the training speed tends to be slow. To address these problems, this paper proposes a deep learning model based on sparse fusion attention - PFA-TransUNet (ProbSparse Fusion Attention TransUNet). This model is an encoder-decoder architecture, where a multi-layer Transformer is introduced in the encoder path. It then decomposes the traditional multi-head self-attention mechanism into computations in the spatiotemporal dimensions, allowing for the full integration of spatiotemporal information. In addition, the sparse attention method is incorporated to reduce the computational complexity of self-attention, significantly shortening the training time. Experimental results on the Hebei Province radar dataset show that compared to other advanced classical models, PFA-TransUNet outperforms them in various evaluation metrics such as extrapolation accuracy, Mean Squared Error (MSE), Structural Similarity Index (SSIM), Critical Success Index (CSI) at 20, 30, and 40 dBz, and training speed. The model demonstrates exceptional overall performance. In recent years, radar echo extrapolation becomes an increasingly important approach in precipitation forecasting, especially for nowcasting (short-term forecasting) tasks, where the ability to predict precipitation with high accuracy and efficiency is critical. However, due to the complex spatiotemporal nature of radar echoes, previous methods struggle to efficiently capture both spatial and temporal dependencies, which leads to suboptimal forecasting results. Furthermore, the computational cost associated with high-resolution and long-time series data further hampers the efficiency of current deep learning models. PFA-TransUNet addresses these limitations by incorporating a sparse attention mechanism, which helps reduce the computational load without sacrificing model performance. Traditional self-attention mechanisms in Transformer models can be computationally expensive due to the quadratic complexity of attention calculations, especially when applied to large datasets. By leveraging sparse attention, the proposed model focuses on the most relevant parts of the input data, thus improving computational efficiency and speeding up training. Another key feature of PFA-TransUNet is its ability to effectively model spatiotemporal dependencies. By decomposing the multi-head self-attention into spatiotemporal dimensions, the model captures the intricate relationships between space and time, leading to more accurate extrapolations of radar echoes. This is crucial in precipitation forecasting, as both spatial distribution and temporal evolution play a significant role in the prediction accuracy. The experimental results from the Hebei radar dataset indicate that PFA-TransUNet achieves superior performance compared to traditional models. The model shows a substantial improvement in forecast accuracy, with lower MSE values and higher SSIM scores, indicating better preservation of the structure of radar echoes. Furthermore, the model excels in terms of CSI at different dBz thresholds, demonstrating its robustness in detecting precipitation events under various conditions. Most importantly, the model’s training speed is significantly improved due to the sparse attention mechanism, making it suitable for real-time forecasting applications. In conclusion, PFA-TransUNet presents a promising solution for radar echo extrapolation tasks, especially in the context of short-term precipitation forecasting. Its combination of sparse fusion attention and spatiotemporal modelling makes it a powerful tool for improving the accuracy and efficiency of radar-based forecasting systems.
The deep learning-based radar echo extrapolation method is widely applied to the challenging task of short-term precipitation forecasting. However, existing methods still face issues with prediction accuracy, and when dealing with high-resolution and long-time sequence data, the training speed tends to be slow. To address these problems, this paper proposes a deep learning model based on sparse fusion attention - PFA-TransUNet (ProbSparse Fusion Attention TransUNet). This model is an encoder-decoder architecture, where a multi-layer Transformer is introduced in the encoder path. It then decomposes the traditional multi-head self-attention mechanism into computations in the spatiotemporal dimensions, allowing for the full integration of spatiotemporal information. In addition, the sparse attention method is incorporated to reduce the computational complexity of self-attention, significantly shortening the training time. Experimental results on the Hebei Province radar dataset show that compared to other advanced classical models, PFA-TransUNet outperforms them in various evaluation metrics such as extrapolation accuracy, Mean Squared Error (MSE), Structural Similarity Index (SSIM), Critical Success Index (CSI) at 20, 30, and 40 dBz, and training speed. The model demonstrates exceptional overall performance. In recent years, radar echo extrapolation becomes an increasingly important approach in precipitation forecasting, especially for nowcasting (short-term forecasting) tasks, where the ability to predict precipitation with high accuracy and efficiency is critical. However, due to the complex spatiotemporal nature of radar echoes, previous methods struggle to efficiently capture both spatial and temporal dependencies, which leads to suboptimal forecasting results. Furthermore, the computational cost associated with high-resolution and long-time series data further hampers the efficiency of current deep learning models. PFA-TransUNet addresses these limitations by incorporating a sparse attention mechanism, which helps reduce the computational load without sacrificing model performance. Traditional self-attention mechanisms in Transformer models can be computationally expensive due to the quadratic complexity of attention calculations, especially when applied to large datasets. By leveraging sparse attention, the proposed model focuses on the most relevant parts of the input data, thus improving computational efficiency and speeding up training. Another key feature of PFA-TransUNet is its ability to effectively model spatiotemporal dependencies. By decomposing the multi-head self-attention into spatiotemporal dimensions, the model captures the intricate relationships between space and time, leading to more accurate extrapolations of radar echoes. This is crucial in precipitation forecasting, as both spatial distribution and temporal evolution play a significant role in the prediction accuracy. The experimental results from the Hebei radar dataset indicate that PFA-TransUNet achieves superior performance compared to traditional models. The model shows a substantial improvement in forecast accuracy, with lower MSE values and higher SSIM scores, indicating better preservation of the structure of radar echoes. Furthermore, the model excels in terms of CSI at different dBz thresholds, demonstrating its robustness in detecting precipitation events under various conditions. Most importantly, the model’s training speed is significantly improved due to the sparse attention mechanism, making it suitable for real-time forecasting applications. In conclusion, PFA-TransUNet presents a promising solution for radar echo extrapolation tasks, especially in the context of short-term precipitation forecasting. Its combination of sparse fusion attention and spatiotemporal modelling makes it a powerful tool for improving the accuracy and efficiency of radar-based forecasting systems.
2025, 53(4):479-487.
DOI: 10.19517/j.1671-6345.20240172
Abstract:
GNSS receivers and antennas are set up in Beijing to receive the second-level signals of the GNSS system. Data quality checks are conducted using software. Leveraging precise ephemeris data from the BeiDou Navigation Satellite System (BDS) B2b signal, real-time zenith total delay (ZTD) and precipitable water vapour (PWV) retrieval experiments are conducted using BDS Precise Point Positioning (PPP) techniques, single GPS, and their integrated solutions. These results are systematically compared against ZTD/PWV estimates derived from BDS/GPS dual-difference network solutions, radiosonde observations, and ERA5 reanalysis datasets. The results show that the average signal-to-noise ratio of the GNSS signal is greater than 35, and the multipath effect is better than 0.5 m, ensuring robust observational conditions for inversion modelling. Compared with the double-difference network solution, the average deviation of the tropospheric delay inversion based on BeiDou precise point positioning is 4.5 mm, the root mean square error is 9.94 mm, and the correlation coefficient is 90%. The corresponding PWV inversion average deviation is 0.35 mm, the root mean square error is 1.33 mm, and the correlation coefficient is 96%. Compared with radiosonde, the average deviation of the tropospheric delay inversion is 5.83 mm, the RMSE is 7.38 mm, and the correlation coefficient is 95.07%. The corresponding PWV inversion average deviation is 1.03 mm, the root mean square error is 1.72 mm, and the correlation coefficient is 94.45%. This indicates that the ZTD/PWV inversion technology derived from BDS makes single-system and single-point solutions possible. This method adopts a distributed computing strategy, avoiding the bandwidth and storage pressure of returning the solution data to the central station at the station end in the past, improving the real-time performance of water vapour solutions, and can represent the trend of water vapour change. It is of great significance for the monitoring and early warning of weather phenomena and meteorological disasters related to water vapour.
GNSS receivers and antennas are set up in Beijing to receive the second-level signals of the GNSS system. Data quality checks are conducted using software. Leveraging precise ephemeris data from the BeiDou Navigation Satellite System (BDS) B2b signal, real-time zenith total delay (ZTD) and precipitable water vapour (PWV) retrieval experiments are conducted using BDS Precise Point Positioning (PPP) techniques, single GPS, and their integrated solutions. These results are systematically compared against ZTD/PWV estimates derived from BDS/GPS dual-difference network solutions, radiosonde observations, and ERA5 reanalysis datasets. The results show that the average signal-to-noise ratio of the GNSS signal is greater than 35, and the multipath effect is better than 0.5 m, ensuring robust observational conditions for inversion modelling. Compared with the double-difference network solution, the average deviation of the tropospheric delay inversion based on BeiDou precise point positioning is 4.5 mm, the root mean square error is 9.94 mm, and the correlation coefficient is 90%. The corresponding PWV inversion average deviation is 0.35 mm, the root mean square error is 1.33 mm, and the correlation coefficient is 96%. Compared with radiosonde, the average deviation of the tropospheric delay inversion is 5.83 mm, the RMSE is 7.38 mm, and the correlation coefficient is 95.07%. The corresponding PWV inversion average deviation is 1.03 mm, the root mean square error is 1.72 mm, and the correlation coefficient is 94.45%. This indicates that the ZTD/PWV inversion technology derived from BDS makes single-system and single-point solutions possible. This method adopts a distributed computing strategy, avoiding the bandwidth and storage pressure of returning the solution data to the central station at the station end in the past, improving the real-time performance of water vapour solutions, and can represent the trend of water vapour change. It is of great significance for the monitoring and early warning of weather phenomena and meteorological disasters related to water vapour.
2025, 53(4):488-496.
DOI: 10.19517/j.1671-6345.20240324
Abstract:
The China Meteorological Administration Satellite Broadcasting System (CMACast system), owing to its extensive coverage and the significant advantage of being intercontinental and end-to-end, unaffected by ground communication conditions, becomes one of the crucial communication means for global meteorological data distribution services. As the China Meteorological Administration continuously enhances its global monitoring, global forecasting, and global service capabilities, the requirements for providing meteorological data distribution services to international users, especially those along the Belt and Road lnitiative, become increasingly demanding. However, the CMACast system has an obvious service shortcoming in that its broadcast signal coverage is limited to the Asia-Pacific region. To meet the global meteorological service demands, the satellite broadcasting system of the meteorological informatisation system project is comprehensively upgraded. Among these upgrades, the expansion of the broadcast coverage area is one of the most significant. The selection of transponders for the new broadcast communication satellites and the design of broadcast parameters are key issues that need to be addressed with priority. Through a survey of all communication satellite resources over China, based on the coverage area of satellite C transponders, four communication satellites are initially selected as the research objects from 20 on-orbit communication satellites of CITIC Satcom and China Satcom. Through a comprehensive comparison and analysis of the coverage area, signal strength, transponder frequency, and the coverage of existing users of these four satellites, the results show that the AsiaSat 7 is the optimal choice. Therefore, based on the AsiaSat 7, the broadcast links to the Belt and Road lnitiative regions and countries are calculated and analysed respectively. The results indicate that using the AsiaSat 7 can meet the requirements of the broadcast service, verifying the correctness of choosing the AsiaSat 7 as the broadcast transmission design. At the same time, to make the new broadcast system compatible with all existing users, actual tests are carried out on various modulation methods, coding rates, roll-off factors, and broadcasting rates under the condition of antennas with different receiving apertures. Through actual tests, 8PSK modulation, 3/4 coding rate, and 0.1 roll-off factor are optimally selected as the operation parameters for the broadcast service. This not only meets the needs of the expanded and upgraded broadcast coverage but also is compatible with all existing users. The achievements are applied to the upgrade and construction of the CMACast system in the meteorological informatisation system project. As a result, the coverage of the new-generation CMACast system is expanded from the Asia-Pacific region to the Belt and Road lnitiative regions such as the Middle East and Africa, enhancing the information network support for meteorological services in these regions.
The China Meteorological Administration Satellite Broadcasting System (CMACast system), owing to its extensive coverage and the significant advantage of being intercontinental and end-to-end, unaffected by ground communication conditions, becomes one of the crucial communication means for global meteorological data distribution services. As the China Meteorological Administration continuously enhances its global monitoring, global forecasting, and global service capabilities, the requirements for providing meteorological data distribution services to international users, especially those along the Belt and Road lnitiative, become increasingly demanding. However, the CMACast system has an obvious service shortcoming in that its broadcast signal coverage is limited to the Asia-Pacific region. To meet the global meteorological service demands, the satellite broadcasting system of the meteorological informatisation system project is comprehensively upgraded. Among these upgrades, the expansion of the broadcast coverage area is one of the most significant. The selection of transponders for the new broadcast communication satellites and the design of broadcast parameters are key issues that need to be addressed with priority. Through a survey of all communication satellite resources over China, based on the coverage area of satellite C transponders, four communication satellites are initially selected as the research objects from 20 on-orbit communication satellites of CITIC Satcom and China Satcom. Through a comprehensive comparison and analysis of the coverage area, signal strength, transponder frequency, and the coverage of existing users of these four satellites, the results show that the AsiaSat 7 is the optimal choice. Therefore, based on the AsiaSat 7, the broadcast links to the Belt and Road lnitiative regions and countries are calculated and analysed respectively. The results indicate that using the AsiaSat 7 can meet the requirements of the broadcast service, verifying the correctness of choosing the AsiaSat 7 as the broadcast transmission design. At the same time, to make the new broadcast system compatible with all existing users, actual tests are carried out on various modulation methods, coding rates, roll-off factors, and broadcasting rates under the condition of antennas with different receiving apertures. Through actual tests, 8PSK modulation, 3/4 coding rate, and 0.1 roll-off factor are optimally selected as the operation parameters for the broadcast service. This not only meets the needs of the expanded and upgraded broadcast coverage but also is compatible with all existing users. The achievements are applied to the upgrade and construction of the CMACast system in the meteorological informatisation system project. As a result, the coverage of the new-generation CMACast system is expanded from the Asia-Pacific region to the Belt and Road lnitiative regions such as the Middle East and Africa, enhancing the information network support for meteorological services in these regions.
2025, 53(4):497-507.
DOI: 10.19517/j.1671-6345.20240298
Abstract:
The development of refined tropical cyclone (TC) forecasting operations relies on high-resolution regional TC numerical forecasting. However, when faced with both the characteristic of expensive computational consumption of high-resolution models and the characteristic of the wide range of TC forecasting responsibility areas, it is difficult for the existing numerical forecasting techniques to meet the high timeliness requirements in operational high-resolution TC forecasting. High-resolution numerical models face challenges in balancing computational demands, forecast timeliness, and prediction accuracy for TC forecasting operations. To save computational resources and meet high timeliness requirements while ensuring TC forecast accuracy, this study proposes an adaptive setting-up approach of a limited area for the short-term forecast of TC by combining an adaptive objective calculation method for the TC simulation domain with multi-TC coexistence processing technology. This approach dynamically adjusts the position and size of the high-resolution TC model simulation domain based on the forecast timeliness and the actual situation of the TC. By automatically providing a scientifically reasonable simulation domain, the computer resource consumption is reduced without losing forecasting skills. Applying this approach to the high-resolution CMA-MESO model, a High-Resolution Typhoon Numerical Prediction System (HRTYM) is established. The numerical experiments and comparative analysis are carried out using Typhoon Lekima (2019) and 16 major typhoon events in 2020 and 2021. The experimental results of Typhoon Lekima show that, compared with the 9 km-resolution operational model (CMA-TYM), the 3 km-resolution HRTYM requires fewer computational resources with model integration time reduced by 11.2%-17.5% and storage space reduced by 58.6%-66.7%, the TC track forecast error decreases by 20.7%-61.0%, and the TS scores for 24-hour rainstorm and heavy rainstorm predictions improve significantly. The results of batch experiments in 2020 show that after 24-48 hours of mode integration, the track error of the 3 km-resolution HRTYM decreases by 3.44-34.91 km compared to the 9 km-resolution CMA-TYM, and the results of batch experiments in 2021 show that after 27-48 hours of mode integration, the track error of the 3 km-resolution HRTYM decreases by 0.6-22.35 km compared to the 9 km-resolution CMA-TYM. The results of batch experiments in 2020 and 2021 demonstrate that HRTYM exhibits superior track prediction skill over CMA-TYM beyond 27 hours. The high-resolution TC numerical prediction system applying the adaptive setting-up approach of a limited area for the short-term forecast of TC proposed in this study effectively reduces the cost of computing resources and computer storage space resources and ensures the skill of TC numerical prediction at the same time.
The development of refined tropical cyclone (TC) forecasting operations relies on high-resolution regional TC numerical forecasting. However, when faced with both the characteristic of expensive computational consumption of high-resolution models and the characteristic of the wide range of TC forecasting responsibility areas, it is difficult for the existing numerical forecasting techniques to meet the high timeliness requirements in operational high-resolution TC forecasting. High-resolution numerical models face challenges in balancing computational demands, forecast timeliness, and prediction accuracy for TC forecasting operations. To save computational resources and meet high timeliness requirements while ensuring TC forecast accuracy, this study proposes an adaptive setting-up approach of a limited area for the short-term forecast of TC by combining an adaptive objective calculation method for the TC simulation domain with multi-TC coexistence processing technology. This approach dynamically adjusts the position and size of the high-resolution TC model simulation domain based on the forecast timeliness and the actual situation of the TC. By automatically providing a scientifically reasonable simulation domain, the computer resource consumption is reduced without losing forecasting skills. Applying this approach to the high-resolution CMA-MESO model, a High-Resolution Typhoon Numerical Prediction System (HRTYM) is established. The numerical experiments and comparative analysis are carried out using Typhoon Lekima (2019) and 16 major typhoon events in 2020 and 2021. The experimental results of Typhoon Lekima show that, compared with the 9 km-resolution operational model (CMA-TYM), the 3 km-resolution HRTYM requires fewer computational resources with model integration time reduced by 11.2%-17.5% and storage space reduced by 58.6%-66.7%, the TC track forecast error decreases by 20.7%-61.0%, and the TS scores for 24-hour rainstorm and heavy rainstorm predictions improve significantly. The results of batch experiments in 2020 show that after 24-48 hours of mode integration, the track error of the 3 km-resolution HRTYM decreases by 3.44-34.91 km compared to the 9 km-resolution CMA-TYM, and the results of batch experiments in 2021 show that after 27-48 hours of mode integration, the track error of the 3 km-resolution HRTYM decreases by 0.6-22.35 km compared to the 9 km-resolution CMA-TYM. The results of batch experiments in 2020 and 2021 demonstrate that HRTYM exhibits superior track prediction skill over CMA-TYM beyond 27 hours. The high-resolution TC numerical prediction system applying the adaptive setting-up approach of a limited area for the short-term forecast of TC proposed in this study effectively reduces the cost of computing resources and computer storage space resources and ensures the skill of TC numerical prediction at the same time.
2025, 53(4):508-519.
DOI: 10.19517/j.1671-6345.20240309
Abstract:
With the continuous improvement of the horizontal resolution of the numerical weather prediction model, cumulus clouds are not distinguishable by the grid scale in the “grey area” (1-10 km) of the convective parameterisation scheme, making the traditional cumulus convective parameterisation scheme difficult to apply to the simulation of precipitation at different resolutions. Therefore, the development of scale-aware cumulus cloud parameterisation schemes is one of the development trends of numerical model refinement. By introducing the scale-aware KFeta (Kain-Fritsch eta) convective parameterisation scheme into the CMA-MESO (China Meteorological Administration Mesoscale model) model, the paper combines three resolutions (1 km, 3 km, and 10 km) and designs three sets of experiments so that a numerical simulation test is carried out on a precipitation process on 11-12 July 2023, in the mountainous area of southwest China, and a 7-day batch test is carried out on the precipitation process on 17-23 June 2023. This is done to test and evaluate the effect of the scale adaptation scheme on precipitation simulation in the southwest mountainous area. The results show that: (1) In the case experiment, the scale adaptation scheme has a good grasp of the precipitation rain band and precipitation intensity, and the simulation of the heavy precipitation centre has certain advantages. With the increase in resolution, the precipitation intensity and falling area of the scale adaptation group are closer to reality, which greatly reduces the false precipitation caused by cumulus clouds and increases the grid precipitation. (2) The combined reflectance factor and vertical velocity simulation results in the strong convection region of the scale adaptation scheme are better. (3) In the batch test, the scale adaptation scheme has a good and stable simulation ability for precipitation in the southwest mountain area, especially the simulation results of the scale adaptation scheme for moderate rain and above, which are more advantageous, and the precipitation TS score of the original scheme improves by 4% overall. In general, the scale adaptation scheme performs well in the forecast of heavy precipitation in the southwest mountainous area, providing a basis for improving the current numerical model of heavy precipitation forecasts.
With the continuous improvement of the horizontal resolution of the numerical weather prediction model, cumulus clouds are not distinguishable by the grid scale in the “grey area” (1-10 km) of the convective parameterisation scheme, making the traditional cumulus convective parameterisation scheme difficult to apply to the simulation of precipitation at different resolutions. Therefore, the development of scale-aware cumulus cloud parameterisation schemes is one of the development trends of numerical model refinement. By introducing the scale-aware KFeta (Kain-Fritsch eta) convective parameterisation scheme into the CMA-MESO (China Meteorological Administration Mesoscale model) model, the paper combines three resolutions (1 km, 3 km, and 10 km) and designs three sets of experiments so that a numerical simulation test is carried out on a precipitation process on 11-12 July 2023, in the mountainous area of southwest China, and a 7-day batch test is carried out on the precipitation process on 17-23 June 2023. This is done to test and evaluate the effect of the scale adaptation scheme on precipitation simulation in the southwest mountainous area. The results show that: (1) In the case experiment, the scale adaptation scheme has a good grasp of the precipitation rain band and precipitation intensity, and the simulation of the heavy precipitation centre has certain advantages. With the increase in resolution, the precipitation intensity and falling area of the scale adaptation group are closer to reality, which greatly reduces the false precipitation caused by cumulus clouds and increases the grid precipitation. (2) The combined reflectance factor and vertical velocity simulation results in the strong convection region of the scale adaptation scheme are better. (3) In the batch test, the scale adaptation scheme has a good and stable simulation ability for precipitation in the southwest mountain area, especially the simulation results of the scale adaptation scheme for moderate rain and above, which are more advantageous, and the precipitation TS score of the original scheme improves by 4% overall. In general, the scale adaptation scheme performs well in the forecast of heavy precipitation in the southwest mountainous area, providing a basis for improving the current numerical model of heavy precipitation forecasts.
2025, 53(4):520-534.
DOI: 10.19517/j.1671-6345.20240361
Abstract:
This study utilises best-track datasets of tropical cyclones (TCs) from the Joint Typhoon Warning Center (JTWC), Japan Meteorological Agency Tokyo Regional Specialised Meteorological Center (RSMC), and Shanghai Typhoon Institute of China Meteorological Administration (CMA), along with NCEP reanalysis data and correlation analysis methods, to investigate the fundamental characteristics of TC intensity and frequency in different seasons (July-September for summer and October-November for autumn) and subregions over the Western North Pacific (WNP) during 1989-2020, as well as their relationships with local environmental factors. The results indicate that: (1) The total TC frequency observed in the three summer WNP subregions (Area I: 10°-25°N, 110°-145°E; Area II: 10°-25°N, 145°E-180°; Area III: 25°-37.5°N, 125°E-180°) is 10164, while the total TC frequency in the three autumn subregions (Area I: 5°-17.5°N, 110°E-180°; Area II: 17.5°-35°N, 142.5°E-180°; Area III: 17.5°-35°N, 120°-142.5°E) is 4984. This demonstrates significantly higher TC activity in summer than in autumn. (2) TC activity during both summer and autumn exhibits statistically significant correlations with 850 hPa relative vorticity (RVOR), except for Area II in autumn. In addition to low-level RVOR, summer TC frequency in Area I is associated with 500 hPa vertical velocity (OMEGA) and 700-500 hPa relative humidity (RHUM). Summer TC intensity in Area II is linked to 700-500 hPa RHUM, 500 hPa OMEGA, and vertical wind shear (VWS), while summer TC frequency in Area II correlates with 500 hPa OMEGA and VWS. Autumn TC frequency in Area I shows a relationship with 500 hPa OMEGA. Regardless of season, TC activity generally displays either nonsignificant correlations or significantly negative correlations with oceanic factors. The local environmental factors influencing TC activity vary across regions and seasons, depending on seasonal and regional divisions, which indicates complex interactions. (3) A strong monsoon trough enhances TC activity in summer and autumn Area I through low-level high RVOR, mid-level ascending motion, and high humidity. The warming of sea surface temperature in the Nino3.4 region can induce anomalous westerly winds at 850 hPa in Area II during summer, leading to increased low-level RVOR. Concurrently, an anomalous anticyclonic circulation emerges at 200 hPa, resulting in reduced VWS. The combination of the enhanced low-level RVOR and upper-level anticyclonic circulation further strengthens mid-level upward motion and moisture convergence, thereby influencing TC activity in this region. When the Western Pacific subtropical high extends westward (retreats eastward), it generates localised negative (positive) vorticity anomalies, leading to reduced (increased) TC frequency entering summer Area III. Strengthened mid-level steering flows further enhance the intrusion of intense TCs into this region. The convergence in the relative low region between two highs enhances low-level RVOR, which consequently modulates TC activity in Area III during autumn.
This study utilises best-track datasets of tropical cyclones (TCs) from the Joint Typhoon Warning Center (JTWC), Japan Meteorological Agency Tokyo Regional Specialised Meteorological Center (RSMC), and Shanghai Typhoon Institute of China Meteorological Administration (CMA), along with NCEP reanalysis data and correlation analysis methods, to investigate the fundamental characteristics of TC intensity and frequency in different seasons (July-September for summer and October-November for autumn) and subregions over the Western North Pacific (WNP) during 1989-2020, as well as their relationships with local environmental factors. The results indicate that: (1) The total TC frequency observed in the three summer WNP subregions (Area I: 10°-25°N, 110°-145°E; Area II: 10°-25°N, 145°E-180°; Area III: 25°-37.5°N, 125°E-180°) is 10164, while the total TC frequency in the three autumn subregions (Area I: 5°-17.5°N, 110°E-180°; Area II: 17.5°-35°N, 142.5°E-180°; Area III: 17.5°-35°N, 120°-142.5°E) is 4984. This demonstrates significantly higher TC activity in summer than in autumn. (2) TC activity during both summer and autumn exhibits statistically significant correlations with 850 hPa relative vorticity (RVOR), except for Area II in autumn. In addition to low-level RVOR, summer TC frequency in Area I is associated with 500 hPa vertical velocity (OMEGA) and 700-500 hPa relative humidity (RHUM). Summer TC intensity in Area II is linked to 700-500 hPa RHUM, 500 hPa OMEGA, and vertical wind shear (VWS), while summer TC frequency in Area II correlates with 500 hPa OMEGA and VWS. Autumn TC frequency in Area I shows a relationship with 500 hPa OMEGA. Regardless of season, TC activity generally displays either nonsignificant correlations or significantly negative correlations with oceanic factors. The local environmental factors influencing TC activity vary across regions and seasons, depending on seasonal and regional divisions, which indicates complex interactions. (3) A strong monsoon trough enhances TC activity in summer and autumn Area I through low-level high RVOR, mid-level ascending motion, and high humidity. The warming of sea surface temperature in the Nino3.4 region can induce anomalous westerly winds at 850 hPa in Area II during summer, leading to increased low-level RVOR. Concurrently, an anomalous anticyclonic circulation emerges at 200 hPa, resulting in reduced VWS. The combination of the enhanced low-level RVOR and upper-level anticyclonic circulation further strengthens mid-level upward motion and moisture convergence, thereby influencing TC activity in this region. When the Western Pacific subtropical high extends westward (retreats eastward), it generates localised negative (positive) vorticity anomalies, leading to reduced (increased) TC frequency entering summer Area III. Strengthened mid-level steering flows further enhance the intrusion of intense TCs into this region. The convergence in the relative low region between two highs enhances low-level RVOR, which consequently modulates TC activity in Area III during autumn.
2025, 53(4):535-544.
DOI: 10.19517/j.1671-6345.20240350
Abstract:
The study of intraseasonal oscillation (ISO) characteristics is crucial for both understanding internal variability and improving prediction skill at the sub-seasonal time scale. Based on daily precipitation from 108 national meteorological stations across Shanxi and NCEP/NCAR daily atmospheric reanalysis datasets spanning 1980 to 2022, this study investigates the climatological spatiotemporal evolution of summer precipitation ISO in Shanxi and its association with atmospheric circulation by using statistical methods of Lanczos filtering, power spectrum analysis, and composite analysis. The main findings are as follows: (1) Summer precipitation in Shanxi shows a significant 10-50-day ISO signal. The intensity of the precipitation ISO displays a significant and positive correlation with precipitation, with a high temporal correlation value of 0.88 and a consistent increasing trend after 2000. Specifically, precipitation increases at a rate of 35.4 mm/decade, while ISO intensity increases by 0.27 (mm·d-1)/decade. Spatially, areas with higher precipitation generally experience stronger ISO, and the most active ISO centres are located in southern Shanxi and the mountainous areas. (2) Two typical summer precipitation ISO cycles in Shanxi exhibit three-stage evolution according to their composite analysis. The initial stage is characterised by a weakening of drought conditions and the onset of positive precipitation anomalies in parts of Shanxi; the active stage features the expansion and intensification of positive precipitation anomalies until peak precipitation progresses southward to southern Shanxi; and the weakening stage begins when ISO-induced positive precipitation anomalies retreat and terminates when the negative precipitation anomalies re-emerge over most parts of Shanxi. (3) The evolution of precipitation ISO is closely linked to vertically integrated water vapour transport. The enhancement (weakening) and westward-northward (eastward-southward) shift of low-frequency anticyclonic water vapour transport over the subtropical western Pacific plays a vital role in regulating the ISO precipitation cycle. During the dry phase, the water vapour transport is too weak to reach Shanxi. As the anomalous anticyclone shifts westward and northward, the ISO enters its active stage, accompanied by strengthened and persistent southeasterly water vapour transport, placing Shanxi in a water vapour convergence zone. As this transport weakens and retreats eastward, the water vapour convergence zone gradually shifts out of Shanxi. After the weakening stage, a new ISO cycle restarts. This study elucidates the climatological spatiotemporal evolution of summer precipitation ISO in Shanxi and its synergistic interaction with atmospheric circulation, providing a scientific foundation for regional sub-seasonal precipitation forecasting and offering new insights into the ISO characteristics and mechanisms over mid-latitude regions with complex terrain.
The study of intraseasonal oscillation (ISO) characteristics is crucial for both understanding internal variability and improving prediction skill at the sub-seasonal time scale. Based on daily precipitation from 108 national meteorological stations across Shanxi and NCEP/NCAR daily atmospheric reanalysis datasets spanning 1980 to 2022, this study investigates the climatological spatiotemporal evolution of summer precipitation ISO in Shanxi and its association with atmospheric circulation by using statistical methods of Lanczos filtering, power spectrum analysis, and composite analysis. The main findings are as follows: (1) Summer precipitation in Shanxi shows a significant 10-50-day ISO signal. The intensity of the precipitation ISO displays a significant and positive correlation with precipitation, with a high temporal correlation value of 0.88 and a consistent increasing trend after 2000. Specifically, precipitation increases at a rate of 35.4 mm/decade, while ISO intensity increases by 0.27 (mm·d-1)/decade. Spatially, areas with higher precipitation generally experience stronger ISO, and the most active ISO centres are located in southern Shanxi and the mountainous areas. (2) Two typical summer precipitation ISO cycles in Shanxi exhibit three-stage evolution according to their composite analysis. The initial stage is characterised by a weakening of drought conditions and the onset of positive precipitation anomalies in parts of Shanxi; the active stage features the expansion and intensification of positive precipitation anomalies until peak precipitation progresses southward to southern Shanxi; and the weakening stage begins when ISO-induced positive precipitation anomalies retreat and terminates when the negative precipitation anomalies re-emerge over most parts of Shanxi. (3) The evolution of precipitation ISO is closely linked to vertically integrated water vapour transport. The enhancement (weakening) and westward-northward (eastward-southward) shift of low-frequency anticyclonic water vapour transport over the subtropical western Pacific plays a vital role in regulating the ISO precipitation cycle. During the dry phase, the water vapour transport is too weak to reach Shanxi. As the anomalous anticyclone shifts westward and northward, the ISO enters its active stage, accompanied by strengthened and persistent southeasterly water vapour transport, placing Shanxi in a water vapour convergence zone. As this transport weakens and retreats eastward, the water vapour convergence zone gradually shifts out of Shanxi. After the weakening stage, a new ISO cycle restarts. This study elucidates the climatological spatiotemporal evolution of summer precipitation ISO in Shanxi and its synergistic interaction with atmospheric circulation, providing a scientific foundation for regional sub-seasonal precipitation forecasting and offering new insights into the ISO characteristics and mechanisms over mid-latitude regions with complex terrain.
2025, 53(4):545-556.
DOI: 10.19517/j.1671-6345.20250023
Abstract:
Based on the National Basic Meteorological Station observation data, European Centre for Medium-Range Weather Forecasts Reanalysis, and the typhoon best track data of Shanghai Typhoon Research Institute from 1951 to 2022, the characteristics of daily extreme rainfall events caused by typhoons and the points of daily extreme rainfall forecast in Wenzhou are studied and analysed using the percentile method and composite analysis. The results show that typhoons causing daily extreme rainfall in Wenzhou are all landing typhoons. Daily extreme rainfall is concentrated between July and October, with the most occurring in August and the strongest in September. According to similar rainfall patterns and paths, they are divided into four types: Southern Zhejiang, Eastern Guangdong, Middle, and Southwest types. The heavy rainfall centres of the Southern Zhejiang type and Eastern Guangdong type are located in the northeast of Wenzhou, and the corresponding typhoons land in the south of Zhejiang Province and the east of Guangdong Province, respectively. The heavy rainfall centre of the Middle type is located in the middle of Wenzhou, and the corresponding typhoons land in the area from the junction of Zhejiang and Fujian Provinces to the middle of Fujian Province. The heavy rainfall centre of the Southwest type is located in the southwest of Wenzhou, and the corresponding typhoons land in the middle and south of Fujian Province. Except for the Eastern Guangdong type, low-layer vorticity at 850 hPa reaches 8×10-5/s or above, which provides a good indication for daily extreme rainfall forecasts. The intensity differences of water vapour transport, water vapour convergence, vertical water vapour flux gradient between 850-925 hPa, and different types of low-layer jets correspond well with the intensity of extreme rainfall. The differences between the west boundary of the water vapour transport above 30 g/(s·hPa·cm) and the position of the strong water vapour convergence centre below -(2-4)×10-6 g/(cm2·hPa·s) correspond to the differences in extreme rainfall areas. The dense zone of water vapour flux and the convergence centre of water vapour flux at 925 hPa correspond well with the area of heavy rainfall, except for the Eastern Guangdong type. The differences in the development height and intensity of vertical ascending motion below -0.8 Pa/s correspond to the differences in extreme rainfall area and intensity. The characteristics of the low-layer convergence zone explain the distribution of vertical ascending motion. The uplift caused by sea-land terrain in the east and mountainous terrain in the west strengthens the ascending motion. The intensity difference of differential pseudo-equivalent potential temperature advection in the middle and lower levels corresponds with the difference in rainfall intensity. Cold air has a certain enhancement effect on the extreme rainfall events of the Eastern Guangdong, Middle and Southwest types.
Based on the National Basic Meteorological Station observation data, European Centre for Medium-Range Weather Forecasts Reanalysis, and the typhoon best track data of Shanghai Typhoon Research Institute from 1951 to 2022, the characteristics of daily extreme rainfall events caused by typhoons and the points of daily extreme rainfall forecast in Wenzhou are studied and analysed using the percentile method and composite analysis. The results show that typhoons causing daily extreme rainfall in Wenzhou are all landing typhoons. Daily extreme rainfall is concentrated between July and October, with the most occurring in August and the strongest in September. According to similar rainfall patterns and paths, they are divided into four types: Southern Zhejiang, Eastern Guangdong, Middle, and Southwest types. The heavy rainfall centres of the Southern Zhejiang type and Eastern Guangdong type are located in the northeast of Wenzhou, and the corresponding typhoons land in the south of Zhejiang Province and the east of Guangdong Province, respectively. The heavy rainfall centre of the Middle type is located in the middle of Wenzhou, and the corresponding typhoons land in the area from the junction of Zhejiang and Fujian Provinces to the middle of Fujian Province. The heavy rainfall centre of the Southwest type is located in the southwest of Wenzhou, and the corresponding typhoons land in the middle and south of Fujian Province. Except for the Eastern Guangdong type, low-layer vorticity at 850 hPa reaches 8×10-5/s or above, which provides a good indication for daily extreme rainfall forecasts. The intensity differences of water vapour transport, water vapour convergence, vertical water vapour flux gradient between 850-925 hPa, and different types of low-layer jets correspond well with the intensity of extreme rainfall. The differences between the west boundary of the water vapour transport above 30 g/(s·hPa·cm) and the position of the strong water vapour convergence centre below -(2-4)×10-6 g/(cm2·hPa·s) correspond to the differences in extreme rainfall areas. The dense zone of water vapour flux and the convergence centre of water vapour flux at 925 hPa correspond well with the area of heavy rainfall, except for the Eastern Guangdong type. The differences in the development height and intensity of vertical ascending motion below -0.8 Pa/s correspond to the differences in extreme rainfall area and intensity. The characteristics of the low-layer convergence zone explain the distribution of vertical ascending motion. The uplift caused by sea-land terrain in the east and mountainous terrain in the west strengthens the ascending motion. The intensity difference of differential pseudo-equivalent potential temperature advection in the middle and lower levels corresponds with the difference in rainfall intensity. Cold air has a certain enhancement effect on the extreme rainfall events of the Eastern Guangdong, Middle and Southwest types.
2025, 53(4):557-571.
DOI: 10.19517/j.1671-6345.20240265
Abstract:
Convection initiation (CI) directly affects the early warning of severe convective weather, while the mechanism of CI with obvious regional characteristics is complex. Based on multi-source high-resolution observation data and ERA5 reanalysis data, the characteristics and causes of the extreme severe convection triggered at the trumpet-shaped terrain in the eastern foot of the Taihang Mountains on 17 May 2023 are explored, combined with a similar case. The results show that under the unstable stratification of the 500 hPa shallow trough carrying weak cold air from the middle layer invading the surface thermal low pressure, the extreme convection caused by a supercell storm evolved from a mesoscale convective cell triggered at the 400 m height of the trumpet-shaped terrain in the eastern foot of the Taihang Mountains. Under the environment of continuous high temperature and weak vertical wind shear, a convective cell was triggered near Wangkuai Reservoir on the warm side of the temperature front below 850 hPa. The 2-m temperature difference between the north and south sides of the convective cell was 3-4 ℃, and the water vapour was close to saturation. Meanwhile, the convergence line of southeast wind and northerly wind extended from the ground to 850 hPa, and the thickness of easterly wind with a maximum wind speed of 6-8 m/s near 0.5 km was about 1 km. Before convection initiation, the new banded convective cumulus clouds at the 200-600 m slope of the eastern foot of the Taihang Mountains were consistent with the mountain direction, which was related to the boundary convergence line and the thermal forcing on the mountain. The convection was triggered on the side of the convergence line near the mountain. Froude number (Fr) , terrain vorticity and terrain divergence quantitatively characterised the terrain uplift effect. The Fr number decreased from the mountain to the plain with the peak value at the height of 400 m where the convective cell was triggered. Before CI, the Fr number escalated to about 1, indicating the airflow climbing effect, and the cyclonic terrain vorticity and terrain horizontal divergence were enhanced, then the convective cell was triggered.
Convection initiation (CI) directly affects the early warning of severe convective weather, while the mechanism of CI with obvious regional characteristics is complex. Based on multi-source high-resolution observation data and ERA5 reanalysis data, the characteristics and causes of the extreme severe convection triggered at the trumpet-shaped terrain in the eastern foot of the Taihang Mountains on 17 May 2023 are explored, combined with a similar case. The results show that under the unstable stratification of the 500 hPa shallow trough carrying weak cold air from the middle layer invading the surface thermal low pressure, the extreme convection caused by a supercell storm evolved from a mesoscale convective cell triggered at the 400 m height of the trumpet-shaped terrain in the eastern foot of the Taihang Mountains. Under the environment of continuous high temperature and weak vertical wind shear, a convective cell was triggered near Wangkuai Reservoir on the warm side of the temperature front below 850 hPa. The 2-m temperature difference between the north and south sides of the convective cell was 3-4 ℃, and the water vapour was close to saturation. Meanwhile, the convergence line of southeast wind and northerly wind extended from the ground to 850 hPa, and the thickness of easterly wind with a maximum wind speed of 6-8 m/s near 0.5 km was about 1 km. Before convection initiation, the new banded convective cumulus clouds at the 200-600 m slope of the eastern foot of the Taihang Mountains were consistent with the mountain direction, which was related to the boundary convergence line and the thermal forcing on the mountain. The convection was triggered on the side of the convergence line near the mountain. Froude number (Fr) , terrain vorticity and terrain divergence quantitatively characterised the terrain uplift effect. The Fr number decreased from the mountain to the plain with the peak value at the height of 400 m where the convective cell was triggered. Before CI, the Fr number escalated to about 1, indicating the airflow climbing effect, and the cyclonic terrain vorticity and terrain horizontal divergence were enhanced, then the convective cell was triggered.
2025, 53(4):572-584.
DOI: 10.19517/j.1671-6345.20240281
Abstract:
From June 26 to 28, 2022, a regional heavy rainfall event occurred in Shandong Province, characterised by significant precipitation intensity and extensive spatial coverage. This event ranks among the most severe heavy rainfall processes that induce disasters in recent years. The precipitation process is divided into three distinct stages, with warm-sector precipitation driven by a low vortex and low-level jet playing a dominant role in this heavy rainstorm. The instability mechanisms of warm-sector precipitation, as well as the triggering and maintenance of heavy precipitation, present significant challenges for operational forecasting and are the primary focus of this study. Based on conventional surface and upper-air meteorological observation data, ERA5 hourly reanalysis data, and radar data, this study analyses the water vapour conditions, atmospheric instability, and frontogenetic characteristics of this heavy rainfall event. The results indicate that the precipitation process in the warm sector of the low vortex primarily occurred within the low-level jet zone south of the warm shear region of the low vortex. The low-level jet provided ample water vapour conditions for precipitation, while a region of strong water vapour flux convergence north of the jet stream served as an effective indicator for heavy precipitation. At the onset of precipitation in the warm vortex region, strong convective instability was observed in the mid-to-lower troposphere, with upward motion initiated by the release of convective instability, exhibiting vertical convection characteristics. During the peak precipitation period, the ascending motion was influenced by both convective instability and symmetric instability, with symmetric instability being predominant, resulting in a combination of vertical and oblique convective processes. This precipitation process was accompanied by pronounced frontogenesis, featuring strong geostrophic wind deviation convergence in the frontogenesis region, which supplied essential dynamic uplift conditions for precipitation initiation and intensification. Analysis of the deformation term and divergence term in the frontogenesis function reveals that the divergence term was the main factor of frontogenesis in this process. Low-level convergence not only provided dynamic conditions for precipitation initiation but also integrated radar precipitation echoes with mesoscale convergence lines at the surface, influencing the morphology of cumulus precipitation echoes and forming mesoscale convective rainbands aligned along the guiding airflow. The mesoscale convective rainband moved along the guiding airflow, creating a “train effect” that resulted in heavy precipitation. These findings enhance operational forecasting capabilities for warm-sector precipitation associated with low vortices and similar processes, providing valuable insights for forecasters to develop systematic models of warm-sector precipitation weather systems.
From June 26 to 28, 2022, a regional heavy rainfall event occurred in Shandong Province, characterised by significant precipitation intensity and extensive spatial coverage. This event ranks among the most severe heavy rainfall processes that induce disasters in recent years. The precipitation process is divided into three distinct stages, with warm-sector precipitation driven by a low vortex and low-level jet playing a dominant role in this heavy rainstorm. The instability mechanisms of warm-sector precipitation, as well as the triggering and maintenance of heavy precipitation, present significant challenges for operational forecasting and are the primary focus of this study. Based on conventional surface and upper-air meteorological observation data, ERA5 hourly reanalysis data, and radar data, this study analyses the water vapour conditions, atmospheric instability, and frontogenetic characteristics of this heavy rainfall event. The results indicate that the precipitation process in the warm sector of the low vortex primarily occurred within the low-level jet zone south of the warm shear region of the low vortex. The low-level jet provided ample water vapour conditions for precipitation, while a region of strong water vapour flux convergence north of the jet stream served as an effective indicator for heavy precipitation. At the onset of precipitation in the warm vortex region, strong convective instability was observed in the mid-to-lower troposphere, with upward motion initiated by the release of convective instability, exhibiting vertical convection characteristics. During the peak precipitation period, the ascending motion was influenced by both convective instability and symmetric instability, with symmetric instability being predominant, resulting in a combination of vertical and oblique convective processes. This precipitation process was accompanied by pronounced frontogenesis, featuring strong geostrophic wind deviation convergence in the frontogenesis region, which supplied essential dynamic uplift conditions for precipitation initiation and intensification. Analysis of the deformation term and divergence term in the frontogenesis function reveals that the divergence term was the main factor of frontogenesis in this process. Low-level convergence not only provided dynamic conditions for precipitation initiation but also integrated radar precipitation echoes with mesoscale convergence lines at the surface, influencing the morphology of cumulus precipitation echoes and forming mesoscale convective rainbands aligned along the guiding airflow. The mesoscale convective rainband moved along the guiding airflow, creating a “train effect” that resulted in heavy precipitation. These findings enhance operational forecasting capabilities for warm-sector precipitation associated with low vortices and similar processes, providing valuable insights for forecasters to develop systematic models of warm-sector precipitation weather systems.
2025, 53(4):585-594.
DOI: 10.19517/j.1671-6345.20240276
Abstract:
Based on the observation data of Shenyang X-band dual-polarisation phased-array radars (XPAR-D) and S-band radar (CINRAD/SC), combined with minutely precipitation data collected by automatic meteorological stations in Shenyang, this paper analyses the characteristics of a short-time heavy rainfall process that occurred in Shenyang on September 18, 2023. The results are as follows. The comparative observation results of XPAR-D were more detailed. However, its detection capability for weak radar echoes and those that were far away from the radar were weaker than that of the SC radar. The comparative observation results show that the SC radar had a larger coverage area and a more complete structure than XPAR-D. In the area with less influence of electromagnetic attenuation, the detection capabilities of the XPAR-D and SC radar in terms of the structure and intensity of the reflectivity factor and radial velocity were basically comparable. The area of strong echoes of the XPAR-D was wider, while the area of the region with high wind speed of the SC radar was larger. The rapid development and maintenance of the relatively strong echoes of XPAR-D, the relatively large values of CR and ZDR, as well as the sharp increase and maintenance of the KDP value jointly contributed to the occurrence of this short-time heavy rainfall. Before the precipitation started, the detection results of XPAR-D often showed large values of ZDR. The rapid increase of CR and the abnormally high value of ZDR had good indicative significance for the onset of precipitation. After the onset of the short-time heavy rainfall, there was a good corresponding relationship between CR and ZDR, which effectively indicated the duration and variation trend of the heavy precipitation. The sharp increase of KDP served as a warning for high values of minute precipitation, and the value of KDP more intuitively reflected the intensity of minute precipitation. During this short-time heavy rainfall process, the ZDR column in the XPAR-D observation results was located on the left side of the updraft of the convective cell, which corresponded well to the location of the weak echo area, and there was a separation phenomenon between the ZDR column and the KDP column. The high-value band of KDP value corresponded to the strong echo centre of the convective cell, and the KDP column corresponded to the heavy precipitation centre on the ground. Although the radial velocity results detected by XPAR-D during this short-time heavy rainfall event didn’t meet the criteria for a mesocyclone, they indicated that weak eddies also had the potential to enhance precipitation.
Based on the observation data of Shenyang X-band dual-polarisation phased-array radars (XPAR-D) and S-band radar (CINRAD/SC), combined with minutely precipitation data collected by automatic meteorological stations in Shenyang, this paper analyses the characteristics of a short-time heavy rainfall process that occurred in Shenyang on September 18, 2023. The results are as follows. The comparative observation results of XPAR-D were more detailed. However, its detection capability for weak radar echoes and those that were far away from the radar were weaker than that of the SC radar. The comparative observation results show that the SC radar had a larger coverage area and a more complete structure than XPAR-D. In the area with less influence of electromagnetic attenuation, the detection capabilities of the XPAR-D and SC radar in terms of the structure and intensity of the reflectivity factor and radial velocity were basically comparable. The area of strong echoes of the XPAR-D was wider, while the area of the region with high wind speed of the SC radar was larger. The rapid development and maintenance of the relatively strong echoes of XPAR-D, the relatively large values of CR and ZDR, as well as the sharp increase and maintenance of the KDP value jointly contributed to the occurrence of this short-time heavy rainfall. Before the precipitation started, the detection results of XPAR-D often showed large values of ZDR. The rapid increase of CR and the abnormally high value of ZDR had good indicative significance for the onset of precipitation. After the onset of the short-time heavy rainfall, there was a good corresponding relationship between CR and ZDR, which effectively indicated the duration and variation trend of the heavy precipitation. The sharp increase of KDP served as a warning for high values of minute precipitation, and the value of KDP more intuitively reflected the intensity of minute precipitation. During this short-time heavy rainfall process, the ZDR column in the XPAR-D observation results was located on the left side of the updraft of the convective cell, which corresponded well to the location of the weak echo area, and there was a separation phenomenon between the ZDR column and the KDP column. The high-value band of KDP value corresponded to the strong echo centre of the convective cell, and the KDP column corresponded to the heavy precipitation centre on the ground. Although the radial velocity results detected by XPAR-D during this short-time heavy rainfall event didn’t meet the criteria for a mesocyclone, they indicated that weak eddies also had the potential to enhance precipitation.
2025, 53(4):595-605.
DOI: 10.19517/j.1671-6345.20240337
Abstract:
Lightning, as one of the frequent natural disasters in China, poses significant meteorological hazards. Weather radar systems, with their inherent advantages of high spatiotemporal resolution, enable precise characterisation of lightning formation mechanisms and evolutionary patterns through synergistic integration with lightning detection datasets. This paper analyses lightning forecasting and early warning services in the eastern and western regions of China, using Shanghai and Kashgar as representatives. By leveraging multi-source observations, including lightning locators, weather radar mosaic products, and sounding data, an annual statistical analysis of the spatiotemporal distribution, three-dimensional characteristics of lightning, and their corresponding radar signatures is conducted in these two regions. The study explores the causes of the differences in lightning characteristics between the eastern and western regions. The results indicate that: (1) Both Shanghai and Kashgar exhibit concentrated lightning activity between May and September, with peak occurrences from afternoon to evening. Notably, Kashgar demonstrates distinct nocturnal characteristics in lightning distribution due to topographic effects. Geospatial analysis reveals contrasting spatial patterns: Shanghai’s lightning hotspots predominantly cluster over urbanised areas and land-water interfaces, whereas Kashgar’s lightning distribution shows strong orographic correlation, with maximum density zones located along the southern foothills of the Western Tianshan Mountains, eastern flanks of the Pamir Plateau, and northern slopes of the Kunlun Mountains. Statistically, the average lightning stroke density in Shanghai significantly surpasses that in Kashgar, maintaining a ratio of approximately 732.1∶1. (2) The combined reflectivity factor intensity, echo top height, and vertical liquid water content associated with lightning echo cells in Shanghai are markedly greater than those observed in Kashgar. The extension height of lightning echo cells in Shanghai is substantially higher than that in Kashgar. Notably, the 30 dBz, 35 dBz, and 40 dBz echo exceeding the -20 ℃, -10 ℃, and 0 ℃ layer height serves as a crucial indicator for lightning forecasting and early warning in Shanghai, whereas for Kashgar, the echo top height surpassing the -10 ℃ layer and the 30 dBz echo reaching the 0 ℃ layer hold greater predictive value. (3) Lightning activity is formed under the combined effects of three essential factors: sufficient atmospheric instability energy, dynamic lifting mechanisms, and adequate moisture supply. Comparative analysis reveals that during thunderstorm days, Shanghai exhibits significantly higher values of Most Unstable CAPE (MUCAPE), mid-level Relative Humidity (midRH), and Precipitable Water (PW) compared to Kashgar, while demonstrating lower Most Unstable Lifted Index (MULI) values. These meteorological parameters indicate stronger convective activity in Shanghai, where intense updrafts transport abundant moisture to upper colder layers. This enhanced vertical transport mechanism creates more favourable conditions for charge separation processes, making Shanghai more prone to lightning activity than Kashgar.
Lightning, as one of the frequent natural disasters in China, poses significant meteorological hazards. Weather radar systems, with their inherent advantages of high spatiotemporal resolution, enable precise characterisation of lightning formation mechanisms and evolutionary patterns through synergistic integration with lightning detection datasets. This paper analyses lightning forecasting and early warning services in the eastern and western regions of China, using Shanghai and Kashgar as representatives. By leveraging multi-source observations, including lightning locators, weather radar mosaic products, and sounding data, an annual statistical analysis of the spatiotemporal distribution, three-dimensional characteristics of lightning, and their corresponding radar signatures is conducted in these two regions. The study explores the causes of the differences in lightning characteristics between the eastern and western regions. The results indicate that: (1) Both Shanghai and Kashgar exhibit concentrated lightning activity between May and September, with peak occurrences from afternoon to evening. Notably, Kashgar demonstrates distinct nocturnal characteristics in lightning distribution due to topographic effects. Geospatial analysis reveals contrasting spatial patterns: Shanghai’s lightning hotspots predominantly cluster over urbanised areas and land-water interfaces, whereas Kashgar’s lightning distribution shows strong orographic correlation, with maximum density zones located along the southern foothills of the Western Tianshan Mountains, eastern flanks of the Pamir Plateau, and northern slopes of the Kunlun Mountains. Statistically, the average lightning stroke density in Shanghai significantly surpasses that in Kashgar, maintaining a ratio of approximately 732.1∶1. (2) The combined reflectivity factor intensity, echo top height, and vertical liquid water content associated with lightning echo cells in Shanghai are markedly greater than those observed in Kashgar. The extension height of lightning echo cells in Shanghai is substantially higher than that in Kashgar. Notably, the 30 dBz, 35 dBz, and 40 dBz echo exceeding the -20 ℃, -10 ℃, and 0 ℃ layer height serves as a crucial indicator for lightning forecasting and early warning in Shanghai, whereas for Kashgar, the echo top height surpassing the -10 ℃ layer and the 30 dBz echo reaching the 0 ℃ layer hold greater predictive value. (3) Lightning activity is formed under the combined effects of three essential factors: sufficient atmospheric instability energy, dynamic lifting mechanisms, and adequate moisture supply. Comparative analysis reveals that during thunderstorm days, Shanghai exhibits significantly higher values of Most Unstable CAPE (MUCAPE), mid-level Relative Humidity (midRH), and Precipitable Water (PW) compared to Kashgar, while demonstrating lower Most Unstable Lifted Index (MULI) values. These meteorological parameters indicate stronger convective activity in Shanghai, where intense updrafts transport abundant moisture to upper colder layers. This enhanced vertical transport mechanism creates more favourable conditions for charge separation processes, making Shanghai more prone to lightning activity than Kashgar.
2025, 53(4):606-616.
DOI: 10.19517/j.1671-6345.20240270
Abstract:
Based on the precipitation data from meteorological stations along the Baomao Expressway in Xiangxi Prefecture from 2016 to 2023, this study conducts a comprehensive analysis of the temporal and spatial distribution characteristics of precipitation along the expressway, including annual and monthly characteristics, various levels of precipitation characteristics, short-term heavy precipitation characteristics, continuous precipitation characteristics, and diurnal variation characteristics. By integrating precipitation data, geographic information data, and road data, an evaluation index system for the risk level of slope failures along the expressway is established from three aspects: precipitation factors, terrain environment factors, and road factors. The slope failure risk level zoning research of the Baomao Expressway in Xiangxi Prefecture is carried out using the Analytic Hierarchy Process (AHP) and the Natural Breakpoint Method. The results show that: (1) The annual average precipitation along the expressway shows a spatial distribution pattern of higher precipitation in the south and lower in the north. In 2020, precipitation is abundant, while in 2022 and 2023, precipitation is scarce. Precipitation mainly occurs from April to September, with an average monthly precipitation exceeding 140 mm, and the highest precipitation is in June, reaching 236 mm. (2) The average number of days with rainstorm and above precipitation at each station along the expressway is 4.5 days, with an average intensity of 77.7 mm/d. Short-term heavy precipitation shows significant differences in distribution, with the maximum being 80 mm/h and the minimum being 46 mm/h. The total frequency of continuous precipitation is the highest at GS56-2 (Longjingao) with 31 times, and the lowest at GS56-7 (Fenghuang) with less than one time per year. The peak precipitation occurs in the afternoon and after dusk, and the night rain feature is obvious. (3) The risk level of slope failures along the expressway is divided into four grades: high, relatively high, medium, and low. The overall risk shows a characteristic of being higher in the north than in the south. The high-risk and relatively high-risk areas of slope failures are distributed in sections such as Biancheng, Longjingao, Maliuchang, and Jixin. The low-risk areas are located near the Jishou Station and the Fenghuang Station. For high-risk and relatively high-risk areas, in terms of disaster prevention and mitigation, measures such as reinforcing the slope and taking drainage measures should be taken, and monitoring and early warning should be strengthened. The results of this study have certain guiding significance for the prevention of slope failure disasters along the Baomao Expressway in Xiangxi Prefecture.
Based on the precipitation data from meteorological stations along the Baomao Expressway in Xiangxi Prefecture from 2016 to 2023, this study conducts a comprehensive analysis of the temporal and spatial distribution characteristics of precipitation along the expressway, including annual and monthly characteristics, various levels of precipitation characteristics, short-term heavy precipitation characteristics, continuous precipitation characteristics, and diurnal variation characteristics. By integrating precipitation data, geographic information data, and road data, an evaluation index system for the risk level of slope failures along the expressway is established from three aspects: precipitation factors, terrain environment factors, and road factors. The slope failure risk level zoning research of the Baomao Expressway in Xiangxi Prefecture is carried out using the Analytic Hierarchy Process (AHP) and the Natural Breakpoint Method. The results show that: (1) The annual average precipitation along the expressway shows a spatial distribution pattern of higher precipitation in the south and lower in the north. In 2020, precipitation is abundant, while in 2022 and 2023, precipitation is scarce. Precipitation mainly occurs from April to September, with an average monthly precipitation exceeding 140 mm, and the highest precipitation is in June, reaching 236 mm. (2) The average number of days with rainstorm and above precipitation at each station along the expressway is 4.5 days, with an average intensity of 77.7 mm/d. Short-term heavy precipitation shows significant differences in distribution, with the maximum being 80 mm/h and the minimum being 46 mm/h. The total frequency of continuous precipitation is the highest at GS56-2 (Longjingao) with 31 times, and the lowest at GS56-7 (Fenghuang) with less than one time per year. The peak precipitation occurs in the afternoon and after dusk, and the night rain feature is obvious. (3) The risk level of slope failures along the expressway is divided into four grades: high, relatively high, medium, and low. The overall risk shows a characteristic of being higher in the north than in the south. The high-risk and relatively high-risk areas of slope failures are distributed in sections such as Biancheng, Longjingao, Maliuchang, and Jixin. The low-risk areas are located near the Jishou Station and the Fenghuang Station. For high-risk and relatively high-risk areas, in terms of disaster prevention and mitigation, measures such as reinforcing the slope and taking drainage measures should be taken, and monitoring and early warning should be strengthened. The results of this study have certain guiding significance for the prevention of slope failure disasters along the Baomao Expressway in Xiangxi Prefecture.
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Supported by:Beijing E-Tiller Technology Development Co., Ltd.