2022 Vol. 28, No. 3
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2022, 28(3): .
Abstract:
2022, 28(3): 261-272.
doi: 10.46267/j.1006-8775.2022.020
Abstract:
In this paper, an explosive cyclone (EC) that occurred over Northeast China in the spring of 2016 is studied by using 6.7 μm FY satellite water vapor (WV) imagery and NCEP (1°×1°) reanalysis data. Moreover, the evolutions of the upper-level jet stream (ULJ), the vertical motions, and the potential vorticity (PV) are analyzed in detail. Results show that different shapes of the WV image dark zones could reflect different stages of the EC. At the pre-explosion stage, a small dark zone and an S-shaped baroclinic leaf cloud can be found on the WV imagery. Then the dark zone expands and the leaf cloud grows into a comma-shaped cloud at the explosively developing stage. At the post-explosion stage, the dark zone brightens, and the spiral cloud forms. The whole process can be well described by the WV imagery. The dynamic dry band associated with the sinking motion and the ULJ can develop into the dry intrusion later, which is an important signal in forecasting the EC and should be paid attention to when analyzing the WV imagery. Furthermore, the mechanism is also analyzed in detail in this article. EC usually occurs in the left-exit region of the 200-hPa jet and the region ahead of the 500-hPa trough where there is significant positive vorticity advection (PVA). When the EC moves onto the sea surface, the decreased friction would favour the development of the EC. The upper-level PVA, the strong convergence at low level, and the divergence at high levels can maintain the strong updraft. Meanwhile, the high PV zone from the upper levels extends downward, approaching the cyclone. Together, they keep the cyclone deepening continuously.
In this paper, an explosive cyclone (EC) that occurred over Northeast China in the spring of 2016 is studied by using 6.7 μm FY satellite water vapor (WV) imagery and NCEP (1°×1°) reanalysis data. Moreover, the evolutions of the upper-level jet stream (ULJ), the vertical motions, and the potential vorticity (PV) are analyzed in detail. Results show that different shapes of the WV image dark zones could reflect different stages of the EC. At the pre-explosion stage, a small dark zone and an S-shaped baroclinic leaf cloud can be found on the WV imagery. Then the dark zone expands and the leaf cloud grows into a comma-shaped cloud at the explosively developing stage. At the post-explosion stage, the dark zone brightens, and the spiral cloud forms. The whole process can be well described by the WV imagery. The dynamic dry band associated with the sinking motion and the ULJ can develop into the dry intrusion later, which is an important signal in forecasting the EC and should be paid attention to when analyzing the WV imagery. Furthermore, the mechanism is also analyzed in detail in this article. EC usually occurs in the left-exit region of the 200-hPa jet and the region ahead of the 500-hPa trough where there is significant positive vorticity advection (PVA). When the EC moves onto the sea surface, the decreased friction would favour the development of the EC. The upper-level PVA, the strong convergence at low level, and the divergence at high levels can maintain the strong updraft. Meanwhile, the high PV zone from the upper levels extends downward, approaching the cyclone. Together, they keep the cyclone deepening continuously.
2022, 28(3): 273-285.
doi: 10.46267/j.1006-8775.2022.021
Abstract:
The extremely heavy Meiyu in the middle and lower reaches of the Yangtze River in 2020 features early beginning, extremely late retreat, long duration, and a dramatic north-south swing rain belt. It can be divided into three phases. The key point of the extremely heavy Meiyu is the long duration of precipitation. The physical mechanism of the phased variation is researched here by analyzing the phased evolution of atmospheric circulation, the thermal effect of Tibetan Plateau, the sea surface temperature anomalies (SSTA), and tropical convection. The results show that: (1) Throughout the whole Meiyu season, the western Pacific subtropical high (WPSH) is stronger and westward, the South Asian high (SAH) is stronger and eastward, and blocking highs are very active with different patterns at different stages; they all form flat mid-latitude westerlies with fluctuation interacting with WPSH and SAH, causing their ridges and the rain belt to swing drastically from north to south or vice versa. (2) The higher temperatures in the upper and middle atmosphere in the eastern and southern Tibetan Plateau and the middle and lower reaches of the Yangtze River, which are produced by the warm advection transport, the heat sources in Tibetan Plateau, and the latent heat of condensation of Meiyu, contribute greatly to the stronger and westward WPSH and the stronger and eastward SAH. The dry-cold air brought by the fluctuating westerlies converges with the warm-humid air over Tibetan Plateau, resulting in precipitation, which in turn enhances the heat source of Tibetan Plateau and regulates the swings of WPSH and SAH. (3) Different from climatological analysis, real-time SSTA in the Indian Ocean has no obviously direct effect on WPSH and Meiyu. The anomalous distribution and phased evolution process of real-time SSTA in South China Sea and the tropical western Pacific affect WPSH and Meiyu significantly through tropical convection and heat sources. The maintenance of strong positive SSTA in the western equatorial Pacific is a critical reason for the prolonged Meiyu season. Both the onset and the retreat of Meiyu in 2020 are closely related to the intensified positive SSTA and corresponding typhoons on the ocean east of the Philippines.
The extremely heavy Meiyu in the middle and lower reaches of the Yangtze River in 2020 features early beginning, extremely late retreat, long duration, and a dramatic north-south swing rain belt. It can be divided into three phases. The key point of the extremely heavy Meiyu is the long duration of precipitation. The physical mechanism of the phased variation is researched here by analyzing the phased evolution of atmospheric circulation, the thermal effect of Tibetan Plateau, the sea surface temperature anomalies (SSTA), and tropical convection. The results show that: (1) Throughout the whole Meiyu season, the western Pacific subtropical high (WPSH) is stronger and westward, the South Asian high (SAH) is stronger and eastward, and blocking highs are very active with different patterns at different stages; they all form flat mid-latitude westerlies with fluctuation interacting with WPSH and SAH, causing their ridges and the rain belt to swing drastically from north to south or vice versa. (2) The higher temperatures in the upper and middle atmosphere in the eastern and southern Tibetan Plateau and the middle and lower reaches of the Yangtze River, which are produced by the warm advection transport, the heat sources in Tibetan Plateau, and the latent heat of condensation of Meiyu, contribute greatly to the stronger and westward WPSH and the stronger and eastward SAH. The dry-cold air brought by the fluctuating westerlies converges with the warm-humid air over Tibetan Plateau, resulting in precipitation, which in turn enhances the heat source of Tibetan Plateau and regulates the swings of WPSH and SAH. (3) Different from climatological analysis, real-time SSTA in the Indian Ocean has no obviously direct effect on WPSH and Meiyu. The anomalous distribution and phased evolution process of real-time SSTA in South China Sea and the tropical western Pacific affect WPSH and Meiyu significantly through tropical convection and heat sources. The maintenance of strong positive SSTA in the western equatorial Pacific is a critical reason for the prolonged Meiyu season. Both the onset and the retreat of Meiyu in 2020 are closely related to the intensified positive SSTA and corresponding typhoons on the ocean east of the Philippines.
2022, 28(3): 286-296.
doi: 10.46267/j.1006-8775.2022.022
Abstract:
The Dynamical-Statistical-Analog Ensemble Forecast model for landfalling tropical cyclones (TCs) precipitation (DSAEF_LTP) utilises an operational numerical weather prediction (NWP) model for the forecast track, while the precipitation forecast is obtained by finding analog cyclones, and making a precipitation forecast from an ensemble of the analogs. This study addresses TCs that occurred from 2004 to 2019 in Southeast China with 47 TCs as training samples and 18 TCs for independent forecast experiments. Experiments use four model versions. The control experiment DSAEF_LTP_1 includes three factors including TC track, landfall season, and TC intensity to determine analogs. Versions DSAEF_LTP_2, DSAEF_LTP_3, and DSAEF_LTP_4 respectively integrate improved similarity region, improved ensemble method, and improvements in both parameters. Results show that the DSAEF_LTP model with new values of similarity region and ensemble method (DSAEF_LTP_4) performs best in the simulation experiment, while the DSAEF_LTP model with new values only of ensemble method (DSAEF_LTP_3) performs best in the forecast experiment. The reason for the difference between simulation (training sample) and forecast (independent sample) may be that the proportion of TC with typical tracks (southeast to northwest movement or landfall over Southeast China) has changed significantly between samples. Forecast performance is compared with that of three global dynamical models (ECMWF, GRAPES, and GFS) and a regional dynamical model (SMS-WARMS). The DSAEF_LTP model performs better than the dynamical models and tends to produce more false alarms in accumulated forecast precipitation above 250 mm and 100 mm. Compared with TCs without heavy precipitation or typical tracks, TCs with these characteristics are better forecasted by the DSAEF_LTP model.
The Dynamical-Statistical-Analog Ensemble Forecast model for landfalling tropical cyclones (TCs) precipitation (DSAEF_LTP) utilises an operational numerical weather prediction (NWP) model for the forecast track, while the precipitation forecast is obtained by finding analog cyclones, and making a precipitation forecast from an ensemble of the analogs. This study addresses TCs that occurred from 2004 to 2019 in Southeast China with 47 TCs as training samples and 18 TCs for independent forecast experiments. Experiments use four model versions. The control experiment DSAEF_LTP_1 includes three factors including TC track, landfall season, and TC intensity to determine analogs. Versions DSAEF_LTP_2, DSAEF_LTP_3, and DSAEF_LTP_4 respectively integrate improved similarity region, improved ensemble method, and improvements in both parameters. Results show that the DSAEF_LTP model with new values of similarity region and ensemble method (DSAEF_LTP_4) performs best in the simulation experiment, while the DSAEF_LTP model with new values only of ensemble method (DSAEF_LTP_3) performs best in the forecast experiment. The reason for the difference between simulation (training sample) and forecast (independent sample) may be that the proportion of TC with typical tracks (southeast to northwest movement or landfall over Southeast China) has changed significantly between samples. Forecast performance is compared with that of three global dynamical models (ECMWF, GRAPES, and GFS) and a regional dynamical model (SMS-WARMS). The DSAEF_LTP model performs better than the dynamical models and tends to produce more false alarms in accumulated forecast precipitation above 250 mm and 100 mm. Compared with TCs without heavy precipitation or typical tracks, TCs with these characteristics are better forecasted by the DSAEF_LTP model.
2022, 28(3): 297-307.
doi: 10.46267/j.1006-8775.2022.023
Abstract:
In the present study, we analyzed the chemical properties and factors impacting the sea fog water during two sea fog events over the northwestern South China Sea in March 2017, and compared our results with those of other regions. The sea fog water during these two events were highly acidic and their average pH was below 3, which was related to the high initial acidifying potential and large amounts of NO3- and SO42- not involved in the neutralization reaction. The dominant cations in the sea fog water were Na+ and NH4+. The primary anions in the sea fog water over the South China Sea were Cl- and NO3-, while that over the North Pacific Ocean was mainly SO42-, and ratios of the three fog water ions near the Donghai Island were similar. Ions in the sea fog water during the two events were mainly derived from marine aerosols, while the difference was that the first low-level sea fog airflow trajectory passed over Hainan Island. Therefore, the proportion of K+ in the first sea fog was much higher than that in sea water and the second. Sulfate was the key to fog water nucleation, which made ion concentration in the sea fog water during the second event higher than that during the first. A decrease in average diameter during the first sea fog formation led to an ion concentration increase, while the average diameter of sea fog water during the second event was lower than that during the first, which corresponded with a moderate ion concentration increase.
In the present study, we analyzed the chemical properties and factors impacting the sea fog water during two sea fog events over the northwestern South China Sea in March 2017, and compared our results with those of other regions. The sea fog water during these two events were highly acidic and their average pH was below 3, which was related to the high initial acidifying potential and large amounts of NO3- and SO42- not involved in the neutralization reaction. The dominant cations in the sea fog water were Na+ and NH4+. The primary anions in the sea fog water over the South China Sea were Cl- and NO3-, while that over the North Pacific Ocean was mainly SO42-, and ratios of the three fog water ions near the Donghai Island were similar. Ions in the sea fog water during the two events were mainly derived from marine aerosols, while the difference was that the first low-level sea fog airflow trajectory passed over Hainan Island. Therefore, the proportion of K+ in the first sea fog was much higher than that in sea water and the second. Sulfate was the key to fog water nucleation, which made ion concentration in the sea fog water during the second event higher than that during the first. A decrease in average diameter during the first sea fog formation led to an ion concentration increase, while the average diameter of sea fog water during the second event was lower than that during the first, which corresponded with a moderate ion concentration increase.
2022, 28(3): 308-325.
doi: 10.46267/j.1006-8775.2022.024
Abstract:
An unprecedented heavy rainfall event occurred in Henan Province, China, during the period of 1200 UTC 19-1200 UTC 20 July 2021 with a record of 522 mm accumulated rainfall. Zhengzhou, the capital city of Henan, received 201.9 mm of rainfall in just one hour on the day. In the present study, the sensitivity of this event to atmospheric variables is investigated using the ECMWF ensemble forecasts. The sensitivity analysis first indicates that a local YellowHuai River low vortex (YHV) in the southern part of Henan played a crucial role in this extreme event. Meanwhile, the western Pacific subtropical high (WPSH) was stronger than the long-term average and to the west of its climatological position. Moreover, the existence of a tropical cyclone (TC) In-Fa pushed into the peripheral of the WPSH and brought an enhanced easterly flow between the TC and WPSH channeling abundant moisture to inland China and feeding into the YHV. Members of the ECMWF ensemble are selected and grouped into the GOOD and the POOR groups based on their predicted maximum rainfall accumulations during the event. Some good members of ECMWF ensemble Prediction System (ECMWF-EPS) are able to capture good spatial distribution of the heavy rainfall, but still underpredict its extremity. The better prediction ability of these members comes from the better prediction of the evolution characteristics (i.e., intensity and location) of the YHV and TC In-Fa. When the YHV was moving westward to the south of Henan, a relatively strong southerly wind in the southwestern part of Henan converged with the easterly flow from the channel wind between In-Fa and WPSH. The convergence and accompanying ascending motion induced heavy precipitation.
An unprecedented heavy rainfall event occurred in Henan Province, China, during the period of 1200 UTC 19-1200 UTC 20 July 2021 with a record of 522 mm accumulated rainfall. Zhengzhou, the capital city of Henan, received 201.9 mm of rainfall in just one hour on the day. In the present study, the sensitivity of this event to atmospheric variables is investigated using the ECMWF ensemble forecasts. The sensitivity analysis first indicates that a local YellowHuai River low vortex (YHV) in the southern part of Henan played a crucial role in this extreme event. Meanwhile, the western Pacific subtropical high (WPSH) was stronger than the long-term average and to the west of its climatological position. Moreover, the existence of a tropical cyclone (TC) In-Fa pushed into the peripheral of the WPSH and brought an enhanced easterly flow between the TC and WPSH channeling abundant moisture to inland China and feeding into the YHV. Members of the ECMWF ensemble are selected and grouped into the GOOD and the POOR groups based on their predicted maximum rainfall accumulations during the event. Some good members of ECMWF ensemble Prediction System (ECMWF-EPS) are able to capture good spatial distribution of the heavy rainfall, but still underpredict its extremity. The better prediction ability of these members comes from the better prediction of the evolution characteristics (i.e., intensity and location) of the YHV and TC In-Fa. When the YHV was moving westward to the south of Henan, a relatively strong southerly wind in the southwestern part of Henan converged with the easterly flow from the channel wind between In-Fa and WPSH. The convergence and accompanying ascending motion induced heavy precipitation.
2022, 28(3): 326-342.
doi: 10.46267/j.1006-8775.2022.025
Abstract:
As a typical physical retrieval algorithm for retrieving atmospheric parameters, one-dimensional variational (1DVAR) algorithm is widely used in various climate and meteorological communities and enjoys an important position in the field of microwave remote sensing. Among algorithm parameters affecting the performance of the 1DVAR algorithm, the accuracy of the microwave radiative transfer model for calculating the simulated brightness temperature is the fundamental constraint on the retrieval accuracies of the 1DVAR algorithm for retrieving atmospheric parameters. In this study, a deep neural network (DNN) is used to describe the nonlinear relationship between atmospheric parameters and satellite-based microwave radiometer observations, and a DNN-based radiative transfer model is developed and applied to the 1DVAR algorithm to carry out retrieval experiments of the atmospheric temperature and humidity profiles. The retrieval results of the temperature and humidity profiles from the Microwave Humidity and Temperature Sounder (MWHTS) onboard the Feng-Yun-3 (FY-3) satellite show that the DNN-based radiative transfer model can obtain higher accuracy for simulating MWHTS observations than that of the operational radiative transfer model RTTOV, and also enables the 1DVAR algorithm to obtain higher retrieval accuracies of the temperature and humidity profiles. In this study, the DNN-based radiative transfer model applied to the 1DVAR algorithm can fundamentally improve the retrieval accuracies of atmospheric parameters, which may provide important reference for various applied studies in atmospheric sciences.
As a typical physical retrieval algorithm for retrieving atmospheric parameters, one-dimensional variational (1DVAR) algorithm is widely used in various climate and meteorological communities and enjoys an important position in the field of microwave remote sensing. Among algorithm parameters affecting the performance of the 1DVAR algorithm, the accuracy of the microwave radiative transfer model for calculating the simulated brightness temperature is the fundamental constraint on the retrieval accuracies of the 1DVAR algorithm for retrieving atmospheric parameters. In this study, a deep neural network (DNN) is used to describe the nonlinear relationship between atmospheric parameters and satellite-based microwave radiometer observations, and a DNN-based radiative transfer model is developed and applied to the 1DVAR algorithm to carry out retrieval experiments of the atmospheric temperature and humidity profiles. The retrieval results of the temperature and humidity profiles from the Microwave Humidity and Temperature Sounder (MWHTS) onboard the Feng-Yun-3 (FY-3) satellite show that the DNN-based radiative transfer model can obtain higher accuracy for simulating MWHTS observations than that of the operational radiative transfer model RTTOV, and also enables the 1DVAR algorithm to obtain higher retrieval accuracies of the temperature and humidity profiles. In this study, the DNN-based radiative transfer model applied to the 1DVAR algorithm can fundamentally improve the retrieval accuracies of atmospheric parameters, which may provide important reference for various applied studies in atmospheric sciences.
2022, 28(3): 343-363.
doi: 10.46267/j.1006-8775.2022.026
Abstract:
Based on the observational hourly precipitation data and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) products from 2006 to 2020, 22 rainstorm processes in the eastern foot of Helan Mountain are objectively classified by using the hierarchical clustering method, and the circulation characteristics of different patterns are comparatively analyzed in this study. The results show that the occurrences of rainstorm processes in the eastern foot of Helan Mountain are most closely related to three circulation patterns. Patterns Ⅰ and Ⅲ mainly occur in July and August, with similar zonal circulations in synoptic backgrounds. Specifically, the South Asia high and the western Pacific subtropical high are stronger and more northward than those in normal years. The frontal systems in westerlies are inactive, while the water vapor from the ocean surface in the south is mainly transported to the rainstorm area by the southerly jet stream at 700 hPa. The dynamic lifting anomalies are relatively weak, the instability of atmospheric stratification is anomalously strong, and thus the localized severe convective rainstorm is more significant. Comparatively, rainstorm processes of pattern Ⅰ are accompanied by stronger and deeper ascending motions, and the warm-sector rainstorm is more extreme. Pattern Ⅲ shows a stronger and deeper convective instability, accompanied by larger low-level moisture. Rainstorm processes of pattern Ⅱ mainly occur in early summer and early autumn, presenting a meridional circulation pattern of high in the east and low in the west in terms of geopotential height. Moreover, the two low-level jets transporting the water vapor northward from the ocean on the east of China encounter with the frontal systems in westerlies, which makes the ascending motion in pattern Ⅱ anomalously strong and deep. The relatively weak instability of atmospheric stratification causes weak convection and long-lasting precipitation formed by the confluence of cold air and warm air. This study may help improve rainstorm forecasting in arid regions.
Based on the observational hourly precipitation data and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) products from 2006 to 2020, 22 rainstorm processes in the eastern foot of Helan Mountain are objectively classified by using the hierarchical clustering method, and the circulation characteristics of different patterns are comparatively analyzed in this study. The results show that the occurrences of rainstorm processes in the eastern foot of Helan Mountain are most closely related to three circulation patterns. Patterns Ⅰ and Ⅲ mainly occur in July and August, with similar zonal circulations in synoptic backgrounds. Specifically, the South Asia high and the western Pacific subtropical high are stronger and more northward than those in normal years. The frontal systems in westerlies are inactive, while the water vapor from the ocean surface in the south is mainly transported to the rainstorm area by the southerly jet stream at 700 hPa. The dynamic lifting anomalies are relatively weak, the instability of atmospheric stratification is anomalously strong, and thus the localized severe convective rainstorm is more significant. Comparatively, rainstorm processes of pattern Ⅰ are accompanied by stronger and deeper ascending motions, and the warm-sector rainstorm is more extreme. Pattern Ⅲ shows a stronger and deeper convective instability, accompanied by larger low-level moisture. Rainstorm processes of pattern Ⅱ mainly occur in early summer and early autumn, presenting a meridional circulation pattern of high in the east and low in the west in terms of geopotential height. Moreover, the two low-level jets transporting the water vapor northward from the ocean on the east of China encounter with the frontal systems in westerlies, which makes the ascending motion in pattern Ⅱ anomalously strong and deep. The relatively weak instability of atmospheric stratification causes weak convection and long-lasting precipitation formed by the confluence of cold air and warm air. This study may help improve rainstorm forecasting in arid regions.
2022, 28(3): 364-376.
doi: 10.46267/j.1006-8775.2022.027
Abstract:
Based on prior investigation, this work defined a new thermodynamic shear advection parameter, which combines the vertical component of convective vorticity vector, horizontal divergence, and vertical gradient of generalized potential temperature. The interaction between waves and fundamental states was computed for the heavy-rainfall event generated by landfalling typhoon"Morakot". The analysis data was produced by ADAS [ARPS (Advanced Regional Prediction System) Data Analysis System] combined with the NCEP / NCAR final analysis data (1° × 1°, 26 vertical pressure levels and 6-hour interval) with the routine observations of surface and sounding. Because it may describe the typical vertical structure of dynamical and thermodynamic fields, the result indicates that the parameter is intimately related to precipitation systems. The parameter's positive high-value area closely matches the reported 6-hour accumulated surface rainfall. And the statistical analysis reveals a certain correspondence between the thermodynamic shear advection parameter and the observed 6-hour accumulated surface rainfall in the summer of 2009. This implies that the parameter can predict and indicate the rainfall area, as well as the initiation and evolution of precipitation systems.
Based on prior investigation, this work defined a new thermodynamic shear advection parameter, which combines the vertical component of convective vorticity vector, horizontal divergence, and vertical gradient of generalized potential temperature. The interaction between waves and fundamental states was computed for the heavy-rainfall event generated by landfalling typhoon"Morakot". The analysis data was produced by ADAS [ARPS (Advanced Regional Prediction System) Data Analysis System] combined with the NCEP / NCAR final analysis data (1° × 1°, 26 vertical pressure levels and 6-hour interval) with the routine observations of surface and sounding. Because it may describe the typical vertical structure of dynamical and thermodynamic fields, the result indicates that the parameter is intimately related to precipitation systems. The parameter's positive high-value area closely matches the reported 6-hour accumulated surface rainfall. And the statistical analysis reveals a certain correspondence between the thermodynamic shear advection parameter and the observed 6-hour accumulated surface rainfall in the summer of 2009. This implies that the parameter can predict and indicate the rainfall area, as well as the initiation and evolution of precipitation systems.
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