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, Available online ,
doi: 10.3878/j.issn.1006-9895.2201.21204
Abstract:
Utilizing the raindrop spectrum observation data from Urumqi, Xinjiang, collected between 3 July and 3 October 2018, this study aimed to enhance the WRF Single-Moment 6-class (WSM6) scheme in the Urumqi regional high-resolution numerical prediction system. The improved scheme’s effectiveness in predicting heavy precipitation events was evaluated in Xinjiang from 1200 BJT (Beijing time) on 15 June to 0000 BJT on 17 June 2021. The results indicated that the average diameter (D0), maximum diameter (Dmax), and mass-weighted average diameter (Dm) of raindrops in Urumqi were 0.65 mm, 1.60 mm, and 0.93 mm, respectively. Furthermore, the refined WSM6-new scheme, which considered the fitting relationship between parameters lgNw and Dm in Xinjiang, enhanced the prediction capability for precipitation intensity and strong center ranges to some extent. Evaluation metrics, such as TS, BR, ETS, and TSS, revealed that with the WSM6-new scheme significantly improved the prediction accuracy as precipitation grade increased, specifically for heavy and torrential rainfall. Different raindrop size distribution parameter schemes influenced precipitation cloud systems characteristics, vertical velocities, atmospheric stratification, and divergence field. Moreover, the effect on cloud microphysical processes primarily manifested in rainwater content and distribution. The WSM6-new scheme incorporated the statistical characteristics of Xinjiang’s raindrop spectrum, rendering the raindrop size distribution in the model more accurate. The number concentration of larger raindrops in the raindrop spectrum increased significantly, along with terminal raindrop velocity and enhanced drag effects. This facilitated the intensification and maintenance of downdraft below the freezing level. The strong downdraft generated a powerful divergent outflow near the ground layer, which intensified air convergence in the ground-level convection area, promoting updraft development and strengthening. Consequently, a more intense precipitation process occurred at the surface, and the prediction capability for heavy rain and torrential rain was remarkably enhanced.
Utilizing the raindrop spectrum observation data from Urumqi, Xinjiang, collected between 3 July and 3 October 2018, this study aimed to enhance the WRF Single-Moment 6-class (WSM6) scheme in the Urumqi regional high-resolution numerical prediction system. The improved scheme’s effectiveness in predicting heavy precipitation events was evaluated in Xinjiang from 1200 BJT (Beijing time) on 15 June to 0000 BJT on 17 June 2021. The results indicated that the average diameter (D0), maximum diameter (Dmax), and mass-weighted average diameter (Dm) of raindrops in Urumqi were 0.65 mm, 1.60 mm, and 0.93 mm, respectively. Furthermore, the refined WSM6-new scheme, which considered the fitting relationship between parameters lgNw and Dm in Xinjiang, enhanced the prediction capability for precipitation intensity and strong center ranges to some extent. Evaluation metrics, such as TS, BR, ETS, and TSS, revealed that with the WSM6-new scheme significantly improved the prediction accuracy as precipitation grade increased, specifically for heavy and torrential rainfall. Different raindrop size distribution parameter schemes influenced precipitation cloud systems characteristics, vertical velocities, atmospheric stratification, and divergence field. Moreover, the effect on cloud microphysical processes primarily manifested in rainwater content and distribution. The WSM6-new scheme incorporated the statistical characteristics of Xinjiang’s raindrop spectrum, rendering the raindrop size distribution in the model more accurate. The number concentration of larger raindrops in the raindrop spectrum increased significantly, along with terminal raindrop velocity and enhanced drag effects. This facilitated the intensification and maintenance of downdraft below the freezing level. The strong downdraft generated a powerful divergent outflow near the ground layer, which intensified air convergence in the ground-level convection area, promoting updraft development and strengthening. Consequently, a more intense precipitation process occurred at the surface, and the prediction capability for heavy rain and torrential rain was remarkably enhanced.
, Available online ,
doi: 10.3878/j.issn.1006-9895.2110.21133
Abstract:
This paper investigates flooding events caused by heavy precipitation and the corresponding 15 heavy rainfall events in the Sichuan-Chongqing area in the summer of 2020 and compares them with the situation in the 2006 drought year. The western Pacific subtropical high (WPSH) was stronger than its climatological mean, and its western edge was beyond 110°E, which is to the west of its climatological position. Since the Qinghai–Tibet high was strong and extended eastward, the upper and lower layers worked together to keep the WPSH stable. The cold air that causes precipitation in the Sichuan–Chongqing region is primarily caused by short waves in the westerlies. Short waves were frequent in the mid-latitudes and influenced the region. The Sichuan–Chongqing region forms an area of major water vapor flux convergence due to the joint influence of the southwesterly flows on the western flank of WPSH and the northerly wind. It provides the best water vapor conditions for the occurrence of heavy rainfall events. Furthermore, the monsoon air stream, which travels from northern India to the east side of the plateau, rounds the south side of the plateau and transports water vapor eastward, forming another important water vapor channel. 2006 was a typical drought year in the Sichuan-Chongqing region, with the fewest heavy rainfall events. In contrast with 2020, the WPSH is easterly this year, the short-wave trough in mid-latitude westerlies is less active, the southwest monsoon is weaker, and water vapor convergence in the Sichuan–Chongqing region is lower.
This paper investigates flooding events caused by heavy precipitation and the corresponding 15 heavy rainfall events in the Sichuan-Chongqing area in the summer of 2020 and compares them with the situation in the 2006 drought year. The western Pacific subtropical high (WPSH) was stronger than its climatological mean, and its western edge was beyond 110°E, which is to the west of its climatological position. Since the Qinghai–Tibet high was strong and extended eastward, the upper and lower layers worked together to keep the WPSH stable. The cold air that causes precipitation in the Sichuan–Chongqing region is primarily caused by short waves in the westerlies. Short waves were frequent in the mid-latitudes and influenced the region. The Sichuan–Chongqing region forms an area of major water vapor flux convergence due to the joint influence of the southwesterly flows on the western flank of WPSH and the northerly wind. It provides the best water vapor conditions for the occurrence of heavy rainfall events. Furthermore, the monsoon air stream, which travels from northern India to the east side of the plateau, rounds the south side of the plateau and transports water vapor eastward, forming another important water vapor channel. 2006 was a typical drought year in the Sichuan-Chongqing region, with the fewest heavy rainfall events. In contrast with 2020, the WPSH is easterly this year, the short-wave trough in mid-latitude westerlies is less active, the southwest monsoon is weaker, and water vapor convergence in the Sichuan–Chongqing region is lower.
, Available online ,
doi: 10.3878/j.issn.1006-9895.2202.21129
Abstract:
Using NCEP/NCAR reanalysis data, ERA5 vertical integrated water vapor flux data, and NOAA monthly mean SST (sea surface temperature) data, the interdecadal variations in the relationship between central and eastern tropical Pacific SSTs and East Asian WVT (water vapor transport) in December and February from 1950 to 2019 were investigated. The finding reveals that the correlation between East Asian meridional WVT and central and eastern tropical Pacific SSTs in December was weak before the mid-1980s, becoming significantly positive afterward. In February, the correlation was significantly positive during 1950–1970 and 1990–2010. Interdecadal variations in the relationship between East Asian meridional WVT and central and eastern tropical Pacific SSTs in December stem from the increased influence of Pacific–East Asian (PEA) teleconnection and Northern Hemisphere circumglobal teleconnections on East Asian meridional WVT, driven by tropical SSTs after the mid-1980s. The PEA teleconnection and Northern Hemisphere circumglobal teleconnection would induce anomalous southerly WVT over East Asia, corresponding to warm SST anomalies in the central and eastern tropical Pacific. Unlike December, the relationship between the two factors in February was primarily modulated by the PEA teleconnection during 1950–1970 and 1990–2010. However, from 1971 to 1989, East Asian WVT was influenced by the circumglobal teleconnection in the Northern Hemisphere, corresponding to cold SST anomalies in the central and eastern tropical Pacific. This resulted in an insignificant relationship between the two factors during 1971–1989, as the above mechanism counteracted the effect of the PEA teleconnection. Furthermore, the impact of tropical Indian Ocean SSTs on East Asian WVT in December and February increased after 1990. In December, East Asian WVT was modulated by the Kelvin wave-induced Ekman divergence mechanism, while in February, it was influenced by the Walker circulation over the Indian Ocean, corresponding to warm SST anomalies in the tropical Indian Ocean.
Using NCEP/NCAR reanalysis data, ERA5 vertical integrated water vapor flux data, and NOAA monthly mean SST (sea surface temperature) data, the interdecadal variations in the relationship between central and eastern tropical Pacific SSTs and East Asian WVT (water vapor transport) in December and February from 1950 to 2019 were investigated. The finding reveals that the correlation between East Asian meridional WVT and central and eastern tropical Pacific SSTs in December was weak before the mid-1980s, becoming significantly positive afterward. In February, the correlation was significantly positive during 1950–1970 and 1990–2010. Interdecadal variations in the relationship between East Asian meridional WVT and central and eastern tropical Pacific SSTs in December stem from the increased influence of Pacific–East Asian (PEA) teleconnection and Northern Hemisphere circumglobal teleconnections on East Asian meridional WVT, driven by tropical SSTs after the mid-1980s. The PEA teleconnection and Northern Hemisphere circumglobal teleconnection would induce anomalous southerly WVT over East Asia, corresponding to warm SST anomalies in the central and eastern tropical Pacific. Unlike December, the relationship between the two factors in February was primarily modulated by the PEA teleconnection during 1950–1970 and 1990–2010. However, from 1971 to 1989, East Asian WVT was influenced by the circumglobal teleconnection in the Northern Hemisphere, corresponding to cold SST anomalies in the central and eastern tropical Pacific. This resulted in an insignificant relationship between the two factors during 1971–1989, as the above mechanism counteracted the effect of the PEA teleconnection. Furthermore, the impact of tropical Indian Ocean SSTs on East Asian WVT in December and February increased after 1990. In December, East Asian WVT was modulated by the Kelvin wave-induced Ekman divergence mechanism, while in February, it was influenced by the Walker circulation over the Indian Ocean, corresponding to warm SST anomalies in the tropical Indian Ocean.
, Available online ,
doi: 10.3878/j.issn.1006-9895.2206.21090
Abstract:
Based on the CMA-MESO (China Meteorological Administration MESOscale weather forecast system) horizontal 3 km resolution 3 h cycle rapid update assimilation and forecast system, an hourly cycle analysis and forecast system was established. In this system, the background error correlation structure is improved by adopting a Gaussian correlation model with five-scale superimposition and introducing an anisotropic correlation scale scheme, and the impact of introducing a global large-scale information scheme on the analysis and forecast of the hourly cycle is examined. Numerical simulations of the strong convective case in eastern China on July 19, 2020, show that: (1) The hourly cycle absorbs more high-frequency observations and uses the more proximate 1 h forecast field as the background field in the cycle, which improves the quality of analysis and short-range forecasts compared to the 3 h cycle. (2) The introduction of large-scale information from the global forecast field to the hourly cycle regional analysis can weaken the influence of regional observations, which can negatively affect forecasting. (3) The improved five-scale superimposed Gaussian correlation model and the anisotropic horizontal correlation scale make the representation of the background error horizontal correlation coefficients of wind variables closer to the statistical results of the samples. Thus, the analyzed wind fields are closer to the observations in the hourly cycle, and the composite reflectivity and short-term precipitation forecasting of the strong convective process in Eastern China are closer to the real situation.
Based on the CMA-MESO (China Meteorological Administration MESOscale weather forecast system) horizontal 3 km resolution 3 h cycle rapid update assimilation and forecast system, an hourly cycle analysis and forecast system was established. In this system, the background error correlation structure is improved by adopting a Gaussian correlation model with five-scale superimposition and introducing an anisotropic correlation scale scheme, and the impact of introducing a global large-scale information scheme on the analysis and forecast of the hourly cycle is examined. Numerical simulations of the strong convective case in eastern China on July 19, 2020, show that: (1) The hourly cycle absorbs more high-frequency observations and uses the more proximate 1 h forecast field as the background field in the cycle, which improves the quality of analysis and short-range forecasts compared to the 3 h cycle. (2) The introduction of large-scale information from the global forecast field to the hourly cycle regional analysis can weaken the influence of regional observations, which can negatively affect forecasting. (3) The improved five-scale superimposed Gaussian correlation model and the anisotropic horizontal correlation scale make the representation of the background error horizontal correlation coefficients of wind variables closer to the statistical results of the samples. Thus, the analyzed wind fields are closer to the observations in the hourly cycle, and the composite reflectivity and short-term precipitation forecasting of the strong convective process in Eastern China are closer to the real situation.
Statistical Characteristics of Tropical Cyclone Gale and Its Accompanying Weather in Southeast China
, Available online ,
doi: 10.3878/j.issn.1006-9895.2110.21136
Abstract:
The China Meteorological Administration (CMA) tropical cyclone best track data and hour-by-hour precipitation data from 2010 to 2016 were used in a statistical analysis of surface gales and their accompanying weather in southeastern China under the influence of tropical cyclones (TCs), and the results show that: (1) In this region, TC gale is primarily dispersed along the coastline, with decreasing frequency from coast to inland; TC gale is dominated by the northeast wind direction, and the gale occurs primarily before the typhoon landfall. Strong wind speeds of magnitude 12 and higher are scattered within 300 km of the TC center; (2) TCs of tropical storm (TS) and typhoon (TY) intensity caused the most gales, while strong wind speeds of magnitude 16 and above are mainly found in the severe typhoon (STY) and super typhoon (Super TY) intensity classes. Gale induced by slow TC appears primarily on the right front side, while gale caused by quick TC appears primarily on the right rear side. The mean onshore wind speed of TC gales is slightly greater than the offshore wind speed, despite the fact that the station frequency of onshore wind is greater than that of offshore wind when the wind speed is between level 12 and level 16, and when the wind speed is above level 16, offshore wind is much greater than that of onshore wind; (3) The percentage of TC gales that are precipitation-accompanied accounts for roughly 89.8% of the total number of TC gales; these gales are primarily caused by northeasterly winds, peaking in August. About 10.2% of the TC’s gales are dry, with the majority occurring at the TC’s periphery with weak northerly and southeasterly winds, primarily in May and December. TC gales with wind speeds above level 12 are almost always accompanied by precipitation, while there are few samples of TC gales with wind speeds above 12 without precipitation; (4) TC gales accompanied by strong convective weather account for approximately 23.8% of the total TC gale, with northeasterly winds dominating, the average wind speed is larger than the non-strong convective TC gale; strong convective weather with short-term heavy precipitation and thunderstorms, with the majority of which is short-term heavy precipitation (approximately 79.5% of this type of TC gale), mainly distributed in the northeast quadrant near the TC center, while thunderstorm TC gale mainly appears in the periphery of TC (approximately 28.0% of this type of TC gale), of which there are relatively few in the southeast quadrant. (5) TC gale with both short-term heavy precipitation and thunderstorms accounts for only 1.8% of the total TC gale and 7.5% of strong convective TC gale, indicating that thunderstorms are not common in TC gale with short-term heavy precipitation.
The China Meteorological Administration (CMA) tropical cyclone best track data and hour-by-hour precipitation data from 2010 to 2016 were used in a statistical analysis of surface gales and their accompanying weather in southeastern China under the influence of tropical cyclones (TCs), and the results show that: (1) In this region, TC gale is primarily dispersed along the coastline, with decreasing frequency from coast to inland; TC gale is dominated by the northeast wind direction, and the gale occurs primarily before the typhoon landfall. Strong wind speeds of magnitude 12 and higher are scattered within 300 km of the TC center; (2) TCs of tropical storm (TS) and typhoon (TY) intensity caused the most gales, while strong wind speeds of magnitude 16 and above are mainly found in the severe typhoon (STY) and super typhoon (Super TY) intensity classes. Gale induced by slow TC appears primarily on the right front side, while gale caused by quick TC appears primarily on the right rear side. The mean onshore wind speed of TC gales is slightly greater than the offshore wind speed, despite the fact that the station frequency of onshore wind is greater than that of offshore wind when the wind speed is between level 12 and level 16, and when the wind speed is above level 16, offshore wind is much greater than that of onshore wind; (3) The percentage of TC gales that are precipitation-accompanied accounts for roughly 89.8% of the total number of TC gales; these gales are primarily caused by northeasterly winds, peaking in August. About 10.2% of the TC’s gales are dry, with the majority occurring at the TC’s periphery with weak northerly and southeasterly winds, primarily in May and December. TC gales with wind speeds above level 12 are almost always accompanied by precipitation, while there are few samples of TC gales with wind speeds above 12 without precipitation; (4) TC gales accompanied by strong convective weather account for approximately 23.8% of the total TC gale, with northeasterly winds dominating, the average wind speed is larger than the non-strong convective TC gale; strong convective weather with short-term heavy precipitation and thunderstorms, with the majority of which is short-term heavy precipitation (approximately 79.5% of this type of TC gale), mainly distributed in the northeast quadrant near the TC center, while thunderstorm TC gale mainly appears in the periphery of TC (approximately 28.0% of this type of TC gale), of which there are relatively few in the southeast quadrant. (5) TC gale with both short-term heavy precipitation and thunderstorms accounts for only 1.8% of the total TC gale and 7.5% of strong convective TC gale, indicating that thunderstorms are not common in TC gale with short-term heavy precipitation.
, Available online ,
doi: 10.3878/j.issn.1006-9895.2108.21108
Abstract:
The impact of summer tropical Atlantic sea temperature (TAST) on the first rainy season precipitation in South China (FRSP) is investigated using monthly precipitation data from 160 stations in China, Hadley Center sea surface temperature (SST) data, National Oceanic and Atmospheric Administration (NOAA) outgoing longwave radiation (OLR) data, and NCEP/NCAR reanalysis data from 1979 to 2019. Correlation analysis and information flow theory indicate that a rise (reduction) in the previous summer TAST partially accounts for an increase (decrease) in FRSP. The SST increases in the critical zone (35°W–10°E, 10°S–5°N) may amplify the Walker circulation and produce abnormal subsidence across the Pacific, resulting in an easterly wind anomaly throughout the central and western equatorial Pacific during the summer. The ocean–atmosphere interactions aided in the formation of La Niña in the fall and winter that followed. The same forces govern the negative SST anomaly but in the opposite direction, which is favorable for the growth of El Niño. When the La Niña (El Niño) reaches its height in the northern hemisphere, convection heating intensifies (or is inhibited) in the western Pacific, triggering atypical cyclones (anticyclones) in the lower troposphere to its north. The anomalies persist until the first rainy season of the second year, resulting in the persistence of abnormal cyclones (anticyclones), which, on the one hand, contribute to the Western Pacific Subtropical High (WPSH) weakening and eastward retreating (strengthening its westward extension), thereby reducing (increasing) the transport of water vapor from the South. Thus, the WPSH reduces (increases) water vapor movement from the South China Sea to South China. On the other hand, in tropical regions, convective activity (suppression) is favorable to strengthening (weakening) the local Hadley circulation, resulting in the subsidence (ascent) anomaly in South China and suppressing (intensifying) convection. Additionally, the negative (positive) SST anomaly in the eastern Pacific energized a Pacific–North American-like wave train, and the SST anomalies in the North Atlantic energized the Eurasian (EU) wave train, resulting in negative (positive)– positive (negative) – negative (positive) geopotential height anomalies in the Eurasian mid-high latitudes region, which is unfavorable (favorable) for the cold air affecting South China.
The impact of summer tropical Atlantic sea temperature (TAST) on the first rainy season precipitation in South China (FRSP) is investigated using monthly precipitation data from 160 stations in China, Hadley Center sea surface temperature (SST) data, National Oceanic and Atmospheric Administration (NOAA) outgoing longwave radiation (OLR) data, and NCEP/NCAR reanalysis data from 1979 to 2019. Correlation analysis and information flow theory indicate that a rise (reduction) in the previous summer TAST partially accounts for an increase (decrease) in FRSP. The SST increases in the critical zone (35°W–10°E, 10°S–5°N) may amplify the Walker circulation and produce abnormal subsidence across the Pacific, resulting in an easterly wind anomaly throughout the central and western equatorial Pacific during the summer. The ocean–atmosphere interactions aided in the formation of La Niña in the fall and winter that followed. The same forces govern the negative SST anomaly but in the opposite direction, which is favorable for the growth of El Niño. When the La Niña (El Niño) reaches its height in the northern hemisphere, convection heating intensifies (or is inhibited) in the western Pacific, triggering atypical cyclones (anticyclones) in the lower troposphere to its north. The anomalies persist until the first rainy season of the second year, resulting in the persistence of abnormal cyclones (anticyclones), which, on the one hand, contribute to the Western Pacific Subtropical High (WPSH) weakening and eastward retreating (strengthening its westward extension), thereby reducing (increasing) the transport of water vapor from the South. Thus, the WPSH reduces (increases) water vapor movement from the South China Sea to South China. On the other hand, in tropical regions, convective activity (suppression) is favorable to strengthening (weakening) the local Hadley circulation, resulting in the subsidence (ascent) anomaly in South China and suppressing (intensifying) convection. Additionally, the negative (positive) SST anomaly in the eastern Pacific energized a Pacific–North American-like wave train, and the SST anomalies in the North Atlantic energized the Eurasian (EU) wave train, resulting in negative (positive)– positive (negative) – negative (positive) geopotential height anomalies in the Eurasian mid-high latitudes region, which is unfavorable (favorable) for the cold air affecting South China.
2023 Issue 3
Display Method:
2023, 47(3): 599-615.
doi: 10.3878/j.issn.1006-9895.2202.21200
Abstract:
This research compared and analyzed the precipitation and temperature differences in North China during winter and summer under different climate conditions to explore the characteristics and differences between various climate normals in this region and their impacts on regional climate monitoring. Then, we analyzed the impact of these average climatic changes on extreme historical events. Investigations revealed that although the average precipitation in winter and summer during 1991–2020 (climate state Ⅱ) was more than that during 1981–2010 (climate state I), it was lesser than that in 1961–2020. However, the annual variation of state Ⅱ was smaller than that of state Ⅰ in winter, whereas vice versa in summer. Furthermore, although the state Ⅱ climate precipitation of the different regions varied in winter, it decreased in the central area and increased in the eastern and western parts of North China in summer. Also, we observed that the average winter and summer extreme precipitation thresholds in North China were higher in state Ⅱ (0.86 and 22.0 mm) than in state Ⅰ (0.83 and 21.6 mm), causing several extreme precipitation days in winter and summer in most parts of North China for the past 60 years. This event, however, reduced corresponding to state Ⅱ than Ⅰ. Although the average winter and summer temperatures of state Ⅱ were significantly higher than those of state Ⅰ, they remained higher than the average winter and summer temperatures of 1961–2020, indicating that while state Ⅱ temperatures maintained the characteristic of being overall warmer than state Ⅰ, the change characteristics of the different regions varied. Conversely, the extremely low average winter temperature and the extremely high summer temperature threshold in state Ⅱ (−9.8°C and 27.9°C) exceeded those in state Ⅰ (−10.2°C and 27.5°C), causing several extremely low winter temperature days in most parts of North China corresponding to state Ⅱ for the past 60 years. While this event increased compared with state Ⅰ, the extremely high summer temperature days corresponding to state Ⅱ reduced to varying degrees compared with state Ⅰ. Overall, our investigations propose that applying new climate normals will increase the extreme precipitation and extreme temperature thresholds in most parts of North China, leading to more frequent low temperatures, less precipitation, and less extreme historical climate events in climate monitoring. Hence, the possible impact of the new climate normals on climate monitoring and prediction over the next decade should be fully considered.
This research compared and analyzed the precipitation and temperature differences in North China during winter and summer under different climate conditions to explore the characteristics and differences between various climate normals in this region and their impacts on regional climate monitoring. Then, we analyzed the impact of these average climatic changes on extreme historical events. Investigations revealed that although the average precipitation in winter and summer during 1991–2020 (climate state Ⅱ) was more than that during 1981–2010 (climate state I), it was lesser than that in 1961–2020. However, the annual variation of state Ⅱ was smaller than that of state Ⅰ in winter, whereas vice versa in summer. Furthermore, although the state Ⅱ climate precipitation of the different regions varied in winter, it decreased in the central area and increased in the eastern and western parts of North China in summer. Also, we observed that the average winter and summer extreme precipitation thresholds in North China were higher in state Ⅱ (0.86 and 22.0 mm) than in state Ⅰ (0.83 and 21.6 mm), causing several extreme precipitation days in winter and summer in most parts of North China for the past 60 years. This event, however, reduced corresponding to state Ⅱ than Ⅰ. Although the average winter and summer temperatures of state Ⅱ were significantly higher than those of state Ⅰ, they remained higher than the average winter and summer temperatures of 1961–2020, indicating that while state Ⅱ temperatures maintained the characteristic of being overall warmer than state Ⅰ, the change characteristics of the different regions varied. Conversely, the extremely low average winter temperature and the extremely high summer temperature threshold in state Ⅱ (−9.8°C and 27.9°C) exceeded those in state Ⅰ (−10.2°C and 27.5°C), causing several extremely low winter temperature days in most parts of North China corresponding to state Ⅱ for the past 60 years. While this event increased compared with state Ⅰ, the extremely high summer temperature days corresponding to state Ⅱ reduced to varying degrees compared with state Ⅰ. Overall, our investigations propose that applying new climate normals will increase the extreme precipitation and extreme temperature thresholds in most parts of North China, leading to more frequent low temperatures, less precipitation, and less extreme historical climate events in climate monitoring. Hence, the possible impact of the new climate normals on climate monitoring and prediction over the next decade should be fully considered.
2023, 47(3): 616-630.
doi: 10.3878/j.issn.1006-9895.2109.21119
Abstract:
Stable isotopes in atmospheric water vapor, which can track moisture sources and water vapor transport, are extensively used as a crucial tracer of the present-day water cycle. To interpret water vapor stable isotopes in the mid-low latitude monsoon region, the “amount effect” is invoked. However, recent studies have demonstrated that nonlocal factors, such as moisture sources and water vapor transport, have a significant effect on stable isotopes. Thus, the Lagrangian Particle Dispersion Model and Satellite remote sensing deuterium isotope data (expressed by parts per thousand of their deviation, δD) in water vapor are used to investigate the primary factors affecting water vapor δD in the region with abundant Chinese stalagmite δ18O records. On the seasonal scale, water vapor δD is more depleted in late summer and early autumn and enriched in winter and spring. This characteristic is difficult to interpret in terms of “temperature effect” or “amount effect.” However, accumulated rainfall over water vapor transport paths is the dominant factor of water vapor δD, and there is a significant negative correlation between them. On an interannual scale, water vapor δD is enhanced in the summer of the El Niño year and depleted in the summer of La Niña year. The contribution of moisture sources to water vapor δD is small; however, the accumulated rainfall over water vapor transport paths increased substantially in the La Niña year compared with the El Niño year. This shows that in the La Niña year, tropical convection and depletion in water vapor transport paths are significant, resulting in depleted water vapor δD in the study area. Finally, on a seasonal to interannual scale, upstream convection, as measured by accumulated rainfall, is the primary driver of water vapor δD variations. In the study area, enhanced convection will deplete δD, whereas the weakened convection will enrich δD.
Stable isotopes in atmospheric water vapor, which can track moisture sources and water vapor transport, are extensively used as a crucial tracer of the present-day water cycle. To interpret water vapor stable isotopes in the mid-low latitude monsoon region, the “amount effect” is invoked. However, recent studies have demonstrated that nonlocal factors, such as moisture sources and water vapor transport, have a significant effect on stable isotopes. Thus, the Lagrangian Particle Dispersion Model and Satellite remote sensing deuterium isotope data (expressed by parts per thousand of their deviation, δD) in water vapor are used to investigate the primary factors affecting water vapor δD in the region with abundant Chinese stalagmite δ18O records. On the seasonal scale, water vapor δD is more depleted in late summer and early autumn and enriched in winter and spring. This characteristic is difficult to interpret in terms of “temperature effect” or “amount effect.” However, accumulated rainfall over water vapor transport paths is the dominant factor of water vapor δD, and there is a significant negative correlation between them. On an interannual scale, water vapor δD is enhanced in the summer of the El Niño year and depleted in the summer of La Niña year. The contribution of moisture sources to water vapor δD is small; however, the accumulated rainfall over water vapor transport paths increased substantially in the La Niña year compared with the El Niño year. This shows that in the La Niña year, tropical convection and depletion in water vapor transport paths are significant, resulting in depleted water vapor δD in the study area. Finally, on a seasonal to interannual scale, upstream convection, as measured by accumulated rainfall, is the primary driver of water vapor δD variations. In the study area, enhanced convection will deplete δD, whereas the weakened convection will enrich δD.
2023, 47(3): 631-641.
doi: 10.3878/j.issn.1006-9895.2202.21096
Abstract:
As an advanced atmospheric detection method, GPS (Global Positioning System) occultation detection technology has been widely used in numerical weather forecasting, climate, and space weather research. One of the problems in occultation detection is that it is easily interfered with by the reflected signals on the surface of the earth. Identifying and separating the reflected signals in the occultation detection signal helps assimilate the occultation data into the numerical weather prediction system, which has considerable importance. This study proposes a deep learning model based on improved GoogLenet (Im-GNet) model and applies it to COSMIC-2 occultation detection data to identify reflected signals. This study selects the COSMIC-2 occultation data (conPhs file) from 1 January to 9 January 2020. After quality control, the radio holography method is used to obtain the spatial spectrum image of the occultation signal, and the Im-GNet deep learning model is trained. The accuracy rate of the Im-GNet model test reached 96.4%, which is significantly higher than the result of the support vector machine method. This study also analyzes the impact of reflected signals on occultation data. The geographic distribution of occultation events and the refractivity comparison between the occultation inversion data (atmPrf file) and the NCEP (National Centers for Environmental Prediction) 12-h forecast files (avnPrf file) shows that the quality of the occultation event data with reflection signals is better, and the atmospheric information contained is richer.
As an advanced atmospheric detection method, GPS (Global Positioning System) occultation detection technology has been widely used in numerical weather forecasting, climate, and space weather research. One of the problems in occultation detection is that it is easily interfered with by the reflected signals on the surface of the earth. Identifying and separating the reflected signals in the occultation detection signal helps assimilate the occultation data into the numerical weather prediction system, which has considerable importance. This study proposes a deep learning model based on improved GoogLenet (Im-GNet) model and applies it to COSMIC-2 occultation detection data to identify reflected signals. This study selects the COSMIC-2 occultation data (conPhs file) from 1 January to 9 January 2020. After quality control, the radio holography method is used to obtain the spatial spectrum image of the occultation signal, and the Im-GNet deep learning model is trained. The accuracy rate of the Im-GNet model test reached 96.4%, which is significantly higher than the result of the support vector machine method. This study also analyzes the impact of reflected signals on occultation data. The geographic distribution of occultation events and the refractivity comparison between the occultation inversion data (atmPrf file) and the NCEP (National Centers for Environmental Prediction) 12-h forecast files (avnPrf file) shows that the quality of the occultation event data with reflection signals is better, and the atmospheric information contained is richer.
2023, 47(3): 642-654.
doi: 10.3878/j.issn.1006-9895.2201.21081
Abstract:
This paper focuses on the dynamic and statistical–dynamical downscaling techniques for estimating the precipitation at the stations in the Heihe River basin of Northwest China based on local observations at 14 sites and the outputs from RIEMS2.0 (Regional Climate Model) with a grid resolution of 3×3 km. The precipitation estimated further using MLR (multiple linear regression) and BMA (Bayesian Model Average) with different factor combinations is tested on the assessment indices as RMSE (Root Mean Square Error), correlation coefficient, variance percent, and “negative precipitation bias” with observation. Results show that the precipitation produced by the dynamic model has the largest RMSE, the most significant coherence, and a considerably larger variance than the observation by a factor of 1.5–2. Except for correlation coefficients, the statistical–dynamical downscaling models are optimal, and the statistical models are between statistical–dynamical models and dynamic model. The test shows that the correlation coefficient of the statistical downscaling models constructed with 700-hPa geopotential height field, meridional wind, and specific humidity is lower, and the RMSE is larger. The statistic indices were improved when the precipitation factor was introduced into the statistically downscaling models. The correlation coefficient and variance percentage of MLR models are considerably higher than BMA models, the RMSE of the two types of models is close in value, but the bias of negative precipitation of the former is significantly higher than that of the latter. The negative precipitation produced by the statistically downscaling models appears mainly in the cold season or dry and arid lands, such as the lower reaches of the river, of which the “negative precipitation” frequency decreases if the model precipitation is added as a factor in the downscaling models. Moreover, the statistical assessment of the monthly precipitation estimated from the downscaling models reveals that the four indices would evolve with season, in which the errors of dynamical downscaling are also the largest among the downscaling models, and their relative errors are smaller in summer and larger in winter, particularly in lower reaches of the river. This implies that precipitation downscaling in the dry land or dry season is still difficult for climate study. These results show a significant bias in dynamic downscaling, even for the high-resolution regional climate model. Therefore, the regional model must be combined with statistic downscaling to form a statistical–dynamical model for decreasing the precipitation uncertainties estimated in the river basin.
This paper focuses on the dynamic and statistical–dynamical downscaling techniques for estimating the precipitation at the stations in the Heihe River basin of Northwest China based on local observations at 14 sites and the outputs from RIEMS2.0 (Regional Climate Model) with a grid resolution of 3×3 km. The precipitation estimated further using MLR (multiple linear regression) and BMA (Bayesian Model Average) with different factor combinations is tested on the assessment indices as RMSE (Root Mean Square Error), correlation coefficient, variance percent, and “negative precipitation bias” with observation. Results show that the precipitation produced by the dynamic model has the largest RMSE, the most significant coherence, and a considerably larger variance than the observation by a factor of 1.5–2. Except for correlation coefficients, the statistical–dynamical downscaling models are optimal, and the statistical models are between statistical–dynamical models and dynamic model. The test shows that the correlation coefficient of the statistical downscaling models constructed with 700-hPa geopotential height field, meridional wind, and specific humidity is lower, and the RMSE is larger. The statistic indices were improved when the precipitation factor was introduced into the statistically downscaling models. The correlation coefficient and variance percentage of MLR models are considerably higher than BMA models, the RMSE of the two types of models is close in value, but the bias of negative precipitation of the former is significantly higher than that of the latter. The negative precipitation produced by the statistically downscaling models appears mainly in the cold season or dry and arid lands, such as the lower reaches of the river, of which the “negative precipitation” frequency decreases if the model precipitation is added as a factor in the downscaling models. Moreover, the statistical assessment of the monthly precipitation estimated from the downscaling models reveals that the four indices would evolve with season, in which the errors of dynamical downscaling are also the largest among the downscaling models, and their relative errors are smaller in summer and larger in winter, particularly in lower reaches of the river. This implies that precipitation downscaling in the dry land or dry season is still difficult for climate study. These results show a significant bias in dynamic downscaling, even for the high-resolution regional climate model. Therefore, the regional model must be combined with statistic downscaling to form a statistical–dynamical model for decreasing the precipitation uncertainties estimated in the river basin.
2023, 47(3): 655-666.
doi: 10.3878/j.issn.1006-9895.2110.21116
Abstract:
We analyzed the structural characteristics and differences in raindrop spectrum at different precipitation stages on the inland leeward side (LSI) and near-coast windward side (WSC) during the impact of typhoon Wipha from August 2 to 3, 2019. We used the raindrop spectrum observation data from Chongzuo National Meteorological Observatory and Fangcheng National Reference Climate Station, combined with rainfall data and radar observation data for the analysis. The results show that typhoon Wipha’s rainfall is mainly contributed by medium and small raindrops, with the proportion of medium raindrops consistently exceeding 70%. The rainfall at LSI is dominated by stratiform clouds with relatively gentle rain intensity, while the rainfall at WSC is characterized by mixed cumulus clouds with considerable rain intensity and severe fluctuations. Raindrop concentration and diameter are significantly larger at WSC than at LSI due to the considerable convective activity and upward velocity. The main factor for the increase in rain intensity at LSI after typhoon landfall is an increase in raindrop diameter. Meanwhile, the increase in rain intensity at WSC after the change from typhoon eye wall to a strong convective spiral rain band is mainly due to an increase in raindrop number concentration. The average mass-weighted mean diameter of typhoon Wipha’s convective precipitation is 1.85 mm, with a logarithmic normalized intercept of 3.95 mm−1 m−3. Convective precipitation occurs in the maritime convective region at LSI, while it occurs between maritime and continental convection at WSC.
We analyzed the structural characteristics and differences in raindrop spectrum at different precipitation stages on the inland leeward side (LSI) and near-coast windward side (WSC) during the impact of typhoon Wipha from August 2 to 3, 2019. We used the raindrop spectrum observation data from Chongzuo National Meteorological Observatory and Fangcheng National Reference Climate Station, combined with rainfall data and radar observation data for the analysis. The results show that typhoon Wipha’s rainfall is mainly contributed by medium and small raindrops, with the proportion of medium raindrops consistently exceeding 70%. The rainfall at LSI is dominated by stratiform clouds with relatively gentle rain intensity, while the rainfall at WSC is characterized by mixed cumulus clouds with considerable rain intensity and severe fluctuations. Raindrop concentration and diameter are significantly larger at WSC than at LSI due to the considerable convective activity and upward velocity. The main factor for the increase in rain intensity at LSI after typhoon landfall is an increase in raindrop diameter. Meanwhile, the increase in rain intensity at WSC after the change from typhoon eye wall to a strong convective spiral rain band is mainly due to an increase in raindrop number concentration. The average mass-weighted mean diameter of typhoon Wipha’s convective precipitation is 1.85 mm, with a logarithmic normalized intercept of 3.95 mm−1 m−3. Convective precipitation occurs in the maritime convective region at LSI, while it occurs between maritime and continental convection at WSC.
2023, 47(3): 667-682.
doi: 10.3878/j.issn.1006-9895.2210.21148
Abstract:
Herein, atmospheric ice nuclei gradient observation results from Huangshan and Shenyang were used as a representative. Using advanced international instruments for atmospheric ice nuclei observation and Bigg-type mixed and diffusion cloud chambers combined with meteorological element observation equipment, variation in the atmospheric ice nuclei number concentration with height, time, temperature, humidity, and particle size in Huangshan and Shenyang of China is analyzed. Two main mechanisms of atmospheric ice nuclei under different space locations, environmental conditions, and particle sizes are obtained. Finally, based on the above observations and research results, the parameter schemes of atmospheric ice nuclei in typical areas of northern and southern China are fitted with parameter formulas, and the attribute differences of atmospheric ice nuclei number concentration and nucleation mechanism in northern and southern China are finally obtained. Thus, it provides a theoretical basis for different artificial precipitation reduction operations in northern and southern China.
Herein, atmospheric ice nuclei gradient observation results from Huangshan and Shenyang were used as a representative. Using advanced international instruments for atmospheric ice nuclei observation and Bigg-type mixed and diffusion cloud chambers combined with meteorological element observation equipment, variation in the atmospheric ice nuclei number concentration with height, time, temperature, humidity, and particle size in Huangshan and Shenyang of China is analyzed. Two main mechanisms of atmospheric ice nuclei under different space locations, environmental conditions, and particle sizes are obtained. Finally, based on the above observations and research results, the parameter schemes of atmospheric ice nuclei in typical areas of northern and southern China are fitted with parameter formulas, and the attribute differences of atmospheric ice nuclei number concentration and nucleation mechanism in northern and southern China are finally obtained. Thus, it provides a theoretical basis for different artificial precipitation reduction operations in northern and southern China.
2023, 47(3): 683-697.
doi: 10.3878/j.issn.1006-9895.2112.21117
Abstract:
The temporal-spatial characteristics of the leading mode of winter cloudy day frequency (CDF) across eastern China are revealed via Empirical Orthogonal Function (EOF) analysis of daily cloud cover obtained from 1078 gauge stations in eastern China from 1961 to 2003. We identified the two influence routes of this leading mode, which we used to conduct a physical-motivated empirical model to the seasonal forecast of the winter CDF in eastern China. The results demonstrate that: (1) The first EOF mode of winter CDF explains 59% of the total variance, which is significant and independent of the other modes. This mode primarily demonstrates a homogenous spatial pattern across eastern China with dominating interannual variability. In the positive phase of this mode, a significant lower-level anticyclonic circulation anomaly occurs across the North Pacific. The anomalous southerly wind across the western flank of the anticyclonic could transport water vapor from the tropical ocean to eastern China, resulting in higher CDF. (2) the preceding persistent North Pacific dipole (NPD) pattern during August and September, and lowering of sea level pressure across midlatitude North Atlantic (LPA) from September–November are the two independent drivers for the formation and variation of this mode. The cold SSTA in the western pole of the NPD is advected southward to the tropical western Pacific using the anomalous northerly of the local low-level anomalous cyclone, forming the Bjerknes feedback, which maintains and accelerates the “cold west warm east” zonal SSTA dipole pattern in the tropical Pacific. This tropical Pacific zonal SSTA pattern stimulates zonal convection dipole, which induces a meridional atmospheric teleconnection in the North Pacific. The anomalous North Pacific anticyclones’ southerly is conducive to more CDF in eastern China. The LPA demonstrates the transition of a quasi-stationary Rossby wave train in mid-high latitudes Eurasia from autumn to winter. In winter, the southerly on the west of the barotropic anticyclonic anomaly across Northeast Asia, the terminal of the Rossby wave train, could result in increased CDF in eastern China. (3) Based on these two independent routes of physical mechanisms from both tropics and ex-tropics, a physics-motivated empirical model is conducted, which demonstrates potential independent prediction skill during the ten years of 2004–2013. The results are essential references for operational departments on seasonal prediction.
The temporal-spatial characteristics of the leading mode of winter cloudy day frequency (CDF) across eastern China are revealed via Empirical Orthogonal Function (EOF) analysis of daily cloud cover obtained from 1078 gauge stations in eastern China from 1961 to 2003. We identified the two influence routes of this leading mode, which we used to conduct a physical-motivated empirical model to the seasonal forecast of the winter CDF in eastern China. The results demonstrate that: (1) The first EOF mode of winter CDF explains 59% of the total variance, which is significant and independent of the other modes. This mode primarily demonstrates a homogenous spatial pattern across eastern China with dominating interannual variability. In the positive phase of this mode, a significant lower-level anticyclonic circulation anomaly occurs across the North Pacific. The anomalous southerly wind across the western flank of the anticyclonic could transport water vapor from the tropical ocean to eastern China, resulting in higher CDF. (2) the preceding persistent North Pacific dipole (NPD) pattern during August and September, and lowering of sea level pressure across midlatitude North Atlantic (LPA) from September–November are the two independent drivers for the formation and variation of this mode. The cold SSTA in the western pole of the NPD is advected southward to the tropical western Pacific using the anomalous northerly of the local low-level anomalous cyclone, forming the Bjerknes feedback, which maintains and accelerates the “cold west warm east” zonal SSTA dipole pattern in the tropical Pacific. This tropical Pacific zonal SSTA pattern stimulates zonal convection dipole, which induces a meridional atmospheric teleconnection in the North Pacific. The anomalous North Pacific anticyclones’ southerly is conducive to more CDF in eastern China. The LPA demonstrates the transition of a quasi-stationary Rossby wave train in mid-high latitudes Eurasia from autumn to winter. In winter, the southerly on the west of the barotropic anticyclonic anomaly across Northeast Asia, the terminal of the Rossby wave train, could result in increased CDF in eastern China. (3) Based on these two independent routes of physical mechanisms from both tropics and ex-tropics, a physics-motivated empirical model is conducted, which demonstrates potential independent prediction skill during the ten years of 2004–2013. The results are essential references for operational departments on seasonal prediction.
2023, 47(3): 698-712.
doi: 10.3878/j.issn.1006-9895.2112.21127
Abstract:
The Tibetan Plateau vortex (TPV) is a shallow mesoscale vortex system in the Tibetan Plateau’s main body. It occurs regularly, affects a wide area, and causes strong disasters. It is a major disaster-causing mesoscale system in China. To fully show the statistical characteristics of TPVs, a crucial basis for TPV research must be established. The accurate identification of TPVs is the key to the statistical characteristics of TPVs. TPV research has a better data basis with the emergence of reanalysis data with a high spatial and temporal resolution. However, neither an artificial identification approach nor an objective identification algorithm based on a coarser resolution can be effectively used for the current new reanalysis data. In this study, a restricted vorticity-based TPV identifying algorithm is proposed, which is suitable for high-resolution reanalysis data. This approach first determines the TPV candidate points, divides several octants with the candidate points as the center, and determines the center of the TPV by restricting the conditions of the average wind field in the octant and counterclockwise rotation (Northern Hemisphere) conditions of the octant group. This method can quickly identify the horizontal and vertical tracing of vortexes without complicated calculations and different thresholds for each pressure layer. A large sample evaluation of 15,466 TPVs (99,090 hours in total) in 42 warm seasons (May–September) from 1979 to 2020 shows that the average hit ratio of RTIA exceeds 95%, the average false alarm ratio is below 9%, and the average missing report rate is below 5%. Thus, the RTIA can correctly identify the centers of TPVs. Furthermore, the test results show that the high accuracy of TPV identification can still be maintained when RTIA is applied to the reanalysis data with different spatial resolutions (e.g., 0.5°or 0.25°). The identification results are primarily affected by the strength of the vortexes themselves, and the identification accuracy of weak vortexes is lower than that of strong vortexes. This approach can be used as a reference for identifying other mesoscale vortexes.
The Tibetan Plateau vortex (TPV) is a shallow mesoscale vortex system in the Tibetan Plateau’s main body. It occurs regularly, affects a wide area, and causes strong disasters. It is a major disaster-causing mesoscale system in China. To fully show the statistical characteristics of TPVs, a crucial basis for TPV research must be established. The accurate identification of TPVs is the key to the statistical characteristics of TPVs. TPV research has a better data basis with the emergence of reanalysis data with a high spatial and temporal resolution. However, neither an artificial identification approach nor an objective identification algorithm based on a coarser resolution can be effectively used for the current new reanalysis data. In this study, a restricted vorticity-based TPV identifying algorithm is proposed, which is suitable for high-resolution reanalysis data. This approach first determines the TPV candidate points, divides several octants with the candidate points as the center, and determines the center of the TPV by restricting the conditions of the average wind field in the octant and counterclockwise rotation (Northern Hemisphere) conditions of the octant group. This method can quickly identify the horizontal and vertical tracing of vortexes without complicated calculations and different thresholds for each pressure layer. A large sample evaluation of 15,466 TPVs (99,090 hours in total) in 42 warm seasons (May–September) from 1979 to 2020 shows that the average hit ratio of RTIA exceeds 95%, the average false alarm ratio is below 9%, and the average missing report rate is below 5%. Thus, the RTIA can correctly identify the centers of TPVs. Furthermore, the test results show that the high accuracy of TPV identification can still be maintained when RTIA is applied to the reanalysis data with different spatial resolutions (e.g., 0.5°or 0.25°). The identification results are primarily affected by the strength of the vortexes themselves, and the identification accuracy of weak vortexes is lower than that of strong vortexes. This approach can be used as a reference for identifying other mesoscale vortexes.
2023, 47(3): 713-724.
doi: 10.3878/j.issn.1006-9895.2112.21218
Abstract:
The OH radical is the primary tropospheric oxidant, accounting for the oxidation capacity of the atmosphere. The GEOS-Chem model was used to examine the impact of anthropogenic emission and meteorological parameter changes on summertime OH concentrations in China since the implementation of the Air Pollution Prevention and Control Action Plan. Our modeling results for the years 2014–2017 demonstrate that the summertime OH concentrations in China exhibited an overall upward trend with the fastest increase occurring around 30°N over eastern China; the North China Plain was also simulated to have an obvious upward OH concentration trend of 0.1 × 106 molecules cm−3 a−1 while the Pearl River Delta experienced a weak downward trend. Further sensitivity experiment simulations showed that changes in both meteorology and anthropogenic emissions over the years 2014–2017 contributed to the increases in OH concentrations in the North China Plain, wherein the contribution of anthropogenic emissions was significantly larger than that of meteorology (10% vs. 1.5%). Meteorology played a major role in OH concentration increase around 30°N over eastern China. Further meteorological analysis demonstrated that the meteorological variable with the greatest contribution was solar shortwave radiation, which can explain the changes in the OH concentrations over a large fraction of China during 2014–2017. However, the role of solar shortwave radiation was offset by the boundary layer height in impacting the changes in OH concentrations during 2014–2017 in the North China Plain.
The OH radical is the primary tropospheric oxidant, accounting for the oxidation capacity of the atmosphere. The GEOS-Chem model was used to examine the impact of anthropogenic emission and meteorological parameter changes on summertime OH concentrations in China since the implementation of the Air Pollution Prevention and Control Action Plan. Our modeling results for the years 2014–2017 demonstrate that the summertime OH concentrations in China exhibited an overall upward trend with the fastest increase occurring around 30°N over eastern China; the North China Plain was also simulated to have an obvious upward OH concentration trend of 0.1 × 106 molecules cm−3 a−1 while the Pearl River Delta experienced a weak downward trend. Further sensitivity experiment simulations showed that changes in both meteorology and anthropogenic emissions over the years 2014–2017 contributed to the increases in OH concentrations in the North China Plain, wherein the contribution of anthropogenic emissions was significantly larger than that of meteorology (10% vs. 1.5%). Meteorology played a major role in OH concentration increase around 30°N over eastern China. Further meteorological analysis demonstrated that the meteorological variable with the greatest contribution was solar shortwave radiation, which can explain the changes in the OH concentrations over a large fraction of China during 2014–2017. However, the role of solar shortwave radiation was offset by the boundary layer height in impacting the changes in OH concentrations during 2014–2017 in the North China Plain.
2023, 47(3): 725-738.
doi: 10.3878/j.issn.1006-9895.2205.21016
Abstract:
In this study, complex Empirical Orthogonal Function (CEOF) and wavelet analyses are applied to the 84-year simulation flow fields in January of the climate model CAS-ESM-C from 1922. The simulation results were compared with the actual situation and theoretical analysis solution to examine the simulation ability of the model for the upper equatorial ocean flow field. The main conclusions are as follows: (1) The variance contributions of the first three modes of the CEOF decomposition are 53.5%, 12.9%, and 9.5%, respectively. The cumulative variance contribution was 75.9%, which is higher than the actual situation. (2) The first and second eigenvector patterns are similar to the actual situation. The equator captures the flow fields, and the flow fields in the capture region are dominated by the partial latitudinal flow. The difference is that the equatorial capture area in this study is larger than the actual situation, and the longitudinal flow component, as well as the cross-equatorial flow, are also more obvious than that of the actual situation. (3) There is no linear trend in the real-time coefficient sequence of the first and second modes in this study, but this trend exists in the actual situation. The inter-annual and inter-decadal variations of the CEOF modes are similar to the actual situation. The inter-annual variation of 3–7 years in the first and second modes reflects ENSO (El Niño–Southern Oscillation). The inter-decadal variation of 22–23 years in the first mode is influenced by the North Pacific main climate modal PDO (Pacific Decadal Oscillation). The inter-decadal variation of 13 years in the second mode is influenced by the North Pacific secondary climate modal NPGO (North Pacific Gyre Oscillation). Both modes have an inter-decadal variation of 16 years, which may be related to the cross-flow in Indonesia. (4) The results in this paper show that the flow field is captured by the equator and zonal in the theoretical analytical solution. However, the flow field is pure zonal due to the absence of wind stress in the analytical solution. (5) The first (second) mode has dynamic SSTA (sea surface temperature anomaly) in the eastern (central) equatorial Pacific Ocean, which can be called the eastern (central) ENSO mode. The climate model performs well in simulating the upper flow field of the tropical Pacific Ocean.
In this study, complex Empirical Orthogonal Function (CEOF) and wavelet analyses are applied to the 84-year simulation flow fields in January of the climate model CAS-ESM-C from 1922. The simulation results were compared with the actual situation and theoretical analysis solution to examine the simulation ability of the model for the upper equatorial ocean flow field. The main conclusions are as follows: (1) The variance contributions of the first three modes of the CEOF decomposition are 53.5%, 12.9%, and 9.5%, respectively. The cumulative variance contribution was 75.9%, which is higher than the actual situation. (2) The first and second eigenvector patterns are similar to the actual situation. The equator captures the flow fields, and the flow fields in the capture region are dominated by the partial latitudinal flow. The difference is that the equatorial capture area in this study is larger than the actual situation, and the longitudinal flow component, as well as the cross-equatorial flow, are also more obvious than that of the actual situation. (3) There is no linear trend in the real-time coefficient sequence of the first and second modes in this study, but this trend exists in the actual situation. The inter-annual and inter-decadal variations of the CEOF modes are similar to the actual situation. The inter-annual variation of 3–7 years in the first and second modes reflects ENSO (El Niño–Southern Oscillation). The inter-decadal variation of 22–23 years in the first mode is influenced by the North Pacific main climate modal PDO (Pacific Decadal Oscillation). The inter-decadal variation of 13 years in the second mode is influenced by the North Pacific secondary climate modal NPGO (North Pacific Gyre Oscillation). Both modes have an inter-decadal variation of 16 years, which may be related to the cross-flow in Indonesia. (4) The results in this paper show that the flow field is captured by the equator and zonal in the theoretical analytical solution. However, the flow field is pure zonal due to the absence of wind stress in the analytical solution. (5) The first (second) mode has dynamic SSTA (sea surface temperature anomaly) in the eastern (central) equatorial Pacific Ocean, which can be called the eastern (central) ENSO mode. The climate model performs well in simulating the upper flow field of the tropical Pacific Ocean.
2023, 47(3): 739-755.
doi: 10.3878/j.issn.1006-9895.2201.21210
Abstract:
Based on the original backscattering signals of the micro rain radar and a new micro rain radar processing methodology (RaProM), the equivalent radar reflectivity, the particle falling velocity, and Doppler spectrum width are calculated after power spectrum calculation, noise removal, and dealiasing. Furthermore, the precipitation types are identified. The RaProM algorithm can identify particle phases, such as snow, drizzle, rain, hail, and their mixed types, considering particle falling velocity, equivalent radar reflectivity, particle size characteristics of different precipitation types, and presence of bright bands. In addition, liquid precipitation parameters, such as radar reflectivity factor and rain intensity, are computed. Subsequently, three typical cases of stratiform cloud precipitation on July 2, 2021, transition of rain and snow on December 25, 2019, and the precipitation with the height of the zero degree layer decreasing gradually on March 4, 2018, are selected to verify and discuss the results. The method of precipitation type classification is applied to typical stratiform precipitation, the vertical structure shows snowflakes in the supercooled water area, mixed-type precipitation in the ice-liquid conversion zone near the 0°C layer, and liquid precipitation below the bright band, proving the validity of the method. The methods are then applied to precipitation type classification and bright band detection. The results show that the RaProM algorithm has the advantage of making no assumptions about precipitation type and considering particle upward velocity (such as snowflakes) over the standard inversion process of micro rain radar. The RaProM algorithm results are in good agreement with the colocated microwave radiometer and cloud radar in the vertical structure, and the deviations from the ground disdrometer in raindrop size distribution and rain intensity are reduced compared with the products of micro rain radar.
Based on the original backscattering signals of the micro rain radar and a new micro rain radar processing methodology (RaProM), the equivalent radar reflectivity, the particle falling velocity, and Doppler spectrum width are calculated after power spectrum calculation, noise removal, and dealiasing. Furthermore, the precipitation types are identified. The RaProM algorithm can identify particle phases, such as snow, drizzle, rain, hail, and their mixed types, considering particle falling velocity, equivalent radar reflectivity, particle size characteristics of different precipitation types, and presence of bright bands. In addition, liquid precipitation parameters, such as radar reflectivity factor and rain intensity, are computed. Subsequently, three typical cases of stratiform cloud precipitation on July 2, 2021, transition of rain and snow on December 25, 2019, and the precipitation with the height of the zero degree layer decreasing gradually on March 4, 2018, are selected to verify and discuss the results. The method of precipitation type classification is applied to typical stratiform precipitation, the vertical structure shows snowflakes in the supercooled water area, mixed-type precipitation in the ice-liquid conversion zone near the 0°C layer, and liquid precipitation below the bright band, proving the validity of the method. The methods are then applied to precipitation type classification and bright band detection. The results show that the RaProM algorithm has the advantage of making no assumptions about precipitation type and considering particle upward velocity (such as snowflakes) over the standard inversion process of micro rain radar. The RaProM algorithm results are in good agreement with the colocated microwave radiometer and cloud radar in the vertical structure, and the deviations from the ground disdrometer in raindrop size distribution and rain intensity are reduced compared with the products of micro rain radar.
2023, 47(3): 756-768.
doi: 10.3878/j.issn.1006-9895.2112.21112
Abstract:
This study analyzed the physical characteristics of rainfall clouds in the West Tianshan Mountains, from May 2019 to August 2020, based on the Ka-band millimeter-wave cloud radar and rainfall data from automatic weather stations. The findings demonstrate that: (1) Rainfall occurs primarily at night. The cumulative rainfall was concentrated from 2100 BJT to 0700 BJT the next day. There was a significant beneficial correlation between rainfall frequency and accumulated precipitation. The frequency of heavy rainfall was the lowest, but its contribution to total accumulated rainfall was significant. (2) The maximum average reflectivity of light, moderate, and heavy rainfall intensities were 30, 35.8, and 39.5 dBZ, respectively, and the maximum average liquid water content was 1.5, 4.2, and 7.3 g m−3, respectively. (3) There are two concentrated areas for the reflectivity of various rainfall intensities. The reflectivity of 2.0–4.4 km was concentrated in 15–26 dBZ, and the reflectivity of light, moderate, and heavy rainfall intensities near the surface was respectively concentrated in 24–32 dBZ, 29–38, and 31–42 dBZ. The frequency of moderate and heavy rain intensity below 1.75 km, where the liquid water content is less than 1 g m−3, is significantly lower than light rain intensity. The greater the intensity of rainfall, the more concentrated the radial velocity of rainfall particles.
This study analyzed the physical characteristics of rainfall clouds in the West Tianshan Mountains, from May 2019 to August 2020, based on the Ka-band millimeter-wave cloud radar and rainfall data from automatic weather stations. The findings demonstrate that: (1) Rainfall occurs primarily at night. The cumulative rainfall was concentrated from 2100 BJT to 0700 BJT the next day. There was a significant beneficial correlation between rainfall frequency and accumulated precipitation. The frequency of heavy rainfall was the lowest, but its contribution to total accumulated rainfall was significant. (2) The maximum average reflectivity of light, moderate, and heavy rainfall intensities were 30, 35.8, and 39.5 dBZ, respectively, and the maximum average liquid water content was 1.5, 4.2, and 7.3 g m−3, respectively. (3) There are two concentrated areas for the reflectivity of various rainfall intensities. The reflectivity of 2.0–4.4 km was concentrated in 15–26 dBZ, and the reflectivity of light, moderate, and heavy rainfall intensities near the surface was respectively concentrated in 24–32 dBZ, 29–38, and 31–42 dBZ. The frequency of moderate and heavy rain intensity below 1.75 km, where the liquid water content is less than 1 g m−3, is significantly lower than light rain intensity. The greater the intensity of rainfall, the more concentrated the radial velocity of rainfall particles.
2023, 47(3): 769-785.
doi: 10.3878/j.issn.1006-9895.2111.21110
Abstract:
Lightning data obtained from the FY-4A satellite and ADTD (Advanced Direction and Time of arrival Detecting system) are significant for studying rainstorms and severe convection weather. This paper compares and analyzes the differences between the two lightning data through a case study of a rainstorm in Mianning, Sichuan Province. A series of numerical experiments are designed to introduce the two kinds of lightning data into a numerical prediction model. The main conclusions are: (1) Two kinds of lightning data have different detection effects in different areas. The ADTD lightning data are more extensive and scattered, whereas the number and distribution of lightning detected by the FY-4A satellite are more intensive. However, there is a good consistency between the two kinds of surrogate radar echo transformed by the two lightning data kinds. For low-frequency lightning, the ADTD lightning localizer may be more efficient than FY-4A LMI (Lightning Mapping Imager). (2) The introduction of these two types of lightning data has positive effects on precipitation forecast, and the application of ADTD lightning data is more effective for improving the accuracy of short-time precipitation forecast. (3) The two types of lightning data have different effects on the cloud microphysical quantities adjustment in different regions. This shows that the distribution of the two types of lightning data is not entirely consistent, but they are complementary to each other.
Lightning data obtained from the FY-4A satellite and ADTD (Advanced Direction and Time of arrival Detecting system) are significant for studying rainstorms and severe convection weather. This paper compares and analyzes the differences between the two lightning data through a case study of a rainstorm in Mianning, Sichuan Province. A series of numerical experiments are designed to introduce the two kinds of lightning data into a numerical prediction model. The main conclusions are: (1) Two kinds of lightning data have different detection effects in different areas. The ADTD lightning data are more extensive and scattered, whereas the number and distribution of lightning detected by the FY-4A satellite are more intensive. However, there is a good consistency between the two kinds of surrogate radar echo transformed by the two lightning data kinds. For low-frequency lightning, the ADTD lightning localizer may be more efficient than FY-4A LMI (Lightning Mapping Imager). (2) The introduction of these two types of lightning data has positive effects on precipitation forecast, and the application of ADTD lightning data is more effective for improving the accuracy of short-time precipitation forecast. (3) The two types of lightning data have different effects on the cloud microphysical quantities adjustment in different regions. This shows that the distribution of the two types of lightning data is not entirely consistent, but they are complementary to each other.
2023, 47(3): 786-804.
doi: 10.3878/j.issn.1006-9895.2208.21261
Abstract:
The synoptic circulation pattern and mesoscale systems associated with the extreme torrential rain occurring in the Shandong Peninsula on 22 July 2020, are analyzed with conventional observational data and a high-resolution numerical simulation using the mesoscale model WRF. The simulation agreed well with the precipitation process. The results show that the rainstorm process is characterized by mesoscale features spatially and temporally, represented in its high intensity of short-term rainfall, severe locality, etc. Precipitation occurs in the southwest airflow between the subtropical north elevation and the bottom of a low vortex. Strong vortices and low-level jets are important weather systems that affect this precipitation. The southwest jet stream is the main carrier of extreme water vapor during this heavy precipitation. Under a high-level weak divergent field, the main influence of this rainstorm is the deep low vortex extending from the surface to the 500-hPa high altitude. Its temporal and spatial evolution characteristics are consistent with the mesoscale cloud cluster changes shown by the FY-2E hourly TBB data. This consistency is directly related to the occurrence of heavy rain. The interaction between the vortex, low-level jet, and subtropical high strengthens the development of the low vortex. There are warm, wet airflows from the north and cold, dry airflows from the south of the low vortex. The specific humidity gradient is roughly distributed from south to north, which is a typical flow field distribution of a vortex accompanied by a low-level jet. The convergence of the low vortex and its interaction with the strong wind speed belt at the edge of the subtropical high lead to the development and maintenance of strong vertical motion, thereby contributing to the persistence of extreme rainstorms.
The synoptic circulation pattern and mesoscale systems associated with the extreme torrential rain occurring in the Shandong Peninsula on 22 July 2020, are analyzed with conventional observational data and a high-resolution numerical simulation using the mesoscale model WRF. The simulation agreed well with the precipitation process. The results show that the rainstorm process is characterized by mesoscale features spatially and temporally, represented in its high intensity of short-term rainfall, severe locality, etc. Precipitation occurs in the southwest airflow between the subtropical north elevation and the bottom of a low vortex. Strong vortices and low-level jets are important weather systems that affect this precipitation. The southwest jet stream is the main carrier of extreme water vapor during this heavy precipitation. Under a high-level weak divergent field, the main influence of this rainstorm is the deep low vortex extending from the surface to the 500-hPa high altitude. Its temporal and spatial evolution characteristics are consistent with the mesoscale cloud cluster changes shown by the FY-2E hourly TBB data. This consistency is directly related to the occurrence of heavy rain. The interaction between the vortex, low-level jet, and subtropical high strengthens the development of the low vortex. There are warm, wet airflows from the north and cold, dry airflows from the south of the low vortex. The specific humidity gradient is roughly distributed from south to north, which is a typical flow field distribution of a vortex accompanied by a low-level jet. The convergence of the low vortex and its interaction with the strong wind speed belt at the edge of the subtropical high lead to the development and maintenance of strong vertical motion, thereby contributing to the persistence of extreme rainstorms.
2023, 47(3): 805-824.
doi: 10.3878/j.issn.1006-9895.2209.22117
Abstract:
Based on a traditional machine learning algorithm (XGBoost), a deep learning algorithm (CU-Net), and the winter wind speed data from 10 m near the ground with a resolution of 100 m, this paper studied and compared the correction methods for wind speed forecast deviation in the mountainous stations and surrounding areas of the Yanqing and Zhangjiakou competition areas (Beijing Winter Olympic Games) using the rapid-refresh integrated seamless ensemble (RISE) system. For station correction, the 10-m wind speed predicted by the RISE system is interpolated to the corresponding automatic weather station. Subsequently, a separate XGBoost model is constructed for each classification according to the wind speed rating table. Afterward, each interval model was combined to form L-XGBoost, using the root mean square error and forecast accuracy as its scoring standard. Investigations revealed that the correction effect of the L-XGBoost algorithm for wind speed classification was better than the original XGBoost model without classification, indicating that introducing a classification method to traditional machine learning helped improve the wind speed prediction skills of the complex mountain stations. Subsequently, for the wind speed correction of the station and its surrounding areas based on the CU-Net model, this paper constructed a new algorithm model (CU-Net++) by introducing the CU-Net sub-networks with different depths, considering the influence of daily forecast errors and complex terrains on the 10-m wind speed. This paper also constructed spatial small-area sample data, considering the automatic weather station as the center, to correct the wind speed prediction deviation of the RISE system. The test results indicated that although both CU-Net and CU-Net++ fully mined the wind field change rules in time and space dimensions, the wind speed correction results of the CU-Net++ model performed better than those of the CU-Net model, effectively reducing the grid wind speed prediction error of RISE products. Hence, introducing prediction error and complex terrain plays an important positive role in the deviation correction of a surface 10 m wind speed-based investigation.
Based on a traditional machine learning algorithm (XGBoost), a deep learning algorithm (CU-Net), and the winter wind speed data from 10 m near the ground with a resolution of 100 m, this paper studied and compared the correction methods for wind speed forecast deviation in the mountainous stations and surrounding areas of the Yanqing and Zhangjiakou competition areas (Beijing Winter Olympic Games) using the rapid-refresh integrated seamless ensemble (RISE) system. For station correction, the 10-m wind speed predicted by the RISE system is interpolated to the corresponding automatic weather station. Subsequently, a separate XGBoost model is constructed for each classification according to the wind speed rating table. Afterward, each interval model was combined to form L-XGBoost, using the root mean square error and forecast accuracy as its scoring standard. Investigations revealed that the correction effect of the L-XGBoost algorithm for wind speed classification was better than the original XGBoost model without classification, indicating that introducing a classification method to traditional machine learning helped improve the wind speed prediction skills of the complex mountain stations. Subsequently, for the wind speed correction of the station and its surrounding areas based on the CU-Net model, this paper constructed a new algorithm model (CU-Net++) by introducing the CU-Net sub-networks with different depths, considering the influence of daily forecast errors and complex terrains on the 10-m wind speed. This paper also constructed spatial small-area sample data, considering the automatic weather station as the center, to correct the wind speed prediction deviation of the RISE system. The test results indicated that although both CU-Net and CU-Net++ fully mined the wind field change rules in time and space dimensions, the wind speed correction results of the CU-Net++ model performed better than those of the CU-Net model, effectively reducing the grid wind speed prediction error of RISE products. Hence, introducing prediction error and complex terrain plays an important positive role in the deviation correction of a surface 10 m wind speed-based investigation.
2023, 47(3): 825-836.
doi: 10.3878/j.issn.1006-9895.2206.22054
Abstract:
This work analyzes the abrupt change in summer surface air temperature (SAT) in Central Asia (CA) and its relationship with sea surface temperature (SST) in the North Atlantic and snow cover in the Qinghai Tibet Plateau between 1980 and 2019 based on NCEP/NCAR reanalysis data, CRU SAT, and snow cover and global SST data. The results reveal a significant summer SAT change in CA in 2005. The standardized regional average temperature index in CA shifts from the previous negative phase to the subsequent positive phase, indicating a significant summer SAT increase in CA. Analysis of the anomalous atmospheric circulations related to interdecadal changes in summer SAT in CA shows the abnormally enhanced anticyclonic circulation system in the west of CA after 2005. The atmospheric subsidence associated with the anomalous anticyclone can cause warming. On the other hand, the reduction in the amount of cloud caused by this anticyclone anomaly enhancement results in the increase in downward short-wave radiation and thus is favorable for the increased summer temperature in CA. Furthermore, the interdecadal summer SAT changes in CA in 2005 are closely related to SST warming in the middle and high latitudes of the North Atlantic and the reduction in snow cover in the west of the Tibet Plateau (TP). The SST increase in the middle and high latitudes of the North Atlantic can stimulate a Rossby wave propagating downstream. The reduction in snow cover in the west of the TP can cause warming to the above atmosphere through the snow albedo effect. The changes in both the North Atlantic SST and the TP snow can strengthen the anticyclone over CA, leading to an abnormally high summer SAT over there.
This work analyzes the abrupt change in summer surface air temperature (SAT) in Central Asia (CA) and its relationship with sea surface temperature (SST) in the North Atlantic and snow cover in the Qinghai Tibet Plateau between 1980 and 2019 based on NCEP/NCAR reanalysis data, CRU SAT, and snow cover and global SST data. The results reveal a significant summer SAT change in CA in 2005. The standardized regional average temperature index in CA shifts from the previous negative phase to the subsequent positive phase, indicating a significant summer SAT increase in CA. Analysis of the anomalous atmospheric circulations related to interdecadal changes in summer SAT in CA shows the abnormally enhanced anticyclonic circulation system in the west of CA after 2005. The atmospheric subsidence associated with the anomalous anticyclone can cause warming. On the other hand, the reduction in the amount of cloud caused by this anticyclone anomaly enhancement results in the increase in downward short-wave radiation and thus is favorable for the increased summer temperature in CA. Furthermore, the interdecadal summer SAT changes in CA in 2005 are closely related to SST warming in the middle and high latitudes of the North Atlantic and the reduction in snow cover in the west of the Tibet Plateau (TP). The SST increase in the middle and high latitudes of the North Atlantic can stimulate a Rossby wave propagating downstream. The reduction in snow cover in the west of the TP can cause warming to the above atmosphere through the snow albedo effect. The changes in both the North Atlantic SST and the TP snow can strengthen the anticyclone over CA, leading to an abnormally high summer SAT over there.
2023, 47(3): 837-852.
doi: 10.3878/j.issn.1006-9895.2211.21262
Abstract:
The Tibetan Plateau vortex (TPV) is a kind of mesoscale weather system that exists near the surface of the Tibetan Plateau (TP). TPVs are the major precipitation-producing weather system over the TP, and a small portion of the TPVs move off the TP, causing catastrophic heavy rainfall in the downstream areas of the TP. The yearbook of the TPVs edited by the Chengdu Institute of Plateau Meteorology offers important references in the field of TPVs research. The TPV source of the yearbook is dominantly located over the eastern TP, but most TPVs obtained via the reanalysis are generated over the western TP. It is the most significant difference between the TPVs derived from the yearbook and the reanalysis. To clarify the source of TPVs, we first examine the differences in the general circulation between the eastern and western regions of the TP that affect the development of the TPVs and find that the large-scale circulation in the western TP is more favorable to the generation of TPVs. Second, the atmospheric moving vector and blackbody bright temperature derived from the FY-2 geostationary satellites during 2005–2019 are used to reexamine the TPV sources from the yearbook, showing that most TPVs are generated from the western TP. Finally, we checked the difference in the TPV source via the yearbook between the former and later periods of the construction of the three new sounding stations over the western TP, which are Shiquanhe, Gaize, and Shenzha. It shows that the new data significantly increases the proportion of TPVs generated from the western TP. Combining the results obtained from multiple sources, we conclude that most TPVs originate in the western part of the TP, and the conclusion of the yearbook may be misguided because of the insufficient soundings in the western part of the TP. This study confirms the availability and reliability of reanalysis data in the study of TPVs and emphasizes the importance of satellite-based observations in the study of weather systems and the urgency of further enhancing observations over the TP.
The Tibetan Plateau vortex (TPV) is a kind of mesoscale weather system that exists near the surface of the Tibetan Plateau (TP). TPVs are the major precipitation-producing weather system over the TP, and a small portion of the TPVs move off the TP, causing catastrophic heavy rainfall in the downstream areas of the TP. The yearbook of the TPVs edited by the Chengdu Institute of Plateau Meteorology offers important references in the field of TPVs research. The TPV source of the yearbook is dominantly located over the eastern TP, but most TPVs obtained via the reanalysis are generated over the western TP. It is the most significant difference between the TPVs derived from the yearbook and the reanalysis. To clarify the source of TPVs, we first examine the differences in the general circulation between the eastern and western regions of the TP that affect the development of the TPVs and find that the large-scale circulation in the western TP is more favorable to the generation of TPVs. Second, the atmospheric moving vector and blackbody bright temperature derived from the FY-2 geostationary satellites during 2005–2019 are used to reexamine the TPV sources from the yearbook, showing that most TPVs are generated from the western TP. Finally, we checked the difference in the TPV source via the yearbook between the former and later periods of the construction of the three new sounding stations over the western TP, which are Shiquanhe, Gaize, and Shenzha. It shows that the new data significantly increases the proportion of TPVs generated from the western TP. Combining the results obtained from multiple sources, we conclude that most TPVs originate in the western part of the TP, and the conclusion of the yearbook may be misguided because of the insufficient soundings in the western part of the TP. This study confirms the availability and reliability of reanalysis data in the study of TPVs and emphasizes the importance of satellite-based observations in the study of weather systems and the urgency of further enhancing observations over the TP.
2023, 47(3): 853-865.
doi: 10.3878/j.issn.1006-9895.2212.22165
Abstract:
To investigate the pollution, source, and transport characteristics of polycyclic aromatic hydrocarbons (PAHs) in the atmosphere of the southeast of Tibetan Plateau, a comprehensive analysis was carried out using 14 different PAHs from the total suspended particulate (TSP) matter and the atmospheric gaseous state in the Lulang area (29.77°N, 94.73°E) and combined with meteorological environment data from the same period. The results show that the variation ranges of PAHs mass concentration in TSP and gas phase are 0.22–5.05 ng m−3 and 0.83–63.75 ng m−3, respectively, with average values of 2.13 ng m−3 and 11.33 ng m−3. The primary source of pollution is the combustion of firewood and diesel, while other sources of pollution include the combustion of gasoline. PAHs are emitted by both local pollution and long-range transmission (LRT). In the four seasons, local pollution varies from source to source. Local pollution is serious in the winter and spring, and the source is in the southeast and due south. Pollution in the summer and autumn is primarily caused by local and LRT sources. The primary local source is mainly in the southeast, but LRT is dominant. The northwest air flow, westerly airflow, and southwest air flow all have an impact on the LRT. When pollution is serious, the dominant airflow is southwest, while the secondary dominant airflow is westerly. When the pollution is light, the dominant airflow is westerly or northwest, and the pollution transmitted by the northwest airflow is the least. The results of this study have contributed to a better knowledge of the changes and transport characteristics of PAHs in Southeast Tibet and a theoretical basis for the control of air pollution in this region and the improvement of plateau air quality.
To investigate the pollution, source, and transport characteristics of polycyclic aromatic hydrocarbons (PAHs) in the atmosphere of the southeast of Tibetan Plateau, a comprehensive analysis was carried out using 14 different PAHs from the total suspended particulate (TSP) matter and the atmospheric gaseous state in the Lulang area (29.77°N, 94.73°E) and combined with meteorological environment data from the same period. The results show that the variation ranges of PAHs mass concentration in TSP and gas phase are 0.22–5.05 ng m−3 and 0.83–63.75 ng m−3, respectively, with average values of 2.13 ng m−3 and 11.33 ng m−3. The primary source of pollution is the combustion of firewood and diesel, while other sources of pollution include the combustion of gasoline. PAHs are emitted by both local pollution and long-range transmission (LRT). In the four seasons, local pollution varies from source to source. Local pollution is serious in the winter and spring, and the source is in the southeast and due south. Pollution in the summer and autumn is primarily caused by local and LRT sources. The primary local source is mainly in the southeast, but LRT is dominant. The northwest air flow, westerly airflow, and southwest air flow all have an impact on the LRT. When pollution is serious, the dominant airflow is southwest, while the secondary dominant airflow is westerly. When the pollution is light, the dominant airflow is westerly or northwest, and the pollution transmitted by the northwest airflow is the least. The results of this study have contributed to a better knowledge of the changes and transport characteristics of PAHs in Southeast Tibet and a theoretical basis for the control of air pollution in this region and the improvement of plateau air quality.
2023, 47(3): 866-880.
doi: 10.3878/j.issn.1006-9895.2203.21156
Abstract:
Based on the monthly ERA5 reanalysis datasets, this study considers the mean flows and eddies in stationary or transient transport using the Lorenz circulation decomposition method. The purpose is to compare the dynamic transport characteristics of ozone over the Arctic and the Tibetan Plateau in detail. Results show that the effect of dynamic transport is strongest in the upper stratosphere of these two regions, which leads to the reduction of ozone. Further analyses indicate that the effect of stationary transport is stronger than that of transient transport and zonal and meridional transports nearly have the opposite effect. However, the intensity of dynamic transport over the Arctic is greater than that over the Tibetan Plateau. Zonal transport over the Arctic results in the reduction of ozone in the upper and middle stratosphere and the increase of ozone in the lower stratosphere, whereas the effect of meridional transport is the opposite and weaker. Both mainly function in the upper stratosphere. Over the Tibetan Plateau, the intensity of zonal transport is the same as that of meridional transport. They nearly have the opposite effect, except for the top of the stratosphere, where both lead to the reduction of ozone. Two centers with the strongest transport are located over the Tibetan Plateau, that is, in the upper stratosphere and the upper troposphere–lower stratosphere. The differences in zonal and meridional transports over these two regions are mainly caused by stationary transport by eddies. The differences in stationary and transient transports over the Tibetan Plateau are smaller than those over the Arctic. Furthermore, the transport of zonal mean ozone by eddies plays a dominant role in stationary and transient transports. Consequently, eddy transport exerts an indispensable influence on the dynamic transport of ozone over the Arctic and the Tibetan Plateau.
Based on the monthly ERA5 reanalysis datasets, this study considers the mean flows and eddies in stationary or transient transport using the Lorenz circulation decomposition method. The purpose is to compare the dynamic transport characteristics of ozone over the Arctic and the Tibetan Plateau in detail. Results show that the effect of dynamic transport is strongest in the upper stratosphere of these two regions, which leads to the reduction of ozone. Further analyses indicate that the effect of stationary transport is stronger than that of transient transport and zonal and meridional transports nearly have the opposite effect. However, the intensity of dynamic transport over the Arctic is greater than that over the Tibetan Plateau. Zonal transport over the Arctic results in the reduction of ozone in the upper and middle stratosphere and the increase of ozone in the lower stratosphere, whereas the effect of meridional transport is the opposite and weaker. Both mainly function in the upper stratosphere. Over the Tibetan Plateau, the intensity of zonal transport is the same as that of meridional transport. They nearly have the opposite effect, except for the top of the stratosphere, where both lead to the reduction of ozone. Two centers with the strongest transport are located over the Tibetan Plateau, that is, in the upper stratosphere and the upper troposphere–lower stratosphere. The differences in zonal and meridional transports over these two regions are mainly caused by stationary transport by eddies. The differences in stationary and transient transports over the Tibetan Plateau are smaller than those over the Arctic. Furthermore, the transport of zonal mean ozone by eddies plays a dominant role in stationary and transient transports. Consequently, eddy transport exerts an indispensable influence on the dynamic transport of ozone over the Arctic and the Tibetan Plateau.
2023, 47(3): 881-892.
doi: 10.3878/j.issn.1006-9895.2207.22089
Abstract:
Based on precipitation and ERA5 reanalysis datasets from 1981 to 2020, this study analyzed the variation characteristics of precipitation at different time scales over the Three-River Headwaters region (TRHR) and the Yarlung Zangbo River basin (YZRB) and their responses to the Tibetan Plateau summer monsoon. Results are shown as follows: (1) The seasonal variation in precipitation over the TRHR and YZRB shows a bimodal distribution, and the peaks appear in early July and late August. The interdecadal transitions in summer precipitation occur in the early 21st century, especially the TRHR precipitation increases significantly during the recent 20 years. The onset time of summer monsoon in the Dynamic Plateau Monsoon Index (DPMI) and the Zhou Plateau Monsoon Index (ZPMI) is earlier than the precipitation increase period over the TRHR and YZRB. The interannual variation in summer precipitation over the TRHR correlates well with two plateau summer monsoon indices. Although the TRHR is close to the YZRB, the summer precipitation of the TRHR is considerably more affected by the Tibetan plateau monsoon than YZRB. When the Tibetan Plateau summer monsoon strengthens (weakens), the TRHR precipitation is more (less). (2) In wet TRHR years, the South Asian High is stronger and more eastward, while the pressure at low-level over the main body of the plateau is lower than in dry years. These situations are conducive to the intersection of southwest and southeast winds over the TRHR so that the warm and humid air from the South can go deep into the hinterland of the plateau, resulting in stronger water vapor convergence. In wet YZRB years, there is no obvious anomaly in the pressure field near the YZRB or the Tibetan Plateau. The water vapor transport over YZRB mainly has two paths. One is the southwest path from the Bay of Bengal along the south slope of the plateau, and the other is the northwest path from Central Asia and through the plateau. The two paths converge on the east side of the plateau and continue to transport eastward.
Based on precipitation and ERA5 reanalysis datasets from 1981 to 2020, this study analyzed the variation characteristics of precipitation at different time scales over the Three-River Headwaters region (TRHR) and the Yarlung Zangbo River basin (YZRB) and their responses to the Tibetan Plateau summer monsoon. Results are shown as follows: (1) The seasonal variation in precipitation over the TRHR and YZRB shows a bimodal distribution, and the peaks appear in early July and late August. The interdecadal transitions in summer precipitation occur in the early 21st century, especially the TRHR precipitation increases significantly during the recent 20 years. The onset time of summer monsoon in the Dynamic Plateau Monsoon Index (DPMI) and the Zhou Plateau Monsoon Index (ZPMI) is earlier than the precipitation increase period over the TRHR and YZRB. The interannual variation in summer precipitation over the TRHR correlates well with two plateau summer monsoon indices. Although the TRHR is close to the YZRB, the summer precipitation of the TRHR is considerably more affected by the Tibetan plateau monsoon than YZRB. When the Tibetan Plateau summer monsoon strengthens (weakens), the TRHR precipitation is more (less). (2) In wet TRHR years, the South Asian High is stronger and more eastward, while the pressure at low-level over the main body of the plateau is lower than in dry years. These situations are conducive to the intersection of southwest and southeast winds over the TRHR so that the warm and humid air from the South can go deep into the hinterland of the plateau, resulting in stronger water vapor convergence. In wet YZRB years, there is no obvious anomaly in the pressure field near the YZRB or the Tibetan Plateau. The water vapor transport over YZRB mainly has two paths. One is the southwest path from the Bay of Bengal along the south slope of the plateau, and the other is the northwest path from Central Asia and through the plateau. The two paths converge on the east side of the plateau and continue to transport eastward.
2023, 47(3): 893-906.
doi: 10.3878/j.issn.1006-9895.2204.21208
Abstract:
Uncertainties in the evapotranspiration (ET) products used in the Tibetan Plateau (TP) region were determined based on the data from satellite remote sensing and observations having different spatial and temporal resolutions, limiting their utility for hydrometeorological and climate assessment. Six ET (PML, EB-ET_V2, GLEAM, GLDAS, ERA5_Land, and MOD16) products were evaluated based on eddy observations, and the differences between the products were compared. Moreover, the uncertainties in ET products in the TP region were analyzed. The results of the analysis are as follows: (1) A good correlation and consistency exist in the mean state and seasonal cycle between the observed and ET values of the corresponding pixel. Moreover, GLEAM product exhibits a high degree of agreement with the observed values and has applicability, and MOD16 product exhibits poor performance at most sites. (2) In terms of seasonal changes, ERA5_Land product values are highly consistent with the observed changes during spring, GLEAM product values are nearly consistent with the observed changes during summer and winter, and EB-ET_V2 product values are highly consistent with observed values during autumn. (3) Spatially, GLEAM product has higher correlation (the correlation coefficient R＞0.88) and consistency (index of agreement IOA＞0.89) compared to those of EB-ET_V2 product and GLDAS product. Substantial differences exist in the temporal and spatial distribution of various products during different seasons, especially during spring. Compared with other products, MOD16 product is underestimated in summer and overestimated in winter in most regions. (4) The annual average ET for each product except for MOD16 product is considerably different. The annual average ET values of the remaining five products over multiple years arranged in descending order are as follows: ERA5_Land product (401.46 mm a−1)＞PML product (334.37 mm a−1)＞GLEAM product (298.46 mm a−1)＞EB-ET_V2 product (271.39 mm a−1)＞GLDAS product (249.67 mm a−1). The total annual evaporation in the TP region is 330.59 mm a−1. The assessment results provide a detailed understanding of the quality and dynamics of ET products in the TP region, which can serve as reference data for regional water management and water resource assessment in the TP region.
Uncertainties in the evapotranspiration (ET) products used in the Tibetan Plateau (TP) region were determined based on the data from satellite remote sensing and observations having different spatial and temporal resolutions, limiting their utility for hydrometeorological and climate assessment. Six ET (PML, EB-ET_V2, GLEAM, GLDAS, ERA5_Land, and MOD16) products were evaluated based on eddy observations, and the differences between the products were compared. Moreover, the uncertainties in ET products in the TP region were analyzed. The results of the analysis are as follows: (1) A good correlation and consistency exist in the mean state and seasonal cycle between the observed and ET values of the corresponding pixel. Moreover, GLEAM product exhibits a high degree of agreement with the observed values and has applicability, and MOD16 product exhibits poor performance at most sites. (2) In terms of seasonal changes, ERA5_Land product values are highly consistent with the observed changes during spring, GLEAM product values are nearly consistent with the observed changes during summer and winter, and EB-ET_V2 product values are highly consistent with observed values during autumn. (3) Spatially, GLEAM product has higher correlation (the correlation coefficient R＞0.88) and consistency (index of agreement IOA＞0.89) compared to those of EB-ET_V2 product and GLDAS product. Substantial differences exist in the temporal and spatial distribution of various products during different seasons, especially during spring. Compared with other products, MOD16 product is underestimated in summer and overestimated in winter in most regions. (4) The annual average ET for each product except for MOD16 product is considerably different. The annual average ET values of the remaining five products over multiple years arranged in descending order are as follows: ERA5_Land product (401.46 mm a−1)＞PML product (334.37 mm a−1)＞GLEAM product (298.46 mm a−1)＞EB-ET_V2 product (271.39 mm a−1)＞GLDAS product (249.67 mm a−1). The total annual evaporation in the TP region is 330.59 mm a−1. The assessment results provide a detailed understanding of the quality and dynamics of ET products in the TP region, which can serve as reference data for regional water management and water resource assessment in the TP region.
2023, 47(3): 907-919.
doi: 10.3878/j.issn.1006-9895.2211.21267
Abstract:
The Tibetan Plateau (TP) vortex (TPV) is the main precipitation system in summer over the TP and downstream regions. This study analyzes a TPV case from 19 to 21 July 2013, based on high-resolution ERA5 reanalysis, the temperature of black body (TBB) obtained from the Fengyun-2E (FY-2E) satellite, and precipitation amount from TRMM (Tropical Rainfall Measurement Mission). The TPV case keeps active on the TP for about 56 h, which can be divided into three stages: Initial, development, and moving-out. Further, the roles of atmospheric heat sources in TPV during different stages and the related mechanisms are investigated. The results show that the TPV intensity increases with fluctuations. Furthermore, by diagnosing the potential vorticity (PV) tendency equation, it was found that the vertical gradient of diabatic heating is the main factor causing TPV development, i.e., a positive (negative) PV is produced below (above) the height where the maximum center of diabatic heating is situated, strengthening the low-level cyclonic and high-level anticyclonic circulations. Further analyses indicate that the atmospheric heat source increased with fluctuations, with the maximum value appearing at noon and the strongest in the moving-out stage. Notably, the formation of TPV is related to the surface warming center driven by surface sensible heat, while its enhancement is mainly dependent on the latent heat of condensation. Furthermore, the main contributor to the latent heat is analyzed as a vertical transport of water vapor that promotes TPV development.
The Tibetan Plateau (TP) vortex (TPV) is the main precipitation system in summer over the TP and downstream regions. This study analyzes a TPV case from 19 to 21 July 2013, based on high-resolution ERA5 reanalysis, the temperature of black body (TBB) obtained from the Fengyun-2E (FY-2E) satellite, and precipitation amount from TRMM (Tropical Rainfall Measurement Mission). The TPV case keeps active on the TP for about 56 h, which can be divided into three stages: Initial, development, and moving-out. Further, the roles of atmospheric heat sources in TPV during different stages and the related mechanisms are investigated. The results show that the TPV intensity increases with fluctuations. Furthermore, by diagnosing the potential vorticity (PV) tendency equation, it was found that the vertical gradient of diabatic heating is the main factor causing TPV development, i.e., a positive (negative) PV is produced below (above) the height where the maximum center of diabatic heating is situated, strengthening the low-level cyclonic and high-level anticyclonic circulations. Further analyses indicate that the atmospheric heat source increased with fluctuations, with the maximum value appearing at noon and the strongest in the moving-out stage. Notably, the formation of TPV is related to the surface warming center driven by surface sensible heat, while its enhancement is mainly dependent on the latent heat of condensation. Furthermore, the main contributor to the latent heat is analyzed as a vertical transport of water vapor that promotes TPV development.
2023, 47(3): 920-924.
doi: 10.3878/j.issn.1006-9895.2302.23014
Abstract:
In 2022, the Meteorological Joint Fund (MJF) supported three key research fields: the key technology of numerical prediction model, the theory and method of disaster weather monitoring and prediction, and the artificial intelligence meteorological application technology. Accordingly, the National Natural Science Foundation of China (NSFC) received 64 MJF applications comprising 87.5% cooperation applications with different unit attributes, and mail/panel reviews were conducted. Keyword analyses of the application revealed that MJF and the key programs in the “weather, climate, and associated sustainable development” field, Department of Earth Sciences (DES), had strong links and obvious differences. The review process of MJF is similar to the key conventional programs of DES, NSFC. NSFC funded 14 key supporting projects with a success rate of 21.9%, and the average annual funding intensity of the MJF exceeded that of DES, NSFC.
In 2022, the Meteorological Joint Fund (MJF) supported three key research fields: the key technology of numerical prediction model, the theory and method of disaster weather monitoring and prediction, and the artificial intelligence meteorological application technology. Accordingly, the National Natural Science Foundation of China (NSFC) received 64 MJF applications comprising 87.5% cooperation applications with different unit attributes, and mail/panel reviews were conducted. Keyword analyses of the application revealed that MJF and the key programs in the “weather, climate, and associated sustainable development” field, Department of Earth Sciences (DES), had strong links and obvious differences. The review process of MJF is similar to the key conventional programs of DES, NSFC. NSFC funded 14 key supporting projects with a success rate of 21.9%, and the average annual funding intensity of the MJF exceeded that of DES, NSFC.
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doi: 10.3878/j.issn.1006-9895.2305.22168
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doi: 10.3878/j.issn.1006-9895.2305.22215
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doi: 10.3878/j.issn.1006-9895.2304.22088
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doi: 10.3878/j.issn.1006-9895.2305.22172
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doi: 10.3878/j.issn.1006-9895.2304.22227
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doi: 10.3878/j.issn.1006-9895.2302.22130
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Abstract:
Since 1976 Bimonthly
Supervisor: Chinese Academy of Sciences
Sponsors by: Institute of Atmospheric Physics, Chinese Academy of Sciences, Chinese Meteorological Society
Editor: Lu Riyu
Email: dqkx@mail.iap.ac.cn
dqkx@post.iap.ac.cn
ISSN 1006-9895
CN 11-1768/O4
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