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doi: 10.3878/j.issn.1006-9585.2021.21031
Abstract:
Abstract The air’s capacity in removing air pollutants during December 2017 was scientifically quantified by using NAQPMS (Nested Air Quality Prediction Modeling System). Moreover, critical influential factors were compared to analyze the difference of the atmosphere’s self-cleaning ability between using the Modified A-value Algorithm (MAA) and the Atmospheric Self-purification Capacity Algorithm (ASPCA). The air self-purification capacity margin and its contribution were also evaluated for the air pollution process. The results show that the planetary boundary layer height, wind profile, and wet scavenging coefficient could describe the atmosphere’s self-cleaning ability more properly than the mixing layer height, wind speed at the height of 10 m, and rain-washing intensity. Both the MAA and ASPCA can represent the atmospheric removal capacity, but the former is highly affected by the city area, whose result is much higher than that of the latter. The atmospheric self-purification capacity margin is negatively correlated with the trend of the PM2.5 concentration, where advection-diffusion contributes the most, followed by the chemical transformation process and finally by the wet deposition processes.
Abstract The air’s capacity in removing air pollutants during December 2017 was scientifically quantified by using NAQPMS (Nested Air Quality Prediction Modeling System). Moreover, critical influential factors were compared to analyze the difference of the atmosphere’s self-cleaning ability between using the Modified A-value Algorithm (MAA) and the Atmospheric Self-purification Capacity Algorithm (ASPCA). The air self-purification capacity margin and its contribution were also evaluated for the air pollution process. The results show that the planetary boundary layer height, wind profile, and wet scavenging coefficient could describe the atmosphere’s self-cleaning ability more properly than the mixing layer height, wind speed at the height of 10 m, and rain-washing intensity. Both the MAA and ASPCA can represent the atmospheric removal capacity, but the former is highly affected by the city area, whose result is much higher than that of the latter. The atmospheric self-purification capacity margin is negatively correlated with the trend of the PM2.5 concentration, where advection-diffusion contributes the most, followed by the chemical transformation process and finally by the wet deposition processes.
, Available online ,
doi: 10.3878/j.issn.1006-9585.2021.21038
Abstract:
The association between the major atmospheric circulation indices and the seasonal surface solar radiation anomaly (SSRA) in China is investigated using ERA5 SSR downwards data from 1989 to 2018. The results show that (1) in spring, the location of the East Asian trough has a consistent influence on the SSRA in the large areas of eastern China, with the intensely significant negative SSRA when the location of the East Asian trough is eastward. The intensity of the East Asian winter monsoon affects the SSRA inversely in the southern and northern Yangtze river basins, whereas El Niño–Southern Oscillation (ENSO) affects the SSRA inversely in the eastern and western parts of south China. (2) In summer, the influencing factors are complicated. The North Atlantic Oscillation (NAO) and summer monsoon are important. The NAO has a significant influence on the SSRA in many parts of north China, and the summer monsoon is associated with the SSRA in the Yangtze–Huaihe River basin. When the NAO index is higher (lower), the SSRA in large parts of north China is less (more). When the summer monsoon index is higher (lower), the SSRA in the Yangtze–Huaihe River basin is significantly less (more). (3) In autumn, the SSRA is connected with the location of the East Asian trough, winter monsoon, and NAO. The SSRA in north China is primarily influenced by the winter monsoon and the location of the East Asian trough. The SSRA in large parts of north China except for Northeast China appears more when accompanied by the western East Asian trough or strong winter monsoon. Moreover, when associated with the SSRA in western China, the strong NAO can lead to less SSRA in the northern part of western China and more SSRA in the large southern parts of west China. (4) In addition, ENSO and winter monsoon are the two important factors affecting the SSRA in winter, but their significantly influencing areas are asymmetric. Negative ENSO and intense winter monsoon can cause more SSRA significantly in most parts of north China, and positive ENSO and weak winter monsoon are most favorable to the less SSRA in southern China, but on a small significant scale.
The association between the major atmospheric circulation indices and the seasonal surface solar radiation anomaly (SSRA) in China is investigated using ERA5 SSR downwards data from 1989 to 2018. The results show that (1) in spring, the location of the East Asian trough has a consistent influence on the SSRA in the large areas of eastern China, with the intensely significant negative SSRA when the location of the East Asian trough is eastward. The intensity of the East Asian winter monsoon affects the SSRA inversely in the southern and northern Yangtze river basins, whereas El Niño–Southern Oscillation (ENSO) affects the SSRA inversely in the eastern and western parts of south China. (2) In summer, the influencing factors are complicated. The North Atlantic Oscillation (NAO) and summer monsoon are important. The NAO has a significant influence on the SSRA in many parts of north China, and the summer monsoon is associated with the SSRA in the Yangtze–Huaihe River basin. When the NAO index is higher (lower), the SSRA in large parts of north China is less (more). When the summer monsoon index is higher (lower), the SSRA in the Yangtze–Huaihe River basin is significantly less (more). (3) In autumn, the SSRA is connected with the location of the East Asian trough, winter monsoon, and NAO. The SSRA in north China is primarily influenced by the winter monsoon and the location of the East Asian trough. The SSRA in large parts of north China except for Northeast China appears more when accompanied by the western East Asian trough or strong winter monsoon. Moreover, when associated with the SSRA in western China, the strong NAO can lead to less SSRA in the northern part of western China and more SSRA in the large southern parts of west China. (4) In addition, ENSO and winter monsoon are the two important factors affecting the SSRA in winter, but their significantly influencing areas are asymmetric. Negative ENSO and intense winter monsoon can cause more SSRA significantly in most parts of north China, and positive ENSO and weak winter monsoon are most favorable to the less SSRA in southern China, but on a small significant scale.
, Available online ,
doi: 10.3878/j.issn.1006-9585.2021.21097
Abstract:
Globally, there have been frequent occurrences of extreme forest fire incidents in recent years. As one kind of the compound extreme events, the occurrence and spread of forest fires are closely associated with meteorological conditions. Under global warming, investigating the changing characteristics of forest fire risk can provide valuable scientific information for forest fire prevention activities in the context of carbon neutrality. In this study, the daily forest fire danger index (FFDI) was used to measure fire weather, and the applicability and spatial distribution of this index were analyzed. In addition, the linear trend in FFDI and related meteorological factors in two major forest areas during 1961–2020 were analyzed. Finally, the ensemble empirical mode decomposition method was used to reveal the multi-time scale characteristics of FFDI in the two forest areas. The results show that the spatial distribution of FFDI has obvious regional characteristics on seasonal and annual time scales. Northeast China has a high FFDI during spring and autumn, whereas southwest China has a high FFDI during spring and winter. These seasonal variations show a good corresponding relationship with the forest fire prevention period in the two forest regions. The number of stations showing a significant increasing trend in FFDI in each season is around 10%–20%, with the highest in spring (21%). The linear trends in FFDI in the northeastern forest area are not significant in all seasons; however, among relevant meteorological factors, the daily maximum temperature and average wind speed respectively show a significant warming trend and a significant weakening trend in all seasons. The FFDI in all seasons of the southwestern forest area showed a significant increasing trend at a level of 0.1 at least, among which the trends during the spring and winter fire prevention periods were 0.09/10a (P<0.1) and 0.05/10a (P<0.1), respectively. The summer, autumn, and winter periods showed a significant warming and drying trend (P<0.05). The interannual variability contributes more than 70% to the evolution of FFDI in the two forest areas. The nonlinear trend of FFDI in the spring and autumn fire prevention periods in northeast China showed a rapid rise at first and then a decline. The nonlinear trend of FFDI in the spring fire season in southwest China changed from a stable stage in the last century to a rapidly increasing trend in the 21st century, whereas the overall trend of FFDI during the winter fire season increased steadily. Therefore, the situation of fire risk in forests of southwest China is increasingly becoming severe.
Globally, there have been frequent occurrences of extreme forest fire incidents in recent years. As one kind of the compound extreme events, the occurrence and spread of forest fires are closely associated with meteorological conditions. Under global warming, investigating the changing characteristics of forest fire risk can provide valuable scientific information for forest fire prevention activities in the context of carbon neutrality. In this study, the daily forest fire danger index (FFDI) was used to measure fire weather, and the applicability and spatial distribution of this index were analyzed. In addition, the linear trend in FFDI and related meteorological factors in two major forest areas during 1961–2020 were analyzed. Finally, the ensemble empirical mode decomposition method was used to reveal the multi-time scale characteristics of FFDI in the two forest areas. The results show that the spatial distribution of FFDI has obvious regional characteristics on seasonal and annual time scales. Northeast China has a high FFDI during spring and autumn, whereas southwest China has a high FFDI during spring and winter. These seasonal variations show a good corresponding relationship with the forest fire prevention period in the two forest regions. The number of stations showing a significant increasing trend in FFDI in each season is around 10%–20%, with the highest in spring (21%). The linear trends in FFDI in the northeastern forest area are not significant in all seasons; however, among relevant meteorological factors, the daily maximum temperature and average wind speed respectively show a significant warming trend and a significant weakening trend in all seasons. The FFDI in all seasons of the southwestern forest area showed a significant increasing trend at a level of 0.1 at least, among which the trends during the spring and winter fire prevention periods were 0.09/10a (P<0.1) and 0.05/10a (P<0.1), respectively. The summer, autumn, and winter periods showed a significant warming and drying trend (P<0.05). The interannual variability contributes more than 70% to the evolution of FFDI in the two forest areas. The nonlinear trend of FFDI in the spring and autumn fire prevention periods in northeast China showed a rapid rise at first and then a decline. The nonlinear trend of FFDI in the spring fire season in southwest China changed from a stable stage in the last century to a rapidly increasing trend in the 21st century, whereas the overall trend of FFDI during the winter fire season increased steadily. Therefore, the situation of fire risk in forests of southwest China is increasingly becoming severe.
2022 Issue 3
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2022, 27(3): 333-350.
doi: 10.3878/j.issn.1006-9585.2021.21060
Abstract:
Given the important role of land–atmosphere coupling (LAC) in extreme hot events, the multi-timescale characteristics of sensitivity-based coupling strength, which is between surface air temperature and land surface conditions in summer, were analyzed over China using the ERA5-Land reanalysis dataset. Results show that LAC strength varies remarkably with regions. In particular, the LAC hot spots where variations in land surface conditions considerably influence the surface air temperature through latent heat exchange are primarily located in Northwest China and Yangtze River basin. However, in terms of LAC defined by the sensitivity of surface air temperature to the land condition anomalies through sensible heat exchange, the hot spots are mainly located in the Hetao–Inner Mongolia areas, southwestern Xinjiang, and part of the south Yangtze River. This indicates that the differences in the spatial distribution of LAC indices can be largely explained by the dominant processes, in which land surface anomalies significantly affect the surface air temperature. Moreover, LAC strength varies considerably among different timescales, with monthly LAC strength being significantly weaker than that of shorter timescales (i.e., daily, pentad, and ten-day). As timescales increasing from one to ten days, the land–air temperature coupling strength based on latent heat flux gets weaker in majority parts of China, while that based on sensible heat flux gets stronger in the northern parts of China but remains a weakened state in other regions. Furthermore, in Northwest China, the coupling strength between the subsurface soil moisture and surface air temperature is weaker than that between the surface soil moisture and surface air temperature.
Given the important role of land–atmosphere coupling (LAC) in extreme hot events, the multi-timescale characteristics of sensitivity-based coupling strength, which is between surface air temperature and land surface conditions in summer, were analyzed over China using the ERA5-Land reanalysis dataset. Results show that LAC strength varies remarkably with regions. In particular, the LAC hot spots where variations in land surface conditions considerably influence the surface air temperature through latent heat exchange are primarily located in Northwest China and Yangtze River basin. However, in terms of LAC defined by the sensitivity of surface air temperature to the land condition anomalies through sensible heat exchange, the hot spots are mainly located in the Hetao–Inner Mongolia areas, southwestern Xinjiang, and part of the south Yangtze River. This indicates that the differences in the spatial distribution of LAC indices can be largely explained by the dominant processes, in which land surface anomalies significantly affect the surface air temperature. Moreover, LAC strength varies considerably among different timescales, with monthly LAC strength being significantly weaker than that of shorter timescales (i.e., daily, pentad, and ten-day). As timescales increasing from one to ten days, the land–air temperature coupling strength based on latent heat flux gets weaker in majority parts of China, while that based on sensible heat flux gets stronger in the northern parts of China but remains a weakened state in other regions. Furthermore, in Northwest China, the coupling strength between the subsurface soil moisture and surface air temperature is weaker than that between the surface soil moisture and surface air temperature.
2022, 27(3): 351-367.
doi: 10.3878/j.issn.1006-9585.2021.20147
Abstract:
The potential distribution of natural vegetation in East Asia and the possible impact of large-scale vegetation restoration from the cropland on climate change are explored using the dynamic vegetation model CLM4-CNDV, regional climate model RegCM4.6-CLM3.5, and global climate model CAM4. Part of the cropland in the northern Mongolia Plateau, Northeast and North China plains, and Sichuan basin could be occupied by bare soil. Part of the cropland in southeastern East Asia and the northern part of the Mongolia Plateau could be covered by woodlands. The cropland in the Sichuan Basin and the Shandong Peninsula could transit to shrubs; that in northeastern China, the Southeast coast, and the middle and lower reaches of the Yangtze River could transit to grassland. The restoration of natural vegetation could make a significant impact on regional climate change. Specifically, the enhancement of evapotranspiration caused by the increase of the vegetation leaf area index in most parts of East Asia could induce a significant increase in precipitation and a decrease in summer. A significant decrease in precipitation and increase in temperature in summer is found in North China, Sichuan Basin, and Central Guangdong Plain, in which the areas’ leaf area index is simulated to decrease. The climate in Mongolia Plateau is affected by the local change of the vegetation coverage and is adjusted by atmospheric circulation, which is caused by the vegetation change in India and southeastern China. Thus, the temperature in winter is simulated to decrease in the western Mongolia Plateau, while the temperature increases in summer in the eastern part with a significant decrease of precipitation. The experimental scheme adopted in the study is carried out under relatively ideal conditions, but results provide a reference for further distinguishing the impacts of vegetation cover changes in different areas.
The potential distribution of natural vegetation in East Asia and the possible impact of large-scale vegetation restoration from the cropland on climate change are explored using the dynamic vegetation model CLM4-CNDV, regional climate model RegCM4.6-CLM3.5, and global climate model CAM4. Part of the cropland in the northern Mongolia Plateau, Northeast and North China plains, and Sichuan basin could be occupied by bare soil. Part of the cropland in southeastern East Asia and the northern part of the Mongolia Plateau could be covered by woodlands. The cropland in the Sichuan Basin and the Shandong Peninsula could transit to shrubs; that in northeastern China, the Southeast coast, and the middle and lower reaches of the Yangtze River could transit to grassland. The restoration of natural vegetation could make a significant impact on regional climate change. Specifically, the enhancement of evapotranspiration caused by the increase of the vegetation leaf area index in most parts of East Asia could induce a significant increase in precipitation and a decrease in summer. A significant decrease in precipitation and increase in temperature in summer is found in North China, Sichuan Basin, and Central Guangdong Plain, in which the areas’ leaf area index is simulated to decrease. The climate in Mongolia Plateau is affected by the local change of the vegetation coverage and is adjusted by atmospheric circulation, which is caused by the vegetation change in India and southeastern China. Thus, the temperature in winter is simulated to decrease in the western Mongolia Plateau, while the temperature increases in summer in the eastern part with a significant decrease of precipitation. The experimental scheme adopted in the study is carried out under relatively ideal conditions, but results provide a reference for further distinguishing the impacts of vegetation cover changes in different areas.
2022, 27(3): 368-382.
doi: 10.3878/j.issn.1006-9585.2021.21036
Abstract:
The present study compares North China's cold surges in the 1990s and 2000s and their relationships with Arctic sea ice using the observed temperature, two atmospheric reanalyses from NCEP/NCAR, and a set of high-resolution sea ice concentration data from NOAA. In the 1990s, North China experienced less frequent cold surges with a strong relative intensity from 1951 to 2011, resulting from cold air originating from Greenland and invading North China and the western path. Contrary, cold surges in the 2000s occurred most frequently with a weak relative intensity during 1951−2011; the cold air originating from Novaya Zemlya invaded North China along northern path. Since the early 2000s, the sea ice in Novaya Zemlya and Buffin Bay has experienced a significant decrease in autumn and winter, which changed some atmospheric circulation systems. The Eurasian continent experienced a stronger large-scale trough/ridge with a stronger East Asia trough and Siberian High. In addition, weaker westerlies and higher geopotential height were observed around the Arctic in the 2000s compared to those in the 1990s, leading to the difference in cold surges in North China between these two decades.
The present study compares North China's cold surges in the 1990s and 2000s and their relationships with Arctic sea ice using the observed temperature, two atmospheric reanalyses from NCEP/NCAR, and a set of high-resolution sea ice concentration data from NOAA. In the 1990s, North China experienced less frequent cold surges with a strong relative intensity from 1951 to 2011, resulting from cold air originating from Greenland and invading North China and the western path. Contrary, cold surges in the 2000s occurred most frequently with a weak relative intensity during 1951−2011; the cold air originating from Novaya Zemlya invaded North China along northern path. Since the early 2000s, the sea ice in Novaya Zemlya and Buffin Bay has experienced a significant decrease in autumn and winter, which changed some atmospheric circulation systems. The Eurasian continent experienced a stronger large-scale trough/ridge with a stronger East Asia trough and Siberian High. In addition, weaker westerlies and higher geopotential height were observed around the Arctic in the 2000s compared to those in the 1990s, leading to the difference in cold surges in North China between these two decades.
2022, 27(3): 383-396.
doi: 10.3878/j.issn.1006-9585.2021.21037
Abstract:
QM and QDM methods are used to correct simulated temperature and precipitation over China from a set of regional climate model (RegCM4) projection simulations in which the RegCM4 is driven by five different general circulation models. Extreme climate indices are derived separately based on both original-simulation and bias-corrected results, and a comparative analysis is conducted. Both the individual simulations and ensemble RCM (ensR) show higher simulation skill scores in the temperature indices compared to those in the precipitation indices in which the annual maximummax daily maximum temperature (TXx) is the best and the annual maximum consecutive dry days (CDD) is the worst. Biases can be effectively reduced using both the QM and QDM methods for all the five simulations and ensR. After bias corrections, the spatial correlations between the simulations and observations are certainly increased. No significant differences exist in the correction effects of the two methods. For future changes under RCP4.5, the QM modifies the originally projected change magnitudes and spatial patterns of changes, whereas the QDM effectively preserves the climate change signals in the extreme indices. Changes in the national average show that all the indices except the CDD will continuously increase, and the results corrected through the QDM are closer to the original future projection simulations. Therefore, employing the QDM to correct climate change simulations is recommended.
QM and QDM methods are used to correct simulated temperature and precipitation over China from a set of regional climate model (RegCM4) projection simulations in which the RegCM4 is driven by five different general circulation models. Extreme climate indices are derived separately based on both original-simulation and bias-corrected results, and a comparative analysis is conducted. Both the individual simulations and ensemble RCM (ensR) show higher simulation skill scores in the temperature indices compared to those in the precipitation indices in which the annual maximummax daily maximum temperature (TXx) is the best and the annual maximum consecutive dry days (CDD) is the worst. Biases can be effectively reduced using both the QM and QDM methods for all the five simulations and ensR. After bias corrections, the spatial correlations between the simulations and observations are certainly increased. No significant differences exist in the correction effects of the two methods. For future changes under RCP4.5, the QM modifies the originally projected change magnitudes and spatial patterns of changes, whereas the QDM effectively preserves the climate change signals in the extreme indices. Changes in the national average show that all the indices except the CDD will continuously increase, and the results corrected through the QDM are closer to the original future projection simulations. Therefore, employing the QDM to correct climate change simulations is recommended.
2022, 27(3): 397-407.
doi: 10.3878/j.issn.1006-9585.2021.21043
Abstract:
Utilizing the hourly precipitation from reference meteorological stations and automatic meteorological stations during 2010–2019, temporal and spatial distribution characteristics of short-time heavy rainfall in Zhejiang Province were analyzed. Results show the following: 1) During 2010–2019, the cumulative frequency of short-time heavy rainfall in Zhejiang was 72601, which decayed exponentially with the increase of intensity. 2) The spatial distribution of short-time heavy rainfall is uneven. The frequency of occurrence decreased from coastal to inland, and the highest frequency occurred in the southwest of Wenzhou. As the influence system changes over time in summer, the spatial distribution of short-time heavy rainfall also changes. Short-time heavy rainfall frequently occurred in western Zhejiang from May to June, which were scattered throughout the province without obvious regional concentration characteristics in July and mainly occurred in coastal areas from August to October. 3) The diurnal variation of short-time heavy rainfall exhibited a peak of 1700 LST. The high-intensity precipitation tended to occur more in the afternoon or at dusk. In summer and autumn, short-time heavy rainfall mostly occurred in the afternoon or at dusk with a peak of 1700 LST–1800 LST. This was related to the strong subtropical high and the good heat and unstable conditions, which could easily trigger strong convective weather. In spring, except in the afternoon and at dusk, short-time heavy rainfall also frequently occurred at night and early in the morning, which may be related to the strengthening of low-level jets. The monthly variation presented a bimodal distribution, with August being the most active (26.0%) (mainly contributed to typhoon precipitation), which was followed by June and July. Moreover, there were obvious differences in the monthly variation characteristics of short-time heavy rainfall in different intensities. The interannual distribution of short-time heavy rainfall was uneven, and the interannual variability increased after 2015. The highest frequency of short-time heavy rainfall was 8728 in 2016, while the lowest frequency was only 5581 in 2017.
Utilizing the hourly precipitation from reference meteorological stations and automatic meteorological stations during 2010–2019, temporal and spatial distribution characteristics of short-time heavy rainfall in Zhejiang Province were analyzed. Results show the following: 1) During 2010–2019, the cumulative frequency of short-time heavy rainfall in Zhejiang was 72601, which decayed exponentially with the increase of intensity. 2) The spatial distribution of short-time heavy rainfall is uneven. The frequency of occurrence decreased from coastal to inland, and the highest frequency occurred in the southwest of Wenzhou. As the influence system changes over time in summer, the spatial distribution of short-time heavy rainfall also changes. Short-time heavy rainfall frequently occurred in western Zhejiang from May to June, which were scattered throughout the province without obvious regional concentration characteristics in July and mainly occurred in coastal areas from August to October. 3) The diurnal variation of short-time heavy rainfall exhibited a peak of 1700 LST. The high-intensity precipitation tended to occur more in the afternoon or at dusk. In summer and autumn, short-time heavy rainfall mostly occurred in the afternoon or at dusk with a peak of 1700 LST–1800 LST. This was related to the strong subtropical high and the good heat and unstable conditions, which could easily trigger strong convective weather. In spring, except in the afternoon and at dusk, short-time heavy rainfall also frequently occurred at night and early in the morning, which may be related to the strengthening of low-level jets. The monthly variation presented a bimodal distribution, with August being the most active (26.0%) (mainly contributed to typhoon precipitation), which was followed by June and July. Moreover, there were obvious differences in the monthly variation characteristics of short-time heavy rainfall in different intensities. The interannual distribution of short-time heavy rainfall was uneven, and the interannual variability increased after 2015. The highest frequency of short-time heavy rainfall was 8728 in 2016, while the lowest frequency was only 5581 in 2017.
2022, 27(3): 408-420.
doi: 10.3878/j.issn.1006-9585.2021.21048
Abstract:
The spatio–temporal distribution characteristics of freezing rain are of high guiding significance for many departments, including electric power, transportation, communications, agriculture, and forestry. Previous studies on freezing rain were mostly based on observation data. Due to the short length, uneven distribution, and partial lack of data, the current understanding of spatio–temporall distribution characteristics may still be insufficient. The ERA5 reanalysis data contains freezing rain data that were not contained in other reanalysis data, which provides the possibility of further understanding the distribution characteristics. This paper uses the ERA5 freezing rain data to analyze the annual and interdecadal characteristics of China’s freezing rain days and freezing rainfall from 1979 to 2020. The results show that China’s annual freezing rain days and rainfall are mostly concentrated in Guizhou, Hunan, etc., directly affecting seven “West-to-East” ultra-high voltage direct current transmission lines, covering a total length of about 4,900 kilometers. The annual freezing rain days and rainfall in concentrated areas show a downward trend. As for the first EOF (Empirical orthogonal function) mode (variance contribution 36.96%) of the number of freezing rain days, it is mainly distributed along the east of the Heihe−Tengchong line, showing an overall decreasing trend, and there is a north−south reverse distribution with the Qinling–Huaihe line as the boundary. The second EOF mode (variance contribution 11.56%) of the number of freezing rain days reflects two anti-phase regions in the southern freezing rain concentrated area, and the phase alternate period spans from one to five years. The EOF mode distribution of the annual freezing rainfall is similar to the annual number of freezing rain days.
The spatio–temporal distribution characteristics of freezing rain are of high guiding significance for many departments, including electric power, transportation, communications, agriculture, and forestry. Previous studies on freezing rain were mostly based on observation data. Due to the short length, uneven distribution, and partial lack of data, the current understanding of spatio–temporall distribution characteristics may still be insufficient. The ERA5 reanalysis data contains freezing rain data that were not contained in other reanalysis data, which provides the possibility of further understanding the distribution characteristics. This paper uses the ERA5 freezing rain data to analyze the annual and interdecadal characteristics of China’s freezing rain days and freezing rainfall from 1979 to 2020. The results show that China’s annual freezing rain days and rainfall are mostly concentrated in Guizhou, Hunan, etc., directly affecting seven “West-to-East” ultra-high voltage direct current transmission lines, covering a total length of about 4,900 kilometers. The annual freezing rain days and rainfall in concentrated areas show a downward trend. As for the first EOF (Empirical orthogonal function) mode (variance contribution 36.96%) of the number of freezing rain days, it is mainly distributed along the east of the Heihe−Tengchong line, showing an overall decreasing trend, and there is a north−south reverse distribution with the Qinling–Huaihe line as the boundary. The second EOF mode (variance contribution 11.56%) of the number of freezing rain days reflects two anti-phase regions in the southern freezing rain concentrated area, and the phase alternate period spans from one to five years. The EOF mode distribution of the annual freezing rainfall is similar to the annual number of freezing rain days.
2022, 27(3): 421-435.
doi: 10.3878/j.issn.1006-9585.2021.21057
Abstract:
In early June, there normally appears a rapid increase followed by a near steadiness of area-mean temperature of northern Asia, which features the transition of general circulation from winter to summer. Based on the timing of summer onset in northern Asia each year (hereafter referred to as summer onset) from 1951 to 2017, along with NCEP reanalysis data and the observation data in China, the connection of the summer onset with the precipitation and circulation anomalies in China during the Meiyu period is studied. It is attained that in the early (late) summer onset years, there is a “+ − +” (“− + −”) meridional wave train like structure of anomaly geopotential height field at mid-troposphere (500 hPa) ranging from northeast Asia, northeast area of China, and western Pacific Ocean. Similarly, a wave train structure is also found in the anomaly wind field at 850 hPa, i. e. a cyclonic (anticyclonic) circulation over northeastern area of China and an anticyclonic (cyclonic) circulation over the subtropical western Pacific. These circulation anomalies lead to a less (more) precipitation in the Yangtze River basin, and flood (drought) in the Northeast China during the Meiyu period. In the paper, a preliminary investigation on the approach by which the timing of summer onset influences the anomaly circulation and precipitation in Meiyu period is also attempted. It is shown that in the early (late) summer onset years, the ridge over northeastern Asia is established earlier (later) and stronger (weaker) than the normal. The time of the summer onset affects the ridge over northeastern Asia and the circulation and precipitation anomalies in the Eastern China during Meiyu period. The anomalous ridge over northeastern Asia maintains till the end of Meiyu. As the ridge over northeastern Asia is stronger (weaker) favors the formation and maintenance of “+ − +” (“− + −”) meridional wave train along the coast of East Asia, hence the distribution of rain belt.
In early June, there normally appears a rapid increase followed by a near steadiness of area-mean temperature of northern Asia, which features the transition of general circulation from winter to summer. Based on the timing of summer onset in northern Asia each year (hereafter referred to as summer onset) from 1951 to 2017, along with NCEP reanalysis data and the observation data in China, the connection of the summer onset with the precipitation and circulation anomalies in China during the Meiyu period is studied. It is attained that in the early (late) summer onset years, there is a “+ − +” (“− + −”) meridional wave train like structure of anomaly geopotential height field at mid-troposphere (500 hPa) ranging from northeast Asia, northeast area of China, and western Pacific Ocean. Similarly, a wave train structure is also found in the anomaly wind field at 850 hPa, i. e. a cyclonic (anticyclonic) circulation over northeastern area of China and an anticyclonic (cyclonic) circulation over the subtropical western Pacific. These circulation anomalies lead to a less (more) precipitation in the Yangtze River basin, and flood (drought) in the Northeast China during the Meiyu period. In the paper, a preliminary investigation on the approach by which the timing of summer onset influences the anomaly circulation and precipitation in Meiyu period is also attempted. It is shown that in the early (late) summer onset years, the ridge over northeastern Asia is established earlier (later) and stronger (weaker) than the normal. The time of the summer onset affects the ridge over northeastern Asia and the circulation and precipitation anomalies in the Eastern China during Meiyu period. The anomalous ridge over northeastern Asia maintains till the end of Meiyu. As the ridge over northeastern Asia is stronger (weaker) favors the formation and maintenance of “+ − +” (“− + −”) meridional wave train along the coast of East Asia, hence the distribution of rain belt.
2022, 27(3): 436-446.
doi: 10.3878/j.issn.1006-9585.2021.21062
Abstract:
Based on the sea ice data from 1979 to 2017, this study used linear regression and a linear baroclinic model to investigate the differences in Antarctic sea ice in Austral summer during two types of El Niño events (Eastern-Pacific, EP and Central-Pacific, CP) and their potential physical mechanisms. The results suggest that the amplitude and spatial pattern of sea ice anomalies differ, despite some similarities. The sea ice anomalies in the Ross Sea and the Amundsen Sea are negative in both EP and CP events, but they are more robust in the EP event than the CP event. The sea ice anomalies in the Weddell Sea are positive, and they are stronger and farther northwestward in the EP event relative to the CP event. The difference in the intensity of sea temperature anomalies between EP and CP events is a major reason for the different amplitude of sea ice. The sea surface temperature anomalies are stronger in the EP event than the CP event, forcing a Pacific–South America teleconnection pattern with a stronger high-pressure anomaly. In the EP event, such atmospheric circulation causes a northeast wind anomaly in the Ross Sea, transporting sea ice to high latitudes and decreasing sea ice. It causes a south wind anomaly in the Weddell Sea, causing sea ice to accumulate on the northern Weddell Sea. Compared to the EP event, the Pacific–South America teleconnection anomaly forced by the CP event is weaker, which induced weaker sea ice anomalies. The positive anomaly of sea ice in the Weddell Sea appeared during the CP event in November and grew stronger due to the ice–albedo feedback in the following spring. Our findings suggest that sea ice anomalies are stronger when the sea surface temperature anomalies in the tropical Pacific are stronger. It differs from previous studies but is more reasonable.
Based on the sea ice data from 1979 to 2017, this study used linear regression and a linear baroclinic model to investigate the differences in Antarctic sea ice in Austral summer during two types of El Niño events (Eastern-Pacific, EP and Central-Pacific, CP) and their potential physical mechanisms. The results suggest that the amplitude and spatial pattern of sea ice anomalies differ, despite some similarities. The sea ice anomalies in the Ross Sea and the Amundsen Sea are negative in both EP and CP events, but they are more robust in the EP event than the CP event. The sea ice anomalies in the Weddell Sea are positive, and they are stronger and farther northwestward in the EP event relative to the CP event. The difference in the intensity of sea temperature anomalies between EP and CP events is a major reason for the different amplitude of sea ice. The sea surface temperature anomalies are stronger in the EP event than the CP event, forcing a Pacific–South America teleconnection pattern with a stronger high-pressure anomaly. In the EP event, such atmospheric circulation causes a northeast wind anomaly in the Ross Sea, transporting sea ice to high latitudes and decreasing sea ice. It causes a south wind anomaly in the Weddell Sea, causing sea ice to accumulate on the northern Weddell Sea. Compared to the EP event, the Pacific–South America teleconnection anomaly forced by the CP event is weaker, which induced weaker sea ice anomalies. The positive anomaly of sea ice in the Weddell Sea appeared during the CP event in November and grew stronger due to the ice–albedo feedback in the following spring. Our findings suggest that sea ice anomalies are stronger when the sea surface temperature anomalies in the tropical Pacific are stronger. It differs from previous studies but is more reasonable.
, Available online ,
doi: 10.3878/j.issn.1006-9585.2022.21119
Abstract:
, Available online ,
doi: 10.3878/j.issn.1006-9585.2021.21165
Abstract:
, Available online ,
doi: 10.3878/j.issn.1006-9585.2022.22015
Abstract:
Since 1996 Bimonthly
Supervisor: Chinese Academy of Sciences
Sponsors by: Institute of Atmospheric Physics, Chinese Academy of Sciences/Chinese Meteorological Society
Editor: Wang Zifa
Email: qhhj@mail.iap.ac.cn
ISSN 1006-9585
CN 11-3693/P
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