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, Available online ,
doi: 10.3878/j.issn.1006-9585.2022.22023
Abstract:
Restriction measures against coronavirus disease 2019 (COVID-19) caused atmospheric trace species to change, especially in relation to air pollution. This severe pollutant emission reduction phenomenon during the pandemic led to intensive studies on its behavior. Most studies evidence a decrease in all pollutants except for O3. However, is this highlighted O3 trend a global trend? This study summarized the research results in the past two years and explored the characteristics, mechanisms, and potential environmental effects of tropospheric O3 and its precursors during the COVID-19 pandemic. During lockdown periods, global anthropogenic NOx emissions decreased by at least 15%; especially, those in high-anthropogenic areas decreased by 18%–25%. In some highly polluted areas (volatile organic compound (VOC)-sensitive areas), NOx emissions on the ground decreased by more than 50%. NOx reduction led to the weakened titration effect of NO on O3, leading to an increase in O3 in such highly polluted areas (10%–50%). However, O3 in remote areas and free troposphere (NOx-sensitive areas) decreased, attributed to NOx reduction and regional transmission effect. During the strict control period of the pandemic, surface O3 was still increasing in most cities in China with significantly decreased NOx concentration, indicating that the effective way to control surface O3 concentration in urban areas in China is controlling O3 precursors based on the sensitive area of O3 chemical generation. However, the drastic change in NOx in each region could change the sensitive area of O3 chemical generation, leading to a change in O3 production efficiency. However, due to the lack of VOC emission measurement and their atmospheric concentration, there are still great uncertainties in the trend and main controlling factors of O3 in each region. In the future, the characteristics of O3 in different regions and corresponding O3 regulation strategies influenced by COVID-19 and global warming are also worthy of further study.
Restriction measures against coronavirus disease 2019 (COVID-19) caused atmospheric trace species to change, especially in relation to air pollution. This severe pollutant emission reduction phenomenon during the pandemic led to intensive studies on its behavior. Most studies evidence a decrease in all pollutants except for O3. However, is this highlighted O3 trend a global trend? This study summarized the research results in the past two years and explored the characteristics, mechanisms, and potential environmental effects of tropospheric O3 and its precursors during the COVID-19 pandemic. During lockdown periods, global anthropogenic NOx emissions decreased by at least 15%; especially, those in high-anthropogenic areas decreased by 18%–25%. In some highly polluted areas (volatile organic compound (VOC)-sensitive areas), NOx emissions on the ground decreased by more than 50%. NOx reduction led to the weakened titration effect of NO on O3, leading to an increase in O3 in such highly polluted areas (10%–50%). However, O3 in remote areas and free troposphere (NOx-sensitive areas) decreased, attributed to NOx reduction and regional transmission effect. During the strict control period of the pandemic, surface O3 was still increasing in most cities in China with significantly decreased NOx concentration, indicating that the effective way to control surface O3 concentration in urban areas in China is controlling O3 precursors based on the sensitive area of O3 chemical generation. However, the drastic change in NOx in each region could change the sensitive area of O3 chemical generation, leading to a change in O3 production efficiency. However, due to the lack of VOC emission measurement and their atmospheric concentration, there are still great uncertainties in the trend and main controlling factors of O3 in each region. In the future, the characteristics of O3 in different regions and corresponding O3 regulation strategies influenced by COVID-19 and global warming are also worthy of further study.
, Available online ,
doi: 10.3878/j.issn.1006-9585.2021.21086
Abstract:
On the basis of a reanalysis of the monthly mean data of surface sensible heat and atmospheric circulation data provided by the Japan Meteorological Agency (JMA), sea surface temperature (SST) data provided by the National Oceanic and Atmospheric Administration, and the monthly precipitation data from 1979 to 2019 provided by the Nation Meteorological Information Center, the possible linkage between SH over the Iranian Plateau and SST over the tropical Indian Ocean in summer and precipitation over the Tarim Basin in the same period is analyzed. Singular value decomposition shows that the surface thermal anomalies in both areas are closely related to summer precipitation in the Tarim Basin and can modulate the precipitation variation by influencing the wind at 500 hPa and water flux transportation. When corresponding to stronger (weaker) sensible heat over the Iranian Plateau and warmer (colder) SSTs over the tropical Indian Ocean, on the one hand, an anomalous cyclone (anticyclone) over central Asia and an anticyclone (cyclone) over the Mongolian Plateau cause the anomalous south (north) wind to prevail over the Tarim Basin and (do not) form favorable dynamic conditions; on the other hand, because of an anomalous anticyclone (cyclone) over the Indian Peninsula and an anomalous cyclone (anticyclone) over central Asia, the water vapor can (not) be transported to the Tarim Basin by two-step transportation based on the above two anomalous circulations. All of the abovementioned components contribute to more (less) summer precipitation occurring. When the heating anomalies over the Iranian Plateau and tropical Indian Ocean are in opposition, they can lead to more precipitation in some regions of the Tarim Basin and less precipitation in other regions.
On the basis of a reanalysis of the monthly mean data of surface sensible heat and atmospheric circulation data provided by the Japan Meteorological Agency (JMA), sea surface temperature (SST) data provided by the National Oceanic and Atmospheric Administration, and the monthly precipitation data from 1979 to 2019 provided by the Nation Meteorological Information Center, the possible linkage between SH over the Iranian Plateau and SST over the tropical Indian Ocean in summer and precipitation over the Tarim Basin in the same period is analyzed. Singular value decomposition shows that the surface thermal anomalies in both areas are closely related to summer precipitation in the Tarim Basin and can modulate the precipitation variation by influencing the wind at 500 hPa and water flux transportation. When corresponding to stronger (weaker) sensible heat over the Iranian Plateau and warmer (colder) SSTs over the tropical Indian Ocean, on the one hand, an anomalous cyclone (anticyclone) over central Asia and an anticyclone (cyclone) over the Mongolian Plateau cause the anomalous south (north) wind to prevail over the Tarim Basin and (do not) form favorable dynamic conditions; on the other hand, because of an anomalous anticyclone (cyclone) over the Indian Peninsula and an anomalous cyclone (anticyclone) over central Asia, the water vapor can (not) be transported to the Tarim Basin by two-step transportation based on the above two anomalous circulations. All of the abovementioned components contribute to more (less) summer precipitation occurring. When the heating anomalies over the Iranian Plateau and tropical Indian Ocean are in opposition, they can lead to more precipitation in some regions of the Tarim Basin and less precipitation in other regions.
, Available online ,
doi: 10.3878/j.issn.1006-9585.2022.21140
Abstract:
The 6.25 km high-resolution downscaling projection datasets under the RCP4.5 scenario based on a combined dynamical (RegCM) and statistical downscaling method are used to evaluate and project the future extreme climatic events and the associated risks in the Yangtze River Economic Zone (YREZ). The results show that the datasets can well reproduce the spatial distribution of all temperature extremes and most precipitation extremes, providing a reliable forecasting capability. However, Slightly larger deviations in some extreme precipitation indices The heat events will increase, while the cold events will decrease substantially in the YREZ. Extreme precipitation is projected to increase in the lower and eastern middle reaches and decrease in the east and south upper reaches. The gross domestic product (GDP) exposure to heat events and heavy rainfall showed an increasing trend in the 21st century in YREZ, most significantly in the lower reaches. Meanwhile, population (POP) exposure increased and then decreased in the 21st century. The contribution of the distribution factor and the non-linear factor are equally important for GDP exposure to high events, while the distribution factor having a greater impact in POP exposure. The GDP (POP) exposure to heavy rainfall mainly depends on its distribution factor.
The 6.25 km high-resolution downscaling projection datasets under the RCP4.5 scenario based on a combined dynamical (RegCM) and statistical downscaling method are used to evaluate and project the future extreme climatic events and the associated risks in the Yangtze River Economic Zone (YREZ). The results show that the datasets can well reproduce the spatial distribution of all temperature extremes and most precipitation extremes, providing a reliable forecasting capability. However, Slightly larger deviations in some extreme precipitation indices The heat events will increase, while the cold events will decrease substantially in the YREZ. Extreme precipitation is projected to increase in the lower and eastern middle reaches and decrease in the east and south upper reaches. The gross domestic product (GDP) exposure to heat events and heavy rainfall showed an increasing trend in the 21st century in YREZ, most significantly in the lower reaches. Meanwhile, population (POP) exposure increased and then decreased in the 21st century. The contribution of the distribution factor and the non-linear factor are equally important for GDP exposure to high events, while the distribution factor having a greater impact in POP exposure. The GDP (POP) exposure to heavy rainfall mainly depends on its distribution factor.
, Available online ,
doi: 10.3878/j.issn.1006-9585.2022.22009
Abstract:
With the PML-V2 model, the evapotranspiration was separated and the trends of intrinsic water use efficiency (iWUE) and canopy water use efficiency (tWUE) was calculated to investigate the differences between them. The results show that the change in these two types of water use efficiency is inconsistent at the site scale. The trend of iWUE is greater than that of iWUE in deciduous broadleaf forests (DBF), whereas the contrary occurs in evergreen coniferous forests (ENF). The discrepancy in canopy conductance and transpiration trends can help explain the difference in iWUE and tWUE trends in DBF. Regression analysis revealed that the trends of air temperature and carbon dioxide concentration in forests (DBF and ENF) have a stronge influence on the trend of tWUE. The results of this paper demonstratethe differences between the trends of iWUE and tWUE. Therefore, study results about iWUE cannot fully indicate the trends of the actual water use efficiency of vegetation, and they cannot thoroughly reflect the interactions between vegetation and the atmosphere. This study reveals the trend difference between iWUE and tWUE under the background of global climate change, which is useful for understanding the interactions between terrestrial ecosystems and the atmosphere and provides a useful reference for predicting future climate change and the evolution of terrestrial vegetation reasonably and effectively.
With the PML-V2 model, the evapotranspiration was separated and the trends of intrinsic water use efficiency (iWUE) and canopy water use efficiency (tWUE) was calculated to investigate the differences between them. The results show that the change in these two types of water use efficiency is inconsistent at the site scale. The trend of iWUE is greater than that of iWUE in deciduous broadleaf forests (DBF), whereas the contrary occurs in evergreen coniferous forests (ENF). The discrepancy in canopy conductance and transpiration trends can help explain the difference in iWUE and tWUE trends in DBF. Regression analysis revealed that the trends of air temperature and carbon dioxide concentration in forests (DBF and ENF) have a stronge influence on the trend of tWUE. The results of this paper demonstratethe differences between the trends of iWUE and tWUE. Therefore, study results about iWUE cannot fully indicate the trends of the actual water use efficiency of vegetation, and they cannot thoroughly reflect the interactions between vegetation and the atmosphere. This study reveals the trend difference between iWUE and tWUE under the background of global climate change, which is useful for understanding the interactions between terrestrial ecosystems and the atmosphere and provides a useful reference for predicting future climate change and the evolution of terrestrial vegetation reasonably and effectively.
, Available online ,
doi: 10.3878/j.issn.1006-9585.2022.21155
Abstract:
The characteristics of the interannual variability of winter (December–February) precipitation over South China and their association with atmospheric and preceding ocean conditions are analyzed using the observed precipitation data from 160 surface meteorological stations in China, the NCEP/NCAR reanalysis dataset, and the sea surface temperature (SST) dataset from the Met Office Hadley Center. The precipitation tends to be more (less) than the climatology under a southward (northward) shift of the East Asian jet stream, the weakened (strengthened) East Asian trough, and the enhanced (attenuated) transient eddy. The southwesterly winds from the Bay of Bengal and the South China Sea in the front of the southern branch trough favor more precipitation over South China. Further analysis suggests that the preceding SST anomalies (SSTAs) over the tropical Indian Ocean and western tropical Pacific in November have a closer relationship with the southern branch trough and low-level southwesterly winds associated with the variation in precipitation over South China, which could not be well explained by the ENSO-like SSTAs. The correlation coefficient between precipitation over South China and the derived index from the preceding SSTA is 0.44 and reaches a maximum when the SSTA index leads precipitation anomalies by approximately one month, which may act as a potential precursor for wintertime precipitation predictions..
The characteristics of the interannual variability of winter (December–February) precipitation over South China and their association with atmospheric and preceding ocean conditions are analyzed using the observed precipitation data from 160 surface meteorological stations in China, the NCEP/NCAR reanalysis dataset, and the sea surface temperature (SST) dataset from the Met Office Hadley Center. The precipitation tends to be more (less) than the climatology under a southward (northward) shift of the East Asian jet stream, the weakened (strengthened) East Asian trough, and the enhanced (attenuated) transient eddy. The southwesterly winds from the Bay of Bengal and the South China Sea in the front of the southern branch trough favor more precipitation over South China. Further analysis suggests that the preceding SST anomalies (SSTAs) over the tropical Indian Ocean and western tropical Pacific in November have a closer relationship with the southern branch trough and low-level southwesterly winds associated with the variation in precipitation over South China, which could not be well explained by the ENSO-like SSTAs. The correlation coefficient between precipitation over South China and the derived index from the preceding SSTA is 0.44 and reaches a maximum when the SSTA index leads precipitation anomalies by approximately one month, which may act as a potential precursor for wintertime precipitation predictions..
, Available online ,
doi: 10.3878/j.issn.1006-9585.2022.21199
Abstract:
Based on the Nested Grid Air Quality Prediction Model System (NAQPMS), the emission source inversion method is utilized to optimize the estimation of ozone (O3) precursor in the emission a priori inventory dominated by China Multi-Scale Emission Inventory (MEIC). From June to August 2019, the effect of improving O3 simulation by employing source inversion emission inventory is mostly examined in “2+26” Cities, Yangtze River Delta, Pearl River Delta, and Chengdu−Chongqing urban agglomerations with severe O3 pollution from June to August 2019 (summer). The evaluation results show that the nitrogen oxide (NOx) emission rate obtained by source inversion is lower than the a priori inventory emission rate of about 0.6 μg m−2 s−1, but the volatile organic compounds (VOCs) emission rate of inversion is higher than the a priori inventory emission rate of about 0.5 μg m−2 s−1 in “2+26” cities. The source inversion emission inventory is used to simulate O3 in four urban agglomerations, and the simulated performance of O3 in summer could be significantly improved by inversion emission data, which reduces the root-mean-square error (RMSE) of the maximum eight-hour mean of O3 (MDA8-O3) from 40–60 μg/m³ to 20–30 μg/m³ and increases the correlation coefficient from 0.6–0.7 to more than 0.8. The discrepancy between the simulated and observed diurnal variation peaks of O3 narrowed from 2–50 μg/m³ to 2–20 μg/m³. The results of this study show that pollution source inversion based on ground observation data may effectively improve the performance of O3 simulation in the key urban agglomeration, and the difference between the emissions of O3 precursor inversion emissions and the a priori inventory may provide a reference for the effectiveness and evaluation of the a priori inventory.
Based on the Nested Grid Air Quality Prediction Model System (NAQPMS), the emission source inversion method is utilized to optimize the estimation of ozone (O3) precursor in the emission a priori inventory dominated by China Multi-Scale Emission Inventory (MEIC). From June to August 2019, the effect of improving O3 simulation by employing source inversion emission inventory is mostly examined in “2+26” Cities, Yangtze River Delta, Pearl River Delta, and Chengdu−Chongqing urban agglomerations with severe O3 pollution from June to August 2019 (summer). The evaluation results show that the nitrogen oxide (NOx) emission rate obtained by source inversion is lower than the a priori inventory emission rate of about 0.6 μg m−2 s−1, but the volatile organic compounds (VOCs) emission rate of inversion is higher than the a priori inventory emission rate of about 0.5 μg m−2 s−1 in “2+26” cities. The source inversion emission inventory is used to simulate O3 in four urban agglomerations, and the simulated performance of O3 in summer could be significantly improved by inversion emission data, which reduces the root-mean-square error (RMSE) of the maximum eight-hour mean of O3 (MDA8-O3) from 40–60 μg/m³ to 20–30 μg/m³ and increases the correlation coefficient from 0.6–0.7 to more than 0.8. The discrepancy between the simulated and observed diurnal variation peaks of O3 narrowed from 2–50 μg/m³ to 2–20 μg/m³. The results of this study show that pollution source inversion based on ground observation data may effectively improve the performance of O3 simulation in the key urban agglomeration, and the difference between the emissions of O3 precursor inversion emissions and the a priori inventory may provide a reference for the effectiveness and evaluation of the a priori inventory.
, Available online ,
doi: 10.3878/j.issn.1006-9585.2022.22017
Abstract:
An analysis of the Antarctic Circumpolar Circulation (ACC) and the southern ocean meridional overturning circulation (MOC) simulated by the LICOM3.0 using the model outputs obtained from the ocean model intercomparison project (OMIP) is presented in this article. The mean, variability, and trends of the ACC and MOC over the 1958–2009 period are focused and their relationships with the surface forcing are studied. The model results are compared with available observations, simulation results from other models having finer resolutions, and also with theoretical constraints to check the reliability of the simulations. Generally, the ACC and the Southern Ocean MOC simulated by LICOM3.0 have a similar and reasonable mean state in the two experiments, presenting similar trends from 1958–2009. However, Southern Ocean transport has a larger trend in the OMIP1 experiment, which is related to surface forces. Their correlation needs to be studied further.
An analysis of the Antarctic Circumpolar Circulation (ACC) and the southern ocean meridional overturning circulation (MOC) simulated by the LICOM3.0 using the model outputs obtained from the ocean model intercomparison project (OMIP) is presented in this article. The mean, variability, and trends of the ACC and MOC over the 1958–2009 period are focused and their relationships with the surface forcing are studied. The model results are compared with available observations, simulation results from other models having finer resolutions, and also with theoretical constraints to check the reliability of the simulations. Generally, the ACC and the Southern Ocean MOC simulated by LICOM3.0 have a similar and reasonable mean state in the two experiments, presenting similar trends from 1958–2009. However, Southern Ocean transport has a larger trend in the OMIP1 experiment, which is related to surface forces. Their correlation needs to be studied further.
, Available online ,
doi: 10.3878/j.issn.1006-9585.2022.22011
Abstract:
Wildfire activities in the Arctic have increased in recent years, especially after the extraordinary explosions in 2019–2020. This study investigated the relationships between wildfire carbon emissions and meteorological factors in the key regions of the Arctic during 1997–2020, with the stepwise regression method using a series of meteorological variables (snowfall, precipitation, wind speed, relative humidity, 2-meter air temperature, and daily maximum temperature) from MERRA-2 re-analyses and the Fire Weather Index (FWI). We further explored the dominant meteorological drivers for the large wildfires in the Arctic during 2019–2020. Results showed that in all three key regions, the Duff Moisture Code (DMC) from FWI makes the dominant contribution to wildfire emissions. The anomalously high geopotential height results in an extremely increased daily maximum temperature and significantly reduced precipitation, jointly leading to anomalously high DMC and consequent wildfire episodes during 2019–2020. This result suggests that climatic anomalies such as warming and drought promote frequent wildfire activities in the Arctic.
Wildfire activities in the Arctic have increased in recent years, especially after the extraordinary explosions in 2019–2020. This study investigated the relationships between wildfire carbon emissions and meteorological factors in the key regions of the Arctic during 1997–2020, with the stepwise regression method using a series of meteorological variables (snowfall, precipitation, wind speed, relative humidity, 2-meter air temperature, and daily maximum temperature) from MERRA-2 re-analyses and the Fire Weather Index (FWI). We further explored the dominant meteorological drivers for the large wildfires in the Arctic during 2019–2020. Results showed that in all three key regions, the Duff Moisture Code (DMC) from FWI makes the dominant contribution to wildfire emissions. The anomalously high geopotential height results in an extremely increased daily maximum temperature and significantly reduced precipitation, jointly leading to anomalously high DMC and consequent wildfire episodes during 2019–2020. This result suggests that climatic anomalies such as warming and drought promote frequent wildfire activities in the Arctic.
, Available online ,
doi: 10.3878/j.issn.1006-9585.2022.21178
Abstract:
Based on the global land cover type and coverage, we used the normalized difference vegetation Index (NDVI) and averaged climate state data (temperature, precipitation) of the growing season from 1982 to 2015 in this study. The relationship between global vegetation distribution and climate factors was discussed, and a multiple regression model was developed. The sensitivity of vegetation to climate states (temperature and precipitation) was analyzed. There was an apparent correspondence between vegetation and climate factors on the climate gradient. The regression model has fitted the distribution pattern of climatic NDVI well, and the correlation coefficient between global fitting and the observed NDVI was 0.90. Among them, the fitting ability of spatial distribution of the broadleaf evergreen forests, mixed forests, needleleaf evergreen forests, broadleaf deciduous forests, and cropland and woody savanna were great (R ＞ 0.8). The NDVIs of different land cover types demonstrated different spatial sensitivity characteristics to temperature and precipitation climate states. Overall, the sensitivity of vegetation to temperature and precipitation demonstrated an inversed correlation (r = −0.6). Different land cover types showed positive/negative sensitivity to temperature. Boreal shrubs demonstrated the greatest sensitivity to temperature, while crops, grasslands, and bare land proved the high negative sensitivity to temperature than others. The sensitivity of vegetation to precipitation was positive, and the spatial sensitivity of needleleaf deciduous forests, grass, and savanna to precipitation was high.
Based on the global land cover type and coverage, we used the normalized difference vegetation Index (NDVI) and averaged climate state data (temperature, precipitation) of the growing season from 1982 to 2015 in this study. The relationship between global vegetation distribution and climate factors was discussed, and a multiple regression model was developed. The sensitivity of vegetation to climate states (temperature and precipitation) was analyzed. There was an apparent correspondence between vegetation and climate factors on the climate gradient. The regression model has fitted the distribution pattern of climatic NDVI well, and the correlation coefficient between global fitting and the observed NDVI was 0.90. Among them, the fitting ability of spatial distribution of the broadleaf evergreen forests, mixed forests, needleleaf evergreen forests, broadleaf deciduous forests, and cropland and woody savanna were great (R ＞ 0.8). The NDVIs of different land cover types demonstrated different spatial sensitivity characteristics to temperature and precipitation climate states. Overall, the sensitivity of vegetation to temperature and precipitation demonstrated an inversed correlation (r = −0.6). Different land cover types showed positive/negative sensitivity to temperature. Boreal shrubs demonstrated the greatest sensitivity to temperature, while crops, grasslands, and bare land proved the high negative sensitivity to temperature than others. The sensitivity of vegetation to precipitation was positive, and the spatial sensitivity of needleleaf deciduous forests, grass, and savanna to precipitation was high.
, Available online ,
doi: 10.3878/j.issn.1006-9585.2022.21042
Abstract:
Dissecting the main features of climate change offers basic data for understanding how climate change affects ecosystem processes and provides scientific and technological support for climate change response. Over the last few decades, the rapid increase in temperature in the Chinese region has had a significant impact on ecosystems. However, few studies have hitherto focused on whether there are transitions in temperature and precipitation temporal trends and whether there are regional differences. Furthermore, the temperature and precipitation changes in the past decades have caused significant changes in moisture gain/loss levels, while the trends of moisture gain/loss in China have received poor attention. A sufficient understanding of the changes in moisture gain/loss levels in different regions can help us better understand the dry and wet changes in the region and improve the efficiency of water resource management and usage. Analyzing the temporal and spatial distribution of the turning points of temperature and precipitation changes will help understand the change trend of water profit and loss and spatial differences. Based on the observational data of 2479 meteorological stations in China, this study uses the segmented regression method to analyze the temporal change trends of annual average temperature, annual precipitation, and water surplus and loss from 1981 to 2015, and the temporal and spatial patterns of turning points. The main results are the following. (1) The national average temperature increased significantly from 1981 to 2015, which demonstrated obvious phase-change characteristics and regional differences: In Yunnan and in northern and northeastern regions, the temperature changed between 1991 and 1995, while the temperature in Yunnan began to increase significantly after 1991. The temperature transition period in most parts of southern Northeast and North China occurred between 1996 and 2000, and the temperature transition period in the southern coastal areas occurred between 2001 and 2005. The temperature increased significantly before the turning point, while it stagnated after the turning point. (2) The temporal precipitation trend in China from 1981 to 2015 significantly differs between different regions. In the arid areas of the western regions and the Shandong Peninsula, the annual precipitation increased significantly, while the precipitation in the southwestern region decreased significantly. In Shaanxi, Shanxi, and other places, the temporal trend of precipitation has turned. The precipitation decreased significantly before the turning point and increased significantly after the turning point. In most parts of the country, the number of precipitation days has decreased, the precipitation intensity has increased, and the frequency of extreme precipitation events has increased. (3) From 1981 to 2015, the water surplus and loss and the standardized precipitation evapotranspiration index in most areas of China dropped significantly, and China showed a trend of aridification. The temporal change trend of water surplus and loss occurred in Shanxi, Shaanxi, Yunnan, andYunnan. Shaanxi, Shanxi, and Yunnan decreased before the water surplus and loss turning point and increased after the turning point; Yunnan and other places increased before the water surplus and loss turning point and decreased after the turning point.
Dissecting the main features of climate change offers basic data for understanding how climate change affects ecosystem processes and provides scientific and technological support for climate change response. Over the last few decades, the rapid increase in temperature in the Chinese region has had a significant impact on ecosystems. However, few studies have hitherto focused on whether there are transitions in temperature and precipitation temporal trends and whether there are regional differences. Furthermore, the temperature and precipitation changes in the past decades have caused significant changes in moisture gain/loss levels, while the trends of moisture gain/loss in China have received poor attention. A sufficient understanding of the changes in moisture gain/loss levels in different regions can help us better understand the dry and wet changes in the region and improve the efficiency of water resource management and usage. Analyzing the temporal and spatial distribution of the turning points of temperature and precipitation changes will help understand the change trend of water profit and loss and spatial differences. Based on the observational data of 2479 meteorological stations in China, this study uses the segmented regression method to analyze the temporal change trends of annual average temperature, annual precipitation, and water surplus and loss from 1981 to 2015, and the temporal and spatial patterns of turning points. The main results are the following. (1) The national average temperature increased significantly from 1981 to 2015, which demonstrated obvious phase-change characteristics and regional differences: In Yunnan and in northern and northeastern regions, the temperature changed between 1991 and 1995, while the temperature in Yunnan began to increase significantly after 1991. The temperature transition period in most parts of southern Northeast and North China occurred between 1996 and 2000, and the temperature transition period in the southern coastal areas occurred between 2001 and 2005. The temperature increased significantly before the turning point, while it stagnated after the turning point. (2) The temporal precipitation trend in China from 1981 to 2015 significantly differs between different regions. In the arid areas of the western regions and the Shandong Peninsula, the annual precipitation increased significantly, while the precipitation in the southwestern region decreased significantly. In Shaanxi, Shanxi, and other places, the temporal trend of precipitation has turned. The precipitation decreased significantly before the turning point and increased significantly after the turning point. In most parts of the country, the number of precipitation days has decreased, the precipitation intensity has increased, and the frequency of extreme precipitation events has increased. (3) From 1981 to 2015, the water surplus and loss and the standardized precipitation evapotranspiration index in most areas of China dropped significantly, and China showed a trend of aridification. The temporal change trend of water surplus and loss occurred in Shanxi, Shaanxi, Yunnan, andYunnan. Shaanxi, Shanxi, and Yunnan decreased before the water surplus and loss turning point and increased after the turning point; Yunnan and other places increased before the water surplus and loss turning point and decreased after the turning point.
2022 Issue 6
Display Method:
2022, 27(6): 679-687.
doi: 10.3878/j.issn.1006-9585.2021.21165
Abstract:
The effects of the kinetic energy of upper jet disturbances on snowstorms on 9 February 2014, 5 December 2015, 20 January 2016, and 20 January 2018 were analyzed using ERA-Interim data. During snowstorms, an upper jet is usually present, causing vertical upward motion that aids in developing the snowstorm. The vertical motion serves two purposes. First, it transports warm and moist air at a low level to a high level, thus providing a continuous stream of water vapor for snowstorms. Second, it transports the kinetic energy of the jet disturbances downward to a intersection area of warm and cold air at a low level. This area exhibits wind shear that provides the kinetic energy of the disturbance to the local area and further promotes the occurrence and development of snowstorms.
The effects of the kinetic energy of upper jet disturbances on snowstorms on 9 February 2014, 5 December 2015, 20 January 2016, and 20 January 2018 were analyzed using ERA-Interim data. During snowstorms, an upper jet is usually present, causing vertical upward motion that aids in developing the snowstorm. The vertical motion serves two purposes. First, it transports warm and moist air at a low level to a high level, thus providing a continuous stream of water vapor for snowstorms. Second, it transports the kinetic energy of the jet disturbances downward to a intersection area of warm and cold air at a low level. This area exhibits wind shear that provides the kinetic energy of the disturbance to the local area and further promotes the occurrence and development of snowstorms.
2022, 27(6): 688-706.
doi: 10.3878/j.issn.1006-9585.2021.21084
Abstract:
Model evaluation is an important part of model development. In this study, the eddy covariance measurements from 30 FLUXNET sites of FLUXNET2015 dataset were used to evaluate the performance of the Common Land Model, version 2014 (CoLM2014) over different land-cover types, focusing on energy fluxes. The results show that the model captures the variation characteristics of sensible heat flux, latent heat flux, and net radiation flux at different time scales, such as the daily, seasonal, and annual averages, and has a good simulation ability for these fluxes. The simulation effect of net radiation is the best, followed by that of latent heat flux. When simulating seasonal variation, the spatial dispersion degree of sensible and latent heat fluxes under different vegetation types is greater in summer than in winter, and the simulation effect varies greatly among different stations. The variation range of net radiation standard deviation is smaller than sensible and latent heat fluxes, and the deviation of the simulation effect between different stations is small. The evaluation performances for evergreen needleleaf forests, savannas, grasslands, and croplands were relatively good, but poor performances were obtained when simulating the sensible heat flux in wetlands and deciduous broadleaf forests. This study provides a useful reference for improving and developing CoLM2014.
Model evaluation is an important part of model development. In this study, the eddy covariance measurements from 30 FLUXNET sites of FLUXNET2015 dataset were used to evaluate the performance of the Common Land Model, version 2014 (CoLM2014) over different land-cover types, focusing on energy fluxes. The results show that the model captures the variation characteristics of sensible heat flux, latent heat flux, and net radiation flux at different time scales, such as the daily, seasonal, and annual averages, and has a good simulation ability for these fluxes. The simulation effect of net radiation is the best, followed by that of latent heat flux. When simulating seasonal variation, the spatial dispersion degree of sensible and latent heat fluxes under different vegetation types is greater in summer than in winter, and the simulation effect varies greatly among different stations. The variation range of net radiation standard deviation is smaller than sensible and latent heat fluxes, and the deviation of the simulation effect between different stations is small. The evaluation performances for evergreen needleleaf forests, savannas, grasslands, and croplands were relatively good, but poor performances were obtained when simulating the sensible heat flux in wetlands and deciduous broadleaf forests. This study provides a useful reference for improving and developing CoLM2014.
2022, 27(6): 707-718.
doi: 10.3878/j.issn.1006-9585.2021.21158
Abstract:
The characteristics of atmospheric Intraseasonal Oscillation (ISO) activity over the tropical Indian Ocean and the Pacific are compared based on the reanalysis data. The results show seasonal jumps in the ISO activity centers over the Indian Ocean and the western Pacific in April and October. In addition, the meridional jumping distance of the ISO activity center over the western Pacific is larger than that over the Indian Ocean. The activity centers of stronger ISO are also the areas with greater annual amplitude in ISO intensity, and the ISO intensity of each activity center reached the peak at significantly different times. Considerable interannual and interdecadal variation is observed in ISO activity, and the intensity and variation trend of ISO show an obvious turning point in the 1980s. In summer, a strong northward propagation of ISO occurs over the Indian Ocean and the western Pacific. The equatorial ISO over the Indian Ocean is stronger than the ISO beyond the equator, and the ISO beyond the equator over the western Pacific is stronger than the equatorial ISO. Moreover, the northward propagation of ISO is slower over the western Pacific Ocean than over the Indian Ocean. When the ISO is active over the Indian Ocean and Western Pacific in winter and summer, its spatial distribution and vertical structure characteristics are obviously discrepant.
The characteristics of atmospheric Intraseasonal Oscillation (ISO) activity over the tropical Indian Ocean and the Pacific are compared based on the reanalysis data. The results show seasonal jumps in the ISO activity centers over the Indian Ocean and the western Pacific in April and October. In addition, the meridional jumping distance of the ISO activity center over the western Pacific is larger than that over the Indian Ocean. The activity centers of stronger ISO are also the areas with greater annual amplitude in ISO intensity, and the ISO intensity of each activity center reached the peak at significantly different times. Considerable interannual and interdecadal variation is observed in ISO activity, and the intensity and variation trend of ISO show an obvious turning point in the 1980s. In summer, a strong northward propagation of ISO occurs over the Indian Ocean and the western Pacific. The equatorial ISO over the Indian Ocean is stronger than the ISO beyond the equator, and the ISO beyond the equator over the western Pacific is stronger than the equatorial ISO. Moreover, the northward propagation of ISO is slower over the western Pacific Ocean than over the Indian Ocean. When the ISO is active over the Indian Ocean and Western Pacific in winter and summer, its spatial distribution and vertical structure characteristics are obviously discrepant.
2022, 27(6): 719-728.
doi: 10.3878/j.issn.1006-9585.2022.21040
Abstract:
The pollutant trajectory, atmospheric circulation background, and meteorological factors of a heavy air pollution fog/haze event in Qingdao from 15 January to 22 January 2018, were analyzed using routine weather observation, air quality monitoring data, and ECMWF reanalysis data. The results indicate that during the early stages of pollution in Qingdao, the primary sources were the convergence and accumulation of dry and cold air from Mongolia and wet air from the Yangtze–Huaihe River basin. In the late stage, the major sources were the local air pollutants in Shandong Province, with PM10 being the primary pollutant. During the pollution process, controlled by the ural blocking high and cold low pressure in central Siberia, the East Asian transverse trough remained stable over the mid-high latitude area at 500 hPa. Over Qingdao, westerly airflow was dominant, with low wind speeds near the ground. As the transverse trough turned vertical, the zonal circulation changed to meridional, the cold air moved southward, the wind speed increased drastically, and the fog/haze dissipated rapidly. Under stable atmospheric circulation, when the surface layer had a weak wind or continuous land breeze, the ascending and descending motion of the air in the lower troposphere was weak, and the water vapor condition was favorable for the maintenance of fog/haze. Thus, by analyzing the relationship among relative humidity, PM2.5 concentration, and visibility at various stages of the process, it was observed that during the haze stage, the influence of both factors was comparable; moreover, during the fog stage, visibility was primarily affected by relative humidity, and accumulation and increase of PM2.5 concentration under static and steady conditions were the primary factors affecting visibility during the fog and haze mixing stage.
The pollutant trajectory, atmospheric circulation background, and meteorological factors of a heavy air pollution fog/haze event in Qingdao from 15 January to 22 January 2018, were analyzed using routine weather observation, air quality monitoring data, and ECMWF reanalysis data. The results indicate that during the early stages of pollution in Qingdao, the primary sources were the convergence and accumulation of dry and cold air from Mongolia and wet air from the Yangtze–Huaihe River basin. In the late stage, the major sources were the local air pollutants in Shandong Province, with PM10 being the primary pollutant. During the pollution process, controlled by the ural blocking high and cold low pressure in central Siberia, the East Asian transverse trough remained stable over the mid-high latitude area at 500 hPa. Over Qingdao, westerly airflow was dominant, with low wind speeds near the ground. As the transverse trough turned vertical, the zonal circulation changed to meridional, the cold air moved southward, the wind speed increased drastically, and the fog/haze dissipated rapidly. Under stable atmospheric circulation, when the surface layer had a weak wind or continuous land breeze, the ascending and descending motion of the air in the lower troposphere was weak, and the water vapor condition was favorable for the maintenance of fog/haze. Thus, by analyzing the relationship among relative humidity, PM2.5 concentration, and visibility at various stages of the process, it was observed that during the haze stage, the influence of both factors was comparable; moreover, during the fog stage, visibility was primarily affected by relative humidity, and accumulation and increase of PM2.5 concentration under static and steady conditions were the primary factors affecting visibility during the fog and haze mixing stage.
2022, 27(6): 729-746.
doi: 10.3878/j.issn.1006-9585.2021.21112
Abstract:
In this study, the simulations of the subseasonal evolution of the East Asian summer monsoon (EASM) by BCC-CSM2-MR and BCC-ESM1 models, two models from the Beijing Climate Center participating in the 6th phase of the Coupled Model Intercomparison Project (CMIP6), are analyzed, including the characteristics of the climatological mean state and features in different ENSO phases. This study compares the results of the atmospheric general circulation model (AGCM) experiments, in which the AGCM is driven by observed sea ice/sea surface temperature (AMIP experiment), with the results of the Historical experiment using the air-sea coupled model. Results show that both models can reasonably reproduce the climate mean state features of the circulation and precipitation associated with the EASM. Compared to the AGCM, the coupled model can significantly improve the simulation of the climate mean state of EASM. For instance, the coupled model simulates the subseasonal variation of the western Pacific subtropical high (WPSH) with northward and eastward shifts from June to August better. With respect to the composites for El Niño decaying years and La Niña years, the atmospheric model can simulate the westward extension (eastward retreat) of WPSH and the associated weakening (strengthening) of convection in El Niño decaying years (La Niña years) to some extent. However, there are deviations in the simulation of the location and intensity of WPSH and convection centers, particularly on a subseasonal scale. Compared to the AGCM, the coupled model does not appear to significantly improve the simulation of the subseasonal evolution of the EASM with the ENSO cycle, which may be caused by the deviation of the ENSO simulation in the coupled model. To improve the simulation of the subseasonal evolution of the EASM and its interannual variation with the ENSO phase, the simulation of ENSO in the coupled model should be enhanced.
In this study, the simulations of the subseasonal evolution of the East Asian summer monsoon (EASM) by BCC-CSM2-MR and BCC-ESM1 models, two models from the Beijing Climate Center participating in the 6th phase of the Coupled Model Intercomparison Project (CMIP6), are analyzed, including the characteristics of the climatological mean state and features in different ENSO phases. This study compares the results of the atmospheric general circulation model (AGCM) experiments, in which the AGCM is driven by observed sea ice/sea surface temperature (AMIP experiment), with the results of the Historical experiment using the air-sea coupled model. Results show that both models can reasonably reproduce the climate mean state features of the circulation and precipitation associated with the EASM. Compared to the AGCM, the coupled model can significantly improve the simulation of the climate mean state of EASM. For instance, the coupled model simulates the subseasonal variation of the western Pacific subtropical high (WPSH) with northward and eastward shifts from June to August better. With respect to the composites for El Niño decaying years and La Niña years, the atmospheric model can simulate the westward extension (eastward retreat) of WPSH and the associated weakening (strengthening) of convection in El Niño decaying years (La Niña years) to some extent. However, there are deviations in the simulation of the location and intensity of WPSH and convection centers, particularly on a subseasonal scale. Compared to the AGCM, the coupled model does not appear to significantly improve the simulation of the subseasonal evolution of the EASM with the ENSO cycle, which may be caused by the deviation of the ENSO simulation in the coupled model. To improve the simulation of the subseasonal evolution of the EASM and its interannual variation with the ENSO phase, the simulation of ENSO in the coupled model should be enhanced.
2022, 27(6): 747-755.
doi: 10.3878/j.issn.1006-9585.2022.21147
Abstract:
The effective temperature in Beijing has been studied by the entire available observation data. The results demonstrate the following: 1) The annual temperature, wind speed, and effective temperature in Beijing were significantly affected by the topographic distribution, without a significant difference in the relative humidity between the mountainous and the urban areas. Beijing became drier and warmer over the study period. Regionally, the stations with the largest increase in the annual and effective temperatures were concentrated in the urban areas, and the stations with the smallest increase were located in the northwest and northeast mountainous areas. Relative humidity decreased evenly across the entire area of interest. 2) According to the thermal grades of effective temperature, the temperature of winter belonged to “very cold”, that of the annual average, spring, and autumn belonged to “cold”, and that of summer belonged to “warm”. The area became dryer and warmer in the spring, summer, and winter. However, in autumn, the regional temperature difference was obvious. 3) The “weather-friendly” days in Beijing accounted for 41.3%, with large regional differences. Over half the sites showed a reduction in the number of “weather-friendly” days. The “weather-friendly” days in spring increased in number, while those in summer decreased, without any consistency in autumn. In winter, there were nearly no “weather-friendly” days, just “very cold” and “cold” days.
The effective temperature in Beijing has been studied by the entire available observation data. The results demonstrate the following: 1) The annual temperature, wind speed, and effective temperature in Beijing were significantly affected by the topographic distribution, without a significant difference in the relative humidity between the mountainous and the urban areas. Beijing became drier and warmer over the study period. Regionally, the stations with the largest increase in the annual and effective temperatures were concentrated in the urban areas, and the stations with the smallest increase were located in the northwest and northeast mountainous areas. Relative humidity decreased evenly across the entire area of interest. 2) According to the thermal grades of effective temperature, the temperature of winter belonged to “very cold”, that of the annual average, spring, and autumn belonged to “cold”, and that of summer belonged to “warm”. The area became dryer and warmer in the spring, summer, and winter. However, in autumn, the regional temperature difference was obvious. 3) The “weather-friendly” days in Beijing accounted for 41.3%, with large regional differences. Over half the sites showed a reduction in the number of “weather-friendly” days. The “weather-friendly” days in spring increased in number, while those in summer decreased, without any consistency in autumn. In winter, there were nearly no “weather-friendly” days, just “very cold” and “cold” days.
2022, 27(6): 756-768.
doi: 10.3878/j.issn.1006-9585.2022.21159
Abstract:
Based on the state-controlled sites and local-controlled sites, using the hourly monitoring data of six conventional pollutants and PM2.5 component data from 1 January to 13 February 2020, the temporal and spatial variation characteristics of air pollutants in the Wuhan area before and after the coronavirus disease 2019 (COVID-19) controls and the impact of control measures at different types of sites were evaluated. The results showed that after implementing epidemic control measures, the particulate matter concentration in Wuhan decreased significantly. Based on the calculation of two observation networks (89 stations), the change rates of PM2.5 and PM10 concentrations were −23.44% and −32.95%, respectively, but the O3 concentration increased significantly, at a rate of 55.22%, 10.6% higher than that of the state-controlled sites. In terms of the spatial distribution, the particulate matter concentration is higher in the north and lower in the south but decreases more at stations in south Wuhan, which is related to the increased frequency of southerly wind, resulting in more control measures affecting the downwind area. The decrease in NO2 concentration at the stations in the south is greater, while the O3 concentration increases. The reason is that as the NO concentration decreases greatly, the titration reaction weakens, and the meteorological conditions are also conducive to continuously accumulating O3 and maintaining a high concentration of O3. From the difference in concentration change among different types of stations, the epidemic control measures have the greatest impact on secondary pollutants at traffic and industrial stations. The concentration change rates calculated based on the two observation networks exceed those of state-controlled stations. The change rates of PM2.5 and O3 are 6% and 18% lower at state-controlled stations compared to traffic stations, respectively. The primary pollutants, SO2 and CO, show small concentration changes at rates of −6.10% and −5.61%, respectively, possibly because key emission sources were not shut down during the epidemic. Among the six conventional pollutants, the NO2 concentration changed the most, decreasing by −55.26%, which is directly related to traffic control. Comparing and analyzing the aerosol component concentrations in the same periods in 2019 and 2020 reveals that during the epidemic control period in 2020, the\begin{document}$ {\mathrm{N}\mathrm{O}}_{3}^{-} $\end{document} ![]()
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Based on the state-controlled sites and local-controlled sites, using the hourly monitoring data of six conventional pollutants and PM2.5 component data from 1 January to 13 February 2020, the temporal and spatial variation characteristics of air pollutants in the Wuhan area before and after the coronavirus disease 2019 (COVID-19) controls and the impact of control measures at different types of sites were evaluated. The results showed that after implementing epidemic control measures, the particulate matter concentration in Wuhan decreased significantly. Based on the calculation of two observation networks (89 stations), the change rates of PM2.5 and PM10 concentrations were −23.44% and −32.95%, respectively, but the O3 concentration increased significantly, at a rate of 55.22%, 10.6% higher than that of the state-controlled sites. In terms of the spatial distribution, the particulate matter concentration is higher in the north and lower in the south but decreases more at stations in south Wuhan, which is related to the increased frequency of southerly wind, resulting in more control measures affecting the downwind area. The decrease in NO2 concentration at the stations in the south is greater, while the O3 concentration increases. The reason is that as the NO concentration decreases greatly, the titration reaction weakens, and the meteorological conditions are also conducive to continuously accumulating O3 and maintaining a high concentration of O3. From the difference in concentration change among different types of stations, the epidemic control measures have the greatest impact on secondary pollutants at traffic and industrial stations. The concentration change rates calculated based on the two observation networks exceed those of state-controlled stations. The change rates of PM2.5 and O3 are 6% and 18% lower at state-controlled stations compared to traffic stations, respectively. The primary pollutants, SO2 and CO, show small concentration changes at rates of −6.10% and −5.61%, respectively, possibly because key emission sources were not shut down during the epidemic. Among the six conventional pollutants, the NO2 concentration changed the most, decreasing by −55.26%, which is directly related to traffic control. Comparing and analyzing the aerosol component concentrations in the same periods in 2019 and 2020 reveals that during the epidemic control period in 2020, the
2022, 27(6): 769-777.
doi: 10.3878/j.issn.1006-9585.2021.21173
Abstract:
Based on the reanalysis data of ERA-5 and the 120-h prediction data of Global Forecast System (GFS), which is the NCEP prediction system, this paper examines the prediction skills of near-surface wind speed and net downward short-wave radiation flux of the numerical model during nine cold waves in East China from December 2020 to March 2021. The following test results are obtained: 1) The GFS prediction system can accurately predict the cold wave process (cooling range and minimum temperature) 1–4 days in advance, with an average prediction accuracy > 80%. 2) The near-surface wind speed increases significantly during the cold wave. Even though the Threat Score (TS) of the wind speed of grades 0–2 is significantly low, the TS score of the wind speed of grades 3–5 and >6 is higher than the general weather process. The relative error in the prediction of the net downward short-wave radiation flux is larger than the general weather processes, particularly on the day of the cold wave outbreak. 3) The prediction skills exhibit significant diurnal variation, during the cold wave. The prediction skill of the wind speed of grades 0–2 is the lowest in the afternoon, particularly on the strongest day of the cold wave. The TS score of the wind speed of grades 3–5 is generally the lowest at around 1800 LST and is extremely low at night on the strongest day of the cold wave. After the afternoon, particularly on the day of the cold wave outbreak, the error in the prediction of the net downward short-wave radiation flux increases significantly. 4) The prediction skills decrease and the prediction time increases during the cold wave. The 24-h prediction has the highest TS score and the minimum error, while the 72-h prediction has the lowest TS score and the maximum error.
Based on the reanalysis data of ERA-5 and the 120-h prediction data of Global Forecast System (GFS), which is the NCEP prediction system, this paper examines the prediction skills of near-surface wind speed and net downward short-wave radiation flux of the numerical model during nine cold waves in East China from December 2020 to March 2021. The following test results are obtained: 1) The GFS prediction system can accurately predict the cold wave process (cooling range and minimum temperature) 1–4 days in advance, with an average prediction accuracy > 80%. 2) The near-surface wind speed increases significantly during the cold wave. Even though the Threat Score (TS) of the wind speed of grades 0–2 is significantly low, the TS score of the wind speed of grades 3–5 and >6 is higher than the general weather process. The relative error in the prediction of the net downward short-wave radiation flux is larger than the general weather processes, particularly on the day of the cold wave outbreak. 3) The prediction skills exhibit significant diurnal variation, during the cold wave. The prediction skill of the wind speed of grades 0–2 is the lowest in the afternoon, particularly on the strongest day of the cold wave. The TS score of the wind speed of grades 3–5 is generally the lowest at around 1800 LST and is extremely low at night on the strongest day of the cold wave. After the afternoon, particularly on the day of the cold wave outbreak, the error in the prediction of the net downward short-wave radiation flux increases significantly. 4) The prediction skills decrease and the prediction time increases during the cold wave. The 24-h prediction has the highest TS score and the minimum error, while the 72-h prediction has the lowest TS score and the maximum error.
2022, 27(6): 778-786.
doi: 10.3878/j.issn.1006-9585.2021.21177
Abstract:
A heavy snowstorm process in the reaches of the Dadu River basin in late February 2016 was analyzed. Through synoptic diagnosis and environmental meteorological parameter refinement, it was revealed that a strong cold air outbreak is a precursor of heavy snowfall in the upper reaches of the Dadu River basin, which can be predicted 2–3 days in advance. The occurrence of a blizzard requires the cooperation of cold air with warm air. For the Dadu River basin, the primary moisture sources come from two paths: 1) The plateau shear line formed by a meeting of cold air with warm and wet air in front of the south trough, which is the dominant synoptic system at the middle level in the upper reaches of the Dadu River basin. 2) The warm and humid air stream that enters the northwestern part of the Sichuan Basin at a low level along the east of the Hengduan Mountains, providing sufficient water vapor conditions for snowfall in the region. The ascending motion driven by the dynamical configuration with convergence at the low level and divergence at the high level lifts the water vapor from the low level to the upper level. The water vapor then directly sublimates into snowflakes because of the cold environment, falling in the upper reaches of the Dadu River basin. The temperature and humidity conditions during this heavy snowstorm process can be summarized as follows: The temperature at 700 hPa is not higher than −5°C, the temperature at 500 hPa is not higher than −9°C, and the surface temperature is not higher than 0°C. The relative humidity of the ambient atmosphere is higher than 70%, and the moisture content in the air reaches above 4 g kg−1.
A heavy snowstorm process in the reaches of the Dadu River basin in late February 2016 was analyzed. Through synoptic diagnosis and environmental meteorological parameter refinement, it was revealed that a strong cold air outbreak is a precursor of heavy snowfall in the upper reaches of the Dadu River basin, which can be predicted 2–3 days in advance. The occurrence of a blizzard requires the cooperation of cold air with warm air. For the Dadu River basin, the primary moisture sources come from two paths: 1) The plateau shear line formed by a meeting of cold air with warm and wet air in front of the south trough, which is the dominant synoptic system at the middle level in the upper reaches of the Dadu River basin. 2) The warm and humid air stream that enters the northwestern part of the Sichuan Basin at a low level along the east of the Hengduan Mountains, providing sufficient water vapor conditions for snowfall in the region. The ascending motion driven by the dynamical configuration with convergence at the low level and divergence at the high level lifts the water vapor from the low level to the upper level. The water vapor then directly sublimates into snowflakes because of the cold environment, falling in the upper reaches of the Dadu River basin. The temperature and humidity conditions during this heavy snowstorm process can be summarized as follows: The temperature at 700 hPa is not higher than −5°C, the temperature at 500 hPa is not higher than −9°C, and the surface temperature is not higher than 0°C. The relative humidity of the ambient atmosphere is higher than 70%, and the moisture content in the air reaches above 4 g kg−1.
2022, 27(6): 787-794.
doi: 10.3878/j.issn.1006-9585.2022.22015
Abstract:
Facing the urgent requirements of air pollution prevention and control in China, the relevant national ministries and scientific research institutions have set up a number of scientific and technological programs to provide continuous support. Great progress has been made in theoretical research, monitoring methods, numerical simulation, and air pollution control and prevention technology, which provides a strong scientific and technological support for the practice of air pollution prevention and control in China and the successful conclusion of the battle of blue sky defense. This paper summarizes the deployment and progress of air pollution prevention and control science and technology in recent ten years, and analyzes the current situation and problems of air pollution prevention and control in China. Aiming at the 14th Five-Year Plan (2021−2025), suggestions on three aspects, that is basic research of air pollution, research and development of key technologies for pollution prevention and control, and application demonstrations are proposed. Focus on the coordination of PM2.5 and O3 control, pollution reduction and carbon reduction, the authors will further advance scientific and technological work on air pollution prevention and control, and provide key scientific and technological support for the building of a Beautiful China Planning and the goal of carbon neutrality and carbon peak.
Facing the urgent requirements of air pollution prevention and control in China, the relevant national ministries and scientific research institutions have set up a number of scientific and technological programs to provide continuous support. Great progress has been made in theoretical research, monitoring methods, numerical simulation, and air pollution control and prevention technology, which provides a strong scientific and technological support for the practice of air pollution prevention and control in China and the successful conclusion of the battle of blue sky defense. This paper summarizes the deployment and progress of air pollution prevention and control science and technology in recent ten years, and analyzes the current situation and problems of air pollution prevention and control in China. Aiming at the 14th Five-Year Plan (2021−2025), suggestions on three aspects, that is basic research of air pollution, research and development of key technologies for pollution prevention and control, and application demonstrations are proposed. Focus on the coordination of PM2.5 and O3 control, pollution reduction and carbon reduction, the authors will further advance scientific and technological work on air pollution prevention and control, and provide key scientific and technological support for the building of a Beautiful China Planning and the goal of carbon neutrality and carbon peak.
, Available online ,
doi: 10.3878/j.issn.1006-9585.2022.22040
Abstract:
, Available online ,
doi: 10.3878/j.issn.1006-9585.2022.21119
Abstract:
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