2023 Vol. 28, No. 1
Display Method:
2023, 28(1): 1-16.
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.
2023, 28(1): 17-29.
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.
2023, 28(1): 30-44.
doi: 10.3878/j.issn.1006-9585.2022.21178
Abstract:
Based on the global land cover type and coverage, we used the NDVI (Normalized Difference Vegetation Index) 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 NDVI (Normalized Difference Vegetation Index) 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.
2023, 28(1): 45-60.
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 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 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 population exposure. The GDP/population 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 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 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 population exposure. The GDP/population exposure to heavy rainfall mainly depends on its distribution factor.
2023, 28(1): 61-73.
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.
2023, 28(1): 74-88.
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.
2023, 28(1): 89-102.
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.
Progress of Research on Global Tropospheric Ozone Variation Characteristics during COVID-19 Pandemic
2023, 28(1): 103-116.
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.
