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doi: 10.3878/j.issn.1006-9585.2022.21180
Abstract:
The daily daytime/nighttime precipitation data of 81 National Meteorological Science Data Center stations on the Qinghai–Tibet Plateau and 80 stations in Southwest China were used to statistically analyze the daytime/nighttime rainy days of different magnitudes, differences in this number in the two regions from 1961 to 2020, and interannual change (trend) characteristics. The results showed the following: (1) The number of daytime/nighttime rainy days of different magnitudes on the Tibetan Plateau and in Southwest China increased rapidly in May and decreased significantly in November; large differences in the number of daytime/nighttime rainy days in the two regions were observed in May–October, and the number of heavy rain and rainstorm days was higher in May–October. The number of rainstorm days on the Tibetan Plateau accounted for ＞85% of the total number of rainstorm days in the year, heavy rain accounted for ＞90%, and the proportions of these two levels of precipitation were 93% and 86%, respectively, in Southwest China. The probability of extremely heavy precipitation (rainstorms) during the rainy season in both regions was substantially higher at night than during the day. (2) In addition to obvious regional differences in the number of daytime/nighttime rainy days of different magnitudes in the two regions during the rainy season, very significant differences were observed between daytime and nighttime. The Three-Rivers Source Region and the southeastern part of the Tibetan Plateau have frequent light and moderate rains during the day and night. Heavy rain occurs exclusively at night in southeastern Tibet and the east of the Three-Rivers Source Region; rainstorms occur only in the east of the Tibetan Plateau, and there are visibly more sites receiving precipitation at night than during the day. Central Sichuan, western Sichuan marginal mountains, and southwestern Yunnan in Southwest China have a high incidence of daytime/nighttime light rain and moderate rain; heavy rain is more likely to occur during the day in southwestern Yunnan, whereas it is more likely to occur at night in central Sichuan. Typical areas with rainstorms are central and eastern Sichuan, western Chongqing, and central and southern Guizhou. (3) The overall trends of interannual changes in the number of rainy seasons in the rainy season are significantly different between daytime/nighttime-graded rain days. In the Tibetan Plateau, except for the significant decrease in the number of light rainy days at night, the rest of the rainy days of different magnitudes increased significantly during the daytime and nighttime, with the increasing trend at night being greater than that during the day, and the increasing trend of heavy rain and rainstorm at night was almost twice that of the day. Unlike the Tibetan Plateau, the number of days with light precipitation (light rain, moderate rain, and heavy rain) decreased significantly in Southwest China. Among them, the number of light rainy days at night decreased the most, approximately twice as much as during the daytime; the number of days with heavy precipitation (rainstorm or torrential rain) increased in the opposite direction, and the increasing trend at night is greater than that during the daytime.
The daily daytime/nighttime precipitation data of 81 National Meteorological Science Data Center stations on the Qinghai–Tibet Plateau and 80 stations in Southwest China were used to statistically analyze the daytime/nighttime rainy days of different magnitudes, differences in this number in the two regions from 1961 to 2020, and interannual change (trend) characteristics. The results showed the following: (1) The number of daytime/nighttime rainy days of different magnitudes on the Tibetan Plateau and in Southwest China increased rapidly in May and decreased significantly in November; large differences in the number of daytime/nighttime rainy days in the two regions were observed in May–October, and the number of heavy rain and rainstorm days was higher in May–October. The number of rainstorm days on the Tibetan Plateau accounted for ＞85% of the total number of rainstorm days in the year, heavy rain accounted for ＞90%, and the proportions of these two levels of precipitation were 93% and 86%, respectively, in Southwest China. The probability of extremely heavy precipitation (rainstorms) during the rainy season in both regions was substantially higher at night than during the day. (2) In addition to obvious regional differences in the number of daytime/nighttime rainy days of different magnitudes in the two regions during the rainy season, very significant differences were observed between daytime and nighttime. The Three-Rivers Source Region and the southeastern part of the Tibetan Plateau have frequent light and moderate rains during the day and night. Heavy rain occurs exclusively at night in southeastern Tibet and the east of the Three-Rivers Source Region; rainstorms occur only in the east of the Tibetan Plateau, and there are visibly more sites receiving precipitation at night than during the day. Central Sichuan, western Sichuan marginal mountains, and southwestern Yunnan in Southwest China have a high incidence of daytime/nighttime light rain and moderate rain; heavy rain is more likely to occur during the day in southwestern Yunnan, whereas it is more likely to occur at night in central Sichuan. Typical areas with rainstorms are central and eastern Sichuan, western Chongqing, and central and southern Guizhou. (3) The overall trends of interannual changes in the number of rainy seasons in the rainy season are significantly different between daytime/nighttime-graded rain days. In the Tibetan Plateau, except for the significant decrease in the number of light rainy days at night, the rest of the rainy days of different magnitudes increased significantly during the daytime and nighttime, with the increasing trend at night being greater than that during the day, and the increasing trend of heavy rain and rainstorm at night was almost twice that of the day. Unlike the Tibetan Plateau, the number of days with light precipitation (light rain, moderate rain, and heavy rain) decreased significantly in Southwest China. Among them, the number of light rainy days at night decreased the most, approximately twice as much as during the daytime; the number of days with heavy precipitation (rainstorm or torrential rain) increased in the opposite direction, and the increasing trend at night is greater than that during the daytime.
2023 Issue 3
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2023, 28(3): 229-241.
doi: 10.3878/j.issn.1006-9585.2022.21050
Abstract:
The Tibetan Plateau (TP) has a significant impact on the climate at the continental to global scale. During summer, the diurnal variation of clouds over the TP not only affects local convection and precipitation processes but also is closely related to floods in the Yangtze River basin of China, the Asian summer monsoon, and the large-scale climate regime in the Northern Hemisphere. Therefore, understanding the bulk characteristics of clouds over the TP is essential to study cloud-climate feedback and their impact on climate change and dynamics. Due to its remote geographical location, satellite cloud retrievals are highly relied upon for studying the TP. Recent satellite observations have revealed many unique features and roles of clouds over the TP. However, sun-synchronous satellites with low temporal resolution can only capture cloud characteristics twice a day, which is insufficient to understand the diurnal variations of clouds that vary spatially and temporally, especially during summer. The Fengyun-4A (FY-4A) is the first satellite of the new generation of Chinese geostationary meteorological satellites. The Advanced Geosynchronous Radiation Imager (AGRI) on board FY-4A has higher radiation, spectrum, and spatial resolution with shortened revisit time, which provides an opportunity to monitor clouds and their daily cycle with a new level of ability. Although FY-4A/AGRI has the capability to provide a complete image of the TP with smaller viewing zenith angles, cloud retrievals over the TP derived from FY-4A have not yet been exploited and utilized. In this study, pixel-level cloud retrievals obtained from FY-4A/AGRI are used to investigate and analyze the occurrence distribution and diurnal variation patterns of clouds over the TP during summer. The results show that clouds occur most frequently over the south and southeast of the TP all day long, and the TP has an obvious diurnal cycle. Cloud frequencies are highest at noon and lowest at 4 a.m., with peak cloud frequencies distributed along major mountains, showing terrain-dependent characteristics. Cloud tops with a most probable height of more than 12 km are concentrated in the Yarlung Zangbo River Valley and its northern side, near the Nyainqentanglha Mountain Range, the vicinity of Nyainqentangula Mountains, and the west of the eastern boundary of Hengduan Mountains. The diurnal cycle of cloud heights shows an apparent delay against that of cloud occurrence frequencies. This study also discusses the strong topographic influences on the spatiotemporal distribution patterns of clouds over the TP.
The Tibetan Plateau (TP) has a significant impact on the climate at the continental to global scale. During summer, the diurnal variation of clouds over the TP not only affects local convection and precipitation processes but also is closely related to floods in the Yangtze River basin of China, the Asian summer monsoon, and the large-scale climate regime in the Northern Hemisphere. Therefore, understanding the bulk characteristics of clouds over the TP is essential to study cloud-climate feedback and their impact on climate change and dynamics. Due to its remote geographical location, satellite cloud retrievals are highly relied upon for studying the TP. Recent satellite observations have revealed many unique features and roles of clouds over the TP. However, sun-synchronous satellites with low temporal resolution can only capture cloud characteristics twice a day, which is insufficient to understand the diurnal variations of clouds that vary spatially and temporally, especially during summer. The Fengyun-4A (FY-4A) is the first satellite of the new generation of Chinese geostationary meteorological satellites. The Advanced Geosynchronous Radiation Imager (AGRI) on board FY-4A has higher radiation, spectrum, and spatial resolution with shortened revisit time, which provides an opportunity to monitor clouds and their daily cycle with a new level of ability. Although FY-4A/AGRI has the capability to provide a complete image of the TP with smaller viewing zenith angles, cloud retrievals over the TP derived from FY-4A have not yet been exploited and utilized. In this study, pixel-level cloud retrievals obtained from FY-4A/AGRI are used to investigate and analyze the occurrence distribution and diurnal variation patterns of clouds over the TP during summer. The results show that clouds occur most frequently over the south and southeast of the TP all day long, and the TP has an obvious diurnal cycle. Cloud frequencies are highest at noon and lowest at 4 a.m., with peak cloud frequencies distributed along major mountains, showing terrain-dependent characteristics. Cloud tops with a most probable height of more than 12 km are concentrated in the Yarlung Zangbo River Valley and its northern side, near the Nyainqentanglha Mountain Range, the vicinity of Nyainqentangula Mountains, and the west of the eastern boundary of Hengduan Mountains. The diurnal cycle of cloud heights shows an apparent delay against that of cloud occurrence frequencies. This study also discusses the strong topographic influences on the spatiotemporal distribution patterns of clouds over the TP.
2023, 28(3): 242-250.
doi: 10.3878/j.issn.1006-9585.2022.21160
Abstract:
Based on the Landsat 8 TIRS remote sensing image data of 2014–2021, land surface radiation temperatures over Shenzhen were retrieved using the split window algorithm (SWA) and atmospheric correction method and verified at specific sites using ground observation temperature data, and the spatial and temporal distribution and influence factors of the urban heat island effect were discussed in this study. A significant linear correlation was found between the land surface temperature from the two algorithms (TSWA) and the ground observation air temperature (TM), i.e., TSWA=1.01×TM+2.65 and TARC= 0.85×TM+5.51 (p＜0.01), but the SWA result is better in reflecting the ground observation air temperature. No significant trend (p=0.94) in the urban heat island area (HI＞0.01) was observed in Shenzhen in 2014–2021. The spatial distribution of the urban heat island was closely related to the urban development pattern, and the land use of urban planning significantly influenced the urban heat island. The land use types of ecological waters and ecological green spaces played an important role in mitigating the urban heat island effects, whereas the types of traffic roads and industrial storage promoted the formation of the urban heat island. The spatial distribution and density of the Shenzhen urban road network have a strongly significant effect on the formation of an urban heat island (p=0.003).
Based on the Landsat 8 TIRS remote sensing image data of 2014–2021, land surface radiation temperatures over Shenzhen were retrieved using the split window algorithm (SWA) and atmospheric correction method and verified at specific sites using ground observation temperature data, and the spatial and temporal distribution and influence factors of the urban heat island effect were discussed in this study. A significant linear correlation was found between the land surface temperature from the two algorithms (TSWA) and the ground observation air temperature (TM), i.e., TSWA=1.01×TM+2.65 and TARC= 0.85×TM+5.51 (p＜0.01), but the SWA result is better in reflecting the ground observation air temperature. No significant trend (p=0.94) in the urban heat island area (HI＞0.01) was observed in Shenzhen in 2014–2021. The spatial distribution of the urban heat island was closely related to the urban development pattern, and the land use of urban planning significantly influenced the urban heat island. The land use types of ecological waters and ecological green spaces played an important role in mitigating the urban heat island effects, whereas the types of traffic roads and industrial storage promoted the formation of the urban heat island. The spatial distribution and density of the Shenzhen urban road network have a strongly significant effect on the formation of an urban heat island (p=0.003).
2023, 28(3): 251-262.
doi: 10.3878/j.issn.1006-9585.2022.21078
Abstract:
We investigated the future climate change over a coordinated regional climate downscaling experiment (CORDEX) in the Southeast Asia region using a regional climate model (RegCM4) in this study. The model is driven by the global model of MPI-ESM-MR (hereinafter referred to as MPI) at a grid spacing of 25 km under the middle range representative concentration pathway of RCP4.5 with the time period of 1981–2099. Results show that MPI and RegCM4 could reproduce the spatial pattern and magnitude of annual mean temperature and precipitation well over the region. Compared to driving MPI, RegCM4 can provide finer spatial details of the climate variables due to its much higher resolution than MPI; however, it has a prevailing cold bias for temperature and wet bias for precipitation during the simulations. The projected future changes using MPI and RegCM4 show an increase in the annual mean temperature. Moreover, the regional average warming toward the end of the 21st century (2081–2099) is predicted to be 1.8°C and 1.7°C using MPI and RegCM4, respectively. Meanwhile large differences are observed in their precipitation projections, more significant over the Maritime Continent compared to other regions. The precipitation projected using MPI shows an increase, whereas that using RegCM4 model show a considerable decrease. By the end of the 21st century, the projected changes in the regional mean precipitation over Southeast Asia using MPI and RegCM4 are 5% (90 mm) and −6% (−147 mm), respectively. An analysis of the extreme indices simulated with the RegCM4 shows a large frequency of heat waves in the future. The projected increases in precipitation intensity and consecutive dry days over the Maritime Continent indicate high risks of flood and drought over the region.
We investigated the future climate change over a coordinated regional climate downscaling experiment (CORDEX) in the Southeast Asia region using a regional climate model (RegCM4) in this study. The model is driven by the global model of MPI-ESM-MR (hereinafter referred to as MPI) at a grid spacing of 25 km under the middle range representative concentration pathway of RCP4.5 with the time period of 1981–2099. Results show that MPI and RegCM4 could reproduce the spatial pattern and magnitude of annual mean temperature and precipitation well over the region. Compared to driving MPI, RegCM4 can provide finer spatial details of the climate variables due to its much higher resolution than MPI; however, it has a prevailing cold bias for temperature and wet bias for precipitation during the simulations. The projected future changes using MPI and RegCM4 show an increase in the annual mean temperature. Moreover, the regional average warming toward the end of the 21st century (2081–2099) is predicted to be 1.8°C and 1.7°C using MPI and RegCM4, respectively. Meanwhile large differences are observed in their precipitation projections, more significant over the Maritime Continent compared to other regions. The precipitation projected using MPI shows an increase, whereas that using RegCM4 model show a considerable decrease. By the end of the 21st century, the projected changes in the regional mean precipitation over Southeast Asia using MPI and RegCM4 are 5% (90 mm) and −6% (−147 mm), respectively. An analysis of the extreme indices simulated with the RegCM4 shows a large frequency of heat waves in the future. The projected increases in precipitation intensity and consecutive dry days over the Maritime Continent indicate high risks of flood and drought over the region.
2023, 28(3): 263-274.
doi: 10.3878/j.issn.1006-9585.2022.21119
Abstract:
The spatial distribution characteristics of atmospheric ammonia (NH3) in East Asia from June to September 2008–2011 were investigated using data from the Michelson interferometer for passive atmospheric sounding on the ENVISAT satellite, the AIRS detector on the Aqua satellite, and the global atmospheric chemistry–climate model EMAC. The results show that the highest concentration of NH3 near the surface appears in northern India, and deep convection exists in the Bay of Bengal near northern India in summer. This deep convection can transport short-lived NH3 to the upper troposphere and lower stratosphere (UTLS) because of the high altitude of the Qinghai-Tibet Plateau. Therefore, an upward transport column of NH3 over the Qinghai-Tibet Plateau exits and is the main channel for the upward transportation of NH3. During the Asian summer monsoon, the location of the Asian summer monsoon anticyclone dominates the spatial distribution of NH3 in the UTLS area. The high-concentration center of NH3 continues to exist during the anticyclone, and its position corresponds well with the position of the anticyclone center. During the anticyclone, one or two NH3 high-concentration centers exist in the anticyclone center, implying that a change in the circulation pattern of the anticyclone has important effects on the NH3 distribution.
The spatial distribution characteristics of atmospheric ammonia (NH3) in East Asia from June to September 2008–2011 were investigated using data from the Michelson interferometer for passive atmospheric sounding on the ENVISAT satellite, the AIRS detector on the Aqua satellite, and the global atmospheric chemistry–climate model EMAC. The results show that the highest concentration of NH3 near the surface appears in northern India, and deep convection exists in the Bay of Bengal near northern India in summer. This deep convection can transport short-lived NH3 to the upper troposphere and lower stratosphere (UTLS) because of the high altitude of the Qinghai-Tibet Plateau. Therefore, an upward transport column of NH3 over the Qinghai-Tibet Plateau exits and is the main channel for the upward transportation of NH3. During the Asian summer monsoon, the location of the Asian summer monsoon anticyclone dominates the spatial distribution of NH3 in the UTLS area. The high-concentration center of NH3 continues to exist during the anticyclone, and its position corresponds well with the position of the anticyclone center. During the anticyclone, one or two NH3 high-concentration centers exist in the anticyclone center, implying that a change in the circulation pattern of the anticyclone has important effects on the NH3 distribution.
2023, 28(3): 275-285.
doi: 10.3878/j.issn.1006-9585.2022.21188
Abstract:
Over the past decade, Yunnan Provinces have experienced multiple instances of seasonal continuous drought. In particular, the prolonged drought in summer and autumn has exacerbated the negative effects of the drought in winter and spring, detrimentally impacting the local economic and social activities. As a result, the underlying reasons for the continuous droughts have become a major topic of concern. This paper utilizes precipitation data from 120 Yunnan Meteorological Bureau stations and sea-level pressure data of NCEP spanning the period from 1970 to 2020. This paper aims to analyze the evolution characteristics of continuous drought events in summer and autumn in Yunnan Province using the precipitation persistence anomaly index. Additionally, it investigates the possible relationship between drought events during summer to autumn and sea-level pressure in early April. The findings of this paper indicate that: (1) The primary characteristics of precipitation persistence anomaly in summer and autumn correspond to the consistent positive or negative anomaly in Yunnan. (2) The early stage of the continuous drought events in summer and autumn in Yunnan is the result of a combination of sea-level pressure anomalies in three regions, namely, the North Atlantic Ocean, the North Indian Ocean, and the Central Pacific Ocean. (3) Based on the previous three signals, an index, referred to as the SAP (Summer and Autumn Precipitation) index, can be constructed in the month of April. The SAP index can effectively represent the continuous precipitation anomaly in summer and autumn in Yunnan. This index demonstrates remarkable potential as an early prediction signal for continuous drought events in the region. The results predicted by this study can provide valuable insights for improving the prediction of such extreme events in Yunnan.
Over the past decade, Yunnan Provinces have experienced multiple instances of seasonal continuous drought. In particular, the prolonged drought in summer and autumn has exacerbated the negative effects of the drought in winter and spring, detrimentally impacting the local economic and social activities. As a result, the underlying reasons for the continuous droughts have become a major topic of concern. This paper utilizes precipitation data from 120 Yunnan Meteorological Bureau stations and sea-level pressure data of NCEP spanning the period from 1970 to 2020. This paper aims to analyze the evolution characteristics of continuous drought events in summer and autumn in Yunnan Province using the precipitation persistence anomaly index. Additionally, it investigates the possible relationship between drought events during summer to autumn and sea-level pressure in early April. The findings of this paper indicate that: (1) The primary characteristics of precipitation persistence anomaly in summer and autumn correspond to the consistent positive or negative anomaly in Yunnan. (2) The early stage of the continuous drought events in summer and autumn in Yunnan is the result of a combination of sea-level pressure anomalies in three regions, namely, the North Atlantic Ocean, the North Indian Ocean, and the Central Pacific Ocean. (3) Based on the previous three signals, an index, referred to as the SAP (Summer and Autumn Precipitation) index, can be constructed in the month of April. The SAP index can effectively represent the continuous precipitation anomaly in summer and autumn in Yunnan. This index demonstrates remarkable potential as an early prediction signal for continuous drought events in the region. The results predicted by this study can provide valuable insights for improving the prediction of such extreme events in Yunnan.
2023, 28(3): 286-302.
doi: 10.3878/j.issn.1006-9585.2022.22021
Abstract:
Based on the numerical simulations provided by the latest 14 coupled models of the sixth phase of the coupled model intercomparison project (CMIP6), the spatial and temporal distribution characteristics of extreme precipitation over Central Asia (CA) and its relationship with regional climate warming in the middle and late 21st century under two shared socioeconomic paths (SSP2-4.5 and SSP5-8.5) are analyzed in this study. The results show that most CMIP6 models can essentially simulate the spatial distribution characteristics of observed precipitation climate states from 1979–2018. However, the model simulations underestimate the observations in the southwest and southeast of CA and overestimate the observations in northern and southern CA. Compared with the historical period (1981–2010), the precipitation intensity at the end of the 21st century (2071–2100) increased by 0.54 mm/10 a and 2.4 mm/10 a under the scenarios of SSP2-4.5 and SSP5-8.5, respectively, while the frequency of extreme precipitation events increased by 5%–7% and 6%–10%, respectively, particularly in the high-altitude mountains in central and southern regions. The signal-to-noise ratio of the predicted precipitation intensity and frequency in northeast CA to the north of the Tianshan Mountains is more reliable. Climate warming will have an obvious regulatory effect on the frequency of extreme precipitation events in CA. Under the scenarios of SSP2-4.5 and SSP5-8.5, a temperature increase of 1 K increased the frequency of extremely heavy precipitation events by approximately 7 and 9 days and the maximum continuous dry days by approximately 3 and 6 days, respectively.
Based on the numerical simulations provided by the latest 14 coupled models of the sixth phase of the coupled model intercomparison project (CMIP6), the spatial and temporal distribution characteristics of extreme precipitation over Central Asia (CA) and its relationship with regional climate warming in the middle and late 21st century under two shared socioeconomic paths (SSP2-4.5 and SSP5-8.5) are analyzed in this study. The results show that most CMIP6 models can essentially simulate the spatial distribution characteristics of observed precipitation climate states from 1979–2018. However, the model simulations underestimate the observations in the southwest and southeast of CA and overestimate the observations in northern and southern CA. Compared with the historical period (1981–2010), the precipitation intensity at the end of the 21st century (2071–2100) increased by 0.54 mm/10 a and 2.4 mm/10 a under the scenarios of SSP2-4.5 and SSP5-8.5, respectively, while the frequency of extreme precipitation events increased by 5%–7% and 6%–10%, respectively, particularly in the high-altitude mountains in central and southern regions. The signal-to-noise ratio of the predicted precipitation intensity and frequency in northeast CA to the north of the Tianshan Mountains is more reliable. Climate warming will have an obvious regulatory effect on the frequency of extreme precipitation events in CA. Under the scenarios of SSP2-4.5 and SSP5-8.5, a temperature increase of 1 K increased the frequency of extremely heavy precipitation events by approximately 7 and 9 days and the maximum continuous dry days by approximately 3 and 6 days, respectively.
2023, 28(3): 303-314.
doi: 10.3878/j.issn.1006-9585.2022.22005
Abstract:
Cloud optical thickness impacts the radiation balance of the earth–atmosphere system and is a key factor in climate change prediction. Furthermore, variation in cloud supersaturation predominantly relies on the physicochemical and activation characteristics of aerosols and the vertical velocity of updraft. These factors affect the activation process and condensation growth process within the cloud, ultimately changing the cloud optical thickness. Based on the simulation results of the adiabatic bubble model, the influences of vertical velocity, aerosol number concentration, and aerosol chemical composition on the cloud optical thickness were studied. The simulation results can reproduce the first indirect radiation effect of aerosols and show a positive correlation between cloud optical thickness and vertical velocity. When the liquid water content in the cloud remained constant, increasing the vertical velocity and aerosol number concentration increased the cloud droplet number concentration while reducing the cloud droplet effective radius. This phenomenon increased the total surface area of cloud droplets, ultimately enhancing the cloud albedo. However, with the rapid increase in vertical velocity and aerosol number concentration, the growth rate of cloud droplet number concentration and the cloud droplet effective radius slowed down simultaneously, consequently leading to a reduction in the growth rate of the cloud droplet total surface area, cloud albedo, and cloud optical thickness. Moreover, when the aerosol chemical composition comprises organic carbon, ammonium sulfate, and sea salt at the same aerosol number concentration, the cloud droplet effective radius decreases, leading to an increase in the total surface area and a consequent increase in the optical thickness of the cloud. The findings of this work have clarified the influence mechanism of the aforementioned factors on cloud optical thickness and deepened the theoretical understanding of the first indirect effects of aerosols.
Cloud optical thickness impacts the radiation balance of the earth–atmosphere system and is a key factor in climate change prediction. Furthermore, variation in cloud supersaturation predominantly relies on the physicochemical and activation characteristics of aerosols and the vertical velocity of updraft. These factors affect the activation process and condensation growth process within the cloud, ultimately changing the cloud optical thickness. Based on the simulation results of the adiabatic bubble model, the influences of vertical velocity, aerosol number concentration, and aerosol chemical composition on the cloud optical thickness were studied. The simulation results can reproduce the first indirect radiation effect of aerosols and show a positive correlation between cloud optical thickness and vertical velocity. When the liquid water content in the cloud remained constant, increasing the vertical velocity and aerosol number concentration increased the cloud droplet number concentration while reducing the cloud droplet effective radius. This phenomenon increased the total surface area of cloud droplets, ultimately enhancing the cloud albedo. However, with the rapid increase in vertical velocity and aerosol number concentration, the growth rate of cloud droplet number concentration and the cloud droplet effective radius slowed down simultaneously, consequently leading to a reduction in the growth rate of the cloud droplet total surface area, cloud albedo, and cloud optical thickness. Moreover, when the aerosol chemical composition comprises organic carbon, ammonium sulfate, and sea salt at the same aerosol number concentration, the cloud droplet effective radius decreases, leading to an increase in the total surface area and a consequent increase in the optical thickness of the cloud. The findings of this work have clarified the influence mechanism of the aforementioned factors on cloud optical thickness and deepened the theoretical understanding of the first indirect effects of aerosols.
2023, 28(3): 315-326.
doi: 10.3878/j.issn.1006-9585.2022.22040
Abstract:
In recent years, air pollution in Yunnan Province during spring has emerged as a major challenge in attaining optimal air quality. This work comprehensively analyzes the evolution characteristics of air quality and the impacts of meteorological factors and biomass burning in foreign regions on air quality in the Yunnan Province during spring from 2018 to 2021. The analysis is based on ground monitoring data and satellite remote sensing data. The results showed that in the past four years, the nonattainment days in spring approached 262 d (including six heavy pollution days), accounting for 91.3% for all cities and 96.8% in southern Yunnan for the whole year. In terms of temporal distribution, the pollution was concentrated in the period spanning mid-March to mid-April, with the heaviest in 2019 followed by 2021, which resulted in a considerable decrease in days with good air quality and an increase in days with moderate air quality. In 2020, pollutant concentration was the lowest, and heavy pollution occurred over a span of 6 d. Spatially, southern Yunnan experienced significantly higher pollution than central and northern Yunnan, with Xishuangbanna accounting for 27% of all nonattainment days. However, ozone (O3) concentration was highest in southwest and central Yunnan, with the highest in Pu’er. From 2018 to 2021, PM2.5 was the prevalent primary pollutant, although the proportion of O3 as the primary pollutant was slightly higher in 2018 and 2019. To this end, PM2.5 and O3 were synergistically correlated, and high O3 levels promoted the secondary generation of PM2.5. Both pollutants were associated with low precipitation and southwest wind. O3 pollution was most likely to occur during mid-high temperatures and mid-low humidity, whereas PM2.5 pollution was associated with mid-high temperatures and mid-high humidity. However, mid-high temperature and mid humidity resulted in synergistic pollution of O3 and PM2.5. In 2019, the highest pollution levels coincided with the highest temperature and the lowest precipitation. Air pollution in Yunnan was influenced by open biomass burning, and pollutant concentrations had a remarkable positive correlation with the number of fire points at lag 0-3 d. The highest correlations for PM2.5 and O3 were observed at lag 2 d and lag 1 d, respectively. In unfavorable meteorological conditions dominated by the southwestern monsoon, biomass burning in foreign regions, particularly in Myanmar in the Indochina Peninsula, is the primary source of air pollution during spring in Yunnan. This biomass burning enhances the secondary generation of air pollution. Therefore, the focus of spring pollution control in Yunnan should be on establishing a perfect cross-border air pollution prevention and control mechanism and strengthening the early warning system for biomass burning in foreign regions under unfavorable weather conditions.
In recent years, air pollution in Yunnan Province during spring has emerged as a major challenge in attaining optimal air quality. This work comprehensively analyzes the evolution characteristics of air quality and the impacts of meteorological factors and biomass burning in foreign regions on air quality in the Yunnan Province during spring from 2018 to 2021. The analysis is based on ground monitoring data and satellite remote sensing data. The results showed that in the past four years, the nonattainment days in spring approached 262 d (including six heavy pollution days), accounting for 91.3% for all cities and 96.8% in southern Yunnan for the whole year. In terms of temporal distribution, the pollution was concentrated in the period spanning mid-March to mid-April, with the heaviest in 2019 followed by 2021, which resulted in a considerable decrease in days with good air quality and an increase in days with moderate air quality. In 2020, pollutant concentration was the lowest, and heavy pollution occurred over a span of 6 d. Spatially, southern Yunnan experienced significantly higher pollution than central and northern Yunnan, with Xishuangbanna accounting for 27% of all nonattainment days. However, ozone (O3) concentration was highest in southwest and central Yunnan, with the highest in Pu’er. From 2018 to 2021, PM2.5 was the prevalent primary pollutant, although the proportion of O3 as the primary pollutant was slightly higher in 2018 and 2019. To this end, PM2.5 and O3 were synergistically correlated, and high O3 levels promoted the secondary generation of PM2.5. Both pollutants were associated with low precipitation and southwest wind. O3 pollution was most likely to occur during mid-high temperatures and mid-low humidity, whereas PM2.5 pollution was associated with mid-high temperatures and mid-high humidity. However, mid-high temperature and mid humidity resulted in synergistic pollution of O3 and PM2.5. In 2019, the highest pollution levels coincided with the highest temperature and the lowest precipitation. Air pollution in Yunnan was influenced by open biomass burning, and pollutant concentrations had a remarkable positive correlation with the number of fire points at lag 0-3 d. The highest correlations for PM2.5 and O3 were observed at lag 2 d and lag 1 d, respectively. In unfavorable meteorological conditions dominated by the southwestern monsoon, biomass burning in foreign regions, particularly in Myanmar in the Indochina Peninsula, is the primary source of air pollution during spring in Yunnan. This biomass burning enhances the secondary generation of air pollution. Therefore, the focus of spring pollution control in Yunnan should be on establishing a perfect cross-border air pollution prevention and control mechanism and strengthening the early warning system for biomass burning in foreign regions under unfavorable weather conditions.
2023, 28(3): 327-342.
doi: 10.3878/j.issn.1006-9585.2022.22071
Abstract:
Short-term climate prediction of precipitation in the basin is imperative for disaster prevention and reduction in the basin. To further improve the prediction capacity of the new-generation atmospheric general circulation model, IAP AGCM 4.1 by the Institute of Atmospheric Physics of the Chinese Academy of Sciences, on the summer precipitation in the Huaihe and Yangtze River Basins, a regional Empirical Orthogonal Function (EOF) correction scheme suitable for the two river basins is established based on the analysis of the regional characteristics of the summer precipitation using the rotating EOF (REOF) method. Furthermore, the new scheme was validated based on 30-year (1981–2010) hindcasts of the IAP AGCM 4.1 climate model in the Huaihe and Yangtze River Basins. Results reveal that the new correction method significantly improves the prediction of summer precipitation in the Huaihe River Basin, with the average correlation coefficient of the Huaihe River Basin increasing from 0.03 to 0.22. Moreover, the seasonal precipitation forecast of the Yangtze River Basin is also significantly improved, with the average correlation coefficient increasing from −0.05 to 0.24. The results of the new correction method are notably better than those of previous methods based on whole-basin data, confirming that using strong local precipitation characteristics to determine the correction area based on REOF analysis can improve the effect and stability of EOF correction. The proposed method can potentially be applied to other basins as well.
Short-term climate prediction of precipitation in the basin is imperative for disaster prevention and reduction in the basin. To further improve the prediction capacity of the new-generation atmospheric general circulation model, IAP AGCM 4.1 by the Institute of Atmospheric Physics of the Chinese Academy of Sciences, on the summer precipitation in the Huaihe and Yangtze River Basins, a regional Empirical Orthogonal Function (EOF) correction scheme suitable for the two river basins is established based on the analysis of the regional characteristics of the summer precipitation using the rotating EOF (REOF) method. Furthermore, the new scheme was validated based on 30-year (1981–2010) hindcasts of the IAP AGCM 4.1 climate model in the Huaihe and Yangtze River Basins. Results reveal that the new correction method significantly improves the prediction of summer precipitation in the Huaihe River Basin, with the average correlation coefficient of the Huaihe River Basin increasing from 0.03 to 0.22. Moreover, the seasonal precipitation forecast of the Yangtze River Basin is also significantly improved, with the average correlation coefficient increasing from −0.05 to 0.24. The results of the new correction method are notably better than those of previous methods based on whole-basin data, confirming that using strong local precipitation characteristics to determine the correction area based on REOF analysis can improve the effect and stability of EOF correction. The proposed method can potentially be applied to other basins as well.
, Available online ,
doi: 10.3878/j.issn.1006-9585.2021.21049
Abstract:
Since 1996 Bimonthly
Supervisor: Chinese Academy of Sciences
Sponsors by: Institute of Atmospheric Physics, Chinese Academy of Sciences/Chinese Meteorological Society
Editor: Wang Zifa
Email: qhhj@mail.iap.ac.cn
ISSN 1006-9585
CN 11-3693/P
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