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Article

Spatiotemporal and Vertical Distribution of Asian Tropopause Aerosol Layer Using Long-Term Multi-Source Data

by
Hongchao Liu
1,
Ren Li
2,* and
Junjie Ma
2,3
1
College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
2
Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
3
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2023, 15(5), 1315; https://doi.org/10.3390/rs15051315
Submission received: 1 February 2023 / Revised: 21 February 2023 / Accepted: 25 February 2023 / Published: 27 February 2023
(This article belongs to the Special Issue Remote Sensing of Atmospheric Aerosols over Asia: Methods and Applications II)
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Abstract

:
The Asian tropopause aerosol layer (ATAL) is an enhanced aerosol concentration layer in the upper troposphere and lower stratosphere over Asia, and it has important effects on radiation balance, atmospheric circulation, regional climate, and atmospheric chemical processes. However, despite its importance, the specific structure and long-term variation trend of the ATAL have been rarely analyzed, which is critical for assessing the impact of ATAL on climate change and evaluating the performance of climate models. This study compared and analyzed the three-dimensional spatial distribution characteristics and temporal variability using CALIPSO, SAGEII, and MERRA-2 data and discussed the possible causes of the variation. The results showed that the ATAL began to appear in the mid-to-late 1990s and then strengthened rapidly until 2010, after which this trend was no longer observed. Moreover, significant heterogeneity existed in the distribution of aerosol concentration in the ATAL, showing north–south differences (NSDs) in both time and space. In addition, it was found that besides surface emissions, atmospheric circulation, the strength of convective transport, and stratosphere–troposphere exchange processes also contribute to this pattern. This study has important implications for quantifying the climate consequences of the ATAL.

1. Introduction

Since the industrial revolution, the human economy and society have developed rapidly. With the explosion of industry and the rapid development of the transportation and energy industries, the pollution problem has become increasingly serious [1,2]. Nitrogen and sulfide emissions form acid rain, damage forests, and destroy the ecological environment [3]. The emission of inhalable particulate matter deteriorates air quality and damages human health [4]. Urban pollution also leads to photochemical reactions under the irradiation of the sun, resulting in the formation of photochemical smog, which seriously harms both human health and the environment [5]. Furthermore, the impact of pollutant emissions on the climate should not be underestimated. Emissions of carbon dioxide and other greenhouse gases are significant contributors to global warming. In addition, climate problems related to anthropogenic emissions, such as the ozone hole, rising sea levels, and increased extreme weather events, are receiving increasing attention [6].
In recent years, as an important part of the global economy, South Asia has experienced rapid economic development among emerging economies in the region [7]. However, along with this development, rapid industrialization and urbanization have also caused many pollution emissions [8]. These emissions have caused serious, atmospheric pollution and air quality problems extending from the planetary boundary layer to the middle and upper troposphere and even to the stratosphere through upward motion, ultimately affecting the entire world [9,10,11,12]. In 2011, Vernier et al. found an aerosol layer that exists in the atmosphere with a vertical scale of 12–18 km and extends horizontally from the Eastern Mediterranean across India to Western China (5–105°E; 15–45°N) using CALIPSO data and named it the Asian tropopause aerosol layer (ATAL) [13,14]. It has been found that anthropogenic emissions from the ground can be transported upward to the upper troposphere lower stratosphere (UTLS) [15,16,17] and then accumulate to form the ATAL.
As the transition region between the troposphere and stratosphere, the UTLS is the key region of mass and energy exchange between the two [18]. The widespread existence of water vapor, ozone, and other chemicals in the UTLS region plays an important role in the energy and radiation balance of the earth–atmosphere system [19,20,21]. Thus, the ATAL has important implications for atmospheric radiation, circulation, and chemical processes in the UTLS region [22,23].
The discovery of the ATAL has drawn significant attention from researchers, who have conducted numerous studies on its formation mechanism and components. Many studies have shown that during the South Asian Summer monsoon (SASM), the near-surface air can be rapidly lifted and transported upward and controlled by the anticyclonic circulation under the combined action of the anticyclonic circulation and persistent deep convective activity [24,25,26]. The research on the ATAL’s components mainly includes observational and model simulation studies. Recent aircraft observations in 2017 and balloon measurements in 2015 show that the ATAL may be composed of sulfate, organics, nitrates, black carbon, and dust [14,27,28]. However, the results from model simulations are quite different. Using the ECHAM5-HAMMOZ model, Fadnavis et al. [29] found that mineral dust aerosols are also an important component. Yu et al. [30] pointed out that the ATAL mainly comprises secondary organic, sulfate, and primary organic aerosols. The simulation results by Fadnavis et al. [31] indicated a continuous maximum value of carbon aerosol in the ATAL. Both Fairlie et al. [32] and Gu et al. [33] confirmed the main contribution of nitrate.
Although there have been numerous studies focused on the ATAL’s formation mechanism and components, its specific three-dimensional structure and long-term change trend have rarely been analyzed. An accurate understanding of the temporal and spatial variation characteristics of the ATAL is important for studying its climate effects [34,35]. However, the reliability of the reanalysis data on the ATAL needs to be verified. In addition, the low spatial and temporal resolution of satellite observations also causes difficulties in the analysis of the ATAL. To solve these problems and clarify the spatiotemporal and vertical distribution characteristics of the ATAL, we employ multi-source data to compare and analyze the three-dimensional spatial distribution characteristics and temporal variability of the ATAL and discuss the possible causes for the variation trend. This study is organized as follows: The materials and methods are described in Section 2. Next, Section 3 shows the spatiotemporal variation characteristics of the ATAL. Section 4 then discusses the possible reasons for the regional differences. Finally, Section 5 provides a conclusion for the study.

2. Materials and Methods

2.1. CALIPSO

The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite provides a new tool to investigate atmospheric aerosols. The CALIPSO dataset used here is level 1B version 4.10 orbital data in the June, July, and August (JJA) from 2006 to 2019, which can be obtained from https://asdc.larc.nasa.gov/project/CALIPSO/CAL_LID_L1-Standard-V4-10_V4-10 (accessed on 11 March 2021), and daytime data were discarded. CALIPSO Level 1B products offer several advantages for studying atmospheric aerosols. For example, the CALIPSO Level 1B products include 199 layers of data from bin 89 to bin 288, covering an altitude range from 8.3 to 20.2 km. The data has a horizontal resolution of 1 km and a vertical resolution of 60 m in the upper troposphere at this altitude. The high-resolution lidar measurements provide detailed vertical profiles of aerosol backscatter and extinction coefficients, enabling researchers to examine the fine structure and layering of aerosols in the atmosphere. Level 1B products also provide direct measurements of these aerosol properties, whereas Level 2 and Level 3 products are derived from these measurements. The Level 1B data undergoes a more rigorous calibration process, ensuring that it accurately reflects the true aerosol properties in the atmosphere. The detailed information available in Level 1B data allows for more in-depth analysis and investigation of aerosol properties, such as particle size distribution, shape, and composition, making it particularly useful for studying atmospheric aerosols. Quality control was implemented according to Equation (1), and data with a depolarization ratio of less than 0.05 were excluded and then interpolated into a regular grid of 1° latitude × 1° longitude [13].
DR = TAB − PAB PAB ,
where DR is the depolarization ratio, TAB refers to total attenuated backscatter at 532 nm, and PAB represents perpendicular attenuated backscatter at 532 nm.

2.2. SAGEII

The Stratospheric Aerosol and Gas Experiment (SAGE) II aims to determine the spatial distributions of stratospheric aerosols, ozone, water vapor, and other substances [36,37,38]. It was launched in October 1984 and operated until September 2005, providing more than two decades of atmospheric data [39]. The instrument used solar occultation, a technique in which the satellite observes the sun as it sets or rises over the Earth’s limb, to measure the concentration and distribution of atmospheric gases and aerosols. By measuring the amount of solar radiation absorbed by different atmospheric components, SAGEII provided data on the vertical distribution of aerosols and gases, as well as their seasonal and latitudinal variations. This long-term stable dataset has proved invaluable in determining ozone trends [40] and identifying responses to episodic events such as volcanic eruptions [41]. SAGEII was a crucial tool for studying the composition and chemical processes of the atmosphere. SAGEII data has been used to investigate climate change, air quality, and the transport of pollutants in the atmosphere [42]. The satellite worked well between 1984 and 2005, and the SAGEII data has been used to confirm the enhancement of the aerosol concentration in the ATAL [43]. The summer-to-winter ratio (SWR) of Ext525 was calculated using SAGEII data, which can be obtained from https://sage.nasa.gov/missions/about-sage-ii/ (accessed on 1 September 2021), from 1994 to 2005 in the entire ATAL region according to the method of Thomason and Vernier [43] and Vernier, et al. [14].

2.3. MERRA-2

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), which is a long-term global reanalysis dataset with a high spatial resolution to assimilate space-based observations variables, such as temperature, wind, humidity, and precipitation, as well as aerosols, provides a global view of weather and climate beginning in 1980. It is produced by NASA’s Global Modeling and Assimilation Office and provides a comprehensive record of the Earth’s weather and climate over the past few decades. It is widely used in weather forecasting, climate modeling [44], air quality studies, and researching aerosols [45], precipitation [46], and other subjects [47]. Data used in this paper include aerosol mass mixing ratios, geopotential altitude, wind, tropopause altitude, and vertical pressure velocity from 1994 to 2019. The MERRA-2 data is open access, and the data link is https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/data_access/ (accessed on 1 September 2021).
This study defines the ATAL region as 5–105°E, 15–45°N, and 12–18 km vertically, according to Vernier et al. [13,14]. The TAB obtained from the CALIPSO level 1B version 4.10 orbital data is used to represent aerosol load in ATAL, and SWR is used for SAGEII. As to MERRA-2, the total aerosol mass mixing ratio is adopted, which is computed from aerosol mass mixing ratios according to Buchard et al. [45] and Provençal et al. [48].
To facilitate comparison among the various variables obtained from CALIPSO, SAGEII, and MERRA-2, we standardized the different variables in each dataset to make them dimensionless. Specifically, we used the original values in Figure 1, Figure 2, Figure 3, Figure 4, Figure 7 and Figure 9, while standardized data was used in Figure 5, Figure 6 and Figure 8 to allow for more effective comparison and analysis.

3. Results

3.1. Spatial Distribution Characteristics of ATAL

Figure 1 shows the data from CALIPSO level 1B at 20:22 on 4 July 2016. The line in Figure 1a represents the ground projection of the satellite orbit over the Qinghai-Tibet Plateau (QTP) and across the ATAL region, where the vertical distribution of the aerosol layer can be observed. The red part of the line is 0–50 degrees north latitude, representing the range of vertical distribution in Figure 1b. It can be seen from Figure 1b that at this moment, the aerosol layer is mainly distributed between 10 and 30 degrees north latitude and 11 and 19 km in height. At the same height, the aerosol concentration in this area is significantly higher than that in other areas, which confirms the existence of the ATAL.
Figure 2 shows the average pattern of the ATAL in the summer months (colors) with the 100-hPa geopotential height (white contours) and wind field (arrows) from 2006 to 2019. As can be seen from the figure, the powerful Asian summer monsoon anticyclone (ASMA) controls the entire south and east Asia region during the Northern Hemisphere summer [49,50]. The north side of the ASMA center is the westerly jet, while the south side is the easterly jet. In June, the 16,800-m isopotential height line of the ASMA extends to the Arabian Peninsula in the west and the eastern side of the QTP in the east. The central geopotential height of the ASMA is 16,861 m. The high-value region of the ATAL aerosol concentration over the Indian Peninsula is not yet evident. Even under the action of dry deposition and wet clearance, aerosol particles still have a considerable retention time [51,52,53]. Thus, the peak time of aerosol concentration is later than that of the UTLS. Southwesterly winds prevail on the west side of the ASMA, and relatively clean air is transported from south to north, forming a low-aerosol-concentration area over the Eastern Mediterranean.
In July, compared with June, the area surrounded by the 16,800-m isopotential height line of the ASMA decreases significantly, and the east–west range is about 45–90 degrees east longitude. The geopotential height of the center of the ASMA is 16,859 m, similar to that from June. The aerosol concentration in South Asia increases significantly, and the aerosol concentrations in the Indian Peninsula and Indochina Peninsula show obvious extreme points. In August, the area surrounded by the 16,800-m isopotential height line of the ASMA decreases further, and the east–west range is from 55 to 80 degrees east longitude. The geopotential height of the center of the ASMA is 16,850 m, with a significant decrease. The extreme regions of aerosol concentration over the Indian Peninsula and Indochina Peninsula are denser, intensifying the westward aerosol transport.
In conclusion, the ASMA located in the middle and upper troposphere dominates the atmospheric circulation over South Asia during the Northern Hemisphere summer. During the JJA, the easterly jet prevails on the south side of the ASMA, while the westerly jet prevails on the north side. Surface pollutants from South Asia can be transported upward to the UTLS region and accumulate there, and then mixed and dispersed in the ASMA along with the atmospheric circulation [54]. It is worth noting that in Figure 2, although the regional mean TAB in the ATAL is higher than that in the surrounding regions, the TAB in the northern region of the QTP (NQTP, red rectangle in Figure 2, which is also located on the north side of the ASMA, between 70 and 90 degrees east longitude and 32 and 42 degrees north latitude) is lower than the regional average of the entire ATAL, forming a clear north–south differences (NSDs), and this region persists during the JJA.

3.2. Temporal Trend of ATAL

Figure 3 shows the horizontal distribution of the temporal trend of TAB in the ATAL region during the JJA from 2006 to 2019. The dotted area indicates that the linear trend passes the 99% significance test. In June, TAB in the ATAL region, which ranges from the Mediterranean region to the eastern side of the QTP, showed an overall positive trend. In the Indian Peninsula and Indochina Peninsula, which are controlled by the SASM, the southerly air from the sea brings abundant water vapor, and the strong upward motion brings water vapor, aerosol, and other substances to the middle and upper troposphere [55,56], forming clouds at high altitudes [57]. In the process of quality control, by eliminating the data under the cloud or with a depolarization ratio less than 0.05, some data in this area are eliminated, thus forming blank areas. However, the high-value area of the positive trend of TAB can still be seen in the southern foot of the QTP from the Indian Peninsula to the Indochina Peninsula, which indicates that the aerosol concentration in the key area affected by the SASM gradually increased between 2006 and 2019. At the same time, the Mediterranean Sea and its coastal regions also show a positive trend in TAB. In contrast, the NQTP shows a weak negative trend, which means a trend discrepancy between this region and neighboring regions under an overall increase in ATAL aerosol concentration.
In July, the TAB in the area south of 30 degrees north latitude shows a positive trend of varying rates. The positive trend of the TAB is more significant from the Indian Peninsula to the Indochina Peninsula. Specifically, the northern Indian Ocean between the Persian Gulf and the Indian Peninsula, along the coast of the Bay of Bengal, and along the southern foothills of QTP show a clear positive trend in the high-value area, and it is higher than that in June. At the same time, compared with June, the area of the negative TAB trend in the NQTP significantly extends from the west side of the Iranian plateau to the east side of the QTP and shows a two-center mode. The western negative trend center is located in the Iranian plateau on the south side of the Caspian Sea. In contrast, the eastern negative trend center is located on the north side of the QTP, which is also the north side of the ASMA center. The negative trend on the north side of the QTP is significantly larger than that on the Iranian Plateau in area, and the maximum negative trend is also the same.
In August, the TAB in the area south of 30 degrees north latitude still shows a positive trend of unequal size, especially in South Asia. The high values in the northern Indian Ocean between the Persian Gulf and the Indian Peninsula, along the coast of the Bay of Bengal, and along the southern foot of the QTP are similar to those in July. On the north side of the QTP, the range of the negative trend area of TAB increases slightly compared to that in July, the two low-value areas in the east and west gradually extend to connect with each other, and the value decreases significantly. This indicates that the aerosol concentration in the negative trend area in the NQTP significantly reduced from 2006 to 2019. The decrease rate is higher when the range is larger in August.
From Figure 3a to Figure 3c, it can be seen that the aerosol concentration in key regions of the ATAL shows a significant increasing trend in the JJA between 2006 and 2019. The rate increases gradually from June to August. At the same time, there is also an area with a low linear trend of TAB in the NQTP, which means that the aerosol concentration in the NQTP presents a significant decreasing trend from 2006 to 2019. In terms of the decrease rate, whether in terms of area or intensity, the order from highest to lowest is August, July, and June.
To analyze the long-term change trend of the ATAL, we refer to the method described by Vernier, Thomason, and Kar [13] and analyze the time series of the ATAL vertical profile using the data of SAGEII from 1985 to 2005. In Figure 4, the horizontal axis represents the year, the vertical axis represents the height, and the fill color represents the SWR calculated using occultation observation data. Figure 4 shows that since the mid-to-late 1990s, there has been a significant region of high SWR between 12 and 17 km in altitude, and the central height is about 15 km, indicating that the ATAL has been gradually emerging since the mid-to-late 1990s. The high SWR from 13 km to 18 km in the early 1990s may be due to major volcanic eruptions during this period [58,59].
Figure 5 shows the ATAL time series of multi-source data from 1994 to 2019. Green lines and ordinates represent SAGEII, red lines, and ordinates represent CALIPSO, and blue lines and ordinates represent MERRA-2. The standardized SWR is used for SAGEII, the standardized TAB is used for CALIPSO, and the standardized total aerosol mass mixing ratio is used for MERRA-2. From satellite data (SAGEII and CALIPSO), the ATAL shows a trend of gradual enhancement since the mid-to-late 1990s. Between 2006 and 2010, the ATAL showed a period of rapid rise and then stabilized. In the early 1990s, MERRA-2 reanalysis data show a stronger response to large volcanoes. From the mid-to-late 1990s to 2010, the ATAL shows a steady upward trend in MERRA-2 reanalysis data, and the rate of increase accelerates from 2006 to 2010, consistent with satellite data. After 2010, both CALIPSO and MERRA-2 data show that the ATAL does not rise. The difference is that in CALIPSO data, the ATAL changes little and tends to be stable in the oscillation, while in MERRA-2 data, the ATAL shows a downward trend. Overall, the data indicate that the ATAL gradually emerged in the mid-to-late 1990s and thereafter showed a general trend of rapid enhancement until 2010, confirmed across different datasets. This behavior has also been confirmed in model simulation results by Bossolasco et al. [60]. Their results show a positive trend for all aerosols simulated by CESM-MAM7 over a long-term period (2000–2015). However, after 2010, the ATAL no longer showed an upward trend in either dataset.

4. Discussion

Many researchers have analyzed and discussed the causes of ATAL formation [14,54,61]. Since the late 20th century, the economy and society in South Asia have developed rapidly, and the regional pollution caused by burning fossil fuels and industrial development has become increasingly serious [7,8]. According to the “heat pump” theory [62,63], the special topography of the QTP makes it an important channel for the upward transport of pollutants, and the SASM also plays an important role in the upward transport of pollutants [26,62]. The QTP, as the highest plateau in the world, extends to the middle troposphere at approximately 500 hPa [64,65] and exerts significant thermal and dynamic effects on atmospheric circulation. During the Northern Hemisphere summer, the QTP acts as a heat source, heating the atmosphere [66,67]. The temperature difference between the sea and the land generates land-sea thermal circulation, which implies an upward branch of the circulation located on the south side of QTP. Additionally, the topographic barrier forces the south-to-north airflow to ascend, facilitating the upward transport of pollutants. During the SASM, strong convection and deep convection events frequently occurred over the southern foothills of the QTP. These deep convective events can transport pollutants from the boundary layer directly into the upper troposphere, and some penetrating convective events even into the lower stratosphere [54,68], creating favorable conditions for the upward transport of pollutants. In addition, large-scale uplifting movement in South Asia also promotes the transport of pollutants into the upper atmosphere [69,70]. In the upper troposphere, the trapping effect of the ASMA allows pollutants to accumulate [71]. However, according to a previous analysis, the distribution of pollutants in the ASMA is also uneven, showing significant NSDs.

4.1. The North–South Differences (NSDs)

In Figure 2, the analysis of the multiyear mean TAB in the ATAL region shows a low TAB in the NQTP throughout the summer, located on the northern side of the ASMA center, showing significant NSDs in the JJA. From June to August, the value of the northern low-value area gradually decreases, but the area gradually increases. In the linear trend diagram of TAB in Figure 3, the low-value area in the north also shows a different linear trend from the surrounding area. During the JJA, the regional mean TAB shows an obvious negative trend, which means that the aerosol concentration in this region decreases year by year. From June to August, the rate of decrease was more rapid, and the area expanded significantly. To compare and analyze the differences in aerosol concentration between the NQTP and the surrounding region, Figure 6 shows the time series of average TAB for the NQTP and the entire ATAL. As can be seen, except for a few years, the average TAB in the NQTP is smaller than that in the entire ATAL region. Combined with Figure 2, it can be confirmed that the NQTP is a low-value region of TAB in both the spatial distribution and time series. In terms of the changing trend, the average TAB in the entire ATAL region shows a gradual increase in the first 5 years and stabilizes at a high level in the last 9 years, while the average TAB in the NQTP shows a decreasing trend.
Figure 7 shows the vertical difference between the NQTP and ATAL, with the x-axis representing the SWR and the y-axis representing the height. As can be seen in Figure 7, the NQTP to ATAL ratio (NAR) is less than 1 when the altitude is above 8 km, which means that compared with the surrounding areas, the NQTP is a low-value area of aerosol content within an altitude of 8–20 km, and the difference increases with the altitude. At altitudes between 5 and 8 km, NAR fluctuates around 1. This indicates little difference in aerosol concentration between the NQTP and surrounding areas in the middle and lower troposphere. Considering that the average altitude of the QTP is above 4 km [72], the altitude interval of 5–8 km includes the boundary layer and the middle and lower troposphere in some areas of the plateau. Strong turbulent mixing and vigorous convective motion are conducive to increasing aerosol concentration at this altitude.
The discussion of TAB in the three-dimensional direction of space confirms that the aerosol distribution in the NQTP is significantly different from that in the other regions of the ATAL in the horizontal direction, vertical direction, and time series. This difference is shown as the lower aerosol concentration for the NQTP in three-dimensional space and the decreasing trend in the time series.

4.2. Causes of NSDs

It is well known that the ASMA plays an important role in forming and maintaining the ATAL. However, there are significant differences in the distribution of aerosols on the north and south sides of the ASMA center. There are also significant differences in the variation trend of aerosols on both sides. Except for the difference in surface emissions, atmospheric circulation also significantly influences aerosol NSDs. The “trapping effect” of the ASMA makes it difficult for the upward transport of pollutants to disperse in the ASMA, which makes the aerosol concentration on the south side of the ASMA center maintain a high level in summer. The north side of the ASMA is located in the westerly jet zone, which is conducive to the diffusion of pollutants under the background of the westerly belt.
Figure 8 shows the mean TAB from 70 to 90 degrees east longitude in August 2014. The horizontal coordinate represents latitude; the vertical coordinates represent altitude and pressure, respectively; and the black solid line represents the mean tropopause height over the years. As can be seen from Figure 8, in the vertical direction of the same latitude, the aerosol concentration is higher in the middle and upper troposphere, and the higher the altitude, the lower the aerosol concentration. In the easterly jet stream region south of about 30 degrees north latitude, the aerosol concentration in the UTLS region between 12 and 18 km is not much different from that in the upper troposphere region between 9 and 12 km. The blank filling in the UTLS region indicates that aerosol particles with a depolarization ratio less than 0.05 exist in this region, which may be cloud droplets with larger particle sizes. This means there is a strong deep convection in the area, and this deep convection activity plays a crucial role in the upward transport of aerosols [73,74]. Aerosol, in turn, affects the microphysical process in the cloud through the aerosol–cloud interactions, thus affecting the growth and development of clouds [75,76]. The high TAB in and under the cloud is evidence of the close interaction between clouds and aerosols. In the westerly jet stream region on the north side of the ASMA center, about 30 to 45 degrees north latitude, the aerosol concentration decreases rapidly from the upper troposphere upward. In the UTLS between 12 and 20 km, the aerosol concentration in the NQTP region is at a low level at the same height. In addition, no cloud droplets with large depolarization ratios are observed in this region. This indicates that the deep convection activity in the northern region is weaker than that in the southern region, and the weaker convection causes the weak upward transport of aerosols, which may be one of the reasons for the low aerosol concentration in the NQTP.
In terms of tropopause height, the tropopause drops between 30 and 45 degrees north latitude. At the same height, the area contains more relatively clean lower stratospheric air than areas south of 30 degrees north latitude, which also favors a northern area with lower aerosol concentrations. Meanwhile, according to the annual average zonal wind isoline, the high-value area of aerosol concentration in areas south of 30 degrees north latitude is mostly located in the easterly jet region, while the low-value area in the north latitude is mainly affected by the westerly jet. The tropopause rolling near the jet axis of the westerly jet forms tropopause folding events, which bring cleaner air from the lower stratosphere to the upper troposphere [77,78], thus forming a low-concentration area of aerosol in the UTLS region.
Figure 9 shows the spatial distribution of the average multiyear ω in the ATAL region in August, with the bottom layer representing the terrain and the filling layers representing the ω on the 750-, 500-, and 200-hPa pressure layers, respectively. During the Northern Hemisphere summer, the QTP becomes a heat source that heats the atmosphere. Thus, a thermal low-pressure system is formed in the QTP region, and the atmosphere converges and rises in the QTP region to form the ASMA in the upper troposphere [66,67]. Moreover, due to the mass continuity equation of the atmosphere, the sinking region of the atmosphere mass will be formed. As shown in Figure 9, at 750 hPa, the southern foot of the plateau in the lower troposphere and the South Asia region is dominated by updrafts, corresponding to the updrafts of the SASM circulation, and the northwest side of the QTP has downdrafts. The high topography of the QTP can block the northward movement of the SASM, resulting in the forced lifting of air. In the middle troposphere at 500 hPa, an obvious sinking motion can be seen on the north and west sides of the QTP, while an ascending movement can be seen on the south side from the lower troposphere to the upper troposphere at 200 hPa. This consistent upward motion can transport the middle and lower troposphere aerosols upward to the UTLS region, which is crucial for the formation of the ATAL.

5. Conclusions

The analysis of multi-source data showed that the ATAL was mainly distributed in the UTLS region of South Asia in summer and that its distribution differed from north to south, showing a low aerosol concentration in the NQTP. The ATAL emerged in the mid-to-late 1990s and then showed a rapid increase until 2010, after which the ATAL did not increase according to satellite and reanalysis data.
Moreover, there were clear differences in aerosol concentration between the NQTP region and the rest of the ATAL region. This difference was shown as the lower aerosol content in three-dimensional space and the aerosol content in the NQTP showed a decreasing trend from 2006 to 2019. At altitudes from 12 to 20 km, the difference gradually increased with height. From June to August, the area of the low-value area gradually extended outward, and the difference was more significant.
In addition, by analyzing the difference between NQTP and ATAL, it was found that, except for surface emissions, the formation of the low-value area in the north was mainly affected by the circulation situation, convective transport, and stratosphere–troposphere exchange processes. The easterly jet prevailed on the south side of the ASMA, and the pollutants transported from the lower troposphere were concentrated under the trapping effect of the ASMA. On the north side of the ASMA, the westerly jet prevailed. The westerly base flow was conducive to the diffusion of pollutants, thus forming the low-value area of aerosol content.
The southern side of the QTP was dominated by upward movement. Large-scale upward movement and intense deep convection provided conditions for the upward transport of pollutants. At the same time, the northern side of the plateau corresponded to downward movement, which was not conducive to the upward transport of pollutants. In addition, the NQTP was located in the region where the tropopause height dropped sharply, and there were frequent stratosphere–troposphere exchange processes in this region. A large amount of dry and clean air in the lower stratosphere was transported to the upper troposphere, which contributed to the formation of the low-value region in the NQTP to some extent.
Due to the low temporal resolution of satellite observation data and the differences between reanalysis data and satellite observation data, quantitative analysis of the ATAL is still difficult. Moreover, the quantitative analysis of the ATAL plays an important role in assessing the ATAL climate effects and evaluating and improving numerical models, which require further research.

Author Contributions

Conceptualization, H.L. and R.L.; Data curation, H.L. and J.M.; Formal analysis, H.L.; Funding acquisition, R.L.; Investigation, H.L.; Methodology, H.L.; Project administration, R.L.; Resources, J.M.; Software, H.L.; Supervision, R.L.; Validation, H.L., R.L. and J.M.; Visualization, H.L.; Writing—original draft, H.L.; Writing—review and editing, R.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (42071093), the State Key Laboratory of Cryospheric Science (SKLCS-ZZ-2023), the Natural Science Foundation of Gansu Province (22JR5RA061, 22JR5RA054).

Data Availability Statement

The CALIPSO data presented in this study are NASA/LARC/SD/ASDC. CALIPSO Lidar Level 1B profile data, V4-10. NASA Langley Atmospheric Science Data Center DAAC; 2016. Available from: https://asdc.larc.nasa.gov/project/CALIPSO/CAL_LID_L1-Standard-V4-10_V4-10 (accessed on 11 March 2021); SAGEII data can be found at https://sage.nasa.gov/missions/about-sage-ii/ (accessed on 1 September 2021); and MERRA-2 data is Global Modeling and Assimilation Office (GMAO) (2015), MERRA-2 inst3_3d_aer_Nv: 3d,3-Hourly, Instantaneous, Model-Level, Assimilation, Aerosol Mixing Ratio V5.12.4, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), at https://disc.gsfc.nasa.gov/datasets/M2I3NVAER_5.12.4/summary (accessed on 1 September 2021).

Acknowledgments

This work is based on the scientific computing platform of the Supercomputer Center of Lanzhou University.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Vertical distribution of aerosol in 2016-07-04T20-22-54 determined by CALIPSO (a) projection of orbit, (b) vertical distribution of total attenuated backscatter at 532 nm (TAB) (unit: km−1 steradian−1) from 0 to 50°N.
Figure 1. Vertical distribution of aerosol in 2016-07-04T20-22-54 determined by CALIPSO (a) projection of orbit, (b) vertical distribution of total attenuated backscatter at 532 nm (TAB) (unit: km−1 steradian−1) from 0 to 50°N.
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Figure 2. Average pattern of Asian tropopause aerosol layer (ATAL) in (a) June, (b) July, and (c) August from 2006 to 2019 using TAB determined by CALIPSO, with 100-hPa geopotential height (unit: m) and wind field (unit: m s−1). The red rectangles represent the northern region of the QTP (NQTP).
Figure 2. Average pattern of Asian tropopause aerosol layer (ATAL) in (a) June, (b) July, and (c) August from 2006 to 2019 using TAB determined by CALIPSO, with 100-hPa geopotential height (unit: m) and wind field (unit: m s−1). The red rectangles represent the northern region of the QTP (NQTP).
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Figure 3. Temporal trend of ATAL in (a) June, (b) July, and (c) August from 2006 to 2019 using TAB determined by CALIPSO. The dotted area indicates that the linear trend passes the 99% significance test. Contours are 100-hPa geopotential height (unit: m). The red rectangles represent the northern region of the QTP (NQTP).
Figure 3. Temporal trend of ATAL in (a) June, (b) July, and (c) August from 2006 to 2019 using TAB determined by CALIPSO. The dotted area indicates that the linear trend passes the 99% significance test. Contours are 100-hPa geopotential height (unit: m). The red rectangles represent the northern region of the QTP (NQTP).
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Figure 4. Vertical distribution of summer-to-winter ratio (SWR) in ATAL region from 1985 to 2005 determined by SAGEII.
Figure 4. Vertical distribution of summer-to-winter ratio (SWR) in ATAL region from 1985 to 2005 determined by SAGEII.
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Figure 5. Calculated ATAL time series of SAGEII, CALIPSO, and MERRA-2 from 1994 to 2019. Variables: standardized SWR, TAB, and total aerosol mass mixing ratio for SAGEII, CALIPSO, and MERRA-2, respectively.
Figure 5. Calculated ATAL time series of SAGEII, CALIPSO, and MERRA-2 from 1994 to 2019. Variables: standardized SWR, TAB, and total aerosol mass mixing ratio for SAGEII, CALIPSO, and MERRA-2, respectively.
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Figure 6. Calculated time series of standardized TAB by 10−4 for NQTP and the entire ATAL region from 2006 to 2019.
Figure 6. Calculated time series of standardized TAB by 10−4 for NQTP and the entire ATAL region from 2006 to 2019.
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Figure 7. Difference between NQTP and the entire ATAL region, NQTP to ATAL ratio (NAR), in the vertical direction.
Figure 7. Difference between NQTP and the entire ATAL region, NQTP to ATAL ratio (NAR), in the vertical direction.
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Figure 8. ATAL patterns in the vertical direction (color-filled contour: TAB anomaly (ratio of TAB to the average value), dimensionless quantity), tropopause height, and zonal winds (unit: m s−1).
Figure 8. ATAL patterns in the vertical direction (color-filled contour: TAB anomaly (ratio of TAB to the average value), dimensionless quantity), tropopause height, and zonal winds (unit: m s−1).
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Figure 9. Distribution of omega at different altitudes. The vertical direction is the pressure coordinate, and the bottom is the terrain.
Figure 9. Distribution of omega at different altitudes. The vertical direction is the pressure coordinate, and the bottom is the terrain.
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Liu, H.; Li, R.; Ma, J. Spatiotemporal and Vertical Distribution of Asian Tropopause Aerosol Layer Using Long-Term Multi-Source Data. Remote Sens. 2023, 15, 1315. https://doi.org/10.3390/rs15051315

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Liu H, Li R, Ma J. Spatiotemporal and Vertical Distribution of Asian Tropopause Aerosol Layer Using Long-Term Multi-Source Data. Remote Sensing. 2023; 15(5):1315. https://doi.org/10.3390/rs15051315

Chicago/Turabian Style

Liu, Hongchao, Ren Li, and Junjie Ma. 2023. "Spatiotemporal and Vertical Distribution of Asian Tropopause Aerosol Layer Using Long-Term Multi-Source Data" Remote Sensing 15, no. 5: 1315. https://doi.org/10.3390/rs15051315

APA Style

Liu, H., Li, R., & Ma, J. (2023). Spatiotemporal and Vertical Distribution of Asian Tropopause Aerosol Layer Using Long-Term Multi-Source Data. Remote Sensing, 15(5), 1315. https://doi.org/10.3390/rs15051315

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