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GEOLOGY, ECOLOGY, AND LANDSCAPES INWASCON https://doi.org/10.1080/24749508.2022.2138013 RESEARCH ARTICLE Spatial variability and trend analysis of dust aerosols loading over Indian sub- continent using MERRA 2 & CALIPSO data a b Mohd Nazish Khan and Md Sajid Akhter a b Department of Physical Geography, Samarkand State University; Interdisciplinary Department of Remote Sensing and GIS Applications, Aligarh Muslim University ABSTRACT ARTICLE HISTORY Received 10 September 2021 This paper summarizes the spatial-temporal analysis of aerosol dust loading and aerosol dust Accepted 13 October 2022 extinction over the Indian subcontinent for identifying trends and patterns for a period of 40 years from 1980 to 2019. These analyses are based on the Cloud-Aerosol Lidar and Infrared KEYWORDS Pathfinder Satellite Observation (CALIPSO) data using Modern-Era Retrospective Analysis for MERRA-2; CALIPSO; spatial Research and Applications, Version 2. The high-resolution data of CALIPSO indicate a high variability; trends; dust concentration of dust column mass density over the northwestern part of India. It increases aerosols from central India to Rajasthan and Jammu & Kashmir regions. Mean dust aerosol optical depth also suggests an increase in the dust loading over northwestern part of the country. 1. Introduction precipitation. Another significant effect of dust aerosols Tiny heterogeneous mixtures of solid and liquid parti- is the scattering of visible radiation and absorption of −3 2 cles of different shapes and sizes (~10 to 10 µm), infrared (IR) light due to the high concentration of suspended in the atmosphere, are termed aerosols hematite in India comparatively to Saharan dust aero- (Prospero et al., 1983) and have a significant impact sols, resulting in warming of the atmosphere on the earth’s climate (Ramanathan & Carmichael, (Deepshikha et al., 2005; Moorthy et al., 2005; 2008), water cycle (Ramanathan et al., 2001), and Satheesh et al., 1999). human health (Lelieveld et al., 2019). Further, these In the last few decades, several earth observation particles affect the earth’s atmosphere in the form of instruments (Moderate Resolution Imaging externally induced aerosol radiative forcing, causing Spectroradiometer- MODIS, Multi-Angle Imaging disturbances in the radiation balance of the earth SpectroRadiometer- MISR, Ozone Monitoring (Toshihiko et al., 2005). The effects of aerosols can be Instrument- OMI, and Cloud-Aerosol Lidar and categorized as direct including scattering and absorp- Infrared Pathfinder Satellite Observation tion of both terrestrial and solar radiation (Russel et al., [CALIPSO]) were developed to retrieve different para- 2014), and indirect works through the modification of meters of the atmosphere including aerosol properties, cloud properties including life span and albedo. concentrations, and effects at different spatial- However, the effects of aerosols can be varied spatially temporal resolutions (Bilal et al., 2017; Mhawish et. and temporally. In addition, a high concentration of al., 2018). However, the present study focuses on aerosols in a particular region can have an adverse CALIPSO data for envisaging the pattern, concentra- impact on human health by entering the respiratory tion, and distribution of aerosols over the Indian sub- system (Miller et al., 1979) and heavy loading of acidic continent. CALIPSO was launched by NASA for aerosols can lead to acid rain, causing damage to the earth’s weather, climate, and air quality analyses. It flora and fauna (Singh & Agrawal, 2007). On the other combines an active LIDAR system and passive IR hand, aerosols can affect the electrical conductivity of visible imager to examine the vertical depth and prop- the atmosphere by altering of mobility of ions, and such erties of thin clouds and aerosols around the globe. properties of aerosols have a significant impact on Modern-Era Retrospective Analysis of Research and regional monsoon systems and exhibit interannual Applications, Version 2 (MERRA-2) was used to ana- trends (Kaskaoutis et al., 2012). lyze climatological factors and dust aerosols over These aerosols are removed from the atmosphere by Indian landmasses and oceanic regions for a period two natural phenomena: dry deposition and wet of 40 years from 1980 to 2019. Further, CALIPSO data removal (Junge C.E., 1963; Slinn and Slinn, 1980; were classified using MERRA-2 for visualizing the Prospero et al., 1983). Dry deposition is a gravitational strength and weakness of the dust loading and long- settling process, while wet removal is in the form of term trends over the Indian subcontinent. CONTACT Mohd Nazish Khan email@example.com Department of Physical Geography, Samarkand State University, Uzbekistan, Samarkand © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 2 M. NAZISH KHAN AND M. SAJID AKHTER To accomplish this task, unique algorithms, remote instrument with passive IR and visible sensors sensing, and GIS techniques have been employed for onboard cloudSat with the aim of better understand- the various measurements in terms of spatial variation ing of aerosols behaviour and cloud formation and temporal coverage. Satellite products of CALIPSO (Winker et al., 2007; Huang et al., 2019). In the present were used to analyze the loading of dust and their study, Level 3 aerosol products were used for the trends to forecast its effects on atmospheric variables production of monthly mean profiles of aerosol optical by using models such as GOES-5. properties on a uniform spatial grid in the troposphere up to an altitude of 12 km. Level 3 products are derived after quality screening by averaging version 3 2. Study area CALIOP Level 2 aerosol profile. For the generation of Level 3 data, sky and lightning conditions were India is the seventh largest country in south Asia, and evaluated every month. Monthly mean data were uti- it lies between latitude 08.000–28.00 and longitude lized for dust aerosol optical depth (AOD) and pol- 77.00–100.00. It experiences different climates from luted dust AOD at a spatial resolution of 2° × 5° north to south as alpine climate monsoon and oceanic (latitude and longitude) from 2007 to 2019. climate and west to east as desert climate, monsoon, and valley climates. The southern boundary of India is surrounded by Western and Eastern Ghats. Indian 3.1 MERRA-2 regions experience four seasons – winter from December to February, pre-monsoon from March to MERRA-2 was introduced to replace the MERRA May, summer monsoon from June to September, and dataset by incorporating advancements in the assim- post-monsoon from October to November (Figure 1). ilation system. It enables the assimilation of modern General aerosol distribution and their characteris- hyperspectral radiance and microwave observations tics display large spatial variation and heterogeneity with GPS-Radio Occultation by using the global navi- over the Indian region which is related to its closeness gation satellite system. MERRA-2 uses the GEOS-5 to a wide variety of aerosol cradles. For example, the atmospheric model and data assimilation system ver- peninsular region is concentrated by a large variety of sion 5.12.4, for the generation of these reanalysis pro- oceanic-origin aerosols. On the western extremity, ducts. Both meteorological and aerosol observations mineral dust particles cover the entire region while are assimilated into a global assimilation system with densely populated urban centres and industrial zones the same spatial resolution (about 50 km in the latitu- produce a significant amount of anthropogenic aero- dinal direction) as MERRA. sols (Miller & Tegen, 1998). It is evident that India has The present study uses monthly mean data of (i) 22% forest cover of the total geographical area and dust surface mass concentration, (ii) dust column witnesses forest fires during dry seasons, resulting in mass density, and (iii) dust extinction aerosol optical addition in the aerosols. It is also noted that a major thickness (AOT) at 0.5° × 0.625° spatial resolution portion of Indian land is used for agricultural activity. from MERRA2 aerosol reanalysis for a period of Consequently, a significant amount of crop residue 40 years from 1980 to 2019. burns which produces biomass aerosols (Bhuvaneshwari et al., 2019; Kaskaoutis et al., 2014). 3.2 Trends analysis During pre-monsoon, prevailing northwesterly and westerly winds transport a large amount of dust aero- Trend analysis helps in the prediction of the direction sols from the western arid continental region over the of dust aerosols over the Indian region during Indian landmass. a considerable period from 2007 to 2019. Data were retrieved from CALIPSO and correlated with meteor- ological data for a period of 40 years from 1980 to 3. Data and methodology 2019. Such analyses have already been performed by Trends of columnar and surface dust loading are esti- other workers such as Tiao et al. (1990), Weatherhead mated using temporal satellite data products and their et al. (1998), and Hsu et al. (2012). These analyses climatological effects (flowchart). CALIPSO data have provide insights about the regional trend of each para- been obtained from Atmospheric Science Data meter in a grid where trends are estimated using the Centrefor further analysis. Further, aerosol reanalysis absolute value of the ratio of the trend to data have been put into MERRA 2for analyzing trends a corresponding uncertainty. Trend results are statis- of aerosols spatially and temporally. tically significant at a 95% confidence level; this ratio is CALIPSO mission was launched on 28 April 2006, greater than 2 while they are significant at a 90% to probe the vertical structure and properties of thin confidence level and the ratio is greater than 1.65 clouds and aerosols by combining an active Lidar (Hsu et al., 2012). GEOLOGY, ECOLOGY, AND LANDSCAPES 3 Figure 1. India and its geographical extent. The country is divided into 28 states and 8 union territories. 4. Climatology Indian landmass and surrounding oceanic regions, dust surface mass concentration data of MERRA-2 Climatology of dust aerosol loading is examined using have been used for the period from 1980 to 2019 dust surface mass concentration, dust column mass (Figure 2). Results reveal as different colors indicate density, and dust extinction AOT from MERRA 2 the varied concentration of dust loading over Indian aerosol reanalysis data. For the estimation of the cli- landmass. Figure 2 clearly reveals that dust matology of surface-level dust aerosol loading over 4 M. NAZISH KHAN AND M. SAJID AKHTER Figure 2. mMean surface level of dust surface mass concentration from 1980 to 2019. concentration increases from the southern region to loading of columnar dust while south India is having lowest concentration of columnar dust loading (0.8– the northwestern region and it accumulates in the −4 −2 1 × 10 kg m ). Similar to the meridional variations northwestern extremity of India. seen with surface-level dust loading, columnar dust Further, it shows heterogeneity in the spatial dis- abundance also shows an increase in concentration tribution of dust aerosol mass concentration in the from north to south over the Indian landmass. It is Indian subcontinent. also observed that mean columnar dust loading is high The monthly mean of dust column mass density −4 −2 as 2 × 10 kg m over the Indo-Gangetic Plain (IGP), over Indian landmass and the surrounding oceanic −4 −2 while it is seen as more than 3.5 × 10 kg m over region was obtained from MERRA 2 for the period from 1980 to 2019 (Figure 3). In this, the Indian northwest India (Jethva et al., 2005). Data indicate that oceanic region (blue) shows regions of low columnar the Thar Desert is the main contributor to dust load- dust loading than Gujrat, Rajasthan, etc. (red). It ing in the northwestern region. In addition, a northern means northwest India is experiencing the highest region of the Arabian Sea which transects its boundary Figure 3. Mean dust column mass density from 1980 to 2019, based on MERRA-2 aerosol reanalysis. GEOLOGY, ECOLOGY, AND LANDSCAPES 5 Figure 4. Mean dust extinction AOT from MERRA2 aerosol reanalysis. with India is also experiencing significant dust loading Dust extinction AOT was used as representative of and columnar dust loading. It is also observed high dust aerosol loading which displays dust extinction over the north and northwest regions. While southern over a period from 1980 to 2019 (Figure 4). On the other hand, Figure 3 indicates low dust AOT by blue latitudes of the Arabian Sea exhibit negligible concen- color (southern region) and high as red color (north- trations of dust aerosols, northern latitudes show large ern region). It shows lower values in the southern dust loading with a density greater than −4 −2 peninsula while higher values are in the northwest 3.5 × 10 kg m . Figure 5. Mean dust AOD from CALIPSO from 2007 to 2010, which is a representative value for spatial distribution over India. 6 M. NAZISH KHAN AND M. SAJID AKHTER region. It means that the influence of dust aerosols polluted dust model is designed for the detection of over the southern part is feeble in comparison to the such episodes (Omar et al., 2009). Polluted dust aero- northwest. The high concentration of dust aerosols in sols are seen over a very large spatial extent, including the northwest corresponds to an arid region where both continental and oceanic regions. Figure 6 shows dust production is very high. the mean value of polluted dust AOD over the Indian region from CALIOP, from January 2007 to August 2010. Polluted dust AOD shows significant 4.1 Satellite-based observation differences from dust AOD which indicate local influ - ence (industrial effluents, construction dust, automo- CALIOP uses state-of-the-art Lidar technology to bile exhaustion, etc.) on polluted dust AOD. Polluted assess and collect data which onboard CALIPSO pro- dust AOD is observed to be higher over the regions of vides measurements of dust aerosols worldwide. This IGP and northeastern parts of peninsular India. instrument measures data at two wavelengths along Polluted dust also shows very low concentrations with polarization ratio and produces different aerosol over the southern latitudes of the Indian region. data for further analysis. It indicates large spatial variation in terms of dis- tribution of dust AOD where blue indicates low dust 4.2 Long-term trends of dust aerosols over India and red indicates high dust AOD. It resembles MERRA 2 reanalysis data and shows close affinity. For long-term trends of dust aerosols over the Indian As AOD increases from south to north, this data subcontinent, the MERRA-2 and CALIPSO data were shows remarkable diversity. However, in some places, analyzed. An east-west running big columnar strip it shows local causes of dust loading in the atmo- (below Himalayan foothills) that comprised dust sur- sphere. Figure 5 shows some regions in the northern face mass concentration was observed, which indicates extremity are showing high AOD values in compar- regional effects on loading dust aerosols over the ison to other surrounding regions having low AOD region (Figure 7). values. Further, this data may be correlated with the It reveals a remarkable trend of increasing dust effects on the health of vegetation, human health, and aerosols over the IGP, while the decreasing trend is impact on pollution. found in a northwest region with a decrease rate of −3 −1 Results are derived from CALIPSO data for pollu- more than −0.5 µg m year . Annual mean values tion dust AOD and depicted in Figure 6. It is clear that were calculated using monthly mean data of loading CALIOP provides information on polluted dust aero- from MERRA-2. Further, it was estimated using dust sols at a regional scale. Results revealed the impact of surface mass concentration for a period of 40 years. local factors on increasing pollution at local levels in Data clearly show that IGP received maximum loading India (Indian cities). In addition, mixing up dust with of dust surface mass extinction. The analyses clearly biomass burning smokes is frequent in regions closer state that the Indian subcontinent experiences a high to the sources of both of these aerosols. CALIPSO concentration of dust aerosols throughout the year Figure 6. Mean polluted dust AOD from CALIPSO from 2007 to 2010. GEOLOGY, ECOLOGY, AND LANDSCAPES 7 Figure 7. Long-term trends of dust surface mass concentration from 1980 to 2019, based on MERRA-2 aerosol reanalysis. 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Geology Ecology and Landscapes – Taylor & Francis
Published: Nov 6, 2022
Keywords: MERRA-2; CALIPSO; spatial variability; trends; dust aerosols
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