Seasonal variability in aerosol optical depth over India: a spatio-temporal analysis using the MODIS aerosol product

Acharya, Prasenjit; Sreekesh, S.

doi:10.1080/01431161.2013.782114

Cited by 45 publications

(23 citation statements)

References 22 publications

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“…The CMIP6 interannual variability of TCF is higher than that of the CMIP5 TCF, particularly in the NH middle-and high-latitudes. Noteworthy changes have been noticed in the CMIP5 and CMIP6's TCF from the 1960s, and this may be due to the anthropogenic forcings that occurred after the year 1960 (Acharya & Sreekesh, 2013;Moorthy et al, 2013).…”

Section: Comparison Of Cmip5 and Cmip6 Tcfmentioning

confidence: 99%

Assessment of CMIP6 Cloud Fraction and Comparison with Satellite Observations

Vignesh

Jiang

Kishore

et al. 2020

Earth and Space Science

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The seasonal and regional variations of cloud fractions are compared across two generations of global climate model ensembles, specifically, the Coupled Model Intercomparison Project‐5 (CMIP5) and CMIP6, through the historical period in terms of skills and multimodel agreement. We find a wider spread of historical cloud fraction changes in the CMIP6 than was simulated by the CMIP5. The global mean cloud fractions of CMIP6 increased by about 4.5% from the CMIP5, which attributed to greater changes in the northern hemisphere than in the southern hemisphere. The CMIP6 cloud fractions in recent years are validated with the CALIPSO_CLOUSAT observations to understand the cloud fraction uncertainties in CMIP6 models. The CMIP6 ensemble mean of cloud fractions compares well with the observations with a mean difference of 0.5% in lower altitudes. The CMIP6 cloud fractions are higher than the observations at higher latitudes in both hemispheres in the upper troposphere, and the biases vary from one model to another. The spatial difference between the ensemble and observations is further revealed over the tropics: where the model displays a 3% higher bias. In addition, we observed a significant trend occuring in the northern hemisphere since the mid‐20th century using calculations of cloud fraction trends based on the robust regression technique. Finally, we reduce the differences between the model and observations by applying a simple regression technique. The results exemplify that the model and modified observations compare well, with the root mean square value decreased by nearly 28%, and the correlation increased significantly.

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Section: Comparison Of Cmip5 and Cmip6 Tcfmentioning

confidence: 99%

Assessment of CMIP6 Cloud Fraction and Comparison with Satellite Observations

Vignesh

Jiang

Kishore

et al. 2020

Earth and Space Science

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“…Following the mid‐1980s, there was an upward trend in observed aerosol optical depth (AOD) in South and East Asia (Acharya & Sreekesh, ; Krishna Moorthy et al, ), while a decreasing aerosol trend is seen over North America and Europe (Mehta et al, ). More recently, anthropogenic sulfur dioxide emissions have started declining drastically over East Asia following emission control measures taken in China (Koukouli et al, ).…”

Section: Introductionmentioning

confidence: 99%

The South Asian Monsoon Response to Remote Aerosols: Global and Regional Mechanisms

et al. 2018

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The South Asian summer monsoon has been suggested to be influenced by atmospheric aerosols, and this influence can be the result of either local or remote emissions. We have used the Hadley Centre Global Environment Model Version 3 (HadGEM3) coupled atmosphere-ocean climate model to investigate for the first time the centennial-scale South Asian precipitation response to emissions of sulfur dioxide (SO 2 ), the dominant anthropogenic precursor of sulfate aerosol, from different midlatitude regions. Despite the localized nature of the regional heating that results from removing SO 2 emissions, all experiments featured a similar large-scale precipitation response over South Asia, driven by ocean-modulated changes in the net cross-equatorial heat transport and an opposing cross-equatorial northward moisture transport. The effects are linearly additive, with the sum of the responses from the experiments where SO 2 is removed from the United States, Europe, and East Asia resembling the response seen in the experiment where emissions are removed from the northern midlatitudes as a whole, but with East Asia being the largest contributor, even per unit of emission or top-of-atmosphere radiative forcing. This stems from the fact that East Asian emissions can more easily influence regional land-sea thermal contrasts and sea level pressure differences that drive the monsoon circulation, compared to emissions from more remote regions. Our results suggest that radiative effects of remote pollution should not be neglected when examining changes in South Asian climate and that and it is important to examine such effects in coupled ocean-atmosphere modeling frameworks.Plain Language Summary Atmospheric aerosols have been shown to exert a strong influence on global and regional climate through their radiative effects. The South Asian summer monsoon, a climate phenomenon on which billions of lives depend, has been suggested to be influenced by aerosols, and this influence can be the result of either local or remote emissions. We have used a global climate model to investigate how sensitive is the monsoon to emissions from remote industrialized regions such as Europe, the North America, and East Asia. Despite the localized nature of the regional heating that results from removing emissions in these regions, all of them featured a similar large-scale rainfall change remotely over South Asia. This similarity reflects a common underlying mechanism, which involves a displacement of the tropical rain belt driven by aerosol effects on the temperature contrast between the two hemispheres of the Earth. We find that the effects of the different regions on South Asia are linearly additive, with East Asia being the largest contributor. This stems from the fact that its emissions can more easily influence regional land-sea thermal contrasts and sea level pressure differences over Asia that drive the summer monsoon circulation, compared to emissions from more remote regions. Our results suggest that influences of remote pollution should not be ...

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“…Based on MODIS aerosol data, it is of great value to analyze the transport and distribution of aerosol, and the spatial and temporal patterns in aerosol loadings are revealed at the regional scale [15,16]. Acharya and Sreekesh [17] used the MODIS_L2 dataset to analyze the dynamic changes of seasonal AOD in India from 2001 to 2009. Luo et al [18] analyzed the characteristics of the optical thickness of remote-sensing aerosol on the Chinese mainland during the first decade of the 21st century and found that the average AOD spatial distribution center in China typically exhibits two low peaks and two high peaks.…”

Section: Introductionmentioning

confidence: 99%

Long-Term Analysis of Aerosol Optical Depth over the Huaihai Economic Region (HER): Possible Causes and Implications

et al. 2018

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The quality of air is increasingly affecting regional climate and human activity. Collection 6 aerosol products retrieved from the Moderate-Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite were validated based on CE-318 sun photometric data to analyze their applicability in the Huaihai economic region (HER) at the Xuzhou and Shouxian sites. The spatio-temporal variations of aerosol optical depth (AOD) were also analyzed over HER from 2000 to 2016, with analyses of the correlation with potential driving factors, including meteorology, vegetation and human factors. HER is an economic cooperation organization with multiple industrial structures, containing coal resource-based cities, a national transportation hub and agricultural and high-altitude areas, which shows regional differences in AOD. The results suggest that MODIS Terra AOD products show good agreement with ground observations, with correlation coefficients of above 0.84 in HER, and the main pollutants for high AOD values are fine particles (the mean Ångström exponent was 1.16). The average annual change in AOD varied with a weak growth trend over the past 17 years, while a transition in 2012 made the tendency change from upward to downward due to the extensive cooperation of cities in the joint prevention and control of the deterioration of the ecological environment. The largest monthly mean AOD value appeared in June, which resulted from significant agricultural residue burning. The spatial distribution of multi-year average AOD occurred with a banded high-value center, extending from the northwest to the southeast. The high aerosol loadings were located in resource-based cities, and industrially developed and southeastern coastal areas, whereas the regions with relatively low AOD in HER were distributed in the southern agricultural and northern high-altitude areas. The AOD value in the western, northern, and eastern coastal areas of HER showed a significant increasing trend, while no area exhibited a decreasing trend. The average wind speed has the largest negative correlation with the AOD value in terms of the natural driving factors, and GDP (gross domestic product) was more positively correlated with AOD with respect to the human factors, in comparison with population density.

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Seasonal variability in aerosol optical depth over India: a spatio-temporal analysis using the MODIS aerosol product

Cited by 45 publications

References 22 publications

Assessment of CMIP6 Cloud Fraction and Comparison with Satellite Observations

Assessment of CMIP6 Cloud Fraction and Comparison with Satellite Observations

The South Asian Monsoon Response to Remote Aerosols: Global and Regional Mechanisms

Long-Term Analysis of Aerosol Optical Depth over the Huaihai Economic Region (HER): Possible Causes and Implications

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