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Preprints
https://doi.org/10.5194/acp-2020-454
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-454
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 25 May 2020

Submitted as: research article | 25 May 2020

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This preprint is currently under review for the journal ACP.

Assessment of Regional Aerosol Radiative Effects under SWAAMI Campaign – PART 2: Clear-sky Direct Shortwave Radiative Forcing using Multi-year Assimilated Data

Harshavardhana Sunil Pathak1, Sreedharan Krishnakumari Satheesh1,2, Krishnaswamy Krishna Moorthy1, and Ravi Shankar Nanjundiah1,2,3 Harshavardhana Sunil Pathak et al.
  • 1Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bangalore, India
  • 2DST – Centre of Excellence in Climate Change, Divecha Centre for Climate Change, Indian Institute of Science, Bangalore, Bengaluru 560012, India
  • 3Indian Institute of Tropical Meteorology, Pune 411008

Abstract. Clear-sky, direct shortwave Aerosol Radiative Forcing (ARF) has been estimated over the Indian region, for the first time employing multi-year (2009–2013) gridded, assimilated aerosol products. The aerosol datasets have been constructed following statistical assimilation of concurrent data from a dense network of ground-based observatories, and multi-satellite products, as described in Part-1 of this two-part paper. The ARF, thus estimated, are assessed for their superiority or otherwise over other ARF estimates based on satellite-retrieved aerosol products, over the Indian region, by comparing the radiative fluxes (upward) at Top of Atmosphere (TOA) estimated using assimilated products with spatio-temporally matched radiative flux values provided by CERES (Clouds and Earth's Radiant Energy System) Single Scan Footprint (SSF) product. This clearly demonstrated improved accuracy of the forcing estimates using the assimilated vis-a-vis satellite-based aerosol datasets; at regional, sub-regional and seasonal scales. The regional distribution of diurnally averaged ARF estimates has revealed (a) significant differences from similar estimates made using currently available satellite data, not only in terms of magnitude but also sign of TOA forcing; (b) largest magnitudes of surface cooling and atmospheric warming over IGP and arid regions from north-western India; and (c) negative TOA forcing over most parts of the Indian region, except for three sub-regions – the Indo-Gangetic plains (IGP), north-western India and eastern parts of peninsular India where the TOA forcing changes to positive during pre-monsoon season. Aerosol induced atmospheric warming rates, estimated using the assimilated data, demonstrate substantial spatial heterogeneities (~ 0.2 to 2.0 K day−1) over the study domain with the IGP demonstrating relatively stronger atmospheric heating rates (~ 0.6 to 2.0 K day−1). There exists a strong seasonality as well; with atmospheric warming being highest during pre-monsoon and lowest during winter seasons. It is to be noted that the present ARF estimates demonstrate substantially smaller uncertainties than their satellite counterparts, which is a natural consequence of reduced uncertainties in assimilated vis-a-vis satellite aerosol properties. The results demonstrate the potential application of the assimilated datasets and ARF estimates for improving accuracies of climate impact assessments at regional and sub-regional scales.

Harshavardhana Sunil Pathak et al.

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Harshavardhana Sunil Pathak et al.

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Short summary
We have estimated the atmospheric warming caused by aerosols by employing the assimilated, gridded aerosol datasets over the Indian region. The present atmospheric warming estimates are more accurate and certain than those estimated using currently available, latest satellite retrieved aeorosol products. Therefore, the present atmospheric warming estimates and corresponding assimilated aerosol products emerge as potential candidates for improving the aerosol climate impact assessment.
We have estimated the atmospheric warming caused by aerosols by employing the assimilated,...
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