Assessment of Regional Aerosol Radiative Effects under SWAAMI Campaign – Part 1: Quality-enhanced Estimation of Columnar Aerosol Extinction and Absorption Over the Indian Subcontinent

Abstract

<p><strong>Abstract.</strong> Improving the accuracy of regional aerosol climate impact assessment calls for an improvement in the accuracy of regional aerosol radiative effects (ARE) estimation. One of the most important means of achieving this is to use spatially homogeneous and temporally continuous datasets of critical aerosol properties, such as spectral aerosol optical depth (AOD) and single scattering albedo (SSA), which are the most important parameters for estimating aerosol radiative effects. However, observations do not provide the above; the space-borne observations though provide wide spatial coverage, are temporally snapshots and suffer from possible sensor degradation over extended periods. On the other hand, the ground-based measurements provide more accurate and temporally continuous data, but are spatially near-point observations. Realizing the need for spatially homogeneous and temporally continuous datasets on one hand and the near-non-existence of such data over the south Asian region (which is one of the regions where aerosols show large heterogeneity in most of their properties), construction of accurate gridded aerosol products by synthesizing the long-term space-borne and ground-based data, has been taken up as an important objective of the South West Asian Aerosol Monsoon Interactions (SWAAMI), a joint Indo-UK field campaign, aiming at characterizing aerosol-monsoon links and their variabilities over the Indian region.</p> <p>In the Part-1 of this two-part paper, we present spatially homogeneous gridded datasets of AOD and absorption AOD (AAOD), generated for the first time over this region. These data products are developed by merging the highly accurate aerosol measurements from the dense networks of 44 (for AOD) and 34 (for AAOD) ground-based observatories of Aerosol Radiative Forcing NETwork (ARFINET) and AErosol RObotic NETwork (AERONET) spread across the Indian region, with satellite-retrieved AOD and AAOD, following statistical assimilation schemes. The satellite data used for AOD assimilation includes AODs retrieved from MODerate Imaging Spectroradiometer (MODIS) and Multiangle Imaging SpectroRadiometer (MISR) over the same domain. For AAOD, the ground-based Black Carbon (BC) mass concentration measurements from the network of 34 ARFINET observatories and satellite-based (Kalpana-1, INSAT-3A) infrared (IR) radiance measurements, are blended with gridded AAODs (500 nm, monthly mean) derived from Ozone Monitoring Instrument (OMI)-retrieved AAODs (at 354 nm and 388 nm). The details of the assimilation methods and the gridded datasets generated are presented in this paper. </p> <p>The merged, gridded AOD and AAOD products thus generated, are validated against the data from independent ground-based observatories, which were not used for the assimilation process, but are representative of different subregions of the complex domain. This validation exercise revealed that the independent ground-based measurements are better confirmed by merged datasets than the respective satellite products. As ensured by assimilation techniques employed, the uncertainties in merged AODs and AAODs are significantly less than those in corresponding satellite products. These merged products also exhibit all important, large-scale spatial and temporal features which are already reported for this region. Nonetheless, the merged AODs and AAODs are significantly different in magnitude, from the respective satellite products. On the background of above mentioned quality enhancements demonstrated by merged products, we have employed them for deriving the columnar SSA and analysed its spatio-temporal characteristics. The columnar SSA thus derived has demonstrated distinct seasonal variation, over various representative subregions of the study domain. The uncertainties in the derived SSA are observed to be substantially less than those in OMI SSA. On the backdrop of these benefits, the merged datasets are employed for the estimation of regional aerosol radiative effects (direct), the results of which would be presented in a companion paper; Part-2 of this two-part paper.</p>

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

“…Accordingly, in this work, we have used the gridded data over the Indian domain for AOD and SSA at 1 • × 1 • resolution. These datasets are generated by assimilating long-term data from ground-based network observatories and space-borne sensors following statistical assimilation techniques (3D-VAR and Weighted Interpolation methods) as described in Pathak et al 2019 (the part-1 paper) and are available at http://dccc.iisc.ac.in/aerosoldata/ (Pathak et al, 2019). These assimilated AOD and SSA are henceforth respectively denoted as AS AOD and AS SSA.…”

“…In addition to assimilated aerosol products, we have also employed satellite-retieved AOD and SSA (denoted as SR AOD and SR SSA respectively) for ARF estimation. The satellite-retrieved AODs employed here are constructed by combining by monthly averaged AOD products (1 • × 1 • resolution) from (L3, collection 6, https://modis.gsfc.nasa.gov/data/ ) MODerate Imaging Spectroradiometer (MODIS) onboard AQUA and TERRA satellites as well as from Multiangle Imaging SpectroRadiometer (MISR) onboard TERRA satellite (L3, https://misr.jpl.nasa.gov/ ) (Diner et al, 1998), as detailed in the Part-1 of the two-part paper (Pathak et al, 2019). The satellite-retrieved SSA are provided by monthly mean SSA (at 500 nm) datasets constructed from upwelling radiance measurements (in the range of 270-500 nm) performed by OMI on-board AURA satellite (Torres et al, 2002;Levelt et al, 2006).…”

“…5. Positive TOA forcing and strong atmospheric absorption over IGP results due to the presence of absorbing aerosol species, (mainly carbonaceous aerosols and mineral dust, (Moorthy et al, 2005;Niranjan et al, 2007;Vaishya et al, 2018)), which brings down the SSA and the repsective ground-based measurements reflecting the same are assimilated in the AS data sets (Pathak et al, 2019). The strong and vigorous vertical motions within the convective boundary layers, (when the surface temperatures are above 40 C during large parts of daytime) lift these aerosols to upper levels of atmosphere (Prijith et al, 2016) even above the low-level clouds (Satheesh et al, 2008;Waquet et al, 2013;Peers et al, 2019) thereby further increasing the absorption (Chand et al, 2009).…”

“…Aerosol types and their properties over Indian region are known to exhibit significant seasonal variation, both at regional and sub-regional scales, primarily due to seasonality in the nature of aerosol sources, advection pathways as well as synoptic and meso-scale meteorology (Jethva et al, 2014;Moorthy et al, 2007;Babu et al, 2013;Vaishya et al, 2018;Pathak et al, 2019).…”

“…In part-1 of this two-part paper, we have presented, the gridded, assimilated datasets of AOD and SSA (Single Scattering Albedo) over India, which provide spatio-temporally continuous data, generated for the first time by harmonizing long-term (2009-2013) measurements from a dense network of ground-based aerosol observatories and multi-satellite datasets following statistical assimilation techniques (Pathak et al, 2019). The resulting improvement in accuracies of the gridded products (over the parent data) in reproducing the spatio-temporal characteristics of aerosol properties at sub-regional scales over the Indian domain was also demonstrated.…”