The remote sensing of radiative forcing by light-absorbing particles (LAPs) in seasonal snow over northeastern China

Light-absorbing particles (LAPs) deposited on snow can decrease snow albedo and affect climate through snow-albedo radiative forcing. In this study, we use MODIS observations combined with a snow-albedo model (SNICAR – Snow, Ice, and Aerosol Radiative) and a radiative transfer model (SBDART – Santa Barbara DISORT Atmospheric Radiative Transfer) to retrieve the instantaneous spectrally integrated radiative forcing at the surface by LAPs in snow (inline-formula $M1inlinescrollmathml{\mathrm{normal\; RF}}_{\mathrm{normal\; MODIS}}^{\mathrm{normal\; LAPs}}$ 43pt17ptsvg-formulamathimg0ffdcf32e6c12ae1f536438a8d04133c acp-19-9949-2019-ie00001.svg43pt17ptacp-19-9949-2019-ie00001.png ) under clear-sky conditions at the time of MODIS Aqua overpass across northeastern China (NEC) in January–February from 2003 to 2017. inline-formula $M2inlinescrollmathml{\mathrm{normal\; RF}}_{\mathrm{normal\; MODIS}}^{\mathrm{normal\; LAPs}}$ 43pt17ptsvg-formulamathimgec04f9fb00bc29e4c51e76c0ee4d17cb acp-19-9949-2019-ie00002.svg43pt17ptacp-19-9949-2019-ie00002.png presents distinct spatial variability, with the minimum (22.3 W minline-formula⁻²) in western NEC and the maximum (64.6 W minline-formula⁻²) near industrial areas in central NEC. The regional mean inline-formula $M5inlinescrollmathml{\mathrm{normal\; RF}}_{\mathrm{normal\; MODIS}}^{\mathrm{normal\; LAPs}}$ 43pt17ptsvg-formulamathimg5a2b24db0c569e0c3f9a78c7081b764c acp-19-9949-2019-ie00003.svg43pt17ptacp-19-9949-2019-ie00003.png is inline-formula $M6inlinescrollmathml\sim \mathrm{normal\; 45.1}\pm \mathrm{normal\; 6.8}$ 60pt10ptsvg-formulamathimg4b28a528847c453147ed6055557a9edf acp-19-9949-2019-ie00004.svg60pt10ptacp-19-9949-2019-ie00004.png  W minline-formula⁻² in NEC. The positive (negative) uncertainties of retrieved inline-formula $M8inlinescrollmathml{\mathrm{normal\; RF}}_{\mathrm{normal\; MODIS}}^{\mathrm{normal\; LAPs}}$ 43pt17ptsvg-formulamathimg330ae56179f5f0f4b2ab991eeafdce99 acp-19-9949-2019-ie00005.svg43pt17ptacp-19-9949-2019-ie00005.png due to atmospheric correction range from 14 % to 57 % (inline-formula−14 % to inline-formula−47 %), and the uncertainty value basically decreases with the increased inline-formula $M11inlinescrollmathml{\mathrm{normal\; RF}}_{\mathrm{normal\; MODIS}}^{\mathrm{normal\; LAPs}}$ 43pt17ptsvg-formulamathimge8aae5d7d6dc978944870391cc138dec acp-19-9949-2019-ie00006.svg43pt17ptacp-19-9949-2019-ie00006.png . We attribute the variations of radiative forcing based on remote sensing and find that the spatial variance of inline-formula $M12inlinescrollmathml{\mathrm{normal\; RF}}_{\mathrm{normal\; MODIS}}^{\mathrm{normal\; LAPs}}$ 43pt17ptsvg-formulamathimg4d757ce65e7fade4491b604cd8723d3f acp-19-9949-2019-ie00007.svg43pt17ptacp-19-9949-2019-ie00007.png in NEC is 74.6 % due to LAPs and 21.2 % and 4.2 % due to snow grain size and solar zenith angle. Furthermore, based on multiple linear regression, the BC dry and wet deposition and snowfall could explain 84 % of the spatial variance of LAP contents, which confirms the reasonability of the spatial patterns of retrieved inline-formula $M13inlinescrollmathml{\mathrm{normal\; RF}}_{\mathrm{normal\; MODIS}}^{\mathrm{normal\; LAPs}}$ 43pt17ptsvg-formulamathimg27f74a816d615d97c0813d4744e738a1 acp-19-9949-2019-ie00008.svg43pt17ptacp-19-9949-2019-ie00008.png in NEC. We validate inline-formula $M14inlinescrollmathml{\mathrm{normal\; RF}}_{\mathrm{normal\; MODIS}}^{\mathrm{normal\; LAPs}}$ 43pt17ptsvg-formulamathimg08235846b325d7830c039e8f382f52f6 acp-19-9949-2019-ie00009.svg43pt17ptacp-19-9949-2019-ie00009.png using in situ radiative forcing estimates. We find that the biases in inline-formula $M15inlinescrollmathml{\mathrm{normal\; RF}}_{\mathrm{normal\; MODIS}}^{\mathrm{normal\; LAPs}}$ 43pt17ptsvg-formulamathimg2833dc67d2fe3c35cca32c84bc5aa4a2 acp-19-9949-2019-ie00010.svg43pt17ptacp-19-9949-2019-ie00010.png are negatively correlated with LAP concentrations and range from inline-formula∼5 % to inline-formula∼350 % in NEC.