Effect of spectrally varying albedo of vegetation surfaces on shortwave radiation fluxes and aerosol direct radiative forcing

摘要

This study develops an algorithm for representing detailed spectral featuresof vegetation albedo based on Moderate Resolution Imaging Spectrometer(MODIS) observations at 7 discrete channels, referred to as the MODISEnhanced Vegetation Albedo (MEVA) algorithm. The MEVA algorithm empiricallyfills spectral gaps around the vegetation red edge near 0.7 μm andvegetation water absorption features at 1.48 and 1.92 μm which cannotbe adequately captured by the MODIS 7 channels. We then assess the effectsof applying MEVA in comparison to four other traditional approaches tocalculate solar fluxes and aerosol direct radiative forcing (DRF) at the topof atmosphere (TOA) based on the MODIS discrete reflectance bands. Bycomparing the DRF results obtained through the MEVA method with the resultsobtained through the other four traditional approaches, we show that fillingthe spectral gap of the MODIS measurements around 0.7 μm based on thegeneral spectral behavior of healthy green vegetation leads to significantimprovement in the instantaneous aerosol DRF at TOA (up to 3.02 W m?2difference or 48% fraction of the aerosol DRF, ?6.28 W m?2,calculated for high spectral resolution surface reflectance from 0.3 to 2.5 μmfor deciduous vegetation surface). The corrections of the spectralgaps in the vegetation spectrum in the near infrared, again missed by theMODIS reflectances, also contributes to improving TOA DRF calculations butto a much lower extent (less than 0.27 W m?2, or about 4% of theinstantaneous DRF).Compared to traditional approaches, MEVA also improves the accuracy of theoutgoing solar flux between 0.3 to 2.5 μm at TOA by over 60 W m?2(for aspen 3 surface) and aerosol DRF by over 10 W m?2 (for dry grass).Specifically, for Amazon vegetation types, MEVA can improve the accuracy ofdaily averaged aerosol radiative forcing in the spectral range of 0.3 to2.5 μm at equator at the equinox by 3.7 W m?2. These improvementsindicate that MEVA can contribute to regional climate studies over vegetatedareas and can help to improve remote sensing-based studies of climateprocesses and climate change.