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

机译:植被表面光谱反照率对短波辐射通量和气溶胶直接辐射强迫的影响

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摘要

This study develops an algorithm for representing detailed spectral features of vegetation albedo based on Moderate Resolution Imaging Spectrometer (MODIS) observations at 7 discrete channels, referred to as the MODIS Enhanced Vegetation Albedo (MEVA) algorithm. The MEVA algorithm empirically fills spectral gaps around the vegetation red edge near 0.7 μm and vegetation water absorption features at 1.48 and 1.92 μm which cannot be adequately captured by the MODIS 7 channels. We then assess the effects of applying MEVA in comparison to four other traditional approaches to calculate solar fluxes and aerosol direct radiative forcing (DRF) at the top of atmosphere (TOA) based on the MODIS discrete reflectance bands. By comparing the DRF results obtained through the MEVA method with the results obtained through the other four traditional approaches, we show that filling the spectral gap of the MODIS measurements around 0.7 μm based on the general spectral behavior of healthy green vegetation leads to significant improvement in the instantaneous aerosol DRF at TOA (up to 3.02 W m~(-2) difference 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 μm for deciduous vegetation surface). The corrections of the spectral gaps in the vegetation spectrum in the near infrared, again missed by the MODIS reflectances, also contributes to improving TOA DRF calculations but to a much lower extent (less than 0.27 W m~(-2), or about 4 % of the instantaneous DRF). Compared to traditional approaches, MEVA also improves the accuracy of the outgoing 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 of daily averaged aerosol radiative forcing in the spectral range of 0.3 to 2.5 μm at equator at the equinox by 3.7 W m~(-2). These improvements indicate that MEVA can contribute to regional climate studies over vegetated areas and can help to improve remote sensing-based studies of climate processes and climate change.
机译:本研究基于中等分辨率成像光谱仪(MODIS)在7个离散通道上的观测结果,开发了一种表示植被反照率详细光谱特征的算法,称为MODIS增强植被反照率(MEVA)算法。 MEVA算法凭经验填充0.7μm附近的植被红色边缘周围的光谱间隙,以及1.48和1.92μm处的植被吸水特征,这不能被MODIS 7通道充分捕获。然后,我们根据MODIS离散反射带,将MEVA与其他四种传统方法进行比较,以评估太阳通量和大气层顶部(TOA)的气溶胶直接辐射强迫(DRF)的效果。通过将通过MEVA方法获得的DRF结果与通过其他四种传统方法获得的结果进行比较,我们发现,基于健康绿色植被的总体光谱行为,填补MODIS测量值的光谱间隙在0.7μm左右可显着改善TOA的瞬时气溶胶DRF(相差高达3.02 W m〜(-2)或气溶胶DRF的48%分数-6.28 W m〜(-2),针对0.3至2.5μm的高光谱分辨率表面反射率计算得出落叶植被表面)。再次被MODIS反射所遗漏的近红外植被光谱中光谱间隙的校正,也有助于改善TOA DRF计算,但幅度要小得多(小于0.27 W m〜(-2),或大约4瞬时DRF的百分比)。与传统方法相比,MEVA还可以在TOA处将出射太阳光通量的精度提高60 W m〜(-2)(对于白杨3表面)在TOA处在0.3至2.5μm之间,将气溶胶DRF的精度提高10 W m〜(-2以上)。 )(用于干草)。具体来说,对于亚马逊植被类型,MEVA可以在赤道处在赤道处在0.3至2.5μm的光谱范围内将日平均气溶胶辐射强迫的精度提高3.7 W m〜(-2)。这些改进表明,MEVA可以为植被区的区域气候研究做出贡献,并有助于改善基于遥感的气候过程和气候变化研究。

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