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首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >Surface reflectivity from the Ozone Monitoring Instrument using the Moderate Resolution Imaging Spectroradiometer to eliminate clouds: Effects of snow on ultraviolet and visible trace gas retrievals
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Surface reflectivity from the Ozone Monitoring Instrument using the Moderate Resolution Imaging Spectroradiometer to eliminate clouds: Effects of snow on ultraviolet and visible trace gas retrievals

机译:臭氧监测仪使用中等分辨率成像光谱仪消除云的表面反射率:雪对紫外线和可见痕量气体回收的影响

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Satellite retrievals of tropospheric composition from measurements of solar backscatter require accurate information about surface reflectivity. We use clear-sky data from the Ozone Monitoring Instrument (OMI) to determine global surface reflectivity under both snow-covered and snow-free conditions at 354 nm. Clear-sky scenes are determined using cloud and aerosol data from the Moderate Resolution Imaging Spectroradiometer/Aqua satellite instrument that flies 12 min ahead of OMI/Aura. The result is a database of OMI-observed Lambertian equivalent reflectivity (LER) that does not rely on statistical methods to eliminate cloud and aerosol contamination. We apply this database to evaluate previous climatologies of surface reflectivity. Except for regions of seasonal snow cover, agreement is best with a climatology from OMI, which selects the surface reflectivity from a histogram of observed LER (mean difference, 0.0002; standard deviation, 0.011). Three other climatologies of surface reflectivity from Total Ozone Mapping Spectrometer, Global Ozone Monitoring Experiment, and OMI, based on minimum observed LER, are less consistent with our cloud- and aerosol-filtered data set (mean difference, -0.008, 0.012, and -0.002; standard deviation, 0.022, 0.026, and 0.033). Snow increases the sensitivity of solar backscatter measurements at ultraviolet and visible wavelengths to trace gases in the lower troposphere. However, all four existing LER climatologies poorly represent seasonal snow. Surface reflectivity over snow-covered lands depends strongly on the vegetation type covering the surface. The monthly variation of snow-covered reflectivity varies by less than 0.1 in fall and winter. Applying our snow-covered surface reflectivity database to OMI NO_2 retrievals could change the retrieved NO_2 column by 20%-50% over large regions with seasonal snow cover.
机译:通过对太阳反向散射的测量来对流层成分进行卫星检索需要有关表面反射率的准确信息。我们使用来自臭氧监测仪器(OMI)的晴空数据确定在354 nm的大雪覆盖和无雪条件下的全球表面反射率。使用来自中等分辨率成像光谱仪/ Aqua卫星仪器的云和气溶胶数据确定晴朗天空的场景,该仪器比OMI / Aura提前12分钟飞行。结果是一个由OMI观测的朗伯等效反射率(LER)的数据库,该数据库不依赖于统计方法来消除云和气溶胶污染。我们将此数据库用于评估以前的表面反射率气候。除季节性积雪的地区外,与OMI的气候条件最吻合,后者从观测到的LER直方图中选择表面反射率(均值,0.0002;标准差,0.011)。根据观测到的最小LER,来自总臭氧测图仪,全球臭氧监测实验和OMI的其他三种表面反射率气候与我们的云和气溶胶过滤数据集不太一致(均值差,-0.008、0.012和- 0.002;标准偏差:0.022、0.026和0.033)。积雪提高了紫外线和可见光波长下太阳反向散射测量对低层对流层中气体的敏感性。但是,现有的四种LER气候都无法很好地代表季节性降雪。在积雪的土地上的表面反射率在很大程度上取决于覆盖该表面的植被类型。秋季和冬季,积雪反射率的每月变化小于0.1。将我们的积雪覆盖的表面反射率数据库应用于OMI NO_2检索,可以在季节性积雪的大区域中将检索到的NO_2列更改20%-50%。

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