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The characterization of deep con vective cloud albedo as a calibrationtarget using MODIS reflectances

机译:利用MODIS反射率表征深对流云反照率作为标定目标

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There are over 25 years of historical satellite data available for climate analysis. The historical satellite data needs to be properly calibrated, especially in the visible, for sensors with no onboard calibration. Accurate vicarious calibration of historical satellites relies on invariant targets, such as the moon, Dome C, and deserts. Deep convective clouds (DCC) also show promise of being a stable or predictable target viewable by all satellites, since they behave as solar diffusers. However DCC have not been well characterized for calibration. Ten years of well-calibrated MODIS radiances are now available. DCC can easily be identified using IR thresholds, where the IR calibration can be traced to the onboard blackbodies. The natural variability of the DCC radiance will be analyzed geographically, seasonally, and for differences of convection initiated over land and ocean. Functionality between particle size and ozone absorption with DCC albedo will be examined theoretically. Although DCC clouds are nearly Lambertian, the angular distribution of reflectances will be sampled and compared with theoretical models. Both Aqua and Terra MODIS DCC angular models were compared for consistency. The DCC method was able to identify two calibration coefficient discontinuities in the Terra-MODIS Collection 5 10-year record and validated the calibration stability of MODIS to within 0.1% per decade. The DCC method needs to take into account the functionality of the 0.65um DCC radiance with the Hum brightness temperature threshold and the DCC 0.65um radiance difference observed over the tropical western pacific and the afternoon generated DCC over land. Both of these cases cause a bias on the order of 5%. These improvements are the first steps towards successful use of DCC as an absolute calibration target.
机译:有超过25年的历史卫星数据可用于气候分析。对于没有机载校准的传感器,需要对历史卫星数据进行正确校准,尤其是在可见光范围内。对历史卫星的精确替代校准取决于不变的目标,例如月球,C型圆顶和沙漠。深对流云(DCC)还显示出有望成为所有卫星都能看到的稳定或可预测目标的目标,因为它们的作用类似于太阳扩散器。但是,DCC尚未很好地进行校准。经过十年校准的MODIS辐射度现已可用。可以使用IR阈值轻松识别DCC,其中IR校准可以追溯到板载黑体。 DCC辐射的自然变异性将在地理,季节和陆地和海洋上对流差异方面进行分析。理论上将研究DCC反照率在粒径和臭氧吸收之间的功能。尽管DCC云接近于朗伯型,但反射率的角度分布将被采样并与理论模型进行比较。比较了Aqua和Terra MODIS DCC角度模型的一致性。 DCC方法能够识别Terra-MODIS Collection 5 10年记录中的两个校准系数不连续性,并将MODIS的校准稳定性验证为每十年0.1%以内。 DCC方法需要考虑到0.65um DCC辐射度与Hum亮度温度阈值的功能以及在热带西太平洋地区和午后在陆地上产生的DCC所观测到的DCC 0.65um辐射度差异的功能。这两种情况都会导致5%左右的偏差。这些改进是成功将DCC用作绝对校准目标的第一步。

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