Cloud model evaluation using radiometric measurements from the airborne multiangle imaging spectroradiometer (AirMISR)
- 作者：Mikhail Ovtchinnikov ; Roger T. March
- 关键词：3D radiative transfer ; AirMISR ; Retrieval algorithms
- 刊名：Remote Sensing of Environment
- 出版年：2007
- 期刊代码：79_00344257
- 类别：ear
- 出版时间：15 March 2007
- 卷：107
- 期：1-2
- 页码：185-193
- 文件大小：2565 K
摘要
Detailed information on cloud properties is needed to rigorously test retrieval algorithms for satellite and ground-based remote sensors. The inherent complexity of clouds makes this information difficult to obtain from observations alone and cloud resolving models (CRMs) are often used to generate synthetic datasets that can be used as proxies for real data. We test the ability of a CRM to reproduce the observed structure of low-level clouds detected by the Earth Observing System (EOS) validation program in north central Oklahoma on March 3, 2000. A three-dimensional radiative transfer model is applied to high-resolution cloud fields generated by the CRM in order to simulate the top of atmosphere radiances. These synthetic radiances are then statistically compared with observations from the airborne Multiangle Imaging SpectroRadiometer (AirMISR), flown on the NASA ER-2 high-altitude aircraft. Simulations match well the blue channel radiance distributions at oblique view angles but overestimate the minimum in reflectance at near-nadir viewing angles. The model reproduces correctly the angular change in the width of radiance distribution, as measured by the standard deviation but the change in skewness of these distributions is captured only qualitatively. The model biases are suggestive of the simulated cloud boundaries being too sharp and the distribution of the vertical liquid water path being too narrow. A power spectrum analysis shows a close agreement between simulations and observations including a break in the scaling properties of the radiance fields around 400 m. The scaling properties of the 1D power spectrum of simulated radiance at smaller scales exhibit directional dependence not seen in corresponding observations.