Toward autonomous surface-based infrared remote sensing of polar clouds: cloud-height retrievals
Toward autonomous surface-based infrared remote sensing of polar clouds: cloud-height retrievals
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DOI：
10.5194/amt-9-3641-2016
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发表时间：
2016-08
影响因子：
3.8
通讯作者：
P. Rowe;C. Cox;V. Walden
中科院分区：
文献类型：
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作者：
P. Rowe;C. Cox;V. Walden
抽象的。极地地区的特点是地处偏远，这使得测量具有挑战性，但提高对云和辐射的了解对于了解极地气候变化是必要的。红外辐射光谱仪可以在表面连续运行，并且相对于有源传感器具有较低的功率要求。在这里，我们探讨了使用专为偏远极地地区使用的红外光谱仪检索云高的可行性。使用不同仪器分辨率下的混合相极地云的各种模拟光谱，使用 CO2 切片/分类和最小局部发射率方差 (MLEV) 方法探索反演精度。在没有强加误差的情况下，对于光学深度大于 ∼ 0.3 的云，使用 CO2 切片/分选和 MLEV 从模拟光谱中检索云高具有大致相当的高精度：在仪器分辨率为 0.5 cm−1 时，发现基线低于 2 的云的平均偏差为 ∼ 0.2 km，对于更高的云，平均偏差为 −0.2 km。研究发现，MLEV 的精度会随着分辨率的粗化而降低，总体上比 CO2 切片/分类更差；然而，这两种方法对不同的误差源具有不同的敏感性，因此建议采用将它们结合起来的方法。对于大气状态下的预期误差以及 0.2 mW/(m2 sr cm−1) 的仪器噪声和偏差，在分辨率为 4 cm−1 时，发现距离地表 1 公里以内的云底平均反演误差小于 ∼ 0.5 km，在 4 km 处增加到 ∼ 1.5 km。这种灵敏度表明，便携式地基红外辐射光谱仪可以为偏远地区的卫星测量提供重要的补充，而卫星测量对低层云的反演具有挑战性。
Abstract. Polar regions are characterized by their remoteness, making measurements challenging, but an improved knowledge of clouds and radiation is necessary to understand polar climate change. Infrared radiance spectrometers can operate continuously from the surface and have low power requirements relative to active sensors. Here we explore the feasibility of retrieving cloud height with an infrared spectrometer that would be designed for use in remote polar locations. Using a wide variety of simulated spectra of mixed-phase polar clouds at varying instrument resolutions, retrieval accuracy is explored using the CO2 slicing/sorting and the minimum local emissivity variance (MLEV) methods. In the absence of imposed errors and for clouds with optical depths greater than ∼ 0.3, cloud-height retrievals from simulated spectra using CO2 slicing/sorting and MLEV are found to have roughly equivalent high accuracies: at an instrument resolution of 0.5 cm−1, mean biases are found to be ∼ 0.2 km for clouds with bases below 2 and −0.2 km for higher clouds. Accuracy is found to decrease with coarsening resolution and become worse overall for MLEV than for CO2 slicing/sorting; however, the two methods have differing sensitivity to different sources of error, suggesting an approach that combines them. For expected errors in the atmospheric state as well as both instrument noise and bias of 0.2 mW/(m2 sr cm−1), at a resolution of 4 cm−1, average retrieval errors are found to be less than ∼ 0.5 km for cloud bases within 1 km of the surface, increasing to ∼ 1.5 km at 4 km. This sensitivity indicates that a portable, surface-based infrared radiance spectrometer could provide an important complement in remote locations to satellite-based measurements, for which retrievals of low-level cloud are challenging.