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Impacts of cloud heterogeneities on cirrus optical properties retrieved from space-based thermal infrared radiometry

机译:云异质性对从天基热红外辐射学获得的卷云光学特性的影响

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This paper presents a study, based on simulations, of the impact of cirrus cloud heterogeneities on the retrieval of cloud parameters (optical thickness and effective diameter) for the Imaging Infrared Radiometer (IIR) on board CALIPSO. Cirrus clouds are generated by the stochastic model 3DCLOUD for two different cloud fields and for several averaged cloud parameters. One cloud field is obtained from a cirrus observed on 25 May 2007 during the airborne campaign CIRCLE-2 and the other is a cirrus uncinus. The radiative transfer is simulated with the 3DMCPOL code. To assess the errors due to cloud heterogeneities, two related retrieval algorithms are used: (i) the split-window technique to retrieve the ice crystal effective diameter and (ii) an algorithm similar to the IIR operational algorithm to retrieve the effective emissivity and the effective optical thickness. Differences between input parameters and retrieved parameters are compared as a function of different cloud properties such as the mean optical thickness, the heterogeneity parameter and the effective diameter. The optical thickness heterogeneity for each 1 km × 1 km observation pixel is represented by the optical thickness standard deviation computed using 100 m × 100 m subpixels. We show that optical thickness heterogeneity may have a strong impact on the retrieved parameters, mainly due to the plane-parallel approximation (PPA assumption). In particular, for cirrus clouds with ice crystal diameter of approximately 10 μm, the averaged error on the retrieved effective diameter and optical thickness is about 2.5 μm (~ 25%) and ?0.20 (~ 12%), respectively. Then, these biases decrease with increasing effective size due to a decrease of the cloud absorption and, thus, the PPA bias. Cloud horizontal heterogeneity effects are greater than other possible sources of retrieval errors such as those due to cloud vertical heterogeneity impact, surface temperature or atmospheric temperature profile uncertainty and IIR retrieval uncertainty. Cloud horizontal heterogeneity effects are larger than the IIR retrieval uncertainty if the standard deviation of the optical thickness, inside the observation pixel, is greater than 1.
机译:本文基于模拟,对CALIPSO板载成像红外辐射仪(IIR)的卷云异质性对云参数(光学厚度和有效直径)的检索的影响进行了研究。卷云是由随机模型3DCLOUD为两个不同的云字段和几个平均云参数生成的。一个云场是从2007年5月25日的CIRCLE-2空降战役中观测到的一个卷云获得的,另一个是未分类的卷云。辐射传递使用3DMCPOL代码进行模拟。为了评估由于云的非均质性引起的误差,使用了两种相关的检索算法:(i)分割窗口技术以检索冰晶有效直径,以及(ii)与IIR运算算法相似的算法以检索有效发射率和有效光学厚度。根据不同云特性(例如平均光学厚度,非均质性参数和有效直径)对输入参数和检索到的参数之间的差异进行比较。每个1 km×1 km观察像素的光学厚度异质性由使用100 m×100 m子像素计算出的光学厚度标准偏差表示。我们表明,光学厚度异质性可能对检索到的参数有很大的影响,这主要是由于平面平行近似(PPA假设)所致。特别是,对于冰晶直径约为10μm的卷云,所获得的有效直径和光学厚度的平均误差分别约为2.5μm(〜25%)和≤0.20(〜12%)。然后,由于云吸收减少,因此PPA偏差减小,这些偏差随着有效尺寸的增加而减小。云水平异质性影响大于其他可能的取回误差源,例如由于云垂直异质性影响,地表温度或大气温度剖面不确定性和IIR取回不确定性引起的误差。如果观察像素内部的光学厚度的标准偏差大于1,则云水平异质性影响大于IIR检索不确定性。

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