On Improvement of Snow Water Equivalence Estimation for Passive Microwave Instrument—AMSR/E

JIANG Ling-mei1; SHI Jian-cheng1; ZHANG Li-xin1

doi:10.11834/jrs.20070593

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On Improvement of Snow Water Equivalence Estimation for Passive Microwave Instrument—AMSR/E
Issue 5, Pages: 677-685(2007)
Published：2007
DOI： 10.11834/jrs.20070593
稿件说明：

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[1]蒋玲梅,施建成,张立新.改进AMSR-E雪水当量算法研究(英文)[J].遥感学报,2007(05):677-685. DOI： 10.11834/jrs.20070593.

JIANG Ling-mei1, SHI Jian-cheng1, ZHANG Li-xin1. On Improvement of Snow Water Equivalence Estimation for Passive Microwave Instrument—AMSR/E[J]. Journal of Remote Sensing, 2007, (5): 677-685. DOI： 10.11834/jrs.20070593.

摘要

为了发展雪水当量物理反演算法

本文对不同散射阶模型——零阶、一阶、多次散射模型进行敏感性试验与分析

结果表明我们必须在前向理论模型和反演模型中考虑多次散射作用。本文采用的多次散射积雪辐射理论模型——双矩阵法（Matrix Doubling）求解辐射传输方程

用致密介质理论模型（DMRT）模拟积雪发射和消光特性

用AIEM模型模拟地表辐射及作为辐射传输方程的边界条件。由于该多次散射积雪辐射理论模型的复杂性

拟发展出简单且高精度的积雪辐射参数化模型

以发展雪水当量物理反演算法。因此

在包括多次散射的积雪理论模型基础上

本文通过建立针对AMSR-E传感器参数设置的积雪辐射模拟数据库

该数据库包含了各种可能的自然积雪和地表特性参数。从而在模拟数据库基础上

本文发展了针对AMSR-E的积雪参数化模型。

Abstract

In this paper

we evaluate the capability of a multi-scattering microwave emission model that includes the Dense Media Radiative Transfer Model（DMRT） and Advanced Integral Equation Model（AIEM） to simulate dry snow emission with the Matrix Doubling approach.We compared the predictions of this model with ground experimental measurements.The comparison showed that our snow microwave emission model agreed well with the experimental measurements.In order to develop retrieval snow properties:snow depth or snow water equivalence（SWE） retrieval algorithm

we carried out the sensitivity test between the emission models with the different scattering-order:the zeroth-order

the first-order and the multi-scattering models.The results indicated that the multi-scattering effects have to be taken into account in the snow emission model

especially for large grain size.Due to the complexity of the multi-scattering model

we developed a parameterized inversion model using our multi-scattering emission model with a wide range of snow and under-ground properties for algorithm development purpose.