Study of snow water equivalence inversion technique with simulating model

Lingmei Jiang; Jiancheng Shi; Saibun Tjuatja; Kun Shan Chen

doi:10.1117/12.578318

22 December 2004 Study of snow water equivalence inversion technique with simulating model

Lingmei Jiang, Jiancheng Shi, Saibun Tjuatja, Kun Shan Chen

Proceedings Volume 5654, Microwave Remote Sensing of the Atmosphere and Environment IV; (2004) https://doi.org/10.1117/12.578318
Event: Fourth International Asia-Pacific Environmental Remote Sensing Symposium 2004: Remote Sensing of the Atmosphere, Ocean, Environment, and Space, 2004, Honolulu, Hawai'i, United States

Abstract

In this paper, we evaluate the capability of a multi-scattering microwave emission model that including the Dense Media Radiative Transfer Model (DMRT) and AIEM to simulation of dry snow emission with Matrix Doubling approach. We compared the predictions of this model with the 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.

Citation Download Citation

Lingmei Jiang, Jiancheng Shi, Saibun Tjuatja, and Kun Shan Chen "Study of snow water equivalence inversion technique with simulating model", Proc. SPIE 5654, Microwave Remote Sensing of the Atmosphere and Environment IV, (22 December 2004); https://doi.org/10.1117/12.578318

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available