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Remote sensing and modelling of snow processes

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This thesis aims to improve snow processes simulations by land surface models (LSM). The LSM simulated snow processes define energy and water fluxes over the snow covered land surface for the numerical weather prediction models. Therefore, the improvements in snow processes simulation are expected to impact positively the weather and stream flow forecasts. The research described in this thesis contribute to the improvement of LSM simulations by investigating i)madvanced methods of model initialization (e.g assimilation of satellite observation), and ii)modification to the model parameterization.
The thesis quantifies the performance of the existing approaches for 10 retrevial from satellite based observations and ii) simulations by LSM of snow properties. The retrieval approaches of snow albedo and fractional snow coverage (FSC) and simulation approache (also called parameterization) for snow albedro are found in good agreement with the in situ measurements. Howeve, uncertainties in terms of biasnand variance exist because the approaches are based on different assumptions and approximation. These uncertainties adversely effect the simulation with or without assimilation of satellite observed snow albedo of snowproperties (depth, albedo, coverage, and duration) and ennergy and water fluxes (runoff, melt rate, evapotranpiration,upward shortwave radiations

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

DS 621.3678 MUH r

Penerbit

Netherland : Universiy of Twete-ITC., 2014

Deskripsi Fisik

xii,133 hlm, illus , 23 cm

Bahasa

Inggris

ISBN/ISSN

978-90-365-3751-3

Klasifikasi

621.3678

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

Penginderaan Jauh

Info Detail Spesifik

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Pernyataan Tanggungjawab

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Versi lain/terkait

Lampiran Berkas

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