کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5754787 | 1621210 | 2017 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Comparison of commonly-used microwave radiative transfer models for snow remote sensing
ترجمه فارسی عنوان
مقایسه مدل های انتقال مایکروویو شعاعی به طور معمول برای سنجش از دور برف
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کلمات کلیدی
مدل انتشار برف مایکروویو، ریز ساختار برف، مدل انتقال تابشی، کانادا، اندازه گیری زمین، دمای روشنایی،
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
کامپیوتر در علوم زمین
چکیده انگلیسی
This paper reviews four commonly-used microwave radiative transfer models that take different electromagnetic approaches to simulate snow brightness temperature (TB): the Dense Media Radiative Transfer - Multi-Layer model (DMRT-ML), the Dense Media Radiative Transfer - Quasi-Crystalline Approximation Mie scattering of Sticky spheres (DMRT-QMS), the Helsinki University of Technology n-Layers model (HUT-nlayers) and the Microwave Emission Model of Layered Snowpacks (MEMLS). Using the same extensively measured physical snowpack properties, we compared the simulated TB at 11, 19 and 37Â GHz from these four models. The analysis focuses on the impact of using different types of measured snow microstructure metrics in the simulations. In addition to density, snow microstructure is defined for each snow layer by grain optical diameter (Do) and stickiness for DMRT-ML and DMRT-QMS, mean grain geometrical maximum extent (Dmax) for HUT n-layers and the exponential correlation length for MEMLS. These metrics were derived from either in-situ measurements of snow specific surface area (SSA) or macrophotos of grain sizes (Dmax), assuming non-sticky spheres for the DMRT models. Simulated TB sensitivity analysis using the same inputs shows relatively consistent TB behavior as a function of Do and density variations for the vertical polarization (maximum deviation of 18Â K and 27Â K, respectively), while some divergences appear in simulated variations for the polarization ratio (PR). Comparisons with ground-based radiometric measurements show that the simulations based on snow SSA measurements have to be scaled with a model-specific factor of Do in order to minimize the root mean square error (RMSE) between measured and simulated TB. Results using in-situ grain size measurements (SSA or Dmax, depending on the model) give a mean TB RMSE (19 and 37Â GHz) of the order of 16-26Â K, which is similar for all models when the snow microstructure metrics are scaled. However, the MEMLS model converges to better results when driven by the correlation length estimated from in-situ SSA measurements rather than Dmax measurements. On a practical level, this paper shows that the SSA parameter, a snow property that is easy to retrieve in-situ, appears to be the most relevant parameter for characterizing snow microstructure, despite the need for a scaling factor.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 190, 1 March 2017, Pages 247-259
Journal: Remote Sensing of Environment - Volume 190, 1 March 2017, Pages 247-259
نویسندگان
Alain Royer, Alexandre Roy, Benoit Montpetit, Olivier Saint-Jean-Rondeau, Ghislain Picard, Ludovic Brucker, Alexandre Langlois,