Determination of Snow Emission on Lake Ice from Airborne Passive Microwave Measurements
ABSTRACT The study focuses on the microwave emission properties of snow-covered lake ice. Lakes typically differ from their surrounding terrain regarding snowpack structure, and thus microwave emission. Ice and water layers beneath the snow also influence the result when compared to frozen ground, decreasing brightness temperatures especially on low frequencies. Estimates of snowpack properties from low-resolution microwave data, such as snow depth or snow water equivalent, are susceptible to these effects. In order to correct for the resulting underestimation, the lake fraction over the area of study as well as the emission properties of those lakes should be known. This could potentially be achieved through the assimilation of modeled estimates of snow-covered lake emissions to satellite data. In this study, a modified HUT snow emission model, including modeled influence from the ice and water layers, is applied to model emission over several lakes in Finland during two winter periods. Input parameters to the model are derived from a large quantity of available ground data. Airborne radiometer data are applied to investigate the quality of the emission estimates. Finally, emissions over several AMSR-E pixels are modeled using fractional lake coverage and available ground data.
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ABSTRACT: The Tibetan Plateau is the highest plateau. And snow in covered at Tibetan Plateau can exert have important influence on the study of climate change and hydrological cycle. In this paper, we found that the brightness temperature of horizontal polarization at Nam Cu Lake is very low, which is about 170K at 18.7 GHz, by the analysis of the time series of the brightness temperature observed by AMSR-E. Even if the lake got frozen, the brightness temperature of horizontal polarization of ice is about 220K at 18.7 GHz, which is much lower than that at land. Then we use HUT (Helsinki University of Technology) snow emission model for a homogeneous snowpack - ice - water system to simulate the brightness temperature at AMSR-E’s frequencies which are used in the current algorithms of estimation SWE at the satellite scale. Also from the seasonal variation of the time series of the brightness temperature, we could see that the brightness temperature of lakes increased sharply when being frozen and decreased rapidly when being melting. The HUT model can match well with the observed brightness temperature at 18.7GHz at horizontal channel . Index Terms—passive microwave remote sensing, lake, snow water equivalence (SWE), Tibetan Plateau2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011, Vancouver, BC, Canada, July 24-29, 2011; 01/2011
Conference Paper: Microwave emission signature of snow-covered lake ice.[Show abstract] [Hide abstract]
ABSTRACT: Airborne microwave radiometer measurements of lake ice have been performed in 2004, 2007, and 2011 in southern Finland. The HUTRAD radiometer system provided data in the 6.9 to 36.5 GHz range using an incidence angle of 50 degrees off nadir. In 2011 also the interferometric HUT-2D radiometer was used to provide 1.4 GHz imagery of lake ice. Index Terms—Microwave radiometry, HUTRAD2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011, Vancouver, BC, Canada, July 24-29, 2011; 01/2011
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ABSTRACT: In this work we chose the Helsinki University of Technology (HUT) snow emission model to character the emission behavior for a snowpack-ice-water system with the ground microwave radiometer observation. This snow and lake ice surveys was conducted in Songhua River, Songyuan city, Jilin Province, on Jan. 21- 22, 2010. Compared to the ground measurements over shallow snow-covered lake ice surface, the simulated brightness temperature at horizontal polarization was better than that at vertical polarizations. The R2 of the HUT simulation and measured value was 0.9304 at H-pol, and 0.9194 at V-pol, respectively. Further, we investigated the impact of lake on snow retrieval using passive microwave remote sensing using these ground-based observations. The snow depth in our ground snow survey was almost 5~8cm, ,the brightness temperature difference at the frequencies of 18.7 GHz and 36.5 GHz at V-pol and H-pol was up to -21.4K, -31.9K, respectively. These negative brightness temperature difference (18.7 GHz-36.5 GHz) over lakes caused errors in current SWE retrieval algorithms. Finally, we took sensitivity analysis of ice thickness and snow depth using HUT model on the show that the current brightness temperature difference snow retrieval algorithm was very sensitive to ice thickness, especially in the case of thinner ice. It needed us to make more study in the lake-rich area to improve the snow estimation accuracy.01/2010;