Observation and Modeling of the Microwave Brightness Temperature of Snow-Covered Frozen Lakes and Wetlands

Kontu, Anna; Lemmetyinen, Juha; Pulliainen, Jouni; Seppänen, Jaakko; Hallikainen, M.

doi:10.1109/tgrs.2013.2272077

Cited by 15 publications

(10 citation statements)

References 37 publications

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“…The Sodankylä manual snow survey program aims to study the spatial and temporal variability of snowpack in varying environmental conditions typical to the boreal forest zone, including pine and spruce forests, open bogs and lake ice (e.g. Hannula et al, 2016;Lemmetyinen et al, 2015;Kontu et al, 2014;Kontu and Pulliainen, 2010). The data set is also important as a reference for the development of remote sensing instruments (Lemmetyinen et al, 2016b) and interpretation algorithms and models (Leinss et al, 2015;Schwank et al, 2014;Rautiainen et al, 2014).…”

Section: Leppänen Et Al: Sodankylä Manual Snow Survey Programmentioning

confidence: 99%

“…Cheng et al (2014) applied lake ice measurements to validate buoy-based measurements of lake snow and ice thicknesses. Moreover, snow pit and lake ice measurements were applied by Kontu et al (2014) to study the effect of snow and ice-covered lakes and wetlands to microwave brightness temperature simulation accuracy. In addition, Kontu and Pulliainen (2010) used the snow pit measurements to simulate a time series of brightness temperatures and compared the results to spaceborne microwave radiometer measurements.…”

Section: Leppänen Et Al: Sodankylä Manual Snow Survey Programmentioning

confidence: 99%

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Sodankylä manual snow survey program

Leppänen

Kontu

Hannula

et al. 2016

Geosci. Instrum. Method. Data Syst.

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Abstract. The manual snow survey program of the Arctic Research Centre of the Finnish Meteorological Institute (FMI-ARC) consists of numerous observations of natural seasonal taiga snowpack in Sodankylä, northern Finland. The easily accessible measurement areas represent the typical forest and soil types in the boreal forest zone. Systematic snow measurements began in 1909 with snow depth (HS) and snow water equivalent (SWE). In 2006 the manual snow survey program expanded to cover snow macro-and microstructure from regular snow pits at several sites using both traditional and novel measurement techniques. Present-day snow pit measurements include observations of HS, SWE, temperature, density, stratigraphy, grain size, specific surface area (SSA) and liquid water content (LWC). Regular snow pit measurements are performed weekly during the snow season. Extensive time series of manual snow measurements are important for the monitoring of temporal and spatial changes in seasonal snowpack. This snow survey program is an excellent base for the future research of snow properties.

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Section: Leppänen Et Al: Sodankylä Manual Snow Survey Programmentioning

confidence: 99%

Section: Leppänen Et Al: Sodankylä Manual Snow Survey Programmentioning

confidence: 99%

Sodankylä manual snow survey program

Leppänen

Kontu

Hannula

et al. 2016

Geosci. Instrum. Method. Data Syst.

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“…At −20 • C, snow is dry and lake ice contains minimal quantity of liquid water at its bottom in contact with lake water with temperature close to 0 • C. At 0 • C, intensive melt process sets on. In this case, the maximum volumetric wetness of snow cover (volume of water contained in unit volume of snow) is determined by its density and structure and ranges 9 %-30 %, but mostly 12 %-15 % (Kuz'min, 1957;Kotlyakov, 2000). Excess snow water trickles down to ice surface, and then leaks into cracks in ice increasing its wetness.…”

Section: Model Modificationmentioning

confidence: 99%

Theoretical study of ice cover phenology at large freshwater lakes based on SMOS MIRAS data

et al. 2018

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Abstract. The paper presents a theoretical analysis of seasonal brightness temperature variations at a number of large freshwater lakes: Baikal, Ladoga, Great Bear Lake (GBL), Great Slave Lake (GSL), and Huron, retrieved from Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) data (1.4 GHz) of the Soil Moisture and Ocean Salinity (SMOS) satellite. The analysis was performed using the model of microwave radiation of plane layered heterogeneous nonisothermal medium. The input parameters for the model were real regional climatological characteristics and glaciological parameters of ice cover of the study lakes. Three distinct seasonal brightness temperature time regions corresponding to different phenological phases of the lake surfaces: complete ice cover, ice melt and deterioration, and open water were revealed. The paper demonstrates the possibility to determine the beginning of ice cover deterioration from satellite microwave radiometry data. The obtained results can be useful for setting the operating terms of winter crossings and roads on ice, as with the beginning of ice deterioration, these transportation routes across water bodies (rivers, lakes, water reservoirs) become insecure and cannot be used any more.

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“…The green line is the average of three neighboring SMP measurements. Takala et al, 2011;Rautiainen et al, 2012;Kontu et al, 2014). We used a value for the complex soil permittivity of frozen ground of g = 3.6 + 0.9i, in line with Rautiainen et al (2012), and set the standard deviation of the soil surface height rms g under the vegetation to 5 mm.…”

Section: Soil Contributionmentioning

confidence: 99%

MEMLS3&a: Microwave Emission Model of Layered Snowpacks adapted to include backscattering

et al. 2015

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Abstract. The Microwave Emission Model of LayeredSnowpacks (MEMLS) was originally developed for microwave emissions of snowpacks in the frequency range 5-100 GHz. It is based on six-flux theory to describe radiative transfer in snow including absorption, multiple volume scattering, radiation trapping due to internal reflection and a combination of coherent and incoherent superposition of reflections between horizontal layer interfaces. Here we introduce MEMLS3&a, an extension of MEMLS, which includes a backscatter model for active microwave remote sensing of snow. The reflectivity is decomposed into diffuse and specular components. Slight undulations of the snow surface are taken into account. The treatment of like-and cross-polarization is accomplished by an empirical splitting parameter q. MEMLS3&a (as well as MEMLS) is set up in a way that snow input parameters can be derived by objective measurement methods which avoid fitting procedures of the scattering efficiency of snow, required by several other models. For the validation of the model we have used a combination of active and passive measurements from the NoSREx (Nordic Snow Radar Experiment) campaign in Sodankylä, Finland. We find a reasonable agreement between the measurements and simulations, subject to uncertainties in hitherto unmeasured input parameters of the backscatter model. The model is written in Matlab and the code is publicly available for download through the following website: http://www.iapmw.unibe.ch/research/ projects/snowtools/memls.html.

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Observation and Modeling of the Microwave Brightness Temperature of Snow-Covered Frozen Lakes and Wetlands

Cited by 15 publications

References 37 publications

Sodankylä manual snow survey program

Sodankylä manual snow survey program

Theoretical study of ice cover phenology at large freshwater lakes based on SMOS MIRAS data

MEMLS3&a: Microwave Emission Model of Layered Snowpacks adapted to include backscattering

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