Detection of soil freezing from L-band passive microwave observations

Rautiainen, Kimmo; Lemmetyinen, Juha; Schwank, Mike; Kontu, Anna; Ménard, Cécile B.; Mätzler, Christian; Drusch, Matthias; Wiesmann, Andreas; Ikonen, Jaakko; Pulliainen, Jouni

doi:10.1016/j.rse.2014.03.007

Cited by 131 publications

(80 citation statements)

References 20 publications

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“…4). These results are also consistent with previous studies documenting increased FT spatial complexity during seasonal transitions in spring and fall (Du et al, 2015;Naeimi et al, 2012;Rautiainen et al, 2014).…”

Section: Factors Affecting Ft Classification Agreementsupporting

confidence: 93%

An extended global Earth system data record on daily landscape freeze–thaw status determined from satellite passive microwave remote sensing

Kim

Kimball

Glassy³

et al. 2017

Earth Syst. Sci. Data

103

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Abstract. The landscape freeze-thaw (FT) signal determined from satellite microwave brightness temperature (T b ) observations has been widely used to define frozen temperature controls on land surface water mobility and ecological processes. Calibrated 37 GHz T b retrievals from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), and SSM/I Sounder (SSMIS) were used to produce a consistent and continuous global daily data record of landscape FT status at 25 km grid cell resolution. The resulting FT Earth system data record (FT-ESDR) is derived from a refined classification algorithm and extends over a larger domain and longer period than prior FT-ESDR releases. The global domain encompasses all land areas affected by seasonal frozen temperatures, including urban, snow-and ice-dominant and barren land, which were not represented by prior FT-ESDR versions. The FT retrieval is obtained using a modified seasonal threshold algorithm (MSTA) that classifies daily T b variations in relation to grid-cell-wise FT thresholds calibrated using surface air temperature data from model reanalysis. The resulting FT record shows respective mean annual spatial classification accuracies of 90.3 and 84.3 % for evening (PM) and morning (AM) overpass retrievals relative to global weather station measurements. Detailed data quality metrics are derived characterizing the effects of sub-grid-scale open water and terrain heterogeneity, as well as algorithm uncertainties on FT classification accuracy. The FT-ESDR results are also verified against other independent cryospheric data, including in situ lake and river ice phenology, and satellite observations of Greenland surface melt. The expanded FT-ESDR enables new investigations encompassing snow-and ice-dominant land areas, while the longer record and favorable accuracy allow for refined global change assessments that can better distinguish transient weather extremes, landscape phenological shifts, and climate anomalies from longer-term trends extending over multiple decades. The dataset is freely available online

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Section: Factors Affecting Ft Classification Agreementsupporting

confidence: 93%

An extended global Earth system data record on daily landscape freeze–thaw status determined from satellite passive microwave remote sensing

Kim

Kimball

Glassy³

et al. 2017

Earth Syst. Sci. Data

103

View full text Add to dashboard Cite

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“…Data from an L-band instrument (Schwank et al, 2010) are available from the same site; these data are not presented here in detail as the relevant information can be found in the literature (Rautiainen et al, 2014;Lemmetyinen et al, 2016). All instruments were mounted on tower structures overlooking the forest clearing, partially allowing the same sectors of the test field to be covered, albeit at differing effective incidence angles.…”

Section: Measurement Locationmentioning

confidence: 99%

“…Data collected in the frame of NoSREx have also been exploited in recent studies focused on passive microwave signatures (e.g. Rautiainen et al, 2014;Pan et al, 2015).…”

Section: Comparison To Observationsmentioning

confidence: 99%

Nordic Snow Radar Experiment

Lemmetyinen

Kontu

Pulliainen

et al. 2016

Geosci. Instrum. Method. Data Syst.

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Abstract. The objective of the Nordic Snow Radar Experiment (NoSREx) campaign was to provide a continuous time series of active and passive microwave observations of snow cover at a representative location of the Arctic boreal forest area, covering a whole winter season. The activity was a part of Phase A studies for the ESA Earth Explorer 7 candidate mission CoReH2O (Cold Regions Hydrology Highresolution Observatory).The NoSREx campaign, conducted at the Finnish Meteorological Institute Arctic Research Centre (FMI-ARC) in Sodankylä, Finland, hosted a frequency scanning scatterometer operating at frequencies from X-to Ku-band. The radar observations were complemented by a microwave dualpolarization radiometer system operating from X-to Wbands. In situ measurements consisted of manual snow pit measurements at the main test site as well as extensive automated measurements on snow, ground and meteorological parameters.This study provides a summary of the obtained data, detailing measurement protocols for each microwave instrument and in situ reference data. A first analysis of the microwave signatures against snow parameters is given, also comparing observed radar backscattering and microwave emission to predictions of an active/passive forward model.All data, including the raw data observations, are available for research purposes through the European Space Agency and the Finnish Meteorological Institute. A consolidated dataset of observations, comprising the key microwave and in situ observations, is provided through the ESA campaign data portal to enable easy access to the data.

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“…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%

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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Detection of soil freezing from L-band passive microwave observations

Cited by 131 publications

References 20 publications

An extended global Earth system data record on daily landscape freeze–thaw status determined from satellite passive microwave remote sensing

An extended global Earth system data record on daily landscape freeze–thaw status determined from satellite passive microwave remote sensing

Nordic Snow Radar Experiment

Sodankylä manual snow survey program

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