Spatial Variability of L-Band Brightness Temperature during Freeze/Thaw Events over a Prairie Environment

Roy, Alexandre; Toose, Peter; Derksen, Chris; Berg, Aaron; Lemmetyinen, Juha; Royer, A.; Tetlock, Erica; Helgason, Warren; Sonnentag, Oliver

doi:10.3390/rs9090894

Cited by 16 publications

(8 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The lower FT classification agreement over the northern (≥45 • N) domain may be attributed to a larger number of daily FT variations over the annual cycle and to wetter snow conditions during seasonal transitions [7,51], where the L-band snow volume emission becomes significant in the presence of even small amounts of snow liquid water [52]. However, the distribution of other physical landscape factors can degrade the Tb signal-to-noise and influence the associated FT accuracy pattern [51,53].…”

Section: Ft Classification Assessmentmentioning

confidence: 99%

Global Assessment of the SMAP Freeze/Thaw Data Record and Regional Applications for Detecting Spring Onset and Frost Events

Kim

Kimball

et al. 2019

Remote Sensing

Self Cite

View full text Add to dashboard Cite

More than half of the global land area undergoes seasonal frozen and thawed conditions that constrain eco-hydrological processes. The freeze-thaw (FT) retrieval from satellite microwave remote sensing detects landscape changes between frozen and non-frozen conditions due to the strong dependence of surface microwave emissions on liquid water abundance. We conducted an assessment of the latest version (R16) of the NASA Soil Moisture Active Passive (SMAP) Level 3 FT (L3_FT) global product. The L3_FT product provides a global FT classification with 3-day mean temporal fidelity derived using SMAP L-band (1.4 GHz) microwave brightness temperature (Tb) retrievals. The R16 product uses both normalized polarization ratio (NPR) and single channel vertically-polarized Tb (FT-SCV) algorithms to obtain FT retrievals over land areas where frozen temperatures are a significant ecological constraint. The L3_FT product is generated in a standard global grid with similar grid cell resolution (36-km) as the SMAP radiometer footprint. An enhanced 9-km global grid L3_FT product is also produced from optimally interpolated SMAP Tb retrievals. The resulting L3_FT products span a larger domain and longer period (2015–present) than earlier product releases. The L3_FT 36-km results showed a respective global mean annual FT classification accuracy of approximately 78 and 90 percent for descending (AM) and ascending (PM) orbit observations in relation to independent surface air temperature-based FT estimates from ~5000 global weather stations. The FT accuracy was lower in areas with greater terrain complexity, open water and vegetation cover; where the combined land cover factors explained 29–53% of the variability in the SMAP FT global accuracy. The L3_FT 9-km product showed an apparent enhancement of FT spatial patterns, but with ~4% lower accuracy than the 36-km product; the lower 9-km accuracy was attributed to stronger degradation from land cover heterogeneity, particularly in coastal areas, and artifact noise introduced from the spatial interpolation of SMAP Tb retrievals. Selected regional applications indicated product utility in capturing anomalous frost events over Australia and seasonal thaw and spring onset patterns over Alaska. Overall, the L3_FT global accuracy meets or exceeds the FT product science requirements established by the mission, while enabling studies of dynamic FT and water mobility constraints influencing hydrological and ecosystem processes, and global water-carbon-energy cycle linkages.

show abstract

Section: Ft Classification Assessmentmentioning

confidence: 99%

Global Assessment of the SMAP Freeze/Thaw Data Record and Regional Applications for Detecting Spring Onset and Frost Events

Kim

Kimball

et al. 2019

Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…The FT-AP is archived and distributed by the NASA Distributed Active Archive Center of the National Snow and Ice Data Center (NSIDC DAAC). The FT-AP can be accessed through the NSIDC online public data server (https: //nsidc.org/data/aq3_ft/versions/5, Roy et al, 2018). Table 6 summarizes all the datasets used in this study and lists where they are available for download.…”

Section: Data Availabilitymentioning

confidence: 99%

“…This study presents the new Aquarius passive FT product for the Northern Hemisphere (Roy et al, 2018), distributed by the US National Snow and Ice Data Center (NSIDC) at http://nsidc.org/data/nsidc-0736/versions/1. The product precision and uncertainties are addressed by comparing Aquarius FT retrievals with the FT-ESDR product for the overlapping period (2011-2014).…”

Section: Introductionmentioning

confidence: 99%

Northern Hemisphere surface freeze–thaw product from Aquarius L-band radiometers

Prince

Roy

Brucker

et al. 2018

Earth Syst. Sci. Data

Self Cite

View full text Add to dashboard Cite

Abstract. In the Northern Hemisphere, seasonal changes in surface freeze–thaw (FT) cycles are an important component of surface energy, hydrological and eco-biogeochemical processes that must be accurately monitored. This paper presents the weekly polar-gridded Aquarius passive L-band surface freeze–thaw product (FT-AP) distributed on the Equal-Area Scalable Earth Grid version 2.0, above the parallel 50° N, with a spatial resolution of 36 km × 36 km. The FT-AP classification algorithm is based on a seasonal threshold approach using the normalized polarization ratio, references for frozen and thawed conditions and optimized thresholds. To evaluate the uncertainties of the product, we compared it with another satellite FT product also derived from passive microwave observations but at higher frequency: the resampled 37 GHz FT Earth Science Data Record (FT-ESDR). The assessment was carried out during the overlapping period between 2011 and 2014. Results show that 77.1 % of their common grid cells have an agreement better than 80 %. Their differences vary with land cover type (tundra, forest and open land) and freezing and thawing periods. The best agreement is obtained during the thawing transition and over forest areas, with differences between product mean freeze or thaw onsets of under 0.4 weeks. Over tundra, FT-AP tends to detect freeze onset 2–5 weeks earlier than FT-ESDR, likely due to FT sensitivity to the different frequencies used. Analysis with mean surface air temperature time series from six in situ meteorological stations shows that the main discrepancies between FT-AP and FT-ESDR are related to false frozen retrievals in summer for some regions with FT-AP. The Aquarius product is distributed by the U.S. National Snow and Ice Data Center (NSIDC) at https://nsidc.org/data/aq3_ft/versions/5 with the DOI https://doi.org/10.5067/OV4R18NL3BQR.

show abstract

“…Because of the large antenna full beamwidth (30 • ) and the footprint geometry of the surface-based radiometer, the simulated T B of a single directional incidence angle (θ) might not be representative of the measured T B over a large footprint, especially at higher incidence angles [37]. Hence, in this study, a weighting function was computed to estimate the integrated T B within the footprint for a range of incidence angles.…”

Section: Footprint Integrationmentioning

confidence: 99%

“…Roy et al [37] showed that spatially distributed surface-based radiometer observations within a SMOS pixel gives constantly lower T B (between 8.5 and 22.9 K) than SMOS observations at 60 • V-pol (not apparent at lower incidence angles). It was hypothesized that these discrepancies were due to the large beamwidth (30 • ) of the surface-based radiometer, which produced an incidence angle in the far range of up to 75 • .…”

Section: Footprint Integrationmentioning

confidence: 99%

Modelling the L-Band Snow-Covered Surface Emission in a Winter Canadian Prairie Environment

et al. 2018

Self Cite

View full text Add to dashboard Cite

Detailed angular ground-based L-band brightness temperature (TB) measurements over snow covered frozen soil in a prairie environment were used to parameterize and evaluate an electromagnetic model, the Wave Approach for LOw-frequency MIcrowave emission in Snow (WALOMIS), for seasonal snow. WALOMIS, initially developed for Antarctic applications, was extended with a soil interface model. A Gaussian noise on snow layer thickness was implemented to account for natural variability and thus improve the TB simulations compared to observations. The model performance was compared with two radiative transfer models, the Dense Media Radiative Transfer-Multi Layer incoherent model (DMRT-ML) and a version of the Microwave Emission Model for Layered Snowpacks (MEMLS) adapted specifically for use at L-band in the original one-layer configuration (LS-MEMLS-1L). Angular radiometer measurements (30°, 40°, 50°, and 60°) were acquired at six snow pits. The root-mean-square error (RMSE) between simulated and measured TB at vertical and horizontal polarizations were similar for the three models, with overall RMSE between 7.2 and 10.5 K. However, WALOMIS and DMRT-ML were able to better reproduce the observed TB at higher incidence angles (50° and 60°) and at horizontal polarization. The similar results obtained between WALOMIS and DMRT-ML suggests that the interference phenomena are weak in the case of shallow seasonal snow despite the presence of visible layers with thicknesses smaller than the wavelength, and the radiative transfer model can thus be used to compute L-band brightness temperature.

show abstract

Spatial Variability of L-Band Brightness Temperature during Freeze/Thaw Events over a Prairie Environment

Cited by 16 publications

References 42 publications

Global Assessment of the SMAP Freeze/Thaw Data Record and Regional Applications for Detecting Spring Onset and Frost Events

Global Assessment of the SMAP Freeze/Thaw Data Record and Regional Applications for Detecting Spring Onset and Frost Events

Northern Hemisphere surface freeze–thaw product from Aquarius L-band radiometers

Modelling the L-Band Snow-Covered Surface Emission in a Winter Canadian Prairie Environment

Contact Info

Product

Resources

About