A Comparison of MODIS LST Retrievals with &amp;lt;i&amp;gt;in Situ&amp;lt;/i&amp;gt; Observations from AWS over the Lambert Glacier Basin, East Antarctica

Wang, Yetang; Wang, Maojian; Zhao, Jun

doi:10.4236/ijg.2013.43056

Cited by 21 publications

(23 citation statements)

References 33 publications

(42 reference statements)

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“…A pilot study using Advanced Very High Resolution Radiometer data confirmed the general locations and value of very low surface temperatures ( Figure S1b; Wang & Key, 2005). We extracted minimum temperatures in the LST satellite swath data south of 70°S (gridded to a 1-km polar stereographic projection) between 15 June to 15 September for a 12-year period (2004-2016; MOD11 Collection 6 and MYD11 Collections 5 and 6; Wan, 2006;Wang et al, 2013). The 2004 winter was the earliest MODIS Collection 6 data available at the time we began our analysis.…”

Section: Methods and Datasupporting

confidence: 52%

Ultralow Surface Temperatures in East Antarctica From Satellite Thermal Infrared Mapping: The Coldest Places on Earth

Scambos¹,

Campbell²,

Pope³

et al. 2018

Geophysical Research Letters

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We identify areas near the East Antarctic ice divide where <−90 °C surface snow temperatures are observed in wintertime satellite thermal‐band data under clear‐sky conditions. The lowest temperatures are found in small (<200 km2) topographic basins of ~2 m depth above 3,800 m elevation. Approximately 100 sites have observed minimum surface temperatures of ~−98 °C during the winters of 2004–2016. Comparisons of surface snow temperatures with near‐surface air temperatures at nearby weather stations indicate that ~−98 °C surfaces imply ~−94 ± 4 °C 2‐m air temperatures. Landsat 8 thermal band data and elevation data show gradients near the topographic depressions of ~6 °C km−1 horizontally and ~4 °C m−1 vertically. Ultralow temperature occurrences correlate with strong polar vortex circulation. We discuss a conceptual model of radiative surface cooling that produces an extreme inversion layer. Further cooling occurs as near‐surface cold air pools in shallow high‐elevation topographic basins, moderated by clear‐air downwelling radiation and heat from subsurface snow.

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Section: Methods and Datasupporting

confidence: 52%

Ultralow Surface Temperatures in East Antarctica From Satellite Thermal Infrared Mapping: The Coldest Places on Earth

Scambos¹,

Campbell²,

Pope³

et al. 2018

Geophysical Research Letters

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“…However, since the focus of this study was on a global T air prediction, Antarctica was only marginally represented in the training data. Applications of MODIS LST to predict T air for Antarctica are limited to the study of Wang et al [19] who compared monthly averages of MODIS LST with T air in the Lambert Glacier Basin in East Antarctica.…”

Section: Introductionmentioning

confidence: 99%

Mapping Daily Air Temperature for Antarctica Based on MODIS LST

et al. 2016

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Spatial predictions of near-surface air temperature (T air ) in Antarctica are required as baseline information for a variety of research disciplines. Since the network of weather stations in Antarctica is sparse, remote sensing methods have large potential due to their capabilities and accessibility. Based on the MODIS land surface temperature (LST) data, T air at the exact time of satellite overpass was modelled at a spatial resolution of 1 km using data from 32 weather stations. The performance of a simple linear regression model to predict T air from LST was compared to the performance of three machine learning algorithms: Random Forest (RF), generalized boosted regression models (GBM) and Cubist. In addition to LST, auxiliary predictor variables were tested in these models. Their relevance was evaluated by a Cubist-based forward feature selection in conjunction with leave-one-station-out cross-validation to reduce the impact of spatial overfitting. GBM performed best to predict T air using LST and the month of the year as predictor variables. Using the trained model, T air could be estimated with a leave-one-station-out cross-validated R 2 of 0.71 and a RMSE of 10.51 • C. However, the machine learning approaches only slightly outperformed the simple linear estimation of T air from LST (R 2 of 0.64, RMSE of 11.02 • C). Using the trained model allowed creating time series of T air over Antarctica for 2013. Extending the training data by including more years will allow developing time series of T air from 2000 on.

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“…In the first part of this paper, the Moderate-Resolution Imaging Spectroradiometer (MODIS) clear-sky land surface temperature (LST) values are evaluated against hourly series of in situ observations of snow surface temperature. Such an evaluation provides better insight than previous evaluations based on a comparison with near-surface temperature, as in Wang et al (2013). In the second section, MODIS LST values from 2000 to 2011 are compared with 3 h ERA-Interim (Dee et al, 2011) snow surface temperatures and hourly snow surface temperatures simulated by the detailed snowpack model Crocus (Brun et al, 1992;Vionnet et al, 2012).…”

mentioning

confidence: 99%

Using MODIS land surface temperatures and the Crocus snow model to understand the warm bias of ERA-Interim reanalyses at the surface in Antarctica

et al. 2014

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Abstract. Moderate-Resolution Imaging spectroradiometer (MODIS) land surface temperatures in Antarctica were processed in order to produce a gridded data set at 25 km resolution, spanning the period 2000-2011 at an hourly time step. The Aqua and Terra orbits and MODIS swath width, combined with frequent clear-sky conditions, lead to very high availability of quality-controlled observations: on average, hourly data are available 14 h per day at the grid points around the South Pole and more than 9 h over a large area of the Antarctic Plateau. Processed MODIS land surface temperatures, referred to hereinafter as MODIS T s values, were compared with in situ hourly measurements of surface temperature collected over the entirety of the year 2009 by seven stations from the Baseline Surface Radiation Network (BSRN) and automatic weather stations (AWSs). In spite of an occasional failure in the detection of clouds, MODIS T s values exhibit a good performance, with a bias ranging from −1.8 to 0.1 • C and errors ranging from 2.2 to 4.8 • C root mean square at the five stations located on the plateau. These results show that MODIS T s values can be used as a precise and accurate reference to test other surface temperature data sets. Here, we evaluate the performance of surface temperature in the European Centre for MediumRange Weather Forecasts (ECMWF) reanalysis known as ERA-Interim reanalysis. During conditions detected as cloud free by MODIS, ERA-Interim shows a widespread warm bias in Antarctica in every season, ranging from +3 to +6 • C on the plateau. This confirms a recent study which showed that the largest discrepancies in 2 m air temperature between ERA-Interim and the global temperature data set HadCRUT4 compiled by the Met Office Hadley Centre and the University of East Anglia's Climatic Research Unit occur in Antarctica. A comparison with in situ surface temperature shows that this bias is not strictly limited to clear-sky conditions. A detailed comparison with stand-alone simulations by the Crocus snowpack model, forced by ERA-Interim, and with the ERA-Interim/land simulations, shows that the warm bias may be due primarily to an overestimation of the surface turbulent fluxes in very stable conditions. Numerical experiments with Crocus show that a small change in the parameterization of the effects of stability on the surface exchange coefficients can significantly impact the snow surface temperature. The ERA-Interim warm bias appears to be likely due to an overestimation of the surface exchange coefficients under very stable conditions.

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A Comparison of MODIS LST Retrievals with <i>in Situ</i> Observations from AWS over the Lambert Glacier Basin, East Antarctica

Cited by 21 publications

References 33 publications

Ultralow Surface Temperatures in East Antarctica From Satellite Thermal Infrared Mapping: The Coldest Places on Earth

Ultralow Surface Temperatures in East Antarctica From Satellite Thermal Infrared Mapping: The Coldest Places on Earth

Mapping Daily Air Temperature for Antarctica Based on MODIS LST

Using MODIS land surface temperatures and the Crocus snow model to understand the warm bias of ERA-Interim reanalyses at the surface in Antarctica

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