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Estimation of air temperature at sites in Maritime Antarctica using MODIS LST collection 6 data
* 1 , 1 , 2
1  Remote Sensing Applications (RSApps) Research Group, Area of Cartographic, Geodesic and Photogrammetric Engineering, Department of Mining Exploitation and Prospecting, Polytechnic School of Mieres, University of Oviedo, C/Gonzalo Gutiérrez Quirós s/n, 336
2  Remote Sensing Applications (RSApps) Research Group, Department of Physics, Polytechnic School of Mieres, University of Oviedo, C/Gonzalo Gutiérrez Quirós s/n, 33600 Mieres, Spain.
Academic Editor: Riccardo Buccolieri

Abstract:

It is known that changes in temperature could cause changes in the Antarctic Ice Sheet, which would have an immediate and long-term impact on the global mean sea level [1]. For this reason, the monitoring of air temperature (Ta) is of great interest to the scientific community. On the other hand, Antarctica constitutes an area of difficult access, which makes it difficult to obtain in-situ data. Because of this, land surface temperature (LST) remote sensing data have become an important alternative for estimating Ta. In this work we estimate Ta from daytime and nighttime LST data at maritime Antarctic sites in the South Shetland Archipelago using empirical models, based on the addition of spatiotemporal variables [2]. We have used Ta data from the Spanish Antarctic stations and from the PERMASNOW project stations [3]. MOD11A1 and MYD11A1 (Collection 6) MODIS LST products were downloaded from the Google Earth Engine platform [4] and only the highest quality data were selected. Outliers associated with clouds were removed with filters. Two different multilinear regression models were tested: models for each individual station and global models based on the data from all the stations. The simple regression analysis LST against Ta showed that a better fit is always achieved with daytime LST data (R2 average = 0.73) than with nighttime LST data (R2 average = 0.56). The performance of the models was improved with the addition of spatiotemporal variables as predictive variables, with which we obtained an average R2 = 0.75 for daytime data and an average R2 = 0.60 for nighttime data. The global models allowed to improve the correlation and reduce the errors with respect to the models obtained using individual stations. Global models provide a precise description of the behavior of the temperature in maritime Antarctica, where it is not possible to install and maintain a dense network of weather stations.

References:

  1. Medley, B.; Thomas, E.R. Increased snowfall over the Antarctic Ice Sheet mitigated twentieth-century sea-level rise. Nat. Clim. Chang. 2019, 9, 34–39, doi:10.1038/s41558-018-0356-x.
  2. Recondo, C.; Corbea-Pérez, A.; Peón, J.; Pendás, E.; Ramos, M.; Calleja, J.F.; de Pablo, M.Á.; Fernández, S.; Corrales, J.A. Empirical Models for Estimating Air Temperature Using MODIS Land Surface Temperature ( and Spatiotemporal. Remote Sens. 2022, 14, 3206, doi:10.3390/rs14133206.
  3. De Pablo, M.A.; Jiménez, J.J.; Ramos, M.; Prieto, M.; Molina, A.; Vieira, G.; Hidalgo, M.A.; Fernández, S.; Recondo, C.; Calleja, J.F.; et al. Frozen Ground and Snow Cover Monitoring in Livingston and Deception Islands, Antarctica: Preliminary Results of the - PERMASNOW Project. Cuad. Investig. Geográfica 2020, 46, 187–222, doi:http://doi.org/10.18172/cig.4381.
  4. Gorelick, N.; Hancher, M.; Dixon, M.; Ilyushchenko, S.; Thau, D.; Moore, R. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 2017, 202, 18–27, doi:10.1016/j.rse.2017.06.031.
Keywords: MODIS; land surface temperature; air temperature
Comments on this paper
Nico England
have read your paper and I found your paper very informative burrito craft
Carmen Recondo
Thank you.

Chris Covington
I think in the remote and challenging environment of Maritime Antarctica, where obtaining in situ data is difficult, estimating air temperature (Ta) becomes crucial for scientific research. Let’s delve into the fascinating work that combines remote sensing data and empirical models to estimate Ta at maritime Antarctic sites. It changes in temperature can significantly affect the Antarctic Ice Sheet, which in turn impacts global mean sea levels. Moreover, Antarctica’s remote location makes it challenging to collect direct temperature measurements on-site. Furthermore, Land Surface Temperature data obtained through remote sensing serve as an alternative for estimating Ta. Researchers used and the MOD11A1 and MYD11A1 (Collection 6) Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. Only the highest quality LST data were chosen, and outliers associated with clouds were filtered out.
Carmen Recondo
Thank you for your good summary and your interest.

Tracy Tew
Two types of multilinear regression models are tested: individual station models and global models based on data from all stations. The analysis shows that daytime LST data consistently provides a better fit than nighttime data when regressed against Ta. The addition of spatiotemporal variables as predictive variables further improves the performance of the models.
Carmen Recondo
Thank you for your comment

Bekean Loinse
Changes in temperature can significantly impact the Antarctic Ice Sheet, leading to immediate and long-term effects on global sea levels . Monitoring air temperature (Ta) in Antarctica is thus crucial for scientific research.




 
 
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