Estimation of Air Temperature at Sites in Maritime Antarctica Using MODIS LST Collection 6 Data

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. 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 estimated 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. We used Ta data from the Spanish Antarctic stations and from the PERMASNOW project stations. MOD11A1 and MYD11A1 (Collection 6) Moderate Resolution Imaging Spectroradiometer (MODIS) LST products were downloaded from the Google Earth Engine platform 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 for improving the correlation and reducing 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.

Keywords

• MODIS
• Land Surface Temperature
• air temperature