A SYNOPTIC-SCALE COMPARISON OF SATELLITE YUKON RIVER MOUTH TEMPERATURE TO IN-SITU AND REANALYSIS DATA DURING 2003–2020

This paper combines remote sensing Sea Surface Temperature (SST), modeled salinity incorporating remote sensing data, reanalysis products, and in-situ data to study surface changes in previously difficult-to-access coastal Gulf of Alaska over the period 2003–2020. Despite river mouth SST warming from the beginning to the end of the study, data illustrate cooling of the Yukon from headwaters to the river mouth from 2011 to 2020. This result suggests a complex forcing in addition to warming, as well as the need for future examination with inverse models capable of assessing physical budgets for parameters like SST, river discharge, and atmospheric forcing. Here, open source data is combined with techniques such as eigenvalue analysis and a toy problem that uses machine-learning techniques to point to parameters related to SST change in the Yukon River mouth.The featured remote-sensing dataset in this study, the Group for High Resolution Sea Surface Temperature Microwave and Infrared (GHRSST-MWIR) has data from the MODIS sensor on the Aqua and Terra platforms [3] and also includes microwave-derived SSTs from the Advanced Microwave Scanning Radiometer. This dataset provides a unique look at nearly 20 years’ worth of SST data in an important NASA Climate Variability and Change focus area (CVC) [4; 5]. To begin to point to which parameters may contribute to change over the interannual SST variability in the Norton Sound, this remote sensing data is combined in a principal components analysis with other parameters of modeled salinity, reanalysis air temperature, water vapor, and precipitation from MERRA-2, and in-situ datasets of river discharge from the Yukon river headwaters (VonFinster dataset) and the Yukon river mouth at the Norton Sound (Arctic Great Rivers Observatory).