Satellite Infrared Retrievals of Sea-surface Temperature at High Latitudes

Chong Jia, Univeristy of Miami / RSMAS, Department of Meteorology and Physical Oceanography, Miami, United States and Peter J Minnett, University of Miami, Rosenstiel School of Marine, Atmospheric, and Earth Science, Department of Ocean Sciences, Miami, United States
Climate change is amplified in the Arctic region relative to elsewhere. This Arctic amplification has also been found in past changes in warm and glacial climates, as well as in historical simulations. The retreat of summer sea-ice cover has many consequences on navigation and commerce in and through the Arctic, and has potentially severe societal impacts. The phenomenon is often explained by retreating snow and ice leading to more solar surface warming (surface albedo feedback). However, by analyzing climate model simulations, Pithan and Mauritsen (2014) found that the largest contribution to Arctic amplification comes from temperature feedbacks. Satellite remote sensing offers the best way of deriving surface temperatures in the Arctic, but given that the surface temperature retrieval algorithms in the infrared are designed to compensate for the effects of the atmosphere, mainly water vapor, satellite-derived surface temperatures in the infrared have larger uncertainties at high latitudes because the atmosphere is very dry and cold. When the water vapor concentrations are low, the correction algorithms tend to over-compensate leading to warm biases. So, the motivation of the study is to improve the algorithms to obtain more accurate surface temperatures which can be used to research the feedback mechanisms. To undertake the study, we use collocated, simultaneous satellite measurements of brightness temperature at the top of atmosphere and in situ measurements of surface temperature. We have analyzed the matchup databases for MODIS on Aqua and Terra to characterize the differences between satellite retrieved temperatures and in-situ measurements, and to identify the main causes of the discrepancies. According to the analysis, we find that the surface emissivity plays an important role in the SST satellite retrieval in Arctic region due to the low atmospheric water vapor content, especially during winter-time. The large air-sea temperature difference in winter amplifies such emissivity effects, resulting in an increased contribution to the SST residual errors. We report on the progress towards improving the satellite-derived surface temperatures with the expectation that the near two-decadal time series of MODIS surface temperature fields will contribute to studying climate change in the Arctic.