The Case for a Single Channel Composite Arctic Sea Surface Temperature Algorithm

Surface temperatures derived from satellite thermal infrared (TIR) data are critical inputs for assessing climate change in polar environments. Sea and ice surface temperature (SST, IST) are commonly determined with split window algorithms that use the brightness temperature from the 11 μm channel (BT11) as the main estimator and the difference between BT11 and the 12 μm channel (BTD11–12) to correct for atmospheric water vapor absorption. An issue with this paradigm in the Arctic maritime environment is the occurrence of high BTD11–12 that is not indicative of atmospheric absorption of BT11 energy. The Composite Arctic Sea Surface Temperature Algorithm (CASSTA) considers three regimes based on BT11 pixel value: seawater, ice, and marginal ice zones. A single channel (BT11) estimator is used for SST and a split window algorithm for IST. Marginal ice zone temperature is determined with a weighted average between the SST and IST. This study replaces the CASSTA split window IST with a single channel (BT11) estimator to reduce errors associated with BTD11–12 in the split window algorithm. The single channel IST returned improved results in the CASSTA dataset with a mean average error for ice and marginal ice zones of 0.142 K and 0.128 K, respectively.

[1]  Peter J. Minnett,et al.  Error characteristics of the atmospheric correction algorithms used in retrieval of sea surface temperatures from infrared satellite measurements: Global and regional aspects , 2003 .

[2]  J. Key,et al.  On the Validation of Satellite-Derived Sea Ice Surface Temperature , 1994 .

[3]  Charles Fowler,et al.  High-latitude surface temperature estimates from thermal satellite data , 1997 .

[4]  R. Evans,et al.  Overview of the NOAA/NASA advanced very high resolution radiometer Pathfinder algorithm for sea surface temperature and associated matchup database , 2001 .

[5]  Rune Storvold,et al.  In-situ measured spectral directional emissivity of snow and ice in the 8-14 μm atmospheric window , 2006 .

[6]  S. Marcq,et al.  Influence of sea ice lead-width distribution on turbulent heat transfer between the ocean and the atmosphere , 2011 .

[7]  I. Robinson,et al.  An Infrared Sea Surface Temperature Autonomous Radiometer (ISAR) for Deployment aboard Volunteer Observing Ships (VOS) , 2008 .

[8]  Peter J. Minnett,et al.  An Independent Assessment of Pathfinder AVHRR Sea Surface Temperature Accuracy Using the Marine Atmosphere Emitted Radiance Interferometer (MAERI) , 2000 .

[9]  William G. Pichel,et al.  Comparative performance of AVHRR‐based multichannel sea surface temperatures , 1985 .

[10]  Steven A. Ackerman,et al.  Inference of ice cloud properties from high spectral resolution infrared observations , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[11]  G. Maykut.  Energy exchange over young sea ice in the central Arctic , 1978 .

[12]  John E. Walsh,et al.  Simulations of Arctic Temperature and Pressure by Global Coupled Models , 2007 .

[13]  P. Minnett,et al.  Arctic waters and marginal ice zones: A composite Arctic sea surface temperature algorithm using satellite thermal data , 2008 .

[14]  K. Sugiura,et al.  Modeling angular-dependent spectral emissivity of snow and ice in the thermal infrared atmospheric window. , 2013, Applied optics.

[15]  P. Minnett,et al.  The Marine-Atmospheric Emitted Radiance Interferometer: A High-Accuracy, Seagoing Infrared Spectroradiometer , 2001 .

[16]  G. Dybkjær,et al.  Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data , 2012 .

[17]  Peter J. Minnett,et al.  Arctic waters and marginal ice zones: 2. An investigation of arctic atmospheric infrared absorption for advanced very high resolution radiometer sea surface temperature estimates , 2008 .

[18]  W P Arnott,et al.  Extinction efficiency in the infrared (2-18 µm) of laboratory ice clouds: observations of scattering minima in the Christiansen bands of ice. , 1995, Applied optics.

[19]  William J. Emery,et al.  Correcting infrared satellite estimates of sea surface temperature for atmospheric water vapor attenuation , 1994 .

[20]  R. Vincent.  The Effect of Arctic Dust on the Retrieval of Satellite Derived Sea and Ice Surface Temperatures , 2018, Scientific Reports.

[21]  Peter J. Minnett,et al.  A numerical study of the effects of anomalous North Atlantic atmospheric conditions on the infrared measurement of sea surface temperature from space , 1986 .

[22]  Dorothy K. Hall,et al.  Sea ice surface temperature product from MODIS , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[23]  Dorothy K. Hall,et al.  Comparison of Near-Surface Air Temperatures and MODIS Ice-Surface Temperatures at Summit, Greenland (2008-13) , 2014 .

[24]  Yachao Li,et al.  An Improved Single-Channel Polar Region Ice Surface Temperature Retrieval Algorithm Using Landsat-8 Data , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[25]  J. Francis,et al.  The Arctic Amplification Debate , 2006 .

[26]  R. Goody,et al.  Formation and Persistence of Summertime Arctic Stratus Clouds. , 1976 .

[27]  T. Scambos,et al.  Validation of Avhrr and Modis ice Surface temperature products using in Situ radiometers , 2006, Annals of Glaciology.

[28]  Yinghui Liu,et al.  Ice Surface Temperature Retrieval from a Single Satellite Imager Band , 2018, Remote. Sens..