[1] The retrieval of Arctic sea surface temperatures (SSTs) using satellite radiometric imagery has not been well documented owing to the paucity of match-ups with in situ data. SST algorithms developed in temperate regions lead to positive biases in high latitudes due to an overestimation of atmospheric IR absorption. The composite arctic sea surface temperature algorithm (CASSTA) presented in this paper was developed from concurrent satellite and shipborne radiometric data collected in the North Water Polynya between April and July 1998. This algorithm considers three temperature regimes: seawater above freezing, the transition zones of water and ice, and primarily ice. These regimes, which are determined by advanced very high resolution radiometer (AVHRR) calibrated brightness temperatures, require different calculations for temperature estimates. For seawater above freezing, a specific Arctic SST algorithm was produced through a linear regression of AVHRR against in situ data. Areas consisting mainly of ice use an established ice surface temperature (IST) algorithm. The transition zone uses a combination of the Arctic SST and IST algorithms. CASSTA determines the Channel 4 brightness temperature for each pixel in a calibrated AVHRR image and then applies the appropriate algorithm to create a thermal image. The mean deviation of CASSTA compared to in situ data was 0.17 K with a standard deviation of 0.21 K. This represents a significant improvement over SST values using McClain coefficients for temperate waters, which overestimate the same data set by an average of 2.40 K. Application of CASSTA to the North Water imagery gives superior results compared to existing SST or IST algorithms.Citation: Vincent, R. F., R. F. Marsden, P. J. Minnett, K. A. M. Creber, and J. R. Buckley (2008), Arctic waters and marginal ice zones: A composite Arctic sea surface temperature algorithm using satellite thermal data,
Forging a stronger connection between mesoscale geometry, performance, and processing techniques can realize practical approaches for controlling battery performance using mesoscale geometry. To this end, 3D X-ray imaging, microstructural characterization, and computational modeling have been applied to analyze the intercalation behavior of Li(Ni 1/3 Mn 1/3 Co 1/3 )O 2 (NMC) cathodes. Samples extracted from pristine cathodes were imaged using X-ray nanotomography. Active material particle geometry was characterized and compared for samples from four cathodes treated with distinct preparation steps. Significant size reduction was observed in calendered and ball milled samples, and distinct differences were observed in particle morphology. Tomographic data for a representative particle was applied in a numerical transport model to assess the effect of particle geometry on intercalation. This assessment proved critical in determining an appropriate estimate of particle size for defining dimensionless parameters that permit rapid estimation of intercalation time. Defining an effective particle radius based on a sphere of equivalent surface area to volume ratio was found to provide the most accurate estimate of intercalation time. Informed by this analysis, dimensionless parameters were used to assess intercalation behavior of the cathode materials. This assessment revealed a substantial change in rate capability connected to particle size reductions achieved in calendering and ball milling.
Observations taken on an expedition into the Arctic Ocean north of Spitsbergen indicated the existence of a region of wind-driven upwelling along the edge of the ice pack. Models underestimate the 12-kilometer width of the upwelling region.
[1] The derivation of sea surface temperatures (SST) from satellite radiometric data is well established in temperate latitudes. Water vapor is typically the greatest clear sky absorber of infrared (IR) energy between the emitting surface and spaceborne sensor, necessitating a corrective term for SST calculation. Algorithms developed for advanced very high resolution radiometers (AVHRR) use the difference in brightness temperatures between Channel 4 (10.3 to 11.3 mm) and Channel 5 (11.5 to 12.5 mm), or T45, to estimate the amount of IR absorption in the atmosphere. While relatively accurate in temperate latitudes, this approach is not applicable to Arctic waters, typically overestimating the SST by 2 to 3 K as a result of high T45 values that are not indicative of IR absorption by water vapor. The high T45 values in the Arctic may be attributable to atmospheric ice crystals. The attenuation of IR energy increases sharply across Channel 4 and 5 for ice crystals, the amount of which is a function of crystal size, shape and orientation. In the development of the Composite Arctic Sea Surface Temperature Algorithm in the North Water polynya (NOW), it was demonstrated that when T45 exceeded a threshold of 2 K the surface temperature could not be estimated owing to the presence of a clear sky absorptive feature. Observations from the NOW study led to the assessment that areas where T45 > 2K were covered by ice fog. This is a significant finding since these regions must be identified to achieve an accurate mapping of the surface temperature.Citation: Vincent, R. F., R. F. Marsden, P. J. Minnett, and J. R. Buckley (2008), Arctic waters and marginal ice zones: 2. An investigation of arctic atmospheric infrared absorption for advanced very high resolution radiometer sea surface temperature estimates,
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