Spatial Variability of Surface-Level State Variables over Arctic Sea Ice

Abstract

AbstractNumerical models of the atmosphere, oceans, and sea ice are divided into horizontal grid cells that can range in size from a few kilometers to hundreds of kilometers. In these models, many surface-level variables are assumed to be uniform over a grid cell. Using a year of in situ data from the experiment to study the Surface Heat Budget of the Arctic Ocean (SHEBA), the authors investigate the accuracy of this assumption of gridcell uniformity for the surface-level variables pressure, air temperature, wind speed, humidity, and incoming longwave radiation. The paper bases its analysis on three statistics: the monthly average and, for each season, the spatial correlation function and the spatial bias. For five SHEBA sites, which had a maximum separation of 12 km, the analysis supports the assumption of gridcell uniformity in pressure, air temperature, wind speed, and humidity in all seasons. In winter, when the incidence of fractional cloudiness is largest, the incoming longwave radiation may not be uniform over a grid cell. In other seasons, the bimodal distribution in cloud cover—either clear skies or total cloud cover—tends to homogenize the incoming radiation at scales of 12 km and less.