A theoretical distribution function for pressure‐ridge, sail heights and keel depths is derived from fundamental assumptions about the randomness of the ridges. It is shown that the distribution function for ridge spacings (distance between ridges) can also be predicted from the assumption of spatially random occurrence. The suggested distribution functions are, in form, negative exponentials of the ridge height (or depth) squared and the ridge spacing, respectively. Extremely good fits were achieved to extensive data collected from sonar profiles of the lower surface of the pack ice and to laser profiles, as well as visual roughness data from the upper ice surface. Using these models, it is possible to completely characterize the ridging, in a one‐dimensional sense, by two parameters: 〈N〉, the mean number of ridges per unit length, and 〈h〉, the mean ridge height (or depth). In addition, there is a linear correlation between 〈N〉 and 〈h〉. This suggests that maps showing the distribution of 〈N〉 or 〈h〉 over an ocean covered with pack ice can be used to statistically characterize both the spacing and the height distribution of the ridges.
A one‐parameter model for pressure ridges is developed and compared, with good agreement, with over 3000 km of laser profile data taken from November 1970 to February 1973 in the Arctic basin. Comparisons are also made with a previously developed two‐parameter model. The number of ridges per kilometer at any height level may be well predicted from the one‐parameter model by using a parameter called ridging intensity (denoted by γh) which may be determined for a region from the mean number of ridges per unit length and the mean ridge height. Regional and temporal variations in ridging intensity in the western Arctic basin are studied. Results indicate that although magnitudes of ridging intensity vary in time, the relative regional variations are similar. Consequently, three distinct regions of ridging intensity having relatively stable boundaries can be defined. Annual variation in new ice production due to ridging is sufficiently large to suggest that ridging plays an important role in the overall mass balance of the Arctic basin.
The spatial aspects of sea ice pressure ridge statistics have been examined by a census of all ridges in each of three small areas in the arctic basin. A model that predicts random orientation of ridges can be rejected at the 0.05 level of significance in each study area. Measurements of ridge spacings generally confirm the usefulness and validity of the probability density function P(x) dx = μe−μx dx. The estimator trueμˆ varies as a function of direction within the study areas, but a mean value 〈μ〉 is shown to be related to the ridge density (total length of ridges per unit area) by the simple equation 〈μ〉 = (2/π)RD.
All available 10 m. snow temperatures from the Greenland Ice Sheet have been analyzed using multiple regression techniques to develop equations capable of accurately predicting these temperatures. The analysis was carried out for all Greenland and for various sub-areas. The resulting equations show that 10 m. snow temperatures can be accurately predicted from the parameters latitude and elevation. Longitude was found to be a further significant parameter in south Greenland.Gradients of 10 m. snow temperatures versus elevation for north Greenland are close to the dry adiabatic lapse rate indicating adiabatic warming of katabatic winds as the controlling mechanism in their altitudinal distribution. In both south Greenland and the Thule peninsula, gradients of 10 m. snow temperatures versus elevation are markedly greater than the dry adiabatic lapse rate and are highly dependent upon elevation, indicating downward transfer of latent heat in the snow, largely as a result of percolating melt water.An isotherm map, showing the distribution of 10 m. snow temperatures on the Greenland Ice Sheet calculated from the prediction equations, was prepared. The map is based upon a revised contour map of the ice sheet made from a compilation of all known elevations.
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