Abstract. Retrieval of Arctic sea ice thickness fromCryoSat-2 radar altimeter freeboard data requires observational data to verify the relation between these two variables. In this study in-situ ice and snow data from 689 observation sites, obtained during the Sever expeditions in the 1980s, have been used to establish an empirical relation between thickness and freeboard of FY ice in late winter. Estimates of mean and variability of snow depth, snow density and ice density were produced on the basis of many field observations. These estimates have been used in the hydrostatic equilibrium equation to retrieve ice thickness as a function of ice freeboard, snow depth and snow/ice density. The accuracy of the ice thickness retrieval has been calculated from the estimated variability in ice and snow parameters and error of ice freeboard measurements. It is found that uncertainties of ice density and freeboard are the major sources of error in ice thickness calculation. For FY ice, retrieval of ≈ 1.0 m (2.0 m) thickness has an uncertainty of 46% (37%), and for MY ice, retrieval of 2.4 m (3.0 m) thickness has an uncertainty of 20% (18%), assuming that the freeboard error is ± 0.03 m for both ice types. For MY ice the main uncertainty is ice density error, since the freeboard error is relatively smaller than that for FY ice. If the freeboard error can be reduced to 0.01 m by averaging measurements from CryoSat-2, the error in thickness retrieval is reduced to about 32% for a 1.0 m thick FY floe and to about 18% for a 2.4 m thick MY floe. The remaining error is dominated by uncertainty in ice density. Provision of improved ice density data is therefore important for accurate retrieval of ice thickness from CryoSat-2 data.Correspondence to: V. Alexandrov

Retrieval of Arctic sea ice thickness from radar altimeter freeboard data, to be provided by CryoSat-2, requires observational data to verify the relation between the two variables. In this study in-situ ice and snow data from 689 observation sites obtained during the Sever expeditions in the 1980s have been used to establish an empirical relation between ice thickness and freeboard. Estimates of mean and variability of snow depth, snow density and ice density were produced based on many field observations, and have been used in the isostatic equilibrium equation to estimate ice thickness as a function of ice freeboard, snow depth and snow/ice density. The accuracy of the ice thickness retrieval has been calculated from the estimated variability in ice and snow parameters and error of ice freeboard measurements. It is found that uncertainties of ice density and freeboard are the major sources of error in ice thickness calculation. For FY ice, retrieval of ≈1.0 m (2.0 m) thickness has an uncertainty of 60% (41%). For MY ice the main uncertainty is ice density error, since the freeboard error is relatively smaller than for FY ice. Retrieval of 2.4 m (3.0 m) thick MY ice has an error of 24% (21%). The freeboard error is ±0.05 m for both the FY and MY ice. If the freeboard error can be reduced to 0.01 m by averaging a large number of measurements from CryoSat, the error in thickness retrieval is reduced to about 32% for a 1.0 m thick FY floe and to about 18% for a 2.3 m thick MY floe. The remaining error is dominated by uncertainty in ice density. Provision of improved ice density data is therefore important for accurate retrieval of ice thickness from CryoSat data

In cold climate regions, chemicals are often applied on roads to facilitate snow and ice removal. A commonly used performance indicator is the ice melting capacity. There is a growing need for stakeholders to measure melting capacity as more commercial products for deicing become available. There are two standardized test methods for measuring melting capacity, SHRP H-205.1 for solid deicers and SHRP H-205.2 for liquid deicers, but there have been concerns that these tests are not accurate. Researchers have developed alternative test methods, including the shaker test, the mechanical rocker test, and the ice cube titration test. This paper summarizes published data on measured melting capacity for sodium chloride (NaCl). The published data were compared with the calculated melting capacity of NaCl. The findings confirm that SHRP tests have low reproducibility and are not able to measure full melting capacity. The newer test methods measured closer to full melting capacity than the SHRP tests did. They also showed improved accuracy, although more data from the newer test methods are needed before conclusions can be drawn.

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The ability to melt snow and ice is an important feature of any deicing chemical or product. This ability is called the “melting capacity” and is defined as the grams of melted ice per gram of deicer. A product’s melting capacity determines its applicability for use in snow and ice control. The standard procedures in the United States for measuring melting capacity are SHRP H-205.1 for solid chemicals and H-205.2 for liquid chemicals. However, these test methods have proved to be inadequately accurate for research purposes. There is a growing need to develop improved procedures as more deicing products are released on the market. This paper describes how calorimetry, which measures the heat changes that occur during a process, may be used to measure melting capacity. A calorimeter was custom made for the research described in this paper. The calorimeter required minimal mechanical handling and had high-precision temperature control that excluded the most extreme causes of measurement errors in previously developed test methods. Liquid sodium chloride was tested and compared with the calculated melting capacity. The calorimeter produced accurate results. Tests were also performed on magnesium chloride; the results demonstrated that magnesium chloride had a higher melting capacity than sodium chloride.