Numerical simulations of Greenland snowpack and comparison with passive microwave spectral signatures

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Abstract
In this paper, we show that a detailed snow model (here, the Crocus model) may help to validate large-scale inferred meteorological datasets (e.g. from climate models or analyses) over the data-sparse ice sheets. Two series of snow simulations are carried out with two different meteorological datasets in input to the snow model. Both datasets are extracted from the European Center for Medium-range Weather Forecasts meteorological analyses and forecast archives. First, the microwave signatures of the surface of central Greenland from the Scanning Multichannel Microwave Radiometer (SMMR) are compared with the simulated density, grain-size and stratigraphy. The annual mean gradient ratio and polarization ratio, which are related to the emissivity of snow, are found to correlate spatially with these snow structural parameters. The sensitivity of the snow structure to differences in the two meteorological sets is then examined. It is found to be high for temperature and infrared radiation, precipitation and surface wind. The quantitative value of this result is limited by a still limited snow model validation over Greenland. Also, an optimal use of satellite data and a snow model for meteorological validation would require physically based translation of the simulated snow parameters into radiative properties, i. e radiation transfer modeling.