Presentation is loading. Please wait.

Presentation is loading. Please wait.

Introduction Knowledge of the snow microstructure (correct a priori parameterization of grain size) is relevant for successful retrieval of snow parameters.

Similar presentations


Presentation on theme: "Introduction Knowledge of the snow microstructure (correct a priori parameterization of grain size) is relevant for successful retrieval of snow parameters."— Presentation transcript:

1 Introduction Knowledge of the snow microstructure (correct a priori parameterization of grain size) is relevant for successful retrieval of snow parameters (e.g. SWE) from microwave observations. Sodankylä has extent measurement site for monitoring development of natural seasonal snowpack Weekly manual snowpit measurements (grain size, grain type, SSA, correlation length and reference measurements) and continuous microwave radiometer measurements are made. Microwave observations are modeled mainly with HUT snow emission model [1]. Different measures of snow structure is compared to inverted values from passive microwave observations to analyze suitability of different grain size definitions in simulation of microwave emission. Comparison of microwave radiometer observations and snow grain size in Sodankylä [1] J. Pulliainen, J. Grandell, and M. Hallikainen, “HUT snow emission model and its applicability to snow water equivalent retrieval,” IEEE Trans. Geosci. Remote Sens, vol.37(3), pp. 1378-1390, 1999. [2] J.-C. Gallet, F. Domine, C. Zender, and G. Picard, “Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm,” The Cryosphere, vol.3, pp. 167- 182, 2009. [3 ] M. Proksch, H. Löwe, and M. Schneebeli, 2014.: “Density, specific surface area and correlation length of snow measured by high resolution penetrometry”, Journal of Geophysical Research Earth surface, submitted. DescriptionSample frequency Method Traditional grain size D max Physical diameter of a typical snow grain One sample from every layer Estimated visually from macro-photographs by accuracy of 0.25 mm. Value for the whole snowpack is calculated by weighted mean with layer height. Optical grain size D0D0 Diameter of ice spheres which have the same optical properties as original grains 3 cmDerived from IceCube-instrument specific surface area (SSA) measurements [2]. Value for the whole snowpack is calculated by weighted mean with sample height (and height from ground for the lowest measurement). Correlation length P ex Length scale of porous media 0.125 cmDerived from Snow Micro Pen (SMP) measurements [3] Effective grain size D eff Parameter which describes microstructure of snowpack in radiative transfer models One value for the whole snowpack Retrieved using inversion of HUT snow emission model from radiometer observations at 18.7 – 36.5 GHz Passive microwave radiometers Measures brightness temperature of snow and ground. Based on 5-m high tower Measurements only from dry snow Frequency channels 10.65, 18.7, 21.0, 36.5, 89 and 150 GHz with horizontal and vertical polarization. Measurements since 2009 Snow Micro Pen [3] IceCube [2] Results Magnitude of traditional grain size (D max ) is larger than magnitude of optical grain size (D 0 ) and correlation length (P ex ) (Fig. 1). Trends of the D max and D 0 are quite similar. Difference (scaling factor) between D max and D 0 is approximately 2.5. RMS error between effective grain size (D eff ) and D max is 0.45 mm, between D eff and D 0 is 0.55 mm and between D eff and p ex is 0.85 mm. RMS error between scaled D 0 and D eff is only 0.29 mm. D eff depends on used frequency, values 18.7 GHz minus 36.5 GHz are mostly used. Grain size photography Radiometers Snowpit measurements Measurement area of radiometers Grain size definitions Conclusion Effective grain size inverted with HUT snow model from radiometer observations in Sodankylä has magnitude closest to traditional grain size, but best similarity (smallest RMSE) with optical grain size multiplied by scaling factor. Leena Leppänen 1, Anna Kontu 1, Juha Lemmetyinen 1, Martin Proksch 2 1 Finnish Meteorological Institute, Arctic Research, Tähteläntie 62, 99600 Sodankylä, Finland 2 WSL Swiss Federal Institute for Snow and Avalanche Research SLF, CH-7260 Davos, Switzerland Figure 1. Height-weighted averages over whole snowpack of D max, D 0 and P ex are compared to D eff. Winter 2014 has D eff. inverted from 18.7 GHz observations and also from 18.7 - 36.5 GHz observations in January (lower dots). Snowpit measurements include grain size macro-photography, IceCube and Snow Micro Pen


Download ppt "Introduction Knowledge of the snow microstructure (correct a priori parameterization of grain size) is relevant for successful retrieval of snow parameters."

Similar presentations


Ads by Google