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Observation of snowfall with a low-power FM-CW K-band radar (Micro Rain Radar) |
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| Authors: | Stefan Kneifel Maximilian Maahn Gerhard Peters Clemens Simmer |
| Institution: | 1. Institute for Geophysics and Meteorology, University of Cologne, Z??lpicherstra?e 49a, 50674, Cologne, Germany 2. Meteorological Institute, University of Bonn, Auf dem H??gel 20, 53121, Bonn, Germany 3. Geophysical Department, University Centre in Svalbard, Pb. 156, 9171, Longyearbyen, Norway 4. Metek, Meteorologische Messtechnik GmbH, Fritz-Stra?mann Str. 4, 25337, Elmshorn, Germany |
| Abstract: | Quantifying snowfall intensity especially under arctic conditions is a challenge because wind and snow drift deteriorate estimates obtained from both ground-based gauges and disdrometers. Ground-based remote sensing with active instruments might be a solution because they can measure well above drifting snow and do not suffer from flow distortions by the instrument. Clear disadvantages are, however, the dependency of e.g. radar returns on snow habit which might lead to similar large uncertainties. Moreover, high sensitivity radars are still far too costly to operate in a network and under harsh conditions. In this paper we compare returns from a low-cost, low-power vertically pointing FM-CW radar (Micro Rain Radar, MRR) operating at 24.1?GHz with returns from a 35.5?GHz cloud radar (MIRA36) for dry snowfall during a 6-month observation period at an Alpine station (Environmental Research Station Schneefernerhaus, UFS) at 2,650?m height above sea level. The goal was to quantify the potential and limitations of the MRR in relation to what is achievable by a cloud radar. The operational MRR procedures to derive standard radar variables like effective reflectivity factor (Z e) or the mean Doppler velocity (W) had to be modified for snowfall since the MRR was originally designed for rain observations. Since the radar returns from snowfall are weaker than from comparable rainfall, the behavior of the MRR close to its detection threshold has been analyzed and a method is proposed to quantify the noise level of the MRR based on clear sky observations. By converting the resulting MRR-Z e into 35.5?GHz equivalent Z e values, a remaining difference below 1?dBz with slightly higher values close to the noise threshold could be obtained. Due to the much higher sensitivity of MIRA36, the transition of the MRR from the true signal to noise can be observed, which agrees well with the independent clear sky noise estimate. The mean Doppler velocity differences between both radars are below 0.3?ms?1. The distribution of Z e values from MIRA36 are finally used to estimate the uncertainty of retrieved snowfall and snow accumulation with the MRR. At UFS low snowfall rates missed by the MRR are negligible when comparing snow accumulation, which were mainly caused by intensities between 0.1 and 0.8 mm?h?1. The MRR overestimates the total snow accumulation by about 7%. This error is much smaller than the error caused by uncertain Z e?Csnowfall rate relations, which would affect the MIRA36 estimated to a similar degree. |
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