Abstract

Abstract. A neural-network-based retrieval method to determine the snow ice water path (SIWP), liquid water path (LWP), and integrated water vapor (IWV) from millimeter and submillimeter brightness temperatures, measured by using airborne radiometers (ISMAR and MARSS), is presented. The neural networks were trained by using atmospheric profiles from the ICON numerical weather prediction (NWP) model and by radiative transfer simulations using the Atmospheric Radiative Transfer Simulator (ARTS). The basic performance of the retrieval method was analyzed in terms of offset (bias) and the median fractional error (MFE), and the benefit of using submillimeter channels was studied in comparison to pure microwave retrievals. The retrieval is offset-free for SIWP > 0.01 kg m−2, LWP > 0.1 kg m−2, and IWV > 3 kg m−2. The MFE of SIWP decreases from 100 % at SIWP = 0.01 kg m−2 to 20 % at SIWP = 1 kg m−2 and the MFE of LWP from 100 % at LWP = 0.05 kg m−2 to 30 % at LWP = 1 kg m−2. The MFE of IWV for IWV > 3 kg m−2 is 5 to 8 %. The SIWP retrieval strongly benefits from submillimeter channels, which reduce the MFE by a factor of 2, compared to pure microwave retrievals. The IWV and the LWP retrievals also benefit from submillimeter channels, albeit to a lesser degree. The retrieval was applied to ISMAR and MARSS brightness temperatures from FAAM flight B897 on 18 March 2015 of a precipitating frontal system west of the coast of Iceland. Considering the given uncertainties, the retrieval is in reasonable agreement with the SIWP, LWP, and IWV values simulated by the ICON NWP model for that flight. A comparison of the retrieved IWV with IWV from 12 dropsonde measurements shows an offset of 0.5 kg m−2 and an RMS difference of 0.8 kg m−2, showing that the retrieval of IWV is highly effective even under cloudy conditions.

Highlights

  • Ice clouds are in an ongoing focus of atmospheric remote sensing as they play an important role in atmospheric radiation due to their reflection of sunlight and their entrapment of infrared radiation

  • Compared to snow ice water path (SIWP), liquid water path (LWP), and integrated water vapor (IWV), the rainwater path (RWP) retrieval is less satisfactory, which is consistent with the results from Sect

  • As the use of International Submillimetre Airborne Radiometer (ISMAR) and Microwave Airborne Radiometer Scanning System (MARSS) makes it possible to sense SIWP but not CIWP, we developed a retrieval method based on a neural networks (NNs) by using nadirviewing brightness temperature measurements with the main purpose of estimating SIWP

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Summary

Introduction

Ice clouds are in an ongoing focus of atmospheric remote sensing as they play an important role in atmospheric radiation due to their reflection of sunlight and their entrapment of infrared radiation. The term IWP is defined for the whole integrated ice bulk mass, for example in the work of Evans et al (2012) and Holl et al (2014). In this paper, we distinguish between cloud ice, which consists mainly of ice particles with diameters < 100 μm, and snow, which consists mainly of ice particles with diameters > 100 μm. This threshold results from the particle size distribution used This distinction between small and large ice particles is similar to that in atmospheric models such as the Icosahedral Nonhydrostatic (ICON) model (Zängl et al, 2015) or in the IFS-137 model of the European Centre for Medium-Range Weather Fore-

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