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Ice crystal characterization in cirrus clouds II: radiometric characterization of HaloCam for the quantitative analysis of halo displays

Forster, Linda and Seefeldner, Meinhard and Baumgartner, Andreas and Kölling, Tobias and Mayer, Bernhard (2020) Ice crystal characterization in cirrus clouds II: radiometric characterization of HaloCam for the quantitative analysis of halo displays. Atmospheric Measurement Techniques (AMT), 13 (7), pp. 3977-3991. Copernicus Publications. doi: 10.5194/amt-13-3977-2020. ISSN 1867-1381.

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Official URL: https://amt.copernicus.org/articles/13/3977/2020/

Abstract

We present a procedure for geometric, spectral, and absolute radiometric characterization of the weather-proof RGB camera HaloCamRAW and demonstrate its application in a case study. This characterization procedure can be generalized to other RGB camera systems with similar field of view. HaloCamRAW is part of the automated halo observation system HaloCam and designed for the quantitative analysis of halo displays. The geometric calibration was performed using a chessboard pattern to estimate camera matrix and distortion coefficients. For the radiometric characterization of HaloCamRAW, the dark signal and vignetting effect were determined to correct the measured signal. Furthermore, the spectral response of the RGB sensor and the linearity of its radiometric response were characterized. The absolute radiometric response was estimated by cross calibrating HaloCamRAW against the completely characterized spectrometer of the Munich Aerosol Cloud Scanner (specMACS). For a typical measurement signal the relative (absolute) radiometric uncertainty amounts to 2.8 % (5.0 %), 2.4 % (5.8 %), and 3.3 % (11.8 %) for the red, green, and blue channel, respectively. The absolute radiometric uncertainty estimate is larger mainly due to the inhomogeneity of the scene used for cross calibration and the absolute radiometric uncertainty of specMACS. Geometric and radiometric characterization of HaloCamRAW were applied to a scene with a 22° halo observed on 21 April 2016. The observed radiance distribution and 22° halo ratio compared well with radiative transfer simulations assuming a range of ice crystal habits and surface roughness values. This application demonstrates the potential of developing a retrieval method for ice crystal properties, such as ice crystal size, shape, and surface roughness using calibrated HaloCamRAW observations together with radiative transfer simulations.

Item URL in elib:https://elib.dlr.de/139774/
Document Type:Article
Title:Ice crystal characterization in cirrus clouds II: radiometric characterization of HaloCam for the quantitative analysis of halo displays
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Forster, LindaUNSPECIFIEDhttps://orcid.org/0000-0002-9738-9571UNSPECIFIED
Seefeldner, MeinhardMeteorologisches Institut, Ludwig-Maximilians-Universität, Munich, GermanyUNSPECIFIEDUNSPECIFIED
Baumgartner, AndreasUNSPECIFIEDhttps://orcid.org/0000-0002-8495-5407UNSPECIFIED
Kölling, TobiasMeteorologisches Institut, Ludwig-Maximilians-Universität, Munich, GermanyUNSPECIFIEDUNSPECIFIED
Mayer, BernhardMeteorologisches Institut, Ludwig-Maximilians-Universität, Munich, Germany; Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt, Oberpfaffenhofen, GermanyUNSPECIFIEDUNSPECIFIED
Date:23 July 2020
Journal or Publication Title:Atmospheric Measurement Techniques (AMT)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:13
DOI:10.5194/amt-13-3977-2020
Page Range:pp. 3977-3991
Publisher:Copernicus Publications
ISSN:1867-1381
Status:Published
Keywords:camera, halo displays, sun-tracking, calibration, geometric, spectral, radiometric, linearity
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Atmospheric and climate research, Vorhaben Spectroscopic Methods in Remote Sensing (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Experimental Methods
Deposited By: Baumgartner, Andreas
Deposited On:17 Dec 2020 19:14
Last Modified:17 Dec 2020 19:14

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