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Ground-based imaging remote sensing of ice clouds: uncertainties caused by sensor, method and atmosphere

Zinner, Tobias and Hausmann, Petra and Ewald, Florian and Bugliaro, Luca and Emde, Claudia and Mayer, Bernhard (2016) Ground-based imaging remote sensing of ice clouds: uncertainties caused by sensor, method and atmosphere. Atmospheric Measurement Techniques (AMT), 9, pp. 4615-4632. Copernicus Publications. DOI: [10.5194/amt-9-4615-2016] ISSN 1867-1381

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Official URL: http://www.atmos-meas-tech.net/9/4615/2016/

Abstract

In this study a method is introduced for the retrieval of optical thickness and effective particle size of ice clouds over a wide range of optical thickness from ground-based transmitted radiance measurements. Low optical thickness of cirrus clouds and their complex microphysics present a challenge for cloud remote sensing. In transmittance, the relationship between optical depth and radiance is ambiguous. To resolve this ambiguity the retrieval utilizes the spectral slope of radiance between 485 and 560 nm in addition to the commonly employed combination of a visible and a short-wave infrared wavelength. An extensive test of retrieval sensitivity was conducted using synthetic test spectra in which all parameters introducing uncertainty into the retrieval were varied systematically: ice crystal habit and aerosol properties, instrument noise, calibration uncertainty and the interpolation in the lookup table required by the retrieval process. The most important source of errors identified are uncertainties due to habit assumption: Averaged over all test spectra, systematic biases in the effective radius retrieval of several micrometre can arise. The statistical uncertainties of any individual retrieval can easily exceed 10 µm. Optical thickness biases are mostly below 1, while statistical uncertainties are in the range of 1 to 2.5. For demonstration and comparison to satellite data the retrieval is applied to observations by the Munich hyperspectral imager specMACS (spectrometer of the Munich Aerosol and Cloud Scanner) at the Schneefernerhaus observatory (2650 m a.s.l.) during the ACRIDICON-Zugspitze campaign in September and October 2012. Results are compared to MODIS and SEVIRI satellite-based cirrus retrievals (ACRIDICON – Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems; MODIS – Moderate Resolution Imaging Spectroradiometer; SEVIRI – Spinning Enhanced Visible and Infrared Imager). Considering the identified uncertainties for our ground-based approach and for the satellite retrievals, the comparison shows good agreement within the range of natural variability of the cloud situation in the direct surrounding.

Item URL in elib:https://elib.dlr.de/105652/
Document Type:Article
Title:Ground-based imaging remote sensing of ice clouds: uncertainties caused by sensor, method and atmosphere
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Zinner, TobiasLMU, MünchenUNSPECIFIED
Hausmann, PetraKIT, Campus Alpin, GarmischUNSPECIFIED
Ewald, FlorianDLR, IPAUNSPECIFIED
Bugliaro, LucaDLR, IPAUNSPECIFIED
Emde, ClaudiaLMU, MünchenUNSPECIFIED
Mayer, BernhardLMU, MünchenUNSPECIFIED
Date:20 September 2016
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:9
DOI :[10.5194/amt-9-4615-2016]
Page Range:pp. 4615-4632
Publisher:Copernicus Publications
ISSN:1867-1381
Status:Published
Keywords:Ground-based remote sensing, ice clouds, imaging spectrometer
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Atmosphären- und Klimaforschung
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Atmospheric Physics > Atmospheric Remote Sensing
Institute of Atmospheric Physics > Lidar
Deposited By: Bugliaro Goggia, Dr.rer.nat. Luca
Deposited On:12 Aug 2016 15:58
Last Modified:08 Mar 2018 18:10

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