Universität zu Köln

Karrer, Markus ORCID: 0000-0002-1748-7252, Seifert, Axel, Ori, Davide ORCID: 0000-0002-9964-2200 and Kneifel, Stefan ORCID: 0000-0003-2220-2968 (2021). Improving the representation of aggregation in a two-moment microphysical scheme with statistics of multi-frequency Doppler radar observations. Atmos. Chem. Phys., 21 (22). S. 17133 - 17167. GOTTINGEN: COPERNICUS GESELLSCHAFT MBH. ISSN 1680-7324

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Abstract

Aggregation is a key microphysical process for the formation of precipitable ice particles. Its theoretical description involves many parameters and dependencies among different variables that are either insufficiently understood or difficult to accurately represent in bulk microphysics schemes. Previous studies have demonstrated the valuable information content of multi-frequency Doppler radar observations to characterize aggregation with respect to environmental parameters such as temperature. Comparisons with model simulations can reveal discrepancies, but the main challenge is to identify the most critical parameters in the aggregation parameterization, which can then be improved by using the observations as constraints. In this study, we systematically investigate the sensitivity of physical variables, such as number and mass density, as well as the forward-simulated multi-frequency and Doppler radar observables, to different parameters in a two-moment microphysics scheme. Our approach includes modifying key aggregation parameters such as the sticking efficiency or the shape of the size distribution. We also revise and test the impact of changing functional relationships (e.g., the terminal velocity-size relation) and underlying assumptions (e.g., the definition of the aggregation kernel). We test the sensitivity of the various components first in a single-column snowshaft model, which allows fast and efficient identification of the parameter combination optimally matching the observations. We find that particle properties, definition of the aggregation kernel, and size distribution width prove to be most important, while the sticking efficiency and the cloud ice habit have less influence. The setting which optimally matches the observations is then implemented in a 3D model using the identical scheme setup. Rerunning the 3D model with the new scheme setup for a multi-week period revealed that the large overestimation of aggregate size and terminal velocity in the model could be substantially reduced. The method presented is expected to be applicable to constrain other ice microphysical processes or to evaluate and improve other schemes.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Karrer, Markus UNSPECIFIED orcid.org/0000-0002-1748-7252 UNSPECIFIED Seifert, Axel UNSPECIFIED UNSPECIFIED UNSPECIFIED Ori, Davide UNSPECIFIED orcid.org/0000-0002-9964-2200 UNSPECIFIED Kneifel, Stefan UNSPECIFIED orcid.org/0000-0003-2220-2968 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-569049
DOI:	10.5194/acp-21-17133-2021
Journal or Publication Title:	Atmos. Chem. Phys.
Volume:	21
Number:	22
Page Range:	S. 17133 - 17167
Date:	2021
Publisher:	COPERNICUS GESELLSCHAFT MBH
Place of Publication:	GOTTINGEN
ISSN:	1680-7324
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language MIXED-PHASE CLOUDS; DUAL-WAVELENGTH RADAR; ICE CRYSTALS; SIZE DISTRIBUTIONS; WINTER STORMS; MODEL; PARAMETERIZATION; SNOW; SNOWFLAKES; PREDICTION Multiple languages Environmental Sciences; Meteorology & Atmospheric Sciences Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/56904