Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations
Riming is an efficient process of converting liquid cloud water into ice and plays an important role in the formation of precipitation in cold clouds. Due to the rapid increase in ice particle mass, riming enhances the particle's terminal velocity, which can be detected by ground-based vertical...
Published in: | Journal of the Atmospheric Sciences |
---|---|
Main Authors: | , |
Other Authors: | , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
American Meteorological Society
2021
|
Subjects: | |
Online Access: | http://hdl.handle.net/10138/324277 |
id |
ftunivhelsihelda:oai:helda.helsinki.fi:10138/324277 |
---|---|
record_format |
openpolar |
institution |
Open Polar |
collection |
HELDA – University of Helsinki Open Repository |
op_collection_id |
ftunivhelsihelda |
language |
English |
topic |
Climatology Cloud microphysics Cloud water/phase Ice particles Icing Cloud retrieval IN-SITU OBSERVATIONS POLARIMETRIC RADAR MICROPHYSICAL PROPERTIES SNOWFALL MICROPHYSICS WINTER STORMS FALL SPEED AGGREGATION GROWTH PARAMETERIZATION 114 Physical sciences |
spellingShingle |
Climatology Cloud microphysics Cloud water/phase Ice particles Icing Cloud retrieval IN-SITU OBSERVATIONS POLARIMETRIC RADAR MICROPHYSICAL PROPERTIES SNOWFALL MICROPHYSICS WINTER STORMS FALL SPEED AGGREGATION GROWTH PARAMETERIZATION 114 Physical sciences Kneifel, Stefan Moisseev, Dmitri Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations |
topic_facet |
Climatology Cloud microphysics Cloud water/phase Ice particles Icing Cloud retrieval IN-SITU OBSERVATIONS POLARIMETRIC RADAR MICROPHYSICAL PROPERTIES SNOWFALL MICROPHYSICS WINTER STORMS FALL SPEED AGGREGATION GROWTH PARAMETERIZATION 114 Physical sciences |
description |
Riming is an efficient process of converting liquid cloud water into ice and plays an important role in the formation of precipitation in cold clouds. Due to the rapid increase in ice particle mass, riming enhances the particle's terminal velocity, which can be detected by ground-based vertically pointing cloud radars if the effect of vertical air motions can be sufficiently mitigated. In our study, we first revisit a previously published approach to relate the radar mean Doppler velocity (MDV) to rime mass fraction (FR) using a large ground-based in situ dataset. This relation is then applied to multiyear datasets of cloud radar observations collected at four European sites covering polluted central European, clean maritime, and Arctic climatic conditions. We find that riming occurs in 1%-8% of the nonconvective ice containing clouds with median FR between 0.5 and 0.6. Both the frequency of riming and FR reveal relatively small variations for different seasons. In contrast to previous studies, which suggested enhanced riming for clean environments, our statistics indicate the opposite; however, the differences between the locations are overall small. We find a very strong relation between the frequency of riming and temperature. While riming is rare at temperatures lower than -12 degrees C, it strongly increases toward 0 degrees C. Previous studies found a very similar temperature dependence for the amount and droplet size of supercooled liquid water, which might be closely connected to the riming signature found in this study. In contrast to riming frequency, we find almost no temperature dependence for FR. Peer reviewed |
author2 |
Institute for Atmospheric and Earth System Research (INAR) Department of Physics Radar Meteorology group |
format |
Article in Journal/Newspaper |
author |
Kneifel, Stefan Moisseev, Dmitri |
author_facet |
Kneifel, Stefan Moisseev, Dmitri |
author_sort |
Kneifel, Stefan |
title |
Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations |
title_short |
Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations |
title_full |
Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations |
title_fullStr |
Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations |
title_full_unstemmed |
Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations |
title_sort |
long-term statistics of riming in nonconvective clouds derived from ground-based doppler cloud radar observations |
publisher |
American Meteorological Society |
publishDate |
2021 |
url |
http://hdl.handle.net/10138/324277 |
long_lat |
ENVELOPE(6.483,6.483,62.567,62.567) |
geographic |
Arctic Rime |
geographic_facet |
Arctic Rime |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
10.1175/JAS-D-20-0007.1 This study and all contributions by SK have been funded by the German Research Foundation [Deutsche Forschungsgemeinschaft (DFG)] under Grant KN 1112/2-1 as part of the Emmy-Noether Group OPTIMIce. DM was supported by the Academy of Finland Finnish Center of Excellence program (Grant 307331) and ERA-PLANET, transnational project iCUPE (Grant Agreement 689443), funded under the EU Horizon 2020 Framework Programme. We especially acknowledge the enormous efforts of the responsible technicians and scientists at the four research sites for collecting high-quality long-term radar observations and for providing their data to CloudNet. All data for this study have been obtained through the CloudNet data portal (http://devcloudnet.fmi.fi/).We acknowledge the ACTRIS-2 project (European Commission Contract H2020-INFRAIA, Grant 654109) for providing the target classification, which was produced by the Finnish Meteorological Institute using measurements from the four sites. Relevant data for developing the methodology were provided by DFG-funded Core Facility (JOYCE-CF) underDFG Research Grant LO 901/7-1. We also would like to thank Bernhard Pospichal and Axel Seifert for fruitful discussions and are grateful to Ewan O'Connor for his support regarding CloudNet data access. Kneifel , S & Moisseev , D 2020 , ' Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations ' , Journal of the Atmospheric Sciences , vol. 77 , no. 10 , pp. 3495-3508 . https://doi.org/10.1175/JAS-D-20-0007.1 ORCID: /0000-0002-4575-0409/work/86483650 7233b57c-0613-465d-b790-d7f774b7fab5 http://hdl.handle.net/10138/324277 000589821600012 |
op_rights |
openAccess info:eu-repo/semantics/openAccess |
container_title |
Journal of the Atmospheric Sciences |
container_volume |
77 |
container_issue |
10 |
container_start_page |
3495 |
op_container_end_page |
3508 |
_version_ |
1787422670063665152 |
spelling |
ftunivhelsihelda:oai:helda.helsinki.fi:10138/324277 2024-01-07T09:41:52+01:00 Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations Kneifel, Stefan Moisseev, Dmitri Institute for Atmospheric and Earth System Research (INAR) Department of Physics Radar Meteorology group 2021-01-08T11:32:01Z 14 application/pdf http://hdl.handle.net/10138/324277 eng eng American Meteorological Society 10.1175/JAS-D-20-0007.1 This study and all contributions by SK have been funded by the German Research Foundation [Deutsche Forschungsgemeinschaft (DFG)] under Grant KN 1112/2-1 as part of the Emmy-Noether Group OPTIMIce. DM was supported by the Academy of Finland Finnish Center of Excellence program (Grant 307331) and ERA-PLANET, transnational project iCUPE (Grant Agreement 689443), funded under the EU Horizon 2020 Framework Programme. We especially acknowledge the enormous efforts of the responsible technicians and scientists at the four research sites for collecting high-quality long-term radar observations and for providing their data to CloudNet. All data for this study have been obtained through the CloudNet data portal (http://devcloudnet.fmi.fi/).We acknowledge the ACTRIS-2 project (European Commission Contract H2020-INFRAIA, Grant 654109) for providing the target classification, which was produced by the Finnish Meteorological Institute using measurements from the four sites. Relevant data for developing the methodology were provided by DFG-funded Core Facility (JOYCE-CF) underDFG Research Grant LO 901/7-1. We also would like to thank Bernhard Pospichal and Axel Seifert for fruitful discussions and are grateful to Ewan O'Connor for his support regarding CloudNet data access. Kneifel , S & Moisseev , D 2020 , ' Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations ' , Journal of the Atmospheric Sciences , vol. 77 , no. 10 , pp. 3495-3508 . https://doi.org/10.1175/JAS-D-20-0007.1 ORCID: /0000-0002-4575-0409/work/86483650 7233b57c-0613-465d-b790-d7f774b7fab5 http://hdl.handle.net/10138/324277 000589821600012 openAccess info:eu-repo/semantics/openAccess Climatology Cloud microphysics Cloud water/phase Ice particles Icing Cloud retrieval IN-SITU OBSERVATIONS POLARIMETRIC RADAR MICROPHYSICAL PROPERTIES SNOWFALL MICROPHYSICS WINTER STORMS FALL SPEED AGGREGATION GROWTH PARAMETERIZATION 114 Physical sciences Article acceptedVersion 2021 ftunivhelsihelda 2023-12-14T00:08:49Z Riming is an efficient process of converting liquid cloud water into ice and plays an important role in the formation of precipitation in cold clouds. Due to the rapid increase in ice particle mass, riming enhances the particle's terminal velocity, which can be detected by ground-based vertically pointing cloud radars if the effect of vertical air motions can be sufficiently mitigated. In our study, we first revisit a previously published approach to relate the radar mean Doppler velocity (MDV) to rime mass fraction (FR) using a large ground-based in situ dataset. This relation is then applied to multiyear datasets of cloud radar observations collected at four European sites covering polluted central European, clean maritime, and Arctic climatic conditions. We find that riming occurs in 1%-8% of the nonconvective ice containing clouds with median FR between 0.5 and 0.6. Both the frequency of riming and FR reveal relatively small variations for different seasons. In contrast to previous studies, which suggested enhanced riming for clean environments, our statistics indicate the opposite; however, the differences between the locations are overall small. We find a very strong relation between the frequency of riming and temperature. While riming is rare at temperatures lower than -12 degrees C, it strongly increases toward 0 degrees C. Previous studies found a very similar temperature dependence for the amount and droplet size of supercooled liquid water, which might be closely connected to the riming signature found in this study. In contrast to riming frequency, we find almost no temperature dependence for FR. Peer reviewed Article in Journal/Newspaper Arctic HELDA – University of Helsinki Open Repository Arctic Rime ENVELOPE(6.483,6.483,62.567,62.567) Journal of the Atmospheric Sciences 77 10 3495 3508 |