Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations

The statistics of cloud base vertical velocity simulated by the non-hydrostatic mesoscale model AROME are compared with Cloudnet remote sensing observations at two locations: the ARM SGP site in central Oklahoma, and the DWD observatory at Lindenberg, Germany. The results show that AROME significant...

Full description

Bibliographic Details
Main Authors: J. Tonttila, E. J. O'Connor, S. Niemelä, P. Räisänen, H. Järvinen
Format: Article
Language:English
Published: Copernicus Publications 2011-09-01
Series:Atmospheric Chemistry and Physics
Online Access:http://www.atmos-chem-phys.net/11/9207/2011/acp-11-9207-2011.pdf
id doaj-bb740d55c5354b4c82f1e742eea2cb0e
record_format Article
spelling doaj-bb740d55c5354b4c82f1e742eea2cb0e2020-11-24T23:29:44ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242011-09-0111179207921810.5194/acp-11-9207-2011Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observationsJ. TonttilaE. J. O'ConnorS. NiemeläP. RäisänenH. JärvinenThe statistics of cloud base vertical velocity simulated by the non-hydrostatic mesoscale model AROME are compared with Cloudnet remote sensing observations at two locations: the ARM SGP site in central Oklahoma, and the DWD observatory at Lindenberg, Germany. The results show that AROME significantly underestimates the variability of vertical velocity at cloud base compared to observations at their nominal resolution; the standard deviation of vertical velocity in the model is typically 4–8 times smaller than observed, and even more during the winter at Lindenberg. Averaging the observations to the horizontal scale corresponding to the physical grid spacing of AROME (2.5 km) explains 70–80 % of the underestimation by the model. Further averaging of the observations in the horizontal is required to match the model values for the standard deviation in vertical velocity. This indicates an effective horizontal resolution for the AROME model of at least 10 km in the presented case. Adding a TKE-term on the resolved grid-point vertical velocity can compensate for the underestimation, but only for altitudes below approximately the boundary layer top height. The results illustrate the need for a careful consideration of the scales the model is able to accurately resolve, as well as for a special treatment of sub-grid scale variability of vertical velocities in kilometer-scale atmospheric models, if processes such as aerosol-cloud interactions are to be included in the future.http://www.atmos-chem-phys.net/11/9207/2011/acp-11-9207-2011.pdf
collection DOAJ
language English
format Article
sources DOAJ
author J. Tonttila
E. J. O'Connor
S. Niemelä
P. Räisänen
H. Järvinen
spellingShingle J. Tonttila
E. J. O'Connor
S. Niemelä
P. Räisänen
H. Järvinen
Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations
Atmospheric Chemistry and Physics
author_facet J. Tonttila
E. J. O'Connor
S. Niemelä
P. Räisänen
H. Järvinen
author_sort J. Tonttila
title Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations
title_short Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations
title_full Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations
title_fullStr Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations
title_full_unstemmed Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations
title_sort cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations
publisher Copernicus Publications
series Atmospheric Chemistry and Physics
issn 1680-7316
1680-7324
publishDate 2011-09-01
description The statistics of cloud base vertical velocity simulated by the non-hydrostatic mesoscale model AROME are compared with Cloudnet remote sensing observations at two locations: the ARM SGP site in central Oklahoma, and the DWD observatory at Lindenberg, Germany. The results show that AROME significantly underestimates the variability of vertical velocity at cloud base compared to observations at their nominal resolution; the standard deviation of vertical velocity in the model is typically 4–8 times smaller than observed, and even more during the winter at Lindenberg. Averaging the observations to the horizontal scale corresponding to the physical grid spacing of AROME (2.5 km) explains 70–80 % of the underestimation by the model. Further averaging of the observations in the horizontal is required to match the model values for the standard deviation in vertical velocity. This indicates an effective horizontal resolution for the AROME model of at least 10 km in the presented case. Adding a TKE-term on the resolved grid-point vertical velocity can compensate for the underestimation, but only for altitudes below approximately the boundary layer top height. The results illustrate the need for a careful consideration of the scales the model is able to accurately resolve, as well as for a special treatment of sub-grid scale variability of vertical velocities in kilometer-scale atmospheric models, if processes such as aerosol-cloud interactions are to be included in the future.
url http://www.atmos-chem-phys.net/11/9207/2011/acp-11-9207-2011.pdf
work_keys_str_mv AT jtonttila cloudbaseverticalvelocitystatisticsacomparisonbetweenanatmosphericmesoscalemodelandremotesensingobservations
AT ejoconnor cloudbaseverticalvelocitystatisticsacomparisonbetweenanatmosphericmesoscalemodelandremotesensingobservations
AT sniemela cloudbaseverticalvelocitystatisticsacomparisonbetweenanatmosphericmesoscalemodelandremotesensingobservations
AT praisanen cloudbaseverticalvelocitystatisticsacomparisonbetweenanatmosphericmesoscalemodelandremotesensingobservations
AT hjarvinen cloudbaseverticalvelocitystatisticsacomparisonbetweenanatmosphericmesoscalemodelandremotesensingobservations
_version_ 1725544137454780416