Developing large-scale forcing data for single-column and cloud-resolving models from the Mixed-Phase Arctic Cloud Experiment

[1] This study represents an effort to develop Single-Column Model (SCM) and Cloud-Resolving Model large-scale forcing data from a sounding array in the high latitudes. An objective variational analysis approach is used to process data collected from the Atmospheric Radiation Measurement Program (AR...

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Bibliographic Details
Published in:Journal of Geophysical Research
Main Authors: Xie, Shaocheng, Klein, Stephen A., Zhang, Minghua, Yio, John J., Cederwall, Richard T., McCoy, Renata
Language:unknown
Published: 2021
Subjects:
58 GEOSCIENCES
54 ENVIRONMENTAL SCIENCES
Arctic
north slope
Alaska
Online Access:http://www.osti.gov/servlets/purl/1305861
https://www.osti.gov/biblio/1305861
https://doi.org/10.1029/2005JD006950
Description
Summary:[1] This study represents an effort to develop Single-Column Model (SCM) and Cloud-Resolving Model large-scale forcing data from a sounding array in the high latitudes. An objective variational analysis approach is used to process data collected from the Atmospheric Radiation Measurement Program (ARM) Mixed-Phase Arctic Cloud Experiment (M-PACE), which was conducted over the North Slope of Alaska in October 2004. In this method the observed surface and top of atmosphere measurements are used as constraints to adjust the sounding data from M-PACE in order to conserve column-integrated mass, heat, moisture, and momentum. Several important technical and scientific issues related to the data analysis are discussed. It is shown that the analyzed data reasonably describe the dynamic and thermodynamic features of the Arctic cloud systems observed during M-PACE. Uncertainties in the analyzed forcing fields are roughly estimated by examining the sensitivity of those fields to uncertainties in the upper-air data and surface constraints that are used in the analysis. Impacts of the uncertainties in the analyzed forcing data on SCM simulations are discussed. Results from the SCM tests indicate that the bulk features of the observed Arctic cloud systems can be captured qualitatively well using the forcing data derived in this study, and major model errors can be detected despite the uncertainties that exist in the forcing data as illustrated by the sensitivity tests. Lastly, the possibility of using the European Center for Medium-Range Weather Forecasts analysis data to derive the large-scale forcing over the Arctic region is explored.

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