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A single-column model ensemble approach applied to the TWP-ICE experiment

Davies, L., Jakob, C., Cheung, K., Del Genio, A., Hill, A., Hume, T., Keane, R. J., Komori, T., Larson, V. E., Lin, Y., Liu, X., Neilsen, B. J., Petch, J., Plant, R. S., Singh, M. S., Shi, X., Song, X., Wang, W., Whitall, M. A., Wolf, A. , Xie, S. and Zhang, G. (2013) A single-column model ensemble approach applied to the TWP-ICE experiment. Journal of Geophysical Research, 118 (12). pp. 6544-6563. ISSN 0148-0227

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To link to this item DOI: 10.1002/jgrd.50450

Abstract/Summary

Single-column models (SCM) are useful test beds for investigating the parameterization schemes of numerical weather prediction and climate models. The usefulness of SCM simulations are limited, however, by the accuracy of the best estimate large-scale observations prescribed. Errors estimating the observations will result in uncertainty in modeled simulations. One method to address the modeled uncertainty is to simulate an ensemble where the ensemble members span observational uncertainty. This study first derives an ensemble of large-scale data for the Tropical Warm Pool International Cloud Experiment (TWP-ICE) based on an estimate of a possible source of error in the best estimate product. These data are then used to carry out simulations with 11 SCM and two cloud-resolving models (CRM). Best estimate simulations are also performed. All models show that moisture-related variables are close to observations and there are limited differences between the best estimate and ensemble mean values. The models, however, show different sensitivities to changes in the forcing particularly when weakly forced. The ensemble simulations highlight important differences in the surface evaporation term of the moisture budget between the SCM and CRM. Differences are also apparent between the models in the ensemble mean vertical structure of cloud variables, while for each model, cloud properties are relatively insensitive to forcing. The ensemble is further used to investigate cloud variables and precipitation and identifies differences between CRM and SCM particularly for relationships involving ice. This study highlights the additional analysis that can be performed using ensemble simulations and hence enables a more complete model investigation compared to using the more traditional single best estimate simulation only.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:38946
Uncontrolled Keywords:TWP-ICE; Single Column Model; Ensemble
Publisher:American Geophysical Union

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