14 April 2014

A Novel Technique to Diagnose the Spatio-Temporal Impact of Convective Systems

Summary

Novel approaches that go beyond simple comparisons of climatologies are necessary to rigorously evaluate models and to provide information on the processes that cause deficiencies in their simulations. In this study that is partially funded by DOE, researchers develop one such technique that systematically details the average characteristics of clouds, water vapor, and radiation and their spatio-temporal evolution in the vicinity of observed tropical deep convection, and to evaluate the EC-Earth climate model against a suite of satellite observations.  The authors collect thousands of snapshots of several observed and modeled fields at various time lags before and after intense rainfall events in the Central Pacific Ocean.  These are then averaged together to diagnose the composite-mean evolution of these fields every 3 hours for 48 hours before and after deep convection.

 

Observed upper tropospheric humidity, cloud fraction, outgoing longwave radiation, and albedo are substantially perturbed by deep convection, with anomalies that cover a broad horizontal area that extends well beyond the immediate vicinity of intense rain rates, and remain enhanced for several hours following deep convection. The EC-Earth model is able to capture most of these gross features, but exhibits numerous differences in the exact details, including important differences in the vertical structure of cloud anomalies. This work demonstrates the utility of this analysis framework in providing a detailed process-level comparison of modeled and observed responses of key fields to deep convection.

Contact
Colin M Zarzycki
University of Michigan
Publications
Zarzycki, CM, C Jablonowski, and MA Taylor.  2013.  "Diagnosing the Average Spatio-Temporal Impact of Convective Systems – Part 1: A methodology for evaluating climate models."  Atmospheric Chemistry and Physics 12043-12058, doi:10.5194/acp-13-12043-2013.
Acknowledgments

The authors would like to thank Jean-Jacques Morcrette, Peter Bechtold, Martin Evaldsson, Andreas Skyman, Ole-Martin Christensen, Benjamin Grandey, Stefan Buehler, and the anonymous reviewers for their technical and scientific help with this study.  The TMPA data were provided by the NASA/Goddard Space Flight Center’s Mesoscale Atmospheric Processes Laboratory and PPS. CERES data were obtained from the NASA Langley Research Center Atmospheric Science Data Center. The NASA CloudSat project provided the CloudSat-CALIPSO dataset. The contribution of Mark D. Zelinka was performed under the auspices of the US Department of Energy (DOE) by Lawrence Livermore National Laboratory (LLNL) under contract DE-AC52-07NA27344 and was supported by the LLNL Institutional Postdoctoral Program and by the Regional and Global Climate Modeling Program of the Office of Science at the DOE. Salomon Eliasson and Patrick Eriksson were supported by the Swedish National Space Board.