Impact of lateral boundary errors on the simulation of clouds with a non-hydrostatic regional climate model

Impact of lateral boundary errors on the simulation of clouds with a non-hydrostatic regional... AbstractA non-hydrostatic regional climate limited-area model (LAM) was used to analyze lateral boundary condition (LBC) errors and their influence on the uncertainties of regional models. Simulations using the fully compressible non-hydrostatic LAM (D-NICAM) were compared against the corresponding global quasi-uniform-grid Non-hydrostatic ICosahedral Atmospheric Model (NICAM) and a stretched-grid counterpart (S-NICAM). By this approach of sharing the same dynamical core and physical schemes, possible causes of model bias and LBC errors are isolated. The simulations were performed for a 395-day period from March 2011 through March 2012 with the horizontal grid intervals of 14 km, 28 km and 56 km at the region of interest. The resulting temporal mean statistics of the temperatures at 500 hPa were generally well correlated between the global and regional simulations, indicating that LBC errors had a minor impact on the large-scale flows. However, the time-varying statistics of the surface precipitation showed that the LBC errors lead to unpredictability of convective precipitation, which affected the mean statistics of the precipitation distributions but induced only minor influences on the large-scale systems. Specifically, extra-tropical cyclones and orographic precipitation are not severely affected. We conclude that the errors of the precipitation distribution are not due to the difference of the model configurations, but due to the uncertainty of the system itself. This study suggests that applications of ensemble runs, internal nudging, or simulations with longer time scales are needed to obtain more statistically significant results of the precipitation distribution in regional climate models. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Monthly Weather Review American Meteorological Society

Impact of lateral boundary errors on the simulation of clouds with a non-hydrostatic regional climate model

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0493
D.O.I.
10.1175/MWR-D-17-0158.1
Publisher site
See Article on Publisher Site

Abstract

AbstractA non-hydrostatic regional climate limited-area model (LAM) was used to analyze lateral boundary condition (LBC) errors and their influence on the uncertainties of regional models. Simulations using the fully compressible non-hydrostatic LAM (D-NICAM) were compared against the corresponding global quasi-uniform-grid Non-hydrostatic ICosahedral Atmospheric Model (NICAM) and a stretched-grid counterpart (S-NICAM). By this approach of sharing the same dynamical core and physical schemes, possible causes of model bias and LBC errors are isolated. The simulations were performed for a 395-day period from March 2011 through March 2012 with the horizontal grid intervals of 14 km, 28 km and 56 km at the region of interest. The resulting temporal mean statistics of the temperatures at 500 hPa were generally well correlated between the global and regional simulations, indicating that LBC errors had a minor impact on the large-scale flows. However, the time-varying statistics of the surface precipitation showed that the LBC errors lead to unpredictability of convective precipitation, which affected the mean statistics of the precipitation distributions but induced only minor influences on the large-scale systems. Specifically, extra-tropical cyclones and orographic precipitation are not severely affected. We conclude that the errors of the precipitation distribution are not due to the difference of the model configurations, but due to the uncertainty of the system itself. This study suggests that applications of ensemble runs, internal nudging, or simulations with longer time scales are needed to obtain more statistically significant results of the precipitation distribution in regional climate models.

Journal

Monthly Weather ReviewAmerican Meteorological Society

Published: Oct 16, 2017

References

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