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Volume 10, issue 1 | Copyright
Geosci. Model Dev., 10, 57-83, 2017
https://doi.org/10.5194/gmd-10-57-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Methods for assessment of models 05 Jan 2017

Methods for assessment of models | 05 Jan 2017

ASoP (v1.0): a set of methods for analyzing scales of precipitation in general circulation models

Nicholas P. Klingaman1, Gill M. Martin2, and Aurel Moise3 Nicholas P. Klingaman et al.
  • 1National Centre for Atmospheric Science–Climate and Department of Meteorology, University of Reading, Earley Gate, P.O. Box 243, Reading, Berkshire RG6 6BB, UK
  • 2Met Office, Exeter, UK
  • 3Bureau of Meteorology, Melbourne, Australia

Abstract. General circulation models (GCMs) have been criticized for their failure to represent the observed scales of precipitation, particularly in the tropics where simulated daily rainfall is too light, too frequent and too persistent. Previous assessments have focused on temporally or spatially averaged precipitation, such as daily means or regional averages. These evaluations offer little actionable information for model developers, because the interactions between the resolved dynamics and parameterized physics that produce precipitation occur at the native gridscale and time step.

We introduce a set of diagnostics (Analyzing Scales of Precipitation, version 1.0 – ASoP1) to compare the spatial and temporal scales of precipitation across GCMs and observations, which can be applied to data ranging from the gridscale and time step to regional and sub-monthly averages. ASoP1 measures the spectrum of precipitation intensity, temporal variability as a function of intensity and spatial and temporal coherence. When applied to time step, gridscale tropical precipitation from 10 GCMs, the diagnostics reveal that, far from the dreary persistent light rainfall implied by daily mean data, most models produce a broad range of time step intensities that span 1–100mmday−1. Models show widely varying spatial and temporal scales of time step precipitation. Several GCMs show concerning quasi-random behavior that may influence and/or alter the spectrum of atmospheric waves. Averaging precipitation to a common spatial ( ≈ 600km) or temporal (3h) resolution substantially reduces variability among models, demonstrating that averaging hides a wealth of information about intrinsic model behavior. When compared against satellite-derived analyses at these scales, all models produce features that are too large and too persistent.

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Weather and climate models show large errors in the frequency, intensity and persistence of daily rainfall, particularly in the tropics. We introduce a set of diagnostics to reveal the spatial and temporal scales of precipitation in models and compare them to satellite observations to inform development efforts. Although models show similar errors in 3 h precipitation, at the time step and gridpoint level some produce coherent precipitation and others exhibit worrying quasi-random behavior.
Weather and climate models show large errors in the frequency, intensity and persistence of...
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