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The Impacts of Horizontal Grid Spacing and Cumulus Parameterization on Subseasonal Prediction in a Global Convection-Permitting Model.
- Source :
-
Monthly Weather Review . Dec2020, Vol. 148 Issue 12, p4747-4765. 19p. 1 Diagram, 1 Chart, 13 Graphs. - Publication Year :
- 2020
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Abstract
- Monthlong simulations targeting four Madden–Julian oscillation events made with several global model configurations are verified against observations to assess the roles of grid spacing and convective parameterization on the representation of tropical convection and midlatitude forecast skill. Specifically, the performance of a global convection-permitting model (CPM) configuration with a uniform 3-km mesh is compared to that of a global 15-km mesh with and without convective parameterization, and of a variable-resolution "channel" simulation using 3-km grid spacing only in the tropics with a scale-aware convection scheme. It is shown that global 3-km simulations produce realistic tropical precipitation statistics, except for an overall wet bias and delayed diurnal cycle. The channel simulation performs similarly, although with an unrealistically higher frequency of heavy rain. The 15-km simulations with and without cumulus schemes produce too much light and heavy tropical precipitation, respectively. Without convection parameterization, the 15-km global model produces unrealistically abundant, short-lived, and intense convection throughout the tropics. Only the global CPM configuration is able to capture eastward-propagating Madden–Julian oscillation events, and the 15-km runs favor stationary or westward-propagating convection organized at the planetary scale. The global 3-km CPM exhibits the highest extratropical forecast skill aloft and at the surface, particularly during week 3 of each hindcast. Although more cases are needed to confirm these results, this study highlights many potential benefits of using global CPMs for subseasonal forecasting. Furthermore, results show that alternatives to global convection-permitting resolution—using coarser or spatially variable resolution—feature compromises that may reduce their predictive performance. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MADDEN-Julian oscillation
*FORECASTING
*PARAMETERIZATION
Subjects
Details
- Language :
- English
- ISSN :
- 00270644
- Volume :
- 148
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Monthly Weather Review
- Publication Type :
- Academic Journal
- Accession number :
- 147852994
- Full Text :
- https://doi.org/10.1175/MWR-D-20-0171.1