Multiscale interactions in an idealized Walker cell: Simulations with sparse space-time superparameterization

AMS Citation:
Slawinska, J., O. Pauluis, A. J. Majda, and W. W. Grabowski, 2015: Multiscale interactions in an idealized Walker cell: Simulations with sparse space-time superparameterization. Monthly Weather Review, 143, 563-580, doi:10.1175/MWR-D-14-00082.1.
Resource Type:article
Title:Multiscale interactions in an idealized Walker cell: Simulations with sparse space-time superparameterization
Abstract: This paper discusses the sparse space-time superparameterization (SSTSP) algorithm and evaluates its ability to represent interactions between moist convection and the large-scale circulation in the context of a Walker cell flow over a planetary scale two-dimensional domain. The SSTSP represents convective motions in each column of the large-scale model by embedding a cloud-resolving model, and relies on a sparse sampling in both space and time to reduce computational cost of explicit simulation of convective processes. Simulations are performed varying the spatial compression and/or temporal acceleration, and results are compared to the cloud-resolving simulation reported previously. The algorithm is able to reproduce a broad range of circulation features for all temporal accelerations and spatial compressions, but significant biases are identified. Precipitation tends to be too intense and too localized over warm waters when compared to the cloud-resolving simulations. It is argued that this is because coherent propagation of organized convective systems from one large-scale model column to another is difficult when superparameterization is used, as noted in previous studies. The Walker cell in all simulations exhibits low-frequency variability on a time scale of about 20 days, characterized by four distinctive stages: suppressed, intensification, active, and weakening. The SSTSP algorithm captures spatial structure and temporal evolution of the variability. This reinforces the confidence that SSTSP preserves fundamental interactions between convection and the large-scale flow, and offers a computationally efficient alternative to traditional convective parameterizations.
Peer Review:Refereed
Copyright Information:Copyright 2015 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be "fair use" under Section 107 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Law (17 USC, as revised by P.L. 94-553) does not require the Society's permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statements, requires written permission or license from the AMS. Additional details are provided in the AMS Copyright Policies, available from the AMS at 617-227-2425 or Permission to place a copy of this work on this server has been provided by the AMS. The AMS does not guarantee that the copy provided here is an accurate copy of the published work.
OpenSky citable URL: ark:/85065/d7pz59z5
Publisher's Version: 10.1175/MWR-D-14-00082.1
  • Joanna Slawinska
  • Olivier Pauluis
  • Andrew Majda
  • Wojciech Grabowski - NCAR/UCAR
  • Random Profile


    Recent & Upcoming Visitors