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Multi-Scale Predictability with a New Coupled Non-Hydrostatic Global Model Over the Arctic

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Technical Report,01 May 2015,29 Jun 2018

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The Board of Regents of the University of Oklahoma Norman United States

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This study evaluates the performance of MPAS by examining a multi-scale feature that is common to the Arctic Tropopause polar vortices TPVs. TPVs are commonly observed tropopause-based vortices that originate in higher latitudes and are precursors to development of surface cyclones. Yet, very little is known about the role of TPVs in longer-term predictability. Fiigher latitude regions are a unique environment for growth and longevity of TPVs due to their relative position pole ward of the polar jet stream and limited heat and moisture. Spatial scales of TPVs range as high as -1000 km and lifetimes can exceed one month Lifetimes can be particularly long over the Arctic Ocean during summer months when the polar jet stream has a relatively weak influence. Given their longevity in the Arctic and their active role in surface cyclone formation and growth, we hypothesize that TPVs are an important component of longer-term prediction, and hence the predictability of sea ice. This hypothesis is tested by extending a new atmospheric nonhydrostatic dynamical core from the Model for Prediction Across Scales MPAS to a framework where MPAS is embedded within the Community Atmosphere Model CAM of the Community Earth System Model CESM, on medium to long range weather prediction week - months focusing on the Arctic region. This fully-coupled atmosphere-ocean-land-sea ice modeling system, referred to as MPAS-CESM, is a global model that allows for local refinement of the horizontal grid such that there is a smooth transition in resolution from the relatively coarse global mesh to finer mesh in regions of primary interest, which in this study is the Arctic region. A hierarchy of modeling experiments are performed summers of 2006 and2007 that evinced anticyclonic and cyclonic sea-level pressure anomalies, respectively, for a variety of mesh configurations and physical parameterizations.

Subject Categories:

  • Meteorology
  • Snow, Ice and Permafrost

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