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Ensemble Kalman Filter for Open GGCM

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Technical Report,15 Jul 2015,14 Jul 2018

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University of New Hampshire Durham United States

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The overall goal of the project is to combine the NCAR Data Assimilation Research Testbed DART with the OpenGGCM geospace model to produce a data assimilation capable geospace model. DART is a software framework that implements an Ensemble Kalman Filter EnKF and has been used with some 30 different models, mostly from the atmospheric and oceanic domains. OpenGGCM is the first magnetosphere-ionosphere ever to be combined with DART. We identified the prognostic and diagnostic variables in OpenGGCM which are suitable for data assimilation and for which sufficient data are available. Specifically, we use the ionosphere oxygen ion O density as a proxy for ionospheric electron e- density as the primary prognostic variable. The ionosphere potential, magnetic perturbations on the ground and in near space, and a subset of space based plasma data, such as DMSP precipitation and density data were identified as suitable diagnostic data for the data assimilation. A number of technical issues were solved to couple OpenGGCM with DART. Both OpenGGCM and DART run on massive parallel computers with 100s to 1000s of processes. Synchronization and data exchange occur through file exchange. We developed, or adapted, as appropriate, netcdf based protocols and implemented them. These were first put in place only for Oe- assimilation of COSMIC data. Since the O grid in the CTIM sub model of OpenGGCM is highly skewed, we implemented a new suite of interpolation routines. We conducted so-called hop tests, where all data exchange and synchronization takes place, but no actual data assimilation is performed. In other words, DART returns unmodified fields to all OpenGGCM instances. The coupled codes have passed the hop tests. We also prepared COSMIC data for assimilation runs of the 2013 St. Patricks day storm event.

Subject Categories:

  • Numerical Mathematics
  • Sociology and Law
  • Electricity and Magnetism

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