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UID:submissions.supercomputing.org_SC24_sess533_post263@linklings.com
SUMMARY:DART-X: Software Infrastructure for Prototyping In-Memory Data Tra
 nsfer Between Ensemble Data Assimilation and Coupled Earth Systems Models
DESCRIPTION:Anh Pham (Mount Holyoke College, National Center for Atmospher
 ic Research (NCAR)); Suman Shekhar (Rutgers University, National Center fo
 r Atmospheric Research (NCAR)); and Helen Kershaw, Dan Amrhein, and Ufuk T
 uruncoglu (National Center for Atmospheric Research (NCAR))\n\nData assimi
 lation (DA) integrates real-world data into coupled climate models, enhanc
 ing prediction accuracy and capturing Earth system complexity. NCAR’s Data
  Assimilation Research Testbed (DART) is an ensemble DA tool for climate p
 redictions with NCAR’s Community Earth System Model (CESM). Traditionally,
  DART has modified "restart" files written to disk to influence models, in
 volving significant I/O and stop/restart processes, which are computationa
 lly expensive, even on large supercomputers.\n\nThis work explores using t
 he National Unified Operational Prediction Capability (NUOPC) layer to ena
 ble direct in-memory data transfer between DART and CESM. We describe the 
 development of a NUOPC cap for DART, focusing on strategies for full softw
 are integration and minimal disruption to existing functionalities. The in
 frastructure addresses software incompatibilities and includes decisions o
 n tools, frameworks, and workflow optimizations. This approach aims to enh
 ance efficiency and scalability in data assimilation, offering the first p
 rototype for in-memory data transfer between DART and CESM.\n\nRegistratio
 n Category: Tech Program Reg Pass, Exhibits Reg Pass\n\nSession Chairs: Ay
 esha Afzal (Friedrich-Alexander University, Erlangen-Nuremberg; Erlangen N
 ational High Performance Computing Center); Sally Ellingson (University of
  Kentucky); and Alan Sussman (University of Maryland)\n\n
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