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Space Weather, New Observation Operators, and the DRAS Project Highlight a Remarkable Year for JCSDA

Space Weather, New Observation Operators, and the DRAS Project Highlight a Remarkable Year for JCSDA

2024 was a big year for JCSDA with the launch of our space weather data assimilation project, several spack-stack releases that now support 14 HPC platforms and AWS cloud services, and the conclusion of JCSDA’s Disaster Relief Appropriations Supplemental (DRAS) project with exceptional success.

Bipartisan Support for Funding of JCSDA and JEDI as Critical to National Weather System

Bipartisan Support for Funding of JCSDA and JEDI as Critical to National Weather System

A bipartisan Dear Colleague Letter with 24 signatures has been sent to the Speaker, Minority Leader, and Appropriations Committee Chair and Ranking Member of the House of Representatives requesting funding for weather prediction innovation in any disaster supplemental or upcoming appropriations bills for science and technology, specifically highlighting the importance of JCSDA and JEDI to the next generation of forecast models.

Code Sprint Standardizes Variable Names Across JEDI

Code Sprint Standardizes Variable Names Across JEDI

Last month the JCSDA held a code sprint to begin standardizing variable names across JEDI, updating the generic code to match naming standards also adopted by the Common Community Physics Package (CCPP). This ensures that the JEDI data assimilation remains model agnostic, eliminates unnecessary code duplication, and ensures consistency across all JEDI model interfaces.

Using JEDI for Snow Depth Variational DA

Using JEDI for Snow Depth Variational DA

With recent advances, JEDI can now perform variational (2DVar) data assimilation for snow depth analysis. The flexibility of JEDI and the generic implementations of data assimilation algorithms (in OOPS) and background error covariances (in SABER, System Agnostic Background Error Representation) enabled a rapid development of this system for snow depth analysis. 

JCSDA Closes out DRAS Project with Enormous Success

JCSDA Closes out DRAS Project with Enormous Success

In 2019 JCSDA was awarded a Disaster Relief Appropriations Supplemental (DRAS) grant from NOAA to accelerate JEDI development and integration, with an emphasis on connecting that development to operational use and systems. The main goals were to accelerate towards use in operational NWS production suites, improving R2O and O2R, and advancing tools for use of observations, all of which were accomplished.

MPAS 3D-Var Experiments Added to Skylab Demonstrate Model-Agnostic Capabilities

MPAS 3D-Var Experiments Added to Skylab Demonstrate Model-Agnostic Capabilities

Adding MPAS experiments to Skylab not only expands Skylab’s functionality, it also allows the team to check that Skylab is being built to be model-agnostic as intended; JEDI and Skylab are both designed to work with all climate and weather models, requiring only a small amount of model-specific code to interface with each while the vast majority of Skylab and JEDI components are generic and remain the same from model to mod

JCSDA and COSMIC Co-Host the 10th Meeting of the International Radio Occultation Working Group

JCSDA and COSMIC Co-Host the 10th Meeting of the International Radio Occultation Working Group

On September 12-18 JCSDA and COSMIC jointly hosted the 10th meeting of the International Radio Occultation Working Group (IROWG) at UCAR Center Green in Boulder, Colorado. JCSDA’s Hui Shao, co-chair of IROWG, Ben Ruston, the OBS lead, and COSMIC’s director, Jan Weiss, formed the local organizing committee with the support team from UCAR.

JCSDA's Q1 Review Showcases Exciting Milestones

JCSDA's Q1 Review Showcases Exciting Milestones

On July 18 the JCSDA team met with our partners at NASA, NOAA, US Navy, US Air Force, and the UK Met Office to celebrate the last quarter of accomplishments and discuss goals for the upcoming quarter and year. Q1 milestones included beginning our space weather program and the establishment of a new model interface team.