Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 1.0.0): EnVar implementation and evaluation

Details

• Journal Title:
  Geoscientific Model Development
• Personal Author:
  Liu, Zhiquan ; Snyder, Chris ; Guerrette, Jonathan J. ; Jung, Byoung-Joo ; Ban, Junmei ; Vahl, Steven ; Wu, Yali ; Trémolet, Yannick ; Auligné, Thomas ; Ménétrier, Benjamin ; Shlyaeva, Anna ; Herbener, Stephen ; Liu, Emily ; Holdaway, Daniel ; Johnson, Benjamin T.
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research)
• Description:
  On 24 September 2021, JEDI-MPAS 1.0.0, a new data assimilation (DA) system for the Model Prediction Across Scales – Atmosphere (MPAS-A) built on the software framework of the Joint Effort for Data assimilation Integration (JEDI) was publicly released for community use. Operating directly on the native MPAS unstructured mesh, JEDI-MPAS capabilities include three-dimensional variational (3DVar) and ensemble–variational (EnVar) schemes as well as the ensemble of DA (EDA) technique. On the observation side, one advanced feature in JEDI-MPAS is the full all-sky approach for satellite radiance DA with the introduction of hydrometeor analysis variables. This paper describes the formulation and implementation of EnVar for JEDI-MPAS. JEDI-MPAS 1.0.0 is evaluated with month-long cycling 3DEnVar experiments with a global 30–60 km dual-resolution configuration. The robustness and credible performance of JEDI-MPAS are demonstrated by establishing a benchmark non-radiance DA experiment, then incrementally adding microwave radiances from three sources: Advanced Microwave Sounding Unit-A (AMSU-A) temperature sounding channels in clear-sky scenes, AMSU-A window channels in all-sky scenes, and Microwave Humidity Sounder (MHS) water vapor channels in clear-sky scenes. JEDI-MPAS 3DEnVar behaves well with a substantial and significant positive impact obtained for almost all aspects of forecast verification when progressively adding more microwave radiance data. In particular, the day 5 forecast of the best-performing JEDI-MPAS experiment yields an anomaly correlation coefficient (ACC) of 0.8 for 500 hPa geopotential height, a gap of roughly a half day when compared to cold-start forecasts initialized from operational analyses of the National Centers for Environmental Prediction, whose ACC does not drop to 0.8 until a lead time of 5.5 d. This indicates JEDI-MPAS's great potential for both research and operations.
• Keywords:
  General Medicine
• Source:
  Geoscientific Model Development, 15(20), 7859-7878
• DOI:
  https://doi.org/10.5194/gmd-15-7859-2022
• ISSN:
  1991-9603
• Format:
  PDF
• Publisher:
  Copernicus GmbH
• Document Type:
  Journal Article
• Funding:
  Grant no. NA21OAR4310383
• License:
  https://creativecommons.org/licenses/by/4.0/
• Rights Information:
  CC BY
• Compliance:
  Library
• Main Document Checksum:
  urn:sha256:4e38a7c2f0baefd2c61708155b46e97549758ad1ca9d1fc311214d93b616441c
• Download URL:
  https://repository.library.noaa.gov/view/noaa/59158/noaa_59158_DS1.pdf
• File Type:
  [PDF - 2.54 MB ]