Land Data Assimilation (DA) System - Earth Prediction Innovation Center

Land Data Assimilation (DA) System - Earth Prediction Innovation Center
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Land Data Assimilation (DA) System
On This Page:
Getting Started
Documentation & User Support
Developer Support
Releases
Other Links
Welcome
The Unified Forecast System (UFS) is a community-based, coupled, comprehensive Earth modeling system. NOAA’s operational model suite for numerical weather prediction (NWP) is quickly transitioning to the UFS from a number of different modeling systems. The UFS enables research, development, and contribution opportunities within the broader Weather Enterprise (including government, industry, and academia). For more information about the UFS, visit the
UFS Portal
Description
The UFS
Land Data Assimilation (DA) System
provides a flexible modular framework for land‑surface modeling and data assimilation within the Unified Forecast System (UFS). The standard UFS Land Data Assimilation (DA) System configuration is based on the
Noah Multi-Physics (Noah-MP)
land surface model (LSM) used in the UFS-Weather Model (WM). The Land DA Version 3.0.0 expands coupling options, observation support, and workflow automation while maintaining full compatibility with the Noah‑MP LSM used in the UFS-WM. It supports both ATMosphere–Land (ATML) coupling—allowing
FV3ATM
to run interactively with Noah‑MP—and
Data ATMosphere (DATM) forcing
configurations using
ECMWF Reanalysis 5th-generation data (ERA5)
or other forcing datasets (e.g., Global Soil Wetness Project Phase 3 (GSWP3) forcing). These options enable users to run fully coupled or land‑only experiments depending on their research needs.
The Land DA framework is built on the Joint Effort for Data assimilation Integration (JEDI) system, which includes:
Object-Oriented Prediction System (OOPS) for data assimilation algorithms (now including 3D‑Var and LETKF‑OI)
Interface for Observation Data Access (IODA) for observation formatting and ingestion
Unified Forward Operator (UFO), H(x) for the evaluation of model forecasts and observations
Land DA v3.0.0 expands its observation capabilities to include Interactive Multi‑sensor Snow and Ice Mapping System (IMS) snow products and introduces the H(x) forward operator mode for Soil Moisture Active Passive (SMAP) and
Soil Moisture Operational Products System (SMOPS)
soil‑moisture datasets, enabling forward‑operator evaluation workflows.
Key Noah‑MP state variables include soil moisture (both liquid and frozen), soil temperature, skin temperature, snow depth, snow water equivalent (SWE), snow density, canopy water content, and surface energy and water fluxes. Collectively, these variables describe the land surface’s physical and hydrological state, supporting diagnostic evaluation and enabling coupling with atmospheric and hydrologic models.
For publications that use or reference the UFS Land DA System, please include the following DOI citation.
UFS Development Team. (2026, April 9). Unified Forecast System (UFS) Land Data Assimilation (DA) System (Version v3.0.0). Zenodo.
Getting Started
Before running the Land DA System, users should determine which of the four levels of platform support tiers applies to their environment. Land DA v3.0.0 expands Tier‑1 support to include Ursa, Gaea‑C6, Orion, and Hercules, with nightly Workflow End‑to‑End (WE2E) tests executed across all platforms.
Most users can run the system on any machine using the updated
Land DA v3.0.0 Singularity/Apptainer container
, which now supports the Spack stack v1.9.2 and JEDI bundle aligned with the Global Data Assimilation System Application (GDASApp).
New users should begin with the
Land DA v3.0.0 User’s Guide
, which provides:
Instructions for cloning, building, and running the Land DA workflow
Guidance for running ATML‑coupled or DATM‑driven configurations
Steps for using the new Python‑based experiment setup tool
Examples of H(x) evaluation for SMAP/SMOPS and IMS snow DA
Updated test cases and input datasets available in the
Land‑DA data bucket
Users on non‑Tier‑1 systems should start with
Section 2.2,
Containerized Land DA Workflow
, which walks through running the full workflow using Singularity/Apptainer. Users can engage with developers through the
Land DA GitHub Discussions
’s and ask questions through the
Q & A
pages or contact the team directly at
support.epic@noaa.gov
GET CODE
Documentation & User Support
The Land DA User’s Guide has the most comprehensive information on the Land DA System. Users may need different versions of the User’s Guide depending on their goals:
Version
Description
Develop Branch
Documentation for the head of the
develop
branch. This may have gaps and errors.
Release v3.0.0
Documentation for the most recent release (v3.0.0).
Release v2.0.0
Documentation for the most recent release (v2.0.0).
Release v1.2.0
Documentation for the v1.2.0 release.
Release v1.1.0
Documentation for the v1.1.0 release.
Users can also get expert help through the
GitHub Discussions Q&A
Developer Support
The
Land DA Developer Information
page provides information on the Land DA hierarchical repository structure, developer support, and testing.
Releases
The latest release of the Land DA System is v3.0.0. See the
Releases
page for more information on current and past releases.
Land Data Assimilation (DA) System v3.0.0
Release Date: April 9, 2026
Release Description:
UFS Land DA v3.0.0 Release
Documentation:
GitHub Wiki
GitHub Repository
User’s Guide
Land Data Assimilation (DA) System v2.0.0
Release Date: October 30, 2024
Release Description:
The Land DA System v2.0.0 features a coupled configuration that combines the UFS WM Noah-MP land component with the data atmosphere (DATM) component and Joint Effort for Data assimilation Integration (JEDI) DA capabilities. Key features for this release include an updated workflow that better conforms to NCO
Implementation Standards
; integration of the
Unified Workflow (UW) Tools
open-source Python package to perform standard numerical weather prediction (NWP) workflow tasks; and validation of analysis outputs using both the CTest framework and the baseline regression test. Updates for this release include:
Model configuration:
In this release, the Land DA System uses a coupled configuration with the UFS WM Noah-MP land component and the DATM component to run a sample case with GSWP3 atmospheric forcing data. A global C96 model resolution is provided for an analysis experiment time period of January 1-31, 2000. The stand-alone driver option to run the Noah-MP routines directly from the Common Community Physics Package (CCPP) has been removed.
Workflow update:
The workflow was refactored to use a standard set of environment variables, file naming conventions, and directory structures defined in the
NCO Implementation Standards
in order to simplify and generalize the DA workflow system and to improve the troubleshooting process (see the workflow directory structure below). A structured, YAML-based Rocoto workflow management configuration approach was applied using
uwtools
to produce the Rocoto workflow XML file that manages a set of land DA cycling tasks, computational resources on a batch system, and computational job dependencies. Analysis output for the workflow end-to-end test can be validated with both the CTest framework and a baseline regression test that runs the Land DA workflow end-to-end. The post-processing task produces multiple plots, including histogram and scatter plots for the analysis task and restart plots for the forecast task.
RDHPCS Platform deployment and container support:
Tier-1 platforms: Hera, Orion, and Hercules (nightly Jenkins run for CTest on these platforms)
Singularity/Apptainer containers: Updates to the Singularity/Apptainer container (ubuntu22.04-intel-landda-release-public-v2.0.0.img) support the changes described above.
Observation database update:
The
Global Historical Climatology Network (GHCN) daily snow depth observation data
have been processed with the JEDI IODA converter for January 1-31, 2000. The IODA-processed data is accessible via the
Land DA data bucket
Library and JEDI version update:
The Joint Effort for Data assimilation Integration (JEDI) system is used to assimilate the GHCN snow depth observation data via the Local Ensemble Transform Kalman Filter (LETKF) algorithm. The required libraries and JEDI-bundle have been updated to
spack-stack v1.6.0
and
JEDI Skylab v7.0
Documentation:
The
v2.0.0 User’s Guide
has been updated to reflect these improvements to the Land DA System.
Known Issues:
The UFS-WM Noah-MP component can be configured to run in two-way coupled mode to the active FV3 atmosphere model through the Community Mediator for Earth Prediction Systems (CMEPS). An effort is underway to set an analysis baseline test case for the coupled FV3 and Noah-MP configuration.
Documentation:
GitHub Wiki
GitHub Repository
User’s Guide
Land Data Assimilation (DA) System v1.2.0
Release Date: 12/11/2023
Release Description:
The Land Data Assimilation (DA) System combines the Noah-MP land surface model with data assimilation capabilities into a user-friendly workflow. The Land DA workflow code base is charting a path forward to unify the Noah-MP forecast model with the UFS Weather Model (WM). Updates for this release include:
Integration of the UFS Noah-MP land component into the Land DA System for use as an alternative to the Common Community Physics Package (CCPP) Noah-MP LSM land driver. The coupling layer of the land component is developed using the Earth System Modeling Framework (ESMF) and the National Unified Operational Prediction Capability (NUOPC) interoperability layer.
Updates to model forcing options for use of the UFS land component
Provided a new analysis option in the cubed-sphere native grid using
GSWP3
forcing
Established global land grid-point consistency with the head of the UFS WM baseline test cases
Added a new sample configuration file (
settings_DA_cycle_gswp3
Included an additional ECMWF ERA5 reanalysis forcing option in the existing vector-to-tile conversion analysis process
CTest suite upgrades—the ERA5 CTests now test the operability of seven major components of Land DA:
vector2tile
create_ens
letkfoi_snowda
apply_jediincr
tile2vector
land_driver
, and
ufs_datm_land
Upgrade of the JEDI DA system to JEDI Skylab v4.0
Updates to sample datasets for the release (see the
Land DA data bucket
Singularity container (
ubuntu20.04-intel-landda-release-public-v1.2.0.img
) updates to support the changes described above
Documentation updates to reflect the changes for this release
Known Issues:
For the GSWP3 forcing option, an artificial GHCN snow depth observation file is provided for a single-cycle analysis test for 2000-01-03. The GHCN observation database will be extended in the near future.
Documentation:
GitHub Wiki
GitHub Repository
User’s Guide
Land Data Assimilation (DA) System v1.1.0
Release Date: 05/25/2023
Release Description:
The Land Data Assimilation (DA) System combines the Noah-MP land surface model with data assimilation capabilities into a user-friendly workflow. The Land DA workflow code base is charting a path forward to unify the Noah-MP forecast model with the UFS Weather Model (WM). Updates for this release include the migration of the Land DA System to the
ufs-community
GitHub space, the addition of a UFS WM build option, modulefile updates to use the
spack-stack
Unified Environment on Level 1 systems, and DA upgrades to utilize JEDI’s Skylab v3.0 release of jedi-bundle.
Known Issues:
The GitHub Actions workflow YAML for the Docker-based build and CTest was turned off due to the limited disk space provided in the GitHub Actions free runner.
Documentation:
GitHub Wiki
GitHub Repository
User’s Guide
Land Data Assimilation (DA) System User’s Guide
UFS Land DA User’s Guide v3.0.0
Other Links
The
spack-stack
repository
contains the prerequisite software needed to run the Land DA System and other UFS software. This software is preinstalled on
Level 1 systems
(e.g., Hera, Orion). Users can view the
spack-stack
documentation
to install it on other systems.
JEDI Documentation
(Skylab v4.0): The Land DA System uses
JEDI code for DA
. The documentation contains information about the JEDI code and how to work with it.
Land DA System Data Bucket
: Get downloadable data to run supported Land DA cases.
NOAA EPIC Docker Hub
: A repository of container images (including Land DA container images) that users can download. Land DA containers package the Land DA System together with all its software dependencies for an easier experience building and running Land DA.
UFS Land DA System README.md
file
Get Started with the Land DA System
GitHub Code
Supported Systems
Resources
User’s Guide
Q&A Forum
Land DA wiki
Technical FAQs
Tutorials
Public Release Code
v3.0.0
(latest)
v2.0.0
v1.2.0
All releases
For Developers
Land DA System Repository Structure
Useful Links
spack-stack
code
and
spack-stack
documentation
JEDI code
and
JEDI documentation
(Skylab v7.0)
Land DA Data Bucket
NOAA EPIC DockerHub
Land DA README.md
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