Assimilation and Verification Innovation Division| NOAA OAR GSL

Who We Are

The Assimilation and Verification Innovation Division (AVID) develops and improves analyses and forecasts for high resolution models and applications through innovative data assimilation and verification techniques.

AVID aligns with the GSL Strategic Plan Goal 2: Develop state-of-the-art Earth-system prediction capabilities

Areas of Research

Advance data assimilation techniques to support precision forecasting.
Advance verification techniques and exploration of new observation datasets.

AVID Branches

Data Assimilation

Data assimilation is the science that uses observations to improve initial conditions and forecasts of numerical weather/Earth models as weather evolves over time.

Verification and Assessments

Through cutting edge and innovative research, AVID's Verification and Assessments Branch provides operational agencies with technology and tools for improving the accuracy and quality of weather information at critical decision points, thus improving services to the public.

Highlights and Accomplishments

Rapid Refresh Forecast System (RRFS)

GSL, NOAA National Centers for Environmental Prediction (NCEP) Environmental Modeling Center (EMC), and other partners are working together on a project to design a single-model, convection-allowing, ensemble-based data assimilation and forecasting system called the Rapid Refresh Forecast System (RRFS). This project aims to develop advanced high-resolution data-assimilation techniques and ensemble-forecasting methods while supporting the unification and simplification of the NCEP modeling suite. The experimental RRFS North America 3km model is not supported 24/7 and may be subject to outages.

Weather Analysis Systems

The 3D Real-Time Mesoscale Analysis (RTMA) and UnRestricted Mesoscale Analysis (URMA) systems, developed by NOAA's Global Systems Laboratory (GSL), provide high-resolution, three-dimensional analyses of atmospheric conditions. These systems assimilate a wide range of observational data, including surface, radar, and satellite inputs, to create accurate and timely representations of weather variables such as temperature, wind, and humidity. By offering detailed, real-time insights into mesoscale weather phenomena, 3D RTMA and URMA support critical decision-making processes in weather forecasting and emergency response.

Testbeds

GSL participates in the NOAA Hazardous Weather Testbed, the Aviation Weather Testbed, and the Hydrometeorology Testbed with several experimental models under the microscope. The primary goals of the testbeds are to accelerate the transfer of promising new tools from research to operations, inspire new initiatives for operationally relevant research, and identify and document sensitivities in the performance of state-of-the art experimental high-resolution modeling systems.

Model Analysis Tool Suite (MATS)

The Model Analysis Tool Suite (MATS) is a software product developed in-house by GSL to assess the forecast skill of regional and global weather models. MATS consists of individual applications, which are each designed to verify particular meteorological phenomena such as ceiling heights, radar reflectivities, or precipitation accumulations. Using MATS, model developers can produce interactive, publication-quality plots to quickly and easily compare the skill of individual models' forecasts as they occur, as well as assess the performance of models under development.

METexpress

GSL and the Developmental Testbed Center (DTC) have collaboratively developed METexpress, a lightweight, quick-start visualization suite used to retrieve and view data from the advanced Model Evaluation Tools (METplus). METplus is a unified verification system for community model development efforts, and marks a major advancement of the Unified Forecast System Research-to-Operations (UFS-R2O) project. Community verification tools have been crucial in these community development projects, as they give all participants a common framework for evidence-based decision-making when transitioning models to operations.

Quality Assessments for Aviation Weather

The quality assessment product development team conducts independent comprehensive assessments to interpret and communicate the accuracy of aviation weather guidance. For example, the Forecast Icing Product has been under investigation to determine the changes associated with using higher resolution numerical weather prediction output to generate the icing information.

Probability of Maximum Precipitation

GSL, the NOAA Physical Sciences Laboratory, Colorado State University's Cooperative Institute for Research in the Atmosphere (CIRA) and the University of Colorado's Cooperative Institute for Research in Environmental Sciences (CIRES) are researching ways to improve estimates of extreme precipitation impacting dams in order to inform risk assessments. Researchers are also exploring various scientific methods and approaches to generate new datasets to address the nuanced needs of high-hazard infrastructure-focused user communities.