Joint Numerical Testbed Program

About JNTP

Assessing Numerical Forecast Techniques for Operations and Research

A bridge between research and operations

The Joint Numerical Testbed (JNT) is a collaborative facility within RAL that is connected to an international network of collaborators.  The main goals of the JNT are to test and evaluate numerical weather prediction (NWP) systems, including data assimilation. Test results provide meaningful information about forecast performance to operational decision makers and to provide the research community with support in their development of these systems. Currently the primary JNT activities cover the following: regional and global modeling activities to support the Developmental Testbed Center (DTC), activities to support the Tropical Cyclone Modeling Team (TCMT), development and testing of real-time regional numerical weather prediction systems, applied statistics, advanced forecast verification, and satellite radiance data assimilation with an emphasis on all-sky (clear and cloudy) radiances.

Test and Evaluation

The JNT makes forecast system evaluation operationally relevant by executing rigorous end-to-end tests on many forecasts spanning multiple seasons. The cases selected for these retrospective tests encapsulate a broad range of weather regimes ranging from quiescent to strong flows. The exact periods chosen vary based on the type of phenomenon that is the focus of the test. For some test activities, these cases will be chosen from all four seasons (e.g., extra–tropical for general predictions), whereas for others the cases will come from a particular season (e.g., hurricane season, convective season). The JNT’s evaluation of these retrospective forecasts includes standard verification techniques, as well as new verification techniques when appropriate. 

By conducting carefully controlled testing, including the generation of objective verification statistics, the JNT is able to provide the operational community with guidance for selecting new NWP technologies with potential value for operational implementation. JNT testing also provides the research community with baselines against which the impacts of new techniques can be evaluated. The statistical results may also aid researchers in selecting model configurations to use for their projects.

Verification and Applied Statistics

Statistical verification of forecasts is a critical component of their development. Verification also benefits forecasters and end users by supplying them with objective data about the quality or accuracy of the forecasts, which can feed into decision processes.

The JNT is focused on developing statistically meaningful advanced verification tools for assessment and comparison of the forecasts performance.  JNT staff support international verification efforts, and advanced statistics including extreme value theory. The JNT also provides statistical support for other projects in RAL.

The JNT continually develops, updates, and supports the community state-of-the-science verification package called the Model Evaluation Tools (MET), which contains novel verification methods including the Method for Object-based Diagnostic Evaluation (MODE).

Community Code

Community code is a free and shared resource with distributed development and centralized support. Ongoing development of community codes is maintained under version control. Periodic releases, which include the latest in developments of new capabilities and techniques, are made available to the user community.

Developers contribute new software capabilities to a shared software repository, and user support is provided via websites, on–line tutorials, on–site tutorials, workshops and helpdesk functions. Ongoing development of community codes is maintained under software version control, and includes extensive regression and pre–release testing. Periodic software releases, which include the latest in developments of new capabilities and techniques, are made available to the user community. The following codes are available to the community:

JNTP Solutions

Tropical Cyclone off Brazil Courtesy of NASA
That is the question hurricane researchers and forecasters aim to answer
Online access to retrospective and demonstration model evaluations to allow wider dissemination to the hurricane community.

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