Multiscale and Probabilistic Prediction

Assessing merits of innovative NWP techniques for multiscale deterministic and probabilistic model guidance
GFS/NAM Precipitation Forecast Comparison: An extensive evaluation of the Global Forecast System (GFS) and the North American Mesoscale (NAM) operational models was performed to quantify the differences in the performance of Quantitative Preciptation Forecasts (QPF) produced by two modeling systems that vary signficantly in horizontal resolution.
GFS/NAM Precipitation Forecast Comparison: An extensive evaluation of the Global Forecast System (GFS) and the North American Mesoscale (NAM) operational models was performed to quantify the differences in the performance of Quantitative Preciptation Forecasts (QPF) produced by two modeling systems that vary signficantly in horizontal resolution.

Numerical weather prediction (NWP) systems are utilized in both research and operational forecasting applications and can generally be configured to suit a broad spectrum of weather regimes. The JNT conducts a variety of testing and evaluation (T&E) activities ranging from diagnostic case studies to extensive, seasonal or year-long experiments. The cases selected incorporate a broad range of weather regimes ranging from null, to weak and strong events. The design for each test is created in consultation with the developers, relevant area experts, and verification experts. Evaluation of these retrospective cases includes traditional verification approaches, as well as advanced verification techniques using the Model Evaluation Tools (MET).

While efforts continue related to evaluating deterministic model output, as operational centers move towards ensemble-based forecasting the JNT is becoming more involved in the T&E of probabilistic information. Emerging multi-scale global models are also an area of recent expansion and will continue to be a strong focus topic into the future.

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.  In addition, the extensive testing provides the research community with baselines against which the impacts of new techniques can be evaluated.  The statistical results also provide guidance to researchers in selecting model configurations to use for their projects.

A number of projects in the JNT are conducted through its participation in the Developmental Testbed Center (DTC).

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Multiscale and Probabilistic Prediction