Real-Time Verification of NWS Aviation Services Products Supporting the NextGen Initial Operating Capabilities

A Network-Enabled Verification Service (NEVS), being developed by the National Oceanic and Atmospheric Administration's (NOAA's) Earth System Research Laboratory, is intended to provide quality assessment information for improving aviation decision-making in support of the Next Generation Air Transportation System (NextGen) goals for enhanced Air Traffic Management (ATM). NEVS is a tool that will be used to verify National Weather Service (NWS) products and forecasts made available for NextGen in a virtual Four-Dimensional Weather Data Cube (4-D Wx Data Cube).

NEVS will provide automated verification information through network-enabled access to relational databases in support of strategic planning for ATM and NWS aviation operations. NEVS will use a scalable Service Oriented Architecture which will facilitate interfaces with users and other NWS verification systems. NEVS will provide real-time verification capabilities for evaluating NWS aviation alphanumeric and gridded products in the 4-D Wx Data Cube.

This paper will present an overview of NWS verification requirements and plans for the NEVS to meet NextGen Initial Operating Capabilities needed by 2013. Requirements for verification capabilities needed in NEVS are being defined by an integrated work team of NOAA verification experts and managers.

New tools for assessment of the value added by the forecasters as compared to numerical and statistical guidance will be a key feature of capabilities needed in NEVS. Object-based verification tools which facilitate evaluation of the spatial extent and the temporal evolution of features are needed to provide feedback on the quality of mesoscale forecast details in gridded forecasts. Methodologies for tracking the placement and distribution of forecast features are also needed to assess gridded forecast performance. Capabilities for real-time feedback on forecast accuracy are needed in NEVS to enable forecasters to continually improve the quality of their forecasts.