The Network-Enabled Verification Service (NEVS) Jennifer Mahoney 6 October 2009

NEVS Development Team Sean Madine – NEVS Project Lead Nick Matheson – NEVS Tech Lead Missy Petty – Engineer Dan Schaffer – Engineer Tim Pease - Engineer Geary Layne – Scientist Steve Lack - Scientist

Outline Background - verification information What is NEVS? NEVS Architecture Timeline

Requirements for Accuracy Information - Summarized Concepts that adequately measure forecast performance in the context of aviation operations A delivery mechanism for distributing the performance information when needed by the SAS and ATM decision tools.

Why Performance Information is Different Forecast Data Weather forecast data valid short period of time and then replaced with next forecast Performance information requires the entire history of forecast data for computing the metrics Performance metrics computed using historical archive of forecast data

Why Performance Information is Different Therefore, to develop and produce performance information continually, A mechanism for managing data is required Integrating operational criteria with performance information is critical Distribution of the performance information when needed is vital Performance metrics computed using historical archive of forecast data

What is NEVS A delivery mechanism for forecast performance information Utilizes relational database technology to integrate weather data with operational decision criteria to generate performance metrics on demand

The NEVS Concept for NextGen ATM-Integration NEVS will provide “dash board-like” information to monitor health of NextGen weather system Importantly, NEVS will provide real-time warning signs to ATM decision tools about the performance of the weather forecast for operational decisions

The NEVS Dash Board NEVS sends warnings to ATM decision tools when: Measures of airspace capacity, as computed by the convective weather forecast, begins to deviate significantly from the forecast and exceed operational planning criteria A wind forecast used for landing aircraft at airports is not performing as expected and dangerous cross winds are beginning to enter the operational domain of interest IFR conditions are developing sooner than forecast and will impact the terminal capacity.

Sector Impact using Mincut Bottleneck Technique 21 Aug 2009; 1500 UTC, 6h lead

Traditional Measures using Mincut Bottleneck Technique Bias Bias with Confidence 21 Aug 2009; 1500 UTC, 6h lead

Planning Point Capacity Plot % Blockage as derived from Mincut Bottleneck Technique Cessation Onset CCFP struggles with 2-h gaps in lead times, but in this case is closer to onset than a 15-min forecast CCFP has no 8-h forecast, tough to make decisions on traffic clean up.

NEVS at MOC ATM Interface NEVS 4-D Wx Cube F F1 F2 F3 O SAS V1 V2 V3 ATM Decision Criteria Automated Monitoring Integrated Common Weather Picture V1 V2 V3 User-specific Verification Info from NEVS V4 V5 NNEW NWS IT 11

NEVS Architecture 14

NEVS Service Perspective Machine to Machine

NEVS Service Perspective: Web Application

NEVS NextGen Services NEVS will be both a service provider and service requester Types of services General Depend on common infrastructure for service location and data publishing and subscription Weather data Core input to NEVS ATM data Data to connect NEVS verification information to weather consumers

NEVS Timeline FY10 FY11 FY12 FY13 Beyond NextGen Relevance Outcome: Performance Measures into ATM Decision tools FY10 FY11 FY12 FY13 Beyond Step 1: NEVS Demo; idea exploration Step 3: IOC Demo: NEVS (v1b) output integrated into ATM tool and 4-D Wx cube exploration for ATM decisions; Performance technique engineering development NNEW Apps Data exchange and engineering NEVS/ATM tool connection; NEVS/ATM tool end to end connection and testing with ATM systems IOC NEVS preparation Performance Techniques Increase functionality and user questions Step 2: NEVS Demo; Integration of preliminary concepts within an ATM tool

Questions?