Denver International Airport Maintenance Decision Support System (MDSS) Modernization and Enhancements

Denver International Airport (DEN) experiences several rounds of adverse winter weather during the cold season that can significantly disrupt airport operations. Runways along with access roads must be maintained and cleared of snow and ice. Safety and efficiency of airport operations hinges on timely and accurate weather forecasts. Managing winter storms at an airport requires collaboration in a complex decision-making environment between inter-dependent stakeholders with different objectives. Therefore having a centralized forecast decision support system is ideal for maintenance managers to get a handle on when and where to treat the runways during winter storms.

In the mid-2000’s the National Center for Atmospheric Research operated by the National Science Foundation (NCAR-NSF) created a custom maintenance decision support system (MDSS) for Colorado with a specific focus on Denver International Airport (DEN) runway operations. The system was configured for all major DEN runways, using known pavement as-builts and rules of practice for treating runways. NCAR has been running an operational prototype system for DEN since 2008.

The MDSS prototype utilizes current weather observations and numerical model predictions from multiple sources to produce runway-specific analyses and forecasts of environmental conditions. Output from this process is used to drive an energy balance model to generate predictions of pavement conditions along each route of interest. Together, environmental and road condition information is used to construct recommended treatments, which are based on standard rules of practice for effective deicing and anti-icing operations. An interactive mobile compatible display is used to visualize graphic and text-based treatment recommendations, as well as diagnostic and prognostic atmosphere and road condition data.

The broad needs met by the current MDSS include the following:

• Centralized Weather Support
• Enhanced Strategic Planning Capability
• Improved Tactical Response Capability
• Improved Adverse Road Weather Notification
• Operation-Specific Decision Support.

This paper describes the modernization of the MDSS system over the last 4 years. NCAR-NSF has made many meaningful enhancements to both the MDSS backend forecast system and the front-end phone application display. The enhancement that will be discussed include

Phone Application Display Enhancements

• Creating a new map based display with clickable runway segments (that are color-coded base on alert level)
• Setup a new backend machine to run MDSS that runs both the backend weather and road forecast system along with the custom WRF model over Colorado
• Updated GoLanguage web-server
• Updated HighCharts display application

Forecast Engine Enhancements / New models

• Added the ECMWF model to the backend forecast engine (DICast) for enhanced 2-3 day forecast skill
• Added a custom, high-resolution WRF model gridded over Colorado to the backend forecast engine (DICast) for enhanced precipitation and snowfall forecasting
• Upgraded the pavement model (METRO) within MDSS to use the very latest version (which uses forecast downward solar-radiation to drive the model)
• Created a new Runway Crosswind Alert forecast variable for DEN Runways that is now indicated on the phone application display
• Set Up an initial Runway Friction Prediction system for DEN Runway (that will forecast runway Mu values to 72 hours out)