Ceiling and Visibility
- About
- Contacts
Overview
Low ceilings and reduced surface visibilities yield critical impacts across the spectrum of aviation activities. For the general aviation pilot, limited ceiling and/or visibility (C&V) present a significant safety hazard – one that must be carefully considered in making go/no-go decisions as well as IFR avoidance and escape decisions while en route. For commercial aviation, advanced aircraft equipment and pilot experience enable safe operations in low C&V conditions, but the traffic flow capacity at impacted terminals drops markedly. This reduction in capacity yields a major cause for flight delays and cancellations, and can propagate 'upstream' from impacted terminals to feeder terminals where no C&V problem exists.
RAL's work toward C&V diagnosis and forecast address both the safety and terminal capacity impacts outlined above.
National Ceiling and Visibility
NCVA Diagnosis Product
Work is nearly complete on the first–generation National Ceiling and Visibility Analysis (NCVA), which presents carefully interpolated ceiling and visibility conditions at and between ∼1600 observing points across the continiental U.S. (CONUS). NCVA's ceiling, visibility and flight category displays are accompanied by product confidence fields that provide users with simplified information on the quality of observations and seek to aid the users' assessment of product representativeness for current conditions. The product is rendered on a 5 km grid and is updated every 5 minutes. A second–generation NCVA product will implement more rigorous probabilistic representation of the undertainty in C&V conditions between observing points.
The product is available on the Experimental ADDS website, and is also used to populate RAL's experimental Helicopter Emergence Medical Services (HEMS) Tool.
NCVF Probabilistic Forecast Product
RAL is currently working toward an experimental probabilistic C&V forecast product. The probabilistic approach acknowledges the inherent uncertainty in the forecast process and seeks to quantify and convey that uncertainty directly to the user. Forecast probabilities can thus be intelligently interpreted by human decision–makers, and can be used quantitatively in decision support systems where are variety of inputs and consequences are considered. In mature form, NCVF will forecast the probabilities for ceiling and visibility conditions ranging from fully obscured to clear. Probabilistic weather forecasts are critical to meeting the air traffic efficiency goals of NextGen.
RAL's NCVF development approach is to maximize the use and synthesis of existing operational models, model output statistics (MOS)–based guidance and other forecast products such as CoSPA. Time–lagged forecast ensembles derived from the Rapid Refresh (RR), High–Resolution Rapid Refresh (HRRR), and NAM are being evaluated for use. Conventional ensembles as available in the SREF and (as proposed for 2012) the RR will also be evaluated. These resources are being augmented with an observations–based forecast component to boost forecast performance from 1 to ∼4 h. The first–generation NCVF product (planned for experimental release in 2012) will produce forecasts from 0 to 12 hours at ∼1600 airport sites across the CONUS. A second–generation product will extend the forecast outlook as far as 30 hours. Short–range forecasts (less than ∼3 hours) will be updated at an interval of 5–15 min, while longer–range forecasts will be updated hourly, over both CONUS and Alaska domains.
San Francisco Marine Stratus Forecast
RAL staff have worked with colleagues from MIT/Lincoln Laboratory to develop the San Francisco Marine Stratus Forecaster Display system, which provides forecasts of the time that low clouds and fog will clear the approach to the San Francisco Airport. The system was transferred to the NWS and is currently running operationally.
The San Francisco Marine Stratus Forecaster Display (above) is used operationally by the Center Weather Service Unit (CWSU) forecaster, WFO aviation forecaster, FAA traffic managers, and airline meteorologists. The left side provides displays of sensor data, used in the forecast models. There are four primitive forecast models and a consensus forecast. The right side provides the forecast information. The historical probability of success is provided as a measure of confidence in the consensus forecast.
Primary Contacts
- CARMICHAEL, Bruce | AAP DIRECTOR | ph: 8406 | email: brucec
- BARRON, Bob: | AAP DEPUTY DIRECTOR | ph: 8410 | email: bob
- POLITOVICH, Marcia | AAP DEPUTY DIRECTOR | ph: 8449 | email: marcia