A Composite-Based Retro-Prediction Method for Jet Contrail Outbreaks Over the United States

Open Access
Silva, Armand Daniel
Graduate Program:
Master of Science
Document Type:
Master Thesis
Date of Defense:
Committee Members:
  • Andrew Mark Carleton, Thesis Advisor
  • contrails
  • regionalization
  • retro-prediction
  • upper troposphere
  • aviation
  • climate diagnostics
  • synoptic climatology
The cirrus-level contrails (condensation trails) produced by jet aircraft likely have contributed to recent climate changes on regional and sub-regional scales in the U.S. and Europe. Accordingly, there is growing concern about reducing the impacts of contrails on climate, especially the surface temperature, through improved forecasting—in real time—of when and where they are most likely to occur. This research develops a climatology of upper troposphere (UT) meteorological conditions associated with multiple occurrences of contrails, or outbreaks, for sub-regions of the U.S. in the mid-season months of 2000-2002. The climatology consists of composites (i.e., multi-case averages) of UT variables developed using the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis data, and is the first step in designing and verifying a retro-prediction method for contrail outbreaks. For mapping the UT climatology of contrail outbreaks, the study develops an objective (GIS-based) regionalization of the conterminous U.S. from the overlaps of outbreak areas in the 2000-2002 period. The regionalization reveals that the high-frequency areas of contrail outbreaks vary spatially according to mid-season month, although the Midwest U.S. has the maximum frequencies on average for the year. The UT composites of meteorological variables indicate that contrail outbreaks tend to occur in advance (to the east) of baroclinic weather systems (troughs, fronts, jet streams), which have associated upward vertical motion, moistening of the air, a thicker upper troposphere (i.e., higher and colder tropopause), and horizontal wind shear. However, statistical analyses (e.g., contingency, logit modeling) of UT conditions associated with contrail outbreaks, reveal that the utility of particular meteorological variables and their associated map characteristics (magnitude, pattern, gradient) in retro-predicting outbreaks for the 2000-2002 study period differs by sub-region and mid-season month. Using the statistical model results of which UT variables are the best retro-predictors for each sub-region and mid-season month, the research conducts a verification study that involves retro-predicting contrail outbreaks for July and October in 2008, and January and April 2009. The results of the verification study are mostly positive. They reveal that a relatively simple map-based method of retro-predicting contrail outbreaks is successful in certain U.S. sub-regions and mid-season months (e.g., the Central region in April). Further verification studies are needed to refine the method and make it suitable for forecasting contrail outbreaks.