Estimated contrail frequency and coverage over the contiguous United States from numerical weather prediction analyses and flight track data

Estimates of contrail frequency and coverage over the contiguous United States (CONUS) are developed using hourly meteorological analyses from the Rapid Update Cycle (RUC) numerical weather prediction model and commercial air traffic data for 2 months during 2001. The potential contrail frequency ov...

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Bibliographic Details
Main Authors: David P. Duda, Patrick Minnis, Rabindra Palikonda
Format: Article
Language:English
Published: Borntraeger 2005-09-01
Series:Meteorologische Zeitschrift
Online Access:http://dx.doi.org/10.1127/0941-2948/2005/0050
Description
Summary:Estimates of contrail frequency and coverage over the contiguous United States (CONUS) are developed using hourly meteorological analyses from the Rapid Update Cycle (RUC) numerical weather prediction model and commercial air traffic data for 2 months during 2001. The potential contrail frequency over the CONUS is computed directly from RUC analyses using several modified forms of the classical Appleman criteria for persistent contrail formation. Various schemes for diagnosing contrails from the RUC analyses were tested by first tuning each model to mean satellite estimates of contrail coverage for the domain and then comparing the resulting distributions to those from the satellite retrievals. The most accurate method for forming persistent contrails for both months uses a fourth root relationship between flight lengths and contrail coverage, accounts for contrail overlap and for the dry bias in the humidity profiles, and assumes that contrails can be detected in all cloudiness conditions. The differences between the simulated and satellite-derived contrail amounts are due to errors in the satellite observations, possible diurnally dependent saturation effects, and uncertainties in the numerical weather analysis humidity fields and other input variables. The algorithms developed here are suitable for eventual application to real-time predictions of potential contrail outbreaks. When refined, the methodology could be useful for both contrail mitigation and for contrail-climate effects assessment.
ISSN:0941-2948