NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Collections About News Help Login
Back to Results
Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample ModelsPrevious studies have shown that probabilistic forecasting may be a useful method for predicting persistent contrail formation. A probabilistic forecast to accurately predict contrail formation over the contiguous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and from the Rapid Update Cycle (RUC) as well as GOES water vapor channel measurements, combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The mean accuracies for both the SURFACE and OUTBREAK models typically exceeded 75 percent when based on the RUC or ARPS analysis data, but decreased when the logistic models were derived from ARPS forecast data.
Document ID
20090034858
Acquisition Source
Langley Research Center
Document Type
Preprint (Draft being sent to journal)
Authors
Duda, David P. (National Inst. of Aerospace Hampton, VA, United States)
Minnis, Patrick (NASA Langley Research Center Hampton, VA, United States)
Date Acquired
August 24, 2013
Publication Date
January 1, 2009
Subject Category
Meteorology And Climatology
Funding Number(s)
CONTRACT_GRANT: NSF-0222623
CONTRACT_GRANT: NAG1-02044
CONTRACT_GRANT: NCC1-02043 NIA-2579
Distribution Limits
Public
Copyright
Public Use Permitted.

Related Records

There are no records associated with this record.
No Preview Available