Patrick Minnis (PI)
NASA Langley Research Center
p.minnis@nasa.gov

Contrail Modeling for Evaluating Climate Effects of Aircraft

Contrail-induced cloud cover has been shown to be a significant factor in regional climate change, especially over the USA. As air traffic increases, the potential for globally significant impacts also rises. To better understand, predict, and mitigate the potential climatic effects, it is necessary to develop models that can provide realistic representations of contrails in both short-term and long-term contexts. The climatic effect is governed by the contrail properties (optical depth, temperature, areal coverage, lifetime), the time of day, the the atmospheric state and the underlying surface, and the aircraft engine type and performance. This proposal seeks to build on our previous experience and  1) Develop improved parameterizations of contrails and their properties for use in climate models.  2) Develop a near-real time persistent contrail prediction methodology that could have real-time applications in flight planning to avoid altitudes in regions where persistent contrails would likely create new cloud cover. 3) Examine the potential climatic effects of contrails by simulating them in a realistic environment including surface and cloud conditions to accurately estimate the radiative interactions. 4) Collaborate with other modeling groups, especially the FAA SAGE and NASA GMAO groups, and provide a state-of-the-art contrail prediction model that is compatible with their emission transport and chemistry models. As a CMAI proposal, it will contribute to the assessment of the anthropogenic perturbations to the Earth system and address the following NRA questions: (1) What are the effects of clouds and surface hydrologic processes on Earth's climate?  (2) What are the effects of regional pollution on the global atmosphere, and the effects of global chemical and climate changes on regional air quality? (3) How can predictions of climate variability and change be improved? (4) How well can transient climate variations be understood and predicted? Two approaches will be used: statistical and phyiscal. To develop the parameterizations, we will make use of high-resolution numerical weather analysis (NWA) models (RUC, ARPS, MM-5) to establish the meteorologicalcoditions, our air traffic flight database to specify flight distributions, and Terra, Aqua, & GOES data to specify cloud conditions and validate the contrail predictions. We will begin with our current statistical model that forms contrails based on aircraft efficiency and then spreads, transports, and dissipates the contrails depending on the model atmosphere conditions. The modeling will include calculating the perturbations in the radiative fields, the particle sizes, and the humidity changes within the contrail layer. A more sophisticated treatment will be pursued in collaboration with Dr. Donghai Wang using the ARPS model as a platform. The results of this study should provide a more accurate assesment of contrail climate effects and a more realistic model of contrails that can be used in chemical reaction and transport and climate models.

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