Editorial Type:
Article
Article Type:
Research Article

An Empirical Model to Predict Widespread Occurrences of Contrails

David J. Travis Department of Geography, University of Wisconsin–Whitewater, Whitewater, Wisconsin

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Andrew M. Carleton Department of Geography and Earth System Science Center, The Pennsylvannia State University, University Park, Pennsylvania

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Stanley A. Changnon Atmospheric Sciences Division, Illinois State Water Survey, Champaign, Illinois

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Print Publication:
01 Sep 1997
DOI:
https://doi.org/10.1175/1520-0450(1997)036<1211:AEMTPW>2.0.CO;2
Page(s):
1211–1220
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Abstract

The increases in total cloud amount documented for large regions during the latter half of the twentieth century have focused attention on the potential contribution from jet condensation trails (contrails). The environmental conditions that favor contrail formation and persistence are not well understood primarily due to the limited number of empirical studies. This study presents an empirical model to predict widespread occurrences of contrails (outbreaks), which was developed from a combination of rawinsonde temperature and GOES water vapor information. Environments containing persisting contrails were first identified on Defense Meteorological Satellite Program satellite imagery for the United States for January and April 1987 and then analyzed in more detail using Advanced Very High Resolution Radiometer (AVHRR) satellite digital data. Adjacent clear and cloudy environments not containing contrails were identified to compare with the conditions favorable for contrail persistence. For this purpose, a predictive logistic model was developed through multiple regression analysis.

The model performance was evaluated through goodness-of-fit methods and found to be statistically significant across a range of atmospheric conditions. To further evaluate the model and to demonstrate its application on a real-time basis, predictions of the probability of persisting contrails were made for a case day. Comparisons of the predictions to satellite observations of the existing conditions (using AVHRR data) demonstrate good model performance and suggest the utility of this approach for predicting persisting contrail occurrence. Implementation of this model should allow climate researchers to better quantify the influence of contrails on surface climate and natural cloud formation.

Corresponding author address: Dr. David J. Travis, Department of Geography, University of Wisconsin–Whitewater, Whitewater, WI 53190.

Abstract

The increases in total cloud amount documented for large regions during the latter half of the twentieth century have focused attention on the potential contribution from jet condensation trails (contrails). The environmental conditions that favor contrail formation and persistence are not well understood primarily due to the limited number of empirical studies. This study presents an empirical model to predict widespread occurrences of contrails (outbreaks), which was developed from a combination of rawinsonde temperature and GOES water vapor information. Environments containing persisting contrails were first identified on Defense Meteorological Satellite Program satellite imagery for the United States for January and April 1987 and then analyzed in more detail using Advanced Very High Resolution Radiometer (AVHRR) satellite digital data. Adjacent clear and cloudy environments not containing contrails were identified to compare with the conditions favorable for contrail persistence. For this purpose, a predictive logistic model was developed through multiple regression analysis.

The model performance was evaluated through goodness-of-fit methods and found to be statistically significant across a range of atmospheric conditions. To further evaluate the model and to demonstrate its application on a real-time basis, predictions of the probability of persisting contrails were made for a case day. Comparisons of the predictions to satellite observations of the existing conditions (using AVHRR data) demonstrate good model performance and suggest the utility of this approach for predicting persisting contrail occurrence. Implementation of this model should allow climate researchers to better quantify the influence of contrails on surface climate and natural cloud formation.

Corresponding author address: Dr. David J. Travis, Department of Geography, University of Wisconsin–Whitewater, Whitewater, WI 53190.

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Cover Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology

  • Aldrich, J. H., and F. D. Nelson, 1984: Linear Probability Logit and Probit Models. Sage Publishing, 96 pp.

  • Angell, J. K., 1990: Variation in United States cloudiness and sunshine between 1850 and the drought year of 1988. J. Climate,3, 296–308.

  • Appleman, H., 1953: The formation of exhaust condensation trails by jet aircraft. Bull. Amer. Meteor. Soc.,34, 14–20.

  • Beckwith, W. B., 1972: Future patterns of aircraft operations and fuel burnouts with remarks on contrail formation over the United States. Preprints, Int. Conf. on Aerospace and Aeronautical Meteorology, Washington, DC, Amer. Meteor. Soc., 422–426.

  • Blackwell, K. G., and J. P. McGuirk, 1996: Tropical upper-tropospheric dry regions from TOVS and rawinsondes. J. Appl. Meteor.,35, 464–481.

  • Boin, M., and L. Levkov, 1994: A numerical study of contrail development. Ann. Geophys.,12, 969–978.

  • Carleton, A. M., and P. J. Lamb, 1986: Jet contrails and cirrus cloud: A feasibility study employing high resolution satellite imagery. Bull. Amer. Meteor. Soc.,67, 301–309.

  • Changnon, S. A., 1981: Midwestern cloud, sunshine, and temperature trends since 1901: Possible evidenceof jet contrail effects. J. Appl. Meteor.,20, 496–508.

  • Chen, C.-T., E. Roeckner, and B. J. Soden, 1996: A comparison of satellite observations and model simulations of column-integrated moisture and upper-tropospheric humidity. J. Climate,9, 1561–1585.

  • DeGrand, J. Q., 1991: A satellite-derived mid-season climatology of jet condensation trails: April 1977–October, 1979. M.S. thesis, Dept. of Geography, Indiana University, 117 pp. plus appendices. [Available from Dept. of Geography, Indiana University, Bloomington, IN 47405.].

  • Detwiler, A., and R. Pratt, 1984: Clear-air seeding: Opportunities and strategies. J. Wea. Modif.,16, 46–60.

  • Englestaad, M., S. K. Sengupta, T. Lee, and R. M. Welch, 1992: Automated detection of jet contrails using the AVHRR split-window. Int. J. Remote Sens.,13, 1391–1412.

  • Erickson, M. C., J. P. Dallavalle, and J. S. Jensenius, 1993: Comments on “Snow versus rain: Looking beyond the ‘magic’ numbers.” Wea. Forecasting,8, 542–544.

  • Gayet, J.-F., G. Febvre, G. Brogniez, H. Chepfer, W. Renger, and P. Wendling, 1996: Microphysical and optical properties of cirrus and contrails: Cloud field study on 13 October 1989. J. Atmos. Sci.,53, 126–138.

  • Hanson, H. M., and D. M. Hanson, 1995: A reexamination of the formation of exhaust condensation trails by jet aircraft. J. Appl. Meteor.,34, 2400–2405.

  • Henderson-Sellers, A., 1992: Continental cloudiness changes this century. GeoJournal,27, 255–262.

  • Karl, T. R., and P. M. Steurer, 1990: Increased cloudiness in the United States during the first half of the twentieth century: Fact or fiction? Geophys. Res. Lett.,17, 1925–1928.

  • ——, and Coauthors, 1993: Asymmetric trends of daily maximum and minimum temperature. Bull. Amer. Meteor. Soc.,74, 1007–1023.

  • Knollenberg, R. G., 1972: Measurements of the growth of the ice budget in a persisting contrail. J. Atmos. Sci.,29, 1367–1374.

  • Lee, J. E., and S. D. Johnson, 1985: Expectancy of cloudless photographic days in the contiguous United States. Photogramm. Eng. Remote Sens.,L1, 1883–1891.

  • Lee, T. F., 1989: Jet contrail identification using the AVHRR infrared split window. J. Appl. Meteor.,28, 993–995.

  • Liou, K.-N., S. C. Ou, and G. Koenig, 1990: An investigation on the climatic effect of contrail cirrus. Air Traffic and the Environment-Background, Tendencies, and Potential Global Atmospheric Effects, U. Schumman, Ed., Springer-Verlag, 154–169.

  • Machta, L., and T. Carpenter, 1971: Trends in high cloudiness at Denver and Salt Lake City. Man’s Impact on the Climate, W. H. Matthews, W. W. Kellogg, and G. D. Robinson, Eds., The MIT Press, 401–405.

  • McCullagh, P., and J. A. Nelder, 1989: Generalized Linear Models. Chapman and Hall, 511 pp.

  • Pilie, R. J., and J. E. Jiusto, 1958: A laboratory study of contrails. J. Meteor.,15, 149–154.

  • Scorer, R. S., and L. J. Davenport, 1970: Contrails and aircraft downwash. J. Fluid Mech.,43, 451–464.

  • Seaver, W. T., and J. E. Lee, 1987: A statistical examination of sky cover changes in the contiguous United States. J. Climate Appl.Meteor.,26, 88–95.

  • Soden, B. J., and F. P. Bretherton, 1993: Upper tropospheric humidity observations from the GOES 6.7 μm channel: Method and climatology for July, 1987. J. Geophys. Res.,98, 16 669–16 688.

  • —— and ——, 1996: Interpretation of TOVS water vapor radiances in terms of layer-average relative humidities: Method and climatology for the upper, middle, and lower troposphere. J. Geophys. Res.,101(D5), 9333–9343.

  • Travis, D. J., 1994: Jet aircraft condensation trails: Their radiative impacts and association with atmospheric conditions. Ph.D. dissertation, Indiana University, 118 pp. [Available from Dept. of Geography, Indiana University, Bloomington, IN 47405.].

  • ——, 1996: Variations in contrail morphology and relationships to atmospheric conditions. J. Wea. Modif.,28, 50–58.

  • Wendland, W. M., and R. G. Semonin, 1982: Effect of contrail cirrus on surface weather conditions in the Midwest: Phase II. Illinois State Water Survey Final Rep. of NSF Grant ATM 8008812, 95 pp. [Available from Illinois State Water Survey, Atmospheric Sciences Division, 2204 Griffith Dr., Champaign, IL 61820-7495.].

  • Willmott, C. J., C. M. Rowe, and W. D. Philpot, 1985: Small-scale climate maps: A sensitivity analysis of some common assumptions associated with grid-point interpolation and contouring. Amer. Cart.,12(1), 5–16.

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