Articles | Volume 11, issue 5
https://doi.org/10.5194/amt-11-2717-2018
https://doi.org/10.5194/amt-11-2717-2018
Research article
 | 
08 May 2018
Research article |  | 08 May 2018

Instantaneous variance scaling of AIRS thermodynamic profiles using a circular area Monte Carlo approach

Jesse Dorrestijn, Brian H. Kahn, João Teixeira, and Fredrick W. Irion

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Cited articles

Aumann, H. H., Chahine, M. T., Gautier, C., Goldberg, M. D., Kalnay, E., McMillin, L. M., Revercomb, H., Rosenkranz, P. W., Smith, W. L., Staelin, D. H., Strow, L. L., and Susskind, J.: AIRS/AMSU/HSB on the Aqua mission: Design, science objectives, data products, and processing systems, IEEE T. Geosci. Remote, 41, 253–264, 2003. a
Bacmeister, J. T., Eckermann, S. D., Newman, P. A., Lait, L., Chan, K. R., Loewenstein, M., Proffitt, M. H., and Gary, B. L.: Stratospheric horizontal wavenumber spectra of winds, potential temperature, and atmospheric tracers observed by high-altitude aircraft, J. Geophys. Res.-Atmos., 101, 9441–9470, 1996. a
Bogenschutz, P. A. and Krueger, S. K.: A simplified pdf parameterization of subgrid-scale clouds and turbulence for cloud-resolving models, J. Adv. Model. Earth Sy., 5, 195–211, 2013. a
Chahine, M. T., Pagano, T. S., Aumann, H. H., Atlas, R., Barnet, C., Blaisdell, J., Chen, L., Divakarla, M., Fetzer, E. J., Goldberg, M., Gautier, C., Granger, S., Hannon, S., Irion, F. W., Kakar, R., Kalnay, E., Lambrigtsen, B. H., Lee, S.-Y., Le Marshall, J., Mcmillan, W. W., Mcmillin, L., Olsen, E. T., Revercomb, H., Rosenkranz, P., Smith, W. L., Staelin, D., Strow, L. L., Susskind, J., Tobin, D., Wolf, W., and Zhou, L.: AIRS: Improving Weather Forecasting and Providing New Data on Greenhouse Gases, B. Am. Meteorol. Soc, 87, 911–926, 2006. a, b, c, d, e
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Short summary
Atmospheric Infrared Sounder (AIRS) satellite observations are used to quantify the scale-dependent variance of temperature and water vapor in the atmosphere. The scale dependence is much more variable than previously thought, using a new methodology based on individual satellite swaths. A break in the scale dependence is found to vary from less than 100 to greater than 1000 km. These new variance scaling results are of high importance for improving climate GCM subgrid parameterizations.