Equivalence of velocity statistics at constant pressure or constant altitude

Geophysical Research Letters

Volumn 37, Issue 8, 2010, Pages

  Frehlich, R G ^a   Sharman, R D ^b  

^a UNIVERSITY OF COLORADO   (United States)

^b NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMMERCIAL AIRCRAFT; CONSTANT ALTITUDE; CONSTANT PRESSURES; HORIZONTAL VELOCITY; LARGE DATASETS; NUMERICAL WEATHER PREDICTION MODELS; SECOND ORDERS; SPATIAL VELOCITY; VELOCITY STATISTICS;

MATHEMATICAL MODELS;

FUNCTIONS;

ALTITUDE; DATA SET; NUMERICAL MODEL; PRESSURE FIELD; SPATIAL ANALYSIS; STATISTICAL APPLICATION; TURBULENCE; VELOCITY PROFILE; WEATHER FORECASTING; WIND MEASUREMENT;

EID: 77952005244     PISSN: 00948276     EISSN: None     Source Type: Journal    
DOI: 10.1029/2010GL042912     Document Type: Article

References (27)

1. Benjamin, S. G., B. E. Schwartz, and R. E. Cole (1999), Accuracy of ACARS wind and temperature observations determined by collocation, Weather Forecast, 14, 1032-1038.
2. Benjamin, S. G., G. A. Grell, J. M. Brown, and T. G. Smirnova (2004), Mesoscale weather prediction with the RUC hybrid isentropic-terrainfollowing coordinate model, Mon. Weather Rev., 132, 473-494.
3. Cho, J. Y. N., and E. Lindborg (2001), Horizontal velocity structure functions in the upper troposphere and lower stratosphere: 1. Observations, J. Geophys. Res., 106, 10223-10232, doi : 10.1029/2000 JD900815.
4. Daniels, T. S, W. R. Moninger, and R. D. Mamrosh (2006), Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Overview, paper presented at 12th Conference on Aviation, Range, and Aerospace Meteorology (ARAM), Am. Meteorol. Soc, Atlanta.
5. Drue, C., W. Frey, A. Hoff, and Th. Hauf (2008), Aircraft type-specific errors in AMDAR weather reports from commercial aircraft, Q. J. R. Meteorol. Soc, 134, 229-239.
6. Frehlich, R., and R. Sharman (2004), Estimates of turbulence from numerical weather prediction model output with application to turbulence diagnosis and data assimilation, Mon. Weather Rev., 132, 2308-2324.
7. Frehlich, R., and R. Sharman (2008), The use of structure functions and spectra from, numerical model output to determine effective model resolution, Mon. Weather Rev., 136, 1537-1553.
8. Frehlich, R., and R. Sharman (2010), Climatology of velocity and temperature turbulence statistics determined from rawinsonde and ACARS/ AMDAR data, J. Appl. Meterolol. Clim., in press.
9. Hamilton, K., Y. O. Takahashi, and W. Ohfuchi (2008), Mesoscale spectrum of atmospheric motions investigated in a very fine resolution global general circulation model, J. Geophys. Res., 113, D18110, doi:10.1029/ 2008JD009785.
10. Hinze, J. O. (1959), Turbulence: An Introduction to Its Mechanism and Theory, 586 pp., McGraw-Hill, New York.
11. Holton, J. R. (2004), An Introduction to Dynamic Meteorology, 4th ed., 535 pp., Academic, New York.
12. Jaatinen, J., and J. B. Elms (2000), On the windflnding accuracy of Loran-C, GPS and radar, Väisälä News, 152, 30-33.
13. Koshyk, J. N., and K. Hamilton (2001), The horizontal kinetic energy spectrum and spectral budget simulated by a high-resolution tropospherestratosphere-mesosphere GCM, J. Atmos. Sci, 58, 329-348.
14. Lindborg, E. (1999), Can the atmospheric kinetic energy spectrum be explained by two-dimensional turbulence?, J. Fluid Mech., 388, 259-288.
15. Lindborg, E. (2005), The effect of rotation on the mesoscale energy cascade in the free atmosphere, Geophys. Res. Lett, 32, L01809, doi:10.1029/ 2004GL021319.
16. Lindborg, E. (2006), The energy cascade in a strongly stratified fluid. J. Fluid Mech., 550, 207-242.
17. Lindborg, E., K. K. Tung, G. D. Nastrom, J. Y. N. Cho, and K. S. Gage (2009), Comment on "Reinterpreting aircraft measurements in anisotropic scaling turbulence" by Lovejoy et al, (2009), Atmos. Chem. Phys. Discuss., 9, 22,331-22,336.
18. Lovejoy, S., A. F. Tuck, S. J. Hovde, and D. Schertzer (2007), Is isotropic turbulence relevant in the atmosphere?, Geophys. Res. Lett, 34, L15802, doi:10.1029/2007GL029359.
19. Lovejoy, S., A. F. Tuck, D. Schertzer, and S. J. Hovde (2009), Reinterpreting aircraft measurements in anisotropic scaling turbulence, Atmos. Chem. Phys., 9, 5007-5025.
20. Lovejoy, S., A. F. Tuck, and D. Schertzer (2010), The horizontal cascade structure of atmospheric fields determined from aircraft data, J. Geophys. Res., doi:10.1029/2009JD013353, in press.
21. Moninger, W. R., S. G. Benjamin, B. D. Jamison, T. W. Schlatter, T. L. Smith, and E. J. Szoke (2009), TAMDAR jet fleets and their impact on rapid update cycle (RUC) forecasts, paper presented at 13th Conference on Integrated Observing and Assimilation Systems for Atmospheres, Oceans, and Land Surface, Am. Meteorol. Soc, Phoenix, 29 Jan.
22. Nastrom, G. D., and K. S. Gage (1985), A climatology at atmospheric wavenumber spectra of wind and temperature observed by commercial aircraft, J. Atmos. Sci, 42, 950-960.
23. Parzen, E. (1960), Modern Probability Theory and Its Applications, 464 pp., John Wiley, Oxford, U. K.
24. Skamarock, W. C. (2004), Evaluating mesoscale NWP models using kinetic energy spectra, Mon. Weather Rev., 132, 3019-3032.
25. Takahashi, Y. O., K. Hamilton, and W. Ohfuchi (2006), Explicit global simulation of mesoscale spectrum of atmospheric motions, Geophys. Res. Lett, 33, L12812, doi:10.1029/2006GL026429.
26. Waite, M. L., and P. Bartello (2006), The transition from geostrophic to stratified turbulence, J. Fluid Mech., 568, 89-108.
27. Waite, M. L., and C. Snyder (2009), The mesoscale kinetic energy spectrum of a baroclinic life cycle, J. Atmos. Sci, 66, 883-901.