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Observations and modelling of severe windstorms during T-REX: importance of the upstream profile

School of Earth and Environment ICAS. Observations and modelling of severe windstorms during T-REX: importance of the upstream profile. Ralph Burton 1 , Simon Vosper 2 , Peter Sheridan 2 , Stephen Mobbs 1. 1 Institute for Climate and Atmospheric Science, School of Earth and Environment,

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Observations and modelling of severe windstorms during T-REX: importance of the upstream profile

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  1. School of Earth and Environment ICAS Observations and modelling of severe windstorms during T-REX: importance of the upstream profile Ralph Burton1, Simon Vosper2, Peter Sheridan2, Stephen Mobbs1 • 1 Institute for Climate and Atmospheric Science, School of Earth and Environment, • University of Leeds, U.K. • Met Office, Exeter, U.K. Leeds T-REX team: Barbara Brooks, Ian Brooks, Rosey Grant, James Groves, Martin Hill, Matt Hobby, Felicity Perry, Victoria Smith, Will Thurston

  2. School of Earth and Environment ICAS Introduction: T-REX Comparing models and observations: Relating the winds in the valley to the upstream flow Summary

  3. T-REX: March – April 2006 The biggest field campaign ever mounted to study rotors/gravity waves ARL White Sands Missile Range Scripps Institute of Oceanography Colorado Research Associates Cooperative Research in Environmental Science Desert Research Institute DLR Lawrence Livermore National Laboratory UK Met Office NASA NCAR Naval Research Laboratory NOAA Arizona State University Colorado State University Harvard University University of Houston University of Innsbruck University of Leeds University of New Hampshire North Carolina State University Stanford University University of Utah Yale University

  4. From “Hazardous Mountain Winds and their Visual Indicators”, 1988 Accident rate 40% higher in the 11 mountain states Accident rate less than 3 per 100,000 Accident rate greater than 3 per 100,000

  5. DEM of the U.S. showing regions of elevated terrain

  6. Will “Thirsty” Thurston

  7. Inyo Register, March 2006

  8. Photo: Carlyle Calvin, UCAR

  9. Schematic of wave-rotor system

  10. T-REX IOP6: 25th – 26th March 2006 Kuettner 1959 “A full temporal evolution of a trapped-lee-wave rotor event was captured in this IOP. There was a strong and well defined wave/rotor event with wave clouds, roll clouds, cap cloud over the Sierra, and a dust storm in Owens Valley.” (Mission Summary) Photo: A. Doernbrack

  11. 26th March 2006 6:39PM LT Height (m) w (m/s)

  12. What we want to do, in a nutshell: Take an upstream profile, and attach a number N1 to it 15 Height (km) 10 5 Θ (K)

  13. What we want to do, in a nutshell: Take an upstream profile at time T, and attach a number N1 to it 15 Height (km) 10 5 Θ (K) Look at the downstream winds at time T: attach a number N2 to them Look at lots of cases (different T). Are N1 and N2 related? - Predictability

  14. For the downstream winds. We seek a statistical parameter to describe the effect of severe winds. From Mobbs et al. 2005 (“Observations of downslope winds and rotors in the Falkland Islands”, QJRMS, 131, 2839-2860 σ2 =σu2 ++ σv2 |U| = average wind speed Produce a time series of σ|U|

  15. Locations of the AWS: DRI Leeds Produce a time series of σ|U|

  16. For the upstream profiles. It is thought that the stratification and the shear of the upstream profile are important parameters in determining the nature of the downstream response. From Hertenstein and Kuettner, “Rotor types associated with steep lee topography: influence of the wind profile”, Tellus A, 57, 117-135

  17. UM model simulations for IOP6 UM configuration

  18. Principal Components Analysis (PCA) of the upstream profiles Take time series of upstream profiles; UM output every 10 seconds Perform PCA: extracts two features: EOFs (Empirical Orthogonal Functions) Describe the dominant structures in the profiles (inversions etc) PC Scores (Principal Component Scores) A numerical value: a measure of how similar the profile is to the dominant structures at each point in time; PCA is an objective method Produce a time series of the principal component scores

  19. UM: Principal components analysis of the upstream profile between 3 and 5 km dU/dz N These are the dominant structures in the N and dU/dz profiles for all upstream profiles (sample size: 6840) Maximum in both shear and stability at 4250m

  20. Time series of principal components; wind effect parameter σ |U| : UM

  21. Time series of principal components; wind effect parameter σ |U| : AWS

  22. Correlations: UM wind effect parameter σ |U| with upstream profile structure UM winds

  23. Correlations: AWS wind effect parameter σ |U| with upstream profile structure Insert pic here AWS winds

  24. School of Earth and Environment ICAS Summary The dominant structure in the UM profiles between 3km and 5km is a peak in shear and a peak in stability at z = 4250m There is a very strong ( r = 0.95; r = 0.87) correlation between the UM winds in the valley and the upstream N and dU/dz profiles for all of IOP6 (19 hours); The correlation is not as strong for the observed winds. But then the model is reacting to the model profiles, which may differ slightly to the observed profiles. Is this behaviour unique? Or does it apply to other IOPs? Ongoing.

  25. Correlations between first PC score for N and dU/dz

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