An Investigation of Atmospheric Stability and Its Impact on Scatterometer Winds Across the Gulf Stream
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1 An Investigation of Atmospheric Stability and Its Impact on Scatterometer Winds Across the Gulf Stream Jim Edson University of Connecticut Doug Vandemark & Amanda Plagge University of New Hampshire
2 CLIMODE Deployments and Cruises November 2005: Mooring & Profiler Deployment Cruise January 18-30, 2006: Pilot Experiment, ASIS/FILIS Deployment October 2006: Mooring Turnaround Cruise February-March 2007: 6week Main Experiment, ASIS/FILIS Deployments, Microstructure, Surveys. November 2007: Mooring Recovery Cruise
3 CLIMODE Deployments and Cruises November 2005: Mooring & Profiler Deployment Cruise January 18-30, 2006: Pilot Experiment, ASIS/FILIS Deployment October 2006: Mooring Turnaround Cruise February-March 2007: 6week Main Experiment, ASIS/FILIS Deployments, Microstructure, Surveys. February 2007: Mooring Recovery Cruise
4 The Gulf Stream Co l d A ir O ak utbre L s 14oC 22oC Cold air outbreaks drive extremely active convection over the region. The net winter heat loss in this region is 400 W/m2.
5 CLIMODE Platforms
6 Sensor Packages R/V Atlantis and Knorr 2-3 DCFS (Sonic/MotionPak/Licor) IR and Solar Radiometers IR SST RH/T/P Sensors ShipSystem (Precip, Tsea, Salinity, ADCP) ASIS DCFS (Sonic/MotionPak/Licor) IR and Solar Radiometers RH/T/P Sensors 6 Wave Wires Subsurface (Tsea, Salinity, ADCP, Nortek) Discus Low Power DCFS (Sonic/MotionPakIII) Redundant IR and Solar Radiometers Redundant U/RH/T/P Sensors (ASIMET) Subsurface (T/S, Nortek, VACM)
7
8 Moving Platform vs. Fixed Tower Uncorrected ~530 m
9 Moving Platform vs. Fixed Tower Corrected ~530 m
10 Bulk Aerodynamic Method Latent Heat Flux: ρ Lv <wq> ρ LvCE U Q Sensible Heat Flux: ρ cp <wθ> ρ cpch U Θ Momentum Flux: -ρ<uw> -ρ CD U 2 Direct Covariance Bulk Aerodynamic
11 Drag Coefficient Formulas Semi-empirical uw κ C D ( z / z0, z / L) = = 2 U ln( z / zo ) ψ m ( z / L) 2 Atmospheric Stability 2 κ uw C DN ( z / z0 ) = = 2 ln( z / z ) U o N Empirical 103 C DN (U10 N ) = TOGA-COARE 4.0 Surface Roughness U10 N 11 ms U10 N 11 U10 N 25 ms -1 Wind Speed Dependent Large & Pond (1981)
12 Drag Coefficient Formulas Semi-empirical uw κ C D ( z / z0, z / L) = = 2 U ln( z / zo ) ψ m ( z / L) 2 Atmospheric Stability 2 κ uw C DN ( z / z0 ) = = 2 ln( z / z ) U o N TOGA-COARE 4.0 Surface Roughness COARE parameterizes the roughness length as: ν u*2 zo = α + β (U10 ) u* g Charnock Parameter
13 MBL/CBLAST/CLIMODE Drag Coefficients ν u*2 zo = α + β (U10 ) u* g
14 Wave Age Dependent Drag u* / c p = U10 N 0.007
15 Wave Age Dependent Drag β = A(c p / u* ) B plus u* / c p = U equals ECMWF
16 Flux Time Series
17 Summary A wind speed dependent drag coefficient give good results over a wind range of sea-states/wave-ages. This requires a wind speed dependent Charnock variable Numerous investigations have shown that the Charnock variable is dependent on wave-age. However, these findings can be reconciled since observed wave ages over the coastal and open ocean are clearly associated with wind ranges.
18 QuikSCAT Wind Speeds
19 QuikSCAT vs. Buoy Wind Direction
20 QuikSCAT vs. Buoy Wind Speeds
21 Atmospheric Forcing Sikora et al. (1995) PO.DAAC
22 Stability Effects Near SST Fronts Boundary Layer Adjustment Baroclinic adjustment to horizontal temperature gradients. Acceleration/deceleration of surface winds. Surface Layer Adjustment QuikSCAT measures surface roughness/stress Surface stress is proportional to neutral winds, UN UN < U in unstable conditions UN > U in stable conditions Mesoscale Adjustment to SST fronts Combination of both?
23 QuikSCAT vs. Buoy Wind Speeds Surface Layer Adjustment U10 U10 U(z) = u*/κ[ln(z/zo) ψm(z/l)]
24 QuikSCAT vs. Buoy Wind Speeds Surface Layer Adjustment U10 U10 U(z) = u*/κ[ln(z/zo) ψm(z/l)] U10N U10N UN(z) = u*/κ[ln(z/zo)]
25 QuikSCAT vs. Buoy Wind Speeds Surface Layer Adjustment U10 U10 U(z) = u*/κ[ln(z/zo) ψm(z/l)] U10N U10N UN(z) = u*/κ[ln(z/zo)]
26 QuikSCAT vs. Buoy Wind Speeds Surface Layer Adjustment Larger than measured Smaller than measured U(z) = u*/κ[ln(z/zo) ψm(z/l)] UN(z) = u*/κ[ln(z/zo)]
27 QuikSCAT vs. Buoy Wind Speeds Surface Layer Adjustment Baroclinicity? U(z) = u*/κ[ln(z/zo) ψm(z/l)] UN(z) = u*/κ[ln(z/zo)]
28 QuikSCAT vs. Buoy Wind Speeds Boundary Layer (Baroclinic) Adjustment
29 Coupling Coefficients O Neill et al. (submitted)
30 30 Day Perturbations Courtesy of JHU/APL
31 QuikSCAT vs. Buoy Wind Speeds Boundary Layer (Baroclinic) Adjustment O Neill et al. (submitted)
32 QuikSCAT vs. Buoy Wind Speeds Boundary Layer (Baroclinic) Adjustment O Neill et al. (submitted)
33 QuikSCAT vs. Buoy Wind Speeds Boundary Layer (Baroclinic) Adjustment No obvious trend in perturbations when computed versus sea-air virtual temperature difference.
34 QuikSCAT vs. Buoy Wind Speeds Boundary Layer (Baroclinic) Adjustment However, it becomes more obvious when you only look at cold/cool air advection. JHU/APL
35 QuikSCAT vs. Buoy Wind Speeds Boundary Layer (Baroclinic) Adjustment However, it becomes more obvious when you only look at cold/cool air advection. JHU/APL
36 Summary A wind speed dependent drag coefficient give good results over a wind range of sea-states/wave-ages. This requires a wind speed dependent Charnock variable Numerous investigations have shown that the Charnock variable is dependent on wave-age. However, these findings can be reconciled since observed wave ages over the coastal and open ocean are clearly associated with wind ranges. Some of the variability in the QuikSCAT winds is due to adjustment of the neutral wind to changes in stratification and not changes in the actual wind speeds. This variability obeys MO-Similarity in the mean. This effect enhances the gradient in neutral winds but not actual. Significant variability in the QuikSCAT winds is not explained by this effect The one-buoy approximation of the coupling coefficients is in reasonably good agreement with previous studies. This includes the neutral wind, measured wind, and directly measured stress. The physical processes responsible for this correlation is Compare stress!
37 Thanks to NSF and NASA for supporting this research.
38 QuikSCAT vs. Buoy Wind Speeds Surface Layer Adjustment U10 U10 U(z) = u*/κ[ln(z/zo) ψm(z/l)] U10N U10N UN(z) = u*/κ[ln(z/zo)]
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