Turbulence, Case Studies, and Comparisons f or StormVex and CAMPS

1. Turbulence, Case Studies, and Comparisons for StormVex and CAMPS Matthew Shupe University of Colorado 6 February 2012, Steamboat Springs, CO

2. Turbulent Dissipation Rate Retrieval Time-variance of mean Doppler velocity (assume last two terms are small): svm2 = sw2 + svt2 + 2 cov (w, vt) It has been shown that: S(k) = A e2/3 k-5/3, A is the Kolmogorov constant Lt= Ut + 2Rsin(q/2), U is horizontal wind speed, q is beamwidth t is the sample time, either 1 or 30-60 seconds (must remain in inertial subrange) Re-arrange to get (function of mean Doppler velocity variance and windspeed):

3. An Example Turbulence related to variance in mean Doppler velocity Spectral width is an independent indication of turbulence See some structure in depol ratio that may be related to turbulence impacts on ice properties

4. Case Comparisons with Aircraft Retrieval nicely captures the magnitude and vertical structure. Red solid is mean, retrieved dissipation rate Horizontal red bars are 5-95th percentile range over case Dots are aircraft measurements, color-coded with distance from THD

5. Case Comparisons with Aircraft Some cases of over- and under-estimation wrt aircraft. Aircraft when through some clear sky briefly.

6. Case Comparisons with Aircraft Lots of scatter, but generally follows the 1-to-1 line. Retrievals biased high at low values and low and high values. Aircraft data are 10-sec averages, color coded with horizontal distance from THD. Radar retrievals are 2-min averages around time-height of aircraft obs.

7. Case Comparisons with Aircraft Retrievals tend to capture the general distribution relatively well. Do not capture as many of the highest dissipation rates.

8. Case Comparisons with Aircraft and other Evaluations • RMS difference is less than an order of magnitude; highest at lowest values • Other evaluation cases are from the Arctic using aircraft (MPACE) or sonic anemometer on a tethered balloon (ASCOS) • “ASCOSsonic” is a comparison of tethered sonic and a sonic on a tower (i.e., the same basic measurement approach). • Arctic retrievals compare similarly or better than two sonics! • Still some work to improve the comparison data set for StormVex. Note: All stats are computed using Log10(e) Thus, RMS difference of 1 is equivalent to an order of magnitude

9. Case Studies (Under Development)

10. Horizontal Grid Patterns @ 2 Heights and Spiral Descent Color shows distance to THD SPL and THD Color shows time of flight

11. Remote Sensors At THD For all plots to follow: 1) Aircraft flight track: Time-height given plotted with color proportional to distance to THD (blues being closest). 2) Black line is estimated lowest cloud base height. • The Scene • Three-layers of supercooled liquid water (but not much). • Ice crystals precipitating from each layer. • Aircraft sampled in two different layers, generally in the liquid portion of these mixed-phase clouds.

12. Some Derived Products • Dynamics: Four layers of turbulence, top three of which are turbulent mixed-layers associated with the cloud liquid (driven by radiative cooling). • Ice Microphysics: Three radar techniques: Z-V IWC does not agree with the Z(LI) and Z-T (HO) results. Likely related to issues with 20-min average. • Microphysical Processes: When single layer present after 24:00, see good correlation between LWP and IWP.

13. Aircraft Measurements • Upper Layer: -31 C, Nd=25-35 cm-3, LWC=0.01-0.1 g/m3, Ni generally <10 L-1. • Lower Layer: -18 C, Nd=40-60 cm-3, LWC=0.1-0.3 g/m3, very little ice observed. • Ice shower: (23:30). Increase in ice # and mass, decrease in liquid #, increase in drop size (?), but LWC stays same. • Turbulence: Higher diss. rate when in liquid, lower when in ice-only. Similar rates for both clouds in spite of big temperature differences (and probably different amounts of LWP).

14. Evaluating IWC with Aircraft Measurements Z retrieval misses the extreme high and low values Z-T retrieval improves on the low end values but still misses high values Z-V retrieval nicely captures the high end values but unable to get low values. Aircraft data are 10-sec averages. Radar retrievals are 2-min averages around time-height of aircraft obs.

15. Comparison of two cases (Both with NW winds)

16. Remote Sensor Measurements Similar reflectivity Larger, more variable MDV (waves?) Larger spectral width Higher depol Similar cloud base Much more liquid (is this real?)

17. Remote Sensor Retrievals Drastically different LWPs but very similar ice magnitudes and variability Significant differences in turbulence structure.

18. Aircraft Measurements 40-60 cm-3 and 0.05-0.5 g/m3 70-90 cm-3 and 0.5-1 g/m3 Not much ice near top Bi-modal turbulence (in vs. out) Similar cloud top T at about -17 to -20 C

19. Case Profile Comparisons • Evidence of well-mixed layers in thermodynamic structure • Distinct turbulent profiles showing source of turbulence generation. • Larger, more variable MDV in 2nd case • Larger, horizontal winds in 2nd case (driving larger turbulence)

20. Some Crystal Photos 18:09Z 18:09Z 22:30Z 22:31Z 22:32Z 20:27Z