Potential of multi-frequency Doppler spectra for rain, snow, and ice cloud

studies

Current Limitations due to Doppler spectra quality

Stefan Kneifel, Pavlos Kollias - McGill Frederic Tridon – Univ. Leicester

Ed Luke - BNL

Scientific objectives and principal technique

Why using Doppler spectra instead of moments and why multi-frequency?

Considering just microphysics, Doppler Spectra depend

on:

Particle size distribution N(D)

Size – fall velocity relation v(D)

Size – backscattering relation

N(D) and v(D) are frequency independent and thus, the spectra should perfectly match in the „small“ particle region (slow falling Rayleigh scatterers) and increasingly deviate from each other for larger and faster falling particles.

Case of rain with the Ka-W band combination

• Scattering with the Ka-W band combination– Rayleigh conditions not

satisfied as a whole– But, smallest drops scatter in

the Rayleigh regime their contribution on the DWR depends on differential attenuation only

• Doppler spectra ratio (DSR)– Drops sorted according to their

fall velocity and size with Vt=f(D) (Atlas et al., 1973)

– The DSR emphasizes the two scattering regimes

• Rayleigh regime plateau• Mie region (with two peaks)

Quasi universal pattern

15/09/2011: homogeneous light rain DSR shape agree well with theory possible to disentangle the Mie and attenuation effects

(Tridon et al. (2013), Geophys. Res. Lett., 40) But some spectra issues prevent this method with the KASACR data (while its volume better

match the measurements of the WSACR) and on more inhomogeneous cases

Presentation of the DSR technique during MC3E session on Monday

Confirmation with KAZR and WSACR data

Additional challenge for ice: Habit dependence of scattering

(Back-)scattering depends on particle size/mass, habit and frequency

Ku (13.4 GHz) Ka (36.5 GHz) W (89 GHz)

‚Soft‘ spheres ‚Soft‘ ellipsoids

Multi-frequency signatures of snowfall seem to be size AND habit dependent

Theoretical triple frequency signatures indicate habit-related signatures…

Observed triple frequency signatures in Wakasa Bay aircraft data by Kulie et al., JAMC, 2013

Aggregates??

Graupel??

Light snowfall example: Ka – W band Spectra

NSA, 12.Feb.2012, 08:52 UTC

KaZR-spectrum: blackWSaCR-spectrum: yellow

Frequency independent Rayleigh scattering region (plateau in spectral DWR)

Mie scattering region

Examples of multi-wavelength spectra from different sites with focus on problematic data quality issues

WSACR narrow Nyquist velocity

CaseKASACR WSACR

VNyq [m/s]

Pulse [m]

VNyq [m/s]

Pulse [m]

10/06/2011 ± 10 455 ± 7.2 45

16/09/2011 ± 10 455 ± 7.2 45

17-18/09/2011

± 10 455 ± 7.2 45

11/12/2011 ± 10 200 ± 4 50

08/03/2012 ± 10 263 ± 4 240

08/07/2012 ± 10 263 ± 4 240

05/08/2012 ± 10 1350 ± 4 240

14/08/2012 ± 10 1350 ± 4 240

18/08/2012 ± 10 1350 ± 4 240

24/08/2012 ± 10 1350 ± 4 240

25/08/2012 ± 10 1350 ± 4 240

25-26/08/2012

± 10 1350 ± 4 240

13-14/09/2012

± 10 1350 ± 4 240

12/10/2012 ± 10 1350 ± 4 240

15/12/2012 ± 10 1350 ± 4 240

Rain spectra can extend over more than 8 m/s width a Nyquist velocity of ± 4 is insufficient

Need wider Nyquist velocity in rain but narrower in ice (cloud and snow) temperature dependant modes?

2600m1500m

800m

kazr-kasacr comparisonRange and time kasacr spectrograms

Spurious bulges appear at the sides of kasacr spectra where there should be only

noise (kazr)

15 Sep 2011 19:32 to 19:58

KASACR spectra artefact

WSACR / KaSACR should be THE perfect tool for snowfall studies.

• WSACR and KaSACR: Very accurate beam matching, similar beam widths, average times, range resolution, …

• NSA WSACR and KaSACR: Spectra from ice clouds show very different spectral width. Time sampling and averaging should be exactly the same; also same range resolution

NSA - KaSACR NSA - WSACR

NSA, 11.07.2013

WACR @ PVC has similar problems (12.04.2013)

Current issues with SACRs: Spectral side lobes

NSA - WSACR

NSA - WSACR

NSA - KaZR

NSA - KaZR

• KaZR shows interesting secondary peak – no spectral sidelobes!• The multiple artifacts in the WSACR makes it impossible to distinguish

artifacts from microphysical signals!• It also affects estimation of radar moments (e.g. skewness, kurtosis,

etc)• Similar artifacts found in the SGP SACRS (but different strength and

not all time periods) and PVC WACR.• Can this be solved/avoided somehow?

NSA, 14.01.2013

Importance of matching in rangeFor best results, the volume should be exactly matched in range i.e. with the same volume centres and sizes (pulse width and range weighting function when pulse coding)

DSR: KASACR-WSACR DSR: KAZR-WSACR

Closest gateOnly 5 m shift!

Importance of matching in rangeOtherwise some interpolation can alleviate the mismatch but not completely in case of inhomogeneous volume

Weighted interpolation between the two closest gates

KASACR-WSACR KAZR-WSACR

Conclusions, Recommendations, and Discussion

Requirements for Doppler spectra analysis (rain/snow/ice cloud specific)

First spectrum analysis clearly indicates that multi-frequency spectra contain wealth of information about cloud and precipitation microphysics.

However, requirements for spectral analysis are very demanding:

„Perfectly“ vertically matched radar volumes -> same pulse width, same range gates, same range weighting function

„Perfect“ beam alignment Possibility of variable Nyquist range for rain and

ice/snow clouds Similar or same velocity resolution for spectra (at least for

both SACR) Same temporal averaging/sampling Radar calibration

Sanity check: Ice clouds -> Multi-frequency spectra MUST match (small ice = Rayleigh

scatterers)

IOP idea: Check radar settings in ice part (Rayleigh)

SGP - KaZR SGP - KaSACR SGP - WSACR

KaZR:0.3 m/s

KaSACR:0.7 m/s

WSACR:0.7-0.8 m/s

SGP, 20.04.2013

Collecting Off-zenith SACR Spectra During Scanning

Motivation Enhanced perspective on cloud process evolution Increased opportunity for data QC Reduction of large time-gaps lacking spectra (esp. at W band) Availability of controlled off-zenith data will drive innovation Offers a controlled development test-bed for moving platforms

Approach

Start small (e.g. with IOP) Collect occasional full RHI scans Can radar be modified to always save spectra for theta < e?

Observing Microphysics with Off-zenith Spectra

ref_primdv_prisw_priskew_pri,kurt_pri,snr_pri,lslope_pri,rslope_pri

ref_secmdv_secsw_secskew_sec,kurt_sec,snr_sec,lslope_sec,rslope_sec

v_leftpeak_pri,dynr_leftpeak_pri

v_rightpeak_pri,dynr_rightpeak_pri

dynr_pri,Vpeak_pri

dynr_sec,Vpeak_sec

vmin_sec vmin_pri vmax_privmax_sec

noise

npeaks_pri

A 256-bin Doppler spectrum experiences shape distortion of less than 1 bin induced by pointing angles up to 7 degrees off zenith.

Observing Microphysics with Off-zenith Spectra

Non motion-compensated spectrum skewness during MAGIC

ARM – IOP with focus on Doppler spectra from ice, and snow clouds (rain might follow)

• First IOP at NSA site with focus on ice clouds and snowfall:– Find out which settings are optimum (time, range

resolution, etc.) in order to investigate the various processes (nucleation, aggregation, riming, etc.)?

– How good can we get the spectra matching in the Rayleigh part of the spectrum from KaZR, KaSACR, WSACR if we run them simultaneousely and with similar settings (range, time res., zenith looking)?

– What are benefits/disadvantages of pulse compression regarding spectra?

Additional snowfall specific experiments within IOP:

– Perform slow RHI scans with KaSACR/WSACR and XSAPR in the same vertical plane to obtain triple frequency signatures

– Compare triple frequency signatures to novel in-situ data (3D snowflake camera MASC) -> Are the trip.-freq. signatures really so strongly related to snowfall habit?

Let‘s start discussing now…

More about Doppler Spectra in „Fingerprinting“ session on Wednesday…

Backup Slides for Discussion

Current issues with NSA SACRs: Spectral side lobes

NSA - KaZR NSA - WSACR

Number and strength of „side lobes“ increase with magnitude of real signal; first artifacts at ca. -15 dBZ for KaSACR and ca. -11 dBZ for WSACR

Comparison WSACR – KaZR: Higher ice part

Despite the different range resolution (25 m vs 30 m), the spectra in the ice part are matching extremely well.

NSA - KaZR NSA - WSACR

NSA - KaZR NSA - KaZRNSA - WSACR NSA - WSACR

Comparison WSACR – KaZR: Lower snow part

In the snowfall part (900 m), the WSACR seems to be shifted by 0.1-0.2 m/s towards larger fall velocities (or KaZR is too slow…?) – Note the shift is independent of the velocity regime -> no Mie scattering effect!

NSA - KaZR NSA - WSACR

NSA - KaZR NSA - KaZRNSA - WSACR NSA - WSACR

Light rain observed by ARM radars at SGP

+++

• Need well-matched beams to avoid artefacts

• Light stratiform rain with higher Z fall-streak zoom to avoid BB and low SNR due to wind shear

• Dual wavelength ratio– increase with height

because of rain and gas attenuation

– except right above the fall-streak possible with important Mie effect in the fall-streak due to larger drops

• Check by looking at spectra

Confirmation with KAZR and WSACR dataKAZR WSACR KAZR-WSACR