Post on 16-Dec-2015
Water vapor estimates using simultaneous S and Ka band
radar measurements
Scott Ellis, Jothiram VivekanandanNCAR, Boulder CO, USA
Background
• NCAR S-Pol radar upgraded with simultaneous S- and Ka-band measurement capability– Matched beam widths– Matched range gates
S-band antenna
Ka-band antenna
• For Rayleigh scatterers reflectivity differences can be related to attenuation by liquid and gas
Objectives• Retrieve path-integrated humidity
– Differential gaseous absorption
– Compare reflectivity at nearest edge of cloud
– Create profile by plotting mid-point of path integrated estimates
Range
Hei
ght
Range resolved cloud liquid
Path integrated water vapor profiles
++
+
• Retrieve range-resolved liquid water content (LWC) and median volume diameter (MVD) through clouds– Differential absorption through
clouds
+
+
Method
• Remove non-meteorological targets• Determine where Rayleigh scattering
approximation is valid at Ka-band– Use S-band dual-pol measurements
• < 1 mm drops– Estimate D0 from S-band Z and ZDR– D0 must be < 0.5 mm
• Z at S-band < 20 dBZ• ZDR < 0.4 dB
– Produce Rayleigh mask
• Estimate attenuations– Liquid– gaseous
Blue = Mie Brown = Rayleigh
Example PPI plot of Rayleigh mask of cloud field during RICO
Distance from radar (km)
Method: Humidity retrieval
• Run radiation model many times varying T, P and specific humidity (SH, g m-3)
• Compute polynomial fit of SH to attenuation
Spe
cifi
c hu
mid
ity
(g m
-3)
1-way atm attenuation (dB km-1)
SH = 201.40A3 – 209.60A2 + 120.55A – 2.25
Where SH is specific humidity (g m-3) and A is gaseous attenuation (dB km-1)
Method: Liquid retrieval
• Liquid water attenuation at Ka-band (Aka) linearly related to LWC (g m-3) – No dependence on drop size distribution
– Small temperature correction (CT)
• MVD (mm) retrieved from LWC and reflectivity (Ze, mm6 m-3)
LWC = 0.74*Aka*CT
MVD3 = 2.16 x 10-4*Ze/LWC
Results from RICO
+ radar retrieval – primary ray + Radar retrieval – secondary ray - Sounding
Without dry layer
With dry layer
RMS difference: sounding (g m-3)
0.85 1.40
Results from RICO
+ radar retrieval – primary ray + Radar retrieval – secondary ray - Sounding - Average sounding
Average sounding computed at height H as the average specific humidity from 0 to 2*H
Results from RICO
+ primary ray + secondary ray - Sounding - Average sounding
Sounding average humidity for secondary ray
Results from RICO
+ radar retrieval – primary ray + Radar retrieval – secondary ray - Sounding
RMS difference: sounding (g m-3)
0.75
LWC and MVD retrievalsS-band reflectivity (dBZ) with C-130 track displaying LWC (g m-3) collected from RICO 12 January, 2005
C-130
LWC and MVD retrievals
S-band reflectivity (dBZ) LWC (g m-3)
Distance from radar (km) Distance from radar (km)
C-130
LWC and MVD retrievals
Outliers due to attenuation underestimates
MVD (mm) LWC (g m-3)
Distance from radar (km) Distance from radar (km)
Future work -- planned• Automate algorithms• Further verification
– Use aircraft/radar matching technique for LWC
• Algorithm refinements– Humidity
• Compute humidity – attenuation relationships for several layers and use most appropriate one
• Compute optimal humidity profiles using primary and secondary rays
– LWC/MVD• Improve attenuation estimation to remove outliers
• Account for increased attenuation in non-Rayleigh rain
Future work -- planned
• Compare dual-wavelength humidity with refractivity, GPS, water vapor DIAL, radiometer… during REFRACTT 06 and COPS 07
• Combine humidity retrieval with near-surface refractive index humidity for radar based 3-D moisture field
• Detection/quantification of super-cooled liquid water– Microphysics
– Aviation safety
Future work -- desired
• Partner with international community to verify satellite derived and model microphysical products– Cloudsat
• Cloud fraction
• LWC
• Ice content
– NASA GPM
• Partner with data assimilation community
Discussion
• Possible to obtain accurate path-integrated water vapor estimates in boundary layer
• Both horizontal and vertical distributions can be obtained
• Depends on cloud distribution
• Path integration limits resolution
• Not automated yet
• Can be automated
Sources of error
• Failure to exclude contamination
• Errors in humidity- and liquid- attenuation relationship
• Radar calibration errors
• Modification of humidity by environmental conditions by clouds; e.g. moist, cool outflows
Sources of error• Radar calibration
– Errors in reflectivity differences
Errors in attenuation and humidity resulting from errors in dBZ differences (S – Ka)
Method: creating secondary rays method 2 (not implemented yet)
S-band reflectivity (dBZ)
Ka-band reflectivity (dBZ)
Method: creating secondary rays method 2 (not implemented yet)
S-band reflectivity (dBZ)
Ka-band reflectivity (dBZ)