Upload
janina
View
41
Download
0
Tags:
Embed Size (px)
DESCRIPTION
College of Engineering Space Physics Research Laboratory Department of Atmospheric, Oceanic & Space Sciences. A Combined Radar-Radiometer Approach to Estimate Rain Rate Profile and Underlying Surface Wind Speed over the Ocean. Shannon Brown and Christopher Ruf University of Michigan - PowerPoint PPT Presentation
Citation preview
A Combined Radar-Radiometer Approach A Combined Radar-Radiometer Approach to Estimate Rain Rate Profile and to Estimate Rain Rate Profile and
Underlying Surface Wind Speed over the Underlying Surface Wind Speed over the OceanOcean
Shannon Brown and Shannon Brown and Christopher RufChristopher Ruf
University of MichiganUniversity of Michigan
26 October 200426 October 2004
College of EngineeringSpace Physics Research Laboratory
Department of Atmospheric, Oceanic & Space Sciences
Brown and Ruf, 26 October 2004 2 of 19
IntroductionIntroduction
• Pacific Field Campaign– LRR-X 10.7 GHz radiometer
– PR-2 13.4 and 35.6 GHz Doppler radar
• Algorithm Overview• Retrieval in stratiform rain
– Effect of melting layer model
Brown and Ruf, 26 October 2004 3 of 19
LRR-X – Synthetic Thinned Aperture LRR-X – Synthetic Thinned Aperture RadiometerRadiometer
Visible Camera
LRR
• Point Reyes National Seashore, CA– DC-8 nadir video camera (left)– LRR-X TB image at 10.7 GHz, H-Pol (right)
• LRR-X Specifications– Synthetic aperture 1 meter2; Cross-track imaging– Spatial res @ 11 km altitude
• 381 x 466 m (nadir); 1079 x 629 m (45o cross track)
– NET of 0.3 K
Brown and Ruf, 26 October 2004 4 of 19
PR-2 – Dual Frequency Doppler RadarPR-2 – Dual Frequency Doppler Radar
• Operates at 13.4 and 35.6 GHz
• Scans cross-track to + 25o
• 37 m vertical resolution
• 800 m horizontal resolution
Brown and Ruf, 26 October 2004 5 of 19
June 13, 2003 Pacific Field CampaignJune 13, 2003 Pacific Field Campaign
VisibleIR
Flight Path
Brown and Ruf, 26 October 2004 6 of 19
Algorithm BasisAlgorithm Basis
• Physically based algorithm • Easily adaptable to multi-instrument platforms• Use radar to determine DSD
– Iteratively solve for two parameters of Gamma DSD at each range gate
– Determine RR(z) and W(z) from DSD(z)
• Use DSD and TB to determine wind speed– Determine absorption and extinction profile from DSD
– Remove atmospheric component to determine surface emissivity
Brown and Ruf, 26 October 2004 7 of 19
Stratiform RetrievalsStratiform Retrievals
• Radiometric retrieval in light stratiform rain driven by absorption in the melting layer– Passive rain retrieval
– Surface parameter retrieval
1500 m
Brown and Ruf, 26 October 2004 8 of 19
Stratiform RetrievalsStratiform Retrievals
• (Bottom left) Retrieved wind speed without Melting Layer
• (Bottom right) PR-2 retrieved rain rate
Brown and Ruf, 26 October 2004 9 of 19
Melting Model AnalysisMelting Model Analysis
• Choose melting layer model based on fit to PR-2 data
• Apply to radiometric retrieval• Thermodynamic model from Mitra et al. 1990
– Ventilation coefficient
– Initial snow density
– Electromagnetic model
Brown and Ruf, 26 October 2004 10 of 19
Electromagnetic ModelsElectromagnetic Models
Maxwell-Garnett Dielectric Model
Water | { air inclusions in ice matrix}
{ice inclusions water matrix} | air
air | {ice inclusions water matrix}
{air inclusions in ice matrix} | water
Strongest
Weakest
absorption
scattering
Fabry-Szyrmer Core-Shell
Meneghini and Liao
Brown and Ruf, 26 October 2004 11 of 19
Fitting ProcedureFitting Procedure
• Assume particle mass conservation • Stationary assumption
• Lapse rate set to 7.7 K/km (from RaOb)• RH assumed to be 100 %
)(/)()()( DVDVDNDN mwwm
Brown and Ruf, 26 October 2004 12 of 19
Fitting ProcedureFitting Procedure
• Analyzed ~ 100 profiles with basal reflectivities of 25 – 31 dBZ
Base of Melting Layer Reflectivity Peak in Melting Layer
Brown and Ruf, 26 October 2004 13 of 19
Fitting ProcedureFitting Procedure
Estimate D0 from dBZm(13.4) using average N0
Melting Layer Model
(Fm, ρs, εm)
N0init, D0
init, μ
Attenuation Correction
τ melt(13.4), τmelt (35.6)
Estimate N0, D0
dBZ(13.4), dBZ(35.6)
Melting Layer Model
(Fm, ρs, εm)N0, D0, μ
Brown and Ruf, 26 October 2004 14 of 19
Fitting ProcedureFitting Procedure
1. {ice inclusions water matrix} | air
2. Fabry-Szyrmer Core(1)-Shell(3)
3. air | {ice inclusions water matrix}
Brown and Ruf, 26 October 2004 15 of 19
Melting Model AnalysisMelting Model Analysis
Dielectric Formula 13.4 Peak Bias
(dB)
35.6 Peak Bias (dB)
13.4 Width Dif. (dB)
Fraction of Opacity
Mean Wind Speed
(1) Water | { air inclusions in ice matrix}
5.2 3.1 1.4 0.72 0.03
(2) {ice inclusions water matrix} | air
3.8 2.5 1.0* 0.66 0.63
(3) Fabry-Szyrmer Core-Shell
-0.3 0.23* 0.37 0.45 9.9
(4) air | {ice inclusions water matrix}
-1.1 0.43 -0.23 0.43 10.3
(5) {air inclusions in ice matrix} | water
-2.3 0.54* -0.52 0.32 12.1
Brown and Ruf, 26 October 2004 16 of 19
Melting LayerMelting Layer
• Combination of MG models fits PR-2 data well– FS core shell
• Snow density model – lowest retrieval error in snow layer produces best fit in melting layer– FS model most sensitive to snow density variations
– ~ 2K variation between different density models/ventilation coefficient
Brown and Ruf, 26 October 2004 17 of 19
Effect on RetrievalsEffect on Retrievals
No Melting Layer
FS core shell
Retrieved Rain Rate
Brown and Ruf, 26 October 2004 18 of 19
Effect on RetrievalsEffect on Retrievals
• Addition of melting layer reduced the wind speed retrievals by 30 to 40 %
• Increased radar retrieved rain rates approximately 10 %
Fraction of Atmospheric Brightness at 10.7 GHz due to melting layer (FS model)
Brown and Ruf, 26 October 2004 19 of 19
ConclusionsConclusions
• Melting layer contributes the majority of the atmospheric absorption in the microwave
• Radiometric retrievals in stratiform rain require an accurate model for the melting layer
• Electromagnetic models which blend MG mixing formulas produce the best results
• FS core shell model fit PR-2 data well and produced reasonable wind speed retrievals
Brown and Ruf, 26 October 2004 20 of 19
Algorithm BasisAlgorithm Basis
Radar DataInvert Backscatter
Equation to get DSD(z)
Correct for attenuation
)(
)(
zT
fMb
Mie Theory
),(),,(),,( Hszfzf fp
absp
ext
DSD(z), T(z)),( Hsf
Invert RTE to get
)( h
Invert Surface Emissivity Model to get Wind Speed
),(),,( zfzf pabs
pext
)( h
Radiometer Data
)( fTB
Output RR(z), W(z), WSpd
Ancillary Data (e.g. SST, mv,
ρv)
Brightband Detection get T(z)
dBZ(f), Vr, LDR
)(
)(
zT
fb
DSD(z)
WSpd
),(
),(
zf
zfcabs
gabs
sfcT