development and implementation progress of community radiative transfer model (crtm) yong han...
TRANSCRIPT
Development and Implementation Progress of Community Radiative Transfer Model
(CRTM)
Yong HanJCSDA/NESDIS
P. van Delst, Q. Liu, F. Weng, Y. Chen, D. Groff, B. Yan, N. Nalli, R. Treadon, J. Derber and Y. Han at JCSDA
JCSDA Workshop, May 31, 2006
Greenbelt Marriott Hotel
Community Contributions
• Community Research: Radiative transfer science AER. Inc: Optimal Spectral Sampling (OSS) Method NRL – Improving Microwave Emissivity Model (MEM) in deserts NOAA/ETL – Fully polarmetric surface models and microwave radiative transfer
model UCLA – Delta 4 stream vector radiative transfer model UMBC – aerosol scattering UWisc – Successive Order of Iteration CIRA/CU – SHDOMPPDA UMBC SARTA Princeton Univ – snow emissivity model improvement NESDIS/ORA – Snow, sea ice, microwave land emissivity models, vector discrete
ordinate radiative transfer (VDISORT), advanced double/adding (ADA), ocean polarimetric, scattering models for all wavelengths
• Core team (ORA/EMC): Smooth transition from research to operation Maintenance of CRTM (OPTRAN/OSS coeff., Emissivity upgrade) CRTM interface Benchmark tests for model selection Integration of new science into CRTM
Outline
• Major progress
• CRTM-v1 implementation
• Ongoing projects
Major Progress
• CRTM has been integrated into the GSI at NCEP/EMC (Dec. 2005)
• Beta version CRTM has been released to the public
• CRTM with OSS (Optimal Spectral Sampling) has been preliminarily implemented and is being evaluated and improved.
• New postdoc Yong Chen has recently joined CRTM development team.
CRTM-v1 implementation
Four main components– Atmospheric gaseous absorption (AtmAbsorption)
– Scattering and absorption by clouds and aerosols (AtmScatter)
– Surface optics; emissivity and reflectivity (SfcOptics)
– Radiative transfer solution (RTSolution) Four models
– Forward used operationally
– Tangent-linear
– Adjoint
– K-Matrix used operationally
CRTM Major Modules
Forward CRTM
SfcOptics(Surface Emissivity Reflectivity Models)
AerosolScatter(Aerosol Absorption
Scattering Model)
AtmAbsorption(Gaseous Absorption
Model)
CloudScatter(Cloud Absorption Scattering Model)
RTSolution(RT Solver)
Source Functions
public interfaces
CRTM Initialization CRTM DestructionJacobian CRTM
still developing
Gaseous Transmittance Model (AtmAbsorption)Compact OPTRAN
d
Ak
ch
chch
:
)exp(
6
10 )()()())(ln(
jjjch APAcAcAk
10,6,0,)ln()(0
,
njAaAcn
m
mmjj
Surface
A1
An
An-1
A0
K – absorption coefficient of an absorberA – integrated absorber amountPj – predictorsaj – constants obtained from regression
Level 0
Level n-1
Level n
Level 1
• Currently water vapor and ozone are the only variable trace gases and other trace gases are “fixed”.• The model provides good Jacobians and is very efficient in using computer memory
estimate layer transmittance
– spectral response function
Channel transmittance definition
0
0.02
0.04
0.06
0.08
0.1
1 3 5 7 9 11 13 15 17 19AMSU channel number
RM
S f
itti
ng
err
or
TotalDryWater Vapor
0
0.05
0.1
0.15
0.2
0.25
1 3 5 7 9 11 13 15 17 19
HIRS channel number
RM
S f
itti
ng
err
or
(K)
TotalDryWater vaporOzone
Radiance errors due to transmittance model uncertainty
Radiance Jacobians with respect to water vapor, compared with LBLRTM
Surface Emissivity/
Reflectivity Module
IR EM module over land
IR EM module over ocean
IR EM module over Snow
IR EM module over Ice
MW EM module over land
MW EM module over ocean
MW EM module over Snow
MW EM module over Ice
Surface Emissivity/Reflectivity Module and Sub-modules
IR Sea Surface Emission Model (IRSSE)
c0 – c4 are regression coefficients, obtained through regression against Wu-Smith model (1997).
,3
,10
42 ˆ,ˆ,,,, wcwc wcwcwcw
The IRSSE model is aparameterized Wu-Smith model for rough sea surface emissivity
IR emissivity database for land surfaces
Surface Type
Compacted soil Grass scrub
Tilled soil Oil grass
Sand Urban concrete
Rock Pine brush
Irrigated low vegetation Broadleaf brush
Meadow grass Wet soil
Scrub Scrub soil
Broadleaf forest Broadleaf(70)/Pine(30)
Pine forest Water
Tundra Old snow
Grass soil Fresh snow
Broadleaf/Pine forest New ice
Surface types included in the IR emissivity database (Carter et al., 2002):
NESDIS Microwave Land Emission Model (LandEM)
(1) Three layer medium:
)(,,2 2 TBLayer
desert, canopy, …
)1( 120 RI
120RI)1)(,( 210 RI
0I1,1 Layer
3,3 Layer)(31 TBeI
),( 1 I231 ),( RI
0
1
(2) Emissivity derived from a two-stream radiative transfer solution and modified Fresnel equations for reflection and transmission at layer interfaces:
)(22121
)(212
)(2
2112 01
0101
)()1(
])[1(]1)[1()1(
k
kk
eRR
eReRRe
Conditions using LandEM: over land: f < 80 GHz, use LandEM; f >= 80 GHz, e_v = e_h = 0.95 over snow: f < 80 GHz, use LandEM; f >= 80 GHz, e_v = e_h = 0.90
Weng, et al, 2001
(1) Emissivity Database:
cos)( 332
12
110 aTaTaTaaDI SBj
N
jjBj
N
jji
(2) Snow type discriminators are used to pick up snow type and emissivity:
Microwave empirical snow and ice surface emissivity model
Tb,j – e.g. AMSU window channel measurements
(3) Supported sensors: AMSU, AMSRE, SSMI, MSU, SSMIS
Microwave Ocean Emissivity Model
Model inputs: satellite zenith angle, water temperature, surface wind speed, and frequency
Model outputs: emissivity (Vertical polarization) and emissivity (horizontal polarization)
FASTEM-1 (English and Hewison, 1998):
Cloud Absorption/Scattering LUT
• Six cloud types: water, ice, rain, snow, graupel and hail
• NESDIS/ORA lookup table (Liu et al., 2005): mass extinction coefficient, single scattering albedo, asymmetric factor and Legendre phase coefficients. Sources:
IR: spherical water cloud droplets (Simmer, 1994); non-spherical ice cloud particles (Liou and Yang, 1995; Macke, Mishenko et al.; Baum et al., 2001).
MW: spherical cloud, rain and ice particles (Simmer, 1994).
RTSolution: Advanced Doubling-Adding Method (ADA)
AtmOpticsOptical depth, single scattering
Albedo, asymmetry factor,Legendre coefficients for
phase matrix
Planck functionsPlanck_Atmosphere
Planck_Surface
SfcOpticsSurface emissivity
reflectivity
Compute the emitted radiance and reflectance at the surface
(without atmosphere)
Compute layer transmittance,reflectance matrices by doubling
method.
Combine (transmittance, reflectance,upwelling source) current level and added
layers to new level
Output radiance
Loopfrom bottom totop layers
(New algorithm) compute layer sources from above layer transmittance and
Reflectance analytically.
Liu and Weng, 2006
1.7 times faster then VDISORT; 61 times faster than DAMaximum differences between ADA,VDISORT and DA are less than 0.01 K.
Ongoing Development
Zeeman effect (theta = 135, B = 0.5 Gauss), US standard Atmosphere
190
200
210
220
230
240
250
260
270
-0.004 -0.003 -0.002 -0.001 0 0.001 0.002 0.003 0.004
Frequency offset from 60.4348, GHz
Tb
(K
)RC, B = 0.5
LC, B = 0.5
RC, B = 0
LC, B = 0
Weighting function (km-1)
Height (km)
Ch20
Ch19Ch21
Ch22
Ch23
Ch24
Zeeman Effect
SSMIS upper-air soundingChannel weighting functions
Fast RT algorithm for SSMIS upper-Air sounding channels affected by Zeeman-splitting
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
19 20 21 22 23 24
SSMIS channel number
RM
S e
rro
r (K
)
Fitting Error
Independent test
Measurement Error(NEDT)
Predictors for estimating absorption coefficients:
Channels Predictors
19, 20 , cosB, cos2B, cos2B, B-1, B-2, cos2B/B2
21 , cos2B, B-1, B-2, B-3, B-4, cos2B/B2
22, 23, 24 , 2, cos2B, B-1
= 300./T, B – Earth magnetic field magnitudeB – angle between magnetic field and propagation direction.
RMS errors, compared with LBL model:
Nick Nalli's Ensemble IR Ocean Surface Emissivity Model
• Properly accounts for reflected downwelling radiance. Conventional approach to modeling IR surface-leaving radiance results in systematic underestimation of surface leaving radiance.
• The approach shows good agreement with M-AERI from CSP and AEROSE. Amounts to a 0.15-0.3% correction in emissivity; 0.1-0.2K correction in bias.
• Work beginning on integration into the CRTM.
Ongoing Development (Cont.)
• CRTM-OSS improvement; OSS LUT-generation software transfer from AER to JCSDA.
• UMBC SARTA forward algorithm implementation; SARTA TL and AD model development (Dr. Yong Chen)
• RTTOV transmittance module integration (Dr. Roger Saunders)
• OPTRAN-v7 improvement and integration
• Aerosol component development
• Visible component development
• CRTM test and validation
Summary
• CRTM has been successfully integrated in the NCEP/EMC GSI.
• CRTM-v1 is implemented with the following models: OPTRAN, IRSSE, LandE, NESDIS MW snow/ice empirical surface emissivity models and ADA radiative transfer solver.
• CRTM-OSS has been preliminarily implemented, tested and evaluated. Several areas have been identified for improvement. The OSS LUT software is being transferred to JCSDA.
• Ongoing development projects also include: fast RT algorithm for SSMIS Zeeman-affected channels, ensemble IR ocean surface emissivity model, integrations of OPTRAN-v7, SARTA and RTTOV and developments of aerosol and visible components.