1

JCSDACommunity Radiative Transfer Model

(CRTM)

Paul van Delst (CIMSS)Yong Han (NESDIS)Quanhua Liu (QSS)

5th MURI Workshop

7-9 June 2005

Madison WI

JCSDA Mission

Accelerate and improve the quantitative use of research and operational satellite data in weather and climate prediction models

JCSDA Partners

NOAA/NWS/NCEPEnvironmental Modeling Center

NASA/GSFCGlobal Modeling & Assimilation Office

NOAA/NESDISOffice of Research and Applications

NOAA/OAROffice of Weather and Air Quality

US NavyOceanographer of the Navy

Naval Research Laboratory (NRL)

US Air ForceAir Force Director of Weather

Air Force Weather Agency

JCSDA Goals

Reduce from two years to one year the average time for operational implementation of new satellite technology

Increase uses of current satellite data in NWP models

Advance the common NWP models and data assimilation infrastructure

Assess the impacts of data from advanced satellite sensors on weather and climate predictions

CRTM Contributors JCSDA/CIMSS. Framework, CloudScatter, IR SfcOptics

for water, RTSolution for validation (VDISORT) AER Inc; Jean-Luc Moncet’s group. OSS AtmAbsorption. NOAA/ETL; Al Gasiewski’s group. CloudScatter (W) and

RTSolution. NASA/GSFC; Clark Weaver. AerosolScatter (IR). NOAA/NESDIS; Fuzhong Weng’s group. Microwave

SfcOptics for land, snow, ice. AOS/SSEC/CIMSS/UWisc-Madison; Ralf Bennartz’s

group. SOI RTSolution. UCLA; Kuo-Nan Liou’s group. -4 stream RTSolution.

CRTM Schematic

What is the CRTM Framework? At the simplest level, it’s a collection of structure

definitions, interface definitions, and stub routines. There are User and Developer interfaces, as well as

Shared Data interfaces and I/O.

The radiative transfer problem is split into various components (e.g. gaseous absorption, scattering etc) to facilitate independent development.

Want to minimise or eliminate potential software conflicts and redundancies.

Components developed by different groups can “simply” be dropped into the framework.

Faster implementation of new science/algorithms.

Why do this?

http://cimss.ssec.wisc.edu/~paulv/CRTM

AtmAbsorption (1)

OPTRAN OSS

Total channel resolution transmittance

Predict band transmittance for each absorbing gas from absorption coefficient, , predicted from regression fits

Select the regression coefficients, cijk, for each gas that minimises transmittance errors.

Channel radiances are obtained from a weighted sum of monochromatic radiances for a set of predefined nodes,

The monochromatic Rn are obtained from the OSS monochromatic optical depth profiles for the selected node frequencies. Nodes are selected and weights calculated for a channel to satisfy a specified accuracy (e.g. 0.05K).

Higher accuracy more nodes longer computation times.

Two methodologies– OPTRAN. Polychromatic (two versions). Adjoint Jacobians.– OSS. Monochromatic. Analytic Jacobians.

J

jjtotal c

1

N

nnnRwR

1

5

1,,,,0

,

1,,,

log

ikjkjik

kj

kjkjkj

Xcc

A

AtmAbsorption (2)

Computation and Memory Efficiency

Instrument OPTRAN-V7Adjoint

CompactOPTRANAdjoint

OSSAdjoint

AIRS 22m36s 35m12s 3m10s

HIRS 13s 17s 9s

Time needed to process 48 profiles with 7 observation angles

Instrument OPTRAN-V7Double precision

CompactOPTRANDouble precision

OSSSingle precision

AIRS 66 5 97

HIRS 0.5 0.04 4

Memory resource required (Megabytes)

CloudScatter (1) NESDIS/ORA lookup table (Liu et al, 2005).

– Mass extinction coefficient– Single scatter albedo– Asymmetry factor– Legendre phase coefficients and delta-truncation factors for 2-, 4-,

6-, 8-, and 16-streams– Analytic phase functions (HG and Rayleigh)

Infrared (Intensity only)– Spherical particles for liquid water and ice cloud (Simmer, 1994)– Non-spherical ice cloud (Liou and Yang, 1995; Macke et al,1997;

Baum et al, 2001) Microwave (including polarisation)

– Spherical particles for rain drops and ice cloud (Simmer, 1994) The number of streams is determined using Mie size

parameter, 2reff/

CloudScatter (2)

ETL library is microwave only, fixed stream (8) Mie spherical scattering model Five hydrometeor phases, exponential size distributions Phase functions

– Currently, Henyey-Greenstein phase function matrix.– Being extended to incorporate full Mie scattering phase functions

via an exact Mie library. Currently, no polarisation capability. Scattering matrix Jacobians are analytical.

AerosolScatter Currently only handles aerosol absorption. Aerosol scattering is

planned. Seven aerosol types

– Dust– Sea salt– Dry and wet organic carbon– Dry and wet black carbon– Sulfates

Multiple size distribution modes. Uses same scattering structure definition as CloudScatter

routines

SfcOptics Microwave

– Land (Weng et al, 2001); Snow and sea ice (Yan and Weng, 2003)– Ocean

Wind vector dependent (Liu and Weng, 2003) Wind speed dependent (English, 1998; FASTEM-3)

Infrared– Land

Measurement database for 24 surface types in visible and infrared (NPOESS Net heat Flux ATBD, 2001)

Regression methods Retrieval methods

– Ocean IRSSE (van Delst, 2003). Based on Wu-Smith (1997) model. Nick Nalli (NESDIS/ORA) also working on sea surface emissivity and

reflectivity model.

New surface optical models are also being developed by other groups (Land data assimilation folks)

RTSolution (1) SOI, Successive Order of Interaction (UWisc-Madison)

– Truncated doubling technique for layer transmission, reflection and source functions. Successive order of scattering (SOS) used to integrate emission and scattering events from surface and atmosphere. IR and W. (Heidinger et al, 2005)

Vector delta 4-stream (UCLA)– Delta truncation is applied to reduce phase functions to four

expansion terms. The optical depth and single scattering albedo, as well as the expansion coefficients, are rescaled to take account of strong forward scattering. The layer transmission, reflection, and source functions are solved analytically. Adding method is used for vertical integration. IR and W. (Liou et al, 2005)

RTSolution (2) DOTLRT, Discrete ordinate tangent linear raditive transfer

(NOAA/ETL)– Layer transmission and reflection computed using a matrix operator

method. Symmetric phase matrix is used to simplify matrix manipulation. Layer source function is obtained from the transmission and reflection. Adding method is used for vertical integration. IR and W. (Voronovich et al, 2004)

– No polarisation capability.

VDISORT (NOAA/NESDIS/ORA)– Used for validation.– Valid for visible, infrared and microwave sensors; fully polarimetric

(all Stokes vectors).– Matrix operator method is used for layer transmission, reflection

and source functions. Vertical integration is performed with linear algebra system where continuity at boundaries is ensured. (Weng and Liu, 2003)

Current Status Currently we are working on the integration of the various CRTM

components. Goal is to produce a working version of an OSS-based CRTM by

end of June (!). An OPTRAN-based model is also being worked on for migration

purposes in the GFS. The development process was deliberately informal so there is a

bit of integration work still to do. Some codes have to be modified from a channel-based form

(e.g. IRSSE model) to a frequency-based form for use with OSS. Other outstanding issues are that some codes produce analytic

Jacobians rather than coding adjoints via the forward tangent linear adjoint K-matrix methodology….

Jacobians. Analytic or adjoint? Here I’m talking about the use of Jacobians in NWP. Other

applications may have other requirements.

Analytic Jacobians are generally not suitable for variational analysis. This is difficult to prove, but experience in NWP has shown this to be the case.

The Jacobian has to take into account any numerical approximations used in the forward model, e.g. quadrature, regression fitting, interpolations, etc.

The Jacobian has to be entirely numerically consistent with the forward model.

Minimisation algorithms in NWP are sensitive to very small inconsistencies or errors.