JCSDA Community Radiative Transfer Model (CRTM)

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

2. JCSDA Mission • Accelerate and improve the quantitative use of research and operational satellite data in weather and climate prediction models JCSDA Partners

3. 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

4. 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.

5. CRTM Schematic

6. 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. Why do this? • 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. http://cimss.ssec.wisc.edu/~paulv/CRTM

7. AtmAbsorption (1) • Two methodologies • OPTRAN. Polychromatic (two versions). Adjoint Jacobians. • OSS. Monochromatic. Analytic Jacobians.

8. AtmAbsorption (2)Computation and Memory Efficiency Time needed to process 48 profiles with 7 observation angles Memory resource required (Megabytes)

9. 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, 2reff/

10. 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.

11. 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

12. 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)

13. 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)

14. 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)

15. 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….

16. 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.