1. Radiance and weighting functions in limb-view geometry Jeroen van Gent & Roeland van Oss Jochen Landgraf & Holger Walter

2. J.I. van Gent – Limb Workshop, Bremen, April 2003 Contents Rationale Model criteria RT Method Preliminary results And then....

3. J.I. van Gent – Limb Workshop, Bremen, April 2003 Rationale Need for SCIAMACHY limb profiles. Algorithm must keep up with instrument data rate fast and accurate Requires limb radiances and weighting functions.

4. J.I. van Gent – Limb Workshop, Bremen, April 2003 Model criteria Accuracy Single scattering exact Well approximated multiple scattering Analytic weighting functions Speed Analytic ms solutions Locally plane- parallel

5. J.I. van Gent – Limb Workshop, Bremen, April 2003 θ φ Single scattering

6. J.I. van Gent – Limb Workshop, Bremen, April 2003 Multiple scattering θ φ

7. J.I. van Gent – Limb Workshop, Bremen, April 2003 Discrete ordinate method Plane-parallel equation of transfer Source function Series expansion: Fourier series; Legendre polynomials D.O.M:

8. J.I. van Gent – Limb Workshop, Bremen, April 2003 Lidort Simultaneous derivation of Radiance Weighting functions Method: differentiation

9. J.I. van Gent – Limb Workshop, Bremen, April 2003 Lidorta Analytic solution for 4 streams (N=2) and 6 streams (N=3) Speed ~ N 2 4 stream Lidorta vs. 20 stream Lidort: 25 x faster; accurate to 1.25% N=2 N=3

10. J.I. van Gent – Limb Workshop, Bremen, April 2003 Post-processing S2S2 S1S1 S Layer integrated source function J from Lidorta Interpolate J on line of sight Integrate along line of sight

11. Sciarali vs. Limbtran

12. J.I. van Gent – Limb Workshop, Bremen, April 2003 What’s next? Compare with existing RTMs Embed in Optimal Estimation Retrieval Algorithm ( OPERA – GOME Retrieval ) Apply to Sciamachy data SCIALINA – improved profiles