Validation of OMPS-LP Radiances

1. Validation of OMPS-LP Radiances P. K. Bhartia, Leslie Moy, Zhong Chen, Steve Taylor NASA Goddard Space Flight Center Greenbelt, Maryland, USA

2. Motivation • Find causes of large radiance residuals from the L2 algorithm • Improve altitude registration methods • Isolate systematic errors in measured and calculated radiances • Evaluate accuracy of MLS and NCEP data • Better understand information content of measurement

3. Methodology • Radiance Simulation • Bass & Paur cross-sections • Atlas/SUSIM solar irradiance • MLS O3, temp and GPH profiles • OMPS-NP reflectivity • limb RTM is scalar but nadir is vector • NO2 climatology, No aerosols • Measured data • Solar irradiances • Ungridded UV (290-350 nm) radiances from two “high gain” images

4. MLS GPH uncertainties Z* 64 km 48 km 32 km 16 km • 500 m error in GPH will produce ~8% error in calculated radiances • Error in T that causes GPH errors will produce additional error in radiances

5. Scalar radiance error at TH = 40 km, R = 0.3 Error is shown for λ = 325, 345, 385, 400, 449,521 nm (solid lines) and 602, 676, 756, 869, 1020 nm (dashed line) Same scalar radiance error pattern prevails for all wavelengths Amplitude at 345 nm is reduced (-3.5% to +5.5%), due to larger R

6. % change in 350 nm radiance due to aerosols % change shown for TH = 20, 25, 30, 35, 40 km Surface reflectivity = 0 λ = 350 nm

7. LP Focal Plan Schematic Low gain Ratio: 1:4.5 High gain Two interleaved exposures in 1:31 ratio Designed for sequencing HG Long/LG long/HG Short/LG short: 1: 4.5: 7: 4.5 Total dynamic range gain: x140

8. High Gain Image in UV No data HG long HG short No HG data There are systematic differences between HG & LG images so our plan is not to use LG image in the UV. This will free up some bytes for other use.

9. Optical distortions in HG Image Variation of wavelength with TH Fixed column no • l variation is smaller than instrument bandpass, but still needs to be corrected. • l variation is 4 times worse for LG image.

10. Optical distortions in HG Image Variation of TH with wavelength Fixed row no

11. Wavelength Under-sampling Radiances convolved with OMPS bandpass Without under-sampling corrn interpolation error can be as large as 3%

12. Solar Irradiance (SI) Comparison OMPS in FWHM/10 steps SUSIM smoothed with OMPS bandpass No l adj l error decreases +0.6 nm shift

13. SI comparison results • We have ~0.6 nm error in l in the 290-320 nm band • Error decreases with increase in l so it is not pixel shift type error • Bias remaining after +0.6 nm shift is partly due to l error and partly due to radiometric calibration errors

14. Explanation of large radiance residuals in L2 • Partly due to l error • Partly due to error in SI assumed in calculating the radiances in L2 • L2 SI doesn’t agree with Atlas/SUSIM

15. Radiance Comparison Example (49.5 km, 70S) Black: Measured Red: Calculated There may be spectral bias between radiance and irradiance. Radiance bias Irradiance bias

16. Alt Registration using 305 nm 305 nm not affected by reflectivity No O3 abs Strong sens to TH strong O3 abs weak sens to TH

17. An example: 70S April 2, 2012 600 m error No TH error Variation in est. TH error with alt is probably due to error in MLS GPH

18. Conclusions • Release 1 data has 0.6 nm l error in the UV. • This amounts to 10% error in O3 x-section. • Limb UV ozone profiles are therefore not reliable. • Error in VIS profile is TBD. • Release 1 altitude registration seems quite accurate (±300 m) • To improve accuracy we will need to rely on multiple approaches. • MLS temperature probably has larger bias in the mesosphere than MLS has estimated

19. Conclusions (cont’d) • Given uncertainties and low vert resolution of of NCEP temperature data it may not be possible to produce accurate/high precision MR profiles from LP above ~40 km • Density profiles are not affected by this problem • It may be possible to improve NCEP temp profiles above 40 km using LP, but this needs further investigation.