Validation of OMPS-LP Radiances

P. K. Bhartia, Leslie Moy, Zhong Chen, Steve Taylor

NASA Goddard Space Flight CenterGreenbelt, Maryland, USA

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

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

MLS GPH uncertainties

64 km48 km32 km16 km

Z*

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

Scalar radiance error at TH = 40 km, R = 0.3Error 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

% change in 350 nm radiance due to aerosols

% change shown for TH = 20, 25, 30, 35, 40 km

Surface reflectivity = 0

λ = 350 nm

LP Focal Plan Schematic

Designed for sequencing HG Long/LG long/HG Short/LG short: 1: 4.5: 7: 4.5 Total dynamic range gain: x140

Two interleaved exposures in 1:31 ratio

Ratio: 1:4.5

Low gain

High gain

High Gain Image in UV

No HG data

HG long

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.

HG short

No data

Optical distortions in HG Image Variation of wavelength with TH

• variation is smaller than instrument bandpass, but still needs to be corrected.• variation is 4 times worse for LG image.

Fixed column no

Optical distortions in HG Image Variation of TH with wavelength

Fixed row no

Wavelength Under-sampling

Without under-sampling corrn interpolation error can be as large as 3%

Radiances convolved with OMPS bandpass

Solar Irradiance (SI) Comparison

SUSIM smoothed with OMPS bandpass

OMPS in FWHM/10 steps

No adj

+0.6 nm shift

error decreases

SI comparison results

• We have ~0.6 nm error in in the 290-320 nm band

• Error decreases with increase in so it is not pixel shift type error

• Bias remaining after +0.6 nm shift is partly due to error and partly due to radiometric calibration errors

Explanation of large radiance residuals in L2

• Partly due to error• Partly due to error in SI assumed in calculating

the radiances in L2– L2 SI doesn’t agree with Atlas/SUSIM

Radiance Comparison Example (49.5 km, 70S)

Black: Measured

Red: Calculated

Radiance bias

Irradiance bias

There may be spectral bias between radiance and irradiance.

Alt Registration using 305 nm

No O3 abs

strong O3 abs

Strong sens to TH

weak sens to TH

305 nm not affected by reflectivity

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

Conclusions

• Release 1 data has 0.6 nm 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

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.