Kris Wargan & Natalya A. Kramarova(*) Extending the GEOS ozone observing system with the OMPS Limb Profiler data Kris Wargan & Natalya A. Kramarova(*) (*) Atmospheric Chemistry and Dynamics Laboratory, NASA/GSFC

Outline The OMPS Limb Profiler Version 2.5 ozone data quality Comparisons of OMPS-LP observations with MLS assimilation results Assessment of an OMPS-LP assimilation experiment

Motivation MLS: 2004 to present OMPS-LP: 2012 to present. Future missions are planned on JPSS satellites Potential for long-term studies of stratospheric ozone including trends but… Can we maintain continuity between MLS and OMPS-LP-based analyses? Objectives Consistent representation of ozone variability Identification and reduction of biases between MLS and OMPS-LP

The Ozone Mapping Profiler Suite (OMPS) Three instruments currently on the Suomi NPP satellite The Nadir Mapper: total ozone The Nadir Profiler: an SBUV-like sensor measuring ozone partial columns The Limb Profiler (OMPS-LP) Data available from mid-2012 to present The Nadir Mapper and Nadir Profiler provide data in near real time. Near real time data are expected from the Limb Profiler; currently there is a ~4 day latency Future missions JPSS (Joint Polar Satellite System)-1 will have a Nadir Mapper and a Nadir Profiler JPSS-2 will have all three instruments

The OMPS Limb Profiler Measures scattered visible and UV radiation from the atmosphere’s limb two-dimensional charge-coupled device allows simultaneous radiance acquisition from the entire profile Separate retrievals in the UV (29.5-52.5 km) and visible (12.5-35.5 km) bands. The upper and lower stratospheric profiles are provided separately 1-D retrieval algorithm The latest version 2.5 has a much reduced bias w.r.t. MLS thanks to an aerosol correction scheme The instrument has three slits but data from the central slit only are distributed (stray light problem in slits 1 and 3)

Seasonal cycle from OMPS-LP and MLS

OMPS-LP vs. ozonesondes within ±5% between 20 and 30 km, except for high NH latitudes; ~-15% – -20% differences in the SH mid-latitudes (20S- 60S) below 18 km; In the tropical UTLS: positive bias in lower stratosphere ~5-20% and negative bias in upper troposphere ~-30%.

UV vs. visible retrievals 157W, 12.5S 143W, 34.5N Sometimes the differences in the overlap layer can be large, posing a challenge for assimilation

UV vs. visible retrievals Large Vis-UV differences at 10 hPa, 1-15 Jan 2016 The differences between UV and visible retrievals in the layer where they overlap can be large and frequent. Which one should we trust? Our approach: trust them if they agree. One could also pick UV if they disagree; Chappuis bands retrievals less reliable

Assimilation strategy Profiles are pre-screened for large differences between UV and Vis retrievals; if the difference exceeds the reported precision then both observations are removed UV and visible profiles are assimilated separately, each with their own errors Approximate vertical range: 15 – 0.5 hPa (UV), 200-4 hPa (Vis) All comparisons shown in this talk are done after applying these criteria and recommended quality data screening

Methodology of comparisons Recall the guiding question: Can we maintain continuity between MLS and OMPS-LP-based analyses? Comparisons of OMPS-LP data against MLS+OMI analysis Comparisons of OMPS-LP+OMI analysis against MLS+OMI analysis Assimilation experiments were run for January-October 2016 using one of the latest versions of GEOS at the MERRA-2 resolution (0.625°× 0.5° longitude by latitude). The two assimilation experiments use identical setup except that one uses MLS v4.2 ozone and the other assimilates OMPS-LP v2.5.

OMPS-LP data vs. analysis How good is the agreement in the UTLS in the presence of complex ozone field morphologies? Focus on the extratropics

Spatial variability compared to MLS analysis 30°N-90°N, Jan-March 2016 100 hPa 50 hPa 30 hPa OMPS-LP [ppmv] OMPS-LP [ppmv] OMPS-LP [ppmv] High latitudes MLS analysis [ppmv] MLS analysis [ppmv] MLS analysis [ppmv] Excellent agreement: biases within 4% above 50 hPa and about 10% at 100 hPa Difference standard deviation within 10% and 20%, respectively Correlations of 0.9 and higher

Spatial variability compared to MLS analysis 90°S-30°S, October 2016 100 hPa 50 hPa 30 hPa OMPS-LP [ppmv] OMPS-LP [ppmv] OMPS-LP [ppmv] The ozone hole MLS analysis [ppmv] MLS analysis [ppmv] MLS analysis [ppmv] Excellent agreement: biases within 2% above 50 hPa and about 10% at 100 hPa Difference standard deviation within 10% Correlations of 0.9 and much higher above 50 hPa

Horizontal and vertical variations 600nm horizontal smoothing functions ‘Horizontal Smoothing functions apply to variations in log of ozone density in the horizontal with respect to  the tangent point.’ ‘All horizontal smoothing show larger contributions from the LOS towards the satellite.  This implies that if the ozone density has S-N gradient the retrieved ozone would have a bias. ‘ Towards satellite Away from satellite PK Bhartia, personal communication Does this affect the retrievals near the sharp ozone gradients across the edge of a polar vortex?

Spatial variability compared to MLS analysis 29 February 2016, 12UTC OMPS-LP reproduces ozone variability along the track, including the sharp gradients across the edge of the polar vortex Colors: MLS+OMI assimilation Circles: OMPS-LP observations color coded by ppmv

Spatial variability compared to MLS analysis 28 September 2016, 12UTC OMPS-LP reproduces ozone variability along the track, including the sharp gradients across the edge of the polar vortex (the ozone hole) Colors: MLS+OMI assimilation Circles: OMPS-LP observations color coded by ppmv

Spatial variability compared to MLS analysis Depressed values inside the vortex “Ozone collar” MLS analysis OMPS-LP data A typical example: the ozone gradient across the edge of the polar vortex is less sharp in OMPS-LP and the sharp maximum at the edge is less pronounced. Ozone hole is the only known example where this is an issue

The model transport sharpens the gradient MLS analysis OMPS-LP data 10-30 Sep 2016 OMPS-LP analysis OMPS-LP data Ozone hole midlatitudes “collar” Ozone at 480 K in the southern hemisphere as a function of potential vorticity The cross-edge ozone gradient is slightly underestimated in OMPS-LP compared to MLS analysis but also it is underestimated compared to OMPS-LP analysis: The model transport sharpens the gradient

OMPS-LP+OMI analysis vs. MLS+OMI analysis We will compare the two experiments Variability Mean differences Comparisons with ozonesondes This is very preliminary

MLS and OMPS-LP analysis: a global picture Zonal mean difference within ~5% in most of the stratosphere. Negative bias of up to 35% below 70 hPa but MLS is biased high there. Positive bias centered at 70 hPa in the tropics Zonal RMS difference within 10 % above 70 % Up to 70% in the upper troposphere where ozone mixing ratio is small

MLS and OMPS-LP analysis: a global picture Difference at the upper boundary of “the middle world”: Mostly negative (OMPS-LP is low) The largest difference of up to 50% around 30°S Positive difference in the tropics may have a seasonal dependence

Global ozonesondes, January-October 2016 Mean and st. dev Relative difference Correlation Sonde mean Analysis mean Sonde st. dev. St. dev. of difference MLS analysis OMPS-LP analysis The comparisons are done in tropopause-based vertical coordinate Both analyses: high bias at the tropopause OMPS-LP analysis: ~10% negative bias at 5 km above the tropopause (compensated in the UT) Very similar representation of variability (difference standard deviations and correlations)

1 km above the tropopause MLS OMPS-LP MLS OMPS-LP Ozonesondes Ozonesondes 3 km above the tropopause Remarkably good agreement with ozonesondes, except very close to the tropopause where ozone variability is high. Very similar performance of MLS and OMPS-LP analyses in terms of variability. MLS OMPS-LP Ozonesondes Ozonesondes

Very promising results, overall! Summary OMPS Limb Profiler is a UV and visible limb sounder currently flying on Suomi NPP and planned for JPSS-2 Version 2.5 ozone data have been released recently: Aerosol correction, central slit data only, UV and visible retrievals are provided separately Much better agreement wit MLS than in previous versions Some biases remain in the lower stratosphere Main conclusions from assimilation OMPS-LP analysis reproduces ozone variability as well as MLS analyses Remaining biases (LS) require attention when combining the two data records There’s some evidence of underestimated gradients across the ozone hole boundary. Using horizontal smoothing functions may be considered Very promising results, overall!