1. Validation and Update of SAO’s OMI Total Column Water Vapor (TCWV) product
Huiqun Wang1
Gonzalo Gonzalez Abad1, Xiong Liu1, Kelly Chance1
1Smithsonian Astrophysical Observatory
TEMPO Science Team Meeting, June 2016

2. Water Vapor Importance
Participates in atmospheric chemistry
Interfere with retrieval of several trace gases
Active player in hydrological cycle
Important factor for the weather
Most abundant greenhouse gas
Essential Climate Variable (ECV)
Water vapor is highly variable in space and time.
It is important to monitor its distribution.

3. Water Vapor Datasets Radiosondes – Reference Upper-Air Network (GRUAN)
Sun-photometers - AERONET
NCAR’s ground based GPS (SuomiNet, GEONET)
GPS radio occultation - CHAMP, COSMIC
Remote Sensing System (RSS) ’s Microwave data over the ocean – SSM/I, SSMI/S, TMI, AMSR-E, GMI, …
Thermal IR – MODIS, TES, AIRS, IASI
Near IR – MODIS, MERIS, SICAMACHY
Visible – GOME, GOME-2, OMI
Numerous datasets exist
Challenge – long term, high quality, consistent

4. Water Vapor Observation
Radiosondes, Microwave radiometer, Sun photometer, Aircrafts –
higher temporal resolution, boundary layer sensitivity,
sparse spatial coverage, calibration inconsistency
GPS – accurate, available under all-sky condition, day&night
non-uniform surface network coverage /
extrapolation errors for GPS radio occultation.
Microwave – reliable, routinely assimilated, all-sky, day&night
non-precipitating ice-free ocean only
Thermal IR – both land & ocean with profiles, day & night
limited sensitivity to PBL,
strongly affected by clouds
Near-IR & Red – sensitive to PBL
daytime only, strongly affected by clouds,
low quality over ocean
Blue – no saturation, land-ocean albedo uniformity
affected by clouds, lower signal-to-noise, larger uncertainty

5. Water Vapor Spectrum Much stronger absorption at longer wavelengths.
GOME, GOME-2
OMI
SCIAMACHY
Much stronger absorption at longer wavelengths.
OMI visible spectrum covers weak water vapor features in blue range.

6. GOME annual mean Surface Albedo
blue
[Koelemeijer et al., 2003]
red
Large land-ocean contrast at longer wavelengths
Ocean is brighter at shorter wavelengths

7. SAO water vapor SCD retrieval using Version 3 OMI data
Algorithm 1.0.0 nm
280K & 0.9atm
Wavelength shift
3rd order polynomial
Common mode
Under-sampling
Distinct spectral feature in the retrieval window

8. SAO OMI water vapor VCD retrieval
VCD = SCD / AMF
Scattering Weight
Shape Factor
VLIDORT
GEOS-Chem

9. SAO’s Level 2 OMI TCWV retrieved with algorithm 1.0.0

10. SAO’s OMI H2O Validation
Ground based network
NCAR’s GPS data (SuomiNet)
AERONET sun-photometer NearIR data
2. Satellite product
Remote Sensing System (RSS)’s SSM/I microwave data over ocean
long-term, global coverage and high quality

11. OMI versus GPS
OMI tracks the seasonal and inter-annual variations of GPS for a wide range of climate regimes

12. Mean(OMI – GPS) (2005 – 2009)
OMI agrees with GPS within 1.5 mm at 71% of the stations.
OMI can be lower by up to 8 mm at a few ocean islands.

13. Mean(OMI – GPS) (2005 – 2009) OMI generally agrees with GPS over landmm
OMI generally agrees with GPS over land
OMI shows significant dry bias over ocean

14. Daily (OMI – GPS) (2005 – 2009) Mode = 0 mm Median = -0.4 mm

15. OMI versus SSM/I over the ocean for July 2005
OMI – SSM/I
OMI
cldfrac<25%
SSM/I
all-sky
mean = -4.3mm
OMI has a low bias over the ocean

16. OMI versus SSM/I for July 2005
OMI is lower than SSM/I over ocean

17. Common Mode
SCD Fitting
Ocean
Land

18. Sensitivity study for SAO’s OMI water vapor algorithm 1.0.0
(430 – 480nm)
It is essential to include liquid water in OMI water vapor retrieval

19. New OMI versus SSM/I for July 2005
OMI agrees with SSM/I over ocean much better than before

20. SAO OMH2O Retrieval Algorithm Update
HITRAN2008
1.0 atm, 288K
428 – 465 nm
[Thalman and Vokamer, 2013]

21. New OMI – Algorithm 1.0.0 OMI July 2005
Land mean = 0.4 mm
Ocean mean = 2.9 mm
New OMI retrievals increase slightly over land,
but significantly over the ocean.

22. New OMI versus SSM/I for July 2005
All sky comparison
mean = -4.3mm
mean = -1.1 mm
OMI agrees with SSM/I over ocean much better than before

23. New OMI versus SSM/I for July 2005
“Clear” sky comparison
OMI agrees with SSM/I over ocean much better than before

24. Algorithm in Development
Scattering Weight
VLIDORT
MERRA2
Shape Factor
High-resolution (0.5°×0.5°) GEOS5 MERRA2 water vapor profile climatology
New version OMI cloud information
Better treatment of surface properties (albedo, pressure)
AMF error analysis (albedo, cloud fraction, cloud top pressure,
surface pressure, profile, aerosol…)

25. Summary Water vapor can be retrieved from the blue spectral range.
Using the Version OMH2O algorithm,
OMI water vapor over land compares well with GPS & AERONET,
OMI water vapor over the ocean has a significant low bias.
The updated Version algorithm leads to
significant improvement over the ocean
without affecting the land result much.
New developments for AMF are being tested.