Long-Term Time Series of Water Vapour Total Columns from GOME, SCIAMACHY and GOME-2

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1 Graphics: ESA Graphics: ESA Graphics: ESA Long-Term Time Series of Water Vapour Total Columns from GOME, SCIAMACHY and GOME-2 S. Noël, S. Mieruch, H. Bovensmann, J. P. Burrows Institute of Environmental Physics/Remote Sensing University of Bremen, Germany

2 Importance of Water Vapour Institut für Umweltphysik/Fernerkundung Strongest natural greenhouse gas. Significant contributions to atmospheric chemistry, weather and climate. High spatial and temporal variability. Global water vapour data especially required for global models. Current sources for global water vapour data: In-situ measurements: Radio sondes, ground-based & airborne / balloon measurements. Space borne (N)IR and MW sensors (like TOVS, SSM/I, MODIS, MERIS). GPS observations. Especially only limited information in polar regions (small columns, ice). Additional data source: GOME, SCIAMACHY & GOME-2 nadir measurements in the visible spectral region (~700 nm) derived with AMC-DOAS (Air Mass Corrected DOAS).

3 The GOME-type Instruments GOME SCIAMACHY GOME-2 Launch date 21 Apr Mar 2002 Platform ERS-2 ENVISAT MetOp Orbit sun-synchronous 10:00 equator Spatial resolution 320 km x 40 km typically 60 km x 30 km 80 km x 40 km (depending on orbital position and wavelength) Swath 960 km 960 km 1920 km Spectral range ca nm ca nm ca nm Measurement geometry Data distribution (Level 1) Expected mission duration sun-synchronous 10:30 equator Nadir Nadir, Limb, Occultation Nadir June 1995 now (since June 2003 reduced coverage) August 2002 now 19 Oct 2006 Graphics: ESA Graphics: ESA Graphics: ESA sun-synchronous 09:30 equator March 2007 now until at least 2011 until at least 2013 with MetOp series until at least 2020

Characteristics of the AMC-DOAS Products Institut für

dayside can be used - No total column data for too cloudy scenes

temporal resolution - Currently no data for high mountain areas

surface elevation data base) Advantages: - Retrievals possible over

4 Characteristics of the AMC-DOAS Products Institut für Umweltphysik/Fernerkundung Limitations: - Only measurements on the dayside can be used - No total column data for too cloudy scenes (removed by AMF correction factor check) - Limited spatial and temporal resolution - Currently no data for high mountain areas (masked out by quality check; can be avoided by use of external surface elevation data base) Advantages: - Retrievals possible over land and ocean (with same algorithm) - No external calibration sources required Completely independent data set!

5 Quality of AMC-DOAS Water Vapour Products Main results of validation: Good general agreement Large scatter (~0.5 g/cm 2 ) due to spatial/temporal variability Precision estimate: 3-5% for columns > 0.6 g/cm 2 Lower columns: up to 10% Absolute precision always better than 0.2 g/cm 2 Accuracy estimate: Difficult to determine because of large variability of water vapour Systematic deviations to e.g. ECMWF and SSM/I data ~ g/cm 2 SCIAMACHY data typically lower (cloud free bias?)

6 Combining GOME & SCIAMACHY Data Institut für Umweltphysik/Fernerkundung GOME and SCIAMACHY instruments are very similar GOME measures (only) ~30 min after SCIAMACHY at same geolocation SCIAMACHY and GOME measurements have different spatial resolution How good do the data match in the overlap time interval?

7 GOME vs. SCIAMACHY: Example 27 Jan 2003 Very good correlation Scatter of data somewhat smaller than e.g. in comparison SCIAMACHY - SSM/I Overall good agreement within the usual scatter GOME & SCIAMACHY AMC-DOAS data V1.0 (spatially gridded to 0.5 x 0.5 )

8 GOME vs. SCIAMACHY: Long-Term Comparison Time interval: Aug 2002 Dec 2003 Very good agreement especially for 2003 data On average no offset, but some scatter Notes: Reduced GOME coverage after June 2003 No actual solar reference spectrum for SCIAMACHY data in 2002 GOME & SCIAMACHY AMC-DOAS data V1.0 (spatially gridded to 0.5 x 0.5 )

GOME-2 Results MetOp was launched in October 2006; Level 1 data distribution since March 2007 AMC-DOAS retrieval method could be easily adapted to GOME-2 (only spectral

9 GOME-2 Results MetOp was launched in October 2006; Level 1 data distribution since March 2007 AMC-DOAS retrieval method could be easily adapted to GOME-2 (only spectral resolution of RTM data base had to be adapted to slit function) Regular retrieval running at IUP Bremen Enhanced daily coverage of GOME-2 at similar spatial resolution as SCIAMACHY

10 GOME-2 vs. SCIAMACHY (1) Institut für Umweltphysik/Fernerkundung Scatter plot shows good agreement between GOME-2 and SCIAMACHY data Results confirmed by statistical analysis based on larger data set Noël et al., ACP, 2008

11 GOME-2 vs. SCIAMACHY (2) Institut für Umweltphysik/Fernerkundung Avg. deviation small Small sinusoidal variation (period ~ 9 days; amplitude ~ 6%, some seasonal change) Related to the relative position of orbits. Possible reason: Scan angle dependencies. GOME-2 & SCIAMACHY AMC-DOAS data V1.0 (spatially gridded to 0.5 x 0.5 )

12 The Combined GOME & SCIAMACHY Institut für Umweltphysik/Fernerkundung Water Vapour Data Set Annual Means Monthly Means GOME: SCIAMACHY: Time series to be continued with SCIAMACHY and GOME-2 until 2020.

Example Application: Trend Fachbereich analysis 1 Institut

data set has been used to determine global water vapour

negative changes over 12 years could be detected Figure and

13 Example Application: Trend Fachbereich analysis 1 Institut für Umweltphysik/Fernerkundung The combined GOME- SCIAMACHY data set has been used to determine global water vapour changes Several regions with significant positive and negative changes over 12 years could be detected Figure and data by S. Mieruch; see also Mieruch et al., ACP, 2008 See poster by Mieruch et al.

14 Conclusions The AMC-DOAS retrieval method has been successfully applied to GOME, SCIAMACHY and GOME-2 measurements. The resulting AMC-DOAS H 2 O columns agree well with correlative data and each other. Potential to extend AMC-DOAS data set until 2020 with GOME-2. GOME-type instruments can provide a new independent global water vapour data set suitable for climatological studies. All data are available on request, details on AMC-DOAS web site (

15 Acknowledgements GOME & SCIAMACHY data have been provided by ESA. GOME-2 data have been provided by EUMETSAT. This work has been funded by DLR-Bonn and by the University of Bremen. Thank you for your attention!

16 Backup Slides

17 Air Mass Corrected DOAS (AMC-DOAS) Institut für Umweltphysik/Fernerkundung DOAS = Differential Optical Absorption Spectroscopy Similar to standard DOAS: Does not rely on absolute radiometric calibration Uses differential structures to derive trace gas column Main differences: Considers saturation effect for water vapour (non-resolved lines): Non-linear relation between absorption depth and absorber amount Air mass factor (AMF) correction (from O 2 absorption): Considers uncertainties in radiative transfer calculation caused by insufficient knowledge of atmospheric conditions (esp. cloudiness) Retrieval also possible for partly cloudy pixels AMF correction also used as quality check

18 Fitting Window Sun-normalized Radiance O 2 H 2 O GOME Channel 4 Fitting Window O 2 H 2 O H 2 O Wavelength, nm 800 O to 700 nm Absorptions of both water vapour and O 2 of same magnitude (required for air mass correction) Further advantage: Harmless region w.r.t. calibration of GOME, SCIAMACHY & GOME-2 very stable

WATER VAPOUR RETRIEVAL FROM GOME DATA INCLUDING CLOUDY SCENES

WATER VAPOUR RETRIEVAL FROM GOME DATA INCLUDING CLOUDY SCENES S. Noël, H. Bovensmann, J. P. Burrows Institute of Environmental Physics, University of Bremen, FB 1, P. O. Box 33 4 4, D 28334 Bremen, Germany