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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de SCIAMACHY Water Vapour Retrieval using AMC-DOAS S. Noël, M. Buchwitz, H. Bovensmann, J. P. Burrows Institute of Environmental Physics/Remote Sensing University of Bremen, Germany
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de The AMC-DOAS Retrieval Method “Air Mass Corrected” (AMC-)DOAS based on well-known DOAS method: –Uses only differential structures of sun-normalised radiances –Numerically fast algorithm Main differences to standard DOAS: –Parameterisation of saturation effect: Non-linear dependence of absorber amount from absorption depth –Air Mass Factor (AMF) correction from O 2 absorption in same fitting window: Inherent data quality check to mask out too cloudy ground pixels, etc. Has been applied successfully to GOME and SCIAMACHY measurements
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de SCIAMACHY and GOME H 2 O Columns SCIAMACHY has higher spatial resolution than GOME (~ 30 km x 60 km) Advantage of VIS spectral region: Retrievals over land and ocean possible (unlike MW sensors) AMC-DOAS method requires no calibration with external sources Independent data source
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de AMC-DOAS Results Analysis of all available SCIAMACHY nadir data for the year 2003 (Level 1 NRT and consolidated data) Automatic retrieval for all 2004 SCIAMACHY Level 1 NRT data (see also: http://www.iup.physik.uni-bremen.de) Remarks: –Not all data are available; larger gaps especially in November 2003 –Inclusion of unconsolidated data may influence weighting of individual measurements –Insufficient radiometric calibration may have an influence on the data quality (although expected to be small) –Always the same (specially calibrated) solar reference spectrum used for SCIAMACHY retrieval (provided by J. Frerick, ESA) –No correction for surface elevation All data have been gridded to 0.5° x 0.5° for the comparison with SSM/I and ECMWF results
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de SSM/I H 2 O Columns (27 January 2003) SSM/I gridded Integrated Water Vapour data provided by GHRC Only descending part of DMSP F-14 orbit (equator crossing at ~ 0800 LT) Only data over ocean available
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de ECMWF H 2 O Columns (27 January 2003) Operational daily analysis data provided by ECMWF Not independent from SSM/I data Daily averages derived from 6-hourly values (integrated over height)
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de SCIAMACHY AMC-DOAS H 2 O Columns (27 January 2003) Regular gaps from alternating limb- nadir measurement mode Additional gaps from AMC-DOAS quality check: –Max. SZA 88° –AMF correction factor has to be larger than 0.8 (mainly because of clouds) (swath data)
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de Correlation (27 January 2003) SCIA vs. SSM/I SCIA vs. ECMWF Good correlation with both SSM/I and ECMWF columns On average good agreement (better with ECMWF data) Smaller SCIA columns seem to be lower, higher larger than correlative data Deviations difficult to quantify because of large scatter
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de Scatter of Water Vapour Data Scatter is mainly due to high spatial and temporal variability of water vapour Difficult to compare individual measurements which are (initially) on different temporal and/or spatial scales Scatter can not be significantly reduced by averaging more data (but correlation and mean values may improve) General problem for validation/verification of water vapour products Concentrate on long-term analysis of correlation and mean values
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de Long-Term Deviations SCIA vs. SSM/ISCIA vs. ECMWF Mean deviation with SSM/I: - 0.2 g/cm 2 Mean deviation with ECMWF: - 0.05 g/cm 2
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de ECMWF Monthly Mean October 2003
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de SCIAMACHY Monthly Mean October 2003 Preliminary data!
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de Difference SCIAMACHY - ECMWF Preliminary data!
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de Comparisons with other ENVISAT Sensors Other ENVISAT instruments providing water vapour column data: -MERIS -AATSR -MWR Here: First comparisons with AATSR and MWR water vapour data provided by I. Barton, CSIRO, Hobart, Australia Advantage of intercomparison: Minimum temporal offset Disadvantages: Different spatial resolution, ENVISAT products not fully validated yet Current limitations: -AATSR and MWR data not independent -Only sub-satellite track data over ocean (cloud free), only few days
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de First Comparisons with AATSR and MWR First preliminary results, only 4 days analysed up to now (partly limited by availability of SCIAMACHY Level 1b data) Agreement with MWR data slightly better than with AATSR AATSRMWR Preliminary data!
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de Summary & Conclusions SCIAMACHY “visible” H 2 O columns agree well with correlative data High scatter (~ 0.5 g/cm 2 ), mainly due to atmospheric variability Validation of water vapour columns difficult Mean SCIAMACHY AMC-DOAS water vapour columns typically lower than ECMWF and SSM/I data SCIAMACHY monthly means look reasonable; some features need further investigation Quite good agreement with first AATSR and MWR water vapour results SCIAMACHY can provide a new independent global water vapour data set
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de Acknowledgements SCIAMACHY data have been provided by ESA. SSM/I data have been provided by the Global Hydrology Resource Center (GHRC) at the Global Hydrology and Climate Center, Huntsville, Alabama. We thank the European Center for Medium Range Weather Forecasting (ECMWF) for providing us with analysed meteorological fields and our colleagues J. Meyer-Arnek and S. Dhomse for assistance in handling these data. MWR and AATSR water vapour data have been provided by I. Barton, Marine Research, Commonwealth Scientific and Industrial Research Organisation, Hobart, Tasmania, Australia. This work has been funded by the BMBF via GSF/PT-UKF and DLR-Bonn and by the University of Bremen.
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de Importance of Water Vapour One of the most abundant atmospheric gases More than 99% located in troposphere 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 data: –In-situ measurements: radio sondes, ground-based & airborne measurements –Space borne (N)IR and MW sensors (TOVS, SSM/I, MODIS, MERIS) –GPS observations Additional data source: Measurements in visible spectral region (GOME & SCIAMACHY nadir data)
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de Correlation for 2003 In general good correlation over the whole year Lower correlations for SSM/I during the first months; mainly due to low number of coincidences (missing data) Reduced correlation with ECMWF data in summer
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de Deviation SCIAMACHY – SSM/I - 0.2 g/cm 2
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Institut für Umweltphysik/Fernerkundung Physik/Elektrotechnik Fachbereich 1 stefan.noel@iup.physik.uni-bremen.de Deviation SCIAMACHY – ECMWF - 0.05 g/cm 2
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