Product User Guide (PUG) for the XCO2 SCIAMACHY Data Product
Contents
1. For all retrieval comparisons it is recommended to define a common a priori cogemmon apriori which is used to adjust the retrieved CO C03 trteved using the averaging kernel A and the original a priori Cog 9 a priori djusted i iori iginal iori cos justed _ Coretrieved a _ A C co anepi As BESD s pressure levels are equally spaced column averages XCOz can then be calculated by simply averaging over the layers of the adjusted profiles 3 5 Tools for Reading the Data The data are stored in Netcdf format which can be read with standard tools in the common programming languages IDL Matlab Python Fortran90 C etc HDF View http Awww hdfgroup org hdf java html hdfview is a great platform independent tool with graphical user interface which can be used to have a first look what is in the data files 3 6 Known Limitations and Issues e Due to instrument issues data earlier than April 2003 are less reliable 3 7 Data file content Table 3 1 Full Data content of the CO2_SCI_BESD data products n number of observations m number of pressure levels Name Type Dimensions Units Description instrument Sting tt ESCIAMACHY I2_processor_version Sting 1 Processor Version Number Tb input filename Sa ooo OO NTB Fene solar_zenith_angle Float n Degrees Solar Zenith Angle 0 zenith viewing_zenith_angle Float n Degrees Viewing Zenith Angle 0 nadir azimuth_diff2. ESA Climate Change Initiative CCI Page 1 ghg Product User Guide PUG for the Verionl cci XCO SCIAMACHY Data 25 Feb 2013 Product BESD for the Essential Climate Variable ECV Greenhouse Gases GHG ESA Climate Change Initiative CCI Product User Guide PUG for the XCO SCIAMACHY Data Product BESD for the Essential Climate Variable ECV Greenhouse Gases GHG Written by GHG CCI project team Lead author Maximilian Reuter Institute of Environmental Physics University of Bremen ESA Climate Change Initiative CCI Page 2 ighg Product User Guide PUG for the Verdoni XCO SCIAMACHY Data 25 Feb 2013 Product BESD for the Essential Climate Variable ECV Greenhouse Gases GHG Change log Version Nr Date Status Reason for change Version 1 draft 1 5 October Template version for input by 2012 project partners Author O Hasekamp Version 1 draft 2 25 February Make one PUG per product 2013 data examples in first section Drafting of the PUG for BESD XCO2 ESA Climate Change Initiative CCI Page 3 ghg Product User Guide PUG for the Version F XCO SCIAMACHY Data 25 Feb 2013 Product BESD for the Essential Climate Variable ECV Greenhouse Gases GHG Table of Contents k Sumay aen a a a re a ee eee ee 4 2 AtrodUCtON eea ee ree ee ee ee ee E 6 2 1 The SCIAMACHY INStMUMIGI xiiss
3. D algorithm is designed to analyze SCIAMACHY sun normalized radiance measurements to retrieve the column average dry air mole fraction of atmospheric COs i e XCO2 BESD is a so called full physics algorithm which uses measurements in the O2 A absorption band to retrieve scattering information of clouds and aerosols This information is transferred to the CO2 absorption band at 1580 nm by simultaneously fitting the spectra measured in both spectral regions The explicit consideration of scattering by this approach reduces potential systematic biases due to clouds or aerosols More details on BESD can be found in the publications of Reuter et al 2010 and Reuter et al 2011 As an example Figure 2 1 shows a global map of the long term seasonal averages April May June top short before the growing season with largest values on the northern hemisphere and July August September bottom during the growing season with lowest values on the southern hemisphere ESA Climate Change Initiative CCI Page 7 Product User Guide PUG for the Versioni XCO SCIAMACHY Data 25 Feb 2013 Product BESD for the Essential Climate Variable ECV Greenhouse Gases GHG SDIAMAGRY XCO Apr May Jun 2003 2011 a me 00 374 378 382 386 390 394 XCO ppm SCIABIAGHY ZGO p JURAIGIS ED 2003 2071 BESD v02 00 04 374 378 382 386 390 394 XCO ppm Figure 2 1 Long term seasonal averages of XCO2 retrieved with BESD Top Apr
4. ed 3 3 Bias Correction Bias correction is an integral part or the BESD retrieval algorithm i e all XCO values within the data files are already bias corrected BESD s bias correction relies on a multi dimensional non linear regression realized by an artificial neural network ANN In order to give an impression of the magnitude of the bias correction the bias correction reduces the standard error relative to TCCON validation data from about 2 7ppm to 2 1ppm 3 4 Data Usage It is recommended to use BESD data as provided within the data files If the data is to be used within in a surface flux inversion framework or if the data is compared with other XCOz data for which vertical profile information is available the column averaging kernels should be used It should be noted that the values within BESD s CO and averaging kernel profiles correspond to layer averages whereas the layering is defined by the pressure profile giving the level boundaries starting with the surface pressure This means one could expect to find pressure profiles having one element more than the CO profiles However this is not the case because the upper most pressure level at the top of the atmosphere is always OhPa and was omitted therefore ESA Climate Change Initiative CCI Page 9 ghg Product User Guide PUG for the Version F XCO SCIAMACHY Data 25 Feb 2013 Product BESD for the Essential Climate Variable ECV Greenhouse Gases GHG
5. erence Float nf Degrees e Azimuth Difference time Double n Seconds Seconds since 01 01 1970 00 00 UTC longitude_centre Float nsf Degrees e Longitude of pixel centre surface_elevation Float n km Mean surface elevation of pixel pressure_levels Float Retrieval pressure levels column_averaging_kernel Float nxm Normalised Column Averaging Kernel Profile ESA Climate Change Initiative CCI Page 10 ghg Product User Guide PUG for the Version F XCO SCIAMACHY Data 25 Feb 2013 Product BESD for the Essential Climate Variable ECV Greenhouse Gases GHG chi2 Float n Chi Square of fit residual rms Float nx3 RMS of fit residual total Oz CO2 xco2_uncertainty Float ppm Uncertainty in retrieved XCO2 vmr_profile_co2 Float Retrieved CO profile vmr_profile_co2_uncertainty ppm Uncertainty in retrieved CO2 profile vmr_profile_co2_apriori Float nxm ppm A priori CO profile 4 References and Further Reading Bovensmann et al 1999 Bovensmann H J P Burrows M Buchwitz J Frerick S No l V V Rozanov K V Chance and A H P Goede SCIAMACHY Mission objectives and measurement modes J Atmos Sci 56 2 127 150 1999 Burrows et al 1995 Burrows J P H lzle E Goede A P H Visser H and Fricke W SCIAMACHY Scanning Imaging Absorption Spectrometer for Atmospheric Chartography Acta Astronautica 35 445 451 1995 Reuter et al 2010 M Reuter M Buchwi
6. ettetcevenivciessliecwtnieediveeiceetnevivisienienevedisnected 6 2 2 The BESD XCO Full Physics Product eeeeeeerrrrrrrrrrrrrrrrrrrrtrrrttrrrttrtrrtrtrrrnrnn 6 S Product D sScript ri sisri ieia Naa EEEE E NEA NEEE E EEEREN EA REES 8 3 1 Product Content and POntal ci cicsscuicrtecncisacs acct ceicenl ccna nbiceicade ni acieiedenteteaucie 8 3 2 Quality Flags and Metadata cccct sscesces canccasheveesscetiacaniestnatdeandead hasten ndemanetten nade 8 33 Bias GONG ION cacaica case seSiccaieta tere ysebictraveniwensseesceaw ie deere sie eerie 8 3 4 Data WIG ACG ccc xaeacials ccccacescas dass eeecea eeeacuals canceatepacacass viascaleecaeaasssaassaeeeenganuieceesus ate 8 3 5 Tools for Reading the Data en ante ere eer ne ee renne 9 3 6 Known Limitations and ISSueS esssesenereneeesserttrrrrtrsstttrnrrnrrrssrrrnrnnnnrsserrnn nenn 9 37 Data file comentas eneissee ni a EE NEE 9 4 References and Further Reading ecccceccceeeeeeeeeeeeeeeeeeeeeeeeeeeeseaaaaaeeeeeeeeeeeeesaaaaes 10 ESA Climate Change Initiative CCI Page 4 Product User Guide PUG for the Version XCO SCIAMACHY Data 25 Feb 2013 Product BESD for the Essential Climate Variable ECV Greenhouse Gases GHG 1 Summary This document is the Product User Guide PUG which is a deliverable of the ESA project GHG CCI The GHG CCI project started on 1st September 2010 The GHG CCI project is one of several projects of ESA s C
7. il May June Bottom July August September ESA Climate Change Initiative CCI Page 8 ghg Product User Guide PUG for the Versioni F XCO SCIAMACHY Data 25 Feb 2013 Product BESD for the Essential Climate Variable ECV Greenhouse Gases GHG 3 Product Description 3 1 Product Content and Format BESD results are stored in one NetCDF file per day The file names follow the convention CO2_SCI_BESD_vXX XX XX_YYYYMMDD nc where XX XX XX stand for a version number and YYYYMMDD stand for year month and day The files include individual level 2 retrieval results No averaging has been applied so that each entry corresponds to an individual SCIAMACHY spatial footprint A table with the full content of the data product is provided in Section 3 7 The product file contains the key product i e the retrieved column averaged dry air mixing ratio XCO and information relevant for the use of the data like geo location time vertical layering averaging kernels and error estimates 3 2 Quality Flags and Metadata BESD data are already quality filtered and include only pixels assumed to be reliable so that an additional data filtering by the user is not required The performed quality filtering relies not on assumptions about realistic XCO values Only XCOz independent retrieval outputs such as fit residuals scattering parameters albedo or instrument related information such as the time of decontamination phases has been us
8. le 1 This document describes the BESD XCO2 data products so that it will be clear for the user how to use the products The description includes quality flags and metadata data format product grid and geographical projection known limitations available tools for decoding and interpreting the data and the product column averaging kernels and a description how to use them XCO SCIA WFMD Weighting Function Modified BESD DOAS IUP Bremen BESD BESD Bremen optimal EStimation Doas IUP Bremen XCO GOSAT OCFP OCO Full Physics UoL OCFP amp SRFP SRFP SRON Full Physics SRON XCO merged N A Ensemble algorithm product EMMA gt Add to GHG CCI portfolio ESA Climate Change Initiative CCI Page 5 ghg Product User Guide PUG for the Versioni F XCO SCIAMACHY Data 25 Feb 2013 Product BESD for the Essential Climate Variable ECV Greenhouse Gases GHG XCH SCIA WFMD WFMD amp IMAP IMAP Iterative Maximum A Posteriori method SRON JPL XCH GOSAT OCFP OCPR OCO Proxy UoL SRFP amp OCPR SRFP SRPR SRON Proxy SRON Table 1 Algorithms evaluated and selected during the round robin phase of the GH CCI project The SRFP algorithms is commonly known as RemoteC and is being jointly developed by SRON and KIT ESA Climate Change Initiative CCI Page 6 ghg Product User Guide PUG for the Versioni F XCO SCIAMACHY Data 25 Feb 2013 Product BESD for the Essential Cli
9. limate Change Initiative CCI The GHG CCI project will deliver the Essential Climate Variable ECV Greenhouse Gases GHG State of the art retrieval algorithms for remote sensing of the ECV Greenhouse Gases GHGs will be developed further in the frame of this project Multi year Carbon Dioxide CO2 and Methane CH4 data sets will be generated and validated Two existing satellite sensors will be used to produce the core GHG ECV products KCO2 and XCH4 SCIAMACHY on ENVISAT and TANSO on GOSAT Both instruments measure NIR SWIR spectra of reflected solar radiation and are sensitive to CO2 and CH4 concentration changes close to the Earth s surface Consequently they carry information on regional surface fluxes The accuracy requirements for such an application are demanding especially for CO2 but also for CH4 A two year round robin exercise has been conducted for eight different CO2 and CH4 retrieval algorithms as developed for SCIAMACHY and GOSAT During the round robin phase of the projects the performance of algorithms has been compared and validated with independent ground based measurements and algorithms have been select to provide input to the Climate Research Data Package CRDP For some products it was not possible to select one algorithm because different algorithms compared equally well with the validation measurements but showed significant differences at a global scale An overview of the selected algorithms is provided in Tab
10. mate Variable ECV Greenhouse Gases GHG 2 Introduction 2 1 The SCIAMACHY Instrument The SCIAMACHY Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY Burrows et al 1995 Bovensmann et al 1999 instrument started its operation in 2002 with the launch of the ESA European Space Agency satellite ENVISAT Environmental Satellite on March 1 2002 Roughly one decade later on May 9 2012 ESA declared end of the mission due to the unexpected loss of ENVISAT SCIAMACHY was the first and during seven years the only satellite instruments which was able to measure the CO mixing ratio XCOz with large sensitivity also in the boundary layer where the signals from the sources and sinks at the surface are largest ENVISAT was in a sun synchronous descending orbit with an equator crossing time of 10 00 SCIAMACHY measured simultaneously the radiance in 8 spectral channels in the range from 240 2400nm each consisting of 1024 spectral points BESD uses SCIAMCHY measurements within two spectral bands namely the O2 A absorption band at around 760nm and the weak CO absorption band at around 1580nm The spectral resolution of these bands was 0 42nm and 1 45nm respectively The measurements in these bands had a ground pixel size of approximately 60km across track and 30km along track The swath width of SCIAMACHY was about 960km 2 2 The BESD XCO Full Physics Product The Bremen Optimal Estimation DOAS BES
11. tz O Schneising J Heymann H Bovensmann J P Burrows A method for improved SCIAMACHY COz2 retrieval in the presence of optically thin clouds Atmospheric Measurement Techniques 3 209 232 2010 Reuter et al 2011 Reuter M Bovensmann H Buchwitz M et al 2011 Retrieval of atmospheric CO2 with enhanced accuracy and precision from SCIAMACHY Validation with FTS measurements and comparison with model results J Geophys Res 116 D04301 doi 10 1029 2010JD015047
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