ESA Climate Change Initiative (CCI) Version 1.0, revision February Author: Will Hewson

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Page 1 ESA Climate Change Initiative (CCI) Product User Guide: University of Leicester full physics XCH 4 retrieval algorithm for CRDP3 OCFP v1.0 : Version 1.0, revision 0. Author: Will Hewson Earth Observation Science Department of Physics and Astronomy University of Leicester Leicester United Kingdom

Page 2 Document history: Version Revision Date Description/Comments 1 0 25 Feb 2016 New document for voluntary full physics XCH 4 retrieval contribution. The research described in this document was carried out at the University of Leicester, United Kingdom. Copyright 2016. All rights reserved.

Page 3 Table of contents Table of contents... 3 List of tables... 4 List of figures... 4 1. Summary... 5 2. Introduction... 6 2.1 GOSAT FTS... 6 2.2 The University of Leicester Full Physics XCH 4 Product... 6 2.3 Validation... 7 3. Product Description... 10 3.1 Product Format and Content... 10 3.2 Quality Flags and Metadata... 10 3.3 Data Usage... 10 3.4 File contents... 11 4. References... 12

Page 4 List of tables Table 1. Product quality filter.... 10 Table 2. Common variables for the CH4_GOS_OCFP data product.... 11 Table 3. Additional variables for CH4_GOS_OCFP.... 11 List of figures Figure 1. Global seasonal maps of OCFPv1.0 XCH 4 retrieved between April 2009 and December 2014... 7 Figure 2. Comparison of retrieved XCH 4 (red) with TCCON XCH 4 (green) between April 2009 and December 2014. Only TCCON/GOSAT data pairs are plotted where co-location criteria are met. Statistics for the mean difference and standard deviation are shown in ppm along with the correlation coefficient and the total number of GOSAT soundings.... 8 Figure 3. Comparison of retrieved UoL XCH 4 with the TCCON XCH 4 between April 2009 and December 2014 across all land TCCON sites, coloured by site. Statistics for mean bias and standard deviation are shown in ppm along with the correlation coefficient.... 9

Page 5 1. Summary This document is the Product User Guide version 1 (PUG1); a deliverable of the ESA project GHG-CCI. The GHG-CCI project started on 1st September 2010 as one of several ESA Climate Change Initiative (CCI) projects. 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 GHG ECV will be developed further in the frame of this project. Multi-year carbon dioxide (CO 2 ) and methane (CH 4 ) data sets will be generated and validated. Currently GHG-CCI is in Phase 2 (2014-2016). This document describes the University of Leicester Full-Physics XCH 4 (CH4_GOS_OCFP) data product for users. The description includes quality flags and metadata, data format, product grid and geographical projection, known limitations. Two existing satellite sensors are used to produce core GHG-ECV products (XCO 2 and XCH 4 ): SCIAM- ACHY on ENVISAT and TANSO on GOSAT. Both instruments measure Near Infra-Red (NIR) and Short Wave Infra-Red (SWIR) spectra of reflected solar radiation and are sensitive to CO 2 and CH 4 concentration changes close to Earth s surface, offering information on regional surface fluxes. The accuracy requirements for such an application are demanding, especially for CO 2 but also for CH 4.

Page 6 2. Introduction 2.1 GOSAT FTS The Japanese Greenhouse gases Observing SATellite (GOSAT) was launched on 23rd January 2009 by the Japanese Space Agency (Yokota et al., 2009). GOSAT provides the first dedicated global measurements of total column CO 2 and CH 4 from its SWIR bands (Yoshida et al., 2011). It is equipped with two instruments; the Thermal And Near infra red Sensor for carbon Observations Fourier Transform Spectrometer (TANSO FTS), and a dedicated Cloud and Aerosol Imager (TANSO CAI). TANSO FTS measures in four spectral bands with a high spectral resolution of 0.3 cm -1, three of which operate in the SWIR at around 0.76, 1.6 and 2.0 μm providing sensitivity to the near-surface absorbers with the fourth channel operating in the thermal infrared between 5.5 and 14.3 μm providing midtropospheric sensitivity (Saitoh et al., 2009). The measurement strategy of TANSO FTS is optimised for characterisation of continental scale GHG sources and sinks, with the aim of achieving a 0.3 1% relative accuracy for 3 month averages of CO 2 at a 100 1000 km spatial resolution (Kuze et al., 2009). The aim for CH 4 is to achieve an accuracy of better than 2% on the same spatial and temporal scales. In order to achieve this, TANSO FTS utilises a pointing mirror to perform off-nadir measurements at the same location on each 3-day repeat cycle. The pointing mirror allows TANSO FTS to observe up to ±35 across track and ±20 along-track. These measurements nominally consist of 5 across track points spaced ~100km apart (although measurements are possible with 1, 3, 5, 7 or 9 across track points) with a ground footprint diameter of approximately 10.5 km and a 4 second exposure duration. Whilst the majority of data is limited to measurements over land where surface reflectance is high, TANSO FTS also observes in sun-glint mode over the ocean within ±20 of the sub-solar latitude. 2.2 The University of Leicester Full Physics XCH 4 Product Full physics XCH 4 retrievals build on the OCFPv6.0 FP XCO 2 retrieval (see OCFPv6.0 PUG), using the same forward and inverse model system as for XCO 2, with a-priori adjusted to per sounding retrieval outputs from OCFPv6.0. These outputs are retrieved surface pressure, temperature and H 2 O profiles (multiplied by their retrieved scaling factors), VMR profiles of CO 2, O 2 and CH 4, and optical depth profiles of type 1, 2, and cirrus aerosols. In the subsequent XCH 4 retrieval, only the CH 4 profile, dispersion and albedo are retrieved at 1.64 μm, allowing for a rapid convergence compared to XCO 2 making use of all three GOSAT SWIR bands. As the FP XCH 4 retrieval relies on FP XCO 2 outputs, only those soundings for which the XCO 2 retrieval was able to successfully converge are processed. Figure 1 shows global seasonal maps of the XCH 4 product retrieved for land and glint modes between April 2009 and December 2014. Note that in August 2010 GOSAT moved from a 5-point grid mode to a 3- point grid mode, explaining the change in spatial coverage.

Page 7 ESA Climate Change Initiative (CCI) Figure 1. Global seasonal maps of OCFPv1.0 XCH4 retrieved between April 2009 and December 2014 2.3 Validation Validation of our retrieved XCH4 has been performed against the Total Carbon Column Observing Network (TCCON), a global network of ground-based high resolution Fourier transform spectrometers recording direct solar spectra in the near infrared spectral region, itself validated against aircraft measurements. Figure 2 shows retrieved GOSAT XCH4 compared to 14 TCCON sites for the period April 2009 to December 2014, using the latest available TCCON data (GGG2015), and co-located spatially and temporally by selecting GOSAT soundings within 550 km of the TCCON site, and ± 2 hours of each TCCON measurement. Whilst this rudimentary selection algorithm is sufficient for most sites, it can lead to issues where sites are situated close to different chemical regimes. A more robust coincidence criterion is therefore currently being explored. Overall a good agreement between TCCON and UoL GOSAT XCH4 is found, with the magnitude and phase of the seasonal cycle being well captured over a variety of sites. Figure 3 shows the total correlation across all sites, with a correlation coefficient of 0.85 and a standard deviation of 1.86 ppb.

Page 8 1900 Sodankyla, Finland 1850 Bialystok, Poland Bremen, Germany Karlsruhe, Germany Orleans, France 1800 1750 XCH 4 mean =-3.30ppb 1700 =14.54ppb r =0.56 n obs. = 332 1650 XCH 4 mean =2.06ppb =13.39ppb r =0.56 n obs. = 523 XCH 4 mean =1.40ppb =13.39ppb r =0.55 n obs. = 256 XCH 4 mean =-1.80ppb =15.78ppb r =0.36 n obs. = 742 XCH 4 mean =2.52ppb =14.26ppb r =0.47 n obs. = 686 1900 Garmisch, Germany 1850 Park Falls, Wisconsin, USA Lamont, Oklahoma, USA Tsukuba, Ibaraki, Japan Saga, Japan XCH 4 (ppb) 1800 1750 XCH 4 mean =-5.76ppb 1700 =15.40ppb r =0.44 n obs. = 769 1650 1900 Darwin, Australia 1850 1800 1750 XCH 4 mean =1.26ppb 1700 =10.66ppb r =0.59 n obs. = 1101 1650 2010 2011 2012 2013 2014 XCH 4 mean =-5.42ppb =13.17ppb r =0.61 n obs. = 868 Wollongong, Australia XCH 4 mean =4.45ppb =15.16ppb r =0.53 n obs. = 1734 2010 2011 2012 2013 2014 XCH 4 mean =5.44ppb =15.68ppb r =0.62 n obs. = 3792 Lauder, New Zealand, 125 XCH 4 mean =-2.25ppb =11.14ppb r =0.67 n obs. = 208 2010 2011 Year 2012 2013 2014 XCH 4 mean =0.28ppb =15.05ppb r =0.65 n obs. = 548 Lauder, New Zealand, 120 XCH 4 mean =-0.50ppb =12.52ppb r =0.64 n obs. = 49 2010 2011 2012 2013 2014 XCH 4 mean =4.89ppb =15.23ppb r =0.66 n obs. = 208 2010 2011 2012 2013 2014 OCFP XCH 4 v1.0 (ppb) TCCON XCH 4 (ppb) Figure 2. Comparison of retrieved XCH 4 (red) with TCCON XCH 4 (green) between April 2009 and December 2014. Only TCCON/GOSAT data pairs are plotted where co-location criteria are met. Statistics for the mean difference and standard deviation are shown in ppm along with the correlation coefficient and the total number of GOSAT soundings.

Page 9 ESA Climate Change Initiative (CCI) 1875 1850 1825 OCFP XCH4 (ppb) 1800 1775 Sodankyla, Finland Bialystok, Poland Bremen, Germany Karlsruhe, Germany 1750 Orleans, France Garmisch, Germany Park Falls, Wisconsin, USA Lamont, Oklahoma, USA Tsukuba, Ibaraki, Japan Saga, Japan 1725 Darwin, Australia Wollongong, Australia Lauder, New Zealand, 125 Lauder, New Zealand, 120 Mean 1700 1700 1725 1750 = 1.86 ppb, = 15.13 ppb, r = 0.85, n obs. = 11816 1775 1800 1825 1850 1875 TCCON XCH4 (ppb) Figure 3. Comparison of retrieved UoL XCH4 with the TCCON XCH4 between April 2009 and December 2014 across all land TCCON sites, coloured by site. Statistics for mean bias and standard deviation are shown in ppm along with the correlation coefficient.

Page 10 3. Product Description 3.1 Product Format and Content XCH 4 data are stored in the netcdf format, with each file containing a single day s GOSAT soundings. Table 2 provides a description of the variables common to all ESA GHG-CCI data products, and all necessary parameters to make use of the data (e.g. a priori data, column averaging kernels, quality information, etc.). Table 3 contains additional product-specific variables, such as instrument flags and important ancillary retrieval profile information. 3.2 Quality Flags and Metadata The data product contains an "xch4_quality_flag" variable, indicating whether the data has passed our quality checks. In normal use, only data with an xch4_quality_flag equal to 0 should be used. Only GO- SAT soundings where a pre-filter of soundings with a signal to noise ratio >= 20, solar zenith angle <= 75, latitude >= -60 S, and passing the cloud screen (i.e. surface pressure difference between O 2 -A band retrieval and ECMWF surface pressure is within 30 hpa) have been successful are processed to retrieve XCO 2. Post-filtering checks for a successful retrieval outcome (a solution is converged upon in the full physics routine), and the full CH4_GOS_OCFP v1 filter, detailed in Table 1. Glint soundings are subjected to modified filters listed in parentheses. Parameter Filter Signal to noise ratio (all bands) >= 45 Band 3 albedo: band 2 albedo >= -0.00025 Cross track angle error (degrees) >= -0.007 and <= 0.007 Along track angle error (degrees) >= -0.05 and <= 0.05 n retrieval iterations <= 7 n diverging retrieval steps <= 2 Retrieved type 1 (small) aerosol optical depth (AOD) <= 0.3 Retrieved type 2 (large) AOD <= 0.15 (<= 0.08) Retrieved ice type AOD <= 0.025 XCO 2 retrieval error (ppm) <= 2.15 (<=1.15) σ retrieved surface pressure (hpa) <= 2000 Retrieved CO 2 profile gradient between the surface and retrieval level 15 <= 0.995 type 1 AOD (relative difference between retrieved and a-priori surface pressure) >= -1.5 type 2 AOD (relative difference between retrieved and a-priori surface pressure) >= -1.2 Weak CO 2 column: strong CO 2 column >= 0.99 and <= 1.035 Table 1. Product quality filter. 3.3 Data Usage The xch4_quality_flag variable must be applied to data before use; a value of 0 indicates that the data passes our quality control. All vertically resolved data is provided on levels (as opposed to layers). This is especially important when applying UoL averaging kernels to model data.

ESA Climate Change Initiative (CCI) Page 11 3.4 File contents netcdf data files contain all of the common parameters for the ESA GHG-CCI data products (as outlined in the GHG-CCI Product Specification Document v3) as well as additional product specific parameters. A dimension of n refers to the number of retrievals per file, whilst a dimension of m refers to the number of levels retrieved for each sounding (typically 20). Name solar_zenith_angle Type Dimension Units degree Description Angle between line of sight to the sun and local vertical sensor_zenith_angle degree Angle between the line of sight to the sensor and the local vertical time dou- n seconds since Measurement time ble 1970-01-01 00:00:00 longitude degrees east Centre longitude latitude degrees north Centre latitude pressure_levels, m hpa Vertical altitude coordinate in pressure units as used for averaging kernels pressure_weight, m Pressure weights as used for averaging kernels xch4 1e-9 Retrieved column-averaged dry-air mole fraction of atmospheric methane (XCH4) in ppb. No bias correction applied xch4_uncertainty 1e-9 Statistical uncertainty of XCH4 in ppb (1σ) xch4_averaging_kernel, m XCH4 averaging kernel (a profile = vector for each single observation). Quantifies the altitude sensitivity of the XCO2 retrieval. ch4_profile_apriori, m 1e-9 A-priori mole fraction profile of atmospheric CH4 in ppm. co2_profile_apriori, m 1e-6 A-priori mole fraction profile of atmospheric CO2 in ppm. xch4_quality_flag byte n Quality flag for XCH4 retrieval, 0=good, 1=bad Table 2. Common variables for the CH4_GOS_OCFP data product. Name exposure_id Type Dimension char n, 22 Units surface_altitude float n metres surface_altitude_stdev float n metres surface_air_pressure_apriori float surface_air_pressure_apriori_std float n n hpa hpa gain byte n air_temperature_apriori float n, m K h2o_profile_apriori float n, m 1e-6 total_aod aod_type1 aod_type2 cirrus retr_flag byte n Table 3. Additional variables for CH4_GOS_OCFP. Description Exposure identification number of the sounding Altitude is the (geometric) height above the geoid, which is the reference geopotential surface. Standard deviation of the surface elevation within the area of the GOSAT sounding, as derived from the SRTM database. A-priori surface pressure value A-priori surface pressure standard deviation GOSAT TANSO FTS instrument gain mode. 1 indicates high gain. 0 indicates medium gain. Air temperature is the bulk temperature of the air, not the surface (skin) temperature. A-priori mole fraction profile of atmospheric H2O in ppm. Retrieved total aerosol optical depth Retrieved AOD type 1 Retrieved AOD type 2 Retrieved AOD cirrus Retrieval type flag (0 = land, 1 = glint).

Page 12 4. References Boesch, H., Baker, D., Connor, B., Crisp, D. and Miller, C.: Global Characterization of CO 2 Column Retrievals from Shortwave-Infrared Satellite Observations of the Orbiting Carbon Observatory-2 Mission, Remote Sens., 3(12), 270 304, doi:10.3390/rs3020270, 2011. Kuze, A., Suto, H., Nakajima, M. and Hamazaki, T.: Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring, Appl. Opt., 48(35), 6716, doi:10.1364/ao.48.006716, 2009. Natraj, V., Boesch, H., Spurr, R. J. D. and Yung, Y. L.: Retrieval of X CO2 from simulated Orbiting Carbon Observatory measurements using the fast linearized R-2OS radiative transfer model, J. Geophys. Res., 113(D11), doi:10.1029/2007jd009017, 2008. O Dell, C. W.: Acceleration of multiple-scattering, hyperspectral radiative transfer calculations via lowstreams interpolation, J. Geophys. Res., 115(D10), doi:10.1029/2009jd012803, 2010. Saitoh, N., Imasu, R., Ota, Y. and Niwa, Y.: CO 2 retrieval algorithm for the thermal infrared spectra of the Greenhouse Gases Observing Satellite: Potential of retrieving CO 2 vertical profile from high-resolution FTS sensor, J. Geophys. Res., 114(D17), doi:10.1029/2008jd011500, 2009. Yokota, T., Yoshida, Y., Eguchi, N., Ota, Y., Tanaka, T., Watanabe, H. and Maksyutov, S.: Global Concentrations of CO2 and CH4 Retrieved from GOSAT: First Preliminary Results, SOLA, 5, 160 163, doi:10.2151/sola.2009-041, 2009. Yoshida, Y., Ota, Y., Eguchi, N., Kikuchi, N., Nobuta, K., Tran, H., Morino, I. and Yokota, T.: Retrieval algorithm for CO 2 and CH 4 column abundances from short-wavelength infrared spectral observations by the Greenhouse gases observing satellite, Atmospheric Meas. Tech., 4(4), 717 734, doi:10.5194/amt-4-717-2011, 2011.