Greenhouse Gases 2

This work outlines progress made on the ESA Living Planet Fellowship project – ELEGANCE-GHG (ExpLoring thE Global cArboN CyclE through atmospheric GreenHouse Gas variability).

This project focuses on assessing the year to year variations in the regional carbon exchange caused by both climatic drivers (e.g. temperature and precipitation) and disturbances (such as biomass burning, deforestation or a major El Nino event).  This is achieved by examining temporal and spatial anomalies in satellite-derived atmospheric CO₂ and CH₄ measurements and linking such anomalies to temporal variations in plant phenology, wetland extent, land-use change and fire activity along with the associated physical drivers such as land surface temperature (LST) and precipitation. The project will investigate to what extent current land system models are able to reproduce these observed anomalies and identify shortcomings and potential model improvements which will impact upon the ability of these models to predict future changes to the climate.

This presentation focuses on the aspects of the project relating to wetland inter-annual variability. Recent unexpected changes in surface concentrations of CH₄ emphasise gaps in our current understanding of the CH₄ budget, which has relied on highly accurate but sparse ground-based measurements. Satellite observations of CH₄ offer new insights into the magnitude of regional sources and sinks and can help overcome large uncertainties associated with the upscaling and interpretation of surface concentration data. The dominant source of global atmospheric methane is through emissions from wetland regions whose magnitude and distribution are still poorly understood and whose sensitivity to climatic drivers such as precipitation still remains uncertain.

This work uses the methane data generated within the ESA GHG-CCI project to examine the relationship between the inter-annual variability in the observed atmospheric CH₄ and estimates of the wetland extent and subsequent CH₄ emissions, derived from both top-down satellite data (e.g. Bloom et al., 2010) and bottom-up land surface modelling (e.g. JULES).

JAXA’s Greenhouse Gases Observing Satellite (GOSAT) is a first dedicated satellite to monitor global greenhouse gases such as CO2 and CH4 from space since 2009. Greenhouse gases are observed by a Fourier Transform Spectrometer (TANSO-FTS) with 3 polarized SWIR narrow bands, which are 0.76, 1.6 and 2.0 microns of O2, CO2, and CH4 absorptions, and a TIR wide band from 5.5 to 14.3 microns, which includes CO2, CH4, O3 and H2O absorptions. The FTS observes globally with gridded points of 10 km FOV using discrete pointing covered 750-km swath in 3 days.  Simultaneously, cloud and aerosol information in FTS sounding is measured by a Cloud and Aerosol Imager (TANSO-CAI) with 4 radiometers in the UV to SWIR bands (0.38, 0.67, 0.87, and 1.6 microns) with high spatial resolution of 0.5-1.5 km and a wide swath of 1000 km.

The GOSAT acquires greenhouse gases observation data over 6.5 years with full operation of FTS SWIR, TIR and CAI.  Observation pattern of FTS is optimized to demonstrate the large point source observation such as mega-city, power plant, volcano, oil field and livestock field. The calibration accuracies are evaluated in annual trends. The radiometric accuracies of the SWIR bands are monitored by the solar diffuser, lunar calibration and stable calibration sites (Railroad valley and Sahara desert) by comparison of other coincident satellite data and simulated radiance using in-situ field experiment data. The TIR radiances are optimized by the polarized calibration using polarization reflectance and transmittance of the optical components and emissivity of the on-board blackbody. The radiometric accuracy of the TIR band is evaluated by comparison of other coincident satellite sensor such as AIRS. The geometric accuracies are evaluated by comparison with reference images and coastline database continuously. The FTS Level 1 product is currently processed by the latest v201 with also all past observation data. The CAI Level 1A product is currently processed by the latest v161. We will update the CAI Level 1B processing and calibration constant for Level 2 processing of cloud mask, cloud property and aerosol property. The long-time XCO2 and XCH4 observation datasets will be re-processed from past 2009 data using updated CAI cloud and aerosol. This presentation shows the on-orbit product status of TANSO FTS and CAI over 6.5-year operation. 

Boreal emissions (50°N – 80°N) account for 8 – 32 % of global wetland CH­₄ emissions. Large uncertainties in magnitude and timing of high-latitude CH­₄ emissions largely stem from poorly characterized role of process controls on boreal wetland CH₄ production. Multi-satellite observations of late-spring to early-autumn CH₄ concentrations can potentially provide constraints on the timing, magnitude and processes controlling boreal wetland CH₄ emissions. We use retrievals of lower-tropospheric CH₄ concentrations – based on SCIAMACHY, GOSAT and TES CH₄ measurements – to confront an ensemble of wetland CH₄ emission scenarios based on MsTMIP terrestrial biosphere models and the SWAMPS satellite-derived inundation extent dataset. For key boreal regions, including North American, Scandinavian and Siberian wetlands, we implement the GEOS-Chem model adjoint – in conjunction with lower troposphere CH₄ retrievals – to produce revised regional estimates of monthly wetland CH₄ emissions. Based on our results and the ensemble of wetland CH₄ emission scenarios, we place quantitative constraints on the role of temperature, carbon availability and inundation on the processes controlling boreal wetland CH₄ emissions. 

The Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS), on board the SCISAT satellite, has been recording solar occultation spectra through the Earth’s atmospheric since 2004 and continues to take measurements with only minor loss in performance.  The ACE-FTS can measure atmospheric profiles for a range of chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs) and hydrofluorocarbons (HFCs), including CCl₄ (CFC-10), CCl₃F (CFC-11), CCl₂F₂ (CFC-12), CHF₂Cl (HCFC-22), CHF₃ (HFC-23) and CF₃CH₂F (HFC-134a).  All these molecules are strong greenhouse gases, with CFCs and HCFCs regulated by the Montreal Protocol due to their deleterious effect on stratospheric ozone.

The upcoming version 4.0 processing of ACE-FTS data will use an improved a priori CO₂ VMR profile for the pressure-temperature retrievals, enabling more accurate trends to be derived, and an improved characterisation of the ACE-FTS instrument lineshape.  Recent improvements in the absorption cross sections for many halogen species, and more judicious microwindow selection in many instances, will contribute to additional improvements in their ACE-FTS retrievals compared with the previous processing versions 3.0/3.5.  This presentation will focus on improvements in the retrievals for a selection of these anthropogenic halogen species.

The Greenhouse gAs Uk and Global Emissions (GAUGE) programme is a NERC-led project in which a comprehensive suite of measurements are used to quantify the UK greenhouse gas (GHG) budget. This includes a combination of measurements from aircraft, satellite, ground-based in situ monitors and global chemical transport model (CTMs) estimates from the TOMCAT, MOZART and GEOS-Chem models. The primary focus of GAUGE is to use this coordinated measurement network to develop high-resolution estimates of UK GHG sources/sinks and improve global GHG flux estimates enabling effective emission reduction policies to be determined.

Space-borne observations of total column and vertical profiles of methane (CH₄) are potentially well-suited to improve our knowledge of the underlying surface fluxes. Furthermore, remote sensing measurements provide global and near-continuous information of methane and are therefore an ideal tool for validation of global model estimates.  Here we will present an inter-comparison of global TOMCAT, MOZART and GEOS-Chem methane with GOSAT shortwave infrared (SWIR) retrievals (Parker et al, 2012) and Thermal Infrared (TIR) IASI methane retrievals from RAL. With a particular focus on global and regional biases in the model estimates, we will assess the variability of model methane from 2009 to 2014 and determine potential sources of uncertainties within model methane fluxes.