A13D-1494
TANSO-FTS and CAI on GOSAT; Project Overview, Design, and Prelaunch Test Results
The Greenhouse gases Observing SATellite (GOSAT) monitors carbon dioxide (CO2) and methane (CH4) globally from space. GOSAT is a joint project of Japan Aerospace Exploration Agency (JAXA), the Ministry of Environment (MOE) and National Institute for Environmental Studies (NIES). The two instruments are accommodated on GOSAT. The Thermal And Near infrared Sensor for carbon Observation Fourier-Transform Spectrometer (TANSO-FTS) detects the Short wave infrared (SWIR) reflected on the earth's surface as well as the thermal infrared (TIR) radiated from the ground and the atmosphere. TANSO-FTS is capable of detecting wide spectral coverage, specifically, three narrow bands (0.76, 1.6, and 2 micron) and a wide band (5.5-14.3 micron) with 0.2 cm-1 spectral resolution. TANSO Cloud and Aerosol Imager (TANSO-CAI) is a radiometer of ultraviolet (UV), visible, and SWIR to detect and correct cloud and aerosol interference. The GOSAT project overview, TANSO design, and prelaunch test results will be presented. http://www.jaxa.jp/projects/sat/gosat/index_e.html
A13D-1495
Calibration Plan for GOSAT Sensors
Greenhouse gases Observing SATellite (GOSAT) is a Japanese mission to observe greenhouse gases, such as CO2 and CH4, from space. The GOSAT carries a Fourier transform spectrometer and a push broom imager. The GOSAT development is going on in phase-C/D and characterized the sensor performance in laboratory. In orbit, the observation data will be evaluated by onboard calibration data and implemented by ground processing system. The post-launch calibration items are planned and the methods will be developed before the launch. The methods are investigated by analyzing the current MODIS data, which has similar wavelength bands to GOSAT. In this paper, we show the calibration plans of post-launch onboard calibration and vicarious calibration of GOSAT sensors in orbit.
A13D-1496
Results from the Orbiting Carbon Observatory First Light Tests
The Orbiting Carbon Observatory flight instrument underwent its pre-flight First Light tests in August and September 2007. These tests were designed to determine the instrument focus and verify its primary optical performance. Determining the as-built instrument focus accurately is critical since it dictates the spectral resolution and instrument line shape function and these parameters directly affect the ability of the measurements to meet their XCO2 sensitivity and bias rejection requirements. Real instrument performance was demonstrated by directing sunlight into the test chamber and recording atmospheric spectra. These preliminary results indicate that the instrument performance meets or exceeds its primary design objectives and will provide excellent data for XCO2 retrievals. Comprehensive performance testing, calibration, and characterization are scheduled for the winter of 2007/8. http://oco.jpl.nasa.gov/
A13D-1497
Feasibility of Monitoring CO2 From ACE-FTS Solar Occultation Instrument
Atmospheric carbon dioxide influences Earth global climate. Global measurement of CO2 distribution in the 6-30 km altitude range should greatly improve our knowledge of the carbon cycle as well as the associated transport problems. In this atmospheric region, CO2 vertical variations of about 2 to 3% are expected based on in situ measurements. Even more than for other species, retrieving CO2 profile from space-borne sensor requires a high precision instrument and radiative transfer model. Space-borne solar occultation observations should provide an opportunity to determine carbon dioxide vertical profiles. Among such instruments, the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE- FTS) on board SCISAT provides (since 2004) atmospheric transmittances with a spectral resolution of 0.02 cm-1 from 750 to 4400 cm-1, a signal to noise ratio of about 300 (for a large part of the spectrum) and with a vertical resolution of about 3 km. The instrument performs sunset and sunrise measurements with coverage between approximately 85°S and 85°N, and with a majority of observations over higher latitudes. Using the LMD 4A-limb viewing radiative transfer model for the simulation of transmittances measured by ACE- FTS, an optimized set of CO2 spectral microwindows has been selected with the aim of enhancing the sensitivity to CO2 and reducing biases resulting from the temperature profile and radiative transfer model uncertainties. The 4A-limb simulations have been satisfactorily compared with the ACE forward model and measurements for the selected microwindows. The retrieval process is constrained by using a priori variance covariance matrices estimated from the chemistry transport model MOZART and aircraft observations for each season for 5 latitude bands. In particular these matrices bring useful constraints for the retrieval of CO2 profile seasonal variation and CO2 tropopause gradient. We also will present preliminary results of retrieved CO2 profiles, their sensitivity to CO2 microwindows and a priori data. Systematic application to real cases is the next step of this feasibility study.
A13D-1498
Experimental processing of spectral information from the Atmospheric Infrared Sounder: non-linear estimation of carbon dioxide spatial distribution in three dimensions
CO2 horizontal field at different atmospheric levels has been derived from AIRS hyperspectral measurements. Results for granule 001 (0 GMT) over South Europe North Africa region of Nov 16, 2002 are presented. Results were obtained using non-linear spatial-spectral analysis performed in four steps. At step 1, spectral data filtering, bad' channels are identified (statistics of second spatial differential of spectral fields are used as predictors). At step 2, cloud identification, effective cloud amount is estimated. At step 3, spatial filtering, measurement noise over cloud free pixels are reduced using spatial smoothing. At step 4, physical interpretation, geophysical parameters at cloud free pixels are retrieved with a non-linear radiative transfer formulation. The radiative transfer model for a cloud free atmosphere includes spectral reflection at the lower boundary. A modified UMBC SARTA code is used for atmospheric spectral transmittance calculations. The physical parameters, included in the model, are: (1) surface emissivity spectrum (13 spectral parameters), (2) surface temperature, (3) atmospheric temperature vertical profile (35 vertical parameters), (4) atmospheric moisture vertical profile (22 vertical parameters), (5) atmospheric ozone vertical profile (17 vertical parameters) and (6) atmospheric CO2 vertical profile (16 vertical parameters). In all 104 variables are estimated with each spatial pixel. A solution is derived from minimization of the spatial integral of a weighted absolute difference (measurement model) plus absolute values of spatial derivates of the atmospheric parameter estimates plus absolute values of the atmospheric parameter estimates. The spatial derivates of the atmospheric parameter estimates introduce a spatial filter to remove un-physical short wave spatial oscillations and to separate spectral effects from different atmospheric constituents using a priori information about their spatial variability scale. Spatial variability scale of CO2 vertical profile of ~250km. was used. The ECMWF forecast was used for solution initialization. First guess of vertically uniform CO2 profile of 365ppmv was assumed (value of ~370 ppmv is predicted by direct CO2 measurements in 2002). Measurements at cloud free areas (~7000 pixels) were interpreted. The average absolute measurement residual is within the range of 0.1-0.35K in used channels(~1900 channels) and in CO2 channels the statistic value of residual is 0.1-0.2K ( 184 channels: 101 channels in SW and 83 channels in LW). CO2 fields were derived for 3 combinations of measurement spectral bands: SW, LW and SW+LW (for the rest of the problem physical parameters measurement spectral content was fixed SW+LW). Results indicate a CO2 increment of +1-5ppmv. SW channels provided a CO2 signal for atmospheric layer of 250 -500mb, LW channels for 100 300mb. CO2 results of SW, LW and SW+LW experiments exhibit mutual spatial consistency. They show presence of spatially local maxima adjacent to cloud areas. Horizontal consistency, location and shape of these CO2 maxima between SW and LW bands results indicate on rather cloud particle spectral effects than on the CO2 spectral absorption. Cloud spectral effects cause a positive bias in CO2 estimates based upon IR measurements. That bias can not be removed by spatial-temporal averaging and will have spatial-temporal distribution pattern similar to the clouds pattern. Local CO2 maxima can be used to identify and remove clouds from the assimilation.
A13D-1499
Recent Results From the JPL Carbon Dioxide Laser Absorption Spectrometer
Active optical sensing of atmospheric molecular species relies on measuring the differential absorption between a number of different wavelengths to determine changes in concentration of the species of interest. At JPL we have been developing an aircraft instrument that uses an Integrated Path Differential Absorption (IPDA) approach in the 2-micron spectral region for high-precision measurements of atmospheric carbon dioxide mixing ratios. The IPDA approach was first used by JPL in the detection of ozone in the 1970s. This instrument development is a response to the growing interest in the use of active optical remote sensing techniques to determine the locations of sinks and sources of carbon dioxide from a space based platform as a successor to the Orbiting Carbon Observatory (OCO) set to launch in 2008, most notably with the identification of the ASCENDS mission in the recently released Earth Science Decadal Survey. In this talk we will provide a brief overview of the aircraft instrument and present experimental results from our first two flight series. The first, carried out in July 2006, was a short series of engineering checkout flights conducted over the California desert. The second series was carried out during August 2007 over the Southern Great Plains Atmospheric Research Monitoring Site over a period of three days.
A13D-1500
Sensitivity Studies for a Space-based CO2 Laser Sounder
NASA is developing a space-based CO2 Laser Sounder at Goddard Space Flight Center that is aimed at providing global CO2 measurement in the troposphere with an ultimate measurement precision goal of less than 1%. The laser technique uses a CO2 absorption band in the near infrared and has a number of laser wavelengths across one strong absorption line centered at 1572 nm. The focus of the laser measurement is lower atmosphere CO2. The lasers are pulsed and the surface return signal can be well separated from that returned by the atmosphere using time gating in the receiver. Atmospheric scattering effects on the returned signals can be greatly reduced by this method. In this paper, we report our line-by-line radiative transfer calculation results for the selection of laser frequencies used in this active technique, including the optimal selection of absorption line and laser frequencies at which the sensitivity to atmospheric temperatures is minimal and response to lower atmospheric CO2 is maximal. Other effects on this measurement, e.g., water vapor as the most variable atmospheric composition, will be also analyzed. In addition, the simultaneous measurement of surface pressure is fundamentally required in order to appropriately estimate the change of CO2 absorption corresponding to pressure fluctuation, to compute the CO2 mixing ratio relative to dry air, and to separate actual CO2 surface flux from variations in atmospheric density. The measurement technique for surface pressure will be similar to that for CO2 but uses the O2 A-band near 768 nm. Radiative transfer calculations for the surface pressure measurement will be also reported. Other information (e.g., temperature and water vapor estimates) required to go from differential absorption measurements to final CO2 concentration retrievals will be assessed and discussed.
A13D-1501
Selection and Optimization of Oxygen Lines Used for LIDAR Measurements of Surface Pressure
AER and ITT have developed a testbed to simulate differential absorption lidar (DIAL) measurements from air- and space-borne platforms. This testbed provides realistic simulations of lidar measurements for a full suite of atmospheric conditions, including changes in the temperature and water vapor profiles along the line-of-sight. One application of this testbed is the rapid analysis of a variety of different oxygen lines in order to optimize the performance of a DIAL system for measuring atmospheric surface pressure. Of the two main visible oxygen bands in the earth's atmosphere, the "singlet-delta" oxygen band (7882 cm-1) and the "A-band" oxygen band (13 121 cm-1), to date only the A-band has been utilized for atmospheric surface pressure retrievals. This presentation will describe a comparison of DIAL pressure measurements using the two oxygen bands. We also discuss the impact of laser linewidth and the ability to use wide bandwidth laser lines on temperature insensitive absorption features. These results from our testbed, in conjunction with open path experiments, demonstrate that relatively wide bandwidth lasers can be used effectively to measure atmospheric surface pressure.
A13D-1502
DOAS-based methodology to account for cirrus cloud in observations of carbon dioxide from space
This paper concerns development of the retrieval algorithms for the processing of the Greenhouse gases Observing SATellite (GOSAT) data. GOSAT is scheduled to be launched in 2008 to monitor column amounts of CO2 and CH4 gases. A nadir-looking Fourier-Transform Spectrometer (FTS) of Short Wavelength Infrared (SWIR, 1.6 microns and 2 microns) and 0.76 microns oxygen A-band regions will be mounted on GOSAT. We present an original methodology that accounts for thin cloud in carbon dioxide retrievals from space-based reflected sunlight observations in near-infrared regions utilized by GOSAT. This approach involves a reasonable, simple parameterization of the effective transmittance using a set of parameters that describe the path-length modification caused by cloud. The complete retrieval scheme includes the estimation of cloud parameters from the 0.76-microns O2 A-band and from the H2O-saturated area of the 2.0-microns band, as well as the retrieval of the averaged-column CO2 concentration for interpolated cloud parameters at the 1.58- microns band. The proposed methodology offers the advantages of differential optical absorption spectroscopy (DOAS) and provides acceptably accurate CO2 retrievals from cloudy atmosphere. The proposed algorithm offers one of the candidates for cloud detection and characterization in GOSAT operational data processing.
A13D-1503
Aerosol Effects on the Estimation of the Carbon Dioxide Concentration From the Measurements of Solar Absorption Spectra at an Altitude of 800 Meters by Using the FTS (GOSAT-BBM) in SWIR Region
The Greenhouse gases Observing SATellite (GOSAT) is scheduled to be launched in 2008 to observe tropospheric CO2 and CH4 from space. We developed a retrieval algorithm, which simultaneously estimates the CO2 column concentration and the surface albedo from a spectrum of surface scattered solar radiation at 1.6 μm region measured by Thermal And Near infrared Sensor for carbon Observation - Fourier Transform Spectrometer (TANSO-FTS) aboard GOSAT. To validate and improve the retrieval algorithm, a field experiment was conducted from 1st to 18th December, 2006 using a bread board model (BBM) of the FTS. The surface scattered solar spectra were measured by BBM, which was installed at the terminal station of the cable car near the summit of Mt. Tsukuba (at an altitude of about 800 m). In-situ CO2 censors (NDIR) and skyradiometers were set up at the surface target point and near the BBM for the continuous measurements. Also, CO2 profile was observed in-situ by Cessna aircraft near the surface up to altitude of 3km. Data obtained with no cloud condition were analyzed. The CO2 column concentrations (CCO2) were retrieved with the assumption of with and without the boundary layer aerosol. Optical properties of aerosol were estimated from the skyradiometer measurements. The difference between the CCO2 with and without aerosol had good correlation with the aerosol optical thickness at 1.6 μm, and -0.1 to 0.6 % change in the CCO2 occurred due to aerosol. Most of the CCO2 agreed with in-situ observation within 1.0 % but the maximum difference reached up to 3.0 %.
A13D-1504
Investigation of Clear-sky and Small Albedo Region From CALIOP and MODIS Observations - Optimal Region for Retrieving Carbon Dioxide From GOSAT TANSO-FTS Observation -
The TANSO-FTS (Thermal And Near infrared Sensor for carbon Observation-Fourier Transform Spectrometer) is anticipated to be onboard the GOSAT (Greenhouse gases Observing SATellite), which will be launched in 2008, and obtain the spectrum of surface-scattered light for the retrieval of CO2 and CH4 column density. One of its main aims is to deliver the CO2 column density with the error less than 1% from 1.6 μ m band. This study investigates the global distribution of the optimal environment for CO2 retrieval (i.e. the region with no cloud cover and the albedo less than 0.5) based on the cloud profile data derived from the CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) and the surface land reflectance at 1.6 μ m from the MODIS (MODerate resolution Imaging Spectrometer) from June 2006 to June 2007. The clear sky ratio from the CALIOP is the ratio of the total number of data detecting the ground as well as no cloud layer to that of all data along 10 km track, because the instantaneous field of view of TANSO-FTS is approximately 10 km. The optimal environment over the land was found to exist around the desert regions, such as northwest Arabian Peninsula, Southern Africa and the West coast of the United States throughout the year, and the continents in the middle latitudes on the winter hemisphere. The optimal environment covered about 13 % of the whole globe on annual average.
A13D-1505
The Orbiting Carbon Observatory Mission: Fast Polarization Calculations Using the R-2OS Radiative Transfer Model
The Orbiting Carbon Observatory (OCO) mission was proposed to quantify the sources and sinks of CO2 by making highly precise measurements of its column abundance. The OCO spectrometers measure absorption of reflected sunlight at the top of the atmosphere (TOA) in three narrowband near infrared (NIR) spectral regions. The high precision requirements in conjunction with the polarization sensitivity of the instrument make it essential to account for polarization in the retrieval algorithm. We use a fast polarization correction algorithm based on the assumption that only two scattering events (two orders of scattering, 2OS) contribute to polarization. The 2OS model was used in conjunction with a scalar RT model (Radiant) to simulate OCO backscatter measurements. Computations were performed for different sites and seasons, spanning a variety of surface and aerosol types. The nadir (high spatial resolution) and glint (high signal to noise ratio over ocean) modes of operation were simulated. The aerosol extinction was also varied. The radiance errors using the Radiant/2OS (R-2OS) RT model are an order of magnitude (or more) smaller than errors arising from the use of the scalar model alone. Further, a linear error analysis study show that the errors in the retrieved column-averaged dry air mole fraction of CO2 ( XCO2) using the R-2OS model are much lower than the "measurement" noise and smoothing errors appearing in the inverse model. On the other hand, use of the scalar model alone induces errors that could dominate the retrieval error budget. The 2OS computation is also an order of magnitude faster than a full multiple scattering scalar calculation.
A13D-1506
Optimization of GOSAT Atmospheric Retrieval of CO2 in Presence of Atmospheric Particles Using Empirical Orthogonal Function Representation
As part of the international effort to promote greenhouse-gases observation and to understand furthermore the carbon cycle, the Ministry of Environment of Japan (MOE), the National Institute for Environmental Studies (NIES), and the Japan Aerospace Exploration Agency (JAXA) plan to launch GOSAT (Greenhouse gases Observing SATellite) in 2008 for the global monitoring of CO2 and CH4 from space. The inverse problem that must be solved for GOSAT level 2 retrieval algorithms is very complex, involving thousands of measurement parameters (wavenumber channels) for 3 of the spectral bands of the TANSO Fourier transform spectrometer. Potentially more than one hundred state parameters would need to be retrieved, depending on the vertical resolution of the volume mixing ratio (VMR) profiles required for the retrieval of each species, to which we must add aerosols and cloud parameters. The most computationally expensive part of current signal processing comes from the computation of the forward model itself, based on HSTAR radiative transfer code, and also from the calculation of the Jacobian (derivative of the forward model relative to state parameters). The Jacobian is calculated using numerical derivatives, which implies computing perturbed states of the forward model. Furthermore, iterative algorithms selected to solve non-linear inverse problems require computing a new Jacobian at each iteration. We explored the benefit of using an optimal representation for the state parameters based on empirical orthogonal functions (EOF). This compact representation allows reducing the number of state parameters near to the level of the number of degrees of freedom in the signal, which is significantly smaller than the actual number of state parameters required for the accurate computation of the forward model in nadir observation mode. We present EOF based on the singular vectors of the normalized Jacobian, taking into account the prior covariance matrix of the state parameters. Such optimal representation proved to be efficient also for non-linear retrieval involving light scattering by atmospheric particles like thin clouds and aerosols. Using EOF derived from clear sky conditions, we developed a simple way to approximate efficiently the Jacobian when considering atmospheric particles, without need to change the EOF basis when particles parameters are updated. This optimization requires evaluating the forward model a number of times that is only the number of optimal parameters (number of EOF) instead of computing it a number of times equal to the number of parameters in full representation. For example, CO2 retrieval in 1.6 μ m band must be performed for more than 25 atmospheric layers, while the number of degrees of freedom of the signal is less than 3 for the vertical profile. When particles parameters are retrieved simultaneously (leading to a non-linear inverse problem), this advantage may becomes even more significant since iterative methods require to recalculate the Jacobian at each iteration. This aspect will be discussed at the meeting.
A13D-1507
Accuracy and Precision of CO2 Vertical Profiles Retrieved from Thermal Infrared Spectra of GOSAT/TANSO-FTS sensor
The Greenhouse gases Observing Satellite (GOSAT) has been developed by National Institute for Environmental Studies (NIES), Ministry of the Environment, and Japan Aerospace Exploration Agency (JAXA), and planed to be lunched in 2008 for global observation of greenhouse gases such as CO2 and CH4 with high accuracy/precision. This study assesses the performance of the FTS sensor on board the GOSAT, Thermal And Near infrared Sensor for carbon Observation (TANSO)-FTS, in retrieving CO2 concentrations from spectra at around 15 μm (700-800 cm-1). For this purpose, we computed pseudo-spectra with the spectral resolution of TANSO-FTS for various atmospheric conditions and then performed CO2 retrieval simulations using the simulated spectra by applying Maximum a posteriori (MAP) method. CO2 concentrations used in the simulations were derived from the transport model based on the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) [ Satoh et al., 2007]. The results show that the retrieved CO2 concentrations agree with true concentrations to within +/-0.5% above 700 hPa every season and every latitudinal region if no temperature bias and random scatter are included. In case of temperature bias of 1 K, +/-15% or larger errors are yielded in retrieved CO2 concentrations below 100 hPa. However, selecting channels appropriate for CO2 retrievals on the basis of information contents computed following the Shannonfs information theory [ Shannon and Weaver, 1949] could greatly reduce the errors attributable to temperature uncertainties; the +/-15% differences between true and retrieved CO2 concentrations decrease less than +/-2% differences through the channel selection. We also applied the developed algorithm to real spectra obtained with a hyper-spectral sensor to confirm the validity of the method.
A13D-1508
The Darwin TCCON Site - CO2 Calibration and First Data
This paper presents the first measurements from the solar observatory deployed to Darwin, Australia in August 2005. The observatory is the second dedicated instrument in the Total Carbon Column Observing Network (TCCON). The first two years of column values are presented, as well as comparison to integrated in situ aircraft profiles obtained during the Tropical Warm Pool - International Cloud Experiment (TWP-ICE) in January - February 2006. Sites in TCCON will provide ground-based validation and calibration for upcoming space-based instruments, such as the Orbiting Carbon Observatory (OCO) and Greenhouse Gases Observing Satellite (GOSAT), which measure the same atmospheric quantities. The TCCON stations are calibrated against integrated columns measured from aircraft by instruments calibrated on the accepted WMO CO2 scale. Two CO2 microwindows are calibrated independently, and the correction factors are determined to be 1.0143 ± 0.0004 (fit ± 95% confidence interval) and 1.0152 ± 0.0003, respectively, for the 6228 cm-1 and 6348 cm-1 bands. These values are in good agreement with similar comparisons made at Park Falls, and show an improvement in the absolute calibration, due to improved CO2 line parameters. The first two years of CO2 data from the solar FTS are analysed for secular and seasonal trends in the column average mixing ratio. These are compared to some surface in situ data trends for the same period. The column data capture the secular trend as observed in surface in situ measurements, however, the seasonal cycle is dampened relative to the surface data illustrating the need for high precision measurements, but also the potential to remove rectifier effects.
A13D-1509
Airborne SWIR FTS for GOSAT validation
In order to validate and calibrate the GOSAT satellite data, and also to develop the retrieval algorism for deriving the column density of CO2 and CH4, the airborne SWIR (Short Wave Infrared Region) FTS (Fourier transform spectrometer) has been developed and demonstrated. This instrument is called TSUKUBA model. TSUKUBA uses the same interferometer as the GOSAT-TANSO-FTS on the single optical box with temperature and humidity control system. This instrument is capable of measuring the same region of interest as GOSAT- TANSO-SWIR. These detectable region are as follows; Band1:12800 13200 cm-1, Band2:5800 6400cm-1, and Band3:4700 5200cm-1, respectively. The FTS has +/- 2.5cm maximum optical path difference, and the signal is sampled with the 1.31um laser fringes with the 40 kHz of optimal sampling rate. The aperture size is 67mm, which is the same as TANSO-FTS, the size of IFOV is 240 m from 15 km altitude. The initial performance test of TSUKUBA was carried out in our laboratory, the measured value of modulation efficiencies are 70% (Band1), 85% (Band2) and 88% (Band3), respectively. The SNR values with the equivalent black body temperature for 30% surface albedo are 220 (13050cm-1), 168 (6200cm-1), and 184 (5000cm-1). And also, the measured values of full width at half maximum (FWHM) of instrumental line shape functions are 0.37cm-1, 0.26cm-1, 0.25 cm-1 for band 1, 2, and 3, respectively. The instrumental design and the results of performance tests will be presented as well as the validation experiment.
A13D-1510
An Overview of the Validation Plans for OCO Observations
The Orbiting Carbon Observatory is scheduled for launch in September 2008. The space-based observatory will sample the dry air, column averaged mole fraction of CO2 (Xco2) based on analysis of reflected solar radiation acquired by three grating spectrometers. We will describe plans and progress to date of the OCO validation program, which consists primarily of a series of ground-based, Fourier Transform Spectrometers, that measure Xco2 in the same spectral regions as the space-based spectrometers. Site selection and procedures for ensuring self-consistency among measurements of the ground-based network will be described. The goal of the OCO validation program is to detect and mitigate any geographically coherent biases, on regional to continental scales, in the space-based retrievals of Xco2 that may affect the accuracy of carbon fluxes inferred from the space-based measurements.
A13D-1511
High Resolution Simulation of the Atmospheric Greenhouse Gases Variability with a Largangian Particle Dispersion Model
Our study focuses on evaluating the merit of using the Lagrangian particle dispersion models for resolving the atmospheric composition variability at time scale of several hours and spatial scales of tenth of kilometers, which is necessary in analysis of continuous ground based monitoring and upcoming space based observation data. Using LPDM is an attractive way to increase the horizontal resolution of fluxes, and has been tested on atmospheric chemistry studies. The backward plume transport approach is more efficient for precalculation of transport matrixes for limited number of observations. Once backward plume transport is calculated, one can carry out forward calculation for any neutral tracer. As part of the effort, we simulate daytime CO2 concentration variations with FLEXPART model at five West-Siberian stations for year 2005 and 3-hourly CO2 and CH4 concentration variations at Hateruma, Japan, from year 2000 to year 2006. Concentration variations calculated by FLEXPART are compared with those calculated by NIES global atmospheric tracer transport model, and with observations. In West-Siberia, seasonal CO2 variations are reproduced in both model results, but FLEXPART shows better agreement with observations than NIES model at synoptic scale, especially in autumn to spring period, when the PBL height is shallower. However, several peaks in observations are not reproduced by both models. Summer time simulations show good resemblance between both models and observations, with LPDM showing better time resolution. In simulation of Hateruma data, we focus attention on CO2 and CH4 concentration variations during winter (late December to early April). Contrary to simulations over Siberia in summer, the observed short-term (synoptic scale) CO2/CH4 concentrations variations appear much stronger in observation than in the NIES model simulation. On the other hand synoptic scale variations of CO2 and CH4 are fairly well reproduced in LPDM simulation, while still there are numerous problems with timing and amplitude of spikes. Nevertheless the results demonstrated feasibility of using LPDM for analyzing continuous observations and showed advantage over using the Eulerian-type models.
A13D-1512
A Geostatistical Approach for Gap-filling XCO2 Using Non-Stationary Spatial Covariance Functions
The Orbiting Carbon Observatory (OCO) will measure global column-averaged CO2 dry air mole fraction (XCO2). However, geophysical sampling limitations (e.g. clouds, aerosols) are expected to cause large gaps in the satellite data product. To reduce the percentage of contaminated soundings, OCO is designed to measure at high resolutions (3km2 at the Nadir). Although this high measurement resolution will improve the clear sky sounding probability, the retrieved data product will still have large data gaps. The availability of a high precision gap filled product, together with an accurate assessment of its associated uncertainty, would allow for improved estimations of CO2 sources and sinks. Furthermore, gap-filled global maps would provide much needed information for validating both biospheric and atmospheric transport models of CO2 over gap- filled areas. This work examines the feasibility of producing high precision XCO2 fields in the presence of geophysical sounding limitations. First, global high resolution maps of geophysical sampling limitations are constructed using measurements from satellites, such as MISR and MODIS. These maps are superimposed on an OCO global sounding grid of 0.5° resolution to identify clear sky locations. Second, a geostatistical spatial interpolation approach (i.e. kriging) is adopted to evaluate the expected precision of future satellite XCO2 gap-filled maps, in the presence of realistic sounding retrieval errors. Filling XCO2 gaps caused by the geophysical sounding limitations raises a number of challenges including the required high resolution and the global scale of the analysis, as well as the expected differences in XCO2 variability over various geographical regions. To handle these challenges, the adopted spatial interpolation approach emphasizes the characterization of local variability and the computational feasibility of the analysis. Simulated XCO2 concentrations are used to characterize the spatial variability of XCO2 using flexible non-stationary covariance functions. This representation of the covariance structure aims to capture regional changes in XCO2 variability. An optimal spatial interpolator (i.e. kriging) is then used together with the non-stationary covariance functions to gap-fill the XCO2 product over areas contaminated by clouds and/or aerosol, on a 0.5° resolution grid, and to provide an estimate of the interpolation precision. Overall, the presented work provides both an evaluation of the effects of geophysical limitations on the precision of future satellite XCO2 data products and a geostatistical gap-filling approach that is able to estimate the uncertainty associated with the resulting spatiotemporal distribution of XCO2.
A13D-1513
Interannual variations of carbon monoxide global burden measured by MOPITT and AIRS; assessments of total carbon emitted by wild fires.
Biomass burning is one of the most unstable sources of carbon for the atmosphere. Variations of carbon monoxide global burden (total tropospheric mass) can be used as a proxy for total carbon emitted by wild fires. This report presents new results of CO global total column measurements using the Atmospheric InfraRed Sounder (AIRS), a space-borne spectrometer aboard the Aqua satellite in combination with data from the Measurements of Pollution in the Troposphere (MOPITT) sensor aboard the Terra satellite. Both data sets were validated using ground-based spectrometric total column measurements in Russia and Australia and compared to the Tropospheric Emission Spectrometer (TES) retrievals. Anomalies of global CO emissions were estimated using a simple one-box model and compared to the Global Fire Emission Database (GFED), version 2. A positive trend of CO global emissions for the second half of the year between 2000 and 2006 was found while no visible trend for the first half of the year was noticed. CO annual emission in 2006 was 184 Tg higher that that in 2000- 2001. Total carbon contribution from biomass burning during the most intense fires, occurred in 1997-1998 (GFED) and 2006 was estimated as high as (0.6 - 1 ) Pg C per year larger than in 2000. This is comparable with the modern estimate of the global continental carbon net sink -0.9 Pg C per year. So, wild fires are able to convert global continental areas from a sink to a weak source of CO2.
A13D-1514
On the utility of GOSAT column average CO2 observations in reducing uncertainties of CO2 flux estimates
The utility of upcoming GOSAT column CO2 observations in surface CO2 flux estimations was evaluated. The main aim was to estimate the CO2 flux uncertainty reductions contributed by GOSAT data. To simulate the global distribution of total column CO2, we used the NIES tracer transport model at 2.5x2.5 resolution. Observation errors on 151 surface and aircraft observation sites used in this work were assigned according to (GLOBALVIEW- CO2, 2006) data product and had seasonal variations. All column CO2 data were aggregated to 7.5x7.5 degree grid cells. GOSAT observations were simulated with transport model. To simulate the spatial and temporal distributions of total column CO2 observation frequency and uncertainty of aggregated monthly mean observations, we used orbit parameters and the monthly mean total cloud coverage from JCDAS reanalysis (to estimate clear-sky frequency). Total column CO2 error is combined of systematic retrieval bias and random error adjusted by number of successful observations for each aggregated grid cell within a month, assuming a single- shot retrieval error of 5 ppm. We applied 66-region time-dependent Bayesian inverse model in cyclo-stationary mode and estimated the regional flux uncertainties of monthly mean regional CO2 flux with and without satellite data. Our results show that GOSAT data with 1.5ppm total error (for monthly mean, observation over land-only) achieve same mean flux uncertainty as the observation data from the existing surface network, with assumed systematic error contributing significantly to the total error in this case. Our estimation shows that the relative reduction in surface flux uncertainties is about 50-60 % for some regions. Expectedly, most of reduction in uncertainties occurs in the regions with low density of surface observation
A13D-1515
Inferring Gross Primary Production and Respiration From a Global Carbon Cycle Model Including Carbonyl Sulfide
Carbonly sulfide (COS), an analog of carbon dioxide is emerging as a useful atmospheric tracer of carbon cycle processes. Previous studies have shown that COS is taken up by leaves in reactions associated with photosynthesis and that the rate of its uptake is closely linked to the rate of gross primary production (GPP). However, unlike CO2, there is apparently no significant source of COS from terrestrial ecosystems. Therefore, changes in the concentration of COS in the atmosphere over these ecosystems reflects the rate of photosynthesis and is largely independent of the rate of respiration (RESP), while that of CO2 reflects the net sum, GPP + RESP = NEE. The potential significance of this can be seen by considering COS and CO2 exchange in a closed box containing either an ecosystem or a leaf from that ecosystem. For a leaf, the ratio of COS/CO2 uptake normalized by the ratio of COS/CO2 concentration (X) is observed to be about 2, while this ratio for an ecosystem (Y) can range from 3 -10. If we know X, and we can measure Y, we may calculate that, GPP = NEE*Y/X and, RESP=NEE*(Y/X-1). Thus, simultaneous measurements of COS and CO2 exchange could provide new information for carbon cycle studies. Toward this end, we have incorporated the biochemical and biophysical mechanisms controlling COS exchange into a land surface model (SIB) and we have used this model to simulate global COS and CO2 fluxes and transported these together with other known sources and sinks in a chemical transport model (PCTM). The model exhibits good skill in simulating observations of the seasonal cycle and vertical profiles of COS and CO2 concentration from NOAA and INTEX-NA over N. America. Though the major features of the observations are captured in the model calculation, discrepancies remain and illustrate some problems in the parameterization of COS fluxes. We use these "modeled data" to test the feasibility of COS-based GPP and RESP estimation.
A13D-1516
Evaluating the Capacity of Global CO2 Flux and Atmospheric Transport Models to Incorporate New Satellite Observations
As we enter the new era of satellite remote sensing for CO2 and other carbon cycle-related quantities, advanced modeling and analysis capabilities are required to fully capitalize on the new observations. Model estimates of CO2 surface flux and atmospheric transport are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, and ultimately for future projections of carbon-climate interactions. For application to current, planned, and future remotely sensed CO2 data, it is desirable that these models are accurate and unbiased at time scales from less than daily to multi-annual and at spatial scales from several kilometers or finer to global. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 1998 through 2006. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at 1x1 degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-2), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to in situ observations at sites in Northern mid latitudes and the continental tropics. The influence of key process representations is inferred. We find that the model can resolve much of the hourly to synoptic variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The seasonal cycle and its interannual variations generally respond adequately, but discrepancies in the tropics suggest the need for a refinement of the soil moisture dependence of the respiration flux in CASA. Examples and inferences for interpretation of satellite data will be discussed. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in the terrestrial CO2 sink and revolutionize our understanding of the key processes controlling atmospheric CO2 and its evolution with time.
A13D-1517
Development of an End-to-End Simulation Testbed for Atmospheric Remote Sensing Measurements: Application to Determining the Impact of LIDAR-based CO2 Column Measurements on Regional Carbon Flux Estimates
AER and ITT have been using a system engineering approach to develop an end-to-end testbed for simulating sensor performance and science impact of measurements from air- and space-borne platforms. The remote sensing part of this testbed couples atmospheric profile data from NWP models and operational satellite-based cloud analyses to a line-by-line radiative transfer model. This provides maximum flexibility in the choice of spectral wavelengths, from the microwave through the visible, enables the sensor system simulations for a global range of atmospheric conditions, and provides realistic simulations of the measurements, including orbital paths, anticipated cloud-cover, atmospheric variability and sensor noise. As part of our end-to-end approach, the remote sensing simulation data can be used directly by regional- and global-scale models to assess the science impact of the data products within a particular data assimilation scheme. This presentation will describe the application of this testbed to atmospheric carbon dioxide measurements in support of the Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission. To this end we have simulated differential absorption lidar (DIAL) measurements and coupled the results to a regional top-down carbon flux model in an effort to assess the impact of the proposed measurement system on regional CO2 flux estimates.