Characterization of the OCO-2 instrument line shape functions using on-orbit solar measurements

Accurately characterizing the instrument line shape (ILS) of the Orbiting Carbon Observatory-2 (OCO-2) is challenging and highly important due to its high spectral resolution and requirement for retrieval accuracy (0. 25 %) compared to previous spaceborne grating spectrometers. On-orbit ILS functions for all three bands of the OCO-2 instrument have been derived using its frequent solar measurements and high-resolution solar reference spectra. The solar reference spectrum generated from the 2016 version of the Total Carbon Column Observing Network (TCCON) solar line list shows significant improvements in the fitting residual compared to the solar reference spectrum currently used in the version 7 Level 2 algorithm in the O₂ A band. The analytical functions used to represent the ILS of previous grating spectrometers are found to be inadequate for the OCO-2 ILS. Particularly, the hybrid Gaussian and super-Gaussian functions may introduce spurious variations, up to 5 % of the ILS width, depending on the spectral sampling position, when there is a spectral undersampling. Fitting a homogeneous stretch of the preflight ILS together with the relative widening of the wings of the ILS is insensitive to the sampling grid position and accurately captures the variation of ILS in the O₂ A band between decontamination events. These temporal changes of ILS may explain the spurious signals observed in the solar-induced fluorescence retrieval in barren areas

The Orbiting Carbon Observatory-2: first 18 months of science data products

The Orbiting Carbon Observatory-2 (OCO-2) is the first National Aeronautics and Space Administration (NASA) satellite designed to measure atmospheric carbon dioxide (CO_2) with the accuracy, resolution, and coverage needed to quantify CO_2 fluxes (sources and sinks) on regional scales. OCO-2 was successfully launched on 2 July 2014 and has gathered more than 2 years of observations. The v7/v7r operational data products from September 2014 to January 2016 are discussed here. On monthly timescales, 7 to 12 % of these measurements are sufficiently cloud and aerosol free to yield estimates of the column-averaged atmospheric CO_2 dry air mole fraction, X_(CO)_2, that pass all quality tests. During the first year of operations, the observing strategy, instrument calibration, and retrieval algorithm were optimized to improve both the data yield and the accuracy of the products. With these changes, global maps of X_(CO)_2 derived from the OCO-2 data are revealing some of the most robust features of the atmospheric carbon cycle. This includes X_(CO)_2 enhancements co-located with intense fossil fuel emissions in eastern US and eastern China, which are most obvious between October and December, when the north–south X_(CO)_2 gradient is small. Enhanced X_(CO)_2 coincident with biomass burning in the Amazon, central Africa, and Indonesia is also evident in this season. In May and June, when the north–south X_(CO)_2 gradient is largest, these sources are less apparent in global maps. During this part of the year, OCO-2 maps show a more than 10 ppm reduction in X_(CO)_2 across the Northern Hemisphere, as photosynthesis by the land biosphere rapidly absorbs CO_2. As the carbon cycle science community continues to analyze these OCO-2 data, information on regional-scale sources (emitters) and sinks (absorbers) which impart X_(CO)_2 changes on the order of 1 ppm, as well as far more subtle features, will emerge from this high-resolution global dataset

The Orbiting Carbon Observatory-2: first 18 months of science data products

The Orbiting Carbon Observatory-2 (OCO-2) is the first National Aeronautics and Space Administration (NASA) satellite designed to measure atmospheric carbon dioxide (CO_2) with the accuracy, resolution, and coverage needed to quantify CO_2 fluxes (sources and sinks) on regional scales. OCO-2 was successfully launched on 2 July 2014 and has gathered more than 2 years of observations. The v7/v7r operational data products from September 2014 to January 2016 are discussed here. On monthly timescales, 7 to 12 % of these measurements are sufficiently cloud and aerosol free to yield estimates of the column-averaged atmospheric CO_2 dry air mole fraction, X_(CO)_2, that pass all quality tests. During the first year of operations, the observing strategy, instrument calibration, and retrieval algorithm were optimized to improve both the data yield and the accuracy of the products. With these changes, global maps of X_(CO)_2 derived from the OCO-2 data are revealing some of the most robust features of the atmospheric carbon cycle. This includes X_(CO)_2 enhancements co-located with intense fossil fuel emissions in eastern US and eastern China, which are most obvious between October and December, when the north–south X_(CO)_2 gradient is small. Enhanced X_(CO)_2 coincident with biomass burning in the Amazon, central Africa, and Indonesia is also evident in this season. In May and June, when the north–south X_(CO)_2 gradient is largest, these sources are less apparent in global maps. During this part of the year, OCO-2 maps show a more than 10 ppm reduction in X_(CO)_2 across the Northern Hemisphere, as photosynthesis by the land biosphere rapidly absorbs CO_2. As the carbon cycle science community continues to analyze these OCO-2 data, information on regional-scale sources (emitters) and sinks (absorbers) which impart X_(CO)_2 changes on the order of 1 ppm, as well as far more subtle features, will emerge from this high-resolution global dataset

Atmospheric greenhouse gases retrieved from SCIAMACHY: comparison to ground-based FTS measurements and model results

SCIAMACHY onboard ENVISAT (launched in 2002) enables the retrieval of global long-term column-averaged dry air mole fractions of the two most important anthropogenic greenhouse gases carbon dioxide and methane (denoted XCO_2 and XCH_4). In order to assess the quality of the greenhouse gas data obtained with the recently introduced v2 of the scientific retrieval algorithm WFM-DOAS, we present validations with ground-based Fourier Transform Spectrometer (FTS) measurements and comparisons with model results at eight Total Carbon Column Observing Network (TCCON) sites providing realistic error estimates of the satellite data. Such validation is a prerequisite to assess the suitability of data sets for their use in inverse modelling. It is shown that there are generally no significant differences between the carbon dioxide annual increases of SCIAMACHY and the assimilation system CarbonTracker (2.00 ± 0.16 ppm yr^(−1) compared to 1.94 ± 0.03 ppm yr−1 on global average). The XCO_2 seasonal cycle amplitudes derived from SCIAMACHY are typically larger than those from TCCON which are in turn larger than those from CarbonTracker. The absolute values of the northern hemispheric TCCON seasonal cycle amplitudes are closer to SCIAMACHY than to CarbonTracker and the corresponding differences are not significant when compared with SCIAMACHY, whereas they can be significant for a subset of the analysed TCCON sites when compared with CarbonTracker. At Darwin we find discrepancies of the seasonal cycle derived from SCIAMACHY compared to the other data sets which can probably be ascribed to occurrences of undetected thin clouds. Based on the comparison with the reference data, we conclude that the carbon dioxide data set can be characterised by a regional relative precision (mean standard deviation of the differences) of about 2.2 ppm and a relative accuracy (standard deviation of the mean differences) of 1.1–1.2 ppm for monthly average composites within a radius of 500 km. For methane, prior to November 2005, the regional relative precision amounts to 12 ppb and the relative accuracy is about 3 ppb for monthly composite averages within the same radius. The loss of some spectral detector pixels results in a degradation of performance thereafter in the spectral range currently used for the methane column retrieval. This leads to larger scatter and lower XCH_4 values are retrieved in the tropics for the subsequent time period degrading the relative accuracy. As a result, the overall relative precision is estimated to be 17 ppb and the relative accuracy is in the range of about 10–20 ppb for monthly averages within a radius of 500 km. The derived estimates show that the SCIAMACHY XCH_4 data set before November 2005 is suitable for regional source/sink determination and regional-scale flux uncertainty reduction via inverse modelling worldwide. In addition, the XCO2 monthly data potentially provide valuable information in continental regions, where there is sparse sampling by surface flask measurements

High-Accuracy Measurements of Total Column Water Vapor From the Orbiting Carbon Observatory-2

Accurate knowledge of the distribution of water vapor in Earth's atmosphere is of critical importance to both weather and climate studies. Here we report on measurements of total column water vapor (TCWV) from hyperspectral observations of near-infrared reflected sunlight over land and ocean surfaces from the Orbiting Carbon Observatory-2 (OCO-2). These measurements are an ancillary product of the retrieval algorithm used to measure atmospheric carbon dioxide concentrations, with information coming from three highly resolved spectral bands. Comparisons to high-accuracy validation data, including ground-based GPS and microwave radiometer data, demonstrate that OCO-2 TCWV measurements have maximum root-mean-square deviations of 0.9-1.3mm. Our results indicate that OCO-2 is the first space-based sensor to accurately and precisely measure the two most important greenhouse gases, water vapor and carbon dioxide, at high spatial resolution [1.3 x 2.3 km(exp. 2)] and that OCO-2 TCWV measurements may be useful in improving numerical weather predictions and reanalysis products

Broadband Lidar Technique for Precision CO2 Measurement

Presented are preliminary experimental results, sensitivity measurements and discuss our new CO2 lidar system under development. The system is employing an erbium-doped fiber amplifier (EDFA), superluminescent light emitting diode (SLED) as a source and our previously developed Fabry-Perot interferometer subsystem as a detector part. Global measurement of carbon dioxide column with the aim of discovering and quantifying unknown sources and sinks has been a high priority for the last decade. The goal of Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission is to significantly enhance the understanding of the role of CO2 in the global carbon cycle. The National Academy of Sciences recommended in its decadal survey that NASA put in orbit a CO2 lidar to satisfy this long standing need. Existing passive sensors suffer from two shortcomings. Their measurement precision can be compromised by the path length uncertainties arising from scattering within the atmosphere. Also passive sensors using sunlight cannot observe the column at night. Both of these difficulties can be ameliorated by lidar techniques. Lidar systems present their own set of problems however. Temperature changes in the atmosphere alter the cross section for individual CO2 absorption features while the different atmospheric pressures encountered passing through the atmosphere broaden the absorption lines. Currently proposed lidars require multiple lasers operating at multiple wavelengths simultaneously in order to untangle these effects. The current goal is to develop an ultra precise, inexpensive new lidar system for precise column measurements of CO2 changes in the lower atmosphere that uses a Fabry-Perot interferometer based system as the detector portion of the instrument and replaces the narrow band laser commonly used in lidars with the newly available high power SLED as the source. This approach reduces the number of individual lasers used in the system from three or more to one - considerably reducing the risk of failure. It also tremendously reduces the requirement for wavelength stability in the source putting this responsibility instead on the Fabry-Perot subsystem

Sensitivity Studies for Argus 1000 Micro-Spectrometer: Measurements of Atmospheric Total Column Carbon Dioxide By Reflected Sunlight

A sensitivity analysis of the atmospheric boundary layer (ABL) and the atmospheric total column carbon dioxide was performed. The absorption of reflected solar radiation from the atmosphere and Earths surface near 1.58 m is utilized in this study. The CO_2 near infrared (NIR) bands at 1.58 m and 1.60 m are located within the Argus 1000 spectrometer spectral range, 1.0-1.7m. The model findings suggest that Argus 1000 spectrometer signal-to-noise ratio (SNR) must be 2000:1 to detect a 1% CO_2 change in the boundary layer (0-2 km). Argus 1000 spectrometer with its current SNR (~ 1520:1) can detect approximately 1.31% CO_2 change in the boundary layer (ABL). Two solar radiance paths were considered using GENSPECT, a line-by-line radiative transfer model, to examine the solar radiance spectra seen by the sensor. In path one, sunlight is assumed to travel through a longer path length in the atmosphere and reflect off the ground back to space. In path two, the solar beam is assumed to travel through a shorter path length and reflect off a cloud layer that is 4 km above the ground. The model findings suggest that the ratio between the solar radiances in both paths is approximately 4.5. The radiance change in both paths was examined for a 1% CO_2 perturbation in the boundary layer. The effect of the presence of clouds on both solar radiation and CO_2 absorption is also analyzed using flight data collected by the Argus 1000 spectrometer over cloudy and cloud-free scenes. The finding shows that CO_2 absorption in a clear sky condition is approximately 5.3% higher than when clouds are present

Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) XCO2_{CO_{2}} measurements with TCCON

NASA\u27s Orbiting Carbon Observatory-2 (OCO-2) has been measuring carbon dioxide column-averaged dry-air mole fraction, X$_{CO_{2}}$, in the Earth\u27s atmosphere for over 2 years. In this paper, we describe the comparisons between the first major release of the OCO-2 retrieval algorithm (B7r) and X$_{CO_{2}}$ from OCO-2\u27s primary ground-based validation network: the Total Carbon Column Observing Network (TCCON). The OCO-2 X$_{CO_{2}}$ retrievals, after filtering and bias correction, agree well when aggregated around and coincident with TCCON data in nadir, glint, and target observation modes, with absolute median differences less than 0.4 ppm and RMS differences less than 1.5 ppm. After bias correction, residual biases remain. These biases appear to depend on latitude, surface properties, and scattering by aerosols. It is thus crucial to continue measurement comparisons with TCCON to monitor and evaluate the OCO-2 X$_{CO_{2}}$ data quality throughout its mission

Total column CO_2 measurements at Darwin, Australia – site description and calibration against in situ aircraft profiles

An automated Fourier Transform Spectroscopic (FTS) solar observatory was established in Darwin, Australia in August 2005. The laboratory is part of the Total Carbon Column Observing Network, and measures atmospheric column abundances of CO_2 and O_2 and other gases. Measured CO_2 columns were calibrated against integrated aircraft profiles obtained during the TWP-ICE campaign in January–February 2006, and show good agreement with calibrations for a similar instrument in Park Falls, Wisconsin. A clear-sky low airmass relative precision of 0.1% is demonstrated in the CO2 and O2 retrieved column-averaged volume mixing ratios. The 1% negative bias in the FTS X_(CO_2) relative to the World Meteorological Organization (WMO) calibrated in situ scale is within the uncertainties of the NIR spectroscopy and analysis

Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) XCO2_{CO_{2}} measurements with TCCON

NASA\u27s Orbiting Carbon Observatory-2 (OCO-2) has been measuring carbon dioxide column-averaged dry-air mole fraction, X$_{CO_{2}}$, in the Earth\u27s atmosphere for over 2 years. In this paper, we describe the comparisons between the first major release of the OCO-2 retrieval algorithm (B7r) and X$_{CO_{2}}$ from OCO-2\u27s primary ground-based validation network: the Total Carbon Column Observing Network (TCCON). The OCO-2 X$_{CO_{2}}$ retrievals, after filtering and bias correction, agree well when aggregated around and coincident with TCCON data in nadir, glint, and target observation modes, with absolute median differences less than 0.4 ppm and RMS differences less than 1.5 ppm. After bias correction, residual biases remain. These biases appear to depend on latitude, surface properties, and scattering by aerosols. It is thus crucial to continue measurement comparisons with TCCON to monitor and evaluate the OCO-2 X$_{CO_{2}}$ data quality throughout its mission