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We present 5 years of GOSAT XCH4 retrieved using the "proxy" approach. The Proxy XCH4 data are validated against ground-based TCCON observations and are found to be of high quality with a small bias of 4.8 ppb (~0:27 %) and a single-sounding precision of 13.4 ppb (~0:74 %). The station-to-station bias (a measure of the relative accuracy) is found to be 4.2 ppb. For the first time the XCH4 = XCO2 ratio component of the Proxy retrieval is validated (bias of 0.014 ppbppm-1 (~0:30 %), single-sounding precision of 0.033 ppbppm-1 (~0:72 %)). The uncertainty relating to the model XCO2 component of the Proxy XCH4 is assessed through the use of an ensemble of XCO2 models. While each individual XCO2 model is found to agree well with the TCCON validation data (r = 0:94-0.97), it is not possible to select one model as the best from our comparisons. The median XCO2 value of the ensemble has a smaller scatter against TCCON (a standard deviation of 0.92 ppm) than any of the individual models whilst maintaining a small bias (0.15 ppm). This model median XCO2 is used to calculate the Proxy XCH4 with the maximum deviation of the ensemble from the median used as an estimate of the uncertainty. We compare this uncertainty to the a posteriori retrieval error (which is assumed to reduce with sqrt(N)) and find typically that the model XCO2 uncertainty becomes significant during summer months when the a posteriori error is at its lowest due to the increase in signal related to increased summertime reflected sunlight. We assess the significance of these model and retrieval uncertainties on flux inversion by comparing the GOSAT XCH4 against modelled XCH4 from TM5-4DVAR constrained by NOAA surface observations (MACC reanalysis scenario S1- NOAA). We find that for the majority of regions the differences are much larger than the estimated uncertainties. Our findings show that useful information will be provided to the inversions for the majority of regions in addition to that already provided by the assimilated surface measurements. [ABSTRACT FROM AUTHOR]

Sentinel-5 (S5) and its precursor (S5P) are future European satellite missions aiming at global monitoring of methane (CH4) column-average dry air mole fractions (XCH4). The spectrometers to be deployed onboard the satellites record spectra of sunlight backscattered from the Earth's surface and atmosphere. In particular, they exploit CH4 absorption in the shortwave infrared spectral range around 1.65 µm (S5 only) and 2.35 µm (both S5 and S5P) wavelength. Given an accuracy goal of better than 2% for XCH4 to be delivered on regional scales, assessment and reduction of potential sources of systematic error such as spectroscopic uncertainties is crucial. Here, we investigate how spectroscopic errors propagate into retrieval errors on the global scale. To this end, absorption spectra of a groundbased Fourier transform spectrometer (FTS) operating at very high spectral resolution serve as estimate for the quality of the spectroscopic parameters. Feeding the FTS fitting residuals as a perturbation into a global ensemble of simulated S5- and S5P-like spectra at relatively low spectral resolution, XCH4 retrieval errors exceed 0.6% in large parts of the world and show systematic correlations on regional scales, calling for improved spectroscopic parameters. [ABSTRACT FROM AUTHOR]

The article presents a study which quantifies the systematic and random errors in measuring carbon dioxide (CO2) emissions from a fossil fuel power plant using hypothetical CarbonSat constellations. The study used the power plant emission database, meteorological fields, and simulated satellite constellation overpasses and statistical analysis was conducted to arrive at the error estimates. Results show that error is somewhat smaller for the CarbonSat constellation configuration.

Ozone profiles retrieved from limb scattering measurements of the SCIAMACHY instrument based on the satellite ENVISAT are compared to ground-based low altitude resolution remote sensors. All profiles are retrieved using optimal estimation. Following the work of Rodgers and Connor (2003) the retrievals of the ground-based instruments are simulated using the SCIAMACHY retrieval. The SCIAMACHY results and the results of the ground-based microwave radiometer in Bremen and Ny Ålesund agree within the expected covariance of the intercomparison. [ABSTRACT FROM AUTHOR]