CarbonTracker Near-Real Time (CT-NRT) is an extension of the formal CarbonTracker CO2 analysis system, designed to bridge the gap between annual updates of the formal CarbonTracker product. It extends model results past the end of the current CarbonTracker release up until the most recent date we can simulate. Usually this is limited by the availability of ERA5 meteorology to drive the TM5 transport model. CT-NRT uses real-time meteorology, different flux priors, and after Jan 2022 assimilates only a fraction of the CO2 observations assimilated by the formal CarbonTracker product. These are provisional, near-real time CO2 observations from the small set of sites able to provide them.
CT-NRT.v2023-4 is the current release. It provides results from 01 Jan 2021 to 26 Feb 2023. CT-NRT.v2023-4 starts from a CT2022 initial condition on 19 Dec 2020 using the CT2022 p1 suite member, which used GFED4.1s land and fire, ODIAC fossil fuels, and the OIF ocean priors. We recommend use of the standard CarbonTracker release (CT2022) until 31 Dec 2020.
Both CT-NRT.v2023-4 and CT2022 were computed using ERA5 reanalysis meteorology. Accordingly, all gridded mole fraction data are available on 34 vertical levels in both products.
CT-NRT.v2023-4 results can be downloaded from https://gml.noaa.gov/aftp/products/carbontracker/co2/CT-NRT.v2023-4/.
CT-NRT.v2023-4 differs from our standard CarbonTracker product in the following ways:
- Assimilation of provisional CO2 observations. CT-NRT.v2023-4 uses CO2 observational data a Near-Real Time (NRT) ObsPack. The NRT data are made available through special arrangement with data providers and have two significant limitations. First, there are fewer data available in each day. This is due to unavoidable delays such as shipping of physical samples, analysis, data processing, and quality-control procedures for the measurements are still underway. Second, these observations generally have not undergone full quality-control procedures. Many of these procedures require a full year's worth of measurements to account for large seasonal variations. For more information, please see the NRT ObsPack release notes.
CT-NRT.v2023-4 uses data from the obspack_co2_1_GLOBALVIEWplus_v8.0_2022-08-27 ObsPack until the end of calendar year 2021, then data from the obspack_co2_1_NRT_v8.2_2023-06-13 ObsPack. Decisions about which observations to assimilate, and with which level of model-data mismatch follow the CT2022 methodology.
- Use of a different prior flux model. Our standard land biosphere flux prior is not available in near-real time, so we had to develop an alternative first-guess flux estimate. For this, we take the climatology of optimized land, wildfire, and ocean fluxes from the latest standard CarbonTracker release (for this release, that is CT2022). Since the majority of flux variability comes from the land biosphere, a land flux anomaly model also has been developed. This is a simple regression of CT2022 land flux anomalies as a function of anomalies of precipitation, shortwave radiation, and temperature. The statistical flux anomaly model was developed for each CarbonTracker ecoregion, and provides daily estimates of NEE anomaly. The radiation and temperature data for this model come from the ERA-interim meteorology used by TM5; the precipitation anomaly comes from the Global Precipitation Climatology Project. Although this flux prior does not reliably reproduce interannual variability, it is arguably a more statistically optimal prior than that for our standard release since it already represents the long-term mean CO2 sinks that we know exist. Since the priors for our standard release do not represent these sinks, the standard CarbonTracker requires that CO2 observations correct these biased priors.
- Fossil-fuel emissions Fossil fuel CO2 emissions in CT-NRT.v2023-4 are the "Miller" fossil fuel emissions as described in the CT2022 documentation. This product accounts for the anomalous emissions of the COVID-19 pandemic based on emissions from the CarbonMonitor project (https://carbonmonitor.org), which have been scaled to be consistent with the national and global annual totals published by the “CDIAC at AppState” project https://energy.appstate.edu/research/work-areas/cdiac-appstate, which we deem to be the most reliable product at those space and time scales.
Previous releases of CT-NRT are available here.