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 ERA-interim meteorology to drive the TM5 transport model. CT-NRT uses real-time meteorology, different flux priors, and 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 was created with sponsorship from NASA, for use in the OCO-2 project.
CT-NRT.v2019-1 is the current release. It provides results from 2016-Dec-24 to 2019-Mar-29. CT-NRT.v2019-1 starts from a CT2017 initial condition on 2016-Dec-24 using the CT2017 p1dm suite member. For dates before 1 January 2017, we recommend use of the standard CarbonTracker release (CT2017).
CT-NRT.v2019-1 results can be downloaded from /aftp/products/carbontracker/co2/CT-NRT.v2019-1/.
CT-NRT.v2019-1 differs from our standard CarbonTracker product in the following ways:
- Assimilation of provisional CO2 observations. CT-NRT.v2019-1 uses CO2 observational data from GLOBALVIEW+ and from 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.v2019-1 uses data from six ObsPacks as detailed below. Most of the observations come from just two products, however. Prior to 2017-Jan-01, data are extracted primarily from the GLOBALVIEWplus_v4.2.2_2019-06-05 ObsPack. After 2018-Jan-01, data come from the_NRT_v4.4.2_2019-06-10 ObsPack. Decisions about which observations to assimilate, and with which level of model-data mismatch follow the CT2017 methodology with some modifications to be reported in the upcoming CT2019 product release.
Source Online availability Comment GLOBALVIEW+ v4.2.2 ObsPack download Main source of observations 2016-2017 NRT v4.4.2 ObsPack download Measurements in 2018, after end of GLOBALVIEW+ 4.2.2 NIES shipboard observations Available from NIES No permission to redistribute NIES JR-STATION Siberia towers Download from NIES website or available upon request to Motoki Sasakawa; ask for access to JR-STATION restricted ObsPack No permission to redistribute AirCore Available upon request to Colm Sweeney; ask for access to AirCore restricted ObsPack No permission to redistribute INPE (Brazil) aircraft data Available upon request to Luciana Gatti; ask for access to INPE restricted ObsPack No permission to redistribute
- 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 CT2017). 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 CT2017 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.
- High-temporal resolution FF emissions CT-NRT.v2019-1 does not yet apply the TIMES scaling factors to fossil fuel emissions, and therefore does not have diurnal and day-of-week variability in those emissions.
Previous releases of CT-NRT are available here.