Near-real-time CO₂ fluxes from CarbonTracker Europe for high-resolution atmospheric modeling

Abstract

Abstract. We present the CarbonTracker Europe High-Resolution (CTE-HR) system that estimates carbon dioxide (CO2) exchange over Europe at high resolution (0.1 × 0.2∘) and in near real time (about 2 months' latency). It includes a dynamic anthropogenic emission model, which uses easily available statistics on economic activity, energy use, and weather to generate anthropogenic emissions with dynamic time profiles at high spatial and temporal resolution (0.1×0.2∘, hourly). Hourly net ecosystem productivity (NEP) calculated by the Simple Biosphere model Version 4 (SiB4) is driven by meteorology from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th Generation (ERA5) dataset. This NEP is downscaled to 0.1×0.2∘ using the high-resolution Coordination of Information on the Environment (CORINE) land-cover map and combined with the Global Fire Assimilation System (GFAS) fire emissions to create terrestrial carbon fluxes. Ocean CO2 fluxes are included in our product, based on Jena CarboScope ocean CO2 fluxes, which are downscaled using wind speed and temperature. Jointly, these flux estimates enable modeling of atmospheric CO2 mole fractions over Europe. We assess the skill of the CTE-HR CO2 fluxes (a) to reproduce observed anomalies in biospheric fluxes and atmospheric CO2 mole fractions during the 2018 European drought, (b) to capture the reduction of anthropogenic emissions due to COVID-19 lockdowns, (c) to match mole fraction observations at Integrated Carbon Observation System (ICOS) sites across Europe after atmospheric transport with the Transport Model, version 5 (TM5) and the Stochastic Time-Inverted Lagrangian Transport (STILT), driven by ECMWF-IFS, and (d) to capture the magnitude and variability of measured CO2 fluxes in the city center of Amsterdam (the Netherlands). We show that CTE-HR fluxes reproduce large-scale flux anomalies reported in previous studies for both biospheric fluxes (drought of 2018) and anthropogenic emissions (COVID-19 pandemic in 2020). After applying transport of emitted CO2, the CTE-HR fluxes have lower median root mean square errors (RMSEs) relative to mole fraction observations than fluxes from a non-informed flux estimate, in which biosphere fluxes are scaled to match the global growth rate of CO2 (poor person's inversion). RMSEs are close to those of the reanalysis with the CTE data assimilation system. This is encouraging given that CTE-HR fluxes did not profit from the weekly assimilation of CO2 observations as in CTE. We furthermore compare CO2 concentration observations at the Dutch Lutjewad coastal tower with high-resolution STILT transport to show that the high-resolution fluxes manifest variability due to different emission sectors in summer and winter. Interestingly, in periods where synoptic-scale transport variability dominates CO2 concentration variations, the CTE-HR fluxes perform similarly to low-resolution fluxes (5–10× coarsened). The remaining 10 % of the simulated CO2 mole fraction differs by >2 ppm between the low-resolution and high-resolution flux representation and is clearly associated with coherent structures (“plumes”) originating from emission hotspots such as power plants. We therefore note that the added resolution of our product will matter most for very specific locations and times when used for atmospheric CO2 modeling. Finally, in a densely populated region like the Amsterdam city center, our modeled fluxes underestimate the magnitude of measured eddy covariance fluxes but capture their substantial diurnal variations in summertime and wintertime well. We conclude that our product is a promising tool for modeling the European carbon budget at a high resolution in near real time. The fluxes are freely available from the ICOS Carbon Portal (CC-BY-4.0) to be used for near-real-time monitoring and modeling, for example, as an a priori flux product in a CO2 data assimilation system. The data are available at https://doi.org/10.18160/20Z1-AYJ2 (van der Woude, 2022a).

Temperature extremes of 2022 reduced carbon uptake by forests in Europe

“…2 ) for that event 31 . The quoted range for vegetation uptake includes one mechanistic model calculation (SiB4) from our CTE-HR near real-time flux product for Europe 32 , as well as first results from atmospheric inverse modeling with a limited set of observation sites (see Supplement E) . The impact of fires is quantified separately below.…”

“…Due to a lack of direct observations, our current results in the eastern region are based mostly on the biosphere model SiB4 44 , downscaled to a higher resolution 32 . SiB4 was found to simulate the NEE response to droughts well in central and northern Europe 31 , 32 , and also in this work its calculations agree well with observed atmospheric and EC-based anomalies where available (see Supplementary Figs. S6 , S10) .…”

“…We used the SiB4 biosphere model 44 driven by ERA5 meteorology, with modified rooting zone depths to better account for soil moisture stress 31 . This product is downscaled to 0.1 x 0.2 ° based on land-use type following van der Woude et al (2023) 32 . Anomalies were calculated based on the data-availability, e.g., 2019–2021 for atmospheric comparisons, 2008–2021 for NIRv comparisons and 2016-2021 for EC-tower comparisons.…”

Measurement report: Temporal variability of vertical profiles of CO2 and CH4 over urban environment

“…On regional scales, the spatial and temporal distributions of CO 2 and CH 4 in the atmosphere are highly dependent on mesoscale weather systems (Zhang et al, 2022) and the distribution of their large-scale sources and sinks. On sub-regional and local scales, the crucial meteorological variables that determine the GHG variability, like wind speed, wind direction, and the planetary boundary layer (PBL) dynamics are superimposed on highly variable (both in space and time) distribution of sources and sinks of GHGs (van der Woude et al, 2023).. The variability in GHG fluxes is closely linked to the heterogeneity of the land-use and can become extremely high where urban environments are considered, due to the wealth of human activities responsible for their releases.…”