Comparing the CarbonTracker and M5-4DVar data assimilation systems for CO2 surface flux inversions

Data assimilation systems allow for estimating surface fluxes of greenhouse gases from atmospheric concentration measurements. Good knowledge about fluxes is essential to understand how climate change affects ecosystems and to characterize feedback mechanisms. Based on the assimilation of more than 1 year of atmospheric in situ concentration measurements, we compare the performance of two established data assimilation models, CarbonTracker and TM5-4DVar (Transport Model 5 - Four-Dimensional Variational model), for CO2 flux estimation. CarbonTracker uses an ensemble Kalman filter method to optimize fluxes on ecoregions. TM5-4DVar employs a 4-D variational method and optimizes fluxes on a 6° x 4° longitude-latitude grid. Harmonizing the input data allows for analyzing the strengths and weaknesses of the two approaches by direct comparison of the modeled concentrations and the estimated fluxes. We further assess the sensitivity of the two approaches to the density of observations and operational parameters such as the length of the assimilation time window. Our results show that both models provide optimized CO2 concentration fields of similar quality. In Antarctica CarbonTracker underestimates the wintertime CO2 concentrations, since its 5-week assimilation window does not allow for adjusting the distant surface fluxes in response to the detected concentration mismatch. Flux estimates by CarbonTracker and TM5-4DVar are consistent and robust for regions with good observation coverage, regions with low observation coverage reveal significant differences. In South America, the fluxes estimated by TM5-4DVar suffer from limited representativeness of the few observations. For the North American continent, mimicking the historical increase of the measurement network density shows improving agreement between CarbonTracker and TM5-4DVar flux estimates for increasing observation density. © Author(s) 2015

Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO2 surface flux inversions

Data assimilation systems allow for estimating surface fluxes of greenhouse gases from atmospheric concentration measurements. Good knowledge about fluxes is essential to understand how climate change affects ecosystems and to characterize feedback mechanisms. Based on assimilation of more than one year of atmospheric in-situ concentration measurements, we compare the performance of two established data assimilation models, CarbonTracker and TM5-4DVar, for CO2 flux estimation. CarbonTracker uses an Ensemble Kalman Filter method to optimize fluxes on ecoregions. TM5-4DVar employs a 4-D variational method and optimizes fluxes on a 6° × 4° longitude/latitude grid. Harmonizing the input data allows analyzing the strengths and weaknesses of the two approaches by direct comparison of the modelled concentrations and the estimated fluxes. We further assess the sensitivity of the two approaches to the density of observations and operational parameters such as temporal and spatial correlation lengths

Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO2 surface flux inversions

Data assimilation systems allow for estimating surface fluxes of greenhouse gases from atmospheric concentration measurements. Good knowledge about fluxes is essential to understand how climate change affects ecosystems and to characterize feedback mechanisms. Based on the assimilation of more than 1 year of atmospheric in situ concentration measurements, we compare the performance of two established data assimilation models, CarbonTracker and TM5-4DVar (Transport Model 5 – Four-Dimensional Variational model), for CO2 flux estimation. CarbonTracker uses an ensemble Kalman filter method to optimize fluxes on ecoregions. TM5-4DVar employs a 4-D variational method and optimizes fluxes on a 6° × 4° longitude–latitude grid. Harmonizing the input data allows for analyzing the strengths and weaknesses of the two approaches by direct comparison of the modeled concentrations and the estimated fluxes. We further assess the sensitivity of the two approaches to the density of observations and operational parameters such as the length of the assimilation time window. Our results show that both models provide optimized CO2 concentration fields of similar quality. In Antarctica CarbonTracker underestimates the wintertime CO2 concentrations, since its 5-week assimilation window does not allow for adjusting the distant surface fluxes in response to the detected concentration mismatch. Flux estimates by CarbonTracker and TM5-4DVar are consistent and robust for regions with good observation coverage, regions with low observation coverage reveal significant differences. In South America, the fluxes estimated by TM5-4DVar suffer from limited representativeness of the few observations. For the North American continent, mimicking the historical increase of the measurement network density shows improving agreement between CarbonTracker and TM5-4DVar flux estimates for increasing observation density

The CarbonTracker Data Assimilation Shell (CTDAS) v1.0: Implementation and global carbon balance 2001-2015

Data assimilation systems are used increasingly to constrain the budgets of reactive and long-lived gases measured in the atmosphere. Each trace gas has its own lifetime, dominant sources and sinks, and observational network (from flask sampling and in situ measurements to space-based remote sensing) and therefore comes with its own optimal configuration of the data assimilation. The CarbonTracker Europe data assimilation system for CO2 estimates global carbon sources and sinks, and updates are released annually and used in carbon cycle studies. CarbonTracker Europe simulations are performed using the new modular implementation of the data assimilation system: the CarbonTracker Data Assimilation Shell (CTDAS). Here, we present and document this redesign of the data assimilation code that forms the heart of CarbonTracker, specifically meant to enable easy extension and modification of the data assimilation system. This paper also presents the setup of the latest version of CarbonTracker Europe (CTE2016), including the use of the gridded state vector, and shows the resulting carbon flux estimates. We present the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans. We show that with equal fossil fuel emissions, 2015 has a higher atmospheric CO2 growth rate compared to 2014, due to reduced net land carbon uptake in later year. The European carbon sink is especially present in the forests, and the average net uptake over 2001-2015 was 0.17 +/- 0.11 PgCyr(-1) with reductions to zero during drought years. Finally, we also demonstrate the versatility of CTDAS by presenting an overview of the wide range of applications for which it has been used so far

MIPAS IMK/IAA carbon tetrachloride (CCl4) retrieval and first comparison with other instruments

MIPAS thermal limb emission measurements were used to derive vertically resolved profiles of carbon tetrachloride (CCl4). Level-1b data versions MIPAS/5.02 to MIPAS/5.06 were converted into volume mixing ratio profiles using the level-2 processor developed at Karlsruhe Institute of Technology (KIT) Institute of Meteorology and Climate Research (IMK) and Consejo Superior de Investigaciones Científicas (CSIC), Instituto de Astrofísica de Andalucía (IAA). Consideration of peroxyacetyl nitrate (PAN) as an interfering species, which is jointly retrieved, and CO2 line mixing is crucial for reliable retrievals. Parts of the CO2 Q-branch region that overlap with the CCl4 signature were omitted, since large residuals were still found even though line mixing was considered in the forward model. However, the omitted spectral region could be narrowed noticeably when line mixing was accounted for. A new CCl4 spectroscopic data set leads to slightly smaller CCl4 volume mixing ratios. In general, latitude–altitude cross sections show the expected CCl4 features with highest values of around 90 pptv at altitudes at and below the tropical tropopause and values decreasing with altitude and latitude due to stratospheric decomposition. Other patterns, such as subsidence in the polar vortex during winter and early spring, are also visible in the distributions. The decline in CCl4 abundance during the MIPAS Envisat measurement period (July 2002 to April 2012) is clearly reflected in the altitude–latitude cross section of trends estimated from the entire retrieved data set

The CarbonTracker Data Assimilation Shell (CTDAS) v1.0 : Implementation and global carbon balance 2001-2015

Data assimilation systems are used increasingly to constrain the budgets of reactive and long-lived gases measured in the atmosphere. Each trace gas has its own lifetime, dominant sources and sinks, and observational network (from flask sampling and in situ measurements to space-based remote sensing) and therefore comes with its own optimal configuration of the data assimilation. The CarbonTracker Europe data assimilation system for CO2 estimates global carbon sources and sinks, and updates are released annually and used in carbon cycle studies. CarbonTracker Europe simulations are performed using the new modular implementation of the data assimilation system: The CarbonTracker Data Assimilation Shell (CTDAS). Here, we present and document this redesign of the data assimilation code that forms the heart of CarbonTracker, specifically meant to enable easy extension and modification of the data assimilation system. This paper also presents the setup of the latest version of CarbonTracker Europe (CTE2016), including the use of the gridded state vector, and shows the resulting carbon flux estimates. We present the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans. We show that with equal fossil fuel emissions, 2015 has a higher atmospheric CO2 growth rate compared to 2014, due to reduced net land carbon uptake in later year. The European carbon sink is especially present in the forests, and the average average net uptake over 2001-2015 was 0:17±0:11 PgCyr-1 with reductions to zero during drought years. Finally, we also demonstrate the versatility of CTDAS by presenting an overview of the wide range of applications for which it has been used so far

The CarbonTracker Data Assimilation Shell (CTDAS) v1.0: implementation and global carbon balance 2001–2015

Data assimilation systems are used increasingly to constrain the budgets of reactive and long-lived gases measured in the atmosphere. Each trace gas has its own lifetime, dominant sources and sinks, and observational network (from flask sampling and in situ measurements to space-based remote sensing) and therefore comes with its own optimal configuration of the data assimilation. The CarbonTracker Europe data assimilation system for CO2 estimates global carbon sources and sinks, and updates are released annually and used in carbon cycle studies. CarbonTracker Europe simulations are performed using the new modular implementation of the data assimilation system: the CarbonTracker Data Assimilation Shell (CTDAS). Here, we present and document this redesign of the data assimilation code that forms the heart of CarbonTracker, specifically meant to enable easy extension and modification of the data assimilation system. This paper also presents the setup of the latest version of CarbonTracker Europe (CTE2016), including the use of the gridded state vector, and shows the resulting carbon flux estimates. We present the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans. We show that with equal fossil fuel emissions, 2015 has a higher atmospheric CO2 growth rate compared to 2014, due to reduced net land carbon uptake in later year. The European carbon sink is especially present in the forests, and the average net uptake over 2001–2015 was 0. 17 ± 0. 11 PgC yr−1 with reductions to zero during drought years. Finally, we also demonstrate the versatility of CTDAS by presenting an overview of the wide range of applications for which it has been used so far