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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 8 | Copyright
Geosci. Model Dev., 11, 3515-3536, 2018
https://doi.org/10.5194/gmd-11-3515-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model description paper 30 Aug 2018

Model description paper | 30 Aug 2018

CTDAS-Lagrange v1.0: a high-resolution data assimilation system for regional carbon dioxide observations

Wei He1,2, Ivar R. van der Velde3,4, Arlyn E. Andrews3, Colm Sweeney3,4, John Miller3, Pieter Tans3, Ingrid T. van der Laan-Luijkx5, Thomas Nehrkorn6, Marikate Mountain6, Weimin Ju1, Wouter Peters2,5, and Huilin Chen2,4 Wei He et al.
  • 1International Institute for Earth System Science, Nanjing University, Nanjing, China
  • 2Center for Isotope Research (CIO), Energy and Sustainability Research Institute Groningen (ESRIG), University of Groningen, Groningen, 9747 AG, the Netherlands
  • 3Global Monitoring Division, NOAA Earth System Research Laboratory, Boulder, Colorado, USA
  • 4Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, Colorado, USA
  • 5Department of Meteorology and Air Quality, Wageningen University, Wageningen, the Netherlands
  • 6Atmospheric and Environmental Research, Lexington, MA, USA

Abstract. We have implemented a regional carbon dioxide data assimilation system based on the CarbonTracker Data Assimilation Shell (CTDAS) and a high-resolution Lagrangian transport model, the Stochastic Time-Inverted Lagrangian Transport model driven by the Weather Forecast and Research meteorological fields (WRF-STILT). With this system, named CTDAS-Lagrange, we simultaneously optimize terrestrial biosphere fluxes and four parameters that adjust the lateral boundary conditions (BCs) against CO2 observations from the NOAA ESRL North America tall tower and aircraft programmable flask packages (PFPs) sampling program. Least-squares optimization is performed with a time-stepping ensemble Kalman smoother, over a time window of 10 days and assimilating sequentially a time series of observations. Because the WRF-STILT footprints are pre-computed, it is computationally efficient to run the CTDAS-Lagrange system.

To estimate the uncertainties in the optimized fluxes from the system, we performed sensitivity tests with various a priori biosphere fluxes (SiBCASA, SiB3, CT2013B) and BCs (optimized mole fraction fields from CT2013B and CTE2014, and an empirical dataset derived from aircraft observations), as well as with a variety of choices on the ways that fluxes are adjusted (additive or multiplicative), covariance length scales, biosphere flux covariances, BC parameter uncertainties, and model–data mismatches. In pseudo-data experiments, we show that in our implementation the additive flux adjustment method is more flexible in optimizing net ecosystem exchange (NEE) than the multiplicative flux adjustment method, and our sensitivity tests with real observations show that the CTDAS-Lagrange system has the ability to correct for the potential biases in the lateral BCs and to resolve large biases in the prior biosphere fluxes.

Using real observations, we have derived a range of estimates for the optimized carbon fluxes from a series of sensitivity tests, which places the North American carbon sink for the year 2010 in a range from −0.92 to −1.26PgCyr−1. This is comparable to the TM5-based estimates of CarbonTracker (version CT2016, −0.91±1.10PgCyr−1) and CarbonTracker Europe (version CTE2016, −0.91±0.31PgCyr−1). We conclude that CTDAS-Lagrange can offer a versatile and computationally attractive alternative to these global systems for regional estimates of carbon fluxes, which can take advantage of high-resolution Lagrangian footprints that are increasingly easy to obtain.

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We have implemented a regional, high-resolution, and computationally attractive carbon dioxide data assimilation system. This system, named CTDAS-Lagrange, is capable of simultaneously optimizing terrestrial biosphere fluxes and the lateral boundary conditions. The CTDAS-Lagrange system can be easily extended to assimilate an additional tracer, e.g., carbonyl sulfide (COS or OCS), for regional estimates of both net and gross carbon fluxes.
We have implemented a regional, high-resolution, and computationally attractive carbon dioxide...
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