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
−1.26 PgC yr−1. This is comparable to the TM5-based estimates of CarbonTracker
(version CT2016, -0.91±1.10 PgC yr−1) and CarbonTracker Europe
(version CTE2016, -0.91±0.31 PgC yr−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.
Developing the 3-Dimensional Flow Model Used in the Data Assimilation System and Verification of Ocean Sequestration Technique of Carbon Dioxide.