influence of co2 observations on the optimized co2 flux in an ensemble kalman filter
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2014
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Abstract
In this study, the effect of CO2 observations on an analysis of surface
CO2 flux was calculated using an influence matrix in the
CarbonTracker, which is an inverse modeling system for estimating surface
CO2 flux based on an ensemble Kalman filter. The influence matrix
represents a sensitivity of the analysis to observations. The experimental
period was from January 2000 to December 2009. The diagonal element of the
influence matrix (i.e., analysis sensitivity) is globally 4.8% on
average, which implies that the analysis extracts 4.8% of the information
from the observations and 95.2% from the background each assimilation
cycle. Because the surface CO2 flux in each week is optimized by 5
weeks of observations, the cumulative impact over 5 weeks is 19.1%,
much greater than 4.8%. The analysis sensitivity is inversely
proportional to the number of observations used in the assimilation, which
is distinctly apparent in continuous observation categories with a
sufficient number of observations. The time series of the globally averaged
analysis sensitivities shows seasonal variations, with greater sensitivities
in summer and lower sensitivities in winter, which is attributed to the
surface CO2 flux uncertainty. The time-averaged analysis sensitivities
in the Northern Hemisphere are greater than those in the tropics and the
Southern Hemisphere. The trace of the influence matrix (i.e., information
content) is a measure of the total information extracted from the
observations. The information content indicates an imbalance between the
observation coverage in North America and that in other regions.
Approximately half of the total observational information is provided by
continuous observations, mainly from North America, which indicates that
continuous observations are the most informative and that comprehensive
coverage of additional observations in other regions is necessary to
estimate the surface CO2 flux in these areas as accurately as in North
America.
| Reference Key |
kim2014atmosphericinfluence
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|---|---|
| Authors | ;J. Kim;H. M. Kim;C.-H. Cho |
| Journal | Journal of agricultural and food chemistry |
| Year | 2014 |
| DOI |
10.5194/acp-14-13515-2014
|
| URL | |
| Keywords |
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