Global monthly averaged CO2 fluxes recovered using a geostatistical inverse modeling approach: 1. Results using atmospheric measurements

نویسندگان

  • Kim L. Mueller
  • Sharon M. Gourdji
  • Anna M. Michalak
چکیده

[1] This study presents monthly CO2 fluxes from 1997 to 2001 at a 3.75 latitude 5 longitude resolution, inferred using a geostatistical inverse modeling approach. The approach focuses on quantifying the information content of measurements from the NOAA-ESRL cooperative air sampling network with regard to the global CO2 budget at different spatial and temporal scales. The geostatistical approach avoids the use of explicit prior flux estimates that have formed the basis of previous synthesis Bayesian inversions and does not prescribe spatial patterns of flux for large, aggregated regions. Instead, the method relies strongly on the atmospheric measurements and the inferred spatial autocorrelation of the fluxes to estimate sources and sinks and their associated uncertainties at the resolution of the atmospheric transport model. Results show that gridscale estimates exhibit high uncertainty and relatively little small-scale variability, but generally reflect reasonable fluxes in areas that are relatively well constrained by measurements. The aggregated continental-scale fluxes are better constrained, and estimates are consistent with results from previous synthesis Bayesian inversion studies for many regions. Observed differences at the continental scale are primarily attributable to the choice of a priori assumptions in the current work relative to those in other synthesis Bayesian studies. Overall, the results indicate that the geostatistical inverse modeling approach is able to estimate global fluxes using the limited atmospheric measurement network without relying on assumptions about a priori estimates of the flux distribution. As such, the method provides a means of isolating the information content of the atmospheric measurements, and thus serves as a valuable tool for reconciling top-down and bottom-up estimates of CO2 flux variability. Citation: Mueller, K. L., S. M. Gourdji, and A. M. Michalak (2008), Global monthly averaged CO2 fluxes recovered using a geostatistical inverse modeling approach: 1. Results using atmospheric measurements, J. Geophys. Res., 113, D21114, doi:10.1029/2007JD009734.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Global monthly averaged CO2 fluxes recovered using a geostatistical inverse modeling approach: 2. Results including auxiliary environmental data

[1] Geostatistical inverse modeling has been shown to be a viable alternative to synthesis Bayesian methods for estimating global continental-scale CO2 fluxes. This study extends the geostatistical approach to take advantage of spatially and temporally varying auxiliary data sets related to CO2 flux processes, which allow the inversion to capture more grid-scale flux variability and better cons...

متن کامل

A geostatistical approach to surface flux estimation of atmospheric trace gases

[1] Inverse modeling methods have been used to estimate surface fluxes of atmospheric trace gases such as CFCs, CH4, and CO2 on the basis of atmospheric mass fraction measurements. A majority of recent studies use a classical Bayesian setup, in which prior flux estimates at regional or grid scales are specified in order to further constrain the flux estimates. This paper, on the other hand, exp...

متن کامل

An estimate of monthly global emissions of anthropogenic CO2: Impact on the seasonal cycle of atmospheric CO2

[1] Monthly estimates of the global emissions of anthropogenic CO2 are presented. Approximating the seasonal CO2 emission cycle using a 2-harmonic Fourier series with coefficients as a function of latitude, the annual fluxes are decomposed into monthly flux estimates based on data for the United States and applied globally. These monthly anthropogenic CO2 flux estimates are then used to model a...

متن کامل

Biases in atmospheric CO2 estimates from correlated meteorology modeling errors

Estimates of CO2 fluxes that are based on atmospheric measurements rely upon a meteorology model to simulate atmospheric transport. These models provide a quantitative link between the surface fluxes and CO2 measurements taken downwind. Errors in the meteorology can therefore cause errors in the estimated CO2 fluxes. Meteorology errors that correlate or covary across time and/or space are parti...

متن کامل

Mapping of CO2 at high spatiotemporal resolution using satellite observations: Global distributions from OCO2

[1] Satellite observations of CO2 offer new opportunities to improve our understanding of the global carbon cycle. Using such observations to infer global maps of atmospheric CO2 and their associated uncertainties can provide key information about the distribution and dynamic behavior of CO2, through comparison to atmospheric CO2 distributions predicted from biospheric, oceanic, or fossil fuel ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008