Laboratoire Des Science Du Climate Et Of Lenvironnement

Gif-sur-Yvette, France

Laboratoire Des Science Du Climate Et Of Lenvironnement

Gif-sur-Yvette, France

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Houweling S.,SRON Netherlands Institute for Space Research | Houweling S.,University Utrecht | Aben I.,SRON Netherlands Institute for Space Research | Breon F.-M.,Laboratoire Des Science Du Climate Et Of Lenvironnement | And 12 more authors.
Atmospheric Chemistry and Physics | Year: 2010

This study presents a synthetic model intercomparison to investigate the importance of transport model errors for estimating the sources and sinks of CO2 using satellite measurements. The experiments were designed for testing the potential performance of the proposed CO2 lidar A-SCOPE, but also apply to other space borne missions that monitor total column CO 2. The participating transport models IFS, LMDZ, TM3, and TM5 were run in forward and inverse mode using common a priori CO2 fluxes and initial concentrations. Forward simulations of column averaged CO2 (xCO2) mixing ratios vary between the models by =0.5 ppm over the continents and =0.27 ppm over the oceans. Despite the fact that the models agree on average on the sub-ppm level, these modest differences nevertheless lead to significant discrepancies in the inverted fluxes of 0.1 PgC/yr per 10 6km2 over land and 0.03 PgC/yr per 106km 2 over the ocean. These transport model induced flux uncertainties exceed the target requirement that was formulated for the A-SCOPE mission of 0.02 PgC/yr per 106km2, and could also limit the overall performance of other CO2 missions such as GOSAT. A variable, but overall encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen, although systematic differences are found exceeding the 0.5 ppm level. Because of this, our estimate of the impact of transport model uncerainty is likely to be conservative. It is concluded that to make use of the remote sensing technique for quantifying the sources and sinks of CO2 not only requires highly accurate satellite instruments, but also puts stringent requirements on the performance of atmospheric transport models. Improving the accuracy of these models should receive high priority, which calls for a closer collaboration between experts in atmospheric dynamics and tracer transport. © 2010 Author(s).


Thompson R.L.,Norwegian Institute For Air Research | Dlugokencky E.,National Oceanic and Atmospheric Administration | Chevallier F.,Laboratoire Des Science Du Climate Et Of Lenvironnement | Ciais P.,Laboratoire Des Science Du Climate Et Of Lenvironnement | And 10 more authors.
Geophysical Research Letters | Year: 2013

Observations of tropospheric N2O mixing ratio show significant variability on interannual timescales (0.2 ppb, 1 standard deviation). We found that interannual variability in N2O is weakly correlated with that in CFC-12 and SF6 for the northern extratropics and more strongly correlated for the southern extratropics, suggesting that interannual variability in all these species is influenced by large-scale atmospheric circulation changes and, for SF6 in particular, interhemispheric transport. N2O interannual variability was not, however, correlated with polar lower stratospheric temperature, which is used as a proxy for stratosphere-to-troposphere transport in the extratropics. This suggests that stratosphere-to-troposphere transport is not a dominant factor in year-to-year variations in N2O growth rate. Instead, we found strong correlations of N2O interannual variability with the Multivariate ENSO Index. The climate variables, precipitation, soil moisture, and temperature were also found to be significantly correlated with N2O interannual variability, suggesting that climate-driven changes in soil N2O flux may be important for variations in N2O growth rate. Key Points Analysis of tropospheric N2O inter-annual variability Tropospheric N2O inter-annual variability correlated with ENSO Climate driven variations in N2O soil emissions influence tropospheric N2O. © 2013. American Geophysical Union. All Rights Reserved.

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