1Department of Soil, Water, and Climate, University of Minnesota, St. Paul, Minnesota, USA
2Department of Mechanical Engineering, University of Colorado at Boulder, Boulder, Colorado, USA
3Earth System Research Laboratory, NOAA, Boulder, Colorado, USA
4Center for Global Change Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
5School of Chemistry, University of Bristol, Bristol, UK
6Scripps Institute of Oceanography, University of California, San Diego, La Jolla, California, USA
7CIRES, University of Colorado, Boulder, Colorado, USA
8CSIRO Oceans and Atmosphere Flagship, Aspendale, Victoria, Australia
9Department of Atmospheric, Oceanic, and Space Sciences, University of Michigan, Ann Arbor, Michigan, USA
10School of Engineering and Applied Science and Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts, USA
11Center for Atmospheric and Oceanic Studies, Tohoku University, Sendai, Japan
12Max-Planck Institute for Chemistry, Mainz, Germany
Received: 27 May 2015 – Published in Geosci. Model Dev. Discuss.: 08 Jul 2015
Abstract. We describe a new 4D-Var inversion framework for nitrous oxide (N2O) based on the GEOS-Chem chemical transport model and its adjoint, and apply it in a series of observing system simulation experiments to assess how well N2O sources and sinks can be constrained by the current global observing network. The employed measurement ensemble includes approximately weekly and quasi-continuous N2O measurements (hourly averages used) from several long-term monitoring networks, N2O measurements collected from discrete air samples onboard a commercial aircraft (Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container; CARIBIC), and quasi-continuous measurements from the airborne HIAPER Pole-to-Pole Observations (HIPPO) campaigns. For a 2-year inversion, we find that the surface and HIPPO observations can accurately resolve a uniform bias in emissions during the first year; CARIBIC data provide a somewhat weaker constraint. Variable emission errors are much more difficult to resolve given the long lifetime of N2O, and major parts of the world lack significant constraints on the seasonal cycle of fluxes. Current observations can largely correct a global bias in the stratospheric sink of N2O if emissions are known, but do not provide information on the temporal and spatial distribution of the sink. However, for the more realistic scenario where source and sink are both uncertain, we find that simultaneously optimizing both would require unrealistically small errors in model transport. Regardless, a bias in the magnitude of the N2O sink would not affect the a posteriori N2O emissions for the 2-year timescale used here, given realistic initial conditions, due to the timescale required for stratosphere–troposphere exchange (STE). The same does not apply to model errors in the rate of STE itself, which we show exerts a larger influence on the tropospheric burden of N2O than does the chemical loss rate over short (< 3 year) timescales. We use a stochastic estimate of the inverse Hessian for the inversion to evaluate the spatial resolution of emission constraints provided by the observations, and find that significant, spatially explicit constraints can be achieved in locations near and immediately upwind of surface measurements and the HIPPO flight tracks; however, these are mostly confined to North America, Europe, and Australia. None of the current observing networks are able to provide significant spatial information on tropical N2O emissions. There, averaging kernels (describing the sensitivity of the inversion to emissions in each grid square) are highly smeared spatially and extend even to the midlatitudes, so that tropical emissions risk being conflated with those elsewhere. For global inversions, therefore, the current lack of constraints on the tropics also places an important limit on our ability to understand extratropical emissions. Based on the error reduction statistics from the inverse Hessian, we characterize the atmospheric distribution of unconstrained N2O, and identify regions in and downwind of South America, central Africa, and Southeast Asia where new surface or profile measurements would have the most value for reducing present uncertainty in the global N2O budget.
Revised: 14 Sep 2015 – Accepted: 17 Sep 2015 – Published: 08 Oct 2015
Wells, K. C., Millet, D. B., Bousserez, N., Henze, D. K., Chaliyakunnel, S., Griffis, T. J., Luan, Y., Dlugokencky, E. J., Prinn, R. G., O'Doherty, S., Weiss, R. F., Dutton, G. S., Elkins, J. W., Krummel, P. B., Langenfelds, R., Steele, L. P., Kort, E. A., Wofsy, S. C., and Umezawa, T.: Simulation of atmospheric N2O with GEOS-Chem and its adjoint: evaluation of observational constraints, Geosci. Model Dev., 8, 3179-3198, doi:10.5194/gmd-8-3179-2015, 2015.