Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.154 IF 5.154
  • IF 5-year value: 5.697 IF 5-year
    5.697
  • CiteScore value: 5.56 CiteScore
    5.56
  • SNIP value: 1.761 SNIP 1.761
  • IPP value: 5.30 IPP 5.30
  • SJR value: 3.164 SJR 3.164
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 59 Scimago H
    index 59
  • h5-index value: 49 h5-index 49
Volume 7, issue 1
Geosci. Model Dev., 7, 303–315, 2014
https://doi.org/10.5194/gmd-7-303-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 7, 303–315, 2014
https://doi.org/10.5194/gmd-7-303-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 13 Feb 2014

Development and technical paper | 13 Feb 2014

Atmospheric inverse modeling with known physical bounds: an example from trace gas emissions

S. M. Miller et al.

Related authors

The impact of improved satellite retrievals on estimates of biospheric carbon balance
Scot M. Miller and Anna M. Michalak
Atmos. Chem. Phys., 20, 323–331, https://doi.org/10.5194/acp-20-323-2020,https://doi.org/10.5194/acp-20-323-2020, 2020
Short summary
Geostatistical inverse modeling with very large datasets: an example from the OCO-2 satellite
Scot M. Miller, Arvind K. Saibaba, Michael E. Trudeau, Marikate E. Mountain, and Arlyn E. Andrews
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-185,https://doi.org/10.5194/gmd-2019-185, 2019
Revised manuscript accepted for GMD
Short summary
Characterizing biospheric carbon balance using CO2 observations from the OCO-2 satellite
Scot M. Miller, Anna M. Michalak, Vineet Yadav, and Jovan M. Tadić
Atmos. Chem. Phys., 18, 6785–6799, https://doi.org/10.5194/acp-18-6785-2018,https://doi.org/10.5194/acp-18-6785-2018, 2018
Short summary
Atmospheric inverse modeling via sparse reconstruction
Nils Hase, Scot M. Miller, Peter Maaß, Justus Notholt, Mathias Palm, and Thorsten Warneke
Geosci. Model Dev., 10, 3695–3713, https://doi.org/10.5194/gmd-10-3695-2017,https://doi.org/10.5194/gmd-10-3695-2017, 2017
Short summary
Constraining sector-specific CO2 and CH4 emissions in the US
Scot M. Miller and Anna M. Michalak
Atmos. Chem. Phys., 17, 3963–3985, https://doi.org/10.5194/acp-17-3963-2017,https://doi.org/10.5194/acp-17-3963-2017, 2017
Short summary

Related subject area

Atmospheric Sciences
Extending square conservation to arbitrarily structured C-grids with shallow water equations
Lilong Zhou, Jinming Feng, Lijuan Hua, and Linhao Zhong
Geosci. Model Dev., 13, 581–595, https://doi.org/10.5194/gmd-13-581-2020,https://doi.org/10.5194/gmd-13-581-2020, 2020
Short summary
Implementation of a roughness sublayer parameterization in the Weather Research and Forecasting model (WRF version 3.7.1) and its evaluation for regional climate simulations
Junhong Lee, Jinkyu Hong, Yign Noh, and Pedro A. Jiménez
Geosci. Model Dev., 13, 521–536, https://doi.org/10.5194/gmd-13-521-2020,https://doi.org/10.5194/gmd-13-521-2020, 2020
Short summary
Development of “Physical Parametrizations with PYthon” (PPPY, version 1.1) and its usage to reduce the time-step dependency in a microphysical scheme
Sébastien Riette
Geosci. Model Dev., 13, 443–460, https://doi.org/10.5194/gmd-13-443-2020,https://doi.org/10.5194/gmd-13-443-2020, 2020
Short summary
An urban trees parameterization for modeling microclimatic variables and thermal comfort conditions at street level with the Town Energy Balance model (TEB-SURFEX v8.0)
Emilie Redon, Aude Lemonsu, and Valéry Masson
Geosci. Model Dev., 13, 385–399, https://doi.org/10.5194/gmd-13-385-2020,https://doi.org/10.5194/gmd-13-385-2020, 2020
Short summary
Are contributions of emissions to ozone a matter of scale? – a study using MECO(n) (MESSy v2.50)
Mariano Mertens, Astrid Kerkweg, Volker Grewe, Patrick Jöckel, and Robert Sausen
Geosci. Model Dev., 13, 363–383, https://doi.org/10.5194/gmd-13-363-2020,https://doi.org/10.5194/gmd-13-363-2020, 2020
Short summary

Cited articles

Andrieu, C., de Freitas, N., Doucet, A., and Jordan, M.: An Introduction to MCMC for machine learning, Mach. Learn., 50, 5–43, https://doi.org/10.1023/A:1020281327116, 2003.
Antoniou, A. and Lu, W.: Practical Optimization: Algorithms and Engineering Applications, Springer, New York, NY, 2007.
Barnes, R. and You, K.: Adding bounds to kriging, Math. Geol., 24, 171–176, https://doi.org/10.1007/BF00897030, 1992.
Bergamaschi, P., Frankenberg, C., Meirink, J. F., Krol, M., Villani, M. G., Houweling, S., Dentener, F., Dlugokencky, E. J., Miller, J. B., Gatti, L. V., Engel, A., and Levin, I.: Inverse modeling of global and regional CH4 emissions using SCIAMACHY satellite retrievals, J. Geophys. Res., 114, D22301, https://doi.org/10.1029/2009JD012287, 2009.
Biraud, S. C., Torn, M. S., Smith, J. R., Sweeney, C., Riley, W. J., and Tans, P. P.: A multi-year record of airborne CO2 observations in the US Southern Great Plains, Atmos. Meas. Tech., 6, 751–763, https://doi.org/10.5194/amt-6-751-2013, 2013.
Publications Copernicus
Download
Citation