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 10, issue 10
Geosci. Model Dev., 10, 3793–3803, 2017
https://doi.org/10.5194/gmd-10-3793-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 10, 3793–3803, 2017
https://doi.org/10.5194/gmd-10-3793-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model evaluation paper 17 Oct 2017

Model evaluation paper | 17 Oct 2017

Sensitivity analysis of the meteorological preprocessor MPP-FMI 3.0 using algorithmic differentiation

John Backman et al.

Related authors

Optical and geometrical aerosol particle properties over the United Arab Emirates
Maria Filioglou, Elina Giannakaki, John Backman, Jutta Kesti, Anne Hirsikko, Ronny Engelmann, Ewan O'Connor, Jari T. T. Leskinen, Xiaoxia Shang, Hannele Korhonen, Heikki Lihavainen, Sami Romakkaniemi, and Mika Komppula
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-133,https://doi.org/10.5194/acp-2020-133, 2020
Preprint under review for ACP
A global analysis of climate-relevant aerosol properties retrieved from the network of GAW near-surface observatories
Paolo Laj, Alessandro Bigi, Clémence Rose, Elisabeth Andrews, Cathrine Lund Myhre, Martine Collaud Coen, Alfred Wiedensohler, Michael Schultz, John A. Ogren, Markus Fiebig, Jonas Gliß, Augustin Mortier, Marco Pandolfi, Tuukka Petäjä, Sang-Woo Kim, Wenche Aas, Jean-Phillipe Putaud, Olga Mayol-Bracero, Melita Keywood, Lorenzo Labrador, Pasi Aalto, Erik Ahlberg, Lucas Alados Arboledas, Andrés Alastuey, Marcos Andrade, Begoña Artíñano, Stina Ausmeel, Todor Arsov, Eija Asmi, John Backman, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Sébastien Conil, Cedric Couret, Derek Day, Wan Dayantolis, Anna Degorska, Sebastiao Martins Dos Santos, Konstantinos Eleftheriadis, Prodromos Fetfatzis, Olivier Favez, Harald Flentje, Maria I. Gini, Asta Gregorič, Martin Gysel-Beer, Gannet A. Hallar, Jenny Hand, Andras Hoffer, Christoph Hueglin, Rakesh K. Hooda, Antti Hyvärinen, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Jeong Eun Kim, Giorgos Kouvarakis, Irena Kranjc, Radovan Krejci, Markku Kulmala, Casper Labuschagne, Hae-Jung Lee, Heikki Lihavainen, Neng-Huei Lin, Gunter Löschau, Krista Luoma, Angela Marinoni, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Nhat Anh Nguyen, Jakub Ondracek, Noemi Peréz, Maria Rita Perrone, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Véronique Pont, Natalia Prats, Anthony Prenni, Fabienne Reisen, Salvatore Romano, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Maik Schütze, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Martin Steinbacher, Junying Sun, Gloria Titos, Barbara Tokzko, Thomas Tuch, Pierre Tulet, Peter Tunved, Ville Vakkari, Fernando Velarde, Patricio Velasquez, Paolo Villani, Sterios Vratolis, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Jesus Yus-Diez, Vladimir Zdimal, Paul Zieger, and Nadezda Zikova
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-499,https://doi.org/10.5194/amt-2019-499, 2020
Preprint under review for AMT
Short summary
Multidecadal trend analysis of aerosol radiative properties at a global scale
Martine Collaud Coen, Elisabeth Andrews, Andrés Alastuey, Todor Petkov Arsov, John Backman, Benjamin T. Brem, Nicolas Bukowiecki, Cédric Couret, Konstantinos Eleftheriadis, Harald Flentje, Markus Fiebig, Martin Gysel-Beer, Jenny L. Hand, András Hoffer, Rakesh Hooda, Christoph Hueglin, Warren Joubert, Melita Keywood, Jeong Eun Kim, Sang-Woo Kim, Casper Labuschagne, Neng-Huei Lin, Yong Lin, Cathrine Lund Myhre, Krista Luoma, Hassan Lyamani, Angela Marinoni, Olga L. Mayol-Bracero, Nikos Mihalopoulos, Marco Pandolfi, Natalia Prats, Anthony J. Prenni, Jean-Philippe Putaud, Ludwig Ries, Fabienne Reisen, Karine Sellegri, Sangeeta Sharma, Patrick Sheridan, James Patrick Sherman, Junying Sun, Gloria Titos, Elvis Torres, Thomas Tuch, Rolf Weller, Alfred Wiedensohler, Paul Zieger, and Paolo Laj
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-1174,https://doi.org/10.5194/acp-2019-1174, 2020
Revised manuscript under review for ACP
Short summary
The importance of the representation of air pollution emissions for the modeled distribution and radiative effects of black carbon in the Arctic
Jacob Schacht, Bernd Heinold, Johannes Quaas, John Backman, Ribu Cherian, Andre Ehrlich, Andreas Herber, Wan Ting Katty Huang, Yutaka Kondo, Andreas Massling, P. R. Sinha, Bernadett Weinzierl, Marco Zanatta, and Ina Tegen
Atmos. Chem. Phys., 19, 11159–11183, https://doi.org/10.5194/acp-19-11159-2019,https://doi.org/10.5194/acp-19-11159-2019, 2019
Short summary
Ground-based observation of clusters and nucleation-mode particles in the Amazon
Daniela Wimmer, Stephany Buenrostro Mazon, Hanna Elina Manninen, Juha Kangasluoma, Alessandro Franchin, Tuomo Nieminen, John Backman, Jian Wang, Chongai Kuang, Radovan Krejci, Joel Brito, Fernando Goncalves Morais, Scot Turnbull Martin, Paulo Artaxo, Markku Kulmala, Veli-Matti Kerminen, and Tuukka Petäjä
Atmos. Chem. Phys., 18, 13245–13264, https://doi.org/10.5194/acp-18-13245-2018,https://doi.org/10.5194/acp-18-13245-2018, 2018
Short summary

Related subject area

Atmospheric Sciences
Representing model uncertainty for global atmospheric CO2 flux inversions using ECMWF-IFS-46R1
Joe R. McNorton, Nicolas Bousserez, Anna Agustí-Panareda, Gianpaolo Balsamo, Margarita Choulga, Andrew Dawson, Richard Engelen, Zak Kipling, and Simon Lang
Geosci. Model Dev., 13, 2297–2313, https://doi.org/10.5194/gmd-13-2297-2020,https://doi.org/10.5194/gmd-13-2297-2020, 2020
Short summary
Coupled online learning as a way to tackle instabilities and biases in neural network parameterizations: general algorithms and Lorenz 96 case study (v1.0)
Stephan Rasp
Geosci. Model Dev., 13, 2185–2196, https://doi.org/10.5194/gmd-13-2185-2020,https://doi.org/10.5194/gmd-13-2185-2020, 2020
Short summary
Evaluating a fire smoke simulation algorithm in the National Air Quality Forecast Capability (NAQFC) by using multiple observation data sets during the Southeast Nexus (SENEX) field campaign
Li Pan, HyunCheol Kim, Pius Lee, Rick Saylor, YouHua Tang, Daniel Tong, Barry Baker, Shobha Kondragunta, Chuanyu Xu, Mark G. Ruminski, Weiwei Chen, Jeff Mcqueen, and Ivanka Stajner
Geosci. Model Dev., 13, 2169–2184, https://doi.org/10.5194/gmd-13-2169-2020,https://doi.org/10.5194/gmd-13-2169-2020, 2020
Short summary
WRF-Chem v3.9 simulations of the East Asian dust storm in May 2017: modeling sensitivities to dust emission and dry deposition schemes
Yi Zeng, Minghuai Wang, Chun Zhao, Siyu Chen, Zhoukun Liu, Xin Huang, and Yang Gao
Geosci. Model Dev., 13, 2125–2147, https://doi.org/10.5194/gmd-13-2125-2020,https://doi.org/10.5194/gmd-13-2125-2020, 2020
Short summary
Bayesian spatio-temporal inference of trace gas emissions using an integrated nested Laplacian approximation and Gaussian Markov random fields
Luke M. Western, Zhe Sha, Matthew Rigby, Anita L. Ganesan, Alistair J. Manning, Kieran M. Stanley, Simon J. O'Doherty, Dickon Young, and Jonathan Rougier
Geosci. Model Dev., 13, 2095–2107, https://doi.org/10.5194/gmd-13-2095-2020,https://doi.org/10.5194/gmd-13-2095-2020, 2020
Short summary

Cited articles

Fisher, B., Kukkonen, J., and Schatzmann, M.: Meteorology applied to urban air pollution problems COST 715, Int. J. Environ. Pollut., 16, 560–570, https://doi.org/10.1504/IJEP.2001.000650, 2001.
Griewank, A. and Walther, A.: Evaluating Derivatives Principles and Techniques of Algorithmic Differentiation, vol. 2, Society for Industrial and Applied Mathematics, Philadelphia, USA, 1–56, 2008.
Guerrette, J. J. and Henze, D. K.: Development and application of the WRFPLUS-Chem online chemistry adjoint and WRFDA-Chem assimilation system, Geosci. Model Dev., 8, 1857–1876, https://doi.org/10.5194/gmd-8-1857-2015, 2015.
Hascoet, L. and Pascual, V.: The Tapenade Automatic Differentiation Tool: principles, model, and specification, ACM T. Math. Software, 39, 20:1–20:43, https://doi.org/10.1145/2450153.2450158, 2013.
Karppinen, A., Joffre, S. M., and Vaajama, P.: Boundary-layer parameterization for Finnish regulatory dispersion models, Int. J. Environ. Pollut., 8, 3–6, 1997.
Publications Copernicus
Download
Short summary
Meteorological input parameters for urban- and local-scale dispersion models can be derived from meteorological observations. This study presents a sensitivity analysis of a meteorological model that utilises readily available meteorological data to derive specific parameters required to model the atmospheric dispersion of pollutants. The study shows that wind speed is the most fundamental meteorological input parameter followed by solar radiation.
Meteorological input parameters for urban- and local-scale dispersion models can be derived from...
Citation