Articles | Volume 12, issue 12
https://doi.org/10.5194/gmd-12-5197-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-5197-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
11 Dec 2019
Methods for assessment of models |
| 11 Dec 2019
Algorithmic differentiation for cloud schemes (IFS Cy43r3) using CoDiPack (v1.8.1)
Manuel Baumgartner
CORRESPONDING AUTHOR
Zentrum für Datenverarbeitung, Johannes Gutenberg University Mainz, Mainz, Germany
Max Sagebaum
Chair for Scientific Computing, Technische Universität Kaiserslautern, Kaiserslautern, Germany
Nicolas R. Gauger
Chair for Scientific Computing, Technische Universität Kaiserslautern, Kaiserslautern, Germany
Peter Spichtinger
Institute for Atmospheric Physics, Johannes Gutenberg University Mainz, Mainz, Germany
André Brinkmann
Zentrum für Datenverarbeitung, Johannes Gutenberg University Mainz, Mainz, Germany
Related authors
Peter Spichtinger, Patrik Marschalik, and Manuel Baumgartner
Atmos. Chem. Phys., 23, 2035–2060, https://doi.org/10.5194/acp-23-2035-2023, https://doi.org/10.5194/acp-23-2035-2023, 2023
Short summary
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We investigate the impact of the homogeneous nucleation rate on nucleation events in cirrus. As long as the slope of the rate is represented sufficiently well, the resulting ice crystal number concentrations are not crucially affected. Even a change in the prefactor over orders of magnitude does not change the results. However, the maximum supersaturation during nucleation events shows strong changes. This quantity should be used for diagnostics instead of the popular nucleation threshold.
Michael A. Olesik, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner, Simon Unterstrasser, and Sylwester Arabas
Geosci. Model Dev., 15, 3879–3899, https://doi.org/10.5194/gmd-15-3879-2022, https://doi.org/10.5194/gmd-15-3879-2022, 2022
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In systems such as atmospheric clouds, droplets undergo growth through condensation of vapor. The broadness of the resultant size spectrum of droplets influences precipitation likelihood and the radiative properties of clouds. One of the inherent limitations of simulations of the problem is the so-called numerical diffusion causing overestimation of the spectrum width, hence the term numerical broadening. In the paper, we take a closer look at one of the algorithms used in this context: MPDATA.
Manuel Baumgartner, Christian Rolf, Jens-Uwe Grooß, Julia Schneider, Tobias Schorr, Ottmar Möhler, Peter Spichtinger, and Martina Krämer
Atmos. Chem. Phys., 22, 65–91, https://doi.org/10.5194/acp-22-65-2022, https://doi.org/10.5194/acp-22-65-2022, 2022
Short summary
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An important mechanism for the appearance of ice particles in the upper troposphere at low temperatures is homogeneous nucleation. This process is commonly described by the
Koop line, predicting the humidity at freezing. However, laboratory measurements suggest that the freezing humidities are above the Koop line, motivating the present study to investigate the influence of different physical parameterizations on the homogeneous freezing with the help of a detailed numerical model.
Julia Schneider, Kristina Höhler, Robert Wagner, Harald Saathoff, Martin Schnaiter, Tobias Schorr, Isabelle Steinke, Stefan Benz, Manuel Baumgartner, Christian Rolf, Martina Krämer, Thomas Leisner, and Ottmar Möhler
Atmos. Chem. Phys., 21, 14403–14425, https://doi.org/10.5194/acp-21-14403-2021, https://doi.org/10.5194/acp-21-14403-2021, 2021
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Homogeneous freezing is a relevant mechanism for the formation of cirrus clouds in the upper troposphere. Based on an extensive set of homogeneous freezing experiments at the AIDA chamber with aqueous sulfuric acid aerosol, we provide a new fit line for homogeneous freezing onset conditions of sulfuric acid aerosol focusing on cirrus temperatures. In the atmosphere, homogeneous freezing thresholds have important implications on the cirrus cloud occurrence and related cloud radiative effects.
Ralf Weigel, Christoph Mahnke, Manuel Baumgartner, Martina Krämer, Peter Spichtinger, Nicole Spelten, Armin Afchine, Christian Rolf, Silvia Viciani, Francesco D'Amato, Holger Tost, and Stephan Borrmann
Atmos. Chem. Phys., 21, 13455–13481, https://doi.org/10.5194/acp-21-13455-2021, https://doi.org/10.5194/acp-21-13455-2021, 2021
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In July and August 2017, the StratoClim mission took place in Nepal with eight flights of the M-55 Geophysica at up to 20 km in the Asian monsoon anticyclone. New particle formation (NPF) next to cloud ice was detected in situ by abundant nucleation-mode aerosols (> 6 nm) along with ice particles (> 3 µm). NPF was observed mainly below the tropopause, down to 15 % being non-volatile residues. Observed intra-cloud NPF indicates its importance for the composition in the tropical tropopause layer.
Ralf Weigel, Christoph Mahnke, Manuel Baumgartner, Antonis Dragoneas, Bärbel Vogel, Felix Ploeger, Silvia Viciani, Francesco D'Amato, Silvia Bucci, Bernard Legras, Beiping Luo, and Stephan Borrmann
Atmos. Chem. Phys., 21, 11689–11722, https://doi.org/10.5194/acp-21-11689-2021, https://doi.org/10.5194/acp-21-11689-2021, 2021
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In July and August 2017, eight StratoClim mission flights of the Geophysica reached up to 20 km in the Asian monsoon anticyclone. New particle formation (NPF) was identified in situ by abundant nucleation-mode aerosols (6–15 nm in diameter) with mixing ratios of up to 50 000 mg−1. NPF occurred most frequently at 12–16 km with fractions of non-volatile residues of down to 15 %. Abundance and productivity of observed NPF indicate its ability to promote the Asian tropopause aerosol layer.
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The potential temperature is routinely used in atmospheric science. We review its derivation and suggest a new potential temperature, based on a temperature-dependent parameterization of the dry air's specific heat capacity. Moreover, we compare the new potential temperature to the common one and discuss the differences which become more important at higher altitudes. Finally, we indicate some consequences of using the new potential temperature in typical applications.
Manuel Baumgartner and Peter Spichtinger
Atmos. Chem. Phys., 18, 2525–2546, https://doi.org/10.5194/acp-18-2525-2018, https://doi.org/10.5194/acp-18-2525-2018, 2018
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Ice crystals are surrounded by liquid cloud droplets in mixed-phase clouds. The coexistence of ice and water is thermodynamically not stable and the particles will influence their respective growth by condensation. This effect is known as the Wegener–Bergeron–Findeisen process. In current models, the local interactions of the particles are neglected and they can only interact indirectly. This work proposes an approach to include local interactions and discusses some implications.
Peter Spichtinger, Patrik Marschalik, and Manuel Baumgartner
Atmos. Chem. Phys., 23, 2035–2060, https://doi.org/10.5194/acp-23-2035-2023, https://doi.org/10.5194/acp-23-2035-2023, 2023
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We investigate the impact of the homogeneous nucleation rate on nucleation events in cirrus. As long as the slope of the rate is represented sufficiently well, the resulting ice crystal number concentrations are not crucially affected. Even a change in the prefactor over orders of magnitude does not change the results. However, the maximum supersaturation during nucleation events shows strong changes. This quantity should be used for diagnostics instead of the popular nucleation threshold.
Michael A. Olesik, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner, Simon Unterstrasser, and Sylwester Arabas
Geosci. Model Dev., 15, 3879–3899, https://doi.org/10.5194/gmd-15-3879-2022, https://doi.org/10.5194/gmd-15-3879-2022, 2022
Short summary
Short summary
In systems such as atmospheric clouds, droplets undergo growth through condensation of vapor. The broadness of the resultant size spectrum of droplets influences precipitation likelihood and the radiative properties of clouds. One of the inherent limitations of simulations of the problem is the so-called numerical diffusion causing overestimation of the spectrum width, hence the term numerical broadening. In the paper, we take a closer look at one of the algorithms used in this context: MPDATA.
Stefan Niebler, Annette Miltenberger, Bertil Schmidt, and Peter Spichtinger
Weather Clim. Dynam., 3, 113–137, https://doi.org/10.5194/wcd-3-113-2022, https://doi.org/10.5194/wcd-3-113-2022, 2022
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We use machine learning to create a network that detects and classifies four types of synoptic-scale weather fronts from ERA5 atmospheric reanalysis data. We present an application of our method, showing its use case in a scientific context. Additionally, our results show that multiple sources of training data are necessary to perform well on different regions, implying differences within those regions. Qualitative evaluation shows that the results are physically plausible.
Manuel Baumgartner, Christian Rolf, Jens-Uwe Grooß, Julia Schneider, Tobias Schorr, Ottmar Möhler, Peter Spichtinger, and Martina Krämer
Atmos. Chem. Phys., 22, 65–91, https://doi.org/10.5194/acp-22-65-2022, https://doi.org/10.5194/acp-22-65-2022, 2022
Short summary
Short summary
An important mechanism for the appearance of ice particles in the upper troposphere at low temperatures is homogeneous nucleation. This process is commonly described by the
Koop line, predicting the humidity at freezing. However, laboratory measurements suggest that the freezing humidities are above the Koop line, motivating the present study to investigate the influence of different physical parameterizations on the homogeneous freezing with the help of a detailed numerical model.
Julia Schneider, Kristina Höhler, Robert Wagner, Harald Saathoff, Martin Schnaiter, Tobias Schorr, Isabelle Steinke, Stefan Benz, Manuel Baumgartner, Christian Rolf, Martina Krämer, Thomas Leisner, and Ottmar Möhler
Atmos. Chem. Phys., 21, 14403–14425, https://doi.org/10.5194/acp-21-14403-2021, https://doi.org/10.5194/acp-21-14403-2021, 2021
Short summary
Short summary
Homogeneous freezing is a relevant mechanism for the formation of cirrus clouds in the upper troposphere. Based on an extensive set of homogeneous freezing experiments at the AIDA chamber with aqueous sulfuric acid aerosol, we provide a new fit line for homogeneous freezing onset conditions of sulfuric acid aerosol focusing on cirrus temperatures. In the atmosphere, homogeneous freezing thresholds have important implications on the cirrus cloud occurrence and related cloud radiative effects.
Ralf Weigel, Christoph Mahnke, Manuel Baumgartner, Martina Krämer, Peter Spichtinger, Nicole Spelten, Armin Afchine, Christian Rolf, Silvia Viciani, Francesco D'Amato, Holger Tost, and Stephan Borrmann
Atmos. Chem. Phys., 21, 13455–13481, https://doi.org/10.5194/acp-21-13455-2021, https://doi.org/10.5194/acp-21-13455-2021, 2021
Short summary
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In July and August 2017, the StratoClim mission took place in Nepal with eight flights of the M-55 Geophysica at up to 20 km in the Asian monsoon anticyclone. New particle formation (NPF) next to cloud ice was detected in situ by abundant nucleation-mode aerosols (> 6 nm) along with ice particles (> 3 µm). NPF was observed mainly below the tropopause, down to 15 % being non-volatile residues. Observed intra-cloud NPF indicates its importance for the composition in the tropical tropopause layer.
Ralf Weigel, Christoph Mahnke, Manuel Baumgartner, Antonis Dragoneas, Bärbel Vogel, Felix Ploeger, Silvia Viciani, Francesco D'Amato, Silvia Bucci, Bernard Legras, Beiping Luo, and Stephan Borrmann
Atmos. Chem. Phys., 21, 11689–11722, https://doi.org/10.5194/acp-21-11689-2021, https://doi.org/10.5194/acp-21-11689-2021, 2021
Short summary
Short summary
In July and August 2017, eight StratoClim mission flights of the Geophysica reached up to 20 km in the Asian monsoon anticyclone. New particle formation (NPF) was identified in situ by abundant nucleation-mode aerosols (6–15 nm in diameter) with mixing ratios of up to 50 000 mg−1. NPF occurred most frequently at 12–16 km with fractions of non-volatile residues of down to 15 %. Abundance and productivity of observed NPF indicate its ability to promote the Asian tropopause aerosol layer.
Manuel Baumgartner, Ralf Weigel, Allan H. Harvey, Felix Plöger, Ulrich Achatz, and Peter Spichtinger
Atmos. Chem. Phys., 20, 15585–15616, https://doi.org/10.5194/acp-20-15585-2020, https://doi.org/10.5194/acp-20-15585-2020, 2020
Short summary
Short summary
The potential temperature is routinely used in atmospheric science. We review its derivation and suggest a new potential temperature, based on a temperature-dependent parameterization of the dry air's specific heat capacity. Moreover, we compare the new potential temperature to the common one and discuss the differences which become more important at higher altitudes. Finally, we indicate some consequences of using the new potential temperature in typical applications.
Martina Krämer, Christian Rolf, Nicole Spelten, Armin Afchine, David Fahey, Eric Jensen, Sergey Khaykin, Thomas Kuhn, Paul Lawson, Alexey Lykov, Laura L. Pan, Martin Riese, Andrew Rollins, Fred Stroh, Troy Thornberry, Veronika Wolf, Sarah Woods, Peter Spichtinger, Johannes Quaas, and Odran Sourdeval
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To improve the representations of cirrus clouds in climate predictions, extended knowledge of their properties and geographical distribution is required. This study presents extensive airborne in situ and satellite remote sensing climatologies of cirrus and humidity, which serve as a guide to cirrus clouds. Further, exemplary radiative characteristics of cirrus types and also in situ observations of tropical tropopause layer cirrus and humidity in the Asian monsoon anticyclone are shown.
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The first analysis of 15 years of global-scale water vapour and relative humidity observations by passenger aircraft in the MOZAIC and IAGOS programmes resolves detailed features of water vapour and ice-supersaturated air in the mid-latitude tropopause. Key results provide in-depth insight into seasonal and regional variability and chemical signatures of ice-supersaturated air masses, including trend analyses, and show a close link to cirrus clouds and their highly important effects on climate.
Manuel Baumgartner and Peter Spichtinger
Atmos. Chem. Phys., 18, 2525–2546, https://doi.org/10.5194/acp-18-2525-2018, https://doi.org/10.5194/acp-18-2525-2018, 2018
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Ice crystals are surrounded by liquid cloud droplets in mixed-phase clouds. The coexistence of ice and water is thermodynamically not stable and the particles will influence their respective growth by condensation. This effect is known as the Wegener–Bergeron–Findeisen process. In current models, the local interactions of the particles are neglected and they can only interact indirectly. This work proposes an approach to include local interactions and discusses some implications.
Qing Mu, Gerhard Lammel, Christian N. Gencarelli, Ian M. Hedgecock, Ying Chen, Petra Přibylová, Monique Teich, Yuxuan Zhang, Guangjie Zheng, Dominik van Pinxteren, Qiang Zhang, Hartmut Herrmann, Manabu Shiraiwa, Peter Spichtinger, Hang Su, Ulrich Pöschl, and Yafang Cheng
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Marcus Klingebiel, André Ehrlich, Fanny Finger, Timo Röschenthaler, Suad Jakirlić, Matthias Voigt, Stefan Müller, Rolf Maser, Manfred Wendisch, Peter Hoor, Peter Spichtinger, and Stephan Borrmann
Atmos. Meas. Tech., 10, 3485–3498, https://doi.org/10.5194/amt-10-3485-2017, https://doi.org/10.5194/amt-10-3485-2017, 2017
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Microphysical and radiation measurements were collected with the unique AIRcraft TOwed Sensor Shuttle (AIRTOSS) – Learjet tandem platform. It is a combination of a Learjet 35A research aircraft and an instrumented aerodynamic bird, which can be detached from and retracted back to the aircraft during flight.
AIRTOSS and Learjet are equipped with radiative, cloud microphysical, trace gas,
and meteorological instruments to study cirrus clouds.
Elisa Johanna Spreitzer, Manuel Patrik Marschalik, and Peter Spichtinger
Nonlin. Processes Geophys., 24, 307–328, https://doi.org/10.5194/npg-24-307-2017, https://doi.org/10.5194/npg-24-307-2017, 2017
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We developed a simple analytical model for describing subvisible cirrus clouds qualitatively. Using theory of dynamical systems we found two different states for the long-term behaviour of subvisible cirrus clouds, i.e. an attractor case (stable equilibrium point) and a limit cycle scenario. The transition between the states constitutes a Hopf bifurcation and is determined by environmental conditions such as vertical updraughts and temperature.
Thomas Berkemeier, Markus Ammann, Ulrich K. Krieger, Thomas Peter, Peter Spichtinger, Ulrich Pöschl, Manabu Shiraiwa, and Andrew J. Huisman
Atmos. Chem. Phys., 17, 8021–8029, https://doi.org/10.5194/acp-17-8021-2017, https://doi.org/10.5194/acp-17-8021-2017, 2017
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Kinetic process models are efficient tools used to unravel the mechanisms governing chemical and physical transformation in multiphase atmospheric chemistry. However, determination of kinetic parameters such as reaction rate or diffusion coefficients from multiple data sets is often difficult or ambiguous. This study presents a novel optimization algorithm and framework to determine these parameters in an automated fashion and to gain information about parameter uncertainty and uniqueness.
Ralf Weigel, Peter Spichtinger, Christoph Mahnke, Marcus Klingebiel, Armin Afchine, Andreas Petzold, Martina Krämer, Anja Costa, Sergej Molleker, Philipp Reutter, Miklós Szakáll, Max Port, Lucas Grulich, Tina Jurkat, Andreas Minikin, and Stephan Borrmann
Atmos. Meas. Tech., 9, 5135–5162, https://doi.org/10.5194/amt-9-5135-2016, https://doi.org/10.5194/amt-9-5135-2016, 2016
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The subject of our study concerns measurements with optical array probes (OAPs) on fast-flying aircraft such as the G550 (HALO or HIAPER). At up to Mach 0.7 the effect of air compression upstream of underwing-mounted instruments and particles' inertia need consideration for determining ambient particle concentrations. Compared to conventional practices the introduced correction procedure eliminates ambiguities and exhibits consistency over flight speeds between 50 and 250 m s−.
Fanny Finger, Frank Werner, Marcus Klingebiel, André Ehrlich, Evelyn Jäkel, Matthias Voigt, Stephan Borrmann, Peter Spichtinger, and Manfred Wendisch
Atmos. Chem. Phys., 16, 7681–7693, https://doi.org/10.5194/acp-16-7681-2016, https://doi.org/10.5194/acp-16-7681-2016, 2016
Short summary
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Solar spectra of optical layer properties of cirrus have been derived from the first truly collocated airborne radiation measurements using an aircraft and a towed sensor platform. The measured layer properties differ slightly due to horizontal cirrus inhomogeneities and the influence of low-level water clouds. Applying a 1-D radiative transfer model sensitivity studies were performed. It was found that if a low-level cloud is not considered, the solar cooling of the cirrus is strongly overestimated.
D. Chang, Y. Cheng, P. Reutter, J. Trentmann, S. M. Burrows, P. Spichtinger, S. Nordmann, M. O. Andreae, U. Pöschl, and H. Su
Atmos. Chem. Phys., 15, 10325–10348, https://doi.org/10.5194/acp-15-10325-2015, https://doi.org/10.5194/acp-15-10325-2015, 2015
A. Cirisan, B. P. Luo, I. Engel, F. G. Wienhold, M. Sprenger, U. K. Krieger, U. Weers, G. Romanens, G. Levrat, P. Jeannet, D. Ruffieux, R. Philipona, B. Calpini, P. Spichtinger, and T. Peter
Atmos. Chem. Phys., 14, 7341–7365, https://doi.org/10.5194/acp-14-7341-2014, https://doi.org/10.5194/acp-14-7341-2014, 2014
H. Joos, P. Spichtinger, P. Reutter, and F. Fusina
Atmos. Chem. Phys., 14, 6835–6852, https://doi.org/10.5194/acp-14-6835-2014, https://doi.org/10.5194/acp-14-6835-2014, 2014
P. Spichtinger and M. Krämer
Atmos. Chem. Phys., 13, 9801–9818, https://doi.org/10.5194/acp-13-9801-2013, https://doi.org/10.5194/acp-13-9801-2013, 2013
E. Kienast-Sjögren, P. Spichtinger, and K. Gierens
Atmos. Chem. Phys., 13, 9021–9037, https://doi.org/10.5194/acp-13-9021-2013, https://doi.org/10.5194/acp-13-9021-2013, 2013
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Aerosol has a large impact on climate. Using a lidar aerosol simulator ensures consistent comparisons between modeled and observed aerosol. We present a lidar aerosol simulator that applies a cloud masking and an aerosol detection threshold. We estimate the lidar signals that would be observed at 532 nm by the Cloud-Aerosol Lidar with Orthogonal Polarization overflying the atmosphere predicted by a climate model. Our comparison at the seasonal timescale shows a discrepancy in the Southern Ocean.
Michael S. Walters and David C. Wong
Geosci. Model Dev., 16, 1179–1190, https://doi.org/10.5194/gmd-16-1179-2023, https://doi.org/10.5194/gmd-16-1179-2023, 2023
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A typical numerical simulation that associates with a large amount of input and output data, applying popular compression software, gzip or bzip2, on data is one good way to mitigate data storage burden. This article proposes a simple technique to alter input, output, or input and output by keeping a specific number of significant digits in data and demonstrates an enhancement in compression efficiency on the altered data but maintains similar statistical performance of the numerical simulation.
Sylvain Mailler, Laurent Menut, Arineh Cholakian, and Romain Pennel
Geosci. Model Dev., 16, 1119–1127, https://doi.org/10.5194/gmd-16-1119-2023, https://doi.org/10.5194/gmd-16-1119-2023, 2023
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Large or even
giantparticles of mineral dust exist in the atmosphere but, so far, solving an non-linear equation was needed to calculate the speed at which they fall in the atmosphere. The model we present, AerSett v1.0 (AERosol SETTling version 1.0), provides a new and simple way of calculating their free-fall velocity in the atmosphere, which will be useful to anyone trying to understand and represent adequately the transport of giant dust particles by the wind.
Yen-Sen Lu, Garrett H. Good, and Hendrik Elbern
Geosci. Model Dev., 16, 1083–1104, https://doi.org/10.5194/gmd-16-1083-2023, https://doi.org/10.5194/gmd-16-1083-2023, 2023
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The Weather Forecasting and Research (WRF) model consists of many parameters and options that can be adapted to different conditions. This expansive sensitivity study uses a large-scale simulation system to determine the most suitable options for predicting cloud cover in Europe for deterministic and probabilistic weather predictions for day-ahead forecasting simulations.
Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan
Geosci. Model Dev., 16, 1039–1052, https://doi.org/10.5194/gmd-16-1039-2023, https://doi.org/10.5194/gmd-16-1039-2023, 2023
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When radionuclides are released into the atmosphere, the assessment of the consequences depends on the evaluation of the magnitude and temporal evolution of the release, which can be highly variable as in the case of Fukushima Daiichi.
Here, we propose Bayesian inverse modelling methods and the reversible-jump Markov chain Monte Carlo technique, which allows one to evaluate the temporal variability of the release and to integrate different types of information in the source reconstruction.
Phuc Thi Minh Ha, Yugo Kanaya, Fumikazu Taketani, Maria Dolores Andrés Hernández, Benjamin Schreiner, Klaus Pfeilsticker, and Kengo Sudo
Geosci. Model Dev., 16, 927–960, https://doi.org/10.5194/gmd-16-927-2023, https://doi.org/10.5194/gmd-16-927-2023, 2023
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HONO affects tropospheric oxidizing capacity; thus, it is implemented into the chemistry–climate model CHASER. The model substantially underpredicts daytime HONO, while nitrate photolysis on surfaces can supplement the daytime HONO budget. Current HONO chemistry predicts reductions of 20.4 % for global tropospheric NOx, 40–67 % for OH, and 30–45 % for O3 in the summer North Pacific. In contrast, OH and O3 winter levels in China are greatly enhanced.
Ryan Vella, Matthew Forrest, Jos Lelieveld, and Holger Tost
Geosci. Model Dev., 16, 885–906, https://doi.org/10.5194/gmd-16-885-2023, https://doi.org/10.5194/gmd-16-885-2023, 2023
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Biogenic volatile organic compounds (BVOCs) are released by vegetation and have a major impact on atmospheric chemistry and aerosol formation. Non-interacting vegetation constrains the majority of numerical models used to estimate global BVOC emissions, and thus, the effects of changing vegetation on emissions are not addressed. In this work, we replace the offline vegetation with dynamic vegetation states by linking a chemistry–climate model with a global dynamic vegetation model.
Danny McCulloch, Denis E. Sergeev, Nathan Mayne, Matthew Bate, James Manners, Ian Boutle, Benjamin Drummond, and Kristzian Kohary
Geosci. Model Dev., 16, 621–657, https://doi.org/10.5194/gmd-16-621-2023, https://doi.org/10.5194/gmd-16-621-2023, 2023
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We present results from the Met Office Unified Model (UM) to study the dry Martian climate. We describe our model set-up conditions and run two scenarios, with radiatively active/inactive dust. We compare both scenarios to results from an existing Mars climate model, the planetary climate model. We find good agreement in winds and air temperatures, but dust amounts differ between models. This study highlights the importance of using the UM for future Mars research.
Sam-Erik Walker, Sverre Solberg, Philipp Schneider, and Cristina Guerreiro
Geosci. Model Dev., 16, 573–595, https://doi.org/10.5194/gmd-16-573-2023, https://doi.org/10.5194/gmd-16-573-2023, 2023
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We have developed a statistical model for estimating trends in the daily air quality observations of NO2, O3, PM10 and PM2.5, adjusting for trends and short-term variations in meteorology. The model is general and may also be used for prediction purposes, including forecasting. It has been applied in a recent comprehensive study in Europe. Significant declines are shown for the pollutants from 2005 to 2019, mainly due to reductions in emissions not attributable to changes in meteorology.
Bianca Adler, James M. Wilczak, Jaymes Kenyon, Laura Bianco, Irina V. Djalalova, Joseph B. Olson, and David D. Turner
Geosci. Model Dev., 16, 597–619, https://doi.org/10.5194/gmd-16-597-2023, https://doi.org/10.5194/gmd-16-597-2023, 2023
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Rapid changes in wind speed make the integration of wind energy produced during persistent orographic cold-air pools difficult to integrate into the electrical grid. By evaluating three versions of NOAA’s High-Resolution Rapid Refresh model, we demonstrate how model developments targeted during the second Wind Forecast Improvement Project improve the forecast of a persistent cold-air pool event.
John Douros, Henk Eskes, Jos van Geffen, K. Folkert Boersma, Steven Compernolle, Gaia Pinardi, Anne-Marlene Blechschmidt, Vincent-Henri Peuch, Augustin Colette, and Pepijn Veefkind
Geosci. Model Dev., 16, 509–534, https://doi.org/10.5194/gmd-16-509-2023, https://doi.org/10.5194/gmd-16-509-2023, 2023
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We focus on the challenges associated with comparing atmospheric composition models with satellite products such as tropospheric NO2 columns. The aim is to highlight the methodological difficulties and propose sound ways of doing such comparisons. Building on the comparisons, a new satellite product is proposed and made available, which takes advantage of higher-resolution, regional atmospheric modelling to improve estimates of troposheric NO2 columns over Europe.
Catalina Poraicu, Jean-François Müller, Trissevgeni Stavrakou, Dominique Fonteyn, Frederik Tack, Felix Deutsch, Quentin Laffineur, Roeland Van Malderen, and Nele Veldeman
Geosci. Model Dev., 16, 479–508, https://doi.org/10.5194/gmd-16-479-2023, https://doi.org/10.5194/gmd-16-479-2023, 2023
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High-resolution WRF-Chem simulations are conducted over Antwerp, Belgium, in June 2019 and evaluated using meteorological data and in situ, airborne, and spaceborne NO2 measurements. An intercomparison of model, aircraft, and TROPOMI NO2 columns is conducted to characterize biases in versions 1.3.1 and 2.3.1 of the satellite product. A mass balance method is implemented to provide improved emissions for simulating NO2 distribution over the study area.
Daan R. Scheepens, Irene Schicker, Kateřina Hlaváčková-Schindler, and Claudia Plant
Geosci. Model Dev., 16, 251–270, https://doi.org/10.5194/gmd-16-251-2023, https://doi.org/10.5194/gmd-16-251-2023, 2023
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The production of wind energy is increasing rapidly and relies heavily on atmospheric conditions. To ensure power grid stability, accurate predictions of wind speed are needed, especially in the short range and for extreme wind speed ranges. In this work, we demonstrate the forecasting skills of a data-driven deep learning model with model adaptations to suit higher wind speed ranges. The resulting model can be applied to other data and parameters, too, to improve nowcasting predictions.
Peter J. M. Bosman and Maarten C. Krol
Geosci. Model Dev., 16, 47–74, https://doi.org/10.5194/gmd-16-47-2023, https://doi.org/10.5194/gmd-16-47-2023, 2023
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We describe an inverse modelling framework constructed around a simple model for the atmospheric boundary layer. This framework can be fed with various observation types to study the boundary layer and land–atmosphere exchange. With this framework, it is possible to estimate model parameters and the associated uncertainties. Some of these parameters are difficult to obtain directly by observations. An example application for a grassland in the Netherlands is included.
Sudipta Ghosh, Sagnik Dey, Sushant Das, Nicole Riemer, Graziano Giuliani, Dilip Ganguly, Chandra Venkataraman, Filippo Giorgi, Sachchida Nand Tripathi, Srikanthan Ramachandran, Thazhathakal Ayyappen Rajesh, Harish Gadhavi, and Atul Kumar Srivastava
Geosci. Model Dev., 16, 1–15, https://doi.org/10.5194/gmd-16-1-2023, https://doi.org/10.5194/gmd-16-1-2023, 2023
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Accurate representation of aerosols in climate models is critical for minimizing the uncertainty in climate projections. Here, we implement region-specific emission fluxes and a more accurate scheme for carbonaceous aerosol ageing processes in a regional climate model (RegCM4) and show that it improves model performance significantly against in situ, reanalysis, and satellite data over the Indian subcontinent. We recommend improving the model performance before using them for climate studies.
Chengzhu Zhang, Jean-Christophe Golaz, Ryan Forsyth, Tom Vo, Shaocheng Xie, Zeshawn Shaheen, Gerald L. Potter, Xylar S. Asay-Davis, Charles S. Zender, Wuyin Lin, Chih-Chieh Chen, Chris R. Terai, Salil Mahajan, Tian Zhou, Karthik Balaguru, Qi Tang, Cheng Tao, Yuying Zhang, Todd Emmenegger, Susannah Burrows, and Paul A. Ullrich
Geosci. Model Dev., 15, 9031–9056, https://doi.org/10.5194/gmd-15-9031-2022, https://doi.org/10.5194/gmd-15-9031-2022, 2022
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Earth system model (ESM) developers run automated analysis tools on data from candidate models to inform model development. This paper introduces a new Python package, E3SM Diags, that has been developed to support ESM development and use routinely in the development of DOE's Energy Exascale Earth System Model. This tool covers a set of essential diagnostics to evaluate the mean physical climate from simulations, as well as several process-oriented and phenomenon-based evaluation diagnostics.
Walter Hannah and Kyle Pressel
Geosci. Model Dev., 15, 8999–9013, https://doi.org/10.5194/gmd-15-8999-2022, https://doi.org/10.5194/gmd-15-8999-2022, 2022
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A multiscale modeling framework couples two models of the atmosphere that each cover different scale ranges. Traditionally, fluctuations in the small-scale model are not transported by the flow on the large-scale model grid, but this is hypothesized to be responsible for a persistent, unphysical checkerboard pattern. A method is presented to facilitate the transport of these small-scale fluctuations, analogous to how small-scale clouds and turbulence are transported in the real atmosphere.
Reimar Bauer, Jens-Uwe Grooß, Jörn Ungermann, May Bär, Markus Geldenhuys, and Lars Hoffmann
Geosci. Model Dev., 15, 8983–8997, https://doi.org/10.5194/gmd-15-8983-2022, https://doi.org/10.5194/gmd-15-8983-2022, 2022
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The Mission Support System (MSS) is an open source software package that has been used for planning flight tracks of scientific aircraft in multiple measurement campaigns during the last decade. Here, we describe the MSS software and its use during the SouthTRAC measurement campaign in 2019. As an example for how the MSS software is used in conjunction with many datasets, we describe the planning of a single flight probing orographic gravity waves propagating up into the lower mesosphere.
Zhizhao Wang, Florian Couvidat, and Karine Sartelet
Geosci. Model Dev., 15, 8957–8982, https://doi.org/10.5194/gmd-15-8957-2022, https://doi.org/10.5194/gmd-15-8957-2022, 2022
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Air quality models need to reliably predict secondary organic aerosols (SOAs) at a reasonable computational cost. Thus, we developed GENOA v1.0, a mechanism reduction algorithm that preserves the accuracy of detailed gas-phase chemical mechanisms for SOA formation, thereby improving the practical use of actual chemistry in SOA models. With GENOA, a near-explicit chemical scheme was reduced to 2 % of its original size and computational time, with an average error of less than 3 %.
Felix Kleinert, Lukas H. Leufen, Aurelia Lupascu, Tim Butler, and Martin G. Schultz
Geosci. Model Dev., 15, 8913–8930, https://doi.org/10.5194/gmd-15-8913-2022, https://doi.org/10.5194/gmd-15-8913-2022, 2022
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We examine the effects of spatially aggregated upstream information as input for a deep learning model forecasting near-surface ozone levels. Using aggregated data from one upstream sector (45°) improves the forecast by ~ 10 % for 4 prediction days. Three upstream sectors improve the forecasts by ~ 14 % on the first 2 d only. Our results serve as an orientation for other researchers or environmental agencies focusing on pointwise time-series predictions, for example, due to regulatory purposes.
Brian T. Dinkelacker, Pablo Garcia Rivera, Ioannis Kioutsioukis, Peter J. Adams, and Spyros N. Pandis
Geosci. Model Dev., 15, 8899–8912, https://doi.org/10.5194/gmd-15-8899-2022, https://doi.org/10.5194/gmd-15-8899-2022, 2022
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The performance of a chemical transport model in reproducing PM2.5 concentrations and composition was evaluated at the finest scale using measurements from regulatory sites as well as a network of low-cost monitors. Total PM2.5 mass is reproduced well by the model during the winter when compared to regulatory measurements, but in the summer PM2.5 is underpredicted, mainly due to difficulties in reproducing regional secondary organic aerosol levels.
Shizhang Wang and Xiaoshi Qiao
Geosci. Model Dev., 15, 8869–8897, https://doi.org/10.5194/gmd-15-8869-2022, https://doi.org/10.5194/gmd-15-8869-2022, 2022
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A local data assimilation scheme (Local DA v1.0) was proposed to leverage the advantage of hybrid covariance, multiscale localization, and parallel computation. The Local DA can perform covariance localization in model space, observation space, or both spaces. The Local DA that used the hybrid covariance and double-space localization produced the lowest analysis and forecast errors among all observing system simulation experiments.
Randall V. Martin, Sebastian D. Eastham, Liam Bindle, Elizabeth W. Lundgren, Thomas L. Clune, Christoph A. Keller, William Downs, Dandan Zhang, Robert A. Lucchesi, Melissa P. Sulprizio, Robert M. Yantosca, Yanshun Li, Lucas Estrada, William M. Putman, Benjamin M. Auer, Atanas L. Trayanov, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 15, 8731–8748, https://doi.org/10.5194/gmd-15-8731-2022, https://doi.org/10.5194/gmd-15-8731-2022, 2022
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Atmospheric chemistry models must be able to operate both online as components of Earth system models and offline as standalone models. The widely used GEOS-Chem model operates both online and offline, but the classic offline version is not suitable for massively parallel simulations. We describe a new generation of the offline high-performance GEOS-Chem (GCHP) that enables high-resolution simulations on thousands of cores, including on the cloud, with improved access, performance, and accuracy.
Daiwen Kang, Nicholas K. Heath, Robert C. Gilliam, Tanya L. Spero, and Jonathan E. Pleim
Geosci. Model Dev., 15, 8561–8579, https://doi.org/10.5194/gmd-15-8561-2022, https://doi.org/10.5194/gmd-15-8561-2022, 2022
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A lightning assimilation (LTA) technique implemented in the WRF model's Kain–Fritsch (KF) convective scheme is updated and applied to simulations from regional to hemispheric scales using observed lightning flashes from ground-based lightning detection networks. Different user-toggled options associated with the KF scheme on simulations with and without LTA are assessed. The model's performance is improved significantly by LTA, but it is sensitive to various factors.
Sujeong Lim, Hyeon-Ju Gim, Ebony Lee, Seungyeon Lee, Won Young Lee, Yong Hee Lee, Claudio Cassardo, and Seon Ki Park
Geosci. Model Dev., 15, 8541–8559, https://doi.org/10.5194/gmd-15-8541-2022, https://doi.org/10.5194/gmd-15-8541-2022, 2022
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The land surface model (LSM) contains various uncertain parameters, which are obtained by the empirical relations reflecting the specific local region and can be a source of uncertainty. To seek the optimal parameter values in the snow-related processes of the Noah LSM over South Korea, we have implemented an optimization algorithm, a micro-genetic algorithm using the observations. As a result, the optimized snow parameters improve snowfall prediction.
Haochen Sun, Jimmy C. H. Fung, Yiang Chen, Zhenning Li, Dehao Yuan, Wanying Chen, and Xingcheng Lu
Geosci. Model Dev., 15, 8439–8452, https://doi.org/10.5194/gmd-15-8439-2022, https://doi.org/10.5194/gmd-15-8439-2022, 2022
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This study developed a novel deep-learning layer, the broadcasting layer, to build an end-to-end LSTM-based deep-learning model for regional air pollution forecast. By combining the ground observation, WRF-CMAQ simulation, and the broadcasting LSTM deep-learning model, forecast accuracy has been significantly improved when compared to other methods. The broadcasting layer and its variants can also be applied in other research areas to supersede the traditional numerical interpolation methods.
Shunji Kotsuki, Takemasa Miyoshi, Keiichi Kondo, and Roland Potthast
Geosci. Model Dev., 15, 8325–8348, https://doi.org/10.5194/gmd-15-8325-2022, https://doi.org/10.5194/gmd-15-8325-2022, 2022
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Data assimilation plays an important part in numerical weather prediction (NWP) in terms of combining forecasted states and observations. While data assimilation methods in NWP usually assume the Gaussian error distribution, some variables in the atmosphere, such as precipitation, are known to have non-Gaussian error statistics. This study extended a widely used ensemble data assimilation algorithm to enable the assimilation of more non-Gaussian observations.
Martin Vojta, Andreas Plach, Rona L. Thompson, and Andreas Stohl
Geosci. Model Dev., 15, 8295–8323, https://doi.org/10.5194/gmd-15-8295-2022, https://doi.org/10.5194/gmd-15-8295-2022, 2022
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In light of recent global warming, we aim to improve methods for modeling greenhouse gas emissions in order to support the successful implementation of the Paris Agreement. In this study, we investigate certain aspects of a Bayesian inversion method that uses computer simulations and atmospheric observations to improve estimates of greenhouse gas emissions. We explore method limitations, discuss problems, and suggest improvements.
Longlei Li, Natalie M. Mahowald, Jasper F. Kok, Xiaohong Liu, Mingxuan Wu, Danny M. Leung, Douglas S. Hamilton, Louisa K. Emmons, Yue Huang, Neil Sexton, Jun Meng, and Jessica Wan
Geosci. Model Dev., 15, 8181–8219, https://doi.org/10.5194/gmd-15-8181-2022, https://doi.org/10.5194/gmd-15-8181-2022, 2022
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This study advances mineral dust parameterizations in the Community Atmospheric Model (CAM; version 6.1). Efforts include 1) incorporating a more physically based dust emission scheme; 2) updating the dry deposition scheme; and 3) revising the gravitational settling velocity to account for dust asphericity. Substantial improvements achieved with these updates can help accurately quantify dust–climate interactions using CAM, such as the dust-radiation and dust–cloud interactions.
Ruizi Shi and Fanghua Xu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-233, https://doi.org/10.5194/gmd-2022-233, 2022
Revised manuscript accepted for GMD
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Based on Gaussian Quadrature method, a fast parameterization scheme of sea spray-mediated heat flux is developed. Compared with the widely-used single-radius scheme, the new scheme shows a better agreement with the full spectrum integral of spray-flux. The new scheme is evaluated in a coupled modeling system, and the simulations of sea surface temperature, wind speed and wave height are improved. Thereby, the new scheme has a great potential to be used in coupled modeling systems.
Youhua Tang, Patrick C. Campbell, Pius Lee, Rick Saylor, Fanglin Yang, Barry Baker, Daniel Tong, Ariel Stein, Jianping Huang, Ho-Chun Huang, Li Pan, Jeff McQueen, Ivanka Stajner, Jose Tirado-Delgado, Youngsun Jung, Melissa Yang, Ilann Bourgeois, Jeff Peischl, Tom Ryerson, Donald Blake, Joshua Schwarz, Jose-Luis Jimenez, James Crawford, Glenn Diskin, Richard Moore, Johnathan Hair, Greg Huey, Andrew Rollins, Jack Dibb, and Xiaoyang Zhang
Geosci. Model Dev., 15, 7977–7999, https://doi.org/10.5194/gmd-15-7977-2022, https://doi.org/10.5194/gmd-15-7977-2022, 2022
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This paper compares two meteorological datasets for driving a regional air quality model: a regional meteorological model using WRF (WRF-CMAQ) and direct interpolation from an operational global model (GFS-CMAQ). In the comparison with surface measurements and aircraft data in summer 2019, these two methods show mixed performance depending on the corresponding meteorological settings. Direct interpolation is found to be a viable method to drive air quality models.
Robin N. Thor, Mariano Mertens, Sigrun Matthes, Mattia Righi, Johannes Hendricks, Sabine Brinkop, Phoebe Graf, Volker Grewe, Patrick Jöckel, and Steven Smith
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-250, https://doi.org/10.5194/gmd-2022-250, 2022
Revised manuscript accepted for GMD
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We report on an inconsistency in the latitudinal distribution of aviation emissions between two versions of a data product which is widely used by researchers. From the available documentation, we do not expect such an inconsistency. We run a chemistry-climate model to compute the effect of the inconsistency in emissions on atmospheric chemistry and radiation and find that the radiative forcing associated for aviation ozone is 7.6 % higher when using the less recent version of the data.
Zhiquan Liu, Chris Snyder, Jonathan J. Guerrette, Byoung-Joo Jung, Junmei Ban, Steven Vahl, Yali Wu, Yannick Trémolet, Thomas Auligné, Benjamin Ménétrier, Anna Shlyaeva, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 15, 7859–7878, https://doi.org/10.5194/gmd-15-7859-2022, https://doi.org/10.5194/gmd-15-7859-2022, 2022
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JEDI-MPAS 1.0.0, a new data assimilation (DA) system for the MPAS model, was publicly released for community use. This article describes JEDI-MPAS's implementation of the ensemble–variational DA technique and demonstrates its robustness and credible performance by incrementally adding three types of microwave radiances (clear-sky AMSU-A, all-sky AMSU-A, clear-sky MHS) to a non-radiance DA experiment. We intend to periodically release new and improved versions of JEDI-MPAS in upcoming years.
Li Fang, Jianbing Jin, Arjo Segers, Hai Xiang Lin, Mijie Pang, Cong Xiao, Tuo Deng, and Hong Liao
Geosci. Model Dev., 15, 7791–7807, https://doi.org/10.5194/gmd-15-7791-2022, https://doi.org/10.5194/gmd-15-7791-2022, 2022
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This study proposes a regional feature selection-based machine learning system to predict short-term air quality in China. The system has a tool that can figure out the importance of input data for better prediction. It provides large-scale air quality prediction that exhibits improved interpretability, fewer training costs, and higher accuracy compared with a standard machine learning system. It can act as an early warning for citizens and reduce exposure to PM2.5 and other air pollutants.
Stella E. I. Manavi and Spyros N. Pandis
Geosci. Model Dev., 15, 7731–7749, https://doi.org/10.5194/gmd-15-7731-2022, https://doi.org/10.5194/gmd-15-7731-2022, 2022
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The paper describes the first step towards the development of a simulation framework for the chemistry and secondary organic aerosol production of intermediate-volatility organic compounds (IVOCs). These compounds can be a significant source of organic particulate matter. Our approach treats IVOCs as lumped compounds that retain their chemical characteristics. Estimated IVOC emissions from road transport were a factor of 8 higher than emissions used in previous applications.
Peter Bräuer and Matthias Tesche
Geosci. Model Dev., 15, 7557–7572, https://doi.org/10.5194/gmd-15-7557-2022, https://doi.org/10.5194/gmd-15-7557-2022, 2022
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This paper presents a tool for (i) finding temporally and spatially resolved intersections between two- or three-dimensional geographical tracks (trajectories) and (ii) extracting of data in the vicinity of intersections to achieve the optimal combination of various data sets.
Benjamin Zanger, Jia Chen, Man Sun, and Florian Dietrich
Geosci. Model Dev., 15, 7533–7556, https://doi.org/10.5194/gmd-15-7533-2022, https://doi.org/10.5194/gmd-15-7533-2022, 2022
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Gaussian priors (GPs) used in least squares inversion do not reflect the true distributions of greenhouse gas emissions well. A method that does not rely on GPs is sparse reconstruction (SR). We show that necessary conditions for SR are satisfied for cities and that the application of a wavelet transform can further enhance sparsity. We apply the theory of compressed sensing to SR. Our results show that SR needs fewer measurements and is superior for assessing unknown emitters compared to GPs.
Paul Konopka, Mengchu Tao, Marc von Hobe, Lars Hoffmann, Corinna Kloss, Fabrizio Ravegnani, C. Michael Volk, Valentin Lauther, Andreas Zahn, Peter Hoor, and Felix Ploeger
Geosci. Model Dev., 15, 7471–7487, https://doi.org/10.5194/gmd-15-7471-2022, https://doi.org/10.5194/gmd-15-7471-2022, 2022
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Pure trajectory-based transport models driven by meteorology derived from reanalysis products (ERA5) take into account only the resolved, advective part of transport. That means neither mixing processes nor unresolved subgrid-scale advective processes like convection are included. The Chemical Lagrangian Model of the Stratosphere (CLaMS) includes these processes. We show that isentropic mixing dominates unresolved transport. The second most important transport process is unresolved convection.
Forwood Wiser, Bryan Place, Siddhartha Sen, Havala O. T. Pye, Benjamin Yang, Daniel M. Westervelt, Daven K. Henze, Arlene M. Fiore, and V. Faye McNeill
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-240, https://doi.org/10.5194/gmd-2022-240, 2022
Revised manuscript accepted for GMD
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We developed an automated method, AMORE, to simplify complex chemical mechanisms. We applied AMORE to the oxidation mechanism for isoprene, an abundant biogenic volatile organic compound. Using AMORE with minimal manual adjustments to the output, we created the AMORE-isoprene mechanism, with improved accuracy and similar size to other reduced isoprene mechanisms. AMORE-Isoprene improved the accuracy of EPA’s CMAQ model compared to observations.
Youngseob Kim, Lya Lugon, Alice Maison, Thibaud Sarica, Yelva Roustan, Myrto Valari, Yang Zhang, Michel André, and Karine Sartelet
Geosci. Model Dev., 15, 7371–7396, https://doi.org/10.5194/gmd-15-7371-2022, https://doi.org/10.5194/gmd-15-7371-2022, 2022
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This paper presents the latest version of the street-network model MUNICH, v2.0. The description of MUNICH v1.0, which models gas-phase pollutants in a street network, was published in GMD in 2018. Since then, major modifications have been made to MUNICH. The comprehensive aerosol model SSH-aerosol is now coupled to MUNICH to simulate primary and secondary aerosol concentrations. New parameterisations have also been introduced. Test cases are defined to illustrate the new model functionalities.
Yongbo Zhou, Yubao Liu, Zhaoyang Huo, and Yang Li
Geosci. Model Dev., 15, 7397–7420, https://doi.org/10.5194/gmd-15-7397-2022, https://doi.org/10.5194/gmd-15-7397-2022, 2022
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The study evaluates the performance of the Data Assimilation Research Testbed (DART), equipped with the recently added forward operator Radiative Transfer for TOVS (RTTOV), in assimilating FY-4A visible images into the Weather Research and Forecasting (WRF) model. The ability of the WRF-DART/RTTOV system to improve the forecasting skills for a tropical storm over East Asia and the Western Pacific is demonstrated in an Observing System Simulation Experiment framework.
Dánnell Quesada-Chacón, Klemens Barfus, and Christian Bernhofer
Geosci. Model Dev., 15, 7353–7370, https://doi.org/10.5194/gmd-15-7353-2022, https://doi.org/10.5194/gmd-15-7353-2022, 2022
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We improved the performance of past perfect prognosis statistical downscaling methods while achieving full model repeatability with GPU-calculated deep learning models using the TensorFlow, climate4R, and VALUE frameworks. We employed the ERA5 reanalysis as predictors and ReKIS (eastern Ore Mountains, Germany, 1 km resolution) as precipitation predictand, while incorporating modern deep learning architectures. The achieved repeatability is key to accomplish further milestones with deep learning.
Mike Bush, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Aravindakshan Jayakumar, Huw Lewis, Adrian Lock, Marion Mittermaier, Saji Mohandas, Rachel North, Aurore Porson, Belinda Roux, Stuart Webster, and Mark Weeks
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-209, https://doi.org/10.5194/gmd-2022-209, 2022
Revised manuscript accepted for GMD
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Building on the baseline of RAL1, the RAL2 science configuration is used for regional modelling around the UM Partnership and in operations at the Met Office. RAL2 has been tested in different parts of the world including Australia, India and the U.K. RAL2 increases medium and low cloud amounts in the mid-latitudes compared to RAL1, leading to improved cloud forecasts and a reduced diurnal cycle of screen temperature. There is also a reduction in the frequency of heavier precipitation rates.
Petri Clusius, Carlton Xavier, Lukas Pichelstorfer, Putian Zhou, Tinja Olenius, Pontus Roldin, and Michael Boy
Geosci. Model Dev., 15, 7257–7286, https://doi.org/10.5194/gmd-15-7257-2022, https://doi.org/10.5194/gmd-15-7257-2022, 2022
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Atmospheric chemistry and aerosol processes form a dynamic and sensitively balanced system, and solving problems regarding air quality or climate requires detailed modelling and coupling of the processes. The models involved are often very complex to use. We have addressed this problem with the new ARCA box model. It puts much of the current knowledge of the nano- and microscale aerosol dynamics and chemistry into usable software and has the potential to become a valuable tool in the community.
Adam Milsom, Amy Lees, Adam M. Squires, and Christian Pfrang
Geosci. Model Dev., 15, 7139–7151, https://doi.org/10.5194/gmd-15-7139-2022, https://doi.org/10.5194/gmd-15-7139-2022, 2022
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MultilayerPy is a Python-based framework facilitating the creation, running and optimisation of state-of-the-art kinetic multi-layer models of aerosol and film processes. Models can be fit to data with local and global optimisation algorithms along with a statistical sampling algorithm, which quantifies the uncertainty in optimised model parameters. This “modelling study in a box” enables more reproducible and reliable results, with model code and outputs produced in a human-readable way.
Johan F. de Haan, Ping Wang, Maarten Sneep, J. Pepijn Veefkind, and Piet Stammes
Geosci. Model Dev., 15, 7031–7050, https://doi.org/10.5194/gmd-15-7031-2022, https://doi.org/10.5194/gmd-15-7031-2022, 2022
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We present an overview of the DISAMAR radiative transfer code, highlighting the novel semi-analytical derivatives for the doubling–adding formulae and the new DISMAS technique for weak absorbers. DISAMAR includes forward simulations and retrievals for satellite spectral measurements from 270 to 2400 nm to determine instrument specifications for passive remote sensing. It has been used in various Sentinel-4/5P/5 projects and in the TROPOMI aerosol layer height and ozone profile products.
Ivette H. Banos, Will D. Mayfield, Guoqing Ge, Luiz F. Sapucci, Jacob R. Carley, and Louisa Nance
Geosci. Model Dev., 15, 6891–6917, https://doi.org/10.5194/gmd-15-6891-2022, https://doi.org/10.5194/gmd-15-6891-2022, 2022
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A prototype data assimilation system for NOAA’s next-generation rapidly updated, convection-allowing forecast system, or Rapid Refresh Forecast System (RRFS) v0.1, is tested and evaluated. The impact of using data assimilation with a convective storm case study is examined. Although the convection in RRFS tends to be overestimated in intensity and underestimated in extent, the use of data assimilation proves to be crucial to improve short-term forecasts of storms and precipitation.
Maria J. Chinita, Mikael Witte, Marcin J. Kurowski, Joao Teixeira, Kay Suselj, Georgios Matheou, and Peter Bogenschutz
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-162, https://doi.org/10.5194/gmd-2022-162, 2022
Revised manuscript accepted for GMD
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Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper, we introduce the first version of the unified turbulence and shallow convection parameterization named SHOC+MF developed to improve the representation of shallow cumulus clouds in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). Here, we also show promising preliminary results in a single-column model framework for two benchmark cases of shallow cumulus convection.
Andrew Geiss, Sam J. Silva, and Joseph C. Hardin
Geosci. Model Dev., 15, 6677–6694, https://doi.org/10.5194/gmd-15-6677-2022, https://doi.org/10.5194/gmd-15-6677-2022, 2022
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This work demonstrates the use of modern machine learning techniques to enhance the resolution of atmospheric chemistry simulations. We evaluate the schemes for an 8 x 10 increase in resolution and find that they perform substantially better than conventional methods. Methods are introduced to target machine learning methods towards this type of problem, most notably by ensuring they do not break known physical constraints.
Cited articles
Albring, T., Sagebaum, M., and Gauger, N. R.: Efficient Aerodynamic Design
using the Discrete Adjoint Method in SU2, AIAA 2016-3518, 2016. a
Asai, T.: A Numerical Study of the Air-Mass Transformation over the Japan Sea
in Winter, J. Meteorol. Soc. Jpn. Ser. II, 43,
1–15, 1965. a
Baumgartner, M.: Algorithmic Differentiation for Cloud Schemes using CoDiPack (v1.8.1), Zenodo, https://doi.org/10.5281/zenodo.3461483, 2019. a
Belikov, D. A., Maksyutov, S., Yaremchuk, A., Ganshin, A., Kaminski, T., Blessing, S., Sasakawa, M., Gomez-Pelaez, A. J., and Starchenko, A.: Adjoint of the global Eulerian–Lagrangian coupled atmospheric transport model (A-GELCA v1.0): development and validation, Geosci. Model Dev., 9, 749–764, https://doi.org/10.5194/gmd-9-749-2016, 2016. a
Bischof, C. H. and Eberhard, P.: Automatic differentiation of numerical
integration algorithms, Math. Comp., 68, 717–731,
https://doi.org/10.1090/S0025-5718-99-01027-3,
1999. a, b, c
Bischof, C. H., Khademi, P., Mauer, A., and Carle, A.: Adifor 2.0: automatic
differentiation of Fortran 77 programs, IEEE Comput. Sci.
Eng., 3, 18–32, https://doi.org/10.1109/99.537089, 1996a. a
Bischof, C. H., Pusch, G. D., and Knoesel, R.: Sensitivity analysis of the MM5
weather model using automatic differentiation, Comput. Phys., 10,
605–612, https://doi.org/10.1063/1.168585,
1996b. a
Blessing, S., Kaminski, T., Lunkeit, F., Matei, I., Giering, R., Köhl, A.,
Scholze, M., Herrmann, P., Fraedrich, K., and Stammer, D.: Testing
variational estimation of process parameters and initial conditions of an
earth system model, Tellus A, 66,
22606, https://doi.org/10.3402/tellusa.v66.22606,
2014. a
Chertock, A., Kurganov, A., Lukáčová-Medvid'ová, M.,
Spichtinger, P., and Wiebe, B.: Stochastic Galerkin Method for Cloud
Simulation, Mathematics of Climate and Weather Forecasting, 5, 65–106, https://doi.org/10.1515/mcwf-2019-0005, 2019. a, b
Cotton, W. R., Bryan, G. H., and van den Heever, S. C.: Storm and Cloud
Dynamics, Academic Press, 2nd Edn., 2010. a
Devenish, B. J., Bartello, P., Brenguier, J.-L., Collins, L. R., Grabowski,
W. W., IJzermans, R. H. A., Malinowski, S. P., Reeks, M. W., Vassilicos,
J. C., Wang, L.-P., and Warhaft, Z.: Droplet growth in warm turbulent clouds,
Q. J. Roy. Meteor. Soc., 138, 1401–1429,
https://doi.org/10.1002/qj.1897,
2012. a, b
Doms, G., Förstner, J., Heise, E., Herzog, H.-J., Mironow, D.,
Raschendorfer, M., Reinhardt, T., Ritter, B., Schrodin, R., Schulz, J.-P.,
and Vogel, G.: A Description of the Nonhydrostatic Regional COSMO Model, Part
II: Physical Parameterization, available at: http://www.cosmo-model.org/content/model/documentation/core/default.htm (last access: 23 October 2019),
2011. a
Elizondo, D., Cappelaere, B., and Faure, C.: Automatic versus manual model
differentiation to compute sensitivities and solve non-linear inverse
problems, Comput. Geosci., 28, 309–326,
https://doi.org/10.1016/S0098-3004(01)00048-6,
2002. a
Grabowski, W. W. and Wang, L.-P.: Growth of Cloud Droplets in a Turbulent
Environment, Annu. Rev. Fluid Mech., 45, 293–324,
https://doi.org/10.1146/annurev-fluid-011212-140750,
2013. a
Griewank, A., Kulshreshtha, K., and Walther, A.: On the numerical stability of
algorithmic differentiation, Computing, 94, 125–149,
https://doi.org/10.1007/s00607-011-0162-z,
2012. a
Grossmann, C. and Roos, H.-G.: Numerical Treatment of Partial Differential
Equations, Universitext, Springer-Verlag, Berlin Heidelberg, 2007. a
Hairer, E., Nørsett, S. P., and Wanner, G.: Solving Ordinary Differential
Equations I, vol. 8 of Springer Series in Computational Mathematics,
Springer-Verlag, Berlin Heidelberg, 2nd revised Edn.,
https://doi.org/10.1007/978-3-540-78862-1, 1993. a
Hascoët, 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. a
Hück, A., Bischof, C. H., and Utke, J.: Checking C++ codes for
compatibility with operator overloading, in: 2015 IEEE 15th International
Working Conference on Source Code Analysis and Manipulation (SCAM),
91–100, https://doi.org/10.1109/SCAM.2015.7335405, 2015. a
Igel, A. L. and van den Heever, S. C.: The Importance of the Shape of Cloud
Droplet Size Distributions in Shallow Cumulus Clouds. Part I: Bin
Microphysics Simulations, J. Atmos. Sci., 74, 249–258,
https://doi.org/10.1175/JAS-D-15-0382.1, 2017a. a
Igel, A. L. and van den Heever, S. C.: The Importance of the Shape of Cloud
Droplet Size Distributions in Shallow Cumulus Clouds. Part II: Bulk
Microphysics Simulations, J. Atmos. Sci., 74, 259–273,
https://doi.org/10.1175/JAS-D-15-0383.1, 2017b. a
Igel, A. L. and van den Heever, S. C.: The role of the gamma function shape parameter in determining differences between condensation rates in bin and bulk microphysics schemes, Atmos. Chem. Phys., 17, 4599–4609, https://doi.org/10.5194/acp-17-4599-2017, 2017c. a
Igel, A. L., Igel, M. R., and van den Heever, S. C.: Make It a Double?
Sobering Results from Simulations Using Single-Moment Microphysics Schemes,
J. Atmos. Sci., 72, 910–925,
https://doi.org/10.1175/JAS-D-14-0107.1,
2015. a
Kalnay, E.: Atmospheric modeling, data assimilation and predictability,
Cambridge University Press, 2003. a
Kaminski, T., Heimann, M., and Giering, R.: A coarse grid three-dimensional
global inverse model of the atmospheric transport: 1. Adjoint model and
Jacobian matrix, J. Geophys. Res.-Atmos., 104,
18535–18553, https://doi.org/10.1029/1999JD900147,
1999. a
Kessler, E.: On the Distribution and Continuity of Water Substance in
Atmospheric Circulations, American Meteorological Society, Boston,
MA, 1–84, https://doi.org/10.1007/978-1-935704-36-2_1,
1969. a, b
Khain, A. P., Ovtchinnikov, M., Pinsky, M., Pokrovsky, A., and Krugliak, H.:
Notes on the state-of-the-art numerical modeling of cloud microphysics,
Atmos. Res., 55, 159–224,
https://doi.org/10.1016/S0169-8095(00)00064-8,
2000. a
Khain, A. P., Beheng, K. D., Heymsfield, A. J., Korolev, A. V., Krichak, S. O.,
Levin, Z., Pinsky, M., Phillips, V., Prabhakaran, T., Teller, A., van den
Heever, S. C., and Yano, J.-I.: Representation of microphysical processes in
cloud-resolving models: Spectral (bin) microphysics versus bulk
parameterization, Rev. Geophys., 53, 247–322,
https://doi.org/10.1002/2014RG000468,
2015. a, b, c
Khairoutdinov, M. and Kogan, Y.: A New Cloud Physics Parameterization in a
Large-Eddy Simulation Model of Marine Stratocumulus, Mon. Weather Rev.,
128, 229–243, https://doi.org/10.1175/1520-0493(2000)128<0229:ANCPPI>2.0.CO;2,
2000. a
Kogan, Y. L. and Martin, W. J.: Parameterization of Bulk Condensation in
Numerical Cloud Models, J. Atmos. Sci., 51, 1728–1739,
https://doi.org/10.1175/1520-0469(1994)051<1728:POBCIN>2.0.CO;2,
1994. a, b
Köhler, H.: The nucleus in and the growth of hygroscopic droplets, T.
Faraday Soc., 32, 1152–1161, https://doi.org/10.1039/TF9363201152,
1936. a
Lamb, D. and Verlinde, J.: Physics and Chemistry of Clouds, Cambridge
University Press, Cambridge, 2011. a
Langlois, W. E.: A rapidly convergent procedure for computing large-scale
condensation in a dynamical weather model, Tellus, 25, 86–87,
https://doi.org/10.1111/j.2153-3490.1973.tb01598.x,
1973. a
Le Dimet, F.-X., Navon, I. M., and Daescu, D. N.: Second-Order Information in
Data Assimilation, Mon. Weather Rev., 130, 629–648,
https://doi.org/10.1175/1520-0493(2002)130<0629:SOIIDA>2.0.CO;2,
2002. a
Le Maître, O. and Knio, O. M.: Spectral Methods for Uncertainty
Quantification: With Applications to Computational Fluid Dynamics, Scientific
Computation, Springer Science & Business Media,
https://doi.org/10.1007/978-90-481-3520-2, 2010. a, b
Maxwell, J. C.: Diffusion, reprinted in: The Scientific Papers
of James Clerk Maxwell, edited by: Niven, W. D., 2, 625–645, 1877. a
McDonald, J. E.: The saturation adjustment in numerical modelling of fog,
J. Atmos. Sci., 20, 476–478, 1963. a
Neidinger, R. D.: Introduction to Automatic Differentiation and MATLAB
Object-Oriented Programming, SIAM Rev., 52, 545–563,
https://doi.org/10.1137/080743627, 2010. a
Orlanski, I.: A Rational Subdivision of Scales for Atmospheric Processes,
B. Am. Meteorol. Soc., 56, 527–530,
1975. a
Porz, N., Hanke, M., Baumgartner, M., and Spichtinger, P.: A model for warm
clouds with implicit droplet activation, avoiding saturation adjustment,
Mathematics of Climate and Weather Forecasting, 4, 50–78,
https://doi.org/10.1515/mcwf-2018-0003,
2018. a
Rauser, F., Riehme, J., Leppkes, K., Korn, P., and Naumann, U.: On the use of
discrete adjoints in goal error estimation for shallow water equations,
Procedia Comput. Sci., 1, 107–115,
https://doi.org/10.1016/j.procs.2010.04.013,
2010. a
Rogers, R. and Yau, M.: A Short Course in Cloud Physics, International Series
in Natural Philosophy, Butterworth-Heinemann, 3rd Edn., 1989. a
Rosemeier, J., Baumgartner, M., and Spichtinger, P.: Intercomparison of
Warm-Rain Bulk Microphysics Schemes using Asymptotics, Mathematics of Climate
and Weather Forecasting, 4, 104–124, https://doi.org/10.1515/mcwf-2018-0005,
2018.
a
Sagebaum, M., Albring, T., and Gauger, N. R.: High-Performance Derivative
Computations using CoDiPack, arXiv preprint arXiv:1709.07229,
2017a. a
Sagebaum, M., Özkaya, E., Gauger, N. R., Backhaus, J., Frey, C., Mann, S.,
and Nagel, M.: Efficient Algorithmic Differentiation Techniques for
Turbo-machinery Design, AIAA 2017-3998, https://doi.org/10.2514/6.2017-3998, 2017b. a
Sagebaum, M., Albring, T., Demidov, D., Möller, M., van der Weide, E., and Lam, M.: SciCompKL/CoDiPack: Version 1.8.1 (Version v1.8.1), Zenodo, https://doi.org/10.5281/zenodo.3460682, 2019. a
Sandu, A.: On the Properties of Runge-Kutta Discrete Adjoints, in:
Computational Science – ICCS 2006, edited by: Alexandrov, V. N., van Albada,
G. D., Sloot, P. M. A., and Dongarra, J., Springer Berlin
Heidelberg, Berlin, Heidelberg, 550–557, 2006. a
Sandu, A., Daescu, D. N., and Carmichael, G. R.: Direct and adjoint sensitivity
analysis of chemical kinetic systems with KPP: Part I – theory and software
tools, Atmos. Environ., 37, 5083–5096,
https://doi.org/10.1016/j.atmosenv.2003.08.019,
2003. a
Soong, S.-T. and Ogura, Y.: A Comparison Between Axisymmetric and
Slab-Symmetric Cumulus Cloud Models, J. Atmos. Sci., 30,
879–893, https://doi.org/10.1175/1520-0469(1973)030<0879:ACBAAS>2.0.CO;2,
1973. a
Sullivan, T. J.: Introduction to Uncertainty Quantification, vol. 63 of
Texts in Applied Mathematics, Springer-Verlag, Cham Heidelberg New York
Dordrecht London, https://doi.org/10.1007/978-3-319-23395-6, 2015. a, b
van Oldenborgh, G. J., Burgers, G., Venzke, S., Eckert, C., and Giering, R.:
Tracking Down the ENSO Delayed Oscillator with an Adjoint OGCM, Mon.
Weather Rev., 127, 1477–1496,
https://doi.org/10.1175/1520-0493(1999)127<1477:TDTEDO>2.0.CO;2,
1999. a
Walther, A.: Automatic differentiation of explicit Runge-Kutta methods for
optimal control, Comput. Optim. Appl., 36, 83–108,
https://doi.org/10.1007/s10589-006-0397-3,
2007. a, b
Xiao, Q., Kuo, Y.-H., Ma, Z., Huang, W., Huang, X.-Y., Zhang, X., Barker,
D. M., Michalakes, J., and Dudhia, J.: Application of an Adiabatic WRF
Adjoint to the Investigation of the May 2004 McMurdo, Antarctica, Severe Wind
Event, Mon. Weather Rev., 136, 3696–3713, https://doi.org/10.1175/2008MWR2235.1,
2008. a
Zhang, X., Huang, X.-Y., and Pan, N.: Development of the Upgraded Tangent
Linear and Adjoint of the Weather Research and Forecasting (WRF) Model,
J. Atmos. Ocean. Tech., 30, 1180–1188,
https://doi.org/10.1175/JTECH-D-12-00213.1,
2013. a
Short summary
Numerical models in atmospheric sciences need to include physical processes through parameterizations, which are not explicitly resolved, e.g., the formation of clouds. As a consequence, the parameterizations contain uncertain parameters. We suggest using the technique of algorithmic differentiation (AD) to identify the most uncertain parameters within parameterizations. In this study, we illustrate AD by analyzing a scheme for liquid clouds incorporated into a parcel model framework.
Numerical models in atmospheric sciences need to include physical processes through...
