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
| 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
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The nuclei onto which noctilucent clouds (NLC) form are largely unknown. We investigated the development of an inertia-based particle collector allowing for sampling NLC particles during a sounding rocket flight for off-line single particle physico-chemical analyzes. Computational fluid dynamics simulations (for Mach numbers 1.31 and 1.75) support the design and development process in reference to a basic mechanical concept of particle sampling and sample storage, which is also presented here.
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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.
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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.
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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
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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
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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.
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
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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.
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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.
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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Philipp Reutter and Peter Spichtinger
EGUsphere, https://doi.org/10.5194/egusphere-2025-2474, https://doi.org/10.5194/egusphere-2025-2474, 2025
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We present a new technique to determine the tropopause based on the gradient of relative humidity over ice. This reflects the character of the tropopause as a transport barrier very well, both in individual vertical profiles and in the long-term average. The results of the investigations using radio sondes are also supported by theoretical considerations.
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We investigate ice formation pathways in idealized convective clouds using a novel microphysics scheme that distinguishes between five ice classes each with their own unique formation mechanism. Ice crystals from rime splintering form the lowermost layer of ice crystals around the updraft core. The majority of ice crystals in the anvil of the convective cloud stems from frozen droplets. Ice stemming from homogeneous and deposition nucleation was only relevant in the overshoot.
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Revised manuscript accepted for GMD
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This study improves how we predict ice formation in clouds by accounting for variable ice sizes and different weather conditions. Using simulations, we developed a more accurate method that works efficiently, making it suitable for application in weather and climate prediction models. The new approach is numerically verified and provides precise predictions of ice formation events and reliable estimates of key parameters.
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In this work, the influence of humidity on the properties of the tropopause is studied. The tropopause is the interface between the troposphere and the stratosphere and represents a barrier for the transport of air masses between the troposphere and the stratosphere. We consider not only the tropopause itself, but also a layer around it called the tropopause inversion layer (TIL). It is shown that the moister the underlying atmosphere is, the more this layer acts as a barrier.
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
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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.
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
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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
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Short summary
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
Atmos. Chem. Phys., 20, 12569–12608, https://doi.org/10.5194/acp-20-12569-2020, https://doi.org/10.5194/acp-20-12569-2020, 2020
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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.
Andreas Petzold, Patrick Neis, Mihal Rütimann, Susanne Rohs, Florian Berkes, Herman G. J. Smit, Martina Krämer, Nicole Spelten, Peter Spichtinger, Philippe Nédélec, and Andreas Wahner
Atmos. Chem. Phys., 20, 8157–8179, https://doi.org/10.5194/acp-20-8157-2020, https://doi.org/10.5194/acp-20-8157-2020, 2020
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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
Short summary
Short summary
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
Atmos. Chem. Phys., 17, 12253–12267, https://doi.org/10.5194/acp-17-12253-2017, https://doi.org/10.5194/acp-17-12253-2017, 2017
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Polycyclic aromatic hydrocarbons (PAHs) are hazardous pollutants with the largest emissions in East Asia. The regional WRF-Chem-PAH model has been developed to reflect the state-of-the-art understanding of current PAHs studies with several new or updated features. It is able to reasonably well simulate the concentration levels and particulate mass fractions of PAHs near the sources and at a remote outflow region of East Asia, in high spatial and temporal resolutions.
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
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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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Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
The Atmospheric Potential Oxygen forward Model Intercomparison Project (APO-MIP1): Evaluating simulated atmospheric transport of air-sea gas exchange tracers and APO flux products
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Development of a High-Resolution Coupled SHiELD-MOM6 Model. Part I – Model Overview, Coupling Technique, and Validation in a Regional Setup
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
CoCoMET v1.0: A Unified Open-Source Toolkit for Atmospheric Object Tracking and Analysis
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Yongzhu Liu, Xiaoye Zhang, Wei Han, Chao Wang, Wenxing Jia, Deying Wang, Zhaorong Zhuang, and Xueshun Shen
Geosci. Model Dev., 18, 4855–4876, https://doi.org/10.5194/gmd-18-4855-2025, https://doi.org/10.5194/gmd-18-4855-2025, 2025
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In order to investigate the feedbacks of chemical data assimilation on meteorological forecasts, we developed a strongly coupled aerosol–meteorology four-dimensional variational (4D-Var) assimilation system, CMA-GFS-AERO 4D-Var, based on the framework of the incremental analysis scheme of the China Meteorological Administration Global Forecasting System (CMA-GFS) operational global numerical weather model. The results show that assimilating BC (black carbon) observations can generate analysis increments not only for BC but also for atmospheric variables.
Meghana Velagar, Christoph Keller, and J. Nathan Kutz
Geosci. Model Dev., 18, 4667–4684, https://doi.org/10.5194/gmd-18-4667-2025, https://doi.org/10.5194/gmd-18-4667-2025, 2025
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We develop the data-driven method of dynamic mode decomposition for producing a robust and stable surrogate reduced-order model of atmospheric chemistry dynamics. The model is computationally efficient, provides interpretable patterns of activity, and produces uncertainty quantification metrics. It is ideal for the forecasting of atmospheric chemistry in a computationally tractable manner.
Quanzhe Hou, Zhiqiu Gao, Zexia Duan, and Minghui Yu
Geosci. Model Dev., 18, 4625–4641, https://doi.org/10.5194/gmd-18-4625-2025, https://doi.org/10.5194/gmd-18-4625-2025, 2025
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This study evaluates various machine learning and statistical methods for interpolating turbulent heat flux data over the Tibetan Plateau. The Transformer model showed the best performance, leading to the development of the Transformer_CNN model, which combines global and local attention mechanisms. Results show that Transformer_CNN outperforms the other models and was successfully applied to interpolate heat flux data from 2007 to 2016.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart J. H. van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
Geosci. Model Dev., 18, 4571–4599, https://doi.org/10.5194/gmd-18-4571-2025, https://doi.org/10.5194/gmd-18-4571-2025, 2025
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We introduce a new simulation platform based on the Dutch Atmospheric Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in turbulent environments at a hectometer resolution. This model incorporates both anthropogenic emission inventories and online ecosystem fluxes. Simulation results for the main urban area in the Netherlands demonstrate the strong potential of DALES to improve CO2 emission modeling and to support mitigation strategies.
Bjarke T. E. Olsen, Andrea N. Hahmann, Nicolas G. Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
Geosci. Model Dev., 18, 4499–4533, https://doi.org/10.5194/gmd-18-4499-2025, https://doi.org/10.5194/gmd-18-4499-2025, 2025
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Low-level jets (LLJs) are strong winds in the lower atmosphere that are important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
Vishnu Nair, Anujah Mohanathan, Michael Herzog, David G. Macfarlane, and Duncan A. Robertson
Geosci. Model Dev., 18, 4417–4432, https://doi.org/10.5194/gmd-18-4417-2025, https://doi.org/10.5194/gmd-18-4417-2025, 2025
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A numerical model that simulates the measurement processes behind the ground-based radars used to detect volcanic ash clouds is introduced. Using weather radars to detect volcanic clouds is not ideal, as fine ash particles are smaller than raindrops and remain undetected. We evaluate the performance of weather radars to study ash clouds and to identify optimal frequencies that balance the trade-off between a higher return signal and the higher path attenuation that comes at these higher frequencies.
Daniel Garduno Ruiz, Colin Goldblatt, and Anne-Sofie Ahm
Geosci. Model Dev., 18, 4433–4454, https://doi.org/10.5194/gmd-18-4433-2025, https://doi.org/10.5194/gmd-18-4433-2025, 2025
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Photochemical models describe how the composition of the atmosphere changes due to chemical reactions, transport, and other processes. These models are useful for studying the composition of the Earth's and other planets' atmospheres. Understanding the results of these models can be difficult. Here, we build on previous work to develop open-source code that can identify the reaction chains (pathways) that produce the results of these models, facilitating the understanding of these results.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
Geosci. Model Dev., 18, 4353–4398, https://doi.org/10.5194/gmd-18-4353-2025, https://doi.org/10.5194/gmd-18-4353-2025, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line And Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, this model is valuable for airglow research and astronomical observatories.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
Geosci. Model Dev., 18, 4335–4352, https://doi.org/10.5194/gmd-18-4335-2025, https://doi.org/10.5194/gmd-18-4335-2025, 2025
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We introduce a new version of WAM2layers (Water Accounting Model – 2 layers), a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data had become a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent, reliable, and easier to maintain.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
Geosci. Model Dev., 18, 4231–4245, https://doi.org/10.5194/gmd-18-4231-2025, https://doi.org/10.5194/gmd-18-4231-2025, 2025
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We assess relevance and utility indicators by evaluating nine Copernicus Atmospheric Monitoring Service models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and winter–summer gradients reveal issues. O3 evaluation shows that seasonal gradients are useful. Overall, the indicators reveal model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev., 18, 4075–4101, https://doi.org/10.5194/gmd-18-4075-2025, https://doi.org/10.5194/gmd-18-4075-2025, 2025
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A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective-scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing–Tianjin–Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025, https://doi.org/10.5194/gmd-18-3985-2025, 2025
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SO2 from explosive volcanic eruptions reaching the stratosphere can oxidize and form sulfur aerosols, potentially persisting for several years. We developed a new submodel, Explosive Volcanic ERuptions (EVER), that seamlessly includes stratospheric volcanic SO2 emissions in global numerical simulations based on a novel standard historical model setup, successfully evaluated with satellite observations. Sensitivity studies on the Nabro eruption in 2011 evaluate different emission methods.
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025, https://doi.org/10.5194/gmd-18-3921-2025, 2025
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It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
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Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre- and sub-kilometre-scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Yuming Jin, Britton B. Stephens, Matthew C. Long, Naveen Chandra, Frédéric Chevallier, Joram J. D. Hooghiem, Ingrid T. Luijkx, Shamil Maksyutov, Eric J. Morgan, Yosuke Niwa, Prabir K. Patra, Christian Rödenbeck, and Jesse Vance
EGUsphere, https://doi.org/10.5194/egusphere-2025-1736, https://doi.org/10.5194/egusphere-2025-1736, 2025
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We carry out a comprehensive atmospheric transport model (ATM) intercomparison project. This project aims to evaluate errors in ATMs and three air-sea O2 exchange products by comparing model simulations with observations collected from surface stations, ships, and aircraft. We also present a model evaluation framework to independently quantify transport-related and flux-related biases that contribute to model-observation discrepancies in atmospheric tracer distributions.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Joseph Mouallem, Kun Gao, Brandon G. Reichl, Lauren Chilutti, Lucas Harris, Rusty Benson, Niki Zadeh, Jing Chen, Jan-Huey Chen, and Cheng Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1690, https://doi.org/10.5194/egusphere-2025-1690, 2025
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We introduce a new high-resolution model that couple the atmosphere and ocean to better simulate extreme weather events. It combines GFDL’s advanced atmospheric and ocean models with a powerful coupling system that allows robust and efficient two-way interactions. Simulations show the model accurately captures hurricane behavior and its impact on the ocean. It also runs efficiently on supercomputers. This model is a key step toward improving extreme weather forecast.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Travis Hahn, Hershel Weiner, Calvin Brooks, Jie Xi Li, Siddhant Gupta, and Dié Wang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1328, https://doi.org/10.5194/egusphere-2025-1328, 2025
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Understanding how clouds evolve is important for improving weather predictions, but existing tools for tracking cloud changes are complex and difficult to compare. To address this, we developed the Community Cloud Model Evaluation Toolkit (CoCoMET) that makes it easier to analyze clouds in both models and observations. By simplifying data processing, standardizing results, and introducing new analysis features, CoCoMET helps researchers better evaluate cloud behavior and improve models.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
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...
