Articles | Volume 16, issue 10
https://doi.org/10.5194/gmd-16-2957-2023
© Author(s) 2023. 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-16-2957-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
30 May 2023
Development and technical paper |
| 30 May 2023
| 30 May 2023
Assessing predicted cirrus ice properties between two deterministic ice formation parameterizations
Institute for Climate and Atmospheric Science, ETH Zurich, Zurich, Switzerland
David Neubauer
Institute for Climate and Atmospheric Science, ETH Zurich, Zurich, Switzerland
Ulrike Lohmann
CORRESPONDING AUTHOR
Institute for Climate and Atmospheric Science, ETH Zurich, Zurich, Switzerland
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Atmos. Chem. Phys., 23, 7673–7698, https://doi.org/10.5194/acp-23-7673-2023, https://doi.org/10.5194/acp-23-7673-2023, 2023
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This study details the first attempt with a GCM to simulate a fully prognostic aerosol species specifically for cirrus climate intervention. The new approach is in line with the real-world delivery mechanism via aircraft. However, to achieve an appreciable signal from seeding, smaller particles were needed, and their mass emissions needed to be scaled by at least a factor of 100. These biases contributed to either overseeding or small and insignificant effects in response to seeding cirrus.
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The proposed geoengineering method, cirrus cloud thinning, was evaluated using a more physically based microphysics scheme coupled to a more realistic approach for calculating ice cloud fractions in the ECHAM-HAM GCM. Sensitivity tests reveal that using the new ice cloud fraction approach and increasing the critical ice saturation ratio for ice nucleation on seeding particles reduces warming from overseeding. However, this geoengineering method is unlikely to be feasible on a global scale.
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Geosci. Model Dev., 16, 5093–5112, https://doi.org/10.5194/gmd-16-5093-2023, https://doi.org/10.5194/gmd-16-5093-2023, 2023
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An algorithm to track tropical cyclones in model simulation data has been developed. The algorithm uses many combinations of varying parameter thresholds to detect weaker phases of tropical cyclones while still being resilient to false positives. It is shown that the algorithm performs well and adequately represents the tropical cyclone activity of the underlying simulation data. The impact of false positives on overall tropical cyclone activity is shown to be insignificant.
Anna J. Miller, Fabiola Ramelli, Christopher Fuchs, Nadja Omanovic, Robert Spirig, Huiying Zhang, Ulrike Lohmann, Zamin A. Kanji, and Jan Henneberger
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-157, https://doi.org/10.5194/amt-2023-157, 2023
Revised manuscript under review for AMT
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We present a method for aerosol and cloud research using two uncrewed aerial vehicles (UAVs). The UAVs have a propeller heating mechanism that allows flights in icing conditions, which has so far been a limitation for cloud research with UAVs. One UAV burns seeding flares, producing a plume of particles that causes ice formation in supercooled clouds. The second UAV measures aerosol size distributions and is used for measuring the seeding plume or for characterizing the boundary layer.
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Atmos. Chem. Phys., 23, 7673–7698, https://doi.org/10.5194/acp-23-7673-2023, https://doi.org/10.5194/acp-23-7673-2023, 2023
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George Jordan, James Haywood, Florent Malavelle, Ying Chen, Amy Peace, Eliza Duncan, Daniel G. Partridge, Paul Kim, Duncan Watson-Parris, Toshihiko Takemura, David Neubauer, Gunnar Myhre, Ragnhild Skeie, and Anton Laakso
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Simulations allowing ice particles to collide with one another producing more ice particles represented surface observations of ice particles accurately. An increase in ice particles formed through collisions was related to sharp changes in the wind direction and speed with height. Changes in wind speed and direction can therefore cause more enhanced collisions between ice particles and alter how fast and how much precipitation forms. Simulations were conducted with the atmospheric model COSMO.
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Atmos. Chem. Phys., 22, 11455–11484, https://doi.org/10.5194/acp-22-11455-2022, https://doi.org/10.5194/acp-22-11455-2022, 2022
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Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
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Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
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Ice formation and its evolution in mixed-phase clouds are still uncertain. We evaluate the lidar retrieval of ice-nucleating particle concentration in dust-dominated and continental air masses over the Swiss Alps with in situ observations. A calibration factor to improve the retrieval from continental air masses is proposed. Ice multiplication factors are obtained with a new method utilizing remote sensing. Our results indicate that secondary ice production occurs at temperatures down to −30 °C.
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Atmos. Chem. Phys., 22, 4737–4762, https://doi.org/10.5194/acp-22-4737-2022, https://doi.org/10.5194/acp-22-4737-2022, 2022
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Cloud microphysical processes shape cloud properties and are therefore important to represent in climate models. Their parameterization has grown more complex, making the model results more difficult to interpret. Using sensitivity analysis we test how the global aerosol–climate model ECHAM-HAM reacts to changes to these parameterizations. The model is sensitive to the parameterization of ice crystal autoconversion but not to, e.g., self-collection, suggesting that it may be simplified.
Jörg Wieder, Claudia Mignani, Mario Schär, Lucie Roth, Michael Sprenger, Jan Henneberger, Ulrike Lohmann, Cyril Brunner, and Zamin A. Kanji
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We investigate the variation in ice-nucleating particles (INPs) relevant for primary ice formation in mixed-phased clouds over the Alps based on simultaneous in situ observations at a mountaintop and a nearby high valley (1060 m height difference). In most cases, advection from the surrounding lower regions was responsible for changes in INP concentration, causing a diurnal cycle at the mountaintop. Our study underlines the importance of the planetary boundary layer as an INP reserve.
Zane Dedekind, Annika Lauber, Sylvaine Ferrachat, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 15115–15134, https://doi.org/10.5194/acp-21-15115-2021, https://doi.org/10.5194/acp-21-15115-2021, 2021
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The RACLETS campaign combined cloud and snow research to improve the understanding of precipitation formation in clouds. A numerical weather prediction model, COSMO, was used to assess the importance of ice crystal enhancement by ice–ice collisions for cloud properties. We found that the number of ice crystals increased by 1 to 3 orders of magnitude when ice–ice collisions were permitted to occur, reducing localized regions of high precipitation and, thereby, improving the model performance.
Paolo Pelucchi, David Neubauer, and Ulrike Lohmann
Geosci. Model Dev., 14, 5413–5434, https://doi.org/10.5194/gmd-14-5413-2021, https://doi.org/10.5194/gmd-14-5413-2021, 2021
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Stratocumulus are thin clouds whose cloud cover is underestimated in climate models partly due to overly low vertical resolution. We develop a scheme that locally refines the vertical grid based on a physical constraint for the cloud top. Global simulations show that the scheme, implemented only in the radiation routine, can increase stratocumulus cloud cover. However, this effect is poorly propagated to the simulated cloud cover. The scheme's limitations and possible ways forward are discussed.
Paraskevi Georgakaki, Aikaterini Bougiatioti, Jörg Wieder, Claudia Mignani, Fabiola Ramelli, Zamin A. Kanji, Jan Henneberger, Maxime Hervo, Alexis Berne, Ulrike Lohmann, and Athanasios Nenes
Atmos. Chem. Phys., 21, 10993–11012, https://doi.org/10.5194/acp-21-10993-2021, https://doi.org/10.5194/acp-21-10993-2021, 2021
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Aerosol and cloud observations coupled with a droplet activation parameterization was used to investigate the aerosol–cloud droplet link in alpine mixed-phase clouds. Predicted droplet number, Nd, agrees with observations and never exceeds a characteristic “limiting droplet number”, Ndlim, which depends solely on σw. Nd becomes velocity limited when it is within 50 % of Ndlim. Identifying when dynamical changes control Nd variability is central for understanding aerosol–cloud interactions.
Fabiola Ramelli, Jan Henneberger, Robert O. David, Johannes Bühl, Martin Radenz, Patric Seifert, Jörg Wieder, Annika Lauber, Julie T. Pasquier, Ronny Engelmann, Claudia Mignani, Maxime Hervo, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 6681–6706, https://doi.org/10.5194/acp-21-6681-2021, https://doi.org/10.5194/acp-21-6681-2021, 2021
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Orographic mixed-phase clouds are an important source of precipitation, but the ice formation processes within them remain uncertain. Here we investigate the origin of ice crystals in a mixed-phase cloud in the Swiss Alps using aerosol and cloud data from in situ and remote sensing observations. We found that ice formation primarily occurs in cloud top generating cells. Our results indicate that secondary ice processes are active in the feeder region, which can enhance orographic precipitation.
Fabiola Ramelli, Jan Henneberger, Robert O. David, Annika Lauber, Julie T. Pasquier, Jörg Wieder, Johannes Bühl, Patric Seifert, Ronny Engelmann, Maxime Hervo, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 5151–5172, https://doi.org/10.5194/acp-21-5151-2021, https://doi.org/10.5194/acp-21-5151-2021, 2021
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Interactions between dynamics, microphysics and orography can enhance precipitation. Yet the exact role of these interactions is still uncertain. Here we investigate the role of low-level blocking and turbulence for precipitation by combining remote sensing and in situ observations. The observations show that blocked flow can induce the formation of feeder clouds and that turbulence can enhance hydrometeor growth, demonstrating the importance of local flow effects for orographic precipitation.
Ulrike Proske, Verena Bessenbacher, Zane Dedekind, Ulrike Lohmann, and David Neubauer
Atmos. Chem. Phys., 21, 5195–5216, https://doi.org/10.5194/acp-21-5195-2021, https://doi.org/10.5194/acp-21-5195-2021, 2021
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Ice crystals falling out of one cloud can initiate freezing in a second cloud below. We estimate the occurrence frequency of this natural cloud seeding over Switzerland from satellite data and sublimation calculations. We find that such situations with an ice cloud above another cloud are frequent and that the falling crystals survive the fall between two clouds in a significant number of cases, suggesting that natural cloud seeding is an important phenomenon over Switzerland.
Annika Lauber, Jan Henneberger, Claudia Mignani, Fabiola Ramelli, Julie T. Pasquier, Jörg Wieder, Maxime Hervo, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 3855–3870, https://doi.org/10.5194/acp-21-3855-2021, https://doi.org/10.5194/acp-21-3855-2021, 2021
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An accurate prediction of the ice crystal number concentration (ICNC) is important to determine the radiation budget, lifetime, and precipitation formation of clouds. Even though secondary-ice processes can increase the ICNC by several orders of magnitude, they are poorly constrained and lack a well-founded quantification. During measurements on a mountain slope, a high ICNC of small ice crystals was observed just below 0 °C, attributed to a secondary-ice process and parametrized in this study.
Jonas Gliß, Augustin Mortier, Michael Schulz, Elisabeth Andrews, Yves Balkanski, Susanne E. Bauer, Anna M. K. Benedictow, Huisheng Bian, Ramiro Checa-Garcia, Mian Chin, Paul Ginoux, Jan J. Griesfeller, Andreas Heckel, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Paolo Laj, Philippe Le Sager, Marianne Tronstad Lund, Cathrine Lund Myhre, Hitoshi Matsui, Gunnar Myhre, David Neubauer, Twan van Noije, Peter North, Dirk J. L. Olivié, Samuel Rémy, Larisa Sogacheva, Toshihiko Takemura, Kostas Tsigaridis, and Svetlana G. Tsyro
Atmos. Chem. Phys., 21, 87–128, https://doi.org/10.5194/acp-21-87-2021, https://doi.org/10.5194/acp-21-87-2021, 2021
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Simulated aerosol optical properties as well as the aerosol life cycle are investigated for 14 global models participating in the AeroCom initiative. Considerable diversity is found in the simulated aerosol species emissions and lifetimes, also resulting in a large diversity in the simulated aerosol mass, composition, and optical properties. A comparison with observations suggests that, on average, current models underestimate the direct effect of aerosol on the atmosphere radiation budget.
Steven T. Turnock, Robert J. Allen, Martin Andrews, Susanne E. Bauer, Makoto Deushi, Louisa Emmons, Peter Good, Larry Horowitz, Jasmin G. John, Martine Michou, Pierre Nabat, Vaishali Naik, David Neubauer, Fiona M. O'Connor, Dirk Olivié, Naga Oshima, Michael Schulz, Alistair Sellar, Sungbo Shim, Toshihiko Takemura, Simone Tilmes, Kostas Tsigaridis, Tongwen Wu, and Jie Zhang
Atmos. Chem. Phys., 20, 14547–14579, https://doi.org/10.5194/acp-20-14547-2020, https://doi.org/10.5194/acp-20-14547-2020, 2020
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A first assessment is made of the historical and future changes in air pollutants from models participating in the 6th Coupled Model Intercomparison Project (CMIP6). Substantial benefits to future air quality can be achieved in future scenarios that implement measures to mitigate climate and involve reductions in air pollutant emissions, particularly methane. However, important differences are shown between models in the future regional projection of air pollutants under the same scenario.
Augustin Mortier, Jonas Gliß, Michael Schulz, Wenche Aas, Elisabeth Andrews, Huisheng Bian, Mian Chin, Paul Ginoux, Jenny Hand, Brent Holben, Hua Zhang, Zak Kipling, Alf Kirkevåg, Paolo Laj, Thibault Lurton, Gunnar Myhre, David Neubauer, Dirk Olivié, Knut von Salzen, Ragnhild Bieltvedt Skeie, Toshihiko Takemura, and Simone Tilmes
Atmos. Chem. Phys., 20, 13355–13378, https://doi.org/10.5194/acp-20-13355-2020, https://doi.org/10.5194/acp-20-13355-2020, 2020
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We present a multiparameter analysis of the aerosol trends over the last 2 decades in the different regions of the world. In most of the regions, ground-based observations show a decrease in aerosol content in both the total atmospheric column and at the surface. The use of climate models, assessed against these observations, reveals however an increase in the total aerosol load, which is not seen with the sole use of observation due to partial coverage in space and time.
Robert J. Allen, Steven Turnock, Pierre Nabat, David Neubauer, Ulrike Lohmann, Dirk Olivié, Naga Oshima, Martine Michou, Tongwen Wu, Jie Zhang, Toshihiko Takemura, Michael Schulz, Kostas Tsigaridis, Susanne E. Bauer, Louisa Emmons, Larry Horowitz, Vaishali Naik, Twan van Noije, Tommi Bergman, Jean-Francois Lamarque, Prodromos Zanis, Ina Tegen, Daniel M. Westervelt, Philippe Le Sager, Peter Good, Sungbo Shim, Fiona O'Connor, Dimitris Akritidis, Aristeidis K. Georgoulias, Makoto Deushi, Lori T. Sentman, Jasmin G. John, Shinichiro Fujimori, and William J. Collins
Atmos. Chem. Phys., 20, 9641–9663, https://doi.org/10.5194/acp-20-9641-2020, https://doi.org/10.5194/acp-20-9641-2020, 2020
Mattia Righi, Johannes Hendricks, Ulrike Lohmann, Christof Gerhard Beer, Valerian Hahn, Bernd Heinold, Romy Heller, Martina Krämer, Michael Ponater, Christian Rolf, Ina Tegen, and Christiane Voigt
Geosci. Model Dev., 13, 1635–1661, https://doi.org/10.5194/gmd-13-1635-2020, https://doi.org/10.5194/gmd-13-1635-2020, 2020
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A new cloud microphysical scheme is implemented in the global EMAC-MADE3 aerosol model and evaluated. The new scheme features a detailed parameterization for aerosol-driven ice formation in cirrus clouds, accounting for the competition between homogeneous and heterogeneous ice formation processes. The comparison against satellite data and in situ measurements shows that the model performance is in line with similar global coupled models featuring ice cloud parameterizations.
Fabiola Ramelli, Alexander Beck, Jan Henneberger, and Ulrike Lohmann
Atmos. Meas. Tech., 13, 925–939, https://doi.org/10.5194/amt-13-925-2020, https://doi.org/10.5194/amt-13-925-2020, 2020
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Boundary layer clouds are influenced by many physical and dynamical processes, making accurate forecasting difficult. Here we present a new measurement platform on a tethered balloon to measure cloud microphysical and meteorological profiles. The unique combination of holography and balloon-borne observations allows high-resolution measurements in a well-defined volume. Field measurements in stratus clouds over the Swiss Plateau revealed unique microphysical signatures in the cloud structure.
Giulia Saponaro, Moa K. Sporre, David Neubauer, Harri Kokkola, Pekka Kolmonen, Larisa Sogacheva, Antti Arola, Gerrit de Leeuw, Inger H. H. Karset, Ari Laaksonen, and Ulrike Lohmann
Atmos. Chem. Phys., 20, 1607–1626, https://doi.org/10.5194/acp-20-1607-2020, https://doi.org/10.5194/acp-20-1607-2020, 2020
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The understanding of cloud processes is based on the quality of the representation of cloud properties. We compared cloud parameters from three models with satellite observations. We report on the performance of each data source, highlighting strengths and deficiencies, which should be considered when deriving the effect of aerosols on cloud properties.
Edward Gryspeerdt, Johannes Mülmenstädt, Andrew Gettelman, Florent F. Malavelle, Hugh Morrison, David Neubauer, Daniel G. Partridge, Philip Stier, Toshihiko Takemura, Hailong Wang, Minghuai Wang, and Kai Zhang
Atmos. Chem. Phys., 20, 613–623, https://doi.org/10.5194/acp-20-613-2020, https://doi.org/10.5194/acp-20-613-2020, 2020
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Aerosol radiative forcing is a key uncertainty in our understanding of the human forcing of the climate, with much of this uncertainty coming from aerosol impacts on clouds. Observation-based estimates of the radiative forcing are typically smaller than those from global models, but it is not clear if they are more reliable. This work shows how the forcing components in global climate models can be identified, highlighting similarities between the two methods and areas for future investigation.
Franz Friebel, Prem Lobo, David Neubauer, Ulrike Lohmann, Saskia Drossaart van Dusseldorp, Evelyn Mühlhofer, and Amewu A. Mensah
Atmos. Chem. Phys., 19, 15545–15567, https://doi.org/10.5194/acp-19-15545-2019, https://doi.org/10.5194/acp-19-15545-2019, 2019
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We investigated the change in cloud droplet activity of size-selected soot particles after being exposed to atmospheric levels of ozone over the course of 12 h. For this, we operated a 3 m3 aerosol chamber in continuous-flow mode. The results were fed into a climate model (ECHAM-HAM). We found that the oxidation of soot particles with ozone is a significant source of cloud condensation nuclei in the atmosphere.
Anina Gilgen, Stiig Wilkenskjeld, Jed O. Kaplan, Thomas Kühn, and Ulrike Lohmann
Clim. Past, 15, 1885–1911, https://doi.org/10.5194/cp-15-1885-2019, https://doi.org/10.5194/cp-15-1885-2019, 2019
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Using the global aerosol–climate model ECHAM-HAM-SALSA, the effect of humans on European climate in the Roman Empire was quantified. Both land use and novel estimates of anthropogenic aerosol emissions were considered. We conducted simulations with fixed sea-surface temperatures to gain a first impression about the anthropogenic impact. While land use effects induced a regional warming for one of the reconstructions, aerosol emissions led to a cooling associated with aerosol–cloud interactions.
André Welti, Ulrike Lohmann, and Zamin A. Kanji
Atmos. Chem. Phys., 19, 10901–10918, https://doi.org/10.5194/acp-19-10901-2019, https://doi.org/10.5194/acp-19-10901-2019, 2019
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The ice nucleation ability of singly immersed feldspar particles in suspended water droplets relevant for ice crystal formation under mixed-phase cloud conditions is presented. The effects of particle size, crystal structure, trace metal and mineralogical composition are discussed by testing up to five different diameters in the submicron range and nine different feldspar samples at conditions relevant for ice nucleation in mixed-phase clouds.
David Neubauer, Sylvaine Ferrachat, Colombe Siegenthaler-Le Drian, Philip Stier, Daniel G. Partridge, Ina Tegen, Isabelle Bey, Tanja Stanelle, Harri Kokkola, and Ulrike Lohmann
Geosci. Model Dev., 12, 3609–3639, https://doi.org/10.5194/gmd-12-3609-2019, https://doi.org/10.5194/gmd-12-3609-2019, 2019
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The global aerosol–climate model ECHAM6.3–HAM2.3 as well as the previous model versions ECHAM5.5–HAM2.0 and ECHAM6.1–HAM2.2 are evaluated. The simulation of clouds has improved in ECHAM6.3–HAM2.3. This has an impact on effective radiative forcing due to aerosol–radiation and aerosol–cloud interactions and equilibrium climate sensitivity, which are weaker in ECHAM6.3–HAM2.3 than in the previous model versions.
Gesa K. Eirund, Anna Possner, and Ulrike Lohmann
Atmos. Chem. Phys., 19, 9847–9864, https://doi.org/10.5194/acp-19-9847-2019, https://doi.org/10.5194/acp-19-9847-2019, 2019
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Low-level mixed-phase cloud (MPC) properties can be highly affected by the ambient aerosol concentration, especially in pristine environments like the Arctic. By employing high-resolution model simulations we investigate the response of a MPC over an open ocean and a sea ice surface to aerosol perturbations. While we find a strong initial sensitivity to changes in aerosol concentration in both cloud regimes, the magnitude as well as the long-term cloud response depends on the surface condition.
Remo Dietlicher, David Neubauer, and Ulrike Lohmann
Atmos. Chem. Phys., 19, 9061–9080, https://doi.org/10.5194/acp-19-9061-2019, https://doi.org/10.5194/acp-19-9061-2019, 2019
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Ice crystals in clouds cover a spectrum of shapes and sizes. We show the first results of a consistent representation of the cloud ice spectrum in the climate model ECHAM6-HAM2. The simulated cloud fields are linked to their sources by new diagnostics. We find that only a small fraction of ice clouds is initiated by freezing of cloud droplets in the mixed-phase temperature regime while most ice forms at temperatures colder than −35 °C.
George S. Fanourgakis, Maria Kanakidou, Athanasios Nenes, Susanne E. Bauer, Tommi Bergman, Ken S. Carslaw, Alf Grini, Douglas S. Hamilton, Jill S. Johnson, Vlassis A. Karydis, Alf Kirkevåg, John K. Kodros, Ulrike Lohmann, Gan Luo, Risto Makkonen, Hitoshi Matsui, David Neubauer, Jeffrey R. Pierce, Julia Schmale, Philip Stier, Kostas Tsigaridis, Twan van Noije, Hailong Wang, Duncan Watson-Parris, Daniel M. Westervelt, Yang Yang, Masaru Yoshioka, Nikos Daskalakis, Stefano Decesari, Martin Gysel-Beer, Nikos Kalivitis, Xiaohong Liu, Natalie M. Mahowald, Stelios Myriokefalitakis, Roland Schrödner, Maria Sfakianaki, Alexandra P. Tsimpidi, Mingxuan Wu, and Fangqun Yu
Atmos. Chem. Phys., 19, 8591–8617, https://doi.org/10.5194/acp-19-8591-2019, https://doi.org/10.5194/acp-19-8591-2019, 2019
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Effects of aerosols on clouds are important for climate studies but are among the largest uncertainties in climate projections. This study evaluates the skill of global models to simulate aerosol, cloud condensation nuclei (CCN) and cloud droplet number concentrations (CDNCs). Model results show reduced spread in CDNC compared to CCN due to the negative correlation between the sensitivities of CDNC to aerosol number concentration (air pollution) and updraft velocity (atmospheric dynamics).
Stephanie Fiedler, Stefan Kinne, Wan Ting Katty Huang, Petri Räisänen, Declan O'Donnell, Nicolas Bellouin, Philip Stier, Joonas Merikanto, Twan van Noije, Risto Makkonen, and Ulrike Lohmann
Atmos. Chem. Phys., 19, 6821–6841, https://doi.org/10.5194/acp-19-6821-2019, https://doi.org/10.5194/acp-19-6821-2019, 2019
Ina Tegen, David Neubauer, Sylvaine Ferrachat, Colombe Siegenthaler-Le Drian, Isabelle Bey, Nick Schutgens, Philip Stier, Duncan Watson-Parris, Tanja Stanelle, Hauke Schmidt, Sebastian Rast, Harri Kokkola, Martin Schultz, Sabine Schroeder, Nikos Daskalakis, Stefan Barthel, Bernd Heinold, and Ulrike Lohmann
Geosci. Model Dev., 12, 1643–1677, https://doi.org/10.5194/gmd-12-1643-2019, https://doi.org/10.5194/gmd-12-1643-2019, 2019
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We describe a new version of the aerosol–climate model ECHAM–HAM and show tests of the model performance by comparing different aspects of the aerosol distribution with different datasets. The updated version of HAM contains improved descriptions of aerosol processes, including updated emission fields and cloud processes. While there are regional deviations between the model and observations, the model performs well overall.
Yvonne Boose, Philipp Baloh, Michael Plötze, Johannes Ofner, Hinrich Grothe, Berko Sierau, Ulrike Lohmann, and Zamin A. Kanji
Atmos. Chem. Phys., 19, 1059–1076, https://doi.org/10.5194/acp-19-1059-2019, https://doi.org/10.5194/acp-19-1059-2019, 2019
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The role non-mineral components play in the freezing behavior of atmospheric desert dust is not well known. In this study, we use chemical imaging methods to investigate this for airborne and surface-collected desert dust samples. We find that in most cases the ice nucleation behavior is determined by the dust mineralogical composition. However, volatile organic material can coat active sites and decrease the dust ice nucleation ability, while biological particles can significantly increase it.
Emma Järvinen, Olivier Jourdan, David Neubauer, Bin Yao, Chao Liu, Meinrat O. Andreae, Ulrike Lohmann, Manfred Wendisch, Greg M. McFarquhar, Thomas Leisner, and Martin Schnaiter
Atmos. Chem. Phys., 18, 15767–15781, https://doi.org/10.5194/acp-18-15767-2018, https://doi.org/10.5194/acp-18-15767-2018, 2018
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Using light diffraction it is possible to detect microscopic features within ice particles that have not yet been fully characterized. Here, this technique was applied in airborne measurements, where it was found that majority of atmospheric ice particles have features that significantly change the way ice particles interact with solar light. The microscopic features make ice-containing clouds more reflective than previously thought, which could have consequences for predicting our climate.
Harri Kokkola, Thomas Kühn, Anton Laakso, Tommi Bergman, Kari E. J. Lehtinen, Tero Mielonen, Antti Arola, Scarlet Stadtler, Hannele Korhonen, Sylvaine Ferrachat, Ulrike Lohmann, David Neubauer, Ina Tegen, Colombe Siegenthaler-Le Drian, Martin G. Schultz, Isabelle Bey, Philip Stier, Nikos Daskalakis, Colette L. Heald, and Sami Romakkaniemi
Geosci. Model Dev., 11, 3833–3863, https://doi.org/10.5194/gmd-11-3833-2018, https://doi.org/10.5194/gmd-11-3833-2018, 2018
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In this paper we present a global aerosol–chemistry–climate model with the focus on its representation for atmospheric aerosol particles. In the model, aerosols are simulated using the aerosol module SALSA2.0, which in this paper is compared to satellite, ground, and aircraft-based observations of the properties of atmospheric aerosol. Based on this study, the model simulated aerosol properties compare well with the observations.
Fabian Mahrt, Claudia Marcolli, Robert O. David, Philippe Grönquist, Eszter J. Barthazy Meier, Ulrike Lohmann, and Zamin A. Kanji
Atmos. Chem. Phys., 18, 13363–13392, https://doi.org/10.5194/acp-18-13363-2018, https://doi.org/10.5194/acp-18-13363-2018, 2018
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The ice nucleation ability of different soot particles in the cirrus and mixed-phase cloud temperature regime is presented. The impact of aerosol particle size, particle morphology, organic matter and hydrophilicity on ice nucleation is examined. We propose ice nucleation proceeds via a pore condensation freezing mechanism for soot particles with the necessary physicochemical properties that nucleated ice well below water saturation.
Anina Gilgen, Carole Adolf, Sandra O. Brugger, Luisa Ickes, Margit Schwikowski, Jacqueline F. N. van Leeuwen, Willy Tinner, and Ulrike Lohmann
Atmos. Chem. Phys., 18, 11813–11829, https://doi.org/10.5194/acp-18-11813-2018, https://doi.org/10.5194/acp-18-11813-2018, 2018
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Microscopic charcoal particles are fire-specific tracers, which are presently the primary source for reconstructing past fire activity. In this study, we implement microscopic charcoal particles into a global aerosol–climate model to better understand the transport of charcoal on a large scale. We find that the model captures a significant portion of the spatial variability but fails to reproduce the extreme variability observed in the charcoal data.
Wan Ting Katty Huang, Luisa Ickes, Ina Tegen, Matteo Rinaldi, Darius Ceburnis, and Ulrike Lohmann
Atmos. Chem. Phys., 18, 11423–11445, https://doi.org/10.5194/acp-18-11423-2018, https://doi.org/10.5194/acp-18-11423-2018, 2018
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In this study, we investigated the potential impact on clouds and climate by organic particles emitted from the ocean surface, using a global climate model. These particles have previously been found to promote ice crystal formation, which may alter the properties of clouds. Our study, however, found a weak global impact by these particles, which brings into question their relative importance and points to the need for further verification with other models and at more regional scales.
Robin G. Stevens, Katharina Loewe, Christopher Dearden, Antonios Dimitrelos, Anna Possner, Gesa K. Eirund, Tomi Raatikainen, Adrian A. Hill, Benjamin J. Shipway, Jonathan Wilkinson, Sami Romakkaniemi, Juha Tonttila, Ari Laaksonen, Hannele Korhonen, Paul Connolly, Ulrike Lohmann, Corinna Hoose, Annica M. L. Ekman, Ken S. Carslaw, and Paul R. Field
Atmos. Chem. Phys., 18, 11041–11071, https://doi.org/10.5194/acp-18-11041-2018, https://doi.org/10.5194/acp-18-11041-2018, 2018
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We perform a model intercomparison of summertime high Arctic clouds. Observed concentrations of aerosol particles necessary for cloud formation fell to extremely low values, coincident with a transition from cloudy to nearly cloud-free conditions. Previous analyses have suggested that at these low concentrations, the radiative properties of the clouds are determined primarily by these particle concentrations. The model results strongly support this hypothesis.
Anina Gilgen, Wan Ting Katty Huang, Luisa Ickes, David Neubauer, and Ulrike Lohmann
Atmos. Chem. Phys., 18, 10521–10555, https://doi.org/10.5194/acp-18-10521-2018, https://doi.org/10.5194/acp-18-10521-2018, 2018
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Aerosol emissions in Arctic summer and autumn are expected to increase in the future because of sea ice retreat. Using a global aerosol–climate model, we quantify the impact of increased aerosol emissions from the ocean and from Arctic shipping in the year 2050. The influence on radiation of both aerosols and clouds is analysed. Mainly driven by changes in surface albedo, the cooling effect of marine aerosols and clouds will increase. Future ship emissions might have a small net cooling effect.
Alexander Beck, Jan Henneberger, Jacob P. Fugal, Robert O. David, Larissa Lacher, and Ulrike Lohmann
Atmos. Chem. Phys., 18, 8909–8927, https://doi.org/10.5194/acp-18-8909-2018, https://doi.org/10.5194/acp-18-8909-2018, 2018
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This study assesses the impact of surface processes (e.g. blowing snow) on in situ cloud observations at Sonnblick Observatory. Vertical profiles of ice crystal number concentrations (ICNCs) above a snow-covered surface were observed up to a height of 10 m. The ICNC near the ground is at least a factor of 2 larger than at 10 m. Therefore, in situ measurements of ICNCs at mountain-top research stations close to the surface are strongly influenced by surface processes and overestimate the ICNC.
Ulrike Lohmann and David Neubauer
Atmos. Chem. Phys., 18, 8807–8828, https://doi.org/10.5194/acp-18-8807-2018, https://doi.org/10.5194/acp-18-8807-2018, 2018
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The climate is warming, at the current rate so much so that the 2 ºC target is likely to be exceeded. Uncertainty remains as to when the 2 ºC of warming will be reached. One factor contributing to this uncertainty is how clouds change in the warmer climate. While previously most emphasis was placed on how low clouds change in the warmer climate, here we investigate the importance of mixed-phase and ice clouds.
Martin G. Schultz, Scarlet Stadtler, Sabine Schröder, Domenico Taraborrelli, Bruno Franco, Jonathan Krefting, Alexandra Henrot, Sylvaine Ferrachat, Ulrike Lohmann, David Neubauer, Colombe Siegenthaler-Le Drian, Sebastian Wahl, Harri Kokkola, Thomas Kühn, Sebastian Rast, Hauke Schmidt, Philip Stier, Doug Kinnison, Geoffrey S. Tyndall, John J. Orlando, and Catherine Wespes
Geosci. Model Dev., 11, 1695–1723, https://doi.org/10.5194/gmd-11-1695-2018, https://doi.org/10.5194/gmd-11-1695-2018, 2018
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The chemistry–climate model ECHAM-HAMMOZ contains a detailed representation of tropospheric and stratospheric reactive chemistry and state-of-the-art parameterizations of aerosols. It thus allows for detailed investigations of chemical processes in the climate system. Evaluation of the model with various observational data yields good results, but the model has a tendency to produce too much OH in the tropics. This highlights the important interplay between atmospheric chemistry and dynamics.
Remo Dietlicher, David Neubauer, and Ulrike Lohmann
Geosci. Model Dev., 11, 1557–1576, https://doi.org/10.5194/gmd-11-1557-2018, https://doi.org/10.5194/gmd-11-1557-2018, 2018
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A new cloud scheme was implemented in the aerosol–climate model ECHAM6-HAM2. Unlike traditional schemes, it does not categorize ice particles by in-cloud and precipitation types but uses a single category with prognostic bulk particle properties. The new scheme is not only conceptually simpler but also closer to first principles as it does not rely on weakly constrained conversion rates between predefined categories and resolves falling ice by local sub-time-stepping.
Larissa Lacher, Ulrike Lohmann, Yvonne Boose, Assaf Zipori, Erik Herrmann, Nicolas Bukowiecki, Martin Steinbacher, and Zamin A. Kanji
Atmos. Chem. Phys., 17, 15199–15224, https://doi.org/10.5194/acp-17-15199-2017, https://doi.org/10.5194/acp-17-15199-2017, 2017
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We characterize the new Horizontal Ice Nucleation Chamber HINC to measure ambient ice nucleating particle concentrations at mixed‐phase cloud conditions. Results from winter measurements at the High Altitude Research Station Jungfraujoch compare well to previous measurements. We find increased ice nucleating particle concentrations during the influence of Saharan dust events and marine events, which highlights the importance of these species on ice nucleation in the free troposphere.
David Neubauer, Matthew W. Christensen, Caroline A. Poulsen, and Ulrike Lohmann
Atmos. Chem. Phys., 17, 13165–13185, https://doi.org/10.5194/acp-17-13165-2017, https://doi.org/10.5194/acp-17-13165-2017, 2017
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When aerosol particles take up water their number may seem to be increased optically. However if aerosol particles are removed by precipitation (formation) their numbers will decrease. We applied methods to account for such effects in model and satellite data to analyse the change in cloud properties by changes in aerosol particle number. The agreement of model and satellite data improves when these effects are accounted for.
Matthew W. Christensen, David Neubauer, Caroline A. Poulsen, Gareth E. Thomas, Gregory R. McGarragh, Adam C. Povey, Simon R. Proud, and Roy G. Grainger
Atmos. Chem. Phys., 17, 13151–13164, https://doi.org/10.5194/acp-17-13151-2017, https://doi.org/10.5194/acp-17-13151-2017, 2017
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The cloud-aerosol pairing algorithm (CAPA) is developed to quantify the impact of near-cloud aerosol retrievals on satellite-based aerosol–cloud statistical relationships. We find that previous satellite-based radiative forcing estimates of aerosol–cloud interactions represented in key climate reports are likely exaggerated by up to 50 % due to including retrieval artefacts in the aerosols located near clouds. It is demonstrated that this retrieval artefact can be corrected in current products.
Hendrik Andersen, Jan Cermak, Julia Fuchs, Reto Knutti, and Ulrike Lohmann
Atmos. Chem. Phys., 17, 9535–9546, https://doi.org/10.5194/acp-17-9535-2017, https://doi.org/10.5194/acp-17-9535-2017, 2017
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Aerosol-cloud interactions continue to contribute large uncertainties to our climate system understanding. In this study, we use near-global satellite and reanalysis data sets to predict marine liquid-water clouds by means of artificial neural networks. We show that on the system scale, lower-tropospheric stability and boundary layer height are the main determinants of liquid-water clouds. Aerosols show the expected impact on clouds but are less relevant than some meteorological factors.
Franziska Glassmeier, Anna Possner, Bernhard Vogel, Heike Vogel, and Ulrike Lohmann
Atmos. Chem. Phys., 17, 8651–8680, https://doi.org/10.5194/acp-17-8651-2017, https://doi.org/10.5194/acp-17-8651-2017, 2017
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We compare two chemistry and aerosol schemes – one designed for air-quality, the other for climate applications. For distribution, composition and radiative properties, the choice of aerosol types and processes turns out to be more important than their implementation. For aerosol–cloud interactions, we find cloud processes, in particular ice formation, to be the main obstacle to our understanding.
Anahita Amiri-Farahani, Robert J. Allen, David Neubauer, and Ulrike Lohmann
Atmos. Chem. Phys., 17, 6305–6322, https://doi.org/10.5194/acp-17-6305-2017, https://doi.org/10.5194/acp-17-6305-2017, 2017
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We use observations from 2004 to 2012 to obtain estimates of the aerosol–cloud radiative effect, including its uncertainty, for dust aerosol influencing Atlantic marine stratocumulus clouds (MSc) off the coast of north Africa. Saharan dust modifies MSc in a way that acts to cool the planet. There is a strong seasonal variation, with the aerosol–cloud radiative effect switching from significantly negative during the boreal summer to weakly positive during boreal winter.
Hanna Joos, Erica Madonna, Kasja Witlox, Sylvaine Ferrachat, Heini Wernli, and Ulrike Lohmann
Atmos. Chem. Phys., 17, 6243–6255, https://doi.org/10.5194/acp-17-6243-2017, https://doi.org/10.5194/acp-17-6243-2017, 2017
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The influence of pollution on the precipitation formation in warm conveyor belts (WCBs), the most rising air streams in low-pressure systems is investigated. We investigate in detail the cloud properties and resulting precipitation along these rising airstreams which are simulated with a global climate model. Overall, no big impact of aerosols on precipitation can be seen, however, when comparing the most polluted/cleanest WCBs, a suppression of precipitation by aerosols is observed.
Blaž Gasparini, Steffen Münch, Laure Poncet, Monika Feldmann, and Ulrike Lohmann
Atmos. Chem. Phys., 17, 4871–4885, https://doi.org/10.5194/acp-17-4871-2017, https://doi.org/10.5194/acp-17-4871-2017, 2017
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Cirrus clouds have, unlike other cloud types, a warming impact on climate. Decreasing their frequency therefore leads to a cooling effect. Cirrus ice crystals grow larger when formed on solid aerosols, inducing a shorter cloud lifetime.
We compare simplified simulations of stripping cirrus out of the sky with simulations of seeding by aerosol injections. While we find the surface climate responses to be similar, the changes in clouds and cloud properties differ significantly.
Alexander Beck, Jan Henneberger, Sarah Schöpfer, Jacob Fugal, and Ulrike Lohmann
Atmos. Meas. Tech., 10, 459–476, https://doi.org/10.5194/amt-10-459-2017, https://doi.org/10.5194/amt-10-459-2017, 2017
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In situ observations of cloud properties in complex alpine terrain are commonly conducted at mountain-top research stations and limited to single-point measurements. The HoloGondel platform overcomes this limitation by using a cable car to obtain vertical profiles of the microphysical and meteorological cloud parameters. In this work example measurements of the vertical profiles observed in a liquid cloud and a mixed-phase cloud at the Eggishorn in the Swiss Alps are presented.
Luisa Ickes, André Welti, and Ulrike Lohmann
Atmos. Chem. Phys., 17, 1713–1739, https://doi.org/10.5194/acp-17-1713-2017, https://doi.org/10.5194/acp-17-1713-2017, 2017
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The goal of this study is to find a parameterization scheme for general circulation models to describe immersion freezing with the ability to shift and adjust the slope of the freezing curve compared to homogeneous freezing to match experimental data. We investigated how accurate different formulations of classical nucleation theory reproduce measured immersion freezing curves for different mineral dust types.
Yvonne Boose, André Welti, James Atkinson, Fabiola Ramelli, Anja Danielczok, Heinz G. Bingemer, Michael Plötze, Berko Sierau, Zamin A. Kanji, and Ulrike Lohmann
Atmos. Chem. Phys., 16, 15075–15095, https://doi.org/10.5194/acp-16-15075-2016, https://doi.org/10.5194/acp-16-15075-2016, 2016
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We compare the immersion freezing behavior of four airborne to 11 surface-collected dust samples to investigate the role of different minerals for atmospheric ice nucleation on desert dust. We find that present K-feldspars dominate at T > 253 K, while quartz does at colder temperatures, and surface-collected dust samples are not necessarily representative for airborne dust. For improved ice cloud prediction, modeling of quartz and feldspar emission and transport are key.
Yvonne Boose, Berko Sierau, M. Isabel García, Sergio Rodríguez, Andrés Alastuey, Claudia Linke, Martin Schnaiter, Piotr Kupiszewski, Zamin A. Kanji, and Ulrike Lohmann
Atmos. Chem. Phys., 16, 9067–9087, https://doi.org/10.5194/acp-16-9067-2016, https://doi.org/10.5194/acp-16-9067-2016, 2016
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Mineral dust is known to be among the most prevalent ice-nucleating particles (INPs) in the atmosphere, playing a crucial role for ice cloud formation. We present 2 months of ground-based in situ measurements of INP concentrations in the free troposphere close to the largest global dust source, the Sahara. We find that some atmospheric processes such as mixing with biological particles and ammonium increase the dust INP ability. This is important when predicting INPs based on emissions.
Baban Nagare, Claudia Marcolli, André Welti, Olaf Stetzer, and Ulrike Lohmann
Atmos. Chem. Phys., 16, 8899–8914, https://doi.org/10.5194/acp-16-8899-2016, https://doi.org/10.5194/acp-16-8899-2016, 2016
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The relative importance of contact freezing and immersion freezing at mixed-phase cloud temperatures is the subject of debate. We performed experiments using continuous-flow diffusion chambers to compare the freezing efficiency of ice-nucleating particles for both these nucleation modes. Silver iodide, kaolinite and Arizona Test Dust were used as ice-nucleating particles. We could not confirm the dominance of contact freezing over immersion freezing for our experimental conditions.
Claudia Marcolli, Baban Nagare, André Welti, and Ulrike Lohmann
Atmos. Chem. Phys., 16, 8915–8937, https://doi.org/10.5194/acp-16-8915-2016, https://doi.org/10.5194/acp-16-8915-2016, 2016
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Silver iodide is one of the best-investigated ice nuclei. It has relevance for the atmosphere since it is used for glaciogenic cloud seeding. Nevertheless, many open questions remain. This paper gives an overview of silver iodide as an ice nucleus and tries to identify the factors that influence the ice nucleation ability of silver iodide.
Sarvesh Garimella, Thomas Bjerring Kristensen, Karolina Ignatius, Andre Welti, Jens Voigtländer, Gourihar R. Kulkarni, Frank Sagan, Gregory Lee Kok, James Dorsey, Leonid Nichman, Daniel Alexander Rothenberg, Michael Rösch, Amélie Catharina Ruth Kirchgäßner, Russell Ladkin, Heike Wex, Theodore W. Wilson, Luis Antonio Ladino, Jon P. D. Abbatt, Olaf Stetzer, Ulrike Lohmann, Frank Stratmann, and Daniel James Cziczo
Atmos. Meas. Tech., 9, 2781–2795, https://doi.org/10.5194/amt-9-2781-2016, https://doi.org/10.5194/amt-9-2781-2016, 2016
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The SPectrometer for Ice Nuclei (SPIN) is a commercially available ice nuclei counter manufactured by Droplet Measurement Technologies in Boulder, CO. This study characterizes the SPIN chamber, reporting data from laboratory measurements and quantifying uncertainties. Overall, we report that the SPIN is able to reproduce previous CFDC ice nucleation measurements.
Shipeng Zhang, Minghuai Wang, Steven J. Ghan, Aijun Ding, Hailong Wang, Kai Zhang, David Neubauer, Ulrike Lohmann, Sylvaine Ferrachat, Toshihiko Takeamura, Andrew Gettelman, Hugh Morrison, Yunha Lee, Drew T. Shindell, Daniel G. Partridge, Philip Stier, Zak Kipling, and Congbin Fu
Atmos. Chem. Phys., 16, 2765–2783, https://doi.org/10.5194/acp-16-2765-2016, https://doi.org/10.5194/acp-16-2765-2016, 2016
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The variation of aerosol indirect effects (AIE) in several climate models is investigated across different dynamical regimes. Regimes with strong large-scale ascent are shown to be as important as stratocumulus regimes in studying AIE. AIE over regions with high monthly large-scale surface precipitation rate contributes the most to the total aerosol indirect forcing. These results point to the need to reduce the uncertainty in AIE in different dynamical regimes.
B. Nagare, C. Marcolli, O. Stetzer, and U. Lohmann
Atmos. Chem. Phys., 15, 13759–13776, https://doi.org/10.5194/acp-15-13759-2015, https://doi.org/10.5194/acp-15-13759-2015, 2015
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We determined collision efficiencies of cloud droplets with aerosol particles experimentally and found that they were around 1 order of magnitude higher than theoretical formulations that include Brownian diffusion, impaction, interception, thermophoretic, diffusiophoretic and electric forces. This is most probably due to uncertainties and inaccuracies in the theoretical formulations of thermophoretic and diffusiophoretic processes.
M. Paramonov, V.-M. Kerminen, M. Gysel, P. P. Aalto, M. O. Andreae, E. Asmi, U. Baltensperger, A. Bougiatioti, D. Brus, G. P. Frank, N. Good, S. S. Gunthe, L. Hao, M. Irwin, A. Jaatinen, Z. Jurányi, S. M. King, A. Kortelainen, A. Kristensson, H. Lihavainen, M. Kulmala, U. Lohmann, S. T. Martin, G. McFiggans, N. Mihalopoulos, A. Nenes, C. D. O'Dowd, J. Ovadnevaite, T. Petäjä, U. Pöschl, G. C. Roberts, D. Rose, B. Svenningsson, E. Swietlicki, E. Weingartner, J. Whitehead, A. Wiedensohler, C. Wittbom, and B. Sierau
Atmos. Chem. Phys., 15, 12211–12229, https://doi.org/10.5194/acp-15-12211-2015, https://doi.org/10.5194/acp-15-12211-2015, 2015
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The research paper presents the first comprehensive overview of field measurements with the CCN Counter performed at a large number of locations around the world within the EUCAARI framework. The paper sheds light on the CCN number concentrations and activated fractions around the world and their dependence on the water vapour supersaturation ratio, the dependence of aerosol hygroscopicity on particle size, and seasonal and diurnal variation of CCN activation and hygroscopic properties.
J. C. Corbin, A. Othman, J. D. Allan, D. R. Worsnop, J. D. Haskins, B. Sierau, U. Lohmann, and A. A. Mensah
Atmos. Meas. Tech., 8, 4615–4636, https://doi.org/10.5194/amt-8-4615-2015, https://doi.org/10.5194/amt-8-4615-2015, 2015
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Peak-integration uncertainties in the Aerodyne high-resolution aerosol mass spectrometer (AMS) are analyzed in detail using a combination of empirical data analysis and Monte Carlo approaches. The most general conclusion, applicable to any mass spectrometer, is that non-zero mass accuracy leads to a percentage error in constrained peak fits, even for well-resolved peaks. For overlapping peaks, this mass-accuracy effect may be viewed as a reduction in the effective m/z-calibration precision.
J. C. Corbin, U. Lohmann, B. Sierau, A. Keller, H. Burtscher, and A. A. Mensah
Atmos. Chem. Phys., 15, 11885–11907, https://doi.org/10.5194/acp-15-11885-2015, https://doi.org/10.5194/acp-15-11885-2015, 2015
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The chemical composition of wood-combustion soot is investigated using a soot-particle aerosol mass spectrometer. The analysis elucidates real-time information on BC oxygenated surface functional groups for a real-world source for the first time. Additional insights into the source of organic material in this soot are provided by positive matrix factorization of the data using a new AMS error model.
E. Hammer, N. Bukowiecki, B. P. Luo, U. Lohmann, C. Marcolli, E. Weingartner, U. Baltensperger, and C. R. Hoyle
Atmos. Chem. Phys., 15, 10309–10323, https://doi.org/10.5194/acp-15-10309-2015, https://doi.org/10.5194/acp-15-10309-2015, 2015
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An important quantity which determines aerosol activation and cloud formation is the effective peak supersaturation. The box model ZOMM was used to simulate the effective peak supersaturation experienced by an air parcel approaching a high-alpine research station in Switzerland. With the box model the sensitivity of the effective peak supersaturation to key aerosol and dynamical parameters was investigated.
S. Pousse-Nottelmann, E. M. Zubler, and U. Lohmann
Atmos. Chem. Phys., 15, 9217–9236, https://doi.org/10.5194/acp-15-9217-2015, https://doi.org/10.5194/acp-15-9217-2015, 2015
V. Sant, R. Posselt, and U. Lohmann
Atmos. Chem. Phys., 15, 8717–8738, https://doi.org/10.5194/acp-15-8717-2015, https://doi.org/10.5194/acp-15-8717-2015, 2015
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We have introduced prognostic precipitation for both liquid (drizzle and rain) and solid (snow) phase precipitation into the global circulation model ECHAM5-HAM. This has a significant effect on the clouds and the parameterized collection rates, also reducing the sensitivity of the liquid water path to the anthropogenic aerosol forcing. Altogether the results suggest that the treatment of precipitation in global circulation models has a significant influence on the phase and lifetime of clouds.
S. Fuzzi, U. Baltensperger, K. Carslaw, S. Decesari, H. Denier van der Gon, M. C. Facchini, D. Fowler, I. Koren, B. Langford, U. Lohmann, E. Nemitz, S. Pandis, I. Riipinen, Y. Rudich, M. Schaap, J. G. Slowik, D. V. Spracklen, E. Vignati, M. Wild, M. Williams, and S. Gilardoni
Atmos. Chem. Phys., 15, 8217–8299, https://doi.org/10.5194/acp-15-8217-2015, https://doi.org/10.5194/acp-15-8217-2015, 2015
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Particulate matter (PM) constitutes one of the most challenging problems both for air quality and climate change policies. This paper reviews the most recent scientific results on the issue and the policy needs that have driven much of the increase in monitoring and mechanistic research over the last 2 decades. The synthesis reveals many new processes and developments in the science underpinning climate-PM interactions and the effects of PM on human health and the environment.
A. Possner, E. Zubler, U. Lohmann, and C. Schär
Atmos. Chem. Phys., 15, 2185–2201, https://doi.org/10.5194/acp-15-2185-2015, https://doi.org/10.5194/acp-15-2185-2015, 2015
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For the first time, real-case simulations of ship tracks are performed at the 2km scale and evaluated against observations. Simulations show that ship tracks are quantitatively and qualitatively captured by the model. Therefore, this approach could be used to evaluate the interplay between parameterisations for aerosol–cloud interactions which occur, in the case of ship tracks, in spatially defined regions and under constrained environmental conditions.
D. Neubauer, U. Lohmann, C. Hoose, and M. G. Frontoso
Atmos. Chem. Phys., 14, 11997–12022, https://doi.org/10.5194/acp-14-11997-2014, https://doi.org/10.5194/acp-14-11997-2014, 2014
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Several biases in the representation of clouds in the stratocumulus regime in the ECHAM6-HAM2 global climate model were found by evaluating the model in the stratocumulus cloud regime. Simulations with changes in model resolution and physics to better represent clouds and aerosol in the stratocumulus regime show that the human influence on clouds and thus climate by emission of aerosol particles is sensitive to the representation of (stratocumulus) clouds.
B. Sierau, R. Y.-W. Chang, C. Leck, J. Paatero, and U. Lohmann
Atmos. Chem. Phys., 14, 7409–7430, https://doi.org/10.5194/acp-14-7409-2014, https://doi.org/10.5194/acp-14-7409-2014, 2014
M. Kuebbeler, U. Lohmann, J. Hendricks, and B. Kärcher
Atmos. Chem. Phys., 14, 3027–3046, https://doi.org/10.5194/acp-14-3027-2014, https://doi.org/10.5194/acp-14-3027-2014, 2014
J. C. Corbin, B. Sierau, M. Gysel, M. Laborde, A. Keller, J. Kim, A. Petzold, T. B. Onasch, U. Lohmann, and A. A. Mensah
Atmos. Chem. Phys., 14, 2591–2603, https://doi.org/10.5194/acp-14-2591-2014, https://doi.org/10.5194/acp-14-2591-2014, 2014
A. Baklanov, K. Schlünzen, P. Suppan, J. Baldasano, D. Brunner, S. Aksoyoglu, G. Carmichael, J. Douros, J. Flemming, R. Forkel, S. Galmarini, M. Gauss, G. Grell, M. Hirtl, S. Joffre, O. Jorba, E. Kaas, M. Kaasik, G. Kallos, X. Kong, U. Korsholm, A. Kurganskiy, J. Kushta, U. Lohmann, A. Mahura, A. Manders-Groot, A. Maurizi, N. Moussiopoulos, S. T. Rao, N. Savage, C. Seigneur, R. S. Sokhi, E. Solazzo, S. Solomos, B. Sørensen, G. Tsegas, E. Vignati, B. Vogel, and Y. Zhang
Atmos. Chem. Phys., 14, 317–398, https://doi.org/10.5194/acp-14-317-2014, https://doi.org/10.5194/acp-14-317-2014, 2014
J. Henneberger, J. P. Fugal, O. Stetzer, and U. Lohmann
Atmos. Meas. Tech., 6, 2975–2987, https://doi.org/10.5194/amt-6-2975-2013, https://doi.org/10.5194/amt-6-2975-2013, 2013
L. A. Ladino Moreno, O. Stetzer, and U. Lohmann
Atmos. Chem. Phys., 13, 9745–9769, https://doi.org/10.5194/acp-13-9745-2013, https://doi.org/10.5194/acp-13-9745-2013, 2013
Z. A. Kanji, A. Welti, C. Chou, O. Stetzer, and U. Lohmann
Atmos. Chem. Phys., 13, 9097–9118, https://doi.org/10.5194/acp-13-9097-2013, https://doi.org/10.5194/acp-13-9097-2013, 2013
C. A. Randles, S. Kinne, G. Myhre, M. Schulz, P. Stier, J. Fischer, L. Doppler, E. Highwood, C. Ryder, B. Harris, J. Huttunen, Y. Ma, R. T. Pinker, B. Mayer, D. Neubauer, R. Hitzenberger, L. Oreopoulos, D. Lee, G. Pitari, G. Di Genova, J. Quaas, F. G. Rose, S. Kato, S. T. Rumbold, I. Vardavas, N. Hatzianastassiou, C. Matsoukas, H. Yu, F. Zhang, H. Zhang, and P. Lu
Atmos. Chem. Phys., 13, 2347–2379, https://doi.org/10.5194/acp-13-2347-2013, https://doi.org/10.5194/acp-13-2347-2013, 2013
C. Chou, Z. A. Kanji, O. Stetzer, T. Tritscher, R. Chirico, M. F. Heringa, E. Weingartner, A. S. H. Prévôt, U. Baltensperger, and U. Lohmann
Atmos. Chem. Phys., 13, 761–772, https://doi.org/10.5194/acp-13-761-2013, https://doi.org/10.5194/acp-13-761-2013, 2013
Related subject area
Climate and Earth system modeling
A sub-grid parameterization scheme for topographic vertical motion in CAM5-SE
Technology to aid the analysis of large-volume multi-institute climate model output at a central analysis facility (PRIMAVERA Data Management Tool V2.10)
A diffusion-based kernel density estimator (diffKDE, version 1) with optimal bandwidth approximation for the analysis of data in geoscience and ecological research
Monte Carlo drift correction – quantifying the drift uncertainty of global climate models
Improvements in the Canadian Earth System Model (CanESM) through systematic model analysis: CanESM5.0 and CanESM5.1
Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations
CIOFC1.0: a common parallel input/output framework based on C-Coupler2.0
Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method
Introducing a new floodplain scheme in ORCHIDEE (version 7885): validation and evaluation over the Pantanal wetlands
URock 2023a: an open-source GIS-based wind model for complex urban settings
DASH: a MATLAB toolbox for paleoclimate data assimilation
Comparing the Performance of Julia on CPUs versus GPUs and Julia-MPI versus Fortran-MPI: a case study with MPAS-Ocean (Version 7.1)
All aboard! Earth system investigations with the CH2O-CHOO TRAIN v1.0
The Canadian Atmospheric Model version 5 (CanAM5.0.3)
The Teddy tool v1.1: temporal disaggregation of daily climate model data for climate impact analysis
Assimilation of the AMSU-A radiances using the CESM (v2.1.0) and the DART (v9.11.13)–RTTOV (v12.3)
Modernizing the open-source community Noah with multi-parameterization options (Noah-MP) land surface model (version 5.0) with enhanced modularity, interoperability, and applicability
Simulated stable water isotopes during the mid-Holocene and pre-industrial periods using AWI-ESM-2.1-wiso
Truly Conserving with Conservative Remapping Methods
Rainbows and climate change: a tutorial on climate model diagnostics and parameterization
ModE-Sim – a medium-sized atmospheric general circulation model (AGCM) ensemble to study climate variability during the modern era (1420 to 2009)
MESMAR v1: a new regional coupled climate model for downscaling, predictability, and data assimilation studies in the Mediterranean region
Climate model Selection by Independence, Performance, and Spread (ClimSIPS v1.0.1) for regional applications
IceTFT v1.0.0: interpretable long-term prediction of Arctic sea ice extent with deep learning
Earth system modeling on Modular Supercomputing Architectures: coupled atmosphere-ocean simulations with ICON 2.6.6-rc
The KNMI Large Ensemble Time Slice (KNMI–LENTIS)
ENSO statistics, teleconnections, and atmosphere–ocean coupling in the Taiwan Earth System Model version 1
Using probabilistic machine learning to better model temporal patterns in parameterizations: a case study with the Lorenz 96 model
The Regional Aerosol Model Intercomparison Project (RAMIP)
DSCIM-Coastal v1.1: an open-source modeling platform for global impacts of sea level rise
TIMBER v0.1: a conceptual framework for emulating temperature responses to tree cover change
Recalibration of a three-dimensional water quality model with a newly developed autocalibration toolkit (EFDC-ACT v1.0.0): how much improvement will be achieved with a wider hydrological variability?
Description and evaluation of the JULES-ES set-up for ISIMIP2b
Simplified Kalman smoother and ensemble Kalman smoother for improving reanalyses
Understanding Changes in Cloud Simulations from E3SM Version 1 to Version 2
Modelling the terrestrial nitrogen and phosphorus cycle in the UVic ESCM
Modeling river water temperature with limiting forcing data: Air2stream v1.0.0, machine learning and multiple regression
WRF (v4.0)-SUEWS (v2018c) Coupled System: Development, Evaluation and Application
A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)
Resolving the mesoscale at reduced computational cost with FESOM 2.5: efficient modeling approaches applied to the Southern Ocean
Modeling and evaluating the effects of irrigation on land-atmosphere interaction in South-West Europe with the regional climate model REMO2020-iMOVE using a newly developed parameterization
The fully coupled regionally refined model of E3SM version 2: overview of the atmosphere, land, and river results
The mixed-layer depth in the Ocean Model Intercomparison Project (OMIP): impact of resolving mesoscale eddies
A new simplified parameterization of secondary organic aerosol in the Community Earth System Model Version 2 (CESM2; CAM6.3)
Deep learning for stochastic precipitation generation – deep SPG v1.0
Developing spring wheat in the Noah-MP land surface model (v4.4) for growing season dynamics and responses to temperature stress
Deep Learning Model based on Multi-scale Feature Fusion for Precipitation Nowcasting
Robust 4D climate-optimal flight planning in structured airspace using parallelized simulation on GPUs: ROOST V1.0
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The Earth system model CLIMBER-X v1.0 – Part 2: The global carbon cycle
Yaqi Wang, Lanning Wang, Juan Feng, Zhenya Song, Qizhong Wu, and Huaqiong Cheng
Geosci. Model Dev., 16, 6857–6873, https://doi.org/10.5194/gmd-16-6857-2023, https://doi.org/10.5194/gmd-16-6857-2023, 2023
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In this study, to noticeably improve precipitation simulation in steep mountains, we propose a sub-grid parameterization scheme for the topographic vertical motion in CAM5-SE to revise the original vertical velocity by adding the topographic vertical motion. The dynamic lifting effect of topography is extended from the lowest layer to multiple layers, thus improving the positive deviations of precipitation simulation in high-altitude regions and negative deviations in low-altitude regions.
Jon Seddon, Ag Stephens, Matthew S. Mizielinski, Pier Luigi Vidale, and Malcolm J. Roberts
Geosci. Model Dev., 16, 6689–6700, https://doi.org/10.5194/gmd-16-6689-2023, https://doi.org/10.5194/gmd-16-6689-2023, 2023
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The PRIMAVERA project aimed to develop a new generation of advanced global climate models. The large volume of data generated was uploaded to a central analysis facility (CAF) and was analysed by 100 PRIMAVERA scientists there. We describe how the PRIMAVERA project used the CAF's facilities to enable users to analyse this large dataset. We believe that similar, multi-institute, big-data projects could also use a CAF to efficiently share, organise and analyse large volumes of data.
Maria-Theresia Pelz, Markus Schartau, Christopher J. Somes, Vanessa Lampe, and Thomas Slawig
Geosci. Model Dev., 16, 6609–6634, https://doi.org/10.5194/gmd-16-6609-2023, https://doi.org/10.5194/gmd-16-6609-2023, 2023
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Kernel density estimators (KDE) approximate the probability density of a data set without the assumption of an underlying distribution. We used the solution of the diffusion equation, and a new approximation of the optimal smoothing parameter build on two pilot estimation steps, to construct such a KDE best suited for typical characteristics of geoscientific data. The resulting KDE is insensitive to noise and well resolves multimodal data structures as well as boundary-close data.
Benjamin S. Grandey, Zhi Yang Koh, Dhrubajyoti Samanta, Benjamin P. Horton, Justin Dauwels, and Lock Yue Chew
Geosci. Model Dev., 16, 6593–6608, https://doi.org/10.5194/gmd-16-6593-2023, https://doi.org/10.5194/gmd-16-6593-2023, 2023
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Global climate models are susceptible to spurious trends known as drift. Fortunately, drift can be corrected when analysing data produced by models. To explore the uncertainty associated with drift correction, we develop a new method: Monte Carlo drift correction. For historical simulations of thermosteric sea level rise, drift uncertainty is relatively large. When analysing data susceptible to drift, researchers should consider drift uncertainty.
Michael Sigmond, James Anstey, Vivek Arora, Ruth Digby, Nathan Gillett, Viatcheslav Kharin, William Merryfield, Catherine Reader, John Scinocca, Neil Swart, John Virgin, Carsten Abraham, Jason Cole, Nicolas Lambert, Woo-Sung Lee, Yongxiao Liang, Elizaveta Malinina, Landon Rieger, Knut von Salzen, Christian Seiler, Clint Seinen, Andrew Shao, Reinel Sospedra-Alfonso, Libo Wang, and Duo Yang
Geosci. Model Dev., 16, 6553–6591, https://doi.org/10.5194/gmd-16-6553-2023, https://doi.org/10.5194/gmd-16-6553-2023, 2023
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We present a new activity which aims to organize the analysis of biases in the Canadian Earth System model (CanESM) in a systematic manner. Results of this “Analysis for Development” (A4D) activity includes a new CanESM version, CanESM5.1, which features substantial improvements regarding the simulation of dust and stratospheric temperatures, a second CanESM5.1 variant with reduced climate sensitivity, and insights into potential avenues to reduce various other model biases.
Shuaiqi Tang, Adam C. Varble, Jerome D. Fast, Kai Zhang, Peng Wu, Xiquan Dong, Fan Mei, Mikhail Pekour, Joseph C. Hardin, and Po-Lun Ma
Geosci. Model Dev., 16, 6355–6376, https://doi.org/10.5194/gmd-16-6355-2023, https://doi.org/10.5194/gmd-16-6355-2023, 2023
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To assess the ability of Earth system model (ESM) predictions, we developed a tool called ESMAC Diags to understand how aerosols, clouds, and aerosol–cloud interactions are represented in ESMs. This paper describes its version 2 functionality. We compared the model predictions with measurements taken by planes, ships, satellites, and ground instruments over four regions across the world. Results show that this new tool can help identify model problems and guide future development of ESMs.
Xinzhu Yu, Li Liu, Chao Sun, Qingu Jiang, Biao Zhao, Zhiyuan Zhang, Hao Yu, and Bin Wang
Geosci. Model Dev., 16, 6285–6308, https://doi.org/10.5194/gmd-16-6285-2023, https://doi.org/10.5194/gmd-16-6285-2023, 2023
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In this paper we propose a new common, flexible, and efficient parallel I/O framework for earth system modeling based on C-Coupler2.0. CIOFC1.0 can handle data I/O in parallel and provides a configuration file format that enables users to conveniently change the I/O configurations. It can automatically make grid and time interpolation, output data with an aperiodic time series, and accelerate data I/O when the field size is large.
Toshiki Matsushima, Seiya Nishizawa, and Shin-ichiro Shima
Geosci. Model Dev., 16, 6211–6245, https://doi.org/10.5194/gmd-16-6211-2023, https://doi.org/10.5194/gmd-16-6211-2023, 2023
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A particle-based cloud model was developed for meter- to submeter-scale resolution in cloud simulations. Our new cloud model's computational performance is superior to a bin method and comparable to a two-moment bulk method. A highlight of this study is the 2 m resolution shallow cloud simulations over an area covering ∼10 km2. This model allows for studying turbulence and cloud physics at spatial scales that overlap with those covered by direct numerical simulations and field studies.
Anthony Schrapffer, Jan Polcher, Anna Sörensson, and Lluís Fita
Geosci. Model Dev., 16, 5755–5782, https://doi.org/10.5194/gmd-16-5755-2023, https://doi.org/10.5194/gmd-16-5755-2023, 2023
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The present paper introduces a floodplain scheme for a high-resolution land surface model river routing. It was developed and evaluated over one of the world’s largest floodplains: the Pantanal in South America. This shows the impact of tropical floodplains on land surface conditions (soil moisture, temperature) and on land–atmosphere fluxes and highlights the potential impact of floodplains on land–atmosphere interactions and the importance of integrating this module in coupled simulations.
Jérémy Bernard, Fredrik Lindberg, and Sandro Oswald
Geosci. Model Dev., 16, 5703–5727, https://doi.org/10.5194/gmd-16-5703-2023, https://doi.org/10.5194/gmd-16-5703-2023, 2023
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The UMEP plug-in integrated in the free QGIS software can now calculate the spatial variation of the wind speed within urban settings. This paper shows that the new wind model, URock, generally fits observations well and highlights the main needed improvements. According to this work, pedestrian wind fields and outdoor thermal comfort can now simply be estimated by any QGIS user (researchers, students, and practitioners).
Jonathan King, Jessica Tierney, Matthew Osman, Emily J. Judd, and Kevin J. Anchukaitis
Geosci. Model Dev., 16, 5653–5683, https://doi.org/10.5194/gmd-16-5653-2023, https://doi.org/10.5194/gmd-16-5653-2023, 2023
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Paleoclimate data assimilation is a useful method that allows researchers to combine climate models with natural archives of past climates. However, it can be difficult to implement in practice. To facilitate this method, we present DASH, a MATLAB toolbox. The toolbox provides routines that implement common steps of paleoclimate data assimilation, and it can be used to implement assimilations for a wide variety of time periods, spatial regions, data networks, and analytical algorithms.
Siddhartha Bishnu, Robert R. Strauss, and Mark R. Petersen
Geosci. Model Dev., 16, 5539–5559, https://doi.org/10.5194/gmd-16-5539-2023, https://doi.org/10.5194/gmd-16-5539-2023, 2023
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Here we test Julia, a relatively new programming language, which is designed to be simple to write, but also fast on advanced computer architectures. We found that Julia is both convenient and fast, but there is no free lunch. Our first attempt to develop an ocean model in Julia was relatively easy, but the code was slow. After several months of further development, we created a Julia code that is as fast on supercomputers as a Fortran ocean model.
Tyler Kukla, Daniel E. Ibarra, Kimberly V. Lau, and Jeremy K. C. Rugenstein
Geosci. Model Dev., 16, 5515–5538, https://doi.org/10.5194/gmd-16-5515-2023, https://doi.org/10.5194/gmd-16-5515-2023, 2023
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The CH2O-CHOO TRAIN model can simulate how climate and the long-term carbon cycle interact across millions of years on a standard PC. While efficient, the model accounts for many factors including the location of land masses, the spatial pattern of the water cycle, and fundamental climate feedbacks. The model is a powerful tool for investigating how short-term climate processes can affect long-term changes in the Earth system.
Jason Neil Steven Cole, Knut von Salzen, Jiangnan Li, John Scinocca, David Plummer, Vivek Arora, Norman McFarlane, Michael Lazare, Murray MacKay, and Diana Verseghy
Geosci. Model Dev., 16, 5427–5448, https://doi.org/10.5194/gmd-16-5427-2023, https://doi.org/10.5194/gmd-16-5427-2023, 2023
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The Canadian Atmospheric Model version 5 (CanAM5) is used to simulate on a global scale the climate of Earth's atmosphere, land, and lakes. We document changes to the physics in CanAM5 since the last major version of the model (CanAM4) and evaluate the climate simulated relative to observations and CanAM4. The climate simulated by CanAM5 is similar to CanAM4, but there are improvements, including better simulation of temperature and precipitation over the Amazon and better simulation of cloud.
Florian Zabel and Benjamin Poschlod
Geosci. Model Dev., 16, 5383–5399, https://doi.org/10.5194/gmd-16-5383-2023, https://doi.org/10.5194/gmd-16-5383-2023, 2023
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Today, most climate model data are provided at daily time steps. However, more and more models from different sectors, such as energy, water, agriculture, and health, require climate information at a sub-daily temporal resolution for a more robust and reliable climate impact assessment. Here we describe and validate the Teddy tool, a new model for the temporal disaggregation of daily climate model data for climate impact analysis.
Young-Chan Noh, Yonghan Choi, Hyo-Jong Song, Kevin Raeder, Joo-Hong Kim, and Youngchae Kwon
Geosci. Model Dev., 16, 5365–5382, https://doi.org/10.5194/gmd-16-5365-2023, https://doi.org/10.5194/gmd-16-5365-2023, 2023
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This is the first attempt to assimilate the observations of microwave temperature sounders into the global climate forecast model in which the satellite observations have not been assimilated in the past. To do this, preprocessing schemes are developed to make the satellite observations suitable to be assimilated. In the assimilation experiments, the model analysis is significantly improved by assimilating the observations of microwave temperature sounders.
Cenlin He, Prasanth Valayamkunnath, Michael Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, Dev Niyogi, and Michael Ek
Geosci. Model Dev., 16, 5131–5151, https://doi.org/10.5194/gmd-16-5131-2023, https://doi.org/10.5194/gmd-16-5131-2023, 2023
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Noah-MP is one of the most widely used open-source community land surface models in the world, designed for applications ranging from uncoupled land surface and ecohydrological process studies to coupled numerical weather prediction and decadal climate simulations. To facilitate model developments and applications, we modernize Noah-MP by adopting modern Fortran code and data structures and standards, which substantially enhance model modularity, interoperability, and applicability.
Xiaoxu Shi, Alexandre Cauquoin, Gerrit Lohmann, Lukas Jonkers, Qiang Wang, Hu Yang, Yuchen Sun, and Martin Werner
Geosci. Model Dev., 16, 5153–5178, https://doi.org/10.5194/gmd-16-5153-2023, https://doi.org/10.5194/gmd-16-5153-2023, 2023
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We developed a new climate model with isotopic capabilities and simulated the pre-industrial and mid-Holocene periods. Despite certain regional model biases, the modeled isotope composition is in good agreement with observations and reconstructions. Based on our analyses, the observed isotope–temperature relationship in polar regions may have a summertime bias. Using daily model outputs, we developed a novel isotope-based approach to determine the onset date of the West African summer monsoon.
Karl E. Taylor
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-177, https://doi.org/10.5194/gmd-2023-177, 2023
Revised manuscript accepted for GMD
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Remapping gridded data in a way that preserves the conservative properties of the climate system can be essential in coupling model components and for accurate assessment of the system’s energy and mass constituents. Remapping packages capable of handling a wide variety of grids can, for common grids, calculate remapping weights that are somewhat inaccurate. Correcting for these errors, guidelines are provided to ensure conservation when the weights are used in practice.
Andrew Gettelman
Geosci. Model Dev., 16, 4937–4956, https://doi.org/10.5194/gmd-16-4937-2023, https://doi.org/10.5194/gmd-16-4937-2023, 2023
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A representation of rainbows is developed for a climate model. The diagnostic raises many common issues. Simulated rainbows are evaluated against limited observations. The pattern of rainbows in the model matches observations and theory about when and where rainbows are most common. The diagnostic is used to assess the past and future state of rainbows. Changes to clouds from climate change are expected to increase rainbows as cloud cover decreases in a warmer world.
Ralf Hand, Eric Samakinwa, Laura Lipfert, and Stefan Brönnimann
Geosci. Model Dev., 16, 4853–4866, https://doi.org/10.5194/gmd-16-4853-2023, https://doi.org/10.5194/gmd-16-4853-2023, 2023
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ModE-Sim is an ensemble of simulations with an atmosphere model. It uses observed sea surface temperatures, sea ice conditions, and volcanic aerosols for 1420 to 2009 as model input while accounting for uncertainties in these conditions. This generates several representations of the possible climate given these preconditions. Such a setup can be useful to understand the mechanisms that contribute to climate variability. This paper describes the setup of ModE-Sim and evaluates its performance.
Andrea Storto, Yassmin Hesham Essa, Vincenzo de Toma, Alessandro Anav, Gianmaria Sannino, Rosalia Santoleri, and Chunxue Yang
Geosci. Model Dev., 16, 4811–4833, https://doi.org/10.5194/gmd-16-4811-2023, https://doi.org/10.5194/gmd-16-4811-2023, 2023
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Regional climate models are a fundamental tool for a very large number of applications and are being increasingly used within climate services, together with other complementary approaches. Here, we introduce a new regional coupled model, intended to be later extended to a full Earth system model, for climate investigations within the Mediterranean region, coupled data assimilation experiments, and several downscaling exercises (reanalyses and long-range predictions).
Anna L. Merrifield, Lukas Brunner, Ruth Lorenz, Vincent Humphrey, and Reto Knutti
Geosci. Model Dev., 16, 4715–4747, https://doi.org/10.5194/gmd-16-4715-2023, https://doi.org/10.5194/gmd-16-4715-2023, 2023
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Using all Coupled Model Intercomparison Project (CMIP) models is unfeasible for many applications. We provide a subselection protocol that balances user needs for model independence, performance, and spread capturing CMIP’s projection uncertainty simultaneously. We show how sets of three to five models selected for European applications map to user priorities. An audit of model independence and its influence on equilibrium climate sensitivity uncertainty in CMIP is also presented.
Bin Mu, Xiaodan Luo, Shijin Yuan, and Xi Liang
Geosci. Model Dev., 16, 4677–4697, https://doi.org/10.5194/gmd-16-4677-2023, https://doi.org/10.5194/gmd-16-4677-2023, 2023
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To improve the long-term forecast skill for sea ice extent (SIE), we introduce IceTFT, which directly predicts 12 months of averaged Arctic SIE. The results show that IceTFT has higher forecasting skill. We conducted a sensitivity analysis of the variables in the IceTFT model. These sensitivities can help researchers study the mechanisms of sea ice development, and they also provide useful references for the selection of variables in data assimilation or the input of deep learning models.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
EGUsphere, https://doi.org/10.5194/egusphere-2023-1476, https://doi.org/10.5194/egusphere-2023-1476, 2023
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We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere-ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 59 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Laura Muntjewerf, Richard Bintanja, Thomas Reerink, and Karin van der Wiel
Geosci. Model Dev., 16, 4581–4597, https://doi.org/10.5194/gmd-16-4581-2023, https://doi.org/10.5194/gmd-16-4581-2023, 2023
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The KNMI Large Ensemble Time Slice (KNMI–LENTIS) is a large ensemble of global climate model simulations with EC-Earth3. It covers two climate scenarios by focusing on two time slices: the present day (2000–2009) and a future +2 K climate (2075–2084 in the SSP2-4.5 scenario). We have 1600 simulated years for the two climates with (sub-)daily output frequency. The sampled climate variability allows for robust and in-depth research into (compound) extreme events such as heat waves and droughts.
Yi-Chi Wang, Wan-Ling Tseng, Yu-Luen Chen, Shih-Yu Lee, Huang-Hsiung Hsu, and Hsin-Chien Liang
Geosci. Model Dev., 16, 4599–4616, https://doi.org/10.5194/gmd-16-4599-2023, https://doi.org/10.5194/gmd-16-4599-2023, 2023
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This study focuses on evaluating the performance of the Taiwan Earth System Model version 1 (TaiESM1) in simulating the El Niño–Southern Oscillation (ENSO), a significant tropical climate pattern with global impacts. Our findings reveal that TaiESM1 effectively captures several characteristics of ENSO, such as its seasonal variation and remote teleconnections. Its pronounced ENSO strength bias is also thoroughly investigated, aiming to gain insights to improve climate model performance.
Raghul Parthipan, Hannah M. Christensen, J. Scott Hosking, and Damon J. Wischik
Geosci. Model Dev., 16, 4501–4519, https://doi.org/10.5194/gmd-16-4501-2023, https://doi.org/10.5194/gmd-16-4501-2023, 2023
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How can we create better climate models? We tackle this by proposing a data-driven successor to the existing approach for capturing key temporal trends in climate models. We combine probability, allowing us to represent uncertainty, with machine learning, a technique to learn relationships from data which are undiscoverable to humans. Our model is often superior to existing baselines when tested in a simple atmospheric simulation.
Laura J. Wilcox, Robert J. Allen, Bjørn H. Samset, Massimo A. Bollasina, Paul T. Griffiths, James Keeble, Marianne T. Lund, Risto Makkonen, Joonas Merikanto, Declan O'Donnell, David J. Paynter, Geeta G. Persad, Steven T. Rumbold, Toshihiko Takemura, Kostas Tsigaridis, Sabine Undorf, and Daniel M. Westervelt
Geosci. Model Dev., 16, 4451–4479, https://doi.org/10.5194/gmd-16-4451-2023, https://doi.org/10.5194/gmd-16-4451-2023, 2023
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Changes in anthropogenic aerosol emissions have strongly contributed to global and regional climate change. However, the size of these regional impacts and the way they arise are still uncertain. With large changes in aerosol emissions a possibility over the next few decades, it is important to better quantify the potential role of aerosol in future regional climate change. The Regional Aerosol Model Intercomparison Project will deliver experiments designed to facilitate this.
Nicholas Depsky, Ian Bolliger, Daniel Allen, Jun Ho Choi, Michael Delgado, Michael Greenstone, Ali Hamidi, Trevor Houser, Robert E. Kopp, and Solomon Hsiang
Geosci. Model Dev., 16, 4331–4366, https://doi.org/10.5194/gmd-16-4331-2023, https://doi.org/10.5194/gmd-16-4331-2023, 2023
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This work presents a novel open-source modeling platform for evaluating future sea level rise (SLR) impacts. Using nearly 10 000 discrete coastline segments around the world, we estimate 21st-century costs for 230 SLR and socioeconomic scenarios. We find that annual end-of-century costs range from USD 100 billion under a 2 °C warming scenario with proactive adaptation to 7 trillion under a 4 °C warming scenario with minimal adaptation, illustrating the cost-effectiveness of coastal adaptation.
Shruti Nath, Lukas Gudmundsson, Jonas Schwaab, Gregory Duveiller, Steven J. De Hertog, Suqi Guo, Felix Havermann, Fei Luo, Iris Manola, Julia Pongratz, Sonia I. Seneviratne, Carl F. Schleussner, Wim Thiery, and Quentin Lejeune
Geosci. Model Dev., 16, 4283–4313, https://doi.org/10.5194/gmd-16-4283-2023, https://doi.org/10.5194/gmd-16-4283-2023, 2023
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Tree cover changes play a significant role in climate mitigation and adaptation. Their regional impacts are key in informing national-level decisions and prioritising areas for conservation efforts. We present a first step towards exploring these regional impacts using a simple statistical device, i.e. emulator. The emulator only needs to train on climate model outputs representing the maximal impacts of aff-, re-, and deforestation, from which it explores plausible in-between outcomes itself.
Chen Zhang and Tianyu Fu
Geosci. Model Dev., 16, 4315–4329, https://doi.org/10.5194/gmd-16-4315-2023, https://doi.org/10.5194/gmd-16-4315-2023, 2023
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A new automatic calibration toolkit was developed and implemented into the recalibration of a 3-D water quality model, with observations in a wider range of hydrological variability. Compared to the model calibrated with the original strategy, the recalibrated model performed significantly better in modeled total phosphorus, chlorophyll a, and dissolved oxygen. Our work indicates that hydrological variability in the calibration periods has a non-negligible impact on the water quality models.
Camilla Mathison, Eleanor Burke, Andrew J. Hartley, Douglas I. Kelley, Chantelle Burton, Eddy Robertson, Nicola Gedney, Karina Williams, Andy Wiltshire, Richard J. Ellis, Alistair A. Sellar, and Chris D. Jones
Geosci. Model Dev., 16, 4249–4264, https://doi.org/10.5194/gmd-16-4249-2023, https://doi.org/10.5194/gmd-16-4249-2023, 2023
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This paper describes and evaluates a new modelling methodology to quantify the impacts of climate change on water, biomes and the carbon cycle. We have created a new configuration and set-up for the JULES-ES land surface model, driven by bias-corrected historical and future climate model output provided by the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP). This allows us to compare projections of the impacts of climate change across multiple impact models and multiple sectors.
Bo Dong, Ross Bannister, Yumeng Chen, Alison Fowler, and Keith Haines
Geosci. Model Dev., 16, 4233–4247, https://doi.org/10.5194/gmd-16-4233-2023, https://doi.org/10.5194/gmd-16-4233-2023, 2023
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Traditional Kalman smoothers are expensive to apply in large global ocean operational forecast and reanalysis systems. We develop a cost-efficient method to overcome the technical constraints and to improve the performance of existing reanalysis products.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2023-1263, https://doi.org/10.5194/egusphere-2023-1263, 2023
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We performed systematic evaluation of clouds simulated in the E3SMv2 to document model performance on clouds and understand what updates in E3SMv2 have caused the changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved primarily due to the re-tuning of cloud macrophysics parameters. This study offers additional insights about clouds simulated in E3SMv2 and will benefit the future E3SM developments.
Makcim L. De Sisto, Andrew H. MacDougall, Nadine Mengis, and Sophia Antoniello
Geosci. Model Dev., 16, 4113–4136, https://doi.org/10.5194/gmd-16-4113-2023, https://doi.org/10.5194/gmd-16-4113-2023, 2023
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In this study, we developed a nitrogen and phosphorus cycle in an intermediate-complexity Earth system climate model. We found that the implementation of nutrient limitation in simulations has reduced the capacity of land to take up atmospheric carbon and has decreased the vegetation biomass, hence, improving the fidelity of the response of land to simulated atmospheric CO2 rise.
Manuel C. Almeida and Pedro S. Coelho
Geosci. Model Dev., 16, 4083–4112, https://doi.org/10.5194/gmd-16-4083-2023, https://doi.org/10.5194/gmd-16-4083-2023, 2023
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Water temperature (WT) datasets of low-order rivers are scarce. In this study, five different models are used to predict the WT of 83 rivers. Generally, the results show that the models' hyperparameter optimization is essential and that to minimize the prediction error it is relevant to apply all the models considered in this study. Results also show that there is a logarithmic correlation among the error of the predicted river WT and the watershed time of concentration.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-117, https://doi.org/10.5194/gmd-2023-117, 2023
Revised manuscript accepted for GMD
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For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Lingcheng Li, Yilin Fang, Zhonghua Zheng, Mingjie Shi, Marcos Longo, Charles D. Koven, Jennifer A. Holm, Rosie A. Fisher, Nate G. McDowell, Jeffrey Chambers, and L. Ruby Leung
Geosci. Model Dev., 16, 4017–4040, https://doi.org/10.5194/gmd-16-4017-2023, https://doi.org/10.5194/gmd-16-4017-2023, 2023
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Accurately modeling plant coexistence in vegetation demographic models like ELM-FATES is challenging. This study proposes a repeatable method that uses machine-learning-based surrogate models to optimize plant trait parameters in ELM-FATES. Our approach significantly improves plant coexistence modeling, thus reducing errors. It has important implications for modeling ecosystem dynamics in response to climate change.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
EGUsphere, https://doi.org/10.5194/egusphere-2023-1496, https://doi.org/10.5194/egusphere-2023-1496, 2023
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Ocean models struggle to simulate small-scale ocean flows due to the computational cost of high-resolution simulations. Several cost-reducing strategies are applied to simulations of the Southern Ocean and evaluated with respect to observations and traditional, lower-resolution modelling methods. The high-resolution simulations effectively reproduce small-scale flows seen in satellite data and are largely consistent with traditional model simulations regarding their response to climate change.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
EGUsphere, https://doi.org/10.5194/egusphere-2023-890, https://doi.org/10.5194/egusphere-2023-890, 2023
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Irrigation modifies the land surface and soil conditions. The caused effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which is simulating the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
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High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, https://doi.org/10.5194/gmd-16-3849-2023, 2023
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The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
Duseong S. Jo, Simone Tilmes, Louisa K. Emmons, Siyuan Wang, and Francis Vitt
Geosci. Model Dev., 16, 3893–3906, https://doi.org/10.5194/gmd-16-3893-2023, https://doi.org/10.5194/gmd-16-3893-2023, 2023
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A new simple secondary organic aerosol (SOA) scheme has been developed for the Community Atmosphere Model (CAM) based on the complex SOA scheme in CAM with detailed chemistry (CAM-chem). The CAM with the new SOA scheme shows better agreements with CAM-chem in terms of aerosol concentrations and radiative fluxes, which ensures more consistent results between different compsets in the Community Earth System Model. The new SOA scheme also has technical advantages for future developments.
Leroy J. Bird, Matthew G. W. Walker, Greg E. Bodeker, Isaac H. Campbell, Guangzhong Liu, Swapna Josmi Sam, Jared Lewis, and Suzanne M. Rosier
Geosci. Model Dev., 16, 3785–3808, https://doi.org/10.5194/gmd-16-3785-2023, https://doi.org/10.5194/gmd-16-3785-2023, 2023
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Deriving the statistics of expected future changes in extreme precipitation is challenging due to these events being rare. Regional climate models (RCMs) are computationally prohibitive for generating ensembles capable of capturing large numbers of extreme precipitation events with statistical robustness. Stochastic precipitation generators (SPGs) provide an alternative to RCMs. We describe a novel single-site SPG that learns the statistics of precipitation using a machine-learning approach.
Zhe Zhang, Yanping Li, Fei Chen, Phillip Harder, Warren Helgason, James Famiglietti, Prasanth Valayamkunnath, Cenlin He, and Zhenhua Li
Geosci. Model Dev., 16, 3809–3825, https://doi.org/10.5194/gmd-16-3809-2023, https://doi.org/10.5194/gmd-16-3809-2023, 2023
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Crop models incorporated in Earth system models are essential to accurately simulate crop growth processes on Earth's surface and agricultural production. In this study, we aim to model the spring wheat in the Northern Great Plains, focusing on three aspects: (1) develop the wheat model at a point scale, (2) apply dynamic planting and harvest schedules, and (3) adopt a revised heat stress function. The results show substantial improvements and have great importance for agricultural production.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-109, https://doi.org/10.5194/gmd-2023-109, 2023
Revised manuscript accepted for GMD
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1. This study present a deep learning architecture MFF to improve the forecast skills of precipitations especially for heavy precipitations. 2. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. 3. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors, so that heavy precipitations are produced.
Abolfazl Simorgh, Manuel Soler, Daniel González-Arribas, Florian Linke, Benjamin Lührs, Maximilian M. Meuser, Simone Dietmüller, Sigrun Matthes, Hiroshi Yamashita, Feijia Yin, Federica Castino, Volker Grewe, and Sabine Baumann
Geosci. Model Dev., 16, 3723–3748, https://doi.org/10.5194/gmd-16-3723-2023, https://doi.org/10.5194/gmd-16-3723-2023, 2023
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This paper addresses the robust climate optimal trajectory planning problem under uncertain meteorological conditions within the structured airspace. Based on the optimization methodology, a Python library has been developed, which can be accessed using the following DOI: https://doi.org/10.5281/zenodo.7121862. The developed tool is capable of providing robust trajectories taking into account all probable realizations of meteorological conditions provided by an EPS computationally very fast.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio Bento, and Angelina Bushenkova
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-136, https://doi.org/10.5194/gmd-2023-136, 2023
Revised manuscript accepted for GMD
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This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data, and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534, https://doi.org/10.5194/gmd-16-3501-2023, https://doi.org/10.5194/gmd-16-3501-2023, 2023
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In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
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Short summary
A new method to simulate deterministic ice nucleation processes based on the differential activated fraction was evaluated against a cumulative approach. Box model simulations of heterogeneous-only ice nucleation within cirrus suggest that the latter approach likely underpredicts the ice crystal number concentration. Longer simulations with a GCM show that choosing between these two approaches impacts ice nucleation competition within cirrus but leads to small and insignificant climate effects.
A new method to simulate deterministic ice nucleation processes based on the differential...
