Articles | Volume 7, issue 6
https://doi.org/10.5194/gmd-7-3037-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-7-3037-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
18 Dec 2014
Development and technical paper |
| 18 Dec 2014
Evaluation of North Eurasian snow-off dates in the ECHAM5.4 atmospheric general circulation model
P. Räisänen
Finnish Meteorological Institute, Helsinki, Finland
A. Luomaranta
Finnish Meteorological Institute, Helsinki, Finland
H. Järvinen
Department of Physics, University of Helsinki, Helsinki, Finland
M. Takala
Finnish Meteorological Institute, Helsinki, Finland
Finnish Meteorological Institute, Helsinki, Finland
O. N. Bulygina
All-Russian Research Institute of Hydrometeorological Information, World Data Centre, Obninsk, Russian Federation (RIHMI-WDC), Russia
K. Luojus
Finnish Meteorological Institute, Helsinki, Finland
A. Riihelä
Finnish Meteorological Institute, Helsinki, Finland
A. Laaksonen
Finnish Meteorological Institute, Helsinki, Finland
Department of Physics, University of Eastern Finland, Kuopio, Finland
J. Koskinen
Finnish Geodetic Institute, Masala, Finland
J. Pulliainen
Finnish Meteorological Institute, Helsinki, Finland
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J. Tonttila, P. Räisänen, and H. Järvinen
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Adriano Lemos and Aku Riihelä
EGUsphere, https://doi.org/10.5194/egusphere-2024-869, https://doi.org/10.5194/egusphere-2024-869, 2024
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Aku Riihelä, Emmihenna Jääskeläinen, and Viivi Kallio-Myers
Earth Syst. Sci. Data, 16, 1007–1028, https://doi.org/10.5194/essd-16-1007-2024, https://doi.org/10.5194/essd-16-1007-2024, 2024
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Emmihenna Jääskeläinen, Kerttu Kouki, and Aku Riihelä
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-278, https://doi.org/10.5194/hess-2023-278, 2024
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Karl-Göran Karlsson, Martin Stengel, Jan Fokke Meirink, Aku Riihelä, Jörg Trentmann, Tom Akkermans, Diana Stein, Abhay Devasthale, Salomon Eliasson, Erik Johansson, Nina Håkansson, Irina Solodovnik, Nikos Benas, Nicolas Clerbaux, Nathalie Selbach, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 15, 4901–4926, https://doi.org/10.5194/essd-15-4901-2023, https://doi.org/10.5194/essd-15-4901-2023, 2023
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Mária Lbadaoui-Darvas, Ari Laaksonen, and Athanasios Nenes
Atmos. Chem. Phys., 23, 10057–10074, https://doi.org/10.5194/acp-23-10057-2023, https://doi.org/10.5194/acp-23-10057-2023, 2023
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Pinja Venäläinen, Kari Luojus, Colleen Mortimer, Juha Lemmetyinen, Jouni Pulliainen, Matias Takala, Mikko Moisander, and Lina Zschenderlein
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Atmos. Chem. Phys., 22, 12207–12220, https://doi.org/10.5194/acp-22-12207-2022, https://doi.org/10.5194/acp-22-12207-2022, 2022
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Atmospheric new particle formation (NPF) is a dominant source of atmospheric ultrafine particles. In urban environments, traffic emissions are a major source of primary pollutants, but their contribution to NPF remains under debate. During the COVID-19 lockdown, traffic emissions were significantly reduced, providing a unique chance to examine their relevance to NPF. Based on our comprehensive measurements, we demonstrate that traffic emissions alone are not able to explain the NPF in Beijing.
Petri Räisänen, Joonas Merikanto, Risto Makkonen, Mikko Savolahti, Alf Kirkevåg, Maria Sand, Øyvind Seland, and Antti-Ilari Partanen
Atmos. Chem. Phys., 22, 11579–11602, https://doi.org/10.5194/acp-22-11579-2022, https://doi.org/10.5194/acp-22-11579-2022, 2022
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A climate model is used to evaluate how the radiative forcing (RF) associated with black carbon (BC) emissions depends on the latitude, longitude, and seasonality of emissions. It is found that both the direct RF (BC absorption of solar radiation in air) and snow RF (BC absorption in snow/ice) depend strongly on the emission region and season. The results suggest that, for a given mass of BC emitted, climatic impacts are likely to be largest for high-latitude emissions due to the large snow RF.
Jaakko Ahola, Tomi Raatikainen, Muzaffer Ege Alper, Jukka-Pekka Keskinen, Harri Kokkola, Antti Kukkurainen, Antti Lipponen, Jia Liu, Kalle Nordling, Antti-Ilari Partanen, Sami Romakkaniemi, Petri Räisänen, Juha Tonttila, and Hannele Korhonen
Atmos. Chem. Phys., 22, 4523–4537, https://doi.org/10.5194/acp-22-4523-2022, https://doi.org/10.5194/acp-22-4523-2022, 2022
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Clouds are important for the climate, and cloud droplets have a significant role in cloud properties. Cloud droplets form when air rises and cools and water vapour condenses on small particles that can be natural or of anthropogenic origin. Currently, the updraft velocity, meaning how fast the air rises, is poorly represented in global climate models. In our study, we show three methods that will improve the depiction of updraft velocity and which properties are vital to updrafts.
Hanna K. Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Mikhail Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Köster, Elena Lapshina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Buenrostro Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenkov, Dmitry Orlov, Jean-Daniel Paris, Roberta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qiu, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergej Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 22, 4413–4469, https://doi.org/10.5194/acp-22-4413-2022, https://doi.org/10.5194/acp-22-4413-2022, 2022
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We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
Angel Navarro Trastoy, Sebastian Strasser, Lauri Tuppi, Maksym Vasiuta, Markku Poutanen, Torsten Mayer-Gürr, and Heikki Järvinen
Geosci. Model Dev., 15, 2763–2771, https://doi.org/10.5194/gmd-15-2763-2022, https://doi.org/10.5194/gmd-15-2763-2022, 2022
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Production of satellite products relies on information from different centers. By coupling a weather model and an orbit determination solver we eliminate the dependence on one of the centers. The coupling has proven to be possible in the first stage, where no formatting has been applied to any of the models involved. This opens a window for further development and improvement to a coupling that has proven to be as good as the predecessor model.
Kerttu Kouki, Petri Räisänen, Kari Luojus, Anna Luomaranta, and Aku Riihelä
The Cryosphere, 16, 1007–1030, https://doi.org/10.5194/tc-16-1007-2022, https://doi.org/10.5194/tc-16-1007-2022, 2022
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We analyze state-of-the-art climate models’ ability to describe snow mass and whether biases in modeled temperature or precipitation can explain the discrepancies in snow mass. In winter, biases in precipitation are the main factor affecting snow mass, while in spring, biases in temperature becomes more important, which is an expected result. However, temperature or precipitation cannot explain all snow mass discrepancies. Other factors, such as models’ structural errors, are also significant.
Terhikki Manninen, Emmihenna Jääskeläinen, Niilo Siljamo, Aku Riihelä, and Karl-Göran Karlsson
Atmos. Meas. Tech., 15, 879–893, https://doi.org/10.5194/amt-15-879-2022, https://doi.org/10.5194/amt-15-879-2022, 2022
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A new method for cloud-correcting observations of surface albedo is presented for AVHRR data. Instead of a binary cloud mask, it applies cloud probability values smaller than 20% of the A3 edition of the CLARA (CM SAF cLoud, Albedo and surface Radiation dataset from AVHRR data) record provided by the Satellite Application Facility on Climate Monitoring (CM SAF) project of EUMETSAT. According to simulations, the 90% quantile was 1.1% for the absolute albedo error and 2.2% for the relative error.
Kimmo Korhonen, Thomas Bjerring Kristensen, John Falk, Vilhelm B. Malmborg, Axel Eriksson, Louise Gren, Maja Novakovic, Sam Shamun, Panu Karjalainen, Lassi Markkula, Joakim Pagels, Birgitta Svenningsson, Martin Tunér, Mika Komppula, Ari Laaksonen, and Annele Virtanen
Atmos. Chem. Phys., 22, 1615–1631, https://doi.org/10.5194/acp-22-1615-2022, https://doi.org/10.5194/acp-22-1615-2022, 2022
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We investigated the ice-nucleating abilities of particulate emissions from a modern diesel engine using the portable ice-nuclei counter SPIN, a continuous-flow diffusion chamber instrument. Three different fuels were studied without blending, including fossil diesel and two renewable fuels, testing different emission aftertreatment systems and photochemical aging. We found that the diesel emissions were inefficient ice nuclei, and aging had no or little effect on their ice-nucleating abilities.
Anna Rutgersson, Erik Kjellström, Jari Haapala, Martin Stendel, Irina Danilovich, Martin Drews, Kirsti Jylhä, Pentti Kujala, Xiaoli Guo Larsén, Kirsten Halsnæs, Ilari Lehtonen, Anna Luomaranta, Erik Nilsson, Taru Olsson, Jani Särkkä, Laura Tuomi, and Norbert Wasmund
Earth Syst. Dynam., 13, 251–301, https://doi.org/10.5194/esd-13-251-2022, https://doi.org/10.5194/esd-13-251-2022, 2022
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A natural hazard is a naturally occurring extreme event with a negative effect on people, society, or the environment; major events in the study area include wind storms, extreme waves, high and low sea level, ice ridging, heavy precipitation, sea-effect snowfall, river floods, heat waves, ice seasons, and drought. In the future, an increase in sea level, extreme precipitation, heat waves, and phytoplankton blooms is expected, and a decrease in cold spells and severe ice winters is anticipated.
Mika Rantanen, Kirsti Jylhä, Jani Särkkä, Jani Räihä, and Ulpu Leijala
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-314, https://doi.org/10.5194/nhess-2021-314, 2021
Revised manuscript not accepted
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Using sea level and precipitation observations, we analysed the meteorological characteristics of days when heavy precipitation and high sea level occur simultaneously in Finland. We found that around 5 % of all heavy precipitation and high sea level events on the Finnish coast are so called compound events when they both occur simultaneously, and these events were associated with close passages of mid-latitude cyclones. Our results act as a basis for compound flooding research in Finland.
Bin Cheng, Yubing Cheng, Timo Vihma, Anna Kontu, Fei Zheng, Juha Lemmetyinen, Yubao Qiu, and Jouni Pulliainen
Earth Syst. Sci. Data, 13, 3967–3978, https://doi.org/10.5194/essd-13-3967-2021, https://doi.org/10.5194/essd-13-3967-2021, 2021
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Climate change strongly impacts the Arctic, with clear signs of higher air temperature and more precipitation. A sustainable observation programme has been carried out in Lake Orajärvi in Sodankylä, Finland. The high-quality air–snow–ice–water temperature profiles have been measured every winter since 2009. The data can be used to investigate the lake ice surface heat balance and the role of snow in lake ice mass balance and parameterization of snow-to-ice transformation in snow/ice models.
Ana A. Piedehierro, André Welti, Angela Buchholz, Kimmo Korhonen, Iida Pullinen, Ilkka Summanen, Annele Virtanen, and Ari Laaksonen
Atmos. Chem. Phys., 21, 11069–11078, https://doi.org/10.5194/acp-21-11069-2021, https://doi.org/10.5194/acp-21-11069-2021, 2021
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Ice crystals in cirrus clouds contain particles that start ice formation. We study whether particles forming above boreal forests can help in the making of cirrus clouds and if the water content in the particles affects this property. In the laboratory, we made boreal-forest-like particles and cooled and humidified them to measure whether an ice crystal develops. We found that only when dry can these particles form an ice crystal but no better than solution droplets.
Pinja Venäläinen, Kari Luojus, Juha Lemmetyinen, Jouni Pulliainen, Mikko Moisander, and Matias Takala
The Cryosphere, 15, 2969–2981, https://doi.org/10.5194/tc-15-2969-2021, https://doi.org/10.5194/tc-15-2969-2021, 2021
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Information about snow water equivalent (SWE) is needed in many applications, including climate model evaluation and forecasting fresh water availability. Space-borne radiometer observations combined with ground snow depth measurements can be used to make global estimates of SWE. In this study, we investigate the possibility of using sparse snow density measurement in satellite-based SWE retrieval and show that using the snow density information in post-processing improves SWE estimations.
Pirkka Ollinaho, Glenn D. Carver, Simon T. K. Lang, Lauri Tuppi, Madeleine Ekblom, and Heikki Järvinen
Geosci. Model Dev., 14, 2143–2160, https://doi.org/10.5194/gmd-14-2143-2021, https://doi.org/10.5194/gmd-14-2143-2021, 2021
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OpenEnsemble 1.0 is a novel dataset that aims to open ensemble or probabilistic weather forecasting research up to the academic community. The dataset contains atmospheric states that are required for running model forecasts of atmospheric evolution. Our capacity to observe the atmosphere is limited; thus, a single reconstruction of the atmospheric state contains some errors. Our dataset provides sets of 50 slightly different atmospheric states so that these errors can be taken into account.
Joonas Merikanto, Kalle Nordling, Petri Räisänen, Jouni Räisänen, Declan O'Donnell, Antti-Ilari Partanen, and Hannele Korhonen
Atmos. Chem. Phys., 21, 5865–5881, https://doi.org/10.5194/acp-21-5865-2021, https://doi.org/10.5194/acp-21-5865-2021, 2021
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Human-induced aerosols concentrate around their emission sources, yet their climate effects span far and wide. Here, we use two climate models to robustly identify the mechanisms of how Asian anthropogenic aerosols impact temperatures across the globe. A total removal of Asian anthropogenic aerosols increases the global temperatures by 0.26 ± 0.04 °C in the models, with the strongest warming taking place over the Arctic due to increased atmospheric transport of energy towards the high north.
Terhikki Manninen, Kati Anttila, Emmihenna Jääskeläinen, Aku Riihelä, Jouni Peltoniemi, Petri Räisänen, Panu Lahtinen, Niilo Siljamo, Laura Thölix, Outi Meinander, Anna Kontu, Hanne Suokanerva, Roberta Pirazzini, Juha Suomalainen, Teemu Hakala, Sanna Kaasalainen, Harri Kaartinen, Antero Kukko, Olivier Hautecoeur, and Jean-Louis Roujean
The Cryosphere, 15, 793–820, https://doi.org/10.5194/tc-15-793-2021, https://doi.org/10.5194/tc-15-793-2021, 2021
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The primary goal of this paper is to present a model of snow surface albedo (brightness) accounting for small-scale surface roughness effects. It can be combined with any volume scattering model. The results indicate that surface roughness may decrease the albedo by about 1–3 % in midwinter and even more than 10 % during the late melting season. The effect is largest for low solar zenith angle values and lower bulk snow albedo values.
André Welti, Kimmo Korhonen, Pasi Miettinen, Ana A. Piedehierro, Yrjö Viisanen, Annele Virtanen, and Ari Laaksonen
Atmos. Meas. Tech., 13, 7059–7067, https://doi.org/10.5194/amt-13-7059-2020, https://doi.org/10.5194/amt-13-7059-2020, 2020
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We describe a modification of the SPectrometer for Ice Nuclei (SPIN) chamber to study ice nucleation at low temperatures, relevant for ice formation in cirrus clouds. Validation experiments of homogeneous freezing of aqueous ammonium sulfate droplets and heterogeneous ice nucleation on silver iodide particles are included to demonstrate the advantages of the modified SPIN chamber for the investigation of ice nucleation in the extended temperature range.
Lauri Tuppi, Pirkka Ollinaho, Madeleine Ekblom, Vladimir Shemyakin, and Heikki Järvinen
Geosci. Model Dev., 13, 5799–5812, https://doi.org/10.5194/gmd-13-5799-2020, https://doi.org/10.5194/gmd-13-5799-2020, 2020
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This paper presents general guidelines on how to utilise computer algorithms efficiently in order to tune weather models so that they would produce better forecasts. The main conclusions are that the computer algorithms work most efficiently with a suitable cost function, certain forecast length and ensemble size. We expect that our results will facilitate the use of algorithmic methods in the tuning of weather models.
Ari Laaksonen, Jussi Malila, and Athanasios Nenes
Atmos. Chem. Phys., 20, 13579–13589, https://doi.org/10.5194/acp-20-13579-2020, https://doi.org/10.5194/acp-20-13579-2020, 2020
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Aerosol particles containing black carbon are ubiquitous in the atmosphere and originate from combustion processes. We examine their capability to act as condensation centers for water vapor. We make use of published experimental data sets for different types of black carbon particles, ranging from very pure particles to particles that contain both black carbon and water soluble organic matter, and we show that a recently developed theory reproduces most of the experimental results.
Irina A. Statnaia, Alexey Y. Karpechko, and Heikki J. Järvinen
Weather Clim. Dynam., 1, 657–674, https://doi.org/10.5194/wcd-1-657-2020, https://doi.org/10.5194/wcd-1-657-2020, 2020
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In this paper we investigate the role of the tropospheric forcing in the occurrence of the sudden stratospheric warming (SSW) that took place in February 2018, its predictability and teleconnection with the Madden–Julian oscillation (MJO) by analysing the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecast. The purpose of the paper is to present the results of the analysis of the atmospheric circulation before and during the SSW and clarify the driving mechanisms.
Janne Lampilahti, Hanna Elina Manninen, Katri Leino, Riikka Väänänen, Antti Manninen, Stephany Buenrostro Mazon, Tuomo Nieminen, Matti Leskinen, Joonas Enroth, Marja Bister, Sergej Zilitinkevich, Juha Kangasluoma, Heikki Järvinen, Veli-Matti Kerminen, Tuukka Petäjä, and Markku Kulmala
Atmos. Chem. Phys., 20, 11841–11854, https://doi.org/10.5194/acp-20-11841-2020, https://doi.org/10.5194/acp-20-11841-2020, 2020
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In this work, by using co-located airborne and ground-based measurements, we show that counter-rotating horizontal circulations in the planetary boundary layer (roll vortices) frequently enhance regional new particle formation or induce localized bursts of new particle formation. These observations can be explained by the ability of the rolls to efficiently lift low-volatile vapors emitted from the surface to the top of the boundary layer where new particle formation is more favorable.
Natalia Korhonen, Otto Hyvärinen, Matti Kämäräinen, David S. Richardson, Heikki Järvinen, and Hilppa Gregow
Atmos. Chem. Phys., 20, 8441–8451, https://doi.org/10.5194/acp-20-8441-2020, https://doi.org/10.5194/acp-20-8441-2020, 2020
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Reanalysis data of the strength of the polar vortex is applied in the post-processing of the European Centre for Medium-Range Weather Forecasts (ECMWF) winter surface temperature forecasts for weeks 3–4 and 5–6 over northern Europe. In this way, the skill scores of these forecasts are slightly improved. It is also found that, in cases where the polar vortex was weak at the start of the forecast, the mean skill scores of these forecasts were higher than average.
Taru Olsson, Anna Luomaranta, Kirsti Jylhä, Julia Jeworrek, Tuuli Perttula, Christian Dieterich, Lichuan Wu, Anna Rutgersson, and Antti Mäkelä
Adv. Sci. Res., 17, 87–104, https://doi.org/10.5194/asr-17-87-2020, https://doi.org/10.5194/asr-17-87-2020, 2020
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Statistics of the frequency and intensity of snow bands affecting the Finnish coast during years 2000–2010 was conducted. A set of criteria for meteorological variables favoring the formation of the snow bands were applied to regional climate model (RCA4) data. We found on average three days per year with favorable conditions for coastal sea-effect snowfall. The heaviest convective snowfall events were detected most frequently over the southern coastline.
Jianwei Yang, Lingmei Jiang, Kari Luojus, Jinmei Pan, Juha Lemmetyinen, Matias Takala, and Shengli Wu
The Cryosphere, 14, 1763–1778, https://doi.org/10.5194/tc-14-1763-2020, https://doi.org/10.5194/tc-14-1763-2020, 2020
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There are many challenges for accurate snow depth estimation using passive microwave data. Machine learning (ML) techniques are deemed to be powerful tools for establishing nonlinear relations between independent variables and a given target variable. In this study, we investigate the potential capability of the random forest (RF) model on snow depth estimation at temporal and spatial scales. The result indicates that the fitted RF algorithms perform better on temporal than spatial scales.
Colleen Mortimer, Lawrence Mudryk, Chris Derksen, Kari Luojus, Ross Brown, Richard Kelly, and Marco Tedesco
The Cryosphere, 14, 1579–1594, https://doi.org/10.5194/tc-14-1579-2020, https://doi.org/10.5194/tc-14-1579-2020, 2020
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Existing stand-alone passive microwave SWE products have markedly different climatological SWE patterns compared to reanalysis-based datasets. The AMSR-E SWE has low spatial and temporal correlations with the four reanalysis-based products evaluated and GlobSnow and perform poorly in comparisons with snow transect data from Finland, Russia, and Canada. There is better agreement with in situ data when multiple SWE products, excluding the stand-alone passive microwave SWE products, are combined.
Henna-Reetta Hannula, Kirsikka Heinilä, Kristin Böttcher, Olli-Pekka Mattila, Miia Salminen, and Jouni Pulliainen
Earth Syst. Sci. Data, 12, 719–740, https://doi.org/10.5194/essd-12-719-2020, https://doi.org/10.5194/essd-12-719-2020, 2020
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We publish and describe a surface spectral reflectance data record of seasonal snow (dry, wet, shadowed), forest ground (lichen, moss) and forest canopy (spruce and pine, branches) constituting the main elements of the boreal landscape and collected at four scales. The data record describes the characteristics and variability of the satellite scene reflectance contributors in boreal landscape, thus enabling the development of improved optical satellite snow mapping methods for forested areas.
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.
Victoria A. Sinclair, Mika Rantanen, Päivi Haapanala, Jouni Räisänen, and Heikki Järvinen
Weather Clim. Dynam., 1, 1–25, https://doi.org/10.5194/wcd-1-1-2020, https://doi.org/10.5194/wcd-1-1-2020, 2020
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We studied how mid-latitude cyclones are likely to change in the future. We used a state-of-the-art numerical model and performed a control and a
warmexperiment. The total number of cyclones did not change with warming and neither did the average strength, but there were more stronger and more weaker storms in the warm experiment. Precipitation associated with the most extreme mid-latitude cyclones increased by up to 50 % and occurred in a more poleward location in the warmer experiment.
Aku Riihelä, Michalea D. King, and Kati Anttila
The Cryosphere, 13, 2597–2614, https://doi.org/10.5194/tc-13-2597-2019, https://doi.org/10.5194/tc-13-2597-2019, 2019
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We used a 1982–2015 time series of satellite observations to examine changes in surface reflectivity (albedo) of the Greenland Ice Sheet. We found notable decreases in albedo over most of the ice sheet margins in July and August, particularly over the west coast and between 2000 and 2015. The results indicate that significant melt now occurs in areas 50 to 100 m higher up the ice sheet relative to the early 1980s. The albedo decrease is consistent and covarying with modelled ice sheet mass loss.
Emilio Cuevas, Pedro Miguel Romero-Campos, Natalia Kouremeti, Stelios Kazadzis, Petri Räisänen, Rosa Delia García, Africa Barreto, Carmen Guirado-Fuentes, Ramón Ramos, Carlos Toledano, Fernando Almansa, and Julian Gröbner
Atmos. Meas. Tech., 12, 4309–4337, https://doi.org/10.5194/amt-12-4309-2019, https://doi.org/10.5194/amt-12-4309-2019, 2019
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A comprehensive comparison of more than 70 000 synchronous 1 min aerosol optical depth (AOD) data from 3 Global Atmosphere Watch precision filter radiometers (GAW-PFR) and 15 Aerosol Robotic Network Cimel radiometers (AERONET-Cimel) was performed for the four
nearwavelengths (380, 440, 500 and 870 nm) in the period 2005–2015. The goal of this study is to assess whether their long term AOD data are comparable and consistent.
Kalle Nordling, Hannele Korhonen, Petri Räisänen, Muzaffer Ege Alper, Petteri Uotila, Declan O'Donnell, and Joonas Merikanto
Atmos. Chem. Phys., 19, 9969–9987, https://doi.org/10.5194/acp-19-9969-2019, https://doi.org/10.5194/acp-19-9969-2019, 2019
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We carry out long equilibrium climate simulations with two modern climate models and show that the climate model dynamic response contributes strongly to the anthropogenic aerosol response. We demonstrate that identical aerosol descriptions do not improve climate model skill to estimate regional anthropogenic aerosol impacts. Our experiment utilized two independent climate models (NorESM and ECHAM6) with an identical description for aerosols optical properties and indirect effect.
Erika Toivonen, Marjo Hippi, Hannele Korhonen, Ari Laaksonen, Markku Kangas, and Joni-Pekka Pietikäinen
Geosci. Model Dev., 12, 3481–3501, https://doi.org/10.5194/gmd-12-3481-2019, https://doi.org/10.5194/gmd-12-3481-2019, 2019
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We evaluated the skill of the road weather model RoadSurf to reproduce present-day road weather conditions in Finland when driven by a high-resolution regional climate model. Simulated road surface temperatures and conditions were compared to observations between 2002 and 2014 at 25 Finnish road weather stations. RoadSurf accurately captured the main characteristics of road weather conditions. Thus, this model can be used to study the future scenarios of road weather in the study area.
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
Tuomo Nieminen, Veli-Matti Kerminen, Tuukka Petäjä, Pasi P. Aalto, Mikhail Arshinov, Eija Asmi, Urs Baltensperger, David C. S. Beddows, Johan Paul Beukes, Don Collins, Aijun Ding, Roy M. Harrison, Bas Henzing, Rakesh Hooda, Min Hu, Urmas Hõrrak, Niku Kivekäs, Kaupo Komsaare, Radovan Krejci, Adam Kristensson, Lauri Laakso, Ari Laaksonen, W. Richard Leaitch, Heikki Lihavainen, Nikolaos Mihalopoulos, Zoltán Németh, Wei Nie, Colin O'Dowd, Imre Salma, Karine Sellegri, Birgitta Svenningsson, Erik Swietlicki, Peter Tunved, Vidmantas Ulevicius, Ville Vakkari, Marko Vana, Alfred Wiedensohler, Zhijun Wu, Annele Virtanen, and Markku Kulmala
Atmos. Chem. Phys., 18, 14737–14756, https://doi.org/10.5194/acp-18-14737-2018, https://doi.org/10.5194/acp-18-14737-2018, 2018
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Atmospheric aerosols have diverse effects on air quality, human health, and global climate. One important source of aerosols is their formation via nucleation and growth in the atmosphere. We have analyzed long-term observations of regional new particle formation events around the globe and provide a comprehensive view on the characteristics of this phenomenon in diverse environments. The results are useful in developing more realistic representation of atmospheric aerosols in global models.
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.
Jorma Joutsensaari, Matthew Ozon, Tuomo Nieminen, Santtu Mikkonen, Timo Lähivaara, Stefano Decesari, M. Cristina Facchini, Ari Laaksonen, and Kari E. J. Lehtinen
Atmos. Chem. Phys., 18, 9597–9615, https://doi.org/10.5194/acp-18-9597-2018, https://doi.org/10.5194/acp-18-9597-2018, 2018
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New particle formation (NPF) in the atmosphere is globally an important source of aerosol particles. NPF events are typically identified and analyzed manually by researchers from particle size distribution data day by day, which is time consuming and might be inconsistent. We have developed an automatic analysis method based on deep learning for NPF event identification. The developed method can be easily utilized to analyze any long-term datasets more accurately and consistently.
Joni-Pekka Pietikäinen, Tiina Markkanen, Kevin Sieck, Daniela Jacob, Johanna Korhonen, Petri Räisänen, Yao Gao, Jaakko Ahola, Hannele Korhonen, Ari Laaksonen, and Jussi Kaurola
Geosci. Model Dev., 11, 1321–1342, https://doi.org/10.5194/gmd-11-1321-2018, https://doi.org/10.5194/gmd-11-1321-2018, 2018
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The regional climate model REMO was coupled with the FLake lake model to include an interactive treatment of lakes. Using this new version, the Fenno-Scandinavian climate and lake characteristics were studied. Our results show that overall the new model version improves the representation of the Fenno-Scandinavian climate in terms of 2 m temperature and precipitation and that the model can reproduce surface water temperature, ice depth and ice season length with reasonably high accuracy.
Andreas Kürten, Chenxi Li, Federico Bianchi, Joachim Curtius, António Dias, Neil M. Donahue, Jonathan Duplissy, Richard C. Flagan, Jani Hakala, Tuija Jokinen, Jasper Kirkby, Markku Kulmala, Ari Laaksonen, Katrianne Lehtipalo, Vladimir Makhmutov, Antti Onnela, Matti P. Rissanen, Mario Simon, Mikko Sipilä, Yuri Stozhkov, Jasmin Tröstl, Penglin Ye, and Peter H. McMurry
Atmos. Chem. Phys., 18, 845–863, https://doi.org/10.5194/acp-18-845-2018, https://doi.org/10.5194/acp-18-845-2018, 2018
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A recent laboratory study (CLOUD) showed that new particles nucleate efficiently from sulfuric acid and dimethylamine (DMA). The reanalysis of previously published data reveals that the nucleation rates are even faster than previously assumed, i.e., nucleation can proceed at rates that are compatible with collision-controlled new particle formation for atmospheric conditions. This indicates that sulfuric acid–DMA nucleation is likely an important source of particles in the boundary layer.
Petri Räisänen, Risto Makkonen, Alf Kirkevåg, and Jens B. Debernard
The Cryosphere, 11, 2919–2942, https://doi.org/10.5194/tc-11-2919-2017, https://doi.org/10.5194/tc-11-2919-2017, 2017
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While snow grains are non-spherical, spheres are often assumed in radiation calculations. Here, we replace spherical snow grains with non-spherical snow grains in a climate model. This leads to a somewhat higher snow albedo (by 0.02–0.03), increased snow and sea ice cover, and a distinctly colder climate (by over 1 K in the global mean). It also impacts the radiative effects of aerosols in snow. Overall, this work highlights the important role of snow albedo parameterization for climate models.
Elham Baranizadeh, Tuomo Nieminen, Taina Yli-Juuti, Markku Kulmala, Tuukka Petäjä, Ari Leskinen, Mika Komppula, Ari Laaksonen, and Kari E. J. Lehtinen
Atmos. Chem. Phys., 17, 13361–13371, https://doi.org/10.5194/acp-17-13361-2017, https://doi.org/10.5194/acp-17-13361-2017, 2017
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Extrapolation of the particle formation rates from one measured larger size (e.g., 7 nm) to smaller sizes (e.g., 3 nm) based on simplified growth-scavenging dynamics works fairly well to estimate mean daily formation rates, but it fails to predict the time evolution of the particle population. This points to the challenges in predicting atmospheric nucleation rates for locations where the particle growth and loss rates are size- and time-dependent.
Taru Olsson, Tuuli Perttula, Kirsti Jylhä, and Anna Luomaranta
Adv. Sci. Res., 14, 231–239, https://doi.org/10.5194/asr-14-231-2017, https://doi.org/10.5194/asr-14-231-2017, 2017
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A new national daily snowfall record was measured in Finland in January 2016 when it snowed 73 cm in less than a day at a small town on the western coast of Finland. The area of the most intense snowfall was very small, which is common in convective precipitation. In this work we used hourly weather radar images to identify the sea-effect snowfall case and found that a weather prediction model worked quite well in simulating the snowbands.
Laura Rontu, Emily Gleeson, Petri Räisänen, Kristian Pagh Nielsen, Hannu Savijärvi, and Bent Hansen Sass
Adv. Sci. Res., 14, 195–215, https://doi.org/10.5194/asr-14-195-2017, https://doi.org/10.5194/asr-14-195-2017, 2017
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This paper provides an overview of the HLRADIA shortwave (SW) and longwave (LW) broadband radiation schemes used in the HIRLAM numerical weather prediction (NWP) model and available in the HARMONIE-AROME mesoscale NWP model. The advantage of broadband, over spectral, schemes is that they can be called more frequently within the NWP model, without compromising on computational efficiency. Fast physically based radiation parametrizations are also valuable for high-resolution ensemble forecasting.
Päivi Haapanala, Petri Räisänen, Greg M. McFarquhar, Jussi Tiira, Andreas Macke, Michael Kahnert, John DeVore, and Timo Nousiainen
Atmos. Chem. Phys., 17, 6865–6882, https://doi.org/10.5194/acp-17-6865-2017, https://doi.org/10.5194/acp-17-6865-2017, 2017
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The dependence of solar-disk and circumsolar radiances on ice cloud
properties is studied with a Monte Carlo radiative transfer model. Ice
crystal roughness (or more generally, non-ideality) is found to be the
most important parameter influencing the circumsolar radiance, and ice
crystal sizes and shapes also play significant roles. When comparing
with radiances measured with the SAM instrument, rough ice crystals
reproduce the measurements better than idealized smooth ice crystals do.
Martin Wegmann, Yvan Orsolini, Emanuel Dutra, Olga Bulygina, Alexander Sterin, and Stefan Brönnimann
The Cryosphere, 11, 923–935, https://doi.org/10.5194/tc-11-923-2017, https://doi.org/10.5194/tc-11-923-2017, 2017
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We investigate long-term climate reanalyses datasets to infer their quality in reproducing snow depth values compared to in situ measured data from meteorological stations that go back to 1900. We found that the long-term reanalyses do a good job in reproducing snow depths but have some questionable snow states early in the 20th century. Thus, with care, climate reanalyses can be a valuable tool to investigate spatial snow evolution in global warming and climate change studies.
Matti Kämäräinen, Otto Hyvärinen, Kirsti Jylhä, Andrea Vajda, Simo Neiglick, Jaakko Nuottokari, and Hilppa Gregow
Nat. Hazards Earth Syst. Sci., 17, 243–259, https://doi.org/10.5194/nhess-17-243-2017, https://doi.org/10.5194/nhess-17-243-2017, 2017
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Freezing rain is a high-impact wintertime weather phenomenon. The direct damage it causes to critical infrastructure (transportation, communication and energy) and forestry can be substantial. In this work a method for estimating the occurrence of freezing rain was evaluated and used to derive the climatology. The method was able to accurately reproduce the observed, spatially aggregated annual variability. The highest frequencies of freezing rain were found in eastern and central Europe.
Mika Rantanen, Jouni Räisänen, Juha Lento, Oleg Stepanyuk, Olle Räty, Victoria A. Sinclair, and Heikki Järvinen
Geosci. Model Dev., 10, 827–841, https://doi.org/10.5194/gmd-10-827-2017, https://doi.org/10.5194/gmd-10-827-2017, 2017
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This paper describes new software OZO, which is a meteorological tool for both studying and research purposes. OZO can be used for investigating physical mechanisms affecting the development of extratropical cyclones. The software is an open-source tool and the distribution is supported by the authors. OZO will be used as a part of the author's PhD, in which the changes in cyclone dynamics due to warmer climate are studied.
Jarmo Mäkelä, Jouni Susiluoto, Tiina Markkanen, Mika Aurela, Heikki Järvinen, Ivan Mammarella, Stefan Hagemann, and Tuula Aalto
Nonlin. Processes Geophys., 23, 447–465, https://doi.org/10.5194/npg-23-447-2016, https://doi.org/10.5194/npg-23-447-2016, 2016
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The land-based hydrological cycle is one of the key processes controlling the growth and wilting of plants and the amount of carbon vegetation can assimilate. Recent studies have shown that many land surface models have biases in this area. We optimized parameters in one such model (JSBACH) and were able to enhance the model performance in many respects, but the response to drought remained unaffected. Further studies into this aspect should include alternative stomatal conductance formulations.
Hanna K. Lappalainen, Veli-Matti Kerminen, Tuukka Petäjä, Theo Kurten, Aleksander Baklanov, Anatoly Shvidenko, Jaana Bäck, Timo Vihma, Pavel Alekseychik, Meinrat O. Andreae, Stephen R. Arnold, Mikhail Arshinov, Eija Asmi, Boris Belan, Leonid Bobylev, Sergey Chalov, Yafang Cheng, Natalia Chubarova, Gerrit de Leeuw, Aijun Ding, Sergey Dobrolyubov, Sergei Dubtsov, Egor Dyukarev, Nikolai Elansky, Kostas Eleftheriadis, Igor Esau, Nikolay Filatov, Mikhail Flint, Congbin Fu, Olga Glezer, Aleksander Gliko, Martin Heimann, Albert A. M. Holtslag, Urmas Hõrrak, Juha Janhunen, Sirkku Juhola, Leena Järvi, Heikki Järvinen, Anna Kanukhina, Pavel Konstantinov, Vladimir Kotlyakov, Antti-Jussi Kieloaho, Alexander S. Komarov, Joni Kujansuu, Ilmo Kukkonen, Ella-Maria Duplissy, Ari Laaksonen, Tuomas Laurila, Heikki Lihavainen, Alexander Lisitzin, Alexsander Mahura, Alexander Makshtas, Evgeny Mareev, Stephany Mazon, Dmitry Matishov, Vladimir Melnikov, Eugene Mikhailov, Dmitri Moisseev, Robert Nigmatulin, Steffen M. Noe, Anne Ojala, Mari Pihlatie, Olga Popovicheva, Jukka Pumpanen, Tatjana Regerand, Irina Repina, Aleksei Shcherbinin, Vladimir Shevchenko, Mikko Sipilä, Andrey Skorokhod, Dominick V. Spracklen, Hang Su, Dmitry A. Subetto, Junying Sun, Arkady Y. Terzhevik, Yuri Timofeyev, Yuliya Troitskaya, Veli-Pekka Tynkkynen, Viacheslav I. Kharuk, Nina Zaytseva, Jiahua Zhang, Yrjö Viisanen, Timo Vesala, Pertti Hari, Hans Christen Hansson, Gennady G. Matvienko, Nikolai S. Kasimov, Huadong Guo, Valery Bondur, Sergej Zilitinkevich, and Markku Kulmala
Atmos. Chem. Phys., 16, 14421–14461, https://doi.org/10.5194/acp-16-14421-2016, https://doi.org/10.5194/acp-16-14421-2016, 2016
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After kick off in 2012, the Pan-Eurasian Experiment (PEEX) program has expanded fast and today the multi-disciplinary research community covers ca. 80 institutes and a network of ca. 500 scientists from Europe, Russia, and China. Here we introduce scientific topics relevant in this context. This is one of the first multi-disciplinary overviews crossing scientific boundaries, from atmospheric sciences to socio-economics and social sciences.
Heikki Järvinen, Teija Seitola, Johan Silén, and Jouni Räisänen
Geosci. Model Dev., 9, 4097–4109, https://doi.org/10.5194/gmd-9-4097-2016, https://doi.org/10.5194/gmd-9-4097-2016, 2016
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This study compares the 20th century multi-annual climate variability modes in reanalysis data sets (ERA-20C and 20CR) and 12 climate model simulations using the randomised multi-channel singular spectrum analysis. The reanalysis data sets are remarkably similar on all timescales, except that the spectral power in ERA-20C is systematically slightly higher than in 20CR. None of the climate models closely reproduce all aspects of the reanalysis spectra, although many aspects are represented well.
Juha Lemmetyinen, Anna Kontu, Jouni Pulliainen, Juho Vehviläinen, Kimmo Rautiainen, Andreas Wiesmann, Christian Mätzler, Charles Werner, Helmut Rott, Thomas Nagler, Martin Schneebeli, Martin Proksch, Dirk Schüttemeyer, Michael Kern, and Malcolm W. J. Davidson
Geosci. Instrum. Method. Data Syst., 5, 403–415, https://doi.org/10.5194/gi-5-403-2016, https://doi.org/10.5194/gi-5-403-2016, 2016
Elham Baranizadeh, Benjamin N. Murphy, Jan Julin, Saeed Falahat, Carly L. Reddington, Antti Arola, Lars Ahlm, Santtu Mikkonen, Christos Fountoukis, David Patoulias, Andreas Minikin, Thomas Hamburger, Ari Laaksonen, Spyros N. Pandis, Hanna Vehkamäki, Kari E. J. Lehtinen, and Ilona Riipinen
Geosci. Model Dev., 9, 2741–2754, https://doi.org/10.5194/gmd-9-2741-2016, https://doi.org/10.5194/gmd-9-2741-2016, 2016
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The molecular mechanisms through which new ultrafine (< 100 nm) aerosol particles are formed in the atmosphere have puzzled the scientific community for decades. In the past few years, however, significant progress has been made in unraveling these processes through laboratory studies and computational efforts. In this work we have implemented these new developments to an air quality model and study the implications of anthropogenically driven particle formation for European air quality.
Henna-Reetta Hannula, Juha Lemmetyinen, Anna Kontu, Chris Derksen, and Jouni Pulliainen
Geosci. Instrum. Method. Data Syst., 5, 347–363, https://doi.org/10.5194/gi-5-347-2016, https://doi.org/10.5194/gi-5-347-2016, 2016
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The paper described an extensive in situ data set of bulk snow depth, snow water equivalent, and snow density collected as a support of SnowSAR-2 airborne campaign in northern Finland. The spatial and temporal variability of these snow properties was analyzed in different land cover types. The success of the chosen measurement protocol to provide an accurate reference for the simultaneous SAR data products was analyzed in the context of spatial scale, sample size, and uncertainty.
Leena Leppänen, Anna Kontu, Henna-Reetta Hannula, Heidi Sjöblom, and Jouni Pulliainen
Geosci. Instrum. Method. Data Syst., 5, 163–179, https://doi.org/10.5194/gi-5-163-2016, https://doi.org/10.5194/gi-5-163-2016, 2016
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The manual snow survey program of Finnish Meteorological Institute consists of numerous observations of natural seasonal snowpack in Sodankylä, in northern Finland. Systematic snow measurements began in 1911 with snow depth and snow water equivalent. In 2006 the manual snow survey program expanded to cover snow macro- and microstructure from snow pits. Extensive time series of manual snow measurements are important for the monitoring of temporal and spatial changes in seasonal snowpack.
Jaakko Ikonen, Juho Vehviläinen, Kimmo Rautiainen, Tuomo Smolander, Juha Lemmetyinen, Simone Bircher, and Jouni Pulliainen
Geosci. Instrum. Method. Data Syst., 5, 95–108, https://doi.org/10.5194/gi-5-95-2016, https://doi.org/10.5194/gi-5-95-2016, 2016
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A comprehensive, distributed network of in situ measurement stations gathering information on soil moisture has been set up in recent years at the Finnish Meteorological Institute's (FMI) Sodankylä Arctic research station. The network is used as a tool to evaluate the validity of satellite retrievals of soil properties. We present the soil moisture observation network and the results of comparisons of top layer soil moisture between 2012 and 2014 against ESA CCI product soil moisture retrievals.
Jenni Kontkanen, Emma Järvinen, Hanna E. Manninen, Katrianne Lehtipalo, Juha Kangasluoma, Stefano Decesari, Gian Paolo Gobbi, Ari Laaksonen, Tuukka Petäjä, and Markku Kulmala
Atmos. Chem. Phys., 16, 1919–1935, https://doi.org/10.5194/acp-16-1919-2016, https://doi.org/10.5194/acp-16-1919-2016, 2016
J. Kim, L. Ahlm, T. Yli-Juuti, M. Lawler, H. Keskinen, J. Tröstl, S. Schobesberger, J. Duplissy, A. Amorim, F. Bianchi, N. M. Donahue, R. C. Flagan, J. Hakala, M. Heinritzi, T. Jokinen, A. Kürten, A. Laaksonen, K. Lehtipalo, P. Miettinen, T. Petäjä, M. P. Rissanen, L. Rondo, K. Sengupta, M. Simon, A. Tomé, C. Williamson, D. Wimmer, P. M. Winkler, S. Ehrhart, P. Ye, J. Kirkby, J. Curtius, U. Baltensperger, M. Kulmala, K. E. J. Lehtinen, J. N. Smith, I. Riipinen, and A. Virtanen
Atmos. Chem. Phys., 16, 293–304, https://doi.org/10.5194/acp-16-293-2016, https://doi.org/10.5194/acp-16-293-2016, 2016
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The hygroscopicity of nucleated nanoparticles was measured in the presence of sulfuric acid, sulfuric acid-dimethylamine, and sulfuric acid-organics derived from α-pinene oxidation during CLOUD7 at CERN in 2012. The hygroscopicity parameter κ decreased with increasing particle size, indicating decreasing acidity of particles.
A. Laaksonen and J. Malila
Atmos. Chem. Phys., 16, 135–143, https://doi.org/10.5194/acp-16-135-2016, https://doi.org/10.5194/acp-16-135-2016, 2016
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Heterogeneous nucleation is a phenomenon that starts the condensation of supersaturated vapours on solid surfaces. An example is the formation of cirrus clouds in the atmosphere: their formation is often triggered at relative humidities clearly above 100%. We derive a new theory that can be used to calculate the threshold supersaturation of heterogeneous nucleation of water vapour on nanoparticles and show that it performs significantly better than older theories when compared to lab experiment.
R. Pirazzini, P. Räisänen, T. Vihma, M. Johansson, and E.-M. Tastula
The Cryosphere, 9, 2357–2381, https://doi.org/10.5194/tc-9-2357-2015, https://doi.org/10.5194/tc-9-2357-2015, 2015
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We illustrate a method to measure the size distribution of a snow particle metric from macro photos of snow particles. This snow particle metric corresponds well to the optically equivalent effective radius. Our results evidence the impact of grain shape on albedo, indicate that more than just one particle metric distribution is needed to characterize the snow scattering properties at all optical wavelengths, and suggest an impact of surface roughness on the shortwave infrared albedo.
J. Joutsensaari, P. Yli-Pirilä, H. Korhonen, A. Arola, J. D. Blande, J. Heijari, M. Kivimäenpää, S. Mikkonen, L. Hao, P. Miettinen, P. Lyytikäinen-Saarenmaa, C. L. Faiola, A. Laaksonen, and J. K. Holopainen
Atmos. Chem. Phys., 15, 12139–12157, https://doi.org/10.5194/acp-15-12139-2015, https://doi.org/10.5194/acp-15-12139-2015, 2015
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Global warming will induce large-scale insect outbreaks in boreal forests. Our results from field and laboratory experiments, satellite observations and global-scale modelling suggest that more frequent insect outbreaks, in addition to temperature-dependent increases in VOC emissions, could result in substantial increases in biogenic SOA formation and therefore affect both aerosol direct and indirect forcing of climate at regional scales. This should be considered in future climate predictions.
O. Kemppinen, T. Nousiainen, S. Merikallio, and P. Räisänen
Atmos. Chem. Phys., 15, 11117–11132, https://doi.org/10.5194/acp-15-11117-2015, https://doi.org/10.5194/acp-15-11117-2015, 2015
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Combinations of simple mathematical model shapes called ellipsoids are used in many remote sensing and modeling applications to denote dust particles. In this study we investigate how accurately various physical parameters can be retrieved by using ellipsoids. The results show that using ellipsoids can lead to wrong results, while at the same time seeming like they work well. This means that extreme care should be used when using ellipsoids for dust, and extra validation measures should be used.
P. Räisänen, A. Kokhanovsky, G. Guyot, O. Jourdan, and T. Nousiainen
The Cryosphere, 9, 1277–1301, https://doi.org/10.5194/tc-9-1277-2015, https://doi.org/10.5194/tc-9-1277-2015, 2015
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While snow grains are distinctly non-spherical, spheres are often assumed in radiative transfer calculations. Here, angular scattering measurements for blowing snow are used to select an optically equivalent snow grain shape model. Parameterizations are then developed for the asymmetry parameter, single-scattering co-albedo and phase function of snow. The parameterizations will help to improve the treatment of snow in radiative transfer applications, including remote sensing and climate models.
E. Malnes, A. Buanes, T. Nagler, G. Bippus, D. Gustafsson, C. Schiller, S. Metsämäki, J. Pulliainen, K. Luojus, H. E. Larsen, R. Solberg, A. Diamandi, and A. Wiesmann
The Cryosphere, 9, 1191–1202, https://doi.org/10.5194/tc-9-1191-2015, https://doi.org/10.5194/tc-9-1191-2015, 2015
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The paper provides detailed information on the outcome of a user survey carried out in the EU FP7 project CryoLand. The project focuses on monitoring of seasonal snow, glaciers and lake/river ice. The user survey showed that a European operational snow and land ice service is required and that there exists products that can meet the specific needs. The majority of the users were mainly interested in the snow services, but also the lake/river ice products and the glacier products were desired.
J. Tonttila, E. J. O'Connor, A. Hellsten, A. Hirsikko, C. O'Dowd, H. Järvinen, and P. Räisänen
Atmos. Chem. Phys., 15, 5873–5885, https://doi.org/10.5194/acp-15-5873-2015, https://doi.org/10.5194/acp-15-5873-2015, 2015
J.-P. Pietikäinen, K. Kupiainen, Z. Klimont, R. Makkonen, H. Korhonen, R. Karinkanta, A.-P. Hyvärinen, N. Karvosenoja, A. Laaksonen, H. Lihavainen, and V.-M. Kerminen
Atmos. Chem. Phys., 15, 5501–5519, https://doi.org/10.5194/acp-15-5501-2015, https://doi.org/10.5194/acp-15-5501-2015, 2015
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The global aerosol--climate model ECHAM-HAMMOZ is used to study the aerosol burden and forcing changes in the coming decades. We show that aerosol burdens overall can have a decreasing trend leading to reductions in the direct aerosol effect being globally 0.06--0.4W/m2 by 2030, whereas the aerosol indirect radiative effect could decline 0.25--0.82W/m2. We also show that the targeted emission reduction measures can be a much better choice for the climate than overall high reductions globally.
H. Gregow, P. Poli, H. M. Mäkelä, K. Jylhä, A. K. Kaiser-Weiss, A. Obregon, D. G. H. Tan, S. Kekki, and F. Kaspar
Adv. Sci. Res., 12, 63–67, https://doi.org/10.5194/asr-12-63-2015, https://doi.org/10.5194/asr-12-63-2015, 2015
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Many users of climate information are unaware of the availability of reanalysis feedback data and input observations, and uptake of feedback data is rather low. The most important factors limiting the use of this data is that the users feel that there is no easy interface to get the data or they do not find it at all. The relevant communities should invest resources to develop tools and provide training to bridge the gap between current capabilities and comprehensive exploitation of the data.
M. Dalirian, H. Keskinen, L. Ahlm, A. Ylisirniö, S. Romakkaniemi, A. Laaksonen, A. Virtanen, and I. Riipinen
Atmos. Chem. Phys., 15, 3815–3829, https://doi.org/10.5194/acp-15-3815-2015, https://doi.org/10.5194/acp-15-3815-2015, 2015
H. Vuollekoski, M. Vogt, V. A. Sinclair, J. Duplissy, H. Järvinen, E.-M. Kyrö, R. Makkonen, T. Petäjä, N. L. Prisle, P. Räisänen, M. Sipilä, J. Ylhäisi, and M. Kulmala
Hydrol. Earth Syst. Sci., 19, 601–613, https://doi.org/10.5194/hess-19-601-2015, https://doi.org/10.5194/hess-19-601-2015, 2015
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The global potential for collecting usable water from dew on an
artificial collector sheet was investigated by utilising 34 years of
meteorological reanalysis data as input to a dew formation model. Continental dew formation was found to be frequent and common, but daily yields were
mostly below 0.1mm.
J. Tonttila, H. Järvinen, and P. Räisänen
Atmos. Chem. Phys., 15, 703–714, https://doi.org/10.5194/acp-15-703-2015, https://doi.org/10.5194/acp-15-703-2015, 2015
S. Schobesberger, A. Franchin, F. Bianchi, L. Rondo, J. Duplissy, A. Kürten, I. K. Ortega, A. Metzger, R. Schnitzhofer, J. Almeida, A. Amorim, J. Dommen, E. M. Dunne, M. Ehn, S. Gagné, L. Ickes, H. Junninen, A. Hansel, V.-M. Kerminen, J. Kirkby, A. Kupc, A. Laaksonen, K. Lehtipalo, S. Mathot, A. Onnela, T. Petäjä, F. Riccobono, F. D. Santos, M. Sipilä, A. Tomé, G. Tsagkogeorgas, Y. Viisanen, P. E. Wagner, D. Wimmer, J. Curtius, N. M. Donahue, U. Baltensperger, M. Kulmala, and D. R. Worsnop
Atmos. Chem. Phys., 15, 55–78, https://doi.org/10.5194/acp-15-55-2015, https://doi.org/10.5194/acp-15-55-2015, 2015
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We used an ion mass spectrometer at CERN's CLOUD chamber to investigate the detailed composition of ammonia--sulfuric acid ion clusters (of both polarities) as they initially form and then grow into aerosol particles, at atmospherically relevant conditions. We found that these clusters’ composition is mainly determined by the ratio of the precursor vapors and ranges from ammonia-free clusters to clusters containing > 1 ammonia per sulfuric acid. Acid--base bindings are a key formation mechanism.
L. Q. Hao, A. Kortelainen, S. Romakkaniemi, H. Portin, A. Jaatinen, A. Leskinen, M. Komppula, P. Miettinen, D. Sueper, A. Pajunoja, J. N. Smith, K. E. J. Lehtinen, D. R. Worsnop, A. Laaksonen, and A. Virtanen
Atmos. Chem. Phys., 14, 13483–13495, https://doi.org/10.5194/acp-14-13483-2014, https://doi.org/10.5194/acp-14-13483-2014, 2014
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Positive matrix factorization (PMF) was applied to the unified high-resolution mass spectra organic species with NO+ and NO2+ ions from the measurement in a mixed region between the boreal forestland and the urban area. The PMF analysis succeeded in separating the mixed spectra into three distinct organic factors and one inorganic factor. The particulate organic nitrate was distinguished by PMF for the first time, with a contribution of one-third of the total nitrate mass.
Y. Gao, T. Markkanen, L. Backman, H. M. Henttonen, J.-P. Pietikäinen, H. M. Mäkelä, and A. Laaksonen
Biogeosciences, 11, 7251–7267, https://doi.org/10.5194/bg-11-7251-2014, https://doi.org/10.5194/bg-11-7251-2014, 2014
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This work studies the biogeophysical impacts of peatland forestation on regional climate conditions in Finland by a regional climate model with two land cover maps produced from Finnish national forest inventories. A warming in spring and a slight cooling in the growing season are found in peatland forestation area, which are mainly induced by the decreased surface albedo and increased ET, respectively. The snow clearance days are advanced. The results are also compared with observational data.
J.-P. Pietikäinen, S. Mikkonen, A. Hamed, A. I. Hienola, W. Birmili, M. Kulmala, and A. Laaksonen
Atmos. Chem. Phys., 14, 11711–11729, https://doi.org/10.5194/acp-14-11711-2014, https://doi.org/10.5194/acp-14-11711-2014, 2014
S. V. Henriksson, J.-P. Pietikäinen, A.-P. Hyvärinen, P. Räisänen, K. Kupiainen, J. Tonttila, R. Hooda, H. Lihavainen, D. O'Donnell, L. Backman, Z. Klimont, and A. Laaksonen
Atmos. Chem. Phys., 14, 10177–10192, https://doi.org/10.5194/acp-14-10177-2014, https://doi.org/10.5194/acp-14-10177-2014, 2014
P. Ollinaho, H. Järvinen, P. Bauer, M. Laine, P. Bechtold, J. Susiluoto, and H. Haario
Geosci. Model Dev., 7, 1889–1900, https://doi.org/10.5194/gmd-7-1889-2014, https://doi.org/10.5194/gmd-7-1889-2014, 2014
M. S. Johnston, S. Eliasson, P. Eriksson, R. M. Forbes, A. Gettelman, P. Räisänen, and M. D. Zelinka
Atmos. Chem. Phys., 14, 8701–8721, https://doi.org/10.5194/acp-14-8701-2014, https://doi.org/10.5194/acp-14-8701-2014, 2014
N. Korhonen, A. Venäläinen, H. Seppä, and H. Järvinen
Clim. Past, 10, 1489–1500, https://doi.org/10.5194/cp-10-1489-2014, https://doi.org/10.5194/cp-10-1489-2014, 2014
M. Abbas, A. Ilin, A. Solonen, J. Hakkarainen, E. Oja, and H. Järvinen
Nonlin. Processes Geophys. Discuss., https://doi.org/10.5194/npgd-1-1283-2014, https://doi.org/10.5194/npgd-1-1283-2014, 2014
Revised manuscript not accepted
H. Portin, A. Leskinen, L. Hao, A. Kortelainen, P. Miettinen, A. Jaatinen, A. Laaksonen, K. E. J. Lehtinen, S. Romakkaniemi, and M. Komppula
Atmos. Chem. Phys., 14, 6021–6034, https://doi.org/10.5194/acp-14-6021-2014, https://doi.org/10.5194/acp-14-6021-2014, 2014
J. Bialek, M. Dall Osto, P. Vaattovaara, S. Decesari, J. Ovadnevaite, A. Laaksonen, and C. O'Dowd
Atmos. Chem. Phys., 14, 1557–1570, https://doi.org/10.5194/acp-14-1557-2014, https://doi.org/10.5194/acp-14-1557-2014, 2014
P. Ollinaho, P. Bechtold, M. Leutbecher, M. Laine, A. Solonen, H. Haario, and H. Järvinen
Nonlin. Processes Geophys., 20, 1001–1010, https://doi.org/10.5194/npg-20-1001-2013, https://doi.org/10.5194/npg-20-1001-2013, 2013
C. E. Chung, H. Cha, T. Vihma, P. Räisänen, and D. Decremer
Atmos. Chem. Phys., 13, 11209–11219, https://doi.org/10.5194/acp-13-11209-2013, https://doi.org/10.5194/acp-13-11209-2013, 2013
J. Tonttila, P. Räisänen, and H. Järvinen
Atmos. Chem. Phys., 13, 7551–7565, https://doi.org/10.5194/acp-13-7551-2013, https://doi.org/10.5194/acp-13-7551-2013, 2013
H. Keskinen, A. Virtanen, J. Joutsensaari, G. Tsagkogeorgas, J. Duplissy, S. Schobesberger, M. Gysel, F. Riccobono, J. G. Slowik, F. Bianchi, T. Yli-Juuti, K. Lehtipalo, L. Rondo, M. Breitenlechner, A. Kupc, J. Almeida, A. Amorim, E. M. Dunne, A. J. Downard, S. Ehrhart, A. Franchin, M.K. Kajos, J. Kirkby, A. Kürten, T. Nieminen, V. Makhmutov, S. Mathot, P. Miettinen, A. Onnela, T. Petäjä, A. Praplan, F. D. Santos, S. Schallhart, M. Sipilä, Y. Stozhkov, A. Tomé, P. Vaattovaara, D. Wimmer, A. Prevot, J. Dommen, N. M. Donahue, R.C. Flagan, E. Weingartner, Y. Viisanen, I. Riipinen, A. Hansel, J. Curtius, M. Kulmala, D. R. Worsnop, U. Baltensperger, H. Wex, F. Stratmann, and A. Laaksonen
Atmos. Chem. Phys., 13, 5587–5600, https://doi.org/10.5194/acp-13-5587-2013, https://doi.org/10.5194/acp-13-5587-2013, 2013
K.-G. Karlsson, A. Riihelä, R. Müller, J. F. Meirink, J. Sedlar, M. Stengel, M. Lockhoff, J. Trentmann, F. Kaspar, R. Hollmann, and E. Wolters
Atmos. Chem. Phys., 13, 5351–5367, https://doi.org/10.5194/acp-13-5351-2013, https://doi.org/10.5194/acp-13-5351-2013, 2013
A. Riihelä, T. Manninen, V. Laine, K. Andersson, and F. Kaspar
Atmos. Chem. Phys., 13, 3743–3762, https://doi.org/10.5194/acp-13-3743-2013, https://doi.org/10.5194/acp-13-3743-2013, 2013
T. Viskari, E. Asmi, P. Kolmonen, H. Vuollekoski, T. Petäjä, and H. Järvinen
Atmos. Chem. Phys., 12, 11767–11779, https://doi.org/10.5194/acp-12-11767-2012, https://doi.org/10.5194/acp-12-11767-2012, 2012
T. Viskari, E. Asmi, A. Virkkula, P. Kolmonen, T. Petäjä, and H. Järvinen
Atmos. Chem. Phys., 12, 11781–11793, https://doi.org/10.5194/acp-12-11781-2012, https://doi.org/10.5194/acp-12-11781-2012, 2012
Related subject area
Climate and Earth system modeling
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Evaluation of CMIP6 model simulations of PM2.5 and its components over China
Assessment of a tiling energy budget approach in a land surface model, ORCHIDEE-MICT (r8205)
Multivariate adjustment of drizzle bias using machine learning in European climate projections
Development and evaluation of the interactive Model for Air Pollution and Land Ecosystems (iMAPLE) version 1.0
A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)
Parallel SnowModel (v1.0): a parallel implementation of a distributed snow-evolution modeling system (SnowModel)
LB-SCAM: a learning-based method for efficient large-scale sensitivity analysis and tuning of the Single Column Atmosphere Model (SCAM)
Quantifying the impact of SST feedback frequency on Madden–Julian oscillation simulations
Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3
A revised model of global silicate weathering considering the influence of vegetation cover on erosion rate
A radiative–convective model computing precipitation with the maximum entropy production hypothesis
Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0
Machine learning parameterization of the multi-scale Kain–Fritsch (MSKF) convection scheme and stable simulation coupled in the Weather Research and Forecasting (WRF) model using WRF–ML v1.0
Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model
cfr (v2024.1.26): a Python package for climate field reconstruction
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
Evaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1
A comprehensive Earth system model (AWI-ESM2.1) with interactive icebergs: effects on surface and deep-ocean characteristics
The regional climate–chemistry–ecology coupling model RegCM-Chem (v4.6)–YIBs (v1.0): development and application
An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1
The computational and energy cost of simulation and storage for climate science: lessons from CMIP6
Subgrid-scale variability of cloud ice in the ICON-AES 1.3.00
INFERNO-peat v1.0.0: a representation of northern high-latitude peat fires in the JULES-INFERNO global fire model
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Continental-scale bias-corrected climate and hydrological projections for Australia
G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies
Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)
DCMIP2016: the tropical cyclone test case
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
Applying double-cropping and interactive irrigation in the North China Plain using WRF4.5
CD-type discretization for sea ice dynamics in FESOM version 2
Dynamic MJO forecasts using an ensemble subseasonal-to-seasonal forecast system of IAP-CAS model
CSDMS Data Components: data–model integration tools for Earth surface processes modeling
A generic algorithm to automatically classify urban fabric according to the local climate zone system: implementation in GeoClimate 0.0.1 and application to French cities
Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)
Localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output
Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space
A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1
Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3
Flux coupling approach on an exchange grid for the IOW Earth System Model (version 1.04.00) of the Baltic Sea region
Using EUREC4A/ATOMIC field campaign data to improve trade wind regimes in the Community Atmosphere Model
New model ensemble reveals how forcing uncertainty and model structure alter climate simulated across CMIP generations of the Community Earth System Model
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
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This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
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We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
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Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
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To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
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This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
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All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
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In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
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Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
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Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
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Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion driven by either uniform erosion where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea-level history, material properties, and the relative influence of different erosional processes.
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024, https://doi.org/10.5194/gmd-17-3385-2024, 2024
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In this paper, we coupled the SURFEX and MEGAN models. The aim of this coupling is to improve the estimation of biogenic fluxes by using the SURFEX canopy environment model. The coupled model results were validated and several sensitivity tests were performed. The coupled-model total annual isoprene flux is 442 Tg; this value is within the range of other isoprene estimates reported. The ultimate aim of this coupling is to predict the impact of climate change on biogenic emissions.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
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We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
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Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
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We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
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Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
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Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
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We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
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This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
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The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
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This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-38, https://doi.org/10.5194/gmd-2024-38, 2024
Revised manuscript accepted for GMD
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
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Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1, https://doi.org/10.5194/egusphere-2024-1, 2024
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This article gives an overview introduction of the IAP-CAS S2S (sub-seasonal to seasonal) ensemble forecasting system and MJO forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its advantages but also exhibits some biases, including underdispersive ensemble, overestimated amplitude and faster propagation speed when forecasting MJO. We also provide the explanation towards these biases and prospects for further improvement of this system in the future.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
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This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
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Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
EGUsphere, https://doi.org/10.5194/egusphere-2024-335, https://doi.org/10.5194/egusphere-2024-335, 2024
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Large volcanic eruptions deposit material into the upper-atmosphere, which is capable of altering temperature and wind patterns of the Earth's atmosphere for years following. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a testbed for climate attribution studies.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Peters, Bjørn Hallvard Samset, Benjamin M. Sanderson, and Ragnhild Bieltvedt Skeie
EGUsphere, https://doi.org/10.5194/egusphere-2024-196, https://doi.org/10.5194/egusphere-2024-196, 2024
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The CICERO-SCM has existed as a FORTRAN model since 1999 and consists of a part that calculates radiative forcing and concentrations from emissions, and an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper we describe an updated version ported to python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
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Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
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As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
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In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
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This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
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A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
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Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
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Short summary
Snowmelt influences greatly the climatic conditions in spring. This study evaluates the timing of springtime end of snowmelt in the ECHAM5 model. A key finding is that, in much of northern Eurasia, snow disappears too early in ECHAM5, in spite of a slight cold bias in spring. This points to the need for a more comprehensive treatment of the surface energy budget. In particular, the surface temperature for the snow-covered and snow-free parts of a climate model grid cell should be separated.
Snowmelt influences greatly the climatic conditions in spring. This study evaluates the timing...
