Articles | Volume 16, issue 16
https://doi.org/10.5194/gmd-16-4853-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-4853-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
ModE-Sim – a medium-sized atmospheric general circulation model (AGCM) ensemble to study climate variability during the modern era (1420 to 2009)
Institute of Geography, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Eric Samakinwa
Institute of Geography, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Laura Lipfert
Institute of Geography, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Stefan Brönnimann
Institute of Geography, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
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Richard Warren, Niklaus Emanuel Bartlome, Noémie Wellinger, Jörg Franke, Ralf Hand, Stefan Brönnimann, and Heli Huhtamaa
Clim. Past, 20, 2645–2662, https://doi.org/10.5194/cp-20-2645-2024, https://doi.org/10.5194/cp-20-2645-2024, 2024
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This paper introduces the ClimeApp web application. The app provides quick access to the ModE-RA global climate reanalysis. Users can calculate and plot anomalies, composites, correlations, regressions and annual cycles across three different datasets and four climate variables. By re-examining the 1815 Tambora eruption, we demonstrate how combining results from different datasets and sources can help us investigate the historical palaeoclimate and integrate it into human history.
Eric Samakinwa, Christoph C. Raible, Ralf Hand, Andrew R. Friedman, and Stefan Brönnimann
Clim. Past Discuss., https://doi.org/10.5194/cp-2023-67, https://doi.org/10.5194/cp-2023-67, 2023
Publication in CP not foreseen
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In this study, we nudged a stand-alone ocean model MPI-OM to proxy-reconstructed SST. Based on these model simulations, we introduce new estimates of the AMOC variations during the period 1450–1780 through a 10-member ensemble simulation with a novel nudging technique. Our approach reaffirms the known mechanisms of AMOC variability and also improves existing knowledge of the interplay between the AMOC and the NAO during the AMOC's weak and strong phases.
Chantal Camenisch, Fernando Jaume-Santero, Sam White, Qing Pei, Ralf Hand, Christian Rohr, and Stefan Brönnimann
Clim. Past, 18, 2449–2462, https://doi.org/10.5194/cp-18-2449-2022, https://doi.org/10.5194/cp-18-2449-2022, 2022
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We present a novel approach to assimilate climate information contained in chronicles and annals from the 15th century to generate climate reconstructions of the Burgundian Low Countries, taking into account uncertainties associated with the descriptions of narrative sources. Our study aims to be a first step towards a more quantitative use of available information contained in historical texts, showing how Bayesian inference can help the climate community with this endeavor.
Stefan Brönnimann, Peter Stucki, Jörg Franke, Veronika Valler, Yuri Brugnara, Ralf Hand, Laura C. Slivinski, Gilbert P. Compo, Prashant D. Sardeshmukh, Michel Lang, and Bettina Schaefli
Clim. Past, 18, 919–933, https://doi.org/10.5194/cp-18-919-2022, https://doi.org/10.5194/cp-18-919-2022, 2022
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Floods in Europe vary on time scales of several decades. Flood-rich and flood-poor periods alternate. Recently floods have again become more frequent. Long time series of peak stream flow, precipitation, and atmospheric variables reveal that until around 1980, these changes were mostly due to changes in atmospheric circulation. However, in recent decades the role of increasing atmospheric moisture due to climate warming has become more important and is now the main driver of flood changes.
Richard Warren, Niklaus Emanuel Bartlome, Noémie Wellinger, Jörg Franke, Ralf Hand, Stefan Brönnimann, and Heli Huhtamaa
Clim. Past, 20, 2645–2662, https://doi.org/10.5194/cp-20-2645-2024, https://doi.org/10.5194/cp-20-2645-2024, 2024
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This paper introduces the ClimeApp web application. The app provides quick access to the ModE-RA global climate reanalysis. Users can calculate and plot anomalies, composites, correlations, regressions and annual cycles across three different datasets and four climate variables. By re-examining the 1815 Tambora eruption, we demonstrate how combining results from different datasets and sources can help us investigate the historical palaeoclimate and integrate it into human history.
Nicolas Duque-Gardeazabal, Andrew R. Friedman, and Stefan Brönnimann
EGUsphere, https://doi.org/10.5194/egusphere-2024-2846, https://doi.org/10.5194/egusphere-2024-2846, 2024
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Understanding hydrological variability is essential for ecological conservation and sustainable development. Evapotranspiration influences the carbon cycle, finding what causes its variability is important for ecosystems. This study shows that not only El Niño – ENSO influences South America’s rainfall and evaporation, but also other phenomena in the Atlantic Ocean. The impacts change depending on the season, impacting the Amazon and Orinoco basins.
Peter Stucki, Lucas Pfister, Yuri Brugnara, Renate Varga, Chantal Hari, and Stefan Brönnimann
Clim. Past, 20, 2327–2348, https://doi.org/10.5194/cp-20-2327-2024, https://doi.org/10.5194/cp-20-2327-2024, 2024
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In our work, we reconstruct the weather of the extremely cold and wet summer in 1816 using a weather forecasting model to obtain high-resolution, three-dimensional weather simulations. We refine our simulations with surface pressure and temperature observations, representing a novel approach for this period. Our results show that this approach yields detailed and accurate weather reconstructions, opening the door to analyzing past weather events and their impacts in detail.
Stefan Brönnimann, Janusz Filipiak, Siyu Chen, and Lucas Pfister
Clim. Past, 20, 2219–2235, https://doi.org/10.5194/cp-20-2219-2024, https://doi.org/10.5194/cp-20-2219-2024, 2024
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The year 1740 was the coldest in central Europe since at least 1421. New monthly global climate reconstructions, together with daily weather reconstructions, allow a detailed view of this climatic event. Following several severe cold spells in January and February, a persistent circulation pattern with blocking over the British Isles caused northerly flow towards western Europe during a large part of the year. It was one of the strongest, arguably unforced excursions in European temperature.
Christian Pfister, Stefan Brönnimann, Andres Altwegg, Rudolf Brázdil, Laurent Litzenburger, Daniele Lorusso, and Thomas Pliemon
Clim. Past, 20, 1387–1399, https://doi.org/10.5194/cp-20-1387-2024, https://doi.org/10.5194/cp-20-1387-2024, 2024
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This bottle of Riesling from the traditional Bassermann Jordan winery in Deidesheim (Germany) is a relic of the premium wine harvested in 1811. It was named “Comet Wine” after the bright comet that year. The study shows that wine quality can be used to infer summer weather conditions over the past 600 years. After rainy summers with cold winds, wines turned sour, while long periods of high pressure led to excellent qualities. Since 1990, only good wines have been produced due to rapid warming.
Lucas Pfister, Lena Wilhelm, Yuri Brugnara, Noemi Imfeld, and Stefan Brönnimann
EGUsphere, https://doi.org/10.5194/egusphere-2024-1346, https://doi.org/10.5194/egusphere-2024-1346, 2024
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Our work compares different machine learning approaches for creating long-term classifications of daily atmospheric circulation patterns using input data from surface meteorological observations. Our comparison reveals a so-called feedforward neural network to perform best in this task. Using this model, we present a daily reconstruction of the CAP9 weather type classification for Central Europe back to 1728.
Stefan Brönnimann, Yuri Brugnara, and Clive Wilkinson
Clim. Past, 20, 757–767, https://doi.org/10.5194/cp-20-757-2024, https://doi.org/10.5194/cp-20-757-2024, 2024
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The early 20th century warming – the first phase of global warming in the 20th century – started from a peculiar cold state around 1910. We digitised additional ship logbooks for these years to study this specific climate state and found that it is real and likely an overlap of several climatic anomalies, including oceanic variability (La Niña) and volcanic eruptions.
Noemi Imfeld, Koen Hufkens, and Stefan Brönnimann
Clim. Past, 20, 659–682, https://doi.org/10.5194/cp-20-659-2024, https://doi.org/10.5194/cp-20-659-2024, 2024
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Climate and weather in spring are important because they can have far-reaching impacts, e.g. on plant growth, due to cold spells. Here, we study changes in climate and phenological indices for the period from 1763 to 2020 based on newly published reconstructed fields of daily temperature and precipitation for Switzerland. We look at three cases of extreme spring conditions, namely a warm spring in 1862, two frost events in 1873 and 1957, and three cold springs in 1785, 1837, and 1852.
Eric Samakinwa, Christoph C. Raible, Ralf Hand, Andrew R. Friedman, and Stefan Brönnimann
Clim. Past Discuss., https://doi.org/10.5194/cp-2023-67, https://doi.org/10.5194/cp-2023-67, 2023
Publication in CP not foreseen
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In this study, we nudged a stand-alone ocean model MPI-OM to proxy-reconstructed SST. Based on these model simulations, we introduce new estimates of the AMOC variations during the period 1450–1780 through a 10-member ensemble simulation with a novel nudging technique. Our approach reaffirms the known mechanisms of AMOC variability and also improves existing knowledge of the interplay between the AMOC and the NAO during the AMOC's weak and strong phases.
Stefan Brönnimann and Yuri Brugnara
Clim. Past, 19, 1435–1445, https://doi.org/10.5194/cp-19-1435-2023, https://doi.org/10.5194/cp-19-1435-2023, 2023
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We present the weather diaries of the Kirch family from 1677–1774 containing weather observations made in Leipzig and Guben and, from 1701 onward, instrumental observations made in Berlin. We publish the imaged diaries (10 445 images) and the digitized measurements (from 1720 onward). This is one of the oldest and longest meteorological records from Germany. The digitized pressure data show good agreement with neighbouring stations, highlighting their potential for weather reconstruction.
Stefan Brönnimann
Clim. Past, 19, 1345–1357, https://doi.org/10.5194/cp-19-1345-2023, https://doi.org/10.5194/cp-19-1345-2023, 2023
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Weather reconstructions could help us to better understand the mechanisms leading to, and the impacts caused by, climatic changes. This requires daily weather information such as diaries. Here I present the weather diary by Georg Christoph Eimmart from Nuremberg covering the period 1695–1704. This was a particularly cold period in Europe, and the diary helps to better characterize this climatic anomaly.
Noemi Imfeld, Lucas Pfister, Yuri Brugnara, and Stefan Brönnimann
Clim. Past, 19, 703–729, https://doi.org/10.5194/cp-19-703-2023, https://doi.org/10.5194/cp-19-703-2023, 2023
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Climate reconstructions give insights into monthly and seasonal climate variability of the past few hundred years. However, to understand past extreme weather events and to relate them to impacts, for example to periods of extreme floods, reconstructions on a daily timescale are needed. Here, we present a reconstruction of 258 years of high-resolution daily temperature and precipitation fields for Switzerland covering the period 1763 to 2020, which is based on instrumental measurements.
Moritz Buchmann, Gernot Resch, Michael Begert, Stefan Brönnimann, Barbara Chimani, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 17, 653–671, https://doi.org/10.5194/tc-17-653-2023, https://doi.org/10.5194/tc-17-653-2023, 2023
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Our current knowledge of spatial and temporal snow depth trends is based almost exclusively on time series of non-homogenised observational data. However, like other long-term series from observations, they are susceptible to inhomogeneities that can affect the trends and even change the sign. To assess the relevance of homogenisation for daily snow depths, we investigated its impact on trends and changes in extreme values of snow indices between 1961 and 2021 in the Swiss observation network.
Jianquan Dong, Stefan Brönnimann, Tao Hu, Yanxu Liu, and Jian Peng
Earth Syst. Sci. Data, 14, 5651–5664, https://doi.org/10.5194/essd-14-5651-2022, https://doi.org/10.5194/essd-14-5651-2022, 2022
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We produced a new dataset of global station-based daily maximum wet-bulb temperature (GSDM-WBT) through the calculation of wet-bulb temperature, data quality control, infilling missing values, and homogenization. The GSDM-WBT covers the complete daily series of 1834 stations from 1981 to 2020. The GSDM-WBT dataset handles stations with many missing values and possible inhomogeneities, which could better support the studies on global and regional humid heat events.
Duncan Pappert, Mariano Barriendos, Yuri Brugnara, Noemi Imfeld, Sylvie Jourdain, Rajmund Przybylak, Christian Rohr, and Stefan Brönnimann
Clim. Past, 18, 2545–2565, https://doi.org/10.5194/cp-18-2545-2022, https://doi.org/10.5194/cp-18-2545-2022, 2022
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We present daily temperature and sea level pressure fields for Europe for the severe winter 1788/1789 based on historical meteorological measurements and an analogue reconstruction approach. The resulting reconstruction skilfully reproduces temperature and pressure variations over central and western Europe. We find intense blocking systems over northern Europe and several abrupt, strong cold air outbreaks, demonstrating that quantitative weather reconstruction of past extremes is possible.
Chantal Camenisch, Fernando Jaume-Santero, Sam White, Qing Pei, Ralf Hand, Christian Rohr, and Stefan Brönnimann
Clim. Past, 18, 2449–2462, https://doi.org/10.5194/cp-18-2449-2022, https://doi.org/10.5194/cp-18-2449-2022, 2022
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We present a novel approach to assimilate climate information contained in chronicles and annals from the 15th century to generate climate reconstructions of the Burgundian Low Countries, taking into account uncertainties associated with the descriptions of narrative sources. Our study aims to be a first step towards a more quantitative use of available information contained in historical texts, showing how Bayesian inference can help the climate community with this endeavor.
Yuri Brugnara, Chantal Hari, Lucas Pfister, Veronika Valler, and Stefan Brönnimann
Clim. Past, 18, 2357–2379, https://doi.org/10.5194/cp-18-2357-2022, https://doi.org/10.5194/cp-18-2357-2022, 2022
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We digitized dozens of weather journals containing temperature measurements from in and around Bern and Zurich. They cover over a century before the creation of a national weather service in Switzerland. With these data we could create daily temperature series for the two cities that span the last 265 years. We found that the pre-industrial climate on the Swiss Plateau was colder than suggested by previously available instrumental data sets and about 2.5 °C colder than the present-day climate.
Gilles Delaygue, Stefan Brönnimann, and Philip D. Jones
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2022-33, https://doi.org/10.5194/wcd-2022-33, 2022
Revised manuscript not accepted
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We test whether any association between solar activity and meteorological conditions in the north Atlantic – European sector could be detected. We find associations consistent with those found by previous studies, with a slightly better statistical significance, and with less methodological biases which have impaired previous studies. Our study should help strengthen the recognition of meteorological impacts of solar activity.
Moritz Buchmann, John Coll, Johannes Aschauer, Michael Begert, Stefan Brönnimann, Barbara Chimani, Gernot Resch, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 16, 2147–2161, https://doi.org/10.5194/tc-16-2147-2022, https://doi.org/10.5194/tc-16-2147-2022, 2022
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Knowledge about inhomogeneities in a data set is important for any subsequent climatological analysis. We ran three well-established homogenization methods and compared the identified break points. By only treating breaks as valid when detected by at least two out of three methods, we enhanced the robustness of our results. We found 45 breaks within 42 of 184 investigated series; of these 70 % could be explained by events recorded in the station history.
Stefan Brönnimann, Peter Stucki, Jörg Franke, Veronika Valler, Yuri Brugnara, Ralf Hand, Laura C. Slivinski, Gilbert P. Compo, Prashant D. Sardeshmukh, Michel Lang, and Bettina Schaefli
Clim. Past, 18, 919–933, https://doi.org/10.5194/cp-18-919-2022, https://doi.org/10.5194/cp-18-919-2022, 2022
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Floods in Europe vary on time scales of several decades. Flood-rich and flood-poor periods alternate. Recently floods have again become more frequent. Long time series of peak stream flow, precipitation, and atmospheric variables reveal that until around 1980, these changes were mostly due to changes in atmospheric circulation. However, in recent decades the role of increasing atmospheric moisture due to climate warming has become more important and is now the main driver of flood changes.
Daniel Steinfeld, Adrian Peter, Olivia Martius, and Stefan Brönnimann
EGUsphere, https://doi.org/10.5194/egusphere-2022-92, https://doi.org/10.5194/egusphere-2022-92, 2022
Preprint archived
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We assess the performance of various fire weather indices to predict wildfire occurrence in Northern Switzerland. We find that indices responding readily to weather changes have the best performance during spring; in the summer and autumn seasons, indices that describe persistent hot and dry conditions perform best. We demonstrate that a logistic regression model trained on local historical fire activity can outperform existing fire weather indices.
Duncan Pappert, Yuri Brugnara, Sylvie Jourdain, Aleksandra Pospieszyńska, Rajmund Przybylak, Christian Rohr, and Stefan Brönnimann
Clim. Past, 17, 2361–2379, https://doi.org/10.5194/cp-17-2361-2021, https://doi.org/10.5194/cp-17-2361-2021, 2021
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This paper presents temperature and pressure measurements from the 37 stations of the late 18th century network of the Societas Meteorologica Palatina, in addition to providing an inventory of the available observations, most of which have been digitised. The quality of the recovered series is relatively good, as demonstrated by two case studies. Early instrumental data such as these will help to explore past climate and weather extremes in Europe in greater detail.
Moritz Buchmann, Michael Begert, Stefan Brönnimann, and Christoph Marty
The Cryosphere, 15, 4625–4636, https://doi.org/10.5194/tc-15-4625-2021, https://doi.org/10.5194/tc-15-4625-2021, 2021
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We investigated the impacts of local-scale variations by analysing snow climate indicators derived from parallel snow measurements. We found the largest relative inter-pair differences for all indicators in spring and the smallest in winter. The findings serve as an important basis for our understanding of uncertainties of commonly used snow indicators and provide, in combination with break-detection methods, the groundwork in view of any homogenization efforts regarding snow time series.
Claudia Timmreck, Matthew Toohey, Davide Zanchettin, Stefan Brönnimann, Elin Lundstad, and Rob Wilson
Clim. Past, 17, 1455–1482, https://doi.org/10.5194/cp-17-1455-2021, https://doi.org/10.5194/cp-17-1455-2021, 2021
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The 1809 eruption is one of the most recent unidentified volcanic eruptions with a global climate impact. We demonstrate that climate model simulations of the 1809 eruption show generally good agreement with many large-scale temperature reconstructions and early instrumental records for a range of radiative forcing estimates. In terms of explaining the spatially heterogeneous and temporally delayed Northern Hemisphere cooling suggested by tree-ring networks, the investigation remains open.
Noemi Imfeld, Leopold Haimberger, Alexander Sterin, Yuri Brugnara, and Stefan Brönnimann
Earth Syst. Sci. Data, 13, 2471–2485, https://doi.org/10.5194/essd-13-2471-2021, https://doi.org/10.5194/essd-13-2471-2021, 2021
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Upper-air data form the backbone of reanalysis products, particularly in the pre-satellite era. However, historical upper-air data are error-prone because measurements at high altitude were especially challenging. Here, we present a collection of data from historical intercomparisons of radiosondes and error assessments reaching back to the 1930s that may allow us to better characterize such errors. The full database, including digitized data, images, and metadata, is made publicly available.
Stefan Brönnimann and Sylvia Nichol
Atmos. Chem. Phys., 20, 14333–14346, https://doi.org/10.5194/acp-20-14333-2020, https://doi.org/10.5194/acp-20-14333-2020, 2020
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Historical column ozone data from New Zealand and the UK from the 1950s are digitised and re-evaluated. They allow studying the ozone layer prior to the era of ozone depletion. Day-to-day changes are addressed, which reflect the flow near the tropopause and hence may serve as a diagnostic for atmospheric circulation in a time and region of sparse radiosondes. A long-term comparison shows the amount of ozone depletion at southern mid-latitudes and indicates how far we are from full recovery.
Christian Stepanek, Eric Samakinwa, Gregor Knorr, and Gerrit Lohmann
Clim. Past, 16, 2275–2323, https://doi.org/10.5194/cp-16-2275-2020, https://doi.org/10.5194/cp-16-2275-2020, 2020
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Future climate is expected to be warmer than today. We study climate based on simulations of the mid-Pliocene (about 3 million years ago), which was a time of elevated temperatures, and discuss implications for the future. Our results are provided towards a comparison to both proxy evidence and output of other climate models. We simulate a mid-Pliocene climate that is both warmer and wetter than today. Some climate characteristics can be more directly transferred to the near future than others.
Stefan Brönnimann
Clim. Past, 16, 1937–1952, https://doi.org/10.5194/cp-16-1937-2020, https://doi.org/10.5194/cp-16-1937-2020, 2020
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Scientists often reconstruct climate from proxy data such as tree rings or historical documents. Here, I do the reverse and produce a weather diary from historical numerical weather data. Such "synthetic weather diaries" may be useful for historians, e.g. to compare with other sources or to study the weather experienced during a journey or a military operation. They could also help train machine-learning approaches, which could then be used to reconstruct weather from historical diaries.
Eric Samakinwa, Christian Stepanek, and Gerrit Lohmann
Clim. Past, 16, 1643–1665, https://doi.org/10.5194/cp-16-1643-2020, https://doi.org/10.5194/cp-16-1643-2020, 2020
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Boundary conditions, forcing, and methodology for the two phases of PlioMIP differ considerably. We compare results from PlioMIP1 and PlioMIP2 simulations. We also carry out sensitivity experiments to infer the relative contribution of different boundary conditions to mid-Pliocene warmth. Our results show dominant effects of mid-Pliocene geography on the climate state and also that prescribing orbital forcing for different time slices within the mid-Pliocene could lead to pronounced variations.
Veronika Valler, Yuri Brugnara, Jörg Franke, and Stefan Brönnimann
Clim. Past, 16, 1309–1323, https://doi.org/10.5194/cp-16-1309-2020, https://doi.org/10.5194/cp-16-1309-2020, 2020
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Data assimilation is becoming more and more important for past climate reconstructions. The assimilation of monthly resolved precipitation information has not been explored much so far. In this study we analyze the impact of assimilating monthly precipitation amounts and the number of wet days within an existing paleoclimate data assimilation framework. We find increased skill in the reconstruction, suggesting that monthly precipitation can constitute valuable input for future reconstructions.
Jörg Franke, Veronika Valler, Stefan Brönnimann, Raphael Neukom, and Fernando Jaume-Santero
Clim. Past, 16, 1061–1074, https://doi.org/10.5194/cp-16-1061-2020, https://doi.org/10.5194/cp-16-1061-2020, 2020
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This study explores the influence of the input data choice on spatial climate reconstructions. We compare three tree-ring-based data sets which range from small sample size, small spatial coverage and strict screening for temperature sensitivity to the opposite. We achieve the best spatial reconstruction quality by combining all available input data but rejecting records with little and uncertain climatic information and considering moisture availability as an additional growth limitation.
Yuri Brugnara, Lucas Pfister, Leonie Villiger, Christian Rohr, Francesco Alessandro Isotta, and Stefan Brönnimann
Earth Syst. Sci. Data, 12, 1179–1190, https://doi.org/10.5194/essd-12-1179-2020, https://doi.org/10.5194/essd-12-1179-2020, 2020
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Early instrumental meteorological observations in Switzerland made before 1863, the year a national station network was created, were until recently largely unexplored. After a systematic compilation of the documents available in Swiss archives, we digitised a large part of the data so that they can be used in climate research. In this paper we give an overview of the development of meteorological observations in Switzerland and describe our approach to convert them into modern units.
Lucas Pfister, Stefan Brönnimann, Mikhaël Schwander, Francesco Alessandro Isotta, Pascal Horton, and Christian Rohr
Clim. Past, 16, 663–678, https://doi.org/10.5194/cp-16-663-2020, https://doi.org/10.5194/cp-16-663-2020, 2020
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This paper aims to reconstruct high-resolution daily precipitation and temperature fields for Switzerland back to 1864 using a statistical approach called the analogue resampling method. Results suggest that the presented method is suitable for weather reconstruction. As illustrated with the example of the avalanche in winter 1887/88, these weather reconstructions have great potential for various analyses of past weather and climate impact modelling.
Angela-Maria Burgdorf, Stefan Brönnimann, and Jörg Franke
Clim. Past, 15, 2053–2065, https://doi.org/10.5194/cp-15-2053-2019, https://doi.org/10.5194/cp-15-2053-2019, 2019
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The western USA is frequently affected by multiannual summer droughts. They can be separated into two groups with distinct spatial patterns. This study analyzes the atmospheric circulation during multiannual droughts in a new 3-D climate reconstruction. We confirm two distinct drought types differing with respect to atmospheric circulation as well as sea surface temperatures. Our results suggest that both the Pacific and the extratropical North Atlantic region affect North American droughts.
This Rutishauser, François Jeanneret, Robert Brügger, Yuri Brugnara, Christian Röthlisberger, August Bernasconi, Peter Bangerter, Céline Portenier, Leonie Villiger, Daria Lehmann, Lukas Meyer, Bruno Messerli, and Stefan Brönnimann
Earth Syst. Sci. Data, 11, 1645–1654, https://doi.org/10.5194/essd-11-1645-2019, https://doi.org/10.5194/essd-11-1645-2019, 2019
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This paper reports 7414 quality-controlled plant phenological observations of the BernClim phenological network in Switzerland. The data from 1304 sites at 110 stations were recorded between 1970 and 2018. The quality control (QC) points to very good internal consistency (only 0.2 % flagged as internally inconsistent) and likely to high quality of the data. BernClim data originally served in regional planning and agricultural suitability and are now valuable for climate change impact studies.
Marcelo Zamuriano, Paul Froidevaux, Isabel Moreno, Mathias Vuille, and Stefan Brönnimann
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2019-286, https://doi.org/10.5194/nhess-2019-286, 2019
Publication in NHESS not foreseen
Thomas Labbé, Christian Pfister, Stefan Brönnimann, Daniel Rousseau, Jörg Franke, and Benjamin Bois
Clim. Past, 15, 1485–1501, https://doi.org/10.5194/cp-15-1485-2019, https://doi.org/10.5194/cp-15-1485-2019, 2019
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In this paper we present the longest grape harvest date (GHD) record reconstructed to date, i.e. Beaune (France, Burgundy) 1354–2018. Drawing on unedited archive material, the series is validated using the long Paris temperature series that goes back to 1658 and was used to assess April-to-July temperatures from 1354 to 2018. The distribution of extremely early GHD is uneven over the 664-year-long period of the series and mirrors the rapid global warming from 1988 to 2018.
Veronika Valler, Jörg Franke, and Stefan Brönnimann
Clim. Past, 15, 1427–1441, https://doi.org/10.5194/cp-15-1427-2019, https://doi.org/10.5194/cp-15-1427-2019, 2019
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In recent years, the data assimilation approach was adapted to the field of paleoclimatology to reconstruct past climate fields by combining model simulations and observations.
To improve the performance of our paleodata assimilation system, we tested various techniques that are well established in weather forecasting and evaluated their impact on assimilating instrumental data and proxy records (tree rings).
Stefan Brönnimann, Luca Frigerio, Mikhaël Schwander, Marco Rohrer, Peter Stucki, and Jörg Franke
Clim. Past, 15, 1395–1409, https://doi.org/10.5194/cp-15-1395-2019, https://doi.org/10.5194/cp-15-1395-2019, 2019
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During the 19th century flood frequency was high in central Europe, but it was low in the mid-20th century. This paper tracks these decadal changes in flood frequency for the case of Switzerland from peak discharge data back to precipitation data and daily weather reconstructions. We find an increased frequency in flood-prone weather types during large parts of the 19th century and decreased frequency in the mid-20th century. Sea-surface temperature anomalies can only explain a small part of it.
Lucas Pfister, Franziska Hupfer, Yuri Brugnara, Lukas Munz, Leonie Villiger, Lukas Meyer, Mikhaël Schwander, Francesco Alessandro Isotta, Christian Rohr, and Stefan Brönnimann
Clim. Past, 15, 1345–1361, https://doi.org/10.5194/cp-15-1345-2019, https://doi.org/10.5194/cp-15-1345-2019, 2019
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The 18th and early 19th centuries saw pronounced climatic variations with impacts on the environment and society. Although instrumental meteorological data for that period exist, only a small fraction has been the subject of research. This study provides an overview of early instrumental meteorological records in Switzerland resulting from an archive survey and demonstrates the great potential of such data. It is accompanied by the online publication of the imaged data series and metadata.
Marcelo Zamuriano, Andrey Martynov, Luca Panziera, and Stefan Brönnimann
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2019-27, https://doi.org/10.5194/nhess-2019-27, 2019
Publication in NHESS not foreseen
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This work investigates the formation of a hailstorm over the Tropical Bolivian Andes. Using the WRF atmospheric model, we are able to numerically reconstruct it and we assess the main factors (mountains, lake and surface heating) in the storm formation. We propose physical mechanisms that have the potential to improve the forecasting of similar events; which are known to have a big impact over the Bolivian Altiplano, especially the region near Titicaca lake.
Peter Stucki, Moritz Bandhauer, Ulla Heikkilä, Ole Rössler, Massimiliano Zappa, Lucas Pfister, Melanie Salvisberg, Paul Froidevaux, Olivia Martius, Luca Panziera, and Stefan Brönnimann
Nat. Hazards Earth Syst. Sci., 18, 2717–2739, https://doi.org/10.5194/nhess-18-2717-2018, https://doi.org/10.5194/nhess-18-2717-2018, 2018
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A catastrophic flood south of the Alps in 1868 is assessed using documents and the earliest example of high-resolution weather simulation. Simulated weather dynamics agree well with observations and damage reports. Simulated peak water levels are biased. Low forest cover did not cause the flood, but such a paradigm was used to justify afforestation. Supported by historical methods, such numerical simulations allow weather events from past centuries to be used for modern hazard and risk analyses.
Stefan Brönnimann, Jan Rajczak, Erich M. Fischer, Christoph C. Raible, Marco Rohrer, and Christoph Schär
Nat. Hazards Earth Syst. Sci., 18, 2047–2056, https://doi.org/10.5194/nhess-18-2047-2018, https://doi.org/10.5194/nhess-18-2047-2018, 2018
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Heavy precipitation events in Switzerland are expected to become more intense, but the seasonality also changes. Analysing a large set of model simulations, we find that annual maximum rainfall events become less frequent in late summer and more frequent in early summer and early autumn. The seasonality shift is arguably related to summer drying. Results suggest that changes in the seasonal cycle need to be accounted for when preparing for moderately extreme precipitation events.
Stefan Hunziker, Stefan Brönnimann, Juan Calle, Isabel Moreno, Marcos Andrade, Laura Ticona, Adrian Huerta, and Waldo Lavado-Casimiro
Clim. Past, 14, 1–20, https://doi.org/10.5194/cp-14-1-2018, https://doi.org/10.5194/cp-14-1-2018, 2018
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Many data quality problems occurring in manned weather station observations are hardly detected with common data quality control methods. We investigated the effects of undetected data quality issues and found that they may reduce the correlation coefficients of station pairs, deteriorate the performance of data homogenization methods, increase the spread of individual station trends, and significantly bias regional trends. Applying adequate quality control approaches is of utmost importance.
Mikhaël Schwander, Marco Rohrer, Stefan Brönnimann, and Abdul Malik
Clim. Past, 13, 1199–1212, https://doi.org/10.5194/cp-13-1199-2017, https://doi.org/10.5194/cp-13-1199-2017, 2017
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We used a new classification of daily weather patterns to analyse the influence of solar variability (11-year cycle) on European climate from 1763 to 2009. The analysis of the weather patterns occurrences shows a reduction in the number of days with a westerly flow over Europe under low solar activity during late winter. In parallel, the number of days with an easterly flow increases. Based on these results we expect colder winter over Europe under low solar activity.
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.
Stefan Brönnimann, Abdul Malik, Alexander Stickler, Martin Wegmann, Christoph C. Raible, Stefan Muthers, Julien Anet, Eugene Rozanov, and Werner Schmutz
Atmos. Chem. Phys., 16, 15529–15543, https://doi.org/10.5194/acp-16-15529-2016, https://doi.org/10.5194/acp-16-15529-2016, 2016
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The Quasi-Biennial Oscillation is a wind oscillation in the equatorial stratosphere. Effects on climate have been found, which is relevant for seasonal forecasts. However, up to now only relatively short records were available, and even within these the climate imprints were intermittent. Here we analyze a 108-year long reconstruction as well as four 405-year long simulations. We confirm most of the claimed QBO effects on climate, but they are small, which explains apparently variable effects.
Chantal Camenisch, Kathrin M. Keller, Melanie Salvisberg, Benjamin Amann, Martin Bauch, Sandro Blumer, Rudolf Brázdil, Stefan Brönnimann, Ulf Büntgen, Bruce M. S. Campbell, Laura Fernández-Donado, Dominik Fleitmann, Rüdiger Glaser, Fidel González-Rouco, Martin Grosjean, Richard C. Hoffmann, Heli Huhtamaa, Fortunat Joos, Andrea Kiss, Oldřich Kotyza, Flavio Lehner, Jürg Luterbacher, Nicolas Maughan, Raphael Neukom, Theresa Novy, Kathleen Pribyl, Christoph C. Raible, Dirk Riemann, Maximilian Schuh, Philip Slavin, Johannes P. Werner, and Oliver Wetter
Clim. Past, 12, 2107–2126, https://doi.org/10.5194/cp-12-2107-2016, https://doi.org/10.5194/cp-12-2107-2016, 2016
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Throughout the last millennium, several cold periods occurred which affected humanity. Here, we investigate an exceptionally cold decade during the 15th century. The cold conditions challenged the food production and led to increasing food prices and a famine in parts of Europe. In contrast to periods such as the “Year Without Summer” after the eruption of Tambora, these extreme climatic conditions seem to have occurred by chance and in relation to the internal variability of the climate system.
Philip Brohan, Gilbert P. Compo, Stefan Brönnimann, Robert J. Allan, Renate Auchmann, Yuri Brugnara, Prashant D. Sardeshmukh, and Jeffrey S. Whitaker
Clim. Past Discuss., https://doi.org/10.5194/cp-2016-78, https://doi.org/10.5194/cp-2016-78, 2016
Preprint withdrawn
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We have used modern weather forecasting tools to reconstruct the dreadful European weather of 200 years ago – 1816 was the ‘year without a summer’; harvests failed, and people starved. We can show that 1816’s extreme climate was caused by the eruption of the Tambora volcano the previous year. This means we have some chance of predicting such extreme summers if they occur in future, though this is still a challenge to today’s forecast models.
Y. Brugnara, R. Auchmann, S. Brönnimann, R. J. Allan, I. Auer, M. Barriendos, H. Bergström, J. Bhend, R. Brázdil, G. P. Compo, R. C. Cornes, F. Dominguez-Castro, A. F. V. van Engelen, J. Filipiak, J. Holopainen, S. Jourdain, M. Kunz, J. Luterbacher, M. Maugeri, L. Mercalli, A. Moberg, C. J. Mock, G. Pichard, L. Řezníčková, G. van der Schrier, V. Slonosky, Z. Ustrnul, M. A. Valente, A. Wypych, and X. Yin
Clim. Past, 11, 1027–1047, https://doi.org/10.5194/cp-11-1027-2015, https://doi.org/10.5194/cp-11-1027-2015, 2015
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A data set of instrumental pressure and temperature observations for the early instrumental period (before ca. 1850) is described. This is the result of a digitisation effort involving the period immediately after the eruption of Mount Tambora in 1815, combined with the collection of already available sub-daily time series. The highest data availability is therefore for the years 1815 to 1817. An analysis of pressure variability and of case studies in Europe is performed for that period.
P. Stucki, S. Brönnimann, O. Martius, C. Welker, M. Imhof, N. von Wattenwyl, and N. Philipp
Nat. Hazards Earth Syst. Sci., 14, 2867–2882, https://doi.org/10.5194/nhess-14-2867-2014, https://doi.org/10.5194/nhess-14-2867-2014, 2014
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This catalog contains 240 (8 extreme) high-impact windstorms in Switzerland since 1859 in 3 severity classes. Validation with independent wind and damage data reveals that the most hazardous winter storms are captured, while too few moderate windstorms may be detected. We find evidence of high winter storm activity in the early and late 20th century compared to the mid-20th century in both damage and wind data. This indicates a covariability of hazard and related damages on decadal timescales.
K. Willett, C. Williams, I. T. Jolliffe, R. Lund, L. V. Alexander, S. Brönnimann, L. A. Vincent, S. Easterbrook, V. K. C. Venema, D. Berry, R. E. Warren, G. Lopardo, R. Auchmann, E. Aguilar, M. J. Menne, C. Gallagher, Z. Hausfather, T. Thorarinsdottir, and P. W. Thorne
Geosci. Instrum. Method. Data Syst., 3, 187–200, https://doi.org/10.5194/gi-3-187-2014, https://doi.org/10.5194/gi-3-187-2014, 2014
S. Muthers, J. G. Anet, A. Stenke, C. C. Raible, E. Rozanov, S. Brönnimann, T. Peter, F. X. Arfeuille, A. I. Shapiro, J. Beer, F. Steinhilber, Y. Brugnara, and W. Schmutz
Geosci. Model Dev., 7, 2157–2179, https://doi.org/10.5194/gmd-7-2157-2014, https://doi.org/10.5194/gmd-7-2157-2014, 2014
I. Mariani, A. Eichler, T. M. Jenk, S. Brönnimann, R. Auchmann, M. C. Leuenberger, and M. Schwikowski
Clim. Past, 10, 1093–1108, https://doi.org/10.5194/cp-10-1093-2014, https://doi.org/10.5194/cp-10-1093-2014, 2014
L. Ramella Pralungo, L. Haimberger, A. Stickler, and S. Brönnimann
Earth Syst. Sci. Data, 6, 185–200, https://doi.org/10.5194/essd-6-185-2014, https://doi.org/10.5194/essd-6-185-2014, 2014
J. G. Anet, S. Muthers, E. V. Rozanov, C. C. Raible, A. Stenke, A. I. Shapiro, S. Brönnimann, F. Arfeuille, Y. Brugnara, J. Beer, F. Steinhilber, W. Schmutz, and T. Peter
Clim. Past, 10, 921–938, https://doi.org/10.5194/cp-10-921-2014, https://doi.org/10.5194/cp-10-921-2014, 2014
P. Breitenmoser, S. Brönnimann, and D. Frank
Clim. Past, 10, 437–449, https://doi.org/10.5194/cp-10-437-2014, https://doi.org/10.5194/cp-10-437-2014, 2014
F. Arfeuille, D. Weisenstein, H. Mack, E. Rozanov, T. Peter, and S. Brönnimann
Clim. Past, 10, 359–375, https://doi.org/10.5194/cp-10-359-2014, https://doi.org/10.5194/cp-10-359-2014, 2014
A. Stickler, S. Brönnimann, S. Jourdain, E. Roucaute, A. Sterin, D. Nikolaev, M. A. Valente, R. Wartenburger, H. Hersbach, L. Ramella-Pralungo, and D. Dee
Earth Syst. Sci. Data, 6, 29–48, https://doi.org/10.5194/essd-6-29-2014, https://doi.org/10.5194/essd-6-29-2014, 2014
F. Arfeuille, B. P. Luo, P. Heckendorn, D. Weisenstein, J. X. Sheng, E. Rozanov, M. Schraner, S. Brönnimann, L. W. Thomason, and T. Peter
Atmos. Chem. Phys., 13, 11221–11234, https://doi.org/10.5194/acp-13-11221-2013, https://doi.org/10.5194/acp-13-11221-2013, 2013
J. G. Anet, S. Muthers, E. Rozanov, C. C. Raible, T. Peter, A. Stenke, A. I. Shapiro, J. Beer, F. Steinhilber, S. Brönnimann, F. Arfeuille, Y. Brugnara, and W. Schmutz
Atmos. Chem. Phys., 13, 10951–10967, https://doi.org/10.5194/acp-13-10951-2013, https://doi.org/10.5194/acp-13-10951-2013, 2013
A. Stenke, C. R. Hoyle, B. Luo, E. Rozanov, J. Gröbner, L. Maag, S. Brönnimann, and T. Peter
Atmos. Chem. Phys., 13, 9713–9729, https://doi.org/10.5194/acp-13-9713-2013, https://doi.org/10.5194/acp-13-9713-2013, 2013
S. Brönnimann, J. Bhend, J. Franke, S. Flückiger, A. M. Fischer, R. Bleisch, G. Bodeker, B. Hassler, E. Rozanov, and M. Schraner
Atmos. Chem. Phys., 13, 9623–9639, https://doi.org/10.5194/acp-13-9623-2013, https://doi.org/10.5194/acp-13-9623-2013, 2013
S. Brönnimann, I. Mariani, M. Schwikowski, R. Auchmann, and A. Eichler
Clim. Past, 9, 2013–2022, https://doi.org/10.5194/cp-9-2013-2013, https://doi.org/10.5194/cp-9-2013-2013, 2013
Y. Brugnara, S. Brönnimann, J. Luterbacher, and E. Rozanov
Atmos. Chem. Phys., 13, 6275–6288, https://doi.org/10.5194/acp-13-6275-2013, https://doi.org/10.5194/acp-13-6275-2013, 2013
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Climate and Earth system modeling
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The DOE E3SM version 2.1: overview and assessment of the impacts of parameterized ocean submesoscales
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Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3522, https://doi.org/10.5194/egusphere-2024-3522, 2024
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We analyzed carbon and nitrogen mass conservation in data from CMIP6 Earth System Models. Our findings reveal significant discrepancies between flux and pool size data, particularly in nitrogen, where cumulative imbalances can reach hundreds of gigatons. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Ingo Richter, Ping Chang, Gokhan Danabasoglu, Dietmar Dommenget, Guillaume Gastineau, Aixue Hu, Takahito Kataoka, Noel Keenlyside, Fred Kucharski, Yuko Okumura, Wonsun Park, Malte Stuecker, Andrea Taschetto, Chunzai Wang, Stephen Yeager, and Sang-Wook Yeh
EGUsphere, https://doi.org/10.5194/egusphere-2024-3110, https://doi.org/10.5194/egusphere-2024-3110, 2024
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The tropical ocean basins influence each other through multiple pathways and mechanisms, here referred to as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models, but have obtained conflicting results. This may be partly due to differences in experiment protocols, and partly due to systematic model errors. TBIMIP aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-183, https://doi.org/10.5194/gmd-2024-183, 2024
Revised manuscript accepted for GMD
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Improving climate predictions has significant socio-economic impacts. In this study, we developed and applied a weakly coupled ocean data assimilation (WCODA) system to a coupled climate model. The WCODA system improves simulations of ocean temperature and salinity across many global regions. It also enhances the simulation of interannual precipitation and temperature variability over the southern US. This system is to support future predictability studies.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
Short summary
Short summary
In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Yucheng Lin, Robert E. Kopp, Alexander Reedy, Matteo Turilli, Shantenu Jha, and Erica L. Ashe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2183, https://doi.org/10.5194/egusphere-2024-2183, 2024
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Short summary
PaleoSTeHM v1.0-rc is a state-of-the-art framework designed to reconstruct past environmental conditions using geological data. Built on modern machine learning techniques, it efficiently handles the sparse and noisy nature of paleo records, allowing scientists to make accurate and scalable inferences about past environmental change. By using flexible statistical models, PaleoSTeHM separates different sources of uncertainty, improving the precision of historical climate reconstructions.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2685, https://doi.org/10.5194/egusphere-2024-2685, 2024
Short summary
Short summary
Forecasting river runoff, crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using Convolutional Long Short-Term Memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
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Short summary
ModE-Sim is an ensemble of simulations with an atmosphere model. It uses observed sea surface temperatures, sea ice conditions, and volcanic aerosols for 1420 to 2009 as model input while accounting for uncertainties in these conditions. This generates several representations of the possible climate given these preconditions. Such a setup can be useful to understand the mechanisms that contribute to climate variability. This paper describes the setup of ModE-Sim and evaluates its performance.
ModE-Sim is an ensemble of simulations with an atmosphere model. It uses observed sea surface...