Articles | Volume 2, issue 3
https://doi.org/10.5194/wcd-2-841-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-2-841-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Sep 2021
Research article |
| 07 Sep 2021
| 07 Sep 2021
Emergence of representative signals for sudden stratospheric warmings beyond current predictable lead times
Institute for Atmospheric and Climate Science, ETH Zürich, Zurich, Switzerland
Bernat Jiménez-Esteve
Institute for Atmospheric and Climate Science, ETH Zürich, Zurich, Switzerland
Raphaël de Fondeville
Swiss Data Science Center, ETH Zürich and EPFL, Zurich, Switzerland
Enikő Székely
Swiss Data Science Center, ETH Zürich and EPFL, Zurich, Switzerland
Guillaume Obozinski
Swiss Data Science Center, ETH Zürich and EPFL, Zurich, Switzerland
William T. Ball
Department of Geoscience and Remote Sensing, Faculty of Civil Engineering and Geosciences, TU Delft, Delft, the Netherlands
Daniela I. V. Domeisen
Institute for Atmospheric and Climate Science, ETH Zürich, Zurich, Switzerland
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Jake W. Casselman, Bernat Jiménez-Esteve, and Daniela I. V. Domeisen
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Zachary D. Lawrence, Marta Abalos, Blanca Ayarzagüena, David Barriopedro, Amy H. Butler, Natalia Calvo, Alvaro de la Cámara, Andrew Charlton-Perez, Daniela I. V. Domeisen, Etienne Dunn-Sigouin, Javier García-Serrano, Chaim I. Garfinkel, Neil P. Hindley, Liwei Jia, Martin Jucker, Alexey Y. Karpechko, Hera Kim, Andrea L. Lang, Simon H. Lee, Pu Lin, Marisol Osman, Froila M. Palmeiro, Judith Perlwitz, Inna Polichtchouk, Jadwiga H. Richter, Chen Schwartz, Seok-Woo Son, Irene Erner, Masakazu Taguchi, Nicholas L. Tyrrell, Corwin J. Wright, and Rachel W.-Y. Wu
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Forecast models that are used to predict weather often struggle to represent the Earth’s stratosphere. This may impact their ability to predict surface weather weeks in advance, on subseasonal-to-seasonal (S2S) timescales. We use data from many S2S forecast systems to characterize and compare the stratospheric biases present in such forecast models. These models have many similar stratospheric biases, but they tend to be worse in systems with low model tops located within the stratosphere.
Rachel Wai-Ying Wu, Zheng Wu, and Daniela I.V. Domeisen
Weather Clim. Dynam., 3, 755–776, https://doi.org/10.5194/wcd-3-755-2022, https://doi.org/10.5194/wcd-3-755-2022, 2022
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Accurate predictions of the stratospheric polar vortex can enhance surface weather predictability. Stratospheric events themselves are less predictable, with strong inter-event differences. We assess the predictability of stratospheric acceleration and deceleration events in a sub-seasonal prediction system, finding that the predictability of events is largely dependent on event magnitude, while extreme drivers of deceleration events are not fully represented in the model.
Peter Hitchcock, Amy Butler, Andrew Charlton-Perez, Chaim I. Garfinkel, Tim Stockdale, James Anstey, Dann Mitchell, Daniela I. V. Domeisen, Tongwen Wu, Yixiong Lu, Daniele Mastrangelo, Piero Malguzzi, Hai Lin, Ryan Muncaster, Bill Merryfield, Michael Sigmond, Baoqiang Xiang, Liwei Jia, Yu-Kyung Hyun, Jiyoung Oh, Damien Specq, Isla R. Simpson, Jadwiga H. Richter, Cory Barton, Jeff Knight, Eun-Pa Lim, and Harry Hendon
Geosci. Model Dev., 15, 5073–5092, https://doi.org/10.5194/gmd-15-5073-2022, https://doi.org/10.5194/gmd-15-5073-2022, 2022
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This paper describes an experimental protocol focused on sudden stratospheric warmings to be carried out by subseasonal forecast modeling centers. These will allow for inter-model comparisons of these major disruptions to the stratospheric polar vortex and their impacts on the near-surface flow. The protocol will lead to new insights into the contribution of the stratosphere to subseasonal forecast skill and new approaches to the dynamical attribution of extreme events.
Chen Schwartz, Chaim I. Garfinkel, Priyanka Yadav, Wen Chen, and Daniela I. V. Domeisen
Weather Clim. Dynam., 3, 679–692, https://doi.org/10.5194/wcd-3-679-2022, https://doi.org/10.5194/wcd-3-679-2022, 2022
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Eleven operational forecast models that run on subseasonal timescales (up to 2 months) are examined to assess errors in their simulated large-scale stationary waves in the Northern Hemisphere winter. We found that models with a more finely resolved stratosphere generally do better in simulating the waves in both the stratosphere (10–50 km) and troposphere below. Moreover, a connection exists between errors in simulated time-mean convection in tropical regions and errors in the simulated waves.
Cristina Pérez-Guillén, Frank Techel, Martin Hendrick, Michele Volpi, Alec van Herwijnen, Tasko Olevski, Guillaume Obozinski, Fernando Pérez-Cruz, and Jürg Schweizer
Nat. Hazards Earth Syst. Sci., 22, 2031–2056, https://doi.org/10.5194/nhess-22-2031-2022, https://doi.org/10.5194/nhess-22-2031-2022, 2022
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A fully data-driven approach to predicting the danger level for dry-snow avalanche conditions in Switzerland was developed. Two classifiers were trained using a large database of meteorological data, snow cover simulations, and danger levels. The models performed well throughout the Swiss Alps, reaching a performance similar to the current experience-based avalanche forecasts. This approach shows the potential to be a valuable supplementary decision support tool for assessing avalanche hazard.
Adam A. Scaife, Mark P. Baldwin, Amy H. Butler, Andrew J. Charlton-Perez, Daniela I. V. Domeisen, Chaim I. Garfinkel, Steven C. Hardiman, Peter Haynes, Alexey Yu Karpechko, Eun-Pa Lim, Shunsuke Noguchi, Judith Perlwitz, Lorenzo Polvani, Jadwiga H. Richter, John Scinocca, Michael Sigmond, Theodore G. Shepherd, Seok-Woo Son, and David W. J. Thompson
Atmos. Chem. Phys., 22, 2601–2623, https://doi.org/10.5194/acp-22-2601-2022, https://doi.org/10.5194/acp-22-2601-2022, 2022
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Great progress has been made in computer modelling and simulation of the whole climate system, including the stratosphere. Since the late 20th century we also gained a much clearer understanding of how the stratosphere interacts with the lower atmosphere. The latest generation of numerical prediction systems now explicitly represents the stratosphere and its interaction with surface climate, and here we review its role in long-range predictions and projections from weeks to decades ahead.
Timofei Sukhodolov, Tatiana Egorova, Andrea Stenke, William T. Ball, Christina Brodowsky, Gabriel Chiodo, Aryeh Feinberg, Marina Friedel, Arseniy Karagodin-Doyennel, Thomas Peter, Jan Sedlacek, Sandro Vattioni, and Eugene Rozanov
Geosci. Model Dev., 14, 5525–5560, https://doi.org/10.5194/gmd-14-5525-2021, https://doi.org/10.5194/gmd-14-5525-2021, 2021
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This paper features the new atmosphere–ocean–aerosol–chemistry–climate model SOCOLv4.0 and its validation. The model performance is evaluated against reanalysis products and observations of atmospheric circulation and trace gas distribution, with a focus on stratospheric processes. Although we identified some problems to be addressed in further model upgrades, we demonstrated that SOCOLv4.0 is already well suited for studies related to chemistry–climate–aerosol interactions.
Amy H. Butler and Daniela I. V. Domeisen
Weather Clim. Dynam., 2, 453–474, https://doi.org/10.5194/wcd-2-453-2021, https://doi.org/10.5194/wcd-2-453-2021, 2021
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We classify by wave geometry the stratospheric polar vortex during the final warming that occurs every spring in both hemispheres due to a combination of radiative and dynamical processes. We show that the shape of the vortex, as well as the timing of the seasonal transition, is linked to total column ozone prior to and surface weather following the final warming. These results have implications for prediction and our understanding of stratosphere–troposphere coupling processes in springtime.
Simone Dietmüller, Hella Garny, Roland Eichinger, and William T. Ball
Atmos. Chem. Phys., 21, 6811–6837, https://doi.org/10.5194/acp-21-6811-2021, https://doi.org/10.5194/acp-21-6811-2021, 2021
Margot Clyne, Jean-Francois Lamarque, Michael J. Mills, Myriam Khodri, William Ball, Slimane Bekki, Sandip S. Dhomse, Nicolas Lebas, Graham Mann, Lauren Marshall, Ulrike Niemeier, Virginie Poulain, Alan Robock, Eugene Rozanov, Anja Schmidt, Andrea Stenke, Timofei Sukhodolov, Claudia Timmreck, Matthew Toohey, Fiona Tummon, Davide Zanchettin, Yunqian Zhu, and Owen B. Toon
Atmos. Chem. Phys., 21, 3317–3343, https://doi.org/10.5194/acp-21-3317-2021, https://doi.org/10.5194/acp-21-3317-2021, 2021
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This study finds how and why five state-of-the-art global climate models with interactive stratospheric aerosols differ when simulating the aftermath of large volcanic injections as part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP). We identify and explain the consequences of significant disparities in the underlying physics and chemistry currently in some of the models, which are problems likely not unique to the models participating in this study.
Arseniy Karagodin-Doyennel, Eugene Rozanov, Ales Kuchar, William Ball, Pavle Arsenovic, Ellis Remsberg, Patrick Jöckel, Markus Kunze, David A. Plummer, Andrea Stenke, Daniel Marsh, Doug Kinnison, and Thomas Peter
Atmos. Chem. Phys., 21, 201–216, https://doi.org/10.5194/acp-21-201-2021, https://doi.org/10.5194/acp-21-201-2021, 2021
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The solar signal in the mesospheric H2O and CO was extracted from the CCMI-1 model simulations and satellite observations using multiple linear regression (MLR) analysis. MLR analysis shows a pronounced and statistically robust solar signal in both H2O and CO. The model results show a general agreement with observations reproducing a negative/positive solar signal in H2O/CO. The pattern of the solar signal varies among the considered models, reflecting some differences in the model setup.
Hilla Afargan-Gerstman, Iuliia Polkova, Lukas Papritz, Paolo Ruggieri, Martin P. King, Panos J. Athanasiadis, Johanna Baehr, and Daniela I. V. Domeisen
Weather Clim. Dynam., 1, 541–553, https://doi.org/10.5194/wcd-1-541-2020, https://doi.org/10.5194/wcd-1-541-2020, 2020
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We investigate the stratospheric influence on marine cold air outbreaks (MCAOs) in the North Atlantic using ERA-Interim reanalysis data. MCAOs are associated with severe Arctic weather, such as polar lows and strong surface winds. Sudden stratospheric events are found to be associated with more frequent MCAOs in the Barents and the Norwegian seas, affected by the anomalous circulation over Greenland and Scandinavia. Identification of MCAO precursors is crucial for improved long-range prediction.
William T. Ball, Gabriel Chiodo, Marta Abalos, Justin Alsing, and Andrea Stenke
Atmos. Chem. Phys., 20, 9737–9752, https://doi.org/10.5194/acp-20-9737-2020, https://doi.org/10.5194/acp-20-9737-2020, 2020
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Recent lower stratospheric ozone decreases remain unexplained. We show that chemistry–climate models are not generally able to reproduce mid-latitude ozone and water vapour changes. Our analysis of observations provides evidence that climate change may be responsible for the ozone trends. While model projections suggest that extratropical ozone should recover by 2100, our study raises questions about their efficacy in simulating lower stratospheric changes in this region.
Daniela I. V. Domeisen, Christian M. Grams, and Lukas Papritz
Weather Clim. Dynam., 1, 373–388, https://doi.org/10.5194/wcd-1-373-2020, https://doi.org/10.5194/wcd-1-373-2020, 2020
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We cannot currently predict the weather over Europe beyond 2 weeks. The stratosphere provides a promising opportunity to go beyond that limit by providing a change in probability of certain weather regimes at the surface. However, not all stratospheric extreme events are followed by the same surface weather evolution. We show that this weather evolution is related to the tropospheric weather regime around the onset of the stratospheric extreme event for many stratospheric events.
Eliane Maillard Barras, Alexander Haefele, Liliane Nguyen, Fiona Tummon, William T. Ball, Eugene V. Rozanov, Rolf Rüfenacht, Klemens Hocke, Leonie Bernet, Niklaus Kämpfer, Gerald Nedoluha, and Ian Boyd
Atmos. Chem. Phys., 20, 8453–8471, https://doi.org/10.5194/acp-20-8453-2020, https://doi.org/10.5194/acp-20-8453-2020, 2020
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To determine the part of the variability of the long-term ozone profile trends coming from measurement timing, we estimate microwave radiometer trends for each hour of the day with a multiple linear regression model. The variation in the trend with local solar time is not significant at the 95 % confidence level either in the stratosphere or in the low mesosphere. We conclude that systematic sampling differences between instruments cannot explain significant differences in trend estimates.
Bernat Jiménez-Esteve and Daniela I. V. Domeisen
Weather Clim. Dynam., 1, 225–245, https://doi.org/10.5194/wcd-1-225-2020, https://doi.org/10.5194/wcd-1-225-2020, 2020
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Atmospheric predictability over Europe on subseasonal to seasonal timescales remains limited. However, the remote impact from the El Niño–Southern Oscillation (ENSO) can help to improve predictability. Research has suggested that the ENSO impact in the North Atlantic region is affected by nonlinearities. Here, we isolate the nonlinearities in the tropospheric pathway through the North Pacific, finding that a strong El Niño leads to a stronger and distinct impact compared to a strong La Niña.
William T. Ball, Justin Alsing, Johannes Staehelin, Sean M. Davis, Lucien Froidevaux, and Thomas Peter
Atmos. Chem. Phys., 19, 12731–12748, https://doi.org/10.5194/acp-19-12731-2019, https://doi.org/10.5194/acp-19-12731-2019, 2019
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We analyse long-term stratospheric ozone (60° S–60° N) trends over the 1985–2018 period. Previous work has suggested that lower stratosphere ozone declined over 1998–2016. We demonstrate that a large ozone upsurge in 2017 is likely related to QBO variability, but that lower stratospheric ozone trends likely remain lower in 2018 than in 1998. Tropical stratospheric ozone (30° S–30° N) shows highly probable decreases in both the lower stratosphere and in the integrated stratospheric ozone layer.
Lauren Marshall, Anja Schmidt, Matthew Toohey, Ken S. Carslaw, Graham W. Mann, Michael Sigl, Myriam Khodri, Claudia Timmreck, Davide Zanchettin, William T. Ball, Slimane Bekki, James S. A. Brooke, Sandip Dhomse, Colin Johnson, Jean-Francois Lamarque, Allegra N. LeGrande, Michael J. Mills, Ulrike Niemeier, James O. Pope, Virginie Poulain, Alan Robock, Eugene Rozanov, Andrea Stenke, Timofei Sukhodolov, Simone Tilmes, Kostas Tsigaridis, and Fiona Tummon
Atmos. Chem. Phys., 18, 2307–2328, https://doi.org/10.5194/acp-18-2307-2018, https://doi.org/10.5194/acp-18-2307-2018, 2018
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We use four global aerosol models to compare the simulated sulfate deposition from the 1815 Mt. Tambora eruption to ice core records. Inter-model volcanic sulfate deposition differs considerably. Volcanic sulfate deposited on polar ice sheets is used to estimate the atmospheric sulfate burden and subsequently radiative forcing of historic eruptions. Our results suggest that deriving such relationships from model simulations may be associated with greater uncertainties than previously thought.
William T. Ball, Justin Alsing, Daniel J. Mortlock, Johannes Staehelin, Joanna D. Haigh, Thomas Peter, Fiona Tummon, Rene Stübi, Andrea Stenke, John Anderson, Adam Bourassa, Sean M. Davis, Doug Degenstein, Stacey Frith, Lucien Froidevaux, Chris Roth, Viktoria Sofieva, Ray Wang, Jeannette Wild, Pengfei Yu, Jerald R. Ziemke, and Eugene V. Rozanov
Atmos. Chem. Phys., 18, 1379–1394, https://doi.org/10.5194/acp-18-1379-2018, https://doi.org/10.5194/acp-18-1379-2018, 2018
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Using a robust analysis, with artefact-corrected ozone data, we confirm upper stratospheric ozone is recovering following the Montreal Protocol, but that lower stratospheric ozone (50° S–50° N) has continued to decrease since 1998, and the ozone layer as a whole (60° S–60° N) may be lower today than in 1998. No change in total column ozone may be due to increasing tropospheric ozone. State-of-the-art models do not reproduce lower stratospheric ozone decreases.
William T. Ball, Justin Alsing, Daniel J. Mortlock, Eugene V. Rozanov, Fiona Tummon, and Joanna D. Haigh
Atmos. Chem. Phys., 17, 12269–12302, https://doi.org/10.5194/acp-17-12269-2017, https://doi.org/10.5194/acp-17-12269-2017, 2017
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Several ozone composites show different decadal trends, even in composites built with the same data. We remove artefacts affecting trend analysis with a new method (BASIC) and construct an ozone composite, with uncertainties. We find a significant ozone recovery since 1998 in the midlatitude upper stratosphere, with no hemispheric difference. We recommend using a similar approach to construct a composite based on the original instrument data to improve stratospheric ozone trend estimates.
Bernd Funke, William Ball, Stefan Bender, Angela Gardini, V. Lynn Harvey, Alyn Lambert, Manuel López-Puertas, Daniel R. Marsh, Katharina Meraner, Holger Nieder, Sanna-Mari Päivärinta, Kristell Pérot, Cora E. Randall, Thomas Reddmann, Eugene Rozanov, Hauke Schmidt, Annika Seppälä, Miriam Sinnhuber, Timofei Sukhodolov, Gabriele P. Stiller, Natalia D. Tsvetkova, Pekka T. Verronen, Stefan Versick, Thomas von Clarmann, Kaley A. Walker, and Vladimir Yushkov
Atmos. Chem. Phys., 17, 3573–3604, https://doi.org/10.5194/acp-17-3573-2017, https://doi.org/10.5194/acp-17-3573-2017, 2017
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Simulations from eight atmospheric models have been compared to tracer and temperature observations from seven satellite instruments in order to evaluate the energetic particle indirect effect (EPP IE) during the perturbed northern hemispheric (NH) winter 2008/2009. Models are capable to reproduce the EPP IE in dynamically and geomagnetically quiescent NH winter conditions. The results emphasize the need for model improvements in the dynamical representation of elevated stratopause events.
Matthias Fischer, Daniela I. V. Domeisen, Wolfgang A. Müller, and Johanna Baehr
Earth Syst. Dynam., 8, 129–146, https://doi.org/10.5194/esd-8-129-2017, https://doi.org/10.5194/esd-8-129-2017, 2017
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In a climate projection experiment with the Max Planck Institute Earth System Model (MPI-ESM), we find that a decline in the Atlantic Ocean meridional heat transport (OHT) is accompanied by a change in the seasonal cycle of the total OHT and its components. We found a northward shift of 5° and latitude-dependent shifts between 1 and 6 months in the seasonal cycle that are mainly associated with changes in the meridional velocity field rather than the temperature field.
William T. Ball, Aleš Kuchař, Eugene V. Rozanov, Johannes Staehelin, Fiona Tummon, Anne K. Smith, Timofei Sukhodolov, Andrea Stenke, Laura Revell, Ancelin Coulon, Werner Schmutz, and Thomas Peter
Atmos. Chem. Phys., 16, 15485–15500, https://doi.org/10.5194/acp-16-15485-2016, https://doi.org/10.5194/acp-16-15485-2016, 2016
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We find monthly, mid-latitude temperature changes above 40 km are related to ozone and temperature variations throughout the middle atmosphere. We develop an index to represent this atmospheric variability. In statistical analysis, the index can account for up to 60 % of variability in tropical temperature and ozone above 27 km. The uncertainties can be reduced by up to 35 % and 20 % in temperature and ozone, respectively. This index is an important tool to quantify current and future ozone recovery.
Laura E. Revell, Andrea Stenke, Eugene Rozanov, William Ball, Stefan Lossow, and Thomas Peter
Atmos. Chem. Phys., 16, 13067–13080, https://doi.org/10.5194/acp-16-13067-2016, https://doi.org/10.5194/acp-16-13067-2016, 2016
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Water vapour in the stratosphere plays an important role in atmospheric chemistry and the Earth's radiative balance. We have analysed trends in stratospheric water vapour through the 21st century as simulated by a coupled chemistry–climate model following a range of greenhouse gas emission scenarios. We have also quantified the contribution that methane oxidation in the stratosphere makes to projected water vapour trends.
Davide Zanchettin, Myriam Khodri, Claudia Timmreck, Matthew Toohey, Anja Schmidt, Edwin P. Gerber, Gabriele Hegerl, Alan Robock, Francesco S. R. Pausata, William T. Ball, Susanne E. Bauer, Slimane Bekki, Sandip S. Dhomse, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Michael Mills, Marion Marchand, Ulrike Niemeier, Virginie Poulain, Eugene Rozanov, Angelo Rubino, Andrea Stenke, Kostas Tsigaridis, and Fiona Tummon
Geosci. Model Dev., 9, 2701–2719, https://doi.org/10.5194/gmd-9-2701-2016, https://doi.org/10.5194/gmd-9-2701-2016, 2016
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Simulating volcanically-forced climate variability is a challenging task for climate models. The Model Intercomparison Project on the climatic response to volcanic forcing (VolMIP) – an endorsed contribution to CMIP6 – defines a protocol for idealized volcanic-perturbation experiments to improve comparability of results across different climate models. This paper illustrates the design of VolMIP's experiments and describes the aerosol forcing input datasets to be used.
Mathew A. Stiller-Reeve, Céline Heuzé, William T. Ball, Rachel H. White, Gabriele Messori, Karin van der Wiel, Iselin Medhaug, Annemarie H. Eckes, Amee O'Callaghan, Mike J. Newland, Sian R. Williams, Matthew Kasoar, Hella Elisa Wittmeier, and Valerie Kumer
Hydrol. Earth Syst. Sci., 20, 2965–2973, https://doi.org/10.5194/hess-20-2965-2016, https://doi.org/10.5194/hess-20-2965-2016, 2016
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Scientific writing must improve and the key to long-term improvement of scientific writing lies with the early-career scientist (ECS). We introduce the ClimateSnack project, which aims to motivate ECSs to start writing groups around the world to improve their skills together. Writing groups offer many benefits but can be a challenge to keep going. Several ClimateSnack writing groups formed, and this paper examines why some of the groups flourished and others dissolved.
Related subject area
Atmospheric predictability
Systematic evaluation of the predictability of different Mediterranean cyclone categories
Understanding winter windstorm predictability over Europe
Intrinsic predictability limits arising from Indian Ocean Madden–Julian oscillation (MJO) heating: effects on tropical and extratropical teleconnections
Predictable decadal forcing of the North Atlantic jet speed by sub-polar North Atlantic sea surface temperatures
Exploiting the signal-to-noise ratio in multi-system predictions of boreal summer precipitation and temperature
Causal associations and predictability of the summer East Atlantic teleconnection
Uncertainty growth and forecast reliability during extratropical cyclogenesis
Convection-parameterized and convection-permitting modelling of heavy precipitation in decadal simulations of the greater Alpine region with COSMO-CLM
Improved extended-range prediction of persistent stratospheric perturbations using machine learning
Increased vertical resolution in the stratosphere reveals role of gravity waves after sudden stratospheric warmings
The impact of microphysical uncertainty conditional on initial and boundary condition uncertainty under varying synoptic control
Subseasonal precipitation forecasts of opportunity over central southwest Asia
Predictability of a tornado environment index from El Niño–Southern Oscillation (ENSO) and the Arctic Oscillation
Differences in the sub-seasonal predictability of extreme stratospheric events
Impact of Eurasian autumn snow on the winter North Atlantic Oscillation in seasonal forecasts of the 20th century
Bimodality in ensemble forecasts of 2 m temperature: identification
Flow dependence of wintertime subseasonal prediction skill over Europe
Seasonal forecasts of the Saharan heat low characteristics: a multi-model assessment
The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6
Seasonal climate influences on the timing of the Australian monsoon onset
Subseasonal prediction of springtime Pacific–North American transport using upper-level wind forecasts
A dynamic and thermodynamic analysis of the 11 December 2017 tornadic supercell in the Highveld of South Africa
How an uncertain short-wave perturbation on the North Atlantic wave guide affects the forecast of an intense Mediterranean cyclone (Medicane Zorbas)
Robust predictors for seasonal Atlantic hurricane activity identified with causal effect networks
Subseasonal midlatitude prediction skill following Quasi-Biennial Oscillation and Madden–Julian Oscillation activity
Large impact of tiny model domain shifts for the Pentecost 2014 mesoscale convective system over Germany
Benjamin Doiteau, Florian Pantillon, Matthieu Plu, Laurent Descamps, and Thomas Rieutord
Weather Clim. Dynam., 5, 1409–1427, https://doi.org/10.5194/wcd-5-1409-2024, https://doi.org/10.5194/wcd-5-1409-2024, 2024
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The predictability of Mediterranean cyclones is investigated through a large dataset of 1960 cyclones tracks, ensuring robust statistical results. The motion speed of the cyclone appears to determine the predictability of its location. In particular, the location of specific slow cyclones concentrated in the Gulf of Genoa is remarkably well predicted. It is also shown that the intensity of deep cyclones, occurring in winter, is particularly poorly predicted in the Mediterranean region.
Lisa Degenhardt, Gregor C. Leckebusch, and Adam A. Scaife
Weather Clim. Dynam., 5, 587–607, https://doi.org/10.5194/wcd-5-587-2024, https://doi.org/10.5194/wcd-5-587-2024, 2024
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This study investigates how dynamical factors that are known to influence cyclone or windstorm development and strengthening also influence the seasonal forecast skill of severe winter windstorms. This study shows which factors are well represented in the seasonal forecast model, the Global Seasonal forecasting system version 5 (GloSea5), and which might need improvement to refine the forecast of severe winter windstorms.
David Martin Straus, Daniela I. V. Domeisen, Sarah-Jane Lock, Franco Molteni, and Priyanka Yadav
Weather Clim. Dynam., 4, 1001–1018, https://doi.org/10.5194/wcd-4-1001-2023, https://doi.org/10.5194/wcd-4-1001-2023, 2023
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The global response to the Madden–Julian oscillation (MJO) is potentially predictable. Yet the diabatic heating is uncertain even within a particular episode of the MJO. Experiments with a global model probe the limitations imposed by this uncertainty. The large-scale tropical heating is predictable for 25 to 45 d, yet the associated Rossby wave source that links the heating to the midlatitude circulation is predictable for 15 to 20 d. This limitation has not been recognized in prior work.
Kristian Strommen, Tim Woollings, Paolo Davini, Paolo Ruggieri, and Isla R. Simpson
Weather Clim. Dynam., 4, 853–874, https://doi.org/10.5194/wcd-4-853-2023, https://doi.org/10.5194/wcd-4-853-2023, 2023
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We present evidence which strongly suggests that decadal variations in the intensity of the North Atlantic winter jet stream can be predicted by current forecast models but that decadal variations in its position appear to be unpredictable. It is argued that this skill at predicting jet intensity originates from the slow, predictable variability in sea surface temperatures in the sub-polar North Atlantic.
Juan Camilo Acosta Navarro and Andrea Toreti
Weather Clim. Dynam., 4, 823–831, https://doi.org/10.5194/wcd-4-823-2023, https://doi.org/10.5194/wcd-4-823-2023, 2023
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Droughts and heatwaves have become some of the clearest manifestations of a changing climate. Near-term adaptation strategies can benefit from seasonal predictions, but these predictions still have limitations. We found that an intrinsic property of multi-system forecasts can serve to better anticipate extreme high-temperature and low-precipitation events during boreal summer in several regions of the Northern Hemisphere with different levels of predictability.
Julianna Carvalho-Oliveira, Giorgia di Capua, Leonard Borchert, Reik Donner, and Johanna Baehr
EGUsphere, https://doi.org/10.5194/egusphere-2023-1412, https://doi.org/10.5194/egusphere-2023-1412, 2023
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We demonstrate with a causality analysis that an important recurrent summer atmospheric pattern, the so-called East Atlantic teleconnection, is influenced by the extratropical North Atlantic in spring during the second half of the 20th century. This causal link is, however, not well represented by our evaluated seasonal climate prediction system. We show that simulations able to reproduce this link show improved surface climate prediction credibility over those that do not.
Mark J. Rodwell and Heini Wernli
Weather Clim. Dynam., 4, 591–615, https://doi.org/10.5194/wcd-4-591-2023, https://doi.org/10.5194/wcd-4-591-2023, 2023
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Midlatitude storms and their downstream impacts have a major impact on society, yet their prediction is especially prone to uncertainty. While this can never be fully eliminated, we find that the initial rate of growth of uncertainty varies for a range of forecast models. Examination of the model of the European Centre for Medium-Range Weather Forecasts (ECMWF) suggests ways in which uncertainty growth could be reduced, leading to sharper and more reliable forecasts over the first few days.
Alberto Caldas-Alvarez, Hendrik Feldmann, Etor Lucio-Eceiza, and Joaquim G. Pinto
Weather Clim. Dynam., 4, 543–565, https://doi.org/10.5194/wcd-4-543-2023, https://doi.org/10.5194/wcd-4-543-2023, 2023
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We evaluate convection-permitting modelling (CPM) simulations for the greater Alpine area to assess its added value compared to a 25 km resolution. A new method for severe precipitation detection is used, and the associated synoptic weather types are considered. Our results document the added value of CPM for precipitation representation with higher intensities, better rank correlation, better hit rates, and an improved amount and structure, but with an overestimation of the rates.
Raphaël de Fondeville, Zheng Wu, Enikő Székely, Guillaume Obozinski, and Daniela I. V. Domeisen
Weather Clim. Dynam., 4, 287–307, https://doi.org/10.5194/wcd-4-287-2023, https://doi.org/10.5194/wcd-4-287-2023, 2023
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We propose a fully data-driven, interpretable, and computationally scalable framework to characterize sudden stratospheric warmings (SSWs), extract statistically significant precursors, and produce machine learning (ML) forecasts. By successfully leveraging the long-lasting impact of SSWs, the ML predictions outperform sub-seasonal numerical forecasts for lead times beyond 25 d. Post-processing numerical predictions using their ML counterparts yields a performance increase of up to 20 %.
Wolfgang Wicker, Inna Polichtchouk, and Daniela I. V. Domeisen
Weather Clim. Dynam., 4, 81–93, https://doi.org/10.5194/wcd-4-81-2023, https://doi.org/10.5194/wcd-4-81-2023, 2023
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Sudden stratospheric warmings are extreme weather events where the winter polar stratosphere warms by about 25 K. An improved representation of small-scale gravity waves in sub-seasonal prediction models can reduce forecast errors since their impact on the large-scale circulation is predictable multiple weeks ahead. After a sudden stratospheric warming, vertically propagating gravity waves break at a lower altitude than usual, which strengthens the long-lasting positive temperature anomalies.
Takumi Matsunobu, Christian Keil, and Christian Barthlott
Weather Clim. Dynam., 3, 1273–1289, https://doi.org/10.5194/wcd-3-1273-2022, https://doi.org/10.5194/wcd-3-1273-2022, 2022
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This study quantifies the impact of poorly constrained parameters used to represent aerosol–cloud–precipitation interactions on precipitation and cloud forecasts associated with uncertainties in input atmospheric states. Uncertainties in these parameters have a non-negligible impact on daily precipitation amount and largely change the amount of cloud. The comparison between different weather situations reveals that the impact becomes more important when convection is triggered by local effects.
Melissa L. Breeden, John R. Albers, and Andrew Hoell
Weather Clim. Dynam., 3, 1183–1197, https://doi.org/10.5194/wcd-3-1183-2022, https://doi.org/10.5194/wcd-3-1183-2022, 2022
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We use a statistical dynamical model to generate precipitation forecasts for lead times of 2–6 weeks over southwest Asia, which are needed to support humanitarian food distribution. The model signal-to-noise ratio is used to identify a smaller subset of forecasts with particularly high skill, so-called subseasonal forecasts of opportunity (SFOs). Precipitation SFOs are often related to slowly evolving tropical phenomena, namely the El Niño–Southern Oscillation and Madden–Julian Oscillation.
Michael K. Tippett, Chiara Lepore, and Michelle L. L’Heureux
Weather Clim. Dynam., 3, 1063–1075, https://doi.org/10.5194/wcd-3-1063-2022, https://doi.org/10.5194/wcd-3-1063-2022, 2022
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The El Niño–Southern Oscillation (ENSO) and Arctic Oscillation (AO) are phenomena that affect the weather and climate of North America. Although ENSO hails from from the tropical Pacific and the AO high above the North Pole, the spatial patterns of their influence on a North American tornado environment index are remarkably similar in computer models. We find that when ENSO and the AO act in concert, their impact is large, and when they oppose each other, their impact is small.
Rachel Wai-Ying Wu, Zheng Wu, and Daniela I.V. Domeisen
Weather Clim. Dynam., 3, 755–776, https://doi.org/10.5194/wcd-3-755-2022, https://doi.org/10.5194/wcd-3-755-2022, 2022
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Accurate predictions of the stratospheric polar vortex can enhance surface weather predictability. Stratospheric events themselves are less predictable, with strong inter-event differences. We assess the predictability of stratospheric acceleration and deceleration events in a sub-seasonal prediction system, finding that the predictability of events is largely dependent on event magnitude, while extreme drivers of deceleration events are not fully represented in the model.
Martin Wegmann, Yvan Orsolini, Antje Weisheimer, Bart van den Hurk, and Gerrit Lohmann
Weather Clim. Dynam., 2, 1245–1261, https://doi.org/10.5194/wcd-2-1245-2021, https://doi.org/10.5194/wcd-2-1245-2021, 2021
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Northern Hemisphere winter weather is influenced by the strength of westerly winds 30 km above the surface, the so-called polar vortex. Eurasian autumn snow cover is thought to modulate the polar vortex. So far, however, the modeled influence of snow on the polar vortex did not fit the observed influence. By analyzing a model experiment for the time span of 110 years, we could show that the causality of this impact is indeed sound and snow cover can weaken the polar vortex.
Cameron Bertossa, Peter Hitchcock, Arthur DeGaetano, and Riwal Plougonven
Weather Clim. Dynam., 2, 1209–1224, https://doi.org/10.5194/wcd-2-1209-2021, https://doi.org/10.5194/wcd-2-1209-2021, 2021
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While the assumption of Gaussianity leads to many simplifications, ensemble forecasts often exhibit non-Gaussian distributions. This work has systematically identified the presence of a specific case of
non-Gaussianity, bimodality. It has been found that bimodality occurs in a large portion of global 2 m temperature forecasts. This has drastic implications on forecast skill as the minimum probability in a bimodal distribution often lies at the maximum probability of a Gaussian distribution.
Constantin Ardilouze, Damien Specq, Lauriane Batté, and Christophe Cassou
Weather Clim. Dynam., 2, 1033–1049, https://doi.org/10.5194/wcd-2-1033-2021, https://doi.org/10.5194/wcd-2-1033-2021, 2021
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Forecasting temperature patterns beyond 2 weeks is very challenging, although occasionally, forecasts show more skill over Europe. Our study indicates that the level of skill varies concurrently for two distinct forecast systems. It also shows that higher skill occurs when forecasts are issued during specific patterns of atmospheric circulation that tend to be particularly persistent.
These results could help forecasters estimate a priori how trustworthy extended-range forecasts will be.
Cedric G. Ngoungue Langue, Christophe Lavaysse, Mathieu Vrac, Philippe Peyrillé, and Cyrille Flamant
Weather Clim. Dynam., 2, 893–912, https://doi.org/10.5194/wcd-2-893-2021, https://doi.org/10.5194/wcd-2-893-2021, 2021
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This work assesses the forecast of the temperature over the Sahara, a key driver of the West African Monsoon, at a seasonal timescale. The seasonal models are able to reproduce the climatological state and some characteristics of the temperature during the rainy season in the Sahel. But, because of errors in the timing, the forecast skill scores are significant only for the first 4 weeks.
Alberto Caldas-Alvarez, Samiro Khodayar, and Peter Knippertz
Weather Clim. Dynam., 2, 561–580, https://doi.org/10.5194/wcd-2-561-2021, https://doi.org/10.5194/wcd-2-561-2021, 2021
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The prediction capabilities of GPS, operational (low-resolution) and targeted (high-resolution) radiosondes for data assimilation in a Mediterranean heavy precipitation event at different model resolutions are investigated. The results show that even if GPS provides accurate observations, their lack of vertical information hampers the improvement, demonstrating the need for assimilating radiosondes, where the location and timing of release was more determinant than the vertical resolution.
Joel Lisonbee and Joachim Ribbe
Weather Clim. Dynam., 2, 489–506, https://doi.org/10.5194/wcd-2-489-2021, https://doi.org/10.5194/wcd-2-489-2021, 2021
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Why do some monsoon seasons start early, while others start late? For the Australian monsoon, some previous research suggested the El Niño–Southern Oscillation in the months before the onset influenced the monsoon timing. This research tests if this is still correct and if other large-scale climate patterns also influenced onset timing. We found that a strong La Niña pattern usually coincided with an early onset but weak La Niña and El Niño patterns did not show a consistent pattern.
John R. Albers, Amy H. Butler, Melissa L. Breeden, Andrew O. Langford, and George N. Kiladis
Weather Clim. Dynam., 2, 433–452, https://doi.org/10.5194/wcd-2-433-2021, https://doi.org/10.5194/wcd-2-433-2021, 2021
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Weather variability controls the transport of ozone from the stratosphere to the Earth’s surface and water vapor from oceanic source regions to continental land masses. Forecasting these types of transport has high societal value because of the negative impacts of ozone on human health and the role of water vapor in governing precipitation variability. We use upper-level wind forecasts to assess the potential for predicting ozone and water vapor transport 3–6 weeks ahead of time.
Lesetja E. Lekoloane, Mary-Jane M. Bopape, Tshifhiwa Gift Rambuwani, Thando Ndarana, Stephanie Landman, Puseletso Mofokeng, Morne Gijben, and Ngwako Mohale
Weather Clim. Dynam., 2, 373–393, https://doi.org/10.5194/wcd-2-373-2021, https://doi.org/10.5194/wcd-2-373-2021, 2021
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We analysed a tornadic supercell that tracked through the northern Highveld region of South Africa for 7 h. We found that atmospheric conditions were conducive for tornado-associated severe storms over the region. A 4.4 km resolution model run by the South African Weather Service was able to predict this supercell, including its timing. However, it underestimated its severity due to underestimations of other important factors necessary for real-world development of these kinds of storms.
Raphael Portmann, Juan Jesús González-Alemán, Michael Sprenger, and Heini Wernli
Weather Clim. Dynam., 1, 597–615, https://doi.org/10.5194/wcd-1-597-2020, https://doi.org/10.5194/wcd-1-597-2020, 2020
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In September 2018 an intense Mediterranean cyclone with structural similarities to a hurricane, a so-called medicane, caused severe damage in Greece. Its development was uncertain, even just a few days in advance. The reason for this was uncertainties in the jet stream over the North Atlantic 3 d prior to cyclogenesis that propagated into the Mediterranean. They led to an uncertain position of the upper-level disturbance and, as a result, of the position and thermal structure of the cyclone.
Peter Pfleiderer, Carl-Friedrich Schleussner, Tobias Geiger, and Marlene Kretschmer
Weather Clim. Dynam., 1, 313–324, https://doi.org/10.5194/wcd-1-313-2020, https://doi.org/10.5194/wcd-1-313-2020, 2020
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Seasonal outlooks of Atlantic hurricane activity are required to enable risk reduction measures and disaster preparedness. Many seasonal forecasts are based on a selection of climate signals from which a statistical model is constructed. The crucial step in this approach is to select the most relevant predictors without overfitting. Here we show that causal effect networks can be used to identify the most robust predictors. Based on these predictors we construct a competitive forecast model.
Kirsten J. Mayer and Elizabeth A. Barnes
Weather Clim. Dynam., 1, 247–259, https://doi.org/10.5194/wcd-1-247-2020, https://doi.org/10.5194/wcd-1-247-2020, 2020
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Tropical storms are key for harnessing midlatitude weather prediction skill 2–8 weeks into the future. Recently, stratospheric activity was shown to impact tropical storminess and thus may also be important for midlatitude prediction skill on these timescales. This work analyzes two forecast systems to assess whether they capture this additional skill. We find there is enhanced prediction out through week 4 when both the tropical and stratospheric phenomena are active.
Christian Barthlott and Andrew I. Barrett
Weather Clim. Dynam., 1, 207–224, https://doi.org/10.5194/wcd-1-207-2020, https://doi.org/10.5194/wcd-1-207-2020, 2020
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The mesoscale convective system (MCS) that affected Germany at Pentecost 2014 was one of the most severe for decades. However, the predictability of this system was very low. By moving the model domain by just one grid point changed whether the MCS was successfully simulated or not. The decisive factor seems to be small differences in the initial track of the convection: cooler air near the coast inhibited development there, but tracks slightly more inland found more favorable conditions.
Cited articles
Albers, J. R. and Newman, M.: Subseasonal predictability of the North Atlantic Oscillation, Environ. Res. Lett., 16, 2021, https://doi.org/10.1088/1748-9326/abe781, 2021. a
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Short summary
We use an advanced statistical approach to investigate the dynamics of the development of sudden stratospheric warming (SSW) events in the winter Northern Hemisphere. We identify distinct signals that are representative of these events and their event type at lead times beyond currently predictable lead times. The results can be viewed as a promising step towards improving the predictability of SSWs in the future by using more advanced statistical methods in operational forecasting systems.
We use an advanced statistical approach to investigate the dynamics of the development of sudden...
