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Forschungsgruppe des Direktors

Die großräumige Dynamik der Ozeane und die Wechselwirkungen zwischen Ozean und Atmosphäre spielen eine grundlegende Rolle für das globale und regionale Klima und beeinflussen den Verlauf des Klimawandels. Meeresströmungen sorgen für die Umverteilung von Wärme, Süßwasser und Stoffen wie CO2. Die relativ langsamen Zeitskalen, auf denen Prozesse im Ozean ablaufen, und seine enorme Speicherkapazität machen den Ozean zum Schwungrad des Klimasystems.

Die Forschungsgruppe des Direktors untersucht die Dynamik der großräumigen Ozeanschwankungen und deren Auswirkungen unter verschiedenen klimatischen Hintergrundzuständen und unter den Bedingungen der globalen Erwärmung. Wir konzentrieren uns auf das Verständnis der Mechanismen, die Ozean- und Atmosphärenschwankungen auf Zeitskalen von einzelnen Tagen bis zu Hunderten von Jahren miteinander verbinden. Unsere Gruppe wendet Theorie- sowie Modellsysteme von unterschiedlicher Komplexität an, die von konzeptionellen Modellen bis hin zu Erdsystemmodellen (ESM) mit verschiedenen Auflösungen reichen. Wir spielen eine führende Rolle bei der Entwicklung des Ozeanmodells ICON-O und des ICON-ESM in seinen Konfigurationen für lange Zeitskalen (RUBY) und für kurze Zeitskalen (SAPPHIRE), einschließlich der anspruchsvollsten sturm- und wirbelauflösenden Modelle mit Gitterweiten im km-Bereich. Durch die Zusammenarbeit im Rahmen des Exzellenzclusters „Klima, Klimawandel und Gesellschaft“ (CLICCS, unter der Leitung der Universität Hamburg) erforscht unsere Gruppe darüber hinaus die Wechselwirkungen zwischen Klima und Wirtschaft.

Im Folgenden finden Sie eine Auswahl von Forschungsthemen, die die weitreichenden Interessen der Gruppe in den Bereichen Klimavariabilität, Ozeandynamik, Prozessverständnis, Modellentwicklung und Beziehungen zwischen Klima und Wirtschaft widerspiegeln.

Kleinräumige Prozesse, die das globale Klima beeinflussen

Neuartige sturm- und wirbelauflösende gekoppelte Ozean-Atmosphären-Modelle wie das ICON-ESM in seiner Sapphire-Konfiguration mit einer Auflösung von 5 km geben einen noch nie dagewesenen Einblick in Mechanismen, die auf kleinen räumlichen Skalen wirken. Ein Beispiel dafür ist die Bildung von Tiefenwasser in hohen Breiten, die in eng begrenzten Regionen mit einem starken Wärmeverlust vom Ozean an die Atmosphäre verbunden ist, gleichzeitig aber auch ein Teil der globalen Umwälzzirkulation ist. In einer Fallstudie (Gutjahr et al., 2022) dokumentieren wir die Entwicklung eines sehr intensiven Kaltluftausbruchs, eines sogenannten katabatischen Sturms an der Ostküste Grönlands, bei dem dem küstennahen Meer durch einen kalten und starken Fallwind enorme Wärmemengen entzogen werden. Das abgekühlte und damit dichtere Wasser sinkt dann in Tiefen von bis zu 1000 m ab. Die Ergebnisse der Studie legen nahe, dass die Auflösung solcher katabatischen Stürme in globalen Modellen die Lage und Intensität des Absinkens des globalen Förderbandes im subpolaren Nordatlantik beeinflussen könnte. Außerdem können die katabatischen Winde intensive Tiefdruckgebiete, sogenannte „Polartiefs“, auslösen, die über die Arktis ziehen und weit entfernte Regionen wie die Barentssee und Sibirien beeinflussen. Weitere Themen der Gruppe sind tropische Wirbelstürme (Kumar et al., 2022), Mischungsprozesse und Instabilitätswellen in den tropischen Ozeanen (Specht et al., 2021) und deren Wechselwirkung mit der Atmosphäre.

Personen: Juergen Bader, Nils Brüggemann, Swantje Bastin, Oliver Gutjahr, Johann Jungclaus, Arjun Kumar, Katja Lohmann, Jochem Marotzke, Tim Rohrschneider, Mia-Sophie Specht

Abbildung 1: Katabatischer Sturm in einer global gekoppelten ICON-Simulation mit einer sturm- und wirbelauflösenden Auflösung von 5 km, mit starken oberflächennahen Windgeschwindigkeiten (linkes Feld). Der katabatische Sturm entsteht durch die Kanalisierung der Strömung vom grönländischen Eisschild in den engen Tälern im Ammassalik-Gebiet (rechtes Feld), was zu einer Beschleunigung der oberflächennahen Windgeschwindigkeiten, aber auch zur Entstehung eines polaren Tiefs ("L" im linken Feld) führt.

Verbindungen zwischen der Arktis und den mittleren Breiten

In der arktischen Region wurde in den letzten Jahrzehnten die schnellste Oberflächenerwärmung weltweit beobachtet. Die Variabilität der Arktis kann das Wetter in entfernten Regionen beeinflussen, aber die Frage, wie und in welchem Ausmaß, ist umstritten. Wir untersuchen die dynamischen Prozesse, die das Wetter in der Arktis mit dem der mittleren Breiten verbinden, und verwenden dabei Klimamodellsimulationen und beobachtungsbasierten Reanalysen. In einer kürzlich erschienenen Publikation (Tyrlis et al., 2019) haben wir die zentrale Rolle der atmosphärischen Blockierung hervorgehoben, wenn Hochdrucksysteme stationär werden und wandernde Zyklone "blockieren" oder umleiten. Im Herbst und Frühwinter 2016-2017 wurden wiederholte Kälteeinbrüche über Eurasien in den mittleren Breiten, außergewöhnlich warme Bedingungen und Meereisverluste über der Arktis sowie eine für die Jahreszeit untypische Abschwächung des stratosphärischen Polarwirbels beobachtet. Atmosphärische Blockaden in der Uralregion spielten eine zentrale Rolle bei der Verknüpfung dieser Dynamik (Abbildung 2). Nach der ungewöhnlich niedrigen Meereisausdehnungin der Ostsibirischen-, der Tschuktschen- und der Beaufortsee im Frühherbst wurden blockierende Antizyklone während des gesamten Herbstes über Eurasien dominant. Wiederkehrenden Blocking-Ereignisse riefen Zirkulationsanomalien hervor, die zu Kaltluftadvektion nach Süden und Warmluftadvektion nach Norden führten. Dies führte im Spätherbst 2016 zu einem noch nie dagewesenen Meereisdefizit in der Barents-Kara-See. Gleichzeitig führten die wiederkehrenden Blocking-Ereignisse zu einer intensiven Aufwärtsbewegung der atmosphärischen Wellenaktivität, die im November zu einer für die Jahreszeit untypischen Abschwächung des stratosphärischen Wirbels führte. Wir konnten zeigen, dass die Auswirkungen dieser Abschwächung auf die Oberfläche mit der Verlagerung der Blockierungsaktivität und der Kältewellen nach Europa im Frühwinter 2017 in Verbindung gebracht werden können.

Personen: Daniela Matei, Jürgen Bader, Quan Liu, Katja Lohmann, Eliza Manzini

Abbildung 2: Schematische Darstellung der Dynamik zwischen den Extremen im Herbst und Frühwinter 2016-2017. Weiß schraffierte Bereiche markieren die Meereisdefizite, die über Ostsibirien, der Tschuktschensee, der Beaufortsee und der Barents- und Karasee beobachtet wurden. Rot bzw. blau schraffierte Bereiche markieren die Regionen mit Erwärmung bzw. Abkühlung, die durch atmosphärische Blockierung verursacht werden. In der Troposphäre markiert der Buchstabe H die bevorzugten Positionen der Blockierung über dem Ural im Herbst 2016 und über Europa im Frühwinter 2016-2017. In der Stratosphäre steht H für die anomal hohe geopotentielle Höhe über der Polkappe, die mit den troposphärischen Blockierungs-Ereignissen einhergeht.

Interne Klimavariabilität unter den Bedingungen der globalen Erwärmung und dekadischen Klimavorhersagen

Die natürliche Klimavariabilität umfasst die interne Variabilität, die spontan durch Prozesse und Rückkopplungen innerhalb des Klimasystems entsteht, und von außen erzwungene Variabilität, die beispielsweise durch Veränderungen der Sonnenaktivität und Vulkanausbrüche verursacht wird. Daher ist die interne Variabilität des Klimasystems eine der größten Unsicherheiten bei der Bewertung der aktuellen Klimaschwankungen und der modellgestützten Projektionen künftiger Klimatrends. Wie wirkt sich die globale Erwärmung auf das Ausmaß der internen Klimavariabilität aus? Inwieweit begrenzt die interne Klimavariabilität mehrjährige Vorhersagen des Klimasystems? Um die Auswirkungen des anthropogenen Antriebs auf die interne Klimavariabilität auf verschiedenen Zeitskalen zu untersuchen, verwenden wir Klimamodellsimulationen, die entweder mit der besten Schätzung des aktuellen Zustands des Ozeans und der Atmosphäre (Matei et al., 2012) oder mit einer Reihe von plausiblen Anfangsbedingungen gestartet wurden, um große Ensembles zu erstellen. Insbesondere das MPI Grand Ensemble (Maher et al., 2019) besteht aus einer Vielzahl (bis zu 100) von Modellsimulationen. Sie unterscheiden sich geringfügig in ihren Ausgangsbedingungen, unterliegen aber den gleichen externen Einflüssen, d. h. zunehmenden Treibhausgasen, Vulkanausbrüchen, Landnutzung und Aerosolen. Mit diesen Instrumenten können wir die Unsicherheit durch interne Klimavariabilität für langfristige Projektionen einschränken (Olonscheck und Notz, 2017; Marotzke, 2019; Olonscheck et al., 2021). In einem weiteren Forschungsfeld analysieren wir die Genauigkeit von mittelfristigen Klimaprognosen in Abhängigkeit von Modelleigenschaften wie der numerischen Auflösung. Zum Beispiel untersuchen wir die Vorteile von wirbelauflösenden Ozeankonfigurationen in einer Fallstudie zur Entwicklung eines Kälteereignisses im subpolaren Nordatlantik und der europäischen Hitzewelle im Jahr 2015.

Auch bevor der Mensch einen spürbaren Einfluss auf das Klima ausübte gab es Klimaschwankungen auf allen Zeitskalen. Einige dieser Schwankungen stellen unser Verständnis vor faszinierende Herausforderungen. Zum Beispiel war die Erde vor etwa 700 Millionen Jahren vollständig von Eis und Schnee bedeckt. Wir untersuchen derzeit das Rätsel, wie die Erde aus diesem "Schneeball"-Zustand durch das anschließende Super-Treibhaus in ein gemäßigteres Klima gelangt ist (Ramme und Marotzke, 2022).

Personen: Dirk Olonscheck, Daniela Matei, Jürgen Bader, Oliver Gutjahr, Johann Jungclaus, Quan Liu, Katja Lohmann, Jochem Marotzke, Lennart Ramme

Klima-Wirtschaft-Wechselwirkungen

Wir wollen verstehen, wie Unsicherheiten und Schwankungen in natürlichen und gesellschaftlichen Prozessen zusammenwirken, indem wir plausiblere Szenarien der Klimazukunft erstellen. Der Klimawandel vollzieht sich über längere Zeiträume, so dass gesellschaftliche Akteure, zum Beispiel aus Politik und Wirtschaft, oft nicht direkt auf aktuelle Klimaereignisse reagieren können. Sie müssen sich auf wissenschaftliche Projektionen und Vorhersagen darüber verlassen, welche Veränderungen durch den Klimawandel wahrscheinlich werden. Diese Vorhersagen müssen auf die Bedürfnisse der Entscheidungsträger*innen zugeschnitten sein. 

So haben wir beispielsweise festgestellt, dass die Begrenzung der Oberflächentemperatur als klimapolitische Maßnahme nicht ausreicht, um den Anstieg des Meeresspiegels – eine der schwerwiegendsten Folgen der globalen Erwärmung – zu kontrollieren. Unter Anwendung eines Klima-Energie-Wirtschaftsmodells mit verbesserter Ozeanphysik haben wir den Meeresspiegel als Klimaziel eingeführt und zeigen, dass das Meeresspiegelziel ein optimales Temperaturüberschreitungsprofil liefert, bei dem ein bestimmtes Klimaziel zunächst überschritten wird, bevor die Temperatur auf dem angestrebten Niveau stabilisiert werden kann (Abb. 3a). Sowohl ein maximales Meeresspiegelziel als auch die Definition einer maximalen Anstiegsrate (Abb. 3b) führen zu geringeren Folgekosten und einer effektiveren langfristigen Stabilisierung des Meeresspiegels (Li et al., 2020).

Personen: Chao Li, Jochem Marotzke

Abbildung 3: (a) Veränderung der globalen Oberflächentemperatur und (b) Ökonomische Verluste bei einem Temperaturziel (Rot), einem Ziel für den Anstieg des Meeresspiegels (durchgehend Blau) und einem Ziel für die Anstiegsrate (gestrichelt Blau)

Modellentwicklung

Die Forschungsgruppe des Direktors beteiligt sich an der Entwicklung des Ozeanmodells ICON-O (Korn et al., 2022) und des Erdsystemmodells ICON-ESM (Jungclaus et al., 2022) mit dem Ziel, die neue Generation von ICON-ESM als Standard-Forschungswerkzeug für die experiment-orientierte Forschungsstrategie am Max-Planck-Institut für Meteorologie bereitzustellen. In Zusammenarbeit mit der MPI-M Arbeitsgruppe Angewandte Mathematik und Computer-basierte Physik sowie der Abteilung Theoretische Ozeanographie der Universität Hamburg liefern wir Beiträge zur Weiterentwicklung von ICON-O durch verbesserte physikalische Parametrisierungen. Im Rahmen von ICON Sapphire erforschen wir die Grenzen der hochauflösenden (weniger als ein Kilometer) Modellierung für die Untersuchung von sub-mesoskaligen Prozessen (Abbildung 4).

Personen: Nils Brüggemann, Oliver Gutjahr, Helmuth Haak, Johann Jungclaus, Stephan Lorenz, Lennart Ramme, Jochem Marotzke

Abbildung 4: Hochauflösende ICON-O „Submesoscale Telescope-Wave“-Simulation mit Fokus auf die Region des Walfischrückens im südöstlichen Südatlantik. Die horizontale Gitterauflösung ist bis auf 530 m in einem lokalen Fokusgebiet verfeinert. Mit dieser einzigartig hohen Auflösung können nicht nur mesoskalige Wirbel wie die markanten Agulhas-Ringe aufgelöst werden (große blaue Wirbelsignale in der Abbildung), sondern auch wesentlich feinere Strukturen, sogenannte submesoskalige Wirbel. Farbige Schattierungen zeigen die relative Wirbelstärke an, die durch den lokalen Coriolis-Parameter skaliert wird. Diese Größe gibt an, wie stark die Meeresströmung rotiert. Die beiden Nahaufnahmen auf der rechten Seite zeigen die stark rotierenden submesoskaligen Wirbel am Rande eines Agulhas-Rings. Mit dieser neuartigen Simulation können wir die Wechselwirkungen und Energieübertragungen zwischen den submesoskaligen Wirbeln, der mesoskaligen Strömung und den Gezeiten untersuchen. Zwei Beobachtungskampagnen (SONETT I und II), die im Rahmen des Sonderforschungsbereichs TRR181 organisiert werden, werden die Modelldaten ergänzen.

Jungclaus, J. H., Lorenz, S. J., Schmidt, H., Brovkin, V., Brüggemann, N., Chegini, F., et al. (2022): The ICON Earth System Model version 1.0. Journal of Advances in Modeling Earth Systems, 14, e2021MS002813. doi.org/10.1029/2021MS002813

Korn, P., Brüggemann, N., Jungclaus, J.H., Lorenz, S.J., Gutjahr, O., Haak, H., et al. (2022): ICON-O: The Ocean Component of the ICON Earth System Model - Global Simulation Characteristics and Local Telescoping Capability. Journal of Advances in Modeling Earth Systems, 14, e2021MS002952. doi.org/10.1029/2021MS002952

Kumar, A. U., Brüggemann, N., Smith, R. K., & Marotzke, J. (2022). Response of a tropical cyclone to a subsurface ocean eddy and the role of boundary layer dynamics. Quarterly Journal of the Royal MeteorologicalSociety, 148(742), 378-402.

Li, C., Held, H., Hokamp, S., & Marotzke, J. (2020). Optimal temperature overshoot profile found by limiting global sea level rise as a lower-cost climate target. Science Advances, 6(2), eaaw9490.

Maher, N., Milinski, S., Suarez‐Gutierrez, L., Botzet, M., Dobrynin, M., Kornblueh, L., … & Marotzke, J. (2019). The Max Planck Institute Grand Ensemble: enabling the exploration of climate system variability. Journal of Advances in Modeling Earth Systems, 11(7), 2050-2069.

Marotzke, J. (2019). Quantifying the irreducible uncertainty in near-term climate projections. Wiley InterdisciplinaryReviews: Climate Change, 10, e563.

Matei, D., H. Pohlmann, J. Jungclaus, W. Müller, H. Haak, and J. Marotzke, 2012: Two tales of initializing decadal climate predictions experiments with the ECHAM5/MPI-OM model. Journal ofClimate, 25, 8502–8523.

Olonscheck, D., & Notz, D. (2017). Consistently estimating internal climate variability from climate model simulations. Journal of Climate, 30(23), 9555-9573.

Olonscheck, D., Schurer, A. P., Lücke, L., & Hegerl, G. C. (2021). Large-scale emergence of regional changes in year-to-year temperature variability by the end of the 21st century. Nature Communications, 12(1), 1-10.

Ramme, L., and J. Marotzke, 2022: Climate and ocean circulation in the aftermath of a Marinoan snowball Earth. Climate of the Past, 18, 759-774.

Specht, M. S., Jungclaus, J., & Bader, J. (2021). Identifying and characterizing subsurface tropical instability waves in the Atlantic Ocean in simulations and observations. Journal of Geophysical Research: Oceans, 126(10), e2020JC017013.

Tyrlis, E., Manzini, E., Bader, J., Ukita, J., Nakamura, H., and Matei, D. (2019) Ural Blocking driving extreme Arctic sea-ice loss, cold Eurasia and stratospheric vortex weakening in autumn and early winter 2016-2017. Journal of GeophysicalResearch Atmosphere, 124, 11313– 11329. doi:10.1029/2019JD031085.

Gruppenmitglieder und Publikationen

Name
Email
Position
Telefon
Raum
Botzet, Michael
Wiss. Programmierer*in
+49 40 41173-137
B 210
Dhame, Shreya
Postdoc
+49 40 41173-310
B 232
Haak, Helmuth
Wiss. Programmierer*in
+49 40 41173-367
B 228
Jungclaus, Johann
Gruppenleiter*in
+49 40 41173-109
B 219
Kampmann, Cornelia
Assistenz
+49 40 41173-467
B 202
Karvinen, Mikael
Doktorand*in
+49 40 41173-116
B 206
Kraus, Simeon
Stud. Hilfskraft
Kumar, Arjun
Postdoc
+49 40 41173-280
B 122
Li, Chao
Research Scientist
+49 40 41173-164
B 218
Liu, Quan
Doktorand*in
+49 40 41173-205
B 227
Lohmann, Katja
Research Scientist
+49 40 41173-137
B 210
Lorenz, Stephan
Wiss. Programmierer*in
+49 40 41173-156
B 224
Marotzke, Jochem
Direktor*in
+49 40 41173-440/311
B 215
Matei, Daniela
Research Scientist
+49 40 41173-460
B 205
Müller, Kornelia
Assistenz
+49 40 41173-311
B 214
Ramme, Lennart
Postdoc
+49 40 41173-162
B 216
Rapanague, Maria-Jesus
Doktorand*in
+49 40 41173-205
B 227
Specht, Mia Sophie
Postdoc
+49 40 41173-168
B 209
  • Bastin, S., Koldunov, A., Schütte, F., Gutjahr, O., Mrozowska, M., Fischer, T., Shevchenko, R., Kumar, A., Koldunov, N., Haak, H., Brüggemann, N., Hummels, R., Specht, M., Jungclaus, J., Danilov, S., Dengler, M. & Jochum, M. (2024). Sensitivity of the tropical Atlantic to vertical mixing in two ocean models (ICON-O v2.6.6 and FESOM v2.5) (open for discussions). doi:10.5194/egusphere-2024-2281 [Preprint] [pre-print]
  • Bishnoi, A., Stein, O., Meyer, C., Redler, R., Eicker, N., Haak, H., Hoffmann, L., Klocke, D., Kornblueh, L. & Suarez, E. (2024). Earth system modeling on modular supercomputing architecture: coupled atmosphere-ocean simulations with ICON 2.6.6-rc. Geoscientific Model Development, 17, 261-273. doi:10.5194/gmd-17-261-2024 [publisher-version]
  • Brüggemann, N., Losch, M., Scholz, P., Pollmann, F., Danilov, S., Gutjahr, O., Jungclaus, J., Koldunov, N., Korn, P., Olbers, D. & Eden, C. (2024). Parameterized internal wave mixing in three ocean general circulation models. Journal of Advances in Modeling Earth Systems, 16: e2023MS003768. doi:10.1029/2023MS003768 [research-data][publisher-version]
  • Di Capua, G., Tyrlis, E., Matei, D. & Donner, R. (2024). Tropical and mid-latitude causal drivers of the eastern Mediterranean Etesians during boreal summer. Climate Dynamics. doi:10.1007/s00382-024-07411-y [publisher-version]
  • García-Pereira, F., González-Rouco, J., Melo-Aguilar, C., Steinert, N., García-Bustamante, E., de Vrese, P., Jungclaus, J., Lorenz, S., Hagemann, S., Cuesta-Valero, F., García-García, A. & Beltrami, H. (2024). First comprehensive assessment of industrial-era land heat uptake from multiple sources. Under open review for Earth System Dynamics. Earth System Dynamics, 15, 547-564. doi:10.5194/esd-15-547-2024 [publisher-version]
  • Ghosh, R., Manzini, E., Gao, Y., Gastineau, G., Cherchi, A., Frankignoul, C., Liang, Y.-C., Kwon, Y.-O., Suo, L., Tyrlis, E., Mecking V, J., Tian, T., Zhang, Y. & Matei, D. (2024). Observed winter Barents Kara Sea ice variations induce prominent sub-decadal variability and a multi-decadal trend in the Warm Arctic Cold Eurasia pattern. Environmental Research Letters, 19: 024018. doi:10.1088/1748-9326/ad1c1a [publisher-version][supplementary-material]
  • Gutjahr, O. & Mehlmann, C. (2024). Polar lows and their effects on sea ice and the upper ocean in the Iceland, Greenland and Labrador Seas. Journal of Geophysical Research: Oceans, 129: e2023JC020258. doi:10.1029/2023JC020258 [supplementary-material][publisher-version]
  • Jin, Y., Köhl, A., Jungclaus, J. & Stammer, D. (2024). Mechanisms of projected sea-level trends and variability in the Southeast Asia region based on MPI-ESM-ER. Climate Dynamics, 62, 973-988. doi:10.1007/s00382-023-06960-y [publisher-version]
  • Karpechko, A., Wu, Z., Simpson, I., Kretschmer, M., Afargan-Gerstman, H., Butler, A., Domeisen, D., Garny, H., Lawrence, Z., Manzini, E. & Sigmond, M. (2024). Northern hemisphere stratosphere-troposphere circulation change in CMIP6 models: 2. mechanisms and sources of the spread. Journal of Geophysical Research: Atmospheres, 129: e2024JD040823.. doi:10.1029/2024JD040823 [publisher-version][supplementary-material]
  • Li, D., Zhou, T., Qi, Y., Zou, L., Li, C., Zhang, W. & Chen, X. (2024). Future reduction of cold extremes over East Asia due to thermodynamic and dynamic warming. Atmospheric Chemistry and Physics, 24, 7347-7358. doi:10.5194/acp-24-7347-2024 [publisher-version]
  • Liu, W., Li, S., Li, C., Rugenstein, M. & Thomas, A. (2024). Contrasting fast and slow intertropical convergence zone migrations linked to delayed Southern Ocean warming. Nature Climate Change, 14, 732-739. doi:10.1038/s41558-024-02034-x
  • Lott, F., Rani, R., McLandress, C., Podglajen, A., Bushell, A., Bramberger, M., Lee, H.-K., Alexander, J., Anstey, J., Chun, H.-Y., Hertzog, A., Kim, Y.-H., Kawatani, Y., Legras, B., Manzini, E., Naoe, H., Osprey, S., Plougonven, R., Pohlmann, H., Richter, J., Scinocca, J., Serrano, J., Serva, F., Stockdale, T., Versick, S., Watanabe, S. & Yoshida, K. (2024). Comparison between non-orographic gravity-wave parameterizations used in QBOi models and Strateole 2 constant-level balloons. Quarterly Journal of the Royal Meteorological Society. doi:10.1002/qj.4793 [publisher-version][supplementary-material]
  • Manzini, E., Ayarzagüena, B., Calvo, N. & Matei, D. (2024). Nonlinearity and asymmetry of the ENSO stratospheric pathway – Revisited. Journal of Geophysical Research: Atmospheres, 129: e2023JD039992. doi:10.1029/2023JD039992 [publisher-version]
  • Mrozowska, M., Jochum, M., Bastin, S., Hummels, R., Koldunov, A., Dengler, M., Fischer, T., Nuterman, R. & Hansen, R. (2024). Using NIW observations to assess mixed layer parameterizations. Journal of Geophysical Research: Oceans, 129: e2024JC020985. doi:10.1029/2024JC020985
  • Olonscheck, D. & Rugenstein, M. (2024). Coupled climate models systematically underestimate radiation response to surface warming. Geophysical Research Letters, 51: e2023GL106909. doi:10.1029/2023GL106909 [supplementary-material][publisher-version]
  • Ramme, L., Ilyina, T. & Marotzke, J. (2024). Moderate greenhouse climate and rapid carbonate formation after Marinoan snowball Earth. Nature Communications, 15: 3571. doi:10.1038/s41467-024-47873-6 [publisher-version]
  • Ritschel, M. (2024). A transforming Arctic: unraveling climate change impacts on sea-ice evolution and oceanic pCO2. Phd Thesis, Berichte zur Erdsystemforschung, 281. [publisher-version]
  • Song, J., Song, F., Feng, Z., Leung, L., Li, C. & Wu, L. (2024). Realistic precipitation diurnal cycle in global convection-permitting models by resolving mesoscale convective systems. Geophysical Research Letters, 51: e2024GL109945. doi:10.1029/2024GL109945 [publisher-version]
  • Specht, M., Jungclaus, J. & Bader, J. (in press). Seasonality of subsurface shear instabilities at tropical instability wave fronts in the Atlantic Ocean in a high-resolution simulation. Journal of Geophysical Research: Oceans, 129: e2023JC020041. doi:10.1029/2023JC020041 [research-data][publisher-version]
  • Steinert, N., Cuesta‐Valero, F., García‐Pereira, F., de Vrese, P., Melo Aguilar, C., García‐Bustamante, E., Jungclaus, J. & González‐Rouco, J. (2024). Underestimated land heat uptake alters the global energy distribution in CMIP6 climate models. Geophysical Research Letters, 51: e2023GL107613. doi:10.1029/2023GL107613 [publisher-version][supplementary-material]
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  • Roeckner, E., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kornblueh, L., Manzini, E., Schlese, U. & Schulzweida, U. (2004). The atmospheric general circulation model ECHAM5 Part II: Sensitivity of simulated climate to horizontal and vertical resolution. Report / Max-Planck-Institut für Meteorologie, 354. [publisher-version]
  • Smith, R., Dubois, C. & Marotzke, J. (2004). Ocean circulation and climate in an idealised Pangean OAGCM. Geophysical Research Letters, 31(18): L18207. doi:10.1029/2004GL020643 [publisher-version]
  • Gorbunov, M. & Kornblueh, L. (2003). Analysis and validation of challenging minisatellite payload (CHAMP) radio occultation data. Journal of Geophysical Research: Atmospheres, 108: 4584. doi:10.1029/2002JD003175 [publisher-version]
  • Gorbunov, M. & Kornblueh, L. (2003). Principles of variational assimilation of GNSS radio occultation data. Report / Max-Planck-Institut für Meteorologie, 350. [publisher-version]
  • Haak, H., Jungclaus, J., Mikolajewicz, U. & Latif, M. (2003). Formation and propagation of great salinity anomalies. Geophysical Research Letters, 30(9), 26-1-26-4: 1473. doi:10.1029/2003GL017065 [publisher-version]
  • Marsland, S., Haak, H., Jungclaus, J., Latif, M. & Röske, F. (2003). The Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear coordinates. Ocean Modelling, 5(2), 91-127. doi:10.1016/S1463-5003(02)00015-X
  • Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E., Rhodin, A., Schlese, U., Schulzweida, U. & Tompkins, A. (2003). The atmospheric general circulation model ECHAM 5. PART I: Model description. Report / Max-Planck-Institut für Meteorologie, 349. [publisher-version]

Kontakt

Prof. Dr. Jochem Marotzke

Direktor
Tel: +49 (0)40 41173-440
jochem.marotzke@we dont want spammpimet.mpg.de

Dr. Johann Jungclaus

Gruppenleiter
Tel: +49 (0)40 41173-109
johann.jungclaus@we dont want spammpimet.mpg.de

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