Oliver Gutjahr

Max Planck Institute for Meteorology

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Johann Jungclaus

Max Planck Institute for Meteorology

Günther Heinemann

Universität Trier

Helmuth Haak

Max Planck Institute for Meteorology

Dian Putrasahan

Max Planck Institute for Meteorology

Nils Brüggemann

Max Planck Institute for Meteorology

Jin‐Song von Storch

Hamburg Institut (Germany)

Katja Lohmann

Max Planck Institute for Meteorology

Malcolm Roberts

Met Office

Jochem Marotzke

Max Planck Institute for Meteorology

Carolin Mehlmann

Otto-von-Guericke University Magdeburg

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Max Planck Institute for Meteorology

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Max Planck Society

Universität Hamburg

Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung

European Centre for Medium-Range Weather Forecasts

German Climate Computing Centre

Centre National de la Recherche Scientifique

NSF National Center for Atmospheric Research

ETH Zurich

Universitat Politècnica de Catalunya

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The ICON Earth System Model Version 1.0 1

Johann Jungclaus Stephan Lorenz Hauke Schmidt Victor Brovkin Natalia Brüggemann

• This work documents ICON-ESM 1.0, the first version of a coupled model based 19 on the ICON framework 20 • Performance of ICON-ESM is assessed by means of CMIP6 DECK experiments 21 at standard CMIP-type resolution 22 • ICON-ESM reproduces the observed temperature evolution. Biases in clouds, winds, 23 sea-ice, and ocean properties are larger than in MPI-ESM. Abstract 25 This work documents the ICON-Earth System Model (ICON-ESM V1.0), the first cou-26 pled model based on the ICON (ICOsahedral Non-hydrostatic) framework with its un-27 structured, icosahedral grid concept. The ICON-A atmosphere uses a nonhydrostatic dy-28 namical core and the ocean model ICON-O builds on the same ICON infrastructure, but 29 applies the Boussinesq and hydrostatic approximation and includes a sea-ice model. The 30 ICON-Land module provides a new framework for the modelling of land processes and 31 the terrestrial carbon cycle. The oceanic carbon cycle and biogeochemistry are repre-32 sented by the Hamburg Ocean Carbon Cycle module. We describe the tuning and spin-33 up of a base-line version at a resolution typical for models participating in the Coupled 34 Model Intercomparison Project (CMIP). The performance of ICON-ESM is assessed by 35 means of a set of standard CMIP6 simulations. Achievements are well-balanced top-of-36 atmosphere radiation, stable key climate quantities in the control simulation, and a good 37 representation of the historical surface temperature evolution. The model has overall bi-38 ases, which are comparable to those of other CMIP models, but ICON-ESM performs 39 less well than its predecessor, the Max Planck Institute Earth System Model. Problem-40 atic biases are diagnosed in ICON-ESM in the vertical cloud distribution and the mean 41 zonal wind field. In the ocean, sub-surface temperature and salinity biases are of con-42 cern as is a too strong seasonal cycle of the sea-ice cover in both hemispheres. ICON-43 ESM V1.0 serves as a basis for further developments that will take advantage of ICON-44 specific properties such as spatially varying resolution, and configurations at very high 45 resolution. 46 Plain Language Summary 47 ICON-ESM is a completely new coupled climate and earth system model that ap-48 plies novel design principles and numerical techniques. The atmosphere model applies 49 a non-hydrostatic dynamical core, both atmosphere and ocean models apply unstruc-50 tured meshes, and the model is adapted for high-performance computing systems. This 51 article describes how the component models for atmosphere, land, and ocean are cou-52 pled together and how we achieve a stable climate by setting certain tuning parameters 53 and performing sensitivity experiments. We evaluate the performance of our new model 54 by running a set of experiments under pre-industrial and historical climate conditions 55 as well as a set of idealized greenhouse-gas-increase experiments. These experiments were 56 designed by the Coupled Model Intercomparison Project (CMIP) and allow us to com-57 pare the results to those from other CMIP models and the predecessor of our model, the 58 Max Planck Institute for Meteorology Earth System Model. While we diagnose overall 59 satisfactory performance, we find that ICON-ESM features somewhat larger biases in 60 several quantities compared to its predecessor at comparable grid resolution. We empha-61 size that the present configuration serves as a basis from where future development steps 62 will open up new perspectives in earth system modelling. 63

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Earth system science

10.1002/essoar.10510175.1

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Citations (9)

Does applying quantile mapping to subsamples improve the bias correction of daily precipitation?

International Journal of Climatology (2017)

Philipp Reiter Oliver Gutjahr Lukas Schefczyk Günther Heinemann Markus Casper

ABSTRACT Quantile mapping (QM) is routinely applied in many climate change impact studies for the bias correction (BC) of daily precipitation data. It corrects the complete distribution, but does not correct for errors in the annual cycle. Therefore, QM is often applied separately to temporal subsamples of the data (e.g. each calendar month), which reduces the calibration sample size. The question arises whether this sample size reduction negates the benefit from applying QM to temporal subsamples. We applied four QM methods in a cross‐validation approach to 40 years of daily precipitation data from 10 regional climate model (RCM) hindcast runs, without and with (semi‐annual, seasonal, and monthly) subsampling. QM subsampling improved the BC of daily RCM precipitation; less distinct for independent data but considerably for the calibration data. The optimal subsampling timescale for the correction of independent data depended on the chosen QM method and ranged between semi‐annual and monthly. Overall, a sub‐annual QM improves the forcing for climate change impact studies and thus their reliability.

Quantile

Hindcast

Forcing (mathematics)

10.1002/joc.5283

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Citations (64)

The ICON Earth System Model Version 1.0

Johann Jungclaus Stephan Lorenz Hauke Schmidt Oliver Gutjahr Helmuth Haak

Earth and Space Science Open Archive This preprint has been submitted to and is under consideration at Journal of Advances in Modeling Earth Systems (JAMES). ESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing the latest version by default [v1]The ICON Earth System Model Version 1.0AuthorsJohann HJungclausiDStephan J.LorenzHaukeSchmidtiDOliverGutjahriDHelmuthHaakiDCarolinMehlmanniDUweMikolajewiczDirkNotziDDianPutrashanJin-Songvon StorchLinardakisLeonidasiDVictorBrokviniDFatemehCheginiVeronikaGayleriDMarco A.GiorgettaStefanHagemannTatianaIlyinaiDPeterKorniDJürgenKrögeriDWolfgang A.MüllerHolgerPohlmanniDThomas JürgenRaddatzLennartRammeiDReick H.ChristianRainerSchneckReinerSchnuriDBjornStevensiDFlorian AndreasZiemenMartinClausseniDJochemMarotzkeiDFabianWachsmannMartinSchupfnerThomasRiddickiDKarl-HermannWienersiDNilsBrueggemannReneRedlerPhilippde VreseJulia Esther Marlene SophiaNabeliDTeffySamMoritzHankeSee all authors Johann H JungclausiDCorresponding Author• Submitting AuthorMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0002-3849-4339view email addressThe email was not providedcopy email addressStephan J. LorenzMax Planck Institute of Meteorologyview email addressThe email was not providedcopy email addressHauke SchmidtiDMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0001-7977-5041view email addressThe email was not providedcopy email addressOliver GutjahriDUniversität HamburgiDhttps://orcid.org/0000-0002-3116-8071view email addressThe email was not providedcopy email addressHelmuth HaakiDMax-Planck-Institut fuer MeteorologieiDhttps://orcid.org/0000-0002-9883-5086view email addressThe email was not providedcopy email addressCarolin MehlmanniDMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0001-7329-5178view email addressThe email was not providedcopy email addressUwe MikolajewiczMax Planck Institute for Meteorologyview email addressThe email was not providedcopy email addressDirk NotziDMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0003-0365-5654view email addressThe email was not providedcopy email addressDian PutrashanMax Planck Institute for Meteorologyview email addressThe email was not providedcopy email addressJin-Song von StorchMax-Plank Institute for Meteorologyview email addressThe email was not providedcopy email addressLinardakis LeonidasiDMax Planck Institute for Meteorology (MPG)iDhttps://orcid.org/0000-0002-0531-6923view email addressThe email was not providedcopy email addressVictor BrokviniDMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0001-6420-3198view email addressThe email was not providedcopy email addressFatemeh CheginiMax-Planck-Institute for Meteorologyview email addressThe email was not providedcopy email addressVeronika GayleriDMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0003-4069-5444view email addressThe email was not providedcopy email addressMarco A. GiorgettaMax Planck Institute for Meteorologyview email addressThe email was not providedcopy email addressStefan HagemannHelmholtz-Zentrum Hereonview email addressThe email was not providedcopy email addressTatiana IlyinaiDMax Planck Institute of MeteorologyiDhttps://orcid.org/0000-0002-3475-4842view email addressThe email was not providedcopy email addressPeter KorniDMPI-MetiDhttps://orcid.org/0000-0002-7525-5732view email addressThe email was not providedcopy email addressJürgen KrögeriDMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0002-6815-4220view email addressThe email was not providedcopy email addressWolfgang A. MüllerMax Planck Institute for Meteorologyview email addressThe email was not providedcopy email addressHolger PohlmanniDMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0003-1264-0024view email addressThe email was not providedcopy email addressThomas Jürgen RaddatzMax Planck Institute for Meteorologyview email addressThe email was not providedcopy email addressLennart RammeiDMax-Planck-Institute for MeteorologyiDhttps://orcid.org/0000-0002-8307-2493view email addressThe email was not providedcopy email addressReick H. ChristianMax Planck Institute for Meteorologyview email addressThe email was not providedcopy email addressRainer SchneckMax Planck Institute for Meteorologyview email addressThe email was not providedcopy email addressReiner SchnuriDMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0002-7380-8313view email addressThe email was not providedcopy email addressBjorn StevensiDMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0003-3795-0475view email addressThe email was not providedcopy email addressFlorian Andreas ZiemenDeutsches Klimarechenzentrumview email addressThe email was not providedcopy email addressMartin ClausseniDMax Planck Institute for Meteorology (MPG)iDhttps://orcid.org/0000-0001-6225-5488view email addressThe email was not providedcopy email addressJochem MarotzkeiDMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0001-9857-9900view email addressThe email was not providedcopy email addressFabian WachsmannDKRZview email addressThe email was not providedcopy email addressMartin SchupfnerDKRZview email addressThe email was not providedcopy email addressThomas RiddickiDMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0002-9364-0343view email addressThe email was not providedcopy email addressKarl-Hermann WienersiDMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0003-3797-7694view email addressThe email was not providedcopy email addressNils BrueggemannMax Planck Institute for Meteorologyview email addressThe email was not providedcopy email addressRene RedlerMax Planck Institute for Meteorologyview email addressThe email was not providedcopy email addressPhilipp de VreseMax Planck Institute for Meteorologyview email addressThe email was not providedcopy email addressJulia Esther Marlene Sophia NabeliDMax Planck Institute for MeteorologyiDhttps://orcid.org/0000-0002-8122-5206view email addressThe email was not providedcopy email addressTeffy SamMax Planck Institute for Meteorologyview email addressThe email was not providedcopy email addressMoritz HankeDKRZview email addressThe email was not providedcopy email address

10.1002/essoar.10507989.1

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Citations (13)

Bias correction of ENSEMBLES precipitation data with focus on the effect of the length of the calibration period

Meteorologische Zeitschrift (2015)

Philipp Reiter Oliver Gutjahr Lukas Schefczyk Günther Heinemann Markus Casper

Period length

10.1127/metz/2015/0714

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Citations (24)

Sensitivity of the tropical Atlantic to vertical mixing in two ocean models (ICON-O v2.6.6 and FESOM v2.5)

Swantje Bastin А. В. Колдунов Florian Schütte Oliver Gutjahr Marta Mrozowska

Abstract. Ocean General Circulation Models still have large upper-ocean biases e.g. in tropical sea surface temperature, possibly connected to the representation of vertical mixing. In earlier studies, the ocean vertical mixing parameterisation has usually been tuned for a specific site or only within a specific model. We present here a systematic comparison of the effects of changes in the vertical mixing scheme in two different global ocean models, ICON-O and FESOM, run at a horizontal resolution of 10 km in the tropical Atlantic. We test two commonly used vertical mixing schemes; the K-Profile Parameterisation (KPP) and the Turbulent Kinetic Energy (TKE) scheme. Additionally, we vary tuning parameters in both schemes, and test the addition of Langmuir turbulence in the TKE scheme. We show that the biases of mean sea surface temperature, subsurface temperature, subsurface currents and mixed layer depth differ more between the two models than between runs with different mixing scheme settings within each model. For ICON-O, there is a larger difference between TKE and KPP than for FESOM. In both models, varying the tuning parameters hardly affects the pattern and magnitude of the mean state biases. For the representation of smaller scale variability like the diurnal cycle or inertial waves, the choice of the mixing scheme can matter: the diurnally enhanced penetration of equatorial turbulence below the mixed layer is only simulated with TKE, not with KPP. However, tuning of the parameters within the mixing schemes does not lead to large improvements for these processes. We conclude that a substantial part of the upper ocean tropical Atlantic biases is not sensitive to details of the vertical mixing scheme.

Mixed layer

Langmuir Turbulence

Ocean dynamics

10.5194/egusphere-2024-2281

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Citations (1)

Comparing bias correction methods for high-resolution COSMO-CLM daily precipitation fields

EGUGA (2012)

Oliver Gutjahr Günther Heinemann

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Max Planck Institute Earth System Model (MPI-ESM1.2) for the High-Resolution Model Intercomparison Project (HighResMIP)

Geoscientific model development (2019)

Oliver Gutjahr Dian Putrasahan Katja Lohmann Johann Jungclaus Jin‐Song von Storch

Abstract. As a contribution towards improving the climate mean state of the atmosphere and the ocean in Earth system models (ESMs), we compare several coupled simulations conducted with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1.2) following the HighResMIP protocol. Our simulations allow to analyse the separate effects of increasing the horizontal resolution of the ocean (0.4 to 0.1∘) and atmosphere (T127 to T255) submodels, and the effects of substituting the Pacanowski and Philander (PP) vertical ocean mixing scheme with the K-profile parameterization (KPP). The results show clearly distinguishable effects from all three factors. The high resolution in the ocean removes biases in the ocean interior and in the atmosphere. This leads to the important conclusion that a high-resolution ocean has a major impact on the mean state of the ocean and the atmosphere. The T255 atmosphere reduces the surface wind stress and improves ocean mixed layer depths in both hemispheres. The reduced wind forcing, in turn, slows the Antarctic Circumpolar Current (ACC), reducing it to observed values. In the North Atlantic, however, the reduced surface wind causes a weakening of the subpolar gyre and thus a slowing down of the Atlantic meridional overturning circulation (AMOC), when the PP scheme is used. The KPP scheme, on the other hand, causes stronger open-ocean convection which spins up the subpolar gyres, ultimately leading to a stronger and stable AMOC, even when coupled to the T255 atmosphere, thus retaining all the positive effects of a higher-resolved atmosphere.

10.5194/gmd-12-3241-2019

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Citations (320)

Supplementary material to "Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models"

Eduardo Moreno‐Chamarro Louis‐Philippe Caron Saskia Loosveldt Tomas Oliver Gutjahr Marie‐Pierre Moine

10.5194/gmd-2021-209-supplement

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The ICON Earth System Model Version 1.0

Journal of Advances in Modeling Earth Systems (2022)

Johann Jungclaus Stephan Lorenz Hauke Schmidt Victor Brovkin Nils Brüggemann

Abstract This work documents the ICON‐Earth System Model (ICON‐ESM V1.0), the first coupled model based on the ICON (ICOsahedral Non‐hydrostatic) framework with its unstructured, icosahedral grid concept. The ICON‐A atmosphere uses a nonhydrostatic dynamical core and the ocean model ICON‐O builds on the same ICON infrastructure, but applies the Boussinesq and hydrostatic approximation and includes a sea‐ice model. The ICON‐Land module provides a new framework for the modeling of land processes and the terrestrial carbon cycle. The oceanic carbon cycle and biogeochemistry are represented by the Hamburg Ocean Carbon Cycle module. We describe the tuning and spin‐up of a base‐line version at a resolution typical for models participating in the Coupled Model Intercomparison Project (CMIP). The performance of ICON‐ESM is assessed by means of a set of standard CMIP6 simulations. Achievements are well‐balanced top‐of‐atmosphere radiation, stable key climate quantities in the control simulation, and a good representation of the historical surface temperature evolution. The model has overall biases, which are comparable to those of other CMIP models, but ICON‐ESM performs less well than its predecessor, the Max Planck Institute Earth System Model. Problematic biases are diagnosed in ICON‐ESM in the vertical cloud distribution and the mean zonal wind field. In the ocean, sub‐surface temperature and salinity biases are of concern as is a too strong seasonal cycle of the sea‐ice cover in both hemispheres. ICON‐ESM V1.0 serves as a basis for further developments that will take advantage of ICON‐specific properties such as spatially varying resolution, and configurations at very high resolution.

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Earth system science

10.1029/2021ms002813

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Citations (96)

Circulation in the northwest Laptev Sea in the eastern Arctic Ocean: Crossroads between Siberian River water, Atlantic water and polynya‐formed dense water

Journal of Geophysical Research Oceans (2017)

Markus Janout Jens Hölemann Leonid Timokhov Oliver Gutjahr Günther Heinemann

Abstract This paper investigates new observations from the poorly understood region between the Kara and Laptev Seas in the Eastern Arctic Ocean. We discuss relevant circulation features including riverine freshwater, Atlantic‐derived water, and polynya‐formed dense water, emphasize Vilkitsky Strait (VS) as an important Kara Sea gateway, and analyze the role of the adjacent ∼250 km‐long submarine Vilkitsky Trough (VT) for the Arctic boundary current. Expeditions in 2013 and 2014 operated closely spaced hydrographic transects and 1 year‐long oceanographic mooring near VT's southern slope, and found persistent annually averaged flow of 0.2 m s −1 toward the Nansen Basin. The flow is nearly barotropic from winter through early summer and becomes surface intensified with maximum velocities of 0.35 m s −1 from August to October. Thermal wind shear is maximal above the southern flank at ∼30 m depth, in agreement with basinward flow above VT's southern slope. The subsurface features a steep front separating warm (–0.5°C) Atlantic‐derived waters in central VT from cold (<–1.5°C) shelf waters, which episodically migrates across the trough indicated by current reversals and temperature fluctuations. Shelf‐transformed waters dominate above VT's slope, measuring near‐freezing temperatures throughout the water column at salinities of 34–35. These dense waters are vigorously advected toward the Eurasian Basin and characterize VT as a conduit for near‐freezing waters that could potentially supply the Arctic Ocean's lower halocline, cool Atlantic water, and ventilate the deeper Arctic Ocean. Our observations from the northwest Laptev Sea highlight a topographically complex region with swift currents, several water masses, narrow fronts, polynyas, and topographically channeled storms.

Trough (economics)

Boundary current

Halocline

Mooring

Estuarine water circulation

10.1002/2017jc013159

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Citations (40)