Articles | Volume 12, issue 8
https://doi.org/10.5194/gmd-12-3805-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-3805-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
TheDiaTo (v1.0) – a new diagnostic tool for water, energy and entropy budgets in climate models
Valerio Lembo
CORRESPONDING AUTHOR
Meteorologisches Institut, Universität Hamburg, Hamburg, Germany
Frank Lunkeit
Meteorologisches Institut, Universität Hamburg, Hamburg, Germany
Valerio Lucarini
Meteorologisches Institut, Universität Hamburg, Hamburg, Germany
Department of Mathematics and Statistics, University of Reading, Reading, UK
Centre for the Mathematics of Planet Earth, Department of Mathematics and Statistics, University of Reading, Reading, UK
Related authors
Federico Fabiano, Paolo Davini, Virna L. Meccia, Giuseppe Zappa, Alessio Bellucci, Valerio Lembo, Katinka Bellomo, and Susanna Corti
Earth Syst. Dynam., 15, 527–546, https://doi.org/10.5194/esd-15-527-2024, https://doi.org/10.5194/esd-15-527-2024, 2024
Short summary
Short summary
Even after the concentration of greenhouse gases is stabilized, the climate will continue to adapt, seeking a new equilibrium. We study this long-term stabilization through a set of 1000-year simulations, obtained by suddenly "freezing" the atmospheric composition at different levels. If frozen at the current state, global warming surpasses 3° in the long term with our model. We then study how climate impacts will change after various centuries and how the deep ocean will warm.
Vera Melinda Galfi, Tommaso Alberti, Lesley De Cruz, Christian L. E. Franzke, and Valerio Lembo
Nonlin. Processes Geophys., 31, 185–193, https://doi.org/10.5194/npg-31-185-2024, https://doi.org/10.5194/npg-31-185-2024, 2024
Short summary
Short summary
In the online seminar series "Perspectives on climate sciences: from historical developments to future frontiers" (2020–2021), well-known and established scientists from several fields – including mathematics, physics, climate science and ecology – presented their perspectives on the evolution of climate science and on relevant scientific concepts. In this paper, we first give an overview of the content of the seminar series, and then we introduce the written contributions to this special issue.
Valerio Lembo, Federico Fabiano, Vera Melinda Galfi, Rune Grand Graversen, Valerio Lucarini, and Gabriele Messori
Weather Clim. Dynam., 3, 1037–1062, https://doi.org/10.5194/wcd-3-1037-2022, https://doi.org/10.5194/wcd-3-1037-2022, 2022
Short summary
Short summary
Eddies in mid-latitudes characterize the exchange of heat between the tropics and the poles. This exchange is largely uneven, with a few extreme events bearing most of the heat transported across latitudes in a season. It is thus important to understand what the dynamical mechanisms are behind these events. Here, we identify recurrent weather regime patterns associated with extreme transports, and we identify scales of mid-latitudinal eddies that are mostly responsible for the transport.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
Short summary
Short summary
The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Valerio Lembo, Isabella Bordi, and Antonio Speranza
Earth Syst. Dynam., 8, 295–312, https://doi.org/10.5194/esd-8-295-2017, https://doi.org/10.5194/esd-8-295-2017, 2017
Short summary
Short summary
The study wishes to better characterize the annual and semiannual cycles of surface temperature and baroclinicity at midlatitudes as observed in ERA-Interim reanalysis data and AOGCM simulations. Results show that at the semiannual frequency model phases between surface temperature and baroclinicity have wide dispersion in both hemispheres with large errors in the estimates, denoting uncertainty and a degree of disagreement among models.
Iana Strigunova, Frank Lunkeit, Nedjeljka Žagar, and Damjan Jelić
EGUsphere, https://doi.org/10.5194/egusphere-2025-892, https://doi.org/10.5194/egusphere-2025-892, 2025
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
Our study builds on previous research by examining how climate models simulate the large-scale Rossby wave circulation during present-day Eurasian heat waves (EHWs) and how it alters in the future. We find no increase in future frequency for EHWs defined with respect to the simulated mean climate. The models capture the averaged atmospheric circulation during EHWs but struggle with daily variability. Our results highlight the need for improvements to enhance predictions of extreme weather.
Rémy Asselot, Philip B. Holden, Frank Lunkeit, and Inga Hense
Earth Syst. Dynam., 15, 875–891, https://doi.org/10.5194/esd-15-875-2024, https://doi.org/10.5194/esd-15-875-2024, 2024
Short summary
Short summary
Phytoplankton are tiny oceanic algae able to absorb the light penetrating the ocean. The light absorbed by these organisms is re-emitted as heat in the surrounding environment, a process commonly called phytoplankton light absorption (PLA). As a consequence, PLA increases the oceanic temperature. We studied this mechanism with a climate model under different climate scenarios. We show that phytoplankton light absorption is reduced under strong warming scenarios, limiting oceanic warming.
Federico Fabiano, Paolo Davini, Virna L. Meccia, Giuseppe Zappa, Alessio Bellucci, Valerio Lembo, Katinka Bellomo, and Susanna Corti
Earth Syst. Dynam., 15, 527–546, https://doi.org/10.5194/esd-15-527-2024, https://doi.org/10.5194/esd-15-527-2024, 2024
Short summary
Short summary
Even after the concentration of greenhouse gases is stabilized, the climate will continue to adapt, seeking a new equilibrium. We study this long-term stabilization through a set of 1000-year simulations, obtained by suddenly "freezing" the atmospheric composition at different levels. If frozen at the current state, global warming surpasses 3° in the long term with our model. We then study how climate impacts will change after various centuries and how the deep ocean will warm.
Vera Melinda Galfi, Tommaso Alberti, Lesley De Cruz, Christian L. E. Franzke, and Valerio Lembo
Nonlin. Processes Geophys., 31, 185–193, https://doi.org/10.5194/npg-31-185-2024, https://doi.org/10.5194/npg-31-185-2024, 2024
Short summary
Short summary
In the online seminar series "Perspectives on climate sciences: from historical developments to future frontiers" (2020–2021), well-known and established scientists from several fields – including mathematics, physics, climate science and ecology – presented their perspectives on the evolution of climate science and on relevant scientific concepts. In this paper, we first give an overview of the content of the seminar series, and then we introduce the written contributions to this special issue.
Yuan-Bing Zhao, Nedjeljka Žagar, Frank Lunkeit, and Richard Blender
Weather Clim. Dynam., 4, 833–852, https://doi.org/10.5194/wcd-4-833-2023, https://doi.org/10.5194/wcd-4-833-2023, 2023
Short summary
Short summary
Coupled climate models have significant biases in the tropical Indian Ocean (TIO) sea surface temperature (SST). Our study shows that the TIO SST biases can affect the simulated global atmospheric circulation and its spatio-temporal variability on large scales. The response of the spatial variability is related to the amplitude or phase of the circulation bias, depending on the flow regime and spatial scale, while the response of the interannual variability depends on the sign of the SST bias.
Lucy G. Recchia and Valerio Lucarini
Earth Syst. Dynam., 14, 697–722, https://doi.org/10.5194/esd-14-697-2023, https://doi.org/10.5194/esd-14-697-2023, 2023
Short summary
Short summary
Simulations are performed with an intermediate-complexity climate model, PLASIM, to assess the future response of monsoons to changing concentrations of aerosols and greenhouse gases. The aerosol loading is applied to India, Southeast Asia, and eastern China, both concurrently and independently, to assess linearity. The primary effect of increased aerosol loading is a decrease in summer precipitation in the vicinity of the applied forcing, although the regional response varies significantly.
Iana Strigunova, Richard Blender, Frank Lunkeit, and Nedjeljka Žagar
Weather Clim. Dynam., 3, 1399–1414, https://doi.org/10.5194/wcd-3-1399-2022, https://doi.org/10.5194/wcd-3-1399-2022, 2022
Short summary
Short summary
We show that the Eurasian heat waves (HWs) have signatures in the global circulation. We present changes in the probability density functions (PDFs) of energy anomalies in the zonal-mean state and in the Rossby waves at different zonal scales in relation to the changes in intramonthly variability. The skewness of the PDF of planetary-scale Rossby waves is shown to increase during HWs, while their intramonthly variability is reduced, a process referred to as blocking.
Valerio Lembo, Federico Fabiano, Vera Melinda Galfi, Rune Grand Graversen, Valerio Lucarini, and Gabriele Messori
Weather Clim. Dynam., 3, 1037–1062, https://doi.org/10.5194/wcd-3-1037-2022, https://doi.org/10.5194/wcd-3-1037-2022, 2022
Short summary
Short summary
Eddies in mid-latitudes characterize the exchange of heat between the tropics and the poles. This exchange is largely uneven, with a few extreme events bearing most of the heat transported across latitudes in a season. It is thus important to understand what the dynamical mechanisms are behind these events. Here, we identify recurrent weather regime patterns associated with extreme transports, and we identify scales of mid-latitudinal eddies that are mostly responsible for the transport.
Miriam D'Errico, Flavio Pons, Pascal Yiou, Soulivanh Tao, Cesare Nardini, Frank Lunkeit, and Davide Faranda
Earth Syst. Dynam., 13, 961–992, https://doi.org/10.5194/esd-13-961-2022, https://doi.org/10.5194/esd-13-961-2022, 2022
Short summary
Short summary
Climate change is already affecting weather extremes. In a warming climate, we will expect the cold spells to decrease in frequency and intensity. Our analysis shows that the frequency of circulation patterns leading to snowy cold-spell events over Italy will not decrease under business-as-usual emission scenarios, although the associated events may not lead to cold conditions in the warmer scenarios.
Valerio Lucarini, Larissa Serdukova, and Georgios Margazoglou
Nonlin. Processes Geophys., 29, 183–205, https://doi.org/10.5194/npg-29-183-2022, https://doi.org/10.5194/npg-29-183-2022, 2022
Short summary
Short summary
In most of the investigations on metastable systems, the stochastic forcing is modulated by Gaussian noise. Lévy noise laws, which describe jump processes, have recently received a lot of attention, but much less is known. We study stochastic versions of the Ghil–Sellers energy balance model, and we highlight the fundamental difference between how transitions are performed between the competing warm and snowball states, depending on whether Gaussian or Lévy noise acts as forcing.
Rémy Asselot, Frank Lunkeit, Philip B. Holden, and Inga Hense
Biogeosciences, 19, 223–239, https://doi.org/10.5194/bg-19-223-2022, https://doi.org/10.5194/bg-19-223-2022, 2022
Short summary
Short summary
Previous studies show that phytoplankton light absorption can warm the atmosphere, but how this warming occurs is still unknown. We compare the importance of air–sea heat versus CO2 flux in the phytoplankton-induced atmospheric warming and determine the main driver. To shed light on this research question, we conduct simulations with a climate model of intermediate complexity. We show that phytoplankton mainly warms the atmosphere by increasing the air–sea CO2 flux.
Yumeng Chen, Alberto Carrassi, and Valerio Lucarini
Nonlin. Processes Geophys., 28, 633–649, https://doi.org/10.5194/npg-28-633-2021, https://doi.org/10.5194/npg-28-633-2021, 2021
Short summary
Short summary
Chaotic dynamical systems are sensitive to the initial conditions, which are crucial for climate forecast. These properties are often used to inform the design of data assimilation (DA), a method used to estimate the exact initial conditions. However, obtaining the instability properties is burdensome for complex problems, both numerically and analytically. Here, we suggest a different viewpoint. We show that the skill of DA can be used to infer the instability properties of a dynamical system.
Rémy Asselot, Frank Lunkeit, Philip Holden, and Inga Hense
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2021-91, https://doi.org/10.5194/esd-2021-91, 2021
Revised manuscript not accepted
Short summary
Short summary
Phytoplankton absorbing light can influence the climate system but its future effect on the climate is still unclear. We use a climate model to investigate the role of phytoplankton light absorption under global warming. We find out that the effect of phytoplankton light absorption is smaller under a high greenhouse gas emissions compared to reduced and intermediate greenhouse gas emissions. Additionally, we show that phytoplankton light absorption is an important mechanism for the carbon cycle.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
Short summary
Short summary
The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Mallory Carlu, Francesco Ginelli, Valerio Lucarini, and Antonio Politi
Nonlin. Processes Geophys., 26, 73–89, https://doi.org/10.5194/npg-26-73-2019, https://doi.org/10.5194/npg-26-73-2019, 2019
Short summary
Short summary
We explore the nature of instabilities in a well-known meteorological toy model, the Lorenz 96, to unravel key mechanisms of interaction between scales of different resolutions and time scales. To do so, we use a mathematical machinery known as Lyapunov analysis, allowing us to capture the degrees of chaoticity associated with fundamental directions of instability. We find a non-trivial group of such directions projecting significantly on slow variables, associated with long term dynamics.
Gabriele Vissio and Valerio Lucarini
Nonlin. Processes Geophys., 25, 413–427, https://doi.org/10.5194/npg-25-413-2018, https://doi.org/10.5194/npg-25-413-2018, 2018
Short summary
Short summary
Constructing good parametrizations is key when studying multi-scale systems. We consider a low-order model and derive a parametrization via a recently developed statistical mechanical approach. We show how the method allows for seamlessly treating the case when the unresolved dynamics is both faster and slower than the resolved one. We test the skill of the parametrization by using the formalism of the Wasserstein distance, which allows for measuring how different two probability measures are.
Lesley De Cruz, Sebastian Schubert, Jonathan Demaeyer, Valerio Lucarini, and Stéphane Vannitsem
Nonlin. Processes Geophys., 25, 387–412, https://doi.org/10.5194/npg-25-387-2018, https://doi.org/10.5194/npg-25-387-2018, 2018
Short summary
Short summary
The predictability of weather models is limited largely by the initial state error growth or decay rates. We have computed these rates for PUMA, a global model for the atmosphere, and MAOOAM, a more simplified, coupled model which includes the ocean. MAOOAM has processes at distinct timescales, whereas PUMA surprisingly does not. We propose a new programme to compute the natural directions along the flow that correspond to the growth or decay rates, to learn which components play a role.
Tamás Bódai, Valerio Lucarini, and Frank Lunkeit
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2018-30, https://doi.org/10.5194/esd-2018-30, 2018
Revised manuscript not accepted
Short summary
Short summary
We establish a framework to conduct a scenario analysis of the best possible outcomes under geoengineering. The scenarios may consist of scenarios of greenhouse gas emission the choice of the quantity that we want to keep under control. The motivation is the desire of an efficient way of assessing the side-effects of geoengineering, concerning the unwanted and uncontrolled changes. Countering CO2 emission by modulating insolation, we find considerable changes in local temperatures or rainfall.
Valerio Lembo, Isabella Bordi, and Antonio Speranza
Earth Syst. Dynam., 8, 295–312, https://doi.org/10.5194/esd-8-295-2017, https://doi.org/10.5194/esd-8-295-2017, 2017
Short summary
Short summary
The study wishes to better characterize the annual and semiannual cycles of surface temperature and baroclinicity at midlatitudes as observed in ERA-Interim reanalysis data and AOGCM simulations. Results show that at the semiannual frequency model phases between surface temperature and baroclinicity have wide dispersion in both hemispheres with large errors in the estimates, denoting uncertainty and a degree of disagreement among models.
M.-A. Knietzsch, A. Schröder, V. Lucarini, and F. Lunkeit
Earth Syst. Dynam., 6, 591–615, https://doi.org/10.5194/esd-6-591-2015, https://doi.org/10.5194/esd-6-591-2015, 2015
Short summary
Short summary
A general circulation model with an aquaplanet setup is used to study the impact of changes in the oceanic heat transport (OHT) on the atmospheric circulation. The atmosphere counterbalances the imposed changes in OHT. A stronger OHT leads to a decline in the intensity and a poleward shift of the maxima of both the Hadley and Ferrel cells. The efficiency of the climate machine, the intensity of the Lorenz energy cycle and the material entropy production of the system decline with increased OHT.
S. Hasson, V. Lucarini, M. R. Khan, M. Petitta, T. Bolch, and G. Gioli
Hydrol. Earth Syst. Sci., 18, 4077–4100, https://doi.org/10.5194/hess-18-4077-2014, https://doi.org/10.5194/hess-18-4077-2014, 2014
P. B. Holden, N. R. Edwards, P. H. Garthwaite, K. Fraedrich, F. Lunkeit, E. Kirk, M. Labriet, A. Kanudia, and F. Babonneau
Geosci. Model Dev., 7, 433–451, https://doi.org/10.5194/gmd-7-433-2014, https://doi.org/10.5194/gmd-7-433-2014, 2014
S. Hasson, V. Lucarini, S. Pascale, and J. Böhner
Earth Syst. Dynam., 5, 67–87, https://doi.org/10.5194/esd-5-67-2014, https://doi.org/10.5194/esd-5-67-2014, 2014
R. Deidda, M. Marrocu, G. Caroletti, G. Pusceddu, A. Langousis, V. Lucarini, M. Puliga, and A. Speranza
Hydrol. Earth Syst. Sci., 17, 5041–5059, https://doi.org/10.5194/hess-17-5041-2013, https://doi.org/10.5194/hess-17-5041-2013, 2013
S. Hasson, V. Lucarini, and S. Pascale
Earth Syst. Dynam., 4, 199–217, https://doi.org/10.5194/esd-4-199-2013, https://doi.org/10.5194/esd-4-199-2013, 2013
Related subject area
Climate and Earth system modeling
Modeling commercial-scale CO2 storage in the gas hydrate stability zone with PFLOTRAN v6.0
DiuSST: a conceptual model of diurnal warm layers for idealized atmospheric simulations with interactive sea surface temperature
High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7
T&C-CROP: representing mechanistic crop growth with a terrestrial biosphere model (T&C, v1.5) – model formulation and validation
An updated non-intrusive, multi-scale, and flexible coupling interface in WRF 4.6.0
Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0
The Earth Science Box Modeling Toolkit (ESBMTK 0.14.0.11): a Python library for research and teaching
CropSuite v1.0 – a comprehensive open-source crop suitability model considering climate variability for climate impact assessment
ICON ComIn – the ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Using feature importance as an exploratory data analysis tool on Earth system models
A new metrics framework for quantifying and intercomparing atmospheric rivers in observations, reanalyses, and climate models
The real challenges for climate and weather modelling on its way to sustained exascale performance: a case study using ICON (v2.6.6)
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
Evaluation of CORDEX ERA5-forced NARCliM2.0 regional climate models over Australia using the Weather Research and Forecasting (WRF) model version 4.1.2
Design, evaluation, and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
Amending the algorithm of aerosol–radiation interactions in WRF-Chem (v4.4)
The very-high-resolution configuration of the EC-Earth global model for HighResMIP
GOSI9: UK Global Ocean and Sea Ice configurations
Decomposition of skill scores for conditional verification: impact of Atlantic Multidecadal Oscillation phases on the predictability of decadal temperature forecasts
Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)
Climate model downscaling in central Asia: a dynamical and a neural network approach
Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4
Subsurface hydrological controls on the short-term effects of hurricanes on nitrate–nitrogen runoff loading: a case study of Hurricane Ida using the Energy Exascale Earth System Model (E3SM) Land Model (v2.1)
CARIB12: a regional Community Earth System Model/Modular Ocean Model 6 configuration of the Caribbean Sea
Architectural insights into and training methodology optimization of Pangu-Weather
Evaluation of global fire simulations in CMIP6 Earth system models
Evaluating downscaled products with expected hydroclimatic co-variances
Software sustainability of global impact models
fair-calibrate v1.4.1: calibration, constraining, and validation of the FaIR simple climate model for reliable future climate projections
ISOM 1.0: a fully mesoscale-resolving idealized Southern Ocean model and the diversity of multiscale eddy interactions
A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1
Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature
Investigating Carbon and Nitrogen Conservation in Reported CMIP6 Earth System Model Data
The need for carbon-emissions-driven climate projections in CMIP7
Robust handling of extremes in quantile mapping – “Murder your darlings”
A protocol for model intercomparison of impacts of marine cloud brightening climate intervention
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2
The Tropical Basin Interaction Model Intercomparison Project (TBIMIP)
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
Development and evaluation of a new 4DEnVar-based weakly coupled ocean data assimilation system in E3SMv2
Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1
PaleoSTeHM v1.0-rc: a modern, scalable spatio-temporal hierarchical modeling framework for paleo-environmental data
From Weather Data to River Runoff: Leveraging Spatiotemporal Convolutional Networks for Comprehensive Discharge Forecasting
Historical Trends and Controlling Factors of Isoprene Emissions in CMIP6 Earth System Models
A new lightning scheme in the Canadian Atmospheric Model (CanAM5.1): implementation, evaluation, and projections of lightning and fire in future climates
Methane dynamics in the Baltic Sea: investigating concentration, flux, and isotopic composition patterns using the coupled physical–biogeochemical model BALTSEM-CH4 v1.0
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
Short summary
Short summary
Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
Short summary
Short summary
The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
Short summary
Short summary
HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
Short summary
Short summary
We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
Short summary
Short summary
This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
Short summary
Short summary
Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
Short summary
Short summary
The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
Short summary
Short summary
CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
Short summary
Short summary
The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
Short summary
Short summary
Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
Short summary
Short summary
A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
Short summary
Short summary
In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
Short summary
Short summary
The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
Short summary
Short summary
We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
Short summary
Short summary
We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
Short summary
Short summary
In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
Short summary
Short summary
We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
Short summary
Short summary
The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
Short summary
Short summary
The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
Short summary
Short summary
Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
Short summary
Short summary
We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
Short summary
Short summary
Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
Short summary
Short summary
Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
Short summary
Short summary
A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
Short summary
Short summary
Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
Short summary
Short summary
This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
Short summary
Short summary
We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
Short summary
Short summary
Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
Short summary
Short summary
Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
Short summary
Short summary
We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
Short summary
Short summary
We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
Short summary
Short summary
Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3522, https://doi.org/10.5194/egusphere-2024-3522, 2024
Short summary
Short summary
We analyzed carbon and nitrogen mass conservation in data from CMIP6 Earth System Models. Our findings reveal significant discrepancies between flux and pool size data, particularly in nitrogen, where cumulative imbalances can reach hundreds of gigatons. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
Short summary
Short summary
We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
Short summary
Short summary
When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
Short summary
Short summary
We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
Short summary
Short summary
We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
Short summary
Short summary
The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
Short summary
Short summary
We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Ingo Richter, Ping Chang, Gokhan Danabasoglu, Dietmar Dommenget, Guillaume Gastineau, Aixue Hu, Takahito Kataoka, Noel Keenlyside, Fred Kucharski, Yuko Okumura, Wonsun Park, Malte Stuecker, Andrea Taschetto, Chunzai Wang, Stephen Yeager, and Sang-Wook Yeh
EGUsphere, https://doi.org/10.5194/egusphere-2024-3110, https://doi.org/10.5194/egusphere-2024-3110, 2024
Short summary
Short summary
The tropical ocean basins influence each other through multiple pathways and mechanisms, here referred to as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models, but have obtained conflicting results. This may be partly due to differences in experiment protocols, and partly due to systematic model errors. TBIMIP aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
Short summary
Short summary
In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
Short summary
Short summary
This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
Short summary
Short summary
We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-183, https://doi.org/10.5194/gmd-2024-183, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Improving climate predictions has significant socio-economic impacts. In this study, we developed and applied a weakly coupled ocean data assimilation (WCODA) system to a coupled climate model. The WCODA system improves simulations of ocean temperature and salinity across many global regions. It also enhances the simulation of interannual precipitation and temperature variability over the southern US. This system is to support future predictability studies.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
Short summary
Short summary
In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Yucheng Lin, Robert E. Kopp, Alexander Reedy, Matteo Turilli, Shantenu Jha, and Erica L. Ashe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2183, https://doi.org/10.5194/egusphere-2024-2183, 2024
Short summary
Short summary
PaleoSTeHM v1.0-rc is a state-of-the-art framework designed to reconstruct past environmental conditions using geological data. Built on modern machine learning techniques, it efficiently handles the sparse and noisy nature of paleo records, allowing scientists to make accurate and scalable inferences about past environmental change. By using flexible statistical models, PaleoSTeHM separates different sources of uncertainty, improving the precision of historical climate reconstructions.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2685, https://doi.org/10.5194/egusphere-2024-2685, 2024
Short summary
Short summary
Forecasting river runoff, crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using Convolutional Long Short-Term Memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Thi Nhu Ngoc Do, Kengo Sudo, Akihiko Ito, Louisa Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
EGUsphere, https://doi.org/10.5194/egusphere-2024-2313, https://doi.org/10.5194/egusphere-2024-2313, 2024
Short summary
Short summary
Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth System Models mainly due to partially incorporating CO2 effects and land cover changes rather than climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant-climate interactions.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
Short summary
Short summary
This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
Short summary
Short summary
Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Cited articles
Adam, O., Schneider, T., Brient, F., and Bischoff, T.: Relation of the
double-ITCZ bias to the atmospheric energy budget in climate models,
Geophys. Res. Lett., 43, 7670–7677, https://doi.org/10.1002/2016GL069465,
2016. a
Allan, R. P., Liu, C., Loeb, N. G., Palmer, M. D., Roberts, M., Smith, D. M.,
and Vidale, P. L.: Changes in global net radiative imbalance 1985-2012,
Geophys. Res. Lett., 41, 5588–5598, https://doi.org/10.1002/2014GL060962,
2014. a
Ambaum, M. H. P.: Thermal Physics of the Atmosphere, Wiley-Blackwell,
https://doi.org/10.1002/9780470710364, 2010. a, b
Awad, M. M.: The science and the history of the two Bejan numbers,
Int. J. Heat Mass Tran., 94, 101–103,
https://doi.org/10.1016/j.ijheatmasstransfer.2015.11.073, 2016. a
Bannon, P. R.: Entropy Production and Climate Efficiency, J.
Atmos. Sci., 72, 3268–3280, https://doi.org/10.1175/JAS-D-14-0361.1, 2015. a, b
Bannon, P. R. and Lee, S.: Toward Quantifying the Climate Heat Engine: Solar
Absorption and Terrestrial Emission Temperatures and Material Entropy
Production, J. Atmos. Sci., 74, 1721–1734,
https://doi.org/10.1175/JAS-D-16-0240.1, 2017. a, b, c
Barry, L., Craig, G. C., and Thuburn, J.: Poleward heat transport by the
atmospheric heat engine, Nature, 415, 774–777, https://doi.org/10.1038/415774a, 2002. a
Bjerknes, J.: Atmospheric Teleconnections from the Equatorial Pacific,
Mon. Weather Rev., 97, 163–172,
https://doi.org/10.1175/1520-0493(1969)097<0163:ATFTEP>2.3.CO;2, 1969. a, b
Boer, G. J. and Lambert, S.: The energy cycle in atmospheric models, Clim. Dynam., 30, 371–390, https://doi.org/10.1007/s00382-007-0303-4, 2008. a
Boschi, R., Lucarini, V., and Pascale, S.: Bistability of the climate around
the habitable zone: A thermodynamic investigation, Icarus, 226, 1724–1742,
https://doi.org/10.1016/j.icarus.2013.03.017, 2013. a, b
Buck, A. L.: New Equations for Computing Vapor Pressure and Enhancement
Factor, J. Appl. Meteorol., 20, 1527–1532,
https://doi.org/10.1175/1520-0450(1981)020<1527:NEFCVP>2.0.CO;2, 1981. a
Caballero, R. and Langen, P. L.: The dynamic range of poleward energy
transport in an atmospheric general circulation model, Geophys. Res.
Lett., 32, L02705, https://doi.org/10.1029/2004GL021581, 2005. a
Carissimo, B. C., Oort, A. H., and Vonder Haar, T. H.: Estimating the
Meridional Energy Transports in the Atmosphere and Ocean, J. Phys. Oceanogr., 15, 82–91,
https://doi.org/10.1175/1520-0485(1985)015<0082:ETMETI>2.0.CO;2, 1985. a, b
CDO: Climate Data Operators, available at: http://www.mpimet.mpg.de/cdo (last access: 26 August 2019), 2015. a
Cohen, J. L., Salstein, D. A., and Rosen, R. D.: Interannual Variability in
the Meridional Transport of Water Vapor, J. Hydrometeorology, 1,
547–553, https://doi.org/10.1175/1525-7541(2000)001<0547:IVITMT>2.0.CO;2, 2000. a
Demory, M.-E., Vidale, P. L., Roberts, M. J., Berrisford, P., Strachan, J.,
Schiemann, R., and Mizielinski, M. S.: The role of horizontal resolution in
simulating drivers of the global hydrological cycle, Clim. Dynam., 42,
2201–2225, https://doi.org/10.1007/s00382-013-1924-4, 2014. a
Enderton, D. and Marshall, J.: Explorations of Atmosphere–Ocean–Ice
Climates on an Aquaplanet and Their Meridional Energy Transports, J.
Atmos. Sci., 66, 1593–1611, https://doi.org/10.1175/2008JAS2680.1, 2009. a
Exarchou, E., Kuhlbrodt, T., Gregory, J. M., and Smith, R. S.: Ocean Heat
Uptake Processes: A Model Intercomparison, J. Climate, 28, 887–908,
https://doi.org/10.1175/JCLI-D-14-00235.1, 2015. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016a. a, b
Eyring, V., Righi, M., Lauer, A., Evaldsson, M., Wenzel, S., Jones, C., Anav, A., Andrews, O., Cionni, I., Davin, E. L., Deser, C., Ehbrecht, C., Friedlingstein, P., Gleckler, P., Gottschaldt, K.-D., Hagemann, S., Juckes, M., Kindermann, S., Krasting, J., Kunert, D., Levine, R., Loew, A., Mäkelä, J., Martin, G., Mason, E., Phillips, A. S., Read, S., Rio, C., Roehrig, R., Senftleben, D., Sterl, A., van Ulft, L. H., Walton, J., Wang, S., and Williams, K. D.: ESMValTool (v1.0) – a community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP, Geosci. Model Dev., 9, 1747–1802, https://doi.org/10.5194/gmd-9-1747-2016, 2016b. a, b
Eyring, V., Andela, B., Broetz, B., de Mora, L., Drost, N., Koldunov, N., Lauer, A., Mueller, B., Predoi, V., Righi, M., Schlund, M., and Vegas-Regidor, J.: ESMValTool User's and Developer's Guide, Release 2.0.0b0, 260 pp., available at: https://buildmedia.readthedocs.org/media/pdf/esmvaltool/latest/esmvaltool.pdf, last access: 27 August 2019. a
Fischer, N. and Jungclaus, J. H.: Effects of orbital forcing on atmosphere and ocean heat transports in Holocene and Eemian climate simulations with a comprehensive Earth system model, Clim. Past, 6, 155–168, https://doi.org/10.5194/cp-6-155-2010, 2010. a
Fraedrich, K. and Lunkeit, F.: Diagnosing the entropy budget of a climate
model, Tellus A, 60, 921–931, https://doi.org/10.1111/j.1600-0870.2008.00338.x, 2008. a, b, c
Frigg, R., Thompson, E., and Werndl, C.: Philosophy of Climate Science Part
II: Modelling Climate Change, Philosophy Compass, 10, 965–977,
https://doi.org/10.1111/phc3.12297, 2015. a
Gassmann, A.: A global hexagonal C-grid non-hydrostatic dynamical core
(ICON-IAP) designed for energetic consistency, Q. J.
Roy. Meteorol. Soc., 139, 152–175, https://doi.org/10.1002/qj.1960, 2013. a
Gassmann, A. and Herzog, H. J.: How is local material entropy production
represented in a numerical model?, Q. J.
Roy. Meteorol. Soc., 141, 854–869, https://doi.org/10.1002/qj.2404, 2015. a, b
Goff, A. J.: Saturation pressure of water on the new Kelvin temperature
scale, Transactions of the American Society of Heating and Ventilating
Engineers, 347–354, 1957. a
Goody, R.: Sources and sinks of climate entropy, Q. J.
Roy. Meteorol. Soc., 126, 1953–1970, https://doi.org/10.1002/qj.49712656619, 2000. a, b
Gupta, A. S., Jourdain, N. C., Brown, J. N., and Monselesan, D.: Climate drift
in the CMIP5 models, J. Climate, 26, 8597–8615,
https://doi.org/10.1175/JCLI_D_12_00521.1, 2013. a, b
Hansen, J., Sato, M., Kharecha, P., and von Schuckmann, K.: Earth's energy imbalance and implications, Atmos. Chem. Phys., 11, 13421–13449, https://doi.org/10.5194/acp-11-13421-2011, 2011. a
Hartmann, D. L.: Global Physical Climatology, Academic Press, 1994. a
Held, I. M. and Soden, B. J.: Robust Responses of the Hydrological Cycle to
Global Warming, J. Climate, 19, 5686–5699,
https://doi.org/10.1175/JCLI3990.1, 2006. a
Herbert, C., Paillard, D., and Dubrulle, B.: Entropy production and multiple equilibria: the case of the ice-albedo feedback, Earth Syst. Dynam., 2, 13-23, https://doi.org/10.5194/esd-2-13-2011, 2011. a
Hernández-Deckers, D. and von Storch, J.-S.: Energetics Responses to
Increases in Greenhouse Gas Concentration, J. Climate, 23,
3874–3887, https://doi.org/10.1175/2010JCLI3176.1, 2010. a, b
Hobbs, W., Palmer, M. D., and Monselesan, D.: An Energy Conservation Analysis
of Ocean Drift in the CMIP5 Global Coupled Models, J. Climate, 29,
1639–1653, https://doi.org/10.1175/JCLI-D-15-0477.1, 2016. a
Hourdin, F., Mauritsen, T., Gettelman, A., Golaz, J.-C., Balaji, V., Duan, Q.,
Folini, D., Ji, D., Klocke, D., Qian, Y., Rauser, F., Rio, C., Tomassini, L.,
Watanabe, M., and Williamson, D.: The Art and Science of Climate Model
Tuning, B. Am. Meteorol. Soc., 98, 589–602,
https://doi.org/10.1175/BAMS-D-15-00135.1, 2017. a, b
Intergovernmental Panel on Climate Change: Climate Change 2013: The Physical Science Basis, Press, Cambridge University, Cambridge,
https://doi.org/10.1017/CBO9781107415324, 2013. a, b, c
Irving, D. B., Wijffels, S., and Church, J. A.: Anthropogenic Aerosols,
Greenhouse Gases, and the Uptake, Transport, and Storage of Excess Heat in
the Climate System, Geophys. Res. Lett., 46, 4894–4903,
https://doi.org/10.1029/2019GL082015, 2019. a
Johnson, D. R.: General Coldness of Climate Models and the Second Law:
Implications for Modeling the Earth System, J. Climate, 10,
2826–2846, https://doi.org/10.1175/1520-0442(1997)010<2826:GCOCMA>2.0.CO;2, 1997. a
Kiehl, J. T. and Trenberth, K. E.: Earth's Annual Global Mean Energy Budget,
B. Am. Meteorol. Soc., 78, 197–208,
https://doi.org/10.1175/1520-0477(1997)078<0197:EAGMEB>2.0.CO;2, 1997. a
Kim, Y. H. and Kim, M. K.: Examination of the global lorenz energy cycle using
MERRA and NCEP-reanalysis 2, Clim. Dynam., 40, 1499–1513,
https://doi.org/10.1007/s00382-012-1358-4, 2013. a, b, c
Kjellsson, J.: Weakening of the global atmospheric circulation with global
warming, Clim. Dynam., 45, 975–988, https://doi.org/10.1007/s00382-014-2337-8,
2015. a
Kleidon, A.: Nonequilibrium thermodynamics and maximum entropy production in
the Earth system: applications and implications, Naturwissenschaften,
96, 653–677, https://doi.org/10.1007/s00114-009-0509-x, 2009. a, b
Kleidon, A. and Lorenz, R.: Non-equilibrium Thermodynamics and the Production
of Entropy, Springer-Verlag, Berlin/Heidelberg, 1 edn.,
https://doi.org/10.1007/11672906_1, 2004. a
Knietzsch, M.-A., Schröder, A., Lucarini, V., and Lunkeit, F.: The impact of oceanic heat transport on the atmospheric circulation, Earth Syst. Dynam., 6, 591–615, https://doi.org/10.5194/esd-6-591-2015, 2015. a
Kunz, T., Fraedrich, K., and Kirk, E.: Optimisation of simplified GCMs using
circulation indices and maximum entropy production, Clim. Dynam., 30,
803–813, https://doi.org/10.1007/s00382-007-0325-y, 2008. a
Laliberté, F. and Pauluis, O.: Winter intensification of the moist
branch of the circulation in simulations of 21st century climate,
Geophys. Res. Lett., 37, 1–6, https://doi.org/10.1029/2010GL045007, 2010. a, b
Laliberté, F., Zika, J., Mudryk, L., Kushner, P. J., Kjellsson, J., and
Doos, K.: Constrained work output of the moist atmospheric heat engine in a
warming climate, Science, 347, 540–543, https://doi.org/10.1126/science.1257103,
2015. a, b, c, d
Lawrence, M. G.: The Relationship between Relative Humidity and the Dewpoint
Temperature in Moist Air: A Simple Conversion and Applications, B. Am. Meteorol. Soc., 86, 225–234,
https://doi.org/10.1175/BAMS-86-2-225, 2005. a
L'Ecuyer, T. S., Beaudoing, H. K., Rodell, M., Olson, W., Lin, B., Kato, S.,
Clayson, C. A., Wood, E., Sheffield, J., Adler, R., Huffman, G., Bosilovich,
M., Gu, G., Robertson, F., Houser, P. R., Chambers, D., Famiglietti, J. S.,
Fetzer, E., Liu, W. T., Gao, X., Schlosser, C. A., Clark, E., Lettenmaier,
D. P., Hilburn, K., L'Ecuyer, T. S., Beaudoing, H. K., Rodell, M., Olson, W.,
Lin, B., Kato, S., Clayson, C. A., Wood, E., Sheffield, J., Adler, R.,
Huffman, G., Bosilovich, M., Gu, G., Robertson, F., Houser, P. R.,Chambers,
D., Famiglietti, J. S., Fetzer, E., Liu, W. T., Gao, X., Schlosser, C. A.,
Clark, E., Lettenmaier, D. P., and Hilburn, K.: The Observed State of the
Energy Budget in the Early Twenty-First Century, J. Climate, 28,
8319–8346, https://doi.org/10.1175/JCLI-D-14-00556.1, 2015. a
Lembo, V., Folini, D., Wild, M., and Lionello, P.: Energy budgets and
transports : global evolution and spatial patterns during the 20th Century as
estimated in two AMIP-like experiments, Clim. Dynam., 48, 1793–1812,
https://doi.org/10.1007/s00382-016-3173-9, 2016. a, b
Lembo, V., Folini, D., Wild, M., and Lionello, P.: Inter-hemispheric
differences in energy budgets and cross-equatorial transport anomalies during
the 20th century, Clim. Dynam., 53, 115–135,
https://doi.org/10.1007/s00382-018-4572-x, 2019a. a, b
Lembo, V., Messori, G., Graversen, R., and Lucarini, V.: Spectral
Decomposition and Extremes of Atmospheric Meridional Energy Transport in the
Northern Hemisphere Midlatitudes, Geophys. Res. Lett., 46,
7602–7613, https://doi.org/10.1029/2019GL082105, 2019b. a
Levang, S. J. and Schmitt, R. W.: Centennial changes of the global water cycle
in CMIP5 models, J. Climate, 28, 6489–6502,
https://doi.org/10.1175/JCLI-D-15-0143.1, 2015. a
Levitus, S., Antonov, J. I., Boyer, T. P., Baranova, O. K., Garcia, H. E.,
Locarnini, R. A., Mishonov, A. V., Reagan, J. R., Seidov, D., Yarosh, E. S.,
and Zweng, M. M.: World ocean heat content and thermosteric sea level change
(0–2000 m), 1955–2010, Geophys. Res. Lett., 39, L10603,
https://doi.org/10.1029/2012GL051106, 2012. a
Liepert, B. G. and Previdi, M.: Inter-model variability and biases of the
global water cycle in CMIP3 coupled climate models, Environ. Res.
Lett., 7, 014006, https://doi.org/10.1088/1748-9326/7/1/014006, 2012. a, b
Lin, P., Paynter, D., Ming, Y., and Ramaswamy, V.: Changes of the Tropical
Tropopause Layer under Global Warming, J. Climate, 30, 1245–1258,
https://doi.org/10.1175/JCLI-D-16-0457.1, 2017. a
Loeb, N. G., Wielicki, B. a., Doelling, D. R., Smith, G. L., Keyes, D. F.,
Kato, S., Manalo-Smith, N., and Wong, T.: Toward optimal closure of the
Earth's top-of-atmosphere radiation budget, J. Climate, 22,
748–766, https://doi.org/10.1175/2008JCLI2637.1, 2009. a
Loeb, N. G., Lyman, J. M., Johnson, G. C., Allan, R. P., Doelling, D. R., Wong,
T., Soden, B. J., and Stephens, G. L.: Observed changes in
top-of-the-atmosphere radiation and upper-ocean heating consistent within
uncertainty, Nat. Geosci., 5, 1–4, https://doi.org/10.1038/ngeo1375, 2012. a
Loeb, N. G., Wang, H., Cheng, A., Kato, S., Fasullo, J. T., Xu, K.-M., and
Allan, R. P.: Observational constraints on atmospheric and oceanic
cross-equatorial heat transports: revisiting the precipitation asymmetry
problem in climate models, Clim. Dynam., 46, 3239–3257,
https://doi.org/10.1007/s00382-015-2766-z, 2015. a, b, c, d, e
Lorenz, E. N.: Available Potential Energy and the Maintenance of the General
Circulation, Tellus, 7, 157–167,https://doi.org/10.1111/j.2153-3490.1955.tb01148.x,
1955. a, b, c
Lucarini, V.: Thermodynamic efficiency and entropy production in the climate
system, Physical Review E – Statistical, Nonlinear, and Soft Matter Physics,
80, 1–5, https://doi.org/10.1103/PhysRevE.80.021118, 2009. a, b, c
Lucarini, V.: Modeling Complexity: The Case of Climate Science, in: Models,
Simulations, and the Reduction of Complexity, edited by: Gähde, U.,
Hartmann, S., and Wolf, J. H., De Gruyter, Berlin, Boston, 229–254,
https://doi.org/10.1515/9783110313680.229, 2013. a
Lucarini, V. and Fraedrich, K.: Symmetry breaking, mixing, instability, and
low-frequency variability in a minimal Lorenz-like system, Phys. Rev. E, 80, 026313, https://doi.org/10.1103/PhysRevE.80.026313, 2009. a
Lucarini, V., Fraedrich, K., and Lunkeit, F.: Thermodynamics of climate change: generalized sensitivities, Atmos. Chem. Phys., 10, 9729–9737, https://doi.org/10.5194/acp-10-9729-2010, 2010a. a, b, c, d
Lucarini, V., Fraedrich, K., and Lunkeit, F.: Thermodynamic analysis of
snowball earth hysteresis experiment: Efficiency, entropy production and
irreversibility, Q. J. Roy. Meteor. Soc., 136,
2–11, https://doi.org/10.1002/qj.543, 2010b. a, b
Manabe, S. and Wetherald, R. T.: Thermal Equilibrium of the Atmosphere with a
Given Distribution of Relative Humidity, J. Atmos.
Sci., 24, 241–259,
https://doi.org/10.1175/1520-0469(1967)024<0241:TEOTAW>2.0.CO;2, 1967. a
Marques, C. A. F., Rocha, A., and Corte-Real, J.: Global diagnostic energetics
of five state-of-the-art climate models, Clim. Dynam., 36, 1767–1794,
https://doi.org/10.1007/s00382-010-0828-9, 2011. a, b
Mauritsen, T., Stevens, B., Roeckner, E., Crueger, T., Esch, M., Giorgetta, M.,
Haak, H., Jungclaus, J., Klocke, D., Matei, D., Mikolajewicz, U., Notz, D.,
Pincus, R., Schmidt, H., and Tomassini, L.: Tuning the climate of a global
model, J. Adv. Model. Earth Syst., 4, M00A01,
https://doi.org/10.1029/2012MS000154, 2012. a, b, c
Novak, L. and Tailleux, R.: On the Local View of Atmospheric Available
Potential Energy, J. Atmos. Sci., 75, 1891–1907,
https://doi.org/10.1175/JAS-D-17-0330.1, 2018. a
Ozawa, H., Ohmura, A., Lorenz, R. D., and Pujol, T.: The second law of
thermodynamics and the global climate system: A review of the maximum entropy
production principle, Rev. Geophys., 41, 1018,
https://doi.org/10.1029/2002RG000113, 2003. a
Paltridge, G. W.: Global dynamics and climate – a system of minimum entropy
exchange, Q. J. Roy. Meteor. Soc., 101,
475–484, https://doi.org/10.1002/qj.49710142906, 1975. a
Pan, Y., Li, L., Jiang, X., Li, G., Zhang, W., Wang, X., and Ingersoll, A. P.:
Earth's changing global atmospheric energy cycle in response to climate
change, Nat. Commun., 8, 14367, https://doi.org/10.1038/ncomms14367, 2017. a, b, c
Pauluis, O.: Water Vapor and Mechanical Work: A Comparison of Carnot and Steam Cycles, J. Atmos. Sci., 68, 91–102,
https://doi.org/10.1175/2010JAS3530.1, 2011. a, b
Pauluis, O. and Dias, J.: Satellite estimates of precipitation-induced
dissipation in the atmosphere, Science, 335, 953–956,
https://doi.org/10.1126/science.1215869, 2012. a
Pauluis, O. and Held, I. M.: Entropy Budget of an Atmosphere in
Radiative–Convective Equilibrium. Part I: Maximum Work and Frictional
Dissipation, J. Atmos. Sci., 59, 125–139,
https://doi.org/10.1175/1520-0469(2002)059<0125:EBOAAI>2.0.CO;2, 2002. a, b, c, d
Prigogine, I.: Non-equilibrium statistical mechanics, Wiley, New York, 1962. a
Raymond, D. J.: Sources and sinks of entropy in the atmosphere, J.
Adv. Model. Earth Syst., 5, 755–763, https://doi.org/10.1002/jame.20050,
2013. a, b, c
Rodell, M., Beaudoing, H. K., L'Ecuyer, T. S., Olson, W. S., Famiglietti,
J. S., Houser, P. R., Adler, R., Bosilovich, M. G., Clayson, C. A., Chambers,
D., Clark, E., Fetzer, E. J., Gao, X., Gu, G., Hilburn, K., Huffman, G. J.,
Lettenmaier, D. P., Liu, W. T., Robertson, F. R., Schlosser, C. A.,
Sheffield, J., Wood, E. F., Rodell, M., Beaudoing, H. K., L'Ecuyer, T. S.,
Olson, W. S., Famiglietti, J. S., Houser, P. R., Adler, R., Bosilovich,
M. G., Clayson, C. A., Chambers, D., Clark, E., Fetzer, E. J., Gao, X., Gu,
G., Hilburn, K., Huffman, G. J., Lettenmaier, D. P., Liu, W. T., Robertson,
F. R., Schlosser, C. A., Sheffield, J., and Wood, E. F.: The Observed State
of the Water Cycle in the Early Twenty-First Century, J. Climate,
28, 8289–8318, https://doi.org/10.1175/JCLI-D-14-00555.1, 2015. a
Rose, B. E. J. and Ferreira, D.: Ocean Heat Transport and Water Vapor
Greenhouse in a Warm Equable Climate: A New Look at the Low Gradient
Paradox, J. Climate, 26, 2117–2136,
https://doi.org/10.1175/JCLI-D-11-00547.1, 2013. a, b
Schneider, T., Bischoff, T., and Haug, G. H.: Migrations and dynamics of the
Intertropical Convergence Zone, Nature, 513, 45–53,
https://doi.org/10.1038/nature13636, 2014. a
Smith, D. M., Allan, R. P., Coward, A. C., Eade, R., Hyder, P., Liu, C., Loeb,
N. G., Palmer, M. D., Roberts, C. D., and Scaife, A. a.: Earth's energy
imbalance since 1960 in observations and CMIP5 models, Geophys. Res.
Lett., 42, 1205–1213, https://doi.org/10.1002/2014GL062669, 2015. a, b
Stone, P. H.: Constraints on dynamical transports of energy on a spherical
planet, Dynam. Atmos. Ocean., 2, 123–139,
https://doi.org/10.1016/0377-0265(78)90006-4, 1978. a, b
Tailleux, R.: Available Potential Energy and Exergy in Stratified Fluids,
Ann. Rev. Fluid Mech., 45, 35–58,
https://doi.org/10.1146/annurev-fluid-011212-140620, 2013. a
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An overview of CMIP5 and the
experiment design, B. Am. Meteorol. Soc., 93,
485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012. a, b
Terai, C. R., Caldwell, P. M., Klein, S. A., Tang, Q., and Branstetter, M. L.:
The atmospheric hydrologic cycle in the ACME v0.3 model, Clim. Dynam.,
50, 3251–3279, https://doi.org/10.1007/s00382-017-3803-x, 2018. a
Trenberth, K. E. and Fasullo, J. T.: Simulation of present-day and
twenty-first-century energy budgets of the southern oceans, J. Climate, 23, 440–454, https://doi.org/10.1175/2009JCLI3152.1, 2010. a
Trenberth, K. E. and Solomon, A.: The Global Heat-Balance – Heat Transports in
the Atmosphere and Ocean, Clim. Dynam., 10, 107–134, https://doi.org/10.1007/Bf00210625, 1994. a
Trenberth, K. E., Caron, J. M., and Stepaniak, D. P.: The atmospheric energy
budget and implications for surface fluxes and ocean heat transports,
Clim. Dynam., 17, 259–276, https://doi.org/10.1007/PL00007927, 2001. a, b
Vannière, B., Demory, M.-E., Vidale, P. L., Schiemann, R., Roberts,
M. J., Roberts, C. D., Matsueda, M., Terray, L., Koenigk, T., and Senan, R.:
Multi-model evaluation of the sensitivity of the global energy budget and
hydrological cycle to resolution, Clim. Dynam., 52, 6817–6846,
https://doi.org/10.1007/s00382-018-4547-y, 2019. a
Veiga, J. A. P. and Ambrizzi, T.: A global and Hemispherical Analysis of the
Lorenz Energetics Based on the Representative Concentration Pathways Used in
CMIP5, Adv. Meteorol., 2013, 1–13, https://doi.org/10.1155/2013/485047, 2013. a
von Schuckmann, K., Palmer, M. D., Trenberth, K. E., Cazenave, A., Chambers,
D., Champollion, N., Hansen, J., Josey, S. A., Loeb, N. G., Mathieu, P.-P.,
Meyssignac, B., and Wild, M.: An imperative to monitor Earth's energy
imbalance, Nat. Clim. Change, 6, 138–144, 2016. a
Wilcox, L. J., Charlton-Perez, A. J., and Gray, L. J.: Trends in Austral jet
position in ensembles of high- and low-top CMIP5 models, J.
Geophys. Res.-Atmos., 117, D13115, https://doi.org/10.1029/2012JD017597,
2012. a
Wild, M. and Liepert, B. G.: The Earth radiation balance as driver of the
global hydrological cycle, Environ. Res. Lett., 5, 025203,
https://doi.org/10.1088/1748-9326/5/2/025203, 2010. a
Wild, M., Long, C. N., and Ohmura, A.: Evaluation of clear-sky solar fluxes in GCMs participating in AMIP and IPCC-AR4 from a surface perspective, J. Geophys. Res., 111, D01104, https://doi.org/10.1029/2005JD006118, 2006. a
Wild, M., Folini, D., Schär, C., Loeb, N. G., Dutton, E. G., and
König-Langlo, G.: The global energy balance from a surface
perspective, Clim. Dynam., 40, 3107–3134,
https://doi.org/10.1007/s00382-012-1569-8, 2013. a
Wild, M., Folini, D., Hakuba, M. Z., Schär, C., Seneviratne, S. I., Kato,
S., Rutan, D., Ammann, C., Wood, E. F., and König-Langlo, G.: The
energy balance over land and oceans: an assessment based on direct
observations and CMIP5 climate models, Clim. Dynam., 44, 3393–3429,
https://doi.org/10.1007/s00382-014-2430-z, 2015. a, b
Zhang, Y., Gao, Z., Li, D., Li, Y., Zhang, N., Zhao, X., and Chen, J.: On the computation of planetary boundary-layer height using the bulk Richardson number method, Geosci. Model Dev., 7, 2599–2611, https://doi.org/10.5194/gmd-7-2599-2014, 2014. a
Short summary
The Thermodynamic Diagnostic Tool (TheDiaTo v1.0) is a collection of diagnostics for the study of the thermodynamics of the climate system in climate models. This is fundamental in order to understand where the imbalances affecting climate projections come from and also to allow for easy comparison of different scenarios and atmospheric regimes. The tool is currently being developed for the assessment of models that are part of the next phase of the Coupled Model Intercomparison Project (CMIP).
The Thermodynamic Diagnostic Tool (TheDiaTo v1.0) is a collection of diagnostics for the study...