Session CL5.6

CL5.6 | Advances in Earth system modelling: process representation, benchmarking and understanding

Advances in Earth system modelling: process representation, benchmarking and understanding

Co-organized by ESSI2

Convener: Roland Séférian | Co-conveners: Joshua DorringtonECSECS, Alicia HouECSECS, Birgit Hassler, Ranjini Swaminathan, Torben Koenigk, Chantelle BurtonECSECS

Orals

| Mon, 15 Apr, 16:15–18:00 (CEST)

Room 0.31/32

Posters on site

| Attendance Mon, 15 Apr, 10:45–12:30 (CEST) | Display Mon, 15 Apr, 08:30–12:30

Hall X5

Posters virtual

| Attendance Mon, 15 Apr, 14:00–15:45 (CEST) | Display Mon, 15 Apr, 08:30–18:00

vHall X5

Earth System Models (ESMs) have evolved considerably in complexity, capability and scale as evidenced in projects such as the Coupled Model Intercomparison Project Phase 6 and the forthcoming CMIP7 project.
Coupled Earth system interactions such as feedbacks and potential abrupt changes are a significant source of uncertainty in our current understanding of the Earth system and how it might respond to future human interventions.
There is therefore a need to credibly assess such developments and capabilities for effective research on climate variability and change.
This session will examine physical, biogeochemical and biophysical processes likely to affect the evolution of the Earth system over the coming decades and centuries. Contributions with a focus on; (a) the latest advances in the representation of these couplings and interactions within state-of-the-art numerical models; (b) novel experimental designs to help improve quantification of these feedbacks, including those targeting CMIP7 activities and (c) novel approaches for benchmarking and evaluation of ESMs including cross-domain and process -based evaluation, observational uncertainties, science and performance metrics and benchmarks; are all particularly welcome.
This session arises from the joint initiative of the The CMIP7 Model Benchmarking Task Team, EU-funded ESM2025 and OptimESM projects.

Orals: Mon, 15 Apr | Room 0.31/32

Chairpersons: Roland Séférian, Ranjini Swaminathan, Birgit Hassler

16:15–16:20

5-minute convener introduction

16:20–16:30

EGU24-2831

On-site presentation

Efficient spin-up of Earth System Models using sequence acceleration

Samar Khatiwala and Eleanor Burke

The ocean and land carbon cycles plays a critical role in the climate system and are key components of the Earth System Models (ESMs) used to project future changes in the environment. However, their slow adjustment time also hinders effective use of ESMs because of the enormous computational resources required to integrate them to a pre-industrial quasi-equilibrium, a prerequisite for performing any simulations with these models and, in particular, identifying the human impact on climate. Here, a novel solution to this ``spin-up'' problem, regarded as one of the grand challenges in climate science, is shown to accelerate the equilibration of state-of-the-art marine biogeochemical models typical of those embedded in ESMs by over an order of magnitude. Based on a ``sequence acceleration'' method originally developed in the context of electronic structure problems, the new technique can be applied in a ``black box'' fashion to any existing model. Even under the challenging protocols used to spin-up ESMs for the IPCC Coupled Model Intercomparison Project, which can take up to two years on even some of the most powerful supercomputers, the new algorithm can reduce simulation times by a factor of 5, with preliminary results suggesting that complex land surface models can be similarly accelerated. The ability to efficiently spin-up ESMs would enable for the first time a quantification of major parametric uncertainties in these models, lead to more accurate estimates of metrics such as climate sensitivity, and allow increased model resolution beyond what is currently feasible.

How to cite: Khatiwala, S. and Burke, E.: Efficient spin-up of Earth System Models using sequence acceleration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2831, https://doi.org/10.5194/egusphere-egu24-2831, 2024.

16:30–16:40

EGU24-19283

ECS

On-site presentation

Understanding uncertainties in the global Earth climate response with reduced complexity climate models

Trevor Sloughter and Joeri Rogelj

Simple climate models provide a flexible, computationally cost-effective way to emulate the more complex and higher resolution earth system models. As ESMs are improved, adding in new processes that weren't explicitly included before, so too can the simple climate models be refined to reflect changes to our understanding of the climate response to changing emissions. New developments in modelling of peatlands, wetlands, permafrost, and negative emissions scenarios have provided new data to test the simple models MAGICC and FAIR. By comparing their projections under the same scenarios used by more complex models, the reduced complexity models' limitations and uncertainties can be shown, and thus they can be improved to better capture the new knowledge. Here, we focus on peatlands, comparing the results of a new module in the model OSCAR with the current output from MAGICC and FAIR, quantifying the impact that explicit peatland processes have on global temperature. Negative emissions scenarios are also considered, all as part of a broader project to understand overshoot pathways, scenarios in which the global temperature anomaly exceeds 1.5°C but returns to a temperature below that mark. These results will show the value and capability of the simple climate models as they continue to be refined to emulate the larger models.

How to cite: Sloughter, T. and Rogelj, J.: Understanding uncertainties in the global Earth climate response with reduced complexity climate models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19283, https://doi.org/10.5194/egusphere-egu24-19283, 2024.

16:40–16:50

EGU24-9963

Highlight

On-site presentation

Exploring the Role of Interactive Methane in Earth System Models used for Climate Projections

Fiona O'Connor, Gerd Folberth, Nicola Gedney, and Chris Jones

Methane plays a crucial role in the Earth System as a greenhouse gas and a tropospheric ozone precursor. However, in Phase 6 of the Coupled Model Intercomparison Project (CMIP6), Earth System Models predominantly relied on prescribed surface methane concentrations derived from historical observations or predefined future pathways. This study uses novel Earth System Model capability to investigate the impact of an emissions-driven methane cycle, including interactive wetland emissions. Specifically, we explore the influence of interactive methane on the effective radiative forcing of carbon dioxide and the model’s transient and equilibrium climate responses to changes in carbon dioxide.

The response of the climate to external forcings is intricately linked to climate feedbacks. With the inclusion of an interactive methane cycle in Earth System Models, understanding how changes in carbon dioxide and climate affect the methane cycle becomes imperative. This work critically re-evaluates the CMIP6 assessment of methane feedbacks and, for the first time, disentangles both the biophysical and radiative effects of carbon dioxide on wetland emissions and methane lifetime.

By enabling the interaction of the biophysical and radiative effects of carbon dioxide with natural methane emissions, concentrations, and climate responses, this presentation highlights the necessity of incorporating interactive methane components in Earth System Models. Notably, this approach provides scientists with the means to assess the direct implications of methane emission reduction policies and climate feedbacks on meeting global climate and air quality targets.

How to cite: O'Connor, F., Folberth, G., Gedney, N., and Jones, C.: Exploring the Role of Interactive Methane in Earth System Models used for Climate Projections, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9963, https://doi.org/10.5194/egusphere-egu24-9963, 2024.

16:50–17:00

EGU24-6106

ECS

On-site presentation

On the implementation of Leith viscosities in NEMO: Results from a forced global ocean model

Thomas Wilder and Till Kuhlbrodt

In CMIP6, eddy-permitting models (notably HadGEM3-GC3.1 N216ORCA025) were found to perform poorly
against their coarse-resolution counterparts, particularly in the Southern Ocean. Compared with N96ORCA1
(1 degree), ORCA025 exhibited an enhanced warm bias, weakened Antarctic Circumpolar Transport (~ 60 Sv),
overactive Antarctic gyres, and lower Antarctic sea-ice extent and volume. The poor performance of the eddy-
permitting model has been attributed to their diﬀiculty in representing mesoscale processes at higher latitudes.
Despite these shortcomings, eddy-permitting models remain desirable for their capacity to resolve meridional
transports of heat and carbon, and ice-ocean interactions.

The objective of this work is to improve the representation of mesoscale processes in ORCA025 through the
implementation of two viscosity schemes: 2D Leith and Quasi-Geostrophic Leith. These viscosity schemes
have been shown to improve interior mixing by mesoscale eddies in eddy-rich models. Both schemes offer a
parameterised viscosity coeﬀicient that is flow and scale-aware, in contrast to a typical constant biharmonic
viscosity employed in N216ORCA025.

In a forced ocean configuration (GOSI9p8.0 ORCA025), both Leith schemes demonstrate a marked impact on
the ocean’s circulation and its properties compared to biharmonic viscosity. Here, the Leith schemes dampen
the eddy kinetic energy field and reduce the Antarctic circumpolar transport, with corresponding changes in
temperature and salinity fields. Additional simulations, both forced and coupled, are ongoing and may provide
further insights into the different impacts of the Leith viscosity schemes on physical processes in eddy-permitting
Earth system models.

How to cite: Wilder, T. and Kuhlbrodt, T.: On the implementation of Leith viscosities in NEMO: Results from a forced global ocean model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6106, https://doi.org/10.5194/egusphere-egu24-6106, 2024.

17:00–17:10

EGU24-3432

ECS

On-site presentation

Evaluation of precipitation and ITCZ characteristics in CMIP6 models

Andreas Karpasitis, George Zittis, and Panos Hadjinicolaou

The Intertropical Convergence Zone (ITCZ) is a band of low pressure near the equator, where the trade winds converge. It is usually accompanied by cloudiness and heavy precipitation, and it migrates northward and southward, following the sun in different seasons. Climate models often misrepresent key atmospheric processes, including ITCZ's position, width and strength. As a result, biases in the modeled precipitation are also common in tropical and sub-tropical regions, such as the Indian subcontinent and parts of South America. Here, we assess the skill of four state-of-the-art Earth System Models in representing key ITCZ characteristics and the associated precipitation. The four ESMs under investigation are EC-EARTH, CNRM-ESM, IPSL-ESM, and UKESM. Besides the CMIP6 version of the aforementioned models, we also aim to evaluate post-CMIP6 simulations, which are currently under development in the framework of the OptimESM Horizon Europe project (https://optimesm-he.eu/). These post-CMIP6 models include advancements in the representation of physical, biogeochemical and biophysical processes. As a reference dataset, we use the ERA5 reanalysis data. Firstly, we divide the world into eight longitudinal zones and then calculate the zonal averages. For each season, we define the ITCZ location as the latitude where there is a peak in the 500hPa vertical velocity, while we consider the edges of the ITCZ at the latitudes where the 500hPa vertical velocity becomes zero. The strength of the ITCZ is defined as the value of the rainfall peak associated with the peak in the vertical velocity field. The analysis is performed on an annual basis, for each year from 1981 through 2010, and the corresponding peaks are clustered. The long-term characteristics of the ITCZ from the ESMs are compared to those from the ERA5 to understand the processes that drive precipitation biases in the global tropics.

How to cite: Karpasitis, A., Zittis, G., and Hadjinicolaou, P.: Evaluation of precipitation and ITCZ characteristics in CMIP6 models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3432, https://doi.org/10.5194/egusphere-egu24-3432, 2024.

17:10–17:20

EGU24-4037

On-site presentation

Revisiting the performance of CMIP6 models in the Arctic: Concerns on benchmarking climate models

Shuting Yang, Tian Tian, Jacob L. Hoyer, Pia Nielsen-Englyst, and Suman Singha

Climate models are known to have difficulty in simulating the present day climate in the Arctic. Many studies, including the most recent Inter-governmental Panel on Climate Change Sixth Assessment Report (IPCC AR6), report that, comparing to reanalysis datasets such as ERA5 as reference, climate models participating the past phases of the Coupled Model Intercomparison Project (CMIP) simulate a too cold Arctic. However, recent studies reveal substantial warm biases over sea ice surface in global atmospheric reanalyses due to missing representation of physical processes such as the snow layer on top of the sea-ice.

In this work we revisit the so-called long-standing climate model bias in the Arctic by using a new, satellite-derived near surface air temperature (T2m) dataset for the Arctic sea ice region as an alternative reference to the commonly used reanalysis data ERA5. This observational T2m dataset is derived from the satellite based on DMI/CMEMS daily gap-free (so called L4) sea surface temperature and sea ice surface temperature climate data record, spanning from 1^st January 1982 to 31^st May 2021, covering the Arctic region (> 58 ◦N). We show that, in comparison with the new observational dataset, the ERA5 reanalysis exhibits widespread warm biases exceeding 2℃ over sea ice in the central Arctic, particularly during winter when the warm bias may be as large as 6-10℃. In contrast, the CMIP6 model ensemble demonstrates reasonable performance, with an annual mean bias less than ±1℃ in the same region. We also find that the CMIP6 model mean slightly outperforms the ERA5 in capturing the observed warming trend over the central Arctic region where is fully covered by sea ice with concentration of more than 70%. Outside of this region, it is evident that ERA5 aligns well with observations, while CMIP6 models show large cold bias in the North Atlantic marginal ice zone, consistent with the well-documented results in the past.

Our results challenge the current assessment of climate models in the central Arctic, suggesting that relying on existing reanalyses datasets as a reference may underestimate the climate models creditability in the region. It is thus imperative to integrate new observational data for benchmarking climate models in the Arctic region.

How to cite: Yang, S., Tian, T., Hoyer, J. L., Nielsen-Englyst, P., and Singha, S.: Revisiting the performance of CMIP6 models in the Arctic: Concerns on benchmarking climate models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4037, https://doi.org/10.5194/egusphere-egu24-4037, 2024.

17:20–17:30

EGU24-8181

ECS

On-site presentation

Discrepancies in temporal pCO2 variability from Earth System Models and pCO2-products related to high-latitude mixed layer dynamics and equatorial upwelling

Christopher Danek and Judith Hauck

The air-sea CO₂ flux FCO₂ is an important component of the global carbon budget and understanding its response to climate change is crucial to adjust mitigation pathways. Multi-linear regression supports the expectation that the balance between the CO₂ partial pressures of air and the sea surface (pCO₂) is the most important driver of temporal FCO₂ variability. Discrepancies between state-of-the-art Earth System Models (ESMs) and gridded pCO₂-products suggest that systematic biases exist across an ensemble of ESMs. In the equatorial regions, upwelling variability of carbon-rich water is biased in ESMs as modeled and observed sea surface temperature are generally uncorrelated. In the high latitudes, the climate change induced trend towards lighter sea water is overestimated in ESMs, which yields - in contrast to observations - shallower mixed layers over the contemporary period and hence a suppressed carbon supply from depth. While mixed layer depth variability and trends appear biased throughout the global ocean, this is not a determining factor for pCO₂ variability in subtropical gyres. The results highlight the importance of accurately modeling hydrographic properties to obtain robust estimates of FCO₂ and its variability.

How to cite: Danek, C. and Hauck, J.: Discrepancies in temporal pCO2 variability from Earth System Models and pCO2-products related to high-latitude mixed layer dynamics and equatorial upwelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8181, https://doi.org/10.5194/egusphere-egu24-8181, 2024.

Discussion Post a comment

17:30–17:40

EGU24-22316

Highlight

On-site presentation

Climate Model Benchmarking for CMIP7 – A CMIP Task Team

Forrest Hoffman and Birgit Hassler

The goal of the Coupled Model Intercomparison Project (CMIP) is to better understand past, present, and future climate changes in a multi-model context. Based on the outcomes of the phase 6 of CMIP (CMIP6) Community Survey, the CMIP panel is seeking to identify ways to increase the project's scientific and societal relevance, improve accessibility, and widen participation. To achieve these goals, a number of Task Teams were established to support the design, scope, and definition of the next phase of CMIP and the evolution of CMIP infrastructure and future operationalization.

An important prerequisite for providing reliable climate information from climate and Earth system models is to understand their capabilities and limitations. Thus, systematically and comprehensively evaluating the models with the best available observations and reanalysis data is essential. For CMIP7 new evaluation challenges stemming from models with higher resolution and enhanced complexity need to be rigorously addressed. These challenges are both technical (e.g., memory limits, increasingly unstructured and regional grids), and scientific. In particular, innovative diagnostics, including the support of machine learning-based analysis of CMIP simulations, must be developed.

The Climate Model Benchmarking Task Team aims to provide a vision and concrete guidance for establishing a systematic, open, and rapid performance assessment of the expected large number of models participating in CMIP7, including a variety of informative diagnostics and performance metrics. The goal is to fully integrate evaluation tools into the CMIP publication workflow, and their diagnostic outputs published alongside the model output on the ESGF, ideally displayed through an easily accessible website. To accomplish this, existing evaluation tools need to be further developed and applied to historical and other CMIP7 simulations. We expect to produce an increasingly systematic characterization of the models which, compared with early phases of CMIP, will more quickly and openly identify the strengths and weaknesses of simulation results. This will also reveal whether long-standing model errors remain evident in newer models and will assist modelling groups in improving their models. This framework will be designed to readily incorporate updates, including new observations and a multitude of additional diagnostics and metrics as they become available from the research community, and will be developed as fully open-source software with high documentation standards.

How to cite: Hoffman, F. and Hassler, B.: Climate Model Benchmarking for CMIP7 – A CMIP Task Team, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22316, https://doi.org/10.5194/egusphere-egu24-22316, 2024.

17:40–17:50

EGU24-12905

Virtual presentation

A new ESMValTool metric using point source observations from AeroNET

Catherine Hardacre, Klaus Zimmermann, Joakim Löw, and Jane Mulcahy

ESMValTool is an open-source community-developed diagnostics and performance metrics tool for the evaluation and analysis of Earth System Models (ESMs). Key to model evaluation with ESMValTool is the use of observational data, which must comply with Climate Model Output Rewriter (CMOR) standards. ESMValTool provides methods to generate CMOR compliant datasets, but these are designed to process gridded observational data sets, such as those from satellites, and currently it is more difficult to develop point source datasets. Here we present a new ESMValTool metric for evaluating model output against an observation-based climatology of aerosol optical depth (AOD) from the Aerosol Robotic Network (AeroNET). This metric includes a downloader and formatter to generate CMOR compliant datasets for the observational AOD timeseries from all AeroNET stations. These are collated into a single NetCDF file. A new ESMValTool recipe and diagnostic process and evaluate the model output against the observational AOD dataset at model grid cells co-located with the AeroNET stations. Model output is processed in the recipe using available pre-processers to generate multi-annual seasonal means. The observational AOD timeseries from the AeroNET stations are processed in the diagnostic to generate multi-annual seasonal means, or ‘climatologies’. Because the AOD timeseries from the AeroNET stations can be incomplete, filtering criteria are applied to the data from each station to ensure sufficient temporal coverage according to the user’s requirements. We evaluate AOD at 440mn simulated by CMIP6 historical ensemble members against the AOD climatologies using the new ESMValTool metric. We also demonstrate how changing the filtering criteria can modify the observational climatologies, and thus the evaluation metrics. The new method extends atmospheric composition evaluation in the ESMValTool framework by adding a key aerosol metric. We hope that the techniques used to develop this metric can be applied to other point source observation datasets.

How to cite: Hardacre, C., Zimmermann, K., Löw, J., and Mulcahy, J.: A new ESMValTool metric using point source observations from AeroNET, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12905, https://doi.org/10.5194/egusphere-egu24-12905, 2024.

17:50–18:00

EGU24-7132

Virtual presentation

Introduction to an open-source tool for collective Earth System Model evaluation and benchmarking: PCMDI Metrics Package (PMP)

Jiwoo Lee, Ana Ordonez, Peter Gleckler, Paul Ullrich, Yann Planton, Bo Dong, Kristin Chang, Paul Durack, Elina Valkonen, and Julie Caron

The PCMDI Metrics Package (PMP) is an open-source Python-based framework that enables objective "quick-look" comparisons and benchmarking of Earth System Models (ESMs) against observation-based reference datasets. The PMP, which is focused primarily on atmospheric quantities, has been used for routine and systematic evaluation of thousands of simulations from the Coupled Model Intercomparison Project (CMIP). Ongoing work aims for seamless application of the tool to the next generation of CMIP (CMIP7), with an aspiration to aid modeling groups during their development cycle. The latest version of PMP offers a diverse suite of evaluation capabilities covering large- to global-scale climatology and annual cycle, variability modes such as tropical and extratropical variability modes e.g., ENSO and MJO, regional monsoons, cloud feedback, and high frequency characteristics e.g., extremes. Current work is expanding the scope of PMP to include the evaluation of the following: (1) Quasi-Biennial Oscillation (QBO) and its teleconnection to MJO, (2) atmospheric blocking and rivers leveraging Machine Learning based pattern detection algorithms, and (3) polar and high-latitude regions by implementing sectional sea-ice area metrics. The PMP is also advancing its evaluation capabilities to help evaluate higher resolution simulations such as those from the HighResMIP, cloud-resolving E3SM experiments, and regionally downscaled products. This presentation will highlight the motivation for routine model evaluation, introduce the PMP, share progress on current polar metrics, and discuss future plans and opportunities to connect with ongoing efforts.

How to cite: Lee, J., Ordonez, A., Gleckler, P., Ullrich, P., Planton, Y., Dong, B., Chang, K., Durack, P., Valkonen, E., and Caron, J.: Introduction to an open-source tool for collective Earth System Model evaluation and benchmarking: PCMDI Metrics Package (PMP), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7132, https://doi.org/10.5194/egusphere-egu24-7132, 2024.

Discussion Post a comment

Posters on site: Mon, 15 Apr, 10:45–12:30 | Hall X5

Display time: Mon, 15 Apr 08:30–Mon, 15 Apr 12:30

Chairpersons: Ranjini Swaminathan, Alicia Hou, Chantelle Burton

X5.83

EGU24-298

ECS

Sensitivity of the CNRM-CM6-1 ocean-climate model to freshwater inputs from Antarctica

Joachim Piret, Sarah Berthet, and Aurore Voldoire

Meltwater fluxes from Antarctica are in general poorly represented in ocean models in terms of quantity and spatio-temporal variability. These meltwater fluxes impact the stratification and the circulation of the Southern Ocean, which is a key component of the climate system. In particular, the opening of deep water polynyas depends, amongst other, on ocean stratification. In turn, these polynyas then, for instance, impact the ventilation of the Southern Ocean and the ocean-atmosphere exchanges of heat.

In this study, we explore how the ocean and sea-ice components of the CNRM-CM6-1 climate model are affected by the spatial distribution and magnitude of meltwater fluxes through three sensitivity experiments. In a first experiment, only a constant basal melting (restricted at the coast) is used as forcing. In a second experiment, only melting from monthly drifting icebergs is used. Finally, in a third experiment, both melting fluxes are used to force the model.

In our experiments, several deep water polynyas are diagnosed in the Weddell Sea and offshore of Pridz Bay. We find that these polynyas are places of deep-water formation impacting water masses properties over the entire column. In this study we analyze how the magnitude, occurrences and frequencies of occurrences of these polynyas are affected by the representation of the meltwater fluxes from Antarctica. We also diagnosed a deep water polynya around Maud Rise with features similar to the giant polynya observed every winter between 1974 and 1976.

Understanding the opening of these polynyas is challenging, since this requires an analysis on the stability of the water column and disentangling the role of external forcing (i.e. the role of the meltwater fluxes) from the model’s internal variability.

How to cite: Piret, J., Berthet, S., and Voldoire, A.: Sensitivity of the CNRM-CM6-1 ocean-climate model to freshwater inputs from Antarctica, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-298, https://doi.org/10.5194/egusphere-egu24-298, 2024.

X5.84

EGU24-1912

ECS

Evaluation of the EC-EARTH3-VEG climate model in reproducing the evolution of maximum and minimum air temperatures in Brazil

Fernanda De Amorim Formigoni, Catarina De Abreu Heil, Juliana Da Costa Mendes Reis, Priscila Esposte Coutinho, Lívia Sancho, and Marcio Cataldi

According to the Sixth Report of the Intergovernmental Panel on Climate Change (IPCC), published in 2023, between 2011 and 2020, global surface temperatures increased by 1.1°C compared to the period 1850-1900. This upward trend in temperature is related to changes in the observed climate patterns, which will potentially lead to a greater incidence of extreme weather events and ecosystem changes, as well as impacting the health of human populations. In Brazil, this scenario could also result in biodiversity losses, reduced agricultural productivity and changes in the availability of water resources, with consequences for the country's economy and energy security. Considering this context, this study aims to evaluate the ability of the EC-Earth3-Veg model, part of the Coupled Model Intercomparison Project Phase 6 (CMIP6), to reproduce the evolution of maximum and minimum air temperatures at 2 meters in Brazil during the historical period, at intervals between 1961 and 2014, comparing it with ERA5 reanalysis data. The CMIP6 data was interpolated to the ERA5 grid to carry out the desired analysis. Based on this, it was observed that EC-Earth3-Veg was able to reproduce the historical climatology for Brazil but showed climatological differences when compared to ERA5 in the four periods observed. It is common among the periods analyzed that the further north of the country is warmer, with maximum temperatures in summer and autumn. In winter and spring, the same happens in the eastern part of the North, the Center-West, and the northern part of the Southeast of Brazil. In the fall, the Northeast and Midwest show cooler highs. The period in which the model's results were closest to ERA5 was from 1961 to 1990, especially for minimum temperatures in summer and winter. Even so, in the fall and spring of this period, the model showed warming in relation to the minimums in the South, and, in all the quarterly cut-outs, it showed cooling in the minimums near the Northeast. In general, certain regional and seasonal patterns were observed in the results, which may indicate a limitation of the model in terms of horizontal resolution in considering a more characteristic atmosphere for Brazil. In the southern region, for example, the maximum and minimum temperatures in the model showed warming. This may indicate that the model is limited in its horizontal resolution and does not consider an atmosphere that is more characteristic of Brazil. Therefore, to improve the model's performance in simulating the climate in Brazil, it is necessary to correct the bias and use EC-Earth3-Veg in conjunction with other models to reduce systematic errors. This study aims to replicate this work for other models.

How to cite: De Amorim Formigoni, F., De Abreu Heil, C., Da Costa Mendes Reis, J., Esposte Coutinho, P., Sancho, L., and Cataldi, M.: Evaluation of the EC-EARTH3-VEG climate model in reproducing the evolution of maximum and minimum air temperatures in Brazil, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1912, https://doi.org/10.5194/egusphere-egu24-1912, 2024.

X5.85

EGU24-1617

ACCESS-NRI: Supporting Climate Science through Robust Model Evaluation and Community-Driven Strategies

Romain Beucher, Michael G. Tetley, Yousong Zeng, Felicity Chun, Dougal Squire, Owen Kaluza, Kelsey Druken, and Andy Hogg

The Australian Earth System Simulator (ACCESS-NRI) is a national research infrastructure designed to support the development and research of the Australian Community Climate and Earth System Simulator (ACCESS). With a strategic goal to enhance the quality and performance of the ACCESS suite of model configurations, ACCESS-NRI supports the open development and release of a Model Evaluation and Diagnostics (MED) framework for the Australian Earth system modeling community.

In climate science, the evaluation of computational models plays a pivotal role in assessing their performance and reliability in simulating the Earth's complex climate system. This process involves a comprehensive analysis of model predictions against observed data to determine accuracy and utility. Through meticulous model evaluation, scientists gain insights into real-world climate processes, identify model strengths and weaknesses, and refine models to enhance predictive capabilities.

Integral to international climate change assessments, climate models are crucial for shaping policies and guiding investments in climate action. Accurate simulations, reliant on precise modeling of climate physics and realistic forcing conditions, such as CO2 emissions, are fundamental to these endeavors. However, the development of these models is a protracted, iterative process requiring constant evaluation of performance and accuracy. Users seek to compare model simulations derived from diverse configurations, necessitating dedicated tools, workflows, and access to diverse data sources within high-performance computing environments.

The development of tools and methods is integral to this initiative, providing essential support for the incorporation of model evaluation within code development cycles. The presentation explores community-driven strategies designed to streamline the evaluation of the ACCESS suite of models, addressing specific requirements and constraints associated with the World Climate Research Programme’s (WCRP) Coupled Model Intercomparison Project phase 7 (CMIP7) and its future iterations. Emphasis is placed on the incorporation of model evaluation within code development cycles.

How to cite: Beucher, R., Tetley, M. G., Zeng, Y., Chun, F., Squire, D., Kaluza, O., Druken, K., and Hogg, A.: ACCESS-NRI: Supporting Climate Science through Robust Model Evaluation and Community-Driven Strategies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1617, https://doi.org/10.5194/egusphere-egu24-1617, 2024.

X5.86

EGU24-1740

ECS

Introduction of tropospheric chemistry in the CNRM Earth System Model (ESM): towards methane emission-driven capability.

Martin Cussac, Martine Michou, Pierre Nabat, Béatrice Josse, and Pelletier Sophie

Methane (CH₄) is the second most important greenhouse gas after carbon dioxide (CO₂), and improving the representation of its cycle in climate models is a key step to reduce uncertainties in climate projections. Its main sink is chemical removal through oxidation with hydroxyl radicals (OH) in the troposphere, which are produced during the photolysis of ozone (O₃) in presence of water vapour. This process is an example of the complex interactions between methane and climate system, highlighting the necessity to have an explicit and interactive representation of atmospheric composition in Earth System Models. Here we present the introduction of two tropospheric/stratospheric chemical schemes of various complexities in ARPEGE-Climat 7.0, the future version of the atmospheric component of CNRM-ESM, and the impact on methane representation. This work includes the addition and changes of multiple processes at stakes in the troposphere, for instance emissions, deposition or production of NO_x by lightning strikes. We first present an evaluation of tropospheric air composition in our model including all the aforementioned developments. Diagnostics from both chemical schemes in AMIP-type simulations are compared to observations and to state of the art atmospheric composition reanalyses such as the CAMS reanalysis. We highlight, in particular, the performance of both chemical schemes in terms of biases and seasonal cycles of major tropospheric tracers like O₃, CO or NO₂. We also compute from RFMIP-type simulations the ozone ERF, and compare it to previous estimates. Secondly, we present an evaluation of the behaviour of pre-industrial simulations in a methane “emission-driven” mode. These simulations are compared to more classical “concentration-driven” simulations in terms of global methane budget and methane chemical lifetime.

How to cite: Cussac, M., Michou, M., Nabat, P., Josse, B., and Sophie, P.: Introduction of tropospheric chemistry in the CNRM Earth System Model (ESM): towards methane emission-driven capability., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1740, https://doi.org/10.5194/egusphere-egu24-1740, 2024.

X5.87

EGU24-3938

Live monitoring, diagnostics and data management for the ACCESS suite of Earth-system simulations.

Michael Tetley, Dougal Squire, and Romain Beucher

As global Earth-System simulations rapidly increase in complexity as a direct result of available compute resources and advancing scientific model development, monitoring long-running models and managing associated big data outputs has become increasingly difficult. This has inspired a need for open community-focussed software tools that provide intuitive and efficient HPC-native functionality to accurately evaluate live model performance and behaviour, perform diagnostic scientific analyses, compare current results with alternative or reference models, and generate standardised data outputs. Addressing these challenges, we present a new community-driven open-source project Model Live Diagnostics (MLD) which integrates the ACCESS-NRI Intake Catalog API, together forming part of The Australian Earth-System Simulator (ACCESS-NRI) Model Evaluation and Diagnostics (MED) framework supporting climate science research within the Australian Community Climate and Earth System Simulator (ACCESS).

MLD is an open-source Python package optimised for use in JupyterLab sessions on the Australian NCI supercomputer Gadi. The primary purpose of MLD is to provide a simple, easy to use and accessible framework for the ACCESS modelling community to check, monitor, visualise and evaluate live running Earth-System model behaviour and progress. Utilising the ACCESS-NRI Intake Catalog API, MLD monitors a given model output data directory on Gadi, dynamically building an intake cataog of the most up-to-date data and automatically generating interactive plots to visualise model variables. From these data, MLD provides functions to perform light-weight diagnostic calculations, compare and plot results against reference models, and export data in standard Xarray format for integration into user workflows. MLD can be installed manually via Conda or PyPI, it comes pre-installed in existing Conda environments on Gadi, and the full source code is available on the project Github repository. MLD currently supports Earth System Model 1.5 (ACCESS-ESM1.5), Model for Ocean/Sea Ice (ACCESS-OM2) and Coupled Model 2 (ACCESS-CM2).

How to cite: Tetley, M., Squire, D., and Beucher, R.: Live monitoring, diagnostics and data management for the ACCESS suite of Earth-system simulations., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3938, https://doi.org/10.5194/egusphere-egu24-3938, 2024.

X5.88

EGU24-8947

ECS

Monitoring and Benchmarking of Earth System Model Simulations with ESMValTool

Manuel Schlund, Axel Lauer, Lisa Bock, and Birgit Hassler

Earth system models (ESMs) are important tools to improve our understanding of present-day climate and to project climate change under different plausible future scenarios. For this, ESMs are continuously improved and extended resulting in more complex models. Particularly during the model development phase, it is important to continuously monitor how well the historical climate is reproduced and to systematically analyze, evaluate, understand, and document possible shortcomings. For this, putting model biases relative to observations into the context of deviations shown by other state-of-the-art models greatly helps to assess which biases need to be addressed with higher priority. Here, we introduce the new capability of the Earth System Model Evaluation Tool (ESMValTool) to monitor running or benchmark existing simulations with observations in the context of results from the Coupled Model Intercomparison Project (CMIP). ESMValTool is an open-source community-developed diagnostics and performance metrics tool for the evaluation and analysis of ESMs. To benchmark model output, ESMValTool calculates metrics such as root mean square error (RMSE) or the coefficient of determination (R²) relative to reference datasets. This is directly compared to the same metric calculated for an ensemble of models such as CMIP6, which provides a statistical measure for the range of values that can be considered typical for state-of-the-art models. Results are displayed in different types of plots such as map plots (using stippling and hatching) or time series (via uncertainty bands). Automatic downloading of CMIP results from the Earth System Grid Federation (ESGF) makes application of ESMValTool for benchmarking of individual model simulations, for example in preparation of CMIP7, easy and very user friendly.

How to cite: Schlund, M., Lauer, A., Bock, L., and Hassler, B.: Monitoring and Benchmarking of Earth System Model Simulations with ESMValTool, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8947, https://doi.org/10.5194/egusphere-egu24-8947, 2024.

X5.89

EGU24-10399

Extreme cold events in Europe under a reduced AMOC

Susanna Corti, Virna Loana Meccia, Claudia Simolo, and Katinka Bellomo

There is a consensus that a weakened Atlantic Meridional Overturning Circulation (AMOC) decreases mean surface temperature in the Northern Hemisphere, both over the ocean and the continents. However, the impacts of a reduced AMOC on cold extreme events have not yet been examined. We analyse the impacts of a reduced AMOC strength on extreme cold events over Europe using targeted sensitivity experiments with the EC-Earth3 climate model. Starting from a fully coupled ocean-atmosphere simulation in which the AMOC was artificially reduced, a set of atmosphere-only integrations with prescribed sea surface temperature and sea-ice cover was conducted to evaluate the effects of weakly and strongly reduced AMOC strength. Despite overall cooling, reduced AMOC leads to fewer winter cold spells in Europe. We find that the weakened AMOC intensifies near-surface meridional gradient temperature in the North Atlantic and Europe, thus providing the energy to boost the jet stream. A stronger jet stream leads to less atmospheric blocking, reducing the frequency of cold spells over Europe. Although limited to the output of one model, our results indicate that a reduced AMOC strength may play a role in shaping future climate change cold spells by modulating the strength of the jet stream and the frequency of atmospheric blocking.

How to cite: Corti, S., Meccia, V. L., Simolo, C., and Bellomo, K.: Extreme cold events in Europe under a reduced AMOC, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10399, https://doi.org/10.5194/egusphere-egu24-10399, 2024.

X5.90

EGU24-10541

ECS

Computationally efficient evaluation of Earth System Models in the presence of complex uncertainties

Nils Weitzel, Muriel Racky, Laura Braschoß, and Kira Rehfeld

Comparing Earth System Model (ESM) simulations with in-situ, lab, and remote sensing measurements often involves analytically intractable uncertainty structures for example due to observational uncertainties, internal variability in the climate system, and limitations of ESMs. With increasing resolution of models, ensemble sizes, length of simulations, and number of observations, this can create computational bottlenecks. Making use of Monte Carlo techniques in a data cube architecture, we present a python package for efficient propagation of complex uncertainties in model-data comparison. Additionally, the package contains functionalities for visualizations of uncertainties and the computation of probabilistic score functions.

Our focus is on measurement operators, in particular so-called proxy system models that map ESM output onto proxy measurements for transient paleoclimate simulations. Proxy system models contain multiple sources of autocorrelated and non-Gaussian uncertainties due to complex proxy-climate relationships, chronological uncertainties, and processes perturbing the recorded climate signal during the sedimentation of the proxy. Thereby, we connect data cube methods for processing climate simulations with analysis techniques for point data such as those stemming from time series of paleoclimate proxy records. We demonstrate our approach by quantifying the discrepancies of temperature and forest cover changes between global proxy networks and transient simulations from the Last Glacial Maximum to present-day. Given the ongoing shift in the paleoclimate modelling community from equilibrium time-slice towards long transient simulations, our work can help integrate the evaluation of simulations from the Paleoclimate Modelling Intercomparison Project (PMIP) into CMIP7 model benchmarking. Additionally, the implemented methods are transferable to other types of observations that are subject to analytically intractable uncertainty structures.

How to cite: Weitzel, N., Racky, M., Braschoß, L., and Rehfeld, K.: Computationally efficient evaluation of Earth System Models in the presence of complex uncertainties, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10541, https://doi.org/10.5194/egusphere-egu24-10541, 2024.

X5.91

EGU24-11464

Highlight

Are early warning signals present for climate tipping points detected in CMIP6?

Tim Lenton, Paul Ritchie, and Chris Boulton

X5.92

EGU24-16708

Towards a coupled nitrogen cycle representation in NorESM – ocean biogeochemistry

Joeran Maerz, Dirk Jan Leo Olivié, Tomas Torsvik, and Christoph Heinze

The nitrogen cycle is substantially anthropogenically perturbed with potential negative consequences on biogeochemical cycles, for the climate and society. Within the project ESM2025, we therefore aim at an improved representation and interactive, emission-driven nitrogen cycle in the Norwegian Earth system model (NorESM) to foster providing information about future societal impacts.

We here focus on the ocean biogeochemistry component iHAMOCC of NorESM, where major upgrades have been carried out with a particular focus on processes related to the highly potent greenhouse gas N₂O. We included two more tracers, namely NH₄⁺ and NO₂^-, which enabled an explicit representation of major canonical ocean nitrogen cycle pathways in both, the water column and the sediment. The in parallel substantially improved atmosphere chemistry of NorESM enabled us to realize the thus far technical capability to interactively couple air-sea N₂O and NH₃ fluxes as well as receiving atmospheric dry and wet deposition fluxes in the form of NH_x and NO_y. Concomitantly, interactive atmosphere-land N₂O and nitrogen deposition fluxes were implemented, further increasing NorESMs capability for coupled nitrogen cycle simulations. The improved NorESM atmosphere and ocean component are currently individually in fine-tuning and spin-up phase in close preparation for first interactively coupled simulations.

Preliminary, partially still in transient ocean-only climatological atmosphere-forced simulations show a reasonable oceanic N₂O emission pattern, also quantitatively close to recent reconstructions of Yang et al. 2020 (4.2 TgN/yr, doi:10.1073/pnas.1921914117), while the global ammonia emissions are at the lower end of current estimates (2-27 TgN/yr). With the current improved oceanic nitrogen cycle representation, N₂O production during nitrification in well-ventilated areas is closely linked to primary production through subsequent decay and ammonification of organic nitrogen. By contrast, the transition zones of oxygen deficit zones (ODZs) entail microbial key processes of both aerobic and anaerobic N₂O production and anaerobic N₂O consumption, making those regions to hotspots of nitrogen cycling relevant to N₂O. For the sediments, productive ocean and shelf regions feature higher N₂O sediment-water column fluxes per unit area than deep sea regions, in line with current observational knowledge. In total, however, the sediments globally contribute significantly less to N₂O production than the water column. In brief, future evolution of export fluxes and ODZs can hence be expected to determine the oceanic N₂O release in response to ongoing climate change.

With the recent developments in NorESM, we increased the representation of nitrogen cycle-relevant processes and enhanced the thus far technical capability to simulate the nitrogen cycle emission-driven and interactively coupled across major Earth system components, while envisaging to also increase NorESMs land-ocean nitrogen transport representation.

How to cite: Maerz, J., Olivié, D. J. L., Torsvik, T., and Heinze, C.: Towards a coupled nitrogen cycle representation in NorESM – ocean biogeochemistry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16708, https://doi.org/10.5194/egusphere-egu24-16708, 2024.

X5.93

EGU24-20894

Methodological Developments in the International Land Model Benchmarking Effort

Nathan Collier, Forrest Hoffman, and Dave Lawrence

As earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model performance. The International Land Model Benchmarking (ILAMB) project is a model-data intercomparison and integration project designed to improve the performance of land models and improve the design of new measurement campaigns to reduce uncertainties associated with key land surface processes. While the effort has been established for over a decade, we continue to make developments and improvements in order to incorporate new datasets as well as adapt our scoring methodology to be more useful for model developers in identifying and diagnosing model errors.

The version 2.7 release of the ILAMB python software includes new datasets for gross primary productivity and latent/sensible heat flux (WECANN: Water, Energy, and Carbon with Artificial Neural Networks), growing season net carbon flux (Loechli2023), biomass (ESACCI: European Space Agency, Biomass Climate Change Initiative and XuSaatchi2021), methane (Fluxnet), and surface soil moisture (Wang2021). In addition to these land-focused datasets, ILAMB v2.7 marks the first release of the International Ocean Model Benchmarking (IOMB) package. While the codebase remains the same as is used with the land, this release encodes datasets and configuration file to be used in benchmarking ocean models.

Finally, we present a shift in the ILAMB scoring methodology. In order to make errors comparable across different areas of the globe, ILAMB originally employed a normalization of errors by the variability of the reference quantity in a particular location. For many variables, this choice tends to strongly weight performance in the tropics and consequently does not give a balanced perspective on model performance across the globe. To balance performance across the globe, we propose a shift to normalize errors by regional error quantiles. We select regions which conform to traditional understanding of biomes in order to focus on areas where we expect errors to be commensurate in the order of magnitude. We then choose a normalizing quantity by taking a quantile of the errors in these biomes across a selection of CMIP5 and CMIP6 era models. In this way, we contextualize the scores by using the performance of the recent generations of models.

How to cite: Collier, N., Hoffman, F., and Lawrence, D.: Methodological Developments in the International Land Model Benchmarking Effort, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20894, https://doi.org/10.5194/egusphere-egu24-20894, 2024.

Posters virtual: Mon, 15 Apr, 14:00–15:45 | vHall X5

Display time: Mon, 15 Apr 08:30–Mon, 15 Apr 18:00

Chairpersons: Birgit Hassler, Joshua Dorrington, Torben Koenigk

vX5.10

EGU24-12558

Recent developments in the Earth System Model evaluation tool

Bouwe Andela, Birgit Hassler, and Manuel Schlund

ESMValTool (Earth System Model eValuation Tool) is open-source, community-developed software for the evaluation of Earth system models, mainly in the context of multi-model analyses, e.g. the Coupled Model Intercomparison Project (CMIP). ESMValTool provides a large number of “recipes” that reproduce published figures, for example, some of the figures found in reports of the Intergovernmental Panel on Climate Change (IPCC). ESMValCore, the framework powering ESMValTool, provides capabilities that make it easy to work with data produced for CMIP as well as related observational and reanalysis data, e.g. discovering, downloading, and preprocessing these data. Here, we present new features that have been added to ESMValCore and ESMValTool in the past year.

Improved computational performance: it is now possible to use Dask Distributed to run the tool and almost all preprocessor functions are now using Dask arrays, resulting in lower memory use and faster computations. This enables the analysis of higher-resolution datasets, such as those expected for the next round of CMIP. Further performance improvements are planned this year as part of the ESiWACE3 service project.

New recipes and better-looking results: several new analyses have been added, including recipes for reproducing figures from the IPCC’s Fifth and Sixth Assessment Reports and generic recipes for monitoring and evaluating Earth System Model simulations. The webpage displaying the results of a recipe run now looks better and allows for interactive filtering.

More datasets: more observational and reanalysis datasets can now be converted to the CMIP data request standard using the tool. Grids used in the Coordinated Regional Climate Downscaling Experiment (CORDEX) are now better supported.

Communication: the ESMValTool tutorial at https://tutorial.esmvaltool.org has been updated, more Jupyter notebooks are available to demonstrate the use of ESMValCore, and there is a new, open-source website at https://esmvaltool.org.

How to cite: Andela, B., Hassler, B., and Schlund, M.: Recent developments in the Earth System Model evaluation tool, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12558, https://doi.org/10.5194/egusphere-egu24-12558, 2024.

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