The aim of this special issue in Geoscientific Model Development is to collate contributions from the EGU General Assembly 2024, specifically the session titled "Advances in Numerical Modelling of Geological Processes". This session explores the complex multi-physics nature of geological processes, which often involve the interaction of different physical phenomena. Such interactions can generate nonlinear responses, leading to the spontaneous localization of flow and deformation.

In addition to physics-based models, geological and geophysical datasets serve as another vital source of information, while recent technological advancements have significantly enhanced spatial and temporal resolutions.

Understanding the interplay between different physical processes necessitates the development of advanced numerical tools and methodologies. Effective new models should utilize various types of parallel hardware efficiently and in a backend-agnostic manner. These models must also balance conciseness with the capability to bridge portability and performance, thereby addressing the challenge of the two-language barrier. Furthermore, new applications that incorporate high-quality data into physics-based predictive numerical simulations are crucial. These applications facilitate workflows that further refine key unknown parameters within the models. The integration of innovative inversion strategies, which connect forward dynamic models with observable data, and the combination of partial differential equation (PDE) solvers with machine learning (ML) through differentiable programming, represent significant areas of research within this field.

We invite contributions from the following two complementary themes also featured in the EGU session:

1. The first of these themes entails computational advances associated with alternative spatial and/or temporal discretization for existing forward/inverse models, scalable high-performance computing implementations of new and existing methodologies (GPUs/multi-core), solver and preconditioner developments, combining PDEs with AI- or ML-based approaches (physics-informed ML), automatic differentiation and differentiable programming, and significant performance increases by using new algorithms or code and methodology comparisons (benchmarks).
2. The second area of interest comprises physics advances associated with the development of PDEs to describe geological processes, inversion strategies and adjoint-based modelling, numerical model validation through comparison with observables (data), scientific discovery enabled by 2D and 3D modelling, and utilization of coupled models to explore nonlinear interactions.

The Agricultural Model Intercomparison and Improvement Project (AgMIP) coordinates protocol-based model intercomparison studies, analyzing model performance in order to build trust in models, identify deficiencies and strategies for model improvements, and to quantify model uncertainties. Within AgMIP, the Global Gridded Crop Model Intercomparison (GGCMI) focuses on global-scale crop model applications, development and evaluation. Several phases of GGCMI are conducted in coordination with the Intersectoral Impact Model Intercomparison (ISIMIP). In this special issue, we summarize protocol and experiment description papers, as well as model development and evaluation papers of the different GGCMI phases. Participation in GGCMI is voluntary and open to all groups that are able to conduct the minimum set of simulations. Different crops and management systems are included in the analyses, and output data are published in open repositories.

Rapid population growth and urbanization worldwide accelerate eco-environmental and socio-economic stress as well as adverse climatic and health impacts on urban dwellers. Atmospheric modelling research has largely been performed on a horizontal grid spacing of kilometres or larger due to a lack of understanding of the local-scale phenomena, appropriate parameterizations, and adequate modelling tools and computer resources. Urban- to hyperlocal-scale (at street or city block level) air pollution, climate change, and their impacts on population exposure and human health have increasingly received attention from both researchers and policy makers around the world. Several state-of-the-science models have recently been developed for urban- to hyperlocal-scale air pollution modelling, including the street-network model, the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) that incorporates detailed representations of gas-phase chemistry and secondary aerosol formation pathways, and the Street-in-Grid (SinG) model that dynamically combines a 3-D Eulerian chemical–transport model (CTM), Polair3D, with MUNICH. There have been increasing numbers of developers and users for MUNICH, SinG, and other similar coupled 3-D CTMs and urban canyon models for street-level air pollution modelling worldwide, such as CALIOPE-Urban, the Operational Street Pollution Model (OSPM) coupled with the Danish Eulerian Hemispheric Model (DEHM), and the Parallelized Large-Eddy Simulation Model (PALM). Meanwhile, air quality measurement data at hyperlocal scales have become increasingly available for model validation and improvement. Recognizing the urgent need for scientific advancement, pollution and exposure assessment, policy making, and public health protection at urban to hyperlocal scales, we launched a special issue on air quality research at street level in 2018, in which we have published 20 journal papers: https://acp.copernicus.org/articles/special_issue994.html. This special issue (Part II) will continue to advance scientific understanding of local-scale atmospheric phenomena, promote discussion on state-of-the-science urban as well as hyperlocal street- and city-block-level air quality research including measurements, emissions, and model development, and encourage application for complex interactions among urban air pollution, climate, and health. The special issue (Part II) is open for all submissions which address the following themes.

• 3-D Street-in-Grid (SinG) model development and application
• Urban canyon and network model development and its incorporation into 3-D CTMs
• Urban and street-level air quality modelling in support of human exposure assessment
• Impact of urban traffic emissions on air quality and human health at a street level
• Hyperlocal (street and city block scales) air quality measurement and modelling
• Urban infrastructure-induced circulation and its impact on city planning

From its origins as a punctuated phasing of a few key coupled atmosphere–ocean general circulation model experiments, the Coupled Model Intercomparison Project (CMIP) has evolved into a continuous climate Earth system modelling programme supported by design of experimental protocol, forcing dataset development, infrastructure solutions, and format requirements. These defined phases tackle key and timely climate science questions and facilitate delivery of relevant multi-model simulations through shared infrastructure for the benefit of the climate research community, climate impact and adaptation practitioners, national and international climate assessments, and society at large. In a series of invited contributions, this special issue describes the evolving design and organization of CMIP, the suite of experiments of its seventh phase (CMIP7) including the new CMIP7 Assessment Fast Track component and registered model intercomparison projects (MIPs) adhering to CMIP data standards and best-practice experimental protocol and data requests, and enabling infrastructure. The papers provide the required information to produce a consistent set of climate model simulations that can be scientifically exploited to support the World Climate Research Programme (WCRP) science priorities, which currently include Fundamental understanding of the climate system, Prediction of the near-term evolution of the climate system, Long-term response of the climate system, and Bridging climate science and society, and future climate assessments informing policy and decision-making. A separate GMD special issue is providing an overview of the various CMIP7 forcings.

Manuscripts submitted to this special issue must be solicited by the Coupled Model Intercomparison Project (CMIP) Panel. For more information, please contact Eleanor O'Rourke (cmip-ipo@esa.int).

Manuscripts documenting model intercomparison projects (MIPs) must have titles adhering to the following convention: CMIP7 Ice Sheet Model Intercomparison Project (ISMIP) experimental protocol; CMIP7 Ice Sheet Model Intercomparison Project (ISMIP) data request; or, for a combined paper, CMIP7 Ice Sheet Model Intercomparison Project (ISMIP) experimental protocol and data request.

The climate record of the last millennium holds much promise for identifying the links between forcings and responses at the global, hemispheric and regional scale. The specifications for the Paleoclimate Model Intercomparison Project Phase III (PMIP3) and the Coupled Model Intercomparison Project Phase V (CMIP5) include controlled experiments for the period 850 to 1850 CE. The implementation of those experiments, the collation and development of the climate drivers over this period, and the assessment of the model responses are the focus of this special issue of Geoscientific Model Development.

The climate crisis is one of the grand challenges of the 21st century. The increase in Earth's surface temperature, commonly known as global warming or anthropogenically induced climate change, is primarily driven by the rise in greenhouse gases (GHGs) in the atmosphere. The two most significant greenhouse gases affected by human activity are carbon dioxide (CO₂) and methane (CH₄).

While human activities such as fossil fuel combustion, oil and gas exploration, waste management, and agriculture are major sources of GHGs, natural sources also play a significant role. Extensive wetlands, for example, are the largest natural source of CH₄ globally. In wetlands, methane is produced by soil microbes and plants that metabolize under anaerobic conditions and is then released into the atmosphere through diffusion, transport via plant tissues, and gas bubble emissions. These processes make global wetlands among the most important yet least understood sources and sinks in the global methane and CO₂ budget.

A major scientific challenge in this context is distinguishing between methane emissions from natural sources and those resulting from human activities. Our understanding of these processes, their relative magnitudes, and the associated feedback mechanisms – such as increased wildfire activity, permafrost thaw, or changes in inundation patterns – is still insufficient to fully meet the needs of scientists and policymakers in predicting and mitigating climate warming.

To enhance our understanding of greenhouse gas budgets, a series of airborne measurement campaigns, known as CoMet (Carbon Dioxide and Methane Mission), have been conducted using the unique capabilities of the German research aircraft HALO. The CoMet campaigns integrate active airborne remote sensing measurements with lasers, passive remote sensing with spectrometers and solar radiation, and advanced in situ greenhouse gas concentration measurements, alongside an extensive suite of meteorological parameters. These observations are further supported by extensive modelling activities that also contribute to validating existing GHG satellite data and preparing for the next generation of such missions.

The first CoMet campaign took place in 2018, and its findings were published in a special inter-journal issue of AMT/ACP/GMD. The follow-up campaign, CoMet 2.0 Arctic (https://comet2arctic.de), was successfully conducted during a 6-week intensive operation period in August and September 2022 in Canada. The research flights focused on greenhouse gas emissions from boreal wetlands, permafrost areas in the Canadian Arctic, and wildfires, as well as anthropogenic sources like oil, gas, and coal extraction sites and landfills (in Canada and, during a test flight, in Spain). This campaign provided a valuable dataset for understanding methane and carbon dioxide cycles, particularly at high northern latitudes.

CoMet 2.0 Arctic is also part of the transatlantic AMPAC (Arctic Methane and Permafrost Challenge) initiative, a collaborative effort between NASA and ESA that fosters cooperation among US, Canadian, and European research institutes in this crucial area of research.

The special issue is open to all contributions that fit the topic from participants of the CoMet 2.0 Arctic field mission, the AMPAC community, and associated research partners.

CMIP5 represents the most ambitious and computer-intensive model inter-comparison project ever attempted. Integrating a new generation of Earth system models and sharing the model results with a broad community has brought with it many significant technical challenges, along with new community-wide efforts to provide the necessary software infrastructure. This special issue will focus on the software that supports the scientific enterprise for CMIP5, including: couplers and coupling frameworks for Earth system models; the Common Information Model and Controlled Vocabulary for describing models and data; The development of the Earth System Grid Federation; the development of new portals for providing data access to different end-user communities; the scholarly publishing of datasets, and studies of the software development and testing processes used for the CMIP5 models. We especially welcome papers that offer comparative studies of the software approaches taken by different groups, and lessons learnt from community efforts to create shareable software components and frameworks.

The natural and anthropogenic climate drivers that impact Earth’s radiation balance, influencing climate states and forcing climate change are termed climate forcing agents. Globally representative forcing estimates are needed to drive Earth system models to simulate past and project future climate states. The Coupled Model Intercomparison Project (CMIP) Forcing Task Team aims to identify, develop, document, and deliver forcings for next-generation models participating in the seventh phase of CMIP (CMIP7). This next phase is likely to be a core contribution to the IPCC seventh assessment cycle (AR7). The special issue welcomes papers documenting forcing data development and evaluation, along with those describing CMIP7 forcing characteristics (in contrast to previous versions). We also invite papers that quantify and assess uncertainties in the spatial and temporal forcing distributions and the influence of forcing on the evolution of climate states across Earth system model configurations.

This special issue describes efforts establishing high-resolution regional ocean and biogeochemical modelling capabilities for Modular Ocean Model 6 (MOM6) and selected initial applications. MOM is amongst the most widely used ocean models for global climate and earth system applications, with a lineage of scientific contributions exceeding 50 years. MOM6 represents an ambitious evolution of previous MOM formulations, embracing numerous recent modelling advances and an open development approach. MOM6 and its associated biogeochemical components have been successfully deployed for the Sixth Coupled Model Intercomparison Project (CMIP6) and other international global climate and ocean prediction efforts. The resolution and regional optimality of global simulations, however, are inevitably limited by the computational, forcing, and parameterization demands of global climate-scale simulations. Ocean modelling frameworks capable of simulating and connecting physical, biogeochemical, and ecosystem processes from ocean basins to coasts and estuaries are needed to understand the role of oceans in global change and to anticipate global change impacts on marine ecosystems and coastal communities. Development of robust regional modelling capabilities for MOM6 (i.e. regional MOM6) creates such a framework, but the extension of MOM6 to high-resolution regional applications presents many challenges.

The papers in this collection present the overall design and implementation of regional MOM6, describe new parameterizations intended for regional applications, present a first generation of regional MOM6 configurations from across the global ocean, and offer select initial applications in ocean science. Advances in horizontal grid generation and boundary condition formulation are highlighted, including those enabling a more seamless transmission of physical and biogeochemical information from global to regional scales and those required to handle flexible Lagrangian vertical coordinates. The robustness of physical and biogeochemical configurations and parameterizations – many of which were developed for global applications – is explored in higher-resolution implementations spanning environments from the Arctic to equatorial waters. Analysis of tradeoffs between model skill and computational cost highlights algorithmic improvements critical for producing decision-relevant ensembles that span a range of ocean futures. The collected works provide a foundation for the expanded application of regional MOM6 to understand and predict ocean conditions across scales.

This is a traditional style special issue open to all papers within the topic. We anticipate that contributions will be primarily to GMD initially but that there will be a growing number of applications suitable for OS once the core development papers have been published. The indefinite ending date will allow for a greater number of initial applications to be published in OS and enable eventual documentation of generational updates planned for some configurations.

Through their interaction with solar and thermal infrared radiation, clouds and aerosols have been implicated as two of the greatest sources of uncertainty in climate projections. The EarthCARE (Earth Cloud, Aerosol and Radiation Explorer) satellite is a joint ESA–JAXA mission designed to provide key new information to tackle this crucial challenge. Launched on 28 May 2024, it carries a Doppler cloud profiling radar (CPR), a high-spectral-resolution atmospheric lidar (ATLID), a multi-spectral imager (MSI), and a three-view broadband radiometer (BBR). CPR is the first radar in space that can measure how fast cloud and precipitation particles are falling in the atmosphere or rising in the cores of thunderstorms, while the ability of ATLID to separately measure the backscatter of particles and air molecules enables it to retrieve the all-important profile of the cloud and aerosol extinction coefficient without having to make any assumption regarding the scattering properties of the particles. A large number of cloud, aerosol, precipitation, and radiation data products are being produced, some derived from individual EarthCARE instruments and others from the synergy of multiple instruments.

This inter-journal special issue (SI) is dedicated to presenting early scientific results using data from the satellite. It is open to the submission of papers that use EarthCARE data and fall into the remit of one of the three journals participating in the SI: Atmospheric Measurement Techniques, Atmospheric Chemistry and Physics, and Geoscientific Model Development. Topics can include, but are not limited to, the following: calibration and validation of EarthCARE data, development of new retrieval algorithms and improvement of existing algorithms, generation of new open-access datasets, improvement of the understanding of atmospheric properties and processes, evaluation of atmospheric models, assimilation of EarthCARE data into weather forecast and air quality models, and combination of EarthCARE with other datasets to estimate climate trends.

In April 2017, the Senate of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) established the Priority Programme “Polarimetric Radar Observations meet Atmospheric Modelling (PROM)” (SPP 2115). The programme is designed to run for 6 years and is now in the third funding year. The overall motivation of the SPP PROM is a better understanding and representation of cloud and precipitation processes in numerical weather prediction and climate models. Since 2015 the whole atmosphere over Germany has been monitored by 17 state-of-the-art polarimetric Doppler weather radar observations suitable to challenge the representation of cloud and precipitation processes in atmospheric models. Data assimilation merges observations and models for state estimation as a prerequisite for prediction and can be regarded as a smart interpolation between observations while exploiting the physical consistency of atmospheric models as mathematical constraints. However, considerable knowledge gaps exist both in radar polarimetry and atmospheric models, which impede the full exploitation of the triangle radar-polarimetry–atmospheric-models–data-assimilation. Objectives of SPP PROM and thus the envisioned publications within the special issue are (1) the exploitation of radar polarimetry for quantitative process detection in precipitating clouds and for model evaluation, (2) the improvement of cloud and precipitation schemes in atmospheric models based on process fingerprints detectable in polarimetric observations, (3) monitoring of the energy budget evolution due to phase changes in the cloudy, precipitating atmosphere for a better understanding of its dynamics, (4) the generation of precipitation system analyses by the assimilation of polarimetric radar observations into atmospheric models for weather forecasting, and (5) radar-based detection of the initiation of convection for the improvement of thunderstorm prediction.

This special issue groups together documentation papers for successive releases of the Met Office Unified Model (UM) Global Atmosphere (GA) and JULES Global Land (GL) configurations. GA and GL are science configurations of the UM and JULES developed for use across weather prediction and climate research timescales. Each paper presents a scientific description of the latest configuration, a fuller description of incremental changes since the previous configuration and a brief summary of their performance.

We invite original research, reviews, and case studies that focus on atmospheric greenhouse gas (GHG) monitoring, emission estimates, and mitigation strategies, particularly in the Asia–Pacific region.

The loss of mass from glaciers, ice caps, and polar ice sheets has accelerated over the last 3 decades as a result of climate change. This has made land ice the major contributor to sea level rise and the main cause of its acceleration. However, the evolution of the land-based cryosphere over the course of the 21st century and beyond adds considerable uncertainties to sea level rise projections, particularly if instability mechanisms are triggered, leading to rapid retreat of marine basins in Antarctica. Critical knowledge gaps pose challenges for predicting the land ice response to the evolution of climate and the resulting impact on sea level, from cryospheric process understanding, ice sheet and glacier modelling, and coupling with the atmosphere and ocean to bridging the gap with sea level and coastal-impact sciences. This special issue includes contributions related to the following:

• Earth observations that help to constrain glacier and ice sheet surface conditions, dynamics, or mass loss;
• theoretical or numerical modelling of cryospheric processes or coupling with the ocean and atmosphere;
• standalone or coupled projections of ice surface mass balance;
• Arctic and Antarctic ocean conditions promoting and/or responding to ice sheet loss;
• glacier or ice sheet dynamics and mass balance;
• approaches to analysing multi-model ensembles or computing global and regional sea level rise projections;
• coastal impacts of sea level rise and climate change, adaptation needs, and related climate services.

The Joint UK Land Environment Simulator (JULES) is a process-based, community model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. JULES-crop is a parameterisation of crops within JULES which was developed with the dual aim of being able to simulate the impact of weather and climate on crop productivity and the impact that croplands have on weather and climate. This ongoing special issue collects together papers on model development, evaluation and application of JULES-crop.

The Joint UK Land Environment Simulator (JULES) is a process-based community model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Configurations of JULES underpin important science applications including the Earth system, global land, hydrology, UK environmental prediction and climate impact modelling. This indefinite special issue covers all publications covering JULES model development, evaluation and benchmarking; the documentation of the code includes schemes and parameterisations. Also included are papers covering the major scientific configurations of JULES that should be a starting point for model application and development. This special issue supports the information available through the JULES code repository (https://code.metoffice.gov.uk/trac/jules). Licences are available here http://jules-lsm.github.io/access_req/JULES_Licence.pdf.

Mercury (Hg) is a chemical pollutant of human health concern worldwide; a consequence of anthropogenic activities; and the focus of the Minamata Convention on Mercury (MC; https://minamataconvention.org/en), an international treaty to protect human health and the environment from the adverse effects of mercury. The MC entered into force on 16 August 2017 and committed to limiting the use and environmental release of mercury. Also, the 1998 Protocol on Heavy Metals of the 1979 Convention on Long-Range Transboundary Air Pollution (LRTAP) commits parties to mitigating emissions of mercury (as well as cadmium and lead) from a variety of point sources and provides guidance on mitigating emissions associated with heavy metal use in manufactured products. The MC framework requires an evaluation of the effectiveness of its measures in meeting the objectives beginning no later than 6 years after the convention’s entry into force and periodically thereafter. The Protocol on Heavy Metals requires a periodic review of the progress towards meeting the obligations in the protocol and the sufficiency and effectiveness of those obligations and an evaluation of whether additional emission reductions are warranted.

This multi-journal special issue (SI) is intended to develop the required information that can be scientifically exploited to address key policy questions of the conventions: (1) what are the contributions of anthropogenic emissions and releases and other Hg sources to current Hg levels observed in air, biota, humans, and other media? (2) How have these contribution levels changed over time and over the timeline of the convention? (3) How do the contribution levels and their trends vary geographically at the global scale? (4) What are the contributions of anthropogenic emissions and releases and other drivers to the temporal trends in observed Hg levels across global regions? (5) How are observed Hg levels expected to change in the future?

The special issue aims at collecting relevant research advances arising from the design, implementation, and results of the Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP) and from the scientific community on all aspects of biogeochemical mercury cycling, including primary and secondary emissions, observations, process studies, and single to multi-compartmental and statistical model development and application. A challenge of analysing the fate of emitted mercury is that it can recycle between the atmosphere, land, and ocean, and as a result, past and present emissions can continue to affect the environment on timescales of decades to centuries. MCHgMAP is an ensemble modelling initiative developed to inform the effectiveness of evaluations of the MC and LRTAP, utilizing a coordinated modelling approach between single-medium (atmosphere, land, and ocean) and multi-media mercury models to consistently simulate the changing global and regional environmental Hg cycling and analyse its drivers. The SI includes an overview paper on MCHgMAP, describing its scientific background and design (an important and crucial preparatory stage), which will be referenced by the individual papers on this project that follow.

For this SI we welcome manuscripts on activities such as MIIPs – Model Intercomparison and Improvement Projects that target long-standing issues in the representation of small-scale processes in numerical weather prediction and climate models. The initiatives may have been taken during the 10-year Polar Prediction Project (PPP) that finished at the end of 2022 or during the Polar Coupled Analysis and Prediction for Services (PCAPS) both part of the WMO World Weather Research Program. These programs suggest an emphasis on processes that are especially important for the polar regions, but contributions that are relevant and important for model performance in other regions of the world are also welcome. Specific targets are the representation of stably stratified boundary layers, mixed-phase clouds and atmospheric coupling with snow and or ice-covered surfaces, sea-ice, ocean mixing etc.

The intention of this SI is to publish results from MIIPs that establish new and improved workflows to facilitate a more efficient path to improved process representation. This includes research-grade observations that are packaged in an easy-to-use format which combine high-frequency observations of the surface and the atmosphere above to be able to directly compare with the parameterizations used in models using time-step data. The Merged Data File (MDF) format that is defined for both observations and model output come with a series of tools that is transferable between models and observational data collections for both file production and analysis. The SI especially welcome contributions that build on, or further develop the MDF concept including new variables, types of data, sites or new analysis tools such as process-oriented diagnostics or insights in models using the targeted files.

Geoscience model infrastructure provides architecture and services for building physics-based numerical models and combining multiple models into a coupled system. Examples of model infrastructure are software libraries and frameworks that provide data structures and functions for parallel data transfer and grid interpolation, define a common interface for model components, manage a model's control flow, abstract details of parallel programming, or provide supporting capabilities such as configuration management and file I/O. The special issue of GMD is dedicated to exploring all aspects of model infrastructure integration and interoperability. Model infrastructure integration is the software engineering process of adopting an infrastructure package into a numerical model's codebase, to address new scientific requirements, enable interoperability with other models, or to improve a model's performance. Model infrastructure interoperability is required whenever multiple infrastructure packages must interact in some way in a coupled system, for example, to couple model components that originate from different scientific communities into a single cohesive system. Topics of interest for this issue include but are not limited to the following: the design and implementation of geoscience model infrastructure software; experience reports on integrating infrastructure into models; modelling systems that span scientific communities; framework interoperability, metadata and semantic mediation; performance on emerging hardware platforms; configuration and build management; and tools that support infrastructure integration, code refactoring, verification, or debugging.

NEMO (Nucleus for European Modelling of the Ocean) is a state-of-the-art modelling framework for oceanographic research, operational oceanography seasonal forecast and climate studies. The NEMO components are NEMO-OPA (the "blue" ocean, modelling the ocean dynamics and solving the primitive equations); NEMO-LIM (the "white ocean" for modelling sea-ice), and NEMO-TOP (the "green ocean" for modelling biogeochemistry). NEMO also includes grid refinement software (AGRIF) and an assimilation component (linear-tangent NEMO-TAM, Observational operators NEMO-OBS, and increment NEMO-ASM). The "blue ocean" component is fundamental to all users. NEMO can also be interfaced to a number of other components such as atmosphere models or alternative other models of sea-ice or biogeochemistry, to enable Earth system modelling.

This Special Issue aims to collect technical and scientific manuscripts dealing with evaluation of model skill and performance as well as development of NEMO components. Submitted manuscripts can cover a wide variety of topics, including process studies, new parameterizations, implementation of new model features and new NEMO configurations. The main scope is to collect relevant and state of the art manuscripts to provide the NEMO users with a single portal to search, discover and understand about the NEMO modelling framework potential and evolution and submit their contributions.

Constraining the circulation in general circulation models by nudging the model variables toward reanalysis provides a rather powerful tool for investigating the sensitivities of predictions and simulations to specific processes or phenomena and enables the impact of model biases to be better quantified. A shared methodology for applying nudging to stratospheric variables has been developed by the World Climate Research Programme (WCRP) Stratosphere–troposphere Process And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi) and Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) activities. This methodology involves nudging (relaxing) only the zonal mean, while atmospheric waves are allowed to evolve freely, though publications that adopt other nudging methodologies or that explore sensitivity to the nudging methodology are encouraged to submit. For SNAPSI the nudging is applied throughout the stratosphere, whereas QBOi applies nudging to a localized region of the equatorial stratosphere. The reliability and robustness of the conclusions obtained from this new approach are further enhanced by the use of coordinated multi-model experiments.

The purpose of the proposed special issue is to provide a common location for reporting results from the SNAPSI and QBOi coordinated experiments utilizing stratospheric nudging, along with results from other related studies that nudge the atmosphere, whether nudging just the zonal mean or the full field. A number of modelling centres have now carried out the SNAPSI and QBOi experiments. The special issue would collect papers analysing these datasets that have been produced by participating modelling centres.

The SNAPSI experiments are designed to study the role of sudden stratospheric warmings (SSWs) in surface predictability; they are hindcast-type experiments, specifying 45-day runs covering three recent SSW events, with a large ensemble size of 50–100 members for each case. Analysis topics include the role of stratospheric variability in surface extremes and predictability and stratosphere–troposphere coupling mechanisms. The QBOi experiments are designed to study the impact of biases in the quasi-biennial oscillation (QBO) on QBO teleconnections and the forcing of the QBO; they are climate-type experiments, specifying 40-year runs with one to three ensemble members. Analysis topics include the QBO teleconnections with the stratospheric polar vortex and the relationship between the QBO and Madden–Julian oscillation (MJO). Analysis of both sets of coordinated experiments, SNAPSI and QBOi, is currently in progress, with papers expected to be submitted in the coming 1–2 years.

The Australian Community Climate and Earth System Simulator, ACCESS, is Australia’s national modelling system for all timescales from weather forecasting to climate projections. ACCESS is a family of related models, configured for specific applications, to meet operational and research needs. ACCESS is built from core component models: the UK Met Office Unified Model (UM) for the atmosphere, the Community Atmosphere Biosphere Land Exchange (CABLE) model for the land, the US NOAA/GFDL Modular Ocean Model (MOM) for the ocean and the LANL CICE model for sea ice. Additional modules support biogeochemistry and atmospheric chemistry. Different ACCESS model configurations may use a subset of the core models for atmosphere-only or ocean-only simulations or may replace component models to meet the needs of a specific application. This special issue brings together papers that describe ACCESS model configurations and code development, as well as papers that evaluate the performance of the model across any ACCESS application.

The CSIRO Mk3L climate system model is a computationally-efficient coupled general circulation model, designed primarily for the study of climate variability and change on millennial timescales. The model distribution is freely available to the research community. This Special Issue allows the history and evolution of Mk3L to be comprehensively documented within a single issue of a journal. Papers are welcome which describe and evaluate components of the model, and which describe and evaluate subsequent enhancements to the modelling system. The issue is also intended for papers which document specific experiments, particularly those which contribute towards Model Intercomparison Projects.

The Canadian Earth System Model, CanESM, is a global coupled Earth System Model designed to simulate climate variability and change on timescales from seasons to centuries. CanESM is developed at the Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, with inputs from other government and university stakeholders. A significant update to the model, CanESM5, has been developed for inclusion in the upcoming Coupled Model Intercomparison Project Phase 6. Beyond CMIP6, the new version of the model will provide an updated tool for climate science applications at CCCma and within Canada and will be submitted for possible integration into the operational Canadian Seasonal to Interseasonal Prediction System (CanSIPS). CanESM5 consists of the Canadian atmospheric model (CanAM) with an embedded land surface scheme and terrestrial biogeochemistry (CLASS-CTEM) and an off-the-shelf but customized ocean model (CanNEMO), which includes sea-ice and Canadian-developed ocean biogeochemistry modules (CMOC and CanOE). The components communicate through a new custom coupler, CanCPL. This special issue hosts the documentation and model evaluation papers for CanESM5.

FAMOUS is climate model based on the widely used "HadCM3" atmosphere–ocean general circulation code, a version of the UK Met Office Unified Model. Run at a lower resolution than HadCM3, its computational requirements make it suitable for large ensembles and millennial-scale climate simulations. This ongoing special issue collects technical documentation and evaluations of the model climatology as FAMOUS is developed and coupled to models of other Earth system components.

This special issue gathers together papers documenting the development of the Firedrake system, and geoscientific models built on Firedrake.

Firedrake provides a model development system which is both high productivity and high performance. Users write high-level code in Python describing the mathematical formulation of a model. The low-level, high-performance, parallel implementation of the algorithm is then automatically generated by a sequence of domain-specific compilers. The user writes maths and gets simulation. Firedrake provides users with a vast range of finite element discretisations, including the compatible finite-element methods which accurately represent the critical force balances in large-scale geoscientific problems. Other important features for the geoscientific user include curved elements and layered meshes, which are key to accurate atmosphere and ocean modelling.

The Lagrangian particle dispersion model FLEXPART was originally designed for calculating the long-range and mesoscale dispersion of air pollutants from point sources, such as after an accident in a nuclear power plant. The model has now evolved into a comprehensive tool for atmospheric transport modelling and analysis. Its application fields are extended to a range of atmospheric transport processes for both atmospheric gases and aerosols, e.g. greenhouse gases, ozone depletion substances, short-lived climate forces like black carbon, volcanic ash and gases as well as studies of the water cycle. It supports ECMWF, NCEP, mesoscale (WRF) and climate (NorESM, CAM) wind fields in both forward and backwards modes. FLEXTPART is open source (https://www.flexpart.eu).

Loop is an open-source integrated and interoperable platform enabling 3D stochastic geological modelling. This special issue groups contributions to the Loop platform in the form of new algorithmic developments and applications. Contributions are open to anyone using, developing, or contributing to the Loop platform.

This special issue is a collection of subsequent extensions and developments of the LPJmL model as well as model evaluation papers. The idea is to have collected in one place all the development stages of the LPJmL model that are described (and will continue to be described) in individual GMD papers.

The Modular Earth Submodel System (MESSy) is a multi-institutional project providing a strategy and the software for developing Earth System Models (ESMs) with highly flexible complexity.

The strategy follows a bottom-up approach, meaning that the various processes and diagnostic tools are implemented as so-called submodels, which are technically independent of each other and strictly separated from the underlying technical model infrastructure, such as memory management, input/output, flow-control, etc.

The MESSy software provides generalized interfaces for the standardized control and interconnection (coupling) of these submodels.

The present time-unlimited Special Issue hosts scientific and technical documentation and evaluation manuscripts concerned with the Modular Earth Submodel System and the models build upon it. Moreover, it comprises manuscripts about scientific applications involving these models.

The Norwegian Earth System Model (NorESM) is a global, coupled model system for the physical climate system, which can be run with various degrees of interactions with biogeochemical processes in the earth system. NorESM is developed as a nationally coordinated effort in Norway, but important parts of the model code are imported from the Community Climate System Model (CCSM) and Community Earth System Model (CESM) projects operated at NCAR on behalf of UCAR in the USA.

The NorESM publications in this special issue address a range of NorESM versions. The first set of model versions delivered results to CMIP5. NorESM1-M is run concentration-driven for greenhouse gases (GHGs) and is based on CCSM4 (released 1 April 2010), while NorESM1-ME can be run emission-driven for GHGs and is based on CESM1 (released 1 July 2010). A low-resolution version, NorESM1-L, was developed mainly for paleo-climate simulations. New versions of NorESM are underway: NorESM1.X, where X indicates updates of the NorESM1 versions, and NorESM2, which is intended to contribute to CMIP6. Further versions will follow thereafter. NorESM includes the following: its own developed code for chemistry–aerosol–cloud–radiation interactions (CAM-Oslo) and enhancements of the dynamics/physics of the atmospheric module; alternative parameterization of surface turbulent fluxes; an isopycnic coordinate ocean model originating from the Miami Isopycnic Coordinate Ocean Model (MICOM) but developed further; and the HAMburg Ocean Carbon Cycle (HAMOCC) model developed at the Max Plank Institute for Meteorology, Hamburg and adapted to the isopycnic coordinate ocean model framework.

Papers developed for full validation (CMIP-DECK) or more specific evaluation of the NorESM versions and further developments of these are welcome in this special issue. Authors intending to contribute papers to this special issue should contact the coordinators (Mats Bentsen and Michael Schulz), e.g., to ensure the consistency of version names and numbers.

SimSphere is a one-dimensional soil–vegetation–atmosphere transfer model devoted to the study of land surface interactions of the Earth’s system. Since its early development, the model has become highly variable in its application use.

Apart from its use as an educational tool at several universities worldwide, SimSphere is used in a number of research studies related to the examination of hypothetical scenarios examining land surface processes and feedbacks. It is also used synergistically with Earth observation (EO) data to retrieve spatiotemporal estimates of energy fluxes and surface soil moisture, involving exploration studies on the development of related operational products.

This special issue hosts contributions concerned with descriptions of further upgrades of SimSphere or its exploitation in any way. It comprises articles on model developments or applications involving the model; this includes – but is not limited to – studies exploring hypothetical scenario examination, model validation, sensitivity analysis and synergies of it with EO data.

Scope: The Transport Matrix Method (TMM) is a computationally efficient ``offline'' scheme for simulation of ocean biogeochemical tracers. The TMM essentially encapsulates the circulation of any ocean model, including sub-grid-scale parameterizations, as a sparse matrix, and advection-diffusion as a sequence of sparse matrix-vector products that can be efficiently carried out on modern distributed-memory computers. Simulations carried out with the TMM can potentially be orders of magnitude faster than the underlying ocean circulation model. The flexible architecture of the TMM framework also allows ``mixing and matching'' of circulations and biogeochemical models. The TMM code, various biogeochemical models, and transport matrices from different ocean models are freely available to download from https://github.com/samarkhatiwala/tmm.

The aim of this Special Issue is to bring together under one roof papers using the TMM as the underlying simulation method. This can range from manuscripts documenting various technical aspects of the TMM framework to those describing new biogeochemical models/parameterizations and their application.

The atmospheric chemistry box modeling system CAABA/MECCA is open-source code published under the GNU General Public License (GPL). The system is based on the box model CAABA (Chemistry As A Boxmodel Application). The chemistry code is provided by the sub-model MECCA (Module Efficiently Calculating the Chemistry of the Atmosphere). Additional sub-models provide the code to calculate photolysis, trajectories, isotope tagging and other features.

All papers of this special issue will undergo the regular interactive peer-review process of Geoscientific Model Development handled by members of the GMD editorial board.

This special issue gathers already-published and future papers that describe and/or apply the global water resources and use model WaterGAP.

WaterGAP (www.watergap.de) is a global freshwater model that calculates human water use as well as water flows and storage on all continents (except Antarctica), taking into account the human influence on the natural freshwater system such as climate change, water abstractions, and dams. As one of the pioneers in the field of global hydrological modelling, it supports our understanding of the global freshwater system since 1996 for historical periods and the future. The model is continuously being improved to answer scientific questions driven by societal demands. WaterGAP is applied to assess water scarcity, droughts, and floods and to quantify the human impact on, for example, groundwater, wetlands, streamflow, and sea-level rise.

iLOVECLIM is an intermediate complexity fully coupled climate Earth system model that aims at computation and understanding of the climate system on a millennial timescale. It is a code fork from the LOVECLIM climate model version 1.2. From its forerunner, iLOVECLIM retains only the physical climate components (atmosphere–ocean–terrestrial vegetation modules). It is developed further to progressively include the components necessary for multi-millennia palaeoclimate and future climate experiments. As such, iLOVECLIM is a tool designed to enhance the integration of model simulations and (palaeo-)data, with an emphasis on the simulation of isotopic tracers throughout all components of the climate system, as indicated by the i- prefix. The present, time-unlimited special issue hosts the technical documentation of the current version of iLOVECLIM as well as model evaluation manuscripts.

The purpose of this special issue is to review and report on recent advances in the design, implementation, and interpretation of ensembles in climate science. This includes theoretical, mathematical, and computational aspects, therefore bringing together contributions from mathematicians, computational scientists, model users and developers, and climate scientists alike.

Climate science, in particular climate prediction and projection, are heavily dependent on the use of Earth system models (ESMs), which are nonlinear, complex, and chaotic representations of the Earth’s spheres. As such, ESMs are susceptible to various sources of uncertainty. These include uncertainty in the initial state, parameter values, model formulation, structure, and external forcing. Ensembles have become a key tool to quantify these uncertainties and improve predictions. However, challenging questions remain regarding how to design and interpret such ensembles within the constraints of limited computational power and the lack of a rigorous framework for their design. Therefore, this special issue will be a valuable resource to climate scientists working on both theoretical and practical aspects of prediction ahead of Phase 7 of the Coupled Model Intercomparison Project (CMIP7) and future assessments.

This issue arises from the minisymposium Theoretical and Computational Aspects of Ensemble Design and Interpretation in Climate Science and Modelling hosted during the SIAM Conference on Mathematical & Computational Issues in Geosciences in Bergen, Norway (19–22 June 2023). It will feature works by participants as well as external contributions.

Through their interaction with solar and thermal infrared radiation, clouds and aerosols have been implicated as two of the greatest sources of uncertainty in climate projections. The EarthCARE (Earth Cloud, Aerosol and Radiation Explorer) satellite is a joint ESA–JAXA mission designed to provide key new information to tackle this crucial challenge. Launched on 28 May 2024, it carries a Doppler cloud profiling radar (CPR), a high-spectral-resolution atmospheric lidar (ATLID), a multi-spectral imager (MSI), and a three-view broadband radiometer (BBR). CPR is the first radar in space that can measure how fast cloud and precipitation particles are falling in the atmosphere or rising in the cores of thunderstorms, while the ability of ATLID to separately measure the backscatter of particles and air molecules enables it to retrieve the all-important profile of the cloud and aerosol extinction coefficient without having to make any assumption regarding the scattering properties of the particles. A large number of cloud, aerosol, precipitation, and radiation data products are being produced, some derived from individual EarthCARE instruments and others from the synergy of multiple instruments.

This inter-journal special issue (SI) is dedicated to presenting early scientific results using data from the satellite. It is open to the submission of papers that use EarthCARE data and fall into the remit of one of the three journals participating in the SI: Atmospheric Measurement Techniques, Atmospheric Chemistry and Physics, and Geoscientific Model Development. Topics can include, but are not limited to, the following: calibration and validation of EarthCARE data, development of new retrieval algorithms and improvement of existing algorithms, generation of new open-access datasets, improvement of the understanding of atmospheric properties and processes, evaluation of atmospheric models, assimilation of EarthCARE data into weather forecast and air quality models, and combination of EarthCARE with other datasets to estimate climate trends.

We invite original research, reviews, and case studies that focus on atmospheric greenhouse gas (GHG) monitoring, emission estimates, and mitigation strategies, particularly in the Asia–Pacific region.

The climate crisis is one of the grand challenges of the 21st century. The increase in Earth's surface temperature, commonly known as global warming or anthropogenically induced climate change, is primarily driven by the rise in greenhouse gases (GHGs) in the atmosphere. The two most significant greenhouse gases affected by human activity are carbon dioxide (CO₂) and methane (CH₄).

While human activities such as fossil fuel combustion, oil and gas exploration, waste management, and agriculture are major sources of GHGs, natural sources also play a significant role. Extensive wetlands, for example, are the largest natural source of CH₄ globally. In wetlands, methane is produced by soil microbes and plants that metabolize under anaerobic conditions and is then released into the atmosphere through diffusion, transport via plant tissues, and gas bubble emissions. These processes make global wetlands among the most important yet least understood sources and sinks in the global methane and CO₂ budget.

A major scientific challenge in this context is distinguishing between methane emissions from natural sources and those resulting from human activities. Our understanding of these processes, their relative magnitudes, and the associated feedback mechanisms – such as increased wildfire activity, permafrost thaw, or changes in inundation patterns – is still insufficient to fully meet the needs of scientists and policymakers in predicting and mitigating climate warming.

To enhance our understanding of greenhouse gas budgets, a series of airborne measurement campaigns, known as CoMet (Carbon Dioxide and Methane Mission), have been conducted using the unique capabilities of the German research aircraft HALO. The CoMet campaigns integrate active airborne remote sensing measurements with lasers, passive remote sensing with spectrometers and solar radiation, and advanced in situ greenhouse gas concentration measurements, alongside an extensive suite of meteorological parameters. These observations are further supported by extensive modelling activities that also contribute to validating existing GHG satellite data and preparing for the next generation of such missions.

The first CoMet campaign took place in 2018, and its findings were published in a special inter-journal issue of AMT/ACP/GMD. The follow-up campaign, CoMet 2.0 Arctic (https://comet2arctic.de), was successfully conducted during a 6-week intensive operation period in August and September 2022 in Canada. The research flights focused on greenhouse gas emissions from boreal wetlands, permafrost areas in the Canadian Arctic, and wildfires, as well as anthropogenic sources like oil, gas, and coal extraction sites and landfills (in Canada and, during a test flight, in Spain). This campaign provided a valuable dataset for understanding methane and carbon dioxide cycles, particularly at high northern latitudes.

CoMet 2.0 Arctic is also part of the transatlantic AMPAC (Arctic Methane and Permafrost Challenge) initiative, a collaborative effort between NASA and ESA that fosters cooperation among US, Canadian, and European research institutes in this crucial area of research.

The special issue is open to all contributions that fit the topic from participants of the CoMet 2.0 Arctic field mission, the AMPAC community, and associated research partners.

The aim of this special issue in Geoscientific Model Development is to collate contributions from the EGU General Assembly 2024, specifically the session titled "Advances in Numerical Modelling of Geological Processes". This session explores the complex multi-physics nature of geological processes, which often involve the interaction of different physical phenomena. Such interactions can generate nonlinear responses, leading to the spontaneous localization of flow and deformation.

In addition to physics-based models, geological and geophysical datasets serve as another vital source of information, while recent technological advancements have significantly enhanced spatial and temporal resolutions.

Understanding the interplay between different physical processes necessitates the development of advanced numerical tools and methodologies. Effective new models should utilize various types of parallel hardware efficiently and in a backend-agnostic manner. These models must also balance conciseness with the capability to bridge portability and performance, thereby addressing the challenge of the two-language barrier. Furthermore, new applications that incorporate high-quality data into physics-based predictive numerical simulations are crucial. These applications facilitate workflows that further refine key unknown parameters within the models. The integration of innovative inversion strategies, which connect forward dynamic models with observable data, and the combination of partial differential equation (PDE) solvers with machine learning (ML) through differentiable programming, represent significant areas of research within this field.

We invite contributions from the following two complementary themes also featured in the EGU session:

1. The first of these themes entails computational advances associated with alternative spatial and/or temporal discretization for existing forward/inverse models, scalable high-performance computing implementations of new and existing methodologies (GPUs/multi-core), solver and preconditioner developments, combining PDEs with AI- or ML-based approaches (physics-informed ML), automatic differentiation and differentiable programming, and significant performance increases by using new algorithms or code and methodology comparisons (benchmarks).
2. The second area of interest comprises physics advances associated with the development of PDEs to describe geological processes, inversion strategies and adjoint-based modelling, numerical model validation through comparison with observables (data), scientific discovery enabled by 2D and 3D modelling, and utilization of coupled models to explore nonlinear interactions.

From its origins as a punctuated phasing of a few key coupled atmosphere–ocean general circulation model experiments, the Coupled Model Intercomparison Project (CMIP) has evolved into a continuous climate Earth system modelling programme supported by design of experimental protocol, forcing dataset development, infrastructure solutions, and format requirements. These defined phases tackle key and timely climate science questions and facilitate delivery of relevant multi-model simulations through shared infrastructure for the benefit of the climate research community, climate impact and adaptation practitioners, national and international climate assessments, and society at large. In a series of invited contributions, this special issue describes the evolving design and organization of CMIP, the suite of experiments of its seventh phase (CMIP7) including the new CMIP7 Assessment Fast Track component and registered model intercomparison projects (MIPs) adhering to CMIP data standards and best-practice experimental protocol and data requests, and enabling infrastructure. The papers provide the required information to produce a consistent set of climate model simulations that can be scientifically exploited to support the World Climate Research Programme (WCRP) science priorities, which currently include Fundamental understanding of the climate system, Prediction of the near-term evolution of the climate system, Long-term response of the climate system, and Bridging climate science and society, and future climate assessments informing policy and decision-making. A separate GMD special issue is providing an overview of the various CMIP7 forcings.

Manuscripts submitted to this special issue must be solicited by the Coupled Model Intercomparison Project (CMIP) Panel. For more information, please contact Eleanor O'Rourke (cmip-ipo@esa.int).

Manuscripts documenting model intercomparison projects (MIPs) must have titles adhering to the following convention: CMIP7 Ice Sheet Model Intercomparison Project (ISMIP) experimental protocol; CMIP7 Ice Sheet Model Intercomparison Project (ISMIP) data request; or, for a combined paper, CMIP7 Ice Sheet Model Intercomparison Project (ISMIP) experimental protocol and data request.

The natural and anthropogenic climate drivers that impact Earth’s radiation balance, influencing climate states and forcing climate change are termed climate forcing agents. Globally representative forcing estimates are needed to drive Earth system models to simulate past and project future climate states. The Coupled Model Intercomparison Project (CMIP) Forcing Task Team aims to identify, develop, document, and deliver forcings for next-generation models participating in the seventh phase of CMIP (CMIP7). This next phase is likely to be a core contribution to the IPCC seventh assessment cycle (AR7). The special issue welcomes papers documenting forcing data development and evaluation, along with those describing CMIP7 forcing characteristics (in contrast to previous versions). We also invite papers that quantify and assess uncertainties in the spatial and temporal forcing distributions and the influence of forcing on the evolution of climate states across Earth system model configurations.

This special issue gathers already-published and future papers that describe and/or apply the global water resources and use model WaterGAP.

WaterGAP (www.watergap.de) is a global freshwater model that calculates human water use as well as water flows and storage on all continents (except Antarctica), taking into account the human influence on the natural freshwater system such as climate change, water abstractions, and dams. As one of the pioneers in the field of global hydrological modelling, it supports our understanding of the global freshwater system since 1996 for historical periods and the future. The model is continuously being improved to answer scientific questions driven by societal demands. WaterGAP is applied to assess water scarcity, droughts, and floods and to quantify the human impact on, for example, groundwater, wetlands, streamflow, and sea-level rise.

Constraining the circulation in general circulation models by nudging the model variables toward reanalysis provides a rather powerful tool for investigating the sensitivities of predictions and simulations to specific processes or phenomena and enables the impact of model biases to be better quantified. A shared methodology for applying nudging to stratospheric variables has been developed by the World Climate Research Programme (WCRP) Stratosphere–troposphere Process And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi) and Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) activities. This methodology involves nudging (relaxing) only the zonal mean, while atmospheric waves are allowed to evolve freely, though publications that adopt other nudging methodologies or that explore sensitivity to the nudging methodology are encouraged to submit. For SNAPSI the nudging is applied throughout the stratosphere, whereas QBOi applies nudging to a localized region of the equatorial stratosphere. The reliability and robustness of the conclusions obtained from this new approach are further enhanced by the use of coordinated multi-model experiments.

The purpose of the proposed special issue is to provide a common location for reporting results from the SNAPSI and QBOi coordinated experiments utilizing stratospheric nudging, along with results from other related studies that nudge the atmosphere, whether nudging just the zonal mean or the full field. A number of modelling centres have now carried out the SNAPSI and QBOi experiments. The special issue would collect papers analysing these datasets that have been produced by participating modelling centres.

The SNAPSI experiments are designed to study the role of sudden stratospheric warmings (SSWs) in surface predictability; they are hindcast-type experiments, specifying 45-day runs covering three recent SSW events, with a large ensemble size of 50–100 members for each case. Analysis topics include the role of stratospheric variability in surface extremes and predictability and stratosphere–troposphere coupling mechanisms. The QBOi experiments are designed to study the impact of biases in the quasi-biennial oscillation (QBO) on QBO teleconnections and the forcing of the QBO; they are climate-type experiments, specifying 40-year runs with one to three ensemble members. Analysis topics include the QBO teleconnections with the stratospheric polar vortex and the relationship between the QBO and Madden–Julian oscillation (MJO). Analysis of both sets of coordinated experiments, SNAPSI and QBOi, is currently in progress, with papers expected to be submitted in the coming 1–2 years.

Mercury (Hg) is a chemical pollutant of human health concern worldwide; a consequence of anthropogenic activities; and the focus of the Minamata Convention on Mercury (MC; https://minamataconvention.org/en), an international treaty to protect human health and the environment from the adverse effects of mercury. The MC entered into force on 16 August 2017 and committed to limiting the use and environmental release of mercury. Also, the 1998 Protocol on Heavy Metals of the 1979 Convention on Long-Range Transboundary Air Pollution (LRTAP) commits parties to mitigating emissions of mercury (as well as cadmium and lead) from a variety of point sources and provides guidance on mitigating emissions associated with heavy metal use in manufactured products. The MC framework requires an evaluation of the effectiveness of its measures in meeting the objectives beginning no later than 6 years after the convention’s entry into force and periodically thereafter. The Protocol on Heavy Metals requires a periodic review of the progress towards meeting the obligations in the protocol and the sufficiency and effectiveness of those obligations and an evaluation of whether additional emission reductions are warranted.

This multi-journal special issue (SI) is intended to develop the required information that can be scientifically exploited to address key policy questions of the conventions: (1) what are the contributions of anthropogenic emissions and releases and other Hg sources to current Hg levels observed in air, biota, humans, and other media? (2) How have these contribution levels changed over time and over the timeline of the convention? (3) How do the contribution levels and their trends vary geographically at the global scale? (4) What are the contributions of anthropogenic emissions and releases and other drivers to the temporal trends in observed Hg levels across global regions? (5) How are observed Hg levels expected to change in the future?

The special issue aims at collecting relevant research advances arising from the design, implementation, and results of the Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP) and from the scientific community on all aspects of biogeochemical mercury cycling, including primary and secondary emissions, observations, process studies, and single to multi-compartmental and statistical model development and application. A challenge of analysing the fate of emitted mercury is that it can recycle between the atmosphere, land, and ocean, and as a result, past and present emissions can continue to affect the environment on timescales of decades to centuries. MCHgMAP is an ensemble modelling initiative developed to inform the effectiveness of evaluations of the MC and LRTAP, utilizing a coordinated modelling approach between single-medium (atmosphere, land, and ocean) and multi-media mercury models to consistently simulate the changing global and regional environmental Hg cycling and analyse its drivers. The SI includes an overview paper on MCHgMAP, describing its scientific background and design (an important and crucial preparatory stage), which will be referenced by the individual papers on this project that follow.

For this SI we welcome manuscripts on activities such as MIIPs – Model Intercomparison and Improvement Projects that target long-standing issues in the representation of small-scale processes in numerical weather prediction and climate models. The initiatives may have been taken during the 10-year Polar Prediction Project (PPP) that finished at the end of 2022 or during the Polar Coupled Analysis and Prediction for Services (PCAPS) both part of the WMO World Weather Research Program. These programs suggest an emphasis on processes that are especially important for the polar regions, but contributions that are relevant and important for model performance in other regions of the world are also welcome. Specific targets are the representation of stably stratified boundary layers, mixed-phase clouds and atmospheric coupling with snow and or ice-covered surfaces, sea-ice, ocean mixing etc.

The intention of this SI is to publish results from MIIPs that establish new and improved workflows to facilitate a more efficient path to improved process representation. This includes research-grade observations that are packaged in an easy-to-use format which combine high-frequency observations of the surface and the atmosphere above to be able to directly compare with the parameterizations used in models using time-step data. The Merged Data File (MDF) format that is defined for both observations and model output come with a series of tools that is transferable between models and observational data collections for both file production and analysis. The SI especially welcome contributions that build on, or further develop the MDF concept including new variables, types of data, sites or new analysis tools such as process-oriented diagnostics or insights in models using the targeted files.

The purpose of this special issue is to review and report on recent advances in the design, implementation, and interpretation of ensembles in climate science. This includes theoretical, mathematical, and computational aspects, therefore bringing together contributions from mathematicians, computational scientists, model users and developers, and climate scientists alike.

Climate science, in particular climate prediction and projection, are heavily dependent on the use of Earth system models (ESMs), which are nonlinear, complex, and chaotic representations of the Earth’s spheres. As such, ESMs are susceptible to various sources of uncertainty. These include uncertainty in the initial state, parameter values, model formulation, structure, and external forcing. Ensembles have become a key tool to quantify these uncertainties and improve predictions. However, challenging questions remain regarding how to design and interpret such ensembles within the constraints of limited computational power and the lack of a rigorous framework for their design. Therefore, this special issue will be a valuable resource to climate scientists working on both theoretical and practical aspects of prediction ahead of Phase 7 of the Coupled Model Intercomparison Project (CMIP7) and future assessments.

This issue arises from the minisymposium Theoretical and Computational Aspects of Ensemble Design and Interpretation in Climate Science and Modelling hosted during the SIAM Conference on Mathematical & Computational Issues in Geosciences in Bergen, Norway (19–22 June 2023). It will feature works by participants as well as external contributions.

This special issue describes efforts establishing high-resolution regional ocean and biogeochemical modelling capabilities for Modular Ocean Model 6 (MOM6) and selected initial applications. MOM is amongst the most widely used ocean models for global climate and earth system applications, with a lineage of scientific contributions exceeding 50 years. MOM6 represents an ambitious evolution of previous MOM formulations, embracing numerous recent modelling advances and an open development approach. MOM6 and its associated biogeochemical components have been successfully deployed for the Sixth Coupled Model Intercomparison Project (CMIP6) and other international global climate and ocean prediction efforts. The resolution and regional optimality of global simulations, however, are inevitably limited by the computational, forcing, and parameterization demands of global climate-scale simulations. Ocean modelling frameworks capable of simulating and connecting physical, biogeochemical, and ecosystem processes from ocean basins to coasts and estuaries are needed to understand the role of oceans in global change and to anticipate global change impacts on marine ecosystems and coastal communities. Development of robust regional modelling capabilities for MOM6 (i.e. regional MOM6) creates such a framework, but the extension of MOM6 to high-resolution regional applications presents many challenges.

The papers in this collection present the overall design and implementation of regional MOM6, describe new parameterizations intended for regional applications, present a first generation of regional MOM6 configurations from across the global ocean, and offer select initial applications in ocean science. Advances in horizontal grid generation and boundary condition formulation are highlighted, including those enabling a more seamless transmission of physical and biogeochemical information from global to regional scales and those required to handle flexible Lagrangian vertical coordinates. The robustness of physical and biogeochemical configurations and parameterizations – many of which were developed for global applications – is explored in higher-resolution implementations spanning environments from the Arctic to equatorial waters. Analysis of tradeoffs between model skill and computational cost highlights algorithmic improvements critical for producing decision-relevant ensembles that span a range of ocean futures. The collected works provide a foundation for the expanded application of regional MOM6 to understand and predict ocean conditions across scales.

This is a traditional style special issue open to all papers within the topic. We anticipate that contributions will be primarily to GMD initially but that there will be a growing number of applications suitable for OS once the core development papers have been published. The indefinite ending date will allow for a greater number of initial applications to be published in OS and enable eventual documentation of generational updates planned for some configurations.

Rapid population growth and urbanization worldwide accelerate eco-environmental and socio-economic stress as well as adverse climatic and health impacts on urban dwellers. Atmospheric modelling research has largely been performed on a horizontal grid spacing of kilometres or larger due to a lack of understanding of the local-scale phenomena, appropriate parameterizations, and adequate modelling tools and computer resources. Urban- to hyperlocal-scale (at street or city block level) air pollution, climate change, and their impacts on population exposure and human health have increasingly received attention from both researchers and policy makers around the world. Several state-of-the-science models have recently been developed for urban- to hyperlocal-scale air pollution modelling, including the street-network model, the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) that incorporates detailed representations of gas-phase chemistry and secondary aerosol formation pathways, and the Street-in-Grid (SinG) model that dynamically combines a 3-D Eulerian chemical–transport model (CTM), Polair3D, with MUNICH. There have been increasing numbers of developers and users for MUNICH, SinG, and other similar coupled 3-D CTMs and urban canyon models for street-level air pollution modelling worldwide, such as CALIOPE-Urban, the Operational Street Pollution Model (OSPM) coupled with the Danish Eulerian Hemispheric Model (DEHM), and the Parallelized Large-Eddy Simulation Model (PALM). Meanwhile, air quality measurement data at hyperlocal scales have become increasingly available for model validation and improvement. Recognizing the urgent need for scientific advancement, pollution and exposure assessment, policy making, and public health protection at urban to hyperlocal scales, we launched a special issue on air quality research at street level in 2018, in which we have published 20 journal papers: https://acp.copernicus.org/articles/special_issue994.html. This special issue (Part II) will continue to advance scientific understanding of local-scale atmospheric phenomena, promote discussion on state-of-the-science urban as well as hyperlocal street- and city-block-level air quality research including measurements, emissions, and model development, and encourage application for complex interactions among urban air pollution, climate, and health. The special issue (Part II) is open for all submissions which address the following themes.

• 3-D Street-in-Grid (SinG) model development and application
• Urban canyon and network model development and its incorporation into 3-D CTMs
• Urban and street-level air quality modelling in support of human exposure assessment
• Impact of urban traffic emissions on air quality and human health at a street level
• Hyperlocal (street and city block scales) air quality measurement and modelling
• Urban infrastructure-induced circulation and its impact on city planning

In April 2017, the Senate of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) established the Priority Programme “Polarimetric Radar Observations meet Atmospheric Modelling (PROM)” (SPP 2115). The programme is designed to run for 6 years and is now in the third funding year. The overall motivation of the SPP PROM is a better understanding and representation of cloud and precipitation processes in numerical weather prediction and climate models. Since 2015 the whole atmosphere over Germany has been monitored by 17 state-of-the-art polarimetric Doppler weather radar observations suitable to challenge the representation of cloud and precipitation processes in atmospheric models. Data assimilation merges observations and models for state estimation as a prerequisite for prediction and can be regarded as a smart interpolation between observations while exploiting the physical consistency of atmospheric models as mathematical constraints. However, considerable knowledge gaps exist both in radar polarimetry and atmospheric models, which impede the full exploitation of the triangle radar-polarimetry–atmospheric-models–data-assimilation. Objectives of SPP PROM and thus the envisioned publications within the special issue are (1) the exploitation of radar polarimetry for quantitative process detection in precipitating clouds and for model evaluation, (2) the improvement of cloud and precipitation schemes in atmospheric models based on process fingerprints detectable in polarimetric observations, (3) monitoring of the energy budget evolution due to phase changes in the cloudy, precipitating atmosphere for a better understanding of its dynamics, (4) the generation of precipitation system analyses by the assimilation of polarimetric radar observations into atmospheric models for weather forecasting, and (5) radar-based detection of the initiation of convection for the improvement of thunderstorm prediction.

Loop is an open-source integrated and interoperable platform enabling 3D stochastic geological modelling. This special issue groups contributions to the Loop platform in the form of new algorithmic developments and applications. Contributions are open to anyone using, developing, or contributing to the Loop platform.

The loss of mass from glaciers, ice caps, and polar ice sheets has accelerated over the last 3 decades as a result of climate change. This has made land ice the major contributor to sea level rise and the main cause of its acceleration. However, the evolution of the land-based cryosphere over the course of the 21st century and beyond adds considerable uncertainties to sea level rise projections, particularly if instability mechanisms are triggered, leading to rapid retreat of marine basins in Antarctica. Critical knowledge gaps pose challenges for predicting the land ice response to the evolution of climate and the resulting impact on sea level, from cryospheric process understanding, ice sheet and glacier modelling, and coupling with the atmosphere and ocean to bridging the gap with sea level and coastal-impact sciences. This special issue includes contributions related to the following:

• Earth observations that help to constrain glacier and ice sheet surface conditions, dynamics, or mass loss;
• theoretical or numerical modelling of cryospheric processes or coupling with the ocean and atmosphere;
• standalone or coupled projections of ice surface mass balance;
• Arctic and Antarctic ocean conditions promoting and/or responding to ice sheet loss;
• glacier or ice sheet dynamics and mass balance;
• approaches to analysing multi-model ensembles or computing global and regional sea level rise projections;
• coastal impacts of sea level rise and climate change, adaptation needs, and related climate services.

The Agricultural Model Intercomparison and Improvement Project (AgMIP) coordinates protocol-based model intercomparison studies, analyzing model performance in order to build trust in models, identify deficiencies and strategies for model improvements, and to quantify model uncertainties. Within AgMIP, the Global Gridded Crop Model Intercomparison (GGCMI) focuses on global-scale crop model applications, development and evaluation. Several phases of GGCMI are conducted in coordination with the Intersectoral Impact Model Intercomparison (ISIMIP). In this special issue, we summarize protocol and experiment description papers, as well as model development and evaluation papers of the different GGCMI phases. Participation in GGCMI is voluntary and open to all groups that are able to conduct the minimum set of simulations. Different crops and management systems are included in the analyses, and output data are published in open repositories.

This special issue is a collection of subsequent extensions and developments of the LPJmL model as well as model evaluation papers. The idea is to have collected in one place all the development stages of the LPJmL model that are described (and will continue to be described) in individual GMD papers.

The Australian Community Climate and Earth System Simulator, ACCESS, is Australia’s national modelling system for all timescales from weather forecasting to climate projections. ACCESS is a family of related models, configured for specific applications, to meet operational and research needs. ACCESS is built from core component models: the UK Met Office Unified Model (UM) for the atmosphere, the Community Atmosphere Biosphere Land Exchange (CABLE) model for the land, the US NOAA/GFDL Modular Ocean Model (MOM) for the ocean and the LANL CICE model for sea ice. Additional modules support biogeochemistry and atmospheric chemistry. Different ACCESS model configurations may use a subset of the core models for atmosphere-only or ocean-only simulations or may replace component models to meet the needs of a specific application. This special issue brings together papers that describe ACCESS model configurations and code development, as well as papers that evaluate the performance of the model across any ACCESS application.

The atmospheric chemistry box modeling system CAABA/MECCA is open-source code published under the GNU General Public License (GPL). The system is based on the box model CAABA (Chemistry As A Boxmodel Application). The chemistry code is provided by the sub-model MECCA (Module Efficiently Calculating the Chemistry of the Atmosphere). Additional sub-models provide the code to calculate photolysis, trajectories, isotope tagging and other features.

This special issue gathers together papers documenting the development of the Firedrake system, and geoscientific models built on Firedrake.

Firedrake provides a model development system which is both high productivity and high performance. Users write high-level code in Python describing the mathematical formulation of a model. The low-level, high-performance, parallel implementation of the algorithm is then automatically generated by a sequence of domain-specific compilers. The user writes maths and gets simulation. Firedrake provides users with a vast range of finite element discretisations, including the compatible finite-element methods which accurately represent the critical force balances in large-scale geoscientific problems. Other important features for the geoscientific user include curved elements and layered meshes, which are key to accurate atmosphere and ocean modelling.

The Joint UK Land Environment Simulator (JULES) is a process-based community model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Configurations of JULES underpin important science applications including the Earth system, global land, hydrology, UK environmental prediction and climate impact modelling. This indefinite special issue covers all publications covering JULES model development, evaluation and benchmarking; the documentation of the code includes schemes and parameterisations. Also included are papers covering the major scientific configurations of JULES that should be a starting point for model application and development. This special issue supports the information available through the JULES code repository (https://code.metoffice.gov.uk/trac/jules). Licences are available here http://jules-lsm.github.io/access_req/JULES_Licence.pdf.

The Canadian Earth System Model, CanESM, is a global coupled Earth System Model designed to simulate climate variability and change on timescales from seasons to centuries. CanESM is developed at the Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, with inputs from other government and university stakeholders. A significant update to the model, CanESM5, has been developed for inclusion in the upcoming Coupled Model Intercomparison Project Phase 6. Beyond CMIP6, the new version of the model will provide an updated tool for climate science applications at CCCma and within Canada and will be submitted for possible integration into the operational Canadian Seasonal to Interseasonal Prediction System (CanSIPS). CanESM5 consists of the Canadian atmospheric model (CanAM) with an embedded land surface scheme and terrestrial biogeochemistry (CLASS-CTEM) and an off-the-shelf but customized ocean model (CanNEMO), which includes sea-ice and Canadian-developed ocean biogeochemistry modules (CMOC and CanOE). The components communicate through a new custom coupler, CanCPL. This special issue hosts the documentation and model evaluation papers for CanESM5.

Scope: The Transport Matrix Method (TMM) is a computationally efficient ``offline'' scheme for simulation of ocean biogeochemical tracers. The TMM essentially encapsulates the circulation of any ocean model, including sub-grid-scale parameterizations, as a sparse matrix, and advection-diffusion as a sequence of sparse matrix-vector products that can be efficiently carried out on modern distributed-memory computers. Simulations carried out with the TMM can potentially be orders of magnitude faster than the underlying ocean circulation model. The flexible architecture of the TMM framework also allows ``mixing and matching'' of circulations and biogeochemical models. The TMM code, various biogeochemical models, and transport matrices from different ocean models are freely available to download from https://github.com/samarkhatiwala/tmm.

The aim of this Special Issue is to bring together under one roof papers using the TMM as the underlying simulation method. This can range from manuscripts documenting various technical aspects of the TMM framework to those describing new biogeochemical models/parameterizations and their application.

The Lagrangian particle dispersion model FLEXPART was originally designed for calculating the long-range and mesoscale dispersion of air pollutants from point sources, such as after an accident in a nuclear power plant. The model has now evolved into a comprehensive tool for atmospheric transport modelling and analysis. Its application fields are extended to a range of atmospheric transport processes for both atmospheric gases and aerosols, e.g. greenhouse gases, ozone depletion substances, short-lived climate forces like black carbon, volcanic ash and gases as well as studies of the water cycle. It supports ECMWF, NCEP, mesoscale (WRF) and climate (NorESM, CAM) wind fields in both forward and backwards modes. FLEXTPART is open source (https://www.flexpart.eu).

The Joint UK Land Environment Simulator (JULES) is a process-based, community model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. JULES-crop is a parameterisation of crops within JULES which was developed with the dual aim of being able to simulate the impact of weather and climate on crop productivity and the impact that croplands have on weather and climate. This ongoing special issue collects together papers on model development, evaluation and application of JULES-crop.

SimSphere is a one-dimensional soil–vegetation–atmosphere transfer model devoted to the study of land surface interactions of the Earth’s system. Since its early development, the model has become highly variable in its application use.

Apart from its use as an educational tool at several universities worldwide, SimSphere is used in a number of research studies related to the examination of hypothetical scenarios examining land surface processes and feedbacks. It is also used synergistically with Earth observation (EO) data to retrieve spatiotemporal estimates of energy fluxes and surface soil moisture, involving exploration studies on the development of related operational products.

This special issue hosts contributions concerned with descriptions of further upgrades of SimSphere or its exploitation in any way. It comprises articles on model developments or applications involving the model; this includes – but is not limited to – studies exploring hypothetical scenario examination, model validation, sensitivity analysis and synergies of it with EO data.

Geoscience model infrastructure provides architecture and services for building physics-based numerical models and combining multiple models into a coupled system. Examples of model infrastructure are software libraries and frameworks that provide data structures and functions for parallel data transfer and grid interpolation, define a common interface for model components, manage a model's control flow, abstract details of parallel programming, or provide supporting capabilities such as configuration management and file I/O. The special issue of GMD is dedicated to exploring all aspects of model infrastructure integration and interoperability. Model infrastructure integration is the software engineering process of adopting an infrastructure package into a numerical model's codebase, to address new scientific requirements, enable interoperability with other models, or to improve a model's performance. Model infrastructure interoperability is required whenever multiple infrastructure packages must interact in some way in a coupled system, for example, to couple model components that originate from different scientific communities into a single cohesive system. Topics of interest for this issue include but are not limited to the following: the design and implementation of geoscience model infrastructure software; experience reports on integrating infrastructure into models; modelling systems that span scientific communities; framework interoperability, metadata and semantic mediation; performance on emerging hardware platforms; configuration and build management; and tools that support infrastructure integration, code refactoring, verification, or debugging.

This special issue groups together documentation papers for successive releases of the Met Office Unified Model (UM) Global Atmosphere (GA) and JULES Global Land (GL) configurations. GA and GL are science configurations of the UM and JULES developed for use across weather prediction and climate research timescales. Each paper presents a scientific description of the latest configuration, a fuller description of incremental changes since the previous configuration and a brief summary of their performance.

NEMO (Nucleus for European Modelling of the Ocean) is a state-of-the-art modelling framework for oceanographic research, operational oceanography seasonal forecast and climate studies. The NEMO components are NEMO-OPA (the "blue" ocean, modelling the ocean dynamics and solving the primitive equations); NEMO-LIM (the "white ocean" for modelling sea-ice), and NEMO-TOP (the "green ocean" for modelling biogeochemistry). NEMO also includes grid refinement software (AGRIF) and an assimilation component (linear-tangent NEMO-TAM, Observational operators NEMO-OBS, and increment NEMO-ASM). The "blue ocean" component is fundamental to all users. NEMO can also be interfaced to a number of other components such as atmosphere models or alternative other models of sea-ice or biogeochemistry, to enable Earth system modelling.

This Special Issue aims to collect technical and scientific manuscripts dealing with evaluation of model skill and performance as well as development of NEMO components. Submitted manuscripts can cover a wide variety of topics, including process studies, new parameterizations, implementation of new model features and new NEMO configurations. The main scope is to collect relevant and state of the art manuscripts to provide the NEMO users with a single portal to search, discover and understand about the NEMO modelling framework potential and evolution and submit their contributions.

iLOVECLIM is an intermediate complexity fully coupled climate Earth system model that aims at computation and understanding of the climate system on a millennial timescale. It is a code fork from the LOVECLIM climate model version 1.2. From its forerunner, iLOVECLIM retains only the physical climate components (atmosphere–ocean–terrestrial vegetation modules). It is developed further to progressively include the components necessary for multi-millennia palaeoclimate and future climate experiments. As such, iLOVECLIM is a tool designed to enhance the integration of model simulations and (palaeo-)data, with an emphasis on the simulation of isotopic tracers throughout all components of the climate system, as indicated by the i- prefix. The present, time-unlimited special issue hosts the technical documentation of the current version of iLOVECLIM as well as model evaluation manuscripts.

The Norwegian Earth System Model (NorESM) is a global, coupled model system for the physical climate system, which can be run with various degrees of interactions with biogeochemical processes in the earth system. NorESM is developed as a nationally coordinated effort in Norway, but important parts of the model code are imported from the Community Climate System Model (CCSM) and Community Earth System Model (CESM) projects operated at NCAR on behalf of UCAR in the USA.

The NorESM publications in this special issue address a range of NorESM versions. The first set of model versions delivered results to CMIP5. NorESM1-M is run concentration-driven for greenhouse gases (GHGs) and is based on CCSM4 (released 1 April 2010), while NorESM1-ME can be run emission-driven for GHGs and is based on CESM1 (released 1 July 2010). A low-resolution version, NorESM1-L, was developed mainly for paleo-climate simulations. New versions of NorESM are underway: NorESM1.X, where X indicates updates of the NorESM1 versions, and NorESM2, which is intended to contribute to CMIP6. Further versions will follow thereafter. NorESM includes the following: its own developed code for chemistry–aerosol–cloud–radiation interactions (CAM-Oslo) and enhancements of the dynamics/physics of the atmospheric module; alternative parameterization of surface turbulent fluxes; an isopycnic coordinate ocean model originating from the Miami Isopycnic Coordinate Ocean Model (MICOM) but developed further; and the HAMburg Ocean Carbon Cycle (HAMOCC) model developed at the Max Plank Institute for Meteorology, Hamburg and adapted to the isopycnic coordinate ocean model framework.

Papers developed for full validation (CMIP-DECK) or more specific evaluation of the NorESM versions and further developments of these are welcome in this special issue. Authors intending to contribute papers to this special issue should contact the coordinators (Mats Bentsen and Michael Schulz), e.g., to ensure the consistency of version names and numbers.

CMIP5 represents the most ambitious and computer-intensive model inter-comparison project ever attempted. Integrating a new generation of Earth system models and sharing the model results with a broad community has brought with it many significant technical challenges, along with new community-wide efforts to provide the necessary software infrastructure. This special issue will focus on the software that supports the scientific enterprise for CMIP5, including: couplers and coupling frameworks for Earth system models; the Common Information Model and Controlled Vocabulary for describing models and data; The development of the Earth System Grid Federation; the development of new portals for providing data access to different end-user communities; the scholarly publishing of datasets, and studies of the software development and testing processes used for the CMIP5 models. We especially welcome papers that offer comparative studies of the software approaches taken by different groups, and lessons learnt from community efforts to create shareable software components and frameworks.

The climate record of the last millennium holds much promise for identifying the links between forcings and responses at the global, hemispheric and regional scale. The specifications for the Paleoclimate Model Intercomparison Project Phase III (PMIP3) and the Coupled Model Intercomparison Project Phase V (CMIP5) include controlled experiments for the period 850 to 1850 CE. The implementation of those experiments, the collation and development of the climate drivers over this period, and the assessment of the model responses are the focus of this special issue of Geoscientific Model Development.

The CSIRO Mk3L climate system model is a computationally-efficient coupled general circulation model, designed primarily for the study of climate variability and change on millennial timescales. The model distribution is freely available to the research community. This Special Issue allows the history and evolution of Mk3L to be comprehensively documented within a single issue of a journal. Papers are welcome which describe and evaluate components of the model, and which describe and evaluate subsequent enhancements to the modelling system. The issue is also intended for papers which document specific experiments, particularly those which contribute towards Model Intercomparison Projects.

All papers of this special issue will undergo the regular interactive peer-review process of Geoscientific Model Development handled by members of the GMD editorial board.

FAMOUS is climate model based on the widely used "HadCM3" atmosphere–ocean general circulation code, a version of the UK Met Office Unified Model. Run at a lower resolution than HadCM3, its computational requirements make it suitable for large ensembles and millennial-scale climate simulations. This ongoing special issue collects technical documentation and evaluations of the model climatology as FAMOUS is developed and coupled to models of other Earth system components.

The Modular Earth Submodel System (MESSy) is a multi-institutional project providing a strategy and the software for developing Earth System Models (ESMs) with highly flexible complexity.

The strategy follows a bottom-up approach, meaning that the various processes and diagnostic tools are implemented as so-called submodels, which are technically independent of each other and strictly separated from the underlying technical model infrastructure, such as memory management, input/output, flow-control, etc.

The MESSy software provides generalized interfaces for the standardized control and interconnection (coupling) of these submodels.

The present time-unlimited Special Issue hosts scientific and technical documentation and evaluation manuscripts concerned with the Modular Earth Submodel System and the models build upon it. Moreover, it comprises manuscripts about scientific applications involving these models.