Abstract. Numerical simulations of volcanic processes play a fundamental role in understanding the dynamics of magma storage, ascent and eruption. The recent extraordinary progress in computer performance and improvements in numerical modeling techniques allow simulating multiphase systems in mechanical and thermodynamical disequilibrium. Nonetheless, the growing complexity of these simulations requires the development of flexible computational tools that can easily switch between sub-models and solution techniques. In this work we present MagmaFOAM, a library based on the open source computational fluid dynamics software OpenFOAM, that incorporates models for solving the dynamics of multiphase, multicomponent magmatic systems. Retaining the modular structure of OpenFOAM, MagmaFOAM allows run-time selection of the solution technique depending on the physics of the specific process, and sets a solid framework for in-house and community model development, testing and comparison. MagmaFOAM models thermo-mechanical non-equilibrium phase coupling and phase change, and implements state-of-the-art multiple volatile saturation models and constitutive equations with composition-dependent and space-time local computation of thermodynamic and transport properties. Code testing is performed using different multiphase modeling approches for processes relevant to magmatic systems: Rayleigh-Taylor instability, for buyoancy-driven magmatic processes; multiphase shock tube simulations, propedeutical to conduit dynamics studies; bubble growth and breakage in basaltic melts. Benchmark simulations illustrate the capabilities and potential of MagmaFOAM to account for the variety of non-linear physical and thermodynamical processes characterizing the dynamics of volcanic systems.
Realistic simulation of the Earth's mean-state climate remains a major challenge, and yet it is crucial for predicting the climate system in transition. Deficiencies in models' process representations, propagation of errors from one process to another, and associated compensating errors can often confound the interpretation and improvement of model simulations. These errors and biases can also lead to unrealistic climate projections and incorrect attribution of the physical mechanisms governing past and future climate change. Here we show that a significantly improved global atmospheric simulation can be achieved by focusing on the realism of process assumptions in cloud calibration and subgrid effects using the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1). The calibration of clouds and subgrid effects informed by our understanding of physical mechanisms leads to significant improvements in clouds and precipitation climatology, reducing common and long-standing biases across cloud regimes in the model. The improved cloud fidelity in turn reduces biases in other aspects of the system. Furthermore, even though the recalibration does not change the global mean aerosol and total anthropogenic effective radiative forcings (ERFs), the sensitivity of clouds, precipitation, and surface temperature to aerosol perturbations is significantly reduced. This suggests that it is possible to achieve improvements to the historical evolution of surface temperature over EAMv1 and that precise knowledge of global mean ERFs is not enough to constrain historical or future climate change. Cloud feedbacks are also significantly reduced in the recalibrated model, suggesting that there would be a lower climate sensitivity when it is run as part of the fully coupled E3SM. This study also compares results from incremental changes to cloud microphysics, turbulent mixing, deep convection, and subgrid effects to understand how assumptions in the representation of these processes affect different aspects of the simulated atmosphere as well as its response to forcings. We conclude that the spectral composition and geographical distribution of the ERFs and cloud feedback, as well as the fidelity of the simulated base climate state, are important for constraining the climate in the past and future.
Oceanic dissolved inorganic carbon (TC) is the largest pool of carbon that interacts considerably with the atmosphere on human timescales. Oceanic TC is increasing through uptake of anthropogenic carbon dioxide (CO2), and seawater pH is decreasing as a consequence. Both the exchange of CO2 between ocean and atmosphere and the pH response are governed by a set of parameters that interact through chemical equilibria, collectively known as the marine carbonate system. To investigate these processes, at least two of the marine carbonate system's parameters are typically measured – most commonly, two from TC, total alkalinity (AT), pH, and seawater CO2 fugacity (fCO2; or its partial pressure, pCO2, or its dry-air mole fraction, xCO2) – from which the remaining parameters can be calculated and the equilibrium state of seawater solved. Several software tools exist to carry out these calculations, but no fully functional and rigorously validated tool was previously available for Python, a popular scientific programming language. Here, we present PyCO2SYS, a Python package intended to fill this capability gap. We describe the elements of PyCO2SYS that have been inherited from the existing CO2SYS family of software and explain subsequent adjustments and improvements. For example, PyCO2SYS uses automatic differentiation to solve the marine carbonate system and calculate chemical buffer factors, ensuring that the effect of every solute and reaction is accurately included in all its results. We validate PyCO2SYS with internal consistency tests and comparisons against other software, showing that PyCO2SYS produces results that are either virtually identical or different for known reasons, with the differences negligible for all practical purposes. We discuss new insights that arose during the development process, for example that the marine carbonate system cannot be unambiguously solved from the total alkalinity and carbonate ion parameter pair. Finally, we consider potential future developments to PyCO2SYS and discuss the outlook for this and other software for solving the marine carbonate system. The code for PyCO2SYS is distributed via GitHub ( https://github.com/mvdh7/PyCO2SYS ) under the GNU General Public License v3, archived on Zenodo (Humphreys et al., 2021), and documented online ( https://PyCO2SYS.readthedocs.io ).
The penultimate deglaciation (PDG, ∼138–128 thousand years before present, hereafter ka) is the transition from the penultimate glacial maximum (PGM) to the Last Interglacial (LIG, ∼129–116 ka). The LIG stands out as one of the warmest interglacials of the last 800 000 years (hereafter kyr), with high-latitude temperature warmer than today and global sea level likely higher by at least 6 m. Considering the transient nature of the Earth system, the LIG climate and ice-sheet evolution were certainly influenced by the changes occurring during the penultimate deglaciation. It is thus important to investigate, with coupled atmosphere–ocean general circulation models (AOGCMs), the climate and environmental response to the large changes in boundary conditions (i.e. orbital configuration, atmospheric greenhouse gas concentrations, ice-sheet geometry and associated meltwater fluxes) occurring during the penultimate deglaciation. A deglaciation working group has recently been set up as part of the Paleoclimate Modelling Intercomparison Project (PMIP) phase 4, with a protocol to perform transient simulations of the last deglaciation (19–11 ka; although the protocol covers 26–0 ka). Similar to the last deglaciation, the disintegration of continental ice sheets during the penultimate deglaciation led to significant changes in the oceanic circulation during Heinrich Stadial 11 (∼136–129 ka). However, the two deglaciations bear significant differences in magnitude and temporal evolution of climate and environmental changes. Here, as part of the Past Global Changes (PAGES)-PMIP working group on Quaternary interglacials (QUIGS), we propose a protocol to perform transient simulations of the penultimate deglaciation under the auspices of PMIP4. This design includes time-varying changes in orbital forcing, greenhouse gas concentrations, continental ice sheets as well as freshwater input from the disintegration of continental ice sheets. This experiment is designed for AOGCMs to assess the coupled response of the climate system to all forcings. Additional sensitivity experiments are proposed to evaluate the response to each forcing. Finally, a selection of paleo-records representing different parts of the climate system is presented, providing an appropriate benchmark for upcoming model–data comparisons across the penultimate deglaciation.
To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land use and climate change on biodiversity and ecosystem services (i.e. nature’s contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenarios selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem service models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modelling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modelling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios.
The chemistry–climate model ECHAM-HAMMOZ contains a detailed representation of tropospheric and stratospheric reactive chemistry and state-of-the-art parameterizations of aerosols using either a modal scheme (M7) or a bin scheme (SALSA). This article describes and evaluates the model version ECHAM6.3-HAM2.3-MOZ1.0 with a focus on the tropospheric gas-phase chemistry. A 10-year model simulation was performed to test the stability of the model and provide data for its evaluation. The comparison to observations concentrates on the year 2008 and includes total column observations of ozone and CO from IASI and OMI, Aura MLS observations of temperature, HNO3, ClO, and O3 for the evaluation of polar stratospheric processes, an ozonesonde climatology, surface ozone observations from the TOAR database, and surface CO data from the Global Atmosphere Watch network. Global budgets of ozone, OH, NOx, aerosols, clouds, and radiation are analyzed and compared to the literature. ECHAM-HAMMOZ performs well in many aspects. However, in the base simulation, lightning NOx emissions are very low, and the impact of the heterogeneous reaction of HNO3 on dust and sea salt aerosol is too strong. Sensitivity simulations with increased lightning NOx or modified heterogeneous chemistry deteriorate the comparison with observations and yield excessively large ozone budget terms and too much OH. We hypothesize that this is an impact of potential issues with tropical convection in the ECHAM model.
Emission inventories are the quantification of pollutants from different sources. They provide important information not only for climate and weather studies but also for urban planning and environmental health protection. We developed an open-source model (called Vehicular Emissions Inventory – VEIN v0.2.2) that provides high-resolution vehicular emissions inventories for different fields of studies. We focused on vehicular sources at street and hourly levels due to the current lack of information about these sources, mainly in developing countries.The type of emissions covered by VEIN are exhaust (hot and cold) and evaporative considering the deterioration of the factors. VEIN also performs speciation and incorporates functions to generate and spatially allocate emissions databases. It allows users to load their own emission factors, but it also provides emission factors from the road transport model (Copert), the United States Environmental Protection Agency (EPA) and Brazilian databases. The VEIN model reads, distributes by age of use and extrapolates hourly traffic data, and it estimates emissions hourly and spatially. Based on our knowledge, VEIN is the first bottom–up vehicle emissions software that allows input to the WRF-Chem model. Therefore, the VEIN model provides an important, easy and fast way of elaborating or analyzing vehicular emissions inventories under different scenarios. The VEIN results can be used as an input for atmospheric models, health studies, air quality standardizations and decision making.
This paper would definitely have benefited from another round or two of rereading and proofreading. Not even the name of the model is unambiguously given: in the title, the name is Bottom RedOx Model, in the model presentation (p. 2, ll. 2–3) it is Bottom RedOx Layer Model. The English of the paper needs some thorough revision. There are parts that are acceptable and others that are almost unsuitable for review. I am not going to point out all the English errors that I found – they are simply to numerous to key them all in here. There is one British co-author and two co-authors with affiliations to institutions in English-speaking countries or regions: could they please have a look at the manuscript and help to correct it and rewrite where necessary! There are errors (spelling, grammar, syntax, style) on nearly every single page, but sections 3.2.4 (Manganese) and 3.3 (Carbonate system) require particularly close attention.
We present the Efficient CH4-CO-OH Module (ECCOH) that allows for the simulation of the methane, carbon monoxide and hydroxyl radical (CH4-CO-OH cycle, within a chemistry climate model, carbon cycle model, or earth system model. The computational efficiency of the module allows many multi-decadal, sensitivity simulations of the CH4-CO-OH cycle, which primarily determines the global tropospheric oxidizing capacity. This capability is important for capturing the nonlinear feedbacks of the CH4-CO-OH system and understanding the perturbations to relatively long-lived methane and the concomitant impacts on climate. We implemented the ECCOH module into the NASA GEOS-5 Atmospheric Global Circulation Model (AGCM), performed multiple sensitivity simulations of the CH4-CO-OH system over two decades, and evaluated the model output with surface and satellite datasets of methane and CO. The favorable comparison of output from the ECCOH module (as configured in the GEOS-5 AGCM) with observations demonstrates the fidelity of the module for use in scientific research.
publication. However, I would then expect some significant extra added value from the model description in this paper that would compensate for the reduced “novelty” aspect expected from any newly published scientific paper. The current version of the manuscript falls somewhat short of providing this extra added value. Actually, not only applications, but even the details of the most important parts of the model have been published before. The salient feature of the sediment model, the variable porosity as a function of the detrital/carbonate composition, has been described in full detail in Zeebe and Zachos (2007); large parts of the description provided here are actually identical to that in Zeebe and Zachos (2007). Unfortunately, shortcomings in that description have not been addressed here: e. g., it is still not known how chemical erosion is implemented, i. e., how the below-surface sediment characteristics are stored and used in case of chemical erosion. The more fundamental ocean tracer equations are far from complete, important information is missing.
I would like to point out that there is already a model called MEDUSA (Model of Early Diagenesis in the Upper Sediment (A)), published by Munhoven (2007). That model has been used for studying the evolution of the carbon cycle over glacial-interglacial time scales (Munhoven, 2007, 2010). It is, however, also being actively used for studying the impact of future ocean acidification on carbon cycling between the ocean, atmosphere and the surface sediment (e.g., Munhoven, 2008, 2009).
Here we describe GENIE-M. a new and improved version of the Grid ENabled lntegrated Earth system madel (GENIE), which is a 3-D earth system madel of intermediate complexity. Main development goals of GENIE-M were to: (1) bring oceanic uptake of anthropogenic transient tracers within data constraints; (2) increase vertical resolution in the upper ocean to better represent near-surface biogeochemical processes; (3) calibrate the deep ocean ventilation with observed abundance of radiocarbon. We achieved ali these goals through a transparent process of calibration that mostly consisted of objective madel optimization. An important new feature in GENIE-M that dramatically improved the uptake of CFC-11 and anthropogenic carbon is the depth dependent vertical diffusivity in the ocean, which is spatially uniform in GENIE-1. ln GENIE-M. biological production occurs in the top two layers above the compensation depth of 1 00 m and is modified, for example, by diagnosed mixed layer depth. ln contrast, production in GENIE-1 occurs in a single layer with thickness of 175 m. These improvements make GENIE-M a well-calibrated madel of intermediate complexity suitable for investigations of the global marine carbon cycle requiring long integration time.
