Posts tagged optional
mHM - mesoscale Hydrologic Model
- 12 December 2024
The mesoscale Hydrologic Model (mHM) developed by the Dept. Computational Hydrosystems at UFZ is a spatially explicit distributed hydrologic model. It is implemented in the Fortran programming language and can be easily installed as software using the conda package manager. The model concept uses grid cells as a primary hydrologic unit, and accounts for the following processes: canopy interception, snow accumulation and melting, soil moisture dynamics, infiltration and surface runoff, evapotranspiration, subsurface storage and discharge generation, deep percolation and baseflow and discharge attenuation and flood routing. The model is driven by hourly or daily meteorological forcings (e.g., precipitation, temperature), and it utilizes observable basin physical characteristics (e.g., soil textural, vegetation, and geological properties) to infer the spatial variability of the required parameters.
ParFlow - Parallel Watershed Flow Model
- 12 December 2024
ParFlow is a parallel, integrated hydrology model that simulates spatially distributed surface and subsurface flow, as well as land surface processes including evapotranspiration and snow. It solves saturated and variably saturated flow in three dimensions using either an orthogonal or terrain-following, semi-structured mesh that enables fine vertical resolution near the land surface and deep (~1 km) confined and unconfined aquifers. ParFlow models dynamic surface and subsurface flow solving the simplified shallow water equations implicitly coupled to Richards’ equation; this allows for dynamic two-way groundwater surface water interactions and intermittency in streamflow. The model uses robust linear and nonlinear solution techniques and exhibits efficient parallel scaling to large processor counts, more than 100K cores, enabling very large extent simulations with fine spatial resolution. ParFlow has been coupled to various land surface and atmospheric models such as CLM, WRF, and TerrSysMP.
QUINCY - Quantifying the effects of interacting nutrient cycles
- 28 November 2024
QUINCY is a state-of-the-art terrestrial biosphere model with fully coupled carbon, nitrogen, water, phosphorus and energy cycles. The objective of QUINCY is to clarify the role of the interacting terrestrial nitrogen and phosphorus cycles and their effects on terrestrial C allocation and residence times as well as terrestrial water fluxes.
CLEO - Clouds made Lagrangian, exascale and open-source
- 28 November 2024
Cloud microphysics remains an integral and under-represented element of the climate system. Not only does this limit our understanding of clouds themselves, but also causes some of the largest uncertainties in climate modelling as a whole. CLEO is a SDM with collisional breakup for warm rain aiming to be computationally feasible in O(100km) LES.
PISM - Parallel Ice Sheet Model
- 10 July 2024
Ice in the Earth system model refers to all components of the cryosphere: ice and snow on land, glaciers and permafrost in soils and the deep sea.
ISSM - Ice-sheet and Sea-level System Model
- 10 July 2024
The Ice Sheet System Model (ISSM) a finite-element 3D thermo-mechanical ice-sheet model that relies on high-order physics to simulate high-resolution ice flow on continental scales.
HAMOCC - HAMburg Ocean Carbon Cycle
- 12 June 2024
Fatemeh Chegini, Tatiana Ilyina
The HAMburg Ocean Carbon Cycle (HAMOCC) model is the ocean biogeochemistry component in ICON and MPI-ESM (Ilyina et al., 2013). HAMOCC simulates at least 20 biogeochemical tracers in the water column, following an extended nutrient, phytoplankton, zooplankton, and detritus approach, also including dissolved organic matter, as described in Six and Maier-Reimer (1996). It also simulates the upper sediment by 12 biologically active layers and a burial layer to represent the dissolution and decomposition of inorganic and organic matter as well as the diffusion of pore water constituents. The co-limiting nutrients consist of phosphate, nitrate, silicate, and iron. A fixed stoichiometry for all organic compounds is assumed. Phytoplankton is represented by bulk phytoplankton and diazotrophs (nitrogen fixers). Particulate organic matter (POM) is produced by zooplankton grazing on bulk phytoplankton and enters the detritus pool. Export production is separated explicitly into CaCO3 and opal particles. The POM sinking speed can be assigned using one of the three implemented methods: constant speed, linearly increasing speed with depths below the euphotic zone (also known as the “Martin curve”; Martin et al., 1987) or calculated using the recently developed M4AGO scheme (Maerz et al., 2020). The remineralization of detritus throughout the water column is either aerobic (if seawater oxygen concentration >0.5 μmolL−1) or anaerobic by denitrification and sulfate reduction. The HAMOCC model as part of ICON and MPI-ESM and has been extensively evaluated and applied in previous single-model (e.g., Ilyina et al., 2013; Paulsen et al., 2017; Müller et al., 2018; Mauritsen et al., 2019; Maerz et al., 2020; Jungclaus et al. 2022, Hohenegger et al. 2022) and multi-model studies (e.g., Bopp et al., 2013; Kwiatkowski et al., 2020; Séférian et al., 2020).
PALM - Parallelized Large-eddy Simulation Model
- 10 June 2024
High-performance Large-Eddy Simulation model for simulating atmospheric boundary layer flows with fully interactive embedded models (urban surface, land surface, radiation, cloud physics, pollutant dispersion). It has been developed as a turbulence-resolving large-eddy simulation (LES) model that is especially designed for performing on massively parallel computer architectures. By default, PALM has at least six prognostic quantities: the velocity components u, v, w on a Cartesian grid, the potential temperature θ, water vapor mixing ratio qv and possibly a passive scalar s. Furthermore, an additional equation is solved for either the subgrid-scale turbulent kinetic energy (SGS-TKE) e (LES mode, default) or the total turbulent kinetic energy. PALM is now an independent name based on a FORTRAN code.
MPTRAC - Massive-Parallel Trajectory Calculations
- 10 June 2024
Massive-Parallel Trajectory Calculations (MPTRAC) is a La-grangian particle dispersion model for the analysis of atmospheric transport processes in the free troposphere and stratosphere.
CLaMS - Chemical Lagrangian Model of the Stratosphere
- 10 June 2024
CLaMS (Chemical Lagrangian Model of the Stratosphere) is a modular chemistry transport model (CTM) system developed at Research Centre Jülich, Germany. CLaMS was first described by McKenna et al (2000a,b) and was expanded into three dimensions by Konopka et al (2004). CLaMS has been employed in various European aircraft field campaigns including THE-SEO, EUPLEX, TROCCINOX, SCOUT-O3, RECONCILE and STRATOCLIM, PHILEAS with a focus on simulating ozone depletion and water vapour transport. Major strengths of CLaMS in comparison to other CTMs are
WaterGAP (Water Global Assessment and Prognosis)
- 06 June 2024
WaterGAP is a global hydrological model that quantifies human use of groundwater and surface water as well as water flows and water storage and thus water re- sources on all land areas of the Earth. Since 1996, it has served to assess water resources and water stress both historically and in the future. It has been used in multiple studies on climate change impacts and drought and includes an advanced estimation of groundwater recharge. WaterGAP simulations regularly contribute to ISIMIP simulation rounds.
HAMMOZ (Hamburg Aerosol Module and atmospheric chemistry code MOZART)
- 04 June 2024
HAMMOZ contains a detailed representation of tropospheric-stratospheric chemistry and state-of-the-art parameterizations of aerosol using either a modal (M7) or a bin scheme (SALSA). The aerosol model HAM calculates the dispersion and evolution of the mass and number concentrations of an aerosol mixture considering the species sulphate, black carbon, organic carbon, sea salt and mineral dust. The standard version of HAM describes the aerosol size spectrum through the modal M7 aerosol model, which simulates a superposition of seven lognormal modes: Nucleation mode, Soluble (mixed) and Insoluble Aitken, Accumulation and Coarse modes. Each aerosol mode is assumed to be internally mixed, so that individual particles in a mode can be mixtures of different species. Insoluble particles can become mixed (soluble) by condensation of soluble substances and by collisions with mixed particles.
VILMA (Viscoelastic Lithosphere and Mantle model)
- 29 May 2024
Volker Klemann and Maik Thomas
The topic of spectral finite-element code VILMA is the reduction of global GRACE, GPS and altimetry data with respect to the glacial-isostatic adjustment applying a 3D viscoelastic earth model. The model calculates the deformation of a viscoelastic and gravitating continuum in spherical domain, where lateral viscosity variations can be considered. Loading is prescribed as ice and ocean mass changes, which are determined consistently with respect to mass conservation, geoid changes and shoreline displacements by the sea-level equation. Code solves field equations of a spherical self-gravitating incompressible 3D-viscoelastic sphere with spectral–finite elements (Martinec 2000). GRD, that is rotational feedback and sea-level equation are solved for (Klemann et al. 2024 in prep.). Output are time-dependent changes in sea level, surface deformation and gravity potential in response to surface mass distribution. It is already coupled offline to PISM (Albrecht et al. 2024 in revision), MPI-ESM and AWI ESM and as compiled module in CLIMBER-X (Willeit et al. 2022). Offline coupling is implemented as exchange of two fields (in: ice load distribution; out: relative sea level).
YAXT (Yet Another eXchange Tool)
- 23 May 2024
YAXT is a communication layer on top of the MPI library. At starting, the library generates a mapping table between source and target decomposition (communication pattern) and a specific redistribution objects, based on MPI derived datatypes, to perform the exchanges. YAXT is used by YAC for both interpolation weight generation and the coupling field exchange. To calculate the communication patterns of exchanges, more efficient than a simple MPI “all to all”, the libraries rely on a rendezvous algorithm based on a distributed directory of global indices. YAXT not only optimises the exchange pattern but also reduces the communication number, grouping the exchanged arrays on MPI derived datatypes, supposed to reduce the array copies and pack-unpack operations.
WAM
- 23 May 2024
The third generation spectral WAve Model (WAM) integrates the basic transport equation describing the evolution of a two-dimensional ocean wave spectrum without additional ad hoc assumptions regarding the spectral shape. The three source functions describing the wind input, nonlinear transfer, and white-capping dissipation are prescribed explicitly. An additional bottom dissipation source function and refraction terms are included in the finite-depth version of the model.
JSBACH (Jena Scheme for Biosphere-Atmosphere Coupling in Hamburg)
- 23 May 2024
Historically, JSBACH grew out of ECHAM5 by collecting all land processes into a separate land component – then called JSBACH – accessed from ECHAM each time step via a single subroutine call. Accordingly, JSBACH inherits all the land processes originally present in ECHAM5, in particular the way the surface energy balance is solved, and how the land processes are coupled to the atmosphere.
CDI-PIO (Climate Data Interface with parallel writing )
- 23 May 2024
CDI-PIO is currently used for parallelized GRIB1/GRIB2 and NetCDF output in ECHAM and ICON models. CDI-PIO is the parallel I/O component of the Climate Data Interface (CDI) that is developed and maintained by the Max-Planck-Institute for Meteorology and DKRZ. It is used by ICON, MPIOM, ECHAM, and the Climate Data Operator (CDO) toolkit. The two main I/O paths for output data are writing GRIB files using MPI-IO, and writing NetCDF4 files using HDF5 (which may then also use MPI-IO,or other VOL plugins).
HeAT (The Helmholtz Analytics Toolkit)
- 22 May 2024
HeAT is a distributed tensor framework for high performance data analytics. It provides highly optimized algorithms and data structures for tensor computations using CPUs, GPUs and distributed cluster systems on top of MPI. HeAT builds on PyTorch and mpi4py to provide high-performance computing infrastructure for memory-intensive applications within the NumPy/SciPy ecosystem.
ESMValTool (Earth System Model Evaluation Tool)
- 22 May 2024
ESMValTool is a diagnostics and performance metrics tool for the evaluation and analysis of Earth System Models (ESMs). ESMValTool allows for a comparison of single or multiple models against predecessor versions and observations. It includes many diagnostics and performance metrics covering different aspects of the Earth system and is high flexible.
ESM-Tools
- 22 May 2024
ESM-Tools is a modular software infrastructure that allows for seamlessly building, configuration and running of Earth System Models across different High Performance Computing (HPC) platforms (DKRZ-Levante, Jülich-Juwels, HLRN-4’s Lise and Emmy, ECMWF-Atos, ICCP-Aleph, etc.).
REcoM - Regulated Ecosystem Model
- 21 May 2024
REcoM is a water column biogeochemistry and ecosystem model, which incorporates cycles of carbon, nutrients (nitrogen, iron, and silicon) and oxygen with varying intracellular stoichiometry in phytoplankton, zooplankton, and detritus. REcoM can be run in configurations of varying complexity with up to three phytoplankton functional types (PFTs), namely diatoms, coccolithophores and small phytoplankton, up to three zooplankton types (micro- meso and polar microzooplankton) and up to two detritus classes (slow- and fast-sinking). REcoM can also simulate carbon and iron isotopes, and can be coupled to the sediment model Medusa. REcoM is the ocean biogeochemistry module of the AWI Earth System Model and is used for hindcasts, CMIP-type future projections and paleo applications.
COSIPY - COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY)
- 21 May 2024
COSIPY is a flexible and user friendly coupled snowpack and ice surface energy and mass balance model written in Python. COSIPY is based on COSIMA, a ‘COupled Snowpack and Ice surface energy and MAss balance model’, translating the code into Python, and developing further the initial concepts. It combines a surface energy balance (SEB) with a multi-layer subsurface snow and ice model to compute the glacier mass balance (MB). The calculated surface melt water serves as input for the subsurface model. The two models are directly coupled in order to account for melt water percolation, retention and refreezing within the snow pack under consideration of latent heat release and resulting subsurface melt as well as the effects on subsurface temperature, snow density and ground heat flux. All subsurface processes are resolved in a vertical layer structure. COSIPY consists of several modules for solving the heat equation, calculating percolation and refreezing and calculating densification. The modular model setup allows replacing single parameterizations.
AgroC
- 21 May 2024
AgroC is a 1-d model of water, energy and matter fluxes in agricultural systems operating at hourly or daily time steps, accounting for organic carbon, nitrogen and phosphorus turnover and soil mineral nitrogen and phosphorus pools. The SoilCO2/RothC model (Herbst et al., 2008; Simunek et al., 1993) was extended with the dynamic plant growth module SUCROS (Spitters et al., 1988). Combining those subroutines allows for a closed carbon balance of cropped ecosystems at an hourly or daily time step. The model explicitly accounts for soil carbon turnover, soil CO2 flux, plant water stress, nutrient stress and organ-specific carbon allocation. Standard crop input parameters exist for cereals, sugar beet, maize, potato and grassland. It was successfully validated for various sites and crops (Klosterhalfen et al., 2017) and the latest implementations comprise soil nitrous gas emissions. AgroC has been applied to simulate the water stress dependent within-field variability of carbon fluxes (Herbst et al., 2021), to model variability of leaf are index and yield at the 1km2 scale (Brogi et al., 2020; Brogi et al., 2021) and it was part of a large crop model intercomparison study (Groh et al., 2020; Groh et al., 2022). Classical agronomical applications are documented for maize (Zydelis et al., 2018) and hemp (Zydelis et al., 2022). Future scenarios of maize cropping under climate change were investigated with AgroC by Zydelis et al., (2021). A quite unique feature of this model is the estimation of leaf-level solar induced fluorescence in dependence of water stress (DeCanniere et al., 2021).
Xarray-Simlab
- 16 May 2024
A Xarray-simlab is a Python library that provides both a generic framework for building computational models in a modular fashion and a xarray extension for setting and running simulations using the “xarray.Dataset” structure. It is designed for fast, interactive and exploratory modeling.
SIMPLACE
- 16 May 2024
The SIMPLACE system is a modelling framework as FOSS (Free and Open Source System) for dynamic agricultural modelling. It integrates components for grassland, 26 main crops, soil-climate interaction, livestock, etc. For model users there is a GUI, for advanced model developpers a IDE to work with SIMPLACE and the included Model Units.
PDAF - Parallel Data Assimilation Framework
- 16 May 2024
The Parallel Data Assimilation Framework - PDAF - is a software environment for data assimilation. PDAF simplifies the implementation of the data assimilation system with existing numerical models. With this, users can obtain a data assimilation system with less work and can focus on applying data assimilation.
MONICA
- 16 May 2024
The acronym MONICA is derived from „MOdel of Nitrogen and Carbon dynamics in Agro-ecosystems”.
HD Model (Hydrological Discharge Model)
- 16 May 2024
The Hydrological Discharge (HD) model calculates the lateral transport of water over the land surface to simulate discharge into the oceans. It has been validated and applied in many studies since the publication of its original global 0.5° version (Hagemann and Dümenil 1998; Hagemann and Dümenil Gates 2001). Hagemann et al. 2020 developed a high-resolution version that can be applied globally at a 5 Min. (~8-9 km) resolution. This HD version was applied and validated over Europe. The HD model has been coupled to several global and regional Earth System Models. It separates the lateral water flow into the three flow processes of overland flow, baseflow, and riverflow. Overland flow and baseflow represent the fast and slow lateral flow processes within a grid box, while riverflow represents the lateral flow between grid boxes. The HD model requires gridded fields of surface and subsurface runoff as input for overland flow and baseflow, respectively, with a temporal resolution of one day or higher.
GLUES (Global Land Use and technological Evolution Simulator)
- 16 May 2024
The Global Land Use and technological Evolution Simulator (GLUES) is an Earth system component of land use intensity and demography. GLUES mathematically resolves the dynamics of local human populations´ density and characteristic sociocultural traits in the context of a changing biogeographical environment. A local sociocultural coevolution is described by changes in mean population density, technology, share of agropastoral activities, and economic diversity, within a simulation region of approximately country-size extent. Each local population utilises its regional resources, which are describey by vegetation productivity and climatic constraints. Each local population interacts with its geographical neighbours via trade and migration.
SERGHEI
- 14 May 2024
The Simulation EnviRonment for Geomorphology, Hydrodynamics, and Ecohydrology in Integrated form is a multi-dimensional, multi-domain, and multi-physics model framework for environmental and landscape simulation.
Optional components
- 18 July 2023
The following table lists, in alphabetical order, all models that have been presented by the corresponding institutions during past natESM events.
The fact that we have listed the models here does not imply that the models or parts of them will be part of the future natESM system.