Models Archive

3D-CMCC FEM

3D-CMCC-FEM – Three Dimension Forest Ecosystem Model (Collalti et al., 2014; Collalti et al., 2016; Marconi et al., 2017; Collalti et al., 2018) is a dynamic process-based model which simulates forest growth, carbon allocation and other dynamics in heterogeneous populations (mixed and un-evenaged). The model is based on the reproduction, at daily time scale and according to climate, soil and stand characteristics, of the main eco-physiological processes governing gross and net primary production (GPP, NPP), carbon and water dynamics.

AQUATOX

AQUATOX is an aquatic ecosystem simulation model developed by Environmental Protection Agency (EPA). Its main goal is to predict the fate of nutrients, organic chemicals, and sediments in different water bodies (e.g.

BFM – Biogeochemical Flux Model

The Biogeochemical Flux Model (BFM) is a generalized marine biogeochemistry model based on a biomass continuum description of lower trophic levels in the marine environment. The major chemical and biological components are described in terms of functional groups by means of the theoretical concepts of Chemical Functional Families and Living Functional Groups (CFF and LFG; Vichi et al., 2023).

C-GLORS – The CMCC Global Ocean Physical Reanalysis System

The CMCC Global Ocean Physical Reanalysis System (C-GLORS) is used at CMCC to simulate the state of the global ocean in the last decades. It consists of a variational data assimilation system (OceanVar), capable of assimilating all in-situ observations along with altimetry data, and a forecast step performed by the ocean model NEMO coupled with the LIM2 sea-ice model.

CIRCEE – CIRCular Energy-Economy Model

CIRCEE (CIRCular Energy-Economy Model) is a stylized deterministic dynamic and stochastic general equilibrium model designed to assess circular economy policies and behavioral changes at the macroeconomic level on socioeconomic systems, resource use, waste generation and CO2 emissions. CIRCEE consists of a dynamic general equilibrium model that incorporates industrial ecology concepts such as material stock and flows consistency (Corbier et al., 2024).

CLACQ – Country Level Air Quality Calculator

The Country Level Air Quality Calculator (CLAQC) is an open-source modeling tool that utilizes national sectoral emissions and weather data to forecast monthly and annual concentrations of fine particulate matter (PM2.5) and tropospheric ozone (O3). CLAQC leverages the recent advancements in the CAMS system, employing CAMS global gridded emissions and CAMS reanalysis pollutant concentrations to improve the accuracy of its predictions.

CMCC EBM

The Estuary Box Model, CMCC EBM, has been jointly developed by OPA Division of CMCC Foundation and the University of Bologna, Department of Physics and Astronomy. It is a time dependent numerical model based on two-layer averaged continuity and salinity conservation equations, linking the riverine freshwater and the salt sea waters (Verri et al., 2020; Verri et al., 2021).

CMCC Med Model

The climate model CMCC-Med is a coupled model atmosphere-ocean-sea-ice based on the climate model CMCC-CM but with a focus on the Mediterranean region. In particular, in the CMCC-Med model the global atmospheric component (ECHAM5) implemented at high-resolution (T159, corresponding to an horizontal grid spacing of about 80 Km) is coupled with the global ocean (OPA8.2 implemented in ORCA2 version) and, on the Mediterranean Sea, with an high-resolution model of this basin (NEMO-MFS implemented to 1/16°).

CMCC-CM – Climate Model

The collaborative effort of researchers from different divisions of the IESP Institute is the foundation for the development and advancement of the CMCC Global Climate Model (CMCC-CM). In the sixth phase of the Coupled Model Intercomparison Project (CMIP), the CMCC-CM2 version of the model was used to complete a set of climate experiments encompassing both low and high resolution global configurations, respectively described in Cherchi et al.

CMCC-ESM – Earth System Model

The Earth System Modeling Unit at ESYDA division is devoted to the development and application of the CMCC Earth System Model. The current version CMCC-ESM2 is based on the coupling between the climate coupled model CMCC-CM2 (Cherchi et al., 2019), that accounts for interactive dynamics of atmosphere, ocean, sea-ice and land components, with the inclusion of the marine biogeochemistry to fully represent the global carbon cycles.

Coexistence Model

The coexistence model (Di Paola et al., 2012) is a simple quantitative dynamic model able to explain the observed co-occurrence of sclerophyllous evergreen oak species with deciduous ones of the Mediterranean forests. The model is formulated as a set of differential equations describing the competitive dynamic between two groups of species having different physiological responses to water stress.

COSMO-CLM – Climate Limited-area Modelling Community

At CMCC, the regional climate model COSMO-CLM (Rockel and Geyer, 2008) is currently used to perform dynamical downscaling of global climate simulations (see figure 1). Figure 1: A RCM domain embedded in a GCM grid.

DESYCO

DESYCO is a GIS-based Decision Support System (DSS) aimed at the integrated assessment of multiple climate change impacts on vulnerable coastal systems (e.g. beaches, river deltas, estuaries and lagoons, wetlands, agricultural and urban areas).

DSK – Dystopian Schumpeter Meeting Keynes climate-economy agent-based model

The Dystopian Schumpeter Meeting Keynes climate-economy agent-based model (DSK) is an agent based integrated assessment model for climate impacts and the study of climate fiscal and monetary policies. The DSK model is an agent-based simulation laboratory representing a global economy and its relationship with changes in climatic conditions.

EDGE – Energy Demand GEnerator

The Energy Demand GEnerator is a building energy sectoral model first developed at PIK and currently at CMCC. It has a global coverage, and only for the EU it has a subnational resolution of 0.5°.

FASST(R) – FAst Scenario Screening Tool

FASST(R) is a source receptor model, an R version of the reduced-form TM5- FASST [5] model developed at JRC-Ispra, to compute the annual concentrations of several pollutants p, namely SO2 , NOx , fine Particulate Matter (PM2.5 ) and O3. The FASST(R) model produces concentrations on a world spatial grid of resolution of 1 ◦ × 1 ◦ , and the fine PM 2.5 concentrations include Particulate Organic Matter (POM), secondary inorganic PM, dust and sea-salt.

FIDELIO – Fully Interregional Dynamic Econometric Long-term Input-Output

The FIDELIO (Full Interregional Dynamic Econometric Long-term Input-Output) model is a tool for estimating the socio-economic and environmental impacts of EU industrial, trade, and innovation policies for a fair and sustainable EU economy. Developed and run by the Joint Research Centre (JRC) and steered by the Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs (DG GROW) to become a fully-fledged model of industrial policy, including an SME dimension, FIDELIO is mostly oriented to demand policies but also flexible to incorporate supply policy shocks as well.

IAMPACT

IAMPACT is a cutting-edge research tool that helps answer one of the most important questions in climate policy: "Is investing in climate action today worth the cost?". The program combines climate science with economic analysis to calculate the costs and benefits of reducing greenhouse gas emissions, providing policymakers with the quantitative evidence needed to make informed decisions about climate policy.

ICES – Inter-temporal Computable Equilibrium System

ICES is a recursive dynamic multiregional Computable General Equilibrium (CGE) model to assess impacts of climate change on the economic system and to study mitigation and adaptation policies. ICES is a multipurpose tool to assess impacts of climate change on the economic system, evaluate costs of mitigation and adaptation policies, describe the key role of public sector for mitigation and adaptation polcies, and draw future sustainability scenarios.

ICES – Intertemporal Computable Equilibrium System

The ICES - Intertemporal Computable Equilibrium System (https://www.icesmodel.org/) model is one of the main modelling tools developed within the FEEM Research Programme "Sustainable Development" and designed to assist in the study of the socio-economic dimension of climate change. ICES is a recursive dynamic general equilibrium model developed with the main (but not exclusive) purpose to assess the final welfare implication of climate change impacts on world economies.

IDI – Integrated Desertification Index

The Integrated Desertification Index (IDI) was developed (Santini et al., 2010) to combine in a semi-quantitative way multiple processes leading to desertification and simulated via mechanistic to empirical models. The outcomes from the modelling efforts on different desertification components are standardized and weighted so to be inserted in the IDI formulation.

LIM

LIM is a numerical model of sea ice designed for climate studies and operational oceanography. It is coupled to the ocean general circulation model OPA (Océan Parallélisé) and is part of NEMO (Nucleus for European Modeling of the Ocean).

LUC@CMCC – Land use change model

The land use change model LUC@CMCC was reformulated in Santini and Valentini (2011) starting from the CLUEs model (Verburg et al. 2002) to reproduce the dynamics of land use/cover change in the past and project them in the future.

MacroEnergy

Macro is a bottom-up, multi-sectoral infrastructure optimization model for macro-energy systems. It co-optimizes the design and operation of user-defined models of multi-sector energy systems and networks.

MARLEY – Multi-Agent Reinforcement Learning for Long-term Electricity Markets

The Multi-Agent Reinforcement Learning for Long-term Electricity Markets (MARLEY) enables the assessment of various market designs, policy instruments, and decarbonization strategies in electricity systems, with a focus on capturing the adaptive behavior of profit-maximizing generation companies making investment decisions. The framework is used in the article "Assessing Long Term Electricity Market Design for Ambitious Decarbonization Targets using Multi-Agent Reinforcement Learning", and employs Independent Proximal Policy Optimization (IPPO) to simulate decentralized, competitive market environments where multiple agents invest in generation assets through wholesale markets, capacity remuneration mechanisms, and Contract for Differences (CfD) auctions.