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Climate Impact Modelling in Research Domain 2

RD2 employs various climate and impact models at global and regional scales. These models have been continuously improved and results have been validated over recent years. They have also been linked to integrate climate impacts across different sectors.

The dynamic global vegetation, crop and hydrological model LPJmL has been coupled with the global agriculture and land use model MAgPIE. The coupled models have been used to analyse climate impacts on agricultural crops and water use, including economic effects like changes in prices and international trade. Both models, together with the REMIND model in RD3, are key elements of the Potsdam Integrated Assessment Modelling (PIAM) framework, covering the energy-climate-land-water nexus.

At the regional scale, a modelling chain has been developed, including the statistical climate model STARS and the dynamic climate model CCLM. The impact modelling chain comprises an integrated ecohydrological model (SWIM), a process-based forest growth model (4C), a statistical crop model (IRMA), and urban climate models (D-CEP, URBGRAV, CITY-OPTIONS). The entire modelling chain can be adapted worldwide to particular regional conditions.

The research area Climate Change and Development has developed a global city assessment model (CITY-OPTIONS) to evaluate cities in terms of GHG emissions and provide different sustainable urban development options. The model is applicable for single cities, but also for the global city system.

RD2 has taken first steps to systematically link global and regional models. Global model results can be used to identify hotspots of climate change, where regional models can zoom in with further detail and higher resolution. At the same time, global models can be improved, based on insights from specific regional case studies, and model results can be interpreted with better understanding of the importance of regional details for overall dynamics.


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  • LPJmL - Lund-Potsdam-Jena managed Land Dynamic Global Vegetation, Agriculture and Water Balance Model is a dynamic global simulation model of vegetation biogeography, vegetation/soil biogeochemistry and agricultural production systems. Taking climate, soil and atmospheric information as input, it dynamically computes spatially explicit transient vegetation composition in terms of plant functional groups, and their associated carbon and water budgets.
  • MAgPIE - Model of Agricultural Production and its Impact on the Environment is a global land and water use model. It provides, in connection with the dynamic global vegetation and hydrology model LPJmL, a consistent link between economic development, food and energy demand in different world regions with spatially explicit patterns of production, land use change and water constraints. As an economic optimisation model, MAgPIE is applied to derive economic values (rents) of land and water resources used in agricultural production.
  • MAGICC - Model for the Assessment of Greenhouse Gas Induced Climate Change is a simple/reduced complexity climate model. It was originally developed by Tom Wigley (National Centre for Atmospheric Research, Boulder, US, and University of Adelaide, Australia) and Sarah Raper (Manchester Metropolitan University, UK) in the late 1980s and continuously developed since then. It has been one of the widely used climate models in various IPCC Assessment Reports. The latest version, MAGICC6, is co-developed by Malte Meinshausen (Potsdam Institute for Climate Impact Research, Germany, and the University of Melbourne, Australia).
  • EXPACT - Prototype impact emulators that accounts for simultaneous occurrence of impacts from extreme events, based on the ISI-MIP database, and will be applied for comprehensive climate risk assessments.


  • STARS - STatistical Analogue Resampling Scheme represents a new statistical method for  regional climate scenarios. The basis for these scenarios are daily meteorological data measured at the stations in the region of interest and trend in temperature for the future, derived e.g. from a GCM-run.
  • CCLM - COSMO-ClimateLimited-areaModelling is a dynamic regional climate model, applicable for studying nonlinear feedback processes. In a new approach, it is applied to generate very-high resolution ensemble simulations for extremes (droughts and floods) under uncertainty with a spatial resolution of about 2.8 km. Temporal resolution is recently between 1 day and 1 hour
  • SWIM - Soil and Water Integrated Model investigates climate and land use change impacts at the regional scale, where the impacts are manifested and adaptation measures take place. The model simulates interlinked processes at the mesoscale such as runoff generation, plant and crop growth, nutrient and carbon cycling, and erosion. It provides numerous model outputs such as river discharge, crop yield, and nutrient concentrations and loads.
  • 4C - FORESEE - FORESt Ecosystems in a Changing Environment is a forest dynamics model which allows  to analyse  forest behaviour under climate change. It describes carbon and water balance of forest stands  and includes management and submodels for wood product (WPM) and socio-economic analyses (SEA).
  • IRMA - Integrated Regional Model Approach is a statistical strategy to simulate yield changes of crops by linking them to changes of weather parameters to assess the combined effects of regional climate change and agricultural
  • URBGRAV - The URBan GRAVity model explores the concept that growth is more likely to take place close to urban space, as formulated more generally by W.R. Tobler 1970 "Everything is related to everything else, but near things are more related than distant things".
  • CITY-OPTIONS - is a (growing) collection of modules which can be combined to quantitatively assess adaptation options regarding future Climate Change in urban areas.
  • D-CEP - Double-Canyon Urban Canopy Scheme is an urban parametrization for use in regional climate models to assess urban climate, energy use and adaptation options.

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