The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project framework

By L. Warszawski, K. Frieler, V. Huber, F. Piontek, O. Serdeczny, J. Schewe. Proceedings of the National Academy of Sciences of the United States of America, 2013

1,159 citations recorded by the source corpus.

Subfields: Ecology, Evolution, Behavior and Systematics, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/e23d407cccd44a847aa358abbf586599aace401f

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In Ecology, Evolution, Behavior and Systematics

1. Frank Ewert
2. Senthold Asseng
3. Molly E. Brown
4. C. Funk
5. Walter Jetz
6. Christoph Müller
7. A. Popp
8. Simon Ferrier

In Global and Planetary Change

1. Martina Flörke
2. Yoshihide Wada
3. Senthold Asseng
4. David B. Lobell
5. D. V. van Vuuren
6. M. Widmann
7. C. Funk
8. Molly E. Brown

Citations in the corpus

• Impact of climate change on global malaria distribution (2014, methodology): “The five models were selected to give a wide range of temperature and rainfall changes, rather than a representation of the likelihood of future climate change (15).”
• Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0) (2019, neutral): “In previous phases of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP; Warszawski et al., 2014; Frieler et al., 2017), climate simulation data were always more coarsely resolved than the climate observation data used for their bias adjustment, and the goal of this bias adjustment was”
• Joint bias correction of temperature and precipitation in climate model simulations (2014, methodology): “This cost is rather small compared to the benefits gained in the improved fidelity of the P-T correlations, especially in situations when the interaction of P-T is of interest, as is the case for many impact models [Tebaldi and Lobell, 2008; Bárdossy and Pegram, 2011; Warszawski et al., 2014].”
• Global water resources affected by human interventions and climate change (2013, background): “This study was conducted in the framework of the ISI-MIP project and the EU WATCH Integrated Project (Contract 036946), in collaboration with the Global Water System Project.”
• Multi-model ensemble projections of European river floods and high flows at 1.5, 2, and 3 degrees global warming (2017, methodology): “…from five GCMs (HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESMCHEM, GFDL-ESM2M and NorESM1-M) is used to force three HMs at the daily time scale for the period 1950–2099 under three RCPs (2.6, 6.0, and 8.5), which was made available by the ISI-MIP project (Warszawski et al 2014, Hempel et al 2013a).”
• Cross-validation of bias-corrected climate simulations is misleading (2018, methodology): “Bias correction is a widely used approach to postprocess climate model simulations before they are applied in impact studies (e.g. Gangopadhyay et al., 2011; Hagemann et al., 2013; Girvetz et al., 2013; Warszawski et al., 2014).”
• A protocol for an intercomparison of biodiversity and ecosystem services models using harmonized land-use and climate scenarios (2018, background): “, 2013), since it provides mid-range projections across the five GCMs (HadGEM2-ESGFDL-ESM2M, IPSL-CM5A-LR, MIROCESM-CHEM, and NorESM1-M) in ISIMIP2a (Warszawski et al., 2014).”
• Climate change impacts in Latin America and the Caribbean and their implications for development (2017, methodology): “The temperature, precipitation, evapo- transpiration and aridity projections are based on five CMIP5 GCMs (as selected by Warszawski et al. (2014), see Schellnhuber et al. 2014: Appendix A.1).”
• Tipping elements and climate–economic shocks: Pathways toward integrated assessment (2016, methodology): “We propose an alternative strategy for improving representation of state shifts in tipping elements that draws upon more disaggregated models of climate change impacts [e.g., Warszawski et al., 2014; Houser et al., 2015].”
• Intercomparison of regional-scale hydrological models and climate change impacts projected for 12 large river basins worldwide—a synthesis (2017, methodology): “The analysis was performed in the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) (www.isi-mip.org; Warszawski et al 2014) by an international team of regional-scale hydrological modellers.”
• Global exposure and vulnerability to multi-sector development and climate change hotspots (2018, methodology): “5◦, bias-corrected [65] to observed data [66], and were selected for coverage of the uncertainty range in temperature and precipitation variables from the CMIP5 models [23].”