Assessing the impacts of 1.5 °C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b)

Abstract

Abstract. In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a "special report in 2018 on the impacts of global warming of 1.5 • C above pre-industrial levels and related global greenhouse gas emission pathways". In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5 • C, including a potential overshoot and longterm impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the lowemissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across different sectors (global and regional hydrology, lakes, global crops, global vegetation, regional forests, global and regional marine ecosystems and fisheries, global and regional coastal infrastructure, energy supply and demand, temperature-related mortality, and global terrestrial biodiversity).

Global soil organic carbon removal by water erosion under climate change and land use change during AD 1850–2005

“…We chose these data as input to the Adj.RUSLE model, because the dataset extended to 1850, in contrast to the CRU-NCEP data. Also, this dataset being bias corrected provides a better distribution of extreme events and frequencies of dry and wet days (Frieler et al, 2017), which is important for the calculation of rainfall erosivity (R factor). The ISIMIP precipitation data were regridded using the bilinear interpolation method to the resolution of the Adj.RUSLE model, before being used to calculate the R factor.…”

“…Daily precipitation data for the period 1850-2005 to calculate soil erosion rates is derived from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), product ISIMIP2b (Frieler et al, 2017). These data are based on model output of the Coupled Model Intercomparison Project Phase 5 (CMIP5 output of IPSL-CM5A-LR (Taylor et al, 2012), which are bias corrected using observational datasets and the method of Hempel et al (2013) and made available at a resolution of 0.5 • (Fig.…”

A global historical data set of tropical cyclone exposure (TCE-DAT)

“…Data from 2010 onwards are based on national GDP time series according to the Shared Socioeconomic Pathways (SSP2) (Dellink et al, 2017;Frieler et al, 2017;Geiger et al, 2017b). Grid-level GDP is downscaled from national GDP estimates, using spatially explicit population estimates and multiple other predictors, e.g., distance to cities and to the coast, road network densities, and others .…”

Continuous national Gross Domestic Product (GDP) time series for 195 countries: past observations (1850–2005) harmonized with future projections according to the Shared Socio-economic Pathways (2006–2100)

“…The Maddison Project data base 25 thereby constitutes the foundation of the period mostly before 1960 while Penn World Table ( The long record and complete coverage enhance the data set's usability. It is has already been assigned as input data for the 30 current climate change impact model runs within the global Inter-sectoral Impact Model Inter-comparison Project (ISIMIP2b, www.isimip.org) [Frieler et al, 2016], and has been used in a downscaling approach to provide spatially-explicit economic information on the grid level [Murakami, D. and Yamagata, 2017] that can e.g. be used to quantify economic values exposed to climate extremes [Geiger et al, 2017].…”

“…in the field of climate impact research in order to facilitate impact simulations on centennial time 15 scales [Frieler et al, 2016]. It further provides the opportunity to generate gridded GDP distributions for the past based on recent downscaling initiatives [Murakami, D. and Yamagata, 2017].…”