Search Results

Now showing 1 - 3 of 3
Loading...
Thumbnail Image
Item

Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response

2020, Nicholls, Zebedee R. J., Meinshausen, Malte, Lewis, Jared, Gieseke, Robert, Dommenget, Dietmar, Dorheim, Kalyn, Fan, Chen-Shuo, Fuglestvedt, Jan S., Gasser, Thomas, Golüke, Ulrich, Goodwin, Philip, Hartin, Corinne, Hope, Austin P., Kriegler, Elmar, Leach, Nicholas J., Marchegiani, Davide, McBride, Laura A., Quilcaille, Yann, Rogelj, Joeri, Salawitch, Ross J., Samset, Bjørn H., Sandstad, Marit, Shiklomanov, Alexey N., Skeie, Ragnhild B., Smith, Christopher J., Smith, Steve, Tanaka, Katsumasa, Tsutsui, Junichi, Xie, Zhiang

Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

Loading...
Thumbnail Image
Item

The PRIMAP-hist national historical emissions time series

2016, Gütschow, Johannes, Jeffery, M. Louise, Gieseke, Robert, Gebel, Ronja, Stevens, David, Krapp, Mario, Rocha, Marcia

To assess the history of greenhouse gas emissions and individual countries' contributions to emissions and climate change, detailed historical data are needed. We combine several published datasets to create a comprehensive set of emissions pathways for each country and Kyoto gas, covering the years 1850 to 2014 with yearly values, for all UNFCCC member states and most non-UNFCCC territories. The sectoral resolution is that of the main IPCC 1996 categories. Additional time series of CO2 are available for energy and industry subsectors. Country-resolved data are combined from different sources and supplemented using year-to-year growth rates from regionally resolved sources and numerical extrapolations to complete the dataset. Regional deforestation emissions are downscaled to country level using estimates of the deforested area obtained from potential vegetation and simulations of agricultural land. In this paper, we discuss the data sources and methods used and present the resulting dataset, including its limitations and uncertainties. The dataset is available from doi:10.5880/PIK.2016.003 and can be viewed on the website accompanying this paper (http://www.pik-potsdam.de/primap-live/primap-hist/).

Loading...
Thumbnail Image
Item

PRIMAP-crf: UNFCCC CRF data in IPCC 2006 categories

2018, Jeffery, M. Louise, Gütschow, Johannes, Gieseke, Robert, Gebel, Ronja

All Annex I Parties to the United Nations Framework Convention on Climate Change (UNFCCC) are required to report domestic emissions on an annual basis in a “Common Reporting Format” (CRF). In 2015, the CRF data reporting was updated to follow the more recent 2006 guidelines from the IPCC and the structure of the reporting tables was modified accordingly. However, the hierarchical categorisation of data in the IPCC 2006 guidelines is not readily extracted from the reporting tables. In this paper, we present the PRIMAP-crf data as a re-constructed hierarchical dataset according to the IPCC 2006 guidelines. Furthermore, the data are organised in a series of tables containing all available countries and years for each individual gas and category reported. It is therefore readily usable for climate policy assessment, such as the quantification of emissions reduction targets. In addition to single gases, the Kyoto basket of greenhouse gases (CO2, N2O, CH4, HFCs, PFCs, SF6, and NF3) is provided according to multiple global warming potentials. The dataset was produced using the PRIMAP emissions module. Key processing steps include extracting data from submitted CRF Excel spreadsheets, mapping CRF categories to IPCC 2006 categories, constructing missing categories from available data, and aggregating single gases to gas baskets. Finally, we describe key aspects of the data with relevance for climate policy: the contribution of NF3 to national totals, changes in data reported over subsequent years, and issues or difficulties encountered when processing currently available data. The processed data are available under an Open Data CC BY 4.0 license, and are available at https://doi.org/10.5880/pik.2018.001.