Abstract
This paper presents guidelines and examples of good practice for the usage of climate model simulation results and some rationale for their application. These guidelines are relevant to climate modellers as well as to climate impact modellers and users of direct climate model output, e.g., for decision support. The topics covered here encompass general information on climate model data as well as recommendations for their use, interpretation, and presentation. This includes subjects such as definition of ‘climate projection’ versus ‘climate forecast’, recommendations for the application of scenarios, temporal and spatial resolution, reference periods, treatment of model biases and significance, treatment of different model generations, and optimal use of colour selection and scaling. Special attention is given to results from multiple simulations (ensembles), as evidence is mounting that there is a need to take ensemble results into account for decision making. The paper represents the view of an ongoing discussion of German federal and state environmental agencies in a semi-annual meeting series and aims at framing a set of minimum requirements and prerequisites for climate impact projects and decision support. Thus, the recommendations we give are under constant further development and we don’t claim completeness. However, since we frequently are asked to share out our discussion results to other user groups we herewith provide some well discussed topics and hope to improve on the communication between the climate modellers and the users of climate model results.
Highlights
There is a major challenge in the communication between ‘producers’ a and ‘users’b of climate information: How can complex physical information be presented to users with little time and little physical background? This challenge is heightened (i) by the users’ expectations with respect to the accuracy of the information delivered and (ii) by the producers’ tendency to use a community-immanent ‘lingo’
Model cascade Two definitions occur frequently, the first of which applies to the topic of this paper. (i) As described above there are different strategies to achieve downscaling. They involve chains or cascades of models of different resolution. (ii) In the terminology of the IPCC, a chain or cascade of different kinds of models is employed when devising emission scenarios: Building upon model assumptions of economic development, a model transfers this information into greenhouse gas (GHG) emissions which are converted into atmospheric GHG concentrations using a carbon cycle model and determine the radiative forcing
ERA-INTERIM Reanalyses project (Dee et al, 2011) using T255 resolution in 60 vertical layers has been producing data for the period 1979–2010. It is considered the state-of-the-art for reanalysis-driven simulations of Regional Climate Models (RCM). 2. 20C: These runs of the Global Climate Models (GCM) aim to statistically reproduce the climate conditions of the 20th century. They are driven by all or a selection of (i) natural climate drivers: volcano eruptions and solar variability and (ii) anthropogenic climate drivers: aerosol contents and the equivalent radiative forcing due to GHG emissions as they occurred during that time
Summary
There is a major challenge in the communication between ‘producers’ a and ‘users’b of climate information: How can complex physical information be presented to users with little time and little physical background? This challenge is heightened (i) by the users’ expectations with respect to the accuracy of the information delivered and (ii) by the producers’ tendency to use a community-immanent ‘lingo’. En route to the IPCC’s 5th Report an Expert Meeting on Assessing and Combining Multi Model Climate Projections took place in Boulder, CO, in January 2010 (Stocker et al (Eds), 2010b) where the Good Practice Guidance Paper (Knutti et al, 2010) was consolidated It provides a treatment of numerous relevant issues including sets of recommendations for (i) ensembles, (ii) model evaluation, (iii) model selection, averaging and weighting, (iv) reproducibility and (v) regional assessments. (ii) In the terminology of the IPCC, a chain or cascade of different kinds of models is employed when devising emission scenarios: Building upon model assumptions of economic development, a model transfers this information into greenhouse gas (GHG) emissions which are converted into atmospheric GHG concentrations using a carbon cycle model and determine the radiative forcing (see definition below) This constitutes the input to a GCM that may be used to force an RCM. Data types There are four types of model-derived atmospheric data which need to be considered
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