Abstract

Evaluating a climate model’s fidelity (ability to simulate observed climate) is a critical step in establishing confidence in the model’s suitability for future climate projections, and in tuning climate model parameters. Model developers use their judgement in determining which trade-offs between different aspects of model fidelity are acceptable. However, little is known about the degree of consensus in these evaluations, and whether experts use the same criteria when different scientific objectives are defined. Here, we report on results from a broad community survey studying expert assessments of the relative importance of different output variables when evaluating a global atmospheric model’s mean climate. We find that experts adjust their ratings of variable importance in response to the scientific objective, for instance, scientists rate surface wind stress as significantly more important for Southern Ocean climate than for the water cycle in the Asian watershed. There is greater consensus on the importance of certain variables (e.g., shortwave cloud forcing) than others (e.g., aerosol optical depth). We find few differences in expert consensus between respondents with greater or less climate modeling experience, and no statistically significant differences between the responses of climate model developers and users. The concise variable lists and community ratings reported here provide baseline descriptive data on current expert understanding of certain aspects of model evaluation, and can serve as a starting point for further investigation, as well as developing more sophisticated evaluation and scoring criteria with respect to specific scientific objectives.

Highlights

  • A critical aspect of any climate modeling research is an evaluation of the realism, or fidelity, of the model’s simulated climate through a careful comparison with observational data

  • Since expert judgement cannot be fully eliminated from the model evaluation process, we propose that it would be valuable to better understand and quantify the relative importance climate modelers assign to different aspects of model fidelity when making decisions about trade-offs

  • We conducted a large international survey of climate model developers and users, and asked them to indicate their view of the relative importance of a subset of variables used in assessing model fidelity, in the context of particular scientific goals

Read more

Summary

Introduction

A critical aspect of any climate modeling research is an evaluation of the realism, or fidelity, of the model’s simulated climate through a careful comparison with observational data. Comparisons of model fidelity across multiple model simulations are carried out in multi-model intercomparison projects (e.g., Gleckler et al, 2008; Reichler and Kim, 2008), and in perturbed parameter ensemble experiments for the purpose of quantifying model uncertainty or sensitivities (Yang et al, 2013; Qian et al, 2015, 2016) Such studies aim to understand what factors lead to inter-model diversity and CHARACTERIZING CLIMATE VARIABLE IMPORTANCE. This paper reports on our first step towards this long-term goal: the establishment of a baseline understanding of the level of importance that experts explicitly state they assign to different variables when evaluating the mean climate state of the atmosphere of a climate model To this end, we conducted a large international survey of climate model developers and users, and asked them to indicate their view of the relative importance of a subset of variables used in assessing model fidelity, in the context of particular scientific goals.

Survey design and methods
Formal consensus measure
Survey results and discussion
Science Driver 1
Science Driver 2
Science Driver 3
Science Driver 4
Science Driver 5
Science Driver 6
Impact of experience on judgments of variable importance
Impact of Science Drivers on judgments of variable importance
Perceived barriers to systematic quantification of model fidelity
Findings
Summary and conclusions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call