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N. R. Kaye; A. Hartley; D. Hemming (2012)
Publisher: Copernicus Publications
Journal: Geoscientific Model Development
Languages: English
Types: Article
Subjects: QE1-996.5, Geology
Maps are a crucial asset in communicating climate science to a diverse audience, and there is a wealth of software available to analyse and visualise climate information. However, this availability makes it easy to create poor maps as users often lack an underlying cartographic knowledge. Unlike traditional cartography, where many known standards allow maps to be interpreted easily, there is no standard mapping approach used to represent uncertainty (in climate or other information). Consequently, a wide range of techniques have been applied for this purpose, and users may spend unnecessary time trying to understand the mapping approach rather than interpreting the information presented. Furthermore, communicating and visualising uncertainties in climate data and climate change projections, using for example ensemble based approaches, presents additional challenges for mapping that require careful consideration. The aim of this paper is to provide background information and guidance on suitable techniques for mapping climate variables, including uncertainty. We assess a range of existing and novel techniques for mapping variables and uncertainties, comparing "intrinsic" approaches that use colour in much the same way as conventional thematic maps with "extrinsic" approaches that incorporate additional geometry such as points or features. Using cartographic knowledge and lessons learned from mapping in different disciplines we propose the following 6 general mapping guidelines to develop a suitable mapping technique that represents both magnitude and uncertainty in climate data: <br><br> <p style="text-indent:1em;">&ndash; use a sensible sequential or diverging colour scheme;<br> <p style="text-indent:1em;">&ndash; use appropriate colour symbolism if it is applicable;<br> <p style="text-indent:1em;">&ndash; ensure the map is usable by colour blind people;<br> <p style="text-indent:1em;">&ndash; use a data classification scheme that does not misrepresent the data;<br> <p style="text-indent:1em;">&ndash; use a map projection that does not distort the data<br> <p style="text-indent:1em;">&ndash; attempt to be visually intuitive to understand. <br><br> Using these guidelines, we suggest an approach to map climate variables with associated uncertainty, that can be easily replicated for a wide range of climate mapping applications. It is proposed this technique would provide a consistent approach suitable for mapping information for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5).
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