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:
– use a sensible sequential or diverging colour scheme;
– use appropriate colour symbolism if it is applicable;
– ensure the map is usable by colour blind people;
– use a data classification scheme that does not misrepresent the data;
– use a map projection that does not distort the data
– attempt to be visually intuitive to understand.
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). |