Abstract. 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).
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. 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. <br> This paper assesses a range of techniques for mapping uncertainties, comparing "intrinsic" approaches that use colour in much the same way as conventional thematic maps, and "extrinsic" approaches that incorporate additional geometry such as points or features. We proposes that, 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. <br> We use cartographic knowledge and lessons learned from mapping other information to propose a suitable mapping technique that represents both magnitude and uncertainty in climate data. This technique adjusts the hue of a small palette of colours to show the mean or median of a climate variable, and the saturation of the colour to illustrate a measure of uncertainty. It is designed to be easy to replicate, visible to colour blind people and intuitive to understand. This technique may be utilised to map a wide range of climate data, and it is proposed that it would provide a consistent approach suitable for mapping information for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5)
The projection of robust regional climate changes over the next 50 years presents a considerable challenge for the current generation of climate models. Water cycle changes are particularly difficult to model in this area because major uncertainties exist in the representation of processes such as large-scale and convective rainfall and their feedback with surface conditions. We present climate model projections and uncertainties in water availability indicators (precipitation, run-off and drought index) for the 1961-1990 and 2021-2050 periods. Ensembles from two global climate models (GCMs) and one regional climate model (RCM) are used to examine different elements of uncertainty. Although all three ensembles capture the general distribution of observed annual precipitation across the Middle East, the RCM is consistently wetter than observations, especially over the mountainous areas. All future projections show decreasing precipitation (ensemble median between −5 and −25%) in coastal Turkey and parts of Lebanon, Syria and Israel and consistent run-off and drought index changes. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) GCM ensemble exhibits drying across the north of the region, whereas the Met Office Hadley Centre work Quantifying Uncertainties in Model Projections-Atmospheric (QUMP-A) GCM and RCM ensembles show slight drying in the north and significant wetting in the south. RCM projections also show greater sensitivity (both wetter and drier) and a wider uncertainty range than QUMP-A. The nature of these uncertainties suggests that both large-scale circulation patterns, which influence region-wide drying/wetting patterns, and regional-scale processes, which affect localized water availability, are important sources of uncertainty in these projections. To reduce large uncertainties in water availability projections, it is suggested that efforts would be well placed to focus on the understanding and modelling of both large-scale processes and their teleconnections with Middle East climate and localized processes involved in orographic precipitation.
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