This section contains the public deliverables (PU) produced by CLIM-RUN consortium and already approved by the EU revisers. Deliverables meant for other programme participants (PP), that do not have sensible data, already approved by the EU revisers are also included in this section.
Global Circulation Models (GCMs) are sophisticated tools based on basic laws of physics to simulate the climate system. In comparison to the first GCMs, the performance of these models has improved over the last decades taking into account different parameterizations and including additional climate components (carbon cycle, aerosols, etc) and atmosphere interactions with landuse and vegetation between others. Despite the increasing ability to successfully model present-day climate, the latest generation of GCMs still has serious difficulties in capturing regional variability details in smaller regions (Räisänen, 2007; Errasti et al., 2011). The coarse resolution of the GCMs to study the regional or local characteristics makes necessary the application of particular regionalization approaches also known as downscaling methods. Different downscaling techniques have therefore been developed as tools for interpolating large-scale information into a local or regional scale (Wilby and Wigley, 1997). Depending on the criterion considered, two general approaches have been developed in downscaling: dynamical and statistical downscaling. On the one hand, dynamical downscaling techniques are based on the integration over a limited area of high spatial resolution regional climate models (RCMs), driven at their boundaries by the outputs from GCMs (Rummukainen, 2010). On the other hand, the statistical downscaling methods are based on a statistical model that takes into account empirical relationships between large (used as predictors) and local scale variables (Zorita and von Storch, 1999). Statistical downscaling is nowadays a sound and mature field that can be applied to outputs from different GCM experiments as long as historical data are available for the region of interest. Another advantage of this approach is the inexpensive computational burden. These two aspects have been considered in the statistical downscaling portal (https://www.meteo.unican.es/downscaling/climrun) developed by the Santander Meteorology group from the University of Cantabria (see the user guide by Gutiérrez et al, 2011 and the deliverable 3.2 from the CLIM-RUN project). The portal has been adapted to the CLIM-RUN project needs and it is currently available for all the partners. This is an interactive user-friendly tool to ease the downscaling process for end users, thus maximizing the exploitation of the available climate projections (see the deliverable 3.2 for more details).
Authors: M. D. Frías, A. Casanueva, C. Giannakopoulos, C. Goodess, M. A. Lange, A. Karali and M. Hatzaki
Many stakeholders request local climate information to assess the relationships between climate forcing and impacts on ecosystems in different sectors. The term ‘transfer function’ within the CLIMRUN project refers to functions, mathematical equations or relations that link pure meteorological and climatic variables with impacts on activity sectors. As such they can be seen as simple impact models for several economic sectors and activities such as tourism, human comfort, fire risk and energy demand. Other definitions for transfer functions, for example in relation to proxy reconstructions and downscaling, also exist, but in CLIMRUN the above definition has been used to describe the use of transfer functions.
Authors: Christos Giannakopoulos(NOA), Ioannis Lemesios (NOA),Manfred A. Lange (CyI) and Panos Hadjinicolaou (CyI)
Many stakeholders request local climate information to assess the relationships between climate forcings and impacts on ecosystems in different sectors (fire, agriculture, tourism, energy, etc). However, General Circulation Models (GCMs) are not able to produce future climate scenarios at the proper scale required for the different impact-orientated applications. An approach to bridge the gap between the coarse resolution of the global models and the high resolution required by end-user applications is the downscaling (dynamical or statistical downscaling).
Authors: A. Casanueva, J. Bedia, S. Herrera, M. D. Frías, J. M. Gutierrez, C. Giannakopoulos, A. Karali and K. Zaninovic
Since many of the largest impacts of climate change on natural and human systems are likely to be due to changes in the frequency and intensity of extreme weather and climate events, it is not surprising that a strong demand for information about these events emerged from the first round of stakeholder workshops held in each of the CLIM-RUN case- study locations. In part, this demand was anticipated and the CLIM-RUN questionnaire produced by Workpackage 4 included questions concerning the current use of information about extremes as well as the desire for future predictions and projections for events such as heavy rainfall, frosts, heatwaves and very hot days/nights.
Authors: Richard Cornes, Clare Goodess, Ana Casanueva, Erika Coppola, Alessandro Dell’Aquila, Clotilde Dubois, M. Dolores Frías, Jose Manuel Gutiérrez, S. Herrera
This document provides a users’ guide for organising the first round of CLIM-RUN stakeholder workshops. It hopefully provides a ‘one-stop shop’ for recommendations, information and resources for work and activities before, during and after the workshops. It has been produced by WP4, based on discussions with other WPs and the Executive Committee, and draws heavily on the early work done by WP7.
Authors: Clare Goodess (UEA)
This deliverable, D4.2, provides a summary and synthesis of the workshops that have taken place (Section 2) together with an assessment of the utility of D4.1 in general (Section 3) and the perception questionnaire in particular (Section 4). Section 5 summarises stakeholder engagement to date, while Section 6 considers how this can be continued. Section 7 summarises the ongoing work on ‘translating’ user needs. Finally, the summary and conclusions (Section 8) consider how work during the first key stages could be modified or improved (and thus potential modifications to the emerging CLIM-RUN protocol).
Authors: Clare Goodess (UEA)
This deliverable, D4.3, provides a summary and synthesis of the second round workshops. Section 2 provides summary information about the number, location and content of the workshops. Section 3 outlines the planning process and support provided while Section 4 considers the use of participatory methods and tools. Section 5 discusses feedback on the presented CLIM-RUN products and tools. Section 6 comments on the process of translating and meeting user needs and Section 7 considers issues relating to continuing stakeholder engagement. Finally, Section 8 provides some concluding remarks.
Authors: Clare Goodess (UEA). Based on WP5-WP8 workshop reports. Reviewed by Cedo Brankovic, Adeline Cauchy, Melanie Davis, Christos Giannakopoulos and Valentina Giannini
The two rounds of stakeholder workshops held in each of the case-study locations have played a major and critical role in CLIM-RUN. A synthesis of the first round workshops is provided in Deliverable D4.2 and of the second round workshops in Deliverable D4.3. These two documents provide important background material for producing D4.4.
Authors: Clare Goodess (UEA)
The purpose of this report is to review existing methodologies for assessing the socioeconomic impacts of climate change and the potential benefits of adaptation. The report complements the other activities of CLIM-RUN Work Package 4 by providing an overview of the methodologies used to estimate the socioeconomic consequences of climate change (usually in terms of monetary valuation), paying particular attention to the Mediterranean region. It also adds value by including three case studies (tourism, forest fires and energy demand) that make use of data gathered as part of the CLIM-RUN project. The report is primarily concerned with the impacts of long-term climate change rather than seasonal to decadal forecasts, although Section 3 (on climate information and climate services) is relevant at the decadal and subdecadal level.
Authors: Miles Perry; Daniele Paci (Institute for Prospective Technological Studies-Joint Research Center, IPTS-JRC)
Tourism is one of the most important economic sectors in Croatia, contributing to more than 15% of the country’s total GDP. It relies heavily upon the country’s rich variations of local climates which are influenced by the mid‐latitudes atmospheric circulation and geographical factors. Tourism is primarily developed in the Adriatic area (coast, islands) during summer with much reduced share of the continental Croatia (the capital, national parks, winter tourism). The summer tourist season in Croatia is, however, relatively short, mainly because the sea water is colder when compared to some other (southern) Mediterranean destinations. Within the climate change framework, the two major groups of the tourism sub‐sectors with different adaptive capacity to climate change will emerge. The first group with high adaptive capacity comprises tourists, tour operators and transport providers; the second group with low adaptive capacity is tourism infrastructure (made of local hotels and resorts) and local communities.
Authors: Čedo Branković (DHMZ), Marjana Gajić-Čapka (DHMZ), Ksenija Zaninović (DHMZ)