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EN
Science-based knowledge about climate-related hazards is an inevitable part of the knowledge basis needed for many stakeholders’ decision-making. Despite continuous advances in climate science, much of this knowledge is perceived to be hardly accessible, understandable, or relevant to stakeholders. One relatively new field where these aspects may become evident is extreme weather event attribution. It has received much attention in science in recent years, but its potential usefulness to stakeholders has rarely been addressed in the literature so far. This study has therefore developed criteria for evaluating potential climate services from a stakeholder perspective, using the example of findings from extreme event attribution. This is illustrated in an empirical mixed-method study about decision-makers dealing with storm surge risks at the German Baltic Sea Coast and (re)insurance sector representatives. The study builds on interviews and workshops with potential users of extreme event attribution. It reveals that there are three main groups of criteria which matter most to the stakeholders in question: 1) trustworthiness, 2) context-sensitivity and decision-relevance, 3) clarity and comprehensibility. Having appropriate evaluation categories, as well as processes to identify stakeholder-specific criteria, will facilitate the inclusion of values, knowledge contexts, and interests. Many stakeholders emphasized that they need a trustworthy knowledge broker who provides decision-oriented information which is intuitively accessible, understandable, and in their mother tongue. Being independent, scientifically competent, and in a continuous dialogue with both scientists and stakeholders, established regional and sector-specific climate services can facilitate the fulfilment of these requirements. A stakeholder-oriented evaluation will thereby help to make climate services more useful to potential user groups – even if a product is not in use yet, as is the case for extreme event attribution products.
EN
We suggest to transfer the empirical downscaling methodology, which was developed mostly for atmospheric dynamics and impacts, to regional ocean problems. The major problem for doing so is the availability of decades-long and homogeneous and spatially detailed data sets. We have examined the performance of the STORM multidecadal simulation, which was run on a 0.1° grid and forced with 1950–2010 NCEP re-analyses, in the South China Sea and found the data suitable. For demonstration we build with this STORM-data downscaling model for the regional throughflow. The STORM data is compared with AVISO satellite observations and the ocean re-analysis dataset C-GLORS. We find the seasonal patterns and the inter-annual variability of sea surface height anomaly in both the C-GLORS data and the STORM simulation consistent with the AVISO-satellite data. Also the strong westward intensification and the seasonal patterns of South China Sea circulation steered by the monsoon have been presented well. As an important indicator of vertical movement, the sea surface temperature distribution maps are also very close, especially for the narrow upwelling region in summer. We conclude that the output of the STORM simulation is realistically capturing both the large-scale as well as the small-scale dynamical features in the South China Sea.
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