Climateurope Festival: An innovative way of linking science and society

The Climateurope Festivals were designed to create synergies between different European, national and international initiatives in the fields of Earth-system modelling & Climate Services and enhance the transfer of information between suppliers and users. It gave an opportunity to display best in class outcomes and engage in world class networking in a less rigid environment than a scientific conference. A number of formats were adopted in the Festival, from traditional impulse talks to innovative interactive sessions, and the thought-provoking discussions allowed the participants to share their experiences and knowledge around the advantages and challenges that Climate Services face within different sectors. Three Climateurope Festivals were originally planned to be held across Europe. Two Festivals were successfully organised, the first in Valencia in 2017, and the second in Belgrade in 2018. Due to the COVID-19 pandemic and associated lockdowns and travel restrictions, the third and final Festival was held online as a series of virtual web-based Festivals in 2020/2021. The Festivals were highly valued by participants. There was a strong desire by the Climateurope network to continue a science-stakeholder dialogue and make the Climateurope Festivals a regular event.}The organization team of the Climateurope Festivals wishes to acknowledge and sincerely thank the entire consortium of Climateurope for their valuable support. Climateurope is funded by the European Commission through the Horizon 2020 Programme for Research and Innovation: Grant Agreement 689029.Peer Reviewed"Article signat per 14 autors/es: Lola Kotova, Maria Máñez Costa, Daniela Jacob, Chris Hewitt, Paula Newton, Natalie Garrett, Stacey New, Rebecca Parfitt, Tyrone Dunbar, Janette Bessembinder, Ralf Toumi, Mauro Buonocore, Aleksandra Krzic, Marta Terrado"Postprint (published version

Need for a common typology of climate services

A comprehensive typology or characterization of the various types of climate services is needed to give an overview that makes (potential) users aware of which climate services are available and where to look for them. It helps identify existing gaps in terms of unserved needs of the users. Different ways of characterizing climate services are used in practice. The factors used for this characterization differ depending on the intended application of the service, the delivery mechanism and project- or user-specific needs. In this paper we discuss the advantages and challenges of using different characterization factors, such as sectors, themes, regions, purposes, time horizons, data sources, level of processing of climate data, background knowledge and type of climate services providers. Some recommendations are given on the factors to use for a common typology of climate services which are understood by a wide range of users. It may be difficult to create a single common typology that will also be understood by users with little background knowledge on climate data. Intermediaries, providing training resources and guidance at web portals on how to use and interpret climate information, can be essential to overcome this problem. Gap analysis is used to compare available and required climate services. Therefore, we advise to use the same typology for the analysis of gaps in available climate services

Evaluation of regional climate models ALARO-0 and REMO2015 at 0.22 degrees resolution over the CORDEX Central Asia domain

To allow for climate impact studies on human and natural systems, high-resolution climate information is needed. Over some parts of the world plenty of regional climate simulations have been carried out, while in other regions hardly any high-resolution climate information is available. The CORDEX Central Asia domain is one of these regions, and this article describes the evaluation for two regional climate models (RCMs), REMO and ALARO-0, that were run for the first time at a horizontal resolution of 0.22 degrees (25 km) over this region. The output of the ERA-Interim-driven RCMs is compared with different observational datasets over the 1980-2017 period. REMO scores better for temperature, whereas the ALARO-0 model prevails for precipitation. Studying specific subregions provides deeper insight into the strengths and weaknesses of both RCMs over the CAS-CORDEX domain. For example, ALARO-0 has difficulties in simulating the temperature over the northern part of the domain, particularly when snow cover is present, while REMO poorly simulates the annual cycle of precipitation over the Tibetan Plateau. The evaluation of minimum and maximum temperature demonstrates that both models underestimate the daily temper-ature range. This study aims to evaluate whether REMO and ALARO-0 provide reliable climate information over the CAS-CORDEX domain for impact modeling and environmental assessment applications. Depending on the evaluated season and variable, it is demonstrated that the produced climate data can be used in several subregions, e.g., temperature and precipitation over western Central Asia in autumn. At the same time, a bias adjustment is required for regions where significant biases have been identified

Wheat yield estimation from NDVI and regional climate models in Latvia

Wheat yield variability will increase in the future due to the projected increase in extreme weather events and long-term climate change effects. Currently, regional agricultural statistics are used to monitor wheat yield. Remotely sensed vegetation indices have a higher spatio-temporal resolution and could give more insight into crop yield. In this paper, we (i) evaluate the possibility to use Normalized Difference Vegetation Index (NDVI) time series to estimate wheat yield in Latvia and (ii) determine which weather variables impact wheat yield changes using both ALARO-0 and REMO Regional Climate Models (RCM) output. The integral from NDVI series (aNDVI) for winter and spring wheat fields is used as a predictor to model regional wheat yield from 2014 to 2018. A correlation analysis between weather variables, wheat yield and aNDVI was used to elucidate which weather variables impact wheat yield changes in Latvia. Our results indicate that high temperatures in June for spring wheat and in July for winter wheat had a negative correlation with yield. A linear regression yield model explained 71% of the variability with a residual standard error of 0.55 Mg/ha. When RCM data were added as predictor variables to the wheat yield empirical model a random forest approach resulted in better results compared to a linear regression approach, the explained variance increased up to 97% and the residual standard error decreased to 0.17 Mg/ha. We conclude that NDVI time series and RCM output enabled regional crop yield and weather impact monitoring at higher spatio-temporal resolutions than regional statistics

Service life prediction of building components in the times of climate change

Buildings components and assemblies are prone to decay over time due to the inherent characteristics of the materials, environmental conditions and operational use of them. For this reason, it is very important to know the right time and type of maintenance and adaptation interventions that need to be applied to the specific compounds. The answer to the above issue can be given through the service life prediction (SLP) of the components by using standardized calculation methods. In historic buildings, the process of SLP takes significant importance because these buildings hold non-renewable cultural heritage value and therefore, the interventions should be performed in a way that preserves the original material and value while enhancing the service life. Nowadays, for such buildings that are predicted to live for centuries, the SLP needs to be corrected by considering the effects of climate change in the construction materials. The paper presents an overview of the application of the well-known factor method in the estimation of the serviceability of the building components, with a special focus on historic buildings impacted by climate change. The technical compatibility, economic viability, use of the building and the indoor/outdoor environments are considered during the assessment of the service life which is strictly linked with the level of decay. It gives a short explanation of the factors that constitute the method by including the effects of climate change and an example of application to a specific case study in Norway

Regionale Klimaprojektionen für Europa und Deutschland: Ensemble Simulationen für die Klimafolgenforschung

Der Bericht enthält eine Übersicht zu regionalen Klimaprojektionen des Max-Planck-Instituts für Meteorologie (MPI-M), des Climate Service Center (CSC) und weiterer Forschungsinstitutionen, die im Rahmen verschiedener internationaler und nationaler Forschungsprojekte und Aktivitäten erstellt wurden. Es werden Arbeiten mit dem Schwerpunkt Deutschland dargestellt. Zur Interpretation der Ergebnisse ist es notwendig, die Methodik zur Erstellung regionaler Klimaprojektionen in die Betrachtung mit einzubeziehen. Diese wird in einem einleitenden Kapitel kurz vorgestellt, mit Verweisen auf weiterführende Informationen und Veröffentlichungen. Dabei werden auch Möglichkeiten und Grenzen regionaler Klimamodellierung aufgezeigt. Es werden die Simulationen und einige Beispielergebnisse der einzelnen Projekte (ENSEMBLES, KLIWAS, KLIFF, KLIMZUG-NORD) vorgestellt. Die Projekte widmen sich verschiedenen geografischen Regionen und Themenschwerpunkten