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In Chile, in the last 20 years, significant changes have led to a notoriously warmer climate, which translates into meteorological records being recorded every year. For this reason, it is increasingly necessary for the National Meteorological Service to have reliable data to respond to the information needs of society and stakeholders.Changes and modifications in meteorological stations, such as relocations, instruments, and environmental changes, can alter the estimation of means and long-term trends. Data homogenization consists of correcting these abrupt changes that are not associated with climate through different statistical methods to obtain reliable estimates. The most widely used homogenization methods are the relative ones, consisting of creating reference series from nearby stations, assuming they have the same long-term climatic signal.In this work, the changing points of daily series of extreme temperatures were evaluated for 17 meteorological stations in Chile in the period 1961-2021. The segmentation method available in the R GNSSfast library was applied to the difference between a candidate series and a reference series created from neighboring stations. The correction of the inhomogeneous series was done through the difference in the daily median of the different segments, taking the most current period as a reference.A total of 15 changepoints were detected in both minimum and maximum temperatures for 11 measurement stations, where 3 and 4 points were explained with dates of changes in the metadata, respectively. The most significant differences in the trend estimation with and without homogenization were observed in the weather stations of the country's central zone.

Under the current climate change situation, the Mediterranean region has been identified as one of the primary hot-spots, expecting not only to become warmer, but also drier during the twenty-first century. Changing conditions also include an increase in the frequency of intense torrential rainfall events, whose occurrence has already caused increasing flash flood events with catastrophic impacts and human casualties. The understanding of the past extreme events is challenging and useful to deal with the current situation.During November 1617 an extreme rain event has been documented by previous studies in a large latitudinal region from southern France to eastern river basins of the Iberian Peninsula (Thorndycraft et al., 2006). Here we present new evidences of the large-scale impact of this extreme event based on a multi-proxy approach. On the one hand, the occurrence of this event is interpreted by means of a flood cave horizon detected in a speleothem from Mallorca (Balearic Islands). On the other hand, historical documents depict this event also in some localities of Pyrenees, enhancing its longitudinal occurrence.Through the integration with previous climate, paleohydrological and qualitative hydrometeorological reconstructions, we try to understand the complex atmospheric mechanisms that caused this event during the Little Ice Age.

Climate strongly impacts socio-ecologic systems. Increasing the intensity and frequency of heatwaves is one of its major consequences. Heatwaves are periods of consecutive days when temperatures are much hotter than normal. Cities are especially affected because their impact is usually aggravated by the Urban Heat Island (UHI), an intrinsic phenomenon that increases urban temperatures compared to surrounding rural areas. Extreme hot temperatures affect urban areas causing health problems, increasing energy requirements, and altering water supplies, among others. Heatwaves have been studied in Argentina but this has not been updated for the whole country recently. Due to these impacts on people’s well-being, infrastructure, and ecosystem functioning, this work proposes to study changes in spatial distribution and frequency of heatwaves in Argentina. We use the ERA5 LAND dataset and the HeatWaver R package to identify heatwaves over mainland Argentina. For the purpose of this study, we define heatwaves as periods where maximum and/or minimum temperatures are above the 90th percentile of the WMO standard reference period (1961-1990) during five or more consecutive days. We inspect the temporal and spatial extent of the phenome and monitor its changes over time. In agreement with global warming tendencies, heatwaves are more frequent, and a larger portion of the country has been under stress in recent years. We also inspect the heterogeneous impact over the territory and large cities. To understand the impact of heatwaves in cities, it is crucial to evaluate the risk, which is the conjunction of hazards, exposure and vulnerability. As a first step, this work studies heatwaves as hazards while those other aspects will be incorporated into future research. Our final objective is to reach an urban heatwave risk index, combining meteorological, environmental, urban, and social aspects. This indicator would liaise climate science with local and regional policies and offer information for adaptation and mitigation policies to face climate variability and change. Keywords: heatwaves, cities, climate change, Argentina.

INDECIS (Integrated approach for the development across Europe of user-oriented climate indicators for GFCS high-priority sectors: agriculture, disaster risk reduction, energy, health, water, and tourism) was a project part ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union Grant 690462). INDECIS main produced different outcomes, such as software packages, improved datasets and a large number of scientific papers (see www.indecis.eu). Even though INDECIS formally ended in July 2021, the knowledge gained continues to pay off. This communication will synthetically show how we took advantage of the methodology for the engagement of stakeholders developed in INDECIS (Font et al. 2021). The co-creation methodology developed in the frame of INDECIS has served as a starting point for the development of further research, transfer, and empowerment actions of stakeholders for decision-making related to climate change in four main axes: in research, in leading international research and transfer projects in collaboration with industry, in local projects developed in partnership with industry, users and administration and, knowledge transference to high schools, bachelor degree and technical training to professionals. The research has continued through a doctoral dissertation based on co-creating a climate service for surfing (see Boqué Ciurana, 2022). It is also continued by developing more indices for tourism and tourism sites to face climate change effects through mitigation measures in the TURLIT-ODS project (see: http://turlit.eu). This project is a local scale project where with users, private actors, and administration, we try to define the optimal conditions to develop sport water activities in Calafell, Costa Daurada, Spain. With the industry, in collaboration with a private organization, we engage stakeholders in the infrastructure sector to co-define climate risk indices to manage risk and investments. In this project, through co-creation workshops developed with local agents from both the company (technical) and the administration and other sectorial actors, indices are being computed to assess the climate risk of mobility infrastructures (railways and highways). The co-creation methodology has been adapted to develop high school co-creation processes to empower young people with tools to fight climate change and misinformation (see EMPOCLIM project: http://www.empoclim.cat ). In the same way, the Geography, Sustainability, and Territorial Analysis bachelor at the Rovira i Virgili University, offers a subject (6 ECTS) to develop essential skills and competences for developing climate services based on the engagement of local stakeholders and co-creation. Last but not least. Updating the quality control and data homogenization software has allowed the development of training for NMHs in Colombia, Peru, and Chile in the frame of the ENANDES project. In this training, we added lectures and practices to capacity-building staff in co-creating climate services with local users.

Coastal Tourist destinations need to adapt to climate variability and change to maintain their tourist competitiveness and appeal. To do this, it is crucial to know the climatic potential of the activities which the destination offers and to manage the location’s natural resources. The Sustainable development goals (SDG) offer guidelines for the development of a tourist destination. In the TURLIT-ODS project, we aim to contribute directly to SDG 3, Good health and well being; SDG 8, decent work and economic growth; SDG 12, Responsible consumption and production and SDG 13, Climate Action.The last decades have seen advances in climate services for multiple fields. Despite this, the determination of the expected optimal days for different nautical sports activities around the central-western Mediterranean has not been done yet.The present research explores, through a co-creation process with local agents, how the atmospheric/oceanic conditions influence nautical sports activity development. With the gained knowledge, we computed the optimal expected days for the specific activities identified by the stakeholders using ocean buoy data and wind and wave data from the SIMAR numerical model owned by Puertos del Estado.Thanks to this approach, we transform raw data into structured information to provide the knowledge of optimal expected days for different nautical sports activities: sailing, stand-up paddling, kayaking, windsurfing, swimming in open waters, diving, snorkeling, water walking, underwater fishing, SUP- yoga, rowing, kitesurfing, surfing, wing foil, jet ski and other recreative uses (like the banana boat).The computation of the optimal days for each one of these activities along Tarragona’s province coast allows us to understand the availability of that conditions and assist decision-making by looking at information that facilitates the definition of diversification strategies of the tourist activities.By considering the meteorological-oceanographical conditions of a territory and, according to the results related to a destination, new tourist products and/or redesigned products offered are depicted. In this way, the destination of Tarragona’s province makes a step closer to the path of the sustainability of their leisure and tourist activities settled on the shore.We acknowledge Diputació Provincial de Tarragona for funding the project TURLIT (T22240S), Puertos del Estado (Ministry of Transport, Mobility and Urban Agenda of Spain), which provided the data for this study, and the Municipality of Calafell for supporting the project and facilitating spaces to generate the co-creation process.

Despite the evidences of the effects of climate change, and the need to adopt adaptation and mitigation measures against its effects, it still exists a significant current of denialism . Radio podcasts, an evolution of classical radio shows, are an interesting communication and leisure tool for disseminating climate misinformation in today's saturated communication world.In the framework of the CLIMACAST: UNDERSTANDING AND EXPOSING CLIMATE MISINFORMATION ON PODCASTS project, we monitor, identify, verify and disseminate short notes to fight this climate misinformation. Currently, the project is in the middle of its execution; and we have monitored monitoring more than a thousand hours of podcasts in Spanish-speaking countries from July to December of 2022. The project, funded by META and Poynter’s International Fact-Checking Network is a joint collaboration between C3/IU-RESCAT/URV, VERIFICAT and Kinzen and Chequeados.The climate misinformation measure unit of this project is a climate claim. A claim is the smallest unit of analysis of verifiable information containing a disputed claim about climate, climate variability and climate change. In addition, to be considered a claim, the information or meaning included in the message should be verifiable content. To track problematic terms, the editors of Verificat monitor podcasts where people post climate disinformation to detect recurring words or phrases in this area to define keywords to find the podcasts. When the podcasts are selected, an artificial intelligence tool transcribes them to a specifically designed dashboard. If it detects problematic content - for example, the word 'calentólogo' (warmist) is typical of negationist slang - the system highlights the keyword for greater detection by analysts. The analyst checks if the keyword refers to some climate and/or meteorological aspect. Then, the analyst determines the content's verifiability based on the message's real climate disinformation. Each claim identified is classified in six main narratives: the main misinformation: climate change does not exist, climate change is not human-caused, climate change is not bad, solutions to face climate change do not work, climate science is not liable and greenwashing.The results show how the claims are regularly identified in regular podcasts. However, it also shows slight growth in the two weeks of COP27.

This research presents a case study of the biases and discontinuities that were introduced in observed long-term mean wind-speed and gust data-series due to anemometer changes in a meteorological station in northern Spain, operated by the Spanish State Meteorological Agency: San Sebastian-Igueldo. Field and wind-tunnel experiments with predefined conditions have been presented in the literature, however this research uses a real case study to assess the impact of anemometer changes on wind speed measurements due to three factors being: (i) the 3-cup anemometer model (SEAC vs. THIES companies); (ii) sensor height (∼19.95 m vs. ∼20.45 m) and (iii) sensor age (20-years old vs. new). Our results show (a) substantial biases in the measured wind speed and daily peak wind gusts, with the new THIES anemometer reporting stronger surface winds than the old SEAC anemometer; (b) opposing biases under weak (negative) and moderate-strong (positive) winds; and (c) significant breakpoints in the long-term wind data-series, which highlight the importance of data homogenization. National Weather Services and climate assessment groups will benefit from these findings since errors in wind speed and gust measurements can be minimized by implementing systematic observation protocols. Robust anemometer observations provide a basis for accurate quantification of the magnitude of changes and the variability of surface winds. This research was funded by the following projects: IBER-STILLING (RTI2018–095749-A-I00, MCIU/AEI/FEDER,UE); VENTS (GVA-AICO/2021/023) and the CSIC Interdisciplinary Thematic Platform (PTI) Clima (PTI-CLIMA).

[EN] Most studies on wind variability have deepened into the stilling vs. reversal phenomena at global to regional scales, while the long-term changes in local-scale winds such as sea-breezes (SB) represent a gap of knowledge in climate research. The state-of-the-art of the wind variability studies suggests a hypothetical reinforcement of SB at coastal stations. We frst developed a robust automated method for the identifcation of SB days. Then, by using homogenized wind observations from 16 stations across Eastern Spain, we identifed 9,349 episodes for analyzing the multidecadal variability and trends in SB speeds, gusts and occurrence for 1961¿2019. The major fnding is the opposite trends and decoupled variability of SB speeds and gusts: the SB speeds declined signifcantly in all seasons (except for winter), and the SB gusts strengthened at the annual scale and in autumn¿winter, being most signifcant in autumn. Our results also show that the SB occurrence has increased across most of Eastern Spain, although presenting contrasting seasonal trends: positive in winter and negative in summer. We found that more frequent anticyclonic conditions, NAOI+and MOI+are positively linked to the increased winter occurrence; however, the causes behind the opposite trends in SB speeds and gusts remain unclear. The SB changes are complex to explain, involving both large-scale circulation and physical-local factors that challenge the understanding of the opposite trends. Further investigation is needed to assess whether these trends are a widespread phenomenon, while climate models could simulate the drivers behind these decoupled SB changes in a warmer climate., We thank AEMET for the observed wind speed data. This research was funded by the following projects: IBER-STILLING (RTI2018-095749-A-I00, MCIU/AEI/FEDER,UE); VENTS (GVA-AICO/2021/023) and the CSIC Interdisciplinary Thematic Platform (PTI) Clima (PTI-CLIMA). C.A.M was granted by Ramon y Cajal fellowship (RYC-2017-22830), and supported by a 2021 Leonardo Grant for Researchers and Cultural Creators, BBVA Foundation. This study is also supported by Unidad Asociada CSIC-Universidad de Vigo: Grupo de Fisica de la Atmosfera y del Océano. The authors wish to acknowledge the anonymous reviewers for their detailed and helpful comments to the original manuscript.

Surfing is one of the most popular activities in coastal tourism resorts. However, the sport depends strongly on the met-ocean weather conditions, particularly on the surface wind-generated waves that reach the coast. This study provides examples of how users? needs and user perspectives are considered by climate data specialists to develop needed, highly useful information addressing human and social needs. In this vein, the climate analysis of such data can provide input on the expected length of a surfing season, according to the surfer?s level of expertise. In addition, other water sports, such as SUP Wave and windsurfing, among others, might be indicated when surfing conditions are not optimal. Finally, the safety of surfers and other tourists who venture into the sea is also dependent on those conditions. We collaborated with the surfing community to define a series of indices for quantifying surfing days (SD), surfing days stratified by surfers? skills (SDS), alternate offers (AOs), and surfers? and swimmers? safety (SuS and SwS). These are of general applications but require wind and wave data at a very fine scale as the input. To illustrate the potential of our indices, we applied them to the Somo beach (Cantabria, Spain). We downscaled a global wave hindcast dataset covering a 30-year period to a spatial resolution of 100 m to obtain wave-surfing information at Somo?s surf spot. The results confirmed Somo?s status as a year-round surf spot, with SD values of 229.5 days/year and monthly values between 22 days/month and 16 days/month. SDS showed different seasonal peaks according to the surfers? skills. Beginners? conditions occurred more often in the summer (18.1 days/month in July), intermediate surfers? conditions appeared in the transitional seasons (14.1 days/month in April), and advanced and big-wave riders in the winter (15.1 days/month in January and 0.7 days/month, respectively). The AO index identified the SUP wave values of 216 days/year. Wind water sports presented values of 141.6 days/year; conversely, SUP sports were possible on only 7.4 days/year. SuS and SwS identified different seasonal hazard values, decreasing from the winter, autumn, and spring to minimum values in the summer. This research is within the INDECIS project (INDECIS is part of ERA4CS, an ERA-NET initiated by JPI Climate and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), and ANR (FR) with co-funding by the European Union Grant 690462). This article publication was possible with the support of the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya, the European Union (UE), and the European Social Fund (ESF) (Doctoral Research Grant 2021FI_B2 00147—Formació personal investigador novell).

Trabajo presentado en EMS Annual Meeting, celebrado en Bonn (Alemania) del 04 al 09 de septiembre de 2022., Sea breezes can occur on any coast of the world affecting meteorological variables broadly used to detect sea breeze episodes. To date, there is no universal method to identify sea breezes that works all over the globe. Most existing methodologies develop their own selection methods based on thresholds related to the local characteristics of the study site: e.g. wind direction based on the coastline orientation, cloud cover, precipitation, humidity, land-sea air temperature difference, pressure amplitude, insolation, among others. However, detecting past episodes from well-defined criteria makes sea breeze identification dependent on these criteria. This makes most classified events on the same site differ from each other, as well as making extrapolation to other regions difficult. The scarcity of high-resolution observed historical data over land and sea surfaces has limited the sea breeze understanding in many coastal regions across the world. To address the need of developing a universal method applicable to any coastal region of the globe, here we explore deep learning techniques (e.g. deep convolutional neural networks). We train these models using a time-series of high-resolution physical reanalysis (e.g. ERA-5 Land) gridded and observed data, after identifying 5 years of sea breezes manually for random stations around the globe. Results from this study constitute the first historical sea breeze global database spanning approximately the last 40 years. The ability of machine learning models to detect sea breezes allows the development of a simple and universal approach, which will improve the understanding of sea breeze at spatial scales which has not been addressed before, as far as we know.

Trabajo presentado en EGU General Assembly, celebrado en Vienna (Austria) del 23 al 27 de mayo de 2022., Sudden Stratospheric Warmings (SSW) are known to have impacts on the tropospheric atmospheric circulation that can persist up to 60 days. The aim of this work is to evaluate the influence of SSW on both observed mean wind speed and daily peak wind gusts across the Northern Hemisphere for 1961-2021. A set of 26 SSW with tropospheric response, including split (12) and displaced (14) events, are chosen for this matter. Daily wind speed means and peak gust data are retrieved from the quality-controlled and sub-daily station dataset: HadISD. The ultimate goal will be to prove the ability of SSW as possible source of predictability in the medium term for surface wind speed across the Northern Hemisphere, which would have direct applications in areas such as: wind-power generation, agriculture and air quality, among many other socioeconomic and environmental issues.

The Erasmus+ ClimEd (2021-2023; http://climed.network; “Multilevel Local, Nation- and Regionwide Education and Training in Climate Services, Climate Change Adaptation and Mitigation”) project is aimed at the development of competency-based curricula for continuous comprehensive training of specialists in the field of climate services and additional education in climate change for decision-makers, experts in climate-dependent economic sectors, and public.Some of the goals and objectives of the project are closely related to the Pan-Eurasian EXperiment (PEEX; www.atm.helsinki.fi/peex), and especially with multi-disciplinary, -scale and -component study climate change at resolving major uncertainties in the Earth system science and global sustainability issues.The ClimEd Trainings (http://climed.network/events/climed-trainings), in total 7, will be carried out during the project and will be focused on training the faculty/ teaching/ research staff and postgraduates at the ClimEd partner institutions and collaborating organizations in advanced educational and information-and-communication technologies for building a flexible multi-level integrated practice-based education system in the field of Climate Services, Climate Change Adaptation and Mitigation.Due to COVID pandemic situation, the originally planned face-to-face first trainings (in Estonia, Ukraine, and Finland) were converted into online training. Such online trainings were divided into 3 consecutive blocks: (i) online lecturing, (ii) home-work-assignments (HWAs) as group projects with established internal communication between the member of the groups and with an option of zoom-consulting during remote work, and (iii) final oral presentations (projects’ defenses) of HWAs with evaluation and feedback, discussions, and awarding certificates (corresponding to ECTS credits) with achieved learning outcomes. The majority of HWAs are based on the ClimEd main themes linking climate change vs. agriculture, energy, technical design and construction, urban economy, water management, health care; although other themes of interest can be selected by groups. Trainings also include questionnaires distributed among participants: evaluation of the training, and evaluation of own learning outcomes. Technically, the Moodle system, Zoom-hosting, e-evaluations, etc. are actively utilized in such trainings. All materials of the trainings are always publicly accessible online at the ClimEd project website as well as long-term stored at the Moodle system for each training.The outcomes/ summaries – including the lecture topics and learning outcomes, information resources, themes of group projects, feedbacks and training results, established network-community of the training participants (trainees and lecturers and teachers of HWAs) – of the online training approach will be presented for the ClimEd Trainings. Summaries are available for: 1st training “Competence-Based Approach to Curriculum Development for Climate Education”; 19 Apr – 12 May 2021; http://climed.network/events/climed-trainings/climed-training-1-online); 2nd – “Adaptation of the Competency Framework for Climate Services to conditions of Ukraine” (29 Jun – 26 Aug 2021; http://climed.network/events/climed-trainings/climed-training-2-online); 3rd – “Digital tools and datasets for climate change education” (26 Oct – 12 Nov 2021; http://climed.network/events/climed-trainings/climed-training-3-online); and 4th “Developing learning courses in climate services considering needs of different users” (7–11 February 2022; http://climed.network/events/climed-trainings/climed-training-4).

Climate change may affect sea breezes in their magnitude and occurrence, having direct implications for the hydrologic cycle and desertification (i.e., development of sea breeze thunderstorms), air pollution dispersal, wind energy production, to name but a few. To date, trends and multidecadal variability of sea breezes have been barely quantified because of the scarcity of long-term series, the low spatial-temporal resolution and the unreliability of observations over land-sea surfaces. Recent studies showed an increase in the occurrence of sea breeze days for the Eastern Spain, as well as opposite trends between the mean speed and gusts. The causes behind these opposite trends remain unknown because of the complexity of thermally driven coastal wind systems. The aim of this study is to advance in the knowledge of the observed changes in sea breezes over the Western Mediterranean area for 1961-2020, and their likely causes. To do so, we will first apply a robust automated algorithm based on alternative criteria to detect potential sea breeze events. Then, we will use homogenized wind speed and gusts data from sub-daily observations across the Mediterranean region to quantify the magnitude and significance of changes in sea breezes for 1961-2020. Finally, we will estimate the relationship with large-scale circulation (e.g., modes of variability, weather types and mean layer vector wind) and physical-local factors (e.g., land use changes and land-sea air temperature gradient) from ERA5 reanalysis to better understand the likely causes behind the observed changes in sea breezes.

This study analyses quality controlled and homogenized near-surface wind speed series (SWS) at 87 meteorological stations distributed across Spain and Portugal for 1961–2019. Multidecadal variability analysis of both mean and gusts SWS confirms for the first time in the region the cessation of the stilling (decline of SWS) and a possible weak reversal phenomenon (increase in SWS) in the last decades, varying its onset from 1999 to 2018, depending on the season and variable. Different atmospheric circulation drivers are evaluated to explain the stilling and reversal phenomena. Among the chosen teleconnection indices, the Western Mediterranean Oscillation index (WeMOi) is the one that presents the highest (positive) correlation with SWS, although the correlation (negative) with the North Atlantic Oscillation index and the Mediterranean Oscillation index in winter is also statistically significant (p < 0.05). Results show that the interannual variability of the WeMOi could exert a strong influence on both the stilling and reversal phenomena, as it displays statistically significant negative trends for 1961–2010 and positive ones (non-significant) for 2010–2019, in agreement with the observed SWS trends. The use of the Jenkinson and Collison weather type classification reveals the marked influence of certain weather types in modulating SWS changes (i.e., west, northwest, and anticyclonic types). We proposed the increase in atmospheric thermal stability and the northward shift of the jet stream as principal causes of the stilling phenomenon in this region. Our results improve our understanding of wind changes, and highlight the importance of regional assessments to discern their socioeconomic and environmental impacts., E.U.-C. was supported by the FPI fellowship (PRE2019-090148), and C.A.-M. by the Ramon y Cajal fellowship (RYC-2017-22830). This study was conducted in the framework of the IBER-STILLING project RTI2018-095749-A-100 (MCIU/AEI/FEDER,UE), the VENTS project AICO/2021/023 (GVA) and the CSIC Interdisciplinary Thematic Platform (PTI) Clima. (PTI-CLIMA).

Conventional time series analysis of observed near-surface wind speed (SWS) have focused both on mean values and on the sign, magnitude and statistical significance of trends. Specifically, a decrease in the SWS has been detected in continental surfaces of the planet's mid-latitudes from 1979 to 2010 approximately, the so-called stilling phenomenon; and an increase from 2010 until now, the reversal phenomenon. However, although various hypotheses have been proposed in the scientific literature, the mechanisms behind these phenomena and what evolution this parameter will follow in the future are still understudied, mainly because the response of a variable dependent on atmospheric circulation, such as wind speed, to a warming climate is uncertain. This study aims to use spectral analysis (Fourier and wavelet) to determine the most significant frequency modes associated with the SWS time series in the Iberian Peninsula (IP), for both mean wind speed and daily peak wind gusts, as well as its temporal evolution for 1961-2019. Subsequently, this study will also attempt to relate these modes to those corresponding to various modes of ocean-atmosphere variability such as the El Niño-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO) or, due to the influence of sudden stratospheric warming (SSW) in the European troposphere, the polar vortex. The ultimate goal will be to explore possible sources of predictability in the medium-long term for SWS across the IP, which would have direct applications in areas such as: wind-power generation, agriculture, air quality, insurance and fishing industries, among many others socioeconomic and environmental issues.

The most frequent and widespread landslides all over the world are induced by prolonged or heavy rainfall events. These phenomena often cause casualties and damages. Recent research on climate change has evidencing the link between the rainfall tendencies and the increase of damaging geohydrological events. This study has been carried out in the ambit of the EC Project INDECIS, whose aim is to develop an integrated approach to produce a series of climate indicators aimed at the high priority sectors of the Global Framework for Climate Services of the World Meteorological Organization (agriculture, risk reduction, energy, health, water), with the addition of tourism. The study area is Calabria, a region of Southern Italy frequently affected by mass movements and characterized by a highly variable climate. In this study, landslide occurrences in the period 1990-2018 have been collected for the whole territory of Calabria, and clustered according to the five provinces of the region. Moreover, 13 rainfall-based climatic indexes, among those proposed in the INDECIS project, have been calculated for each of the 79 rain gauges presenting complete and homogeneous databases. For each province and for the whole Calabria, the average and the maximum values of the climatic indices have been compared with the landslide occurrences in each year. The comparisons showed the best agreements with the following climatic indices: a) the total annual precipitation (RTA), the annual count of days when daily precipitation amount ≥ 10mm (R10mm), the annual count of days when daily precipitation amount ≥ 20mm (R20mm), the annual total precipitation when daily rainfall is greater than 95th-percentile (R95TOT) and, secondarily, the annual count of days with daily rainfall >= 50 mm (D50mm). For the best matches, the curves interpolating the two databases have been also drawn. The obtained results can be useful to predict the impacts that tendencies of rainfall indices patterns can have on slope stabilities of the territory.Acknowledgments:The Project INDECIS is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462)

All over the world wildfires destroy property and vegetation and can have an adverse effect on slope stability and soil erosion. Even though the number and the size of wildfires are often related to changes in land cover, population, and fire management practices, climatic and soil conditions remain the main factors influencing the extension of burnt areas. The goal of the EC Project INDECS, in which this study has been carried out, is to develop an integrated approach to produce a series of climate indicators aimed at the high priority sectors of the Global Framework for Climate Services of the World Meteorological Organization (agriculture, risk reduction, energy, health, water), with the addition of tourism. The study area is Calabria, a region of Southern Italy frequently affected by wildfires. In this research, data about the burnt areas (monthly data of extension - in hectares - and the number of fires in the period 2008-2018), provided by means of the module “Rapid Damage Assessment” (R.D.A.) of E.F.F.I.S. (European Forest Fire Information System) have been compared with the Keetch-Byram Drought Index (KBDI). This index, ranging between 0 and 203.2 (extreme dry condition of the soil), is used all over the world for monitoring and forecasting forest fires. The index was calculated with the daily rainfall and temperature data of 79 stations presenting complete and homogeneous databases. The monthly mean values were evaluated and the KBDI values were averaged for each province, given that the data of the wild fires are available for each of the five provinces of the region. The comparison results show that the peaks of the burnt areas almost always correspond with the highest of the KDBI values. Analogous results were obtained considering the number of fires. It is important to highlight that the results can be influenced by the following factors: a) the KBDI monthly mean value is evaluated by means of a database with a variable number of monthly values owing to missing data; b) the extension of the burnt areas is determined by the efficiency of the fire monitoring system and by the rapidity of first response operations; c) the RDA module database of EFFIS is referred to burnt areas with an extension greater than 30 hectares (in Europe, these fires are about 75-80% of the total fires) and does not contain differences between natural fires and human-induced fires. However, the obtained results can help to predict the impacts that tendencies of the KBDI patterns can have on the territory as an extension of burnt areas. In this way, the present study gives a useful service for agriculture and risk reduction sectors.Acknowledgments:The Project INDECIS is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462).

This paper extends the work of previous research by investigating surfing practices and surf-recreation companies from a behavioral perspective. The study’s main aim is to gain insights into the role of meteorological/climatological information in decision-making related to the surf-tourism activities market. This information was gathered employing an online survey that asked respondents about where they surf and how they check forecasts for surfing. Climate services (CS) are promoted to support the decision-making process to better prepare for and adapt to the risks and opportunities of climate variability and change. The current market for CS is still in its early stages. In this paper, we report the findings from our recent investigation into the actual and potential market for CS for the Iberian Peninsula surf-tourism sector. Based on surfers’ and surf companies’ demands, it was found that an improved surfing climate service (herein, SCS) will have clear implications in the management of these tourism areas and provide insights into whether surfing activities may be successful. At the same time, such services can help to manage adaptive actions in regard to the impacts of climate change in surfing areas.

Trabajo presentado en EGU General Assembly, celebrada en modalidad virtual del 4 al 8 de mayo de 2020., In a context of global climate change, the scientific community has evidenced a significant decrease in wind speed, a phenomenon known as «stilling». This climate trend has mainly been observed over mid-latitude continental surfaces since the 1980s. On the contrary, other studies have detected an increase in wind speed over ocean surfaces; and there is little conclusive scientific evidence on trends in wind speed across the troposphere. Furthermore, a reversal in global terrestrial stilling has recently been documented in few regional and global studies since the 2010s. The causes associated with the climate variability of wind speed have not yet been resolved and there are many uncertainties behind the «stilling» and «recovery» phenomenon because neither the quantity nor the quality of wind speed observations is adequate. This contribution shows an overview of the IBER-STILLING project (RTI2018-095749-A-I00) funded by the Spanish Ministry of Science, Innovation and Universities. This project aims to move forward on the assessment of wind speed and wind gusts variability and underlying causes globally, with emphasis on the Spanish territory and surrounding ocean (Atlantic) and sea (Mediterranean) surfaces. The IBER-STILLING project will collect and generate climate information of wind speed from different data sources; climate data will be subject to a comprehensive protocol for quality control and homogenization. The statistical analysis of these climate databases will allow characterizing trends and climatic cycles of wind speed, allowing a pioneering global analysis of wind speed over continental and ocean surfaces, and across the boundary layer and the entire troposphere. The project will also conduct wind-tunnel experiments to quantify biases introduced by anemometers devices.

Monitoring and management of several environmental and socioeconomic sectors require climate data that can be summarized using a set of standard and meaningful climate metrics. This study describes a newly developed gridded dataset for the whole of Europe, which employed a set of 125 climate indices spanning different periods based on data availability, but mainly 1950–2017 and 1979–2017. This dataset comprehensively summarizes climate variability in Europe for a wide range of climate variables and conditions, including air temperature, precipitation, biometeorology, aridity, continentality, drought, amongst others. Climate indices were computed at different temporal scales (i.e. monthly, seasonal and annual) and mapped at a grid interval of 0.25°. We intend to update these indices on an annual basis. This dataset is freely available to research and end-user communities., Measurement(s)climateTechnology Type(s)computational modeling techniqueFactor Type(s)air temperature • precipitation • sea level pressure • wind at 10 m • wind gust at 10 m • TOA radiation • radiation • insolation • snow density • snow depth • snowfall • total cloud cover • low cloud coverSample Characteristic - EnvironmentclimateSample Characteristic - LocationEurope Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12029427

Madagascar is an Island in Western Indian Ocean Region. It is mainly exposed to the easterly trade winds and has a rugged topography, which promote different local climates and biodiversity. Climate change inflicts a challenge on Madagascar socio-economic activities. However, Madagascar has low density station and sparse networks on observational weather stations to detect changes in climate. On average, one station covers more than 20 000 km2 and closer neighbor stations are less correlated. Previous studies have demonstrated the changes on Madagascar climate, but this paper contributes and enhances the approach to assess the quality control and homogeneity of Madagascar daily climate data before developing climate indices over 1950 – 2018 on 28 synoptic stations. Daily climate data of minimum and maximum temperature and precipitation are exploited.Firstly, the quality of daily climate data is controlled by INQC developed and maintained by Center for Climate Change (C3) of Rovira i Virgili University, Spain. It ascertains and improves error detections by using six flag categories. Most errors detected are due to digitalization and measurement.Secondly, daily quality controlled data are homogenized by using CLIMATOL. It uses relative homogenization methods, chooses candidate reference series automatically and infills the missing data in the original data. It has ability to manage low density stations and low inter-station correlations and is tolerable for missing data. Monthly break points are detected by CLIMATOL and used to split daily climate data to be homogenized.Finally, climate indices are calculated by using CLIMIND package which is developed by INDECIS* project. Compared to previous works done, data period is updated to 10 years before and after and 15 new climate indices mostly related to extremes are computed. On temperature, significant increasing and decreasing decade trends of day-to-day and extreme temperature ranges are important in western and eastern areas respectively. On average decade trends of temperature extremes, significant increasing of daily minimum temperature is greater than daily maximum temperature. Many stations indicate significant decreasing in very cold nights than significant increasing in very warm days. Their trends are almost 1 day per decade over 1950 – 2018. Warming is mainly felt during nighttime and daytime in Oriental and Occidental parts respectively. In contrast, central uplands are warming all the time but tropical nights do not appear yet. On rainfall, no major significant findings are found but intense precipitation might be possible at central uplands due to shortening of longest wet period and occurrence of heavy precipitation. However, no influence detected on total precipitation which is still decreasing over 1950 - 2018. Future works focus on merging of relative homogenization methodologies to ameliorate the results.-------------------*INDECIS is a part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462).

Before using climatological time series in research studies, it is necessary to perform their quality control and homogenization in order to remove possible artefacts (inhomogeneities) usually present in the raw data sets. In the vast majority of cases, the homogenization procedure allows to improve the consistency of the data, which then can be verified by means of the statistical comparison of the raw and homogenized time series. However, a new question then arises: how far are the homogenized data from the true climate signal or, in other words, what errors could still be present in homogenized data?The main objective of our work is to estimate the uncertainty produced by the adjustment algorithm of the widely used Climatol homogenization software when homogenizing daily time series of the additive climate variables. We focused our efforts on the minimum and maximum air temperature. In order to achieve our goal we used a benchmark data set created by the INDECIS* project. The benchmark contains clean data, extracted from an output of the Royal Netherlands Meteorological Institute Regional Atmospheric Climate Model (version 2) driven by Hadley Global Environment Model 2 - Earth System, and inhomogeneous data, created by introducing realistic breaks and errors.The statistical evaluation of discrepancies between the homogenized (by means of Climatol with predefined break points) and clean data sets was performed using both a set of standard parameters and a metrics introduced in our work. All metrics used clearly identifies the main features of errors (systematic and random) present in the homogenized time series. We calculated the metrics for every time series (only over adjusted segments) as well as their averaged values as measures of uncertainties in the whole data set.In order to determine how the two key parameters of the raw data collection, namely the length of time series and station density, influence the calculated measures of the adjustment error we gradually decreased the length of the period and number of stations in the area under study. The total number of cases considered was 56, including 7 time periods (1950-2005, 1954-2005, …, 1974-2005) and 8 different quantities of stations (100, 90, …, 30). Additionally, in order to find out how stable are the calculated metrics for each of the 56 cases and determine their confidence intervals we performed 100 random permutations in the introduced inhomogeneity time series and repeated our calculations With that the total number of homogenization exercises performed was 5600 for each of two climate variables.Lastly, the calculated metrics were compared with the corresponding values, obtained for raw time series. The comparison showed some substantial improvement of the metric values after homogenization in each of the 56 cases considered (for the both variables).-------------------*INDECIS is a part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462). The work has been partially supported by the Ministry of Education and Science of Kazakhstan (Grant BR05236454) and Nazarbayev University (Grant 090118FD5345).

The recent decades have been characterized by a noticeable warming over most of the globe. This warming has been accompanied by a global increase in precipitation, although many regions are projected to evolve towards a dryer climate. This is the case for the flanks of the subtropical dry regions, such as the Mediterranean and, more specifically, the Iberian PeninsulaIn this contribution, we use climate normal extracted from the E-OBS 20.0 gridded temperature and precipitation datasets E-OBS 20.0, from the EU-FP6 project UERRA (http://www.uerra.eu) and the Copernicus Climate Change Service, and the data providers in the ECA&D project (https://www.ecad.eu), with a resolution of 0.1 deg, to assess the evolution across three 20-year periods (1951-1970; 1971-1990 and the slightly shorter 1991-2018) of the extension occupied by the Köppen-Geiger climate types. In consonance with the observed and projected climate change, we observe an increase in the Iberian Peninsula of the extension of the dry (B) types, as replacement of the colder varieties by warmer ones.The analysis with the gridded dataset is compared to station records corresponding to the areas which swap climate-types for validation purposes. This work has been funded by the INDECIS project. INDECIS is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union Grant 690462).

The practice of surf is extended around the Iberian Peninsula’s coast. Surf-spots are the specific nearshore locations where surfing occurs. This coastal sport needs specific environmental conditions to be done. Knowing which is the distribution of surfing days around the Iberian Peninsula is a complex task. This is because good surfing conditions are the result of different climatological, geomorphological and oceanographical variables. Moreover, data collected used to define the distribution of surfing days is registered far away from the shore. Thus, the conditions registered – in the location of the buoys- will change somehow once arrive to the shore where surfers try to perform their best.Research has explored the advancements of climate services in multiple fields but the determination of frequency of surfing days around the Iberian Peninsula by attributing data from oceanographic buoys to surf-spots was not done before. Atmospheric variability modulates in different temporal scales occurrence and severity of the waves. In this way knowing how the climate works, how the atmosphere exchanges energy with the ocean or how is transferred and how this affects to low pressures and high pressures is fundamental for understanding the conditions for surfing.In this sense, Climate Services can provide the knowledge of the expected surfing days on surf-spots in the Iberian Peninsula by the methodology created in this study. The aim of this method is to identify the main variables which will make a good day for surfing or not. Into this context is important to know that surfing days are the result of two main factors: the influence of travelling low pressures from the ocean/sea to the specific shore (1) and the local conditions of each specific surf-spot -- thermal winds and beach orientation-- (2). The way of attributing these two factors is using buoys data to know the influence of travelling low pressures from the ocean to the shore by knowing significant wave height in open sea-. Then the form in which are attributed the local conditions is by knowing the specific favourable swell direction needed in each surf-spot and matching the direction of the swell that is registered by the buoys. In this way, it is made an attribution from the buoy data in the open sea to the surf-spots conditions located on the shore. The main results show the distribution of the expected days for surfing in the Iberian Peninsula based on historical data.Acknowledgments:Puertos del Estado from Ministry of Development in Spain and Instituto Hidrográfico marinha Portugal provided the data for doing this study.

Meteorological conditions determine the viability and competitiveness of socio-economic activities of any territory for many sectors, like those earmarked as priority areas in the Global Framework for Climate Services (GFCS). Yet, although the tourist sector is not one of those, the INDECIS project does include it.Climate services, understood as the transmission of processed information from meteorological and climatological data in a way that becomes useful for the end-user in the decision-making process, should be useful to trigger actions that adapt tourism activity to long-term trends and sudden changes of the competitive context, or else mitigate the effects that tourism generates on climatic conditions.In the framework of INDECIS project, researchers have been carried out different workshops for co-designing climate services in five European tourism destinations. The destination cases have the purpose of responding to the design of climate services taking into account the participation of different stakeholders in vulnerable destinations to Climate Change. As the main output, it has been developed different sectoral tourism indexes, which allow defining the optimum conditions to carry out tourism activities (snow tourism, sun & beach tourism, cultural tourism and outdoor tourism).The present research shows the preliminary results of the INDECIS Snow tourism Index (ISTI) through the case study of Jacetania’s County (Aragon Pyrenees). The ISTI has been co-created with the participation of local stakeholders, the Destination Management Organization (DMO), companies and end-users. Meanwhile, the economic value has been tested with tourism data from the destination, specifically offer and supply regarding the snow tourism activities. In this sense, the STI is made of three-dimensional perspectives: definition of meteorological conditions that condicionate the snow tourism (1), inclusion of other local variables, such as accessibility, infrastructures and characteristics of the ski stations (2), and consideration of the dynamics and seasonality of the destination (3). The first facet is essential for all users while the second facet is giving value specifically to skiers and the third facet is very useable as a planning tool for DMOs. The results allow validating the used methodology for the co-creation of climate services in the tourism sector. Concretely, the STI is a sectorial meteorological index for snow tourism in the Pyrenees’ Region. This index, that complements the Tourism Climate Index (TCI) and Holiday Climate Index (HCI), is based on the qualitative data received from the local agents and quantitatively transformed into a three-dimensional index for different users. Acknowledgments: INDECIS is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union Grant 690462).

A fundamental key to understanding climate change and its implications is the availability of databases with wide spatial coverage, over a long period of time, with constant updates and high spatial resolution. This study describes a newly gridded data set and its map viewer “European Climatology and Trend Atlas of Climate Indices” (ECTACI), which contains four statistical parameters (climatology, coefficient of variation, slope, and significant trend) from 125 standard climate indices for the whole Europe at 0.25° grid intervals from 1979 to 2017 at various temporal scales (monthly, seasonal, and annual). In addition, this study shows, for the first time, the general trends of a wide variety of updated standard climate indices at seasonal and annual scales for the whole of Europe, which could be a useful tool for climate analysis and its impact on different sectors and socioeconomic activities. The data set and ECTACI map viewer are available for free (http://ECTACI.csic.es/).

We present the second update to a data set of gridded land‐based temperature and precipitation extremes indices: HadEX3. This consists of 17 temperature and 12 precipitation indices derived from daily, in situ observations and recommended by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). These indices have been calculated at around 7,000 locations for temperature and 17,000 for precipitation. The annual (and monthly) indices have been interpolated on a 1.875°×1.25° longitude‐latitude grid, covering 1901–2018. We show changes in these indices by examining ”global”‐average time series in comparison with previous observational data sets and also estimating the uncertainty resulting from the nonuniform distribution of meteorological stations. Both the short and long time scale behavior of HadEX3 agrees well with existing products. Changes in the temperature indices are widespread and consistent with global‐scale warming. The extremes related to daily minimum temperatures are changing faster than the maximum. Spatial changes in the linear trends of precipitation indices over 1950–2018 are less spatially coherent than those for temperature indices. Globally, there are more heavy precipitation events that are also more intense and contribute a greater fraction to the total. Some of the indices use a reference period for calculating exceedance thresholds. We present a comparison between using 1961–1990 and 1981–2010. The differences between the time series of the temperature indices observed over longer time scales are shown to be the result of the interaction of the reference period with a warming climate. The gridded netCDF files and, where possible, underlying station indices are available from www.metoffice.gov.uk/hadobs/hadex3 and www.climdex.org. Robert Dunn was supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra (GA01101) and thanks Nick Rayner and Lizzie Good for helpful comments on the manuscript. Lisa Alexander is supported by the Australian Research Council (ARC) Grants DP160103439 and CE170100023. Markus Donat acknowledges funding by the Spanish Ministry for the Economy, Industry and Competitiveness Ramón y Cajal 2017 Grant Reference RYC‐2017‐22964. Mohd Noor'Arifin Bin Hj Yussof and Muhammad Khairul Izzat Bin Ibrahim thank the Brunei Darussalam Meteorological Department (BDMD). Ying Sun was supported by China funding agencies 2018YFA0605604 and 2018YFC1507702. Fatemeh Rahimzadeh and Mahbobeh Khoshkam thank I.R. of Iranian Meteorological Organization (IRIMO) and the Atmospheric Science and Meteorological Organization Research Center (ASMERC) for Data and also sharing their experiences, especially Abbas Rangbar. Jose Marengo was supported by the National Institute of Science and Technology for Climate Change Phase 2 under CNPq Grant 465501/2014‐1, FAPESP Grants 2014/50848‐9 and 2015/03804‐9, and the National Coordination for High Level Education and Training (CAPES) Grant 88887.136402‐00INCT. The team that worked on the data in West Africa received funding from the UK's National Environment Research Council (NERC)/Department for International Development DFID) Future Climate For Africa programme, under the AMMA‐2050 project (Grants NE/M020428/1 and NE/M019969/1). Data from Southeast Asia (excl. Indonesia) was supported by work on using ClimPACT2 during the Second Workshop on ASEAN Regional Climate Data, Analysis and Projections (ARCDAP‐2), 25–29 March 2019, Singapore, jointly funded by Meteorological Service Singapore and WMO through the Canada‐Climate Risk and Early Warning Systems (CREWS) initiative. This research was supported by Thai Meteorological Department (TMD) and Thailand Science Research and Innovation (TSRI) under Grant RDG6030003. Daily data for Mexico were provided by the Servicio Meteorológico Nacional (SMN) of Comisión Nacional del Agua (CONAGUA). We acknowledge the data providers in the ECA&D project (https://www.ecad.eu), the SACA&D project (https://saca-bmkg.knmi.nl), and the LACA&D project (https://ciifen.knmi.nl). We thank the three anonymous reviewers for their detailed comments which improved the manuscript.

A dense monthly precipitation dataset of Ireland and Northern Ireland was homogenized with several modern homogenization methods. The efficiency of these homogenizations was tested by examining the similarity of homogenization results both in the real data homogenization and in the homogenization of a simulated dataset. The analysis of homogenization results shows that the real dataset is characterized by a large number of, but mostly small, non-climatic biases, and a moderate reduction of such biases can be achieved with homogenization. Finally, a combination of the ACMANT and Climatol homogenization results was applied to improve the data accuracy before the trend calculations. These two methods were selected for their proven high accuracy, missing data tolerance and ability to complete time series via the infilling of missing values before the trend calculations. Metadata were used within the Climatol method. To facilitate this analysis the study area was split into smaller climatic regions by using the Ward clustering method. Five climatic zones consistent with the known spatial patterns of precipitation in Ireland were established. Linear regression fitting and the Mann-Kendall test were applied. Low frequency fluctuations were also examined by applying a Gaussian filter. The results show that the precipitation amount generally increases in the study area, particularly in the northwestern region. The most significant increasing trends for the whole study period (1941–2010) are found for late winter and spring precipitation, as well as for the annual totals. In the period from the early 1970s the increase of precipitation is general in all seasons of the year except in winter, but the statistical significance of this increase is weak.

Time series homogenization for 299 of the available precipitation records for the island of Ireland (IENet) was performed. Four modern relative homogenization methods, that is, HOMER, ACMANT, CLIMATOL and AHOPS were applied to this network of station series where contiguous intact monthly records range from 30 to 70 years within the base period 1941–2010. Break detection results are compared between homogenization methods, and coincidences with available documentary information (metadata) were analysed. The lowest (highest) number of breaks were detected with HOMER (ACMANT). Large differences of break frequency were found, namely ACMANT and AHOPS detected 8 times as many breaks than HOMER, while the break frequency with CLIMATOL was intermediate. Also, the ratio of series classified to be homogeneous varies widely between the methods. It is 85% with HOMER, 60% with CLIMATOL, 31% with AHOPS, while only 22% with ACMANT. In a further experiment, all the available time series for Ireland and Northern Ireland, (910 series) were used with ACMANT and CLIMATOL to explore the stability of break frequency for the same 299 series examined in the base experiment. While overall break frequency slightly increased (by 6–13%), the break positions notably changed for individual time series. The number of breaks changed for 59% (23%) of the series with ACMANT (CLIMATOL). For the breaks detected coincidentally by at least three methods including ACMANT and CLIMATOL in the base experiment, the second experiment confirmed the break positions in 86–87% of the breaks. The consequences of these results in relation to the reliability of statistical homogenization are discussed. Sometimes markedly different step functions provide comparable good approaches. However, the accuracy of homogenized time series cannot be related directly to the instability of break detection results., We found 116 concordant breaks indicated with at least three homogenization methods including metadata analysis. This together with some other aspects of the results suggests that the break frequency is higher than in several other European precipitation datasets. However, spatial correlations are generally higher in IENet than in many other precipitation datasets. Additionally, the ratio of series found to be homogeneous and the frequency of detected breaks are strongly method dependent. In the figure, ratios of homogeneous series for the four programmes. Homogeneous series are denoted in blue; series with one detected break in yellow and series with multiple breaks detected in red.

This article presents an exploratory methodology to co-create climate services for the tourism sector together with local stakeholders, emphasizing focus groups as an essential step for obtaining relevant data throughout the process. The article describes the user engagement for defining the optimal conditions for tourism in four different types of destinations in terms of tourist specialisation in Spain (Jacetania Council in the Aragon Pyrenees, the city of Calvia on the island of Majorca; the city of Barcelona and the Barcelona Coast) and Italy (Sila National Park) This methodology involves a sequence of steps to extract and validate such information through engagement, with destination stakeholders along the value chain (from accommodation managers to destination planners as well as final users). The process facilitates the design of numerical indices based on the information collected (from qualitative to quantitative data). Our methodology is suitable for application in other contexts and tourism activities where the subjective perception of weather and climate plays a role, as well as in other sectors.