Comparison of five strategies for seasonal prediction of bioclimatic indicators in the olive sector

The forecast quality of five seasonal prediction strategies used to obtain tailored bioclimatic indicators in the olive sector has been assessed over the Iberian Peninsula (IP). In total, five indicators have been selected considering their importance in the management of the olive orchard. As time progresses through the indicator target period, the impact of the increasing share of actual observations included in its computation has been evaluated by examining the variabilities of correlation and fair Rank Probability Skill Score (fair RPSS) in each initialization date. The results show that blending either seasonal predictions or climatology with observations enhanced the capability of forecasting the tercile category for all the indicators when compared with the use of climatology or seasonal predictions alone. In fact, for Spring Temperature Maximum (SPRTX) and Growing Season Temperature (GST) indicators, the combination of observations and SEAS5 prediction could outperform the other methods for most of the start months. As for those threshold-defined indicators, namely Spring Heat Days (SPR32) and Summer Heat Stress Days (SU36 and SU40), the end-users are highly encouraged to use climatology in the first month and combine it with observations as soon as they become available

Evaluación de los índices de teleconexión que afectan a la Península Ibérica con modelos climáticos del AR4

Ponencia presentada en: VII Congreso de la Asociación Española de Climatología: clima, ciudad y ecosistemas, celebrado en Madrid entre el 24 y 26 de noviembre de 2010.[ES]En el contexto de la variabilidad a escala global y las teleconexiones, se investiga cómo las salidas de los modelos climáticos globales son capaces de simular los índices de teleconexión. El estudio se centra en el cálculo de los índices de teleconexión que afectan directamente al clima de la Península Ibérica, como son la Oscilación del Atlántico Norte (NAO), el Atlántico Oriental (EA), el Escandinavia (SCAND) y el Atlántico Oriental-Oeste de Rusia (EA/WR). Se utilizan los datos de geopotencial en 500-hPa de los modelos climáticos globales del World Climate Research Program Coupled Model Intercomparison Project phase 3 (WCRP CMIP3) para los experimentos del siglo XX y de emisiones medias A1B. El método para obtener los índices de teleconexión se basa en una regresión por Mínimos Cuadrados Parciales. Se analizan las diferencias espaciales y temporales entre los índices simulados y los que proporcionan en el “Climate Prediction Center”, mediante correlaciones espaciales y tendencias. Este estudio serviría para determinar los posibles cambios de dichos patrones bajo escenarios de cambio climático y cómo estos pueden afectar al clima de la Península Ibérica.[EN]In the context of global variability and teleconnections, we investigate how climate models are able to simulate the Teleconnection Indices. The analysis is focused on the Teleconnection Indices that have impact on Iberian Peninsula climate, which are the North Atlantic Oscillation (NAO), the East Atlantic (EA), the Scandinavian pattern (SCAND) and the East Atlantic West Russia (EATL/WRUS). We use 500-hPa geopotential height data from models of World Climate Research Program Coupled Model Intercomparison Project phase 3 (WCRP CMIP3) of the twenty century (20C3M) and emissions A1B experiments. The procedure to obtain the Teleconnection Indices is based on Partial Least Square (PLS) regression. Comparison of the simulated indices and the ones from Climate Prediction Center is performed in spatial and temporal domains by computing the spatial correlation and trends of the indices. This evaluation could be used to determinate the Teleconnection Patterns changes under warming conditions and how they could affect the Iberian Peninsula climate.Este trabajo se ha realizado con la ayuda de los proyectos de investigación: CGL2008-04619 del Ministerio de Ciencia e Innovación, SA123/A08 de la Junta de Castilla y León con fondos Europeos del FEDER y MOVAC ref.200800050084028 del Ministerio de Medio Ambiente

Evaluación de los índices de teleconexión que afectan a la PI con modelos climáticos del AR4 [Póster]

Póster presentado en: VII Congreso de la Asociación Española de Climatología: clima, ciudad y ecosistemas, celebrado en Madrid entre el 24 y 26 de noviembre de 2010.Este trabajo se ha realizado con la ayuda de los proyectos de investigación: CGL2008‐04619 del Ministerio de Ciencia e Innovación, SA123/A08 de la Junta de Castilla y León con fondos Europeos del FEDER y MOVAC ref.200800050084028 del Ministerio de Medio Ambiente

State-of-the-art climate predictions for energy climate services

Seasonal predictions of 10-m wind speed can be used by the wind energy sector in a number of decision making processes. Two different techniques of post-processing are applied in order to correct the unavoidable systematic errors present in all forecast systems. Besides an assessment of the impact of these corrections on the quality of the probabilistic forecast system is provided

State-of-the-art climate predictions for energy climate services

Seasonal predictions of 10-m wind speed can be used by the wind energy sector in a number of decision making processes. Two different techniques of post-processing are applied in order to correct the unavoidable systematic errors present in all forecast systems. Besides an assessment of the impact of these corrections on the quality of the probabilistic forecast system is provided

Co-production pathway of an end-to-end climate service for improved decision-making in the wine sector

Climate services are one of the tools that can support the agriculture sector to address the impacts of climate change on agricultural production systems, not only considering climatic aspects but also social needs. This work describes the knowledge co-production journey of the EU-funded project MED-GOLD to create an end-to-end climate service for wine sector users. In this work, co-production is understood as an iterative, interactive and collaborative process among an interdisciplinary group of scientists and users that were engaged, involved, and empowered. The co-production process included activities to raise awareness on the vulnerability of grape and wine production to climate change, exchange knowledge between climate service providers and users, and co-develop customised climate services, such as the MED-GOLD Dashboard. Lessons learned are that repeated interaction between scientists and users allow to better frame research questions, jointly decide how to address these questions, and test the outcomes with feedback from real-world decision-makers. Furthermore, having a user who co-developed the service and helped assess its added value was key to ensure that it could truly inform decision-making needs and to promote its broader uptake by the wine sector community. Although the MED-GOLD Dashboard constitutes the most tangible result of this collaboration, the outcomes of co-production also encompass the joint learning process, the shared sense of ownership, and the co-creation of new knowledge between scientists and stakeholders. Nevertheless, further research will be needed to understand how the knowledge coproduced with a single user can be scaled up to users with other profiles and requirements.The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 776467 (MED-GOLD) and 869565 (VitiGEOSS)."Article signat per 15 autors/es: Marta Terrado, Raül Marcos, Nube González-Reviriego, Ilaria Vigo, Andria Nicodemou, Antonio Graça, Marta Teixeira, Natacha Fontes, Sara Silva, Alessandro Dell'Aquila, Luigi Ponti, Sandro Calmanti, Marta Bruno Soares, Mehri Khosravi, Federico Caboni "Postprint (published version

Subseasonal predictions for climate services, a recipe for operational implementation

The implementation of operational climate service prototypes, which encompasses the co-design and delivery of real-time actionable products with/to stakeholders, contributes to efficiently leveraging operational climate predictions into actionable climate information by providing practical insight on the actual use of climate predictions. This work showcases a general guideline for implementing an operational climate service based on subseasonal predictions. At this timescale, many strategic decisions can benefit from timely predictions of climate variables. Still, the use of subseasonal predictions is not fully exploited. Here, we describe the key aspects considered to set up an operational climate service from the conception to the production phase. These include the choice of the subseasonal systems, the data sources and the methodology employed for post-processing the predictions. To illustrate the process with a real case, we present the detailed workflow design of the implementation of a climate service based on subseasonal predictions and describe the bias adjustment and verification methodologies implemented. This work was developed in the H2020 S2S4E project, where industrial and research partners co-developed a fully-operational Decision Support Tool (DST) providing 18 months of real-time subseasonal and seasonal forecasts tailored to the specific needs of the renewable energy sector. The operational workflow can be adapted to serve forecast products to other sectors, as has been proved in the H2020 vitiGEOSS project, where the workflow was modified to provide downscaled subseasonal predictions to specific locations. We consider this a valuable contribution to future developments of similar service implementations and the producers of the climate data.The research leading to these results has received funding from the European Union’ss Horizon 2020 research and innovation programme under Grants 7767874 (S2S4E) and 869565 (VitiGEOSS). ECMWF-Ext-ENS real-time predictions used for the operational prototype were provided by the Subseasonal to Seasonal (S2S) Prediction Project’s Real-Time Pilot Initiative to S2S4E Project as one of the participating projects. The data can be obtained from the S2S Project database through its two data portals: ECMWF ( https://apps.ecmwf.int/datasets/data/s2s/levtype=sfc/type=cf/) and CMA ( http://s2s.cma.cn/index). The ECMWF ERA-5 reanalysis was accessed from Copernicus Climate Change Service (C3S) Climate Data Store ( https://cds.climate.copernicus.eu/#!/home).Peer ReviewedPostprint (published version

Ensayos de simulación del índice NAO de inviernos con datos de CMIP5

Ponencia presentada en: VIII Congreso de la Asociación Española de Climatología celebrado en Salamanca entre el 25 y el 28 de septiembre de 2012.[ES]Resultados inferidos del 4º informe del IPCC y de posteriores análisis de los datos CMIP3 sobre temperatura y precipitación, coinciden en señalar la región del Mediterráneo y la Península Ibérica como zonas especialmente vulnerables a los impactos del cambio climático. Debido a las relaciones existentes entre dichas variables y las teleconexiones, es de gran interés el estudio de estas últimas bajo condiciones de aumento de emisiones por sus aplicaciones en predicciones regionalizadas. En este trabajo se muestran los resultados para la estación de invierno del patrón de la Oscilación del Atlántico Norte (NAO), obtenido con datos de geopotencial en 500hPa pertenecientes al proyecto CMIP5 y experimentos ‘historical’ y ‘RCP 8.5’. El método utilizado para su obtención es la regresión Parcial por Mínimos Cuadrados (PLS) tomando como referencia los patrones de teleconexión del CPC de la NOAA. Se presentan análisis espaciales y temporales del multi-modelo elaborado a partir de los modelos que mejor representan la NAO, según los resultados que proporciona el diagrama de Taylor.[EN]Results from the IPCC AR4 report and other recent analyses of temperature and precipitation from CMIP3 dataset, agreed that Mediterranean region and Iberian Peninsula are highly vulnerable to the impacts of climate change. Due to the connections between those variables and Teleconnections patterns, is interesting to study them under increasing emission scenarios, to apply this study for regional downscaling. This work shows results of the North Atlantic Oscillation (NAO) pattern for winter season (DJF). This pattern was obtained from 500 hPa geopotential height data from the World Climate Research Programme´s (WCRP´s) Coupled Model Intercomparison Project phase 5 (CMIP5) with the experiments “Historical “ and “RCP 8.5”. We used Partial Least Squares Regression (PLS) procedure in order to obtain the patterns and indices, taking into account the patterns of the Climate Prediction Center (CPC) of NOAA as reference. Results focus on spatial and temporal analysis of the multi-model that was built with models that best reproduce the observed NAO according to the Taylor Diagram.Este trabajo se ha realizado con la ayuda de los proyectos de investigación: CGL2011-23209 del Ministerio de Ciencia e Innovación, SA222A11-2 de la Junta de Castilla y León con fondos Europeos del FEDER

Development of a wind energy climate service based on seasonal climate prediction

Climate predictions tailored to the wind energy sector represent an innovation to better understand the future variability of wind energy resources. In this work an illustration of the downstream impact of the forecasts as a source of climate information, the post-processed seasonal predictions of wind speed and temperature will be used as input in a transfer model that translates climate information into capacity factor. This transfer model is based on multivariate regression that assumes a linear relationship between wind speed and temperature with the capacity factor

Variability of extreme precipitation over Europe and its relationships with teleconnection patterns

A growing interest in extreme precipitation has spread through the scientific community due to the effects of global climate change on the hydrological cycle, and their threat to natural systems' higher than average climatic values. Understanding the variability of precipitation indices and their association to atmospheric processes could help to project the frequency and severity of extremes. This paper evaluates the trend of three precipitation extremes: the number of consecutive dry/wet days (CDD/CWD) and the quotient of the precipitation in days where daily precipitation exceeds the 95th percentile of the reference period and the total amount of precipitation (or contribution of very wet days, R95pTOT). The aim of this study is twofold. First, extreme indicators are compared against accumulated precipitation (RR) over Europe in terms of trends using non-parametric approaches. Second, we analyse the geographically opposite trends found over different parts of Europe by considering their relationships with large-scale processes, using different teleconnection patterns. The study is accomplished for the four seasons using the gridded E-OBS data set developed within the EU ENSEMBLES project. Different patterns of variability were found for CWD and CDD in winter and summer, with north–south and east–west configurations, respectively. We consider physical factors in order to understand the extremes' variability by linking large-scale processes and precipitation extremes. Opposite associations with the North Atlantic Oscillation in winter and summer, and the relationships with the Scandinavian and East Atlantic patterns as well as El Niño/Southern Oscillation events in spring and autumn gave insight into the trend differences. Significant relationships were found between the Atlantic Multidecadal Oscillation and R95pTOT during the whole year. The largest extreme anomalies were analysed by composite maps using atmospheric variables and sea surface temperature. The association of extreme precipitation indices and large-scale variables found in this work could pave the way for new possibilities regarding the projection of extremes in downscaling techniques