OSA3.4

Climate change will exert a considerable influence across the area of Greece with temperature and precipitation extreme events becoming more frequent creating significant impacts on many societal and economic sectors. Future projections based on a range of anthropogenic scenarios show that decreases of annual rainfall amounts associated with increases of heat-waves and droughts are anticipated in several regions of Greece. Τhe Weather Research and Forecasting (WRF) model has appropriately been set-up and parameterized with a high spatial resolution of 5 km for the area of Greece. Previous research has revealed the capability of the configured WRF high resolution model to reproduce the main climatological variables in this region, which is dominated by highly variable topographic characteristics. The scope of this study is to investigate climate change projections for indices that express human‐perceived temperature extremes such as the Humidity index (Humidex), Wind Chill index (WCI) and Heat stress index (HI) in order to evaluate the potential impact on human health. These indices use different meteorological variables or a combination of them such as temperature, relative humidity and wind speed. The computation of these indices is based on daily simulated data, under two different scenarios (RCP4.5 and RCP 8.5) and periods (2025-2049 and 2075-2099) compared to present climate conditions (1980-2004). Downscaled results are derived from the global EC-EARTH model dataset, used for initial and boundary conditions. Our findings contribute to the quantification of future changes as well as on the identification of potential areas that might become prone to different degrees of heat/cold stress over the area of Greece.

How to cite: Politi, N., Vlachogiannis, D., Sfetsos, A., and Markantonis, I.: Future Projections of heat and cold stress based on two RCP Scenarios over Greece, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-142, https://doi.org/10.5194/ems2021-142, 2021.

In this study we examine the impacts of climate change on the tourism sector using a number of tailored climate indicators assessing whether climate conditions are suitable for touristic activities such as the Tourism Climate Index -focusing on outdoor activities- and the Beach Climate Index -focusing on beach activities- as well as fire danger indicators such as the Canadian Fire Weather Index, focusing on forest fire risk. To this aim daily or sub-daily data for a number of meteorological variables from a large ensemble member of Regional Climate Models from the EURO-CORDEX data base are used. The data cover the period 1971-2100 under three RCP emissions scenarios, namely RCP2.6, RCP4.5 and RCP8.5. The analysis is performed for three periods, the 1971-2000 which is used as a reference period and two future periods, the 2021-2050 and 2071-2100. The results indicate that the robust warming projected on a seasonal basis, under all three climate scenarios, drives the changes on all indicators examined. Regarding the climate suitability indicators for tourism the results indicate a lengthening of the tourist season suitable climate conditions while for the fire danger indicators, an increase in the number of days with high and very high fire danger conditions is projected. The most pronounced changes are evident towards the end of the century and under the RCP8.5 future emissions scenario. This study is performed in the framework of CLIMPACT, a Greek national funded project which aims to immediate integration, harmonization and optimization of existing climate services and early warning systems for climate change-related natural disasters in Greece, including supportive observations from relevant national infrastructure.

How to cite: Varotsos, K. V., Karali, A., Kitsara, G., and Giannakopoulos, C.: Climate change impacts on the Greek tourism sector, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-324, https://doi.org/10.5194/ems2021-324, 2021.

We assess the quality of state-of-the-art regional climate information intended to support adaptation decision-making. We use the UK Climate Projections 2018 (UKCP18) as an example of such information. The probabilistic, global and regional land projections of UKCP18 exemplify some of the key methodologies that are at the forefront of providing regional climate information for decision support in adapting to a changing climate. We assess the quality of the evidence and the methodology used to support their statements about future regional climate derived from these projections along five quality dimensions: transparency, theory, diversity, completeness and adequacy for purpose. The assessment produced two major insights. First, the main issue that taints the quality of UKCP18 is the lack of transparency. The lack of transparency is particularly problematic if the information is directed towards non-expert users, who would need to develop technical skills to evaluate the quality and epistemic reliability of this information. Second, the probabilistic projections are of lower quality than the global projections. This assessment is a consequence of both lack of transparency in the probabilistic projections, and the way the method is used and justified to produce quantified uncertainty estimates about future climate. We suggest how higher quality could be achieved. This can be achieved by improving transparency of evidence and methodology and by better satisfying other dimensions through changes in elements of evidence and methodology. We conclude by recommending further avenues for testing the effectiveness of the framework and highlighting the need for further research in user perspectives on quality.

How to cite: Baldissera Pacchetti, M., Dessai, S., Stainforth, D., and Bradley, S.: Assessing the quality of state-of-the-art regional climate information: the case of the UK Climate Projections 2018, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-316, https://doi.org/10.5194/ems2021-316, 2021.

Climate change knowledge can inform regional and local adaptation decisions. However, estimates of future climate are uncertain and methods for assessing uncertainties typically rely on the results of climate model simulations, which are constrained by the quality of assumptions used in model experiments and the limitations of available models. To strengthen knowledge for adaptation decisions, we use structured expert elicitation to assess future climate change in the Lower Yangtze region in China. We elicit judgements on future changes in temperature and precipitation as well as uncertainty sources, comparing elicited judgements and model outputs from phase 5 of the Couple Model Intercomparison Project (CMIP5). We find high consensus amongst experts that the Lower Yangtze region will be warmer in the coming decades, albeit with differences in the magnitude of change. There is less consensus around the direction and magnitude of change for future precipitation change in the region. When compared with CMIP5 model outputs, experts provide similar or narrower uncertainty ranges for temperature change and diverse ranges for precipitation. Experts considered additional factors (e.g. model credibility, observations, theory and paleo-climatic evidence) and uncertainties not usually represented in conventional modelling approaches. We explore the value in bringing together multiple lines of evidence in the context of climate services, arguing that while decision makers should not rely solely on expert judgements, this information can complement model information to strengthen regional climate change knowledge. These multiple lines of evidence can help in building dialogue between climate experts and regional stakeholders, contributing to the development of climate services. 

How to cite: Grainger, S., Dessai, S., Daron, J., Taylor, A., and Siu, Y. L.: Using expert elicitation to strengthen future regional climate information for climate services, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-364, https://doi.org/10.5194/ems2021-364, 2021.

Water resources management is often regarded as a complex issue which requires the process of planning, developing, allocating, distributing and managing the use of water resources. Climate change poses challenges (and risks) to the water sector, especially when the nation state is vast and has uneven distribution of water sources such as China. Furthermore, water management still largely relies on the use of historic, seasonal and annual climate data. There is limited demand from water managers for longer term climate information such as multi-annual and multi-decadal data. To promote the use of longer term climate information in the water sector in China, in this research, we have adopted an interdisciplinary approach and have applied a user-centred, co-production method to develop an integrated climate and water resources climate service prototype (iC-WRM) with water managers and their intermediaries. The Upper Yellow River Basin was used as a demonstration in iC-WRM to provide water managers with different scenario-based simulations to gain insights to the impacts of climate change on the region. Noticeably, the development of the prototype was constructed, tested and evaluated by water managers under Coronavirus restrictions which had prevented the typical co-development and user-evaluation processes to be undertaken. iC-WRM was shown to be successful, as key messages relating to be the impact of climate change could be effectively communicated through the prototype interface. Also, it has promoted a degree of understanding about the potential impact of climate change in terms of water resources management in China. This will encourage the development of other climate services to understand and implement the key outputs of this climate service prototype to other sectors (e.g. agriculture/food production, regional planning).

How to cite: Siu, Y. L., Willis, T., Turner, A., Dessai, S., and Taylor, A.: An integrated climate and water resources management (iC-WRM) prototype for long term water allocation in the Upper Yellow River Region of China, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-433, https://doi.org/10.5194/ems2021-433, 2021.

EPISODES is an empirical statistical downscaling method which has been developed at the German national weather service, DWD (Kreienkamp et al. 2019). Its main aim is the downscaling of climate projections and climate predictions (seasonal to decadal) from global climate models (GCMs) to regional scale. A specific aim is to enhance ensembles based on dynamical downscaling and to improve robustness of deduced indices and statements.

The methodology involves two main steps, first, analogue downscaling in connection with linear regression and, second, a sort of weather generator. An important precondition is the availability of long-term observation data sets of high quality and resolution. The synthetic time-series resulting from EPISODES are multivariate and consistent in space and time. The data provide daily values for selected surface variables and can be delivered on grid or station representation. As such, they meet the main requirements for applications in climate impact research. Thanks to low computational needs, EPISODES can provide climate projections within short time. This enables early insights in the local effects of climate change as projected by GCMs and allows flexibility in the selection of ensembles.

While good results for EPISODES projections have already been achieved for Germany, the methodology needs to be adapted for the more complex terrain of the Alpine region. This is done in close collaboration of DWD and ZAMG (Austria). Among other tasks, the adaptions include a regionalization of the selection of relevant weather regimes, optimal fragmentation of the target region into climatic sub-zones and correction of precipitation class frequencies.

The presentation will refer to the progress of the adaption process. In doing so the quality of downscaled climate projections is shown for a test ensemble in comparison with existing projections of the Austrian ÖKS15 data set and EURO-CORDEX. 

Reference: Kreienkamp, F., Paxian, A., Früh, B., Lorenz, P., Matulla, C.: Evaluation of the empirical–statistical downscaling method EPISODES. Clim Dyn 52, 991–1026 (2019). https://doi.org/10.1007/s00382-018-4276-2

How to cite: Schellander-Gorgas, T., Lorenz, P., Kreienkamp, F., and Matulla, C.: Empirical statistical downscaling with EPISODES in an Alpine territory, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-73, https://doi.org/10.5194/ems2021-73, 2021.

In order to develop seasonal forecast applications, raw forecast data generally need to be corrected to remove their systematic errors and drifts in time. In the climate community, methods based on quantile mapping techniques are quite common for their easy implementation. In the framework of the SECLI-FIRM project, we have tested a refinement of quantile mapping by conditioning the correction to weather regimes, in order to take large-scale circulation into account. For that purpose, we have used ADAMONT, a tool originally developed by Météo-France to correct climate projection scenarios. It was applied on four C3S seasonal forecast models over Europe, using ERA5 as a reference. Three parameters were treated at daily time-step: 2-metre temperature, precipitation and 10-metre wind-speed.

One of the main objectives of this study was to better understand the role weather regimes can play, if/when/where/for which parameter we gain in quality and predictability. For instance, a series of experiments were conducted on an idealized case of “perfect forecasts” of weather regimes, to point out the maximum benefits we could expect from the method.

Another focus of research was to test some strategies to optimize the positive impact of the introduction of weather regimes, by selecting members in one model ensemble or by using a multi-model approach. The selection was based on a sub-sampling of the best members in terms of weather regime frequency forecast, in order to determine the needed precision of weather regime forecast, for it to be useful in the correction.

We will present the main results of this work and some operational perspectives.

How to cite: Viel, C., Marson, P., Grigis, L., and Soubeyroux, J.-M.: Improvement of seasonal forecast correction by using weather regimes, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-52, https://doi.org/10.5194/ems2021-52, 2021.

Indonesia is one of the tropical regions with strong solar radiation exposure throughout the year, and this indicates the large potential for solar energy utilization in the country. Nevertheless, the utilization of solar energy in Indonesia until 2020 had only reached 10 MWp, as reported by the Ministry of Energy and Mineral Resources (ESDM), which is very small compared to the total potential of solar energy in Indonesia (approximately 112,000 GWp). One of the challenges for the development of solar energy in Indonesia is the weather and climate factors, as several weather parameters can cause intermittency in solar energy input in this region.

In the solar energy sector, a reliable forecast of potential energy input is of great importance in designing operational plans, whether it is a short-term, annual, or longer-term work plan. Global horizontal irradiance is an important quantity to determine the power generated from photovoltaic devices, and different resources are used to generate global radiation forecasts all over the world, ranging from ground-observed radiation, remote sensing observation, to numerical weather models. The European Centre for Medium-Range Weather Forecasts (ECMWF) provides solar radiation forecasts for various timescales, from hourly forecast to monthly and seasonal forecast. Whilst short-term solar radiation forecast is provided by other standard weather forecasting models, forecasts in the longer timescale are less commonly available and thus the seasonal forecast becomes a valuable information in making long-term operational plans.

A new solar radiation observation network has been installed in a number of locations across Indonesia in recent years, which allows the evaluation and modification of the seasonal forecast generated by the model. To improve the performance of the forecast, a statistical post-processing approach is implemented, by making use of measurements provided by the radiation observation network and ERA5 reanalysis dataset. To generate historical solar radiation data in all parts of Indonesia, a co-kriging interpolation of the ground-observed solar radiation is executed, using reanalysis data as an external drift in the interpolation process. The new gridded solar radiation data is then utilized to create transfer functions that represent the relationship between the statistical moments of both the numerical model output and observed radiation based on its probabilistic distributions. The transfer functions are generated in the training period, which will then be used to modify the model output in the forecast period. The implementation of the bias-correction process applied in this explorative study is aimed to provide the foundation of solar radiation prediction information that will support the operational activities of solar energy production in Indonesia.

How to cite: Sianturi, Y., Sopaheluwakan, A., Amin, T., Sartika, K. A., Hermawanto, A., and Marjuki, M.: Development of Climate Services for Renewable Energy: Statistical Post-processing of Solar Radiation Seasonal Forecast Over the Indonesian Region, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-319, https://doi.org/10.5194/ems2021-319, 2021.

 Evapo-Transpiration calculated from the new regional climate projections data set DRIAS-2020 over France

Changes in climatic variables such as temperature, precipitation, relative humidity or solar radiation strongly affect the agricultural sector. Relevant indicators are strongly needed to quantify the expected impacts and implement adaptation measures. Information on the future trend of Evapo-Transpiration (ET) is one of the key issues in order to take up the water management challenge.

In 2020, a new set of climate indicators based on regional climate projections corrected over France was produced and published on the French national climate service DRIAS (www.drias-climat.fr) and the associated report was published in January 2021. The latter portal provides climate information in a variety of graphical or numerical forms. The climate projections are based on the EURO-CORDEX ensemble and have been corrected using the ADAMONT method according to the SAFRAN reference data set.

ET is calculated from this new data set with the aim of making it freely available on the DRIAS portal. Various calculation methods are used and compared. First, ET is calculated upstream and downstream of the ADAMONT method. Second, different calculation procedures are tested for the FAO recommended formula. One uses the average specific humidity instead of minimum and maximum of daily relative humidity which are not available in all selected models. ET is also calculated using the Hargreaves proxy for the visible radiation based on the square root of the maximum daily thermal amplitude multiplied by a coefficient. Three different values were tested for this coefficient : 0.16, 0.175 and 0.19.

These various ET are then analyzed with a view to quantify the influence of the calculation method on the resulting estimated trends.

Authors : BERNUS S.¹, CORRE L.², DROUIN A.², SAAVEDRA SORIANO G.³, SIMON P.², PRATS S.⁴,

¹ Météo-France, Direction de la Climatologie et des Services Climatiques, Toulouse, France, sebastien.bernus@meteo.fr

²Météo-France, Direction de la Climatologie et des Services Climatiques, Toulouse, France, first-name.last-name@meteo.fr

³École des Mines, Antibes, France, genaro.soriano@mines-paristech.fr

⁴Météo-France, Direction des Services Météorologiques, Toulouse, France, sebastien.prats@meteo.fr

References :

FAO (1998). Crop evapotranspiration: Guidelines for computing crop water requirements. FAO Irrigation and drainage paper 56, Rome, Italy

How to cite: Bernus, S., Corre, L., Drouin, A., Saavedra Soriano, G., Simon, P., and Prats, S.: Evapo-Transpiration calculated from the new regional climate projections data set DRIAS-2020 over France, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-109, https://doi.org/10.5194/ems2021-109, 2021.

For long-term planning of the highway infrastructure, engineers in the Ministry of Infrastructure and Water Management of the Netherlands are considering the trade-offs between the risk posed by extreme precipitation in a changing climate and the cost of measures to reduce this risk for the entire network of highways and its critical elements, such as tunnels. This leads them to questions such as "How often does the precipitation over 10 minutes exceed 50 mm somewhere on a given network of roads?"

Naturally, this frequency is higher than the frequency of exceedance of the same depth at a site; it depends on the size and shape of the domain and on the spatial dependence of extreme precipitation. 

In the present study, statistics describing the spatial dependence of extreme precipitation are estimated from 11 years of gauge-adjusted radar precipitation data collected over the Netherlands.  At each radar pixel, annual maxima of precipitation depth are computed for durations ranging from 15 min to 12h. From these maxima, the values of the extremal coefficient function (ECF) for selected spatial domains are estimated.

From these values, a simple model is derived for converting return values of precipitation depth at a single site to return values of the highest precipitation depth within an arbitrary spatial domain, for durations from 10 min to 12 h. The model describes the duration-dependent statistics of the parameterized footprints of heavy precipitation events.

Confidence intervals are predicted using bootstrapping. The model is checked for fitness for its application to the design and maintenance of the drainage of highways, and the scope for further improvement is discussed. 

How to cite: de Valk, C., Overeem, A., Fortuin, P., and Garcia Martin, I.: How often does the precipitation over 10 minutes exceed 50 mm somewhere on a given network of roads?, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-425, https://doi.org/10.5194/ems2021-425, 2021.

Weather and climate information tailored to support decision-making in the built-up environment is becoming increasingly important. Energy-efficiency and climate resilience of buildings constitute a key subject in climate change mitigation and adaptation. Increasing outdoor air temperatures influence the heating and cooling energy demand of buildings and may increase the overheating risk of indoor conditions. Besides, more frequent rainfall events at the expense of snowfall in winter may intensify mold growth and moisture condensation in structures and slow down the drying of structures. Therefore, because buildings are designed to last for several decades, the planning, construction and maintenance of buildings need to be prepared for the changing weather conditions.

The National Building Code of Finland demands that new buildings have to pass the nearly zero-energy requirements for energy performance and conformity, and this needs to be verified by calculations which use so-called test reference year (TRY) hourly weather data as input. TRY data sets describe typical present-day weather conditions during twelve months that usually originate from different years. Following the related standard (ISO 15927-4:2005) with a few modifications, the TRY data files have been constructed for Finland twice: in 2012 and 2020. While the former (TRY2012) is officially still in use, the latter (TRY2020) was recently developed with the aid of a newer set of weather observations, covering the period 1989-2018 and containing the following variables at hourly resolution: temperature, relative humidity, wind speed and direction, global, diffuse and direct solar radiation, and precipitation.

An important part of work was to assess what kinds of weather conditions the built environment should be prepared for, depending on the forthcoming greenhouse gas emissions. Therefore, the tridecadal (1989-2018) weather datasets were transformed to represent future climate by modifying the hourly values of the weather variables in accordance with multi-model mean projections derived from an ensemble of 28 CMIP5 climate models. The transformations were performed using delta-change methods tailored for the various climatic variables. The observed partition of the global radiation between direct and diffuse components was also utilized in the transformation algorithm.

The new climate information supports the design of healthy, safe and energy-efficient buildings in the changing climate of Finland. The work was part of a chain of multi-year ongoing research activities funded by the Ministry of the Environment and Healthy Premises 2028 program set by Prime Ministers´s Office. The materials produced in the project can also be utilized in education and scientific research. Previously, based on future scenarios linked to TRY2012, the annual energy demand was simulated to decrease by 20-40 % for heating and increase by 40-80 % for cooling in Finland by 2100.

How to cite: Jylhä, K., Ruosteenoja, K., Böök, H., Lindfors, A., Pirinen, P., Laapas, M., and Mäkelä, A.: Tailored climate information for assessing energy demand and physical functioning of buildings, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-243, https://doi.org/10.5194/ems2021-243, 2021.

Resilience plans to cope with climate change are of particular relevance in cities, because of the large and still increasing percentage of population living in urbanized environments. Urban adaptation implies general planning, but reflects also in single and limited urbanistic, engineering and architectural projects, in which local authorities as well as professionals and practitioners are directly involved.

The basic concept of ClimaMi (www.progettoclimami.it), a locally funded but easily replicable project for the city of Milan and immediate neighborhood (a densely populated and industrial area in the western-central part of Po valley in northern Italy), relies on the need to provide, bottom-up, updated and useful climatological information to agencies and personnel directly involved in public and private enterprises and management practices, which have immediate impact in present and future urban climate and citizens wellness. The 3 years Project was therefore developed as an interdisciplinary activity, directly involving not only climatologists but also local professional organizations, and producing as a first result a common basis of knowledge and technical language among different disciplines.

A second fundamental task has been the creation of an as much as possible complete database of 7 essential climatic variables and relevant derived indexes (94 in total) for specific applications, representing an updated and detailed description of the urban environment in the most recent climate. Relating mainly on a high-quality and metrologically managed climate network of urban automatic weather stations (CN by OMD), and integrating data from stations of third-party networks according to accurate selection criteria for homogeneity and reliability, a 6 years DB for 19 selected points and 6 different time windows is now openly available to professionals for direct and immediate use in their activities.

A further development has been the production of interactive GIS-based maps of air temperature distribution at medium-high resolution (100 m) in the Project area: a climatological and geostatistical methodology has been in this case applied to optimally integrate near surface measurements and space-borne observations of land skin temperature. The result is an Atlas of mean thermal fields in selected typical weather situations of specific relevance for resilience applications, for instance in case of enhanced Urban Heat Island and Heat Wave episodes. In the third and last Project year (2021), a DB and Atlas update is planned, while similar methodologies are specifically applied to precipitation.

In order to make the Project results as effective as possible with real impacts on planning and project activities, numerous capacity building courses have also been planned and activated, involving hundreds of officials and professionals. Furthermore, practical laboratories and case studies were performed in order to evaluate the real effects in the aware and informed use of updated climatological information in adaptation projects.

How to cite: Lavecchia, C., Pilati, S., and Frustaci, G.: Starting an effective Climate Service for urban applications: the ClimaMi Project in Milan., EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-207, https://doi.org/10.5194/ems2021-207, 2021.