ITS3.3/CL3.2.20

For climate-change impact studies at the catchment scale, meteorological variables are typically extracted from ensemble simulations provided by global (GCMs) and regional climate models (RCMs), which are then downscaled and bias-adjusted for each study site. For bias adjustment, different statistical methods that re-scale climate model outputs have been suggested in the scientific literature. They range from simple univariate methods that adjust each meteorological variable individually to more complex and statistically as well as computationally more demanding multivariate methods that take existing relationships between meteorological variables into consideration. While several attempts have been made over the past decade to evaluate such methods in various regions, there is no guidance for choosing an appropriate bias adjustment method in relation to the study question at hand. In particular, the question whether more complex multivariate methods are worth the effort by resulting in better adjustments of a wide range of univariate, multivariate and temporal features, remains unanswered. 
We here present an approach to systematically assess the performance of the most commonly used univariate and multivariate bias adjustment methods at different catchment scales in Sweden. Based on a multi-catchment and multi-model approach, we evaluated numerous univariate, multivariate and temporal features of precipitation, temperature and streamflow. Finally, we discuss potential benefits (skills and added value) and trade-offs (complexity and computational demand) of each method, in particular for hydrological climate-change impact studies in high latitudes.

How to cite: Teutschbein, C., Tootoonchi, F., Todorovic, A., Räty, O., Haerter, J., and Grabs, T.: Bias adjustment of RCM simulations in high-latitude catchments: complexity versus skill in a changing climate, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10396, https://doi.org/10.5194/egusphere-egu22-10396, 2022.

Climate model output is widely used as input to impact models. Such applications include hydrological, crop, energy modeling, and more.  However, due to model deficiencies and the stochastic nature of climate processes, some variables (e.g., daily precipitation) tend to present systematic biases and deviations from the observed conditions. This is particularly important when studying high-impact extreme events. The present study aims to develop a Copula-based method for bias-correcting modeled daily precipitation. Precipitation data are provided by two EURO-CORDEX regional climate models (KNMI-RACMO22E and CLMcom-CCLM4) and for two time periods (1981-2010 and 2031-2060). The demonstration area is the island of Cyprus, located in the eastern Mediterranean climate change hot-spot. Cyprus is characterized by a complex coastline and steep orography that drive the precipitation distribution. As a reference dataset, we used a high resolution (1x1km) gridded observational dataset, derived from a dense network of stations. For this application, we developed a copula-based structure scheme between the reference and the simulated data sets. This was for the historical period and each model grid cell. Then, assuming this relation remains unchanged, we corrected the biases for both study periods (historical and near future). Due to the stochastic nature of precipitation, the copula schemes were developed separately for each hydrological season (i.e., wet: November to March and dry: April to October). In addition, different copula schemes were developed for non-extreme and extreme events. The results showed that the proposed method could significantly improve the modeled precipitation for both models in 85% and 92% of grid cells, respectively. These improvements are evident throughout the year and for both extreme and non-extreme values. The climate change signal (precipitation decline near 7%) remains unchanged after applying the bias correction.

How to cite: Lazoglou, G., Zittis, G., and Bruggeman, A.: A novel, Copula-based approach for the bias correction of daily precipitation: a case study in the eastern Mediterranean, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2518, https://doi.org/10.5194/egusphere-egu22-2518, 2022.

Four climate parameters (i.e., maximum, mean and minimum air temperature and precipitation amount) from 10 regional climate models, provided by the EURO-CORDEX initiative, are adjusted using as reference the ROCADA gridded dataset. The adjustment was performed on a daily temporal resolution for the historical period (1971-2005), as well as for climate change scenarios based on two Representative Concentration Pathways (RCP45 and RCP85).

The best method for bias-correction was selected following a 2-fold cross-validation approach, which was performed on historical data using two methods: Quantile Mapping (QMAP) and Multivariate Bias Correction with N-dimensional probability (MBCn). The performances of the two methods are very similar when analysing the frequency distribution of each selected variable, whereas the comparison between the inter-variables correlation of the adjusted datasets and the reference dataset revealed much smaller differences for the dataset adjusted with the multivariate method, hence this was used for producing the BC climate scenario dataset.

Based on the MBCn adjusted dataset, a climate change analysis over Romania was performed at the seasonal and annual scales. Overall, for the multimodel ensemble mean, at the country level, a substantial temperature increase is reported for both scenarios and no significant trend is revealed for precipitation amount.

The adjusted RCMs are provided without any restrictions via an open-access repository in netCDF CF-1.4-compliant file format (https://doi.org/10.5281/zenodo.4642463). The BC climate models are archived at the 0.1° spatial resolution, in the WGS-84 coordinate system, at a daily temporal resolution. Based on bias-corrected dataset, relevant information about climate change over Romania’s territory is provided by using an interactive dashboard, implemented in an open-source web application (RoCliB data explorer - http://suscap.meteoromania.ro/roclib).

How to cite: Dumitrescu, A., Vlad Amihăesei, V., and Cheval, S.: RoCliB - Bias corrected CORDEX RCM dataset over Romania, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12415, https://doi.org/10.5194/egusphere-egu22-12415, 2022.

We share our experiences for impact and adaptation studies, by presenting results of a climate modelling study, which is based on ERA5 data at different horizontal resolutions, i.e., down from approximately 300 km to 25 km. The ERA5 data is used as a meteorological constraint (nudging) to perform a numerical model study on the influence of horizontal resolution on aerosol hygroscopic growth effects on meteorology in urban and remote atmospheric locations. For this sensitivity study we only switch on/off the associated aerosol water mass. Aerosol water is crucial form climate impact and adaptation studies as it links air pollution with weather and climate through direct and indirect radiative feedbacks. We try to separate urban from continental-scale effects using the EMAC atmospheric chemistry climate and Earth system model. EMAC is applied globally in various horizontal resolutions, in a set-up similar to our previous PMAp evaluation study (https://www.eumetsat.int/PMAp), i.e., resolving weather time-scales. We compare our EMAC results of the aerosol optical depth (AOD) against CAMS reference simulations (40 km), various satellite data (MODIS-Aqua/Terra, PMAp) and AERONET surface observations (~ 30km radius around the instrument). While CAMS REA includes AOD data assimilation (Modis/PMAp), EMAC calculates the AOD ab initio from size-resolved aerosol hygroscopic growth without any data assimilation, and with an option to include aerosol-cloud feedbacks. Our results show that the EMAC AOD results are within the range of CAMS and satellite AOD. Aerosol water effect on AOD is noticeable for nudged and free running EMAC versions at both, urban and remote locations. The aerosol water effect is larger for free running EMAC versions, and more pronounced for urban AERONET sites, e.g., Hamburg, Karlsruhe, Thessaloniki, Zaragoza. The moisture feedback with air pollution is resolution dependent (time and space). Generally, this becomes more relevant with increasing resolution due to finer moisture and air pollution gradients, which is an indication for the importance of horizontal resolution for impact and adaptation studies.

How to cite: Metzger, S., Feigel, G., Steil, B., Rémy, S., and Christen, A.: Influence of horizontal resolution on aerosol hygroscopic growth effects in urban andremote boundary layers in the context of climate impact and adaptation studies, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13495, https://doi.org/10.5194/egusphere-egu22-13495, 2022.

Medium- and long-term energy planning at regional scale requires, among others, the estimate of the future energy demand driven by expected  heating and cooling needs of buildings, according to the local impact of changing climate. To support the development of the 2021-2030 Energy Plan of the Province of Trento in the Alps, temperature projections provided by EURO-CORDEX Regional Climate Models (RCMs) were downscaled at 11 weather stations, representative of altitudes between 0 and 700 m a.m.s.l., to estimate the future values of a set of parameters that are commonly used to model the energy demand of buildings, such as: Heating and Cooling Degree Days (HDDs and CDDs), Test Reference Years (TRYs) and Extreme Reference Years (ERYs). A dataset of temperature and solar radiation hourly measurements, taken at the stations starting from 1983, was quality-controlled and analyzed to estimate statistics and observed trends for both variables, as well as degree days, reference years and climate change indices from the ETCCDI set. A hybrid downscaling approach (combining statistical and dynamical techniques) is then applied to temperature projections, based on the application of the morphing method to the results of an ensemble of 16 RCMs, allowing the estimate of future TRYs, ERYs and degree days in 2030 and 2050 at the selected sites (notice that no significant variation associated with climate change was assumed for solar radiation). According to historical observations (1983-2019), the warming tendency for monthly mean temperatures is clear and falls around 0.06 °C year^-1, slightly higher than reported at national level. The increase is more pronounced in spring and summer than in autumn and winter, with minima in December and especially May. No significant trend is observed for solar radiation trends. As for HDDs, stations at different altitudes show comparable reductions, of around -10 HDDs year^-1, with an apparent tendency to accelerate in the most recent years. The increase of CDDs can be quantified in less than 5 CDDs year^-1. The ensemble of temperature projections estimate temperature increases of 0.5 °C between 2016 and 2030 and 1.3 °C between 2016 and 2050 on average (0.03-0.04 °C year^-1), implying further future reductions of HDDs (between -4 and -11% at 2030, between -10 and -21% at 2050) and increases of CDDs (between 12 and 36% at 2030, between 36 and 87% at 2050). Such changes will correspond to major modifications in the seasonal profile of the energy demand associated with the winter heating and summer cooling of buildings in the Alpine area.

How to cite: Zardi, D., Laiti, L., and Giovannini, L.: Local downscaling of temperature projections for energy planning purposes in an Alpine area, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11372, https://doi.org/10.5194/egusphere-egu22-11372, 2022.

Adaptation to climate change is an inevitable challenge in many regions. In our study area, which is located in the state of Brandenburg in eastern Germany, land use is increasingly affected by long-lasting soil moisture deficits in the vegetation period. It is therefore important to implement measures for water retention at the landscape scale that postpone and mitigate the severity of these drought periods. Our objective is to identify cost-effective measures in a manner that maximizes expected ecological benefits for available budgets. For this purpose, we combine a scientific analysis of the determinants of land surface temperature with site-specific cost calculations.

The distribution of land surface temperature serves as a proxy for environmental conditions that favor water retention and, as a consequence, provide a certain cooling effect during hot and dry periods. Landsat thermal images from the vegetation seasons of 2013 to 2020 were rescaled (min-max normalization) and used as the response variable for a Bayesian multilevel model. Several parameters of the physical environment such as land cover, forest and crop type, soil water holding capacity, canopy cover and degree of soil sealing were used as explanatory variables. In addition, an antecedent moisture index and potential evapotranspiration at time of satellite overpass were incorporated into the model. First results highlight the importance of land use and canopy cover for land surface temperature distribution. In general, the analysis enables the identification of overheated landscapes. Moreover, model predictions after hypothetical implementation of adaptation measures provide an ecological benefit assessment based on the cooling capacities. We also determine the costs of the different measures in a spatially differentiated manner. An integrated modeling procedure combines the results from the ecological and economic assessments.

In this contribution, we will present the results of the Bayesian modeling and discuss a first example of the cost-effectiveness analysis in an agricultural landscape.

How to cite: Zimmermann, B., Hildmann, C., Kruber, S., Witt, J. C., Sturm, A., Hecker, L. P., and Wätzold, F.: Cost-effective measures for climate change adaptation in a drought-prone area in eastern Germany, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4596, https://doi.org/10.5194/egusphere-egu22-4596, 2022.

How to cite: Gleixner, S., Tomalka, J., Lange, S., and Gornott, C.: AGRICA - Climate Risk Profiles for Sub-Saharan Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11337, https://doi.org/10.5194/egusphere-egu22-11337, 2022.

APENA 3 ”Strengthening the capacity of regional and local administrations for implementation and enforcement of EU environmental and climate change legislation and development of infrastructure projects” is an EU-funded project, targeting to effectively raise Ukrainian public authorities capacities at local and regional level in designing and implementing key reforms. The main feature of Component 3 is the development of climate adaptation strategies followed by implementation plans for three Ukrainian Oblasts. Following an evaluation process, the Oblasts of Ivano-Frankivs’ka, L’vivs’ka and Mykolaivs’ka were determined to be the most appropriate in which to undertake the above activities. The first important step, was to identify the sectors of interest in relation to climate change, in Oblast but also National level utilizing the experiences and know-how from Europe and internationally, since the pilot Strategies and Implementation Plans, will be used as a guidance for other Oblasts in the future to elaborate regional climate adaptation planning. The selected sectors include agriculture, forests, biodiversity and ecosystems, water management, fisheries, coastal areas, tourism, critical infrastructure, energy, health, built environment and cultural heritage. The next step in the methodology is the vulnerability and risk assessment. The project team will identify the appropriate climate indices to evaluate vulnerability and risk based on specific climatic impact drivers for the respective sectors. Sensitivity and exposure analysis will follow in order to identify the degree of vulnerability of each sector and geographic area in the three pilot Oblasts. Based on the previous assessment, impacts will be identified and examined in terms of likelihood and severity, guiding the team to determine the risk. The various challenges (stakeholder engagement, sectoral issues identification, collection of climate data etc.) in the use of climate data will be identified and tackled in this stage. Following the preparation of the project’s scientific basis, the Experts team will determine sectoral adaptation thematic pillars, that will include horizontal and location specific measures and actions for the evaluated sectors.

How to cite: Tsompanidis, C., Krakovska, S., Lolos, T., Sakalis, A., Ieremiadi, E., Gittelson, A., Kysil, O., and Krasnozhon, A.: APENA3 – Methodology and steps for the preparation of three pilot climate adaptation strategies and implementation plans in Ukraine, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12037, https://doi.org/10.5194/egusphere-egu22-12037, 2022.

As uncertainty around the impacts of climate change become more apparent, businesses and communities are relying on cutting-edge information to help them navigate their next steps. Climate X are a climate risk information provider that aims to help businesses and communities prepare for a rapidly changing environment, with an explainable and transparent method.

Our flagship product, Spectra, presents users with a multitude of potential hazards including flooding (fluvial, pluvial, and coastal), subsidence, landslides, and extreme heat. Each hazard risk is quantified at street level, and we project risks and impacts for low emissions (RCP2.6) and high emissions (RCP8.5) scenarios. This allows users to see the difference between the best-case and worst-case scenarios for assets across the UK.

This poster will cover our methods of finding data, interpolating, modelling, and predicting, as well as a tour of our easy-to-use UI.

How to cite: Zeneli, M., Burke, C., Ramsamy, L., Mitchell, H., Brennan, J., and Kluza, K.: Climate X: Meeting the demand for multi-hazard climate risk information tailored to financial services, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7810, https://doi.org/10.5194/egusphere-egu22-7810, 2022.

Climate change increasingly affects all parts of society. Different economic sectors such as the agricultural sector have to adapt to climate change. More and more climate services are being developed in order to support this adaptation to climate change with accurate and suitable products. Good practises for the design of climate services include transdisciplinary approaches and co-creation of climate service products. The development of usable and useful climate service products and effective adaptation measures requires constant interactions between climate service providers and users of the products. To assess the effectiveness of these co-creation endeavours, continuous evaluation is crucial. At present, output and outcome assessments are conducted occasionally in this research field. However, these summative evaluations that are preformed ex-post do not help to adjust the ongoing process of co-creation. Therefore, the focus of the presented work is on formative evaluation of the co-creative development of science-based climate service products. A formative evaluation is done during the run-time of a project with the intention to reflect and readjust it. For this purpose, we analysed in detail the process of co-creation of climate service products in the knowledge transfer project ADAPTER (ADAPT tERrestrial systems, https://adapter-projekt.org/) and combine this analysis with a systematic literature review. In ADAPTER, simulation-based climate service products are developed together with key partners and practitioners from the agricultural sector, with the aim of supporting decision making in the context of climate change adaptation.

As a first step, main characteristics of the product development process were identified empirically and six sub-processes of product development were determined. Secondly , questions for a formative evaluation were assigned to the different steps and sub-processes. Thirdly, a literature review including fields other than climate services delivered additional qualitative aspects. As a result, a scheme of quality criteria and related assessment questions for the different sub-processes in climate service development was created, based on both empirical and theoretical work. Subsequently, this scheme needs validation and testing. The resulting formative evaluation scheme will be particularly helpful to reflect on and to improve the co-creation processes in climate services and beyond.

How to cite: Keup-Thiel, E., Bathiany, S., Dressel, M., El Zohbi, J., Rechid, D., Schuck-Zöller, S., Suhari, M., and Timm, E.: Evaluation of co-creation processes in climate services  -  Development of a formative evaluation scheme, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4090, https://doi.org/10.5194/egusphere-egu22-4090, 2022.

How do we succeed in supporting climate adaptation also outside of the large urban areas? Which measures for mitigating do we need to deal with the consequences of climate change? What support and which tools do smaller communities need in planning and implementing necessary measures? What is specific for low mountain ranges? To answer these questions a targeted process was initiated by researchers and practitioners from three German federal states (Saxony, Saxony-Anhalt and Thuringia), working together in the interdisciplinary project KlimaKonform within BMBF RegIKlim.

The model region covers three counties in the catchment area of the Weiße Elster. The low mountain region is typical for large parts of Germany and other Central European countries. Thus, the approach, experiences, methods and products are easily transferable to other low mountain ranges. Small and medium-sized municipalities have to deal often with limited budgets, as well as limited technical and administrative capacities. Community income is mainly generated by agriculture and forestry, small businesses and partly tourism. At the same time, the challenges posed by the increasing intensity and frequency of extreme events such as flash floods, water shortage, heat waves and storms are similar to large cities with much higher capacities in personnel and finances.

Unfortunately, adaptation to extreme weather and climate change often comes only after a damaging event, for example after extreme precipitation destroyed the municipal water infrastructure (paths, sewer network, and waste water treatment plants). KlimaKonform supports communities to become active before damage occurs and thus foster the move from event-related to preventive and strategic action. Therefore, KlimaKonform offers new concepts and customised tools to assess the impacts of climate change, determine their capacities for adaptation and derive appropriate measures. The tools will consider the needs in the model region and address the uncertainties related to future climate change and climate model output.

Examples are given for various foci of the project. One focus of KlimaKonform involves the interdisciplinary assessment of extreme events by coupled model chains ranging from climate change ensembles to third order impact models. Hazards as heavy rainfall and floods with their impacts are incorporated. The location in the low mountain range requires high-resolution climate input data for modelling due to corresponding high flow velocities. These data are not sufficiently available for regional climate impact modelling. In cooperation with the project NUKLEUS and hydro-impact modellers in RegIKlim, approaches like bias adjustment of climate model outputs are tested for applicability. The aim is to reduce uncertainties in model application while increasing the effectiveness of precautionary and adaptation measures. Another focus of KlimaKonform is the systematic identification of vulnerable infrastructure during heat waves. In this context, urban climate simulations are used to assess the potential of green infrastructure to reduce outdoor and indoor heat stress conditions. All results of KlimaKonform will be available free of charge and in a comprehensible form via a freely accessible internet platform. Here, the already existing and well-received Regional Climate Information System ReKIS will be expanded to provide guidance for smaller communities.

How to cite: Bernhofer, C., Heidenreich, M., Maleska, V., Schinke, R., and Wollschläger, N.: KlimaKonform – An interdisciplinary project to support smaller communities in climate change adaptation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8085, https://doi.org/10.5194/egusphere-egu22-8085, 2022.