OSA3.4

The Norwegian Centre for Climate Services (NCCS), a national collaboration on the natural scientific knowledge for climate adaptation, has published the national climate assessment reports for Norway (Hanssen-Bauer et al., 2009; Hanssen-Bauer et al., 2015, Hanssen-Bauer et al., 2019). The work on national climate projections and associated products are described in Nilsen et al., 2022. In the wake of IPCC AR6 (CMIP6), the Norwegian Environment Agency has commissioned an update of the report “Climate in Norway 2100”, including new fine-scale climate projections for Norway. The report will present changes in past climate of the last 2000 years, current climate and hydrological normals and projected future changes in climate, hydrology and effects on natural hazards.

A literature review of climate change in the Arctic islands of Svalbard will be included (mainly based on “Climate in Svalbard 2100” (Hanssen-Bauer et al., 2019)). However, Svalbard will not be included in the modeling work due to the large difference in data availability, both measurements and model simulations, between mainland Norway and the Arctic.

Due to limited resources, delays in the international collaboration on climate projections (CMIP and EURO-CORDEX) and expectations from society of updated recommendations in the light of the already launched IPCC report, strict priorities in the modeling group are necessary. Early model selection and ensemble size is particularly urged by hydrological modeling. In this presentation we will share decisions made so far in the project. We anticipate our priorities and considerations as working with the newest generation of climate model simulations to be of interest to the international community and other national climate services. 

The presentation will include considerations around emission scenarios and the GCM-RCM ensemble, where a combination of CMIP5 and CMIP6 simulations will be used. We also present results from the historical climate development, the use of empirical statistical downscaling, convective-permitting simulations for improved understanding of changes in heavy rainfall, bias adjustment methods, improvements in the hydrological model and some early ideas on data distribution and outreach. 

References: 

Hanssen-Bauer et al., 2009: Klima i Norge 2100. Bakgrunnsmateriale til NOU Klimatilpasning (in Norwegian).

Hanssen-Bauer et al., 2015: Klima i Norge 2100. Kunnskapsgrunnlaget for klimatilpasning oppdatert i 2015 (in Norwegian). NCCS report 02/2015.

Hanssen-Bauer et al., 2019: Climate in Svalbard. A knowledge base for climate adaptation. NCCS report 02/2019.

Nilsen et al., 2022: From climate model output to actionable climate information in Norway. Frontiers in Climate, accepted.

How to cite: Dyrrdal, A. V., Nilsen, I. B., Mayer, S., Hygen, H. O., Dobler, A., and Hanssen-Bauer, I.: Decisions made when updating national climate projections for Norway, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-378, https://doi.org/10.5194/ems2022-378, 2022.

Nowadays, climate simulations represent petabytes of data. About 30 institutions provided nearly 1.6 PBytes of data for the Coupled Model Intercomparison Project Phase 5 (CMIP5) and estimations for the Phase 6 (CMIP6) data volume range from 15 to 30 PBytes. Despite this large volume of climate data, climate projections data are often available at lower spatio-temporal resolution. Only few climate simulations are available today at a temporal frequency higher than a daily time step. For example, for CMIP6 about a hundred runs are available at hourly time step compared to nearly 2000 runs at a daily or monthly time step. However climate impact studies are usually conducted at finer scales, and so impact model (e.g., energy demand model ) require data at a higher spatio-temporal resolution as input. In this study, we investigate the capabilities of three temporal downscaling techniques to recover the diurnal cycle of temperature from given daily climate simulations (from CMIP6 data base) using a perfect model approach. A quantile-mapping technique, an analogue technique and a linear regression technique were calibrated using a 30-year historical simulations and applied to a 30-year “future” period (from an SSP5-8.5 scenario) using daily average, maximum and minimum temperature as input over a Euro-Mediterranean domain. Results show that overall, the linear regression performs better than the quantile-mapping and the analogue techniques. The performances depend on the geographical region and the season and can be fully explained by the differences between the climate change signal (historical vs future scenario) of daily average temperature and daily maximum/minimum temperature. Indeed, both analogue and quantile-mapping approaches assume that the change in daily maximum/minimum temperature between the historical and future period should be the same as daily average temperature. However, the diurnal cycle of temperature is not only shifted to warmer temperatures but the shape of the cycle changes under future climate scenarios. The linear regression outperforms the other two approaches over the whole domain and for all the seasons by taking into account the daily average, maximum and minimum temperature to reconstruct the diurnal cycle.

How to cite: Omrani, H. and Michelangeli, P.-A.: Reconstructing the diurnal cycle of temperature from daily climate simulations using three temporal downscaling techniques in a perfect model approach, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-14, https://doi.org/10.5194/ems2022-14, 2022.

The national climate assessment report series ‘Klima i Norge – 2100’ by the Norwegian Centre for Climate Services provides information on past and future changes in meteorological parameters and derived indices, hydrological components and effects on natural hazards. As a consequence, one of the key-user of national weather and climate data in downstream applications, namely hydrologists, are directly involved in the process of framing the report, including the selection of simulations and the application of bias-adjustment methods.

For the upcoming update of the report (expected to be published in 2024), a set of nine variables from an ensemble of regional climate model (RCM) projections will be bias-adjusted on a 1x1 km grid covering the complete Norwegian mainland. To this end, different methods have been implemented, including empirical quantile mapping, which has already been used in the former reports, quantile delta mapping and multivariate bias-adjustment. Applying the methods to a set of RCMs yields a variety of datasets. These datasets, by design of the methods, reproduce the reference data with various accuracy, for instance in terms of spatial, temporal and inter-variable consistencies. Furthermore, the bias-adjusted climate projections differ on how they inherit specific climate change signals from the RCMs. Compared to the raw data, they may or may not preserve monthly or seasonal trends, changes in the quantiles or in the dependency structures. Since it is not always clear whether all the changes in the RCMs are physically plausible and relevant, selecting a single method may not be appropriate. And even if it’s clear, the corresponding bias-adjustment method may have other undesirable shortcomings.

In this presentation we will show examples of how the different methods can affect the projected climate change signals in various aspects, and thus are adding a level of uncertainty. We will further emphasise the point of investigating these uncertainties in climate change assessments when bias-adjustment is involved. By feeding the data into a downstream application, the projected changes may differ substantially.

How to cite: Dobler, A., Kwok Wong, W., Haddeland, I., Lawrence, D., Haugen, J. E., and Verpe Dyrrdal, A.: Uni- and multivariate bias-adjustment on a 1 km grid over Norway, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-392, https://doi.org/10.5194/ems2022-392, 2022.

Empirical-statistical downscaling (ESD) methods are sparing regarding computational costs compared to dynamical downscaling models. Due to this advantage ESD can be applied in a short time frame and in a demand-based manner. It enables, e.g., the creation of ensembles of downscaled climate projections, which can be assessed either as stand-alone data set or to enhance ensembles based on dynamical methods. This helps improve the robustness of climatological statements for the purpose of climate impact research.

EPISODES is an ESD method for the regionalisation of output of general circulation models (GSMs). The initial development of EPISODES has been done at Deutscher Wetterdienst (DWD) for the area of Germany. Results of EPISODES results of CMIP5 projections are available for public download at the Earth System Grid Federation (ESGF). In the meantime, EPISODES has been extended for the downscaling of climate predictions on different timescales (decadal, seasonal, sub-seasonal) to meet the needs of climate data users for high spatial resolution datasets. Furthermore, is has been applied to a number of CMIP6 global projections.

In co-operation with the Zentralanstalt für Meteorologie und Geodynamik (ZAMG) EPISODES is currently further developed and adjusted for handling besides the German area also the Alpine region. In addition to the interest of ZAMG to carry out downscaling with EPISODES for Austria, the complete coverage of the catchment areas of the Rhine, Elbe and Danube is a common interest of this cooperation.

The presentation will give an overview of the current status of EPISODES, show results, and provide an insight into recent developments.

How to cite: Lorenz, P., Schellander-Gorgas, T., Hoff, A., and Kreienkamp, F.: Empirical-Statistical downscaling with EPISODES – status and current developments, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-645, https://doi.org/10.5194/ems2022-645, 2022.

The fraction of renewables in the energy mix has steadily increased over the last decade, but system integration remains a challenge due to their intrinsic volatility. The development, operation and maintenance of a renewable power system requires a clear understanding of the impact of current climatic conditions and their potential changes under climate change scenarios. For example, wind power generation will become one key technology in the global pathway toward the net-zero objectives of the European climate strategy and for EU energy independence, with expected demand to ramp up installations of both onshore and offshore production systems by 2050. Year 2021 was characterized by low annual average wind speeds in northwestern and central Europe, with implications for the wind power generation, as reported by the C3S European State of the Climate 2021.  The wind energy industry therefore needs relevant climate-derived information at different timescales, depending on the specific project and application. The Copernicus Climate Change Service (C3S) delivers data and information designed to address the needs of users to assess the impact of climate on energy operations, management and planning, as well as the needs of the community of energy modelers, needing user-friendly datasets for their assessment studies. Those users need datasets coherent at continental level, which make use of homogenized and long-term climate data sources, and that permit to link energy demand and production to climate variability and projected climate changes. Several applications built on C3S data have been further developed in downstream Services, demonstrating the relevance of the C3S data value chain to support the energy sector users.  

How to cite: Cagnazzo, C., Buontempo, C., Almond, S., Zanacchi, M., Vermoote, S., Nicolas, J., and Vamborg, F.: Copernicus Climate Change Service (C3S) climate information for the energy sector, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-582, https://doi.org/10.5194/ems2022-582, 2022.

UNESCO has defined 1154 properties of world heritage, which all face an increased threat of degradation of their values due to climate change. Eight world heritage sitesare based in Norway (with one transboundary). As a response to this known threat, The Directorate for Cultural Heritage in Norway has started to assess the threat, and effect, of climate change on the sites and the communities around the sites by applying a method called CVI (https://cvi-heritage.org/) to the world heritage site on Vega archipelago. As part of this process, an assessment of the known climate changes affecting Vega was developed.

The Norwegian Ccentre for Climate Services has delivered two national assessments for Norway. Based on the later assessment, climate factsheets (Klimaprofiler) have been issued for every county, describing current conditions as well as the most important changes from the reference period to 2100. These fact sheets are tailored to meet the county and municipal needs of climate information for climate adaptation. The workshops regarding the climate vulnerability Vega archipelago demonstrated the need of a tailored interpretation of the fact sheet highlighting the threats affecting the world heritage sites. Whereas the county-wise climate change factsheets are developed to serve climate change adaptation needs related to design and planning, and therefore present results towards 2100, the world heritage sites preferred site specific information towards the middle of this century. During the winter and spring of 2022, a prototype for climate factsheets for the world heritage of Rock art in Alta was developed, and a first version presented at a workshop on Vega in april 2022. Based on the response of this presentation, similar factsheets will be co-produced for each of the eight world heritage properties in Norway. These factsheets are meant as a supplement to the county-wise factsheets, not a replacement. The comments provided in the process will inspire the next generation of county-wise factsheets which are planned to be issued by the Norwegian Centre of Climate Services in 2025.

How to cite: Hygen, H. O., Nilsen, I. B., and Dalen, E.: Climate factsheets for world heritage sites in Norway, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-513, https://doi.org/10.5194/ems2022-513, 2022.

Despite the strong relationship between tourism and weather/climate and the sustained research in the area, little climate and environmental information customized for tourism is easily accessible for tourists. Several aspects may be considered as possible explanations, as for example tourists satisfaction with the current products and less interest for other new ones, availability, costs, efficiency in providing and delivering of new products and services to tourists etc.

We aim to identify some characteristics of a potential climate service of interest for tourists that may contribute to a better user uptake, by addressing in particular three aspects: (1) which are the weather, climate and/or environmental features most commonly marked ‘of interest’ in the general case of ‘any destination type’ and for the particular case of rural destinations; (2) which are the delivery and presentation forms of greatest interest for tourists; (3) how willing would be the tourists to pay for such information/service.

To this end, we used a questionnaire with 5 closed questions regarding the aspects mentioned before; four questions involve a five-fold Likert -type scale, while one is a multiple-choice question. The questionnaire was available online and disseminated through social media and e-mail.

The results confirm some expectations based on scientific literature like the interest for air quality and highlight the user interest for information encompassing several climate and/or environmental aspects preferably in one single product, like the thermal comfort, weather fit for outdoor activities, air quality. The survey also highlighted that mobile phone application would be the preferred mean of access, while the information should be presented in graphical form and preferably associated with some descriptive text. The financial attractivity of such information is quite low, as most of the respondents would not pay for such information and only 30% would agree to one single payment for a broader package.

How to cite: Velea, L. and Gallo, A.: Preliminary assessment of tourists interest for tourism-tailored climate and environmental products, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-32, https://doi.org/10.5194/ems2022-32, 2022.

Adapting buildings to a changing climate has become an increasingly popular topic of research. A
critical tool for evaluating the proposed adaptation measures, is simulation models of future climatic
strains. Using future climate scenarios introduces uncertainties into the study conclusions, as they
are based on complex socio-economic and meteorological models and predict consequences far into
the future. Accounting for, and treatment of, these uncertainties are paramount for the quality of
the results. We have mapped the methodology used for calculating the climate strains in building
simulation models in 132 studies within the topic of building adaptation measures from the past 7
years. In particular, the treatment of climate-model induced uncertainties and presentation of their
influence on the final results have been mapped.

In order to quantify the uncertainties introduced by climate-modelling in some way, the calculated
climatic strains need to be based on more than one strain of climate-models, to root out the
variations, biases, and deviations in the chosen model. The studies presenting the most
comprehensive evaluation of climate related uncertainties produced means and standard deviations
for all used-GCM-RCM chains and evaluated the variations. The methods for downscaling and bias-
correcting were well-documented in these studies, providing a transparent presentation of the
underlying uncertainties. Producing such results is work-demanding and probabilistic results may be
more challenging to present in a clear way. However, presenting an analysis of the uncertainties
greatly increases the quality and credibility of the results, and even more importantly it reminds the
reader that assessments of complex systems far into the future are not deterministic in nature.

The different kinds of uncertainties introduced from climate-modelling found in the study selection
have been characterized and structured by level of uncertainty and source of uncertainty in this
paper, as well as how they are dealt with in principle. Further, a flow chart of how information loss
increases progressively through methodological choices along the way from emission scenario to
result presentation have been mapped and structured, as a tool for addressing the climate-
modelling-specific uncertainties in such studies. A frequent conclusion in studies calculating and
analyzing the uncertainties was that this should not be omitted, as it was found to have a great
impact on the results. By careful description of the methods, by calculating and carrying quantified
uncertainties from the climate-model to the results, and by evaluating the validity of the results, the
reader of such studies will certainly be reminded of the uncertain nature of the future.

How to cite: Gaarder, J. E., Hygen, H. O., and Kvande, T.: Methodological choices influencing uncertainties andinformation loss in research on climate adaptation of buildings, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-498, https://doi.org/10.5194/ems2022-498, 2022.

Responding to the challenges of a changing climate requires information that is relevant and actionable at the local scale where adaptation actions take place. Here we describe the development of Klimaatlas, the Danish National Climate Atlas, a tool to provide information to ministries, regional authorities, businesses and citizens about climate change in Denmark.  We focus in particular on the key decisions that needed to be made during development and the lessons learnt from doing so that are relevant to the development of similar tools in other jurisdictions. We describe the user groups that we involved in the development of the atlas, how their interactions shaped the final product, and the ongoing role of the user in the project. Communication and dissemination of results was approached on three different levels simultaneously, and we describe this approach, and its benefits, in detail. We detail some of the major technical challenges faced, particularly around the choice of bias-correction methods, and how these issues were overcome. The approach to quantifying and communicating uncertainty, and its importance, also receives particular attention. We assess the impact of Klimaatlas, and the challenges around quantifying its usefulness, together with the results of a recent user survey identifying the strengths and weaknesses. We also place Klimaatlas in the context of other comparable products, and particularly the recently developed IPCC Interactive Atlas. Finally, we discuss issues around future maintenance and possible expansions of Klimaatlas, including the use of convection permitting simulations, incorporation of compound events, updates between IPCC cycles and extensions to new sectors.

How to cite: Payne, M. R., Sørensen, A., Christiansen, B., Andree, E., Boberg, F., Su, J., Madsen, K. S., Madsen, M. S., Olesen, M., Christensen, O. B., Pedersen, R. A., Thejll, P., Langen, P. L., Olsen, S. M., and Schmith, T.: Lessons in climate service development from Klimaatlas, the Danish National Climate Atlas, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-579, https://doi.org/10.5194/ems2022-579, 2022.

DWD publishes operational seasonal climate predictions since 2016. In the following years work towards a seamless climate predictions website commenced, with the aim to provide consistent climate predictions across all timescales, focused on the needs of national users.

Today, the DWD climate predictions website www.dwd.de/climatepredictions contains operational decadal and seasonal predictions. Next, we will add post-processed subseasonal prediction products, derived from the IFS forecasts provided by ECMWF, as a further step towards the seamless climate prediction approach.

The user-oriented graphical presentation of the climate predictions is identical over all timescales. It was co-designed with stakeholders from various sectors at user workshops on climate predictions and through surveys and individual user meetings to guarantee its comprehensibility and usability. This co-design always includes the aspect of how the available predictive power is clearly addressed and its limitations are presented in a way that is understandable to users.

As a result, the website offers different layers of information on a basic and an expert level. It includes maps, time series and tables of 1- and 5-year means (decadal) and 3-month means (seasonal) ensemble mean and probabilistic predictions of temperature and precipitation on a global scale and for Europe, Germany, and German regions. For the subseasonal scale, we will add corresponding figures for weekly means of temperature and precipitation.

The information on DWD’s climate predictions website is retrieved from post-processed model output of the German seasonal and decadal prediction systems based on MPI-ESM. A statistical recalibration is applied to improve the skill of decadal climate predictions. It performs a drift correction as well as a lead time dependent optimization of conditional bias and ensemble spread. To fit the needs of German climate data users of a high spatial resolution in Germany (~20 km) and for climate predictions for German cities (based on ~5 km simulations), the empirical-statistical downscaling EPISODES is applied. All predictions are displayed in combination with their skill.

We work on several extensions of the website: multi-year seasonal predictions (e.g. 5-year summer means), the prediction of extreme indices (e.g. drought indices) and El Nino Southern Oscillation predictions. In addition, a seamless time series combining observations, climate predictions and climate projections is in preparation.

How to cite: Mannig, B., Paxian, A., Tivig, M., Pankatz, K., Fröhlich, K., Hoff, A., Reinhardt, K., Isensee, K., Wehring, S., Buchholz, S., Pasternack, A., Lorenz, P., Kreienkamp, F., and Früh, B.: User-tailored climate predictions – the DWD climate predictions website, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-583, https://doi.org/10.5194/ems2022-583, 2022.