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The Digital Earth project aimed for the integration of data science and Earth science. Here, we reflect on the main lessons learned that include the need for interdisciplinary collaboration, thinking out of the box, the concept of ‘thinking in workflows’ and models for the sustainable implementation of scientific software, data infrastructure and policies.

Digital Earth is a project funded by the German Helmholtz Association with all centers of the research field Earth and Environment involved. The main goal of the Digital Earth project is to develop and bundle data science methods in extendable and maintainable scientific workflows that enable natural scientists in collaboration with data scientists to achieve a deeper understanding of the Earth system. This has been achieved by developing solutions for data analysis and exploration with visual and computational approaches with data obtained in a SMART monitoring approach and modeling studies, accompanied by a continuous evaluation of the collaboration processes. In this chapter, the history, setup, and focus of the Digital Earth project are described.

Digital Earth is a project funded by the German Helmholtz Association with all centers of the research field Earth and Environment involved. The main goal of the Digital Earth project is to develop and bundle data science methods in extendable and maintainable scientific workflows that enable natural scientists in collaboration with data scientists to achieve a deeper understanding of the Earth system. This has been achieved by developing solutions for data analysis and exploration with visual and computational approaches with data obtained in a SMART monitoring approach and modelingstudies, accompanied by acontinuous evaluation of the collaboration processes. In this chapter, the history, setup, and focus of the Digital Earth project are described.

Climate change and its socio-ecological impacts affect all sectors of society. To tackle the multiple risks of climate change the field of climate services evolved during the last decades. In this scientific field products to be applied in practice are developed in constant interaction between climate service providers and users. To judge the effectiveness of these co-creation endeavours, evaluation is crucial. At present, output and outcome assessments are conducted occasionally in this research field. However, the summative evaluation does not help to adjust the ongoing process of co-creation. Thus, our work focuses on the formative evaluation of co-creative development of science-based climate service products. As the first step, main characteristics of the product development process were identified empirically. Secondly, we determined the six sub- processes of climate service product development and related process steps. Thirdly, we selected the questions for the formative evaluation relevant to all the sub-processes and process-steps. Then, a literature review delivered the theoretical background for further work and revealed further quality aspects. These aspects from literature were brought together with our results from the empirical work. In the end, we created a new scheme of quality criteria and related assessment questions for the different sub-processes in climate services, based on both, empirical and theoretical work. As the authors take into account the process of co-production in a real-life case, the criteria and assessment questions proposed are operational and hands-on. The quality aspects refer to the five principles of applicability, theoretical and empirical foundation, professionalism, transparency of processes and the disclosure of preconditions. They are elaborated comprehensively in our study. The resulting formative evalu- ation scheme is novel in climate service science and practice and useful in improving the co-creation processes in climate services and beyond.

The Digital Earth project aimed for the integration of data science and Earth science. Here, we reflect on the main lessons learned that include the need for interdisciplinary collaboration, thinking out of the box, the concept of ‘thinking in workflows’ and models for the sustainable implementation of scientific software, data infrastructure and policies.

Artificial intelligence and machine learning (ML) methods are increasinglyappliedinEarthsystemresearch,forimprovingdataanalysis,andmodelperformance,andeventuallysystemunderstanding.IntheDigitalEarthproject,severalML approaches have been tested and applied, and are discussed in this chapter. These include data analysis using supervised learning and classification for detection of river levees and underwater ammunition; process estimation of methane emissions andforenvironmentalhealth;point-to-spaceextrapolationofvaryingobservedquantities; anomaly and event detection in spatial and temporal geoscientific datasets. We present the approaches and results, and finally, we provide some conclusions on the broad applications of these computational data exploration methods and approaches.

In this study, the projected future long-term changes of the local wave conditions at the German Baltic Sea coast over the course of the 21st century are analyzed and assessed with special focus on model agreement, statistical significance and ranges/spread of the results. An ensemble of new regional climate model (RCM) simulations with the RCM REMO for three RCP forcing scenarios was used as input data. The outstanding feature of the simulations is that the data are available with a high horizontal resolution and at hourly timesteps which is a high temporal resolution and beneficial for the wind&ndash, wave modelling. A new data interface between RCM output data and wind&ndash, wave modelling has been developed. Suitable spatial aggregation methods of the RCM wind data have been tested and used to generate input for the calculation of waves at quasi deep-water conditions and at a mean water level with a hybrid approach that enables the fast compilation of future long-term time series of significant wave height, mean wave period and direction for an ensemble of RCM data. Changes of the average wind and wave conditions have been found, with a majority of the changes occurring for the RCP8.5 forcing scenario and at the end of the 21st century. At westerly wind-exposed locations mainly increasing values of the wind speed, significant wave height and mean wave period have been noted. In contrast, at easterly wind-exposed locations, decreasing values are predominant. Regarding the changes of the mean wind and wave directions, westerly directions becoming more frequent. Additional research is needed regarding the long-term changes of extreme wave events, e.g., the choice of a best-fit extreme value distribution function and the spatial aggregation method of the wind data.

The CORDEX-CORE initiative was developed with the aim of producing homogeneous regional climate model (RCM) projections over domains world wide. In its first phase, two RCMs were run at 0.22° resolution downscaling 3 global climate models (GCMs) from the CMIP5 program for 9 CORDEX domains and two climate scenarios, the RCP2.6 and RCP8.5. The CORDEX-CORE simulations along with the CMIP5 GCM ensemble and the most recently produced CMIP6 GCM ensemble are analyzed, with focus on several temperature, heat, wet and dry hazard indicators for present day and mid-century and far future time slices. The CORDEX-CORE ensemble shows a better performance than the driving GCMs for several hazard indices due to its higher spatial resolution. For the far future time slice the 3 ensembles project an increase in all temperature and heat indices analyzed under the RCP8.5 scenario. The largest increases are always shown by the CMIP6 ensemble, except for Tx > 35 °C, for which the CORDEX-CORE projects higher warming. Extreme wet and flood prone maxima are projected to increase by the RCM ensemble over the la Plata basin in South America, the Congo basin in Africa, east North America, north east Europe, India and Indochina, regions where a better performance is obtained, whereas the GCM ensembles show small or negligible signals. Compound hazard hotspots based on heat, drought and wet indicators are detected in each continent worldwide in region like Central America, the Amazon, the Mediterranean, South Africa and Australia, where a linear relation is shown between the heatwave and drought change signal, and region like Arabian peninsula, the central and south east Africa region (SEAF), the north west America (NWN), south east Asia, India, China and central and northern European regions (WCE, NEU) where the same linear relation is found for extreme precipitation and HW increases. Although still limited, the CORDEX-CORE initiative was able to produce high resolution climate projections with almost global coverage and can provide an important resource for impact assessment and climate service activities.

Urban decision makers rely on evidence-based climate information tailored to their needs to adequately adapt and prepare for future climate change impacts. Regional climate models, with grid sizes between 50-10 km, are a useful outset to understand potential future climate change impacts in urban regions. The recently developed convection-permitting models have grid sizes less than 5 km, and better resolve smaller scale atmospheric processes such as convection, and its interactions with the land surface, by also better representing complex terrain, for instance cities. This study investigates how the convection-permitting resolution affects the simulation of climate change conditions in the urban-rural context, demonstrated through three impact cases: influenza spread and survival; ragweed pollen dispersion, and in-door mold growth. Simulations by the regional climate model REMO are analyzed for the near future (2041-2050) under emission scenario RCP8.5. Taking the Berlin region as a testbed, the findings show that the change signal reverses for the 3 km compared to the 12.5 km grid resolution for the impact cases pollen, and mold, which indicates an added value. More pollen days are projected in Berlin under future climate conditions. Less mold days can be expected, but longer consecutive periods, under future climate conditions. For influenza, the convection-permitting resolution intensifies the decrease of influenza days, nevertheless longer periods of consecutive influenza days are found under near-term climate change. The results show the potential of convection-permitting simulations to generate improved information about climate change impacts for urban regions to support decision makers, and in order to build the resilient cities of tomorrow.

The Hengduan Mountains and Tibetan Plateau possess unique topographical characteristics that serve as an effective blocking of the movement of the westerly wind in the middle and lower troposphere towards East China. This study examines results from a regional climate model (REMO) at the resolutions of 25 and 50 km for the period 1980–2012. The model is run using lateral boundary conditions from ERA-Interim (European Centre for Medium-Range Weather Forecasts interim reanalysis). There are only a few differences between 25 and 50 km in land surface/vegetation characteristics, but the major differences in this region are due to the orography. Results show that the high-resolution simulation performance is poor in winter, when southwesterly wind prevails, whereas it performs well in summer, when the westerly wind is substantially weakened in southern China. In comparison to the ERA-Interim wind field, the high-resolution simulation overestimates the air flow over the Hengduan Mountains near the ground surface, which influences the transport of atmospheric water vapor in the downstream region, i.e., over southern China. Specifically, with the help of the overestimated southwesterly wind, the amount of atmospheric water vapor transported increases considerably perennially by up to 20% in southern China, while it decreases remarkably by more than 5% throughout the year in a large area of Central and North China. These features lead to excessive precipitation and underestimated cloud cover in southern China, which probably causes the overestimated 2-m temperature in southern China. Our study emphasizes that, in such high-resolution-model studies for East Asia, special attention should be paid to the near-surface winds over the Hengduan Mountains.

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The main objective of this study is the coupling of the regional climate model REMO with a new land surface scheme including dynamic vegetation phenology, and the evaluation of the new model version called REMO with interactive MOsaic-based VEgetation: REMO-iMOVE. First, we focus on the documentation of the technical aspects of the new model constituents and the coupling mechanism. The representation of vegetation in iMOVE is based on plant functional types (PFTs). Their geographical distribution is prescribed to the model which can be derived from different land surface data sets. Here, the PFT distribution is derived from the GLOBCOVER 2000 data set which is available on 1 km × 1 km horizontal resolution. Plant physiological processes like photosynthesis, respiration and transpiration are incorporated into the model. The vegetation modules are fully coupled to atmosphere and soil. In this way, plant physiological activity is directly driven by atmospheric and soil conditions at the model time step (two minutes to some seconds). In turn, the vegetation processes and properties influence the exchange of substances, energy and momentum between land and atmosphere. With the new coupled regional model system, dynamic feedbacks between vegetation, soil and atmosphere are represented at regional to local scale. In the evaluation part, we compare simulation results of REMO-iMOVE and of the reference version REMO2009 to multiple observation data sets of temperature, precipitation, latent heat flux, leaf area index and net primary production, in order to investigate the sensitivity of the regional model to the new land surface scheme and to evaluate the performance of both model versions. Simulations for the regional model domain Europe on a horizontal resolution of 0.44° had been carried out for the time period 1995–2005, forced with ECMWF ERA-Interim reanalyses data as lateral boundary conditions. REMO-iMOVE is able to simulate the European climate with the same quality as the parent model REMO2009. Differences in near-surface climate parameters can be restricted to some regions and are mainly related to the new representation of vegetation phenology. The seasonal and interannual variations in growth and senescence of vegetation are captured by the model. The net primary productivity lies in the range of observed values for most European regions. This study reveals the need for implementing vertical soil water dynamics in order to differentiate the access of plants to water due to different rooting depths. This gets especially important if the model will be used in dynamic vegetation studies.

BACKGROUND: A regional-scale sensitivity study has been carried out to investigate the climatic effects of forest cover change in Europe. Applying REMO (regional climate model of the Max Planck Institute for Meteorology), the projected temperature and precipitation tendencies have been analysed for summer, based on the results of the A2 IPCC-SRES emission scenario simulation. For the end of the 21st century it has been studied, whether the assumed forest cover increase could reduce the effects of the greenhouse gas concentration change. RESULTS: Based on the simulation results, biogeophysical effects of the hypothetic potential afforestation may lead to cooler and moister conditions during summer in most parts of the temperate zone. The largest relative effects of forest cover increase can be expected in northern Germany, Poland and Ukraine, which is 15-20% of the climate change signal for temperature and more than 50% for precipitation. In northern Germany and France, potential afforestation may enhance the effects of emission change, resulting in more severe heavy precipitation events. The probability of dry days and warm temperature extremes would decrease. CONCLUSIONS: Large contiguous forest blocks can have distinctive biogeophysical effect on the climate on regional and local scale. In certain regions of the temperate zone, climate change signal due to greenhouse gas emission can be reduced by afforestation due to the dominant evaporative cooling effect during summer. Results of this case study with a hypothetical land cover change can contribute to the assessment of the role of forests in adapting to climate change. Thus they can build an important basis of the future forest policy.

The Digital Earth project aims at a strong interrelation between Data and Earth Science and a step-change in implementing data science methods within Earth science research. During the project, the progress of interdisciplinary collaboration and adoption of data science methods has been measured and assessed with the goal to trace the success of the project. This chapter provides the set-up of this evaluation and the results from two online questionnaires that were held after the start and before the end of the project.

This open access book presents the results of three years collaboration between earth scientists and data scientist, in developing and applying data science methods for scientific discovery. The book will be highly beneficial for other researchers at senior and graduate level, interested in applying visual data exploration, computational approaches and scientifc workflows.

The European CORDEX (EURO-CORDEX) initiative is a large voluntary effort that seeks to advance regional climate and Earth system science in Europe. As part of the World Climate Research Programme (WCRP) - Coordinated Regional Downscaling Experiment (CORDEX), it shares the broader goals of providing a model evaluation and climate projection framework and improving communication with both the General Circulation Model (GCM) and climate data user communities. EURO-CORDEX oversees the design and coordination of ongoing ensembles of regional climate projections of unprecedented size and resolution (0.11° EUR-11 and 0.44° EUR-44 domains). Additionally, the inclusion of empirical-statistical downscaling allows investigation of much larger multi-model ensembles. These complementary approaches provide a foundation for scientific studies within the climate research community and others. The value of the EURO-CORDEX ensemble is shown via numerous peer-reviewed studies and its use in the development of climate services. Evaluations of the EUR-44 and EUR-11 ensembles also show the benefits of higher resolution. However, significant challenges remain. To further advance scientific understanding, two flagship pilot studies (FPS) were initiated. The first investigates local-regional phenomena at convection-permitting scales over central Europe and the Mediterranean in collaboration with the Med-CORDEX community. The second investigates the impacts of land cover changes on European climate across spatial and temporal scales. Over the coming years, the EURO-CORDEX community looks forward to closer collaboration with other communities, new advances, supporting international initiatives such as the IPCC reports, and continuing to provide the basis for research on regional climate impacts and adaptation in Europe., S.S. acknowledges the support of NOTUR/NORSTORE projects NN9280K/NS9001K and the Research Council of Norway and its basic institute support of the strategic project on Climate Services. E.K. acknowledges the support of the Greek Research & Technology Network (GRNET) for provision of technical support and facilities (HPC-ARIS). L.S. and I.G. acknowledge the support of Croatian Science Foundation project CARE (2831) and Ministry of Environment and Energy project TF/HR/P3-M1-O1-0101 (www.prilagodba-klimi.hr). J. F. acknowledges support from the Spanish R+D Programme through grant INSIGNIA (CGL2016-79210-R), co-funded by ERDF/FEDER, and the Altamira Supercomputer at Instituto de Física de Cantabria (IFCA-CSIC), member of the Spanish Supercomputing Network. P.T. acknowledges support from the Belgian Science Policy (BELSPO) within the CORDEX.be (BR/143/A2) project, and the VSC (Flemish Supercomputer Center), funded by the Research Foundation - Flanders (FWO) and the Flemish Government – department EWI.M.A.G. acknowledges support from the Spanish R+D Programme through grants CGL2013-47261-R and CGL2017-89583-R, co-funded by the European Regional Development Fund. RF acknowledges support provided by ICHEC (Irish Centre for High End Computing) and the Irish Environmental Protection Agency. K.G. and S.K. gratefully acknowledge the computing time granted through JARA-HPC on the supercomputers JUROPA and JURECA at Forschungszentrum Jülich. M.B. and T.H. acknowledge support by The Ministry of Education, Youth and Sports from the Large Infrastructures for Research, Experimental Development and Innovations project “IT4Innovations National Supercomputing Center – LM2015070” and the INTER-EXCELLENCE program LTT17007, and support by Charles University from the PROGRES Q16 program. We acknowledge the approval and support of the two Flagship Pilot Studies (the FPS on Convective phenomena at high resolution over Europe and the Mediterranean and the FPS on Land Use and Climate Across Scales) by WRCP CORDEX. We thank Merja Tölle for providing simulation CCLM5-0-9-JLU as contribution to the CORDEX-FPS “Convective phenomena at high resolution over Europe and the Mediterranean”. D. M., M.P., and H.T. gratefully acknowledge the support received via the projects HighEnd:Extremes, SPIRIT, and reclip:convex, funded by the Austrian Climate Research Programme (ACRP) of the Klima- und Energiefonds (nos. B368608, B960272, and B769999, respectively), as well as the Jülich Supercomputing Centre (JSC) for compute time on JURECA through the grant JJSC39 and the Vienna Scientific Cluster (VSC) through the grants 70992 and 71193.