ICON in Climate Limited-area Mode (ICON release version 2.6.1): a new regional climate model

For the first time, the Limited-Area Mode of the new ICON (Icosahedral Nonhydrostatic) weather and climate model has been used for a continuous long-term regional climate simulation over Europe. Built upon the Limited-Area Mode of ICON (ICON-LAM), ICON-CLM (ICON in Climate Limited-area Mode, hereafter ICON-CLM, available in ICON release version 2.6.1) is an adaptation for climate applications. A first version of ICON-CLM is now available and has already been integrated into a starter package (ICON-CLM_SP_betal). The starter package provides users with a technical infrastructure that facilitates long-term simulations as well as model evaluation and test routines. ICON-CLM and ICON-CLM_SP were successfully installed and tested on two different computing systems. Tests with different domain decompositions showed bit-identical results, and no systematic outstanding differences were found in the results with different model time steps. ICON-CLM was also able to reproduce the large-scale atmospheric information from the global driving model. Comparison was done between ICON-CLM and the COnsortium for Small-scale MOdeling (COSMO)-CLM (the recommended model configuration by the CLM-Community) performance. For that, an evaluation run of ICON-CLM with ERA-Interim boundary conditions was carried out with the setup similar to the COSMO-CLM recommended optimal setup. ICON-CLM results showed biases in the same range as those of COSMO-CLM for all evaluated surface variables. While this COSMO-CLM simulation was carried out with the latest model version which has been developed and was carefully tuned for climate simulations on the European domain, ICON-CLM was not tuned yet. Nevertheless, ICON-CLM showed a better performance for air temperature and its daily extremes, and slightly better performance for total cloud cover. For precipitation and mean sea level pressure, COSMO-CLM was closer to observations than ICON-CLM. However, as ICON-CLM is still in the early stage of development, there is still much room for improvement

Cost-effective conservation in the face of climate change: combining ecological-economic modelling and climate science for the cost-effective spatio-temporal allocation of conservation measures in agricultural landscapes

In agricultural landscapes, climate change has profound impacts on species that society aims to conserve. In response to climate change, species may adapt spatially (with range shifts) and temporally (with phenological adaptations), which may make formerly effective conservation sites and measures less effective. As climate change also has an impact on yields, opportunity costs of land use-based conservation measures may also change spatially and with respect to the timing of conservation measures. Due to these spatio-temporal modifications of the costs of conservation measures and their impacts on species, formerly cost-effective conservation sites and measures may no longer be so in a changing climate. We combine ecological-economic modelling with climate science to investigate climate change-induced modifications of the timing and spatial allocation of cost-effective conservation measures. We apply our model to the case study of conserving the large marsh grasshopper on agricultural grasslands in the German federal state of Schleswig-Holstein. Comparing the periods 2020-2039 and 2060-2079, our model indeed indicates that climate change induces modifications in the cost-effective spatial allocation of conservation measures and that measures which are adapted to phenological changes remain cost-effective under climate change

The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, part I: Evaluation of precipitation

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼ 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼ −40% at 12 km to ∼ −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales.Fil: Ban, Nikolina. Universidad de Innsbruck; AustriaFil: Caillaud, Cécile. Université de Toulouse; FranciaFil: Coppola, Erika. The Abdus Salam. International Centre for Theoretical Physics; Italia. The Abdus Salam; ItaliaFil: Pichelli, Emanuela. The Abdus Salam; Italia. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Sobolowski, Stefan. Norwegian Research Centre; NoruegaFil: Adinolfi, Marianna. Fondazione Centro Euro-Mediterraneo sui cambiamenti climatici; ItaliaFil: Ahrens, Bodo. Goethe Universitat Frankfurt; AlemaniaFil: Alias, Antoinette. Université de Toulouse; FranciaFil: Anders, Ivonne. German Climate Computing Center; AlemaniaFil: Bastin, Sophie. Universite Paris-Saclay;Fil: Belušić, Danijel. Swedish Meteorological and Hydrological Institute; SuizaFil: Berthou, Ségolène. Met Office Hadley Centre; Reino UnidoFil: Brisson, Erwan. Université de Toulouse; FranciaFil: Cardoso, Rita M.. Universidade Nova de Lisboa; PortugalFil: Chan, Steven C.. University of Newcastle; Reino UnidoFil: Christensen, Ole Bøssing. Danish Meteorological Institute; DinamarcaFil: Fernández, Jesús. Universidad de Cantabria; EspañaFil: Fita Borrell, Lluís. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios del Clima y sus Impactos; ArgentinaFil: Frisius, Thomas. Helmholtz Gemeinschaft; AlemaniaFil: Gaparac, Goran. Croatia Control Ltd.; CroaciaFil: Giorgi, Filippo. The Abdus Salam. International Centre for Theoretical Physics; Italia. The Abdus Salam; ItaliaFil: Goergen, Klaus. Centre for High-Performance Scientific Computing in Terrestrial Systems; Alemania. Helmholtz Gemeinschaft. Forschungszentrum Jülich; AlemaniaFil: Haugen, Jan Erik. Norwegian Meteorological Institute; NoruegaFil: Hodnebrog, Øivind. Center for International Climate and Environmental Research-Oslo; NoruegaFil: Kartsios, Stergios. Aristotle University Of Thessaloniki; GreciaFil: Katragkou, Eleni. Aristotle University Of Thessaloniki; GreciaFil: Kendon, Elizabeth J.. Met Office Hadley Centre; Reino UnidoFil: Keuler, Klaus. Brandenburg University of Technology Cottbus-Senftenberg; AlemaniaFil: Lavin Gullon, Alvaro. Universidad de Cantabria; EspañaFil: Lenderink, Geert. Royal Netherlands Meteorological Institute; Países Bajo

COSMO-CLM regional climate simulations in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework: a review

In the last decade, the Climate Limited-area Modeling Community (CLM-Community) has contributed to the Coordinated Regional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM-Community model, ERA-Interim reanalysis and eight global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44∘ (∼ 50 km), 0.22∘ (∼ 25 km), and 0.11∘ (∼ 12 km) over the CORDEX domains Europe, South Asia, East Asia, Australasia, and Africa. This major effort resulted in 80 regional climate simulations publicly available through the Earth System Grid Federation (ESGF) web portals for use in impact studies and climate scenario assessments. Here we review the production of these simulations and assess their results in terms of mean near-surface temperature and precipitation to aid the future design of the COSMO-CLM model simulations. It is found that a domain-specific parameter tuning is beneficial, while increasing horizontal model resolution (from 50 to 25 or 12 km grid spacing) alone does not always improve the performance of the simulation. Moreover, the COSMO-CLM performance depends on the driving data. This is generally more important than the dependence on horizontal resolution, model version, and configuration. Our results emphasize the importance of performing regional climate projections in a coordinated way, where guidance from both the global (GCM) and regional (RCM) climate modeling communities is needed to increase the reliability of the GCM–RCM modeling chain

The worldwide C3S CORDEX grand ensemble: A major contribution to assess regional climate change in the IPCC AR6 Atlas

peer reviewedAbstract The collaboration between the Coordinated Regional Climate Downscaling Experiment (CORDEX) and the Earth System Grid Federation (ESGF) provides open access to an unprecedented ensemble of Regional Climate Model (RCM) simulations, across the 14 CORDEX continental-scale domains, with global coverage. These simulations have been used as a new line of evidence to assess regional climate projections in the latest contribution of the Working Group I (WGI) to the IPCC Sixth Assessment Report (AR6), particularly in the regional chapters and the Atlas. Here, we present the work done in the framework of the Copernicus Climate Change Service (C3S) to assemble a consistent worldwide CORDEX grand ensemble, aligned with the deadlines and activities of IPCC AR6. This work addressed the uneven and heterogeneous availability of CORDEX ESGF data by supporting publication in CORDEX domains with few archived simulations and performing quality control. It also addressed the lack of comprehensive documentation by compiling information from all contributing regional models, allowing for an informed use of data. In addition to presenting the worldwide CORDEX dataset, we assess here its consistency for precipitation and temperature by comparing climate change signals in regions with overlapping CORDEX domains, obtaining overall coincident regional climate change signals. The C3S CORDEX dataset has been used for the assessment of regional climate change in the IPCC AR6 (and for the interactive Atlas) and is available through the Copernicus Climate Data Store (CDS)

Regional climate change over Europe in COSMO-CLM: Influence of emission scenario and driving global model

The variability of climate change over Europe is analyzed in a new ensemble of eight high-resolution scenario simulations with the dynamically nested regional climate model COSMO-CLM. The simulations are a contribution of the CLM-Community to EURO-CORDEX – the European branch of the international CORDEX initiative. The study documents the influence of two emission scenarios (RCP4.5 and RCP8.5) and four driving global climate models (MPI-ESM-LR, HadGEM2-ES, CNRM-CM5, EC-EARTH) on the climate change signal of seasonal near-surface air temperature, seasonal precipitation amount and daily precipitation intensity in eight different regions of Europe. Both temperature and precipitation changes show comparable spatial patterns across the ensemble. The warming magnitude, however, strongly depends on the emission scenario and the driving GCM. The analysis demonstrates that the influence of the driving GCM on the temperature change signal can be of comparable magnitude as the influence of the emission scenario. For seasonal precipitation changes the influence of the driving GCM is even more important. All ensemble members show a consistent increase in the frequency of days with intense precipitation while the total number of precipitation days decreases. A further aspect is the comparison between the climate change signals in the regional and the driving global simulations. A critical intensity class is used to quantify the transition from decreasing to increasing precipitation frequencies. The analysis reveals that the variability of frequency changes is smaller in the regional than in the global model ensemble, which can be interpreted as an improved robustness and a possible added value of the regional projections. It is also shown that the regional simulations tend to reduce the seasonal mean temperature change of the driving global simulation. In some seasons and regions the damping of the warming signal can amount to more than 2 K. Overall, the analysis reveals a strong influence of comparable magnitude of the choice of the emission scenario and the driving global model on regional climate change signals, and stresses the necessity of a large regional model ensemble for a reliable and robust assessment of regional climate change.ISSN:0941-2948ISSN:1610-122