Displays

The Coordinated Output for Regional Evaluations (CORE) simulation ensemble is an effort of the WCRP CORDEX community to provide high-resolution regional climate change information for the major inhabited areas of the world and thus generate a solid scientific basis for further research related vulnerability, impact, adaptation and climate services. This is especially important in those areas in which only a few high-resolution simulations or only comparatively coarse simulations from global models were available. The driving global climate model (GCM) simulations were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. Initially, two regional climate models (RCMs) REMO and RegCM4 were used to downscale GCM output to a spatial resolution of 0.22°. It is intended that the CORDEX-CORE ensemble can then be extended by additional regional simulations to further increase the ensemble size and thus the representation of possible future climate change pathways. 

The aim of this study is to investigate and document the climate change information provided by the current CORDEX-CORE ensemble with respect to the mean climate change in different regions of the world and in comparison to previously existing global climate information, especially those global climate simulations used as boundary forcing for CORDEX-CORE RCMs. First, the regional biases of the RCMs simulations and its driving GCMs simulations were quantified compared to the CRU TS 4.02 observational dataset during the reference period from 1971 to 2000. Second, the near future (2036 to 2065) and far future (2071 to 2099) climate change signals were quantified from the new CORDEX-CORE ensemble. The analysis focuses on the mean temperature and precipitation changes based on the new IPCC physical climate reference regions. For selected regions, the differences of the climate change information at different resolutions are documented. Using this selected regions, the climate change signals from the CORDEX-CORE ensemble were compared to other existing CORDEX simulations and the CMIP5 GCM ensemble. First results of this comparison will be presented.

How to cite: Teichmann, C., Jacob, D., Remedio, A. R., and Coppola, E. and the CORDEX-CORE team: Assessing mean climate change signals in the global CORDEX-CORE ensemble, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20479, https://doi.org/10.5194/egusphere-egu2020-20479, 2020.

Projections of the precipitation associated with cyclones in the main cyclogenetic regions of the Extratropical Southern Hemisphere domains (Africa - AFR, Australia - AUS and South America - SAM) are here analyzed during the winter season (JJA). The projections were obtained with the Regional Climate Model version 4 (RegCM4) nested in three global climate models (GCMs) from the Coupled Model Intercomparison Project phase 5 (CMIP5) under the Representative Concentration Pathway 8.5. RegCM4 simulations were executed with horizontal grid spacing of 25 km and for the period 1979-2100. As reference period, we consider the interval 1995-2014 and as future climate, the period 2080-2099. Cyclones are identified using an algorithm based on the neighbor nearest approach applied to 6 hourly mean sea level pressure (SLP) fields. In SAM and AUS domains, two hotspot regions for cyclogenesis are selected while for AFR only one is considered. First, in each hotspot region, the cyclogeneses are identified and, then, the mean precipitation from the previous day (day_-1) to the day after (day₊₁) of these processes is calculated. A general negative trend in the cyclone's frequency is projected for the period 2080-2099. However, for the same period, it is projected an increase of precipitation intensity for AFR domain, mainly near the southwestern coast of the continent. In AUS the increase is observed between southeastern Australia and New Zeland, and over north New Zealand. For SAM there is an expansion of the area with a maximum precipitation intensity close to southern Brazil and Uruguay and to the east of 60^oW near 40^oS. Summarizing, the precipitation associated with individual cyclones will increase on average in the future (for example 30% in the SAM domain), being the storms less frequent but more intense.

How to cite: Reboita, M., Reale, M., da Rocha, R., Giuliani, G., Coppola, E., Nino, R., Llopart, M., Torres, J., and Cavazos, T.: Precipitation Associated with Cyclogenetic Hotspot Regions in the Extratropical Southern Hemisphere: CORDEX-CORE Projections , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3147, https://doi.org/10.5194/egusphere-egu2020-3147, 2020.

One of the most largely recognized effect of the Global Warming is the change of weather extremes. The increase of extreme precipitation events is directly linked to a greater availability of precipitable water induced by a warmer atmosphere.The flood projected signals are heterogeneous and influenced by different phenomena. As an example, the rise in temperature could increase the risk of floods over the regions sensible to extreme precipitations and at the same time could reduce the risk of floods over the regions sensible to the melted snow accumulated during the cold season. In this work the CORDEX-CORE simulations completed using two different Regional Climate Models (RegCM and REMO) are used to estimate the future changes on flood risk for eight CORDEX domains (North-America, Central-America, South-America, Europe, Africa, West-Asia, East-Asia, South-East-Asia and Australasia). A river-routing model is applied to simulate the river discharge of a high resolution grid (0.06 degree) for three different driving Global Climate Models, two different scenarios (rcp2.6 and rcp8.5) and for each of the domains. The simulated discharges are hence used to fit a generalized extreme value (GEV) distribution to estimate the change on flood risk related to the future climate projections.

How to cite: Raffaele, F. and Di Sante, F. and the CORDEX-CORE: Future projections of river floods hazard over the multiple CORDEX-CORE domains, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18858, https://doi.org/10.5194/egusphere-egu2020-18858, 2020.

Regional Climate Models (RCMs) have undergone substantial development, resulting in increasingly reliable high-resolution simulations. Despite this, the added value of these simulations compared to their driving General Circulation Models (GCMs) has been a recurring issue. Past studies have used different techniques to quantify the added value of a RCM. A new method is now being presented, based on these past studies, that quantifies the added value and presents it spatially. The method was also adapted to assess the Downscaling Signal (DS) in climate change simulations and compare this to the added value.

This new method has been used to assess the daily precipitation of the 55-model EURO-CORDEX ensemble and the CORDEX-CORE ensemble, focusing especially on the higher-end of the PDFs. This revealed an overall positive added value across all domains, especially in areas of complex topography, cost-lines, and tropical regions. This DS was similar to that of the added value when looking at RCP 8.5 far-future simulations.

How to cite: Ciarlo`, J. M., Coppola, E., Fantini, A., Gao, X., Tong, Y., Glazer, R. H., Torres Alavez, J. A., Sines, T., Pichelli, E., Raffaele, F., Das, S., Ashfaq, M., Im, E.-S., Nguyen-Xuan, T., Teichmann, C., Remedio, A., Remke, T., Bülow, K., Weber, T., Buntemeyer, L., Sieck, K., Rechid, D., and Jacob, D.: A new spatially distributed Added Value Index for Regional Climate Models: the EURO-CORDEX and the CORDEX-CORE highest resolution ensembles, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2611, https://doi.org/10.5194/egusphere-egu2020-2611, 2020.

We use an unprecedented ensemble of regional climate model (RCM) projections over seven regional CORDEX domains to provide, for the first time, an RCM-based global view of monsoon changes at various levels of increased greenhouse gas (GHG) forcing. All regional simulations are conducted using RegCM4 at a 25km horizontal grid spacing using lateral and lower boundary forcing from three General Circulation Models (GCMs), which are part of the fifth phase of the Coupled Model Inter-comparison Project (CMIP5). Each simulation covers the period from 1970 through 2100 under two Representative Concentration Pathways (RCP2.6 and RCP8.5). Regional climate simulations exhibit high fidelity in capturing key characteristics of precipitation and atmospheric dynamics across monsoon regions in the historical period. In the future period, regional monsoons exhibit a spatially robust delay in the monsoon onset, an increase in seasonality, and a reduction in the rainy season length at higher levels of radiative forcing. All regions with substantial delays in the monsoon onset exhibit a decrease in pre-monsoon precipitation, indicating a strong connection between pre-monsoon drying and a shift in the monsoon onset. The weakening of latent heat driven atmospheric warming during the pre-monsoon period delays the overturning of atmospheric subsidence in the monsoon regions, which defers their transitioning into deep convective states. Monsoon changes under the RCP2.6 scenario are mostly within the baseline variability. 

How to cite: Ashfaq, M., Cavazos, T., Reboita, M., Torres-Alavez, J. A., Im, E.-S., Olusegun, C., Alves, L., Key, K., Adeniyi, M., Tall, M., Sylla, M. B., Mehmood, S., Zafar, Q., Das, S., Diallo, I., and Coppola, E.: Robust Late 21st Century Shift in the Regional Monsoons in RegCM-CORDEX Simulations , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12102, https://doi.org/10.5194/egusphere-egu2020-12102, 2020.

Under the Coordinated Regional Downscaling Experiment (CORDEX) initiative, simulations of tropical cyclones were performed using the latest version of the International Centre for Theoretical Physics (ICTP) Regional Climate Model 4 (RegCM4) at a spatial resolution of 25 km over four domains (Australasia, Central America, Western Pacific and South Asia). These simulations cover the 130-year period, 1970-2099, for two Representative Concentration Pathways, 2.6 (RCP2.6) and 8.5 (RCP8.5) emission scenarios and were driven by three General Circulation Models (GCMs) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5). In these simulations, the potential changes in TC activity for future climate conditions over five areas of tropical cyclone formation (North Indian Ocean, the Northwest Pacific, North Atlantic, Australasia and Eastern Pacific) are investigated, using an objective algorithm to identify and track them. The RegCM4 simulations driven by GCMs are evaluated for the period of 1995–2014 by comparing them with the observed tropical cyclone data from the International Best Track Archive for Climate Stewardship (IBTrACS); then the changes in two future periods (2041-2016 and 2080–2099), relative to the baseline period (1995–2014), are analyzed for RegCM4 simulations driven by GCMs. Preliminary results show that RegCM4 simulations driven by GCMs are capable of most of the features of the observed tropical cyclone climatology, and the future projections show an increase in the number of tropical cyclones over the North Indian Ocean, the Northwest Pacific and Eastern Pacific regions. These changes are consistent with an increase in mid-tropospheric relative humidity. On the other hand, the North Atlantic and Australasia regions show a decrease in tropical cyclone frequency, mostly associated with an increase in wind shear. We also find a consistent increase in the future storm rainfall rate and the frequency of the most intense tropical cyclones over almost all the domains. Our study shows robust and statistically significant responses, often, but not always, in line with previous studies. This implies that a robust assessment of tropical cyclone changes requires analyses of ensembles of simulations with high-resolution models capable of representing the response of different characteristics of different key atmospheric factors.

How to cite: Torres, A., Glazer, R., Coppola, E., Gao, X., Hodges, K., Das, S., and Ashfaq, M.: Future projections in tropical cyclone activity over multiple CORDEX domains from RegCM4 CORDEX-CORE simulations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8800, https://doi.org/10.5194/egusphere-egu2020-8800, 2020.

Dangerous weather related to severe thunderstorms including tornadoes, high-winds, and hail cause significant damage globally to life and property every year. Yet the impact on these storms from a warming climate remains a difficult task due to their transient nature. In this study we investigate changes in the large-scale environments in which severe thunderstorms form during 21^st century warming (RCP2.6 and RCP8.5) in a group of RegCM CORDEX-CORE simulations. Severe potential is measured in terms of CAPE (Convective Available Potential Energy) and shear during the severe seasons in three regions which are known to currently be prone to severe hazards: North America, the southeastern coast of South America east of the Andes, and eastern India and Bangladesh. In every region environments supportive for severe thunderstorms are increasing during the warm season months in both RCP2.6 and RCP8.5 during the 21^st century. The number of days supportive for severe thunderstorms increases by several days per season over the vast majority of each region by the end of the century. In the case of RCP2.6, where greenhouse gas forcing is relatively weak compared to RCP8.5, there is still a consistent positive trend in the impact on severe days. The simulations using RCP8.5 forcing show large changes to the annual cycle of severe weather as well as the number of days supportive for severe weather per season. In some regions, like for example Northern Argentina along the Andes mountains, the number of days with severe conditions present increases by nearly 100% by the end of the century. Analyzing the CAPE and shear trends during the 21^st century we find seasonal and regionally specific changes driving the increased severe potential. 21^st century surface warming is clearly driving a robust increase in CAPE in all regions, however poleward displacement of vertical shear in the future leads to the movement of severe environments over North America and South America. The results found here relate that severe impacts in the future cannot be generalized globally, and that regionally specific changes in vertical shear may drive future movement of regions prone to severe weather.

How to cite: Glazer, R., Torres-Alavez, J. A., Coppola, E., Das, S., Ashfaq, M., and Sines, T.: Projected changes to Severe Thunderstorm environments as a result of 21st century warming from RegCM CORDEX-CORE simulations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9970, https://doi.org/10.5194/egusphere-egu2020-9970, 2020.

 This study evaluated tropical cyclone (TC) activity simulated by two regional climate models (RCMs) incorporated in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework with two different horizontal resolutions. Evaluation experiments with two RCMs (RegCM4 and MM5) forced by reanalysis data were conducted over the CORDEX-East Asia domain with 25 km and 50 km horizontal resolutions. The 20-year (1989–2008) mean performances of the experiments were investigated in terms of TC genesis, track, intensity, and TC-induced precipitation. In general, the simulated TC activities over the western North Pacific (WNP) varied depending on the model type and horizontal resolution. The MM5 tended to simulate more reasonable TC activity compared with the RegCM4. For both models, higher horizontal resolution improved the simulation of TC tracks near the coastal regions of East Asia, whereas the coarse horizontal resolution led to underestimated TC genesis compared with the best track data because of greater convective precipitation and enhanced atmospheric stabilization. In addition, the increased horizontal resolution prominently improved the simulation of TCs landfalling in East Asia and associated precipitation around coastal regions. This finding implies that high-resolution RCMs can produce added value in improving the simulation of TCs over the WNP; thus, they have an advantage in climate change assessment studies.

How to cite: Cha, D.-H., Lee, M., Suh, M.-S., Chang, E.-C., Ahn, J.-B., Min, S.-K., and Byun, Y.-H.: Impact of horizontal resolution on the tropical cyclone activity over the western North Pacific in CORDEX-East Asia phase I and II experiments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4481, https://doi.org/10.5194/egusphere-egu2020-4481, 2020.

How much water will come in future from the Himalayan watersheds under changing climate is a growing concern for ensuring sustainable development of downstream agrarian economies and for socioeconomic wellbeing of dependent communities. However, robust assessment of future water availability largely depends upon fidelity of climate modelling experiments simulating future change scenarios, beyond the debate of their possibility and plausibility. Thus, I assess the fidelity of CORDEX experiments over the Himalayan watersheds for the historical period against a broader set of observational datasets, in terms of reproducibility of the observed climatology of temperature and precipitation. Changes in these basic variables relevant for impact studies will also be presented under different scenarios and their robustness will be discussed in view of their fidelity for the historical period. The study will suggest the suitability of CORDEX experiments for the impact studies and further possibilities for improvement.

How to cite: Hasson, S.: Fidelity of CORDEX experiments over Himalayan Watersheds, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14592, https://doi.org/10.5194/egusphere-egu2020-14592, 2020.

The NCAR Water System Program has been striving to improve the representation of the water cycle and its future changes in both regional and global models during the past decade. One of our efforts is conducting continental-scale convection-permitting simulations of the current and future climate of North America using the WRF model based atmospheric-hydrological coupling system. The major science objectives of these simulations are: 1) to evaluate the capability of convection-permitting WRF model in capturing orographic precipitation and snow mass balance over the western mountains of North America and convective precipitation in the eastern part of the continent; 2) to assess future changes in seasonal snowfall and snowpack and associated surface hydrological cycles under the CMIP5-projected global warming; 3) to investigate water cycle changes in response to climate warming, including the summertime convective precipitation and associated mesoscale convective storm tracks; and 4) to examine the impact of climate change on severe weather over North America. As such, two phases of convection-permitting climate modeling have been undertaken using 4-km horizontal grid spacing covering most of North America.

The phase-one effort involves two 13-year simulations as reported in Liu et al. (2017): 1) a historical simulation with initial and boundary conditions from ERA-interim, and 2) a future climate sensitivity simulation, called pseudo-global warming (PGW), with modified reanalysis-derived initial and boundary conditions by adding the CMIP5 ensemble-mean projected climate change. These WRF-downscaled climate change simulations provide a unique high-resolution dataset to the community for studying one possible scenario of regional climate changes and impacts.

Recognizing that only the thermodynamic future climate impacts can be adequately addressed in the PGW approach, the NCAR Water System team has started conducting a second set (phase II) of current and future simulations at 4-km grid spacing over North America. In these simulations, the WRF model is forced using the weather perturbations derived from the NCAR CESM model 6-hourly output plus the reanalysis-based bias-corrected CMIP5 ensemble mean climate as detailed in Dai et al. (2017). The model domain is also expanded northward to include Canada and the Canadian Arctic. Because storm track changes are permitted, these simulations complement the previous PGW simulations, allowing us to address the impact of dynamic changes in the future warmer climate. We will present some preliminary analysis results of these simulations, with focus on the evaluation of the historical simulation and the added value of convection-permitting resolution and mean climate bias corrections.

How to cite: Liu, C., Ikeda, K., and Rasmussen, R.: Convection-Permitting Regional Climate Simulations over North America, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3732, https://doi.org/10.5194/egusphere-egu2020-3732, 2020.

Sub-Saharan Africa is one of the most food insecure regions in the world and is highly vulnerable to climate change. We use a comprehensive set of bias-corrected global (CMIP5) and regional (CORDEX-Africa) models and a new convection-permitting pan-Africa simulation (and its parameterized counterpart) to examine changes in rainfall and temperature and the impact on agricultural suitability of maize, cassava and soy in sub-Saharan Africa by 2100 (RCP8.5). This is the first time a convection-permitting projection has been used to examine agricultural suitability in Africa. Increasing temperatures and declining rainfall led to large parts of sub-Saharan Africa becoming unsuitable for multiple staple crops, which may necessitate a transition to more heat and drought resistant crops to ensure food and nutrition security. Soy was resilient to temperature increases, however maize and cassava were not, leading to declines in crop suitability. Inclusion of sensitivity to extreme temperatures led to larger declines in maize suitability than when this was excluded. The variation in rainfall projections within the multi-model ensemble was examined in detail for Tanzania, Malawi, Zambia and South Africa. In each country the range of projections included wetting and drying, but the majority of models projected rainfall declines, except in Tanzania, leading to declines in crop suitability. Overall, the CORDEX and CMIP5 models gave similar results for agricultural suitability. Explicit-convection led to more temperature extremes, but had little systematic impact on temperature and rainfall, and the resulting suitability analysis. Global model uncertainty, rather than convection parameterizations, still makes up the largest part of the uncertainty in future climate. Explicit-convection may have more impact if suitability included a more comprehensive treatment of extremes. This work highlights the key uncertainty from global climate projections for crop suitability projections, and the need for improved information on sensitivities of African crops to extremes, in order to give better predictions and make better use of the new generation of explicit-convection models.

How to cite: Chapman, S., Birch, C., Pope, E., Sallu, S., Bradshaw, C., Davie, J., and Marsham, J.: AFRICAP - The impact of climate change on agriculture in Tanzania, Malawi, Zambia and South Africa, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1927, https://doi.org/10.5194/egusphere-egu2020-1927, 2020.

Deforestation in Colombia has drastically increased in recent years. At the same time, droughts and floods are affecting the country more frequently due to climate change. Analyzing the impacts and interactions of deforestation and global warming is challenging due to the terrain’s complexity and the high climate variability along with the severe lack of regional climate modelling.

Here, we quantify the impact of historical anthropogenic global warming (CC) and land cover changes (LCC) on precipitation, temperature and the surface energy balance in Colombia by running the Weather Research and Forecasting model WRF v3.9.1.1. across different land cover and climate scenarios during the study period 2009-2011 for Colombia.

We find that precipitation is increased by CC with a stronger effect over forests. LCC implies a small reduction of precipitation which is strongly enhanced above deforested areas. LCC is found to be a strong driver of regional precipitation changes representing up to 25% and 60% of the CC effects magnitude in Coastal Caribbean and Andean regions, respectively. CC causes a temperature increase across the whole domain, in particular with increasing altitude. Surprisingly however, WRF simulates a slight cooling after deforestation which is not in line with almost all observations and modelling studies regarding biophysical effects of tropical deforestation. This apparent bias is further investigated across different WRF schemes and parameters because of its great importance for climate studies using WRF with default parametrization in tropical contexts.

How to cite: Manciu, A., Krause, A., Rammig, A., and Quesada, B.: Impacts of land cover changes and global warming on climate in Colombia using the regional climate model WRF, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7093, https://doi.org/10.5194/egusphere-egu2020-7093, 2020.

With the increasing number of global climate models available, regional modellers have to make choices to select a manageable subset for downscaling. This limits the representation of both present day climate and future climate change compared to the full GCM ensemble.

We present the interactive web-based tool called “GCMeval”, available at https://gcmeval.met.no. This tool lets you assign weights to different regions, seasons, climate variables, and skill scores and presents a ranking with model performance for a historical period. We demonstrate how the tool can be used to, for example, remove models with the largest historical biases for the selected criteria, or to optimise the spread. The weighting can be used to illustrate the sensitivity of the results to model choice.

Based on the choice of regions and weights, the tool produces scatter plots of projected future temperature and precipitation and shows how the selected sub-ensemble compares to the full ensemble. The tool can also be used to evaluate ensemble selections "post-hoc", as demonstrated with examples from CORDEX.

How to cite: Landgren, O. A., Parding, K., Dobler, A., McSweeney, C. F., Benestad, R., Erlandsen, H. B., Mezghani, A., Gregow, H., Räty, O., Viktor, E., El Zohbi, J., Bøssing Christensen, O., and Loukos, H.: Effects of GCM selection for regional climate modelling illustrated by the interactive tool GCMeval, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13441, https://doi.org/10.5194/egusphere-egu2020-13441, 2020.

Climate models have been used to study water resources and regional hydrologic responses to climate change, but climate model outputs must be downscaled to provide relevant regional data. However, the accuracy of this regional data is limited by uncertainties across and within downscaling methods, uncertainty across global outputs, and discontinuities at downscaled boundaries. A new alternative to traditional downscaling is a variable resolution model that incorporates fine-resolution regions directly into a coarse-resolution, global climate simulation in order to capture contiguous dynamics across resolution boundaries. In this study, we used the Variable-Resolution Community Earth System Model (VR-CESM) to generate one-eighth degree (14 km) fine-resolution outputs for the western U.S. and eastern China from 1970-2006.

We focus our evaluation on precipitaiton, temperature, snow pack, solar radiation, and wind. We compare the model outputs with remote-sensing-based precipitation data, and both reanalysis and gridded weather station data for precipitation and temperature. VR-CESM generally has a cold bias in winter and a warm bias in summer in the western U.S., which compensate each other to reduce the annual bias. In eastern China, however, the sign of temperature biases are more consistent throughout the year with cold biases in the higher mountains and warm biases throughout most of the rest of the region. Precipitation biases are dependent upon reference data, and show slight overestimation in high mountain regions in both the U.S. and China with respect to gridded weather station data. Simulated snow cover in the western U.S. is reasonable compared to remote sensing data, but snow cover and snow water equivalent have larger biases when compared to reanalysis data. In eastern China there are widespread snow cover biases compared to remote sensing data. VR-CESM underestimates downward shortwave radiation to a greater degree in summer than in winter, and underestimates surface layer windspeed over mountains to a greater degree than in other areas. Comparison between VR-CESM and a coarser simulation (1-degree Beijing Climate Center model) shows reduced precipitation biases in the mountainous regions with finer resolution, indicating the value of variable-resolution modeling for reigonal studies.

How to cite: Di Vittorio, A., Xu, Z., Zhang, J., Xin, X., Xu, H., and Xiao, C.: Evaluating fine-resolution, regional outputs of a variable resolution global climate model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10324, https://doi.org/10.5194/egusphere-egu2020-10324, 2020.

Under the CORDEX umbrella the CORDEX-CORE initiative has been developed that was able to produce an ensemble of two RCMs at 0.22° resolution downscaling 3 GCMs for each of the 9 CORDEX domains for two climate scenarios the RCP2.6 and the RCP8.5. The CORDEX-CORE and the CMIP5 driving ensemble together with the most recently produced CMIP6 ensemble has been analyzed and several temperature, heat, wet and dry hazard indicators have been computed for the present day and mid and far future time slices.

As a results CORDEX-CORE shows a better validation for several hazard indices due to the higher spatial resolution. For the far future time slice the 3 ensembles project an increase for all the temperature and heat indices under the RCC8.5 scenario. The highest values are always shown by the CMIP6 ensemble except that for Tx>35 °C for which CORDEX-CORE projects higher warming. Extreme wet and flood prone maxima are projected by the regional ensemble over la Plata basin in South America , over the Congo basin in Africa, in east North America, north east Europe , India and Indochina, notably the regions where a better validation is obtained, whereas the global ensembles show quite small or not existent signal. Compound hazard hotspots based on heat and drought indicators have been identified in Central America, in the Amazon region, in the Mediterranean, South Africa, India and Australia since in all these regions a linear relation is shown by the heatwave and drought change signal. Although still limited the CORDEX-CORE initiative was able to produce high resolution climate projections with a quasi global coverage. This can be seen as a first step to foster collaboration among the global and regional climate community. The existence of the first of this kind ensemble together with the previous CORDEX 0.44 ensembles and the global ensemble is very valuable for climate impact assessment studies since can provide information on the mean and extreme regional climate projections but also more robust quantification on the model spread. All being an added value for the impact and climate services communities.

How to cite: Coppola, E. and the CORDEX-CORE: Climate hazard indices projections based on CORDEX-CORE, CMIP5 and CMIP6 ensemble., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15001, https://doi.org/10.5194/egusphere-egu2020-15001, 2020.

Tropical-like Mediterranean storms associated with strong winds, low pressure centers and extreme precipitation are called medicanes. These devastating storms threaten the coastal regions and some small islands in the Mediterranean. Recent studies including future climate projections indicate that the intensity of medicanes could increase under the climate change conditions. Therefore it is important to improve a comprehensive understanding of the medicanes and theirs occurrence processes including thermodynamic mechanisms between the atmosphere and the sea. In pursuing these mechanisms, we use reanalysis/observations (ECMWF’s ERA5 and MyOCEAN etc.) and coupled Regional Earth System Model (RegESM). The RegESM model is run in coupled mode (Regional Climate Model-RegCM4-12km coupled with Regional Ocean Modelling System-ROMS-1/12^°, and Wave Model-WAM-0.125^°) and uncoupled mode (RegCM4 only-12km) for 1979-2012 period over the Med-CORDEX domain prescribed under the CORDEX framework. Additionally, standalone simulation of RegCM4 has been forced by Era-Interim Reanalysis over the Med-CORDEX domain and the standalone simulation of the wave model (WAM) has been forced by the standalone RegCM4 wind field (12 km horizontal resolution) for the Mediterranean Sea.

We analyze the ability of the coupled and uncoupled models to reproduce the characteristics of the observed medicanes and to investigate the role of air-sea interaction in the simulation of key processes that govern medicane occurrences over the study area. In general, the spatial extent and the timing of the observed medicanes better simulated with the coupled model. The reason behind this better replication with the coupled model is the wave model’s interactive contribution with the roughness length to the surface winds, which allows necessary conditions for medicane formation. Our results also reveals that the recently developed modeling system RegESM incorporates atmosphere, ocean and wave components and thereby is better capable to improve the understanding of the mechanisms driving medicanes.

Keywords Regional earth system model, Ocean-atmosphere-wave coupling, Medicanes

Acknowledgements This study has been supported by a research grant 40248 by the Scientific Research Projects Coordination Unit of Istanbul Technical University (ITU) and  a research grant (116Y136) provided by The Scientific and Technological Research Council of Turkey (TUBITAK). The computing resources used in this work were provided by the National Center for High Performance Computing of Turkey (UHEM) under grant number 5004782017.

How to cite: Batıbeniz, F., Önol, B., and Turuncoglu, U. U.: Hindcast Simulation of Medicanes with an Atmosphere-Ocean-Wave Coupled Modelling System , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1062, https://doi.org/10.5194/egusphere-egu2020-1062, 2020.

The occurrence of extreme weather events and climate extremes over Europe and the Mediterranean region are believed to be associated with changes and variability in the mid-latitude atmospheric circulation. CMIP5 models exhibits a substantial decrease in mid-latitude mean storm track activity for summer under climate change for a variety of scenarios. In this work, we aim to investigate future change in summer circulation and its implication for summer temperature and precipitation extremes over Europe particularly focusing on the Southeastern Mediterranean. EURO-CORDEX regional climate projections at 0.11° grid-mesh are used to analyze future climate projections addressing climate warming targets of 1°C, 2°C and 3°C, respectively. Simple scaling with the global mean temperature change is applied to the regional climate projections for the variables in concern in order to provide robust signals not to be dependent on climate sensitivity. Our focus in this study is on monthly mean geopotential height, winds at mid- and lower-troposphere as indicators of the simulated circulation changes.

How to cite: Ozturk, T., Matte, D., and Christensen, J. H.: Future circulation changes over the EURO-CORDEX domain, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-971, https://doi.org/10.5194/egusphere-egu2020-971, 2020.

Snow cover is a crucial part of the climate system due to its distinctive alteration of surface reflectance (snow-albedo-feedback) and its influence on further physical surface properties (e.g. heat conduction and water storage). These effects are particularly relevant in alpine areas and high latitude regions, where snow coverage prevails for a significant part of the season. In addition, various human activities rely on snow cover duration and/or snow amounts, such as winter tourism, agriculture and hydropower production.

The EURO-CORDEX project provides an RCM ensemble with a horizontal resolution of ~50 and ~12 km for both present-day and future climates assuming different emission scenarios. These simulations present a potentially valuable information source for the future snow cover evolution. Prerequisite, however, is the ability of RCMs to reproduce historical snow cover conditions. These issues are addressed in the present work on a European scale. A horizontal resolution of ~12 km allows for an improved representation of topography and is thus particularly interesting for snow cover studies, as snow in alpine regions strongly correlates with elevation. We therefore only consider the high-resolution EURO-CORDEX RCMs and, for the climate projection part, simulations for RCP2.6, RCP4.5 and RCP8.5.

To assess the RCMs’ ability of reproducing current snow cover conditions in Europe, we evaluate simulated snow water equivalent and snow cover duration/extent by comparison against different reanalysis data (e.g. ERA5, UERRA MESCAN-SURFEX) and snow products derived from remote sensing. Regarding the spatial domain, we consider entire Europe with a focus on four mountainous regions (Alps, Norway, Pyrenees and Carpathians). The evaluation reveals that, on an European scale, mean yearly snow cover duration is well captured by the ensemble mean of the models. However, the majority of the RCMs underestimates snow cover extent throughout the season. This bias is more pronounced in the reanalysis (ERA-Interim) driven set of simulations than in the GCM-driven runs. In regions with complex topography, winter snow water equivalent is distinctively overestimated in some simulations - whereas certain grid cells reveal glaciation (i.e. year-round snow coverage). A comparison with E-OBS data indicates that biases in snow cover duration and amount are, besides arising from inaccurate snow schemes, linked to mismatches in simulated air temperature and precipitation patterns. Scenarios for the 21st century show a distinctive reduction in snow cover duration for low-elevation regions, whereas the magnitude of this decrease depends, amongst other factors, on the climate scenario. Projected decreases in the snow cover are less pronounced for medium to high-elevation regions.

How to cite: Bülow, K., Kotlarski, S., Steger, C., and Teichmann, C.: Can the latest generation of regional climate models reproduce European snow conditions and how do biases translate into uncertainties of snow cover projections?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9964, https://doi.org/10.5194/egusphere-egu2020-9964, 2020.

Extreme weather events, like heavy precipitation, heat waves, droughts and wind storms have a detrimental impact on East African societies. The Lake Victoria Basin (LVB) is especially vulnerable, since nightly storms on the lake catch fishermen by surprise. As the frequency and intensity of climate extremes is projected to further increase substantially with climate change, so do the risks, with potentially major consequences for livelihoods and policy in the LVB.

The ultimate aim of the ELVIC CORDEX-FPS is to investigate how extreme weather events evolve in the future in the LVB and to provide improved probabilistic information to the impact community. ELVIC (Climate Extremes in the Lake Victoria Basin) brings together different research groups that perform simulations with multiple high-resolution regional climate models operating at the convection-permitting scale (CPS) (https://ees.kuleuven.be/elvic).

As a first step towards this overall goal, the added value of the CPS on the representation of deep convective systems in Equatorial Africa was assessed. For this purpose, 10-year present-day model simulations were carried out with five regional climate models both at the CPS and at the scale where convection was parameterized, namely COSMO-CLM, RegCM, HCLIM-AROME, WRF and the Met Office Unified Model. From a comparison of model output with different observational products, no robust improvement was found for seasonal average meteorological variables. Moreover, the change in the seasonal precipitation when going to CPS differs between the models. A robust improved performance was found for deep convection, reflected in an improved representation of the daily precipitation cycle. Preliminary results also point towards an improvement in the representation of extreme precipitation. This suggests that regional climate model simulations at the convection-permitting scale are indeed relevant to assess the climate sensitivity of extreme precipitation in the Lake Victoria Basin.

How to cite: van Lipzig, N., Van de Walle, J., Thiery, W., Nikulin, G., Wu, M., Glazer, R., Coppola, E., Pinto, J., Fink, A., Ludwig, P., Rowell, D., Berthou, S., Finney, D., and Marsham, J.: Climate Extremes in the Lake Victoria Basin: The ELVIC CORDEX Flagship Pilot Study, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17466, https://doi.org/10.5194/egusphere-egu2020-17466, 2020.

At the UK Met Office we have recently completed climate change simulations at convection-permitting resolution (2.2km grid scale) across a pan-European domain, which are feeding into the CORDEX-FPS and European Climate Prediction System (EUCP) projects. At such high resolution, the model gives a much better representation of convection and is able to capture hourly precipitation characteristics, including extremes, as well as better representing the influence of mountains, coastlines and cities. In this talk, I will present results from these new convection-permitting climate simulations, looking at future changes in high impact events, including hourly precipitation extremes and severe winds. I will also discuss remaining outstanding issues, such as the deficiencies in land-surface-atmosphere coupling, and work underway to try and address these.

How to cite: Kendon, E., Chan, S., Berthou, S., Manning, C., and Kahraman, A.: Future changes in high-impact events in pan-European convection-permitting projections, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2357, https://doi.org/10.5194/egusphere-egu2020-2357, 2020.

Regional models used for downscaling the European climate usually include a relatively small area of the Atlantic Ocean and are uncoupled, with the SST used as lower boundary conditions much coarser than the mesh of the regional atmospheric model. Concerns thus arise about the proper representation of the oceanic influence and the role of air-sea coupling in such experiments.  A complex orography and the exposure to different air and ocean masses make the Iberian Peninsula (IP) an ideal test case for exploring the impact of including explicitly the North Atlantic in the regional domain and the added value that coupling brings to regional climate modeling. To this end, the regionally-coupled model ROM and its atmospheric component, the regional atmospheric model REMO are used in a set of coupled and uncoupled experiments forced by the ERA-Interim reanalysis and by the global climate model MPI-ESM. The atmospheric domain is the same in all simulations and includes the North Atlantic and the ocean component is global and eddy permitting. Results show that the impact of air-sea coupling on the IP winter biases can be traced back to the features of the simulated North Atlantic Ocean circulation. In summer, it is the air-sea interactions in the Mediterranean that exert the largest influence on the regional biases. Despite improvements introduced by the eddy-permitting ocean, it is suggested that a higher resolution could be needed for a correct simulation of the features of the large-scale atmospheric circulation that impact the climate of the IP.     

How to cite: Cabos, W., Sein, D., de la Vara, A., and Alvarez Garcia, F.: Impact of ocean-atmosphere coupling on regional climate: the Iberian Peninsula case, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13098, https://doi.org/10.5194/egusphere-egu2020-13098, 2020.

The analysis of climate patterns can be performed for each climatic variable separately or the data can be aggregated using e.g. a kind of climate classification. The advantage of such method, in our case Köppen-Trewartha classification, is putting together the most important variables, i.e. temperature and precipitation, considering not only annual means, but through monthly values the annual cycle as well. These classifications usually correspond to vegetation distribution in the sense that each climate type is dominated by one vegetation zone or eco-region. Climate classifications represent a convenient tool for the assessment and validation of climate models and for the analysis of simulated future climate changes.

The results of RegCM driven by selected CMIP5 simulations (mostly HadGEM, MPI and NorESM) produced within the CORDEX-CORE experiment over nine CORDEX domains are analysed. Validation based on ERA-Interim driven runs compared to CRU database (E-OBS for higher resolution in Europe) shows reasonable agreement in the Northern hemisphere with a tendency towards wetter and colder climate types in North America. Worse representation in Southern hemisphere is observed, mainly in Australia (lack of desert type). Through the analysis of the control experiments together with the performance of driving GCMs we can assess the sources of the biases in present conditions as well as the added value, which comes mainly from better representation of topography in higher resolution and thus appearance of mountaineous tundra type, as well as better representation of coastal regions and thus separating maritime subtypes. Finally, for two scenarios RCP8.5 and RCP2.6 we show the projections of the individual types‘ area changes, mainly decline of boreal and polar types, their shift to the higher latitudes and altitudes, increase of temperate, subtropical and dry climates. Magnitude, and in some cases (temperate climate) even the sign of change is largely dependent on the region and driving model.

How to cite: Belda, M. and Halenka, T.: Global Changes of Köppen-Trewartha Climate Zones Derived from RegCM CORDEX-CORE Simulations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16236, https://doi.org/10.5194/egusphere-egu2020-16236, 2020.

Within the framework of WCRP CORDEX, the CORE (CORDEX Coordinated Output for Regional Evaluations) experiment provides a homogeneous ensemble of regional climate projections for 9 domains covering all land areas of the globe with the exception of the Arctic and Antarctic regions (http://www.cordex.org/experiment-guidelines/cordex-core/). CORDEX-CORE provides data from two regional climate models (REMO2015 and RegCM), driven by 3 GCMs and under 2 RCP scenario conditions at a resolution of about 25 km. In addition, within the same framework, simulations of the current climate, driven by ERA-Interim, were carried out for all areas with REMO2015 at a grid resolution of approx. 25 km.

Within the German Project ViWA (Virtual Water Values, https://viwa.geographie-muenchen.de), simulations with the regional climate model REMO2015, driven by ERA-INTERIM analyses were carried out for the same regions globally, but on a significantly higher spatial resolution of approx. 12.5 km. These simulations cover the time period from 2015 to 2018. Comparing these highly resolved simulations to the coarsely resolved CORDEX-CORE simulations, can give indications, in which regions and for which processes the CORDEX-CORE resolution of 25 km is sufficient and where a higher resolution brings a clear added value.

We will show first results of this comparison, focusing on selected regions and processes which potentially benefit from higher spatial resolution of the simulations.

How to cite: Schubert-Frisius, M., Pfeifer, S., Reca Remedio, A., Teichmann, C., Buntemeyer, L., Sieck, K., Weber, T., Rechid, D., and Jacob, D.: First results of a comparison study of multi-domain REMO CORDEX simulations between 0.11° and 0.22° resolution with ERA-Interim forcing, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20151, https://doi.org/10.5194/egusphere-egu2020-20151, 2020.

Five of the most prominent low-level jets (LLJs) around the world – the Monsoon Low-Level Jet, Caribbean Low-Level Jet, West African Westerly Jet, Great Plains Low-Level Jet and South American Low-Level Jet – are examined for future climate conditions relative to the present using an ensemble of Regional Climate Model (RCM) simulations under the Coordinated Regional Downscaling Experiment (CORDEX) initiative. The simulations were conducted on a 25 km horizontal grid spacing using lateral and lower boundary forcing from three Coupled Model Inter-comparison Project 5 (CMIP5) global climate models (GCMs) for a near-present historical period (1995–2014) and two future periods (2041–2060 and 2080–2099) under the Representative Concentration Pathway 8.5 (RCP8.5). The RCM is capable of capturing most of the observed climatological features of the LLJs and exhibits a much greater capacity to represent their positioning and core strength compared to the driving GCMs. Analysis of the influence of global warming on the LLJs shows a consistent strengthening of the jets and a shift in their location under both future scenarios. The Monsoon and West African LLJs exhibit a northward shift, while the Caribbean and South American LLJs undergo a westward expansion. The use of an ensemble of high-resolution simulations provides a key element in a robust assessment of changes in LLJs associated with future global-warming scenarios.

How to cite: Das, S., Torres, A., Corrales, A., Coppola, E., Giorgi, F., Raffaele, F., Bukovsky, M., Ashfaq, M., and Sines, T.: Future projections in the climatology of five low-level jets across different CORDEX domains, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18411, https://doi.org/10.5194/egusphere-egu2020-18411, 2020.

CORDEX-CORE is a new phase of CORDEX simulations with higher resolutions (0.22 degrees) consisting of two RCMs forced by three GCMs. This higher resolution ensemble could provide added value to regional climate change information, however, since the data has just recently been released, more studies are required to validate and report on its climate change signal. With this in mind, we computed the mean climate and extreme indices over Africa using the CORDEX-CORE ensemble. These results are compared to the results of  the driving models as well as to the lower resolution CORDEX-phase 1 ensemble. We found that for most of the extreme indices the CORDEX-CORE shows lower biases over Africa owing to its higher spatial resolution. We also found that the mean climate change signal over Africa was broadly consistent across the three different ensembles. Indicating that the new CORDEX-CORE ensemble is able to capture the uncertainty spread well. We report the projected changes in extreme indices over Africa found in the new higher resolution CORDEX-CORE ensemble. We also examine and compare the representation of some key dynamical features over Africa in the different ensembles. Africa is especially vulnerable to extreme events, due to its limited capacity for disaster management. Thus, this study adds important, higher resolution information to the existing climate change impact knowledge for Africa. 

How to cite: Abba-Omar, S., Raffaele, F., Coppola, E., Jacob, D., Teichmann, C., and Remedio, A.: Assessment of the CORDEX-CORE Africa simulations: evaluation and uncertainties in the mean and extreme indices climate change signal, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21337, https://doi.org/10.5194/egusphere-egu2020-21337, 2020.

Projected changes in temperature extremes at 1.5°C and 2°C global warming levels (GWLs) have been evaluated for Southeast Asia (SEA) based on temperature extreme indices from ETCCDI using the latest available CORDEX simulations. Results show that the temperature indices significant increase across Indochina Peninsula and Maritime Continent at 1.5°C and 2°C GWLs except for the decreasing daily temperature range (DTR) in the dry season. The most pronounced increases of summer days (SU) are projected in Sulawesi with the percentage magnitude of 31.7% and 19.7% (47.2% and 31.3%) at the 1.5°C (2°C) GWL for wet and dry seasons, respectively, while tropical nights (TR) increase significantly over Sumatra and Sulawesi. Robust differences of temperature extremes can be found over the SEA in both wet and dry seasons for the additional global warming of 0.5°C. The temperature extremes under the global warming of 1.5°C and 2°C levels and their differences primarily concentrate on the main islands in the densely populated coastal regions, suggesting more conspicuous impacts on the human system in the developing countries over the SEA.

How to cite: Ge, F., Zhu, S., Zhi, X., Sielmann, F., and Fraedrich, K.: Projected changes of temperature extremes over Southeast Asia under 1.5 and 2 degrees global warming , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2290, https://doi.org/10.5194/egusphere-egu2020-2290, 2020.

Based on the historical measured temperature data (1971 ~ 2010) and the output of coordinated regional downscaling experiment (CORDEX) East Asia, including the climate prediction based on RCP4.5 and RCP8.5, the authors get the evolution pattern of climatic growth period in historical period and future scenarios.. The results show : (1) in the 40 years from 1971 to 2010, the duration of the climatic growth period in most regions of China increased slightly, and the effect of the advance of the start date of the growth period on the climatic growth period was dominant. (2)In RCP4.5, the change of the start date of the climatic growth period is mainly in East China, Central China, Northwestern South China, Northern South China and the Qinghai-Tibet Plateau, while the change of the end date is mainly in the central, southern and eastern parts of the Tibetan Plateau and the mountainous regions of Xinjiang. (3)In RCP8.5, days of change of start date  increase significantly. The duration of the climatic growth season in southern South China has remained unchanged, and the rest of the region has been extended for more than 20 days. (4) Although the number of meteorological stations in the Qinghai-Tibet Plateau is relatively small, the terrain is more complex, and the accuracy of the calculation results is affected, the northern Qinghai-Tibet Plateau is the most sensitive to global changes in both historical periods and future scenarios.

How to cite: Yang, H., Li, P., and Zhao, X.: Evolution of Climate Growth Period in Chinese Based on Coordinated Regional Downscaling Experiment, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4422, https://doi.org/10.5194/egusphere-egu2020-4422, 2020.

East Asia is a highly industrialized region with high CO2 emissions from fossil fuel use. Therefore, to achieve the goal of the Paris Agreement on CO2 reduction, an increase in the production of renewable energy such as photovoltaic (PV) and wind power generation is required in this region. Most renewable energy production is directly affected by weather and climate. This study projected changes in future PV power generation and climate variables affecting them using CORDEX phase 2 RCMs with 25km horizontal resolution forced by HadGEM2-AO GCM over East Asia. The present change and future projection of PV potential production (PVpot) depend critically on changes in surface-downwelling shortwave radiation (RSDS). In the analysis of recent changes in PVpot over East Asia using the ERA5 reanalysis data, PVpot overall increased slightly. For PVpot projections using the high-emission scenario during the late 21C, RegCM4 is expected to increase, while the other RCMs will decrease. The results of this study will help to develop policies for efficient future production of renewable energy over East Asia by presenting the projection of future photovoltaic power generation on a detailed regional scale.

How to cite: Park, C., Cha, D.-H., Shin, S.-W., Kim, G., and Kim, T.: Future projections of photovoltaic power generation on climate change simulated by CORDEX II multi-RCMs over East Asia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12934, https://doi.org/10.5194/egusphere-egu2020-12934, 2020.

In the framework of the CORDEX-East Asia, evaluation simulations using high-resolution regional climate models (SNURCM and HadGEM3-RA) with ~25km (Phase2) grid scale have been conducted. In this study, we investigate whether the higher-resolution regional climate models (RCMs) can generate added values for summer mean precipitation, large-scale circulation, and extreme precipitation compared to those with lower-resolution (~50km, Phase 1). In addition, the added value index is used to quantitatively analyze the abilities of fine- and coarse-resolution RCMs. Hence, sets of phase 1 and phase 2 simulations of two RCMs are compared to observations in the East Asia region. In SNURCM simulations, positive (negative) added value of summer mean precipitation is reproduced over most ocean (land) region of East Asia in fine-resolution simulation. Extreme precipitation over Korea and Japan is well reproduced in Phase 2 simulations because the simulations of typhoons and East Asia summer monsoon are improved. In HadGEM3-RA simulations, the results of summer mean precipitation over most East Asian regions above 25°N are improved in Phase 2, while worse results are reproduced below 25°N. But, extreme precipitation in fine-resolution simulation is adequately reproduced in most regions of East Asia except China and the Yellow sea. As a result, the results of the simulations are different depending on the characteristics of the individual models, but more positive added values for the intensity and spatial distribution of precipitation over East Asia are generated as the horizontal resolution of RCMs increases.

This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI(KMI2018-01211)

How to cite: Kim, T., Cha, D.-H., Kim, G., Shin, S.-W., Park, C., Lee, M., Byun, Y.-H., and Kang, H.-S.: Added Value of reproduced precipitation by high resolved regional climate model simulation over CORDEX-East Asia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13548, https://doi.org/10.5194/egusphere-egu2020-13548, 2020.

The regional model program (RMP) that is the regional atmospheric model component of the Global/Regional Integrated Model system (GRIMs), which has the spectral dynamical core, have been participated in the Regional Model comparison project (RMIP) and the COordinated Regional Climate Downscaling Experiment (CORDEX) East Asia. The spectral method has advantages of accuracy, because numerical problems related to the spatial truncation in the grid system does not occur. However, the spectral system has the Gibbs phenomenon, which is the problem that negative values of positive definite quantities (e.g., moisture, tracer gases) can be generated by the spectral space transformation in a spectral model system. In this study, the non-iteration dimensional-split semi-Lagrangian (NDSL) advection scheme is applied to the RMP for the dynamical downscaling of the East Asian summer monsoon. In a regional climate simulation, the RMP with the NDSL scheme simulated enhanced precipitation by improving moisture field in the lower troposphere. The improvement is also induced by the revised vertical momentum which is affected by evaporation and condensation adjustment from the corrected moisture field.

How to cite: Chang, E.-C., Yeo, N., and Cha, D.-H.: Semi-Lagrangian advection scheme for the dynamical downscaling of the East Asian summer monsoon in a regional spectral model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21084, https://doi.org/10.5194/egusphere-egu2020-21084, 2020.

Extreme temperature can have a devastating impact on the ecological environment (i.e., human health and crops) and the socioeconomic system. To adapt to and cope with the rapidly changing climate, it is essential to understand the present climate and to estimate the future change in terms of temperature. In this study, we evaluate the characteristics of near-surface air temperature (SAT) simulated by two regional climate models (i.e., MM5 and HadGEM3-RA) over East Asia, focusing on the mean and extreme values. To analyze extreme climate, we used the indices for daily maximum (Tmax) and minimum (Tmin) temperatures among the developed Expert Team on Climate Change Detection and Indices (ETCCDI) indices. In the results of the CORDEX-East Asia phase Ⅰ, the mean and extreme values of SAT for DJF (JJA) tend to be colder (warmer) than observation data over the East Asian region. In those of CORDEX-East Asia phase Ⅱ, the mean and extreme values of SAT for DJF and JJA have warmer than those of the CORDEX-East Asia phase Ⅰ except for those of HadGEM3-RA for DJF. Furthermore, the Extreme Temperature Range (ETR, maximum value of Tmax - minimum value of Tmin) of CORDEX-East Asia phase Ⅰ data, which are significantly different from those of observation data, are reduced in that of CORDEX-East Asia phase Ⅱ. Consequently, the high-resolution regional climate models play a role in the improvement of the cold bias having the relatively low-resolution ones. To understand the reasons for the improved and weak points of regional climate models, we investigated the atmospheric field (i.e., flow, air mass, precipitation, and radiation) influencing near-surface air temperature. Model performances for SAT over East Asia were influenced by the expansion of the western North Pacific subtropical high and the location of convective precipitation in JJA and by the contraction of the Siberian high, the spatial distribution of snowfall and associated upwelling longwave radiation in DJF.

How to cite: Shin, S.-W., Cha, D.-H., Kim, T., Kim, G., Park, C., Lee, M., Byun, Y.-H., and Kang, H.-S.: Evaluation of MM5 and HadGEM3-RA hindcast in the CORDEX East Asia Phase Ⅱ: near-surface air temperature, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15161, https://doi.org/10.5194/egusphere-egu2020-15161, 2020.

There are few studies dedicated to assessing the impact of biogeochemistry feedbacks on the climate change signal. In this study, we evaluate this impact in a future climate change scenario over the Indian subcontinent with the coupled regional model ROM in the Indian CORDEX area.In ROM a global ocean model (MPIOM) with regionally high horizontal resolution (up to 15 km resolution in the Bay of Bengal) is coupled to an atmospheric regional model (REMO, with 25 km resolution) and global terrestrial hydrology model. The ocean and the atmosphere are interacting within the region covered by the atmospheric domain. Outside this domain, the ocean model is not coupled to the atmosphere, being driven by prescribed atmospheric forcing, thus running in so-called stand-alone mode.

To assess the impact of biogeochemical feedbacks on the climate change signal, we compare two simulations with ROM. In both simulations, the model is driven by data from a climate change simulation under the RCP 8.5 scenario with the MPI-ESM global model and differ only in the activation of the biochemistry module of MPIOM. In the first simulation, we use a light attenuation parameterization based on the Jerlov water types, when the attenuation coefficient varies spatially depending on the water type specified but does not vary in time. In the second simulation, we introduce the biochemical feedbacks as implemented in the global ocean biogeochemistry model HAMOCC.  

Both simulations capture the main features of the present time atmospheric and oceanic variability in the region and the model with HAMOCC reproduces well the intra-annual dynamics of the marine ecosystem in the northern Indian Ocean.

A comparison of the simulated changes in atmospheric variables shows that the feedbacks have a substantial impact on the climate change signal for precipitation and air temperature, especially over the central Indian region.

Acknowledgement: The work was supported by the Russian Science Foundation (Project 19-47-02015) and Indian project no. DST/INT/RUS/RSF/P-33/G.

How to cite: Sein, D., Cabos, W., Kumar, P., Ryabchenko, V., Martyanov, S., and Dvornikov, A.: Impact of biogeochemistry feedbacks on the projected climate change signal over the Indian Continent, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19402, https://doi.org/10.5194/egusphere-egu2020-19402, 2020.

The major rainfall period over the southern peninsular part of the Indian Subcontinent generally occurs during the months of October-December (OND) through the northeast (NE) monsoon (also called winter monsoon or post-monsoon season). The present study focuses on the ability of regional climate model RegCM4 forced with MIROC5 Global Climate Model and three different land-surface parameterization schemes: Biosphere-Atmosphere Transfer Scheme (BATS, herewith referred as CONTROL), Community Land Model (CLM4.5), and Sub-grid BATS in capturing the mean features of NE monsoon for the present climate (1975-2005) over India region. Based on their ability to simulate the inter-annual and intra-seasonal variability, and seasonal mean during monsoon, the current GCM is selected for downscaling from the available literature. The model performance is evaluated against the gridded temperature and precipitation datasets from the Climate Research Unit (CRU) and India Meteorological Department (IMD) respectively. We have found that the MIROC5_CLM4.5 is simulating the precipitation and surface temperature better than other experiments with relatively less bias over the study. MIROC5_CLM4.5 experiment again performs well in capturing the precipitation and surface temperature during wet and dry years’ composite. Overall, our results show a better representation of NE Monsoon mean features by MIROC5_CLM4.5 compared to other sets. The RegCM4-CLM4.5 coupled simulation has shown promising performance in representing NE monsoon. Further, it is envisaged to test and customize this framework in order to generate reliable future projections in subsequent studies.

Keywords: RegCM4, CLM4.5, NE Monsoon, Downscaling.

How to cite: Rai, P., Maharana, P., Kumar, D., Dimri, A. P., and Paeth, H.: Study of Northeast Monsoon over India using a coupled land-atmosphere model RegCM4-CLM4.5, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7772, https://doi.org/10.5194/egusphere-egu2020-7772, 2020.

In this study, it is aimed to compare wind patterns at Menderes area in Aegean Region in Turkey using HadGEM2 dataset from Hadley Center, United Kingdom and MPI-ESM-MR dataset from Max Planck Institute, Germany. These datasets are downscaled to high resolutions at 10km, 5km and 1km for two different RCP scenarios RCP 4.5 and RCP 8.5 and for different time periods 1970-1999, 2020-2049 and 2070-2099 using Regional Climate Modeling RegCM4.5 and above of the Abdus Salam International Centre for Theoretical Physics (ICTP) to see the changes of the wind patterns at Menderes area in Aegean Regiion in Turkey due to climate change.

How to cite: Collu, K. and Kurnaz, M. L.: Comparing Wind Patterns at Menderes Area in Aegean Region, Turkey using different datasets at higher resolutions using Regional Climate Modeling RegCM4, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8002, https://doi.org/10.5194/egusphere-egu2020-8002, 2020.

Cyclones developing in eastern coast of South America impact weather and control the climate in most parts of the continent as well as over the South Atlantic Ocean. Current knowledge of these cyclones shows that they can have different thermal and dynamic structures along their lifecycles being classified as tropical, subtropical or extratropical. Cyclones occurring over the sea generate intense near-surface winds with major impacts on human activities and ecosystems. Given this context, we are producing fine resolution (~25 km) dynamic downscaling with RegCM4 to investigate the climatic trends of the different phases of cyclones over the southwest South Atlantic Ocean. Special emphasis will be given on the contribution of subtropical cyclones causing extreme events (rainfall and wind) in eastern Brazil. The simulations cover South America and wider area of South Atlantic Ocean. For evaluation simulation RegCM4 is forced by ERA-Interim reanalysis, while for the projections by CMIP5 models under RCP4.5 and RCP8.5 scenarios. Cyclones are tracked using an algorithm based on cyclonic relative vorticity. In this study we present the climatology of all cyclones provided by the ERA-Interim evaluation simulation in the period 1979-2015. Basically, we discuss the ability of fine resolution simulation in reproducing the main cyclogenetic areas over the continent, seasonality and interannual variability of cyclones. Comparisons with previous simulations allow discussing the impact of fine resolution downscaling on the climatological features of all cyclones and their classification in South America domain.    

How to cite: Porfírio da Rocha, R., Reboita, M. S., Crespo, N. M., de Jesus, E. M., Cardoso, A. A., Dutra, L. M. M., and Nunes, A. M. B.: Climate projections in fine resolution downscaling over South America: trends and classification of cyclonic systems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10647, https://doi.org/10.5194/egusphere-egu2020-10647, 2020.

Snowpack and snowmelt driven extreme events can have large societal and economic consequences. Extreme snow can damage infrastructure and buildings. Snow meltwater is a dominant driver of severe spring flooding in the north-central and -eastern U.S. and southern Canada with impacts to the built and natural environments. However, the currently there is very limited guidance regarding the magnitude of “future” snow-driven extremes in a changing climate as needed to plan, design, and manage potentially vulnerable infrastructure and ecosystems. Regional climate models (RCMs) are commonly used to study and quantify regional climate changes, even though the ability of these models to accurately represent snow varies. In this study, trends and designs of extreme 25- and 100-year snowpack (snow water equivalent; SWE) and snowmelt events are estimated in the mid and late 21st century using the North America - Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) ensemble of RCMs under Representative Con-centration Pathways 8.5 (RCP 8.5). This study aims to answer the following three research questions:

1. How much will snow-driven extreme events be changed in the mid and late 21st century?
2. Which regions have the largest differences among models?
3. Which RCM models are the source of these regional uncertainties?

How to cite: Cho, E., McCrary, R. R., and Jacobs, J. M.: Future Snow Water Equivalent and Snowmelt Extremes from NA-CORDEX Ensembles, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5955, https://doi.org/10.5194/egusphere-egu2020-5955, 2020.

The representation and projection of extreme temperature and precipitation events in climate models are of major importance for developing polices to build communities’ resilience in the face of climate change. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensities, durations and frequencies of these extremes.

Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) Regional Climate Model (RCM) to determine the influence of the choice of land surface model (LSM) component on the uncertainty in the simulation of extreme event statistics. First, we evaluate land-atmosphere interactions within four simulations performed with the WRF model coupled to three different LSMs from 1980 to 2012 over North America. Results show regional differences among simulations for the frequency of events when surface conditions are altered by atmospheric forcing or by land surface processes. Second, we find a large inter-model range of extreme statistics across the ensemble of WRF-LSM simulations. This is particularly the case for indices related to the intensity and duration of temperature and precipitation extremes.

Regions displaying large uncertainty in the WRF simulation of extreme events are also identified in a model ensemble experiment carried out with three different RCMs participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project. This agreement between the model simulations performed in this work and the set of CORDEX simulations suggests that the implications of our results are valid for other model ensembles. This study illustrates the importance of supporting the development of new multi-LSM modeling studies to understand inter-model differences in simulating extreme events, ultimately helping to narrow down the range across climate model projections.

How to cite: García-García, A., Cuesta-Valero, F. J., Beltrami, H., González-Rouco, J. F., García-Bustamante, E., and Finnis, J.: Land Surface Model influence on the simulated climatologies of extreme temperature and precipitation events within the WRF model over North America, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3151, https://doi.org/10.5194/egusphere-egu2020-3151, 2020.

In order to assess the combined effects of green-house-gas-induced climate change and land-use land-cover change (LULCC), we have produced regional climate model (RCM) simulations that are complementary to the North-American Coordinated Regional Downscaling Experiment (NA-CORDEX) simulations, but with future LULCCs that are consistent with particular Shared Socioeconomic Pathways (SSPs).  In standard, existing NA-CORDEX simulations, land surface characteristics are held constant at present day conditions.  These new simulations, in conjunction with the NA-CORDEX simulations, will help us assess the magnitude of the changes in regional climate forced by LULCC relative to those produced by increasing greenhouse gas concentrations.     

Understanding the magnitude of the regional climate effects of LULCC is important to the SSP-RCP scenarios framework.  Whether or not the pattern of climate change resulting from a given SSP-RCP pairing is sensitive to the pattern of LULCC is an understudied problem.  This work helps address this question, and will inform thinking about possible needed modifications to the scenarios framework to better account for climate-land use interactions.

Accordingly, in this presentation, we will examine the state of the climate at the end of the 21^st century with and without SSP-driven LULCCs in RCM simulations produced using WRF under the RCP8.5 concentration scenario.  The included LULCC change effects have been created following the SSP3 and SSP5 narratives using an existing agricultural land model linked with a new long-term spatial urban land model. 

How to cite: Bukovsky, M., Mearns, L., Gao, J., and O'Neill, B.: The Sensitivity of Regional Climate Projections to SSP-Based Land Use Changes in the North American CORDEX Domain , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5906, https://doi.org/10.5194/egusphere-egu2020-5906, 2020.

The urban heat island (UHI) is a relaively old concept and has been widely studied using both observational and modeling approches. However, urban canopies impact the meteorological conditions in the planetary boundary layer (PBL) and above in many other ways, e.g. urban breeze circulation can form, enhanced drag causes intensification of the turbulent diffusion leading to elevated PBL height, reduced evaporation results in decreased absolute humidity, changes in cloudiness etc.
A well established regional model representation of these phenomena is crucial for both mitigation and adaptation in areas affected by intense urbanization and climate change. There are however large uncertainities how the underlying physical processes are represented in numerical models, i.e. what models are used along with which parameterizations and parameters.

Here we perform a regional multi-model analysis over central Europe using the Regional Climate Model (RegCM4) and Weather Research and Forecast (WRF) regional models with different configurations representing different PBL treatment, convection parameterization, surface layer physics, microphysics and urban canopy models. Model results are extensively compared to surface measurements as well as satellite observation of surface temperatures. We analyse the model results mainly in terms of the urban-rural contrast which is a measure of the difference between the urban core value and the vicitinity (with respect to the particular city) for selected meteorological parameters. Our results show substantial impact of the choice of the model as well as the choice of parameterization on the intensity of UHI and other meteorological effects. The urban-rural difference of PBL height and average wind speed between urban areas and their vicinity is affected the most, controlled by the boundary layer physics parameterization.
Our simulations confirm the large uncertainity in how models resolve the meteorological features specific to urbanized areas and this has to be taken into account when designing different strategies for urban planning and multimodel approaches should be preferred.

How to cite: Huszár, P., Karlický, J., Ďoubalová, J., Nováková, T., Švábik, F., Belda, M., and Halenka, T.: Regional modeling of urban climate: the impact of physical process representation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7001, https://doi.org/10.5194/egusphere-egu2020-7001, 2020.

High number of regional climate model (RCM) experiments have been accomplished over different subregions of the globe in the framework of the international initiative called the COordinated Regional Downscaling Experiment (CORDEX). Being the European branches of the CORDEX program: EURO-CORDEX and Med-CORDEX provide RCM simulations targeting Europe at grid resolutions of 0.11°. Investigation of ensembles of driving GCM and nested RCM simulations for the late 21^st century with respect to late 20^th century from the CMIP5, EURO-CORDEX, and Med-CORDEX experiments are presented at high resolution, with a special focus on mountainous regions such as the Alps and the Carpathians. Present work gives an overview on how the fine-scale RCM downscaling can modulate the GCM-produced precipitation change signal in future climate projections over the regions of interest. Our findings point to the fact that the topographically induced fine scale precipitation signal is mostly of dynamical nature in winter, while is more thermodynamic in nature during summer which manifests in strong elevation dependence, thus the high-resolution representation of topography in climate models is crucial for the provision of fine scale precipitation projections in mountainous regions.

How to cite: Torma, C. Z.: Orographic modulation and elevation dependence of regional fine scale precipitation change signals - European examples, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1251, https://doi.org/10.5194/egusphere-egu2020-1251, 2020.

International model intercomparison initiatives, such as CORDEX or CMIP5, along with several relatively recent projects at international and national level, provide a wealth of model simulations of future regional climate. In a recent work, Fernandez et al (2019) collected 196 different future climate change projections over Spain, considering data from ENSEMBLES, ESCENA, EURO- and Med-CORDEX, along with their driving global climate projections from CMIP3 and CMIP5. This ensemble mixed different multi-model initiatives in an ensemble of opportunity, in the sense that it does not respond to any scientific design beyond the exploration of multi-model uncertainty. This ensemble of opportunity is not only the result of the mixture of different initiatives, but also responds to the lack of a balanced experimental design within most of the initiatives. Many of the initiatives -especially those unfunded, such as CORDEX- are carried out on a voluntary basis, with no strong constraint in the global climate models (GCMs) used as boundary conditions or in the number of contributing members per regional climate model (RCM).

Fernandez et al (2019) found in this ensemble a strong influence of the driving GCM on the regional climate change signal, along with favored GCMs, selected by many regional climate modelling groups to the detriment of GCMs publishing their output later or not at all. In this work, we quantitatively assess the impact of unbalanced GCM-RCM ensembles. For this purpose, we subsampled the ensemble of opportunity to obtain balanced sets of members according to different “what-if” situations: What if all RCMs had contributed a single member to the ensemble? What if each GCM had been dynamically downscaled only once? What if a given GCM/RCM had not contributed to the ensemble? For each hypothesis, there are a number of alternative sub-ensembles, which are used to evaluate uncertainty.

Acknowledgement:

This work is partially funded by the Spanish government through MINECO/FEDER co-funded projects INSIGNIA (CGL2016-79210-R) and MULTI-SDM (CGL2015-66583-R). 

References:

Fernández, J., et al. (2019) Consistency of climate change projections from multiple global and regional model intercomparison projects. Clim Dyn 52:1139. https://doi.org/10.1007/s00382-018-4181-8

How to cite: Fernández, J. and Frías, M. D.: Balanced subsampling of future regional climate ensembles of opportunity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20052, https://doi.org/10.5194/egusphere-egu2020-20052, 2020.

In previous studies, it was noticed that many Regional Climate Models (RCMs) tend to overestimate mean near surface air temperature and underestimate precipitation in the Pannonian Basin during summer, leading to so-called summer drying problem [1]. Our intention for this study was to analyze temperature and precipitation biases in the state of the art EURO-CORDEX multi-model ensemble results in the summer season. Models’ results from the historical runs, and over time period 1971-2000, for temperature, precipitation and sea level pressure were verified against gridded E-OBS data set. In total there were 30 selected integrations, with different combinations of RCMs and Global Climate Models (GCMs). In order to assess the impact of the different lateral boundary conditions on the results from RCMs simulations, emphasizing the errors of the corresponding driving models used in 30 RCMs simulations, results from driving GCMs are also verified.

Verification results for selected time period was expressed in term of four verification scores: bias, root mean square error (RMSE), spatial correlation coefficient and standard deviations. Verification scores were evaluated within a sub-domain in the center of the region bounded by longitudes, 14E and 27E, and latitudes, 43.5N and 50N, in which topography elevation is below 200 m. This sub-domain was selected to eliminate the influence of results over the surrounding mountains on spatially averaged scores [2], because previous studies indicated a pronounced summer drying problem in low lying areas. Our analysis showed that 17 RCMs tend to overestimate the temperature, 8 RCMs tend to underestimate the temperature and 5 RCMs tend to estimate temperature around E-OBS gridded data set. On the other hand, most of the RCMs that overestimate the temperature, underestimate the precipitation. According to the results, temperature bias was in the range from -1.9°C to +4.4°C , while precipitation bias was in the range from 42% to -70%. For some models the positive temperature and negative precipitation bias were even more pronounced, leading to the conclusion, that the problem is still present in the majority of analyzed simulations. Analysis of the sea level pressure was conducted as an indirect indicator of errors in advection processes in RCMs, which was indicated, beside others, as a potential precursor of temperature and precipitation biases [3]. To better understand the sources and reasons for summer drying problem further research is needed.

[1] Kotlarski S. et al., (2014): Regional climate modelling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble. Geoscientific Model Development 7:1297–1333, doi: 10.5194/gmd-7-1297-2014

[2] Lazic I., Djurdjevic V., (2019): EURO-CORDEX regional climate models’ performances in representing temperature and precipitation over Pannonian Basin, Book of abstracts, 5th PannEx Workshop, 3-5 June 2019, Novi Sad, Serbia.

[3] Szépszó G., (2006): Adaptation of the REMO model at the Hungarian Meteorological Service (in Hungarian). Proceedings of the 31st Scientific Days for Meteorology, 125–135.

Keywords: summer drying problem, verification, EURO-CORDEX, Pannonian Basin

Acknowledgement: This study was supported by the Serbian Ministry of Science and Education, under grant no. 176013.

How to cite: Lazic, I. and Djurdjevic, V.: Temperature and precipitation verification over Pannonian Basin in EURO-CORDEX simulations during summer season, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-517, https://doi.org/10.5194/egusphere-egu2020-517, 2020.

Regional Climate Models (RCMs) are powerful tools to study changes in the climate system on the regional scale. However, the reliability of their simulations has been considerably limited by the longstanding issue that climate models often fail to reproduce various aspects of the historical climate. In our study, we analyse how RCMs from the EURO-CORDEX project are able to reproduce high-impact winter weather. We analyse temporal and spatial characteristics of snowfalls, wind gust, extreme temperatures, late spring frosts, total precipitation, and winter storms. Model outputs are validated against observed data from the gridded European database (EOBS) and the novel ERA5 reanalysis. We focus on the Central European domain (defined roughly between 48–52°N and 10–20°E) over the 1979 – 2017 period. We investigate a set of 12 simulations of 4 different RCMs driven by 3 different global climate models which allow us to analyse the influence of driving data on the RCM’s performance. Since local climate elements are relatively tightly linked to a large-scale atmospheric circulation over Europe in winter, we also evaluate the ability of RCMs to reproduce the atmospheric circulation and its links to selected high-impact winter weather in detail. Investigation of these links can lead to better physical understanding of the climate and to the identification of inadequacies in simulated characteristics of the studied events. All of this is an important step forward in further improving the models and enhancing the credibility of climate change scenarios based on climate model simulations.

How to cite: Plavcová, E., Lhotka, O., and Stryhal, J.: High-impact winter weather in EURO-CORDEX climate models and their links to large-scale atmospheric circulation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4620, https://doi.org/10.5194/egusphere-egu2020-4620, 2020.

Snow is a key environmental parameter in mountains, and in this changing climate reductions in snow are expected. Traditionally, future estimates of snow are based on dedicated snow/hydrological models forced by climate projections, which, however, are computationally intensive and which decouple hydrology from climate forcing. Recently, regional climate models (RCM) have been used as an alternative, although snow is only an auxiliary parameter in RCMs and not as accurately represented as compared to dedicated snow models. Nonetheless, RCMs encompass the climate-hydrology feedbacks, cover large areas, and have recently become available in moderate horizontal resolutions.

Here, we skip the need to biascorrect the input variables to the snow/hydrological models (i.e. temperature, precipitation, …) and use observations to directly biascorrect the target variable, i.e. snow cover. Quantile delta mapping (QDM), a trend preserving bias correction method, is used to correct biases in EURO-CORDEX RCMs that provide snow cover fraction as output (CCLM4-8-17, ALADIN63, WRF331F, WRF381P, RACMO22E, RCA4) using remote sensing observations of snow cover from MODIS for the European Alps. As such, snow cover biases were accounted for, which originated mostly from orographic mismatches as well as temperature and precipitation biases. Model ensemble means were calculated for two emission scenarios (rcp26 and rcp85; with 6 and 21 GCM-RCM combinations available). The biascorrected projections can be used to put the climate model projections into context of current observations thus facilitating interpretations.

These are results from CliRSnow, a project that aims at providing bias corrected and downscaled projections of snow cover for the whole Alpine region until 2100. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 795310.

How to cite: Matiu, M., Petitta, M., Notarnicola, C., and Zebisch, M.: Biascorrected projections of snow cover fraction from EURO-CORDEX regional climate models with MODIS remote sensing observations for the European Alps, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4610, https://doi.org/10.5194/egusphere-egu2020-4610, 2020.

Vapor Pressure Deficit (VPD) is an atmospheric variable that represents the extra water vapor that air may contain prior to condensation. It is a relevant variable for climatology due to its consideration as a measure of ‘air dryness’, but also for hydrology and ecohydrology. In spite of its relevance, studies focusing on VPD are scarce, especially when comparing with other variables such as temperature or precipitation. To obtain VPD values, temperature and air humidity data are required at the same time and location, which is difficult to obtain even in dense observational networks. While temperature is positively related with VPD, relative humidity shows a negative relation with VPD.

Within the framework of the CLICES Project, a spatial regionalization of VPD will be performed for mainland Spain. This project is focused on the climatic reconstruction of the last century and, for the most recent decades, data from a Regional Climate Model (RCM) simulation will be used as a complement of the observational data. Specifically, the climate of Spain for the period 1980-2017 at 3-hourly time step was simulated using REMO. Among a high amount of available methods, a bias correction procedure based on a quantile-quantile mapping in spatial coherent regions will be tested for the RCM correction. In order to implement this methodology, the VPD spatial regionalization is required and it will be addressed using a clustering methodology. Furthermore, regionalization of VPD will sharply improve our knowledge of this variable in Spain, a region showing high spatial contrasts affecting temperature, precipitation and wind speed. It is expected that the combination of the dissimilarities between temperature and precipitation will emerge in the regionalization of VPD values.

How to cite: Tomas-Burguera, M., Beguería Portugués, S., Serrano-Notivoli, R., and Cabos, W.: Regionalization of Vapor Pressure Deficit (VPD) in Spain, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16235, https://doi.org/10.5194/egusphere-egu2020-16235, 2020.

Water is one of Earth’s most important geo-ecosystem components. Here we present an evaluation of water cycle components using 12 EURO-CORDEX Regional Climate Models (RCMs) and the Terrestrial Systems Modeling Platform (TSMP) from ERA-Interim driven evaluation runs. Unlike the other RCMs, TSMP provides an integrated representation of the terrestrial water cycle by coupling the numerical weather prediction model COSMO, the land surface model CLM and the surface-subsurface hydrological model ParFlow, which simulates shallow groundwater states and fluxes. The study analyses precipitation (P), evapotranspiration (E), runoff (R), and terrestrial water storage (TWS=P-E-R) at a 0.11degree spatial resolution (about 12km) on EUR-11 CORDEX grid from 1996 to 2008. As reference datasets, we use ERA5 reanalysis to represent the complete terrestrial water budget, as well as the E-OBS, GLEAM and E-Run datasets for precipitation, evapotranspiration and runoff, respectively. The terrestrial water budget is investigated for twenty catchments over Europe (Guadalquivir, Guadiana, Tagus, Douro, Ebro, Garonne, Rhone, Po, Seine, Rhine, Loire, Maas, Weser, Elbe, Oder, Vistuala, Danube, Dniester, Dnieper, and Neman). Annual cycles, seasonal variations, empirical frequency distributions, spatial distributions for the water cycle components and budgets over the catchments are assessed. The analysis demonstrates the capability of the RCMs and TSMP to reproduce the overall characteristics of the water cycle over the EURO-CORDEX domain, which is a prerequisite if, e.g., climate change projections with the CORDEX RCMs or TSMP are to be used for vulnerability, impacts, and adaptation studies.

How to cite: Eltahan, M., Goergen, K., Furusho-Percot, C., and Kollet, S.: Intercomparison of terrestrial water budgets in EURO-CORDEX and TSMP evaluation runs, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5745, https://doi.org/10.5194/egusphere-egu2020-5745, 2020.

By modelling and forecasting  of meteorological  time  series it is possible to  improve   understanding  of  the  weather dynamics and fluctuations as a result of climate change . The most frequently used forecasting models are exponential smoothing, ARIMA models (Box and Jenkins, 1970), state-space models (Harvey, 1989) and innovations State Space Models (Hyndman et al., 2008).

The aim of this study was to check the effectiveness of the coupled TBATS and Support Vector Machines (SVM) model, supplied with some measured meteorological quantities to forecast air temperature for six years for four climatic localizations in Europe. The study was calculated from northern (Jokioinen in Finland), central (Dikopshof located in the west part of Germany and Nossen in the south part of Germany) and southern (Lleida in Spain) Europe to present different climatic conditions. Jokioinen city has a subarctic climate that has severe winters, with cool and short summers and strong seasonality. Lleida has a semi-arid climate with Mediterranean. Dikopshof represents maritime temperate climate. There are significant precipitation throughout the year in Dikopshof and Nossen. In the study we study on air temperature dataset collected on a daily basis from January 1st 1980 to December 31st 2010 (11322 days).

For all the studied sites coupled TBATS/SVM models occurred to be effective in predicting air temperature courses, giving an improved precision (up to 25%) in forecasting of the seasonality and local temperature variations, compared to pure SVM or TBATS modelling. The precision of prediction of the maximum and minimum air temperatures strongly depended on the dynamics of the weather conditions, and varied for different climatic zones.

This study has been partly financed from the funds of the Polish National Centre for Research and Development in frame of the project: MSINiN, contract number: BIOSTRATEG3/343547/8/NCBR/2017.

Reference to a journal publication:

BOX, G.E.P. – Jenkins, G. 1970. Time Series Analysis: forecasting and control. Holden-Day, p. 20-31.

HARVEY A. 1989. Forecasting Structural Time Series Model and the Kalman Filter. New York, Cambridge University press., p. 32-41.

HYNDMAN, R.J. – KOEHLER, A.B. – ORD, J.K. – SNYDER, R.D. 2008. Forecasting with Exponential Smoothing: The State Space Approach. Springer-Verlag, p. 50-62.

How to cite: Gos, M., Baranowski, P., Krzyszczak, J., Murat, M., and Malinowska, I.: Modeling of air temperatures using a combination of TBATS and SVM models for various climatic locations in Europe, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22227, https://doi.org/10.5194/egusphere-egu2020-22227, 2020.

Within the frame of BigData@Geo, a collaborative EFRE-funded project between the University of Würzburg and several medium-sized companies in regional pomi- and viticulture, a webportal similar to a climate-atlas is built. An Ensemble of six RCM/GCM-Couples from EURO-CORDEX with EUR-11 resolution is therefore retrieved. After a Nearest-Neighbour-Remap onto a 1x1km-grid within Lower Franconia (Bavaria, Germany), a linear bias-correction of air-temperature and precipitation is executed. The applied method calibrates mean seasonal cycles for the reference period 1970-1999 using gridded observation data from the German Weather Service. Subsequently, climatic tendecies of seasonal temperature and precipitation as well as various derived indizes (e.g. frostdays, hot days, tropical nights, vegetation period, huglin index) are evaluated along emission pathways rcp45 and rcp85 during the 21st century.

How to cite: Schönbein, D., Keupp, L., Pollinger, F., and Paeth, H.: BigData@Geo: A Climate Atlas for Lower Franconia (Germany), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3498, https://doi.org/10.5194/egusphere-egu2020-3498, 2020.

In cooperation with the Climate Service Center Germany (GERICS) we want to improve the land surface module in the regional climate model REMO. Due to the need of high-resolution regional climate models to get information about local climate change, new data and new processes have to be integrated in these models.

Based on the REMO2015 version and focusing on EUR-CORDEX region we included and compared five different high-resolution topographic data sets. To improve the thermal and hydrological processes in the model’s soil we also tested three new soil data sets with a much higher spatial resolution and with new parameters for a new soil parameterization.

How to cite: Ziegler, K., Pollinger, F., Abel, D., and Paeth, H.: REMOLAND: New high-resolution surface boundary data for the regional climate model REMO and their impacts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3005, https://doi.org/10.5194/egusphere-egu2020-3005, 2020.

The KlimAdat national project was started in 2016 to create a complex database of detailed meteorological information aiming to support local climate change impact studies in different sectors, adaptation strategies and related decision making. Besides observation data its primary basis will be ALADIN-Climate and REMO regional climate model simulations achieved by the Hungarian Meteorological Service and this set of projections will be extended by members of the Euro-CORDEX ensemble in order to quantify the projection uncertainties. 
This study is focusing on analysis of the ALADIN-Climate model projections driven with RCP4.5 and RCP8.5 scenarios. Firstly, the CNRM-CM5 global model outputs were downscaled to 50 km horizontal resolution over the EURO-CORDEX domain with ALADIN-Climate Version 5.2. Then using these  results as lateral boundary conditions, 10 km experiments were prepared on a domain covering Central and South-Eastern Europe.
The presentation aims to introduce the behaviour of these simulations achieved by different scenarios and at different spatial resolution from the aspect of temperature and precipitation change over Hungary. Special attention will be put on the differences in extreme indices. Finally, our 10 km resolution simulations are compared with EURO-CORDEX results to specify their place in a larger ensemble.

How to cite: Bán, B. and Zsebeházi, G.: Impacts of different RCP scenarios on ALADIN-Climate regional climate model projections over Hungary, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15871, https://doi.org/10.5194/egusphere-egu2020-15871, 2020.

Regional climate projections are necessary to assess possible changes in the exposure and risk to allow planning the adaptation strategies.

Projections of temperature and precipitation trends were developed using a consistent methodology and homogeneous datasets to address the needs of up-to-date climate change scenarios for Poland.

The Euro-Cordex results with the resolution of 0.11deg (about 12.5km) for RCP4.5 and RCP8.5 were downscaled based on various historical gridded datasets (EOBS, ERA5, UERRA and data from IMWM).

Ensemble analysis was undertaken to assess the projection uncertainty and ensemble mean were calculated for base parameters (daily average, minimum, and maximum temperature and daily precipitation sum) as well as for the number of climate indices.

We will present spatial and temporal variability of selected climate indices over Poland for subsequent decades. Increase of the annual average temperature is due to the rise in the number of hot days and the reduction of the number of frost days. All temperature indices are characterized by statistically significant trends, strongest for RCP8.5. The most pronounced changes in the frequency and amount of precipitation occur in the north-east of Poland. The total number of days with precipitation increases slightly. The increase in the annual rainfall is due to the increase in the number of days with extreme precipitation.

Results are presented via an interactive web portal. Further analysis includes the development of projection for solar radiation, wind speed, humidity and snow cover.

How to cite: Struzewska, J., Jefimow, M., Jagiełło, P., Kłeczek, M., Sattari, A., Gienibor, A., Norowski, A., Durka, P., Walczak, B., and Drzewiecki, P.: Temperature and precipitation projections for Poland based on downscaled EuroCORDEX ensemble, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14899, https://doi.org/10.5194/egusphere-egu2020-14899, 2020.

Almost universally, in Regional Climate Modeling (RCM) integrations, Davies’ relaxation lateral boundary conditions are applied. They force variables in a number of rows around the boundary to conform to the driver global model values, completely at the boundary, and less and less toward the inside of the integration domain. Very often, in addition, investigators apply so-called large scale or spectral nudging inside the domain, forcing the integration variables not to depart much from those of the driver model.

It is pointed out that there is no scientific basis for these two practices. So why are they used? In particular for the former of these two, it is suggested that reasons must be either a belief that this is a practice RCM should follow, or a technique to address numerical issues of the limited area model used, or a combination of the two.  For the latter, a belief only.

Examples are shown that, in the absence of these two stratagems, the limited area model can improve on large scales inside its domain. This demonstrates that their use, aimed to force variables inside the domain not to depart much from the driver model data, should be detrimental, if possible numerical issues of the model used were to be remedied.

How to cite: Mesinger, F., Veljovic, K., and Chou, S. C.: Lateral boundary relaxation and large scale nudging in RCM runs, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20830, https://doi.org/10.5194/egusphere-egu2020-20830, 2020.

The EFRE project Big Data@Geo aims at providing high resolution environmental information for the Lower Franconian region in Bavaria, Germany, including climate change simulations suitable and relevant for adaptation. Hence, it is a crucial tasks within this interdisciplinary project to enhance the regional climate model REMO, both by substantially increasing the spatial resolution as well as by including further processes in the model, which must be resolved on this new spatial scale.

For the first time, we successfully coupled REMO’s version 2015 (REMO15) with a superior land surface parametrization scheme (iMOVE) based on JSBACH. REMO15-iMOVE’s core feature is the interactive vegetation, represented on subgrid level via discrete classes. These plant functional types do not only respond to atmospheric forcing but in turn also affect numerous near-surface climate variables. In contrast, the standard version of REMO15 employs an idealized, constant seasonal cycle. Preliminary results indicate that REMO15-iMOVE vegetation's dynamic is in good agreement with observational data and hence the atmosphere’s lower boundary conditions should be more realistic than in REMO15.

To estimate the effects of the enhanced model on the simulation of thermal extreme events typically affecting Lower Franconia, we analyze for both versions one simulation with 0.1°x0.1° and one with 0.44°x0.44° horizontal resolution forced with ERA-Interim for the decade 2000-2009. We evaluate the occurrence of extremely warm (minimum temperature of 20.0°C or above or maximum temperature above 30.0°C) and cold days (maximum temperature below 0.0°C) as well as the spatio-temporal pattern of the European Heat Wave 2003 in comparison to E-OBS data. While the spatial resolution is clearly the main factor affecting the quality of the simulations, we also find significant effects of the land surface scheme on warm events.

Based on these first results, REMO15-iMOVE appears to be a capable and flexible tool for transient climate change simulations as well as for studies focussing on thermal extremes.

How to cite: Pollinger, F., Ziegler, K., Abel, D., and Paeth, H.: Effects of a new land surface parametrization scheme on thermal extremes in a Regional Climate Model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16320, https://doi.org/10.5194/egusphere-egu2020-16320, 2020.

Land surface-related processes play an essential role in the climate conditions at a regional scale. In this study, the impact of soil moisture (SM) initialization on regional climate modeling has been explored by using a dynamical downscaling experiment. To this end, the Weather Research and Forecasting (WRF) model was used to generate a set of high-resolution climate simulations driven by the ERA-Interim reanalysis for a period from 1989 to 2009. As the spatial configuration, two one-way nested domains were used, with the finer domain being centered over the Iberian Peninsula (IP) at a spatial resolution of about 10 km, and nested over a coarser domain that covers the Euro-CORDEX region at 50 km of spatial resolution.

The sensitivity experiment consisted of two control runs (CTRL) performed using as SM initial conditions those provided by ERA-Interim, and initialized for two different dates times (January and June). Additionally, another set of runs was completed driven by the same climate data but using as initial conditions prescribed SM under wet and dry scenarios.

The study is based on assessing the WRF performance by comparing the CTRL simulations with those performed with the different prescribed SM, and also, comparing them with the observations from the Spanish Temperature At Daily scale (STEAD) dataset. In this sense, we used two temperature extreme indices within the framework of decadal predictions: the warm spell index (WSDI) and the daily temperature range (DTR).

These results provide valuable information about the impact of the SM initial conditions on the ability of the WRF model to detect temperature extremes, and how long these affect the regional climate in this region. Additionally, these results may provide a source of knowledge about the mechanisms involved in the occurrence of extreme events such as heatwaves, which are expected to increase in frequency, duration, and magnitude under the context of climate change.

Keywords: soil moisture initial conditions, temperature extremes, regional climate, Weather Research and Forecasting model

Acknowledgments: This work has been financed by the project CGL2017-89836-R (MINECO-Spain, FEDER). The WRF simulations were performed in the Picasso Supercomputer at the University of Málaga, a member of the Spanish Supercomputing Network.

How to cite: García-Valdecasas Ojeda, M., Rosa-Cánovas, J. J., Romero-Jiménez, E., Yeste, P., Gámiz-Fortis, S. R., Castro-Díez, Y., and Esteban-Parra, M. J.: Impact of Soil Moisture Initialization on Temperature Extreme Detection in the context of Regional Climate Modeling , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17121, https://doi.org/10.5194/egusphere-egu2020-17121, 2020.

Climate indices, calculated from observations or model simulations, have become a common source of information for many climate impact studies. On the other hand, systematic errors in climate model results often present a barrier for wider use of indices, especially when calculated using the fixed threshold value. We propose and test a method of transformation of fixed threshold indices to percentile threshold indices, that can help to bypass a problem of model biases. To demonstrate the proposed method over Europe, we chose three fixed threshold indices: summer days (SU, TX > 25 °C), ice days (ID, TX < 0 °C) and number of days with daily rainfall greater than 10 mm (RR10, RR ≥ 10 mm), and two datasets: E-OBS gridded data and outputs from two regional climate models' (RCMs) simulations from the EURO-CORDEX database. We selected these indices and datasets, after more detailed analysis over Serbia [1], as a convenient subset to test proposed method over wider region.

The initial step in our method is to find corresponding percentile value for each fixed threshold of selected indices, within the historical period 1986-2005, for each grid point of E-OBS data. Then using these percentile values, and model results for the same time period, we set a unique new threshold for each model grid point such that the model-based  frequency of events that defines SU, ID, and RR10 is equal to the observed one. The difference between original fixed threshold and the new calculated threshold for each model grid point could be considered as an estimate of the systematic model error, and potentially could be used as additional information for model verification. Finally, we calculated future changes of the indices for the RCP8.5 scenario, using redefined thresholds and applying them for indices calculation over three future periods: 2016-2035, 2046-2065 and 2081-2100. To verify the proposed method, we compared our results of future changes of the indices with changes obtained from results of the same model which are bias corrected (i.e. bias-adjusted EURO-CORDEX) before calculation of the indices. Considering that bias-adjusted data are available just for limited number of all models in EURO-CORDEX ensemble, this method could help to increase number of ensemble members that could be used for analysis of future changes of climate indices, without bias correction of temperature and precipitation.

[1] Tosic, M., Djurdjevic, V., 2019: Transformation of fixed threshold to percentile based climate indices and implication on their change in the future, Book of abstracts, 5th PannEx Workshop: Building PannEx Task Teams to address environmental needs in the Pannonian basin, 3-5. june 2019, Novi Sad, Serbia

Key words: climate indices, temperature, precipitation, EURO-CORDEX, RCP8.5 scenario, bias correction

How to cite: Tosic, M. and Djurdjevic, V.: Proposal for transformation of fixed threshold to percentile based climate indices and implications on their changes in the future, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-516, https://doi.org/10.5194/egusphere-egu2020-516, 2020.