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An abnormal episode of high rain or snow is classified as heavy precipitation; its extreme intensity and driver mechanisms can vary a lot depending on location and season. The most extreme events can turn into a severe impact at ground (in terms of flood or flash-flood, human casualties and injuries, ecosystem and economy damages and losses).We have implemented a method to detect the most extreme precipitation events trough 10-year long dataset of high-resolution observations and built on a list of the most disastrous ones occurred between 2000 and 2009 within the so called great alpine region (1°–17° East, 40°–50° North).The method is then applied to the models belonging to the coordinated experiment CORDEX-FPS dedicated to convection and the ensemble at the convection permitting scale is able to represent the 70% of such kind of extreme events. The main drivers of the extreme precipitation are analysed and the factors affecting the model ability in correctly reproducing the unsuccessful cases are also investigated.The same framework has been applied also to the model projections under the RCP8.5 scenario to study the sensitivity of such episodes and of their driving mechanisms to the climate change. The extreme events are projected to increase in frequency especially in the fall season over sub-regions with prevailing orographic forcing, whereas the events related to complex mesoscale interactions are projected to affect larger areas at the end of the century, posing the conditions of increased flood risk.

Heatwaves (HWs) are high-impact phenomena stressing both societies and ecosystems. Their intensity and frequency are expected to increase in a warmer climate over many regions of the world. While these impacts can be wide-ranging, they are potentially influenced by local to regional features such as topography, land cover, and urbanization. Here, we leverage recent advances in the very high-resolution modelling required to elucidate the impacts of heatwaves at these fine scales. Further, we aim to understand how the new generation of km-scale regional climate models (RCMs) modulates the representation of heatwaves over a well-known climate change hot spot. We analyze an ensemble of 15 convection-permitting regional climate model (CPRCM, ~ 2–4 km grid spacing) simulations and their driving, convection-parameterized regional climate model (RCM, ~ 12–15 km grid spacing) simulations from the CORDEX Flagship Pilot Study on Convection. The focus is on the evaluation experiments (2000–2009) and three subdomains with a range of climatic characteristics. During HWs, and generally in the summer season, CPRCMs exhibit warmer and drier conditions than their driving RCMs. Higher maximum temperatures arise due to an altered heat flux partitioning, with daily peaks up to ~ 150 W/m2 larger latent heat in RCMs compared to the CPRCMs. This is driven by a 5–25% lower soil moisture content in the CPRCMs, which is in turn related to longer dry spell length (up to double). It is challenging to ascertain whether these differences represent an improvement. However, a point-scale distribution-based maximum temperature evaluation, suggests that this CPRCMs warmer/drier tendency is likely more realistic compared to the RCMs, with ~ 70% of reference sites indicating an added value compared to the driving RCMs, increasing to 95% when only the distribution right tail is considered. Conversely, a CPRCMs slight detrimental effect is found according to the upscaled grid-to-grid approach over flat areas. Certainly, CPRCMs enhance dry conditions, with knock-on implications for summer season temperature overestimation. Whether this improved physical representation of HWs also has implications for future changes is under investigation.

We describe the development of a non-hydrostatic version of the regional climate model RegCM4, called RegCM4-NH, for use at convection-permitting resolutions. The non-hydrostatic dynamical core of the Mesoscale Model MM5 is introduced in the RegCM4, with some modifications to increase stability and applicability of the model to long-term climate simulations. Newly available explicit microphysics schemes are also described, and three case studies of intense convection events are carried out in order to illustrate the performance of the model. They are all run at a convection-permitting grid spacing of 3 km over domains in northern California, Texas and the Lake Victoria region, without the use of parameterized cumulus convection. A substantial improvement is found in several aspects of the simulations compared to corresponding coarser-resolution (12 km) runs completed with the hydrostatic version of the model employing parameterized convection. RegCM4-NH is currently being used in different projects for regional climate simulations at convection-permitting resolutions and is intended to be a resource for users of the RegCM modeling system.

We present the first evaluation of the wind field from the CORDEX-FPS ensemble of kilometer-scale simulations, with focus on the Adriatic region. Kilometer-scale climate models, also known as convection-permitting models (CPMs), produce a good representation of small-scale topographic features and consequently a more detailed depiction of dynamical and thermal circulation. These enable a reliable view of climate characteristics of the wind field, especially in coastal regions and over complex terrain, such as the Adriatic. We investigate the (potential) added value introduced by CPMs compared to classical “cumulus-parametrized” regional climate models (RCMs), reanalysis and station observations. For this purpose, wind components at 10 meter level are used at 3-hourly frequency. All simulations cover a 10-year period, extending from 2000 to 2009. In terms of the standard statistical parameters such as correlation coefficient and temporal standard deviation, CPMs are very dependent on their parent RCM performance. However, the orographic forcing emphasizes the potential added value and CPMs contain some fine spatial scale variability (i.e. stronger extremes by 25% and accurate wind direction) that is absent in coarser RCMs and reanalysis. The potential added value is higher in the cold season compared to the warm season due to the proportion of severe wind events. CPMs reproduce well the typical wind regimes along the Adriatic coast, namely Bora and Sirocco. The benefit of using CPMs is especially pronounced in simulating Bora maximum wind speeds in northern Adriatic and Sirocco frequencies in southern Adriatic. Based on our overall analysis, we conclude that CPMs provide added value compared to coarser models, especially in the complex coastal terrain.

The added value of using regional climate models (RCMs) to downscale data from general circulation models (GCMs) has often been questioned and researched. Although several studies have used different methods to identify (and in some cases quantify) the added value, there is still a need to find a general metric that quantifies the added value of any variable. This paper builds on past studies to propose a new metric of added value in the simulation of present-day climate which measures the difference in the probability density functions (PDFs) at each grid-cell between a model and an observation source, and then compares the results of the RCM and GCM in order to spatially compute the added value index. The same method is also adapted to quantify the climate change downscaling signal in a way that is consistent with the present-day metric. These new metrics are tested on the daily precipitation output from the EURO-CORDEX and CORDEX-CORE projection ensembles and reveal an overall positive added value of RCMs, especially at the tail-end of the distribution. Higher added value is obtained in areas of complex topography and coast-lines, as well as in tropical regions. Areas with large added value in present-day climate are consistent with areas of significant climate change downscaling signal in the RCP 8.5 far future simulations, and when the analysis is repeated at a low-resolution. The use of different resolution observations shows that the added value tends to decrease when models are compared to low-resolution observation datasets.

Compared to standard regional climate models (RCMs), convection-permitting models (CPMs) provide an improved representation of sub-daily precipitation statistics and extremes thanks mainly to the possibility to switch off the deep convection parameterisation, a known source of model error and uncertainties. The more realistic representation of local processes in CPMs leads to a greater confidence in their projections of future changes in short-duration precipitation extremes.The quantification of uncertainties on future changes at this resolution has been barely touched. Using the first-ever ensemble of CPMs run within the UK Climate Projections project, Fosser et al. (2020) found that the climate change signal for extreme summer precipitation may converge in CPMs in contrast to RCMs, thanks to a more realistic representation of the local storm dynamics.Here we use the first multi-model CPMs ensemble over the greater Alpine region, run under the auspices of the World Climate Research Programme’s (WCRP) Coordinated Regional Downscaling Experiment Flagship Pilot Study on Convective phenomena at high resolution over Europe and the Mediterranean (Coppola et al. 2020). Several statistics are used to determine the uncertainties in the climate change signal trying to disentangle model uncertainties from natural variability. We found that the contribution of model to the total uncertainties is substantially reduced in CPMs compared to the driving models in summer. This is likely linked to the removal of the uncertainties associated with the convective parameterisation and to a more realistic representation of convective and local dynamical processes in the CPMs. Fosser G, Kendon EJ, Stephenson D, Tucker S (2020) Convection‐Permitting Models Offer Promise of More Certain Extreme Rainfall Projections. Geophys Res Lett 47:0–2. doi: 10.1029/2020GL088151Coppola, E., Sobolowski, S., Pichelli, E. et al.A first-of-its-kind multi-model convection permitting ensemble for investigating convective phenomena over Europe and the Mediterranean. Clim Dyn55, 3–34 (2020). https://doi.org/10.1007/s00382-018-4521-8

Climate change exhibits one of its strongest and shocking effects through extreme precipitation events. Extreme convective precipitation events are getting more intense and more frequent and their attribution to global warming is confirmed by recent studies in many regions of the world. During October the 4th and 5th a Nord-Atlantic trough entering the western Mediterranean favored the formation of deep convective systems feeded by the wet and warm prefrontal flow. One of them built up over the Ligurian Gulf on the 4th. Sustained by long-lasting interaction of large scale conditions and local forcings, the V-shape storm persisted over 24 hours locally accumulating more than 900 mm of rain. The event exceeded local and European precipitation records and caused landslides and flash-floods. In this study we try to objectively link the event to climate change through an extreme value theory analysis. This has been carried out through rain-gauge observations over Liguria, available continuously from 1960 for the fall season. The climate conditions of the event are compared to a pre-industrial period 1.2°C cooler than the present days. The Euro-CORDEX 12km resolution ensemble has been also used to confirm the event attribution to global warming.

Flash floods rank among the most dangerous and costliest hazards of the alpine and mediterranean region. The severe convective storms causing them are influenced by both, the presence of a large body of sea water and a complex orography. These storms are the main subject of the present study and in the following referred to as heavy precipitation events (HPEs).We here study heavy precipitation events by using an ensemble of convection permitting regional climate models and applying a tracking algorithm, and focus on their charateristic properties. The domain covers the Alps and the central part of the Mediterranean, and we investigate and compare three 10-year periods under the rcp85 forcing scenario: historical [2000-2009], near-future [2040-2049] and far-future [2090-2099].Our analysis reproduces a most important message: even though in the future the mediterranean climate is drying, precipitation associated with heavy precipitation events is increasing. Further, HPEs will be more frequent in the future. In particular, their occurrence frequency will increases in wintertime, whereas it will decrease in summertime.We investigate the climate change signal of characteristic properties describing the propagation, the spatial and temporal scales and the intensity of HPEs: on average HPEs travel by 10% farther [8km], they last longer by 5% [20 min], their area increases by 16% and their total rain volume by 34%. Regarding metrics of intensity the changes of the highest percentiles are greatest: the 90th percentiles of a HPE's precipitation field increases by 5.6%, the 99th percentile by 9.4% and the maximum increases by 12.7%.Eventually we unravel the characterics for specific regions and seasons: changes are more dramatical for HPEs that cross the coastline and in wintertime.In summary, this study confirms important messages of climate research in an ensemble of state-of-the-art regional climate models, demonstrates the capabilities of convection-permitting spatial resolution and explores the possibilities that come with applying a tracking algorithm and by looking into precipitation extremes in the Lagrangion framework of reference.

A new metric that quantifies Added Value (AV) was developed that compares the difference within the entire probability distribution functions (PDFs) of the Regional Climate Model (RCM) and its driving General Circulation Model (GCM) with a high-resolution observation source, at every grid point, to obtain a spatial distribution of AV. This is important to assess the validity of the computationally expensive process of downscaling, especially for Convection Permitting Models (CPMs). The method can be adapted to focus on the tail-end of the distribution, since GCMs struggle to resolve precipitation extremes. To achieve this, the threshold value of the percentile of interest (for example, the 95th percentile) is obtained from the observation source and then applied to the PDF data as a filter, after which the corresponding AV can be obtained. This metric can also be adapted to assess the Climate Change Downscaling Signal (CCDS) of climate projections, by comparing to the corresponding historical data-set instead of an observation source.This method is now being adapted to CPM simulations using a multi-model approach. The analysis is focused on both daily and hourly data from a 14-model ensemble of the ALP-3 domain using 5 high-resolution observation sources (GRIPHO for Italy; EURO4M for large alpine area; COMEPHORE for France; RADKLIM for Germany; and RdisaggH for Switzerland). The primary objective is to assess the added value of the CPM with the driving RCM, but a comparison to the GCM is also included. Preliminary results show that the CPM runs add value over the RCM, with possible emphasis in models/regions of lower RCM AV (requires confirmation by comparing RCMs to the driving GCMs). The analysis is will also focus on the CCDS metric of the near- and far-future simulations of the CPM, and the historical analysis is being replicated using hourly precipitation instead of daily.

Made available in DSpace on 2022-04-28T19:51:16Z (GMT). No. of bitstreams: 0 Previous issue date: 2022-02-01 Stichting Combined Ophthalmic Research Rotterdam Deutsche Kniegesellschaft European Society of Gastrointestinal Endoscopy We describe the first effort within the Coordinated Regional Climate Downscaling Experiment-Coordinated Output for Regional Evaluation, or CORDEX-CORE EXP-I. It consists of a set of twenty-first-century projections with two regional climate models (RCMs) downscaling three global climate model (GCM) simulations from the CMIP5 program, for two greenhouse gas concentration pathways (RCP8.5 and RCP2.6), over nine CORDEX domains at ~25-km grid spacing. Illustrative examples from the initial analysis of this ensemble are presented, covering a wide range of topics, such as added value of RCM nesting, extreme indices, tropical and extratropical storms, monsoons, ENSO, severe storm environments, emergence of change signals, and energy production. They show that the CORDEX-CORE EXP-I ensemble can provide downscaled information of unprecedented comprehensiveness to increase understanding of processes relevant for regional climate change and impacts, and to assess the added value of RCMs. The CORDEX-CORE EXP-I dataset, which will be incrementally augmented with new simulations, is intended to be a public resource available to the scientific and end-user communities for application to process studies, impacts on different socioeconomic sectors, and climate service activities. The future of the CORDEX-CORE initiative is also discussed. Abdus Salam International Centre for Theoretical Physics Climate Service Center Germany (GERICS) Oak Ridge National Laboratory University of Innsbruck National Center for Atmospheric Research, Boulder Centro de Investigación Científica y de Educación Superior de Ensenada National Institute of Oceanography and Applied Geophysics (INOGS) Abdus Salam International Centre for Theoretical Physics University of São Paulo Climate Change Research Centre School of Biological Earth and Environmental Science University of New South Wales Institute of Atmospheric Physics Chinese Academy of Sciences Hong Kong University of Science and Technology São Paulo State University Federal University of Itajuba University of Augsburg São Paulo State University

International audience; We here inter-compare four different tracking algorithms by applying them onto the precipitation fields of an ensemble of convection-permitting regional climate models (cpRCMs) and on high-resolution observational datasets of precipitation. The domain covers the Alps and the northern Mediterranean and thus we here analyse heavy precipitation events, that are renowned for causing hydrological hazards. In this way, this study is both, an inter-comparison of tracking algorithms as well as an evaluation study of cpRCMs in the Lagrangian frame of reference. The tracker inter-comparison is performed by comparison of two case studies as well as of climatologies of cpRCMs and observations. We find that that all of the trackers produce qualitatively equal results concerning characteristic track properties. This means that, despite of quantitative differences, equivalent scientific conclusions would be drawn. This result suggests that all trackers investigated are reliable analysis tools of atmospheric research. With respect to the model ensemble evaluation, we find an encouraging performance of cpRCMs in comparison to radar-based observations. In particular prominent hotspots of heavy precipitation events are well-reproduced by the models. In general most characteristic properties of precipitation events have positive biases. Assuming the under-catchment of precipitation in observations in a domain of such complex orography, this result is to be expected. Only the mean area of tracks is underestimated, while their duration is overestimated. Mean precipitation rate is estimated well, while maximum precipitation rate is overestimated. Furthermore, geometrical and rain volume are overestimated. We find that models overestimate the occurrence of precipitation events over all mountain chains, whereas over plain terrain in summer precipitation events are seen underestimated. This suggests that, despite the convection-permitting resolution, thermally driven thunderstorms are either not triggered or their dynamics still under-resolved. Eventually we find that biases in the spatio-temporal properties of precipitation events appear reduced when evaluating cpRCMs against Doppler radar-based and rain gauge-adjusted observational datasets of comparable spatial resolution, strengthening their role in evaluation studies.

The increase in computational resources has enabled the emergence of multi-model ensembles of convection-permitting regional climate model (CPRCM) simulations at very high horizontal resolutions. An example is the CORDEX Flagship Pilot Study on “Convective phenomena at high resolution over Europe and the Mediterranean”, a set of kilometre-scale simulations over an extended Alpine domain. This first-of-its-kind multi-model ensemble, forced by the ERA-Interim reanalysis, can be considered a benchmark dataset. This study uses a recently proposed metric to determine the added value of all the available Flagship Pilot Study hindcast kilometre-scale simulations for maximum and minimum temperature. The analysis is performed using state-of-the-art gridded and station observations as ground truth. This approach directly assesses the added value between the high-resolution CPRCMs against their driving global simulations and coarser resolution RCM counterparts. Overall, models display some modest gains, but also considerable shortcomings are exhibited. In part, these deficiencies can be attributed to the assimilation of temperature observations into ERA-Interim. Although the gains for the use of kilometre-scale resolution for temperature are limited, the improvement of the spatial representation of local atmospheric circulations and land–atmosphere interactions can ultimately lead to gains, particularly in coastal areas. The added value of km-scale simulations to describe temperature over complex orography: the CORDEX FPS-Convection multi-model ensemble runs over the Alps publishedVersion

Downscaling data from General Circulation Models (GCMs) with Regional Climate Models (RCMs) is a computationally expensive process, even more so running at the convection permitting scale (CP). Despite the high-resolution products of these simulations, the Added Value (AV) of these runs compared to their driving models is an important factor for consideration. A new method was recently developed to quantify the AV of historical simulations as well as the Climate Change Downscaling Signal (CCDS) of forecast runs. This method presents these quantities spatially and thus the specific regions with the most AV can be identified and understood.An analysis of daily precipitation from a 55-model EURO-CORDEX ensemble (at 12 km resolution) was assessed using this method. It revealed positive AV throughout the domain with greater emphasis in regions of complex topography, coast-lines, and the tropics. Similar CCDS was obtained when assessing the RCP 8.5 far future runs in these domains. This paper looks more closely at the CCDS obtained with this method and compares it to other climate change signals described in other studies.The same method is now being applied to assess the AV and CCDS of daily precipitation from an ensemble of models at the CP scale (~3 km) over different domains within Europe. The current stage of the analysis is also looking into the AV of using hourly precipitation instead of daily.

We here present a climate study on Heavy Precipitation Events (HPEs). To this aim we use an ensemble of convection-permitting regional climate models on a domain that covers the alps and large parts of the Mediterranean. These HPEs are generally meso-scale convective systems, which often are related to a landfall or orographic blocking. For society they are of major interest as they may damage infrastructure and threaten lives through flash floods and strong winds. From the models' output of precipitation we identify HPEs by applying an well-established clustering and tracking algorithm (MET MTD).Our study is organized into an evaluation and a climate study part. We evaluate the models by comparison of the evaluation scenario, driven by reanalysis data, against observations. In order to evaluate the tracking algorithm we analyse three specific historic events, occurring in southern France, central Italy and Germany. Eventually we investigate the climate response by comparison of the far future projection (2090-2100) under the rcp85 forcing against the historical scenario (1996-2006).In regards of the model evaluation we find that the annual cycle is very well captured by model ensemble, although the models overestimate HPEs over orography and underestimated HPEs over flatter terrain.Concerning the climate response our main result highlights that precipitation associated with HPEs is increasing in the far future, even though total annual precipitation is decreasing. Overall more HPEs occur in the far future, but only for an extended winter season (October to April), while for months May to September the occurrence of HPEs is decreasing. This behaviour motivates us to investigate the annual cycle of HPEs in greater detail.

Compared to standard regional climate models (RCMs), convection-permitting models (CPMs) provide an improved representation of sub-daily precipitation statistics and extremes thanks mainly to the possibility to switch off the deep convection parameterisation, a known source of model error and uncertainties. The more realistic representation of local processes in CPMs leads to a greater confidence in their projections of future changes in short-duration precipitation extremes. Recent literature on CPMs seems to agree on a future increase of extreme precipitation, above Clausius‐Clapeyron scaling in some cases, which is likely to have severe socio-economic impacts.The quantification of uncertainties on future changes at this resolution has been barely touched. Using the first‐ever ensemble of CPMs run within the UK Climate Projections project, Fosser et al. (2020) found that the climate change signal for extreme summer precipitation may converge in CPMs in contrast to RCMs, thanks to a more realistic representation of the local storm dynamics.Here we use the first multi-model CPMs ensemble over the greater Alpine region, run under the auspices of the World Climate Research Programme’s (WCRP) Coordinated Regional Downscaling Experiment Flagship Pilot Study on Convective phenomena at high resolution over Europe and the Mediterranean (Coppola et al. 2020). In our analysis we compared the uncertainties in the CPMs ensemble to the driving models following a similar method to Fosser et al. (2020). In this presentation we will show if multi-model CPMs can really provide more certain extreme rainfall projections then their parent coarser resolution models. Fosser G, Kendon EJ, Stephenson D, Tucker S (2020) Convection‐Permitting Models Offer Promise of More Certain Extreme Rainfall Projections. Geophys Res Lett 47:0–2. doi: 10.1029/2020GL088151Coppola, E., Sobolowski, S., Pichelli, E. et al. A first-of-its-kind multi-model convection permitting ensemble for investigating convective phenomena over Europe and the Mediterranean. Clim Dyn 55, 3–34 (2020). https://doi.org/10.1007/s00382-018-4521-8

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

The new Coordinated Output for Regional Evaluations (CORDEX-CORE) ensemble provides high-resolution, consistent regional climate change projections for the major inhabited areas of the world. It serves as a solid scientific basis for further research related to vulnerability, impact, adaptation and climate services in addition to existing CORDEX simulations. The aim of this study is to investigate and document the climate change information provided by the CORDEX-CORE simulation ensemble, as a part of the World Climate Research Programme (WCRP) CORDEX community. An overview of the annual and monthly mean climate change information in selected regions in different CORDEX domains is presented for temperature and precipitation, providing the foundation for detailed follow-up studies and applications. Initially, two regional climate models (RCMs), REMO and RegCM were used to downscale global climate model output. The driving simulations by AR5 global climate models (AR5-GCMs) were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. The CORDEX-CORE ensemble has doubled the spatial resolution compared to the previously existing CORDEX simulations in most of the regions (25$$\,\mathrm {km}$$km(0.22$$^{\circ }$$∘) versus 50$$\,\mathrm {km}$$km(0.44$$^{\circ }$$∘)) leading to a potentially improved representation of, e.g., physical processes in the RCMs. The analysis focuses on changes in the IPCC physical climate reference regions. The results show a general reasonable representation of the spread of the temperature and precipitation climate change signals of the AR5-GCMs by the CORDEX-CORE simulations in the investigated regions in all CORDEX domains by mostly covering the AR5 interquartile range of climate change signals. The simulated CORDEX-CORE monthly climate change signals mostly follow the AR5-GCMs, although for specific regions they show a different change in the course of the year compared to the AR5-GCMs, especially for RCP8.5, which needs to be investigated further in region specific process studies.

N. Ban et al., Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼ −40% at 12 km to ∼ −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales., Open access funding provided by University of Innsbruck and Medical University of Innsbruck., The ETH team, MZ, CNRM IPSL, ICTP, SMHI, Met-Office, DMI, CMCC, HZG, KNMI acknowledge funding from the HORIZON 2020 EUCP (European Climate Prediction System) project (https://www.eucp-project.eu, grant agreement No. 776613). AL-G acknowledges support by the Spanish government through grant BES-2016-078158 and MINECO/FEDER co-funded project MULTI-SDM (CGL2015-66583-R).

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.

We present a multi-model ensemble of regional climate model scenario simulations run at scales allowing for explicit treatment of convective processes (2-3km) over historical and end of century time slices, providing an overview of future precipitation changes over the Alpine domain within the convection-permitting CORDEX-FPS initiative. The 12 simulations of the ensemble have been performed by different research groups around Europe. The simulations are compared with high resolution observations to assess the performance over the historical period and the ensemble of 12 to 25 km resolution driving models is used as a benchmark.An improvement of the representation of fine scale details of the analyzed fields on a seasonal scale is found, as well as of the onset and peak of the summer diurnal convection. An enhancement of the projected patterns of change and modifications of its sign for the daily precipitation intensity and heavy precipitation over some regions are found with respect to coarse resolution ensemble. A change of the amplitude of the diurnal cycle for precipitation intensity and frequency is also shown, as well also a larger positive change for high to extreme events for daily and hourly precipitation distributions. The results are challenging and promising for further assessment of the local impacts of climate change.

Two Intensive Observation Periods (IOPs) of the Hydrological cycle in the Mediterranean eXperiment (HyMeX) are examined in this study. IOP6 and IOP13 were characterized by troughs with associated cold fronts entering the western Mediterranean and, in both cases, organized frontal convection in the Po Valley was observed. These similarities notwithstanding, predictability of the Po-Valley convection was limited for IOP6 for most of the forecast models available during HyMeX, but not for IOP13. Using the Weather Research and Forecast (WRF) model in research mode, the present study confirms the relatively good forecast for frontal convection in IOP13 is not very sensitive to modeling assumptions. In contrast, it is found that only a two-way-nested simulation, initialized close to the event, was able to produce a realistic representation of the squall line in the Po Valley for IOP6. A comparison between a ‘successful’ and an ‘unsuccessful’ simulation of the Po-Valley convection in IOP6 suggests the sensitivity lies with the orographic flow modification which was at the threshold between ‘flow-over’ and ‘flow-around’ responses to the Maritime Alps. In particular, in the ‘flow-over’ regime, downslope winds from the Maritime Alps and Apennines suppress the convergence/uplift where the front encounters the barrier wind in the Po Valley, while in the ‘flow-around’ regime, it is unimpeded. A delicate balance between the competing mechanisms of orographically induced subsidence on the lee side of the Apennines and frontal uplift in the Po Valley is found to be crucial for squall-line survival.

This paper is a contribution to the special issue on Advances in Convection-Permitting Climate Modeling, consisting of papers that focus on the evaluation, climate change assessment, and feedback processes in kilometer-scale simulations and observations., A recently launched project under the auspices of the World Climate Research Program’s (WCRP) Coordinated Regional Downscaling Experiments Flagship Pilot Studies program (CORDEX-FPS) is presented. This initiative aims to build first-of-its-kind ensemble climate experiments of convection permitting models to investigate present and future convective processes and related extremes over Europe and the Mediterranean. In this manuscript the rationale, scientific aims and approaches are presented along with some preliminary results from the testing phase of the project. Three test cases were selected in order to obtain a first look at the ensemble performance. The test cases covered a summertime extreme precipitation event over Austria, a fall Foehn event over the Swiss Alps and an intensively documented fall event along the Mediterranean coast. The test cases were run in both “weather-like” (WL, initialized just before the event in question) and “climate” (CM, initialized 1 month before the event) modes. Ensembles of 18–21 members, representing six different modeling systems with different physics and modelling chain options, was generated for the test cases (27 modeling teams have committed to perform the longer climate simulations). Results indicate that, when run in WL mode, the ensemble captures all three events quite well with ensemble correlation skill scores of 0.67, 0.82 and 0.91. They suggest that the more the event is driven by large-scale conditions, the closer the agreement between the ensemble members. Even in climate mode the large-scale driven events over the Swiss Alps and the Mediterranean coasts are still captured (ensemble correlation skill scores of 0.90 and 0.62, respectively), but the inter-model spread increases as expected. In the case over Mediterranean the effects of local-scale interactions between flow and orography and land–ocean contrasts are readily apparent. However, there is a much larger, though not surprising, increase in the spread for the Austrian event, which was weakly forced by the large-scale flow. Though the ensemble correlation skill score is still quite high (0.80). The preliminary results illustrate both the promise and the challenges that convection permitting modeling faces and make a strong argument for an ensemble-based approach to investigating high impact convective processes., IG and LS have been supported by the Croatian Science Foundation (HrZZ) project CARE (no. 2831). JF acknowledges support by the Spanish R + D programme through MINECO/FEDER co-funded project INSIGNIA (CGL2016-79210-R). AL-G is supported by the Spanish government though grant BES-2016-078158 and MINECO/FEDER co-funded project MULTI-SDM (CGL2015-66583-R). JM and KW-S gratefully acknowledge the support by the German Science Foundation (DFG) through project FOR 1695. DM, MP, and HT gratefully acknowledge the support received via the Austrian Science Fund (FWF) project NHCM-2 (no. P24758-N29) and the projects HighEnd:Extremes and EASICLIM, funded by the Austrian Climate Research Programme (ACRP) of the Klima- und Energiefonds (nos. KR13AC6K10981 and KR16AC0K13160, respectively). SS and TL acknowledge the support of NOTUR project no. NN9280K and the Research Council of Norway and its basic institute support of their strategic project on Climate Services. RMC and PMMS gratefully acknowledge the support of the SOLAR project (PTDC/GEOMET/7078/2014) financed by the Portuguese Foundation for Science and Technology. EJ Kendon gratefully acknowledges funding from the Joint Department of Energy and Climate Change (DECC) and Department for Environment Food and Rural Affairs (Defra) Met Office Hadley Centre Climate Programme (GA01101). S. Khodayar research is supported by the Bundesministerium für Bildung und Forschung (BMBF; German Federal Ministry of Education and Research). Support of Ministry of Education, Youth and Sports of the Czech Republic for funding the participation in Euro-CORDEX activities via the scheme INTER-TRANSFER under the Grant no. LTT17007. Funding from the Research Council of Norway through the SUPER (Grant no. 250573) and HYPRE (Grant no. 243942) projects.

High Impact Weather (HIW), particularly Heavy Precipitation Events (HPE), are common phenomena affecting the Western Mediterranean (WMED) especially in the fall period. Understanding and evaluating the capability to adequately represent such events in model simulations is one of the main goals of the Hydrological cycle in the Mediterranean Experiment (HyMeX) and the main motivation of this investigation. In order to gain a better knowledge of the model representation of HPE and related processes we perform a seamless multi-model intercomparison at the event scale. Limited area model runs (grid spacing from 2 to 20 km) at weather and climate timescales are considered, four with parameterized and five with explicit convection. The performance of the nine models is compared by analysing precipitation, as well as convection-relevant parameters. An Intensive Observation Period (IOP12) from the HyMeX-SOP1 (Special Observation Period) is used to illustrate the results. During IOP12, HPE affected the north-western Mediterranean region, from Spain to Italy, as a consequence of Mesoscale Convective Systems (MCSs) which initiated and intensified in the area of investigation. Results show that: (i) the timing of the maximum precipitation seems to be linked with the representation of large-scale conditions rather than differences among models, (ii) Convection Permitting Models (CPMs) exhibit differences among each other, but better represent the short-intense convective events. All four convection-parameterised models produce a large number of weak and long-lasting events. Regional Climate Models (RCMs) capture the occurrence of the event but produce notably lower precipitation amount and hourly intensities than CPMs and Numerical Weather Prediction (NWP) models with parameterized convection. (iii) These differences do not seem to come from mean moisture or Convective Available Potential Energy (CAPE) which are in the same range for all models, but rather from differences in the variability and vertical distribution of moisture and the triggering of deep convection.

Spaceborne interferometric synthetic aperture radar (SAR) (InSAR) imaging has been used for over a decade to monitor tectonic movements and landslides, as well as to improve digital elevation models. However, InSAR is affected by variations in round-trip propagation delay due to changes in ionospheric total electron content and in tropospheric humidity and temperature along the signal path. One of the largest sources of uncertainty in estimates of tropospheric path delay is the spatial and temporal variability of water vapor density, which currently limits the quality of InSAR products. This problem can be partially addressed by using a number of SAR interferograms from subsequent satellite overpasses to reduce the degradation in the images or by analyzing a long time series of interferometric phases from permanent scatterers. However, if there is a sudden deformation of the Earth's surface, the detection of which is one of the principal objectives of InSAR measurements over land, the effect of water vapor variations cannot be removed, reducing the quality of the interferometric products. In those cases, high-resolution information on the atmospheric water vapor content and its variation with time can be crucial to mitigate the effect of wet-tropospheric path delay variations. This paper describes the use of a ground-based microwave radiometer network to retrieve 3-D water vapor density with fine spatial and temporal resolution, which can be used to reduce InSAR ambiguities due to changes in wet-tropospheric path delay. Retrieval results and comparisons between the integrated water vapor measured by the radiometer network and satellite data are presented.

The Special Observation Period (SOP1), part of the HyMeX campaign (Hydrological cycle in the Mediterranean Experiments, 5 September–6 November 2012), was dedicated to heavy precipitation events and flash floods in the western Mediterranean, and three Italian hydro-meteorological monitoring sites were identified: Liguria–Tuscany, northeastern Italy and central Italy. The extraordinary deployment of advanced instrumentation, including instrumented aircrafts, and the use of several different operational weather forecast models, including hydrological models and marine models, allowed an unprecedented monitoring and analysis of high-impact weather events around the Italian hydro-meteorological sites. This activity has seen strong collaboration between the Italian scientific and operational communities. In this paper an overview of the Italian organization during SOP1 is provided, and selected Intensive Observation Periods (IOPs) are described. A significant event for each Italian target area is chosen for this analysis: IOP2 (12–13 September 2012) in northeastern Italy, IOP13 (15–16 October 2012) in central Italy and IOP19 (3–5 November 2012) in Liguria and Tuscany. For each IOP the meteorological characteristics, together with special observations and weather forecasts, are analyzed with the aim of highlighting strengths and weaknesses of the forecast modeling systems, including the hydrological impacts. The usefulness of having different weather forecast operational chains characterized by different numerical weather prediction models and/or different model set up or initial conditions is finally shown for one of the events (IOP19).

The urban forcing on thermo-dynamical conditions can largely influences local evolution of the atmospheric boundary layer. Urban heat storage can produce noteworthy mesoscale perturbations of the lower atmosphere. The new generations of high-resolution numerical weather prediction models (NWP) is nowadays largely applied also to urban areas. It is therefore critical to reproduce correctly the urban forcing which turns in variations of wind, temperature and water vapor content of the planetary boundary layer (PBL). WRF-ARW, a new model generation, has been used to reproduce the circulation in the urban area of Rome. A sensitivity study is performed using different PBL and surface schemes. The significant role of the surface forcing in the PBL evolution has been verified by comparing model results with observations coming from many instruments (LiDAR, SODAR, sonic anemometer and surface stations). The crucial role of a correct urban representation has been demonstrated by testing the impact of different urban canopy models (UCM) on the forecast. Only one of three meteorological events studied will be presented, chosen as statistically relevant for the area of interest. The WRF-ARW model shows a tendency to overestimate vertical transmission of horizontal momentum from upper levels to low atmosphere, that is partially corrected by local PBL scheme coupled with an advanced UCM. Depending on background meteorological scenario, WRF-ARW shows an opposite behavior in correctly representing canopy layer and upper levels when local and non local PBL are compared. Moreover a tendency of the model in largely underestimating vertical motions has been verified.

Spaceborne Interferometric Synthetic Aperture Radar (InSAR) is a well established technique useful in many land applications, such as landslide monitoring and digital elevation model extraction. One of its major limitation is the atmospheric effect, and in particular the high water vapour spatial and temporal variability which introduces an unknown delay in the signal propagation. However, the sensitivity of SAR interferometric phase to atmospheric conditions could in principle be exploited and InSAR could become in certain conditions a tool to monitor the atmosphere, as it happens with GPS receiver networks. This paper describes a novel attempt to assimilate InSAR derived information on the atmosphere, based on the Permanent Scatterer multipass technique, into a numerical weather forecast model. The methodology is summarised and the very preliminary results regarding the forecast of a precipitation event in Central Italy are analysed. The work was done in the framework of an ESA funded project devoted to the mapping of the water vapour with the aim to mitigate its effect for InSAR applications.

Spaceborne Interferometric Synthetic Aperture Radar (InSAR) is a well established technique useful in many land applications, such as tectonic movements, landslide monitoring and digital elevation model extraction. One of its major limitation is the atmospheric effect, and in particular the high water vapour spatial and temporal variability which introduces an unknown delay in the signal propagation. This paper describes the general approach and some results achieved in the framework of an ESA funded project devoted to the mapping of the water vapour with the aim to mitigate its effect in InSAR applications. Ground based (microwave radiometers, radiosoundings, GPS) and spaceborne observations (AMSR-E, MERIS, MODIS) of columnar water vapour were compared with Numerical Weather Prediction model runs in Central Italy during a 15-day experiment. A dense network of GPS receivers was deployed close to Como, in Northern Italy, to complement the operational network in order to derive Zenith Total Delay as well as Slant Delay which can support InSAR processing. A comparison with Atmospheric Phase Screens (APS) derived from a sequence of Envisat multi pass interferometric acquisitions processed using the Permanent Scatters technique on the two test sites has been also performed. The acquired experimental data and their comparison give a valuable idea of what can be done to gather information on water vapour, which, besides InSAR applications, plays a fundamental role in weather prediction and radio propagation studies. The work has been carried out in the framework of an ESA funded project, named “Mitigation of Electromagnetic Transmission errors induced by Atmospheric Water Vapour Effects” (METAWAVE). This paper presents the general approach an the various methodologies exploited in the project, together with the overall intercomparison of the results. In deep details on the comparison with the InSAR APS maps derived by the PS technique, as well as on GPS receiver processing and water vapour tomography are reported in two companion papers.

Spaceborne Interferometric Synthetic Aperture Radar (InSAR) is a well established technique useful in many land applications, such as monitoring tectonic movements and landslides or extracting digital elevation models. One of its major limitations is the atmospheric variability, and in particular the high water vapor spatial and temporal variability, which introduces an unknown delay in the signal propagation. On the other hand, these effects might be exploited, so as InSAR could become a tool for highresolution water vapor mapping. This paper describes the approach and some preliminary results achieved in the framework of an ESA funded project devoted to the mitigation of the water vapor effects in InSAR applications. Although very preliminary, the acquired experimental data and their comparison give a first idea of what can be done to gather valuable information on water vapor, which play a fundamental role in weather prediction and radio propagation studies.

[1] Hourly and daily variations of surface ozone have been analyzed in relation to radon and meteorological parameters to explore its controlling mechanisms. Measurements in central Italy cover the years 2004 and 2005, showing a relevant role of transport in the ozone concentration variability. An analysis based on back trajectories shows that the site is affected by air masses originating from the west to northeast sector in about 74% of the days, suggesting that L’Aquila could be considered a background site. The background hypothesis is also supported by the rather low values of the following ozone quantities: maximum of monthly averages (39 ppbv, July), annual median of hourly data (29 ppbv), and annual average of hourly maxima recorded daily (49 ppbv). Only six hourly data recorded ozone above 90 ppbv in 2 years but never above 100 ppbv. The regression model reproduces measured ozone with accuracy in 67% of hourly observations and 74% of daily mean data. Here the model includes information from the following meteorological parameters: temperature, relative humidity, horizontal wind speed/direction, sun radiation, and radon concentration. A tracer like radon that tracks the dynamical changes of the lower atmosphere has a significant role in the model ozone prediction improvement, especially for hourly observations and for the synoptic component. In the first case (hourly observation), inclusion of radon data improves the regression model performance by 5% (from 62 to 67%); in the last case (synoptic component), the model accuracy increases by 3% (from 78 to 81%).

This paper presents the first multi-model ensemble of 10-year, “convection-permitting” kilometer- scale regional climate model (RCM) scenario simulations downscaled from selected CMIP5 GCM projections for historical and end of century time slices. The technique is to first downscale the CMIP5 GCM projections to an intermediate 12–15 km resolution grid using RCMs, and then use these fields to downscale further to the kilometer scale. The aim of the paper is to provide an overview of the representation of the precipitation characteristics and their projected changes over the greater Alpine domain within a Coordinated Regional Climate Downscaling Experiment Flagship Pilot Study and the European Climate Prediction system project, tasked with investigating convective processes at the kilometer scale. An ensemble of 12 simulations performed by different research groups around Europe is analyzed. The simulations are evaluated through comparison with high resolution observations while the complementary ensemble of 12 km resolution driving models is used as a benchmark to evaluate the added value of the convection-permitting ensemble. The results show that the kilometer-scale ensemble is able to improve the representation of fine scale details of mean daily, wet-day/hour frequency, wet- day/hour intensity and heavy precipitation on a seasonal scale, reducing uncertainty over some regions. It also improves the representation of the summer diurnal cycle, showing more realistic onset and peak of convection. The kilometer-scale ensemble refines and enhances the projected patterns of change from the coarser resolution simulations and even modifies the sign of the precipitation intensity change and heavy precipitation over some regions. The convection permitting simulations also show larger changes for all indices over the diurnal cycle, also suggesting a change in the duration of convection over some regions. A larger positive change of frequency of heavy to severe precipitation is found. The results are encouraging towards the use of convection-permitting model ensembles to produce robust assessments of the local impacts of future climate change.

The local distribution of water vapour in the urban area of Rome has been studied using both a high resolution mesoscale model (MM5) and Earth Remote Sensing-1 (ERS-1) satellite radar data. Interferometric Synthetic Aperture Radar (InSAR) techniques, after the removal of all other geometric effects, estimate excess path length variation between two different SAR acquisitions (Atmospheric Phase Screen: APS). APS are strictly related to the variations of the water vapour content along the radar line of sight. To the aim of assessing the MM5 ability to reproduce the gross features of the Integrated Water Vapour (IWV) spatial distribution, as a first step ECMWF IWV has been used as benchmark against which the high resolution MM5 model and InSAR APS maps have been compared. As a following step, the high resolution IWV MM5 maps have been compared with both InSAR and surface meteorological data. The results show that the high resolution IWV model maps compare well with the InSAR ones. Support to this finding is obtained by semivariogram analysis that clearly shows good agreement beside from a model bias.

Synthetic Aperture Radar (InSAR) imaging is a well established technique to derive useful products for several land applications. One of the major limitations of InSAR is due to atmospheric efiects, and in particular to high water vapor variability. In this work, we make an experimental analysis to research the capability of Numerical Weather Prediction (NWP) models as MM5 to produce high resolution (1km{500m) maps of Integrated Water Vapor (IWV) in the atmosphere to mitigate the well-known disturbances that afiect the radar signal while traveling from the sensor to the ground and back. Experiments have been conducted over the area surrounding Rome using ERS data acquired during the three days phase in '94 and using Envisat data acquired in recent years. By means of the PS technique SAR data have been processed and the Atmospheric Phase Screen (APS) of Slave images with respect to a reference Master have been extracted. MM5 provides realistic water vapor distribution flelds that can be converted into electromagnetic slant delays. PSInSAR APS's have then been compared to MM5 IWV maps revealing interesting results. MM5 IWV maps have a much lower resolution than PSInSAR APS's: the turbulent term of the atmospheric vapor fleld cannot be well resolved by MM5, at least with the low resolution ECMWF inputs. However, the vapor distribution term that depends on the local topography has been found quite in accordance. In this work, we will present experimental results as well as discussions over the adopted processing strategy.