We implement and evaluate a new parameterization scheme for stratiform cloud microphysics and precipitation within regional climate model RegCM4. This new parameterization is based on a ...multiple-phase one-moment cloud microphysics scheme built upon the implicit numerical framework recently developed and implemented in the ECMWF operational forecasting model. The parameterization solves five prognostic equations for water vapour, cloud liquid water, rain, cloud ice, and snow mixing ratios. Compared to the pre-existing scheme, it allows a proper treatment of mixed-phase clouds and a more physically realistic representation of cloud microphysics and precipitation. Various fields from a 10-year long integration of RegCM4 run in tropical band mode with the new scheme are compared with their counterparts using the previous cloud scheme and are evaluated against satellite observations. In addition, an assessment using the Cloud Feedback Model Intercomparison Project (CFMIP) Observational Simulator Package (COSP) for a 1-year sub-period provides additional information for evaluating the cloud optical properties against satellite data. The new microphysics parameterization yields an improved simulation of cloud fields, and in particular it removes the overestimation of upper level cloud characteristics of the previous scheme, increasing the agreement with observations and leading to an amelioration of a long-standing problem in the RegCM system. The vertical cloud profile produced by the new scheme leads to a considerably improvement of the representation of the longwave and shortwave components of the cloud radiative forcing.
The identification of flood prone areas is essential for a range of engineering, risk reduction and research applications. Here, we describe a combined hydrological and hydraulic modelling approach ...for the assessment of flood‐prone areas and we present the results obtained over the Po river (Northern Italy). Runoff and river discharges are calculated through the hydrological model CHyM driven by GRIPHO, a new precipitation dataset for Italy. River flow data are used to obtain flood hydrographs for the CA2D hydraulic model, which calculates flood hazard maps at a resolution of 90 m. Flood simulations are run over a re‐shaped HydroSHEDS digital elevation model that includes information of the channel geometry. Modeled flood hydrographs are compared with observed data for a choice of gauging stations, showing a good performance of the CHyM model. We validate the flood hazard maps against observed flood events and official hazard maps. For high return periods, modelled maps can correctly identify up to 67% of the flood extent, both on the Po River and on smaller tributaries, while performances are more variable for lower return periods. Overall, the proposed approach suggests a strong potential for further applications, such as flood hazard assessment under future climate scenarios.
Abstract Observations are increasingly used to constrain multi-model projections for future climate assessments. This study assesses the performance of five constraining methods, which have ...previously been applied to attempt to improve regional climate projections from CMIP5-era models. We employ an out-of-sample testing approach to assess the efficacy of these constraining methods when applied to “pseudo-observational” datasets to constrain future changes in the European climate. These pseudo-observations are taken from CMIP6 simulations, for which future changes were withheld and used for verification. The constrained projections are more accurate and broadly more reliable for regional temperature projections compared to the unconstrained projections, especially in the summer season, which was not clear prior to this study. However, the constraining methods do not improve regional precipitation projections. We also analysed the performance of multi-method projections by combining the constrained projections, which are found to be competitive with the best-performing individual methods and demonstrate improvements in reliability for some temperature projections. The performance of the multi-method projection highlights the potential of combining constraints for the development of constraining methods.
Climate change impact on flood hazard over Italy García-Valdecasas Ojeda, Matilde; Di Sante, Fabio; Coppola, Erika ...
Journal of hydrology (Amsterdam),
December 2022, 2022-12-00, Letnik:
615
Journal Article
Recenzirano
•Validation of CHyM hydrological model simulation over the whole Italian river basin.•Projection of flood hazards in Italy with CHyM driven by a RegCM EURO-CORDEX projection.•The sensitivity of ...climate projection results to the use of a bias correction method.
This study assesses future projections of flood hazards across the Italian river basins. For this purpose, sub-daily river discharge for the entire Italian territory was simulated with the CETEMPS hydrological model (CHyM) using as climate forcing both observational datasets and regional climate simulations completed with the ICTP Regional Climate Model (RegCM4). First, simulated precipitation and river discharge were evaluated against observational products, showing both models good performance in simulating Italian precipitation and discharge characteristics. Then, projections of these variables were explored for two time slices, near (2020–2049) and far (2070–2099) future, under the RCP8.5 emission scenario, with RegCM4 driven by output from a global climate model projection. The RegCM4 outputs were also bias-adjusted by means of the N-dimension multivariate bias correction (MBCn) method. We found that, although the bias correction leads to a benefit in capturing mean precipitation, the improvement is less clear for extreme precipitation. In terms of discharge, however, bias correction has a noticeable impact on mean discharge as well as average yearly peak flow and hourly peak flow at return periods of 10, 50, and 100 years. Nevertheless, for a large part of the Italian territory, projected changes in mean precipitation and discharge do not show significant differences when bias correction is applied, while for extreme events only ∼30 % of river points show significant sensitivity to bias correction. Under the RCP8.5 scenario, an increase in yearly peak flow is evident over most of the Italian peninsula, with values increasing from 30 % to more than 100 % for the mid and far time slices respectively, especially over the Po River and along the eastern coasts of Italy. Similar conclusions are found for the hourly peak flows of 10, 50, and 100-year return periods. These indicators thus suggest a general increase in flood hazard expected over the region.
Our planet’s climate has been warming much faster over the past 100 years than it has over the 10,000 years before that. In this article, we will explore how we know that the climate has changed so ...quickly in the last century, what carbon dioxide (CO
2
) has to do with climate change, and why humans are responsible for the recent increase of CO
2
in the atmosphere. Understanding the problem is the best way to find a solution!
Political decisions, adaptation planning, and impact assessments need reliable estimates of future climate change and related uncertainties. To provide these estimates, different approaches to ...constrain, filter, or weight climate model projections into probabilistic distributions have been proposed. However, an assessment of multiple such methods to, for example, expose cases of agreement or disagreement, is often hindered by a lack of coordination, with methods focusing on a variety of variables, time periods, regions, or model pools. Here, a consistent framework is developed to allow a quantitative comparison of eight different methods; focus is given to summer temperature and precipitation change in three spatial regimes in Europe in 2041–60 relative to 1995–2014. The analysis draws on projections from several large ensembles, the CMIP5 multimodel ensemble, and perturbed physics ensembles, all using the high-emission scenario RCP8.5. The methods’ key features are summarized, assumptions are discussed, and resulting constrained distributions are presented. Method agreement is found to be dependent on the investigated region but is generally higher for median changes than for the uncertainty ranges. This study, therefore, highlights the importance of providing clear context about how different methods affect the assessed uncertainty—in particular, the upper and lower percentiles that are of interest to risk-averse stakeholders. The comparison also exposes cases in which diverse lines of evidence lead to diverging constraints; additional work is needed to understand how the underlying differences between methods lead to such disagreements and to provide clear guidance to users.
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.
This paper analyzes the ensemble of regional climate model (RCM) projections for Europe completed within the EURO‐CORDEX project. Projections are available for the two greenhouse gas concentration ...scenarios RCP2.6 (22 members) and RCP8.5 (55 members) at 0.11° resolution from 11 RCMs driven by eight global climate models (GCMs). The RCM ensemble results are compared with the driving CMIP5 global models but also with a subset of available last generation CMIP6 projections. Maximum warming is projected by all ensembles in Northern Europe in winter, along with a maximum precipitation increase there; in summer, maximum warming occurs in the Mediterranean and Southern European regions associated with a maximum precipitation decrease. The CMIP6 ensemble shows the largest signals, both for temperature and precipitation, along with the largest inter‐model spread. There is a high model consensus across the ensembles on an increase of extreme precipitation and drought frequency in the Mediterranean region. Extreme temperature indices show an increase of heat extremes and a decrease of cold extremes, with CMIP6 showing the highest values and EURO‐CORDEX the finest spatial details. This data set of unprecedented size and quality will provide the basis for impact assessment and climate service activities for the European region.
Key Points
This paper presents the first of this size regional climate model ensemble to investigate and understand the climate change response over the whole of Europe
The paper confirms previous findings for mean and extreme climate change but is able to show the added value information of the high‐resolution regional ensemble
The paper assesses the regional and global model consensus in the projection and presents also the uncertainty of the signal
The use of regional climate model (RCM)‐based projections for providing regional climate information in a research and climate service contexts is currently expanding very fast. This has been ...possible thanks to a considerable effort in developing comprehensive ensembles of RCM projections, especially for Europe, in the EURO‐CORDEX community (Jacob et al., 2014, 2020). As of end of 2019, EURO‐CORDEX has developed a set of 55 historical and scenario projections (RCP8.5) using 8 driving global climate models (GCMs) and 11 RCMs. This article presents the ensemble including its design. We target the analysis to better characterize the quality of the RCMs by providing an evaluation of these RCM simulations over a number of classical climate variables and extreme and impact‐oriented indices for the period 1981–2010. For the main variables, the model simulations generally agree with observations and reanalyses. However, several systematic biases are found as well, with shared responsibilities among RCMs and GCMs: Simulations are overall too cold, too wet, and too windy compared to available observations or reanalyses. Some simulations show strong systematic biases on temperature, others on precipitation or dynamical variables, but none of the models/simulations can be defined as the best or the worst on all criteria. The article aims at supporting a proper use of these simulations within a climate services context.
Plain Language Summary
This study analyses the ability of the unprecedently large ensemble of 55 regional climate simulations to properly simulate the climatology of several variables, extremes, and impact‐oriented indices over the European continent. This analysis should guide the use of regional climate projections in climate services development.
Key Points
Biases of an unprecedentedly large ensemble of 55 European climate simulations using 8 global climate models and 11 regional climate models are assessed
Climate variables, extremes, and impact‐oriented indices are assessed, indicating whether such ensemble can—or cannot—be used in climate service applications
Simulations are generally too wet, too cold and too windy, and the share of contributions to the bias from GCMs and RCMs is found to differ for each variable or index
Abstract 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.
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