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This study uses a state-of-the-art regional climate model (RCM) to examine how tropical deforestation affects the meteorology of the Indian Summer Monsoon (ISM). Incorporating insights from existing research on deforestation by climate scientists, alongside evidence of environmental deterioration in semi-arid, hilly and tropical regions of Southeast Asia, this research seeks to elucidate the critical influence of anthropogenic reasons of climate change on the hydroclimate of ISM. Employing "tropical deforestation" design experiments with the ICTP-RegCMv4.4.5.10 RCM the study evaluates the effects on meteorological parameters including precipitation, circulation patterns and surface parameters. This experimental design entails substituting vegetation type in the land use map of RegCMv4.4.5.10 model, such as deciduous and evergreen trees in Southeast Asia with "short grass" to mimic tropical deforestation. Findings reveal that deforestation induces abnormal anti-cyclonic circulation over eastern India curtails moisture advection, diminishing latent heat flux and moisture transport, leads to a decrease in precipitation compared to control experiment scenario. Alterations in albedo and vegetation roughness length attributable to deforestation impact temperature, humidity, precipitation, consequently exacerbating drought and heatwave occurrences. Additionally, the study also explores deforestation-induced feedback on ISM precipitation variability. The study concludes that deforestation substantially alters land-surface characteristics, water and energy cycle, and atmospheric circulation, thereby influencing regional climate dynamics. These findings offer foundational insights into comprehending land-use and land-cover changes and their implications for climate change adaptation strategies. [ABSTRACT FROM AUTHOR]

The advancement of computational resources has allowed researchers to run convection-permitting regional climate model (CPRCM) simulations. A pioneering effort promoting a multimodel ensemble of such simulations is the CORDEX Flagship Pilot Studies (FPS) on "Convective Phenomena over Europe and the Mediterranean" over an extended Alps region. In this study, the Distribution Added Value metric is used to determine the improvement of the representation of all available FPS hindcast simulations for the daily mean near-surface wind speed. The analysis is performed on normalized empirical probability distributions and considers station observation data as the reference. The use of a normalized metric allows for spatial comparison among the different regions (coast and inland), altitudes and seasons. This approach permits a direct assessment of the added value between the CPRCM simulations against their global driving reanalysis (ERA-Interim) and respective coarser resolution regional model counterparts. In general, the results show that CPRCMs add value to their global driving reanalysis or forcing regional model, due to better-resolved topography or through better representation of ocean-land contrasts. However, the nature and magnitude of the improvement in the wind speed representation vary depending on the model, the season, the altitude, or the region. Among seasons, the improvement is usually larger in summer than winter. CPRCMs generally display gains at low and medium-range altitudes. In addition, despite some shortcomings in comparison to ERA-Interim, which can be attributed to the assimilation of wind observations on the coast, the CPRCMs outperform the coarser regional climate models, both along the coast and inland. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Angola is exceptionally vulnerable to climate change, and sectors such as health, agricultural, water resources and ecosystems may endure severe impacts. Here, an extensive analysis of the signal of climate change on temperature, precipitation, extremes and compound events, for the end of the 21st century, is presented. The analysis is based on a CORDEX-Africa multi-model ensemble at 0.44° resolution built with 19 individual simulations, which allows a robust study of climate change future projections and depict model's uncertainty. For the RCP8.5, the end of the century future warming can reach maxima values ∼ 7 °C for maximum temperature in south-eastern Angola, and 6 °C for minimum temperature. The extreme temperatures (90th percentile) is projected to rise more than 7 °C in southern areas. In general, projections display a rainfall reduction in the drier seasons and a rise in the wet seasons, leading to sharper annual cycles; it is also projected a growth on extreme precipitation (95th percentile), as much as plus ∼ 50 % in some coastal regions. Angola is projected to endure in the future more frequent and longer heatwaves and droughts. In agreement with the RCP8.5, up to 10 heatwaves and more 4 moderate droughts will occur, respectively in coastal and interior areas. Finally, the number of days when a compound of heatwave and moderate drought occurs is projected to growth immensely, around +30 % for many regions, which corresponds to multiply by 10 these events in the future. For the RCP4.5, changes are projected to be smaller but significant in what regards especially extremes and compound events. The magnitude of the projected changes for vulnerable countries as Angola constitute an urgent call for global mitigation and national to regional adaptation strategies, and ultimately to a constant effort of updating and deepen the quality of climate information produced.

The increase in extreme precipitation with global warming (GW) and associated uncertainties are major challenges for climate adaptation. To project future extreme precipitation on different time and intensity scales (return periods [RPs] from 1 to 100 a and durations from 1 h to 3 days), we use a novel convection‐permitting (CP), multi‐global climate model ensemble of COSMO‐CLM regional simulations with a transient projection time (1971–2100) over Germany. We find an added value of the CP scale (2.8 km) with respect to the representation of hourly extreme precipitation intensities compared to the coarser scale with parametrized deep convection (7 km). In general, the return levels (RLs) calculated from the CP simulations are in better agreement with those of the conventional observation‐based risk products for the region for short event durations than for longer durations, where an overestimation by the simulation‐based results was found. A maximum climate change signal of 6–8.5% increase per degree of GW is projected within the CP ensemble, with the largest changes expected for short durations and long RPs. Analysis of the uncertainty in the climate change signal shows a substantial residual standard deviation of a linear approximation, highlighting the need for transient data sets instead of time‐slice experiments to increase confidence in the estimates. Furthermore, the ensemble spread is found to be smallest for intensities of short duration, where changes are expected to be based mainly on thermodynamic contributions. The ensemble spread is larger for long, multi‐day durations, where a stronger dependence on the dynamical component is ascribed. In addition, an increase in spatial variance of the RLs with GW implies a more variable future climate and points to an increasing importance of accounting for uncertainties. [ABSTRACT FROM AUTHOR]

Widespread spatially coherent flood events can cause severe damage and disruption. Climate change has the potential to change the severity and frequency of such events. Despite this, assessment of future fluvial flood risk typically gives little to no consideration to potential changes in the spatial structure of future events. To understand the significance of this gap, climate model simulations are coupled with a national hydrological model to identify event spatially coherent present and future flood events. A statistical Empirical Copula is used to generate a large number of unseen events and linked to a national flood risk simulation model. The research finds that including changes in the spatial structure of flood events materially increases projected changes in risk when compared to conventional approaches based on local uplifts alone; increasing the projected change in Expected Annual Damage across Great Britain by a factor of ~ 1.5. The event-based approach is also shown to provide new insights into the extreme distribution fluvial risk including single event damage, damage seasons, and damage years. The results suggest the 1-in-100-year winter flood may increase from £1.3b to £2.1b, and the 1-in-100 year single event damage may rise from £1.1b today to £1.7b by the 2080s given a 4 °C rise in Global Mean Surface Temperature (assuming current adaptation policies continue and no population growth). Consequently, the findings suggest a much greater emphasis is needed on spatial 'flood events' if future risk is to be understood and adaptation responses appropriately framed. [ABSTRACT FROM AUTHOR]

We have developed a physics ensemble of Weather Research and Forecasting (WRF) model simulations for the Middle East, Mediterranean and North Africa (MEMNA) regions. These simulations use different configurations for the cumulus, microphysics, surface layer, planetary boundary layer, and land surface schemes and are forced by the Community Earth System Model (CESM) General Circulation Model for the historical period 1979-1993. We have also created a complementary ensemble in which the WRF model is fully-coupled to the Regional Ocean Modelling System (ROMS) that simulates the dynamics of the entire Mediterranean Sea. Analysis of our ensembles reveals that the simulated precipitation and near surface temperature (T2) fields in WRF are largely influenced by the cumulus and the land surface schemes during the summer and winter seasons, respectively. The coupling of Weather Research and Forecasting to Regional Ocean Modelling System yields Mediterranean sea surface temperatures that are directly correlated with T2 and have higher spatial resolution than the global model. Meanwhile no significant difference is found between the atmospheric fields from the coupled and uncoupled runs because the Community Earth System Model sea surface temperatures over the Mediterranean, that are used for surface forcing in the uncoupled runs, are already in close agreement with both Regional Ocean Modelling System and observations. We conclude that our high-resolution coupled atmosphere-ocean modelling system is capable of producing climate data of good quality, and we identify those combinations of physics schemes that result in an acceptable level of bias that facilitates their use in future studies. [ABSTRACT FROM AUTHOR]

The exploration of renewable energy such as wind and solar radiation has the potential of reducing reliance on fossil fuels, thus cutting emissions of carbon dioxide, particulate matter, and several other greenhouse gasses. However, recent findings indicate that wind speed across Zambia is very slow, it is increasing but remains unlikely to support large commercial wind farms. In this study, we explore the future impacts of climate change on solar photovoltaic resources. To do this, we examine the new high-resolution (25 km) Coordinated Regional Climate Downscaling Experiment—CORDEX-CORE simulations for the African domain, using two different emission scenarios until 2100. At an annual scale, results indicate a weak but steady decrease in PVRes of around 0.02 W/m2 per annum under RCP2.6 and about 0.005 W/m2 per annum under RCP8.5. Results further show that at an average of ~ 237 ± 3.3 W/m2 and 212 ± 2.5 W/m2, respectively, RCP2.6 comes along with 12 ± 3% more PVRes than RCP8.5. Thus RCP2.6, a greener and climate-friendly pathway, points towards a higher renewable energy potential across Zambia compared to the business-as-usual pathway. [ABSTRACT FROM AUTHOR]

Background: Wildfire simultaneity affects the availability and distribution of resources for fire management: multiple small fires require more resources to fight than one large fire does. Aims: The aim of this study was to project the effects of climate change on simultaneous large wildfires in the Western USA, regionalised by administrative divisions used for wildfire management. Methods: We modelled historical wildfire simultaneity as a function of selected fire indexes using generalised linear models trained on observed climate and fire data from 1984 to 2016. We then applied these models to regional climate model simulations of the 21st century from the NA-CORDEX data archive. Key results: The results project increases in the number of simultaneous 1000+ acre (4+ km2) fires in every part of the Western USA at multiple return periods. These increases are more pronounced at higher levels of simultaneity, especially in the Northern Rockies region, which shows dramatic increases in the recurrence of high return levels. Conclusions: In all regions, the models project a longer season of high simultaneity, with a slightly earlier start and notably later end. These changes would negatively impact the effectiveness of fire response. Implications: Because firefighting decisions about resource distribution, pre-positioning, and suppression strategies consider simultaneity as a factor, these results underscore the importance of potential changes in simultaneity for fire management decision-making. We project future numbers of simultaneous very large wildfires in Western USA based on outputs from climate simulations. In all regions, we project more fires and longer seasons of simultaneity, and years with high simultaneity becoming both more frequent and more extreme. [ABSTRACT FROM AUTHOR]

Colombia is highly vulnerable to climate change which may be intensified due to the climatic effects of regional deforestation. Here, we quantify the impact of historical (1900–2011) land cover changes (LCC) and of global warming during ENSO events (CC) on precipitation, temperature and surface energy balance components by running the Weather Research and Forecasting model WRF v3.9 at 10 km resolution. We find that historical anthropogenic CC causes a mean temperature increase of 0.77 ± 0.02 °C in Colombia, which is more pronounced in high altitudes. Precipitation is enhanced by 0.98 ± 0.30 mm/day (+ 9%), particularly over forested areas and reduced at the Pacific coast. LCC imply a reduction of precipitation particularly above the Andes (− 0.48 ± 0.10 mm/day) and Caribbean Coast (− 0.67 ± 0.12 mm/day), where LCC effects dampen CC effects by 24% and 72%, respectively. La Niña tends to intensify LCC and CC effects in the Andes but dampens them at the Coast, roughly by a factor of two compared to El Niño impacts in both regions. At the subregional level, LCC and CC can have impacts of similar magnitude on precipitation highlighting the need to precisely account for both drivers in hydroclimatic assessments. Contrary to almost all observations and similar simulations with climate models, WRF simulates a cooling bias after historical deforestation in Colombia, even with alternative WRF land surface models. We identify two main sources of biases in the default WRF parametrization to explain this inaccuracy: (1) surface shortwave radiation reflected after deforestation is overestimated; (2) associated evapotranspiration loss is underestimated. Improved model representation and validation of tropical vegetation properties are necessary to provide more robust and confident projections. [ABSTRACT FROM AUTHOR]

The impact of rising greenhouse gases (GHGs) in the atmosphere on the temperature distributions is felt not only in the mean values but primarily in the extremes. The temperature distributions are becoming slightly flattened and more broadened towards higher values, leading to a decrease in extreme cold events and more importantly to a considerable increase in the frequency and intensity of extreme hot events. These changes are no longer simple projections but are already occurring. It is thus imperative an assessment of the projected changes even under reduced emissions scenarios for the entire 21st century. In this study, a multi-variable ensemble based on 13 EURO-CORDEX high-resolution simulations at 0.11° resolution, was used to analyse the extreme heat events as well as the Universal Thermal Climate Index (UTCI) for such extremes between March and November over Portugal. The 13 simulations have in common three Representative Concentration Pathways (RCP), RCP2.6, RCP4.5 and RCP8.5 as well as data covering a historical period (1971–2000) and three future consecutive periods, 2011–2040, 2041–2070 and 2071–2 100. The results show that severe future heatwaves will develop beyond the extended summer months in all scenarios. Even under a high mitigation scenario (RCP2.6), the number of heatwaves will more than double in number, relative to the historical record. In the high emission scenario (RCP8.5), a sharp increase in the number, severity and areal extension of heatwaves is projected for the end of the 21st century. The analysis of the heat stress indicates that most of the projected future heatwaves will induce heat stress and the projected increase in areal extension and the number of occurrences will have an impact on morbidity and mortality rates simply due to the shear rise in the number of the affected population and the increased frequency of occurrence.

A multi-scenario, multi-model ensemble of simulations from regional climate models is outlined to provide the core data source for a set of climate projections and a climate change service. A subset of realisations from CMIP6 Global Climate Models (GCMs) are selected for downscaling by Regional Climate Models (RCMs) under a ‘sparse matrix’ framework using the CORDEX guidelines for Shared Socio-economic Pathways that feature low emissions (SSP1-2.6) and high emissions (SSP3-7.0). The subset excludes poor performing models, with performance assessed by the climatology over a large Indo-Pacific domain and an Australian-specific domain, the simulation of atmospheric circulation and teleconnections to major drivers, then incorporating other evaluation from the literature. The models are selected to be relatively independent by simply choosing one model from each ‘family’ where possible. The projected change in temperature and rainfall in climatic regions of Australia in the selected models are broadly representative of that from the whole CMIP6 ensemble, after deliberately treating models with very high climate sensitivity separately. A limited but carefully constructed ensemble will not represent statistically balanced estimates but can be used effectively under a ‘storylines’ style approach and can maximise representativeness within limits. The resulting ensemble can be used as a key data source for the future climate component of climate services in Australia. The ensemble will be used in conjunction with CMIP6 and large ensembles of GCM simulations as important context, and targeted ‘convective permitting resolution’ modelling, deep learning models and emulators for added insights to inform climate change planning in Australia.

High-quality climate information at appropriate spatial and temporal resolution is essential to develop and provide tailored climate services for Africa. A common method to produce regional climate change data is to dynamically downscale global climate projections by means of regional climate models (RCMs). Deficiencies in the representation of the sea surface temperatures (SSTs) in earth system models (ESMs) and missing atmosphere–ocean interactions in RCMs contribute to the precipitation bias. This study analyzes the influence of the regional atmosphere–ocean coupling on simulated precipitation and its characteristics over Africa, and identifies those regions providing an added value using the regionally coupled atmosphere–ocean model ROM. For the analysis, the MPI-ESM-LR historical simulation and emission scenario RCP8.5 were dynamically downscaled with ROM at a spatial resolution of 0.22° × 0.22° for the whole African continent, including the tropical Atlantic and the Southwest Indian Ocean. The results show that reduced SST warm biases in both oceans lead to more realistic simulated precipitation over most coastal regions of Sub-Saharan Africa and over southern Africa to varying degrees depending on the season. In particular, the annual precipitation cycles over the coastal regions of the Atlantic Ocean are closer to observations. Moreover, total precipitation and extreme precipitation indices in the coupled historical simulation are significantly lower and more realistic compared to observations over the majority of the analyzed sub-regions. Finally, atmosphere–ocean coupling can amplify or attenuate climate change signals from precipitation indices or even change their sign in a regional climate projection. [ABSTRACT FROM AUTHOR]

In the context of the CORDEX project, an ensemble of regional climate simulations (RCMs) of high resolution on a 0.11° grid has been generated for Europe with the objective of improving the representation of regional to local‐scale atmospheric phenomena. However, such simulations are computationally expensive and do not always reveal added value. Here, a recently proposed metric (the distribution added value [DAV]) is used to determine the added value of all available EURO‐CORDEX high‐resolution simulations at 0.11° for daily mean wind speed compared to their respective coarser‐gridded 0.44° counterparts and their driving fields, hindcast and historical experiments. The analysis consists in comparing the degree of similarity between normalized wind probability density function (PDF) of simulations and observations. In addition, the use of a normalized PDF allows for a direct spatial comparison among the different regions and time periods. Results show that RCMs add value to their reanalysis or forcing global model, but the nature and magnitude of the improvement on the representation of wind speed may vary depending on the model, region and season. We found most RCMS at 0.11° to outperform models at the 0.44° resolution in terms of their quality in capturing the measured wind speed PDF. When looking at the upper tail of the wind speed PDF, the benefits of downscaling are generally larger. At the regional scale, added value is obtained for 0.11° with respect to 0.44° resolution for all subdomains studied, particularly over the Mediterranean, the Iberian Peninsula and the Alps. When analysing the added value dependence on altitude, runs at 0.11° models represent better the locations below 50 m and above 350 m of altitude, and the 0.44° increasingly under‐perform for higher altitudes. Overall, DAV are larger at 0.11° than at 0.44° resolution, due to a better performance of local‐scale feedbacks at high resolution. [ABSTRACT FROM AUTHOR]

In this study, we estimated near‐surface wind speed 100‐year return values over the southwestern South Atlantic Ocean, using present‐day (1979–2018) simulations from the regional climate models (RCMs) WRF and RegCM4. Extreme wind events, associated with hazardous conditions over coastal and oceanic areas, must be well represented in numerical models for risk assessment, and few studies focused on the added value offered by RCMs to wind extremes. Events were selected with the peaks‐over‐threshold method and extremes were calculated by fitting peaks to a generalized Pareto distribution. For the assessment of model performance, we used the satellite‐based dataset from the Cross‐Calibrated Multi Platform (CCMP), which has great agreement with in situ observations. While modern reanalysis underestimated higher wind speed quantiles, the CCMP was able to represent these quantiles. Dynamical downscaling with the WRF (RegCM4) indicates an underestimation (overestimation) of wind speed for upper quantiles. To mitigate the effects of these differences in the extreme value estimate, we applied a linear adjustment in the simulated wind speed using the CCMP as reference. This application reduced the bias for higher wind speeds in simulations for all regions, except over the coastal area near Argentina and Uruguay, where downscaling already realistically represents extreme events. The spatial distribution of the simulated extremes is compatible with previous results based on reanalysis and satellite data, although with finer‐scale structure, especially over the southern South Atlantic, a region frequently affected by cyclone occurrence and extreme near‐surface winds. The extreme wind speed maps estimated for 100 years reflect these conditions with values reaching around 30 m·s−1 in the area, even after the wind adjustment. Besides, the fine‐scale features aggregate important new information related to extreme winds in the region, which is a relevant added value in the study of return values estimates. [ABSTRACT FROM AUTHOR]

Regional and local wind systems are often complex, particularly near coastal areas with a highly variable orography. Thus, the realistic representation of regional wind systems in weather and climate models is of strong relevance. Here, we evaluate the ability of a 13‐year convection‐permitting climate simulation in reproducing the interaction of several regional summer wind systems over the complex orography in the eastern Mediterranean region. The COSMO‐CLM simulations are driven by hourly ERA‐5 reanalysis and have a spatial resolution of 2.8 and 7.0 km. The simulated near‐surface wind fields are compared with unique very high‐resolution wind observations collected within the "Dead Sea Research Venue" project (DESERVE) and data from the Israel Meteorological Service synop network. The high‐resolution COSMO‐CLM simulations largely reproduce the main characteristics of the regional wind systems (Mediterranean and Dead Sea breeze, slope winds in the Judean Mountains and winds along the Jordan Rift valley), whereas ERA‐5 is only able to represent the Mediterranean Sea breeze. The high‐resolution simulations substantially improve the representation of regional winds, particularly over complex orography. Indeed, the 2.8 km simulation outperforms the 7.0 km run, on 88% of the days. Two mid‐July 2015 case studies show that only the 2.8 simulation can realistically simulate the penetration of the Mediterranean Sea Breeze into the Jordan Rift valley and complex interactions with other wind systems like the Dead Sea breeze. Our results may have profound implications for regional weather and climate prediction since very high‐resolution information seems to be necessary to reproduce the main summertime climatic features in this region. We envisage that such simulations may also be required at other regions with complex orography. [ABSTRACT FROM AUTHOR]

Renewable energy development is growing fast and is expected to expand in the next decades in West Africa as a contribution to addressing the power demand and climate change mitigation. However, the future impacts of climate change on solar PV and the wind energy potential in the region are still unclear. This study investigates the expected future impacts of climate change on solar PV and wind energy potential over West Africa using an ensemble of three regional climate models (RCMs). Each RCM is driven by three global climate models (GCMs) from the new coordinated high-resolution output for regional evaluations (CORDEX-CORE) under the RCP8.5 scenario. Two projection periods were used: the near future (2021–2050) and the far future (2071–2100). For the model evaluation, reanalysis data from ERA5 and satellite-based climate data (SARAH-2) were used. The models and their ensemble mean (hereafter Mean) show acceptable performance for the simulations of the solar PV potential, the wind power density, and related variables with some biases. The Mean predicts a general decrease in the solar PV potential over the region of about −2% in the near future and −4% in the far future. The wind power density (WPD) is expected to increase by about 20% in the near future and 40% in the far future. The changes for solar PV potential seem to be consistent, although the intensity differs according to the RCM used. For the WPD, there are some discrepancies among the RCMs in terms of intensity and direction. This study can guide governments and policymakers in decision making for future solar and wind energy projects in the region. [ABSTRACT FROM AUTHOR]

Rainfall is considered the most important physical process for landslide triggering in Portugal. It is expected that changes in the precipitation regimes in the region, as a direct consequence of climate change, will have influence in the occurrence of extreme rainfall events that will be more frequently, throughout the century. The aim of this study relied on the assessment of the projected future changes in the extreme precipitation over Portugal mainland and quantifying the correlation between extreme rainfall events and landslide events through Rainfall Triggering Thresholds (RTTs). This methodology was applied for two specific locations within two Portuguese areas of great geomorphological interest. To analyze the past frequency of landslide events, we resorted to the DISASTER database. To evaluate the possible projected changes in the extreme precipitation, we used the Iberia02 dataset and the EURO-CORDEX models' runs at a 0.11° spatial resolution. It was analyzed the models' performance to simulate extreme values in the precipitation series. The simulated precipitation relied on RCM-GCM models' runs, from EURO-CORDEX, and a multimodel ensemble mean. The extreme precipitation assessment relied on the values associated to the highest percentiles, and to the values associated to the RTTs' percentiles. To evaluate the possible future changes of the precipitation series, both at the most representative percentiles and RTTs' percentiles, a comparison was made between the simulated values from EURO-CORDEX historical runs (1971–2000) and the simulated values from EURO-CORDEX future runs (2071–2100), considering two concentration scenarios: RCP 4.5 and RCP 8.5. In the models' performance, the multimodel ensemble mean appeared to be within the best representing models. As for the projected changes in the extreme precipitation for the end of the century, when following the RCP 4.5 scenario, most models projected an increase in the extreme values, whereas, when following the RCP 8.5 scenario, most models projected a decrease in the extreme values. [ABSTRACT FROM AUTHOR]

Late Marine Isotope Stage (MIS) 3 and MIS 2 loess–palaeosol sequences in Western Europe comprise alternating loess layer and 3‐ to 30‐cm‐thick bleached soil horizons with Fe–Mn oxide precipitations, which are usually interpreted as waterlogged active layers and referred to as 'tundra gleys'. Active layer thickness data derived from a regional climate model simulation and the fossils (shells, earthworm granules) found in 'tundra gleys' argue against such an assumption. Most of these horizons better correspond to Fe‐depleted, slightly humic topsoil horizons or subsurface eluvial horizons and should be referred to as (incipient) Ag or Eg horizons. They formed during climate ameliorations associated with vegetation (cryptogams, herbs) development, possibly limited by long‐lasting snow cover. Strong mixing usually occurred in these horizons due to the activity of anecic earthworms and frost activity. [ABSTRACT FROM AUTHOR]

Australia experiences a variety of climate extremes that result in loss of life and economic and environmental damage. This paper provides a first evaluation of the performance of state-of-the-art Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models (GCMs) in simulating climate extremes over Australia. Here, we evaluate how well 37 individual CMIP6 GCMs simulate the spatiotemporal patterns of 12 climate extremes over Australia by comparing the GCMs against gridded observations (Australian Gridded Climate Dataset). This evaluation is crucial for informing, interpreting, and constructing multimodel ensemble future projections of climate extremes over Australia, climate-resilience planning, and GCM selection while conducting exercises like dynamical downscaling via GCMs. We find that temperature extremes (maximum-maximum temperature -TXx, number of summer days -SU, and number of days when maximum temperature is greater than 35 °C -Txge35) are reasonably well-simulated in comparison to precipitation extremes. However, GCMs tend to overestimate (underestimate) minimum (maximum) temperature extremes. GCMs also typically struggle to capture both extremely dry (consecutive dry days -CDD) and wet (99th percentile of precipitation -R99p) precipitation extremes, thus highlighting the underlying uncertainty of GCMs in capturing regional drought and flood conditions. Typically for both precipitation and temperature extremes, UKESM1-0-LL, FGOALS-g3, and GCMs from Met office Hadley Centre (HadGEM3-GC31-MM and HadGEM3-GC31-LL) and NOAA (GFDL-ESM4 and GFDL-CM4) consistently tend to show good performance. Our results also show that GCMs from the same modelling group and GCMs sharing key modelling components tend to have similar biases and thus are not highly independent. [ABSTRACT FROM AUTHOR]

Projected changes to the El Niño Southern Oscillation (ENSO) climate mode have been explored using global Earth system models (ESMs). Regional expressions of such changes have yet to be fully advanced and may require the use of regional downscaling. Here, we employ regional climate modeling (RCM) using the Weather Research and Forecasting (WRF) model at convection-permitting resolution and nested in output from the HadGEM2 ESM. We quantify ENSO teleconnections to temperature and precipitation anomalies in historical and future climate scenarios over eastern North America. Two paired simulations are run, a strong El Niño (positive ENSO phase) and a weak La Niña (negative ENSO phase), for the historical and future years. The HadGEM2 direct output and HadGEM2-WRF simulation output are compared to the anomalies derived from the NOAA ENSO Climate Normals dataset. The near-surface temperature and precipitation differences by ENSO phase, as represented by the HadGEM2-WRF historical simulations, show a poor degree of association with the NOAA ENSO Climate Normals, in part because of the large biases in the HadGEM2 model. Downscaling with the WRF model does improve the agreement with the observations, and large discrepancies remain. The model chain HadGEM2-WRF reverses the sign of the ENSO phase response over eastern North America under simulations of the future climate with high greenhouse gas forcing, but due to the poor agreement with the NOAA ENSO Climate Normals it is difficult to assign confidence to this prediction. [ABSTRACT FROM AUTHOR]

The abundant surface solar radiation (SSR) over South‐West Indian Ocean (SWIO) presents significant temporal variability. To characterize this temporal variability is important for the application of solar energy, such as photovoltaic industry. This article studied the intraseasonal and synoptic climate variability of SSR by regional climate modelling over SWIO region. The regional climate model, RegCM4's skill is first evaluated through analysing the seasonal mean SSR with the precipitation, near surface temperature and total cloud cover in austral summer and winter. The basic validation of those simulated parameters with the reference data showed model's performance on SSR. The austral summer (November–February) 1999–2008 was chosen to search the Madden–Julian Oscillation patterns and tropical temperate troughs which are the major expression of intraseasonal and synoptic climate variability. The circulation, moisture fluxes, and radiation fluxes have been checked at the beginning for RegCM4's input dataset (ERA‐Interim) to find the signals. Then, the output simulation results were taking into account to see if the model can reproduce the intraseasonal and synoptic climate variability or not. SSR from SARAH‐E (CM SAF@5 km) as the reference dataset in the end has been used to validate the simulated patterns, which showed that the eastward SSR anomalies propagation and negative SSR anomalies bands can be observed in RegCM4 and the according satellite dataset. These results identified and explained SSR's intraseasonal and synoptic climate variability over SWIO region, which provide a way through RegCM to perform SSR's evaluation and prediction. [ABSTRACT FROM AUTHOR]

Regional climate simulations with high horizontal resolutions are becoming increasingly common and although model development has continually enhanced the representation of atmospheric phenomena, the model improvements are variable, region and time scale‐dependant. The high computational costs of increasingly smaller grid‐spacing underline the need for a robust assessment of the benefits or losses associated to the dynamical downscaling of coarser resolution models (reanalysis, global climate models or ~tenths km runs), that is, quantitative added value evaluation. In the current study, a probability density function (PDF) matching score is used to determine the distribution added value (DAV) of the EURO‐CORDEX maximum and minimum temperatures from the hindcast simulations at 0.44° and 0.11° resolutions. The gridded maximum and minimum temperatures from European Climate Assessment & Dataset (E‐Obs) were used as benchmarks for the matching scores and DAVs were determined for the 0.44° and 0.11° simulations individually against ERA‐Interim as well as against each other. Temperature added value against ERA‐Interim is difficult to find due to the assimilation of surface temperatures in the reanalysis. Nonetheless, there is positive added value in Tmax for half of the models at the yearly time scale, and the increase in resolution also implies positive DAV in half of the models, with DAVs between 0.1 and 3.8%. More importantly, the benefits of downscaling are significantly visible in the extreme end tail of Tmax, where all models have high added value at all resolutions and seasons except in summer (from ~1 to ~21%). In minimum temperature there is added value in winter and autumn at both resolutions. The Mediterranean and the British Isles are the regions where larger positive DAV values for both variables and resolutions are identified. In Tmax, added value is also associated to the increase in resolution (from 50 to 10 km) for half of the models in all regions. Scandinavia, the Alps, and eastern Europe are regions where negative added value is clearly linked with the highest mountain peaks for both variables. [ABSTRACT FROM AUTHOR]

Regional climate simulations from the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment – Southeast Asia (SEA) indicated model biases in temperature and rainfall over SEA. Given the influence of sea surface temperature (SST) variability on SEA climate, this study examines SST representation in climate models to investigate its potential contribution to the resulting model biases over the Philippines. Observed SST over SEA is first characterized by its spatial patterns and temporal variability. An analysis of the SST representation over SEA and its potential influence on modelled climate over the Philippines in Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCMs) is then conducted, followed by an assessment of the potential influence of SST representation in CMIP5 GCMs on downscaled regional climate output. Our results show that GCMs with well represented SSTs (i.e., low bias, well captured variability, and pattern) can produce climate simulations well over the Philippines. Whether or not the GCMs with poor SST representation can perform well is inconclusive. During boreal winter (summer), climate variables with high (low) spatial correlation with model SST get poor (better) spatial correlation with observed climate. Over west of the Philippines, where model SST seasonal variability is captured well, models also adequately simulate climate variables. Results suggest that the negative temperature biases, and positive precipitation and wind speed biases, in both GCMs and downscaled simulations, are associated with negative model SST biases. These findings give a better understanding on how SST potentially influences modelled climatology over the Philippines. [ABSTRACT FROM AUTHOR]

Two 11‐year simulations were conducted to investigate the influence of two runoff schemes in the community land model version 4.5 (CLM45) on the Amazon surface energy balance and surface climate using a high‐resolution regional climate model (RegCM4‐CLM45). The default scheme is TOPMODEL (TOP), while the alternative is Variable Infiltration Capacity (VIC). In the two simulations, the vegetation status is prescribed (satellite phenology; SP). The first simulation was designated as SP‐TOP, while the second simulation was referred to as SP‐VIC, and both of them were evaluated using reanalysis products (e.g., ERA5) and micrometeorology data measurements. Results show that the SP‐VIC severely underestimates latent heat and overestimates sensible heat fluxes, more than SP‐TOP in comparison with the ERA5. This explains the large warm bias observed in the winter season. On the other hand, the SP‐VIC shows a slightly smaller dry bias than SP‐TOP against the Climate Research Unit (CRU) data. Our results show that SP‐VIC does not improve the quality of the simulation compared to SP‐TOP, which suggests the necessity of additional calibration of the VIC surface parameters using in situ observations of the Amazon and revising the VIC runoff scheme to perform new sensitivity experiments. The same needs to be done with SP‐TOP. [ABSTRACT FROM AUTHOR]

Precipitation patterns are expected to change in the future climate, affecting humans through a number of factors. Global climate models (GCM) are our best tools for projecting large-scale changes in climate, but they cannot make reliable projections locally. To abate this problem, we have downscaled three GCMs with the Weather Research and Forecasting (WRF) model to 50 km horizontal resolution over South America, and 10 km resolution for central Chile, Peru and southern Brazil. Historical simulations for years 1996–2005 generally compare well to precipitation observations and reanalyses. Future simulations for central Chile show reductions in annual precipitation and increases in the number of dry days at the end-of-the-century for a high greenhouse gas emission scenario, regardless of resolution and GCM boundary conditions used. However, future projections for Peru and southern Brazil are more uncertain, and simulations show that increasing the model resolution can switch the sign of precipitation projections. Differences in future precipitation changes between global/regional and high resolution (10 km) are only mildly influenced by the orography resolution, but linked to the convection parameterization, reflected in very different changes in dry static energy flux divergence, vertical velocity and boundary layer height. Our findings imply that using results directly from GCMs, and even from coarse-resolution (50 km) regional models, may give incorrect conclusions about regional-scale precipitation projections. While climate modelling at convection-permitting scales is computationally costly, we show that coarse-resolution regional simulations using a scale-aware convection parameterization, instead of a more conventional scheme, better mirror fine-resolution precipitation projections. [ABSTRACT FROM AUTHOR]

The Canary current upwelling is one of the major eastern boundary coastal upwelling systems in the world, bearing a high productive ecosystem and commercially important fisheries. The Canary current upwelling system (CCUS) has a large latitudinal extension, usually divided into upwelling zones with different characteristics. Eddies, filaments and other mesoscale processes are known to have an impact in the upwelling productivity, thus for a proper representation of the CCUS and high horizontal resolution are required. Here we assess the CCUS present climate in the atmosphere–ocean regionally coupled model. The regional coupled model presents a global oceanic component with increased horizontal resolution along the northwestern African coast, and its performance over the CCUS is assessed against relevant reanalysis data sets and compared with an ensemble of global climate models (GCMs) and an ensemble of atmosphere-only regional climate models (RCMs) in order to assess the role of the horizontal resolution. The coupled system reproduces the larger scale pattern of the CCUS and its latitudinal and seasonal variability over the coastal band, improving the GCMs outputs. Moreover, it shows a performance comparable to the ensemble of RCMs in representing the coastal wind stress and near-surface air temperature fields, showing the impact of the higher resolution and coupling for CCUS climate modelling. The model is able of properly reproducing mesoscale structures, being able to simulate the upwelling filaments events off Cape Ghir, which are not well represented in most of GCMs. Our results stress the ability of the regionally coupled model to reproduce the larger scale as well as mesoscale processes over the CCUS, opening the possibility to evaluate the climate change signal there with increased confidence. [ABSTRACT FROM AUTHOR]

Extreme weather events represent one of the most visible and immediate hazards to society. Many of these types of phenomena are projected to increase in intensity, duration or frequency as the climate warms. Of these extreme winds are among the most damaging historically over Europe yet assessments of their future changes remain fraught with uncertainty. This uncertainty arises due to both the rare nature of extreme wind events and the fact that most model are unable to faithfully represent them. Here we take advantage of a 15 member ensemble of high resolution Euro-CORDEX simulations (∼12 km) and investigate projected changes in extreme winds using a peaks-over-threshold approach. Additionally we show that – despite lingering model deficiencies and inadequate observational coverage – there is clear added value of the higher resolution simulations over coarser resolution counterparts. Further, the spatial heterogeneity and highly localised nature is well captured. Effects such as orographic interactions, drag due to urban areas, and even individual storm tracks over the oceans are clearly visible. As such future changes also exhibit strong spatial heterogeneity. These results emphasise the need for careful case-by-case treatment of extreme wind analysis, especially when done in a climate adaptation or decision making context. However, for more general assessments the picture is more clear with increases in the return period (i.e. more frequent) extreme episodes projected for Northern, Central and Southern Europe throughout the 21st century. While models continue to improve in their representation of extreme winds, improved observational coverage is desperately needed to obtain more robust assessments of extreme winds over Europe and elsewhere.

Climate extremes affected cities and their populations during the last decades. Future climate projections indicate climate extremes will increasingly impact urban areas during the 21st century. Humidity related fluctuations and extremes directly underpin convective processes, as well as can influence human health conditions. Regional climate models are a powerful tool to understand regional-to-local climate change processes for cities and their surroundings. Convection-permitting regional climate models, operating on very high resolutions, indicate improved simulation of convective extremes, particularly on sub-daily timescales and in regions with complex terrain such as cities. This research aims to understand how crossing spatial resolutions from ~12.5 km to ~3 km grid size affect humidity extremes and related variables under future climate change for urban areas and its surroundings. Taking Berlin and its surroundings as the case study area, the research identifies two categories of unprecedented future extreme atmospheric humidity conditions happening under 1.5 °C and 2.0 °C mean warming based on statistical distributions, respectively near surface specific humidity >0.02 kg/kg and near surface relative humidity

We investigate the glacial climate conditions in the southeastern Carpathian Basin (Vojvodina, Serbia) based on the reconstruction of malacological palaeotemperatures and results from a high‐resolution regional climate simulation. Land snail assemblages from eight loess profiles are used to reconstruct July temperatures during the Last Glacial Maximum (LGM). The malacological reconstructed temperatures are in good agreement with the simulated LGM July temperatures by the Weather Research and Forecast model. Both methods indicate increasing temperatures from the northwestern towards the southeastern parts of the study area. LGM aridity indices calculated based on the regional climate model data suggest more arid conditions in the southeastern parts compared with more humid conditions in the northwestern parts. However, for present‐day conditions, the moisture gradient is reversed, exhibiting more humid (arid) conditions in the southeast (northwest). An explanation for the reversed LGM aridity pattern is provided by an analysis of the prevailing wind directions over the South Banat district (Serbia). The prevailing moist northwesterly winds during summer are not able to compensate for the annual lack of moisture induced by the dry winds from the southeast that are more frequent during the LGM for the other seasons. [ABSTRACT FROM AUTHOR]

Extratropical cyclones of type Vb develop over the western Mediterranean and move north-eastward, leading to heavy precipitation over central Europe and posing a major natural hazard. Thus, this study aims at assessing their sensitivity to climate change and deepens the understanding of the underlying processes of Vb-type cyclones. The analysis is based on global climate model output, which is dynamically downscaled for extreme Vb cyclones. Thereby two periods are compared: the reference period 1979 to 2013, and the future period 2070 to 2099 under the representative concentration pathway RCP8.5. Additionally, we include the analysis from a large ensemble (LENS), where 25 ensemble members are analysed for the reference period 1990–2005 and the future period 2071–2080. The results show a reduction of Vb cyclones from 3.2 events per year during the reference period to only 2.1 Vb cyclones per year at the end of the 21st century. This result is supported by the LENS, which shows a significant reduction from 2.9 to 2.6 Vb events per year. This reduction is induced by a northward shift of cyclone track over Europe in the future. To gain insight into the impact of Vb cyclones, 10 Vb cyclones with the most intense precipitation over the Alps are selected and dynamically downscaled for each period, separately. Although the overall precipitation in the innermost domain stays the same in the two periods, results indicate that future Vb events tend to affect more strongly the eastern coasts of the Mediterranean Sea, while the impact in the Alpine region becomes slightly ameliorated compared to the current conditions. Furthermore, the dynamical downscaling exhibits an increased temperature contrast between the Mediterranean Sea and the European land for these 10 events in future. This contrast leads to a higher instability at coastal areas and thus explains the changed precipitation pattern.

Study region: Pra River Basin (PRB) located in Ghana Study focus: Now, hydrological and climate change impact studies are shifting towards reliance on openly accessible databases particularly for regions with limited observed datasets. There is therefore the need to evaluate the reliability of such datasets in order to reduce modelling uncertainties and boost confidence in modelling results. We present an evaluation of the performance of nine CORDEX RCA4 Regional Climate Model simulations in replicating the observed precipitation for a 31-year period (1975–2005). New hydrological insights for the region: On the annual timescale, CanESM2, IPSL, CNRM-CM5 and HadGEM2-ES reproduced minimal annual mean biases (0.8–18.4 %) and thus selected for the seasonal and monthly timescale analysis. Generally, with the exception of spring (March, April and May), all the selected models were able to simulate quite well the seasonal climatology of the Pra River Basin (PRB) with noticeable distinctions in the reproducibility of the spatial patterns, variability and magnitude of the observed data. The multi-model ensemble means indicated strong correlation with observations (r > 0.75) but with weak spatial variability (σ < 0.25). It is recommended that for climate impact assessment and hydrologic modelling studies, multi-model ensembles of CanESM2, IPSL, CNRM-CM5 and HadGEM2-ES be used. However, on singular basis, the CanESM2 and HadGEM2-ES RCA4 simulation outputs present better representation of the climate of the basin.

Climate models in the past decades have been developed to such an extent to include atmospheric chemistry as part of their climate simulations. This is necessary for providing policy-makers and other stakeholders with reliable atmospheric projections as well as information about changes in chemical species as a consequence of climate change. The regional climate model (RCM), RegCM4 is a community model which contains only one gas-phase mechanism module (CBM-Z) that includes the formation, deposition, and transport of a number of volatile organic compounds (VOCs). In this paper, the CB6-C, a new gas-phase mechanism module, is combined with RegCM4 to produce a larger suite of VOCs and chemical mechanisms for important anthropogenic and biogenic species, most notably benzene, terpenes, acetylene and their corresponding oxidation products. In order to evaluate this new module, climatologies of the CB6-C and CBM-Z simulations are compared to gridded and station data. The results reveal the two schemes to be similar with some improvement of surface carbon monoxide and tropospheric ozone in the CB6-C. However, organic products were found to be under-predicted for both schemes, suggesting the need of more development in the implementation of atmospheric chemistry in RegCM4. Despite its limitations, the input conditions (emissions and boundary conditions) are easy to modify, making the new gas-phase scheme an important advancement in the modelling of atmospheric chemistry within a RCM, as it provides a pathway for new research that may eventually help health studies. [ABSTRACT FROM AUTHOR]

The role of vegetation-runoff system—in simulating the tropical African climate—was examined by analysing two 13-year simulations with two runoff schemes of the community land model version 4.5 (CLM45): the default one is TOPMODEL (TOP) and the other one is the Variable Infiltration Capacity (VIC) using a regional climate model (RegCM4-CLM45). In both simulations, the carbon-nitrogen (CN) module was activated. The first simulation was referred to as CN-TOP, while the second one was designated as CN-VIC. Overall, the results showed that the CN-VIC severely decreases the leaf area index (LAI), vegetation transpiration and soil evaporation relative to the CN-TOP. Eventually, it severely underestimates the total evapotranspiration but overestimates the sensible heat flux in comparison with the reanalysis product; meanwhile the CN-TOP opposes this effect. As a result, the CN-TOP shows a strong cold bias, and the CN-VIC shows a slightly warm bias in comparison with the observation. Moreover, enabling the interactive vegetation module leads to intensifying the dry bias of the total surface precipitation in both simulations with respect to the static vegetation case against the reanalysis product; however the CN-VIC still outperforms the CN-TOP in comparison with the observations. In conclusion, the coupled vegetation-runoff system has a strong influence on the tropical African climate relative to the static case, and calibrating the four parameters of the VIC surface dataset ensures a better and more reliable performance of the coupled RegCM4-CLM45-CN-VIC model for simulating the tropical African climate. [ABSTRACT FROM AUTHOR]

In this study, a subset of the downscaled simulations of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment—Southeast Asia (SEACLID/CORDEX‐SEA) was analysed to examine the representation of tropical cyclone (TC) climatology over Southeast Asia, in terms of pattern, intensity, frequency, and lifetime. A modified vortex tracking algorithm is used to detect TCs over the SEACLID/CORDEX‐SEA domain in the historical simulations from 1986 to 2005. Sensitivity tests for the detection method criteria, including vorticity, outer core wind strength, sea level pressure anomaly, and temperature anomaly at 300, 500, 700, and 850 hPa, were conducted to determine the optimum threshold configuration for each SEACLID/CORDEX‐SEA simulation used in the study. Comparison with the best track data of the Joint Typhoon Warning Center showed that model simulations underestimated the total number of TCs east of the Philippines for the 1986–2005 period but captured the annual cycle of the total number of TCs. This underestimation of TCs is possibly due to the domain used, which does not extend further east to cover most of the TC genesis area in the Western North Pacific. The structure of a typical TC from the regional climate model simulation is comparable to observed TC structure. However, results indicate that the resolution of the simulations is still not sufficient to capture the fine details of the observed TC structure, which could explain in part the lower intensification rate of TCs in the model output. [ABSTRACT FROM AUTHOR]

Climatology has increasingly become an important discipline for understanding tourism and recreation, especially in the era of contemporary climate change. Climate indices, in this respect, have been useful tools to yield the climatic attractiveness of tourism destinations as well as in understanding their altering suitability to various tourism types along with the changing climates. In this study, a major gap for a comprehensive climate index tailored for ski tourism is aimed to be fulfilled. For this purpose, initially the Ski Climate Index (SCI) is specified, based on fuzzy logic and as informed by literature and through extensive co-creation with the ski tourism industry experts, and applied to an emerging destination, Turkey, based on regional climate modeling projections. The index is designed as a combination of snow reliability and aesthetics and comfort facets, the latter of which includes sunshine, wind, and thermal comfort conditions. Results show that the Eastern Anatolia region is climatically the most suitable area for future development, taking account of the overriding effects of natural and technical snow reliability. Future research suggestions include the incorporation of more components into the index as well as technical recommendations to improve its application and validation. [ABSTRACT FROM AUTHOR]

Climate projections at very high resolution (kilometre-scale grid spacing) are becoming affordable. These 'convection-permitting' models (CPMs), commonly used for weather forecasting, better represent land-surface characteristics and small-scale processes in the atmosphere such as convection. They provide a step change in our understanding of future changes at local scales and for extreme weather events. For short-duration precipitation extremes, this includes capturing local storm feedbacks, which may modify future increases. Despite the major advance CPMs offer, there are still key challenges and outstanding science issues. Heavy rainfall tends to be too intense; there are challenges in representing land-surface processes; sub-kilometre scale processes still need to be parametrized, with existing parametrization schemes often requiring development for use in CPMs; CPMs rely on the quality of lateral boundary forcing and typically do not include ocean-coupling; large CPM ensembles that comprehensively sample future uncertainties are costly. Significant progress is expected over the next few years: scale-aware schemes may improve the representation of unresolved convective updrafts; work is underway to improve the modelling of complex land-surface fluxes; CPM ensemble experiments are underway and methods to synthesize this information with larger coarser-resolution model ensembles will lead to local-scale predictions with more comprehensive uncertainty context for user application. Large-domain (continental or tropics-wide) CPM climate simulations, potentially with additional earth-system processes such as ocean and wave coupling and terrestrial hydrology, are an exciting prospect, allowing not just improved representation of local processes but also of remote teleconnections. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'. [ABSTRACT FROM AUTHOR]

In the last decades, offshore wind harvesting has increased enormously, and is seen as a renewable energy resource with great potential in many regions of the world. Therefore, it is crucial to understand how this resource will evolve in a warming climate. In the present study, offshore wind resource in the Southwestern African region is analysed for the present and future climates. A ROM (REMO-OASIS-MPIOM) climate simulation in uncoupled and coupled atmosphere–ocean mode, at 25 km horizontal resolution, and a multi-model ensemble built with a set of regional climate models from the CORDEX-Africa experiment at 0.44° resolution were used. The projected changes of the offshore wind energy density throughout the twenty-first century are examined following the RCP4.5 and RCP8.5 greenhouse gas emissions scenarios. Characterised by strong coastal-parallel winds, the Southwestern African offshore region shows high values of wind energy density at 100 m, up to 1500 Wm−2 near the coast, particularly offshore Namibia and west South Africa. Conversely, along Angola's coast the available offshore wind energy density is lower. Throughout the twenty-first century, for the weaker climate mitigation scenario (RCP8.5), an increase of the offshore wind resource is projected to occur along Namibia and South African western coasts, more pronounced at the end of the century (+ 24%), while a decrease is projected along Angola's coasts, reaching a negative anomaly of about − 32%. Smaller changes but with the same pattern are projected for the stronger climate mitigation scenario (RCP4.5). The future deployment of offshore floating hub turbines placed at higher heights may allow higher production of energy in this region. Along offshore Namibia and west South Africa, the wind energy density at 250 m showed differences that range between 30 and 50% relative to wind energy density at 100 m. [ABSTRACT FROM AUTHOR]

High-quality land use and land cover (LULC) information is of crucial importance for the performance of regional climate models (RCMs), in particular at high spatial resolutions down to convection permitting scales below 4 km. Several satellite-based high-resolution products are currently available for implementation into RCMs. One of the most recent products is the European Space Agency Climate Change Initiative Land Cover (ESA CCI LC) dataset. While the ESA CCI LC has been assessed globally, an evaluation against regional, independent LULC datasets is necessary to identify LULC inaccuracies in the respective region of interest and to give regional climate modelers estimates for the uncertainty in the land use forcing. In the present work the ESA CCI LC dataset is compared to the COoRdination and INformation on the Environment (CORINE) Land Cover (CLC). Agreement between the datasets is assessed by proportional area comparison (PAC). The resulting agreement measures are compared to the results of a majority approach (MA) to explore possible differences between the methods. Three timesteps of ESA CCI LC matching the timesteps of CLC are assessed to take a change in agreement over time into account. In addition to the quantification of agreement, spatial patterns of possible issues with ESA CCI LC are identified through utilization of geospatial information systems (GIS). Using the PAC, the agreement of ESA CCI LC with CLC is found to be ∼76 % for the research area (RA). Although the agreement decreases slightly using the PAC, no substantial differences in agreement measures were found compared to the results of the MA. Dominant LULC categories agriculture and forest show an agreement of over 80 % with CLC. A few major issues were found for grassland, wetlands, settlements, and water bodies in the RA of which some might influence RCM performance if the dataset is implemented without adjustment. We highly recommend to apply the PAC to other regions in Europe and further globally to investigate if the found issues are also found elsewhere. The use of more independent regional and specified datasets for validation but also for possible improvement of the ESA CCI LC dataset is suggested.

The weather research and forecasting (WRF) model and a combination of the regional spectral model (RSM) and the Japanese Meteorological Agency Non‐Hydrostatic Model (NHM) were used to dynamically downscale selected CMIP5 global climate models to provide 2‐km projections with hourly model output for Puerto Rico and the U.S. Virgin Islands. Two 20‐year time slices were downscaled for historical (1986–2005) and future (2041–2060) periods following RCP8.5. Projected changes to mean and extreme temperature and precipitation were quantified for Holdridge life zones within Puerto Rico and for the U.S. Virgin Islands. The evaluation reveals a persistent cold bias for all islands in the U.S. Caribbean, a dry bias across Puerto Rico, and a wet bias on the windward side of mountains within the U.S. Virgin Islands. Despite these biases, model simulations show a robust drying pattern for all islands that is generally larger for Puerto Rico (25% annual rainfall reduction for some life zones) than the U.S. Virgin Islands (12% island average). The largest precipitation reductions are found during the more convectively active afternoon and evening hours. Within Puerto Rico, the model uncertainty increases for the wetter life zones, especially for precipitation. Across the life zones, both models project unprecedented maximum and minimum temperatures that may exceed 200 days annually above the historical baseline with only small changes to the frequency of extreme rainfall. By contrast, in the U.S. Virgin Islands, there is no consensus on the location of the largest drying relative to the windward and leeward side of the islands. However, the models project the largest increases in maximum temperature on the southern side of St. Croix and in higher elevations of St. Thomas and St. John. [ABSTRACT FROM AUTHOR]

Two 16‐year simulations were conducted to study the influence of two runoff schemes [the default one is TOPMODEL (hereafter referred as TOP) and the other one is the variable infiltration capacity (VIC)] with vegetation is being interactive [by enabling the carbon–nitrogen (CN) module] on the terrestrial carbon cycle fluxes of Africa using the regional climate model—RegCM4. The first simulation was labelled as CN‐TOP, while the second simulation was hereafter referred to as CN‐VIC. The results were evaluated and compared against various observation‐based satellites and reanalysis products. Results showed that the CN‐TOP overestimates leaf area index (LAI) and slightly underestimates the terrestrial carbon fluxes in comparison with the reference product; meanwhile, the CN‐VIC severely underestimates both LAI and terrestrial fluxes particularly over the Congo basin. In addition, the CN‐VIC shows a superior performance for simulating the net ecosystem exchange (NEE) than when it is simulated by the CN‐TOP. In summary, the coupled RegCM4‐CLM45‐CN‐VIC model can be recommended for future studies of NEE over Africa. To obtain robust results for simulating the terrestrial carbon fluxes especially the NEE; it is highly recommended to calibrate the four parameters of the VIC surface data set over Africa particularly over the Congo basin against in‐situ observations. [ABSTRACT FROM AUTHOR]

Extratropical cyclones of type Vb develop over the western Mediterranean and move north-eastward, leading to heavy precipitation over central Europe and posing a major natural hazard. Thus, this study aims at assessing their sensitivity to climate change and deepens the understanding of the underlying processes of Vb-type cyclones. The analysis is based on global climate model output, which is dynamically downscaled for extreme Vb cyclones. Thereby two periods are compared: the reference period 1979 to 2013, and the future period 2070 to 2099 under the representative concentration pathway RCP8.5. Additionally, we include the analysis from a large ensemble (LENS), where 25 ensemble members are analysed for the reference period 1990–2005 and the future period 2071–2080. The results show a reduction of Vb cyclones from 3.2 events per year during the reference period to only 2.1 Vb cyclones per year at the end of the 21st century. This result is supported by the LENS, which shows a significant reduction from 2.9 to 2.6 Vb events per year. This reduction is induced by a northward shift of cyclone track over Europe in the future. To gain insight into the impact of Vb cyclones, 10 Vb cyclones with the most intense precipitation over the Alps are selected and dynamically downscaled for each period, separately. Although the overall precipitation in the innermost domain stays the same in the two periods, results indicate that future Vb events tend to affect more strongly the eastern coasts of the Mediterranean Sea, while the impact in the Alpine region becomes slightly ameliorated compared to the current conditions. Furthermore, the dynamical downscaling exhibits an increased temperature contrast between the Mediterranean Sea and the European land for these 10 events in future. This contrast leads to a higher instability at coastal areas and thus explains the changed precipitation pattern. [ABSTRACT FROM AUTHOR]

Coarse resolution global climate models (GCMs) cannot resolve fine-scale drivers of regional climate, which is the scale where climate adaptation decisions are made. Regional climate models (RCMs) generate high-resolution projections by dynamically downscaling GCM outputs. However, evidence of where and when downscaling provides new information about both the current climate (added value, AV) and projected climate change signals, relative to driving data, is lacking. Seasons and locations where CORDEX-Australasia ERA-Interim and GCM-driven RCMs show AV for mean and extreme precipitation and temperature are identified. A new concept is introduced, 'realised added value', that identifies where and when RCMs simultaneously add value in the present climate and project a different climate change signal, thus suggesting plausible improvements in future climate projections by RCMs. ERA-Interim-driven RCMs add value to the simulation of summer-time mean precipitation, especially over northern and eastern Australia. GCM-driven RCMs show AV for precipitation over complex orography in south-eastern Australia during winter and widespread AV for mean and extreme minimum temperature during both seasons, especially over coastal and high-altitude areas. RCM projections of decreased winter rainfall over the Australian Alps and decreased summer rainfall over northern Australia are collocated with notable realised added value. Realised added value averaged across models, variables, seasons and statistics is evident across the majority of Australia and shows where plausible improvements in future climate projections are conferred by RCMs. This assessment of varying RCM capabilities to provide realised added value to GCM projections can be applied globally to inform climate adaptation and model development. [ABSTRACT FROM AUTHOR]

Surface melting on Antarctic Peninsula ice shelves can influence ice shelf mass balance, and consequently sea level rise. We show that summertime cloud phase on the Larsen C ice shelf on the Antarctic Peninsula strongly influences the amount of radiation received at the surface and can determine whether or not melting occurs. While previous work has separately evaluated cloud phase and the surface energy balance (SEB) during summertime over Larsen C, no previous studies have examined this relationship quantitatively. Furthermore, regional climate models frequently produce surface radiation biases related to cloud ice and liquid water content. This study uses a high‐resolution regional configuration of the UK Met Office Unified Model (MetUM) to assess the influence of cloud ice and liquid properties on the SEB, and consequently melting, over the Larsen C ice shelf. Results from a case‐study show that simulations producing a vertical cloud phase structure more comparable to aircraft observations exhibit smaller surface radiative biases. A configuration of the MetUM adapted to improve the simulation of cloud phase reproduces the observed surface melt most closely. During a five‐week simulation of summertime conditions, model melt biases are reduced to <2 W·m−2: a four‐fold improvement on a previous study that used default MetUM settings. This demonstrates the importance of cloud phase in determining summertime melt rates on Larsen C. [ABSTRACT FROM AUTHOR]

Recent accelerated warming over the Arctic coincides with sea ice reduction and shifting patterns of land cover. We use a state‐of‐the‐art regional Earth system model, RCAO‐GUESS, which comprises a dynamic vegetation model (LPJ‐GUESS), a regional atmosphere model (RCA), and an ocean sea ice model (RCO), to explore the dynamic coupling between vegetation and sea ice during 1989–2011. Our results show that RCAO‐GUESS captures recent trends in observed sea ice concentration and extent, with the inclusion of vegetation dynamics resulting in larger, more realistic variations in summer and autumn than the model that does not account for vegetation dynamics. Vegetation feedbacks induce concomitant changes in downwelling longwave radiation, near‐surface temperature, mean sea level pressure, and sea ice reductions, suggesting a feedback chain linking vegetation change to sea ice dynamics. This study highlights the importance of including interactive vegetation dynamics in modeling the Arctic climate system, particularly when predicting sea ice dynamics. Plain Language Summary: Recent accelerated warming over the Arctic is associated with dramatic changes in the physical environment, among which unprecedented sea ice decline has received particular attention. In this study, we use a regional Earth system model accounting for interactive coupling between the atmosphere, land vegetation, and sea ice dynamics to explore their potential links. Our model simulates observed spatiotemporal patterns of sea ice thickness and extent reasonably well. Furthermore, the results show that feedbacks of warming‐driven vegetation changes on the near‐surface radiation balance can cause greater variations in sea ice between seasons, which can contribute to an accelerated trend of sea ice reduction. The changes in mean sea level pressure caused by vegetation changes can alter the transport of energy and warm the land, sea, and sea ice surfaces. Downwelling longwave radiation is the dominant factor contributing to the near‐surface warming and increased sea ice melting. Our study highlights the importance of adopting fully coupled Earth system models that account for interactive effects of vegetation dynamics on the physical climate system, in particular when analyzing the reduction of sea ice in the Arctic. Key Points: Sea ice concentration and extent are simulated by a fully coupled regional Earth system model, including interactive vegetation dynamicsInteractive vegetation dynamics increase the interannual variations of seasonal sea ice coverIncreased downwelling longwave radiation induced by vegetation feedbacks enhances sea ice melting [ABSTRACT FROM AUTHOR]