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When selecting a subset of climate change scenarios (GCM models), the priority is to ensure that the subset reflects the comprehensive range of possible model results for all variables concerned. Though many studies have attempted to improve the scenario selection, there is a lack of studies that discuss methods to ensure that the results from a subset of climate models contain the same range of uncertainty in hydrologic variables as when all models are considered. We applied the Katsavounidis-Kuo-Zhang (KKZ) algorithm to select a subset of climate change scenarios and demonstrated its ability to reduce the number of GCM models in an ensemble, while the ranges of multiple climate extremes indices were preserved. First, we analyzed the role of 27 ETCCDI climate extremes indices for scenario selection and selected the representative climate extreme indices. Before the selection of a subset, we excluded a few deficient GCM models that could not represent the observed climate regime. Subsequently, we discovered that a subset of GCM models selected by the KKZ algorithm with the representative climate extreme indices could not capture the full potential range of changes in hydrologic extremes (e.g., 3-day peak flow and 7-day low flow) in some regional case studies. However, the application of the KKZ algorithm with a different set of climate indices, which are correlated to the hydrologic extremes, enabled the overcoming of this limitation. Key climate indices, dependent on the hydrologic extremes to be projected, must therefore be determined prior to the selection of a subset of GCM models. [ABSTRACT FROM AUTHOR]

Changes in the essential climate extremes indices and surface variables for the end of the twenty-first century are assessed in this study based on two transient climate change simulations, with and without land-use and land-cover changes (LULCC), but identical atmospheric forcing. The two simulations are performed with the 5th generation of the Canadian Regional Climate Model (CRCM5) driven by the Canadian Earth System Model for the (2006-2100)-Representative Concentration Pathway 4.5 (RCP4.5) scenario. For the simulation with LULCC, land-cover data sets are taken from the global change assessment model (GCAM) representing the RCP4.5 scenario for the period 2006-2100. LULCC in RCP4.5 scenario suggest significant reduction in cultivated land (e.g. Canadian Prairies and Mississippi basin) due to afforestation. CRCM5 climate projections imply a general warming by the end of the twenty-first century, especially over the northern regions in winter. CRCM5 projects more warm spell-days per year over most areas of the continent, and implicitly more summer days and tropical nights at the expense of cold-spell, frost and ice days whose number is projected to decrease by up to 40% by the end of the twenty-first century with respect to the baseline period 1971-2000. Most land areas north of 45°N, in all seasons, as well as the southeastern United States in summer, exhibit increases in mean precipitation under the RCP4.5 scenario. In contrast, central parts of the continent in summer and much of Mexico in all seasons show reduced precipitation. In addition, large areas of North America exhibit changes of 10 to 40% (depending on the season and geographical location) in the number of heavy precipitation days. Results also suggest that the biogeophysical effects of LULCC on climate, assessed through differences between the two simulations, lead to warmer regional climates, especially in winter. The investigation of processes leading to this response shows high sensitivity of the results to changes in albedo as a response to LULCC. Overall, at the seasonal scale, results show that intense afforestation may contribute to an additional 25% of projected changes. [ABSTRACT FROM AUTHOR]

Extreme weather events are more detrimental to human culture and ecosystems than typical weather patterns. A multimodel ensemble (MME) of the top-performing global climate models (GCMs) to simulate 11 precipitation extremes was selected using a hybrid method to project their changes in Pakistan. It also compared the benefits of using all GCMs compared to using only selected GCMs when projecting precipitation extremes for two future periods (2020–2059) and (2060–2099) for four shared socioeconomic pathways (SSPs), SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5. Results showed that EC-Earth3-Veg, MRI-ESM2-0 and NorESM2-MM performed best among GCMs in simulating historical and projecting future precipitation extremes. Compared to the MME of all GCMs, the uncertainty in future projections of all precipitation indices of the selected GCMs were significantly smaller. The MME median of the selected GCMs showed increased precipitation extremes over most of Pakistan. The greater increases were in RX1day by 6–12 mm, RX5day by 12–20 mm, Prcptot by 40–50 mm, R95ptot by greater than 30 mm, R99ptot by more than 9 mm, R4mm ≥ 4 mm by 0–4 days, R10mm by 2–6 days, R20mm by 1–3 days, and SDII by 1 mm/day, CWD by one day, CDD by 0–4 days in the northern high elevated areas for SSP5-8.5 in the late future. These results emphasize the greater influence of climate change on precipitation extremes in the northern, high-elevation areas, which provide the majority of the country's water. This emphasizes the necessity to adopt suitable climate change mitigation strategies for sustainable development, particularly in the country's northern regions. [ABSTRACT FROM AUTHOR]

In the coming few decades, projected increases in global temperature and humidity are generally expected to exacerbate human exposure to climate extremes (e.g., humid-heat and rainfall extremes). Despite the growing risk of humid-heat stress (measured by wet-bulb temperature), it has received less attention in East Africa, where arid and semi-arid climatic conditions prevail. Moreover, no consensus has yet been reached across models regarding future changes in rainfall over this region. Here, we screen Global Climate Models (GCMs) from CMIP5 and CMIP6 and use, for boundary conditions, simulations from only those GCMs that simulate successfully recent climatic trends. Based on these GCMs and Regional Climate Model (RCM) simulations, we project that annual mean temperature is likely to rise by 2 ℃ toward midcentury (2021–2050) ​at a faster rate than the global average (about 1.5 ℃), under the RCP8.5 and SSP5-8.5 scenarios, associated with more frequent and severe climate extremes. In particular, low-lying regions in East Africa will be vulnerable to severe heat stress, with an extreme wet-bulb temperature approaching or exceeding the US National Weather Service's extreme danger threshold of 31 ℃. On the other hand, population centers in the highlands of Ethiopia will receive significantly more precipitation during the autumn season and will see more extreme rainfall events, with implications for flooding and agriculture. The robustness of these results across all GCM and RCM simulations, and for both of CMIP5 and CMIP6 frameworks (CMIP: Coupled Model Inter-comparison Project) supports the reliability of these future projections. Our simulations of near-term climate change impacts are designed to inform the development of sound adaptation strategies for the region. [ABSTRACT FROM AUTHOR]

How the value of higher-resolution climate variables dynamically downscaled can affect the hydrological impact assessment has been a long standing issue. This study investigates the potential benefit of high-resolution climate data locally tailored over South Korea in terms of the reduction of uncertainties in hydrological projections. For this purpose, a large ensemble consisting of three Global Climate Model (GCM) projections and their dynamical downscaling products in different resolutions (i.e., 20 and 5 km), and four bias correction (BC) methods is fed into a semi-distributed hydrological model (HM) customized over Korean river basins. The in-depth comparison among the 45-members hydrological simulations proves the benefit in using high-resolution Regional Climate Model (RCM) for the runoff projections. While this study acknowledges the necessity of BC to remove the systematic bias in climate simulations, it is found that the high-resolution dynamical downscaling can significantly narrow the spread brought with different BC methods, thus reducing the uncertainty in the projected hydrological change. The projected runoff changes for both the mean of wet season and the high flows indicate that there will be an intensified runoff, especially for the extremes, over South Korea under the warming. Altogether, this study provides a valuable exploration of uncertainty reduction in hydrological projections from the perspective of resolution effect of dynamical downscaling, which is meaningful for hydroclimate studies and climate change impact assessment. [ABSTRACT FROM AUTHOR]

The frequency and severity of climatic extremes is expected to escalate in the future primarily because of the increasing greenhouse gas concentrations in the atmosphere. This study aims to assess the impact of climate change on the extreme temperature and precipitation scenarios using climate indices in the Kashmir Himalaya. The analysis has been carried out for the twenty-first century under different representative concentration pathways (RCPs) through the Statistical Downscaling Model (SDSM) and ClimPACT2. The simulation reveals that the climate in the region will get progressively warmer in the future by increments of 0.36–1.48 °C and 0.65–1.07 °C in mean maximum and minimum temperatures respectively, during 2080s (2071–2100) relative to 1980–2010 under RCP8.5. The annual precipitation is likely to decrease by a maximum of 2.09–6.61% (2080s) under RCP8.5. The seasonal distribution of precipitation is expected to alter significantly with winter, spring, and summer seasons marking reductions of 9%, 5.7%, and 1.7%, respectively during 2080s under RCP8.5. The results of extreme climate evaluation show significant increasing trends for warm temperature-based indices and decreasing trends for cold temperature-based indices. Precipitation indices on the other hand show weaker and spatially incoherent trends with a general tendency towards dry regimes. The projected scenarios of extreme climate indices may result in large-scale adverse impacts on the environment and ecological resource base of the Kashmir Himalaya. [ABSTRACT FROM AUTHOR]

In this study, the performance of sixteen Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating extreme precipitation indices over West Africa has been evaluated. Nine extreme precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) have been used. The performance of CMIP6 models and their ensemble mean was examined by comparing the model results to that of Global Precipitation Climatology Project One-Degree Daily Dataset (GPCP) and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis 3B42 (TRMM) gridded observations during the present-day period 1997–2014 with focus on the summer months (i.e., June–July–August, JJA). Our results show that CMIP6 models reasonably reproduce the spatial patterns of the extreme precipitation indices over the entire region, although their performance is quite different between Sahel and Guinea coast subregions. The gridded observations exhibit significant differences in their estimates of the indices evaluated, and the CMIP6 models are generally closer to GPCP than to TRMM. The models broadly exhibit too many consecutive wet days (CWD) resulting in widespread overestimation over entire West Africa. Also, the heavy (R10 mm) and very heavy (R20 mm) precipitation days are considerably overestimated especially over the mountain regions. Overall, the ensemble mean outperforms any individual model at capturing mean distributions of the extreme precipitation indices, particularly in comparison to the two gridded observations. [ABSTRACT FROM AUTHOR]

Studies that evaluate climate change projections over the whole of South America (SA) and including different seasons and models are scarce. In this context, the objective of this work is to assess climate projections for SA through the use of climatic indices, considering the entire continent, distinct seasons, and ensembles of models. Projections performed with the Eta regional climate model and its driving global climate models (GCMs) are analysed. From these projections, 19 climate indices based on daily precipitation and maximum and minimum temperature are computed. The results focus on two ensembles (GCMs and Eta), time slices (1980–2005 and 2050–2080), and scenarios (RCP4.5 and RCP8.5). In the validation of the present climate, it is shown that Eta adds value to GCMs. Future projections indicate, for both austral summer (DJF) and winter (JJA), an increase in the frequency and intensity of extreme events of daily rainfall over southeastern and extreme north of SA. Over the Amazon, during DJF, there is a statistically significant increase in the number of consecutive dry days and a decrease in the consecutive wet days. For northeastern Brazil, these features are more intense in JJA. The frequency of cold (warm) nights and days is projected to decrease (increase) over the whole continent and seasons. The climate change signal for the 19 climate indices is more intense under RCP8.5, and the regions more vulnerable to climate change are the Amazon, northeastern Brazil, and southeastern SA. Considering Brazil, the projections of precipitation and air temperature are also shown by biomes. [ABSTRACT FROM AUTHOR]

Based on four reanalyses or gridded data sets (ERA5, 20CR, APHRODITE and REGEN), we provide an overview of 23 Historical and 7 HighResMIP experiments' performance from the Coupled Model Intercomparison Project Phase 6 (CMIP6) (for short, 6-Hist, HighRes) in simulating seven extreme precipitation indices over Asia defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). We compare them with 28 Historical experiments in CMIP5 (5-Hist). CMIP5 and CMIP6 models are generally able to reproduce extreme precipitation's spatial distribution and their trend patterns in comparison to the benchmark data set (APHRODITE). The overall performance of individual model is summarized by a "portrait" diagram based on four statistics for each index. We divide all 58 models into three groups (A, the top 20%; B, the median 60% and C group, the last 20%) according to MR rankings (the comprehensive ranking measure). Based on the "portrait" diagram and MR rankings, models that perform relatively well for all seven extreme precipitation indices include HadCM3, HadGEM2-AO, HadGEM2-CC and HadGEM2-ES from 5-Hist, EC-Earth3, EC-Earth3-Veg from 6-Hist and ECMWF-IFS-HR, ECMWF-IFS-LR, ECMWF-IFS-MR from HighRes. The simulated performance of CMIP6 is polarized, for the top four and the last five ranking models are both from CMIP6. Compared with the counterpart models in CMIP6 and CMIP5, the improvement of PCC (pattern correlation coefficient) is more obvious. Furthermore, the dry biases of CMIP6 (both 6-Hist and HighRes) in Southern China and India and the wet biases of CMIP6 in Tibet are reduced compared to CMIP5. This may benefit from the improvement that CMIP6 models can capture the characteristics of meridional moisture flux convergence, and improve the overestimation or underestimation of meridional and zonal specific humidity eddies compared to CMIP5. [ABSTRACT FROM AUTHOR]

A new regional climate projection ensemble has been created for the Australasia region as part of the World Climate Research Programs Coordinated Regional Downscaling Experiment (CORDEX). The CORDEX-Australasia ensemble is the largest regional climate projection ensemble ever created for the region. It is a 20-member ensemble made by 6 regional climate models downscaling 11 global climate models. Overall the ensemble produces a good representation of recent climate. Consistent biases within the ensemble include an underestimation of the diurnal temperature range and an underestimation of precipitation across much of southern Australia. Under a high emissions scenario projected temperature changes by the end of the twenty-first century reach ~ 5 K in the interior of Australia with smaller increases found toward the coast. Projected precipitation changes are towards drying, particularly in the most populated areas of the southwest and southeast of the continent. The projected precipitation change is very seasonal with summer projected to see little change leaning toward an increase. These results provide a foundation enabling future studies of regional climate changes, climate change impacts, and adaptation options for Australia. [ABSTRACT FROM AUTHOR]

Climate extremes can severely impact socio-economic development. Climate trends of three temperature and three precipitation climate indices were evaluated in observational data, 23 models from the 5th Coupled Model Intercomparison Projects (CMIP5), and 20 models from CMIP6. The climate indices were calculated over the whole of China, and individually over the basins of its three major rivers. The indices are the spatio-temporal evolution characteristics of annual mean temperature (Tas), minimum of daily minimum temperature (TNn), maximum of daily maximum temperature (TXx), number of tropical nights (TR), daily precipitation (Pre), very heavy precipitation days (R20mm), maximum consecutive 5-day precipitation (Rx5day) and consecutive dry days (CDD). From 1961 to 2018, most of China has warmed; Tas, TNn, TXx and TR over China has increased by 1.7 °C, 2.8 °C, 1.1 °C and 9 days, respectively. Changes of Tas, TNn and TXx over the Yellow River Basin, Yangtze River Basin and Pearl River Basin were generally similar in sign. The most significant increase of TR was seen over the Pearl River Basin. Historical Tas was well reproduced by both CMIP5 and CMIP6 over the study regions, but obvious uncertainties exist in the simulation of Pre. In general, CMIP6 models were improved from CMIP5 models. Climate projections were calculated for the 2021–2100 period. Future warming over China would be stronger with higher SSP scenarios; TNn over China would warm seven times more under the SSP5-8.5 scenario (5.6 °C) compared to the SSP1-2.6 scenario. Future wetting over China would be stronger with higher the SSP scenarios; Under the SSP5-8.5 scenario, Pre, R20mm, Rx5day would increase by 28%, 150%, and 38%, respectively. Projected changes of CDD different by region—decreasing over most of China and the Yellow River Basin, but increasing over the Yangtze and Pearl River Basins. The higher of the emission scenario, the less significant the reduction of CDD over the two basins. This suggests that the temporal distribution of precipitation over China will become more uneven in the future, especially under the higher SSP scenarios. [ABSTRACT FROM AUTHOR]

The Intergovernmental Panel on Climate Change (IPCC) suggests limiting global warming to 1.5 °C compared to 2 °C would avoid dangerous impacts of anthropogenic climate change and ensure a more sustainable society. As the vulnerability to global warming is regionally dependent, this study assesses the effects of 0.5 °C less global warming on climate extremes in the United States. Eight climate extreme indices are calculated based on Coupled Model Intercomparison Project—phase 5 (CMIP5), and North American—Coordinated Regional Climate Downscaling Experiments (NA-CORDEX) with and without bias correction. We evaluate the projected changes in temperature and precipitation extremes, and examine their differences between the 1.5 and 2 °C warming targets. Under a warming climate, both CMIP5 and NA-CORDEX show intensified heat extremes and reduced cold extremes across the country, intensified and more frequent heavy precipitation in large areas of the North, prolonged dry spells in some regions of the West, South, and Midwest, and more frequent drought events in the West. Results suggest that the 0.5 °C less global warming would avoid the intensification of climate extremes by 32–46% (35–42%) for heat extremes intensity (frequency) across the country and, by 23–41% for heavy precipitation intensity in the North, South, and Southeast. The changes in annual heavy precipitation intensity are mainly contributed by winter and spring. However, impacts of the limited warming on the frequency of heavy precipitation, dry spell, and drought frequency are only evident in a few regions. Although uncertainties are found among the climate models and emission scenarios, our results highlight the benefits of limiting warming at 1.5 °C in order to reduce the risks of climate extremes associated with global warming. [ABSTRACT FROM AUTHOR]

Simulation of past climate is an important tool for the validation of climate models. The comparison with observed daily values allows us to assess the reliability of their projections on climatic extremes in a future climate. The frequency and amplitude of extreme events are fundamental aspects that climate simulations need to reproduce as they have high impacts on economy and society. The ability to simulate them will help policy makers in taking better measures to face climate change. This work aims at evaluating how six models within the High Resolution Model Intercomparison Project reproduce the trends on extreme indices as they have been observed over Europe in the 1970–2014 period. Observed values are provided by the new homogenized version of the E-OBS gridded dataset. The comparison is performed through the use of indices based on seasonal averages and on exceedances of percentile-based thresholds, focusing on six subregions. Winter-average minimum temperature is generally underestimated by models (down to − 4 °C difference over Italy and Norway) while simulated trends in seasonal averages and extreme values are found to be too cold on Eastern Europe and too warm on Iberia and Southern Europe (e.g. up to a difference of − 4% per decade on the number of Cold Nights over Spain). On the other hand the models tend to overestimate summer maximum temperatures averages in the Mediterranean Area (up to + 5 °C over the Balkans) and underestimate these at higher latitudes. Iberia, Southern and Eastern Europe are simulated with too low trends in average summer temperatures. The simulated trends are too strong on the North West part and too weak on the South East part of Europe (down to − 3%/decade on the number of Warm Days over Italy and Western Balkans). These results corroborate the findings of previous studies about the underestimation of the warming trends of summer temperatures in Southern Europe, where these are more intense and have more impacts. The high-resolution versions of the models are compared to their lower-resolution counterparts, similar to those used in the CMIP5, showing a slight improvement for the simulation of extreme winter minimum temperatures, while no significant progresses have been found for extreme summer maximum temperatures. [ABSTRACT FROM AUTHOR]

The precipitation behaviour at different timescales (interannual, intraseasonal and synoptic) and extreme events in a warmer scenario over South America is analysed. This study is based on a set of Regional Climate Models (RCM) from the CORDEX database and their driving Global Climate Models (GCM) from the CMIP5 Project. Historical simulations for 1979–2005 and from the RCP4.5 scenario for 2071–2100 are used. The projected changes in the precipitation behaviour are evaluated in terms of the consistency between the pairs RCM-GCM aiming to explore the added value of RCMs. The agreement between projected changes from RCMs is also evaluated as a measure of confidence of the regional climate change signal. The analysis is carried out for two extended seasons (April to September and October to March). The projected change in the mean precipitation over subtropical latitudes is associated with both changes in the frequency of rainy days and in the intensity of extreme events, while for the tropics the changes are mainly associated with changes in the wet day frequency. The increase of extreme precipitation events over the subtropics arises as a robust signal among models, while for tropical latitudes the dispersion among models is high, which reduces the confidence of the projections. In general, the consistency of the projections in the pairs RCM-GCM and the agreement among models are higher for the low frequency variability patterns during winter, while for summertime a better agreement in the projected changes of the precipitation behaviour at different timescales among RCMs is found. [ABSTRACT FROM AUTHOR]

In the present study, the Max-Planck-Institute for Meteorology's Earth System Model is used to investigate irrigation's general effect on severe and extreme hydrometeorological regimes. Our idealized simulations show a large potential to modulate the magnitude and occurrence frequency of severe and extreme precipitation rates, indicating the possibility to mitigate some of the detrimental effects of future climate change, but also a substantial risk due to the declining water availability in drying regions. Irrigation almost exclusively reduces the magnitude and occurrence frequency of severely and extremely dry conditions and has the potential to counter the drying trends that result from the 21st century increase in greenhouse gas concentrations—according to the RCP4.5 scenario. At the same time, irrigation does not only have a mitigating effect, as it increases the occurrence frequency and intensity of severely wet conditions in many regions. The study aims at irrigation's theoretical (maximum) impact and investigates a highly idealized trajectory in which global irrigation is being maximized within hydrologically sustainable limits. However, even for this scenario, we find large regions in which present-day water extractions are not sustainable as they often rely on exhaustible sources. Especially, a depletion of non-renewable ground water in South Asia would lead to a strong reduction in irrigation and, consequently, a substantial increase in the occurrence frequency of severely and extremely dry months throughout the region. [ABSTRACT FROM AUTHOR]

Brazil experiences extreme weather and climate events that cause numerous economic and social losses, and according to climate change projections, these events will increase in intensity and frequency over this century.This study adds to the body of research on Brazil's climate change by analyzing the historical patterns and projected changes in temperature and precipitation extremes across Brazil using the World Climate Research Program's Expert Team on Climate Change Detection and Indices framework. This novel approach analyzes climate extreme events over the past four decades (1980–2016) using multiple gridded observation and reanalysis datasets. Furthermore, future changes in climate extremes are analyzed from 20 downscaled Earth System Models (ESMs) at high horizontal resolution (0.25° of latitude/longitude), under two representative concentration pathway scenarios (RCP4.5 and RCP8.5). Projected changes in the extreme indices are analyzed over mid-twenty-first century (2046–2065) and end-of-twenty-first century (2081–2100) relative to the reference period 1986–2005. Results show consistent warming patterns with increasing (decreasing) trends in warm (cold) extremes in the historical datasets. A similar but more intense warm pattern is projected in the mid and end of the twenty-first century. For precipitation indices, observations show an increase in consecutive dry days and a reduction of consecutive wet days over almost all Brazil. The frequency and intensity of extremely wet days over Brazil are expected to increase according to future scenarios. Designing effective adaptation and mitigation measures in response to changes in climate extremes events depends on this improved understanding of how conditions have and are likely to change in the future at regional scales. [ABSTRACT FROM AUTHOR]

The study assesses the performance of 24 model runs from five COordinated Regional climate Downscaling Experiment (CORDEX) regional climate models (RCMs) in simulating East Africa's spatio-temporal precipitation characteristics using a set of eight descriptors: consecutive dry days (CDD), consecutive wet days (CWD), simple precipitation intensity index (SDII), mean daily annual (pr_ANN), seasonal (pr_MAM and pr_OND) precipitation, and representatives of heavy precipitation (90p) and very intense precipitation (99p) events. Relatively better performing RCM runs are then used to assess projected precipitation changes (for the period 2071–2099 relative to 1977–2005) over the study domain under the representative concentration pathway (RCP) 8.5 scenario. The performance of RCMs is found to be descriptor and scope specific. Overall, RCA4 (r1i1p1) forced by CNRM-CERFACS-CNRM-CM5 and MPI-M-MPI-ESM-LR, REMO2009 (r1i1p1) forced by MPI-M-MPI-ESM-LR, and RCA4 (r2i1p1) forced by MPI-M-MPI-ESM-LR emerge as the top four RCM runs. We show that an ensemble mean of the top four model runs outperforms an ensemble mean of 24 model simulations and ensemble means for all runs in an RCM. Our analysis of projections shows a reduction (increase) in mean daily precipitation for MAM(OND), an increase(decrease) in CDD(CWD) events, and a general increase in SDII and the width of the right tail of the precipitation distribution (99p–90p). An increase in SDII and 99p–90p implies a possibility of occurrence of heavy and extreme precipitation incidences by the end of the twenty-first century. Our findings provide important information to support the region's climate change adaptation and mitigation efforts. [ABSTRACT FROM AUTHOR]

Recent studies indicated that the internal climate variability plays an important role in various aspects of projected climate changes on regional and local scales. Here we present results of the spreads in projected trends of wintertime North American surface air temperature and extremes indices of warm and cold days over the next half-century, by analyzing a 50-member large ensemble of climate simulations conducted with CanESM2. CanESM2 simulations confirm the important role of internal variability in projected surface temperature trends as demonstrated in previous studies. Yet the spread in North American warming trends in CanESM2 is generally smaller than those obtained from CCSM3 and ECHAM5 large ensemble simulations. Despite this, large spreads in the climate means as well as climate change trends of North American temperature extremes are apparent in CanESM2, especially in the projected cold day trends. The ensemble mean of forced climate simulations reveals high risks of warm days over the western coast and northern Canada, as well as a weakening belt of cold days extending from Alaska to the northeast US. The individual ensemble members differ from the ensemble mean mainly in magnitude of the warm day trends, but depart considerably from the ensemble mean in spatial pattern and magnitude of the cold day trends. The signal-to-noise ratio pattern of the warm day trend resembles that of the surface air temperature trend, with stronger signals over northern Canada, Alaska, and the southwestern US than the midsection of the continent. The projected cold day patterns reveal strong signals over the southwestern US, northern Canada, and the northeastern US. In addition, the internally generated components of mean and extreme temperature trends exhibit spatial coherences over North America, and are comparable to their externally forced trends. The large-scale atmospheric circulation-induced temperature variability influences these trends. Overall, our results suggest that climate change trends of North American temperature extremes are likely very uncertain and need to be applied with caution. [ABSTRACT FROM AUTHOR]

The extreme temperature changes under a 0.5 °C global mean surface temperature warming increment is of great importance for climate change adaption and risk management on post-Paris-Agreement agenda. The impacts of the already happened 0.5 °C warming increment on extreme temperature can serve as essential references for the 1.5/2 °C projections. Quantifying the observed changes of climate extremes is hampered by the limitation of observational datasets in both spatial coverage and temporal continuity. The reanalysis datasets are hoped to be useful substitutes for the observations, but their performance over continental China remains unknown. In this study, we compare the extreme temperature changes associated with the past 0.5 °C warming derived from three reanalysis datasets including JRA-55, ERA and 20CR with the observation in China. Distinct increases (decreases) in warm (cold) extremes are detected in all three reanalyses in a spatially aggregated perspective as in the observation. On regional scales the reanalyses have evident spreads in regions with insufficient observational coverage such as the western China. JRA-55 shows good agreement with the observation in both spatial patterns and magnitudes of extreme temperature changes. Both ERA and 20CR show weaker consistency with the observation, particularly in western China, mainly due to less observational constraints in data assimilation. The different aerosol data used in reanalysis assimilation systems also influenced the data quality. Our results indicate that while the reanalyses can serve as useful substitutes to fill in the observational gaps, cautious should be taken in regions with sparse observations and large anthropogenic aerosol emissions. [ABSTRACT FROM AUTHOR]

Flooding events associated with extreme precipitation have had large impacts in Norway. It is well known that these heavy precipitation events affecting Norway (and other parts of Europe) are strongly associated with atmospheric rivers (ARs). We assess trends in Norwegian AR characteristics, and the influence of AR variability on extreme precipitation in Norway. We first evaluate the ability of a high-resolution global climate model (EC-Earth) to simulate ARs, compared to ERA-Interim. We evaluate the EC-Earth simulated relationship between ARs and extreme precipitation in western Norway, compared to the observed relationship. We find that EC-Earth is able to simulate well the statistics of AR events and the related precipitation. The intensity and frequency of ARs making landfall in Norway both increase by the end of the century and we find a shift in seasonality of AR events in the future period. In two regions on the west coast, the majority of winter precipitation maxima are associated with AR events (> 80% of cases). Next we assess the influence of AR variability on extreme precipitation. A non-stationary extreme value analysis indicates that the magnitude of extreme precipitation events in these regions is associated with AR intensity. Indeed, the 1-in-20 year extreme event is 17% larger when the AR-intensity is high, compared to when it is low. There is little influence of specific humidity on the variability of extreme precipitation after all variables are de-trended. Finally, we find that the region mean temperature during winter AR events increases in the future. In the future, when the climate is generally warmer, AR days will tend to make landfall when the temperature is above the freezing point. The partitioning of more precipitation as rain, rather than as snow, can have severe impacts on flooding and water resource management. [ABSTRACT FROM AUTHOR]

Arid Central Asia is highly vulnerable to extreme climate events. Information on potential future changes in extreme climate events in Central Asia is limited. In this study, the performances of models from the Coupled Model Intercomparison Project phase 5 (CMIP5) in simulating climatological extremes in Central Asia are first evaluated, and a bias correction method is employed to constrain future projections. The responses of extreme climate events over Central Asia to future warming and, in particular, the impact of 1.5 and 2 °C global warming scenarios are then assessed based on the observationally constrained projections. During the twenty-first century, coldest night (TNn), coldest day (TXn), warmest night (TNx), warmest day (TXx), 1-day maximum precipitation (RX1 day), 5-day maximum precipitation (RX5 day), and precipitation intensity (SDII) in Central Asia would robustly increase at best estimated rates of 1.93 °C, 1.71 °C, 1.18 °C, 1.25 °C, 6.30%, 5.71%, and 4.99% per degree of global warming, respectively, under Representative Concentration Pathway (RCP) 8.5. Compared with the 2 °C warming scenario, limiting global warming to 1.5 °C could reduce the intensification (relative to 1986–2005) of TNn, TNx, TXn, TXx, RX1 day, RX5 day, and SDII by 33%, 24%, 32%, 29%, 39%, 42%, and 53% from the best estimates under RCP8.5, respectively. The avoided intensification of TNn, TNx, TXn and TXx (RX1 day and SDII) would be larger (smaller) under RCP4.5. This suggests that a low warming target is necessary for avoiding the dangerous risk of extremes in this arid region. [ABSTRACT FROM AUTHOR]

Present study attempts to project extreme precipitation indices over 34 different meteorological subdivisions and six homogeneous regions such as Northwest, Central Northeast, Northeast, West Central, Peninsular India and Hilly Region during summer monsoon season in the twenty-first century. For this purpose, the Regional Climate Model version4 (RegCM4) had been run at 50 km horizontal resolution forced with the global model GFDL-ESM2 M, during reference period 1976–2005 for the model validation, and the mid- (2031–2060) and far-future (2070–2099) for projections under RCP8.5 scenario over the South Asia CORDEX domain. In this paper, model simulated precipitation has been validated against IMD, APHRODITE and NCEP/NCAR data sets. The results indicate that RegCM4 captures the important features of seasonal precipitation and various extreme indices over the study area. The RegCM4 has projected an increase in the mean seasonal precipitation by 0.56 mm/day whereas in case of GFDL model the rate is 0.39 mm/day during the far-future relative to the reference period. The heavy precipitation indices are projected to increase more frequently (0.264/decade) than the mean precipitation rate (0.01/decade) over India. The correlations between the extreme precipitation indices and the seasonal mean precipitation are found to be strong. In addition, the consecutive dry days are projected to occur more frequently (3–5 days) over West Central (Telangana, Vidarbha and Marathwada) and west Rajasthan while consecutive wet days are projected to decrease over larger parts of India during far-future. Similarly, 1 day maximum precipitation and the simple daily intensity index are projected to increase consistently from mid- to far- futures over some sub-divisions of West coast, Hilly and Northeast regions. From a spatial probability perspective, model projection indicates more frequent severe drought and flood conditions over India. [ABSTRACT FROM AUTHOR]

We employ a large ensemble of Regional Climate Models (RCMs) from the COordinated Regional-climate Downscaling EXperiment to explore two questions: (1) what can we know about the future precipitation characteristics over Africa? and (2) does this information differ from that derived from the driving Global Climate Models (GCMs)? By taking into account both the statistical significance of the change and the models' agreement on its sign, we identify regions where the projected climate change signal is robust, suggesting confidence that the precipitation characteristics will change, and those where changes in the precipitation statistics are non-significant. Results show that, when spatially averaged, the RCMs median change is usually in agreement with that of the GCMs ensemble: even though the change in seasonal mean precipitation may differ, in some cases, other precipitation characteristics (e.g., intensity, frequency, and duration of dry and wet spells) show the same tendency. When the robust change (i.e., the value of the change averaged only over the land points where it is robust) is compared between the GCMs and RCMs, similarities are striking, indicating that, although with some uncertainty on the geographical extent, GCMs and RCMs project a consistent future. Potential added value of downscaling future climate projections (i.e., non-negligible fine-scale information that is absent in the lower resolution simulations) is found for instance over the Ethiopian highlands, where the RCM ensemble shows a robust decrease in mean precipitation in contrast with the GCMs results. This discrepancy may be associated with the better representation of topographical details that are missing in the large scale GCMs. The impact of the heterogeneity of the GCM–RCM matrix on the results has been also investigated; we found that, for most regions and indices, where results are robust or non-significant, they are so independently on the choice of the RCM or GCM. However, there are cases, especially over Central Africa and parts of West Africa, where results are uncertain, i.e. most of the RCMs project a statistically significant change but they do not agree on its sign. In these cases, especially where results are clearly clustered according to the RCM, there is not a simple way of subsampling the model ensemble in order to reduce the uncertainty or to infer a more robust result. [ABSTRACT FROM AUTHOR]

As the second biggest economy in the world, China has been experiencing significant impacts of global climate change. Developing future projections of regional climate over China is an indispensable step for designing appropriate mitigation and adaptation strategies against future climate change. To this end, this study focuses on exploring how the regional climate over China, including the mean and extreme climate, will be affected in the context of global warming throughout this century. The RegCM model is used to develop high-resolution climate scenarios for the whole country of China driven by boundary conditions of the Geophysical Fluid Dynamics Laboratory (GFDL) model under the Representative Concentration Pathways (RCPs). RegCM performance on simulating the present climate over China is evaluated and the results indicate that it is capable of reproducing the spatial distributions of temperature and precipitation. Future projections from RegCM suggest that an increase of 2 °C in daily mean temperature is expected in China by the end of the twenty-first century under RCP4.5 while an increase of 4 °C would be seen under RCP8.5. The Tibetan Plateau is likely to expect the most substantial temperature increase as well as the most significant decrease in extreme cold climate in China. In comparison, the annual total precipitation over China is projected to increase by 58 mm/year at the end of the twenty-first century under RCP4.5 and by 71 mm/year under RCP8.5. The projected changes in precipitation show apparent spatial variability due to the influences of local topography and land cover/use. [ABSTRACT FROM AUTHOR]

The assessment of predictability for decadal predictions of quantities like temperature and precipitation typically focuses on regional and temporal mean values. However, changes in extremes can be different to changes in mean climate, and accordingly their predictability may be different. We use simulations from CSIRO-Mk3-6-0 (CMIP5 archive) to set up a 'perfect model' experiment to compare the predictability for mean and extreme temperature and precipitation on interannual to decadal time-scales. The results show that both the mean and likelihood of near-surface temperature extremes is potentially predictable in many regions in the first lead year, while the areas with precipitation predictability tend to be mostly in low-latitude regions during this period. On decadal time scales, significant potential skill for mean and extreme temperatures is found over the North Atlantic and Southern Ocean but also over some land areas including North Africa, Europe and North America. The general spatial patterns of predictability are very similar between the mean and extremes. However, indices of moderate temperature extremes in particular show a tendency towards higher predictability than the mean. The approach to studying predictability presented here uses international coordinated model intercomparison project simulations. However a larger number of different initializations would be required from more models to allow improved robustness of the results. [ABSTRACT FROM AUTHOR]

Climate-impact projections are subject to uncertainty arising from climate models, greenhouse gases emission scenarios, bias correction and downscaling methods (BCDS), and the impact models. We studied the effects of hydrological model parameterization and regionalization (HM-P and HM-R) on the cascade of uncertainty. We developed a new, widely-applicable approach that improves our understanding of how HM-P and HM-R along with other uncertainty drivers contribute to the overall uncertainty in climate-impact projections. We analyzed uncertainties arising from general circulation models (GCMs), representative concertation pathways, BCDS, evapotranspiration calculation methods, and specifically HM-P and HM-R. We used the Soil and Water Assessment Tool, a semi-physical process-based hydrologic model with a high capability of parameterization, to project blue and green water resources for historical (1983–2007), near future (2010–2035) and far future (2040–2065) periods in Alberta, a western province of Canada. We developed an Analysis of Variance (ANOVA)-Sequential Uncertainty Fitting Program approach, to decompose the overall uncertainty into contributions of single drivers using the projected blue and green water resources. The monthly analyses of projected water resources showed that HM-P and HM-R contribute 21–51% and 15–55% to the blue water, and 20–48% and 15–50% to the green water overall uncertainty in near future and far future, respectively. Overall, we found that in spring and summer seasons uncertainty arising from HM-P and HM-R dominates other uncertainty sources, e.g. GCMs. We also found that global climate models are another dominant source of uncertainty in future impact projections. [ABSTRACT FROM AUTHOR]

A statistical framework for evaluating changes in extreme events is proposed and applied to evaluate a 20-member, regional climate model ensemble simulation with 30-km resolution. The model is found to represent the statistics and distributions of extreme events, including observed wet day characteristics, wet/dry days, and wet/dry spell characteristics, reasonably across Africa. Simulations of the mid-twenty-first and late-twenty-first century project statistically-significant changes in these societally-relevant climate characteristics in three regions. Intensification of rainfall is projected for the Sahel rainy season, including large increases in wet spell frequency, wet spell duration, and wet spell intensity. These changes are statistically significant at mid-twenty-first century and become more spatially robust by the end of the century. A weaker intensified rainfall trend is also projected over East Africa, for northern Ethiopia in boreal summer, Tanzania in boreal winter, and southern Ethiopia, Somalia, and the Lake Victoria region in boreal fall. The changes are significant in scattered regions at mid-twenty-first century, but widespread and highly significant by the end of the century. In contrast, increased dry periods is projected for parts of southern Africa (Angola, Zambia, Malawi), including 50–100% reductions in wet spell frequency annually and increases in dry spell duration in austral spring. The spatial coherence and rigorous statistical analysis of the projected changes combined with their physical consistency with the findings of previous studies support confidence in these results. [ABSTRACT FROM AUTHOR]

In this study, we use four statistical downscaling methods to statistically downscale seven Coupled Model Intercomparison Project (CMIP5) Global Climate Models (GCMs) and project the changes in precipitation and temperature over China under RCP4.5 and RCP8.5 emission scenarios. The four statistical downscaling methods are bias-correction and spatial downscaling (BCSD), bias-correction and climate imprint (BCCI), bias correction constructed analogues with quantile mapping reordering (BCCAQ), and cumulative distribution function transform (CDF-t). Though large inter-model variability exists in the distribution and magnitude of changes in projected precipitation, particularly for wet spell length (CWD), all downscaling methods generally project a consistent enhancement of precipitation in both summer and winter over most parts of China. For the arid and semiarid Northwest China, the shortened dry spell length (CDD) is accompanied by the pronouncedly intensified very wet days (R95p), as well as the increase in maximum 5-day precipitation amount (Rx5day). In contrast, southeastern regions may experience more consecutive dry days and more severe wet precipitation extremes. The projected changes from different downscaling techniques are fairly similar for temperature, apart from the diurnal temperature range for BCSD. Warming is projected across the whole domain with larger magnitude over the north and in winter under RCP8.5. More summer days and fewer frost days would appear in the future. The bias correction components of downscaling methods cause a higher degree of agreement among models, and the downscaled results generally retain the main climate change signal of the driving models. [ABSTRACT FROM AUTHOR]

A first systematic analysis was conducted to assess near-term future changes in climate extremes over East Asia during the summer season (June–August) using five regional climate model (RCM) simulations participating in the CORDEX-East Asia project (HadGEM3-RA, RegCM4, SNU-MM5, SNU-WRF, and YSU-RSM). The 20-year return values of extreme temperature and precipitation were compared between the present (1979–2005) and near-term future (2024–2049) periods, which were estimated using the generalized extreme value (GEV) analysis. Multi-RCM mean results show that temperature and precipitation will increase in both means and extremes and that the increase in precipitation extreme will follow the enhanced moisture availability with warming (~ 7% °C−1, Clausius–Clapeyron relation). It was found that the increases in GEV location parameter (mean intensity) and scale parameter (inter-annual variability) contribute dominantly to the increase in extremes of temperature and precipitation, respectively. Robust inter-RCM relations were observed between mean and extreme projections over East Asia and even on grid scales, more strongly for temperature. Model biases and future projections exhibit a significant relationship for temperature such that RCMs with warmer biases tend to predict stronger warming and vice versa. Results from three sub-regions (South Korea, Southern China, and Mongolia and northern China) consistently indicate that temperature increase involves an overall shift of the daily temperature distribution toward warmer conditions while precipitation increases are due to dominant increases in moderate-heavy rainfall events. Our multi-RCM assessment provides new insights to the uncertainty in future climate extremes over East Asia. [ABSTRACT FROM AUTHOR]

Global warming has a profound impact on the vulnerable environment of West Africa; hence, robust climate projection, especially of rainfall extremes, is quite important. Based on two representative concentration pathway (RCP) scenarios, projected changes in extreme summer rainfall events over West Africa were investigated using data from the Coordinated Regional Climate Downscaling Experiment models. Eight (8) extreme rainfall indices (CDD, CWD, r10mm, r20mm, PRCPTOT, R95pTOT, rx5day, and sdii) defined by the Expert Team on Climate Change Detection and Indices were used in the study. The performance of the regional climate model (RCM) simulations was validated by comparing with GPCP and TRMM observation data sets. Results show that the RCMs reasonably reproduced the observed pattern of extreme rainfall over the region and further added significant value to the driven GCMs over some grids. Compared to the baseline period 1976-2005, future changes (2070-2099) in summer rainfall extremes under the RCP4.5 and RCP8.5 scenarios show statistically significant decreasing total rainfall (PRCPTOT), while consecutive dry days and extreme rainfall events (R95pTOT) are projected to increase significantly. There are obvious indications that simple rainfall intensity (sdii) will increase in the future. This does not amount to an increase in total rainfall but suggests a likelihood of greater intensity of rainfall events. Overall, our results project that West Africa may suffer more natural disasters such as droughts and floods in the future. [ABSTRACT FROM AUTHOR]

Large temperature spatio-temporal gradients are a common feature of Mediterranean climates. The Portuguese complex topography and coastlines enhances such features, and in a small region large temperature gradients with high interannual variability is detected. In this study, the EURO-CORDEX high-resolution regional climate simulations (0.11° and 0.44° resolutions) are used to investigate the maximum and minimum temperature projections across the twenty-first century according to RCP4.5 and RCP8.5. An additional WRF simulation with even higher resolution (9 km) for RCP8.5 scenario is also examined. All simulations for the historical period (1971-2000) are evaluated against the available station observations and the EURO-CORDEX model results are ranked in order to build multi-model ensembles. In present climate models are able to reproduce the main topography/coast related temperature gradients. Although there are discernible differences between models, most present a cold bias. The multi-model ensembles improve the overall representation of the temperature. The ensembles project a significant increase of the maximum and minimum temperatures in all seasons and scenarios. Maximum increments of 8 °C in summer and autumn and between 2 and 4 °C in winter and spring are projected in RCP8.5. The temperature distributions for all models show a significant increase in the upper tails of the PDFs. In RCP8.5 more than half of the extended summer (MJJAS) has maximum temperatures exceeding the historical 90th percentile and, on average, 60 tropical nights are projected for the end of the century, whilst there are only 7 tropical nights in the historical period. Conversely, the number of cold days almost disappears. The yearly average number of heat waves increases by seven to ninefold by 2100 and the most frequent length rises from 5 to 22 days throughout the twenty-first century. 5% of the longest events will last for more than one month. The amplitude is overwhelming larger, reaching values which are not observed in the historical period. More than half of the heat waves will be stronger than the extreme heat wave of 2003 by the end of the century. The future heatwaves will also enclose larger areas, approximately 100 events in the 2071-2100 period (more than 3 per year) will cover the whole country. The RCP4.5 scenario has in general smaller magnitudes. [ABSTRACT FROM AUTHOR]

Canada has experienced some of the most rapid warming on Earth over the past few decades with a warming rate about twice that of the global mean temperature since 1948. Long-term warming is observed in Canada's annual, winter and summer mean temperatures, and in the annual coldest and hottest daytime and nighttime temperatures. The causes of these changes are assessed by comparing observed changes with climate model simulated responses to anthropogenic and natural (solar and volcanic) external forcings. Most of the observed warming of 1.7 °C increase in annual mean temperature during 1948-2012 [90% confidence interval (1.1°, 2.2 °C)] can only be explained by external forcing on the climate system, with anthropogenic influence being the dominant factor. It is estimated that anthropogenic forcing has contributed 1.0 °C (0.6°, 1.5 °C) and natural external forcing has contributed 0.2 °C (0.1°, 0.3 °C) to the observed warming. Up to 0.5 °C of the observed warming trend may be associated with low frequency variability of the climate such as that represented by the Pacific decadal oscillation (PDO) and North Atlantic oscillation (NAO). Overall, the influence of both anthropogenic and natural external forcing is clearly evident in Canada-wide mean and extreme temperatures, and can also be detected regionally over much of the country. [ABSTRACT FROM AUTHOR]

In recent decades the water resource of Nile river basin (NRB) has suffered from increasing demands from competing users, and global warming impact that exacerbate occurrences of hydrologic extremes. To investigate climate change impact on the future precipitation and temperature of NRB, a regional climate model, weather research and forecasting (WRF) was set up at one domain, 36-km resolution to dynamically downscale the base period (1976-2005), RCP4.5 and RCP8.5 climate scenarios of four General Circulation Model (GCMs) of CMIP5 over NRB for 2050s and 2080s. For base periods, WRF simulated surface temperature and precipitation that agree well with observed CRU and GPCC data of NRB, respectively. Under downscaled RCP4.5 and RCP8.5 climate scenarios, the annual precipitation of Blue Nile, Atbara, and Sobat river basin, Bahar El Ghazal and Lake Victoria regions are projected to change by about [− 7, 14.2], [− 19, 25.3], [− 7, 39], [− 5.9, 23], and [3.6, 27] % in the 2050s, and [− 14, 25], [− 22.5, 39], [− 4.7, 60.4], [− 11, 31], and [11.8, 41] % in the 2080s, respectively. The mean annual air temperature for sub-basins of NRB is projected to increase by 1.67-2 °C in the 2050s, 2-2.5 °C in the 2080s under RCP4.5, and by 2.5-3 °C in the 2050s and 3.9-4.6 °C in the 2080s under RCP8.5, respectively. Most precipitation extreme indices investigated are projected to increase, which implies that NRB could experience more severe and frequent extreme precipitation in future. Furthermore, extreme temperature indices of NRB are projected to decrease in cold, but increase in warm night/days. [ABSTRACT FROM AUTHOR]

Analyses of observed non-Gaussian daily minimum and maximum temperature probability distribution functions (PDFs) in the Southwest US highlight the importance of variance and warm tail length in determining future heat wave probability. Even if no PDF shape change occurs with climate change, locations with shorter warm tails and/or smaller variance will see a greater increase in heat wave probability, defined as exceedances above the historical 95th percentile threshold, than will long tailed/larger variance distributions. Projections from ten downscaled CMIP5 models show important geospatial differences in the amount of warming expected for a location. However, changes in heat wave probability do not directly follow changes in background warming. Projected changes in heat wave probability are largely explained by a rigid shift of the daily temperature distribution. In some locations where there is more warming, future heat wave probability is buffered somewhat by longer warm tails. In other parts of the Southwest where there is less warming, heat wave probability is relatively enhanced because of shorter tailed PDFs. Effects of PDF shape changes are generally small by comparison to those from a rigid shift, and fall within the range of uncertainty among models in the amount of warming expected by the end of the century. [ABSTRACT FROM AUTHOR]

This study focuses on the evaluation of daily precipitation and temperature climate indices and extremes simulated by an ensemble of 12 Regional Climate Model (RCM) simulations from the ARCTIC-CORDEX experiment with surface observations in the Canadian Arctic from the Adjusted Historical Canadian Climate Dataset. Five global reanalyses products (ERA-Interim, JRA55, MERRA, CFSR and GMFD) are also included in the evaluation to assess their potential for RCM evaluation in data sparse regions. The study evaluated the means and annual anomaly distributions of indices over the 1980-2004 dataset overlap period. The results showed that RCM and reanalysis performance varied with the climate variables being evaluated. Most RCMs and reanalyses were able to simulate well climate indices related to mean air temperature and hot extremes over most of the Canadian Arctic, with the exception of the Yukon region where models displayed the largest biases related to topographic effects. Overall performance was generally poor for indices related to cold extremes. Likewise, only a few RCM simulations and reanalyses were able to provide realistic simulations of precipitation extreme indicators. The multi-reanalysis ensemble provided superior results to individual datasets for climate indicators related to mean air temperature and hot extremes, but not for other indicators. These results support the use of reanalyses as reference datasets for the evaluation of RCM mean air temperature and hot extremes over northern Canada, but not for cold extremes and precipitation indices. [ABSTRACT FROM AUTHOR]

The Mediterranean region, located in the transition zone between the dry subtropical and wet European mid-latitude climate, is very sensitive to changes in the global mean climate state. Projecting future changes of the Mediterranean hydroclimate under global warming therefore requires dynamic climate models to reproduce the main mechanisms controlling regional hydroclimate with sufficiently high resolution to realistically simulate climate extremes. To assess future winter precipitation changes in the Mediterranean region we use the Geophysical Fluid Dynamics Laboratory high-resolution general circulation model for control simulations with pre-industrial greenhouse gas and aerosol concentrations which are compared to future scenario simulations. Here we show that the coupled model is able to reliably simulate the large-scale winter circulation, including the North Atlantic Oscillation and Eastern Atlantic patterns of variability, and its associated impacts on the mean Mediterranean hydroclimate. The model also realistically reproduces the regional features of daily heavy rainfall, which are absent in lower-resolution simulations. A five-member future projection ensemble, which assumes comparatively high greenhouse gas emissions (RCP8.5) until 2100, indicates a strong winter decline in Mediterranean precipitation for the coming decades. Consistent with dynamical and thermodynamical consequences of a warming atmosphere, derived changes feature a distinct bipolar behavior, i.e. wetting in the north—and drying in the south. Changes are most pronounced over the northwest African coast, where the projected winter precipitation decline reaches 40% of present values. Despite a decrease in mean precipitation, heavy rainfall indices show drastic increases across most of the Mediterranean, except the North African coast, which is under the strong influence of the cold Canary Current. [ABSTRACT FROM AUTHOR]

A gridded, geographically extended weather type classification has been developed based on the Jenkinson-Collison (JC) classification system and used to evaluate the representation of weather types over Europe in a suite of climate model simulations. To this aim, a set of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) is compared with the circulation from two reanalysis products. Furthermore, we examine seasonal changes between simulated frequencies of weather types at present and future climate conditions. The models are in reasonably good agreement with the reanalyses, but some discrepancies occur in cyclonic days being overestimated over North, and underestimated over South Europe, while anticyclonic situations were overestimated over South, and underestimated over North Europe. Low flow conditions were generally underestimated, especially in summer over South Europe, and Westerly conditions were generally overestimated. The projected frequencies of weather types in the late twenty-first century suggest an increase of Anticyclonic days over South Europe in all seasons except summer, while Westerly days increase over North and Central Europe, particularly in winter. We find significant changes in the frequency of Low flow conditions and the Easterly type that become more frequent during the warmer seasons over Southeast and Southwest Europe, respectively. Our results indicate that in winter the Westerly type has significant impacts on positive anomalies of maximum and minimum temperature over most of Europe. Except in winter, the warmer temperatures are linked to Easterlies, Anticyclonic and Low Flow conditions, especially over the Mediterranean area. Furthermore, we show that changes in the frequency of weather types represent a minor contribution of the total change of European temperatures, which would be mainly driven by changes in the temperature anomalies associated with the weather types themselves. [ABSTRACT FROM AUTHOR]

Climate change simulation based on 30-member ensemble of Voeikov Main Geophysical Observatory RCM (resolution 25 km) for northern Eurasia is used to drive hydrological model CaMa-Flood. Using this modeling framework, we evaluate the uncertainties in the future projection of the peak river discharge and flood hazard by 2050-2059 relative to 1990-1999 under IPCC RCP8.5 scenario. Large ensemble size, along with reasonably high modeling resolution, allows one to efficiently sample natural climate variability and increase our ability to predict future changes in the hydrological extremes. It has been shown that the annual maximum river discharge can almost double by the mid-XXI century in the outlets of major Siberian rivers. In the western regions, there is a weak signal in the river discharge and flood hazard, hardly discernible above climate variability. Annual maximum flood area is projected to increase across Siberia mostly by 2-5% relative to the baseline period. A contribution of natural climate variability at different temporal scales to the uncertainty of ensemble prediction is discussed. The analysis shows that there expected considerable changes in the extreme river discharge probability at locations of the key hydropower facilities. This suggests that the extensive impact studies are required to develop recommendations for maintaining regional energy security. [ABSTRACT FROM AUTHOR]

Climate change is expected to have severe impacts on natural systems as well as various socio-economic aspects of human life. This has urged scientific communities to improve the understanding of future climate and reduce the uncertainties associated with projections. In the present study, ten statistically downscaled CMIP5 GCMs at 1/16th deg. spatial resolution from two different downscaling procedures are utilized over the Columbia River Basin (CRB) to assess the changes in climate variables and characterize the associated uncertainties. Three climate variables, i.e. precipitation, maximum temperature, and minimum temperature, are studied for the historical period of 1970-2000 as well as future period of 2010-2099, simulated with representative concentration pathways of RCP4.5 and RCP8.5. Bayesian Model Averaging (BMA) is employed to reduce the model uncertainty and develop a probabilistic projection for each variable in each scenario. Historical comparison of long-term attributes of GCMs and observation suggests a more accurate representation for BMA than individual models. Furthermore, BMA projections are used to investigate future seasonal to annual changes of climate variables. Projections indicate significant increase in annual precipitation and temperature, with varied degree of change across different sub-basins of CRB. We then characterized uncertainty of future projections for each season over CRB. Results reveal that model uncertainty is the main source of uncertainty, among others. However, downscaling uncertainty considerably contributes to the total uncertainty of future projections, especially in summer. On the contrary, downscaling uncertainty appears to be higher than scenario uncertainty for precipitation. [ABSTRACT FROM AUTHOR]

Simulations from 35 global climate models (GCMs) in the Coupled Model Intercomparison Project Phase 5 provide projections of 21st century climate in the Columbia River Basin under scenarios of anthropogenic activity given by Representative Concentration Pathways (RCP4.5 and RCP8.5). The multi-model ensemble 30-year mean annual temperature increases by 2.8 °C (5.0 °C) by late 21st century under RCP4.5 (RCP8.5) over the 1979-1990 baseline, with 18% (24%) more warming in summer. By late 21st century, annual precipitation increases by 5% (8%), with an 8% (14%) winter increase and a 4% (10%) summer decrease, but because some models project changes of opposite sign, confidence in these sign changes is lower than those for temperature. Four questions about temperature and precipitation changes were addressed: (1) How and why do climate projections vary seasonally? (2) Is interannual variability in seasonal temperature and precipitation projected to change? (3) What explains the large inter-model spread in the projections? (4) Do projected changes in climate depend on model skill? Changes in precipitation and temperature vary seasonally as a result of changes in large-scale circulation and regional surface energy budget, respectively. Interannual temperature variability decreases slightly during the cool seasons and increases in summer, while interannual precipitation variability increases in all seasons. The magnitude of regional warming is linked to models' global climate sensitivity, whereas internal variability dominates the inter-model spread of precipitation changes. Lastly, GCMs that better reproduce historical climate tend to project greater warming and larger precipitation increases, though these results depend on the evaluation method. [ABSTRACT FROM AUTHOR]

The most severe effects of global warning will be related to the frequency and severity of extreme events. We provide an analysis of projections of temperature and related extreme events for Africa based on a large ensemble of Regional Climate Models from the COordinated Regional climate Downscaling EXperiment (CORDEX). Results are presented not only by means of widely used indices but also with a recently developed Heat Wave Magnitude Index-daily (HWMId), which takes into account both heat wave duration and intensity. Results show that under RCP8.5, warming of more than 3.5 °C is projected in JFM over most of the continent, whereas in JAS temperatures over large part of Northern Africa, the Sahara and the Arabian peninsula are projected to increase up to 6 °C. Large increase in in the number of warm days (Tx90p) is found over sub equatorial Africa, with values up to more than 90 % in JAS, and more than 80 % in JFM over e.g., the gulf of Guinea, Central African Republic, South Sudan and Ethiopia. Changes in Tn90p (warm nights) are usually larger, with some models projecting Tn90p reaching 95 % starting from around 2060 even under RCP4.5 over the Gulf of Guinea and the Sahel. Results also show that the total length of heat spells projected to occur normally (i.e. once every 2 years) under RCP8.5 may be longer than those occurring once every 30 years under the lower emission scenario. By employing the recently developed HWMId index, it is possible to investigate the relationship between heat wave length ad intensity; in particular it is shown that very intense heat waves such as that occurring over the Horn of Africa may have values of HWMId larger than that of longer, but relatively weak, heat waves over West Africa. [ABSTRACT FROM AUTHOR]

This study investigates the effect of reduced aerosol emissions on projected temperature and precipitation extremes in China during 2031-2050 and 2081-2100 relative to present-day conditions using the daily data output from the Community Earth System Model ensemble simulations under the Representative Concentration Pathway (RCP) 8.5 with an applied aerosol reduction and RCP8.5 with fixed 2005 aerosol emissions (RCP8.5_FixA) scenarios. The reduced aerosol emissions of RCP8.5 magnify the warming effect due to greenhouse gases (GHG) and lead to significant increases in temperature extremes, such as the maximum of daily maximum temperature (TXx), minimum of daily minimum temperature (TNn), and tropical nights (TR), and precipitation extremes, such as the maximum 5-day precipitation amount, number of heavy precipitation days, and annual total precipitation from days ˃95th percentile, in China. The projected TXx, TNn, and TR averaged over China increase by 1.2 ± 0.2 °C (4.4 ± 0.2 °C), 1.3 ± 0.2 °C (4.8 ± 0.2 °C), and 8.2 ± 1.2 (30.9 ± 1.4) days, respectively, during 2031-2050 (2081-2100) under the RCP8.5_FixA scenario, whereas the corresponding values are 1.6 ± 0.1 °C (5.3 ± 0.2 °C), 1.8 ± 0.2 °C (5.6 ± 0.2 °C), and 11.9 ± 0.9 (38.4 ± 1.0) days under the RCP8.5 scenario. Nationally averaged increases in all of those extreme precipitation indices above due to the aerosol reduction account for more than 30 % of the extreme precipitation increases under the RCP8.5 scenario. Moreover, the aerosol reduction leads to decreases in frost days and consecutive dry days averaged over China. There are great regional differences in changes of climate extremes caused by the aerosol reduction. When normalized by global mean surface temperature changes, aerosols have larger effects on temperature and precipitation extremes over China than GHG. [ABSTRACT FROM AUTHOR]

The Loess Plateau is particularly sensitive to climate change owing to its fragile ecological environment and geographic features. Here, we present a comprehensive analysis of the joint probabilistic characteristics and tendencies for bivariate and trivariate precipitation and temperature indices across the plateau, based on copula theory. The results show that the southeast region of the plateau had a higher potential for flooding: the 10-year return levels for the number of days with heavy and very heavy precipitation (R10mm, R20mm) and for the maximum 5-day precipitation value (RX5day) were higher in this region. The northwest region of the plateau, however, had a higher potential for drought, as reflected in the high and increasing 10-year return levels for the number of consecutive dry days (CDD) and the number of days with low precipitation (R1mm). In a joint analysis of precipitation indices, large areas of the Loess Plateau showed a relatively high risk of concurrent extreme precipitation events. However, the risk of concurrent extreme wet and dry events did not increase over the past half century, as demonstrated by nonsignificant changes in the probability of concurrently long CDD and long consecutive wet days (CWD). A trivariate copula analysis showed that some grid locations in the southeast of the plateau had an increasing risk of extreme precipitation events occurring at a high frequency and a high intensity, and forming a large percentage of the annual precipitation. Joint analysis of precipitation and temperature indices showed that the risk of higher temperatures and longer spells of consecutive dry days had increased over the past 50 years in grid locations scattered in the northern and southern regions: there were negative trends in the bivariate return periods for warm days (TX90p) and CDD. In addition, there was a decreased probability of concurrent long spells of consecutive wet days and colder temperatures, as demonstrated by the positive trends in the bivariate return periods for cold days (TX10p) and CWD across large areas of the plateau. Overall, the risk of severe floods and droughts over the Loess Plateau increased over the period 1961-2011. [ABSTRACT FROM AUTHOR]

Cold temperature and associated extremes often impact adversely human health and environment and bring disruptions in economic activities during winter over Canada. This study investigates projected changes in winter (December to March) period cold extreme days (i.e., cold nights, cold days, frost days, and ice days) and cold spells over Canada based on 11 regional climate model (RCM) simulations for the future 2040-2069 period with respect to the current 1970-1999 period. These simulations, available from the North American Regional Climate Change Assessment Program, were obtained with six different RCMs, when driven by four different Atmosphere-Ocean General Circulation Models, under the Special Report on Emissions Scenarios A2 scenario. Based on the reanalysis boundary conditions, the RCM simulations reproduce spatial patterns of observed mean values of the daily minimum and maximum temperatures and inter-annual variability of the number of cold nights over different Canadian climatic regions considered in the study. A comparison of current and future period simulations suggests decreases in the frequency of cold extreme events (i.e., cold nights, cold days and cold spells) and in selected return levels of maximum duration of cold spells over the entire study domain. Important regional differences are noticed as the simulations generally indicate smaller decreases in the characteristics of extreme cold events over western Canada compared to the other regions. The analysis also suggests an increase in the frequency of midwinter freeze-thaw events, due mainly to a decrease in the number of frost days and ice days for all Canadian regions. Especially, densely populated southern and coastal Canadian regions will require in depth studies to facilitate appropriate adaptation strategies as these regions are clearly expected to experience large increases in the frequency of freeze-thaw events. [ABSTRACT FROM AUTHOR]

In this paper, a stochastic model is used to simulate daily minimum temperature time series coming from observations and two CMIP5 climate models (IPSL-CM5A-MR and CNRM-CM5) in order to analyze the changes in cold wave number and proportions under future climate conditions. The stochastic model allows computing 100 temperature time series for each different source (observation or climate model), and for 22 locations in France, which enables inferring the statistical significance of the changes. Two future time periods, near (around 2010-2060) and far future (around 2050-2100), and two RCPs (RCP4.5 and RCP8.5) are considered, while 3 different thresholds are used to identify cold waves: 0 °C and the 10th and 5th percentiles of observed wintertime (December-January-February) daily minimum temperature distribution. The results show that both models project a significantly lower number of cold waves in the future, all durations considered, but the changes mainly concern the proportion of the longest cold waves (10 days and more). The decreases are higher with IPSL-CM5A-MR than with CNRM-CM5. The main driver of this change is the decreasing frequency of the observation based thresholds in the future, which is higher for IPSL-CM5-MR model because the impact of a higher mean is enhanced by a decrease in the variance. [ABSTRACT FROM AUTHOR]

The two main focuses of this study are a comparison of the general circulation models (GCMs) from Phase 5 of the Coupled Model Inter-Comparison Project (CMIP5) and an assessment of the surface air temperature under multiple climate scenarios in a high middle latitude area of China. In the past 55 years temperatures in this area have shown an obvious upward trend (a rise of 1.50 °C), and another important change during this time period was a significant alteration in tillage practices that occurred in 1986. Using methods and tools such as average deviation, the Taylor figure and the space techniques rating (SS), time sequence related coefficient, and the M2 index, a comprehensive spatial-temporal assessment was performed based on the CMIP5 models. The simulations provided by the models had certain common features, but there were also significant differences. The three best models (CanCM4, INMCM4, and IPSL-CM5A-MR) have a common characteristic: the institutions where they were developed are located at latitudes that are similar to or higher than the latitude of the study area. Future climate changes were analyzed by simulating a representative concentration pathway 4.5/8.5 (RCP4.5/RCP8.5) of emission scenarios with a multi-model ensemble. The temperatures under the RCP4.5 and RCP8.5 scenarios have a certain upward trend, with increases of 2.24 and 5.44 °C, respectively. From a spatial perspective, the distributions of the temperature change trend showed a southwest to northeast step increase under both scenarios, but the warming trend in the area of each lattice point under the RCP4.5 scenario is much lower than that of the RCP8.5 scenario. There are no obvious changes in the spatial distribution of the accumulated intensity and frequency of the regional air temperature in the three periods (2016-2035, 2036-2065, and 2066-2095) under the two scenarios. [ABSTRACT FROM AUTHOR]

Extreme hot spells can have significant impacts on human society and ecosystems, and therefore it is important to assess how these extreme events will evolve in a changing climate. In this study, the impact of climate change on hot days, hot spells, and heat waves, over 10 climatic regions covering Canada, based on 11 regional climate model (RCM) simulations from the North American Regional Climate Change Assessment Program for the June to August summer period is presented. These simulations were produced with six RCMs driven by four Atmosphere-Ocean General Circulation Models (AOGCM), for the A2 emission scenario, for the current 1970-1999 and future 2040-2069 periods. Two types of hot days, namely HD-1 and HD-2, defined respectively as days with only daily maximum temperature (Tmax) and both Tmax and daily minimum temperature (Tmin) exceeding their respective thresholds (i.e., period-of-record 90th percentile of Tmax and Tmin values), are considered in the study. Analogous to these hot days, two types of hot spells, namely HS-1 and HS-2, are identified as spells of consecutive HD-1 and HD-2 type hot days. In the study, heat waves are defined as periods of three or more consecutive days, with Tmax above 32 °C threshold. Results suggest future increases in the number of both types of hot days and hot spell events for the 10 climatic regions considered. However, the projected changes show high spatial variability and are highly dependent on the RCM and driving AOGCM combination. Extreme hot spell events such as HS-2 type hot spells of longer duration are expected to experience relatively larger increases compared to hot spells of moderate duration, implying considerable heat related environmental and health risks. Regionally, the Great Lakes, West Coast, Northern Plains, and Maritimes regions are found to be more affected due to increases in the frequency and severity of hot spells and/or heat wave characteristics, requiring more in depth studies for these regions to facilitate appropriate adaptation measures. [ABSTRACT FROM AUTHOR]

In the framework of the coordinated regional climate downscaling experiment (CORDEX), an ensemble of climate change projections for Africa has been created by downscaling the simulations of four global climate models (GCMs) by means of the consortium for small-scale modeling (COSMO) regional climate model (RCM) (COSMO-CLM, hereafter, CCLM). Differences between the projected temperature and precipitation simulated by CCLM and the driving GCMs are analyzed and discussed. The projected increase of seasonal temperature is found to be relatively similar between GCMs and RCM, although large differences (more than 1 °C) exist locally. Differences are also found for extreme-event related quantities, such as the spread of the upper end of the maximum temperature probability distribution function and, in turn, the duration of heat waves. Larger uncertainties are found in the future precipitation changes; this is partly a consequence of the inter-model (GCMs) variability over some areas (e.g. Sahel). However, over other regions (e.g. Central Africa) the rainfall trends simulated by CCLM and the GCMs show opposite signs, with CCLM showing a significant reduction in precipitation at the end of the century. This uncertain and sometimes contrasting behaviour is further investigated by analyzing the different models' response to the land-atmosphere interaction and feedback. Given the large uncertainty associated with inter-model variability across GCMs and the reduced spread in the results when a single RCM is used for downscaling, we strongly emphasize the importance of exploiting fully the CORDEX-Africa multi-GCM/multi-RCM ensemble in order to assess the robustness of the climate change signal and, possibly, to identify and quantify the many sources of uncertainty that still remain. [ABSTRACT FROM AUTHOR]

We investigate heat waves defined as periods of at least 3 consecutive days of extremely high daily maximum temperature affecting at least 30 % of western Europe. This definition has been chosen to select heat waves that might impact western European electricity supply. Even though not all such heat waves threaten it, the definition allows to identify a sufficient number of events, the strongest being potentially harmful. The heat waves are characterised by their duration, spatial extent, intensity and severity. The heat wave characteristics are calculated for historical and future climate based on results of climate model simulations conducted during the 5th Phase of the Coupled Model Intercomparison Project (CMIP5). The uncertainty of future anthropogenic forcing is taken into account by analysing results for the Representative Concentration Pathway scenarios RCP2.6, RCP4.5 and RCP8.5. The historical simulations are evaluated against the EOBS gridded station data. The CMIP5 ensemble median captures well the observed mean heat wave characteristics. However, no model simulates a heat wave as severe as observed during August 2003. Under future climate conditions, the heat waves become more frequent and have higher mean duration, extent and intensity. The ensemble spread is larger than the scenario uncertainty. The shift of the temperature distribution is more important for the increase of the cumulative heat wave severity than the broadening of the temperature distribution. However, the broadening leads to an amplification of the cumulative heat wave severity by a factor of 1.7 for RCP4.5 and 1.5 for RCP8.5. [ABSTRACT FROM AUTHOR]

Australian rainfall is strongly influenced by El Niño-southern oscillation (ENSO). The relationship between ENSO and rainfall in eastern Australia is non-linear; the magnitude of La Niña events has a greater effect on rainfall than does the magnitude of El Niño events, and the cause of the non-linearity is unclear from previous work. The twentieth century reanalysis succeeds in capturing the asymmetric ENSO-rainfall relationship. In the reanalysis the asymmetry is strongly related to moisture availability in the south-west Pacific whereas wind flow is of less importance. Some global climate models (GCMs) in the coupled model intercomparison project (CMIP5) archive capture the asymmetric nature of the ENSO-rainfall relationship whilst others do not. Differences in thermodynamic processes and their relationships with ENSO are the primary cause of variability in model performance. Analysis of an atmosphere-only run of a GCM which fails to capture the non-linear ENSO-rainfall relationship is also conducted. The atmospheric run forced by observed sea surface temperatures shows no significant improvement in the ENSO-rainfall relationship over the corresponding coupled model run in the CMIP5 archive. This result suggests that some models are failing to capture the atmospheric teleconnection between the tropical Pacific and Australia, and both this and a realistic representation of oceanic ENSO characteristics are required for coupled models to accurately capture the ENSO-rainfall teleconnection. These findings have implications for the study of rainfall projections in the region. [ABSTRACT FROM AUTHOR]