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Groundwater is an essential resource for agriculture and domestic use in drought-prone regions, particularly in northwestern Bangladesh. Accurate forecast of groundwater level (GWL) fluctuations is crucial for sustainable water regulation. This work investigates the application of deep learning and dynamic system response models to forecast GWL changes in this vulnerable area. The models employed include Long Short-Term Memory (LSTM) networks, Autoregressive Moving Average (ARMA), Discrete-Time State-Space Model (n4sid), Continuous-Time State-Space Model (SSEST), Discrete-Time State-Space Model through a Regularized ARX Model Reduction (SSREGEST), and coupled ARMA-state-space models. A total of eight models were trained and tested on historical GWL data from 19 observation wells. The top-performing models at various locations delivered satisfactory results, with C, IOA, NRMSE, and MAD values ranging from 0.53 to 0.92, 0.62 to 0.95, 0.01 to 0.25, and 0.08 m to 1.09 m, respectively. Model comparison using the Entropy-Distance from Average Solution (Entropy-EDAS) method revealed that LSTM networks outperformed traditional time series (ARMA), system dynamic (n4sid, SSEST, SSREGEST), and coupled ARMA-state-space models (ARMA-n4sid, ARMA-SSEST, and ARMA-SSREGEST) in most locations, while other models exhibited varying performances across different observation wells. The varying performance across different observation wells highlights that prediction accuracy depends not only on the modeling algorithms but also on the quantity and quality of the learning and testing data. The projections generated by the best models effectively captured historical trends, providing the first-ever five-year forecasts of GWL fluctuations for the region. These projections offer valuable insights for water resource management and planning in areas vulnerable to drought and climate variability. [ABSTRACT FROM AUTHOR]

Monsoons are a vital part of the agriculture and economy of India which most of its population rely on for their livelihoods. It still is not clear how climate change will impact precipitation events over India due to the complexity of accurately modelling precipitation. Using twelve Coupled Model Intercomparison Project Six (CMIP6) models, we compared their performance to observed data taken from CRU as well as looking at the future changes in precipitation until the end of the twenty first century for the six precipitation homogenous regions over India. The individual models showed varying degrees of wet and dry biases and the ensemble mean of these models showed relatively lesser bias and improved spatial correlation. Out of 12 models, NorESM and MIROC6 models outperform other models in terms of capturing the spatial variability of precipitation over the Indian region. It is also found that due to lesser moisture transport from the adjoining seas represented through vertically integrated moisture transport (VIMT) analysis, there is consistent dry bias across the models. Further a comprehensive analysis of model performance across six homogeneous precipitation regions indicates that NorESM demonstrates better performance in the CNE and HR regions, EC-Earth excels in the PR, WC, and NE regions, while CMCC shows better performance specifically in the NW region compared to other models. Shared Socioeconomic Pathways (SSPs) were used for future projections and a slight increase in June, July, August, and September (JJAS) precipitation until the end of the century with SSP5-8.5 showing the largest increase. We found an increase in precipitation of 0.49, 0.74 and 1.4 mm/day under SSP1-2.6, SSP2-4.5 and SSP5-8.5 in the far future. The northeast region was shown to receive the largest increase in precipitation (2.9 mm/day) compared to other precipitation homogenous regions and northwest will experience largest shift in precipitation. Interestingly, the number of wet days is expected to increase in the northwest region implying more VIMT towards the region. Our results indicate that monsoon precipitation extremes across all the homogenous regions will increase into the future with a higher severity under fossil-fuelled development, although the models still show large biases lowering confidence in our results. [ABSTRACT FROM AUTHOR]

We compared the projected results of future hydrological changes (from 2040 to 2050) based on a 30-year weather dataset (1984–2014) in 7 rain gauges in the Jazmurian watershed with paleoclimatic changes inferred from established proxies in the region. By drawing parallels between anticipated future changes and past climatic conditions, we aim to develop a general understanding of how climate change may alter precipitation patterns in the watershed. The region is influenced by the Indian Ocean Summer Monsoon (IOSM) as well as the Mid-Latitude Westerlies (MLW). Precipitation projections for the future are derived using statistical downscaling outputs from IPCC Sixth Report models (CMIP6) under various Shared Socioeconomic Pathway (SSP) scenarios. In the western watershed, the CanESM5 model forecasts a decrease in MLW precipitation (32–20%) and an increase in IOSM precipitation (157–253%), leading to an overall rise of 0–28%. Conversely, the eastern section shows variable MLW precipitation changes (– 19% to + 20%) and a projected increase in IOSM precipitation (21–405%), resulting in a 9–120% rise. In the western region, the MPI-ESM1-2-HR model predicts a decline in MLW precipitation (30–3%) and an increase in IOSM precipitation (142–189%), with an overall rise of 9–22%. In the east, there is a decrease in MLW precipitation (23–9%) and an increase in IOSM precipitation (252–437%), leading to a rise of 44–91%. Future precipitation in the Jazmurian watershed is projected to increase despite potential decreases in MLW precipitation. Results suggest increases in the present low IOSM precipitation, leading to overall precipitation rises by 2050 compared to the historical levels. These findings highlight a trend towards wetter conditions, with the SSP 370 scenario showing the most significant rise in IOSM precipitation. The decrease in Mediterranean precipitation is consistent with findings from other GCMs and aligns with historical climate variations observed during previous warm and humid phases in the region. Nevertheless, given the strong correlation between the rise in the Earth's radiation budget and increased monsoon rainfall in the Jazmurian watershed since the late Pleistocene, we anticipate a significant rise in IOSM activity.Highlights: Findings indicate a trend towards wetter conditions across the Jazmurian watershed. GCMs forecast a decrease in MLW precipitation while IOSM precipitation increases over the region. The SSP 370 scenario shows the most significant rise in IOSM precipitation. Multi-proxy data displays intense paleo IOSM activity during past warm/wet periods in the region. Decreases in MLW precipitation align with past warm/wet period climate shifts. [ABSTRACT FROM AUTHOR]

Multi-decadal trends in the wintertime North Atlantic Oscillation (NAO) are under-represented by coupled general circulation models (CGCMs), consistent with a lack of autocorrelation in their NAO index series. This study proposes and tests two simple "reddening" approaches for correcting this problem in simulated indices based on simple one parameter short-term (AR; Auto-Regressive order 1) and long-term (FD; Fractional-Difference) time series filters. Using CGCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6), the FD filter successfully improves the autocorrelation structure of the NAO, and in turn the simulation of extreme trends, while the AR filter is less successful. The 1963–1993 NAO trend is the maximum 31-year trend in the historical period. Raw CGCMs underestimate the likelihood of this trend by a factor of ten but this discrepancy is corrected after reddening. CMIP6 future projections show that long-term (2024–2094) NAO ensemble mean trends systematically increase with the magnitude of radiative forcing: -2.4 to 3.5 hPa/century for low-to-high forcing after reddening (more than double the range using raw output). The related likelihood of future maximum 31year trends comparable to 1963–1993 ranges from 3 to 7% whereas none of these CMIP6 projections simulate this without reddening. Near-term projections of the next 31 years (2024–2054) are less sensitive than long term trends to the future scenario, showing weak-to-no forced trend. However, reddening increases the ensemble range by 74% (to +/-1 standard deviation/decade), which could increase/decrease regional climate change signals in the Northern Hemisphere by magnitudes that are underestimated when using raw CGCM output. [ABSTRACT FROM AUTHOR]

This study evaluates the performance of 16 models sourced from the coupled model intercomparison project phase 6 (CMIP6) in simulating marine heatwaves (MHWs) in the South China Sea (SCS) during the historical period (1982–2014), and also investigates future changes in SCS MHWs based on simulations from three shared socioeconomic pathway (SSP) scenarios (SSP126, SSP245, and SSP585) using CMIP6 models. Results demonstrate that the CMIP6 models perform well in simulating the spatial-temporal distribution and intensity of SCS MHWs, with their multi-model ensemble (MME) results showing the best performance. The reasonable agreement between the observations and CMIP6 MME reveals that the increasing trends of SCS MHWs are attributed to the warming sea surface temperature trend. Under various SSP scenarios, the year 2040 emerges as pivotal juncture for future shifts in SCS MHWs, marked by distinct variations in changing rate and amplitudes. This is characterized by an accelerated decrease in MHWs frequency and a notably heightened increase in mean intensity, duration, and total days after 2040. Furthermore, the projection results for SCS MHWs suggest that the spatial pattern of MHWs remains consistent across future periods. However, the intensity shows higher consistency only during the near-term period (2021–2050), while notable inconsistencies are observed during the medium-term (2041–2070) and long-term (2071–2100) periods under the three SSP scenarios. During the near-term period, the SCS MHWs are characterized by moderate and strong events with high frequencies and relatively shorter durations. In contrast, during the medium-term period, MHWs are also characterized by moderate and strong events, but with longer-lasting and more intense events under the SSP245 and SSP585 scenarios. However, in the long-term period, extreme MHWs become the dominant feature under the SSP585 scenario, indicating a substantial intensification of SCS MHWs, effectively establishing a near-permanent state. [ABSTRACT FROM AUTHOR]

Marine heatwaves (MHWs) are oceanic conditions characterized by extremely high sea surface temperature (SST) anomalies that last for several days to years. Because MHWs have devastating effects on marine ecosystems and significant impacts on fisheries, understanding future MHWs is important for adapting to upcoming climate changes. In this study, we examined future changes in MHWs in the northwestern Pacific Ocean (18–53ºN, 117ºE–170ºW) under two CO2 emission scenarios using a high-resolution ensemble (four members for each scenario) simulation product using a high-resolution ocean model that satisfactorily resolves the Kuroshio, Kuroshio Extension, and SST fronts. Following global warming, MHWs based on a threshold in the historical period (1981–2005) will increase and intensify (i.e., occur with higher SST anomalies than before). In the historical period, the annual MHW days ranged from 20 to 34 days. Annual MHW days increase to 63–313 days (188 days–all year round) depending on the region under the high CO2 mitigation (emission) scenario at the end of the twenty-first century of 2076–2100. Furthermore, we investigated the spatial details of future MHWs. Future MHWs reflect the magnitude of SST variability in addition to that of sea surface warming in the twenty-first century; future MHWs are less frequent and more intense in the subtropical–subarctic frontal zone with large SST variability than in other regions. [ABSTRACT FROM AUTHOR]

Based on the multi-model ensemble mean of CMIP6 simulations, the future changes in frequency, intensity and duration of Compound (both daytime and nighttime) heatwaves (HWs) in summer over China at various global warming levels (GWLs) under the SSP3-7.0 and SSP5-8.5 are assessed. HWs over China become more frequent and hotter, and the duration of HWs becomes longer compared to those in the recent climate. The magnitudes of these changes are primarily dependent on GWLs, but they are not very sensitive to the scenarios. At 4 ℃ GWL, the frequency of HWs increases by more than fivefold under both scenarios, and the intensity (duration) of HWs averaged under the two scenarios is 2.28 ℃ hotter (3.59 days longer) than the one in the recent climate over the entire China. Meanwhile, the maximum duration of HW events can reach more than 25 days in summer in comparison with 8 days in the recent climate. The changes in HW properties are regionally dependent at the four GWLs. For example, the largest increase in HW frequency is over the Northwest China, the largest increase in intensity in HWs is seen over the Northeast and Northwest, and the largest increase in HW duration is over the Southwest China. The extreme rare events (50-year and 100-year events) in the recent climate would become the norm over China and four sub-regions at 4 ℃ GWL. Overall, seasonal mean warming dominates the changes in HW properties over China at the different GWLs. The seasonal mean warming in summer across China is related to the increases of longwave radiation, partly due to increase in greenhouse gas forcing and partly resulted from increased water vapor and the increase of shortwave radiation (under the SSP5-8.5) over eastern China related to decreases in aerosols and total cloud cover. Furthermore, the regional variations in the water vapor over China are consistent with atmospheric circulation changes. The seasonal mean surface warming results in enhanced upward sensible and latent heat fluxes, leading to increased summer mean daily maximum and minimum of near-surface air temperature and the enhancement of HWs properties over the entire China. Changes of shortwave radiation tend to play a weaker role for surface warming under the SSP3-7.0 than those under the SSP5-8.5, which is related to increased aerosol changes under the SSP3-7.0. [ABSTRACT FROM AUTHOR]

Extreme precipitation events (EPEs) and heatwaves (HWs) can trigger floods, droughts, and other natural disasters, resulting in severe socioeconomic losses in eastern China. However, the accurate links between EPEs and HWs and future changes in these extremes are not fully resolved, which potentially impedes disaster warning and preparedness efforts. This study examines historical and future changes in summer EPEs and HWs in eastern China based on observations and model outputs from the Coupled Model Intercomparison Project Phase 6. The results show that EPEs and HWs in eastern China have increased in the past four decades and are projected to rise in the future. According to multi-model projections, the Yangtze River Basin, along with areas to its south, are expected to experience an increase in compound disasters due to HWs and EPEs. High values of the multi-year mean total population exposure to EPEs and HWs are observed in the North China Plain, Yangtze River Delta, Sichuan Basin, and southeast coast. The total population exposure to EPEs shows a decreasing trend under Shared Socioeconomic Pathway (SSP) 245 and SSP585 scenarios during 2021–2100, consistent with future population decline. However, the annual total population exposure to HWs will increase, reaching nearly 3.0 billion and 5.0 billion by the end of the century under the SSP245 and SSP585 scenarios, respectively. Within the context of global warming, the relationship between the mean-state of precipitation and maximum temperature as well as the relationship between extreme precipitation and heatwaves shift from negative correlation in the historical period to positive correlation in future projections for eastern China. [ABSTRACT FROM AUTHOR]

In this study, Bezier search differential evolution (BeSD) and black widow optimization (BWO) algorithms-based estimation models in different forms have been developed to estimate the transportation energy consumption in Turkey. In order to examine the effect of demand distribution in modes of transportation on energy consumption, parameters in modes of transportation which are Passenger-km and Freight-km, Carbon dioxide emissions, Gross Domestic Product and Infrastructure Investment parameters are used as model parameters. Model performances are evaluated within different error criteria, and their performances are revealed. The BeSD algorithm performed better than the BWO algorithm and revealed that it is the most appropriate method for transportation energy demand (TED) estimation. Although each model developed using two different approaches is usable, BeSD-based quadratic model has shown the highest performance with a 0.95% MAPE value, and TED's predictions for the future have been put forth based on this model. According to two different scenarios, TED projections until 2040 are presented for cases in which the current distribution of demand in modes of transportation and there is a demand shift from highway to other modes of transportation. The projections of the parameters have been determined by the least squares method. In the first scenario, it has been predicted that there will be 63 MTOE energy demand in 2040, and the projection values are consistent with the Ministry of Energy and Natural Resources values. In the second scenario, when demand shifts from the highway to other modes of transportation, it is predicted that energy consumption will decrease and there will be 42 MTOE in 2040. [ABSTRACT FROM AUTHOR]

The Indian summer monsoon rainfall (ISMR, June–September) is an important factor in agricultural planning and the Indian economy. The ISMR over East India (EI: Chhattisgarh-Bihar-Jharkhand-Odisha) is particularly significant, and it can have an impact on the country's average ISMR. The current study examined projected changes in ISMR over EI with two emission scenarios, RCP4.5 and RCP8.5, for near (2017–2040) and far-future (2041–2070) projections using a set of ten CORDEX-SA Regional Climate Model (RCMs). To begin, the performance of raw and bias-corrected ISMR over EI outputs from ten CORDEX-SA RCMs was compared to a high-resolution (0.25° × 0.25°) gridded rainfall analysis dataset from the India Meteorological Department (IMD) over the hindcast period (1971–2005). Following that, bias-corrected results were used to calculate ISMR projections over EI for the near and distant futures. Most RCMs, according to the findings, can imitate the spatial pattern of ISMR across EI but are restricted in their ability to capture actual magnitudes. Notably, RCM prediction skill increased greatly after employing various bias-correction approaches, the quantile mapping (QQM) bias-correction technique outperformed other current conventional bias correction methods, and the QQM technique was employed for ISMR future projections using RCP4.5 and RCP8.5 emission scenarios. The analysis of ISMR projections over EI reveals that there will be more deficit rainfall years in the short term while more excess rainfall years in the far future. [ABSTRACT FROM AUTHOR]

This study assesses the response of hydrological processes to climate change in an Eastern Himalayan river basin using the SWAT model forced by high-resolution NEX-GDDP dataset. The SWAT model was set up to simulate streamflow under data-scarce scenario. Snow and elevation-related parameters for snow-dominated sub-basins were included during the model set-up to account for snow dynamics in the region. The model calibration and parametrisation as well as sensitivity analysis were performed using SWAT-CUP SUFI2 algorithm. Sensitivity analysis revealed that 19 parameters were sensitive for the region. The curve number (CN2) was determined to be the most sensitive parameter in the region, while the threshold depth in the shallow aquifer for return flow (GWQMN) was shown to be the least sensitive. Results showed a satisfactory estimate of daily streamflow for calibration (R2 = 0.88; NSE = 0.85; PBIAS = 1.02) and validation periods (R2 = 0.90; NSE = 0.84; PBIAS = –8.45). Uncertainty analysis during calibration (validation) resulted in p-factor value of 0.82 (0.90) and r-factor value of 0.87 (0.88), respectively. The ensemble of six RCMs under the NEX-GDDP dataset for precipitation and temperature was compared with the available observed data on a monthly time-step. The graphical comparison, as well as the performance indices, suggested that the NEX-GDDP dataset is capable of capturing the climatology of the region without bias. The NEX-GDDP dataset were divided into four different time periods, baseline period (1979–2005) and three future time slices, the 2030s (2019–2045), 2060s (2046–2072), and 2080s (2073–2099) under RCP 4.5 and RCP 8.5 scenarios. Under both RCP 4.5 and 8.5 scenarios, changes in average annual and seasonal precipitation (%), maximum and minimum temperatures (°C), streamflow, and other hydrological parameters were estimated for all future time slices (2020s, 2050s, and 2080s). The results of the climate change study estimated an increase in the average annual precipitation (+23.18%), maximum temperature (+2.4°C), minimum temperature (+2.64°C), streamflow (+31.62%), water yield (+31.81%), actual evapotranspiration (+6.37%), and groundwater flow (+33.41%), while soil water (–2.0%) was projected to decrease under RCP 4.5 scenario. In the case of RCP 8.5 scenario, the average annual precipitation, maximum temperature, minimum temperature, streamflow, water yield, actual evapotranspiration, and groundwater flow were projected to increase by 49.29%, 4.18°C, 4.23°C, 69.09%, 69.54%, 10.91%, and 65.15%, respectively, and soil water was projected to decrease by 4.52% by the end of the 21st century. The estimations prepared in this work will be useful for water resource planning and management under limited data conditions, hydropower developers, and decision makers and water policy specialists in devising future interventions in response to climate change projections. [ABSTRACT FROM AUTHOR]

Regional projections of extreme precipitation intensity (EPI) are strongly influenced by changes of "extreme ascent", i.e. ascending air during periods of extreme precipitation. Earlier studies have suggested that long-term changes in eddy length scale and vertical stability are key factors influencing extreme ascent projections, but these mechanisms have yet to be confirmed with controlled model experiments. In this study, we perform such controlled experiments using a cloud-resolving model (CRM). The selected CRM domains are three locations over the subtropical Atlantic Ocean where global climate models consistently project weakening of extreme ascent with accordingly decreased EPI. At each study location, four to ten pairs of 20-year-maximum precipitation events are simulated with the CRM, with each pair consisting of an event during the historical period (1981–2000) and an event during the future period (2081–2100). Large-scale forcings for these events are derived from members of an initial condition ensemble of the Canadian Earth System Model version 2 (CanESM2). These experiments reveal that, in all three study locations, weakening of differential cyclonic vorticity advection (dCVA) is a key driver of projected decreases in extreme ascent and EPI. Possible mechanisms responsible for weakening dCVA are discussed. Although there is evidence that EPI in the CRM has different sensitivity to large-scale forcings than CanESM2, the role of dCVA changes may nonetheless be important to consider for EPI changes in the real world. [ABSTRACT FROM AUTHOR]

Extreme climate events can cause large risks to ecosystems and human society in a short period. Investigating the changing trends of such events is essential for regional climate risk management. However, there is limited information on the regional assessment of the history and future trends of extreme climate events in Xinjiang, China. This study investigated the historical changes and projected trends of extreme climate events in Xinjiang based on observational data and Coupled Model Intercomparison Project phase 6 (CMIP6) model simulations. The results showed that the bias correction effectively reduced the bias of the CMIP6 model to the extreme climate indices simulation. During the period 1961–2014, the extreme indices representing warmth showed robust growth, while the extreme indices representing cold showed a robust decline. The intensity and frequency indices of extreme precipitation continued to increase, while consecutive dry days (CDDs) shortened and consecutive wet days (CWDs) lengthened. The changing trend of the extreme temperature indices had strong spatial consistency, while the changing trend of the extreme precipitation indices had obvious spatial heterogeneity. Based on the CMIP6 model simulations, the extreme climate indices in the twenty-first century were projected to continue the changing trend of the historical period (1961–2014). Compared with north Xinjiang (NXJ) and south Xinjiang (SXJ), the cold spell duration index (CSDI), cold nights (TN10p), cold days (TX10p), and extreme precipitation events in the Tianshan Mountains (TSM) were projected to experience stronger changes in the twenty-first century. The response of extreme temperature and extreme precipitation indices to global warming was approximately linear. Compared with SSP585, most extreme climate indices under the SSP245 scenario changed slightly in response to global warming. The superposition of the increase (decrease) in extreme warm (cold) events and the increase in extreme precipitation events will exacerbate the threat of extreme climate events to the agricultural and ecological security of the Xinjiang oasis, especially in the TSM. Given the limited water vapor sources and precipitation and the high rate of evapotranspiration, it is projected that the current situation of water shortages in Xinjiang will not be fundamentally changed. [ABSTRACT FROM AUTHOR]

This study establishes the improvements in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) simulations as compared to its previous version, CMIP5. First, the historical simulations are compared with the reanalysis products from the 5th generation European Centre for Medium-Range Weather Forecasts (ERA5). Quality improvement in CMIP6 is assured through its correspondence with ERA5 in terms of mean, standard deviation and mean bias. Global fields of three hydrometeorological variables, i.e. temperature, precipitation and soil moisture, are considered from multiple General Circulation Models. Among the three variables, maximum improvement is noticed in case of soil moisture followed by precipitation, especially in the tropical belt. In case of temperature, the mean bias has reduced by ± 3 °C across the parts of North America, Africa, and South Asia. Better reliance on the CMIP6 motivates for a trend analysis to peek into the future. The results indicate a significant increasing trend for precipitation in the temperate, polar and sub-polar regions, whereas a significant increase in temperature is noticed almost all across the world with highest slope in the polar and sub-polar regions. Furthermore, soil moisture shows a significant trend that can be grouped continent-wise, e.g. Africa, Central and South Asia exhibit an increasing trend, whereas North and Central America and Northern parts of South America exhibit an overall decreasing trend. Apart from underlining the better reliance on CMIP6, the findings of this study will also be useful across different parts of the world for many climate related studies using CMIP6. [ABSTRACT FROM AUTHOR]

We analyse the expected characteristics of drought events in northern Italy for baseline (1971–2000), near (2021–2050), and far (2071–2100) future conditions, estimating the drought spatial extent and duration, the percentage of affected area, and the frequency of drought episodes. To this end, daily ensembles of precipitation and temperature records from Global Climate Models (GCMs) and Regional Climate Models (RCMs) pairs, extracted from EURO-CORDEX and MED-CORDEX for the RCP 4.5 and 8.5 scenarios, are collected at spatial resolution of 0.11 degrees. Before the analysis, model outputs are validated on daily weather station time series, and scaling factors for possible use in bias correction are identified. Annual temperature and precipitation anomalies for near and far future conditions are investigated; drought events are identified by the standardized precipitation evapotranspiration index and standardized precipitation index at the 12-, 24-, and 36-month timescales. This study highlights the importance of using multiple drought indicators in the detection of drought events, since the comparison reveals that evapotranspiration anomaly is the main triggering factor. For both scenarios, the results indicate an intensification of droughts in northern Italy for the period 2071–2100, with the Alpine chain being especially affected by an increase of drought severity. A North-to-South spatial gradient of drought duration is also observed. [ABSTRACT FROM AUTHOR]

A recent study of global wind power using an ensemble of ten CMIP5 climate simulations indicated an interhemispheric asymmetry of wind power changes over the twenty-first century, featured by power decreases across the Northern Hemisphere mid-latitudes and increases across the tropics and subtropics of the Southern Hemisphere. Here we analyze future projections of surface mean and extreme winds by means of a single-model initial-condition 50-member ensemble of climate simulations generated with CanESM5, the Canadian model participated in CMIP6. We analyze the ensemble mean and spread of boreal winter mean and extreme wind trends over the next half-century (2021–2070) and explore the contribution of internal climate variability to these trends. Surface wind speed is projected to mostly decrease in northern mid-low latitudes and southern mid-latitudes and increase in northern high latitudes and southern tropical and subtropical regions, with considerable regional variations. Large ensemble spreads are apparent, especially with remarkable differences over northern parts of South America and northern Russia. The interhemispheric asymmetry of wind projections is found in most ensemble members, and can be related to large-scale changes in surface temperature and atmospheric circulation. The extreme wind has similar structure of future projections, whereas its reductions tend to be more consistent over northern mid-latitudes. The projected mean and extreme wind changes are attributed to changes in both externally anthropogenic forced and internal climate variability generated components. The spread in wind projections is partially due to large-scale atmospheric circulation variability. [ABSTRACT FROM AUTHOR]

Renewable energy is key for the development of African countries, and knowing the best location for the implementation of solar and wind energy projects is important within this context. The purpose of this study is to assess the impact of climate change on solar and wind energy potential over Africa under low end (RCP2.6) and high end (RCP8.5) emission scenarios using a set of new high resolution (25 km) simulations with the Regional Climate Model version 4 (RegCM4) produced as part of the CORDEX-CORE initiative. The projections focus on two periods: (i) the near future (2021–2040) and ii) the mid-century future (2041–2060). The performance of the RegCM4 ensemble mean (Rmean) in simulating relevant present climate variables (1995–2014) is first evaluated with respect to the ERA5 reanalysis and satellite-based data. The Rmean reproduces reasonably well the observed spatial patterns of solar irradiance, air temperature, total cloud cover, wind speed at 100 m above the ground level, photovoltaic power potential (PVP), concentrated solar power output (CSPOUT) and wind power density (WPD) over Africa, though some biases are still evident, especially for cloud-related variables. For the future climate, the sign of the changes is consistent in both scenarios but with more intense magnitude in the middle of the century RCP8.5 scenario. Considering the energy variables, the Rmean projects a general decrease in PVP, which is more pronounced in the mid-century future and under RCP8.5 (up to 2%). Similarly, a general increase in CSPOUT (up to 2%) is projected over the continent under both the RCP2.6 and RCP8.5 scenarios. The projection in WPD shows a similar change (predominant increase) in the near and mid-century future slices under both RCPs with a maximum increase of 20%. The present study suggests that the RCP2.6 emission scenario, in general, favours the implementation of renewable energy in Africa compared to the RCP8.5. [ABSTRACT FROM AUTHOR]

This study evaluates the ability of 19 models of CMIP phase 6 (CMIP6) to simulate Paraguay’s climate features. Historical multi-member simulations of single models and their multi-model ensembles are bias-corrected and evaluated with statistical metrics. Future projections of precipitation and temperature are generated with the ensembles for three integrated scenarios of socio-economic development and greenhouse gas emissions (SSP1–2.6, SSP2–4.5, and SSP5–8.5). The 19 models simulate well the observed mean temperature. The bias-corrected multi-model ensemble reaches the highest skill scores and accurately reproduces the mean spatial field and annual cycle. The bias-corrected multi-model ensemble of precipitation represents the annual cycle weakly, missing the sharp onset and decay of the South American Monsoon. Some individual models and the multi-model ensemble correctly reproduce the west-east gradient, although they underestimate its pronounced spatial variability. Ensembles of future simulations project that by 2100, the annual mean temperature will increase for the three scenarios. On average, the increases are almost 1.7 °C in the sustainable development and low emissions scenario (SSP1–2.6), 3 °C in the middle-of-the-road development and medium emissions scenario (SSP2–4.5), and 5.5 °C in the fossil-fueled development and high emissions scenario (SSP5–8.5). Models project a slight decrease in annual precipitation towards the northwest (less than 50 mm) and an increase towards the southeast (more than 200 mm). Paraguay’s humid eastern part is projected to have a small growth in temperature and an increase in precipitation. In contrast, the western arid Chaco region would experience a substantial increase in temperature, while rainfall would slightly decrease. [ABSTRACT FROM AUTHOR]

This study explores the relative changes and future projections of temperature and precipitation for baseline (1976–2005) and future (2006–2040, 2041–2070, and 2071–2100) periods for the Bajaur, Mohmand, and Khyber districts of Pakistan situated in the Hindu Kush region. Data from 14 GCMs (out of which five GCMs were selected based on evaluation and validation) and three RCMs were downscaled and bias corrected using the quantile delta mapping (QDM) method for GCMs and the best easy systemic (BES) method for RCMs. The future extremes were projected by using the standard indices from the Expert Team on Climate Change Detection and Indices (ETCCDI). Uncertainty in the data was analysed by a probabilistic distribution function (PDF), boxplots, and standard deviation. For RCP4.5, the GCM and RCM projections show an increase in the average maximum temperature of 0.98 °C for 2006–2040, 1.89 °C and 2.04 °C for 2041–2070, and 2.25 °C and 2.56 °C for 2071–2100, respectively, while the increase is almost double for RCP8.5 during the last period (2071–2099) over the whole study area. The percent increase in precipitation over the whole study area from GCMs and RCMs for RCP4.5 is 10.00–17.00% and 21.14–34.47%, while for RCP8.5, it is 11.73–22.12% and 16.17–31.50%, respectively. In RCM projections for RCP4.5, the Khyber district will experience drier conditions in mid-century, while for GCMs (RCP4.5), the same conditions are projected through the end of the century. In terms of extreme events, warm temperature extremes and extreme precipitation events show an increasing trend accompanied by a decrease in cold extremes over all regions. Hence, it is concluded that warm and wet conditions are projected to prevail in all regions. However, GCM data depict less uncertainty compared with RCM data, and while models show less error for the baseline period, the error increases slightly for the future periods. Thus, this study provides research findings along with policy recommendations essential to combat the potential impacts of projected changes in the regional climate. [ABSTRACT FROM AUTHOR]

Temperature and precipitation distributions depend on variable topography and heterogeneous landuse/landcover in the Indian Himalayan Region (IHR). It imparts a major concern for hydrological, glaciological modelling, dam structure assessment, etc. Thus, there is an inherent requirement of robust information for climate impact studies over the topographical variable and landuse heterogenous region in the Indian Himalayan Region (IHR). In particular, the importance of bias corrections become critically important over Himalayan river basins, in which model outputs with the corresponding in-situ observations are used for improving the model distribution. These improved details in present and future, as well, are important to carry out the climate change impact studies at basin scale for hydrological, glaciological, climatological studies, etc. Thus, in the present study firstly, model fields are bias corrected with the corresponding in-situ observations. And then trends in these bias corrected data is compared with the corresponding in-situ observations. These assessment of present and future changes in temperature and precipitation over Satluj River Basin (SRB) located in the western Himalayas is illustrated. Model fields are considered from a Regional climate model (REMO) from Coordinated Regional Downscaling Experiment-South Asia (CORDEX-SA) in three Representative Concentration Pathways (RCPs), i.e., 2.6, 4.5 and 8.5 W/m2. These projections are bias corrected using distributed quantile mapping. The precipitation (temperature) bias correction is performed using the distributed quantile mapping on the gamma (normal) distribution. The standard trend statistics is applied for quantitative assessment. A good capture of bias correction in temperature and precipitation is illustrated. Efficient bias removal is depicted in cumulative distribution curve (CDF) at individual station. Trend analysis shows that highest rate of precipitation decrement at low altitude station (Kasol) with the rate of −6.362 mm/year in RCP 8.5. Over the SRB highest rate of temperature increment is seen at highest altitude station (Kaza) with the rate of 0.084°C/year in RCP 8.5. On an average, fall in precipitation and increase in temperature with >99% confidence level in RCP 8.5 is seen. In addition, intensity lowers in other lower RCPs. The study sums up with the efficacy of CORDEX-SA REMO model in capturing present and future change in temperature and precipitation over the SRB in western Himalayas using the bias correction. [ABSTRACT FROM AUTHOR]

As the dominant driver of interannual climate variability globally, any changes in the remote impacts of the El Niño-Southern Oscillation (ENSO) due to climate change are of considerable importance. Here we assess whether climate models from Phase 5 of the Coupled Model Intercomparison Project (CMIP5) project robust changes in ENSO's regional temperature and precipitation teleconnections in the late 21st century, comparing the historical simulations (between 1950 and 1999) and high-emission future simulations (between 2040 and 2089). In order to quantify the importance of internal variability in these projected changes, we examine an ensemble of coupled model simulations from the Max-Planck-Institute Grand Ensemble (MPI-GE). Except for a few regions, the changes in ENSO's temperature and precipitation teleconnections for most regions are not significant across the majority of models. Exceptions include consistent projected changes to temperature teleconnections over equatorial South America and East Africa, which are robust during La Niña events. Despite this, by assessing all regions together, a significant amplification of the temperature teleconnections is identified for La Niña events. Additionally, we find an overall projected weakening relative to the historical precipitation teleconnection when analysis is limited to regions that correctly reproduce the observed precipitation teleconnections. It remains unclear to what extent a change in regional ENSO teleconnections will be apparent, as it is clear that the changes in ENSO's teleconnections are relatively small compared to the regional variability during the historical period. [ABSTRACT FROM AUTHOR]

Atmospheric water vapor has not only been reported to increase in the real world, but is also expected to increase in climate models. Correctly simulating water vapor and its relationship with temperature is thus vital for climate models. In this study, atmospheric precipitable water (PW) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) is evaluated over China during 1970–2005, and then the future changes of PW and their correlation with near-surface air temperature (Ts) are further investigated. The results show that the PW biases in the model simulations are within ~ 20% for most of eastern China, but have larger root-mean-square error over southeastern China. Most models are able to simulate the observed PW upward trends since 1970, but with large inter-model spread. CanESM2, GFDL-CM3, HadGEM2-ES and MIROC5 are relatively better at reproducing the observed long-term variations and trends for the whole of China and its subregions. An empirical orthogonal function (EOF) analysis shows that the model simulations reproduce the first observed leading modes well, but barely capture the temporal variation revealed by the second observed EOF. The model simulations project ubiquitous increases in PW in the twenty-first century, resulting from an increase in the mean and a flattening of the probability distribution functions of the PW anomalies. In particular, the increases in PW under the most severe future emissions scenario (RCP8.5) are nearly twice as much as those under the low–mid emissions scenario (RCP4.5) for most of China by the late twenty-first century. The model simulations suggest that the changes in PW are largely consistent with the changes in Ts during 1970–2005, with a dPW/dTs slope of ~ 4.6–6.0% K−1, which roughly agrees with the observed results but is slightly lower than the 7% K−1 implied by the Clausius–Clapeyron equation with a constant relative humidity. In the twenty-first century, the dPW/dTs is projected to be about 5.5–7.0% K−1 under the RCP4.5 scenario, but may reach ~ 7.4% K−1 or higher under the RCP8.5 scenario. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change has already been shown to effect the frequency, intensity, spatial extent, duration and seasonality of extreme climate events. Understanding these changes is an important step in determining exposure, vulnerability and focus for adaptation. In an attempt to support adaptation decision-making we have examined statistical modelling techniques to improve the representation of global climate model (GCM) derived projections of minimum temperature extremes (frosts) in Australia. We examine the spatial changes in minimum temperature extreme metrics (e.g. monthly and seasonal frost frequency etc.), for a region exhibiting the strongest station trends in Australia, and compare these changes with minimum temperature extreme metrics derived from 10 GCMs, from the Coupled Model Inter-comparison Project Phase 5 (CMIP 5) datasets, and via statistical downscaling. We compare the observed trends with those derived from the "raw" GCM minimum temperature data as well as examine whether quantile matching (QM) or spatio-temporal (spTimerQM) modelling with Quantile Matching can be used to improve the correlation between observed and simulated extreme minimum temperatures. We demonstrate, that the spTimerQM modelling approach provides correlations with observed daily minimum temperatures for the period August to November of 0.22. This represents an almost fourfold improvement over either the "raw" GCM or QM results. The spTimerQM modelling approach also improves correlations with observed monthly frost frequency statistics to 0.84 as opposed to 0.37 and 0.81 for the "raw" GCM and QM results respectively. We apply the spatio-temporal model to examine future extreme minimum temperature projections for the period 2016 to 2048. The spTimerQM modelling results suggest the persistence of current levels of frost risk out to 2030, with the evidence of continuing decadal variation. [ABSTRACT FROM AUTHOR]

In Part I of our study (Zazulie et al. Clim Dyn, 2017, hereafter Z17) we analyzed the ability of a subset of fifteen high-resolution global climate models (GCMs) from the Coupled Model Intercomparison Project phase 5 to reproduce the past climate of the Subtropical Central Andes (SCA) of Argentina and Chile. A subset of only five GCMs was shown to reproduce well the past climate (1980-2005), for austral summer and winter. In this study we analyze future climate projections for the twenty-first century over this complex orography region using those five GCMs. We evaluate the projections under two of the representative concentration pathways considered as future scenarios: RCP4.5 and RCP8.5. Future projections indicate warming during the twenty-first century over the SCA region, especially pronounced over the mountains. Projections of warming at high elevations in the SCA depend on altitude, and are larger than the projected global mean warming. This phenomenon is expected to strengthen by the end of the century under the high-emission scenario. Increases in winter temperatures of up to 2.5 °C, relative to 1980-2005, are projected by 2040-2065, while a 5 °C warming is expected at the highest elevations by 2075-2100. Such a large monthly-mean warming during winter would most likely result in snowpack melting by late winter-early spring, with serious implication for water availability during summer, when precipitation is a minimum over the mountains. We also explore changes in the albedo, as a contributing factor affecting the net flux of energy at the surface and found a reduction in albedo of 20-60% at high elevations, related to the elevation dependent warming. Furthermore, a decrease in winter precipitation is projected in central Chile by the end of the century, independent of the scenario considered. [ABSTRACT FROM AUTHOR]

Land use and land cover (LULC), as well as their geographical and temporal variations, affect landslide occurrence and the related risk, in ways that are difficult to determine. Here, we propose a method for the regional analysis of variations in landslide frequency and distribution in response to observed and projected LULC changes. The method is quantitative and reproducible. We test it in Calabria, southern Italy, where a catalogue of 7037 landslides occurred between 1921 and 2010 is available. First, we defined empirical relationships linking the observed LULC variations to landslide occurrence. We found that, in the period 1921–1965, the majority of the landslides occurred in forests and grassland areas, while, in the period 1966–2010, the landslide density became higher in grassland areas, lower in arable lands and remained about constant in the forests. We consider this an evidence of the positive effect of agricultural practices and land management in reducing landslide occurrence. We noticed that both the landslide occurrence and the distribution of the vulnerable elements changed in the observation period. Then, we calculated the projected variations (to 2050) in landslide occurrence related to 32 scenarios of LULC changes. Our projections reveal a modest increase in landslide occurrence in all scenarios, in the range from 0.9 to 3.2%, with an average increase of 2%. Considering all scenarios, we expect an increase in the number of landslides due to LULC variations in 291 municipalities in Calabria (71%), with 4 municipalities where the increase is expected to exceed 50%. We maintain that the observed and the projected variations in the occurrence of landslides in Calabria are related to changes in natural (i.e. the number and distribution of the triggering events) and environmental and societal (i.e. the number and the distribution of the exposed elements) components. [ABSTRACT FROM AUTHOR]

Halogenated Very Short-lived Substances (VSLS), such as bromoform, dibromomethane and methyl iodide, are naturally produced in the oceans and are involved in ozone depletion in the troposphere and the stratosphere. The effect of climate change on the oceanic emissions of these compounds is not well quantified. Based on present-day observed global oceanic and atmospheric concentrations, and historic and future data from three CMIP5 models, past and future sea-to-air fluxes of these VSLS are calculated. The simulations are used to infer possible effects of projected changes of physical forcing on emissions in different oceanic regimes. CMIP5 model output for 1979-2100 from the historical scenario and the RCP scenarios 2.6 and 8.5 are used as input data for the emission calculations. Of the parameters that have the main influence on the sea-to-air fluxes, the global sea surface temperatures show a steady increase during the twenty-first century, while the projected changes of sea surface wind speed is very small. The calculated emissions based on the historical CMIP5 model runs (1979-2005) increased over the 26 year period and agree well with the emissions based on ERA-Interim data. The future sea-to-air fluxes of VSLS generally increase during the twenty-first century under the assumption of constant concentration fields in the ocean and atmosphere. The multi-model mean global emissions of bromoform increase by 29.4% (9.0%) between 1986 and 2005 and 2081-2100 under RCP 8.5 (2.6) and dibromomethane and methyl iodide emissions increase by 23.3% (6.4%) and 5.5% (1.5%), respectively. Uncertainties of the future emission estimates, driven by ongoing environmental changes such as changing oceanic productivity (not considered in this study) are discussed. [ABSTRACT FROM AUTHOR]

Different epidemiological studies have shown that high temperatures are directly related to mortality, furthermore many studies on the effects of climate change on future mortality are being conducted. The objective of this study is to estimate the effect of extreme hot temperatures on daily mortality in Zaragoza (Spain) from 2014 to 2021, utilising various climate-change scenarios. The relationship between temperature and mortality is defined by the concepts of heat wave, threshold temperature and the relative risk of daily deaths according to extreme temperatures in 1987-2006 period. The effect on future mortality is projected by estimating deaths attributable to extreme temperatures in 2014-2021. This estimation was calculated utilising exposure-response functions for three scenarios (A1B, A2 and B1) from the ECHAM5 general circulation model after applying a statistical downscaling technique. Because this study considers the effect of rising temperatures from a health perspective, minimising uncertainty was added to the numerical values obtained from the projected future relation between temperature and mortality. The results shows that expected mortality in Zaragoza will increase by 0.4 % for the period 2014-2021, an excess that can be directly attributed to extreme temperatures. This effect is expected to increase in the 2040s and 2050s until the end of the twenty first century because of a predicted increase in temperatures over this period, with special emphasis on the need to continue studying this line of inquiry and local studies as which arises. Finally, this study will luckily be used to create prevention plans for minimising the effect on health of the high temperatures. [ABSTRACT FROM AUTHOR]

This study aims to estimate the incidence and costs of osteoporosis-related fractures in The Netherlands in 2010 and project them to 2030. The incidence and costs of five different types of fractures (spine, hip, upper extremity, lower extremity, wrist/distal forearm, other) were derived from claims data of all Dutch healthcare insurers. Given that fracture-codes in claims data do not indicate whether fractures are related to osteoporosis, we used a large dataset with DXA measurements to attribute fractures to osteoporosis. Future projections used four scenarios: (1) demographic, (2) demographic + annual trend in incidence rates, (3) demographic + annual trend in incidence rates + annual trend in costs, and (4) treatment. Of all registered fractures, 32 % was attributed to osteoporosis (36 % in women and 21 % in men). Over time (2010-2030) the increase in incidence of osteoporosis-related fractures was estimated to be 40 % (scenario 1); for the hip 60-79 % (scenario 1-2). In 2010, approximately €200 million was spent on treatment of osteoporosis-related fractures, most on fractures of the hip followed by wrist/distal forearm. In both men and women, the excess costs due to osteoporosis-related fractures were highest for hip fractures (€11,000-€13,000 per person), followed by spine fractures (€6000-€7000).The costs for osteoporosis-related fractures were projected to increase with 50 % from 2010 to 2030 (scenario 1); for the hip 60-148 % (scenario 1-3). Pharmacotherapeutic prevention can lead to cost-savings of €377 million in 2030 (scenario 1 and 4 combined). The projected increase in incidence and costs of osteoporosis-related fractures calls for a wider use of prevention and treatment. [ABSTRACT FROM AUTHOR]

Increasing pressures from land use coupled with future changes in climate will present unique challenges for California's protected areas. We assessed the potential for future land use conversion on land surrounding existing protected areas in California's twelve ecoregions, utilizing annual, spatially explicit (250 m) scenario projections of land use for 2006-2100 based on the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios to examine future changes in development, agriculture, and logging. We calculated a conversion threat index (CTI) for each unprotected pixel, combining land use conversion potential with proximity to protected area boundaries, in order to identify ecoregions and protected areas at greatest potential risk of proximal land conversion. Our results indicate that California's Coast Range ecoregion had the highest CTI with competition for extractive logging placing the greatest demand on land in close proximity to existing protected areas. For more permanent land use conversions into agriculture and developed uses, our CTI results indicate that protected areas in the Central California Valley and Oak Woodlands are most vulnerable. Overall, the Eastern Cascades, Central California Valley, and Oak Woodlands ecoregions had the lowest areal percent of protected lands and highest conversion threat values. With limited resources and time, rapid, landscape-level analysis of potential land use threats can help quickly identify areas with higher conversion probability of future land use and potential changes to both habitat and potential ecosystem reserves. Given the broad range of future uncertainties, LULC projections are a useful tool allowing land managers to visualize alternative landscape futures, improve planning, and optimize management practices. [ABSTRACT FROM AUTHOR]

A new methodology based on complex network analysis is applied to state-of-the-art climate model simulations to assess their performances, quantify uncertainties, and uncover changes in global linkages between past and future projections. Network properties of modeled sea surface temperature and precipitation over 1956-2005 are constrained towards observations or reanalyses, and their differences quantified using two metrics. Projected changes from 2051 to 2300 under the scenario with the highest representative and extended concentration pathways (RCP8.5 and ECP8.5) are then determined. The network of models capable of reproducing well major climate modes in the recent past, change little during this century. In contrast, among those models the uncertainties in the projections after 2100 are substantial, and are primarily associated with divergences in the representation of the modes of variability, particularly of the El Niño Southern Oscillation, and their connectivity, and therefore with their intrinsic predictability, more so than with differences in the mean state evolution. [ABSTRACT FROM AUTHOR]

Many climate models have problems simulating Indian summer monsoon rainfall and its variability, resulting in considerable uncertainty in future projections. Problems may relate to many factors, such as local effects of the formulation of physical parametrisation schemes, while common model biases that develop elsewhere within the climate system may also be important. Here we examine the extent and impact of cold sea surface temperature (SST) biases developing in the northern Arabian Sea in the CMIP5 multi-model ensemble, where such SST biases are shown to be common. Such biases have previously been shown to reduce monsoon rainfall in the Met Office Unified Model (MetUM) by weakening moisture fluxes incident upon India. The Arabian Sea SST biases in CMIP5 models consistently develop in winter, via strengthening of the winter monsoon circulation, and persist into spring and summer. A clear relationship exists between Arabian Sea cold SST bias and weak monsoon rainfall in CMIP5 models, similar to effects in the MetUM. Part of this effect may also relate to other factors, such as forcing of the early monsoon by spring-time excessive equatorial precipitation. Atmosphere-only future time-slice experiments show that Arabian Sea cold SST biases have potential to weaken future monsoon rainfall increases by limiting moisture flux acceleration through non-linearity of the Clausius-Clapeyron relationship. Analysis of CMIP5 model future scenario simulations suggests that such effects are small compared to other sources of uncertainty, although models with large Arabian Sea cold SST biases may suppress the range of potential outcomes for changes to future early monsoon rainfall. [ABSTRACT FROM AUTHOR]

Global aerosol and ozone distributions and their associated radiative forcings were simulated between 1850 and 2100 following a recent historical emission dataset and under the representative concentration pathways (RCP) for the future. These simulations were used in an Earth System Model to account for the changes in both radiatively and chemically active compounds, when simulating the climate evolution. The past negative stratospheric ozone trends result in a negative climate forcing culminating at −0.15 W m in the 1990s. In the meantime, the tropospheric ozone burden increase generates a positive climate forcing peaking at 0.41 W m. The future evolution of ozone strongly depends on the RCP scenario considered. In RCP4.5 and RCP6.0, the evolution of both stratospheric and tropospheric ozone generate relatively weak radiative forcing changes until 2060-2070 followed by a relative 30 % decrease in radiative forcing by 2100. In contrast, RCP8.5 and RCP2.6 model projections exhibit strongly different ozone radiative forcing trajectories. In the RCP2.6 scenario, both effects (stratospheric ozone, a negative forcing, and tropospheric ozone, a positive forcing) decline towards 1950s values while they both get stronger in the RCP8.5 scenario. Over the twentieth century, the evolution of the total aerosol burden is characterized by a strong increase after World War II until the middle of the 1980s followed by a stabilization during the last decade due to the strong decrease in sulfates in OECD countries since the 1970s. The cooling effects reach their maximal values in 1980, with −0.34 and −0.28 W m respectively for direct and indirect total radiative forcings. According to the RCP scenarios, the aerosol content, after peaking around 2010, is projected to decline strongly and monotonically during the twenty-first century for the RCP8.5, 4.5 and 2.6 scenarios. While for RCP6.0 the decline occurs later, after peaking around 2050. As a consequence the relative importance of the total cooling effect of aerosols becomes weaker throughout the twenty-first century compared with the positive forcing of greenhouse gases. Nevertheless, both surface ozone and aerosol content show very different regional features depending on the future scenario considered. Hence, in 2050, surface ozone changes vary between −12 and +12 ppbv over Asia depending on the RCP projection, whereas the regional direct aerosol radiative forcing can locally exceed −3 W m. [ABSTRACT FROM AUTHOR]

Contemporary research has documented a large number of shifts in spring phenology and changes in distribution range although the average spring temperatures have increased by only 0.3-0.6 °C over the past 100 years. Generally, earlier breeding birds have larger clutch sizes, and the advancing spring could thus potentially increase breeding success. Shifts in spring phenology can, however, be crucial for bird reproduction, and mistiming the breeding event may even have negative consequences for population development. Our aim was to explore how weather and prey abundance relates to the breeding performance of a north European top predator, the northern goshawk Accipiter gentilis. Our nationwide dataset from Finland, spanning the period 1989-2004, shows that ambient weather has a greater impact on the timing and success of breeding than the density of grouse Tetraonidae, the main prey of goshawks. Higher early spring temperatures were associated with advancing hatching date of goshawks. Correspondingly, grouse density and temperature during laying and brooding were positively associated with brood size, while precipitation showed a negative connection. Applying our models to a future scenario of climate warming, combined with a 50 % reduction in grouse density, suggests that average breeding dates will advance only 2.5 days and average breeding success would remain the same. Notably, breeding success was not spatially equal throughout Finland, as northern and eastern populations suffered most from declining grouse densities. The observed pattern is thus the opposite to what is expected from a population situated at the northern edge of its distribution range, and thus may help to understand why populations may not increase at the northern edge of their thermal distribution due to climate change. [ABSTRACT FROM AUTHOR]

Uncertainties in projected future changes in tropical cyclone (TC) activity are investigated using future (2075-2099) ensemble projections of global warming under the Intergovernmental Panel on Climate Change (IPCC) A1B scenario. Twelve ensemble experiments are performed using three different cumulus convection schemes and four different assumptions for prescribed future sea surface temperatures (SSTs). All ensemble experiments consistently project significant reductions in global and hemispheric TC genesis numbers as well as reductions in TC frequency of occurrence (TCF) and TC genesis frequency (TGF) in the western North Pacific, South Indian Ocean, and South Pacific Ocean. TCF and TGF are projected to increase over the central Pacific which is consistent with the findings of Li et al. (). Inter-experimental variations of projected future changes in TGF and TC genesis number are caused mainly by differences in large-scale dynamical parameters and SST anomalies. Thermodynamic parameters are of secondary importance for variations in TGF and TC genesis number. These results imply that differences in SST spatial patterns can cause substantial variations and uncertainties in projected future changes of TGF and TC numbers at ocean-basin scales. [ABSTRACT FROM AUTHOR]

European surface temperatures have increased during the past decades. According to climate projections, this warming is expected to continue in future years under enhanced radiative forcings. In addition to the mean increase, changes in temperature variability are likely to occur, with more frequent extreme seasons such as those recently observed in the past decade (e.g. summer 2003, autumn 2006). Yet, most of the processes driving such long-term tendencies remain unidentified and unexplored. A particularly important issue is how changes in the atmospheric dynamics over the North-Atlantic and Europe (NAE) contribute to trends in both mean and extreme temperatures. The high occurrence of the positive phase of the North Atlantic Oscillation (NAO) in the 1980s-1990s suggested that the European warming could result from a re-organization in the main structures of the NAE dynamics. However, the 2000s have rather revealed an inconsistency between atmospheric circulation conditions and European temperatures. Here we investigate the relationship between sea-level pressure (SLP) and 2-m temperature (T2m) using a flow-analogues method applied over both observations and future projections. We use 13 models of the Third phase of the Coupled Model Intercomparison Project (CMIP3) over 1961-2000, 2046-2065 and 2081-2100, from which we extract seasonal subensembles with respect to their representation of observed SLP-T2m seasonal relationships. First we show that the distribution of SLP does not undergo major changes in future climate according to these seasonal model-ensembles, albeit a general decline of the variability is observed for all seasons. Then, using the flow-analogues, we conclude that the projected European warming appears disconnected from changes in the NAE dynamics. Only in winter a slight shift towards positive NAO conditions could partially contribute to the future temperature increase. Finally, a focus over unusually warm/cold seasons reveals that future temperature extremes should likely to be associated with similar atmospheric circulations as observed during recent ones. [ABSTRACT FROM AUTHOR]

This study examines the surface air temperature projections and associated uncertainties over the Arabian Peninsula by using data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under the Representative Concentration Pathways RCP4.5 and RCP8.5 scenarios. The 30-member CMIP5 mean multi-model ensemble (MME) reveals a significant (at the 99% level) increase in temperature by the end of the twenty-first century of around 2.28 (5.53) °C/100 years under the RCP4.5 (RCP8.5) scenarios. The warming as well as the uncertainty associated with the temperature projections over the Arabian Peninsula will increase with time up to the end of the twenty-first century. In the near future (2021-2050), both RCPs (RCP4.5 and RCP8.5) reveal similar increases (~ 2 to 2.5 °C) in temperature compared to the present climate (1976-2005). For the period 2070-2099, the temperatures are projected to be from 2.55 ± 1.58 (4.89 ± 1.58) °C relative to the present climate under RCP4.5 (RCP8.5), while the associated uncertainty ranges from − 1.38 to 5.95 (0.57 to 7.9) °C. Under RCP4.5 (RCP8.5), all models reach 2 °C in the Arabian Peninsula in the twenty-first century relative to 1976-2005 from 2023 (2030) to 2062 (2049). The warming over the Arabian Peninsula is projected to be asymmetric that will vary both spatially and seasonally. A strong increase in the annual mean temperature over the central and northwestern parts of the Arabian Peninsula comes mainly from the summer and autumn season. The projected warming rate is higher in the autumn compared to the other seasons during the twenty-first century. The decadal and centurial warming rates are lower in winter and higher in autumn. [ABSTRACT FROM AUTHOR]