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We describe the bias adjustment and downscaling to a resolution of 1 × 1 km of daily temperature, precipitation and solar radiation of a multimodel ensemble of Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs with the local observational data set BhutanClim for Bhutan and an analysis of the results for 1996–2100. The GCMs were selected based on their ability to reproduce local temporal and spatial precipitation patterns, resulting in a total of 14 models for each shared socioeconomic pathway (SSP). The results are shown for five global warming levels (GWLs) 1.5, 2, 3, 4 and 5°C, providing insight into the projected impacts of climate change at different warming levels. The daily temperature and precipitation data are publicly available, which is of great benefit for climate impact studies, such as ecological, hydrological or infrastructure‐related studies. In this paper, we discuss showcase climate indicators. Peak‐over‐threshold climate indicators such as hot days above 30°C are relevant for human health. In the capital city of Thimphu, these are currently rare, at 4 days per year, but might increase to more than 80 for GWL5.0. Precipitation increases in the summer months, but slightly decreases in the drier winter months. Accordingly, the 3‐month SPEI drought index is projected to increase in summer, but strongly decreases in the winter months, mostly pronounced in February. The increasing severity of late‐winter and spring droughts might have a negative impact on vegetation, wildfires and water supply. [ABSTRACT FROM AUTHOR]

Climate classifications are useful to synthesize the physical state of the climate with a proxy that can be directly related to biota. However, they present a potential drawback, namely a strong sensitivity because of the use of hard thresholds (step functions). Thus, minor discrepancies in the base data produce large differences in the type of climate. However, such an a priori limitation is also a strength because such sensitivity can be used to better gauge model performance. Although previous attempts of classifying climates of the world using global climate model outputs were encouraging, the applicability of their classifications to impact studies has been limited by past model issues. Notwithstanding the persistence of certain imperfections and limitations in current models, the high‐quality physical simulations from phase six of the Coupled Intercomparison Project (CMIP6) has opened new possibilities in the field, thanks to their improved representation of atmospheric and oceanic physics. The purpose of this paper is twofold: to show that climate classifications from CMIP6 are sufficiently robust for use in impact studies, and to use those classifications for identifying error sources and potential issues that deserve further attention in models. Thus, 52 CMIP6 climate models were evaluated by using three climate classifications schemes, classical Köppen, extended‐Köppen, and modified Thornthwaite. We first assessed model ability to reproduce present climate types by comparing their outputs with observational data. Models performed best for the Köppen and extended‐Köppen classification methods (Cohen's kappa κ = 0.7), and had moderate scores for the Thornthwaite climate classification (κ = 0.4). By tracing back the observed biases, we were able to pinpoint the misrepresentation of dry climates as a major source of error. Another finding was that most models still had some difficulties in representing the seasonal variability of precipitation over several monsoonal regions, thereby yielding the wrong climate type there. Models were also evaluated for future climate. Substantial changes in climate types are projected in the SSP5‐8.5 scenario. These changes include a shrinkage of polar/frigid climates (22%) and an increase of dry climates (7%). [ABSTRACT FROM AUTHOR]

This study investigates some of the uncertainties sources associated with the pseudo global warming (PGW) approach which was employed to project future patterns of tropical cyclones (TCs) over the Arabian Sea (AS). First, the climate variables controlling the patterns of tropical cyclones were extracted from reanalysis datasets of ERA5, ERAI, CFSR, and NCEP/NCAR. Then, each dataset was evaluated against long‐term measurements to identify the best‐performing reanalysis dataset. ERA5 showed the best performance for most of the variables. Outputs of 20 CMIP5 global climate models (GCMs) were then evaluated against the ERA5 data resulting in an ensemble of the best performing GCMs. A PGW framework was then used to project the changes in patterns of three significant historical cyclones: Gonu, Phet, and Ashobaa. In doing so, the signals of future climate variables were extracted from the GCMs ensemble to modify the initial and boundary conditions of the WRF model which was previously tuned for reproducing the historical TCs. Different tests were conducted to address the sources of uncertainty in the PGW approach, including the selection of the climate variables contributing to the computation of the signals, the selection of GCMs, and the spatial variation of signals. A considerable sensitivity of the projected track and intensity of TCs to the choice of GCMs was observed, acknowledging the importance of GCMs evaluation before calculating the signals. Moreover, it was found that among all variables, signals of sea surface temperature and air temperature have major effects on the cyclone's track and intensity. Apart from that, when the signals were applied to the domain of the WRF model uniformly, compared to applying spatially varying signals, different tracks and intensities for future TCs were also observed. Overall, the findings of this paper challenge the reliability of the projected changes in TCs patterns obtained from PGW. [ABSTRACT FROM AUTHOR]

This paper investigates the time trend coefficients in the temperatures in 48 US states using monthly data from January 1895 to December 2017, as well as in their anomalies with respect to the base period 1901–2000. For this purpose, we use techniques based on fractional integration, which is a more general approach than the standard methods used in the literature based on integer differentiation. The results indicate that with the exception of 10 states, in the remaining 38, the temperature anomalies have increased across time, with the increase being higher than the one expected under the other more standard approaches. The highest increases correspond to New Jersey and Rhode Island, with an increase of approximately 2.9°C over the last 100 years. [ABSTRACT FROM AUTHOR]

ABSTRACT The purpose of this paper is to describe the variability of sunshine duration and air temperature and to assess the relationship between these variables. The paper is based on daily means of air temperature and daily sunshine duration totals from the 1884-2012 period. The variability analyses of these variables for the whole period is supplemented by additional trend analyses for two separate time periods described in the literature as dimming (1958-1985) and brightening (1985-2012). All the data come from the Jagiellonian University Research Station in Krakow. In Krakow, there is a decrease in the number of sunshine hours in the 1950s to 1980s period followed by an increase in the last two decades of the 20th century. The long-term course of air temperature in Krakow confirms the results obtained in other places in the world and exhibits increasing warming of the climate. The temperature increase is visible in each month but is highest in winter (exceeding 1.5 °C per 100 years). Therefore, it may be assumed that the increase in air temperature, which has been particularly strong since the 1980s, showed the full effect of global warming in the brightening period that was previously masked by global dimming as shown in the sunshine duration records. The time course of air temperature for the whole study period (1884-2012) shows a statistically significant positive linear trend. The present warming is influenced probably by the air-quality improvement (brightening period) and an increase in sunshine duration in the years 1980-2012. [ABSTRACT FROM AUTHOR]

ABSTRACT The aim of this paper is to study the model's simulated frequency, track, intensity and location of cyclonic storms (CSs) and severe cyclonic storms (SCSs) in the Bay of Bengal (BoB), India. For the purpose, the PRECIS (Providing REgional Climates for Impacts Studies) a regional climate modelling system, of UK Met Office, is used. This model is integrated for the period 1961-1990 (baseline) and the future time period 2071-2100 (High emission scenario, A2). To run the model, the initial and lateral boundary conditions are supplied by UK Met Office. The analysis of frequency, track, intensity and location are carried out for May, June, September and October for the period 1961-1990 and 2071-2100. To evaluate the model's performance in simulating storms frequency during 1961-1990, chi square test is carried out with observed storms for the same period. The model's simulated frequency of storms is an overestimation of observations although the frequency of model's simulated storms during 2071-2100 is less than that of during 1961-1990. In general, model's simulated storms are found moving in the northwest direction from their initial location in all months during 1961-1990 and 2071-2100. In model's simulations, the drop in central pressure is relatively more in the months of May, June, September and October during 2071-2100 compared with that during 1961-1990. During 2071-2100, more intense storms may be possible in the months of May and June compared with that of September and October. It is observed that the model is able to simulate the initial locations of storms during 1961-1990 and 2071-2100 close to observations for the months of June and September, especially. [ABSTRACT FROM AUTHOR]

Downscaled regional climate simulations for Fiji and Federated States of Micronesia (FSM) from Coupled Model Intercomparison Project 3 (CMIP3) Global Coupled Models (GCMs) are carried out as part of the Pacific Climate Change Science Program (PCCSP) using the CSIRO stretched-grid Conformal Cubic Atmospheric Model (CCAM) for the period 1980-2000. The model simulations are performed at 60 km and at 8 km horizontal resolutions. The higher resolution is chosen to partly resolve the detailed orography of the countries selected, providing insight into the spatial distribution of temperature and precipitation for an individual island that GCMs are unable to represent. The downscaling is carried out in two steps. First, CCAM simulations are run on a global 60 km grid using bias-corrected sea surface temperatures (SST) and sea ice from six CMIP3 GCMs. Three of these 60 km simulations are then further downscaled to 8 km resolution over the two countries. The focus of this paper is validation of these high-resolution simulations against gridded analyses, satellite rainfall climatologies and available station data for rainfall and temperature for the period 1980-2000. The results show that high resolution orography plays an important role in capturing the current climate. The validation demonstrates that the 8 km simulations are capable of realistically depicting the current climate when the topography influences the wind flow and rainfall (Fiji), performing better than both the GCMs and the 60 km downscaled simulations. However, the performance of the 8 km simulations is similar to the GCM and 60 km simulations when topographical features are not present (FSM). [ABSTRACT FROM AUTHOR]

ABSTRACT This paper presents an analysis of winter climate variability based on daily mean temperature and precipitation data since 1970 in the Chic-Chocs Mountain range (located in the Gaspé Peninsula, Eastern Quebec, Canada). Mountain environments are particularly sensitive to rapid climate change and are therefore good indicators of recent global warming. The main goal of this study is to demonstrate how joint probability temperature/precipitation distributions can be used to estimate winter condition changes (trends) for six meteorological stations in the study area (the altitudinal range for the stations is from 5 to 574 m). The presence and persistence of snow cover was also estimated. Previous studies have shown a lack of evidence of significant trends in snow-cover characteristics (density, depth and snow water equivalent (SWE)) from the early 1980s to the present, despite an increase in temperature over the same period. A reanalysis of these data sets in addition to the use of a combination of temperature and precipitation data categorized into four modes (warm/wet, warm/dry, cold/wet and cold/dry) was also performed. Despite this new analysis, no clear evidence of climate change could be found in the study area over the last four decades. The results revealed that patterns and trends are quite different from one station to another, but when the environment is taken into account (valley or plateau, coastal versus inland) some apparent patterns emerge. [ABSTRACT FROM AUTHOR]

Climate projections for the UK exhibit substantial uncertainty, and this uncertainty is a hindrance to robust and timely decision making on both adaptation and mitigation policy issues. A large part of the uncertainty is associated with dynamical changes of the regional atmospheric circulation rather than thermodynamic changes which are better constrained by model simulations. Of particular importance for the UK is the extent to which the North Atlantic jet will change over coming decades and the impact this will have on weather and climate in the region. In this article, we propose the use of jet‐based storylines for assessing and communicating uncertainty in climate projections for the UK, wherein changes in each impact are explicitly conditioned on changes in the North Atlantic jet. This approach provides a framework for evaluating the impacts associated with a range of plausible future climate outcomes for the UK, including outcomes that may not be well represented in the current generation of climate models, and for communicating these potential outcomes. We construct a simple yet useful set of future jet storylines for both summer and winter and for 2°C and 4°C global warming levels and illustrate the utility of the approach by evaluating the impact of each jet storyline on future changes in UK precipitation. In doing so, we demonstrate that the relationships between the jet and UK precipitation are consistent between observed interannual variability and projected changes. This finding increases our confidence in projecting changes in UK precipitation associated with each storyline. [ABSTRACT FROM AUTHOR]

Various climatic factors and their interactions affect China's snow depth alterations. However, a measure of the relative importance of climatic factors regarding the variance in snow depth is lacking. Here, we use a heretofore largest dataset, quality‐controlled daily observations from 1,665 meteorological stations, and statistical analyses to identify proxy drivers and their contributions regarding regional variability and trends in China's snow depth and snow depth‐climate relationships from 1951 to 2019. Results show that seasonal snow depth alterations are substantial in China and caused by various climatic drivers. In winter, observed positive trends in the northwest and northeast of China mainly respond to augmentation in solid precipitation and snow accumulation in fall. For the Tibetan Plateau, the negative snow depth anomaly seems to respond to the rising air temperature below the freezing point along with some secular changes in solid precipitation and shallower fall snowpacks. All these trends in winter snow depth over the northwest, northeast, and Tibetan Plateau of China account approximately for 30% of the total interannual variance in spring snow depth in these regions. In the milder central north and south of China, snow accumulation is not evident. Besides solid precipitation and rising air temperature below the freezing point, atmospheric humidity is also notable for its effect on the interannual variance in winter snow depth in these regions. In spring and fall, however, the negative effect of warming climate on snow depth becomes remarkably more important. It seems that about 13–33% (12–50%) of the total interannual variance in the widespread decrease (insignificant perturbation), except for some weak increases in the northeast region (decreases in the Tibetan Plateau), of China's spring (fall) snow depth are caused by the rising air temperature below the freezing point. [ABSTRACT FROM AUTHOR]

Climate warming is steadily increasing drought risk in many regions of the world. However, the contribution of warming over the past few decades to drought evolution in China remains unclear. This study used the self‐calibrating Palmer drought severity index (sc‐PDSI) and a detrending experiment to quantify the contribution of warming to severe drought (sc‐PDSI < −3.0) characteristics (intensity, frequency, and duration) over China from 1980 to 2019. Differences in drought characteristics calculated from original and detrended temperature data were attributed to warming effects. The results showed that 93.8% of areas in China have experienced a significant (p <.05) warming trend from 1980 to 2019. Warming remarkably intensified severe drought characteristics across China. Without warming, the extent, frequency, and duration of severe droughts in China would reduce by 2.04%, 2.0%, and 0.82 months. In addition, there are apparent regional differences in the response of severe drought characteristics to warming. Severe drought characteristics in high elevations and high latitudes are more sensitive to warming than in other regions. [ABSTRACT FROM AUTHOR]

China's surface air temperature is increasing due to global warming, so it is interesting that how low temperatures would be changed during the growth period of winter wheat in future. We focused on the low temperatures of winter wheat from 2021 to 2050, using temperatures under the high emission scenario Representative Concentration Pathway 8.5 (RCP8.5) projected by the RegCM4.4 regional climate model. The results showed that the annual mean temperature was projected to increase by 0.42°C⋅decade−1 in the northern and by 0.35°C⋅decade−1 in the southern winter wheat region. Furthermore, the temperature was expected to increase rapidly in spring, which could advance the dates of flowering and the start of the grain‐filling period. Using the genetic parameters determined by the calibration and validation of WOFOST and bias‐corrected projected meteorological data, simulations of winter wheat growth were performed over the winter wheat region for 2021–2050. The simulated number of days to the flowering period of winter wheat for 2041–2050 was on average 6.5 days less than in 2021–2030, due to the spring warming. Because of the earlier start of the growing season, winter wheat could face negative effects by being subjected to low temperatures. Indeed, the number of low‐temperature days was projected to increase by 110% from 2041 to 2050 compared to 2021–2030, and the number of killing degree days (KDDs) is projected to increase by 120% at the same time. If the number of days to flowering did not change, the number of low‐temperature days and KDDs only changed slightly, showing that the negative influence of low temperature was mainly caused by the advancement of the flowering date. The effect of low temperature on growth was underestimated when the response of winter wheat growth to global warming was not considered. [ABSTRACT FROM AUTHOR]

The evolution of the frequency of dry/wet spells is a hot topic in global climate change research. The synergistic effects of dry/wet spells make their consequences far more significant than a single disaster, having considerable impacts on hydrology, ecology, and economies, especially in the context of global warming. In this study, the standardized precipitation evapotranspiration index (SPEI)‐based identification of dry/wet spells was used to explore the evolution of the frequency of dry/wet abrupt alternation (DWAA) events in the past four decades in China, makes up for the lack of research on the evolution of such compound disasters. China has been affected by dry/wet spells in many areas for a long time. Studies found that high‐frequency DWAA areas are concentrated in densely populated areas, China's essential food bases and core areas for economic development. Dry‐to‐wet (D–W) events and wet‐to‐dry (W–D) events basically increased or decreased at the same pace in this period. We innovatively find DWAA events (D–W events and W–D events) are projected to occur increasingly in a wider region of China. The frequency of D–W events across China has increased from 2.35 in the 1980s to 3.56 in the last decade, a 50% increase. On the other hand, W–D events increased from 2.6 to 3.23, increasing 24%. The three regions with the most remarkable changes in the past four decades are Inner Mongolia, northwest China, and north China, where D–W events increased by 121, 61, and 58%, respectively, and W–D events increased by 71, 57, and 61%, respectively. Hereby, it is vital to implement effective prevention against DWAA events in the area which has been neglected in the past decades because of lower frequency. These results may help policymakers develop suitable disaster mitigation plans for reducing the potential risks of extreme compound natural events. [ABSTRACT FROM AUTHOR]

Long‐term homogenized haze data are important to understand long‐term changes in air quality. However, there is uncertainty with regard to the trend of haze days due to frequent changes in weather phenomena and visibility observation methods used in China, thereby impairing the understanding of how air quality has varied over time due to global warming. In this study, we analysed historical data on haze days collected by surface weather stations across China and identified several issues in the raw data, including the incorrect identification of floating dust as haze, zero annual records of haze days due to a lack of visibility observations, and incorrect identification of haze as smoke. To correct the affected data, inhomogeneities in the raw annual haze‐day data series since 1980 were resolved by removing floating dust observations from the haze data. Then, automated visibility measurements recorded since 2014 were calibrated according to the percentage of visibility measurements using <10 km as a reference. Finally, based on the corrected and quality‐controlled visibility, relative humidity, and weather data, haze identification was performed to reconstruct daily haze‐day data for China between 1961 and 2020. During this process, automated observation data were homogeneously standardized with former manual observation data. The mean annual haze‐day trends of each region in China showed that the national average number of haze days gradually increased at a rate of 4.27 days per decade between 1961 and 2014, after which it decreased at −1.9 days per year. This trend was verified with the variations in PM2.5 concentrations. Overall, this study presents a novel method for determining the variation and spatial distribution of haze days over the last 60 years in China. The study findings will facilitate future analyses of the spatiotemporal trends of haze days, as well as atmospheric, environmental, and climatic changes over China. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) forming over the South China Sea (SCS) are hard to predict as they often make landfall shortly after their formation, resulting in a severe loss of properties and human lives to the adjacent countries. As climate change continues to pose a threat to our planet, it is of importance to understand how TCs forming over the SCS might change under global warming. In this study, we examine the potential changes of local TC activity over the SCS based on HiRAM (high‐resolution atmospheric model) simulations and projections at 0.23 × 0.23° horizontal resolution with the representative concentration pathway (RCP) 8.5 scenario. The SCS TC activity, including genesis number and passage frequency, is projected to decrease significantly (about 59%) in the late 21st century period (2075–2099) compared to the present‐day period (1980–2004). Analysing the genesis potential index (GPI) clearly indicates that the suppression of SCS TC activity comes mainly from the decrease in low‐level vorticity over the SCS. From a large‐scale circulation view, the decrease in low‐level vorticity can be linked to the weakened monsoon gyre along with the southwestward retreat of monsoon trough under global warming. [ABSTRACT FROM AUTHOR]

In recent years, Kilimanjaro and its vanishing glaciers have become an ‘icon’ of global warming, attracting broad interest. In this paper, a synopsis of (a) field observations made by the authors and (b) climatic data as reported in the literature (proxy and long-term instrumental data) is presented to develop a new concept for investigating the retreat of Kilimanjaro's glaciers, based on the physical understanding of glacier–climate interactions. The concept considers the peculiarities of the mountain and implies that climatological processes other than air temperature control the ice recession in a direct manner. A drastic drop in atmospheric moisture at the end of the 19th century and the ensuing drier climatic conditions are likely forcing glacier retreat on Kilimanjaro. Future investigations using the concept as a governing hypothesis will require research at different climatological scales. Copyright © 2004 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Global warming is likely to cause a progressive drought increase in some regions, but how population and natural resources will be affected is still underexplored. This study focuses on global population, forests, croplands and pastures exposure to meteorological drought hazard in the 21st century, expressed as frequency and severity of drought events. As input, we use a large ensemble of climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), population projections from the NASA‐SEDAC dataset and land‐use projections from the Land‐Use Harmonization 2 project for 1981–2100. The exposure to drought hazard is presented for five Shared Socioeconomic Pathways (SSP1‐SSP5) at four Global Warming Levels (GWLs: 1.5°C to 4°C). Results show that considering only Standardized Precipitation Index (SPI; based on precipitation), the SSP3 at GWL4 projects the largest fraction of the global population (14%) to experience an increase in drought frequency and severity (versus 1981–2010), with this value increasing to 60% if temperature is considered (indirectly included in the Standardized Precipitation‐Evapotranspiration Index, SPEI). With SPEI, considering the highest GWL for each SSP, 8 (for SSP2, SSP4, SSP5) and 11 (SSP3) billion people, that is, more than 90%, will be affected by at least one unprecedented drought. For SSP5 at GWL4, approximately 2 × 106 km2 of forests and croplands (respectively, 6% and 11%) and 1.5 × 106 km2 of pastures (19%) will be exposed to increased drought frequency and severity according to SPI, but for SPEI this extent will rise to 17 × 106 km2 of forests (49%), 6 × 106 km2 of pastures (78%) and 12 × 106 km2 of croplands (67%), being mid‐latitudes the most affected. The projected likely increase of drought frequency and severity significantly increases population and land‐use exposure to drought, even at low GWLs, thus extensive mitigation and adaptation efforts are needed to avoid the most severe impacts of climate change. [ABSTRACT FROM AUTHOR]

Water vapour is among the most critical variables that shape the Earth's energy balance and hydrologic cycle. Surface relative humidity (RH) and specific humidity (SH) are the main measures of atmospheric moisture. Long‐term changes in these variables in South Korea vary regionally as well as locally, but have not been explored using long‐term observation data. This study analyzes the annual trends of the means and SD of RH, surface air temperature, and SH in South Korea at 55 stations for the period 1973–2018. Three trend detection tests based on the Mann–Kendall test have been performed to detect trends at the 5% significance level for the annual and monthly statistics (means and SD) of these variables. Significant decreasing and increasing trends have been detected in the annual means of RH and air temperature, while the annual mean of SH has remained nearly constant. Overall, the surface air in South Korea has become drier over the study period, particularly in winter. The trend in RH and SH varies widely according to months to result in the increase in the SD over the annual cycle. The monthly SD of RH, SH, and surface air temperature show especially large positive trends for March and September, when the transition from winter to spring and summer to fall, respectively, occurs. [ABSTRACT FROM AUTHOR]

Technological advances have the potential to balance climate change mitigation and economic development. However, it remains unclear how much technological advances alone can mitigate climate change and the associated economic losses in the future. Through designing a suite of technological advances scenarios and using an earth system model with an integrated assessment model, we illustrate that rapid technological progress without production control might achieve the 2°C global warming target in the 2100s. Relative to a world of stagnant technology, the frequency (intensity) of extreme warm events at the end of the 21st century (2081–2100) would be reduced by ∼21% (5.5°C) via rapid technological advances, with a reduction in extreme precipitation (droughts) by ∼41% (10 times). Furthermore, fast technological advances may reduce the global economic losses linked with climate change at 2081–2100 by ∼21% and those in China related to floods (droughts) by 86% (67%). Our results highlight the potential of technological advances to fill the emission gap between the Paris Agreement and unconditional Nationally Determined Contributions and hence to efficiently mitigate global warming. [ABSTRACT FROM AUTHOR]

The global mean surface temperature does not increase monotonously over the past decades, with accelerated warming from the late 1970s to 1998 and followed by the warming slowdown during 1998–2013 (the so‐called warming hiatus). This study assessed and compared the temporal evolutions of sea surface temperature (SST) trends in the East China Seas (ECS, including Bohai, Yellow and East China Sea) and other key ocean regions. The results revealed an amplified response of ECS SST to both global warming acceleration and hiatus. This amplification was manifested as remarkably enhanced winter warming rates in the ECS of over 1.1 and 0.8°C⋅decade–1 for the 1980–1989 and 1990–1999, respectively, and as an obvious cooling trend of nearly −0.5°C⋅decade‑1 during 1998–2013. The enhanced response can be explained well by the combined effects of the Kuroshio Current (KC) and East Asian Winter Monsoon (EAWM). The weakened EAWM during the 1980s, accompanied by lower wind speeds and higher air temperatures, impeded the releases of latent and sensible heat fluxes from the ocean to the atmosphere, resulting in rapid ECS warming. During 1998–2013, the strengthened EAWM led to the enhanced cooling trend in the ECS. In addition, the volume transport of the KC east of Taiwan strengthened (weakened) during the 1990s (2000s), which might also have contributed to the enhanced warming (cooling) in the ECS. Our research suggests their sensitivity makes the ECS potentially vulnerable to the effects of global climate change, which has important implications regarding regional impact assessments. [ABSTRACT FROM AUTHOR]

Extreme climate events and related risk exposures in Huang‐Huai‐Hai (HHH) river basin were projected under global warming of 1.5–2°C using the high‐resolution combined dynamical and statistical downscaling dataset. Firstly, evaluation indicated that the dataset can well reproduce the spatial distribution of all temperature extremes and most of the precipitation extremes, providing a reliable ability for future projections. Then, projections showed that the hot events were projected to increase, while the cold events were projected to decrease substantially in the whole HHH river basin for 1.5°C and 2°C global warming. The additional 0.5°C of warming roughly accelerated the increase of extreme temperatures by 0.6°C, and increased the number of heat days by 2.7 days. In addition, the rainfall events and the precipitation intensity were projected to increase while the drought events were projected to decrease, with the slight changes due to the additional 0.5°C warming. The gross domestic product (GDP) exposures to heat events and heavy rainfall increased more than nine fold for 1.5°C and 2°C global warming, while the growing population (POP) exposures to that increased by more than 100% and 20%, respectively. For the increased exposures to heat events, the changes in GDP (POP) were as important as changes in interaction effect between climate and GDP (POP), while the exposures to heavy rainfall events was mainly dominated by GDP (POP). In addition, the enhanced interaction effect was the most important factor to the increase of exposures due to additional 0.5°C of warming. Notably, the largest increases of heat events and heavy rainfall events were projected in Huaihe river basin due to the additional 0.5°C warming, accompanied by greatest increase of exposures, implying larger risk in the future. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ETo) is one of the most important factors influencing hydrologic and climatic quantities, and increases in ETo are often considered as a primary cause for drying under global warming scenarios. Based on bias‐corrected data from the Half a degree Additional Warming, Prognosis and Projected Impacts (HAPPI) experiment, we investigated changes in ETo and drying across the Yellow River Basin (YRB) for 1.5°C and 2°C stabilized warming, relative to the current decade (2006–2015). We used changes in the climatic water deficit (WD: defined as precipitation (P) minus (ETo) to determine drying and wetting trends. Results projected that mean annual ETo would increase significantly over the whole YRB, under 1.5°C and 2°C warming scenarios, with an increase of 4.54% (1.57–7.59% full uncertainty range) and 7.66% (4.49–10.61%), at 1.5°C and 2°C, respectively, averaged over the YRB for the multi‐model mean. It is unclear whether the YRB source region (the NE region of the Tibet Plateau) would be drier or wetter under 1.5°C and 2°C of warming, although it is likely that the N regions of the YRB, and the whole YRB except for the source region will be drier under 1.5°C and 2°C warming scenarios, respectively. With an additional 0.5°C warming, further intensification of drying is projected in the whole YRB, resulting from a more pronounced increase in ETo, and lesser increase/decrease in P. The increased ETo projected under a 0.5°C additional warming was mainly attributed to rising maximum temperatures (tasmax). These results highlight the importance of ETo, in terms of potential future YRB drying, and our study suggests that limiting future warming to 1.5°C would impact regional drying the least. [ABSTRACT FROM AUTHOR]

This study investigated the change in precipitation concentration due to global warming based on the output of one experiment (a scenario of 1% CO2 increase per year) from 12 general circulation models provided by the Coupled Model Intercomparison Project Phase 5 (CMIP5). Two different indices were used to describe precipitation concentration: (a) concentration index (CI), which measures the evenness of total precipitation on wet days, and (b) precipitation concentration degree (PCD), which measures the evenness of the annual precipitation distributions over time. We found that widespread increases in CI were distributed over all land areas except for some arid areas, indicating a less uniform distribution of precipitation on wet days in a warming climate caused by CO2 increasing. We also found that the spatial patterns of changes in PCD are complex, with large regional differences. All of the results suggest a global‐scale readjustment of precipitation distribution in magnitude and timing. This kind of readjustment may have significant impacts on climatic and hydrological events and thus cause severe ecological and environmental damage. [ABSTRACT FROM AUTHOR]

Natural disasters in High Mountain Asia (HMA) are largely induced by precipitation and temperatures extremes. Precipitation extremes will change due to global warming, but these low frequency events are difficult to analyse using (short) observed time series. In this study, we analysed large 2000 year ensembles of present day climate and of a 2 and 3°C warmer world produced with the EC‐Earth model. We performed a regional assessment of climate indicators related to temperature and precipitation (positive degree days, accumulated precipitation, [pre‐ and post‐] monsoon precipitation), their sensitivity to temperature change and the change in return periods of extreme temperature and precipitation in a 2 and 3°C warmer climate. In general, the 2°C warmer world shows a homogeneous response of changes in climate indicators and return periods, while distinct differences between regions are present in a 3°C warmer world and changes no longer follow a general trend. This non‐linear effect can indicate the presence of a tipping point in the climate system. The most affected regions are located in monsoon‐dominated regions, where precipitation amounts, positive degree days, extreme temperature, extreme precipitation and compound events are projected to increase the most. Largest changes in climate indicators are found in East Himalaya, followed by the Hindu Kush and West and Central Himalaya regions. Western regions will experience drier summers and wetter winters, while monsoon dominated regions drier winters and wetter summers and northern regions a wetter climate year round. We also found that precipitation increases in HMA in a 3°C warmer world are substantially larger (13%) compared to the global average (5.9%). Additionally, the increase in weather extremes will exacerbate natural hazards with large possible impacts for mountain communities. The results of this study could provide important guidance for formulating climate change adaptation strategies in HMA. [ABSTRACT FROM AUTHOR]

This study investigates possible impacts of four global warming levels (GWLs: GWL1.5, GWL2.0, GWL2.5, and GWL3.0) on drought characteristics over Niger River basin (NRB) and Volta River basin (VRB). Two drought indices—Standardized Precipitation Index (SPI) and Standardized Precipitation‐Evapotranspiration Index (SPEI)—were employed in characterizing droughts in 20 multi‐model simulation outputs from the Coordinated Regional Climate Downscaling Experiment (CORDEX). The performance of the simulation in reproducing basic hydro‐climatological features and severe drought characteristics (i.e., magnitude and frequency) in the basins were evaluated. The projected changes in the future drought frequency were quantified and compared under the four GWLs for two climate forcing scenarios (RCP8.5 and RCP4.5). The regional climate model (RCM) ensemble gives a realistic simulation of historical hydro‐climatological variables needed to calculate the drought indices. With SPEI, the simulation ensemble projects an increase in the magnitude and frequency of severe droughts over both basins (NRB and VRB) at all GWLs, but the increase, which grows with the GWLs, is higher over NRB than over VRB. More than 75% of the simulations agree on the projected increase at GWL1.5 and all simulations agree on the increase at higher GWLs. With SPI, the projected changes in severe drought is weaker and the magnitude remains the same at all GWLs, suggesting that SPI projection may underestimate impacts of the GWLs on the intensity and severity of future drought. The results of this study have application in mitigating impact of global warming on future drought risk over the regional water systems. [ABSTRACT FROM AUTHOR]

Global warming acts to prolong thermal summers and shorten winters. In this work, future changes in the lengths and timing of four thermal seasons in northern Europe, with threshold temperatures 0 and 10°C, are derived from bias‐adjusted output data from 23 CMIP5 global climate models. Three future periods and two Representative Concentration Pathway (RCP) scenarios are discussed. The focus is on the period 2040–2069 under RCP4.5, which approximately corresponds to a 2°C global warming relative to the preindustrial era. By the period 2040–2069, the average length of the thermal summer increases by nearly 30 days relative to 1971–2000, and the thermal winter shortens by 30–60 days. The timing of the thermal springs advances while autumns delay. Within the model ensemble, there is a high linear correlation between the modelled annual‐mean temperature increase and shifts in the thermal seasons. Thermal summers lengthen by about 10 days and winters shorten by 10–24 days per 1°C of local warming. In the mid‐21st century, about two‐thirds of all summers (winters) are projected to be very long (very short) according to the baseline‐period standards, with an anomaly greater than 20 days relative to the late‐20th century temporal mean. The proportion of years without a thermal winter increases remarkably in the Baltic countries and southern Scandinavian peninsula. Implications of the changing thermal seasons on nature and human society are discussed in a literature review. [ABSTRACT FROM AUTHOR]

Future climate change predictions by global climate models or earth system models diverge significantly, most likely due to their different cloud responses to global warming. There is an uncertainty as to how the cloud frequency (or cloud fraction) and height will change, in turn, affecting the sign, and amount of cloud feedbacks. While satellite observations have been very useful in augmenting information on clouds, it is mostly related to cloud tops, and there is a lack of information on cloud base height (CBH). In this study, a unique record of CBH information was collected at 706 Automated Surface Observing System (ASOS) ceilometer stations to evaluate the ability of the North American Regional Reanalysis (NARR) model to correctly simulate similar information. It was found that NARR can capture the geographical distribution and the seasonal variation of CBH and cloud base frequency (CBF). On average, the CBF values of NARR were 7% fewer and the CBH values of NARR were 631 m lower than those from observations that span the distance from the surface to 7,600 m. NARR simulates CBH better in arid area in the west of the contiguous United States (CONUS) than in humid areas, where NARR frequently predicted cloud bases too low compared with observations. In the west coast area of the CONUS, the discontinuity between high cloud bases over arid inland areas and low marine cloud layers from the Pacific Ocean over coastal areas produced especially large deviations between the NARR‐simulated and ASOS‐observed CBHs. [ABSTRACT FROM AUTHOR]

We present an analysis of the global annual mean surface temperature anomaly in 2014, 2015, and 2016 based on five datasets of historical observational records of surface temperature. These three years are the three warmest on record in all but one of the datasets. The largest warming occurred over land, especially at high latitudes. Since the strong El Niño event that occurred in 2015/2016 was similar to the 1997/1998 El Niño, we compared the 2014–2016 period with 1998, the warmest year in the 20th century. The contribution to the annual mean surface temperature anomaly of climate variations at different time scales was assessed using ensemble empirical mode decomposition. Results based on the HadCRUT4 dataset suggest that the interannual component may have contributed an anomaly of −0.01°C in 2014, 0.12°C in 2015, and 0.06°C in 2016. These values are substantially lower than the contribution in 1998 (0.18°C). In comparison, the combined contribution of the decadal‐to‐multidecadal (DM) component and the long‐term warming trend was 0.64°C in 2014, 0.70°C in 2015, and 0.77°C in 2016, which are substantially greater than that in 1998 (0.41°C). Similar results were obtained using the other four datasets. The larger contribution from the DM component and the long‐term warming trend implies that warmer years like 2014–2016 may occur more frequently in the near future. We conclude that the so‐called warming hiatus has faded away. [ABSTRACT FROM AUTHOR]

An improved knowledge of long‐term climatic variations over the Altai‐Dzungarian region will increase our understanding of the current climate and help to predict the effects of global warming on future water availability in this region. We sampled 77 Larix sibirica Ledeb. trees at upper and lower treelines in the southern Mongolian Altai mountains and reconstructed temperature and precipitation for longer periods than previous studies from this area. We reconstructed mean June–July air temperatures for the period 1402–2012 and June–December precipitation for the period 1569–2012 based on tree ring width chronologies. The temperature and precipitation reconstructions explain 39.7 and 41.3% of the respective station observation variance during the common periods. The precipitation reconstruction shows alternating wet and dry conditions during the Little Ice Age (1580–1874) followed by more stable conditions until a late 20th century wetting. The temperature reconstruction attributes the warmest period to the 20th century, which follows cooler periods related to volcanic and low solar activities during the Little Ice Age. Long‐term climatic variation and change over the Altai‐Dzungarian region is inferred from the analysis of the combined temperature and precipitation reconstructions for the common period 1580–2012. Accordingly, this region has become warmer since 1875 as the number of warm/moist and warm/dry years increased by 2 and 14%, respectively, while the number of cool/moist and cool/dry years both decreased by 8% compared to the Little Ice Age. Our findings also reveal a late 20th century cool and wet period, which has also been observed across other mountainous areas of China and Nepal. This period was most probably caused by volcanic‐induced cooling and coincided positive phases of the Arctic Oscillation and North Atlantic Oscillation promoting an intensified subtropical westerly jet and a positive summer rainfall anomaly over the Altai‐Dzungarian region. [ABSTRACT FROM AUTHOR]

Atmospheric studies document both a periodic variability in the winter temperatures in the Kara Sea region related to internal Arctic climate variability and a recent trend of winter warming—one of the strongest warming trends in the whole Arctic. This study aims to analyse side by side with other energy budget terms the contribution of horizontal heat and moisture advection to the observed recent warming. The atmospheric energy budget terms vertically integrated from the surface up to 500 hPa are estimated using the ERA‐Interim reanalysis for the period 1979–2014. The core of this study is to relate variability and changes in heat fluxes in the Kara Sea region to synoptic‐scale processes using the Russian weather‐type classification system. Singular spectrum analysis is applied to the heat flux data which were previously stratified into changes due to changes in frequency and due to changes in amplitude. We have shown that the multi‐decadal variations in the horizontal heat advection (now on a rising phase) are comparable to the positive trend in the turbulent heat fluxes due to sea ice reduction, although relatively weaker. We have also found that the changes in sensible heat flux (a constant increase in the first principal component since 1999) is a general regional feature and not related to any weather pattern, while the changes in horizontal heat advection are clearly related to the changes in frequency of the weather type A (characterized by a low‐pressure system in the central Arctic surrounded by high pressure in the continents, winds of S, S‐W direction and a positive horizontal heat advection and surface temperature anomaly over the Kara Sea) which are periodic in nature with a period of about 22 years. In recent years (at least until 2012) not only is warm air advection, associated with A type, more frequent, but it also brings much more energy from the continent to the Kara Sea compared to the reference period (1980–1990). This is most probably related to the increase in the radiatively forced surface air temperature at the source. There are number of sources of heat to the cold Arctic in winter period and neither of them is stable in time, currently leading to Arctic warming that is pronounced over the Kara Sea. The major source is turbulent heat transferred to the atmosphere in the areas of ice‐free water as shown in the image. We discuss here the second source too—the transport of heat to the Arctic from the middle latitudes by synoptic waves and how this process changes in time due to atmospheric circulation re‐configuration. [ABSTRACT FROM AUTHOR]

This study examines the spatio‐temporal changes of heat risk in South China and the possible effects of urbanization using a dynamic method for classifying urban and rural sites based on time‐varying DMSP‐OLS night‐time light images. Ten different indicators are analysed, which include daily means and consecutive heat wave (HW) measures at 86 stations in Guangdong Province from 1971 to 2014. Results show that these heat risk indicators have been intensifying across the study area, and the intensifying trends are more profound in urbanized and populated areas (e.g., the Pearl River Delta) than less urbanized inland areas. In addition, the mean of daily maximum, minimum, and mean temperatures in urban (rural) areas increased by 0.35 (0.24), 0.21 (0.11), and 0.23 (0.13) °C per decade, and urbanization contributes to 31, 48, and 43% of the total trends, respectively. We also estimate that the urbanization effects on (contributions to) the increasing hot days and warm nights are 2.52 (36%) and 4.21 days per decade (53%). Moreover, urbanization induces an additional increase in the frequency and participating days of HW by 0.44 events (49%) and 3.96 days (51%) per decade, respectively. Effects of urbanization on increasing heat risks in South China are investigated by dynamically classifying meteorological stations into urban and rural types based on time‐varying DMSP‐OLS nighttime lights images. We found that both daily extremes and consecutive heat wave measures have been increasing during the past decades, and the increasing trends are especially strong in highly urbanized and densely populated areas. It is estimated that the urbanization contribution to the increasing heat risks reaches 50%. [ABSTRACT FROM AUTHOR]

As the climate changes, increasing variations in environmental factors directly influence crop cultivation at different magnitudes over a broad range of local communities worldwide. As a result, there is an urgent need to develop local impact assessments and adaptation strategies for use at local, rather than national or global, levels. In this study, we predicted the future frost damage of kiwifruit in the Jeonnam province, Korea, as a case study for the local impact assessment of climate change. This study included a series of models that integrated both the biological responses of plants and the physical influences of climatic factors. First, potential changes in the suitable area for kiwifruit cultivation under a changing climate were simulated using downscaled high resolution (1 km) climate data. Through the development of a frost‐forecasting model and linking it to a kiwifruit phenology model, we also assessed the interaction of plant and climatic factors. Because of the warming climate, the last frost date in spring occurred 13.7 days earlier in average under climate change. Nevertheless, the potential risk of spring frost damage of kiwifruit continued to exist at a similar magnitude in the future. Additional study at the county level indicated that the date of bud burst is advancing even faster than the last frost date (approximately 1 day per every decade), resulting in the increasing risk of spring frost damage for kiwifruit through 2100. In this study, the local impacts of climate change on kiwifruit frost damage were assessed using the integrated modelling approach. As such, local policy makers and stakeholders will be able to prepare more realistic adaptation strategies to cope with upcoming threats in a changing climate. In this study, the local impacts of climate change on kiwifruit frost damage in the Jeonnam Province, Korea were assessed using an integrated modelling approach. First, optimal areas for kiwifruit cultivation under a changing climate were simulated, resulting in almost 98% of lands becoming "Highly suitable" in the 2080s. In addition, through the development of a frost‐forecasting model and linking it to a kiwifruit phenology model, we found that the potential risk of spring frost damage of kiwifruit continued to exist at a similar magnitude as shown in the figure below. [ABSTRACT FROM AUTHOR]

The "Warm‐Arctic/Cold‐continents" (WACC) winter weather pattern is investigated using the European Centre for Medium‐Range Weather Forecasts 20th Century reanalysis data (ERA20C) spanning 1901–2010. Both the 1920–1940 and 1990–2010 periods are characterized by Arctic amplification (AA) and mid‐latitude continental cooling, although the Arctic warming signal for 1990–2010 is twice as strong as that for 1920–1940. Significant weakening in the mid‐latitude polewards temperature gradient and zonal wind, wavier upper‐level flow character, and strong regional blocking frequency/intensity changes are also detected during both AA periods. These results based on statistical analyses highlight the possible role of AA in affecting mid‐latitude weather patterns, but further work is needed to quantify the influence of AA on particular mid‐latitude dynamical features. "Warm‐Arctic/Cold‐continents" (WACC) winter weather pattern is clearly shown in both 1920–1940 and 1990–2010 periods. Significant weakening in mid‐latitude polewards temperature gradient and zonal wind, wavier upper‐level flow character, and strong regional blocking frequency/intensity changes are detected during both periods. Noticeable regional differences of trends in these dynamical features between AA1 and AA2 period suggest the need for a more in‐depth dynamical meteorological investigation of regional mechanisms of AA and mid‐latitude weather linkages. [ABSTRACT FROM AUTHOR]

Inhomogeneities in climate data are the main source of uncertainty for secular warming estimates. To reduce the influence of inhomogeneities in station data statistical homogenization compares a candidate station to its neighbours to detect and correct artificial changes in the candidate. Many studies have quantified the performance of statistical break detection tests used in this comparison. Also, full homogenization methods have been studied numerically, but correction methods by themselves have not been studied much. We analyse the ANOVA (analysis of variance) joint correction method, which is expected to be the most accurate published method. We find that, if all breaks are known, this method produces unbiased trend estimates and that in this case the uncertainty in the trend estimates is not determined by the variance of the inhomogeneities, but by the variance of the weather and measurement noise. For low signal‐to‐noise ratios and high numbers of breaks, the correction may also worsen the data by increasing the original random unbiased trend error. Any uncertainty in the break dates leads to a systematic undercorrection of the trend errors and in this more realistic case the variance of the inhomogeneities is also important. Inhomogeneities in climate station data may produce spurious temperature trends. After the detection of the breaks the data have to be adjusted by a correction scheme. We analyse simulated data with known properties to assess their skill. The scatterplot compares the trend error before and after the adjustment. The original trend error is largely reduced, but not completely removed. [ABSTRACT FROM AUTHOR]

Extreme precipitation and associated flooding cause severe damage to society and the environment. Future climate projections suggest an intensification of precipitation extremes in many regions. However, there is an increasing need for climate change impact assessment at higher spatial resolution, particularly for regions with complex geography such as Southeast Asia (SEA). In this study, we analysed the NASA Earth Exchange 0.25° resolution daily precipitation projections from an ensemble of 20 climate models under two emission scenarios RCP4.5 and RCP8.5. The variability in future precipitation projections is analysed and quantified for six geographical subregions, two climatological regions (wet and dry), and the low‐elevation coastal zones in SEA. Various aspects of precipitation structure are studied using indices that characterize precipitation amount, number of heavy precipitation days, extreme precipitation amount, and maximum daily precipitation at annual and seasonal scales. The results show substantial increases in mean and extreme precipitation in many parts of SEA by the end of the 21st century under both emission scenarios, thus increasing the region's vulnerability to precipitation‐driven hazards. The projected centennial increase in total annual precipitation relative to the baseline period of 1970–1999 when averaged over all land grid cells is about 15% under RCP8.5 scenario, with larger values (∼20%) over mainland SEA and Philippines and smaller values (∼6%) in Java island. The projected changes in extreme precipitation are stronger compared to the total annual precipitation under both emission scenarios. The New Guinea and Java regions show the largest and smallest increases in annual maximum daily precipitation, with ensemble mean values of 30 and 17%, respectively, under RCP8.5 scenario. The results also reveal large inter‐model spread in projected changes, particularly during boreal winter and summer months. The study assessed changes in different precipitation characteristics such as the annual maximum daily rainfall (shown here) over nine regional masks in Southeast Asia for the time period 2070–2099 relative to the baseline period of 1970–1999. Results indicate substantial changes in total precipitation and extreme precipitation, particularly for the RCP8.5 scenario. The regional and seasonal variability in future changes and associated uncertainties are described in detail in this study. [ABSTRACT FROM AUTHOR]

A number of studies on the surface warming in the Korean Peninsula reported that there has been a notable increasing trend of surface air temperatures over the past several decades. Here, by analysing long‐term surface air temperature data at 12 stations in South Korea that have records longer than 60 years, the authors show that the warming of spring and autumn temperatures is characterized by quasi‐linear increases with time whereas the warming in winter and summer is characterized by one or two abrupt jumps. Change‐point analysis of the seasonal‐mean temperature time series shows that abrupt jumps in winter temperatures occurred in the late 1940s and late 1980s, while the jump in summer temperatures occurred in 1994 at most stations. The shape of the frequency distribution of the daily‐mean temperature anomalies at all stations shifts to the warmer side after the jumps for both winter and summer. This shift in turn results in the decrease of cold extremes in winter and the increase of warm extremes in summer at all stations. Our results indicate that recent temperature records in South Korea are characterized by the two different types of warming according to seasons. [ABSTRACT FROM AUTHOR]

This study evaluates the ability of the Regional Climate Model (RegCM4) to reproduce the observed rainfall and wind over West and central Africa (WCA) during two contrasting years of the Atlantic cold tongue (ACT): the very cold in 1992 and very warm in 2007 depicted by the Caniaux et al.’s index. The convective schemes of Kuo, Massachusetts Institute of Technology‐Emanuel (Ema) and Grell with closure assumptions of Arakawa–Schubert (GAS) and Fritch–Chappel (GFC) were compared and the best scheme was tested to study the sensitivity of WCA climate to ACT in August of each chosen year—the month which follows that of the peak of ACT. Comparisons of simulations for 1992 and 2007 reveal that some areas are sensitive to extreme ACT events. The regional distribution of observed precipitation (wind) in August 2007 was heavier (lower intensity) than that for the 1992, particularly in West than central Africa region. From GPCP data, it is observed that the range of Cameroon highlands and the Bauchi Plateau of Nigeria are not significantly affected by the ACT. It is shown that rainfall of some subregions is very sensitive to ACT. The GFC scheme is capable of reproducing the amount and distribution of the precipitation for the 2 years in the ACT area, the west and east Guinean coasts, and failed to reproduce the rainfall in west and central Soudano–Sahel regions and East Africa. However, the Kuo scheme reproduces well in these three zones. Contrarily to rainfall, the Ema scheme better reproduces, but overestimating, the wind distribution in the Sahara region. GFC better simulates the wind speed sensitivity to ACT far from the coast in Soudano–Sahel and Nigeria–Cameroon zones. The GAS and Kuo are not well correlated with ERA‐Interim in WCA. Most of the schemes adequately mimic the African easterly jet structure. [ABSTRACT FROM AUTHOR]

ABSTRACT: During the last decades, the effects of global warming have become apparent also in Europe, causing relevant impacts in many sectors. Under projected future global warming, such a tendency can be expected to persist until the end of this century and beyond. Identifying which climate‐related impacts are likely to increase, and by how much, is an important element of any effective strategy for managing future climate risks. This study investigates whether energy demand for cooling and heating buildings can be expected to increase or decrease under climate change. Two indicators of weather‐related energy consumption for heating and cooling buildings are considered: heating degree‐days (HDD) and cooling degree‐days (CDD). The evolution of these indicators has been analysed based on 11 high‐resolution bias‐adjusted EURO‐CORDEX simulations for two emission representative concentration pathways (RCP4.5 and RCP8.5). Both indicators have been validated over the period 1981–2010 using an independent data set that contains more than 4000 station data, showing very high correlation over most of Europe. Trends of HDD and CDD from 1981 to 2100, together with their uncertainties, are analysed. For both RCPs, all simulations project a significant decrease for HDD, especially over Scandinavia and European Russia, and an increase of CDD which peaks over the Mediterranean region and the Balkans. Overall, degree‐day trends do not show remarkable differences if population weighting is applied. If a constant population scenario is considered, the decrease in HDD will outbalance the increase in CDD in the 21st century over most of Europe. Thus the related energy demand (expressed as Energy Degree‐days, EDD) is expected to decrease. If, however, population projections over the 21st century are included in the calculations, it is shown that despite the persisting warming, EDD will increase over northern Europe, the Baltic countries, Great Britain, Ireland, Benelux, the Alps, Spain, and Cyprus, resulting in an overall increase in EDD over Europe. [ABSTRACT FROM AUTHOR]

ABSTRACT: We use the Global Historical Climatology Network – daily database to calculate a nonparametric statistic that describes the rate at which all‐time daily high‐ and low‐temperature records have been set in nine geographic regions (continents or major portions of continents) during periods mostly from the mid‐20th century to the present. This statistic was defined in our earlier work on temperature records in the 48 contiguous United States. In contrast to this earlier work, we find that in every region except North America all‐time high records were set at a rate significantly (at least 3σ) higher than in the null hypothesis of a stationary climate. Except in Antarctica, all‐time low records were set at a rate significantly lower than in the null hypothesis. In Europe, North Africa and North Asia the rate of setting new all‐time highs increased suddenly in the 1990s, suggesting a change in regional climate regime; in most other regions there was a steadier increase. [ABSTRACT FROM AUTHOR]

ABSTRACT This study analysed the time series of tropical cyclone ( TC) frequency during October-December ( OND) for 32 years (1980-2011). There was a strong decreasing trend of TCs until recently, and the TC sharply decreased from 1996 after the statistical change-point analysis was applied to this time series. To investigate the cause of such recent decrease in TC genesis frequency, the differences ( TC activity and its relation to large-scale environments, and others) between the mean of the period from 1996 to 2011 and the mean of the period from 1980 to 1995 were analysed. TCs during the period 1996-2011 mainly occurred in the western region of tropical western North Pacific ( TWNP), whereas during the 1980-1995 period they mainly occurred in the eastern region of TWNP. In the analysis of differences periods in the 850 hPa and 500 hPa stream flows between the two periods, an anomalous huge anticyclone existed from the north Pacific to the TWNP, and an anomalous huge cyclone existed to the west of 125°E including the East Asian continent. In other words, this is a typical low-west-high-east pressure system that appears in East Asia during summer, and this anomalous pressure system pattern caused the low TC genesis frequency during the 1996-2011 period. The low-west-high-east anomalous pressure system pattern which has been strengthened recently in East Asia suggests that the East Asian winter monsoon ( EAWM) has weakened during the 1996-2011 period. As a result, the amount of snow depth decreased in many areas of the East Asian continent except for the North China and the ground heat net flux also increased in many areas. This weakening of the EAWM strengthened the anomalous huge anticyclone in the TWNP as well as in the central North Pacific, which caused the low TC genesis frequency during the OND in recent years. [ABSTRACT FROM AUTHOR]

ABSTRACT The village Haparanda in northern Sweden hosts one of the longest meteorological station records in Europe depicting climate conditions in the subarctic. Since the station was relocated several times, moving gradually from urbanized to more rural areas, the record is likely biased by anthropogenic influences. We here assess these influences and demonstrate that even in villages urban heat island biases might affect the temperature readings. We detail a method to quantify this bias and remove it from the long Haparanda station record running since 1859. The correction is based on parallel temperature measurements at previous station locations in Haparanda. These measurements revealed a distinct urban warming pattern, largest in minimum temperatures during summer, since urban geometry and its heat capacity amplify additional warming and night-time heat release, especially during a period of high insolation and calm conditions. Due to the station movement from the village centre to the outskirts, the net correction results in an additional warming trend over the past 155 years. The trend increase is most substantial for minimum temperatures (+0.03 °C 10 years−1). Maximum and mean temperatures are less affected (+0.01 °C 10 years−1). An increase in trend is even more severe if the 20th century is regarded exclusively, displaying a rise in annual mean temperature trend by +0.03 °C 10 years−1 and +0.07 °C 10 years−1 in annual minimum temperatures, respectively. Our approach of using actual temperature differences between historical station locations did not take into account other factors that might have influenced the data such as changes in instruments or observers. The presented adjustment for temperature residuals caused by a change in historical station locations might be considered as a minimum approach to improve long-term temperature readings. The adjustment of the Haparanda station record results in an increased warming trend, thereby adding critical information to the evaluation and explanation of 20th century anthropogenic warming. [ABSTRACT FROM AUTHOR]

This study investigates the El Niño-Southern Oscillation (ENSO)-related seasonal variations in precipitation extremes based on the observed daily precipitation dataset of 23 meteorological stations in Malaysia, spanning a period of 46 years from 1966 to 2011. The extreme indices were a subset of the Expert Team for Climate Change Detection and Indices (ETCCDI) that covers the duration, frequency and intensity aspects of precipitation extremes. Seasonal composites of 'El Niño minus neutral' and 'La Niña minus neutral' years of these indices were computed based on El Niño and La Niña occurrences during the period. The results showed that the ENSO-related variations in precipitation extremes were generally coherent with the variations in total precipitation. Generally, dry (wet) precipitation extremes tended to enhance during El Niño (La Niña); however, this was dependent on season and location. The El Niño and La Niña influences on precipitation extremes were not entirely linear. While the impacts of El Niño and La Niña were generally opposite for most locations and seasons, there were cases where both exerted in-phase influences. The impacts were also dependent on the intensity of the event itself. While the El Niño impacts were generally coherent across different intensities, La Niña can have entirely different impacts among different categories. During December–January–February (DJF), strong (moderate) La Niña caused a significant decrease (increase) in wet precipitation extremes over the Peninsular Malaysia. This was related to the broadening (narrowing and westward displacement) of the anomalous cyclonic circulation over the western north Pacific during strong (moderate) La Niña. Hence, the likelihood for widespread flooding over the east coast of the Peninsular Malaysia during DJF increases during moderate but not during strong La Niña events. [ABSTRACT FROM AUTHOR]

The purpose of this study is to assess the ability of Coupled Model Intercomparison Project 5 (CMIP5) models in reproducing the variability and change of the austral summer precipitation observed in Southeastern South America (SESA) along the 20th century and beginning of the 21st. Models show a reduction in mean precipitation biases and inter-model dispersion, and a significant improvement in the representation of the leading pattern of precipitation interannual variability (EOF1), in comparison with Coupled Model Intercomparison Project 3 (CMIP3) models. Changes of the EOF1 activity in the present climate, as represented by both, climate model simulations and rainfall gridded datasets, evidence an increase of the frequency of EOF1 positive events (associated with positive precipitation anomalies in SESA and negative ones in the South Atlantic Convergence Zone) and a decrease of the frequency of EOF1 negative events. Nevertheless there are still large uncertainties due to model differences and the internal variability of the climate system. In order to reduce the impact of model uncertainties, an ensemble of the climate simulations that represent better the features associated with EOF1 activity was built, regardless to which model they correspond. The results obtained with this ensemble confirm that largest precipitation trends in SESA are those represented by climate simulations associated with an increase (decrease) of EOF1 positives (negative) events. It was also found that positive precipitation trends in SESA resulted from climate simulations forced by anthropogenic sources are the largest and significantly different from those from simulations forced by natural sources only, which are not significantly different from zero. [ABSTRACT FROM AUTHOR]

An important step in developing climate forecasts is the identification of an appropriate set of predictors. Seasonal rainfall forecasts for South Australia (SA) currently have low predictive skill. It is hypothesised that this is because the large-scale climate processes influencing SA's rainfall variability have yet to be completely identified and therefore are not adequately represented in forecast models. Here, relationships between large-scale climate influences and rainfall in SA are assessed with a focus on methods that account for non-linearities inherent in the climate system. A threshold method and also a novel method for climate predictor selection, Partial Mutual Information, are used to establish the hierarchy of importance of the key influences. From a large suite of potential predictors, variability in the Subtropical Ridge intensity, blocking and the gradient of sea surface temperatures (SSTs) in the tropical central and eastern Indian Ocean are found to be key indicators of seasonal rainfall variability in SA. Interactions between processes are shown to increase the amount of variability accounted for and therefore need to be better considered when producing seasonal forecasts. Notably, the view of which climate process(es) is(are) important changes depending on the input variables used, suggesting that it is not wise to make a priori assumptions about what is or is not important. Furthermore, even a perfect forecast of El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD), the focus of forecasting efforts in Australia, will not necessarily lead to an improvement to forecast skill in SA given that these processes are not key for the region. The results of this analysis can inform the development of existing and new statistical and dynamical seasonal forecasting systems for SA, and for other regions where the impacts of climate variability are significant but not necessarily dominated by ENSO and IOD. [ABSTRACT FROM AUTHOR]

The Chajnantor plateau is located in the Atacama Desert at over 4800m above sea level. The plateau features a large fraction of days during the year where dry and stable atmospheric conditions predominate. The suitability of the type of astronomy observations routinely made at sites across the Chajnantor region at different times of the year depends on the variability of atmospheric water vapour. In this work, we study seasonal and intraseasonal variability associated with periods of large and low precipitable water vapour (PWV) in the Chajnantor region over 32 years. We establish large-scale conditions favourable for above- and below-normal PWV for each of the four seasons. We also explore whether intraseasonal PWV variations are related to the Madden-Julian Oscillation (MJO). Below-normal PWV in winter, spring, and autumn seasons was found associated with mostly zonal 500-hPa winds, which advect drier than normal air from the anticyclone over the eastern portions of the southeast (SE) Pacific Ocean. In summer, periods with below-normal PWV were found to have anomalously south-westerly winds at mid-levels, also indicating transport of anomalously dry air from the stable SE Pacific. In winter, spring, and autumn seasons, above-normal PWV was generally associated with north-westerly mid-tropospheric wind anomalies, indicating advection of above-normal PWV from the subtropical and tropical regions of the SE Pacific Ocean. Above-normal PWV conditions in summer were associated with nearly calm winds at 500 hPa. Months and phases of the MJO for the most extreme anomalies of PWV for each season agreed well with the seasonal anomalies. Furthermore, three independent reanalysis data sets generally agreed on MJO phases associated with largest positive and negative PWV anomalies. This agreement provides evidence for the first time that the MJO modulates the PWV content over the Atacama Desert. [ABSTRACT FROM AUTHOR]

Simulations of the regional climate model REMO at 25 and 50 km (0.44° and 0.22°, respectively) grid spacing are evaluated over Central Africa for the period 1998-2010. The model's ability to simulate various aspects of the observed climate is assessed with a main focus on precipitation characteristics. The results show that the REMO model has a good skill to reproduce the main regional features of the mean climate fields as well as seasonal and annual cycles, although some biases still exist. The model captures the variability in precipitation anomalies between different events associated with El Niño/Southern Oscillation. Generally, the findings remain largely insensitive to the refinement of the horizontal resolution, especially when considering the regional scale. This points the fact that the model dynamical and physical setup may have to be adjusted when setting a focus on the Central African region, in order to better represent the climate mechanisms. It is further found that REMO is capable of capturing the basic features of climatic extremes and accurately represents the shape of the frequency distribution of daily precipitation data. Daily characteristics of precipitation are simulated much better by REMO at 25 km. [ABSTRACT FROM AUTHOR]

ABSTRACT Under global warming, increasing temporal variability of climatic factors at various timescales (e.g. from inter-daily to inter-annual) has been reported in many places of the world over the past decades. The changes of temporal variability can be characterized by more extreme climate, such as more frequent and intensive heavy precipitation, less light rain days, and longer dry spells. These changes can subsequently bring about more frequent and intensive hydrologic extremes, including floods and droughts. This study shows that increase in inter-daily variability of precipitation and temperature not only triggers more intensive hydrologic extremes, but also causes considerable impacts on long-term water availability. Sixteen climate scenarios are designed to separate overall changes of precipitation and temperature into two aspects: (1) change in monthly mean and (2) change in inter-daily variability. Runoff of the Pearl River Basin ( PRB) is simulated by the variable infiltration capacity ( VIC) model under these scenarios. The results indicate that increase in inter-daily variability of the climate alone can lead to considerable increase in long-term water availability with reduced actual evapotranspiration ( AET). The simulations also show that the inter-daily interaction between precipitation and temperature (i.e. lower temperature on a rain day) is important for long-term hydrologic simulations. The changing directions of simulated AET under scenarios with this interaction are opposite to those under scenarios without the interaction. [ABSTRACT FROM AUTHOR]

ABSTRACT Valleys can trap cold air to form Valley Cold Pools ( VCPs). Characterized by stable stratification and weak winds, VCPs, especially those that last over multiple days, can produce adverse effects such as poor visibility and severe air pollution. Using the gridded data set of the North American Regional Reanalysis ( NARR) for the period of 1979 through 2012, this study examines the climatology of VCPs in the western United States with a focus on spatial and temporal variability. The results reveal a widespread occurrence of short-lived (1-2 days) VCPs over both the mountainous areas of the West and the Northern Plains. Longer VCP episodes, however, tend to be limited to large basins/valleys in the Northwest and the Intermountain West. The leading mode of variability in the annual number of cold-season multi-day VCP event anomalies appears to be linked to a sea-surface temperature anomaly pattern typically found during the warm phase of Pacific Decadal Oscillation. Corresponding to the positive phase of the leading mode of variability is an anomalous 500- hPa ridge over the western United States induced by a Rossby wave train, which, by blocking cold-air intrusions and producing mid-level subsidence warming, leads to more persistent VCP episodes in the western United States. In addition to large-scale wintertime circulation anomalies, local surface temperature anomalies also contribute to the variability. [ABSTRACT FROM AUTHOR]

ABSTRACT 'Tipping points' ( TPs) are thresholds of potentially disproportionate changes in the Earth's climate system associated with future global warming and are considered today as a 'hot' topic in environmental sciences. In this study, TP interactions are analysed from an integrated and conceptual point of view using two qualitative Boolean models built on graph grammars. They allow an accurate study of the node TP interactions previously identified by expert elicitation and take into account a range of various large-scale climate processes potentially able to trigger, alone or jointly, instability in the global climate. Our findings show that, contrary to commonly held beliefs, far from causing runaway changes in the Earth's climate, such as self-acceleration due to additive positive feedbacks, successive perturbations might actually lead to its stabilization. A more comprehensive model defined TPs as interactions between nine (non-exhaustive) large-scale subsystems of the Earth's climate, highlighting the enhanced sensitivity to the triggering of the disintegration of the west Antarctic ice sheet. We are claiming that today, it is extremely difficult to guess the fate of the global climate system as TP sensitivity depends strongly on the definition of the model. Finally, we demonstrate the stronger effect of decreasing rules (i.e. mitigating connected TPs) over other rule types, thus suggesting the critical role of possible 'stabilizing points' that are yet to be identified and studied. [ABSTRACT FROM AUTHOR]

We studied rainfall characteristics of Brazil for the period 1979-2011. This is an update for an earlier study with data from 1958 to 1978. We compared the three consecutive wet and dry months in the two data sets. In the northern most part rainy season earlier was in April to July and now it is occurring later. In a large part of the south central region the rainy season in austral summer and dry season in austral winter did not change. However, to the east of this region rainy season in the latter data occurs earlier. Calculation of linear tendencies showed, that over the northern Amazon region there is a significant increase of rainfall. This agreed with previous results. Over this region dry season is becoming drier and wet season wetter. In the west of Northeast Brazil (NEB) there is an increase of rainfall. In southeast Brazil there is a region of highly significant decrease of rainfall in both wet and dry seasons. This is confirmed in our analysis on river discharges in Sao Paulo and Minas Gerais states. The negative tendencies in rainfall have great impact on the hydroelectric generation not only in this region but also at the national level because the hydroelectric dams furnish energy on a national level. The increase in rainfall in Northern Amazon is probably associated with Atlantic warming that resulted in higher moisture transport from east. The decrease of rainfall in southeast Brazil seems to be associated with the plummet of rain producing systems from south due to increase of mean sea level pressure in the south. [ABSTRACT FROM AUTHOR]