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Many regions around the world are facing climate changes, with substantial increase in air temperature over the past decades, which is mainly related to continental and global warming forced by the higher greenhouse gas (GHG) emissions. The objectives of this study were to use the Köppen climate classification to detect local climate change based on a historical series of 100 years and to assess if such change is related to those that are occurring in other spatial scales as a likely consequence of increasing GHG. This paper brings a content full of innovative results. The study area presented an average annual air temperature increase by 0.9 °C between 1917 and 2016, rising from 21.4 °C for the first climatological normal (1917–1946) to 22.3 °C for the last one (1987–2016). Furthermore, in the summer months, the temperature rose from 24.5 to 25.3 °C, and in the winter months, such increase was from 17.1 (1917–1946) to 18.3 °C (1987–2016). Our findings showed the subtropical conditions (Cfa in Köppen's classification) in the study area persisted from the beginning of the analysis (1917–1946) until the climatological normal of 1979–2008, with a clear tendency of tropicalization after that with a change in the climate type of Piracicaba from subtropical to tropical, which can now be classified as tropical with dry winter (Aw climate type). The local average air temperature showed concordances with the long-term air temperature anomalies from regional, continental, and global scales, indicating that all of them may be linked with increasing GHG emissions, since well-defined long-term linear relationships (r2 = 0.99) were observed between continental and global average air temperature anomalies and atmospheric CO2 concentration observed at the NOAA Lab in Mauna Loa in the last 59 years. While the local and regional forcing effects remain to be fully unraveled, our study provided a valid and strong scientific sound evidence that climate change occurred in Piracicaba, southeastern Brazil, in the last 100 years. [ABSTRACT FROM AUTHOR]

Air temperature is the main climatic variable for climate change and global warming assessment. In different regions, different climatic features and forcing factors affect air temperature behaviour and development differently. In this paper, time series of monthly and annual absolute minimum, mean and absolute maximum air temperatures measured in the period Jan. 1949–Dec. 2018 at two meteorological stations, Zagreb Grič and Lastovo, were analysed. The stations are situated in distinct climatological areas in geographically and climatologically completely opposite parts of Croatia. The climate of Zagreb Grič station is mild continental. Station Lastovo is located on the small isolated Adriatic Sea island, which has a hot Mediterranean climate. The distance by air between the two analysed meteorological stations is 340 km. In time series of the absolute annual minimum air temperatures measured at both analysed stations, an increasing trend is not statistically significant, while in the time series of mean annual and absolute annual maximum air temperatures, the trends are statistically significant at the level p<0.01. The statistically significant trend of air temperature increase at both stations appeared in the warm season of the year generally from May to August. The day-to-day (DTD) method established a decrease in night-time to night-time air temperature variability, and an increase in the day-time to day-time temperature variability at Lastovo. In Zagreb Grič, the situation is the opposite but the process is very slow. [ABSTRACT FROM AUTHOR]

Adaption for temperature should be suitable to local conditions for regional differences in temperature change features. This paper proposed to utilize nine temperature modes that joint the trend (increasing/decreasing/unchanged) with variability (intensifying/weakening/unchanged) to investigate features of temperature change in mainland China. Monthly temperature data over the period 1960-2013 were obtained from 522 national basic and reference meteorological stations. Here, temperature trend (TT) was reflected by the trend of mean annual temperature (MAT) and the uptrend (downtrend) of inter-monthly sliding standard deviation (SSD) series with a sliding length of 29 years (348 months) was used for representing the intensification (weakening) of temperature variability (TV). The Mann-Kendall method and the least squares method were applied to assess the significance and quantify the magnitude of trend in MAT and SSD time series, respectively. The results show that there is a consistent warming trend throughout the country except for only three stations in which a cooling trend is identified. Moreover, the overall increasing rate in the north of 35° N is the highest, over 0.4 °C/decade for most stations. TV is weakened for almost 98% of the stations, indicating the low instability of temperature at a national scale. Finally, temperature mode (TM), for more than 90% of the stations, is the combination of an increasing TT with a weakened TV (mode 8). So, it is more important for people to adapt to the increasing temperature in these regions. Compared to using annual temperature data to calculate SSD, monthly data can accurately reflect the inter-monthly change of temperature and reserve more initial characteristics of temperature. [ABSTRACT FROM AUTHOR]

Characterizing the response of temperature variables to agricultural irrigation is expected to be an important challenge for understanding the full impact of water management on regional climate change. In this paper, the trend analysis and abrupt change test were applied to detect the global warming effect. Then, the quantitative irrigation-induced cooling effects on temperature variables between April and August from 1970 to 2010 in the Lhasa River basin were estimated using historical time series of gridded meteorological records and a map of the area equipped for irrigation. Trends in the maximum temperature (Tmax) were statistically positive, and a significant increasing trend for the minimum temperature (Tmin) was detected at the 0.01 and 0.05 confidence levels. No abrupt changing point of warming was detected in the time series for Tmax. The abrupt changes in Tmin in the irrigation concentration period took place in 1995, 5 years later than the corresponding change in April. Affected by global warming, the increase in temperature was the largest in July and August, when the irrigation-induced cooling effect was also the most significant. The irrigation-induced cooling effect for Tmax and Tmin in April–August (except for June) ranged from − 0.017 to − 0.009 °C/decade and from − 0.011 to − 0.001 °C/decade, respectively, and the cooling effect for diurnal temperature range (DTR) ranged from − 0.011 to 0 °C/decade. The cooling effect on temperature reached above 0.01 °C in July and August, but for the growing seasons, the effect was weak, only 0.001 °C. The Tmax and Tmin trends during the whole growing seasons decreased by both 0.002 °C/decade, respectively, with a 10% increase in irrigation land proportion. Even in July and August, the trends were expected to decrease by about 0.005 °C/decade with a 10% increase in irrigation land proportion. The irrigation-induced cooling effect could partially slow global warming. [ABSTRACT FROM AUTHOR]

In mountain regions, important differences in the time trends of climate series can be detected even within relatively small areas, leading to uncertainty when assessing climate change. The paper deals with a structured algorithm for high-resolution downscaling of climate characterisation in a region (precipitation and temperature), leading to a twofold application: increasing spatial resolution of past climate definition for the area and attaining high-resolution downscaling for climate projections. In the first stage, multi-variate analysis ('partial least squares' regression) was applied to a number of time series (10) in order to obtain climate averages for a larger number of sites. Predictions made with single-site values (such as seasonal means) can in some cases be improved by applying 'random perturbation' of the value and averaging single predictions in the ensemble. This analysis laid the foundation for implementing the same technique to the output of statistical downscaling of multi-model climate projections. Climate shift in the study area (Trentino), located in the north-eastern Italian Alps, was simulated for two 30-year time windows: 2021-2050 and 2071-2099. Progressive warming is predicted, being stronger in the summer, along with a mixed, seasonally differentiated trend for precipitation. [ABSTRACT FROM AUTHOR]

Climate change and global warming surge the frequency and severity of extreme weather events like heatwaves, cyclones, floods, etc. This study assesses future heatwave events in four Indian cities, i.e., Srinagar, Jaipur, Guwahati, and Visakhapatnam. It uses CMIP 6 projections with four SSP scenarios, i.e., SSP 126, 245, 370, and 585. The yearly value of the heatwave magnitude index is used to classify the events in cities. The forthcoming forecast is distributed into three identical periods of 27 years each, i.e., near- (2020–2046), mid- (2047–2073), and long-term periods (2074–2100). The outcomes from the study showed that heatwave events would increase across the cities for all periods under SSP 370 and 585 scenarios. It is computed that 104 extreme events are probable to be observed across these four cities. This study highlights the importance of adaptive techniques in dealing with the negative implications of predicted heatwave weather events. [ABSTRACT FROM AUTHOR]

A warming climate cause changes in regional climate and climate extremes. However, understanding how future warming can affect the arid climate and drought in Asia is still unclear. Global warming (GW) impacts on shifts in arid regions and change patterns of drought in the Asia region are investigated using the shared socioeconomic pathway 5–8.5 of the Coupled Model Intercomparison Project Phase 6. The variations in the arid region are explored under potential GW targets above preindustrial levels (+ 0.66 °C for the reference period and + 1.5 °C, + 2.5 °C, + 3.0 °C for future periods). We examine changes in precipitation and temperature indices related to drought, the drought patterns corresponding to consistent arid zones and arid-wet shifting zones based on GW scenarios. The results indicate that warming climates influence temperature and precipitation, and consequently alter climate distribution toward an expansion of the arid region. Due to shifts in climate zones, arid regions may expand by 2.6% relative to the reference climate in response to 3.0 °C of warming. Changes in precipitation indices contribute to the spatial patterns and magnitude of drought changes. Future drought features induced by meteorological conditions exhibit different behaviors according to arid-wet shifts and drought events. Especially, drought features throughout Asia are likely to be aggravated in terms of both severity and frequency in response to a greater degree of GW, especially in arid regions and regarding extreme droughts. This study provides valuable information on the relationship between regional climate and drought features in a world affected by GW. [ABSTRACT FROM AUTHOR]

The agricultural sector in Poland is of considerable social and economic importance for the nation. Climate variability and change are of primary relevance to this largely climate-dependent sector. Changes in seven temperature-related agroclimatic indices (lengths of the growing season and of the frost-free season, days of occurrence of the last spring frost and of the first autumn frost; and annual sums of growing degree-days for three values of temperature threshold) in Poland in 1951-2010 are examined. As expected, they generally correspond to the overwhelming and ubiquitous warming. Many, but not all, detected trends are statistically significant. However, for some indices, strong natural variability overshadows eventual trends. Projections of temperature-related agroclimatic indices for the future, based on regional climate models, are also discussed. [ABSTRACT FROM AUTHOR]

In many parts of the world, teleconnection patterns are one of the climate phenomena that significantly change the causative climate anomalies, especially temperature and precipitation. Thus, statistical analysis and modeling of their effects are of great importance in order to understand the fluctuations and climate variability in a region. In this study, 52 teleconnection indices were utilized to perform statistical analysis and conceptual modeling as well as simulation of temperature and precipitation fluctuations in Iran. For this purpose, temperature and precipitation data of 36 synoptic stations in Iran and 52 teleconnection indices for the period 1951–2019 were used. For the analysis, the relevant data were classified into four groups of global (GLB), regional (RGN), El Niño–Southern Oscillation (ENSO), and all indices (ALL). Then, the correlation of the aforementioned indices with temperature and precipitation was calculated using the teleconnectional–statistical model (TSM). Afterward, 5 years with the highest correlation coefficient was selected and considered as the forecasting parameters. The results revealed that the local temperature forecasting using RGN indices and the precipitation forecasting using GLB and ALL indices were more accurate than those using other indices. Our findings highlighted the prominent role of the indices with broader geographical regions that mainly were evolved across the oceans. Moreover, the effect of ENSO teleconnection on Iran climate was explained by the dynamic mechanism of the atmospheric bridge. Comparing TSM outputs and the Climate Forecast System Version 2 (CFSV2), TSM outperformed CFSV2 in the conducting experiment. Overall, the findings of this study emphasized on the existence of coincided synergy in the fluctuation or trend within almost all indices and atmospheric parameters, and most of the fluctuations in the indices occurred simultaneously or right after the ENSO events, including specific super El Niño in 1997–1998 (turning point). Also, the dramatic effect of sunspots on the average temperature of Iran is shown in inverse harmony, which is not easily revealed by correlation analysis. Also, the influence of global warming and especially synchronization with El Niño event on climatic change was briefly discussed in the Middle East. In this work, for the first time in the Middle East, physical mechanisms of how linkages affect Iran's climate and rainfall were proposed in a synoptic conceptual model. [ABSTRACT FROM AUTHOR]

ICEEMDAN, a variant of Empirical Mode Decomposition (EMD), is used to extract temperature cycles with periods from half a year to multiple decades from the HadCRUT5 global temperature anomaly data. The residual indicates an overall warming trend. The analysis is repeated for the Southern and Northern Hemispheres as well as the Tropics, defined as areas lying at or below 30 degrees of latitude. Multiannual cycles explain the apparently anomalous pause in global warming starting around 2000. The previously identified multidecadal cycle is found to be the most energetic and to account for recent global warming acceleration, beginning around 1993. This cycle's amplitude is found to be more variable than by previous work. Moreover, this variability varies by latitude. Sea ice loss acceleration is proposed as an explanation for global warming acceleration. [ABSTRACT FROM AUTHOR]

Climate change and its impacts at global warming of 1.5 °C and 2 °C are major concerns of the international community. Based on the multi-model dynamical downscaling outputs, by using the quantile–quantile (Q-Q) adjustment method to correct the biases for the future periods, projections are made for the variation trend of the extreme precipitation events over the middle and upper Yangtze River in the context of global warming of 1.5 °C and 2 °C. The results show that the Q-Q adjustment method significantly reduces the bias of simulated extreme precipitation. In the dynamical downscaling simulation over the middle and upper Yangtze River, the bias of the number of rainy days for daily precipitation exceeding 25 mm (R25) is reduced from 6 to 1d after correction, and the 95th percentile of precipitation (pq95) is reduced from 40 to 10% over the whole region. At 1.5 °C and 2 °C warming thresholds, precipitation will be more extreme, with increasing frequency and much greater intensity. Under the RCP4.5 scenario, the precipitation intensity (SDII), extreme precipitation contribution rate (pfl95), R25, and pq95 increase more at 2 °C than at 1.5 °C warming level, but the maximum consecutive 1-day and 5-day precipitation (R1d, R5d) increase slightly less. Under the RCP8.5 scenario, SDII, pq95, R1d, and R5d increase more at 2 °C than at 1.5 °C warming target, but pfl95 and R25 increase slightly less. From the perspective of spatial distribution, the future changes of each extreme precipitation indices show significant regional differences. All show a significant increasing trend in the upper Jialing River, the Wu River Basin, and the southern Sichuan Basin, but decreases trend in pq95, pfl95, R1d, and, R5d over the Northern Sichuan Basin. [ABSTRACT FROM AUTHOR]

Groundwater accounts for 30% of the world drinking water resources and is rarely taken into account in climate assessments. Climate change affects groundwater levels and regimes, but there is very little specific research on the future impacts of climate change on groundwater. This study examines data from 15 groundwater wells of various ages for the period from 1965 to 2015. To obtain reliable data, an analysis was made of the groundwater level changes in the upper hydrodynamic zone, which is not disturbed by anthropogenic activity. A statistically significant increase in the average annual groundwater levels in the study area was observed, in agreement with data indicating an increase in groundwater runoff in the winter season for large and medium rivers in the region. To explain the revealed changes in the groundwater levels, an analysis of the characteristic climatic changes (air temperature and amount of precipitation) and the groundwater runoff was performed. In winter, the unfrozen moisture content in the soil has increased; accordingly, groundwater recharge and groundwater levels have increased. Meanwhile, in summer, an increase in evaporation from the drainage basin has occurred as a result of the increasing air temperature. To some extent, this compensates for the changes in the annual runoff and groundwater levels that are hydraulically connected to the rivers. [ABSTRACT FROM AUTHOR]

In this study, we investigated the consequences of climate change on bioclimatic indices in vineyards along the edge of Lake Neuchatel in Switzerland. Like in other vineyards all around the world, the typicity of wines and the phenology of vines have changed, particularly since the 1970s. Trends in the growing season average temperature and in Huglin's heliothermal index show that the climate in the Neuchatel vineyards changed from very cool or cool to temperate during the last decades. Trends in the cool night index and in the prior to harvest cool night index both indicate that in the near future this wine region will frequently experience temperate instead of cool nights during the weeks leading up to harvest. Our results highlight the need for adaptation strategies, such as an upward elevational shift for Pinot Noir, as climatic conditions will become too warm at its current location in the next decades. They also show that conditions in this region are already favorable for more thermophilic varieties such as Merlot. In the context of global warming, this kind of analysis should be conducted throughout winegrowing regions in order to develop efficient adaptation strategies at the microclimatic scale. [ABSTRACT FROM AUTHOR]

The rise in the frequency and magnitude of extreme temperature phenomena across the globe has led to the recurrent incidence of global climate hazards, which have had severe effects on socioeconomic development. The daily maximum and minimum temperature datasets of 27 sites in Bangladesh were used to detect spatiotemporal trends of temperature extremes over Bangladesh during 1980–2017 based on ten temperature extreme indices using multi-statistical modeling namely linear regression, Pearson correlation coefficient, and factor analyses. Besides, mutation analyses based on the Mann-Kendall test, Sen's slope estimator, and Pettit test were employed to show the changing trend in extreme temperature. Results show that except for warmest days, the warm indices showed an increasing trend, mainly since the 2000s, while the growth rate was faster, and the response to global climate warming was sensitive. The cold indices were demonstrated a reverse trend since the 2010s. Diurnal temperature range (DTR) and summer days (SU) increased faster, implying that the rising speed of daily max temperature was higher than of daily min-temperature in Bangladesh. The de-trended fluctuation analysis (DFA) revealed a continuous increase in temperature extreme in the future except for cold days. The probability distribution functions (PDF) analysis revealed an evident variation of the curves in recent decades compared to the past three decades. Besides the warm night, DTR and SU primarily control the general warming trend of temperature extremes over Bangladesh during the study period. The mutation of the warm indices occurred before the cold index, indicating that the warm indices were more sensitive to global climate warming. The temperature extremes recognized in our research suggest that elevated warm temperature extremes due to global climate warming may have huge implications on the sustainable development of Bangladesh in the forthcoming period. [ABSTRACT FROM AUTHOR]

A two-zone model of the atmospheric circulation over a hemisphere is considered. The latitude φ of the boundary between the zone of the Rossby circulation regime at mid and high latitudes and the zone of the Hadley circulation regime at low latitudes serves as a model variable. The principle of maximum of the (information) entropy of the eddy regime within the Rossby regime zone is used to determine a statistical (climatic) equilibrium value of φ. Based on the proposed model, the question of atmospheric blocking action over the hemisphere is addressed. An attempt has been made to represent a blocking phenomenon as a necessary attribute of the atmospheric circulation in statistical equilibrium. The model suggests that long-term climate change related either to the (significant) global warming or to the (significant) global cooling, both respective to the current climate state, and quantified in terms of changes in latitude φ, leads to an increase in the probability of blocking action. [ABSTRACT FROM AUTHOR]

Using time series data for the period 1959–2015, our empirical analysis examines the simultaneous effects of the individual components of the global carbon budget on temperature. Specifically, we explore the possible effects of carbon emissions caused by fossil fuel combustion, cement production, land-use change emissions, and carbon sinks (here in terms of land sink and ocean sink) on climate change. The simultaneous inclusion of carbon emissions and carbon sinks allows us to look at the coexistent and opposing effects of the individual components of the carbon budget and thus provides a holistic perspective from which to explore the relationship between the global carbon budget and global warming. The results reveal a significant positive effect of carbon emissions on temperature for both fossil fuels emissions and emissions from land-use change, confirming previous results concerning carbon dioxide and temperature. Further, while ocean sink does not seem to have a significant effect, we identify a temperature-decreasing effect for land sink. [ABSTRACT FROM AUTHOR]

Global warming has accelerated surface water loss around the world. This study investigates in detail the change and attribution of potential evapotranspiration (PET) across China from 1901 to 2100 by the Hargreaves model, based on a 1-km temperature dataset downscaled from the low-spatial-resolution datasets using a Delta downscaling framework. Results showed that (1) relative to 1961–1990, PET increased by 0.62% in the historic period (1901–2017) and 6.43–12.89% for the future period (2018–2100), suggesting considerable future drying for China. Moreover, these increments had strong spatial variations and the largest increases were detected in high-elevation regions; (2) PET over entire China demonstrated a nonsignificant upward trend during the historic period and significant upward trends for the future period. For each period and GCM, significant upward PET trends occupied a much larger percent area than significant downward trends; (3) PET variations during the historic period were most sensitive to mean temperature (TMP), while in the future period it was more sensitive to maximum temperature (TMX), suggesting a change in the primary sensitivity factor due to global warming; (4) minimum temperature (TMN) made the largest contribution (45%) to PET variations during the historic period, while TMX had the largest contribution (36–40%) in the future period. Therefore, the primary contributing factor might transform from TMN to TMX under climate change; and (5) PET variations exhibited strong spatial heterogeneity, detected on fine geographic scales, due to the use of downscaled dataset. Overall, the results present a deep insight for planning coping strategies of global warming in China. [ABSTRACT FROM AUTHOR]

Against the background of global warming, extreme agrometeorological events have become more intense and frequent during the growing season of maize (Zea mays L.). In this study, we focused on the five types of extreme agrometeorological events that greatly affect maize production in Northeast China, including chilling injury, drought, rainstorm, frost, and gale. We averaged the actual timing of phenological events from the study agrometeorological stations and divided the maize growing season into four growth stages: emergence—jointing, jointing—flowering, flowering—kernel milk, and kernel milk—physiological maturity. Based on the historical weather data from 1960 to 2017 in the study region, we derived the values of pertinent indices for the five types of study extreme agrometeorological events during the four selected maize growth stages. The results showed that chilling injury and drought were relatively more frequent during the four growth stages of maize from 1960 to 2017 in the Northeast China. As time goes on during the growing season of maize, the spatial coverage of chilling injury, frost, and gale all showed a decreasing trend. By contrast, the spatial coverage of drought showed an increasing trend during the study growth stages of maize. During growth stages of maize, chilling injury was the main extreme agrometeorological event before the 2000s, while drought became the main extreme agrometeorological event after the 2000s. Identifying the main extreme climate events that could cause yield loss is imperative, and it is important for farmers to acknowledge ongoing changes in these extreme climate events in order to take preventive measures if necessary. [ABSTRACT FROM AUTHOR]

Drought is a natural hazard that has affected agriculture which is the main livelihood of the people in the Sahel region of Nigeria (SRN) in the last few decades. Continental and regional drought monitoring is very essential for the development of an early warning system especially in the context of global warming. The severity of drought was simulated to evaluate climate change impacts on drought conditions in the SRN using the standardized precipitation evapotranspiration index (SPEI), the standardized precipitation index (SPI), the original and self-calibrated Palmer drought severity indices (PDSI and scPDSI). The difference between the Hargreaves (Har) and Penman-Monteith (PM) potential evapotranspiration (PET) models used for the computation of the SPEI were also studied. The Mann-Kendall test was used to analyze the trends and significance of the climatic data. The time series of four drought indices were compared at six synoptic stations within the SRN. The influences of climate change on drought conditions were examined with a hypothetical gradual precipitation changes (+ 10%) and 2 °C increase in temperature. The findings showed that there was a significant correlation between Har and PM models, and between the SPEIs estimated from the two PET models. However, a major drought episode (1982–1983) indicated by SPEI-PM was not captured under SPEI-Har. Considering climate change conditions, the severity and intensity of drought increases as the twenty-first century progresses under both the scPDSI and SPEI mainly due to more demand for moisture based on a temperature rise of 2 °C. Either a slight (10%) increase or decrease in the monthly accumulation of rainfall depth will not have a significant impact on drought, if there is a slight increase in temperature as it is being currently observed in the SRN. Thus, it is pertinent for stakeholders to critically consider establishing policies that can ameliorate this phenomenon as the twenty-first century progresses. [ABSTRACT FROM AUTHOR]

The Eastern Mediterranean resides on the border between the temperate and semi-arid and arid climate zones, and is thus influenced by both mid-latitude and sub-tropical weather systems. Precipitation and extreme weather in this region are mainly associated with either Cyprus Lows or the "wet" Red Sea Troughs. Current regional climate projections indicate that the region may become warmer and drier in future decades. Here, we analyze the influence of enhanced greenhouse gas forcing on the climatological properties of the 'wet' and 'dry' Red Sea Trough (WRST & DRST, respectively). With this aim, a regional synoptic classification and a downscaling algorithm based on past analogs are applied to eighteen rain stations over the main ground water basins in Israel. The algorithms are applied to the NCEP/NCAR reanalysis data for 1986–2005 and to eight CMIP5 model simulations for the historical (1986–2005) and end of the century (2081–2100) climate conditions according to the RCP8.5 scenario. For the historical period, the CMIP5 models are largely able to represent the characteristics of the Red Sea Trough. Based on the multi-model mean, significant changes are found for WRST and DRST for the late XXI Century. First, an increase in the meridional pressure gradient is found for both the WRST and the DRST, implying stronger horizontal winds. Furthermore, a significant decrease in the occurrence of the WRST (− 20%) and a significant increase in the frequency of the DRST (+ 19%) are identified. Accordingly, the persistence of the WRST decreases (− 9%), while for DRST increases (+ 9%). The decline in the frequency of WRST occurs primarily in the transition seasons, while the increase for DRST is found throughout the wet season. In total, the daily rainfall associated with the WRST system is projected to significantly decline (− 37%) by the end of the XXI century. These results document the projected changes in a dominant synoptic system in this area, which can facilitate a better estimation of the arising challenges, e.g., related to shortage of water resources and associated political unrest, reduced agricultural potential, and increased air pollution and forest fires. Such a pathway can ultimately foster novel mitigation strategies for water resources management and regional climate change adaptation. [ABSTRACT FROM AUTHOR]

The study area, with arid to semi-humid climates, is located in northern Fars Province, southern Iran. Daily precipitation and temperature data from 22 models of the Coupled Model Inter-comparison Project Phase 5 (CMIP5) are used to study climate change for period 2026–2085 under RCP2.6, RCP4.5, and RCP8.5. Daily outputs of each CMIP5 model are downscaled to climatic stations over the study area using LARS-WG tool and transient change factors approach. Daily precipitation is downscaled to seven climatic stations while daily temperature downscaled to two stations. Downscaling results indicate that temperature will increase by + 1.85, + 2.5, and + 3.45 °C under the RCP2.6, RCP4.5, and RCP8.5, respectively, while precipitation will reduce by 14, 22, and 20.8%, respectively, within the study area. Standardized precipitation index (SPI) analysis, performed for 3-, 6-, 9-, and 12-month time scales, shows that frequency (duration) of normal periods will increase (decrease) under climate change, however, 12-month SPI analysis shows decreased frequency and increased duration for normal periods. Frequency, duration, severity, and intensity of wet periods may increase, decrease, or not change under climate change, depending on the SPI time scale. The study area will experience more frequent, longer-duration, severed, intensified droughts in the future due to global warming. Extreme storm analysis shows that precipitation depth of most frequent storms (2-year return period storms) will increase, but precipitation depth of less frequent storms (10- and 20-year return period storms) will decrease under climate change. Temperature enhancement, precipitation reduction, and longer-duration, severed, intensified droughts will increase water shortage in the future, resulting in water crisis and reduced security of food production over northern Fars Province. [ABSTRACT FROM AUTHOR]

It is well recognized that the global climate has been warming and it can have adverse regional impacts in the future. Besides producing changes in mean climate, global warming can also substantially alters the weather and climate extremes. Considering the impact of weather extremes on agriculture as well as water resource management in an agrarian country like India, present study aims to characterize future changes in precipitation extremes in northeast monsoon season (October–November–December) over south peninsular India based on statistically downscaled high-resolution NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) datasets. This NEX-GDDP dataset simulates the mean rainfall reasonably well. There may be an increase in precipitation in near (5% under RCP 4.5 and 11% under RCP 8.5) and far future (21% and 38% under RCP4.5 and RCP 8.5 respectively). Future climate projections indicate that both the intensity and frequency of precipitation extremes in most parts of the south peninsular India may increase under both the warming scenarios during northeast monsoon season. [ABSTRACT FROM AUTHOR]

The Standardized Precipitation Index (SPI) for different time scales of n = 1, 2, 3, 6, 9, 12, and 24 months and the monthly Palmer Drought Severity Index (PDSI) were calculated for the Zagreb-Grič Observatory, located in North-Western Croatia, for the period 1862–2012. The PDSI exhibits a stronger long-term negative trend than the SPI due to the influence of the global warming, which corresponds with the global scale results published in the 4th IPCC (Intergovernmental Panel on Climate Change) report. The SPI for a 9-month scale was compared with the PDSI for a monthly scale because the correlation between them is the highest in comparison with other SPI time scales. The Chapman percentile classification regarding dryness/wetness severity was used instead of the "originally" proposed classes. Thirty-year moving averages indicate that long-term variation in dryness/wetness severity is more clearly emphasised for the PDSI than for the SPI, showing the last 30-year period to be the driest on record. Autoregressive function analysis indicates that the SPI for a 1-month scale has serialy independent values, while the SPI for the 9-month scale and the monthly PDSI are close to a Markov process. A significant correlation was established between the SPI and PDSI indices and crop damages in Croatia. [ABSTRACT FROM AUTHOR]

Contrary to expectations that global warming will be accompanied by an increase in terrestrial evaporation, pan evaporation (PE) has decreased in several parts of the world during the last decades. This opposing relationship is known as the pan evaporation paradox phenomenon that can be affected by climate change. For this purpose, this study identifies spatial and temporal trends in PE and its associated climate variables (Cvars) in Iran at seasonal and annual time scales. Hence, PE and Cvars data from 68 meteorological stations distributed over Iran during the period 1987–2016 were selected. The analyses of the temporal and spatial trends in PE, Cvars, and relationships among them were examined using the statistical techniques to identify the causes of PE trends. Results indicated that stations located in the subtropical region (latitude below 32°), which is mostly located in the southern half of Iran, showed significant negative PE trends (about 20–30% of stations) in spite of an increasing trend in temperatures indicating the "pan paradox" phenomenon. However, stations with significant positive PE trends (about 40% of stations), which are mostly located in the northern half of Iran, are placed at latitudes above 32°. Trend analysis of other Cvars indicated significant increases in temperatures, sunshine duration, and wind speed in more than half of the stations on all time scales. In addition, minimum, maximum, and mean temperatures, and sunshine duration were the most dominant variables affecting PE in annual, spring, autumn, and summer, respectively, in Iran. [ABSTRACT FROM AUTHOR]

Global warming has substantial impacts on the hydrologic cycle and precipitation characteristics. This study aimed to explore variability in the form of precipitation by analysis of trends in the snowfall-day (SD)/total precipitation-day (PD) ratio across Iran. To this end, the PD and SD records were acquired from 33 synoptic stations during 1965–2014. The Mann-Kendall (MK) test was the main method used for trend detection. Analyzing data exposed that the annual SD/PD ratio was less than 25% in a plethora of the stations. The MK test findings indicated downward tendencies in the SD/PD ratio over most regions of the country; although in many cases, the observed trends were not statistically significant. The changes in the annual SD/PD ratio were estimated down to − 2% per decade over ~ 70% of Iran's total area. Further studies are required to ascertain the linkages between the large-scale climate oscillations and the form of precipitation across this region. Also, using remotely sensed data (e.g., obtained from the MODIS) and fine-resolution gridded data (e.g., global and regional reanalysis data) in future research could improve the findings of such studies and dwindle the uncertainties caused by the scanty site-based observations. [ABSTRACT FROM AUTHOR]

Based on daily mean temperature data from 32 meteorological stations in the Qinling Mountains (QMs) of China, we analyzed the characteristics and differences of the spatiotemporal changes in the climatic growing season (CGS) in the QMs from 1964 to 2015. Our results are as follows. First, over the past 52 years, the temperature of the QMs significantly increased at a mean rate of 0.22 °C/decade (P < 0.01) in over 98.04% of the area. Significant north–south spatial differences were observed in temperature changes; also, significant differences in the temperature changing trends were observed before and after the abrupt change in temperature. Second, the spatial distributions of the mean growing season start (GSS), end (GSE), and length (GSL) in the QMs varied based on regional differences in latitude and topography. Notably, the GSS, GSE, and GSL were gradually delayed, advanced, and shortened, respectively, as latitude and elevation increased. After the abrupt change in temperature, whether it is in the NSQM (northern slopes of the QMs) or the SSQM (southern slopes of the QMs), the GSS, GSE, and GSL expanded into high-elevation areas. Third, over the past 52 years, the GSS in the QMs exhibited a significant advancing trend of 2.7 days/decade, the GSE was delayed at a rate of 0.66 days/decade, and the GSL displayed a significant extension of 3.36 days/decade. Before the abrupt change in temperature, the GSS, GSE, and GSL exhibited non-significant changing trends; however, the trends in the GSS, GSE, and GSL were more significant after the abrupt change than before. Fourth, the GSS, GSE, and GSL trends in the QMs were significantly different in the NSQM and SSQM regions. After the abrupt change, the GSS, GSE, and GSL trends along the NSQM were more significant than those along the SSQM. [ABSTRACT FROM AUTHOR]

Land surface air temperature (SAT) change is one of the core issues in monitoring and assessing regional climate change. In this study, the characteristics of SAT change over DPR Korea for the period 1918–2015 were investigated using a high-quality historical dataset. Results show that the region-averaged annual mean SAT increased 0.21 °C/decade for the period 1918–2015 on the basis of data from four stations and 0.19 °C/decade for the period 1941–2015 as estimated based on data from nine stations. Before the 1970s, Pyongyang station in the central region experienced the largest warming trend. Linear trends of seasonal mean SAT during 1941–1970 were negative for all seasons in eastern coast and for summer and autumn in western coast and northern inland areas. Since 1971, however, the annual and seasonal mean SAT trends have shifted to positive values in all regions, with winter experiencing the most rapid warming. During the period of global warming slowdown since 1998 or 2000, no significant seasonal warming trend of wintertime was detectable, and this caused the smallest winter warming for the last 45 years. Other seasons also witnessed a generally weakened warming during 1971–2015 compared to that of 1971–2000. The results of the study will help in understanding regional climate change and in assessing the impacts of climate change on economic and natural ecosystems in the country. [ABSTRACT FROM AUTHOR]

Reliable drought projections are crucial for the effective managements of future drought risk. Most of the existing drought projections over Southern Africa are based on precipitation alone, neglecting the influence of potential evapotranspiration (PET). The present study shows that inclusion of PET may alter the magnitude and robustness of the drought projections. The study used two drought indices to project potential impacts of global warming on Southern African droughts, focusing on four major river basins. One of the drought indices (SPEI: Standardized Precipitation Evapotranspiration Index) is obtained from climate water balance (i.e. precipitation minus potential evapotranspiration) while the other (SPI: Standardized Precipitation Index) is calculated from precipitation alone. For the projections, we analyzed multi-model regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) at four specific global warming levels (GWLs) (i.e., 1.5 °C, 2.0 °C, 2.5 °C, and 3.0 °C) above the pre-industrial level and used the self-organizing maps to classify the drought projections into groups based on their similarities. Our results show that the CORDEX simulations give a realistic representation of all the necessary climate variables for quantifying droughts over Southern Africa. The simulations project a robust increase in SPEI drought intensity and frequency over Southern Africa and indicate that the magnitude of the projection increases with increasing GWLs, especially over the various river basins. In contrast, they project a non-significant change in SPI droughts at all the GWLs. The majority of the simulations clearly distinguish between the projected SPEI and SPI drought patterns, and the distinction becomes clearer with increasing GWLs. Hence, using precipitation alone for drought projection over Southern Africa may underestimate the magnitude and robustness of the projections. This study has application in mitigating climate change impacts on drought risk over Southern African river basins in the future. [ABSTRACT FROM AUTHOR]

We here investigated the recent (1976–2014) evolution of the Ararat mountain glaciers, paradigmatic of the evolution of ice bodies in Western Asia and the Caucasus. We gathered ice cover maps, including debris cover from different sources, to depict glaciers' extension, and its variation under recent climate patterns. We then gathered data of (daily/monthly) weather variables (temperature, precipitation, snow cover depth) from two local stations managed by Turkish State Meteorological Service, which we subsequently analyzed to assess the presence of significant trends. We used the recently developed, weather-driven glaciological model Poly-Ice, able to mimic distributed ice and snow melt, mass budget, and gravity-driven ice flow of glaciers, to reproduce recent evolution of the Ararat ice bodies. We found a measurable decrease of the area (− 2.38 km2, − 30% of the initial area, − 0.06 km2 year−1) of the Ararat glaciers, including loss of ice under debris covered tongue (− 1.99 km2, − 70% of the initial area), driven by significantly increasing temperature especially in spring (+ 0.05 °C year−1). Using our Poly-Ice model, we could (i) mechanistically reproduce the response of the glaciers to the changing climate patterns, (ii) confirm faster downwasting ever since the 1990s under increasing temperature, and (iii) highlight decreased winter snow cover at thaw at the highest altitudes ever since the 1990s, further driving ice melt. Such physically based tool will further allow to project forward the dynamics of these glaciers under future climate. Our results are fully consistent with the present know how of glaciers' retreat from Europe to Caucasus, and Central and Southern Asia, and contribute to the ongoing discussion about retreating glaciers worldwide. [ABSTRACT FROM AUTHOR]

As the recent global warming hiatus and the warming on high elevations are attracting worldwide attention, this study examined the robustness of the warming slowdown over the Tibetan plateau (TP) and its related driving forces. By integrating multiple-source data from 1982 to 2015 and using trend analysis, we found that the mean temperature (Tmean), maximum temperature (Tmax) and minimum temperature (Tmin) showed a slowdown of the warming trend around 1998, during the period of the global warming hiatus. This was found over both the growing season (GS) and non-growing season (NGS) and suggested a robust warming hiatus over the TP. Due to the differences in trends of Tmax and Tmin, the trend of diurnal temperature range (DTR) also shifted after 1998, especially during the GS temperature. The warming rate was spatially heterogeneous. The northern TP (NTP) experienced more warming than the southern TP (STP) in all seasons from 1982 to 1998, while the pattern was reversed in the period from 1998 to 2015. Water vapour was found to be the main driving force for the trend in Tmean and Tmin by influencing downward long wave radiation. Sunshine duration was the main driving force behind the trend in Tmax and DTR through a change in downward shortwave radiation that altered the energy source of daytime temperature. Water vapour was the major driving force for temperature change over the NTP, while over the STP, sunshine duration dominated the temperature trend. [ABSTRACT FROM AUTHOR]

A two-step statistical downscaling method has been reviewed and adapted to simulate twenty-first-century climate projections for the Gulf of Fonseca (Central America, Pacific Coast) using Coupled Model Intercomparison Project (CMIP5) climate models. The downscaling methodology is adjusted after looking for good predictor fields for this area (where the geostrophic approximation fails and the real wind fields are the most applicable). The method’s performance for daily precipitation and maximum and minimum temperature is analysed and revealed suitable results for all variables. For instance, the method is able to simulate the characteristic cycle of the wet season for this area, which includes a mid-summer drought between two peaks. Future projections show a gradual temperature increase throughout the twenty-first century and a change in the features of the wet season (the first peak and mid-summer rainfall being reduced relative to the second peak, earlier onset of the wet season and a broader second peak). [ABSTRACT FROM AUTHOR]

In this study, the trends and periodicity in climate extremes are examined in Hunan Province over the period 1960-2013 on the basis of 27 extreme climate indices calculated from daily temperature and precipitation records at 89 meteorological stations. The results show that in the whole province, temperature extremes exhibit a warming trend with more than 50% stations being statistically significant for 7 out of 16 temperature indices, and the nighttime temperature increases faster than the daytime temperature at the annual scale. The changes in most extreme temperature indices show strongly coherent spatial patterns. Moreover, the change rates of almost all temperature indices in north Hunan are greater than those of other regions. However, the statistically significant changes in indices of extreme precipitation are observed at fewer stations than in extreme temperature indices, forming less spatially coherent patterns. Positive trends in indices of extreme precipitation show that the amount and intensity of extreme precipitation events are generally increasing in both annual and seasonal scales, whereas the significant downward trend in consecutive wet days indicates that the precipitation becomes more even over the study period. Analysis of changes in probability distributions of extreme indices for 1960- 1986 and 1987-2013 also demonstrates a remarkable shift toward warmer condition and increasing tendency in the amount and intensity of extreme precipitation during the past decades. The variations in extreme climate indices exhibit inconstant frequencies in the wavelet power spectrum. Among the 16 temperature indices, 2 of them show significant 1-year periodic oscillation and 7 of them exhibit significant 4- year cycle during some certain periods. However, significant periodic oscillations can be found in all of the precipitation indices.Wet-day precipitation and three absolute precipitation indices show significant 1-year cycle and other seven provide significant power at the 4-year period, which are mainly found during 1970-1980 and after 1992. [ABSTRACT FROM AUTHOR]

As a preliminary and major step for land use planning of the coming years, the study of variability of the past decades' climatic conditions with comprehensive indicators is of high importance. Given the fact that one of the affected areas by climatic change includes variability of thermal comfort, this study uses the physiologically equivalent temperature (PET) to identify and evaluate bioclimatic conditions of 40 meteorological stations in Iran. In this study, PET changes for the period of 1960 to 2010 are analyzed, with the use of Mann-Kendall non-parametric test and Pearson parametric method. The study focuses particularly on the diversity in spatio-temporal distribution of Iran's bioclimatic conditions. The findings show that the mean frequency percentage of days with comfort is 12.9 % according to the total number of selected stations. The maximum and minimum frequency percentage with values of 17.4 and 10.3 belong to Kerman and Chabahar stations, respectively. The findings of long-term trend analysis for the period of 1960-2010 show that 55 % of the stations have significant increasing trend in terms of thermal comfort class based on the Pearson method, while it is 40 % based on Mann-Kendall test. The results indicate that the highest frequency of days with thermal comfort in the southern coasts of Iran relates to the end of autumn and winter, nevertheless, such ideal conditions for the coastal cities of Caspian Sea and even central stations of Iran relate to mid-spring and mid-autumn. Late summer and early autumn along with late spring can be identified as the most ideal times in the west and northwest part of Iran. In addition, the most important inhibiting factors of thermal comfort prove to be different across the regions of Iran. For instance, in the southern coasts, warm to very hot bioclimatic events and in the west and northwest regions, cold to very cold conditions turn out to be the most important inhibiting factors. When considering the variations across the studied period, an increase in the frequency of thermal comfort condition is observed in almost half of the stations. Moreover, based on Pearson and Mann-Kendall methods, the trend of changes in monthly averages of PET has decreased in most stations and months, which can lead to different consequences in each month and station. Thus, it is expected that due to PET changes in recent decades and to the intensified global warming conditions, Iran's bioclimatic conditions change in a way that transfers the days with comfort to early spring and late autumn. [ABSTRACT FROM AUTHOR]

Based on daily maximum and minimum temperature data from 437 weather stations over China, this study examined the spatiotemporal change of temperature extremes in China from 1960 to 2011. Results showed a general downward trends in the occurrence of cold days (TX10) and nights (TN10) (base period 1961-1990), but upward tendency on the occurrence of warm days (TX90) and nights (TN90), the temperatures of coldest day (TXn), coldest night (TNn), warmest day (TXx), and warmest night (TNx) in China and most climate regions. At the national scale, TX10 and TN10 have significantly decreased by −1.89 and −4.39 days/decade, and TX90 and TN90 have significantly increased by 2.49 and 4.72 days/decade from 1960 to 2011. The national average trends for TXn, TNn, TXx, and TNx were 0.28, 0.54, 0.17, and 0.27 °C/decade, respectively. The temporal changes of extremes indices showed that changes in cold (warm) relative indices may be primarily related to that of corresponding winter (summer) T and T, respectively. Regionally, the magnitudes of changes in extreme indices decreased from the north to south of China. However, we found significant increase of warm extremes, especially warm days and nights in Southeast China. For most climate regions, the trend magnitudes in warm days/nights were larger than that in cold days/nights, but the trend in coldest temperature was much higher than that in warmest temperature. The trend magnitudes in minimum temperature indices were larger than those based on daily maximum temperature, explaining the faster increase of T than T in China. [ABSTRACT FROM AUTHOR]

The observed late twentieth century warming must be assessed in relation to natural long-term variations of the climatic system. Here, we present a Northern Hemisphere (NH) temperature reconstruction for the mid-to-late Holocene of the past 6000 years, based on a synthesis of existing paleo-temperature proxies that are capable of revealing centennial-scale variability. This includes 56 published temperature records across the NH land areas, with a sampling resolution ranging from 1 to 100 years and a time span of at least 1000 years. The composite plus scale (CPS) method is adopted with spatial weighting to develop the NH temperature reconstruction. Our reconstruction reveals abrupt cold epochs that match well the Bond events during the past 6000 years. The study further reveals two prominent cycles in NH temperature: 1700-2000-year cycle during the mid-to-late Holocene and 1200-1500-year cycle during the past 3500 years. Our reconstruction indicates that the late twentieth century NH temperature and its rate of warming are both unprecedentedly high over the past 5000 years. By comparing our reconstruction with the projected temperature increase scenarios, we find that temperature by the end of the twenty-first century would likely exceed any peaks during the mid-to-late Holocene. [ABSTRACT FROM AUTHOR]

Nowadays, climate change is a fact, and its impacts on heterogeneous chemistry mechanisms that take place in various atmospheric layers are of great interest. As an example, the uptake of atmospheric species on solid and liquid surfaces induces qualitative and quantitative changes from climatic alterations of the atmospheric thermal regime. We hereby present the experience gained on this subject by analysing real measurements of various atmospheric species and parameters conducted in Athens, Greece, exploring the atmospheric height region from the Earth's surface up to the lower stratosphere. [ABSTRACT FROM AUTHOR]

This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year) occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year) in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period. [ABSTRACT FROM AUTHOR]

The objective of this study was to analyze long-term temperature-related phenomena in the eastern portion of the Middle East, focusing on the coastal region of Qatar. Extreme temperature indices were examined, which were defined by the Expert Team on Climate Change Detection and Indices, for Doha, Qatar; these indices were then compared with those from neighboring countries. The trends were calculated for a 30-year period (1983-2012), using hourly data obtained from the National Climatic Data Center. The results showed spatially consistent warming trends throughout the region. For Doha, 11 of the 12 indices studied showed significant warming trends. In particular, the warming trends were represented by an increase in the number of warm days and nights and a decrease in the number of cool nights and days. The high-temperature extremes during the night have risen at more than twice the rate of their corresponding daytime extremes. The intensity and frequency of hot days have increased, and the minimum temperature indices exhibited a higher rate of warming. The climatic changes in Doha are consistent with the region-wide heat-up in recent decades across the Middle East. However, the rapid economic expansion, increase of population since the 1990s, and urban effects in the region are thought to have intensified the rapidly warming climate pattern observed in Doha since the turn of the century. [ABSTRACT FROM AUTHOR]

Responses of the Kuroshio Extension (KE) and its southern recirculation gyre (SRG) to global warming are investigated using CMIP5 experiments with a high-resolution climate model MIROC4h. The results show that MIROC4h well reproduces the essential features of the KE system and its low-frequency variations. In three-member-ensemble future climate experiments (with a medium mitigation emissions scenario RCP4.5), the strengths of the KE and its SRG increase, relative to the prescribed historical run with natural and anthropogenic forcing. By investigating the mechanism resulting in these variations of the KE and its SRG, it turns out that wind stress changes and ocean stratification changes both contribute to the enhancement of the KE and its SRG. Specifically, the wind stress changes increase upper ocean momentum in the SRG region. Meanwhile, the increased stratifications hinder the transfer of momentum from the upper ocean to the deeper ocean. Besides, the strengthened ocean stratification could enhance the eddy kinetic energy (EKE) in the downstream KE region, which can feedback to intensify the SRG. As a result, the strength of the SRG increases under global warming condition. Then the intensification of the SRG leads to large acceleration of the KE. Eventually, both the KE and its SRG intensify. [ABSTRACT FROM AUTHOR]

The assessment of climate change impacts requires updated estimates of the tendencies in temperature extremes. With the objective of studying recent variations in frequency and intensity of temperature extremes over Italy, a collection of daily minimum and maximum temperature time series was selected for the calculation of a set of indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The trend of each index was investigated through a non-parametric statistical analysis over the last half-century (1961-2011), and its spatial variability was illustrated through trend maps. Mean national-scale trends were also assessed at annual and seasonal level. The results show that mean annual series exhibit a general warming tendency from 1961 to 2011, with significant trends for summer days, tropical nights, heat waves, and percentile-based indices at most stations, with warming trends more pronounced in summer and spring and weaker in winter and autumn. As a changepoint was identified in 1977 for the minimum ( T) and maximum temperature ( T) Italian annual series, the trend analysis was also performed for the two sub-periods 1961-1977 and 1978-2011. Non-significant 'cooling' trends characterize the sub-period 1961-1977, while significant 'warming' trends were identified over the period 1978-2011. This study updates previous research in the extent of time series, in the number of indices and in the approach followed for their analysis, providing useful information for evaluating the impacts of temperature extremes in the context of a changing climate in Italy. [ABSTRACT FROM AUTHOR]

Boreal fires can cool the climate; however, this conclusion came from individual fires and may not represent the whole story. We hypothesize that the climatic impact of boreal fires depends on local landscape heterogeneity such as burn severity, prefire vegetation type, and soil properties. To test this hypothesis, spatially explicit emission of greenhouse gases (GHGs) and aerosols and their resulting radiative forcing are required as an important and necessary component towards a full assessment. In this study, we integrated remote sensing (Landsat and MODIS) and models (carbon consumption model, emission factors model, and radiative forcing model) to calculate the carbon consumption, GHGs and aerosol emissions, and their radiative forcing of 2001-2010 fires at 30 m resolution in the Yukon River Basin of Alaska. Total carbon consumption showed significant spatial variation, with a mean of 2,615 g C m and a standard deviation of 2,589 g C m. The carbon consumption led to different amounts of GHGs and aerosol emissions, ranging from 593.26 Tg (CO) to 0.16 Tg (NO). When converted to equivalent CO based on global warming potential metric, the maximum 20 years equivalent CO was black carbon (713.77 Tg), and the lowest 20 years equivalent CO was organic carbon (−583.13 Tg). The resulting radiative forcing also showed significant spatial variation: CO, CH, and NO can cause a 20-year mean radiative forcing of 7.41 W m with a standard deviation of 2.87 W m. This emission forcing heterogeneity indicates that different boreal fires have different climatic impacts. When considering the spatial variation of other forcings, such as surface shortwave forcing, we may conclude that some boreal fires, especially boreal deciduous fires, can warm the climate. [ABSTRACT FROM AUTHOR]

Temperatures were examined at 118 stations located in the Arctic and compared to observations at 50 European stations whose records averaged 200 years and in a few cases extend to the early 1700s. Nearly all stations exhibited warming trends. For each station, the temperature relative to the average value during 1961-1990 was found. The resulting temperature change averaged over the Arctic stations was plotted. For the period 1820-2014, trends were found for the January, July and annual temperatures of 1.0, 0.0 and 0.7 °C per century, respectively. Decadal variations are evident and much of the temperature increase occurred during the 1990s. Over the past century, Siberia, Alaska and Western Canada have experienced somewhat greater warming than Eastern Canada, Greenland and Northern Europe. The temperature change experienced by the Arctic stations during the last two centuries closely tracks that found for the European stations. [ABSTRACT FROM AUTHOR]

In this work, we analyze climate variability and glacier evolution for a study area in the Northwestern Italian Alps from the Little Ice Age (LIA) to the 2010s. In this area, glacier retreat has been almost continuous since the end of the LIA, and many glaciers are now extinct. We compared glaciological and climatic data in order to evaluate the sensitivity of glaciers to temperature and precipitation trends. We found that temperatures show significant warming trends, while precipitation shows no clear signal. After the 1980s, the total number of positive trends in temperature increased, particularly minimum temperature. The latter does not seem to be the only cause of glacier shrinkage but rather on acceleration of an ongoing trend documented since the end of the LIA. In some rare cases, the effects of warming trends on glacier dynamics have been accentuated by a concomitant decrease in precipitation. We hope that this study will contribute to increase the knowledge of the relationships between climate variation and glacier evolution in the Greater Alpine Region. [ABSTRACT FROM AUTHOR]

The presented study was concentrated on the trend analysis of the annual mean temperature series of 40 meteorological stations in all climatic zones of Turkey. The sensitivity of the parametric and nonparametric tests to the selected record periods was investigated in detail. Backward-shifted and forward-shifted trend analyses were accomplished by keeping either the beginning or the ending data period constant and varying the other period ending. This analysis resulted with a trend statistic direction turning point at the year 1992. Following this result, the trend tests were applied to three different records to distinguish the effect of 1992 on the trend direction. For the period 1950-1992, the downward trend was dominating several stations whereas only upward trend was observed for 1986-2006 period. Clearly, the trend direction change in 1992 dominated the trend behavior between 1986 and 2006. The opposite trend orientations on 1950-1992 and 1986-2006 periods seem to be neutralized on 1950-2006 period with the majority of the stations showing no trend as the result. This study displays the effect of different lengths of data record on the trend analysis results. It has been clear by this study that a sudden change on trend direction is obvious at the stations above 39°N in Turkey provinces in 1992. These results are conformed to the previous studies related with climate change like temperature, sea level, meteorological observations, and dominant climatic events as North Atlantic Oscillation and El-Niño and Southern Oscillation. [ABSTRACT FROM AUTHOR]

Afforestation has been deployed as a mitigation strategy for global warming due to its substantial carbon sequestration, which is partly counterbalanced with its biogeophysical effects through modifying the fluxes of energy, water, and momentum at the land surface. To assess the potential biophysical effects of afforestation, a set of extreme experiments in an Earth system model of intermediate complexity, the McGill Paleoclimate Model-2 (MPM-2), is designed. Model results show that latitudinal afforestation not only has a local warming effect but also induces global and remote warming over regions beyond the forcing originating areas. Precipitation increases in the northern hemisphere and decreases in southern hemisphere in response to afforestation. The local surface warming over the forcing originating areas in northern hemisphere is driven by decreases in surface albedo and increases in precipitation. The remote surface warming in southern hemisphere is induced by decreases in surface albedo and precipitation. The results suggest that the potential impact of afforestation on regional and global climate depended critically on the location of the forest expansion. That is, afforestation in 0°-15°N leaves a relatively minor impact on global and regional temperature; afforestation in 45°-60°N results in a significant global warming, while afforestation in 30°-45°N results in a prominent regional warming. In addition, the afforestation leads to a decrease in annual mean meridional oceanic heat transport with a maximum decrease in forest expansion of 30°-45°N. These results can help to compare afforestation effects and find areas where afforestation mitigates climate change most effectively combined with its carbon drawdown effects. [ABSTRACT FROM AUTHOR]