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Separating existing historical precipitation data into solid and liquid precipitation remains a challenge in the study of climate change, extreme precipitation, and hydrological modelling. Based on historical daily air temperature and precipitation data, as well as visual observations of precipitation phase (weather phenomena records) in China mainland, this study proposed a snow‐day direct definition method (SDDM) to determine the threshold air temperature (TAT) of rainfall and snowfall, and analysed the spatial pattern and its influential factors. The main findings include: (1) the TAT based on the SDDM varied from −1.2 to 6.3°C, with a mean value of 2.8°C for the entire study region; (2) TAT was generally higher and more variable in the low‐latitude areas, and the Qinghai‐Tibet Plateau was characterized by an abnormally high average TAT of 5.2°C, almost twice as large as that of the eastern monsoon region; (3) TAT exhibited a significant positive correlation with altitude and negative correlation with precipitation and relative humidity. The results presented in this paper have potential application for studies of large‐scale snowfall climatology and climate change, weather forecasting techniques, and hydrological model parameterization in areas with complex and diverse geographical and climatic conditions. [ABSTRACT FROM AUTHOR]

Long‐term climate monitoring by universities provides fundamental data for various disciplines in the natural sciences. Kyoto University once managed 10 university forest stations and is currently managing five. At these stations, climate data have been monitored almost since the establishment of each station until today, with the exception of the stations in foreign countries. We compiled and report the monthly climate data at these forest stations from the start of monitoring until December 2018. These data are important for investigating environmental changes in East Asia, including China (Taiwan), South Korea (Chosen) and Russia (Sakhalin, Karafuto) over the last 100 years. Long‐term monitoring often involves minor and major changes in the monitoring procedures, devices and even monitoring sites due to unavoidable circumstances, such as technological advances, changes in standard methods and climatic and anthropogenic disasters. Therefore, associated metadata on the monitoring methods are also important. We also compiled metadata on changes in monitoring methods. In addition, to examine the effects of changes in the methods on the observed climate data, we compared the values recorded before and after the change for each climate variable at each monitoring site. Methodological changes affected only a few variables, with the exception of humidity. Careful interpretation may be required when a researcher uses humidity data in any analysis. The complete data set for this abstract published in the Data Paper section of the journal is available in electronic format in MetaCat in JaLTER at http://db.cger.nies.go.jp/JaLTER/metacat/metacat/ERDP-2020-03.1/jalter-en. [ABSTRACT FROM AUTHOR]

The rise in the Earth's global average surface temperature and the increase of extreme weather events have been the focus of scientific discussion in the last decades. Extreme heat combined with other environmental extremes, like high concentrations of air pollution, may induce health problems—especially in socioeconomically vulnerable populations. Spring in South America requires particular attention due to its association with hot, dry weather and air pollution in most parts of the continent. This paper intends to better comprehend the behaviour of heatwaves during the austral winter–spring transition. We propose identifying the spatial coverage, frequency and intensity of heatwaves in homogeneous areas of maximum air temperature near the surface (Tmax). We employed cluster analyses during the period between July and October for 41 years (1979–2019) through the ERA5 reanalysis. Homogeneous Tmax areas in South America were defined by cluster analyses that indicated three homogeneous Tmax regions, as follows: a larger area of the continent including the tropical region (Area 1), eastern and southeastern South America (Area 2) and southernmost and steep areas in the Andes (Area 3). The heatwave events identified via ERA5 reanalysis were classified according to their intensity (intense, moderate and weak events). Spatial frequency and trend analyses were also performed regarding the intensity and persistence of heatwave episodes. These methods allowed the identification of the behavioural aspect of heatwaves spanning the last four decades. The Mann–Kendall statistical test (MK) was applied in order to analyse the heatwave trend with a statistical significance level of 5%. A total of 191 heatwave episodes were identified. Of this total, 47.12, 35.60 and 17.28% of episodes occurred in Areas 2, 3 and 1, respectively. The hotter area extending from northeast to southwest in central South America stood out by its largest frequencies of intense heatwave episodes. Across the continent there was a significant increase in the intensity and persistence of heatwaves over the period of 1979 through to 2019. [ABSTRACT FROM AUTHOR]

This paper investigated the trends and variability in warmest daily maximum (TXx) and warmest daily minimum (TNx) air temperatures, and heatwave characteristics in Turkey in May during 1950–2020. It also analysed the climatological and synoptic meteorological evolutions of heatwave (HW) observed in May 2020. Trend analysis revealed significant increasing trends in TXx and TNx series and heatwave characteristics in May since 1950. Since the mid‐1980s, a continuously increasing trend in TXx and TNx series, and the number, frequency, and magnitude of the heatwaves were observed that accelerated with the mid‐1990s. The most severe heatwave in Turkey since 1950 in May was observed in 2020. The record‐breaking daily maximum (daily minimum) air temperatures were noted at 32 (23) of 96 stations in May 2020, mainly over Turkey's western and southern parts. Record‐high maximum (minimum) air temperature was 43.2°C (31.1°C) reached for the first time in May since 1950. The generalized extreme value model applied to the May TXx and TNx series revealed that the daily air temperatures in May 2020 exceeded 100 years' return periods at many stations of Turkey. This heatwave was linked to a regionalized strong anticyclonic blocking anomaly circulation and other associated atmospheric anomalies in May 2020. This also resulted in the centring of an unprecedented subsiding, calm, and stable warm air mass over Turkey. Adiabatic warming and drying developed very likely under subsidence control because of relatively weak circulation conditions. Such circumstances resulted in extremely hotter conditions in May 2020 compared to the long‐term averages. [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]

Mountain areas are biodiversity hotspots and provide a multitude of ecosystem services of irreplaceable socio‐economic value. In the European Alps, air temperature has increased at a rate of about 0.36°C decade−1 since 1970, leading to glacier retreat and significant snowpack reduction. Due to these rapid environmental changes, this mountainous region is undergoing marked changes in spring phenology and elevational distribution of animals, plants and fungi. Long‐term monitoring in the European Alps offers an excellent natural laboratory to synthetize climate‐related changes in spring phenology and elevational distribution for a large array of taxonomic groups. This review assesses the climatic changes that have occurred across the European Alps during recent decades, spring phenological changes and upslope shifts of plants, animals and fungi from evidence in published papers and previously unpublished data. Our review provides evidence that spring phenology has been shifting earlier during the past four decades and distribution ranges show an upwards trend for most of the taxonomic groups for which there are sufficient data. The first observed activity of reptiles and terrestrial insects (e.g. butterflies) in spring has shifted significantly earlier, at an average rate of −5.7 and −6.0 days decade−1, respectively. By contrast, the first observed spring activity of semi‐aquatic insects (e.g. dragonflies and damselflies) and amphibians, as well as the singing activity or laying dates of resident birds, show smaller non‐significant trends ranging from −1.0 to +1.3 days decade−1. Leaf‐out and flowering of woody and herbaceous plants showed intermediate trends with mean values of −2.4 and −2.8 days decade−1, respectively. Regarding species distribution, plants, animals and fungi (N = 2133 species) shifted the elevation of maximum abundance (optimum elevation) upslope at a similar pace (on average between +18 and +25 m decade−1) but with substantial differences among taxa. For example, the optimum elevation shifted upward by +36.2 m decade−1 for terrestrial insects and +32.7 m decade−1 for woody plants, whereas it was estimated to range between −1.0 and +11 m decade−1 for semi‐aquatic insects, ferns, birds and wood‐decaying fungi. The upper range limit (leading edge) of most species also shifted upslope with a rate clearly higher for animals (from +47 to +91 m decade−1) than for plants (from +17 to +40 m decade−1), except for semi‐aquatic insects (−4.7 m decade−1). Although regional land‐use changes could partly explain some trends, the consistent upward shift found in almost all taxa all over the Alps is likely reflecting the strong warming and the receding of snow cover that has taken place across the European Alps over recent decades. However, with the possible exception of terrestrial insects, the upward shift of organisms seems currently too slow to track the pace of isotherm shifts induced by climate warming, estimated at about +62 to +71 m decade−1 since 1970. In the light of these results, species interactions are likely to change over multiple trophic levels through phenological and spatial mismatches. This nascent research field deserves greater attention to allow us to anticipate structural and functional changes better at the ecosystem level. [ABSTRACT FROM AUTHOR]

This paper presents changes in the ice regime of lakes located in the northern part of Poland. It has been established that in the period 1960–2019, there was a successive decline in the ice extent of lakes, clearly visible in individual parameters; formation of ice cover is delayed by 3.0 days/decade (on average for all lakes), its decline occurred earlier by 3.8 days/decade, and the length of ice cover is shorter by 6.8 days/decade. Moreover, the maximum thickness of the ice cover is becoming thinner, and this process has progressed at an average rate of 2.3 cm/decade. The aforementioned situation shows strong relations with air temperature. It was particularly evident in the late 1980s, when a change in the thermal regime took place, which was documented in most of the analysed parameters, as demonstrated in the study. It has been established that from that period up to now, the decline of ice cover tends to start 19 days earlier, the duration of ice cover is shorter by 22 days, and the ice cover is 8 cm thinner, on average. The observed transformation affects the imbalance of the existing equilibrium in lakes, which can be related to both biotic and abiotic processes. [ABSTRACT FROM AUTHOR]

Atmospheric boundary layer (ABL) dynamics over glaciers mediate the response of glacier mass balance to large‐scale climate forcing. Despite this, very few ABL observations are available over mountain glaciers in complex terrain. An intensive field campaign was conducted in June 2015 at the Athabasca Glacier outlet of Columbia Icefield in the Canadian Rockies. Observations of wind and temperature profiles with novel kite and radio‐acoustic sounding systems showed a well‐defined mesoscale circulation developed between the glacier and snow‐free valley in fair weather. The typical vertical ABL structure above the glacier differed from that expected for "glacier winds"; strong daytime down‐glacier winds extended through the lowest 200 m with no up‐valley return flow aloft. This structure suggests external forcing at mesoscale scales or greater and is provisionally termed an "icefield breeze." A wind speed maximum near the surface, characteristic of a "glacier wind," was only observed during night‐time and one afternoon. Lapse rates of air temperature down the glacier centerline show the interaction of down‐glacier cooling driven by sensible heat loss into the ice, entrainment and periodic disruption and warming. Down‐glacier cooling was weaker in "icefield breeze" conditions, while in "glacier wind" conditions, stronger down‐glacier cooling enabled large increases in near‐surface temperature on the lower glacier during periods of surface boundary layer (SBL) disruption. These results raise several questions, including the impact of Columbia Icefield on the ABL and melt of Athabasca Glacier. Future work should use these observations as a testbed for modeling spatio‐temporal variations in the ABL and SBL within complex glaciated terrain. Plain Language Summary: Mountain glaciers are experiencing rapid change in response to climate change. But to confidently attribute past change and predict future change, our mathematical models need to account for how glaciers modify the climate they experience. New measurements of wind and temperature have been made over an outlet glacier of the Columbia Icefield, Canadian Rockies using a novel kite‐based measurement system along with an extensive set of meteorological measurements on the glacier surface and in the valley below the glacier. They show that the persistent down‐glacier winds observed at the glacier surface have a different vertical structure than expected from previous observations and theory. Down‐glacier winds typically cool the air next to the surface as it travels down‐glacier. Here it is shown that this cooling process is more limited when the wind is strong throughout the lower valley over the glacier, compared with times when wind speed is strongest next to the glacier and weaker above. The data set presented in this paper provides an opportunity to test the models used to link glaciers and climate. Key Points: A well‐developed mesoscale wind develops over a Columbia Icefield outlet glacier but differs from previously documented "glacier winds"Novel kite and radio‐acoustic observations indicate strong down‐glacier winds typically extend through the lowest 200 m of above‐glacier ABLKatabatic cooling in the glacier surface boundary layer is reduced during periods with "icefield breezes" compared to periods with typical "glacier winds" [ABSTRACT FROM AUTHOR]

In climate change research, accurate temperature data are often demanded. However, affected by many factors, especially solar radiation, the accuracy of environmental air temperature measurement can be greatly reduced, since there is a difference in temperature between the environmental air and the related temperature measured by the sensor accommodated inside the radiation shield. In the paper, the term “temperature error” refers to the temperature difference described above. To improve the accuracy of the temperature data, a temperature errorcorrection method is proposed. First, a computational fluid dynamics (CFD) method is adopted to quantify the temperature errors accurately. A neural network algorithm is then applied to form a universal correction equation by fitting temperature errors calculated using the CFD method. Finally, to validate the correction equation, field observation experiments are performed. The root mean square error (RMSE) and the mean absolute error (MAE) between the temperature errors obtained experimentally using a sensor inside the DTR503A shield and the corresponding temperature errors determined by using the proposed correction method are 0.043 and 0.038°C, respectively. The RMSE and MAE for the DTR13 radiation shield are 0.049 and 0.044°C, respectively. This method may reduce the error of the temperature data to 0.05°C. If the environmental factors corresponding to the temperature data can be quantified accurately, the factors influencing the temperature error can be added to the correction method continuously. The accuracy of this correction method may be furtherly improved. [ABSTRACT FROM AUTHOR]

A new data set of Night Marine Air Temperature (NMAT) is presented that builds on the HadNMAT2 data set, which was released in 2013. In a similar manner to HadNMAT2, the new data set (CLASSnmat) provides uninterpolated, monthly global values at a 5° resolution back to 1880. In addition to being extended to the end of 2019, four main developments are made in CLASSnmat: (1) the NMAT values are extracted from the most recent version of the International Comprehensive Ocean‐Atmosphere Data Set (ICOADS Release 3) and a revised method of eliminating duplicated observations is used; (2) values of NMAT are adjusted to 2m and 20m heights in addition to the 10 m height used in HadNMAT2; (3) a refinement is made to the corrections necessary during World War 2, which uses more of the NMAT observations and hence results in a more extensive spatial coverage for this period than was possible in HadNMAT2; (4) an updated gridding method is used that allows for an improved propagation of uncertainty from the individual NMAT values through to the gridded estimates. In this paper, the method used to construct CLASSnmat (version 1.0.0.0) is described. [ABSTRACT FROM AUTHOR]

Alpine headwaters in subarctic regions are particularly sensitive to climate change, yet there is little information on stream thermal regimes in these areas and how they might respond to global warming. In this paper, we characterize and compare the hydrological and thermal regimes of two subarctic headwater alpine streams within an empirical framework. The streams investigated are located within two adjacent catchments with similar geology, size, elevation and landscape, Granger Creek (GC) and Buckbrush Creek (BB), which are part of the Wolf Creek Research Basin in the Yukon Territory, Canada. Hydrometeorological and high‐resolution stream temperature data were collected throughout summer 2016. Both sites exhibited a flow regime typical of cold alpine headwater catchments influenced by frozen ground and permafrost. Comparatively, GC was characterized by a flashier response with more extreme flows, than BB. In both sites, stream temperature was highly variable and very responsive to short‐term changes in climatic conditions. On average, stream temperature in BB was slightly higher than in GC (respectively 5.8 and 5.7°C), but less variable (average difference between 75th and 25th quantiles of 1.6 and 2.0°C). Regression analysis between mean daily air and stream temperature suggested that a greater relative (to stream flow) groundwater contribution in BB could more effectively buffer atmospheric fluctuations. Heat fluxes were derived and utilized to assess their relative contribution to the energy balance. Overall, non‐advective fluxes followed a daily pattern highly correlated to short‐wave radiation. G1enerally, solar radiation and latent heat were respectively the most important heat source and sink, while air–water interface processes were major factors driving nighttime stream temperature fluctuations. [ABSTRACT FROM AUTHOR]

Permafrost on the Qinghai–Tibet Plateau (QTP) has undergone degradation as a result of recent climate change. This may alter the thermo‐hydrological processes and unlock soil organic carbon, and thereby affect local hydrological, ecological, and climatic systems. The relationships between permafrost and climate change have received extensive attention, and in this paper we review climate change for permafrost regions of the QTP over the past 30 years. We summarize the current state and changes in permafrost distribution and thickness, ground temperature, and ground ice conditions. We focus on changes in permafrost thermal state and in active‐layer thickness (ALT). Possible future changes in ground temperature and ALT are also discussed. Finally, we discuss the changes in hydrological processes and to ecosystems caused by permafrost degradation. Air temperature and ground temperature in the permafrost regions of the QTP have increased from 1980 to 2018, and the active layer has been thickening at a rate of 19.5 cm per decade. The response of permafrost to climate change is not as fast as in some reports, and permafrost degradation is slower than projected by models that do not account for conditions deep in permafrost. [ABSTRACT FROM AUTHOR]

This article attempts to predict the spatiotemporal changes of permafrost in the Headwater Area of the Yellow River (HAYR) on the northeastern Qinghai‐Tibet Plateau, Southwest China by using field monitoring and numerical models. Permafrost in the HAYR is categorized into four types: low‐ and high‐ice‐content high‐plain permafrost and low‐ and high‐ice‐content alpine permafrost. According to these permafrost types, changes in permafrost temperature were calculated by coupling a geometric model with the soil thermal conduction model. Based on the calculation results, this paper evaluates the changes of permafrost in the HAYR over the past 50 years and predicts the change trends of permafrost in the HAYR under the scenarios of RCP2.6, RCP6.0, and RCP8.5 for possible climate change in 2050 and 2010 from the Intergovernmental Panel on Climate Change Fifth Assessment Report. The results show that (a) in the process of permafrost degradation, the same permafrost type at different degradation stages results in different modes and rates of increasing temperature. The response of permafrost to climate change differs in various degradation stages of permafrost; (b) from 1972 to 2012, the areal extent of permafrost degradation was 1,056 km2, resulting from a sharp air temperature increase after the 1980s. By 2050, the areal extent of permafrost degradation into seasonal frost is similar under the three scenarios of climate change. The areal extent of permafrost degradation is 2,224, 2,347, and 2,559 km2 or 7.5%, 7.9%, and 8.6% of the total area in the HAYR, respectively. In RCP2.6, the areal extent of permafrost degradation into seasonal frost by 2100 would be approximately 3,500 km2 greater than that by 2050. In RCP6.0, the areal extent of permafrost degradation by 2100 would be 10,000 km2 or 32.9% of the total area in the HAYR. In RCP8.5, the area of permafrost degradation by 2100 would be 18,492 km2 or 62.2% of the total area in the HAYR; (c) the active layer thickness (ALT) in the HAYR would increase significantly. The average of the ALT was 1.51 m by 1972 and 2.01 m by 2012, respectively. Under the RCP2.6, RCP6.0, and RCP8.5 scenarios, the basin‐wide average of ALT would be 2.21, 2.40, and 3.08 m by 2050 and 2.78, 4.07, and 4.39 m by 2100, respectively. [ABSTRACT FROM AUTHOR]

The primary objective of this paper was to determine the circulation conditions of the occurrence of cold spells in Poland and Germany. The observed inconsiderable warming slightly contributed to a change in the number of cold days and cold spells. The occurrence of cold spells in Poland and Germany was related to considerably more active and intensive pressure systems than on average in the winter season in the studied years. A strong high pressure system was located over much of the continent, blocking westerly circulation. During the occurrence of cold spells, negative anomalies of isobaric surface heights were recorded with the greatest anomalies being in the 300–250 hPa heights. The highest air temperature anomalies were recorded on the lowest isobaric levels, where they amounted to <−10°C. On average, anomalies on the 300 hPa isobaric level began developing approximately 9 days before the beginning of cold spells over the study area. The decay of cold spells was not related to rapid exchange of air masses, but rather to gradual weakening of anomalies in the upper troposphere, and their shifting westwards. [ABSTRACT FROM AUTHOR]

Macroclimate drives vegetation distributions, but fine‐scale topographic variation can generate microclimate refugia for plant persistence in unsuitable areas. However, we lack quantitative descriptions of topography‐driven microclimatic variation and how it shapes forest structure, diversity, and composition. We hypothesized that topographic variation and the presence of the forest overstory cause spatiotemporal microclimate variation affecting tree performance, causing forest structure, diversity, and composition to vary with topography and microclimate, and topography and the overstory to buffer microclimate. In a 20.2‐ha inventory plot in the North American Great Plains, we censused woody stems ≥1 cm in diameter and collected detailed topographic and microclimatic data. Across 59‐m of elevation, microclimate covaried with topography to create a sharp desiccation gradient, and topography and the overstory buffered understory microclimate. The magnitude of microclimatic variation mirrored that of regional‐scale variation: with increasing elevation, there was a decrease in soil moisture corresponding to the difference across ~2.1° of longitude along the east‐to‐west aridity gradient and an increase in air temperature corresponding to the difference across ~2.7° of latitude along the north‐to‐south gradient. More complex forest structure and higher diversity occurred in moister, less‐exposed habitats, and species occupied distinct topographic niches. Our study demonstrates how topographic and microclimatic gradients structure forests in putative climate‐change refugia, by revealing ecological processes enabling populations to be maintained during periods of unfavorable macroclimate. [ABSTRACT FROM AUTHOR]

The research on the trends of mountainous aridity and the issue of elevation‐dependent aridity (EDA) has long been hindered by limitations in data validity. In this study, we present global monthly merged data sets of Vapor Pressure Deficit and Aridity Index (AI) from 1960 to 2020, aiming to detect and attribute elevation‐dependent patterns of atmospheric and soil aridity in six representative high mountainous areas worldwide. Our findings reveal that most of the mountainous regions experienced significant aridification after the 1970s (p < 0.05). The Rocky Mountains and Ethiopian Highlands are identified as the most vulnerable areas, with both atmospheric and soil aridity increasing by 13% across all elevation gradients. Significant humidification has been observed only in High Asian Regions at 4,000 m above sea level with an approximate decrease of 11% in soil AI. In both temporal and spatial patterns, soil aridity exhibits stronger heterogeneity compared to atmospheric aridity, with certain regions and seasons showing humidification, despite the overall aridification trend. Elevation‐dependent aridity is observed in two‐thirds of the mountains, but whether high altitude alleviates or amplifies aridity depends on the pattern of precipitation changes at different elevations. The rise in air temperature is the primary driving factor for soil and atmospheric aridification, contributing to over 50% of each. In two‐thirds of the regions, changes in precipitation exacerbate soil aridity. Simulations show that human activities are closely related to the ongoing prolonged atmospheric aridification. This study contributes to a comprehensive understanding of global mountainous aridity evolution projected under climate change. Plain Language Summary: Due to limitations in data validity, the conclusions regarding mountainous aridity changes and related elevation‐dependent aridity issues have often been contradictory. To address this issue, we generated a comprehensive data set of drought indices by integrating observed and simulated data, covering the period from 1960 to 2020. Our analysis revealed that the 1970s marked a significant turning point for aridity patterns in mountainous regions globally. Since then, except for the High Asian Regions, both soil and atmospheric aridity have exhibited a rapid increase in mountainous areas worldwide, with the most severe aridification observed in the Rocky Mountains and Ethiopian Highlands. We also identified a certain relationship between the severity of aridification and elevation gradients, although it is not a straightforward relationship where higher elevations necessarily experience more severe aridification. Importantly, our attribution analysis suggests that human activities may impact the observed atmospheric aridification in mountainous regions on a global scale. Key Points: The period from 1970 to 1980 witnessed a significant shift from humidification to aridification in most mountainous regions worldwideThe relationship between changes in precipitation and elevation gradients shapes the distinct patterns of elevation‐dependent aridityProlonged atmospheric aridification in mountainous regions may not be solely attributed to natural variability [ABSTRACT FROM AUTHOR]

Continuous urban development significantly transforms the ecosystem in a big city. The increasing frequency of heat waves and their influence on the rise in mortality in big cities suggest that the thermal hazard (long‐term occurrence of high air temperature) is one of the key climatic hazards of present times. The global temperature rise, reinforced in urbanized areas by the anthropogenic heat flux, leads to intensified convection processes and increased precipitation, especially torrential rain. One of the most important hydrological hazards in a big conurbation is the urban flood hazard. In this paper the identified climatic hazards occurring in a big city are analysed: the thermal hazard and the urban flood hazard. The areas currently exposed to thermal and urban flood hazards in Warsaw are identified and assessed in terms of the hazard level. The results obtained are verified with the data from meteorological measuring stations (the thermal hazard) and from the Fire Department interventions connected with rainfall and flooding (the urban flood hazard). A map of hydro‐meteorological hazards was created by combining thermal hazard and urban flood hazard maps. The approach combining the exposure to thermal and urban flood hazards, presented in this study, uses widely accessible spatial data and can be applied to any location. It can also play a significant role in assessing the adaptation of urban areas to climate change and be an important source of information on the current exposure to hydro‐meteorological hazards as well as their possible increase. [ABSTRACT FROM AUTHOR]

Hoar frost, one of the most common types of road slipperiness, can reduce road surface friction thereby adversely affecting traffic safety. The two main causes of hoar frost are warm air advection and radiative cooling. This paper investigates the impact of a changing climate on the formation of hoar frost in Sweden during the winter months due to warm air advection and radiative cooling. The analysis is based on in situ observations from 244 stations in the Swedish Road Weather Information System. The results show that in northern Sweden, hoar frost was mainly caused by warm air advection, while radiative cooling was the main cause of hoar frost in southern Sweden. Given the increase in the air temperature over land due to climate change during the period 2000–2016, the relative frequency of hoar frost due to warm air advection has significantly decreased, while the relative frequency of hoar frost due to radiative cooling has significantly increased. Further analysis showed that the weakened temperature gradient between land and ocean, which leads to weakened warm air advection, is the main cause of the changes. Locations of in situ RWIS stations and their respective clusters (triangles), and the centres of geostrophic wind calculated for the three regions (stars). The background shows the four traditional Swedish climate zones as shown in Wallman (2004). [ABSTRACT FROM AUTHOR]

In the paper we focus on the notes of botanist and meteorologist Gottfried Reyger on the weather conditions in Gdańsk, Poland. In our estimation, this chronicle, covering the period from December 1721 to June 1786 (the longest weather chronicle recorded by a single person), is a reliable source of information with the potential to contribute to the understanding of climate variability in 18th‐century Gdańsk, the significant old Hanseatic city in northern Poland. The temperature and precipitation series for the period 1721–1786 were indexed against contemporary conditions using the calculated percentages of cold, normal and warm decades. The climate in the 18th century in Gdańsk was colder than nowadays; the springs were much cooler, as were the winters, while the summers were warmer. A few relatively cold periods and several warm periods were identified. The first half of the analysed period was very humid, whereas the second was quite dry. The reconstructed indexed data series were compared to annual and seasonal mean values of air temperature and precipitation derived from regular instrumental observations made in Gdańsk since 1739. The linear regression method was applied to calibrate the reconstructed index series against anomalies from the 1961–1990 average. The correlation coefficient, standard error of estimate and the root‐mean‐square error statistics were used to diagnose the quality of calibration and verification. The highest correlation between the temperature indices and the observational series was found for winter. The reconstructed series for precipitation has a smaller variability than in reality. The reconstructed values for the years prior to 1739 indicate cold years for 1725–1732 and a wet period in the 1730s. The chronicle of botanist and meteorologist Gottfried Reyger, covering the period 1721–1786, characterizes the thermal and precipitational conditions in Gdańsk, Poland. The series were indexed against contemporary conditions, compared with instrumental data and reconstructed for early non‐instrumental period. The 18th‐century Gdańsk was colder than nowadays, particularly on case of springs, while the summers were warmer. The first decades of the period were very humid, whereas the latter ones quite dry. In the figure, annual air temperature (left panel) and precipitation (right panel) reconstruction for Gdańsk for the period 1722–1785 presented in the context of observational series, 1739–1785 for air temperature and 1739–1772 for precipitation. Solid line shows observational data; dotted line shows reconstructed series. [ABSTRACT FROM AUTHOR]

Abstract: Innovative and effective responses to climate change require that we move beyond reliance on government to include organisations spanning different sectors, such as not‐for‐profit, private, and community groups. Interactions among these organisations in collaborative networks—or “forums”—may provide important mechanisms to successfully address climate change impacts. This paper investigates the relationships between organisational participation and involvement in forums and responses to climate change. Survey data show that people from many organisations are participating in forums and using these meeting points to discuss climate change, even when forums are intended to serve other purposes. The data suggest that participation in any type of forum is related to organisational responses to climate change. Attributes such as type of organisation and knowledge of climate change issues were also found to be related to organisational responses to climate change but these became less important when climate change was discussed in forums. The results of the research suggest that a practical way to increase the volume and variety of organisational responses to climate change may be to encourage participation in forums and/or to influence existing networks to incorporate more discussions of climate change issues. [ABSTRACT FROM AUTHOR]

Reconstructed temperatures through the Phanerozoic indicate a gradual cooling or, at best, no significant temperature trend, despite a 4.4% increase in solar heating. It is possible that an underlying warming trend has simply been swamped by 'noise' due to significant data-errors and/or natural fluctuations. Alternatively, the lack of warming may indicate cooling by biological and/or geological processes, which happen to have the right amplitude to cancel the effects of solar warming. This paper demonstrates that the absence of Phanerozoic warming cannot be explained as a warming trend hidden by noise. It also shows that, given widely accepted estimates of climate sensitivity, it cannot be explained as cancellation by negative feedback in the climate system. The Gaia hypothesis, anthropic selection or some other unconventional mechanism may therefore have to be invoked to explain the absence of long-term warming through the Phanerozoic. [ABSTRACT FROM AUTHOR]

ABSTRACT: Extreme precipitation events are widely thought to intensify in a warmer atmosphere through the Clausius‐Clapeyron equation. The temperature‐extreme precipitation scaling was proposed to analyse the temperature dependency of short‐duration extreme precipitation and since then, the concept has been widely used in climatology. Bao et al. (2017) suggest that the apparent scaling reflects not only how surface air properties affect extreme precipitation, but also reflects how synoptic conditions and localized cooling due to the storm itself affect the scaling – implying two‐way causality. We address here critical issues of this paper and provide evidence that dew point temperature drives extreme precipitation, with the direction of causality reversed only for the storm's peak intensity. This physical inference may serve as a basis to better quantify scaling rates and to help establish the relationship between extreme precipitation and environmental conditions in the current climate, and thereby provide insights into future changes to precipitation extremes due to climate change. [ABSTRACT FROM AUTHOR]

This review was undertaken to draw together research on how climate change impacts sugarcane production, and to assess the implications of climate change for the sugarcane industry, as well as possible response options. Much of the extant research examines how changes in climate lead to changes in primary production; however, few studies consider how climate change translates into industry-wide impacts and economic consequences across the sugarcane value chain. Of the 90 studies we reviewed (published as journal articles, proceedings, and book chapters), 61 assess observed and/or projected impacts of climate change on sugarcane production. These studies reach largely different conclusions regarding how increases in air temperature or atmospheric carbon dioxide levels impact sugarcane production. These mixed results can be attributed to differences between the studies in terms of methods, time frames, and growing regions, which all limit cross-study comparability. A total of 17 studies focus on the adaptation to observed and/or projected impacts of climate change, such as changed management procedures or farming practices, but there is limited evidence regarding successful adaptation outcomes. In addition, a separate stream of papers discusses mitigating energy use and greenhouse gas emissions in the sugarcane production process, often with a view to reducing environmental impacts. Our review concludes by outlining the pathways for future research, highlighting that further insights are needed in particular regarding the economic consequences of climate change for the sugarcane industry. WIREs Clim Change 2018, 9:e498. doi: 10.1002/wcc.498 This article is categorized under: Future of Global Energy > Evaluating Future Impacts of Climate Change [ABSTRACT FROM AUTHOR]

In light of global climate change, ecological studies increasingly address effects of temperature on organisms and ecosystems. To measure air temperature at biologically relevant scales in the field, ecologists often use small, portable temperature sensors. Sensors must be shielded from solar radiation to provide accurate temperature measurements, but our review of 18 years of ecological literature indicates that shielding practices vary across studies (when reported at all), and that ecologists often invent and construct ad hoc radiation shields without testing their efficacy. We performed two field experiments to examine the accuracy of temperature observations from three commonly used portable data loggers ( HOBO Pro, HOBO Pendant, and iButton hygrochron) housed in manufactured Gill shields or ad hoc, custom-fabricated shields constructed from everyday materials such as plastic cups. We installed this sensor array (five replicates of 11 sensor-shield combinations) at weather stations located in open and forested sites. HOBO Pro sensors with Gill shields were the most accurate devices, with a mean absolute error of 0.2°C relative to weather stations at each site. Error in ad hoc shield treatments ranged from 0.8 to 3.0°C, with the largest errors at the open site. We then deployed one replicate of each sensor-shield combination at five sites that varied in the amount of urban impervious surface cover, which presents a further shielding challenge. Bias in sensors paired with ad hoc shields increased by up to 0.7°C for every 10% increase in impervious surface. Our results indicate that, due to variable shielding practices, the ecological literature likely includes highly biased temperature data that cannot be compared directly across studies. If left unaddressed, these errors will hinder efforts to predict biological responses to climate change. We call for greater standardization in how temperature data are recorded in the field, handled in analyses, and reported in publications. [ABSTRACT FROM AUTHOR]

Environmental descriptors derived from mean performances of contemporary groups ( CGs) are assumed to capture any known and unknown environmental challenges. The objective of this paper was to obtain a finer definition of the unknown challenges, by adjusting CG estimates for the known climatic effects of monthly maximum air temperature (MaxT), minimum air temperature (MinT) and monthly rainfall (Rain). As the unknown component could include infection challenges, these refined descriptors may help to better model varying responses of sire progeny to environmental infection challenges for the definition of disease resilience. Data were recorded from 1999 to 2013 at a piggery in south-east Queensland, Australia ( n = 31,230). Firstly, CG estimates of average daily gain ( ADG) and backfat ( BF) were adjusted for MaxT, MinT and Rain, which were fitted as splines. In the models used to derive CG estimates for ADG, MaxT and MinT were significant variables. The models that contained these significant climatic variables had CG estimates with a lower variance compared to models without significant climatic variables. Variance component estimates were similar across all models, suggesting that these significant climatic variables accounted for some known environmental variation captured in CG estimates. No climatic variables were significant in the models used to derive the CG estimates for BF. These CG estimates were used to categorize environments. There was no observable sire by environment interaction (Sire×E) for ADG when using the environmental descriptors based on CG estimates on BF. For the environmental descriptors based on CG estimates of ADG, there was significant Sire×E only when MinT was included in the model ( p = .01). Therefore, this new definition of the environment, preadjusted by MinT, increased the ability to detect Sire×E. While the unknown challenges captured in refined CG estimates need verification for infection challenges, this may provide a practical approach for the genetic improvement of disease resilience. [ABSTRACT FROM AUTHOR]

While previous studies have largely focused on anthropogenic warming characterized by surface air temperature, little is known about the behaviors of human‐perceived temperature (HPT), which describe the "feels‐like" equivalent temperature by considering the joint effects of temperature, humidity and/or wind speed. Here we adopted an optimal fingerprinting method to compare seasonal mean HPTs in China with those from simulations conducted with multiple climate models participating in the Coupled Model Intercomparison Project Phase 6. We found clear anthropogenic signals in the observational records of changes in both summer and winter HPTs over the period 1971–2020. Moreover, the anthropogenic greenhouse gas influence was robustly detected, with clear separation from natural and anthropogenic aerosol forcings. The anthropogenic greenhouse gas forcing plays the dominant role (>90%) of human‐perceived warming. Urbanization effects contribute slightly and moderately to the estimated trends in summer and winter HPTs, respectively, in addition to the effects of external forcing. Plain Language Summary: Human influences have been identified in the observed warming quantified by surface air temperature (SAT), but SAT alone is inadequate as a metric for human thermal comfort. Here we focus on human‐perceived temperature (HPT), which describes the "feels‐like" equivalent temperature by considering the joint effects of temperature, humidity, and/or wind speed. We isolate anthropogenic impacts on the observed increase in summer and winter HPTs in China during 1971–2020 by comparing observations with state‐of‐the‐art climate models. Results show that the influence of anthropogenic greenhouse gas is detected, with clear separation from other external forcings such as solar and volcanic activities and anthropogenic aerosols. The human‐induced greenhouse gas increases are also found to explain most (>90%) of the observed human‐perceived warming. Along with the effects of large‐scale anthropogenic forcing, urbanization effects also have a slight to moderate influence on the estimated trends in summer and winter HPTs. Our work is an early attempt to provide quantitative evidence for the physiological impacts of anthropogenic global warming and local urbanization on human beings. Key Points: The warming is quantified by human‐perceived temperature that considers the joint effects of temperature, humidity and/or wind speedHuman influence could be robustly detected in both summer and winter human‐perceived warmingThe observed increase in human‐perceived temperature is mostly attributed to anthropogenic greenhouse gas increases [ABSTRACT FROM AUTHOR]

In a changing climate, it is likely that precipitation patterns will experience shifts in amount and seasonality, with a tendency towards increased drought in many parts of Europe. In order to investigate what could be some of the feedbacks of dry conditions on temperature, this paper has investigated close to 30 European locations to assess the influence of observed dry summer days on daily maximum temperature ( Tmax) as well as a clustering of rainless days, and finally the temperature impact related to drought conditions as defined by the Standardized Precipitation Index. The results show that for the three main European climatic regions investigated ('Mediterranean', 'Maritime', 'Continental'), the influence of rainless days is discernible, with an average difference between mean summer Tmax and Tmax during rainless days only of up to 1.5 °C. A further aim of the study is to determine whether recent shifts in the occurrence of rainless days during the summer have a bearing on temperature trends. Results show that shifts in rainless days explain only a fraction of the observed temperature change at the locations studied, thereby hinting that the enhanced greenhouse effect remains the dominant mechanism for temperature change. Finally, using a regional climate model, very preliminary insight into a 'greenhouse climate' highlights the fact that changes in dry conditions seem to confirm the findings for current climate, i.e. they account for only a fraction of the increase in temperatures. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

ABSTRACT This paper documents the changes in climate extremes over Indonesia during the past three decades (1983-2012) based on a subset of extreme indices recommended by the Expert Team on Climate Change Detection and Indices ( ETCCDI). The extreme indices were calculated based on the quality controlled daily observational data (minimum and maximum temperature and precipitation) from 88 weather stations. Overall, we found significant and spatially coherent trends of warming in the temperature indices over Indonesia, consistent with other studies conducted at different countries within the Southeast Asia. The frequency of cool days ( TX10p) and cools nights ( TN10p) had decreased whereas warm days ( TX90p) and warm nights ( TN90p) were observed more frequently. Averaged over the country, the annual mean of daily maximum ( TXmean) and minimum temperature ( TNmean) had increased significantly by 0.18 and 0.30 °C decade−1, respectively. Other temperature indices also showed significant warming trends. In contrast, trends in the precipitation extremes indices were generally not significant and less spatially coherent. However, a tendency towards wetter conditions was observed, in agreement with the results at the global scale. The daily precipitation intensity ( SDII) had increased significantly over the country by 0.21 mm day−1 decade−1 during the period studied. At the regional scale, we observed a significant wetting trend in the annual highest daily amount ( RX1day) and the rainfall amount contributed by the extremely very wet days (R99p) in the northern part of the country. The wetting trends of a number of extreme precipitation indices were depicted prominently in December-January-February ( DJF) and/or March-April-May ( MAM) seasons, both at country and regional levels. However, for the southern region of Indonesia, a drying tendency was observed for June-July-August ( JJA), September-October-November ( SON) and MAM. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is the largest permafrost distribution zone at high‐altitude in the mid‐latitude region. Climate change has caused significant permafrost degradation on the TP, which has important impacts for the eco‐hydrological processes. In this study, the frost number is utilized to calculate the frost number (F) based on the air freezing/thawing index obtained from the downscaled Coupled Model Intercomparison Project Phase 6 (CMIP6) data sets. A novel method is proposed to determine the frost number threshold (Ft) for diagnosing permafrost distribution. Then the simulated permafrost distribution maps are compared with the existing permafrost distribution map, employing the Kappa coefficient as the measure of classification accuracy to identify the optimal Ft. Finally, the permafrost distribution on the TP under different Shared Socio‐economic Pathways (SSP) scenarios are diagnosed with the optimal Ft. Simulation results demonstrate that across all scenarios, the rates of permafrost degradation during the mid‐future period (2040–2060) remain comparable to those observed in the baseline period (2000), ranging from 33% ± 3% to 53% ± 4%. Conversely, during the far‐future (2080–2099), the permafrost degradation rates display significant variation across different scenarios, ranging from 37% ± 4% to 96% ± 3%. The profound impacts of permafrost degradation on the TP are reflected in decreasing trends in soil moisture and runoff, as well as a slower increasing trend in Normalized Difference Vegetation Index (NDVI) compared to other regions, indicating negative impacts on vegetation growth. Plain Language Summary: The Tibetan Plateau, the highest plateau in the world and the largest high‐altitude permafrost region, is experiencing permafrost degradation due to climate change, significantly impacting eco‐hydrological processes in this region. In this study, we used the frost number model with air temperature to simulate the distribution of permafrost on the Tibetan Plateau under different scenarios. The results show that permafrost on the Tibetan Plateau is projected to degrade in the 21st century, especially under high‐emission scenarios. The degradation of permafrost will likely reduce soil moisture and runoff. Additionally, vegetation growth in areas with permafrost degradation is expected to be slow. These findings are of great significance for understanding permafrost changes on the Tibetan Plateau and their impacts on eco‐hydrological processes. Key Points: A new method using the frost number model with Kappa coefficient is proposed to diagnose permafrost distributionPermafrost on the Tibetan Plateau will experience the least degradation (33% ± 3%) under SSP126, and the most (96% ± 3%) under SSP585 in 2080–2099Permafrost degradation on the Tibetan Plateau is anticipated to reduce soil moisture and runoff, adversely affecting vegetation growth [ABSTRACT FROM AUTHOR]

There is an increasing focus on the usefulness of climate model--based seasonal precipitation forecasts as inputs for hydrological applications. This study reveals that most models from the North American Multi-Model Ensemble (NMME) have potential to forecast seasonal precipitation over 17 hydroclimatic regions in continental China. In this paper, we evaluated the NMME precipitation forecast against observations. The evaluation indices included the correlation coefficient (R), relative root-mean-square error (RRMSE), rank histogram (RH), and continuous ranked probability skill score (CRPSS).We presented the RRMSE-R diagram to distinguish differences between the performances of individual models. We find that the predictive skill is seasonally and regionally dependent, exhibiting higher values in autumn and spring and lower values in summer. Higher predictive skill is observed over most regions except the southeastern monsoon regions, which may be attributable to local climatology and variability. Among the 11 NMME models, CFS, especially CFSv2, exhibits the best predictive skill. The GFDL and NASA models, which are followed by CMC, perform worse than CFS. The performances of IRI and CCSM3 are relatively worse than that of the other models. The forecast skills are significantly improved in multi-model mean forecasts based on simple model averaging (SMA). The improvement is more obvious for Bayesian model averaging (BMA), which is employed to further improve the forecast skill and address model uncertainty using multiple model outputs, than individual model and SMA. [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]

SUMMARY On March 11, 2011, the power system suffered heavy damage from the huge earthquake and tsunami in the Tohoku region. This paper describes the change of features included in the time series of open demand data for the disaster of 3/11/2011. The demand data are separated into three sections: one for the 'predisaster' analysis from April 2008 to February 2011, the second for the 'during-disaster' survey from March to May 2011, and the last for the 'postdisaster' analysis from June 2011 to March 2013. We distinguished the periodic components of daily, weekly, and seasonal fluctuation among the demand time series by applying a newly developed procedure, the quasi-ideal moving average method. Some significant changes were observed in the statistics of the predisaster and postdisaster periodic component analysis. The change in temperature sensitivity was also surveyed by using open weather data for Sendai. [ABSTRACT FROM AUTHOR]

New Zealand's best‐known record of surface air temperature is the partially homogenised seven‐station series of the National Institute of Water and Atmospheric Research. The homogeneity analysis used in constructing this series depends on the completeness of the site histories and issues arise if relevant information is missing. Recent developments in the online availability of searchable historical records provide an opportunity to supplement early metadata. This potential is explored here using Albert Park (Auckland) as a case study. A wealth of relevant historical information about Albert Park was found in online archives, especially related to a major episode of site disturbance, evolving site environment and instrumentation changes. [ABSTRACT FROM AUTHOR]

Rail infrastructure is vulnerable to extreme weather events, resulting in damage and delays to networks. The impact of heat is a major concern for the London Underground (LU) by Transport for London (TfL) both now and in future, but existing studies are limited to passenger comfort on the deep tube and do not focus on infrastructure or the vast majority of the network, which is in fact above ground. For the first time, the present empirical study examines quantitatively the statistical relationship between LU delays (by synthesizing 2011-2016 industry data) with air temperature data (from Met Office archives). A range of testing shows strong statistical relationships between most delay variables and high temperatures, though not causality. Relationships were found between high temperatures and delays associated with different asset classes on different LU lines. Track-related delays, often the focus of high-temperature research (i.e. track buckling), show a relationship, although this is small relative to delays caused by other assets. Using UK Climate Projections 2009 (UKCP09) and assuming a similar future performance indicates that the share of annual delays owed to temperatures > 24°C may increase in frequency and length, depending on the emissions scenario. Recommendations include extending the analysis to the LU asset scale and considering the local environment to understand failure causality in order to mitigate future heat risk. A review of how TfL and other infrastructure operators capture delays for future analysis is necessary to facilitate climate resilience benchmarking between networks. [ABSTRACT FROM AUTHOR]

ABSTRACT This work introduces a new climate description scheme based on a long range statistical model fitted to local daily temperature anomaly series. The appropriate model can be considered as a sum of two processes, namely, stationary white noise ( WN) and nonstationary random walk ( RW). In the case of local series, the variance of the WN component appears to be much larger than that for the generator of RW (also a WN, but independent on the first one). Such a situation enables us to approximate the range of variability for local temperature anomalies by means of the standard deviation of the stationary WN component of the model. This means that the climate description splits into two parts; one describes ordinary and the other extreme weather events. This paper presents a detailed description of that approach using the air temperature series from Stockholm (1756-2011) as an example. The scheme produced here enables us to see that large weather variability does not always mean climate variability. It separates climate and weather scale variability, which is important for precise determination of climate variability and does not confuse the weather and climate time scales in climate description. [ABSTRACT FROM AUTHOR]

Because of its low topographic relief, unique hydrology, and the large interannual variability of precipitation, Florida is especially vulnerable to climate change. In this paper, we investigate a comprehensive collection of climate metrics to study historical trends in both averages and extremes of precipitation and temperature in the state. The data investigated consist of long-term records (1892-2008) of precipitation and raw (unadjusted) temperature at 32 stations distributed throughout the state. To evaluate trends in climate metrics, we use an iterative pre-whitening method, which aims to separate positive autocorrelation from trend present in time series. Results show a general decrease in wet season precipitation, most evident for the month of May and possibly tied to a delayed onset of the wet season. In contrast, there seems to be an increase in the number of wet days during the dry season, especially during November through January. We found that the number of dog days (above 26.7 °C) during the year and during the wet season has increased at many locations. For the post-1950 period, a widespread decrease in the daily temperature range (DTR) is observed mainly because of increased daily minimum temperature (Tmin). Although we did not attempt to formally attribute these trends to natural versus anthropogenic causes, we find that the urban heat island effect is at least partially responsible for the increase in Tmin and its corresponding decrease in DTR at urbanized stations compared with nearby rural stations. In the future, a formal trend attribution study should be conducted for the region. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper presents the new procedure MAC-D for the automated detection of undocumented Multiple Abrupt Changes in the mean value of Daily temperature series, recorded in a network of meteorological stations. MAC-D can be applied to series containing seasonality, multiple change points, outliers, and with a noise component that can be autocorrelated and non-normally distributed. The main novelties of the procedure are (1) the pretreatment of the observed series, to derive a series of daily values that complies with the theoretical requirements of the change point detection tests and in (2) the combined use of the reference series and pairwise comparison approaches. MAC-D consists of three phases in sequence. In phase 1, the seasonal and climatic fluctuations are estimated and removed, using the reference series approach. Phase 2 combines a linear filtering with a change point detection test in an iterative algorithm, which runs until full compliance between the characteristics of the filtered series and the test requirements is achieved. Phase 3 is aimed at removing the false change points, due to error propagation in the reference series analysis, by double checking the detected change points with the pairwise comparison approach. Monte Carlo estimations of the actual significance and overall performance of the procedure for different series features and test resolutions are provided. Results demonstrate that MAC-D performs very well with daily series having a wide range of different characteristics. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Increasing temperatures are likely to impact ectothermic pests of fruits and nuts. This paper aims to assess changes to pest pressure in California's US$0.7 billion walnut industry due to recent historic and projected future temperature changes. For two past (1950 and 2000) and 18 future climate scenarios (2041-2060 and 2080-2099; each for three General Circulation Models and three greenhouse gas emissions scenarios), 100 years of hourly temperature were generated for 205 locations. Degree-day models were used to project mean generation numbers for codling moth ( Cydia pomonella L.), navel orangeworm ( Amyelois transitella Walker), two-spotted spider mite ( Tetranychus urticae Koch), and European red mite ( Panonychus ulmi Koch). In the Central Valley, the number of codling moth generations predicted for degree days accumulated between April 1 and October 1 rose from 2-4 in 1950 to 3-5 among all future scenarios. Generation numbers increased from 10-18 to 14-24 for two-spotted spider mite, from 9-14 to 14-20 for European red mite, and from 2-4 to up to 5 for navel orangeworm. Overall pest pressure can thus be expected to increase substantially. Our study did not include the possibility of higher winter survival rates, leading to higher initial pest counts in spring, or of extended pest development times in the summer, factors that are likely to exacerbate future pest pressure. On the other hand, initiation of diapause may prevent an extension of the season length for arthropods, and higher incidence of heat death in summer may constrain pest population sizes. More information on the impact of climate change on complex agroecological food webs and on the response of pests to high temperatures is needed for improving the reliability of projections. [ABSTRACT FROM AUTHOR]

Trend analysis is an ideal way of investigating first‐hand information about climate change; climate variables exhibit trends on variety of scales, and an understanding of these trends can be used to make estimates about the future of the climate. The objective of this paper is to examine temporal variations in climate by analysing climatic variables. Angul is one of the hottest districts in India, with a maximum summer temperature of 50°C recorded in 2005. Climate data for the period 1901 to 2015 have been statistically analysed to investigate variations in climate in the region. The nonparametric Mann–Kendall rank test, Pearson's correlation, Kendall's rank correlation, analysis of variance (ANOVA) and the autoregressive integrated moving average (ARIMA) model were used to identify diurnal, monthly, seasonal, and annual changes in temperature, precipitation, vapour pressure, potential evapotranspiration and crop evapotranspiration. The results of these analyses reveal the presence of both increasing and decreasing trends for a number of climate variables. Temperature has increased drastically over the last three decades. The average minimum and maximum temperatures for 1901 were 20 and 31°C, respectively; these values increased to 23 and 33°C in 2015. The Auto‐Regressive Integrated Moving Average model projected a significant rise in seasonal temperature and a decreasing trend in rainfall; these results are considered to be an early warning sign for future extreme climate events. Significant changes in climate have been identified through statistical analysis of climate data from 1901 to 2015. A statistically significant positive trend has been identified in the temperature data: the average minimum and maximum temperatures for 1901 are 20 and 31°C, increasing to 23 and 33°C in 2015. Correlation techniques found a negative correlation between rainfall and temperature. Projections made using the ARIMA model predicted significant changes in temperature and rainfall, indicating the possibility of the continued occurrence of extreme climate events such as heatwaves and drought. [ABSTRACT FROM AUTHOR]

In this paper, we present a new approach, based on a mixed model procedure, to quantify the tree-ring-based growth-climate relationship of trembling aspen along a latitudinal gradient from 46 to 54 °N in eastern Canada. This approach allows breaking down the growth response into general intersite and local climatic responses, and analyzing variations of absolute ring width as well as interannual variations in tree growth. The final model also integrates nonclimatic variables such as soil characteristics and the occurrence of insect outbreaks into the growth predictions. Tree level random effects on growth were important as intercepts but were nonsignificant for the climatic variables, indicating that a single climate–growth relationship was justified in our case. The response of tree growth to climate showed, however, a strong dependence on the spatial scale at which the analysis was performed. Intersite variations in tree growth were mostly dependent on variations in the thermal heat sum, a variable that showed low interannual and high intersite variation. When variation for a single site was analyzed, other variables showed up to be important while the heat sum was unimportant. Finally, future growth under six different climate change scenarios was simulated in order to study the potential impact of climate change. Results suggest only moderate growth increases in the northern portion of the gradient and a growth decrease in the southern portion under future climatic conditions. [ABSTRACT FROM AUTHOR]

This paper traces the history of the use of ships' logbooks in climatological studies from the earliest days of the 17th century to the present day. Although early theories concerning global air circulations by Halley and Hadley were based on information gathered by mariners and recorded in their logbooks, it has only been in the last two decades that interest has returned to this important, but long-overlooked, source of climatic information. Attention is drawn to the many advantages offered by logbooks, in particular the long period of time that they collectively cover, their near-global geographic range, the large number of such documents that have survived, and the degree of detailed and reliable record that they provide. Before the mid-19th century, much of the recorded information is noninstrumental in character but its scientific potential is reflected in the variety of approaches and methods that have been used in its analysis and in the equally wide range of outcomes, from databases to synoptic charts and long-time series indices that have emerged from the most recent research. Attention is also drawn to the benefits to be derived from old and more recent instrumental logbook data. As only a small percentage of the tens of thousands of logbooks that have been preserved have thus far been examined, the potential for yet further development is enormous. [ABSTRACT FROM AUTHOR]

Recent studies have shown that ice duration in lakes and rivers over the Northern Hemisphere has decreased over the 19th and 20th centuries in response to global warming. However, lake ice trends have not been well documented in Canada. Because of its size, considerable variability may exist in both freeze‐up and break‐up dates across the country. In this paper, results of the analysis of recent trends (1951–2000) in freeze‐up and break‐up dates across Canada are presented. Trends toward earlier break‐up dates are observed for most lakes during the time periods of analysis which encompass the 1990s. Freeze‐up dates, on the other hand, show few significant trends and a low degree of temporal coherence when compared with break‐up dates. These results are compared with trends in autumn and spring 0 °C isotherm dates over the time period 1966–95. Similar spatial and temporal patterns are observed, with generally significant trends toward earlier springs/break‐up dates over most of western Canada and little change in isotherm and freeze‐up dates over the majority of the country in autumn. Strong correlations (r > 0·5) between 0 °C isotherm dates and freeze‐up/break‐up dates at many locations across the country reveal the high synchrony of these variables. These results are also consistent with more recent observations of other cryospheric and atmospheric variables that indicate, in particular, a general trend toward earlier springs in the latter part of the 20th century. The results of this study provide further evidence of the robustness of lake ice as a proxy indicator of climate variability and change. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The effects of elevated carbon dioxide on plant–herbivore interactions have been summarized in a number of narrative reviews and metaanalyses, while accompanying elevation of temperature has not received sufficient attention. The goal of our study is to search, by means of metaanalysis, for a general pattern in responses of herbivores, and plant characteristics important for herbivores, to simultaneous experimental increase of carbon dioxide and temperature (ECET) in comparison with both ambient conditions and responses to elevated CO2 (EC) and temperature (ET) applied separately. Our database includes 42 papers describing studies of 31 plant species and seven herbivore species. Nitrogen concentration and C/N ratio in plants decreased under both EC and ECET treatments, whereas ET had no significant effect. Concentrations of nonstructural carbohydrates and phenolics increased in EC, decreased in ET and did not change in ECET treatments, whereas terpenes did not respond to EC but increased in both ET and ECET; leaf toughness increased in both EC and ECET. Responses of defensive secondary compounds to treatments differed between woody and green tissues as well as between gymnosperm and angiosperm plants. Insect herbivore performance was adversely affected by EC, favoured by ET, and not modified by ECET. Our analysis allowed to distinguish three types of relationships between CO2 and temperature elevation: (1) responses to EC do not depend on temperature (nitrogen, C/N, leaf toughness, phenolics in angiosperm leaves), (2) responses to EC are mitigated by ET (sugars and starch, terpenes in needles of gymnosperms, insect performance) and (3) effects emerge only under ECET (nitrogen in gymnosperms, and phenolics and terpenes in woody tissues). This result indicates that conclusions of CO2 elevation studies cannot be directly extrapolated to a more realistic climate change scenario. The predicted negative effects of CO2 elevation on herbivores are likely to be mitigated by temperature increase. [ABSTRACT FROM AUTHOR]

The land surface is a key component of climate models. It controls the partitioning of available energy at the surface between sensible and latent heat, and it controls the partitioning of available water between evaporation and runoff. The land surface is also the location of the terrestrial carbon sink. Evidence is increasing that the influence of the land surface is significant on climate and that changes in the land surface can influence regional- to global-scale climate on time scales from days to millennia. Further, there is now a suggestion that the terrestrial carbon sink may decrease as global temperatures increase as a consequence of rising CO2 levels. This paper provides the theoretical background that explains why the land surface should play a central role in climate. It also provides evidence, sourced from climate model experiments, that the land surface is of central importance. This paper then reviews the development of land surface models designed for climate models from the early, very simple models through to recent efforts, which include a coupling of biophysical processes to represent carbon exchange. It is pointed out that significant problems remain to be addressed, including the difficulties in parameterizing hydrological processes, root processes, sub-grid-scale heterogeneity and biogeochemical cycles. It is argued that continued development of land surface models requires more multidisciplinary efforts by scientists with a wide range of skills. However, it is also argued that the framework is now in place within the international community to build and maintain the latest generation of land surface models. Further, there should be considerable optimism that consolidating the recent rapid advances in land surface modelling will enhance our capability to simulate the impacts of land-cover change and the impacts of increasing CO2 on the global and regional environment. Copyright © 2003 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Frost is damaging to plants when air temperature drops below their tolerance threshold. The set of mechanisms used by cold‐tolerant plants to withstand freezing is called "hardening" and typically take place in autumn to protect against winter damage. The recent incorporation of a hardening scheme in the demographic vegetation model FATES opens up the possibility to investigate frost mortality to vegetation. Previously, the hardening scheme was used to improve hydraulic processes in cold‐tolerant plants. In this study, we expand upon the existing hardening scheme by implementing hardiness‐dependent frost mortality into CLM5.0‐FATES to study the impacts of frost on vegetation in temperate and boreal sites from 1950 to 2015. Our results show that the original freezing mortality approach of FATES, where each plant type had a fixed freezing tolerance threshold—an approach common to many other dynamic vegetation models, was restricted to predicting plant type distribution. The main results emerging from the new scheme are a high autumn and spring frost mortality, especially at colder sites, and increasing mid‐winter frost mortality due to global warming, especially at warmer sites. We demonstrate that the new frost scheme is a major step forward in dynamically representing vegetation in ESMs by for the first time including a level of frost tolerance that is responding to the environment and includes some level of cost (implicitly) and benefit. By linking hardening and frost mortality in a land surface model, we open new ways to explore the impact of frost events in the context of global warming. Plain Language Summary: Frost can lead to partial or full mortality of a plant, unless it has evolved a tolerance to cold weather to avoid the formation of ice crystals in its tissues. Frost mortality is poorly represented in most advanced dynamic vegetation models, which are our primary tools for predicting climate change and to understand its effects on the biosphere. In one of those models, the functionally assembled simulator (FATES), a minimum temperature threshold is assigned to each plant type to represent the limit at which it will start to incur frost injury. In this study, we focus on making the fixed temperature threshold of FATES variable in time and space—depending on the local conditions of temperature and light. Our results show that the new frost mortality scheme can simulate autumn and spring frost mortality, also for cold‐adapted species, and increases mid‐winter frost mortality due to variable winter weather—especially at warmer sites. This is in contrast to the original frost mortality scheme, which was only applicable to predict the distribution of plant types across climate zones. The implementation presented here opens up new ways to explore the spatial evolution of frost occurrences and intensities under changing climatic conditions. Key Points: We compare the original freezing mortality implementation in FATES (based on hard‐coded temperature thresholds) to a more dynamic approach (based on hardening)In contrast to the original approach, a new frost scheme is able to predict the damaging effects of extreme winter events and late spring frost eventsWe show that autumn and spring frost mortality is large, especially at colder sites, and that mid‐winter frost mortality increases with global warming [ABSTRACT FROM AUTHOR]

The homogenization of climate observational series is a needed process before undertaking confidently any study of their internal variability, since changes in the observation methods or in the surroundings of the observatories, for instance, can introduce biases in the data of the same order of magnitude than the underlying climate variations and trends. Many methods have been proposed in the past to remove the unwanted perturbations from the climatic series, and some of them have been implemented in software packages freely available on the Internet. The Spanish project MULTITEST was intended to test their performance in an automatic way with synthetic monthly series of air temperature and atmospheric precipitation, to update inter‐comparison results from former projects, especially those of the COST Action ES0601. Several networks representing different climates and station densities were used to test a variety of homogenization packages on hundreds of random samples. Results were evaluated mainly in the form of root mean squared errors and errors in the trend of the series, showing that ACMANT, followed by Climatol, minimized these errors. However, other packages performed also relatively well, even outperforming them when there were simultaneous biases of the same sign in most or all the test series. [ABSTRACT FROM AUTHOR]

Blue carbon ecosystems (BCEs) are important nature‐based solutions for climate change‐mitigation. However, current debates question the reliability and contribution of BCEs under future climatic‐scenarios. The answer to this question depends on ecosystem processes driving carbon‐sequestration and ‐storage, such as primary production and decomposition, and their future rates. We performed a global meta‐analysis on litter decomposition rate constants (k) in BCEs and predicted changes in carbon release from 309 studies. The relationships between k and climatic factors were examined by extracting remote‐sensing data on air temperature, sea‐surface temperature, and precipitation aligning to the decomposition time of each experiment. We constructed global numerical models of litter decomposition to forecast k and carbon release under different scenarios. The current k averages at 27 ± 3 × 10−2 day−1 for macroalgae were higher than for seagrasses (1.7 ± 0.2 × 10−2 day−1), mangroves (1.6 ± 0.1 × 10−2 day−1) and tidal marshes (5.9 ± 0.5 × 10−3 day−1). Macrophyte k increased with both air temperature and precipitation in intertidal BCEs and with sea surface temperature for subtidal seagrasses. Above a temperature threshold for vascular plant litter at ~25°C and ~20°C for macroalgae, k drastically increased with increasing temperature. However, the direct effect of high temperatures on k are obscured by other factors in field experiments compared with laboratory experiments. We defined "fundamental" and "realized" temperature response to explain this effect. Based on relationships for realized temperature response, we predict that proportions of decomposed litter will increase by 0.9%–5% and 4.7%–28.8% by 2100 under low‐ (2°C) and high‐warming conditions (4°C) compared to 2020, respectively. Net litter carbon sinks in BCEs will increase due to higher increase in litter C production than in decomposition by 2100 compared to 2020 under RCP 8.5. We highlight that BCEs will play an increasingly important role in future climate change‐mitigation. Our findings can be leveraged for blue carbon accounting under future climate change scenarios. [ABSTRACT FROM AUTHOR]

The present research focuses on temperature change signals over the Carpathian Basin with a special focus on selected lowland and mountainous subregions. High‐resolution (0.11°) EURO‐ and Med‐CORDEX regional climate model (RCM) simulations of near‐surface air temperature are analysed based on raw and bias‐adjusted data. The mini‐ensemble consists of eight RCM simulations driven by five different general circulation models for the period 1976–2099 under the high‐end RCP8.5 scenario. The high‐resolution, homogenized and quality controlled CARPATCLIM was used as a reference dataset. The selected subregions cover eight municipalities located at diverse altitudes: Bratislava, Budapest, Brassov, Debrecen, Hoverla, Novi Sad, Pécs and Poprad. The following climate indices are assessed: summer days, ice days, frost days, tropical nights, the coldest day, the warmest day, the coldest night and the warmest night. In general, for the reference period (1976–2005) bias‐adjusted RCM data showed almost perfect match with observations. Accordingly, no best performing RCM is found for all indices. The ensemble mean of the bias‐adjusted RCM simulations projects an increase (decrease) of 32% and 112% (18% and 25%) in the annual number of summer days and tropical nights (frost days and ice days) for the period 2021–2050. For 2070–2099 we can expect more frequent tropical nights (about five times) with respect to the reference period and the frequency of frost days can be halved. Profound warming manifests in the increase of the warmest temperature of day of up to 2–3°C by the near future and of 5–7°C by the end of the 21st century, which means the absolute maximum temperature can reach 44–47°C for the period 2070–2099. Our results also highlight the need for bias‐adjusted data adapted by different sectors (human health, agriculture, transport, disaster management, heritage conservation) under the national adaptation strategies. [ABSTRACT FROM AUTHOR]

In the mid‐latitudes, the strongly meandering jet stream has contributed to worldwide weather patterns and climate variations. However, the shape variations of the jet and its climatic impacts remain unclear. In this study, we introduced an ellipse‐fitting technique to fit the high‐value wind speeds and identified the location, shape, and strength variations of the winter‐averaged North Pacific jet (NPJ). Particularly, this method has the advantage of objectively detecting the shape variations of the NPJ, including the area and orientation. Focused on the NPJ shape, the area and orientation variations are generally out‐of‐phase, leading to a large‐straight jet and a small‐tilted jet. The shape variation of the NPJ is highly linked to the variations in both mean and extreme temperatures in winter over East Asia and North America. Associated with the small‐tilted NPJ, northern East Asia and northern North America frequently suffer from warm and cold events in winter, respectively, while associated with the large‐straight NPJ, the patterns are almost opposite but with an asymmetric distribution to the small‐tilted NPJ. The distribution of the 300 hPa wind speed anomalies shows a spatial‐asymmetric feature at the exit and entrance of the NPJ. Large positive (negative) anomalies and the poleward (equatorward) shift at the NPJ exit and locations downstream (170°E−140°W) act in combination on the formation and maintenance of the large‐straight (small‐tilted) jet, which may be strongly connected with the sea surface temperature variations and synoptic‐scale transient eddy activities there. Our findings would be helpful in providing potential indicators of temperature variations. Plain Language Summary: The shape of the upper‐level jet stream is closely associated with weather and climate variations, which is not clearly understood yet. In this study, we introduced an ellipse‐fitting technique to fit high‐value wind speeds and identify the location, shape, and strength variations of the North Pacific jet (NPJ). This method has the advantage of objectively detecting characteristics of the jet stream, particularly for shape variations. The shape variations of the NPJ are closely linked to the variations both in winter mean and extreme temperature, particularly over East Asia and North America. Associated with the small‐tilted NPJ, warm events would more frequently occur in the northern part of East Asia, while cold events would easily affect northern North America. Sea surface temperature anomalies and the increased presence of surface high and low‐pressure systems around the jet exit region may have a strong connection with the different structures of the NPJ. Our findings would be helpful in providing a potential indicator of temperature variations. Key Points: An ellipse‐fitting technique has been introduced to detect the jet stream automatically and objectivelyPrimary combinations of the North Pacific jet's (NPJ's) shape include a large‐straight and small‐tilted jetVariations in the NPJ's shape are highly linked to out‐of‐phase variations in temperature extremes over East Asia and North America [ABSTRACT FROM AUTHOR]