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Recent research has indicated high economic and environmental costs of human paper usage. Technologies have been developed to reduce consumers' paper use behavior, including mechanical dispensers that institute a delay between opportunities to obtain each consecutive unit. However, there is no empirical evidence that these dispensers or delays reduce paper use. In Experiment 1, implementing a delay between paper-unit deliveries using mechanical dispensers in a university cafe resulted in a significant decrease in units per person, material per person, and cost per person, compared to free-access dispensers. In Experiment 2, a relatively long delay was more effective than a short delay in reducing paper consumption in a laboratory experiment using mechanical dispensers. These results indicate that delays could be used to decrease paper use in many contexts on a larger scale. More research is necessary to determine the underlying behavioral mechanisms responsible for the observed reduction and the cost-benefit relationship under different circumstances. Keywords Reinforcement delays * Paper dispensers * Sustainability * Climate change * Behavioral nudges, Sustainability is rooted in human behavior, which is controlled by variables that can be manipulated (Baum, 2005; Skinner, 1953; Ylek & Steg, 2007). Verbal strategies (e.g., requests, education, information) to [...]

We thank the authors (hereafter referred to as CCC) for providing us an opportunity to clarify some points of our original paper. CCC list in their abstract three "key points"that we respond to in this Reply. The first comment is the central one and the most developed. It deals mainly with discussion of features of methods of spectral analysis, mainly SSA. We have quoted the sub‐parts of that comment as items 1a to 1k. The replies to comments/key points 2 and 3 are shorter. We disagree with most of the comments by CCC and explain why. We conclude that we have successfully countered CCC's criticism and shown many of their points to be unsubstantiated. The main problem seems to reside in differences concerning the literature on Singular Spectral Analysis and our use of it. Much of our response to the comments can be found in textbooks and review papers on SSA and time series analysis; we quote extensively, both in our original paper and in this response to CCC, Golyandina and Zhigljavsky (2013). Key Points: We find compelling results showing a significant co‐variability between sunspot numbers and global temperature.We do not have a mechanism to explain that forcing: it remains to be found. We do not discuss further the parts of CCC on mechanisms.The trends of temperature and sunspots (first SSA component) are similar; the second component results in an opposite trend in the last 30 years. [ABSTRACT FROM AUTHOR]

The discrepancy between simulated and observed globally averaged monthly atmospheric concentrations of carbon dioxide could be attributed either to deficiencies in the observation network or to inadequacies in the global carbon cycle models. This paper shows that model results could be brought closer to observations by improving model components that describe the seasonal changes in the storage of quickly decaying fractions of litter. [ABSTRACT FROM AUTHOR]

The article focuses on the metrics used for comparing greenhouse gases with focus on the Integrated Temperature Change Potential (IGTP). It states that the IGTP and global warming potentials (GWP) are asymptotically equal is the time horizon reaches infinity. It says that the IGTP is equal to the Sustained Global Temperature change Potential (SGTP) under standard assumptions when calculating GWPs.

The article presents information on a study conducted on a 500 year model simulation of the mid-Pliocene Warm Period (mPWP) by using the Community Climate System Model, version 4 (CCSM4). Results from the CCSM4 mPWP simulation showed a 1.9 Degrees Centigrade increase in global mean annual temperature, along with a polar amplification of nearly three times the global warming.

In recent years, research on climate change and human security has received much attention among policy makers and academia alike. Communities in the Global South that rely on an intact resource base will especially be affected by predicted changes in temperature and precipitation. The objective of this article is to better understand under what conditions local communities can adapt to anticipated impacts of climate change and avoid conflict over the loss of resources. The empirical part of the paper answers the question to what extent local communities in the Chilwa Basin in Malawi have experienced climate change and how they are affected by it. Further, it assesses one of Malawi's adaptation projects designed to build resilience to a warmer and more variable climate, and points to some of its limitations. This research shows that not all adaptation strategies are suited to cope with a warmer and more variable climate. [ABSTRACT FROM AUTHOR]

The article discusses the interpretation and definition of quantities relating to climate sensitivity in the discussions paper "Climate sensitivity in the Anthropocene," by M. Previdi and colleagues. It states that the paper brought several errors and inconsistencies in the discussion of climate sensitivity. It says that definition of temperature which denoted surface temperature was inconsistent.

Iron oxide assemblages are central to many pursuits, ranging from Mars exploration to environmental remediation. Oxides and oxyhydroxides of iron both carry the special properties of color and magnetism. In this paper, we use visible-light spectroscopy and rock magnetic data collected at varying temperatures (~77–973 K) to analyze the concentrations and identities of iron oxides found in natural hematite-dominated samples that were obtained from a scientific drill core of Late Triassic red beds in the American Southwest. Our results suggest that hematite colorization of Earth materials varies from red to blue/purple as crystal size increases. Second-derivative analysis of the collected visible-light spectra allows this variation to be measured through the characteristic wavelength band position. Magnetic coercivity data indicate "hardness" differences that also may suggest smaller grain sizes are associated with redder colors. Yellowish maghemite and goethite have overlapping characteristic wavelength band positions that make it challenging to distinguish their contributions to mixed assemblages from visible-light data alone. Remanent magnetizations acquired at ~77 K and room temperature suggest the presence of hematite and a low-coercivity phase that may be maghemite and/or oxidized magnetite. However, we interpret this phase as maghemite in order to explain the changes in iron oxide concentrations indicated by visible-light intensities near ~425 nm and because the thermal demagnetization data suggest that goethite is absent from the samples. Future research that increases the resolution of hematite, maghemite, and goethite detection in experimental and natural samples will provide opportunities to refine the study of past climates and constrain soil iron availability under future changes in global moisture and temperature. Multimethod datasets improve understanding of environmental conditions that cause iron oxides assemblages to shift in phase dominance, grain size, and crystallinity. [ABSTRACT FROM AUTHOR]

A paradigm is a set of scientific and metaphysical beliefs that provide a theoretical framework within which scientific theories can be tested. Replacement of an existing paradigm by another is called a paradigm shift. Most of the following papers in this issue argue that an alternative paradigm is needed for the functioning of the so-called greenhouse effect of the Earth and hence for the explanation of observed climatic change. Some others contest it. The observed coincidence between global warming and rise of CO2 in the atmosphere over the last century - more accurately measured over the last 30 years of it - need not indicate a causal relationship, and it certainly need not give rise to global catastrophe. An assumed correlation is based on the expectation that the infrared radiation from CO2 contributes significantly to the greenhouse effect of the Earth. However, irregularities in the trends raise doubts of such a simple causal relationship and, at least, considerable doubt about the magnitude of such an expected effect. [ABSTRACT FROM AUTHOR]

Fear of anthropogenic "global warming" can adversely affect patients' well-being. Accordingly, the state of the scientific consensus about climate change was studied by a review of the 539 papers on "global climate change" found on the Web of Science database from January 2004 to mid-February 2007, updating research by Oreskes, who had reported that between 1993 and 2003 none of 928 scientific papers on "global climate change" had rejected the consensus that more than half of the warming of the past 50 years was likely to have been anthropogenic. In the present review, 31 papers (6% of the sample) explicitly or implicitly reject the consensus. Though Oreskes said that 75% of the papers in her former sample endorsed the consensus, fewer than half now endorse it. Only 7% do so explicitly. Only one paper refers to "catastrophic" climate change, but without offering evidence. There appears to be little evidence in the learned journals to justify the climate-change alarm that now harms patients. [ABSTRACT FROM AUTHOR]

Given the potential for elements of the Earth system to undergo rapid, hard to reverse changes in state, there is a pressing need to establish robust methods to produce early warning signals of such events. Here we present a conceptual ecosystem model in which a diversity of stable states emerge, along with rapid changes, referred to as critical transitions, as a consequence of external driving and non-linear ecological dynamics. We are able to produce robust early warning signals that precede critical transitions. However, we show that there is no correlation between the magnitude of the signal and magnitude or reversibility of any individual critical transition. We discuss these findings in the context of ecosystem management prior to and post critical transitions. We argue that an understanding of the dynamics of the systems is necessary both for management prior and post critical transitions and the effective interpretation of any early warning signal that may be produced for that system. [ABSTRACT FROM AUTHOR]

Robust appraisals of climate impacts at different levels of global-mean temperature increase are vital to guide assessments of dangerous anthropogenic interference with the climate system. Currently, two such levels are discussed in the context of the international climate negotiations as long-term global temperature goals: a below 2 °C and a 1.5 °C limit in global-mean temperature rise above pre-industrial levels. Despite the prominence of these two temperature limits, a comprehensive assessment of the differences in climate impacts at these levels is still missing. Here we provide an assessment of key impacts of climate change at warming levels of 1.5 °C and 2 °C, including extreme weather events, water availability, agricultural yields, sea-level rise and risk of coral reef loss. Our results reveal substantial differences in impacts between 1.5 °C and 2 °C. For heat-related extremes, the additional 0.5 °C increase in global-mean temperature marks the difference between events at the upper limit of present-day natural variability and a new climate regime, particularly in tropical regions. Similarly, this warming difference is likely to be decisive for the future of tropical coral reefs. In a scenario with an end-of-century warming of 2 °C, virtually all tropical coral reefs are projected to be at risk of severe degradation due to temperature induced bleaching from 2050 onwards. This fraction is reduced to about 90 % in 2050 and projected to decline to 70 % by 2100 for a 1.5 °C scenario. Analyses of precipitation-related impacts reveal distinct regional differences and several hot-spots of change emerge. Regional reduction in median water availability for the Mediterranean is found to nearly double from 9 to 17 % between 1.5 °C and 2 °C, and the projected lengthening of regional dry spells increases from 7 % longer to 11 %. Projections for agricultural yields differ between crop types as well as world regions. While some (in particular high-latitude) regions may benefit, tropical regions like West Africa, South-East Asia, as well as Central and Northern South America are projected to face local yield reductions, particularly for wheat and maize. Best estimate sea-level rise projections based on two illustrative scenarios indicate a 50 cm rise by 2100 relative to year 2000-levels under a 2 °C warming, which is about 10 cm lower for a 1.5 °C scenario. Our findings highlight the importance of regional differentiation to assess future climate risks as well as different vulnerabilities to incremental increases in global-mean temperature. The article provides a consistent and comprehensive assessment of existing projections and a solid foundation for future work on refining our understanding of warming-level dependent climate impacts. [ABSTRACT FROM AUTHOR]

We formulate and analyze a simple dynamical systems model for climate-vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet, which in turn changes its energy balance and hence the temperature evolution. Our highly idealized, conceptual model is governed by two nonlinear, coupled ordinary differential equations, one for global temperature, the other for vegetation cover. The model exhibits either bistability between a vegetated and a desert state or oscillatory behavior. The oscillations arise through a Hopf bifurcation of the vegetated state, when the death rate of vegetation is low enough. These oscillations are anharmonic and exhibit a sawtooth shape that is characteristic of relaxation oscillations, as well as suggestive of the sharp deglaciations of the Quaternary. Our model's behavior can be compared, on the one hand, with the bistability of even simpler, Daisyworld-style climate-vegetation models. On the other hand, it can be integrated into the hierarchy of models trying to simulate and explain oscillatory behavior in the climate system. Rigorous mathematical results are obtained that link the nature of the feedbacks with the nature and the stability of the solutions. The relevance of model results to climate variability on various time scales is discussed. [ABSTRACT FROM AUTHOR]

The article discusses a study conducted to compare three types of data sets with the Coupled Model Intercomparison Project (CMIP5) climate model simulations to understand similarities or differences between temperature trends in CMIP5 simulations with those from the radiosonde observations, reanalyses and CMIP3 climate simulations. It is stated that data sets are compared between the stratosphere and troposphere as well as between the tropics, Arctic and Antarctic.

Terrestrial ecosystems of northern Eurasia are greening, yet few studies have provided definitive attribution for the changes. While prior studies point to increasing temperatures as the principle environmental control, influences from moisture and other factors are less clear. We assess how changes in temperature, precipitation, cloudiness and forest fires contribute to the trend in Gross Primary Productivity (GPP) derived from satellite data across northern Eurasia. For the period 1982-2008 we find that GPP, estimated using ensemble satellite NDVI (Normalized Difference Vegetation Index) observations from GIMMS3g and VIP datasets, is most sensitive to temperature, precipitation and cloudiness during summer, the peak of the growing season. For regional median GPP, summer temperature explains 33.3% of the variation in GPP, while the other environmental variables explain from 2.2 to 11.8 %. Warming over the period analyzed, even without a sustained increase in precipitation, led to a significant GPP increase over 67.3% of the region. A significant decrease in GPP was found over 6.2% of the region, primarily the dryer grasslands in the south-western. For this area, precipitation positively correlates with GPP, as does cloudiness. This shows that the south-western part of northern Eurasia is relatively more vulnerable to drought than other areas. Our results further advance the notion that air temperature is the dominant environmental control for the recent GPP increases across northern Eurasia. [ABSTRACT FROM AUTHOR]

There are many uncertainties in future climate, including how the Earth may react to different types of radiative forcing, such as CO2, aerosols, and even geoengineered changes in the amount of sunlight absorbed by Earth's surface. Here, we analyze model simulations where the climate system is subjected to an abrupt change of the solar constant by ±4%, and where the atmospheric CO2 concentration is abruptly changed to quadruple and half its preindustrial value. Using these experiments, we examine how clouds respond to changes in solar forcing, compared to CO2, and feedback on global surface temperature. The total cloud response can be decomposed into those responses driven by changes in global surface temperature, called the temperature mediated cloud feedbacks, and responses driven directly by the forcing that are independent of the global surface temperature. In this paper, we study the temperature mediated cloud changes to answer two primary questions: (a) How do temperature mediated cloud feedbacks differ in response to abrupt changes in CO2 and solar forcing? And (b) Are there symmetrical (equal and opposite) temperature mediated cloud feedbacks during global warming and global cooling? We find that temperature mediated cloud feedbacks are similar in response to increasing solar and increasing CO2 forcing, and we provide a short review of recent literature regarding the physical mechanisms responsible for these feedbacks. We also find that cloud responses to warming and cooling are not symmetric, due largely to non‐linearity introduced by phase changes in mid‐to‐high latitude low clouds and sea ice loss/formation. Plain Language Summary: As the global mean temperature changes, there are changes in cloud amount, location, and thickness, which can all impact the radiative balance of the Earth. Cloud changes driven directly by global temperature change are called temperature mediated cloud feedbacks. In this paper, we study the temperature mediated cloud feedbacks that occur in model simulations where the amount of sunlight incident upon the Earth is increased or decreased abruptly, and then held constant for 150 years. We compare the cloud changes in these experiments with experiments where the CO2 concentration is similarly increased or decreased abruptly and held constant for 150 years. In doing so we find that the temperature mediated cloud feedbacks following abrupt changes in solar radiation are characteristically similar to those occurring following CO2 increase. There are however substantial differences in the temperature mediated cloud feedbacks that occur while the climate is warming versus cooling. Key Points: The temperature mediated cloud changes and feedbacks incurred by changes in solar and CO2 forcing are similarOptical depth changes at high latitudes produce substantial differences in cloud feedbacks in cooling and warming experimentsLikewise, tropical circulations respond differently in models to cooling and warming, with a stronger change in the Walker circulation in warming experiments [ABSTRACT FROM AUTHOR]

Copyright of Herald of Journalism / Habaršy Žurnalistika Seriâsy is the property of Al-Farabi Kazakh National University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Earth's climate exhibits internal modes of variability on various time scales. Here we investigate multi-decadal variability of the Atlantic meridional overturning circulation (AMOC) in the control runs of an ensemble of CMIP5 models. By decomposing global- mean-temperature (GMT) variance into contributions of the AMOC and Northern Hemisphere sea-ice extent using a graph-theoretical statistical approach, we find the AMOC to contribute 8% to GMT variability in the ensemble mean. Our results highlight the importance of AMOC sea-ice feedbacks that explain 5% of the GMT variance, while the contribution solely related to the AMOC is found to be about 3 %. As a consequence of multi-decadal AMOC variability, we report substantial variations in North Atlantic deepocean heat content with trends of up to 0.7×1022 J decade-1 that are of the order of observed changes over the last decade and consistent with the reduced GMT warming trend over this period. Although these temperature anomalies are largely density-compensated by salinity changes, we find a robust negative correlation between the AMOC and North Atlantic deep-ocean density with density lagging the AMOC by 5 to 11 yr in most models. While this would in principle allow for a self-sustained oscillatory behavior of the coupled AMOC-deep-ocean system, our results are inconclusive about the role of this feedback in the model ensemble. [ABSTRACT FROM AUTHOR]

Soil organic matter (SOM) is the largest store of organic carbon (C) in the biosphere, but still the turnover of SOM is incompletely understood and not well described in global C cycle models. Here we use the Community Land Model (CLM) and compare the out- put for soil organic C (SOC) to estimates from a global data set. We also modify the assumptions about SOM turnover in two ways: (1) we assume distinct temperature sensitivities of SOC pools with different turnover time and (2) we assume a priming effect, such that decomposition rate of native SOM increases in response to a supply of fresh organic matter. The standard model predicted the global distribution of SOM reasonably well in most areas, but it failed to predict the very high stocks of SOM at high latitudes. It also predicted somewhat too much SOC in areas with high plant productivity, such as tropical rain forests and some mid-latitude areas. Assuming that the temperature sensitivity of SOC decomposition is dependent on the turnover rate of component pools reduced total SOC at equilibrium by a relatively small amount (<1% globally). Including a priming effect reduced total global SOC more (6.6% globally) and tended to decrease SOC most in areas with high plant input (tropical and temperate forests), which were also the areas where the unmodified model overpredicted SOC (by about 40 %). The model was then run with climate change prediction for the standard and modified versions. Future simulations showed that differences between the standard and modified versions were maintained in a future with climate change (4-6 and 23-47 Pg difference in soil carbon between standard simulation and the modified with temperature sensitivity and priming respectively). [ABSTRACT FROM AUTHOR]

The article presents a study which focuses on the use of polar-focused approach to solar radiation management (SRM) to limit the pace of climatic changes in high latitudes. The study used the CAM3.1 atmospheric model coupled to a slab ocean from the National Center for Atmospheric Research. The study shows that green house gas emission is sufficient to limit the warming influence of greenhouse gas concentrations and polar reductions in solar radiation.

Drawing on ecological economics, post-development studies, and political ecology, this paper argues that sustainable development notions have run their course within sustainability marketing debates and proposes degrowth as an alternative framework to steer disciplinary debates in new directions. We chart unexplored territory, offering sustainability marketing scholars tools to navigate degrowth-minded policies, transformative frameworks, and business models. In doing so, our work contributes to existing sustainability marketing debates in three ways: first, we respond to the paucity of studies engaging with the political economy of sustainability marketing. Second, we make visible the tensions and contradictions that arise as marketers seek to reconcile imperatives of economic growth and sustainability. Finally, we foreground degrowth as an emerging sustainability proposition, with potential for inspiring the radical set of transformations required to avert catastrophic climate change and keep global temperatures well below +2°C (relative to pre-industrial levels), as pledged in the Paris Agreement. [ABSTRACT FROM AUTHOR]

Phenology is experiencing dramatic changes over deciduous forests in the US. Estimates of trends in phenology on the continental scale are uncertain, however, with studies failing to agree on both the magnitude and spatial distribution of trends in spring and autumn. This is due to the sparsity of in situ records, uncertainties associated with remote sensing data, and the regional focus of many studies. It has been suggested that reported trends are a result of recent temperature changes, though multiple processes are thought to be involved and the nature of the temperature forcing remains unknown. To date, no study has directly attributed long-term phenological trends to individual forcings across the US through integrating observations with models. Here, we construct an extensive database of ground measurements of phenological events across the US, and use it to calibrate and evaluate a suite of phenology models. The models use variations of the accumulative temperature summation, with additional chilling requirements for spring phenology and photoperiod limitation for autumn. Including a chilling requirement or photoperiod limitation does not improve model performance, suggesting that temperature change, especially in spring and autumn, is the dominant driver of the observed trend during the past 3 decades. Our results show that phenological trends are not uniform over the contiguous US, with a significant advance of 0.34 day yr-1 for the spring budburst in the East, a delay of 0.15 day yr-1 for the autumn dormancy onset in the Northeast and West, but no evidence of change elsewhere. Relative to the 1980s, the growing season in the 2000s is extended by about 1 week (3-4%) in the East, New England, and the upper Rocky Mountains forests. These results help reconcile conflicting reports of phenological trends in the literature, and directly attribute observed trends to long-term changes in temperature. [ABSTRACT FROM AUTHOR]

The article presents a newly composed dataset of climate change scenario to pacify requirements for global assessments of climate change impacts. It is evident that global mean temperature change has become the yardstick to gauze impact of unavoidable climate change and requirement of adaptation. It is informed that the dataset helps in analyzing impact of climate change and implement climate model.

It is often argued that dependence on carbon fuels should be reduced as soon as possible - both for fears of our 'running out' of them and of their impact on global warming. But the ideas of 'peak oil' and 'peak gas' are both myths. Indeed, there is little by way of 'renewable' sources of energy being able to secure more than 40% of total energy requirements in 2100. Thus oil, gas and coal will continue to dominate the world's energy supply for many decades. If need be, the only solution in the event of global warming would be by sequestering the carbon underground. [ABSTRACT FROM AUTHOR]

The article discusses a research study which evaluates a climate simulation through the Global Environmental and Ecological Simulation of Interactive Systems and Modular Ocean Model version 2 (GENMOM). Findings reveal that the said model developed a global temperature bias of 0.6 degree-Celsius. It indicates the development of a split intertropical convergence zone (ITCZ) and weaker-than-observed overturning circulation as the two main weaknesses depicted in the simulations.

Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and may play a key role in biospheric feedback to elevated atmospheric carbon dioxide (CO2) in the warmer future world. We examined seven biome models with climate projections forced by four representative-concentration-pathways (RCPs)-based atmospheric concentration scenarios. The goal was to specify uncertainty in global SOC stock projections from global and regional perspectives. Our simulations showed that SOC stocks among the biome models varied from 1090 to 2650 PgC even in historical periods (ca. 2000). In a higher forcing scenario (RCP8.5), inconsistent estimates of impact on the total SOC (2099-2000) were obtained from different model simulations, ranging from a net sink of 347 PgC to a net source of 122 PgC. In all models, the elevated atmospheric CO2 concentration in the RCP8.5 scenario considerably contributed to carbon accumulation in SOC. However, magnitudes varied from 93 to 264 PgC by the end of the 21st century. Using time-series data of total global SOC estimated by biome biome model, we statistically analyzed the sensitivity of the global SOC stock to global mean temperature and global precipitation anomalies (▵ T and ▵ P respectively) in each biome model using a state-space model. This analysis suggests that ▵ T explained global SOC stock changes in most models with a resolution of 1-2° C, and the magnitude of global SOC decomposition from a 2 °C rise ranged from almost 0 PgCyr-1 to 3.53 PgCyr-1 among the biome models. On the other hand, ▵ P had a negligible impact on change in the global SOC changes. Spatial heterogeneity was evident and inconsistent among the changes in SOC estimated by the biome models, especially in boreal to arctic regions. Our study revealed considerable climate change impact uncertainty in SOC decomposition among biome models. Further research is required to improve our understanding and ability to estimate biospheric feedback through SOC-relevant processes as well as vegetation processes. [ABSTRACT FROM AUTHOR]

The article presents a study which compares the changes in global mean temperature obtained from emission driven Global Climate Model (GCM) in response to various future scenarios. It states GCM simulations models uncertainties in atmospheric feedbacks, ocean physics, and land carbon cycle and aerosol sulphur cycles. It suggests that uncertainty sampling from the emission leads to a wide range of atmospheric concentrations and results of changes in temperature.

The article discusses a research about the use of tree rings in providing information about the amount of snow or rainfall. It references a study by Kerstin Treydte and colleagues published within the issue. They concluded that the latter part of the twentieth century was by far the wettest period, suggesting that humans may play a role in the climate of the world.

Sensor measurement uncertainty has never been fully considered in prior appraisals of global average surface air temperature. The estimated average ±0.2 C station error has been incorrectly assessed as random, and the systematic error from uncontrolled variables has been invariably neglected. The systematic errors in measurements from three ideally sited and maintained temperature sensors are calculated herein. Combined with the ±0.2 C average station error, a representative lower-limit uncertainty of ±0.46 C was found for any global annual surface air temperature anomaly. This ±0.46 C reveals that the global surface air temperature anomaly trend from 1880 through 2000 is statistically indistinguishable from 0 C, and represents a lower limit of calibration uncertainty for climate models and for any prospective physically justifiable proxy reconstruction of paleo-temperature. The rate and magnitude of 20th century warming are thus unknowable, and suggestions of an unprecedented trend in 20th century global air temperature are unsustainable. [ABSTRACT FROM AUTHOR]

Several studies have connected emissions of greenhouse gases to economic and trade data to quantify the causal chain from consumption to emissions and climate change. These studies usually combine data and models originating from different sources, making it difficult to estimate uncertainties in the end results. We estimate uncertainties in economic data, multi-pollutant emission statistics and metric parameters, and use Monte Carlo analysis to quantify contributions to uncertainty and to determine how uncertainty propagates to estimates of global temperature change from regional and sectoral territorial- and consumption-based emissions for the year 2007. We find that the uncertainties are sensitive to the emission allocations, mix of pollutants included, the metric and its time horizon, and the level of aggregation of the results. Uncertainties in the final results are largely dominated by the climate sensitivity and the parameters associated with the warming effects of CO2. The economic data have a relatively small impact on uncertainty at the global and national level, while much higher uncertainties are found at the sectoral level. Our results suggest that consumption-based national emissions are not significantly more uncertain than the corresponding production based emissions, since the largest uncertainties are due to metric and emissions which affect both perspectives equally. The two perspectives exhibit different sectoral uncertainties, due to changes of pollutant compositions. We find global sectoral consumption uncertainties in the range of ±9-±27% using the global temperature potential with a 50 year time horizon, with metric uncertainties dominating. National level uncertainties are similar in both perspectives due to the dominance of CO2 over other pollutants. The consumption emissions of the top 10 emitting regions have a broad uncertainty range of ±9-±25 %, with metric and emissions uncertainties contributing similarly. The Absolute global temperature potential with a 50 year time horizon has much higher uncertainties, with considerable uncertainty overlap for regions and sectors, indicating that the ranking of countries is uncertain. [ABSTRACT FROM AUTHOR]

Instrumental data from the pre–Industrial Revolution period are important to -understand climate change. In this paper, the observations made by the French missionary J. Amiot in present-day central Beijing during 1757–62 were processed and analyzed. The observations represent the earliest continuous dataset of meteorological records found in China that have been digitized recently. Comparisons between the Amiot annual temperature range and extreme values with modern observations showed that the observations were read at approximately 0800 and 1500 local solar time (LST) in a well-ventilated outdoor site. The daily maximum, minimum, and mean temperatures (T-max, T-min, and T-mean, respectively) during 1757–62 were determined by examining the relationship between temperature at 0800 and 1500 LST and T-max, T-min, and T-mean in modern reference series. Nearly 260 years ago, Beijing's climate was typical of an inland temperate monsoon zone with annual T-mean, annual mean T-max, and annual mean T-min being 11.5°, 17.8°, and 6.1°C, respectively; further, the temperatures did not vary considerably from the 1951–1980 temperatures, but differed evidently compared to relatively recent decades (1981–2020). The difference was larger than the magnitudes of global and regional temperature changes. Thus, climate warming since the pre–Industrial Revolution period in the urban areas of Beijing has dominantly occurred over the last four decades. Uncertainties related to the thermometer and observational conditions 260 years ago and the interpolation method used have also been discussed in this paper. [ABSTRACT FROM AUTHOR]

Copyright of Urban Academy/ Kent Akademisi is the property of ICAM NETWORK and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An introduction is presented in which the editor discusses various reports within the issue on topics including the promotion of sustainable development, the implementation of climate policy and the justification of solar geoengineering.

This paper is an introduction to the new package in R called smoots (smoothing time series), developed for data-driven local polynomial smoothing of trend-stationary time series. Functions for data-driven estimation of the first and second derivatives of the trend are also built-in. It is first applied to monthly changes of the global temperature. The quarterly US-GDP series shows that this package can also be well applied to a semiparametric multiplicative component model for non-negative time series via the log-transformation. Furthermore, we introduced a semiparametric Log-GARCH and a semiparametric Log-ACD model, which can be easily estimated by the smoots package. Of course, this package applies to suitable time series from any other research area. The smoots package also provides a useful tool for teaching time series analysis, because many practical time series follow an additive or a multiplicative component model. [ABSTRACT FROM AUTHOR]

The article discusses a study on geologic constraints on Earth system sensitivity (ESS) to carbon dioxide during the Cretaceous and early Paleogene periods. It mentions that the sensitivity has climate policy implications due to anticipated decline of global temperature despite of decrease in anthropogenic greenhouse-gas emissions. It also notes its estimates of 3° Celsius on both periods based on paleo-reconstructions of the gas and temperature.

Understanding seasonal climatic conditions is critical for better management of resources such as water, energy, and agriculture. Recently, there has been a great interest in utilizing the power of Artificial Intelligence (AI) methods in climate studies. This paper presents cutting-edge deep-learning models (UNet++, ResNet, PSPNet, and DeepLabv3) trained by state-of-the-art global CMIP6 models to forecast global temperatures a month ahead using the ERA5 reanalysis dataset. ERA5 dataset was also used for fine-tuning as well performance analysis in the validation dataset. Ten different setups (with CMIP6 and CMIP6 + ERA5 fine-tuning) including six meteorological parameters (i.e., 2 m temperature, 10 m eastward component of wind, 10 m northward component of wind, geopotential height at 500 hPa, mean sea-level pressure, and precipitation flux) and elevation were used with both four different algorithms. For each model 14 different sequential and nonsequential temporal settings were used. The mean absolute error (MAE) analysis revealed that UNet++ with CMIP6 with 2 m temperature + elevation and ERA5 fine-tuning model with “Year 3 Month 2” temporal case provided the best outcome with an MAE of 0.7. Regression analysis over the validation dataset between the ERA5 data values and the corresponding AI model predictions revealed slope and R² values close to 1 suggesting a very good agreement. The AI model predicts significantly better than the mean CMIP6 ensemble between 2016 and 2021. Both models predict the summer months more accurately than the winter months. [ABSTRACT FROM AUTHOR]

The phenomenon of global warming is raising concerns in the U.S. and abroad as scientific studies report that potentially costly climate changes are to take place. For the U.S. in particular, it is expected that the 2008 presidential elections will shift the U.S. approach to global warming. Using externality theory, public goods, and game theory, this paper provides a theoretical, economic analysis of different responses to global warming. It concludes that a science and technology based market strategy is superior to a regulatory approach under the assumptions of a flat social marginal benefit curve and uncertainty about the costs and benefits of pollution reduction. However, the paper argues that an adequate carbon tax or a capand- trade system can stimulate firms to turn to green production, depending on their response to the regulatory regime. [ABSTRACT FROM AUTHOR]

The failure of states to take the necessary actions to prevent global temperatures from soaring may be interpreted as more than an act of environmental negligence. In terms of a knowing imposition of harm, it also represents an act of domination. That is, a deliberate denial of rights to a safe, democratic, and sustainable future. This paper notes the role played by institutional power in preserving this system of domination and in shaping the discursive spaces in which carbon energy options continue to be vigorously defended even in the face of mounting evidence of their danger. Yet as signs of eco-distress grow stronger, so too does a questioning of the legitimacy of this power order. This paper examines how youth employ 'communicative power', as the product of a common will formed in non-coercive communication, to counter this domination and reinterpret climate change as the product of dysfunctional decision-making and 'abnormal' justice relations between generations. It notes the significance of these actors' mobilization efforts to societal processes of learning about democracy's better potentialities and capacities to transform society from within (via law). [ABSTRACT FROM AUTHOR]

Cement is one of the highest energy-consuming and emission generating industries around the world. To reduce greenhouse emissions, several mitigation measures have been proposed, and their effectiveness is estimated. However, estimates of the global temperature change potential of the cement industry have seldom been performed. Hence, in this study, we propose a new framework that estimates CO2 emissions and other seven pollutants to estimate temperature change potential from the cement industry. The underlying framework uses system dynamics, where the effectiveness of four mitigation measures, i.e., a shift in demand, newer methodologies to produce clinker, use of energy efficiency improvements, and implementation of renewable energy, are explored. The results indicate that renewable sources of energy show highest mitigation potential. The cement industry has contributed to an increase in 2 mK temperature since 1990, which is likely to grow up to 14.8 mK by 2050 if no mitigation measures are applied. Energy efficiency improvements by extensions of perform achieve and trade scheme can reduce 0.33 mK from the Indian cement industry. This paper provides a unique opportunity for estimating temperature influence of the cement industry, which can be further implemented for other countries. [ABSTRACT FROM AUTHOR]

An increase in energy demand and consumption is one of the significant challenges of the world community. Global climate change and temperature rise can significantly affect energy demand, especially in the building sector. Green passive design strategies (GPDS) such as green roof and green wall are considered a passive energy-saving technology which can deal with further climate change in near future. This paper compares the energy demand and CO2 emissions of a building with different structural scenarios during the current (2000–2019) and future climatic conditions (the 2050s) in two hot-dry (Kerman) and hot-humid (BandarAbbas) climate samples in Iran. The base case, green roof, and green wall modeling of the selected building have been developed by DesignBuilder software. Results revealed that 61% of the annual energy consumption of Kerman is related to the heating sector, while it will be changed to 47% under the effect of climate change and based on RCP2.6. However, 99% of the annual energy consumption of BandarAbbas belongs to cooling demand and it will not change by 2050s. Also, the maximum heating and cooling energy demand were calculated for the base building. Based on the results, green wall has more efficiency in optimizing total energy consumption compared to green roof in both climate types. On the other hand, GPDS are more efficient to optimize heating energy demand in comparison with cooling energy demand. Furthermore, the green wall strategy has better performance in reducing CO2 emissions as well. Accordingly, CO2 emissions reduce in Kerman by 2.73% and 2.93% by the implementation of the green wall during the observation period and 2050s, respectively. Meanwhile, this strategy can reduce CO2 emissions by only 1% per year in BandarAbbas during all studied periods. [ABSTRACT FROM AUTHOR]

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This short communication discusses the need to transform food systems towards sustainability and focuses on recent political events. Especially the United Nations Food Systems Summit (UNFSS) from 2021 and the respective stocktaking event, which took place in July 2023, are presented and critically analyzed as the process has faced criticism for its lack of transparency, corporate influence, and perceived disregard for human rights frameworks. In this context, the recent UNFSS +2 Stocktaking Moment (STM) in Rome aimed to assess developments in 2021. While over 100 countries presented their progress, many reports focused more on intentions rather than measurable achievements. The outcomes of the STM were perceived as mixed messaging, as no binding agreement or declaration was signed by member states. A major point of criticism is the absence of comparable targets and indicators for tracking and comparing progress across countries, which hinders effective global stocktaking. The paper also underlines the need for universally agreed-upon targets and indicators to provide a clear direction for food systems transformation. It proposes the development of a roadmap with intermediate targets and gradual steps. Alignment with international frameworks such as the Agenda 2030 and the Rio Conventions is also recommended. Collaboration among policymakers, marginalized groups, civil society, scientists, and business leaders is highlighted as being crucial, ensuring inclusive participation and addressing diverse perspectives. Furthermore, the importance of addressing food systems injustices (such as unfair trade practices, exploitative working conditions, and the disproportionate impact of climate change), particularly in Africa, is highlighted. Overall, the paper highlights the challenges and complexities involved in transforming food systems towards sustainability and calls for concerted efforts to address these issues at both global and local levels. Key words: Food systems, Governance, Stock taking, UNFSS, Targets, Africa, INTRODUCTION The term 'food systems' emerged in the 1970s, but the idea to holistically transform food systems towards sustainability gained momentum in the last decade [1, 2]. Calls for transformation [...]

This paper describes a four-step process to guide national governments in formulating and explaining greenhouse gas (GHG) emissions reduction targets in their Nationally Determined Contributions (NDCs) under the Paris Agreement. The NDC pledges in aggregate are intended to achieve the Paris Agreement's warming limit goal to hold the increase in the global temperature to well below 2°C and to pursue efforts to limit the temperature increase to 1.5°C. Nations also agreed in the Paris Agreement that their mitigation pledges would be based on equity and common but differentiated responsibilities and respective capabilities, in the light of different national circumstances. This paper describes the four steps that are required to fulfil these commitments, and to ensure that the NDCs are sufficiently transparent to allow the Paris Agreement's 'stocktake' process and 'transparency mechanism' to achieve their goal of increasing the NDCs' ambition and fairness. The four steps are necessary to implement the legal obligations of the parties under the UNFCCC and the Paris Agreement. These four steps are: (i) Select a global warming limit to be achieved by the GHG emissions reduction target; (2) Identify a global carbon budget consistent with achieving the global warming limit at an acceptable probability; (3) Determine the national fair share of the global carbon budget based upon equity and common but differentiated responsibilities and respective capabilities; and, (4) Specify the annual rate of national GHG emissions reductions on the pathway to net zero emissions. [ABSTRACT FROM AUTHOR]

This paper aims to better understand why there was a global warming pause in 2000–2015 and why the global mean surface temperature (GMST) has risen again in recent years. We present and statistically analyze substantial time-series observed datasets of global lower-stratospheric temperature (GLST), troposphere–stratosphere temperature climatology, global land surface air temperature, GMST, sea ice extent (SIE) and snow cover extent (SCE), combined with modeled calculations of GLSTs and GMSTs. The observed and analyzed results show that GLST/SCE has stabilized since the mid-1990s with no significant change over the past two and a half decades. Upper-stratospheric warming at high latitudes has been observed and GMST or global land surface air temperature has reached a plateau since the mid-2000s with the removal of natural effects. In marked contrast, continued drastic warmings at the coasts of polar regions (particularly Russia and Alaska) are observed and well explained by the sea-ice-loss warming amplification mechanism. The calculated GMSTs by the parameter-free quantum-physics warming model of halogenated greenhouse gases (GHGs) show excellent agreement with the observed GMSTs after the natural El Niño southern oscillation and volcanic effects are removed. These results have provided strong evidence for the dominant warming mechanism of anthropogenic halogenated GHGs. The results also call for closer scrutiny of the assumptions made in current climate models. [ABSTRACT FROM AUTHOR]

This paper documents the experimental setup and general features of the coupled historical and future climate simulations with the first version of the US Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv1.0). The future projected climate characteristics of E3SMv1.0 at the highest emission scenario (SSP5-8.5) designed in the Scenario Model Intercomparison Project (ScenarioMIP) and the SSP5-8.5 greenhouse gas (GHG) only forcing experiment are analyzed with a focus on regional responses of atmosphere, ocean, sea ice, and land. Due to its high equilibrium climate sensitivity (ECS of 5.3 K), E3SMv1.0 is one of the Coupled Model Intercomparison Project phase 6 (CMIP6) models with the largest surface warming by the end of the 21st century under the high-emission SSP5-8.5 scenario. The global mean precipitation change is highly correlated with the global temperature change, while the spatial pattern of the change in runoff is consistent with the precipitation changes. The oceanic mixed layer generally shoals throughout the global ocean. The annual mean Atlantic meridional overturning circulation (AMOC) is overly weak with a slower change from ∼11 to ∼6 Sv (Sverdrup) relative to other CMIP6 models. The sea ice, especially in the Northern Hemisphere, decreases rapidly with large seasonal variability. We detect a significant polar amplification in E3SMv1.0 from the atmosphere, ocean, and sea ice. Comparing the SSP5-8.5 all-forcing experiment with the GHG-only experiment, we find that the unmasking of the aerosol effects due to the decline of the aerosol loading in the future projection period causes transient accelerated warming in the all-forcing experiment in the first half of the 21st century. While the oceanic climate response is mainly controlled by the GHG forcing, the land runoff response is impacted primarily by forcings other than GHG over certain regions, e.g., southern North America, southern Africa, central Africa, and eastern Asia. However, the importance of the GHG forcing on the land runoff changes grows in the future climate projection period compared to the historical period. [ABSTRACT FROM AUTHOR]

Over the last century, the global mean surface air temperature (SAT) has experienced two periods of warming slowdown (hiatuses), namely 1940–1975 and 1998–2012, as well as showing well-defined interdecadal oscillations. Previous studies have focused mainly on the most recent hiatus, and little is known about the period between 1940 and 1975. From the point of view of the sea surface temperature (SST), there are two aspects of interest; i.e., the climatological SST and SST variability. In this paper, observational and modelling evidence is used to show that, compared with the climatological SST, SST variability has been the main cause of the slowdown in rate of increase in SAT since 1940. In addition, the observational data and simulation results show that SST variability had a greater impact on the slowdown in rate of increase in SAT from 1940 to 1975 (− 1.2 × 10−3 °C/year) than from 1998 to 2012 (− 5.7 × 10−3 °C/year). The SAT change over the period 1940–1975 (1.0 × 10−4 °C/year) was less affected by the climatological SST forcing experiment than that over the period 1998–2012 (− 5.0 × 10−4 °C/year). Comparing with 1940–1975, the SAT change over the period 1998–2012 was much affected by the global SAT long-term warming. The distributions of wind stress and atmospheric pressure both indicate that, although the eastern Pacific Ocean played an important role in influencing the global SAT trend between 1998 and 2012, it made little contribution to changes in global SAT between 1940 and 1975. In addition, from the perspective of seasonality, the interdecadal variation of SAT over these two periods was a seasonally dependent phenomenon. Over the period 1940–1975, the annual SAT trend essentially followed the summer SAT trend, whereas between 1998 and 2012, winter was the dominant season of annual SAT change. [ABSTRACT FROM AUTHOR]