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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]

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]

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In investigating global patterns of biodiversity through deep time, many large-scale drivers of diversification have been proposed, both biotic and abiotic. However, few robust conclusions about these hypothesized effectors or their roles have been drawn. Here, we use a linear stochastic differential equation (SDE) framework to test for the presence of underlying drivers of diversification patterns before examining specific hypothesized drivers. Using a global dataset of observations of skeletonized marine fossils, we infer origination, extinction and sampling rates (collectively called fossil time series) throughout the Phanerozoic using a capture–mark–recapture approach. Using linear SDEs, we then compare models including and excluding hidden (i.e. unmeasured) drivers of these fossil time series. We find evidence of large-scale underlying drivers of marine Phanerozoic diversification rates and present quantitative characterizations of these. We then test whether changing global temperature, sea-level, marine sediment area or continental fragmentation could act as drivers of the fossil time series. We show that it is unlikely any of these four abiotic factors are the hidden drivers we identified, though there is evidence for correlative links between sediment area and origination/extinction rates. Our characterization of the hidden drivers of Phanerozoic diversification and sampling will aid in the search for their ultimate identities. [ABSTRACT FROM AUTHOR]

Maintaining high-quality welded connections is crucial in many industries. One of the challenges is assessing the mechanical properties of a joint during its production phase. Currently, in industrial practice, this occurs through NDT (non-destructive testing) conducted after the production process. This article proposes the use of a virtual sensor, which, based on temperature distributions observed on the joint surface during the welding process, allows for the determination of hardness distribution across the cross-section of a joint. Welding trials were conducted with temperature recording, hardness measurements were taken, and then, neural networks with different hyperparameters were tested and evaluated. As a basis for developing a virtual sensor, LSTM networks were utilized, which can be applied to time series prediction, as in the analyzed case of hardness value sequences across the cross-section of a welded joint. Through the analysis of the obtained results, it was determined that the developed virtual sensor can be applied to predict global temperature changes in the weld area, in terms of both its value and geometry changes, with the mean average error being less than 20 HV (mean for model ~35 HV). However, in its current form, predicting local hardness disturbances resulting from process instabilities and defects is not feasible. [ABSTRACT FROM AUTHOR]

Carbon capture, utilization, and storage (CCUS) is believed to be the most promising technology to mitigate climate change and global temperature rise. As an effective method for reducing carbon emissions, carbon dioxide (CO 2) storage on the seabed can be achieved by injecting captured CO 2 from offshore platforms into subsea storage sites, such as the sediment layers, depleted oil and gas reservoirs and deep saline aquifers, thereby permanently removing it from the atmosphere. Additionally, hundreds to thousands of meters of seawater above seabed storage layers provide naturally high seawater pressure and abundant barrier settings that can reduce leakage risk. Consequently, this has become an ideal storage location for long-term CO 2 storage. In order to thoroughly investigate the mechanism and potential of marine CO 2 storage and promote further development of CCUS, this paper provides a comprehensive description of theoretical research of marine CO 2 geological storage, including storage mechanisms, storage capacity, wellbore flow, CO 2 migration, cap rocks integrity and CO 2 leakage monitoring. The implementation status of global engineering projects is summarized. Currently, there are relatively few successful marine storage projects globally, with the majority of others still in the research and testing stages. Finally, the challenges and prospects of marine CO 2 storage are also discussed. This review demonstrates the enormous potential and promising future of marine CO 2 storage, but there are also leakage risks. It can be avoided through in-depth theoretical research to clarify the entire process of storage mechanisms and take corresponding technological measures. Ultimately, a new technology for large-scale efficient injection and enhanced storage of marine CO 2 storage will be formed. • Marine CO 2 storage has enormous potential and promising prospects. • The flow of CO 2 in the storage reservoir will cause phase change, heat transfer, storage leakage, etc. • Remote monitoring technology can prevent CO 2 leakage. • Storage projects require adequate funding and policy support. [ABSTRACT FROM AUTHOR]

Extreme climate events are hotspots in global change. However, research on the changes in future compound events and population exposure is still limited. Leveraging from the data of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), this paper aims to analyze the temporal and spatial changes of global compound temperature and precipitation extreme events in the future. We also predict the risk of population exposure and quantify the contribution of different factors to exposure. The results show that: (1) In the next 80 years, compound hot-dry event (CHDE) will increase at a rate of 0.02, 0.03, and 0.08 days per decade under the three scenarios of SSP1–2.6, SSP2–4.5 and SSP5–8.5, respectively. By comparison, compound hot-humidity event (CHHE) shows a downward trend under the three scenarios, with a downward rate of 0.01, 0.02, and 0.11 days per decade, respectively. (2) Under the SSP1–2.6 and SSP2–4.5 scenarios, CHDE and CHHE have two or more mutation points. Under the SSP5–8.5 scenario, CHDE shows a significant upward and CHHE shows a significant downward trend in the middle and late 21st century. These two indices exhibit periodic changes in all three scenarios (3) South Asia, West Asia, and Northeast Africa have higher CHDE values, while regions with higher CHHE values are located in North Asia and Greenland. (4) Climate change is a major factor affecting population exposure. For CHDE, climate, population, and their synergistic effects contribute about 75%, 20%, and 5% to the exposure, respectively. For CHHE, the contributions of these three factors are 85%, 10%, and 5% respectively. These findings provide scientific guidance for the rational formulation of population policies, the effective avoidance of climate disaster risks and the protection of human health. • Frequency of hot-dry events and hot-humidity events will increase and decrease, respectively, in the future. • There are abrupt points and periodicity in the future time series of compound temperature and precipitation extremes. • Asia is projected to have the greatest exposure and climate change contributes the most to exposure. [ABSTRACT FROM AUTHOR]

Quantitative constraints on past mean ocean temperature (MOT) critically inform our historical understanding of Earth's energy balance. A recently developed MOT proxy based on paleoatmospheric Xe, Kr, and N2 ratios in ice core air bubbles is a promising tool rooted in the temperature dependences of gas solubilities. However, these inert gases are systematically undersaturated in the modern ocean interior, and it remains unclear how air‐sea disequilibrium may have changed in the past. Here, we carry out 30 tracer‐enabled model simulations under varying circulation, sea ice cover, and wind stress regimes to evaluate air‐sea disequilibrium in the Last Glacial Maximum (LGM) ocean. We find that undersaturation of all three gases was likely reduced, primarily due to strengthened high‐latitude winds, biasing reconstructed MOT by −0.38 ± 0.37°C (1σ). Accounting for air‐sea disequilibrium, paleoatmospheric inert gases indicate that LGM MOT was 2.27 ± 0.46°C (1σ) colder than the pre‐industrial era. Plain Language Summary: The ocean plays a central role in Earth's climate system as a major reservoir of heat. Understanding how ocean heat content (OHC) changed in the past is therefore key to unraveling the history of global climate. Xenon, krypton, and nitrogen trapped in ice core air bubbles offer a means of reconstructing past OHC, because changes in global ocean temperature affect the solubilities of these gases in seawater, leading to corresponding changes in their atmospheric abundances. For example, a colder ocean can hold more xenon, meaning less xenon resides in the atmosphere. However, these gases in the ocean today are slightly out of equilibrium with the atmosphere (i.e., they are undersaturated), and it remains unclear to what extent this disequilibrium could have changed in the past. We carried out global atmosphere‐ocean model simulations, finding that undersaturation was likely reduced in the Last Glacial Maximum (LGM), a colder era of global climate ∼20,000 years ago. Our analysis suggests that a small component of the additional xenon in the colder LGM ocean arose from this change in air‐sea disequilibrium. After accounting for this effect, ice core noble gas measurements suggest a slightly warmer LGM ocean than previously thought. Key Points: Global ocean air‐sea gas exchange simulations suggest reduced undersaturation of inert gases in the Last Glacial Maximum (LGM) oceanReduced LGM undersaturation indicates a small cold bias in mean ocean temperature (MOT) reconstruction from ice core noble gasesA revised estimate of MOT, accounting for air‐sea disequilibrium, is 2.27 ± 0.46°C colder than the pre‐industrial era [ABSTRACT FROM AUTHOR]

Climate change has been a significant threat to sustainable agriculture impacting trade and food security. This research investigates the impacts of climate change on agricultural trade and food security in emerging economies focusing on Southern Africa. The research employed the dynamic panel Generalised Method of Moments (GMM) using panel data for the period 2012 to 2021 obtained from a sample of 12 Southern African countries selected based on data availability. The main independent variables to the research were climate change variables (temperature and precipitation). Other control variables included were population growth, food inflation and agricultural growth. The study found significant negative effects of climate change on agriculture trade. Whilst temperature changes were found to have insignificant effects, precipitation changes were found to have significant positive effects. The research recommends concerted efforts towards climate change adaptation and mitigation for sustainable agriculture. Based on the Findings, sustainable food security and agricultural trade Southern African emerging economies may be attained through effective climate change mitigation and adaptation approaches particularly promoting climate-smart agriculture (CSA). [ABSTRACT FROM AUTHOR]

The Great Plains of North America host a stark climatic gradient, separating the humid and well-watered eastern US from the semi-arid and arid western US, and this gradient shapes the region's water availability, its ecosystems, and its economies. This climatic boundary is largely set by the influence of two competing atmospheric circulation systems that meet over the Great Plains – the wintertime westerlies bring dominantly dry air that gives way to moist, southerly air transported by the Great Plains low-level jet in the warmer months. Climate model simulations suggest that, as CO 2 rises, this low-level jet will strengthen, leading to greater precipitation in the spring but less in the summer and, thus, no change in mean annual precipitation. Combined with rising temperatures that will increase potential evapotranspiration, semi-arid conditions will shift eastward, with potentially large consequences for the ecosystems and inhabitants of the Great Plains. We examine how hydroclimate in the Great Plains varied in the past in response to warmer global climate by studying the paleoclimate record within the Ogallala Formation, which underlies nearly the entire Great Plains and provides a spatially resolved record of hydroclimate during the globally warmer late Miocene. We use the stable isotopes of oxygen (δ18 O) as preserved in authigenic carbonates hosted within the abundant paleosol and fluvial successions that comprise the Ogallala Formation as a record of past hydroclimate. Today, and coincident with the modern aridity gradient, there is a sharp meteoric water δ18 O gradient with high (-6 ‰ to 0 ‰) δ18 O in the southern Great Plains and low (-12 ‰ to -18 ‰) δ18 O in the northern plains. We find that the spatial pattern of reconstructed late Miocene precipitation δ18 O is indistinguishable from the spatial pattern of modern meteoric water δ18 O. We use a recently developed vapor transport model to demonstrate that this δ18 O spatial pattern requires air mass mixing over the Great Plains between dry westerly and moist southerly air masses in the late Miocene – consistent with today. Our results suggest that the spatial extents of these two atmospheric circulation systems have been largely unchanged since the late Miocene and any strengthening of the Great Plains low-level jet in response to warming has been isotopically masked by proportional increases in westerly moisture delivery. Our results hold implications for the sensitivity of Great Plains climate to changes in global temperature and CO 2 and also for our understanding of the processes that drove Ogallala Formation deposition in the late Miocene. [ABSTRACT FROM AUTHOR]

The continued and envisioned large-scale integration of renewable energy sources as a reaction to rising global temperatures and climate change will need a readily available DC grid to increase commissioning and operating efficiency. The effective operation of these grids is predicated on the correct control of its main control points. A plethora of DC-DC converters that find use in DC microgrids act as the main control points. DC-DC converters are non-linear and can operate in different modes with completely unique characteristics. To utilise classical control techniques, laborious equivalent linear models are derived for DC-DC converters using averaging modelling schemes. The application and limitations of these modelling techniques are well captured in the available literature. The most common limitation of the available modelling schemes is that more focus is dedicated to converter attributes like order, functionality and operating mode, even when optimal power flow and voltage regulation within the DC network are of more interest. Structure-based modelling techniques like the use of basic building blocks nullify converter attributes in the modelling process which translates to modelling efficiency. In light of the merits seen with the use of basic building blocks when modelling converters in CCM, the current study extends these merits to converters operation in DCM. Similar to modelling converters in CCM, modelling techniques that are available in the literature continue to consider converter attributes in the modelling process for DCM operation. Moreover, the two modes of operation are treated as unique entities and often modelled in a non-unified manner, which compromise modelling efficiency since the same converter can operate in a different state solely based on loading. The aim is to increase modelling efficiency but also nullify operating mode in the modelling process. The same basic building blocks are now modelled as two-port networks for DCM operation and adopted based on the exact configuration of a specified converter to compute its steady-state and dynamic models. All the advantages seen when modelling converters in CCM using basic building blocks are retained and augmented when considering DCM operation. Thus, any converter with well-defined basic building blocks can be easily modelled solely based on the connection of constituent basic building blocks. [ABSTRACT FROM AUTHOR]

The Fennoscandian boreal and mountain regions harbour a wide range of vegetation types, from boreal forest to high alpine tundra and barren soils. The area is facing a rise in air temperature above the global average and changes in temperature and precipitation patterns. This is expected to alter the Fennoscandian vegetation composition and change the conditions for areal land use such as forestry, tourism and reindeer husbandry. In this study we used a unique high-resolution (3 km) climate scenario with considerable warming resulting from strongly increasing carbon dioxide emissions to investigate how climate change can alter the vegetation composition, biodiversity and availability of suitable reindeer forage. Using a dynamical vegetation model, including a new implementation of potential reindeer grazing, resulted in simulated vegetation maps of unprecedented high resolution for such a long time period and spatial extent. The results were evaluated at the local scale using vegetation inventories and for the whole area against satellite-based vegetation maps. A deeper analysis of vegetation shifts related to statistics of threatened species was performed in six "hotspot" areas containing records of rare and threatened species. In this high-emission scenario, the simulations show dramatic shifts in the vegetation composition, accelerating at the end of the century. Alarmingly, the results suggest the southern mountain alpine region in Sweden will be completely covered by forests at the end of the 21st century, making preservation of many rare and threatened species impossible. In the northern alpine regions, most vegetation types will persist but shift to higher elevations with reduced areal extent, endangering vulnerable species. Simulated potential for reindeer grazing indicates latitudinal differences, with higher potential in the south in the current climate. In the future these differences will diminish, as the potentials will increase in the north, especially for the summer grazing grounds. These combined results suggest significant shifts in vegetation composition over the present century for this scenario, with large implications for nature conservation, reindeer husbandry and forestry. [ABSTRACT FROM AUTHOR]

The temporal relationship between global glaciations and the Great Oxidation Event (GOE) suggests that climate change played an important role in Earth's oxygenation. The potential role of temperature is captured by the stratigraphic proximity between glacial deposits and sediments containing mass‐independent fractionation of sulfur isotopes (MIF‐S). We use a time‐dependent one‐dimensional photochemical model to investigate whether temperature changes associated with global glaciations can drive oscillations in atmospheric O2 levels and MIF‐S production across the GOE. We find that extreme climate change can cause atmospheric O2 to oscillate between pre (<10−6 times the present atmospheric level, PAL) and post‐GOE (>10−5 PAL) levels. Post‐glacial hot‐moist greenhouse climates lead to post‐GOE O2 levels because the abundant H2O vapor and oxidizing radicals drive the depletion of reduced species. This pattern is generally consistent with the MIF‐S signal observed in the sedimentary record, suggesting a link between global glaciations and O2 oscillations across the GOE. Plain Language Summary: The Great Oxidation Event was the most significant environmental and chemical transformation in Earth's history, marking the first time oxygen accumulated in the atmosphere around 2.4 billion years ago. Oxygen increased from below one millionth (low) to at least one‐thousandth of a percent (intermediate) of the present oxygen concentration during this event. However, measurements of geochemical oxygen proxies suggest that oxygen levels oscillated between low and intermediate levels before stabilizing after this event. The first rise of atmospheric oxygen occurred during a period of extreme climate variability indicated by the presence of glacial rock deposits around this time. In this study, we use a time‐dependent photochemical model to show that extreme temperature changes caused by global glaciations can drive oscillations in atmospheric oxygen levels across the Great Oxidation Event (GOE). Our results can help explain why atmospheric oxygen shows drastic changes across the GOE in a way that is consistent with the geochemical record. Key Points: Across the Great Oxidation Event (GOE), extreme climate change linked to global glaciations can drive oscillations in atmospheric O2 levels and mass‐independent fractionation of sulfur isotopes (MIF‐S) productionGlacial climates and hot‐moist greenhouse climates were likely characterized by pre‐GOE and post‐GOE O2 levels respectivelyTemperature changes associated with global glaciations can help explain the MIF‐S record across the GOE [ABSTRACT FROM AUTHOR]

Organisms are experiencing higher average temperatures and greater temperature variability because of anthropogenic climate change. Some populations respond to changes in temperature by shifting their ranges or adjusting their phenotypes via plasticity and/or evolution, while others go extinct. Predicting how populations will respond to temperature changes is challenging because extreme and unpredictable climate changes will exert novel selective pressures. For this reason, there is a need to understand the physiological mechanisms that regulate organismal responses to temperature changes. In vertebrates, glucocorticoid hormones mediate physiological and behavioral responses to environmental stressors and thus are likely to play an important role in how vertebrates respond to global temperature changes. Glucocorticoids have cascading effects that influence the phenotype and fitness of individuals, and some of these effects can be transmitted to offspring via trans- or intergenerational effects. Consequently, glucocorticoid-mediated responses could affect populations and could even be a powerful driver of rapid evolutionary change. Here, we present a conceptual framework that outlines how temperature changes due to global climate change could affect population persistence via glucocorticoid responses within and across generations (via epigenetic modifications). We briefly review glucocorticoid physiology, the interactions between environmental temperatures and glucocorticoid responses, and the phenotypic consequences of glucocorticoid responses within and across generations. We then discuss possible hypotheses for how glucocorticoid-mediated phenotypic effects might impact fitness and population persistence via evolutionary change. Finally, we pose pressing questions to guide future research. Understanding the physiological mechanisms that underpin the responses of vertebrates to elevated temperatures will help predict population-level responses to the changing climates we are experiencing. [ABSTRACT FROM AUTHOR]

Bioenergetics models estimate ectotherm growth, production, and prey consumption – all key for effective ecosystem management during changing global temperatures. Based on species‐specific allometric and thermodynamic relationships, these models typically use the species' lab‐derived optimum temperatures (physiological optimum) as opposed to empirical field data (realized thermal niche) that reflect actual thermal experience. Yet, dynamic behavioral thermoregulation mediated by biotic and abiotic interactions may provide substantial divergence between physiological optimum and realized thermal niche temperatures to significantly bias model outcomes. Here, using the Wisconsin bioenergetics model and in‐situ year‐round temperature data, we tested the two approaches and compared the maximum attainable lifetime weight and lifetime prey consumption estimates for two salmonid species with differing life histories. We demonstrate that using the realized thermal niche is the better approach because it eliminates significant biases in estimates produced by the physiological optimum. Specifically, using the physiological optimum, slower‐growing Salvelinus namaycush maximum attainable lifetime weight was underestimated, and consumption overestimated, while fast‐growing Oncorhynchus tshawytscha maximum attainable weight was overestimated. While the physiological optimum approach is useful for theoretical studies, our results demonstrate the critical importance that models used by management utilize up‐to‐date system‐ and species‐specific field data representing actual in‐situ behaviors (i.e., realized thermal niche). [ABSTRACT FROM AUTHOR]

The Report: Intergovernmental Panel on Climate Change (IPCC) set a goal global warming of 1.5°C on global temperature change. Extreme climate changes have increased the demand for electricity consumption by people and enterprises. In fact, China's total power generation in 2019 exceeded 25% of the world's amount, and its thermal power generation accounted for more than 70%. Although past research on electricity efficiency seldom discusses the issue of climate change, the topic still remains important. This research thus considers extreme temperature days (climate change variable) as exogenous variable and uses the Two-Stage Meta Under exogenous undesirable EBM model to examine power efficiency in China. The results are as follows. (1) In the west only Qinghai's GDP, CO2, PM2.5, and electricity consumption have technology gap ratio (TGR) efficiency values of 1 in the 5 years. (2) China's electricity consumption has the same trend with the TGR efficiency of CO2 and is higher than PM2.5. (3) The national overall efficiency, meta overall efficiency, and TGR overall efficiency are the worst in China's west region. [ABSTRACT FROM AUTHOR]

Urgent emission reduction and community adaptation efforts are necessary to avert catastrophic climate-change harms. To assess our nation's progress toward such efforts, this Article develops a comprehensive structural analysis of U.S. climate policy at the federal, state, and local levels. It observes that current climate policies reflect disparate federal, state, and local strategies around emissions regulation, emission reduction subsidies, adaptation, and liability approaches. The Article then analyzes the dynamics between federal, state, and local strategies in these policy areas. This examination leads to some surprising conclusions. Under current policy alignments, further emission regulation measures do not appear to be realistic policy options. Though such regulatory measures have long been considered the most efficient climate interventions, this analysis suggests they have little near-term prospect for further deployment. Rather, current dynamics among the states and federal government indicate that previously second- and third-choice policies, like subsidies and liability measures, have greater potential for expansion. Thus, these less-favored policy approaches may represent the best hopes for pressing emission reduction efforts. Further, the analysis suggests that while most climate adaptation policy is implemented at the local level, federal adaptation policies require the more immediate attention. Because federal adaptation policies reflect a deferential funding strategy, where the federal government attempts to match support with state and local policy preferences, altering federal programs to better recognize state and local choices will enhance adaptation efforts at all levels of government. [ABSTRACT FROM AUTHOR]

Projections of precipitation extremes over land are crucial for socioeconomic risk assessments, yet model discrepancies limit their application. Here we use a pattern-filtering technique to identify low-frequency changes in individual members of a multimodel ensemble to assess discrepancies across models in the projected pattern and magnitude of change. Specifically, we apply low-frequency component analysis (LFCA) to the intensity and frequency of daily precipitation extremes over land in 21 CMIP-6 models. LFCA brings modest but statistically significant improvements in the agreement between models in the spatial pattern of projected change, particularly in scenarios with weak greenhouse forcing. Moreover, we show that LFCA facilitates a robust identification of the rates at which increasing precipitation extremes scale with global temperature change within individual ensemble members. While these rates approximately match expectations from the Clausius-Clapeyron relation on average across models, individual models exhibit considerable and significant differences. Monte Carlo simulations indicate that these differences contribute to uncertainty in the magnitude of projected change at least as much as differences in the climate sensitivity. Last, we compare these scaling rates with those identified from observational products, demonstrating that virtually all climate models significantly underestimate the rates at which increases in precipitation extremes have scaled with global temperatures historically. Constraining projections with observations therefore amplifies the projected intensification of precipitation extremes as well as reducing the relative error of their distribution. [ABSTRACT FROM AUTHOR]

When the Albanese government was elected, it was widely proclaimed that climate policy was back on track in Australia. Eight bleak years of Coalition denialism and intransigence had been punished [...]

While some degree of competition is present in many authoritarian regimes, the implications of such controlled competition on international issues have not received much consideration, including towards international environmental accords. We attempt to rectify this through a framework where we focus on internal political competition in a hybrid, nondemocratic system where national elections are held regularly. Specifically, we argue that the presence of multiple actors competing in elections in nondemocratic settings results in them assuming positions on various issues, justifying their positions, and attempting to mobilize their supporters with considerable implications for international environmental policies. We display our argument in the context of Iranian debates on the ratification of the Paris Climate Accords. Our findings demonstrate that the competing Iranian sides rely on different justifications for their environmental positions, resulting in extensive (negative) competitions of rhetoric where the international dimension emerges as an important feature in the internal competition. Overall, we show that political competition within non-democracies is likely to add to the complexity of international (environmental) negotiations and cooperation. Keywords: internatonal negotatons on climate change; competng narratves and electons in authoritarian regimes; politcal factons; environment and sanctons; regime survival, Introduction The Paris Climate Change Agreement, a legally binding international treaty that sets goals for temperature increases, was adopted by 196 parties at the United Nations (UN) Climate Change Conference [...]

Honorary Member Mary Glackin Honorary Member John Toohey-Morales Honorary Member Andrea Celeste Saulo The Carl-Gustaf Rossby Research Medal Benjamin Santer For outstanding contributions to comprehending how climate change affects atmospheric [...]

On Earth Day next year, expert judges will decide who should get the biggest incentive prize in history--$80 million for removing at least 1,000 tons of carbon dioxide from the [...]