This article presents and discusses the scientific publication record from 1910 to 2020 on two topics: "climate" (CL) and "climate change/global warming/climate emergency" (CC/GW/CE). The goal is to comparatively visualize how these two distinct publication records have evolved over time, from different classification perspectives, using publication ratios as the key indicator. It is found that research output related to the Earth's contemporary changing climate overtook that of general climate research in 2010, and the publication ratio (CC/GW/CE)/(CL) has been expanding in the last decade. There are significant differences in the publication countries and sources between the two topics. Differentiation factors that affect the level of research output and engagement on the climate challenge include island versus landlocked nations, specialized versus general scientific journals, academic versus institutional organizations. The future of the publication records is discussed, such as the emergence of new terms to refer to the climate challenge, such as "climate emergency".

Although the message of "global climate change" is catalyzing international action, it is local and regional changes that directly affect people and ecosystems and are of immediate concern to scientists, managers, and policy makers. A major barrier preventing informed climate-change adaptation planning is the difficulty accessing, analyzing, and interpreting climate-change information. To address this problem, we developed a powerful, yet easy to use, web-based tool called Climate Wizard (http://ClimateWizard.org) that provides non-climate specialists with simple analyses and innovative graphical depictions for conveying how climate has and is projected to change within specific geographic areas throughout the world.

Climate negotiation outcomes are difficult to evaluate objectively because there are no clear reference scenarios. Subjective assessments from those directly involved in the negotiations are particularly important, as this may influence strategy and future negotiation participation. Here we analyze the perceived success of the climate negotiations in a sample of more than 600 experts involved in international climate policy. Respondents were pessimistic when asked for specific assessments of the current approach centered on voluntary pledges, but were more optimistic when asked for general assessments of the outcomes and usefulness of the climate negotiations. Individuals who are more involved in the negotiation process tended to be more optimistic, especially in terms of general assessments. Our results indicate that two reinforcing effects are at work: a high degree of involvement changes individuals' perceptions and more optimistic individuals are more inclined to remain involved in the negotiations.

Riparian habitats have been frequently identified as priority areas for conservation under climate change because they span climatic gradients and have cool, moist microclimates relative to surrounding areas. They are therefore expected to act as dispersal corridors for climate-induced species range shifts and to provide microclimatic refugia from warming. Despite recognition of these values, rigorous methods to identify which riparian areas are most likely to facilitate range shifts and provide refugia are currently lacking. We completed a novel analysis across the Pacific Northwest, USA, that identifies potential riparian corridors featuring characteristics expected to enhance their ability to facilitate range shifts and provide refugia. These features include large temperature gradients, high canopy cover, large relative width, low exposure to solar radiation, and low levels of human modification. These variables were used to calculate a riparian climate-corridor index using a multi-scale approach that incorporates results ranging in scale from local watersheds to the entire Pacific Northwest. Resulting index values for potential riparian corridors in the Pacific Northwest were highest within mountainous areas and lowest within relatively flat, lowland regions. We also calculated index values within ecoregions, to better identify high-value riparian climate corridors within the relatively flat, degraded areas where they may most contribute to climate adaptation. We found that high-value riparian climate-corridors are least protected in flat, lowland areas, suggesting that such corridors should be high priorities for future conservation effort. Our analysis provides critical information on valuable riparian climate-corridors to guide climate adaptation efforts (and riparian management and restoration efforts) in the Pacific Northwest, while offering a novel approach that may be applied to similar efforts in other geographies.

Uncertainty in climate projections is driven by three components: scenario uncertainty, intermodel uncertainty, and internal variability. Although socioeconomic climate impact studies increasingly take into account the first two components, little attention has been paid to the role of internal variability, although underestimating this uncertainty may lead to underestimating the socioeconomic costs of climate change. Using large ensembles from seven coupled general circulation models with a total of 414 model runs, we partition the climate uncertainty in classic dose-response models relating county-level corn yield, mortality, and per-capita gross domestic product to temperature in the continental United States. The partitioning of uncertainty depends on the time frame of projection, the impact model, and the geographic region. Internal variability represents more than 50% of the total climate uncertainty in certain projections, including mortality projections for the early 21st century, although its relative influence decreases over time. We recommend including uncertainty due to internal variability for many projections of temperature-driven impacts, including early-century and midcentury projections, projections in regions with high internal variability such as the Upper Midwest United States, and impacts driven by nonlinear relationships.

Plants will experience considerable changes in climate within their geographic ranges over the next several decades. They may respond by exhibiting niche flexibility and adapting to changing climates. Alternatively, plant taxa may exhibit climate fidelity, shifting their geographic distributions to track their preferred climates. Here, we examine the responses of plant taxa to changing climates over the past 18,000 y to evaluate the extent to which the 16 dominant plant taxa of North America have exhibited climate fidelity. We find that 75% of plant taxa consistently exhibit climate fidelity over the past 18,000 y, even during the times of most extreme climate change. Of the four taxa that do not consistently exhibit climate fidelity, three-elm (Ulmus), beech (Fagus), and ash (Fraxinus)-experience a long-term shift in their realized climatic niche between the early Holocene and present day. Plant taxa that migrate longer distances better maintain consistent climatic niches across transition periods during times of the most extreme climate change. Today, plant communities with the highest climate fidelity are found in regions with high topographic and microclimate heterogeneity that are expected to exhibit high climate resilience, allowing plants to shift distributions locally and adjust to some amount of climate change. However, once the climate change buffering of the region is exceeded, these plant communities will need to track climates across broader landscapes but be challenged to do so because of the low habitat connectivity of the regions.

Mean annual temperature reported by the Intergovernmental Panel on Climate Change increases at least 1.1°C to 6.4°C over the next 90 years. In context, a change in climate of 6°C is approximately the difference between the mean annual temperature of the Last Glacial Maximum (LGM) and our current warm interglacial. Species have been responding to changing climate throughout Earth's history and their previous biological responses can inform our expectations for future climate change. Here we synthesize geological evidence in the form of stable oxygen isotopes, general circulation paleoclimate models, species' evolutionary relatedness, and species' geographic distributions. We use the stable oxygen isotope record to develop a series of temporally high-resolution paleoclimate reconstructions spanning the Middle Pleistocene to Recent, which we use to map ancestral climatic envelope reconstructions for North American rattlesnakes. A simple linear interpolation between current climate and a general circulation paleoclimate model of the LGM using stable oxygen isotope ratios provides good estimates of paleoclimate at other time periods. We use geologically informed rates of change derived from these reconstructions to predict magnitudes and rates of change in species' suitable habitat over the next century. Our approach to modeling the past suitable habitat of species is general and can be adopted by others. We use multiple lines of evidence of past climate (isotopes and climate models), phylogenetic topology (to correct the models for long-term changes in the suitable habitat of a species), and the fossil record, however sparse, to cross check the models. Our models indicate the annual rate of displacement in a clade of rattlesnakes over the next century will be 2 to 3 orders of magnitude greater (430-2,420 m/yr) than it has been on average for the past 320 ky (2.3 m/yr).

Global climate change impacts on human and natural systems are predicted to be severe, far reaching, and to affect the most physically and economically vulnerable disproportionately. Society can respond to these threats through two strategies: mitigation and adaptation. Industry, commerce, and government play indispensable roles in these actions but so do individuals, if they are receptive to behavior change. We explored whether the health frame can be used as a context to motivate behavioral reductions of greenhouse gas emissions and adaptation measures.

Changing climate will impact species' ranges only when environmental variability directly impacts the demography of local populations. However, measurement of demographic responses to climate change has largely been limited to single species and locations. Here we show that amphibian communities are responsive to climatic variability, using >500,000 time-series observations for 81 species across 86 North American study areas. The effect of climate on local colonization and persistence probabilities varies among eco-regions and depends on local climate, species life-histories, and taxonomic classification. We found that local species richness is most sensitive to changes in water availability during breeding and changes in winter conditions. Based on the relationships we measure, recent changes in climate cannot explain why local species richness of North American amphibians has rapidly declined. However, changing climate does explain why some populations are declining faster than others. Our results provide important insights into how amphibians respond to climate and a general framework for measuring climate impacts on species richness.

Climate change velocity is an increasingly used metric to assess the broad-scale climatic exposure and climate change induced risks to terrestrial and marine ecosystems. However, the utility of this metric in conservation planning can be enhanced by determining the velocities of multiple climatic drivers in real protected area (PA) networks on ecologically relevant scales. Here we investigate the velocities of three key bioclimatic variables across a nation-wide reserve network, and the consequences of including fine-grained topoclimatic data in velocity assessments. Using 50-m resolution data describing present-day and future topoclimates, we assessed the velocities of growing degree days, the mean January temperature and climatic water balance in the Natura 2000 PA network in Finland. The high-velocity areas for the three climate variables differed drastically, indicating contrasting exposure risks in different PAs. The 50-m resolution climate data revealed more realistic estimates of climate velocities and more overlap between the present-day and future climate spaces in the PAs than the 1-km resolution data. Even so, the current temperature conditions were projected to disappear from almost all the studied PAs by the end of this century. Thus, in PA networks with only moderate topographic variation, far-reaching climate change induced ecological changes may be inevitable.

While the Atlantic Meridional Overturning Circulation (AMOC) is projected to slow down under anthropogenic warming, the exact role of the AMOC in future climate change has not been fully quantified. Here, we present a method to stabilize the AMOC intensity in anthropogenic warming experiments by removing fresh water from the subpolar North Atlantic. This method enables us to isolate the AMOC climatic impacts in experiments with a full-physics climate model. Our results show that a weakened AMOC can explain ocean cooling south of Greenland that resembles the North Atlantic warming hole and a reduced Arctic sea ice loss in all seasons with a delay of about 6 years in the emergence of an ice-free Arctic in boreal summer. In the troposphere, a weakened AMOC causes an anomalous cooling band stretching from the lower levels in high latitudes to the upper levels in the tropics and displaces the Northern Hemisphere midlatitude jets poleward.

Cities with a Mediterranean-type climate (Med-cities) are particularly susceptible to health risks from climate change since they are located in biogeographical hot-spots that experience some of the strongest effects of the changing climate. The study aims to highlight health impacts of climate change in Med-cities, analyze local climate adaptation plans and make adaptation policy recommendations for the Med-city level. We identified five Med-cities with a climate change adaptation plan: Adelaide, Barcelona, Cape Town, Los Angeles and Santiago. Beyond their similar Med-climate features (although Santiago's are slightly different), the cities have different socio-economic characteristics in various aspects. We analyzed each plan according to how it addresses climate change-related drivers of health impacts among city dwellers. For each driver, we identified the types of policy adaptation tools that address it in the urban climate adaptation plans. The surveyed cities address most of the fundamental climate change-related drivers of risks to human health, including rising temperatures, flooding and drought, but the policy measures to reduce negative impacts vary across cities. We suggest recommendations for Med-cities in various aspects, depending on their local needs and vulnerability challenges: assessment of health risks, extreme events management and long-term adaptation, among others.

Climate change damages are expected to increase with global warming, which could be limited directly by solar geoengineering. Here we analyse the views of 723 negotiators and scientists involved in international climate policy who will have a significant influence on whether solar geoengineering will be deployed to counter climate change. We find that respondents who expect severe global climate change damages and who have little confidence in current mitigation efforts are more opposed to geoengineering than respondents who are less pessimistic about global damages and mitigation efforts. However, we also find that respondents are more supportive of geoengineering when they expect severe climate change damages in their home country than when they have more optimistic expectations for the home country. Thus, when respondents are more personally affected, their views are closer to what rational cost-benefit analyses predict.

An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one.

Building on achievements and experience gained through the EU project DAMOCLES and international data management during the International Polar Year, ACCESS, data management was implemented using the same platform as used for DAMOCLES. A metadata-driven approach through which all datasets are properly described with discovery and use metadata was chosen in order to simplify data management and data usage. The system provides automated submission and checking of datasets, search and download as well as visualisation and transformation on user demand and metadata export. Long-term management of ACCESS climate datasets is done within the context of the Arctic Data Centre. This ensures visibility of ACCESS datasets in the context of WMO and GEOSS catalogues. Challenges with ACCESS data management have mainly been cultural with the consequence that the system has been underutilised within the duration of the project duration.

Diabetes mellitus, a looming crisis, is approaching worldwide epidemic proportions. In 2018, 34.2 million Americans, or 10.5% of the population had diabetes. Climate change, and in particular rising global temperatures, may exacerbate various health issues, including diabetes and ultimately lead to increased mortality.

Climatology has increasingly become an important discipline for understanding tourism and recreation, especially in the era of contemporary climate change. Climate indices, in this respect, have been useful tools to yield the climatic attractiveness of tourism destinations as well as in understanding their altering suitability to various tourism types along with the changing climates. In this study, a major gap for a comprehensive climate index tailored for ski tourism is aimed to be fulfilled. For this purpose, initially the Ski Climate Index (SCI) is specified, based on fuzzy logic and as informed by literature and through extensive co-creation with the ski tourism industry experts, and applied to an emerging destination, Turkey, based on regional climate modeling projections. The index is designed as a combination of snow reliability and aesthetics and comfort facets, the latter of which includes sunshine, wind, and thermal comfort conditions. Results show that the Eastern Anatolia region is climatically the most suitable area for future development, taking account of the overriding effects of natural and technical snow reliability. Future research suggestions include the incorporation of more components into the index as well as technical recommendations to improve its application and validation.

Changing climate conditions threaten the health and safety of the State of Delaware's most important assets: its workforce. Building on momentum at the state level to assess climate risks and implement relevant adaptation actions, five state agencies implemented the Climate- Ready Workforce Pilot Project to identify and safeguard at-risk workers from the impacts of extreme events such as storms and floods as well as extreme temperatures. Findings indicate that the five participating agencies have an important foundation of worker health and safety policies, procedures and practices. Enhancing their climate resilience will require both strengthening the fundamentals of current policies and procedures by improving processes for policy development, implementation, and enforcement, more explicitly incorporating climate considerations, and sharing agency good practices are key actions.

Surveys are commonly used to quantify public opinions of climate change and to inform sustainability policies. However, conducting large-scale population-based surveys is often a difficult task due to time and resource constraints. This paper outlines a machine learning framework-grounded in statistical learning theory and natural language processing-to augment climate change opinion surveys with social media data. The proposed framework maps social media discourse to climate opinion surveys, allowing for discerning the regionally distinct topics and themes that contribute to climate opinions. The analysis reveals significant regional variation in the emergent social media topics associated with climate opinions. Furthermore, significant correlation is identified between social media discourse and climate attitude. However, the dependencies between topic discussion and climate opinion are not always intuitive and often require augmenting the analysis with a topic's most frequent n-grams and most representative tweets to effectively interpret the relationship. Finally, the paper concludes with a discussion of how these results can be used in the policy framing process to quickly and effectively understand constituents' opinions on critical issues.

Three different methods of specifying ozone in an atmosphere-only version of the HadGEM3-A global circulation model are compared to the coupled chemistry configuration of this model. These methods include a specified zonal-mean ozone climatology, a specified 3-D ozone climatology, and a calculated-asymmetry scheme in which a specified zonal-mean ozone field is adapted online to be consistent with dynamically produced zonal asymmetries. These simulations all use identical boundary conditions and, by construction, have the same climatological zonal-mean ozone, that of the coupled chemistry configuration of the model. Prescribing ozone, regardless of scheme, results in a simulation which is 3-4 times faster than the coupled chemistry-climate model (CCM). Prescribing climatological zonal asymmetries leads to a vortex which is the correct intensity but which is systematically displaced over regions with lower prescribed ozone. When zonal asymmetries in ozone are free to evolve interactively with model dynamics, the modeled wintertime stratospheric vortex shape and mean sea level pressure patterns closely resemble that produced by the full CCM in both hemispheres, in terms of statistically significant differences. Further, we separate out the two distinct pathways by which zonal ozone asymmetries influence modeled dynamics. We present this interactive-ozone zonal-asymmetry scheme as an inexpensive tool for accurately modeling the impacts of dynamically consistent ozone fields as seen in a CCM which ultimately influence mean sea level pressure and tropospheric circulation (particularly during wintertime in the Northern Hemisphere, when ozone asymmetries are generally largest), without the computational burden of simulating interactive chemistry.