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Climate change is one of the biggest threats to human living and health in the 21st century. Whilst a large number of papers have been published addressing the health impact of climate change, there is a lack of comprehensive bibliometric analysis in the crosscutting field. This study evaluated the global scientific output of research in the field of climate change and health between 1990 and 2020, based on the Web of Science Core Collection database. Research themes were identified using a social network analysis technique based on author keywords. Research trends were assessed by the change in overall publication number and the percentage of publications in each research theme. Articles were further categorized by the availability of funding and author affiliation to compare the difference between developed and developing countries. Results showed that the research output in the field of climate change and health has increased dramatically in the past 30 years, mainly dominated by researchers in developed countries. The percentage of research receiving funding was found to be the lowest in those published by developing countries only and the highest in those published by the collaboration of developed and developing countries. A total of nine major research themes was identified. Research related to 'risk assessment and adaptation', 'sustainable development' and 'infectious diseases' were relatively underfunded. A significant research trend was observed between 2006 and 2020, with increased attention on research themes related to 'risk assessment and adaptation', 'sustainable development', 'extreme events' and 'air pollution', and reduced attention on research themes related to 'ocean', 'infectious disease' and 'phenology'. The shift of the research trend was mainly driven by research in developed countries. Suggestions, recommendations and future priorities identified by experts in the field of atmospheric sciences, epidemiology, public health, climate change, environmental sciences, and policy development are also provided to guide future research. It is important to shift our focus from single health aspects to an integrated system (such as One Health framework, which considers environmental health, animal health and human health as a whole), with future research focusing more on the systemic impact of climate change in order to achieve better, more effective and efficient risk governance. More funding should be mobilized to support the research capacity building in developing countries and to support climate change adaptation strategies for sustainable development. [ABSTRACT FROM AUTHOR]

The ability of Bayesian networks (BNs) to model complex systems and uncertainties makes it a perfect tool for the research on subfields related to climate change. In fact, in the past 30 years, BNs have been widely used in this field, with 1502 articles in total. Quantitatively understanding influential researchers, institutions, mainstream topics and research trends will help us quickly go deeper into this field. Thus, a scientometric method was conducted. In this paper, we identified the influential authors, journals, countries, institutions, topics and disciplines, key articles and research trends by collaboration network analysis, keyword co-occurrence network and document co-citation network analysis. As a result, we found that environmental sciences technology and water resources were the most popular research subfields, followed by energy fuels and meteorological atmospheric sciences. While as time goes on, research focuses have gradually shifted. Public environmental occupational health will become one of the most popular research subfields in the future. • We review papers of Bayesian networks in the subfields of climate change. • Influential journals, institutions, landmark papers, citation bursts are identified. • Recent topics focus on environmental sciences technology. • Public environmental occupational health will become new hot issues. [ABSTRACT FROM AUTHOR]

For the last 25 years, CO-PDD (Cézeaux-Aulnat-Opme-puy de Dôme) has evolved to become a full instrumented platform for atmospheric research. It has received credentials as a national observing platform in France and is internationally recognized as a global station in the GAW (Global Atmosphere Watch) network. It is a reference site of European and national research infrastructures ACTRIS (Aerosol Cloud and Trace gases Research Infrastructure) and ICOS (Integrated Carbon Observing System). The site located on top of the puy de Dôme mountain (1465 m a.s.l.) is completed by additional sites located at lower altitudes and adding the vertical dimension to the atmospheric observations: Opme (660 m a.s.l.), Cézeaux (410 m), and Aulnat (330 m). The integration of different sites offers a unique combination of in situ and remote sensing measurements capturing and documenting the variability of particulate and gaseous atmospheric composition, but also the optical, biochemical, and physical properties of aerosol particles, clouds, and precipitations. Given its location far away from any major emission sources, its altitude, and the mountain orography, the puy de Dôme station is ideally located to sample different air masses in the boundary layer or in the free troposphere depending on time of day and seasons. It is also an ideal place to study cloud properties with frequent presence of clouds at the top in fall and winter. As a result of the natural conditions prevailing at the site and of the very exhaustive instrumental deployment, scientific studies at the puy de Dôme strongly contribute to improving knowledge in atmospheric sciences, including the characterization of trends and variability, the understanding of complex and interconnected processes (microphysical, chemical, biological, chemical and dynamical), and the provision of reference information for climate/chemistry models. In this context, CO-PDD is a pilot site to conduct instrumental development inside its wind tunnel for testing liquid and ice cloud probes in natural conditions, or in situ systems to collect aerosol and cloud. This paper reviews 25 years (1995–2020) of atmospheric observation at the station and related scientific research contributing to atmospheric and climate science. [ABSTRACT FROM AUTHOR]

For the last twenty-five years, CO-PDD (Cézeaux-Aulnat-Opme-puy de Dôme) has evolved to become a full instrumented platform for atmospheric research. It is nationally accredited by CNRS, the French national center for scientific research, and recognized as a global station in the GAW network (Global Atmospheric Watch). It is a reference site of the European and national research infrastructures ACTRIS (Aerosol Cloud and Trace gases Research Infrastructure) and ICOS (Integrated Carbon Observing System). The site located on-top of the puy de Dôme mountain (1465 m a.s.l.) is completed by additional sites located at lower altitudes and adding the vertical dimension to the atmospheric observations: Opme (660 m a.s.l.), Cézeaux (410 m) and Aulnat (330 m). On the sites has been developed a unique combination of in-situ and remote sensing measurements capturing and documenting the variability of particulate and gaseous atmospheric composition, but also the optical, biochemical and physical properties of aerosol particles, clouds and precipitations. Given its location far away from any major emission sources, its altitude and the mountain orography, the puy de Dôme station is ideally situated to sample different air masses in the boundary layer or in the free troposphere depending on time of day and seasons. It is also an ideal place to study cloud properties with frequent presence of clouds at the top in autumn and winter. As a result of the natural conditions prevailing at the site and of the very exhaustive instrumental deployment, scientific studies at puy de Dôme strongly contribute to improving the knowledge in atmospheric sciences including the characterization of trends and variability, the understanding of complex and interconnected processes (microphysical, chemical, biological, chemical and dynamical) and providing a reference point for climate models. In this context, CO-PDD is a pilot site to conduct instrumental development inside its wind tunnel for testing liquid/ice cloud probes in natural conditions, or in-situ systems to collect aerosol and cloud. This paper reviews 25 years (1995-2020) of atmospheric observation at the station, and related scientific research contributing to atmospheric and climate science. [ABSTRACT FROM AUTHOR]

This paper investigates how former hunter-gatherers living along the southern North Sea coast in NW Europe adapted to long-term and short-term climatic and environmental changes at the beginning of the Holocene. It is argued that contemporaneous hunter-gatherers repeatedly changed their hunting equipment in response to changing climate and environment, not just for functional reasons but mainly driven by socio-territorial considerations. Based on a Bayesian analysis of 122 critically selected radiocarbon dates a broad chronological correlation is demonstrated between rapid changes in the design and technology of stone projectiles and short but abrupt cooling events, occurring at 10.3, 9.3 and 8.2 ka cal BP. Combined with the rapid sea level rises and increased wildfires these climatic events probably impacted the lifeways of hunter-gatherers in such a way that they increasingly faced resource stress and competition, forcing them to invest in the symbolic defense of their social territories. [ABSTRACT FROM AUTHOR]

The National Center for Atmospheric Research (NCAR) operates a state-of-the-art S-band dual-polarization Doppler radar (S-Pol) for the National Science Foundation (NSF). This radar has some similar and some distinguishing characteristics to the National Weather Service (NWS) operational Weather Surveillance Radar-1988 Doppler Polarimetric (WSR-88DP). One key difference is that the WSR-88DP is used for operational purposes where rapid 360° volumetric scanning is required to monitor rapid changes in storm characteristics for nowcasting and issuing severe storm warnings. Since S-Pol is used to support the NSF research community, it usually scans at much slower rates than operational radars. This results in higher resolution and higher data quality suitable for many research studies. An important difference between S-Pol and the WSR-88DP is S-Pol's ability to use customized scan strategies including scanning on vertical surfaces ([range–height indicators (RHIs)], which are presently not done by WSR-88DPs. RHIs provide high-resolution microphysical structures of convective storms, which are central to many research studies. Another important difference is that the WSR-88DP simultaneously transmits horizontal (H) and vertical (V) polarized pulses. In contrast, S-Pol typically transmits alternating H and V pulses, which results in not only higher data quality for research but also allows for the cross-polar signal to be measured. The cross-polar signal provides estimates of the linear depolarization ratio (LDR) and the co- to cross-correlation coefficient that give additional microphysical information. This paper presents plots and interpretations of high-quality, high-resolution polarimetric data that demonstrate the value of S-Pol's polarimetric measurements for atmospheric research. [ABSTRACT FROM AUTHOR]

When comparing climate models to observations, it is often observed that the mean over many models has smaller errors than most or all of the individual models. This paper will show that a general consequence of the nonintuitive geometric properties of high-dimensional spaces is that the ensemble mean often outperforms the individual ensemble members. This also explains why the ensemble mean often has an error that is 30% smaller than the median error of the individual ensemble members. The only assumption that needs to be made is that the observations and the models are independently drawn from the same distribution. An important and relevant property of high-dimensional spaces is that independent random vectors are almost always orthogonal. Furthermore, while the lengths of random vectors are large and almost equal, the ensemble mean is special, as it is located near the otherwise vacant center. The theory is first explained by an analysis of Gaussian- and uniformly distributed vectors in high-dimensional spaces. A subset of 17 models from the CMIP5 multimodel ensemble is then used to demonstrate the validity and robustness of the theory in realistic settings. [ABSTRACT FROM AUTHOR]

There is growing attention that the contrail by aviation may affect the earth's energy balance and climate change. In this paper, we propose a novel approach, the convolutional neural network model termed ContrailMod, which can be used in contrail classification with Himawari-8 stationary satellite and outperforms the representative conventional algorithm contrail detection algorithm (CDA). We estimate the distribution of potential contrail formation using temperature and specific humidity from ECMWF reanalysis (ERA-Interim) in South China region. According to the convolutional neural network identification (CNNI) and artificial visual inspection (AVI), we adopt the contrail occurrence and persistence (COP) measured from Himawari-8 stationary satellite imagery to evaluate the potential contrail coverage (PCC) fractions of the ECMWF reanalysis data. There is a high correlation between contrail occurrence and persistence and potential contrail coverage. The correlation coefficient of convolutional neural network identification is close to artificial visual inspection, which illustrates that the parameterization is reliable by comparing the observation results and the actual reflection of contrail coverage in parameterization calculation of South China region. [ABSTRACT FROM AUTHOR]

Over the 20th century, urbanization has substantially shaped the surface of Earth. With population rapidly shifting from rural locations towards the cities, urban areas have dramatically expanded on a global scale and represent crystallization points of social, cultural and economic assets and activities. This trend is estimated to persist for the next decades, and particularly the developing countries are expected to face rapid urban growth. The management of this growth will require good governance strategies and planning. By threatening the livelihoods, assets and health as foundations of human activities, another major global change contributor, climate change, became an equally important concern of stakeholders. Based on the climate trends observed over the 20th century, and a spatially explicit model of urbanization, this paper investigates the impacts of climate change in relation to different stages of development of urban areas, thus evolving a more integrated perspective on both processes. As a result, an integrative measure of climate change trends and impacts is proposed and estimated for urban areas worldwide. We show that those areas facing major urban growth are to a large extent also hotspots of climate change. Since most of these hotspots are located in the Global South, we emphasize the need for stakeholders to co-manage both drivers of global change. The presented integrative perspective is seen as a starting point to foster such co-management, and furthermore as a means to facilitate communication and knowledge exchange on climate change impacts. [ABSTRACT FROM AUTHOR]

In September 2013 the Intergovernmental Panel on Climate Change published its Working Group 1 report, the first comprehensive assessment of physical climate science in six years, constituting a critical event in the societal debate about climate change. This paper analyses the nature of this debate in one public forum: Twitter. Using statistical methods, tweets were analyzed to discover the hashtags used when people tweeted about the IPCC report, and how Twitter users formed communities around their conversational connections. In short, the paper presents the topics and tweeters at this particular moment in the climate debate. The most used hashtags related to themes of science, geographical location and social issues connected to climate change. Particularly noteworthy were tweets connected to Australian politics, US politics, geoengineering and fracking. Three communities of Twitter users were identified. Researcher coding of Twitter users showed how these varied according to geographical location and whether users were supportive, unsupportive or neutral in their tweets about the IPCC. Overall, users were most likely to converse with users holding similar views. However, qualitative analysis suggested the emergence of a community of Twitter users, predominantly based in the UK, where greater interaction between contrasting views took place. This analysis also illustrated the presence of a campaign by the non-governmental organization Avaaz, aimed at increasing media coverage of the IPCC report. [ABSTRACT FROM AUTHOR]

This paper presents the results of a consensus-driven process identifying 50 priority research questions for historical ecology obtained through crowdsourcing, literature reviews, and in-person workshopping. A deliberative approach was designed to maximize discussion and debate with defined outcomes. Two in-person workshops (in Sweden and Canada) over the course of two years and online discussions were peer facilitated to define specific key questions for historical ecology from anthropological and archaeological perspectives. The aim of this research is to showcase the variety of questions that reflect the broad scope for historical-ecological research trajectories across scientific disciplines. Historical ecology encompasses research concerned with decadal, centennial, and millennial human-environmental interactions, and the consequences that those relationships have in the formation of contemporary landscapes. Six interrelated themes arose from our consensus-building workshop model: (1) climate and environmental change and variability; (2) multi-scalar, multi-disciplinary; (3) biodiversity and community ecology; (4) resource and environmental management and governance; (5) methods and applications; and (6) communication and policy. The 50 questions represented by these themes highlight meaningful trends in historical ecology that distill the field down to three explicit findings. First, historical ecology is fundamentally an applied research program. Second, this program seeks to understand long-term human-environment interactions with a focus on avoiding, mitigating, and reversing adverse ecological effects. Third, historical ecology is part of convergent trends toward transdisciplinary research science, which erodes scientific boundaries between the cultural and natural. [ABSTRACT FROM AUTHOR]

Studies have suggested that the persistence in the meridional vacillation of the midlatitude jet (i.e., annular mode time scale) in comprehensive climate models is related to the model biases in climatological jet latitude, with important implications for projections of future climates and midlatitude weather events. Through the use of the recently developed finite-amplitude wave activity formalism and feedback quantifying techniques, this paper has quantified the role of barotropic and baroclinic eddy feedbacks in annular mode time scales using an idealized dry atmospheric model. The eddy-mean flow interaction that characterizes the persistent anomalous state of the midlatitude jet depends on processes associated with the lower-tropospheric source of vertically propagating Rossby waves, baroclinic mechanisms, and processes associated with upper-tropospheric wave propagation and breaking, barotropic mechanisms. A variety of climate change-like thermal forcings are used to generate a range of meridional shifts in the midlatitude eddy-driven jet. The idealized model shows a reduction in annular mode time scale associated with an increase in jet latitude, similar to comprehensive climate models. This decrease in time scale can be attributed to a similar decrease in the strength of the barotropic eddy feedback, which, in the positive phase of the annular mode, is characterized by anomalous potential vorticity (PV) mixing on the equatorward flank of the climatological jet. The decrease in subtropical PV mixing is, in turn, associated with a stronger subtropical jet as the eddy-driven jet is more distant from the subtropics. These results highlight the importance of subtropical eddy-mean flow interactions for the persistence of an eddy-driven jet. [ABSTRACT FROM AUTHOR]

In previous work, the authors demonstrated how data from climate simulations can be utilized to estimate regional wind power densities. In particular, it was shown that the quality of wind power densities, estimated from the UPSCALE global dataset in offshore regions of Mexico, compared well with regional high resolution studies. Additionally, a link between surface temperature and moist air density in the estimates was presented. UPSCALE is an acronym for UK on PRACE (the Partnership for Advanced Computing in Europe)—weather-resolving Simulations of Climate for globAL Environmental risk. The UPSCALE experiment was performed in 2012 by NCAS (National Centre for Atmospheric Science)-Climate, at the University of Reading and the UK Met Office Hadley Centre. The study included a 25.6-year, five-member ensemble simulation of the HadGEM3 global atmosphere, at 25km resolution for present climate conditions. The initial conditions for the ensemble runs were taken from consecutive days of a test configuration. In the present paper, the emphasis is placed on the single climate run for a potential future climate scenario in the UPSCALE experiment dataset, using the Representation Concentrations Pathways (RCP) 8.5 climate change scenario. Firstly, some tests were performed to ensure that the results using only one instantiation of the current climate dataset are as robust as possible within the constraints of the available data. In order to achieve this, an artificial time series over a longer sampling period was created. Then, it was shown that these longer time series provided almost the same results than the short ones, thus leading to the argument that the short time series is sufficient to capture the climate. Finally, with the confidence that one instantiation is sufficient, the future climate dataset was analysed to provide, for the first time, a projection of future changes in wind power resources using the UPSCALE dataset. It is hoped that this, in turn, will provide some guidance for wind power developers and policy makers to prepare and adapt for climate change impacts on wind energy production. Although offshore locations around Mexico were used as a case study, the dataset is global and hence the methodology presented can be readily applied at any desired location. [ABSTRACT FROM AUTHOR]

The general circulation models used to simulate global climate typically feature resolution too coarse to reproduce many smaller-scale processes, which are crucial to determining the regional responses to climate change. A novel approach to downscale climate change scenarios is presented which includes the interactions between the North Atlantic Ocean and the European shelves as well as their impact on the North Atlantic and European climate. The goal of this paper is to introduce the global ocean-regional atmosphere coupling concept and to show the potential benefits of this model system to simulate present-day climate. A global ocean-sea ice-marine biogeochemistry model (MPIOM/HAMOCC) with regionally high horizontal resolution is coupled to an atmospheric regional model (REMO) and global terrestrial hydrology model (HD) via the OASIS coupler. Moreover, results obtained with ROM using NCEP/NCAR reanalysis and ECHAM5/MPIOM CMIP3 historical simulations as boundary conditions are presented and discussed for the North Atlantic and North European region. The validation of all the model components, i.e., ocean, atmosphere, terrestrial hydrology, and ocean biogeochemistry is performed and discussed. The careful and detailed validation of ROM provides evidence that the proposed model system improves the simulation of many aspects of the regional climate, remarkably the ocean, even though some biases persist in other model components, thus leaving potential for future improvement. We conclude that ROM is a powerful tool to estimate possible impacts of climate change on the regional scale. [ABSTRACT FROM AUTHOR]

In this paper we analyse all currently available simulated climate scenarios, proposed by the Spanish Agency of Meteorology (AEMET), for the period 2010–2040 on the geographical area covered by the Júcar River basin, located in eastern Spain. This is done through the validation of these scenarios using historical records, and by assessing the impact on water resources for the next 30 years by means of a hydrological model. By taking the period 1960–1990 as the control period, a careful comparison of its historical records against AEMET scenarios is performed. Although temperature records are modelled properly, precipitation data are widely underestimated in a range from 8% to 29%. This wide variability observed in the control period is also found in the precipitation scenarios for the period 2010–2040. The impact on water resources shows a great degree of dispersion, ranging from –13.45% to 18.1% with a mean value of –2.13%.Editor Z.W. Kundzewicz; Associate editor F. Hattermann [ABSTRACT FROM AUTHOR]

Planning of mitigation and adaptation strategies to a changing climate can benefit from a good understanding of climate change impacts on human life and local society, which leads to an increasing requirement for reliable projections of future climate change at regional scales. This paper presents an ensemble of high-resolution regional climate simulations for the province of Ontario, Canada, developed with the Providing Regional Climates for Impacts Studies (PRECIS) modeling system. A Bayesian statistical model is proposed through an advance to the method proposed by Tebaldi et al. for generating probabilistic projections of temperature changes at gridpoint scale by treating the unknown quantities of interest as random variables to quantify their uncertainties in a statistical way. Observations for present climate and simulations from the ensemble are fed into the statistical model to derive posterior distributions of all the uncertain quantities through a Markov chain Monte Carlo (MCMC) sampling algorithm. Detailed analyses at 12 selected weather stations are conducted to investigate the practical significance of the proposed statistical model. Following that, maps of projected temperature changes at different probability levels are presented to help understand the spatial patterns across the entire province. The analysis shows that there is likely to be a significant warming trend throughout the twenty-first century. It also suggests that people in Ontario are very likely to suffer a change greater than 2°C to mean temperature in the forthcoming decades and very unlikely to suffer a change greater than 10°C to the end of this century. [ABSTRACT FROM AUTHOR]

This paper summarizes the results of an intercomparison project with Earth System Models of Intermediate Complexity (EMICs) undertaken in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The focus is on long-term climate projections designed to 1) quantify the climate change commitment of different radiative forcing trajectories and 2) explore the extent to which climate change is reversible on human time scales. All commitment simulations follow the four representative concentration pathways (RCPs) and their extensions to year 2300. Most EMICs simulate substantial surface air temperature and thermosteric sea level rise commitment following stabilization of the atmospheric composition at year-2300 levels. The meridional overturning circulation (MOC) is weakened temporarily and recovers to near-preindustrial values in most models for RCPs 2.6-6.0. The MOC weakening is more persistent for RCP8.5. Elimination of anthropogenic CO2 emissions after 2300 results in slowly decreasing atmospheric CO2 concentrations. At year 3000 atmospheric CO2 is still at more than half its year-2300 level in all EMICs for RCPs 4.5-8.5. Surface air temperature remains constant or decreases slightly and thermosteric sea level rise continues for centuries after elimination of CO2 emissions in all EMICs. Restoration of atmospheric CO2 from RCP to preindustrial levels over 100-1000 years requires large artificial removal of CO2 from the atmosphere and does not result in the simultaneous return to preindustrial climate conditions, as surface air temperature and sea level response exhibit a substantial time lag relative to atmospheric CO2. [ABSTRACT FROM AUTHOR]

This paper discusses the distribution of certainty around General Circulation Models (GCMS) - computer models used to project possible global climatic changes due to human emissions of greenhouse gases. It examines the trope of distance underpinning Donald MacKenzie's concept of 'certainty trough', and calls for a more multi-dimensional and dynamic conceptualization of how uncertainty is distributed around technology. The certainty trough describes the level of certainty attached to particular technoscientific constructions as distance increases from the site of knowledge production, and proposes that producers of a given technology and its products are the best judges of their accuracy. Processes and dynamics associated with GCM modeling challenge the simplicity of the certainty trough diagram, mainly because of difficulties with distinguishing between knowledge producers and users, and because GCMs involve multiple sites of production. This case study also challenges the assumption that knowledge producers always are the best judges of the accuracy of their models. Drawing on participant observation and interviews with climate modelers and the atmospheric scientists with whom they interact, the study discusses how modelers, and to some extent knowledge producers in general, are sometimes less able than some users to identify shortcomings of their models. [ABSTRACT FROM AUTHOR]