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The STatistical Analogue Resampling Scheme (STARS) statistical approach was recently used to project changes of climate variables in Germany corresponding to a supposed degree of warming. We show by theoretical and empirical analysis that STARS simply transforms interannual gradients between warmer and cooler seasons into climate trends. According to STARS projections, summers in Germany will inevitably become dryer and winters wetter under global warming. Due to the dominance of negative interannual correlations between precipitation and temperature during the year, STARS has a tendency to generate a net annual decrease in precipitation under mean German conditions. Furthermore, according to STARS, the annual level of global radiation would increase in Germany. STARS can be still used, e.g., for generating scenarios in vulnerability and uncertainty studies. However, it is not suitable as a climate downscaling tool to access risks following from changing climate for a finer than general circulation model (GCM) spatial scale. [ABSTRACT FROM AUTHOR]

Among papers stating a position on anthropogenic global warming (AGW), 97 % endorse AGW. What is happening with the 2 % of papers that reject AGW? We examine a selection of papers rejecting AGW. An analytical tool has been developed to replicate and test the results and methods used in these studies; our replication reveals a number of methodological flaws, and a pattern of common mistakes emerges that is not visible when looking at single isolated cases. Thus, real-life scientific disputes in some cases can be resolved, and we can learn from mistakes. A common denominator seems to be missing contextual information or ignoring information that does not fit the conclusions, be it other relevant work or related geophysical data. In many cases, shortcomings are due to insufficient model evaluation, leading to results that are not universally valid but rather are an artifact of a particular experimental setup. Other typical weaknesses include false dichotomies, inappropriate statistical methods, or basing conclusions on misconceived or incomplete physics. We also argue that science is never settled and that both mainstream and contrarian papers must be subject to sustained scrutiny. The merit of replication is highlighted and we discuss how the quality of the scientific literature may benefit from replication. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of future precipitation patterns over the Lake Victoria Basin, East Africa, using bias-corrected CMIP6 model projections. A mean increase of about 5% in mean annual (ANN) and seasonal [March–May (MAM), June–August (JJA), and October–December (OND)] precipitation climatology is expected over the domain by mid-century (2040–2069). The changes intensify towards the end of the century (2070–2099) with an increase in mean precipitation of about 16% (ANN), 10% (MAM), and 18% (OND) expected, relative to the 1985–2014 baseline period. Additionally, the mean daily precipitation intensity (SDII), the maximum 5-day precipitation values (RX5Day), and the heavy precipitation events—represented by the width of the right tail distribution of precipitation (99p–90p)—show an increase of 16%, 29%, and 47%, respectively, by the end of the century. The projected changes have a substantial implication for the region—which is already experiencing conflicts over water and water-related resources. [ABSTRACT FROM AUTHOR]

Though a small fraction of the US citizenry, agricultural producers are directly responsible for the stewardship of almost half of the country's land. This group is therefore an especially important one to understand from the standpoint of how they process and respond to science as it relates to agroecological phenomena. Data from a sample (n = 111) of farmers and ranchers located in the US state of Colorado are used to expand our understanding of how food producers process scientific claims. These insights, I argue, help us think through public understandings of science more generally. Using semi-structured interviews, the paper unpacks an identified asymmetry in how respondents perceive climate science and the science associated with genetically modified food and seed. These tensions are interrogated with the help of a novel methodological design that generated data converted to shading matrices—also known as heat maps. The heat maps illuminate certain cultural values among respondents, which were reinforced by motivated reasoning. This allows for an interrogation of tensions and inconsistencies in respondents' remarks about a variety of scientific claims. The heat maps, coupled with the qualitative data, allow for an exploration into how respondents perceive certain salient socio-technical issues. [ABSTRACT FROM AUTHOR]

The public education system can play a pivotal role in creating an electorate that is well informed of the consensus around climate change and its anthropogenic causes. In particular, more states have education standards that specifically address climate change today than ever before. However, previous research raises concerns about the discretion teachers have in if and how particular types of content are presented. The effectiveness of new state standards and the extent to which such state-level standards are coopted by teacher discretion has received minimal attention. Therefore, using a nationally representative sample of 1500 middle school and high school science teachers, this research examines the effectiveness of such state-level standards and the extent to which teacher ideology and knowledge mediate the relationship between standards and actual use of a consensus-informed approach to teaching climate science. Results show that teachers in states with any type of standards around climate change spend significantly more time on the topic in the classroom. However, teachers in states that have standards that require teachers to present "both sides" of climate change are significantly less likely to use a consensus-informed approach. While teacher characteristics (knowledge and ideology) can weaken their effect, standards continue to be important predictors of the time spent on climate change in the classroom and how content is presented. The paper concludes with a discussion of the policy implications of climate science standards. [ABSTRACT FROM AUTHOR]

Mesoscale convective systems (MCSs) are important warm-season precipitation systems in eastern China. However, our knowledge of their climatology and capability in their simulation is still insufficient. This paper examines their characteristics over the 2008–2017 warm seasons using convection-permitting climate simulations (CPCSs) with a 3-km grid spacing that explicitly resolves MCSs, as well as a high-resolution gauge-satellite merged precipitation product. An object-based tracking algorithm is applied to identify MCSs. Results indicate that the MCS genesis and occurrence are closely related to the progression of the East Asian monsoon and are modulated by the underlying topography. On average, about 243 MCSs are observed each season and contribute 19% and 47% to total and extreme warm-season precipitation. The climatological attributes and variabilities are reasonably reproduced in the CPCS. The major model deficiencies are excessive small MCS occurrence and overmuch MCS rainfall, consequently overestimating the precipitation contributions, whereas observational uncertainties may play a role too. Both the observed and simulated MCS precipitation feature a nocturnal or morning maximum and an eastward delayed diurnal peak east of the Tibetan Plateau, in contrast to the dominant afternoon peak of non-MCS precipitation. The favorable comparison with observations demonstrates the capability of CPCSs in simulating MCSs in the Asian monsoon climate, and its usefulness in projecting the future changes of MCSs under global warming. The finding that non-MCS precipitation is responsible for the high biased afternoon precipitation provides helpful guidance for further model improvement. [ABSTRACT FROM AUTHOR]

As global warming intensifies, efforts to understand the changes in extreme climate events have increased in recent years. A combined analysis of the changes in extreme temperature and precipitation events is presented in this paper. Using observational data from 1961 to 2015, a set of hotter and wetter (HW) events is defined, and we examine the changes in these events across China. The results show that more HW events occur in Central and Eastern China than in other subregions, especially in South China (SC). The rate of increase in HW events is 2.7 and 1.9 per decade in SC and East China (EC), respectively. In China, most HW events occurred in the last 20 years of the study period, indicating that China entered a period of high-frequency HW events. Indeed, the range in anomalies in the torrential rain days is greater than that of the high-temperature days in Northwest China (NWC), Central China (CC), and EC after the mid- to late 1990s. The opposite pattern is found in Northeast China (NEC), Southwest China-region 1 (SWC1), Southwest China-region 2 (SWC2), and SC. Finally, the increase in HW events in most regions of China is closely associated with warming. [ABSTRACT FROM AUTHOR]

Climate feedback mechanisms that have the potential to intensify global warming have been omitted almost completely in the integrated assessment of climate change and the economy so far. In the present paper, we incorporate the permafrost carbon feedback (PCF) into the well-known integrated assessment model DICE-2013R. We calibrate the parameters for our extended version of DICE-2013R and compute the optimal emission mitigation rates that maximize welfare. Our results indicate that accounting for the PCF leads to an increase in mitigation. Finally, we quantify the economic losses resulting from a climate policy which ignores the impacts of the PCF. [ABSTRACT FROM AUTHOR]

The snow cover extent in mid-high latitude areas of the Northern Hemisphere has significantly declined corresponding to the global warming, especially since the 1970s. Snow-climate feedbacks play a critical role in regulating the global radiation balance and influencing surface heat flux exchange. However, the degree to which snow cover changes affect the radiation budget and energy balance on a regional scale and the difference between snow-climate and land use/cover change (LUCC)-climate feedbacks have been rarely studied. In this paper, we selected Heilongjiang Basin, where the snow cover has changed obviously, as our study area and used the WRF model to simulate the influences of snow cover changes on the surface radiation budget and heat balance. In the scenario simulation, the localized surface parameter data improved the accuracy by 10 % compared with the control group. The spatial and temporal analysis of the surface variables showed that the net surface radiation, sensible heat flux, Bowen ratio, temperature and percentage of snow cover were negatively correlated and that the ground heat flux and latent heat flux were positively correlated with the percentage of snow cover. The spatial analysis also showed that a significant relationship existed between the surface variables and land cover types, which was not obviously as that for snow cover changes. Finally, six typical study areas were selected to quantitatively analyse the influence of land cover types beneath the snow cover on heat absorption and transfer, which showed that when the land was snow covered, the conversion of forest to farmland can dramatically influence the net radiation and other surface variables, whereas the snow-free land showed significantly reduced influence. Furthermore, compared with typical land cover changes, e.g., the conversion of forest into farmland, the influence of snow cover changes on net radiation and sensible heat flux were 60 % higher than that of land cover changes, indicating the importance of snow cover changes in the surface-atmospheric feedback system. [ABSTRACT FROM AUTHOR]

Mitigation and adaptation represent two solutions to the issue of global warming. While mitigation aims at reducing $$\hbox {CO}_2$$ emissions and preventing climate change, adaptation encompasses a broad scope of techniques used to reduce the impacts of climate change once they have occurred. Both have direct costs on a country's gross domestic product, but costs also arise from temperature increases due to inaction. This paper introduces a tipping point in a real options model and analyzes optimal investment choices in mitigation and their timing. [ABSTRACT FROM AUTHOR]

Finance ministries are increasingly involved in UN climate finance negotiations, yet this development received very limited attention in the literature on climate finance or climate negotiations. It is not obvious from the literature on bureaucratic politics how these ministries will position themselves on climate finance: they may frame climate finance as expenditure to be limited or as an instrument for correcting the market failure of climate change. This paper investigates which frames have characterised the positions of finance ministries on key issues in the climate finance negotiations, and whether the use of a given frame corresponds to particular factors. Case studies of Denmark, India, Indonesia and the USA based on official documents and interviews show that the position of each finance ministry is generally consistent with one particular frame. The Indonesian and Danish finance ministries predominantly framed climate finance as a way of correcting a market failure. The Indian Ministry of Finance emphasised Common but Differentiated Responsibilities, which fits with the budget frame. The US Treasury's position similarly fits with the budget frame while sharing elements of the market failure frame. Finance ministries that had the lead on climate finance were more likely follow the budget frame. The use of both frames cuts across the divide between industrialised and emerging economies. With the exception of the USA, left- and right-wing governments were equally likely to adopt either frame. These findings indicate that strengthening finance ministry forums built around the market failure frame can be a way of reducing norm fragmentation. [ABSTRACT FROM AUTHOR]

The global warming potential (GWP) is widely used in policy analysis, national greenhouse gas (GHG) accounting, and technology life cycle assessment (LCA) to compare the impact of non-CO2 GHG emissions to the impact of CO2 emissions. While the GWP is simple and versatile, different views about the appropriate choice of time horizon—and the factors that affect that choice—can impede decision-making. If the GWP is viewed as an approximation to a climate metric that more directly measures economic impact—the global damage potential (GDP)—then the time horizon may be viewed as a proxy for the discount rate. However, the validity of this equivalence rests on the theoretical basis used to equate the two metrics. In this paper, we develop a new theoretical basis for relating the GWP time horizon and the economic discount rate that avoids the most restrictive assumptions of prior studies, such as an assumed linear relationship between economic damages and temperature. We validate this approach with an extensive set of numerical experiments using an up-to-date climate emulator that represents state-dependent climate-carbon cycle feedbacks. The numerical results largely confirm the theoretical finding that, under certain reasonable assumptions, time horizons in the GWP of 100 years and 20 years are most consistent with discount rates of approximately 3% and 7% (or greater), respectively. [ABSTRACT FROM AUTHOR]

Geoengineering is defined as the 'deliberate and large-scale intervention in the Earth's climatic system with the aim of reducing global warming'. The technological proposals for doing this are highly speculative. Research is at an early stage, but there is a strong consensus that technologies would, if realisable, have profound and surprising ramifications. Geoengineering would seem to be an archetype of technology as social experiment, blurring lines that separate research from deployment and scientific knowledge from technological artefacts. Looking into the experimental systems of geoengineering, we can see the negotiation of what is known and unknown. The paper argues that, in renegotiating such systems, we can approach a new mode of governance-collective experimentation. This has important ramifications not just for how we imagine future geoengineering technologies, but also for how we govern geoengineering experiments currently under discussion. [ABSTRACT FROM AUTHOR]

This paper examines farm household-level impacts of climate change by examining the relationship between climatic variables and Vietnamese agricultural output. The Ricardian technique is applied with panel data which accounts for both adaptation strategies and household characteristics. This study proposes a two-stage Hsiao model to correct for collinearity between climatic variables and individual effects. The results show that in the dry season, increases in temperatures are beneficial to all farms in the warmer southern regions, while increases in precipitation will damage only irrigated farms in the Central and South regions. The impact of higher temperature in the wet season is similar, except that it will negatively affect net revenue of irrigated farms in the long run. More rainfall in the wet season will increase net revenue in the North region only. Finally, this study combines the estimated results with future climate scenarios to predict how future changes in climate will affect farmers on aggregate. [ABSTRACT FROM AUTHOR]

Tropical glaciers are extremely sensitive to a warming climate. In this paper, the evolution of the remaining tropical glaciers in Australasia (Irian Jaya, Indonesia) during the period 1988-2015 was quantified. Landsat series images, a digital elevation model from SRTM, and previously published data were used. Estimated total glacier area in 1988, 1993, 1997 and 2004 was 3.85 km2±0.13 km2, 3.01 km2±0.08 km2, 2.49 km2±0.07 km2 and 1.725 km2 ±0.042 km2, respectively. Only 0.58 km2±0.016 km2 glacierized area remained in 2015 in Puncak Jaya, which is about 84.9% loss in just 27 years. If this rate continued, the remaining tropical glaciers in Australasia would disappear in the 2020s. Timeseries analysis of climate variables showed significant positive trends in air temperature (0.009°C per year) and relative humidity (0.43% per year) but no considerable tendency was observed for precipitation. Warming climate together with mining activities would accelerate loss of glacier coverage in this region. [ABSTRACT FROM AUTHOR]

This research has developed mathematical models for computing lifetime greenhouse gas (GHG) emissions associated with materials. The models include embodied carbon (EC) emissions from the manufacture of materials, and GHG emissions from incineration, or landfill gas (LFG) production from landfill disposal of the material beyond their service lives. The models are applicable to all materials; however, their applications here are demonstrated for the lumber from a residential building with 50- and 100-year service lives, and with incineration, landfill, and deconstruction as end-of-life treatments. This paper introduces a new metric for lifetime GHG emissions associated with materials termed "Global Warming Impact of Materials (GWIM)." The GWIM is subdivided into two portions: (i) productive portion (GWIMp) that includes the materials' emissions until the service life of the facility and (ii) non-productive portion (GWIMnp) which includes the materials' GHG emissions beyond the service life until they are eliminated from the atmosphere. In place of the current, static, EC measurements (kgCO2e or MTCO2e), this model reports the GWIMs in units of kgCO2e-years or MTCO2e-years, which includes the effects of "time of use" of a facility. Using the models, this paper has computed GHG reductions by deconstruction, with material recoveries of 30%, 50%, and 70% at demolition for reuse, recycle, or repurpose. A 70% material recovery, after a 50-year service life of the building, affected a savings of 47% and 52% if the remaining 30% debris was incinerated or landfilled respectively. All of the values computed using models checked out with manual calculations. [ABSTRACT FROM AUTHOR]

Land-sea surface air temperature (SAT) contrast, an index of tropospheric thermodynamic structure and dynamical circulation, has shown a significant increase in recent decades over East Asia during the boreal summer. In Part I of this two-part paper, observational data and the results of transient warming experiments conducted using coupled atmosphere-ocean general circulation models (GCMs) are analyzed to examine changes in land-sea thermal contrast and the associated atmospheric circulation over East Asia from the past to the future. The interannual variability of the land-sea SAT contrast over the Far East for 1950-2012 was found to be tightly coupled with a characteristic tripolar pattern of tropospheric circulation over East Asia, which manifests as anticyclonic anomalies over the Okhotsk Sea and around the Philippines, and a cyclonic anomaly over Japan during a positive phase, and vice versa. In response to CO increase, the cold northeasterly winds off the east coast of northern Japan and the East Asian rainband were strengthened with the circulation pattern well projected on the observed interannual variability. These results are commonly found in GCMs regardless of future forcing scenarios, indicating the robustness of the East Asian climate response to global warming. The physical mechanisms responsible for the increase of the land-sea contrast are examined in Part II. [ABSTRACT FROM AUTHOR]

This study examines the oceanic and atmospheric variability over the Intra-American Seas (IAS) from a 32-year integration of a 15-km coupled regional climate model consisting of the Regional Spectral Model (RSM) for the atmosphere and the Regional Ocean Modeling System (ROMS) for the ocean. It is forced at the lateral boundaries by National Centers for Environmental Prediction-Department of Energy (NCEP-DOE R-2) atmospheric global reanalysis and Simplified Ocean Data Assimilation global oceanic reanalysis. This coupled downscaling integration is a free run without any heat flux correction and is referred as the Regional Ocean-Atmosphere coupled downscaling of global Reanalysis over the Intra-American Seas (ROARS). The paper examines the fidelity of ROARS with respect to independent observations that are both satellite based and in situ. In order to provide a perspective on the fidelity of the ROARS simulation, we also compare it with the Climate Forecast System Reanalysis (CFSR), a modern global ocean-atmosphere reanalysis product. Our analysis reveals that ROARS exhibits reasonable climatology and interannual variability over the IAS region, with climatological SST errors less than 1 °C except along the coastlines. The anomaly correlation of the monthly SST and precipitation anomalies in ROARS are well over 0.5 over the Gulf of Mexico, Caribbean Sea, Western Atlantic and Eastern Pacific Oceans. A highlight of the ROARS simulation is its resolution of the loop current and the episodic eddy events off of it. This is rather poorly simulated in the CFSR. This is also reflected in the simulated, albeit, higher variance of the sea surface height in ROARS and the lack of any variability in the sea surface height of the CFSR over the IAS. However the anomaly correlations of the monthly heat content anomalies of ROARS are comparatively lower, especially over the Gulf of Mexico and the Caribbean Sea. This is a result of ROARS exhibiting a bias of underestimation (overestimation) of high (low) clouds. ROARS like CFSR is also able to capture the Caribbean Low Level Jet and its seasonal variability reasonably well. [ABSTRACT FROM AUTHOR]

The Murray dairy region produces approximately 1.85 billion litres of milk each year, representing about 20 % of Australia's total annual milk production. An ongoing production challenge in this region is the management of the impacts of heat stress during spring and summer. An increase in the frequency and severity of extreme temperature events due to climate change may result in additional heat stress and production losses. This paper assesses the changing nature of heat stress now, and into the future, using historical data and climate change projections for the region using the temperature humidity index (THI). Projected temperature and relative humidity changes from two global climate models (GCMs), CSIRO MK3.5 and CCR-MIROC-H, have been used to calculate THI values for 2025 and 2050, and summarized as mean occurrence of, and mean length of consecutive high heat stress periods. The future climate scenarios explored show that by 2025 an additional 12-15 days (compared to 1971 to 2000 baseline data) of moderate to severe heat stress are likely across much of the study region. By 2050, larger increases in severity and occurrence of heat stress are likely (i.e. an additional 31-42 moderate to severe heat stress days compared with baseline data). This increasing trend will have a negative impact on milk production among dairy cattle in the region. The results from this study provide useful insights on the trends in THI in the region. Dairy farmers and the dairy industry could use these results to devise and prioritise adaptation options to deal with projected increases in heat stress frequency and severity. [ABSTRACT FROM AUTHOR]

Present-day land temperatures simulated by state-of-the-art global climate models exhibit considerable uncertainty. Generally it is assumed that these temperature biases do not affect the projected warming in response to rising greenhouse gas concentrations (i.e. drop out by subtracting projected and present-day temperatures), but for specific regions and seasons this assumption is invalid. Here we show that, on the contrary, for large continental regions, such as Europe, state-of-the art global climate models with a warm summer bias project a relatively strong warming. This is because continental summer temperatures depend chiefly on soil drying in response to spring and summer solar radiation increase: models that dry fastest (due to the interaction of clouds, convection and soil hydrology) exhibit the strongest reductions in evaporation and consequently a more pronounced end-of-summer warming. These physical mechanisms acting on a seasonal timescale also govern the long-term climate response to greenhouse forcing over continental regions in summer. Combining these findings, we use the current model biases to reduce the uncertainty range in the projected warming over Europe from 3.6–8.6 °C to 4.6–7.3 °C (a reduction of about 50%). Given the huge potential impacts of the warmest projections on health, agriculture and water management, constraining the range of future summer climate change is imperative for relevant mitigation and adaptation strategies. [ABSTRACT FROM AUTHOR]

Assessing the regional responses to different Global Warming Levels (GWLs; e.g. + 1.5, 2, 3 and 4 ºC) is one of the most important challenges in climate change sciences since the Paris Agreement goal of keeping global temperature increase well below 2 °C with respect to the pre-industrial period. Regional responses to global warming were typically analyzed using global projections from Global Climate Models (GCMs) and, more recently, using higher resolution Regional Climate Models (RCMs) over limited regions. For instance, the IPCC AR6 WGI Atlas provides results of the regional response to different GWLs for several climate variables from both GCMs and RCMs. These results are calculated under the assumption that the regional signal to global warming is consistent between the GCMs and the nested RCMs. In the present study we investigate the above assumption by evaluating the consistency of regional responses to global warming from global (CMIP5) and regional (CORDEX) projections. The dataset aggregated over the new IPCC reference regions, available from the IPCC AR6 WGI Atlas repository, is analyzed here for temperature and precipitation. The existing relationships between the regional climate change signals and global warming are compared for both CMIP5 and CORDEX. Our results show significant linear scaling relationships between regional changes and global warming for most of the regions. CORDEX and CMIP5 show remarkably similar scaling relationships and similar robustness in the emergence of the climate change signal for most of the regions. These results support the use of regional climate models in the context of global warming level studies. [ABSTRACT FROM AUTHOR]

The net effect on the upwelling radiation caused by tropical cyclone clouds is calculated over a 20-year global data set, and the corresponding contribution to the earth energy balance is analyzed. Tropical cyclone clouds are shown on average to increase the upwelling radiation at the top of the atmosphere compared with the background non-tropical-cyclone-cloud climatology. This increase in upwelling radiation provides an overall cooling effect on the climate system because the increased reflected shortwave radiation (cooling) outweighs the decreased emitted longwave radiation (warming). While the effect neglects the (likely considerable) contribution due to tropical cyclone drying, the amount of cooling by clouds alone represents a considerable fraction of the excess warming energy in the climate system. Thus, any future change in tropical cyclone activity has the potential to impact the overall energy balance if it substantially alters this total. The seasonal and geographic distribution of warming and cooling effects, and the diurnal dynamics that impact whether any particular cyclone is net cooling or net warming are discussed in this study. [ABSTRACT FROM AUTHOR]

A deeper understanding of how clouds will respond to a warming climate is one of the outstanding challenges in climate science. Uncertainties in the response of clouds, and particularly shallow clouds, have been identified as the dominant source of the discrepancy in model estimates of equilibrium climate sensitivity. As the community gains a deeper understanding of the many processes involved, there is a growing appreciation of the critical role played by fluctuations in water vapor and the coupling of water vapor and atmospheric circulations. Reduction of uncertainties in cloud-climate feedbacks and convection initiation as well as improved understanding of processes governing these effects will result from profiling of water vapor in the lower troposphere with improved accuracy and vertical resolution compared to existing airborne and space-based measurements. This paper highlights new technologies and improved measurement approaches for measuring lower tropospheric water vapor and their expected added value to current observations. Those include differential absorption lidar and radar, microwave occultation between low-Earth orbiters, and hyperspectral microwave remote sensing. Each methodology is briefly explained, and measurement capabilities as well as the current technological readiness for aircraft and satellite implementation are specified. Potential synergies between the technologies are discussed, actual examples hereof are given, and future perspectives are explored. Based on technical maturity and the foreseen near-mid-term development path of the various discussed measurement approaches, we find that improved measurements of water vapor throughout the troposphere would greatly benefit from the combination of differential absorption lidar focusing on the lower troposphere with passive remote sensors constraining the upper-tropospheric humidity. [ABSTRACT FROM AUTHOR]

The history of the Polynesian civilization on Rapa Nui (Easter Island) over the Common Era has come to exemplify the fragile relationship humans have with their environment. Social dynamics, deforestation, land degradation, and climatic shifts have all been proposed as important parts of the settlement history and societal transformations on Rapa Nui. Furthermore, climate dynamics of the Southeast Pacific have major global implications. While the wetlands of Rapa Nui contain critical sedimentological archives for reconstructing past hydrological change on the island, connections between the island's hydroclimate and fundamental aspects of regional climatology are poorly understood. Here we present a hydroclimatology of Rapa Nui showing that there is a clear seasonal cycle of precipitation, with wet months receiving almost twice as much precipitation as dry months. This seasonal cycle can be explained by the seasonal shifts in the location and strength of the climatological south Pacific subtropical anticyclone. For interannual precipitation variability, we find that the occurrence of infrequent, large rain events explains 92% of the variance of the observed annual mean precipitation time series. Approximately one third (33%) of these events are associated with atmospheric rivers, 21% are associated with classic cold-front synoptic systems, and the remainder are characterized by cut-off lows and other synoptic-scale storm systems. As a group, these large rain events are most strongly controlled by the longitudinal position of the south Pacific subtropical anticyclone. The longitudinal location of this anticyclone explains 21% of the variance in the frequency of large rain events, while the remaining variance is left unexplained by any other major atmosphere-ocean dynamics. We find that over the observational era there appears to be no linear relationship between the number of large rain events and any other major climate phenomena. With the south Pacific subtropical anticyclone projected to strengthen and expand westward under global warming, our results imply that Rapa Nui will experience an increase in the number of dry years in the future. [ABSTRACT FROM AUTHOR]

Egypt, a predominantly arid and hyper-arid country, is one of the environmentally most fragile regions of the world. The country became a hot spot for climatic extremes and aridity change in the global warming context. The unavailability of a detailed and reliable climate zonation map is a major hindrance to climatic studies in Egypt. This study attempted to generate a high-resolution climate zone map of Egypt based on a novel image analysis technique. For this purpose, a colored image representing Egypt's composite climatology was developed using three high-resolution (1-km) climate variables: rainfall, maximum temperature and minimum temperature during 1979–2013. A spherical evolution algorithm was used to classify the image into different climate zones. Subsequently, the climate zones representing similar climate distribution were merged to generate the climate map of Egypt. The study revealed that Egypt's distinguishable climate zones could be recognized when the land area was classified into nine zones using the image analysis technique. The statistical analysis of climate variables of each zone revealed similar climatology only in two pairs of zones. The merging of similar climate zones yielded seven climate zones having distinct climate characteristics. The validation of climate zonation using various statistical tests revealed the robustness of the proposed method in classifying climate. The climate zone map generated in the study can be used as a reference for climate change analysis in Egypt. [ABSTRACT FROM AUTHOR]

This editorial introduces the journal Climate Action to its audience and defines its aims and scope. It first calls for the need to understand climate action as the choices and behavior of international organizations, governments, civil society, businesses, and individuals. Next, it discusses both the facilitators and impacts of climate action. The editorial concludes with a research agenda for climate action to be studied from a transdisciplinary perspective with practitioners for triggering widespread societal transformation. [ABSTRACT FROM AUTHOR]

The potential changes in the strength and location of five low-level jets (LLJs) located within four Coordinated Regional Climate Downscaling Experiment (CORDEX) domains are examined for present and future climate conditions using an ensemble of simulations conducted with the RegCM4 regional model at a 25 km horizontal grid spacing. Lateral and lower boundary forcing fields are from three General Circulation Models (GCMs), and we analyse a historical period (1995–2014) along with two future periods (2041–2060 and 2080–2099) under the Representative Concentration Pathways 2.6 and 8.5. The RegCM4, as driven by the GCMs, is capable of capturing most of the observed climatological features of the LLJs, both in terms of spatial location and seasonal evolution. Analysis of the influence of global warming on the LLJs shows a consistent strengthening of the jets and a shift in their location under both warming scenarios. The Monsoon and West African westerly LLJs exhibit a northward shift, while the Caribbean and South American LLJs present a westward expansion. The use of an ensemble of high-resolution simulations is found to provide a key element for a robust assessment of changes in LLJs associated with future global warming scenarios. [ABSTRACT FROM AUTHOR]

Natural variability of climate considerably affects hydro-climatic trend significance, and therefore, removal of such influence is essential to understand the unidirectional trends due to global warming. The objective of this study was to evaluate the trends in precipitation extremes in the arid province of Pakistan by removing the natural variability of climate to understand the effect of global warming on precipitation extremes during two major cropping seasons, Rabi and Kharif. Daily precipitation data of APHRODITE (Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation) for the period 1951–2015 was used for this purpose. An improved form of classical Mann-Kendall (MK) test known as modified Mann-Kendall (MMK) was used which can estimate trends by discarding the influence of natural cycles present in time series. The results were compared with the classical MK test to show the novelty in the findings of this investigation. The results revealed a large influence of climate fluctuations on the trends in all the extreme precipitation indices for both seasons. The reduction in trend significance was noticed between 25 and 100% for different precipitation indices when MMK instead of MK test was used. The reduction was observed more for the positive trends in the indices compared with negative trends. The results revealed that global warming caused an increase in total annual precipitation at a rate of 2.8–34.8 mm/decade during 1951–2015. Besides, the annual number of extreme precipitation days was found to increase in the north by 0.1–0.84 days/decade and the number of annual precipitation days to decrease in the west for all seasons up to − 8.6 days/decade. An increase in continuous precipitation days was detected by 0.6–1.0 day/decade in the northeast while a decrease by − 0.5 to − 1.0 days/decade in the southwest and northwest. The continuous dry days decreased in the north and the central regions by up to − 6.3 days/decade while a rise in 1-day maximum precipitation by 6.6–35 mm/decade in the central north. Analysis of results revealed that the overestimation of trends by classical MK test is more in the arid region of Pakistan compared with other regions. [ABSTRACT FROM AUTHOR]

The study area, with arid to semi-humid climates, is located in northern Fars Province, southern Iran. Daily precipitation and temperature data from 22 models of the Coupled Model Inter-comparison Project Phase 5 (CMIP5) are used to study climate change for period 2026–2085 under RCP2.6, RCP4.5, and RCP8.5. Daily outputs of each CMIP5 model are downscaled to climatic stations over the study area using LARS-WG tool and transient change factors approach. Daily precipitation is downscaled to seven climatic stations while daily temperature downscaled to two stations. Downscaling results indicate that temperature will increase by + 1.85, + 2.5, and + 3.45 °C under the RCP2.6, RCP4.5, and RCP8.5, respectively, while precipitation will reduce by 14, 22, and 20.8%, respectively, within the study area. Standardized precipitation index (SPI) analysis, performed for 3-, 6-, 9-, and 12-month time scales, shows that frequency (duration) of normal periods will increase (decrease) under climate change, however, 12-month SPI analysis shows decreased frequency and increased duration for normal periods. Frequency, duration, severity, and intensity of wet periods may increase, decrease, or not change under climate change, depending on the SPI time scale. The study area will experience more frequent, longer-duration, severed, intensified droughts in the future due to global warming. Extreme storm analysis shows that precipitation depth of most frequent storms (2-year return period storms) will increase, but precipitation depth of less frequent storms (10- and 20-year return period storms) will decrease under climate change. Temperature enhancement, precipitation reduction, and longer-duration, severed, intensified droughts will increase water shortage in the future, resulting in water crisis and reduced security of food production over northern Fars Province. [ABSTRACT FROM AUTHOR]

Contrary to expectations that global warming will be accompanied by an increase in terrestrial evaporation, pan evaporation (PE) has decreased in several parts of the world during the last decades. This opposing relationship is known as the pan evaporation paradox phenomenon that can be affected by climate change. For this purpose, this study identifies spatial and temporal trends in PE and its associated climate variables (Cvars) in Iran at seasonal and annual time scales. Hence, PE and Cvars data from 68 meteorological stations distributed over Iran during the period 1987–2016 were selected. The analyses of the temporal and spatial trends in PE, Cvars, and relationships among them were examined using the statistical techniques to identify the causes of PE trends. Results indicated that stations located in the subtropical region (latitude below 32°), which is mostly located in the southern half of Iran, showed significant negative PE trends (about 20–30% of stations) in spite of an increasing trend in temperatures indicating the "pan paradox" phenomenon. However, stations with significant positive PE trends (about 40% of stations), which are mostly located in the northern half of Iran, are placed at latitudes above 32°. Trend analysis of other Cvars indicated significant increases in temperatures, sunshine duration, and wind speed in more than half of the stations on all time scales. In addition, minimum, maximum, and mean temperatures, and sunshine duration were the most dominant variables affecting PE in annual, spring, autumn, and summer, respectively, in Iran. [ABSTRACT FROM AUTHOR]

How much and fast the Earth is warming in response to increasing greenhouse gas concentrations is one of the fundamental questions in climate science. Here we investigate the role that different modes of climate variability play in modulating the temperature response. We show evidence for a robust statistical relationship between global warming rate variations and Atlantic Multidecadal Variability (AMV) across multiple observational datasets since 1850. The correlation between AMV and the global warming rate is maximized—with a correlation coefficient of about − 0.8—at ~ 10 to 20 years lead-time. In contrast, such a relation between global warming rate and the Interdecadal Pacific Oscillation (IPO) is far less coherent, showing negative correlation before the 1920s and positive correlation after that. Similar statistical relationships between global warming rate variations and the AMV/IPO can also be seen in the majority of the models from the Phase 5 of Coupled Models Inter-comparison Project. Further, a targeted model experiment is conducted to demonstrate the dominant control of the AMV on the unforced fraction of the global warming rate (compared to the IPO). [ABSTRACT FROM AUTHOR]

Four bias correction methods, i.e., gamma cumulative distribution function (GamCDF), quantile–quantile adjustment (QQadj), equidistant cumulative probability distribution function (CDF) matching (EDCDF), and transform CDF (CDF-t), to read are applied to five daily precipitation datasets over China produced by LMDZ4-regional that was nested into five global climate models (GCMs), BCC-CSM1-1m, CNRM-CM5, FGOALS-g2, IPSL-CM5A-MR, and MPI-ESM-MR, respectively. A unified mathematical framework can be used to define the four bias correction methods, which helps understanding their natures and essences for identifying the most reliable probability distributions of projected climate. CDF-t is shown to be the best bias correction method based on a comprehensive evaluation of different precipitation indices. Future precipitation projections corresponding to the global warming levels of 1.5 °C and 2 °C under RCP8.5 were obtained using the bias correction methods. The multi-method and multi-model ensemble characteristics allow to explore the spreading of projections, considered a surrogate of climate projection uncertainty, and to attribute such uncertainties to different sources. It was found that the spread among bias correction methods is smaller than that among dynamical downscaling simulations. The four bias correction methods, with CDF-t at the top, all reduce the spread among the downscaled results. Future projection using CDF-t is thus considered having higher credibility. [ABSTRACT FROM AUTHOR]

Weather and climate hazards cause too many fatalities each year. These weather and climate hazards are projected to increase in frequency and intensity due to global warming. Here, we use a disaster database to investigate continentally aggregated fatality data for trends. We also examine whether modes of climate variability affect the propensity of fatalities. Furthermore, we quantify fatality risk by computing effective return periods which depend on modes of climate variability. We find statistically significant increasing trends for heat waves and floods for worldwide aggregated data. Significant trends occur in the number of fatalities in Asia where fatalities due to heat waves and floods are increasing, while storm-related fatalities are decreasing. However, when normalized by population size, the trends are no longer significant. Furthermore, the number of fatalities can be well described probabilistically by an extreme value distribution, a generalized Pareto distribution (GPD). Based on the GPD, we evaluate covariates which affect the number of fatalities aggregated over all hazard types. For this purpose, we evaluate combinations of modes of climate variability and socio-economic indicators as covariates. We find no evidence for a significant direct impact from socio-economic indicators; however, we find significant evidence for the impact from modes of climate variability on the number of fatalities. The important modes of climate variability affecting the number of fatalities are tropical cyclone activity, modes of sea surface temperature and atmospheric teleconnection patterns. This offers the potential of predictability of the number of fatalities given that most of these climate modes are predictable on seasonal to inter-annual time scales. [ABSTRACT FROM AUTHOR]

Over the past century, the Earth has experienced roughly 0.4–0.8 ∘C rise in the average temperature and which is projected to increase between 1.4 and 5.8 ∘C by the year 2100. The increase in the Earth's temperature directly influences physiological traits of individual species in ecosystems. However, the effect of these changes in community dynamics, so far, remains relatively unknown. Here, we show that the consequences of warming (i.e., increase in the global mean temperature) on the interacting species persistence or extinction are correlated with their trophic complexity and community structure. In particular, we investigate different nonlinear bioenergetic tri-trophic food web modules, commonly observed in nature, in the order of increasing trophic complexity: a food chain, a diamond food web, and an omnivorous interaction. We find that at low temperatures, warming can destabilize the species dynamics in the food chain as well as the diamond food web, but it has no such effect on the trophic structure that involves omnivory. In the diamond food web, our results indicate that warming does not support top-down control induced co-existence of intermediate species. However, in all the trophic structures, warming can destabilize species up to a threshold temperature. Beyond the threshold temperature, warming stabilizes species dynamics at the cost of the extinction of higher trophic species. We demonstrate the robustness of our results when a few system parameters are varied together with the temperature. Overall, our study suggests that variations in the trophic complexity of simple food web modules can influence the effects of climate warming on species dynamics. [ABSTRACT FROM AUTHOR]

This study presents the results of the ERTDF S-12 project for searching an optimum reduction scenario of the short-lived climate pollutants (SLCPs) to simultaneously mitigate the global warming and environmental problems. The study utilized REAS emission inventory, Asia-Pacific Integrated Model-Enduse (AIM/Enduse), MIROC6 climate model, NICAM non-hydrostatic atmospheric model, and models for estimating environmental damages to health, agriculture, and flood risks. Results of various scenario search indicate that it is difficult to attain simultaneous reduction of global warming and environmental damages, unless a significant reduction of CO2 is combined with carefully designed SLCP reductions for CH4, SO2, black carbon (BC), NOx, CO, and VOCs. In this scenario design, it is important to take into account the impact of small BC reduction to the surface air temperature and complex atmospheric chemical interactions such as negative feedback between CH4 and NOx reduction. We identified two scenarios, i.e., B2a and B1c scenarios which combine the 2D-scenario with SLCP mitigation measures using End-of-Pipe (EoP) and new mitigation technologies, as promising to simultaneously mitigate the temperature rise by about 0.33 °C by 2050 and air pollution in most of the globe for reducing damages in health, agriculture, and flood risk. In Asia and other heavy air pollution areas, health-care measures have to be enhanced in order to suppress the mortality increase due to high temperature in hot spot areas caused by a significant cut of particulate matter. For this situation, the B1b scenario is better to reduce hot spot areas and high-temperature damage to the public health. [ABSTRACT FROM AUTHOR]

Although a significant number of studies have evaluated the trends in different characteristics of precipitation in Iran, the trends in precipitation indicators related to bioclimate are still not explored. The 0.5° spatial resolution gauge-based gridded monthly precipitation data of global precipitation climatology centre (GPCC) for the period 1901–2016 was used in this study for the evaluation of the geographical distribution of the trends of bioclimatic precipitation indicators of Iran. The trends in the indicators due to global warming were estimated using modified Mann-Kendall (MMK) trend test which can estimate unidirectional trend by separating the natural variability in climate. Obtained results were compared with that found using classical Mann-Kendall (MK) test. Besides, gridded temperature data of climate research unit (CRU) was used to identify the warm/cold periods at each grid point to assess the trends in precipitation during warm/cold periods, considering a wide spatial variation in the onset time of different seasons in Iran. The results revealed that many of the trends in some of the precipitation indicators obtained in earlier studies were due to natural fluctuation of climate. Annual precipitation in Iran was found decreasing only in the northwest semi-arid region at a rate of − 12.1 to − 14.05 mm/decade, while the precipitation in the wettest month was found increasing in a large area in the southwest semi-arid region at a rate of 3.1 to 5.3 mm/decade. The most significant changes were observed in precipitation seasonality, which was found to increase in 22.4% area, mostly in the central dry and northeast semi-dry regions and decrease in 11.3% area, mostly in the northern wetter region. The study indicates that the long-term natural variability in large-scale atmospheric phenomena that influences the precipitation of Iran may be the cause of many significant changes observed in precipitation in previous studies. [ABSTRACT FROM AUTHOR]

Novel high-resolution convection-permitting regional climate simulations over the US employing the pseudo-global warming approach are used to investigate changes in the convective population and thermodynamic environments in a future climate. Two continuous 13-year simulations were conducted using (1) ERA-Interim reanalysis and (2) ERA-Interim reanalysis plus a climate perturbation for the RCP8.5 scenario. The simulations adequately reproduce the observed precipitation diurnal cycle, indicating that they capture organized and propagating convection that most climate models cannot adequately represent. This study shows that weak to moderate convection will decrease and strong convection will increase in frequency in a future climate. Analysis of the thermodynamic environments supporting convection shows that both convective available potential energy (CAPE) and convective inhibition (CIN) increase downstream of the Rockies in a future climate. Previous studies suggest that CAPE will increase in a warming climate, however a corresponding increase in CIN acts as a balancing force to shift the convective population by suppressing weak to moderate convection and provides an environment where CAPE can build to extreme levels that may result in more frequent severe convection. An idealized investigation of fundamental changes in the thermodynamic environment was conducted by shifting a standard atmospheric profile by ± 5 °C. When temperature is increased, both CAPE and CIN increase in magnitude, while the opposite is true for decreased temperatures. Thus, even in the absence of synoptic and mesoscale variations, a warmer climate will provide more CAPE and CIN that will shift the convective population, likely impacting water and energy budgets on Earth. [ABSTRACT FROM AUTHOR]

Increased knowledge of future changes in rainfall variability is needed to reduce vulnerability to potential impacts of global warming, especially in highly vulnerable regions like West Africa. While changes in mean and extreme rainfall have been studied extensively, rainfall variability has received less attention, despite its importance. In this study, future changes in West African summer monsoon (WASM) rainfall variability were investigated using data from two regional climate models that participated in the Coordinated Regional Climate Downscaling Experiment (CORDEX). The daily rainfall data were band-pass filtered to isolate variability at a wide range of timescales. Under global warming, WASM rainfall variability is projected to increase by about 10–28% over the entire region and is remarkably robust over a wide range of timescales. We found that changes in mean rainfall significantly explain the majority of intermodel spread in projected WASM rainfall variability. The role of increased atmospheric moisture is examined by estimating the change due to an idealized local thermodynamic enhancement. Analysis reveals that increased atmospheric moisture with respect to warming following the Clausius–Clapeyron relationship can explain the majority of the projected changes in rainfall variability at all timescales. [ABSTRACT FROM AUTHOR]

The melting of permafrost and the degradation of alpine meadow ecosystems caused by climate warming and high-intensity human activities have imposed serious threats to local and global ecological security. In order to estimate the effects of climate warming and grazing interference on the photosynthesis and respiration of alpine meadow plant community in permafrost regions, warming – infrared radiator is applied to simulate the climate warming (increasing temperature by +2°С). The winter grazing level is simulated by mowing the aboveground biomass of all plants. The responses of permafrost meadow community in terms of photosynthesis, respiration, surface soil temperature and moisture, as well as the carbon balance to simulated different climate warming and grazing level were analyzed and discussed. The results showed that: (1) the surface soil temperature in climate warming and grazing plots is significantly higher than in Ck plots (P < 0.01); (2) warming and warming + grazing plots enhanced community photosynthesis and respiration (P < 0.01); (3) warming and warming + grazing treatments increased community aboveground biomass (P < 0.05); (4) the photosynthetic rate increased in the second year, then decreased in the third year when both temperature and grazing level increased during the growing season. However, the ecosystem respiration increasingly increased year by year; (5) compared with the control groups, warming and grazing treatments resulted in an increase in carbon sequestration of the permafrost meadow community during the growing season. [ABSTRACT FROM AUTHOR]

Weather and climate extremes cause significant economic damages and fatalities. Over the last few decades, the frequency of these disasters and their economic damages have significantly increased in the USA. The prediction of the future evolution of these damages and their relation to global warming and US economic growth is essential for deciding on cost-efficient mitigation pathways. Here we show using a probabilistic extreme value statistics framework that both the increase in US Gross Domestic Product per capita and global warming are significant covariates in probabilistically modeling the increase in economic damages. We also provide evidence that the Pacific Decadal Oscillation affects the number of fatalities. Using the Intergovernmental Panel on Climate Change scenarios, we estimate the potential future economic risks. We find that by 2060, the extreme risks (as measured by 200-year effective return level) will have increased by 3–5.4 times. The damage costs due to extreme risks are projected to be between 0.1 and 0.7% of US Gross Domestic Product by 2060 and could reach 5–16% by 2100. [ABSTRACT FROM AUTHOR]

The daily cloud cycle or diurnal cloud cycle (DCC) and its response to global warming are critical to the Earth's energy budget, but their radiative effects have not been systematically quantified. Toward this goal, here we analyze the radiation at the top of the atmosphere and propose a measure of the DCC radiative effect (DCCRE) as the difference between the total radiative fluxes with the full cloud cycle and its uniformly distributed cloud counterpart. When applied to the frequency of cloud occurrence, DCCRE is linked to the covariance between DCC and cloud radiative effects. Satellite observations show that the daily cloud cycle is strongly linked to pacific decadal oscillation (PDO) and climate hiatus, revealing its potential role in controlling climate variability. Climate model outputs show large inter-model spreads of DCCRE, accounting for approximately 20% inter-model spread of the cloud radiative effects. Climate models also suggest that while DCCRE is not sensitive to rising temperatures at the global scale, it can be important in certain regions. Such a framework can be used to conduct a more systematic evaluation of the DCC in climate models and observations with the goal to understand climate variability and reduce uncertainty in climate projections. [ABSTRACT FROM AUTHOR]

While there is evidence that ENSO activity will increase in association with the increased vertical stratification due to global warming, the underlying mechanisms remain unclear. Here we investigate this issue using the simulations of the NCAR Community Earth System Model Large Ensemble (CESM-LE) Project focusing on strong El Niño events of the Eastern Pacific (EP) that can be associated to flooding in Northern and Central Peru. It is shown that, in the warmer climate, the duration of strong EP El Niño events peaking in boreal winter is extended by two months, which results in significantly more events peaking in February–March–April (FMA), the season when the climatological Inter-Tropical Convergence Zone is at its southernmost location. This larger persistence of strong EP events is interpreted as resulting from both a stronger recharge process and a more effective thermocline feedback in the eastern equatorial Pacific due to increased mean vertical stratification. A heat budget analysis reveals in particular that the reduction in seasonal upwelling rate is compensated by the increase in anomalous vertical temperature gradient within the surface layer, yielding an overall increase in the effectiveness of the thermocline feedback. In CESM-LE, the appearance of strong EP El Niño events peaking in FMA accounts for one-quarter of the increase in frequency of occurrence of ENSO-induced extreme precipitation events, while one-third results from weak-to-moderate El Niño events that triggers extreme precipitation events because of the warmer mean SST becoming closer to the convective threshold. In CESM-LE, both the increase in mean EP SST and the change in ENSO processes thus contribute to the increase in extreme precipitation events in the warmer climate. [ABSTRACT FROM AUTHOR]

Arid Central Asia is highly vulnerable to extreme climate events. Information on potential future changes in extreme climate events in Central Asia is limited. In this study, the performances of models from the Coupled Model Intercomparison Project phase 5 (CMIP5) in simulating climatological extremes in Central Asia are first evaluated, and a bias correction method is employed to constrain future projections. The responses of extreme climate events over Central Asia to future warming and, in particular, the impact of 1.5 and 2 °C global warming scenarios are then assessed based on the observationally constrained projections. During the twenty-first century, coldest night (TNn), coldest day (TXn), warmest night (TNx), warmest day (TXx), 1-day maximum precipitation (RX1 day), 5-day maximum precipitation (RX5 day), and precipitation intensity (SDII) in Central Asia would robustly increase at best estimated rates of 1.93 °C, 1.71 °C, 1.18 °C, 1.25 °C, 6.30%, 5.71%, and 4.99% per degree of global warming, respectively, under Representative Concentration Pathway (RCP) 8.5. Compared with the 2 °C warming scenario, limiting global warming to 1.5 °C could reduce the intensification (relative to 1986–2005) of TNn, TNx, TXn, TXx, RX1 day, RX5 day, and SDII by 33%, 24%, 32%, 29%, 39%, 42%, and 53% from the best estimates under RCP8.5, respectively. The avoided intensification of TNn, TNx, TXn and TXx (RX1 day and SDII) would be larger (smaller) under RCP4.5. This suggests that a low warming target is necessary for avoiding the dangerous risk of extremes in this arid region. [ABSTRACT FROM AUTHOR]

This study investigates the added value of very high resolution in long-term climate simulations over South Korea using the Weather Research and Forecasting (WRF) model. A one-way double-nested modeling system consisting of a mother domain (20-km resolution) and nested domain (5-km resolution) is customized for simulating the distinct climatological patterns in Korea, where the region-specific climate is largely influenced by the area's complex geographical features. The ERA-Interim reanalysis data are used for the initial and boundary conditions, and the simulation spans the period from December 1, 1985 to December 31, 2005 (20-year analysis period with 1-month spin-up). Simulations from both the mother and the nested domain show reasonable performance in capturing the general characteristics of summer temperature and precipitation in terms of temporally and spatially averaged quantities. However, the added value from the nested domain with its higher resolution is apparently found in the reproduction of the intensity and frequency of extreme events and in the physical realism related to the partitioning of convective and large-scale precipitation. The nested domain not only better resolves the sharp gradients of temperature variation over short distances but also substantially reduces the systematic cold bias seen in temperature extremes produced by the mother domain. Furthermore, the nested domain is better able to simulate the upper tail of precipitation distributions and thus of extreme events. The higher resolution also improves the simulation of partitioning between convective and large-scale precipitation, leading to a plausible relationship between extreme precipitation and temperature and showing good agreement with in situ observation. Given the different behaviors of convective and large-scale precipitation in response to temperature changes, their realistic partitioning in the model has important potential for enhancing the reliability of precipitation projection under global warming. [ABSTRACT FROM AUTHOR]

Despite the monotonically rising greenhouse gas emission, global warming rate changes again and again, especially the slowdown during 1998–2013, challenging the current global temperature change mechanisms. Recently, different-scale natural climate variabilities have been individually recognized as the potential causes of global warming rate change, particularly the recent warming slowdown, but disagreements still exist on their relative importance. Here we quantify the contribution of interannual, interdecadal and multidecadal variabilities (IAV, IDV and MDV) in modulating the global warming rate during the period 1850–2017 via decomposing the global mean temperature timeseries derived from 12 datasets into several quasi-periodic fluctuations and a monotonical secular trend (ST) using the ensemble empirical mode decomposition method. Our results show that the IAV, IDV and MDV dominate the global warming rate change together, rather than one-scale variability alone. For example, during 1998–2013 both the IAV and IDV present obvious negative trends and combine to cut 59 ± 22% of global mean surface temperature (GMST) and 65 ± 38% of sea surface temperature (SST) positive trends which are caused by the steadily warming ST and the warming phase of MDV, thus causing an apparent warming slowdown during this period. Furthermore, we illustrate that the IAV, IDV and MDV mainly originate from the El Niño-Southern oscillation (ENSO), Pacific decadal oscillation (PDO) and Atlantic multidecadal oscillation (AMO), respectively. Our work partly reconciles the controversy over the importance of different-scale natural variabilities, and provides some insights for climate change attribution and prediction research. [ABSTRACT FROM AUTHOR]

For aiming to keep global warming well-below 2 °C and pursue efforts to limit it to 1.5 °C, as set out in the Paris Agreement, a full-fledged assessment of negative emission technologies (NETs) that remove carbon dioxide from the atmosphere is crucial to inform science-based policy making. With the Paris Agreement in mind, we re-analyse available scenario evidence to understand the roles of NETs in 1.5 °C and 2 °C scenarios and, for the first time, link this to a systematic review of findings in the underlying literature. In line with previous research, we find that keeping warming below 1.5 °C requires a rapid large-scale deployment of NETs, while for 2 °C, we can still limit NET deployment substantially by ratcheting up near-term mitigation ambition. Most recent evidence stresses the importance of future socio-economic conditions in determining the flexibility of NET deployment and suggests opportunities for hedging technology risks by adopting portfolios of NETs. Importantly, our thematic review highlights that there is a much richer set of findings on NETs than commonly reflected upon both in scientific assessments and available reviews. In particular, beyond the common findings on NETs underpinned by dozens of studies around early scale-up, the changing shape of net emission pathways or greater flexibility in the timing of climate policies, there is a suite of "niche and emerging findings", e.g. around innovation needs and rapid technological change, termination of NETs at the end of the twenty-first century or the impacts of climate change on the effectiveness of NETs that have not been widely appreciated. Future research needs to explore the role of climate damages on NET uptake, better understand the geophysical constraints of NET deployment (e.g. water, geological storage, climate feedbacks), and provide a more systematic assessment of NET portfolios in the context of sustainable development goals. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to determine transparent food carbon footprint values for use in a climate tax, using a consistent methodology across the taxed food products and taking into account the need for such a tax to be administratively simple and accepted by affected stakeholders. Methods: A method based on Life Cycle Assessment following the ISO 14067 standard was developed for establishing simplified, yet consistent and transparent, datasets on the carbon footprint of food, for use as a base in a climate tax on food. Several sensitivity analyses were carried out to test the effects of inevitable methodological choices on the carbon footprint of different foods. The choices were then discussed in relation to taxation of food. The methodological choices included in the sensitivity analyses were different approaches to system boundaries, how to account for soil carbon changes and how to weigh greenhouse gases (GHGs). Results and discussion: The results on the carbon footprint of food calculated with the suggested method are in line with earlier findings in the field, with animal products, especially beef, showing a substantially higher value than most plant-based foods. Regarding choice of system boundaries for using the values in a tax, it is of particular importance to target emissions from biological processes, as these are currently untaxed. This would also be administratively simpler but less acceptable as large emission sources especially for imported products and greenhouse grown vegetables would not be included. Modelling emissions from soil carbon changes using a site-dependent method can be an advantage to obtain results in line with empirical data. Using Global Warming Potential over 100 years to weigh GHGs would be most in line with current climate reporting, which is an advantage for the consistency and acceptability of a tax. Conclusions: Ultimately, how taxes are set is a political decision, but food carbon footprint values determined with a consistent and simplified methodology are required in the process. This study presents carbon footprint values established using such method and provides valuable insights into how methodological choices affect the results of climate impact values and the implications for taxation. [ABSTRACT FROM AUTHOR]

Drylands are one of the most sensitive areas to climate change. Many previous studies assessed the impact of 1.5 °C and 2 °C warming targets using transient warming scenarios by representative concentration pathways of CMIP5. Here we compared the climate changes over global drylands in transient and stabilized 1.5 °C and 2 °C warmer worlds using Community Earth System Model simulations. The projections indicate a warming of 2.3 °C (1.6 °C) over drylands could occur in a stabilized 2 °C (1.5 °C) warmer world by the end of this century. The warming in drier regions is higher and the hyper-arid areas would experience warming of 2.4 °C (1.8 °C). Comparing the 2 °C to 1.5 °C warming targets, the additional 0.5 °C warming will lead to ~ 1.0 °C warming in drylands of Eurasia and North America. Responding to the 2 °C warming, the increased precipitation (21.8–42.6 mm/year) is not enough to offset the increased PET (88.3–101.7 mm/year) over drylands, resulting in the drylands expansion, and the additional 0.5 °C global warming will aggravate the drought in drylands in southern North America and North Africa. Compared to the stabilized 2 °C warming target, controlling the global warming to within 1.5 °C will reduce the warming in drylands by 0.7 °C, and reduce the drylands expansion relative to 1961–1990 by ~ 44%. Compared to the stabilized warming scenarios, the temperature response and drylands area coverage increase are higher in the transient warming scenarios, but the difference of temperature caused by additional 0.5 °C global warming and the precipitation increase in drylands are lower. [ABSTRACT FROM AUTHOR]

Assessing multiple climatic and non-climatic variables affecting one region at the same time is a crucial aspect to support climate adaptation action. This publication presents a method to display relevant measures of any three adaptation relevant parameters (or optionally their projected future changes) at once on a map by allocating them to multiple transparency levels of the three primary colors of additive color mixing (red, green, and blue). The overlay of information allows the combined assessment of the regional exposures. The method is demonstrated by two examples based on an ensemble of regional climate projections analyzed for 1.5 °C, 2 °C, and 3 °C global warming periods. The first example shows the increasing number of people at risk for summer climate extremes under 1.5 °C, 2 °C, and 3 °C global warming by combining projected increases in tropical nights and summer intense precipitation days with today's population density. Under 3 °C global warming, many heavily populated areas across Europe are affected by both heat stress and summer precipitation extremes, whereas under 1.5 °C global warming, heat stress regions are restricted to southern Europe and the large settlements along the Eastern Mediterranean coast. A second example combines daily mean and minimum and maximum summer temperatures and highlights the regional expansion and the increasing robustness of projected mean summer warming with rising global warming levels, as well as the regional day to night differences of the warming signal. [ABSTRACT FROM AUTHOR]

West Africa faces an increasing challenge related to water resources in the coming decades; hence high-confidence climate projection is crucial for the region's future. In this study, future changes in summer monsoon rainfall under the RCP8.5 scenario were investigated over West Africa for the period of 2074–2099 with respect to the present-day period of 1980–2005 using the Rossby Centre Regional Climate Model (RCA4), driven by six Coupled Model Intercomparison Project phase 5 (CMIP5) global circulation models (GCMs). Through evaluation of the present climate, the RCA4 simulations and their multi-model ensemble mean (EnsMean) reasonably reproduced the climatology of the summer rainfall and associated tropospheric circulation features. In a warmer climate, summer monsoon rainfall is projected to increase in most parts of West Africa, but a decrease is expected in the northwest, around Senegal. Changes in the monsoon circulation are opposite in the lower and upper troposphere, with the tipping point at 400 hPa. Specifically, a projected strengthening and northward shift is observed at the lower and mid-tropospheric level, while weakening is evident at the upper tropospheric level. A diagnosis based on a moisture budget equation reveals that the robust positive response of West African summer monsoon rainfall to global warming is largely explained by the enhancement of moisture convergence and surface evaporation. [ABSTRACT FROM AUTHOR]