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This study assesses the policy/legal status of both multistream residues and potential secondary products ('symbiosis products') and whether there could be environmental benefits associated with the utilization of residues from integrated pulp and paper and carbon steel mills as raw materials for such secondary products. Waste-related European Union (EU) and Finnish policy and legal instruments were reviewed to identify potential constraints for, and suggested next steps in, the development of potential process industry residue-based symbiosis products. The products were soil amendment pellets, low-grade concrete, and mine filler. A global warming potential (GWP) assessment and an exergy analysis were applied to these potential symbiosis products. Some indicative GWP calculations of greenhouse gas emissions associating similar and/or analogous products based on virgin primary raw materials, more energy-intensive processes, and the alternative treatment of these residues as wastes are also presented. This study addresses GWP, exergy, and legal aspects in a holistic manner to determine the potential environmental benefits of secondary products within the EU legal framework. The GWP assessment and exergy analysis indicate that the utilization of multistream residues causes very low environmental burdens in terms of GWP. The utilization option can have potential environmental benefits in terms of GWP through process replacement and avoided landfilling and waste treatment impacts, as well as potentially through emission reductions from product replacement if suitable and safe applications can be identified. Waste regulation does not define the legal requirements under which utilizing residues in such novel concepts as introduced in this study would be possible, nor how waste status could be removed and product-based legislation be applied to the potential products instead. [ABSTRACT FROM AUTHOR]

Understanding the impact of various climate forcing agents, such as aerosols, on extreme precipitation is socially and scientifically vital. While anthropogenic absorbing aerosols influence Earth's energy balance and atmospheric convection, their role in extreme events remains unclear. This paper uses convective‐resolving radiative‐convective‐equilibrium simulations, with fixed solar radiation, to investigate the influence of absorbing aerosols on extreme precipitation comprehensively. Our findings reveal an underappreciated mechanism through which absorbing aerosols can, under certain conditions, strongly intensify extreme precipitation. Notably, we demonstrate that a mechanism previously reported for much warmer (hothouse) climates, where intense rainfall alternates with multi‐day dry spells, can operate under current realistic conditions due to absorbing aerosol influence. This mechanism operates when an aerosol perturbation shifts the lower tropospheric radiative heating rate to positive values, generating a strong inhibition layer. Our work highlights an additional potential effect of absorbing aerosols, with implications for climate change mitigation and disaster risk management. Plain Language Summary: Aerosols, particles suspended in the atmosphere, can interact with the incoming solar radiation by scattering or absorbing it. Aerosol species that absorb solar radiation generate local warming of the atmosphere. This local warming changes the vertical profile of temperature and by that affects cloud and precipitation development. In this paper we use idealized computer simulations to investigate the effect of absorbing aerosols on precipitation, and specifically on extreme precipitation events in the tropics. We demonstrate that under certain conditions, absorbing aerosols can strongly enhance extreme precipitation even despite reducing the mean. We show that this trend can be explained by a mechanism previously reported for much warmer climate conditions than currently found on Earth, involving heating by radiation of the lower part of the troposphere. These results have implications for climate change mitigation and disaster risk management. Key Points: The effect of absorbing aerosol on extreme precipitation is examined in idealized convective‐resolving radiative‐convective‐equilibrium simulationsAerosol perturbation that shifts the lower tropospheric radiative heating rate to positive values strongly enhances extreme precipitationThis trend is explained by a mechanism reported before for hothouse climate conditions involving a shift into an "episodic deluge" regime [ABSTRACT FROM AUTHOR]

Northwest China is much more sensitive to climate warming, and the climate has varied rapidly from warm and drought to warm and humid conditions. In addition, due to the complex terrain of Northwest China, the methods and parameterization schemes of different CMIP6 models, these models are mostly applied to arid areas in Northwest China or Central Asia, lacking climate data for plateau areas and eastern Lanzhou, specifically in filtering CMIP6 models and evaluating applicable models. In this paper, 34 CMIP6 climate models are used to evaluate and forecast future trends in Northwest China under the SSP126, SSP245 and SSP585 scenarios in the short, medium and long term. CMIP6 models of temperature and precipitation are identified by applying the interannual variability skill score (IVS) between CN05.1 datasets and historical CMIP6 models, which are suitable for Northwest China. Then, we assess the characteristics, warming and wetting deviations, and uncertainties in the prediction of climatic change according to CMIP6 models over Northwest China. The results show that CMIP6 models in precipitation and temperature applicable to Northwest China are AWI‐CM‐1‐1‐MR, BCC‐CSM2‐MR, FGOALS‐g3, INM‐CM4‐8, INM‐CM5‐0 and MRI‐ESM2‐0. The multi‐model ensemble mean (MMEM) has better capability than individual CMIP6 models in precipitation and temperature prediction. Spatiotemporal climatic change over Northwest China shows overall warming and wetting trends. The IVS provides the ability to estimate CMIP6 model simulation performance both temporally and spatially. The temperature simulation is quite good in the Tarim Basin and Hexi Corridor region, and the precipitation simulation is quite good in the plateau region, Altai Mountains, Tianshan Mountains and Hexi Corridor region. Cold and wet deviations occur in Northwest China due to the topography and few stations, which are common reasons. The main sources of uncertainties in temperature prediction during this century are model uncertainty (before the 2090s) and scenario variability (after the 2090s), and model uncertainty in precipitation for CMIP6 becomes the main source of uncertainty. [ABSTRACT FROM AUTHOR]

We describe the bias adjustment and downscaling to a resolution of 1 × 1 km of daily temperature, precipitation and solar radiation of a multimodel ensemble of Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs with the local observational data set BhutanClim for Bhutan and an analysis of the results for 1996–2100. The GCMs were selected based on their ability to reproduce local temporal and spatial precipitation patterns, resulting in a total of 14 models for each shared socioeconomic pathway (SSP). The results are shown for five global warming levels (GWLs) 1.5, 2, 3, 4 and 5°C, providing insight into the projected impacts of climate change at different warming levels. The daily temperature and precipitation data are publicly available, which is of great benefit for climate impact studies, such as ecological, hydrological or infrastructure‐related studies. In this paper, we discuss showcase climate indicators. Peak‐over‐threshold climate indicators such as hot days above 30°C are relevant for human health. In the capital city of Thimphu, these are currently rare, at 4 days per year, but might increase to more than 80 for GWL5.0. Precipitation increases in the summer months, but slightly decreases in the drier winter months. Accordingly, the 3‐month SPEI drought index is projected to increase in summer, but strongly decreases in the winter months, mostly pronounced in February. The increasing severity of late‐winter and spring droughts might have a negative impact on vegetation, wildfires and water supply. [ABSTRACT FROM AUTHOR]

With its focus on the species level of the Anthropos, there is growing concern that the Anthropocene analytic lacks the conceptual nuance needed to grapple with the unevenly distributed harms and responsibilities tied up with issues of biodiversity loss, global warming, and land use change. Conceptual variants like the patchy Anthropocene have been proposed to better capture the justice implications of these socio‐ecological crises, directing attention to their spatially ubiquitous yet context‐specific character. The figure of the plantation has come to play an important role in this scholarship due to the contribution intensive agriculture had made to these interlinking crises. Through empirical study of the regenerative agricultural movement, this paper reflects on how regenerative farmers use different sites (fields, soils, livestock stomachs) to apprehend their agro‐ethical responsibilities to more‐than‐human actors both near to and far from the landscapes they manage. Our aims here are two‐fold. First, we provide a more affirmative account of agricultural management than is currently offered by plantation farming: a model of food production that is not just 'in' the Anthropocene, but 'for' it. Second, we contribute to ongoing discussions unfolding in the social sciences around the tools needed to conceptualise the interlinking spatial and justice aspects of the Anthropocene transition. By bringing the patchy analytic into conversation with more established geographic writing on scale, volume, and horizontal connections, we show the merit of juxtaposing multiple models of spatial relation as a way of gaining ethical and conceptual traction on complex socio‐ecological issues. We argue that the 'polymorphic' spatial imaginaries of regenerative agriculturalists can offer some guidance on the tools needed to attend to the specificity of local Anthropocene outcomes in relation to socio‐ecological forces actuating the world at much greater spatio‐temporal scales. [ABSTRACT FROM AUTHOR]

The cloud feedback may result in amplification or damping of Arctic warming. Two common techniques used to diagnose the top‐of‐the‐atmosphere cloud feedback are the Adjusted Cloud Radiative Effect (AdjCRE) method and the Cloud Radiative Kernel (CRK) method. We apply both to CMIP5 and CMIP6 model data, finding that the AdjCRE calculated Arctic shortwave cloud feedback is twice as correlated with sea ice loss in CMIP5, and four times in CMIP6, as the CRK method. We find that the CRK method produces Arctic all‐sky residual percentages exceeding 20% in 15 of 18 models. We use the CRK method to decompose the feedback in CMIP5 and CMIP6 finding that its median value changed from negative to positive driven by a less‐negative cloud optical depth feedback. Despite its lack of closure, we conclude that the CRK method is better suited for Arctic SW feedbacks as it is less impacted by surface albedo changes. Plain Language Summary: The cloud feedback is the process by which cloud property changes in a warming climate can either further enhance warming or damp it. The Arctic is warming faster than the rest of the globe, and one of the largest sources of uncertainty in its climate projections is the cloud feedback. There are two popular methods to calculate the cloud feedback: the Adjusted Cloud Radiative Effect technique, and the Cloud Radiative Kernel technique. In this paper we compare the two methods in a suite of climate models by considering the extent to which changes in Arctic sea ice impact the cloud feedbacks. From this analysis we conclude that the Cloud Radiative Kernel method is less affected by sea ice loss. We then apply the Cloud Radiative Kernel technique to data from the two most recent generations of global climate models to investigate how polar day Arctic cloud feedbacks have changed between these generations. We find that the median value of these Arctic feedbacks is slightly positive in the newest generation of models, a change from slightly negative in the previous generation that is largely fueled by a weakening of the feedback associated with changes in cloud optical depth. Key Points: The Cloud Radiative Kernel method is less sensitive to surface albedo changes than the Adjusted Cloud Radiative Effect techniqueThe Cloud Radiative Kernel method provides poor radiative closure in a suite of global climate modelsThe median shortwave Arctic cloud feedback in recent climate models is slightly positive due to a weakened cloud optical depth feedback [ABSTRACT FROM AUTHOR]

The uneven changes in potential evapotranspiration (PET) in response to temperature rise are called the 'evapotranspiration paradox' phenomenon, which is expected to intensify further under a warming climate. In this paper, we explored the spatial–temporal changes in the future 'evapotranspiration paradox' phenomenon over China and its 10 major river sub‐regions under different climate change scenarios. Thus, this paper uses four global climate model outputs under seven shared socioeconomic pathway‐based scenarios (SSP1‐1.9, SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, SSP4‐3.4, SSP4‐6.0 and SSP5‐8.5) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Considering the latest IPCC's 6th Assessment Report (AR6), this research emphasizes the 2021–2040 (near‐term), 2041–2060 (mid‐term) and 2081–2100 (long‐term) periods to anticipate the 'evapotranspiration paradox' phenomenon. In this study, PET is estimated based on the modified Penman–Monteith (P‐M) method (considering CO2). Furthermore, the paradox phenomenon in this study is defined considering two pivotal conditions: the surface temperature increases but the evaporation decreases (Type I), and the temperature decreases but the evaporation still tends to increase (Type II). The results show that there were only Type I 'evapotranspiration paradoxes' that existed in the historical period, which were dominant especially before the 1990s. Nearly 50% of the areas experienced the Type I 'evapotranspiration paradox' phenomenon that occurred during 1975–1994 and 1995–2014. Spatially, it covered 100% of the area of the Southeast River (SER) and the Liaohe River (LR) during 1975–1994 and the area of the SER, the HAR, the HHR and the LR during 1995–2014. In the future, the interdecadal growth rate of PET in China is projected to be the highest under the SSP5‐8.5 and the lowest under the SSP3‐7.0 with spatial variation. Importantly, the largest areas of approximately 36% and 45% with the Type I phenomenon are inclined to occur under the SSP1‐1.9 and SSP4‐6.0, respectively, over the long‐term period (2081–2100). The area with the Type I phenomenon will be less than 20% in the near‐term, and it is less than 12% in the mid‐term period. For the Type II evapotranspiration paradox, the uppermost 45% of the area is expected to experience the Type II phenomenon under SSP1‐1.9 during the mid‐term period, while it is 30% under SSP1‐2.6 during the long‐term period. However, this study's findings provide the scientific basis for formulating adaptation and mitigation strategies to combat 'evapotranspiration paradox'‐related extremes at regional scales. [ABSTRACT FROM AUTHOR]

Scafetta (2022, https://doi.org/10.1029/2022gl097716) purports to test Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models through a comparison of temperature changes over three decades. Unfortunately, the paper contains numerous conceptual and statistical errors that undermine all of the conclusions. First, no uncertainty is given for the observational temperature difference, making it impossible to assess compatibility with any model result. Second, the CMIP6 data are the ensemble means for each model, but the metric being tested is sensitive to the internal variability and so the full ensemble for each model must be used. When this is corrected, the conclusion that "all models with ECS > 3.0°C overestimate the observed global surface warming" is not sustained. Third, the statistical test in Section 2 would reject all models even in a perfect model setup given sufficient ensemble members, thus the second conclusion "that spatial t‐statistics rejects the data‐model agreement" is also not sustainable. Plain Language Summary: Comparisons of models and observations need to account from multiple sources of uncertainty in both the observations and due to the chaotic dynamics of the weather. The analyses in Scafetta (2022, https://doi.org/10.1029/2022gl097716) do not take either of these issues into account and thus the conclusions in that paper are not supportable. Key Points: Scafetta (2022) contains errors in both of the statistical tests used that make the conclusions unsupportable [ABSTRACT FROM AUTHOR]

Summary: The dedication of the international anaesthetic community to reducing the environmental impact of healthcare is important and to be celebrated. When this is underpinned by robust science, it has the potential to make a real difference. However, volatile anaesthetic agents have been widely promoted in the medical literature as damaging to the climate, leading to a drive to remove them from clinical practice. This is based on notional 'CO2‐equivalent' values created using the simple emission metric known as the global warming potential. Here, we assert that when proper consideration is given to the science of climate change, volatile anaesthetic gas emissions cannot be simply equated to real carbon dioxide emissions, and that their climate impact is vanishingly small. This paper gives anaesthetists a framework to make informed choices founded on climate science and calls for attention to be refocused on the urgent need to reduce the real carbon dioxide emissions associated with healthcare. [ABSTRACT FROM AUTHOR]

This paper examines the changes of El Niño–Southern Oscillation (ENSO) associated winter rainfall relationship in Southeast Asia (SEA) in the historical period (1981–2010) and future period (2071–2100) based on the Coupled Model Intercomparison Project Phase 6 (CMIP6) models simulations. Twenty general circulation models (GCMs) are chosen from the Scenario Model Intercomparison Project (ScenarioMIP) highest emission scenario—Shared Socioeconomic Pathway (SSP) 5‐8.5. This study focuses only on the GCMs that have been able to replicate the consistent associated patterns observed, referred to as "teleconnection‐consistent models" (TCMs). During historical period, ENSO has significant negative association with SEA winter rainfall, particularly over Indochina mainland, Maritime Continent (MC) and northern Borneo. The significant negative‐associated teleconnection affected area has increased under future climate, particularly over southern part of South China Sea (SCS). The weakening of south westerlies at Western North Pacific (WNP) centred near 20°N reduces the moisture transport from Indochina into south of China, increase the negative correlated affected area in the SEA regions above equator. The northeasterlies/easterlies that prevailed from the WNP anticyclone (AC) brings significant moisture flux into southern Borneo, causing increment of significant positive‐associated moisture flux convergence to that region. The weakening of upward motion in TCM results in less warm and moist air rising over SEA MC, reducing the rainfall availability. The 1° eastward expansion of WC downward branch eastern edge leads to suppression of convective activities, increasing the dry affected area. The results suggest that the ENSO has a larger influence on the negative‐associated SEA rainfall and atmospheric circulation in the December–January–February (DJF) late‐21st century when compared to the 1980–2010. [ABSTRACT FROM AUTHOR]

To investigate the relative contributions of current vs. historical factors in explaining broad-scale diversity gradients using a combination of contemporary factors and a quantitative estimate of the temporal accessibility of areas for recolonization created by glacial retreat following the most recent Ice Age. The part of the Nearctic region of North America that was covered by ice sheets during the glacial maximum 20 000 BP. We used range maps to estimate the species richness of mammals and terrestrial birds in 48 400 km2 cells. Current conditions in each cell were quantified using seven climatic and topographical variables. Historical conditions were estimated using the number of years before present when an area became exposed as the ice sheets retreated during the post-Pleistocene climate warming. We attempted to tease apart contemporary and historical effects using multiple regression, partial regression and spatial autocorrelation analysis. A measure of current energy inputs, potential evapotranspiration, explained 76–82% of the variance in species richness, but time since deglaciation explained an additional 8–13% of the variance, primarily due to effects operating at large spatial scales. Because of spatial covariation between the historical climates influencing the melting of the ice sheet and current climates, it was not possible to partition their effects fully, but of the independent effects that could be identified, current climate explained two to seven times more variance in richness patterns than age. Factors acting in the present appear to have the strongest influence on the diversity gradient, but an historical signal persisting at least 13 000 years is still detectable. This has implications for modelling changes in diversity patterns in response to future global warming. [ABSTRACT FROM AUTHOR]

Summary: Potato is a tuber that, due to its great variety, is available in the markets all year round. Moreover, it is a widely consumed product worldwide on the account of its affordability and versatility. Therefore, studying it in depth is significant from not only a nutritional or economic point of view, but also for considering its potential environmental impact. In this paper, a Life Cycle Assessment (LCA) model is developed to assess the environmental impact of a model 5 kg bag of fresh washed potatoes. It considers all phases of potato processing, from the time the potato enters the facility until it leaves the gate (gate‐to‐gate LCA). The phase of the process with the greatest environmental impact is the cleaning and classification phase, mainly due to the significant consumption of water used in the cleaning process. The general consumption and storage phases are also relevant environmental impact phases to consider. In the case of these phases, the electricity consumption resulting from the operation of the facilities and product cooling is particularly noteworthy. After establishing the critical points, based on the environmental impact perspective, this paper proposes three measures to reduce the environmental impact of the process. The application of these three measures would reduce the environmental impact by 40% in environmental impact categories such as acidification or by 32% in the global warming category. [ABSTRACT FROM AUTHOR]

From mother nature and carbon footprints to greenhouse gasses and the race against global warming, popular discourse on environmental issues is saturated with metaphor. Some people view these metaphors as obfuscating or ineffective, while others believe they are crucial for improving climate communications and environmental attitudes. In this paper, we provide a systematic overview and evaluation of the use of English metaphors in Anglo environmental discourse, drawing on a range of empirical and popular media sources. We begin by discussing the role of metaphor in language in thought. Next, we introduce a range of metaphors used to frame discussions of (1) our relationship to nature (e.g., the earth is our common home), (2) our impact on the environment (e.g., we are knocking the climate off balance), and (3) how we should address this impact (e.g., reduce our ecological footprint). We classify these metaphors along several dimensions, including how conventional they are, how systemic they are, how emotionally impactful they are, and how aptly they capture the topics they are used to describe. From this analysis, we derive several promising candidate metaphors that may help increase public understanding and engagement with environmental issues. However, we note that such claims must be tested empirically in future research; currently, there are few large, systematic, replicable experiments in the literature assessing the impact of environmental metaphors. We conclude by offering general recommendations for using metaphors in communications about climate change and sustainability. This paper provides a systematic overview and evaluation of the use of metaphors in environmental discourse. Our analysis illuminates how certain metaphors could help increase public understanding of and engagement with issues like climate change and sustainability. [ABSTRACT FROM AUTHOR]

A reference or "no‐feedback" radiative response to warming is fundamental to understanding how much global warming will occur for a given change in greenhouse gases or solar radiation incident on the Earth. The simplest estimate of this radiative response is given by the Stefan‐Boltzmann law as −4σTe‾3≈−3.8 ${-}4\sigma {\overline{{T}_{e}}}^{3}\approx -3.8$ W m−2 K−1 for Earth's present climate, where Te‾ $\overline{{T}_{e}}$ is a global effective emission temperature. The comparable radiative response in climate models, widely called the "Planck feedback," averages −3.3 W m−2 K−1. This difference of 0.5 W m−2 K−1 is large compared to the uncertainty in the net climate feedback, yet it has not been studied carefully. We use radiative transfer models to analyze these two radiative feedbacks to warming, and find that the difference arises primarily from the lack of stratospheric warming assumed in calculations of the Planck feedback (traditionally justified by differing constraints on and time scales of stratospheric adjustment relative to surface and tropospheric warming). The Planck feedback is thus masked for wavelengths with non‐negligible stratospheric opacity, and this effect implicitly acts to amplify warming in current feedback analysis of climate change. Other differences between Planck and Stefan‐Boltzmann feedbacks arise from temperature‐dependent gas opacities, and several artifacts of nonlinear averaging across wavelengths, heights, and different locations; these effects partly cancel but as a whole slightly destabilize the Planck feedback. Our results point to an important role played by stratospheric opacity in Earth's climate sensitivity, and clarify a long‐overlooked but notable gap in our understanding of Earth's reference radiative response to warming. Plain Language Summary: Earth's climate is stable because a warmer planet loses more energy to space, at infrared wavelengths invisible to the naked eye. The rate of change of this energy loss as the planet warms provides an estimate how Earth's energy balance responds to warming, which is simple enough to write on a small piece of paper. When scientists investigate the warming predicted by climate models, they often start from a similar but not identical calculation of how Earth's energy balance responds to warming. This calculation, based on model output, is about 15% less stabilizing than the simple pencil‐and‐paper estimate. In this paper, we explore the causes of this 15% difference between the pencil‐and‐paper estimate and the calculations using climate models. We show that the difference is primarily caused by the lack of assumed warming in climate models high in Earth's atmosphere, where temperatures are not closely linked to surface warming. This lack of warming acts as a hidden destabilizing feedback in current analysis of climate models. Key Points: Earth's reference radiative response, or "Planck feedback," is ∼0.5 W m−2 K−1 less stabilizing than a Stefan‐Boltzmann estimateWe find this deviation is mostly due to the assumed lack of stratospheric warming in calculations of the Planck feedbackThe lack of stratospheric warming serves as an implicit positive feedback in analysis of climate model warming [ABSTRACT FROM AUTHOR]

As small poikilotherms, insects are largely dependent on their environment for thermoregulation and so are particularly vulnerable to changing temperatures.Butterflies are a well‐studied group often used as models to investigate insect responses to temperature. However, little has been done to synthesise and present this large volume of literature in an accessible format, particularly with reference to knowledge gaps and areas rich in information. Using a systematic mapping method, we synthesised the last 40 years of research on the topic of butterfly responses to temperature.We identified and coded 451 research papers, in which butterfly species were studied 3198 times. We identified taxonomic groups, regions and experimental designs that were well or poorly represented.We found that there was a relatively good balance of representation across butterfly families in relation to the number of species within each family. The tropics were less frequently studied than temperate regions, and there were more studies reporting outcomes on adults than at any other life stage. Finally, in situ studies were more common than ex situ studies.Taken together, the higher representation of certain regions, life stages and approaches could lead to an incomplete understanding of the impacts of temperature on butterflies, potentially resulting in ill‐informed decisions.We make suggestions for how to resolve these discrepancies in representation, including calling for an increased focus on the tropics, the establishment of butterfly monitoring schemes in the global south, a greater focus on the effects of temperature on non‐adult life stages, an increase in experiments investigating fluctuating thermal regimes and the incorporation of more behavioural responses to temperature in future research. Only by addressing these disparities can we gain a complete understanding of how butterflies will respond to climate change. [ABSTRACT FROM AUTHOR]

The onset of periods with very high or low air temperatures has aroused general interest for a long time, which is understandable since it has many dangerous effects directly affecting humans. Such perilous climatic phenomena include exceptionally cold and exceptionally warm months, which this study investigates for all Europe and for its five physico‐geographic regions over the 190‐year period of 1831–2020. Therefore, the research in this paper includes two periods characteristic of the history of climate – the late Little Ice Age (LIA) and present‐day warming. The studies are based on average monthly air temperature values from 40 weather stations in Europe. In this paper, exceptionally cold months (ECMs) or exceptionally warm months (EWMs) are considered to have occurred when the average air temperature at a station differed from the respective long‐term average by at least two standard deviations. The highlights of the study include the identification of a drop in the number of ECMs by 20 over the entire 190‐year period, and a highly statistically significant increase in EWMs by 44 between 1980 and 2020. These changes proceeded with different intensities from one physico‐geographic region of Europe to another. [ABSTRACT FROM AUTHOR]

Numerical weather prediction is pushing the envelope of grid resolution at local and global scales alike. Aiming to model topography with higher precision, a handful of articles introduced unstructured vertical grids and tested them for dry atmospheres. The next step toward effective high‐resolution unstructured grids for atmospheric modeling requires that also microphysics is independent of any vertical columns, in contrast to what is ubiquitous across operational and research models. In this paper, we present a non‐column based continuous and discontinuous spectral element implementation of Kessler's microphysics with warm rain. We test the proposed algorithm against standard three‐dimensional benchmarks for precipitating clouds and show that the results are comparable with those presented in the literature across all of the tested effective resolutions. While presented for both continuous and discontinuous spectral elements in this paper, the method that we propose can be adapted to any numerical method used in other codes, as long as the code can already handle vertically unstructured grids. Plain Language Summary: The earth climate is warming faster than ever. While climate models are the tool available to scientists to forecast its future evolution, they are biased by uncertainties that are, arguably, mostly embedded in the modeling of clouds. Thanks to the advent of exascale computing, a reduction of cloud modeling uncertainties can be expected by simulating clouds at higher and higher resolutions. While uniform high resolution across the whole domain is ideal, for computational efficiency reasons scientists are likely to increase the model resolution in some regions more than others not only in the horizontal direction—which is a standard approach—but also along the vertical direction. Grid refinement in the vertical direction, however, may lead to the loss of the vertical structure of the grid columns, affecting the usability of column‐based physics packages that are used to model clouds and precipitation. To overcome this problem, we present an algorithm to solve the equations that model precipitating clouds along arbitrarily shaped grids in any spatial direction. This approach is advantageous from a modeling perspective as well as from a computational one because it allows full flexibility of the domain partitioning algorithms when hundreds of thousands of parallel processors are used. Key Points: A non‐column based spectral element approach to model precipitating clouds is presentedThe approach can be easily applied to any microphysics scheme with and without precipitationThis approach will make full physics simulations of the atmosphere on unstructured grids possible [ABSTRACT FROM AUTHOR]

General circulation models (GCMs) are developed to simulate the past climate and generate future climate predictions. In the context of global warming, their important roles in identifying possible solutions to water resources planning/management are recognized by the world. However, in actual and regional implementation, due to many factors like initial and boundary conditions, parameters and model structures and so forth, there are great variabilities and uncertainties across the future climate projections of GCMs outputs, which has attracted criticism from water resources planners. Thus, the GCMs usually must be evaluated for assessing their performances in simulating the historical observations. Currently, there are many different conclusions and opinions as to whether the optimal individual model is more advantageous or whether the combined consideration of MME works better. The purpose of this paper is to compare the advantages and disadvantages between the selection of the optimal single GCM and multi‐model ensemble (MME) based on one of the more objective selection methods called TOPSIS. The results show that the performances of GCMs in simulating precipitation and temperature in different climate subregions over China are not identical. For CMIP6 GCMs simulations, the optimal precipitation GCM is CMCC‐CM2‐SR5 for EC, MIROC6 for SC, SWC and NWC, CESM2‐WACCM for NC and NEC, and FGOALS‐g3 for QTP. As for temperature, only NESM3 and BCC‐ESM1 are the optimal GCM for QTP and NWC, respectively; in other subregions, MME is better than single GCM. In general, a simple arithmetic averaging approach employed to generate the MME model is not superior to the optimal GCM, although the error metric with the observed data is reduced, at the cost of a severe compression of the interannual variability. [ABSTRACT FROM AUTHOR]

Single‐model initial‐condition large ensembles are powerful tools to quantify the forced response, internal climate variability, and their evolution under global warming. Here, we present the CMIP6 version of the Max Planck Institute Grand Ensemble (MPI‐GE CMIP6) with currently 30 realizations for the historical period and five emission scenarios. The power of MPI‐GE CMIP6 goes beyond its predecessor ensemble MPI‐GE by providing high‐frequency output, the full range of emission scenarios including the highly policy‐relevant low emission scenarios SSP1‐1.9 and SSP1‐2.6, and the opportunity to compare the ensemble to complementary high‐resolution simulations. First, we describe MPI‐GE CMIP6, evaluate it with observations and reanalyzes and compare it to MPI‐GE. Then, we demonstrate with six application examples how to use the power of the ensemble to better quantify and understand present and future climate extremes, to inform about uncertainty in approaching Paris Agreement global warming limits, and to combine large ensembles and artificial intelligence. For instance, MPI‐GE CMIP6 allows us to show that the recently observed Siberian and Pacific North American heatwaves would only avoid reaching 1–2 years return periods in 2071–2100 with low emission scenarios, that recently observed European precipitation extremes are captured only by complementary high‐resolution simulations, and that 3‐hourly output projects a decreasing activity of storms in mid‐latitude oceans. Further, the ensemble is ideal for estimates of probabilities of crossing global warming limits and the irreducible uncertainty introduced by internal variability, and is sufficiently large to be used for infilling surface temperature observations with artificial intelligence. Plain Language Summary: Climate model simulations that start from different initial states and differ only due to the chaos in the climate system are used extensively to quantify the forced climate response, variability intrinsic to the climate system, and their change under global warming. Here, we present a new version of the Max Planck Institute Grand Ensemble (MPI‐GE CMIP6) that is run as part of the latest generation of climate models. This single‐model ensemble currently consists of 30 realizations for the historical period 1850–2014 and for five scenarios of possible future climates until 2100. The power of MPI‐GE CMIP6 goes beyond its predecessor by not only providing monthly mean but also 3‐hourly to daily model output, the full range of future scenarios including the two highly policy‐relevant scenarios that were designed to match the Paris Agreement global warming limits of 1.5 and 2°C, and the opportunity to compare the low‐resolution ensemble to simulations of the same model version with higher horizontal resolution. In this paper, we describe the new ensemble and demonstrate with application examples how to use its power. Key Points: The Max Planck Institute Grand Ensemble in its CMIP6 version (MPI‐GE CMIP6) is a 30‐member initial‐condition large ensemble with up to 3‐hourly model output and five emission scenariosThe ensemble is specifically suited to investigate climate extremes and Paris Agreement global warming limitsMPI‐GE CMIP6 adequately represents heat extremes, while precipitation extremes are captured by complementary high‐resolution simulations [ABSTRACT FROM AUTHOR]

The long‐known, widely documented inverse relationship between body size and environmental temperature ("temperature‐size rule") has recently led to predictions of body size decline following current climatic warming ("size shrinking effect"). For keystone pollinators such as wild bees, body shrinking in response to warming can have significant effects on pollination processes but there is still little direct evidence of the phenomenon because adequate tests require controlling for confounding factors linked to climate change (e.g., habitat change). This paper assesses the shrinking effect in a community of solitary bees from well‐preserved habitats in the core of a large nature reserve experiencing climatic warming without disturbances or habitat changes. Long‐term variation in mean body mass was evaluated using data from 1704 individual bees (137 species, 27 genera, 6 families) sampled over 1990–2023. Climate warmed at a fast rate during this period, annual mean of daily maximum temperature increasing 0.069°C/year on average during 2000–2020. Changes in bee body mass verified expectations from the size shrinking effect. The mean individual body mass of the community of solitary bees declined significantly, irrespective of whether the analysis referred to the full species sample or only to the subset of species that were sampled in both the old (1990–1997) and recent (2022–2023) periods. On average, body mass declined ~0.7%·year−1, or an estimated average cumulative reduction of ~20 mg per individual bee from 1990 to 2023. Proportional size reduction was greatest among large‐bodied species, ranging from around −0.6%·year−1 for the smallest species to −0.9%·year−1 for the largest ones. Declining rate was steeper for cavity‐nesting than ground‐nesting species. The pollination and mating systems of bee‐pollinated plants in the study region are probably undergoing significant alterations as a consequence of supra‐annual decline in bee body mass. [ABSTRACT FROM AUTHOR]

In response to global warming, ozone is predicted to increase aloft due to stratospheric cooling but decrease in the tropical lower stratosphere. The ozone reductions have been primarily attributed to a strengthening Brewer‐Dobson circulation, which upwells ozone‐poor air. Yet, this paper finds that strengthening upwelling only explains part of the reduction. The reduction is also driven by tropospheric expansion under global warming, which erodes the ozone layer from below, the low ozone anomalies from which are advected upwards. Strengthening upwelling and tropospheric expansion are correlated under global warming, making it challenging to disentangle their relative contributions. Therefore, chemistry‐climate model output is used to validate an idealized model of ozone photochemistry and transport with a tropopause lower boundary condition. In our idealized decomposition, strengthening upwelling and tropospheric expansion both contribute at leading order to reducing tropical ozone. Tropospheric expansion drives bottom‐heavy reductions in ozone, which decay in magnitude into the mid‐stratosphere. Plain Language Summary: The ozone layer absorbs ultraviolet light otherwise harmful to life. Due to compliance with the Montreal Protocol, the ozone layer is generally recovering from depletion. But, at the same time, global warming is predicted to impact ozone, increasing ozone in the upper stratosphere and decreasing ozone in the tropical lower stratosphere. These decreases are typically argued to result from a strengthening of tropical stratospheric upwelling under global warming. Yet, this paper shows that in addition to contributions from strengthening upwelling, much of the ozone loss arises from a deepening of the troposphere under global warming. The deepening of the troposphere erodes the ozone layer from below, with the low ozone anomalies in the eroded region subsequently transported upwards by the background upwelling. Deepening of the troposphere therefore helps to explain the predicted ozone reductions throughout the tropical lower stratosphere. Key Points: Global warming reduces ozone in the tropical lower stratosphere, an effect typically attributed to strengthening stratospheric upwellingYet, global warming also deepens the troposphere, which erodes the ozone layer and reduces transport of ozone into the lower stratosphereAlong with strengthening upwelling, tropospheric expansion contributes at leading order to reductions in tropical lower stratospheric ozone [ABSTRACT FROM AUTHOR]

Blooms of various types of seaweeds have been reported worldwide, with recent expansions in surface waters. While most of the expansions have been attributed to eutrophication due mainly to human activities, any potential role of climate change is unclear. Here we show that, in the East China Sea and Yellow Sea, increased biomass of Sargassum horneri (S. horneri, brown seaweed) from 2000 to 2021 appears to be caused primarily by ocean warming, as S. horneri prefers a certain temperature range to grow. In contrast, while increases of Ulva prolifera (U. prolifera, green seaweed) in the same regions might also be related to ocean warming, during the same period, human activities such as coastal aquaculture or seaweed mitigation may muddle such effects. With the projected ocean warming in the next decades, we hypothesize that S. horneri blooms may occur earlier during the year and may continue to expand in the future. Plain Language Summary: Seaweed macroalgae blooms have been reported around the world in the last two decades, yet the exact reasons are often unclear. This paper attempts to solve this puzzle for the Sargassum and Ulva seaweeds in the East China Sea and Yellow Sea using long‐term observations and laboratory‐based seaweed physiology measurements. The paper shows not only how seaweeds have expanded in the two marginal seas in the past four decades, but also how a warming ocean (due to climate variability) and nutrient enrichment (due mainly to human activities) controlled such expansions. Among 63 large marine ecosystems (LMEs) in the world, the East China Sea (where seaweeds expanded) is one of the three LMEs that experienced "super‐fast" warming. Given the IPCC‐projected seawater temperature rise of 1.6°C by 2050, will these seaweeds continue to expand? Key Points: Multi‐sensor satellite data show significant and near‐synchronized expansions of Sargassum horneri and Ulva prolifera in the past 38 yearsOcean warming appears to be a main factor behind the recent expansions of S. horneri because of its physiological requirementOcean warming may also play a role in U. prolifera expansions, but the effect appears confounded by human mitigation efforts [ABSTRACT FROM AUTHOR]

This paper presents the response to anthropogenic forcing in the GISS‐E2.1 climate models for the 21st century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The experiments were performed using an updated and improved version of the NASA Goddard Institute for Space Studies (GISS) coupled general circulation model that includes two different versions for atmospheric composition: A non‐interactive version (NINT) with prescribed composition and a tuned aerosol indirect effect and the One‐Moment Aerosol model (OMA) version with fully interactive aerosols which includes a parameterized first indirect aerosol effect on clouds. The effective climate sensitivities are 3.0°C and 2.9°C for the NINT and OMA models, respectively. Each atmospheric version is coupled to two different ocean general circulation models: The GISS ocean model (E2.1‐G) and HYCOM (E2.1‐H). We describe the global mean responses for all future scenarios and spatial patterns of change for surface air temperature and precipitation for four of the marker scenarios: SSP1‐2.6, SSP2‐4.5, SSP4‐6.0, and SSP5‐8.5. By 2100, global mean warming ranges from 1.5°C to 5.2°C relative to 1,850–1,880 mean temperature. Two high‐mitigation scenarios SSP1‐1.9 and SSP1‐2.6 limit the surface warming to below 2°C by the end of the 21st century, except for the NINT E2.1‐H model that simulates 2.2°C of surface warming. For the high emission scenario SSP5‐8.5, the range is 4.6–5.2°C at 2100. Due to about 15% larger effective climate sensitivity and stronger transient climate response in both NINT and OMA CMIP6 models compared to CMIP5 versions, there is a stronger warming by 2100 in the SSP emission scenarios than in the comparable Representative Concentration Pathway (RCP) scenarios in CMIP5. Changes in sea ice area are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with the largest sea ice area decreases occurring during September in the Northern Hemisphere in both E2.1‐G (−1.21 × 106 km2/°C) and E2.1‐H models (−0.94 × 106 km2/°C). Both coupled models project decreases in the Atlantic overturning stream function by 2100. The largest decrease of 56%–65% in the 21st century overturning stream function is produced in the warmest scenario SSP5‐8.5 in the E2.1‐G model, comparable to the reduction in the corresponding CMIP5 GISS‐E2 RCP8.5 simulation. Both low‐end scenarios SSP1‐1.9 and SSP1‐2.6 also simulate substantial reductions of the overturning (9%–37%) with slow recovery of about 10% by the end of the 21st century (relative to the maximum decrease at the middle of the 21st century). Plain Language Summary: The projections of future climate change are uncertain because they are dependent on different possible scenarios of human‐caused emissions and their interaction with natural forcings, internal climate variability, and inter‐model differences. This paper presents the results of the climate model of the NASA Goddard Institute for Space Studies, GISS‐E2.1, for the anthropogenically forced climate response for the twenty first century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The sensitivity of the model response to different magnitudes of anthropogenic forcings in the twenty‐first‐century scenarios were performed using two different versions for the atmospheric composition and two different ocean general circulation models. Compared to CMIP5 GISS‐E2 versions, the CMIP6 GISS‐E2.1 climate model shows a stronger warming by 2100 in comparable scenarios due to larger effective climate sensitivity and transient climate response. Both climate models with two different ocean components project decreases in the Atlantic overturning stream function by 2100. Key Points: GISS E2.1 model with different configurations is used to carry out 134 Shared Socioeconomic Pathway (SSP) experimentsGISS‐E2.1 climate model shows a stronger warming by 2,100 in comparable Representative Concentration Pathway scenarios in CMIP5 due to larger effective climate sensitivity and stronger transient climate responseBoth coupled models, E2.1‐G and E2.1‐H, project decreases in the Atlantic overturning stream function by 2100 with the largest decrease in the warmest scenario SSP5‐8.5 in the E2.1‐G model [ABSTRACT FROM AUTHOR]

Cirrus clouds provide a significant radiative forcing on the Earth's climate system. This paper looks at the connection in space and time between monthly mean lightning activity observed from the Lightning Imaging Sensor on board the International Space Station, and the global monthly mean cirrus cloud cover obtained from the MERRA‐2 reanalysis product. The correlation coefficient between the global monthly mean cloud optical thickness of the cirrus clouds (clouds at altitudes above the 400 hPa pressure levels) with the monthly mean lightning flash counts is 0.84, implying that monthly mean lightning can explain 70% of monthly variability of the global high cloud optical thickness. In addition, lightning amount explains nearly 60% of the monthly mean global area coverage of cirrus clouds. Given these statistically significant connections between lightning and cirrus clouds, we propose using global lightning data as an additional tool for monitoring monthly variability of cirrus clouds. Plain Language Summary: Cirrus clouds are one of the most important components maintaining the Earth's radiation budget. They reflect shortwave radiation from the Sun while absorbing the longwave radiation from the Earth. The net cloud radiative forcing for cirrus clouds results a warming of the climate. More/less cirrus clouds result in more/less warming of the planet. The moisture for the formation of cirrus clouds in the upper atmosphere is transported there in large part via deep convective storms, many associated with lightning activity and hence defined as thunderstorms. An increasing in cirrus clouds in a warmer atmosphere will amplify the initial warming. We explored in this study the relationship between global cirrus cloud coverage and global lightning activity. The results of the research show that 60%–70% of the monthly variability in global cirrus clouds can be explained by mean global lightning activity. Key Points: Cirrus clouds are one of the essential components in the atmosphere, with many important feedbacks on the radiation balance of EarthMonthly mean lightning can explain 70% of the monthly variability of the global high cloud optical thicknessLightning explains nearly 60% of the monthly mean global area coverage of cirrus clouds [ABSTRACT FROM AUTHOR]

Solar energy is the basic source of renewable energy, and it is being used for controlling global pollution/warming. As the Cross nanofluid is very useful for cooling solar devices, in this paper analysis of the global warming effect is investigated by incorporating the nonlinear thermal radiation over the exponentially extendable surface because it plays a major role related to solar energy absorption of nanofluid. Furthermore, the mathematical modeling of Cross nanofluid involving magnetic effect and diffusion is discussed by using the fact of chemical reaction. Chemical reaction finds astonishing applications in pollution studies, chemical processing equipment, and polymer production. As a result of this study, it is noticed that more magnetized conducting fluid controls the motion of fluids for both cases of shear thinning and shear thickening. Brownian motion parameter Nb affects the rate of the random motion of nanoparticles. Increased Nb temperature also increases due to these random movements of nanoparticles. That is the reason why pollutant nanoparticles spread in air as a result of global warming increase. [ABSTRACT FROM AUTHOR]

This paper introduces the key concepts of sustainability in the construction industry, together with a call for an urgent action to change the culture of all implied agents. The work presents an objective framework to evaluate sustainability through the analysis of the stages of the Integrated Life Cycle Assessment (ILCA). Such approach is applied to the global warming emissions indicator, and different aspects are investigated to support designers toward more sustainable designs. First, the principles for ILCA are introduced and sound values for the emissions of different structural materials are critically discussed and filtered taking into account the recently increased sensitivity to environmental aspects. On that basis, objective comparisons are presented for practical examples related to buildings and bridges. Specific design alternatives, based on the use of different materials and structural typologies, are also illustrated and compared to the original solution. The conclusions help the designer to identify which are the critical decisions leading to projects respectful of sustainability considerations. Specifically, material selection, structural efficiency, and a sound conceptual design are identified as the key aspects of sustainability. [ABSTRACT FROM AUTHOR]

As the climate system warms, megafires have become more frequent with devastating effects. A byproduct of these events is the creation of smoke plumes that can rise into the stratosphere and spread across the globe where they reside for many months. To gain a deeper understanding of the plume dynamics, global climate simulations of a megafire were performed at a wide range of grid spacings from 2.0° down to 7 km, including a 7 km nonhydrostatic experiment. The analysis focuses on how the resolved dynamics affects the specification of the plume characteristics such as injection height and black carbon (BC) mass. Prior studies initialize the smoke plume at one or a few grid points and this is shown here to produce severely dissipative dynamics. In order to validate such simulations with observations, enhancements of the plume characteristics to offset the dissipation is necessary. Using a numerically converged simulation, sensitivity tests show that to approximate the observed stratospheric lifetime, a reduction in BC fraction by 50% is necessary for external mixtures. The vorticity dynamics of the plume is also analyzed with a Lagrangian budget to understand the mechanisms responsible for the evolution of a collocated anticyclonic vortex. The results can be distilled down into a simple conceptual model. As the plume rises, the air diverges at the top of the updraft where the largest concentrations of smoke are found. This divergence induces a dilution of the background cyclonic absolute vorticity producing an anticyclonic vortex. Vortex decay occurs from opposite arguments. Plain Language Summary: Recently, there has been an increase in large and intense wildfires ("megafires") across the Earth in response to global warming. These megafire events produce large amounts of smoke that can rise high up in the atmosphere to a level well above clouds and weather. The smoke can stay at these high levels for long periods of time and spread across much of the Earth, which blocks sunlight from reaching the surface. It is important to understand the properties of these smoke plumes and how to correctly predict their consequences on human life. However, uncertainties in both observations and models make it difficult to achieve these goals. In particular, models contain various sources of uncertainty that can interact in complex ways. In this paper, we show that previous research has used a model grid spacing that does not sample the plume accurately, which leads to errors that affect the interpretation of the smoke properties, evolution of the plume and potential climatic effects. By choosing a model grid spacing that accurately samples the plume structure, the errors in the dynamics component of the model can be minimized, providing a baseline for reducing uncertainty in other parts of the system. Key Points: Simulations of megafire smoke plumes require fully resolved dynamics (∼8 Δx) in order to accurately characterize plume properties (e.g., black carbon [BC] fraction)For the 2017 British Columbia event, smoke injected at ∼12 km height requires a reduction in BC fraction by 50% to match observations for external mixturesAnalysis of the vorticity dynamics shows that smoke plume anti‐cyclonic vortices form (decay) due to the dilution (concentration) of cyclonic absolute vorticity [ABSTRACT FROM AUTHOR]

Tree diversity and species identity are known to play an important role in modulating forest productivity and its capacity to buffer the effects of climatic events. The FunDivEurope exploratory platform allowed us to analyse this modulating effect in a medium‐term time span, after an abrupt rise to a new stable level of the average summer temperature of ca 2°C, in Mediterranean forests in central Italy. This paper aims to answer the following questions: 1) did increasing temperature and drought events affect the growth of thermophilous deciduous forests? 2) Was this effect buffered in mixed stands compared to monocultures? 3) Did co‐occurring tree species with different ecological characteristics, from more mesophilous to more xerophilous, have different responses? In 2012 and 2017, wood cores were collected from 659 trees in 36 plots representative of thermophilous deciduous forests. The selected tree species were Castanea sativa, Ostrya carpinifolia, Quercus cerris, Quercus ilex and Quercus petraea. In the sampling plots, they were present in pure stands and mixtures from two to four species. After measuring annual rings on cores, chronologies of basal area increment were built, and inventory data were used to estimate tree growth. Results showed a strong reduction of growth, lasting at least 18 years, after the temperature rise. Tree diversity significantly reduced the growth drop after the sudden and stable rise in summer average temperature. Tree mixture effect on growth stability appeared to be dependent on the tree species present in the mixture. Temperature rise and associated drought events, even without changes in rainfall, are one of the main challenges that European forests will face in the current scenarios of climate change. Tree diversity can buffer the effects of climate change over periods of at least 15 years and should be considered in forest management plans. [ABSTRACT FROM AUTHOR]

Research at the biophysical level constitutes the main approach to study the path through which climate influences infectious diseases, but the influence of socioeconomic factors on climate change and the spread of infectious diseases also cannot be ignored. In the current context, with its emphasis on carbon emission reduction, countries have begun to adopt "total control and trading" methods to reduce greenhouse gas emissions. This paper is based on the monthly relevant data of various provinces and cities from 2015 to 2019, adds the moderating variable of "carbon emission trading volume" based on current research results, establishes a static model of unbalanced panel fixed effects and a dynamic panel model, and deeply analyzes the impact of climate change on infectious disease popularity and the moderating effect of the carbon trading market. The study found that climate warming, frequent precipitation, and shortened sunshine duration will lead to an increase in the number of infectious disease cases and that the "carbon emission trading volume" variable plays a negative role in the positive correlation between climate change (temperature/precipitation) and the number of infectious disease cases. There are seasonal differences, and the moderating effect in summer/autumn is more obvious than that in winter/spring. [ABSTRACT FROM AUTHOR]

Since the early 1990s the Pacific Walker circulation shows a multi‐decadal strengthening, which contradicts future model projections. Whether this trend, evident in many climate indices especially before the 2015 El Niño, reflects the coupled ocean‐atmosphere response to global warming or the negative phase of the Pacific Decadal Oscillation (PDO) remains debated. Here we show that sea surface temperature trends during 1980–2020 are dominated by three signals: a spatially uniform warming trend, a negative PDO pattern, and a Northern Hemisphere‐Indo‐West Pacific warming pattern. The latter pattern, which closely resembles the transient ocean thermostat‐like response to global warming emerging in a subset of CMIP6 models, shows cooling in the central‐eastern equatorial Pacific but warming in the western Pacific and tropical Indian Ocean. Together with the PDO, this pattern drives the Walker circulation strengthening in the equatorial band. Historical simulations appear to underestimate this pattern, contributing to the models' inability to replicate the Walker cell strengthening. Plain Language Summary: This paper investigates the observed changes in the tropical Pacific during the satellite era, including the recent decadal strengthening of the atmospheric zonal circulation—the Walker cell. We aim to understand the extent to which these changes represent a forced response to rising CO2 concentrations versus natural variability. We apply an approach in which we decompose the observed sea surface temperature trends into three components—a pattern associated with the Pacific Decadal Oscillation, which is part of natural variability, a uniform warming pattern, and a residual pattern. This residual pattern shows a remarkable resemblance to a forced ocean thermostat‐like transient response generated in some of the climate models, characterized by equatorial Pacific (EP) cooling, and a broad warming of the Northern Hemisphere, and the Indian Ocean and West Pacific. These results challenge studies arguing that the recent strengthening of the Pacific Walker cell can be explained simply by multi‐decadal natural variability in the tropics. Furthermore, the inability of climate models at large to fully capture this forced pattern with historical forcing puts into focus the reliability of future projections of climate change in the tropical Pacific, specifically the timing of emergence of the eastern EP warming. Key Points: A multi‐decadal strengthening of the Pacific Walker cell is observed in a wide range of indices, especially after 1990A Northern Hemisphere ‐ Indo West Pacific warming sea surface temperature pattern, which differs from the Pacific Decadal Oscillation, is evident since 1980This pattern resembles a forced response to abrupt CO2 forcing, emerging in a subset of climate models, and contributes to the Walker circulation strenthening [ABSTRACT FROM AUTHOR]

Global warming intensifies the hydrological cycle, which results in changes in precipitation regime (frequency and amount), and will likely have significant impacts on soil respiration (Rs). Although the responses of Rs to changes in precipitation amount have been extensively studied, there is little consensus on how Rs will be affected by changes in precipitation frequency (PF) across the globe. Here, we synthesized the field observations from 296 published papers to quantify the effects of PF on Rs and its components using meta-analysis. Our results indicated that the effects of PF on Rs decreased with an increase in background mean annual precipitation. When the data were grouped by climate conditions, increased PF showed positive effects on Rs under the arid condition but not under the semi-humid or humid conditions, whereas decreased PF suppressed Rs across all the climate conditions. The positive effects of increased PF mainly resulted from the positive response of heterotrophic respiration under the arid condition while the negative effects of decreased PF were mainly attributed to the reductions in root biomass and respiration. Overall, our global synthesis provided for the first time a comprehensive analysis of the divergent effects of PF on Rs and its components across climate regions. This study also provided a framework for understanding and modeling responses of ecosystem carbon cycling to global precipitation change. [ABSTRACT FROM AUTHOR]

Globally, treelines form a transition zone between tree‐dominated forest downslope and treeless alpine vegetation upslope. Treelines represent the highest boundary of "tree" life form in high‐elevation mountains and at high latitudes. Recently, treelines have been shifting upslope in response to climate warming, so it has become important to understand global tree diversity and treeline distributions. However, to the best of our knowledge, no global database on tree flora of treelines exists, which limits our capacity to undertake macroecological analyses. Here, for the first time, we present a global data set on the trees of the treeline ecotone, supported by an online ToTE database. We synthesized the database from 1202 studies published over the last 60 years (1962 to 2022) following the Preferred Reporting Items in Systematic Reviews and Meta‐Analysis (PRISMA) protocol. We classified the tree species in the database into three categories: treeline tree (TL) species, near to treeline (NTL) tree species, and tree species with an upper montane range limit (TUMR). The ToTE Version‐1 presents a total of 208 tree taxa, including 189 species, five subspecies, and 14 varieties, belonging to 54 genera and 26 families distributed across 34 mountain regions worldwide that either grow exactly at the treeline or have a range limit below the treeline. Of the total taxa, 155, 14, and 39 belong to TL, NTL, and TUMR, respectively. Genera such as Abies, Picea, Pinus, Larix, and Juniperus are more represented in the treeline tree category. On the other hand, Acer, Prunus, Populus, and Quercus have more representatives in the near to treeline category, whereas Erica, Nothofagus, and Polylepis contribute more tree species with an upper montane range limit. Furthermore, families such as Rosaceae and Pinaceae include trees that occur both at the treeline and with an upper montane range limit, whereas Sapindaceae includes trees that occur exclusively near to treeline. Our database also includes information on the global distribution patterns of treeline tree species richness across mountains and biomes. The mountains with the highest number of tree species are the Andes (39) followed by the Himalaya (37). Close to 67% of tree species show restricted distributions in different mountains, with the highest endemism in the Andes and the Himalaya. In terms of tree species distribution, Pinus sylvestris was widespread, with a distribution across nine mountain regions, followed by Picea glauca and Fagus sylvatica, both distributed across five mountain regions. In terms of species' distribution across biomes, the temperate biome harbors the highest treeline tree species richness (152 species), which may reflect the fact that the majority of studies are available from the temperate regions of the world. The remaining 56 species are distributed within five other biomes, with the least in dry tropical and subarctic (four species each). Furthermore, currently 40 treeline tree species fall under different International Union for Conservation of Nature threat categories. We anticipate that our database will help advance research on macroecological, biogeographic, evolutionary, climate‐change, and conservation aspects of the treeline on a global scale. The data are released under a Creative Commons Attribution 4.0 international license. Please cite this data paper when the data are reused. [ABSTRACT FROM AUTHOR]

Tokyo Bay is a semienclosed coastal system located in the center of Japan. Eutrophication has progressed since 1950, resulting in red tides and blue tides appearing frequently. This Data Paper reports the abundance of phytoplankton species sampled monthly from April 1998 to March 2019 at 17 stations in Tokyo Bay. Monitoring has been carried out by Chiba Prefectural Government. Phytoplankters were enumerated by microscopy as numbers of cells or colonies. The abundance of each species was expressed as cells per milliliter of seawater. The total cell density ranged from 102 to 106 cells·ml−1. The dominant taxa were diatoms, such as Chaetoceros spp., Skeletonema spp., and Thalassiosira spp. in most of the months. The dominant diatom species reached concentrations of 106 cells·ml−1. Microflagellates or Cryptomonadaceae were also abundant, especially in winter, reaching 106 cells·ml−1. These data can be used to appreciate how anthropogenic disturbances such as eutrophication and global warming affect the density and community composition of phytoplankton. The detailed Metadata for this abstract published in the Data Paper section of the journal is available in MetaCat in JaLTER at http://db.cger.nies.go.jp/JaLTER/metacat/metacat/ERDP-2021-03.1/jalter-en. [ABSTRACT FROM AUTHOR]

The magnitude and distribution of the ocean's biological pump (the downward flux of organic carbon (OC) from the ocean surface) influences the pCO2 of the atmosphere and the O2 content of the deep sea, but has not been well quantified. We determine this flux in the ocean's five subtropical gyres using upper‐ocean oxygen mass balance and measurements of T, S, and pO2 by autonomous profiling floats. Our results suggest that the biological OC pump is not globally uniform among the subtropical gyres: values in the North Pacific and Atlantic indicate distinct autotrophy (1–2 mol C m−2 yr−1) while near zero values in the S. Indian Ocean suggest the possibility of net heterotrophy. There is a correlation between the surface water iron/nitrate ratio and the magnitude of the biological pump suggesting an important role for nitrogen fixation in controlling the global distribution. Plain Language Summary: The ocean's biological pump is the most important natural flux controlling ocean and atmosphere carbon concentrations on decadal to millennial time scales, with a value that is fortuitously about the same as the present anthropogenic flux of carbon to the atmosphere. Understanding this flux is key to determining the marine carbon cycle feedback to global warming, but presently even the sign of this flux is debated in some subtropical ocean regions. This paper demonstrates how it is possible to determine the global value of the biological pump by remote measurements on autonomous profiling floats. Our findings suggest that the ocean's biological pump is very different in the subtropical northern and southern hemispheres probably because of the geographic variability of the flux of iron to the surface ocean. Key Points: The geographic distribution of the downward flux of biological organic carbon from the upper ocean (the ocean's biological pump) is uncertain and difficult to determine from observationsT, S, and pO2 measurements from 21 profiling floats in the world's subtropical oceans are interpreted in terms of the net biological oxygen production in the upper oceanThe measured net biological oxygen flux is higher in the northern hemisphere subtropics than in the southern subtropics and correlated with surface‐water iron concentration [ABSTRACT FROM AUTHOR]

Methane (CH4) is a potent greenhouse gas and the second highest contributor to global warming. CH4 emissions are still growing at an alarmingly high pace. To limit global warming to 1.5 °C, one of the most effective strategies is to reduce rapidly the CH4 emissions by developing large‐scale methane removal methods. The purpose of this perspective paper is threefold. (1) To highlight the technology gap dealing with low concentration CH4 (at many emission sources and in the atmosphere). (2) To analyze the challenges and prospects of solar‐driven gas phase advanced oxidation processes for CH4 removal. And (3) to propose some ideas, which may help to develop solar‐driven gas phase advanced oxidation processes and make them deployable at a climate significant scale. [ABSTRACT FROM AUTHOR]

Tropical convection is expected to decrease with warming, in a variety of ways. Specific incarnations of this idea include the "stability‐iris" hypothesis of decreasing anvil cloud coverage, as well as the decrease of both tropospheric and cloud‐base mass fluxes with warming. This paper seeks to encapsulate these phenomena into three "rules," and to explore their interrelationships and robustness, using both analytical reasoning as well as cloud‐resolving and global climate simulations. We find that each of these rules can be derived analytically from the usual expression for clear‐sky subsidence, so they all embody the same essential physics. But, these rules do not all provide the same degree of constraint: the stability‐iris effect is not entirely robust due to unconstrained microphysical degrees of freedom, and the decrease in cloud‐base mass flux is not entirely robust due to unconstrained effects of entrainment and detrainment. Tropospheric mass fluxes on the other hand are shown to be well‐constrained theoretically, and when evaluated in temperature coordinates they exhibit a monotonic decrease with warming at all vertical levels and across a hierarchy of models. Plain Language Summary: Tropical convection and high cloudiness are expected to decrease with global warming, in a variety of ways. This phenomenon has a few different manifestations in the literature, whose relationships are unclear. We show analytically that these explanations all embody the same essential physics, but are not equally robust and thus do not all have the same predictive power. Key Points: Three constraints on tropical convection can all be derived analytically from clear‐sky subsidenceTropospheric mass fluxes at a fixed isotherm should robustly decrease under global warmingDecreases in anvil cloud area and cloud‐base mass flux are not as robust [ABSTRACT FROM AUTHOR]

Evolutionary developmental biology, and especially ecological developmental biology, is essential for discussions of sustainability and the responses to global climate change. First, this paper explores examples of animals that have successfully altered their development to accommodate human‐made changes to their environments. We next document the ability of global warming to disrupt the development of those organisms with temperature‐dependent sex‐determination or with phenologies coordinating that organism's development with those of other species. The thermotolerance of Homo sapiens is also related to key developmental factors concerning brain development and maintenance, and the development of corals, the keystone organisms of tropical reefs, is discussed in relation to global warming as well as to other anthropogenic changes. While teratogenic and endocrine‐disrupting compounds are not discussed in this essay, the ability of glyphosate herbicides to block insect development is highlighted. Last, the paper discusses the need to creatively integrate developmental biology with ecological, political, religious, and economic perspectives, as the flourishing of contemporary species may require altering the ways that Western science has considered the categories of nature, culture, and self. Research Highlights: Knowledge of developmental biology is critical for discussions of sustainability and for the possibilities of multispecies flourishing. Endangered coral reefs and turtle species highlight the developmental interactions between the biotic and abiotic portions of the environment. Developmental biology must interact creatively with philosophy, economics, religion, politics in order for environmental survival. [ABSTRACT FROM AUTHOR]

It is very well known that parameter tuning can have a major impact on the performance of Global Climate Models. However, parameter tuning is not the only implementation detail that can drastically affect model performance and the representation of various phenomena in models. "Minor‐looking treatments" often exert a critical control on model performance; they include lower and upper limits of physical variables, thresholds of variables that control the enabling or disabling of a specific process, whether two schemes can work together or only one scheme works exclusively, and numerical methods including the order of calling various physics schemes. The impacts of such minor‐looking treatments are sometimes comparable to or even larger than those obtained by introducing advanced parameterizations based on theory and observation. Because the importance of these treatments is often overlooked and not discussed in the literature, we comprehensively summarize examples of various minor‐looking treatments that can considerably affect model performance. Plain Language Summary: Global climate models (GCMs) are used for climate simulations, including global warming simulations. Global climate models (GCMs) simulate various physical processes such as convection, clouds, radiation, and turbulence. A lot of effort is devoted to improving the representation of these physical processes by introducing more sophisticated or more complicated and detailed processes. The values of parameters in such processes significantly affect the model performance, and many modelers carefully set such parameter values. However, other factors can also affect model performance. The lower or upper limits specified in the detailed implementation of such processes, threshold values for switching on a certain effect, how to calculate each effect, vertical resolutions, and so on can significantly affect the model performance. We call these "minor‐looking treatments" and show a wide range of examples in this paper. Key Points: Minor‐looking treatments crucially determine the performance of global climate modelsThey include lower limits, upper limits, thresholds for enabling physical processes, and numerical methodsMinor‐looking treatments should be documented in detail, shared, and discussed more in the climate community [ABSTRACT FROM AUTHOR]

Under the context of global warming, we identified a significant increase in lightning activity in the last two decades over the Tibetan Plateau (TP), the highest plateau on earth, based on two data sets. The largest rise of lightning activity was found over the region with high lightning density represented by the eastern TP at a rate of 0.072 ± 0.069 fl km−2 yr−1 during 1996–2013 from Optical Transient Detector/Lightning Imaging Sensor. World Wide Lightning Location Network data also showed a remarkable increase in lightning strokes during 2010–2019 in the maximum lightning density region, while the change was insignificant in the low lightning density region. Further investigations revealed that most of the TP region experienced a significant increase in thunderstorm frequency, which was responsible for the increase in lightning activity, rather than an increase in thunderstorm intensity. Increased lightning activity implies a potential risk to human beings and the fragile ecosystem over the TP in a warmer climate. Plain Language Summary: Lightning is a natural source of nitrogen oxides and wildfires, and thus has important effects on atmospheric chemistry and ecosystem. Lightning is also a serious threat to human life and property. Using satellite‐based and ground‐based data, the trend of lightning activity over the Tibetan Plateau (TP) in the past two decades has been investigated in this paper. In the global warming context, TP experienced an increase in lightning activity. The lightning increase was significant in the high lightning density region, such as the central and eastern TP, and insignificant in the lower lightning density region, such as the western TP and the Brahmaputra Valley. The thunderstorm frequency also experienced an increase over most parts of the TP, which caused the rising trend in lightning activity. However, the thunderstorm intensity shows weak and insignificant changes. Since the TP is getting warmer much faster than that observed over the globe, the increased lightning activity over the TP may exert enhanced potential threat to human beings and impacts on the fragile ecosystem over the Plateau. Key Points: Lightning activity over the Tibetan Plateau increased significantly in the past two decades based on the Optical Transient Detector/Lightning Imaging Sensor and World Wide Lightning Location Network datasetsLightning activity in the high‐flash‐density region increased faster than that in the low‐flash‐density regionThe apparent rise in lightning activity is due to increase in thunderstorm rate rather than change in thunderstorm intensity [ABSTRACT FROM AUTHOR]

Climate classifications are useful to synthesize the physical state of the climate with a proxy that can be directly related to biota. However, they present a potential drawback, namely a strong sensitivity because of the use of hard thresholds (step functions). Thus, minor discrepancies in the base data produce large differences in the type of climate. However, such an a priori limitation is also a strength because such sensitivity can be used to better gauge model performance. Although previous attempts of classifying climates of the world using global climate model outputs were encouraging, the applicability of their classifications to impact studies has been limited by past model issues. Notwithstanding the persistence of certain imperfections and limitations in current models, the high‐quality physical simulations from phase six of the Coupled Intercomparison Project (CMIP6) has opened new possibilities in the field, thanks to their improved representation of atmospheric and oceanic physics. The purpose of this paper is twofold: to show that climate classifications from CMIP6 are sufficiently robust for use in impact studies, and to use those classifications for identifying error sources and potential issues that deserve further attention in models. Thus, 52 CMIP6 climate models were evaluated by using three climate classifications schemes, classical Köppen, extended‐Köppen, and modified Thornthwaite. We first assessed model ability to reproduce present climate types by comparing their outputs with observational data. Models performed best for the Köppen and extended‐Köppen classification methods (Cohen's kappa κ = 0.7), and had moderate scores for the Thornthwaite climate classification (κ = 0.4). By tracing back the observed biases, we were able to pinpoint the misrepresentation of dry climates as a major source of error. Another finding was that most models still had some difficulties in representing the seasonal variability of precipitation over several monsoonal regions, thereby yielding the wrong climate type there. Models were also evaluated for future climate. Substantial changes in climate types are projected in the SSP5‐8.5 scenario. These changes include a shrinkage of polar/frigid climates (22%) and an increase of dry climates (7%). [ABSTRACT FROM AUTHOR]

This study investigates some of the uncertainties sources associated with the pseudo global warming (PGW) approach which was employed to project future patterns of tropical cyclones (TCs) over the Arabian Sea (AS). First, the climate variables controlling the patterns of tropical cyclones were extracted from reanalysis datasets of ERA5, ERAI, CFSR, and NCEP/NCAR. Then, each dataset was evaluated against long‐term measurements to identify the best‐performing reanalysis dataset. ERA5 showed the best performance for most of the variables. Outputs of 20 CMIP5 global climate models (GCMs) were then evaluated against the ERA5 data resulting in an ensemble of the best performing GCMs. A PGW framework was then used to project the changes in patterns of three significant historical cyclones: Gonu, Phet, and Ashobaa. In doing so, the signals of future climate variables were extracted from the GCMs ensemble to modify the initial and boundary conditions of the WRF model which was previously tuned for reproducing the historical TCs. Different tests were conducted to address the sources of uncertainty in the PGW approach, including the selection of the climate variables contributing to the computation of the signals, the selection of GCMs, and the spatial variation of signals. A considerable sensitivity of the projected track and intensity of TCs to the choice of GCMs was observed, acknowledging the importance of GCMs evaluation before calculating the signals. Moreover, it was found that among all variables, signals of sea surface temperature and air temperature have major effects on the cyclone's track and intensity. Apart from that, when the signals were applied to the domain of the WRF model uniformly, compared to applying spatially varying signals, different tracks and intensities for future TCs were also observed. Overall, the findings of this paper challenge the reliability of the projected changes in TCs patterns obtained from PGW. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive trend analysis of spatiotemporal temperature change patterns over the territory of what is now the Czech Republic (CR) during the 1961–2019 period. Employing daily mean temperatures (TAVG), maximum (TMAX) and minimum (TMIN) temperatures and diurnal temperature range (DTR), supplied by 133 stations of the Czech Hydrometeorological Institute, daily, monthly, seasonal and annual series were calculated for four altitudinal groups and the entire CR, for which linear trends were calculated and further analysed. For the purposes of relative trend comparison, the linear trends were also calculated from standardized series (mean 0, SD 1, in 1961–1990). All seasonal and annual TAVG, TMAX and TMIN series exhibit statistically significant increasing trends, with the exceptions of only a few cases for winter (DJF) and autumn (SON). DTR trends increase significantly in spring (MAM) and summer (JJA), but decrease in DJF and SON. The highest increases in trends occur in JJA and from stations at lower altitudes for groups I (up to 300 m asl) and II (301–600 m asl). Trends in JJA and SON TMIN are relatively higher than in TMAX, while the opposite holds true of DJF and MAM. Comparing the three decades after 1990 with the 1961–1990 normal, each decade was generally warmer than the previous period, with particularly enhanced warming in 2011–2019. This is also reflected in prominent increases in cumulative temperature sums throughout the year. The results obtained are discussed in the context of other European papers and with respect to explaining existing differences. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive trend analysis of spatiotemporal temperature change patterns over the territory of what is now the Czech Republic (CR) during the 1961–2019 period. Employing daily mean temperatures (TAVG), maximum (TMAX) and minimum (TMIN) temperatures and diurnal temperature range (DTR), supplied by 133 stations of the Czech Hydrometeorological Institute, daily, monthly, seasonal and annual series were calculated for four altitudinal groups and the entire CR, for which linear trends were calculated and further analysed. For the purposes of relative trend comparison, the linear trends were also calculated from standardized series (mean 0, SD 1, in 1961–1990). All seasonal and annual TAVG, TMAX and TMIN series exhibit statistically significant increasing trends, with the exceptions of only a few cases for winter (DJF) and autumn (SON). DTR trends increase significantly in spring (MAM) and summer (JJA), but decrease in DJF and SON. The highest increases in trends occur in JJA and from stations at lower altitudes for groups I (up to 300 m asl) and II (301–600 m asl). Trends in JJA and SON TMIN are relatively higher than in TMAX, while the opposite holds true of DJF and MAM. Comparing the three decades after 1990 with the 1961–1990 normal, each decade was generally warmer than the previous period, with particularly enhanced warming in 2011–2019. This is also reflected in prominent increases in cumulative temperature sums throughout the year. The results obtained are discussed in the context of other European papers and with respect to explaining existing differences. [ABSTRACT FROM AUTHOR]

Due to the enhanced price of electricity, the gradual depletion of fossil fuels, and the global warming concerns, power loss minimization through deployment of distributed generators (DGs) has attracted significant attention in recent decades. This paper proposes a genetic algorithm (GA) based strategy for minimization of active and reactive power losses through optimal location and size of DGs. It also quantifies and tallies the total network power losses for the cases with random as well as optimal allocation of DGs. To validate the accuracy of the obtained results from GA, another nature‐inspired optimization algorithm, cuckoo search, is also deployed. The simulation results on IEEE 30 and 118 bus systems indicate that the proposed strategy not only can effectively reduce the total network active and reactive power losses but also lead to the improvement of network voltage profile. [ABSTRACT FROM AUTHOR]

Grid integration of solar photovoltaic (PV) systems is becoming popular recently due to the merits of stable support to conventional grid, limiting global warming and reduced emissions. However, maintaining capacitor voltage balancing, unity power factor, sinusoidal grid current, and harmonic profile improvement are challenging tasks owing to change in irradiation conditions. Multilevel inverters (MLI) in grid‐connected systems will enhance the system's power quality in terms of voltage and current total harmonic distortion (THD). One of the most promising multilevel topologies for renewable energy applications is the cascaded H‐bridge (CHB) inverter. Since CHB inverters include many components, they have a higher risk of failure, lowering system reliability. Due to the change in irradiation condition, the voltage across the corresponding DC link capacitor may vary. Therefore, the DC‐link capacitor balancing is mandatory and done by an individual control scheme. This paper presents a highly reliable, robust, and modular solar PV‐fed fault‐tolerant CHB inverter with an individual voltage/current control strategy for grid integration. Higher reliability and modularity, power factor correction, and harmonic profile improvement are the main objectives of the proposed system. The proposed system has been simulated in MATLAB/Simulink and validated with experimental results on the developed prototype for different irradiation conditions. [ABSTRACT FROM AUTHOR]

High Asian glaciers and precipitation have directly or indirectly influenced the freshwater supply of billions of people and natural ecosystems in surrounding areas. To better understand the hydroclimatic changes in the High Asian transboundary river basins in the context of global warming, more precipitation‐sensitive proxy data are needed. In this paper, we used the tree‐ring cores of Pinus densata and Picea brachytyla from the southern Tibetan Plateau (TP) to establish a tree‐ring‐width composite chronology and estimate hydrological annual (September–August) precipitation (r2 = 47.0%, p < 0.01) for the Lohit River basin from 1720 to 2019. Our reconstructed precipitation was closely linked with the glacier mass balance of Shishapangma peak, which may provide us with some evidence for glacier fluctuations in the southern TP. Our precipitation reconstruction successfully captured recent dry trends and generally agreed with other tree‐ring‐based precipitation reconstructions from nearby regions. In addition, reconstructed precipitation variations were inconsistent with recorded monsoon‐season Brahmaputra discharge. [ABSTRACT FROM AUTHOR]

In this paper, we investigate whether the relationship between the El Niño‐Southern Oscillation and tropical cyclone (TC) rain rate over the western North Pacific (WNP) changes between the global warming slowdown (2001–2012) and resumption (2013–2020) periods. Using high‐resolution satellite rainfall data, we show that the average TC rain rate increases by 9% but decreases by 14% during the recent El Niño and La Niña years (since 2013), respectively. During the El Niño years, the increase is related to higher TC track density at lower latitudes, where more water vapor and stronger convergence are present. On the other hand, the decrease in TC rain rate during the recent La Niña years is mainly related to an increase in track density at higher latitudes and a decrease in TC intensity. These changes in TC track density and intensity are both associated with the strengthening of the subtropical high since 2013. Plain Language Summary: The impacts on various weather phenomena associated with the global surface warming slowdown (or "hiatus": 1998–2012) and its subsequent resumption since 2013 have been extensively investigated. An unresolved issue is whether the tropical cyclone (TC) rain rate over the western North Pacific (WNP) basin has also changed, especially during the El Niño (or La Niña) years. Considering the availability of high‐resolution satellite rainfall data, we mainly focus on the period of 2001–2020 (slowdown period: 2001–2012; resumption period: 2013–2020). Our results show that, consistent with the increase in atmospheric water vapor after the global warming resumption, the average TC rain rate has increased by ∼2%. However, TC rain rate increases in El Niño years but decreases in La Niña years during the resumption period. This opposite change in TC rain rate is mainly influenced by the strengthened WNP subtropical high. Our findings suggest that it is necessary to properly consider the influence of the subtropical high on the projections in TC migration, intensity, and rain rate under global warming. Key Points: Compared with El Niño‐Southern Oscillation (ENSO) years in the global warming slowdown period, tropical cyclone (TC) rain rate increases and decreases in recent El Niño and La Niña yearsThis opposite change in TC rain rate in recent ENSO years is mainly affected by the changes in TC track density and TC intensityChanges in TC track density and intensity are both influenced by the extremely strengthened subtropical high since 2013 [ABSTRACT FROM AUTHOR]

The denitrification process profoundly affects soil nitrogen (N) availability and generates its byproduct, nitrous oxide, as a potent greenhouse gas. There are large uncertainties in predicting global denitrification because its controlling factors remain elusive. In this study, we compiled 4301 observations of denitrification rates across a variety of terrestrial ecosystems from 214 papers published in the literature. The averaged denitrification rate was 3516.3 ± 91.1 µg N kg−1 soil day−1. The highest denitrification rate was 4242.3 ± 152.3 µg N kg−1 soil day−1 under humid subtropical climates, and the lowest was 965.8 ± 150.4 µg N kg−1 under dry climates. The denitrification rate increased with temperature, precipitation, soil carbon and N contents, as well as microbial biomass carbon and N, but decreased with soil clay contents. The variables related to soil N contents (e.g., nitrate, ammonium, and total N) explained the variation of denitrification more than climatic and edaphic variables (e.g., mean annual temperature (MAT), soil moisture, soil pH, and clay content) according to structural equation models. Soil microbial biomass carbon, which was influenced by soil nitrate, ammonium, and total N, also strongly influenced denitrification at a global scale. Collectively, soil N contents, microbial biomass, pH, texture, moisture, and MAT accounted for 60% of the variation in global denitrification rates. The findings suggest that soil N contents and microbial biomass are strong predictors of denitrification at the global scale. [ABSTRACT FROM AUTHOR]

Advances in high‐performance computing have enabled large‐eddy simulations (LES) of turbulence, convection, and clouds. However, their potential to improve parameterizations in global climate models (GCMs) is only beginning to be harnessed, with relatively few canonical LES available so far. The purpose of this paper is to begin creating a public LES library that expands the training data available for calibrating and evaluating GCM parameterizations. To do so, we use an experimental setup in which LES are driven by large‐scale forcings from GCMs, which in principle can be used at any location, any time of year, and in any climate state. We use this setup to create a library of LES of clouds across the tropics and subtropics, in the present and in a warmer climate, with a focus on the transition from stratocumulus to shallow cumulus over the East Pacific. The LES results are relatively insensitive to the choice of host GCM driving the LES. Driven with large‐scale forcing under global warming, the LES simulate a positive but weak shortwave cloud feedback, adding to the accumulating evidence that low clouds amplify global warming. Plain Language Summary: Clouds remain one of the largest uncertainties in our understanding and in predictions of climate change because it is challenging to represent their small‐scale dynamics in climate models. However, high‐resolution simulations can provide faithful simulations of clouds and turbulence in limited areas, and these can be used to calibrate climate models. So far, only a limited set of simulations has been used for calibration of climate models, with focus on a few specific locations. This study presents an experimental setup that allows the high‐resolution simulations to be run anywhere on the globe, in any climate state, driven by output from different climate models. The setup is used to create a library of high‐resolution simulations of clouds across the tropics and subtropics in both the current and a warmer climate. The library substantially expands the data set available for the calibration and evaluation of climate models. Key Points: A library of high‐resolution simulations of clouds is created with large‐eddy simulations (LES) driven by a few global climate models (GCMs)Clouds simulated by LES driven by different GCMs are more similar to one another than the corresponding GCM‐simulated cloudsUnder global warming, LES‐simulated low clouds exhibit a weak but positive feedback on warming [ABSTRACT FROM AUTHOR]

Using four reanalysis data sets and ground‐based observations, this paper uncovers that on average, 30% of the time, Northern Hemisphere snow cover experiences unfrozen bottom soil. It is demonstrated that the probability of occurrence of unfrozen soils is correlated with the snow types and is maximum over the ephemeral followed by the maritime and prairie snow. The results based on reanalysis data unveil that the seasonal evolution of the unfrozen soil areas is not synchronous with the snow cover extent and exhibits sub‐annual bi‐modality with two annual maxima in April and October. Interannual trend analyses indicate that shrinkage of spring snow in the past few decades has been accompanied by an increase in the proportion of unfrozen bottom soils, more significantly over polar climate regimes dominated by the tundra and taiga snow. The findings imply that the snowpack basal melting could have increased due to global warming. Plain Language Summary: Unfrozen bottom soils below snow layers play an important role in the persistence and stability of snowpack, yet less knowledge is known about its spatial variability and seasonal evolution on a global scale. This study uncovers that, on average, around 30% of annual Northern Hemisphere's snow cover extent is over unfrozen soils with a spatial variability that is highly correlated with snow types. Specifically, unfrozen soils appear more frequently below the ephemeral followed by the maritime and prairie snow. In addition, it is demonstrated that the unfrozen soil areas exhibit different seasonal evolution from snow cover extent with two annual peaks in April and October. The results show that the areas of unfrozen soils are expanding in spring as the snow cover extent is shrinking. Key Points: On average 30% of the year the soil below global snowpack is unfrozenSeasonal evolution of the areas of unfrozen soil below snowpack is not synchronous with snow cover extentBasal snowpack melting could have increased in a warming climate [ABSTRACT FROM AUTHOR]