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Improved understanding of how our coasts will evolve over a range of time scales (years‐decades) is critical for effective and sustainable management of coastal infrastructure. A robust knowledge of the spatial, directional and temporal variability of the inshore wave climate is required to predict future coastal evolution and hence vulnerability. However, the variability of the inshore directional wave climate has received little attention, and an improved understanding could drive development of skillful seasonal or decadal forecasts of coastal response. We examine inshore wave climate at 63 locations throughout the United Kingdom and Ireland (1980–2017) and show that 73% are directionally bimodal. We find that winter‐averaged expressions of six leading atmospheric indices are strongly correlated (r = 0.60–0.87) with both total and directional winter wave power (peak spectral wave direction) at all studied sites. Regional inshore wave climate classification through hierarchical cluster analysis and stepwise multi‐linear regression of directional wave correlations with atmospheric indices defined four spatially coherent regions. We show that combinations of indices have significant skill in predicting directional wave climates (R 2 = 0.45–0.8; p, Key Points Over 70% of inshore wave climates analyzed throughout the United Kingdom and Ireland were directionally bimodalCombinations of winter atmospheric indices NAO, WEPA, SCAND, and EA are significantly correlated with directional wave climate in all regionsRegression models using multiple winter atmospheric indices enable skillful reconstructions of directional wave climate in all regions

Many nations responded to the corona virus disease‐2019 (COVID‐19) pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO2, other greenhouse gases and ozone and aerosol precursors. We present the initial results from a coordinated Intercomparison, CovidMIP, of Earth system model simulations which assess the impact on climate of these emissions reductions. 12 models performed multiple initial‐condition ensembles to produce over 300 simulations spanning both initial condition and model structural uncertainty. We find model consensus on reduced aerosol amounts (particularly over southern and eastern Asia) and associated increases in surface shortwave radiation levels. However, any impact on near‐surface temperature or rainfall during 2020–2024 is extremely small and is not detectable in this initial analysis. Regional analyses on a finer scale, and closer attention to extremes (especially linked to changes in atmospheric composition and air quality) are required to test the impact of COVID‐19‐related emission reductions on near‐term climate., Key Points Lockdown restrictions during COVID‐19 have reduced emissions of aerosols and greenhouse gases12 CMIP6 Earth system models have performed coordinated experiments to assess the impact of this on climateAerosol amounts are reduced over southern and eastern Asia but there is no detectable change in annually averaged temperature or precipitation

Geoenergy and geoengineering applications usually involve fluid injection into and production from fractured media. Accounting for fractures is important because of the strong poromechanical coupling that ties pore pressure changes and deformation. A possible approach to the problem uses equivalent porous media to reduce the computational cost and model complexity instead of explicitly including fractures in the models. We investigate the validity of this simplification by comparing these two approaches. Simulation results show that pore pressure distribution significantly differs between the two approaches even when both are calibrated to predict identical values at the injection and production wells. Additionally, changes in fracture stability are not well captured with the equivalent porous medium. We conclude that explicitly accounting for fractures in numerical models may be necessary under some circumstances to perform reliable coupled thermohydromechanical simulations, which could be used in conjunction with other tools for induced seismicity forecasting., A.Z. acknowledges the financial support received from the “Iran's Ministry of Science, Research and Technology” (PhD students' sabbatical grants) for visiting IDAEA‐CSIC. The contribution of F.P. is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—project number PA 3451/1‐1. R.M. is thankful for the support from US DOE through Carbon SAFE Macon County Project DE‐FE0029381. V.V. acknowledges funding from the Spanish National Research Council (CSIC) through the Intramural project 201730I100 and from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Program through the Starting Grant GEoREST (www.georest.eu) (Grant agreement No. 801809). IDAEA‐CSIC is a Center of Excellence Severo Ochoa (Spanish Ministry of Science and Innovation, Project CEX2018‐000794‐S). The authors declare no conflict of interest.

Due to the specific hydrothermal conditions of dry‐hot valleys, temperature changes caused by the development of large‐scale hydropower projects may be more extreme than they are in other regions. In this study, we analyzed these temperature changes at four hydropower stations in both dry‐hot and non‐dry‐hot valleys. Based on the calculated relative temperatures of the downstream river and the areas surrounding the reservoirs, we employed two indices to quantify the influence of the reservoirs on the temperatures of these two regions: the downstream river temperature change and the reservoir effect change intensity. Our results are as follows: (a) In the downstream rivers, the temperature regulation effect was more pronounced in the wet season; in the regions surrounding the reservoirs, the temperature regulation effect was more pronounced in the dry season. (b) The downstream river temperature in both the dry‐hot and wet‐hot valleys exhibited noticeable warming in both the wet and dry seasons, while the cold‐dry valley was characterized by cooling in the dry season and warming in the wet season. With the exception of the Liyuan station (where the influence of the reservoir on the downstream temperatures only extended to a distance of 9 km from the dam) during the dry season, the existence of the hydropower stations affected the temperatures of the entire downstream region. (c) For the areas surrounding the reservoir, the presence of a hydropower station mainly caused the temperatures in the dry‐hot valleys to rise and the temperatures in the non‐dry‐hot valleys to decrease., Key Points The difference of surface temperature affected by reservoirs was compared in dry‐hot and non‐dry‐hot valleysTo facilitate comparison of the different downstream river temperature changes, downstream river temperature change index was establishedThe reservoir effect change intensity was established to explore how reservoirs regulate the surface temperature in the surrounding areas

Whilst the capability of climate services to reduce climate impacts is alluring, empirical evidence on how best to mainstream climate information services in Africa is lacking. This paper determines how climate information services have been incorporated into national policies by Anglophone West African states for building agricultural resilience and provides a detailed analysis of issues facing Ghanaian agricultural systems. The paper addresses the questions: (i) to what extent is climate change recognised as a threat to agricultural development in national climate facing policies of Anglophone West African states? (ii) to what extent have climate information services been incorporated into national and regional policy frameworks of Anglophone West African states for resilient agricultural systems? (iii) what are the key challenges in mainstreaming climate information services into national policies for resilient agricultural building in Ghana? The study employed thematic content analysis, multi-stakeholder workshops and expert interviews to understand climate discourses around climate services. Findings show that climate change is highlighted in national and regional level policies as a serious threat to socioeconomic development and agricultural productivity in West Africa. Anglophone West Africa countries are at various stages in establishing a National Framework for Climate Services to help guide future adaptation planning. This study shows that Anglophone West African states have not yet incorporated climate information services into strategic national and regional climate facing policies that are critical in shaping efforts aimed at managing climate risks. For the case of Ghana, the study reveals low awareness of climate change among policy-makers, human and institutional capacity constraints as some of the key factors militating against the mainstreaming of climate information services. Capacity building of policy makers and institutional strengthening are both vital for more effective mainstreaming of climate services across West Africa.

Micromagnetic tomography aims at reconstructing large numbers of individual magnetizations of magnetic particles from combining high‐resolution magnetic scanning techniques with micro X‐ray computed tomography (microCT). Previous work demonstrated that dipole moments can be robustly inferred, and mathematical analysis showed that the potential field of each particle is uniquely determined. Here, we describe a mathematical procedure to recover higher orders of the magnetic potential of the individual magnetic particles in terms of their spherical harmonic expansions (SHE). We test this approach on data from scanning superconducting quantum interference device microscopy and microCT of a reference sample. For particles with high signal‐to‐noise ratio of the magnetic scan we demonstrate that SHE up to order n = 3 can be robustly recovered. This additional level of detail restricts the possible internal magnetization structures of the particles and provides valuable rock magnetic information with respect to their stability and reliability as paleomagnetic remanence carriers. Micromagnetic tomography therefore enables a new approach for detailed rock magnetic studies on large ensembles of individual particles., Key Points Micromagnetic Tomography uniquely recovers higher‐order multipole terms for several individual grains in a sampleHigher order multipole moments are an expression of the internal domain structure of magnetic grainsUltimately, this enables to select individual grains for rock‐ and paleomagnetic studies based on domain configuration

Intensive observations and WRF‐Chem simulations are applied in this study to investigate the adverse impacts of regional transport on the PM2.5 (fine particulate matter; diameter ≤2.5 μm) changes in Shanghai during the Coronavirus Disease 2019 lockdown. As the local atmospheric oxidation capacity was observed to be generally weakened, strong regional transport carried by the frequent westerly winds is suggested to be the main driver of the unexpected pollution episodes, increasing the input of both primary and secondary aerosols. Contributing 40%–80% to the PM2.5, the transport contributed aerosols are simulated to exhibit less decreases (13.2%–21.8%) than the local particles (37.1%–64.8%) in urban Shanghai due to the lockdown, which largely results from the less decreased industrial and residential emissions in surrounding provinces. To reduce the influence of the transport, synergetic emission control, especially synergetic ammonia control, measures are proved to be effective strategies, which need to be considered in future regulations., Key Points PM2.5 pollution in Shanghai were mostly attributed to the regional transport carried by frequent westerly winds during the COVID‐lockdownThe transport contributed aerosols in Shanghai are less affected by the lockdown measures due to the less decreased surrounding emissionsSynergetic emission control measures, especially those on ammonia emissions, are effective in mitigating the adverse transport impacts

Although uncommon, nontuberculous mycobacterial (NTM) pulmonary infection in the Hawaiian Islands has a relatively high incidence and mortality compared to the mainland U.S. As a result, this study examines the possible geological and hydrological pathways by which NTM patients may become infected, including the environmental conditions that may favor growth and transport. Previously suggested infection routes include the inhalation of NTM attached to micro‐droplets from infected home plumbing systems and aerosolized dust from garden soil. In this study, we evaluate the possible routes NTM may take from riparian environments, into groundwater, into public water supplies and then into homes. Because NTM are notoriously hydrophobic and prone to attach to surfaces, mineralogy, and surface chemistry of suspended sediment in streams, soils, and rock scrapings suggest that NTM may especially attach to Fe‐oxides/hydroxides, and be transported as particles from losing streams to the aquifer on time‐scales of minutes to days. Within the aquifer, flow models indicate that water may be drawn into production wells on time scales (months) that permit NTM to survive and enter domestic water supplies. These processes depend on the presence of interconnected fracture networks with sufficient aperture to preclude complete autofiltration. The common occurrence of NTM in and around streams, in addition to wells, implies that the natural and built environments are capable of introducing a source of NTM into domestic water supplies via groundwater withdrawals. This may produce a persistent source of NTM infection to individuals through the presence of NTM‐laden biofilms in home plumbing., Key Points Nontuberculous mycobacterial (NTM) are found in soils and biofilms of riparian environments in Hawai'iNTM are likely transported from losing streams to aquifersPumped wells draw NTM into culinary water supplies and into homes. NTM are chlorine resistant and outcompete other taxa in home plumbing

In a rapidly changing world, what is today an unprecedented extreme may soon become the norm. As a result, extreme‐related disasters are expected to become more frequent and intense. This will have widespread socio‐economic consequences and affect the ability of different societal groups to recover from and adapt to rapidly changing environmental conditions. Therefore, there is the need to decipher the relation between genesis of unprecedented events, accumulation and distribution of risk, and recovery trajectories across different societal groups. Here, we develop an analytical approach to unravel the complexity of future extremes and multiscalar societal responses—from households to national governments and from immediate impacts to longer term recovery. This requires creating new forms of knowledge that integrate analyses of the past—that is, structural causes and political processes of risk accumulation and differentiated recovery trajectories—with plausible scenarios of future environmental extremes grounded in the event‐specific literature. We specifically seek to combine the physical characteristics of the extremes with examinations of how culture, politics, power, and policy visions shape societal responses to unprecedented events, and interpret the events as social‐environmental extremes. This new approach, at the nexus between social and natural sciences, has the concrete advantage of providing an impact‐focused vision of future social‐environmental risks, beyond what is achievable within conventional disciplinary boundaries. In this paper, we focus on extreme flooding events and the societal responses they elicit. However, our approach is flexible and applicable to a wide range of extreme events. We see it as the first building block of a new field of research, allowing for novel and integrated theoretical explanations and forecasting of social‐environmental extremes., Key Points We conceptualize unprecedented extremes as social‐environmental processes shaped by institutional, political, and economic changeAs social‐environmental extremes become more frequent, there is an urgency to unravel their genesis and the possible societal responsesThis approach is the first building block of a new field of research in social‐environmental extreme event forecasts

A growing constellation of satellites is providing near‐global coverage of column‐averaged CO2 observations. Launched in 2019, NASA’s OCO‐3 instrument is set to provide XCO2 observations at a high spatial and temporal resolution for regional domains (100 × 100 km). The atmospheric column version of the Stochastic Time‐Inverted Lagrangian Transport (X‐STILT) model is an established method of determining the influence of upwind sources on column measurements of the atmosphere, providing a means of analysis for current OCO‐3 observations and future space‐based column‐observing missions. However, OCO‐3 is expected to provide hundreds of soundings per targeted observation, straining this already computationally intensive technique. This work proposes a novel scheme to be used with the X‐STILT model to generate upwind influence footprints with less computational expense. The method uses X‐STILT generated influence footprints from a key subset of OCO‐3 soundings. A nonlinear weighted averaging is applied to these footprints to construct additional footprints for the remaining soundings. The effects of subset selection, meteorological data, and topography are investigated for two test sites: Los Angeles, California, and Salt Lake City, Utah. The computational time required to model the source sensitivities for OCO‐3 interpretation was reduced by 62% and 78% with errors smaller than other previously acknowledged uncertainties in the modeling system (OCO‐3 retrieval error, atmospheric transport error, prior emissions error, etc.). Limitations and future applications for future CO2 missions are also discussed., Key Points Determining sources of spatially dense XCO2 observations with LPDM techniques can become time intensive and strain computational resourcesPresented in this work is an interpolation scheme that eases the computational burden of spatially dense XCO2 source determination studiesEvaluating the efficiency of this interpolation scheme revealed reductions of >50% in computational time at two testing locations

The intensification of heat stress reduces the labor capacity and hence poses a threat to socio‐economic development. The reliable projection of the changing climate and the development of sound adaptation strategies are thus desired for adapting to the decreasing labor productivity under climate change. In this study, an optimization modeling approach coupled with dynamical downscaling is proposed to design the optimal adaptation strategies for improving labor productivity under heat stress in China. The future changes in heat stress represented by the wet‐bulb globe temperature (WBGT) are projected with a spatial resolution of 25 × 25 km by a regional climate model (RCM) through the dynamical downscaling of its driving global climate model (GCM). Uncertain information such as system costs, environmental costs, and subsidies are also incorporated into the optimization process to provide reliable decision alternatives for improving labor productivity. Results indicate that the intensification of WBGT is overestimated by the GCM compared to the RCM. Such an overestimation can lead to more losses in working hours derived from the GCM than those from the RCM regardless of climate scenarios. Nevertheless, the overestimated heat stress does not alter the regional measures taken to adapt to decreasing labor productivity. Compared to inland regions, the monsoon‐affected regions tend to improve labor productivity by applying air conditioning rather than working overtime due to the cost differences. Consequently, decision‐makers need to optimally make a balance between working overtime and air conditioning measures to meet sustainable development goals., Key Points An optimization model coupled with dynamical downscaling is developed to improve labor productivity under intensified heat stress in ChinaCivilian workers in inland regions will be more vulnerable to the intensified heat stress in a changing climateCompared to the regional climate model, the global climate model overestimates heat stress and thus exaggerates related system costs to recover from the working hour loss

Supraglacial debris affects glacier mass balance as a thin layer enhances surface melting, while a thick layer reduces it. While many glaciers are debris‐covered, global glacier models do not account for debris because its thickness is unknown. We provide the first globally distributed debris thickness estimates using a novel approach combining sub‐debris melt and surface temperature inversion methods. Results are evaluated against observations from 22 glaciers. We find the median global debris thickness is ∼0.15 ± 0.06 m. In all regions, the net effect of accounting for debris is a reduction in sub‐debris melt, on average, by 37%, which can impact regional mass balance by up to 0.40 m water equivalent (w.e.) yr‐1. We also find recent observations of similar thinning rates over debris‐covered and clean ice glacier tongues is primarily due to differences in ice dynamics. Our results demonstrate the importance of accounting for debris in glacier modeling efforts., Key Points We produce the first distributed global debris thickness estimatesAccounting for debris significantly reduces regional glacier mass lossThe similar thinning rates of debris‐covered and clean ice glaciers in High Mountain Asia is primarily caused by differences in ice dynamics

The decline in global emissions of carbon dioxide due to the COVID‐19 pandemic provides a unique opportunity to investigate the sensitivity of the global carbon cycle and climate system to emissions reductions. Recent efforts to study the response to these emissions declines has not addressed their impact on the ocean, yet ocean carbon absorption is particularly susceptible to changing atmospheric carbon concentrations. Here, we use ensembles of simulations conducted with an Earth system model to explore the potential detection of COVID‐related emissions reductions in the partial pressure difference in carbon dioxide between the surface ocean and overlying atmosphere (ΔpCO2), a quantity that is regularly measured. We find a unique fingerprint in global‐scale ΔpCO2 that is attributable to COVID, though the fingerprint is difficult to detect in individual model realizations unless we force the model with a scenario that has four times the observed emissions reduction., Key Points COVID‐related emissions reductions will be imperceptible in surface ocean pH observationsThe CanESM5 COVID ensemble predicts a unique fingerprint of COVID‐related emissions reductions in global mean ΔpCO2 (pCO2oc ‐ pCO2atm)The fingerprint is potentially detectable in global‐scale observations of ΔpCO2, but only with large emissions reductions

Humboldt Gletscher is a 100‐km wide, slow‐moving glacier in north Greenland which holds a 19‐cm global sea level equivalent. Humboldt has been the fourth largest contributor to sea level rise since 1972 but the cause of its mass loss has not been elucidated. Multi‐beam echo sounding data collected in 2019 indicate a seabed 200 m deeper than previously known. Conductivity temperature depth data reveal the presence of warm water of Atlantic origin at 0°C at the glacier front and a warming of the ocean waters by 0.9 ± 0.1°C since 1962. Using an ocean model, we reconstruct grounded ice undercutting by the ocean, combine it with calculated retreat caused by ice thinning to floatation, and are able to fully explain the observed retreat. Two thirds of the retreat are caused by undercutting of grounded ice, which is a physical process not included in most ice sheet models., Key Points The 100‐km wide Humboldt Gletscher holds a 19‐cm sea level rise equivalent, lost 161 billion tons of mass, and retreated 13 km since 1972Warm waters at 0°C flood a 350–400 m deep trough on its northern flank that remains below sea level more than 100 km inlandWe explain the glacier retreat as 70% from ocean‐induced undercutting and 30% from thinning‐induced retreat

17 pags., 9 figs., 1 tab., Ocean-going ships supply products from one region to another and contribute to the world’s economy. Ship exhaust contains many air pollutants and results in significant changes in marine atmospheric composition. The role of reactive halogen species (RHS) in the troposphere has received increasing recognition and oceans are the largest contributors to their atmospheric burden. However, the impact of shipping emissions on RHS and that of RHS on ship-originated air pollutants have not been studied in detail. Here, an updated Weather Research Forecasting coupled with Chemistry model is utilized to explore the chemical interactions between ship emissions and oceanic RHS over the East Asia seas in summer. The emissions and resulting chemical transformations from shipping activities increase the level of NO and NO at the surface, increase O in the South China Sea, but decrease O in the East China Sea. Such changes in pollutants result in remarkable changes in the levels of RHS (>200% increase of chlorine; ∼30% and ∼5% decrease of bromine and iodine, respectively) as well as in their partitioning. The abundant RHS, in turn, reshape the loadings of air pollutants (∼20% decrease of NO and NO; ∼15% decrease of O) and those of the oxidants (>10% reduction of OH and HO; ∼40% decrease of NO) with marked patterns along the ship tracks. We, therefore, suggest that these important chemical interactions of ship-originated emissions with RHS should be considered in the environmental policy assessments of the role of shipping emissions in air quality and climate., This study received funding from the European Research Council Executive Agency under the European Union’s Horizon 2020 Research and Innovation Program (Project ERC-2016- COG 726349 CLIMAHAL) and was supported by the Consejo Superior de Investigaciones Científicas (CSIC) of Spain and The Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning and Shanghai Thousand Talents Program. The development and maintenance of the WRF-Chem model are conducted by NOAA/ESRL/GSD in active collaboration with other institutes. Computing resources, support, and data storage were provided by the Climate Simulation Laboratory at NCAR’s Computational and Information Systems Laboratory (CISL), sponsored by the NSF. International cooperation between CSIC (Spain) and CONICET (Argentina) was supported by the i-COOP program (B20331). R.P.F. would like to thank ANPCyT (PICT 2015-0714), UNCuyo (SeCTyP M032/3853), and UTN (PID 4920-194/2018) for financial support. IITM is funded by the Ministry of Earth Sciences, Government of India.

Low‐cloud based emergent constraints have the potential to substantially reduce uncertainty in Earth’s equilibrium climate sensitivity, but recent work has shown that previously developed constraints fail in the latest generation of climate models, suggesting that new approaches are needed. Here, we investigate the potential for emergent constraints to reduce uncertainty in regional cloud feedbacks, rather than the global‐mean cloud feedback. Strong relationships are found between the monthly and interannual variability of tropical clouds, and the tropical net cloud feedback. These relationships are combined with observations to substantially narrow the uncertainty in the tropical cloud feedback and demonstrate that the tropical cloud feedback is likely >0Wm−2K−1. Promising relationships are also found in the 90°–60°S and 30°–60°N regions, though these relationships are not robust across model generations and we have not identified the associated physical mechanisms., Key Points Global low‐cloud‐based emergent constraints on equilibrium climate sensitivity fail in CMIP6Strong relationships are found between unforced cloud variability and long‐term cloud feedbacks in several regionsRegional emergent constraints suggest the tropical cloud feedback is likely positive

We analyzed the effect of the North American monsoon anticyclone (NAMA) on the meridional transport of summertime cross‐tropopause convective outflow by applying a trajectory analysis to a climatology of convective overshooting tops (OTs) identified in GOES satellite images, which covers the domain from 29°S to 68°N and from 205°W to 1.25°W for the time period of May to September, 2013. From this analysis, we identify seasonal development of geographically distinct outflow regions of convectively influenced air masses (CIAMs) from the NAMA circulation to the global stratosphere and quantify the associated meridional displacement of CIAMs. We find that prior to the development of the NAMA, the majority of CIAMs exit the study area in a southeastern region between 5°N and 35°N at 45°W (75.5% in May). During July and August, when the NAMA is strongest, two additional outflow regions develop that constitute the majority of outflow: 68.1% in a northeastern region between 35°N and 60°N at 45°W and 13.4% in a southwestern region between 5°N and 35°N at 145°W. The shift in the location of most CIAM outflow from the pre‐NAMA southeastern region to NAMA‐dependent northeastern and southwestern regions corresponds to a change in average meridional displacement of CIAMs from 3.3° northward in May to 24.5° northward in July and August. Meridional transport of CIAMs through persistent outflow regions from the NAMA circulation to the global stratosphere has the potential to impact global stratospheric composition beyond convective source regions., Key Points Trajectory analysis of overshooting tops identified by GOES satellite is used to evaluate meridional transport of cross‐tropopause convective outflowThe North American monsoon anticyclone (NAMA) circulation and its seasonality dictates the extent of meridional transport that occurs in the lower stratosphereDuring July and August, when the NAMA is strongest, the average convectively influenced air mass is transported 22.0° northward

Compound climate extremes, such as events with concurrent temperature and precipitation extremes, have significant impacts on the health of humans and ecosystems. This paper aims to analyze temporal and spatial characteristics of compound extremes of monthly temperature and precipitation, evaluate the performance of the sixth phase of the Coupled Model Intercomparison Project (CMIP6) models in simulating compound extremes, and investigate their future changes under Shared Socioeconomic Pathways (SSPs). The results show a significant increase in the frequency of compound warm extremes (warm/dry and warm/wet) but a decrease in compound cold extremes (cold/dry and cold/wet) during 1985–2014 relative to 1955–1984. The observed upward trends of compound warm extremes over China are much higher than those worldwide during the period of interest. A multi‐model ensemble (MME) of CMIP6 models performs well in simulating temporal changes of warm/wet extremes, and temporal correlation coefficients between MME and observations are above 0.86. Under future scenarios, CMIP6 simulations show substantial rises in compound warm extremes and declines in compound cold extremes. Globally, the average frequency of warm/wet extremes over a 30‐yr period is projected to increase for 2070–2099 relative to 1985–2014 by 18.53, 34.15, 48.79, and 59.60 under SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5, respectively. Inter‐model uncertainties for the frequencies of compound warm extremes are considerably higher than those of compound cold extremes. The projected uncertainties in the global occurrences of warm/wet extremes are 3.82 times those of warm/dry extremes during 2070–2099 and especially high for the Amazon and the Tibetan Plateau., Key Points A multi‐model ensemble of CMIP6 models performs well in simulating temporal changes of warm/wet extremesThe inter‐model uncertainties for the frequencies of compound warm extremes are considerably higher than those of compound cold extremesThe projected uncertainties in the global occurrences of warm/wet extremes are 3.82 times those of warm/dry extremes during 2070–2099

After a tropical storm makes landfall, its vortex interacts with the surrounding environment and the underlying surface. It is expected that diurnal variation over land will affect storm structures. However, this has not yet been explored in previous studies. In this paper, numerical simulation of postlandfall Tropical Storm Bill (2015) is conducted using a research version of the NCEP Hurricane Weather Research and Forecasting (HWRF) model. Results indicate that during the storm's interaction with midlatitude westerlies over the Great Plains, the simulated storm with the SLAB land‐surface scheme is stronger, with faster eastward movement and attenuation, and more asymmetric structures than that with the NOAH land‐surface scheme. More symmetric structures correspond with a slower weakening and slower eastward movement of the storm over land. Further diagnoses suggest an obvious response of the storm's asymmetric structures to diurnal effects over land. Surface diabatic heating in the storm environment is important for the storm's symmetric structures and intensity over land. Specifically, during the transition from nighttime to daytime, the evident strengthening of convective instability, atmospheric baroclinicity, and the lateral advection of high θe air in the storm environment, associated with the rapid increase in surface diabatic heating, are conducive to the development of vertical vorticity and storm‐relative helicity, thus contributing to the maintenance of the storm's symmetric structures and intensity after landfall., Key Points An evident response of the storm's asymmetric structures to diurnal effects over land are revealedSurface diabatic heating in the storm environment is important for the evolution of the storm's symmetric structures and intensity over landEffects of surface diabatic heating storm's symmetric structure and intensity over land are mainly manifested in storm's upshear quadrants

Microplastic debris ending up at the sea surface has become a known major environmental issue. However, how microplastic particles move and when they sink in the ocean remains largely unknown. Here, we model microplastic subject to biofouling (algal growth on a substrate) to estimate sinking timescales and the time to reach the depth where particles stop sinking. We combine NEMO‐MEDUSA 2.0 output, that represents hydrodynamic and biological properties of seawater, with a particle‐tracking framework. Different sizes and densities of particles (for different types of plastic) are simulated, showing that the global distribution of sinking timescales is largely size‐dependent as opposed to density‐dependent. The smallest particles we simulate (0.1 μm) start sinking almost immediately around the globe and their trajectories take the longest time to reach their first sinking depth (relative to larger particles). In oligotrophic subtropical gyres with low algal concentrations, particles between 1 and 0.01 mm do not sink within the simulation time of 90 days. This suggests that in addition to the comparatively well‐known physical processes, biological processes might also contribute to the accumulation of floating plastic (of 1–0.01 mm) in subtropical gyres. Particles of 1 μm in the gyres start sinking largely due to vertical advection, whereas in the equatorial Pacific they are more dependent on biofouling. The qualitative impacts of seasonality on sinking timescales are small, however, localized sooner sinking due to spring algal blooms is seen. This study maps processes that affect the sinking of virtual microplastic globally, which could ultimately impact the ocean plastic budget., Key Points Sinking timescales of virtual particles subject to biofouling are more dependent on the initial size of particles than initial densityLow algal presence in subtropical gyres and minimal biofouling can contribute to particles between 1 and 0.01 mm remaining at the surfaceModeled biofouled particles of 0.1 microns start sinking almost immediately and show a global median sinking timescale of one day

We document an exceptional large‐spatial scale case of changes in tidal range in the North Sea, featuring pronounced trends between −2.3 mm/yr at tide gauges in the United Kingdom and up to 7 mm/yr in the German Bight between 1958 and 2014. These changes are spatially heterogeneous and driven by a superposition of local and large‐scale processes within the basin. We use principal component analysis to separate large‐scale signals appearing coherently over multiple stations from rather localized changes. We identify two leading principal components (PCs) that explain about 69% of tidal range changes in the entire North Sea including the divergent trend pattern along United Kingdom and German coastlines that reflects movement of the region’s semidiurnal amphidromic areas. By applying numerical and statistical analyses, we can assign a baroclinic (PC1) and a barotropic large‐scale signal (PC2), explaining a large part of the overall variance. A comparison between PC2 and tide gauge records along the European Atlantic coast, Iceland, and Canada shows significant correlations on time scales of less than 2 years, which points to an external and basin‐wide forcing mechanism. By contrast, PC1 dominates in the southern North Sea and originates, at least in part, from stratification changes in nearby shallow waters. In particular, from an analysis of observed density profiles, we suggest that an increased strength and duration of the summer pycnocline has stabilized the water column against turbulent dissipation and allowed for higher tidal elevations at the coast., Key Points 70 North Sea tide gauges evince contrasting trends in tidal range between the United Kingdom (−1.0 mm/yr) and the German Bight (3.3 mm/yr) since 1958We use principal component analysis (PCA) to separate local (e.g., building measures) from large‐scale effects of oceanographic originThe first PC explains 77% of variance in the German Bight and is linked to stability changes in shallow, seasonally stratified waters

Sea surface temperature (SST) is an essential climate variable, that is directly used in climate monitoring. Although satellite measurements can offer continuous global coverage, obtaining a long‐term homogeneous satellite‐derived SST data set suitable for climate studies based on a single instrument is still a challenge. In this work, we assess a homogeneous SST data set derived from reprocessed Infrared Atmospheric Sounding Interferometer (IASI) level‐1 (L1C) radiance data. The SST is computed using Planck's Law and simple atmospheric corrections. We assess the data set using the ERA5 reanalysis and the EUMETSAT‐released IASI level‐2 SST product. Over the entire period, the reprocessed IASI SST shows a mean global difference with ERA5 close to zero, a mean absolute bias under 0.5°C, with a SD of difference around 0.3°C and a correlation coefficient over 0.99. In addition, the reprocessed data set shows a stable bias and SD, which is an advantage for climate studies. The interannual variability and trends were compared with other SST data sets: ERA5, Hadley Centre's SST (HadISST), and NOAA's Optimal Interpolation SST Analysis (OISSTv2). We found that the reprocessed SST data set is able to capture the patterns of interannual variability well, showing the same areas of high interannual variability (>1.5°C), including over the tropical Pacific in January corresponding to the El Niño Southern Oscillation. Although the period studied is relatively short, we demonstrate that the IASI data set reproduces the same trend patterns found in the other data sets (i.e., cooling trend in the North Atlantic, warming trend over the Mediterranean)., Key Points First IASI algorithm focused on sea surface temperature (SST) suitable for climate studiesThe IASI‐derived SST data set is compared with other available data setsClimate variability and trends are shown and compared to other data sets

The ocean's “biological pump” significantly modulates atmospheric carbon dioxide levels. However, the complexity and variability of processes involved introduces uncertainty in interpretation of transient observations and future climate projections. Much research has focused on “parametric uncertainty,” particularly determining the exponent(s) of a power‐law relationship of sinking particle flux with depth. Varying this relationship's functional form introduces additional “structural uncertainty.” We use an ocean biogeochemistry model substituting six alternative remineralization profiles fit to a reference power‐law curve, to systematically characterize structural uncertainty, which, in atmospheric pCO2 terms, is roughly 50% of parametric uncertainty associated with varying the power‐law exponent within its plausible global range, and similar to uncertainty associated with regional variation in power‐law exponents. The substantial contribution of structural uncertainty to total uncertainty highlights the need to improve characterization of biological pump processes, and compare the performance of different profiles within Earth System Models to obtain better constrained climate projections., Key Points Six alternative flux profiles fit to a Martin Curve yield large differences in atmospheric carbonStructural uncertainty comprises one‐third of total uncertainty in the ocean's biological pumpVarying particle attenuation with depth may account for half of the biological pump's overall carbon drawdown

Earth system models are valuable tools for understanding how the Arctic snow‐ice system and the feedbacks therein may respond to a warming climate. In this analysis, we investigate snow on Arctic sea ice to better understand how snow conditions may change under different forcing scenarios. First, we use in situ, airborne, and satellite observations to assess the realism of the Community Earth System Model (CESM) in simulating snow on Arctic sea ice. CESM versions one and two are evaluated, with V1 being the Large Ensemble experiment (CESM1‐LE) and V2 being configured with low‐ and high‐top atmospheric components. The assessment shows CESM2 underestimates snow depth and produces overly uniform snow distributions, whereas CESM1‐LE produces a highly variable, excessively‐thick snow cover. Observations indicate that snow in CESM2 accumulates too slowly in autumn, too quickly in winter‐spring, and melts too soon and rapidly in late spring. The 1950–2050 trends in annual mean snow depths are markedly smaller in CESM2 (−0.8 cm decade−1) than in CESM1‐LE (−3.6 cm decade−1) due to CESM2 having less snow overall. A perennial, thick sea‐ice cover, cool summers, and excessive summer snowfall facilitate a thicker, longer‐lasting snow cover in CESM1‐LE. Under the SSP5‐8.5 forcing scenario, CESM2 shows that, compared to present‐day, snow on Arctic sea ice will: (1) undergo enhanced, earlier spring melt, (2) accumulate less in summer‐autumn, (3) sublimate more, and (4) facilitate marginally more snow‐ice formation. CESM2 also reveals that summers with snow‐free ice can occur ∼30–60 years before an ice‐free central Arctic, which may promote faster sea‐ice melt., Key Points CESM2 (CESM1‐LE) snow depths on Arctic sea ice are thinner (thicker) than observed depthsThe 1950–2050 trends in annual mean snow depth on Arctic sea ice are −0.8 and −3.6 cm decade−1 in CESM2 and CESM1‐LE, respectivelyCESM2 shows enhanced earlier snowmelt, less snow accumulation, more sublimation, and slightly more snow‐ice formation in future decades

We present a set of idealized numerical experiments of a solstitial aquaplanet ocean and examine the thermodynamic and dynamic implications of surface gravity waves (SGWs) upon its mean state. The aquaplanet's oceanic circulation is dominated by an equatorial zonal jet and four Ekman driven meridional overturning circulation (MOC) cells aligned with the westerly atmospheric jet streams and easterly trade winds in both hemispheres. Including SGW parameterization (representing modulations of air‐sea momentum fluxes, Langmuir circulation, and Stokes‐Coriolis force) increases mixed layer vertical momentum diffusivity by ∼40% and dampens surface momentum fluxes by ∼4%. The correspondingly dampened MOC impacts the oceanic density structure to 1 km depth by lessening the large‐scale advective transports of heat and salt, freshening the equatorial latitudes (where evaporation minus precipitation [E − P] is negative) and increasing salinity in the subtropics (where E − P is positive) by ∼1%. The midlatitude pycnocline in both hemispheres is deepened by the inclusion of SGWs. Including SGWs into the aquaplanet ocean model acts to increase mixed layer depth by ∼10% (up to 20% in the wintertime in midlatitudes), decrease vertical shear in the upper 200 m and alter local midlatitude buoyancy frequency. Generally, the impacts of SGWs upon the aquaplanet ocean are found to be consistent across cooler and warmer climates. We suggest that the implications of these simulations could be relevant to understanding future projections of SGW climate, exoplanetary oceans, and the dynamics of the Southern Ocean mixed layer., Key Points Idealized oceanic climates forced by ranging atmospheric regimes following equator‐to‐pole thermal gradient perturbations are investigatedWind‐forced surface gravity waves deepen the mixed layer, increase mixed layer vertical momentum diffusivity and dampen surface currentsThe consistency of the effects of waves on ocean dynamics and stratification across cooler/warmer aquaplanet climates is examined

A reduced‐physics model is employed at 1/25° to 1/100° global resolution to determine (a) if linear dynamics can reproduce the observed low‐mode M2 internal tide, (b) internal‐tide sensitivity to bathymetry, stratification, surface tides, and dissipation parameterizations, and (c) the amount of power transferred to the nonstationary internal tide. The simulations predict 200 GW of mode‐1 internal‐tide generation, consistent with a general circulation model and semianalytical theory. Mode‐1 energy is sensitive to damping, but a simulation using parameterizations for wave drag and wave‐mean interaction predicts 84% of satellite observed sea‐surface height amplitude variance on a 1° × 1° grid. The simulation energy balance indicates that 16% of stationary mode‐1 energy is scattered to modes 2–4 and negligible energy propagates onto the shelves. The remaining 84% of energy is lost through parameterizations for high‐mode scattering over rough topography (54%) and wave‐mean interactions that transfer energy to the nonstationary internal tide (29%)., Key Points Global mode‐1 internal tides are predictable from a linearized, reduced physics modelThe choice of damping parameterizations predetermines mode‐1 internal‐tide energySimulations with damping by wave drag and wave‐mean interactions largely agree with satellite data

The transport of plastic particles from inland sources to the oceans garbage patches occurs trough coastal regions where the transport processes depend highly on wave‐induced motions. In this study, experimental measurements of the plastic particles wave‐induced Lagrangian drift in intermediate water depth are presented investigating the influence of the wave conditions, particle size and density on the motion of relatively large plastic particles. A large influence of the particle density is observed causing particles to float or sink for relative densities lower and larger than water respectively. The measured net drift of the floating particles correlates well with theoretical solutions for particle Stokes drift, where the net drift is proportional to the square of the wave steepness. Floating particles remain at the free water surface because of buoyancy and no evidence of any other influence of particle inertia on the net drift is observed. Nonfloating particles move close to the bed with lower velocity magnitudes than the floating particles’ motion at the free surface. The drift of nonfloating particles reduces with decreasing wave number, and therefore wave steepness., Key Points A 16 m wave flume is used to measure wave transport of floating and non‐floating plasticFloating plastic transport correlates well with Stokes drift and buoyancy is the only non‐inertial effectNon‐floating particles experience shear forces. Transport varies with particle size and density

African dust exhibits strong variability on a range of time scales. Here we show that the interhemispheric contrast in Atlantic SST (ICAS) drives African dust variability at decadal to millennial timescales, and the strong anthropogenic increase of the ICAS in the future will decrease African dust loading to a level never seen during the Holocene. We provide a physical framework to understand the relationship between the ICAS and African dust activity: positive ICAS anomalies push the Intertropical Convergence Zone (ITCZ) northward and decrease surface wind speed over African dust source regions, which reduces dust emission and transport. It provides a unified framework for and is consistent with relationships in the literature. We find strong observational and proxy‐record support for the ICAS‐ITCZ‐dust relationship during the past 160 and 17,000 years. Model‐projected anthropogenic increase of the ICAS will reduce African dust by as much as 60%, which has broad consequences., Key Points The ICAS drives African dust change at decadal and longer time scalesA unified framework supports the ICAS drive of African dust, and observations also support the ICAS‐dust‐ITCZ relationshipsClimate models suggest strong reduction in African dust due to increase in ICAS driven by global warming

The North Atlantic warming hole (NAWH) is referred to as a reduced warming, or even cooling, of the North Atlantic during an anthropogenic‐driven global warming. A NAWH is predicted by climate models during the 21st century, and its pattern is already emerging in observations. Despite the known key role of the North Atlantic surface temperatures in setting the Northern Hemisphere climate, the mechanisms behind the NAWH are still not fully understood. Using state‐of‐the‐art climate models, we show that anthropogenic aerosol forcing opposes the formation of the NAWH (by leading to a local warming) and delays its emergence by about 30 years. In agreement with previous studies, we also demonstrate that the relative warming of the North Atlantic under aerosol forcing is due to changes in ocean heat fluxes, rather than air‐sea fluxes. These results suggest that the predicted reduction in aerosol forcing during the 21st century may accelerate the formation of the NAWH., Key Points Using CMIP6 and CESM‐LE simulations, we show that aerosol forcing generates a global cooling trend with a warming in the North AtlanticThis trend opposes the North Atlantic warming hole trend due to greenhouse gasesAerosol forcing delays the formation of the North Atlantic warming hole by about 30 years

We present an assessment of the impacts on atmospheric composition and radiative forcing of short‐lived pollutants following a worldwide decrease in anthropogenic activity and emissions comparable to what has occurred in response to the COVID‐19 pandemic, using the global composition‐climate model United Kingdom Chemistry and Aerosols Model (UKCA). Emission changes reduce tropospheric hydroxyl radical and ozone burdens, increasing methane lifetime. Reduced SO2 emissions and oxidizing capacity lead to a decrease in sulfate aerosol and increase in aerosol size, with accompanying reductions to cloud droplet concentration. However, large reductions in black carbon emissions increase aerosol albedo. Overall, the changes in ozone and aerosol direct effects (neglecting aerosol‐cloud interactions which were statistically insignificant but whose response warrants future investigation) yield a radiative forcing of −33 to −78 mWm−2. Upon cessation of emission reductions, the short‐lived climate forcers rapidly return to pre‐COVID levels; meaning, these changes are unlikely to have lasting impacts on climate assuming emissions return to pre‐intervention levels., Key Points Emission reductions are likely to have led to a global reduction in short‐lived climate forcers and tropospheric oxidizing capacityReductions in O3 and aerosol from both lower emissions and decreased sulfate oxidation resulted in a net negative radiative forcingThe radiative impacts are small and short‐lived. Longer term climate impacts must come through future sustained emission reductions

Biophysical vegetation responses to elevated atmospheric carbon dioxide (CO2) affect regional hydroclimate through two competing mechanisms. Higher CO2 increases leaf area (LAI), thereby increasing transpiration and water losses. Simultaneously, elevated CO2 reduces stomatal conductance and transpiration, thereby increasing rootzone soil moisture. Which mechanism dominates in the future is highly uncertain, partly because these two processes are difficult to explicitly separate within dynamic vegetation models. We address this challenge by using the GISS ModelE global climate model to conduct a novel set of idealized 2×CO2 sensitivity experiments to: evaluate the total vegetation biophysical contribution to regional climate change under high CO2; and quantify the separate contributions of enhanced LAI and reduced stomatal conductance to regional hydroclimate responses. We find that increased LAI exacerbates soil moisture deficits across the sub‐tropics and more water‐limited regions, but also attenuates warming by ∼0.5–1°C in the US Southwest, Central Asia, Southeast Asia, and northern South America. Reduced stomatal conductance effects contribute ∼1°C of summertime warming. For some regions, enhanced LAI and reduced stomatal conductance produce nonlinear and either competing or mutually amplifying hydroclimate responses. In northeastern Australia, these effects combine to exacerbate radiation‐forced warming and contribute to year‐round water limitation. Conversely, at higher latitudes these combined effects result in less warming than would otherwise be predicted due to nonlinear responses. These results highlight substantial regional variation in CO2‐driven vegetation responses and the importance of improving model representations of these processes to better quantify regional hydroclimate impacts., Key Points We evaluate the separate and combined biophysical vegetation effects on hydroclimate in a high‐CO2 world using the GISS ModelE global climate modelIncreased leaf areas enhance soil moisture drying at lower latitudes; reduced stomatal conductance enhances high‐latitude warmingIncreased leaf area and reduced stomatal conductance also produce complex nonlinear and either competing or mutually amplifying regional hydroclimate responses

Filaments of intense vapor transport called atmospheric rivers (ARs) are responsible for the majority of poleward vapor transport in the midlatitudes. Despite their importance to the hydrologic cycle, there remain many unanswered questions about changes to ARs in a warming climate. In this study we perform a series of escalating uniform SST increases (+2, +4, and +6K, respectively) in the Community Atmosphere Model version 5 in an aquaplanet configuration to evaluate the thermodynamic and dynamical response of AR vapor content, transport, and precipitation to warming SSTs. We find that AR column integrated water vapor (IWV) is especially sensitive to SST and increases by 6.3–9.7% per degree warming despite decreasing relative humidity through much of the column. Further analysis provides a more nuanced view of AR IWV changes: Since SST warming is modest compared to that in the midtroposphere, computing fractional changes in IWV with respect to SST results in finding spuriously large increases. Meanwhile, results here show that AR IWV transport increases relatively uniformly with temperature and at consistently lower rates than IWV, as modulated by systematically decreasing low‐level wind speeds. Similarly, changes in AR precipitation are related to a compensatory relationship between enhanced near‐surface moisture and damped vertical motions., Key Points Aquaplanet atmospheric rivers grow in size and intensity as sea surface temperatures increaseIncreases in column water vapor beyond Clausius‐Clapeyron rates mask drying at upper levelsWeakening dynamics damp changes in atmospheric river vapor transport and precipitation

Understanding the past, present, and future evolution of methane remains a grand challenge. Here we have used a hierarchy of models, ranging from simple box models to a chemistry‐climate model (CCM), UM‐UKCA, to assess the contemporary and possible future atmospheric methane burden. We assess two emission data sets for the year 2000 deployed in UM‐UKCA against key observational constraints. We explore the impact of the treatment of model boundary conditions for methane and show that, depending on other factors, such as CO emissions, satisfactory agreement may be obtained with either of the CH4 emission data sets, highlighting the difficulty in unambiguous choice of model emissions in a coupled chemistry model with strong feedbacks. The feedbacks in the CH4‐CO‐OH system, and their uncertainties, play a critical role in the projection of possible futures. In a future driven by large increases in greenhouse gas forcing, increases in tropospheric temperature drive, an increase in water vapor, and, hence, [OH]. In the absence of methane emission changes this leads to a significant decrease in methane compared to the year 2000. However, adding a projected increase in methane emissions from the RCP8.5 scenario leads to a large increase in methane abundance. This is modified by changes to CO and NOx emissions. Clearly, future levels of methane are uncertain and depend critically on climate change and on the future emission pathways of methane and ozone precursors. We highlight that further work is needed to understand the coupled CH4‐CO‐OH system in order to understand better future methane evolution., Key Points We study methane in present and future climate in a model employing flux‐based treatment of methane emissionsWe examine the source and importance of feedbacks in the CH4‐CO‐OH system using a 0‐D box model and a 3‐D chemistry‐climate modelWe examine methane levels in future climate and the role played by climate and emissions changes

Human activity has led to increased atmospheric concentrations of many gases, including halocarbons, and may lead to emissions of many more gases. Many of these gases are, on a per molecule basis, powerful greenhouse gases, although at present‐day concentrations their climate effect is in the so‐called weak limit (i.e., their effect scales linearly with concentration). We published a comprehensive review of the radiative efficiencies (RE) and global warming potentials (GWP) for around 200 such compounds in 2013 (Hodnebrog et al., 2013, https://doi.org/10.1002/rog.20013). Here we present updated RE and GWP values for compounds where experimental infrared absorption spectra are available. Updated numbers are based on a revised “Pinnock curve”, which gives RE as a function of wave number, and now also accounts for stratospheric temperature adjustment (Shine & Myhre, 2020, https://doi.org/10.1029/2019MS001951). Further updates include the implementation of around 500 absorption spectra additional to those in the 2013 review and new atmospheric lifetimes from the literature (mainly from WMO (2019)). In total, values for 60 of the compounds previously assessed are based on additional absorption spectra, and 42 compounds have REs which differ by >10% from our previous assessment. New RE calculations are presented for more than 400 compounds in addition to the previously assessed compounds, and GWP calculations are presented for a total of around 250 compounds. Present‐day radiative forcing due to halocarbons and other weak absorbers is 0.38 [0.33–0.43] W m−2, compared to 0.36 [0.32–0.40] W m−2 in IPCC AR5 (Myhre et al., 2013, https://doi.org/10.1017/CBO9781107415324.018), which is about 18% of the current CO2 forcing., Key Points Radiative efficiencies are reassessed for more than 600 compounds and global warming potentials calculated for around 250 of theseForty‐two compounds have >10% different radiative efficiency compared to a comprehensive review in 2013Present‐day radiative forcing due to halocarbons and other weak absorbers is 0.38 [0.33–0.43] W m−2, which is ~18% of the CO2 forcing

We analyze projected changes in climate extremes (extreme temperatures and heavy precipitation) in the multimodel ensembles of the fifth and sixth Coupled Model Intercomparison Projects (CMIP5 and CMIP6). The results reveal close similarity between both ensembles in the regional climate sensitivity of the projected multimodel mean changes in climate extremes, that is, their projected changes as a function of global warming. This stands in contrast to widely reported divergences in global (transient and equilibrium) climate sensitivity in the two multimodel ensembles. Some exceptions include higher warming in the South America monsoon region, lower warming in Southern Asia and Central Africa, and higher increases in heavy precipitation in Western Africa and the Sahel region in the CMIP6 ensemble. The multimodel spread in regional climate sensitivity is found to be large in both ensembles. In particular, it contributes more to intermodel spread in projected regional climate extremes compared with the intermodel spread in global climate sensitivity in CMIP6. Our results highlight the need to consider regional climate sensitivity as a distinct feature of Earth system models and a key determinant of projected regional impacts, which is largely independent of the models' response in global climate sensitivity., Key Points Changes in climate extremes as a function of global warming are quasilinear and determine a “regional climate sensitivity” in CMIP5 and CMIP6The regional climate sensitivity of climate extremes is found to be very similar in CMIP5 and CMIP6, unlike global climate sensitivityModel spread in regional climate sensitivity in CMIP6 contributes more to uncertainty of projected extremes than global climate sensitivity

In climate models, the subgrid‐scale orography (SSO) parameterization imposes a blocked flow drag at low levels that is opposed to the local flow. In IPSL‐CM6A‐LR, an SSO lift force is also applied perpendicular to the local flow to account for the effect of locally blocked air in narrow valleys. Using IPSL‐CM6A‐LR sensitivity experiments, it is found that the tuning of both effects strongly impacts the atmospheric circulation. Increasing the blocking and reducing the lift lead to an equatorward shift of the Northern Hemisphere subtropical jet and a reduction of the midlatitude eddy‐driven jet speed. It also improves the simulated synoptic variability, with a reduced storm‐track intensity and increased blocking frequency over Greenland and Scandinavia. Additionally, it cools the polar lower troposphere in boreal winter. Transformed Eulerian Mean diagnostics also show that the low‐level eddy‐driven subsidence over the polar region is reduced consistent with the simulated cooling. The changes are amplified in coupled experiments when compared to atmosphere‐only experiments, as the low‐troposphere polar cooling is further amplified by the temperature and albedo feedbacks resulting from the Arctic sea ice growth. In IPSL‐CM6A‐LR, this corrects the warm winter bias and the lack of sea ice that were present over the Arctic before adjusting the SSO parameters. Our results, therefore, suggest that the adjustment of SSO parameterization alleviates the Arctic sea ice bias in this case. However, the atmospheric changes induced by the parametrized SSO also impact the ocean, with an equatorward shift of the Northern Hemisphere oceanic gyres and a weaker Atlantic meridional overturning circulation., Key Points The adjustment of the parametrized orography in climate models can alleviate the near‐surface winter biases over the ArcticIncreasing low‐level drag reduces Northern Hemisphere stationary wave amplitudes and shifts the subtropical jet equatorwardIncreasing low‐level drag increases the Arctic sea ice coverage and reduces the Atlantic meridional overturning circulation

We used monthly precipitation and temperature data to give early warning of years with higher West Nile Virus (WNV) risk in Nebraska. We used generalized additive models with a negative binomial distribution and smoothing curves to identify combinations of extremes and timing that had the most influence, experimenting with all combinations of temperature and drought data, lagged by 12, 18, 24, 30, and 36 months. We fit models on data from 2002 through 2011, used Akaike's Information Criterion (AIC) to select the best‐fitting model, and used 2012 as out‐of‐sample data for prediction, and repeated this process for each successive year, ending with fitting models on 2002–2017 data and using 2018 for out‐of‐sample prediction. We found that warm temperatures and a dry year preceded by a wet year were the strongest predictors of cases of WNV. Our models did significantly better than random chance and better than an annual persistence naïve model at predicting which counties would have cases. Exploring different scenarios, the model predicted that without drought, there would have been 26% fewer cases of WNV in Nebraska through 2018; without warm temperatures, 29% fewer; and with neither drought nor warmth, 45% fewer. This method for assessing the influence of different combinations of extremes at different time intervals is likely applicable to diseases other than West Nile, and to other annual outcome variables such as crop yield., Key Points A dry year preceded by a wet year in combination with warm temperatures increases the number of human cases of West Nile Virus in NebraskaWe found that drought accounted for 26% of WNV cases 2002–2018, and drought and temperature together accounted for 45% of cases

Strong links are seen in observations between convective clustering and several properties of the Intertropical Convergence Zone (ITCZ). These links suggest that biases in how climate models simulate the ITCZ may be related to model biases in convective clustering or that there may be biases in how models represent the relationship between clustering and the ITCZ. We investigate these issues by analyzing convective clustering, and the link between clustering and ITCZ properties in 18 climate models. We find that the links between variability in convective clustering and variability of ITCZ properties are generally weaker and less robust in models than in observations. By contrast, model biases in the climatological convective clustering explain a substantial fraction of the climatological double‐ITCZ bias, though they do not explain biases in the climatological ITCZ width., Key Points Climate models underestimate the link between zonal convective clustering and the ITCZ widthModel biases in convective clustering explain double‐ITCZ biases, but not ITCZ width biasesSeveral factors may play a role in linking convective clustering and the ITCZ width, but no dominant mechanism was found

This study examines the modifications of air‐sea coupling processes by dust‐radiation‐cloud interactions over the North Atlantic Ocean using a high‐resolution coupled atmosphere‐wave‐ocean‐dust (AWOD) regional model. The dust‐induced mechanisms that are responsible for changes of sea surface temperature (SST) and latent and sensible heat fluxes (LHF/SHF) are also examined. Two 3‐month numerical experiments are conducted, and they differ only in the activation and deactivation of dust‐radiation‐cloud interactions. Model results show that the dust significantly reduces surface downward radiation fluxes (SDRF) over the ocean with the maximum change of 20–30 W m−2. Over the dust plume region, the dust effect creates a low‐pressure anomaly and a cyclonic circulation anomaly, which drives a positive wind stress curl anomaly, thereby reducing sea surface height and mixed layer depth. However, the SST change by dust, ranging from −0.5 to 0.5 K, has a great spatial variation which differs from the dust plume shape. Dust cools SST around the West African coast, except under the maximum dust plume ridge, and extends westward asymmetrically along the northern and southern edges of the dust plume. Dust unexpectedly warms SST over a large area of the western tropical North Atlantic and north of the dust plume. These SST changes are controlled by different mechanisms. Unlike the SST change pattern, the LHF and SHF changes are mostly reduced underneath the dust plume region, though they are different in detail due to different dominant factors, and increased south of the dust plume over the tropic., Key Points Dust‐radiation‐cloud interactions mainly cool SST offshore the North Africa and warm SST over the southwestern dust plume regionDust reduces upward LHF and SHF underneath the dust plume region and increases the values south of the dust plumeChanges of SST/LHF/SHF by dust are not only attributed to the dust‐induced SDRF reduction but also changes of WSC and upper‐ocean dynamic

Future changes in tropical cyclone properties are an important component of climate change impacts and risk for many tropical and midlatitude countries. In this study we assess the performance of a multimodel ensemble of climate models, at resolutions ranging from 250 to 25 km. We use a common experimental design including both atmosphere‐only and coupled simulations run over the period 1950–2050, with two tracking algorithms applied uniformly across the models. There are overall improvements in tropical cyclone frequency, spatial distribution, and intensity in models at 25 km resolution, with several of them able to represent very intense storms. Projected tropical cyclone activity by 2050 generally declines in the South Indian Ocean, while changes in other ocean basins are more uncertain and sensitive to both tracking algorithm and imposed forcings. Coupled models with smaller biases suggest a slight increase in average TC 10 m wind speeds by 2050., Key Points Biases in tropical cyclone distribution, frequency, and intensity are generally reduced in models at 25 km resolutionNorthern Hemisphere basins show mixed responses to future forcing, while Southern Indian Ocean activity projected to declineFuture changes in 10 m wind speed in coupled models are mixed, and models with lower bias suggest small increases

Understanding humanity&rsquo, s relationship with nature is crucial for the well-being and sustainable development of mankind in the face of global environmental change. Communities depend on landscapes for survival and landscapes determine if sustainable development is to be achieved. The links between landscapes, ecosystem services, livelihoods, and climate change are often complex, misunderstood, and barely studied in rural areas of Africa, where communities live side-by-side with conservation areas. Our study surveyed the perception of the nexus of landscape change, climate change, ecosystem services, and livelihoods in Gonarezhou, a national park in southeastern Zimbabwe. We also used Landsat satellite imagery to map the landscape change over 20 years to validate and to correlate with the survey data. The survey results indicated that people relied on rainfed agriculture as a means of livelihood, but droughts as a result of climate change force communities to engage in other means of livelihoods such as small-scale poaching of small game such as impala and harvesting of natural resources such as edible shrubs. Crops and livestock as provisional ecosystem services have been negatively affected by climate change and landscape change. Landsat data confirmed that there was a negative transformation of the landscape as a result of agriculture, growth in settlements, and large herbivores. However, there was also a positive landscape transformation resulting from the conservation efforts by the Gonarezhou Conservation Trust (GCT). Cultural services about education and awareness of the environment and provisional services such as wild fruits are booming. Challenges such as soil erosion, human&ndash, wildlife conflict, and minimal community benefits from conservation efforts hindered sustainable development in the study area. While changes in landscape, climate, livelihoods, and ecosystem services happened at a local scale, the underlying drivers such as politics and the economy were also identified as drivers of landscape change.

Human activities are elevating atmospheric carbon dioxide concentrations to levels unprecedented in human history. The majority of anticipated impacts of anthropogenic CO2 emissions are mediated by climate warming. Recent experimental studies in the fields of indoor air quality and cognitive psychology and neuroscience, however, have revealed significant direct effects of indoor CO2 levels on cognitive function. Here, we shed light on this connection and estimate the impact of continued fossil fuel emissions on human cognition. We conclude that indoor CO2 levels may indeed reach levels harmful to cognition by the end of this century, and the best way to prevent this hidden consequence of climate change is to reduce fossil fuel emissions. Finally, we offer recommendations for a broad, interdisciplinary approach to improving such understanding and prediction., Key Points Atmospheric carbon dioxide concentrations are reaching levels never experienced by Homo sapiens Recent experiments have linked high indoor carbon dioxide concentrations to reduced cognitive functionOur models predict that future carbon emissions will increase indoor concentrations to levels harmful to human cognition

To quantitatively determine the effect of Xiluodu Reservoir on the temperature of the surrounding mountains, the temperature differences between various locations and the reservoir were calculated based on Landsat 8 thermal infrared sensor (TIRS) data. Elevation, slope, aspect, normalized difference vegetation index (NDVI), and visual field were selected as the impact factors, and the most significant grid size used to explore the effect of reservoir on the surrounding mountains was determined by spatial analysis and partial correlation analysis. The effect of the Xiluodu Reservoir on the surrounding mountains' temperature was then quantitatively studied while accounting for the effect of water surface width on temperature. The results are summarized as follows. The most significant grid size for determining the influence of Xiluodu Reservoir on the surrounding mountains' temperature is 90 m. The effect range threshold of the entire reservoir on the temperature of the surrounding mountains is approximately 600 m, and the partial correlation coefficient in each buffer area decreases gradually with increasing distance from the reservoir. The effect threshold of the reservoir on the temperature of the surrounding mountains is approximately 1,500 m in the head area with a water surface width approximately 1,000 m, but it is negligible in the tributary area where the width is approximately 60 m., Key Points Elevation, slope, aspect, normalized difference vegetation index (NDVI), and visual field were selected as the impact factorsTo overcome the scale‐dependence of LST, the most significant grid size was determined by spatial analysis and partial correlation analysisStudy the effect of reservoir on the surrounding mountains' temperature while accounting for the effect of water surface width

Extreme rainfall and flooding associated with landfalling tropical cyclones (TCs) have large societal impacts, both in fatalities and economic losses. This study examines the response of TC rainfall to climate change projected under future anthropogenic greenhouse emissions, focusing on Hurricane Irene, which produced severe flooding across the Northeastern United States in August 2011. Numerical simulations are made with the Weather Research and Forecasting model, placing Irene in the present‐day climate and one projected for the end of 21st century climate represented by Phase 5 of the Coupled Model Intercomparison Project Representative Concentration Pathway 8.5 scenario. Projected future changes to surface and atmospheric temperature lead to a storm rainfall increase of 32% relative to the control run, exceeding the rate expected by the Clausius‐Clapeyron relation given a ~3‐K lower atmospheric warming. Analyses of the atmospheric water balance highlight contributions to the increase in rainfall rate from both increased circulation strength and atmospheric moisture. Storm rainfall rate shows contrasting response to global warming during TC and extratropical transition periods. During the TC phase, Irene shows a significant increase of storm rainfall rate in inner core regions. This increase shifts to outer rainbands as Irene undergoes extratropical transition, collocated with the maximum tangential wind increase and the change of secondary circulation strength. Changes of storm track from the control run to global warming projections play a role in the change of spatial rainfall pattern. Distinct roles of surface and atmospheric warming in storm rainfall and structure changes are also examined., Key Points Increase of Irene rain rate is observed in inner core regions for tropical cyclone phase but in outer rainbands during transition periodIncrease of Irene rain rate exceeds the rate of water vapor increase in a warming climate, suggesting the importance of dynamical effects

The ability of smallholder farmers to utilise seasonal climate forecast (SCF) information in farm planning to reflect anticipated climate is a precursor to improved farm management. However, the integration of SCF by smallholder farmers into farm planning has been poor, partly because of the lack of forecast skill, lack of communication and inability to see the relevance of the SCFs for specific farming decisions. The relevance of seasonal climate forecasting in farming decisions can be enhanced through improved understanding of SCF from the smallholder farmers’ perspective. Studies that have been done of how smallholder farmers understand SCF and how the available SCFs influence smallholder farmers’ decisions are limited. Therefore, the objective of this paper was to review how smallholder farmers make decisions on farming practices based on SCFs and the challenges and opportunities thereof. The review shows that the majority of smallholder farmers in Africa make use of either scientific or indigenous knowledge climate forecasts and, in some cases, a combination of both. There are mixed results in the area of evaluating benefits of SCFs in decision-making and farm production. In some cases, the outcomes are positive, whereas in others they are difficult to quantify. Thus, the integration of SCFs into smallholder farmers’ decision-making is still a challenge. We recommend that significant work must be done to improve climate forecasts in terms of format, and spatial and temporal context in order for them to be more useful in influencing decision-making by smallholder farmers. Significance: At the farm level, making the right decisions at the right time is rendered even more difficult in light of the increasing frequency of extreme weather patterns. The threat of climate change makes accurate seasonal climate forecasting essential for African smallholder farmers. Technological, social and interdisciplinary issues, communication and scale are some key challenges which impact the utility and uptake of SCFs in rural smallholder farms. The integration of both scientific and indigenous knowledge forecasts is an opportunity for further exploration.