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Dust and high cloud interactions are critical for climate change, primarily due to the dominant roles of high cloud in the greenhouse effect and the continental precipitation. Nonetheless, disentangling the specific impacts of dust from the overlying meteorology influence on high clouds presents great challenges. In this study, we construct a meteorological pattern that successfully reveal the intricate connection between high cloud distribution and atmospheric conditions. Through this strong bounded relationship, we find that dust exhibits notable controls over the facilitation or inhibition of ice particle growth contingent upon the prevailing meteorological fields. More dust can increase precipitation rate and shorten high cloud lifetime particularly under favorable meteorology. These findings underscore the crucial role of dust concentration in mitigating global warming for future climate change. Plain Language Summary: Dust particles in the atmosphere play a crucial role in the formation and dissipation of high clouds, which can significantly impact global climate and weather patterns. By analyzing satellite observations and climate model data, we discovered that dust can either enhance or suppress the growth of ice crystals, depending on the atmospheric conditions. In moist environments with favorable weather, increased dust leads to larger ice crystals and more precipitation, accelerating the life cycle of high clouds. Conversely, in dry conditions with unfavorable weather, excessive dust competes for limited moisture, resulting in smaller ice crystals, although it can still increase rainfall during the dissipation stage of high clouds. As climate change progresses and dust storms become more frequent, the increased presence of dust in the atmosphere may lead to more extreme weather events and potentially mitigate some of the warming effects caused by high clouds. Understanding these complex interactions between dust, high clouds, and weather conditions is essential for improving climate models and predicting future changes in Earth's water cycle and energy balance. Key Points: Extracted first principal component, highly correlated with high cloud fraction, isolating meteorological effects on cloudsDust facilitates ice crystal formation and precipitation, catalyzing cloud lifecycle and ultimately modifying radiative effectsIncreased dust accelerates high cloud lifecycle, causing more extreme weather and mitigating climate warming [ABSTRACT FROM AUTHOR]

Mesoscale Convective Systems (MCSs) play a critical role in tropical rainfall patterns and circulations. To reduce persistent biases and improve understanding of the climate system, international groups have called for unprecedented investment in global convection–permitting (CP) climate models. It is essential such models accurately represent MCSs, and in particular environmental interactions such as dynamical control by wind shear. We show that in representative current generation CP simulations, MCS updraft entrainment decreases with shear, leading to a realistic increase of extreme rainfall. We find the control of environmental shear extends to mean storm rainfall and anvil heights. The simulation of these effects depends strongly on model physics in both CP and parameterized models. We show that in West Africa, MCS shear response influences the zonal distribution of storm diabatic heating, modifying upscale impacts of convection. Our results demonstrate key tests for focused process–based assessment of CP model fidelity. Plain Language Summary: Movements of tropical air are driven by interactions between large, continental–scale circulations and localized deep convection — cells of ascending moist air reaching to the tropopause. These cells can aggregate to form Mesoscale Convective Systems (MCSs), long–lived thunderstorm clusters with large cold cloud shields that dominate tropical rainfall and atmospheric heating, forcing air circulations. Meanwhile, the strength of MCS rainfall depends on local atmospheric conditions. Such local process interactions occur on scales much smaller than typical global climate model grid spacings (>25 km), thus requiring a sub–grid parameterization of deep convection that introduces model biases. Here we show that kilometer–scale models can realistically capture the response of MCSs to local atmospheric moisture and wind conditions. A realistic response to the wind field relies on models showing variable mixing of dry environmental air into convective updrafts, with reduced rates for stronger vertical wind shear. We find that this wind (i.e., dynamical) control on MCSs explains patterns of mean rainfall biases in West Africa and influences atmospheric heating, likely mediating MCSs' upscale impacts on tropical circulations. Our results provide vital process–based methods for verifying the added value of explicitly representing convective storms in novel kilometer–scale global models. Key Points: Convection‐permitting models can capture the response of Mesoscale Convective Systems to both moisture and shear in West AfricaStrong shear gives larger cores, reduced entrainment and greater maximum and mean storm rainfall; this is missed in a parameterized modelShear response has upscale impacts through control of zonal distribution of biases in storm mean rainfall and diabatic heating [ABSTRACT FROM AUTHOR]

The lack of high vertical resolution atmospheric thermodynamic structure observations inside or near major weather events impedes our understanding of physical processes and their predictability in numerical weather prediction (NWP) models. Airborne Global Navigation Satellite System (GNSS) radio occultation (airborne radio occultation [ARO]) has proven to be a viable remote sensing option to offer dense soundings near flight tracks. The global fleet of commercial aircraft already equipped with GNSS receivers could be leveraged to produce an unprecedented number of ARO soundings along global flight paths. Eleven cases of atmospheric bending angle and refractivity profiles were successfully retrieved and compared with the colocated European Center for Medium‐Range Weather Forecasting global reanalysis data. Good quality measurements are obtained with median refractivity differences less than 1% in the middle and upper troposphere, between 5.5 and 11.5 km. Given the use of aircraft data (e.g., Aircraft Meteorological DAta Relay) for data assimilation, incorporating ARO profiles would be a valuable addition, further enhancing the accuracy of aviation and weather forecasts. Plain Language Summary: Global Navigation Satellite System radio occultation (RO) can be used to obtain vertical profiles of atmospheric conditions. This study shows how position data from commercial aircraft with existing hardware can be used to retrieve vertical profiles of atmospheric thermodynamic conditions (such as temperature, pressure, and humidity). Preliminary results show that high‐quality RO profiles can be extracted from unaltered aircraft information with low biases in the middle‐ and upper‐troposphere. The large number of commercial aircraft fleets could offer dense thermodynamic profiles in addition to the in‐situ observations to be operationally assimilated into global numerical weather prediction models, and greatly enhance regional model forecasts. Key Points: For the first time, Global Navigation Satellite System (GNSS) radio occultation (RO) profiles from commercial aircraft with no purpose‐built science payload were extractedGood quality RO profiles are retrievable from commercial closed‐loop GNSS receivers onboard aircraft between flight level and 4 km above mean‐sea‐levelCommercial aircraft could offer thermodynamic profiles along with observations to be assimilated into numerical weather prediction models, and enhance forecasts [ABSTRACT FROM AUTHOR]

Circulation patterns linked to the East Asian winter monsoon (EAWM) affect precipitation, surface temperature, and air quality extremes over East Asia. These circulation patterns can in turn be influenced by aerosol radiative and microphysical effects through diabatic heating and its impacts on atmospheric vorticity. Using global model simulations, we investigate the effects of anthropogenic aerosol emissions and concentration changes on the intensity and variability of the EAWM. Comparison with reanalysis products indicates that the model captures the mean state of the EAWM well. The experiments indicate that anthropogenic aerosol emissions strengthen the Siberian High but weaken the East Asian jet stream, making the land areas of East Asia colder, drier, and snowier. Aerosols reduce mean surface air temperatures by approximately 1.5° $1.5{}^{\circ}$C, comparable to about half of the difference between strong and weak EAWM episodes in the control simulation. The mechanisms behind these changes are evaluated by analyzing differences in the potential vorticity budget. Anthropogenic aerosol effects on diabatic heating strengthen anomalous subsidence over southern East Asia, establishing an anticyclonic circulation anomaly that suppresses deep convection and precipitation. Aerosol effects on cloud cover and cloud longwave radiative heating weaken stability over the eastern flank of the Tibetan Plateau, intensifying upslope flow along the western side of the anticyclone. Both circulation anomalies contribute to reducing surface air temperatures through regional impacts on thermal advection and the atmospheric radiative balance. Plain Language Summary: The East Asian winter monsoon (EAWM) is a large‐scale circulation system that controls the occurrence of cold air outbreaks and severe winter storms throughout the densely populated land areas of East Asia. By reducing the amount of sunlight reaching the surface, warming the atmosphere, and changing the properties and lifetimes of clouds, aerosols can alter the atmospheric circulation and regional weather conditions. Here, we examine the characteristics of the EAWM in global model simulations with and without aerosol emissions from industry, energy generation, transportation, and other human activities. Our results show that the aerosols produced by these activities make East Asian land areas colder, drier, and snowier during winter. We explain the reasons for these changes by diagnosing how various physical effects of aerosols impact temperature and winds within the East Asian monsoon region. Key Points: Anthropogenic aerosols make East Asian land areas roughly 1.5° $1.5{}^{\circ}$C colder during winter while reducing precipitation and increasing snowfallAerosol effects are diagnosed by analyzing how changes in diabatic heating alter the winter monsoon potential vorticity intrusionColder surface temperatures can be attributed to both aerosol direct effects and circulation responses to cloud‐aerosol interactions [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) are important atmospheric species that regulate the formation of both ozone and secondary organic aerosol. Compared with continental environments, VOC species, concentration and origins in marine environments were much less understood. Here, we conducted a 2‐month VOCs measurement using a proton‐transfer‐reaction mass spectrometer during the cruise of DongFangHong III research vessel over the eastern oceanic areas of China in winter 2019. According to the location of DongFangHong III, we divided our cruise into five regions: Qingdao port (QD), Zhoushan port (ZS), Bohai Sea (BHS), Yellow Sea (YS), and East China Sea (ECS). For most individual VOCs, their concentration exhibited the trend of ZS > QD > BHS > YS > ECS. A decreasing tendency was also found when the measurement location was progressively farther away from the coastline. Further, we performed Positive Matrix Factorization and retrieved five distinct VOC sources, including shipping emission, DongFangHong III emission, regional background, aged transport, and port and nearshore emission. Contributions of these five factors varied depending on the location, influenced by emission, atmospheric oxidation, and meteorological conditions. In addition, the inland anthropogenic sources were found to have a larger contribution than oceanic ones. Overall, by conducting in situ measurements of VOCs and source apportionment, this study complements the lack of information on the speciation, abundance, and sources of VOCs in the marine environment of China. Plain Language Summary: Compared to their better‐studied continental counterparts, marine volatile organic compounds (VOCs), critical precursors for ozone and secondary organic aerosol formation, are poorly characterized. In this study, we measured VOCs across China's eastern offshore areas during a winter 2019 voyage of the DongFangHong III. Our study region spanned five distinct areas: Qingdao port, Zhoushan port, and the Bohai, Yellow, and East China Seas. We observed a decline in most VOC concentrations sequentially from Zhoushan port to the East China Sea, and alongside increasing distance from the coastline. We identified five VOC sources, including emissions from shipping, the research vessel itself, regional background, aged transport, and combined port and nearshore activities. The influence of these sources varied by location, reflecting variations in emissions, atmospheric reactions, and local weather conditions. Notably, VOCs from inland anthropogenic activities overshadowed those from marine sources. This study provides critical insights into the VOC composition and sources over China's eastern marine environment, addressing a gap in our understanding of marine VOCs. Key Points: Volatile organic compounds (VOCs) across China's eastern offshore areas were measured during a winter 2019 voyage of the DongFangHong IIIMost VOC concentrations declined alongside increasing distance from the coastline5 VOC sources were identified with inland anthropogenic activities overshadowing those from marine sources [ABSTRACT FROM AUTHOR]

The atmospheric activity on Kalimantan Island (KI) is important for regulating regional weather and climate. This study investigates the effect of autumn soil moisture over KI on following winter precipitation over southern China (SC) during 1968–2014. The results show that the autumn soil moisture over the KI has a significant negative correlation with subsequent winter precipitation over SC. The correlation remains statistically significant when using partial correlation to filter out the concurrent influences of El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) signals. The soil moisture anomalies over KI, which initiate in the autumn and persist into the winter, lead to changes in local thermal conditions and atmospheric temperature. Negative soil moisture anomalies over KI will result in positive heating anomalies of the atmosphere above the land surface. This atmospheric heating causes ascending motion, which creates a semi‐closed vertical circulation from KI to the tropical northwest Pacific. This vertical circulation would strengthen the northwest Pacific anticyclone and weaken the East Asian winter monsoon (EAWM). Consequently, southwesterly water vapour flux prevails in the SC as well as the South China Sea (SCS), facilitating the transportation of more water vapour into the SC. Simultaneously, water vapour convergence in the SC. Collectively, these contribute to an addition of precipitation over SC. [ABSTRACT FROM AUTHOR]

Societal Impact Statement Summary Long‐term phenology data is crucial to elucidate the effects of climate change on plants, but such efforts are lacking in the tropics. Historical records at the Singapore Botanic Gardens and ongoing phenological monitoring have allowed us to study leafing behaviour and its association with changing rainfall patterns over nine decades in equatorial Singapore. We found that the leafing behaviour of trees in our tropical site changed between 1927 and 2022. This study was made possible by assiduous past and present record‐keeping, and demonstrates the potential of botanical gardens as sentinels of environmental change, which is especially important in the tropics. Understanding tropical phenology and the potential impacts of a changing climate requires long‐term monitoring but such efforts are rare in the tropics. We took advantage of the availability of historical phenological and weather records at the Singapore Botanic Gardens and ongoing phenological monitoring to ask whether leafing behaviour has changed over an exceptionally long period of about nine decades, and whether these changes are associated with changing rainfall patterns in supposedly aseasonal Singapore. Records of leaf flush intervals from 1927 to 1939 in the Singapore Botanic Gardens were compared against leaf flush intervals calculated from present‐day phenological monitoring conducted since 2016. Daily rainfall was modelled as a predictor of present‐day leaf flushing events using moving‐window analyses. Leaf flush intervals have shortened considerably for most of the species that were monitored in the two periods. Mean daily rainfall over a window of 1 to 4 months before was negatively associated with probability of leaf flushing for five species and positively associated with four out of a total of 23 species analysed. Long‐term rainfall records from 1929 to 2022 show that February has become drier and May has become wetter since the 1960s. The results consistently support that more distinctive dry and wet periods today compared to nine decades ago have resulted in more frequent leaf flushing, which may have implications for plant‐herbivore interactions, nutrient cycling and consequently plant health and ecosystem resilience. We also demonstrate the potential and importance of supporting long‐term research in botanical gardens in the tropics. [ABSTRACT FROM AUTHOR]

In the final paper in this series, we review how remarkable advances in weather forecasting over successive decades have changed the role of the UK guidance forecaster. We then look at what might happen to this role in the future by examining how the continued growth of artificial intelligence might impact upon weather forecasting and whether forecasts will continue to improve. By contrast we also consider aspects such as risks to the observing network, which could potentially have an adverse effect. We also ask "will the weather forecaster still have a role in the future?" [ABSTRACT FROM AUTHOR]

A written account of two flood events in 1844 and 1877 at Easkey in Co. Sligo on the west coast of Ireland is explored with several meteorological datasets and historical newspaper accounts. Gridded daily precipitation fields for Ireland for the late twentieth century are analysed to assess rainfall extremes and most probable month of the annual maximum. Historic rainfall datasets are analysed to corroborate the account of the floods. A lot of rainfall data have survived from the nineteenth century, but there is still an imperfect match between the written account and the old weather records. [ABSTRACT FROM AUTHOR]

The management of big game harvest is important for maintaining viable populations and providing recreational opportunities to hunters. There are numerous strategies used by management agencies to achieve these goals, but they are complicated by variation in factors that are difficult to control, such as harvest success rates. For harvest management decisions to have the desired effect on big game populations, the mechanisms affecting factors like harvest success rates need to be properly understood. We used Bayesian hierarchical survival models to explore the factors influencing spatial and temporal variation in moose (Alces alces) harvest success rates in Ontario, Canada. We estimated harvest success rates from hunter reports from 59 Wildlife Management Units from 2000–2019. Overall, harvest success rates were primarily influenced by variables under the control of management agencies, such as season length and tag allocations, but they were also affected by external factors like moose density and weather. Season length, while positively related to harvest success for shorter seasons (e.g., <25 days), exhibited limited influence for longer seasons (>25 days). Our results were largely consistent across spatial and temporal scales, with a similarly strong positive effect of moose density and negative effect of tag allocation between management units and across years. This study emphasizes the need for managers to recognize the inherent uncertainty in harvest outcomes beyond their control and the importance of open communication with hunters in achieving effective harvest management, while offering concrete pathways for influencing harvest success. [ABSTRACT FROM AUTHOR]

Hymenoscyphus fraxineus causes ash dieback in Europe. It overwinters on ash leaf residue (rachis) within the forest litter. In late spring, the fungus produces apothecia on the rachises and releases ascospores to infect leaves. Previous studies reported that H. fraxineus was able to produce apothecia on the rachis for 5 years after the leaf infection under artificial conditions. However, ash litter is known to decompose rapidly in situ. We therefore monitored the decomposition kinetics of ash leaf debris and the persistence of the pathogen, as well as its ability to produce apothecia in the forest litter. For this, leaves shed in autumn in stands affected by ash dieback were placed in mesh bags and left in the forest litter for 6, 18 and 30 months. At each sampling period, litter mass loss and level of colonization of the rachises by H. fraxineus were measured, as was the pathogen's ability to produce apothecia on them. Despite high fragmentation, about 14% of the rachis dry weight remained in the mesh bags after 30 months, and the pathogen retained the ability to produce apothecia on these rachises. A simulation estimating the age composition of the colonized rachises present in the litter during the fruiting period was developed from these results. It shows that the persistence of H. fraxineus in old rachises of the litter represents a reservoir of inoculum that could compensate for poor colonization of autumn leaves and revive local outbreaks after years of unfavourable weather for the development of the pathogen. [ABSTRACT FROM AUTHOR]

Functional analysis of variance (ANOVA) models are often used to compare groups of functional data. Similar to the traditional ANOVA model, a common follow‐up procedure to the rejection of the functional ANOVA null hypothesis is to perform functional linear contrast tests to identify which groups have different mean functions. Most existing functional contrast tests assume independent functional observations within each group. In this article, we introduce a new functional linear contrast test procedure that accounts for possible time dependency among functional group members. The test statistic and its normalized version, based on the Karhunen–Loève decomposition of the covariance function and a weak convergence result of the error processes, follow respectively a mixture chi‐squared and a chi‐squared distribution. An extensive simulation study is conducted to compare the empirical performance of the existing and new contrast tests. We also present two applications of these contrast tests to a weather study and a battery‐life study. We provide software implementation and example data in the Supplementary Material. [ABSTRACT FROM AUTHOR]

Increased female age at mating is considered a detrimental factor on reproductive output and fitness in insects, even if the impact is rather species specific. The effect of delayed mating on reproductive output has been widely studied in pest species controlled with mating disruption, as if the method is not fully effective in suppressing matings, it could still delay them, limiting female fitness and pest damage. Female mating delay, however, may also occur in natural habitats without invoking mating disruption. We studied the effect of female delayed mating in Cerambyx welensii (Küster) (Coleoptera: Cerambycidae), an oak‐living sapro‐xylophagous longhorn beetle considered a critical factor in oak decline. Several life history and ecological traits may potentially delay mating, including low abundance, (re)colonisation processes, sexual communication channel, host‐produced kairomones, operational sex ratio, reproductive interference and adverse weather conditions. We conducted laboratory tests to assess the impact of mating delays (0‐, 10‐, 20‐ and 30‐day post‐emergence) on reproductive output. Data showed that mating delay until at least 20 days of age had a limited effect on mating success, lifetime fecundity, longevity and fertility. The daily fecundity pattern depended on mating delay, and virgin females showed ovarian retention. We conclude that C. welensii females have evolved physiological adaptations to overcome mating delays and optimise fitness. We discuss our results from an evolutionary perspective, considering specifically the risk of early predation and egg‐laying time limitation. We hypothesise that unpredictable recurrent stochastic variation in male availability could act as an additional driver selecting for synovigeny in this longhorn species. [ABSTRACT FROM AUTHOR]

Aflatoxin contamination in peanuts (Arachis hypogaea L.) is a significant public health risk. Aflatoxin is detected postharvest after inspection of loads associated with grading at peanut buying points, leaving growers and shellers in a precarious position. Stricter limits on aflatoxin contamination could restrict the United States access to international markets. Predicting aflatoxin risk remains challenging, but improved tools could help inform postharvest storage segregation decisions and alert industry stakeholders to seasonal threats. This study aimed to develop and evaluate multiple statistical models that estimate the regional status of peanut aflatoxin contamination based on preharvest weather conditions. Our approach expanded on an existing peanut aflatoxin model for which a new geographic area and time period were tested. Weather variables served as independent variables to predict the risk of aflatoxin as the proportion of samples with greater than 20 ppb and 4 ppb aflatoxin (PGT20 [the proportion of samples with greater than 20 ppb aflatoxin] and PGT4 [the proportion of samples with greater than 4 ppb aflatoxin], respectively) across 10 counties in Georgia for 2018–2022. Best-performing models were developed through multiple linear stepwise regression explaining more than 72% and 41% of the variability in PGT20 and PGT4, respectively. Model performance further varied whether it was a year of low or high aflatoxin incidence, with temperature observed as a key influencing factor across best-performing models. This study established an adaptive approach to monitoring and managing aflatoxin risk through statistical predictive modeling, with output targeting farmers, industry, regulators, and public health officials. Future model development will aim to improve interpretation and confidence with in-season aflatoxin prediction and efficacy testing of this approach across space and time. [ABSTRACT FROM AUTHOR]

The herbicide dicamba (3,6-dichloro-2-methoxybenzoic acid) is commonly used to control broadleaf weeds in soybeans. Dicamba, however, is susceptible to volatilization and drift, thereby causing significant plant damage to nontarget crops downwind. Dicamba was reformulated to reduce volatility and off-target movement. The effectiveness of the dicamba reformulation was assessed by quantifying dicamba emissions following spray application and investigated how meteorological factors influenced the off-target movement. The experiments were conducted at the University of Minnesota Agricultural Experiment Station (UMORE Park) during the growing season of 2018, 2019, 2021, and 2022. Multiple high-flow polyurethane foam air samplers were used to measure dicamba concentrations downwind from a 4-ha soybean field sprayed with dicamba. Dicamba emissions were estimated using backward Lagrangian modeling constrained by the air sample observations. The results indicate that dicamba emissions and downwind transport were significant for several days following application. Further, non-traited soybeans located within 15–45 m showed substantial dicamba-related damage. In warmer, drier seasons, increased dicamba emissions caused more severe damage to downwind soybeans, likely worsened by drought stress preventing recovery. Favorable atmospheric conditions that reduced potential drift can be difficult to achieve in terms of the typical weather experienced over agricultural sites in the Upper Midwest. These results indicate that the dicamba reformulation has not adequately prevented significant post-spray volatilization losses and downwind transport. [ABSTRACT FROM AUTHOR]

The ambient air quality is continuously declining especially in emerging countries because of rapid rate of urbanization, industrialization, and allied activities. Thus, the principal objective of this research is to inspect the spatiotemporal variation of particulate matters and to identify the drivers of pollutant dispersal. The month‐wise PM10 and PM2.5 data of 2022 and 2023 were obtained from the West Bengal Pollution Control Board. Meteorological datasets such as wind speed (m/s) and wind direction (degree) were collected from the NASA power access website. The HYSPLIT (Hybrid Single‐Particle Lagrangian Integrated Trajectory) model was applied to identify the pollutant's trajectories. Results showed that Purulia station stood highest in case of absolute AQI 715 (23‐1‐2022 at 7 a.m.), PM2.5 483.47 µg/m3 (23‐1‐2022 at 8 a.m.), and PM10 682.28 µg/m3 (23‐1‐2022 at 7 a.m.), respectively. During winter, the vertical expansion of particles was within the 100‐m boundary layer while during summer, it dispersed vertically and crossed 2000 m above the ground surface due to the combined effect of atmospheric conditions such as wind speed, wind direction, air pressure, and temperature. Moreover, the industrial outputs of Jharkhand and West Bengal play a significant role in elevating the pollution level. Plantation of suitable pollution‐resistant plants including Banyan (Ficus bengalensis), Mango (Mangifera indica), Peepul (Ficus religiosa), Guava (Psidium guajava), Kadam (Neolamarkia cadamba), Neem (Azadirachta indica) is a suitable management technique against pollution in this region. [ABSTRACT FROM AUTHOR]

This study proposes a model‐based methodology to estimate design precipitation for long durations during the winter and spring seasons (October to June) through its application to the drainage areas of two dams in the Columbia River Basin, United States. For basins with large reservoir storage or snowpack, design precipitation and floods need to be estimated based on long‐duration processes rather than focusing only on flood peaks or single storm durations. This study used the advanced research version of weather research and forecasting (WRF) model to maximize the target precipitation over the drainage areas by means of the Atmospheric Boundary Condition Shifting and Relative Humidity Perturbation with relaxed moisture flux thresholds. The greatest cumulative basin‐average precipitation depths during Oct–Jun were estimated to be 1220.5 and 1595.4 mm for the drainage areas of Bonneville and Libby Dams, respectively. The 95% confidence interval (CI) of the exceedance probabilities of the estimated design precipitation depths were found to range from 10−3 to 10−5 at Bonneville Dam's drainage area. Those orders were found to be comparable with the documented exceedance probabilities of PMP/PMF in the US. The estimated design precipitation and corresponding atmospheric/land‐surface fields together will drive a physical model to estimate the design flood. [ABSTRACT FROM AUTHOR]

This article examines the scientific background of Daniel Defoe's The Storm (1704). This work is a collection of letters on the Great Storm, a tempest which battered the south of England on 26–27 November 1703 causing casualties in the thousands and extensive damage. Like other extreme natural phenomena, the Great Storm was interpreted by many as divine warning. This article argues that, differently to Defoe's other works on the Great Storm, The Storm reconciles the traditional religious reading of catastrophes with recent breakthroughs in empiricist philosophy and early meteorology. In its concluding section, the article offers a reassessment of Defoe's interest in scientific ideas in The Storm so as to include early‐eighteenth‐century empiricism and examines Defoe's ambivalent attitude towards them. [ABSTRACT FROM AUTHOR]

Observational and modeling studies have elucidated the influential role played by the southern and northern extratropical Pacific (SEP and NEP) forcing in shaping dynamics of tropical Pacific climate variability. However, the relative importance of the NEP and SEP and the timescale on which they impact the tropics remain unclear. Using a linear inverse model (LIM) that selectively incorporates or excludes tropical‐extratropical coupling, we find a reduction in tropical interannual variability (∼40%) and low‐frequency (sub‐decadal to decadal) variability in the southeastern tropical Pacific region (∼70%) in the absence of SEP. Conversely, the absence of NEP yields no significant impact on tropical interannual variability but markedly diminishes low‐frequency variability in the central tropical Pacific region (∼70%). LIM and statistic diagnostics on CMIP6 models show the low‐frequency to total variability ratio in the tropical Pacific depending on their NEP and SEP representation. Models with more (less) low‐frequency power tend to show stronger NEP (SEP) dynamics. Plain Language Summary: The tropical Pacific climate variability exerts a strong impact on global climate, regional weather, and marine ecosystems. The tropical and extratropical Pacific are closely coupled with each other through oceanic and atmospheric processes. Previous studies have shown that the southern and northern extratropical Pacific (SEP and NEP) forcing greatly impact the tropical Pacific climate variability. To understand and predict tropical Pacific variability, it is necessary to study the relative importance and the timescale on which the SEP and NEP exert their influence. In this study, we use an empirical dynamical model to exclude the impacts of SEP or NEP on the tropical Pacific based on the observational data. We find that the absence of SEP leads to a significant reduction of interannual variance (∼40%) and the low‐frequency (sub‐decadal to decadal) variance in the southeastern tropical Pacific region (∼70%), while the absence of the NEP does not change the interannual variance but significantly reduces the low‐frequency variance in the central tropical Pacific region (∼70%). In observations, the ratio of low‐frequency to total tropical variability is 0.36, while CMIP6 models exhibit a wider range, with enhanced low (high) frequency power associated with stronger NEP (SEP) dynamics. Key Points: The SEP dynamics contribute ∼40% of the tropical interannual variance and ∼70% of the southeastern tropical low‐frequency varianceThe NEP dynamics do not impact the tropical interannual variance but lead to ∼70% of the central tropical low‐frequency variabilityCMIP6 models show stronger NEP (SEP) dynamics tend to manifest ENSO with more (less) low‐frequency (>6 years) power [ABSTRACT FROM AUTHOR]

An obvious long‐term drying trend in recent early springs (February–March–April) is observed over southeastern China (SEC). Here, we attribute this drying to the weakened subtropical westerlies and deflected by the Tibetan Plateau (TP). Climatologically, the low‐level southwesterlies at the southeastern margin of the TP, a branch of the upstream subtropical westerly jet deflected by the TP terrain, bring water vapor to SEC and the southerlies move upward over SEC mainly through isentropic gliding mechanism, inducing persistent precipitation in early spring. However, the subtropical westerlies weakened significantly in recent decades due potentially to the decreased Eurasian snow cover. Consequently, an easterly trend appears along the southern margin of the TP with anomalous northeasterlies over SEC. These northeasterlies suppress both moisture supply and upward motions over SEC, and reduce regional early spring precipitation. Our results highlight the interaction between the TP terrain and the weakened subtropical westerlies that leads to the drying SEC. Plain Language Summary: Spring precipitation in southeastern China (SEC) is a major rainband during the pre‐flood season in East Asia, which is significant for agricultural production and social economy. However, in the recent few decades, a robust long‐term drying trend has occurred over SEC in early spring. In this study, we propose a new mechanism for the decreased SEC precipitation and highlight the important influence of the weakened subtropical westerlies and their interaction with the Tibetan Plateau (TP). Deflected by the TP large terrain, the upstream weakened subtropical westerlies induce weakened westerlies and southwesterlies along the southern and southeastern margins of the TP, respectively. As a result, the weakened southwesterlies at the southeastern TP not only reduce the moisture transport downstream, but also suppress the ascending motions over SEC through the isentropic gliding mechanism. Both the water vapor and atmospheric circulation conditions finally induce the drying SEC in recent early springs. Key Points: An early spring drying trend has occurred in southeastern China (SEC), much of this can be attributed to the weakened subtropical westerliesDeflected by the Tibetan Plateau (TP), the weakened subtropical westerlies decelerate downstream westerlies along the TP's southern marginThe decelerated westerlies at the southeastern TP suppress moisture supply and rising motions over SEC, both processes cause the drying SEC [ABSTRACT FROM AUTHOR]

We investigate the synoptic and mesoscale dynamics of two wet and two dry cold surges in January 2021 using a combination of observations, reanalysis, and convective‐scale model forecasts from the Met Office Unified Model (MetUM). We focus on the wet surges, and particularly the wettest days which are locally extreme over Singapore and the surrounding region (i.e., the daily mean and area‐averaged rainfall over 20 years exceeds the 99th percentile). On the large scale, the wet surges are characterized by an anomalously strong anticyclone over Siberia prior to their onset. The anticyclone and resultant surge winds are stronger than those of the dry surges. There is also a relatively moist (dry) environment prior to the onset of the wet (dry) surges, with the Madden‐Julian Oscillation (MJO) being in Phase 3 (Phase 6). On the mesoscale, the combination of the cold surge and a local tropical low produce strong, moist north‐easterly winds and convection over the Singapore region. The equatorward advection of positive anomalies of equivalent potential temperature resembles a weak gravity‐current‐like structure at its head, although the spatial scale is much too large for a gravity current. There is a moist bias in the model forecasts, although the precipitation is underestimated regionally during the wet surges and particularly on the extreme rainfall days. Overall, the model forecasts perform well synoptically but not in the details of mesoscale convection. Plain Language Summary: Cold surges are weather systems in the winter monsoon that bring strong north‐easterly winds, colder air, and sometimes very heavy rainfall and flooding to Singapore and the surrounding region. We investigate the structure and development of two wet and two dry cold surges in January 2021 using a combination of observations and high‐resolution model forecasts. We focus on the wet surges, and especially the wettest days, which are characterized by very heavy rainfall over Singapore and the surrounding region. The wet surges are driven by a very strong high‐pressure system over Siberia, which results in strong north‐easterly winds. These north‐easterlies are stronger in the wet surges than in the dry surges. A relatively moist (dry) environment precedes the wet (dry) surges. On the smaller scale, the combination of the cold surge and a local tropical low‐pressure system produce strong, moist north‐easterly winds and heavy rainfall over the Singapore region. Overall, the model forecasts the large‐scale well but not the smaller‐scale details of heavy rainfall. Key Points: Two wet cold surges produced locally extreme rainfall over Singapore in January 2021 and were followed by two dry surgesThe dynamics of the January 2021 cold surges and the associated convection are explored in convection‐permitting forecastsThe combination of the cold surge and a tropical low produced strong, moist north‐easterlies, and heavy rainfall over the Singapore region [ABSTRACT FROM AUTHOR]

Weather features, such as extratropical cyclones, atmospheric rivers (ARs), and fronts, contribute to substantial amounts of precipitation globally and are associated with different precipitation characteristics. However, future changes in these characteristics, as well as their representation in climate models, remain uncertain. We attribute 6‐hourly accumulated precipitation to cyclones, moisture transport axes (AR‐like features), fronts, and cold air outbreaks, and the combinations thereof in 10 ensemble members of the CESM2‐LE between 1960 and 2100 under the SSP3‐7.0 scenario. We find that, despite some biases in both precipitation and weather features, CESM2‐LE adeptly represents the precipitation characteristics associated with the different combinations of weather features. The combinations of weather features that contribute most to precipitation in the present climate also contribute the most to future changes, both due to changes in intensity as well as frequency. While the increase in precipitation intensity dominates the overall response for total precipitation in the storm track regions, the precipitation intensity for the individual weather features does not necessarily change significantly. Instead, approximately half of the increase in precipitation intensity in the storm track regions can be attributed to a higher occurrence of the more intensely precipitating combinations of weather features, such as the co‐occurrence of extratropical cyclones, fronts, and moisture transport axes. Plain Language Summary: Most precipitation is associated with weather features such as storms, atmospheric rivers, and fronts. Different combinations of these weather features are associated with different precipitation characteristics, but how these characteristics are represented in climate models as well as their possible future changes is not known. We attribute 6‐hourly accumulated precipitation to weather features, such as storms, fronts, and atmospheric rivers, from 1960 to 2100 under a high greenhouse emission scenario in a climate model. Despite some biases, the climate model represents the precipitation characteristics associated with these weather features well. We find that the weather features with the largest contribution to precipitation in the current climate also contribute the most to future changes in precipitation. The changes are caused by changes in both frequency of occurrence and precipitation intensity. Key Points: We attribute precipitation to cyclones, fronts, moisture transport axes, and cold air outbreaks in 10 ensemble members CESM2‐LE in 1960–2100CESM2‐LE adeptly represents the precipitation characteristics associated with the different weather features and their combinationsCo‐occurring weather features, associated with intense precipitation, contribute to a larger fraction of the precipitation in the future [ABSTRACT FROM AUTHOR]

Local ensemble transform Kalman filter (LETKF)‐based Ocean Research Analysis (LORA) version 1.0 datasets for western North Pacific (WNP) and Maritime Continent (MC) regions (LORA‐WNP and ‐MC, respectively) are released through the JAXA‐RIKEN Ocean Analysis website. The LORA datasets are created using an eddy‐resolving LETKF‐based ocean data assimilation system with satellite sea‐surface temperature, salinity, and height data and with in‐situ temperature and salinity data assimilated daily. The LORA datasets include 128‐member ensemble analyses at the sea surface (2D), each term of mixed‐layer temperature and salinity budget equations, and the related variables (2D) such as mixed‐layer depth and heat and freshwater fluxes as well as system grid information and analysis ensemble mean and spread (3D), from August 2015 to January 2024 (as of June 2024). The LORA datasets are useful for geoscience research and practical applications, especially for particle tracking, boundary conditions of atmospheric models, and research on spatiotemporal variations in sea‐surface temperature and salinity. [ABSTRACT FROM AUTHOR]

Flash droughts (FDs) are distinguished by a rapid development associated with strong precipitation deficits and/or increases in atmospheric evaporative demand in the short‐term, but little is known about the atmospheric conditions underlying these events. In this study, we analyse for the first time the atmospheric dynamics involved in the development of FDs in Spain over the period 1961–2018. FDs are related to large‐scale atmospheric circulation patterns affecting the region, in particular with the positive phase of the North Atlantic Oscillation (NAO). The NAO is the main atmospheric driver of FDs in winter and autumn, and it is essential in explaining FD development in spring. We also found that FDs are typically linked to strong positive anomalies in 500 hPa geopotential height and sea level pressure over the region during the weeks prior to the onset. At the synoptic scale, the most common weather types (WTs) recorded during the development of FDs are Anticyclonic Western (ANT_W_AD), East (E_AD) and Northeast (NE_AD) advection, and Anticyclonic (ANTICYC). In particular, ANTICYC WT is the main atmospheric driver of FDs in summer. Ridging conditions occur frequently during FDs in all seasons, being the most important factor controlling FD development in spring. Likewise, we noted that some of the FDs recorded in summer are related to and/or exacerbated by Saharan air intrusions associated with pronounced ridges. The results of this research have important implications for the understanding, monitoring and prediction of FDs in Spain, providing a detailed assessment of the main atmospheric dynamics involved in FD triggering at different spatial scales. [ABSTRACT FROM AUTHOR]

Climate models indicate that a warmer environment will increase low‐level moisture, potentially intensify extreme precipitation. However, its impact on different rainfall types remains unclear. Using satellite data, we examined changes in light (0‐95th percentile, ≤5.28 mm hr−1) and heavy (95‐100th percentile, >5.28 mm hr−1) precipitation in the tropics from 1998 to 2019. Our findings show a −9 ± 2% (23 ± 2%) change in heavy (light) rain intensity and a 13 ± 2% (−24 ± 1%) change in heavy (light) rain frequency. These changes link to warmer sea surface temperatures, increased atmospheric stability and water vapor, and weakened upward velocity. These insights shed light on how heavy and light precipitation patterns respond to changing climate, emphasizing the complexities within the hydrological cycle. Plain Language Summary: The hydrologic cycle depends greatly on precipitation. With the expectation of climate warming causing substantial changes to the global water cycle, comprehending these shifts becomes pivotal in foreseeing how climate changes will affect society. Climate models suggest that as temperatures rise, low‐level moisture will increase. However, the specific impacts of this heightened moisture on the intensity and frequency of precipitation events remain uncertain. Analyzing data from the Tropical Rainfall Measuring Mission (1998–2019), we found notable changes: a 23 ± 2% increase in light rain intensity, a −9 ± 2 % decrease in heavy rain intensity, a 13 ± 2 % rise in heavy rain frequency, and a significant −24 ± 1% decrease in light rain frequency. These changes result diverse factors like warming oceans, stabilized atmospheric conditions, increased water vapor, and weakened upward velocity. This underscores the intricate interplay between different rainfall types and how they respond to the evolving climate. Key Points: In the tropics from 1998 to 2019, heavy rain intensity decreased and light rain intensity increasedIn the tropics from 1998 to 2019, heavy rain frequency increased and light rain frequency decreasedRain shifting patterns linked to increased SST, atmospheric stability, and water vapor and decreased upward velocity [ABSTRACT FROM AUTHOR]

Understanding the key drivers controlling rainfall stable isotope variations in inland tropical regions remains a global challenge. We present novel high‐frequency isotope data (5–30 min intervals) to disentangle the evolution of six stratiform rainfall events (N = 112) during the passage of convective systems in inland Brazil (September 2019–June 2020). These systems produced stratiform rainfall of variable cloud features. Depleted stratiform events (δ18Oinitial ≤ −4.2‰ and δ18Omean ≤ −6.1‰) were characterized by cooler cloud‐top temperatures (≤−38°C), larger areas (≥48 km2), higher liquid‐ice ratios (≥3.1), and higher melting layer heights (≥3.8 km), compared to enriched stratiform events (δ18Oinitial ≥ −3.8‰ and δ18Omean ≥ −5.1‰). Cloud vertical structure variability was reflected in a wide range of δ18O temporal patterns and abrupt shifts in d‐excess. Our findings provide a new perspective to the ongoing debate about isotopic variability and the partitioning of rainfall types across the tropics. Plain Language Summary: Stable water isotopes were used to analyze the formation of stratiform rainfall in the inland tropics of Brazil. The growth of this type of precipitation is associated with continuous condensation‐deposition processes. High‐resolution isotopic variations were analyzed using meteorological information, including satellite products and vertical micro rain radar observations. Our results showed that for stratiform rainfall, clouds with higher temperatures are related to more heavy isotopes, while less heavy isotopes are more frequent for stratiform rainfall coming from colder clouds. Our findings provide a detailed framework to improve isotope enabled models skills to represent the isotopic composition for different cloud types based on observations. Key Points: Weather systems and cloud development modulate rainfall isotope depletionsCloud top temperature, rain area, and water content (liquid‐ice ratio) are key parameters to decipher tropical rainfall isotope variationsIsotopic variations during intra‐evens are controlled by cloud phases, rainfall vertical structure, and the height of the melting layer [ABSTRACT FROM AUTHOR]

Surface solar radiation is fundamental for terrestrial life. It provides warmth to make our planet habitable, drives atmospheric circulation, the hydrological cycle and photosynthesis. Europe has experienced an increase in surface solar radiation, termed "brightening," since the 1980s. This study investigates the causative factors behind this brightening. A novel algorithm from the EUMETSAT satellite application facility on climate monitoring (CM SAF) provides the unique opportunity to simulate surface solar radiation under various atmospheric conditions for clouds (clear‐sky or all‐sky), aerosol optical depth (time‐varying or climatological averages) and water vapor content (with or without its direct influence on surface solar radiation). Through a multiple linear regression approach, the study attributes brightening trends to changes in these atmospheric parameters. Analyzing 61 locations distributed across Europe from 1983 to 2020, aerosols emerge as key driver during 1983–2002, with Southern Europe and high elevations showing subdued effects (0%/decade–1%/decade) versus more pronounced impacts in Northern and Eastern Europe (2%/decade–6%/decade). Cloud effects exhibit spatial variability, inducing a negative effect on surface solar radiation (−3%/decade–−2%/decade) at most investigated locations in the same period. In the period 2001–2020, aerosol effects are much smaller, while cloud effects dominate the observed brightening (2%/decade–5%/decade). This study therefore finds a substantial decrease in the cloud radiative effect over Europe in the first two decades of the 21st century. Water vapor exerts negligible influence in both sub‐periods. Plain Language Summary: This study explores the recent increase in surface solar radiation in Europe, commonly referred to as "brightening," which began in the mid‐1980s. Surface solar radiation is crucial for life on Earth, fostering warmth, shaping wind patterns, and fueling the hydrological cycle and photosynthesis. Utilizing data derived from satellites, we simulated surface solar radiation under different atmospheric conditions regarding clouds, aerosols, and water vapor. This allowed us to separate the individual effects and analyze their contributions to the observed brightening across 61 locations in Europe from 1983 to 2020. We find that the decrease in aerosols was the dominant driver for the brightening during the initial period from 1983 to 2002. Southern Europe and high‐elevation areas showed modest aerosol effects, while Northern and Eastern Europe experienced higher values. Cloud effects were predominantly negative (decreasing surface solar radiation) at most locations. However, between 2001 and 2020 the aerosol effect resulted much smaller and the brightening was mostly attributed to a decrease in cloudiness during that sub‐period. Water vapor was found to have a negligible impact on surface solar radiation trends. Key Points: Satellite application facility on climate monitoring (CM SAF) Land Flux v1.0 surface solar radiation data agree well with station‐based measurements over Europe, also at high‐altitude locationsThe direct aerosol effect was the main driver of the European brightening from 1983 to 2002. Changes in cloudiness rather counteracted itFrom 2001 to 2020 the brightening in Europe was dominated by the cloud effect and the aerosol effect resulted much smaller [ABSTRACT FROM AUTHOR]

As a crucial element in the Earth's system, development of convective clouds is still insufficiently understood and simulated in both weather and climate models, particularly for small‐scale regional convective clouds. In this study, a series of convective clouds cases with relatively small scales are selected over south China, and the evolution characteristics of those convective clouds are investigated using high spatiotemporal resolution geostationary satellite data. Statistical results show that the shorter the life cycle or the smaller the area, the higher the proportion of convective clouds. Notably, approximately 79.23% of convective clouds have a life cycle of less than 3 hr, and 63.81% have an area of less than 500 km2 for selected cases. In addition, there are significant differences in the cloud characteristics and meteorological parameters during various convective cloud stages and durations. Nevertheless, the relative proportions of convective clouds at three identified stages remain relatively constant with almost no dependence on duration of convective clouds, which are 33.50%, 23.92%, and 42.58% for the developing, mature, and dissipation stages, respectively. In addition, we find that the cloud‐top cooling rate during the developing stage also affects the characteristics of the later stage of convective clouds. Quantitatively, the average cloud area and duration changed by 157.03 km2 and 0.17 hr when the cloud‐top cooling rate varies by 15 K/h. Plain Language Summary: Convective clouds have complex structures, develop rapidly, and pose a significant threat to aviation safety. The initiation and evolution of convective clouds are not well resolved, making the simulation of convective clouds highly challenging among current weather and climate models, particularly in south China, a hotpot of convective clouds. Evolution characteristics of convective clouds with relatively small spatial scales are investigated in this study based on the high spatiotemporal resolution Himawari‐8 data. It shows that convective clouds have significant diurnal variation, while with short‐term (duration less than 3 hr) and small‐scale (area less than 500 km2) convective clouds dominant. In addition, there are significant differences in cloud characteristics and meteorological conditions for convective clouds at various stages or with different durations. However, the duration proportion of convective clouds at different stages (developing, mature, and dissipation stages) remains basically the same relative to the total convective cloud life cycle, no matter how long the duration of convective cloud life cycle is. Key Points: Significant differences exist in cloud characteristics for convective clouds at various stages or with different durationsThe larger the cloud top cooling rate during the development stage, the smaller the maximum area and the shorter the cloud life cycleThe developing, mature, and dissipation stages account for 33.50%, 23.92%, and 42.58% of convective cloud duration, respectively [ABSTRACT FROM AUTHOR]

The coastal boundary layer height (CBLH/Coastal‐BLH) is critical in determining the exchange of heat, momentum, and materials between the land and ocean, thereby regulating the local climate and weather change. However, due to the complexity of geographical characteristics and meteorological conditions, accurate estimation of the CBLH remains challenging. Herein, based on continuous high‐resolution measurements of CBL performed from November 2019 to April 2020 in coastal Ningbo city in eastern China, an optimal weighted ensemble model (OWEM) integrating multi‐meteorological variables of the ERA5 reanalysis data sets is constructed and validated to estimate the CBLH. The mean absolute percentage error of the derived CBLH by OWEM is as low as 3%–5%, significantly lower than that of 36%–65% of the ERA5 CBLH products. Furthermore, three categories of different weather scenarios, that is, sunny, cloudy, and rainy, are separately discussed, and OWEM shows greater performance and higher accuracies in comparison with the traditional Least Absolute Shrinkage and Selection Operator, Random Forest, Adaboost, LightGBM, and ensemble model, among which, OWEM under fair weather days behave best, with a robust R2 of 0.97 and a minimum mean absolute error (MAE) of 23 m. Further training results based on wind flow classification, that is, land breeze, sea breeze, and parallel wind, also indicate the outperformance of OWEM than other models, with a relatively large error in parallel wind of 50 m. Subsequent analysis of the Shapley Additive Explanations method strongly correlated with model feature importance, both reveal that thermodynamic factors such as temperature (T2m) and wind velocity (10 m U) are the major factors positively related to estimation accuracy during sunny days. Nevertheless, Relative Humidity dominates on rainy and cloudy days, TP on land breeze days, and dynamic variables like 10 m U and 10 m V on entire types of wind flow weather. In conclusion, the accurate estimation of CBLH from OWEM serves as a feasible and innovative approach, providing technical support for marine meteorology and related engineering applications, for example, onshore wind power, coastal ecological protection, etc. Plain Language Summary: The coastal boundary layer height (CBLH) is fast becoming a key parameter in atmosphere‐ocean interaction studies, and machine learning has been thought of as an effective way to accurate estimate it. In this work, we present a new model called optimal weighted ensemble model (OWEM), which integrates several meteorological variables from reanalysis data sets to estimate the CBLH and make a comparison with the ERA5 BLH under different weather conditions. We also analyze the feature importance that affects estimation accuracy using the Shapley Additive Explanations method and identify several variables as essential factors, to better understand the applicability and characterization of the OWEM for sunny, cloudy, rainy, and different wind flow days. [ABSTRACT FROM AUTHOR]

Semiconducting photoresists hold great promise for scale‐up manufacturing of organic field‐effect transistors (OFETs) for integrated organic electronics. While photolithographic p‐type OFETs have achieved a considerable balance among patterning precision, electrical properties and process stability, it remains challenging for n‐type OFETs due to the inherent limited mobility and ambient instability. Herein, a n‐type semiconducting photoresist (SPr) is developed that is compatible with photolithography procedures. By utilizing the solvent‐driven force, a self‐encapsulated blend film with gradient semiconductor phase is prepared, where the underneath transistor active layer is protected by the upper cross‐linked network, avoiding solvent erosion and air doping. As such, a mobility up to 1.1 cm2 V−1 s−1 that is comparable with amorphous Si is achieved, with remained mobility by ≈90% after long‐term exposure to developer and stripper or atmospheric conditions. The sub‐micrometer patterning accuracy of SPr enables the fabrication of organic transistor arrays with a density of 9 × 105 units cm−1, which is comparable to other state‐of‐the‐art devices fabricated by the printing or photolithography, demonstrating immense potential in integrated organic electronics. [ABSTRACT FROM AUTHOR]

Electron energy loss spectra collected from fresh and corroded silver nanoparticles are compared with those from a number of reference materials, focusing on the M4,5 edge. Chemical shifts and changes in the energy loss near edge structure (ELNES) are described and found to be sufficient to distinguish metallic silver from chemically oxidised silver. The measurements, in conjunction with electron energy loss spectrum imaging, are used to assess the mechanisms for atmospheric corrosion of silver nanoparticles. We unambiguously assign the corrosion product under atmospheric conditions to be silver sulphide, but show the reaction process to be distinctly inhomogeneous, producing a variety of types of corroded particles.LAY DESCRIPTION: >Here, we use analytical electron microscopy to track the corrosion of silver nanoparticles and present chemical maps of the corrosion products. We show clear spectroscopic differences between metallic and corroded silver using the M4,5 electron energy loss spectral feature, which is not commonly studied. Our study shows that corrosion is due to interactions with sulphur in the atmosphere; and the corrosion is not uniform, but appears to develop from specific points on the surface of the nanoparticles. [ABSTRACT FROM AUTHOR]

In many animal species, larger body size is positively correlated with male mating success and female fecundity. However, in the case of insects, in high seasonality environments, natural selection favors a faster maturation that decreases the risk of pre‐reproductive death. However, this advantageous adaptation comes at a tradeoff, resulting in a reduction in body size. Maturation time is influenced by environmental factors, such as temperature, season length, and food availability during the rains. The geographic variation in these parameters provides an opportunity to study their impact on the adaptive evolution of body size in Pyrgomorphidae grasshoppers. These grasshoppers exhibit remarkable variation in body size and wing development and can be found in diverse plant communities across Africa, Asia, Australia, and tropical America. In this study, we utilized a phylogenetic approach to examine the evolution of body size, considering climatic factors, and the influence of sexual selection on size differences between males and females. We found a positive correlation between mean annual temperature and sexual size dimorphism (SSD). Remarkably, species exhibiting a strong bias toward larger females were found to be adapted to regions with higher temperatures. In the Pyrgomorphidae family, an intermediate body size was identified as the ancestral trait. Additionally, winged male and female grasshoppers were observed to be larger than their wingless counterparts. Despite the potential conflicting pressures on body size in males and females, these grasshoppers adhere to Rench's Rule, suggesting that sexual selection on males' body size may explain the evolution of SSD. [ABSTRACT FROM AUTHOR]

Piping plovers (Charadrius melodus sp.) rank among North America's most endangered shorebird species, facing compounding environmental challenges that reduce habitat availability and suppress recruitment and survival rates. Despite these challenges, research on the direct effects of climate variability and extremes on their breeding ecology remains limited. Here, we employ a spatiotemporal modelling approach to investigate how location, nest timing and weather conditions influence reproductive success rates in a small breeding population of C. m. melodus in Prince Edward Island (PEI), Canada from 2011 to 2023. Analysis of 40 years of monitoring records from a subset of nesting sites revealed that flooding and predation have been persistent sources of reproductive failures in this population, with unexplained losses increasing in recent years. Contrary to our hypotheses, our modelled results did not support a negative impact of extreme high temperatures and strong precipitation events on reproductive outcomes. Instead, we identified a positive effect of TMAX and no effect of strong precipitation, perhaps due to limited exposure to extreme high temperatures (>32°C) and context‐specific risks associated with precipitation‐induced flooding. However, trends in regional climate change are likely to increase exposure to—and the influence of—such factors in the near future. Our models also identified spatiotemporal variability in apparent hatch success over the study period, as well as worse hatch outcomes across popular beachgoing regions and for delayed nesting attempts. While our results offer preliminary insights into factors affecting breeding success in this population, further research will be imperative to enhance understanding of constraints on recruitment. To this end, we encourage the collection and analysis of additional time‐series data of prey populations, human activities, fine‐scale weather data and predator/flood risks associated with each nest on PEI. [ABSTRACT FROM AUTHOR]

Human behavior is a key driver of the biodiversity crisis, and addressing it requires changing individual choices and actions. Yet, the same processes that imperil biodiversity (e.g., urbanization) also alienate people from the experience of nature, eroding care for the natural world. Although averting this extinction of experience is increasingly recognized as a major contemporary conservation challenge, understanding of what constitutes nature experience remains elusive and few empirical studies have explored it directly. Most researchers have used nature interactions as a stand‐in for experience, even though experience extends beyond interactions. We aimed to determine what constitutes the experience of nature and to propose a holistic, empirically derived framework that incorporates the multiple dimensions and components of the experience of nature. Using a mixed‐method approach across 3 countries (the United States, Switzerland, and Israel), we conducted a multistage, conceptual content, cognitive mapping (3CM) exercise with 106 participants. This methodology included developing a prompt to capture participants' perceptions of nature experiences and subsequently refining and organizing their input into distinct components and underlying dimensions through an iterative engagement process. Beyond multisensory interactions with nature, experience of nature consisted of 2 dimensions: the circumstances in which interactions occur and the internal responses that encompass various cognitive, affective, and restorative benefits associated with nature interactions. These 3 dimensions had 33 components that occurred consistently across participants in the 3 countries. Frequently mentioned components included seeing animals, landscapes, or scenery; lack of human influence; weather conditions; relaxing, recharging; feeling good; and awe for nature. Fear and nature experienced at home were the least mentioned components. Together, our results showed that nature experience is a combination of nature interactions, circumstances, and internal responses. The emphasized components underscore the significance of offering access to extensive, less human‐influenced natural spaces. This in turn can foster a profound nature experience, cultivating feelings of connectedness and care for nature. [ABSTRACT FROM AUTHOR]

Migration plays a central role in many ecological and evolutionary processes. Global patterns of climatic variation are having a profound influence upon animal migration patterns. Even though regular counts of bird migrations at bottleneck sites can certainly offer insights into how natural populations of different species at different scales are responding to changes in weather conditions, they have not yet been widely used. By analysing a time series of regular counts, collected during autumn, of 126 species migrating during the daytime through one of the most important migratory bottlenecks in Western Europe, we found that an increase in temperature at the regional scale, as well as a decrease in precipitation level during the breeding period, may result not only in a decrease in the migration rate during autumn but also in a delay in the timing of fall migration. Furthermore, adverse weather conditions at the local scale interrupted bird migration through the bottleneck until favourable weather conditions returned. Importantly, temporal variation in the number of migratory birds followed a nonlinear pattern, something which might be partially due to the idiosyncratic responses of migratory species with different life‐history characteristics to changes in weather conditions. Our results highlight that migration is a nonlinear, multiscale and multi‐faceted process, suggesting that it will be difficult to predict the responses of idiosyncratic migratory species to the unpredictable effects of climate change. [ABSTRACT FROM AUTHOR]

Summary: The technique to overcome the challenge while implementing the fiber optical link is investigated using an alternative optical link called a free‐space optical (FSO) link with advanced modulation and signal processing techniques. A dual‐polarized 16‐quadrature amplitude‐modulated signal is transmitted over single and multi‐FSO channels under various atmospheric attenuation conditions. High bandwidth and data rates (up to 10 Gbps), unlicensed spectrum (above 300 GHz), and simplicity of deployment are significant benefits of the FSO system. However, the weather conditions of haze, rain, and fog cause signal attenuation when the optical carrier wave is transmitted over free space, and atmospheric turbulence is a challenge to FSO implementation, which degrades the transmission performance of optical signals for long‐distance communication. For 120 Gbps data transmission, the performance of a multi‐input and multi‐output (MIMO) FSO system is evaluated by observing the bit error rate (BER) and received signal constellation diagram. Optical signal‐to‐noise ratio (OSNR) parameters were iterated to determine the optimal value for back‐to‐back, single‐input, single‐output (SISO), and MIMO systems. Moreover, we examined the proposed system's output with recent articles, including MIMO, multiplexing, and various modulation techniques. The comparison of results shows that the suggested MIMO‐FSO model has enhanced the performance with the lower BER as less than 3.8 × 10−3 (log of BER is −2.42) forward error correction (FEC) limit for 18.7 km link range in clear air with 0.54 dB/km attenuation, 4.8, 4.5, 1.35, and 0.57 km under haze, light fog, medium, and heavy fog with 4.6, 6.9, 28.9, and 75 dB/km attenuations. [ABSTRACT FROM AUTHOR]

As a central topic in Behavioral Ecology, animal space use involves dynamic responses to social and ecological factors. We collared 22 rhesus macaques (Macaca mulatta) from six groups on Neilingding Island, China, and collected 80,625 hourly fixes over a year. Using this high‐resolution location data set, we quantified the macaques' space use at the individual level and tested the ecological constraints model while considering various environmental and human interfering factors. As predicted by the ecological constraints model, macaques in larger groups had longer daily path lengths (DPLs) and larger home ranges. We found an inverted U‐shape relationship between mean daily temperatures and DPLs, indicating that macaques traveled farther on mild temperature days, while they decreased DPLs when temperatures were too high or too low. Anthropogenic food subsidies were positively correlated to DPLs, while the effect of rainfall was negative. Macaques decreased their DPLs and core areas when more flowers and less leaves were available, suggesting that macaques shifted their space use patterns to adapt to the seasonal differences in food resources. By applying GPS collars on a large number of individuals living on a small island, we gained valuable insights into within‐group exploitation competition in wild rhesus macaques. Highlight: By applying GPS collars, we assessed home range quality and space utilization for 22 rhesus macaques in six groups.Our results offered supportive evidence for the ecological constraints model, indicating that within‐group exploitation feeding competition is the predominant factor influencing macaques' space use on Neilingding Island. [ABSTRACT FROM AUTHOR]

The Kingdom of Saudi Arabia (KSA) is characterized by a desert climate, with rainfall mainly occurring during the cooler months (November–April) and sometimes in conjunction with intense extratropical systems that can cause serious damage and casualties. Given the vast size of KSA, there are gaps in understanding the association between large‐scale atmospheric circulations and local organized rainfall events, and in characterizing the diversity of this association. To address these gaps, we analyse an in‐house 5‐km horizontal grid spacing regional atmospheric reanalysis that has been specifically generated for the Arabian Peninsula to explore the mechanisms behind the organized rainfall events over KSA. Nine major regions with distinct climate regimes were objectively selected to represent KSA rainfall climatology. The results demonstrate that organized thunderstorms over KSA only occur under sufficient moisture and environmental instabilities. Mesoscale convective systems responsible for organized rainfall generally develop and propagate with low‐level moisture flow from the nearby seas (the Red Sea to the west and Arabian Gulf to the east) toward the desert. In the central part of KSA, the most frequent physical mechanism responsible for rainfall is winter extratropical influence, followed by spring extratropical–tropical interactions, and spring tropical influence. The east coast is characterized by two rainfall modes: a continuous southwest–northeast rain corridor and concentrated southwestern rain. Large‐scale organized convection following three physically distinct mechanisms (extratropical, transition and tropical) is revealed along the west coast. [ABSTRACT FROM AUTHOR]

Scene text detection has been widely studied on haze‐free images with reliable ground truth annotation. However, detecting scene text in inclement weather conditions remains a major challenge due to the severe domain distribution mismatch problem. This paper introduces a domain adaptation curriculum learning method to address this problem. The scene text detector is self‐trained in an easy‐to‐hard manner using the pseudo‐labels predicted from foggy images. Thus, our method reduces the pseudo‐labeling noise level. Then, a feature alignment module is introduced to help the network learn domain‐invariant features by training a domain classifier. Experimental results show that our method improved significantly on both synthetic foggy data sets and natural foggy data sets, outperforming many state‐of‐the‐art scene text detectors. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Critical review of temperature criteria for controlling cracking due to concrete hardening Various limits for the concrete temperature are specified for the production of concrete on site. These are primarily to ensure the workability of the fresh concrete in extreme weather conditions and to ensure proper hydration. There are also additional concrete temperature requirements for certain applications to reduce the risk of cracking or crack intensity due to hardening‐induced restraint stresses. In this context, the maximum member temperature, the maximum fresh concrete temperature or the maximum temperature gradient across the cross‐section are generally limited. However, these limits are defined independently of the ambient temperature. The extent to which these temperature limits are justified in terms of the risk of cracking due to concrete hardening is investigated using thermo‐mechanical simulations on 3D volume models. In detail, the temperature and stress evolution due to concrete hardening is simulated for different member types and ambient boundary conditions and evaluated with respect to the associated risk of cracking. The systematic evaluation of the results shows that the general limits of maximum member temperature and fresh concrete temperature are only pragmatic solutions for controlling the risk of cracking due to concrete hardening. These limits should always be considered with regard to the ambient temperature. [ABSTRACT FROM AUTHOR]

Background: The complexity, high prevalence, and substantial personal and socioeconomic burden collectively render atopic dermatitis (AD) a major public health concern. Using crowdsourced Internet data has the potential to provide unique insights into this concern, as demonstrated by several previous studies. However, a comprehensive comparison across European countries remains lacking. Objectives: The study aimed to investigate AD‐related web searches across Europe to assess spatiotemporal variations and associations between disease‐related and external factors. Methods: AD‐related web search data were extracted for 21 European countries between February 2019 and January 2023. Descriptive analysis and autocorrelation functions were performed to examine spatiotemporal patterns. Correlations (r) were used to evaluate the associations between web searches and disease‐related, socioeconomic and meteorological data. Results: Over 241 million AD‐related web searches were identified, with search volume varying substantially among European countries (p < 0.001) and correlating with AD prevalence and disease burden (both r = 0.51, p = 0.019). Search volume increased between 2019 and 2023 in all countries and seasonally peaked in January and March. Negative correlations with median population age (r = −0.46, p = 0.039), number of general practitioners (r = −0.29, p = 0.226) and specialists (r = −0.27, p = 0.270) were observed. Moderate to strong correlations were found between search volume and cold, humid and windy weather with fewer sunshine hours, while higher online interest typically occurred 1–3 months after such weather conditions. Conclusion: The study highlights the great potential of online crowdsourced data analysis, for example, to investigate the impact of climate change or to identify unmet needs at a population level. Furthermore, the growing online interest in AD and the corresponding seasonal peaks emphasize the necessity of adapting treatment plans, intensifying public health campaigns, and disseminating reliable online information by governments and healthcare providers, especially during these periods. [ABSTRACT FROM AUTHOR]

Arthropod movement has been noticeably understudied compared to vertebrates. A crucial knowledge gap pertains to the factors influencing arthropod movement at habitat boundaries, which has direct implications for population dynamics and gene flow. While larger arthropod species generally achieve greater dispersal distances and large‐scale movements are affected by weather conditions, the applicability of these relationships at a local scale remains uncertain. Existing studies on this subject are not only scarce but often limited to a few species or laboratory conditions. To address this knowledge gap, we conducted a field study in two nature reserves in Belgium, focusing on both flying and cursorial (non‐flying) arthropods. Over 200 different arthropod species were captured and released within a circular setup placed in a resource‐poor environment, allowing quantification of movement speed and direction. By analysing the relationship between these movement variables and morphological (body size) as well as environmental factors (temperature and wind), we aimed to gain insights into the mechanisms driving arthropod movement at natural habitat boundaries. For flying species, movement speed was positively correlated with both body size and tailwind speed. In contrast, movement speed of cursorial individuals was solely positively related with temperature. Notably, movement direction was biased towards the vegetated areas where the arthropods were originally caught, suggesting an internal drive to move towards suitable habitat. This tendency was particularly strong in larger flying individuals and under tailwind conditions. Furthermore, both flying and cursorial taxa were hindered from moving towards the habitat by strong upwind. In conclusion, movement speed and direction at patch boundaries are dependent on body size and prevailing weather conditions, and reflect an active decision‐making process. [ABSTRACT FROM AUTHOR]

Antarctic sea ice extent has been persistently low since late 2016, possibly owing to changes in atmospheric and oceanic conditions. However, the relative contributions of the ocean, the atmosphere and the underlying mechanisms by which they have affected sea ice remain uncertain. To investigate possible causes for this sea‐ice decrease, we establish a seasonal timeline of sea ice changes following 2016, using remote sensing observations. Anomalies in the timing of sea ice retreat and advance are examined along with their spatial and interannual relations with various indicators of seasonal sea ice and oceanic changes. They include anomalies in winter ice thickness, spring ice removal rate due to ice melt and transport, and summer sea surface temperature. We find that the ice season has shortened at an unprecedented rate and magnitude, due to earlier retreat and later advance. We attribute this shortening to a winter ice thinning, in line with ice‐albedo feedback processes, with ice transport playing a smaller role. Reduced ice thickness has accelerated spring ice area removal as thinner sea ice requires less time to melt. The consequent earlier sea ice retreat has in turn increased ocean solar heat uptake in summer, ultimately delaying sea ice advance. We speculate that the observed winter sea ice thinning is consistent with previous evidence of subsurface warming of the Southern Ocean. Plain Language Summary: Following 2016, the Antarctic sea ice cover has been persistently low. To understand why, we retrace the seasonal timeline of sea ice and oceanic changes, using satellite observations. We find that the sea ice season has been significantly shorter following 2016, due to a later start and an earlier end. This shortening is likely caused by thinner sea ice in winter, accelerating sea ice melt in spring and causing sea ice to disappear earlier. In turn, this has caused the ice‐free ocean to absorb more solar heat in summer, and to take longer to cool down in the fall, ultimately delaying the ice season onset. Warmer waters beneath the Southern Ocean's surface, as evidenced by previous studies, could be a plausible cause of the observed thinning, by increasing the heat supply to sea ice. Key Points: The Antarctic sea ice season duration has undergone an unprecedented shortening since 2016The changes include thinner ice, faster melt, earlier retreat, larger ocean heat uptake, later advance, in line with the ice‐albedo feedbackThe near‐circumpolar ice thinning suggests a possible increase in sensible heat supply by the ocean [ABSTRACT FROM AUTHOR]

Ephemeral streams in dry environments can convey high intensity sediment‐laden flash floods. The study of these events is quite difficult due to remote locations with limited accessibility, unexpected events, rough weather conditions and safety concerns. Hence combined data of rainfall and flood hydrograph is rather scarce in the world, and null in Patagonia‐South America. The Experimental Basin Arroyo Sagmata (total drained area of 129 km2), located in the Lower Valley of the Chubut River has been equipped with 4 rain gauges, and 4 time‐lapse cameras in four reaches of the arroyos. Data from a 4‐year monitoring provides valuable insights about the hydrological response of basins in the drylands of Patagonia, such as the time of response, the shape of hydrographs and its relation with the hyetographs. Four hydrograph styles have been observed: single‐peak (S), multi‐peaks (M), flat‐top (F) and compound (C) peaks. Rainfall styles have also been classified into single, multiple and compound. Soil processes operate reducing the number of peaks (M‐type hyetographs are transformed into S‐ or M‐type hydrographs). The rain structure is also important, especially when the high intensity occurs in the beginning of the event. Channel connectivity pattern and disconnections explain the observation of M‐type hydrograph and F‐type hydrograph, respectively. Key Points: Flash floods are rare events that account for only 4% of the total water volume received by the basinFour hydrograph shapes have been identified: single‐peak, multiple‐peaks, compound and flat‐topThe hydrograph diversity depends on the rainfall temporal structure and its spatial distribution, soil, hillslope and channel processes [ABSTRACT FROM AUTHOR]

Atmospheric prediction at 2–6 weeks lead time (so‐called subseasonal‐to‐seasonal timescales) entails large forecast uncertainty. Here we investigate the flow‐dependence of this uncertainty during Boreal winter. We categorize the large‐scale flow using North Atlantic‐European weather regimes. First, we show that forecast uncertainty of near‐surface geopotential height (Z1000) and temperature (T2m) are strongly sensitive to the prevailing regime. Specifically, forecast uncertainty of Z1000 reduces over northern Europe following Greenland Blocking (enhanced predictability) due to a southward shifting eddy‐driven jet. However, due to strong temperature gradients and variable flow patterns, Greenland blocking is linked to increased forecast uncertainty of T2m over Europe (reduced predictability). Second, we show that forecast uncertainty of weather regimes is modulated via the stratospheric polar vortex. Weak polar vortex states tend to reduce regime‐uncertainty, for example, due to more frequent predicted occurrence of Greenland blocking. These regime changes are associated with increased T2m uncertainty over Europe. Plain Language Summary: Weather is chaotic, and forecasts several weeks ahead are quite uncertain. Nevertheless, the degree of uncertainty varies, which can be relevant for long‐term planning in various sectors, including agriculture, energy supply, and public health. Here we show that the degree of uncertainty depends on the weather at the time of forecast start, which we categorize using eight characteristic weather patterns for the North Atlantic and Europe. We analyze a large set of forecasts during winter, with lead times up to 6 weeks. For example, persistent high‐pressure systems over Greenland are known to favor low temperatures over northern Europe. Our results indicate that, in addition, temperatures are highly variable in these cases, leading to unusually high forecast uncertainty. In contrast, uncertainty of near‐surface air pressure tends to decrease due to less frequent storms over the North Atlantic. Furthermore, we show that forecast uncertainty of the weather patterns themselves varies, which is useful when large‐scale flow conditions are more critical than local weather. We analyze forecasts under different circulation conditions in the Arctic stratosphere, as these can have long‐lasting impacts on surface weather. We find forecasts of weather patterns become less uncertain when the circumpolar winds in the Arctic stratosphere are weak. Key Points: Ensemble spread of near‐surface weather in subseasonal forecasts is sensitive to the prevailing North Atlantic‐European weather regimeGreenland blocking is linked to the smallest ensemble spread of geopotential but to the largest spread of temperature over northern EuropeWeak polar vortex states are followed by reduced forecast uncertainty of weather regimes but increased uncertainty of European temperature [ABSTRACT FROM AUTHOR]

To address the increasing demand for diurnal information on trace gases and aerosols, a series of geostationary (GEO) satellite programs called GEO‐constellation have been initiated, with the launch of the Geostationary Environment Monitoring Spectrometer (GEMS) onboard Geostationary Korea Multi‐Purpose Satellite 2B (GK2B). To assess the sensor performance of GEMS in orbit, the current work suggests employing an inter‐calibration methodology involving the Advanced Meteorological Imager (AMI) aboard its twin satellite, GK2A. Twin satellites have a significant advantage in obtaining collocation data sets across diverse spatiotemporal, angular, and atmospheric conditions, enabling rigorous collocation criteria effectively reducing mismatch uncertainty. The results present robust correlation coefficients over 0.99, revealing the current calibration characteristics of the sensors. This research emphasizes the advantages of the GEO‐GEO inter‐calibration, particularly the capability of analyzing spatial and temporal dependencies. These findings confirm the mutual benefit of utilizing the sensors in similar configurations, highlighting their importance for future satellite monitoring endeavors. Plain Language Summary: Understanding diurnal changes in air pollutants is crucial for grasping how these substances move and disperse in the air, thereby aiding efforts to reduce pollution. In this regard, satellites have a distinct advantage in observation owing to their wide spatial coverage at regular time intervals. GEMS is one of the geostationary sensors providing such information for the Asia‐Pacific region, nearly 7–8 times a day. To evaluate the reliability of GEMS, this study proposes an inter‐calibration method by comparing GEMS observations with those of AMI aboard GK2A. These satellites have a unique advantage as they fly close to each other, observing the Earth with matched optical viewing paths. Scenes simultaneously observed by AMI and GEMS exhibit strong agreement, thus revealing the inherent observation characteristics of each sensor. These findings confirm the mutual benefit of utilizing the sensors in similar configurations for satellite monitoring during the operation. Key Points: Inter‐calibration based on ray‐matching between geostationary satellite sensors onboard twin satellitesImplementation of collocation process in the visible wavelengths and the application of weighted statistics for ensuring collocation stabilityThe novel advantages of the GEO‐GEO inter‐calibration approach for future applications [ABSTRACT FROM AUTHOR]

Although the 2021 Western North America (WNA) heat wave was predicted by weather forecast models, questions remain about whether such strong events can be simulated by global climate models (GCMs) at different model resolutions. Here, we analyze sets of GCM simulations including historical and future periods to check for the occurrence of similar events. High‐ and low‐resolution simulations both encounter challenges in reproducing events as extreme as the observed one, particularly under the present climate. Relatively stronger amplitudes are observed during the future periods. Furthermore, high‐ and low‐resolution short initialized GCM simulations are both able to reasonably predict such strong events and their associated high‐pressure ridge over the WNA with a 1 week forecast lead time. Moisture sensitivity experiments further indicate a drier atmospheric moisture condition results in substantially higher near‐surface temperatures in the simulated heat events. Plain Language Summary: During June 2021, an extraordinarily strong heat wave occurred over parts of Western North America (WNA). It obliterated the high temperature record there and caused severe societal and ecological impacts, and is believed to be exacerbated by climate change. Low‐resolution Global Climate Models (GCMs) are currently used to quantify the atmospheric responses to climate change, even though they exhibit significant biases in their simulated climate. Their ability to predict extraordinarily strong heat wave events remains unassessed. In this study, low‐ and high‐resolution GCM simulations are shown to be able to reproduce extraordinarily strong heat wave events in the near future, but face challenges in reproducing the events as extreme as the observed one. This highlights the role of climate change in such events. A suite of short GCM simulations initialized from observations is used to show that even low‐resolution GCMs can forecast observed extreme strong heat wave events and their high‐pressure ridge over WNA at short lead times. We further show that in these short‐term forecasts, drier atmospheric moisture initial condition can lead to significantly higher near‐surface temperature. Key Points: Global climate models (GCMs) climate simulations can reproduce extreme heat events, but face challenges in capturing the observed extremityLow‐ and high‐resolution GCMs predict the 2021 Western North America heat wave similarly within a 1‐week forecast lead timeDry atmospheric conditions in GCMs can lead to significantly higher near‐surface temperatures in the simulated heat waves [ABSTRACT FROM AUTHOR]

Clouds can be classified into regimes based on their appearance or meteorological controlling factors. The cloud appearance regimes inherently include adjustments to aerosol effects, such as transitions between closed and open cells. Therefore, calculating cloud susceptibilities to aerosols for each cloud‐appearance regime individually and then aggregating them excludes much of the cloud adjustment component of the susceptibilities. In contrast, aggregating susceptibilities over regimes defined by cloud‐controlling factors includes the full effects of cloud adjustments. Here we compared the susceptibilities of the two kinds of cloud regimes and demonstrated this effect. Overall, increasing cloud droplet number concentration (Nd) consistently correlates to weaker precipitation, higher cloud fraction (CF), and reduced liquid water path, regardless of how the regime is defined. However, their susceptibilities to Nd aggregated over cloud‐appearance regimes are significantly lower than those aggregated over cloud‐controlling factors regimes, with lower‐tropospheric stability (LTS) serving as an example to define cloud‐controlling factors regimes. This underestimation is more pronounced for CF susceptibility, where the susceptibility for cloud appearance regimes is only 1/4 of the susceptibility for cloud controlling regimes. These findings imply that relying solely on cloud‐appearance regimes may underestimate the effective radiative forcing produced by cloud adjustment (ERFaci). Nevertheless, the substantial variability in the magnitude of cloud adjustment across appearance regimes at similar LTS also suggests that a single cloud‐controlling factor is not sufficient to fully separate cloud regimes to quantify cloud adjustment. Therefore, identifying a comprehensive set of cloud‐controlling factors is essential for accurately quantifying cloud adjustments in future studies. Plain Language Summary: Understanding the impact of aerosols on marine low clouds is vital for accurately predicting changes in Earth's climate. Their interactions, known as aerosol‐cloud interactions (ACI), introduce significant uncertainty into our estimates of how much human activities contribute to climate change. Clouds exhibit varying responses to changes in cloud droplet number concentration (Nd), a proxy for aerosols, depending on specific cloud regimes representing distinct atmospheric conditions. However, the definition of cloud regime is often vague, with some defined based on the appearance of clouds and others on their meteorological controlling factors. In our study, we compared the sensitivity of cloud properties to Nd between these two different definitions of cloud regimes. We found that cloud susceptibilities to Nd aggregated over cloud‐appearance regimes are notably lower than those aggregated over cloud‐controlling factors regimes. Cloud fraction susceptibility to Nd aggregated over cloud appearance regimes is only one‐fourth of that over cloud controlling regimes. These results suggest that quantifying cloud adjustment to Nd simply within cloud appearance regimes will likely underestimate the effective radiative forcing of ACI (ERFaci) without accounting for the effect of aerosols on cloud‐appearance regimes. Key Points: Cloud‐appearance regimes are unsuitable for quantifying cloud adjustment to cloud droplet number concentration (Nd)The susceptibility of cloud fraction to Nd for cloud‐appearance regimes is only 1/4 of that based on cloud‐controlling regimesQuantifying cloud adjustment simply within cloud‐appearance regimes is likely to underestimate ERFaci [ABSTRACT FROM AUTHOR]

Snow is the most reflective natural surface on Earth. Since fresh snow on bare sea ice increases the surface albedo, the impact of summer snow accumulation can have a negative radiative forcing effect, which would inhibit sea ice surface melt and potentially slow sea‐ice loss. However, it is not well known how often, where, and when summer snowfall events occur on Arctic sea ice. In this study, we used in situ and model snow depth data paired with surface albedo and atmospheric conditions from satellite retrievals to characterize summer snow accumulation on Arctic sea ice from 2003 to 2017. We found that, across the Arctic, ∼2 snow accumulation events occurred on initially snow‐free conditions each year. The average snow depth and albedo increases were ∼2 cm and 0.08, respectively. 16.5% of the snow accumulation events were optically thick (>3 cm deep) and lasted 2.9 days longer than the average snow accumulation event (3.4 days). Based on a simple, multiple scattering radiative transfer model, we estimated a −0.086 ± 0.020 W m−2 change in the annual average top‐of‐the‐atmosphere radiative forcing for summer snowfall events in 2003–2017. The following work provides new information on the frequency, distribution, and duration of observed snow accumulation events over Arctic sea ice in summer. Such results may be particularly useful in understanding the impacts of ephemeral summer weather on surface albedo and their propagating effects on the radiative forcing over Arctic sea ice, as well as assessing climate model simulations of summer atmosphere‐ice processes. Plain Language Summary: As sea ice declines in the Arctic, it is necessary to understand the role that sea ice plays in the Arctic climate. During summer, ice is particularly important because it acts as a barrier between the atmosphere and ocean, and shields the ocean from sunlight. Sea ice is a surface on which snowfall can accumulate. Since snow is the most reflective natural surface on earth, its presence during the sunny season can reflect significant amounts of sunlight away from the earth's surface and reduce warming. In this work, we studied the impact of summer snowfall on sea ice by combining data from buoys, satellites, and models to determine how much sunlight is reflected by short‐lived summer snow accumulation on Arctic sea ice. We learned that the average snow event raises the reflectivity of the surface by 0.08 with ∼2 cm of snow depth change. Events with more than 3 cm of accumulation lasted ∼3 days longer than average (∼3 days). Overall, summer snow accumulation reduces the amount of energy absorbed by the Arctic region by 0.086 W m−2 each year. These results help to improve our understanding of the Arctic climate and may also be useful for evaluating climate models. Key Points: Ephemeral summer snowfall increased albedo by 0.08 and decreased TOA radiative forcing by 0.086 ± 0.020 W m−2 across the Arctic Ocean in 2003–2017The average snow accumulation event led to a ∼2 cm increase in snow depth and lasted 3.4 daysOptically thick (>3 cm) snow accumulation events occurred in 16.5% of all events and lasted 6.3 days [ABSTRACT FROM AUTHOR]