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This study examines the temporal and spatial variability of near‐surface air temperature and the canopy layer urban heat island (UHICL) of Kuwait City. Observations collected at 12 locations across the country of Kuwait and for the period 2010–2022 are analysed on an hourly and 3‐hourly basis to provide monthly and diurnal insights of the city's UHICL characteristics. Research on Kuwait's UHICL was first conducted by Nasrallah et al. (International Journal of Climatology, 10, 401–405). Results presented here have been afforded the benefit of additional stations and more extensive data compared with the earlier study. Mean positive UHICL intensities, ranging from 1.1°C to 3.8°C at night, are observed consistently across all months, owing to the prevalence of clear skies from winter to summer. Negative UHICL intensities, indicating a typical daytime urban cool island (UCICL), are most prominent on summer days, exhibiting a mean hourly magnitude range between 0.6°C and 2.6°C that extends into the early parts of the evening. Heat and cool island effects are maintained up to wind speeds approaching 10 m s−1 at the urban periphery. A coastal site near the city demonstrates strong influences of the Arabian Gulf temperatures and associated sea and land breeze effects on UHICL development. The results can be used for comparison with other desert locales, in the evaluation of urban climate models, for urban planning policies and improving local weather forecasts. This study honours in memoriam Dr. Hassan Nasrallah, who produced the first UHICL study in the Arab World. [ABSTRACT FROM AUTHOR]

The seasonal cycle (SC) of surface air temperature is a substantial element in climatology. Some basic and important topics in climate change studies are based on accurate and reliable estimation of SCs, such as percentile‐based indices of extremes and probability density function (PDF) changes of daily temperatures. For both of them, most studies characterized SCs using averages of multi‐days windows, which is not smooth and accurate enough representing the extreme thresholds and climatological normal of SCs. It is necessary to construct smooth and reasonable SCs for more accurate estimation of temperature changes on extreme thresholds and PDFs. In this study, we propose a flexible method based on generalized additive models for location scale and shape and penalized b‐spline smoothing technique with respective distributions to construct smooth SCs and SC for extreme temperatures (SCETs). The accuracy of the constructed smooth SCETs is good with the estimation biases of percentiles tending to be zero. The constructed smooth SCET also exhibits good stability over time, such that the magnitude changes of temperatures on each calendar day are close to climatic changes of mean temperature when the concerned period shifts. Based on the constructed smooth SCs, climatic changes by seasons and PDFs between two periods, 1961–1990 and 1991–2020, are examined over China. The increase of thresholds for hot extremes in spring during the recent period is prominent, while the increase of thresholds for daytime cold extremes in summer over a part of central to southern China is also notable. The smooth SCs and SCETs based on our flexible statistical modelling framework can characterize daily extreme temperatures reasonably and accurately, and should be expected to have more applications for a better understanding of climate changes related to distributions and seasonal cycles. [ABSTRACT FROM AUTHOR]

This study investigates the response of surface air temperature (SAT) to strong tropical volcanic eruptions (STVEs), focusing on the seasonal anchoring of SAT recovery, using the Coupled Model Intercomparison Project 5 (CMIP5) and CMIP6 climate model outputs. The decrease in SAT was more significant in the Northern Hemisphere than in the Southern Hemisphere. After the STVEs, shortwave radiation at the surface (SW) decreased rapidly and reached a minimum in approximately 6 months, whereas the decrease in SAT lasted for approximately 1 year; thus, the SAT minima lagged behind those of SW. The recovery of SAT from the major minimum SAT after the STVEs occurred in the same seasons, the second boreal autumn and winter. The SAT recovery occurred during the climatologically low solar radiation season after the STVEs. During this season, the decreasing effects of the downward SW (DSRS) by volcanic aerosols could become negligible. The weakening of the decrease in SAT and DSRS had a seasonal cycle in the high‐latitude regions of both hemispheres, which could be a significant factor in the seasonal alignment of returning SATs. Furthermore, the SAT response to the El Niño–Southern Oscillation (ENSO) was examined using composite analysis based on the initial state of ENSO. The influence of ENSO on surface cooling after the STVE was at least 1/5 that of the STVEs and might exceed that of the STVEs, particularly in moderate STVEs. These results were commonly found in the CMIP5 and CMIP6 climate models. Plain Language Summary: Strong tropical volcanic eruptions (STVEs) transport volcanic sulfur aerosols into the stratosphere, affecting downward solar radiation and decreasing surface air temperature (SAT) for several years. After the 1991 Pinatubo eruption, the global average surface air temperature dropped by 0.5 K. We investigated the SAT response to the STVEs using the simulation results from multiple climate models. Analyzing many simulations increases the reliability of our results. As is well known from previous studies, a SAT drop has been clearly observed in the Northern Hemisphere. In addition, the SAT response to volcanic aerosols was weakened in the second northern winter after the STVEs, even when the STVE occurred in northern spring and fall. Because solar radiation at the Earth's surface is climatologically weak in northern winter, the effects of volcanic aerosols on SAT decrease can be negligibly small in northern winter. Therefore, the recovery of SAT after STVEs occurred in the northern winter. Key Points: Surface air temperature (SAT) responses to strong tropical volcanic eruptions (STVEs) were investigated using CMIP5/6 climate modelsDecrease in SAT after the STVEs tended to stop in the second winter, even though the timing of the eruption was differentSeasonally anchoring SAT recovery after STVEs is related to weak solar radiation in winter [ABSTRACT FROM AUTHOR]

Seasonality plays a critical role in cold mountain regions as variation in air temperature, ground thermal status, and precipitation phase alter the rate, timing and magnitude of hydrological and chemical transport. Additionally, cold mountain catchments can have highly variable topography, geology, permafrost, and landcover, which intrinsically add to this irregularity. Understanding how external and internal variability act to control mass fluxes requires sampling at a high spatial resolution over time, which rarely occurs in cold remote regions. In this work, we conduct five snapshot sampling surveys across 34 subcatchments during the ice‐free period in Wolf Creek Research Basin (a mesoscale montane subarctic catchment) and two additional winter surveys across a subset of sites to assess the drivers of variability in stream chemistry and discharge. We sampled for specific conductance (SpC), major ions, and dissolved organic carbon (DOC) and used statistical metrics and Bayesian mixing analysis to quantify patterns of flow and chemistry across space and time. Our results indicate patterns in both flow and chemistry remain largely consistent across seasons for all solutes. However, there was weaker correlation of chemistry between sites, suggesting asynchronous behaviour within the catchment. There was evidence of increasing production of ions and DOC along the stream network during high spring flows but not during low flows. Although concentrations and flows exhibit high seasonality in subarctic mountains, this seasonal variability does not alter spatial patterns that arise from highly variable catchment characteristics. [ABSTRACT FROM AUTHOR]

Extreme thermal conditions have been known for a long time as is evidenced by the oldest preserved historical accounts referring to weather. However, direct data, that is, air temperature measurements, which began in Europe in the 17th century, are the only reliable source of information. They provide insight into how climate evolved over the characteristic period of the climate timeline known as the Little Ice Age. This study focuses on extreme climatic phenomena, referred to here as exceptionally cold (EC) and exceptionally warm (EW) months and seasons that occurred in the early instrumental period (until 1830). The research is based on average monthly air temperature values (of different lengths) from five meteorological stations in Europe. The Central England Temperature series (CET) offers the longest series that spans 172 years whereas Padua has the shortest, 57 years. Consequently, the year 1659, which is the start date of the Central England Temperature series, marks the beginning of the study period for the research presented in this article. Thermally anomalous periods are identified based on the standard deviation of the average temperature from the corresponding long‐term average (1831–2020). The highlights of the study include the identification of the pronounced prevalence at all five stations of EC months and seasons when compared to EW months and seasons, especially in Western Europe (CET) during the Maunder Minimum. The study also finds a lack of synchronicity in the timing of the anomalous periods under investigation in the different parts of Europe. [ABSTRACT FROM AUTHOR]

This study analyzes the long‐term observed changes of mean (Tmean), maximum (Tmax) and minimum (Tmin) air temperatures, relative humidity (RH) and vapour pressure deficit (VPD) at different elevation ranges across Bolivia from 1950 to 2019. The linear trends in air temperature series present a significant increase, with no substantial seasonal or spatial differences. On an annual basis, RH exhibited a non‐significant decrease (−0.08% decade−1), while VPD showed a significant increase (0.01 hPa decade−1) (p < 0.05). Although prior research has suggested that highland elevations experience faster warming than the global average, we have not identified a distinct correlation between elevation gradients and differential warming rates in Bolivia. Future research could investigate elevation‐dependent climate trends by examining seasonal and monthly patterns of climatic variables in relation to topographical gradients in various highland regions. [ABSTRACT FROM AUTHOR]

Communal nesting behaviour of small mammals is thought to function mainly as a method of thermoregulation. However, this behaviour is also observed during the non‐winter season when there are no obvious thermoregulatory benefits. Siberian flying squirrels (Pteromys volans) nest communally during the non‐winter season. This may facilitate mating, but other functions such as thermoregulation have not been sufficiently studied. Therefore, we examined whether communal nesting of P. volans during the non‐winter season plays a role in thermoregulation in addition to mating. In the event that communal nesting in the non‐winter season has any function other than mating, we expected an increase in non‐mating groups consisting of only‐males during the nurturing period (duration of mother squirrel and cubs living together) because females rearing their young do not participate in communal nesting. In Obihiro, Hokkaido, Japan, during the non‐winter season (May–October) between 2019 and 2021, we captured P. volans in 252 nests by using nest boxes. The occurrence of male‐only groups showed a tendency to increase during the nurturing period. Moreover, the number of mixed‐sex groups increased between August and October each year; these changes in communal nesting during the non‐winter season were unrelated to the variation in air temperature or precipitation. These results suggest that during the non‐winter season, communal nesting of P. volans is related to reproductive behaviour. Additional studies are needed to determine how communal nesting during the non‐winter season enhances the reproductive success of male and female P. volans. [ABSTRACT FROM AUTHOR]

Significant imbalances in terrestrial water storage (TWS) and severe drought have been observed around the world as a consequence of climate changes. Improving our ability to monitor TWS and drought is critical for water‐resource management and water‐deficit estimation. We use continuous seismic ambient noise to monitor temporal evolution of near‐surface seismic velocity, dv/v, in central Oklahoma from 2013 to 2022. The derived dv/v is found to be negatively correlated with gravitational measurements and groundwater depths, showing the impact of groundwater storage on seismic velocities. The hydrological effects involving droughts and recharge of groundwater occur on a multi‐year time scale and dominate the overall derived velocity changes. The thermoelastic response to atmospheric temperature variations occurs primarily on a yearly timescale and dominates the superposed seasonal velocity changes in this study. The occurrences of droughts appear simultaneously with local peaks of dv/v, demonstrating the sensitivity of near‐surface seismic velocities to droughts. Plain Language Summary: Terrestrial water storage (TWS) is fundamental to the well‐being of inhabitants on Earth. However, current approaches to measure TWS variations have limited temporal or spatial resolution. In this study, we use near‐surface seismic velocity variations, dv/v, derived from continuous seismic recordings to monitor changes of TWS in central Oklahoma. A negative correlation between the long‐term trend of dv/v with gravity measurements reflects the impact of groundwater recharge/discharge on near‐surface seismic velocity. In addition, a seasonal cycling of dv/v has similar periodicity to recordings of air temperature, which can be explained by thermo‐elastic strain at the subsurface. Comparisons between dv/v and drought index further show the possibility of using near‐surface seismic velocity as a proxy for monitoring severe drought for local communities. Considering the high temporal sampling and flexible spatial deployment, seismometers may be used to monitor subsurface water distributions. This can be useful for sustainable water management and reliable water‐deficit estimation. Key Points: A long‐term trend of dv/v in Oklahoma correlates well with gravity measurements, which may reflect groundwater recharge and dischargeShort‐term peaks of dv/v agree with the drought index, demonstrating a potential for monitoring meteorological droughtsA seasonal cycle of dv/v in central Oklahoma can be explained by thermo‐elastic strains driven by atmospheric temperature changes [ABSTRACT FROM AUTHOR]

In this study, multi‐year near‐surface observations were conducted at two sites in Jakarta, Indonesia to analyse seasonal sea breeze variation. Seasonal length was defined using observed zonal wind components, the rainy season was defined as December–March, and the dry season was defined as May–September. We found that the sea breeze in Jakarta started earlier, propagated more rapidly, and lasted for a shorter period of time during the rainy than dry season. Variation in the air temperature difference between urban and coastal areas of Jakarta was the major factor driving sea breeze seasonal variation. During the rainy season, night‐time cloud downwelling decreased this air temperature difference, causing earlier sea breeze onset and more rapid sea breeze propagation due to a weaker land breeze. By contrast, during the dry season, intense night‐time radiative cooling inland caused a strong negative temperature difference that produced a stronger land breeze, thus, slowing sea breeze propagation. Seasonal differences in urban surface heating and urban heat island circulation may also affect sea breeze onset and propagation speed. Discrepancies in thermal properties between urban core and coastal areas of Jakarta also prolonged positive temperature differences after sunset, thus extending the sea breeze duration in the dry season. [ABSTRACT FROM AUTHOR]

In 2021/2022 winter, an intraseasonal surface air temperature (SAT) reversal occurred in China, shifting from regional warm to cold phase in late January 2022. The intraseasonal variations of winter SAT in China are tightly connected with 500 hPa potential height. In particular, the Arctic Oscillation (AO) positive phase is diagnosed to be contributing to the SAT reversal. Under its influence, the intraseasonal build‐up and collapse of blockings over Urals Mountain led to the cold surges in February 2022. Seasonal prediction systems (SPSs) such as NCEP_CFSv2, EC_SYSTEM5 and BCC_CSM1.1 are assessed to have poor predictability in this SAT reversal and similar historical events, owing to not only the poor skills in winter SAT predictions but also the integral inertia in SPSs. Prediction skill only increases as the forecasting time approaches, owing to initial values. Besides, the SPSs can simulate the physical process of the influence on SAT from circulation. The poor predictability is attributed to the poor prediction skills in mid–high latitude circulation pattern and potential height over China. [ABSTRACT FROM AUTHOR]

The article analyses the variability of thermal seasons in Poland in 1961–2020. Based on the average monthly air temperature values from 55 stations, the onset and end dates as well as the duration of the six thermal seasons were calculated. Taking into account the thermal thresholds of 0°C, 5°C and 15°C for each year, early spring, spring, summer, autumn, early winter and winter can be distinguished. A significant spatial differentiation of the dates of the beginning and duration of the thermal seasons in Poland was observed. The influence of continentalism (in the east) and oceanic climate (in the west) and the influence of the Baltic Sea are noticeable, and in mountainous regions, altitude above sea level is the main factor. The air temperature in Poland increases at the rate of 0.3°C–0.4°C/10 years. This causes significant changes in the occurrence and duration of the thermal seasons. An early beginning of early spring and spring was observed. Summer arrives earlier and is significantly longer, becoming the longest season of the year (above 110 days in the south of Poland). Autumn and early winter are delayed and get shorter, whereas winter comes much later. Throughout the country, winter is 44 days shorter, and in the north‐west it does not occur at all. Changes in the onset of thermal seasons are a clear indicator of progressing global warming. They have also a decisive impact on the environment and human activity. [ABSTRACT FROM AUTHOR]

At most latitudes, the seasonal cycle of zonal‐mean surface air temperature is notably asymmetric: the length of the warming season is not equal to the length of the cooling season. The asymmetry varies spatially, with the cooling season being ∼40 days shorter than the warming season in the subtropics and the warming season being ∼100 days shorter than the cooling season at the poles. Furthermore, the asymmetry differs between the Northern Hemisphere and the Southern Hemisphere. Here, we show that these observed features are broadly captured in a simple model for the evolution of temperature forced by realistic insolation. The model suggests that Earth's orbital eccentricity largely determines the hemispheric contrast, and obliquity broadly dictates the meridional structure. Clouds, atmospheric heat flux convergence, and time‐invariant effective surface heat capacity have minimal impacts on seasonal asymmetry. This simple, first‐order picture has been absent from previous discussions of the surface temperature seasonal cycle. Plain Language Summary: Away from the equator, most places on Earth experience a noticeable seasonal cycle in surface air temperature. The seasonal cycle of temperature governs many aspects of human and ecosystem behavior. Observations show that, at most latitudes, the length of the warming season is not equal to the length of the cooling season, that is, the seasonal cycle is asymmetric. For example, at 25°N, the average warming season is 35 days longer than the cooling season. Here, we look at how this asymmetry varies with distance from the equator. We find that the asymmetry can largely be explained as a result of variations in the amount of radiation from the sun that reaches Earth, which are determined by Earth's orbit. Key Points: The seasonal cycle in zonal‐mean surface air temperature is asymmetricThe warming period tends to be shorter than 6 months in high latitudes and longer than 6 months in low latitudesThe asymmetry can largely be explained by variations in top‐of‐atmosphere insolation, dictated by Earth's orbit [ABSTRACT FROM AUTHOR]

In coastal West Antarctic Peninsula (WAP) waters, large phytoplankton blooms in late austral spring fuel a highly productive marine ecosystem. However, WAP atmospheric and oceanic temperatures are rising, winter sea ice extent and duration are decreasing, and summer phytoplankton biomass in the northern WAP has decreased and shifted toward smaller cells. To better understand these relationships, an Imaging FlowCytobot was used to characterize seasonal (spring to autumn) phytoplankton community composition and cell size during a low (2017–2018) and high (2018–2019) chlorophyll a year in relation to physical drivers (e.g., sea ice and meteoric water) at Palmer Station, Antarctica. A shorter sea ice season with early rapid retreat resulted in low phytoplankton biomass with a low proportion of diatoms (2017–2018), while a longer sea ice season with late protracted retreat resulted in the opposite (2018–2019). Despite these differences, phytoplankton seasonal succession was similar in both years: (1) a large‐celled centric diatom bloom during spring sea ice retreat; (2) a peak summer phase comprised of mixotrophic cryptophytes with increases in light and postbloom organic matter; and (3) a late summer phase comprised of small (< 20 μm) diatoms and mixed flagellates with increases in wind‐driven nutrient resuspension. In addition, cell diameter decreased from November to April with increases in meteoric water in both years. The tight coupling between sea ice, meltwater, and phytoplankton species composition suggests that continued warming in the WAP will affect phytoplankton seasonal dynamics, and subsequently seasonal food web dynamics. [ABSTRACT FROM AUTHOR]

Northern high latitudes are experiencing some of the greatest increases in air temperatures on Earth. Air temperatures (along with other modulating variables including precipitation and the onset of snowmelt) are influenced by atmospheric–oceanic circulation patterns, some of which are persistent and recurrent. One pattern in particular, the Arctic Dipole (AD) anomaly, is a persistent sea‐level pressure teleconnection pattern between the Canadian Archipelago and Barents Sea that has unknown impacts on local climate variability. These patterns may be important, especially in hydro‐ecologically sensitive areas such as Northwest Territories (NWT), Canada where permafrost thaw and ecosystem changes are influenced by interannual climate variability. The goal of this research is to determine the impacts of the AD on local climate (air temperature, precipitation, snowmelt) for a 66‐year period (1950–2015) spanning both latitudinal and longitudinal gradients across NWT from north to south and foothills to plains. Deviations during strong positive and negative modes of the AD index were calculated in reference to the complete 66‐year record. Results showed considerable year‐to‐year variability in the AD pattern, with more frequent strong negative modes during the 2000s. During 1950–2015, there were 64 and 56 occurrences of strong positive and strong negative AD modes, respectively, across all seasons. Spring and summer strong AD modes led to local air temperature anomalies of greater than 0.8°C compared with the long‐term (66 years) mean. Earlier onset of snowmelt, by an average of 3–5 days, was also noted during positive AD modes. Despite strong connectivity between the AD and local air temperature, we found less correspondence between the AD and seasonal precipitation. These findings improve understanding of the impacts of the AD on local weather and climate in NWT and suggest implications for ecosystem change, such as drying and shrubification of northern boreal peatlands and possible connectivity to teleconnection impacts on wildland fire. [ABSTRACT FROM AUTHOR]

Atmospheric warming results in an intensification of annual precipitation over the globe but large uncertainties remain regionally and at seasonal scales, especially for extremes. Using 29 models from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), we investigate future seasonal changes in extreme precipitation (under the scenario SSP5‐8.5) and how it compares to changes in mean precipitation. Over land, we find a strong intensification of the wettest day in all seasons over the mid and high latitudes of the Northern Hemisphere and over India during the monsoon. Extreme intensity decreases in the subtropics for some seasons, including over large regions around the Mediterranean basin and Southern Africa, and these drying patterns are not apparent in annual results. The key finding is that the CMIP6 multi‐model mean always shows that seasonal changes in mean and extreme precipitation align where there is high model agreement. That is, in all seasons by the end of the 21st century, extremes intensify in regions where mean precipitation increases and decline where mean precipitation decreases. This should not hide inherent uncertainties associated, namely the large range of changes intensity that can be found across the models, and an important modulation of the changes by internal variability. Yet, this study shows that the multi‐model mean shows broad consistency such that future seasonal changes in mean precipitation could be used to infer future changes in extremes (and vice versa), thus providing valuable information for risk planning and mitigation strategies. Plain Language Summary: The rise in surface air temperature due to human influence results in an intensification of the most extreme events of precipitation over the globe. Although this is shown by both observations and Earth System Models at the global scale, more uncertainties remain regionally and at the seasonal scales. In this study, we use a large ensemble of state‐of‐the‐art Earth System Models and investigate future seasonal changes in extreme precipitation and how it compares to changes in total precipitation. Our key finding is that, in all seasons by the end of the 21st century, extremes intensify in regions where mean precipitation increases and decline where mean precipitation decreases. This is found locally and in regions where there is high agreement between the models with projected changes of a same sign. Hence, when future seasonal changes in precipitation can be assessed with high confidence, we find that changes in totals and extremes align in the future. Our results demonstrate that there is potential added value from examining concomitant projected changes in totals and extremes of precipitation on seasonal and regional scales which could help better inform decision‐making in relevant climate‐sensitive sectors. Key Points: We present projected seasonal changes in Coupled Model Intercomparison Project (CMIP6) total and extreme precipitation and show that they scale into the futureCMIP6 multi‐model mean seasonal change is of same sign for total and extreme precipitation when there is high agreement between modelsThis is found locally (at the grid cell scale) and regionally and is generally supported by the 29 individual models [ABSTRACT FROM AUTHOR]

The surface air temperature seasonal cycle in China has clearly changed in response to global warming, but its future projection has yet to be studied. Here, we investigate the performance and projection of the temperature seasonal cycle in China in 32 global climate models participating in the Coupled Model Intercomparison Project 6 (CMIP6). The characteristics of the temperature seasonal cycle, as represented by the amplitude and phase, are measured by the Fourier transform. The results show that the CMIP6 models can reasonably capture the observed typical temperature seasonal cycle feature with clear north–south gradients both for amplitude and phase in China. In the twenty‐first century, the models robustly project a delay in the phase across the whole country and a reduction in the amplitude in most of China relative to the reference period. Those changes are similar in the two shared socioeconomic pathway (SSP) scenarios, with overall larger magnitudes in the SSP5‐8.5 scenario than in the SSP2‐4.5 scenario. Projected amplitude changes are mainly linked to surface energy flux changes, especially latent heat flux changes. In response to future global warming, larger increases in the latent heat flux and thus stronger surface evaporative cooling lead to weaker surface warming in summer than in winter, contributing to a decrease in the amplitude of the temperature seasonal cycle in most regions of China. [ABSTRACT FROM AUTHOR]

Understanding the response of terrestrial ecosystem water use efficiency (WUE) to climate change is critical to accurately represent the carbon‐water cycle processes. However, how WUE dynamics are evolving under seasonal climate variations and biome‐specific characteristics remains still unclear. In this study, we integrated two state‐of‐the‐art retrieval algorithms to estimate gross primary productivity (GPP) and evapotranspiration (ET) from satellite MODIS records. Such metrics served as input to quantify ecosystem WUE, expressed as the ratio of GPP to ET, and explore its dynamics during the dry and wet season from 2001 to 2018 in China's key tropical to subtropical transitional zones, that is, Yunnan Province. Results show large spatial and seasonal variability in WUE over the observational period. During the dry season, the increasing trends in GPP and ET have led to contrasting WUE patterns in forest and non‐forest biomes, leading to positive and negative WUE trends, respectively. During the wet season, the declining trends in GPP occurring in combination with opposite trends in ET, have caused decreasing WUE consistently across all biomes except croplands, likely further modulated by human factors. The observed changes in WUE appear primarily driven by variations in air temperature (Ta) and vapor pressure deficit (VPD) during both dry and wet seasons. Overall, these results contribute to a better understanding of the carbon‐water interplay in tropical‐subtropical transitional zones and provide new insights to improve our capacity to predict the terrestrial ecosystem's response to climate change. Key Points: Terrestrial water use efficiencies (WUEs) show biome‐specific and season‐differential responses to climate changesEvergreen broadleaf forests have more stable water use efficiency across dry and wet seasons than the other biomesDry (wet) season WUE dominantly show positive (negative) trends, mainly caused by change in productivity (evapotranspiration) [ABSTRACT FROM AUTHOR]

Reanalysis data and a numerical model are employed to explore how diffusion in the upper ocean evolves in different seasons and to understand its contribution to seasonal heat storage (SHS) and Arctic amplification. The numerical simulation results are closely consistent with observations. First, Arctic solar radiation absorption anomaly (maximum in June) due to ice‐loss is mainly stored as SHS (maximum in June and July) or warms the surface (minimum in July) in observations. Furthermore, the numerical simulation suggests that vertical diffusion dominates SHS formation/discharge. Second, surface ocean becomes warmer than surface air in cold season and releases SHS in Arctic. Sea‐ice loss allows more ocean be directly driven by wind; surface high pressure over Arctic may enhance the wind stress; increased water freeze leads to more salt rejection and additional dense water being produced and sinking downward; all of the occurrences strengthen vertical mixing and release more SHS to the atmosphere. As a result, Arctic surface warming reaches its maximum in cold season. In observations, much stronger outgoing longwave radiation due to the warmer surface in October causes Arctic surface warming to reach its maximum in November, although increased carbon dioxide forcing also contributes to maintain longwave radiation in November. Finally, Arctic surface (air) warming in cold season exhibits different spatial patterns from SHS discharge due to heat convergence/divergence induced by anomalous surface wind, which is determined by the variation in surface high pressure over the Arctic. Plain Language Summary: Due to little seasonal variation in global surface warming, seasonality of Arctic amplification (AA) is mainly determined by seasonal variation of Arctic surface warming. Seasonal heat storage (SHS) in the subsurface Arctic Ocean contributes to Arctic surface warming by holding anomalous heat in summer and releasing it in autumn and winter. As a result, there is significant seasonal variation in AA. In this study, we directly estimate the SHS with ocean data and focus on spatial feature discussions. (a) In summer, additional solar radiation is stored as SHS via vertical diffusion in the upper ocean, resulting in weak Arctic warming. (b) In cold season, more current is driven directly by wind due to sea‐ice loss; variation in surface high pressure over the Arctic enhances the wind stress; more dense water, which is produced due to additional water freezes, sink downward; all of which strengthen the vertical mixing and release more SHS, resulting in the Arctic warming maximum. (c) Although SHS discharge dominates Arctic warming in cold season, anomalous surface wind induces heat convergence/divergence and influences the spatial distribution of surface air temperature, which in turn impacts surface warming via air‐sea/air‐land interactions. Finally, the SHS anomaly and surface warming share different spatial patterns. Key Points: With (without) land surface warming occurring in June, the observational (numerical) Arctic warming/Arctic amplification reaches its minimum in July (June)Though seasonal heat storage (SHS) discharge dominates Arctic warming in cold season, anomalous wind makes their spatial patterns differentLess insulation by sea‐ice loss, wind acceleration or more dense water sinking increases vertical mixing and SHS discharge in cold season [ABSTRACT FROM AUTHOR]

European climate variability is shaped by atmospheric dynamics over the North Atlantic and local processes. Better understanding their future seasonality is essential to anticipate changes in weather conditions for human and natural systems. We explore atmospheric seasonality over 1979–2017 and 1979–2100 with seasonal circulation regimes (SCRs), by clustering year‐round daily fields of Z500 from the ERA‐Interim reanalysis and 12 Coupled Model Intercomparison Project phase 5 (CMIP5) climate models (historical and RCP8.5 runs). The spatial and temporal variability of SCR structures and associated patterns of surface air temperature are investigated. Climate models have biases but reproduce structures and evolutions of SCRs similar to the reanalysis over 1979–2017: decreasing frequency of winter conditions (starting later and ending earlier in the year) and the opposite for summer conditions. These changes are stronger over 1979–2100 than over 1979–2017, associated with a large increase of North Atlantic seasonal mean Z500 and temperature. When using more SCRs (more freedom in definition of seasonality), the changes over 1979–2100 correspond to a long‐term swap between SCRs, resulting in similar structures (annual cycle and spatial patterns) relative to the evolution of seasonal mean Z500 and temperature. To understand whether the evolution of SCRs is linked to uniform warming, or to changes in circulation patterns, we remove the calendar trend in the Z500 regional average to define SCRs based on detrended data (d‐SCRs). The temporal properties of d‐SCRs appear almost constant whereas their spatial patterns change, indicating that the calendar Z500 regional trend drives the evolutions of SCRs, and that changing spatial patterns in d‐SCRs account for the heterogeneity of this trend. Our study suggests that historical winter conditions will continue to decrease in the future while historical summer conditions continue to increase. However, it also suggests that the spatial and temporal patterns of SCRs would remain similar, relatively to the year‐round Z500 increase. [ABSTRACT FROM AUTHOR]

Diel and seasonal rhythms affect an animal's environment and life history. Understanding how these rhythms influence movement increases our knowledge on how animals adjust to changing resources, environmental conditions, and risk to their survival. To better understand how diel and seasonal rhythms affect animals, we evaluated movements of Northern Bobwhite (Colinus virginianus, hereafter bobwhite). Because bobwhite are a small non‐migratory species that must cope with daily and seasonal changes in their environment year‐around, they are a model species to study how diel and seasonal rhythms influence animal movement of a non‐migratory species. GPS data from transmitters attached to bobwhite at four wildlife management sites across Oklahoma were collected during 2019–2021. We parsed the diel data as daytime (7:00 AM–7:00 PM Central Daylight Savings Time [CDT]) and nighttime (7:00 PM–7:00 AM CDT), and diurnal (sunrise–sunset) and nocturnal (sunset–sunrise), as well as by astronomical season. We calculated three movement metrics: net displacement (Euclidean distance from the starting fix to the ending fix of a path, which encompasses consecutive relocations in a time series of geographic fixes); cumulative distance (sum of all Euclidean distances between each consecutive fix along the path); and hourly movement. We modeled the data using a generalized linear mixed modeling approach. Across season, model predictions showed that net displacement was highest during spring, and daytime cumulative distance slowly increased as the year progressed. Bobwhite had two movement peaks during the diurnal period, one during 9:00 AM–10:00 AM and the other during 5:00 PM–8:00 PM depending on the season. Despite being diurnal, bobwhite occasionally made nocturnal movements, likely in response to a disturbance by a predator, inclement weather, or energetic demands. Movement peaks during the diurnal period may reflect changes in behavior in response to energy requirements, predator risk, and changes in air temperature. Life history events likely cause seasonal differences in movement. This study furthers our understanding of how animals move daily and seasonally, suggesting the importance of analyzing movement across the entire year because animals move differently across the day and year. [ABSTRACT FROM AUTHOR]

Summary: The plume of hot gases rising above a wildfire can heat and kill the buds in tree crowns. This can reduce leaf area and rates of photosynthesis, growth, and reproduction, and may ultimately lead to mortality. These effects vary seasonally, but the mechanisms governing this seasonality are not well understood.A trait‐based physical model combining buoyant plume and energy budget theories shows the seasonality of bud necrosis height may originate from temporal variation in climate, fire behaviour, and/or bud functional traits. To assess the relative importance of these drivers, we parameterized the model with time‐series data for air temperature, fireline intensity, and bud traits from Pinus contorta, Picea glauca, and Populus tremuloides.Air temperature, fireline intensity, and bud traits all varied significantly through time, causing significant seasonal variation in predicted necrosis height. Bud traits and fireline intensity explained almost all the variation in necrosis height, with air temperature explaining relatively minor amounts of variation.The seasonality of fire effects on tree crowns appears to originate from seasonal variation in functional traits and fire behaviour. Our approach and results provide needed insight into the physical mechanisms linking environmental variation to plant performance via functional traits. [ABSTRACT FROM AUTHOR]

Seasonal variations in gut microbiota of small mammals and how they are influenced by environmental variables are relatively poorly understood. We sampled 162 wild plateau pikas (Ochotona curzoniae) in 4 seasons over 2 and a half years and recorded the air temperature, precipitation, and nutrient content in edible vegetation at the sampling site. After conducting 16S rRNA and shotgun metagenomic sequencing, we found that the highest alpha diversity, the relative abundance of Firmicutes, and the simplest co‐occurrence network occurred in winter, whereas the highest relative abundance of Proteobacteria and the most complex network structure were observed in spring. The highest relative abundance of Verrucomicrobiota and Spirochaetota was seen in summer and autumn, respectively. Air temperature, precipitation, and the contents of crude protein, crude fiber, and polysaccharide in vegetation had significant effects on the seasonal changes in gut microbiota. Diet contributed more to microbial variation than climatic factors. Metagenomic analysis revealed that the amino acid metabolism pathway and axillary activity enzymes were most abundant in summer, while abundance of carbohydrate‐binding modules and carbohydrate esterases was highest in spring. These microbial variations were related to the changes in dietary nutrition, indicating that gut microbiota of plateau pika contribute to the efficient use of food resources. This study provides new evidence of how external environmental factors affect the intestinal environment of small mammals. [ABSTRACT FROM AUTHOR]

Seasonal abandonment in the previously rice‐based rotation system is increasingly prevalent worldwide particularly in southern China. Assessing the effect of this abandonment on evapotranspiration (ET) and water resources is of major importance for regional water cycle change and agricultural water management. This study analyzed the ET characterization of rice‐winter rape and rice‐winter fallow rotation systems and its relation to weather factors in a humid lowland region, southern China based on a half‐hourly ET measurement with Bowen ratio energy balance system from 2017 to 2020. Then the strategic modeling experiment combining ET and rainfall‐runoff models was used to explore the land abandoning effect on ET and water resources. The results showed that the daily ET values of the rice, rape, and fallow seasons were 3.30 ± 1.89, 1.31 ± 1.31, and 1.55 ± 1.19 mm/d, respectively. The averaged summed ET values of the rice‐winter rape and rice‐fallow rotation systems were 652.3 and 737.8 mm, respectively. Net radiation (Rn) was identified as the most critical weather factor for ET of all seasons. Air temperature and water vapor pressure deficit mainly affected ET indirectly through the path of Rn. Compared with the previously winter rape, the change in daily ET caused by seasonal abandonment was 0.13 ± 0.11 mm/d. This abandonment‐induced ET change increased the average daily storage deficit by 12.0% and groundwater depth by 4.5%, while reduced the daily runoff by 20.3%. Plain Language Summary: Effect of seasonal cropland abandonment on ET and water resources in the humid lowland region. Key Points: The evapotranspiration (ET) of rice, rape, and fallow were compared using Bowen ratio energy balance observationThe modeling strategies with field experiment quantified the seasonal abandonment effectSeasonal abandonment increased ET and decreased surface water and groundwater resources relative to the previous winter rape [ABSTRACT FROM AUTHOR]

This study examines the sub‐seasonal forecast skill of the dominant mode of atmospheric circulation variability in the Northern Hemisphere (NH) mid‐latitudes, the Middle Latitudes Seasonal Oscillation (MLSO), and the influence of MLSO on the forecast skill of surface weather in this area. The analysis is conducted using reforecasts produced by four forecast systems, which archive their output in the Subseasonal‐to‐Seasonal (S2S) Data Base. A reduced ensemble of reforecasts for each model is verified against the ERA‐Interim reanalysis. The S2S models display significant ability to predict the MLSO on the S2S time scale. The MLSO prediction skill is higher in boreal winter than in summer. A relationship is found between the MLSO and the forecast skill of 2‐m temperature (T2m) in the NH mid‐latitudes during the extended boreal winter. The prediction of T2m improves when MLSO events are in the initial conditions and the improvement depends on the phase of MLSO. Plain Language Summary: Many phenomena are routinely predicted, yet prediction on time scales longer than two weeks is regarded as limited because of the chaotic nature of atmospheric dynamics. Phenomena with life cycles longer than two weeks can enhance the predictability of phenomena with shorter life cycles if there is a linkage between the two, and especially if the former is characterized by large‐scale patterns and the latter consists of small‐scale patterns. The forecast skill or how successful a prediction can be, depends also on the ability of the forecast model to predict the longer time scale variability. In this study, the forecast skill of four state‐of‐the‐art forecast models is evaluated to assess their ability to predict an atmospheric oscillation with a life cycle of 120 days coined as the Middle Latitudes Seasonal Oscillation (MLSO) and whether this oscillation can improve the forecast skill of surface air temperature over the Northern Hemisphere. We find that models show a skillful forecast of the 120‐day oscillation especially during boreal winter, and MLSO is a source of predictability for the surface air temperature. Key Points: The Middle Latitudes Seasonal Oscillation (MLSO) can be predicted by the S2S models up to four weeksThe forecast skill of MLSO is higher during boreal winter than summerMLSO is an important source of predictability for the surface air temperature during boreal winter [ABSTRACT FROM AUTHOR]

In tropical regions, particularly in Central and South America (CSA), the projections of climate seasonality under climate change are still uncertain. This is especially true for ecologically‐relevant variables such as precipitation and temperature. However, assessments of model‐based projections of seasonal climate for this region are scarce. We analyzed the simulation of seasonal precipitation and air surface temperature in CSA and six sub‐regions within from 49 models included in the Coupled Intercomparison Project Phase 5 (CMIP5) and 33 models from CMIP6. In general, continental patterns and seasonality of both variables are moderately well resembled, while most models show systematic biases over the oceans, producing unrealistic spatial patterns. To quantify how well CMIP5/CMIP6 models simulate these variables, we used Taylor diagrams with respect to TRMM for precipitation and ERA5 for temperature. Precipitation shows the largest spread among models. Conversely, temperature shows a better simulation. CMIP5/CMIP6 models exhibit a better performance simulating both variables during December–January–February and March–April–May than during the other seasons. This is partly due to the reduced model biases in representing the Intertropical Convergence Zone during these two seasons. In general, biases are reduced in the CMIP6 models with respect to CMIP5. Regarding regional evaluations, precipitation patterns for Mesoamerica, Cerrado and Chaco regions are better reproduced compared to TRMM, while the annual cycles for the Andes hotspot, Central Chile and Guianas are not well simulated, mainly during their wet seasons. However, these biases are reduced in CMIP6 models. In regard to precipitation projections, models only agree over most of the regions with decreasing precipitation. Conversely, temperature exhibits a general consensus on persistent warming even during the historical period, with an average increase of 6°C by the end of the century, according to the CMIP6 models. [ABSTRACT FROM AUTHOR]

Whether sea‐ice loss or lapse‐rate feedback dominates the Arctic amplification (AA) remains an open question. Analysis of data sets based upon observations reveals a 1.11 K per decade surface warming trend in the Arctic (70°–90°N) during 1979–2020 cold season (October–February) that is five times higher than the corresponding global mean. Based on surface energy budget analysis, we show that the largest contribution (∼82%) to this cold season warming trend is attributed to changes in clear‐sky downward longwave radiation. In contrast to that in Arctic summer and over tropics, a reduction in lower‐tropospheric inversions plays a unique role in explaining the reduction of the downward longwave radiation associated with atmospheric nonuniform temperature and corresponding moisture changes. Our analyses also suggest that Arctic lower‐tropospheric stability should be considered in conjunction with sea‐ice decline during the preceding warm season to explain AA. Plain Language Summary: Observations and climate models have consistently shown a stronger surface warming in the Arctic than the global mean, a.k.a. Arctic amplification (AA), which has a strong asymmetry between the cold season and warm season. Previous studies suggested that key contributors to AA are the positive surface‐albedo feedback and lapse‐rate feedback. However, the lapse‐rate feedback itself depends on temperature profiles and sea‐ice loss. Whether sea‐ice loss or lapse‐rate feedback dominates AA remains an open question. Here, by analyzing the latest generation of observationally‐based reanalysis data (1979–2020), we present a unique role of lower‐tropospheric temperature inversion changes in representing the contribution of vertically inhomogeneous atmospheric temperature and associated moisture changes to clear‐sky downward longwave radiation during the cold season. This unique role is not found either in the tropics or during Arctic summertime. We further link the inversion during the cold season to sea‐ice loss during the preceding warm season. These results reinforce previous findings not only that lapse‐rate feedback and sea‐ice loss play a key role in AA but also that lapse‐rate feedback in the cold season is likely a consequence of sea‐ice albedo feedback during the preceding warm season. Key Points: An increase in clear‐sky downward longwave radiation (rldsclr) explains 82% of the recent cold season Arctic surface warming trendReduced low inversion largely explains the Arctic rldsclr reduction due to vertical nonuniform temperature and related moisture changesLapse‐rate feedback in the Arctic cold season is likely a consequence of sea‐ice albedo feedback during the preceding warm season [ABSTRACT FROM AUTHOR]

This study explores the teleconnection between the boreal summer precipitation for the central highlands of Eritrea, with respect to global sea‐surface temperature (SST) and atmospheric parameters (winds, pressure, humidity, and vertical velocity) as indirect indicators of atmospheric circulation. The central‐highland summer (Jul–Aug) precipitation (1914–2015) is significantly negatively correlated with the Atlantic Niño (ATL3) index. Similarly, with a 2‐month (May) or 1‐month lead (Jun), SSTs over the equatorial Atlantic (Gulf of Guinea) are inversely correlated with the central‐highland summer precipitation. Moreover, the regional atmospheric circulation reveals that the boreal summer precipitation series has a significant positive correlation with the westerly wind over the Gulf of Guinea at 700 hPa and a negative correlation with the Tropical Easterly Jet (TEJ) at 200 hPa. Overall, these findings depict the African Walker circulation cell, whereby a low‐level westerly wind flows from the Gulf of Guinea across central Africa, coupled with a rising branch over north‐eastern Africa, and reverses as an easterly wind at a higher level. These significant correlations between Atlantic Ocean SST as the precipitation‐driving factor enabled the development and validation of an area‐specific seasonal precipitation prediction model, as precipitation in this region is temporally and spatially highly variable. [ABSTRACT FROM AUTHOR]

We analyse seasonal and annual trends of extreme indices of air temperature and precipitation over Brazil during the period 1961–2018. The main goal is to investigate whether the climate is changing and if so, to explore if there is any marked seasonality in such changes. The daily observed datasets of maximum and minimum temperatures, and precipitation, are provided by the Brazilian National Institute of Meteorology and National Water Agency. We use the Sen Curvature and Mann‐Kendall statistical tests to compute the magnitudes and to evaluate the statistical significance of climate extremes trends, respectively. The results show that the warm extremes frequency of occurrence is increasing significantly while the opposite occurs for cold extremes, which reveals a very consistent and widespread warming over Brazil. The highest increases in warm extremes occur during austral spring and summer while for the cold extremes the greatest decreases are observed during austral winter. Unlike temperature, precipitation extremes show heterogeneous signals for most of the country. In Northeast Brazil, there are changes towards a drier climate, especially in summer and autumn. In the Southern region, the climate is becoming wetter, with a reduction in consecutive dry days, especially in spring. For the other regions, there is no strong clear change sign, but both positive and negative precipitation extreme trends, without statistical significance (mostly in Southeast Region). [ABSTRACT FROM AUTHOR]

Understanding the influences of local hydroclimatology and two large‐scale oceanic‐atmospheric oscillations (i.e., Atlantic Multidecadal Oscillation (AMO) and El Niño‐Southern Oscillation (ENSO)) on seasonal precipitation (P) and temperature (T) relationships for a tropical region (i.e., Florida) is the focus of this study. The warm and cool phases of AMO and ENSO are initially identified using sea surface temperatures (SSTs). The associations of SSTs and regional minimum, maximum and average surface air temperatures (SATs) with precipitation are then evaluated. The seasonal variations in P‐SATs and P‐SSTs associations considering AMO and ENSO phases for sites in (1) two soil temperature regimes (i.e., thermic and hyperthermic); (2) urban and non‐urban regions; and (3) regions with and without water bodies, are analysed using two monthly datasets. The analyses are carried out using trend tests, two association measures, nonparametric and parametric statistical hypothesis tests and kernel density estimates. Decreasing (increasing) trend in precipitation (SATs) is noted in the recent multi‐decadal period (1985–2019) compared to the previous one (1950–1984) indicating a progression towards warmer and drier climatic conditions across Florida. Spatially and temporally non‐uniform variations in the associations of precipitation with SATs and SSTs are noted. Strong positive (weak negative) P–T associations are noted during the wet (dry) season for both AMO phases and El Niño, while significant (positive) P–T associations are observed across southern Florida during La Niña in the dry season. The seasonal influences are predominant in governing the P–T relationship over the regions with and without water bodies; however, considerable variations between El Niño and La Niña are noted during the dry season. The climate variability influences on P–T correlations for hyperthermic and thermic soil zones are found to be insignificant (significant) during the wet (dry) season. Nonparametric clustering is performed to identify the spatial clusters exhibiting homogeneous P–T relationships considering seasonal and climate variability influences. [ABSTRACT FROM AUTHOR]

Marine cold‐air outbreaks (MCAOs) create conditions for hazardous maritime mesocyclones (polar lows) posing risks to marine infrastructure. For marine management, skilful predictions of MCAOs would be highly beneficial. For this reason, we investigate (a) the ability of a seasonal prediction system to predict MCAOs and (b) the possibilities to improve predictions through large‐scale causal drivers. Our results show that the seasonal ensemble predictions have high prediction skill for MCAOs over the Nordic Seas for about 20 days starting from November initial conditions. To study causal drivers of MCAOs, we utilize a causal effect network approach applied to the atmospheric reanalysis ERA‐Interim and identify local sea surface temperature and atmospheric circulation patterns over Scandinavia as valuable predictors. Prediction skill for MCAOs is further improved up to 40 days by including MCAO predictors in the analysis. [ABSTRACT FROM AUTHOR]

Seasonal water‐level fluctuations (WLFs) in reservoirs influence ecological processes, in turn affecting their benthic macroinvertebrate communities. The present study was carried out in 10 irrigation reservoirs of Sri Lanka to investigate the effects of seasonal WLFs on the benthic macroinvertebrate fauna. The study period was divided into two distinct phases: the drained period and the inundated period. Benthic macroinvertebrates were sampled during both periods and enumerated. Air temperature and soil quality parameters were also measured simultaneously, and hydrological data related to the Kala Oya River basin were obtained from irrigation authorities. Data analysis using non‐metric multi‐dimensional scaling revealed two distinct reservoir groups, namely, Hydrological Stress Group 1 (HSG1) and Hydrological Stress Group 2 (HSG2). A low hydrological residence time and low relative reservoir level fluctuations (RRLF) characterized HSG1, with the opposite describing HSG2. Temporal variations of macrobenthos indicated a high taxa richness and diversity in HSG1 reservoirs during the drained period, with scrapers and collector‐gatherers being the dominant functional feeding groups. Reservoirs in the lower river basin (HSG1) exhibited a high taxa richness and diversity. During the inundated periods, insect taxa colonized, particularly, chironomids and ephemeropterans. Molluscan taxa were prominent during the drained periods. These observations highlight the influence of seasonal fluctuations of reservoir water levels on benthic macroinvertebrates. Benthic macroinvertebrate communities in reservoirs were significantly influenced by the RRLF, manifesting the importance of hydrological regimes in reservoirs to develop macroinvertebrate metrics for water‐quality monitoring. [ABSTRACT FROM AUTHOR]

Snowfall and snow season length across Alaska control the surface hydrology and underlying soil properties and also influence near‐surface air temperature by changing the energy balance. Current projections of warming suggest that considerable change will occur to key snow parameters, possibly contributing to extensive infrastructure damage from thawing permafrost, an increased frequency of rain‐on‐snow events and reduced soil recharge in the spring due to shallow end‐of‐winter snowpack. This study investigates projected changes to mean annual snowfall, dates of snow onset and snowmelt and extreme snowfall for Alaska, using dynamically downscaled reanalysis and climate model simulations. These include the ERA‐Interim reanalysis from 1981 to 2010, and two Coupled Model Intercomparison Project Phase 5 models: Community Climate System Model version 4 (CCSM4) and Geophysical Fluid Dynamics Laboratory Climate Model version 3 (GFDL‐CM3) from 1981 to 2100. The analysis is presented in 30‐year periods (i.e., 1981–2010, 2011–2040, 2041–2070 and 2071–2100) with the future scenarios from Representative Concentration Pathway 8.5. Late‐century projections of average annual snowfall at low elevations (0–1,000 m) show decreases of 41.3 and 40.6% for CCSM4 and GFDL‐CM3, respectively. At high elevations (1,000–2,000 m), the reductions are smaller at 13.5 and 14.2%, respectively. End‐of‐winter snow‐water equivalent displays reductions at all elevations in the future periods. Snow season length is shortened due to later snow onset and earlier snowmelt; many locations in southwest Alaska no longer experience continuous winter snowpack by the late‐century period. Maximum 2‐day snowfall amounts are projected to decrease near Anchorage and Nome, while Fairbanks and Utqiaġvik (Barrow) show no significant trend. [ABSTRACT FROM AUTHOR]

The spatiotemporal pattern of precipitation is significantly changing with global climate change. Snowfall is a solid phase of precipitation and an important water resource. With two gridded data sets of APHRO (Asia Precipitation‐Highly‐Resolved Observational Data Integration Towards Evaluation of Water Resources) and CN05.1, this study analyses the changes in the spatiotemporal pattern of snowfall in a snow‐dominant region of China from 1961 to 2015. The results indicate the significant increasing trend of winter snowfall in horizontal and altitude dimension in snow‐dominant regions, but the winter snowing season length shortened. For the frequency of snowfall intensity level, light, and heavy snowfall and snowstorms increased, but moderate snowfall showed no change. However, the intensity of extreme snowfall in once‐in‐a‐century was decreasing in all of the snow‐dominant regions. In the altitude dimension, the increasing trend in snow‐dominant conditions was not uniform, which may be related to change in air temperature and water vapour through the vertical atmospheric levels. The upwards trend in snowfall may be caused by the increase of atmospheric water content rather than the change of snowy weather conditions. In addition, the change values of climate indices can also contribute to snowfall increasing in snow‐dominant regions. [ABSTRACT FROM AUTHOR]

Greenland fjords provide a pathway for the inflow of warm shelf waters to glacier termini and outflow of glacially modified waters to the coastal ocean. Characterizing the dominant modes of variability in fjord circulation, and how they vary over subannual and seasonal time scales, is critical for predicting ocean heat transport to the ice. Here we present a 2‐year hydrographic record from a suite of moorings in Davis Strait and two neighboring west Greenland fjords that exhibit contrasting fjord and glacier geometry (Kangerdlugssuaq Sermerssua and Rink Isbræ). Hydrographic variability above the sill exhibits clear seasonality, with a progressive cooling of near‐surface waters and shoaling of deep isotherms above the sill during winter to spring. Renewal of below‐sill waters coincides with the arrival of dense waters at the fjord mouth; warm, salty Atlantic‐origin water cascades into fjord basins from winter to midsummer. We then use Seaglider observations at Davis Strait, along with reanalysis of sea ice and wind stress in Baffin Bay, to explore the role of the West Greenland Current and local air‐sea forcing in driving fjord renewal. These results demonstrate the importance of both remote and local processes in driving renewal of near‐terminus waters, highlighting the need for sustained observations and improved ocean models that resolve the complete slope‐trough‐fjord‐ice system. Plain Language Summary: Submarine melting of ice due to warm ocean waters has been implicated as a mechanism for the retreat and destabilization of marine‐terminating glaciers worldwide. In Greenland, fjords provide an important connection between marine‐terminating glaciers and warm subsurface waters located offshore. However, due to sparse ocean‐glacier observations in these ice‐choked systems, especially during winter months, we lack an understanding of how the large‐scale circulation along Greenland's periphery influences near‐glacier ocean temperatures. To address this, we present a 2‐year mooring record from Davis Strait and two neighboring west Greenland fjords. Above the sill, fjord temperatures exhibit a clear seasonal cycle that is inherited from the continental shelf and slope. Below the sill, warming of fjord waters occurs more intermittently and is initiated when salty Atlantic‐origin waters arrive at the fjord mouth. In summary, these novel observations allow for a better understanding of ocean‐glacier interactions in Greenland. Key Points: We analyze a 2‐year hydrographic record from a suite of moorings in Davis Strait and two adjacent west Greenland fjordsHydrography above the sill exhibits clear seasonality; subannual warming of basin waters coincides with the arrival of dense Atlantic‐origin waters at the mouthWe use Seaglider observations and reanalysis of sea ice and winds to explore the role of local and remote forcing in driving fjord renewal [ABSTRACT FROM AUTHOR]

Abstract: Background: The aim of the study was to examine the influence of the changes in the atmospheric temperature (ATemp) and the atmospheric pressure (APres) on the occurrence of a spontaneous pneumothorax (SP). Patients and methods: From January 2000 to March 2014, 192 consecutive SP events were examined. The ATemp and APres data at the onset of SP, as well as those data at 12, 24, 36, 48, 60, and 72 h prior to the onset time, were analyzed. Results: The frequencies of SP occurrence were not statistically different according to the months or seasons, but were statistically different according to the time period (P < .01) and SP events occurred most frequently from 12:00 to 18:00. SP events frequently occurred at an ATemp of 25 degrees Celsius or higher. There was a significantly negative correlation between the APres and the ATemp at the SP onset time. The values of change in the APres from 36 to 24 h prior to SP onset were significantly lower than the preceding values. Conclusions: In this study, we observed that a SP event was likely to occur in the time period from 12:00 to 18:00, at an ATemp of 25 degrees Celsius or higher, and at 24–36 h after a drop of APres. [ABSTRACT FROM AUTHOR]

Background: Preeclampsia is associated with conception during warm months and delivery during cold months. We sought to determine whether season of conception and shorter gestation bias the associations.Methods: We used hospital discharge summaries to identify 65 273 pregnancies with and 1 825 438 without preeclampsia in Quebec, Canada between 1989 and 2012. We obtained data on mean temperature for the month following conception and the month before hospital admission. We used cubic splines in log-binomial models to estimate the association between temperature and preeclampsia (risk ratios, RR; 95% confidence interval, CI). To assess the potential for bias, we compared models progressively adjusted for baseline maternal characteristics, season of conception, and length of gestation at admission.Results: With adjustment for baseline maternal characteristics only, risk of preeclampsia was higher for hot temperatures at conception and cold temperatures at end of pregnancy. Adjusting for season at conception removed the association between preeclampsia and temperature at conception. Adjustment for length of gestation removed the association between preeclampsia and temperature at end of pregnancy.Conclusions: This study demonstrates that associations between ambient temperature and preeclampsia may be biased by short gestation, because preeclampsia commonly occurs earlier in pregnancy. Temperatures during gestation change with time for all women, and temperatures early in pregnancy frequently differ from temperatures later in pregnancy. Variation in temperature over gestation may lead to a coincidental association with preeclampsia. [ABSTRACT FROM AUTHOR]

Ensuring food security in a changing climate is a major contemporary challenge and requires development of climate‐resilient crops that perform well under variable environments. The hypothesis that yield stability in suboptimal conditions is linked to yield penalties in optimal conditions was investigated in field‐grown wheat in the UK. The phenotypic responses, rate of wheat crop development, and final grain yield to varying sowing date, rainfall, air temperature, and radiation patterns were studied for a panel of 61 elite commercial wheat cultivars grown in the UK in 2012, 2013, and 2014. Contrasting climatic patterns, particularly rainfall accumulation and distribution over the season, influenced the relative performance of the cultivars affecting the duration of grain development stage and impacting on productivity. Indices for crop productivity, yield stability, and performance under suboptimal conditions revealed four cultivars with a combination of stable and high relative grain yields over the three seasons: Gladiator, Humber, Mercato, and Zebedee. Genetic similarity between cultivars partially explained yield performance in the contrasting seasons. The year of release of the cultivars correlated with grain yield but not with yield stability, supporting the contention that breeding for yield potential does not select for climate resilience and yield stability of crops. Further analysis of the outstanding cultivars may unravel target traits for breeding efforts aimed at increasing wheat yield potential and stability in the changing climate. [ABSTRACT FROM AUTHOR]