Search

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]

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]

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]

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 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]

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]

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 and purpose: Environmental factors are thought to be important in multiple sclerosis (MS) pathophysiology. We aimed to evaluate if there was an association between MS relapses and some climatic factors in a Portuguese population. Methods: Four year retrospective study analyzing 414 MS relapses in 249 consecutive relapsing–remitting patients. Non-parametric statistics were used to compare the distribution of relapses across months and seasons. Spearman’s coefficient was determined to evaluate the correlation between relapses frequency and maximum and minimum atmospheric temperatures, humidity and atmospheric pressure. Results: The mean number of relapses was not significantly different between months or seasons. No correlation was found between relapse frequency and any climatic factor. Conclusion: Our series is one of the largest addressing the influence of specific climatic factors on MS relapses. The number of clinical MS relapses seems to be unrelated to climatic factors. [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]

The article discusses a study conducted which explores the effects of hydroclimatic changes at the North America Monsoon System (NAMS) region. It reveals that warming occurred during dry season while minimum temperatures happened during wet season. Moreover, remote-sensing data and regional modeling experiments are needed to determine the changes in atmospheric circulation.