Winter Patterns Research Articles

Predictability of European winter 2022/23

AbstractThe boreal winter of 2022/23 was notable as a third consecutive winter in which La Niña had an influence on the European weather. The GloSea6 seasonal forecast system predicted a blocked circulation pattern in the North Atlantic in early winter (December), and then a transition through mid‐winter (January) into a more zonal pattern in late winter (February), consistent with the canonical La Niña teleconnection pattern seen previously. The seasonal forecast for the UK was an increased likelihood of near average temperatures, and drier‐ and calmer‐than‐average conditions. Both the predicted broad‐scale circulation patterns and UK winter mean weather conditions verified well against observations, and we show that seasonal forecasts of the North Atlantic Oscillation (NAO) over the last 10 winters show similar skill to previously reported hindcasts. Throughout the winter, the Madden–Julian Oscillation (MJO) was particularly active. On three occasions, it exhibited strong phases 6 and 7. There was also a sudden stratospheric warming (SSW) that occurred on 16th February. This was followed by colder conditions and associated impacts similar to the canonical negative NAO response over the UK, although the main impact fell in March and so did not affect the winter (December–January–February) mean conditions.

Cloud base height variability observed using a Laser-Based Ceilometer over a tropical station Pune, India

ABSTRACT Clouds play a pivotal role in determining Earth’s climate, impacting several atmospheric processes influencing the weather. The study explores the temporal variations in cloud base height (CBH) over Pune, a tropical station, from 2017 to 2023 using a Laser-Based Ceilometer with a range of 0–7500 m. Our analysis shows seasonal trends in CBH, with the monsoon season exhibiting unique characteristics showing the lowest average CBH and minimal diurnal changes during the study period. Conversely, the pre-monsoon, post-monsoon, and winter season show a gradual rise of CBH in the morning, maintaining higher levels until late afternoon, followed by a decline in the evening. Analysis of the diurnal frequency of cloud occurrence at 500 m intervals reveals the monsoon season’s dominance in the 500 m to 1000 m layer. Throughout the year, low cloud bases (CBH <2000 m) are most frequent, outpacing the frequency of mid and high cloud bases. High cloud base (7500 < CBH > 6000 m) is the least common, showing a semi-diurnal pattern in winter with peaks around noon and midnight. These findings not only enhance our understanding of Pune’s atmospheric behaviour but also offer valuable information for weather prediction, climate modelling, and environmental monitoring.

The role of seasonal characteristics in addressing scattering species for improved visibility in Shanghai, China

Submicron particle extinction significantly contributed to reduced horizontal visibility during severe pollution episodes. However, seasonal variations in the scattering coefficients of chemical components, particularly with their size and mass concentration, are still not fully understood. This study investigated the scattering coefficients of the main chemical components of submicron particles (PM1) in Shanghai using advanced instruments. We discovered that the main scattering species exhibited seasonal variations. Notably, organics (OA) and ammonium sulfate ((NH4)2SO4) dominated in spring, summer, and autumn, whereas ammonium nitrate (NH4NO3) was the primary scattering species in winter. Analyzing the particle scattering coefficient size revealed that the scattering coefficients for OA in Shanghai exhibited bimodal distributions in spring, autumn, and winter, with peak sizes of 500–700 nm. The distribution was unimodal in summer, with a 400–500 nm peak size range. In addition, the peak particle size distributions of NH4NO3 and (NH4)2SO4 demonstrated a pattern of winter > spring/autumn > summer, potentially owing to the different species sources and formation pathways throughout the four seasons. Seasonal variations in the mass scattering efficiency (MSE) showed that OA exhibited a higher MSE than NH4NO3 or (NH4)2SO4. Further, NH4NO3 exhibited a higher MSE in winter, whereas (NH4)2SO4 exhibited the highest MSE in summer at 5.63. This study highlighted the importance of considering seasonal characteristics controlling scattered species and their precursors to enhance visibility. These findings can assist in formulating visibility control strategies in Shanghai.

Different ENSO Impacts on Eastern China Precipitation Patterns in Early and Late Winter Associated with Seasonally-Varying Kuroshio Anticyclonic Anomalies

Different ENSO Impacts on Eastern China Precipitation Patterns in Early and Late Winter Associated with Seasonally-Varying Kuroshio Anticyclonic Anomalies

Relative Impacts of Sea Ice Loss and Atmospheric Internal Variability on the Winter Arctic to East Asian Surface Air Temperature Based on Large-Ensemble Simulations with NorESM2

To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia” (WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day (or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day (or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four (ten) times larger than the ice-induced East Asian cooling in the present-day (future) experiment; the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60% (80%) to the Arctic winter warming in the present-day (future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-loss-induced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.

Different responses of surface air temperature over Eurasia in early and late winter to the autumn Kara–Laptev Sea ice

The Arctic climate is changing rapidly, along with intensified melting of sea ice, which has significant impacts on surface air temperature (SAT) in Eurasia. This study reveals that the subseasonal response of SAT to the autumn Kara–Laptev Sea ice (KLSIC) differs significantly between early and late winter. The response of SAT to KLSIC forms a warm Arctic–cold Eurasia pattern in early winter. Conversely, the negative anomaly response of SAT to KLSIC in late winter is only distributed in the band range of Eurasia, without significant positive SAT anomaly over the Arctic Ocean. After further examination of the separate physical mechanisms involved in early and late winter, it is found that a decrease in KLSIC in autumn can lead to a strengthened Ural high and Siberian high in the Arctic–Eurasia region, which is conducive to cold events in the mid-latitudes of Eurasia in early winter. For late winter, a westward shift in the response of atmospheric circulation to KLSIC leads to a negative anomaly feedback of North Sea surface temperature, which triggers the propagation of Rossby waves to the Sea of Japan through the wave activity flux. Meanwhile, the deep trough of East Asia is strengthened and extends to the southeast, guiding northern cold air to the western Pacific. Our results highlight that different subseasonal effects of sea ice should be considered in Eurasian climate prediction, rather than only consider the effects in winter mean.

The role of atmospheric rivers and associated circulation patterns in the Arctic warming in boreal winter

AbstractAtmospheric rivers (ARs) serve a narrow, filamentary channels responsible for intense moisture and heat transport, which are vital for the Arctic sea ice loss and surface air warming, particularly in winter. In this study, ERA5 reanalysis data from 1979 to 2020 are used to investigate the evolution of ARs in the Arctic and the corresponding atmospheric circulation patterns in winter. Our findings indicate that atmospheric circulation is a key factor that facilitates the transport and dispersion of ARs. Cyclonic circulation anomalies provide the dynamical support for ARs in the early development stages, while anticyclonic anomalies are essential for maintaining the thermal and moisture conditions of ARs, particularly after their intrusions into the Arctic region. The cooperation between cyclonic and anticyclonic anomalies plays a critical role in the infiltration and dispersion of ARs, governed by distinct circulation modes for regional intrusions. A positive Arctic Oscillation‐like pattern manifests as a cyclonic system over the Arctic, increasing the likelihood of AR intrusion into Baffin Bay. Conversely, a negative pattern induces a more intense anticyclonic system over the Arctic, thereby raising the frequency of ARs in the Bering Strait. The Pacific‐North American pattern not only directly affects ARs entering the Arctic via the Pacific but also has downstream impacts on ARs intruding the Arctic through Baffin Bay.

Northern Hemisphere winter atmospheric teleconnections are intensified by extratropical ocean-atmosphere coupling

The role of extratropical atmosphere-ocean coupling in generating and maintaining large-scale atmospheric low-frequency variability remains an open question owing to vigorous atmospheric internal fluctuations. Here, we use coupled and uncoupled large-ensemble global model simulations to clarify how the coupling intensifies atmospheric teleconnection patterns in the Northern Hemisphere winter. We show that the extratropical coupling selectively enhances the variance of three principal modes of variability, explaining 13%, 11%, and 10% of the total variance of Pacific/North American, North Atlantic Oscillation, and Warm-Arctic Cold-Eurasian patterns, respectively. Atmosphere-ocean coupling reduces damping to lower-tropospheric available potential energy, which in turn increases kinetic energy by changing energy transfer within the mode. The extratropical ocean is overall passive (adjustable) to large-scale atmospheric variation, thus contributing to the prominence of these modes. The geographical dependence of available potential energy damping suggests the existence of mode-specific sweet spots where the influence of coupling operates efficiently, providing a clue to improving the model biases in variance and signal-to-noise ratio of these modes.

Evolving winter atmospheric teleconnection patterns and their potential triggers across western North America

We present a comprehensive analysis diagnosing the primary factors driving the observed changes in major atmospheric teleconnection patterns in the Northern Hemisphere winter, including the Pacific North American pattern (PNA), North Atlantic Oscillation (NAO), and North American winter dipole (NAWD), with particular focus on their roles in shaping anomalous weather across North America. Our investigation reveals a consistent influence of the NAWD over seven decades, contrasting with fluctuating impacts from PNA and minor impacts from NAO. In particular, an emergent negative correlation between the NAWD and PNA, signaling a shifted phase of teleconnection patterns, is identified. Such a relationship change is traced to enhanced upper-level ridges across western North America, reflecting a reinforced winter stationary wave. Through attribution analysis, we identify greenhouse gas emissions as a probable driver for the northward drift of the Asia-Pacific jet core, which, aided by orographic lifting over the Alaskan Range, subsequently amplifies the winter stationary wave across western North America. This work emphasizes the pronounced effect of human-induced global warming on the structure and teleconnection of large-scale atmospheric circulation in the Northern Hemisphere winter, providing vital perspectives on the dynamics of current climate trends.

Optimization scheduling of power system under load winter and summer double-peak scenario

In recent years, due to people’s need for a better life and the impact of extreme weather factors, the annual load curve shows a winter-summer double-peak pattern in summer and winter. In addition, due to the large-scale grid integration of renewable energy sources such as wind power, the uncertainty of its output has further increased the net load during the double-peak scenario, putting the power system under even greater pressure to supply electricity. In this paper, we study the day-ahead hierarchical optimal scheduling model of the power system under the double-peak scenario, considering the pumped-storage flexibility space and the extreme boundary flexibility demand. We simulate and analyze the impacts of different operation modes of the pumped-storage power plant on the scheduling results. The simulation shows that the proposed method can give full play to the effect of pumped storage peak shaving and valley filling and guarantee the reliability of the power supply under the double-peak scenario.

On the effectiveness of Reynolds-averaged and subgrid scale models in predicting flows inside car cabins

The aim of the present study is to analyze the performances of unsteady Reynolds-averaged Navier–Stokes (URANS) and large eddy simulation (LES) approaches in predicting the airflow patterns inside car cabins and to give insight in the design of computational fluid dynamics simulations of a real car cabin. For this purpose, one eddy viscosity-based turbulence model (shear stress transport k–ω) and two subgrid scale models (wall-adapting local eddy-viscosity and dynamic kinetic energy) were tested, and numerical results were compared with particle image velocimetry measurements carried out on a commercial car. The URANS model exhibited great accuracy in predicting the mean flow behavior and was appreciably outperformed by the LES models only far from the inlet sections. For this reason, it was deemed suitable for conducting further analyses, aimed at characterizing the airflow patterns in winter and summer conditions and performing a thermal comfort analysis. The thermal regime was found to have a very little effect on the air flow patterns, once the quasi-steady state regime is achieved; in fact, both in winter and in summer, the temperature field is fairly uniform within the car cabin, making the contribution of buoyancy negligible and velocity fields to be very similar in the two seasons. Findings also reveal that thermal comfort sensation can be different for passengers sharing the same car but sitting on different seats; this aspect should be considered when designing and operating the ventilation system, since the minimum comfort requirements should be met for all the occupants.

MINERAL STATUS OF LACTATING EWES IN THE ARID AND SEMI-ARID ZONES OF NORTH-CENTRAL MEXICO

Profitable sheep production depends greatly on the mineral content of range forages, as adequate nutrition is a prerequisite for reaching the animal’s optimum performance. The objective was to determine the contents of calcium (Ca), phosphorus (P), copper (Cu), zinc (Zn), and manganese (Mn) in range forages and blood serum of grazing, lactating ewes in the arid and semi-arid zones of North-Central Mexico. Samples of forages and blood of lactating ewes were collected in two seasons (spring and winter) from four randomly selected sheep farms located in the state of Aguascalientes. The P content was analyzed using the colorimetrical method, while levels of Ca, Cu, Zn, and Mn were determined by spectrophotometry. Forage mineral content averaged 0.20% P, 0.34% Ca, 8 ppm Cu, 483 ppm Mn, and 29 ppm Zn. In blood serum, mineral content reached 20 ppm P, 147 ppm Ca, 0.52 ppm Cu, 2.9 ppm Mn, and 0.80 ppm Zn in winter, and values of 20.5 ppm P, 177 ppm Ca, 0.57 ppm Cu, 3.13 ppm Mn, and 0.89 ppm Zn in spring. Overall, in both spring and winter seasons, 58-100% of sampled forages showed Ca, P, Cu, and Zn deficiencies, but all of them fitted the optimal content of Mn. Blood samples showed similar patterns in winter and spring seasons, Ca was not deficient (145-180 ppm vs. optimal range: 90-120 ppm), but P, Cu, and Zn were deficient (P: 9-21 ppm vs. optimal range: 50-65 ppm; Cu: 0.51-0.58 vs. optimal range: 0.60-1.5 ppm; and Zn: 0.71-0.92 ppm vs. optimal range: 0.50-1.2 ppm); Mn was slightly over the optimal range (2.89-3.2 μg/L vs. optimal range: 2 to 40 μg/L). In some cases, forage mineral content might not be related to blood serum contents. However, it should be desirable to understand all the uncontrolled factors in addition to the mineral interactions that could interfere with further studies.

ENSO and MJO Modulation of U.S. Cloud-to-Ground Lightning Activity

Abstract Cloud-to-ground (CG) lightning substantially impacts human health and property. However, the relations between U.S. lightning activity and the Madden–Julian oscillation (MJO) and El Niño–Southern Oscillation (ENSO), two predictable drivers of global climate variability, remain uncertain, in part because most lightning datasets have short records that cannot robustly reveal MJO- and ENSO-related patterns. To overcome this limitation, we developed an empirical model of 6-hourly lightning flash count over the contiguous United States (CONUS) using environmental variables (convective available potential energy and precipitation) and National Lightning Detection Network data for 2003–16. This model is shown to reproduce the observed daily and seasonal variability of lightning over most of CONUS. Then, the empirical model was applied to construct a proxy lightning dataset for the period 1979–2021, which was used to investigate the summer MJO–lightning relationship at daily resolution and the winter–spring ENSO–lightning relationship at seasonal resolution. Overall, no robust relationship between MJO phase and lightning patterns was found when seasonality was taken into consideration. El Niño is associated with increased lightning activity over the coastal Southeast United States during early winter, the Southwest during winter through spring, and the Northwest during late spring, whereas La Niña is associated with increased lightning activity over the Tennessee River valley during winter. Significance Statement Cloud-to-ground lightning is dangerous for humans via direct strikes or through triggering wildfires, generating air pollution, etc. How lightning activity can be affected by climate remains unclear, and it is challenging to study their links because the data record for lightning is short. With the available lightning record, we developed a model that relates lightning flash counts over the United States to environmental factors. This model well represents observed fluctuations in daily and seasonal lightning over most of the United States. Because the model only needs environmental information to predict lightning flash counts, we were able to construct a longer record of predicted lightning based on the longer data record of environmental variables. With this dataset, we investigated the links between lightning and climate and found that the state of sea surface temperatures in the tropical Pacific (El Niño–Southern Oscillation) is linked to changes in U.S. lightning patterns in winter and spring.

Comprehensive Representation of Tropical–Extratropical Teleconnections Obstructed by Tropical Pacific Convection Biases in CMIP6

Abstract The central role of tropical sea surface temperature (SST) variability in modulating Northern Hemisphere (NH) extratropical climate has long been known. However, the prevailing pathways of teleconnections in observations and the ability of climate models to replicate these observed linkages remain elusive. Here, we apply maximum covariance analysis between atmospheric circulation and tropical SST to reveal two coexisting tropical–extratropical teleconnections albeit with distinctive spatiotemporal characteristics. The first mode, resembling the Pacific–North American (PNA) pattern, favors a tropical–Arctic in-phase (warm Pacific–warm Arctic) teleconnection in boreal spring and winter. However, the second mode, with a slight seasonal preference of summer, is manifested as an elongated Rossby wave train emanating from the tropical eastern Pacific that features an out-of-phase relationship (cold Pacific–warm Arctic) between tropical central Pacific SSTs and temperature variability over the Arctic (referred to as the PARC mode). While climate models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) appear to successfully simulate the PNA mode and its temporal characteristics, the majority of models’ skill in reproducing the PARC mode is obstructed to some extent by biases in simulating low-frequency SST and rainfall variability over the tropical eastern Pacific and the climatological mean flow over the North Pacific during boreal summer. Considering the contribution of the PARC mode in shaping low-frequency climate variations over the past 42 years from the tropics to the Arctic, improving models’ capability to capture the PARC mode is essential to reduce uncertainties associated with decadal prediction and climate change projection over the NH. Significance Statement This study focuses on the skill of models in phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating two leading observed Northern Hemisphere (NH) teleconnections that show distinctive spatial and temporal characteristics. The first one, the Pacific–North American (PNA) mode, exhibits a warm Pacific–warm Arctic pattern in boreal spring and winter, and the second one, the Pacific–Arctic (PARC) mode, features a cold Pacific–warm Arctic out-of-phase relationship. We find that models are skillful in simulating the PNA mode but not the PARC mode. This limitation may be rooted in unrealistic simulations of the mean state of winds and the low-frequency sea surface temperature variability in the tropical eastern Pacific. These biases call for caution when interpreting current models’ projections of extratropical circulations on multidecadal time scales.

Overview and statistical analysis of boundary layer clouds and precipitation over the western North Atlantic Ocean

Abstract. Due to their fast evolution and large natural variability in macro- and microphysical properties, the accurate representation of boundary layer clouds in current climate models remains a challenge. One of the regions with large intermodel spread in the Coupled Model Intercomparison Project Phase 6 ensemble is the western North Atlantic Ocean. Here, statistically representative in situ measurements can help to develop and constrain the parameterization of clouds in global models. To this end, we performed comprehensive measurements of boundary layer clouds, aerosol, trace gases, and radiation in the western North Atlantic Ocean during the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) mission. In total, 174 research flights with 574 flight hours for cloud and precipitation measurements were performed with the HU-25 Falcon during three winter (February–March 2020, January–April 2021, and November 2021–March 2022) and three summer seasons (August–September 2020, May–June 2021, and May–June 2022). Here we present a statistical evaluation of 16 140 individual cloud events probed by the fast cloud droplet probe and the two-dimensional stereo cloud probe during 155 research flights in a representative and repetitive flight strategy allowing for robust statistical data analyses. We show that the vertical profiles of distributions of the liquid water content and the cloud droplet effective diameter (ED) increase with altitude in the marine boundary layer. Due to higher updraft speeds, higher cloud droplet number concentrations (Nliquid) were measured in winter compared to summer despite lower cloud condensation nucleus abundance. Flight cloud cover derived from statistical analysis of in situ data is reduced in summer and shows large variability. This seasonal contrast in cloud coverage is consistent with a dominance of a synoptic pattern in winter that favors conditions for the formation of stratiform clouds at the western edge of cyclones (post-cyclonic). In contrast, a dominant summer anticyclone is concomitant with the occurrence of shallow cumulus clouds and lower cloud coverage. The evaluation of boundary layer clouds and precipitation in the Nliquid ED phase space sheds light on liquid, mixed-phase, and ice cloud properties and helps to categorize the cloud data. Ice and liquid precipitation, often masked in cloud statistics by a high abundance of liquid clouds, is often observed throughout the cloud. The ACTIVATE in situ cloud measurements provide a wealth of cloud information useful for assessing airborne and satellite remote-sensing products, for global climate and weather model evaluations, and for dedicated process studies that address precipitation and aerosol–cloud interactions.

Seasonal fluctuations of hemolymph microbiota and immune parameters in Mytilus galloprovincialis farmed at La Spezia, Italy

Marine bivalves include economically highly important aquacultured species worldwide (oysters, mussels, clams, scallops). Although one third of production in Europe is represented by mussels (Mytilus edulis, M. galloprovincialis) a significant decline has been observed in the last two decades, whose causes are likely to be multifactorial, from the presence of pathogens to climate change, often exacerbated by local conditions, leading to mortality outbreaks.Knowledge of the composition of the microbial communities, together with their relationship with the host, represents a primary target for understanding bivalve health in different environmental conditions. The microbiome is strongly influenced by both local environmental factors and endogenous factors, such as the host immune status. However, information on the seasonal fluctuations of microbial communities in mussels, together with immune parameters, is still lacking.In the present work, M. galloprovincialis cultivated in north-western Italy (La Spezia) were sampled from February to November 2020 and hemolymph microbiome was evaluated using 16S rRNA gene, together with a set of immune biomarkers in hemocytes (lysosomal membrane stability-LMS, phagocytic activity, ROS production) and soluble lysozyme activity, and parameters of general health conditions (gametogenesis, survival in air).The results show that M. galloprovincialis hemolymph microbiota was characterized by the constant presence of 8 bacterial genera (Vibrio, Pseudoalteromonas, Tenacibaculum, Colwellia, Shewanella, Amphritea, and 2 from the Arcobacteracea family, Halarcobacter and Arcobacter-like). Seasonal changes in their relative abundance were observed, showing a distinct pattern in winter (February–November) and summer (July, September). Water temperature contributed to shaping the microbiota composition, in particular with regards to the abundance of Vibrios, Psychrilobacter and Photobacterium, Halarcobacter and Arcobacter-like, that was favored by higher temperatures. Seasonal variations of LMS and phagocytosis were also observed, indicating a reduced immunocompetence in winter, concomitant with general stressful conditions associated with spawning. In contrast, the main fluctuations in extracellular immune defences (ROS and lysozyme) were apparently independent of temperature or gametogenic stage. Overall, the results confirm the robustness of mussel immune system, at the same time underlying the potential susceptibility to disease at certain times of the year to additional stressful conditions (i.e. pathogen challenge, pollutant exposure, or further changes in water chemico-physical parameters). These data provide background information useful for monitoring local mussel farming and predicting potential impacts of changing environmental conditions.

Squamate metabolic rates decrease in winter beyond the effect of temperature.

The reptilian form of hibernation (brumation) is much less studied than its mammalian and insect equivalents. Hibernation and brumation share some basic features but may differ in others. Evidence for hypometabolism in brumating reptiles beyond the effect of temperature is sporadic and often ignored. We calculated the standard metabolic rates (SMR, oxygen uptake during inactivity), in winter and/or summer, of 156 individuals representing 59 species of Israeli squamates across all 17 local families. For 32 species, we measured the same individuals during both seasons. We measured gas exchange continuously in a dark metabolic chamber, under the average January high and low temperatures (20°C and 12°C), during daytime and nighttime. We examined how SMR changes with season, biome, body size, temperature and time of day, using phylogenetic mixed models. Metabolic rates increased at sunrise in the diurnal species, despite no light or other external cues, while in nocturnal species the metabolic rates did not increase. Cathemeral species shifted from a diurnal-like diel pattern in winter to a nocturnal-like pattern in summer. Regardless of season, Mediterranean species SMRs were 30% higher than similar-sized desert species. Summer SMR of all species together scaled with body size with an exponent of 0.84 but dropped to 0.71 during brumation. Individuals measured during both seasons decreased their SMR between summer and winter by a 47%, on average, at 20°C and by 70% at 12°C. Q10 was 1.75 times higher in winter than in summer, possibly indicating an active suppression of metabolic processes under cold temperatures. Our results challenge the commonly held perception that squamate physiology is mainly shaped by temperature, with little role for intrinsic metabolic regulation. The patterns we describe indicate that seasonal, diel and geographic factors can trigger remarkable shifts in metabolism across squamate species.

Evaluating the climate projections for China through the lens of the simulations of planetary boundary layer height

The planetary boundary layer height (PBLH) plays an essential role in affecting many meteorological parameters in climate change, and it is closely associated with the concentration of near surface air pollutants as well. Uncertainty of simulating PBLH is large partly due to the complexity in the modulation of surface energy, and the behaviors of the climate models in reproducing PBLH have not been fully evaluated, which also limits the understanding of future changes in PBLH. Here by utilizing a multi-model ensemble of Coupled Model Intercomparison Project Phase 6 (CMIP6), we first thoroughly evaluate the capability of CMIP6 models in reproducing the spatial distribution of PBLH over China during the period of 1995–2014, revealing large discrepancies among the CMIP6 models. Meanwhile, inaccuracy of simulated meteorological parameters can lead to large deviations of PBLH in models, among which sensible heat flux (SHFLX) and near surface relative humidity (RH) show stronger modulation effects. To enhance the confidence of future projections, we apply a method by selecting the five models with the smallest biases and a high signal-to-noise ratio, and the results indicate that changes in PBLH under shared socioeconomic pathways exhibit a dipole pattern in both summer and winter. Specifically, PBLH is projected to decrease over North China and increase over Central China and South China in summer, while in winter PBLH tends to increase stronger in southern China and weaker in the northern flank. To reveal the mechanism governing the PBLH, we find that changes of PBLH is closely associated with surface energy. SHFLX and near surface RH are the dominant factors shaping the changes in the spatial heterogeneity of PBLH in the future. This study has important implications for the improvement of surface energy and PBLH in climate models in order to effectively predict the future changes of air pollutants.

Application of synoptic patterns to the definition of seasons in the Republic of Korea

AbstractIn this study, we applied the classification of synoptic patterns to define seasons. Principal component analysis (PCA) and k‐means clustering were employed to classify the synoptic patterns. In this analysis, seven synoptic patterns were classified, corresponding to two patterns exhibiting winter, spring, and autumn‐like patterns each and one representing summer‐like patterns. The climate characteristics of each synoptic pattern for summer, spring, and autumn were clearly different from each other. The two winter patterns were considered as one season. Seasons were defined based on the occurrence frequency of each synoptic pattern, using the 11‐day window size. Accordingly, the year was divided into first spring, second spring, summer, first autumn, second autumn, and winter. The onset dates of the corresponding seasons were March 8, April 15, June 6, September 8, October 23, and November 29, respectively. In the changing trend of the seasons calculated by year, the start date of first spring was earlier by approximately 2.0 days per decade, and second autumn was delayed by 1.7 days per decade. In addition, the length of first autumn increased by 2.9 days per decade, whereas the length of winter decreased by 3.3 days per decade. In this study, a new method that had not previously been applied in Korea was used to define seasons by considering various climate variables. Compared to previous studies, the seasonal definition method used in this study is objective and reflects comprehensive climate characteristics by considering diverse variables. Furthermore, the proposed methodology for defining the seasons for each year is applicable to the study of changes in seasonal onsets.

Ecosystem resilience to invasion and drought: Insights after 24 years in a rare never-grazed grassland.

Understanding the resilience of ecosystems globally is hampered by the complex and interacting drivers of change characteristic of the Anthropocene. This is true for drylands of the western US, where widespread alteration of disturbance regimes and spread of invasive non-native species occurred with westward expansion during the 1800s, including the introduction of domestic livestock and spread of Bromus tectorum, an invasive non-native annual grass. In addition, this region has experienced a multi-decadal drought not seen for at least 1200 years with potentially large and interacting impacts on native plant communities. Here, we present 24 years of twice-annual plant cover monitoring (1997-2021) from a semiarid grassland never grazed by domestic livestock but subject to a patchy invasion of B. tectorum beginning in ~1994, compare our findings to surveys done in 1967, and examine potential climate drivers of plant community changes. We found a significant warming trend in the study area, with more than 75% of study year temperatures being warmer than average (1966-2021). We observed a native perennial grass community with high resilience to climate forcings with cover values like those in 1967. In invaded patches, B. tectorum cover was greatest in the early years of this study (1997-2001; ~20%-40%) but was subsequently constrained by climate and subtle variation in soils, with limited evidence of long-term impacts to native vegetation, contradicting earlier studies. Our ability to predict year-to-year variation in functional group and species cover with climate metrics varied, with a 12-month integrated index and fall and winter patterns appearing most important. However, declines to near zero live cover in recent years in response to regional drought intensification leave questions regarding the resiliency of intact grasslands to ongoing aridification and whether the vegetation observations reported here may be a leading indicator of impending change in this protected ecosystem.