Winter Clusters Research Articles

Added value of seasonal hindcasts to create UK hydrological drought storylines

Abstract. The UK has experienced recurring periods of hydrological droughts in the past, including the drought declared in summer 2022. Seasonal hindcasts, consisting of a large sample of plausible weather sequences, can be used to create drought storylines and add value to existing approaches to water resources planning. In this study, the drivers of winter rainfall in the Anglian region in England are investigated using the ECMWF SEAS5 hindcast dataset, which includes 2850 plausible winters across 25 ensemble members and 3 lead times. Four winter clusters are defined using the hindcast winters based on possible combinations of various atmospheric circulation indices (such as the North Atlantic Oscillation, NAO; East Atlantic, EA, pattern; and El Niño–Southern Oscillation). Using the 2022 drought as a case study, we demonstrate how storylines representing alternative ways the event could have unfolded can be used to explore plausible worst-case scenarios over winter 2022/23 and beyond. The winter clusters span a range of temperature and rainfall response in the study region and represent circulation storylines that could have happened over winter 2022/23. River flow and groundwater level simulations with the large sample of plausible hindcast winters show that drier-than-average winters characterised by predominantly NAO−/EA− and NAO+/EA− circulation patterns could have resulted in the continuation of the drought with a high likelihood of below-normal to low river flows across all selected catchments and boreholes by spring and summer 2023. Catchments in Norfolk were particularly vulnerable to a dry summer in 2023 as river flows were not estimated to recover to normal levels even with wet winters characterised predominantly by NAO−/EA+ and NAO+/EA+ circulation patterns, due to insufficient rainfall to overcome previous dry conditions and the slow response nature of groundwater-dominated catchments. Through this analysis, we aim to demonstrate the added value of this approach to create drought storylines during an ongoing event. Storylines constructed in this way supplement traditional weather forecasts and hydrological outlooks, in order to explore a wider range of plausible outcomes.

Influence of short and long term processes on SAR11 communities in open ocean and coastal systems

SAR11 bacteria dominate the surface ocean and are major players in converting fixed carbon back to atmospheric carbon dioxide. The SAR11 clade is comprised of niche-specialized ecotypes that display distinctive spatiotemporal transitions. We analyzed SAR11 ecotype seasonality in two long-term 16S rRNA amplicon time series representing different North Atlantic regimes: the Sargasso Sea (subtropical ocean-gyre; BATS) and the temperate coastal Western English Channel (WEC). Using phylogenetically resolved amplicon sequence variants (ASVs), we evaluated seasonal environmental constraints on SAR11 ecotype periodicity. Despite large differences in temperature and nutrient availability between the two sites, at both SAR11 succession was defined by summer and winter clusters of ASVs. The summer cluster was dominated by ecotype Ia.3 in both sites. Winter clusters were dominated by ecotypes Ib and IIa.A at BATS and Ia.1 and IIa.B at WEC. A 2-year weekly analysis within the WEC time series showed that the response of SAR11 communities to short-term environmental fluctuations was variable. In 2016, community shifts were abrupt and synchronized to environmental shifts. However, in 2015, changes were gradual and decoupled from environmental fluctuations, likely due to increased mixing from strong winds. We demonstrate that interannual weather variability disturb the pace of SAR11 seasonal progression.

Impact of the ice thickness distribution discretization on the sea ice concentration variability in the NEMO3.6–LIM3 global ocean–sea ice model

Abstract. This study assesses the impact of different sea ice thickness distribution (ITD) discretizations on the sea ice concentration (SIC) variability in ocean stand-alone NEMO3.6–LIM3 simulations. Three ITD discretizations with different numbers of sea ice thickness categories and boundaries are evaluated against three different satellite products (hereafter referred to as “data”). Typical model and data interannual SIC variability is characterized by K-means clustering both in the Arctic and Antarctica between 1979 and 2014. We focus on two seasons, winter (January–March) and summer (August–October), in which correlation coefficients across clusters in individual months are largest. In the Arctic, clusters are computed before and after detrending the series with a second-degree polynomial to separate interannual from longer-term variability. The analysis shows that, before detrending, winter clusters reflect the SIC response to large-scale atmospheric variability at both poles, while summer clusters capture the negative and positive trends in Arctic and Antarctic SIC, respectively. After detrending, Arctic clusters reflect the SIC response to interannual atmospheric variability predominantly. The cluster analysis is complemented with a model–data comparison of the sea ice extent and SIC anomaly patterns. The single-category discretization shows the worst model–data agreement in the Arctic summer before detrending, related to a misrepresentation of the long-term melting trend. Similarly, increasing the number of thin categories reduces model–data agreement in the Arctic, due to a poor representation of the summer melting trend and an overly large winter sea ice volume associated with a net increase in basal ice growth. In contrast, more thin categories improve model realism in Antarctica, and more thick ones improve it in central Arctic regions with very thick ice. In all the analyses we nonetheless identify no optimal discretization. Our results thus suggest that no clear benefit in the representation of SIC variability is obtained from increasing the number of sea ice thickness categories beyond the current standard with five categories in NEMO3.6–LIM3.

Breeding origins and migratory connectivity at a northern roost of Vaux’s Swift, a declining aerial insectivore

ABSTRACT Populations of Vaux’s Swift (Chaetura vauxi), like those of many aerial insectivores, are rapidly declining. Determining when and where populations are limited across the annual cycle is important for their conservation. Establishing the linkages between wintering and breeding sites and the strength of the connections between them is a necessary first step. In this study, we analyzed 3 stable isotopes (δ13C, δ15N, δ2H) from feathers collected during spring migration from Vaux’s Swifts that perished during a stopover on Vancouver Island, British Columbia, Canada. We previously analyzed claw tissue (grown during winter) from the same individuals, revealing that the swifts likely wintered in 2 or 3 locations/habitats. Here, we used stable isotope analysis of flight feathers presumed to have been grown on, or near, the breeding grounds to determine the likely previous breeding locations and presumed destinations for the swifts. Stable isotope values (δ13C, δ15N, δ2H) showed no meaningful variation between age classes, sexes, or with body size. Surprisingly, ~26% of the birds sampled had feather isotope values that were not consistent with growth on their breeding grounds. For the remaining birds, assigned breeding origins appeared most consistent with molt origins on Vancouver Island. Overall, migratory connectivity of this population was relatively weak (rM = 0.07). However, the degree of connectivity depended on how many winter clusters were analyzed; the 2-cluster solution suggested no significant connectivity, but the 3-cluster solution suggested weak connectivity. It is still unclear whether low migratory connectivity observed for Vaux’s Swift and other aerial insectivores may make their populations more or less vulnerable to habitat loss; therefore, further efforts should be directed to assessing whether aerial insectivores may be habitat limited throughout the annual cycle.

Structure and Long-Term Fluctuations in the Wintering Mallard (Anas platyrhynchos, Anseriformes, Anatidae) Population in the City of Moscow

Abstract—The structure of and long-term fluctuations in the wintering mallard (Anas platyrhynchos) population were studied from 1985 to 2016 in the city of Moscow. The number of wintering mallards was counted annually on the same day at all ice-free ponds and rivers of Moscow. The total winter population of mallards increased 1.6–3.3 times compared to the summer one. The growth of the wintering group continued from 1985 (17 200) to 1990 (27 900). From 1991 to 1998 its size decreased to 7500, remained low until 2002–2003, after which it began to grow up to 29 700 in 2015. The freezing season has decreased from 132 to 104.5 days (Z = 3.8, p = 0.0001, n = 32) during the study period. At the same time, the average air temperatures of November and December have increased significantly. Mallards gather at the southeastern urban section of the Moscow River exclusively in the cold season. There is no correlation between mallard numbers and interurban winter clusters. This gave grounds to divide the total bird numbers conditionally into the riverine and interurban groups, which were analyzed separately. The size of the interurban group correlates with the duration of the freezing season (r = –0.47, p = 0.006, n = 32), while that of the riverine group correlates with the average (r = 0.41, p = 0.02, n = 32) and minimum (r = 0.54, p = 0.001, n = 32) winter temperatures. The proportion of mallards that wintered in the Moscow Zoo changed in the opposite direction compared to the size of the interurban group (r = –0.83, p < 0.01, n = 32). The numbers of mallards wintering at internal water bodies correlates with the purchasing power (r = 0.44, p = 0.012, n = 31) and welfare of citizens from 1985 until 2015. The more rapid growth in the size of the wintering interurban group compared to the riverine group indicates the advantages of living in urban conditions. These are the lack of permanent human persecution, additional food sources, and a milder climate.

Sepsis and Hemocyte Loss in Honey Bees (Apis mellifera) Infected with Serratia marcescens Strain Sicaria.

Global loss of honey bee colonies is threatening the human food supply. Diverse pathogens reduce honey bee hardiness needed to sustain colonies, especially in winter. We isolated a free-living Gram negative bacillus from hemolymph of worker honey bees (Apis mellifera) found separated from winter clusters. In some hives, greater than 90% of the dying bees detached from the winter cluster were found to contain this bacterium in their hemolymph. Throughout the year, the same organism was rarely found in bees engaged in normal hive activities, but was detected in about half of Varroa destructor mites obtained from colonies that housed the septic bees. Flow cytometry of hemolymph from septic bees showed a significant reduction of plasmatocytes and other types of hemocytes. Interpretation of the16S rRNA sequence of the bacterium indicated that it belongs to the Serratia genus of Gram-negative Gammaproteobacteria, which has not previously been implicated as a pathogen of adult honey bees. Complete genome sequence analysis of the bacterium supported its classification as a novel strain of Serratia marcescens, which was designated as S. marcescens strain sicaria (Ss1). When compared with other strains of S. marcescens, Ss1 demonstrated several phenotypic and genetic differences, including 65 genes not previously found in other Serratia genomes. Some of the unique genes we identified in Ss1 were related to those from bacterial insect pathogens and commensals. Recovery of this organism extends a complex pathosphere of agents which may contribute to failure of honey bee colonies.

Wintering of honey bee colonies in cylindrical nest cavities versus oblong box-hives in a North European climate

We compared the efficacy of wintering honey bee colonies in wooden cylinders and wooden oblong box hives. Five colonies in “cylinders” and three colonies in “box-hives” were compared over two winters. The cylinders were 450 mm high with an internal diameter of 280 mm. The oblong box hives were Estonian standard one-box long hives with a frame size of 414 × 277 mm. Eight vertical rows of thermistors were fixed along the inner walls of both cylinders and hives and temperatures were measured at about weekly intervals. Food consumption and bee mortality of colonies were also assessed. In the cylinders, the winter clusters remained close to their front walls and away from the back wall, especially in cold weather. It was considerably warmer by the inner walls of the cylinders than in the hives, especially in the lower part. The surface of warm area decreased with cold weather and increased at around 0 °C indicating contraction and expansion of the cluster, respectively. In the second half of winter, there was a larger warm area in the cylinders than in the hives indicating that the clusters touched the walls of the cylinder more, thereby reducing heat losses further. Considerably, less food (13.5%) was consumed in the cylinders than in the hives. The numbers of dead bees on the floor was significantly lower in the cylinders than in the hives, but total bee mortality (dead bees on the floor + bees flown out in winter) differed little between cylinders and hives.

Hibernation alters the diversity and composition of mucosa-associated bacteria while enhancing antimicrobial defence in the gut of 13-lined ground squirrels.

The gut microbiota plays important roles in animal nutrition and health. This relationship is particularly dynamic in hibernating mammals where fasting drives the gut community to rely on host-derived nutrients instead of exogenous substrates. We used 16S rRNA pyrosequencing and caecal tissue protein analysis to investigate the effects of hibernation on the mucosa-associated bacterial microbiota and host responses in 13-lined ground squirrels. The mucosal microbiota was less diverse in winter hibernators than in actively feeding spring and summer squirrels. UniFrac analysis revealed distinct summer and late winter microbiota clusters, while spring and early winter clusters overlapped slightly, consistent with their transitional structures. Communities in all seasons were dominated by Firmicutes and Bacteroidetes, with lesser contributions from Proteobacteria, Verrucomicrobia, Tenericutes and Actinobacteria. Hibernators had lower relative abundances of Firmicutes, which include genera that prefer plant polysaccharides, and higher abundances of Bacteroidetes and Verrucomicrobia, some of which can survive solely on host-derived mucins. A core mucosal assemblage of nine operational taxonomic units shared among all individuals was identified with an average total sequence abundance of 60.2%. This core community, together with moderate shifts in specific taxa, indicates that the mucosal microbiota remains relatively stable over the annual cycle yet responds to substrate changes while potentially serving as a pool for 'seeding' the microbiota once exogenous substrates return in spring. Relative to summer, hibernation reduced caecal crypt length and increased MUC2 expression in early winter and spring. Hibernation also decreased caecal TLR4 and increased TLR5 expression, suggesting a protective response that minimizes inflammation.

A six‐step approach to developing future synoptic classifications based on GCM output

AbstractOne way in which global climate model (GCM) output can be utilized to infer local impacts is through the use of synoptic climatology: creating a set of atmospheric patterns that capture the variability in the climate system, and then analyzing trends and variability in the frequency of these patterns moving into the future. In this paper, we demonstrate a new synoptic climatological technique for classifying atmospheric patterns that can be used in conjunction with GCM output data (in this case, the Community Climate System Model 3). We apply this method to 850‐hPa temperature patterns over the contiguous United States to derive daily categorizations. A total of 15 clusters are created from the data set; once the mean GCM bias is removed, historical cluster frequencies in the GCM data set are not statistically different from those of the reanalysis data set. In the future, significant changes in frequency are observed across most of the transition season clusters, as they broaden in seasonality at the expense of winter clusters, some of which nearly entirely disappear. Changes are greater moving further into the future, and greater for the more carbon‐intensive special report on emissions scenarios (SRES) scenarios (A1FI, A2) than the less‐intensive scenario tested (B1). Diagnostics test how well the mean patterns of the reanalysis data set, GCM historical data set and the future GCM data sets resemble each other. For some clusters, mean bias between the historical and future data sets grows substantially by the end of the 21st century under the more carbon‐intensive scenarios. Copyright © 2011 Royal Meteorological Society

Concurrent Parasitism Alters Thermoregulation in Honey Bee (Hymenoptera: Apidae) Winter Clusters

Abstract Thermoregulation is crucial for honey bee, Apis mellifera L. (Hymenoptera: Apidae), colony survival in temperate regions, but possible interference by parasites is currently unknown. The small hive beetle, Aethina tumida Murray (Coleoptera: Nitidulidae), and the ectoparasitic mite Varroa destructor Anderson &amp; Trueman are honey bee parasites and both overwinter in host colonies. The efficiency of thermoregulation might thus be affected in infested host winter clusters, due to altered worker activity. Here, we show for the first time that parasites can alter honey bee thermoregulation. Moreover, the data suggest that only combined infestations with V. destructor and A. tumida result in higher thermal maxima in the winter clusters, whereas infestations with one parasite alone had no significant effect compared with the controls. Due to the ubiquitous mite V. destructor combined infestations with parasites or combined infections with pathogens are almost inevitable. Therefore, our data indicate that an altered thermoregulation due to multiple infestations might be another widespread factor contributing to winter losses of honey bee colonies.

Mathematical modeling of the temperature field distribution in insect winter clusters

A model is proposed for the distribution of temperature fields and mechanisms of thermoregulation in an insect (honeybee) cluster self-organizing for protection against long-term cooling. The winter cluster is an ordered system of heat generation, accumulation, and dissipation. Estimates are obtained for the influence of ambient temperature that promotes clustering and of the number of clustered insects on the efficiency of cold protection. Described are the dynamic links between the cluster structures that ensure minimal energy expenditures in metabolism and thermoregulation; this allows the cluster to withstand the long unfavorable exposure to temperature varying far beyond the limits of viability for an individual insect.

A qualitative model of mortality in honey bee (Apis mellifera) colonies infested with tracheal mites (Acarapis woodi)

The tracheal mite has been associated with colony deaths worldwide since the mite was first discovered in 1919. Yet controversy about its role in honey bee colony mortality has existed since that time. Other pathogens such as bacteria and viruses have been suggested as the cause of colony deaths as well as degenerative changes in individual honey bees. Using data from published work we developed a qualitative mortality model to explain colony mortality due to tracheal mite infestation in the field. Our model suggests that colonies of tracheal-mite infested honey bees, with no other pathogens present, can die out in the late winter/early spring period due to their inability to thermoregulate. An accumulation of factors conspire to cause colony death including reduced brood/bee population, loose winter clusters, reduced flight muscle function and increasing mite infestation. In essence a cascade effect results in the colony losing its cohesion and leading to its ultimate collapse.

Endothermic heat production in honeybee winter clusters.

In order to survive cold northern winters, honeybees crowd tightly together in a winter cluster. Present models of winter cluster thermoregulation consider the insulation by the tightly packed mantle bees as the decisive factor for survival at low temperatures, mostly ignoring the possibility of endothermic heat production. We provide here direct evidence of endothermic heat production by 'shivering' thermogenesis. The abundance of endothermic bees is highest in the core and decreases towards the surface. This shows that core bees play an active role in thermal control of winter clusters. We conclude that regulation of both the insulation by the mantle bees and endothermic heat production by the inner bees is necessary to achieve thermal stability in a winter cluster.

Transport in the Low-Latitude Tropopause Zone Diagnosed Using Particle Trajectories

Abstract Recent literature has described a “transition zone” between the average top of deep convection in the Tropics and the stratosphere. Here transport across this zone is investigated using an offline trajectory model. Particles were advected by the resolved winds from the European Centre for Medium-Range Weather Forecasts reanalyses. For each boreal winter clusters of particles were released in the upper troposphere over the four main regions of tropical deep convection (Indonesia, central Pacific, South America, and Africa). Most particles remain in the troposphere, descending on average for every cluster. The horizontal components of 5-day trajectories are strongly influenced by the El Nino–Southern Oscillation (ENSO), but the Lagrangian average descent does not have a clear ENSO signature. Tropopause crossing locations are first identified by recording events when trajectories from the same release regions cross the World Meteorological Organization lapse rate tropopause. Most crossing events occ...

An assessment of air quality variations in the south‐western USA using an upper air synoptic climatology

AbstractDaily particulate concentrations in the Desert South‐west from 1984 to 1988 are analysed using a synoptic climatology based upon tropospheric thermal, moisture, and flow conditions. Using a combination of principal components analysis and cluster analysis, 13 distinct synoptic types (clusters) are identified that correspond to seasonal variations in the atmosphere's general circulation. These include summer clusters, which reflect monsoonal and non‐monsoonal conditions, winter clusters defined by the positions of the polar and subtropical jets and shortwave ridges and troughs, and clusters that predominate in the transition seasons.Particulate concentrations vary significantly by synoptic type. Three clusters have poor air quality. ‘Summer monsoon’ days have high humidity and cloud cover, conditions that encourage aerosol growth. ‘Continental high’ days have a slow‐moving anticyclone centred over the Great Basin that traps particulates within the boundary layer. ‘Rockies ridge’ days are associated with strong south‐westerly flow and the advection of regional haze from southern California into the Desert South‐west. In all of these clusters, high humidity or cloud cover enhance particulate growth. Good air quality in the summer occurs on monsoonal ‘break’ days when relative humidity and cloud cover decrease. In the winter, good air quality occurs when Arctic or continental polar air masses are present, or when either the polar or subtropical jets are strong and positioned over the South‐west. In some of these latter situations, widespread precipitation removes particulates through wet deposition.These results suggest that the Navajo Generating Station (NGS), a large coal‐fired power plant on the Arizona‐Utah border, does not contribute significantly to air quality degradation in the Grand Canyon National Park, Arizona. Most of the days with high particulate levels are associated with transport from southern California or unstable summer days with high humidity and contributions from many point and regional sources. There may be some contribution from the NGS on ‘continental high’ days, but when this cluster occurs on consecutive days, air quality improves rather than declines. This research provides a useful framework for future mesoscale modelling studies of air quality in south‐western USA.

A model for heat production and thermoregulation in winter clusters of honey bees using differential heat conduction equations

A model is proposed for heat production and thermoregulation in the winter cluster of the honey bee Apis mellifera. It describes heat production within the cluster by an exponential decrease from the periphery to the centre, and takes into account threshold values for the central and the peripheral temperatures as well as changing diameters of the cluster. The results agree well with experimental data.

Thermoregulation in the winter cluster of the honeybee, Apis Mellifera

A model is presented based on the assumption that the apparently coordinated thermoregulatory responses of the broodless winter cluster of the honeybee, Apis mellifera , are results of the individuals acting behaviourally and physiologically to regulate their own body temperature. The predictive potential of the model is elucidated by a set of mathematically formulated relationships. The results include predictions concerning radial distributions of metabolic rate, and temperature profiles, as a function of ambient temperature. Furthermore, the apparently equal mass specific metabolic rate observed from weak and strong winter clusters is shown to be consistent with the proposed model. Consideration is also given to the generally accepted view of how the thermoregulation is accomplished, which is shown to give very unrealistic predictions.