Seasonal Time Research Articles

Major Artifacts in ERA5 2‐m Air Temperature Trends Over Antarctica Prior to and During the Modern Satellite Era

AbstractGlobal reanalyzes are widely used for investigations of Antarctic climate variability and change. The European Centre for Medium‐Range Weather Forecasts 5th generation reanalysis (ERA5) is well regarded and spans 1940 to today. We investigate whether ERA5 reliably represents the 2‐m air temperature trends across the 1940–2022 (83 years) period at seasonal and annual time scales. We compare ERA5 temperatures with an observation‐based temperature reconstruction for Antarctica (RECON) that has monthly resolution for 1958–2022, the period of reliable observational availability. Results for individual stations are also examined. ERA5 anomalously warms Antarctica in relation RECON especially for the period prior to 1979 when satellite observations over the Southern Ocean were sparse. Trend hotspots that are shown to be artifacts are found at three locations and are present until today. The results demonstrate that ERA5 temperature trends can be questionable even today, but variability is well captured after 1979.

Strength and timing of austral winter Angolan coastal upwelling

The tropical Angolan upwelling system (tAUS) is a highly productive ecosystem of great socio-economic importance. Productivity peaks in austral winter and is linked to the passage of remotely forced upwelling coastal trapped waves (CTWs), where the strength of the productivity peak is associated with the amplitude of the upwelling CTW. Here, we analyze the year-to-year variability in the timing and amplitude of the austral winter upwelling CTW by examining sea surface temperature, sea level anomaly, and wind fields. Our results show that the timing of the CTW is influenced by variability in the equatorial region and along the southern African coast. Weaker equatorial easterlies from April to July delay the generation of the upwelling Kelvin wave, leading to a later arrival of the upwelling CTW. In contrast, the amplitude of the CTW is primarily influenced by variability in the eastern equatorial Atlantic and the central South Atlantic, where the South Atlantic Anticyclone is located. A cooling in the eastern equatorial Atlantic three to four months before the arrival of the CTW causes stronger zonal winds, ultimately leading to a stronger austral winter upwelling CTW. Our results suggest that the timing and amplitude of the upwelling CTW in the tAUS during austral winter are predictable on seasonal time scales.

Incidence and Risk Factors of Infection After Fracture Fixation: A Multicenter Cohort Study.

Infection after fracture fixation (IAFF) is a severe complication. There are few multicenter studies targeting IAFF. This paper identifies independent risk factors associated with IAFF by analyzing multicenter clinical data. Appropriate interventions should be implemented to reduce the risk of IAFF. This is a multicenter retrospective cohort study. This study screened medical records of patients who underwent internal fixation for fractures at participating medical institutions from January 1, 2011, to December 31, 2020. Data extraction included demographic characteristics, disease features, surgical variables, and laboratory indicators. Logistic regression analysis was employed to identify the relationship between relevant risk factors and IAFF. Research data were sourced from the hospital's electronic medical record system and self-constructed databases. In our study, 202 patients who underwent internal fixation for fractures experienced postoperative infections, which corresponds to an overall incidence rate of approximately 1.7%. The predominant pathogen identified in these infections was Staphylococcus aureus. A multifactorial analysis indicated that several factors were independently associated with the occurrence of IAFF. These factors included BMI ranges of 24.0-27.9 and 28.0-31.9, smoking, a high ASA score, high-energy trauma, diabetes, open fracture, seasonal timing of the surgery (summer), bone grafting, drainage duration, surgical duration ≥ 180 min, and A/G ratio < 1.2. We strongly recommend that orthopedic surgeons perform comprehensive preoperative assessments on fracture patients to identify factors that may increase the risk of infection. Through the implementation of targeted interventions and beneficial modifications to these modifiable risk factors, it is possible to lower the incidence of IAFF. Additionally, proactive screening, risk stratification, and thorough patient education should be prioritized for patients with high risk but nonmodifiable factors.

Seasonal and Local Time Variation in the Observed Peak of the Meteor Altitude Distributions by Meteor Radars

AbstractMeteoroids of sub‐milligram sizes burn up high in the Earth's atmosphere and cause streaks of plasma trails detectable by meteor radars. The altitude at which these trails, or meteors, form depends on a number of factors including atmospheric density and the astronomical source populations from which these meteoroids originate. A previous study has shown that the altitude of these meteors is affected by long‐term linear trends and the 11‐year solar cycle related to changes in our atmosphere. In this work, we examine how shorter diurnal and seasonal variations in the altitude distribution of meteors are dependent on the geographical location at which the measurements are performed. We use meteoroid altitude data from 18 independent meteor radar stations at a broad range of latitudes and investigate whether there are local time (LT) and seasonal variations in the altitude of the peak meteor height, defined as the majority detection altitude of all meteors within a certain period, which differ from those expected purely from the variation in the visibility of their astronomical source. We find a consistent LT and seasonal response for the Northern Hemisphere locations regardless of latitude. However, the Southern Hemisphere locations exhibit much greater LT and seasonal variation. In particular, we find a complex response in the four stations located within the Southern Andes region, which indicates that the strong dynamical atmospheric activity, such as the gravity waves prevalent here, disrupts, and masks the seasonality and dependence on the astronomical sources.

Shared environmental similarity between relatives influences heritability of reproductive timing in wild great tits.

Intraspecific variation is necessary for evolutionary change and population resilience, but the extent to which it contributes to either depends on the causes of this variation. Understanding the causes of individual variation in traits involved with reproductive timing is important in the face of environmental change, especially in systems where reproduction must coincide with seasonal resource availability. However, separating the genetic and environmental causes of variation is not straightforward, and there has been limited consideration of how small-scale environmental effects might lead to similarity between individuals that occupy similar environments, potentially biasing estimates of genetic heritability. In ecological systems, environments are often complex in spatial structure, and it may therefore be important to account for similarities in the environments experienced by individuals within a population beyond considering spatial distances alone. Here, we construct multi-matrix quantitative genetic animal models using over 11,000 breeding records (spanning 35 generations) of individually-marked great tits (Parus major) and information about breeding proximity and habitat characteristics to quantify the drivers of variability in two key seasonal reproductive timing traits. We show that the environment experienced by related individuals explains around a fifth of the variation seen in reproductive timing, and accounting for this leads to decreased estimates of heritability. Our results thus demonstrate that environmental sharing between relatives can strongly affect estimates of heritability and therefore alter our expectations of the evolutionary response to selection.

A probabilistic forecast for multi-year ENSO using Bayesian convolutional neural network

Abstract A robust El Niño Southern Oscillation (ENSO) prediction is essential for monitoring the global climate, regional monsoons, and weather extremes. Despite dedicated efforts spanning decades, the precise prediction of ENSO events through numerical modeling beyond a couple of seasonal lead times remains a daunting challenge. The advent of deep learning-based approaches marks a transformative era in climate and weather prediction. However, many machine learning-based studies attempting ENSO prediction are confined to singular estimates, lacking adequate quantification of uncertainty in learned parameters and overlooking the crucial need for a nuanced understanding of ENSO prediction confidence. Here, we introduce a deep learning-based Bayesian convolutional neural network model that provides robust probabilistic predictions for ENSO with a lead time of up to 9–10 months across all seasons. The Bayesian layers within the convolutional neural network maintain the capability to predict a distribution of learned parameters. Augmented with bias correction, our model reproduces the amplitude of the Niño 3.4 index with fidelity for lead up to 9–10 months. The inherent capacity for uncertainty modeling enhances the reliability of bayesian neural networks (BNNs), making them particularly valuable in operational services. This research holds substantial socio-economic implications as it enhances our forecasting capabilities and rigorously quantifies forecast uncertainties, providing valuable insights for planning and policymaking.

Climate‐associated variation in the within‐season dynamics of juvenile ticks in California

AbstractChanging climate has driven shifts in species phenology, influencing a range of ecological interactions from plant–pollinator to consumer–resource. Phenological changes in host–parasite systems have implications for pathogen transmission dynamics. The seasonal timing, or phenology, of peak larval and nymphal tick abundance is an important driver of tick‐borne pathogen prevalence through its effect on cohort‐to‐cohort transmission. Tick phenology is tightly linked to climatic factors such as temperature and humidity. Thus, variation in climate within and across regions could lead to differences in phenological patterns. These differences may explain regional variation in tick‐borne pathogen prevalence of the Lyme disease‐causing Borrelia bacteria in vector populations in the United States. For example, one factor thought to contribute to high Lyme disease prevalence in ticks in the eastern United States is the asynchronous phenology of ticks there, where potentially infected nymphal ticks emerge earlier in the season than uninfected larval ticks. This allows the infected nymphal ticks to transmit the pathogen to hosts that are subsequently fed upon by the next generation of larval ticks. In contrast, in the western United States where Lyme disease prevalence is generally much lower, tick phenology is thought to be more synchronous with uninfected larvae emerging slightly before, or at the same time as, potentially infected nymphs, reducing horizontal transmission potential. Sampling larval and nymphal ticks, and their host‐feeding phenology, both across large spatial gradients and through time, is challenging, which hampers attempts to conduct detailed studies of phenology to link it with pathogen prevalence. In this study, we demonstrate through intensive within‐season sampling that the relative abundance and seasonality of larval and nymphal ticks are highly variable along a latitudinal gradient and likely reflect the variable climate in the far western United States with potential consequences for pathogen transmission. We find that feeding patterns were variable and synchronous feeding of juvenile ticks on key blood meal hosts was associated with mean temperature. By characterizing within‐season phenological patterns of the Lyme disease vector throughout a climatically heterogeneous region, we can begin to identify areas with high potential for tick‐borne disease risk and underlying mechanisms at a finer scale.

Protection of the quiet and nocturnal landscape

Motives: We associate landscape primarily with the presence of vistas that change with the time of day, season and weather conditions. Landscape is shaped by light and darkness, sound and silence, all of which influence its perception. Quiet and nocturnal landscapes, however, remain on the margins of scientific interest in traditional landscape studies.Aim: The main aim of the study was to identify the younger generation’s awareness of the importance of nocturnal landscapes, light and noise pollution, and their preferences for protection against these threats. For this purpose, a diagnostic survey method was used. The results of the survey were referred to the 2015 TNS Poland report prepared for the Ministry of the Environment. In addition, the legal conditions of landscape protection in Poland were identified, with reference to protection against noise and light pollution. National and international experiences in the protection of quiet and nocturnal landscapes were also presented.Results: The survey demonstrated that public awareness of light pollution is increasing. A nocturnal (and quiet) landscape is of high value to the respondents. Light pollution causes, among other things, energy waste and landscape degradation (change of landscape characteristics), while noise negatively affects human and animal health. Therefore, the nocturnal (and quiet) landscape should be protected by law. Currently, there are no direct instruments for the protection of nocturnal landscapes in Poland. On the other hand, in the case of quiet landscapes, there are some instruments (e.g. quiet zones), but they have not been used yet. It is encouraging that public awareness of light and noise pollution is increasing. It is necessary to link landscape protection with the protection of the night sky and quiet zones, for example through advertising resolutions and the establishment of cultural parks. It is also important to educate the public about the risks involved.

Underestimation of meteorological drought intensity due to lengthening of the drought season with climate change

Abstract Meteorological drought may lead to water shortages, which has negative impacts on water-dependent sectors. Whilst there is a wealth of studies on changing drought intensity or frequency due to climate change, much less is known regarding potential shifts in the timing of drought. The purpose of this study is to analyse the timing of the drought season in the Netherlands and climatic changes therein, with a special focus on the onset of the drought season. Based on an analysis of meteorological observations in the Netherlands over the period 1965-2023, we conclude that the Dutch meteorological drought season has extended forward in time. On average, the drought season starts 16 days earlier in the period 1994-2023 compared to 1965-1993. This is mostly the result of an increase in potential evapotranspiration, while the amount of precipitation does not show a clear change at the start of the growing season. Using three climate model ensembles, we show that a forced climate change signal exists, but that natural variability also plays a role. Following this assessment of trends in meteorological variables, we analyse the consequences for the operational monitoring of meteorological drought. In the Netherlands, this is done by means of the `precipitation deficit’-indicator, based on a fixed-in-time starting point (1 April) of the drought season. The combination of this fixed starting point and the observed earlier onset of the drought season, means that in some years the indicator underestimates drought intensity, and that climatic trends are underestimated. We therefore advocate for an update of the operational drought indicator, such that meteorological drought occurring before 1 April will not be missed.

Different migration patterns of Wahlberg's eagles Hieraaetus wahlbergi across Africa

Intra‐Africa movements of most African migratory birds remain an enigma. We describe the migrations of Wahlberg's eagle Hieraaetus wahlbergi using GPS‐GSM transmitters on adult eagles in their South African (n = 3) and Kenyan (n = 7) breeding areas between 2018 and 2022. The dataset included 57 migratory tracks, 29 post‐breeding and 28 pre‐breeding. We found long‐distance migrants (LDMs; from South Africa) and short‐distance migrants (SDMs; from Kenya) using common non‐breeding areas centered in the Sudans and Central African Republic. The timing of annual phases was similar, but LDMs departed on their pre‐breeding migration on average later than SDMs (13 August versus 31 July) and arrived later on their breeding grounds (13 September versus 10 August). Conversely, the average departure date on the post‐breeding migration was 4 April for SDM and 23 March for LDMs. LDMs spent significantly less time of the year than SDMs on breeding grounds (44 versus 57%), and slightly but not significantly more time (40 versus 38%) on non‐breeding areas. The post‐breeding migration distance was on average 3413.9 ± 170.9 km for LDMs and 491.9 ± 158.5 km for SDMs. At non‐breeding areas, LDMs reached more northerly latitudes than SDMs, increasing the pre‐breeding migration distance to 4495.9 ± 372.5 km for LDMs versus 1701.9 ± 167.3 for SDMs. Daily flight distances back to the breeding areas averaged 153.4 ± 130.3 km for LDMs and 167.4 ± 122.3 km for SDMs and to non‐breeding areas were shorter for SDMs (124.8 ± 113.0 km) than LDMs (178.0 ± 134.4 km). Migration speed was similar across populations and for pre‐ and post‐breeding migrations. LDMs used more stopover days than SDMs. We conclude that Wahlberg's eagles from different parts of Africa have adapted their migration to differences in timing of the breeding season, distance of travel, and resources in the landscapes encountered during migration.

A review of climate change impacts on migration patterns of marine vertebrates in Arctic and Subarctic ecosystems

Climate change is impacting marine ecosystems throughout the circumpolar Arctic, altering seasonal habitats and the food bases for fishes, seabirds, and marine mammals. Arctic and Subarctic regions provide resources for resident species and for species that migrate to the north from more southerly regions. Changes in northerly latitudes thus impact endemic as well as non-endemic animals. Herein, we review what is known about climate-driven changes in the migration patterns of Arctic and Subarctic marine vertebrates, including: 1) Arctic residents with seasonal movements – those fishes, seabirds, and marine mammals that complete their entire life cycle within the Arctic but exhibit seasonal movements; 2) Breeding migrants – many seabirds enter the Arctic to breed and subsequently migrate south in the fall; and 3) Summer visitors for feeding – certain species of boreal fishes, seabirds and marine mammals arrive during the northern summer to feed on abundant prey though they breed elsewhere. Migratory movements are often driven by the timing and extent of sea ice, which defines suitable habitat for some animals and limits access to open water and prey for others. Longer open-water seasons, warmer ocean temperatures, and stronger winds have resulted in earlier production blooms in spring and often, extended open-ocean plankton blooms into late summer, resulting in altered prey types and distributions. A common thread among taxa is that shifts in distribution and timing of migrating animals indicate they are traveling farther north, or shifting longitudinally, and migrations are occurring over longer seasonal time frames. Species performing multiple lifetime migrations or long-distance migrants may need to adjust migration timing or routing iteratively to match changes in marine productivity. Altered animal distributions or phenology, and reduced sea ice, affects access to animals that are critical nutritional, economical, and cultural components of Indigenous people’s lives in the Arctic. Ongoing changes challenge the resilience and adaptability of Arctic people and ecosystems, and will require adaptive research and management approaches.

HOLT WINTERS EXPONENTIAL SMOOTHING UNTUK MERAMALKAN PRODUK DOMESTIK BRUTO DI INDONESIA

A country's economic growth will be seen as having grown better or worse than in the past by measuring based on the increase in Gross Domestic Product (GDP). The pattern of Indonesian GDP from 2010 to 2022 shows that the data increases from year to year and there are seasonal fluctuations in the quarter. Holt Winters method is part of the Exponential Smoothing method used for forecasting if the data shows a trend and seasonality in the data pattern. The Holt Winters method has two models, namely additive and multiplicative. Holt Winters Additive is used if the data shows trends and seasonal patterns remain constant. Multiplicative Holt Winter is used if the data shows trends and seasonal patterns proportional to the average rate of the seasonal time series. The data used in this study are GDP Based on Current Prices (Nominal GDP) and GDP on the Basis of Constant Prices (Real GDP). Based on the evaluation of model performance using test data forecasting, the Holt Winters Multiplicative model of Nominal GDP with a MAPE value of 4,767535% is the best model because it has an accuracy value of &lt;10%. While the Holt Winters Additive model of Real GDP with a MAPE value of 4,42387% is also the best model because it has an accuracy value of &lt;10%.

Prolonged dry seasons lengthen coccidioidomycosis transmission seasons: implications for a changing California.

Coccidioidomycosis, a fungal disease caused by soil-borne Coccidioides spp., exhibits pronounced seasonal transmission, with incidence in California typically peaking in the fall. However, the influence of climate on the timing and duration of transmission seasons remains poorly understood. Using weekly data on reported coccidioidomycosis cases in California from 2000-2023, we developed a distributed-lag Markov state-transition model to estimate the effects of temperature and precipitation on the timing of transmission season onset and end. We found that transitions from cooler, wetter conditions to hotter, drier conditions accelerate season onset. Dry conditions (10 th percentile of precipitation) in the spring shifted season onset an average of 2.8 weeks (95% CI: 0.43-3.58) earlier compared to wet conditions (90 th percentile of precipitation). Conversely, transitions back to cooler, wetter conditions hastened season end, with dry fall conditions extending the season by an average of 0.69 weeks (95% CI: 0.37-1.41) compared to wet conditions. When dry conditions occurred in the spring and fall, the transmission season extended by 3.70 weeks (95% CI: 1.23-4.22). As California is expected to experience prolonged dry seasons with climate change, our findings suggest this shift may lengthen the time at which populations are at elevated coccidioidomycosis risk.

Insect responses to seasonal time constraints under global change are facilitated by warming and counteracted by invasive alien predators.

In seasonal environments, organisms with complex life cycles not only contend with seasonal time constraints (TC) but also increasingly face global change stressors that may interfere with responses to TC. Here, we tested how warming and predator stress imposed during the egg and larval stages shaped life history and behavioural responses to TC in the temperate damselfly Ischnura elegans. Eggs from early and late clutches in the season were subjected to ambient and 4°C warming temperature and the presence or absence of predator cues from perch and signal crayfish. After hatching, larvae were retained at the same thermal regime, and the predator treatment was continued or not up to emergence. The late eggs decreased their development time, especially under warming and when not exposed to predator cues. However, the late eggs increased their development time when exposed to predator cues, especially to crayfish cues. The TC decreased survival of late larvae that were as eggs exposed to crayfish cues, indicating a carry-over effect. The TC and warming additively reduced late larvae development time to emergence. Independent of the TC, predator cue effects on development time were stronger during the egg than during the larval stage. The late individuals expressed lower mass at emergence, which mirrored the size difference between field-collected mothers. Warming caused a higher mass at emergence. The late individuals increased their boldness and showed a higher number of moves, whereas warming caused a decreased boldness. There was no predator cue effect on larval behaviour. The results indicate that late individuals compensate for late season egg laying, which is facilitated under warming but counteracted under predation risk, especially when imposed by the crayfish.

Statistical seasonal prediction of Arctic sea ice concentration based on spatiotemporal anomaly persistent method

Abstract Accurate prediction of Arctic sea ice is crucial for high-latitude and even mid-latitude climate prediction. It significantly affects atmospheric circulation, the environment, ecology, and maritime transport. This study developed a statistical prediction model to predict monthly Arctic sea ice concentration (SIC) for up to one year based on the season-reliant empirical orthogonal functions (SEOFs) technique. Its prediction skill was compared with that of a dynamical prediction model. The spatiotemporal pattern of sea ice anomalies, which exhibit strong seasonality and are maintained for a significant period above the seasonal time scale by atmosphere-ocean interactions, was extracted using SEOFs. A prediction model was constructed by extrapolating from the recent anomalous state of sea ice to predict the future. Experimental retrospective predictions with monthly time resolution for 1982–2021 were performed to validate the prediction skill of Arctic SIC and areal extent. Statistically significant prediction skills were achieved over several months, even up to six months, exceeding the skill of the dynamical model.

Factors determining semen sample collection and semen quality parameters in African penguins Spheniscus demersus

Our research focuses on semen collection from 42 African penguin males, grouped by age, habituation levels, and reproductive season timing. We assess behavioral and physiological responses to dorso-abdominal massage, evaluating species-specific seminal traits using conventional and advanced methods. Positive behavioral responses corresponded with successful semen collection. Young and human-reared males exhibited more favorable behaviors, and samples containing spermatozoa were more likely collected during the reproductive season. Age did not influence sample collectability or spermatozoa presence, though mature males produced higher semen volumes. Young males exhibited more sperm morphological abnormalities, especially outside the breeding season. Sperm concentration and number per ejaculate showed no significant differences across age or seasonal groups. Young males had higher motile and progressive sperm percentages, while mature males had more static sperm. Additionally, percentages of live sperm and intact acrosomes were higher in mature males. Young males and samples from non-reproductive season presented more dead sperm with damaged acrosomes. Plasma membrane integrity positively correlated with age for live sperm and negatively for dying sperm. This research demonstrates the feasibility of semen collection from African penguins regardless of habituation level, fills the knowledge gap by describing sperm morphological abnormalities, and provides insights into using flow cytometry in Sphenisciformes.

Chronic oral toxicity protocol for adult solitary bees (Osmia bicornis L.): Reduced survival under long-term exposure to a “bee-safe” insecticide

Pollinators are essential for crop productivity. Yet, in agricultural areas, they may be threatened by pesticide exposure. Current pesticide risk assessments predominantly focus on honey bees, with a lack of standardized protocols for solitary bees. This study addresses this gap by developing a long-term oral exposure protocol tailored for O. bicornis. We conducted initial trials to determine optimal container sizes and feeding methods, ensuring high survival rates and accurate syrup consumption measurements. A validation test involving five laboratories was then conducted with the insecticide Flupyradifurone (FPF). Control mortality thresholds were set at ≤ 15% at 10 days. Three laboratories achieved ≤10%, demonstrating the protocol's effectiveness in maintaining healthy test populations. The seasonal timing of experiments influenced control mortality, underscoring the importance of aligning tests with the natural flight period of the population used. Our findings revealed dose-dependent effects of FPF on syrup consumption, showing stimulatory effects at lower concentrations and inhibitory effects at higher ones. The 10-day median lethal daily dose (LDD50) of FPF for O. bicornis (531.92 ng/bee/day) was 3.4-fold lower than that reported for Apis mellifera (1830 ng/bee/day), indicating Osmia's higher susceptibility. Unlike other insecticides, FPF did not exhibit time-reinforced toxicity. This study introduces a robust protocol for chronic pesticide exposure in solitary bees, addressing a critical gap in current risk assessment. Based on its low risk to honey bees and bumblebees, FPF is approved for application during flowering. However, our results suggest that it may threaten Osmia populations under realistic field conditions. Our findings underscore the need for comparative toxicity studies to ensure comprehensive protection of all pollinators and the importance of accounting for long term exposure scenarios in risk assessment. By enhancing our understanding of chronic pesticide effects in solitary bees, our study should contribute to the development of more effective conservation strategies and sustainable agricultural practices.

Atmospheric Precursors of Skillful SST Prediction in the Northeast Pacific

Abstract Forecasts of sea surface temperature anomalies (SSTAs) provide essential information to stakeholders of marine resources in coastal ecosystems, such as the California Current Large Marine Ecosystem (CCLME), at management-relevant monthly-to-annual time scales. Diagnosing dynamical sources of predictability and the mechanisms differentiating skill among forecasts is required for verification and improvement in operational forecasting systems. Using retrospective forecasts (1982–2020) from a four-member subset of the North American Multi-Model Ensemble (NMME), we evaluate the conditional skill of SSTA forecasts in the CCLME at monthly resolution for lead times up to 10.5 months. Forecasts from ensemble members with relatively small SSTA errors at shorter lead times retain higher skill at longer lead times, with the most substantial and long-lasting increases for forecasts initialized in the fall and early spring. The “best” low-error SSTA forecasts are characterized by increased skill in the prediction of North Pacific atmospheric circulation [sea level pressure (SLP) and 200-hPa geopotential height] the month prior to the evaluation of SSTA errors in the CCLME and exhibit more realistic progressions of anomalous SLP. The Pacific meridional mode (PMM) emerges as a diagnostic of skillful North Pacific atmosphere–ocean coupling, as forecasts that correctly simulate the PMM and its associated SLP variability increase the SSTA prediction skill in the CCLME in the fall through spring. Predictable coupled ocean–atmosphere modes provide a target for enhancing predictability with early detection of the onset of a deterministic progression emerging from stochastic atmospheric variability. Significance Statement Global forecast systems provide near-term climate predictions that inform the management of marine resources, such as those of the California Current Large Marine Ecosystem. In this study, we probe the processes which lead forecasts to succeed or fail at predicting sea surface temperatures in the California Current at seasonal time scales among retrospective forecasts from the North American Multimodel Ensemble. We demonstrate that forecasts which best simulate sea surface temperatures at the earliest lead times sustain advantages in forecast skill and find that correctly simulating extratropical atmospheric circulation increases the predictive skill of sea surface temperatures in the northeast Pacific in the following lead times. Our results offer North Pacific atmospheric circulation as a target for forecast model improvement that would additionally enhance ocean forecasts.

Locally defined seasonal rainfall characteristics within the Horn of Africa drylands from rain gauge observations

Abstract Seasonal rainfall is critical to lives and livelihoods within the Horn of Africa drylands (HAD), but it is highly variable in space and time. The HAD rainfall seasons are typically defined as March-April-May (MAM) and October-November-December (OND). However, these three-month periods are only generalised definitions of seasonality across the HAD, and local experience of rainfall may depart from these substantially. Here, we use daily rain gauge data with a duration of at least 10 years from 69 stations across Kenya, Somalia, and Ethiopia to locally delineate key rainfall seasons. By calculating local seasonal rainfall timings, totals, and extremes we obtain more accurate estimates of the spatial variability in rainfall delivery across the HAD, as well as climatological patterns. Results show high spatial variability in season onset, cessation, and length across the region, indicating that a homogenous classification of rainfall seasons across the HAD (e.g. MAM and OND) is inadequate for representing local rainfall characteristics. Our results show that the ‘long rains’ season is not significantly longer than ‘short rains’ season over the period of study. This could be related to the previously documented decline of the ‘long rains’ rainfall totals over recent decades. Several rainfall metrics also vary spatially between seasons, and the rainfall on the most extreme days can accumulate to double the mean seasonal total. The locally defined rainfall seasons better capture the bulk of the rainfall during the season, giving improved characterisation of rainfall metrics, consistent with the aim of a better understanding of rainfall impacts on local communities.

Sex-specific expression of circadian rhythms enables allochronic speciation

Abstract Noctuid moths provide prime examples of species in various stages of allochronic speciation, where reproductive barriers are mediated by genetic divergence in daily or seasonal timing. Theory indicates that allochronic divergence might be one of the most plausible mechanisms of adaptive speciation, especially when timing is subject to divergent ecological selection. Here, we show that the validity of this theoretical expectation is entirely contingent on species characteristics of the mating system. Our analysis focuses on the moth Spodoptera frugiperda (Lepidoptera, Noctuidae), which occurs as two strains that differ in circadian reproductive activity. Unlike in generic models of assortative mating, where chronotypes diverge under mild assumptions, individual-based evolutionary simulations of the mating system and life cycle of S. frugiperda fail to recover allochronic diversification, even under conditions highly conducive to speciation. Instead, we observe that both chronotypes advance their activity schedule toward the early night, resulting in a rapid loss of allochronic variation. This outcome is caused by the fact that mating in S. frugiperda takes considerable time and potential mates are encountered sequentially, so that early males enjoy a systematic advantage. The undermining effect of male mate competition can be overcome when circadian genes evolve sex-specific expression, enabling early and late chronotypes to be maintained or even to diversify in sympatry. These results give new significance to sex differences in biological rhythms and suggest that species characteristics of the mating system and genetic architecture are key to understanding the scope for allochronic speciation across diverse species exhibiting variation in timing.