Length Of Season Research Articles

Quantifying phenotypic and genetic variation for cow fertility phenotypes in American Simmental using total herd reporting data.

Reproduction plays a major role in the production efficiency of livestock species. However, cow-centric reproductive traits tend to be lowly heritable and are not expressed until later in an animal's lifetime, making phenotypic selection alone inefficient at generating genetic gain. Genetic progress can be accelerated by focusing selection on the predicted genetic component of reproductive traits using Expected Progeny Differences (EPDs). We used the American Simmental Association's performance and Total Herd Enrollment data, made up of 533,155 calving records from 303,158 females (132,403 cows and 170,755 heifers), 33,732 of which are genotyped, to explore three continuous and two discrete phenotypes focused on quantifying early and sustained fertility in beef cows. We analyzed calving date (cow's calving date relative to the start of the calving season), calving interval (days between calves), first calving interval (calving interval observation between the first and second calving record for a female), heifer pregnancy (did the animal calve as 2-year-old), and discrete early calving (did animal calve in the first 30 days of the calving season) as distinct, but correlated measures of fertility. This dataset provides insight into population-wide trends related to cow attrition, calving season lengths, and phenotypic variation in fertility. We used pedigree and genomic REML to estimate these six phenotypes' genetic, permanent environment, and temporary environmental variance components. Pedigree estimated heritabilities were 0.06 (±0.000011) for calving date, (0.04 ±0.000005) for calving interval, 0.07 (±0.000016) for discrete early calving, 0.05 ±0.000041 for first calving interval, and 0.23 (±0.000099) for heifer pregnancy, consistent with other fertility traits across beef and dairy cattle. The incorporation of genomics increased the heritability estimate for heifer pregnancy (0.24 ±0.000098) and decreased the estimate for first calving interval (0.04 ±0.000029). Positive phenotypic and genetic correlations were found among these phenotypes (rG = 0.01-0.96). These results call for further work in optimizing genetic predictions and exploration of the genetic architecture through genome-wide studies. Whole herd reporting date frameworks represent opportunities for measuring new reproductive phenotypes, but their utility in genetic evaluations will rely on novel trait initiatives and consistent recording that captures more detailed data.

Changes in high-latitude surface energy balance driven by snowpack and vegetation dynamics under warmer climate

Abstract With rapid climate warming, expected changes in snowpack and vegetation will alter the seasonal surface albedo of high-latitude ecosystems. The extent to which these albedo changes may affect surface energy balances and thus soil temperatures is uncertain, but represents a potentially important component of ecosystem feedbacks to climate change. Here, we apply a well-tested process-rich ecosystem model, ecosys, to examine changes in seasonal surface albedo and soil temperature driven by climate-induced snowpack and vegetation changes across Alaska under a warmer twenty-first century climate. Under the Representative Concentration Pathway 8.5 climate change scenario, the modeled changes in surface albedo exhibited large seasonal and spatial variations. We found spring albedo decreases driven by increases in snow-free periods (>20 d) and an extended growing season length that resulted in greater gains in leaf area index (LAI) in most parts of Alaska. In contrast, we modeled increases in summer and winter albedo (despite modeled increases in LAI) across much of the boreal forest due to an increased proportion of aspen, which has a higher leaf albedo than the currently dominant black spruce. Modeled latent heat fluxes generally increase across the twenty-first century, particularly during the spring and summer. Overall, climate warming and changes in surface energy fluxes resulted in a 3.5 ± 0.50 °C increase in spatial- and annual-averaged top 10 cm surface soil temperatures across Alaskan ecosystems by the year 2100, with larger increases in tundra than boreal forest regions. We conclude that under warmer climates, seasonal variations in albedo and surface energy fluxes are particularly pronounced during the spring and summer, driven by changes in snowpack and vegetation dynamics.

Effects of heat, elevated vapor pressure deficits and growing season length on growth trends of European beech

In recent decades, continued growth decline has been observed in various beech forest regions of Central and Western Europe, especially in the warmer lowlands, which is not necessarily linked to increased mortality. While earlier dendrochronological studies have shown that a deteriorating climatic water balance in the course of climate warming can drive negative growth trends, less is known about the effects of climatic extremes on tree growth, notably heat and rising atmospheric vapor pressure deficits (VPD). Through climate-growth analysis, we analyzed the influence of summer heat duration (frequency of hot days with Tmax > 30°C) and elevated VPD on the basal area increment (BAI) of dominant beech trees in 30 stands across a precipitation gradient in the northern German lowlands. Summer heat (especially in June) and elevated VPD are reducing BAI in a similar manner as does a deteriorated climatic water balance. While growing season length (GSL), derived from thermal thresholds of growth activity, has substantially increased since 1980, BAI has declined in the majority of stands, demonstrating a recent decoupling of tree productivity from GSL. We conclude that heat and elevated VPD most likely are important drivers of the recent beech growth decline in this region, while growing season length has lost its indicative value of beech productivity.

Effects of Porcine Zona Pellucida Immunocontraception on Mare Body Condition and Foaling Season Length in Two Western Wild Horse Populations

Wildlife managers and the public have expressed considerable interest in the use of contraception to help manage the populations of wild horses and burros (Equus caballus and E. asinus). Field testing has shown that two preparations of the porcine zona pellucida (PZP) vaccine, a simple emulsion (ZonaStat-H) and PZP-22 (which supplements ZonaStat-H with a controlled-release component) effectively prevent pregnancy in individual mares and can substantially reduce population foaling rates. To determine whether some PZP preparations might have secondary effects that harm treated mares or their foals, we examined the effects of PZP-22 vaccinations and the follow-up boosters of either PZP-22 or ZonaStat-H on adult female body condition, foaling season, and foal mortality in two wild horse herds in the western USA, Cedar Mountains Herd Management Area, Utah (CM; 2008–2015), and Sand Wash Basin Herd Management Area, Colorado (SWB; 2008–2014). At both sites in every study year, summer body condition scores improved faster in mares without foals than mares with foals (p < 0.001; CM, n = 234; SWB, n = 172), but PZP treatments did not affect mare body condition apart from their contraceptive effects. Births to mares treated with PZP within the previous three years were delayed and spread out over the foaling season, but foal mortality rates through the first and second year were low, unrelated to date of birth, and virtually identical for the foals of PZP-treated and untreated mothers (all comparisons n.s.; CM, n = 775, SWB, n = 640). Thus, in these two populations, we found no evidence that changes in reproductive timing associated with PZP treatments were harmful to either mares or foals.

Climate change and disturbance interact to alter landscape reflectivity (albedo) in boreal forests across a large latitudinal gradient in Siberia

Boreal forests form the largest terrestrial biome globally. Climate change is expected to induce large changes in vegetation of high latitude ecosystems, but there is considerable uncertainty about where, when, and how those changes will occur. Such vegetation change produces major feedback to the climate system, including by modifying albedo (reflectivity). Our study used the LANDIS-II forest landscape model to project forest dynamics on four representative landscapes (1 M ha) for 280 years into the future under a range of climate scenarios across a broad latitudinal gradient in Siberia. The model estimated the albedo of the vegetation and any snow on each landscape grid-cell through time to quantify surface albedo change in response to climate change and disturbances. We found that the shortening of the snow-covered season (winter) decreased annual average albedo dramatically, and climate change facilitated the invasion of tundra by boreal trees in the northernmost landscape (reducing albedo in all seasons). However, in other landscapes, albedo increased in summer due to disturbances (fire, wind, insects, harvest), eliminating or reducing leaf area in the short-term, and in the mid-term by promoting more reflective forest types (deciduous, light conifers). This increased albedo was somewhat ephemeral and under climate change was overwhelmed by the shortening of the snow-covered season that greatly reduced albedo. We conclude that the primary driver of the overall reflectivity of boreal ecosystems is not vegetation, but rather, the length of the snow-covered season. Because climate change is likely to dramatically shorten the snow season, the concurrent reduction of albedo has the potential to act as a powerful positive feedback for climate change. Managing natural and anthropogenic disturbances may be the only tool with potential to mitigate the reduction of albedo by climate change in boreal ecosystems because management to encourage more reflective forest types has relatively small effect.

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 main HAD rainfall seasons are typically defined as March–May (MAM) and October–December (OND). However, these 3-month periods are only generalized 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 the drylands of 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 the “short rains” season over the period of study. This could be related to the previously documented decline of the “long rains” seasonal 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 local mean seasonal total. The locally defined rainfall seasons better capture the bulk of the rainfall during the season, giving improved characterization of rainfall metrics, consistent with the aim of a better understanding of rainfall impacts on local communities.

1997–2016, Twenty Years of Pollen Monitoring Activity in Rome Tor Vergata (Rome South-East): Trends Analysis

Global environmental change is rapidly altering the dynamics of terrestrial vegetation, with consequences for the functioning of the Earth system. Recent studies show that climate change is influencing the phenology and distribution of plants. Airborne pollen reflects the flowering period of the plant, which is influenced by meteorological variables such as temperature and rainfall. The analysis of pollen trends is a very useful tool for understanding the effects of climate change on vegetation. In fact, it is accepted that the onset and peak abundance of certain pollen types should be used as possible bioindicators of climate change. The aim of the work is to analyze the presence of various pollen in Rome—from their release from the anthers to their permanence in the atmosphere, the trends of phenological (start, length, and end of the pollen season) and production (pollen abundance and pollen peaks) pollen indicators, the trends of the meteorological variables mainly involved (temperature and precipitation), and any relationships between pollen and meteorological variables, also based on the variation in vegetation. In the period considered, the analysis of the pollen spectra shows an increasing trend in herbaceous taxa, probably attributed to a gradual abandonment of farming practices in the neighboring area, which in recent years has been the subject of intense new construction activity and to a progressive deterioration in the maintenance of green areas.

Effect of factory reliability on bagasse usage and surplus

Poor factory reliability increases season length, reduces sugar production and reduces the supply of bagasse available for cogeneration and the production of by-products. The financial justification for capital expenditure, maintenance and control system upgrades usually account for the extended season length and lost sugar production associated with stoppages. However, the extra bagasse use due to stoppages is often harder to quantify, and, therefore, the resulting financial consequences are often not considered. This work attempts to quantify the effects of stoppages on bagasse use in factories so that the true costs of factory stoppages can be more accurately determined. Factory data have been used to predict the effects of long and short factory stops on bagasse consumption and surpluses. Calculations were carried out for a factory data set with a relatively small number of short stops and a factory data set with a large number of short stops. For both data sets, far more bagasse was lost due to short stops than long stops, and the quantity of bagasse consumed due to short stops represents a significant loss of revenue. Stops disrupt and increase the bagasse consumption of the boiler station in ways that are difficult to model, so it is likely that the calculations in this work underestimate the bagasse consumption and, therefore, revenue lost due to stops.

Weighing Policy Effectiveness Through Recent Forest Fire Status

Forest fires pose a great threat to the global ecological environment as well as human life and the safety of property. Formulating effective policies for preventing forest fires is not only a scientific concern but also an urgent need for government management. Canada and China both have extensive forest areas but have different fire management strategies. Canada primarily focuses on fire suppression while China pays more attention on fire prevention. This difference led to significant discrepancies in the forest fire regimes between the two countries, providing an opportunity to explore the impact of fire management policies on forest fire. By analyzing the fire occurrences in Canada and China since 1990, combining the fire prevention funds and fire management strategies, this paper discussed the influence of different policies on fire occurrence. Previously, Canada’s forest suppression strategy has been widely recognized internationally, but recent widespread fires indicate that its fire management policy may still require further improvement to cope with future global warming. Although China’s fire prevention strategy can effectively control current forest fires, the lack of fundamental theories on forest fires and the backwardness of fire prevention technology and equipment may increase the likelihood of major forest fires in the future. As global warming continues to intensify in the future, the length of the forest fire season and the intensity of fires will increase, making it urgent to develop more effective forest fire prevention and suppression policies to achieve sustainable development.

Indications of a changing winter through the lens of lake mixing in Earth’s largest freshwater system

Abstract Global surface freshwater primarily resides in lakes, with the overwhelming majority found in Earth’s largest lakes, thus understanding potential climate change effects in these large lakes is critical. In dimictic lakes, climate change has extended the duration of summer thermal stratification and reduced the length of the ice season. These changes are relatively straightforward to evaluate in smaller, inland lakes. However in large lakes, such as the North American Great Lakes, temporally intermittent and spatially heterogeneous ice cover, and spatial thermal heterogeneity limit the utility of simple ice on-off or mixing classifications; therefore, assessing how climate change is impacting winter conditions in large lakes is challenging. Here, we use in-situ and satellite-derived surface water temperature observations from the North American Great Lakes to overcome these limitations and show that warming air temperatures are driving reductions in the number of winter days, collectively those with either ice cover or inverse thermal stratification, in favor of increases in isothermal conditions for the period 1995 to 2023. We find that on average the Great Lakes are experiencing a loss of 14 winter days per decade. Our results demonstrate how climate change has yielded disproportionate changes in the annual thermal cycle and mixing conditions of Earth’s largest freshwater system and signals the potential for fundamental ecosystem shifts due to a loss of winter.

Advancing the Seasonal Outlook of the Wet Seasons of Florida

Abstract In this study, we introduce an ensemble approach to provide a probabilistic seasonal outlook of the length and seasonal rainfall anomaly of the wet season over Florida using the observed variations of the onset date of the season at the granularity of ∼10-km grid resolution (which is the spatial resolution of the observed rainfall data used for this work). The time series of daily precipitation at the grid resolution of NASA’s Global Precipitation Mission is randomly perturbed 1000 times to account for the uncertainty of synoptic to mesoscale variations on the diagnosis of the onset and demise date of the wet season. The strong covariability of the onset date with the seasonal length and seasonal rainfall anomaly of the wet season is then leveraged to provide the seasonal outlooks by monitoring the onset date of the wet season. This simple seasonal outlook is effective in predicting extreme tercile and even extreme pentile anomalies across Florida. We suggest that the proposed approach to the seasonal outlook of the wet season of Florida provides a viable alternative in the absence of strong external forcing like ENSO or tropical Atlantic variability that potentially limits the predictability of numerical climate models used for seasonal prediction. Significance Statement Earlier studies have shown that the seasonal prediction from the numerical climate models even at zero lead time has very limited prediction skills over the summer in Florida, which also coincides with the wettest part of the year. Florida’s wet season exhibits significant interannual variations, which exert its influence on water management decisions for subsequent drier seasons of the year. Therefore, strategies to improve this skill are highly relevant. We propose in this study that by monitoring the onset of the wet season variations, we can usefully provide a probabilistic seasonal outlook of the season over Florida. This is done by leveraging the observed linear relationships between the onset date variations with the length and the seasonal rainfall anomaly of the season. Furthermore, the outlook is provided at the spatial resolution of the observed dataset, which in this case is at 10-km grid resolution.

Competition, Drought, Season Length? Disentangling Key Factors for Local Adaptation in Two Mediterranean Annuals across Combined Macroclimatic and Microclimatic Aridity Gradients.

Competition in mesic sites and drought stress combined with short growing seasons in drier sites are key environmental factors along macroclimatic aridity gradients. They impose a triangular trade-off for local adaptation. However, as experiments have rarely disentangled their effects on plant fitness, uncertainty remained whether mesic populations are indeed better competitors and drier populations better adapted to drought stress and short season length. Aridity differs also at microclimatic scale between north (more mesic) and south (more arid) exposed hill-slopes. Little is known whether local adaptation occurs among exposures and whether south exposures harbor conspecifics better adapted to drier climates that could provide adaptive reservoirs under climate change. We sampled two Mediterranean annuals (Brachypodium hybridum, Hedypnois rhagadioloides) in 15 sites along a macroclimatic aridity gradient (89-926 mm rainfall) on corresponding north and south exposures. In a large greenhouse experiment, we measured their fitness under drought stress, competition, and short vs. long growing seasons. Along the macroclimatic gradient, mesic populations were better competitors under benign conditions. Drier populations performed no better under drought stress per se but coped better with the short growing seasons typical for drier macroclimates. At microclimatic scale, north exposure plants were slightly better competitors in H. rhagadioloides; in B. hybridum, south exposure plants coped better with drought under short season length. We demonstrate that local adaptation to drier macroclimates is trading-off with competitive ability under benign conditions and vice-versa. Drought escape via short life-cycles was the primary adaptation to drier macroclimates, suggesting that intensified drought stress within the growing season under climate change challenges arid and mesic populations alike. Moreover, the drier microclimates at south exposures exhibited some potential as nearby reservoirs of drier-adapted genotypes. This potential needs further investigation, yet may assist populations to persist under climate change and lessen the need for long-distance migration.

Trends and Variability in annual and seasonal rainfall amount and timing in Wereilu district, Northeastern Highlands of Ethiopia

Studying climate change can significantly benefit agricultural practices in a country where many people rely heavily on subsistence farming. To this end, this study aimed to examine trends and variability in rainfall amounts and timing in the climate-vulnerable Wereilu district, northeastern highlands of Ethiopia. The coefficient of variation and standardized rainfall anomaly were employed to analyse rainfall variability, while the Innovative Trend Analysis (ITA) was applied to examine rainfall trends. The findings revealed that Kiremt (main rainy season) exhibited moderate variability, whereas Belg (small rainy season) exhibited high variability. The trend analysis showed significant changes in both seasonal and annual rainfall amounts and their timing. Annual and Kiremt rainfall significantly increased at Wereilu by 55.5 mm and 88.7 mm per decade, respectively, and at Kabie by 16.6 mm and 48.4 mm per decade (p < 0.01). In contrast, Belg rainfall revealed a significant declining trend at both sites. The graphical trend analysis revealed a positive trend for all clusters during Kiremt. In contrast, Belg showed a declining trend across all clusters, with a more pronounced decline in higher values at both sites. Rainfall onset dates significantly shifted towards earlier onset, while rainfall cessation dates showed insignificant late cessation. The length of the rainy season exhibited a positive trend (p < 0.01) at Wereilu and (p < 0.05) at Kabie. Overall, the observed substantial changes in rainfall amounts and timing imply the need for relevant adaptation measures, particularly in the farming system and water sector.

Inverse Trend Between Tree Pollen and Fungal Concentrations With Allergic Sensitization Rates in Seoul for 25 Years.

A growing number of individuals are developing allergic diseases due to pollen exposure. Seasonal variations and increased pollen concentrations have occurred with the increased rates of allergic sensitization among both children and adults. Temperature significantly influences pollination, particularly in spring- and early summer-flowering plants, with weather conditions affecting pollen allergen levels. Human activities, including agriculture and deforestation, increase carbon emissions, leading to higher atmospheric CO₂ levels that may enhance allergenic plant productivity. Climate change affects the range of allergenic plant species and length of pollen season. Studies indicate that higher CO₂ and temperature levels are linked to increased pollen concentrations and allergenicity, whereas atmospheric fungal concentrations have declined annually over the past 25 years. Despite more intense precipitation in summer and autumn, the number of rainy days has decreased across all seasons. This concentration of rainfall over shorter periods likely prolongs the dry season and shortens the period of fungal sporulation. Future climate changes, including atmospheric dryness, drought, and desertification could further decrease allergenic fungal sporulation. It remains unclear whether the inverse relationship between pollen and fungal concentrations and distributions directly results from climate change. It is crucial to evaluate the patterns of aeroallergens and their associated health risks.

Interplay of abiotic conditions, density, and body size in shaping demography in a high‐elevation toad population

AbstractIn natural populations, vital rates such as survival and reproduction are influenced by a complex interplay of abiotic conditions (e.g., environment), density dependence, and individual factors (e.g., phenotypic traits). Studies at the extremes of species distributions, particularly high elevations, offer unique insights due to the intensified effects of abiotic stressors, which can amplify both direct and indirect effects on vital rates. In this study, we focus on a high‐elevation population of the common toad (Bufo bufo) located near the upper limit of its elevational range in the Swiss Alps. This setting provides a critical context for examining how extreme abiotic conditions interact with density dependence and individual factors to influence life history traits. Utilizing 28 years of capture–mark–recapture data and individual body size measurements from nearly 2500 toads, we applied in a Bayesian statistical framework a Cormack–Jolly–Seber model for estimating male survival probabilities, and a multistate model for assessing female survival and breeding probabilities, alongside sex‐specific growth curves. Our analysis indicates that survival probabilities are significantly impacted by interactions between abiotic conditions such as the active season length and temperature at emergence from hibernation, density dependence, and individual phenotypic traits such as body size. The breeding patterns of females showed a biennial cycle, with temperature at hibernation emergence influencing the likelihood of skipping breeding events and density affecting the resumption of breeding. These results highlight the role of abiotic conditions and density in shaping physiological and reproductive strategies in a high‐stress ecological niche. Moreover, we uncovered indications of indirect effects, where both abiotic conditions and density potentially affect asymptotic growth and thus survival, mediated through changes in body size. Our findings illustrate the complex dynamics at play in high‐elevation populations and the importance of long‐term, individual‐based data in studying these processes. This study underscores the value of integrating multiple sources of variation to understand population dynamics comprehensively, particularly in understudied, extreme environments where traditional ecological models may not fully capture the nuanced interdependencies of natural systems.

Shifts in Plant Phenology Significantly Affect the Carbon Allocation in Different Plant Organs.

Earlier start of the growing season (SGS) and delayed end of the growing season (EGS) affect plant carbon uptake. However, the effects of phenological changes on carbon allocation to different plant organs remain unclear. Here, we examined the effects and potential mechanisms of phenological changes on carbon allocation to different organs over the northern hemisphere (> 30° N). We found the earlier SGS facilitated allocating carbon to roots in warm areas, and delayed EGS benefited allocating carbon to roots in dry areas. Moreover, the effects of SGS and EGS on carbon accumulation in different organs significantly enhanced over time. Path analyses indicated that phenological changes contributed to root-stem ratio mainly by regulating the growing season length. Our findings further highlight that phenological changes alter plants' investment strategies in carbon allocation for above- and below-ground parts, and considering this role is critical for accurately estimating the carbon budget in terrestrial ecosystems.

Exploring Climate Change Impacts on Temperature Extremes in the South Saskatchewan River Watershed, Alberta, Canada

In recent years, the frequency and intensity of extreme temperature events have escalated, posing unprecedented challenges to ecosystems, economies, and human health. As global temperatures rise, these events are emerging as critical threats; therefore, understanding their changes is essential for developing strategies to mitigate their growing risks under global warming. In this study, we used ETCCDI (Expert Team on Climate Change Detection, Monitoring, and Indices) temperature indices to analyze future changes in extreme temperature events in the South Saskatchewan River Watershed (SSRW) in Southern Alberta, Canada, a critical area for irrigation, agriculture, and food production. This analysis is based on an ensemble of 26 Global Circulation Models (GCMs) and three Shared Socio-economic Pathway (SSP) scenarios, in three periods (2015–2030, 2041–2060, 2071–2100), compared against the base period of 1951–1990. The results suggest substantial changes in most of the studied indices towards higher temperatures, with a significant rise in both the numbers of days with extreme temperatures and the magnitude of the temperature itself, as well as a notable drop in the number of cold days. As a result of warming, the growing season length is 16 days longer in 2015–2030 compared to the base period and is projected to increase substantially by the end of the century. A longer growing season might seem favourable for agriculture, but it can disrupt water availability and cause unpleasant environmental consequences. Overall, the scenarios considered in this research suggest that the SSRW could experience warming at a significant rate. This finding underscores the urgent need for adaptation and mitigation actions to enhance resilience and sustainability.

Reconstructing and Hindcasting Sea Ice Conditions in Hudson Bay Using a Thermal Variability Framework

The Hudson Bay seasonal sea ice record has been well known since the advent of satellite reconnaissance, with a continuous record since 1971. To extend the record to earlier decades, a thermal variability framework is used with the surface temperature climatological records from four climate stations along the Hudson Bay shoreline: Churchill, Manitoba; Kuujjurapik, Quebec; Inukjuak, Quebec; and Coral Harbour, Nunavut. The day-to-day surface temperature variation for the minimum temperature of the day was found to be well correlated to the known seasonal sea ice distribution in the Bay. The sea ice/thermal variability relationship was able to reproduce the existing sea ice record (the average breakup and freeze-up dates for the Bay) largely within the error limits of the sea ice data (1 week), as well as filling in some gaps in the existing sea ice record. The breakup dates, freeze-up dates, and ice-free season lengths were generated for the period of 1922 to 1970, with varying degrees of confidence, adding close to 50 years to the sea ice record. Key periods in the spring and fall were found to be critical, signaling the time when the changes in the sea conditions are first notable in the temperature variability record, often well in advance of the 5/10th ice coverage used for the sea ice record derived from ice charts. These key periods in advance of the breakup and freeze-up could be potentially used, in season, as a predictor for navigation. The results are suggestive of a fundamental change in the nature of the breakup (faster) and freeze-up (longer) in recent years.

Phenological Monitoring of Irrigated Sugarcane Using Google Earth Engine, Time Series, and TIMESAT in the Brazilian Semi-arid

Monitoring sugarcane phenology is essential since the globalized market requires reliable information on the quantity of raw materials for the industrial production of sugar and alcohol. In this context, the general objective of this study was to evaluate the phenological seasonality of the sugarcane varieties SP 79-1011 and VAP 90-212 observed from the NDVI time series over 19 years (2001–2020) from global databases. In addition, this research had the following specific objectives: (i) to estimate phenological parameters (Start of Season (SOS), End of Season (EOS), Length of Season (LOS), and Peak of Season (POS)) using TIMESAT software in version 3.3 applied to the NDVI time series over 19 years; (ii) to characterize the land use and land cover obtained from the MapBiomas project; (iii) to analyze rainfall variability; and (iv) to validate the sugarcane harvest date (SP 79-1011). This study was carried out in sugarcane growing areas in Juazeiro, Bahia, Brazil. The results showed that the NDVI time series did not follow the rainfall in the region. The sugarcane areas advanced over the savanna formation (Caatinga), reducing them to remnants along the irrigation channels. The comparison of the observed harvest dates of the SP 79-1011 variety to the values estimated with the TIMESAT software showed an excellent fit of 0.99. The mean absolute error in estimating the sugarcane harvest date was approximately ten days, with a performance index of 0.99 and a correlation coefficient of 0.99, significant at a 5% confidence level. The TIMESAT software was able to estimate the phenological parameters of sugarcane using MODIS sensor images processed on the Google Earth Engine platform during the evaluated period (2001 to 2020).

Lengthening Atlantic Hurricane Seasons with Earlier Storm Formation Dates Including Implications from 2020

Abstract This paper analyzes the formation dates of the nth storm in a sequence for all named North Atlantic tropical cyclones and assesses whether the intraseasonal length of the Atlantic hurricane season has changed temporally. The record-breaking 2020 season, with 30 named storms, set records for the earliest 3rd TC formation (Cristobal) and from the 6th TC (Fay) onward. Analysis of season length from 1851–2022 identifies only one statistically significant breakpoint detected in the early 1970s, roughly coinciding with the introduction of satellite observations. Since 1970, we also find a trend towards longer North Atlantic hurricane seasons The 1971–2022 trend is robust and statistically significant, whether assessed as the number of days between the first and last storm, or by the distance between intermediate percentiles (e.g., 10th to 90th, 15th to 85th). These increases are mainly associated with storms forming earlier in the calendar year and are best described as an upward trend rather than a stepwise shift between eras. Although a simple trend fits better than a stepwise model, improvement falls short of significance, so we do not formally reject the stepwise hypothesis. If, following this hypothesis, the 1950–2022 period is segmented into a high activity era (HAE1; 1950–1969), a low activity era (LAE; 1970–1994), and second high activity era (HAE2; 1995–2022), the median season length HAE2 is 12 days longer than in the first HAE, but this difference is not statistically significant (p = 0.58) and could be explained by the substantial difference in the observational network. The median season length in both HAE1 and AE2 are significantly longer (by 36 and 48 days, respectively) than the intervening LAE.