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Nitrous oxide (N2O) is a greenhouse gas and stratospheric ozone-depleting substance with large and growing anthropogenic emissions. Previous studies identified the influx of N2O-depleted air from the stratosphere to partly cause the seasonality in tropospheric N2O (aN2O), but other contributions remain unclear. Here, we combine surface fluxes from eight land and four ocean models from phase 2 of the Nitrogen/N2O Model Intercomparison Project with tropospheric transport modeling to simulate aN2O at eight remote air sampling sites for modern and pre-industrial periods. Models show general agreement on the seasonal phasing of zonal-average N2O fluxes for most sites, but seasonal peak-to-peak amplitudes differ several-fold across models. The modeled seasonal amplitude of surface aN2O ranges from 0.25 to 0.80 ppb (interquartile ranges 21%–52% of median) for land, 0.14–0.25 ppb (17%–68%) for ocean, and 0.28–0.77 ppb (23%–52%) for combined flux contributions. The observed seasonal amplitude ranges from 0.34 to 1.08 ppb for these sites. The stratospheric contributions to aN2O, inferred by the difference between the surface-troposphere model and observations, show 16%–126% larger amplitudes and minima delayed by ∼1 month compared to Northern Hemisphere site observations. Land fluxes and their seasonal amplitude have increased since the pre-industrial era and are projected to grow further under anthropogenic activities. Our results demonstrate the increasing importance of land fluxes for aN2O seasonality. Considering the large model spread, in situ aN2O observations and atmospheric transport-chemistry models will provide opportunities for constraining terrestrial and oceanic biosphere models, critical for projecting carbon-nitrogen cycles under ongoing global warming.

The likely changes to precipitation seasonality with warming are both impactful and not well understood. This work aims to describe areas that experience similar changes to seasonal precipitation irrespective of the original underlying precipitation seasonality. We train a self-organizing map on the difference between the seasonal cycle of precipitation in the past and in a high-warming future climate as represented by the Community Earth System Model, version 2, to create regions with similar changes in precipitation seasonality. This method is applied separately over land and ocean surfaces because of the differing processes leading to precipitation over each. This method indicates that future changes in seasonal precipitation are most varied in the tropics because of a southward shift in the intertropical convergence zone. The seasonal shifts found over midlatitude oceans indicate a poleward shift in atmospheric river activity. We find a correspondence between certain land-based precipitation changes and Köppen climate classification. The seasonality of large-scale and convective precipitation is examined for each region. The relationship between the seasonal changes to precipitation and associated atmospheric processes is discussed. These processes include atmospheric rivers, the intertropical convergence zone, tropical cyclones, and monsoons. [ABSTRACT FROM AUTHOR]

Atmospheric general circulation models (AGCMs) and coupled general circulation models (CGCMs) in the High Resolution Model Intercomparison Project (HighResMIP) were evaluated on their ability to simulate tropical cyclone (TC) activity in the western North Pacific (WNP) over its annual cycle. Specifically, we examined these models' ability to simulate the south–north migration of the mean TC genesis location. The results revealed that both types of models realistically captured TC numbers and the south–north migration of TC genesis locations associated with the meridional migration of the WNP subtropical high ridge in response to the annual cycle. However, TC numbers decreased less rapidly in the AGCMs than in both the CGCMs and observed data during the monsoon retreat period (after September). This bias was probably attributed to a low-tropospheric cyclonic anomaly over the Philippine Sea in response to La Niña–like sea surface temperature (SST) differences between the AGCMs and the CGCMs. Because of these differences, the TC genesis frequency in the AGCMs over the Philippine Sea was overestimated. The cyclonic anomaly occurred when the northeasterly trade wind arose and was maintained through wind–evaporation–SST feedback. In future climate (2021–50), the main changes occurred during the monsoon retreat period. A more rapid decrease in TC numbers shown in AGCMs was likely attributed to the decrease (increase) of low-level vorticity (vertical wind shear) modulated by enhanced WNP subtropical high and subsidence anomalies. Conversely, a cyclonic circulation and ascending anomalies projected by CGCMs were identified off-equator, which favored TC genesis location shifting northward. Significance Statement: Model performance and future changes in the annual cycle of tropical cyclone (TC) activity in the western North Pacific are investigated. We found that high-resolution uncoupled and coupled models realistically captured the TC numbers and meridional migration of TC genesis locations associated with the meridional migration of subtropical high ridge. However, TC numbers decreased more gradually in the uncoupled models than in the coupled models after September. This lower skill may stem from differences between the uncoupled and coupled models in simulating a cyclonic anomaly over the Philippine Sea in response to the La Niña–like sea surface temperature difference. In future climate (2021–50), TC numbers are significantly projected to decrease more rapidly during the monsoon retreat period in uncoupled models. [ABSTRACT FROM AUTHOR]

In this work, we investigated the seasonal cycle of atmospheric potential oxygen (APO), a unique tracer of air‐sea gas exchanges of molecular oxygen (O2) and carbon dioxide (CO2), expressed as APO = O2 + 1.1 × CO2. APO data were obtained from flask air samples collected since the late 1990s at three Japanese ground stations and on commercial cargo ships sailing between Japan and Australia/New Zealand, North America, and Southeast Asia. We also analyzed the APO spatial distribution and seasonal cycles with simulations from an atmospheric transport model using climatological oceanic O2 fluxes from an empirical product that relate O2 flux to ocean heat as input. Model simulations reproduced the observed APO seasonal cycles generally well, but with larger amplitudes and earlier occurrence of seasonal minima and maxima than in the observations. Moreover, the observed seasonal cycles exhibited larger APO enhancements than the simulations in autumn and early winter, especially in the North Pacific at 20°N–60°N. These enhancements remained when refining the comparison by adjusting the simulated APO peak‐to‐peak amplitudes and seasonal phases to the observations. This suggests additional O2 emissions in the North Pacific, not well expressed in the air‐sea O2 fluxes used as input for our model simulations. The average autumn enhancement at 40°N–60°N was approximately twice that measured at 20°N–40°N. Confirming previous studies, our results indicate two distinct mechanisms possibly contributing to the additional oceanic O2 emissions: outgassing from a subsurface shallow oxygen maximum at 20°N–40°N and autumn phytoplankton bloom at 40°N–60°N. Plain Language Summary: Seasonal variations of air‐sea molecular oxygen (O2) exchanges are mainly driven by spring/summer emission and autumn/winter absorption. Emission results mainly from O2 production by phytoplankton at the ocean surface; absorption is related to O2 uptake in deep oxygen‐depleted water layers caused by oceanic ventilation. A phytoplankton bloom in autumn and outgassing from water rich in dissolved O2 just below the mixed layer, known as the shallow oxygen maximum, have been suggested as possible mechanisms contributing to the O2 seasonal cycles. Unfortunately, these oceanic autumn O2 emissions are not well characterized. In this study, we analyzed air samples collected in the western and northern Pacific to evaluate the oceanic component of the O2 seasonal cycle, known as "atmospheric potential oxygen" and calculated as the sum of atmospheric O2 and carbon dioxide. By comparing these observations with model simulations that used previous air‐sea O2 flux estimates as input, we identified marked enhancements in autumn at latitudes between 20°N and 60°N in the Pacific. This corresponds to the geographic area where the autumn phytoplankton bloom and the shallow oxygen maximum occur. This result is a strong indication of additional autumn O2 emissions in the extratropical North Pacific. Key Points: We analyzed atmospheric potential oxygen (APO), a tracer of air‐sea exchanges of molecular oxygen (O2) and carbon dioxide, in the PacificThe observed seasonal APO enhancement at 20°N–60°N in autumn, relative to model simulations, suggests additional oceanic O2 emissionsOutgassing from a shallow oxygen maximum (20–40°N) and an autumn phytoplankton bloom (40–60°N) likely contribute to this enhancement [ABSTRACT FROM AUTHOR]

The Gravity Recovery and Climate Experiment (GRACE) satellite provides valuable data to monitor groundwater variation. This study investigates groundwater dynamics in India during deficit and excess monsoon years. It finds possible interactions by exploring how groundwater levels respond to meteorological and hydrological conditions. Groundwater anomalies (GWA) are estimated using Terrestrial Water Storage Anomalies (TWSA) from GRACE and hydrological parameters from the Global Land Data Assimilation System (GLDAS). The statistical analysis reveals that the standard deviation is higher for hydrological parameters in summer (June to September), whereas it is higher in fall (October to November) for GWA in many parts of India. The modulation in hydrological parameters subsequently impacts GWA during the following seasons. The study reports increased groundwater across many parts of India during fall. However, groundwater decline is closely linked to unsaturated soil moisture from fall to winter (December to February). Groundwater storage is at its lowest levels during the following spring (March to May) over India. Four deficit and three excess summer monsoons occurred from 2002 to 2022. Composite analysis of GWA reveals that there is replenishment (depletion) of groundwater during the following fall and winter in excess (deficit). The analysis based on extreme deficit monsoon years (2002, 2009) and excess monsoon year (2019) reveals that during the deficit years, groundwater recharge is less, and excess monsoon year it is more; and is vice versa for GWA. The study reports decline in GWA during the summer 2019, which is attributed to the hydrological conditions of the preceding year and modulation of the hydrological processes. As climate variability and water scarcity become increasingly pressing issues, understanding the relationships between hydrological factors and groundwater dynamics is essential for ensuring sustainable water use and resilience to extremely varying climate conditions. [ABSTRACT FROM AUTHOR]

Atmospheric trace gas measurements can be used to independently assess national greenhouse gas inventories through inverse modeling. Atmospheric nitrous oxide (N2O) measurements made in the United Kingdom (UK) and Republic of Ireland are used to derive monthly N2O emissions for 2013–2022 using two different inverse methods. We find mean UK emissions of 90.5 ± 23.0 (1σ) and 111.7 ± 32.1 (1σ) Gg N2O yr−1 for 2013–2022, and corresponding trends of −0.68 ± 0.48 (1σ) Gg N2O yr−2 and −2.10 ± 0.72 (1σ) Gg N2O yr−2, respectively, for the two inverse methods. The UK National Atmospheric Emissions Inventory (NAEI) reported mean N2O emissions of 73.9 ± 1.7 (1σ) Gg N2O yr−1 across this period, which is 22%–51% smaller than the emissions derived from atmospheric data. We infer a pronounced seasonal cycle in N2O emissions, with a peak occurring in the spring and a second smaller peak in the late summer for certain years. The springtime peak has a long seasonal decline that contrasts with the sharp rise and fall of N2O emissions estimated from the bottom‐up UK Emissions Model (UKEM). Bayesian inference is used to minimize the seasonal cycle mismatch between the average top‐down (atmospheric data‐based) and bottom‐up (process model and inventory‐based) seasonal emissions at a sub‐sector level. Increasing agricultural manure management and decreasing synthetic fertilizer N2O emissions reduces some of the discrepancy between the average top‐down and bottom‐up seasonal cycles. Other possibilities could also explain these discrepancies, such as missing emissions from NH3 deposition, but these require further investigation. Plain Language Summary: Atmospheric nitrous oxide (N2O) is an important greenhouse gas and ozone depleting substance. Atmospheric N2O measurements made in the United Kingdom (UK) and Republic of Ireland were used to derive UK N2O emissions for 2013–2022 using two inverse methods. UK emissions derived using atmospheric N2O measurements were on average 22%–51% higher than emissions reported in the UK National Atmospheric Emissions Inventory. A pronounced seasonal cycle in N2O emissions is inferred from the atmospheric N2O observations which contrasts the seasonal N2O emissions estimated in the bottom‐up (process model and inventory‐based) UK Emissions Model (UKEM). We find increasing agricultural manure management N2O emissions and decreasing synthetic fertilizer N2O emissions reduces some of the discrepancy between the seasonal cycles. Key Points: Atmospheric N2O measurements from 2013 to 2022 are used to evaluate the UK's reported emissions using two inverse methodsEmissions derived from atmospheric data are on average 22%–51% higher than the UK's national emissions inventory values across 2013–2022Agreement between the average top‐down and bottom‐up seasonal emissions was improved by decreasing bottom‐up synthetic fertilizer emissions [ABSTRACT FROM AUTHOR]

Pacific salmon (Oncorhynchus spp.) spend much of their life near the ocean surface where climatic and oceanographic conditions affect their habitat and survival. Despite decades of study, critical knowledge gaps persist regarding their ecology and distributions. Consequently, it has been difficult to assess how environmental conditions influence the high‐seas distribution and habitat use of these culturally and socioeconomically important fishes, presenting challenges to fisheries managers trying to evaluate how climate change and fishing activities may impact salmon populations. We used a recently compiled, comprehensive database of historical coastal and high‐seas salmon survey data (1953–2022) in the North Pacific to fit species distribution models that (1) characterize the marine spatial distribution of six species of Oncorhynchus, (2) evaluate species‐specific temperature preferences, and (3) investigate how species' temperature preferences influence distribution. Sea surface temperature, along with seasonal migrations associated with spawning and feeding, significantly affects the distribution of all species, where the warm limits of estimated preferred thermal ranges were more similar than the cold limits. Furthermore, the distributions of some species appear more responsive to temperature than others and recently observed warm conditions have likely impacted realized ranges. These models have expanded our understanding of salmon ocean distributions and thermal niches by providing a unique window into this often unobserved but important part of the life cycle. They also serve as a baseline for future investigations into the mechanisms influencing salmon spatial ecology, responses to climate change, and vulnerability to harvest across the North Pacific. [ABSTRACT FROM AUTHOR]

We revisit the nature of the ocean bottom pressure (pb) seasonal cycle by leveraging the mounting GRACE‐based pb record and its assimilation in the ocean state estimates produced by the project for Estimating the Circulation and Climate of the Ocean (ECCO). We focus on the mean seasonal cycle from both data and ECCO estimates, examining their similarities and differences and exploring the underlying causes. Despite substantial year‐to‐year variability, the 21‐year period studied (2002–2022) provides a relatively robust estimate of the mean seasonal cycle. Results indicate that the pb annual harmonic tends to dominate but the semi‐annual harmonic can also be important (e.g., subpolar North Pacific, Bellingshausen Basin). Amplitudes and short‐scale phase variability are enhanced near coasts and continental shelves, emphasizing the importance of bottom topography in shaping the seasonal cycle in pb. Comparisons of GRACE and ECCO estimates indicate good qualitative agreement, but considerable quantitative differences remain in many areas. The GRACE amplitudes tend to be higher than those of ECCO typically by 10%–50%, and by more than 50% in extensive regions, particularly around continental boundaries. Phase differences of more than 1 (0.5) months for the annual (semiannual) harmonics are also apparent. Larger differences near coastal regions can be related to enhanced GRACE data uncertainties and also to the absence of gravitational attraction and loading effects in ECCO. Improvements in both data and model‐based estimates are still needed to narrow present uncertainties in pb estimates. Plain Language Summary: We revisit the nature of the ocean bottom pressure (pb) seasonal cycle by leveraging the mounting data from space gravity missions and their use in constraining model‐based estimates produced by the project for Estimating the Circulation and Climate of the Ocean (ECCO). We focus on the mean seasonal cycle from both data and ECCO estimates, examining their similarities and differences and exploring the underlying causes. Despite substantial year‐to‐year variability, the 21‐year period studied (2002–2022) provides a relatively robust estimate of the mean seasonal cycle. The pb annual cycle tends to dominate but the semi‐annual cycle can also be important in some regions. Amplitudes are enhanced near shallow coastal regions and can also vary more strongly across the coastal zone, pointing to the importance of changes in ocean bottom topography in shaping the seasonal cycle in pb. Comparisons of data and ECCO estimates indicate good qualitative agreement, but considerable quantitative differences in the magnitude and timing of maxima remain. Largest differences, which tend to occur near coastal regions, can be related to enhanced data uncertainties and also to the absence in ECCO of effects from gravitational attraction of land ice and water storage and related deformation of the ocean bottom. Key Points: Substantial differences remain in satellite and model‐based estimates of the mean seasonal cycle in ocean bottom pressure (pb)Differences between two satellite gravimetry products suggest largest uncertainties around many continental boundariesAbsence of gravitational attraction and loading effects and intrinsic ocean variability can lead to errors in model‐based pb estimates [ABSTRACT FROM AUTHOR]

Nitrous oxide (N2O) is a greenhouse gas and stratospheric ozone‐depleting substance with large and growing anthropogenic emissions. Previous studies identified the influx of N2O‐depleted air from the stratosphere to partly cause the seasonality in tropospheric N2O (aN2O), but other contributions remain unclear. Here, we combine surface fluxes from eight land and four ocean models from phase 2 of the Nitrogen/N2O Model Intercomparison Project with tropospheric transport modeling to simulate aN2O at eight remote air sampling sites for modern and pre‐industrial periods. Models show general agreement on the seasonal phasing of zonal‐average N2O fluxes for most sites, but seasonal peak‐to‐peak amplitudes differ several‐fold across models. The modeled seasonal amplitude of surface aN2O ranges from 0.25 to 0.80 ppb (interquartile ranges 21%–52% of median) for land, 0.14–0.25 ppb (17%–68%) for ocean, and 0.28–0.77 ppb (23%–52%) for combined flux contributions. The observed seasonal amplitude ranges from 0.34 to 1.08 ppb for these sites. The stratospheric contributions to aN2O, inferred by the difference between the surface‐troposphere model and observations, show 16%–126% larger amplitudes and minima delayed by ∼1 month compared to Northern Hemisphere site observations. Land fluxes and their seasonal amplitude have increased since the pre‐industrial era and are projected to grow further under anthropogenic activities. Our results demonstrate the increasing importance of land fluxes for aN2O seasonality. Considering the large model spread, in situ aN2O observations and atmospheric transport‐chemistry models will provide opportunities for constraining terrestrial and oceanic biosphere models, critical for projecting carbon‐nitrogen cycles under ongoing global warming. Plain Language Summary: Anthropogenic N2O emissions, for example, from fertilizer use on agricultural land, fossil fuel burning, and some industrial activities, continue to increase atmospheric N2O to values unprecedented for at least the past 800,000 years. This increase causes harmful global warming and stratospheric ozone depletion. Understanding how N2O emissions from land and ocean influence atmospheric composition and climate is a research priority. Here, we address specifically how land and ocean emissions contribute to the seasonality of N2O at eight air monitoring sites. We apply surface N2O fluxes simulated by eight land biosphere and four ocean biogeochemical models with a representation of lower atmosphere transport. This study complements earlier studies that show a strong influence on N2O seasonality by the influx of N2O‐depleted air from the upper atmosphere. We demonstrate that land biosphere and ocean surface fluxes contribute substantially to the observed seasonal cycle at the different measurement sites. The surface contributions dampen the seasonal signal from the upper atmosphere and must be considered for explaining the observed N2O seasonality. However, surface fluxes differ widely across models. In future work, atmospheric N2O observations and transport modeling, considering both lower and upper atmospheric contributions, may help to better constrain biosphere models. Key Points: Model land biosphere and ocean surface fluxes are combined with tropospheric transport to simulate N2O seasonality at eight monitoring sitesSurface N2O fluxes contribute substantially to the observed seasonality of tropospheric N2O, partly offsetting stratospheric contributionLarge spread in seasonal land fluxes calls for biosphere model improvements, for example, using N2O observations and transport‐chemistry modeling [ABSTRACT FROM AUTHOR]

Abstract: At most latitudes, the seasonal cycle of zonal‐mean surface air temperature is notably asymmetric: the length of the warming season is not equal to the length of the cooling season. The asymmetry varies spatially, with the cooling season being ∼40 days shorter than the warming season in the subtropics and the warming season being ∼100 days shorter than the cooling season at the poles. Furthermore, the asymmetry differs between the Northern Hemisphere and the Southern Hemisphere. Here, we show that these observed features are broadly captured in a simple model for the evolution of temperature forced by realistic insolation. The model suggests that Earth's orbital eccentricity largely determines the hemispheric contrast, and obliquity broadly dictates the meridional structure. Clouds, atmospheric heat flux convergence, and time‐invariant effective surface heat capacity have minimal impacts on seasonal asymmetry. This simple, first‐order picture has been absent from previous discussions of the surface temperature seasonal cycle.

The seasonal fluctuations of the copepod Eodiaptomus japonicus, which dominates the zooplankton community of Lake Biwa, have been disrupted several times over the past 45 years. The aim of this study was to clarify the primary environmental factor that caused the disrupted seasonal cycle in population density of E. japonicus. Here, we tested the hypothesis that the disruption in their seasonal cycle was due to the impacts of water temperature, food conditions, and predator pressure, using an individual-based model (IBM). Based on the experimental data from the literature, we described the growth and reproduction of E. japonicus using temperature- and food-dependent functions. Previously, the developmental time of this species was expressed using Bělehrádek's equation. In this study, we applied the Kontodimas equation, which successfully reproduced the effects of food scarcity at higher temperatures. Additionally, the influence of predators was incorporated into the survival rate of adult individuals. The long-term data set of Lake Biwa was input into the developed model to simulate the population fluctuations during the disruption period (1975–1979) and stable period (1995–1999) of their seasonal cycle. The combination of environmental data to be input was (1) water temperature, food availability, and predators; (2) water temperature and food availability; and (3) water temperature and predators. Disruptions in the seasonal cycle of the population were only observed in scenario (1) during the disruption period simulation, suggesting that the disrupted seasonal cycle of this species in Lake Biwa may have been caused by the effects of both food condition and predators. The results of simulation scenarios (2) and (3) indicated that predators have a stronger impact on the population than food availability. This time, we used common and simple indicators to describe food conditions and predators, but the model can be improved to be more complex and accurate as more data become available. Such models are important tools for understanding the relationship between environmental factors and the dynamics of diaptomid copepod populations. [ABSTRACT FROM AUTHOR]

The seasonal cycle (SC) of surface air temperature is a substantial element in climatology. Some basic and important topics in climate change studies are based on accurate and reliable estimation of SCs, such as percentile‐based indices of extremes and probability density function (PDF) changes of daily temperatures. For both of them, most studies characterized SCs using averages of multi‐days windows, which is not smooth and accurate enough representing the extreme thresholds and climatological normal of SCs. It is necessary to construct smooth and reasonable SCs for more accurate estimation of temperature changes on extreme thresholds and PDFs. In this study, we propose a flexible method based on generalized additive models for location scale and shape and penalized b‐spline smoothing technique with respective distributions to construct smooth SCs and SC for extreme temperatures (SCETs). The accuracy of the constructed smooth SCETs is good with the estimation biases of percentiles tending to be zero. The constructed smooth SCET also exhibits good stability over time, such that the magnitude changes of temperatures on each calendar day are close to climatic changes of mean temperature when the concerned period shifts. Based on the constructed smooth SCs, climatic changes by seasons and PDFs between two periods, 1961–1990 and 1991–2020, are examined over China. The increase of thresholds for hot extremes in spring during the recent period is prominent, while the increase of thresholds for daytime cold extremes in summer over a part of central to southern China is also notable. The smooth SCs and SCETs based on our flexible statistical modelling framework can characterize daily extreme temperatures reasonably and accurately, and should be expected to have more applications for a better understanding of climate changes related to distributions and seasonal cycles. [ABSTRACT FROM AUTHOR]

In the European Mediterranean Region, palm trees are a common element in cities and semi-urban landscapes and have become important habitat structures for local fauna. This study aimed to monitor the invertebrate and vertebrate fauna occurring on and associated with ornamental palms of the genus Phoenix, over the course of one year. Five study sites were used in southern Spain, with varying levels of management. Several complementary methods were applied monthly in order to assess the vertebrates and invertebrates associated with the full seasonal cycle of palms, including flowering and fruiting. The study resulted in the identification of 216 invertebrate families from seven different classes and 89 vertebrate species, consisting of 62 bird, 20 mammal (including bats), six reptile and one amphibian species associated with Phoenix palms. It thus highlights that Phoenix palms provide a habitat for many species and individuals over the course of one year. [ABSTRACT FROM AUTHOR]

Abstract We revisit the nature of the ocean bottom pressure (pb) seasonal cycle by leveraging the mounting GRACE‐based pb record and its assimilation in the ocean state estimates produced by the project for Estimating the Circulation and Climate of the Ocean (ECCO). We focus on the mean seasonal cycle from both data and ECCO estimates, examining their similarities and differences and exploring the underlying causes. Despite substantial year‐to‐year variability, the 21‐year period studied (2002–2022) provides a relatively robust estimate of the mean seasonal cycle. Results indicate that the pb annual harmonic tends to dominate but the semi‐annual harmonic can also be important (e.g., subpolar North Pacific, Bellingshausen Basin). Amplitudes and short‐scale phase variability are enhanced near coasts and continental shelves, emphasizing the importance of bottom topography in shaping the seasonal cycle in pb. Comparisons of GRACE and ECCO estimates indicate good qualitative agreement, but considerable quantitative differences remain in many areas. The GRACE amplitudes tend to be higher than those of ECCO typically by 10%–50%, and by more than 50% in extensive regions, particularly around continental boundaries. Phase differences of more than 1 (0.5) months for the annual (semiannual) harmonics are also apparent. Larger differences near coastal regions can be related to enhanced GRACE data uncertainties and also to the absence of gravitational attraction and loading effects in ECCO. Improvements in both data and model‐based estimates are still needed to narrow present uncertainties in pb estimates.

Estimates of soil moisture from two National Oceanic and Atmospheric Administration (NOAA) models are compared to in situ observations. The estimates are from a high-resolution atmospheric model with a land surface model [High-Resolution Rapid Refresh (HRRR) model] and a hydrologic model from the NOAA Climate Prediction Center (CPC). Both models produce wetter soils in dry regions and drier soils in wet regions, as compared to the in situ observations. These soil moisture differences occur at most soil depths but are larger at the deeper depths below the surface (100 cm). Comparisons of soil moisture variability are also assessed as a function of soil moisture regime. Both models have lower standard deviations as compared to the in situ observations for all soil moisture regimes. The HRRR model's soil moisture is better correlated with in situ observations for drier soils as compared to wetter soils—a trend that was not present in the CPC model comparisons. In terms of seasonality, soil moisture comparisons vary depending on the metric, time of year, and soil moisture regime. Therefore, consideration of both the seasonality and soil moisture regime is needed to accurately determine model biases. These NOAA soil moisture estimates are used for a variety of forecasting and societal applications, and understanding their differences provides important context for their applications and can lead to model improvements. Significance Statement: Soil moisture is an essential variable coupling the land surface to the atmosphere. Accurate estimates of soil moisture are important for forecasting near-surface temperature and moisture, predicting where clouds will form, and assessing drought and fire risks. There are multiple estimates of soil moisture available, and in this study, we compare soil moisture estimates from two different National Oceanic and Atmospheric Administration (NOAA) models to in situ observations. These comparisons include both soil moisture amount and variability and are conducted at several soil depths, in different soil moisture regimes, and for different seasons and years. This comprehensive assessment allows for an accurate assessment of biases within these models that would be missed when conducting analyses more broadly. [ABSTRACT FROM AUTHOR]

Negative Indian Ocean Dipole (nIOD) can exert great impacts on global climate and can also strongly influence the climate in China. Early nIOD is a major type of nIOD, which can induce more pronounced climate anomalies in summer than La Niña-related nIOD. However, the characteristics and triggering mechanisms of early nIOD are unclear. Our results based on reanalysis datasets indicate that the early nIOD and La Niña-related nIOD are the two major types of nIOD, and the former accounts for over one third of all the nIOD events in the past six decades. These two types of nIODs are similar in their intensities, but are different in their spatial patterns and seasonal cycles. The early nIOD, which develops in spring and peaks in summer, is one season earlier than the La Niña-related nIOD. The spatial pattern of the wind anomaly associated with early nIOD exhibits a winter monsoon-like pattern, with strong westerly anomalies in the equatorial Indian Ocean and eastly anomalies in the northern Indian Ocean. Opposite to the triggering mechanism of early positve IOD, the early nIOD is induced by delayed Indian summer monsoon onset. The results of this study are helpful for improving the prediction skill of IOD and its climate impacts. [ABSTRACT FROM AUTHOR]

While changing lake surface conditions have received significant research scrutiny, changes in subsurface conditions, including stratification and heat content, remain largely unexplored. In this work, we highlight changes in thermal structure, stratification dynamics, and ice characteristics in the Laurentian Great Lakes (Lakes Superior, Huron, Michigan, Erie, and Ontario) as simulated between 1979 and 2021. Three-dimensional lake hydrodynamics and ice cover were modeled using the Finite Volume Community Ocean Model (FVCOM) coupled with the Los Alamos sea ice model (CICE). Analysis revealed significant increases in surface (0.4°–0.6°C decade−1) and subsurface (0.1°–0.4°C decade−1) temperatures as well as dramatic losses in ice cover (1%–8% decade−1) and ice volume (0–3 km3 decade−1) over the last 40 years. Estimated surface heating rates were strongest during the summer and fall, while subsurface warming was most rapid during the nearly isothermal winter and spring. Intensified (decreased) summer (winter) stratification led to shifts in lake turnover dynamics, with delayed fall turnover dates (2–6 days decade−1) and earlier spring overturn dates (2–9 days decade−1). Modeled surface temperatures (LST), bottom temperatures (LBT), and annual averaged ice cover (AAIC) were used to estimate low-frequency climate signals, which were highly correlated with the Atlantic multidecadal oscillation. Warming trends fit to residual climate signals (LST: 0.1°C decade−1; LBT: 0.03°C decade−1; AAIC: −1% decade−1), calculated by removing low-frequency variability from the raw climate signal, were lower than those fit to associated low-frequency components, suggesting that recent climate change in the Great Lakes may be strongly influenced by natural multidecadal climate variability. [ABSTRACT FROM AUTHOR]

The intertropical convergence zone (ITCZ), with its twice-annual passage over central Africa, is considered as the main driver of the rainfall seasonality. In this ITCZ paradigm, high rainfall occurs over regions of large low-level convergence. But recently, this paradigm was challenged over central Africa. Here, we show that a shallow meridional overturning circulation—driven by surface conditions—plays a thermodynamical control on the rainfall seasonality over central Africa. Indeed, due to the local evaporative cooling effect, the foot of the ascending branch of Hadley cells occurs where the temperature is the warmest, indicating a thermal low. This distorts the southern Hadley cell by developing its bottom-heavy structure. As result, both shallow and deep Hadley cells coexist over central Africa year-round. The deep mode is associated with the poleward transport of atmospheric energy at upper levels. The shallow mode is characterized by a shallow meridional circulation, with its moisture transport vanishing and converging in the midtroposphere rather than at lower troposphere. This midtropospheric moisture convergence is also the dominant component that shapes the vertically integrated moisture flux convergence, with little contribution of African easterly jets. This convergence zone thus controls the precipitating convection. Its meridional migration highlights the interhemispheric rainfall contrast over central Africa and outlines the unimodal seasonality. On the other hand, forced by the Congo basin cell, the precipitable water regulates the deep convection from the vegetated surface of Congo basin, acting as a continental sea. This nonlinear mechanism separates the rainfall into three distinct regimes: the moisture-convergence-controlled regime, with convective rainfall exclusively occurring in the rainy season; the local evaporation-controlled regime with drizzle in the dry season; and the precipitable-water-controlled regime, with exponential rainfall increase in the dry season. [ABSTRACT FROM AUTHOR]

The latest generation of climate models continue to exhibit biases in their representation of climatological sea surface temperature (SST), affecting their ability to simulate climate variability including the Indian Ocean Dipole which is typically too strong. Here, we analyze the surface layer heat budget of the Indian Ocean to diagnose the processes leading to biases in climatological SST biases in 20 Coupled Model Intercomparison Project Phase 6 (CMIP6) models, in comparison to a suite of observational and reanalysis products. In the western tropical Indian Ocean, we find that weaker than observed winds reduce the strength of surface currents leading to warm SST bias. In the south‐eastern tropical Indian Ocean, overly strong southeasterly winds are associated with overestimated coastal upwelling that increases cooling across CMIP6 models. In the Arabian Sea, overly strong surface winds increase latent heat loss and leads to cool SST biases. We also analyze other regions like the Bay of Bengal, where a persistent cool bias cannot be explained by seasonal heat budgets, and southern Indian Ocean, where overly strong surface winds are responsible for cool SST biases. These biases in surface processes are supported by intermodel relationships between relevant variables, thus explaining differences in simulating the climatological SSTs across the model ensemble. Our analysis suggests that biases in atmospheric processes in particular surface winds are a primary cause of biases in Indian Ocean SST. Reducing these biases would improve the simulation of climate variability in the Indian Ocean toward more reliable climate projections and predictions. Plain Language Summary: Climate models still have difficulties in accurately representing sea surface temperatures (SST) and climate patterns in the Indian Ocean. By examining the surface‐layer heat balance of the Indian Ocean in 20 CMIP6 climate models, a suite of observational products, and inter‐model relationships, we investigate why the models simulate climatological SST that is too high or too low in different regions at different times of the year. We discovered that in the western tropical Indian Ocean, the models underestimate the strength of surface currents due to weaker winds, which leads to warmer SST than observed in some months. In the southeastern tropical Indian Ocean, the models overestimate the strength of southeasterly winds, causing stronger coastal upwelling and increased cooling, resulting in cold biases. In the Arabian Sea, the models simulate excessively strong surface winds, leading to more heat loss and cooler SST. These findings highlight the relationship between atmospheric and surface ocean processes in setting SST biases in the Indian Ocean. Key Points: Climate models show biases in Indian Ocean (IO) sea surface temperatures (SST) affecting representation of climate variabilityWeaker winds lead to warm SST biases in western tropical IO while stronger winds cause cool biases in Arabian Sea and southeast tropical IOThe seasonally varying wind driven mechanism leading to SST bias is different in each region analyzed [ABSTRACT FROM AUTHOR]

The seasonal cycle in temperature is a large and well-observed response to radiative forcing, suggesting its potential as a natural analog to human-caused climate change. Although there have been advances constraining some climate feedback parameters using seasonal observations, the seasonal cycle has not been used to inform about the local temperature sensitivity to greenhouse gas forcing. In this study, we uncover a nonlinear relationship between the amplitude and phase of the seasonal cycle and forced temperature trends in seven CMIP5-era large ensembles across the Northern Hemisphere extratropical continents. We develop a mixture energy balance model that reproduces this relationship and reveals the unexpected finding that the phasing of the seasonal cycle-in addition to the amplitude-contains information about local temperature sensitivity to seasonal forcing over land. Using this energy balance model framework, we compare the pattern and magnitude of the seasonally inferred sensitivity of the surface temperature response to anthropogenic radiative forcing. The seasonally constrained model largely reproduces the pattern of human-caused temperature trends seen in climate models (r = 0.81, p value < 0.01), including polar amplification, but the magnitude of the response is smaller by about a factor of 3. Our results show the relevance of both phasing and amplitude for constraining patterns of local feedbacks and suggest the utility of additional research to better understand the differences in sensitivity between seasonal and greenhouse gas forcing. [ABSTRACT FROM AUTHOR]

The present study reconstructs the river discharge climatology and its respective historical series for all rivers of the Adriatic Sea with averaged climatological daily river discharge above 1 m3s−1, to reach a better representation of the Adriatic rivers in hydrodynamic models and, consequently, to develop a more realistic freshwater balance in the different regions of the hydrographic basin. Based on the European Flood Awareness System (EFAS) data set, a careful method of identification and selection of the Adriatic rivers, followed by a rigorous assessment against observational data, was developed to evaluate the current state of the Adriatic river discharges and their respective trends throughout several climate indicators from 1991 to 2022. Observational data are limited to 85% of the identified rivers, totaling 98% of the overall freshwater input into the Adriatic Sea. The results confirm that the Shallow Northern Adriatic receives the largest freshwater inputs with a daily average exceeding 2,400 m3s−1, which amounts to 61% of the overall Adriatic discharges. Consequently, this region guides the freshwater seasonal cycle of the Adriatic Sea, which presents a well-defined pattern of two flood peaks in late autumn and late spring, separated by a minimum discharge period at mid-summer. From the Central to the Southern Adriatic subregions, the absence of snow-melting effects prevents the secondary flood peak during the spring, shaping the seasonal cycle of river discharges from a single flood peak in late autumn to a drought period in August. The 32 years of continuous river discharge data reveal a negligible trend in the overall Adriatic Sea but a negative trend for the last decade (2013–2022). This decadal decrease is driven by the extreme drought that drastically pounded the northern Adriatic in 2022.

The results of research on the reproductive dynamics of the key amphibian species of the Ukrainian Roztochchia are presented. Since reproduction is one of the most important and key stages of the seasonal cycle of amphibians, special attention was paid to this period. We used classic and typical methods of recording reproductive activity of amphibians: route records, searching for dead amphibians on the roads, vocalization methods and installation of temporary protective barriers that prevent amphibians from crossing the road. Therefore, amphibians of the genera Rana and Bufo belong to the species with a sudden type of reproduction. We included representatives of the genera Lissotriton, Triturus, Bombina, Hyla, and Pelophylax to the long-term breeding species. In particular, temporary protective barriers gave us indicative and clear concepts regarding the temporal peaks and troughs of reproductive migrations of the studied amphibian species, as well as the direction of movement to reproductive and trophic habitats. Comparing the beginning of reproductive activity and its course throughout the season, we can see certain differences between the model species B. bufo and R. temporaria, in particular, the choice of breeding ponds, the time of spawning and the period of activity of sexually active individuals. Reproductive activity of the common frog occurs in the first half of March — mid-April. In the second half of April, we caught common frogs on both sides of the barriers, which indicates a “turning point” in the sexual activity of this species. Although the common toad is the first to appear after hibernation, spawning occurs approximately a decade later than that of the common frog but takes a little longer. We believe that such research should be continued regularly and our results will encourage herpetologists to further and long-term research.

This study examines the annual cycle of monsoon precipitation simulated by models from phase 6 of the Coupled Model Intercomparison Project (CMIP6), then uses moist energy diagnostics to explain globally inhomogeneous projected future changes. Rainy season characteristics are quantified using a consistent method across the globe. Model bias is shown to include rainy season onsets tens of days later than observed in some monsoon regions (India, Australia, and North America) and overly large summer precipitation in others (North America, South America, and southern Africa). Projected next-century changes include rainy season lengthening in the two largest Northern Hemisphere monsoon regions (South Asia and central Sahel) and shortening in the two largest SouthernHemisphere regions (South America and southern Africa). Changes in the North American and Australian monsoons are less coherent across models. To understand these changes, relative moist static energy (MSE) is defined as the difference between local and tropical-mean surface airMSE. Future changes in relativeMSEin each region correlate well with onset and demise date changes. Furthermore, Southern Hemisphere regions projected to undergo rainy season shortening are spanned by an increasing equator-to-poleMSE gradient, suggesting their rainfallwill be increasingly inhibited by fluxes of dry extratropical air; Northern Hemisphere regionswith projected lengthening of rainy seasons undergo little change in equator-topole MSE gradient. Thus, although model biases raise questions as to the reliability of some projections, these results suggest that globally inhomogeneous future changes in monsoon timing may be understood through simple measures of surface air MSE.

Abstract The Singapore Strait is located at the transition between the dominantly semidiurnal Indian Ocean and the mixed-to-diurnal South China Sea, resulting in complex tidal dynamics. In this work, we use sea-level estimates from two coastal Global Navigation Satellite Systems (GNSS) stations and one tide gauge to study tides and tidal asymmetry in the Strait. We first generate sea-level measurements from GNSS signal-to-noise ratio (SNR) data using the GNSS Interferometric Reflectometry technique, which can estimate sea-surface heights from a coastal GNSS station. Second, we perform tidal harmonic analysis and quantify tidal asymmetry based on the skewness method. Finally, we examine seasonal sea-level changes in the Strait from GNSS SNR data, tide-gauge records and satellite altimetry. Our results reveal an increase in M2 and S2 amplitudes toward the west of the Strait and a decrease in the K1 and O1 amplitudes. Our results also show that tides at the two sites in the east are ebb dominant with asymmetry originating from the O1–K1–M2 triad by astronomical forcing, whereas tidal asymmetry at the site in the west is flood dominant and mainly caused by non-linear interaction of the major tidal constituents. Analysis of seasonal sea-level changes shows that annual amplitudes in the east are around 13.6 cm, and 6.7 cm in the west. A possible explanation for the discrepancy in the amplitudes is the effect of seasonal monsoon winds flowing from the South China Sea.

AbstractAn in situ analysis of mucin secretions along the annual cycle was performed on the striped Venus clam, Chamelea gallina. Individuals of both sexes from an exploited stock of Margherita di Savoia (Southern Adriatic Sea, Central Mediterranean Sea) were made in June 2020 and 2021, and in January 2021 and 2022, representative of summer and winter seasons, respectively. Tissues from the foot and the gills were analyzed for histochemical and lectin-histochemical analyses. Staining with Periodic Acid-Schiff, Alcian Blue pH 2.5 and High-Iron-Diamine indicated that mucins from both the foot and the gills were acidic, mostly sulfated. Lectin-binding analyses with PNA, SBA, WGA, LTA, UEA-I, AAA, SNA, MAA-II and ConA indicated the presence of N-acetyl-glycosaminylated, mannosylated and fucosylated residuals in the saccharidic chains. In the gills, the amount of acidic and glycosaminylated residuals was higher in summer in both sexes, whereas fucosylation was similar along the sampling period and mannosylation was never observed. In the foot, both surface epithelial and subepidermal secreting cells increased sulfation in winter in males, but not in females. Glycosaminylation and fucosylation were observed only in the surface cells of males. Mannosylated residuals were observed in all the foot cell types in both sexes. It is hypothesized that the observed qualitative and quantitative variations in mucin secretion is linked to the reproductive cycle.

The Pacific Meridional Mode (PMM) has long been associated with extra‐tropical air‐sea coupling processes, which are thought to influence the development of El Niño‐Southern Oscillation (ENSO). Here we show that the PMM on seasonal to interannual timescales is closely associated with a newly proposed tropical mode known as the ENSO Combination mode (C‐mode), which arises from the nonlinear interaction between ENSO and the background annual cycle in the deep tropics. The PMM exhibits a remarkable resemblance with the C‐mode in atmospheric patterns, spectral characteristics, and local impacts. Based on a simple Hasselmann‐type model, we further demonstrate that the C‐mode‐related atmospheric anomalies can effectively drive PMM‐like sea surface temperature anomalies. As the C‐mode captures seasonally modulated ENSO characteristics, the seasonal‐to‐interannual PMM variability could naturally establish a connection with ENSO, thereby offering an alternative explanation for the observed relationship between PMM and ENSO. Plain Language Summary: Previous studies demonstrated that the Pacific Meridional Mode (PMM) is driven by the extratropical climate systems, which can impact the development of El Niño‐Southern Oscillation (ENSO) events in the tropics. In our study, we establish a close connection between the PMM on seasonal‐to‐interannual timescales and a tropical atmospheric mode arising from the nonlinear interaction between ENSO and the background annual cycle (the ENSO Combination mode, C‐mode). The C‐mode closely resembles the PMM in terms of atmospheric patterns and spectral characteristics. We further demonstrate that the C‐mode could drive a PMM‐like SST pattern in the tropical Pacific. Consequently, we suggest that the PMM on seasonal‐to‐interannual timescales has tropical origins, thereby offering an alternative explanation for the relationship between the conventional PMM index and the mature phase of ENSO. Key Points: The spatiotemporal features of Pacific Meridional Mode (PMM) on seasonal‐to‐interannual timescales exhibit a remarkable resemblance with those of the tropical combination modeC‐mode‐related atmospheric anomalies are capable of inducing PMM‐like sea surface temperature changes in the tropical PacificEl Niño‐Southern Oscillation (ENSO)'s interaction with the annual cycle manifests in PMM‐related air‐sea conditions, which explains the observed ENSO‐PMM linkage [ABSTRACT FROM AUTHOR]

Changes in the path and intensity of jet streams have major impacts on regional weather and climate patterns. We investigated changes in the intensity, meridional position, and altitude of the North Pacific jet in different seasons during the period 1979–2020 using the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation reanalysis (ERA5) dataset. Our analysis indicates that the intensity and the meridional position of the North Pacific jet exhibit a pronounced seasonal cycle, with the most intense core of the jet in winter and its equatorward shift from 32.75 ∘ N in winter to around 40.75 ∘ N in summer. The jet also has a relatively large latitudinal spread in spring compared to the other seasons. The North Pacific jet has only weakened over the Yellow Sea in summer during the period 1979–2020. Maximum upper-tropospheric wind speeds have intensified over the Sea of Japan in winter in response to the poleward shift of the jet but weakened in spring due to the equatorward shift of the jet. Indeed, the jet has shifted poleward over the far western (125–140 ∘ E) and central (180 ∘ -150 ∘ W) North Pacific in winter, but the poleward shift of the jet is smaller over the far western North Pacific where the jet is stronger. This suggests that there might be a link between the speed of the North Pacific jet and the magnitude of its longitudinal poleward shifting variability. The jet has also shifted poleward over the central-eastern North Pacific (135–155 ∘ W) in summer, while changes in the altitude of the North Pacific jet have been insignificant during the period 1979–2020. The identified changes in the characteristics of the North Pacific jet have important implications for the understanding of weather patterns and the frequency of extreme events in the North Pacific and nearby regions. [ABSTRACT FROM AUTHOR]

The mechanism that determines the dynamics of subsurface chlorophyll maximum depth (zSCM) has long been debated. Although a coupling between zSCM and the top of nitracline (znit) has been widely observed in the open ocean, a co‐location of zSCM and an isolume depth (ziso) has often been reported in oligotrophic waters. In this study, based on continuous observations of ten BGC‐Argo floats, we found that the seasonal displacement of zSCM in all subtropical gyres was driven mainly by light, but zSCM displayed a nutrient‐driven pattern occasionally when znit became shallower than ziso. We therefore proposed a "two‐group competition framework": zSCM in subtropical gyres is determined by the competition of two phytoplankton groups, nutrient‐sensitive picoeukaryotes and light‐sensitive Prochlorococcus. When znit (ziso) is shallower than ziso (znit), picoeukaryotes (Prochlorococcus) dominate the chlorophyll biomass at the SCM, and thus zSCM follows znit (ziso). This paradigm reconciles the inconsistent conclusions drawn from earlier studies. Plain Language Summary: Phytoplankton growth requires both light and nutrients. In most open oceans, the vertical distribution of the chlorophyll‐a concentration generally is a maximum at a subsurface depth because of nutrient depletion in surface waters and inadequate light at depth. We took advantage of the continuous observations from autonomous profiling floats of the chlorophyll maximum depth in oligotrophic subtropical oceans. Our analysis of those data showed that the depth of the chlorophyll maximum depth in these areas usually followed either the depth where there was enough light for phytoplankton to grow or the depth where there were enough nutrients for them to grow. This discovery suggests that two different groups of phytoplankton determine where the chlorophyll maximum appears. One group is sensitive to nutrient supply and responds more quickly to variations of nutrient supply than of light, and the other group is sensitive to light availability and responds more quickly to variations of light than of nutrient supply. The depth of the chlorophyll maximum is determined by the interaction between light and nutrient availability, which determines which group dominates. Key Points: The displacement of subsurface chlorophyll maximum (SCM) depth in subtropical gyres is mainly driven by the isolume depth, which is generally above the top of nitraclineThe top of nitracline impacts the SCM depth when it occasionally becomes above the isolume depth, displaying a nutrient‐driven SCM patternThe dynamics of SCM depth are likely due to the competition of light‐sensitive Prochlorococcus and nutrient‐sensitive picoeukaryotes [ABSTRACT FROM AUTHOR]

Accurate assessment of the size and distribution of carbon dioxide (CO2) sources and sinks is important for efforts to understand the carbon cycle and support policy decisions regarding climate mitigation actions. Satellite retrievals of the column-averaged dry-air mole fractions of CO2 (XCO2) have been widely used to infer spatial and temporal variations of carbon fluxes through atmospheric inversion techniques. In this study, we present a global spatially resolved terrestrial and ocean carbon flux dataset for 2015–2022. The dataset was generated by the Global ObservatioN-based system for monitoring Greenhouse GAses (GONGGA) atmospheric inversion system through the assimilation of Orbiting Carbon Observatory 2 (OCO-2) XCO2 retrievals. We describe the carbon budget, interannual variability, and seasonal cycle for the global scale and a set of TransCom regions. The 8-year mean net biosphere exchange and ocean carbon fluxes were −2.22 ± 0.75 PgC yr−1 and –2.32 ± 0.18 PgC yr−1, absorbing approximately 23 % and 24 % of contemporary fossil fuel CO2 emissions, respectively. The annual mean global atmospheric CO2 growth rate was 5.17 ± 0.68 PgC yr−1, which is consistent with the National Oceanic and Atmospheric Administration (NOAA) measurement (5.24 ± 0.59 PgC yr−1). Europe has the largest terrestrial sink among the 11 TransCom land regions, followed by Boreal Asia and Temperate Asia. The dataset was evaluated by comparing posterior CO2 simulations with the observations from Total Carbon Column Observing Network (TCCON) and Observation Package (ObsPack). Compared with CO2 simulations using the unoptimized fluxes, the bias and root mean square error of posterior CO2 simulations were largely reduced across the full range of locations, confirming that the GONGGA system improves the estimates of spatial and temporal variations in carbon fluxes by assimilating OCO-2 XCO2 data. This dataset will improve the broader understanding of global carbon cycle dynamics and their response to climate change. [ABSTRACT FROM AUTHOR]

While the seasonal testicular cycle has been well studied regarding internal components, no attention has been given to the testicular capsule (tunica albuginea and tunica serosa). This study elucidated the structure‐function modulations of intra‐testicular functions by its capsule in the finch red munia (Amandava amandava) during the annual testicular cycle. The birds were studied during breeding (preparatory and breeding) and nonbreeding (regressive and quiescent) reproductive phases using hematoxylin‐eosin and acridine orange‐ethidium bromide capsule staining, hormonal ELISA (LH and testosterone) and immunohistochemical expression of neuropeptides (GnRH, GnIH) and androgen receptor (AR). The thickness of the tunica albuginea was significantly increased with multiple myoid layers during the nonbreeding phases (p < 0.05). The thickness of the tunica serosa was not altered, although characteristics and distribution of squamous cells showed significant seasonal alterations. Immunoreactive (‐ir) AR and GnIH cells were differentially localized on both layers of the capsule. Strong AR‐ir cells on tunica serosa during breeding phases showed increased expression of the receptor; a significant increase in plasma LH and testosterone was also observed during the breeding cycle (p < 0.01). Contrarily, intense GnIH‐ir cells on both the capsular layers peaked during testicular regression. Differential structural alterations of the testicular capsule provide mechanical support and help maintain internal homeostasis in tune with changing seasons. The seasonal expressions and alterations of reproduction‐related receptors, hormones, and neuropeptides provide evidence for the potential regulatory roles of the capsule in the peripheral modulation of intratesticular functions. Highlights: Differential AR and GnIH expression suggest capsular sensitivity to seasonal cuesBreeding phase AR expression indicates local testicular maintenance by testosteroneNonbreeding phase GnIH expression suggests capsular role in testicular regression [ABSTRACT FROM AUTHOR]

The Pacific-North American (PNA) teleconnection pattern is one of the prominent atmospheric circulation modes in the extratropical Northern Hemisphere, and its seasonal to interannual predictability is suggested to originate from El Niño-Southern Oscillation (ENSO). Intriguingly, the PNA teleconnection pattern exhibits variance at near-annual frequencies, which is related to a rapid phase reversal of the PNA pattern during ENSO years, whereas the ENSO sea surface temperature (SST) anomalies in the tropical Pacific are evolving much slower in time. This distinct seasonal feature of the PNA pattern can be explained by an amplitude modulation of the interannual ENSO signal by the annual cycle (i.e., the ENSO combination mode). The ENSO-related seasonal phase transition of the PNA pattern is reproduced well in an atmospheric general circulation model when both the background SST annual cycle and ENSO SST anomalies are prescribed. In contrast, this characteristic seasonal evolution of the PNA pattern is absent when the tropical Pacific background SST annual cycle is not considered in the modeling experiments. The background SST annual cycle in the tropical Pacific modulates the ENSO-associated tropical Pacific convection response, leading to a rapid enhancement of convection anomalies in winter. The enhanced convection results in a fast establishment of the large-scale PNA teleconnection during ENSO years. The dynamics of this ENSO-annual cycle interaction fills an important gap in our understanding of the seasonally modulated PNA teleconnection pattern during ENSO years. [ABSTRACT FROM AUTHOR]

The seasonal properties and heat budget of marine heatwaves (MHWs) on the northern South China Sea (SCS) continental shelf are investigated. The winter MHWs are generally the warmest, gradually weakening in the following seasons. In winter and spring, all events have a temperature elevated by more than 1 °C while approximately half of the MHWs in summer and fall have temperatures elevated by less than 1 °C. The MHW duration is longest in winter, second longest in fall, and shortest in spring. Three types of MHWs have been defined based on the main heat source; i.e., air–sea heat flux dominant, ocean advection dominant, and mixed types. Air–sea heat flux is the dominant source for more than 80% of MHWs in winter and fall, ~ 70% of MHWs in spring, and ~ 50% in summer. There are slightly more ocean advection dominant events than Mixed-MHWs. Ocean advection always weakens an air–sea heat flux dominant MHW and enhances other types of events, so that the net heat supply is smallest for air–sea heat flux dominant MHW types. Ocean advection is mainly modulated by cross-slope water exchanges along the continental shelf edge. The offshore (onshore) cross-slope flow induces a negative (positive) contribution to MHW development. These results provide new insight into the seasonal cycle of MHWs on the northern SCS continental shelf. [ABSTRACT FROM AUTHOR]

Over most tropical land areas, the annual peak in precipitation occurs during summer, associated with the local monsoon circulation. However, in some coastal regions in the tropics the bulk of annual precipitation occurs in autumn, after the low-level summer monsoon westerlies have abated. Examples include the Nordeste region of Brazil, southeastern India and Sri Lanka, and coastal Tanzania. Unlike equatorial regions, they receive little rainfall during local spring. Such regions are present along the eastern coasts of nearly all continents, suggesting that they comprise a coherent yet previously unrecognized global phenomenon. In this study, we identify eight tropical locations that experience an ‘‘autumn monsoon’’ and show that this unusual seasonal cycle is generated by similar mechanisms in all of these. When these regions receive their peak rainfall, they lie poleward of the ITCZ in easterly low-level winds. The spatial structure of precipitation in these regions can be explained by their placement to the east of mountain ranges that organize moist convection on their windward sides. However, orographic forcing alone cannot explain their unique seasonal cycle: despite similarities in wind direction, surface humidity, and sea surface temperatures (SSTs) between autumn and spring, these regions receive significantly more rainfall in autumn than in spring. We show that this is due to differences in the large-scale atmospheric stability between the equinoctial seasons, which can be captured by a relative SST metric and is influenced by SSTs in the remote eastern upwelling zones of the Pacific and Atlantic Oceans.

Gross primary production (GPP) is the largest flux and a crucial player in the terrestrial carbon cycle and has been studied extensively, yet large uncertainties remain in the spatiotemporal patterns of GPP in both observations and simulations. This study evaluates the performance of the second version of the Beijing Climate Center Atmosphere−Vegetation Interaction Model (BCC_AVIM2.0) in simulating GPP on multiple spatial and temporal scales in the Coupled Model Intercomparison Project Phase 6 (CMIP6) experiments. Model simulations driven by two meteorological datasets were compared with two observation-based GPP products covering 1982–2008. Spatial patterns of annual GPP show a significant latitudinal gradient in each dataset, increasing from cold (tundra) and dry (desert) biomes to warm (temperate) and humid (tropical rainforest) biomes. BCC_AVIM2.0 overestimates GPP in most parts of the globe, especially in boreal forest regions and Southeast China, while underestimating GPP in subhumid regions in eastern South America and tropical Africa. The four datasets broadly agree on the GPP seasonal cycle, but BCC_AVIM2.0 predicts an earlier beginning of spring growth and a larger amplitude of seasonal variations than those in the observations. The observation-based datasets exhibit slight interannual variability (IAV) and weak GPP linear trends, while the BCC_AVIM2.0 simulations demonstrate relatively large year-to-year variability and significant trends in the low-latitudes and temperate monsoon regions in North America and East Asia. Regarding the possible relationships between annual means of GPP and climate factors, BCC_AVIM2.0 predicts more extensive regions of the globe where the IAV of annual GPP is dominated by precipitation, especially in mid-to-high latitudes of the Northern Hemisphere and tropical Africa, while the observed GPP in the above regions is temperature- or radiation-dominant. The positive GPP biases due to earlier spring growth in boreal forest regions and negative GPP biases in off-equator tropical areas in the BCC_AVIM2.0 simulations imply that cold stress on biomes in boreal mid-to-high latitudes should be strengthened to restrain plant growth, while drought stress in low-latitude regions might be eased to enhance plant production in the future version of BCC_AVIM.

The seasonal fluctuations of the copepod Eodiaptomus japonicus, which dominates the zooplankton community of Lake Biwa, have been disrupted several times over the past 45 years. The aim of this study was to clarify the primary environmental factor that caused the disrupted seasonal cycle in population density of E. japonicus. Here, we tested the hypothesis that the disruption in their seasonal cycle was due to the impacts of water temperature, food conditions, and predator pressure, using an individual-based model (IBM). Based on the experimental data from the literature, we described the growth and reproduction of E. japonicus using temperature- and food-dependent functions. Previously, the developmental time of this species was expressed using Bělehrádek’s equation. In this study, we applied the Kontodimas equation, which successfully reproduced the effects of food scarcity at higher temperatures. Additionally, the influence of predators was incorporated into the survival rate of adult individuals. The long-term data set of Lake Biwa was input into the developed model to simulate the population fluctuations during the disruption period (1975–1979) and stable period (1995–1999) of their seasonal cycle. The combination of environmental data to be input was (1) water temperature, food availability, and predators; (2) water temperature and food availability; and (3) water temperature and predators. Disruptions in the seasonal cycle of the population were only observed in scenario (1) during the disruption period simulation, suggesting that the disrupted seasonal cycle of this species in Lake Biwa may have been caused by the effects of both food condition and predators. The results of simulation scenarios (2) and (3) indicated that predators have a stronger impact on the population than food availability. This time, we used common and simple indicators to describe food conditions and predators, but the model can be improved to be more complex and accurate as more data become available. Such models are important tools for understanding the relationship between environmental factors and the dynamics of diaptomid copepod populations.

Abstract The Pacific Meridional Mode (PMM) has long been associated with extra‐tropical air‐sea coupling processes, which are thought to influence the development of El Niño‐Southern Oscillation (ENSO). Here we show that the PMM on seasonal to interannual timescales is closely associated with a newly proposed tropical mode known as the ENSO Combination mode (C‐mode), which arises from the nonlinear interaction between ENSO and the background annual cycle in the deep tropics. The PMM exhibits a remarkable resemblance with the C‐mode in atmospheric patterns, spectral characteristics, and local impacts. Based on a simple Hasselmann‐type model, we further demonstrate that the C‐mode‐related atmospheric anomalies can effectively drive PMM‐like sea surface temperature anomalies. As the C‐mode captures seasonally modulated ENSO characteristics, the seasonal‐to‐interannual PMM variability could naturally establish a connection with ENSO, thereby offering an alternative explanation for the observed relationship between PMM and ENSO.

Abstract The mechanism that determines the dynamics of subsurface chlorophyll maximum depth (zSCM) has long been debated. Although a coupling between zSCM and the top of nitracline (znit) has been widely observed in the open ocean, a co‐location of zSCM and an isolume depth (ziso) has often been reported in oligotrophic waters. In this study, based on continuous observations of ten BGC‐Argo floats, we found that the seasonal displacement of zSCM in all subtropical gyres was driven mainly by light, but zSCM displayed a nutrient‐driven pattern occasionally when znit became shallower than ziso. We therefore proposed a “two‐group competition framework”: zSCM in subtropical gyres is determined by the competition of two phytoplankton groups, nutrient‐sensitive picoeukaryotes and light‐sensitive Prochlorococcus. When znit (ziso) is shallower than ziso (znit), picoeukaryotes (Prochlorococcus) dominate the chlorophyll biomass at the SCM, and thus zSCM follows znit (ziso). This paradigm reconciles the inconsistent conclusions drawn from earlier studies.

The Tibetan Plateau (TP) precipitation is experiencing the north‐south dipole tendency pattern since 1979. In this study, we identify four primary seasonally evolving patterns (SEPs) that explain approximately 50% of the total variance in precipitation variability over the TP. These SEPs contribute 60%–90% of the spatial mean amplitude of precipitation trends across seasons. In particular, the second SEP that features a north‐south dipole pattern dominates the annual mean trend of the precipitation over the TP. The interdecadal variability of the seasonally evolving north‐south dipole pattern is linked to the interdecadal variations of summer Silk Road Pattern and Indian monsoon. These findings suggest that the climate variability expressed through SEPs could potentially serve as a significant source for the interdecadal rainfall prediction. Plain Language Summary: The Tibetan Plateau (TP) is experiencing the north‐wetting‐south‐drying trend due to the imbalance of the Asian water tower since 1979, influencing the water supply to billions of people and regional and global climate. However, the characteristics of the seasonally evolving variations of precipitation across seasons on multiyear timescales, as well as the associated major circulation patterns, remain unknown. Here we identify four primary seasonally evolving patterns (SEPs) and focus on investigating their corresponding long‐term trends and interdecadal variations. These four modes collectively contribute by 60%–90% of the spatial mean amplitude of precipitation trends across seasons. In particular, the trend of the second SEP that features a north‐south dipole explains the spatio‐temporal disparity of the total precipitation trend, displaying the strongest amplitude in summer over the TP. Our findings provide insight into the climate variability manifested in SEPs as a major source for the interdecadal prediction of rainfall evolution in the Asian water tower. Key Points: Seasonally evolving patterns (SEPs) explain 60%–90% of the spatial mean amplitude of total precipitation trend over the Tibetan PlateauThe second SEP trend with a north‐south dipole pattern mainly contributes to the spatio‐temporal disparity of the total precipitation trendThe seasonally evolving north‐south dipole trend is linked to the Silk Road pattern and the Indian monsoon variations [ABSTRACT FROM AUTHOR]

Tropical forests play a pivotal role in regulating the global carbon cycle. However, the response of these forests to changes in absorbed solar energy and water supply under the changing climate is highly uncertain. Three‐year (2018–2021) spaceborne high‐resolution measurements of solar‐induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI) provide a new opportunity to study the response of gross primary production (GPP) and more broadly tropical forest carbon dynamics to differences in climate. SIF has been shown to be a good proxy for GPP on monthly and regional scales. Combining tropical climate reanalysis records and other contemporary satellite products, we find that on the seasonal timescale, the dependence of GPP on climate variables is highly heterogeneous. Following the principal component analyses and correlation comparisons, two regimes are identified: water limited and energy limited. GPP variations over tropical Africa are more correlated with water‐related factors such as vapor pressure deficit (VPD) and soil moisture, while in tropical Southeast Asia, GPP is more correlated with energy‐related factors such as photosynthetically active radiation (PAR) and surface temperature. Amazonia is itself heterogeneous: with an energy‐limited regime in the north and water‐limited regime in the south. The correlations of GPP with climate variables are supported by other observation‐based products, such as Orbiting Carbon Observatory‐2 (OCO2) SIF and FluxSat GPP. In each tropical continent, the coupling between SIF and VPD increases with the mean VPD. Even on the interannual timescale, the correlation of GPP with VPD is still discernable, but the sensitivity is smaller than the intra‐annual correlation. By and large, the dynamic global vegetation models in the TRENDY v8 project do not capture the high GPP seasonal sensitivity to VPD in dry tropics. The complex interactions between carbon and water cycles in the tropics illustrated in this study and the poor representation of this coupling in the current suite of vegetation models suggest that projections of future changes in carbon dynamics based on these models may not be robust. [ABSTRACT FROM AUTHOR]

The seasonal cycle is the dominant mode of variability in the air‐sea CO2 flux in most regions of the global ocean, yet discrepancies between different seasonality estimates are rather large. As part of the Regional Carbon Cycle Assessment and Processes Phase 2 project (RECCAP2), we synthesize surface ocean pCO2 and air‐sea CO2 flux seasonality from models and observation‐based estimates, focusing on both a present‐day climatology and decadal changes between the 1980s and 2010s. Four main findings emerge: First, global ocean biogeochemistry models (GOBMs) and observation‐based estimates (pCO2 products) of surface pCO2 seasonality disagree in amplitude and phase, primarily due to discrepancies in the seasonal variability in surface DIC. Second, the seasonal cycle in pCO2 has increased in amplitude over the last three decades in both pCO2 products and GOBMs. Third, decadal increases in pCO2 seasonal cycle amplitudes in subtropical biomes for both pCO2 products and GOBMs are driven by increasing DIC concentrations stemming from the uptake of anthropogenic CO2 (Cant). In subpolar and Southern Ocean biomes, however, the seasonality change for GOBMs is dominated by Cant invasion, whereas for pCO2 products an indeterminate combination of Cant invasion and climate change modulates the changes. Fourth, biome‐aggregated decadal changes in the amplitude of pCO2 seasonal variability are largely detectable against both mapping uncertainty (reducible) and natural variability uncertainty (irreducible), but not at the gridpoint scale over much of the northern subpolar oceans and over the Southern Ocean, underscoring the importance of sustained high‐quality seasonally resolved measurements over these regions. Plain Language Summary: Changes in the seasonal cycle amplitude of surface ocean carbon dioxide partial pressure (pCO2) are described over the historical period spanning 1985–2018, using both observation‐based and model‐based estimates. We identify increasing pCO2 seasonality over most regions due to increases in anthropogenic carbon in the surface ocean. Observation‐based products indicate that there have been important high‐latitude changes in pCO2 seasonality due to perturbations to the climate system. We also find important discrepancies between observation‐based and modeled pCO2 seasonality over much of the globe that are likely associated with systematic biases in model representations of the surface dissolved inorganic carbon (DIC) seasonal cycle and the ratio of total alkalinity to DIC. Both reducible and irreducible forms of uncertainty associated with monitoring pCO2 seasonality changes are quantified, highlighting the need for sustained, seasonally unbiased measurements over the high latitudes as part of an optimized marine carbon observing system. Key Points: pCO2 seasonal cycle amplitude changes over 1985–2018 are detectable against both mapping uncertainty and natural variability uncertaintyThe dominant driver of pCO2 amplitude increases over decadal timescales is attributed to the direct effect of Cant invasionA discrepancy is found with surface dissolved inorganic carbon (DIC) seasonality being systematically less in global ocean biogeochemistry models than in surface DIC observation‐based products [ABSTRACT FROM AUTHOR]

The Singapore Strait is located at the transition between the dominantly semidiurnal Indian Ocean and the mixed-to-diurnal South China Sea, resulting in complex tidal dynamics. In this work, we use sea-level estimates from two coastal Global Navigation Satellite Systems (GNSS) stations and one tide gauge to study tides and tidal asymmetry in the Strait. We first generate sea-level measurements from GNSS signal-to-noise ratio (SNR) data using the GNSS Interferometric Reflectometry technique, which can estimate sea-surface heights from a coastal GNSS station. Second, we perform tidal harmonic analysis and quantify tidal asymmetry based on the skewness method. Finally, we examine seasonal sea-level changes in the Strait from GNSS SNR data, tide-gauge records and satellite altimetry. Our results reveal an increase in M2 and S2 amplitudes toward the west of the Strait and a decrease in the K1 and O1 amplitudes. Our results also show that tides at the two sites in the east are ebb dominant with asymmetry originating from the O1–K1–M2 triad by astronomical forcing, whereas tidal asymmetry at the site in the west is flood dominant and mainly caused by non-linear interaction of the major tidal constituents. Analysis of seasonal sea-level changes shows that annual amplitudes in the east are around 13.6 cm, and 6.7 cm in the west. A possible explanation for the discrepancy in the amplitudes is the effect of seasonal monsoon winds flowing from the South China Sea. [ABSTRACT FROM AUTHOR]

Tropical rainfall variations are of direct societal relevance and drive climate variations worldwide via teleconnections. The convective rainfall tends to occur when sea surface temperature (SST) exceeds a threshold, SSTthr, usually taken to be constant in time and space. We analyze 40-yr monthly observations and find that SSTthr varies by up to 48C in space and with season. Based on local convective instability, we develop a quantitative theory that largely explains the SSTthr variations using the climatological state of the tropical atmosphere. Although it is often assumed that spatial variations of tropical upper-tropospheric temperature are small and can be neglected, it is shown that lower climatological values favor a lower SSTthr. Similarly, a small increase in climatological surface relative humidity also leads to a decrease in SSTthr, as does a lower climatological air–sea temperature difference. Consequently, efforts to understand and predict natural or forced variations in tropical rainfall must account for, in addition to SST, the temperatures aloft and the near-surface humidity and temperature and requires improved understanding of what controls their distribution in space and time. [ABSTRACT FROM AUTHOR]

A positive trend in time has been noted in the seasonal amplitude of surface ocean pCO2 over much of the oceans, which is expected to have detrimental impacts on marine ecosystems. To determine whether or not this has an anthropogenic cause, this study investigates historical climate simulations from the Detection and Attribution Model Intercomparison Project with and without anthropogenic forcing. The simulations with anthropogenic forcing show clear evidence of positive trends, whereas the simulations with constant preindustrial atmospheric CO2 and natural external forcing give only negligible trends. A statistical analysis of five zonal latitudinal bands reveals that the trends detected over 1990–2014 in an ensemble of six observational products are attributable to anthropogenic forcing in mid‐latitudes (40°N–10°N, 10°S–40°S), while no trends are detected and modeled in the tropics and the Southern Ocean. Most models fail to represent the sign of the observed climatological mean seasonal cycle difference in high latitudes. Plain Language Summary: Global warming due to fossil fuel use is unequivocal and documented by long records. In contrast, measurements for other important Earth system parameters are only available over recent decades. A short record length makes the attribution of observed trends to human‐induced forcing challenging. Trends may be hard to identify due to chaotic Earth system variability. The seasonal amplitude of the partial pressure of CO2 (pCO2) in the surface ocean is observed to increase, with global‐scale data available since 1990. A continued increase is expected to have negative impacts on fish as the amplified seasonality leads to very high pCO2, hindering the uptake of oxygen during breathing. Here, we analyze pCO2 from climate model historical simulations forced by human‐caused and natural factors versus simulations with natural factors only. The results allow us to firmly attribute the observed trend in the pCO2 seasonal amplitude in mid‐latitudes to human activities. Key Points: Trends in seasonal amplitudes of surface ocean pCO2 are analyzed in observations and CMIP6 simulations with/without anthropogenic forcingApplying an Analysis of Covariance, the observed trends in mid‐latitude regions are firmly attributed to anthropogenic forcingThe model ensemble shows large data‐model and model‐model discrepancies in the pCO2 seasonal cycle, in particular in high‐latitude regions [ABSTRACT FROM AUTHOR]

A positive trend in time has been noted in the seasonal amplitude of surface ocean pCO2 over much of the oceans, which is expected to have detrimental impacts on marine ecosystems. To determine whether or not this has an anthropogenic cause, this study investigates historical climate simulations from the Detection and Attribution Model Intercomparison Project with and without anthropogenic forcing. The simulations with anthropogenic forcing show clear evidence of positive trends, whereas the simulations with constant preindustrial atmospheric CO2 and natural external forcing give only negligible trends. A statistical analysis of five zonal latitudinal bands reveals that the trends detected over 1990–2014 in an ensemble of six observational products are attributable to anthropogenic forcing in mid‐latitudes (40°N–10°N, 10°S–40°S), while no trends are detected and modeled in the tropics and the Southern Ocean. Most models fail to represent the sign of the observed climatological mean seasonal cycle difference in high latitudes. Plain Language Summary: Global warming due to fossil fuel use is unequivocal and documented by long records. In contrast, measurements for other important Earth system parameters are only available over recent decades. A short record length makes the attribution of observed trends to human‐induced forcing challenging. Trends may be hard to identify due to chaotic Earth system variability. The seasonal amplitude of the partial pressure of CO2 (pCO2) in the surface ocean is observed to increase, with global‐scale data available since 1990. A continued increase is expected to have negative impacts on fish as the amplified seasonality leads to very high pCO2, hindering the uptake of oxygen during breathing. Here, we analyze pCO2 from climate model historical simulations forced by human‐caused and natural factors versus simulations with natural factors only. The results allow us to firmly attribute the observed trend in the pCO2 seasonal amplitude in mid‐latitudes to human activities. Key Points: Trends in seasonal amplitudes of surface ocean pCO2 are analyzed in observations and CMIP6 simulations with/without anthropogenic forcingApplying an Analysis of Covariance, the observed trends in mid‐latitude regions are firmly attributed to anthropogenic forcingThe model ensemble shows large data‐model and model‐model discrepancies in the pCO2 seasonal cycle, in particular in high‐latitude regions [ABSTRACT FROM AUTHOR]

The North Pacific storm-track activity is suppressed substantially under the excessively strong westerlies to form a distinct minimum in midwinter, which seems inconsistent with linear baroclinic instability theory. This “midwinter minimum” of the storm-track activity has been intensively investigated for decades as a test case for storm-track dynamics. However, the mechanisms controlling it are yet to be fully unveiled and are still under debate. Here we investigate the detailed seasonal evolution of the climatological density of surface migratory anticyclones over the North Pacific, in comparison with its counterpart for cyclones, based on a Lagrangian tracking algorithm. We demonstrate that the frequency of surface cyclones over the North Pacific maximizes in midwinter, whereas that of anticyclones exhibits a distinct midwinter minimum under the upstream influence, especially from the Japan Sea region. In midwinter, it is only on such a rare occasion that prominent weakening of the East Asian winter monsoon allows a migratory surface anticyclone to form over the Japan Sea, despite the unfavorable climatological-mean conditions due to persistent monsoonal cold-air outbreaks and the excessively strong upper-tropospheric westerlies. The midwinter minimum of the North Pacific anticyclone density suggests that anticyclones are likely the key to understanding the midwinter minimum of the North Pacific storm-track activity as measured by Eulerian eddy statistics. [ABSTRACT FROM AUTHOR]

Recently, we presented a classification of "primitive" relative humidity (RH) profiles into eight distinct clusters over Earth's oceans, based on about 18 years (2003–20) of observations from the AIRS on NASA's Aqua satellite. Here we investigate the seasonal variability and decadal trends, both in the vertical structure of these RH profiles, and in their associated area of occurrence. Since vertical structures (except in the marine boundary layer) of each RH class are generally robust across all seasons and change only weakly in a warming climate, seasonal or decadal changes to their occurrence areas shift patterns of global moisture distribution. Globally, the marine boundary layer exhibits nonlinear moistening effects after about 2010, the end of the warming hiatus. Annual time series of ocean areas dominated by RH classes have linear trends, which are positive only for the most moist and driest RH classes (in terms of the free troposphere) associated with deep convection and large-scale subsidence favoring conditions for low-level stratocumulus clouds, respectively. Based on estimated linear trends of RH-class occurrences and sea surface temperatures, we infer projected linear responses of RH in a warming climate. Ocean areas dominated by most moist and driest RH classes (in terms of the free atmosphere) are estimated to increase by about 1% and 2%, respectively (corresponding to about 2.5% K−1 and 4.5% K−1, respectively). The averaged global and tropical RH structure remain almost constant in a warming climate. While this is consistent with other studies, our results show how increases in most moist and dry areas compensate each other, indicating possible increases in the frequency or persistence of future extreme events. [ABSTRACT FROM AUTHOR]

The western-central equatorial Pacific (WCEP) zonal wind affects El Niño-Southern Oscillation (ENSO) by involving a series of multiscale air-sea interactions. Its interannual variation contributes the most to ENSO amplitude. Thus, understanding the predictability of the WCEP interannual wind is of great importance for better predictions of ENSO. Here, we show that the North Pacific Oscillation (NPO) and the South Pacific Oscillation (SPO) alternate in fueling this interannual wind from late boreal winter to austral winter in the presence of background trade winds in different hemispheres. During the boreal winter-spring, the NPO registers footprints in the tropics by benefiting from the Pacific meridional mode and modulating the northwestern Pacific intertropical convergence zone (NITCZ). However, as austral winter approaches, the SPO takes over the role of the NPO in maintaining the anomalous NITCZ. Moreover, the interannual wind is further driven to the east in the positive phase of the SPO, by intensified central-eastern equatorial Pacific convection resulting from tropical-extratropical heat flux adjustments. A reconstructed WCEP interannual wind index involving only the NPO and the SPO possesses a long lead time for ENSO prediction of nearly one year. These two extratropical boosters enhance the viability of equatorial Pacific zonal wind anomalies associated with the large growth rate of ENSO, and the one in the winter hemisphere seems to be more efficient in forcing the tropics. Our result further indicates that the NPO benefits a long-lead prediction of the WCEP interannual wind and ENSO, while the SPO is the dominant extratropical predictor of ENSO amplitude. [ABSTRACT FROM AUTHOR]

Seasonal cycle, migration and defensive behaviour of O. nigricornis is studied. Population of adults goes on peak in July and declines slightly in August and September. But, there remain almost constant during October to December and again decline in January and February due to cold temperature. Nymphal population increase in number from last week of March to June. There is only one generation in a year. Local migration in Odontopus occurs from main host to accessory host or sheltering plants, distant migration only occurs in absence of main food plant, P. alata. Warning colouration (Red and black) protect from enemies. Fleeing from the spot, on sensing danger is primary defensive act. Scent fluid secreted from the metathoracic and abdominal scent glands repel predators and parasites. [ABSTRACT FROM AUTHOR]

Seasonal cycle, population fluctuation and colour variations in Leptocoris augur is described in this paper. Population of bug reaches on the peak during May to September when the pulpy fruits and seeds of the host plant are maximum. Minimum number of bugs occur during winter months January and February. Low temperature, low R.H. and absent of fruits and seeds under kusum tree is responsible to it. Neotenic forms (Brachypterous) develops also during winter months October to February, being on peak in November and decline in summer and rainy months March to September. Though, bug population occurs in field area throughout year but nymphs and adults are found maximum during April to September. Breeding almost stops during winter. Good colour variation has been observed in the naturally occurring population. Type-I (Reddish), type-II (Orangish), type-III (Dark-yellowish) and type-IV (Blackish red) individuals are observed. Commonly occurring is type-I and type-II and type-III is rare occurs during winter is 1:15 ratio but becomes abundant during May to September (3:4). During gregarious feeding on the seeds colour variation in individuals give variegated appearance, which warns natural enemies up to some extent. [ABSTRACT FROM AUTHOR]