169 research outputs found

    Constrained CMIP6 projections indicate less warming and a slower increase in water availability across Asia

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    Climate projections are essential for decision-making but contain non-negligible uncertainty. To reduce projection uncertainty over Asia, where half the world's population resides, we develop emergent constraint relationships between simulated temperature (1970-2014) and precipitation (2015-2100) growth rates using 27 CMIP6 models under four Shared Socioeconomic Pathways. Here we show that, with uncertainty successfully narrowed by 12.1-31.0%, constrained future precipitation growth rates are 0.39 ± 0.18 mm year-1 (29.36 mm °C-1, SSP126), 0.70 ± 0.22 mm year-1 (20.03 mm °C-1, SSP245), 1.10 ± 0.33 mm year-1 (17.96 mm °C-1, SSP370) and 1.42 ± 0.35 mm year-1 (17.28 mm °C-1, SSP585), indicating overestimates of 6.0-14.0% by the raw CMIP6 models. Accordingly, future temperature and total evaporation growth rates are also overestimated by 3.4-11.6% and -2.1-13.0%, respectively. The slower warming implies a lower snow cover loss rate by 10.5-40.2%. Overall, we find the projected increase in future water availability is overestimated by CMIP6 over Asia

    Elasticity curves describe streamflow sensitivity to precipitation across the entire flow distribution

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    Streamflow elasticity is a simple approximation of how responsive a river is to precipitation. It is represented as a ratio of the expected percentage change in streamflow for a 1 % change in precipitation. Typically estimated for the annual median streamflow, we here propose a new concept in which streamflow elasticity is estimated across the full range of streamflow percentiles in a large-sample context. This “elasticity curve” can be used to develop a more complete depiction of how streamflow responds to precipitation. We find three different elasticity curve types which characterize this relationship at the annual and seasonal timescales in the USA, based on two statistical modelling approaches, a panel regression which facilitates causal inference and a single catchment model which allows for consideration of static attributes. Type A describes catchments where low flows are the least and high flows are the most responsive to precipitation. The majority of catchments at the annual, winter, and fall timescales exhibit this behavior. Type B describes catchments where the response is relatively consistent across the flow distribution. At the seasonal timescale, many catchments experience a consistent level of response across the flow regime. This is especially true in snow-fed catchments during cold months, when the actual elasticity skews towards zero for all flow percentiles while precipitation is held in storage. Consistent response is also seen across the majority of the country during spring when streamflow is comparatively stable and in summer when evaporation demand is high and soil moisture is low. Finally, Type C describes catchments where low flows are the most responsive to precipitation change. These catchments are dominated by highly flashy low flow behavior. We show that the curve type varies separately from the magnitude of the elasticity. Finally, we demonstrate that available water storage is likely the key control which determines curve type

    Screening for low energy availability in male athletes : Attempted validation of LEAM-Q

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    A questionnaire-based screening tool for male athletes at risk of low energy availability (LEA) could facilitate both research and clinical practice. The present options rely on proxies for LEA such screening tools for disordered eating, exercise dependence, or those validated in female athlete populations. in which the female-specific sections are excluded. To overcome these limitations and support progress in understanding LEA in males, centres in Australia, Norway, Denmark, and Sweden collaborated to develop a screening tool (LEAM-Q) based on clinical investigations of elite and sub-elite male athletes from multiple countries and ethnicities, and a variety of endurance and weight-sensitive sports. A bank of questions was developed from previously validated questionnaires and expert opinion on various clinical markers of LEA in athletic or eating disorder populations, dizziness, thermoregulation, gastrointestinal symptoms, injury, illness, wellbeing, recovery, sleep and sex drive. The validation process covered reliability, content validity, a multivariate analysis of associations between variable responses and clinical markers, and Receiver Operating Characteristics (ROC) curve analysis of variables, with the inclusion threshold being set at 60% sensitivity. Comparison of the scores of the retained questionnaire variables between subjects classified as cases or controls based on clinical markers of LEA revealed an internal consistency and reliability of 0.71. Scores for sleep and thermoregulation were not associated with any clinical marker and were excluded from any further analysis. Of the remaining variables, dizziness, illness, fatigue, and sex drive had sufficient sensitivity to be retained in the questionnaire, but only low sex drive was able to distinguish between LEA cases and controls and was associated with perturbations in key clinical markers and questionnaire responses. In summary, in this large and international cohort, low sex drive was the most effective self-reported symptom in identifying male athletes requiring further clinical assessment for LEA

    Resilience of UK crop yields to compound climate change

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    Recent extreme weather events have had severe impacts on UK crop yields, and so there is concern that a greater frequency of extremes could affect crop production in a changing climate. Here we investigate the impacts of future climate change on wheat, the most widely grown cereal crop globally, in a temperate country with currently favourable wheat-growing conditions. Historically, following the plateau of UK wheat yields since the 1990s, we find there has been a recent significant increase in wheat yield volatility, which is only partially explained by seasonal metrics of temperature and precipitation across key wheat growth stages (foundation, construction and production). We find climate impacts on wheat yields are strongest in years with compound weather extremes across multiple growth stages (e.g. frost and heavy rainfall). To assess how these conditions might evolve in the future, we analyse the latest 2.2 km UK Climate Projections (UKCP Local): on average, the foundation growth stage (broadly 1 October to 9 April) is likely to become warmer and wetter, while the construction (10 April to 10 June) and production (11 June to 26 July) stages are likely to become warmer and slightly drier. Statistical wheat yield projections, obtained by driving the regression model with UKCP Local simulations of precipitation and temperature for the UK's three main wheat-growing regions, indicate continued growth of crop yields in the coming decades. Significantly warmer projected winter night temperatures offset the negative impacts of increasing rainfall during the foundation stage, while warmer day temperatures and drier conditions are generally beneficial to yields in the production stage. This work suggests that on average, at the regional scale, climate change is likely to have more positive impacts on UK wheat yields than previously considered. Against this background of positive change, however, our work illustrates that wheat farming in the UK is likely to move outside of the climatic envelope that it has previously experienced, increasing the risk of unseen weather conditions such as intense local thunderstorms or prolonged droughts, which are beyond the scope of this paper

    Hydrological controls on oviposition habitat are associated with egg-laying phenology of some caddisflies

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    1. Seasonal variation in resource availability can have strong effects on life histories and population densities. Emergent rocks (ERs) are an essential oviposition resource for multiple species of stream insects. The availability of ERs depends upon water depth and clast size, which vary with discharge and river geomorphology, respectively. Recruitment success for populations may depend on whether peak egg-laying periods occur at times when ER are also abundant. For multiple species that oviposit on ER, we tested whether seasonal fluctuations in ER abundance were concurrent with oviposition phenology. We also tested whether high discharge drowned ERs for sufficiently long periods to preclude egg laying, and whether this problem varied between rivers differing in channel morphology and particle size distribution.2. We obtained a continuous timeseries of water level (WL) measured every 30 min for two years at sites on three rivers in south-eastern Australia with similar hydrology but different geomorphology. A relationship between WL and ER numbers was determined empirically at each site and these relationships were used to predict ER availability over the two years. Egg masses of ten species of caddisflies were enumerated each month for a year in one river to establish oviposition phenology. 3. Abundance of ERs was inversely related to discharge in all three rivers. ERs were most abundant during autumn and scarce during spring. Site-specific geomorphology resulted in skewed or multimodal distributions of ER abundance each year. Between years, catchment-scale hydrometeorology mediated patterns of ER availability, despite the close proximity of sites. Temporal variance in ER availability was not consistently correlated with mean WL or WL variance. ER variance increased with WL variance, when WL was below a threshold equivalent to mean annual WL. Above this threshold, most ER were likely to be submerged.4. Oviposition phenology varied strongly among the ten species of caddisflies, with egg-laying ranging from in 1-2 months to year-round. Temporal variations in ER and egg mass abundance were not correlated for most species. Below a threshold minimum number of ER, egg masses were highly crowded onto the few available ER, which is evidence that ER were in short supply. For five species, high egg mass abundance was positively associated with periods of the year when the time above the threshold number of ERs was high. Unusually, two species laid most egg masses during winter and when the time above this threshold was short. Three species showed no association between egg mass abundance and time above this threshold; two of these species laid eggs year-round.5. Regional hydrometeorology controlled the availability of ERs, but between-river differences were sufficient to deliver different outcomes in the availability of oviposition sites between years and seasons. Caddisflies were rarely prevented from laying eggs but periods when ERs were in short supply created crowding, which may be associated with negative fitness effects on hatching larvae. Geomorphological controls on availability of oviposition resources may have strong implications for the coexistence of species that overlap temporally in egg-laying

    Slower-decaying tropical cyclones produce heavier precipitation over China

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    The post-landfall decay of tropical cyclones (TC) is often closely linked to the magnitude of damage to the environment, properties, and the loss of human lives. Despite growing interest in how climate change affects TC decay, data uncertainties still prevent a consensus on changes in TC decay rates and related precipitation. Here, after strict data-quality control, we show that the rate of decay of TCs after making landfall in China has significantly slowed down by 45% from 1967 to 2018. We find that, except the warmer sea surface temperature, the eastward shift of TC landfall locations also contributes to the slowdown of TC decay over China. That is TCs making landfall in eastern mainland China (EC) decay slower than that in southern mainland China (SC), and the eastward shift of TCs landfall locations causes more TCs landfalling in EC with slower decay rate. TCs making landfall in EC last longer at sea, carry more moisture upon landfall, and have more favorable dynamic and thermodynamic conditions sustaining them after landfall. Observational evidence shows that the decay of TC-induced precipitation amount and intensity within 48 h of landfall is positively related to the decay rate of landfalling TCs. The significant increase in TC-induced precipitation over the long term, due to the slower decay of landfalling TCs, increases flood risks in China’s coastal areas. Our results highlight evidence of a slowdown in TC decay rates at the regional scale. These findings provide scientific support for the need for better flood management and adaptation strategies in coastal areas under the threat of greater TC-induced precipitation

    Substituting carbohydrate at lunch for added protein increases fat oxidation during subsequent exercise in healthy males

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    Context How pre-exercise meal composition influences metabolic and health responses to exercise later in the day is currently unclear. Objective Examine the effects of substituting carbohydrate for protein at lunch on subsequent exercise metabolism, appetite, and energy intake. Methods Twelve healthy males completed three trials in randomized, counterbalanced order. Following a standardized breakfast (779 ± 66 kcal; ∼08:15), participants consumed a lunch (1186 ± 140 kcal; ∼13:15) containing either 0.2 g·kg-1 carbohydrate and ∼2 g·kg-1 protein (LO-CARB), 2 g·kg-1 carbohydrate and ∼0.4 g·kg-1 protein (HI-CARB), or fasted (FAST). Participants later cycled at ∼60% V̇O2peak for 1 h (∼16:15) and post-exercise ad-libitum energy intake was measured (∼18:30). Substrate oxidation, subjective appetite, and plasma concentrations of glucose, insulin, non-esterified fatty acids (NEFA), peptide YY (PYY), glucagon-like peptide-1 (GLP-1), and acylated ghrelin (AG) were measured for 5 h post-lunch. Results Fat oxidation was greater during FAST (+11.66 ± 6.63 g) and LO-CARB (+8.00 ± 3.83 g) than HI-CARB (p < 0.001), with FAST greater than LO-CARB (+3.67 ± 5.07 g; p < 0.05). NEFA were lowest in HI-CARB and highest in FAST, with insulin demonstrating the inverse response (all p < 0.01). PYY and GLP-1 demonstrated a stepwise pattern, with LO-CARB greatest and FAST lowest (all p < 0.01). AG was lower during HI-CARB and LO-CARB versus FAST (p < 0.01). Energy intake in LO-CARB was lower than FAST (-383 ± 233 kcal; p < 0.001) and HI-CARB (-313 ± 284 kcal; p < 0.001). Conclusion Substituting carbohydrate for protein in a pre-exercise lunch increased fat oxidation, suppressed subjective and hormonal appetite, and reduced post-exercise energy intake

    GTWS-MLrec: global terrestrial water storage reconstruction by machine learning from 1940 to present

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    Terrestrial water storage (TWS) includes all forms of water stored on and below the land surface, and is a key determinant of global water and energy budgets. However, TWS data from measurements by the Gravity Recovery and Climate Experiment (GRACE) satellite mission are only available from 2002, limiting global and regional understanding of the long-term trends and variabilities in the terrestrial water cycle under climate change. This study presents long-term (i.e., 1940–2022) and relatively high-resolution (i.e., 0.25∘) monthly time series of TWS anomalies over the global land surface. The reconstruction is achieved by using a set of machine learning models with a large number of predictors, including climatic and hydrological variables, land use/land cover data, and vegetation indicators (e.g., leaf area index). The outcome, machine-learning-reconstructed TWS estimates (i.e., GTWS-MLrec), fits well with the GRACE/GRACE-FO measurements, showing high correlation coefficients and low biases in the GRACE era. We also evaluate GTWS-MLrec with other independent products such as the land–ocean mass budget, atmospheric and terrestrial water budget in 341 large river basins, and streamflow measurements at 10 168 gauges. The results show that our proposed GTWS-MLrec performs overall as well as, or is more reliable than, previous TWS datasets. Moreover, our reconstructions successfully reproduce the consequences of climate variability such as strong El Niño events. The GTWS-MLrec dataset consists of three reconstructions based on (a) mascons of the Jet Propulsion Laboratory of the California Institute of Technology, the Center for Space Research at the University of Texas at Austin, and the Goddard Space Flight Center of NASA; (b) three detrended and de-seasonalized reconstructions; and (c) six global average TWS series over land areas, both with and without Greenland and Antarctica. Along with its extensive attributes, GTWS_MLrec can support a wide range of geoscience applications such as better understanding the global water budget, constraining and evaluating hydrological models, climate-carbon coupling, and water resources management. GTWS-MLrec is available on Zenodo through https://doi.org/10.5281/zenodo.10040927 (Yin, 2023)
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