bluuebunny/crossref_metadata_2025_split huggingface dataset:
How the Green Architecture of the 2023–2027 Common Agricultural Policy could have been greener
Authors: Guyomard Herve , Détang-Dessendre Cécile , Dupraz Pierre , Delaby Luc , Huyghe Christian , Peyraud Jean-Louis , Reboud Xavier , Sirami Clélia 
Published: May 2023

AbstractA new 5-year Common Agricultural Policy has been in place since January 2023. Like its predecessors, this new policy will fail to deliver significant climatic and environmental benefits. We show how the Green Architecture of the policy relying on the three instruments of conditionality, eco-schemes, and agri-environment and climate measures could have been used more consistently and effectively. Our proposals are based on core principles of public economics and fiscal federalism as well as on research results in agronomy and ecology. Conditionality criteria are the minimal requirements that every agricultural producer must meet. Farmers should be rewarded for efforts that go beyond these basic requirements through eco-schemes for global public goods complemented by agri-environment and climate measures centred on local public goods. Eco-schemes should cover the whole agricultural area by targeting permanent grasslands, crop diversification, and green cover and non-productive agro-ecological infrastructures. We discuss trade-offs that our proposals could generate.
The importance of local fisheries as a cultural attribute: insight from a discrete choice experiment of seafood consumers
Authors: Martino Simone , Azzopardi Elaine , Fox Clive , Chiaroni Emma , Payne Elena , Kenter Jasper 
Published: May 2023

AbstractThe role of maritime heritage in providing benefits such as sense of place and identity has been well documented, but there is limited quantitative analysis (especially in monetary valuation) of its influence on people’s preferences. In this paper, we present results from a choice experiment where we valued cultural and heritage aspects of fishing through the preferences of seafood consumption. We found a strong preference for some attributes of seafood such as “locality” (origin of the catches), freshness, and sustainability in harvesting, but also a significant role of tangible maritime cultural heritage, such as visible fishing operations. This analysis can be helpful in informing public policies aiming to enhance experiences of fisheries as a living heritage and to valorise local produce to increase income of local communities.
Measures Used to Assess Treatment Outcomes in Children with Autism Receiving Early and Intensive Behavioral Interventions: A Review
Authors: Ridout Samantha , Eldevik Sigmund 
Published: May 2023

Abstract
This review is aimed at identifying assessment instruments used to measure treatment outcomes in children with autism spectrum disorder who received early and intensive behavioral interventions. Forty three articles were included and appraised using the Council for Exceptional Children’s Standards for Evidence Based Practice quality index rater. Ninety-two outcome measures were discovered. Measures of adaptive functioning (91%), intellectual functioning (86%), and core symptoms (67%) of autism were represented with the highest frequencies. Measures of challenging behavior and parent or caregiver wellbeing were reported at 30% and 14% respectively. Reliability and validity of each measure were determined by recently published psychometric data. The utility of outcome measures in clinical practice is discussed.
Immersive VR Assessment and Intervention Research of Individuals with Neurodevelopmental Disorders Is Dominated by ASD and ADHD: a Scoping Review
Authors: Satu Paavola , Minna Laakso , Satu Saalasti 
Published: May 2023

AbstractIn this scoping review on 34 studies, we examined the use of immersive virtual reality (IVR) in neurodevelopmental disorders (NDD). IVR was mostly used in connection with autism spectrum disorder (ASD) for assessment of and intervention in social skills, and in attention deficit hyperactivity disorder (ADHD) for assessment of executive performance. Diagnostic measures varied or were not available, and the level of evidence was generally observational/descriptive. Furthermore, few studies reported on feasibility and user experience and even fewer on human guidance and the generalization of intervention to everyday life. Our results suggest that human guidance during and after immersive VR may be crucial for generalization of skills. More research on IVR in other NDDs is needed.
Metamorphism as a covariant transform for the SSR group
Authors: Alqurashi Taghreed , Kisil Vladimir V. 
Published: May 2023

AbstractMetamorphism is a recently introduced integral transform, which is useful in solving partial differential equations. Basic properties of metamorphism can be verified by direct calculations. In this paper, we present metamorphism as a sort of covariant transform and derive its most important features in this way. Our main result is a characterisation of metamorphism’s image space. Reading this paper does not require advanced knowledge of group representations or theory of covariant transform.
Teachers Responding to Pacific Community Voice: Supporting Relationships Through an Ecological Research Initiative
Authors: Chu-Fuluifaga Cherie , Reynolds Martyn 
Published: May 2023

AbstractPacific education is an area of priority in Aotearoa New Zealand. It involves the teaching of Pacific students by a workforce that is largely of European origin. Pacific communities value education and have the capability to contribute to the understandings of teachers as they seek to provide the kinds of service that communities want to see. This article reports on a Teaching and Learning Research Initiative (TLRI), Learning From Each Other. Leveraging talanoa as a dialogic research approach, the initiative examines the change value of Pacific voice in enhancing teacher understanding and promoting deliberate action to improve Pacific education. We present findings organised by spaces in which educators enact change using a contextualised revision of Bronfenbrenner’s ecological model as a mapping tool. What emerges is a sense of how non-Pacific educators’ growing Pacific-informed understandings support Pacific learners in personal, classroom and institutional spaces.
A Compositional Global Implicit Approach for Modeling Coupled Multicomponent Reactive Transport
Authors: Seigneur Nicolas , Socié Adrien , Mayer K. Ulrich 
Published: May 2023

AbstractReactive transport modeling has become widely used to help improve understanding of hydrogeochemical processes from the pore scale to the watershed scale. In recent years, the scope of reactive transport applications has increased toward a higher level of complexity and process coupling. For example, the production and consumption of water as well as porosity evolution associated with the dissolution and precipitation of hydrated minerals can impact system evolution. Waste rock weathering, carbon sequestration, or the degradation of engineered barriers in radioactive waste repositories all constitute applications in which geochemistry and hydrodynamics can strongly influence each other. For these purposes, the traditional formulation of reactive transport simulators, which decouples groundwater flow and reactive transport processes, is limited. We present a global implicit compositional approach, which integrates the flow processes directly into the reactive transport and geochemical framework. This approach solves the flow field implicitly with the reactive transport equations, simultaneously accounting for water consumption and production due to geochemical reactions. Applications show that the model allows tackling complex reactive transport problems while accounting for intra‐aqueous reactions, redox reactions, and reactions involving mass transfer with the gas and solid phases. The presented simulations also demonstrate that the compositional and traditional approaches yield similar results for complex geochemical systems with relatively low reactivity.
Intraseasonal Sea Ice Concentration Variability Over the Weddell Sea During Austral Autumn
Authors: Song Lei , Wu Renguang , Chen Wen , Li Xichen , Lan Xiaoqing , An Lu , Zhu Jialei 
Published: May 2023

AbstractThe sea ice concentration (SIC) over the Weddell Sea displays obvious intraseasonal variability during austral autumn with a dominant frequency of 5–20 days. The intraseasonal SIC variability is manifested as development of sea ice anomalies from the northeastern Antarctic Peninsula toward the central Weddell Sea. Rossby wave train associated with the internal atmospheric variability featuring circumglobal zonal wavenumber 4 pattern induces the development of anomalous surface winds and sea ice drifting, leading to the SIC anomalies directly. The thermodynamical processes associated with the intraseasonal SIC variability include the air temperature, the moisturizing of the lower troposphere, the latent and sensible heating, and the downwelling longwave radiation, which contribute to the variation of the local greenhouse effect over the Weddell Sea, and thus lead to the sea ice variation. The investigation of the intraseasonal SIC variability helps the understanding of sea‐ice‐atmosphere interaction over the Antarctic region.
A Vorticity‐Divergence View of Internal Wave Generation by a Fast‐Moving Tropical Cyclone: Insights From Super Typhoon Mangkhut
Authors: Brizuela Noel G. , Johnston T. M. Shaun , Alford Matthew H. , Asselin Olivier , Rudnick Daniel L. , Moum James N. , Thompson Elizabeth J. , Wang Shuguang , Lee Chia‐Ying 
Published: May 2023

AbstractTropical cyclones (TCs) are powered by heat fluxes across the air‐sea interface, which are in turn influenced by subsurface physical processes that can modulate storm intensity. Here, we use data from 6 profiling floats to recreate 3D fields of temperature (T), salinity (S), and velocity around the fast‐moving Super Typhoon Mangkhut (western North Pacific, September 2018). Observational estimates of vorticity (ζ) and divergence (Γ) agree with output from a 3D coupled model, while their relation to vertical velocities is explained by a linear theoretical statement of inertial pumping. Under this framework, inertial pumping is described as a linear coupling between ζ and Γ, whose oscillations in quadrature cause periodic displacements in the ocean thermocline and generate near‐inertial waves (NIWs). Vertical profiles of T and S show gradual mixing of the upper ocean with diffusivities as high as κ ∼ 10−1 m2 s−1, which caused an asymmetric cold wake of sea surface temperature (SST). We estimate that ∼10% of the energy used by mixing was used to mix rainfall, therefore inhibiting SST cooling. Lastly, watermass transformation analyses suggest that κ > 3 × 10−3 m2 s−1 above ∼110 m depth and up to 600 km behind the TC. These analyses provide an observational summary of the ocean response to fast‐moving TCs, demonstrate some advantages of ζ and Γ for the study of internal wave fields, and provide conceptual clarity on the mechanisms that lead to NIW generation by winds.
A Global Survey of Rotating Convective Updrafts in the GFDL X‐SHiELD 2021 Global Storm Resolving Model
Authors: Harris Lucas , Zhou Linjiong , Kaltenbaugh Alex , Clark Spencer , Cheng Kai‐Yuan , Bretherton Chris 
Published: May 2023

AbstractWe present the global characteristics of rotating convective updrafts in the 2021 version of GFDL's eXperimental System for High‐resolution prediction on Earth‐to‐Local Domains (X‐SHiELD), a kilometer‐scale global storm resolving model (GSRM). Rotation is quantified using 2–5 km Updraft Helicity (UH) in a year‐long integration forced by analyzed SSTs. Updrafts with UH magnitudes above 50 m2 s−2 are common over the mid‐latitude continents, where they are associated with severe weather especially in the warm seasons but are also common over most tropical ocean basins. In nearly all areas cyclonically rotating convection dominates, with larger UH values increasingly preferring cyclonic rotation. The ratio of cyclonic to anticyclonic updrafts is largest in the subtropical and mid‐latitude oceans and is slightly lower over mid‐latitude continents. The ratio of cyclonic to anticyclonic updrafts can be substantively explained by the mean storm‐relative helicity (SRH) in convective regions, indicating the importance for environmental controls on the sense of storm rotation, although internal storm dynamics also plays a role in the generation of anticyclonic updrafts.
Last Glacial Maximum ITCZ Changes From PMIP3/4 Simulations
Authors: Wang Ting , Wang Na , Jiang Dabang 
Published: May 2023

AbstractWe investigate global and regional changes in the intertropical convergence zone (ITCZ) position, width, and intensity during the last glacial maximum (LGM) relative to the preindustrial period using multiple simulations from Phases 3 and 4 of the Paleoclimate Modelling Intercomparison Project (PMIP3/4). On annual scale, most models show that LGM tropical precipitation decreases, and the deficit in the Northern Hemisphere is larger than that in the Southern Hemisphere, resulting in the southward shift, narrowing, and weakening of the ITCZ at the global scale. The arithmetic mean of 13 models shows that the global zonal mean ITCZ shifts southward by 0.85° (1σ = 0.86°), narrows by 1.05° (1σ = 1.33°), and weakens by 7% (1σ = 4%) during the LGM. Regionally, position and intensity changes are larger in the central and eastern Pacific, while width changes are most obvious in the Indian Ocean–western Pacific. Precipitation changes in the central and eastern Pacific and Atlantic oceans are dominated by the dynamic term. In the Indian Ocean–western Pacific, the thermodynamic term is the main cause for precipitation changes within 10°S–10°N, while the dynamic term plays a leading role at other tropical latitudes. Seasonally, the September–October–November and June–July–August mainly contribute to the annual ITCZ position, width, and intensity changes globally and in most regions. The convergence factor dominates both the dynamic and thermodynamic terms annually and seasonally. The model results are compatible with the existing site reconstructions on the southward shift of the LGM ITCZ.
Characterizing Uncertainty in Pan‐Arctic Land‐Ocean Dissolved Organic Carbon Flux: Insights From the Onega River, Russia
Authors: Starr Sommer , Johnston Sarah Ellen , Sobolev Nikita , Perminova Irina , Kellerman Anne , Fiske Greg , Bulygina Ekaterina , Shiklomanov Alexander , McKenna Amy , Spencer Robert G. M. 
Published: May 2023

AbstractDissolved organic carbon (DOC) flux from rivers in the pan‐Arctic watershed represents an important connection between major terrestrial carbon stocks and the Arctic Ocean. Previous estimates of Arctic carbon flux and dissolved organic matter (DOM) seasonal dynamics have relied predominantly on measurements from the six major Arctic rivers, yet these may not be representative of northern high‐latitude constrained smaller watersheds. Here, we evaluate DOC concentration and DOM composition in the Onega River, a small Arctic watershed, using optical measurements and ultrahigh resolution mass spectrometry. Compared to the six largest Arctic rivers, DOC, absorbance at a350, and indicators of terrestrial DOM (e.g., specific UV absorbance at 254 nm, modified aromaticity index, relative abundance of condensed aromatics and polyphenolics) were elevated in the Onega throughout the year. Seasonality was also generally muted in comparison to the major Arctic rivers with relatively elevated DOC and terrestrial markers in both spring and fall seasons. The Onega exhibits a strong relationship between a350 and DOC, and its organic‐rich nature is apparent in its high DOC yield (4.85 g m2yr−1), and higher chromophoric DOM per unit DOC than the six largest Arctic rivers. As DOC yield from the Onega may be more representative of smaller northern high‐latitude rivers, we derived a new pan‐Arctic DOC flux scaling estimate which is over 50% higher than previous estimates scaled solely from the six major Arctic rivers. These observations suggest that smaller northern high‐latitude rivers may be underrepresented in Arctic carbon flux models and highlights uncertainty around constraining the export of DOC to the Arctic Ocean.
Simultaneous Multiscale Data Assimilation Using Scale‐ and Variable‐Dependent Localization in EnVar for Convection Allowing Analyses and Forecasts: Methodology and Experiments for a Tornadic Supercell
Authors: Wang Yongming , Wang Xuguang 
Published: May 2023

AbstractThis study introduces a simultaneous multiscale data assimilation method by implementing model space spatial scale‐dependent localization (SDL) and variable‐dependent localization (VDL) within an ensemble variational system. This method updates all resolved scales by assimilating all observations at once. The impact of such an approach is examined by a series of radar data assimilation experiments. Single‐observation experiments show that SDL concurrently and more properly updates the storm and its ambient environments compared to a traditional single scale localization (SSL) for radar data assimilation. Including VDL on top of SDL (SDLVDL) realistically decreases the spatial coverage and intensity of moisture increments compared to SDL. Comparisons are then performed on the analyses and forecasts of the 8 May 2003 Oklahoma City supercell storm. Results show that SDL improves the analyses and forecasts during the data assimilation cycling by producing more realistic enhanced low‐level convergences than SSL. SDLVDL obtains more accurate analyses and subsequent forecasts for moisture than SDL. SDLVDL yields the best performance in reflectivity forecasts and storm maintenance. Compared to SSL, SDL has higher forecast skills before 2230 UTC and produces degraded forecasts in the later lead time.
A Physics‐Incorporated Deep Learning Framework for Parameterization of Atmospheric Radiative Transfer
Authors: Yao Yichen , Zhong Xiaohui , Zheng Yongjun , Wang Zhibin 
Published: May 2023

AbstractThe atmospheric radiative transfer calculations are among the most time‐consuming components of the numerical weather prediction (NWP) models. Deep learning (DL) models have recently been increasingly applied to accelerate radiative transfer modeling. Besides, a physical relationship exists between the output variables, including fluxes and heating rate profiles. Integration of such physical laws in DL models is crucial for the consistency and credibility of the DL‐based parameterizations. Therefore, we propose a physics‐incorporated framework for the radiative transfer DL model, in which the physical relationship between fluxes and heating rates is encoded as a layer of the network so that the energy conservation can be satisfied. It is also found that the prediction accuracy was improved with the physic‐incorporated layer. In addition, we trained and compared various types of DL model architectures, including fully connected (FC) neural networks (NNs), convolutional‐based NNs (CNNs), bidirectional recurrent‐based NNs (RNNs), transformer‐based NNs, and neural operator networks, respectively. The offline evaluation demonstrates that bidirectional RNNs, transformer‐based NNs, and neural operator networks significantly outperform the FC NNs and CNNs due to their capability of global perception. A global perspective of an entire atmospheric column is essential and suitable for radiative transfer modeling as the changes in atmospheric components of one layer/level have both local and global impacts on radiation along the entire vertical column. Furthermore, the bidirectional RNNs achieve the best performance as they can extract information from both upward and downward directions, similar to the radiative transfer processes in the atmosphere.
A Pareto‐Based Sensitivity Analysis and Multiobjective Calibration Approach for Integrating Streamflow and Evaporation Data
Authors: Yeste Patricio , Melsen Lieke A. , García‐Valdecasas Ojeda Matilde , Gámiz‐Fortis Sonia R. , Castro‐Díez Yolanda , Esteban‐Parra María Jesús 
Published: May 2023

AbstractEvaporation is gaining increasing attention as a calibration and evaluation variable in hydrologic studies that seek to improve the physical realism of hydrologic models and go beyond the long‐established streamflow‐only calibration. However, this trend is not yet reflected in sensitivity analyses aimed at determining the relevant parameters to calibrate, where streamflow has traditionally played a leading role. On the basis of a Pareto optimization approach, we propose a framework to integrate the temporal dynamics of streamflow and evaporation into the sensitivity analysis and calibration stages of the hydrologic modeling exercise, here referred to as “Pareto‐based sensitivity analysis” and “multiobjective calibration.” The framework is successfully applied to a case study using the Variable Infiltration Capacity (VIC) model in three catchments located in Spain as representative of the different hydroclimatic conditions within the Iberian Peninsula. Several VIC vegetation parameters were identified as important to the performance estimates for evaporation during sensitivity analysis, and therefore were suitable candidates to improve the model representation of evaporative fluxes. Sensitivities for the streamflow performance, in turn, were mostly driven by the soil and routing parameters, with little contribution from the vegetation parameters. The multiobjective calibration experiments were carried out for the most parsimonious parameterization after a comparative analysis of the performance gains and losses for streamflow and evaporation, and yielded optimal adjustments for both hydrologic variables simultaneously. Results from this study will help to develop a better understanding of the trade‐offs resulting from the joint integration of streamflow and evaporation data into modeling frameworks.
Plant Hydraulics Improves Predictions of ET and GPP Responses to Drought
Authors: Xie Shudi , Mo Xingguo , Liu Suxia , Hu Shi 
Published: May 2023

AbstractLand surface models typically ignore plant hydraulic processes and use empirical soil moisture stress functions to limit transpiration and photosynthesis. How plant hydraulics impacts the predictions of carbon and water fluxes and their responses to drought remains unclear. Here, we developed an analytical plant hydraulic scheme wherein hydraulic capacitances at the leaf level and stem level were considered, and incorporated it into the vegetation interface processes model (hereafter, VIP‐PHS). Then, we calibrated the VIP‐PHS parameters using a Markov Chain Monte Carlo (MCMC) method and conducted an ecosystem‐scale evaluation of the VIP‐PHS at 30 FLUXNET sites. The results showed that VIP‐PHS improved evapotranspiration (ET) and gross primary production (GPP) simulations across the studied sites, reducing the root mean square error (RMSE) by 0.02–0.27 mm day−1 and 0.04–0.52 g C m−2 day−1 in relation to the empirical soil hydraulic scheme (hereafter, VIP‐SHS). VIP‐PHS decreased the RMSE in ET and GPP by up to 45% and 55% in evergreen needleleaf forests. Compared to VIP‐SHS, VIP‐PHS decreased the sensitivities of ET and GPP to soil moisture stress, and significantly improved ET and GPP predictions under low soil moisture conditions. The sensitivity analysis showed that larger stem hydraulic capacitance better relieved xylem water stress, resulting in greater transpiration and GPP and less‐negative daily minimum stem water potential. These findings highlight the need to incorporate plant hydraulics into the next generation of Earth system models under future drought conditions.