Arctic sea ice dynamics forecasting through interpretable machine learning

Machine Learning (ML) has become an increasingly popular tool to model the evolution of sea ice in the Arctic region. ML tools produce highly accurate and computationally efficient forecasts on specific tasks. Yet, they generally lack physical interpretability and do not support the understanding of system dynamics and interdependencies among target variables and driving factors. Here, we present a 2-step framework to model Arctic sea ice dynamics with the aim of balancing high performance and accuracy typical of ML and result interpretability. We first use time series clustering to obtain homogeneous subregions of sea ice spatiotemporal variability. Then, we run an advanced feature selection algorithm, called Wrapper for Quasi Equally Informative Subset Selection (W-QEISS), to process the sea ice time series barycentric of each cluster. W-QEISS identifies neural predictors (i.e., extreme learning machines) of the future evolution of the sea ice based on past values and returns the most relevant set of input variables to describe such evolution. Monthly output from the Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) from 1978 to 2020 is used for the entire Arctic region. Sea ice thickness represents the target of our analysis, while sea ice concentration, snow depth, sea surface temperature and salinity are considered as candidate drivers. Results show that autoregressive terms have a key role in the short term (with lag time 1 and 2 months) as well as the long term (i.e., in the previous year); salinity along the Siberian coast is frequently selected as a key driver, especially with a one-year lag; the effect of sea surface temperature is stronger in the clusters with thinner ice; snow depth is relevant only in the short term. The proposed framework is an efficient support tool to better understand the physical process driving the evolution of sea ice in the Arctic region

Variability of adenoidectomy/tonsillectomy rates among children of the Veneto Region, Italy

<p>Abstract</p> <p>Background</p> <p>Despite national guidelines in 2003 aimed at limiting the recourse to tonsillectomy and/or adenoidectomy (A/T), the latter are among the most frequent pediatric surgeries performed in Italy. Aim of the study is to investigate variability of A/T rates among children of the Veneto Region, Italy.</p> <p>Methods</p> <p>All discharges of Veneto residents with Diagnosis-Related Groups 57–60 and ICD9-CM intervention codes 28.2 (tonsillectomy), 28.3 (adenotonsillectomy), 28.6 (adenoidectomy) were selected in the period 2000–2006 for a descriptive analysis. A multilevel Poisson regression model was applied to estimate Incidence Rate Ratios (IRR) with 95% Confidence Intervals (CI) for A/T surgery among children aged 2–9 years in 2004–2006, while taking into account clustering of interventions within the 21 Local Health Units.</p> <p>Results</p> <p>Through 2000–2006, the overall number of A/T surgeries decreased (-8%); there was a decline of adenoidectomies (-20%) and tonsillectomies (-8%), whereas adenotonsillectomies raised (+18%). Analyses on children aged 2–9 resulted in an overall rate of 14.4 surgeries per 1000 person-years (16.1 among males and 12.5 among females), with a wide heterogeneity across Local Health Units (range 8.1–27.6). At random intercept Poisson regression, while adjusting for sex and age, intervention rates were markedly lower among foreign than among Italian children (IRR = 0.57, CI 0.53–0.61). A/T rates in the 10–40 age group (mainly tonsillectomies) computed for each Local Health Unit and introduced in the regression model accounted for 40% of the variance at Local Health Unit level of pediatric rates (mainly adenoidectomies and adenotonsillectomies).</p> <p>Conclusion</p> <p>A/T rates in the Veneto Region, especially adenoidectomies among children aged 2–9 years, remain high notwithstanding a decrease through 2000–2006. A wide heterogeneity according to nationality and Local Health Units is evident. The propensity to A/T surgery of each Local Health Unit is similar in different age groups and for different surgical indications.</p

Farmers in the transition toward sustainability: what is the role of their entrepreneurial identity?

This is the final version. Available on open access from Frontiers Media via the DOI in this recordData availability statement: The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Introduction: The European Union has recently prompted a shift toward Ecological Intensification (EI) practices, aiming to harmonize agricultural productivity and environmental conservation. Despite the benefits of EI, its implementation has been limited, as farmers face challenges in business reorganization and supply chain adaptation. This paper investigates the role of contract farming (CF) in promoting the adoption of sustainable practices among Italian wheat producers. Specifically, it analyzes the influence of farmers’ entrepreneurial identity on their engagement in such initiatives. Methods: Using the case study of Barilla Group’s Carta del Mulino initiative, an innovative contract farming scheme incentivizing sustainable EI practices, the study explores the relationship between entrepreneurial identity and participation in CF schemes supporting EI. Data from a sample of 314 soft wheat farmers in four regions of Northern Italy were collected to examine the role of entrepreneurial identity in the adoption of sustainable practices and participation in CF schemes. To evaluate the research hypotheses, two distinct econometric models were developed. Results and discussion: The findings reveal that farmers with a more developed entrepreneurial identity are more likely to adopt more sustainable agricultural practices and engage in contractual schemes involving EI practices. The study highlights the importance of fostering and supporting farmers’ entrepreneurial identity while increasing their knowledge of alternative agricultural techniques to address the challenges of the agricultural sector. This integration of individual perspectives (entrepreneurial identity) with a systems view (contract farming schemes) offers valuable insights for future research, policy, and practice in agri-food systems sustainability.European Union Horizon 202

Global Mean Climate and Main Patterns of Variability in the CMCC-CM2 Coupled Model

Euro-Mediterranean Centre on Climate Change coupled climate model (CMCC-CM2) represents the new family of the global coupled climate models developed and used at CMCC. It is based on the atmospheric, land and sea ice components from the Community Earth System Model coupled with the global ocean model Nucleus for European Modeling of the Ocean. This study documents the model components, the coupling strategy, particularly for the oceanic, atmospheric, and sea ice components, and the overall model ability in reproducing the observed mean climate and main patterns of interannual variability. As a first step toward a more comprehensive, process-oriented, validation of the model, this work analyzes a 200-year simulation performed under constant forcing corresponding to present-day climate conditions. In terms of mean climate, the model is able to realistically reproduce the main patterns of temperature, precipitation, and winds. Specifically, we report improvements in the representation of the sea surface temperature with respect to the previous version of the model. In terms of mean atmospheric circulation features, we notice a realistic simulation of upper tropospheric winds and midtroposphere geopotential eddies. The oceanic heat transport and the Atlantic meridional overturning circulation satisfactorily compare with present-day observations and estimates from global ocean reanalyses. The sea ice patterns and associated seasonal variations are realistically reproduced in both hemispheres, with a better skill in winter. Main weaknesses of the simulated climate are related with the precipitation patterns, specifically in the tropical regions with large dry biases over the Amazon basin. Similarly, the seasonal precipitation associated with the monsoons, mostly over Asia, is weaker than observed. The main patterns of interannual variability in terms of dominant empirical orthogonal functions are faithfully reproduced, mostly in the Northern Hemisphere winter. In the tropics the main teleconnection patterns associated with El Nino-Southern Oscillation and with the Indian Ocean Dipole are also in good agreement with observations

Towards Useful Decadal Climate Services

The decadal time scale (∼1–10 years) bridges the gap between seasonal predictions and longer-term climate projections. It is a key planning time scale for users in many sectors as they seek to adapt to our rapidly changing climate. While significant advances in using initialized climate models to make skillful decadal predictions have been made in the last decades, including coordinated international experiments and multimodel forecast exchanges, few user-focused decadal climate services have been developed. Here we highlight the potential of decadal climate services using four case studies from a project led by four institutions that produce real-time decadal climate predictions. Working in co-development with users in agriculture, energy, infrastructure, and insurance sectors, four prototype climate service products were developed. This study describes the challenge of trying to match user needs with the current scientific capability. For example, the use of large ensembles (achieved via a multisystem approach) and skillfully predicted large-scale environmental conditions, are found to improve regional predictions, particularly in midlatitudes. For each climate service, a two-page “product sheet” template was developed that provides users with both a concise probabilistic forecast and information on retrospective performance. We describe the development cycle, where valuable feedback was obtained from a “showcase event” where a wider group of sector users were engaged. We conclude that for society to take full and rapid advantage of useful decadal climate services, easier and more timely access to decadal climate prediction data are required, along with building wider community expertise in their use.This study received support from the C3S_34c contract (ECMWF/COPERNICUS/2019/C3S_34c_DWD) of the Copernicus Climate Change Service (C3S) operated by ECMWF. DS, AS, and HT were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. AP, KP, and BF were funded by the Deutscher Wetterdienst.Peer Reviewed"Article signat per 22 autors/es: Nick Dunstone, Julia Lockwood, Balakrishnan Solaraju-Murali, Katja Reinhardt, Eirini E. Tsartsali, Panos J. Athanasiadis, Alessio Bellucci, Anca Brookshaw, Louis-Philippe Caron, Francisco J. Doblas-Reyes, Barbara Früh, Nube González-Reviriego, Silvio Gualdi, Leon Hermanson, Stefano Materia, Andria Nicodemou, Dario Nicolì, Klaus Pankatz, Andreas Paxian, Adam Scaife, Doug Smith, and Hazel E. Thornton"Postprint (published version

Esterase Cleavable 2D Assemblies of Magnetic Iron Oxide Nanocubes: Exploiting Enzymatic Polymer Disassembling to Improve Magnetic Hyperthermia Heat Losses

Here, we report a nanoplatform based on iron oxide nanocubes (IONCs) coated with a bioresorbable polymer that, upon exposure to lytic enzymes can be disassembled increasing the heat performances in comparison with the initial clusters. We have developed bi-dimensional (2D) clusters by exploiting benchmark iron oxide nanocubes as heat mediators for magnetic hyperthermia and a polyhydroxyalkanoate (PHA) copolymer, a biodegradable polymer produced by bacteria that can be digested by intracellular esterase enzymes. The comparison of magnetic heat performance of the 2D assemblies with 3D centro-symmetrical assemblies or single iron oxide nanocubes emphasize the benefit of the 2D assembly. On one hand, the heat losses of 2D assemblies dispersed in water are better than the 3D assemblies, but worse than for single nanocubes. On the other hand, when the bi-dimensional magnetic beads (2D-MNBs) are incubated with the esterase enzyme at a physiological temperature, their magnetic heat performances began to progressively increase. After 2 hours of incubation, specific absorption rate values of the 2D assembly double the ones of individually coated nanocubes. Such an increase can be mainly correlated to the splitting of the 2D-MNBs into smaller size clusters with a chain- like configuration containing few nanocubes. Moreover, 2D-MNBs exhibited non-variable-heat performances even after intentionally inducing their aggregation. Magnetophoresis measurements indicate a comparable response of 3D and 2D clusters to external magnets (0.3T) that is by far faster than that of single nanocubes. This feature is crucial for a physical accumulation of magnetic materials in the presence of magnetic field gradients. This system is the first example of a nanoplatform that, upon exposure to lytic enzymes, such as those present in a tumor environment, can be disassembled from the initial 2D-MNB organization to chain-like assemblies with clear improvement of the heat magnetic losses resulting in better heat dissipation performances. The potential application of 2D nano-assemblies based on the cleavable PHAs for preserving their magnetic losses inside cells will benefit hyperthermia therapies mediated by magnetic nanoparticles under alternating magnetic fields

Esterase-Cleavable 2D Assemblies of Magnetic Iron Oxide Nanocubes: Exploiting Enzymatic Polymer Disassembling to Improve Magnetic Hyperthermia Heat Losses

Here, we report a nanoplatform based on iron oxide nanocubes (IONCs) coated with a bioresorbable polymer that, upon exposure to lytic enzymes, can be disassembled increasing the heat performances in comparison with the initial clusters. We have developed two-dimensional (2D) clusters by exploiting benchmark IONCs as heat mediators for magnetic hyperthermia and a polyhydroxyalkanoate (PHA) copolymer, a biodegradable polymer produced by bacteria that can be digested by intracellular esterase enzymes. The comparison of magnetic heat performance of the 2D assemblies with 3D centrosymmetrical assemblies or single IONCs emphasizes the benefit of the 2D assembly. Moreover, the heat losses of 2D assemblies dispersed in water are better than the 3D assemblies but worse than for single nanocubes. On the other hand, when the 2D magnetic beads (2D-MNBs) are incubated with the esterase enzyme at a physiological temperature, their magnetic heat performances began to progressively increase. After 2 h of incubation, specific absorption rate values of the 2D assembly double the ones of individually coated nanocubes. Such an increase can be mainly correlated to the splitting of the 2D-MNBs into smaller size clusters with a chain-like configuration containing few nanocubes. Moreover, 2D-MNBs exhibited nonvariable heat performances even after intentionally inducing their aggregation. Magnetophoresis measurements indicate a comparable response of 3D and 2D clusters to external magnets (0.3 T) that is by far faster than that of single nanocubes. This feature is crucial for a physical accumulation of magnetic materials in the presence of magnetic field gradients. This system is the first example of a nanoplatform that, upon exposure to lytic enzymes, such as those present in a tumor environment, can be disassembled from the initial 2D-MNB organization to chain-like assemblies with clear improvement of the heat magnetic losses resulting in better heat dissipation performances. The potential application of 2D nanoassemblies based on the cleavable PHAs for preserving their magnetic losses inside cells will benefit hyperthermia therapies mediated by magnetic nanoparticles under alternating magnetic fields