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Agricultural fertilization significantly enhances amplitude of land-atmosphere CO2 exchange
No full textInternational audienceObservations show an increase in the seasonal cycle amplitude of CO2 in northern latitudes over the past half century. Although multiple drivers contribute, observations and inversion models cannot quantitatively account for the factors contributing to the increased CO2 amplitude and older versions of Earth System Models (ESMs) do not simulate it. Here we show that several current generation ESMs are closer to the observed CO2 amplitude and highlight that in the Community Earth System Model (CESM) agricultural nitrogen (N) fertilization increases CO2 amplitude by 1-3 ppm throughout the Northern Hemisphere and up to 9 ppm in agricultural hotspots. While agricultural N fertilization is the largest contributor to the enhanced amplitude (45%) in Northern Hemisphere land-atmosphere carbon fluxes in CESM, higher CO2 concentrations and warmer temperatures also contribute, though to a lesser extent (40% and 18% respectively). Our results emphasize the fundamental role of agricultural management in Northern Hemisphere carbon cycle feedbacks and illustrate that agricultural N fertilization should be considered in future carbon cycle simulations
Tackling the Accuracy-Interpretability Trade-off in a Hierarchy of Machine Learning Models for the Prediction of Extreme Heatwaves
No full textInternational audienceWhen performing predictions that use Machine Learning (ML), we are mainly interested in performance and interpretability. This generates a natural trade-off, where complex models generally have higher skills but are harder to explain and thus trust. Interpretability is particularly important in the climate community, where we aim at gaining a physical understanding of the underlying phenomena. Even more so when the prediction concerns extreme weather events with high impact on society. In this paper, we perform probabilistic forecasts of extreme heatwaves over France, using a hierarchy of increasingly complex ML models, which allows us to find the best compromise between accuracy and interpretability. More precisely, we use models that range from a global Gaussian Approximation (GA) to deep Convolutional Neural Networks (CNNs), with the intermediate steps of a simple Intrinsically Interpretable Neural Network (IINN) and a model using the Scattering Transform (ScatNet). Our findings reveal that CNNs provide higher accuracy, but their black-box nature severely limits interpretability, even when using state-of-the-art Explainable Artificial Intelligence (XAI) tools. In contrast, ScatNet achieves similar performance to CNNs while providing greater transparency, identifying key scales and patterns in the data that drive predictions. This study underscores the potential of interpretability in ML models for climate science, demonstrating that simpler models can rival the performance of their more complex counterparts, all the while being much easier to understand. This gained interpretability is crucial for building trust in model predictions and uncovering new scientific insights, ultimately advancing our understanding and management of extreme weather events
Algorithme Self-Consistent Field pour la méthode Hartree-Fock restreinte à couche ouverte (ROHF)
No full textInternational audienceIn this chapter, we propose a simple geometrical derivation of the restricted open-shell Hartree-Fock (ROHF) equations in the density matrix and molecular orbitals formalism. We then introduce a new, parameter-free, basic fixed-point method to solve these equations, that, in contrast with existing self consistent field (SCF) schemes, is not based on the introduction of a non-physical, parameter-dependent, composite Hamiltonian. We also extend the Optimal Damping Algorithm to the ROHF framework. We finally present numerical results on challenging systems (complexes with transition metals) demonstrating the performance of the new algorithms we propose
Out-of-core Algorithms for Binary Partition Hierarchies
No full textInternational audienceBinary partition hierarchies (BPH) and minimum spanning trees are essential data structures for hierarchical analysis, such as quasi-flat zones and watershed segmentation. Traditional BPH construction algorithms are limited by their requirement to load the data entirely into memory, making them impractical for processing large images whose processing exceeds the capacity of the computer's main memory. To overcome this limitation, an algebraic framework was introduced, enabling the out-of-core computation of BPH leveraging three key operations: select, join, and insert. In this publication, we present two distinct calculi based on these operations: one designed for general spatial partitions and another optimized for causal partitioning. The second calculus is specifically tailored to meet out-of-core constraints, ensuring efficient processing of large-scale data. We provide detailed algorithms, including pseudo-code and complexity analysis, and conduct experimental comparisons between the two approaches
Methodological investigations and understanding of the transfer dynamics of microplastics in the River Seine
No full textInternational audienceUrban areas discharge significant quantities of microplastics (MPs) into the environment. In rivers the flux of MPs is poorly estimated due to metrological and analytical limitations as well as a poor assessment of the hydrodynamic role. These limitations are mainly related to the sampling devices (e.g, net or pumping samplers) which do not allow to produce representative data in spatial and temporal scales, as, the sampling is executed at one specific location in the water column and for short duration. To address these issues, this project proposes to improve current methods for quantifying MPs and understand their dynamics across various river spatio-temporal scales. A passive sampler was adapted for MP studies and the first experiment to be carried out is focusing on assessing spatio-temporal variability in a river located upstream of the Paris metropolitan area. The device will be placed within the water column of the Seine river (France) at different distances from the shore. The samples will a pre-treatment protocol: organic matter digestion and density separation. Analysis will be executed using micro Fourrier Transform Infra-Red. Specially for this project, the uncertainties will be accessed by comparing two different analytical devices (Nicolet - Thermo-Fischer and Spotlight 4000 - Perkin Elmer). In parallel we will quantify and characterise the total suspended solids for all samples. These approaches will give insights in MP dynamics within the water column over a year allowing to provide a fine temporal variation of the MPs flux in the Seine river and its associated uncertainties. Additionally, the aim would be to establish whether total suspended solids could be used as a reliable proxy for following MPs dynamics
Heterogeneous Trade Elasticity and Managerial Skills
No full textThis paper investigates the role played by firms' managerial skills in the heterogeneous reaction of exporters to common exogenous changes in their international competitiveness (here captured by changes in the real exchange rate). Relying on a simple theoretical framework, we show that firms with better managerial skills have higher profits, market power, and are able to adapt their markup more when faced with a competitiveness shock. We test this prediction relying on detailed firm-product-destination level export data from France for the period 1995-2007 matched with specific information on the firms' share of managers. Our findings show that managerial intensive firms have larger exporter price elasticity to real exchange rate variations. The effect is not trivial: in the wake of a depreciation, exporters whose management intensity is one standard deviation higher than the average, increase their prices by 51% to 73% more than the average exporter. This finding is robust to controlling for the alternative explanations suggested by the previous literature to explain the heterogeneous pass-through of firms
Beyond Present Bias: Exploring Temporal Smoothing Biases
No full textThe importance of the literature on present bias may have overlooked some other forms of temporal inconsistencies anchored in the smoothing properties of consumption. The article first clarifies how a list of axioms enable the obtention of time-dependent recursive utility functions. The properties of the latters are analysed in light of the well-known present bias but also through a temporal smoothing bias that emerges when two successives selves do no share the same aversion to fluctuations. It is shown that this new concept relates to a time-varying Morishima intertemporal elasticity of substitution. The second part of the article brings an axiomatic construction providing a parametric representation that is aimed at a careful account of future and present bias, how they relate to each other or to substitution mechanisms and is finally concerned with the testable implications of the current framework. The theory is finally applied by considering intertemporal choices with Markovian strategies and temporally consistent solutions. For some parameters configurations, there exists a multiplicity of Nash equilibria, and then an indeterminacy in the agent behaviour
Pollution, public debt, and growth: the question of sustainability
No full textInternational audienceThis paper examines an endogenous growth model that allows us to consider the dynamics and sustainability of debt, pollution, and growth. Debt evolves according to the financing adaptation and mitigation efforts and to the damages caused by pollution. Three types of features are important for our analysis: the technology through the negative effect of pollution on TFP; the fiscal policy; the initial level of pollution and debt with respect to capital. Indeed, if the initial level of pollution is too high, the economy is relegated to an endogenous tipping zone where pollution perpetually increases relatively to capital. If the effect of pollution on TFP is too strong, the economy cannot converge to a stable and sustainable long-run balanced growth path. If the income tax rates are high enough, we can converge to a stable balanced growth path with low pollution and high debt relative to capital. This sustainable equilibrium can even be characterized by higher growth and welfare. This last result underlines the role that tax policy can play in reconciling debt and environmental sustainability
France: How taxation can increase inequality
No full textInternational audienceThe evolution of inequality in France is specific compared with most OECD countries. Inequality only started to rise at the end of the 1990s after a period of decline during the 1970s and the 1980s. This late increase partly explains the limited effects of inequality on social, political, and cultural outcomes. However, social gradients like income or education play a considerable role for fields such as health, housing, political participation, or trust in institutions. France is also particular with regard to the role of taxation. This chapter provides evidence about the absence of progressivity in the tax system. It concludes that the reforms implemented during the past decade have contributed to the increase in income inequality
Reprint of: Inequality and optimal monetary policy in the open economy
No full textInternational audienceWe study optimal monetary policy in a tractable Small Open Economy Heterogeneous-Agent New Keynesian (SOE-HANK) model in which households face uninsured idiosyncratic risk and unequal bond-market access. We derive conditions under which optimal policy in our SOE-HANK economy entails domestic producer price stability, extending the ”open-economy divine coincidence” result of Galí and Monacelli (2005) beyond the Representative-Agent benchmark (SOE-RANK). Away from those conditions, inefficient fluctuations in consumption inequality generate monetary policy tradeoffs. Under plausible calibrations for the trade elasticities, the elasticity of intertemporal substitution, and the cyclicality of income risk, the central bank stabilizes output and the exchange rate more than in SOE-RANK