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Spectrally refined unbiased Monte Carlo estimate of the Earth's global radiative cooling

  • Yaniss Nyffenegger-Péré
  • , Raymond Armante
  • , Mégane Bati
  • , Stéphane Blanco
  • , Jean Louis Dufresne
  • , Mouna El Hafi
  • , Vincent Eymet
  • , Vincent Forest
  • , Richard Fournier
  • , Jacques Gautrais
  • , Raphaël Lebrun
  • , Nicolas Mellado
  • , Nada Mourtaday
  • , Mathias Paulin
  • Université de Toulouse
  • Instituto de Astrofísica de Andalucía-CSIC
  • Sorbonne Université
  • Centre national de la recherche scientifique
  • Université de Toulouse
  • Méso-Star
  • Toulouse University

Research output: Contribution to journalArticlepeer-review

Abstract

The Earth's radiative cooling is a key driver of climate. Determining how it is affected by greenhouse gas concentration is a core question in climate-change sciences. Due to the complexity of radiative transfer processes, current practices to estimate this cooling require the development and use of a suite of radiative transfer models whose accuracy diminishes as we move from local, instantaneous estimates to global estimates over the whole globe and over long periods of time (decades). Here, we show that recent advances in nonlinear Monte Carlo methods allow a paradigm shift: a completely unbiased estimate of the Earth's infrared cooling to space can be produced using a single model, integrating the most refined spectroscopic models of molecular gas energy transitions over a global scale and over years, all at a very low computational cost (a few seconds).

Original languageEnglish
Article numbere2315492121
JournalProceedings of the National Academy of Sciences of the United States of America
Volume121
Issue number5
DOIs
Publication statusPublished - 1 Jan 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Monte Carlo
  • climate change
  • line-by-line
  • radiative forcing

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