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Upscaling hotspots – Understanding the variability of critical land-atmosphere fluxes to strengthen climate models (Spot-On)

Flux processes between the land surface and the air plays an important role for weather and climate. In the 'Spot-On'-project we aim to develop methods to better account for the land surface flux heterogeneity in validations of climate models.

Large eddy simulation of particle dispersion from a hypothetical point source at Finse, Hardangervidda Mountain Plateau/Norway. Figure: Project-team

Large eddy simulation of particle dispersion from a hypothetical point source at Finse, Hardangervidda Mountain Plateau/Norway. Figure: Project-team

About the project

Many important processes take place right where the land and the air above touch each other. To understand such processes has become a scientific imperative as human activities threaten to change our weather and climate systems. We therefore need better predictions for the exchange of greenhouse gases like methane, CO2, and water vapor. A critical limitation to our understanding has long been that the greenhouse gas exchange varies considerably in the landscape.

With this project we aim to develop and apply novel tools to map this variability and compare these observations to climate models, in order to reduce the uncertainties of the predictions given in the models.

Objectives

This project will use recent developments in sensor technology, statistical methods, high performance computing capabilities to deliver high-resolution maps of greenhouse gas fluxes in the landscape. To this end, we will configure a drone swarm with gas analysers that feeds its measurements to a data assimilation algorithm using fluid mechanics to calculate the surface gas exchange.

Based on real-time output while the drones are flying, the system can subsequently repositions individual drones to minimise the uncertainty of the surface map. The ambition is to map large areas comparable to points in global climate models, to be able to compare the greenhouse gas exchange directly.

Targeted case studies in the project will give new insights into critical biogeochemical processes of northern ecosystems, which will fundamentally reduce uncertainties and potential errors in climate projections

Financing

The full project title is 'Upscaling hotspots – understanding the variability of critical land-atmosphere fluxes to strengthen climate models (SpotOn)'. The project is financed by The Research Council of Norway in the FRIPRO-programme, with project number 301552. It is given in the category – Young Research Talents.

Duration: The Spot-On-project started up in 2020 and will end in 2024.

Publications

  • Nickelsen, Trine (2021). Verdens største karbonlager lekker – han måler utslippene. Apollon : Forskningsmagasin for Universitetet i Oslo. ISSN 0803-6926.
  • Aalstad, Kristoffer; Westermann, Sebastian; Pirk, Norbert; Fiddes, Joel & Bertino, Laurent (2021). Retrieving fractional snow-covered area from optical satellites using data assimilation.
  • Aalstad, Kristoffer; Alonso-Gonzalez, Esteban; Bazilova, Varvara; Bertino, Laurent; Fiddes, Joel & Pirk, Norbert [Show all 7 contributors for this article] (2021). Leveraging emerging Earth observations using data assimilation.
  • Nickelsen, Trine (2021). Verdens største karbonlager lekker – han måler utslippene. Apollon : Forskningsmagasin for Universitetet i Oslo. ISSN 0803-6926.
  • Aalstad, Kristoffer; Fiddes, Joel; Martin, Leo Celestin Paul; Alonso-Gonzalez, Esteban; Yilmaz, Yeliz A. & Pirk, Norbert [Show all 7 contributors for this article] (2021). Workshop on downscaling with TopoSCALE for cryospheric applications.
  • Aalstad, Kristoffer; Alonso-Gonzalez, Esteban; Bertino, Laurent; Fiddes, Joel; van Hove, Alouette & Pirk, Norbert [Show all 8 contributors for this article] (2021). Learning from Earth observations using data assimilation.
  • Aalstad, Kristoffer; Alonso-Gonzalez, Esteban; Bazilova, Varvara; Bertino, Laurent; Fiddes, Joel & Filhol, Simon [Show all 9 contributors for this article] (2021). Unmixing satellite imagery using data assimilation to map snow and albedo.

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Published Sep. 28, 2020 10:37 AM - Last modified Mar. 3, 2022 1:25 PM