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FRINATEK-Fri prosj.st. mat.,naturv.,tek

Upscaling hotspots - understanding the variability of critical land-atmosphere fluxes to strengthen climate models

Alternative title: Beregne punktkilder - forstå variabiliteten av kritiske flukser mellom landoverflaten og atmosfæren for å styrke klimamodeller

Awarded: NOK 8.0 mill.

Many important processes take place right where the land and the air above touch each other. Understanding these 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. This project will therefore develop and apply novel tools to map this variability and compare these observations to climate models, in order to reduce the uncertainties of their predictions. This project will use recent developments in sensor technology, statistical methods, and 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 inversely 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. So far in the project, we have implemented the data assimilation framework that couples observations and the fluid dynamical model simulations to estimate surface flux parameters. We have tested this extensively in experiments with synthetic data and are in the process of writing a manuscript about this work, which looks promising. We have also developed the drone and sensor hardware considerably, and have had about 50 flights during field campaigns at our measurement stations. We are in the process of writing a manuscript about this field campaigns to prove the applicability of the method and compare it to established flux measurement techniques.

Understanding the interactions between the land surface and the atmosphere has become a scientific imperative as human activities threaten to excite irreversible changes in our weather and climate systems. The urgent need for stronger predictive capabilities for fluxes of greenhouse gases like methane, CO2, and water vapor asks for advancements of in-situ flux measurements and Earth System Models (ESMs), as well as the comparisons between the two. A critical limitation to such data-model comparisons has long been the large spatial flux variability in the scale gap between ESMs and site observations. This project will therefore develop and apply novel tools to map spatial flux variability of crucial greenhouse gas fluxes to bridge the gap between in-situ flux observations and ESMs, thereby facilitating direct model validation, and ultimately reducing the uncertainty in climate model predictions. This project aims to capitalise on recent advances in sensor technology, statistical methods, high performance computing capabilities to build a full-stack solution that can 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 large eddy simulations to calculate surface fluxes and their uncertainties. Based on real-time output while the drones are flying, the system can subsequently repositions individual drones to minimise the uncertainty of the surface flux map. The ambition is to map areas comparable to ESM grid-cell size, to be able to upscale and compare greenhouse gas fluxes directly. Targeted case studies in SPOT-ON will give new insights into critical biogeochemical processes of northern high latitude ecosystems, which will fundamentally reduce uncertainties and potential errors in climate projections.

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FRINATEK-Fri prosj.st. mat.,naturv.,tek