Impacts of extreme weather events on terrestrial carbon sequestration revealed by weather stations in the Northern Hemisphere

TL;DR

This study uses weather station data and machine learning to analyze how extreme weather events like droughts and heatwaves affect terrestrial carbon sequestration in the Northern Hemisphere, revealing significant impacts and the need for improved predictive models.

Contribution

It introduces a station-specific, data-driven approach to assess extreme weather impacts on ecosystem carbon cycling, surpassing previous coarse-resolution analyses.

Findings

Droughts and heatwaves significantly reduce carbon sequestration.

Compound events of droughts and heatwaves have amplified effects.

Precipitation and cold extremes effects may be underestimated.

Abstract

The increasing frequency of global climate extremes has significantly impacted the terrestrial carbon cycle. Extreme weather events such as heatwaves, droughts, and extreme precipitation pose serious threats to ecosystem carbon sequestration. This study investigated the impacts of these extreme events on terrestrial carbon sequestration using data from weather stations in the Northern Hemisphere, by combining weather station observations and machine learning-based Gross Primary Production (GPP) and ecosystem respiration (Reco) estimates. Droughts and heatwaves have the most significant impact, often correlated as compound events. The effects of extreme precipitation and cold extremes may have been underestimated in the past. Whether various extreme events occur in spring or summer led to different mechanisms. We provided a more precise and station-specific analysis compared to using coarse-resolution climate reanalysis and model simulations. It also suggests the need for improved methodologies and the integration of data-driven and process-based models to better predict and understand the effects of extreme weather on ecosystem carbon cycling.