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Land surface conductance linked to precipitation: Co-evolution of vegetation and climate in Earth system models.

Peter J FranksNicholas HeroldGordon B BonanKeith W OlesonJeffrey S DukesMatthew HuberJulian I SchroederPeter M CoxSimon Jones
Published in: Global change biology (2024)
Vegetation and precipitation are known to fundamentally influence each other. However, this interdependence is not fully represented in climate models because the characteristics of land surface (canopy) conductance to water vapor and CO 2 are determined independently of precipitation. Working within a coupled atmosphere and land modelling framework (CAM6/CLM5; coupled Community Atmosphere Model v6/Community Land Model v5), we have developed a new theoretical approach to characterizing land surface conductance by explicitly linking its dynamic properties to local precipitation, a robust proxy for moisture available to vegetation. This will enable regional surface conductance characteristics to shift fluidly with climate change in simulations, consistent with general principles of co-evolution of vegetation and climate. Testing within the CAM6/CLM5 framework shows that climate simulations incorporating the new theory outperform current default configurations across several error metrics for core output variables when measured against observational data. In climate simulations for the end of this century the new, adaptive stomatal conductance scheme provides a revised prognosis for average and extreme temperatures over several large regions, with increased primary productivity through central and east Asia, and higher rainfall through North Africa and the Middle East. The new projections also reveal more frequent heatwaves than originally estimated for the south-eastern US and sub-Saharan Africa but less frequent heatwaves across east Europe and northeast Asia. These developments have implications for evaluating food security and risks from extreme temperatures in areas that are vulnerable to climate change.
Keyphrases
  • climate change
  • human health
  • molecular dynamics
  • healthcare
  • mental health
  • south africa
  • gene expression
  • risk assessment
  • dna methylation
  • machine learning
  • electronic health record
  • genome wide
  • data analysis