13 June 2017

Competing Influences on Aridity: Present and future

How anthropogenic warming, ENSO, and plant physiology impact future terrestrial aridity

Science

While most droughts relief occur once a favorable phase of El Niño-Southern Oscillation (ENSO) returns, most climate projections show a signal of persistent 21st century increases in aridity in response to CO2-induced warming. These projections, however, often rely on aridity indices based on atmospheric evaporative demand estimates (PET, potential evapotranspiration) that assume a CO2-invariant value for plants stomatal resistance. (i.e, the opening in leaves regulating regulate transpiration and plant CO2 intake).

The scientific team, composed of LLNL, GISS, and INRA scientists analyzed atmosphere -only experiments to identify land regions in which aridity is currently sensitive to ENSO, and where projected future changes in mean aridity exceed the range caused by ENSO variability. Insights into the drivers of these aridity changes are obtained in simulations with incremental addition of three different factors to current climate: 1) the ocean warming; 2) the vegetation response to elevated CO2 levels; and 3) the intensified CO2 radiative forcing.

 

 

 

Impact

Impact 1: Future aridity will increase in ∼70% of the regions where aridity is currently driven by ENSO variability. When both radiative and physiological effects are also considered, the area affected by aridity rises to about 75-79% when using PET-derived measures of aridity. This prediction is much weaker (41%) when total soil moisture aridity indicator is employed. This reduction mainly occurs because plant stomatal resistance increases under enhanced CO2 concentrations, which results in improved plant water use efficiency, and hence reduced evapotranspiration and soil desiccation.

Impact 2: Imposing CO2-invariant stomatal resistance may have overestimated future drying in PET-derived indices in previous studies.

Summary

While most droughts relief occur once a favorable phase of El Niño-Southern Oscillation (ENSO) returns, most climate projections show a signal of persistent 21st century increases in aridity in response to CO2-induced warming. These projections, however, often rely on aridity indices based on atmospheric evaporative demand estimates (PET, potential evapotranspiration) that assume a CO2-invariant value for plants stomatal resistance (i.e, the opening in leaves regulating regulate transpiration and plant CO2 intake).

The scientific team, composed of LLNL, GISS, and INRA scientists analyzed atmosphere-only experiments to identify land regions in which aridity is currently sensitive to ENSO, and where projected future changes in mean aridity exceed the range caused by ENSO variability. Insights into the drivers of these aridity changes are obtained in simulations with incremental addition of three different factors to current climate: 1) the ocean warming; 2) the vegetation response to elevated CO2 levels; and 3) the intensified CO2 radiative forcing.

Due to a worldwide increase in potential evapotranspiration (PET), aridity increases in about 70% of the regions where aridity is currently driven by ENSO variability. When both radiative and physiological effects are also considered, the area affected by aridity rises to about 75-79% when using PET-derived measures of aridity. This prediction is much weaker (41%) when total soil moisture aridity indicator is employed. This reduction mainly occurs because plant stomatal resistance increases under enhanced CO2 concentrations, which results in improved plant water use efficiency, and hence reduced evapotranspiration and soil desiccation. Imposing a CO2-invariant stomatal resistance to plants may overestimate future drying in PET-derived indices.

Contact
Celine Bonfils
Lawrence Livermore National Laboratory
Funding
Programs
  • Earth System Modeling
  • Regional & Global Climate Modeling
Projects
  • Early Career: Detection and Attribution of Regional Climate Change with a Focus on the Precursors of Droughts
  • The Climate Model Analysis and Intercomparison Project at the Program for Climate Model Diagnosis