Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

Abstract The EC-Earth earth system model has been
recently developed to include the dynamics of vegetation.
In its original formulation, vegetation variability is simply
operated by the Leaf Area Index (LAI), which affects climate
basically by changing the vegetation physiological
resistance to evapotranspiration. This coupling has been
found to have only a weak effect on the surface climate
modeled by EC-Earth. In reality, the effective sub-grid
vegetation fractional coverage will vary seasonally and at
interannual time-scales in response to leaf-canopy growth,
phenology and senescence. Therefore it affects biophysical
parameters such as the albedo, surface roughness and
soil field capacity. To adequately represent this effect in
EC-Earth, we included an exponential dependence of the
vegetation cover on the LAI. By comparing two sets of
simulations performed with and without the new variable
fractional-coverage parameterization, spanning from centennial
(twentieth century) simulations and retrospective
predictions to the decadal (5-years), seasonal and weather
time-scales, we show for the first time a significant multiscale
enhancement of vegetation impacts in climate simulation
and prediction over land. Particularly large effects at
multiple time scales are shown over boreal winter middleto-
high latitudes over Canada, West US, Eastern Europe,
Russia and eastern Siberia due to the implemented timevarying
shadowing effect by tree-vegetation on snow surfaces.
Over Northern Hemisphere boreal forest regions the
improved representation of vegetation cover tends to correct
the winter warm biases, improves the climate change
sensitivity, the decadal potential predictability as well as
the skill of forecasts at seasonal and weather time-scales.
Significant improvements of the prediction of 2 m temperature
and rainfall are also shown over transitional land surface
hot spots. Both the potential predictability at decadal
time-scale and seasonal-forecasts skill are enhanced over
Sahel, North American Great Plains, Nordeste Brazil and
South East Asia, mainly related to improved performance
in the surface evapotranspiration.