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 multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying 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.
Highlights
The notion of seamless prediction is at the hearth of the World Meteorological Organization strategic framework aimed at the development of a new generation of dynamical climate forecasting tools based on Earth System Models (ESMs; World Meteorological Organization 2015).The seamless concept originates from the fact that the Earth System exhibits a wide range of dynamical, physical, biological, and chemical interactions involving spatial and temporal variability continuously spanning all weather/climate scales
3 Institut Català de Ciències del Clima (IC3), Barcelona, Spain 4 European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK 5 Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain 6 Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC-CNS), Barcelona, Spain 7 Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden fractional-coverage parameterization, spanning from centennial 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
The exactly same initialization for all model components of the MODIFdec and the CTRLdec decadal predictability experiments is used, the only difference is that in CTRLdec the new effective vegetation cover parameterization has been switched off and as a consequence the vegetation densities are constant in time
Summary
The notion of seamless prediction is at the hearth of the World Meteorological Organization strategic framework aimed at the development of a new generation of dynamical climate forecasting tools based on Earth System Models (ESMs; World Meteorological Organization 2015). To properly represent vegetation variability in HTESSEL and the coupling with the overlying atmosphere (IFS) in EC-Earth, we designed a modified version of the code to allow vegetation effective fractional coverage to change as a function of LAI for both low and high vegetation To this aim an exponential dependence of the vegetation densities to LAI has been introduced in HTESSEL following the approach described in Alessandri et al (2007) and to what already implemented in other land surface models (e.g. Organizing Carbon and Hydrology In Dynamic Ecosystems, ORCHIDEE; Krinner et al 2005).
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