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dc.contributor.authorAlessandri, Andrea
dc.contributor.authorCatalano, Franco
dc.contributor.authorde Felice, Matteo
dc.contributor.authorvan der Hurk, Bart
dc.contributor.authorDoblas-Reyes, Francisco
dc.contributor.authorBoussetta, Souhail
dc.contributor.authorBalsamo, Gianpaolo
dc.contributor.authorMiller, Paul A.
dc.contributor.otherBarcelona Supercomputing Center
dc.identifier.citationAlessandri, A. [et al.]. Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth. "Climate Dynamics", Agost 2017, vol. 49, núm. 4, p. 1215-1237.
dc.description.abstractThe 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.
dc.description.sponsorshipThis work was supported by the European Union Seventh Framework Programme (FP7/2007-13) under Grant 308378 (SPECS Project; The ECMWF experiments were supported by the EU-FP7 ImagineS project (http://fp7-imagines. eu/) in support to the Copernicus Global land. Further support was provided to this work by the European Union’s Horizon 2020 research and innovation programme under grant agreement N. 641816 (CRESCENDO project; and under grant agreement N. 704585 (PROCEED project). Acknowledgement is made for the use of ECMWF’s computing and archive facilities in this research (special project SPITALES).
dc.format.extent23 p.
dc.subjectÀrees temàtiques de la UPC::Energies
dc.subject.lcshClimate science
dc.subject.lcshVegetation and climate
dc.subject.lcshEarth system -- environmental sciences
dc.subject.otherClimate prediction
dc.subject.otherClimate simulation
dc.subject.otherVegetation dynamics
dc.subject.otherLand-climate interactions
dc.subject.otherEarth system modeling
dc.subject.otherMulti-scale prediction enhancement
dc.titleMulti-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth
dc.subject.lemacVegetació i clima
dc.subject.lemacCiències de la terra
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/308378/EU/Seasonal-to-decadal climate Prediction for the improvement of EuropeanClimate Services/SPECS
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/641816/EU/Coordinated Research in Earth Systems and Climate: Experiments, kNowledge, Dissemination and Outreach/CRESCENDO
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/704585/EU/PROCess-based sEamless development of useful Earth system predictions over lanD/PROCEED
upcommons.citation.publicationNameClimate Dynamics

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