Beer, C.

Carvalhais, N.

Kompter, E.

Santoro, M.

Schepaschenko, D.

Shvidenko, A.

Thurner, M.

Wutzler, T.

International Institute for Applied Systems Analysis (IIASA)

Geophysical Research AbstractsVol. 15, EGU2013-9784, 2013EGU General Assembly 2013© Author(s) 2013. CC Attribution 3.0 License.Derivation of a northern-hemispheric biomass map for use in globalcarbon cycle modelsMartin Thurner (1), Christian Beer (1), Maurizio Santoro (2), Nuno Carvalhais (1,3), Thomas Wutzler (1), DmitrySchepaschenko (4), Anatoly Shvidenko (4), Elisabeth Kompter (1), Shaun Levick (1), and Christiane Schmullius(5)(1) Max Planck Institute for Biogeochemistry, Jena, Germany (mthurn@bgc-jena.mpg.de), (2) Gamma Remote Sensing,Gümligen, Switzerland, (3) Departamento de Ciências e Engenharia do Ambiente, Faculdade de Ciências e Tecnologia,Universidade Nova de Lisboa, Portugal, (4) International Institute for Applied Systems Analysis, Laxenburg, Austria, (5)Earth Observation, Institute of Geography, Friedrich-Schiller-University, Jena, GermanyQuantifying the state and the change of the World’s forests is crucial because of their ecological, social and eco-nomic value. Concerning their ecological importance, forests provide important feedbacks on the global carbon,energy and water cycles. In addition to their influence on albedo and evapotranspiration, they have the potentialto sequester atmospheric carbon dioxide and thus to mitigate global warming. The current state and inter-annualvariability of forest carbon stocks remain relatively unexplored, but remote sensing can serve to overcome thisshortcoming. While for the tropics wall-to-wall estimates of above-ground biomass have been recently published,up to now there was a lack of similar products covering boreal and temperate forests.Recently, estimates of forest growing stock volume (GSV) were derived from ENVISAT ASAR C-band data forlatitudes above 30˚N. Utilizing a wood density and a biomass compartment database, a forest carbon density mapcovering North-America, Europe and Asia with 0.01˚ resolution could be derived out of this dataset. Allomet-ric functions between stem, branches, root and foliage biomass were fitted and applied for different leaf types(broadleaf, needleleaf deciduous, needleleaf evergreen forest). Additionally, this method enabled uncertainty es-timation of the resulting carbon density map. Intercomparisons with inventory-based biomass products in Russia,Europe and the USA proved the high accuracy of this approach at a regional scale (r2 = 0.70 – 0.90).Based on the final biomass map, the forest carbon stocks and densities (excluding understorey vegetation) forthree biomes were estimated across three continents. While 40.7 ± 15.7 Gt of carbon were found to be storedin boreal forests, temperate broadleaf/mixed forests and temperate conifer forests contain 24.5 ± 9.4 Gt(C) and14.5±4.8 Gt(C), respectively. In terms of carbon density, most of the carbon per area is stored in temperate conifer(62.1±20.7 Mg(C)/ha(Forest)) and broadleaf/mixed forests (58.0±22.1 Mg(C)/ha(Forest)), whereas boreal forestshave a carbon density of only 40.0 ± 15.4 Mg(C)/ha(Forest). While European forest carbon stocks are relativelysmall, the carbon density is higher compared to the other continents.The derived biomass map substantially improves the knowledge on the current carbon stocks of the northern-hemispheric boreal and temperate forests, serving as a new benchmark for spatially explicit and consistent biomassmapping with moderate spatial resolution. This product can be of great value for global carbon cycle models as wellas national carbon monitoring systems. Further investigations concentrate on improving biomass parameterizationsand representations in such kind of models. The presented map will help to improve the simulation of biomassspatial patterns and variability and enables identifying the dominant influential factors like climatic conditions anddisturbances.

Derivation of a northern-hemispheric biomass map for use in global carbon cycle models

Derivation of a northern-hemispheric biomass map for use in global carbon cycle models

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