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Forest management greatly affects the distribution of tree species and the age class composition of a forest, shaping its overall structure and functioning, and in turn, surface-atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management, good accounts of forest structure are necessary. Here, using Fennoscandia as a case study, we make use of regional National Forest Inventory (NFI) data to systematically classify forest cover into groups of similar aboveground forest structure. An enhanced forest classification scheme and related Look-Up-Table (LUT) of key forest structural parameter values was developed, and the classification was applied for NFI maps from Norway, Sweden and Finland. To provide a complete surface representation, our product was integrated with the European Space Agency Climate Change Intiative's Land Cover (ESA CCI LC) map of present land cover (v.1.6.1) (http://maps.elie.ucl.ac.be/CCI/). An enhanced grouping by aboveground structure can improve climate predictions in intensively managed forested regions and is consistent with climate model routines that simulate the effects of land transitions through area-based changes in vegetation cover. Further, such a classification scheme is congruent with existing forestry tools employed to predict the evolution of forest structure over interannual time scales, and as such, may be viewed as a tool that links the climate and forest modeling communities. [ABSTRACT FROM AUTHOR]

Vegetation optical properties have a direct impact on canopy radiation absorption and scattering and are thus needed for modeling surface fluxes. Although Plant Functional Type (PFT) classification varies between different land surface models, they all must specify optical properties of their PFTs. The aim of this study is to revisit the 'time-invariant optical properties table of SiB' (later referred as 'SiB-table') presented 30-years ago (in 1989) by Dorman and Sellers, which have been adapted to suit different land surface models such as Community Land Models (CLMs) or land surface model developed at the Institut d'Astronomie et de Ge´ophysique Georges Lemaıˆtre (IAGL). The revisit is needed, as some of data underlying the SiB-table is not formally reviewed or published, or is based on earlier research citing even older papers or personal communications (i.e. the validity of the source data cannot be rigorously examined due to a lack of transparency and diversity in methods used to measure or obtain the data). As many of today's land surface models either rely on the optical properties tracing back to the original SiB-table, or data which are not well-documented or made readily transparent, there is clear need to verify (and confirm or correct) the validity of the PFT-dependent optical properties based on data collected and stored using present-day research norms and documentation standards. We base our assessment of the PFT-dependent optical properties on reputable data stored into openly available online archives using CLM PFT-classification as an example, as it is well known and provides sufficient differentiation between different vegetation covers. [ABSTRACT FROM AUTHOR]