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Peter E. Thornton

Researcher at Oak Ridge National Laboratory

Publications -  237
Citations -  32498

Peter E. Thornton is an academic researcher from Oak Ridge National Laboratory. The author has contributed to research in topics: Carbon cycle & Climate change. The author has an hindex of 74, co-authored 227 publications receiving 27754 citations. Previous affiliations of Peter E. Thornton include National Center for Atmospheric Research & University of Montana.

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Journal ArticleDOI

TRY - a global database of plant traits

Jens Kattge, +136 more
TL;DR: TRY as discussed by the authors is a global database of plant traits, including morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs, which can be used for a wide range of research from evolutionary biology, community and functional ecology to biogeography.
Book ChapterDOI

Carbon and Other Biogeochemical Cycles

TL;DR: For base year 2010, anthropogenic activities created ~210 (190 to 230) TgN of reactive nitrogen Nr from N2 as discussed by the authors, which is at least 2 times larger than the rate of natural terrestrial creation of ~58 Tg N (50 to 100 Tg nr yr−1) (Table 6.9, Section 1a).
Journal ArticleDOI

Generating surfaces of daily meteorological variables over large regions of complex terrain

TL;DR: In this paper, a method for generating daily surfaces of temperature, precipitation, humidity, and radiation over large regions of complex terrain is presented, based on the spatial convolution of a truncated Gaussian weighting filter with the set of station locations.
Journal ArticleDOI

Parameterization improvements and functional and structural advances in version 4 of the Community Land Model

TL;DR: The Community Land Model (CLM) as discussed by the authors is the land component of the Community Climate System Model (CCSM) and has been extended with a carbon-nitrogen (CN) biogeochemical model that is prognostic with respect to vegetation, litter, and soil carbon and nitrogen states.
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A continental phenology model for monitoring vegetation responses to interannual climatic variability

TL;DR: In this article, the authors developed predictive phenology models based on traditional phenology research using commonly available meteorological and climatological data and compared with satellite phenology observations at numerous 20 km x 20 km contiguous landcover sites.