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Andrew D. Friend
Researcher at University of Cambridge
Publications - 83
Citations - 14514
Andrew D. Friend is an academic researcher from University of Cambridge. The author has contributed to research in topics: Climate change & Ecosystem. The author has an hindex of 40, co-authored 77 publications receiving 13034 citations.
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Journal ArticleDOI
Europe-wide reduction in primary productivity caused by the heat and drought in 2003
Philippe Ciais,Markus Reichstein,Nicolas Viovy,A. Granier,Jérôme Ogée,Vincent Allard,M. Aubinet,Nina Buchmann,C. Bernhofer,Arnaud Carrara,Frédéric Chevallier,N. de Noblet,Andrew D. Friend,Pierre Friedlingstein,Thomas Grünwald,Bernard Heinesch,Petri Keronen,Alexander Knohl,Gerhard Krinner,Denis Loustau,Giovanni Manca,Giorgio Matteucci,Franco Miglietta,Jean-Marc Ourcival,Dario Papale,Kim Pilegaard,Serge Rambal,G. Seufert,Jean-François Soussana,María José Sanz,Ernst Detlef Schulze,Timo Vesala,Riccardo Valentini +32 more
TL;DR: An increase in future drought events could turn temperate ecosystems into carbon sources, contributing to positive carbon-climate feedbacks already anticipated in the tropics and at high latitudes.
Journal ArticleDOI
Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models
Wolfgang Cramer,Alberte Bondeau,F. Ian Woodward,I. Colin Prentice,Richard Betts,Victor Brovkin,Peter M. Cox,Veronica A. Fisher,Jonathan A. Foley,Andrew D. Friend,Christopher J. Kucharik,Mark R. Lomas,Navin Ramankutty,Stephen Sitch,Benjamin Smith,Andrew White,Christine Young-Molling +16 more
TL;DR: In this paper, the possible responses of ecosystem processes to rising atmospheric CO2 concentration and climate change are illustrated using six dynamic global vegetation models that explicitly represent the interactions of ecosystem carbon and water exchanges with vegetation dynamics.
Journal ArticleDOI
Efficacy of climate forcings
James Hansen,James Hansen,Makiko Sato,Reto Ruedy,Larissa Nazarenko,Andrew A. Lacis,Andrew A. Lacis,Gavin A. Schmidt,Gavin A. Schmidt,Gary L. Russell,I. Aleinov,Mike Bauer,Susanne E. Bauer,N. Bell,Brian Cairns,Vittorio Canuto,Mark A. Chandler,Yu Cheng,A. D. Del Genio,A. D. Del Genio,G. Faluvegi,Eric L. Fleming,Andrew D. Friend,Timothy M. Hall,Timothy M. Hall,Charles H. Jackman,M. Kelley,Nancy Y. Kiang,D. Koch,D. Koch,Judith Lean,J. Lerner,Ken K. Lo,Surabi Menon,Ron L. Miller,Ron L. Miller,Patrick Minnis,T. Novakov,Valdar Oinas,Ja. Perlwitz,J. Perlwitz,David Rind,David Rind,Anastasia Romanou,Anastasia Romanou,Drew Shindell,Drew Shindell,Peter Stone,Shan Sun,Shan Sun,N. Tausnev,D. Thresher,Bruce A. Wielicki,Takmeng Wong,Mao-Sung Yao,S. Zhang +55 more
TL;DR: The authors used a global climate model to compare the effectiveness of many climate forcing agents for producing climate change and found that replacing traditional instantaneous and adjusted forcings with an easily computed alternative, Fs, yields a better predictor of climate change, i.e., its efficacies are closer to unity.
Journal ArticleDOI
Present-Day Atmospheric Simulations Using GISS ModelE: Comparison to In Situ, Satellite, and Reanalysis Data
Gavin A. Schmidt,Reto Ruedy,James Hansen,Igor Aleinov,N. Bell,Mike Bauer,Susanne E. Bauer,Brian Cairns,Vittorio Canuto,Y. Cheng,Anthony D. Del Genio,Greg Faluvegi,Andrew D. Friend,Timothy M. Hall,Yongyun Hu,Max Kelley,Nancy Y. Kiang,Dorothy Koch,Andrew A. Lacis,Jean Lerner,Ken K. Lo,Ron L. Miller,Larissa Nazarenko,Valdar Oinas,J. P. Perlwitz,Judith Perlwitz,David Rind,Anastasia Romanou,Gary L. Russell,Makiko Sato,Drew Shindell,Peter Stone,Shan Sun,N. Tausnev,Duane Thresher,Mao-Sung Yao +35 more
TL;DR: The ModelE version of the GISS atmospheric general circulation model (GCM) and results for present-day climate simulations (ca. 1979) were presented in this article, where the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced.
Journal ArticleDOI
A process-based, terrestrial biosphere model of ecosystem dynamics (Hybrid v3.0)
TL;DR: In this paper, a numerical process-based model of terrestrial ecosystem dynamics is described and tested, which combines a mass-balance approach with the capacity to predict the relative dominance of different species or generalised plant types.