A few extreme events dominate global interannual variability in gross primary production

Understanding the impacts of climate extremes on the carbon cycle is important for quantifying the carbon-cycle climate feedback and highly relevant to climate change assessments. Climate extremes and fires can have severe regional effects, but a spatially explicit global impact assessment is still lacking. Here, we directly quantify spatiotemporal contiguous extreme anomalies in four global data sets of gross primary production (GPP) over the last 30 years. We find that positive and negative GPP extremes occurring on 7% of the spatiotemporal domain explain 78% of the global interannual variation in GPP and a significant fraction of variation in the net carbon flux. The largest thousand negative GPP extremes during 1982?2011 (4.3% of the data) account for a decrease in photosynthetic carbon uptake of about 3.5?Pg?C?yr?1, with most events being attributable to water scarcity. The results imply that it is essential to understand the nature and causes of extremes to understand current and future GPP variability.

[1]  T. Vesala,et al.  Reduction of ecosystem productivity and respiration during the European summer 2003 climate anomaly: a joint flux tower, remote sensing and modelling analysis , 2007 .

[2]  P. Ciais,et al.  The impacts of climate change on water resources and agriculture in China , 2010, Nature.

[3]  J. Aber,et al.  A generalized, lumped-parameter model of photosynthesis, evapotranspiration and net primary production in temperate and boreal forest ecosystems , 1992, Oecologia.

[4]  Axel Kleidon,et al.  A method of determining rooting depth from a terrestrial biosphere model and its impacts on the global water and carbon cycle , 1998 .

[5]  C. H. R I S T O P H E R P O T T E R,et al.  Major Disturbance Events in Terrestrial Ecosystems Detected Using Global Satellite Data Sets , 2003 .

[6]  Peter Troch,et al.  Observed timescales of evapotranspiration response to soil moisture , 2006 .

[7]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[8]  Christian Körner,et al.  Slow in, Rapid out--Carbon Flux Studies and Kyoto Targets , 2003, Science.

[9]  Scott V. Ollinger,et al.  Environmental variation is directly responsible for short‐ but not long‐term variation in forest‐atmosphere carbon exchange , 2007 .

[10]  A. Arneth,et al.  Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations , 2011 .

[11]  Pierre Friedlingstein,et al.  Carbon and nitrogen cycle dynamics in the O‐CN land surface model: 2. Role of the nitrogen cycle in the historical terrestrial carbon balance , 2010 .

[12]  J. Randerson,et al.  Forecasting Fire Season Severity in South America Using Sea Surface Temperature Anomalies , 2011, Science.

[13]  S S I T C H,et al.  Evaluation of Ecosystem Dynamics, Plant Geography and Terrestrial Carbon Cycling in the Lpj Dynamic Global Vegetation Model , 2022 .

[14]  Vladimir Kossobokov,et al.  Extreme events: dynamics, statistics and prediction , 2011 .

[15]  Cheng Li,et al.  Changes in climate extremes and their impact on wheat yield in Tianshan Mountains region, northwest China , 2016, Environmental Earth Sciences.

[16]  Atul K. Jain,et al.  The global carbon budget 1959-2011 , 2012 .

[17]  N. Batjes,et al.  The Harmonized World Soil Database , 2009 .

[18]  Pang-Ning Tan,et al.  Major disturbance events in terrestrial ecosystems detected using global satellite data sets , 2003 .

[19]  W. Oechel,et al.  FLUXNET: A New Tool to Study the Temporal and Spatial Variability of Ecosystem-Scale Carbon Dioxide, Water Vapor, and Energy Flux Densities , 2001 .

[20]  Patrick J. Bartlein,et al.  VEGETATION AND CLIMATE CHANGE IN EASTERN NORTH AMERICA SINCE THE LAST GLACIAL MAXIMUM , 1991 .

[21]  R. Q. Thomas,et al.  Clustered disturbances lead to bias in large-scale estimates based on forest sample plots. , 2008, Ecology letters.

[22]  Christopher B. Field,et al.  Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: List of Major IPCC Reports , 2012 .

[23]  Markus Reichstein,et al.  Detection and attribution of large spatiotemporal extreme events in Earth observation data , 2013, Ecol. Informatics.

[24]  T. Huntington.  Evidence for intensification of the global water cycle: Review and synthesis , 2006 .

[25]  S. Seneviratne,et al.  Hot days induced by precipitation deficits at the global scale , 2012, Proceedings of the National Academy of Sciences.

[26]  Philippe Ciais,et al.  Terrestrial biosphere model performance for inter‐annual variability of land‐atmosphere CO2 exchange , 2012 .

[27]  Maosheng Zhao,et al.  A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production , 2004 .

[28]  J. Kok,et al.  The physics of wind-blown sand and dust , 2012, Reports on progress in physics. Physical Society.

[29]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[30]  F. Zwiers,et al.  Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections , 2013 .

[31]  I. C. Prentice,et al.  A dynamic global vegetation model for studies of the coupled atmosphere‐biosphere system , 2005 .

[32]  I. C. Prentice,et al.  Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model , 2003 .

[33]  Andrew D. Friend,et al.  Carbon and nitrogen cycle dynamics in the O‐CN land surface model: 1. Model description, site‐scale evaluation, and sensitivity to parameter estimates , 2010 .

[34]  Maosheng Zhao,et al.  Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009 , 2010, Science.

[35]  S. Seneviratne,et al.  Global Convergence in the Temperature Sensitivity of Respiration at Ecosystem Level , 2010, Science.

[36]  J. Randerson,et al.  An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker , 2007, Proceedings of the National Academy of Sciences.

[37]  P. Vellinga,et al.  Climate Change and Extreme Weather Events , 2000 .

[38]  F. Woodward,et al.  Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate , 2010, Science.

[39]  Mark E. J. Newman,et al.  Power-Law Distributions in Empirical Data , 2007, SIAM Rev..

[40]  Melinda D. Smith.  An ecological perspective on extreme climatic events: a synthetic definition and framework to guide future research , 2011 .

[41]  C. Rosenzweig,et al.  Climate Change and Extreme Weather Events; Implications for Food Production, Plant Diseases, and Pests , 2001 .

[42]  Jason P. Kaye,et al.  Long‐term impact of a stand‐replacing fire on ecosystem CO2 exchange of a ponderosa pine forest , 2008 .

[43]  Magnus Nyström,et al.  Reserves, Resilience and Dynamic Landscapes , 2003, Ambio.

[44]  C. Federer,et al.  Transpirational supply and demand: Plant, soil, and atmospheric effects evaluated by simulation , 1982 .

[45]  Benjamin Lloyd-Hughes,et al.  A spatio‐temporal structure‐based approach to drought characterisation , 2012 .

[46]  O. Phillips,et al.  The 2010 Amazon Drought , 2011, Science.

[47]  Ricardo García-Herrera,et al.  The Hot Summer of 2010: Redrawing the Temperature Record Map of Europe , 2011, Science.

[48]  S. Seneviratne,et al.  Climate extremes and the carbon cycle , 2013, Nature.

[49]  J. Randerson,et al.  Assessing variability and long-term trends in burned area by merging multiple satellite fire products , 2009 .

[50]  Guirui Yu,et al.  Regional drought-induced reduction in the biomass carbon sink of Canada's boreal forests , 2012, Proceedings of the National Academy of Sciences.

[51]  P. Ciais,et al.  Europe-wide reduction in primary productivity caused by the heat and drought in 2003 , 2005, Nature.