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Title: The Rainfall Sensitivity of Tropical Net Primary Production in CMIP5 Twentieth- and Twenty-First-Century Simulations

Abstract

In this study, the authors used the relationship between mean annual rainfall (MAR) and net primary production (NPP) (MAR–NPP) observed in tropical forests to evaluate the performance (twentieth century) and predictions (twenty-first century) of tropical NPP from 10 earth system models (ESMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Over the tropical forest domain most of the CMIP5 models showed a positive correlation between NPP and MAR similar to observations. The GFDL, CESM1, CCSM4, and Beijing Normal University (BNU) models better represented the observed MAR–NPP relationship. Compared with observations, the models were able to reproduce the seasonality of rainfall over areas with long dry seasons, but NPP seasonality was difficult to evaluate given the limited observations. From 2006 to 2100, for representative concentration pathway 8.5 (RCP8.5) (and most RCP4.5 simulations) all models projected increases in NPP, but these increases occurred at different rates. By the end of the twenty-first century the models with better performance against observed NPP–MAR projected increases in NPP between ~2% (RCP4.5) and ~19% (RCP8.5) relative to contemporary observations, representing increases of ~9% and ~25% relative to their historical simulations. When climate and CO 2 fertilization are considered as separate controls on plant physiology,more » the current climate yields maximum productivity. Yet, as future climate changes become detrimental to productivity, CO 2 fertilization becomes the dominant response, ending in an overall increase in NPP toward the end of the twenty-first century. Thus, the way in which models represent CO 2 fertilization affects their performance. Additional studies addressing the individual and simultaneous effect of other climate variables on NPP are needed.« less

Authors:
 [1];  [1];  [1];  [1];  [2];  [3]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Univ. of Colorado, Boulder, CO (United States)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1512121
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Climate
Additional Journal Information:
Journal Volume: 28; Journal Issue: 23; Journal ID: ISSN 0894-8755
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Models and modeling; Climate models; General circulation models

Citation Formats

Negrón-Juárez, Robinson I., Riley, William J., Koven, Charles D., Knox, Ryan G., Taylor, Philip G., and Chambers, Jeffrey Q. The Rainfall Sensitivity of Tropical Net Primary Production in CMIP5 Twentieth- and Twenty-First-Century Simulations. United States: N. p., 2015. Web. doi:10.1175/JCLI-D-14-00675.1.
Negrón-Juárez, Robinson I., Riley, William J., Koven, Charles D., Knox, Ryan G., Taylor, Philip G., & Chambers, Jeffrey Q. The Rainfall Sensitivity of Tropical Net Primary Production in CMIP5 Twentieth- and Twenty-First-Century Simulations. United States. doi:10.1175/JCLI-D-14-00675.1.
Negrón-Juárez, Robinson I., Riley, William J., Koven, Charles D., Knox, Ryan G., Taylor, Philip G., and Chambers, Jeffrey Q. Mon . "The Rainfall Sensitivity of Tropical Net Primary Production in CMIP5 Twentieth- and Twenty-First-Century Simulations". United States. doi:10.1175/JCLI-D-14-00675.1. https://www.osti.gov/servlets/purl/1512121.
@article{osti_1512121,
title = {The Rainfall Sensitivity of Tropical Net Primary Production in CMIP5 Twentieth- and Twenty-First-Century Simulations},
author = {Negrón-Juárez, Robinson I. and Riley, William J. and Koven, Charles D. and Knox, Ryan G. and Taylor, Philip G. and Chambers, Jeffrey Q.},
abstractNote = {In this study, the authors used the relationship between mean annual rainfall (MAR) and net primary production (NPP) (MAR–NPP) observed in tropical forests to evaluate the performance (twentieth century) and predictions (twenty-first century) of tropical NPP from 10 earth system models (ESMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Over the tropical forest domain most of the CMIP5 models showed a positive correlation between NPP and MAR similar to observations. The GFDL, CESM1, CCSM4, and Beijing Normal University (BNU) models better represented the observed MAR–NPP relationship. Compared with observations, the models were able to reproduce the seasonality of rainfall over areas with long dry seasons, but NPP seasonality was difficult to evaluate given the limited observations. From 2006 to 2100, for representative concentration pathway 8.5 (RCP8.5) (and most RCP4.5 simulations) all models projected increases in NPP, but these increases occurred at different rates. By the end of the twenty-first century the models with better performance against observed NPP–MAR projected increases in NPP between ~2% (RCP4.5) and ~19% (RCP8.5) relative to contemporary observations, representing increases of ~9% and ~25% relative to their historical simulations. When climate and CO2 fertilization are considered as separate controls on plant physiology, the current climate yields maximum productivity. Yet, as future climate changes become detrimental to productivity, CO2 fertilization becomes the dominant response, ending in an overall increase in NPP toward the end of the twenty-first century. Thus, the way in which models represent CO2 fertilization affects their performance. Additional studies addressing the individual and simultaneous effect of other climate variables on NPP are needed.},
doi = {10.1175/JCLI-D-14-00675.1},
journal = {Journal of Climate},
number = 23,
volume = 28,
place = {United States},
year = {2015},
month = {12}
}

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