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Title: Reducing Model Uncertainty of Climate Change Impacts on High Latitude Carbon Assimilation

Abstract

The Arctic Boreal Region (ABR) has a large impact on global vegetation-atmosphere interactions and is experiencing markedly greater warming than the rest of the planet, a trend that is projected to continue with anticipated future emissions of CO2. The ABR is a significant source of uncertainty in estimates of carbon uptake in terrestrial biosphere models (TBMs) such that reducing this uncertainty is critical for more accurately estimating global carbon cycling and understanding the response of the region to global change. Process representation and parameterization associated with gross primary productivity (GPP) drives a large amount of this model uncertainty, particularly within the next 50 years, where the response of existing vegetation to climate change will dominate estimates of GPP for the region. Furthermore, we review our current understanding and model representation of GPP in northern latitudes, focusing on vegetation composition, phenology and physiology, and consider how climate change alters these three components. We highlight challenges in the ABR for predicting GPP, but also focus on the unique opportunities for advancing knowledge and model representation, particularly through the combination of remote sensing and traditional boots-on-the-ground science.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]
  1. Brookhaven National Lab. (BNL), Upton, NY (United States)
  2. Brookhaven National Lab. (BNL), Upton, NY (United States); Univ. of Western Ontario, London, ON (Canada); Duke Univ., Durham, NC (United States)
Publication Date:
Research Org.:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1828308
Alternate Identifier(s):
OSTI ID: 1829521
Report Number(s):
BNL-222318-2021-JAAM
Journal ID: ISSN 1354-1013
Grant/Contract Number:  
SC0012704
Resource Type:
Accepted Manuscript
Journal Name:
Global Change Biology
Additional Journal Information:
Journal Volume: 28; Journal Issue: 4; Journal ID: ISSN 1354-1013
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; arctic; boreal; taiga; tundra; forest; photosynthesis; remote sensing; GPP

Citation Formats

Rogers, Alistair, Serbin, Shawn P., and Way, Danielle A. Reducing Model Uncertainty of Climate Change Impacts on High Latitude Carbon Assimilation. United States: N. p., 2021. Web. doi:10.1111/gcb.15958.
Rogers, Alistair, Serbin, Shawn P., & Way, Danielle A. Reducing Model Uncertainty of Climate Change Impacts on High Latitude Carbon Assimilation. United States. https://doi.org/10.1111/gcb.15958
Rogers, Alistair, Serbin, Shawn P., and Way, Danielle A. Sun . "Reducing Model Uncertainty of Climate Change Impacts on High Latitude Carbon Assimilation". United States. https://doi.org/10.1111/gcb.15958. https://www.osti.gov/servlets/purl/1828308.
@article{osti_1828308,
title = {Reducing Model Uncertainty of Climate Change Impacts on High Latitude Carbon Assimilation},
author = {Rogers, Alistair and Serbin, Shawn P. and Way, Danielle A.},
abstractNote = {The Arctic Boreal Region (ABR) has a large impact on global vegetation-atmosphere interactions and is experiencing markedly greater warming than the rest of the planet, a trend that is projected to continue with anticipated future emissions of CO2. The ABR is a significant source of uncertainty in estimates of carbon uptake in terrestrial biosphere models (TBMs) such that reducing this uncertainty is critical for more accurately estimating global carbon cycling and understanding the response of the region to global change. Process representation and parameterization associated with gross primary productivity (GPP) drives a large amount of this model uncertainty, particularly within the next 50 years, where the response of existing vegetation to climate change will dominate estimates of GPP for the region. Furthermore, we review our current understanding and model representation of GPP in northern latitudes, focusing on vegetation composition, phenology and physiology, and consider how climate change alters these three components. We highlight challenges in the ABR for predicting GPP, but also focus on the unique opportunities for advancing knowledge and model representation, particularly through the combination of remote sensing and traditional boots-on-the-ground science.},
doi = {10.1111/gcb.15958},
journal = {Global Change Biology},
number = 4,
volume = 28,
place = {United States},
year = {Sun Oct 24 00:00:00 EDT 2021},
month = {Sun Oct 24 00:00:00 EDT 2021}
}

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