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Title: Rapidly changing high-latitude seasonality: Implications for the 21st century carbon cycle in Alaska: Modeling Archive

Abstract

This Modeling Archive is in support of an NGEE Arctic publication ?Rapidly changing high-latitude seasonality: Implications for the 21st century carbon cycle in Alaska? DOI: 10.1088/1748-9326/ac4362.The dataset contains ?ecosys? model outputs reported in Shirley et al. (2022) that explored how climate warming will shift carbon cycle seasonality in Alaska. The study used analysis of seasonal dynamics to support the prediction that high-latitude ecosystems are carbon sinks and will continue to accumulate carbon throughout the century. The study predicts surprisingly large increases in spring net carbon uptake that result in larger net carbon uptake in spring than in summer by year 2100.Included as *.nc files are modeled daily net ecosystem exchange (NEE), net primary productivity (NPP), heterotrophic respiration (Rh), autotrophic respiration (Ra), gross primary productivity (GPP), and plant nitrogen uptake. The output is provided (1) at 25 km resolution across Alaska; (2) for years 2010 through 2100. Scripts to generate publication figures included as text files (*.m) from MATLAB.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological andmore » Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).« less

Authors:
ORCiD logo; ORCiD logo; ORCiD logo;
Publication Date:
Research Org.:
Next Generation Ecosystems Experiment - Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US); NGEE Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Contributing Org.:
ORNL
OSTI Identifier:
1861071
Report Number(s):
NGA275
DOE Contract Number:  
DE-AC05-00OR22725
Resource Type:
Data
Country of Publication:
United States
Availability:
ORNL
Language:
English
Subject:
54 Environmental Sciences

Citation Formats

Mekonnen, Zelalem, Riley, William, Shirley, Ian, and Grant, Robert. Rapidly changing high-latitude seasonality: Implications for the 21st century carbon cycle in Alaska: Modeling Archive. United States: N. p., 2021. Web. doi:10.5440/1861071.
Mekonnen, Zelalem, Riley, William, Shirley, Ian, & Grant, Robert. Rapidly changing high-latitude seasonality: Implications for the 21st century carbon cycle in Alaska: Modeling Archive. United States. https://doi.org/10.5440/1861071
Mekonnen, Zelalem, Riley, William, Shirley, Ian, and Grant, Robert. 2021. "Rapidly changing high-latitude seasonality: Implications for the 21st century carbon cycle in Alaska: Modeling Archive". United States. https://doi.org/10.5440/1861071. https://www.osti.gov/servlets/purl/1861071.
@article{osti_1861071,
title = {Rapidly changing high-latitude seasonality: Implications for the 21st century carbon cycle in Alaska: Modeling Archive},
author = {Mekonnen, Zelalem and Riley, William and Shirley, Ian and Grant, Robert},
abstractNote = {This Modeling Archive is in support of an NGEE Arctic publication ?Rapidly changing high-latitude seasonality: Implications for the 21st century carbon cycle in Alaska? DOI: 10.1088/1748-9326/ac4362.The dataset contains ?ecosys? model outputs reported in Shirley et al. (2022) that explored how climate warming will shift carbon cycle seasonality in Alaska. The study used analysis of seasonal dynamics to support the prediction that high-latitude ecosystems are carbon sinks and will continue to accumulate carbon throughout the century. The study predicts surprisingly large increases in spring net carbon uptake that result in larger net carbon uptake in spring than in summer by year 2100.Included as *.nc files are modeled daily net ecosystem exchange (NEE), net primary productivity (NPP), heterotrophic respiration (Rh), autotrophic respiration (Ra), gross primary productivity (GPP), and plant nitrogen uptake. The output is provided (1) at 25 km resolution across Alaska; (2) for years 2010 through 2100. Scripts to generate publication figures included as text files (*.m) from MATLAB.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).},
doi = {10.5440/1861071},
url = {https://www.osti.gov/biblio/1861071}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Oct 31 00:00:00 EDT 2021},
month = {Sun Oct 31 00:00:00 EDT 2021}
}