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Title: Detecting regional patterns of changing CO 2 flux in Alaska

Abstract

With rapid changes in climate and the seasonal amplitude of carbon dioxide (CO 2) in the Arctic, it is critical that we detect and quantify the underlying processes controlling the changing amplitude of CO 2 to better predict carbon cycle feedbacks in the Arctic climate system. We use satellite and airborne observations of atmospheric CO 2 with climatically forced CO 2 flux simulations to assess the detectability of Alaskan carbon cycle signals as future warming evolves. We find that current satellite remote sensing technologies can detect changing uptake accurately during the growing season but lack sufficient cold season coverage and near-surface sensitivity to constrain annual carbon balance changes at regional scale. Airborne strategies that target regular vertical profile measurements within continental interiors are more sensitive to regional flux deeper into the cold season but currently lack sufficient spatial coverage throughout the entire cold season. Thus, the current CO 2 observing network is unlikely to detect potentially large CO 2 sources associated with deep permafrost thaw and cold season respiration expected over the next 50 y. In conclusion, although continuity of current observations is vital, strategies and technologies focused on cold season measurements (active remote sensing, aircraft, and tall towers) andmore » systematic sampling of vertical profiles across continental interiors over the full annual cycle are required to detect the onset of carbon release from thawing permafrost.« less

Authors:
 [1]; ORCiD logo [2];  [2];  [3];  [4];  [5];  [6];  [7];  [8]
  1. California Inst. of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Lab.; Univ. of California, Los Angeles, CA (United States). Joint Inst. for Regional Earth System Science and Engineering
  2. Harvard Univ., Cambridge, MA (United States). Dept. of Earth and Planetary Sciences; Harvard Univ., Cambridge, MA (United States). Harvard School of Engineering and Applied Sciences
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Climate and Ecosystem Sciences Division
  4. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Earth System Research Lab.; Univ. of Colorado, Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences
  5. National Center for Atmospheric Research, Boulder, CO (United States). Climate and Global Dynamics Lab.
  6. Harvard Univ., Cambridge, MA (United States). Dept. of Earth and Planetary Sciences; Colorado State Univ., Fort Collins, CO (United States). Dept. of Atmospheric Science
  7. Dalhousie Univ., Halifax, NS (Canada). Dept. of Physics and Atmospheric Science
  8. California Inst. of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Lab.
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); National Aeronautic and Space Administration (NASA)
OSTI Identifier:
1259729
Grant/Contract Number:
AC02-05CH11231; FC03-97ER62402; PLR-1304220
Resource Type:
Journal Article: Published Article
Journal Name:
Proceedings of the National Academy of Sciences of the United States of America
Additional Journal Information:
Journal Volume: 113; Journal Issue: 28; Journal ID: ISSN 0027-8424
Publisher:
National Academy of Sciences, Washington, DC (United States)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; carbon cycle; permafrost thaw; climate; Earth system models; remote sensing

Citation Formats

Parazoo, Nicholas C., Commane, Roisin, Wofsy, Steven C., Koven, Charles D., Sweeney, Colm, Lawrence, David M., Lindaas, Jakob, Chang, Rachel Y. -W., and Miller, Charles E.. Detecting regional patterns of changing CO2 flux in Alaska. United States: N. p., 2016. Web. doi:10.1073/pnas.1601085113.
Parazoo, Nicholas C., Commane, Roisin, Wofsy, Steven C., Koven, Charles D., Sweeney, Colm, Lawrence, David M., Lindaas, Jakob, Chang, Rachel Y. -W., & Miller, Charles E.. Detecting regional patterns of changing CO2 flux in Alaska. United States. doi:10.1073/pnas.1601085113.
Parazoo, Nicholas C., Commane, Roisin, Wofsy, Steven C., Koven, Charles D., Sweeney, Colm, Lawrence, David M., Lindaas, Jakob, Chang, Rachel Y. -W., and Miller, Charles E.. 2016. "Detecting regional patterns of changing CO2 flux in Alaska". United States. doi:10.1073/pnas.1601085113.
@article{osti_1259729,
title = {Detecting regional patterns of changing CO2 flux in Alaska},
author = {Parazoo, Nicholas C. and Commane, Roisin and Wofsy, Steven C. and Koven, Charles D. and Sweeney, Colm and Lawrence, David M. and Lindaas, Jakob and Chang, Rachel Y. -W. and Miller, Charles E.},
abstractNote = {With rapid changes in climate and the seasonal amplitude of carbon dioxide (CO2) in the Arctic, it is critical that we detect and quantify the underlying processes controlling the changing amplitude of CO2 to better predict carbon cycle feedbacks in the Arctic climate system. We use satellite and airborne observations of atmospheric CO2 with climatically forced CO2 flux simulations to assess the detectability of Alaskan carbon cycle signals as future warming evolves. We find that current satellite remote sensing technologies can detect changing uptake accurately during the growing season but lack sufficient cold season coverage and near-surface sensitivity to constrain annual carbon balance changes at regional scale. Airborne strategies that target regular vertical profile measurements within continental interiors are more sensitive to regional flux deeper into the cold season but currently lack sufficient spatial coverage throughout the entire cold season. Thus, the current CO2 observing network is unlikely to detect potentially large CO2 sources associated with deep permafrost thaw and cold season respiration expected over the next 50 y. In conclusion, although continuity of current observations is vital, strategies and technologies focused on cold season measurements (active remote sensing, aircraft, and tall towers) and systematic sampling of vertical profiles across continental interiors over the full annual cycle are required to detect the onset of carbon release from thawing permafrost.},
doi = {10.1073/pnas.1601085113},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
number = 28,
volume = 113,
place = {United States},
year = 2016,
month = 6
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1073/pnas.1601085113

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  • With rapid changes in climate and the seasonal amplitude of carbon dioxide (CO 2) in the Arctic, it is critical that we detect and quantify the underlying processes controlling the changing amplitude of CO 2 to better predict carbon cycle feedbacks in the Arctic climate system. We use satellite and airborne observations of atmospheric CO 2 with climatically forced CO 2 flux simulations to assess the detectability of Alaskan carbon cycle signals as future warming evolves. We find that current satellite remote sensing technologies can detect changing uptake accurately during the growing season but lack sufficient cold season coverage andmore » near-surface sensitivity to constrain annual carbon balance changes at regional scale. Airborne strategies that target regular vertical profile measurements within continental interiors are more sensitive to regional flux deeper into the cold season but currently lack sufficient spatial coverage throughout the entire cold season. Thus, the current CO 2 observing network is unlikely to detect potentially large CO 2 sources associated with deep permafrost thaw and cold season respiration expected over the next 50 y. In conclusion, although continuity of current observations is vital, strategies and technologies focused on cold season measurements (active remote sensing, aircraft, and tall towers) and systematic sampling of vertical profiles across continental interiors over the full annual cycle are required to detect the onset of carbon release from thawing permafrost.« less
  • As climate warms, changes in the carbon (C) balance of arctic tundra will play an important role in the global C balance. The C balance of tundra is tightly coupled to the nitrogen (N) and phosphorus (P) cycles because soil organic matter is the principal source of plant-available nutrients and determines the spatial variation of vegetation biomass across the North Slope of Alaska. Warming will accelerate these nutrient cycles, which should stimulate plant growth.
  • Recent warming and drying in the arctic has resulted in a change from CO{sub 2} sink to CO{sub 2} source with respect to the atmosphere. The large stores of soil carbon of perhaps up to 177 PgC, and its sensitivity changes in soil temperature and soil moisture, mean that strong positive feedbacks on atmospheric CO{sub 2} and climate change are possible and make understanding the patterns of and controls on CO{sub 2} flux important. However, the large spatial variability in arctic tundra composition and trace gas fluxes make large-scale estimations challenging. We are using a combinations of rapid cuvette, tower-basedmore » eddy correlation, and aircraft-based eddy correlation measurements to estimate regional CO{sub 2} fluxes. Recent measurements indicate good agreement between chamber, tower-based measurements, and that most tundra sites are a source of CO{sub 2} to the atmosphere. Site specific changes in CO{sub 2} flux have been demonstrated. US IBP site 2, at Barrow, Alaska, was found to be a strong sink of CO{sub 2} of 25 g m{sup -2} y{sup -1} in the early 1970s, and is now seen to be a source of CO{sup 2} to the atmosphere of about 1.3 g C m{sup -2} y{sup -1}. A decrease in soil moisture content or water table has a greater effect on CO{sub 2} loss than does an increase in temperature. Methods of predicting fluxes from remotely sensed imagery and surface characteristics are being explored.« less
  • Regional climate models (RCMs) are a standard tool for downscaling climate forecasts to finer spatial scales. The evaluation of RCMs against observational data is an important step in building confidence in the use of RCMs for future prediction. In addition to model performance in climatological means and marginal distributions, a model’s ability to capture spatio-temporal relationships is important. This study develops two approaches: (1) spatial correlation/variogram for a range of spatial lags, with total monthly precipitation and non-seasonal precipitation components used to assess the spatial variations of precipitation; and (2) spatio-temporal correlation for a wide range of distances, directions, andmore » time lags, with daily precipitation occurrence used to detect the dynamic features of precipitation. These measures of spatial and spatio-temporal dependence are applied to a high-resolution RCM run and to the National Center for Environmental Prediction (NCEP)-U.S. Department of Energy (DOE) AMIP II reanalysis data (NCEP-R2), which provides initial and lateral boundary conditions for the RCM. The RCM performs better than NCEP-R2 in capturing both the spatial variations of total and non-seasonal precipitation components and the spatio-temporal correlations of daily precipitation occurrences, which are related to dynamic behaviors of precipitating systems. The improvements are apparent not just at resolutions finer than that of NCEP-R2, but also when the RCM and observational data are aggregated to the resolution of NCEP-R2.« less