Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?
Abstract
Abstract. Understanding methane emissions from the Arctic, a fast-warming carbon reservoir, is important for projecting future changes in the global methane cycle. Here we optimized methane emissions from north of 60°N (pan-Arctic) regions using a nested-grid high-resolution inverse model that assimilates both high-precision surface measurements and column-average SCanning Imaging Absorption spectroMeter for Atmospheric CHartogrphY (SCIAMACHY) satellite retrievals of methane mole fraction. For the first time, methane emissions from lakes were integrated into an atmospheric transport and inversion estimate, together with prior wetland emissions estimated with six biogeochemical models. In our estimates, in 2005, global methane emissions were in the range of 496.4–511.5Tgyr–1, and pan-Arctic methane emissions were in the range of 11.9–28.5Tgyr–1. Methane emissions from pan-Arctic wetlands and lakes were 5.5–14.2 and 2.4–14.2Tgyr–1, respectively. Methane emissions from Siberian wetlands and lakes are the largest and also have the largest uncertainty. Our results indicate that the uncertainty introduced by different wetland models could be much larger than the uncertainty of each inversion. We also show that assimilating satellite retrievals can reduce the uncertainty of the nested-grid inversions. The significance of lake emissions cannot be identified across the pan-Arctic by high-resolution inversions, but it is possible to identify high lake emissions frommore »
- Authors:
- Publication Date:
- Research Org.:
- Purdue Univ., West Lafayette, IN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1328713
- Alternate Identifier(s):
- OSTI ID: 1465820
- Grant/Contract Number:
- FG02-08ER64599; AC02-05CH11231
- Resource Type:
- Published Article
- Journal Name:
- Atmospheric Chemistry and Physics (Online)
- Additional Journal Information:
- Journal Name: Atmospheric Chemistry and Physics (Online) Journal Volume: 16 Journal Issue: 19; Journal ID: ISSN 1680-7324
- Publisher:
- Copernicus Publications, EGU
- Country of Publication:
- Germany
- Language:
- English
- Subject:
- 58 GEOSCIENCES
Citation Formats
Tan, Zeli, Zhuang, Qianlai, Henze, Daven K., Frankenberg, Christian, Dlugokencky, Ed, Sweeney, Colm, Turner, Alexander J., Sasakawa, Motoki, and Machida, Toshinobu. Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?. Germany: N. p., 2016.
Web. doi:10.5194/acp-16-12649-2016.
Tan, Zeli, Zhuang, Qianlai, Henze, Daven K., Frankenberg, Christian, Dlugokencky, Ed, Sweeney, Colm, Turner, Alexander J., Sasakawa, Motoki, & Machida, Toshinobu. Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?. Germany. https://doi.org/10.5194/acp-16-12649-2016
Tan, Zeli, Zhuang, Qianlai, Henze, Daven K., Frankenberg, Christian, Dlugokencky, Ed, Sweeney, Colm, Turner, Alexander J., Sasakawa, Motoki, and Machida, Toshinobu. Wed .
"Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?". Germany. https://doi.org/10.5194/acp-16-12649-2016.
@article{osti_1328713,
title = {Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?},
author = {Tan, Zeli and Zhuang, Qianlai and Henze, Daven K. and Frankenberg, Christian and Dlugokencky, Ed and Sweeney, Colm and Turner, Alexander J. and Sasakawa, Motoki and Machida, Toshinobu},
abstractNote = {Abstract. Understanding methane emissions from the Arctic, a fast-warming carbon reservoir, is important for projecting future changes in the global methane cycle. Here we optimized methane emissions from north of 60°N (pan-Arctic) regions using a nested-grid high-resolution inverse model that assimilates both high-precision surface measurements and column-average SCanning Imaging Absorption spectroMeter for Atmospheric CHartogrphY (SCIAMACHY) satellite retrievals of methane mole fraction. For the first time, methane emissions from lakes were integrated into an atmospheric transport and inversion estimate, together with prior wetland emissions estimated with six biogeochemical models. In our estimates, in 2005, global methane emissions were in the range of 496.4–511.5Tgyr–1, and pan-Arctic methane emissions were in the range of 11.9–28.5Tgyr–1. Methane emissions from pan-Arctic wetlands and lakes were 5.5–14.2 and 2.4–14.2Tgyr–1, respectively. Methane emissions from Siberian wetlands and lakes are the largest and also have the largest uncertainty. Our results indicate that the uncertainty introduced by different wetland models could be much larger than the uncertainty of each inversion. We also show that assimilating satellite retrievals can reduce the uncertainty of the nested-grid inversions. The significance of lake emissions cannot be identified across the pan-Arctic by high-resolution inversions, but it is possible to identify high lake emissions from some specific regions. In contrast to global inversions, high-resolution nested-grid inversions perform better in estimating near-surface methane concentrations.},
doi = {10.5194/acp-16-12649-2016},
journal = {Atmospheric Chemistry and Physics (Online)},
number = 19,
volume = 16,
place = {Germany},
year = {Wed Oct 12 00:00:00 EDT 2016},
month = {Wed Oct 12 00:00:00 EDT 2016}
}
https://doi.org/10.5194/acp-16-12649-2016
Web of Science
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