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Quantifying the impact of winter warming on the Arctic carbon cycle

Pongrácz, Alexandra LU orcid (2023)
Abstract
The Arctic has undergone extreme changes during the last decades and is warming over twice the global average. There has been increasing interest in understanding how warming and changes in snow and rainfall will affect high-latitude ecosystems. Although observational studies highlight the importance of cold-season carbon fluxes on the annual carbon balance, models, in general, cannot realistically capture these wintertime processes. In this thesis, we developed the LPJ-GUESS ecosystem model to better represent cold season processes. Our aim is to evaluate how changing winter conditions would affect arctic ecosystems and, indirectly, the global carbon and hydrological cycles.

In our first study, we introduced a new snow scheme... (More)
The Arctic has undergone extreme changes during the last decades and is warming over twice the global average. There has been increasing interest in understanding how warming and changes in snow and rainfall will affect high-latitude ecosystems. Although observational studies highlight the importance of cold-season carbon fluxes on the annual carbon balance, models, in general, cannot realistically capture these wintertime processes. In this thesis, we developed the LPJ-GUESS ecosystem model to better represent cold season processes. Our aim is to evaluate how changing winter conditions would affect arctic ecosystems and, indirectly, the global carbon and hydrological cycles.

In our first study, we introduced a new snow scheme that improved the pan-Arctic model-data correspondence in observed snow depth, snow season length and snow insulation capacity. We used the updated model to examine the relationships between snow conditions and carbon flux changes under different future scenarios. We found that the coldest regions and coldest season are most vulnerable to environmental changes, which corresponds to the areas where we currently have the largest uncertainties. We explored the impact of extreme winter events on ground conditions and carbon fluxes. This study highlighted the still-existing shortcomings of the model in capturing short-term extreme weather phenomena and their impact. We tested a conceptual model to enable the simulation of autumn-time methane emissions at a high-arctic study site. The updated module could simulate both the growing season and autumn-time methane emission peaks, and we proposed further investigation into the possibilities of including physical controls of methane emissions in the model.

Our studies improved the model’s performance in simulating wintertime processes across the Arctic. We highlight the importance of further developing snow dynamics and cold season greenhouse exchange processes in ecosystem models. Further improvements are necessary to create more robust future predictions regarding the impact of climate change on arctic ecosystems and their global consequences. (Less)
Abstract (Swedish)
The Arctic has undergone extreme changes during the last decades and is warming over twice the global average. There has been increasing interest in understanding how warming and changes in snow and rainfall will affect high-latitude ecosystems. Although observational studies highlight the importance of cold-season carbon fluxes on the annual carbon balance, models, in general, cannot realistically capture these wintertime processes. In this thesis, we developed the LPJ-GUESS ecosystem model to better represent cold season processes. Our aim is to evaluate how changing winter conditions would affect arctic ecosystems and, indirectly, the global carbon and hydrological cycles.

In our first study, we introduced a new snow scheme... (More)
The Arctic has undergone extreme changes during the last decades and is warming over twice the global average. There has been increasing interest in understanding how warming and changes in snow and rainfall will affect high-latitude ecosystems. Although observational studies highlight the importance of cold-season carbon fluxes on the annual carbon balance, models, in general, cannot realistically capture these wintertime processes. In this thesis, we developed the LPJ-GUESS ecosystem model to better represent cold season processes. Our aim is to evaluate how changing winter conditions would affect arctic ecosystems and, indirectly, the global carbon and hydrological cycles.

In our first study, we introduced a new snow scheme that improved the pan-Arctic model-data correspondence in observed snow depth, snow season length and snow insulation capacity. We used the updated model to examine the relationships between snow conditions and carbon flux changes under different future scenarios. We found that the coldest regions and coldest season are most vulnerable to environmental changes, which corresponds to the areas where we currently have the largest uncertainties. We explored the impact of extreme winter events on ground conditions and carbon fluxes. This study highlighted the still-existing shortcomings of the model in capturing short-term extreme weather phenomena and their impact. We tested a conceptual model to enable the simulation of autumn-time methane emissions at a high-arctic study site. The updated module could simulate both the growing season and autumn-time methane emission peaks, and we proposed further investigation into the possibilities of including physical controls of methane emissions in the model.

Our studies improved the model’s performance in simulating wintertime processes across the Arctic. We highlight the importance of further developing snow dynamics and cold season greenhouse exchange processes in ecosystem models. Further improvements are necessary to create more robust future predictions regarding the impact of climate change on arctic ecosystems and their global consequences. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Professor Sitch, Stephen, University of Exeter, UK
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Arctic, snow, permafrost, LPJ-GUESS, non-growing season, carbon cycling, LPJ-GUESS, Arctic, permafrost, snow, carbon cycling, non-growing season
pages
237 pages
publisher
Lund University (Media-Tryck)
defense location
Världen (Hörsal F111), Geocentrum 2
defense date
2023-03-03 10:00:00
ISBN
978-91-89187-21-4
978-91-89187-22-1
language
English
LU publication?
yes
id
32c8470b-a8f0-4038-b61c-3c732756afd2
date added to LUP
2023-01-23 10:39:24
date last changed
2023-02-06 13:41:24
@phdthesis{32c8470b-a8f0-4038-b61c-3c732756afd2,
  abstract     = {{The Arctic has undergone extreme changes during the last decades and is warming over twice the global average. There has been increasing interest in understanding how warming and changes in snow and rainfall will affect high-latitude ecosystems. Although observational studies highlight the importance of cold-season carbon fluxes on the annual carbon balance, models, in general, cannot realistically capture these wintertime processes. In this thesis, we developed the LPJ-GUESS ecosystem model to better represent cold season processes. Our aim is to evaluate how changing winter conditions would affect arctic ecosystems and, indirectly, the global carbon and hydrological cycles. <br/><br/>In our first study, we introduced a new snow scheme that improved the pan-Arctic model-data correspondence in observed snow depth, snow season length and snow insulation capacity. We used the updated model to examine the relationships between snow conditions and carbon flux changes under different future scenarios. We found that the coldest regions and coldest season are most vulnerable to environmental changes, which corresponds to the areas where we currently have the largest uncertainties. We explored the impact of extreme winter events on ground conditions and carbon fluxes. This study highlighted the still-existing shortcomings of the model in capturing short-term extreme weather phenomena and their impact. We tested a conceptual model to enable the simulation of autumn-time methane emissions at a high-arctic study site. The updated module could simulate both the growing season and autumn-time methane emission peaks, and we proposed further investigation into the possibilities of including physical controls of methane emissions in the model. <br/><br/>Our studies improved the model’s performance in simulating wintertime processes across the Arctic. We highlight the importance of further developing snow dynamics and cold season greenhouse exchange processes in ecosystem models. Further improvements are necessary to create more robust future predictions regarding the impact of climate change on arctic ecosystems and their global consequences.}},
  author       = {{Pongrácz, Alexandra}},
  isbn         = {{978-91-89187-21-4}},
  keywords     = {{Arctic; snow; permafrost; LPJ-GUESS; non-growing season; carbon cycling; LPJ-GUESS; Arctic; permafrost; snow; carbon cycling; non-growing season}},
  language     = {{eng}},
  month        = {{01}},
  publisher    = {{Lund University (Media-Tryck)}},
  school       = {{Lund University}},
  title        = {{Quantifying the impact of winter warming on the Arctic carbon cycle}},
  url          = {{https://lup.lub.lu.se/search/files/135577009/AP_kappa.pdf}},
  year         = {{2023}},
}