Gustaf Hugelius, Justine L. Ramage, Eleanor J. Burke, Abhishek Chatterjee, Thomas Luke Smallman, Tuula Aalto, Ana Bastos, Christina Biasi, Josep G. Canadell, Naveen Chandra, Frederic Chevallier, Philippe Ciais, Jinfeng Chang, Liang Feng, Matthew W Jones, Thomas Kleinen, McKenzie Kuhn, Ronny Lauerwald, Junjie Liu, Efrén López-Blanco, Ingrid T. Luijkx, Maija E. Marushchak, Susan M. Natali, Yosuke Niwa, David Olefeldt, Paul Palmer, Prabir K. Patra, Wouter Peters, Stefano Potter, Benjamin Poulter, Brendan Rogers, William J. Riley, Marielle Saunois, Edward A. G. Schuur, Rona L. Thompson, Claire C. Treat, Aki Tsuruta, Merritt R. Turetsky, Anna- Maria Virkkala, Carolina Voigt, Jennifer Watts, Qing Zhu, Bo Zheng
This dataset contains monthly estimated inversion model CO₂, CH₄ and N₂O fluxes for the northern permafrost region over the period 2000 – 2020. The data was used to calculate annual and decadal greenhouse gas budgets.
In order to calculate the greenhouse gas budgets from natural ecosystems and human activities, different sources of data are needed. One important source of data is inversion model systems, which combine measured concentrations of greenhouse gases in Earth's atmosphere with weather models.
The dataset contains data from several independent inversion model systems from international research groups. The data includes spatial subsets extracted from global inversion model runs. These were summarized to ensemble fluxes for the final budgets. The included number of inverse modelling estimates are 7, 14 and 2 for CO₂, CH₄ and N₂O, respectively.
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Citation
Gustaf Hugelius, Justine L. Ramage, Eleanor J. Burke, Abhishek Chatterjee, Thomas Luke Smallman, Tuula Aalto, Ana Bastos, Christina Biasi, Josep G. Canadell, Naveen Chandra, Frederic Chevallier, Philippe Ciais, Jinfeng Chang, Liang Feng, Matthew W Jones, Thomas Kleinen, McKenzie Kuhn, Ronny Lauerwald, Junjie Liu, Efrén López-Blanco, Ingrid T. Luijkx, Maija E. Marushchak, Susan M. Natali, Yosuke Niwa, David Olefeldt, Paul Palmer, Prabir K. Patra, Wouter Peters, Stefano Potter, Benjamin Poulter, Brendan Rogers, William J. Riley, Marielle Saunois, Edward A. G. Schuur, Rona L. Thompson, Claire C. Treat, Aki Tsuruta, Merritt R. Turetsky, Anna- Maria Virkkala, Carolina Voigt, Jennifer Watts, Qing Zhu, Bo Zheng (2024) Monthly estimated inversion model CO₂, CH₄ and N₂O fluxes for the northern permafrost region over the period 2000 – 2020. Dataset version 1. Bolin Centre Database. https://doi.org/10.17043/hugelius-2024-permafrost-fluxes-1
References
Hugelius G, Ramage J, Burke E, Chatterjee A, Smallman TL, Aalto T, Bastos A, Biasi C, Canadell JG, Chandra N, Chevallier F, Ciais P, Chang J, Feng L, Jones MW, Kleinen T, Kuhn M, Lauerwald R, Liu J, López-Blanco E, Luijkx IT, Marushchak ME, Natali SM, Niwa Y, Olefeldt D, Palmer PI, Patra PK, Peters W, Potter S, Poulter B, Rogers BM, Riley WJ, Saunois M, Schuur EAG, Thompson RL, Treat C, Tsuruta A, Turetsky MR, Virkkala A-M, Voigt C, Watts J, Zhu Q, Zheng B (2024) Permafrost region greenhouse gas budgets suggest a weak CO2 sink and CH4 and N2O sources, but magnitudes differ between top-down and bottom-up methods. In press, Global Biogeochemical Cycles
Ciais P, Bastos A, Chevallier F, Lauerwald R, Poulter B, Canadell JG, Hugelius G, Jackson RB, Jain A, Jones M, Kondo M, Luijkx IT, Patra PK, Peters W, Pongratz J, Petrescu AMR, Piao S, Qiu C, Von Randow C, Regnier P, Saunois M, Scholes R, Shvidenko A, Tian H, Yang H, Wang X, Zheng B (2022) Definitions and methods to estimate regional land carbon fluxes for the second phase of the REgional Carbon Cycle Assessment and Processes Project (RECCAP-2). Geosci. Model Dev. 15:1289–1316. https://doi.org/10.5194/gmd-15-1289-2022
Data description
The data consists of three comma separated value csv
spreadsheets:
-
CO2_monthly_conversion_flux_2000_2020.csv
contains data for CO₂ and includes columns:
- year (year, from 2000 to 2020)
- month (numeric Julian month, from 1 to 12)
- ACTM_PgC_yr
- CAMS_PgC_yr
- sEXTocNEET_PgC_yr
- CTE2021_PgC_yr
- NISMON_PgC_yr
- CMSFlux_PgC_yr
- UoE_PgC_yr
- mean (mean of all inversion estimates)
- std_dev (standard deviation of all inversion estimates)
-
CH4_monthly_conversion_flux_2000_2020.csv
contains data for CH₄ and includes columns:
- year (year, from 2000 to 2020)
- month (numeric Julian month, from 1 to 12)
- NTF_4DVAR_NIES_GOSAT_TgCH4_month
- TM5_CAMS_GOSAT_TgCH4_month
- LMDZ_PYVAR_GOSAT_TgCH4_month
- TM5_4DVAR_GOSAT_TgCH4_month
- TM5_4DVAR_surface_TgCH4_month
- CTE_surface_TgCH4_month
- GELCA_surface_TgCH4_month
- MIROCv4_surface_TgCH4_month
- NICAM_surface_TgCH4_month
- NTF_4DVAR_NIES_surface_TgCH4_month
- TM5_CAMS_surface_TgCH4_month
- TOMCAT_surface_TgCH4_month
- ACTM_TgCH4_month
- mean (mean of all inversion estimates)
- std_dev (standard deviation of all inversion estimates)
-
N2O_monthly_conversion_flux_2000_2020.csv
contains data for N₂O and includes columns:
- year (year, from 2000 to 2020)
- month (numeric Julian month, from 1 to 12)
- CAMS_TgN_month
- ACTM_TgN_month
- mean (mean of all inversion estimates)
- std_dev (standard deviation of all inversion estimates)
More information can be found in the README file which contains an inventory of all the inverse model systems used for each ensemble, including references and units. For more details of data processing we refer to Hugelius et al. (2024).