Synthesis of Winter In Situ Soil CO2 Flux in pan-Arctic and Boreal Regions, 1989-2017

This dataset provides a synthesis of winter ( September-April) in situ soil CO2 flux measurement data from locations across pan-Arctic and Boreal permafrost regions. The in situ data were compiled from 66 published and 21 unpublished studies conducted from 1989-2017. The data sources (publication references) are provided. Sampling sites spanned pan-Arctic Boreal and tundra regions (>53 Deg N) in continuous, discontinuous, and isolated/sporadic permafrost zones. The CO2 flux measurements were aggregated at the monthly level, or seasonally when monthly data were not available, and are reported as the daily average (g C m-2 day-1) over the interval. Soil moisture and temperature data plus environmental and ecological model driver data (e.g., vegetation type and productivity, soil substrate availability) are also included based on gridded satellite remote sensing and reanalysis sources.

These CO2 flux and model driver data were used to create gridded estimates of CO2 emissions by applying a Boosted Regression Tree (BRT) machine learning approach. The gridded estimates are provided in a related dataset.

There is one data file in comma-separated format (.csv) with this dataset.

This dataset provides a synthesis of winter (September-April) in situ soil CO2 flux measurement data from locations across pan-Arctic and Boreal permafrost regions. The in situ data were compiled from 66 published and 21 unpublished studies conducted from 1989-2017. The data sources (publication references) are provided. Sampling sites spanned pan-Arctic Boreal and tundra regions (>53 Deg N) in continuous, discontinuous, and isolated/sporadic permafrost zones. The CO2 flux measurements were aggregated at the monthly level, or seasonally when monthly data were not available, and are reported as the daily average (g C m-2 day-1) over the interval. Soil moisture and temperature data plus environmental and ecological model driver data (e.g., vegetation type and productivity, soil substrate availability) are also included based on gridded satellite remote sensing and reanalysis sources.

These CO2 flux and model driver data were used to create gridded estimates of CO2 emissions by applying a Boosted Regression Tree (BRT) machine learning approach. The gridded estimates are provided in a related dataset listed below.

Project: Arctic-Boreal Vulnerability Experiment

The Arctic-Boreal Vulnerability Experiment (ABoVE) is a NASA Terrestrial Ecology Program field campaign conducted in Alaska and western Canada between 2016 and 2021. Research for ABoVE links field-based, process-level studies with geospatial data products derived from airborne and satellite sensors, providing a foundation for improving the analysis, and modeling capabilities needed to understand and predict ecosystem responses to, and societal implications of, climate change in the Arctic and Boreal regions.

Related Publication:

Natali, S. J.D. Watts, S. Potter, B.M. Rogers, and S.M. Ludwig et al., 2019. Large loss of CO2 in winter observed across pan-Arctic permafrost region. Nature Climate Change

Related Dataset:

Watts, J., S. Natali, S. Potter, and B.M. Rogers. 2019. Gridded Winter Soil CO2 Flux Estimates for pan-Arctic and Boreal Regions, 2003-2100. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1683

Acknowledgements:

This research was funded as part of NASA's Arctic Boreal Vulnerability Experiment under grant number NNX15AT81A.

 

Spatial Coverage: pan-Arctic boreal and tundra regions (>53 Deg N)

ABoVE reference locations: 

Domain: Core ABoVE (Alaska and Canada only)

Ah0Av0.Bh5Bv5.Ch035Cv003

Ah0Av1.Bh1Bv9.Ch08Cv58, Ah0Av1.Bh1Bv9.Ch08Cv59, Ah0Av1.Bh4Bv6.Ch28Cv40, Ah0Av1.Bh4Bv6.Ch29Cv41, Ah0Av1.Bh5Bv6.Ch30Cv41, Ah0Av1.Bh4Bv7.Ch28Cv42, Ah0Av1.Bh2Bv9.Ch15Cv55

Ah1Av0.Bh6Bv1.Ch036Cv06, Ah1Av0.Bh6Bv1.Ch37Cv07, Ah1Av0.Bh6Bv5.Ch36Cv31,  Ah1Av0.Bh6Bv5.Ch037Cv31, Ah1Av0.Bh6Bv5.Ch36Cv33, Ah1Av0.Bh6Bv2.Ch41Cv12, Ah1Av0.Bh6Bv4.Ch41Cv27, Ah1Av0.Bh6Bv4.Ch41Cv28, Ah1Av0.Bh6Bv4.Ch40Cv29, Ah1Av0.Bh6Bv5.Ch38Cv30, Ah1Av0.Bh6Bv5.Ch38Cv31, Ah1Av0.Bh6Bv5.Ch39Cv32, Ah1Av0.Bh6Bv5.Ch38Cv33, Ah1Av0.Bh6Bv5.Ch39Cv33, Ah1Av0.Bh6Bv5.Ch39Cv34, Ah1Av0.Bh7Bv4.Ch45Cv24, Ah1Av0.Bh7Bv4.Ch44Cv25, Ah1Av0.Bh7Bv4.Ch46Cv05, Ah1Av0.Bh7Bv4.Ch42Cv27, Ah1Av0.Bh7Bv3.Ch47Cv19, Ah1Av0.Bh7Bv3.Ch7Cv21, Ah1Av0.Bh7Bv3.Ch47Cv22, Ah1Av0.Bh7Bv3.Ch46Cv23, Ah1Av0.Bh7Bv2.Ch042Cv13, Ah1Av0.Bh7Bv2.Ch43Cv14, Ah1Av0.Bh7Bv0.Ch45Cv00, Ah1Av0.Bh7Bv0.Ch46Cv02, Ah1Av0.Bh7Bv1.Ch46Cv08, Ah1Av0.Bh11Bv0.Ch69Cv00, Ah1Av0.Bh10Bv0.Ch64Cv05, Ah1Av0.Bh10Bv1.Ch064Cv06, Ah1Av0.Bh9Bv1.Ch58Cv11, Ah1Av0.Bh9Bv2.Ch54Cv17, Ah1Av0.Bh8Bv3.Ch52Cv18, Ah1Av0.Bh8Bv3.Ch52Cv18, Ah1Av0.Bh8Bv3.Ch52Cv18, Ah1Av0.Bh8Bv3.Ch052Cv18, Ah1Av0.Bh8Bv3.Ch052Cv18, Ah1Av0.Bh8Bv3.Ch052Cv18, Ah1Av0.Bh8Bv3.Ch052Cv18, Ah1Av0.Bh8Bv3.Ch048Cv19, Ah1Av0.Bh8Bv3.Ch050Cv19, Ah1Av0.Bh8Bv3.Ch052Cv19, Ah1Av0.Bh8Bv3.Ch048Cv20, Ah1Av0.Bh8Bv3.Ch049Cv20, Ah1Av0.Bh8Bv3.Ch051Cv20, Ah1Av0.Bh8Bv3.Ch048Cv21, Ah1Av0.Bh8Bv3.Ch049Cv21, Ah1Av0.Bh8Bv3.Ch050Cv21, Ah1Av0.Bh8Bv3.Ch051Cv19, Ah1Av0.Bh8Bv3.Ch049Cv22, Ah1Av0.Bh8Bv3.Ch049Cv23, Ah1Av0.Bh8Bv2.Ch053Cv16, Ah1Av0.Bh8Bv2.Ch052Cv17, Ah1Av0.Bh8Bv1.Ch049Cv06

Ah1Av1.Bh6Bv6.Ch41Cv36

Ah2Av1.Bh13Bv6.Ch79Cv41, Ah2Av1.Bh16Bv7.Ch101Cv47, Ah2Av1.Bh19Bv6.Ch09Cv74, Ah2Av1.Bh15Bv7.Ch92Cv45

Ah3Av1.Bh23Bv7.Ch140Cv44, Ah3Av1.Bh16Bv18.Ch110Cv48

Ah4Av0.Bh27Bv5.Ch166Cv30

Ah4Av1.Bh24Bv6.Ch149Cv40

Spatial Resolution: multiple points

Temporal Resolution: monthly during the winter non-growing season (September – April) of each year

Temporal Coverage: 1989-09-01 to 2017-04-30

Study Area: (all latitudes and longitudes given in decimal degrees)

Site (Region)	Westernmost Longitude	Easternmost Longitude	Northernmost Latitude	Southernmost Latitude
Circumpolar Arctic	-163.711	161.992	78.917	53.876

 

Data File Information

There is one data file in comma-separated format (.csv) - nongrowing_season_CO2_flux.csv - and one companion file with the data sources (publication references) - Sources_nongrowing_season_CO2_flux.pdf.

Table 1. Variables in nongrowing_season_CO2_flux.csv. Missing data are represented by -9999'.

Column name	Units	Description
author		1st author of paper, last name
pub_yr	Year	Publication year
title		Publication title
journal		Publication journal
latitude	Decimal degrees	Latitude North
longitude	Decimal degrees	Longitude East
loc		Location description from publication (e.g., city, state, field station)
site		Sites (e.g., different veg types) within a location
country		Country
biome		Boreal or tundra
tsoil	°C	Soil temperature during the measurement interval; 10 cm average depth
permafrost_reported		Reported permafrost (Y=yes; N=no; na= not mentioned/known)
meas_method		Measurement method. ch (chamber on soil); ch_snow (chamber placed on top of snow pack); diff (diffusion through snow pack); ECC (eddy covariance closed path); ECO (eddy covariance open path); SL (soda lime)
meas_mo_start		1st measurement month for flux data in this row
meas_yr_start		1st measurement year for flux data in this row
meas_mo_end		Last measurement month for flux data in this row
meas_yr_end		Last measurement year for flux data in this row
meas_mo_start_2		If >1 data interval; same as above
meas_yr_start_2		If >1 data interval; same as above
meas_mo_end_2		If >1 data interval; same as above
meas_yr_end_2		If >1 data interval; same as above
season		Sub-season during the winter when data were collected. E (early)=Aug-Nov; M (mid)=Dec-Feb; L(late)=Mar-Jun; NGS=spans > 1 season
spatial_replicates		Number of spatial replicates (within the source)
temporal_replicates		Number of temporal replicates (within the source); eddy towers all reported as >100
winter_flux	g C m-2 day-1	Monthly aggregated winter flux
se_flux	g C m-2 day-1	Flux standard error
gpp_meas	g C m-2 yr-1	Annual GPP from previous growing season
landcover *		Vegetation classification. CAVM (Walker et al. 2005) for tundra regions, ESA CCI Land Cover (ESA 2014) for non-tundra; corrected based on site descriptions. See table 2 for classes.
evi_meanband *		MODIS; mean EVI from previous growing season
perm_zone *		Permafrost zone; Brown et al. (2002)
pzi *		Permafrost zonation index (Gruber 2013)
soc *	%	SOC density (% by weight) in top 30 cm, SoilGrids (Hengl et al. 2017)
sand *	%	Soil Sand % in top 30 cm, SoilGrids (Carroll et al. 2017)
silt *	%	Soil Silt % in top 30 cm, SoilGrids (Carroll et al. 2017)
modis_treecover *	%	Tree cover (%), MODIS 205m C6 (Hansen et al. 2003), year of measurement start (or 2000 for pre-2000 measurements)
smap_gpp *	g C m-2 yr-1	9-km SMAP L4C Nature Run 4.1 (Jones et al. 2017)
modis_lai *	m2 m-2	Max leaf area index (LAI) (Myneni et al. 2015) within July 10 through Aug 20 window
amsr_vsm *	cm3 cm-3	Mean microwave AMSR soil/litter surface non-frozen moisture for month of flux observation. 25 km res. 0 = frozen state. Note: 2002-16 climatology for years prior to 2002, (Du et al. 2017)
amsr_vsm_sum *	cm3 cm-3	Mean microwave AMSR soil/litter surface non-frozen moisture for summer (June, July) prior to flux observation. 0 = frozen state. 25 km res. Note: 2002-16 climatology for years prior to 2002, (Du et al. 2017)
tair_ra *	K	Air Temp at 2 m height (K), NASA MERRA 2, (Reichle et al. 2017)
tsoil_ra1 *	K	Soil Temp (K) in first soil layer from surface, NASA MERRA 2, Reichle et al. 2017)
soil_moisture_ra		Soil moisture

User Notes: 

• Data extracted from gridded datasets are marked with an asterisk; otherwise in situ measured data are from publications or unpublished datasets.
• Columns author, pub_yr, and title are the index fields to cross reference to the publication references companion file -- Sources_nongrowing_season_CO2_flux.pdf.
• Unpublished data are denoted with values for author and pub_yr, where pub_yr provides a code for the source, e.g., unpub5 and unpub6. 

 

Table 2.  Land cover classes extracted from the Circumpolar Arctic Vegetation Map (CAVM) (Walker et al. 2005) for tundra regions, ESA CCI Land Cover (ESA 2014) for non-tundra.

Source	Code	Land Cover Description
CAVM	P2	Prostrate dwarf shrub and forb tundra
CAVM	S1	Erect dwarf shrub tundra
CAVM	S2	Erect low shrub tundra
CAVM	G1-G4	Graminoid tussock and non-tussock (sedge, moss, minimal shrub)
CAVM	W1	Wet sedge, grass and moss tundra
CAVM	W2	Wet sedge, shrub and moss tundra
CAVM	NMC	Noncarbonate mountain complex (barren; minimal plant cover)
CAVM	CMC	Carbonate mountain complex (barren; minimal plant cover)
CCI	SBV	Sparse boreal vegetation (tree, shrub, herb)
CCI	BDF	Deciduous broadleaved forest, closed to open canopy
CCI	DNF	Deciduous needle leaf forest, closed to open canopy
CCI	ENLF	Evergreen needle leaf forest, closed to open canopy
CCI	BSW	Shrub or herb cover, flooded

This study provides a critical constraint on carbon budgets for the Arctic during a period of greatest uncertainty and provides further insight into the drivers, magnitudes, and variability of CO2 released during the winter season.

The standard error of CO2 flux is included in the dataset.

In situ winter season (Sept-April) CO2 emissions and potential driving variables were compiled from sites within the northern permafrost zone. The data included 66 published studies and 21 unpublished studies conducted at 104 sites (i.e., sample areas with unique geographic coordinates) and in 152 sampling locations (i.e., different locations within a site as distinguished by vegetation type, landscape position, etc.). Sites spanned boreal and tundra landcover classes (Table 2) in continuous permafrost (n=69), discontinuous (n=24), and isolated/sporadic (n=11) permafrost zones (Fig. 1). Data were aggregated at the monthly level; however, the number of measurements per month varied among studies. The dataset included more than 1000 site-month flux measurements (Natali et al., 2019).

Data were collected using several measurement methods:

1. Chamber: chamber placed over the ground after digging a snow pit or placed underneath the snowpack prior to snow accumulation, and gas flux measured as a change in gas concentration in the chamber over time;

2. Chamber-snow: chamber placed on top of the snow pack, and flux measured as a change in gas concentration in the chamber over time;

3. Diffusion: Gas concentrations measured at two or more locations through the snow pack, and gas flux calculated based on gas diffusion rate through the snowpack;

4. Eddy covariance: Gas flux calculated based on covariance of gas concentration and vertical wind velocity; separated into closed path (air is drawn in through a sampling tube to an infrared gas analyzer) and open path (air passes freely between infrared source and detector) systems;

5. Soda lime: Seasonal release of CO₂ from soils determined from CO₂ adsorption onto soda lime placed in a closed chamber on top of the soil.

Fluxes of net ecosystem exchange (NEE) were used for eddy covariance data, or when fluxes were partitioned, ecosystem respiration, which were essentially the same during the winter. When a monthly winter flux was negative (i.e., signifying CO₂ uptake), that month was excluded from the dataset. For experimental sites, only control or unmanipulated plots were included.

Regional gridded geospatial products

Data were extracted from regional gridded geospatial products including climatological data, soil temperature and moisture, snow water equivalent, soil carbon stocks and texture, permafrost status, vegetation cover, proxies of vegetation growth and productivity (e.g.,enhanced vegetation index, EVI; leaf area index, LAI; gross primary productivity, GPP) (Natali et al., 2019, in process).

Brown, J., Ferrians, O., Heginbottom, J. and Melnikov, E. Circum-Arctic map of permafrost and ground-ice conditions, version 2. (2002).

Du, J., J.S. Kimball, L.A. Jones, Y. Kim, J. Glassy, and J.D. Watts. 2017. A global satellite environmental data record derived from AMSR-E and AMSR2 microwave Earth observations. Earth Syst. Sci. Data, 9, 791–808, 2017. https://doi.org/10.5194/essd-9-791-2017.

ESA-European Space Agency, 2014. CCI Land Cover Product User Guide version 2.4, 448ESA CCI LC project.

Gruber, Stephan & National Center for Atmospheric Research Staff (Eds). Last modified 08 Oct 2013. The Climate Data Guide: Global Permafrost Zonation Index Map. Retrieved from https://climatedataguide.ucar.edu/climate-data/global-permafrost-zonation-index-map.

Hansen, M.C., R.S. DeFries, J.R.G. Townshend, M. Carroll, C. Dimiceli, and R.A. Sohlberg. Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the MODIS Vegetation Continuous Fields Algorithm. Earth Interactions Volume 7 (2003). https://doi.org/10.1175/1087-3562(2003)007<0001:GPTCAA>2.0.CO;2

Hengl, T., J. Mendes de Jesus, G. B.M. Heuvelink, M. Ruiperez Gonzalez, M. Kilibarda et al. (2017) SoilGrids250m: global gridded soil information based on Machine Learning. PLoS ONE 12(2): e0169748. https://doi.org/10.1371/journal.pone.0169748.

Jones, L.A., J.S. Kimball, R.H. Reichle, N. Madani, J. Glassy, J.V. Ardizzone et al. 2017. The SMAP Level 4 Carbon Product for Monitoring Ecosystem Land–Atmosphere CO₂Exchange. IEEE Transactions on Geoscience and Remote Sensing. 55: 11, https://doi.org/10.1109/TGRS.2017.2729343

Myneni, R., Knyazikhin, Y., Park, T. (2015). MOD15A2H MODIS Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V006. NASA EOSDIS Land Processes DAAC. http://doi.org/10.5067/MODIS/MOD15A2H.006 (Terra), http://doi.org/10.5067/MODIS/MYD15A2H.006 (Aqua)

Natali, S., J.D. Watts, S. Potter, B.M. Rogers, and S.M. Ludwig, A.-K. Selbmann, P.F. Sullivan, B.W. Abbott, K.A. Arndt, L.Birch, M.P Björkman, A.A. Bloom, G. Celis, T.R. Christensen, C.T. Christiansen, R. Commane, E.J. Cooper, P. Crill, C. Czimczik, S. Davydov, J. Du, J.E. Egan, B. Elberling, E.S. Euskirchen, T. Friborg, H. Genet, M. Göckede, J.P. Goodrich, P. Grogan, M. Helbig, E.E. Jafarov, J.D. Jastrow, A.A.M. Kalhori, Y. Kim, J. Kimball, L. Kutzbach, M.J. Lara, K.S. Larsen, Z. Liu, M.M. Loranty, M. Lund, M. Lupascu, N. Madani, R. Matamala, A. Malhotra, J. McFarland, A.D. McGuire, A. Michelsen, C. Minions, W.C. Oechel,, D. Olefeldt, F.-J.W. Parmentier, N. Pirk, B. Poulter, W. Quinton, F. Rezanezhad, D. Risk, T. Sachs, K. Schaefer, N.M. Schmidt, E.A.G. Schuur, P.R. Semenchuk, G. Shaver, O. Sonnentag, G. Starr, C.C. Treat, M.P. Waldrop, Y. Wang, J. Welker, C. Wille, X. Xu, Z. Zhang, Q. Zhuang, and D. Zona. Large loss of CO2 in winter observed across pan-arctic permafrost region. Nature Climate Change.

Reichle, R.H., Q. Liu, R.D. Koster, C.S. Draper, and S.P.P. Mahanama, G.S. Partyka. 2017. Land Surface Precipitation in MERRA-2. J. Clim, 30, 5, 1643-1664. https://doi.org/10.1175/JCLI-D-16-0570.1.

Walker, D.A., Raynolds, M.K., Daniëls, F.J., Einarsson, E., Elvebakk, A., Gould, W.A., Katenin, A.E., Kholod, S.S., Markon, C.J., Melnikov, E.S. and Moskalenko, N.G., 2005. The circumpolar Arctic vegetation map. Journal of Vegetation Science, 16(3), pp.267-282. http://dx.doi.org/10.1111/j.1654-1103.2005.tb02365.x