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Oehri, Jacqueline; Schaepman-Strub, Gabriela; Kim, Jin-Soo; Grysko, Raleigh; Kropp, Heather; Grünberg, Inge; Zemlianskii, Vitalii; Sonnentag, Oliver; Euskirchen, Eugénie S; Reji Chacko, Merin; Muscari, Giovanni; Blanken, Peter D; Dean, Joshua F; di Sarra, Alcide; Harding, Richard J; Sobota, Ireneusz; Kutzbach, Lars; Plekhanova, Elena; Riihelä, Aku; Boike, Julia; Miller, Nathaniel B; Beringer, Jason; López-Blanco, Efrén; Stoy, Paul C; Sullivan, Ryan C; Kejna, Marek; Parmentier, Frans-Jan W; Gamon, John A; Mastepanov, Mikhail; Wille, Christian; Jackowicz-Korczynski, Marcin; Karger, Dirk N; Quinton, William L; Putkonen, Jaakko; van As, Dirk; Christensen, Torben R; Hakuba, Maria Z; Stone, Robert S; Metzger, Stefan; Vandecrux, Baptiste; Frost, Gerald V; Wild, Martin; Hansen, Birger Ulf; Meloni, Daniela; Domine, Florent; te Beest, Mariska; Sachs, Torsten; Kalhori, Aram; Rocha, Adrian V; Williamson, Scott N; Morris, Sara; Atchley, Adam L; Essery, Richard; Runkle, Benjamin R K; Holl, David; Riihimaki, Laura; Iwata, Hiroki; Schuur, Edward A G; Cox, Christopher J; Grachev, Andrey A; McFadden, Joseph P; Fausto, Robert S; Göckede, Mathias; Ueyama, Masahito; Pirk, Norbert; de Boer, Gijs; Bret-Harte, M Syndonia; Leppäranta, Matti; Steffen, Konrad; Friborg, Thomas; Ohmura, Atsumu; Edgar, Colin W; Olofsson, Johan; Chambers, Scott D (2022): Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites - Environmental conditions [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.949789, In: Oehri, Jacqueline; Schaepman-Strub, Gabriela; Kim, Jin-Soo; Grysko, Raleigh; Kropp, Heather; Grünberg, Inge; Zemlianskii, Vitalii; Sonnentag, Oliver; Euskirchen, Eugénie S; Reji Chacko, Merin; Muscari, Giovanni; Blanken, Peter D; Dean, Joshua F; di Sarra, Alcide; Harding, Richard J; Sobota, Ireneusz; Kutzbach, Lars; Plekhanova, Elena; Riihelä, Aku; Boike, Julia; Miller, Nathaniel B; Beringer, Jason; López-Blanco, Efrén; Stoy, Paul C; Sullivan, Ryan C; Kejna, Marek; Parmentier, Frans-Jan W; Gamon, John A; Mastepanov, Mikhail; Wille, Christian; Jackowicz-Korczynski, Marcin; Karger, Dirk N; Quinton, William L; Putkonen, Jaakko; van As, Dirk; Christensen, Torben R; Hakuba, Maria Z; Stone, Robert S; Metzger, Stefan; Vandecrux, Baptiste; Frost, Gerald V; Wild, Martin; Hansen, Birger Ulf; Meloni, Daniela; Domine, Florent; te Beest, Mariska; Sachs, Torsten; Kalhori, Aram; Rocha, Adrian V; Williamson, Scott N; Morris, Sara; Atchley, Adam L; Essery, Richard; Runkle, Benjamin R K; Holl, David; Riihimaki, Laura; Iwata, Hiroki; Schuur, Edward A G; Cox, Christopher J; Grachev, Andrey A; McFadden, Joseph P; Fausto, Robert S; Göckede, Mathias; Ueyama, Masahito; Pirk, Norbert; de Boer, Gijs; Bret-Harte, M Syndonia; Leppäranta, Matti; Steffen, Konrad; Friborg, Thomas; Ohmura, Atsumu; Edgar, Colin W; Olofsson, Johan; Chambers, Scott D (2022): Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites [dataset bundled publication]. PANGAEA, https://doi.org/10.1594/PANGAEA.949792

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Abstract:
Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models.
This dataset describes the environmental conditions for 64 tundra and glacier sites (>=60°N latitude) across the Arctic, for which in situ measurements of surface energy budget components were harmonized (see Oehri et al. 2022). These environmental conditions are (proxies of) potential drivers of SEB-components and could therefore be called SEB-drivers. The associated environmental conditions, include the vegetation types graminoid tundra, prostrate dwarf-shrub tundra, erect-shrub tundra, wetland complexes, barren complexes (≤ 40% horizontal plant cover), boreal peat bogs and glacier. These land surface types (apart from boreal peat bogs) correspond to the main classification units of the Circumpolar Arctic Vegetation Map (CAVM, Raynolds et al. 2019). For each site, additional climatic and biophysical variables are available, including cloud cover, snow cover duration, permafrost characteristics, climatic conditions and topographic conditions.
Keyword(s):
Arctic; dry tundra; Eddy covariance; eddy heat flux; glacier; graminoids; ground heat flux and net radiation; harmonized data; high latitude; Land-Atmosphere; Land-cover; latent and sensible heat; latent heat flux; longwave radiation; meteorological data; observatory data; Peat bog; Radiation fluxes; Radiative energy budget; sensible heat flux; shortwave radiation; shrub tundra; surface energy balance; synthetic data; tundra vegetation; wetland
Further details:
Raynolds, Martha K; Walker, Donald A; Balser, Andrew; Bay, Christian; Campbell, Mitch; Cherosov, Mikhail M; Daniëls, Frederikus J A; Eidesen, Pernille Bronken; Ermokhina, Ksenia A; Frost, Gerald V; Jedrzejek, Birgit; Jorgenson, M Torre; Kennedy, Blair E; Kholod, Sergei S; Lavrinenko, Igor A; Lavrinenko, Olga V; Magnússon, Borgþór; Matveyeva, Nadezhda V; Metúsalemsson, Sigmar; Nilsen, Lennart; Pospelov, Igor N; Pospelova, Vera; Pouliot, Darren; Razzhivin, Vladimir; Schaepman-Strub, Gabriela; Šibík, Jozef; Telyatnikov, Mikhail Yu; Troeva, Elena I (2019): A raster version of the Circumpolar Arctic Vegetation Map (CAVM). Remote Sensing of Environment, 232, 111297, https://doi.org/10.1016/j.rse.2019.111297
Project(s):
Funding:
Universität Zürich (UZH), grant/award no. 178753
Coverage:
Median Latitude: 69.281003 * Median Longitude: -56.111532 * South-bound Latitude: 61.030800 * West-bound Longitude: -157.408900 * North-bound Latitude: 79.910800 * East-bound Longitude: 161.341430
Date/Time Start: 1994-01-01T00:00:00 * Date/Time End: 2022-01-01T00:00:00
Minimum ELEVATION: 0.2 m a.s.l. * Maximum ELEVATION: 3249.0 m a.s.l.
Event(s):
Arctic_SEB_CA-SCB  * Latitude: 61.308900 * Longitude: -121.298400 * Date/Time Start: 2014-01-01T00:00:00 * Date/Time End: 2017-12-31T00:00:00 * Elevation: 269.7 m * Method/Device: Field observation
Arctic_SEB_CP1  * Latitude: 69.879750 * Longitude: -46.986670 * Date/Time Start: 1998-01-01T00:00:00 * Date/Time End: 2017-12-31T00:00:00 * Elevation: 2002.9 m * Method/Device: Field observation
Arctic_SEB_Dye-2  * Latitude: 66.480010 * Longitude: -46.278890 * Date/Time Start: 1998-01-01T00:00:00 * Date/Time End: 2017-12-31T00:00:00 * Elevation: 2160.4 m * Method/Device: Field observation
Comment:
List of Ameriflux, AON and FLUXNET sites contained in this dataset and their corresponding siteid's and doi's: CA-SCB (https://doi.org/10.17190/AMF/1498754), FI-Lom (https://doi.org/10.18140/FLX/1440228), GL-NuF (https://doi.org/10.18140/FLX/1440222), GL-ZaF (https://doi.org/10.18140/FLX/1440223), GL-ZaH (https://doi.org/10.18140/FLX/1440224), RU-Che (https://doi.org/10.18140/FLX/1440181), RU-Cok (https://doi.org/10.18140/FLX/1440182), RU-Sam (https://doi.org/10.18140/FLX/1440185), RU-Tks (https://doi.org/10.18140/FLX/1440244), RU-Vrk (https://doi.org/10.18140/FLX/1440245), SE-St1 (https://doi.org/10.18140/FLX/1440187), SJ-Adv (https://doi.org/10.18140/FLX/1440241), SJ-Blv (https://doi.org/10.18140/FLX/1440242), US-A03 (https://doi.org/10.17190/AMF/1498752), US-A10 (https://doi.org/10.17190/AMF/1498753), US-An1 (https://doi.org/10.17190/AMF/1246142), US-An2 (https://doi.org/10.17190/AMF/1246143), US-An3 (https://doi.org/10.17190/AMF/1246144), US-Atq (https://doi.org/10.17190/AMF/1246029), US-Brw (https://doi.org/10.17190/AMF/1246041), US-EML (https://doi.org/10.17190/AMF/1418678), US-HVa (https://doi.org/10.17190/AMF/1246064), US-ICh (https://doi.org/10.17190/AMF/1246133), US-ICs (https://doi.org/10.17190/AMF/1246130), US-ICt (https://doi.org/10.17190/AMF/1246131), US-Ivo (https://doi.org/10.17190/AMF/1246067), US-NGB (https://doi.org/10.17190/AMF/1436326), US-Upa (https://doi.org/10.17190/AMF/1246108), US-xHE (https://doi.org/10.17190/AMF/1617729), US-xTL (https://doi.org/10.17190/AMF/1617739).
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
Event labelEventOehri, Jacqueline
Type of studyStudy typeOehri, Jacqueline
LATITUDELatitudeOehri, JacquelineGeocode
LONGITUDELongitudeOehri, JacquelineGeocode
Date/Time of eventDate/TimeOehri, Jacqueline
ELEVATIONElevationm a.s.l.Oehri, JacquelineGeocode – at Location ID; from ArcticDEM
Location IDLoc IDOehri, Jacquelinenetwork-specific site identifier
Data sourceData sourceOehri, Jacquelinenetwork/repository
Vegetation typeVegetation typeOehri, Jacquelinefrom in-situ site descriptions
10 Vegetation typeVegetation typeOehri, Jacquelinefrom in-situ site descriptions; with number code
11 Vegetation typeVegetation typeOehri, Jacquelinedominant vegetation type within 500m radius; from CAVM raster
12 Vegetation typeVegetation typeOehri, Jacquelinedominant vegetation type within 500m radius with number code; from CAVM raster
13 Vegetation typeVegetation typeOehri, Jacquelineweight of dominant CAVM vegetation type within 500m radius (range: 0-1; 1=full occupation).
14 Vegetation typeVegetation typeOehri, Jacquelinevegetation type for specific study location; from CAVM raster (with no regard of dominant CAVM type)
15 Land cover typeLC typeOehri, Jacquelinedescribed by data repository []
16 Land cover classesLCCOehri, Jacquelineland-cover type classification scheme; IGBP=International Geosphere-Biosphere Programme
17 Species presentSpec presentOehri, Jacquelineplant species present at specific sites; from in situ descriptions
18 Vegetation typeVegetation typeOehri, Jacquelinevegetation types present within 500m radius; from CAVM raster
19 Number of vegetation typesN veg types#Oehri, Jacquelinewithin 500m radius; from CAVM raster
20 Shannon Diversity IndexH'Oehri, Jacquelinefrom CAVM raster
21 Shannon Diversity Index, maximumH' maxOehri, Jacquelinefrom CAVM raster []
22 ZoneZoneOehri, JacquelineA=coldest, E=warmest
23 Permafrost, typePermafrost typeOehri, Jacquelinepermafrost-ground ice-landform type
24 Permafrost, typePermafrost typeOehri, Jacquelineaggregated in main types
25 Permafrost extentPermafrost extOehri, Jacquelineaggregated in main types
26 Permafrost ice content, descriptionPermafrost ice cont descrOehri, Jacqueline
27 PrecipitationPrecipmm/dayOehri, JacquelineDaily mean
28 Precipitation, daily, maximumPrecip day maxmm/dayOehri, JacquelineDaily maximumAverage for each Location ID
29 Humidity, relativeRH%Oehri, JacquelineDaily meanAverage for each Location ID
30 Wind speedffm/sOehri, JacquelineDaily mean
31 Vapour pressure deficitVPDhPaOehri, JacquelineDaily meanAverage for each Location ID
32 Pressure, atmosphericPPPPhPaOehri, JacquelineDaily meanAverage for each Location ID
33 Soil water content, volumetricvol SWC%Oehri, JacquelineDaily meanAverage for each Location ID
34 SlopeSlopedegOehri, Jacquelineat Location ID; from ArcticDEM
35 AspectAspectarbitrary unitsOehri, JacquelineNorthness; 1=north-exposed, -1=south-exposed; at Location ID; from ArcticDEM
36 AspectAspectarbitrary unitsOehri, JacquelineEastness; 1=east-exposed, -1=west-exposed; at Location ID; from ArcticDEM
37 ELEVATIONElevationm a.s.l.Oehri, JacquelineMean valuesGeocode – mean; within 500m radius; from ArcticDEM
38 ELEVATIONElevationm a.s.l.Oehri, JacquelineMedian valuesGeocode – median; within 500m radius; from ArcticDEM
39 Elevation, standard deviationElev std dev±Oehri, Jacquelinewithin 500m radius; from ArcticDEM
40 SlopeSlopedegOehri, JacquelineCalculated average/mean valueswithin 500m radius; from ArcticDEM
41 Slope, coefficient of variationSlope CVOehri, Jacquelinewithin 500m radius; from ArcticDEM
42 AspectAspectarbitrary unitsOehri, JacquelineNorthness; 1=north-exposed, -1=south-exposed; within 500m radius; from ArcticDEM
43 Aspect, coefficient of variationAspect CVOehri, JacquelineNorthness; within 500m radius; from ArcticDEM
44 AspectAspectarbitrary unitsOehri, JacquelineEastness; 1=east-exposed, -1=west-exposed; within 500m radius; from ArcticDEM
45 Aspect, coefficient of variationAspect CVOehri, JacquelineEastness; within 500m radius; from ArcticDEM
46 Precipitation, sumPrecip summmOehri, Jacquelineannual sum; averaged from 1979-2018
47 Precipitation, coefficient of variationPrecip CVOehri, Jacquelineof annual sum; from 1979-2018
48 Slope, mathematicalSlope mathOehri, Jacquelinechange of precipitation (mm/year) estimated from linear model; from 1979-2018
49 Precipitation, snowSnowmmOehri, Jacquelineannual sum; averaged from 1979-2018
50 Snowfall, coefficient of variationSnowfall CVOehri, Jacquelineof annual sum; from 1979-2018
51 Slope, mathematicalSlope mathOehri, Jacquelinechange of snowfall (mm/year) estimated from linear model; from 1979-2018
52 Temperature, air, annual meanMAAT°COehri, Jacquelineaveraged from 1979-2018
53 Temperature, air, coefficient of variationT air CVOehri, Jacquelineof annual sum; from 1979-2018
54 Slope, mathematicalSlope mathOehri, Jacquelinechange of air temperature (°C/year) estimated from linear model; from 1979-2018
55 Summer warmth indexSWI°COehri, Jacquelineannual sum of monthly mean temperatures above 0°C; averaged from 1979-2018
56 Conrad's continentality indexConrad cont indexOehri, Jacquelinederived from Summer warmth index; averaged from 1979-2018
57 Temperature, annual mean rangeMART°COehri, Jacquelineaveraged from 1979-2018
58 Cloud coverCloud cov%Oehri, Jacquelineaveraged from 1984-2016
59 Cloud cover, standard deviationCloud cov std dev±Oehri, Jacquelineaveraged from 1984-2016
60 Slope, mathematicalSlope mathOehri, Jacquelinechange of cloud cover (%/year) estimated from linear model; from 1984-2016
61 Cloud coverCloud cov%Oehri, Jacquelinedeteced by infrared; averaged from 1984-2016
62 Cloud cover, standard deviationCloud cov std dev±Oehri, Jacquelinedeteced by infrared; averaged from 1984-2016
63 Slope, mathematicalSlope mathOehri, Jacquelinechange of cloud cover (%/year) estimated from linear model; deteced by infrared; averaged from 1984-2016
64 Cloud top pressureCloud top presshPaOehri, Jacquelineaveraged from 1984-2016
65 Cloud top pressure, standard deviationCloud top press std dev±Oehri, Jacquelineaveraged from 1984-2016
66 Slope, mathematicalSlope mathOehri, Jacquelinechange of cloud top pressure (hPa/year) estimated from linear model; averaged from 1984-2016
67 Cloud top pressureCloud top presshPaOehri, Jacquelinedeteced by infrared; averaged from 1984-2016
68 Cloud top pressure, standard deviationCloud top press std dev±Oehri, Jacquelinedeteced by infrared; averaged from 1984-2016
69 Slope, mathematicalSlope mathOehri, Jacquelinechange of cloud top pressure (hPa/year) estimated from linear model; deteced by infrared; averaged from 1984-2016
70 Cloud top temperatureCloud top T°COehri, Jacquelineaveraged from 1984-2016
71 Cloud top temperature, standard deviationCloud top T std dev±Oehri, Jacquelineaveraged from 1984-2016
72 Slope, mathematicalSlope mathOehri, Jacquelinechange of cloud top temperature (°C/year) estimated from linear model; averaged from 1984-2016
73 Cloud top temperatureCloud top T°COehri, Jacquelinedeteced by infrared; averaged from 1984-2016
74 Cloud top temperature, standard deviationCloud top T std dev±Oehri, Jacquelinedeteced by infrared; averaged from 1984-2016
75 Slope, mathematicalSlope mathOehri, Jacquelinechange of cloud top temperature(°C/year) estimated from linear model; deteced by infrared; averaged from 1984-2016
76 Snow typeSnowOehri, Jacqueline
77 Snow cover, number of daysSnow cov num daysdaysOehri, JacquelineMedian valuesfrom 2000-2020
78 Slope, mathematicalSlope mathOehri, Jacquelinechange of snow cover (days/year) estimated from linear model; from 2000-2020
79 p-valuep-valueOehri, Jacquelinefor slope of snow cover; from 2000-2020
80 Snow-free daysSnow-free daysdaysOehri, JacquelineMedian valuesfrom 2000-2020
81 Slope, mathematicalSlope mathOehri, Jacquelinechange of snow-free days (days/year) estimated from linear model; from 2000-2020
82 p-valuep-valueOehri, Jacquelinefor slope of snow-free days; from 2000-2020
83 Snow, onset, day of the yearSnow onset day of yeardayOehri, JacquelineMedian valuesfrom 2000-2020
84 Slope, mathematicalSlope mathOehri, Jacquelinechange of snow onset (day of year/year) estimated from linear model; from 2000-2020
85 p-valuep-valueOehri, Jacquelinefor slope of snow onset; from 2000-2020
86 SiteSiteOehri, Jacquelinestudy-site ID
87 Uniform resource locator/link to referenceURL refOehri, Jacqueline#1 information about the specific study site
88 Reference/sourceReferenceOehri, Jacqueline#2 more information about the specific study site
89 Land cover classesLCCOehri, Jacquelinefrom CERES Surface Type IDs
Status:
Curation Level: Enhanced curation (CurationLevelC)
Size:
4705 data points

Data

Download dataset as tab-delimited text — use the following character encoding:


Event

Study type

Latitude

Longitude

Date/Time

Elevation [m a.s.l.]
(at Location ID; from ArcticDEM)

Loc ID
(network-specific site identifier)

Data source
(network/repository)

Vegetation type
(from in-situ site descriptions)
10 
Vegetation type
(from in-situ site description...)
11 
Vegetation type
(dominant vegetation type with...)
12 
Vegetation type
(dominant vegetation type with...)
13 
Vegetation type
(weight of dominant CAVM veget...)
14 
Vegetation type
(vegetation type for specific ...)
15 
LC type
(described by data repository [])
16 
LCC
(land-cover type classificatio...)
17 
Spec present
(plant species present at spec...)
18 
Vegetation type
(vegetation types present with...)
19 
N veg types [#]
(within 500m radius; from CAVM...)
20 
H'
(from CAVM raster)
21 
H' max
(from CAVM raster [])
22 
Zone
(A=coldest, E=warmest)
23 
Permafrost type
(permafrost-ground ice-landfor...)
24 
Permafrost type
(aggregated in main types)
25 
Permafrost ext
(aggregated in main types)
26 
Permafrost ice cont descr
27 
Precip [mm/day]
(Daily mean)
28 
Precip day max [mm/day]
(Average for each Location ID,...)
29 
RH [%]
(Average for each Location ID,...)
30 
ff [m/s]
(Daily mean)
31 
VPD [hPa]
(Average for each Location ID,...)
32 
PPPP [hPa]
(Average for each Location ID,...)
33 
vol SWC [%]
(Average for each Location ID,...)
34 
Slope [deg]
(at Location ID; from ArcticDEM)
35 
Aspect [arbitrary units]
(Northness; 1=north-exposed, -...)
36 
Aspect [arbitrary units]
(Eastness; 1=east-exposed, -1=...)
37 
Elevation [m a.s.l.]
(mean; within 500m radius; fro...)
38 
Elevation [m a.s.l.]
(median; within 500m radius; f...)
39 
Elev std dev [±]
(within 500m radius; from Arct...)
40 
Slope [deg]
(within 500m radius; from Arct...)
41 
Slope CV
(within 500m radius; from Arct...)
42 
Aspect [arbitrary units]
(Northness; 1=north-exposed, -...)
43 
Aspect CV
(Northness; within 500m radius...)
44 
Aspect [arbitrary units]
(Eastness; 1=east-exposed, -1=...)
45 
Aspect CV
(Eastness; within 500m radius;...)
46 
Precip sum [mm]
(annual sum; averaged from 197...)
47 
Precip CV
(of annual sum; from 1979-2018)
48 
Slope math
(change of precipitation (mm/y...)
49 
Snow [mm]
(annual sum; averaged from 197...)
50 
Snowfall CV
(of annual sum; from 1979-2018)
51 
Slope math
(change of snowfall (mm/year) ...)
52 
MAAT [°C]
(averaged from 1979-2018)
53 
T air CV
(of annual sum; from 1979-2018)
54 
Slope math
(change of air temperature (°C...)
55 
SWI [°C]
(annual sum of monthly mean te...)
56 
Conrad cont index
(derived from Summer warmth in...)
57 
MART [°C]
(averaged from 1979-2018)
58 
Cloud cov [%]
(averaged from 1984-2016)
59 
Cloud cov std dev [±]
(averaged from 1984-2016)
60 
Slope math
(change of cloud cover (%/year...)
61 
Cloud cov [%]
(deteced by infrared; averaged...)
62 
Cloud cov std dev [±]
(deteced by infrared; averaged...)
63 
Slope math
(change of cloud cover (%/year...)
64 
Cloud top press [hPa]
(averaged from 1984-2016)
65 
Cloud top press std dev [±]
(averaged from 1984-2016)
66 
Slope math
(change of cloud top pressure ...)
67 
Cloud top press [hPa]
(deteced by infrared; averaged...)
68 
Cloud top press std dev [±]
(deteced by infrared; averaged...)
69 
Slope math
(change of cloud top pressure ...)
70 
Cloud top T [°C]
(averaged from 1984-2016)
71 
Cloud top T std dev [±]
(averaged from 1984-2016)
72 
Slope math
(change of cloud top temperatu...)
73 
Cloud top T [°C]
(deteced by infrared; averaged...)
74 
Cloud top T std dev [±]
(deteced by infrared; averaged...)
75 
Slope math
(change of cloud top temperatu...)
76 
Snow
77 
Snow cov num days [days]
(from 2000-2020, Median values)
78 
Slope math
(change of snow cover (days/ye...)
79 
p-value
(for slope of snow cover; from...)
80 
Snow-free days [days]
(from 2000-2020, Median values)
81 
Slope math
(change of snow-free days (day...)
82 
p-value
(for slope of snow-free days; ...)
83 
Snow onset day of year [day]
(from 2000-2020, Median values)
84 
Slope math
(change of snow onset (day of ...)
85 
p-value
(for slope of snow onset; from...)
86 
Site
(study-site ID)
87 
URL ref
(#1 information about the spec...)
88 
Reference
(#2 more information about the...)
89 
LCC
(from CERES Surface Type IDs)
Arctic_SEB_CA-SCB Data synthesis61.308900-121.2984002014-01-01269.4CA-SCBAmerifluxBPBBPBNNAr1.0NArWETIGBPChamaedaphne calyculata; Andromeda polifolia; Vaccinium oxycoccos; Sphagnum balticum; S. magellanicum; Scheuchzeria palustrisNAr1-0.00000.0000<ESlfsporadicsporadic or isolated patcheslow (>20%)0.01980.280263.41.41978.40.22390.6740.739269.7269.70.600.18470.46770.3481.530.4261.51613.785250.213.6280184.60.2290.2264-1.9-0.520.027766.1360.641.670.92.53-0.049769.52.80-0.0484480.952.400.6159633.050.860.3767-28.96.560.0469-16.510.040.0122Seasonal snow198.00-0.52330.3086121.50-0.37340.2292290.500.06620.808621ameriflux.lbl.govHelbig, M., Chasmer, L. E., Kljun, N., Quinton, W. L., Treat, C. C., & Sonnentag, O. (2017). The positive net radiative greenhouse gas forcing of increasing methane emissions from a thawing boreal forest-wetland landscape. Global Change Biology, 23(6), 2413-2427. web: onlinelibrary.wiley.comMixed-Forest
Arctic_SEB_CP1 Data synthesis69.879750-46.9866701998-01-012003.2CP1GC-NetGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers0.05040.261293.67.280.36390.620-0.7852002.92003.11.280.31940.27420.04612.22-0.815-0.18792.349750.336.5406784.90.3266.3013-16.8-0.080.04340.0024.622.348.93.76-0.104444.16.57-0.1099523.927.070.6205566.834.58-0.1059-30.37.340.1048-27.88.600.0628Continuous snow365.000.000048Permanent-Snow
Arctic_SEB_Dye-2 Data synthesis66.480010-46.2788901998-01-012160.6Dye-2GC-NetGLGLGLGL1.0GLiceown_descriptionGL1-0.00000.0000Glaciersglaciersglaciersglaciersglaciers0.04900.264592.27.240.58710.237-0.9722160.42160.62.480.56210.07920.2430.24-0.968-0.02626.057250.406.2355606.40.3966.2237-16.1-0.080.03970.0024.221.951.74.44-0.105347.07.44-0.0607491.629.200.2842548.536.510.0609-32.26.940.0636-28.78.470.0576Continuous snow365.000.000049Permanent-Snow
Arctic_SEB_EGP Data synthesis75.624700-35.9748002016-01-012704.8EGPPROMICEGLGLGLGL1.0GLiceown_descriptionGL1-0.00000.0000Glaciersglaciersglaciersglaciersglaciers96.55.24719.10.11960.0870.9962705.02705.00.530.12390.16430.1571.420.9610.06132.275500.382.6958132.30.3832.6958-27.6-0.040.04640.0037.630.343.311.50-0.013239.714.59-0.0738474.250.630.6549489.755.180.1023-36.69.460.0950-35.89.800.0595Continuous snow365.000.000059Permanent-Snow
Arctic_SEB_FI-Lom Data synthesis67.99724024.2091802007-01-01295.8FI-LomFLUXNETBPBBPBNNAr1.0NArWETIGBPCarex rostrata; C. chordorrhiza; C. magellanica; C. lasiocarpa; Menyanthes trifoliata; Equisetum fluviatile; Betula nana; Salix lapponum; Andromeda polyfolia; Vaccinium oxycoccos; Sphagnum riparium; S. fallax; S. jensenii; S. teres; S. russowii; S. angustifolium; Warnstorfia exannulata; Helodium blandowii; Paludella squarrosaNAr10.00000.0000<EDlrdiscontinuousdiscontinuouslow (>20%)0.03050.369581.12.221.78966.00.7197-0.9940.105300.0298.14.751.16620.7313-0.417-1.75-0.177-2.90769.629000.174.8639254.40.2291.3085-0.0-38.570.038149.5836.729.167.73.45-0.082464.54.24-0.0633590.640.94-0.1124674.433.580.1131-21.45.59-0.0049-15.27.940.0123Seasonal snow220.500.78030.2035137.500.49030.1677288.00-0.09340.720712europe-fluxdata.euAurela, M., Lohila, A., Tuovinen, J. P., Hatakka, J., Penttilä, T., & Laurila, T. (2015). Carbon dioxide and energy flux measurements in four northern-boreal ecosystems at Pallas. web: helda.helsinki.fiEvergreen-Needleleaf-Forest
Arctic_SEB_GL-NuF Data synthesis64.130830-51.3861102008-01-0170.7GL-NuFFLUXNETWW3SS10.583313938393434S1WETIGBPCarex rariflora; Eriophorum angustifolium; Scirpus caespitosusP1|P2|S1|SW40.79151.3863DIlrInland lakessporadic or isolated patcheslow (>20%)0.05490.278872.91.801.941.9062-0.999-0.03273.770.620.116.30150.78490.5401.050.3741.331494.903250.4118.9018727.60.45010.3830-3.9-0.410.056119.9325.422.378.15.32-0.062974.57.76-0.0561610.881.65-0.0593723.827.00-0.0730-22.55.730.0447-15.25.460.0591Seasonal snow248.50-0.25130.6574161.00-0.09680.8283269.000.33750.517916europe-fluxdata.euweb: link.springer.com; Westergaard-Nielsen, A., Lund, M., Hansen, B. U., & Tamstorf, M. P. (2013). Camera derived vegetation greenness index as proxy for gross primary production in a low Arctic wetland area. ISPRS Journal of Photogrammetry and Remote Sensing, 86, 89-99. web: sciencedirect.comTundra
Arctic_SEB_GL-ZaF Data synthesis74.481430-20.5545202008-01-0185.7GL-ZaFFLUXNETSS1SS11.0S1WETIGBPEriophorum scheuchzeri; Carex stands; Duponita psilosantha; E. triste; S. arctica; Andromeda latifoliaS110.00000.0000CClrcontinuouscontinuouslow (>20%)0.01070.092376.02.551.550.6788-0.997-0.08086.986.73.070.86960.3922-0.599-0.900.0876.72432.150500.6611.5192339.20.7119.3848-10.9-0.100.06937.8633.727.971.94.60-0.061269.93.91-0.0692550.440.920.2700642.463.320.1877-27.65.010.0271-20.710.560.0264Seasonal snow265.00-0.76550.2630167.00-0.14170.7298272.000.46440.18143europe-fluxdata.euStiegler, C., Lund, M., Christensen, T. R., Mastepanov, M., & Lindroth, A. (2016). Two years with extreme and little snowfall: effects on energy partitioning and surface energy exchange in a high-Arctic tundra ecosystem. Cryosphere, 10(4). web: core.ac.ukGrassland
Arctic_SEB_GL-ZaH Data synthesis74.473280-20.5503002000-01-0185.0GL-ZaHFLUXNETPP2SS10.887152309362531S1GRAIGBPCassiope tetragona; Salix arctica; D. integrifolia; Vaccinium uliginosum; E. scheuchzeriP2|S120.35240.6931CClrcontinuouscontinuouslow (>20%)0.00920.080271.72.341.1536.60.1873-0.7110.70382.283.73.671.07120.8063-0.455-1.100.1614.44423.855000.6611.2806330.90.7149.2594-10.8-0.100.06998.3133.828.071.94.60-0.061269.93.91-0.0692550.440.920.2700642.463.320.1877-27.65.010.0271-20.710.560.0264Seasonal snow265.00-0.76550.2630167.00-0.14170.7298272.000.46440.18144europe-fluxdata.euLund, M., Hansen, B. U., Pedersen, S. H., Stiegler, C., & Tamstorf, M. P. (2014). Characteristics of summer-time energy exchange in a high Arctic tundra heath 2000-2010. Tellus B: Chemical and Physical Meteorology, 66(1), 21631. web: tandfonline.comGrassland
Arctic_SEB_KAN_B Data synthesis67.125200-50.1832002011-01-01377.9KAN_BPROMICEBB3SS10.80310317345783S1landown_descriptionP2|S120.49610.6931EClrcontinuouscontinuouslow (>20%)68.72.29964.96.4008-0.0410.999404.5390.241.519.00610.6526-0.305-1.730.6830.59327.967750.463.8324131.20.5381.7432-5.3-0.330.053730.5641.431.868.63.07-0.033266.44.21-0.0325517.859.050.6985648.245.270.4676-30.04.420.0816-20.010.100.0631Seasonal snow147.50-0.80120.1663266.5074Tundra
Arctic_SEB_KAN_L Data synthesis67.095500-49.9513002008-01-01697.0KAN_LPROMICEGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers76.44.51927.02.8793-0.509-0.861691.1693.512.502.71490.4912-0.501-0.90-0.637-0.58364.414500.474.1706171.90.5222.2947-6.3-0.270.047921.5736.729.052.12.96-0.131447.74.97-0.1228513.435.130.5453601.846.880.1405-31.05.790.0769-24.79.300.0543Continuous snow365.000.000075Permanent-Snow
Arctic_SEB_KAN_M Data synthesis67.067000-48.8355002008-01-011303.6KAN_MPROMICEGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers84.66.13859.60.13990.996-0.0941303.31303.51.390.41250.48150.6400.780.1523.71522.664300.445.2573426.40.4674.5024-10.5-0.140.04130.0922.621.052.12.96-0.131447.74.97-0.1228513.435.130.5453601.846.880.1405-31.05.790.0769-24.79.300.0543Continuous snow365.000.000076Permanent-Snow
Arctic_SEB_KAN_U Data synthesis67.000300-47.0253002009-01-011879.1KAN_UPROMICEGLGLGLGL0.999999999999999GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers88.96.51799.80.6029-0.593-0.8051879.41879.42.620.59480.1033-0.559-0.17-0.821-0.08633.970700.415.7829596.00.4055.6622-14.4-0.090.04110.0023.621.652.12.96-0.131447.74.97-0.1228513.435.130.5453601.846.880.1405-31.05.790.0769-24.79.300.0543Continuous snow365.000.000077Permanent-Snow
Arctic_SEB_KPC_L Data synthesis79.910800-24.0828002008-01-01406.9KPC_LPROMICEGLGLGLGL1.0GLiceown_descriptionGL1-0.00000.0000Glaciersglaciersglaciersglaciersglaciers76.15.84966.62.9241-0.1190.993402.3404.713.003.30720.48050.1122.900.9320.12220.213750.495.4823199.80.5225.4553-17.1-0.060.05671.3340.131.854.25.490.044152.34.880.0181531.727.921.1877614.974.900.6375-30.95.670.1059-24.711.360.0641Continuous snow365.000.000057Permanent-Snow
Arctic_SEB_KPC_U Data synthesis79.834700-25.1662002008-01-01903.1KPC_UPROMICEGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers84.34.85906.20.35210.8280.560903.0903.01.510.34470.14180.8720.090.4480.41235.777000.495.8081227.70.4985.7223-17.1-0.050.05350.4236.029.454.25.490.044152.34.880.0181531.727.921.1877614.974.900.6375-30.95.670.1059-24.711.360.0641Continuous snow365.000.000058Permanent-Snow
Arctic_SEB_MIT Data synthesis65.692200-37.8280002009-01-01494.7MITPROMICEGLGLBB30.752492667669437B3independent_glacierown_descriptionB1|B320.55960.6931Dglaciersglaciersglaciersglaciers78.83.04953.03.0764-0.479-0.878487.3489.618.735.00540.4005-0.252-1.87-0.821-0.241628.879250.3312.77121059.40.4018.9012-3.2-0.320.065915.7916.617.579.06.44-0.049476.28.83-0.0182559.273.95-0.2380682.715.890.4030-25.44.530.0090-16.75.990.0445Continuous snow365.000.000062Barren/Desert
Arctic_SEB_NASA-E Data synthesis75.000000-29.9997201998-01-012658.7NASA-EGC-NetGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers0.02380.131594.55.791.0530-0.179-0.9842659.12659.44.380.97800.1648-0.177-0.21-0.984-0.01169.942750.564.1134169.90.5594.1134-25.6-0.040.04840.0033.828.047.83.97-0.016943.51.53-0.0822502.528.300.5131576.258.390.0420-32.96.020.0830-27.510.280.0654Continuous snow365.000.000053Permanent-Snow
Arctic_SEB_NASA-SE Data synthesis66.479700-42.5002001998-01-012430.1NASA-SEGC-NetGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers0.07770.417394.35.280.5428-0.8080.5892429.72429.72.320.52020.0736-0.816-0.040.5760.081024.822250.3712.96791024.30.37212.9905-18.4-0.060.04420.0023.621.548.44.14-0.115143.57.01-0.0754494.323.610.1424544.029.57-0.0585-31.86.600.0508-28.88.020.0469Continuous snow365.000.000050Permanent-Snow
Arctic_SEB_NASA-U Data synthesis73.841890-49.4983101998-01-012367.8NASA-UGC-NetGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers0.03350.181494.76.940.0623-0.367-0.9302367.72367.70.290.07240.2903-0.266-1.88-0.753-0.44405.298750.335.8560403.70.3245.7955-21.0-0.060.03810.0028.524.846.44.31-0.060941.87.27-0.1133526.128.030.7932572.135.83-0.1729-31.57.110.1142-28.68.570.0508Continuous snow365.000.000054Permanent-Snow
Arctic_SEB_NUK_K Data synthesis64.162300-51.3587002014-01-01745.3NUK_KPROMICEGLGLBB30.899061083024017B3independent_glacierown_descriptionB3|P1|P230.38641.0986DIlrInland lakessporadic or isolated patcheslow (>20%)79.62.75921.75.64671.0000.025762.4749.447.9213.52820.50370.6010.930.0717.961171.581250.4214.7992525.00.4657.2534-3.5-0.480.061823.7827.623.678.15.32-0.062974.57.76-0.0561610.881.65-0.0593723.827.00-0.0730-22.55.730.0447-15.25.460.0591Seasonal snow263.75164.25-0.43550.4584278.5072Tundra
Arctic_SEB_NUK_L Data synthesis64.482200-49.5358002007-01-01564.1NUK_LPROMICEGLGLBB11.0B1iceown_descriptionB110.00000.0000EDlrdiscontinuousdiscontinuouslow (>20%)68.83.49941.92.34380.664-0.747564.6562.512.912.92870.62760.4400.97-0.715-0.47925.623000.4311.1523347.70.4795.5833-4.9-0.320.050913.8523.521.363.47.58-0.096961.77.56-0.0659494.057.34-0.5612618.235.000.0626-31.23.68-0.0085-22.08.750.0415Continuous snow365.000.000070Barren/Desert
Arctic_SEB_NUK_N Data synthesis64.945200-49.8850002010-01-01949.6NUK_NPROMICEGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers77.64.79899.32.9235-0.764-0.646948.7953.411.832.88620.5187-0.513-0.99-0.504-0.951101.201250.4212.7301555.10.4266.8368-6.7-0.240.055412.0728.924.463.47.58-0.096961.77.56-0.0659494.057.34-0.5612618.235.000.0626-31.23.68-0.0085-22.08.750.0415Continuous snow365.000.000073Barren/Desert
Arctic_SEB_NUK_U Data synthesis64.510800-49.2692002007-01-011152.7NUK_UPROMICEGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers76.65.37875.11.66370.451-0.8931154.71152.95.391.27470.46560.3261.52-0.465-1.411075.459750.4413.3422676.10.4589.3469-8.4-0.170.04230.8520.319.463.47.58-0.096961.77.56-0.0659494.057.34-0.5612618.235.000.0626-31.23.68-0.0085-22.08.750.0415Continuous snow365.000.000071Permanent-Snow
Arctic_SEB_QAS_A Data synthesis61.243000-46.7328002012-01-011046.6QAS_APROMICEGLGLGLGL1.0GLiceown_descriptionGL1-0.00000.0000Glaciersglaciersglaciersglaciersglaciers84.85.78883.52.1042-0.8750.4841047.81046.87.941.70870.2866-0.891-0.100.3950.532216.904750.3212.63081479.60.3606.8379-6.1-0.200.04263.3516.517.062.13.57-0.152358.63.20-0.1056475.750.67-0.7589601.434.170.0467-31.04.05-0.0337-21.68.140.0235Continuous snow365.000.000069Permanent-Snow
Arctic_SEB_QAS_L Data synthesis61.030800-46.8493002007-01-01319.7QAS_LPROMICEGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers72.74.30971.32.5756-0.325-0.946315.7315.510.592.42410.3861-0.504-0.58-0.786-0.271657.418500.318.6189598.20.3692.5031-1.9-0.680.045221.4518.318.062.13.57-0.152358.63.20-0.1056475.750.67-0.7589601.434.170.0467-31.04.05-0.0337-21.68.140.0235Continuous snow365.000.000066Permanent-Snow
Arctic_SEB_QAS_M Data synthesis61.099800-46.8330002016-01-01668.9QAS_MPROMICEGLGLGLGL0.999999999999999GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers79.35.34931.63.1287-0.920-0.391670.7668.911.992.65410.2754-0.824-0.16-0.427-0.812022.873500.3110.9072951.40.3794.1668-3.7-0.340.043212.7117.917.762.13.57-0.152358.63.20-0.1056475.750.67-0.7589601.434.170.0467-31.04.05-0.0337-21.68.140.0235Continuous snow365.000.000067Permanent-Snow
Arctic_SEB_QAS_U Data synthesis61.175300-46.8195002008-01-01933.5QAS_UPROMICEGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers85.65.03899.40.6580-0.320-0.947933.5933.82.700.63440.3813-0.396-0.49-0.892-0.112212.549000.3212.09101311.30.3717.6079-5.2-0.230.04236.4217.017.362.13.57-0.152358.63.20-0.1056475.750.67-0.7589601.434.170.0467-31.04.05-0.0337-21.68.140.0235Continuous snow365.000.000068Permanent-Snow
Arctic_SEB_RU-Che Data synthesis68.613040161.3414302002-01-018.9RU-CheFLUXNETWW3NNAr1.0NArWETIGBPCarex appendiculata; Carex lugens; Eriophorum angustifoliumNAr1-0.00000.0000<EChfcontinuouscontinuoushigh (0-10%)0.00630.085172.43.332.241013.00.0457-0.132-0.9918.99.00.390.08341.4416-0.058-8.51-0.439-1.71355.259750.295.4112171.90.2961.8846-10.4-0.140.091939.2271.549.365.25.66-0.067463.36.61-0.0560527.644.290.5215642.080.720.0865-29.38.040.0610-20.713.750.0341Seasonal snow223.000.17310.6916141.000.33700.2611282.000.22210.33349europe-fluxdata.euGöckede, M., Kittler, F., Kwon, M. J., Burjack, I., Heimann, M., Kolle, O., ... & Zimov, S. (2017). Shifted energy fluxes, increased Bowen ratios, and reduced thaw depths linked with drainage-induced changes in permafrost ecosystem structure. Cryosphere. web: helda.helsinki.fi; web: onlinelibrary.wiley.com; Kittler, F., Heimann, M., Kolle, O., Zimov, N., Zimov, S., & Göckede, M. (2017). Long-term drainage reduces CO2 uptake and CH4 emissions in a Siberian permafrost ecosystem. Global Biogeochemical Cycles, 31(12), 1704-1717. web: agupubs.onlinelibrary.wiley.comOpen-Shrubland(Desert)
Arctic_SEB_RU-Cok Data synthesis70.829140147.4942802003-01-017.6RU-CokFLUXNETGG4GG40.556411998359392G4OSHIGBPBetula nana; Salix sp.; Sphagnum sp.; Potentilla palustris; Carex sp.; Eriophorum sp.G4|S1|W330.82341.0986EChfcontinuouscontinuoushigh (0-10%)0.00920.134476.53.581.741012.40.47660.648-0.7618.89.21.700.47661.01010.4081.76-0.345-1.29292.355250.290.1361158.80.2531.1549-13.2-0.110.094624.6764.845.761.27.70-0.043958.87.38-0.0470561.456.110.3595644.874.03-0.1302-28.19.230.0598-22.113.070.0242Seasonal snow246.50-0.39970.4061157.00-0.25190.2963272.750.25950.46897europe-fluxdata.euVan der Molen, M. K., Van Huissteden, J., Parmentier, F. J. W., Petrescu, A. M. R., Dolman, A. J., Maximov, T. C., ... & Suzdalov, D. A. (2007). The growing season greenhouse gas balance of a continental tundra site in the Indigirka lowlands, NE Siberia. web: hal.archives-ouvertes.frOpen-Shrubland(Desert)
Arctic_SEB_RU-Sam Data synthesis72.373800126.4958002002-01-015.6RU-SamFLUXNETWW2WW20.954587132032523W2GRAIGBPCarex aquatilis; Limprichtia revolvens; Meesia longeseta; Dryas octopetala; Hylocomnium splendens; Timmia austriacaFW|W220.18480.6931Docean/inland seasocean/inland seasocean/inland seasocean/inland seas81.54.810.951012.30.0991-0.9780.2075.65.70.510.18030.7994-0.108-6.120.2632.65410.019000.273.8730221.20.3431.2665-13.0-0.120.095324.8863.645.260.810.30-0.038158.18.81-0.0159590.051.060.2838659.965.68-0.0079-27.19.350.0427-22.212.520.0240Seasonal snow252.25-0.33910.4999158.000.12060.7106271.50-0.24890.41935europe-fluxdata.euBoike, J., Wille, C., & Abnizova, A. (2008). Climatology and summer energy and water balance of polygonal tundra in the Lena River Delta, Siberia. Journal of Geophysical Research: Biogeosciences, 113(G3). Web: agupubs.onlinelibrary.wiley.comTundra
Arctic_SEB_RU-Tks Data synthesis71.594270128.8878202010-01-01RU-TksFLUXNETGG3GG40.691297387118316G4GRAIGBPG4|SW|W230.72641.0986Docean/inland seasocean/inland seasocean/inland seasocean/inland seas79.03.761.1127.79.97.58.193.95260.60550.7810.26-0.067-8.77504.187750.211.0197261.60.317-0.9159-13.0-0.110.085621.1359.842.963.111.45-0.042461.110.39-0.0285570.840.73-0.0757654.357.90-0.2884-28.18.650.0324-22.112.780.0212Seasonal snow247.50-0.34080.4132153.50-0.10520.7057273.250.27420.35596europe-fluxdata.euKodama, Y., Sato, N., Yabuki, H., Ishii, Y., Nomura, M., & Ohata, T. (2007). Wind direction dependency of water and energy fluxes and synoptic conditions over a tundra near Tiksi, Siberia. Hydrological Processes: An International Journal, 21(15), 2028-2037. web: onlinelibrary.wiley.comGrassland
Arctic_SEB_RU-Vrk Data synthesis67.05468062.9404702008-01-0192.7RU-VrkFLUXNETSS2SS11.0S1CSHIGBPSalix sp.; Carex aquatilis; Betula nana L.; Eriophorum russeolum; Comarum palustre L.; Sphagnum sp.S110.00000.0000ESmfsporadicsporadic or isolated patchesmedium (10-20%)87.73.152.220.35550.4340.90191.992.01.410.47360.49290.2302.550.4701.32766.521000.212.9184341.90.2811.2882-4.9-0.320.057939.3853.838.866.84.15-0.039364.03.72-0.0274585.549.98-0.3110672.430.69-0.1875-24.16.81-0.0200-17.79.88-0.0074Seasonal snow231.50-0.07450.8763146.500.66120.0580284.500.62100.040414europe-fluxdata.euMarushchak, M. E., Friborg, T., Biasi, C., Herbst, M., Johansson, T., Kiepe, I., ... & Søgaard, H. (2016). Methane dynamics in the subarctic tundra: combining stable isotope analyses, plot-and ecosystem-scale flux measurements. Biogeosciences. web: helda.helsinki.fiOpen-Shrubland(Desert)
Arctic_SEB_Saddle Data synthesis65.999470-44.5001601998-01-012506.4SaddleGC-NetGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers0.06120.318993.15.420.23160.828-0.5602506.22506.21.090.24970.13610.7190.12-0.683-0.13742.091750.369.7278738.00.3669.8840-18.6-0.060.03950.0024.822.251.95.28-0.135046.88.60-0.0637487.627.520.1040538.647.180.1909-33.07.010.0440-30.08.330.0454Continuous snow365.000.000051Permanent-Snow
Arctic_SEB_SCO_L Data synthesis72.223000-26.8182002008-01-01519.2SCO_LPROMICEGLGLGLGL1.0GLiceown_descriptionGL1-0.00000.0000Glaciersglaciersglaciersglaciersglaciers67.22.62955.21.8269-0.8950.445515.1514.86.121.94730.3716-0.549-0.550.3821.78243.538000.617.2946202.00.6656.5538-12.6-0.080.06683.8233.327.661.19.370.014257.39.33-0.0021539.940.780.5251622.753.470.4379-28.84.380.0817-22.59.710.0766Continuous snow365.000.000060Grassland
Arctic_SEB_SCO_U Data synthesis72.393300-27.2333002008-01-011028.6SCO_UPROMICEGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers69.34.77895.40.6572-0.8080.5891028.51028.62.600.71660.3643-0.235-2.260.7950.23213.337000.626.3813197.00.6455.8081-15.4-0.060.06040.4332.427.158.311.96-0.071255.710.93-0.0961506.432.650.5434587.548.910.2416-31.44.860.0769-25.29.790.0670Continuous snow365.000.000061Permanent-Snow
Arctic_SEB_SE-St1 Data synthesis68.35415019.0503302012-01-01382.7SE-St1FLUXNETBPBBPBNNAr1.0NArWETIGBPEmpetrum hermaphroditum; Vaccinium vitis-idaea; Rubus chamaemorus; Carex rotundata; Eriophorum vaginatum; Eriophorum angustifolium; Sphagnum sp.; Betula nana; Betula pubescens ssp.NAr10.00000.0000<EDlrdiscontinuousdiscontinuouslow (>20%)0.01500.186183.44.151.57965.50.59090.576-0.817383.9383.11.980.67220.93480.01737.93-0.395-1.69670.556750.204.6449208.40.3120.58220.51.880.057246.9631.226.069.54.51-0.030866.95.28-0.0202565.744.56-0.4421656.932.47-0.0280-23.74.09-0.0445-16.77.83-0.0038Seasonal snow222.500.21440.7828150.000.52400.0890290.25-0.30550.553511europe-fluxdata.euweb: icos-sweden.seWoody-Savanna
Arctic_SEB_SJ-Adv Data synthesis78.18600015.9230002011-01-0144.3SJ-AdvFLUXNETGG1PP20.999999999999999P2WETIGBPSalix polaris; Eriophorum scheuchzeri; Carex subsp. athaceaP210.00000.0000CCmfcontinuouscontinuousmedium (10-20%)0.00950.091081.66.111.061011.51.03390.949-0.31543.042.53.060.69260.49710.4951.15-0.527-0.74357.110000.394.9897218.50.2820.7504-6.4-0.330.144313.4227.724.561.15.09-0.010656.66.90-0.0443627.832.700.8243672.316.340.4030-23.74.520.0584-20.57.220.0299Seasonal snow276.000.37760.5478163.50-0.72760.0885256.50-0.66770.13722europe-fluxdata.euPirk, N., Sievers, J., Mertes, J., Parmentier, F. J., Mastepanov, M., & Christensen, T. R. (2017). Spatial variability of CO2 uptake in polygonal tundra: assessing low-frequency disturbances in eddy covariance flux estimates. web: munin.uit.noTundra
Arctic_SEB_SJ-Blv Data synthesis78.92163011.8310901998-01-0153.4SJ-BlvFLUXNETPP1BB10.99726205017953B1SNOIGBPCarex spp.; Deschampsia spp.; Eriophorum spp.; Festuca spp.; Luzula spp.; Silene sp.; Saxifraga sp.; Salix sp.; Dryas octopetala; Oxyria digyna; Polygonum viviparumB1|P120.01890.6931Bglaciersglaciersglaciersglaciers0.02410.145479.63.380.991007.911.22.30110.340-0.94156.254.76.701.87990.7048-0.062-10.33-0.598-0.81779.985500.3311.8607429.10.2502.6479-5.3-0.310.10688.5717.418.576.83.370.093774.74.640.0905649.959.350.9646719.518.520.5076-21.53.450.0781-16.85.930.0423Seasonal snow288.75-1.33010.0227178.00-0.76780.0343257.500.98810.03031europe-fluxdata.euBoike, J., Roth, K., & Ippisch, O. (2003). Seasonal snow cover on frozen ground: Energy balance calculations of a permafrost site near Ny-Ålesund, Spitsbergen. Journal of Geophysical Research: Atmospheres, 108(D2), ALT-4 web: agupubs.onlinelibrary.wiley.com; Boike, J., Juszak, I., Lange, S., Chadburn, S., Burke, E., Paul Overduin, P., ... & Gouttevin, I. (2018). A 20-year record (1998-2017) of permafrost, active layer and meteorological conditions at a high Arctic permafrost research site (Bayelva, Spitsbergen). Earth System Science Data, 10(1), 355-390. web: duo.uio.noPermanent-Snow
Arctic_SEB_SouthDome Data synthesis63.148890-44.8171701998-01-012930.3South DomeGC-NetGLGLGLGL0.999999999999999GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers0.06820.358691.96.220.0491-0.568-0.8232930.22930.20.330.07900.2525-0.404-1.03-0.765-0.371102.714500.3718.10461102.50.37318.1129-19.0-0.060.04030.0022.720.757.02.18-0.141152.53.28-0.0707447.937.92-0.3836554.243.730.3998-34.64.79-0.0137-26.88.590.0459Continuous snow365.000.000052Permanent-Snow
Arctic_SEB_Summit Data synthesis72.579720-38.5045401998-01-013249.0SummitGC-NetGLGLGLGL1.0GLiceown_descriptionGL1-0.00000.0000Glaciersglaciersglaciersglaciersglaciers0.03190.161693.44.470.07680.184-0.9833248.93249.00.330.07650.21990.1980.89-0.963-0.05262.886250.283.7281262.90.2753.7281-27.5-0.040.04520.0031.226.450.512.910.005846.516.15-0.0227449.242.340.6409474.056.700.4051-38.08.870.0711-36.79.620.0584Continuous snow365.000.000055Permanent-Snow
Arctic_SEB_TAS_A Data synthesis65.779000-38.8995002013-01-01948.6TAS_APROMICEGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers83.25.39900.91.0238-0.0211.000946.6946.55.021.19060.1559-0.023-16.150.9270.082127.016500.3319.69041785.40.37818.1305-6.4-0.130.04951.5212.214.979.06.44-0.049476.28.83-0.0182559.273.95-0.2380682.715.890.4030-25.44.530.0090-16.75.990.0445Continuous snow365.000.000065Permanent-Snow
Arctic_SEB_TAS_L Data synthesis65.640200-38.8987002007-01-01311.9TAS_LPROMICEGLGLGLGL1.0GLiceown_descriptionGL1-0.00000.0000Glaciersglaciersglaciersglaciersglaciers80.13.28976.12.0923-0.9980.057307.4309.113.953.27730.2509-0.978-0.02-0.043-4.701738.127750.3215.2205935.00.3987.2097-2.4-0.400.057311.909.413.379.06.44-0.049476.28.83-0.0182559.273.95-0.2380682.715.890.4030-25.44.530.0090-16.75.990.0445Continuous snow365.000.000063Tundra
Arctic_SEB_TAS_U Data synthesis65.697800-38.8668002008-01-01617.3TAS_UPROMICEGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers82.63.52938.21.4679-0.9970.071615.8617.05.881.45170.3831-0.889-0.23-0.162-2.331935.279750.3317.02571350.30.38312.0071-4.3-0.210.05275.8110.513.979.06.44-0.049476.28.83-0.0182559.273.95-0.2380682.715.890.4030-25.44.530.0090-16.75.990.0445Continuous snow365.000.000064Permanent-Snow
Arctic_SEB_THU_L Data synthesis76.399800-68.2665002010-01-01580.3THU_LPROMICEGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers78.46.41940.23.76790.547-0.837576.6577.416.733.76570.22700.5970.24-0.780-0.15345.813500.467.0110228.50.4293.6190-14.2-0.080.01375.8443.733.953.614.24-0.031650.412.71-0.0750564.535.380.9919629.538.930.4622-29.25.080.0932-24.49.420.0472Continuous snow365.000.000080Permanent-Snow
Arctic_SEB_THU_U Data synthesis76.419700-68.1463002010-01-01777.6THU_UPROMICEGLGLGLGL1.0GLiceown_descriptionGL10.00000.0000Glaciersglaciersglaciersglaciersglaciers84.86.32916.13.73520.499-0.867773.5774.416.193.64960.09400.4730.14-0.878-0.04383.249500.467.8685264.20.4314.1212-14.8-0.080.00944.2543.133.553.614.24-0.031650.412.71-0.0750564.535.380.9919629.538.930.4622-29.25.080.0932-24.49.420.0472Continuous snow365.000.000081Permanent-Snow
Arctic_SEB_Tunu-N Data synthesis78.016770-33.9938701998-01-012112.2Tunu-NGC-NetGLGLGLGL1.0GLiceown_descriptionGL1-0.00000.0000Glaciersglaciersglaciersglaciersglaciers0.01520.092193.25.820.61170.984-0.1792112.02112.01.770.37070.34740.9800.02-0.157-0.77127.671000.493.0728127.70.4943.0727-25.3-0.040.04390.0038.330.837.08.770.000333.511.56-0.0675509.439.310.7510529.650.170.0201-33.18.860.1065-31.99.590.0560Continuous snow365.000.000056Permanent-Snow
Arctic_SEB_UPE_L Data synthesis72.893200-54.2955002009-01-01245.9UPE_LPROMICEGLGLGLGL1.0GLiceown_descriptionGL1-0.00000.0000Glaciersglaciersglaciersglaciersglaciers76.03.53982.81.35170.166-0.986238.0239.113.073.35110.5430-0.101-4.99-0.753-0.55490.145200.326.1083269.20.3763.5734-8.4-0.190.067515.1236.029.274.63.940.082372.05.830.0837601.567.191.2756694.522.770.9668-26.14.660.1197-19.68.410.0903Continuous snow365.000.000078Permanent-Snow
Arctic_SEB_UPE_U Data synthesis72.887800-53.5783002009-01-01972.9UPE_UPROMICEGLGLGLGL1.0GLiceown_descriptionGL1-0.00000.0000Glaciersglaciersglaciersglaciersglaciers78.35.85894.61.55360.371-0.929973.1974.36.781.58820.15280.3221.11-0.870-0.12488.555500.326.2765371.60.3304.0584-11.5-0.120.04972.3829.425.474.63.940.082372.05.830.0837601.567.191.2756694.522.770.9668-26.14.660.1197-19.68.410.0903Continuous snow365.000.000079Permanent-Snow
Arctic_SEB_US-A03 Data synthesis70.495328-149.8822972014-01-010.2US-A03AmerifluxWW1WW20.993630402517228W2BSVIGBPB1|W220.03860.6931CChfcontinuouscontinuoushigh (0-10%)33.75.131016.814.90.50.40.32199.626500.424.457880.50.4191.6867-10.3-0.140.087316.0044.233.868.85.04-0.124165.65.13-0.1794563.366.011.4041662.954.450.4663-25.85.680.1242-18.69.660.0492Seasonal snow248.50-0.45130.3751159.50-0.31820.3259272.000.22960.543023ameriflux.lbl.govRyan Sullivan rcsullivan@anl.gov - Argonne National LaboratoryTundra
Arctic_SEB_US-A10 Data synthesis71.324200-156.6149002011-01-013.2US-A10AmerifluxSS1GG30.624952004580749G3BSVIGBPG3|SW20.66160.6931CChfcontinuouscontinuoushigh (0-10%)49.15.241014.520.70.75080.2470.9692.92.71.370.46570.62660.0689.800.2892.37242.944750.415.1205104.90.4962.4966-10.2-0.140.096310.4737.530.075.24.63-0.024371.47.78-0.0921596.877.011.5139684.540.160.4531-24.05.530.1271-17.88.150.0442Seasonal snow253.00-0.71960.1654165.00-0.11100.7338275.500.40710.283624ameriflux.lbl.govarm.govTundra
Arctic_SEB_US-An1 Data synthesis68.990000-150.2800002008-01-01355.5US-An1AmerifluxGG4GG41.0G4OSHIGBPEriophorum spp.; Rubus chamaemorus L.; Ledum palustreG41-0.00000.0000ECmfcontinuouscontinuousmedium (10-20%)79.52.44969.22.88440.8310.556357.4355.810.762.28100.35060.5990.580.6400.51455.290250.5012.1815166.10.4443.6422-9.5-0.150.071031.5057.341.258.57.13-0.123154.87.73-0.1278558.836.070.1201641.850.39-0.0420-26.54.710.0333-20.39.490.0291Seasonal snow242.75-0.45110.3043150.00-0.30320.1688268.000.15520.698025ameriflux.lbl.govRocha, A. V., & Shaver, G. R. (2011). Burn severity influences postfire CO2 exchange in arctic tundra. Ecological Applications, 21(2), 477-489. web: esajournals.onlinelibrary.wiley.com; web: esajournals.onlinelibrary.wiley.comWoody-Savanna
Arctic_SEB_US-An2 Data synthesis68.950000-150.2100002008-01-01409.0US-An2AmerifluxGG4SS10.676470639902217S1OSHIGBPSphagnum spp.; Hylocomium spp.; Eriophorum spp.; Ledum palustre; Cavvinium vitis-idaea L.G4|S120.62950.6931ECmfcontinuouscontinuousmedium (10-20%)79.52.44963.30.88870.7000.714407.0407.15.081.33140.5488-0.020-30.890.7510.33488.846000.4912.9752178.80.4514.0092-9.4-0.150.068930.9756.540.758.57.13-0.123154.87.73-0.1278558.836.070.1201641.850.39-0.0420-26.54.710.0333-20.39.490.0291Seasonal snow239.75-0.74100.0785149.50-0.30780.1513268.000.43180.292026ameriflux.lbl.govRocha, A. V., & Shaver, G. R. (2011). Burn severity influences postfire CO2 exchange in arctic tundra. Ecological Applications, 21(2), 477-489. web: esajournals.onlinelibrary.wiley.com; web: esajournals.onlinelibrary.wiley.comWoody-Savanna
Arctic_SEB_US-An3 Data synthesis68.930000-150.2700002008-01-01431.0US-An3AmerifluxGG4SS10.714971743409079S1OSHIGBPSphagnum spp.; Hylocomium spp.; Eriophorum spp.; Rubus chamaemorus; Rhododendron tomentosum; Vaccinium macrocarpon; Betula nana L.G4|S120.59760.6931ECmfcontinuouscontinuousmedium (10-20%)77.82.64960.71.45971.0000.022431.3431.24.831.20810.18200.7810.390.4010.92503.093500.5013.3644185.00.4484.1740-9.4-0.150.068430.7756.240.558.57.13-0.123154.87.73-0.1278558.836.070.1201641.850.39-0.0420-26.54.710.0333-20.39.490.0291Seasonal snow247.00-0.49400.2493150.50-0.26300.2017268.000.28960.449227ameriflux.lbl.govRocha, A. V., & Shaver, G. R. (2011). Burn severity influences postfire CO2 exchange in arctic tundra. Ecological Applications, 21(2), 477-489. web: esajournals.onlinelibrary.wiley.com; web: esajournals.onlinelibrary.wiley.comWoody-Savanna
Arctic_SEB_US-Atq Data synthesis70.469600-157.4089001999-01-0122.4US-AtqAmeriflux--FLUXNETGG4GG40.560509384430247G4WETIGBPEriophorum vaginatum; Aulacomnion turgidum; Rubus chamaemorus; Carex bigelowii; E. angustifolium; E. russeolumFW|G4|W230.94601.0986DChfcontinuouscontinuoushigh (0-10%)0.00640.081982.73.750.851012.20.7537-0.696-0.71820.120.74.321.10140.7302-0.675-0.59-0.383-1.27289.968500.404.9791103.60.4901.8686-10.2-0.150.095024.3352.838.863.66.72-0.165260.46.76-0.1764576.355.251.1451659.260.680.6677-25.57.130.1008-19.510.160.0631Seasonal snow256.50-0.28630.4692162.50-0.15580.5530271.500.26230.394428ameriflux.lbl.govDavidson, S. J., Sloan, V. L., Phoenix, G. K., Wagner, R., Fisher, J. P., Oechel, W. C., & Zona, D. (2016). Vegetation type dominates the spatial variability in CH 4 emissions across multiple arctic tundra landscapes. Ecosystems, 19(6), 1116-1132. web: link.springer.com; web: daac.ornl.gov; Oechel, W. C., Laskowski, C. A., Burba, G., Gioli, B., & Kalhori, A. A. (2014). Annual patterns and budget of CO2 flux in an Arctic tussock tundra ecosystem. Journal of Geophysical Research: Biogeosciences, 119(3), 323-339. web: agupubs.onlinelibrary.wiley.com; Kwon, H. J., Oechel, W. C., Zulueta, R. C., & Hastings, S. J. (2006). Effects of climate variability on carbon sequestration among adjacent wet sedge tundra and moist tussock tundra ecosystems. Journal of Geophysical Research: Biogeosciences, 111(G3). web: agupubs.onlinelibrary.wiley.comTundra
Arctic_SEB_US-Brw Data synthesis71.322500-156.6091701998-01-015.6US-BrwAmerifluxWW1GG30.917207512758035G3WETIGBPCarex aquatilis; Eriophorum russeolum; Eriophorum angustifolium; Salix rotundifolia; Calliergon richardsonii; Cinclidium subrotundum; Peltigera sp.G3|SW20.28550.6931CChfcontinuouscontinuoushigh (0-10%)0.00600.075785.94.660.3854-0.759-0.6513.12.91.370.48800.5832-0.133-5.78-0.035-17.95277.924250.415.8580120.10.4962.8598-10.2-0.140.096110.6337.830.175.24.63-0.024371.47.78-0.0921596.877.011.5139684.540.160.4531-24.05.530.1271-17.88.150.0442Seasonal snow253.50-0.68870.1932165.00-0.11100.7338274.750.39200.332832ameriflux.lbl.govDavidson, S. J., Sloan, V. L., Phoenix, G. K., Wagner, R., Fisher, J. P., Oechel, W. C., & Zona, D. (2016). Vegetation type dominates the spatial variability in CH 4 emissions across multiple arctic tundra landscapes. Ecosystems, 19(6), 1116-1132. web: link.springer.com; web: daac.ornl.gov; Kwon, H. J., Oechel, W. C., Zulueta, R. C., & Hastings, S. J. (2006). Effects of climate variability on carbon sequestration among adjacent wet sedge tundra and moist tussock tundra ecosystems. Journal of Geophysical Research: Biogeosciences, 111(G3). web: agupubs.onlinelibrary.wiley.comTundra
Arctic_SEB_US-EML Data synthesis63.878400-149.2536002008-01-01684.7US-EMLAmerifluxGG4NNAr1.0NArOSHIGBPEriophorum vaginatum; Vaccinium uliginosum; Rubus chamaemorus; Betula nana; Ledum palustre; Sphagnum spp.; Dicranum spp.NAr10.00000.0000<EDlrdiscontinuousdiscontinuouslow (>20%)67.12.65931.824.31.2775-0.2620.965683.5683.16.221.92280.4256-0.016-41.660.6280.59639.688500.298.8355175.30.4041.0139-3.3-0.380.036248.3349.736.063.77.85-0.086260.48.92-0.0590510.061.27-0.8453627.732.67-0.0280-28.42.45-0.0679-19.07.580.0234Seasonal snow201.50-0.92550.2822119.75-0.66760.1896284.500.11690.829833ameriflux.lbl.govBelshe, E. F., Schuur, E. A. G., Bolker, B. M., & Bracho, R. (2012). Incorporating spatial heterogeneity created by permafrost thaw into a landscape carbon estimate. Journal of Geophysical Research: Biogeosciences, 117(G1). web: agupubs.onlinelibrary.wiley.comWoody-Savanna
Arctic_SEB_US-HVa Data synthesis69.142300-148.8412001994-01-01329.9US-HVaAmerifluxGG4GG41.0G4WETIGBPEriophorurn vaginaturn L.; Carex bigelowiiG410.00000.0000ECmfcontinuouscontinuousmedium (10-20%)0.10791.33352.763.11210.1900.982317.0316.111.453.82920.5127-0.219-3.610.2192.41429.318000.4810.4140148.60.4262.8309-10.0-0.150.074132.1659.942.756.26.09-0.123052.76.29-0.1383569.437.380.7421650.554.170.3947-25.65.310.0765-19.610.030.0500Seasonal snow238.25-0.61050.1650147.00-0.45260.0634268.000.14550.731235ameriflux.lbl.govOechel, W. C., Vourlitis, G. L., Brooks, S., Crawford, T. L., & Dumas, E. (1998). Intercomparison among chamber, tower, and aircraft net CO2 and energy fluxes measured during the Arctic System Science Land-Atmosphere-Ice Interactions (ARCSS-LAII) Flux Study. Journal of Geophysical Research: Atmospheres, 103(D22), 28993-29003. web: agupubs.onlinelibrary.wiley.comWoody-Savanna
Arctic_SEB_US-ICh Data synthesis68.606803-149.2958442007-01-01956.2US-IChAmeriflux--AON_2PP2SS11.0S1HeathTundraown_descriptionDryas spp.S110.00000.0000EClrcontinuouscontinuouslow (>20%)0.01140.158672.02.481.74895.72.16970.7830.622946.1948.912.833.56540.57410.4951.550.3320.73587.892750.4613.9361220.60.4564.8780-10.0-0.110.050324.3950.737.357.88.40-0.091653.69.01-0.1065555.442.190.3320634.137.920.0451-26.14.000.0378-19.89.080.0249Seasonal snow249.500.31970.5181146.00-0.24480.4049263.25-0.54640.167190ameriflux.lbl.govEuskirchen, E. S., Bret-Harte, M. S., Scott, G. J., Edgar, C., & Shaver, G. R. (2012). Seasonal patterns of carbon dioxide and water fluxes in three representative tundra ecosystems in northern Alaska. Ecosphere, 3(1), 1-19. web: esajournals.onlinelibrary.wiley.com; web: aon.iab.uaf.eduWoody-Savanna
Arctic_SEB_US-ICs Data synthesis68.605825-149.3110102007-01-01904.8US-ICsAmeriflux--AON_2WW2SS11.0S1WetSedgeTundraown_descriptionEriophorum angustifolium; Betula nana; Salix spp.S110.00000.0000EClrcontinuouscontinuouslow (>20%)0.01270.176372.72.331.62902.01.16680.6930.721912.0908.812.073.34570.65760.5721.230.3250.83555.227500.4613.1792203.30.4484.4335-9.7-0.120.051526.0651.437.757.88.40-0.091653.69.01-0.1065555.442.190.3320634.137.920.0451-26.14.000.0378-19.89.080.0249Seasonal snow246.75-0.20080.7008143.50-0.33570.1910262.000.22610.605192ameriflux.lbl.govEuskirchen, E. S., Bret-Harte, M. S., Scott, G. J., Edgar, C., & Shaver, G. R. (2012). Seasonal patterns of carbon dioxide and water fluxes in three representative tundra ecosystems in northern Alaska. Ecosphere, 3(1), 1-19. web: esajournals.onlinelibrary.wiley.com; web: aon.iab.uaf.eduWoody-Savanna
Arctic_SEB_US-ICt Data synthesis68.606260-149.3040592007-01-01925.5US-ICtAmeriflux--AON_2GG4SS11.0S1TussockTundraown_descriptionEriophorum vaginatum; Sphagnum spp.; Betula nana; Salix spp.S11-0.00000.0000EClrcontinuouscontinuouslow (>20%)0.02120.247469.72.622.13899.86.64120.9970.076927.9924.919.393.76260.57790.6201.070.3380.74587.892700.4613.9360220.60.4564.8780-10.0-0.110.050324.3950.737.357.88.40-0.091653.69.01-0.1065555.442.190.3320634.137.920.0451-26.14.000.0378-19.89.080.0249Seasonal snow246.75-0.20080.7008143.50-0.33570.1910262.000.22610.605191ameriflux.lbl.govEuskirchen, E. S., Bret-Harte, M. S., Scott, G. J., Edgar, C., & Shaver, G. R. (2012). Seasonal patterns of carbon dioxide and water fluxes in three representative tundra ecosystems in northern Alaska. Ecosphere, 3(1), 1-19. web: esajournals.onlinelibrary.wiley.com; web: aon.iab.uaf.eduWoody-Savanna
Arctic_SEB_US-Ivo Data synthesis68.486500-155.7503002003-01-01565.0US-IvoAmeriflux--FLUXNETGG4GG41.0G4WETIGBPEriophorum vaginatum; Sphagnum spp.; Rubus chamaemorus; Drepanocladus sp.; Carex aquatilis; Salix pulchra; Betula nanaG410.00000.0000EClrcontinuouscontinuouslow (>20%)0.01510.185377.62.761.35945.233.10.8638-0.7690.640561.5562.06.061.54870.3139-0.818-0.300.2132.23549.909250.3610.9302210.70.3623.2160-10.0-0.140.070627.5954.839.767.55.37-0.127965.35.50-0.1208536.739.880.1049626.950.950.2239-27.36.120.0215-20.39.910.0407Seasonal snow250.00-0.91890.0567147.00-0.69810.0036267.250.32720.342039ameriflux.lbl.govDavidson, S. J., Sloan, V. L., Phoenix, G. K., Wagner, R., Fisher, J. P., Oechel, W. C., & Zona, D. (2016). Vegetation type dominates the spatial variability in CH 4 emissions across multiple arctic tundra landscapes. Ecosystems, 19(6), 1116-1132. web: link.springer.com; web: daac.ornl.govWoody-Savanna
Arctic_SEB_US-NGB Data synthesis71.280044-156.6091812012-01-012.6US-NGBAmerifluxWW2GG31.0G3SNOIGBPCarex aquatilis; Eriophorum spp.; Luzula spp.; Sphagnum spp.; Drepanocladus spp.G310.00000.0000CChfcontinuouscontinuoushigh (0-10%)86.94.811014.40.0297-0.9670.2532.12.20.440.12750.8852-0.276-2.29-0.184-3.81275.298500.415.7640117.90.5022.9124-10.3-0.140.096711.8739.331.075.24.63-0.024371.47.78-0.0921596.877.011.5139684.540.160.4531-24.05.530.1271-17.88.150.0442Seasonal snow251.00-0.96760.0603161.50-0.08830.7814268.000.79640.041540ameriflux.lbl.govRaz-Yaseef, N., Young-Robertson, J., Rahn, T., Sloan, V., Newman, B., Wilson, C., ... & Torn, M. S. (2017). Evapotranspiration across plant types and geomorphological units in polygonal Arctic tundra. Journal of Hydrology, 553, 816-825. web: sciencedirect.com; Davidson, S. J., Sloan, V. L., Phoenix, G. K., Wagner, R., Fisher, J. P., Oechel, W. C., & Zona, D. (2016). Vegetation type dominates the spatial variability in CH 4 emissions across multiple arctic tundra landscapes. Ecosystems, 19(6), 1116-1132. web: link.springer.com; web: daac.ornl.govTundra
Arctic_SEB_US-Upa Data synthesis70.281470-148.8848301994-01-0110.4US-UpaAmerifluxWW3WW20.969751501847393W2WETIGBPCarex aquatilis; Eriophorurn scheuchzeri; C. bigelowii; E. vaginaturn L.B1|W220.13560.6931DChfcontinuouscontinuoushigh (0-10%)1.610.2545-0.6140.79010.110.50.790.16110.8393-0.347-1.730.5610.81252.835000.445.6672100.70.4201.8834-10.4-0.140.087320.6349.736.968.85.04-0.124165.65.13-0.1794563.366.011.4041662.954.450.4663-25.85.680.1242-18.69.660.0492Seasonal snow248.00-0.67790.0926158.00-0.20910.4457272.000.59360.069544ameriflux.lbl.govOechel, W. C., Vourlitis, G. L., Brooks, S., Crawford, T. L., & Dumas, E. (1998). Intercomparison among chamber, tower, and aircraft net CO2 and energy fluxes measured during the Arctic System Science Land-Atmosphere-Ice Interactions (ARCSS-LAII) Flux Study. Journal of Geophysical Research: Atmospheres, 103(D22), 28993-29003. web: agupubs.onlinelibrary.wiley.comTundra
Arctic_SEB_US-xHE Data synthesis63.875690-149.2133402017-01-01691.0US-xHEAmerifluxSS2NNAr1.0NArOSHIGBPBetula glandulosa; Betula nana; Picea glauca; Ledum palustreNAr1-0.00000.0000<EDlrdiscontinuousdiscontinuouslow (>20%)0.03210.435966.53.07929.32.01.5314-0.7290.685691.0691.910.122.39210.3042-0.573-0.770.6330.43657.413750.309.0121182.30.4021.0293-3.4-0.370.035647.2849.335.863.77.85-0.086260.48.92-0.0590510.061.27-0.8453627.732.67-0.0280-28.42.45-0.0679-19.07.580.0234Seasonal snow206.50-0.92310.2843121.25-0.53070.2876284.500.18050.741846ameriflux.lbl.govweb: neonscience.orgWoody-Savanna
Arctic_SEB_US-xTL Data synthesis68.661090-149.3704702017-01-01832.7US-xTLAmerifluxGG4GG31.0G3WETIGBPEriophorum vaginatum; Vaccinium vitis-idaea; Betula glandulosaG310.00000.0000ECmfcontinuouscontinuousmedium (10-20%)0.03010.242867.83.56913.15.01.07310.5420.840823.2826.410.463.59850.45020.1815.090.1322.37542.738000.4613.1503198.70.4474.3956-9.7-0.120.053626.7052.438.357.88.40-0.091653.69.01-0.1065555.442.190.3320634.137.920.0451-26.14.000.0378-19.89.080.0249Seasonal snow248.250.10090.8515145.00-0.23900.3611263.50-0.19430.665647ameriflux.lbl.govweb: neonscience.orgWoody-Savanna