• Energy Research

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). 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 comprises harmonized, standardized and aggregated in-situ observations of surface energy budget components measured at 64 sites on vegetated and glaciated sites north of 60° latitude, in the time period from 1994 till 2021. The surface energy budget components include net radiation, sensible heat flux, latent heat flux, ground heat flux, net shortwave radiation, net longwave radiation, surface temperature and albedo, which were aggregated to daily mean, minimum and maximum values from hourly and half-hourly measurements. Data were retrieved from the monitoring networks FLUXNET, AmeriFlux, AON, GC-Net and PROMICE.

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. Therefore, we here provide four datasets comprising:1. Harmonized, standardized and aggregated in situ observations of SEB components at 64 vegetated and glaciated sites north of 60° latitude, in the time period 1994-20212. A description of all study sites and associated environmental conditions, including the vegetation types, which correspond to the classification of the Circumpolar Arctic Vegetation Map (CAVM, Raynolds et al. 2019).3. Data generated in a literature synthesis from 358 study sites on vegetation or glacier (>=60°N latitude) covered by 148 publications.4. Metadata, including data contributor information and measurement heights of variables associated with Oehri et al. 2022. Code underlying the dataset and publication is available in a Github repository and can be accessed at: https://github.com/oehrij/ArcticSEBSynthesis

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). 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 contains metadata information about surface energy budget components measured at 64 tundra and glacier sites >60° N across the Arctic. This information was taken from the open-access repositories FLUXNET, Ameriflux, AON, GC-Net and PROMICE. The contained datasets are associated with the publication vegetation type as an important predictor of the Arctic Summer Land Surface Energy Budget by Oehri et al. 2022, and intended to support research of surface energy budgets and their relationship with environmental conditions, in particular vegetation characteristics across the terrestrial Arctic.

AbstractThe regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.

AbstractDespite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.

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). 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.

AbstractLong‐term atmospheric CO2 concentration records have suggested a reduction in the positive effect of warming on high‐latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long‐term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength. In this study, we used a record of nearly 100 site‐years of eddy covariance data from 11 continuous permafrost tundra sites distributed across the circumpolar Arctic to test the temperature (expressed as growing degree days, GDD) responses of gross primary production (GPP), net ecosystem exchange (NEE), and ecosystem respiration (ER) at different periods of the summer (early, peak, and late summer) including dominant tundra vegetation classes (graminoids and mosses, and shrubs). We further tested GPP, NEE, and ER relationships with soil moisture and vapor pressure deficit to identify potential moisture limitations on plant productivity and net carbon exchange. Our results show a decrease in GPP with rising GDD during the peak summer (July) for both vegetation classes, and a significant relationship between the peak summer GPP and soil moisture after statistically controlling for GDD in a partial correlation analysis. These results suggest that tundra ecosystems might not benefit from increased temperature as much as suggested by several terrestrial biosphere models, if decreased soil moisture limits the peak summer plant productivity, reducing the ability of these ecosystems to sequester carbon during the summer.