Climate change is leading to a disproportionately large warming in the high northern latitudes, but the magnitude and sign of the future carbon balance of the Arctic are highly uncertain. Using 40 terrestrial biosphere models for Alaska, we 5 provide a baseline of terrestrial carbon cycle structural and parametric uncertainty, defined as the multi-model standard deviation () against the mean (x) for each quantity. Mean annual uncertainty (/x) was largest for net ecosystem exchange (NEE) (−0.01±0.19 kgCm−2 yr−1), then net primary production (NPP) (0.14± 0.33 kgCm−2 yr−1), autotrophic respiration (Ra) (0.09±0.20 kgCm−2 yr−1), gross pri10 mary production (GPP) (0.22±0.50 kgCm−2 yr−1), ecosystem respiration (Re) (0.23± 0.38 kgCm−2 yr−1), CH4 flux (2.52±4.02 gCH4m−2 yr−1), heterotrophic respiration (Rh) (0.14±0.20 kgCm−2 yr−1), and soil carbon (14.0±9.2 kgCm−2). The spatial patterns in regional carbon stocks and fluxes varied widely with some models showing NEE for Alaska as a strong carbon sink, others as a strong carbon source, while still others as 15 carbon neutral. Additionally, a feedback (i.e., sensitivity) analysis was conducted of 20th century NEE to CO2 fertilization () and climate ( ), which showed that uncertainty in was 2x larger than that of , with neither indicating that the Alaskan Arctic is shifting towards a certain net carbon sink or source. Finally, AmeriFlux data are used at two sites in the Alaskan Arctic to evaluate the regional patterns; observed seasonal NEE 20 was captured within multi-model uncertainty. This assessment of carbon cycle uncertainties may be used as a baseline for the improvement of experimental and modeling activities, as well as a reference for future trajectories in carbon cycling with climate change in the Alaskan Arctic

Abstract. Climate change is leading to a disproportionately large warming in the high northern latitudes, but the magnitude and sign of the future carbon balance of the Arctic are highly uncertain. Using 40 terrestrial biosphere models for Alaska, we provide a baseline of terrestrial carbon cycle structural and parametric uncertainty, defined as the multi-model standard deviation (σ) against the mean (x) for each quantity. Mean annual uncertainty (σ/x) was largest for net ecosystem exchange (NEE) (−0.01± 0.19 kg C m−2 yr−1), then net primary production (NPP) (0.14 ± 0.33 kg C m−2 yr−1), autotrophic respiration (Ra) (0.09 ± 0.20 kg C m−2 yr−1), gross primary production (GPP) (0.22 ± 0.50 kg C m−2 yr−1), ecosystem respiration (Re) (0.23 ± 0.38 kg C m−2 yr−1), CH4 flux (2.52 ± 4.02 g CH4 m−2 yr−1), heterotrophic respiration (Rh) (0.14 ± 0.20 kg C m−2 yr−1), and soil carbon (14.0± 9.2 kg C m−2). The spatial patterns in regional carbon stocks and fluxes varied widely with some models showing NEE for Alaska as a strong carbon sink, others as a strong carbon source, while still others as carbon neutral. Additionally, a feedback (i.e., sensitivity) analysis was conducted of 20th century NEE to CO2 fertilization (β) and climate (γ), which showed that uncertainty in γ was 2x larger than that of β, with neither indicating that the Alaskan Arctic is shifting towards a certain net carbon sink or source. Finally, AmeriFlux data are used at two sites in the Alaskan Arctic to evaluate the regional patterns; observed seasonal NEE was captured within multi-model uncertainty. This assessment of carbon cycle uncertainties may be used as a baseline for the improvement of experimental and modeling activities, as well as a reference for future trajectories in carbon cycling with climate change in the Alaskan Arctic.

The African humid tropical biome constitutes the second largest rainforest region, significantly impacts global carbon cycling and climate, and has undergone major changes in functioning owing to climate and land-use change over the past century. We assess changes and trends in CO2 fluxes from 1901 to 2010 using nine land surface models forced with common driving data, and depict the inter-model variability as the uncertainty in fluxes. The biome is estimated to be a natural (no disturbance) net carbon sink (−0.02 kg C m−2 yr−1 or −0.04 Pg C yr−1, p < 0.05) with increasing strength fourfold in the second half of the century. The models were in close agreement on net CO2 flux at the beginning of the century (σ1901 = 0.02 kg C m−2 yr−1), but diverged exponentially throughout the century (σ2010 = 0.03 kg C m−2 yr−1). The increasing uncertainty is due to differences in sensitivity to increasing atmospheric CO2, but not increasing water stress, despite a decrease in precipitation and increase in air temperature. However, the largest uncertainties were associated with the most extreme drought events of the century. These results highlight the need to constrain modelled CO2 fluxes with increasing atmospheric CO2 concentrations and extreme climatic events, as the uncertainties will only amplify in the next century.

ABSTRACT. Oil-dependent indigenous communities in remote regions of Alaska and elsewhere are facing an unprecedented crisis. With the cost of fuel and transport skyrocketing, energy costs are crippling local economies, leading to increasing outmigration and concern for their very existence in the future. What can be done to address this energy crisis, and promote energy security, sustainability and resilience in rural forest communities? We examine the potential of developing a sustainable biomass-energy industry in Southeast Alaska, home to nearly 16,000 Alaska Natives in a dozen rural and two urban communities within the United States' largest national forest: The Tongass. Although the potential for biomass energy has long been touted, realization of the opportunity has been catalyzed only recently as part of a model of sustainable development being enacted by the region's largest Native corporation, Sealaska, and its subsidiary, Haa Aaní ("Our Land") L.L.C. In this paper we examine the unique nature of Alaska Native corporations and their potential as engines of sustainable development, particularly through Sealaska's emerging cultural model of sustainability in relation to social-ecological well-being. We assess the economic, ecological, and atmospheric emissions parameters of a wood-biomass energy industry at various scales according to the "triple bottom line" of sustainability. Finally, we address what additional policy and support measures may be necessary to nurture the successful transition to biomass energy at a sustainable scale to support rural indigenous communities, a more resilient, renewable energy system, and a lower carbon footprint.

Reliable and fine resolution estimates of surface net-radiation are required for estimating latent and sensible heat fluxes between the land surface and the atmosphere. However, currently, fine resolution estimates of net-radiation are not available and consequently it is challenging to develop multi-year estimates of evapotranspiration at scales that can capture land surface heterogeneity and are relevant for policy and decision-making. We developed and evaluated a global net-radiation product at 5 km and 8-day resolution by combining mutually consistent atmosphere and land data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra. Comparison with net-radiation measurements from 154 globally distributed sites (414 site-years) from the FLUXNET and Surface Radiation budget network (SURFRAD) showed that the net-radiation product agreed well with measurements across seasons and climate types in the extratropics (Wilmott's index ranged from 0.74 for boreal to 0.63 for Mediterranean sites). Mean absolute deviation between the MODIS and measured net-radiation ranged from 38.0 ± 1.8 W·m −2 in boreal to 72.0 ± 4.1 W·m −2 in the tropical climates. The mean bias was small and constituted only 11%, 0.7%, 8.4%, 4.2%, 13.3%, and 5.4% of the mean absolute error in daytime net-radiation in boreal, Mediterranean, temperate-continental, temperate, semi-arid, and tropical climate, respectively. To assess the accuracy of the broader spatiotemporal patterns, we upscaled error-quantified MODIS net-radiation and compared it with the net-radiation estimates from the coarse spatial (1 • × 1 • ) but high temporal resolution gridded net-radiation product from the Clouds and Earth's Radiant Energy System (CERES). Our estimates agreed closely with the net-radiation estimates from the CERES. Difference between the two was less than 10 W·m −2 in 94% of the total land area. MODIS net-radiation product will be a valuable resource for the science community studying turbulent fluxes and energy budget at the Earth's surface.

&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; The land surface provides a boundary condition to atmospheric forward and flux inversion models. These models require prior estimates of CO&lt;sub&gt;2&lt;/sub&gt; fluxes at relatively high temporal resolutions (e.g., 3-hourly) because of the high frequency of atmospheric mixing and wind heterogeneity. However, land surface model CO&lt;sub&gt;2&lt;/sub&gt; fluxes are often provided at monthly time steps, typically because the land surface modeling community focuses more on time steps associated with plant phenology (e.g., seasonal) than on sub-daily phenomena. Here, we describe a new dataset created from 15 global land surface models and 4 ensemble products in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), temporally downscaled from monthly to 3-hourly output. We provide 3-hourly output for each individual model over 7 years (2004&amp;#8211;2010), as well as an ensemble mean, a weighted ensemble mean, and the multi-model standard deviation. Output is provided in three different spatial resolutions for user preferences: 0.5&amp;#176; &amp;#215; 0.5&amp;#176;, 2.0&amp;#176; &amp;#215; 2.5&amp;#176;, and 4.0&amp;#176; x 5.0&amp;#176; (latitude/longitude). These data are publicly available from: . &lt;a href=&quot; ftp://daac.ornl.gov/data/cms/CMS_NEE_CO2_Fluxes_TBMO/data&quot;target=&quot;_blank&quot;&gt;ftp://daac.ornl.gov/data/cms/CMS_NEE_CO2_Fluxes_TBMO/data&lt;/a&gt; .&lt;/p&gt;

Abstract. The land surface provides a boundary condition to atmospheric forward and flux inversion models. These models require prior estimates of CO2 fluxes at relatively high temporal resolutions (e.g., 3-hourly) because of the high frequency of atmospheric mixing and wind heterogeneity. However, land surface model CO2 fluxes are often provided at monthly time steps, typically because the land surface modeling community focuses more on time steps associated with plant phenology (e.g., seasonal) than on sub-daily phenomena. Here, we describe a new dataset created from 15 global land surface models and 4 ensemble products in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), temporally downscaled from monthly to 3-hourly output. We provide 3-hourly output for each individual model over 7 years (2004–2010), as well as an ensemble mean, a weighted ensemble mean, and the multi-model standard deviation. Output is provided in three different spatial resolutions for user preferences: 0.5°  ×  0.5°, 2.0°  ×  2.5°, and 4.0°  ×  5.0° (latitude  ×  longitude). These data are publicly available from doi:10.3334/ORNLDAAC/1315.

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