The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

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Permafrost, which covers 15 million km 2 of the land surface, is one of the components of the Earth system that is most sensitive to warming 1,2 . Loss of permafrost would radically change high-latitude hydrology and biogeochemical cycling, and could therefore provide very significant feedbacks on climate change [3][4][5][6][7][8] . The latest climate models all predict warming of high-latitude soils and thus thawing of permafrost under future climate change, but with widely varying magnitudes of permafrost thaw 9,10 . Here we show that in each of the models, their present-day spatial distribution of permafrost and air temperature can be used to infer the sensitivity of permafrost to future global warming. Using the same approach for the observed permafrost distribution and air temperature, we estimate a sensitivity of permafrost area loss to global mean warming at stabilization of 4.0 +1.0 −1.1 million km 2 • C −1 (1σ confidence), which is around 20% higher than previous studies 9 . Our method facilitates an assessment for COP21 climate change targets 11 : if the climate is stabilized at 2 • C above pre-industrial levels, we estimate that the permafrost area would eventually be reduced by over 40%. Stabilizing at 1.5 • C rather than 2 • C would save approximately 2 million km 2 of permafrost.Permafrost, defined as ground that remains at or below 0 • C for two or more consecutive years, underlies 24% of the land in the Northern Hemisphere 12 . Under recent climate warming, permafrost has begun to thaw, causing changes in ecosystems and impacting northern communities, for example through collapse of roads and buildings as the ground becomes unstable 13 . Large quantities of carbon are stored in organic matter in permafrost soils 14 , which starts to decompose when the permafrost thaws, resulting in the emission of greenhouse gases such as carbon dioxide and methane. In the future, carbon release from permafrost thaw may have a significant impact on the Earth's climate 6 . Due to its global importance, numerous modelling studies have assessed the rate of permafrost thaw under future climate warming 9,10,15,16 . However, despite progress in process-based modelling on local and regional scales, for example, ref. 17, a lack of data availability and model limitations mean that permafrost is still poorly simulated in global climate models, where the historical simulations show a present-day permafrost area anywhere between 0.1 and 1.8 times the size of that observed 9 . Models often have shallow soil columns, a limited representation of soil properties, inadequate snow thermal and physical dynamics and other missing processes 9 . Here we present a projection of large-scale permafrost thaw that is based on observations, avoiding model bias, and accounting for observational uncertainty.Our approach is based on using the relationship between mean annual air temperature (MAAT) and permafrost occurrence

Degradation of near-surface permafrost can pose a serious threat to the utilization of natural resources, and to the sustainable development of Arctic communities. Here we identify at unprecedentedly high spatial resolution infrastructure hazard areas in the Northern Hemisphere’s permafrost regions under projected climatic changes and quantify fundamental engineering structures at risk by 2050. We show that nearly four million people and 70% of current infrastructure in the permafrost domain are in areas with high potential for thaw of near-surface permafrost. Our results demonstrate that one-third of pan-Arctic infrastructure and 45% of the hydrocarbon extraction fields in the Russian Arctic are in regions where thaw-related ground instability can cause severe damage to the built environment. Alarmingly, these figures are not reduced substantially even if the climate change targets of the Paris Agreement are reached.

Abstract. Samoylov Island is centrally located within the Lena River Delta at 72° N, 126° E and lies within the Siberian zone of continuous permafrost. The landscape on Samoylov Island consists mainly of late Holocene river terraces with polygonal tundra, ponds and lakes, and an active floodplain. The island has been the focus of numerous multidisciplinary studies since 1993, which have focused on climate, land cover, ecology, hydrology, permafrost and limnology. This paper aims to provide a framework for future studies by describing the characteristics of the island's meteorological parameters (temperature, radiation and snow cover), soil temperature, and soil moisture. The land surface characteristics have been described using high resolution aerial images in combination with data from ground-based observations. Of note is that deeper permafrost temperatures have increased between 0.3 to 1.3 °C over the last five years. However, no clear warming of air and active layer temperatures is detected since 1998, though winter air temperatures during recent years have not been as cold as in earlier years. Data related to this article are archived under: http://doi. pangaea.de/10.1594/PANGAEA.806233 .