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The FLUXNET2015 dataset provides ecosystem-scale data on CO2, 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.

Knowledge of soil moisture conditions is important for modeling soil temperatures, as soil moisture influences the thermal dynamics in multiple ways. However, in permafrost regions, soil moisture is highly heterogeneous and difficult to model. Satellite soil moisture data may fill this gap, but the degree to which they can improve permafrost modeling is unknown. To explore their added value for modeling soil temperatures, we assimilate fine‐scale satellite surface soil moisture into the CryoGrid‐3 permafrost model, which accounts for the soil moisture's influence on the soil thermal properties and the surface energy balance. At our study site in the Canadian Arctic, the assimilation improves the estimates of deeper (>10 cm) soil temperatures during summer but not consistently those of the near‐surface temperatures. The improvements in the deeper temperatures are strongly contingent on soil type: They are largest for porous organic soils (30%), smaller for thin organic soil covers (20%), and they essentially vanish for mineral soils (only synthetic data available). That the improvements are greatest over organic soils reflects the strong coupling between soil moisture and deeper temperatures. The coupling arises largely from the diminishing soil thermal conductivity with increasing desiccation thanks to which the deeper soil is kept cool. It is this association of dry organic soils being cool at depth that lets the assimilation revise the simulated soil temperatures toward the actually measured ones. In the future, the increasing availability of satellite soil moisture data holds promise for the operational monitoring of soil temperatures, hydrology, and biogeochemistry.

We conducted eddy covariance measurements from April to August 2014 on a Siberian thermokarst lake. The study site is located in the Lena River Delta and characterized as a floating ice lake. Heat fluxes differed in magnitudes, directions and temporal patterns depending on the lake surface conditions (“frozen” ice cover, ice cover melt, and open water). Significant heat release during frozen ice cover conditions highlighted the importance of lakes for the landscape heat budget and water balance. The energy balance was nearly closed during the open water period and highlighted the impact of melting energy on its closure during the ice cover period. Sensible and latent heat dynamics were driven by temperature and water vapor gradients scaled by wind speed, respectively. We calculated bulk aerodynamics transfer coefficients and evaluated the performance of the derived in situ and three independent heat flux parameterization schemes. We found that bulk transfer models perform moderately to poorly for the different lake surface conditions. During the open water period small‐scale temporal variability could not be represented by the models, particularly in case of latent heat flux. The model results were less sensitive to the specific model type than to the accuracy of the surface water temperature measurement, which is dependent on a well‐thought‐out measurement design. Our study stresses considerations that are crucial for similar campaigns in the future, in order to face the measurement challenges encountered on arctic lakes especially during the ice cover period.

Thawing of permafrost in a warming climate is governed by a complex interplay of different processes of which only conductive heat transfer is taken into account in most model studies. However, observations in many permafrost landscapes demonstrate that lateral and vertical movement of water can have a pronounced influence on the thaw trajectories, creating distinct landforms, such as thermokarst ponds and lakes, even in areas where permafrost is otherwise thermally stable. Novel process parameterizations are required to include such phenomena in future projections of permafrost thaw and subsequent climatic-triggered feedbacks. In this study, we present a new land-surface scheme designed for permafrost applications, CryoGrid 3, which constitutes a flexible platform to explore new parameterizations for a range of permafrost processes. We document the model physics and employed parameterizations for the basis module CryoGrid 3, and compare model results with in situ observations of surface energy balance, surface temperatures, and ground thermal regime from the Samoylov permafrost observatory in NE Siberia. The comparison suggests that CryoGrid 3 can not only model the evolution of the ground thermal regime in the last decade, but also consistently reproduce the chain of energy transfer processes from the atmosphere to the ground. In addition, we demonstrate a simple 1-D parameterization for thaw processes in permafrost areas rich in ground ice, which can phenomenologically reproduce both formation of thermokarst ponds and subsidence of the ground following thawing of ice-rich subsurface layers. Long-term simulation from 1901 to 2100 driven by reanalysis data and climate model output demonstrate that the hydrological regime can both accelerate and delay permafrost thawing. If meltwater from thawed ice-rich layers can drain, the ground subsides, as well as the formation of a talik, are delayed. If the meltwater pools at the surface, a pond is formed that enhances heat

Freshwaters are an important component of the continental greenhouse gas (GHG) balance with emissions estimated to correspond to about 80 % of the land GHG sink [Bastviken et al., 2011]. Thaw lakes in permafrost landscapes and especially in Yedoma permafrost are considered to be strong processors of organic carbon and essential emitters of CH4 [Walter et al., 2006]. As the Arctic experiences the recent global warming at a much faster rate than other regions of the world [AMAP, 2015], the importance of thaw lakes in the global GHG budget is expected to rapidly increase due to progressive permafrost degradation. However, especially arctic lakes are highly underrepresented in observational studies on lakeatmosphere GHG exchange. Only a few short-term studies exist, with a majority missing the ice break-up. This event is assumed to result in a spring emission peak that contributes considerably to the annual GHG emissions. In consequence, arctic freshwaters are not adequately represented in modelling approaches and scenarios of climate change. Using a floating eddy covariance (EC) system, we investigate ecosystem CH4 and CO2 flux dynamics between the atmosphere and a Yedoma thaw lake in the Lena River Delta in northern Siberia. The compiled dataset covers the ice break-up and most of the ice-free period 2014. We chose the EC method as it allows direct, automatic and non-intrusive flux measurements in remote areas. The investigated lake is one of > 500 lakes on Kurungnakh Island in the Lena River Delta. The study site lies within the zone of continuous permafrost and belongs to the arctic tundra zone. The lake covers an area of approximately 1.25 km2 with a mean depth of eight meters. We will present first results of this study and discuss the importance of a spring emission peak during ice break-up in the annual GHG budge

The focus of this research has been on detecting changes in lake areas, vegetation, land surface temperatures, and the area covered by snow, using data from remote sensing. The study area covers the main (central) part of the Lena River catchment in the Yakutia region of Siberia (Russia), extending from east of Yakutsk to the central Siberian Plateau, and from the southern Lena River to north of the Vilyui River. Approximately 90% of the area is underlain by continuous permafrost. Remote sensing products were used to analyze changes in water bodies, land surface temperature (LST), and leaf area index (LAI), as well as the occurrence and extent of forest fires, and the area and duration of snow cover. The remote sensing analyses (for LST, snow cover, LAI, and fire) were based on MODIS–derived NASA products (250–1000 m) for 2000 to 2011. Changes in water bodies were calculated from two mosaics of (USGS) Landsat (30 m) satellite images from 2002 and 2009. Within the study area's 315,000 km2 the total area covered by lakes increased by 17.9% between 2002 and 2009, but this increase varied in different parts of the study area, ranging between 11% and 42%.The land surface temperatures showed a consistent warming trend, with an average increase of about 0.12 °C/year. The average rate of warming during the April–May transition period was 0.17 °C/year and 0.19 °C/year in the September–October period, but ranged up to 0.49 °C/year during September–October. Regional differences in the rates of land surface temperature change, and possible reasons for the temperature changes, are discussed with respect to changes in the land cover.Our analysis of a broad spectrum of variables over the study area suggests that the spring warming trend is very likely to be due to changes in the area covered by snow. The warming trend observed in fall does not, however, appear to be directly related to any changes in the area of snow c

Modeling soil thermal dynamics at high latitudes and altitudes requires representations of physical processes such as snow insulation, soil freezing and thawing and subsurface conditions like soil water/ice content and soil texture. We have compared six different land models: JSBACH, ORCHIDEE, JULES, COUP, HYBRID8 and LPJ-GUESS, at four different sites with distinct cold region landscape types, to identify the importance of physical processes in capturing observed temperature dynamics in soils. The sites include alpine, high Arctic, wet polygonal tundra and non-permafrost Arctic, thus showing how a range of models can represent distinct soil temperature regimes. For all sites, snow insulation is of major importance for estimating topsoil conditions. However, soil physics is essential for the subsoil temperature dynamics and thus the active layer thicknesses. This analysis shows that land models need more realistic surface processes, such as detailed snow dynamics and moss cover with changing thickness and wetness, along with better representations of subsoil thermal dynamics.

Thermokarst lakes are typical features of the northern permafrost ecosystems, and play an important role in the thermal exchange between atmosphere and subsurface. The objective of this study is to describe the main thermal processes of the lakes and to quantify the heat exchange with the underlying sediments. The thermal regimes of five lakes located within the continuous permafrost zone of northern Siberia (Lena River Delta) were investigated using hourly water temperature and water level records covering a 3-year period (2009–2012), together with bathymetric survey data. The lakes included thermokarst lakes located on Holocene river terraces that may be connected to Lena River water during spring flooding, and a thermokarst lake located on deposits of the Pleistocene Ice Complex. Lakes were covered by ice up to 2 m thick that persisted for more than 7 months of the year, from October until about mid-June. Lake-bottom temperatures increased at the start of the ice-covered period due to upward-directed heat flux from the underlying thawed sediment. Prior to ice break-up, solar radiation effectively warmed the water beneath the ice cover and induced convective mixing. Ice break-up started at the beginning of June and lasted until the middle or end of June. Mixing occurred within the entire water column from the start of ice break-up and continued during the ice-free periods, as confirmed by the Wedderburn numbers, a quantitative measure of the balance between wind mixing and stratification that is important for describing the biogeochemical cycles of lakes. The lake thermal regime was modeled numerically using the FLake model. The model demonstrated good agreement with observations with regard to the mean lake temperature, with a good reproduction of the summer stratification during the ice-free period, but poor agreement during the ice-covered period. Modeled sensitivity to lake depth demonstrated that lakes in this climatic zone with mean depths > 5 m develop cont

Modeling soil thermal dynamics at high latitudes and altitudes requires representations of physical processes such as snow insulation, soil freezing and thawing and subsurface conditions like soil water/ice content and soil texture. We have compared six different land models: JSBACH, ORCHIDEE, JULES, COUP, HYBRID8 and LPJ-GUESS, at four different sites with distinct cold region landscape types, to identify the importance of physical processes in capturing observed temperature dynamics in soils. The sites include alpine, high Arctic, wet polygonal tundra and non-permafrost Arctic, thus showing how a range of models can represent distinct soil temperature regimes. For all sites, snow insulation is of major importance for estimating topsoil conditions. However, soil physics is essential for the subsoil temperature dynamics and thus the active layer thicknesses. This analysis shows that land models need more realistic surface processes, such as detailed snow dynamics and moss cover with changing thickness and wetness, along with better representations of subsoil thermal dynamics.

There is a large amount of organic carbon stored in permafrost in the northern high latitudes, which may become vulnerable to microbial decomposition under future climate warming. In order to estimate this potential carbon–climate feedback it is necessary to correctly simulate the physical dynamics of permafrost within global Earth system models (ESMs) and to determine the rate at which it will thaw. Additional new processes within JULES, the land-surface scheme of the UK ESM (UKESM), include a representation of organic soils, moss and bedrock and a modification to the snow scheme; the sensitivity of permafrost to these new developments is investigated in this study. The impact of a higher vertical soil resolution and deeper soil column is also considered. Evaluation against a large group of sites shows the annual cycle of soil temperatures is approximately 25 % too large in the standard JULES version, but this error is corrected by the model improvements, in particular by deeper soil, organic soils, moss and the modified snow scheme. A comparison with active layer monitoring sites shows that the active layer is on average just over 1 m too deep in the standard model version, and this bias is reduced by 70 cm in the improved version. Increasing the soil vertical resolution allows the full range of active layer depths to be simulated; by contrast, with a poorly resolved soil at least 50 % of the permafrost area has a maximum thaw depth at the centre of the bottom soil layer. Thus all the model modifications are seen to improve the permafrost simulations. Historical permafrost area corresponds fairly well to observations in all simulations, covering an area between 14 and 19 million km2. Simulations under two future climate scenarios show a reduced sensitivity of permafrost degradation to temperature, with the near-surface permafrost loss per degree of warming reduced from 1.5 million km2 °C−1 in the standard version of JULES to between 1.1 and 1.2 million km2 °C−1 in

High-latitude soils store vast amounts of perennially frozen and therefore inert organic matter. With rising global temperatures and consequent permafrost degradation, a part of this carbon stock will become available for microbial decay and eventual release to the atmosphere. We have developed a simplified, two-dimensional multi-pool model to estimate the strength and timing of future carbon dioxide (CO2) and methane (CH4) fluxes from newly thawed permafrost carbon (i.e. carbon thawed when temperatures rise above pre-industrial levels). We have especially simulated carbon release from deep deposits in Yedoma regions by describing abrupt thaw under newly formed thermokarst lakes. The computational efficiency of our model allowed us to run large, multi-centennial ensembles under various scenarios of future warming to express uncertainty inherent to simulations of the permafrost carbon feedback. Under moderate warming of the representative concentration pathway (RCP) 2.6 scenario, cumulated CO2 fluxes from newly thawed permafrost carbon amount to 20 to 58 petagrams of carbon (Pg-C) (68% range) by the year 2100 and reach 40 to 98 Pg-C in 2300. The much larger permafrost degradation under strong warming (RCP8.5) results in cumulated CO2 release of 42 to 141 Pg-C and 157 to 313 Pg-C (68% ranges) in the years 2100 and 2300, respectively. Our estimates only consider fluxes from newly thawed permafrost, not from soils already part of the seasonally thawed active layer under pre-industrial climate. Our simulated CH4 fluxes contribute a few percent to total permafrost carbon release yet they can cause up to 40% of total permafrost-affected radiative forcing in the 21st century (upper 68% range). We infer largest CH4 emission rates of about 50 Tg-CH4 per year around the middle of the 21st century when simulated thermokarst lake extent is at its maximum and when abrupt thaw under thermokarst lakes is taken into account. CH4 release from newly thawed carbon in wetland

The Lena River forms one of the largest deltas in the Arctic. We compare two sets of data to reveal new insights into the hydrological, hydrochemical, and geochemical processes within the delta: (i) long-term hydrometric observations at the Khabarova station at the head of the delta from 1951 to 2005; (ii) field hydrological and geochemical observations carried out within the delta since 2002. Periods with differing relative discharge and intensity of fluvial processes were identified from the long-term record of water and sediment discharge. Ice events during spring melt (high water) reconfigured branch channels and probably influenced sediment transport within the delta. Based on summer field measurements during 2005–2012 of discharge and sediment fluxes along main delta channels, both are increased between the apex and the front of the delta. This increase is to a great extent connected with an additional influx of water from tributaries, as well as an increase of suspended and dissolved material released from the ice complex. Summer concentrations of major ion and biogenic substances along the delta branches are partly explained by water sources within the delta, such as thawing ice complex waters, small Lena River branches and estuarine areas.

Lakes and ponds play a key role in the carbon cycle of permafrost ecosystems, where they are considered to be hotspots of carbon dioxide CO2 and methane CH4 emission. The strength of these emissions is, however, controlled by a variety of physical and biogeochemical processes whose responses to a warming climate are complex and only poorly understood. Small waterbodies have been attracting an increasing amount of attention since recent studies demonstrated that ponds can make a significant contribution to the CO2 and CH4emissions of tundra ecosystems. Waterbodies also have a marked effect on the thermal state of the surrounding permafrost; during the freezing period they prolong the period of time during which thawed soil material is available for microbial decomposition.

This study presents net CH4 production rates during the freezing period from ponds within a typical lowland tundra landscape in northern Siberia. Rate estimations were based on CH4 concentrations measured in surface lake ice from a variety of waterbody types. Vertical profiles along ice blocks showed an exponential increase in CH4 concentration with depth. These CH4 profiles were reproduced by a 1-D mass balance model and the net CH4 production rates were then inferred through inverse modeling.

Results revealed marked differences in early winter net CH4 production am

In permafrost environments exposed to strong winds, drifting snow can create a small-scale pattern of strongly variable snow heights, which has profound implications for the thermal regime of the ground. Arrays of 26 to more than 100 temperature loggers were installed to record the distribution of ground surface temperatures within three study areas across a climatic gradient from continuous to sporadic permafrost in Norway. A variability of the mean annual ground surface temperature of up to 6°C was documented within areas of 0.5 km2. The observed variation can, to a large degree, be explained by variation in snow height. Permafrost models, employing averages of snow height for grid cells of, e.g., 1 km2, are not capable of representing such sub-grid variability. We propose a statistical representation of the sub-grid variability of ground surface temperatures and demonstrate that a simple equilibrium permafrost model can reproduce the temperature distribution within a grid cell based on the distribution of snow heights.