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Abstract Climate change affects Indian agriculture, which depends heavily on the spatiotemporal distribution of monsoon rainfall. Despite the nonlinear relationship between crop yield and rainfall, little is known about the optimal rainfall threshold, particularly for monsoon rice. Here, we investigate the responses of rice yield to monsoon rainfall in India by analyzing historical rice production statistics and climate data from 1990 to 2017. Results show that excessive and deficit rainfall reduces rice yield by 33.7% and 19%, respectively. The overall optimal rainfall threshold nationwide is 1621 ± 34 mm beyond which rice yield declines by 6.4 kg per hectare per 100 mm of rainfall, while the identifiable thresholds vary spatially across 14 states. The temporal variations in rice yield are influenced by rainfall anomalies featured by El Niño-Southern Oscillation events.

Abstract Changes are projected for the boreal biome with complex and variable effects on forest vegetation including drought‐induced tree mortality and forest loss. With soil and atmospheric conditions governing drought intensity, specific drivers of trees water stress can be difficult to disentangle across temporal scales. We used wavelet analysis and causality detection to identify potential environmental controls (evapotranspiration, soil moisture, rainfall, vapor pressure deficit, air temperature and photosynthetically active radiation) on daily tree water deficit and on longer periods of tree dehydration in black spruce and tamarack. Daily tree water deficit was controlled by photosynthetically active radiation, vapor pressure deficit, and air temperature, causing greater stand evapotranspiration. Prolonged periods of tree water deficit (multi‐day) were regulated by photosynthetically active radiation and soil moisture. We provide empirical evidence that continued warming and drying will cause short‐term increases in black spruce and tamarack transpiration, but greater drought stress with reduced soil water availability.

Abstract Wetlands are responsible for 20%–31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data‐driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom‐up estimates of wetland CH4 emissions. Here, we develop a six‐predictor random forest upscaling model (UpCH4), trained on 119 site‐years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET‐CH4 Community Product. Network patterns in site‐level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash‐Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH4 emissions of 146 ± 43 TgCH4 y−1 for 2001–2018 which agrees closely with current bottom‐up land surface models (102–181 TgCH4 y−1) and overlaps with top‐down atmospheric inversion models (155–200 TgCH4 y−1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH4 fluxes has the potential to produce realistic extra‐tropical wetland CH4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid‐to‐arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ORNLDAAC/2253).

An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations.

Abstract At the edge of alpine and Arctic ecosystems all over the world, a transition zone exists beyond which it is either infeasible or unfavorable for trees to exist, colloquially identified as the treeline. We explore the possibility of a thermodynamic basis behind this demarcation in vegetation by considering ecosystems as open systems driven by thermodynamic advantage—defined by vegetation’s ability to dissipate heat from the earth’s surface to the air above the canopy. To deduce whether forests would be more thermodynamically advantageous than existing ecosystems beyond treelines, we construct and examine counterfactual scenarios in which trees exist beyond a treeline instead of the existing alpine meadow or Arctic tundra. Meteorological data from the Italian Alps, United States Rocky Mountains, and Western Canadian Taiga-Tundra are used as forcing for model computation of ecosystem work and temperature gradients at sites on both sides of each treeline with and without trees. Model results indicate that the alpine sites do not support trees beyond the treeline, as their presence would result in excessive CO $$_2$$ 2 loss and extended periods of snowpack due to temperature inversions (i.e., positive temperature gradient from the earth surface to the atmosphere). Further, both Arctic and alpine sites exhibit negative work resulting in positive feedback between vegetation heat dissipation and temperature gradient, thereby extending the duration of temperature inversions. These conditions demonstrate thermodynamic infeasibility associated with the counterfactual scenario of trees existing beyond a treeline. Thus, we conclude that, in addition to resource constraints, a treeline is an outcome of an ecosystem’s ability to self-organize towards the most advantageous vegetation structure facilitated by thermodynamic feasibility.

Abstract Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO2 sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO2 sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO2 later in the season.

Future warming of the Arctic not only threatens to destabilize the enormous pool of organic carbon accumulated in permafrost soils but may also mobilize elements such as calcium (Ca) or silicon (Si). While for Greenlandic soils, it was recently shown that both elements may have a strong effect on carbon dioxide (CO2) production with Ca strongly decreasing and Si increasing CO2 production, little is known about the effects of Si and Ca on carbon cycle processes in soils from Siberia, the Canadian Shield, or Alaska. In this study, we incubated five different soils (rich organic soil from the Canadian Shield and from Siberia (one from the top and one from the deeper soil layer) and one acidic and one non-acidic soil from Alaska) for 6 months under both drained and waterlogged conditions and at different Ca and amorphous Si (ASi) concentrations. Our results show a strong decrease in soil CO2 production for all soils under both drained and waterlogged conditions with increasing Ca concentrations. The ASi effect was not clear across the different soils used, with soil CO2 production increasing, decreasing, or not being significantly affected depending on the soil type and if the soils were initially drained or waterlogged. We found no methane production in any of the soils regardless of treatment. Taking into account the predicted change in Si and Ca availability under a future warmer Arctic climate, the associated fertilization effects would imply potentially lower greenhouse gas production from Siberia and slightly increased greenhouse gas emissions from the Canadian Shield. Including Ca as a controlling factor for Arctic soil CO2 production rates may, therefore, reduces uncertainties in modeling future scenarios on how Arctic regions may respond to climate change.

Wetland methane emissions contribute to global warming, and are oversimplified in climate models. Here the authors use eddy covariance measurements from 48 global sites to demonstrate seasonal hysteresis in methane-temperature relationships and suggest the importance of microbial processes.

Adapting to climate change as a consequence of increasing greenhouse gas (GHG) emissions is of paramount importance in the near future. Therefore, recognition of spatial and temporal variations of atmospheric carbon dioxide (CO2) concentration both globally and regionally is critical. The goal of this study was to analyze spatio-temporal patterns of atmospheric CO2 concentration (XCO2) for Iran over the period from 2003 to 2020 to shed light on the role of various biotic and abiotic controls. First, by using atmospheric XCO2 data obtained from the SCIAMACHY and GOSAT satellite instruments, a series of spatio-temporal XCO2 distribution maps were developed. Second, to understand of the potential causes underlying the spatio-temporal distributions in XCO2, the correlations between monthly XCO2 and vegetation abundance, air temperature, precipitation, and fossil fuel CO2 emissions were examined. The spatio-temporal patterns in XCO2 indicated an increasing gradient of XCO2 from north to south and from west to east in Iran, with the highest XCO2 in the central, southern and southeastern parts of the country. The findings revealed that XCO2 was negatively correlated with vegetation abundance and precipitation, and positively correlated with air temperature in different months from 2003 to 2020. Among the different explanatory variables, vegetation abundance explained most of the spatial variation in XCO2. Furthermore, in spring (April and May), which has the highest amount of vegetation abundance and precipitation, biotic controls had a substantial impact on the diffusion and absorption of XCO2 in the northern and northwestern parts of Iran. Our results suggest that CO2 is moved from the center of Iran to the outer parts of the country in summer (July–September) and vice-versa in winter (January–March). Our findings provide policy- and decision makers with crucial information regarding the spatio-temporal dynamics in XCO2 to reduce and, ultimately, halt its increase.

Northwestern Canada is currently warming nearly four times faster than the global average, driving accelerated permafrost thaw and changes to ecosystem vegetation, hydrology and landscape structure across the landscape. While permafrost peatlands constitute a large carbon reservoir, there is no consensus yet on the direction and magnitude of changes to their vulnerable carbon balance. Here, we assessed changes in peatland ecosystems following permafrost thaw at three sites located along a 1000 km long climate and permafrost gradient along the Mackenzie River valley, Canada. Specifically, we examined vegetation succession over the last few decades to evaluate the possible impact of climate warming on peat and carbon accumulation. Results from the palaeoecological analysis of 20 surficial peat cores, supported by robust chronologies, show a return to Sphagnum accumulation since ca. 1980 CE in the sporadic and discontinuous permafrost zones and ca . 2000 CE in the continuous permafrost zone. The average rates of peat and carbon accumulation reached 4 mm yr ^−1 and 134 g C m ^−2 yr ^−1 at the northernmost site in the continuous permafrost zone. In contrast, peat and carbon accumulation reached 3 mm yr ^−1 and 81 g C m ^−2 yr ^−1 , respectively, in the sporadic and discontinuous permafrost zones. This study highlights the need for a net carbon budget that integrates the recent accelerated Sphagnum growth and carbon uptake from the atmosphere to better assess the potential carbon emissions offset following permafrost thaw. High-resolution palaeoecological studies can offer insights into decadal-scale patterns of vegetation and carbon balance changes to improve model predictions of peat climate-carbon cycle feedbacks.

Climate change is rapidly altering composition, structure, and functioning of the boreal biome, across North America often broadly categorized into ecoregions. The resulting complex changes in different ecoregions present a challenge for efforts to accurately simulate carbon dioxide (CO _2 ) and energy exchanges between boreal forests and the atmosphere with terrestrial ecosystem models (TEMs). Eddy covariance measurements provide valuable information for evaluating the performance of TEMs and guiding their development. Here, we compiled a boreal forest model benchmarking dataset for North America by harmonizing eddy covariance and supporting measurements from eight black spruce ( Picea mariana )-dominated, mature forest stands. The eight forest stands, located in six boreal ecoregions of North America, differ in stand characteristics, disturbance history, climate, permafrost conditions and soil properties. By compiling various data streams, the benchmarking dataset comprises data to parameterize, force, and evaluate TEMs. Specifically, it includes half-hourly, gap-filled meteorological forcing data, ancillary data essential for model parameterization, and half-hourly, gap-filled or partitioned component flux data on CO _2 (net ecosystem production, gross primary production [GPP], and ecosystem respiration [ER]) and energy (latent [LE] and sensible heat [H]) and their daily aggregates screened based on half-hourly gap-filling quality criteria. We present a case study with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) to: (1) demonstrate the utility of our dataset to benchmark TEMs and (2) provide guidance for model development and refinement. Model skill was evaluated using several statistical metrics and further examined through the flux responses to their environmental controls. Our results suggest that CLASSIC tended to overestimate GPP and ER among all stands. Model performance regarding the energy fluxes (i.e., LE and H) varied greatly among the stands and exhibited a moderate correlation with latitude. We identified strong relationships between simulated fluxes and their environmental controls except for H, thus highlighting current strengths and limitations of CLASSIC.

Arctic-boreal regions are experiencing major anthropogenic disturbances in addition to intensifying natural disturbance regimes as a consequence of climate change. Oil and natural gas (OG) activities are extensive in the Arctic-boreal region of western North America, a large portion of which is underlain by permafrost. The total number and distribution of OG wells and their potential fate remain unclear. Consequently, the collective impacts of OG wells on natural and cultural resources, human health and emissions of methane (CH _4 ), are poorly understood. Using public OG well databases, we analysed the distribution of OG wells drilled between 1984 and 2018 across the Core Domain of the NASA Arctic-Boreal Vulnerability Experiment (‘ABoVE domain’). We identified 242 007 OG wells drilled as of 2018 in the ABoVE domain, of which almost two thirds are now inactive or abandoned OG wells. We found that annual drilling has increased from 269 to 8599 OG wells from 1984 to 2014 with around 1000, 700 and 1800 OG wells drilled annually in evergreen forest, deciduous forest and herbaceous land cover types, respectively. 65 588 OG well sites were underlain by permafrost in 2012. Fugitive CH _4 emissions from active and abandoned OG wells drilled in the Canadian portion of the ABoVE domain accounted for approximately 13% of the total anthropogenic CH _4 emissions in Canada in 2018. Our analysis identified OG wells as an anthropogenic disturbance in the ABoVE domain with potentially non-negligible consequences to local populations, ecosystems, and the climate system.

The overall spatial and temporal influence of shrub expansion on permafrost is largely unknown due to uncertainty in estimating the magnitude of many counteracting processes. For example, shrubs shade the ground during the snow-free season, which can reduce active layer thickness. At the same time, shrubs advance the timing of snowmelt when they protrude through the snow surface, thereby exposing the active layer to thawing earlier in spring. Here, we compare 3056 in situ frost table depth measurements split between mineral earth hummocks and organic inter-hummock zones across four dominant shrub–tundra vegetation types. Snow-free date, snow depth, hummock development, topography, and vegetation cover were compared to frost table depth measurements using a structural equation modeling approach that quantifies the direct and combined interacting influence of these variables. Areas of birch shrubs became snow free earlier regardless of snow depth or hillslope aspect because they protruded through the snow surface, leading to deeper hummock frost table depths. Projected increases in shrub height and extent combined with projected decreases in snowfall would lead to increased shrub protrusion across the Arctic, potentially deepening the active layer in areas where shrub protrusion advances the snow-free date.

Ecosystems in the North American Arctic-Boreal Zone (ABZ) experience a diverse set of disturbances associated with wildfire, permafrost dynamics, geomorphic processes, insect outbreaks and pathogens, extreme weather events, and human activity. Climate warming in the ABZ is occurring at over twice the rate of the global average, and as a result the extent, frequency, and severity of these disturbances are increasing rapidly. Disturbances in the ABZ span a wide gradient of spatiotemporal scales and have varying impacts on ecosystem properties and function. However, many ABZ disturbances are relatively understudied and have different sensitivities to climate and trajectories of recovery, resulting in considerable uncertainty in the impacts of climate warming and human land use on ABZ vegetation dynamics and in the interactions between disturbance types. Here we review the current knowledge of ABZ disturbances and their precursors, ecosystem impacts, temporal frequencies, spatial extents, and severity. We also summarize current knowledge of interactions and feedbacks among ABZ disturbances and characterize typical trajectories of vegetation loss and recovery in response to ecosystem disturbance using satellite time-series. We conclude with a summary of critical data and knowledge gaps and identify priorities for future study.

Photosynthesis of terrestrial ecosystems in the Arctic-Boreal region is a critical part of the global carbon cycle. Solar-induced chlorophyll Fluorescence (SIF), a promising proxy for photosynthesis with physiological insight, has been used to track gross primary production (GPP) at regional scales. Recent studies have constructed empirical relationships between SIF and eddy covariance-derived GPP as a first step to predicting global GPP. However, high latitudes pose two specific challenges: (a) Unique plant species and land cover types in the Arctic–Boreal region are not included in the generalized SIF-GPP relationship from lower latitudes, and (b) the complex terrain and sub-pixel land cover further complicate the interpretation of the SIF-GPP relationship. In this study, we focused on the Arctic-Boreal vulnerability experiment (ABoVE) domain and evaluated the empirical relationships between SIF for high latitudes from the TROPOspheric Monitoring Instrument (TROPOMI) and a state-of-the-art machine learning GPP product (FluxCom). For the first time, we report the regression slope, linear correlation coefficient, and the goodness of the fit of SIF-GPP relationships for Arctic-Boreal land cover types with extensive spatial coverage. We found several potential issues specific to the Arctic-Boreal region that should be considered: (a) unrealistically high FluxCom GPP due to the presence of snow and water at the subpixel scale; (b) changing biomass distribution and SIF-GPP relationship along elevational gradients, and (c) limited perspective and misrepresentation of heterogeneous land cover across spatial resolutions. Taken together, our results will help improve the estimation of GPP using SIF in terrestrial biosphere models and cope with model-data uncertainties in the Arctic-Boreal region.

Foundation species have disproportionately large impacts on ecosystem structure and function. As a result, future changes to their distribution may be important determinants of ecosystem carbon (C) cycling in a warmer world. We assessed the role of a foundation tussock sedge ( Eriophorum vaginatum ) as a climatically vulnerable C stock using field data, a machine learning ecological niche model, and an ensemble of terrestrial biosphere models (TBMs). Field data indicated that tussock density has decreased by ∼0.97 tussocks per m ^2 over the past ∼38 years on Alaska’s North Slope from ∼1981 to 2019. This declining trend is concerning because tussocks are a large Arctic C stock, which enhances soil organic layer C stocks by 6.9% on average and represents 745 Tg C across our study area. By 2100, we project that changes in tussock density may decrease the tussock C stock by 41% in regions where tussocks are currently abundant (e.g. −0.8 tussocks per m ^2 and −85 Tg C on the North Slope) and may increase the tussock C stock by 46% in regions where tussocks are currently scarce (e.g. +0.9 tussocks per m ^2 and +81 Tg C on Victoria Island). These climate-induced changes to the tussock C stock were comparable to, but sometimes opposite in sign, to vegetation C stock changes predicted by an ensemble of TBMs. Our results illustrate the important role of tussocks as a foundation species in determining future Arctic C stocks and highlight the need for better representation of this species in TBMs.

Soil respiration (i.e. from soils and roots) provides one of the largest global fluxes of carbon dioxide (CO _2 ) to the atmosphere and is likely to increase with warming, yet the magnitude of soil respiration from rapidly thawing Arctic-boreal regions is not well understood. To address this knowledge gap, we first compiled a new CO _2 flux database for permafrost-affected tundra and boreal ecosystems in Alaska and Northwest Canada. We then used the CO _2 database, multi-sensor satellite imagery, and random forest models to assess the regional magnitude of soil respiration. The flux database includes a new Soil Respiration Station network of chamber-based fluxes, and fluxes from eddy covariance towers. Our site-level data, spanning September 2016 to August 2017, revealed that the largest soil respiration emissions occurred during the summer (June–August) and that summer fluxes were higher in boreal sites (1.87 ± 0.67 g CO _2 –C m ^−2 d ^−1 ) relative to tundra (0.94 ± 0.4 g CO _2 –C m ^−2 d ^−1 ). We also observed considerable emissions (boreal: 0.24 ± 0.2 g CO _2 –C m ^−2 d ^−1 ; tundra: 0.18 ± 0.16 g CO _2 –C m ^−2 d ^−1 ) from soils during the winter (November–March) despite frozen surface conditions. Our model estimates indicated an annual region-wide loss from soil respiration of 591 ± 120 Tg CO _2 –C during the 2016–2017 period. Summer months contributed to 58% of the regional soil respiration, winter months contributed to 15%, and the shoulder months contributed to 27%. In total, soil respiration offset 54% of annual gross primary productivity (GPP) across the study domain. We also found that in tundra environments, transitional tundra/boreal ecotones, and in landscapes recently affected by fire, soil respiration often exceeded GPP, resulting in a net annual source of CO _2 to the atmosphere. As this region continues to warm, soil respiration may increasingly offset GPP, further amplifying global climate change.

Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests—the dominant boreal forest type—and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a ∼20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 °C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (∼45°N) and decrease toward the northern limit of the boreal biome (∼70°N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining.

Soils are warming as air temperatures rise across the Arctic and Boreal region concurrent with the expansion of tall-statured shrubs and trees in the tundra. Changes in vegetation structure and function are expected to alter soil thermal regimes, thereby modifying climate feedbacks related to permafrost thaw and carbon cycling. However, current understanding of vegetation impacts on soil temperature is limited to local or regional scales and lacks the generality necessary to predict soil warming and permafrost stability on a pan-Arctic scale. Here we synthesize shallow soil and air temperature observations with broad spatial and temporal coverage collected across 106 sites representing nine different vegetation types in the permafrost region. We showed ecosystems with tall-statured shrubs and trees (>40 cm) have warmer shallow soils than those with short-statured tundra vegetation when normalized to a constant air temperature. In tree and tall shrub vegetation types, cooler temperatures in the warm season do not lead to cooler mean annual soil temperature indicating that ground thermal regimes in the cold-season rather than the warm-season are most critical for predicting soil warming in ecosystems underlain by permafrost. Our results suggest that the expansion of tall shrubs and trees into tundra regions can amplify shallow soil warming, and could increase the potential for increased seasonal thaw depth and increase soil carbon cycling rates and lead to increased carbon dioxide loss and further permafrost thaw.

NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses. We compiled feedback from ecosystem modeling teams on key data needs, which encompass carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance dynamics. A suite of variables was identified as part of this activity with a critical requirement that they are collected concurrently and representatively over space and time. Individual projects in ABoVE may not capture all these needs, and thus there is both demand and opportunity for the augmentation of field observations, and synthesis of the observations that are collected, to ensure that science questions and integrated modeling activities are successfully implemented.

Passive microwave measurements from space are known to be sensitive to the freeze/thaw (F/T) state of the land surface. These measurements are at a coarse spatial resolution (~15–50 km) and the spatial variability of the microwave emissions within a pixel can have important effects on the interpretation of the signal. An L-band ground-based microwave radiometer campaign was conducted in the Canadian Prairies during winter 2014–2015 to examine the spatial variability of surface emissions during frozen and thawed periods. Seven different sites within the Kenaston soil monitoring network were sampled five times between October 2014 and April 2015 with a mobile ground-based L-band radiometer system at approximately monthly intervals. The radiometer measurements showed that in a seemingly homogenous prairie landscape, the spatial variability of brightness temperature (TB) is non-negligible during both frozen and unfrozen soil conditions. Under frozen soil conditions, TB was negatively correlated with soil permittivity (εG). This correlation was related to soil moisture conditions before the main freezing event, showing that the soil ice volumetric content at least partly affects TB. However, because of the effect of snow on L-Band emission, the correlation between TB and εG decreased with snow accumulation. When compared to satellite measurements, the average TB of the seven plots were well correlated with the Soil Moisture Ocean Salinity (SMOS) TB with a root mean square difference of 8.1 K and consistent representation of the strong F/T signal (i.e., TB increases and decreases when soil freezing and thawing, respectively). This study allows better quantitative understanding of the spatial variability in L-Band emissions related to landscape F/T, and will help the calibration and validation of satellite-based F/T retrieval algorithms.

About a fifth of the global wetland methane emissions originate from boreal peatlands, which represent an important land cover type in boreal landscapes in the sporadic permafrost zone. There, rising air temperatures could lead to warmer spring and longer growing seasons, changing landscape methane emissions. To quantify the effect of warmer spring conditions on methane emissions of a boreal peat landscape in the sporadic permafrost zone of northwestern Canada, we analyzed four years (2013–2016) of methane fluxes measured with the eddy covariance technique and long-term (1951–2016) meteorological observations from a nearby climate station. In May, after snowmelt was complete, mean air temperatures were more than 2 °C warmer in 2013, 2015, and 2016 than in 2014. Mean growing season (May–August) air temperatures, in contrast, differed by less than 1 °C over the four years. Warmer May air temperatures caused earlier wetland soil warming, with temperatures rising from ~0 °C to >12 °C 25 to 40 days earlier and leading to ~6 °C warmer mean soil temperatures between May and June. However, from July to August, soil temperatures were similar among years. Mean May to August and annual methane emissions (6.4 g CH _4 m ^−2 and 9.4 g CH _4 m ^−2 , respectively) of years with warmer spring (i.e. May) temperatures exceeded emissions during the cooler year by 20%–30% (4.5 g CH _4 m ^−2 and 7.2 g CH _4 m ^−2 , respectively). Among years with warmer springs, growing season methane emissions varied little (±0.5 g CH _4 m ^−2 ). The observed interannual differences are most likely caused by a strong soil temperature control on methane fluxes and large soil temperature differences during the spring. Thus, in a warming climate, methane emissions from waterlogged boreal peat landscapes at the southern limit of permafrost are likely to increase in response to more frequent occurrences of warm springs.