Corrigendum to "Cajander larch (<i>Larix cajanderi</i>) biomass distribution, fire regime and post-fire recovery in northeastern Siberia" published in Biogeosciences, 9, 3943&minus;3959, 2012

No abstract available

Brief communication: Identification of tundra topsoil frozen/thawed state from SMAP and GCOM-W1 radiometer measurements using the spectral gradient method

From 2015 to 2020, using the spectral gradient radiometric method, the possibility of the frozen/thawed (FT) state identification of tundra soil was investigated based on Soil Moisture Active Passive (SMAP) and Global Change Observation Mission – Water Satellite 1 (GCOM-W1) satellite observations of 10 test sites located in the Arctic regions of Canada, Finland, Russia, and the USA. It is shown that the spectral gradients of brightness temperature and reflectivity (measured in the frequency range from 1.4 to 36.5 GHz with horizontal polarization, a determination coefficient from 0.775 to 0.834, a root-mean-square error from 6.6 to 10.7 d and a bias from −3.4 to +6.5 d) make it possible to identify the FT state of the tundra topsoil. The spectral gradient method has a higher accuracy with respect to the identification of the FT state of tundra soils than single-frequency methods based on the calculation of polarization index.</p

Are vegetation influences on Arctic–boreal snow melt rates detectable across the Northern Hemisphere?

The timing and rate of northern high latitude spring snowmelt plays a critical role in surface albedo, hydrology, and soil carbon cycling. Ongoing changes in the abundance and distribution of trees and shrubs in tundra and boreal ecosystems can alter snowmelt via canopy impacts on surface energy partitioning. It is unclear whether vegetation-related processes observed at the ecosystem scale influence snowmelt patterns at regional or continental scales. We examined the influence of vegetation cover on snowmelt across the boreal and Arctic region across a ten-year reference period (2000–2009) using a blended snow water equivalent (SWE) data product and gridded estimates of surface temperature, tree cover, and land cover characterized by the dominant plant functional type. Snow melt rates were highest in locations with a late onset of melt, higher temperatures during the melt period, and higher maximum SWE before the onset of melt. After controlling for temperature, melt onset, and the maximum SWE, we found snow melt rates were highest in evergreen needleleaf forest, mixed boreal forest, and herbaceous tundra compared to deciduous needleleaf forest and deciduous shrub tundra. Tree canopy cover had little effect on snowmelt rate within each land cover type. While accounting for the influence of vegetative land cover type is necessary for predictive understanding of snowmelt rate variability across the Arctic–Boreal region. The relationships differed from observations at the ecosystem and catchment scales in other studies. Thus highlighting the importance of spatial scale in identifying snow-vegetation relationships

Retrieving landscape freeze/thaw state fromSoil Moisture Active Passive (SMAP) radar and radiometer measurements

Over one-third of the global land area undergoes a seasonal transition between predominantly frozen and non-frozen conditions each year, with the land surface freeze/thaw (FT) state a significant control on hydrological and biospheric processes over northern land areas and at high elevations. The NASA Soil Moisture Active Passive (SMAP) mission produced a daily landscape FT product at 3-km spatial resolution derived from ascending and descending orbits of SMAP high-resolution L-band (1.4 GHz) radar measurements. Following the failure of the SMAP radar in July 2015, coarser (36-km) footprint SMAP radiometer inputs were used to develop an alternative daily passive microwave freeze/thaw product. In this study, in situ observations are used to examine differences in the sensitivity of the 3-km radar versus the 36-km radiometer measurements to the landscape freeze/thaw state during the period of overlapping instrument operation. Assessment of the retrievals at high-latitude SMAP core validation sites showed excellent agreement with in situ flags, exceeding the 80% SMAP mission accuracy requirement. Similar performance was found for the radar and radiometer products using both air temperature and soil temperature derived FT reference flags. There was a tendency for SMAP thaw retrievals to lead the surface flags due to the influence of wet snow cover conditions on both the radar and radiometer signal. Comparison with other satellite derived FT products showed those derived from passive measurements (SMAP radiometer; Aquarius radiometer; Advanced Microwave Scanning Radiometer - 2) retrieved less frozen area than the active products (SMAP radar; Aquarius radar)

Permafrost and Climate Change: Carbon Cycle Feedbacks From the Warming Arctic

Rapid Arctic environmental change affects the entire Earth system as thawing permafrost ecosystems release greenhouse gases to the atmosphere. Understanding how much permafrost carbon will be released, over what time frame, and what the relative emissions of carbon dioxide and methane will be is key for understanding the impact on global climate. In addition, the response of vegetation in a warming climate has the potential to offset at least some of the accelerating feedback to the climate from permafrost carbon. Temperature, organic carbon, and ground ice are key regulators for determining the impact of permafrost ecosystems on the global carbon cycle. Together, these encompass services of permafrost relevant to global society as well as to the people living in the region and help to determine the landscape-level response of this region to a changing climate

Variability in above- and belowground Carbon Stocks in a Siberian Larch Watershed

Permafrost soils store between 1330 and 1580Pg carbon (C), which is 3 times the amount of C in global vegetation, almost twice the amount of C in the atmosphere, and half of the global soil organic C pool. Despite the massive amount of C in permafrost, estimates of soil C storage in the high-latitude permafrost region are highly uncertain, primarily due to undersampling at all spatial scales; circumpolar soil C estimates lack sufficient continental spatial diversity, regional intensity, and replication at the field-site level. Siberian forests are particularly undersampled, yet the larch forests that dominate this region may store more than twice as much soil C as all other boreal forest types in the continuous permafrost zone combined. Here we present above- and belowground C stocks from 20 sites representing a gradient of stand age and structure in a larch watershed of the Kolyma River, near Chersky, Sakha Republic, Russia. We found that the majority of C stored in the top 1m of the watershed was stored belowground (92%), with 19% in the top 10cm of soil and 40% in the top 30cm. Carbon was more variable in surface soils (10cm; coefficient of variation (CV) = 0.35 between stands) than in the top 30cm (CV = 0.14) or soil profile to 1m (CV = 0.20). Combined active-layer and deep frozen deposits (surface – 15m) contained 205kgCm−2 (yedoma, non-ice wedge) and 331kgCm−2 (alas), which, even when accounting for landscape-level ice content, is an order of magnitude more C than that stored in the top meter of soil and 2 orders of magnitude more C than in aboveground biomass. Aboveground biomass was composed of primarily larch (53%) but also included understory vegetation (30%), woody debris (11%) and snag (6%) biomass. While aboveground biomass contained relatively little (8%) of the C stocks in the watershed, aboveground processes were linked to thaw depth and belowground C storage. Thaw depth was negatively related to stand age, and soil C density (top 10cm) was positively related to soil moisture and negatively related to moss and lichen cover. These results suggest that, as the climate warms, changes in stand age and structure may be as important as direct climate effects on belowground environmental conditions and permafrost C vulnerability

Surface Energy Budgets of Arctic Tundra During Growing Season

This study analyzed summer observations of diurnal and seasonal surface energy budgets across several monitoring sites within the Arctic tundra underlain by permafrost. In these areas, latent and sensible heat fluxes have comparable magnitudes, and ground heat flux enters the subsurface during short summer intervals of the growing period, leading to seasonal thaw. The maximum entropy production (MEP) model was tested as an input and parameter parsimonious model of surface heat fluxes for the simulation of energy budgets of these permafrost‐underlain environments. Using net radiation, surface temperature, and a single parameter characterizing the thermal inertia of the heat exchanging surface, the MEP model estimates latent, sensible, and ground heat fluxes that agree closely with observations at five sites for which detailed flux data are available. The MEP potential evapotranspiration model reproduces estimates of the Penman‐Monteith potential evapotranspiration model that requires at least five input meteorological variables (net radiation, ground heat flux, air temperature, air humidity, and wind speed) and empirical parameters of surface resistance. The potential and challenges of MEP model application in sparsely monitored areas of the Arctic are discussed, highlighting the need for accurate measurements and constraints of ground heat flux.Plain Language SummaryGrowing season latent and sensible heat fluxes are nearly equal over the Arctic permafrost tundra regions. Persistent ground heat flux into the subsurface layer leads to seasonal thaw of the top permafrost layer. The maximum energy production model accurately estimates the latent, sensible, and ground heat flux of the surface energy budget of the Arctic permafrost regions.Key PointThe MEP model is parsimonious and well suited to modeling surface energy budget in data‐sparse permafrost environmentsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150560/1/jgrd55584.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150560/2/jgrd55584_am.pd