Science Highlights

Spatial variability in mean annual soil temperatures is primarily influenced by the thermal decoupling between air- and ground-surface temperature in winter.

Combined temperature and electrical resistivity measurements show the distribution of permafrost and how it is related to topographic position and vegetation.

Drying of tundra landscapes will limit subsidence-induced acceleration of permafrost thaw.

Since its inception, the NGEE Arctic project has worked hard to develop and promote a culture of safety, respect, and inclusion. 

Drying of tundra landscapes will limit subsidence-induced acceleration of permafrost thaw.

The Arctic is warming at a faster rate than any other biome on Earth, resulting in widespread changes in vegetation composition, structure, and function that have important feedbacks to the global climate system. 

The Arctic tundra biome has become a hot spot of global environmental change because the vegetation and permafrost soils are strongly influenced by warming air temperatures and declining sea ice in the Arctic Ocean. In the late 1990s, global satellite observations revealed a sharp increase in the apparent productivity of tundra vegetation, a phenomenon that has come to be known as Arctic greening. Arctic greening is dynamically linked with Earth’s changing climate, interacting in complex ways with permafrost thaw, snow and sea ice change, and disturbances. However, the greening trend has not been universal, and some areas in the Arctic are even experiencing an opposite browning trend in response to disturbance and extreme weather events. 

Process model simulations reveal shortcomings in machine learning techniques commonly used to upscale and forecast ecosystem processes.

The ESS community generates a variety of multidisciplinary data, and the purpose of the reporting formats is to create a level of consistency that will allow for better integration and analysis of data. 

Iron cycling is key to modeling greenhouse gas emissions from permafrost soils.

Snow spatial distribution plays a vital role in sub-Arctic and Arctic climate, hydrology, and ecology due to its fundamental influence on the water balance, thermal regimes, vegetation, and carbon flux. However, the spatial distribution of snow is not well understood and therefore not well modeled, which can lead to substantial uncertainties in snow cover representations. To capture key hydro-ecological controls on snow spatial distribution, a team of scientists carried out intensive field studies over multiple years (2017–2019) for two small sub-Arctic study sites located on the Seward Peninsula of Alaska.

Organizers will host a workshop with the goal of giving NGEE Arctic scientists with limited or no computational or modeling experience a chance to run the E3SM Land Model (ELM), visualize model simulation output, and test questions using model simulations.

Parameter estimation approach advances cost-effective methodology for estimating soil thermal and physical properties with unprecedented spatial resolution.

Multiscale remote sensing technologies are helping researchers better understand the effects of climate change on vegetation productivity and regional variability in greening and browning trends.

An analytical model predicts how ice-wedge polygon geometry influences the export of solute-rich waters from tundra soils to ponds and streams.

NGEE Arctic investigators and others provide “best practices” on data and metadata from field gas-exchange measurements.

New technology adds value to monitoring, observational, and experimental sites in remote areas.

Field observations of community composition improve how plant functional types (PFT) are represented in E3SM simulations.

Model-data integration with international partner highlights how thawing permafrost can impact conditions of water discharged to near-by streams.

Inspired by fluid instabilities, NGEE Arctic researchers developed a mathematical theory that predicts solifluction lobe development.

Using a mechanistic land model, Ecosys, to demonstrate that short-term (< 10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with multi-decadal responses due to the tightly coupled, nonlinear nature of high-latitude ecosystems

Using a mechanistic ecosystem model, ecosys, to demonstrate that static temperature relations cannot accurately predict wetland CH4 production and emission rates due to substrate-mediated microbial and abiotic interactions.

A novel mathematical formulation allows accurate solution of water flow in geometrically complicated soil structures, including overturned soil layers and other soil disturbance.

The study provides new insight into hydrological processes of low- and high-centered polygon systems, where flow and transport field investigations are almost totally lacking.

Leadership team takes time and intentional steps to build a culture of safety and respect across the project.

Most models project a long-term drying of the surface soil for the permafrost region despite increases in the net air–surface water flux.

Rates and controls on CO2 and CH4 production were observed for two contrasting water‐saturated tundra soils within a permafrost‐affected watershed near Nome, AK.

Multiple models are needed to capture true uncertainty of soil carbon fate in a changing world.

Plant stoichiometric flexibility controls the CO2 fertilization effect on ecosystem carbon accumulation.

Novel bromide tracer experiments are used to develop a model of subsurface flow and transport within ice-wedge polygons.

Artificial intelligence applied to multiple remote sensing datasets accurately represents shrub distribution across hillslopes at the Kougarok field site.

Light-harvesting processes involved in photosynthesis by tundra plants are unexpectedly sensitive to growth at low temperatures.

Worldwide trait database addresses long-standing questions about trait-environment relationships and provides an unprecedented digital resource to inform Earth system models.

Field observations and model simulations confirm the presence of unfrozen permafrost in shrub-dominated landscapes.

A convolutional neural network (CNN) approach produced highly accurate vegetation classifications. Hyper-spectral datasets (e.g., AVIRIS) were most useful for our machine learning approaches. Accurate and high-resolution datasets generated using our approach are needed for Arctic models.

Biochemical composition is proposed to improve process-based models of SOM degradation and climate feedbacks

Several scaling strategies based on geomorphology were evaluated for complex polygonal landscapes.

Microtopographic variation among troughs, rims, and centers strongly affects the movement of surface water and snow and thereby affects soil water contents and active layer development.

Study highlights the poor representation of Arctic photosynthesis in TBMs, and provides the critical data necessary to improve our ability to project the response of the Arctic to global environmental change.

Modeling approach improving representations of permafrost dynamics in evolving landscapes.

Ponds and lakes affect high-latitude carbon, water, and energy budgets, however, there is no good observationally-constrained characterization of waterbodies for high-latitude systems. The Permafrost Region Pond and Lake (PeRL) database addresses this problem. PeRL includes 69 maps covering a wide range of environmental conditions.

The ability to map snow depth in high resolution and over a large areas permits for the first time a dataset that can be used to quantify the impact of heterogeneous snow distribution on hydrology and carbon exchange.

Observationally-constrained photosynthetic traits for land models.

Rapid warming in the Arctic is leading to the thawing of carbon-rich soils that have been permanently frozen for millennia. The release of greenhouse gases from thawed permafrost could increase the rate of global warming, but this depends on the amount of carbon released into the atmosphere, and whether carbon is released as carbon dioxide or the more potent greenhouse gas methane.

Results show that climate warming and permafrost thaw could potentially enhance methylmercury toxin production by an order of magnitude, impacting Arctic terrestrial and aquatic ecosystems by increased exposure to mercury through bioaccumulation and biomagnification in the food web.

Ice wedges, which are a common subsurface feature in permafrost landscapes, appear to be rapidly melting throughout the Arctic altering the microtopography and causing succession in polygon type that has profound changes to the storage and flow of water on the landscape.

Exploring potential future climate effects on permafrost using hydrothermal modeling of arctic soils.

A flexible and extensible soil biogeochemistry module for the land component of a multi-scale Earth System Model.

Study of thawing permafrost uncovers greenhouse gas (CO2 and CH4) precursors and their degradation rates and pathways.