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Abstract Accelerated warming of the Arctic can affect the global climate system by thawing permafrost and exposing organic carbon in soils to decompose and release greenhouse gases into the atmosphere. We used a process-based biosphere model (DVM-DOS-TEM) designed to simulate biophysical and biogeochemical interactions between the soil, vegetation, and atmosphere. We varied soil and environmental parameters to assess the impact on cryohydrological and biogeochemical outputs in the model. We analyzed the responses of ecosystem carbon balances to permafrost thaw by running site-level simulations at two long-term tundra ecological monitoring sites in Alaska: Eight Mile Lake (EML) and Imnavait Creek Watershed (IMN), which are characterized by similar tussock tundra vegetation but differing soil drainage conditions and climate. Model outputs showed agreement with field observations at both sites for soil physical properties and ecosystem CO₂fluxes. Model simulations of Net Ecosystem Exchange (NEE) showed an overestimation during the frozen season (higher CO₂emissions) at EML with a mean NEE of 26.98 ± 4.83 gC/m²/month compared to observational mean of 22.01 ± 5.67 gC/m²/month, and during the fall months at IMN, with a modeled mean of 19.21 ± 7.49 gC/m²/month compared to observation mean of 11.9 ± 4.45 gC/m²/month. Our results underscore the importance of representing the impact of soil drainage conditions on the thawing of permafrost soils, particularly poorly drained soils, which will drive the magnitude of carbon released at sites across the high-latitude tundra. These findings can help improve predictions of net carbon releases from thawing permafrost, ultimately contributing to a better understanding of the impact of Arctic warming on the global climate system. 

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under- sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.