• Energy Research

AbstractThe regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.

AbstractThe Antarctic Peninsula (AP) experienced a new extreme warm event and record-high surface melt in February 2022, rivaling the recent temperature records from 2015 and 2020, and contributing to the alarming series of extreme warm events over this region showing stronger warming compared to the rest of Antarctica. Here, the drivers and impacts of the event are analyzed in detail using a range of observational and modeling data. The northern/northwestern AP was directly impacted by an intense atmospheric river (AR) attaining category 3 on the AR scale, which brought anomalous heat and rainfall, while the AR-enhanced foehn effect further warmed its northeastern side. The event was triggered by multiple large-scale atmospheric circulation patterns linking the AR formation to tropical convection anomalies and stationary Rossby waves, with an anomalous Amundsen Sea Low and a record-breaking high-pressure system east of the AP. This multivariate and spatial compound event culminated in widespread and intense surface melt across the AP. Circulation analog analysis shows that global warming played a role in the amplification and increased probability of the event. Increasing frequency of such events can undermine the stability of the AP ice shelves, with multiple local to global impacts, including acceleration of the AP ice mass loss and changes in sensitive ecosystems.

The dataset includes daily mean solar radiation (DSR) in W.m-2 and daily mean cloud modification factor (CMF) for J.G. Mendel (James Ross Island) and King Sejong (King George Island, South Shetland Islands) stations located in the Antarctic Peninsula region for the period 2011–2016. The dataset is included in: Szymszová, S., Láska, K., Kim, S.-J., Park, S.-J., 2025. Variability of solar radiation and cloud cover in the Antarctic Peninsula region. Atmospheric Research, 316, 107940. https://doi.org/10.1016/j.atmosres.2025.107940 DSR was measured by CMP11 pyranometer (Kipp & Zonen, the Netherlands) at J.G. Mendel station and Eppley Precision Pyranometer (The Eppley Laboratory, USA) at King Sejong station in a 10-min time step. CMF was calculated as ratio of measured DSR and theoretical DSR (DSR at the same atmospheric conditions as the measured DSR, but with excluded influence of clouds). Theoretical DSR was calculated using Bird and Hulstrom model (Bird and Hulstrom, 1981*). Input parameters to the model were solar zenith angle, atmospheric pressure, water vapour content, ozone, albedo, forward-scatterd irradiance ratio and aerosol optical depth at wavelenghts of 380 and 500 nm. *Bird, R. E. and Hulstrom, R. L., 1981. A Simplified Clear Sky Model for Direct and Diffuse Insolation on Horizontal Surfaces, Technical Report No. SERI/TR-642-761, Golden, CO: Solar Energy Research Institute.