Snow-to-Rain Shifts Modulate CO2 Emissions From pan-Arctic Permafrost Regions

The precipitation phase reaching the ground surface (e.g., rain or snow) is primarily determined by atmospheric temperature and humidity. The recent warming climate has caused precipitation to fall more as rainfall than snowfall, resulting in a shift from snowfall to rainfall ( i.e., snow-to-rain shifts) and decreasing the snow fraction of total precipitation. These shifts have increased rainfall events and decreased snow coverage and snowpack depth in pan-Arctic permafrost regions. The snow depth decline reduces snowpack thermal insulation to the ground, allowing more heat to escape from the soil to the atmosphere during the cold season, resulting in a cooling effect on soil temperature. This cooling effect can partially offset the current warming of cold-season soil temperature induced by the warming atmospheric temperature. Additionally, the decline in snow coverage and snow-season length has dual effects. On one hand, it leads to decreased land surface albedo, increasing solar radiation absorption, soil temperature, and ecosystem respiration. On the other hand, it allows for more outgoing longwave radiation, which decreases soil temperature. However, the integrated net impact of changes in snowfall fraction on soil warming and ecosystem carbon budget remains uncertain, as the effects of reduced snow depth and snow coverage on soil temperature and ecosystem are opposite. Thus, the net impact can be either a positive or negative feedback.

Despite the critical role of snow conditions in terrestrial hydrology and ecosystem biogeochemical cycling, the specific impact of snow-to-rain shifts on permafrost carbon-climate feedback is still unclear. To address this knowledge gap, we utilize the Energy Exascale Earth System Model (E3SM) land model (ELM) to investigate the impact of snow-to-rain shifts on CO2 emissions from pan-Arctic permafrost ecosystems. Specifically, we first analyzed the sensitivity of ELM-simulated snow water equivalent (SWE), active layer thickness (ALT), warm-season net CO2 uptake, and cold-season net CO2 emissions to climate forcing and precipitation-phase partitioning methods (PPMs). We then evaluated ELM-simulated SWE and CO2 emissions against observationally-constrained datasets. Furthermore, we predicted trends of snow-to-rain shifting and cold-season carbon emissions over pan-Arctic ecosystems under the Representative Concentration Pathway (RCP) 8.5 scenario. The simulation results demonstrated good agreements with observation-derived SWE, ALT, and CO2 emissions over tundra ecosystems. The results also reveal positively correlated relationships between changes in ELM-simulated snowfall fraction and the corresponding changes in cold-season cumulative net CO2 flux with Pearson coefficient R as 0.89 and 0.79 for the tundra and taiga areas, respectively. This suggests that current snow-to-rain shifts will likely slow down cold-season CO2 emissions from permafrost tundra and taiga areas, indicating potentially negative feedback between snow-to-rain shifts and climate warming. However, under future climate change scenarios, the predicted cold-season snowfall fraction is expected to be only around 10% of the total precipitation by the end of the 21st century under the RCP 8.5 scenario. By then, snow cover decrease-induced positive feedback may exceed the negative feedback associated with decreasing snow thermal insulation, significantly modulating permafrost water-carbon-climate interactions.