• Energy Research

AbstractSeasonal ice in lakes plays an important role for local communities and lake ecosystems. Here we use Large Ensemble simulations conducted with the Community Earth System Model version 2, which includes a lake simulator, to quantify the response of lake ice to greenhouse warming and to determine emergence patterns of anthropogenic lake ice loss. Our model simulations show that the average duration of ice coverage and maximum ice thickness are projected to decrease over the next 80 years by 38 days and 0.23 m, respectively. In the Canadian Arctic, lake ice loss is accelerated by the cold-season polar amplification. Lake ice on the Tibetan Plateau decreases rapidly due to a combination of strong insolation forcing and ice-albedo feedbacks. Comparing the anthropogenic signal with natural variability represented by the Large Ensemble, we find that lake ecosystems in these regions may be exposed to no-analogue ice coverage within the next 4-5 decades.

AbstractThis contribution to the RECCAP2 (REgional Carbon Cycle Assessment and Processes) assessment analyzes the processes that determine the global ocean carbon sink, and its trends and variability over the period 1985–2018, using a combination of models and observation‐based products. The mean sea‐air CO2 flux from 1985 to 2018 is −1.6 ± 0.2 PgC yr−1 based on an ensemble of reconstructions of the history of sea surface pCO2 (pCO2 products). Models indicate that the dominant component of this flux is the net oceanic uptake of anthropogenic CO2, which is estimated at −2.1 ± 0.3 PgC yr−1 by an ensemble of ocean biogeochemical models, and −2.4 ± 0.1 PgC yr−1 by two ocean circulation inverse models. The ocean also degasses about 0.65 ± 0.3 PgC yr−1 of terrestrially derived CO2, but this process is not fully resolved by any of the models used here. From 2001 to 2018, the pCO2 products reconstruct a trend in the ocean carbon sink of −0.61 ± 0.12 PgC yr−1 decade−1, while biogeochemical models and inverse models diagnose an anthropogenic CO2‐driven trend of −0.34 ± 0.06 and −0.41 ± 0.03 PgC yr−1 decade−1, respectively. This implies a climate‐forced acceleration of the ocean carbon sink in recent decades, but there are still large uncertainties on the magnitude and cause of this trend. The interannual to decadal variability of the global carbon sink is mainly driven by climate variability, with the climate‐driven variability exceeding the CO2‐forced variability by 2–3 times. These results suggest that anthropogenic CO2 dominates the ocean CO2 sink, while climate‐driven variability is potentially large but highly uncertain and not consistently captured across different methods.

Climate change projections consistently demonstrate that warming temperatures and dwindling seasonal snowpack will elicit cascading effects on ecosystem function and water resource availability. Despite this consensus, little is known about potential changes in the variability of ecohydrological conditions, which is also required to inform climate change adaptation and mitigation strategies. Considering potential changes in ecohydrological variability is critical to evaluating the emergence of trends, assessing the likelihood of extreme events such as floods and droughts, and identifying when tipping points may be reached that fundamentally alter ecohydrological function. Using a single-model Large Ensemble with sophisticated terrestrial ecosystem representation, we characterize projected changes in the mean state and variability of ecohydrological processes in historically snow-dominated regions of the Northern Hemisphere. Widespread snowpack reductions, earlier snowmelt timing, longer growing seasons, drier soils, and increased fire risk are projected for this century under a high-emissions scenario. In addition to these changes in the mean state, increased variability in winter snowmelt will increase growing-season water deficits and increase the stochasticity of runoff. Thus, with warming, declining snowpack loses its dependable buffering capacity so that runoff quantity and timing more closely reflect the episodic characteristics of precipitation. This results in a declining predictability of annual runoff from maximum snow water equivalent, which has critical implications for ecosystem stress and water resource management. Our results suggest that there is a strong likelihood of pervasive alterations to ecohydrological function that may be expected with climate change.