Adam Hugh Monahan

Variations in snow, sea ice, and upper-ocean conditions influence the development of sea ice algal blooms. To better understand these links, the Canadian Sea Ice Biogeochemistry (CSIB2) model has been used to analyze field observations from landfast ice near Resolute in the Canadian Arctic Archipelago. Measurements from three sites with different snow depths captured the response of ice algae to varying light conditions and guided model improvements in the representation of photophysiology. A novel representation of photoacclimation has been developed, including variable ice algal carbon-to-chlorophyll (C:Chl) and C:Chl-dependent photosynthesis parameters, capturing variations in photophysiology associated with spatial and temporal changes in light regimes. Photophysiological parameters were estimated by identifying parameter values that minimized differences between simulated and observed blooms. Differences in simulated photophysiological characteristics between closely located sites differing only in snow depth highlight the strong photoacclimation capacity of ice algae. Model simulations indicate that differences in ice algal blooms were driven by variations in light availability and the associated differences in photophysiological parameters. Earlier increases in bottom-ice irradiance at sites with less snow promoted earlier growth and photoacclimation in simulations. Higher values of the photosynthetic efficiency parameter were estimated at these sites, corresponding to greater low-light photosynthetic capacity and consistent with early blooms dominated by low-light-adapted ice algae. In contrast, persistently low irradiance at the high snow site delayed bloom development, with limited changes simulated in photosynthetic characteristics.

We use the Canadian Sea Ice Biogeochemistry model (CSIB2) to analyze field observations of a spring ice algal bloom in Resolute Passage, Canadian Arctic Archipelago, and investigate how ice-ocean exchanges regulate nitrogen availability, ice algal stoichiometry, and biomass export. Model simulations show that turbulent diffusion across the ice-ocean interface provided most of the nitrogen required to sustain strong ice algal blooms. However, tidal modulation of these diffusive exchanges could produce periods of transient nitrogen limitation, contributing to variability in the simulated ice algal carbon-to-nitrogen (C:N) ratios. We introduce a novel nitrogen uptake parameterization in which the target ice algal C:N increases with the ice algal carbon-to-chlorophyll (C:Chl) ratio, to represent greater production of carbon-rich storage compounds as irradiance increases. This approach better reproduces observations than a fixed Redfield ratio parametrization, suggesting that carbon enrichment could provide an alternative explanation to nutrient limitation for the observed seasonal increase of ice algal C:N. The mechanisms responsible for the release of ice algal biomass from sea ice to the ocean are also examined, and we show how different thermodynamic processes regulate the timing of biomass export. Including an export process linked to the sea ice warming rate was essential to reproduce the early export of ice algal biomass before snowmelt onset under low snow conditions. These results demonstrate that accurate representations of ice-ocean exchanges are essential for simulating sea ice algal bloom dynamics and biogeochemical fluxes.

Arctic aerosol, cloud, and surface radiation budgets are highly sensitive to how dimethylsulfide (DMS) is represented in atmospheric models. We investigate the impact of (a) the gas‐phase DMS oxidation mechanism (simple 3‐reaction scheme vs. a complex gas‐phase scheme), (b) the representation of oceanic DMS (global climatology vs. detailed Arctic Ocean biogeochemistry simulation), and (c) the parameterization of new particle formation from marine biogenic precursor gases, represented by methanesulfonic acid (MSA). We find that the more detailed approach in (a) and (b) improves agreement with observed DMS and concentrations, and that activating (c) enables the model to capture the observed summertime maximum in total aerosol number concentrations. Together, these changes result in large‐scale modifications to cloud microphysics and surface energy budget in the Arctic, which lead to a very good agreement with observations of cloud cover and surface radiation. We recommend that climate models consider adopting these updates.

In the Northeast Pacific, the marine carbonate system's variability across timescales is not well constrained. Here, we quantify observed seasonal and non‐seasonal variability in Dissolved Inorganic Carbon (DIC), partial pressure of carbon dioxide () and aragonite saturation state and discuss potential drivers. We used three decades of observations from four Line P time series stations, the longest marine carbonate system time series in the Northeast Pacific (1990–2019). To gauge the spatial extent of the variability patterns, we used output from a global ocean model representing the observed period. In the Northeast Pacific, seasonal and non‐seasonal variability at 10 m was minimal, mostly damped by the opposing influence of DIC and temperature changes at both seasonal and interannual timescales. For DIC and , the seasonal cycle dominated total variability in the top 60–70 m, with mean‐transect 10 m seasonal amplitudes of 35 3 μmol and 0.31 0.04, respectively. In the upper 60–70 m, the magnitude of non‐seasonal variability was at least half that of the seasonal variability for most variables. From five climate indices examined, we focused on the basin‐scale Pacific Decadal Oscillation index (PDO) to investigate potential drivers of non‐seasonal variability, with 20%–40% of the non‐seasonal variability in DIC and associated to this index. In the Northeast Pacific, positive PDO periods were linked to a mean reduction in 10 m DIC of 5 μmol and an increase in 10 m of 0.04 for each PDO unit increase, which could potentially reduce the occurrence and severity of ocean acidification events. The opposite could be expected during negative PDO periods.

Arctic aerosol, cloud, and surface radiation budgets are highly sensitive to how dimethylsulfide (DMS) is represented in atmospheric models. We investigate the impact of (1) the gas-phase DMS oxidation mechanism (simple versus complex), (2) the representation of oceanic DMS (global climatology versus detailed Arctic Ocean biogeochemistry simulation), and (3) the parameterization of new particle formation (NPF) from methanesulfonic acid (MSA). We find that the more detailed approach in (1) and (2) improves agreement with observed DMS and SO2 concentrations, and that activating (3) enables the model to capture the observed summertime maximum in aerosol number concentrations. Together, these changes result in large-scale modifications to cloud microphysics and the arctic surface energy budget, with radiative impacts of ±13Wm ^-2 annually, reaching up to ±50Wm ^-2 in summertime when combining all the model updates.

A document by Ruth A. R. Digby. Click on the document to view its contents.

Observational constraint methods based on the relationship between the past global warming trend and projected warming across climate models were used to reduce uncertainties in projected warming by the Intergovernmental Panel on Climate Change. Internal climate variability in the eastern tropical Pacific associated with the so-called pattern effect weakens this relationship and has reduced the observed warming trend over recent decades. Here we show that regressing out this variability before applying the observed global mean warming trend as a constraint results in higher and narrower twenty-first century warming ranges than other methods. Whereas the Intergovernmental Panel on Climate Change assessed that warming is unlikely to exceed 2 °C under a low-emissions scenario, our results indicate that warming is likely to exceed 2 °C under the same scenario, and hence, limiting global warming to well below 2 °C will be harder than previously anticipated. However, the reduced uncertainties in these projections could benefit adaptation planning.

The future of Arctic sea ice algae is examined using a regional ocean and sea ice biogeochemical model, with a simulation from 1980 to 2085, considering a future scenario with strong warming. To analyze the impacts of climate change, we computed key dates in the development of sympagic blooms, corresponding to the occurrence of specific growth conditions, and designed diagnostics of ice algal phenology to estimate the onset and peak of blooms. These diagnostics help understand how the timing of light and nutrient availability governs the growth of ice algae and how environmental controls will be altered by climate change across regions. With thinner ice, photosynthetically active radiation in bottom ice will reach levels sufficient for growth earlier, resulting in a better synchrony of high levels of light and nutrients. Increases in snow cover can potentially offset the effect of thinner ice, leading to shorter periods of favorable growth conditions in certain regions. The loss of sea ice cover before the late 21st century only impacts sympagic blooms at lower latitudes, as the timing of sea ice break-up shows little change relative to other key dates at higher latitudes. In response to climate change, the model simulates a modified spatial distribution of blooms, with the emergence of highly productive areas and the loss of blooms in other regions. However, the changes in the timing of growth conditions do not substantially alter the timing of blooms, and both onset and peak ice algae see little change. The simulated lack of sensitivity of bloom onset is attributed to the delay in sea ice freeze-up projected by the model, causing a reduction of overwintering ice algae. The resulting lower initial biomass at the beginning of spring then causes a delay in the development of blooms, offsetting earlier light from thinner ice.