Climate dynamics

Abstract:

Arctic amplification (AA), the phenomenon by which Arctic surface temperatures are warming faster than the global average, may have significant unexplored impacts on temperature-related mortality in human populations across Canada. We explore the role of Arctic sea ice loss, a key driver of AA, in changing cold temperature extremes across Canada and their impact on human mortality. We use a multi-model ensemble of climate simulations from the Polar Amplification Model Intercomparison Project and a distributed lag nonlinear mortality model in 27 regions covering Canada to quantify the role of Arctic sea ice loss in changing human mortality in the cold season. We find that despite a robust increase in 5th percentile temperatures across eastern Canada, there is no detectable decrease in mortality associated with the most extreme cold, due to mortality in many regions having low sensitivity to warming of cold extremes. The study attributes the temperature-related mortality impact of a physical process, namely Arctic sea ice loss, and highlights Canada’s robust adaptation to extreme cold.

Abstract:

To address the effect of stratiform latent heating on meso- to large-scale circulations, an enhanced implementation of the Multiscale Coherent Structure Parameterization (MCSP) is developed for the Met Office Unified Model. MCSP represents the top-heavy stratiform latent heating from under-resolved organized convection in general circulation models. We couple the MCSP with a mass-flux convection scheme (CoMorph-A) to improve storm lifecycle continuity. The improved MCSP trigger is specifically designed for mixed-phase deep convective cloud, combined with a background vertical wind shear, both known to be crucial for stratiform development. We also test a cloud top temperature dependent convective-stratiform heating partitioning, in contrast to the earlier fixed partitioning. Assessments from ensemble weather forecasts and decadal simulations demonstrate that MCSP directly reduces cloud deepening and precipitation areas by moderating mesoscale circulations. Indirectly, it amends tropical precipitation biases, notably correcting dry and wet biases over India and the Indian Ocean, respectively. Remarkably, the scheme outperforms a climate model ensemble by improving seasonal precipitation cycle predictions in these regions. The scheme also improves Madden-Julian Oscillation (MJO) spectra, achieving better alignment with observational and reanalysis data by intensifying the simulated MJO over the Indian Ocean during phases 4 to 5. However, the scheme increases precipitation overestimation over the Western Pacific. Shifting from fixed to temperature-dependent convective-stratiform partitioning reduces the Pacific precipitation overestimation and further improves the seasonal cycle in India. Spatially correlated biases highlight the necessity for advances beyond deterministic approaches to align MCSP with environmental conditions.