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Objectives: Weather is a key source of marine risk, but relationships between fishing activity, safety, and weather remain poorly understood. Critically, the fit between available marine forecast products, fish harvesters' needs, and harvester's decision-making processes has not been rigorously assessed. This paper addresses these gaps by documenting a) weather-related decision-making by harvesters, and its relationship to forecasts across multiple regions and fisheries on Canada's East coast (Newfoundland) and b) the dynamics of forecast production priorities. Methods: A multi-disciplinary, community-engaged research approach, conducted in partnership with the Newfoundland and Labrador Fish Harvesting Safety Association (NL-FHSA). Data consist of semi-structured interviews with fish harvesters and weather forecasters, focused on marine forecast production and use. Results: Results emphasize that there is a subjective "art" to both production and use of marine forecasts. Forecasters and harvesters share several common values regarding forecasts, but different emphases: forecasters favor some combination of accuracy, consistency, and utility, while harvesters are largely concerned with utility. Finally, harvesters' decision-making is based on nuanced and contextual interpretations of a few key hazards (winds and, to a lesser extent, waves). Conclusion: This community-engaged research has triggered experimentation with forecasts tailored to fisheries utility within Environment and Climate Change Canada (ECCC). It lays the groundwork for ongoing, mutually beneficial dialogue between forecasters and harvesters, engaging harvesters with the forecasting process while familiarizing forecasters with harvester's decision-making processes. Ongoing industry partnerships (NL-FHSA) continue to sustain momentum from this study towards further enhancing the utility of future marine forecasts for small-scale harvesters. [ABSTRACT FROM AUTHOR]

The Canadian Earth System Model version 5 (CanESM5) developed at Environment and Climate Change Canada's Canadian Centre for Climate Modelling and Analysis (CCCma) is participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). A 40-member ensemble of CanESM5 historical decadal forecasts (or hindcasts) is integrated for ten years from realistic initial states during 1961 to present using prescribed external forcing. The results are part of CCCma's contribution to the Decadal Climate Prediction Project (DCPP) component of CMIP6. This paper evaluates CanESM5 large ensemble decadal hindcasts against observational benchmarks and against historical climate simulations initialized from preindustrial control run states. The focus is on the evaluation of the potential predictability and actual skill of annual and multi-year averages of key oceanic and atmospheric fields at regional and global scales. The impact of initialization on prediction skill is quantified from the hindcasts decomposition into uninitialized and initialized components. The dependence of potential and actual skill on ensemble size is examined. CanESM5 decadal hindcasts skilfully predict upper-ocean states and surface climate with a significant impact from initialization that depend on climate variable, forecast range, and geographic location. Deficiencies in the skill of North Atlantic surface climate are identified and potential causes discussed. The inclusion of biogeochemical modules in CanESM5 enables the prediction of carbon cycle variables which are shown to be skilful on decadal time scales, with a strong long-lasting impact from initialization on skill in the ocean and a moderate short-lived impact on land. [ABSTRACT FROM AUTHOR]

Sustainable building practices are rooted in the need for reliable information on the long-term performance of building materials; specifically, the expected service-life of building materials, components, and assemblies. This need is ever more evident given the anticipated effects of climate change on the built environment and the many governmental initiatives world-wide focused on ensuring that structures are not only resilient at their inception but also, can maintain their resilience over the long-term. The Government of Canada has funded an initiative now being completed at the National Research Council of Canada's (NRC) Construction Research Centre on "Climate Resilience of Buildings and Core Public infrastructure". The outcomes from this work will help permit integrating climate resilience of buildings into guides and codes for practitioners of building and infrastructure design. In this paper, the impacts of climate change on buildings are discussed and a review of studies on the durability of building envelope materials and elements is provided in consideration of the expected effects of climate change on the longevity and resilience of such products over time. Projected changes in key climate variables affecting the durability of building materials is presented such that specifications for the selection of products given climate change effects can be offered. Implications in regard to the maintainability of buildings when considering the potential effects of climate change on the durability of buildings and its components is also discussed. [ABSTRACT FROM AUTHOR]

The approach of applying different amounts of horizontal localization to different ranges of background-error covariance horizontal scales as proposed by Buehner and Shlyaeva was recently implemented in the four-dimensional ensemble–variational (4DEnVar) data assimilation scheme of the global deterministic prediction system (GDPS) at Environment and Climate Change Canada operations. To maximize the benefits from this approach to reduce the sampling noise in the ensemble-derived background-error covariances, it was necessary to adopt a new weighting between the climatological and flow-dependent covariances that increases significantly the role of the latter. Thus, in December 2021 the GDPS became the first operational global deterministic medium-range weather forecasting system to rely completely on flow-dependent covariances in the troposphere and the lower stratosphere. The experiments that led to the adoption of these two related changes and their impacts on the forecasts up to 7 days for various regions of the globe during the boreal summer of 2019 and winter of 2020 are presented here. It is also illustrated that relying more on ensemble-derived covariances amplifies the positive impacts on the GDPS when the background ensemble generation strategy is improved. [ABSTRACT FROM AUTHOR]

Early warning systems to predict infectious disease outbreaks have been identified as a key adaptive response to climate change. Warming, climate variability and extreme weather events associated with climate change are expected to drive an increase in frequency and intensity of mosquito-borne disease (MBD) outbreaks globally. In Canada, this will mean an increased risk of endemic and emerging MBD outbreaks such as West Nile virus and other MBDs. The availability of timely information on the risk of impending MBD outbreaks has important public health implications, by allowing implementation of mosquito control measures and targeted communications regarding the need for increased personal protective measures-before an outbreak occurs. In Canada, both mechanistic and statistical weather-based models have been developed to predict West Nile virus outbreaks. These include models for different species of mosquitoes that transmit West Nile virus in different geographical areas of Canada. Although initial results have been promising, further validation and assessment of forecasting skill are needed before wide scale implementation. Weather-based forecasting for other emerging MBDs in Canada, such as Eastern equine encephalitis, may also be feasible. [ABSTRACT FROM AUTHOR]

BACKGROUND: A number of studies have assessed possible climate change impacts on the Lyme disease vector, Ixodes scapularis. However, most have used surface air temperature from only one climate model simulation and/or one emission scenario, representing only one possible climate future. OBJECTIVES: We quantified effects of different Representative Concentration Pathway (RCP) and climate model outputs on the projected future changes in the basic reproduction number (R0) of I. scapularis to explore uncertainties in future R0 estimates. METHODS: We used surface air temperature generated by a complete set of General Circulation Models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to hindcast historical (1971-2000), and to forecast future effects of climate change on the R0 of I. scapularis for the periods 2011-2040 and 2041-2070. RESULTS: Increases in the multimodel mean R0 values estimated for both future periods, relative to 1971-2000, were statistically significant under all RCP scenarios for all of Nova Scotia, areas of New Brunswick and Quebec, Ontario south of 47°N, and Manitoba south of 52°N. When comparing RCP scenarios, only the estimated R0 mean values between RCP6.0 and RCP8.5 showed statistically significant differences for any future time period. CONCLUSION: Our results highlight the potential for climate change to have an effect on future Lyme disease risk in Canada even if the Paris Agreement's goal to keep global warming below 2°C is achieved, although mitigation reducing emissions from RCP8.5 levels to those of RCP6.0 or less would be expected to slow tick invasion after the 2030s. [ABSTRACT FROM AUTHOR]