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A strong atmospheric river made landfall in southwestern British Columbia, Canada on November 14th, 2021, bringing two days of intense precipitation to the region. The resulting floods and landslides led to the loss of at least five lives, cut Vancouver off entirely from the rest of Canada by road and rail, and made this the costliest natural disaster in the province's history. Here we show that when characterised in terms of storm-averaged water vapour transport, the variable typically used to characterise the intensity of atmospheric rivers, westerly atmospheric river events of this magnitude are approximately one in ten year events in the current climate of this region, and that such events have been made at least 60% more likely by the effects of human-induced climate change. Characterised in terms of the associated two-day precipitation, the event is substantially more extreme, approximately a one in fifty to one in a hundred year event, and the probability of events at least this large has been increased by a best estimate of 45% by human-induced climate change. The effects of this precipitation on streamflow were exacerbated by already wet conditions preceding the event, and by rising temperatures during the event that led to significant snowmelt, which led to streamflow maxima exceeding estimated one in a hundred year events in several basins in the region. Based on a large ensemble of simulations with a hydrological model which integrates the effects of multiple climatic drivers, we find that the probability of such extreme streamflow events in October to December has been increased by human-induced climate change by a best estimate of 120–330%. Together these results demonstrate the substantial human influence on this compound extreme event, and help motivate efforts to increase resiliency in the face of more frequent events of this kind in the future.

This issue of the PCIC Update covers the following stories: Downscaled CMIP6 Data Now Available; Release of the Design Value Explorer; IPCC Reports on Impacts, Adaptation, Vulnerability and Mitigation; and New Section and Sector Modules on ClimateData.ca. The Science Brief mentioned in this issue is on changes to Western Canadian glaciers. The talks discussed in this issue were delivered by Professor Ted Shepherd, Dr. Mohamed Ali Ben Alaya, Dr. Nathan Gillett and Markus Schnorbus, Dr. John Fyfe, Dr. Paul Kushner and Dr. Hans von Storch. The staff profile in this issue is on Stacey O'Sullivan.

On 6–8 January 2021, a cold air outbreak swept across eastern China, peaking over the North China Plain the night of 6 January, when 219 weather stations recorded the lowest nighttime temperature since 1961. In total, 498 stations recorded the lowest daytime or nighttime temperature since 1961 during the 3-day event. This event, together with two other cold outbreaks that affected the region on 13–15 December 2020 and 29 December 2020–1 January 2021, led to historic peak electricity demand and resumption of the operation of the only remaining coalfired generating plant in Beijing. This analysis puts the cold outbreak into historical perspective by considering changes in the likelihood of such events over 1961–2020 in the context of a climate that is being warmed by anthropogenic forcing.

PCIC is a regional climate service provider dedicated to ensuring the provision of quantitative, high qualityclimate information to stakeholders and the public in BC and more widely. PCIC considers itself to be a competent, innovative and reliable climate service provider that works at a very high level of technical proficiency. Motivated by our stakeholders’ needs, PCIC bases its services on results obtained from the global climate research community and its own applied, regional climate research. It also works to increase the capacity of others to use climate information and understand its limitations.

This plan articulates PCIC’s ambition to serve as THE authoritative climate services provider in our region by setting out several service objectives for the organization that encompass a spectrum of activities ranging from direct data delivery to user-specific interpretation and training. These overarching service objectives are supported by several strategic objectives that are required to achieve our service objectives as well as a strategy for electronic services delivery. A key tool in achieving these objectives will be the careful use of climate change simulations produced for Phase 6 of the Coupled Model Intercomparison Project (CMIP6; Eyring et al., 2016), which uses updated models compared to those considered in IPCC (2014), and considers a wider range of emissions scenarios, called Shared Socioeconomic Pathways (SSPs).

Understanding the dynamics of water-energy-food (WEF) nexus interactions with climate change and human intervention helps inform policymaking. This study demonstrates the WEF nexus behavior under ensembles of climate change, transboundary inflows, and policy options, and evaluates the overall nexus performance using a previously developed system dynamics-based WEF nexus model—WEF-Sask. The climate scenarios include a baseline (1986–2014) and near-future climate projections (2021–2050). The approach is demonstrated through the case study of Saskatchewan, Canada. Results show that rising temperature with increased rainfall likely maintains reliable food and feed production. The climate scenarios characterized by a combination of moderate temperature increase and slightly less rainfall or higher temperature increase with slightly higher rainfall are easier to adapt to by irrigation expansion. However, such expansion uses a large amount of water resulting in reduced hydropower production. In contrast, higher temperature, combined with less rainfall, such as SSP370 (+2.4 °C, −6 mm), is difficult to adapt to by irrigation expansion. Renewable energy expansion, the most effective climate change mitigation option in Saskatchewan, leads to the best nexus performance during 2021–2050, reducing total water demand, groundwater demand, greenhouse gas (GHG) emissions, and potentially increasing water available for food&feed production. In this study, we recommend and use food&feed and power production targets and provide an approach to assessing the impacts of hydroclimate and policy options on the WEF nexus, along with suggestions for adapting the agriculture and energy sectors to climate change.

Information about snow water equivalent in southwestern British Columbia, Canada, is used for flood management, agriculture, fisheries, and water resource planning. This study evaluates whether a process-based, energy balance snow model supplied with high-resolution statistically downscaled temperature and precipitation data can effectively simulate snow water equivalent (SWE) in the mountainous terrain of this region. Daily values of SWE from 1951 to 2018 are simulated at 1-km resolution and evaluated using a reanalysis SWE product [Snow Data Assimilation System (SNODAS)], manual snow-survey measurements at 41 sites, and automated snow pillows at six locations in the study region. Simulated SWE matches observed interannual variability well (R2 > 0.8 for annual maximum SWE), but peak SWE biases of 20%–40% occur at some sites in the study domain, and higher biases occur where observed SWE is very low. Modeled SWE displays lower bias relative to SNODAS reanalysis at most manual survey locations. Future projections for the study area are produced using 12 downscaled climate model simulations and are used to illustrate the impacts of climate change on SWE at 1°, 2°, and 3°C of warming. Model results are used to quantify spring SWE changes at different elevations of the Whistler mountain ski resort and the sensitivity of annual peak SWE in the Metropolitan Vancouver municipal watersheds to moderate temperature increases. The results both illustrate the potential utility of a process-based snow model and identify areas where the input meteorological variables could be improved.

Recent studies have identified stronger warming in the latest generation of climate model simulations globally, and the same is true for projected changes in Canada. This study examines differences for Canada and six sub-regions between simulations from the latest Sixth Coupled Model Intercomparison Project (CMIP6) and its predecessor CMIP5. Ensembles from both experiments are assessed using a set of derived indices calculated from daily precipitation and temperature, with projections compared at fixed future time intervals and fixed levels of global temperature change. For changes calculated at fixed time intervals most temperature indices display higher projected changes in CMIP6 than CMIP5 for most sub-regions, while greater precipitation changes in CMIP6 occur mainly in extreme precipitation indices. When future projections are calculated at fixed levels of global average temperature increase, the size and spread of differences for future projected changes between CMIP6 and CMIP5 are substantially reduced for most indices. Temperature scaling behaviour, or the regional response to increasing global temperatures, is similar in both ensembles, with annual temperature anomalies for Canada and its sub-regions increasing at between 1.5 and 2.5 times the rate of increase globally, depending on the region. The CMIP6 ensemble projections exhibit modestly stronger scaling behaviour for temperature anomalies in northern Canada, as well as for certain indices of moderate and extreme events. Such temperature scaling differences persist even if anomalously warm CMIP6 global climate models are omitted. Comparing the mean and variance of future projections for Canada in CMIP5 and CMIP6 simulations from the same modelling centre suggests CMIP6 models are significantly warmer in Canada than CMIP5 models at the same level of forcing, with some evidence that internal temperature variability in CMIP6 is reduced compared with CMIP5.

The regression-based optimal fingerprinting is a key tool for quantifying human climate influence. Most studies over the past decade used Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations, limiting fingerprinting regression configuration options. The CMIP6 Detection and Attribution Model Intercomparison Project (DAMIP) provides several types of individual forcing simulations and thus greater configuration flexibility. To avoid overfitting the limited observational data, we suggest that a DAMIP-based perfect model study is first used to best configure the fingerprinting regression prior to its application to observations. We find that a regression using all-forcing, aerosol-only, and natural-only simulations is an overall best option for constraining human-induced global terrestrial warming, which differs from choices commonly made previously. Applying this configuration to observations, we estimate that of the observed terrestrial warming of ∼1.5°C between 1850–1900 and 2011–2020, anthropogenic greenhouse gases contributed 1.4 to 2.3°C, offset by aerosol cooling of 0.2 to 1.2°C.

Climate change is warming the ocean and impacting lower trophic level (LTL) organisms. Marine ecosystem models can provide estimates of how these changes will propagate to larger animals and impact societal services such as fisheries, but at present these estimates vary widely. A better understanding of what drives this inter-model variation will improve our ability to project fisheries and other ecosystem services into the future, while also helping to identify uncertainties in process understanding. Here, we explore the mechanisms that underlie the diversity of responses to changes in temperature and LTLs in eight global marine ecosystem models from the Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP). Temperature and LTL impacts on total consumer biomass and ecosystem structure (defined as the relative change of small and large organism biomass) were isolated using a comparative experimental protocol. Total model biomass varied between −35% to +3% in response to warming, and -17% to +15% in response to LTL changes. There was little consensus about the spatial redistribution of biomass or changes in the balance between small and large organisms (ecosystem structure) in response to warming, an LTL impacts on total consumer biomass varied depending on the choice of LTL forcing terms. Overall, climate change impacts on consumer biomass and ecosystem structure are well approximated by the sum of temperature and LTL impacts, indicating an absence of nonlinear interaction between the models’ drivers. Our results highlight a lack of theoretical clarity about how to represent fundamental ecological mechanisms, most importantly how temperature impacts scale from individual to ecosystem level, and the need to better understand the two-way coupling between LTL organisms and consumers. We finish by identifying future research needs to strengthen global marine ecosystem modelling and improve projections of climate change impacts.