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Item Detectable anthropogenic influence in mean precipitation of China(Geophysical Research Letters, 2025) Wang, Tao; Sun, Ying; Zhang, Xuebin; Yang, Xiu-Qun; Song, HeyangDetecting and attributing regional-scale mean precipitation changes remains a challenging scientific problem. Due to significant spatiotemporal variability of precipitation changes and the limited ability of climate models to simulate these variations, attribution studies of China's mean precipitation changes remain scarce. We analyze China's long-term precipitation changes using four observational data sets and CMIP6 simulations, with percentage precipitation anomaly as a key metric. Through optimal fingerprinting detection, we identify anthropogenic signals in China's mean precipitation changes. Results reveal an increasing trend in annual precipitation across most regions since the 1960s, which CMIP6 models generally capture, though large inter-model discrepancies persist in simulating trends in southern China. Human influence on China's mean precipitation changes is detectable and separable from natural forcings. Anthropogenic signals are detected in three sub-climatic regions: Northwest China, Northeast China, and Tibetan Plateau. Three-signal analysis indicates that the increase in China's precipitation is primarily driven by greenhouse gas forcing.Item Heat wave trends in Canadian regions(Atmosphere-Ocean, 2025) Kirchmeier-Young, Megan; Li, Guilong; Wan, Hui; Zhang, XuebinDespite their widespread impacts, there has been limited work to quantify how heat waves have changed in Canada. With no standard definition of a heat wave, we consider two different types of heat waves: climatological heat waves defined by the exceedance of a climatological percentile threshold and heat-warning heat waves which are based on the absolute threshold criteria for issuing heat warnings in Canada. These two heat waves represent different types of events with different primary impacts. We find the type of heat wave strongly influences the number of heat waves each year and the regional patterns of where such events are more prevalent. After the evaluation of climatologies, considering station observations and spatially complete gridded datasets, trends in annual metrics of heat waves were calculated for Canadian regions. Climatological heat waves increased in frequency, duration, and cumulative intensity between 1961 and 2020 across the country and in most regions. Heat-warning heat waves have increased over Northern and Atlantic Canada.Item Observed surface wind speed trends inferred from homogenized in situ data and reanalysis datasets(Atmosphere-Ocean, 2026) Wang, Xioalan; Feng, Yang; Isaac, Victor; Zwiers, Francis W.; Vincent, Lucie A.; Hartwell, Megan H.This paper describes the development of an updated Canadian homogenized monthly mean wind speed dataset, CanHomW mlyV2, for the period 1953–2023 and characterizes observed changes in surface wind speed across Canada. Hourly data from 154 stations in Canada were first quality controlled and adjusted for any non-standard anemometer heights. Then, monthly mean wind speed series were derived and subject to a semi-automated comprehensive data homogenization procedure to identify and diminish non-climatic changes. The procedure uses a combination of station metadata and multiple statistical tests with and without using reference series. The results of the automated procedure were reviewed manually. All of the 154 data series were identified to have one or more non-climatic changes, which were diminished by quantile matching adjustments. Station relocation and/or joining (i.e. joining of different stations’ data records into one data series), and instrument changes/problems were found to be the main causes of non-climatic changes. The homogenized dataset shows weakening winds in a large part of southern Canada (spanning from the southern Prairies to Labrador) and strengthening winds in most other regions, particularly in the area that spans south-central British Columbia to the Rocky Mountains. The weakening winds in the southern Prairies are also seen consistently in the three modern reanalysis datasets (ERA5, OCADA, 20CRv3), while the four datasets show inconsistent trends in most of the other regions. The Canadian wind trends show notable seasonality, as do the agreement/disagreement among the four datasets.Item Observed changes in Canada's snowfall as inferred from precipitation and daily mean temperatures(Atmosphere-Ocean, 2026) Qian, Budong; Wang, Xiaolan; Zwiers, Francis W.; Feng, YangLimited long-term snowfall observations make it difficult to document how snowfall is changing across Canada. Proxy snowfall measures derived from more plentiful temperature and precipitation may therefore be helpful. We consider simple partitioning of daily precipitation into rainfall and snowfall based on whether temperature is above or below either 0°C or a station specific threshold. Using daily mean temperature and the fixed 0°C threshold resulted in more accurate estimates of annual and seasonal snow-day number and water equivalent snowfall amount than using daily maximum or daily minimum temperature. Using station-specific thresholds further improved estimation accuracy. Trends estimated from these proxy snowfall indices well match those estimated from observed snowfall data for periods and locations when both are available. The median annual proxy snowfall amount in Canada derived from homogenized daily precipitation and temperature data decreased 2.5% per decade over 1949–2023 south of 60°N and increased 0.5% per decade north of 60°N. Seasonally, annual proxy snowfall amount has changed most rapidly in winter, declining 2.6% per decade in southern Canada and increasing 3.6% per decade in northern Canada. This simple approach improves prospects for the continuation of long-term snowfall monitoring in Canada by exploiting long-term daily precipitation and temperature data.Item Precipitation trends in version 2 of the Canadian homogenized monthly precipitation dataset(Atmosphere-Ocean, 2026) Wang, Xiaolan; Feng, Yang; Zwiers, Francis W.; Cheng, VincentThis paper describes the development of two improved Canadian homogenized monthly precipitation datasets, the CanHomP mlyV2 station dataset, which includes the entire data record of 425 long-term stations across Canada (since 1840 or later), and its gridded version CanGridP mlyV2, which covers the entire Canadian land mass for the 1949–2023 period and southern Canada for 1916–2023. The latter is subsequently used to provide updated estimates of Canada's historical precipitation trends with an assessment of trend representativeness. The V2 datasets benefit from the use of improved station data and metadata and an improved data homogenization procedure, which together result in better spatial consistency of trends than seen in unhomogenized data. Estimates of precipitation trends based on CanGridP mlyV2 also exhibit temperature scaling rates that are more in line with physical expectations than the previous versions of gridded precipitation datasets, which exhibited unphysically high temperature scaling rates. Precipitation is estimated to have increased in most areas from southern Nunavut to the Arctic Archipelago and from Labrador to northeastern Quebec in all seasons. It has also increased in a zonal band around 62°N in summer, and in most areas in British Columbia and along the St. Lawrence River in spring and autumn. The most outstanding variation of trends in seasonal precipitation is seen in a broad band across southern Canada, where winter precipitation has decreased significantly without extensively significant changes in the other seasons. The best estimate of increase in the period 1949–2023 is 9.7% for Canada as a whole, 18.9% for Canada's North, and 7.5% for Canada's South. The estimated rate of change in Canada's annual precipitation expressed as a function of surface air temperature change is 4.9% per 1˚C of warming for the period 1949–2023. Over the century-long period 1916–2023, annual precipitation in Canada's South is estimated to have increased 10.7%.Item On the importance of the reference data: Uncertainty partitioning of bias-adjusted climate simulations over eastern Canada(Climate Services, 2025) Lavoie, Juliette; Louis-Philippe, Caron; Logan, Travis; Sobie, Stephen; Turcotte, Richard; Mailhot, Edouard; Pelletier-Dumont, JasmineBias-adjusted climate simulations are increasingly disseminated through online platforms to support adaptation actions. However, there is no consensus on an operational framework to choose what to include in these ‘‘decision-ready’’ ensembles and for communicating the related uncertainty. In this paper, we use a systematic approach to assess the uncertainty related to bias-adjusted climate simulations across five dimensions: internal variability, greenhouse gases scenario, global climate model, observational reference and bias-adjustment method. We calculate the fraction of uncertainty associated with each dimension for precipitation-based, temperature-based and multivariate indicators over eastern Canada and focus particularly on three locations: Montréal, Gaspé and Kawawachikamach. The results show that the uncertainty associated with the reference dataset can be very large and in some instances can become the first or second largest source of uncertainty. Using simple examples, we show that the resulting differences could lead to different conclusions with respect to some adaptation solutions or possibly create confusion with users. These results raise questions on the robustness of climate projections distributed through these web platforms and the ethical responsibility of data providers to adequately evaluate and communicate the underlying uncertainty.Item Dataset of future-shifted weather files for Canada using climate projections from CMIP6(Data in Brief, 2025) Sobie, Stephen; Curry, CharlesInvestigating energy use in new building designs or existing structures in Canada is often performed with energy models that incorporate present-day climate information from the Canadian Weather Year for Energy Calculation 2020 (CWEC2020) weather files. Here we present a new dataset of future-shifted versions of these weather files that have been produced at all CWEC2020 sites across Canada, incorporating projections from the latest generation of climate models from CMIP6. These future-shifted files have been generated using a weather file “morphing” procedure applied to adjust hourly time series of selected thermodynamic variables including dry bulb and dew point temperature, relative humidity, and surface pressure. Projected changes used to calculate morphing factors were taken from CMIP6 global climate models following low, medium and high future emissions pathways (SSP1 2.6, SSP2 4.5, SSP5 8.5). Using the projections from each pathway, future-shifted files have been produced for five future periods from the 2040s through the 2080s. These files facilitate the use of energy modelling to understand building performance and guide design choices for infrastructure under future climate change. All of the future-shifted CWEC2020 files are publicly available via the Pacific Climate Impacts Consortium (PCIC) Weather Files Data Portal at https://www.pacificclimate.org/data/weather-filesItem Effect of human-driven, autonomous, and connected autonomous vehicles on geometric highway design(Alexandria Engineering Journal, 2025) Khan, Zawar Hussain; Ali, Faryal; Altamimi, Ahmed B.; Gulliver, Thomas AaronHighway geometric design plays a crucial role in maintaining traffic safety and operational efficiency. The number of Autonomous Vehicles (AVs) and Connected Autonomous Vehicles (CAVs) on highway networks has increased in recent years. In this study, a traffic model is developed from a spring-mass system theory perspective to investigate traffic dynamics on horizontal highway curves. The Intelligent Driver (ID) model is based on a constant exponent δ to characterize driver response, which is unrealistic. By utilizing a spring-mass system analogy, the proposed model provides a more accurate and realistic representation of traffic. This model is used to evaluate the behavior of Human-driven Vehicles (HVs), AVs, and CAVs over a 1300 m circular road. The results obtained show that CAVs have better performance compared to HVs and AVs on horizontal curves, leading to better understanding of safety and efficiency on roads. Further, CAVs improve energy efficiency and emission reduction, contributing to effective and sustainable transportation systems. In addition, the results indicate that the proposed model has better performance compared to the ID model.Item Constrained estimates of externally forced past and future warming for Canada(Earth's Future, 2025) Li, Tong; Zwiers, Francis W.; Zhang, Xuebin; Wang, XiaolanThe Arctic has experienced the most rapid warming on Earth in recent decades. This affects Canada's landmass, which extends well into the Arctic. Nevertheless, limited spatial and temporal observational coverage, combined with large climate model uncertainties, pose challenges to understanding both past and future climate changes in these regions relative to preindustrial conditions. This is particularly challenging in a place like Canada that has insufficient historical data to determine preindustrial reference conditions. Emergent constraints can overcome this limitation by using historical observations for the modern post‐industrial era to constrain estimates of both preindustrial reference levels and future warming. Here we apply a carefully tested Bayesian observational constraint method to simultaneously assess the externally forced historical and future warming in Canada. Testing indicates that the approach reduces bias and uncertainty in historical and future warming estimates, increasing confidence that it may also serve as a basis for developing a broader understanding of climate change in other high‐latitude regions. We estimate that external forcing from human activity, has warmed Canada by 2.2 [1.3, 3.1]°C between the 1850–1900 pre‐industrial period and the recent 2015–2024 decade. Applying these same observational constraints to future climate conditions indicates that Canada will warm to 5.1 [3.2, 7.0]°C above pre‐industrial levels by the end‐of‐century under an intermediate emissions scenario SSP 2‐4.5, and to 6.7 [4.6, 8.9]°C under a high‐emissions scenario SSP 3‐7.0, with the largest warming projected for Northern Canada, followed by Quebec.Item Multivariate Canadian downscaled climate scenarios for CMIP6 (CanDSC-M6)(Geoscience Data Journal, 2024) Sobie, Stephen; Ouali, Dhouha; Curry, Charles; Zwiers, Francis W.Canada-wide, statistically downscaled simulations of global climate models from the Sixth Coupled Model Inter-comparison Project (CMIP6) have been made available for 26 models using a new multivariate approach and an improved observational target dataset. These new downscaled scenarios comprise daily simulations of precipitation, maximum temperature, and minimum temperature at 1/12° resolution across Canada. Simulations from each of the 26 downscaled global climate models span a historical period (1950–2014), and three future Shared Socio-economic Pathways (SSPs) representing low (SSP1 2.6), moderate (SSP2 4.5) and high (SSP5 8.5) future emissions from 2015 to 2100. Results from an evaluation of the multivariate downscaling method over Canada yield improved performance in replicating multivariate and compound climate indices compared to previously used univariate downscaling methods. This Multivariate Canadian Downscaled Climate Scenarios for CMIP6 (CanDCS-M6) dataset is intended to facilitate climate impacts assessments, hydrologic modelling, and analysis tools for presenting climate projections.Item How are we doing weather forecasts? The Canadian recipe(Pacific Climate Impacts Consortium (PCIC), 2026) Gagnon, Normand; Brunet, GilbertNormand Gagnon, acting director of the Meteorological Research Division, Environment and Climate Change Canada (ECCC), and Dr. Gilbert Brunet, a retired ECCC meteorologist whose career spans over three decades of leadership, research and international collaboration, present "How are we doing weather forecasts? The Canadian recipe." Weather forecasting has evolved greatly in the last decades thanks to increased model realism, computer power and enhanced remote sensing observations. The process of forecasting the atmosphere behavior is complex and it needs big computers to be able to tackle this non-linear process in time to deliver timely useful forecast. The quality of the weather outlooks has improved significantly over the last decades in a quiet revolution. Canadian scientists were pioneers in this endeavor and the Canadian Meteorological Centre in Dorval is among the top 5 best centers in the world. In this talk, the presenters will go thru the actual steps needed to do numerical weather forecasting from ingesting input observations data, preparing the initial conditions and then go forward in the future with a numerical model. The impact of the arrival of Artificial Intelligence in the fields will be discussed as well. There will be a special emphasis on the Canadian contributions to numerical weather and environmental fields.Item PCIC update: February 2026(Pacific Climate Impacts Consortium (PCIC), 2026-02-26) Pacific Climate Impacts Consortium (PCIC)In this issue of the PCIC newsletter, we share updates on: - New high-resolution modelling for understanding how climate change will affect rivers, streams and lakes in BC that will be added to our Salmon Climate Impacts Portal - Understanding past and future warming in Canada for the Canada's Changing Climate Report 2026 - Updates to the National Building Code of Canada 2025 (NBCC2025), which now considers future climate data - Release of Seasonal to Decadal (S2D) data on ClimateData.ca - New publications by PCIC staffItem Rapid attribution of extreme events in Canada(Pacific Climate Impacts Consortium (PCIC), 2026) Gillett, NathanIn recent years, Canada has experienced a number of impactful extreme events, such as the 2021 BC heatwave, which was the deadliest natural disaster on record in Canada, and the 2021 BC floods, which were the costliest natural disaster on record in BC. Quantification of the influence of human-induced climate change on the probability of such extreme events can help inform climate change adaptation and public understanding of the effects of climate change, and such information is much more impactful if available shortly after an event. This has prompted Environment and Climate Change Canada to develop a rapid event attribution system for extreme events in Canada. The system runs automatically on a daily basis and provides information on the human influence on hot extremes, cold extremes and precipitation extremes for extreme events across Canada shortly after they are observed. This talk will describe the current event attribution system, based on existing CMIP6 coupled climate model simulations, and describe its extension to higher resolution atmosphere model simulations using Canadian climate and weather predictions models, which will allow the better representation of impactful phenomena such as atmospheric rivers and post-tropical cyclones. Examples of results for recent extreme events in BC will also be presented.Item Development of freshwater hazard indicators to assess climate change impacts to salmon(Pacific Climate Impacts Constortium (PCIC), 2024) Schnorbus, Markus A.; Schoeneberg (Werner), Arelia T.; Tai, Travis C.; Larabi, Samah; Zeman, LeeThis report details the Development of Freshwater Hazard Indicators to Assess Climate Change Impacts to Salmon.Item Pacific Region VICGL - DynWat Model Deployment(Pacific Climate Impacts Consortium (PCIC), 2024) Schnorbus, Markus A.This report details the development of the VIC-GL - DynWat Model.Item Raven model deployment to select salmon watersheds(Pacific Climate Impacts Consortium, 2023) Schoeneberg (Werner), Arelia T.; Larabi, Samah; Schnorbus, Markus A.This report details Raven Model Deployment to Select Salmon Watersheds.Item PCIC Seminar: "Weather to run: Building climate data infrastructure for science and society"(Pacific Climate Impacts Consortium (PCIC), 2026-01-14) Hiebert, JamesBritish Columbia’s climate varies dramatically over short distances, from coastal rainforests to inland fjords and glaciated alpine terrain. Capturing that variability requires more than static datasets: it demands continuous, high-resolution climate monitoring supported by robust data infrastructure. This talk describes the Provincial Climate Data Set (PCDS)–a product of PCIC and BC’s Climate Related Monitoring Program–as a living, relational database designed to ingest near-real-time observations from many official and operational sources, manage evolving metadata, and track revisions to observations and metadata over time. Using a simple and relatable use case—the percentage of “runnable” days per year defined by temperature and precipitation thresholds–this talk demonstrates how structured, provenance-aware climate data enable reproducible analysis across stations, regions, and decades. The example illustrates why relational data models, change tracking, and sustained technical investment are essential for trustworthy climate services. While the case study is grounded in everyday experience, the underlying message is serious: decisions affecting safety, infrastructure, and livelihoods rely on climate data that can accommodate variability, uncertainty, and change.Item PCIC Update: December 2025(Pacific Climate Impacts Consortium, 2025-12-22) Pacific Climate Impacts ConsortiumThis issue of the PCIC Update includes the following stories: - BC Risk and Resilience Assessment Released - Continued Outreach to Small, Rural and Remote BC Communities - ClimateData.ca Version 2 Launched - New PCIC Corporate Report Released - PCIC Science Brief on Potential Changes to Internal Climate Variability - Website Launch - Staff profile: Ed Beard - The Pacific climate seminar series - PCIC staff news - PublicationsItem Anthropogenic influence on altitudinally amplified temperature change in the Tibetan Plateau(IOP Science, 2024) Sun, Ying; Hu, Ting; Zhang, XuebinAs the highest plateau on the Earth, the Tibetan Plateau (TP) has experienced rapid warming in the last decades, affecting natural ecosystem and water resources extending far beyond the plateau itself. A distinctive characteristic known as elevation-dependent warming (EDW) in the high mountain regions was particularly pronounced in the TP, whereby the magnitude of temperature warming was amplified with increasing altitudes. Different mechanisms have been proposed to explain this phenomenon, however, the link between the root cause of warming, human activities, and the EDW remains poorly understood. Here we used the homogenized observation and simulations by the newest climate models to discern human influence on both mean and extreme temperatures within the region. An optimal fingerprinting method was applied in a vertical space rather than in traditional horizontal space. We found that the long-term trends in mean and extreme temperature amplified with increasing elevation, with larger magnitude of trends at higher elevations. The response to external forcing, primarily driven by human activities, was robustly detected in altitudinal amplification of temperature increase, providing clear evidence of human causes of EDW. As warming increases, the EDW in the region will continue, with more pronounced EDW corresponding to larger magnitude of warming under a high emission scenario. These findings mark the first evidence of human influence on temperature across different vertical altitudes of climate system.Item Do meteorological, agricultural, and hydrological indicators all point to an increased frequency and intensity of droughts across Canada under a changing climate?(Atmosphere-Ocean, 2025) Bonsal, Barrie; Tam, Benita; Zhang, Xuebin; Li, Guilong; Philps, Lisa; Rong, RobinDroughts, one of the most significant natural hazards, are complex in nature with varying definitions typically tailored to the timing and/or duration of the episode along with associated impacts. Although previous investigations have assessed future drought occurrence across Canada, none have comprehensively and collectively assessed changes to meteorological, agricultural, and hydrological drought indicators using CMIP6 GCM projections. The main objective of this study was to assess future drought conditions across Canada at various temporal scales using standardized indices representing meteorological, agricultural, and hydrological droughts under multiple shared socio-economic pathways for the near (2041–2060) and far (2081–2100) future. On an annual basis, projected changes to all three drought indicators signify increased drying across the Prairies, portions of interior British Columbia, and most of Ontario. This drying is greater and covers more of the country during the warm season (April to September), while in summer and to a lesser extent autumn, widespread changes are only projected for meteorological and agricultural indicators. In spring, increased dry conditions are only prevalent in meteorological and hydrological indices. The cold season of October to March essentially shows little to no drying in any type of drought. Changes in all drought indices are amplified for higher SSPs and during the late century. This study improves an understanding of the spatial and temporal variations in projected changes to various drought types across Canada in response to human-induced warming. While results from this analysis are applicable for nation-wide drought assessments and drought management plans, they are less suitable for application at local scales where more detailed modelling may be required.