Publications Library

Highlights:
Improve the estimation of water temperature extremes at ungauged sites.
Incorporate non-linearities in the homogenous region delineation step using NLCCA.
Consider non-linear models in the whole estimation procedure (NLCCA + GAM).
Compare fully and partially non-linear approaches for water temperature regionalization.
The results underline the importance of considering the non-linearity of thermal processes.

El Niño–Southern Oscillation (ENSO) has a profound influence on the occurrence of extreme precipitation events at local and regional scales in the present-day climate, and thus it is important to understand how that influence may change under future global warming. We consider this question using the large-ensemble simulations of CESM2, which simulates ENSO well historically. CESM2 projects that the influence of ENSO on extreme precipitation will strengthen further under the SSP3–7.0 scenario in most regions whose extreme precipitation regimes are strongly affected by ENSO in the boreal cold season. Extreme precipitation in the boreal cold season that exceeds historical thresholds is projected to become more common throughout the ENSO cycle. The difference in the intensity of extreme precipitation events that occur under El Niño and La Niña conditions will increase, resulting in “more extreme and more variable hydroclimate extremes.” We also consider the processes that affect the future intensity of extreme precipitation and how it varies with the ENSO cycle by partitioning changes into thermodynamic and dynamic components. The thermodynamic component, which reflects increases in atmospheric moisture content, results in a relatively uniform intensification of ENSO-driven extreme precipitation variation. In contrast, the dynamic component, which reflects changes in vertical motion, produces a strong regional difference in the response to forcing. In some regions, this component amplifies the thermodynamic-induced changes, while in others, it offsets them or even results in reduction in extreme precipitation variation.

The projected increase in the frequency and intensity of extreme heat events due to climate change means an associated increase in risk of heat-related illnesses and mortality. Public health systems need to be prepared to identify and reduce the susceptibility of vulnerable populations to increased occurrence of heat-related illness and stress. To facilitate this, climate services have begun developing climate change projections for heat-stress indices based on exceedances of thresholds used operationally in meteorological heat warning systems. This task is complicated by the fact that heat-stress indices are generally computed using hourly data whereas climate model outputs are often archived at daily or longer time steps. This study focuses on Humidex, a heat-stress index used in heat alerts issued by the Meteorological Service of Canada. Several potential solutions for computing robust Humidex indices using daily data are examined, including a new approximation method. Indices obtained with the new method are compared with indices obtained using the classic method based on hourly data as well as with other two methods based on average daily values. The new approximation gives good estimations for humidex indices, while the daily-average-value methods present biases with respect to the hourly-value method.

Towards the end of June 2021, temperature records were broken by several degrees Celsius in several cities in the Pacific Northwest areas of the US and Canada, leading to spikes in sudden deaths and sharp increases in emergency calls and hospital visits for heat-related illnesses. Here we present a multi-model, multi-method attribution analysis to investigate the extent to which human-induced climate change has influenced the probability and intensity of extreme heat waves in this region. Based on observations, modelling and a classical statistical approach, the occurrence of a heat wave defined as the maximum daily temperature (TXx) observed in the area 45–52∘ N, 119–123∘ W, was found to be virtually impossible without human-caused climate change. The observed temperatures were so extreme that they lay far outside the range of historical temperature observations. This makes it hard to state with confidence how rare the event was. Using a statistical analysis that assumes that the heat wave is part of the same distribution as previous heat waves in this region led to a first-order estimation of the event frequency of the order of once in 1000 years under current climate conditions. Using this assumption and combining the results from the analysis of climate models and weather observations, we found that such a heat wave event would be at least 150 times less common without human-induced climate change. Also, this heat wave was about 2 ∘C hotter than a 1-in-1000-year heat wave would have been in 1850–1900, when global mean temperatures were 1.2 ∘C cooler than today. Looking into the future, in a world with 2 ∘C of global warming (0.8 ∘C warmer than today), a 1000-year event would be another degree hotter. Our results provide a strong warning: our rapidly warming climate is bringing us into uncharted territory with significant consequences for health, well-being and livelihoods. Adaptation and mitigation are urgently needed to prepare societies for a very different future.

Study region:
Nechako Reservoir, British Columbia, Canada.

Study focus:
Hydrological regulation affect both hydrological and thermal conditions in the reservoir and downstream reach, subsequently disrupting fish habitats. This paper aims at developing an integrated model simulating physical processes that govern the quantity and quality of inflow, reservoir, and outflow water of the Nechako Reservoir. Such a model would help stakeholders understand the response of in-reservoir water temperature stratification and downstream water temperature to changes in inflow and reservoir operation under future climate change.

New hydrological insights for the region:
The model was calibrated against historical reservoir levels and in-reservoir and outlet water temperature field data. The integrated model simulated accurately the wide variation of reservoir levels as well as the in-reservoir water temperature at Kenney Dam and the outlet temperature. Sensitivity analysis shows that reservoir water temperature particularly the epilimnion is sensitive to changes in both meteorological and hydrological forcing. Forcing the model with different outflow scenarios shows the weak sensitivity of temperature of water released to outflow rates. Given epilimnion water releases at the spillway, the Summer Temperature Management Program could be inefficient to provide cool water in the Nechako River during the critical period of salmon migration in a warming climate. However, colder water remains available at depth at Kenney Dam to potentially mitigate and better control downstream water temperature.

This article focuses on the importance of collaboration in statistics by Canadian researchers and highlights the contributions that Canadian statisticians have made to many research areas in environmetrics. We provide a discussion about different vehicles that have been developed for collaboration by Canadians in the environmetrics context as well as specific scientific areas that are focused on environmetrics research in Canada including climate science, forestry, and fisheries, which are areas of importance for natural resources in Canada.

Nocturnal warming events (NWEs) are abrupt interruptions in the typical cooling of surface temperatures at night. Using temperature time series from the high-resolution Vancouver Island School-Based Weather Station Network (VWSN) in British Columbia, Canada, we investigate temporal and spatial characteristics of NWEs. In this coastal region, NWEs are more frequently detected in winter than in summer, with a seasonal shift from slowly warming NWEs dominating the winter months to rapidly warming NWEs dominating the summer months. Slow-warming NWEs are of relatively small amplitude and exhibit slow cooling rates after the temperature peaks. In contrast, fast-warming NWEs have a temperature increase of several kelvins with shorter-duration temperature peaks. The median behavior of these distinct NWE classes at individual stations is similar across the entire set of stations. The spatial synchronicity of NWEs across the VWSN (determined by requiring NWEs at station pairs to occur within given time windows) decreases with distance, including substantial variability at nearby stations that reflects local influences. Fast-warming NWEs are observed to occur either simultaneously across a number of stations or in isolation at one station. Spatial synchronicity values are used to construct undirected networks to investigate spatial connectivity structures of NWEs. We find that, independent of individual seasons or NWE classes, the networks are largely unstructured, with no clear spatial connectivity structures related to local topography or direction.

This report, the second volume in the VIC Generation 2 deployment reports, provides a description of modelling glacier dynamics with the HydroConductor Model.

This, the fifth volume in the VIC Generation 2 deployment reports, provides a description of model calibration.