Publications Library

This study evaluates regional-scale projections of climate indices that are relevant to climate change impacts in Canada. We consider indices of relevance to different sectors including those that describe heat conditions for different crop types, temperature threshold exceedances relevant for human beings and ecological ecosystems such as the number of days temperatures are above certain thresholds, utility relevant indices that indicate levels of energy demand for cooling or heating, and indices that represent precipitation conditions. Results are based on an ensemble of high-resolution statistically downscaled climate change projections from 24 global climate models (GCMs) under the RCP2.6, RCP4.5, and RCP8.5 emissions scenarios. The statistical downscaling approach includes a bias-correction procedure, resulting in more realistic indices than those computed from the original GCM data. We find that the level of projected changes in the indices scales well with the projected increase in the global mean temperature and is insensitive to the emission scenarios. At the global warming level about 2.1 °C above pre-industrial (corresponding to the multi-model ensemble mean for 2031–2050 under the RCP8.5 scenario), there is almost complete model agreement on the sign of projected changes in temperature indices for every region in Canada. This includes projected increases in extreme high temperatures and cooling demand, growing season length, and decrease in heating demand. Models project much larger changes in temperature indices at the higher 4.5 °C global warming level (corresponding to 2081–2100 under the RCP8.5 scenario). Models also project an increase in total precipitation, in the frequency and intensity of precipitation, and in extreme precipitation. Uncertainty is high in precipitation projections, with the result that models do not fully agree on the sign of changes in most regions even at the 4.5 °C global warming level.

The Fraser Valley Climate Adaptive Drainage Management Forum project was initiated to generate and share the best available precipitation projections for the Fraser Valley; research collaborative climate adaptive drainage management strategies adopted in comparable settings; and host a Forum between producers, local government and agency staff, researchers and agricultural association representatives to deliberate preferred drainage management strategies to address local runoff and drainage challenges.

Since local weather and climate greatly affect the construction and performance of buildings, reliable meteorological
data is essential when simulating building performance. It is well understood that climate change will affect future
weather and there is a growing interest in generating future weather files to support climate resilient building design.
Weather files that account for climate change have not been widely used for the lower mainland region of British
Columbia. In this study, hourly weather files for future climate conditions in Vancouver are created for three time periods
using a “morphing” methodology. Morphing uses results from global climate models to adjust observed weather data
at a specific location. In this study, daily data from climate simulations for the RCP8.5 emission scenario have been
used. The weather variables that have been adjusted are dry-bulb temperature, relative humidity, solar radiation, cloud
cover, wind speed and atmospheric pressure. The impact of climate change on the energy performance of a multi-unit
residential building located on the University of BC campus is analyzed using the energy modelling software
EnergyPlus. The simulation results indicate that the changing climate in Vancouver, following RCP8.5, would have a
considerable effect on building energy performance and energy demand due to decrease in space heating and increase
in cooling requirements.

Parties to the United Nations Framework Convention on Climate Change have agreed to hold the “increase in global average temperature to well below 2°C above preindustrial levels and to pursue efforts to limit the temperature increase to 1.5°C.” Comparison of the costs and benefits for different warming limits requires an understanding of how risks vary between warming limits. As changes in risk are often associated with changes in exposure due to projected changes in local or regional climate extremes, we analyze differences in the risks of extreme daily temperatures and extreme daily precipitation amounts under different warming limits. We show that global warming of 2°C would result in substantially larger changes in the probabilities of the extreme events than global warming of 1.5°C. For example, over the global land area, the probability of a warm extreme that occurs once every 20 years on average in the current climate is projected to increase 130% and 340% at the 1.5°C and 2.0°C warming levels, respectively (median values). Moreover, the relative changes in probability are larger for rarer, more extreme events, implying that risk assessments need to carefully consider the extreme event thresholds at which vulnerabilities occur.

Two recent articles in the journal Climatic Change examine some of the effects that climate change may have on agriculture in the Pacific Northwest.

Focusing on specialty fruit production, Houston et al. (2018) find that overall warmer conditions and reduced water availability may reduce net returns on crops due to increasing farming costs, affecting yields and altering product quality. They suggest that management strategies currently employed in marginal production areas that moderate temperatures and offset mismatches between the needs of the plant at various growth stages and seasonal weather conditions may be useful adaptation strategies.

Neibergs and colleagues (2018) review the impacts of climate change on beef cattle production. They find that changes to seasonal temperature and precipitation may affect the availability of the plants on which cattle forage. This in turn could affect the number of cattle that an area can support, and the dates at which cattle are "turned-out" to pasture and taken in from pasture.

Tardive frosts, i.e. frost events occurring after grapevine budburst, are a significant risk for viticultural practices, which have recently caused substantial yield losses over different winegrowing regions of France, e.g. in 2016 and 2017. So far, it is unclear whether the frequency of late frosts events is destined to increase or decrease under future climatic conditions. Here, we assess the risk of tardive frosts for the French vineyards throughout the 21st century by analyzing temperature projections from eight climate models and their statistical regional downscaling. Our approach consists in comparing the statistical occurrences of the last frost (day of the year) and the characteristic budburst date for nine grapevine varieties as simulated by three different phenological models. Climate models qualitatively agree in projecting a gradual increase in temperature all over the France, which generally produces both an earlier characteristic last frost day and an earlier characteristic budburst date. However, the latter notably depends on the specific phenological model, implying a large uncertainty in assessing the risk exposure. Overall, we identified Alsace, Burgundy and Champagne as the most vulnerable regions, where the probability of tardive frost is projected to significantly increase throughout the 21st century for two out of three phenological models. The third phenological model produces opposite results, but the comparison between simulated budburst dates and observed records over the last 60 years suggests its lower reliability. Nevertheless, for a more trustworthy risk assessment, the validity of the budburst models should be accurately tested also for warmer climate conditions, in order to narrow down the associated large uncertainty.

Three recent journal articles examine the rate of sea level rise and the ability of models to accurately simulate sea level rise at a global and regional scale.

Publishing in Geophysical Research Letters, Yi et al. (2017) examine the rate at which sea level rise is accelerating and find that the rate of acceleration over the 2005-2015 period is three times faster than it was over the 1993-2014 period and an order of magnitude larger than the acceleration over the 1920-2011 period. They also identify three primary contributors to this acceleration: the thermal expansion of sea water, reduced storage of water on land and the melting of ice on land.

In a pair of articles published in the Journal of Climate, Slangen et al. (2017) and Meyssignac et al. (2017) analyze the of climate models to simulate both global and regional sea level rise. They find that simulations can only explain about half (50% ± 30%) of the observed sea level rise. After bias corrections are included for the Greenland ice sheet and the possibility that ice sheets and the deep ocean were not in equilibrium with the 20th Century climate, the models explain about three-quarters (75% ± 38%) of the observed 20th Century sea level rise and all (105% ± 35%) of the observed sea level rise over the period from 1993-1997 to 2011-2015 period. Regionally, climate models underestimate the amount of sea level rise that occured, but do show reasonable agreement for interannual and multidecadal variability. When the same bias corrections are applied, the models come into closer agreement with observations. In addition, they find that the spatial variability in regional sea level rise is largely due to the thermal expansion of sea water and ongoing isostatic adjustment resulting from the end of the last glacial period.

Extratropical cyclones (ETCs) intensify due to three vertically interacting positive potential vorticity anomalies that are associated with warm temperature anomalies at the surface, condensational heating in the lower-level atmosphere, and stratospheric intrusion in the upper-level atmosphere. It remains unclear how much each mechanism contributes to ETC intensification, as results from case studies are conflicting and a climatological assessment has not yet been done. Such a climatology would be useful for identifying sources of ETC biases and uncertainties in global climate models (GCMs). To fill this gap, this study presents the first climatology of mechanisms that generate intense ETCs in the Northern Hemisphere for the period 1980 to 2016 (3273 ETCs). Using piecewise potential vorticity inversion, I show that the lower level contributes most to maximum ETC intensification (52%), followed by the upper level (26%), and the surface (22%). These values vary during the last 36 hours prior to maximum ETC intensity, with decreasing surface contributions (from 35% to 22%) and increasing upper-level contributions (from 13% to 26%). The dominance of the lower level applies to 74% of ETCs, followed by the upper level (18% of ETCs) and the surface (8% of ETCs). Upper-level contributions are stronger in eastern than in western ocean basins, while the opposite applies to surface and lower-level contributions. This is consistent with regional patterns of potential vorticity anomalies, which, as discussed, may be associated with Rossby wave breaking and western boundary currents. The ability of GCMs to reproduce the mechanisms quantified in this study remains to be assessed.

A critical question for climate mitigation and adaptation is to understand when and where the signal of changes to climate extremes have persistently emerged or will emerge from the background noise of climate variability. Here we show observational evidence that such persistent changes to temperature extremes have already occurred over large parts of the Earth. We further show that climate models forced with natural and anthropogenic historical forcings underestimate these changes. In particular, persistent changes have emerged in observations earlier and over a larger spatial extent than predicted by models. The delayed emergence in the models is linked to a combination of simulated change (‘signal’) that is weaker than observed, and simulated variability (‘noise’) that is greater than observed. Over regions where persistent changes had not occurred by the year 2000, we find that most of the observed signal-to-noise ratios lie within the 16–84% range of those simulated. Examination of simulations with and without anthropogenic forcings provides evidence that the observed changes are more likely to be anthropogenic than nature in origin. Our findings suggest that further changes to temperature extremes over parts of the Earth are likely to occur earlier than projected by the current climate models.