Publications Library

To improve local understanding and manage the impacts of atmospheric river events, the B.C. Ministry of Environment commissioned work to summarize the current state of knowledge pertaining to BC on this topic and conduct a multi-agency qualitative risk assessment.
In April 2013, scientists and researchers gathered in Victoria, B.C. to review and summarize the current state of knowledge on atmospheric rivers. As a result of their efforts, the Pacific Climate Impacts Consortium and Pinna Sustainability produced this "Atmospheric River State of Knowledge Report."

The discrepancy between recent observed and simulated trends in global mean surface temperature has provoked a debate about possible causes and implications for future climate change projections. However, little has been said in this discussion about observed and simulated trends in global temperature extremes. Here we assess trend patterns in temperature extremes and evaluate the consistency between observed and simulated temperature extremes over the past four decades (1971–2010) in comparison to the recent 15 years (1996–2010). We consider the coldest night and warmest day in a year in the observational dataset HadEX2 and in the current generation of global climate models (CMIP5). In general, the observed trends fall within the simulated range of trends, with better consistency for the longer period. Spatial trend patterns differ for the warm and cold extremes, with the warm extremes showing continuous positive trends across the globe and the cold extremes exhibiting a coherent cooling pattern across the Northern Hemisphere mid-latitudes that has emerged in the recent 15 years and is not reproduced by the models. This regional inconsistency between models and observations might be a key to understanding the recent hiatus in global mean temperature warming.

A recent meta-analysis published in the journal Nature Climate Change, by Challinor et al. (2014) examines 1,722 crop model simulations, run using global climate model output under several emissions scenarios, to evaluate the potential effects of climate change and adaptation on crop yield. The authors find that, without adaptation, projected corn, rice and wheat production is reduced when areas experience 2.0 °C or more of local warming, with losses greater in the second half of the century due to larger changes in climate. Crop-level adaptations are projected to be able to increase yields by an average of 7-15% when compared to similar scenarios that do not utilize adaptation. Projections indicate that adaptation may be more successful for wheat and rice than for corn. Though less data is available on yield variability, Challinor et al. find that it is likely to increase.

This study analyzed potential hydroclimatic change in the Peace River basin in the province of British Columbia, Canada, based on two structurally different approaches: (i) statistically downscaled global climate models (GCMs) using the bias-corrected spatial disaggregation (BCSD) and (ii) dynamically downscaled GCM with the Canadian Regional Climate Model (CRCM). Additionally, simulated hydrologic changes from the GCM–BCSD-driven Variable Infiltration Capacity (VIC) model were compared to the CRCM integrated Canadian Land Surface Scheme (CLASS) output. The results show good agreements of the GCM–BCSD–VIC simulated precipitation, temperature, and runoff with observations, while the CRCM-simulated results differ substantially from observations. Nevertheless, differences (between the 2050s and 1970s) obtained from the two approaches are qualitatively similar for precipitation and temperature, although they are substantially different for snow water equivalent and runoff. The results obtained from the five Coupled Global Climate Model, version 3, (CGCM3)-driven CRCM runs are similar, suggesting that the multidecadal internal variability is not a large source of uncertainty for the Peace River basin. Overall, the GCM–BCSD–VIC approach, for now, remains the preferred approach for projecting basin-scale future hydrologic changes, provided that it explicitly accounts for the biases and includes plausible snow and runoff parameterizations. However, even with the GCM–BCSD–VIC approach, projections differ considerably depending on which of an ensemble of eight GCMs is used. Such differences reemphasize the uncertain nature of future hydroclimatic projections.

It is a common practice to employ hydrologic models for assessing alterations to streamflow as a result of anthropogenically driven changes, such as riverine, land use, and climate change. However, the ability of the models to replicate different components of the hydrograph simultaneously is not clear. Hence, this study evaluates the ability of a standard hydrologic model set-up: Variable Infiltration Capacity (VIC) hydrologic model for two headwater sub-basins in the Fraser River (Salmon and Willow), British Columbia, Canada, with climate inputs derived from observations and statistically downscaled global climate models (GCMs); to simulate six general water resource indicators (WRIs) and 32 ecologically relevant indicators of hydrologic alterations (IHA). The results show a generally good skill of the observation-driven VIC model in replicating most of the WRIs and IHAs. Although the WRIs, including annual volume, centre of timing, and seasonal flows, and the IHAs, including maximum and minimum flows, were reasonably well replicated, statistically significant differences in some of the monthly flows, number and duration of flow pulses, rise and fall rates, and reversals were noted. In the case of GCM-driven results, additional monthly, maximum, and minimum flow indicators produced statistically significant differences. A number of issues with the model input/output data, hydrologic model parametrization and structure as well as downscaling methods were identified, which lead to such discrepancies. Therefore, there is a need to exercise caution in the use of model-simulated indicators. Overall, the WRIs and IHAs can be useful tools for evaluating changes in an altered hydrologic system, provided the skill and limitations of the model in replicating these indicators are understood.

Hydrologic modelling has been applied to assess the impacts of projected climate change within three study areas in the Peace, Campbell and Columbia River watersheds of British Columbia, Canada. These study areas include interior nival (two sites) and coastal hybrid nival–pluvial (one site) hydro-climatic regimes. Projections were based on a suite of eight global climate models driven by three emission scenarios to project potential climate responses for the 2050s period (2041–2070). Climate projections were statistically downscaled and used to drive a macro-scale hydrology model at high spatial resolution. This methodology covers a large range of potential future climates for British Columbia and explicitly addresses both emissions and global climate model uncertainty in the final hydrologic projections. Snow water equivalent is projected to decline throughout the Peace and Campbell and at low elevations within the Columbia. At high elevations within the Columbia, snow water equivalent is projected to increase with increased winter precipitation. Streamflow projections indicate timing shifts in all three watersheds, predominantly because of changes in the dynamics of snow accumulation and melt. The coastal hybrid site shows the largest sensitivity, shifting to more rainfall-dominated system by mid-century. The two interior sites are projected to retain the characteristics of a nival regime by mid-century, although streamflow-timing shifts result from increased mid-winter rainfall and snowmelt, and earlier freshet onset.