Climate change is a major concern for freshwater allocation and management, but there is a lack of attention regarding how water impoundment impacts boreal climate at the intersection of mountain topography. We explore how the local climate was affected by the construction of one of North America’s largest reservoirs, the Williston Hydropower Reservoir, in British Columbia’s Rocky Mountain Trench. High-resolution simulations of the Weather Research and Forecasting model over a 10-year period were used to analyze differences in mean meteorological states with and without the reservoir represented in the landscape. Relative to terrain without the Williston Reservoir, autumn precipitation increased by up to 30 mm (11.5

Abstract Environmental modelling of remote areas requires dynamical downscaling of meteorological data to obtain precipitation values that could substitute for sparse in‐situ observations. This study examined numerical simulations of precipitation over the Terrace‐Kitimat Valley, an industrializing corridor in the Coast Mountains of northern British Columbia, Canada. Modelling uncertainty was explored for 1 year of output from the Weather Research and Forecasting model at 1‐km grid spacing for three atmospheric forcing datasets and two planetary boundary layer (PBL) schemes. The observed total precipitation ranged from 1170 to 2380 mm and was often underestimated by more than 40% when using the North American Regional Reanalysis as atmospheric forcing data or the Mellor‐Yamada‐Nakanishi‐Niino level 3 (MYNN3) parameterization as PBL scheme. Persistent low bias from model configurations using these configurations suggested that merely selecting an alternative atmospheric forcing dataset does not ameliorate systematic error occasioned by a poorly performing PBL parameterization. Hence, the choice of the PBL scheme and the meteorological dataset is important for spatial estimation of precipitation using WRF. Model output best corresponded with annual gauge measurements when simulations with the Mellor‐Yamada‐Janjić (MYJ) PBL scheme were forced with ERA5. The North American Mesoscale Analyses (NAM‐ANL) however demonstrated better performance for monthly variation and high‐intensity precipitation than ERA5. Using both datasets therefore may be valuable for calculations related to environmental change. With either NAM‐ANL or ERA5 as atmospheric forcing data and MYJ as the PBL scheme, the uncertainty in annual simulated precipitation amount ranged between 38% overestimation and 21% underestimation of observational data.

Four correction models with differing forms were developed on a training dataset of 32 PurpleAir–Federal Equivalent Method (FEM) hourly fine particulate matter (PM2.5) observation colocation sites across North America (NA). These were evaluated in comparison with four existing models from external sources using the data from 15 additional NA colocation sites. Colocation sites were determined automatically based on proximity and a novel quality control process. The Canadian Air Quality Health Index Plus (AQHI+) system was used to make comparisons across the range of concentrations common to NA, as well as to provide operational and health-related context to the evaluations. The model found to perform the best was our Model 2, PM2.5-corrected=PM2.5-cf-1/(1+0.24/(100/RH%-1)), where RH is limited to the range [30 %,70 %], which is based on the RH growth model developed by Crilley et al. (2018). Corrected concentrations from this model in the moderate to high range, the range most impactful to human health, outperformed all other models in most comparisons. Model 7 (Barkjohn et al., 2021) was a close runner-up and excelled in the low-concentration range (most common to NA). The correction models do not perform the same at different locations, and thus we recommend testing several models at nearby colocation sites and utilizing that which performs best if possible. If no nearby colocation site is available, we recommend using our Model 2. This study provides a robust framework for the evaluation of low-cost PM2.5 sensor correction models and presents an optimized correction model for North American PurpleAir (PA) sensors.

Computational tools used to implement the critical-load approach of atmospheric deposition impact often do not elucidate modeling uncertainty making it difficult for environmental policy-makers to know how much confidence to put in its results, also hampering aspects that may need improving. This study evaluated acid deposition modeling for various parameterization of the planetary boundary-layer (PBL) over the Terrace-Kitimat valley, a physiographically complex region of northwestern British Columbia. Of five schemes, simulations with the Mellor-Yamada-Nakanishi-Niino Level 3 and Mellor-Yamada-Janjic PBL schemes best captured weekly wet deposition fluxes of acidifying ions (SO42-, NO3-, NH4+) within a factor of 2 of observations at an industrial fence line station. Alongside the Yonsei University PBL scheme, these two schemes slightly overestimated the chemical species at a station that was distant from major anthropogenic precursor sources in the valley, hence useful for worst-scenario projections of atmospheric deposition on the natural environment. Forest soils in the vicinity of a large aluminum smelter in Kitimat was estimated to be in exceedance of critical load of acidity by 30.1-53.5 kg S ha(-1) yr(-1). Exceedance of critical load of nutrient nitrogen restricted to the Terrace area (<= 7 km(2)), ranged between none and 0.71 kg ha(-1) yr(-1). This work provides guidance for using PBL schemes in the Weather Research and Forecasting model that is coupled to a deposition model when calculating critical-load exceedance over temperate, rugged, coastal geographies.

In this study, the GOSAT Proxy Retrieval (v9.0) data product of column‐averaged dry‐air mole fractions of atmospheric methane (XCH 4 ) for the period 2009–2019 was analyzed to detect methane (CH 4 ) trends in the three western Canadian provinces where oil and gas development activities have changed significantly over the last decade. Although we found statistically significant increasing XCH 4 trends in all subdomains (northeast British Columbia‐NE, Alberta‐AB, southern Saskatchewan‐SK), XCH 4 trends are not higher than the background trend (7.25 ± 0.30 ppb/yr) and enhancement trends (ΔXCH 4 , after removing the background quantity) are not detectable at any subdomain during 2009–2019. For further insight into trends in all subdomains, we divided the whole period (2009–2019) into two shorter periods (2009–2013 and 2014–2019) and estimated trends. We found XCH 4 trends are higher than background trends particularly in the AB and SK subdomains during 2009–2013, and their ΔXCH 4 trends are positive and also marginally statistically significant. However, we do not find any detectable ΔXCH 4 trend if we consider either long‐term (2009–2019) or the second shorter period (2014–2019), suggesting local emission sources are dominating year to year fluctuation. From the source attribution analysis, we found both wetland and oil and gas sectors are controlling the CH 4 growth rate in western Canada, but the oil and gas sector is the dominant driver in NE and SK subdomains. We also found the satellite‐based average ΔXCH 4 trend (15.43 ± 8.19%/yr) between 2009 and 2013 likely reflects a trend in oil and gas CH 4 emissions in AB and SK for the same period.

anl_6MYJdiv and anl_6MYNNdiv contains pairwise normalizations of dataset outputs (NAM/ERA5, NAM/NARR and ERA5/NARR) of total rainfall in 2017 for simulations with the MYJ and MYNN3 PBL schemes, that can be plotted by fig3_4.ncl. anl_MYJMYNN_div contains MYJ/MYNN3 spatial contours for each of ERA5, NAM -ANL and NARR outputs. anl_snow_MYJ contains MYJ output for total snow in 2017 by the ERA5, NAM-ANL and NARR datasets, for which values at discrete locations can be retrieved with yr2017snow.ncl, daily_ppt.ncl is script to extract modeled daily precipitation (dly_MYJ and dly_MYNN) from the various locations. Fig_ppt_monthly.R is the plotting script for observed and modeled precipitation time series from hydro31pt1pk.txt. nullwrf is array holder for plotting with ncl scripts. rivs_coasts.shp is shape file that is used in the spatial plots.

Chemical transport models (CTM) can have large biases and errors when simulating pollutant concentrations. To improve the characterization of fine particulate matter (PM2.5) over complex terrain for exposure assessments, three mathematical formulae that utilized the relationship between modeled and observed quantile concentrations at a monitor location were developed. These were then applied to 1 year of CMAQ model output of PM2.5 over the Terrace-Kitimat Valley of northwestern British Columbia, Canada. The final products enhanced the representation of ambient levels at existing monitoring stations when evaluated with conventional statistical measures. Better agreement of corrected outputs with observed compliance metrics was also found. On average, the absolute errors of amended outputs were 11% and 10% for the annual mean PM2.5 and 98th percentiles of daily concentrations, respectively, compared to 45% and 61%, respectively, in the original outputs. These improvements provided greater confidence to use the amended outputs to estimate concentrations at locations without monitors. The predominance of pristine conditions in the modeling domain was exploited to derive annual background PM2.5 concentrations over the valley, which was estimated to be 2.0-2.3 mu g m(-3). To our knowledge, this is the first study to calculate background PM2.5 concentrations over northern BC coastlands using bias-corrected outputs from an air quality model. Implications: Bias correction of CMAQ model output was necessary for assessing regulatory compliance for ambient PM2.5. The implications are notable. First, for low to moderate spatial heterogeneity in monitoring data, the use of regression equations that relates quantile mean concentrations of model outputs to those of observational data enhances the estimation of PM2.5 at unmonitored locations. Second, by providing spatial pollutant distribution ahead of planned industrial development in Terrace-Kitimat Valley (TKV), corrected model output offers a baseline for tracking progress in airshed management. Third, correction improved pollutant exposure classification, for which the risk was predominantly low. Finally, 2.0-2.3 mu g m(-3) should be considered as PM2.5 concentrations that are irreducible when setting voluntary targets for ambient levels in the area.

Excitation of basin-scale, internal waves (i.e., internal seiches) in lakes require spatially homogeneous wind fields that vary on time scales comparable to the seiche period, which can be on the order of several days in large lakes. We evaluate 2 years (October 1, 2016 to September 30, 2018) of 15-min wind data from a shore-based meteorological station to identify strong wind episodes likely to excite internal seiches in a large and geometrically complex lake surrounded by convoluted topography, Quesnel Lake, British Columbia, Canada. Our findings include the identification of strong wind event seasonality, with peak mean monthly wind speeds in April and November, and minimum mean monthly wind speeds in August. Using geopotential heights (GPHs) from 1.5 degrees x 1.5 degrees gridded reanalysis data to reconstruct the atmospheric state for each strong wind episode, two primary synoptic patterns are identified that, in conjunction with local topographic channelling, lead to either easterlies or westerlies occurring at our sampling station, with strong easterly episodes three times more frequent than westerly episodes. This highlights the important role that developing low-pressure systems in the Northeastern Pacific Basin have in setting up the GPH gradient required for persistent strong winds at Quesnel Lake, in the hours and days before these storms make landfall. The projection of synoptic patterns of strong wind events onto a 4 x 3 self-organizing map clustered strong wind events by mean wind direction, similar to the results of a manual classification. Methods to identify the strong wind episodes and the resulting self-organizing map are both evaluated in-part by two case studies where strong winds are known to have excited a basin-scale baroclinic response in Quesnel Lake.

Glaciers are commonly located in mountainous terrain subject to highly variable meteorological conditions. High resolution meteorological (HRM) data simulated by atmospheric models can complement meteorological station observations in order to assess changes in glacier energy fluxes and mass balance. We examine the performance of two snow models, SnowModel and Alpine3D, forced by different meteorological data for winter mass balance simulations at four glaciers in the Canadian portion of the Columbia Basin. The Weather Research and Forecasting model (WRF) with resolution of 1 km and the North American Land Data Assimilation System with similar to 12 km resolution, provide HRM data for the two snow models. Evaluation is based on the ability of the snow models to simulate snow depth at both point locations (automated snow weather stations) and over the entire glacier surface (airborne LiDAR [Light Detection and Ranging] surveys) during the 2015/2016 winter accumulation. When forced with HRM data, both models can reproduce snow depth to within +/- 15% of observed values. Both models underestimate winter mass balance when forced by HRM data. When driven with WRF data, SnowModel underestimates winter mass balance integrated over the glacier area by 1 and 10%, whilst Alpine3D underestimates winter mass balance by 12 and 22% compared with LiDAR and stake measurements, respectively. The overall results show that SnowModel forced by WRF simulated winter mass balance the best.

Northeast British Columbia (BC) Canada, is a region in which natural gas production has undergone rapid development since 2007. We used nitrogen dioxide (NO2) and sulphur dioxide (SO2) data products of the Ozone Monitoring Instrument (OMI) to assess the impact of natural gas development activity on air quality in this region from 2005 to 2018. We noticed that values of both pollutants were elevated in the immediate vicinity of large emission sources within the Montney formation and Horn River Basin – regions, which have experienced an increase in unconventional natural gas activities. Places with elevated NO2 Vertical Column Densities (VCDs) are Fort St. John, Taylor, and Dawson Creek located in the Montney formation, and higher SO2 VCDs are found near the Fort Nelson gas plant situated in the Horn River and Liard Basin areas. Although all the OMI data products consistently reported relatively high NO2 VCDs in the same areas, VCD values vary substantially with data products largely due to differences in Air Mass Factor (AMF) calculations. The rate of increase in NO2 VCDs and mass between 2005 and 2018 in the Dawson Creek area was assessed at 2.34% yr−1 and 4.32% yr−1, respectively, and these rates of change are statistically significant. Although we obtained an overall increasing trend for NO2 in Northeast BC, we also noticed a decreasing trend in the period of 2011–2013, which may be attributed, in part, to compliance and enforcement of regulations concerning flaring activities from oil and gas activities in Northeast BC, or due to less development activities. From our analysis, we suggest that the current air quality monitoring network in Northeast BC should be expanded to capture the spatial distribution of SO2 by deploying one additional station near Fort Nelson equipped with meteorology and SO2 monitoring systems.

Three-dimensional chemical transport models are useful for spatial and temporal analyses of outdoor air quality. However, the suitability of boundary-layer parameterizations for air pollution modeling over deep, coastal valleys has seldom been tested. An evaluation of the Community Multiscale Air Quality (CMAQ) model performance for five planetary boundary-layer schemes (PBL) with the Weather Research and Forecasting (WRF) meteorological driver was conducted at 1-km horizontal resolution for fine particulate matter (PM2.5), sulfur dioxide (SO2) and nitrogen dioxide (NO2) over the Terrace-Kitimat valley of northwestern British Columbia, Canada. The top-ranked schemes were Mellor-Yamada-Nakanishi-Niino Level 3 (MYNN3) for PM2.5 and Mellor-Yamada-Janjic for NO2. Both schemes ranked high for absolute SO2 levels, but the MYJ and Asymmetric Convective Model, version 2 (ACM(2)) schemes qualitatively emulated peak summertime diurnal concentrations in the near field of elevated point sources. Greater nighttime SO2 concentrations with MYNN3 and Yonsei University PBL schemes, in less agreement with station monitoring 8 km downwind of emissions from tall stacks, suggested sustained pollutant mixing and downward transport within the nocturnal boundary layer. Consequently, for these two schemes with representations of nonlocal mass flux transfers between model layers, inland penetrations of pollutant plumes were farther than those of ACM2, MYJ, and University of Washington schemes. For NO2 and PM2.5 that mainly discharged passively from fugitive, ground-level sources, hence are less accurately quantified than SO2 emissions, the fully local MYJ, and semi-local MYNN3 PBL schemes more reasonably reproduced peak season concentrations than other schemes. It is concluded that for air pollution modeling in rugged, remote areas, the mode of pollutant emissions is important for the choice of a PBL scheme. PM2.5 was consistently underestimated by the various PBL schemes, and aspects for improving CMAQ simulations for a complex environment are discussed.

Evaluation of downscaled meteorological information is crucial to identifying model behaviors that may propagate to end applications such as the simulation of local air quality. This study conducted and assessed yearlong simulations of hourly meteorological conditions over the Terrace–Kitimat Valley of northwestern British Columbia, Canada, at 1-km horizontal gridding for six PBL schemes in the Weather and Forecasting (WRF) Model, version 4.0. In terms of key surface meteorological variables that affect air quality, simulations over land demonstrated better skill for specific humidity and wind direction than for air temperature and wind speed. Spatial differences in modeled atmospheric properties and vertical profiles, especially for moisture content, were used to diagnose the relative capacity of each PBL scheme to represent pollutant dispersion and dilution. Stable conditions at night increased suppression of boundary layer mixing by the nonlocal Yonsei University (YSU) scheme when compared with suppression by the local eddy-diffusion component of the Asymmetric Convective Model, version 2 (ACM2), scheme, resulting in decreased wind speed and ambient temperature but moister air with the YSU scheme. The weakening of mixing by the Mellor–Yamada–Nakanishi–Niino (MYNN3) scheme with inland distance suggested that higher-order, nonlocal transport is sensitive to increasing topographic steepness toward the northern part of the valley. Disparities in mixing strengths among PBL schemes were greater in the summer when conditions were generally less stable with moist, warm air blowing inland than in winter when the valley channels cold, stable air from the interior. Increased convection in daytime led to greater entrainment of air from aloft and a thicker PBL with the YSU scheme than with the ACM2 scheme in summer while increasing countergradient transport in the MYNN3 scheme that reduces dilution.

In this study, variations of offshore wind speed in the northern and central coasts of British Columbia are examined using wind observations from nine buoys distributed in the region. Wind speeds from all buoys are extrapolated to the standard (10 m) wind measurement height as well as to the wind turbine hub height (100 m) using Monin–Obukhov similarity theory. Sustained winds above several thresholds are analysed and values of 50 and 100‐year return extreme wind speed levels are calculated for all locations. The percentage of sustained winds between the wind turbine cut‐in and cut‐out wind speed thresholds at 100 m indicates short periods without power generation. The highest 50 and 100‐year return level values are found at locations west of Haida Gwaii, while the lowest values are calculated at the most southern and eastern locations. Spatial coherency analysis of high wind speeds between all locations shows high same‐day coherency ratios between all buoys located offshore of the mainland coast, which emphasizes the importance of the atmospheric circulation at the synoptic‐scale as the main driver of intense wind events; consequently, a synoptic‐scale circulation analysis is carried out by applying principal components analysis and k‐means clustering, and then relating the calculated synoptic patterns to some of the previously classified wind categories. The synoptic‐scale circulation analysis reveals that high wind speed events are mainly associated with a system of low pressure located west or northwest of the study region, which induces intense southerly to southeasterly winds. Low wind speeds are often associated with a high‐pressure system (Pacific High) originating southwest of the region that mainly predominates during the summer.

Prince George British Columbia has among the highest levels of ambient particulate matter (PM) in western Canada. In order to effectively lower ambient PM levels, management agencies need to be able to attribute ambient levels to specific sources, which can then be targeted for reduction. Dispersion modelling can be used to attribute sources to ambient levels, but one issue is that emissions from many PM sources are poorly known and must be estimated. The Calpuff dispersion modelling system was applied to all known sources of PM10, PM2.5, NOx and SO2 affecting the Prince George airshed over the three-year period 2003–2005. The model results were evaluated by comparison with ambient levels as well as with results from a speciation study using Positive Matrix Factorization and Chemical Mass Balance techniques. This resulted in constraints on the emissions of some of the more poorly characterized sources. In addition, a web-based visualization and scenario tool was developed for air quality managers to enable them to make science-based decisions to improve air quality. The results of the modelling and source attribution will be discussed, and the web-based scenario tool demonstrated.

Strong winds crossing elevated terrain and descending to its lee occur over mountainous areas worldwide. Winds fulfilling these two criteria are called foehn in this paper although different names exist depending on the region, the sign of the temperature change at onset, and the depth of the overflowing layer. These winds affect the local weather and climate and impact society. Classification is difficult because other wind systems might be superimposed on them or share some characteristics. Additionally, no unanimously agreed-upon name, definition, nor indications for such winds exist. The most trusted classifications have been performed by human experts. A classification experiment for different foehn locations in the Alps and different classifier groups addressed hitherto unanswered questions about the uncertainty of these classifications, their reproducibility, and dependence on the level of expertise. One group consisted of mountain meteorology experts, the other two of master’s degree students who had taken mountain meteorology courses, and a further two of objective algorithms. Sixty periods of 48 h were classified for foehn–no foehn conditions at five Alpine foehn locations. The intra-human-classifier detection varies by about 10 percentage points (interquartile range). Experts and students are nearly indistinguishable. The algorithms are in the range of human classifications. One difficult case appeared twice in order to examine the reproducibility of classified foehn duration, which turned out to be 50% or less. The classification dataset can now serve as a test bed for automatic classification algorithms, which—if successful—eliminate the drawbacks of manual classifications: lack of scalability and reproducibility.

ABSTRACTA synoptic climatology using mean sea level pressure and 500‐hPa geopotential height composites is conducted for strong along‐channel winds that occur through five of the channels dissecting British Columbia's coast. Seasonal (winter, summer) and directional (inflow, air moving from the coast inland; outflow, air moving from inland towards the coast) partitioning of the winds, results in four distinct along‐channel winds that occur: summertime inflow, summertime outflow, wintertime inflow and wintertime outflow. Composite analyses using reanalysis data and in situ observations are used to examine each wind type at all locations. Wintertime composites produce patterns that are distinct from the overall winter climatology, in which outflows occur when an arctic surface high‐pressure area on the inland side of the coastal mountains is accompanied by the presence of an area of low surface pressure in the northeastern Pacific. Inflow composites in the winter indicate low‐pressure areas associated with mid‐latitude cyclones over the Gulf of Alaska. Summertime composites are similar to the overall summer climatology; therefore, other approaches are applied to explain these winds. We analyse 104 summertime inflow events at three locations using surface analysis charts for 13 summer seasons. The analysis reveals the importance of fronts at the time of inflows, with fronts associated with almost half of the events. Non‐hierarchical clustering analysis is applied for the summertime inflow events. The clustering analysis gives a better explanation of the summertime inflows than the composites. This is achieved by grouping events into different clusters, allowing for better illustration of the variance between the clusters.

A significant shift in the mountain pine beetle (Dendroctonus ponderosae Hopkins, 1902) range has been attributed to long-distance dispersal from the observed spatiotemporal patterns of beetle infestations in the recent outbreak in western Canada. However, long-distance dispersal is still the least understood aspect of mountain pine beetle ecology. In particular, the mechanisms responsible for the three major phases of long-distance dispersal, the ascent, transport, and descent, are poorly known. In this study, we used the North American Regional Reanalysis meteorological data (1999–2010) to determine climate conditions under and above the forest canopy during mountain pine beetle emergence and flight at the landscape scale. We found that climate conditions are distinct during emergence and flight. They provide an ideal underlying environment to facilitate the potential long-distance dispersal. Climate conditions are unstable under the forest canopy during emergence, which would help loft beetles above the forest canopy to initiate long-distance dispersal. The first direct evidence from wind directions above the forest canopy suggests that atmospheric transportation of mountain pine beetle in the planetary boundary layer is aided by wind.

ABSTRACT This paper examines along-channel winds within Howe Sound, British Columbia, Canada, that occur from both the interior plateau out toward the coast as outflows and from the coast inland as inflows. First, the relationships between along-channel winds and pressure, temperature, and humidity are explored in Howe Sound–Cheakamus Valley. The pressure gradients between Pam Rocks and Squamish and Pam Rocks and Pemberton have the strongest correlations with outflow strength and that between Pam Rocks and Squamish has the strongest correlation with inflow strength. Outflows (inflows) have lower (higher) temperatures and dew point temperatures, except for the inflows in summer, which have lower dewpoint temperatures than the overall mean. Second, two case studies of outflow events are presented and described during the period of intensive observations prior to and during the Vancouver 2010 Winter Olympics. The January 2010 outflow event is caused by a zone of strong across-barrier mean sea level pressure gradient. The pressure gradient is formed behind an Arctic front that moved southward across Howe Sound. The February 2010 outflow event is caused by an approaching sea level low pressure centre from the Pacific that formed a northeast–southwest mean sea level pressure gradient across southern British Columbia. In the January case, the outflow layer is about 1.5 km deep, while it is shallower in the February case. Only the January outflow case exhibits hydraulic behaviour.