Figure 4 - uploaded by Pedro Odon
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(on left). Fifteen-day averaged minimum 2-m temperature anomaly centered on December 11th, 2016, relative to 1979-2017 period. Figure 5 (on right). Daily minimum 2-m temperature time series for Vancouver, smoothed using a 5-day rolling window for readability. Time series for all years in grey, 1937/38-2016/17 average in blue, 2012/13-2016/17 average in red, 1992/92 in orange and 2016/17 in black. Days with snowfall indicated with green dashed lines.
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... In this study, a highresolution regional climate model based on the 4.8.12 version of Environment Canada's Global Environment Multiscale in CLImate Model (GEMCLIM) is used to simulate the PMP values for the AR-related extreme precipitation events in Metro Vancouver. In addition, winter-time weather extremes over this urban region such as freezing rain and extreme snowfall can result in high risks of major disruption to public transport and significant property damage, which has been highlighted by the cold air outbreak event during the fall and winter seasons of 2016/17 (Odon et al., 2017). Therefore, the PMP simulations performed are also used to explore the mechanism associated with the occurrence of PMP and the changes to two different hazardous types of precipitation, i.e., snowfall and freezing rain, in Vancouver. ...
... Frontiers in Marine Science | www.frontiersin.org greater hazardous impact on the transportation and electricity infrastructure of the city (Odon et al., 2017(Odon et al., , 2019. The more widespread freezing rain implies a more pronounced thermal stratification in the lower troposphere. ...
The west coast of Canada is strongly affected by the extreme precipitation events triggered by frequent atmospheric river (AR) activities over the eastern North Pacific. Across the region, assessing the probable maximum precipitation (PMP), can provide valuable information for resilience building of the coastal communities that are vulnerable to hydrological risks. In this study, a 3-km convection-permitting regional climate model is used to physically estimate the PMP in Vancouver. This technique maximizes the effect of AR-related water vapor transport by spatially adjusting the lateral boundary conditions (LBCs) of the model simulations for the selected AR-related extreme precipitation events. The PMP in Vancouver is identified among the simulations driven by the spatially adjusted LBCs that are corresponding with the AR-induced “worst-case scenario,” i.e., landfalling ARs hit Vancouver with optimal landfalling location and transport direction. Results suggest that the PMP in Vancouver, in terms of the maxima of the regionally averaged 72-h total precipitation for the historical extreme precipitation events, is up to 790 mm, which is 130% greater than the historical peak precipitation for the period 1980∼2017. On average, all the PMP simulations shows an overall increase by 81% in precipitation by relative to historical simulations. In addition, the PMP simulations suggested an overall decrease in snowfall by 12% due to the warmer near-surface air temperature; however, a pronounced increase in freezing rain is seen. The precipitation increase for the estimated PMP relative to the historical extreme precipitation is closely associated with the increased atmospheric moisture transport and the changes in the atmospheric dynamic factors when the AR effects are maximized. These include the enhanced low-tropospheric ascent and moisture transport convergence, which can induce stronger depletion of atmospheric moistures as indicated by the increased precipitation efficiency.
... Fall 2016 was one of the warmest and wettest recorded on the South Coast of BC (Odon et al. 2017). Many parts of the region experienced a long-lasting and almost undisrupted rain period resulting in an accumulated precipitation anomaly of over 200% at several locations (Odon et al. 2017). ...
... Fall 2016 was one of the warmest and wettest recorded on the South Coast of BC (Odon et al. 2017). Many parts of the region experienced a long-lasting and almost undisrupted rain period resulting in an accumulated precipitation anomaly of over 200% at several locations (Odon et al. 2017). Managing the unusual reservoir inflows was a challenge for the province's primary electric utility, BC Hydro. ...
Physics parameterizations in the Weather Research and Forecasting (WRF) model are systematically varied to investigate precipitation forecast performance over the complex terrain of southwest British Columbia (BC). Comparing a full year of modelling data from over 100 WRF configurations to station observations reveals sensitivities of precipitation intensity, season, location, grid resolution, and accumulation window. The choice of cumulus and microphysics parameterizations is most important. The WSM5 microphysics scheme yields competitive verification scores when compared to more sophisticated and computationally expensive parameterizations. Although the cale-aware Grell-Freitas cumulus parameterization performs better for summertime convective precipitation, the conventional Kain-Fritsch parameterization better simulates wintertime frontal precipitation, which contributes to the majority of the annual precipitation in southwest BC. Finer grid spacings have lower relative biases and a more realistic spread in precipitation intensity distribution, yet higher relative standard deviations of their errors — they produce finer spatial differences and local extrema. Finer resolutions produce the best fraction of correct-to-incorrect forecasts across all precipitation intensities, whereas the coarser 27-km domain yields the highest hit rates and equitable threat scores. Verification metrics improve greatly with longer accumulation windows — hourly precipitation values are prone to double-penalty issues, while longer accumulation windows compensate for timing errors but lose information about short-term precipitation intensities. This study provides insights regarding WRF precipitation performance in complex terrain across a wide variety of configurations, using metrics important to a range of end users.
... Precipitation is examined here because of its various financial, societal, and environmental impacts such as hydroelectric power generation (Odon et al. 2017), flooding and water management (White et al. 2016;Odon et al. 2017;Sun and Miao 2018), agriculture (Rosenzweig et al. 2001;Sun and Miao 2018), tourism (Patz et al. 2005;White et al. 2016), health (Curriero et al. 2001;Patz et al. 2005), and flora and fauna (Parmesan et al. 2000). ...
... Precipitation is examined here because of its various financial, societal, and environmental impacts such as hydroelectric power generation (Odon et al. 2017), flooding and water management (White et al. 2016;Odon et al. 2017;Sun and Miao 2018), agriculture (Rosenzweig et al. 2001;Sun and Miao 2018), tourism (Patz et al. 2005;White et al. 2016), health (Curriero et al. 2001;Patz et al. 2005), and flora and fauna (Parmesan et al. 2000). ...
This study evaluates how well reanalyses represent daily and multiday accumulated precipitation (hereinafter daily PCP) over British Columbia, Canada (Part I evaluated 2-m temperature). Reanalyses are compared with observations from 66 meteorological stations distributed over the complex terrain of British Columbia, separated into climate regions by k-means clustering. Systematic error, two-sample χ ² statistic, and frequency of daily PCP occurrence are evaluated from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim), the Climate Forecast System Reanalysis (CFSR), the Japanese 55-year Reanalysis (JRA-55), and the latest Modern-Era Retrospective Analysis for Research and Applications (version 2; MERRA-2). The 2- and 30-yr return levels of daily PCP are estimated from a generalized extreme value (GEV) distribution fitted by the method of L moments, and their systematic errors are analyzed. JRA-55 and MERRA-2 generally outperform ERA-Interim and CFSR across all metrics. Biases are largely explained by poor reanalysis representation of terrain characteristics such as steepness, exposure, elevation, location of barriers, and wind speed and direction. Statistical stationarity of precipitation intensity and frequency over the 30-yr period is assessed by using confidence intervals and GEV distributions fitted with and without time-dependent parameters. It is determined that stationary distributions are sufficient to represent the climate of daily PCP for this region and time period.
... We analyze both daily and extreme maximum and minimum T2M (defined in section 2) and compare them with weather stations in BC for the period 1980-2010. T2M is examined because of its importance and impact on ecosystems (Parmesan et al. 2000), agriculture (Rosenzweig et al. 2001), tourism (Patz et al. 2005;White et al. 2016), urbanization and health (Curriero et al. 2001;White et al. 2016;Odon et al. 2017), and because of observational data availability (Jones et al. 1985;Peterson and Vose 1997;Jones et al. 1999). ...
Weather-station data coverage, quality, and completeness across British Columbia, Canada, degrade outside of population centers and as one goes back in time. This data paucity motivates the search for the best reanalysis to serve as a climatological reference dataset. This study focuses on how well reanalyses represent 2-m temperature (T2M). Systematic error, random error, and two-sample Kolmogorov-Smirnov statistics of daily maximum and minimum T2M are evaluated from the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim), the Climate Forecast System Reanalysis (CFSR), the Japanese 55-year Reanalysis (JRA-55), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Also evaluated are the 2- and 30-yr return levels of T2M, which are estimated by the method of L moments from a fitted generalized extreme value (GEV) distribution. Reanalyses are compared with observations from 57 meteorological stations distributed over the complex terrain of British Columbia from 1980 to 2010. Minimum temperatures are better captured than maximum temperatures by all four reanalyses. JRA-55 and ERA-Interim generally perform better across all metrics. Biases are largely explained by poor reanalysis terrain representation. Statistical stationarity over the 30-yr period is assessed by using Gaussian and GEV distributions fitted with and without time-dependent parameters. It is determined that stationary distributions are sufficient to represent the climate of T2M for this region and time period.
