Climate Change Canada Research Articles

Canada and the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES): Lessons Learned on Implementation and Compliance

Unsustainable and illegal wildlife trade are contributing to the unprecedented levels of biodiversity loss and possible extinction of one million species. Law enforcement and the criminal justice system have a role to play in helping to regulate and monitor such trade. The main international instrument to regulate wildlife trade is the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). This mixed methods study researched the lessons learned and best practice in regards to implementation of and compliance with CITES. As part of the study, three countries were identified as case studies and Canada was selected as one of these. Lessons can also be learned from Canada’s Wild Animal and Plant Protection and Regulation of International and Interprovincial Trade Act, which is cumbersome to update when species protections change within CITES. Canada has several elements of good practice, such as the remit, effectiveness and relationships of the three CITES authorities located within Environment and Climate Change Canada, the public health approach to some wildlife imports, and the protection of native CITES species. CITES needs to be improved to further protect endangered species and lessons from Canada and other countries can contribute to this improvement.

EOLakeWatch; delivering a comprehensive suite of remote sensing algal bloom indices for enhanced monitoring of Canadian eutrophic lakes

Early detection and comprehensive monitoring of inland water algal blooms is fundamental to their effective management and mitigation of potential ecosystem and public health impacts. With the spatial and temporal limitations of in situ sampling, algal bloom monitoring capabilities have been enhanced greatly by advancements in satellite Earth Observation (EO). Three turbid, eutrophic Canadian lakes (Lake Winnipeg (LW); Lake Erie (LE); Lake of the Woods (LoW)) have been the focus of Environment and Climate Change Canada (ECCC) research and monitoring initiatives due to concerns over persistent degraded water quality from recurring algal blooms. ECCC’s EOLakeWatch was developed to deliver a suite of useful, easily interpretable, and accessible EO-derived products to support algal bloom monitoring on these three lakes. Algal bloom indices, describing bloom spatial extent, intensity, duration, and severity were derived using the European Space Agency’s OLCI (Ocean and Land Colour Instrument) sensor for observations from 2016 to present and its predecessor MERIS (Medium Resolution Imaging Spectrometer) for 2002 to 2011. Results document widespread blooms on each lake, with maximum spatial extent of 21,641 km2 (representing 88.1% of the lake area) on LW, 3070 km2 (79.5%) on LoW and 5257 km2 (19.7%) on LE. Bloom intensity showed seasonal and inter-annual variability on all three lakes, with a suggestion that LoW may be responding to reduced nutrient loads with a recent decrease in bloom intensity. Annual bloom duration on LW and LoW was on average 44 and 47 days respectively, while on LE blooms were significantly shorter in duration at an average of 24 days. Variance among the derived bloom indices was shown to be significant (i.e. the most extensive bloom was not necessarily the longest or most intensive), demonstrating the need for the indices to be used collectively, or for any single comprehensive bloom indicator to capture the variability of all individual metrics. Bloom indices are processed in a fully automated operational capacity, distributed in near-real-time through a web portal and collated into end-user-friendly annual algal bloom reports for each lake. These products go a long way to address existing monitoring gaps, delivering prompt, consistent measures of lake-wide algal bloom conditions required to provide stakeholders with early warning of bloom risks, identify areas of potential concern, quantify spatio-temporal trends, further understand bloom dynamics and drivers, as well as guide and determine the effectiveness of implemented management actions.

SCDNA: a serially complete precipitation and temperature dataset for North America from 1979 to 2018

Abstract. Station-based serially complete datasets (SCDs) of precipitation and temperature observations are important for hydrometeorological studies. Motivated by the lack of serially complete station observations for North America, this study seeks to develop an SCD from 1979 to 2018 from station data. The new SCD for North America (SCDNA) includes daily precipitation, minimum temperature (Tmin⁡), and maximum temperature (Tmax⁡) data for 27 276 stations. Raw meteorological station data were obtained from the Global Historical Climate Network Daily (GHCN-D), the Global Surface Summary of the Day (GSOD), Environment and Climate Change Canada (ECCC), and a compiled station database in Mexico. Stations with at least 8-year-long records were selected, which underwent location correction and were subjected to strict quality control. Outputs from three reanalysis products (ERA5, JRA-55, and MERRA-2) provided auxiliary information to estimate station records. Infilling during the observation period and reconstruction beyond the observation period were accomplished by combining estimates from 16 strategies (variants of quantile mapping, spatial interpolation, and machine learning). A sensitivity experiment was conducted by assuming that 30 % of observations from stations were missing – this enabled independent validation and provided a reference for reconstruction. Quantile mapping and mean value corrections were applied to the final estimates. The median Kling–Gupta efficiency (KGE′) values of the final SCDNA for all stations are 0.90, 0.98, and 0.99 for precipitation, Tmin⁡, and Tmax⁡, respectively. The SCDNA is closer to station observations than the four benchmark gridded products and can be used in applications that require either quality-controlled meteorological station observations or reconstructed long-term estimates for analysis and modeling. The dataset is available at https://doi.org/10.5281/zenodo.3735533 (Tang et al., 2020).

Establishing Climate Change Resilience in the Great Lakes in Response to Flooding

Over the past decade, both the average rainfall and the frequency of high precipitation storm events in the Great Lakes Basin have been steadily increasing as a consequence of climate change. In this same period, cities and communities along the coasts are experiencing record high water levels and severe flooding events (ECC Canada et al. 2018). When cities are unprepared for these floods, the safety of communities and the water quality of the Great Lakes are jeopardized. For example, coastal flooding increases runoff pollution and contaminates the freshwater resource that 40 million people rely on for drinking water (Lyandres and Welch 2012, Roth 2016). Since the Great Lakes are shared between two nations, the United States and Canada, the region is protected by several international treaties and national compacts, including the Great Lakes Water Quality Agreement (GLWQA) and the Great Lakes Restoration Initiative (GLRI). In order to increase climate change resiliency against flooding in the region, we recommend the United States Environmental Protection Agency (EPA) work with Environment and Climate Change Canada to relocate the GLRI under the GLWQA in order to guarantee consistent funding and protection efforts. We additionally recommend expansion of both agreements in their scope and long-term commitments to engender cooperative efforts to protect the Great Lakes against climate change.

Implementation of Slant-Path Radiative Transfer in Environment Canada’s Global Deterministic Weather Prediction System

AbstractThe standard approach for assimilating satellite radiance observations is to interpolate all vertical levels of the background state and analysis increment to the same horizontal location for input to the radiative transfer model. This can add significant error for observations with large zenith angle. The impact of accounting for the true slanted satellite-viewing geometry was tested by modifying the horizontal interpolation routines in Environment and Climate Change Canada’s Global Deterministic Weather Prediction System. Consequently, model variables are interpolated to a different horizontal position at each model level, for either just the innovation or both the innovation and increment calculation. When this slant-path operator is used for simulation of radiances, reductions in innovation standard deviation, up to 4.5%, for upper-tropospheric and stratospheric temperature and humidity channels of ATMS, AMSU-A, MHS, and CrIS instruments have similar magnitudes as reported in previous studies. In data assimilation experiments, statistically significant reductions in innovation standard deviation (up to 0.3%) for global GPSRO observations are obtained, due to an improved background state. Verification of short- and medium-range forecasts against ERA5, and our own analyses over the region poleward of 60°S show statistically significant reductions of error standard deviation by 2%–3% for wind and temperature in the upper troposphere and lower stratosphere. These positive impacts are mostly due to performing slant-path interpolation on the background state, while also using slant path on the analysis increment has little additional impact. This is expected since the analysis increment in this global configuration has lower spatial resolution, with grid spacing comparable with the maximum horizontal position error from not using the slant-path operator.

On the Progressive Attenuation of Finescale Orography Contributions to the Vertical Coordinate Surfaces within a Terrain-Following Coordinate System

AbstractA modified hybrid terrain-following vertical coordinate has recently been implemented within the Global Environmental Multiscale atmospheric model that introduces separately controlled height-dependent progressive decaying of the small- and large-scale orography contributions on the vertical coordinate surfaces. The new vertical coordinate allows for a faster decay of the finescale orography imprints on the coordinate surfaces with increasing height while relaxing the compression of the lowest model levels over complex terrain. A number of tests carried out—including experiments involving Environment and Climate Change Canada’s operational regional and global deterministic prediction systems—demonstrate that the new vertical coordinate effectively eliminates terrain-induced spurious generation and amplification of upper-air vertical motion and kinetic energy without increasing the computational cost. Results also show potential improvements in precipitation over complex terrain.

Mercury Exposure and Toxicological Consequences in Fish and Fish-Eating Wildlife from Anthropogenic Activity in Latin America.

ABSTRACTDespite the risk of significant adverse toxicological effects of Hg to humans and wildlife, Hg use in anthropogenic activities, and artisanal small‐scale gold mining (ASGM) in particular, is widespread throughout Latin America. However, there are few research and monitoring studies of Hg toxicity in fish and fish‐eating wildlife in Latin America compared to North America. In the present paper, we reviewed the literature from published articles and reports and summarized and assessed data on Hg in fish from 10 391 individuals and 192 species sampled across Latin America. We compared fish Hg levels with toxicity reference values (TRVs) for fish and dietary TRVs for fish‐eating wildlife. We determined that fish, piscivorous birds, and other wildlife are at risk of Hg toxicity. We observed a large disparity in data quantity between North and Latin America, and identified regions requiring further investigation. In particular, future biomonitoring and research should focus on exposure of wildlife to Hg in Peru, Chile, Uruguay, the eastern and northern regions of Brazil, Venezuela, Ecuador, and Colombia. We also discuss Hg risk assessment methodological issues and recommend that future evaluations of Hg risk to wildlife must collect key physiological variables, including age, body size, and ideally Hg‐to‐Se molar ratios. Integr Environ Assess Manag 2021;17:13–26. © 2020 Environment and Climate Change Canada. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)

Development of a Reduced-Volume Acute Lethality Toxicity Test for Hyalella azteca.

Effects‐directed analysis (EDA) is used to identify the principal toxic components within a complex mixture using iterative steps of chemical fractionation guided by bioassay results. Bioassay selection can be limited in EDA because of the volume requirements for many standardized test methods, and therefore, a reduced‐volume acute toxicity test that also provides whole‐organism responses is beneficial. To address this need, a static, 7‐d, water‐only, reduced‐volume method (50 mL, 10 organisms) was developed for Hyalella azteca that substantially decreases the volume requirements of standard‐volume acute test exposures (200–500 mL of test solution, 15–20 organisms) while maintaining water quality and meeting control survival criteria. Standard‐ and reduced‐volume methods were compared by conducting concurrent toxicity tests with 2 inorganic toxicants (KCl and CdCl2) and 2 organic mixtures of naphthenic acid fraction components (NAFCs) to evaluate test performance. There was no difference between methods when comparing the median lethal concentrations (LC50s) for KCl and both NAFC mixtures (p > 0.05). The LC50s for CdCl2 were statistically different (p = 0.0002); however, this was not considered biologically meaningful because the difference between LC50s was <2‐fold. In conclusion, the reduced‐volume H. azteca test method generated results comparable to standard‐volume test methods and is suitable for use in situations where limited testing material is available, such as when conducting EDA. Environ Toxicol Chem 2020;39:2221–2227. © 2020 Her Majesty the Queen in Right of Canada. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Reproduced with the permission of the Minister of Environment and Climate Change Canada.

Impact of Urbanization on the Predictions of Urban Meteorology and Air Pollutants over Four Major North American Cities

The sensitivities of meteorological and chemical predictions to urban effects over four major North American cities are investigated using the high-resolution (2.5-km) Environment and Climate Change Canada’s air quality model with the Town Energy Balance (TEB) scheme. Comparisons between the model simulation results with and without the TEB effect show that urbanization has great impacts on surface heat fluxes, vertical diffusivity, air temperature, humidity, atmospheric boundary layer height, land-lake circulation, air pollutants concentrations and Air Quality Health Index. The impacts have strong diurnal variabilities, and are very different in summer and winter. While the diurnal variations of the impacts share some similarities over each city, the magnitudes can be very different. The underlying mechanisms of the impacts are investigated. The TEB impacts on the predictions of meteorological and air pollutants over Toronto are evaluated against ground-based observations. The results show that the TEB scheme leads to a great improvement in biases and root-mean-square deviations in temperature and humidity predictions in downtown, uptown and suburban areas in the early morning and nighttime. The scheme also leads to a big improvement of predictions of NOx, PM2.5 and ground-level ozone in the downtown, uptown and industrial areas in the early morning and nighttime.

Caught red handed: iDNA points to wild source for CITES-protected contraband leeches

In October of 2018, Canada Border Services Agency (CBSA) at Pearson International Airport in Toronto notified the Wildlife Enforcement Branch of Environment and Climate Change Canada that a passenger had arrived aboard a flight from Russia with a large quantity of live leeches. The leeches had been discovered in the passenger’s carry-on luggage. An enforcement officer with Environment and Climate Change Canada detained the leeches to identify the species in order to determine whether the import was lawful. We identified the leeches as Hirudo verbana and extracted DNA from the bloodmeals of a subsample of 240 leeches and used metabarcoding of 6 mitochondrial loci to determine the vertebrate host species on which the leeches had previously fed. Sixteen undomesticated vertebrate host species were identified from the bloodmeals of the imported leeches, indicating that these leeches were collected from wild habitats. Furthermore, the overlap of host species’ distributions point to a possible collecting source in the Volga delta, the Danube delta, or the coastal area region on the east side of the Sea of Azov. Our findings support the utility of invertebrate-derived DNA (iDNA) as a valuable tool in forensic evaluation of trafficked wildlife and provide new evidence regarding illegal exploitation of the European medicinal leech.

Which Caribou? Misnaming Caribou Population Units Leads to Conservation Errors

In reviewing the genetic, morphological, behavioural, and ecological distinctiveness of caribou throughout Canada, the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) (2011) divided “Southern Mountain caribou” (c.f. COSEWIC 2002) into three designatable units (DU) for conservation purposes: Northern Mountain (DU7), Central Mountain (DU8), and Southern Mountain (DU9) populations of woodland caribou. These new designations mean that each is considered a “wildlife species” according to the Species at Risk Act. Recent federal and provincial government reports refer to “Southern Mountain caribou,” conflating Southern Mountain, Central Mountain, and nine of the 45 subpopulations of Northern Mountain caribou into one pseudo-population, with clear conservation consequences. For example, in 2018, a federal decision on an emergency order required the Minister of Environment and Climate Change Canada (ECCC) to ascertain whether there were immediate threats to the survival or recovery of the Southern Mountain population of woodland caribou. By conflating two ecotypes and part of another into “Southern Mountain caribou”—an obsolete, geographical grouping not used since2002—ECCC’s assessment falsely informed the Minister that there were 3,764 “Southern Mountain caribou,” when in fact there were only 1,240 in the Southern Mountain (DU9)mpopulation. Other errors arising from the first distorted the number and trajectories of extant subpopulations. Instead of issuing the emergency order, the Minister entered into protracted negotiations with the province on recovery planning that continue at this writing. The nomenclatural ambiguity can be resolved by 1) using the currently accepted taxonomy naming Osborn’s caribou a valid subspecies, R. t. osborni, instead of Northern Mountain population of woodland caribou, 2) using original English names for Mountain caribou and Rocky Mountain caribou, and 3) basing conservation actions on these distinct phylogenetic units as per COSEWIC (2011, 2014).

A Canadian River Ice Database from the National Hydrometric Program Archives

Abstract. River ice, like open-water conditions, is an integral component of the cold-climate hydrological cycle. The annual succession of river ice formation, growth, decay and clearance can include low flows and ice jams, as well as midwinter and spring break-up events. Reports and associated data of river ice occurrence are often limited to single locations or regional assessments, are season-specific, and use readily available data. Within Canada, the National Hydrometric Program (NHP) operates a network of gauging stations with water level as the primary measured variable to derive discharge. In the late 1990s, the Water Science and Technology Directorate of Environment and Climate Change Canada initiated a long-term effort to compile, archive and extract river-ice-related information from NHP hydrometric records. This data article describes the original research data set produced by this near 20-year effort: the Canadian River Ice Database (CRID). The CRID holds almost 73 000 recorded variables from a subset of 196 NHP stations throughout Canada that were in operation within the period 1894 to 2015. Over 100 000 paper and digital files were reviewed, representing 10 378 station years of active operation. The task of compiling this database involved manual extraction and input of more than 460 000 data entries on water level, discharge, ice thickness, date, time and data quality rating. Guidelines on the data extraction, rating procedure and challenges are provided. At each location, time series of up to 15 variables specific to the occurrence of freeze-up and winter-low events, midwinter break-up, ice thickness, spring break-up, and maximum open-water level were compiled. This database follows up on several earlier efforts to compile information on river ice, which are summarized herein, and expands the scope and detail for use in Canadian river ice research and applications. Following the Government of Canada Open Data initiative, this original river ice data set is available at https://doi.org/10.18164/c21e1852-ba8e-44af-bc13-48eeedfcf2f4 (de Rham et al., 2020).

A high-resolution reanalysis of global fire weather from 1979 to 2018 – overwintering the Drought Code

Abstract. We present a global high-resolution calculation of the Canadian Fire Weather Index (FWI) System indices using surface meteorology from the ERA5 HRES reanalysis for 1979–2018. ERA5 HRES represents an improved dataset compared to several other reanalyses in terms of accuracy, as well as spatial and temporal coverage. The FWI calculation is performed using two different procedures for setting the start-up value of the Drought Code (DC) at the beginning of the fire season. The first procedure, which accounts for the effects of inter-seasonal drought, overwinters the DC by adjusting the fall DC value with a fraction of accumulated overwinter precipitation. The second procedure sets the DC to its default start-up value (i.e. 15) at the start of each fire season. We validate the FWI values over Canada using station observations from Environment and Climate Change Canada and find generally good agreement (mean Spearman correlation of 0.77). We also show that significant differences in early season DC and FWI values can occur when the FWI System calculation is started using the overwintered versus default DC values, as is highlighted by an example from 2016 over North America. The FWI System moisture codes and fire behaviour indices are made available for both versions of the calculation at https://doi.org/10.5281/zenodo.3626193 (McElhinny et al., 2020), although we recommend using codes and indices calculated with the overwintered DC, unless specific research requirements dictate otherwise.

CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance

Abstract. Recent reports by the Global Carbon Project highlight large uncertainties around land surface processes such as land use change, strength of CO2 fertilization, nutrient limitation and supply, and response to variability in climate. Process-based land surface models are well suited to address these complex and emerging global change problems but will require extensive development and evaluation. The coupled Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem Model (CLASS-CTEM) framework has been under continuous development by Environment and Climate Change Canada since 1987. As the open-source model of code development has revolutionized the software industry, scientific software is experiencing a similar evolution. Given the scale of the challenge facing land surface modellers, and the benefits of open-source, or community model, development, we have transitioned CLASS-CTEM from an internally developed model to an open-source community model, which we call the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC) v.1.0. CLASSIC contains many technical features specifically designed to encourage community use including software containerization for serial and parallel simulations, extensive benchmarking software and data (Automated Model Benchmarking; AMBER), self-documenting code, community standard formats for model inputs and outputs, amongst others. Here, we evaluate and benchmark CLASSIC against 31 FLUXNET sites where the model has been tailored to the site-level conditions and driven with observed meteorology. Future versions of CLASSIC will be developed using AMBER and these initial benchmark results to evaluate model performance over time. CLASSIC remains under active development and the code, site-level benchmarking data, software container, and AMBER are freely available for community use.

The Canadian Seasonal to Interannual Prediction System Version 2 (CanSIPSv2)

AbstractThe second version of the Canadian Seasonal to Interannual Prediction System (CanSIPSv2) was implemented operationally at Environment and Climate Change Canada (ECCC) in July 2019. Like its predecessors, CanSIPSv2 applies a multimodel ensemble approach with two coupled atmosphere–ocean models, CanCM4i and GEM-NEMO. While CanCM4i is a climate model, which is upgraded from CanCM4 of the previous CanSIPSv1 with improved sea ice initialization, GEM-NEMO is a newly developed numerical weather prediction (NWP)-based global atmosphere–ocean coupled model. In this paper, CanSIPSv2 is introduced, and its performance is assessed based on the reforecast of 30 years from 1981 to 2010, with 10 ensemble members of 12-month integrations for each model. Ensemble seasonal forecast skill of 2-m air temperature, 500-hPa geopotential height, precipitation rate, sea surface temperature, and sea ice concentration is assessed. Verification is also performed for the Niño-3.4, the Pacific–North American pattern (PNA), the North Atlantic Oscillation (NAO), and the Madden–Julian oscillation (MJO) indices. It is found that CanSIPSv2 outperforms the previous CanSIPSv1 system in many aspects. Atmospheric teleconnections associated with the El Niño–Southern Oscillation (ENSO) are reasonably well captured by the two CanSIPSv2 models, and a large part of the seasonal forecast skill in boreal winter can be attributed to the ENSO impact. The two models are also able to simulate the Northern Hemisphere teleconnection associated with the tropical MJO, which likely provides another source of skill on the subseasonal to seasonal time scale.

Ice Concentration From Dual-Polarization SAR Images Using Ice and Water Retrievals at Multiple Spatial Scales

A new technique for automated retrieval of ice concentration from RADARSAT-2 dual-polarization HH-HV ScanSAR Wide images for subsequent assimilation in ice numerical models is presented. First, we extended our previously introduced ice and water detection approach operating at a 2.05 km x 2.05 km spatial scale to a set of 19 different spatial scales ranging from 2.05 km (41 pixels) down to 0.25 km (5 pixels). As the spatial resolution was increased, the overall accuracy of ice and water detection stayed at a very high level across all scales (between 99.5% and 99.8%), but the number of water retrievals substantially dropped. Second, we designed an approach for estimating ice concentration in a 2 km × 2 km (40 × 40 pixels) area consisting of 64 5 × 5 pixel blocks. The 5 × 5 pixel blocks which are initially classified as unknowns are iteratively combined in clusters with effective spatial scales larger than 5 pixels. The clusters are further classified as ice or water using the ice probability model corresponding to the effective spatial scale. The 40 x 40 pixel area becomes populated with high-resolution (5 x 5 pixels) ice and water retrievals, and the ice concentration is estimated based on the number of ice and water retrievals. The proposed approach produces a much better agreement with the Canadian Ice Service Image Analysis ice concentrations (rootmean-square error (RMSE) = 2.2%) compared to the original 2-km ice/water detection approach (RMSE = 19.9%). The developed technique will be adapted to the RADARSAT Constellation Mission data for data assimilation in Environment and Climate Change Canada Regional Ice-Ocean Prediction System.

Protecting rural Canadians from extreme heat.

KEY POINTS The frequency, intensity and duration of extreme heat events are increasing across Canada.[1][1] However, as reflected in recent reports by Environment and Climate Change Canada[1][1] and the Council of Canadian Academies,[2][2] extreme heat events are regarded as primarily an urban issue

An improved post-processing technique for automatic precipitation gauge time series

Abstract. The unconditioned data retrieved from accumulating automated weighing precipitation gauges are inherently noisy due to the sensitivity of the instruments to mechanical and electrical interference. This noise, combined with diurnal oscillations and signal drift from evaporation of the bucket contents, can make accurate precipitation estimates challenging. Relative to rainfall, errors in the measurement of solid precipitation are exacerbated because the lower accumulation rates are more impacted by measurement noise. Precipitation gauge measurement post-processing techniques are used by Environment and Climate Change Canada in research and operational monitoring to filter cumulative precipitation time series derived from high-frequency, bucket-weight measurements. Four techniques are described and tested here: (1) the operational 15 min filter (O15), (2) the neutral aggregating filter (NAF), (3) the supervised neutral aggregating filter (NAF-S), and (4) the segmented neutral aggregating filter (NAF-SEG). Inherent biases and errors in the first two post-processing techniques have revealed the need for a robust automated method to derive an accurate noise-free precipitation time series from the raw bucket-weight measurements. The method must be capable of removing random noise, diurnal oscillations, and evaporative (negative) drift from the raw data. This evaluation primarily focuses on cold-season (October to April) accumulating automated weighing precipitation gauge data at 1 min resolution from two sources: a control (pre-processed time series) with added synthetic noise and drift and raw (minimally processed) data from several WMO Solid Precipitation Intercomparison Experiment (SPICE) sites. Evaluation against the control with synthetic noise shows the effectiveness of the NAF-SEG technique, recovering 99 %, 100 %, and 102 % of the control total precipitation for low-, medium-, and high-noise scenarios respectively for the cold-season (October–April) and 97 % of the control total precipitation for all noise scenarios in the warm season (May–September). Among the filters, the fully automated NAF-SEG produced the highest correlation coefficients and lowest root-mean-square error (RMSE) for all synthetic noise levels, with comparable performance to the supervised and manually intensive NAF-S method. Compared to the O15 method in cold-season testing, NAF-SEG shows a lower bias in 37 of 44 real-world test cases, a similar bias in 5 cases, and a higher bias in 2 cases. In warm-season testing, the NAF-SEG bias was lower or similar in 7 of 11 cases. The results indicate that the NAF-SEG post-processing technique provides substantial improvement over current automated techniques, reducing both uncertainty and bias in accumulating-gauge measurements of precipitation, with a 24 h latency. Because it cannot be implemented in real time, we recommend that NAF-SEG be used in combination with a simple real-time filter, such as the O15 or similar filter.

Chemical Analysis of Surface-Level Ozone Exceedances during the 2015 Pan American Games

Surface-level ozone (O3) continues to be a significant health risk in the Greater Toronto Hamilton Area (GTHA) of Canada even though precursor emissions in the area have decreased significantly over the past two decades. In July 2015, Environment and Climate Change Canada (ECCC) led an intensive field study coincident with Toronto hosting the 2015 Pan American Games. During the field study, the daily 1-h maximum O3 standard (80 ppbv) was exceeded twice at a measurement site in North Toronto, once on July 12 and again on July 28. In this study, ECCC’s 2.5-km configuration of the Global Environmental Multi-scale (GEM) meteorological model was combined with the Modelling Air-quality and CHemistry (MACH) on-line atmospheric chemistry model and the Town Energy Balance (TEB) urban surface parameterization to create a new urban air quality modelling system. In general, the model results showed that the nested 2.5-km grid-spaced urban air quality model performed better in statistical scores compared to the piloting 10-km grid-spaced GEM-MACH model without TEB. Model analyses were performed with GEM-MACH-TEB for the two exceedance periods. The local meteorology for both cases consisted of light winds with the highest O3 predictions situated along lake-breeze fronts. For the July 28 case, O3 production sensitivity analysis along the trajectory of the lake-breeze circulation showed that the region of most efficient O3 production occurred in the updraft region of the lake-breeze front, as the precursors to O3 formation underwent vertical mixing. In this updraft region, the ozone production switches from volatile organic compound (VOC)-sensitive to NOx-sensitive, and the local net O3 production rate reaches a maximum. This transition in the chemical regime is a previously unidentified factor for why O3 surface-level mixing ratios maximize along the lake-breeze front. For the July 12 case, differences between the model and observed Lake Ontario water temperature and the strength of lake-breeze opposing wind flow play a role in differences in the timing of the lake-breeze, which impacts the predicted location of the O3 maximum north of Toronto.

Predictability of the Strong Ural blocking Event in January 2012 in the Subseasonal to Seasonal Models of Europe and Canada

The occurrence of a Ural blocking (UB) event is an important precursor of severe cold air outbreaks in Siberia and East Asia, and thus is significant to accurately predict UB events. Using subseasonal to seasonal (S2S) models of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Environment and Climate Change Canada (ECCC), we evaluated the predictability of a persistent UB event on 18 to 26 January 2012. Results showed that the ECCC model was superior to the ECMWF model in predicting the development stage of the UB event ten days in advance, while the ECMWF model had better predictions than the ECCC model for more than ten days in advance and the decaying stage of the UB event. By comparing the dynamic and thermodynamic evolution of the UB event predicted by the two models via the geostrophic vorticity tendency equation and temperature tendency equation, we found that the ECCC model better predicted the vertical vorticity advection, ageostrophic vorticity tendency, the tilting effect, horizontal temperature advection, and adiabatic heating during the development stage, whereas the ECMWF model better predicted the three dynamic and the two thermodynamic terms during the decaying stage. In addition, during both the development and decaying stages, the two models were good (bad) at predicting the vortex stretching term (horizontal vorticity advection), with the PCC between both the predictions and the observations larger (smaller) than +0.70 (+0.10) Thus, we suggest that the prediction of the persistent UB event in the S2S model might be improved by the better prediction of the horizontal vorticity advection.