Using the snow-day fraction to measure climatic change in southern Ontario (Canada): historical trends in winter season precipitation phase.

Global temperatures are increasing, and regional precipitation patterns are changing. Snow is an excellent indicator of regional climate change; 50 years of temperature and precipitation data were analysed from weather stations located within the five most populated cities of Ontario (Canada). Recorded measurements for temperature and precipitation were converted into binary values to indicate the frequency of rain days, snow days, wet days (when total precipitation is greater than 0.2 mm) and freezing days (when the average temperature is less than 0 °C); then, these values were summed over each winter season from 1970/71 to 2019/20. The snow-day fraction was calculated from the seasonal totals by dividing the total number of snow days by the total number of wet days. Historical trends were detected using Pearson's R, Kendall's Tau and Spearman's Rho. Differences in mean values between the first decade (1971-1980) and the last decade (2011-2020) within the time series for the snow-day fraction and total freezing days were determined using Student's t-tests. During the winter season in southern Ontario (December 1 to March 31), total snow days, total wet days, the snow-day fraction and freezing days were all decreasing at statistically significant rates (90 to 99% confidence levels) across four of the five cities studied (Toronto, Ottawa, Hamilton and London). Mississauga was the exception, being the only city where rain days were increasing, but no trends were detected for snow days or wet days. The snow-day fraction was decreasing in Mississauga but not at a statistically significant rate, despite freezing days decreasing at the greatest rate compared to the other four cities. Total freezing days were highly correlated with the snow-day fraction during the winter season, being able to explain 61 to 76 percent of the observed variability, where Mississauga recorded the weakest correlation and London recorded the strongest correlation.

Enabling Nature-Based Solutions to Build Back Better-An Environmental Regulatory Impact Analysis of Green Infrastructure in Ontario, Canada.

The application of green infrastructure in the built environment delivers a nature-based solution to address the impacts of climate change. This study presents a qualitative evidence synthesis that evaluates policy instruments which enable the use and implementation of green infrastructure, using Ontario, Canada as a case study. Unpacking the elements of the policy landscape that govern green infrastructure through environmental regulatory impact analysis can inform effective implementation of this nature-based solution and support decision-making in public policy. This environmental regulatory impact analysis is based on a systematic review of existing policy instruments, contextual framing in a continuum of coercion, and identification of alignment with relevant UN SDGs. Enabling widespread usage of green infrastructure in the built environment could be a viable strategy to build back better, localize the UN SDGs, and address multiple climate change impacts.

Ecological Risk Assessment of Trace Metal in Pacific Sector of Arctic Ocean and Bering Strait Surface Sediments.

The arctic region is a remote area with relatively few anthropogenic inputs, but there is increasing concern over toxic trace metal contamination in the Arctic Ocean. In this study, distribution characteristics of eight trace metals in the surface sediment of the Pacific Sector of the Arctic Ocean and Bering Strait are analyzed. The geochemical baseline value of each metal element is explored using the relative cumulative frequency curve method; the enrichment factor (EF), geo-accumulation index (Igeo) and potential ecological risk index (RI) are applied to assess the ecological risk level of the trace metals. According to the results, Cu, As and Hg had a little more content variation, and their contents in some areas were significantly higher than the previous reports. EF values show an obvious enrichment of element As, followed by Cr element with the moderate enrichment; the enrichment of the other six elements are not related to human activity. The Igeo value shows a moderately contaminated to heavily contaminated level of As and a moderately contaminated level of Cr. According to the potential ecological risk indexes in each site, most sites are at a low ecological risk level except five sites with RI/baseline values exceeding 150 which are at a moderate ecological risk level.

Comparing future climatic suitability to shoreline loss for recreational beach use: a case study of five Japanese beaches.

Coastal tourism is impacted by regional environmental change, including sea-level rise and climatic change. A case study at five Japanese beaches was conducted to determine the relative difference in coastal and climatic changes that are important for recreational beach tourism. Future climate conditions and projections of shoreline changes due to sea-level rise were estimated using ensembles of 14 and 21 Global Circulation Models (GCMs), respectively. The Holiday Climate Index (HCI:Beach) specific to recreational beach use was used to assess historical and future climatic suitability while beach loss area was used to quantify physical changes to beach conditions. Diminished beaches with improved climate conditions were observed at all sites except Yonehara, which had both diminished beach and climate conditions. Comparing HCI:Beach scores relative to historical conditions revealed a change of -2.4 to +10%, while beach losses were typically >60%. These results highlight that beach tourism suitability at the study sites will likely exhibit greater changes due to sea-level rise, compared to those driven by changing atmospheric conditions. Supplementary Information: The online version contains supplementary material available at 10.1007/s10113-022-01906-2.

Characterizing observed surface wind speed in the Hudson Bay and Labrador regions of Canada from an aviation perspective.

Wind speed analysis is important for informing airport operation and safety. Many communities in the Hudson Bay and Labrador regions (Canada) are remote communities that rely heavily on aircraft for passenger and freight movement. Historical trends in average daily wind speed and maximum daily wind speed from 1971 to 2010 were examined to identify patterns of change and determine how these changes may influence aviation in six northern communities across Hudson Bay and Labrador in Canada. Significant increases in average wind speed and maximum wind speed were found for some of the months and seasons of the year for the Hudson Bay region, along with a significant decrease in those variables for the Labrador communities. Average wind speeds at multiple locations are approaching the threshold (18.5 km/h or 10 knots) when take-off and landing would be restricted to one direction. The results of this study agree with previous research that examined historical patterns for wind speed in these regions but calls into question climate change impact assessments that suggest wind speeds will continue to increase under future climatic conditions for this study area. Future research is needed to further analyse shifts in prevailing wind directions and changes in the frequency of extreme wind conditions, to better understand the potential impacts of projected climate change on this climatic variable and the implications these changes may have on applied sectors, such as aviation.

Nature-based cooling potential: a multi-type green infrastructure evaluation in Toronto, Ontario, Canada.

The application of green infrastructure presents an opportunity to mitigate rising temperatures using a multi-faceted ecosystems-based approach. A controlled field study in Toronto, Ontario, Canada, evaluates the impact of nature-based solutions on near surface air temperature regulation focusing on different applications of green infrastructure. A field campaign was undertaken over the course of two summers to measure the impact of green roofs, green walls, urban vegetation and forestry systems, and urban agriculture systems on near surface air temperature. This study demonstrates that multiple types of green infrastructure applications are beneficial in regulating near surface air temperature and are not limited to specific treatments. Widespread usage of green infrastructure could be a viable strategy to cool cities and improve urban climate.

Development and validation of the Climate Model Confidence Index (CMCI): measuring ability to reproduce historical climate conditions.

This study further develops and finally validates the Climate Model Confidence Index (CMCI) as a simple and effective metric for evaluating and ranking the ability of climate models to reproduce historical climate conditions. Modelled daily climate data outputs from two different statistical downscaling techniques (PCIC: Pacific Climate Impacts Consortium; SDSM: Statistical Down-Scaling Model) are compared with observational data recorded by Environment Canada weather stations located in Kelowna, BC (Canada), for the period from 1969 to 2005. Using daily data (N > 13,000), Student's t-tests determined if there were statistically significant differences between the modelled and observed means while ANOVA F-tests identified differences between variances. Using aggregated annual data (N = 37), CMCI values were also calculated for the individual model runs from each statistical downscaling technique. Climate model outputs were ranked according to the absolute value of the t statistics. The 20 SDSM ensembles outperformed the 27 PCIC models for both minimum and maximum temperatures, while PCIC outperformed SDSM for total precipitation. Linear regression determined the correlation between the absolute value of the t statistics and the corresponding CMCI values (R 2 > 0.99, P < 0.001). Rare discrepancies (< 10% of all model rankings) between the t statistic and CMCI rankings occurred at the third decimal place and resulted in a one rank difference between models. These discrepancies are attributed to the precision of the t tests which rely on daily data and consider observed as well as modelled variance, whereas the simplicity and utility of the CMCI are demonstrated by only requiring annual data and observed variance to calculate.

Nature-Based Equity: An Assessment of the Public Health Impacts of Green Infrastructure in Ontario Canada.

The built environment is a physical determinant of health essential to the planning and development of a more equitable society. Communities face growing challenges due to environmental stressors such as climate change, with vulnerable communities experiencing a disproportionate burden of adverse health outcomes. The interdependencies between urban planning and public health outcomes are inextricable, with respect to improving access to healthier built environments for vulnerable and marginalized groups. Widespread implementation of nature-based solutions, such as green infrastructure, provides a multi-functional strategy to support sustainable development, increase climate resilience, enhance ecological connectivity, and create healthier communities. A Health Equity Impact Assessment presents the findings of a participatory research study utilizing key informant interviews of public health unit professionals (eight) and a survey of green infrastructure volunteers and workers (36) on the impact of green infrastructure on individual and community mental and physical well-being, service use, and perceived unmet needs, using Ontario, Canada as a case study. Study findings indicate that where green infrastructure is both productive and publicly accessible, the benefits were significant for vulnerable populations. These benefits include increased social connectivity, skills development, and food security. Green infrastructure could be a viable strategy to address environmental stressors, improve health equity, and support localization of the UN Sustainable Development Goals (SDGs).

Persistence and spatial-temporal variability of drought severity in Iran.

Drought is a natural hazard that can inflict significant damage to agriculture, society, economy, and ecosystems. The assessment of the persistence of drought severity (PDS) assists in understanding the characteristics of droughts better and enables the development of associated prediction tools and models. This work explores the persistence and spatial-temporal variability of drought severity (DS) in the diverse dryland of Iran. Using monthly precipitation and temperature data of 44 synoptic stations from 1989 to 2018, relationships between DS coefficient of precipitation variation, aridity, and the persistence percentage are determined by the application of the standardized precipitation index (SPI), the dryland index, and the Hurst exponent (H). The results confirm the persistence of droughts in Iran as H exceeded the 0.5 threshold for all stations. The PDS average in Iran is 0.78 with high regional variability reflective of different climatic conditions and geographical locations. An inverse relationship exists between the long-term coefficient of variation of monthly precipitation and PDS in the hyper-arid and arid regions of watersheds. Higher PDS values and increasing trend in the DS are detected in dry-subhumid areas. Also, the effect of the El Niño-Southern Oscillation (ENSO), a teleconnection metric, on the DS displays high spatial and temporal variability in Iran. The results show that the PDS is consistent with the spatial variation of DS changes during the period of 2009-2018.

Inter- and intraspecific variation in leaf economic traits in wheat and maize.

Leaf Economics Spectrum (LES) trait variation underpins multiple agroecological processes and many prominent crop yield models. While there are numerous independent studies assessing trait variation in crops, to date there have been no comprehensive assessments of intraspecific trait variation (ITV) in LES traits for wheat and maize: the world's most widespread crops. Using trait databases and peer-reviewed literature, we compiled over 700 records of specific leaf area (SLA), maximum photosynthetic rates (Amax) and leaf nitrogen (N) concentrations, for wheat and maize. We evaluated intraspecific LES trait variation, and intraspecific trait-environment relationships. While wheat and maize occupy the upper 90th percentile of LES trait values observed across a global species pool, ITV ranged widely across the LES in wheat and maize. Fertilization treatments had strong impacts on leaf N, while plant developmental stage (here standardized as the number of days since planting) had strong impacts on Amax; days since planting, N fertilization and irrigation all influenced SLA. When controlling for these factors, intraspecific responses to temperature and precipitation explained 39.4 and 43.7 % of the variation in Amax and SLA, respectively, but only 5.4 % of the variation in leaf N. Despite a long history of domestication in these species, ITV in wheat and maize among and within cultivars remains large. Intraspecific trait variation is a critical consideration to refine regional to global models of agroecosystem structure, function and food security. Considerable opportunities and benefits exist for consolidating a crop trait database for a wider range of domesticated plant species.

Differences in the importance of weather and weather-based decisions among campers in Ontario parks (Canada).

Parks and protected areas represent an important resource for tourism in Canada, in which camping is a common recreational activity. The important relationship between weather and climate with recreation and tourism has been widely acknowledged within the academic literature. Howbeit, the need for activity-specific assessments has been identified as an on-going need for future research in the field of tourism climatology. Furthermore, very little is known about the interrelationships between personal characteristics and socio-demographics with weather preferences and behavioural thresholds. This study uses a stated climate preferences approach (survey responses) to explore differences in the importance of weather and related weather-based decisions among summer campers in Ontario parks. Statistically significant differences were found among campers for each of the four dependent variables tested in this study. Physically active campers placed greater importance on weather but were still more tolerant of adverse weather conditions. Older campers placed greater importance on weather. Campers travelling shorter distances placed greater importance on weather and were more likely to leave the park early due to adverse weather. Campers staying for longer periods of time were less likely to leave early due to weather and were willing to endure longer durations of adverse weather conditions. Beginner campers placed greater importance on weather, were more likely to leave early due to weather and recorded lower temporal weather thresholds. The results of this study contribute to the study of tourism climatology by furthering understanding of how personal characteristics such as gender, age, activity selection, trip duration, distance travelled, travel experience and life cycles affect weather preferences and decisions, focusing this time on recreational camping in a park tourism context.

Weather sensitivity for zoo visitation in Toronto, Canada: a quantitative analysis of historical data.

Based on a case study of the Toronto Zoo (Canada), multivariate regression analysis, involving both climatic and social variables, was employed to assess the relationship between daily weather and visitation. Zoo visitation was most sensitive to weather variability during the shoulder season, followed by the off-season and, then, the peak season. Temperature was the most influential weather variable in relation to zoo visitation, followed by precipitation and, then, wind speed. The intensity and direction of the social and climatic variables varied between seasons. Temperatures exceeding 26 °C during the shoulder season and 28 °C during the peak season suggested a behavioural threshold associated with zoo visitation, with conditions becoming too warm for certain segments of the zoo visitor market, causing visitor numbers to decline. Even light amounts of precipitation caused average visitor numbers to decline by nearly 50 %. Increasing wind speeds also demonstrated a negative influence on zoo visitation.

A Bayesian modelling framework for tornado occurrences in North America.

Tornadoes represent one of nature's most hazardous phenomena that have been responsible for significant destruction and devastating fatalities. Here we present a Bayesian modelling approach for elucidating the spatiotemporal patterns of tornado activity in North America. Our analysis shows a significant increase in the Canadian Prairies and the Northern Great Plains during the summer, indicating a clear transition of tornado activity from the United States to Canada. The linkage between monthly-averaged atmospheric variables and likelihood of tornado events is characterized by distinct seasonality; the convective available potential energy is the predominant factor in the summer; vertical wind shear appears to have a strong signature primarily in the winter and secondarily in the summer; and storm relative environmental helicity is most influential in the spring. The present probabilistic mapping can be used to draw inference on the likelihood of tornado occurrence in any location in North America within a selected time period of the year.

Use of traditional environmental knowledge to assess the impact of climate change on subsistence fishing in the James Bay Region of Northern Ontario, Canada.

INTRODUCTION: In Canada, unique food security challenges are being faced by Aboriginal people living in remote-northern communities due to the impacts of climate change on subsistence harvesting. This study used traditional environmental knowledge (TEK) to investigate whether there was a temporal relationship between extreme climatic events in the summer of 2005, and fish die-offs in the Albany River, northern Ontario, Canada. Also, TEK was utilized to examine a potential shift in subsistence fish species distribution due to climate change. METHODS: To investigate whether there was a temporal relationship between the fish die-offs of July 2005 (as identified by TEK) and an extreme climatic event, temperature and daily precipitation data for Moosonee weather station were utilized. To determine if there was an increasing trend in mean maximal summer temperatures with year, temperature data were examined, using regression analysis. Present-day fish distributions were determined using unpublished TEK data collated from previous studies and purposive, semi-directive interviews with elders and experienced bushman. RESULTS: Fish die-offs in 2005 occurred during the time period 11-18 July, as reported by participants. Recorded air-temperature maxima of the two July 2005 heat waves delineate exactly the time period of fish die-offs. Two heat waves occurring during the same summer season and so close together has never before been recorded for this region. A highly significant (p < 0.0009) positive relationship between mean maximal summer temperatures and year was evident. Regionally novel fish species were not apparent, utilizing TEK. CONCLUSIONS: Traditional environmental knowledge coupled with climate data revealed temporal relationships between extreme climatic events in 2005, and fish die-offs in the Albany River. Thus, climate change can directly impact food security by decreasing the number of fish through mortality - and indirectly through population dynamics - by impacting the yield of fish subsistence harvests in the future. By contrast, TEK did not reveal northward expansion of novel fish species in the Albany River or fish distributional contraction in the western James Bay region.