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Under the possible impact of climate warming, recent changes in dry and wet spells have contributed significantly to climate-related hazards around the world. In this work, spatial and temporal variations in dry and wet spells over Canada are investigated using daily precipitation data from 1979 to 2018. The time-varying relationships between precipitation spells and large-scale climate anomalies are modeled using a nonstationary generalized extreme value (GEV) distribution and Bayesian quantile regression. Over the period 1979–2018, significant changes in dry and wet spells have been observed across Canada, particularly in the southern Canadian Prairies (CP), where both the number and duration of dry spells show positive trends. Dry and wet spells over many parts of Canada are nonstationary under the effects of the El Niño–Southern Oscillation (ENSO) and the Pacific–North American pattern (PNA), with PNA having stronger effects on annual maximum dry spells than ENSO, especially in the central CP and eastern Ontario. For western Canada, the influence of ENSO on dry spells tends to be relatively strong, especially for dry spells of high quantiles, as El Niño generally induces atmospheric moisture deficit. For central Canada, ENSO and PNA have a negative (positive) impact on the wet spell duration of low (high) quantiles. For eastern Canada, PNA is negatively correlated with the duration of wet spells, especially for wet spells of high quantiles. Therefore, a better understanding of the spatial and temporal variability in dry and wet spell return periods will be useful for the effective management of water resources, and for developing effective disaster mitigation measures against the possible social and economic impacts of climate-related hazards. [ABSTRACT FROM AUTHOR]

Both large-scale atmospheric circulation and moisture content in the atmosphere govern regional precipitation. We partition recent changes in mean, heavy, and extreme precipitation for all seasons over Canada to changes in synoptic circulation patterns (dynamic changes) and in atmospheric moisture conditions (thermodynamic changes) using 500-hPa geopotential height and precipitation data over 1979–2014. Using the self-organizing map (SOM) cluster analysis, we identify statistically significant trends in occurrences of certain synoptic circulation patterns over the Canadian landmass, which have dynamically contributed to observed changes in precipitation totals and occurrence of heavy and extreme precipitation events over Canada. Occurrences of circulation patterns such as westerlies and ridges over western North America and the North Pacific have considerably affected regional precipitation over Canada. Precipitation intensity and occurrences of precipitation extremes associated with each SOM circulation pattern also showed statistically significant trends resulting from thermodynamic changes in the atmospheric moisture supply for precipitation events. A partition analysis based on the thermodynamic–dynamic partition method indicates that most (~90%) changes in mean and extreme precipitation over Canada resulted from changes in precipitation regimes occurring under each synoptic circulation pattern (thermodynamic changes). Other regional precipitation changes resulted from changes in occurrences of synoptic circulation patterns (dynamic changes). Because of the high spatial variability of precipitation response to changes in thermodynamic and dynamic conditions, dynamic contributions could offset thermodynamic contributions to precipitation changes over some regions if thermodynamic and dynamic contributions are in opposition to each other (negative or positive), which would result in minimal changes in precipitation intensity and occurrences of heavy and extreme precipitation events. [ABSTRACT FROM AUTHOR]

Dominant synoptic moisture pathway patterns of vertically integrated water vapor transport (IVT) in winter and spring over Canada West and East were identified using the self-organizing map method. Large-scale meteorological patterns (LSMPs), together with synoptic moisture pathway patterns, were related to the variability in seasonal precipitation totals and occurrences of extreme precipitation events. Changes in both occurrences of LSMPs and seasonal precipitation occurred under those LSMPs were analyzed to explain observed changes in seasonal precipitation totals and occurrences of extreme precipitation events. The effects of large-scale climate anomalies on occurrences of LSMPs were also examined by composite analyses. Results show that synoptic moisture pathways and LSMPs exhibit the propagation of jet streams resulting from the Rossby wave resonance, as the location and direction of ridges and troughs, and the strength and center of pressure lows and highs varied considerably. Even though LSMPs resulting in positive precipitation anomalies are associated with more frequent occurrences of extreme precipitation events than those resulting in negative precipitation anomalies, the patterns featured with anomalously low IVT are sometimes associated with more frequent occurrences of extreme precipitation events. Significant decreases in occurrences of synoptic moisture pathway patterns that are favorable with positive precipitation anomalies and more precipitation extremes in winter over Canada West, and significant decreases in seasonal precipitation and occurrences of precipitation extremes under most synoptic moisture patterns resulted in decreases in seasonal precipitation and the occurrence of extreme precipitation events. LSMPs resulting in a hot and dry (cold and wet) climate and less (more) frequent extreme precipitation events over the Canadian Prairies in winter and northwestern Canada in spring are more likely to occur in years with a negative (positive) phase of PNA. Occurrences of LSMPs for a wet climate and frequent occurrences of extreme precipitation events over southeastern Canada are associated with a positive phase of NAO. In El Niño years or negative PDO years, occurrences of LSMPs tend to associate with a dry climate and less frequent precipitation extremes over western Canada. [ABSTRACT FROM AUTHOR]

Large-scale meteorological patterns (LSMPs), especially vertically integrated water vapor transport (IVT) patterns were identified using the self-organizing map algorithm, and LSMPs were related to seasonal precipitation totals and widespread precipitation extremes for summer and fall seasons over Canada West and East, using the JRA-55 reanalysis and the ANUSPLIN precipitation dataset (1958-2013). Changes in the frequency of occurrences, persistence and maximum duration of each LSMP were detected. Trends in seasonal precipitation totals and extreme precipitation events associated with each LSMP were also detected. Our results show that synoptic settings of precipitation that have occurred over Canada exhibit a variety of spatial clusters of IVT anomalies, pressure highs and lows, troughs and ridges over North America, North Pacific, North Atlantic and Arctic. Extremely high IVT magnitude anomaly (|IVT|′) over central Canada West are associated with the Aleutian low and Gulf cyclone across Canada West and Alaska, which force moisture from North Pacific to Canada West. Widespread positive |IVT|′ over Canada East are related to a strengthened and southwest-shifted trough across Canada East. Annually, only 19.4% of the occurrence characteristics of LSMPs show statistically significant changes. More statistically significant changes in the daily precipitation and occurrences of extreme precipitation related to each LSMP, than changes in the occurrence of LSMPs, have resulted in changes to seasonal precipitation totals and the occurrence of extreme precipitation across Canada. LSMPs associated with a dry climate and less frequent extreme precipitation events over Canada West in summer and fall tend to occur during the negative phase of PNA. LSMPs associated with a wet climate and frequent occurrence of extreme precipitation events over the south (north) of Canada East are more likely to occur during the positive (negative) phase of NAO. [ABSTRACT FROM AUTHOR]

In the past few decades, there have been more extreme climate events occurring worldwide, including Canada, which has also suffered from many extreme precipitation events. In this paper, trend analysis, probability distribution functions, principal component analysis, and wavelet analysis were used to investigate the spatial and temporal patterns of extreme precipitation events of Canada. Ten extreme precipitation indices were calculated using long-term daily precipitation data (1950–2012) from 164 Canadian gauging stations. Several large-scale climate patterns such as El Niño–Southern Oscillation (ENSO), Pacific decadal oscillation (PDO), Pacific–North American (PNA), and North Atlantic Oscillation (NAO) were selected to analyze the relationships between extreme precipitation and climate indices. Convective available potential energy (CAPE), specific humidity, and surface temperature were employed to investigate potential causes of trends in extreme precipitation. The results reveal statistically significant positive trends for most extreme precipitation indices, which means that extreme precipitation of Canada has generally become more severe since the mid-twentieth century. The majority of indices display more increasing trends along the southern border of Canada while decreasing trends dominated the central Canadian Prairies. In addition, strong teleconnections are found between extreme precipitation and climate indices, but the effects of climate patterns differ from region to region. Furthermore, complex interactions of climate patterns with synoptic atmospheric circulations can also affect precipitation variability, and changes to the summer and winter extreme precipitation could be explained more by the thermodynamic impact and the combined thermodynamic and dynamic effects, respectively. The seasonal CAPE, specific humidity, and temperature are correlated to Canadian extreme precipitation, but the correlations are season dependent, which could be positive or negative. [ABSTRACT FROM AUTHOR]

Climate change and large-scale climate patterns may result in changes in probability distributions of climate variables that are associated with changes in the mean and variability, and severity of extreme climate events. In this paper, we applied a flexible framework based on the Bayesian spatiotemporal quantile (BSTQR) model to identify climate changes at different quantile levels and their teleconnections to large-scale climate patterns such as El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO) and Pacific-North American (PNA). Using the BSTQR model with time (year) as a covariate, we estimated changes in Canadian winter precipitation and their uncertainties at different quantile levels. There were some stations in eastern Canada showing distributional changes in winter precipitation such as an increase in low quantiles but a decrease in high quantiles. Because quantile functions in the BSTQR model vary with space and time and assimilate spatiotemporal precipitation data, the BSTQR model produced much spatially smoother and less uncertain quantile changes than the classic regression without considering spatiotemporal correlations. Using the BSTQR model with five teleconnection indices (i.e., SOI, PDO, PNA, NP and NAO) as covariates, we investigated effects of large-scale climate patterns on Canadian winter precipitation at different quantile levels. Winter precipitation responses to these five teleconnections were found to occur differently at different quantile levels. Effects of five teleconnections on Canadian winter precipitation were stronger at low and high than at medium quantile levels. [ABSTRACT FROM AUTHOR]

Nine regions with spatially coherent seasonal 3-day total precipitation extremes across Canada were identified using a clustering method that is compliant to the extreme value theory. Using storm back-trajectory analyses, we then identified possible moisture sources and pathways that are conducive to occurrences of seasonal extreme precipitation events in four seasons for the nine regions identified. Moisture pathways for all extreme precipitation events were clustered to nine dominant moisture pathway patterns using the self-organizing map method. Results show that horizontal moisture pathway patterns and their occurrences were not evidently different between seasons. However, warm (summer and fall) and cold (winter and spring) seasons show considerable differences in the spreading of moisture sources in all nine regions, even though many sources do not frequently contribute to extreme precipitation events. In all four seasons, terrestrial evapotranspiration had provided major moisture sources to many extreme precipitation events occurred in inland regions. Central Canada had received more widespread moisture sources over surrounding oceans of North America than western and eastern Canada, because of more diverse moisture pathway patterns for central Canada that transport moisture from all surrounding oceans to central Canada. Extreme precipitation in southwestern Canada mainly resulted from atmospheric rivers over the North Pacific Ocean. For northwestern Canada, moisture pathway patterns were from the northern Pacific, Arctic and northern Atlantic oceans, even though more than 78% of trajectories for northwestern Canada were from the North Pacific. Westerlies from the North Pacific Ocean and northern polar jet streams controlled dominant pathways to central and eastern Canada. More extreme precipitation events over Canada were fed by the Arctic Ocean in warm than in cold seasons. [ABSTRACT FROM AUTHOR]

ABSTRACT The detrended fluctuation analysis ( DFA) and multifractal DFA, which can detect nonstationarities of time series with trends, were applied to study long-term persistence ( LTP) and multifractal behaviour of 100 stations of daily precipitation and 145 stations of streamflow time series of Canada. Results show that all precipitation time series showed LTP at both small and large time scales, while streamflow time series generally showed nonstationary behaviour at small time scales and LTP at large time scales. The significant multifractal behaviour of Canadian precipitation and streamflow data can be accurately described by the universal multifractal model and the modified multiplicative cascade model. Precipitation over central Canada showed stronger multifractality than that of western and eastern Canada, while multifractality of streamflow data is less spatially homogeneous. The multifractal strength of precipitation is generally smaller than that of streamflow. Eleven (9) out of 100 precipitation stations showed positive (negative) temporal trends in parameters derived using the universal multifractal model, and about half of the stations whose streamflow data exhibited statistically significant abrupt change points showed a weakening or strengthening in the multifractal strength moving from the pre-change to the post-change periods. Differences in the multifractal strength between Canadian precipitation and streamflow data suggest that the persistence of streamflow was not only because streamflow is more autocorrelated than precipitation but also it is more consistently affected by human activities such as streamflow regulation. [ABSTRACT FROM AUTHOR]

Slowly varying (trend) and abrupt (change points) changes in annual maximum daily precipitation (AMP) and seasonal maximum daily precipitation (SMP) across Canada for 223 stations in six regions during four periods (1900–2010, 1930–2010, 1950–2010 and 1970–2010) were analyzed. Variants of the Mann-Kendall (MK) test considering influences of short-term persistence (STP), long-term persistence (LTP) and large-scale climate anomalies on trend detection were applied to detect trends, and the Pettitt test was used to evaluate change points. The results indicate that there was a mix of increasing and decreasing trends for Canadian AMPs and SMPs. Most regions in Pacific Maritime, central Boreal regions and the Atlantic Maritime showed an increase in AMP, while a decrease in Canadian Prairies and most Boreal regions. More stations showing statistically significant increases than decreases in spring, summer and autumn SMPs were found while there was a statistically significant decrease (increase) in winter SMP over southern (northern) Canada. LTP significantly increased the likelihood of trends detected in AMPs and SMPs. The effects of STP on the trend detection were also evident as shown by the differences in results obtained from the MK tests with and without considering the effect of STP. The effects of large-scale climate anomalies on trends were significant for winter SMPs. More than 1/4 of stations were detected with statistically significant change points in AMPs and SMPs which occurred around 1960–1990. More stations showed significant change points than trends, and winter showed more evident trends and change points in SMPs than other three seasons. Trends and change points detected were field-significant. [ABSTRACT FROM AUTHOR]

Both natural climate change and anthropogenic impacts may cause nonstationarities in hydrological extremes. In this study, long-term annual maximum streamflow (AMS) records from 145 stations over Canada were used to investigate the nonstationary characteristics of AMS, which include abrupt changes and monotonic temporal trends. The nonparameteric Pettitt test was applied to detect abrupt changes, while temporal monotonic trend analysis in AMS series was conducted using the nonparameteric Mann-Kendall and Spearman tests, as well as a parametric Pearson test. Nonstationary frequency analysis of the AMS series was done using a group of nonstationary probability distributions. The nonstationary characteristics of Canadian AMS were further investigated in terms of the Hurst exponent ( H), which represents the long-term persistence (LTP) of streamflow data. The results presented here indicate that for Canadian AMS data, abrupt changes are detected more frequently than monotonic trends, partly because many rivers began to be regulated in the twentieth century. Drainage basins that have experienced significant land-use changes are more likely to show temporal trends in AMS, compared to pristine basins with stable land-use conditions. The nonstationary characteristics of AMS were accounted for by fitting the data with probability distributions with time-varying parameters. Large H found in almost ⅔ of the Canadian AMS dataset indicates strong LTP, which may partly represent the presence of long-term memories in many Canadian river basins. Furthermore, H values of AMS data are positively correlated with the basin area of Canadian rivers. It seems that nonstationary frequency analysis, instead of the traditional stationary hydrologic frequency analysis, should be employed in the future. [ABSTRACT FROM AUTHOR]

Statistical methods of wavelet, independent component analysis (ICA), and empirical orthogonal function (EOF) analysis were used together with geographical information systems (GIS) to regionalize runoff variability, establish baseline predisturbance hydrologic regimes, and account for runoff heterogeneity across Alberta, Canada as part of an effort to develop future adaptive forest management practices for Alberta. Both ICA and EOF identified three hydrologic clusters from 59 stations of catchment runoff data. However, ICA identified hydrologic clusters that agree better with the five ecoregions of Alberta than that of EOF. These are the Rocky Mountains and foothills, where runoff was characterized by a fairly consistent temporal variability and dominated by a strong annual cycle, southern Alberta/central Alberta, where temporal heterogeneity and a weak annual cycle dominated the runoff variability, and in southwestern Alberta, where the runoff variability was characterized by annual, 4-7, and 11-year cycles. Apparently stagnation moraine dominate hydrologic responses of most catchments in the grasslands and part of the boreal forests of western, central, and eastern Alberta. Empirical equations developed showed that stagnation moraine explained 64% of the runoff variability of selected catchments and that runoff was significantly diminished when stagnation moraines covered at least 74% of the catchment area. The identification of three spatially heterogeneous hydrologic clusters in Alberta, a province that is defined by four spatially homogeneous precipitation regimes indicates the necessity to develop forest management practices that will be suitable to manage Alberta's forests. [ABSTRACT FROM AUTHOR]

By applying a suit of statistical techniques, this study investigated the impacts of the El Nino-Southern Oscillation (ENSO), the Pacific-North America (PNA) pattern, the West Pacific (WP) pattern and the Pacific decadal oscillation (PDO) teleconnections on the interannual to interdecadal variability of southwestern (SW) Canadian streamflow anomalies. It is shown that El Nino (La Nina) episodes lead to significant negative (positive) streamflow anomalies in several subregions during the spring and/or summer months following the ENSO onset year. A simple composite analysis of streamflow for anomalous PNA years conditioned on non-ENSO years showed that the high phase of PNA could also produce an El Nino-like streamflow response over the region. In addition, the ENSO-streamflow relationship appears to be modulated by the interdecadal oscillation of the North Pacific (NP) climate as indexed by the PDO. The interaction between PDO and ENSO was found to be constructive when the two are in phase and destructive otherwise. The potential of using the three large-scale climate anomalies (ENSO, PNA and PDO) for long-range streamflow forecasting in SW Canada was assessed using a partial correlation analysis with the southern oscillation index (SOI), the PNA and PDO indices at lead times of up to 10 months. While partial correlations with all three indices were found to be statistically significant for several basins, the ENSO and PDO effects appear to be far more important than that of the PNA pattern. The winter season SOI, which is an indicator of the mature phase of ENSO, shows modest correlations with basins whose flow regimes are dominated by winter rain/spring snowmelt. On the other hand, the winter season PDO shows relatively strong correlations with basins originating in the Rocky Mountains, whose flow regimes are dominated by spring-summer snow/glacier melt. The modest SOI-streamflow relationships are partly attributed to nonlinearity induced by the interference from the extratropical sources of variability (i.e. PNA and PDO). Long-range streamflow forecasting strategies for this region should thus incorporate information from the three large-scale climate anomalies. Copyright © 2006 Royal Meteorological Society. [ABSTRACT FROM AUTHOR]

Trends of monthly Convective Available Potential Energy (CAPE) and of single or multiple event extreme precipitation indices, namely RX1day, RX5day and R20mm, were analyzed for the summer of 1979–2013 over the United States (US) and southern Canada. A homogeneity test in CAPE data using the Wilcoxon-rank-sum test showed that statistically significant change points mainly occurred between 2000 and 2003 probably due to changes in humidity sensors during this period. Therefore, the trend analysis was split into two categories: 1979–2013 for regions where no statistically significant change points in CAPE were detected and 1979–2001 and 2002–2013 for regions where statistically significant change points in CAPE were detected. The results show that increasing trends in CAPE and extreme precipitation indices dominate the eastern Atlantic coast of the US and some parts of the Great Lakes. Mixed increasing and decreasing trends were detected in the US mid-west while the western US and the Canadian Pacific coast had little trend in CAPE and extreme precipitation indices. Although both increasing and decreasing trends were detected, the average trends in RX1day and RX5day were about 0.2 mm/decade and 0.5 mm/decade over 1979–2013. However, the average trend for the 1979–2001 period was 0.2 mm/decade (RX1day) and 1.2 mm/decade (RX5day) as compared 1.2 mm/decade (RX1day) and 1.7 mm/decade (RX5day) for the 2002–2013 period. Temperatures also increased more during the 2002–2013 period (0.3 °C/decade) as compared to the 1979–2001 period (0.1 °C/decade). The higher increasing trend of the recent decades suggests that increasing temperatures could potentially lead to an overall increase in CAPE and extreme precipitation over the US and southern Canada. (a) Mean June–August CAPE for 1979–2013, (b) Mean annual CAPE over USA and southern Canada, the gray area shows the range of CAPE data while the dotted line shows the mean annual profile of CAPE over the region, and (c) detected change point years in summer CAPE data over USA and southern Canada for 1979–2013. [Display omitted] • Trends of Convective Available Potential Energy (CAPE) & extreme precipitation indices (EPI) were analyzed for USA & Canada. • Wilcoxon-rank-sum test shows increasing trends in monthly CAPE & EPI dominated eastern Atlantic USA & parts of Great Lakes. • The average trends for 1979–2001 [2002–2013] was 0.2 [1.2] mm/decade for RX1day and 1.2 [1.7] mm/decade for RX5day. • Temperatures also increased more in the 2002–2013 period (0.3 °C/decade) as compared to the 1979–2001 period (0.1 °C/decade). • Recent higher increasing trends suggest that warming could lead to higher CAPE and extreme precipitation over USA & Canada. [ABSTRACT FROM AUTHOR]

There has been a growing concern regarding impacts of global warming on droughts, which can have devastating effects on the environment, society, and economy of nations worldwide. Drought characteristics in terms of duration, frequency, area, and severity are investigated using the Standardized Precipitation Evapotranspiration Index (SPEI) at seasonal (3-month) and annual (12-month) time scales for Canada over 1950–2016 derived from the Climatic Research Unit (CRU) TS4.03 gridded data. Using k-means clustering, Canada is divided into four sub-regions, each with distinct drought characteristics. Next, the influence of climate drivers such as the El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) on regional drought variability were examined using a Bayesian Dynamic Linear (BDL) model. The results show that between 1950 and 2016 (1) there has been a prevalent drying trend in southwestern Canada during winter; (2) changes in maximum drought durations have occurred with dipolar patterns, i.e., northern Canada has experienced a longer drought duration than southern Canada; (3) drought frequency, area, and severity have predominantly shown statistically significant decreasing trends, indicating that droughts in Canada have generally become less severe; and (4) the relationships between climate anomalies and drought variability have changed over time. Droughts are generally more negatively correlated to ENSO and PDO after 1970s, but more positively correlated to the Atlantic Multi-decadal Oscillation (AMO) and Arctic Oscillation (AO) after the 1980s. The results provide a better understanding of the characteristics of meteorological droughts in Canada, essential for improving the risk management and mitigation strategies on the impact of droughts. • Drought frequency, area, and severity of Canada have generally become less severe. • In southwestern Canada, drying trend has been prevalent in winter. • Influence of large-scale climate patterns on droughts in Canada is dynamic. • Droughts in Canada and ocean dynamics show non-stationary teleconnections. • Decline in severe droughts led to decline in annual total drought severity/duration. [ABSTRACT FROM AUTHOR]

• Evaluate various climate data sources and calibration schemes based on SWAT model and SUFI2-SWATCUP. • Automatically eliminate unrealistic snow parameter combinations resulted from SUFI2-SWATCUP parameter sampling, and improve the performance of SUFI2-SWATCUP. • Simultaneously calibrate streamflow and Snow Water Equivalent (SWE) in a multi-variable calibration framework. • Significantly improve the simulation of snow-affected spring streamflow using multi-variable calibration (streamflow and SWE). The choice of proper input data and suitable calibration schemes is challenging in the hydrological modeling of higher-latitude watersheds with their unique hydro-climatic conditions. Based on the Soil and Water Assessment Tool (SWAT) and Sequential Uncertainty Fitting Program (SUFI2) of the SWATCUP tool, our study revisits various climate data and calibration schemes, and develops a more automatic calibration framework to thoroughly assess model performance in simulating Snow Water Equivalent (SWE) and resulting streamflow in a cold region watershed, the Peace River Basin (PRB) in western Canada. We evaluated the effects of (1) the observed and two widely used gridded climate data sources; (2) unrealistic snow parameter combinations arising from SUFI2-SWATCUP parameter sampling; and (3) 'calibration schemes' including the choice of (i) objective function, (ii) number of simulations in each calibration iterations, (iii) regional versus global parameterization and calibration schemes, and (iv) single-variable (streamflow) versus multi-variable calibration (streamflow and SWE). Model results showed that the gridded ERA5 data was the best climate input for driving the SWAT model in PRB. A modified SUFI2-SWATCUP method to automatically remove unrealistic snow parameter combinations outperformed the standard SUFI2-SWATCUP, and it significantly reduced the total number of simulations. Compared with single-variable calibration using streamflow, an automatic multi-variable calibration using streamflow and SWE was shown to effectively limit the uncertainty of snow-related parameters and provide better prediction of snow-affected spring streamflow. The framework developed in our study can help reduce uncertainties in the hydrological modeling of large-scale, regulated, and snow-dominated watersheds in higher latitudes and can help the development of reliable strategies for water resources planning and management. [ABSTRACT FROM AUTHOR]