scholarly journals Historical Spatiotemporal Trends in Snowfall Extremes over the Canadian Domain of the Great Lakes Basin

2018 ◽  
Vol 2018 ◽  
pp. 1-20 ◽  
Author(s):  
Janine A. Baijnath-Rodino ◽  
Claude R. Duguay

The Laurentian Great Lakes Basin (GLB) is prone to snowfall events developed from extratropical cyclones or lake-effect processes. Monitoring extreme snowfall trends in response to climate change is essential for sustainability and adaptation studies because climate change could significantly influence variability in precipitation during the 21st century. Many studies investigating snowfall within the GLB have focused on specific case study events with apparent under examinations of regional extreme snowfall trends. The current research explores the historical extremes in snowfall by assessing the intensity, frequency, and duration of snowfall within Ontario’s GLB. Spatiotemporal snowfall and precipitation trends are computed for the 1980 to 2015 period using Daymet (Version 3) monthly gridded interpolated datasets from the Oak Ridge National Laboratory. Results show that extreme snowfall intensity, frequency, and duration have significantly decreased, at the 90% confidence level, more so for the Canadian leeward shores of Lake Superior than that of Lake Huron, for the months of December and January. To help discern the spatiotemporal trends is snowfall extremes, several trend analyses for lake-induced predictor variables were analysed for two cities, Wawa and Wiarton, along the snowbelts of Lakes Superior and Huron, respectively. These variables include monthly maximum and minimum air temperature, maximum wind gust velocity, lake surface temperature, and maximum annual ice cover concentration. Resultant significant increase in December’s maximum and minimum air temperature for the city of Wawa may be a potential reason for the decreased extreme snowfall trends.

2008 ◽  
Vol 12 (1) ◽  
pp. 239-255 ◽  
Author(s):  
E. McBean ◽  
H. Motiee

Abstract. In the threshold of the appearance of global warming from theory to reality, extensive research has focused on predicting the impact of potential climate change on water resources using results from Global Circulation Models (GCMs). This research carries this further by statistical analyses of long term meteorological and hydrological data. Seventy years of historical trends in precipitation, temperature, and streamflows in the Great Lakes of North America are developed using long term regression analyses and Mann-Kendall statistics. The results generated by the two statistical procedures are in agreement and demonstrate that many of these variables are experiencing statistically significant increases over a seven-decade period. The trend lines of streamflows in the three rivers of St. Clair, Niagara and St. Lawrence, and precipitation levels over four of the five Great Lakes, show statistically significant increases in flows and precipitation. Further, precipitation rates as predicted using fitted regression lines are compared with scenarios from GCMs and demonstrate similar forecast predictions for Lake Superior. Trend projections from historical data are higher than GCM predictions for Lakes Michigan/Huron. Significant variability in predictions, as developed from alternative GCMs, is noted. Given the general agreement as derived from very different procedures, predictions extrapolated from historical trends and from GCMs, there is evidence that hydrologic changes particularly for the precipitation in the Great Lakes Basin may be demonstrating influences arising from global warming and climate change.


2014 ◽  
Vol 119 (18) ◽  
pp. 10,799-10,812 ◽  
Author(s):  
Marc d'Orgeville ◽  
W. Richard Peltier ◽  
Andre R. Erler ◽  
Jonathan Gula

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 347 ◽  
Author(s):  
Ruotong Wang ◽  
Qiuya Cheng ◽  
Liu Liu ◽  
Churui Yan ◽  
Guanhua Huang

Based on three IPCC (Intergovernmental Panel on Climate Change) Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5), observed meteorological data, ERA-40 reanalysis data, and five preferred GCM (general circulation model) outputs selected from 23 GCMs of CMIP5 (Phase 5 of the Coupled Model Intercomparison Project), climate change scenarios including daily precipitation, maximum air temperature, and minimum air temperature from 2021 to 2050 in the Heihe River basin, which is the second largest inland river basin in Northwest China, were generated by constructing a statistical downscaling model (SDSM). Results showed that the SDSM had a good prediction capacity for the air temperature in the Heihe River basin. During the calibration and validation periods from 1961 to 1990 and from 1991 to 2000, respectively, the coefficient of determination (R2) and the Nash–Sutcliffe efficiency coefficient (NSE) were both larger than 0.9, while the root mean square error (RMSE) was within 20%. However, the SDSM showed a relative lower simulation efficiency for precipitation, with R2 and NSE values of most meteorological stations reaching 0.5, except for stations located in the downstream desert areas. Compared with the baseline period (1976–2005), changes in the annual mean precipitation simulated by different GCMs during 2021–2050 showed great difference in the three RCP scenarios, fluctuating from −10 to +10%, which became much more significant at seasonal and monthly time scales, except for the consistent decreasing trend in summer and increasing trend in spring. However, the maximum and minimum air temperature exhibited a similar increasing tendency during 2021–2050 in all RCP scenarios, with a higher increase in maximum air temperature, which increased as the CO2 concentration of the RCP scenarios increased. The results could provide scientific reference for sustainable agricultural production and water resources management in arid inland areas subject to climate change.


2006 ◽  
Vol 3 (5) ◽  
pp. 3183-3209 ◽  
Author(s):  
E. McBean ◽  
H. Motiee

Abstract. Historical trends in precipitation, temperature, and streamflows in the Great Lakes are examined using regression analysis and Mann-Kendall statistics, with the result that many of these variables demonstrate statistically significant increases ongoing for a six decade period. Future precipitation rates as predicted using fitted regression lines are compared with scenarios from Global Climate Change Models (GCMs) and demonstrate similar forecast predictions for Lake Superior. Trend projections from historical data are, however, higher than GCM predictions for Michigan/Huron. Significant variability in predictions, as developed from alternative GCMs, is noted. Given the general agreement as derived from very different procedures, predictions extrapolated from historical trends and from GCMs, there is evidence that hydrologic changes in the Great Lakes Basin are likely the result of climate change.


2012 ◽  
Vol 25 (21) ◽  
pp. 7723-7742 ◽  
Author(s):  
Jonathan Gula ◽  
W. Richard Peltier

The Weather Research and Forecasting model (WRF) is employed to dynamically downscale global warming projections produced using the Community Climate System Model (CCSM). The analyses are focused on the Great Lakes Basin of North America and the climate change projections extend from the instrumental period (1979–2001) to midcentury (2050–60) at a spatial resolution of 10 km. Because WRF does not currently include a sufficiently realistic lake component, simulations are performed using lake water temperature provided by D.V. Mironov’s freshwater lake model “FLake” forced by atmospheric fields from the global simulations. Results for the instrumental era are first compared with observations to evaluate the ability of the lake model to provide accurate lake water temperature and ice cover and to analyze the skill of the regional model. It is demonstrated that the regional model, with its finer resolution and more comprehensive physics, provides significantly improved results compared to those obtained from the global model. It much more accurately captures the details of the annual cycle and spatial pattern of precipitation. In particular, much more realistic lake-induced precipitation and snowfall patterns downwind of the lakes are predicted. The midcentury projection is analyzed to determine the impact of downscaling on regional climate changes. The emphasis in this final phase of the analysis is on the impact of climate change on winter snowfall in the lee of the lakes. It is found that future changes in lake surface temperature and ice cover under warmer conditions may locally increase snowfall as a result of increased evaporation and the enhanced lake effect.


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