Program - Workshops
DAY 3: Friday May 6, 2005: 2:00 – 5:00 PM
The Canadian Water Network Presents a Workshop on Climate Change and Water
The changing patterns of precipitation in the observed data, indicate that climate change is already a reality. For example, research carried out by CWN researchers shows increased variance of precipitation everywhere. Consistent with this finding, we observe that wet areas become wetter; dry and arid areas become more so. In addition, the following general changing pattern is emerging: (a) increased precipitation in high latitudes (northern Hemisphere); (b) reductions in precipitation in China, Australia and the Small Island States in the Pacific; and (c) equatorial regions become more variable, i.e. increased variance. The changes in the major ocean currents also appear to be affecting precipitation patterns. For example, increased intensity and frequency of El Niño and ENSO seems associated with evidence of an observed "dipole" pattern affecting Africa and Asia, although this time series is too short so far. But the changing pattern calls for renewed efforts for adaptation to climate change, as the changing precipitation pattern will also affect the regional availability of food supply. The objective of this Special CWN Session is to present some new findings relevant to these issues on the impact of climate change on water supply and the required adaptation measures.
Teleconnectivity Between Global Oceans and Prolonged Droughts in Canada
Amir Shabbar and Walter Skinner
Meteorological Service of Canada
The memory component of the global sea surface temperatures is used to teleconnect large-scale patterns of summer droughts in Canada to well known oscillations in the ocean circulation. The statistical technique of maximum covariance analysis is used to match summer Palmer Drought Index patterns to previous winter global SSTs.
El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) explain approximately 48% of the squared covariance, thus making interannual ENSO phenomenon and ENSO-related interdecadal variability the most significant process in the determination of the summer moisture availability in Canada. The trend in global SSTs and multidecadal variation of the Atlantic SST explain approximately one-third of the squared covariance. It is reflective of both the warming trend in the global southern oceans and the influences of the Atlantic Multidecadal Oscillation (AMO) variability. The six-month lag relationship between the PDSI and large scale SSTs provides a basis for developing long-range forecasting schemes for drought in Canada.
Statistical Downscaling Methods for Climate Change Impact Studies
Van-Thanh-Van Nguyen1,3, Tan-Danh Nguyen1,3 and Philippe Gachon2,3
1McGill University, Montreal, Quebec, Canada
2Environment Canada
3OURANOS Consortium, Montreal, Quebec, Canada
van.tv.nguyen@mcgill.ca
General Circulation Models (GCMs) have been recognized to be able to represent reasonably well the main features of the global atmospheric circulation, but these models so far could not reproduce well details of regional climate conditions at temporal and spatial scales of relevance to hydrological impact studies. Hence, there is a need to develop tools for downscaling GCM predictions of climate change to regional scales. Of particular importance for the management of water resources systems are those tools dealing with the linkage of the large-scale climate variability to the historical observations of the surface parameters of interest (e.g., precipitation and temperature). If this linkage could be established, then the projected change of climate conditions given by a GCM could be used to predict the resulting change of the selected surface parameters. The required linkage could be developed using downscaling methods.
In general, two broad categories of downscaling procedures currently exist: dynamical downscaling (DD) and statistical downscaling (SD). DD procedures are mainly based on regional climate models (RCMs) that describe the climate processes using fundamental conservation laws for mass, energy and momentum. DD methods contain thus more complete physics than SD techniques. However, the more complete physics significantly increases computational cost, which limits the simulation of a climate by RCMs to typically a single realization. On the other hand, SD approaches are relatively fast and much less expensive. These advantages of the SD allow the users to develop a large number of different climate realizations and thus to be able to quantify the confidence interval of simulated climate variables. In addition, SD methods can directly account for the observed weather data available at the study site. The results are hence more consistent with the local climate conditions.
In view of the above-mentioned issues, the main objective of this study is to perform a critical assessment of the adequacy of various existing SD techniques to find the most suitable procedure for hydrological impact studies. Of particular interest is the ability of SD techniques to simulate accurately the characteristics of precipitation and temperature extremes since these two parameters are the main components of the hydrologic cycle. Following a state-of-the-art review of different SD methods, the feasibility of two popular downscaling methods, namely the Statistical Downscaling Model (SDSM) and the Stochastic Weather Generator (LARS-WG) Model, were assessed using daily precipitation and temperature extreme data available in the southern Quebec region in Canada for the 1961-1990 period. In general, it was found that both models were able to describe accurately the basic statistical properties of daily temperature extremes at local sites. However, none of these models appears to be able to simulate well the statistical properties of daily precipitation processes. Finally, the LARS-WG is relatively easy for use as compared with the SDSM since it requires a simpler calibration method for parameter estimation.
From Modelling to Scenarios of Climate Change
Philippe Gachon
Environment Canada, OURANOS
Gachon.Philippe@ouranos.ca
The basic information used to simulate climate scenarios is derived from Global Climate Models (GCMs). However, the coarse horizontal resolution of GCMs is not sufficient to resolve small scale physical processes, especially those related to the precipitation regime. That is why downscaling techniques, both dynamical (with Regional Climate Model) and statistical, are particularly relevant to be developed and used in this context. These two methods are developed and evaluated within the OURANOS consortium in collaboration with Environment Canada, universities, and other partners (i.e. Hydro Québec and few Québec departments) to provide high resolution climate scenarios for impact and adaptation (I&A) studies. The presentation will focus on the statistical downscaling assessment to reconstruct the observed climate variability and extremes. In order to validate statistical downscaling methods, precipitation and temperature extremes indices are analysed from the observed data and downscaling results. We also compared the added value at local scale from these statistical downscaling tools using two GCMs output (namely CGCM1 and HadCM3 over the 1961-1990). We conclude about the strength and weaknesses of statistical downscaling methods for simulating extremes of precipitation and temperature and/or new insights that have been gained through the use of these tools for climate scenarios development.
A Nonparametric Approach to Detecting and Dating Climate Change: Implications for Adapting Water Supply
Mohammed Dore
Brock University
dore@brocku.ca
We examine the past 100 year data on precipitation for the Sooke Reservoir for Victoria, BC, and analyze the data using probability density estimation to detect and date climate change and assess how rapidly the climate has changed over the last 100 years. We then use the same methods for downscaled precipitation projections using CGCM1 in order to draw lessons for future climate change and assess the nature of required adaptations
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Climate Change in the South Saskatchewan River Basin: implications for adaptation
Thian Gan
University of Alberta
tgan@ualberta.ca
Agriculture in the Canadian Prairies withdraw up to 50% of the total water withdrawals in the Canadian Prairies, which have been hard hit by several consecutive droughts, so much so that water rationing became necessary in southern Alberta during summer(?). Water supply in the South Saskatchewan River Basin has been fully allocated due to droughts and industrial growth in the Calgary metropolitan areas. A key question is what measures, both structural (building hydraulic structures, and integration of water networks/systems) and non-structural (water conservations, water pricing, etc.) should be considered for implementation to reduce the vulnerability to future droughts which could become more severe and more frequent.
2005-04-11 |
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