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Evaluation of surface climate data from the North American Regional Reanalysis for Hydrological Applications in central CanadaKim, Sung Joon 22 June 2012 (has links)
A challenge in hydrological studies in the Canadian Prairie region is to find good-quality meteorological data because many basins are located in remote regions where few stations are available, and existing stations typically have short records and often contain a high number of missing data.
The recently released North American Regional Reanalysis (NARR) data set appears to have potential for hydrological studies in data-scarce central Canada. The main objectives of this study are: (1) to evaluate and utilize NARR data for hydrologic modelling and statistical downscaling, (2) to develop methods for estimating missing precipitation data using NARR data, and (3) to investigate and correct NARR precipitation bias in the Canadian Prairie region.
Prior to applying NARR for hydrological modelling, the NARR surface data were evaluated by comparison with observed meteorological data over the Canadian Prairie region. The comparison results indicated that NARR is a suitable alternative to observed surface meteorological data and thus useful for hydrological modelling.
After evaluation of NARR surface climate data, the SLURP model was set up with input data from NARR and calibrated for several watersheds. The results indicated that the hydrological model can be reasonably calibrated using NARR data as input. The relatively good agreement between precipitation from NARR and observed station data suggests that NARR information may be used in the estimation of missing precipitation records at weather stations. Several traditional methods for estimating missing data were compared with three NARR-based estimation methods.
The results show that NARR-based methods significantly improved the estimation of precipitation compared to the traditional methods. The existence of NARR bias is a critical issue that must be addressed prior to the use of the data. Using observed weather station data, a statistical interpolation technique (also known as Optimum Interpolation) was employed to correct gridded NARR precipitation for bias. The results suggest that the method significantly reduces NARR bias over the selected study area.
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An investigation of sea-breeze driven convection along the northern Gulf CoastFord, Caitlin 13 May 2022 (has links) (PDF)
Although sea-breezes frequently initiate convection, it is oftentimes challenging to forecast the precise location of storm development. This research examines temporal and spatial characteristics of sea-breeze driven convection and environmental conditions that support convective or non-convective sea-breeze days along the Northern Gulf Coast. Base reflectivity products were used to identify the initial time of convection (values greater than 30 dBZs) along the sea-breeze front. It was found that convective sea-breezes initiated earlier in the day compared to non-convective sea-breezes. Mapping convective cells in ArcGIS revealed favored locations of thunderstorm development including the southeastern cusp of Mobile County, Alabama and convex coastlines. Meteorological variables from the North American Regional Reanalysis dataset were compared between convective and non-convective sea-breeze days via a bootstrap analysis to reveal environmental characteristics pertinent to forecasting sea-breeze driven convection. Lapse rates, CAPE, CIN, specific humidity, dew point temperature, relative humidity, and precipitable water values were statistically significant.
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Reconstruction et analyse de sensibilité climatique du bilan de masse du glacier Saskatchewan, CanadaLarouche, Olivier January 2020 (has links) (PDF)
No description available.
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Present and Future Wind Energy Resources in Western CanadaDaines, Jeffrey Thomas 17 September 2015 (has links)
Wind power presently plays a minor role in Western Canada as compared to
hydroelectric power in British Columbia and coal and natural gas thermal power generation in Alberta. However, ongoing reductions in the cost of wind power generation
facilities and the increasing costs of conventional power generation, particularly if the
cost to the environment is included, suggest that assessment of the present and future
wind field in Western Canada is of some importance.
To assess present wind power, raw hourly wind speeds and homogenized monthly
mean wind speeds from 30 stations in Western Canada were analyzed over the period
1971-2000 (past). The hourly data were adjusted using the homogenized monthly
means to attempt to compensate for differences in anemometer height from the standard
height of 10m and changes in observing equipment at stations.
A regional reanalysis product, the North American Regional Reanalysis (NARR),
and simulations conducted with the Canadian Regional Climate Model (CRCM)
driven with global reanalysis boundary forcing, were compared to the adjusted station
wind-speed time-series and probability distributions. The NARR had a better temporal
correlation with the observations, than the CRCM. We posit this is due to the NARR assimilating regional observations, whereas the
CRCM did not. The NARR was generally worse than the CRCM in reproducing the observed speed distribution, possibly due to the crude representation of the regional
topography in NARR. While the CRCM was run at both standard (45 km) and
fine (15 km) resolution, the fine grid spacing does not always provide better results:
the character of the surrounding topography appears to be an important factor for
determining the level of agreement.
Multiple simulations of the CRCM at the 45 km resolution were also driven by
two global climate models (GCMs) over the periods 1971-2000 (using only historic
emissions) and 2031-2060 (using the A2 emissions scenario). In light of the CRCM
biases relative to the observations, these simulations were calibrated using quantile-quantile matching to the adjusted station observations to obtain ensembles of 9 and
25 projected wind speed distributions for the 2031-2060 period (future) at the station
locations. Both bias correction and change factor techniques were used for calibration.
At most station locations modest increases in mean wind speed were found for most
of the projected distributions, but with a large variance.
Estimates of wind power density for the projected speed distributions were made
using a relationship between wind speed and power from a CRCM simulation for both
time periods using the 15km grid. As would be expected from the wind speed results
and the proportionality of wind power to the cube of wind speed, wind power at the
station locations is more likely than not to increase in the 2031-2060 period from the
1971-2000 period.
Relative changes in mean wind speeds at station locations were found to be insensitive
to the station observations and choice of calibration technique, suggesting
that we estimate relative change at all 45km grid points using all pairs of past/future
mean wind speeds from the CRCM simulations. Overall, our results suggest that
wind energy resources in Western Canada are reasonably likely to increase at least
modestly in the future. / Graduate / 0725 / 0608 / jtdaines@uvic.ca
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