An investigation of the impact of the subgrid-scale variability of cloud liquid water on the autoconversion process as parameterized in a general circulation model is presented in this paper. For this purpose, a prognostic statistical probability density distribution (PDF) of the subgrid scale variability of cloud water is incorporated in a continuous autoconversion parameterization. Thus, the revised autoconversion rate is calculated by an integral of the autoconversion equation over the PDF of total water mixing ratio from the saturation vapor mixing ratio to the maximum of total water mixing ratio. An evaluation of the new autoconversion parameterization is carried out by means of one year simulations with the ECHAM5 climate model. The results indicate that the new autoconversion scheme causes an increase of the frequency of occurrence of high autoconversion rates and a decrease of low ones compared to the original scheme. This expected result is due to the emphasis on areas of high cloud liquid water in the new approach, and the non-linearity of the autoconversion with respect to liquid water mixing ratio. A similar trend as in the autoconversion is observed in the accretion process resulting from the coupling of both processes. As a consequence of the altered autoconversion, large-scale surface precipitation also shows a shift of occurrence from lower to higher rates. The vertically integrated cloud liquid water estimated by the model shows slight improvements compared to satellite data. Most importantly, the artificial tuning factor for autoconversion in the continuous parameterization could be reduced by almost an order of magnitude using the revised parameterization.

Three different boundary layer cloud models are incorporated into the ECHAM5 general circulation model (GCM) and compared to CloudSat and CALIPSO satellite observations. The first boundary layer model builds upon the standard Tiedtke (1989) parameterization for shallow convection with an adapted convective trigger; the second is a bulk parameterization of the effects of transient shallow cumulus clouds; and lastly the Dual Mass Flux (DMF) scheme adjusted to better represent shallow convection. The three schemes improved (Sub)Tropical oceanic low-level cloud cover, however, the fraction of low-level cloud cover remains underestimated compared to CALIPSO observations. The representation of precipitation was improved by all schemes as they reduced the frequency of light intensity events <0.01 mm d-1, which were found to dominate the radar reflectivity histograms as well as be the greatest source of differences between ECHAM5 and CloudSat radar reflectivity histograms. For both lidar and radar diagnostics, the differences amongst the schemes are smaller than the differences compared to observations. While the DMF approach remains experimental, as its top-of-atmosphere radiative balance has not been retuned, it shows the most promise in producing nonprecipitating boundary layer clouds. With its internally consistent boundary layer scheme that uses the same bimodal joint distribution with a diffusive and an updraft component for clouds and turbulent transport, the ECHAM5_DMF produces the most realistic boundary layer depth as indicated by the cloud field. In addition, it reduced the frequency of large-scale precipitation intensities of <0.01 mm d-1 the greatest.

Three different boundary layer cloud models are incorporated into the ECHAM5 general circulation model (GCM) and compared to CloudSat and CALIPSO satellite observations. The first boundary layer model builds upon the standard Tiedtke (1989) parameterization for shallow convection with an adapted convective trigger; the second is a bulk parameterization of the effects of transient shallow cumulus clouds; and lastly the Dual Mass Flux (DMF) scheme adjusted to better represent shallow convection. The three schemes improved (Sub)Tropical oceanic low-level cloud cover, however, the fraction of low-level cloud cover remains underestimated compared to CALIPSO observations. The representation of precipitation was improved by all schemes as they reduced the frequency of light intensity events <0.01 mm d-1, which were found to dominate the radar reflectivity histograms as well as be the greatest source of differences between ECHAM5 and CloudSat radar reflectivity histograms. For both lidar and radar diagnostics, the differences amongst the schemes are smaller than the differences compared to observations. While the DMF approach remains experimental, as its top-of-atmosphere radiative balance has not been retuned, it shows the most promise in producing nonprecipitating boundary layer clouds. With its internally consistent boundary layer scheme that uses the same bimodal joint distribution with a diffusive and an updraft component for clouds and turbulent transport, the ECHAM5_DMF produces the most realistic boundary layer depth as indicated by the cloud field. In addition, it reduced the frequency of large-scale precipitation intensities of <0.01 mm d-1 the greatest.

An investigation of the impact of the subgrid-scale variability of cloud liquid water on the autoconversion process as parameterized in a general circulation model is presented in this paper. For this purpose, a prognostic statistical probability density distribution (PDF) of the subgrid scale variability of cloud water is incorporated in a continuous autoconversion parameterization. Thus, the revised autoconversion rate is calculated by an integral of the autoconversion equation over the PDF of total water mixing ratio from the saturation vapor mixing ratio to the maximum of total water mixing ratio. An evaluation of the new autoconversion parameterization is carried out by means of one year simulations with the ECHAM5 climate model. The results indicate that the new autoconversion scheme causes an increase of the frequency of occurrence of high autoconversion rates and a decrease of low ones compared to the original scheme. This expected result is due to the emphasis on areas of high cloud liquid water in the new approach, and the non-linearity of the autoconversion with respect to liquid water mixing ratio. A similar trend as in the autoconversion is observed in the accretion process resulting from the coupling of both processes. As a consequence of the altered autoconversion, large-scale surface precipitation also shows a shift of occurrence from lower to higher rates. The vertically integrated cloud liquid water estimated by the model shows slight improvements compared to satellite data. Most importantly, the artificial tuning factor for autoconversion in the continuous parameterization could be reduced by almost an order of magnitude using the revised parameterization.

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