Canadian Global Research Articles

Ice water content and precipitation rate as a function of equivalent radar reflectivity and temperature based on in situ observations

Using ice particle spectra measured in stratiform ice clouds in midlatitude and Arctic regions, ice water content (IWC) and precipitation rate (Fm) retrieval algorithms as a function of temperature and radar reflectivity factor (Z) have been developed. These parameterizations were compared with (1) direct measurements of IWC using a Nevzorov probe, (2) precipitation retrieved using an X‐band Doppler scanning radar and a Precipitation Occurrence Sensor System (POSS), (3) the Canadian Global Environmental Multiscale (GEM) and High‐Resolution Model Application Project (HIMAP) models, and (4) derived IWC and precipitation from measured ice spectra during four field projects. The derived IWC and Fm from measured spectra have a correlation coefficient (r) better than 0.8. The IWC retrieved using the X‐band scanning radar during the First Alliance Icing Research Studies (AIRS I) agreed with IWC measured using the Nevzorov Probe much better than conventional IWC retrieval schemes. The retrieved precipitation rate based on the new algorithm using the POSS reflectivity measurements during the Second Alliance Icing Research Study (AIRS II) project agreed reasonably well with the precipitation rates predicted by the GEM and HIMAP models. This study clearly demonstrated that conventional IWC‐Ze relationships fail to replicate the IWC measured with Nevzorov probe. Furthermore, the Fm –Z relationship currently in use in the Canadian operational radar network appears to underestimate the ice precipitation rate. However, since there are some uncertainties in the direct measurements of IWC and no reliable direct measurements of precipitation, further studies are required to validate these parameterizations.

Uncertainty analysis of statistical downscaling methods using Canadian Global Climate Model predictors

AbstractThree downscaling models, namely the Statistical Down‐Scaling Model (SDSM), the Long Ashton Research Station Weather Generator (LARS‐WG) model and an artificial neural network (ANN) model, have been compared in terms of various uncertainty attributes exhibited in their downscaled results of daily precipitation, daily maximum and minimum temperature. The uncertainty attributes are described by the model errors and the 95% confidence intervals in the estimates of means and variances of downscaled data. The significance of those errors has been examined by suitable statistical tests at the 95% confidence level. The 95% confidence intervals in the estimates of means and variances of downscaled data have been estimated using the bootstrapping method and compared with the observed data. The study has been carried out using 40 years of observed and downscaled daily precipitation data and daily maximum and minimum temperature data, starting from 1961 to 2000. In all the downscaling experiments, the simulated predictors of the Canadian Global Climate Model (CGCM1) have been used. The uncertainty assessment results indicate that, in daily precipitation downscaling, the LARS‐WG model errors are significant at the 95% confidence level only in a very few months, the SDSM errors are significant in some months, and the ANN model errors are significant in almost all months of the year. In downscaling daily maximum and minimum temperature, the performance of all three models is similar in terms of model errors evaluation at the 95% confidence level. But, according to the evaluation of variability and uncertainty in the estimates of means and variances of downscaled precipitation and temperature, the performances of the LARS‐WG model and the SDSM are almost similar, whereas the ANN model performance is found to be poor in that consideration. Further assessment of those models, in terms of skewness and average dry‐spell length comparison between observed and downscaled daily precipitation, indicates that the downscaled daily precipitation skewness and average dry‐spell lengths of the LARS‐WG model and the SDSM are closer to the observed data, whereas the ANN model downscaled precipitation underestimated those statistics in all months. Copyright © 2006 John Wiley & Sons, Ltd.

Comparing modelled responses of two high-permeability, unconfined aquifers to predicted climate change

The responses of two small, regional-scale aquifers to predicted climate change are compared. The aquifers are unconfined, heterogeneous, highly permeable, and representative of glaciofluvial environments in southern British Columbia, Canada and Washington State, USA. In one case, river–aquifer interactions dominate the hydraulic response. The climate change data set is that predicted by Canadian Global Climate Model 1 (CGCM1), for consecutive 30-yr intervals from present to 2069. Downscaling of GCM predictions and stochastic weather generation were done for each geographic location separately. Both studies employed identical methodologies and software for downscaling global climate model data, modelling weather for input to recharge models, determining the spatio-temporal distribution of recharge, and modelling groundwater flow using MODFLOW. Results suggest observable, but small, changes in groundwater levels, forced by changes in recharge. At the site in which river–aquifer interactions occur, water levels within the floodplain respond significantly and more directly to shifts in the river hydrograph under scenarios of climate change.

Simulating forest ecosystem response to climate warming incorporating spatial effects in north‐eastern China

AbstractAim Predictions of ecosystem responses to climate warming are often made using gap models, which are among the most effective tools for assessing the effects of climate change on forest composition and structure. Gap models do not generally account for broad‐scale effects such as the spatial configuration of the simulated forest ecosystems, disturbance, and seed dispersal, which extend beyond the simulation plots and are important under changing climates. In this study we incorporate the broad‐scale spatial effects (spatial configurations of the simulated forest ecosystems, seed dispersal and fire disturbance) in simulating forest responses to climate warming. We chose the Changbai Natural Reserve in China as our study area. Our aim is to reveal the spatial effects in simulating forest responses to climate warming and make new predictions by incorporating these effects in the Changbai Natural Reserve.Location Changbai Natural Reserve, north‐eastern China.Method We used a coupled modelling approach that links a gap model with a spatially explicit landscape model. In our approach, the responses (establishment) of individual species to climate warming are simulated using a gap model (linkages) that has been utilized previously for making predictions in this region; and the spatial effects are simulated using a landscape model (LANDIS) that incorporates spatial configurations of the simulated forest ecosystems, seed dispersal and fire disturbance. We used the recent predictions of the Canadian Global Coupled Model (CGCM2) for the Changbai Mountain area (4.6 °C average annual temperature increase and little precipitation change). For the area encompassed by the simulation, we examined four major ecosystems distributed continuously from low to high elevations along the northern slope: hardwood forest, mixed Korean pine hardwood forest, spruce‐fir forest, and sub‐alpine forest.Results The dominant effects of climate warming were evident on forest ecosystems in the low and high elevation areas, but not in the mid‐elevation areas. This suggests that the forest ecosystems near the southern and northern ranges of their distributions will have the strongest response to climate warming. In the mid‐elevation areas, environmental controls exerted the dominant influence on the dynamics of these forests (e.g. spruce‐fir) and their resilience to climate warming was suggested by the fact that the fluctuations of species trajectories for these forests under the warming scenario paralleled those under the current climate scenario.Main conclusions With the spatial effects incorporated, the disappearance of tree species in this region due to the climate warming would not be expected within the 300‐year period covered by the simulation. Neither Korean pine nor spruce‐fir was completely replaced by broadleaf species during the simulation period. Even for the sub‐alpine forest, mountain birch did not become extinct under the climate warming scenario, although its occurrence was greatly reduced. However, the decreasing trends characterizing Korean pine, spruce, and fir indicate that in simulations beyond 300 years these species could eventually be replaced by broadleaf tree species. A complete forest transition would take much longer than the time periods predicted by the gap models.

Downscaling Precipitation and Temperature with Temporal Neural Networks

Abstract The issues of downscaling the outputs of a global climate model (GCM) to a scale that is appropriate to hydrological impact studies are investigated using a temporal neural network approach. The time-lagged feed-forward neural network (TLFN) is proposed for downscaling daily total precipitation and daily maximum and minimum temperature series for the Serpent River watershed in northern Quebec (Canada). The downscaling models are developed and validated using large-scale predictor variables derived from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis dataset. Atmospheric predictors such as specific humidity, wind velocity, and geopotential height are identified as the most relevant inputs to the downscaling models. The performance of the TLFN downscaling model is also compared to a statistical downscaling model (SDSM). The downscaling results suggest that the TLFN is an efficient method for downscaling both daily precipitation and temperature series. The best downscaling models were then applied to the outputs of the Canadian Global Climate Model (CGCM1), forced with the Intergovernmental Panel on Climate Change (IPCC) IS92a scenario. Changes in average precipitation between the current and the future scenarios predicted by the TLFN are generally found to be smaller than those predicted by the SDSM model. Furthermore, application of the downscaled data for hydrologic impact analysis in the Serpent River resulted in an overall increasing trend in mean annual flow as well as earlier spring peak flow. The results also demonstrate the emphasis that should be given in identifying the appropriate downscaling tools for impact studies by showing how a future climate scenario downscaled with different downscaling methods could result in significantly different hydrologic impact simulation results for the same watershed.

Canadian Global Database May Move to Singapore After Loss of Funding

OTTAWA, CANADA-- The world9s largest free repository for proteomics data appears headed to Singapore from Toronto, barring an 11th-hour reprieve by Canadian funding authorities.

Evaluation of GPS Precipitable Water over Canada and the IGS Network

Abstract Precipitable water (PW) derived from the GPS zenith tropospheric delay (ZTD) is evaluated (as a first step toward variational data assimilation) through comparison with that of collocated radiosondes (RS_PW), operational analyses, and 6-h forecasts (from the Canadian Global Environmental Multiscale model) of the Canadian Meteorological Centre. Two sources of ZTD data are considered: 1) final ZTD (over Canada), computed by the Geodetic Survey Division (GSD) of Natural Resources Canada, and 2) final ZTD (distributed globally), obtained from the International GPS Service (IGS). The mean GSD GPS–derived PW (GPS_PW) is 14.9 mm (reflecting the relatively cold Canadian climate), whereas that of the IGS dataset is 20.8 mm. Intercomparison statistics [correlation, standard deviation (SD), and bias] between GPS_PW and RS_PW are, respectively, 0.97, 2.04 mm, and 1.35 mm for the GSD data and 0.98, 2.6 mm, and 0.67 mm for the IGS data. Comparisons of GPS_PW with 6-h forecast PW (TRIAL_PW) show slightly lower correlations and a higher SD. The increase in SD is greater for the IGS data, which is not surprising, because in regions such as the Tropics and subtropics, moisture forecasts are of a lower quality and the RS observation network is sparse. From a three-way intercomparison (IGS GPS_PW, RS_PW, and TRIAL_PW) of the SD statistics, it is found that GPS_PW has the lowest estimated PW error (≈1 mm) for PW in the 5–30-mm range. For PW greater than 30 mm, the RS_PW estimated error is ≈2 mm, and that of GPS_PW is ≈2.5 mm. The TRIAL_PW estimated error increases with PW, reaching 5.5 mm in the 40–55-mm PW range. These intercomparison results indicate that GPS_PW should be a useful source of humidity information for NWP applications.

Weather systems occurring over Fort Simpson, Northwest Territories, Canada, during three seasons of 1998–1999: 1. Cloud features

An investigation of high‐latitude continental cloud systems was carried out in the interior of the Northwest Territories of Canada during three multiweek periods during the fall, winter, and spring of 1998–1999 as part of the Canadian Global Energy and Water Cycle Experiment (GEWEX) Enhanced Study. Radar data supplemented by satellite, upper air, and surface observations were used to determine the seasonal behavior of cloud macroscopic properties and compare these with similar observations elsewhere. Unique features included the prevalence of multilayered systems, the cold temperatures of low clouds, and a significant diurnal trend in cloud properties in the winter. A synoptic classification was developed and shown to be an important factor in explaining the variability of cloud properties. A consistent picture emerges of the upslope component and wind shear aloft contributing to the cloud structure in five synoptic classes. Vertically resolved cloud properties highlighted the importance of the ice process in these cloud systems. The cloud system reflectivity and temperature dependencies further supported the synoptic characterizations and highlighted the significance of using seasonally based relationships in automated cloud identification algorithms. The implication of the cloud system variability for radiation measurements was also shown. The radar reflectivity data, degraded to match CloudSat resolution and sensitivity, showed that cloud detection was reliable but that there was a positive bias with cloud thickness. Negative biases in cloud top retrievals based on advanced very high resolution radiometer data were also identified. The Global Environmental Multiscale model illustrated some degree of bias in the occurrence and vertical distribution of these cloud systems. Winter situations in general and midclouds situations in particular were the most poorly handled in both the satellite applications and the model simulations.

Impact of the GEM model simplified physics on extratropical singular vectors

AbstractA simplified physics package, containing parametrizations of vertical diffusion, subgrid‐scale orographic drag, stratiform precipitation and convective precipitation, was built for the four‐dimensional variational data assimilation system that is being developed for the Canadian Global Environmental Multiscale model. To validate this package and measure its impact on the behaviour of unstable disturbances, a series of singular vector experiments was conducted. In a control experiment with vertical diffusion only, a set of 45 extratropical singular vectors was generated for a northern hemisphere winter case, using the total energy norm and an optimization time interval of 48 hours. Subsequently, the remaining components of the simplified physics were activated one by one and their influence was measured by changes in the energy partition, energy growth and spatial distribution of singular vectors. Cross‐propagation tests were also made, where singular vectors from one experiment were evolved with the tangent‐linear model of another. Results show that the orographic drag reduces the growth of singular vectors while the moist physics enhance the growth and shifts the energy of singular vectors toward smaller scales. Integrations of the nonlinear model with full physics indicate that, for amplitudes typical of analysis increments, the evolution of extratropical singular vectors is well described by the linearized model although growth rates are reduced by nonlinearities. © Crown copyright, 2004. Royal Meteorological Society

Climate change and winter damage to fruit trees in eastern Canada

Climatic conditions during the cold season represent a serious constraint to fruit production in eastern Canada. Meteorological models predict that temperatures of winter months will increase by 2 to 6°C by 2050. The possible impact of climate change on fruit trees in eastern Canada was assessed using agroclimatic indices expressing the risks associated with known causes of damage during fall, winter, and spring. Indices were calculated for 15 agricultural regions in eastern Canada for recent (1961–1990) and future periods (2010–2039 and 2040–2069) using temperature and precipitation data predicted by the Canadian Global General Circulation Model (CGCMI). Averaged across all agricultural regions, the first fall frost in 2040–2069 would be delayed by 16 d while the last spring frost (≤-2°C) would be advanced by 15 d. By 2040 to 2069, the risks of damage to fruit trees by early winter frosts in eastern Canada are likely to decrease because the shorter photoperiod at the time of the first fall frost would result in a longer hardening period. Milder winter temperatures will also reduce the cold stress as the accumulation of cold degree-days (<-15°C) would be reduced and the annual minimum temperature would be increased in all regions of eastern Canada. More frequent winter thaw events, however, would result in a loss of hardiness and in a thinner snow cover that would increase the plant vulnerability to subsequent extreme sub-freezing temperatures. The risk of damage to flower buds by a late frost would increase in southern Ontario, remain almost unchanged in the Maritimes and Ottawa Valley-southern Québec regions, and decrease in the Continental North. The projected climate change should allow for the introduction of new varieties and species where fruit trees are currently grown and for an extension further north of the commercial production in eastern Canada. Key words: Overwintering, fruit production, climatic indices, winter injury, spring frost

Monthly Mean Afternoon Mixing-Layer Depths “Tuned” to the Eco-Climatic Regions of the Canadian Prairie Provinces

A simple diagnostic model was used to derive afternoon (0000 UTC) mixing-layer depths from gridded zero hour output from the Canadian Global Environmental Multiscale (GEM) numerical weather model interpolated to approximately 200 locations in the Prairie provinces of Canada. Knowledge of the spatial pattern of monthly mean afternoon mixing-layer depths was enhanced by associating the annual cycles of monthly means with eco-climatic regions – regions with fairly uniform terrain and soils, and where similar vegetation indicate that the area experiences, on average, similar synoptic-scale weather and produces similar surface fluxes of heat and moisture. When the mixing-layer depth is used to assess the dilution of airborne pollutants or to determine the specific humidity of the boundary layer, the eco-climatic region rather than proximity to the location-of-interest should be the primary factor in the selection of an appropriate radiosonde site.

Statistical downscaling and scenario construction of precipitation in Scania, southern Sweden

Statistical downscaling models for precipitation in Scania, southern Sweden, have been developed and applied to calculate the changes in the future Scanian precipitation climate due to projected changes in the atmospheric composition. The models are based on multiple linear regression, linking large-scale predictors at monthly time resolution to regional statistics of daily precipitation on a monthly basis. To account for spatial precipitation variability within the area, the precipitation statistics were derived for different regions in Scania. The final downscaling models, developed for different regions and seasons, use atmospheric circulation, large-scale humidity and precipitation as predictors. Among the precipitation statistics examined, only the models for estimating the mean precipitation and the frequency of wet days were skilful. Based on the Canadian Global Circulation Model 1 (CGCM1), a future scenario of these two statistics was created. The downscaled scenario shows a significant increase of the annual mean precipitation by about 10% and a slight decrease in the frequency of wet days, indicating an increase in the precipitation amounts as well as in the precipitation intensity. The main increase of precipitation amounts and intensity occur during winter, while the summer precipitation amounts decrease slightly. The seasonal changes found in precipitation are likely attributed to changes in the westerly flow of the atmospheric circulation.

Multisensor analysis of integrated atmospheric water vapor over Canada and Alaska

Atmospheric water vapor is a key parameter for the analysis of climatic systems (greenhouse gas effect), in particular over high latitudes where water vapor displays an important seasonal variability. The sparse spatial and temporal sampling of atmospheric water vapor observations across Canada needs to be improved. A series of instruments and methods including a 940‐nm solar absorption band radiometer (R) and radiosonde (S) analysis from a numerical weather prediction model and a ground‐based bi‐frequency Global Positioning System (GPS) were used to evaluate the integrated atmospheric water vapor (IWV) at various sites in Canada and Alaska from a multiyear database. The IWV‐R measurements were collected within the framework of the North American Sun Radiometry network (AERONET/AEROCAN). Intercomparisons between [IWV‐GPS and IWV‐S], [IWV‐R and IWV‐GPS], and [IWV‐R and IWV‐S] show root mean square (RMS) differences of 1.8, 1.9, and 2.2 kg m−2, respectively. GPS meteorology appears to be the easiest approach to calibrate the solar radiometer water vapor band owing to its flexibility, and it allows us to overcome the Sun radiometry limitation in high‐latitude areas like the Arctic. The sensitivity of the GPS retrieval to various parameters like GPS satellite constellation and meteorological data are discussed. The classical linear relationship between the surface temperature and the integrated weighted mean temperature profile needed for IWV‐GPS retrieval may be significantly different for Arctic air masses compared with midlatitude air masses in the case of tropospheric temperature profile inversion. An ever‐expanding multiyear (1994–2001) North American summer water vapor climatology, derived from AERONET/Canadian Sun Radiometer Network, is presented and analyzed, showing a mean value of 19.8 ± 6.1 kg m−2 and variations from 17 kg m−2 in Alaska to 23 kg m−2 in southeastern Canada. The results in Bonanza Creek, Alaska, show significant interannual variations with a peak in 1997, which may be linked to an El Niño event that occurred in the same year. Such a database may also be useful for climate model validation as shown for the Canadian Global Environmental Model (RMS difference of 3.4 kg m−2). In the end we show that, even if data are selected only for cloud‐free atmospheres, there are no significant differences as compared with radiosonde climatology at Canadian Northwestern sites (≤3% relatively to Bonanza Creek summer mean value).

Over-Lake Meteorology and Estimated Bulk Heat Exchange of Great Slave Lake in 1998 and 1999

Abstract Meteorological and thermistor moorings were deployed in Great Slave Lake during the Canadian Global Energy and Water Cycle Experiment (GEWEX) Enhanced Study (CAGES) in 1998 and 1999. Large-scale meteorology included influence from a record ENSO extending from 1997 to mid-1998. Meteorological variables varied across the lake especially during the lake-heating phase after ice breakup. Generally higher over-lake air temperature and surface water temperatures occurred in 1998, but larger vapor pressure gradients over water and ∼8% higher solar radiation was observed in 1999. Although wind speed averages were similar in both years, nearly 30% more over-lake storms with winds >10 m s−1 occurred in 1998. High sensitivity of the lake temperatures to surface wind forcing was observed in 1998 in the spring warming phase. Passive microwave imagery [from the Special Sensor Microwave Imager (SSM/I)] at 85 GHz showed a record 213 ice-free days in 1998 compared to 186 days in 1999. The extended ice-free period ...

Radiation Budgets in the Mackenzie River Basin: Retrieval from Satellite Observations and an Evaluation of the Canadian Regional Climate Model

Abstract The Canadian Global Energy and Water Cycle Experiment (GEWEX) Enhanced Study (CAGES) was a 14-month period in 1998–99 during which there were enhanced measurements of water vapor, precipitation, snow cover, radiation, snowmelt, evaporation, stream discharge, and other variables in the Mackenzie River basin (MRB). These measurements provided the initialization and validation fields for modeling and remote sensing studies. During the CAGES period there were only limited broadband satellite observations of radiation fluxes over the MRB from the second flight module of the Scanner for Radiation Budget (ScaRaB) instrument. A more extensive dataset of solar radiation fluxes at the top of the atmosphere (TOA) and at the surface was derived for CAGES from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) observations. The derived solar radiation fluxes at the surface were evaluated against the surface measurements in the basin. The results show th...

Modeling Mackenzie Basin Surface Water Balance during CAGES with the Canadian Regional Climate Model

Abstract The Canadian Regional Climate Model has been used to estimate surface water balance over the Mackenzie River basin during the water year 1998–99 in support of the Canadian Global Energy and Water Cycle Experiment (GEWEX) Enhanced Study (CAGES). The model makes use of a developmental third-generation physics parameterization package from the Canadian Centre for Climate Modelling and Analysis GCM, as well as a high-resolution land surface dataset. The surface water balance is simulated reasonably well, though Mackenzie basin annual mean daily maximum and minimum temperatures were both colder than observed by 1.7°C. The cold bias contributed to a longer snow-covered season and larger peak snow water equivalent than was observed, though snow accumulated realistically compared with two independently observed estimates after 1 November. Mackenzie basin annual precipitation was simulated as 496 mm, about 9% larger than observed, and P − E was 225 mm. Net soil moisture change during this water year was f...

Energy Budget Processes of a Small Northern Lake

Abstract There is a paucity of information on the energy budget of Canada's northern lakes. This research determines processes controlling the magnitude of energy fluxes between a small Canadian Shield lake and the atmosphere. Meteorological instruments were deployed on a floating platform in the middle of a 5-ha lake during the 1999 and 2000 open-water seasons. High attenuation of incoming radiation at shallow depths and the sheltered location of the lake allows a strong thermocline to develop during the summer months, which prevents deeper water from exchanging energy with the atmosphere. Only after the lake becomes isothermal in late August do deeper waters interact with the atmosphere. When the lake is warming, evaporation is controlled by net radiation, but when the lake is cooling, turbulent energy fluxes are mainly influenced by the vapor pressure deficit. An empirically derived logarithmic relationship was identified between the Bowen ratio and the vapor pressure deficit. The Canadian Global Energ...

Interannual and Seasonal Variability of the Surface Energy Balance and Temperature of Central Great Slave Lake

This paper addresses interannual and seasonal variability in the thermal regime and surface energy fluxes in central Great Slave Lake during three contiguous open-water periods, two of which overlap the Canadian Global Energy and Water Cycle Experiment (GEWEX) Enhanced Study (CAGES) water year. The specific objectives are to compare the air temperature regime in the midlake to coastal zones, detail patterns of air and water temperatures and atmospheric stability in the central lake, assess the role of the radiation balance in driving the sensible and latent heat fluxes on a daily and seasonal basis, quantify magnitudes and rates of the sensible and latent heat fluxes and evaporation, and present a comprehensive picture of the seasonal and interannual thermal and energy regimes, their variability, and their most important controls. Atmospheric and lake thermal regimes are closely linked. Temperature differences between midlake and the northern shore follow a seasonal linear change from 68C colder midlake in June, to 68C warmer in November‐December. These differences are a response to the surface energy budget of the lake. The surface radiation balance, and sensible and latent heat fluxes are not related on a day-to-day basis. Rather, from final lake ice melt in mid-June through to mid- to late August, the surface waters strongly absorb solar radiation. A stable atmosphere dominates this period, the latent heat flux is small and directed upward, and the sensible heat flux is small and directed downward into the lake. During this period, the net solar radiation is largely used in heating the lake. From mid- to late August to freeze up in December to early January, the absorbed solar radiation is small, the atmosphere over the lake becomes increasingly unstable, and the sensible and latent heat fluxes are directed into the atmosphere and grow in magnitude into the winter season. Comparing the period of stable atmospheric conditions with the period of unstable conditions, net radiation is 6 times larger during the period of stable atmosphere and the combined latent and sensible heat fluxes are 9 times larger during the unstable period. From 85% to 90% of total evaporation occurs after mid-August, and evaporation rates increase continuously as the season progresses. This rate of increase varies from year to year. The time of final ice melt exerts the largest single control on the seasonal thermal and energy regimes of this large northern lake.

Global estimation of crop productivity and the impacts of global warming by GIS and EPIC integration

In this paper, a new methodology for global estimation of crop productivity is proposed. This methodology integrates Erosion Productivity Impact Calculator (EPIC) model with Geographic Information System (GIS) and Inference Engine (IE) technique. EPIC was developed by USDA to analyze the relationship between soil erosion and agricultural productivity just at field level. With the integration of GIS, EPIC can be extended to the application of global or regional level. In this integration, IE is developed to determine possible crop combinations, the optimum starting and ending dates of growth cycle for each crop type and grid cell, in order to ensure best possible crop yields for both rain-fed and irrigated conditions. A case of global crop productivity estimation is tested with GIS-based EPIC in 2000. National averages are computed to be comparable to yields in FAO statistics. The comparison indicates that the GIS-based EPIC is able to simulate crop productivity at global level. In addition, with the global climate change data provided by the Intergovernment Panel on Climate Change (IPCC) from the first version of the Canadian Global Coupled Model (CGCM1), GIS-based EPIC is run for scenarios of future climate in the year of 2010, 2020, 2030, 2040, and 2050 to predict the effects of global warming on main crop yields. Results show the global warming will be harmful for most of the countries, and an efficient adaptation to alternative climates tends to reduce the damages.

The subgrid‐scale orographic blocking parametrization of the GEM Model

The impact of the physical parametrization called subgrid‐scale orographic blocking, recently introduced in the physics of the Canadian Global Environmental Mutiscale (GEM) model is described. It is based on a formulation by Lott and Miller (1997) and represents the unresolved component of the drag on low‐level winds that are blocked at the flanks of mountains. The blocking term plus the gravity‐wave drag are now part of a unified parametrization of the subgrid orographic drag that became operational in the global GEM model on 11 December 2001. Results from tests made with various configurations of the model are shown, illustrating how the blocking term impacts the large‐scale flow and improves both the short‐ and the medium‐range forecasts, especially in winter. It is shown that at day 5 of the model integrations, the influence of the blocking force applied near the surface is felt by the entire tropospheric and the lower‐stratospheric circulation. A mechanism based on perturbations of the Eliassen‐Palm flux caused by the low‐level forcing is proposed to explain the vertical propagation of the signal generated by the blocking term.