ALBERT

Beschreibung: Recently, two analog-based postprocessing methods were demonstrated to reduce the systematic and random errors from Weather Research and Forecasting (WRF) Model predictions of 10-m wind speed over the central United States. To test robustness and generality, and to gain a deeper understanding of postprocessing forecasts with analogs, this paper expands upon that work by applying both analog methods to surface stations evenly distributed across the conterminous United States over a 1-yr period. The Global Forecast System (GFS), North American Mesoscale Forecast System (NAM), and Rapid Update Cycle (RUC) forecasts for screen-height wind, temperature, and humidity are postprocessed with the two analog-based methods and with two time series–based methods—a running mean bias correction and an algorithm inspired by the Kalman filter. Forecasts are evaluated according to a range of metrics, including random and systematic error components; correlation; and by conditioning the error distributions on lead time, location, error magnitude, and day-to-day error variability. Results show that the analog methods are generally more effective than time series–based methods at reducing the random error component, leading to an overall reduction in root-mean-square error. Details among the methods differ and are elucidated upon in this study. The relative levels of random and systematic error in the raw forecasts determine, to a large extent, the effectiveness of each postprocessing method in reducing forecast errors. When the errors are dominated by random errors (e.g., where thunderstorms are common), the analog-based methods far outperform the time series–based methods. When the errors are strictly systematic (i.e., a bias), the analog methods lose their advantage over the time series methods. It is shown that slowly evolving systematic errors rarely dominate, so reducing the random error component is most effective at reducing the error magnitude. The results are shown to be valid for all seasons. The analog methods show similar performance to the operational model output statistics (MOS) while showing greater reduction of random errors at certain lead times.

Beschreibung: The effects of small water bodies or lakes on the surface sensible and latent heat fluxes and the transport of heat and water vapour in the atmospheric boundary layer (ABL) over the Mackenzie River Basin (MRB) are studied from two cases, which occurred on 2 and 8 June 1999 during the warm season. The synoptic condition for the cases is representative of about 33% of the synoptic situation over the MRB. The two events are simulated using the Canadian mesoscale compressible community (MC2) model. A one-way nesting grid approach is employed with the highest resolution of 100 m over a domain of 100 km2. Experiments were conducted with (LAKE) and without (NOLAKE) the presence of small water bodies, whose size distribution is obtained through an inversion algorithm using information of their linear dimension determined from aircraft measurement of surface temperature during MAGS (the Mackenzie GEWEX (Global Energy and Water Cycle Experiment) Study) in 1999. The water bodies are assumed to be distributed randomly in space with a fractional area coverage of 10% over the MRB. The results show that, in the presence of lakes, the domain-averaged surface sensible heat flux on 2 June 1999 (8 June 1999) decreases by 9·3% (6·6%). The surface latent heat flux is enhanced by 18·2% (81·5%). Low-level temperature advection and the lake surface temperature affect the air-land/lake temperature contrast, which in turn controls the sensible heat flux. In the absence of lakes the surface wind speed impacts the latent heat flux, but in the presence of lakes the moisture availability and the atmospheric surface layer stability control the latent heat flux. The enhancement is smaller on 2 June 1999 as a result of a stable surface layer caused by the presence of colder lake temperatures. The domain-averaged apparent heat source and moisture sink due to turbulent transports were also computed. The results show that, when lakes are present, heating and drying occur in the lowest 100 m from the surface. Above 100 m and within the ABL, there was apparent cooling. However, the apparent moistening profiles reveal that lakes tend to moisten the ABL through transfer of moisture from the lowest 50-100 m layer. © 2004 John Wiley and Sons, Ltd.

Beschreibung: The arctic environment, and in particular the Mackenzie Basin, displays a vey dynamic interrelationship between the atmosphere and the surface for the different ecosystems represented. The Canadian Twin Otter research aircraft flew a total of 24 grid and long regional transects, over tundra, forest and delta ecosystems, during the period of snow melt (late May-early June) and early summer (early July) as part of the 1999 Mackenzie Area GEWEX (Global Energy and Water Cycle Experiment) Study (MAGS) field campaign. Observations over tundra showed a sharp rise in the sensible heat flux at the onset of melt, reaching a maximum at the end of the melting period similar to those observed in early summer. The latent heat flux showed a more gradual rise from snowmelt to early summer with a Bowen ratio (sensible heat/latent heat) of two during melt. The forested system demonstrated a similar gradual rise in the latent heat flux, whereas the sensible heat flux was already high with Bowen ratios reaching three at the start of the observation period in late May. The gradual rise in latent heat flux can be tied to gradual thawing of the root zone and the onset of photosynthesis activity. The relatively low solar elevation angle and earlier start of snow melt along the regional transect may account for the much larger sensible heat flux. An analysis of the turbulent coherent structures indicates that the spatial density of structures for both latent heat and sensible heat increases strongly with season, from snow melt into the early summer conditions. This has implications for sampling criteria and optimum flux averaging period. There are distinct differences in energy partitioning between the various arctic ecosystems. At the beginning of the observation period, almost all the net radiation over the delta and tundra regions is utilized in non-turbulent form, whereas the forested areas use less than 50%. Model simulations of the ground heat flux showed observed diurnal imbalances and suggest that the magnitudes depend on the position of the permafrost table and may partially account for the large non-turbulent energy. Preliminary results from the Canadian MC2 model using the MAGS aircraft data for diagnosis and validation have identified sensitive model components that may merit further investigation. The findings from this study will help to fill gaps in our knowledge about surface-atmosphere interactions in arctic environments, particularly during snow melt, and broadens our contemporary view of evapotranspiration dynamics of wet surfaces. Copyright © 2001 John Wiley & Sons, Ltd.

Beschreibung: A one-dimensional variational (1DVAR) technique is applied to assimilate rain gauge precipitation data to extend the predictability of the Saguenay flood cyclone associated with a trough-merger event on 19–21 July 1996 in the Saguenay-Lac-Saint-Jean region of Quebec, Canada. Two 60-h simulations initialized at 0000 UTC 19 July were performed with the Canadian Mesoscale Compressible Community (MC2) model. The control (CTL) and NCEP simulations were initialized with the enhanced temperature and moisture profiles obtained from the 1DVAR scheme and the NCEP reanalysis data, respectively. Compared to observations, the CTL simulation reasonably reproduced the observed mass and wind fields and showed a marked improvement in the threat scores for heavy precipitation. The CTL run captured the observed spatial and temporal distribution of precipitation but overpredicted the area of precipitation. Sensitivity experiments showed that the threat (bias) scores are less (somewhat) sensitive to the specification of the observation error of the precipitation data. Of the four precipitation systems present at model initial time, the systems in the vicinity of the southern trough had the biggest impact on the threat score. Potential vorticity diagnostics of the CTL simulation suggested that the initial temperature and moisture field near the southern trough decreased the condensational heating relative to NCEP. This resulted in a stronger zonal wind component in the upper levels associated with the southern trough in CTL that retarded the eastward propagation of the northern trough, resulting in a correct placement of the surface precipitation and an improvement in the threat scores relative to NCEP.

Beschreibung: This study explores an analog-based method to generate an ensemble [analog ensemble (AnEn)] in which the probability distribution of the future state of the atmosphere is estimated with a set of past observations that correspond to the best analogs of a deterministic numerical weather prediction (NWP). An analog for a given location and forecast lead time is defined as a past prediction, from the same model, that has similar values for selected features of the current model forecast. The AnEn is evaluated for 0–48-h probabilistic predictions of 10-m wind speed and 2-m temperature over the contiguous United States and against observations provided by 550 surface stations, over the 23 April–31 July 2011 period. The AnEn is generated from the Environment Canada (EC) deterministic Global Environmental Multiscale (GEM) model and a 12–15-month-long training period of forecasts and observations. The skill and value of AnEn predictions are compared with forecasts from a state-of-the-science NWP ensemble system, the 21-member Regional Ensemble Prediction System (REPS). The AnEn exhibits high statistical consistency and reliability and the ability to capture the flow-dependent behavior of errors, and it has equal or superior skill and value compared to forecasts generated via logistic regression (LR) applied to both the deterministic GEM (as in AnEn) and REPS [ensemble model output statistics (EMOS)]. The real-time computational cost of AnEn and LR is lower than EMOS.