Search Results

You are looking at 1 - 10 of 15 items for

  • Author or Editor: Gregory West x
  • All content x
Clear All Modify Search
Julia Jeworrek, Gregory West, and Roland Stull

Abstract

Physics parameterizations in the Weather Research and Forecasting (WRF) model are systematically varied to investigate precipitation forecast performance over the complex terrain of southwest British Columbia (BC). Comparing a full year of modelling data from over 100 WRF configurations to station observations reveals sensitivities of precipitation intensity, season, location, grid resolution, and accumulation window. The choice of cumulus and microphysics parameterizations is most important. The WSM5 microphysics scheme yields competitive verification scores when compared to more sophisticated and computationally expensive parameterizations. Although the scale-aware Grell-Freitas cumulus parameterization performs better for summertime convective precipitation, the conventional Kain-Fritsch parameterization better simulates wintertime frontal precipitation, which contributes to the majority of the annual precipitation in southwest BC. Finer grid spacings have lower relative biases and a more realistic spread in precipitation intensity distribution, yet higher relative standard deviations of their errors — they produce finer spatial differences and local extrema. Finer resolutions produce the best fraction of correct-to-incorrect forecasts across all precipitation intensities, whereas the coarser 27-km domain yields the highest hit rates and equitable threat scores. Verification metrics improve greatly with longer accumulation windows — hourly precipitation values are prone to double-penalty issues, while longer accumulation windows compensate for timing errors but lose information about short-term precipitation intensities. This study provides insights regarding WRF precipitation performance in complex terrain across a wide variety of configurations, using metrics important to a range of end users.

Open access
Julia Jeworrek, Gregory West, and Roland Stull

Abstract

This study evaluates the grid-length dependency of the Weather Research and Forecasting (WRF) Model precipitation performance for two cases in the Southern Great Plains of the United States. The aim is to investigate the ability of different cumulus and microphysics parameterization schemes to represent precipitation processes throughout the transition between parameterized and resolved convective scales (e.g., the gray zone). The cases include the following: 1) a mesoscale convective system causing intense local precipitation, and 2) a frontal passage with light but continuous rainfall. The choice of cumulus parameterization appears to be a crucial differentiator in convective development and resulting precipitation patterns in the WRF simulations. Different microphysics schemes produce very similar outcomes, yet some of the more sophisticated schemes have substantially longer run times. This suggests that this additional computational expense does not necessarily provide meaningful forecast improvements, and those looking to run such schemes should perform their own evaluation to determine if this expense is warranted for their application. The best performing cumulus scheme overall for the two cases studies here was the scale-aware Grell–Freitas cumulus scheme. It was able to reproduce a smooth transition from subgrid- (cumulus) to resolved-scale (microphysics) precipitation with increasing resolution. It also produced the smallest errors for the convective event, outperforming the other cumulus schemes in predicting the timing and intensity of the precipitation.

Open access
Pedro Odon, Gregory West, and Roland Stull

Abstract

Weather-station data coverage, quality, and completeness across British Columbia, Canada, degrade outside of population centers and as one goes back in time. This data paucity motivates the search for the best reanalysis to serve as a climatological reference dataset. This study focuses on how well reanalyses represent 2-m temperature (T2M). Systematic error, random error, and two-sample Kolmogorov–Smirnov statistics of daily maximum and minimum T2M are evaluated from the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim), the Climate Forecast System Reanalysis (CFSR), the Japanese 55-year Reanalysis (JRA-55), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Also evaluated are the 2- and 30-yr return levels of T2M, which are estimated by the method of L moments from a fitted generalized extreme value (GEV) distribution. Reanalyses are compared with observations from 57 meteorological stations distributed over the complex terrain of British Columbia from 1980 to 2010. Minimum temperatures are better captured than maximum temperatures by all four reanalyses. JRA-55 and ERA-Interim generally perform better across all metrics. Biases are largely explained by poor reanalysis terrain representation. Statistical stationarity over the 30-yr period is assessed by using Gaussian and GEV distributions fitted with and without time-dependent parameters. It is determined that stationary distributions are sufficient to represent the climate of T2M for this region and time period.

Open access
Gregory L. West and W. James Steenburgh

Abstract

High-resolution analyses and MesoWest surface observations are used to examine the life cycle and mesoscale frontal structure of the “Tax Day Storm,” an intermountain cyclone that produced the second lowest sea level pressure observed in Utah during the instrumented period and the strongest cold frontal passage at the Salt Lake City International Airport in the past 25 years. A key mesoscale surface feature contributing to the cyclone’s evolution is a confluence zone that extends downstream from the Sierra Nevada across the Great Basin. Strong contraction (i.e., deformation and convergence) within this Great Basin confluence zone (GBCZ) forms an airstream boundary that is initially nonfrontal but becomes the locus for surface frontogenesis as it collects and concentrates baroclinicity from the northern Great Basin, including that accompanying an approaching baroclinic trough. Evaporative and sublimational cooling from postfrontal precipitation, as well as cross-front contrasts in surface sensible heating, also play an important role, accounting for up to 40% of cross-front baroclinicity. As an upper-level cyclonic potential vorticity anomaly and quasigeostrophic forcing for ascent move over the Great Basin, cyclone development occurs along the GBCZ and developing cold front rather than within the Sierra Nevada lee trough, as might be inferred from classic models of lee cyclogenesis. Front–mountain interactions ultimately produce a very complex frontal evolution over the basin-and-range topography of northern Utah.

The analysis further establishes the role of the GBCZ in intermountain frontogenesis and cyclone evolution. Recognition of this role is essential for improving the analysis and prediction of sensible weather changes produced by cold fronts and cyclones over the Intermountain West.

Full access
Gregory L. West and W. James Steenburgh

Abstract

Recent studies indicate that strong cold fronts develop frequently downstream of the Sierra Nevada over the Intermountain West. To help ascertain why, this paper examines the influence of the Sierra Nevada on the rapidly developing Intermountain cold front of 25 March 2006. Comparison of a Weather Research and Forecasting (WRF) model control simulation with a simulation in which the height of the Sierra Nevada is restricted to 1500 m (roughly the elevation of the valleys and basins of the Intermountain West) shows that the interaction of southwesterly prefrontal flow with the formidable southern High Sierra produces a leeward orographic warm anomaly that enhances the cross-front temperature contrast. Several processes generate this orographic warm anomaly, including flow modification by the Sierra Nevada (i.e., windward blocking of low-level Pacific air, leeward subsidence, and increased southerly flow from the Mojave Desert and lower Colorado River basin into the Intermountain West), diabatic heating and water vapor loss associated with orographic precipitation, and increased sensible heating and reduced subcloud diabatic cooling in the downstream cloud and precipitation shadow. In contrast, the postfrontal air mass experiences comparatively little orographic modification as it moves across the relatively low northern Sierra Nevada. These results show that the Sierra Nevada can enhance frontal development, which may contribute to the high frequency of strong cold-frontal passages over the Intermountain West.

Full access
Pedro Odon, Gregory West, and Roland Stull

Abstract

This study evaluates how well reanalyses represent daily and multiday accumulated precipitation (hereinafter daily PCP) over British Columbia, Canada (Part I evaluated 2-m temperature). Reanalyses are compared with observations from 66 meteorological stations distributed over the complex terrain of British Columbia, separated into climate regions by k-means clustering. Systematic error, two-sample χ 2 statistic, and frequency of daily PCP occurrence are evaluated from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim), the Climate Forecast System Reanalysis (CFSR), the Japanese 55-year Reanalysis (JRA-55), and the latest Modern-Era Retrospective Analysis for Research and Applications (version 2; MERRA-2). The 2- and 30-yr return levels of daily PCP are estimated from a generalized extreme value (GEV) distribution fitted by the method of L moments, and their systematic errors are analyzed. JRA-55 and MERRA-2 generally outperform ERA-Interim and CFSR across all metrics. Biases are largely explained by poor reanalysis representation of terrain characteristics such as steepness, exposure, elevation, location of barriers, and wind speed and direction. Statistical stationarity of precipitation intensity and frequency over the 30-yr period is assessed by using confidence intervals and GEV distributions fitted with and without time-dependent parameters. It is determined that stationary distributions are sufficient to represent the climate of daily PCP for this region and time period.

Open access
David Siuta, Gregory West, and Roland Stull

Abstract

This study evaluates the sensitivity of wind turbine hub-height wind speed forecasts to the planetary boundary layer (PBL) scheme, grid length, and initial condition selection in the Weather Research and Forecasting (WRF) Model over complex terrain. Eight PBL schemes available for the WRF-ARW dynamical core were tested with initial conditions sources from the North American Mesoscale (NAM) model and Global Forecast System (GFS) to produce short-term wind speed forecasts. The largest improvements in forecast accuracy primarily depended on the grid length or PBL scheme choice, although the most important factor varied by location, season, time of day, and bias-correction application. Aggregated over all locations, the Asymmetric Convective Model, version 2 (ACM2) PBL scheme provided the best forecast accuracy, particularly for the 12-km grid length. Other PBL schemes and grid lengths, however, did perform better than the ACM2 scheme for individual seasons or locations.

Full access
David Siuta, Gregory West, Henryk Modzelewski, Roland Schigas, and Roland Stull

Abstract

As cloud-service providers like Google, Amazon, and Microsoft decrease costs and increase performance, numerical weather prediction (NWP) in the cloud will become a reality not only for research use but for real-time use as well. The performance of the Weather Research and Forecasting (WRF) Model on the Google Cloud Platform is tested and configurations and optimizations of virtual machines that meet two main requirements of real-time NWP are found: 1) fast forecast completion (timeliness) and 2) economic cost effectiveness when compared with traditional on-premise high-performance computing hardware. Optimum performance was found by using the Intel compiler collection with no more than eight virtual CPUs per virtual machine. Using these configurations, real-time NWP on the Google Cloud Platform is found to be economically competitive when compared with the purchase of local high-performance computing hardware for NWP needs. Cloud-computing services are becoming viable alternatives to on-premise compute clusters for some applications.

Open access
David Siuta, Gregory West, Roland Stull, and Thomas Nipen

Abstract

This work evaluates the use of a WRF ensemble for short-term, probabilistic, hub-height wind speed forecasts in complex terrain. Testing for probabilistic-forecast improvements is conducted by increasing the number of planetary boundary layer schemes used in the ensemble. Additionally, several prescribed uncertainty models used to derive forecast probabilities based on knowledge of the error within a past training period are evaluated. A Gaussian uncertainty model provided calibrated wind speed forecasts at all wind farms tested. Attempts to scale the Gaussian distribution based on the ensemble mean or variance values did not result in further improvement of the probabilistic forecast performance. When using the Gaussian uncertainty model, a small-sized six-member ensemble showed equal skill to that of the full 48-member ensemble. A new uncertainty model called the pq distribution that better fits the ensemble wind forecast error distribution is introduced. Results indicate that the gross attributes (central tendency, spread, and symmetry) of the prescribed uncertainty model are more important than its exact shape.

Full access
Gregory L. West, W. James Steenburgh, and William Y. Y. Cheng

Abstract

Spurious grid-scale precipitation (SGSP) occurs in many mesoscale numerical weather prediction models when the simulated atmosphere becomes convectively unstable and the convective parameterization fails to relieve the instability. Case studies presented in this paper illustrate that SGSP events are also found in the North American Regional Reanalysis (NARR) and are accompanied by excessive maxima in grid-scale precipitation, vertical velocity, moisture variables (e.g., relative humidity and precipitable water), mid- and upper-level equivalent potential temperature, and mid- and upper-level absolute vorticity. SGSP events in environments favorable for high-based convection can also feature low-level cold pools and sea level pressure maxima. Prior to 2003, retrospectively generated NARR analyses feature an average of approximately 370 SGSP events annually. Beginning in 2003, however, NARR analyses are generated in near–real time by the Regional Climate Data Assimilation System (R-CDAS), which is identical to the retrospective NARR analysis system except for the input precipitation and ice cover datasets. Analyses produced by the R-CDAS feature a substantially larger number of SGSP events with more than 4000 occurring in the original 2003 analyses. An oceanic precipitation data processing error, which resulted in a reprocessing of NARR analyses from 2003 to 2005, only partially explains this increase since the reprocessed analyses still produce approximately 2000 SGSP events annually. These results suggest that many NARR SGSP events are not produced by shortcomings in the underlying Eta Model, but by the specification of anomalous latent heating when there is a strong mismatch between modeled and assimilated precipitation. NARR users should ensure that they are using the reprocessed NARR analyses from 2003 to 2005 and consider the possible influence of SGSP on their findings, particularly after the transition to the R-CDAS.

Full access