scholarly journals Ensemble Forecast Uncertainty of the 1 December 2011 Wasatch Windstorm

2015 ◽  
Vol 30 (6) ◽  
pp. 1749-1761 ◽  
Author(s):  
John Lawson ◽  
John Horel

Abstract A downslope windstorm on 1 December 2011 led to considerable damage along a narrow 50-km swath at the western base of the Wasatch Mountains in northern Utah. Operational forecasts issued by the Salt Lake City National Weather Service Forecast Office provided accurate guidance for the event at 1–2-day lead times, partially based on locally generated high-resolution numerical forecasts. Forecasters highlighted the possibility of the windstorm 4 days in advance. To address the apparent reduced uncertainty for this windstorm, three 11-member three-domain ensemble forecasts were initialized at 0000 UTC 25 November, 0000 UTC 27 November, and 0000 UTC 29 November 2011 using the Weather Research and Forecasting (WRF) Model with initial and boundary conditions supplied by Global Ensemble Forecast System Reforecast, version 2 (GEFS/R2). Eight of the 11 ensemble members from the 29 November 2011 forecast (60 h before the windstorm) generated a strong, localized windstorm with outliers arising from reduced cross-barrier flow. Analysis of kinetic energy error growth suggests that the reduced uncertainty of 60-h forecasts was not primarily a result of the underdispersion of GEFS/R2 initial and boundary conditions but was related to a regional reduction in error growth in midtropospheric flow upstream of northern Utah. The ensemble initialized 2 days earlier (27 November, 108 h before the windstorm) contains fewer members that generate strong windstorms, while no members generate a windstorm in the ensemble initialized on 25 November (156 h prior). This sudden increase in uncertainty with forecast lead time results from the sensitivity of the ensemble solutions to the lateral boundary conditions imposed by the GEFS/R2 between 0000 UTC 29 November and 0000 UTC 30 November.

2018 ◽  
Vol 57 (3) ◽  
pp. 733-753 ◽  
Author(s):  
Sergio Fernández-González ◽  
María Luisa Martín ◽  
Eduardo García-Ortega ◽  
Andrés Merino ◽  
Jesús Lorenzana ◽  
...  

AbstractWind energy requires accurate forecasts for adequate integration into the electric grid system. In addition, global atmospheric models are not able to simulate local winds in complex terrain, where wind farms are sometimes placed. For this reason, the use of mesoscale models is vital for estimating wind speed at wind turbine hub height. In this regard, the Weather Research and Forecasting (WRF) Model allows a user to apply different initial and boundary conditions as well as physical parameterizations. In this research, a sensitivity analysis of several physical schemes and initial and boundary conditions was performed for the Alaiz mountain range in the northern Iberian Peninsula, where several wind farms are located. Model performance was evaluated under various atmospheric stabilities and wind speeds. For validation purposes, a mast with anemometers installed at 40, 78, 90, and 118 m above ground level was used. The results indicate that performance of the Global Forecast System analysis and European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) as initial and boundary conditions was similar, although each performed better under certain meteorological conditions. With regard to physical schemes, there is no single combination of parameterizations that performs best during all weather conditions. Nevertheless, some combinations have been identified as inefficient, and therefore their use is discouraged. As a result, the validation of an ensemble prediction system composed of the best 12 deterministic simulations shows the most accurate results, obtaining relative errors in wind speed forecasts that are <15%.


2010 ◽  
Vol 33 (4) ◽  
pp. 294-314 ◽  
Author(s):  
U. C. Mohanty ◽  
Krishna K. Osuri ◽  
A. Routray ◽  
M. Mohapatra ◽  
Sujata Pattanayak

2018 ◽  
Vol 18 (2) ◽  
pp. 445-454 ◽  
Author(s):  
Jeonghyeon Choi ◽  
Jeonghoon Lee ◽  
Hyeon-gyo Jeong ◽  
Juhyoung Jang ◽  
Sangdan Kim

1971 ◽  
Vol 2 (3) ◽  
pp. 146-166 ◽  
Author(s):  
DAVID A. WOOLHISER

Physically-based, deterministic models, are considered in this paper. Physically-based, in that the models have a theoretical structure based primarily on the laws of conservation of mass, energy, or momentum; deterministic in the sense that when initial and boundary conditions and inputs are specified, the output is known with certainty. This type of model attempts to describe the structure of a particular hydrologic process and is therefore helpful in predicting what will happen when some change occurs in the system.


1998 ◽  
Vol 21 (2) ◽  
pp. 299-305 ◽  
Author(s):  
Fengxin Chen ◽  
Ping Wang ◽  
Chaoshun Qu

In this paper we study the system governing flows in the magnetic field within the earth. The system is similar to the magnetohydrodynamic (MHD) equations. For initial data in spaceLp, we obtained the local in time existence and uniqueness ofweak solutions of the system subject to appropriate initial and boundary conditions.


2016 ◽  
Vol 31 (3) ◽  
pp. 1001-1017 ◽  
Author(s):  
Omar V. Müller ◽  
Miguel A. Lovino ◽  
Ernesto H. Berbery

Abstract Weather forecasting and monitoring systems based on regional models are becoming increasingly relevant for decision support in agriculture and water management. This work evaluates the predictive and monitoring capabilities of a system based on WRF Model simulations at 15-km grid spacing over the La Plata basin (LPB) in southern South America, where agriculture and water resources are essential. The model’s skill up to a lead time of 7 days is evaluated with daily precipitation and 2-m temperature in situ observations for the 2-yr period from 1 August 2012 to 31 July 2014. Results show high prediction performance with 7-day lead time throughout the domain and particularly over LPB, where about 70% of rain and no-rain days are correctly predicted. Also, the probability of detection of rain days is above 80% in humid regions. Temperature observations and forecasts are highly correlated (r &gt; 0.80) while mean absolute errors, even at the maximum lead time, remain below 2.7°C for minimum and mean temperatures and below 3.7°C for maximum temperatures. The usefulness of WRF products for hydroclimate monitoring was tested for an unprecedented drought in southern Brazil and for a slightly above normal precipitation season in northeastern Argentina. In both cases the model products reproduce the observed precipitation conditions with consistent impacts on soil moisture, evapotranspiration, and runoff. This evaluation validates the model’s usefulness for forecasting weather up to 1 week in advance and for monitoring climate conditions in real time. The scores suggest that the forecast lead time can be extended into a second week, while bias correction methods can reduce some of the systematic errors.


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