WRF Evaluation During Storm Ophelia Using Remote Sensing and In-situ Measurements at Mace Head, Ireland

Storm Ophelia made landfall over Ireland as an extra-tropical storm on the morning of the 16th of October 2017. The storm caused major power outages, lifted roofs, caused coastal flooding in Ireland, and resulted in the loss of three lives. A model’s capability to forecast extreme weather events such as Storm Ophelia is of utmost importance and now with a changing climate, it becomes more important to improve and enhance model forecasting capability. The Weather Research and Forecasting (WRF) model V3.9 has been configured for the Irish domain and this study presents a preliminary evaluation of the Model during Storm Ophelia. Simulated wind speed and direction were compared with hourly remote sensing (lidar) and in-situ (wind speed and wind direction at 10m) observations at the coastal site of Mace Head Atmospheric Research Station on the West coast of Ireland (53.33◦ N, 9.90 49 ◦ W). The model simulation has generally small biases in the simulated wind speed and wind direction during this case study. The model also realistically simulated the magnitude and geographical distribution of the wind speed and wind direction observed during Ophelia.

Influence of sea surface roughness length parameterization on Mistral and Tramontane simulations

The Mistral and Tramontane are mesoscale winds in southern France and above the Western Mediterranean Sea. They are phenomena well suited for studying channeling effects as well as atmosphere–land/ocean processes. This sensitivity study deals with the influence of the sea surface roughness length parameterizations on simulated Mistral and Tramontane wind speed and wind direction. Several simulations with the regional climate model COSMO-CLM were performed for the year 2005 with varying values for the Charnock parameter α. Above the western Mediterranean area, the simulated wind speed and wind direction pattern on Mistral days changes depending on the parameterization used. Higher values of α lead to lower simulated wind speeds. In areas, where the simulated wind speed does not change much, a counterclockwise rotation of the simulated wind direction is observed.

An Empirical Study of Two Numerical Models for Wind Resource Simulation in Complex Terrain

The choice of wind measured data and numerical simulation method has an important impact on the results of wind resource assessment. This paper will take a wind farm, in Yangjiang City, Guangdong Province, for an example and discuss the simulation accuracy by linear model WAsP and nonlinear model based on simulation software Fluent. First of all, contrast mean absolute percentage error (MAPE) about simulated wind speed under four kinds of wind conditions, which are simulated by four sets of wind data in WAsP, and then select the wind data with the smallest . Then, using WAsP and CFD method simulates wind field by the optimal wind data. Compare simulated wind speed and annual generation capacity. In this paper, the simulated wind speed in the simulation model CFD based on Fluent is closer to the measured wind speed. The MAPE of wind speed and annual generation capacity by CFD model is smaller than that by WAsP. Therefore, for the wind resource assessment in the complex terrain, the nonlinear model CFD based on Fluent will be qualified to response the relationship between wind resource and terrain, simulation accuracy, and has higher simulation accuracy than the linear model WAsP.

Numerical Simulation of Wind Energy Characteristics in Jiangsu Coastal Area

In order to explore the surface layer wind energy characteristics in Jiangsu coastal area, MM5 model and CALMET model and wind observations data are used in this paper. The comparison of simulated wind speed and observed wind speed shows that the MM5 and CALMET model can well simulate wind resource distribution and the simulated result is well agreed with observation. The results show that (1) Wind Resource in coastal area is more abundant than other area in Jiangsu Province;(2) Wind speed and wind power density in winter and spring are higher than that in summer and autumn;(3) predominant wind direction is NNW-N and SE-SSE.

Predicting Wind Speed for Wind Energy; Progress of the WINDENG Project

The suitability of the computer model MM5 for predicting wind speed, and hence wind energy, is investigated by performing simulations for different geographical regions. The focus is on wind speed in the lowest 200 m of the planetary boundary layer (PBL). The dependency of the simulated wind speed on PBL parameterization and atmospheric stability is studied. The smallest deviation between measured and simulated wind speed, averaged over a three-day period, is 1% and occurs for an off-shore simulation with unstable stratification. The largest deviations of 31% and 20% occur with orographically structured terrain, stable stratification and weak synoptic forcing. The results suggest that unstable conditions are simulated with better accuracy by MM5. Changes of the PBL scheme cause wind speed variations between 9% and 40% of the average wind speed. None of the PBL schemes is clearly the best and their performance can strongly vary for different conditions. Nevertheless, the Mellor-Yamada-Janjic (ETA) and the Blackadar PBL parameterization (BLK) schemes seem to be the most suitable schemes for wind energy applications. Additionally, MM5 was successfully adapted for idealised, stationary simulations in order to calculate a wind-climatology for Sardinia using a statistical-dynamical downscaling approach.