An Experiment on the Prediction of the Surface Wind Speed in Chongli Based on the WRF Model: Evaluation and Calibration

2021 ◽  
Vol 38 (5) ◽  
pp. 845-861
Author(s):  
Na Li ◽  
Lingkun Ran ◽  
Dongdong Shen ◽  
Baofeng Jiao
Keyword(s):  
Wind Speed ◽  
Model Evaluation ◽  
Surface Wind ◽  
Wrf Model ◽  
Surface Wind Speed

scholarly journals Numerical Simulation of Near-Surface Wind during a Severe Wind Event in a Complex Terrain by Multisource Data Assimilation and Dynamic Downscaling

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
De Zhang ◽  
Luyuan Chen ◽  
Feimin Zhang ◽  
Juan Tan ◽  
Chenghai Wang
Keyword(s):  
Wind Speed ◽  
Data Assimilation ◽  
Surface Wind ◽  
Wrf Model ◽  
Surface Wind Speed ◽  
Dynamic Downscaling ◽  
Near Surface ◽  
Wind Event ◽  
Weak Wind

Accurate forecast and simulation of near-surface wind is a great challenge for numerical weather prediction models due to the significant transient and intermittent nature of near-surface wind. Based on the analyses of the impact of assimilating in situ and Advanced Tiros Operational Vertical Sounder (ATOVS) satellite radiance data on the simulation of near-surface wind during a severe wind event, using the new generation mesoscale Weather Research and Forecasting (WRF) model and its three-dimensional variational (3DVAR) data assimilation system, the dynamic downscaling of near-surface wind is further investigated by coupling the microscale California Meteorological (CALMET) model with the WRF and its 3DVAR system. Results indicate that assimilating in situ and ATOVS radiance observations strengthens the airflow across the Alataw valley and triggers the downward transport of momentum from the upper atmosphere in the downstream area of the valley in the initial conditions, thus improving near-surface wind simulations. Further investigations indicate that the CALMET model provides more refined microtopographic structures than the WRF model in the vicinity of the wind towers. Although using the CALMET model achieves the best simulation of near-surface wind through dynamic downscaling of the output from the WRF and its 3DVAR assimilation, the simulation improvements of near-surface wind speed are mainly within 1 m s−1. Specifically, the mean improvement proportions of near-surface wind speed are 64.8% for the whole simulation period, 58.7% for the severe wind period, 68.3% for the severe wind decay period, and 75.4% for the weak wind period. The observed near-surface wind directions in the weak wind conditions are better simulated in the coupled model with CALMET downscaling than in the WRF and its 3DVAR system. It is concluded that the simulation improvements of CALMET downscaling are distinct when near-surface winds are weak, and the downscaling effects are mainly manifested in the simulation of near-surface wind directions.

scholarly journals Evaluation of Extratropical Cyclone Precipitation in the North Atlantic Basin: An Analysis of ERA-Interim, WRF, and Two CMIP5 Models

2018 ◽  
Vol 31 (6) ◽  
pp. 2345-2360 ◽  
Author(s):  
James F. Booth ◽  
Catherine M. Naud ◽  
Jeff Willison
Keyword(s):  
Wind Speed ◽  
North Atlantic ◽  
Surface Wind ◽  
Wrf Model ◽  
Surface Wind Speed ◽  
Convective Precipitation ◽  
Cmip5 Models ◽  
Convection Scheme ◽  
The North ◽  
The North Atlantic

The representation of extratropical cyclone (ETC) precipitation in general circulation models (GCMs) and the Weather Research and Forecasting (WRF) Model is analyzed. This work considers the link between ETC precipitation and dynamical strength and tests if parameterized convection affects this link for ETCs in the North Atlantic basin. Lagrangian cyclone tracks of ETCs in ERA-Interim (ERAI), GISS and GFDL CMIP5 models, and WRF with two horizontal resolutions are utilized in a compositing analysis. The 20-km-resolution WRF Model generates stronger ETCs based on surface wind speed and cyclone precipitation. The GCMs and ERAI generate similar composite means and distributions for cyclone precipitation rates, but GCMs generate weaker cyclone surface winds than ERAI. The amount of cyclone precipitation generated by the convection scheme differs significantly across the datasets, with the GISS model generating the most, followed by ERAI and then the GFDL model. The models and reanalysis generate relatively more parameterized convective precipitation when the total cyclone-averaged precipitation is smaller. This is partially due to the contribution of parameterized convective precipitation occurring more often late in the ETC’s life cycle. For reanalysis and models, precipitation increases with both cyclone moisture and surface wind speed, and this is true if the contribution from the parameterized convection scheme is larger or not. This work shows that these different models generate similar total ETC precipitation despite large differences in the parameterized convection, and these differences do not cause unexpected behavior in ETC precipitation sensitivity to cyclone moisture or surface wind speed.

scholarly journals Investigation of the Effects of Different Land Use and Land Cover Patterns on Mesoscale Meteorological Simulations in the Taiwan Area

2013 ◽  
Vol 52 (3) ◽  
pp. 570-587 ◽  
Author(s):  
Fang-Yi Cheng ◽  
Yu-Ching Hsu ◽  
Pay-Liam Lin ◽  
Tang-Huang Lin
Keyword(s):  
Land Use ◽  
Wind Speed ◽  
Roughness Length ◽  
Surface Wind ◽  
Wrf Model ◽  
Surface Wind Speed ◽  
Sea Breezes ◽  
Modis Data ◽  
Wind Speeds ◽  
Moderate Resolution Imaging Spectroradiometer

AbstractThe U.S. Geological Survey (USGS) land use (LU) data employed in the Weather Research and Forecasting (WRF) model classify most LU types in Taiwan as mixtures of irrigated cropland and forest, which is not an accurate representation of current conditions. The WRF model released after version 3.1 provides an alternative LU dataset retrieved from 2001 Moderate Resolution Imaging Spectroradiometer (MODIS) satellite products. The MODIS data correctly identify most LU-type distributions, except that they represent western Taiwan as being extremely urbanized. A new LU dataset, obtained using 2007 Système Probatoire d’Observation de la Terre (SPOT) satellite imagery [from the National Central University of Taiwan (NCU)], accurately shows the major metropolitan cities as well as other land types. Three WRF simulations were performed, each with a different LU dataset. Owing to the overestimation of urban area in the MODIS data, WRF-MODIS overpredicts daytime temperatures in western Taiwan. Conversely, WRF-USGS underpredicts daytime temperatures. The temperature variation estimated by WRF-NCU falls between those estimated by the other two simulations. Over the ocean, WRF-MODIS predicts the strongest onshore sea breezes, owing to the enhanced temperature gradient between land and sea, while WRF-USGS predicts the weakest onshore flow. The intensity of the onshore breeze predicted by WRF-NCU is between those predicted by WRF-MODIS and WRF-USGS. Over Taiwan, roughness length is the key parameter influencing wind speed. WRF-USGS significantly overpredicts the surface wind speed owing to the shorter roughness length of its elements, while the surface wind speeds estimated by WRF-NCU and WRF-MODIS are in better agreement with the observed data.

Improving the Representation of Resolved and Unresolved Topographic Effects on Surface Wind in the WRF Model

2012 ◽  
Vol 51 (2) ◽  
pp. 300-316 ◽  
Author(s):  
Pedro A. Jiménez ◽  
Jimy Dudhia
Keyword(s):  
Wind Speed ◽  
Grid Point ◽  
High Surface ◽  
Surface Wind ◽  
Wrf Model ◽  
Surface Wind Speed ◽  
Topographic Effects ◽  
Low Wind Speed ◽  
Sink Term ◽  
Wind Simulation

AbstractThe Weather Research and Forecasting (WRF) model presents a high surface wind speed bias over plains and valleys that constitutes a limitation for the increasing use of the model for several applications. This study attempts to correct for this bias by parameterizing the effects that the unresolved topographic features exert over the momentum flux. The proposed parameterization is based on the concept of a momentum sink term and makes use of the standard deviation of the subgrid-scale orography as well as the Laplacian of the topographic field. Both the drag generated by the unresolved terrain and the possibility of an increase in the speed of the flow over the mountains and hills, where it is herein shown that WRF presents a low wind speed bias, are considered in the scheme. The surface wind simulation over a complex-terrain region that is located in the northeast of the Iberian Peninsula is improved with the inclusion of the new parameterization. In particular, the underestimation of the wind speed spatial variability resulting from the mentioned biases is corrected. The importance of selecting appropriate grid points to compare with observations is also examined. The wind speed from the nearest grid point is not always the most appropriate one for this comparison, nearby ones being more representative. The new scheme not only improves the climatological winds but also the intradiurnal variations at the mountains, over which the default WRF shows limitations in reproducing the observed wind behavior. Some advantages of the proposed formulation for wind-resource evaluation are also discussed.

scholarly journals Combined Kalman Filter and Universal Kriging to Improve Storm Wind Speed Predictions for the Northeastern United States

2019 ◽  
Vol 34 (3) ◽  
pp. 587-601 ◽  
Author(s):  
Alexander Samalot ◽  
Marina Astitha ◽  
Jaemo Yang ◽  
George Galanis
Keyword(s):  
Kalman Filter ◽  
Wind Speed ◽  
Spatial Interpolation ◽  
Surface Wind ◽  
Model Performance ◽  
Wrf Model ◽  
Surface Wind Speed ◽  
Bias Reduction ◽  
Universal Kriging ◽  
Model Errors

Abstract The scope of this study is to assess a combination of well-known techniques for bias reduction and spatial interpolation in an attempt to improve wind speed prediction for storms on a gridded domain. This is accomplished by implementing Kalman filter (KF) for bias reduction and universal kriging (UK) for spatial interpolation as postprocessing steps for the Weather Research and Forecasting (WRF) Model. It is shown that for surface wind speed, a linear KF is adequate for eliminating systematic model errors with the available storm history. KF-estimated wind speed biases at station locations are then interpolated across the model domain using UK. The combined KF–UK approach improves the wind speed forecast median bias by 55% and RMSE by 15% (bulk statistics), while benefits obtained at station-specific locations can reach maximum improvements of 72% for RMSE and 100% for bias. Contingency statistics that inform on model performance over four categories of wind speed magnitude reveal that calm/moderate winds are successfully corrected but strong/gale winds cannot be adequately corrected by the combination of KF and UK, which is a disadvantage for improving prediction of severe storm conditions.

Recurrence Characteristics Analysis of Near-Surface Wind Speed Signal with Different Sampling Frequencies

2014 ◽  
Vol 599-601 ◽  
pp. 1605-1609 ◽  
Author(s):  
Ming Zeng ◽  
Zhan Xie Wu ◽  
Qing Hao Meng ◽  
Jing Hai Li ◽  
Shu Gen Ma
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Recurrence Plot ◽  
Sampling Frequency ◽  
Near Surface ◽  
Gas Leakage ◽  
Time Period ◽  
Characteristics Analysis ◽  
Quantification Analysis

The wind is the main factor to influence the propagation of gas in the atmosphere. Therefore, the wind signal obtained by anemometer will provide us valuable clues for searching gas leakage sources. In this paper, the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) are applied to analyze the influence of recurrence characteristics of the wind speed time series under the condition of the same place, the same time period and with the sampling frequency of 1hz, 2hz, 4.2hz, 5hz, 8.3hz, 12.5hz and 16.7hz respectively. Research results show that when the sampling frequency is higher than 5hz, the trends of recurrence nature of different groups are basically unchanged. However, when the sampling frequency is set below 5hz, the original trend of recurrence nature is destroyed, because the recurrence characteristic curves obtained using different sampling frequencies appear cross or overlapping phenomena. The above results indicate that the anemometer will not be able to fully capture the detailed information in wind field when its sampling frequency is lower than 5hz. The recurrence characteristics analysis of the wind speed signals provides an important basis for the optimal selection of anemometer.

Ocean surface wind speed retrieval from C-band quad-polarized SAR measurements at optimal spatial resolution

2020 ◽  
Vol 12 (2) ◽  
pp. 155-164
Author(s):  
He Fang ◽  
William Perrie ◽  
Gaofeng Fan ◽  
Tao Xie ◽  
Jingsong Yang
Keyword(s):  
Wind Speed ◽  
Spatial Resolution ◽  
Surface Wind ◽  
Ocean Surface ◽  
Surface Wind Speed ◽  
Ocean Surface Wind
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