Toward Real-Time, Remote Observations of the Coastal Wind Resource Using High-Frequency Radar

2013 ◽  
Vol 47 (4) ◽  
pp. 206-217 ◽  
Author(s):  
Anthony Kirincich
Keyword(s):  
Wind Speed ◽  
High Frequency ◽  
Transfer Functions ◽  
Surface Wind ◽  
The United States ◽  
Coastal Ocean ◽  
Error Rates ◽  
Hf Radar ◽  
Variable Surface

AbstractThere is now a large installed base of high-frequency (HF) coastal ocean radars in the United States able to measure surface currents on an operational basis. However, these instruments also have the potential to provide estimates of the spatially variable surface wind field over distances ranging from 10 to 200 km offshore. This study investigates the ability of direction-finding HF radars to recover spatial maps of wind speed and direction from the dominant first-order region radar returns using empirical models. Observations of radar backscatter from the Martha’s Vineyard Coastal Observatory HF radar system were compared to wind observations from an offshore tower, finding significant correlations between wind speed and the backscatter power for a range of angles between the wind and radar loop directions. Models for the directional spreading of wind waves were analyzed in comparison to data-based results, finding potentially significant differences between the model and data-based spreading relationships. Using empirical fits, radar-based estimates of wind speed and direction at the location of the in situ wind sensor had error rates of 2 m/s and 60°, which decreased with hourly averaging. Attempts to extrapolate the results to the larger domain illustrated that spatially dependent transfer functions for wind speed and direction appear possible for large coastal ocean domains based on a small number of temporary, or potentially mobile, in situ wind sensors.

scholarly journals Factors of boreal summer latent heat flux variations over the tropical western North Pacific

2021 ◽  
Author(s):  
Yuqi Wang ◽  
Renguang Wu
Keyword(s):  
Heat Flux ◽  
Wind Speed ◽  
North Pacific ◽  
High Frequency ◽  
Western North Pacific ◽  
Surface Wind ◽  
Low Frequency ◽  
Boreal Summer ◽  
Wind Intensity ◽  
Tropical Western North Pacific

AbstractSurface latent heat flux (LHF) is an important component in the heat exchange between the ocean and atmosphere over the tropical western North Pacific (WNP). The present study investigates the factors of seasonal mean LHF variations in boreal summer over the tropical WNP. Seasonal mean LHF is separated into two parts that are associated with low-frequency (> 90-day) and high-frequency (≤ 90-day) atmospheric variability, respectively. It is shown that low-frequency LHF variations are attributed to low-frequency surface wind and sea-air humidity difference, whereas high-frequency LHF variations are associated with both low-frequency surface wind speed and high-frequency wind intensity. A series of conceptual cases are constructed using different combinations of low- and high-frequency winds to inspect the respective effects of low-frequency wind and high-frequency wind amplitude to seasonal mean LHF variations. It is illustrated that high-frequency wind fluctuations contribute to seasonal high-frequency LHF only when their intensity exceeds the low-frequency wind speed under which there is seasonal accumulation of high-frequency LHF. When high-frequency wind intensity is smaller than the low-frequency wind speed, seasonal mean high-frequency LHF is negligible. Total seasonal mean LHF anomalies depend on relative contributions of low- and high-frequency atmospheric variations and have weak interannual variance over the tropical WNP due to cancellation of low- and high-frequency LHF anomalies.

scholarly journals Tropical deep convection and density current signature in surface pressure: comparison between WRF model simulations and infrasound measurements

2013 ◽  
Vol 13 (6) ◽  
pp. 15993-16046 ◽  
Author(s):  
L. Costantino ◽  
P. Heinrich
Keyword(s):  
Wind Speed ◽  
Surface Pressure ◽  
High Frequency ◽  
Ivory Coast ◽  
Deep Convection ◽  
Real Case ◽  
Density Current ◽  
Model Simulations ◽  
Tropical Deep Convection

Abstract. Deep convection is a major atmospheric transport process in the tropics, affecting the global weather and the climate system. In the framework of the ARISE (Atmospheric dynamics Research InfraStructure in Europe) project, we combine model simulations of tropical deep convection with in-situ ground measurements, from a IMS (International Monitoring System) infrasound station in Ivory Coast, to analyse the effects of density current propagation. The WRF (Weather Research and Forecasting) model is firstly run in a simplified (referred to as "idealized case") and highly resolved configuration, to explicitly account for convective dynamics. Then, a coarser threedimensional simulation (referred to as "real") is nudged towards meteorological re-analysis data, to compare the real case with the idealized model and in-situ observations. In the 2-D run, the evolution of a deep convective cloud generates a density current, that moves outward up to 30 km away from storm center. The increase in surface density (up to 18 g m−3 larger than surrounding air) is mostly due to the sudden temperature decrease (down to −2 °C, with respect to domain averaged value), from diabatic cooling by rain evaporation near ground level. It is accompanied by a dramatic decrease in relative humidity (down to −50%), buoyancy (down to −0.08 m s−2), equivalent potential temperature (25 °C lower than the PBL) and the rapid enhancement of horizontal wind speed (up to 15 m s−2). If temperature and density changes are strong enough, surface pressure gets largely affected and high frequency disturbances (up to several tens of Pa) can be detected, at the leading edges of density current. The moister and warmer air of subcloud layer is lifted up and replaced by a more stable flow. The resulting thermodynamical instabilities are shown to play a key role in triggering new convection. If the initial environment is sufficiently unstable, they can give rise to continuous updrafts that may lead to the transition from single-cell to multi-cell cloud systems, even without the presence of an initial wind shear. The overall consistence and similarity between idealized and real simulation, and the good agreement of real case with in-situ retrievals of temperature, pressure, wind speed and direction, seem to confirm the ability of 2-D and 3-D model to well reproduce convective dynamics. Surface pressure disturbances, simulated in both idealized and real cases as a consequence of cold pool propagation, are very similar to those recorded in Ivory Coast. Present results stress the direct link between mesoscale convective system activity and high-frequency surface pressure variations, suggesting the possibility of developing a new method for real-time rainstorm tracking, based on the ground-based infrasound monitoring of pressure field.

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 Coastal observing and forecasting system for the German Bight – estimates of hydrophysical states

Ocean Science ◽  
2011 ◽  
Vol 7 (5) ◽  
pp. 569-583 ◽  
Author(s):  
E. V. Stanev ◽  
J. Schulz-Stellenfleth ◽  
J. Staneva ◽  
S. Grayek ◽  
J. Seemann ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Assimilation ◽  
German Bight ◽  
Numerical Models ◽  
Coastal Ocean ◽  
Hf Radar ◽  
Optimal Interpolation ◽  
Surface Currents ◽  
Arctic Seas

Abstract. A coastal observing system for Northern and Arctic Seas (COSYNA) aims at construction of a long-term observatory for the German part of the North Sea, elements of which will be deployed as prototype modules in Arctic coastal waters. At present a coastal prediction system deployed in the area of the German Bight integrates near real-time measurements with numerical models in a pre-operational way and provides continuously state estimates and forecasts of coastal ocean state. The measurement suite contributing to the pre-operational set up includes in situ time series from stationary stations, a High-Frequency (HF) radar system measuring surface currents, a FerryBox system and remote sensing data from satellites. The forecasting suite includes nested 3-D hydrodynamic models running in a data-assimilation mode, which are forced with up-to-date meteorological forecast data. This paper reviews the present status of the system and its recent upgrades focusing on developments in the field of coastal data assimilation. Model supported data analysis and state estimates are illustrated using HF radar and FerryBox observations as examples. A new method combining radial surface current measurements from a single HF radar with a priori information from a hydrodynamic model is presented, which optimally relates tidal ellipses parameters of the 2-D current field and the M2 phase and magnitude of the radials. The method presents a robust and helpful first step towards the implementation of a more sophisticated assimilation system and demonstrates that even using only radials from one station can substantially benefit state estimates for surface currents. Assimilation of FerryBox data based on an optimal interpolation approach using a Kalman filter with a stationary background covariance matrix derived from a preliminary model run which was validated against remote sensing and in situ data demonstrated the capabilities of the pre-operational system. Data assimilation significantly improved the performance of the model with respect to both SST and SSS and demonstrated a good skill not only in the vicinity of the Ferry track, but also over larger model areas. The examples provided in this study are considered as initial steps in establishing new coastal ocean products enhanced by the integrated COSYNA-observations and numerical modelling.

scholarly journals An Examination of Wind Decay, Sustained Wind Speed Forecasts, and Gust Factors for Recent Tropical Cyclones in the Mid-Atlantic Region of the United States

2015 ◽  
Vol 30 (1) ◽  
pp. 153-176 ◽  
Author(s):  
Bryce Tyner ◽  
Anantha Aiyyer ◽  
Jonathan Blaes ◽  
Donald Reid Hawkins
Keyword(s):  
Surface Roughness ◽  
Wind Speed ◽  
Tropical Cyclones ◽  
Surface Wind ◽  
Software Tool ◽  
Weather Forecast ◽  
The United States ◽  
Atlantic Region ◽  
Wind Speeds ◽  
Gust Factors

Abstract In this study, several analyses were conducted that were aimed at improving sustained wind speed and gust forecasts for tropical cyclones (TCs) affecting coastal regions. An objective wind speed forecast analysis of recent TCs affecting the mid-Atlantic region was first conducted to set a benchmark for improvement. Forecasts from the National Digital Forecast Database were compared to observations and surface wind analyses in the region. The analysis suggests a general overprediction of sustained wind speeds, especially for areas affected by the strongest winds. Currently, National Weather Service Weather Forecast Offices use a software tool known as the Tropical Cyclone Forecast/Advisory (TCM) wind tool (TCMWindTool) to develop their wind forecast grids. The tool assumes linear decay in the sustained wind speeds when interpolating the National Hurricane Center 12–24-hourly TCM product to hourly grids. An analysis of postlandfall wind decay for recent TCs was conducted to evaluate this assumption. Results indicate that large errors in the forecasted wind speeds can emerge, especially for stronger storms. Finally, an analysis of gust factors for recent TCs affecting the region was conducted. Gust factors associated with weak sustained wind speeds are shown to be highly variable but average around 1.5. The gust factors decrease to values around 1.2 for wind speeds above 40 knots (kt; 1 kt = 0.51 m s−1) and are in general insensitive to the wind direction, suggesting local rather than upstream surface roughness largely dictates the gust factor at a given location. Forecasters are encouraged to increase land reduction factors used in the TCMWindTool and to modify gust factors to account for factors including the sustained wind speed and local surface roughness.

scholarly journals Homogenization and Trend Analysis of Canadian Near-Surface Wind Speeds

2010 ◽  
Vol 23 (5) ◽  
pp. 1209-1225 ◽  
Author(s):  
Hui Wan ◽  
Xiaolan L. Wang ◽  
Val R. Swail
Keyword(s):  
Wind Speed ◽  
Trend Analysis ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
The United States ◽  
Homogeneity Test ◽  
Near Surface ◽  
Wind Speeds ◽  
Long Term Trends

Abstract Near-surface wind speeds recorded at 117 stations in Canada for the period from 1953 to 2006 were analyzed in this study. First, metadata and a logarithmic wind profile were used to adjust hourly wind speeds measured at nonstandard anemometer heights to the standard 10-m level. Monthly mean near-surface wind speed series were then derived and subjected to a statistical homogeneity test, with homogeneous monthly mean geostrophic wind (geowind) speed series being used as reference series. Homogenized monthly mean near-surface wind speed series were obtained by adjusting all significant mean shifts, using the results of the statistical test and modeling along with all available metadata, and were used to assess the long-term trends. This study shows that station relocation and anemometer height change are the main causes for discontinuities in the near-surface wind speed series, followed by instrumentation problems or changes, and observing environment changes. It also shows that the effects of artificial mean shifts on the results of trend analysis are remarkable, and that the homogenized near-surface wind speed series show good spatial consistency of trends, which are in agreement with long-term trends estimated from independent datasets, such as surface winds in the United States and cyclone activity indices and ocean wave heights in the region. These indicate success in the homogenization of the wind data. During the period analyzed, the homogenized near-surface wind speed series show significant decreases throughout western Canada and most parts of southern Canada (except the Maritimes) in all seasons, with significant increases in the central Canadian Arctic in all seasons and in the Maritimes in spring and autumn.

scholarly journals Assessment of Wind Pattern Accuracy from the QuikSCAT Satellite and the WRF Model along the Galician Coast (Northwest Iberian Peninsula)

2013 ◽  
Vol 141 (2) ◽  
pp. 742-753 ◽  
Author(s):  
M. C. Sousa ◽  
I. Alvarez ◽  
N. Vaz ◽  
M. Gomez-Gesteira ◽  
J. M. Dias
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Western Coast ◽  
Wind Pattern ◽  
Wind Speeds ◽  
Galician Coast ◽  
Key Factor

Abstract Surface wind along the Galician coast is a key factor allowing the analysis of important oceanographic features that are related to the great primary production in this area, as upwelling events. A comparative analysis between surface winds obtained from the Quick Scatterometer (QuikSCAT), the Weather Research and Forecasting (WRF) Model, and in situ observations from buoys along the Galician coast is carried out from November 2008 to October 2009. This comparison evaluates the accuracy of satellite and modeled data. The results show that the wind speeds derived from QuikSCAT and the WRF Model are similar along the coast, with errors ranging from 1.5 to 2 m s−1. However, QuikSCAT tends to overestimate wind speeds when compared to the buoys measurements. Regarding the wind direction, the RMSE values are about 35° for the stations under analysis. The bias presents a similar pattern between satellite and modeled data, with positive values at the western coast and negative values at the middle and northern coasts, the satellite data always being lower in absolute value than the modeled data. A spatial comparison between QuikSCAT and WRF data is also performed over the whole Galician coast to evaluate the differences between the two datasets. This comparison shows that the modeled wind speed tends to be lower than satellite winds over the entire domain, with the highest RMSE and bias values found for the wind speed and direction observed near the shoreline.

scholarly journals Dynamical Global Downscaling of Global Reanalysis

2008 ◽  
Vol 136 (8) ◽  
pp. 2983-2998 ◽  
Author(s):  
Kei Yoshimura ◽  
Masao Kanamitsu
Keyword(s):  
High Resolution ◽  
Wind Speed ◽  
Surface Temperature ◽  
Dynamical Downscaling ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
The United States ◽  
Full Data ◽  
Global Spectral Model ◽  
Global Reanalysis

Abstract With the aim of producing higher-resolution global reanalysis datasets from coarse-resolution reanalysis, a global version of the dynamical downscaling using a global spectral model is developed. A variant of spectral nudging, the modified form of scale-selective bias correction developed for regional models is adopted. The method includes 1) nudging of temperature in addition to the zonal and meridional components of winds, 2) nudging to the perturbation field rather than to the perturbation tendency, and 3) no nudging and correction of the humidity. The downscaling experiment was performed using a T248L28 (about 50-km resolution) global model, driven by the so-called R-2 reanalysis (T62L28 resolution, or about 200-km resolution) during 2001. Evaluation with high-resolution observations showed that the monthly averaged global surface temperature and daily variation of precipitation were much improved. Over North America, surface wind speed and temperature are much better, and over Japan, the diurnal pattern of surface temperature is much improved, as are wind speed and precipitation, but not humidity. Three well-known synoptic/subsynoptic-scale weather patterns over the United States, Europe, and Antarctica were shown to become more realistic. This study suggests that the global downscaling is a viable and economical method for obtaining high-resolution reanalysis without rerunning a very expensive high-resolution full data assimilation.

scholarly journals Estimating Coastal Winds by Assimilating High-Frequency Radar Spectrum Data in SWAN

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7811
Author(s):  
Philip Muscarella ◽  
Kelsey Brunner ◽  
David Walker
Keyword(s):  
High Frequency ◽  
Wave Spectrum ◽  
Coastal Ocean ◽  
Ocean Model ◽  
Hf Radar ◽  
Doppler Spectrum ◽  
Observation Data ◽  
Swan Model ◽  
Wave Models ◽  
Using Data

Many activities require accurate wind and wave forecasts in the coastal ocean. The assimilation of fixed buoy observations into spectral wave models such as SWAN (Simulating Waves Nearshore) can provide improved estimates of wave forecasts fields. High-frequency (HF) radar observations provide a spatially expansive dataset in the coastal ocean for assimilation into wave models. A forward model for the HF Doppler spectrum based on first- and second-order Bragg scattering was developed to assimilate the HF radar wave observations into SWAN. This model uses the spatially varying wave spectra computed using the SWAN model, forecast currents from the Navy Coastal Ocean Model (NCOM), and system parameters from the HF radar sites to predict time-varying range-Doppler maps. Using an adjoint of the HF radar model, the error between these predictions and the corresponding HF Doppler spectrum observations can be translated into effective wave-spectrum errors for assimilation in the SWAN model for use in correcting the wind forcing in SWAN. The initial testing and validation of this system have been conducted using data from ten HF radar sites along the Southern California Bight during the CASPER-West experiment in October 2017. The improved winds compare positively to independent observation data, demonstrating that this algorithm can be utilized to fill an observational gap in the coastal ocean for winds and waves.

scholarly journals Evaluation of Global Reanalysis Land Surface Wind Speed Trends to Support Wind Energy Development Using In Situ Observations

2021 ◽  
Vol 60 (1) ◽  
pp. 33-50
Author(s):  
Wenxin Fan ◽  
Yi Liu ◽  
Adrian Chappell ◽  
Li Dong ◽  
Rongrong Xu ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Land Surface ◽  
Turning Point ◽  
Surface Wind ◽  
Energy Resource ◽  
Surface Wind Speed ◽  
Wind Speeds ◽  
Global Reanalysis

AbstractGlobal reanalysis products are important tools across disciplines to study past meteorological changes and are especially useful for wind energy resource evaluations. Studies of observed wind speed show that land surface wind speed declined globally since the 1960s (known as global terrestrial stilling) but reversed with a turning point around 2010. Whether the declining trend and the turning point have been captured by reanalysis products remains unknown so far. To fill this research gap, a systematic assessment of climatological winds and trends in five reanalysis products (ERA5, ERA-Interim, MERRA-2, JRA-55, and CFSv2) was conducted by comparing gridcell time series of 10-m wind speed with observational data from 1439 in situ meteorological stations for the period 1989–2018. Overall, ERA5 is the closest to the observations according to the evaluation of climatological winds. However, substantial discrepancies were found between observations and simulated wind speeds. No reanalysis product showed similar change to that of the global observations, although some showed regional agreement. This discrepancy between observed and reanalysis land surface wind speed indicates the need for prudence when using reanalysis products for the evaluation and prediction of winds. The possible reasons for the inconsistent wind speed trends between reanalysis products and observations are analyzed. The results show that wind energy production should select different products for different regions to minimize the discrepancy with observations.

Sign in / Sign up

Export Citation Format

Share Document