The Australian coastal ocean radar network: Temporal and spatial scales of HF radar wave data

Author(s):  
Andrew Middleditch ◽  
Simone Cosoli
2013 ◽  
Vol 72 ◽  
pp. 17-31 ◽  
Author(s):  
Jennifer Waters ◽  
Lucy R. Wyatt ◽  
Judith Wolf ◽  
Adrian Hines

10.29007/wg8s ◽  
2018 ◽  
Author(s):  
Marco Picone ◽  
Arianna Orasi ◽  
Aldo Drago ◽  
Fulvio Capodici ◽  
Giuseppe Ciraolo ◽  
...  

The CALYPSO HF radar network is a permanent and fully operational observing system currently composed of four CODAR HF stations. The system is providing real- time hourly maps of sea surface currents and wave data in the Malta-Sicily Channel since 2012. Significant wave height derived from the HF radar wave measurements are confirmed to be a reliable source of wave information even in case of extreme events. However, it is noticed that the HF radar wave data are subject to differing interfering noise in the signal from unknown sources that may be competing with transmissions in the same frequency band. These interferences lead to frequent gaps and/or outliers that affect the continuity and reliability of the data set. The aim of this work is to estimate missing values and to detect possible outliers building and fitting a Markov chain mixture model on the significant wave height data collected at the four stations. It is verified that the proposed procedure is sufficiently robust since the model estimates succeed to classify radar observations with a high percentage of missing data and to equally highlight spikes and outliers.


2016 ◽  
Vol 33 (7) ◽  
pp. 1377-1392 ◽  
Author(s):  
Anthony Kirincich

AbstractThe calibration and validation of a novel approach to remotely sense surface winds using land-based high-frequency (HF) radar systems are described. Potentially available on time scales of tens of minutes and spatial scales of 2–3 km for wide swaths of the coastal ocean, HF radar–based surface wind observations would greatly aid coastal ocean planners, researchers, and operational stakeholders by providing detailed real-time estimates and climatologies of coastal winds, as well as enabling higher-quality short-term forecasts of the spatially dependent wind field. Such observations are particularly critical for the developing offshore wind energy community. An autonomous surface vehicle was deployed within the Massachusetts Wind Energy Area, located south of Martha’s Vineyard, Massachusetts, for one month, collecting wind observations that were used to test models of wind-wave spreading and HF radar energy loss, thereby empirically relating radar-measured power to surface winds. HF radar–based extractions of the remote wind speed had accuracies of 1.4 m s−1 for winds less than 7 m s−1, within the optimal range of the radar frequency used. Accuracies degraded at higher winds due to low signal-to-noise ratios in the returned power and poor resolution of the model. Pairing radar systems with a range of transmit frequencies with adjustments of the extraction model for additional power and environmental factors would resolve many of the errors observed.


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