Real-time, continuous, and long-term marine monitoring data benefits ocean research. This study developed a low-cost, multi-parameter, miniature wave buoy. High spatial and temporal resolution of sea surface parameters, including wind, waves, and current, can be obtained at low cost through the deployment of numerous buoys, thus forming an observation array. Tested in the laboratory water tank, the relative error of water surface slope measurement of the buoy was approximately 5.6% when the slope angle was less than 15°. For frequencies between 0.1 and 1.0 Hz, the measurement of slope spectrum was almost identical to that of the wave gauge. The buoy underestimated the slope spectrum between 1.0–1.56 Hz. A good relationship (r² = 0.75) was obtained between wind speed at 10 m above sea surface (U10) and the low-pass-filtered mean square slope (LPMSS). After incorporating the wave age into the U10 inversion process, the root mean square error (RMSE) and BIAS were reduced to 1.15 m/s and 0.02 m/s, respectively. The 2D distribution of buoy-measured slope components was used to detect the wind direction, with an RMSE of 23.7°. The spectral tail slope steepened with increasing wind speed at low wind speeds (<7 m/s). A technical flow chart of the miniature wave buoy is proposed to observe the sea surface parameters. This miniature buoy will play an essential complementary role in the growing demand for sea state monitoring, especially in nearshore oceans.

The pivotal role of oceanographic parameters in informed decision-making spans a spectrum of marine issues, including resource management, ecological preservation, maritime safety, and national security. Conventional data acquisition methods, such as buoys and survey ships, have become increasingly inadequate in addressing the complex demands of these domains. This insufficiency has propelled the global development of spatially-oriented observational technologies, among which High-Frequency (HF) ocean radar is a standout. Globally, the deployment of HF ocean radar systems has surpassed 1000 units. Taiwan, since the 1990s, has installed 48 HF radar systems, including variants like CODAR, WEAR, and LERA. Despite initial successes, a decline in system performance post-deployment is a recurring issue, often linked to policy discontinuity, fluctuating financial support, team dynamics, technical proficiency, and data application and dissemination challenges. This study explores Taiwan's unique experiences with these impediments in the evolution of HF ocean radar systems, aiming to strategize effective long-term operational planning. A case in point is the Taiwan Ocean Radar Observation System (TOROS), established by the Taiwan Ocean Research Institute (TORI) in 2016. This system confronted operational challenges due to insufficient maintenance budgets soon after its inauguration, leading to the cessation of some station operations. Further analysis identified a reactive data dissemination model, requiring user applications and approvals, as a primary issue. This inefficiency, compounded by inadequate promotion, weakened the system's perceived utility, resulting in unsustainable policy support, budget cuts, and the loss of specialized personnel, thereby adversely impacting system functionality in a cyclic manner. This paper argues that the ubiquity of data fosters demand, a critical metric for evaluating system utility. Such utility influences administrative decisions, which in turn affect financial commitment, vital for cultivating a skilled technical team. The strategic deployment of this workforce is crucial for consistent system operation and maintenance, ultimately determining operational success. Leveraging insights from past installations and operational experiences, the study proposes methodologies to sustain operational continuity and bolster the efficacy and resilience of HF ocean radar systems.

This study focuses on the spatiotemporal analysis of High Frequency Radar (HFR) signal intensity under various environmental conditions, utilizing data from four LERA MKIII systems along the northern coast of Taiwan. This investigation spans from 2023 to 2024. The radar systems are strategically positioned at different locations: Shalun station operates at 24.4 MHz with a boresight angle of 0 degrees, Beigang station at 26.77 MHz with a boresight of 345 degrees, Chaojing station at 27.75 MHz with a boresight of 0 degrees, and Zhongjiao Bay station at 31.75 MHz with a boresight of 55 degrees. The coordinates for these stations are respectively 121.24°E, 25.11°N (Shalun); 121.16°E, 25.08°N (Beigang); 121.80°E, 25.14°N (Chaojing); and 121.63°E, 25.24°N (Zhongjiao Bay). Each HFR system consists of a linear array of 16 receiving antennas and utilizes the beamforming method to process signals within a boresight angle range of ±60 degrees. This study's methodology employs time series analysis techniques to scrutinize High Frequency Radar (HFR) data, correlating it with various environmental observations. By charting the Signal-to-Noise Ratio (SNR) of the radar signals across different range cells along the radar's boresight azimuth over time, we identify temporal and spatial trends. Notably, periodic fluctuations in the radar signal time series have been observed. These fluctuations seem intricately linked to tidal cycles, exhibiting a significant correlation with the angular disparity between tidal flow direction and the radar's boresight azimuth. Additionally, a decrease in radar signal strength coupled with an increase in noise levels was noticed under conditions of elevated winds and waves. The research aims to precisely quantify the interplay between radar signals and the collective influence of tides, waves, and wind speeds. This thorough analysis seeks to deepen our understanding of how environmental elements impact radar performance, thereby contributing to a more nuanced comprehension of coastal ocean dynamics.