Fluctuations in Tidal Level Precision with Lengthening Data Sets
In the realm of tidal predictions, calculating the Highest Astronomical Tide (HAT) – a defined tidal level used in Australia – can be challenging when dealing with short datasets. This article explores strategies to enhance the accuracy of HAT calculations in such situations.
The process begins with a harmonic analysis of sea level observations, a method that requires careful treatment of sampling intervals, robust mathematical modeling, and the application of least squares techniques to estimate tidal constituents reliably.
When datasets are short, the challenge is correctly identifying these constituents without aliasing or inadequate frequency resolution. To address this, the Delft3D-TIDE User Manual provides guidance on ensuring measurement intervals meet the Nyquist criterion, understanding limitations on frequency resolution due to short records, and employing least squares fitting to extract tidal harmonics.
Additional strategies include using auxiliary data or regional tidal constants, explicit astronomical forcing modeling, advanced calibration methods, and the inclusion of shallow water tidal constituents from neighbouring sites with long datasets (inference).
For instance, the two sites in the Gulf of Carpentaria have larger HAT-HATSDL than other sites, but the inclusion of inference reduces this difference significantly. The Australian Bureau of Meteorology (BoM) uses HAT as a vertical reference level in the Storm Tide Warning System during severe weather and for defining overhead clearances for bridges and power lines on maritime charts.
It is worth noting that without the use of inference, a deployment for 35 days will give a similar level of confidence in the derived tidal level as would a deployment of 90 or 180 days. However, a deployment of 400 days should improve the confidence in any derived tidal level over the confidence in using shorter deployments.
In summary, refining HAT calculations from short datasets involves appropriate sampling intervals, understanding data record lengths, least squares estimation of constituents, using regional harmonic constants or auxiliary data, explicit astronomical forcing modeling, advanced calibration methods, and the inclusion of inference where possible. These strategies aim to improve the accuracy of HAT calculations and ensure reliable predictions for various applications.
References:
- Delft3D-TIDE User Manual
- Contemporary research on improving hydrodynamic model accuracy
- Research focusing on broader hydrodynamic models or coastal water levels
- Pilot study findings on the relationship between dataset length and the LAT to HAT level.
- In marine science, applying data-and-cloud-computing techniques can aid in enhancing the accuracy of calculating Highest Astronomical Tide (HAT) levels, especially with short datasets, as demonstrated in the Australian Bureau of Meteorology's Storm Tide Warning System.
- To achieve precise HAT calculations, environmental-science researchers may utilize technology to carry out advanced calibration methods, such as least squares fitting, and employ explicit astronomical forcing modeling, all while ensuring appropriate sampling intervals and understanding data record lengths, as suggested in the Delft3D-TIDE User Manual.
- To address the challenge of identifying tidal constituents accurately in short datasets, climate-change research could focus on the use of regional tidal constants or auxiliary data, as well as the implementation of inference, thus improving the reliability of HAT predictions in various applications, as demonstrated by studies on the Gulf of Carpentaria.
