Tidetech environmental data — sources and validation

Weather data

Tidetech provides a range of numerical weather model outputs sourced from official government sources and private weather providers. They include GFS – Global Forecast System (US National Centre for Environmental Prediction), ECMWF (European Centre for Medium Range Weather Forecasting) and CMC (Canadian Meteorological Centre). The primary operational product provided is the GFS, a model in common use by weather routing companies.

Validation statistics, comparing operational forecast weather models, are routinely provided by NOAA.

Statistical metrics averaged over the latest month’s data compare the performance of six operational models (including GFS, CMC and ECMWF) at the global and regional scale. Figure 1 shows the Anomaly Correlation Coefficient (ACC) across the northern hemisphere for six global models; a score of 1.0 on a particular valid date indicates that the forecast made five days prior to that valid date was highly accurate (i.e., essentially perfect). Typically, the three models we use (GFS-black, ECMWF-red, CMC-dark blue) have ACC > 0.9.

Wave data

The World Meteorological Organization (WMO) routinely conducts world-wide three-monthly summary statistics for wave parameters from all operational wave model forecasts (17 models, five-day forecasts) against a common set of wave buoys (details here).

These wave buoys are mostly concentrated in the areas of the northwest European shelf, the northeast USA, the northwest USA, the Caribbean and Hawaii with a handful of buoys elsewhere. The latest summary for December 2025 to March 2026 for the northern hemisphere in winter is shown in Figure 2 (observation location (above) and RMSE of significant wave height (Hs) (below)). RMSE increases with forecast time (from 0.4m to 0.8m, with a consistent spread of 0.2m). Models tend to consistently either underestimate or overestimate Hs through the forecast window by approximately 0.1m.

Tidetech supplies forecast wave data from two models, the Copernicus Global Ocean Wave model from MeteoFrance (METFR), and the NCEP WW3 model (NCEP), both of which perform similarly, the higher spatial resolution of METFR giving slightly better statistics.

Ocean models

Tidetech obtains ocean model data from the Mercator (NEMO) model run by the Copernicus Environment Monitoring Service (CMEMS), and Global RTOFS run by NOAA Global Ocean Prediction Center.

Validation for Mercator example: Metrics, comparing model against in-situ or satellite observations, are routinely calculated for several model parameters (salinity, temperature, sea level anomaly, sea surface temperature). Figure 3 shows the sea level anomaly (SLA) comparison for the north Atlantic Ocean (30-70N) between satellite altimeter and model over the past three years, January 2023-December 2025. Sea level anomaly is chosen because this is the major contributor to determining the forecast accuracy of the large scale geostrophic currents.

It is seen, Figure 3, that the north Atlantic experiences a strong seasonal cycle with a range of 10cm, minimum in March, maximum in September.  There is little difference between the forecasts for day1 (fc01) and day5 (fc05) and the analysis (ana).  On average across the domain, the Root Mean Square Error (RMSE) for the analysis at time t0 (ana) has a value 0.06m which increases to 0.08m for forecast day 5 (fc05). The bias is nearly always between +/- 0.02m.

The shaded area shows the number of altimeter measurements per averaging period, a function of the number of satellites available. It is noticeable that with the ramp up of the SWOT satellite data in January 2025 the number of observations increases by a factor of three and, correspondingly, the RMSE shows a reduction of ~0.01m.  The sudden increase in RMSE in November 2025  corresponds with a reduction in SWOT measurements, indicating the increased dependency on SWOT.

Tides

Tidetech constructs hydrodynamic models of tidal elevation and currents using techniques developed within the SCHISM open source community and, historically, at the UK National Oceanography Centre (formerly the Proudman Oceanographic Laboratory).

Model output is validated using available observations. The preferred method is validation against tidal currents obtained from current meters. Below is an example of validation of Tidetech’s high resolution model for San Francisco Bay.

Unfortunately, only a very small amount of current meter data is available worldwide due to the challenges of measuring currents in the open sea.

In lieu of current meter data, model output can be validated against tidal elevations obtained from analysis of tide gauge data. At least 12 months of observations is required to obtain sufficient tidal constituents to accurately predict future tidal elevations.

Locations where this quality of information is available is limited to major (primary or standard) ports. Ideally, to obtain the full set of tidal constituents the observations would need to span 18.6 years (the full tidal cycle).

Figure 5 shows validation of Tidetech’s high resolution model for San Francisco Bay against tide gauge data.

On a larger model grid, averaging of model values over a grid square will make comparisons more general in nature, but they are useful nonetheless.

Figure 6 shows comparisons between Tidetech 2km resolution English Chanel Model and Tidal elevation predictions produced from analysis of tide gauge data.

Tidal currents can also be validated against official sources, although this approach should be used with caution. Unfortunately, unlike predictions of tidal elevations at major ports, predicted tidal currents from official sources can vary considerably in accuracy. Many are from observations taken a long time ago, before modern instrumentation. At least one month’s worth of observations is required to reproduce the primary constituents at a single location and in plenty of cases only a couple of day’s observations have been taken.

Observations taken when the meteorological conditions were not calm are also questionable, since wind driven surface currents can distort results. Figure 7 shows tidal currents from Tidetech’s 2km English Channel model validated against predictions obtained from UKHO tidal diamonds. Where there is a discrepancy, it is impossible to say whether the model is incorrect or the observations incomplete.

Satellite-derived products

Sea surface temperature (SST). Tidetech uses a 1-km global blended product, produced daily. This product arises from a combination of different satellites and is produced by the Jet Propulsion Laboratory in California.

Comparison of the global product with in-situ data is carried out daily. Figure 8 below shows a scatter plot of blended SST against ship measurements for the 2nd May 2014, indicating the use of more than 3000 observations, with a mean bias of -0.12°C and a RMS of 0.79°C. This is a day taken at random and appears typical.