Comparison of Two Methods for Measuring Sea Surface Temperature When Surfing

Abstract

Nearshore coastal waters are among the most dynamic regions on the planet and difficult to sample from conventional oceanographic platforms. It has been suggested that environmental sampling of the nearshore could be improved by mobilising vast numbers of citizens who partake in marine recreational sports, like surfing. In this paper, we compared two approaches for measuring sea surface temperature (SST), an Essential Climate Variable, when surfing. One technique involved attaching a commercially-available miniature temperature logger (Onset UTBI-001 TidbiT v2) to the leash of the surfboard (tether connecting surfer and surfboard) and the second, attaching a surfboard fin (Smartfin) that contained an environmental sensor package. Between July 2017 and July 2018, 148 surfing sessions took place, 90 in the southwest UK and 58 in San Diego, California, USA. During these sessions, both Smartfin and leash sensors were deployed simultaneously. On the leash, two TidbiT v2 sensors were attached, one with (denoted LP) and one without (denoted LU) a protective boot, designed to shield the sensor from sunlight. The median temperature from each technique, during each surfing session, was extracted and compared along with independent water temperature data from a nearby pier and benthic logger, and matched with photosynthetically available radiation (PAR) data from satellite observations (used as a proxy for solar radiation during each surf). Results indicate a mean difference ( δ ) of 0.13 °C and mean absolute difference ( ϵ ) of 0.14 °C between Smartfin and LU, and a δ of 0.04 °C and an ϵ of 0.06 °C between Smartfin and LP. For UK measurements, we observed better agreement between methods ( δ = 0.07 °C and ϵ = 0.08 °C between Smartfin and LU, and δ = 0.00 °C and ϵ = 0.03 °C between Smartfin and LP) when compared with measurements in San Diego ( δ = 0.22 °C and ϵ = 0.23 °C between Smartfin and LU, and δ = 0.08 °C and ϵ = 0.11 °C between Smartfin and LP). Surfing SST data were found to agree well, in general, with independent temperature data from a nearby pier and benthic logger. Differences in SST between leash and Smartfin were found to correlate with PAR, both for the unprotected (LU) and protected (LP) TidbiT v2 sensors, explaining the regional differences in the comparison (PAR generally higher during US surfing sessions than UK sessions). Considering that the Smartfin is sheltered from ambient light by the surfboard, unlike the leash, results indicate the leash TidbiT v2 sensors warm with exposure to sunlight biasing the SST data positively, a result consistent with published tests on similar sensors in shallow waters. We matched all LU data collected prior to this study with satellite PAR products and corrected for solar heating. Results highlight the need to design temperature sensor packages that minimise exposure from solar heating when towed in the surface ocean.

Comparison of a Smartfin with an Infrared Sea Surface Temperature Radiometer in the Atlantic Ocean

“…Note for the iButton, Brewin et al [40] previously reported a median (not mean as used here) difference of 0.283 K for these experiments. These differences were within the accuracies stated by the sensor manufacturers, with the TidbiT v2 sensors accurate to 0.2 K over a range of 273.15 to 323.15 K, and the iButton 0.5 K over a range of 263.15 to 333.15 K. The differences between the TidbiT v2 sensor and the Themometrics ES 225 temperature probe (δ = 0.089) were also consistent with similar laboratory tests of the TidbiT v2 sensors in other studies [27,35], for example, Brewin et al [27] reported differences (δ) of 0.04 to 0.15 K for five TidbiT v2 sensors. The differences between the probe and the TidbiT v2 and iButton sensors (δ = 0.089 and δ = 0.292, Figure 2) were relatively systematic over the temperature range tested (Figure 2), and consequently, were removed from all data collected using these sensors in subsequent analysis.…”

“…The Smartfin records temperature continuously at 1/6 Hz using two different sensors, one within the body (motherboard) of the Smartfin (internal), the other placed on the tip of the fin (external). The external temperature sensor is a MAX31725 temperature circuit (see [34] for technical details) and was used in the study, as it has a quicker response and a higher precision and resolution than the internal sensor (e.g., see [35]). When submerged, the sensible part of the external temperature sensor is located at 0.1 m depth.…”

“…To motivate the remote-sensing community to use data collected by Smartfin surfers, Smartfin data needs to be carefully evaluated against state-of-the-art sensors, so that uncertainties in measurements can be quantified. Initial comparison work in the laboratory [34] and nearshore [35] has indicated the Smartfin can collect high-quality measurements, with uncertainties in temperature readings around 0.05 K, well below target accuracy requirements for satellite thermal sensors in coastal waters (<0.5 K; [36]). However, to date the Smartfin has not been compared with shipboard radiometers, the gold standard (FRM) for the validation of satellite derived SST, or other state-of-the art temperature instruments used on oceanography research vessels.…”

An Evaluation of Autonomous In Situ Temperature Loggers in a Coastal Region of the Eastern Mediterranean Sea for Use in the Validation of Near-Shore Satellite Sea Surface Temperature Measurements

“…For these near-surface sensors, following the recommendations of Castillo and Lima [23], the installation will be with their long surface vertical to the sea surface in order to be less affected/biased due to direct solar radiation heating. This will also provide the most accurate method for investigating any stratification phenomena in the study area, since it will as much as possible prevent direct solar radiation heating-which, when using unshaded loggers, can result in areas with transparent clear waters, with erroneously high underwater temperature measurements, according to Bahr et al [48] and Brewin et al [49]. A land-based meteorological station is also going to be installed in the vicinity of the study area, so that it will be possible to investigate and quantify any correlations between atmospheric conditions and satellite SST measurement anomalies, following the methods of Brewin et al [21].…”

New water and air pollution sensors added to the Sonic Kayak citizen science system for low cost environmental mapping

“…The Sonic Kayak system sets itself apart from these projects as the environmental data is geolocated and can be collected while moving, allowing very quick mapping without the need for multiple sets of equipment. A similar initiative, the Smartfin (https://smartfin.org/) is close in its aims, but is specific to surfboards and stand-up-paddleboards (as the electronics are embedded within a fin), currently only measures temperature, and is not open source so is not available for people to build or develop themselves (Brewin et al 2020).…”