Validation of Landsat 8 high resolution Sea Surface Temperature using surfers

This is the final version. Available on open access from Elsevier via the DOI in this record.Nearshore coastal waters are highly dynamic in both space and time. They can be difficult to sample using conventional methods due to their shallow depth, tidal variability, and the presence of strong currents and breaking waves. High resolution satellite sensors can be used to provide synoptic views of Surface Temperature (ST), but the performance of such ST products in the nearshore zone is poorly understood. Close to the shoreline, the ST pixels can be influenced by mixed composition of water and land, as a result of the sensor’s spatial resolution. This can cause thermal adjacency effects due to the highly different diurnal temperature cycles of water bodies and land. Previously, temperature data collected during surfing sessions has been proposed for validation of moderate resolution (1 km pixel size) satellite ST products. In this paper we use surfing temperature data to validate three high resolution (100 m resampled to 30 m pixel size) ST products derived from the Thermal InfraRed Sensor (TIRS) on board Landsat 8 (L8). ST was derived from Collection 1 and 2 Level 1 data (C1L1 and C2L1) using the Thermal Atmospheric Correction Tool (TACT), and was obtained from the standard Collection 2 Level 2 product (USGS C2L2). This study represents one of the first evaluations of the new C2 products, both L1 and L2, released by USGS at the end of 2020. Using automated matchup and image quality control, 88 matchups between L8/TIRS and surfers were identified, distributed across the NorthWestern semihemisphere. The unbiased Root Mean Squared Difference (uRMSD) between satellite and in situ measurements was generally < 2 K, with warm biases (Mean Average Difference, MAD) of 1.7 K (USGS C2L2), 1.3 K (TACT C1L1) and 0.8 K (TACT C2L1). Large interquartile ranges of ST in 5 × 5 satellite pixels around the matchup location were found for several images, especially for the summer matchups around the Californian coast. By filtering on target stability the number of matchups reduced to 31, which halved the uRMSD across the three methods (to around 1.1K), MAD were much lower, i.e. 1.1 K (USGS C2L2), 0.6 K (TACT C1L1), and 0.2 K (TACT C2L1). The larger biases of the C2L2 product compared to TACT C2L1 are caused as a result of: (1) a lower emissivity value for water targets used in USGS C2L2, and (2) differences in atmospheric parameter retrieval, mainly from differences in upwelling atmospheric radiance and lower atmospheric transmittance retrieved by USGS C2L2. Additionally, tiling artefacts are present in the C2L2 product, which originate from a coarser atmospheric correction process. Overall, the L8/TIRS derived ST product compares well with in situ measurements made while surfing, and we found the best performing ST product for nearshore coastal waters to be the Collection 2 Level 1 data processed with TACT.UK Research and InnovationFederal Belgian Science Policy Office (BELSPO)Lost Bird Foundatio

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

This is the final version. Available on open access from MDPI via the DOI in this recordThe accuracy and precision of satellite sea surface temperature (SST) products in nearshore coastal waters are not well known, owing to a lack of in-situ data available for validation. It has been suggested that recreational watersports enthusiasts, who immerse themselves in nearshore coastal waters, be used as a platform to improve sampling and fill this gap. One tool that has been used worldwide by surfers is the Smartfin, which contains a temperature sensor integrated into a surfboard fin. If tools such as the Smartfin are to be considered for satellite validation work, they must be carefully evaluated against state-of-the-art techniques to quantify data quality. In this study, we developed a Simple Oceanographic floating Device (SOD), designed to float on the ocean surface, and deployed it during the 28th Atlantic Meridional Transect (AMT28) research cruise (September and October 2018). We attached a Smartfin to the underside of the SOD, which measured temperature at a depth of ∼0.1 m, in a manner consistent with how it collects data on a surfboard. Additional temperature sensors (an iButton and a TidbiT v2), shaded and positioned a depth of ∼1 m, were also attached to the SOD at some of the stations. Four laboratory comparisons of the SOD sensors (Smartfin, iButton and TidbiT v2) with an accurate temperature probe (±0.0043 K over a range of 273.15 to 323.15 K) were also conducted during the AMT28 voyage, over a temperature range of 290–309 K in a recirculating water bath. Mean differences (δ), referenced to the temperature probe, were removed from the iButton (δ=0.292 K) and a TidbiT v2 sensors (δ=0.089 K), but not from the Smartfin, as it was found to be in excellent agreement with the temperature probe (δ=0.005 K). The SOD was deployed for 20 min periods at 62 stations (predawn and noon) spanning 100 degrees latitude and a gradient in SST of 19 K. Simultaneous measurements of skin SST were collected using an Infrared Sea surface temperature Autonomous Radiometer (ISAR), a state-of-the-art instrument used for satellite validation. Additionally, we extracted simultaneous SST measurements, collected at slightly different depths, from an underway conductivity, temperature and depth (CTD) system. Over all 62 stations, the mean difference (δ) and mean absolute difference (ϵ) between Smartfin and the underway CTD were −0.01 and 0.06 K respectively (similar results obtained from comparisons between Smartfin and iButton and Smartfin and TidbiT v2), and the δ and ϵ between Smartfin and ISAR were 0.09 and 0.12 K respectively. In both comparisons, statistics varied between noon and predawn stations, with differences related to environmental variability (wind speed and sea-air temperature differences) and depth of sampling. Our results add confidence to the use of Smartfin as a citizen science tool for evaluating satellite SST data, and data collected using the SOD and ISAR were shown to be useful for quantifying near-surface temperature gradients.European Space AgencyLost Bird Projec

Comparison of Two Methods for Measuring Sea Surface Temperature When Surfing

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

Expanding Aquatic Observations through Recreation

Accurate observations of the Earth system are required to understand how our planet is changing and to help manage its resources. The aquatic environment—including lakes, rivers, wetlands, estuaries, coastal and open oceans—is a fundamental component of the Earth system controlling key physical, biological, and chemical processes that allow life to flourish. Yet, this environment is critically undersampled in both time and space. New and cost-effective sampling solutions are urgently needed. Here, we highlight the potential to improve aquatic sampling by tapping into recreation. We draw attention to the vast number of participants that engage in aquatic recreational activities and argue, based on current technological developments and recent research, that the time is right to employ recreational citizens to improve large-scale aquatic sampling efforts. We discuss the challenges that need to be addressed for this strategy to be successful (e.g., sensor integration, data quality, and citizen motivation), the steps needed to realize its potential, and additional societal benefits that arise when engaging citizens in scientific sampling

Expanding aquatic observations through recreation

This is the final version. Available on open access from Frontiers Media via the DOI in this recordAccurate observations of the Earth system are required to understand how our planet is changing and to help manage its resources. The aquatic environment-including lakes, rivers, wetlands, estuaries, coastal and open oceans-is a fundamental component of the Earth system controlling key physical, biological, and chemical processes that allow life to flourish. Yet, this environment is critically undersampled in both time and space. New and cost-effective sampling solutions are urgently needed. Here, we highlight the potential to improve aquatic sampling by tapping into recreation. We draw attention to the vast number of participants that engage in aquatic recreational activities and argue, based on current technological developments and recent research, that the time is right to employ recreational citizens to improve large-scale aquatic sampling efforts. We discuss the challenges that need to be addressed for this strategy to be successful (e.g., sensor integration, data quality, and citizen motivation), the steps needed to realize its potential, and additional societal benefits that arise when engaging citizens in scientific sampling.UK National Centre for Earth ObservationSmartfin/Lostbird FoundationDefr

On the Seasonal Dynamics of Phytoplankton Chlorophyll-a Concentration in Nearshore and Offshore Waters of Plymouth, in the English Channel: Enlisting the Help of a Surfer

This is the final version. Available on open access from MDPI via the DOI in this recordData Availability Statement: Surfer data collected are openly available through the British Oceanographic Data Centre https://www.bodc.ac.uk/data/published_data_library/catalogue/10.5285/d6a5a863-a43d-28a9-e053-6c86abc0b1f4/). L4 datasets are available through the Western Channel Observatory (www.westernchannelobservatory.org.uk). Satellite data used are freely available through NASA (https://oceancolor.gsfc.nasa.gov) and ESA (https://climate.esa.int/en/projects/ocean-colour/).The role of phytoplankton as ocean primary producers and their influence on global biogeochemical cycles makes them arguably the most important living organisms in the sea. Like plants on land, phytoplankton exhibit seasonal cycles that are controlled by physical, chemical, and biological processes. Nearshore coastal waters often contain the highest levels of phytoplankton biomass. Yet, owing to difficulties in sampling this dynamic region, less is known about the seasonality of phytoplankton in the nearshore (e.g., surf zone) compared to offshore coastal, shelf and open ocean waters. Here, we analyse an annual dataset of chlorophyll-a concentration—a proxy of phytoplankton biomass—and sea surface temperature (SST) collected by a surfer at Bovisand Beach in Plymouth, UK on a near weekly basis between September 2017 and September 2018. By comparing this dataset with a complementary in-situ dataset collected 7 km offshore from the coastline (11 km from Bovisand Beach) at Station L4 of the Western Channel Observatory, and guided by satellite observations of light availability, we investigated differences in phytoplankton seasonal cycles between nearshore and offshore coastal waters. Whereas similarities in phytoplankton biomass were observed in autumn, winter and spring, we observed significant differences between sites during the summer months of July and August. Offshore (Station L4) chlorophyll-a concentrations dropped dramatically, whereas chlorophyll-a concentrations in the nearshore (Bovsiand Beach) remained high. We found chlorophyll-a in the nearshore to be significantly positively correlated with SST and PAR over the seasonal cycle, but no significant correlations were observed at the offshore location. However, offshore correlation coefficients were found to be more consistent with those observed in the nearshore when summer data (June–August 2018) were removed. Analysis of physical (temperature and density) and chemical variables (nutrients) suggest that the offshore site (Station L4) becomes stratified and nutrient limited at the surface during the summer, in contrast to the nearshore. However, we acknowledge that additional experiments are needed to verify this hypothesis. Considering predicted changes in ocean stratification, our findings may help understand how the spatial distribution of phytoplankton phenology within temperate coastal seas could be impacted by climate change. Additionally, this study emphasises the potential for using marine citizen science as a platform for acquiring environmental data in otherwise challenging regions of the ocean, for understanding ecological indicators such as phytoplankton abundance and phenology. We discuss the limitations of our study and future work needed to explore nearshore phytoplankton dynamics.UK Research and InnovationLost Bird ProjectNatural Environment Research Council (NERC)European Regional Development Fund (ERDF

Incidence of Schizophrenia and Other Psychoses in England, 1950–2009: A Systematic Review and Meta-Analyses

Background We conducted a systematic review of incidence rates in England over a sixty-year period to determine the extent to which rates varied along accepted (age, sex) and less-accepted epidemiological gradients (ethnicity, migration and place of birth and upbringing, time). Objectives To determine variation in incidence of several psychotic disorders as above. Data Sources Published and grey literature searches (MEDLINE, PSycINFO, EMBASE, CINAHL, ASSIA, HMIC), and identification of unpublished data through bibliographic searches and author communication. Study Eligibility Criteria Published 1950–2009; conducted wholly or partially in England; original data on incidence of non-organic adult-onset psychosis or one or more factor(s) pertaining to incidence. Participants People, 16–64 years, with first -onset psychosis, including non-affective psychoses, schizophrenia, bipolar disorder, psychotic depression and substance-induced psychosis. Study Appraisal and Synthesis Methods Title, abstract and full-text review by two independent raters to identify suitable citations. Data were extracted to a standardized extraction form. Descriptive appraisals of variation in rates, including tables and forest plots, and where suitable, random-effects meta-analyses and meta-regressions to test specific hypotheses; rate heterogeneity was assessed by the I2-statistic. Results 83 citations met inclusion. Pooled incidence of all psychoses (N = 9) was 31.7 per 100,000 person-years (95%CI: 24.6–40.9), 23.2 (95%CI: 18.3–29.5) for non-affective psychoses (N = 8), 15.2 (95%CI: 11.9–19.5) for schizophrenia (N = 15) and 12.4 (95%CI: 9.0–17.1) for affective psychoses (N = 7). This masked rate heterogeneity (I2: 0.54–0.97), possibly explained by socio-environmental factors; our review confirmed (via meta-regression) the typical age-sex interaction in psychosis risk, including secondary peak onset in women after 45 years. Rates of most disorders were elevated in several ethnic minority groups compared with the white (British) population. For example, for schizophrenia: black Caribbean (pooled RR: 5.6; 95%CI: 3.4–9.2; N = 5), black African (pooled RR: 4.7; 95%CI: 3.3–6.8; N = 5) and South Asian groups in England (pooled RR: 2.4; 95%CI: 1.3–4.5; N = 3). We found no evidence to support an overall change in the incidence of psychotic disorder over time, though diagnostic shifts (away from schizophrenia) were reported. Limitations Incidence studies were predominantly cross-sectional, limiting causal inference. Heterogeneity, while evidencing important variation, suggested pooled estimates require interpretation alongside our descriptive systematic results. Conclusions and Implications of Key Findings Incidence of psychotic disorders varied markedly by age, sex, place and migration status/ethnicity. Stable incidence over time, together with a robust socio-environmental epidemiology, provides a platform for developing prediction models for health service planning

A systematic review of the incidence of schizophrenia: the distribution of rates and the influence of sex, urbanicity, migrant status and methodology

BACKGROUND: Understanding variations in the incidence of schizophrenia is a crucial step in unravelling the aetiology of this group of disorders. The aims of this review are to systematically identify studies related to the incidence of schizophrenia, to describe the key features of these studies, and to explore the distribution of rates derived from these studies. METHODS: Studies with original data related to the incidence of schizophrenia (published 1965–2001) were identified via searching electronic databases, reviewing citations and writing to authors. These studies were divided into core studies, migrant studies, cohort studies and studies based on Other Special Groups. Between- and within-study filters were applied in order to identify discrete rates. Cumulative plots of these rates were made and these distributions were compared when the underlying rates were sorted according to sex, urbanicity, migrant status and various methodological features. RESULTS: We identified 100 core studies, 24 migrant studies, 23 cohort studies and 14 studies based on Other Special Groups. These studies, which were drawn from 33 countries, generated a total of 1,458 rates. Based on discrete core data for persons (55 studies and 170 rates), the distribution of rates was asymmetric and had a median value (10%–90% quantile) of 15.2 (7.7–43.0) per 100,000. The distribution of rates was significantly higher in males compared to females; the male/female rate ratio median (10%–90% quantile) was 1.40 (0.9–2.4). Those studies conducted in urban versus mixed urban-rural catchment areas generated significantly higher rate distributions. The distribution of rates in migrants was significantly higher compared to native-born; the migrant/native-born rate ratio median (10%–90% quantile) was 4.6 (1.0–12.8). Apart from the finding that older studies reported higher rates, other study features were not associated with significantly different rate distributions (e.g. overall quality, methods related to case finding, diagnostic confirmation and criteria, the use of age-standardization and age range). CONCLUSIONS: There is a wealth of data available on the incidence of schizophrenia. The width and skew of the rate distribution, and the significant impact of sex, urbanicity and migrant status on these distributions, indicate substantial variations in the incidence of schizophrenia

Syndromics: A Bioinformatics Approach for Neurotrauma Research

Substantial scientific progress has been made in the past 50 years in delineating many of the biological mechanisms involved in the primary and secondary injuries following trauma to the spinal cord and brain. These advances have highlighted numerous potential therapeutic approaches that may help restore function after injury. Despite these advances, bench-to-bedside translation has remained elusive. Translational testing of novel therapies requires standardized measures of function for comparison across different laboratories, paradigms, and species. Although numerous functional assessments have been developed in animal models, it remains unclear how to best integrate this information to describe the complete translational “syndrome” produced by neurotrauma. The present paper describes a multivariate statistical framework for integrating diverse neurotrauma data and reviews the few papers to date that have taken an information-intensive approach for basic neurotrauma research. We argue that these papers can be described as the seminal works of a new field that we call “syndromics”, which aim to apply informatics tools to disease models to characterize the full set of mechanistic inter-relationships from multi-scale data. In the future, centralized databases of raw neurotrauma data will enable better syndromic approaches and aid future translational research, leading to more efficient testing regimens and more clinically relevant findings