Sea Surface Temperature Measurements Research Articles

Controls on δ18O and δ13C profiles within the aragonite bivalve Arctica islandica

The geochemistry of Arctica islandica shells provides an opportunity to reconstruct intra-annual resolution climate records in temperate latitudes, and the annual banding allows close temporal constraint. Stable isotope analyses of carbon and oxygen from an Arctica islandica live-collected at 6 m depth from Irvine Bay, UK are presented. Seawater temperature ranges reconstructed from shell δ18O agree, within error, with instrumental sea surface temperature measurements. The saw-tooth profile of the seasonal δ 18O signal (compared with the sinusoidal seawater temperature) indicates that shell accretion rate is not constant throughout the year. Modelling the expected δ18O profile from water temperature, salinity and shell growth rate suggest that A. islandica at this site has significant variation in the shell extension rate during the year. Material deposited during shell damage shows a positive shift in δ18O. A strong ontogenetic effect is seen in δ13C and damage to the shell is associated with a significant (>0.5‰) and sustained shift of δ 13C.

Comparison of AMSR‐E and TMI sea surface temperature with Argo near‐surface temperature over the Indian Ocean

Sea surface temperature (SST) measurements from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are compared with near‐surface temperature (foundation SST) in situ measurements obtained from Argo floats over the Indian Ocean. Spatial variation was compared for 2002–2006 and 11 floats were used for temporal variation collocated observations. The results show that TMI and AMSR‐E SST measurements are slightly overestimated during the pre‐ and post‐monsoon seasons and underestimated during the monsoon season. Statistical analysis shows that the SST from the AMSR‐E is better correlated with the Argo foundation SST compared to the TMI. The standard deviation (SD) and root mean square error (RMSE) for AMSR‐E SST are 0.58°C and 0.35°C, respectively, over the Equatorial Indian Ocean (EIO). The corresponding values for the TMI are 0.66°C and 0.47°C. Over the Arabian Sea the SD values are slightly higher compared to the EIO values, whereas RMSE values are less for both TMI and AMSR‐E SST. These retrieval accuracies are above the expected retrieval accuracy. The seasonal average spatial distribution of AMSR‐E SST shows a better match with the Argo foundation SST compared to TMI SST distributions. The robustness of the good spatial match during the monsoon season may be attributed to strong winds.

Measurement of dissolved oxygen using optodes in a FerryBox system

Optode sensors can provide detailed information on concentrations of dissolved oxygen, which in turn may be used to quantify variations in net primary productivity. Throughout 2005 and 2006 the performance of commercially available oxygen optodes was examined, one in each year. The optode was part of an autonomous measurement system (FerryBox) on a ferry operating between Portsmouth (UK) and Bilbao (Spain). On crossings during which water samples were collected manually, the optode outputs were compared to measurements of dissolved oxygen made by Winkler titrations. The optodes maintained good stability with no evidence of instrumental drift during the course of a year. Over the observed concentration range (230–330 mM m −3) the optode data were approximately 2% low in both years. By fitting the optode data to the Winkler data the median difference between the optode and Winkler measurements is reduced to less than 1 mM m −3 (0.3%) in both years. The most appropriate calibration factor for 2005 was corrected O 2 = Optode O 2 × 1.018 and for 2006 the corresponding equation is corrected O 2 = Optode O 2 × 0.884 + 36.8. The standard deviation (95%) of the difference between the individual Winkler measurements was 5 mM m −3 and 3 mM m −3 in 2005 and 2006 respectively. Calculation of the oxygen saturation anomaly is required for calculation of the air sea exchange of oxygen and net biological production. This calculation requires the use of both salinity and temperature data. Salinity is measured to better than 0.1 so the corresponding error in anomaly is less than 0.2 mM m −3. Distortion of the temperature data is present due to warming of the water pumped to the optode. In winter this warming at the optode may be as great as 0.4 °C. The difference in the pumped water temperature can be corrected for by reference to other measurements of sea surface temperature reducing the error to less than 1 mM m −3.

Ocean's response to Hurricane Frances and its implications for drag coefficient parameterization at high wind speeds

The drag coefficient parameterization of wind stress is investigated for tropical storm conditions using model sensitivity studies. The Massachusetts Institute of Technology (MIT) Ocean General Circulation Model was run in a regional setting with realistic stratification and forcing fields representing Hurricane Frances, which in early September 2004 passed east of the Caribbean Leeward Island chain. The model was forced with a NOAA‐HWIND wind speed product after converting it to wind stress using four different drag coefficient parameterizations. Respective model results were tested against in situ measurements of temperature profiles and velocity, available from an array of 22 surface drifters and 12 subsurface floats. Changing the drag coefficient parameterization from one that saturated at a value of 2.3 × 10−3 to a constant drag coefficient of 1.2 × 10−3 reduced the standard deviation difference between the simulated minus the measured sea surface temperature change from 0.8°C to 0.3°C. Additionally, the standard deviation in the difference between simulated minus measured high pass filtered 15‐m current speed reduced from 15 cm/s to 5 cm/s. The maximum difference in sea surface temperature response when two different turbulent mixing parameterizations were implemented was 0.3°C, i.e., only 11% of the maximum change of sea surface temperature caused by the storm.

Model-based estimates of Calanus finmarchicus abundance in the Gulf of Maine

Ocean observing systems and satellites routinely collect a wealth of information on physical conditions in the ocean. With few exceptions, such as chlorophyll concentrations, infor- mation on biological properties is harder to measure autonomously. Here, we present a system to produce estimates of the distribution and abundance of the copepod Calanus finmarchicus in the Gulf of Maine. Our system uses satellite-based measurements of sea surface temperature and chloro- phyll concentration to determine the developmental and reproductive rates of C. finmarchicus. The rate information then drives a population dynamics model of C. finmarchicus that is embedded in a 2-dimensional circulation field. The first generation of this system produces realistic information on interannual variability in C. finmarchicus distribution and abundance during the winter and spring. The model can also be used to identify key drivers of interannual variability in C. finmarchicus. Experiments with the model suggest that changes in initial conditions are overwhelmed by variabil- ity in growth rates after approximately 50 d. Temperature has the largest effect on growth rate. Elevated chlorophyll during the late winter can lead to increased C. finmarchicus abundance during the spring, but the effect of variations in chlorophyll concentrations is secondary to the other inputs. Our system could be used to provide real-time estimates or even forecasts of C. finmarchicus distri- bution. These estimates could then be used to support management of copepod predators such as herring and right whales.

Trends and anomalies in sea-surface temperature, observed over the last 60 years, within the southeastern Bay of Biscay

The Oceanographic Society of Gipuzkoa has recorded daily sea-surface temperature (SST) measurements, since 2nd July 1946, on a (nearly) daily basis. Sixty years of SST measurements (1947–2007) have been considered, in order to analyse the hydrographic trends and anomalies at the southeastern Bay of Biscay. The study reviews initially the consistency and reliability of the time-series; and trends and anomaly patterns. Then, the periodicity of the series; a reference period, for analysing seasonality during the period 2001–2007; and oceano-meteorological coupling within the period 2001–2007, with reference to the baseline period, have been determined. Within this context, a slight cooling trend has been observed for the whole of the time-series, in contrast to the warming over the last three-decadal period. Regarding the periodicity of the series, several cycles have been identified, with periods of about 8, 11 and 18 years; these represent the influence of climate cycles over the (local) SST series. Additionally, seasonal anomaly patterns between 2001 and 2007 have been examined based upon the selected reference period (1980–2002). Several extreme seasonal events have been observed, such as warm summer SST values in 2003 and 2006 and cold winter values in 2005. Such events can be explained by the “deseasonality” phenomenon, observed throughout the study period. In addition to the direct influence of atmospherical parameters, such as air temperature and irradiance on SST, dynamical variables (turbulence and upwelling–downwelling) account also for this coupling. Overall, despite the marginal location and surface character of the time-series, it reveals anomalies that agree with those described for larger zones of the northeastern Atlantic Ocean; hence, it can be characterised as being a reliable and representative long-term SST series.

Prediction of a Rift Valley fever outbreak

El Niño/Southern Oscillation related climate anomalies were analyzed by using a combination of satellite measurements of elevated sea-surface temperatures and subsequent elevated rainfall and satellite-derived normalized difference vegetation index data. A Rift Valley fever (RVF) risk mapping model using these climate data predicted areas where outbreaks of RVF in humans and animals were expected and occurred in the Horn of Africa from December 2006 to May 2007. The predictions were subsequently confirmed by entomological and epidemiological field investigations of virus activity in the areas identified as at risk. Accurate spatial and temporal predictions of disease activity, as it occurred first in southern Somalia and then through much of Kenya before affecting northern Tanzania, provided a 2 to 6 week period of warning for the Horn of Africa that facilitated disease outbreak response and mitigation activities. To our knowledge, this is the first prospective prediction of a RVF outbreak.

A Multivariate Regression Approach to Adjust AATSR Sea Surface Temperature to In Situ Measurements

The Advanced Along-Track Scanning Radiometer (AATSR) onboard Envisat is designed to provide very accurate measurements of sea surface temperature (SST). Using colocated in situ drifting buoys, a dynamical matchup database (MDB) is used to assess the AATSR-derived SST products more precisely. SST biases are then computed. Currently, Medspiration AATSR SST biases are discrete values and can introduce artificial discontinuities in AATSR level-2 SST fields. The new AATSR SST biases presented in this letter are continuous. They are computed, for nighttime and best proximity confidence data, by linear regression with different MDB covariables (wind speed, latitude, aerosol optical depth, etc.). As found, the difference between dual-view and nadir-only SST products explains most of the variability (26%).

Sea surface temperature trends in Kuwait Bay, Arabian Gulf

The waters of Kuwait Bay, northern Arabian Gulf, are well mixed by macrotidal, semi-diurnal tides. Sea surface temperature (SST) is thus a good proxy of water mass temperature in the bay. The factors governing SST have been conveniently sub-divided into global, regional and local drivers. This paper provides a study on long-term drivers of temperature change in the northern Arabian Gulf: that is, factors that influence decadal changes. AVHRR (NOAA) satellite data of Kuwait Bay, collected between 1985 and 2002, show that SST has steadily increased at a rate of 0.6 (±0.3)°C/decade. This trend was three times greater than the concurrent global average. The rate of change was greatest in May and June and least during winter months. The trends defined by satellite data were substantiated by routine in situ monthly measurements of SST made in the region and were also similar to air temperature trends recorded at Kuwait airport. The monthly measurements of SST also showed a peak in summer temperature coincident with an El Nino event in 1998. A relatively low summertime peak during 1991 in the aftermath of Iraqi invasion of Kuwait is considered to be the result of atmospheric dimming brought about by dense smoke that persisted in the region for most of that year.

Sea level and paleotemperature records from a mid-Holocene reef on the North coast of Java, Indonesia

Mid-Holocene age fossil-fringing reefs occur along the tectonically stable north coast of Java, Indonesia, presenting an opportunity for sea level and paleoclimate reconstruction. The fossil reef at Point Teluk Awur, near Jepara, Central Java, contains two directly superposed horizons of Porites lobata microatolls. Corals in the lower horizon, 80 cm above modern sea level, yielded Uranium series dates of 7090 ± 90 year BP, while corals in the upper horizon at 1.5 m grew at 6960 ± 60 year BP. These dates match the transgressive phase of regional sea-level curves, but suggest a mid-Holocene highstand somewhat older than that recorded on mid-Pacific islands. Paleotemperature was calibrated using Sr/Ca and δ18O values of a modern P. lobata coral and the locally measured sea surface temperature (SST), yielding SST–Sr/Ca and SST–δ18O calibration equations [T Sr/Ca = 91.03–7.35(Sr/Ca) and $$ T_{{\delta^{18} {\text{O}}}} $$ = −3.77 to −5.52(δ18O)]. The application of the local equations to Sr/Ca and δ18O measurements on these corals yielded a range of temperatures of 28.8 ± 1.7°C, comparable to that of the modern Java Sea (28.4 ± 0.7°C). A paleo-salinometer [Δδ18O = ∂δ18O/∂T ( $$ T_{{\delta^{18} {\text{O}}}} $$ − T Sr/Ca)], re-calculated using the local parameters, also suggests Java Sea mid-Holocene paleosalinity similar to modern values.

The Kuroshio Extension Front from satellite sea surface temperature measurements

The position and strength of the surface Kuroshio Extension Front (KEF), defined as the sea surface temperature (SST) gradient maximum adjacent to the Kuroshio Extension (KE) axis (approximated by a specific SSH contour consistently located at, or near, the maximum of the SSH gradient magnitude), have been studied using weekly, microwave SST measurements from the later 1997 to early 2008. The mean KEF meanders twice around ∼36°N between the east coast of Japan and 153°E. It then migrates southeast to ∼34°N, just before reaching the Shatsky Rise (∼158°E), then progresses mostly eastward. Spatially, the KEF is strongest near the Japan coast, while it is seasonally strongest in winter and weakest in summer. Low-frequency variations of its strength, most notably in its upstream region, can be related to the known bimodal states of the KE. During 2003–2005, when the KE was in its stable state, the winter KEF SST gradient exceeded 10°C/100 km.

Optimizing smoothed sea surface temperature for improving archival tag geolocation

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 365:35-44 (2008) - DOI: https://doi.org/10.3354/meps07497 Optimizing smoothed sea surface temperature for improving archival tag geolocation Benjamin Galuardi1,*, Anders Nielsen2, Molly Lutcavage1 1Large Pelagics Research Lab, 177 Spaulding Hall, University of New Hampshire, Durham, New Hampshire 03824, USA 2Pelagic Fisheries Research Program, Joint Institute for Marine and Atmospheric Research, University of Hawai’i at Manoa, 1000 Pope Road, MSB 312, Honolulu, Hawaii 96822, USA *Email: galuardi@cisunix.unh.edu ABSTRACT: Pop-up satellite archival tags (PSATs) and data loggers (archival tags) have become key tools for tracking movements of marine animals, but uncertainties in location estimates can range from tens to hundreds of kilometers. Sea surface temperature (SST) may be used in models to improve light-based geolocation by comparing SSTs measured in tags to those measured by satellites (e.g. with a Kalman filter). Daily SST measurements are retrieved from the data recorded in the tag by averaging the near surface temperatures. Raw satellite SST data are represented as points in a grid, but measurement noise and areas missing due to cloud cover can produce an uneven SST field that may not correspond well with the local average of SST measured by the tags. A smoothed satellite SST field is used to compensate for these problems. We used 2 crossvalidation schemes to analyze what degree of smoothing produces the optimal match with the SST from the tag. Simulations based on data returned by PSATs deployed on Atlantic bluefin tuna Thunnus thynnus are used as a test case. We demonstrate that the optimal scale of smoothing, which affects overall variance in any type of geolocation estimation, is influenced by the scale of diffusive animal movement and that treatment of satellite SST in a geolocation framework should be carefully considered. The developed crossvalidation scheme provides an objective method for choosing the optimal smoothing scale and allows for better control of the overall geolocation process. KEY WORDS: Satellite SST · Kalman filter · Local polynomial regression · Animal movement · Bluefin tuna · Thunnus thynnus Full text in pdf format PreviousNextCite this article as: Galuardi B, Nielsen A, Lutcavage M (2008) Optimizing smoothed sea surface temperature for improving archival tag geolocation. Mar Ecol Prog Ser 365:35-44. https://doi.org/10.3354/meps07497 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 365. Online publication date: August 18, 2008 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2008 Inter-Research.

Estimating upper ocean phosphate concentrations using ARGO float temperature profiles

The ARGO free-drifting profiling float array, with >3125 floats deployed between 60°N and 60°S latitudes at about 3° resolution as of May 2008 and each float profiling through 2000 m every 10 days, provides a comprehensive four-dimensional view of temperature and salinity in the world ocean. The resulting dataset complements satellite-based sea surface temperature (SST) measurements and similarly will complement future satellite-based sea surface salinity measurements. Although plans exist to add biogeochemical sensors to future floats, cost and depth restrictions may limit comprehensive upgrades to a fraction of all floats deployed after 2008. Temperature–nutrient (TN) relationships provide a mechanism to estimate nutrient concentrations from temperature to supplement sparser nutrient concentration measurements potentially obtained using non-chemical approaches like ISUS-based nitrate. Both negative and positive aspects of applying a temperature–phosphate (TP) linear regression matrix with global coverage (70°N and 70°S) are examined. The TP linear regression matrix was derived by combining an existing 1° latitude and longitude table of phosphate depletion temperatures (PDT) or X-intercepts with representative TP linear regression slopes derived from the GEOSECS dataset. Temperatures from datasets with associated latitude and longitude coordinates and, in some cases, measured phosphate concentrations ([PO 4]) were matched with calculated TP linear regression slopes and Y-intercepts in the global matrix with 1° resolution using MSExcel Lookup worksheet functions to calculate TP-estimated [PO 4]. The mean deviation of TP-estimated [PO 4] <3.0 μM from measured [PO 4] is 0.18±0.18 μM at Hawaii (HOT) and 0.04±0.08 μM at Bermuda (BATS) time series stations and 0.28±0.27 μM over all considered World Ocean Circulation Experiment (WOCE) stations representing the different ocean basins. In general, TP-estimated [PO 4] represents measured [PO 4] more accurately in the southern hemisphere than in the northern hemisphere. For the World Ocean Atlas 2005 (WOA05), a TP-estimated [PO 4] map based on annual statistical mean SST approximates an annual statistical mean measured [PO 4] map in overall geographic pattern but less so in absolute concentration. ARGO 0–10 m temperature data and derived TP-estimated [PO 4] maps from all 2006 compare more favorably with the WOA05 annual statistical mean SST and measured [PO 4] maps. For winter 2006, ARGO 0–10 m temperature and derived TP-estimated [PO 4] maps favorably compare with MODIS mean SST and derived TP-estimated [PO 4] maps. ARGO 30–50 m and 75–100 m temperatures from winter 2006 and derived TP-estimated [PO 4] demonstrate that the ARGO dataset provides a subsurface nutrient complement to nutrient inferences based on MODIS SST. The TP-estimated [PO 4] approach is responsive to changing conditions since the independent variable, temperature, integrates ambient environmental variability as expressed in the vertical thermal structure at the time of the ARGO profile. TP-estimated [PO 4] can enhance the interpretation of developing ARGO-based ecosystem applications by providing more specific estimates of nutrient availability than temperature alone.

An efficient method of selecting ocean observing locations for capturing the leading modes and reconstructing the full field

We present a method of selecting a small number of observing locations for capturing the leading spatial modes of an ocean field and reconstructing the field, assuming sufficient historical data for extraction of the field's empirical orthogonal functions (EOFs). The selection metric contains two main requirements: (1) The EOFs should have large magnitudes at the selected locations. (2) The cross products between the EOFs should be small at the selected locations. We select observing points sequentially: adding points one by one, without modifying the already picked ones. Selection of each location is by a simple sorting based on the presented metric. We apply the method to the Pacific sea surface temperature (SST) field, using the Smith‐Reynolds SST data set and the Tropical Atmosphere Ocean Project (TAO) buoys' SST measurements. We demonstrate that using observations at a small number of selected locations, one can quite accurately estimate the leading modes' amplitudes. Consequently, the full field can be reconstructed by observations at the selected locations. To evaluate the performance gain realized by employing the presented algorithm, we also provide two comparisons. In the first, we confine selections to regions considered logistically accessible. In the second, we use locations of existing buoys. The reconstruction error using observing locations selected by our algorithm is significantly lower than that using the buoys' locations. The presented algorithm takes into account mismatch between the base data set and the observations.

Error characterization of infrared and microwave satellite sea surface temperature products for merging and analysis

The complementary nature of infrared and microwave sea surface temperature (SST) products provides opportunities for merging the data, but significant differences among the products must first be understood and characterized. This paper presents a method for specifying the uncertainty in existing infrared and microwave SST products in terms of available satellite‐derived parameters, explores which environmental and sensor parameters contribute most to the errors, and determines if the derived uncertainty estimates can enable significant reductions in the differences among the SST products. Collocations among the satellite retrievals and SST measurements from buoys are used to derive the error estimates. Simple multidimensional lookup tables expressing the expected bias and standard deviation of individual retrievals as functions of various combinations of parameters provide an effective characterization of the uncertainty suitable for operational applications. Bias adjustments derived from the satellite zenith angle, 11–12 μm brightness temperature difference, and SST for the infrared, and wind speed, water vapor content, and SST for the microwave products significantly reduce the variability of differences both between the satellite products and with buoy observations. Further improvements are possible through inclusion of additional independent corrections based on the climatological SST anomaly and aerosol optical depth. These corrections reduce the monthly rms difference between the products by as much as 42% and reduce differences with independent buoys by as much as 10%. The largest individual corrections are to the infrared data in regions of low SST, but the microwave corrections are more geographically distributed and affect more retrievals.

Operational ocean models in the Adriatic Sea: a skill assessment

Abstract. In the framework of the Mediterranean Forecasting System (MFS) project, the performance of regional numerical ocean forecasting systems is assessed by means of model-model and model-data comparison. Three different operational systems considered in this study are: the Adriatic REGional Model (AREG); the Adriatic Regional Ocean Modelling System (AdriaROMS) and the Mediterranean Forecasting System General Circulation Model (MFS-GCM). AREG and AdriaROMS are regional implementations (with some dedicated variations) of POM and ROMS, respectively, while MFS-GCM is an OPA based system. The assessment is done through standard scores. In situ and remote sensing data are used to evaluate the system performance. In particular, a set of CTD measurements collected in the whole western Adriatic during January 2006 and one year of satellite derived sea surface temperature measurements (SST) allow to asses a full three-dimensional picture of the operational forecasting systems quality during January 2006 and to draw some preliminary considerations on the temporal fluctuation of scores estimated on surface quantities between summer 2005 and summer 2006. The regional systems share a negative bias in simulated temperature and salinity. Nonetheless, they outperform the MFS-GCM in the shallowest locations. Results on amplitude and phase errors are improved in areas shallower than 50 m, while degraded in deeper locations, where major models deficiencies are related to vertical mixing overestimation. In a basin-wide overview, the two regional models show differences in the local displacement of errors. In addition, in locations where the regional models are mutually correlated, the aggregated mean squared error was found to be smaller, that is a useful outcome of having several operational systems in the same region.

Empirical relationship between sea surface temperature and water vapor: Improvement of the physical model with remote sensing derived data

We have improved the previous model quantifying the bulk relationship between two key geophysical parameters, sea surface temperature (SST) and water vapor (WV) based on 14-year accumulated datasets. This improvement is achieved by the modification of the physical model derived by Stephens in 1990 and Gaffen et al. in 1992. With this improved model, we estimated WV between 2002 and 2004 using historical SST measurements. The estimated WV was compared with those derived from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) observation and National Centers for Environmental Predictions (NCEP) reanalysis. Discrepancies of ‐1.16 mm and 3.19 mm with TMI- and NCEP-derived WV were obtained, respectively, suggesting a reliable retrieval of WV using the improved model. The improved model can potentially be used to calibrate and validate the WV measurements from other observations or model reanalyses, given that the accurate measurement of WV over a wide range of spatial and temporal scales has been a challenging task hitherto. Due to the limited time span of the current data, the temporal variation of WV in parts of the tropical oceans is not captured in this improved model, which we should study further with additional accumulation of SST and WV datasets in the future.

Seasonal and interannual variability of the characteristics of Scotia-Sea front based on the satellite measurements of sea-surface temperature

We determine the characteristic features of the space structure of the Scotia-Sea Front and study the variations of its characteristics on the seasonal and interannual scales. It is shown that, in the climatic seasonal cycle, the Scotia-Sea Front is intensified in the warm period of the year when the temperature contrast between the cold waters formed as a result of thawing of ice and warmer waters transported by the South Branch of the Antarctic Circumpolar Current becomes more pronounced. The maximum seasonal variations of the intensity of this front are observed in the region of minimum intraannual displacements of the boundary of drift ice. The interannual variations of the characteristics of the front are observed in the form anomalous variations of its intensity and latitudinal displacements. A significant relationship is established between the interannual anomalies of the characteristics of the front and the areas of warm tropical waters in the Pacific Ocean caused by the events of El Nino.

Accuracy and precision of archival tag data: a multiple‐tagging study conducted on a whale shark (Rhincodon typus) in the Indian Ocean

AbstractPop‐up satellite archival tags (PSATs) are now widely used to document the geographic and vertical movements of large pelagic fishes. These instruments record measurements of ambient light, depth and temperature at regular intervals and the light data are used to compute daily estimates of latitude and longitude. Several methods have been developed to improve those estimates, including the application of Kalman filter models and matching sea surface temperatures (SST) from tags with remotely sensed SSTs. Despite their widespread use, few studies have evaluated the accuracy of raw estimates of location from PSATs or quantified the improvements that may result from refinement techniques. To assess the accuracy of raw and refined estimates of locations from PSATs, we attached two PSATs and one Argos satellite‐linked transmitter (SAT tag) to one whale shark (Rhincodon typus) at Ningaloo Reef, Western Australia. The root mean square error (RMSE) in raw estimates of location provided by the PSATs was 5.16° latitude and 2.00° longitude. Estimates were more accurate after processing the data with a Kalman filter (RMSE = 2.97° latitude and 0.78° longitude) and most accurate after processing with a Kalman filter model that integrates SST measurements (RMSE = 1.84° latitude and 0.78° longitude). We also assessed the precision of the PSAT‐derived locations, and depth and temperature measurements by comparing the data from the two PSATs. Our findings support the use of archival tag data to reconstruct the large‐scale movements of marine animals and demonstrate the significant improvements that may result from two refinement techniques.

Comparison of In Situ and Satellite-Derived Sea Surface Temperatures in the Gulf of Carpentaria

Abstract During 30 days in May and June 2003, the R/V Southern Surveyor was operating in the Gulf of Carpentaria, northern Australia. Measurements of sea surface temperature (SST) were made with an accurate single-channel infrared radiometer as well as with the ship’s thermosalinograph. These ship-based measurements have been used to assess the quality of the SST derived from nine satellite-borne instruments. The satellite dataset compiled during this period also allows the intercomparison of satellite-derived SST fields in areas not covered by the ship’s track. An assessment of the SST quality from each satellite instrument is presented, and suggestions for blending ground and satellite measurements into a single product are made. These suggestions are directly applicable to the international Global Ocean Data Assimilation Experiment (GODAE) High Resolution SST Pilot Project (GHRSST-PP) that is currently developing an operational system to provide 6-hourly global fields of SST at a spatial resolution close to 10 km. The paper demonstrates how the Diagnostic Datasets (DDSs) and Matchup Database (MDB) of the GHRSST-PP can be used to monitor the quality of individual and blended SST datasets. Recommendations for future satellite missions that are critical to the long-term generation of accurate blended SST datasets are included.