Sea Surface Temperature Measurements Research Articles

Evaluation of new and net community production estimates by multiple ship-based and autonomous observations in the Northeast Pacific Ocean

New production (NP) and net community production (NCP) measurements are often used as estimates of carbon export potential from the mixed layer of the ocean, an important process in the regulation of global climate. Diverse methods can be used to measure NP and NCP, from research vessels, autonomous platforms, and remote sensing, each with its own set of benefits and uncertainties. The various methods are rarely applied simultaneously in a single location, limiting our ability for direct comparisons of the resulting measurements. In this study, we evaluated NP and NCP from thirteen independent datasets collected via in situ, in vitro, and satellite-based methods near Ocean Station Papa during the 2018 Northeast Pacific field campaign of the NASA project EXport Processes in the Ocean from RemoTe Sensing (EXPORTS). Altogether, the datasets indicate that carbon export potential was relatively low (median daily averages between −5.1 and 12.6 mmol C m−2 d−1), with most measurements indicating slight net autotrophy in the region. This result is consistent with NCP estimates based on satellite measurements of sea surface temperature and chlorophyll a. We explored possible causes of discrepancies among methods, including differences in assumptions about stoichiometry, vertical integration, total volume sampled, and the spatiotemporal extent considered. Results of a generalized additive mixed model indicate that the spatial variation across platforms can explain much of the difference among methods. Once spatial variation and temporal autocorrelation are considered, a variety of methods can provide consistent estimates of NP and NCP, leveraging the strengths of each approach.

Validation of Himawari-8 Sea Surface Temperature Retrievals Using Infrared SST Autonomous Radiometer Measurements

This study has evaluated five years (2016–2020) of Himawari-8 (H8) Sea Surface Temperature (SST) Level 2 Pre-processed (L2P) data produced by the Australian Bureau of Meteorology (Bureau) against shipborne radiometer SST measurements obtained from the Infrared SST Autonomous Radiometer (ISAR) onboard research vessel RV Investigator. Before being used, all data sets employed in this study have gone through careful quality control, and only the most trustworthy measurements are retained. With a large matchup database (31,871 collocations in total, including 16,418 during daytime and 15,453 during night-time), it is found that the Bureau H8 SST product is of good quality, with a mean bias ± standard deviation (SD) of −0.12 °C ± 0.47 °C for the daytime and −0.04 °C ± 0.37 °C for the night-time. The performance of the H8 data under different environmental conditions, determined by the observations obtained concurrently from RV Investigator, is examined. Daytime and night-time satellite data behave slightly differently. During the daytime, a cold bias can be seen under almost all environmental conditions, including for most values of wind speed, SST, and relative humidity. On the other hand, the performance of the night-time H8 SST product is consistently more stable under most meteorological conditions with the mean bias usually close to zero.

Evaluation of SST Data Products from Multi-Source Satellite Infrared Sensors in the Bohai-Yellow-East China Sea

The measurement of sea surface temperature (SST) is of utmost importance in the realm of oceanography. The increasing utilization of satellite data in SST research has highlighted the crucial need to compare and evaluate various satellite data sources. Using iQuam2 in situ SST data, this study aims to assess the accuracy of SST datasets obtained from three polar-orbiting satellites (AVHRR, Modis-Aqua, and Modis-Terra) and one geostationary satellite (Himawari-8) in the Bohai-Yellow-East China Sea (BYECS) throughout 2019. The results showed a strong correlation between satellite and in situ data, with R correlation coefficients exceeding 0.99. However, the accuracy of the satellite datasets exhibited some variability, with Himawari-8 showing the highest deviation error and MODIS-Aqua showing the least. Subsequently, the Modis-Aqua data were used as a benchmark to evaluate the SST data of the other three satellites over the previous six years (July 2015–June 2021). The results indicate that, in addition to intricate temporal variations, the deviations of the three satellites from Modis-Aqua also show significant spatial disparities due to the effect of seawater temperature. Compared to Modis-Aqua, the deviation of Himawari-8 generally displayed a negative trend in BYECS and showed pronounced seasonal variation. The deviation of AVHRR showed a negative trend across all regions except for a substantial positive value in the coastal region, with the time variation exhibiting intricate features. The SST values obtained from MODIS-Terra exhibited only marginal disparities from MODIS-Aqua, with positive values during the day and negative values at night. All three satellites showed significantly abnormal bias values after December 2020, indicating that the MODIS-Aqua-derived SST reference dataset may contain outliers beyond this period. In conclusion, the accuracy of the four satellite datasets varies across different regions and time periods. However, they could be effectively utilized and integrated with relevant fusion algorithms to synthesize high-precision datasets in the future.

Tensor-based flow reconstruction from optimally located sensor measurements

Reconstructing high-resolution flow fields from sparse measurements is a major challenge in fluid dynamics. Existing methods often vectorize the flow by stacking different spatial directions on top of each other, hence confounding the information encoded in different dimensions. Here, we introduce a tensor-based sensor placement and flow reconstruction method which retains and exploits the inherent multidimensionality of the flow. We derive estimates for the flow reconstruction error, storage requirements and computational cost of our method. We show, with examples, that our tensor-based method is significantly more accurate than similar vectorized methods. Furthermore, the variance of the error is smaller when using our tensor-based method. While the computational cost of our method is comparable to similar vectorized methods, it reduces the storage cost by several orders of magnitude. The reduced storage cost becomes even more pronounced as the dimension of the flow increases. We demonstrate the efficacy of our method on three examples: a chaotic Kolmogorov flow, in situ and satellite measurements of the global sea surface temperature and three-dimensional unsteady simulated flow around a marine research vessel.

Global High-Resolution Random Forest Regression Maps of Ocean Heat Content Anomalies Using In Situ and Satellite Data

Abstract The ocean, with its low albedo and vast thermal inertia, plays key roles in the climate system, including absorbing massive amounts of heat as atmospheric greenhouse gas concentrations rise. While the Argo array of profiling floats has vastly improved sampling of ocean temperature in the upper half of the global ocean volume since the mid-2000s, they are not sufficient in number to resolve eddy scales in the oceans. However, satellite sea surface temperature (SST) and sea surface height (SSH) measurements do resolve these scales. Here we use random forest regressions to map ocean heat content anomalies (OHCA) using in situ training data from Argo and other sources on a 7-day × 1/4° × 1/4° grid with latitude, longitude, time, SSH, and SST as predictors. The maps display substantial patterns on eddy scales, resolving variations of ocean currents and fronts. During the well-sampled Argo period, global integrals of these maps reduce noise relative to estimates based on objective mapping of in situ data alone by roughly a factor of 3 when compared to time series of CERES (satellite data) top-of-the-atmosphere energy flux measurements and improve correlations of anomalies with CERES on annual time scales. Prior to and early on in the Argo period, when in situ data were sparser, global integrals of these maps retain low variance, and do not relax back to a climatological mean, avoiding potential deficiencies of various methods for infilling data-sparse regions with objective maps by exploiting temporal and spatial patterns of OHCA and its correlations with SST and SSH. Significance Statement We use a simple machine learning technique to improve maps of subsurface ocean warming by exploiting the relationships between subsurface ocean temperature both sea surface temperature and sea level. Mapping ocean warming is important because it contributes to sea level rise through thermal expansion; impacts marine life through marine heatwaves and changes in mixing, oxygen, and carbon dioxide levels; increases energy available to tropical cyclones; and stores most of the energy building up in Earth’s climate system owing to the accumulation of anthropogenic greenhouse gases in the atmosphere. Our new estimates generally have lower noise energy and higher correlations than other products when compared with global energy fluxes at the top of the atmosphere measured by satellite.

Hydrodynamic and atmospheric drivers create distinct thermal environments within a coral reef atoll

Within coral reefs, different thermal environments can be found at locations separated by less than 100 s of meters and can generate fine-scale patterns of thermal stress and subsequent bleaching. In this study, we use an 11-month record of in situ temperature measurements, coupled with oceanographic and atmospheric data to examine the role of surface and advective heat fluxes in driving spatial patterns of temperature variability across several reef zones (i.e., fore-reef, reef flat, channel and lagoon) within an individual coral reef atoll. We show that advection of heat (driven by a combination of wave and tidal flows) was dominant across all sites and surface heating was more important across shallow areas or areas of low net exchange (i.e., reef flat and lagoon zones). Tidal flows were important in driving short term variability in the transport of heat across the atoll, but their contribution to the net transport of heat (cooling vs heating) was less significant over the longer timescales (days to weeks) that are typically used to assess thermal stress experienced by coral reef communities (e.g., Degree Heating Weeks). Conversely, although the wave-driven advection of heat contributed minimally to reef temperature changes over short timescales, the net transport of heat over daily to weekly timescales had a significant influence on persistent temperature anomalies. By parameterising the mechanisms driving temperature variability across the reef flat and lagoon zones, we demonstrate how satellite measurements of sea surface temperatures can be corrected to provide robust temperature estimates at the reef scale.

Global and Regional Discrepancies between Early-Twentieth-Century Coastal Air and Sea Surface Temperature Detected by a Coupled Energy-Balance Analysis

Abstract A major uncertainty in reconstructing historical sea surface temperature (SST) before the 1990s involves correcting for systematic offsets associated with bucket and engine-room intake temperature measurements. A recent study used a linear scaling of coastal station-based air temperatures (SATs) to infer nearby SSTs, but the physics in the coupling between SATs and SSTs generally gives rise to more complex regional air–sea temperature differences. In this study, an energy-balance model (EBM) of air–sea thermal coupling is adapted for predicting near-coast SSTs from coastal SATs. The model is shown to be more skillful than linear-scaling approaches through cross-validation analyses using instrumental records after the 1960s and CMIP6 simulations between 1880 and 2020. Improved skill primarily comes from capturing features reflecting air–sea heat fluxes dominating temperature variability at high latitudes, including damping high-frequency wintertime SAT variability and reproducing the phase lag between SSTs and SATs. Inferred near-coast SSTs allow for intercalibrating coastal SAT and SST measurements at a variety of spatial scales. The 1900–40 mean offset between the latest SST estimates available from the Met Office (HadSST4) and SAT-inferred SSTs range between −1.6°C (95% confidence interval: [−1.7°, −1.4°C]) and 1.2°C ([0.8°, 1.6°C]) across 10° × 10° grids. When further averaged along the global coastline, HadSST4 is significantly colder than SAT-inferred SSTs by 0.20°C ([0.07°, 0.35°C]) over 1900–40. These results indicate that historical SATs and SSTs involve substantial inconsistencies at both regional and global scales. Major outstanding questions involve the distribution of errors between our intercalibration model and instrumental records of SAT and SST as well as the degree to which coastal intercalibrations are informative of global trends. Significance Statement To evaluate the consistency of instrumental surface temperature estimates before the 1990s, we develop a coupled energy-balance model to intercalibrate measurements of sea surface temperature (SST) and station-based air temperature (SAT) near global coasts. Our model captures geographically varying physical regimes of air–sea coupling and outperforms existing methods in inferring regional SSTs from SAT measurements. When applied to historical temperature records, the model indicates significant discrepancies between inferred and observed SSTs at both global and regional scales before the 1960s. Our findings suggest remaining data issues in historical temperature archives and opportunities for further improvements.

Application of Unmanned Aerial Vehicle–Based Infrared Images in Determining Characteristics of Sea Surface Temperature Distribution

This study investigated the temperature field of a body of water by using rotary-wing unmanned aerial vehicles (DJI Mavic 2 Enterprise Dual) comprising visible light and infrared cameras to determine sea temperature distribution. With a flight height of 150 m, image overlap of 80%, and image resolution of 4.75 cm/pixel, the proposed method was more effective than the conventional portable conductivity–temperature–depth device in rapidly measuring sea surface temperature and determining sea temperature distribution. The discharged heated water of the Hoping Power Plant traveled 100–330 m from the wastewater outfall and then gradually diffused in the range of 100–490 m before reaching a similar temperature to the background sea temperature. The diffusion of the thermal plume was mainly affected by regional marine meteorological conditions

Satellite-Based Ocean Color and Thermal Signatures Defining Habitat Hotspots and the Movement Pattern for Commercial Skipjack Tuna in Indonesia Fisheries Management Area 713, Western Tropical Pacific

Understanding the mechanisms that determine the critical habitat of commercial species is one of the significant challenges in marine science, particularly for species that inhabit the vast ocean worldwide. Previous investigations primarily focused on determining skipjack habitats without considering the feasible size for sustainable fisheries. To define habitat hotspots and movement patterns for decently sized skipjack tuna (≥50 cm) in Indonesia Fisheries Management Area (IFMA) 713, Indonesia, we examined the remote sensing of synoptic sea surface temperature (SST) and chlorophyll-a concentration (Chl-a) measurements with catch data from 2007 to 2016. A new skipjack tuna habitat model was developed based on the link between the key satellite-based environmental data and the best tuna fishery performance using a combination of generalized additive models (GAMs) and kernel density estimates. The findings reveal that feasible skipjack catch sizes were found in approximately 27% of total fishing grounds and were significantly captured in areas with a Chl-a of 0.15–0.28 mg m−3 and an SST of 29.5–31.0 °C, corresponding with an elevated skipjack habitat index (SHI). The habitat hotspots for the commercial skipjack were particularly produced by favorable Chl-a and SST, in association with Chl-a front and anticyclonic and cyclonic eddies, especially in October, which coincided with the highest skipjack catch per unit effort (CPUE). Skipjack distributions were mostly found within 10 km of favorable feeding habitats. They used the hotspot area as an indicator of their dynamics and movement pattern in the environment. The observed CPUEs cross-validated the predicted SHI values, suggesting that the model provided a reliable proxy for defining the potential habitats and the spatial movement of mature skipjack schools. Our findings have global significance for locating ecological hotspots, monitoring sustainable skipjack fisheries, and tracking skipjack migration, especially within the western tropical Pacific.

Determination of discrete sampling locations minimizing both the number of samples and the maximum interpolation error: Application to measurements of carbonate chemistry in surface ocean

Over the past three decades, a variety of programs have conducted extensive measurements of ocean properties at fixed stations throughout the water column, as well as in the surface ocean via oceanographic ships and ships of opportunity. Ships of opportunity were particularly used to determine the air-sea CO2 fluxes from automated measurements of sea-surface temperature, salinity, and CO2 fugacity. These underway measurements, often recorded at a frequency of every minute, generate large data files that need to be quality controlled, stored and analyzed. For practical use these data are often binned by 1° latitude x 1° longitude. Unfortunately, by doing so, there is a consequential loss of accuracy for these data sets.Here, using the original 2010 underway data sets of sea-surface temperature, sea-surface salinity, total alkalinity and total inorganic carbon, along the cruise track from Hobart (Tasmania) to Dumont D'Urville (Antarctica), we show what would had been a more appropriate sampling strategy for each of these properties, maintaining their full measurement accuracy, while improving their interpolation accuracy. Furthermore, this analysis illustrates a general methodology for objectively determining, under suitable conditions, the appropriate locations for each property measurement according to a required accuracy. These results should greatly facilitate future cruise preparation and reduce the cost of measurements, while improving their scientific value.

Offshore wind energy forecasting sensitivity to sea surface temperature input in the Mid-Atlantic

Abstract. As offshore wind farm development expands, accurate wind resource forecasting over the ocean is needed. One important yet relatively unexplored aspect of offshore wind resource assessment is the role of sea surface temperature (SST). Models are generally forced with reanalysis data sets, which employ daily SST products. Compared with observations, significant variations in SSTs that occur on finer timescales are often not captured. Consequently, shorter-lived events such as sea breezes and low-level jets (among others), which are influenced by SSTs, may not be correctly represented in model results. The use of hourly SST products may improve the forecasting of these events. In this study, we examine the sensitivity of model output from the Weather Research and Forecasting model (WRF) 4.2.1 to different SST products. We first evaluate three different data sets: the Multiscale Ultrahigh Resolution (MUR25) SST analysis, a daily, 0.25∘ × 0.25∘ resolution product; the Operational Sea Surface Temperature and Ice Analysis (OSTIA), a daily, 0.054∘ × 0.054∘ resolution product; and SSTs from the Geostationary Operational Environmental Satellite 16 (GOES-16), an hourly, 0.02∘ × 0.02∘ resolution product. GOES-16 is not processed at the same level as OSTIA and MUR25; therefore, the product requires gap-filling using an interpolation method to create a complete map with no missing data points. OSTIA and GOES-16 SSTs validate markedly better against buoy observations than MUR25, so these two products are selected for use with model simulations, while MUR25 is at this point removed from consideration. We run the model for June and July of 2020 and find that for this time period, in the Mid-Atlantic, although OSTIA SSTs overall validate better against in situ observations taken via a buoy array in the area, the two products result in comparable hub-height (140 m) wind characterization performance on monthly timescales. Additionally, during hours-long flagged events (< 30 h each) that show statistically significant wind speed deviations between the two simulations, both simulations once again demonstrate similar validation performance (differences in bias, earth mover's distance, correlation, and root mean square error on the order of 10−1 or less), with GOES-16 winds validating nominally better than OSTIA winds. With a more refined GOES-16 product, which has been not only gap-filled but also assimilated with in situ SST measurements in the region, it is likely that hub-height winds characterized by GOES-16-informed simulations would definitively validate better than those informed by OSTIA SSTs.

NOAA's operational satellite ocean heat content products

ABSTRACT NOAA generates a suite of Ocean Heat Content (OHC) products for the North Atlantic and the North and South Pacific basins on a daily basis. Knowledge of the upper Ocean Heat Content is a critical aid in assessing the ocean's impact on Tropical Cyclones (TCs) and weather events. In-situ and satellite measurements of Sea Surface Temperature (SST) and Sea Surface Height Anomaly (SSHA) are used to generate the OHC product suite. The evaluated suite includes the 20°C (D20) and 26°C (D26) isotherm depths, the mixed layer depth (MLD) and mapping errors. Two cases are presented within the context of situational awareness showing the underling oceanic variability during the lifecycles of TC's Irma and Dorian.

Assessing the ability of satellite sea surface temperature analyses to resolve spatial variability – The northwest tropical Atlantic ATOMIC region

Direct measurements of the sea surface temperature (SST) from multiple platforms deployed during the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) field campaign are used to evaluate the ability of satellite SST products to accurately represent spatial gradients within the region. The results further provide insight into the suitability of different satellite SST products for application to ATOMIC and other northwest tropical Atlantic scientific analyses. In situ SST measurements from the Research Vessel Ronald H. Brown, Saildrones, and Surface Velocity Program – Salinity (SVPS) drifters were collocated with five daily Level 4 satellite SST analyses and two Level 3 single-sensor satellite SST products during the period from January 1 to February 24, 2020. The absolute accuracy of the satellite products was generally good with random errors on the order of 0.2 K or less, though most exhibited a small cool bias of ∼0.1 K. The biases were not representative of a consistent offset, but rather larger cool biases of a subset of observations influenced the overall statistics. Sub-grid SST variability in the ATOMIC region was small (< 0.03 K) in relationship both to other regions and to uncertainties in the satellite products. Despite their absolute accuracy, the L4 analyses accurately reproduced the spatial SST variability within the ATOMIC domain only on scales of 0.5–1° or more. At the scale of their respective grid resolutions, correlations between satellite-derived and Saildrone-inferred grid-scale SST gradients were low, as the satellite–Saildrone SST differences dominated over small cell-to-cell variability in the region. One reason was the coarser feature resolution of the analyses compared to their grid resolution. Correlations increased with the distance over which the SST values were averaged. Simulations demonstrated that a satellite product precision near 0.05 K was needed to successfully reproduce the observed SST spatial variability at the grid cell level. Comparison with Saildrone observations from the Arctic showed sub-grid SST variability six-times larger and a relaxed satellite accuracy requirement of near 0.5 K in that region, but the satellite product accuracy was also degraded, again hindering the accurate sampling of SST gradients at the scale of the L4 analyses.

Sea Surface Temperature Trends in the Coastal Zone of Southern England

Kassem, H.; Amos, C.L., and Thompson, C.E.L., 2023. Sea surface temperature trends in the coastal zone of southern England. Journal of Coastal Research, 39(1), 18–31. Charlotte (North Carolina), ISSN 0749-0208. Sea surface temperature (SST) trends along the south coast of England (northern English Channel) were examined based on data from systematic buoy measurements deployed by the National Network of Regional Coastal Monitoring Programmes of England (NNRCMP) since 2003. These data were supplemented with: (1) long-term, coastal SST measurements by the Centre for Environment, Fisheries and Aquaculture Science (CEFAS); (2) global data sets compiled by the Hadley Centre since 1900, and (3) satellite-derived observations from Moderate Resolution Imaging Spectroradiometer (MODIS) (Aqua) since 2002. These data sets were used to evaluate de-seasoned nearshore trends in SST along the south coast of England and examine links to regional ocean-atmosphere teleconnections. The analyses of long-term, CEFAS data support the proposal that prior to the mid-1980s there were no de-seasoned trends in SST and conditions from year to year were relatively stable. Subsequently, interannual fluctuations appear to have increased, associated with a period of warming between 1985 and 2003 (0.28 °C/decade). Post 2003, interannual fluctuations in SST monitored by the NNRCMP buoys continued, and the warming trend appears to be greater (0.42 °C/decade). This trend in SST is greatest in the nearshore and decreases with distance offshore. The warming in SST also varied greatly from month to month. The greatest warming took place from December to March, whilst the least heating (and sometimes cooling) occurred between September and November. Analysis of Hadley (HadSST1.1) and MODIS data sets substantiated these trends. The greatest warming (post 2003) was found west of Portland Bill (up to 0.76 °C/decade) and decreased towards the Strait of Dover. Despite this west-to-east trend, all 12 NNRCMP stations between Penzance and Folkestone showed remarkably similar results, suggesting regional and global sources of heat rather than local sources. This is corroborated through wavelet coherence analysis linking SST anomalies to regional/global ocean-atmosphere teleconnection indices at seasonal scales.

Dose rate assessment of 137Cs to mussels and pelagic fish from the combined use of field measurements, satellite data and the ERICA Assessment Tool

Cesium-137 (137Cs) is the most important indicator of radioactive pollution in the marine environment due to its half-life (Tph: 30.2 years), its high fission yield, its solubility (70% in ionic form) and its bioavailability (similar to potassium). Soluble radionuclides, like 137Cs, in the seawater are associated with physicogeochemical and biological parameters of the marine environment (e.g. temperature, water density, biota exchange processes, water mass translocation etc.). Considering this characteristic, we investigate the potential relation between 137Cs activity concentration and sea surface temperature (SST). The parameter of SST is selected, as the element of cesium in the seawater is conservative and its horizontal and vertical dispersion depends on the water mass translocation and water currents. Water mass translocation and water currents are processes that are both governed by the SST. SST also influences the uptake of 137Cs in some marine organisms as it makes it more bioavailable and affects the biological retention time and the elimination rate. The study area is the Gulf of Corinth (Greece). Cs-137 in the Gulf of Corinth originates from water runnoff from the land (Chernobyl fallout from 1986) and a small influence exists from the Ionian and Aegean Sea water currents. A total of 17 measurements spanning 2004-2005, of 137Cs activity concentrations were retrieved from the Environmental Radioactivity Laboratory (ERL) database of NCSR “D”. Furthermore, SST measurements issued from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). Databases of 137Cs activity concentrations and SST are used for regression analysis and definition of a linear model. The estimated 137Cs activity concentrations obtained by the model are then compared with the newest measured values obtained by seawater samples from September and November 2018 (a total of 8 seawater samples). Estimated concentrations present a relative difference of about 9% to the measured values. In order to conduct the risk assessment analysis in the studied area, the dose rates are calculated for marine organisms. The selected marine organisms are mussels and pelagic fish that are abundant in the area and have significant commercial value, with mussels also being an important bioindicator of marine pollution. The total dose rates in these organisms (resulting by both the internal and external exposure) vary from 3.30 × 101 to 5.40 × 101 μGy/year for the mussels and from 2.97 × 10-1 to 4.86 × 10-1 μGy/year for pelagic fish, which are much lower that the intervention levels, indicating low impact due to the 137Cs exposure.

Observing system simulation experiments reveal that subsurface temperature observations improve estimates of circulation and heat content in a dynamic western boundary current

Abstract. Western boundary currents (WBCs) form the narrow, fast-flowing poleward return flows of the great subtropical ocean gyres and are sources of rapidly varying mesoscale eddies. Accurate simulation of the vertical structure, separation latitude, and ocean heat content of WBCs is important for understanding the poleward transport of heat in the global ocean. However, state estimation and forecasting in WBC regions, such as the East Australian Current (EAC), the WBC of the South Pacific subtropical gyre, is challenging due to their dynamic nature and lack of observations at depth. Here we use observing system simulation experiments to show that subsurface temperature observations in a high eddy kinetic energy region yield large improvement in representation of key EAC circulation features, both downstream and ∼ 600 km upstream of the observing location. These subsurface temperature observations (in concert with sea surface temperature and height measurements) are also critical for correctly representing ocean heat content along the length of the EAC. Furthermore, we find that a more poleward separation latitude leads to an EAC and eddy field that is represented with far reduced error, compared to when the EAC separates closer to the Equator. Our results demonstrate the importance of subsurface observations for accurate state estimation of the EAC and ocean heat content that can lead to marine heatwaves. These results provide useful suggestions for observing system design under different oceanographic regimes, for example, adaptive sampling to target high energy states with more observations and low energy states with fewer observations.

In-Situ Sea Surface Temperature (SST) Mapping Of Barangay Maac Marine Protected Area (MPA), Sogod, Southern Leyte

This paper intends to generate a geo-referenced heat map based on Sea Surface Temperature (SST) readings at Maac Marine Protected Area. Significance level on variability and difference of the average temperature level and the upper limit of the normal value were also determined using a One Sample t-test. The study site is in the barangay of Maac, located in the Municpality of Sogod, Province of Southern Leyte and is approximately 7 kilometers northeast from the municipality’s center. It has a total area of 11.67 hectares. This study uses an experimental design. SST measurements were taken using a pre-calibrated hull temperature sensor connected to a fish finder. Out of the total 128 data points that were measured with temperature measurement, only 49 contained temperature readings. Statistical tests revealed that the average temperature level is significantly lesser than the upper limit of the normal value. Variability test showed that the average temperature level is significantly greater than the lowest temperature reading. The generated heat map provided a graphic representation of relatively high temperature readings within and outside the MPA.

Identifying Oceanic Responses with Validated Satellite Observations after the Passage of Typhoons in the Northern South China Sea

Tropical cyclone-induced upwelling has an important influence on ocean temperature and chlorophyll-a (Chl-a) concentrations, which are modified by the existence of mesoscale eddies. This paper investigates the regional dynamics and associated variability in temperature and Chl-a during the passage of three typhoons (Kammuri, Nuri, and Hagupit) with similar tracks in the northern South China Sea (SCS) during 2008 using remote sensing and in situ observations. The measurements of wind and sea surface temperature obtained by a buoy and satellite were found to be similar, and both showed that typhoons have prominent impacts on the ocean’s upper layer. Sea surface cooling is first identified during the passage of each typhoon, particularly on the right side of typhoon tracks. Increased Chl-a concentrations were observed in the surrounding areas after the passage of typhoons Nuri and Hagupit, with large offshore blooms (Chl-a increases of 0.27–0.33 mg m−3) identified along the tracks of Nuri and Hagupit 3 to 4 days after their passage. Such blooms are highly dependent on the cooling associated with typhoon-induced mixing and upwelling. The pre-existing eddies modified the surface variations, and a perfect match was identified between the polarities of the eddies and the ocean surface changes. An anomalously high offshore Chl-a enhancement entrained by a cyclonic eddy occurred along the track of Nuri 4 days after its passage; in this instance, typhoon-induced upwelling was reinforced by the cyclonic eddy. In comparison, typhoon-induced upwelling is inhibited by anticyclonic eddies, resulting in much less prominent changes. The combination of typhoon winds and eddies can modify the productivity of marine phytoplankton, and a comprehensive understanding of typhoon-induced dynamics will aid in understanding ecosystem responses to typhoons.

Spatial and temporal variability of the physical, carbonate and CO2 properties in the Southern Ocean surface waters during austral summer (2005-2019)

In situ measurements of sea surface temperature (SST), salinity (SSS), Total Alkalinity (AT) and Total Carbon (CT) were obtained during austral summer (mid-February to mid-March) from 2005 to 2019 in the Southern Ocean (SO), along a transect between Hobart, Tasmania and Dumont d’Urville French Antarctic Station. The studied transect is divided in four regions from North to South: the Subtropical Zone (STZ), the Subantarctic Region (SAR), the Antarctic Region (AAR) and the Coastal Antarctic Zone (CAZ). Latitudinal distribution of measured SST, SSS, AT, CT as well as calculated pH, CO2 parameters (seawater fugacity of CO2 (fCO2sw), difference between seawater and atmospheric fCO2 (ΔfCO2), CO2 flux (FCO2)) and satellite-derived Chlorophyll a (Chl-a) are discussed. We show that the variability of physical and carbonate parameters in the STZ and north of the SAR are related to the mesoscale activity. In the CAZ, the freshwater inputs from sea-ice melting strongly impact the variability of all parameters. The comparison between physical and carbonate parameters highlights that AT and CT are directly related to the latitudinal variability of SST and SSS. Study of the CO2 parameters shows that the transect is a sink of CO2 during February and March, with a mean FCO2 of −4.0 ± 2.8 mmol m−2 d−1. The most negative values of FCO2 are found in the STZ and SAR north of 50°S and in the AAR south of 62°S, where biological activity is high. New simple empirical relationships are developed for AT from SST and SSS and for CT using SST, SSS and atmospheric fCO2 (fCO2atm) for the austral summer in the studied area. Using high resolution SSS and SST from the SURVOSTRAL program, trends of AT and CT are determined in the SAR and the AAR from 2005 to 2019. SST, SSS and AT increase over this period in the SAR, which might be explained by the southward migration of the Subtropical Front. In the AAR, no clear trend is detected. CT increases by 1.0 ± 0.2 and 0.8 ± 0.3 μmol kg−1 yr−1 in the SAR and AAR respectively. The trend in the AAR is attributed to the increase in anthropogenic CO2 emissions in the atmosphere while, in the SAR, hydrographic changes also contribute to the increase. Using the coefficient associated with fCO2atm in the equation of CT, we estimate the impact of atmospheric CO2 increase on CT at 1.18 ± 0.14 μmol kg−1 yr−1 and 1.07 ± 0.13 μmol kg−1 yr−1 in the SAR and AAR respectively. Decreases in pH are observed in both regions (−0.0018 ± 0.0001 and −0.0026 ± 0.0003 yr−1 in the SAR and AAR respectively), indicating the sensitivity of surface waters in the area towards the development of ocean acidification processes under rising anthropogenic emissions.

Measurement of SST and SSS Using Frequencies in the Range 0.3–2.0 GHz

AbstractWide bandwidth radiometer systems that make measurements at multiple frequencies in the range from 300 MHz to 2 GHz have been proposed to address parameters important for understanding issues in the cryosphere associated with climate change such as ice sheet thickness and temperature. It is also possible with such a system to retrieve sea surface salinity (SSS), which is important for understanding the impact of climate change on ocean circulation at high latitude. In contemporary sensors for retrieving SSS, such as on Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP), sea surface temperature (SST), another parameter important for understanding ocean circulation and necessary in the retrieval of salinity, is treated as an ancillary parameter obtained from an independent source. However, both SSS and SST have peaks in sensitivity below 1 GHz; and it has been shown that measurements at multiple frequencies in this portion of the spectrum can take advantage of this peak in sensitivity to improve the accuracy of the retrieval of SSS. In this manuscript, it will be shown that there is also the potential to retrieve SST and, in cold water, the possibility for improved accuracy over existing retrievals.