Satellite Sea Surface Temperature Measurements Research Articles

Impacts of the Assimilation of Satellite Sea Surface Temperature Data on Volume and Heat Budget Estimates for the North Sea

AbstractMechanisms controlling the heat budget of the North Sea are investigated based on a combination of satellite sea surface temperature measurements and numerical model simulations. Lateral heat fluxes across the shelf edge and into the Baltic Sea as well as vertical ocean‐atmosphere heat exchange are considered. A 3‐D variational (3DVAR) data assimilation (DA) scheme is applied, which contains assumed model error correlations that depend on the mixed layer depth derived from a coupled circulation/ocean wave model. The analysis balances pressure gradients introduced by temperature modifications. Significant hydrodynamic model response to DA was found, which should be considered in the heat budget estimations. The observed change of the current velocity field decreases the lateral advective volume/heat exchanges between the North Sea and the Atlantic, yielding an increased heat flux from the Atlantic into the North Sea and more heat flux from the sea to the atmosphere. The largest DA impact on volume/heat transport is in the Norwegian Channel, where the dominant process is Eulerian transport, followed by tidal pumping and wind pumping. Further analysis reveals an acceleration of the along‐shelf current at the northern edge of the North Sea, a decrease in the horizontal pressure gradient from the Atlantic to the North Sea, and a reduction of the Eulerian transport of volume/heat outward the North Sea. Furthermore, the coupling between the circulation model and the wave model has significant impacts on lateral heat advection in the DA run, which is due to the wave impact on the mixed layer depth.

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

The 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.

A hybrid ensemble adjustment Kalman filter based high‐resolution data assimilation system for the Red Sea: Implementation and evaluation

AbstractA new Hybrid ensemble data assimilation system is implemented with a Massachusetts Institute of Technology general circulation model (MITgcm) of the Red Sea. The system is based on the Data Assimilation Research Testbed (DART) and combines a time‐varying ensemble generated by the Ensemble Adjustment Kalman Filter (EAKF) with a pre‐selected quasi‐static (monthly varying) ensemble as used in an Ensemble Optimal Interpolation (EnOI) scheme. The goal is to develop an efficient system that enhances the state estimate and model forecasting skill in the Red Sea with reduced computational load compared to the EAKF. Observations of satellite sea‐surface temperature (SST), altimeter sea‐surface height (SSH), and in situ temperature and salinity profiles are assimilated to evaluate the new system. The performance of the Hybrid scheme (hereafter Hybrid‐EAKF) is assessed with respect to the EnOI and the EAKF results. The comparisons are based on the daily averaged forecasts against satellite SST and SSH measurements and independent in situ temperature and salinity profiles. Hybrid‐EAKF yields significant improvements in terms of ocean state estimates compared to both EnOI and EAKF, in particular mitigating for dynamical imbalances that affect EnOI. Hybrid‐EAKF improves the estimation of SST and SSH root‐mean‐square differences by up to 20% compared to EAKF. High‐resolution mesoscale eddy features, which dominate the Red Sea circulation, are further better represented in Hybrid‐EAKF. Important reduction, by about 75%, in computational cost is also achieved with the Hybrid‐EAKF system compared to the EAKF. These significant improvements were obtained with the Hybrid‐EAKF after accounting for uncertainties in the atmospheric forcing and internal model physics in the time‐varying ensemble.

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

The coastal ocean is one of the most important environments on our planet, home to some of the most bio-diverse and productive ecosystems and providing key input to the livelihood of the majority of human society. It is also a highly dynamic and sensitive environment, particularly susceptible to damage from anthropogenic influences such as pollution and over-exploitation as well as the effects of climate change. These have the added potential to exacerbate other anthropogenic effects and the recent change in sea temperature can be considered as the most pervasive and severe cause of impact in coastal ecosystems worldwide. In addition to open ocean measurements, satellite observations of sea surface temperature (SST) have the potential to provide accurate synoptic coverage of this essential climate variable for the near-shore coastal ocean. However, this potential has not been fully realized, mainly because of a lack of reliable in situ validation data, and the contamination of near-shore measurements by the land. The underwater biotechnological park of Crete (UBPC) has been taking near surface temperature readings autonomously since 2014. Therefore, this study investigated the potential for this infrastructure to be used to validate SST measurements of the near-shore coastal ocean. A comparison between in situ data and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua and Terra SST data is presented for a four year (2014–2018) in situ time series recorded from the UBPC. For matchups between in situ and satellite SST data, only nighttime in situ extrapolated to the sea surface (SSTskin) data within ±1 h from the satellite’s overpass are selected and averaged. A close correlation between the in situ data and the MODIS SST was found (squared Pearson correlation coefficient-r2 > 0.9689, mean absolute error-Δ < 0.51 both for Aqua and Terra products). Moreover, close correlation was found between the satellite data and their adjacent satellite pixel’s data further from the shore (r2 > 0.9945, Δ < 0.23 for both Aqua and Terra products, daytime and nighttime satellite SST). However, there was also a consistent positive systematic difference in the satellite against satellite mean biases indicating a thermal adjacency effect from the land (e.g., mean bias between daytime Aqua satellite SST from the UBPC cell minus the respective adjacent cell’s data is δ = 0.02). Nevertheless, if improvements are made in the in situ sensors and their calibration and uncertainty evaluation, these initial results indicate that near-shore autonomous coastal underwater temperature arrays, such as the one at UBPC, could in the future provide valuable in situ data for the validation of satellite coastal SST measurements.

Submesoscale Impacts on Mesoscale Agulhas Dynamics

AbstractMesoscale dynamics of the Agulhas Current system determine the exchange between the Indian and Atlantic oceans, thereby influencing the global overturning circulation. Using a series of ocean model experiments compared to observations, we show that the representation of mesoscale eddies in the Agulhas ring path improves with increasing resolution of submesoscale flows. Simulated submesoscale dynamics are validated with time‐mean horizontal‐wavenumber spectra from satellite sea surface temperature measurements and mesoscale dynamics with spectra from sea surface height. While the Agulhas ring path in a nonsubmesoscale‐resolving (1/20)° configuration is associated with too less power spectral densities on all scales and too steep spectral slopes, the representation of the mesoscale dynamics improves when the diffusion and the dissipation of the model are reduced and some small‐scale features are resolved. Realistic power spectral densities over all scales are achieved when additionally the horizontal resolution is increased to (1/60)° and a larger portion of the submesoscale spectrum is resolved. Results of an eddy detection algorithm applied to the model outputs as well as to a gridded sea surface height satellite product show that in particular strong cyclones are much better represented when submesoscale flows are resolved by the model. The validation of the submesoscale dynamics with sea surface temperature spectra provides guidance for the choice of advection schemes and explicit diffusion and dissipation as well as for further subgrid‐scale parameterizations. For the Agulhas ring path, the use of upstream biased advection schemes without explicit diffusion and dissipation is found to be associated with realistically simulated submesoscales.

Evaluating the influences of temperature, primary production, and evolutionary history on bivalve growth rates

AbstractOrganismal metabolic rates reflect the interaction of environmental and physiological factors. Thus, calcifying organisms that record growth history can provide insight into both the ancient environments in which they lived and their own physiology and life history. However, interpreting them requires understanding which environmental factors have the greatest influence on growth rate and the extent to which evolutionary history constrains growth rates across lineages. We integrated satellite measurements of sea-surface temperature and chlorophyll-a concentration with a database of growth coefficients, body sizes, and life spans for 692 populations of living marine bivalves in 195 species, set within the context of a new maximum-likelihood phylogeny of bivalves. We find that environmental predictors overall explain only a small proportion of variation in growth coefficient across all species; temperature is a better predictor of growth coefficient than food supply, and growth coefficient is somewhat more variable at higher summer temperatures. Growth coefficients exhibit moderate phylogenetic signal, and taxonomic membership is a stronger predictor of growth coefficient than any environmental predictor, but phylogenetic inertia cannot fully explain the disjunction between our findings and the extensive body of work demonstrating strong environmental control on growth rates within taxa. Accounting for evolutionary history is critical when considering shells as historical archives. The weak relationship between variation in food supply and variation in growth coefficient in our data set is inconsistent with the hypothesis that the increase in mean body size through the Phanerozoic was driven by increasing productivity enabling faster growth rates.

The frontal system at the boundary of the East China Sea: Its variability and response to large-scale atmospheric forcing

High-resolution satellite sea surface temperature measurements (PATHFINDER dataset) indicate that the fronts at the boundary of the East China Sea (Taiwan front, Kuroshio frontal zone, and South Korean coastal front) appear as a unified dominating frontal structure when climatological averaging is applied. This structure is about 1200 km in length, spreads over the continental shelf from Taiwan to the Tsushima Islands, and separates productive seawaters from the oligotrophic oceanic waters. The Kuroshio frontal zone, incorporated into this structure, reveals interannual variability with periods consistent with El Nino–Southern Oscillation (4–5 years).

Impact of warming events on reef‐scale temperature variability as captured in two Little Cayman coral Sr/Ca records

AbstractThe rising temperature of the world's oceans is affecting coral reef ecosystems by increasing the frequency and severity of bleaching and mortality events. The susceptibility of corals to temperature stress varies on local and regional scales. Insights into potential controlling parameters are hampered by a lack of long term in situ data in most coral reef environments and sea surface temperature (SST) products often do not resolve reef‐scale variations. Here we use 42 years (1970–2012) of coral Sr/Ca data to reconstruct seasonal‐ to decadal‐scale SST variations in two adjacent but distinct reef environments at Little Cayman, Cayman Islands. Our results indicate that two massive Diploria strigosa corals growing in the lagoon and in the fore reef responded differently to past warming events. Coral Sr/Ca data from the shallow lagoon successfully record high summer temperatures confirmed by in situ observations (>33°C). Surprisingly, coral Sr/Ca from the deeper fore reef is strongly affected by thermal stress events, although seasonal temperature extremes and mean SSTs at this site are reduced compared to the lagoon. The shallow lagoon coral showed decadal variations in Sr/Ca, supposedly related to the modulation of lagoonal temperature through varying tidal water exchange, influenced by the 18.6 year lunar nodal cycle. Our results show that reef‐scale SST variability can be much larger than suggested by satellite SST measurements. Thus, using coral SST proxy records from different reef zones combined with in situ observations will improve conservation programs that are developed to monitor and predict potential thermal stress on coral reefs.

A comparative assessment of satellite-derived Adriatic Sea surface temperature

In this article, five Advanced Very High Resolution Radiometer (AVHRR) and four Moderate Resolution Imaging Spectrometer (MODIS)-based Adriatic-focused satellite sea surface temperature (SST) products are analysed and compared with two sets of in situ SST measurements: a drifter-based dataset collected in 2003, and a platform-based dataset gathered in 2004; an additional set was used to validate the new SST coefficients. Analysis of satellite minus in situ SST residuals shows similar results for both in situ datasets, with the differences being within 0.2 K. All daytime SST biases exhibited positive values (less than 0.5 K). Night-time biases for short-wave infrared (IR) algorithms exhibited near zero and small negative values with an exceptionally low standard deviation (about 0.3 K) regardless of the sensor used. Analysis of filtered residual time-series allowed direct comparison between different SST products. The seasonal change in the daytime biases was found to covary with similar changes in atmospheric water vapour and the Adriatic specific wind regime.

The impact of measurement uncertainty and spatial variability on the accuracy of skin and subsurface regression-based sea surface temperature algorithms

An ongoing limitation of common regression-based infrared (IR) satellite sea surface temperature (SST) algorithms has been the lack of sufficient in situ skin temperature measurements for derivation of the algorithm coefficients. Since IR brightness temperatures respond to the skin temperature, use of the more numerous subsurface observations to tune the algorithms introduces uncertainty into the resulting SST products. Coincident in situ skin and subsurface SST measurements from three years of cruises are used to derive parallel skin and subsurface multichannel SST (MCSST)-type regression algorithms to determine the extent to which improved accuracy can be obtained using the skin measurements. Through use of only coincident measurements, the advantage offered by the greater volume of available subsurface observations is eliminated. Surprisingly, we find no accuracy improvement using skin SST algorithms relative to algorithms derived from the research-grade ship-borne subsurface temperature measurements used in our analysis. However, better accuracy was found relative to algorithms derived from subsurface observations whose accuracy was degraded to that of buoys. The results are robust with regard to satellite resolution, collocation criteria, geographical regions, and time of day. The accuracy differences are found to be generally consistent with the effects of: (1) increased measurement uncertainty of radiometric measurements relative to research-grade subsurface observations, and (2) differences in spatial variability between the skin SST and temperature-at-depth. The subsurface algorithms are regenerated after degrading the subsurface measurements by adding increasing levels of Gaussian white noise to determine the amplitude of the additional variability required to ensure equal accuracy between the skin and subsurface products. The required supplemental noise ranges between 0.10 and 0.17 K for all data combined and generally decreases with tighter collocation windows and higher-resolution satellite observations. Variogram analysis and filtering of the in situ measurements suggest that differences in measurement uncertainty between the infrared radiometers and the subsurface sensors can explain 0.07–0.10 K of the required noise, while differences in spatial variability with depth can account for up to 0.07–0.10 K of the residual noise. A key consequence is that spatial averages of the skin temperature over satellite footprints of 2 km or more, while potentially biased in the mean, may exhibit less variance relative to point samples of the subsurface temperature than to the actual radiometric skin temperature.

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.

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.

Location of the Antarctic Polar Front from AMSR-E Satellite Sea Surface Temperature Measurements

Abstract The location of the Southern Ocean polar front (PF) is mapped from the first 3 yr of remotely sensed Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) sea surface temperature (SST) measurements. In agreement with previous studies, the mean path of the Antarctic PF and its standard deviation are strongly influenced by bottom topography. However, the mean PF path diverges slightly from previous studies in several regions where there is high mesoscale variability. Although the SST and SST gradient at the PF show spatially coherent seasonal variations, with the highest temperature and the lowest temperature gradient during summer, the seasonal variations in the location of the PF are not spatially coherent. The temporal mean SST at the PF corresponds well to the mean PF path: the temperature is high in the Atlantic and Indian Ocean sections and is low in the Pacific Ocean section where the PF has a more southerly position. The relationship of the wind field with the Antarctic PF location and proxies for the zonal and meridional PF transports are examined statistically. Coherence analysis suggests that the zonal wind stress accelerates the zonal transport of the PF. The analysis presented herein also suggests that the meridional shifts of the Antarctic PF path correspond to the meridional shifts of the wind field.

Seasonal and interannual variations of the field of sea-surface temperature in the southwest Atlantic according to the data of satellite and contact measurements

We study the seasonal and interannual variations of the field of sea-surface temperature (SST) in the Southwest Atlantic on the basis of the analysis of three data arrays, namely, the Levitus-Boyer-1994 hydrological array, the WOD-98 actual database, and the data of satellite measurements of SST. We perform the comparative analysis of the amplitude-phase characteristics of the annual course of the SST field and discuss the distinctive features of its seasonal and interannual variations. It is shown that the results obtained by using different data arrays are in good agreement. The values of the coefficient of linear correlation are equal to 0.7–0.9. It is discovered that the maximum seasonal variations of SST are observed in the zone of confluence of the Falkland and Brasil Currents in the vicinities of the South Subtropical and Antarctic Polar fronts. The minimum seasonal variations are recorded in the Antarctic region and in the Weddell Sea. The satellite data demonstrate that the level of interannual variability is high in the zones of climatic fronts.

Seasonal constraints on the estimation of new production from space using temperature‐nitrate relationships

Inverse relationships between sea surface temperature and concentrations of the major inorganic nutrients have recently been exploited to estimate new production from remotely sensed data. In situ surface data collected in the Irminger Basin during four successive seasons in 2001/2 allow a robust examination of the conceptual processes behind temperature‐nitrate relationships. The data confirm a simple model of the seasonal variation in the temperature‐nitrate relationship. A strong inverse correlation between temperature and nitrate is found in both winter data sets, but no correlation is seen in spring or summer. Furthermore, the slope of the temperature‐nitrate regression is found to be different for the two winter data sets. The results have implications for using temperature‐nitrate relationships to derive new production estimates at high latitudes from satellite sea surface temperature measurements. However, the data allow a simple, lower‐bound estimate of the region's new production to be made by exploiting Argo float data.

Diurnal signals in satellite sea surface temperature measurements

During the daytime, solar heating may lead to the formation of a near‐surface diurnal warm layer, particularly in regions with low wind speeds. This effect can be clearly seen in global, satellite‐derived, maps of the difference between daytime and nighttime SSTs. Analysis of TMI and AVHRR SSTs revealed that the onset of warming begins as early as 8 AM and peaks near 3 PM., with a magnitude of 2.8 C during favorable conditions. After this peak, the signal decays gradually until 11 PM, when the skin temperature approaches the bulk temperature. An empirical model is calculated from satellite SST and wind speed data, then used to derive daily global maps of diurnal warming. When modeled warming is removed from daytime SSTs, the mean and standard deviation of day minus night SST differences are diminished.

An s coordinate density evolving model of the northwest European continental shelf: 1. Model description and density structure

The Proudman Oceanographic Laboratory Three‐Dimensional Baroclinic B grid model (POL3DB) has been developed to incorporate features suitable for the modeling of baroclinic processes on the shelf, at the shelf slope, and in ocean regions to allow long‐term coupled ocean‐shelf simulations. We test the model on the northwest European continental shelf in the period November 1988 to October 1989 against satellite sea surface temperature measurements, against CTD sections both on and off the shelf, and (in summary) against the whole of the North Sea Project CTD data set. The model accurately reproduces the seasonal cycle in the shelf‐wide spatial temperature structure seen in the observations. Spatial correlations range from r = 0.92 in December to 0.79 in July, and the overall rms errors range from 0.8°C in April to 1.6°C in July. We demonstrate that the increase in the errors during the summer is due to uncertainties in modeling the vertical temperature structure. Compared with a climatology, the large‐scale sea surface salinity structure is also well modeled (r = 0.80), but there is a tendency for the model to overestimate the salinity in the Norwegian Trench and underestimate it in the Kattegat. The s coordinates (a modified sigma‐coordinate system) allow the formation of a seasonal mixed layer across the shelf break and into the northeast Atlantic with a modest vertical resolution. The accuracy to which this deep water region is modeled is limited by the initial and boundary conditions and by the extent of the model domain.

The 26‐day oscillation observed in the satellite sea surface temperature measurements in the equatorial western Indian Ocean

A 26‐day oscillation in sea surface temperature (SST) data is observed in the western Indian Ocean, from 52° to 60°E and in the vicinity of the equator. The SST data used in this study are obtained from the NOAA 9 satellite and are for the years 1987 and 1988. This fluctuation of SST at a period near 26 days is found to be antisymmetric about the equator and is trapped within the equatorial waveguide (equator ±6°). The variance associated with this oscillation has a maximum located at about 3° latitude; furthermore, the variance decreases at a faster rate toward the equator than poleward. These characteristics are consistent with the latitudinal structure for the mixed Rossby‐gravity (or Yanai) waves as predicted from linear wave theory. The temporal variation of this 26‐day oscillation is most energetic during the summer season (July to September), with maximum values of 0.4°C and 0.8°C found during August of 1987 and 1988 respectively. This observation agrees with the temporal variation of Yanai waves inferred from drifting buoy observations and numerical studies of the Indian Ocean. Thus we conclude that the Yanai wave is responsible for the 26‐day fluctuation observed in the SST data in this region.

A correction for Saharan dust effects on satellite sea surface temperature measurements

Sea surface temperature (SST) retrievals obtained from NOAA advanced very high resolution radiometer (AVHRR) data can determine SST within 0.7°C on a global basis. However, retrievals have been severely limited in the presence of tropospheric aerosol particles because no adequate aerosol correction algorithm exists. High tropospheric aerosol concentrations in the atmosphere significantly increase infrared signal attenuation and prevent the retrieval of accurate satellite SSTs. This paper presents tropospheric aerosol correction algorithms derived from NOAA AVHRR SST and optical depth measurements and from drifting buoy in situ SSTs. We show that the correction algorithms perform better than the current global algorithm in an atmosphere that contains high Saharan dust concentrations and generate statistical accuracy comparable to satellite SST performance globally. These corrections would significantly increase the quantity and quality of satellite retrievals under such atmospheric conditions, and the observations would greatly benefit both global climate research and maritime operations conducted in such regions.

Inertial wind path and sea surface temperature patterns near the Gulf of Tehuantepec and Gulf of Papagayo

During the northern hemisphere winter the surface atmospheric pressure on the Gulf of Mexico side of Central America is often higher than that on the Pacific side. The resultant southward pressure gradient drives strong southward winds through a gap in the Sierra Madre mountain range at the Isthmus of Tehuantepec. The atmospheric jet is narrow in comparison with the relevant radius of deformation, so when it leaves the coast and flows out over the Gulf of Tehuantepec, it is an inertial jet. Therefore the jet is expected to be deflected into a clockwise inertial circle by the Coriolis force. A similar process should also occur for Central American atmospheric jets through mountain range gaps near the Gulf of Papagayo. Satellite measurements of sea surface temperature together with coastal wind data for the first 41 days of 1986 were examined to see if the expected wind path influenced sea surface temperature (SST) near the Gulf of Tehuantepec and the Gulf of Papagayo. Consecutive daily satellite images when the coastal southward Tehuantepec wind increased suggest that the initial development of cold surface water in a clockwise loop is due to the wind mixing the shallow thermocline surface water along its inertial path. A simple 1½‐layer analytical ocean model suggests, in agreement with observations, that the wind can drive surface quasi‐geostrophic currents of ∼1 m s−1. Since the wind path is circular, the wind actually generates a clockwise rotating ocean eddy with the approximate scale of the wind inertial circle. The satellite sea surface temperature measurements also suggest that the wind‐driven surface ocean current is unstable. In addition, stronger gradients in SST to the right of the expected wind flow are consistent with advection of sea surface temperature by ocean surface Ekman flow.