Diurnal variability in sea surface temperature in the Arctic

The formation of diurnal warming events in sea surface temperature (SST) observations in the Arctic is investigated using multiple satellite derived SST products and in situ buoy temperature measurements. Significant diurnal warming events (of the order of several K) are shown to occur even in the Arctic during summer months, when the total daily insolation at high latitudes is, in fact, higher than that at low and mid latitudes. The observed Arctic diurnal warming events are shown to usually happen in persistent low wind conditions, and are more frequent in shallow waters than deep waters. During the studied period of June and July 2008, significant diurnal warming events were observed over most of the studied area, although with smaller spatial extent and reoccurring less often when compared to events reported at low and mid latitudes.     

The effect of monomolecular surface films on the microwave brightness temperature of the sea surface

Abstract

Airborne microwave radiometer measurements at 1·43 and 2·65 GHz over a sea surface covered with a monomolecular oleyl alcohol surface film and over adjacent slick sea surfaces are presented. The measurements show that at 2·65 GHz the brightness temperature T _B is not affected by the slick, while at 1·43 GHz it drops from 93 K to a minimum value of almost O K. This implies that at 1·43 GHz the emissivity of the slick-covered sea surface is extremely small, similar to a metallic layer, and that this resonant-type phenomenon is confined to a narrow frequency band of width δ?/ ?<0·6.

The theoretical implications of these experimental findings are discussed in the framework of the Debye relaxation theory of polar liquids. It is conjectured that a thin layer of water molecules polarized by the surface film gives rise to an anomalous dispersion, which causes the large decrease in brightness temperature at 1·43 GHz.

The modulus of the relative dielectric constant ε? is estimated to be ≥ 5·2 × 10^?4 and the thickness of the emitting layer ≤1·9 × 10^?4 m for 1·43 GHz. Furthermore, the film-induced surface activation energy is calculated to be 9·18 × 10^?21 J. These values seem reasonable in the light of the theories on the physicochemical structure of surface layers.     

Seasonal and interannual variability of oceanographic processes in the Gulf of Guinea: An investigation using AVHRR sea surface temperature data

The Gulf of Guinea is situated in a critical position for understanding Atlantic equatorial dynamics. This study investigates seasonal and interannual variability in sea surface temperature (SST) throughout this region, focusing on dynamical ocean processes. A 10.5-year time series of remotely sensed SST data with 4 km spatial resolution from the Advanced Very High Resolution Radiometer (AVHRR) were used for this investigation, as they are sufficient to resolve shelf processes. Firstly, patterns of cloud cover were assessed, then spatio-temporal variability in SST patterns was investigated. Features identified in climatological SST images were the Senegalese upwelling influence, coastal upwelling, tropical surface water, river run-off and fronts. Of particular interest is a shelf-edge cooling along the coast of Liberia and Sierra Leone in February. Interannual variability, assessed using annual mean images, time series decomposition and spectral analysis, showed a quasi-cyclic pattern of warm and cool years, perhaps related to El Niño-type forcing. The results of this study show the usefulness of infrared remote sensing for tropical oceanography, despite high levels of cloud cover and atmospheric water vapour contamination, and they provide evidence for theories of westward movement of the upwelling against the Guinea current and remote forcing of the upwelling.     

Mesoscale variability of sea surface temperature in the North Atlantic

Abstract

Analyses of mesoscale horizontal distributions of temperature were performed for an area of the North Atlantic using data from the NOAA-7 and NOAA-6 Advanced Very High Resolution Radiometer (AVHRR). The zonal and meridianal variance spectra have.slopes between —1.4 and —2.5 with a clear maximum at -2.0. This is also true for the direction-dependent structure functions. The isotropic part of the variance spectra has a mean slope of —2.2±0.17 at scales of 10— 100km; this lies between the slopes of -1 and —3 predicted by the theories of two-dimensional and geostrophic turbulence. A comparison between measurements and theories is difficult because of the insufficient applicability of these theories to boundary layers. Moreover, in some cases there are significant maxima in the variance spectra at scales between 50 km and 250 km.     

Satellite based forecasting of sea surface temperature in the Tuscan Archipelago

The system described employs a nonlinear forecasting technique based on a combination of genetic algorithms and empirical orthogonal function (EOF) analysis. The genetic algorithm identifies the equations that best describe the behaviour of the different temporal orthogonal functions in the EOF decomposition and therefore, enables global forecasting of future time variability. The method is applied to obtain a one-month ahead forecast of the monthly mean space-time variability of the sea surface temperature (SST) of the Tuscan Archipelago, northwest coast of Italy. The system performance has been validated comparing forecast fields with real satellite observations. Results indicate that the system provides better predictions than those based on climatology. Future research is oriented to make the system applicable to military operations, environmental control and fisheries activities.     

Emittance effect on the remotely sensed sea surface temperature

A systemtic underestimation of remotely sensed sea surface temperature occurs in calculations which assume a value of the surface emittance equal to unity in the atmospheric window, where the measurements are taken. The paper includes a detailed examination of the effect on the sea surface temperature estimation caused by assuming a wrong value of the emittance. Results show that this effect is a function of the atmospheric transmittance and the surface temperature. The angular dependence and the influence of the sea state on this effect are also investigated     

Sea surface effects on the sea surface temperature estimation by remote sensing

By using a sea surface temperature profiler buoy, the behaviour of the vertical temperature profile near the sea surface was observed in Mutsu Bay. In the daytime under calm and strong sunshine condition, there occurred a large temperature difference between the uppermost sea surface and the 1 m depth. The difference disappeared when the wind began to blow with a speed greater than 4ms^?1. Besides the atmospheric effects the inhomogeneity of the vertical temperature distribution near the sea surface must be another major error factor in the sea surface temperature estimation by satellite remote sensing.     

Infrared sensing of sea surface temperature from space

Error sources in infrared remote sensing of sea surface temperature are discussed, e.g., imperfect transmittance models, uncertain or unknown atmospheric pressure-temperature-humidity vertical profiles, temperature discontinuities at the air-sea interface, temperature differences between surface and bulk water, and neglect of surface emissivity and reflectance. Some of these are analyzed using a simplified version of the transmittance function of Prabhakara et al. (1974). The rms error in conventional sea surface temperature retrievals, in which computers are used to integrate the equation of radiative transfer over many atmospheric layers, has thus far been reduced to about ±1 K (Maul, 1980). This error is for optimum conditions, and seems irreducible. Unless the accuracy can be improved it seems impractical to spend so much effort on lengthy computer retrievals. Prabhakara et al. (1974) have devised a much simpler retrieval method using three infrared bands, which yields an rms error of ±1.1 K. A very simple method yielding ±1.0 K with two infrared bands is described here.     

Inter-comparison of various global sea surface temperature products

In this study, eight global sea surface temperature (SST) products for 2009 are compared to clarify their characteristics. The median of eight daily values, the Ensemble Median as Reference Product (EMRP), is used as a reference product for inter-comparison. The results show that the absolute value of mean differences and the value of root mean square (RMS) differences are higher in single-microwave products such as Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E), Tropical Rainfall Measuring Mission Microwave Imager (TMI), and WindSat, than in products such as MicroWave Optimally Interpolated SST (MWOI), Merged satellite and in situ data Global Daily SST (MGD), and Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) constructed by merging several SST data. It is of note that the characteristics of SST products depend on the type of SST used within the product, rather than the data source used. A comparison of SST products was also conducted using EMRP and data observed by moored buoys. The results show that only AMSR-E has a warm bias (+0.06°C) while other products have a cool bias (maximum value ?0.10°C). The RMS error of TMI is the highest (0.57°C), and that of EMRP the lowest (0.28°C). Furthermore, the temporal variability between the data in each SST product was compared to those observed by the Kuroshio Extension Observatory (KEO) buoy. Results show that the temporal variability of EMRP corresponds well to that of buoy data, and that the RMS error of EMRP is lower than that of the other SST products.     

Combined remote-sensing,model, and in situ measurements of sea surface temperature as an aid to recreational navigation: crossing the Gulf Stream

Combined in situ, model, and satellite remote-sensing observations are used to determine the location of the Gulf Stream as an aid to safe navigation for small recreational vessels.

A field study was executed from Hamilton, Bermuda, to Virginia Beach, USA, over a period of 5 days, from 30 June 2010 to 4 July 2010 to test the feasibility of using remote-sensing products as an aid to cross the Gulf Stream from the point of view of a small, slow-moving (?6 knots, 3 m s^?1) sailboat. The in situ data collected were compared to NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) remote-sensing data, to the Global High Resolution Sea Surface Temperature (GHRSST) microwave and infrared blended data set, to the National Oceanic and Atmospheric Administration Real-Time Ocean Forecast System (NOAARTOFS) ocean model, and to selected NOAA buoy and ship measurements.

A spatio-temporal analysis was performed by comparing the in situ measurements with observations retrieved at the same time and location in each of the data sets. The least error (correlation coefficient r?=?0.94) was obtained using MODIS data, and the largest error (r?=?0.78) was obtained using the RTOFS model data. Overall, most observations agree with the general spatio-temporal trend of the in situ data, with 95% of the errors within ±1°C and 98% of the errors within ±2°C.

The study shows that MODIS data are particularly suited to identification of the location of the Gulf Stream, which can be used by small vessels to optimize the crossing route and to minimize the risks associated with the passage.     

Optimal estimation of sea surface temperature from split-window observations

Optimal estimation (OE) improves sea surface temperature (SST) estimated from satellite infrared imagery in the “split-window”, in comparison to SST retrieved using the usual multi-channel (MCSST) or non-linear (NLSST) estimators. This is demonstrated using three months of observations of the Advanced Very High Resolution Radiometer (AVHRR) on the first Meteorological Operational satellite (Metop-A), matched in time and space to drifter SSTs collected on the global telecommunications system. There are 32,175 matches. The prior for the OE is forecast atmospheric fields from the Météo-France global numerical weather prediction system (ARPEGE), the forward model is RTTOV8.7, and a reduced state vector comprising SST and total column water vapour (TCWV) is used. Operational NLSST coefficients give mean and standard deviation (SD) of the difference between satellite and drifter SSTs of 0.00 and 0.72 K. The “best possible” NLSST and MCSST coefficients, empirically regressed on the data themselves, give zero mean difference and SDs of 0.66 K and 0.73 K respectively. Significant contributions to the global SD arise from regional systematic errors (biases) of several tenths of kelvin in the NLSST. With no bias corrections to either prior fields or forward model, the SSTs retrieved by OE minus drifter SSTs have mean and SD of − 0.16 and 0.49 K respectively. The reduction in SD below the “best possible” regression results shows that OE deals with structural limitations of the NLSST and MCSST algorithms. Using simple empirical bias corrections to improve the OE, retrieved minus drifter SSTs are obtained with mean and SD of − 0.06 and 0.44 K respectively. Regional biases are greatly reduced, such that the absolute bias is less than 0.1 K in 61% of 10°-latitude by 30°-longitude cells. OE also allows a statistic of the agreement between modelled and measured brightness temperatures to be calculated. We show that this measure is more efficient than the current system of confidence levels at identifying reliable retrievals, and that the best 75% of satellite SSTs by this measure have negligible bias and retrieval error of order 0.25 K.     

Summertime sea surface temperature and salinity fronts in the southern Taiwan Strait

Based on hydrographic survey and satellite data, three fronts were observed in the southern Taiwan Strait in summer. They are the Taiwan Bank Front (TBF), the Southwest Coastal Upwelling Front (SCUF), and the Pearl River Plume Extension Front (PRPEF). In addition to the temperature aspect of TBF and SCUF as indicated in previous studies, we find that TBF and SCUF could also be identified according to salinity. The TBF is closely related to the Taiwan Bank upwelling, tidal mixing, and the Pearl River Plume Extension. Different hydrographic conditions on the southern and northern sides of this front lead to a south–north asymmetric structure of the TBF. The relatively small Simpson–Hunter number around the Taiwan Bank indicates that the TBF may be a tidal front. The SCUF separates the wind-driven cold, saline coastal upwelling water from the warm, less saline offshore water. Owing to frontal instability, SCUF exhibits both short temporal (several days) and small spatial (several kilometres) scales, indicative of intense sub-mesoscale processes. Nonetheless, the weak summertime SCUF was revealed in the log-transformed satellite frontal map. Finally, apart from the commonly observed dominant PRPEF in summer, a bifurcation from the PRPEF was identified in most hydrographic sections. Once generated, this bifurcation is carried by the topography-following current away from the PRPEF.     

Comparison of polar and geostationary satellite infrared observations of sea surface temperatures in the Gulf of Maine

A comparison is made between the polar orbiting (NOAA) and the geostationary (GOES) satellite infrared observations of sea surface temperatures in the Gulf of Maine between 23 May and 6 June 1978. Color image enhancement is used to demonstrate that both satellites are capable of detecting the large-scale surface patterns associated with the Gulf Stream and sea surface temperature fronts in the vicinity of Georges Bank and Nova Scotia. The main difference between the range of surface temperatures detected by the two satellites is due to their different spacial resolution: 1 km for the NOAA and 8 km for the GOES. The equivalent blackbody temperatures recorded by the GOES are 2–3°C lower than those obtained by the NOAA satellite because of a GOES calibration offset. The comparison of the NOAA data with ship observations off Nantucket indicates that, at sea surface temperatures of 6–7°C, the NOAA Satellite and ship observations agree within 1°C. A similar comparison in the Gulf Stream at sea surface temperatures of 23–27°C, indicates that the NOAA measurements are 2–3°C lower than in situ observations. Coastal radiosonde profiles are used to estimate the correction for atmospheric attenuation of the infrared radiation. A comparison of Maul and Sidran (1973) and Weinreb and Neuendorffer (1973) models for attenuation of infrared by atmospheric water vapor shows significant differences. It was not possible to resolve the discrepancy between the models because of measurement uncertainties.     

Prediction of currents and sea surface elevation in the Gulf of California from tidal to seasonal scales

A web tool that provides currents and/or sea surface elevation in the Gulf of California is presented. The above variables are reconstructed from harmonic constants obtained from harmonic analyses of time series produced by a 3D baroclinic numerical model of the Gulf. The numerical model was forced (1) at the Gulf's mouth by the tides and the hydrographic variability of the Pacific Ocean (at semiannual and annual frequencies), and (2) at the Gulf's surface by winds, heat and fresh water fluxes (also at the semiannual and annual frequencies). The response to these forcings results in motions with time scales limited to semidiurnal and diurnal, fortnightly and monthly (due to nonlinear interactions of the tidal components), and semiannual and annual frequencies (due to the nontidal forcing).     

Seasonal and interannual studies of vortices in sea surface temperature data

An algorithm for calculating feature displacement velocities and for detecting vortices has been applied to 13 years of sea surface temperature data derived from Advanced Very High Resolution Radiometer (AVHRR) data. A unique global event database for seasonal and interannual studies of the spatial distribution of oceanic vortices was created for the years 1986–1998. The results indicate that (1) the number of vortices in each season is fairly constant from year to year in each hemisphere—however, their preferred locations change on seasonal to interannual time-scales; (2) the maximum number of vortices were detected in the summer and in the winter in all oceans and the minimum number were detected in the autumn; and (3) the distribution of the spatial density function shows preferred localizations such as 40°?S, the tropical instability region, marginal seas, western boundary and eastern boundary current regimes.     

Spatial and temporal variability of satellite-derived sea surface temperature in the Barents Sea

The Barents Sea (BS) is an important region for studying climate change. This sea is located on the main pathway of the heat transported from low to high latitudes. Since oceanic conditions in the BS may influence vast areas of the Arctic Ocean, it is important to continue to monitor this region and analyse the available oceanographic data sets. One of the important quantities that can be used to track climate change is the sea surface temperature (SST). In this study, we have analysed the 32 years, (1982–2013) National Oceanic and Atmospheric Administration (NOAA) Optimum Interpolation SST Version 2 data for the BS. Our results indicate that the regionally averaged SST trend in the BS (about 0.03°C year^–1) is greater than the global trend. This trend varies spatially with the lowest values north from 76° N and the highest values (about 0.06°C year^–1) in proximity of Svalbard and in coastal regions near the White Sea. The SST and 2 m air temperature (AT) trends are high in winter months in the open BS region located west from Novaya Zemlya. Such trends can be linked to a significant retreat of sea ice in this area in recent years. In this article, we also documented spatial patterns in the annual cycle of SST in the BS. We have shown that the interannual variability of SST is similar in different regions of the BS and well correlated with the interannual patterns in AT variability.     

Analysis of sea surface temperature time series of the south-eastern North Atlantic

The dominant periods in time series of sea surface temperature (SST) of the south-eastern North Atlantic are determined and related to atmospheric forcing and ocean dynamics. We analyse five-day composite images of a 10.5-year-long (from 10 July 1981 to 31 December 1991) time series of Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA satellites. The dominant signal present in the whole region is the annual cycle. It explains 70% of the SST variance in the northern region and 40% in the southern. The pattern of the annual amplitudes is related to the seasonal cooling and warming cycle in the region. The second dominant period is a semi-annual frequency, estimated by means of periodograms of the residual time series with the annual cycle subtracted. This semi-annual frequency is responsible of making short springs and long autumns. The semi-annual frequency is present in 44% of the time series in the region, contrary to the generalized idea that a time series must always contain it. The geographical distribution of the semi-annual component of SST suggests that it is associated with the curl of the wind stress. The third dominant period is four years, found in three different areas: south of the Canary islands, off the Cape Verde islands and towards the northwest of Lanzarote Island. The main effect of this signal is to increase the maximum temperature every four years and to decrease the minimum temperature two years later. The 4-year signal does not seem to be associated with any atmospheric forcing field. The presence of a signal in the curl of the wind stress with periodicities of 25–30 days located south of the Canary Islands led us to conclude that the curl of the wind stress is important for the generation and shedding of eddies downstream these islands.     

Interannual variability of the chlorophyll-a and sea surface temperature of the Black Sea

A comparative analysis of the Black Sea surface temperature and chlorophyll-a concentration was based on the satellite data (PODAAC JPL AVHRR Pathfinder and SeaWiFS) for 1998–2005. The fields of dispersion and spatial gradient were analysed as well. On the interannual scale, no statistical relationship was found between the field of sea surface temperature and chlorophyll-a. The mesoscale variability (which masked the statistical assessments of interannual coupling) was well pronounced in the fields of both parameters. For the deep part of the sea, a sign of the wave-type origin of the variability of chlorophyll-a and sea surface temperature was evaluated.     

A non-regression-coefficients method of sea surface temperature retrieval from space

For several years now NOAA/NESDIS have derived an operational global sea surface temperature (SST) product from the AVHRR instrument on the NOAA satellites. This is done using the MCSST and CPSST algorithms which contain coefficients that are determined from a regression analysis of satellite data against in situ surface data. The current algorithms are used to provide global SST data without taking into account the latitude, climate or location of the satellite data, although the CPSST coefficients do have a weak dependence on the satellite brightness temperatures. Because of this global application the current SST algorithms have inherent errors due to local climate influences. In this paper a new SST algorithm is developed that does not rely on regression analysis to derive its coefficients. By using the spatial variation of the brightness temperatures in a small area (50 km by 50 km) it is possible to derive the appropriate coefficients to use in the algorithm. The SST field can thus be derived at any location without need for prior determination of the algorithm coefficients. In a simulation study, data from twenty-five radiosonde ascents-arc use with an atmospheric transmission model to derive a range of atmospheric transmittances and satellite brightness temperatures. Coincident AVHRR data and ship data are used to assess the accuracy of the new algorithm. The various dependencies of the terms in the SST algorithm are investigated. As with the MCSST and CPSST algorithms, the new method has largest errors when applied in situations of abnormal atmospheric structure. The improvement over the MCSST product may initially be only marginal, but with the advent of the more precise data from the Along Track Scanning Radiometer (ATSR) a more accurate global SST product may be possible.