Estimation of sea surface temperature from SEVIRI data: algorithm testing and comparison with AVHRR products

Three surface temperature (ST) algorithms for Spinning Enhanced Visible and InfraRed Imager (SEVIRI) data are developed and tested. A general split window algorithm for ST estimation, a sea surface temperature (SST) algorithm and a nonlinear algorithm (NLSST) developed for SEVIRI data. The test was carried out by comparing SEVIRI data with two types of data: (a) in situ and (b) obtained with the NLSST algorithm applied to Advanced Very High Resolution Radiometer (AVHRR). The field campaign was carried out over sea using a thermal radiometer. The algorithms were applied to SEVIRI images in coincidence with the field campaign and the results show an rms error lower than 0.7 K. The comparison with AVHRR data was carried out in six test regions and provided an rms error lower than 1.3 K. The best results were obtained for the SST algorithm proposed.     

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.     

Generating global surface albedo products from multiple geostationary satellites

Operational weather geostationary satellites have acquired data for more than two decades and offer thus the possibility to generate long time series of Essential Climate Variables like surface albedo as suggested by GCOS. This paper investigates the possibility to generate consistent global, to the exception of the polar regions, surface broadband albedo product from these satellites. In this context, the paper addresses two specific issues. Firstly, the spatial consistency of surface albedo derived from five different geostationary satellites is examined in detail. Secondly, this product is compared with the equivalent MODIS one to define the temporal consistency between surface albedo derived with old geostationary instruments and technologically advanced radiometers like MODIS. The analysis of the surface albedo products has revealed a good agreement between the products derived from the various geostationary satellites. Comparison of this global product with the one routinely derived from MODIS shows that on the average, the mean relative difference between these two data sets agree within 10%. These first encouraging results open therefore a new avenue for the exploitation of the archived data for the generation of long time series, covering the last 25 years or so, of global surface albedo from geostationary weather satellites.     

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.     

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     

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.     

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.     

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.     

Retrieving ocean surface current by 4-D variational assimilation of sea surface temperature images

In this article we propose a new method to estimate ocean mesoscale structures of the surface current velocity by processing sea surface satellite images. Assuming that the intensity level can be described by a transport-diffusion equation, the proposed approach is based on variational assimilation of image observations within a simple transport-diffusion model. This approach permits to retrieve the current velocity field from a sequence of satellite images. Results of processing synthetic data and real NOAA-AVHRR satellite images are presented and commented.     

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.     

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.     

Stabilizing global mean surface temperature: A feedback control perspective

In this paper, we develop a discrete time, state variable feedback control regime to analyze the closed-loop properties associated with stabilizing the global mean surface temperature anomaly at 2 °C within a sequential decision making framework made up of 20 year review periods beginning in 2020. The design of the feedback control uses an optimal control approach that minimizes the peak deceleration of anthropogenic CO₂ emissions whilst avoiding overshooting the 2 °C target. The peak value for emissions deceleration that satisfies the closed-loop optimization was found to be linearly related to climate sensitivity and a climate sensitivity of 3.5 °C gave a deceleration of ?1.9 GtC/a/20 years². In addition to accounting for the predicted climate dynamics, the control system design includes a facility to emulate a robust corrective action in the face of uncertainty. The behavior of the overall control action is evaluated using an uncertainty scenario for climate model equilibrium sensitivity.     

Angular correction of sea surface temperature observed by thermal infrared radiometer

Abstract

A thermal infrared radiometer indicates a lower sea surface temperature at a large observation angle than the directly measured one. In order to explain this decrease in the apparent temperature, the intensity of the radiation reaching the radiometer is formulated as a function of observation angles of the radiometer. In the equation, we assume that a reflection loss occurs at the sea surface for the radiation from below the surface. The temperature predicted from this formula at the large observation angles fits well to the observed one, indicating that temperatures observed at large observation angles can be corrected     

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.     

Using sea surface temperature measurements from microwave and infrared satellite measurements

The Tropical Rainfall Mapping Mission Microwave Imager (TMI) instrument Sea Surface Temperature (SST) product (v1.0) is compared with in situ observations obtained in the Atlantic Ocean. The TMI SST has a mean warm bias of 0.25?K±0.7?K when compared to in situ SST at a depth of 7?m. When TMI SST are compared to in situ skin SST measurements, the bias is 0.6?K±0.5?K. A limited global comparison between TMI SST and co-incident ERS-2 Along-Track Scanning Radiometer (ATSR/2) skin SST demonstrates a bias of 0.6?K±0.6?K consistent with the result obtained using in situ observations. These results are consistent with the predicted accuracy of the TMI SST data products. Based on these results, a simple method to merge the TMI and ATSR data is proposed.     

Measuring sea surface temperature from satellites: a ground truth approach

Determining the correction for atmospheric attenuation is a major problem in processing thermal infrared digital data from very high resolution radiometers aboard NOAA Polar Orbiting Satellites. An empirical equation for estimating this correction is developed. The coefficients of the equation are determined by using regression techniques and comparing satellite observations to sea surface temperature measurements. Although there is not sufficient data to fully evaluate this procedure, initial satellite measurements are within 0.5°C of independent sea surface temperature measurements.     

Size estimates of the factors controlling sea surface temperature with AVHRR data

NOAA AVHRR thermal infrared images, meteorological measurements and model calculations have been used to estimate the magnitude of the processes controlling the sea surface temperature variability in the Bay of Biscay. The estimates are based on the equation of temperature conservation and the equation for the total derivative. The results show that local time change, advection, horizontal diffusion and vertical turbulent flux vary with time and space. The sea surface temperature variability is mainly controlled by vertical turbulent flux and advection. For an average of five-day estimates, the order of the relative importance of the processes is vertical turbulence (38 per cent), advection (32 per cent), local time change (22 per cent) and horizontal diffusion (8 per cent).     

Identification of upwelling areas on sea surface temperature images using fuzzy clustering

Sixteen sea surface temperature (SST) images obtained over the coastal ocean of Portugal during the period September 1992-September 2003 were used aiming to identify automatically the areas covered by upwelling waters. Suitable high resolution colour scales were applied to the SST images in order to enhance the thermal patterns and easily identify the waters with a coastal upwelling origin. The automatic identification of the areas covered by upwelling waters was developed by the authors in a previous work, through the application of fuzzy clustering and validation indexes, and here is explored as an oceanographic application to the Portuguese coastal upwelling. The fuzzy c-means (FCM) algorithm showed to be able to find partitions that closely defined the upwelling areas and the visualization of the fuzzy c-partitions was achieved through the application of a colour scale. The Xie-Beni validation index was used to select the c-partition that best represented the stage of the upwelling event and showed an agreement with the oceanographic interpretation in 10 of the 14 SST segmented images used in this work. Two SST images without upwelling were also used in order to check the response of the algorithm to the absence of the phenomena. The computation of the matching rate between a c-partition and the two areas split by the hand-contoured upwelling boundary also allowed the evaluation of how closely the obtained segmentation reproduced the shape of the areas covered by upwelling waters. This method successfully identified the upwelling boundary regions in 10 of the 14 SST images. The values obtained for the matching rate were higher than 0.77, thus indicating the good quality of the fuzzy partitions. The segmented images with 3 or 4 clusters were the most suitable ones to reproduce the areas covered by upwelling waters, but it was also shown that, for some cases, the upwelling areas could be reasonably well reproduced by the FCM 2-partition images. While in the latter, the area covered with upwelling waters was coincident with the first cluster, in the former, the segmented image showed two clusters within the upwelling area: the first cluster coincided with the area occupied by the most recently upwelled waters near the coast, while the second cluster was coincident with the area occupied by the “older” upwelling waters with its extensions offshore, the so-called cold filaments. The FCM algorithm revealed to be a promising technique in the automatic identification of upwelling areas on SST images.     

Split-window and multi-angle methods of sea surface temperature determination: An analysis

A physical model of split-window and multi-angle algorithms for the retrieval of sea surface temperature has been obtained. It is shown that optical thickness in the thermal infrared window region is approximately represented by a separable function of wavelength and atmospheric variables which greatly simplify the radiative transfer model. In modelling the temperature retrieval algorithms we exploit the correlation that exists between the sea surface temperature and the average temperature of the atmosphere. It is shown that, to the extent this correlation is maintained, there is a simple relationship between surface temperature and the brightness temperatures measured in two split-window or multi-angle channels. The different atmospheric conditions which cause spread in this relationship are briefly discussed. It is shown that measurements at three optical thicknesses instead of two as in the case of the split-window method improve the SST retrieval accuracy since it can take care of non-equilibrium conditions such as inversions, surface instabilities, etc., prevailing in the atmosphere.