Sea Surface Temperature Retrieval Research Articles

Errors at large satellite zenith angles on AVHRR derived sea surface temperatures

Abstract The study presented here is a part of an attempt to improve the operational algorithm used at the Centre de Météorologie Spatiale (CMS) to calculate Sea Surface Temperature (SST) from Advanced Very High Resolution Radiometer (AVHRR) data. The errors produced by SST retrieval algorithms are analysed through two experiments: an examination of the errors calculated on a validation file and an analysis of the temperatures of oceanic cloud-free areas seen under two distinct satellite zenith angles (θ) for consecutive night-time orbits. This Letter presents the part of the study dedicated to the effect of large viewing angles on the retrieval of SST. Correction terms are proposed and compared, on the same set of data, to split window algorithms using θ dependent coefficients

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.

A basic limitation of the split window method for SST retrievals when applied to a wide range of water vapor conditions

The split window method for retrieving sea surface temperatures (SST) from satellite‐based observations is evaluated from radiative transfer calculations, and shown to have an inherent limitation that arises from a linear assumption in the correction scheme. This general limitation leads to significant errors (of several degrees in some cases) in the retrieved SST; the theoretical basis for the error is examined.

Remote observation of the sea surface and atmosphere The oceanic skin effect

Abstract A comparison is made between the measurements of sea surface temperature (SST), obtained using an infrared radiometer mounted on a vessel of the British Antarctic Survey, and from a conventional Meteorological Office rubber bucket with mercury thermometer. These measurements are used to investigate the size and variability of the oceanic skin effect from the tropical Atlantic to the waters of Antarctica. The implication of the skin effect on the validation of satellite-borne infrared sensors of the sea surface temperature is also investigated. In terms of the overall average for the complete Atlantic Ocean data set, the skin of the sea is about 0-30 deg K cooler than the bulk at about 10cm below the surface. There are only a few cases of the skin being warmer than the bulk temperature, on the other hand there are some occasions when the skin can be of the order of 1 -0 deg K cooler than the bulk. There is a suggestion that the skin effect at night-time is smaller than it is during the day-time, and a possible explanation of this is given in terms of the complication of the diurnal thermocline. The skin effect can be an important source of error in the validation of space-borne sensors of SST, particularly with the requirement for high accuracy of SST measurement for climate studies. In terms of the retrieval of SST from satellite infrared sensors the skin effect is only one of several physical effects that create uncertainty in the value of SST.

Retrieval of sea surface temperature from INSAT-IB radiometer measurements using a multi -channel simulation approach

In the multi-channel sea surface temperature (MC SST) retrieval technique, brightness temperatures obtained from different satellite radiometer window channels viewing the same area are used to eliminate the atmospheric effects. The MC SST technique cannot be used with satellite radiometers having a single infrared window, e.g., INSAT-1.B \'HRR. In the present paper, a method has been proposed to split up the radiance received over a single channel, .10.5-12.5 /L, as a sum of two component radiances over .10.5- 11.5 and 11.5-12.5 /L bands parametrically in terms of the atmospheric water vapour content, thus allowing the MC SST algorithm to be applied if the water vapour content is known or assumed. The difference between MC SST and the single-window brightness temperature (Tsw) is defined interms of Tsw and the total atmospheric Water vapour content. Using climatological (IIOE) water vapour data, isotherms of INSAT-IB sea surface temperature over Arabian Sea, Bay of Bengal and Indian Ocean are presented for Jaruary and May. 1986. Comparison with NOAA retrievals shows good agreement. The method is meant for cloud-free areas.

Optimized Retrievals of Precipitable Water from the VAS “Split Window”

Precipitable water fields have been retrieved from the VISSR Atmospheric Sounder (VAS) using a radiation transfer model for the differential water vapor absorption between the 11- and 12-micron 'split window' channels. Previous moisture retrievals using only the split window channels provided very good space-time continuity but poor absolute accuracy. This note describes how retrieval errors can be significantly reduced from plus or minus 0.9 to plus or minus 0.6 gm/sq cm by empirically optimizing the effective air temperature and absorption coefficients used in the two-channel model. The differential absorption between the VAS 11- and 12-micron channels, empirically estimated from 135 colocated VAS-RAOB observations, is found to be approximately 50 percent smaller than the theoretical estimates. Similar discrepancies have been noted previously between theoretical and empirical absorption coefficients applied to the retrieval of sea surface temperatures using radiances observed by VAS and polar-orbiting satellites. These discrepancies indicate that radiation transfer models for the 11-micron window appear to be less accurate than the satellite observations.

Comparison of satellite‐derived sea surface temperatures with in situ skin measurements

Sea surface temperatures (SSTs), computed from sensor systems on the National Oceanographic and Atmospheric Administration (NOAA) polar‐orbiting satellites, are compared with surface skin temperatures (from an infrared radiometer mounted on a ship) and subsurface temperature measurements. Three split window retrieval methods using channels 4 and 5 of the NOAA 7 advanced very high resolution radiometer (AVHRR) sensor were investigated. These methods were (1) using AVHRR alone, (2) using AVHRR with atmospheric temperature and water vapor profiles from the TIROS operational vertical sounder (TOVS), and (3) using AVHRR and data from the high‐resolution infrared sounder (HIRS). TOVS sensors (including HIRS) are carried by the same satellite as the AVHRR and provide simultaneous corrections for the AVHRR‐based SST estimates. The importance of scan angle correction to define the correct atmospheric path is discussed, and the improvement of SST retrievals using sensor combinations is demonstrated with satellite versus ship skin temperature mean differences ranging from 0.55° to 0.73°C for AVHRR alone, from −0.39° to 0.71°C for AVHRR plus TOVS, and from 0.22° to 0.33°C for AVHRR plus HIRS. The improved SST accuracy by AVHRR plus HIRS is due to additional correction for the atmospheric water vapor and temperature structures, made possible with some of the HIRS channels. Significant differences between ship skin and subsurface temperatures were observed, with the mean deviation being 0.2°C for a range of temperature differences between −0.25° and 0.6°C.

Remote sensing of sea surface temperature through infrared radiometry — a review

A review on the estimation of sea surface temperature (SST) from space using infrared radiometry is presented. The principle of the remote sensing technique, the infrared radiometers and the theory of SST measurement have been explained briefly. The absorption of infrared radiation from earth by the atmospheric constituents has been a major problem in the retrieval of SST from space-borne sensors. The effect of clouds and other atmospheric constituents, especially moisture content/water vapour, has been discussed and the various techniques used for evaluating the atmospheric correction and their limitations are summarised. Development of separate algorithms for each oceanic area coupled with validation by realistic sea truth measurements has been suggested for improving the accuracy of SST measurements from space.

On the use of synthetic 12 μm data in a split-window retrieval of sea surface temperature from AVHRR measurements

Abstract A numerical model of the radiation transfer through the atmosphere is used with a set of mid-latitude atmospheric profiles to simulate split-window measurements of the AVHRR/2 on the NOAA-7 satellite. These are used to quantify the degradation in accuracy which results in going from a sea surface temperature retrieval in which the effect of the atmosphere is estimated using measurements at 11 μm and 12 μm (channels 4 and 5), to one in which it is estimated using synthetic channel 5 data, as advocated by Singh et al (1985).

Operational measurement of sea surface temperatures at CMS Lannion from NOAA-7 AVHRR data

Abstract Data from the NOAA-7 Advanced Very-High-Resolution Radiometer (AVHRR) have been used on a routine basis for sea surface temperature (SST) retrieval at the Centre de Meteorologie Spatiale (CMS) in Lannion (France) since September 1983. Operational SST retrieval is still practised at CMS, using NOAA-9 data. Two methods are used. The first, which is automatic, produces numerical fields (resolution: 15 × 15 nautical miles); the second is manual and produces graphic documents (resolution about 10 km). The corresponding products are published in a monthly bulletin, SATMER. The accuracy of satellite SSTs has been tested by various methods, the results of which are discussed. Some case studies of SST time variability in the Mediterranean are presented. One of the main conclusions is the need for mesoscale (10 km) numerical SST fields produced as often as possible (daily) by interactive methods.

A numerical study of the effects of anomalous North Atlantic atmospheric conditions on the infrared measurement of sea surface temperature from space

A line‐by‐line radiation transfer model is used to simulate the brightness temperatures measured in the atmospheric “window” between 10 and 13 μm by the advanced very high resolution radiometer (AVHRR/2) on the NOAA 7 satellite. The atmospheric properties are described by a large set of marine radiosonde profiles over the NE Atlantic Ocean and characterize the month of July. The effects of anomalous atmospheric conditions on the brightness temperatures are simulated by independently adjusting the humidity and temperature profiles, and it is found that the consequences of humidity anomalies are greater if they occur at height (pressure of <850 mbar), whereas temperature anomalies have greater effect if they are in the lower troposphere. Sea surface temperature (SST) retrieval coefficients, optimized for these July conditions, are derived and tested against simulated brightness temperatures derived using a “withheld” set of profiles and found to be accurate. Mean errors of several tenths of a kelvin were found when other, nonoptimized coefficients, taken from the literature, were applied to the original July conditions. The mean errors in SST derived using the optimized coefficients can also be a few tenths of a kelvin in extremely anomalous atmospheric conditions. These errors are large enough to be of concern to climate researchers but probably too small to permit direct verification by comparison with currently available conventional SST measurements.

Antenna Pattern Correction for the Nimbus-7 SMMR

This paper describes the philosophy and method used to develop the antenna pattern correction (APC) algorithm that was used on the data from the Scanning Multichannel Microwave Radiometer (SMMR) on Nimbus-7. There are limitations on what can be accomplished plished with such a procedure; these limitations are explored with the aid of Fourier analysis, even though the algorithm used on the SMMR data does not perform any Fourier transforms. The resulting analysis showed that, for the SMMR instrument, no useful improvement could be made in the data in terms of reduction of side lobes, but the quality of the sea surface temperature retrievals could be improved considerably by matching the antenna beamwidths at the different frequencies.

Retrieval of sea surface temperatures from HIRS2/MSU

The methods used at the Goddard Laboratory for Atmospheres (GLA) to retrieve sea surface temperatures from HIRS2/MSU data for the last 2 months of the NASA sea surface temperature intercomparison workshop are described. Results are shown that compare anomaly fields produced by using data from ships, AVHRR, and HIRS2/MSU for these months. Monthly mean fields derived from AVHRR and HIRS2 data show roughly comparable statistical accuracy compared to ship fields. Errors in the HIRS2 fields appear more random, while AVHRR data have larger regionally dependent biases and show large area spatially coherent errors. The random errors in the HIRS2 fields should be further reduced by performing the retrievals at a higher spatial resolution.

Retrieval of Ocean Surface Parameters from the Scanning Multifrequency Microwave Radiometer(SMMR) on the Nimbus-7 Satellite

Sea-surface temperature retrievals have been tested on 2 months of Nimbus-7 scanning multichannel microwave radiometer data. Using the prelaunch versions of the instrument calibration and geophysical parameter retrieval algorithms the initial results were poor. Improved algorithms produced substantially better results. It appears that at least for the night-Southern Hemisphere portion of the Nimbus-7 orbit, a rms measurement accuracy of 1.45°C has been achieved. Similar tests with wind speed retrievals yield an accuracy of 2.7 m/s rms with no substantial differences between day and night measurements but limited by availability of surface observations to the Northern Hemisphere. Moreover, it appears that the retrieved wind speed is more nearly related to the square of the wind observed at the surface than to the wind itself.

Zenith angle effects in multichannel infrared sea surface remote sensing

Several approaches to infrared multichannel sea surface temperature retrievals propose using a universal set of constants. It is shown that the single-channel multiangle technique (i.e., GOES and NOAA) and the multichannel single-angle technique (NOAA-n) are similar concepts with a common derivation from radiative transfer theory. It is also shown that the linear correlation factor between surface temperature minus satellite temperature in one channel versus the difference in satellite temperatures in two channels is not independent of the difference in satellite sensed equivalent blackbody temperature. The 3.7-μm, 11-μm, and 12-μm channels on the NOAA-n AVHRR can be used in combination to compute atmospheric transmissivity and average atmospheric temperature, but a better combination would be substituting three 0.5-μm-wide channels centered on 11.25 μm, 11.75 μm, and 12.25 μm. A triple window multispectral scanner in the 11–12.5 μm region allows determination of diffuse surface reflectance which can bias sea surface temperatures −0.4 K±0.3 K.

A Two Step Linear Statistical Technique Using Leaps And Bounds Procedure for Retrieval of Geophysical Parameters from Microwave Radiometric Data

A linear statistical technique using leaps and bounds procedure is developed for retrieving geophysical parameters from remote measurements. It is applied to the retrieval of sea surface temperature (SST) from the Scanning Multichannel Microwave Radiometer (SMMR) on the SEASAT Satellite. The technique involves the application of an efficient algorithm to select the best fixed-size subset, of the 10 SMMR channels for linearly retrieving a given geophysical parameter. The 5 channel subset [6.6 V, 6.6H, 10H, 18 V, 21H], where V and H refer to the vertical and horizontal polarizations, respectively and numbers are the channel frequencies in gigahertz, provides the minimum rms error in estimating SST. Comparison with ground truth indicates that the algorithm infers SST with an rms accuracy of better than 1.5K under most environmental conditions. A quality control procedure is proposed which should further improve the accuracy.

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.