MEASUREMENTS OF NEAR-SURFACE OCEAN TEMPERATURE VARIABILITY – CONSEQUENCES ON THE VALIDATION OF AATSR ON ENVISAT. Peter J. Minnett (1) and Brian Ward (2) (1)
Meteorology and Physical Oceanography Rosenstiel School of Marine and Atmospheric Science University of Miami 4600 Rickenbacker Causeway Miami, FL 33149-1098 USA Email:
[email protected] (2)
Geophysical Institute, University of Bergen Allégaten 70, N5007 Bergen, Norway.
Email:
[email protected]
INTRODUCTION The objective of in situ validation of satellite-derived sea-surface temperature (SST) fields is primarily to confirm the validity of the operations and algorithms used to retrieve the SSTs from the spacecraft radiometer measurements. In so doing, the limits of accuracy of the SST retrievals are established. The requirement to relate the satellite-derived SSTs to absolute temperature references is important not only in providing a good measurement with known error characteristics, but also in facilitating the generation of time series longer than the lifetime of a single sensor by merging data from several instruments. Correct validation of the SST fields also helps define the type of problems that can be studied with the satellite-derived data; it is particularly pertinent in climate research where the anticipated signals are small and comparable to the best estimates of currently achievable measurement accuracies from low earth orbit. Satellite-borne instruments offer the best opportunity to detect changes in surface temperature as they provide consistent, global coverage over long periods. The conventional approach of validating satellite-derived SSTs is to compare these with collocated measurements from thermometers, usually mounted on buoys, but this comparison includes variability introduced by vertical temperature gradients in the water between the depth of the in situ thermometer and the sea surface. The temperature of the sea surface interface, the so-called skin temperature, is the source of the electromagnetic emission that is itself the source of the signal measured by the spacecraft radiometer. The effects of the temperature variability are usually assigned to the uncertainty in the satellite measurement. This approach has been followed because of the relative abundance of measurements from buoys, and relative paucity of radiometric measurements of the skin temperatures from ships and aircraft. Where near-surface radiometric measurements are available to validate satellite-derived SSTs, the residual error in the satellite measurements is about half of that derived when in situ measurements are used [1]. The anticipated uncertainties in SST derived from the Advanced Along-Track Scanning Radiometer (AATSR) to be flown on the ENVISAT, like those of the Along-Track Scanning Radiometer (ATSR), are sufficiently small, at ~0.3K, that the effects of vertical temperature gradients in the oceanic near-surface layer can be an important, if not dominant, term in the perceived inaccuracies in the satellite SSTs when these are determined by comparison with bulk temperatures. In this paper we review some of the aspects of the vertical temperature gradients revealed in recent measurements in the open ocean, and discuss how these impact the validation of the SSTs derived from satellite radiometers such as the ATSR and the AATSR. The effects of horizontal gradients and temporal changes on the error budgets of satellite validation have been discussed elsewhere [2].
BACKGROUND The physical behavior of the thermal skin effect (Fig. 1) has a marked consequence on the validation and applications of satellite-derived SST fields. The near-surface temperature gradients are caused by diurnal heating and by the thermal skin effect. Inadequate understanding of the response of these gradients to external forcing, principally wind and heat fluxes, imposes a severe limitation on the full exploitation of satellite-derived surface temperatures, especially in their use with other variables to determine air-sea exchanges. Until recently, the interface temperature structure has been observed only with great difficulty and with coarse vertical resolution [3,4]. This layer, less than 1 mm thick, is often ruptured by breaking waves [5,6], boundary-layer turbulence, rainfall, and other disturbances but re-establishes itself in seconds. Originating in the topmost molecules, the radiometric skin temperature measured by satellites is generally cooler than the bulk water temperature a few mm below due to heat loss by sensible and latent heat fluxes as well as outgoing longwave radiative fluxes [e.g. 7]. This skin - bulk temperature difference has been examined in a growing body of measurements using radiometric determination of the skin temperature and in situ measurements of bulk temperature [8-15]. However, the ‘two point’ (skin and bulk) temperature measurements do not provide information on the shape of the temperature profile. The shape of the profile and the depth of the conductive sublayer have only been described by means of two theoretical models [e.g. 9, 16,17]. Diffusion or boundary layer models assume the flow patterns to be like those near a solid wall in parameterizing the turbulent diffusion coefficient in terms of the distance from the wall [18,19]. Another model is based on surface renewal theory that assumes that the surface water is episodically renewed by bulk water driven by turbulence elements acting on the surface. Between renewal events, the molecular diffusion modifies the temperature profile close to the surface [16,17,20]. Neither model is self-evidently superior to the other in representing the physics of the thermal structure of the interface. The diffusion model assumes a rigid wall as a boundary, neglects important horizontal motion of the free surface [21] while the surface renewal model includes time scales that are in disparity with the periods of capillary waves and microbreaking events [6]. The latter are believed to have an important influence on the exchange of gases [18]. Further problems relating to the structure of the cool skin are the temperature dependence of the gas solubility in sea water [22, 23], irreversible thermodynamic coupling between heat and gas exchange [24] and the interpretation of space-borne infrared SST measurements in conjunction with in situ bulk measurements [1, 7,12]. To attempt to resolve the inherent differences between these models and to understand the nature and behavior of the ocean’s skin layer, observations of the interface temperature profile have been made using fine-wire profilers. These have been employed in the laboratory [3] and in the open sea, but only in a ‘proof-of-concept mode’ [4]. Such measurements in the open ocean pose a severe challenge. An alternative way to measure this gradient makes use of the inherent frequency variations in the absorption properties of water. This technique makes use of highly accurate (RMSE = 0.02 K) radiometric measurements in a range of frequencies whose optical depths pass through the skin layer. When these data are plotted at each frequency's optical depth, laboratory experiments have shown that the resulting "spectral gradients" measure the temperature gradient in the sub-millimeter surface layer [25]. Although this technique has been applied successfully in the open air [15], rather than in the laboratory, the experiments were done at night (to avoid the complicating issue of sunglint reflected at the water surface) and under conditions of elevated heat flux (700 Wm-2), so it is not yet clear whether this technique can be applied to at-sea measurements, where the net heat fluxes are generally much smaller, and the surface conditions are beyond the control of the experimenter. Fig. 1. Sketch of the vertical temperature gradients at the surface of the ocean
However, infrared satellite sensors can only sense the radiometric skin temperature from the topmost molecules. Many recent studies [12,14, 26 - 29] have clearly demonstrated that it is not possible to assume a constant offset between skin and bulk SST (e.g. Fig. 2). One must include both the effects of wind and net air-sea heat flux in determining the nature of the connection between skin and bulk SST. But common practice uses buoy measurements of bulk SST to validate the algorithm used to compute SST from infrared satellite measurements [30, 31], leading to an over-estimate of the uncertainties in the satellite-derived SSTs [1]. To summarize: temperature gradients in the air-water interface, which both control and respond to air-sea heat transfer, are poorly understood because of measurement difficulties. These gradients connect satellite-derived skin temperatures with bulk water temperatures. The variations in the bulk-skin temperature difference are a fundamental problem in validating satellite SST retrieval algorithms [1]. THERMAL SKIN EFFECTS The temperature gradients through the skin layer exist because of the heat exchange between the ocean and atmosphere, and since the ocean is generally warmer than the overlying atmospheric boundary layer, heat usually flows from the ocean to atmosphere, meaning that the skin temperature is cooler than the bulk temperature just below the skin layer. It is sensitive to radiative heat flow, sensible heat flow, and heat loss caused by evaporation at the sea surface. It is present at all times, except in those extremely rare conditions when there is no net heat flow between ocean and atmosphere. The skin temperature can be measured radiometrically using either a radiometer with a pass band determined by a filter, or by an interferometer that measures the infrared emission spectrum of the sea surface. One such device is the Marine – Atmospheric Emitted Radiance Interferometer (M-AERI), which is the source of the skin temperature data discussed here. The M-AERI The M-AERI is a Fourier transform Infrared (FTIR) spectroradiometer that operates in the range of infrared wavelengths from ~3 to ~18µm and measures spectra with a resolution of ~0.5 cm-1. It uses two infrared detectors to achieve this wide spectral range, and these are cooled to ~78oK (i.e. close to the boiling point of liquid nitrogen), by a Stirling cycle mechanical cooler, to reduce the noise equivalent temperature difference to levels well below 0.1K. The M-AERI includes two internal black-body cavities for accurate real-time calibration. A scan mirror directs the field of view from the interferometer to either of the black-body calibration targets or to the environment from nadir to zenith. The mirror is programmed to step through a pre-selected range of angles. When the mirror is angled below the horizon the instrument measures the spectrum of radiation emitted by the sea-surface, and when it is directed above the horizon it measures the radiation emitted by the atmosphere. The sea-surface measurement also includes a small component of reflected sky radiance. The interferometer integrates measurements over a pre-selected time interval, usually a few tens of seconds, to obtain a satisfactory signal-to-noise ratio, and a typical cycle of measurements including two view angles to the atmosphere, one to the ocean, and calibration measurements, takes about five minutes. The M-AERI is equipped with pitch and roll sensors so that the influence of the ship’s motion on the measurements can be determined. The radiometric calibration of the M-AERI is done continuously, for, as with simpler self-calibrating radiometers, an FTIR spectroradiometer can be calibrated by using two black-body targets at known temperatures. These provide two reference spectra to determine the gains and offsets of the detectors and associated electronics. Since the instrument measures interferograms rather than spectra or spectrally integrated radiance (as is the case with a band-pass filter radiometer), it is important that the calibration be independent of the positions of the moving mirrors. This is achieved by very careful assembly, so that the effective aperture size and its projection onto the detectors, is insensitive to path length differences. Further details of the technicalities of FTIR calibration are given by [32]. The mirror scan sequence includes measurements of the reference cavities before and after each set of spectra from the ocean and atmosphere. The absolute accuracy of the infrared spectra produced by the M-AERI is determined by the effectiveness of the blackbody cavities as calibration targets. The black-body cavities are copper cylinders with conical end plates, one with a circular orifice to allow the radiation to emerge. The internal walls are painted matte black and the cavity has an effective emissivity of 0.998. During construction, the black-body thermistors are calibrated against thermometers traceable to NIST (National Institute of Standards and Technology) standards. An independent determination of the absolute radiometric accuracy was made during an infrared radiometry workshop held at RSMAS in early 1998 [33]. A water-bath black-body calibration target [34] was provided by NIST and an M-
AERI was set up to measure its temperature at three set-point temperatures. The M-AERI was mounted so the axis of the scan mirror was at the same height as, and orthogonal to, the axis of the black-body cone. The results of the measurements in two clear parts of the spectrum, from each of the two detectors, are shown in Table 1. Table 1. Laboratory tests of M-AERI accuracy (from [15]) SW LW (2510-2515 cm-1) (980-985 cm-1) 20oC +0.013 K +0.010 K 30oC -0.024 K -0.030 K 60oC -0.122 K -0.086 K The mean discrepancies in the M-AERI 02 measurements of the NIST water bath blackbody calibration target in two spectral intervals where the atmosphere absorption and emission are low. Discrepancies are M-AERI minus NIST temperatures. Target Temp.
The skin temperature of the ocean is derived from the calibrated spectra [13,15], and the accuracy of these retrievals was determined by running two M-AERIs side-by-side on the R/V Roger Revelle during a long section form Hawaii to New Zealand. Before mounting on the ship the calibrations of both M–AERIs were checked by measuring the temperature of a third black body target at a known temperature. Both M–AERIs measured the temperature of this target with uncertainties of
