An approximate model for the microwave brightness temperature of the sea

Abstract

A modified two-scale model is proposed for scattering and emissivity calculations for certain classes of random rough surfaces. It is based on an approach by Burrows and by Brown, but it has been extended to bistatic scattering by lossy dielectric surfaces, and it incorporates modified Fresnel reflection coefficients and a simple correction for multiple-scattering effects. The method is shown to be applicable to the ocean surface for light and moderate winds. A contracted form of the radiative-transfer equation is proposed and the included Wentz correction for surface scattering is discussed. This could lead to a method that could be both simple and accurate enough for real-time inversion algorithms in microwave remote sensing.     

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     

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.     

Simulating the effect of spatial variability of soil hydraulic properties on microwave brightness temperature over a corn field

Spatial variability of L-band (21?cm wavelength) microwave brightness temperature over a corn field, caused by spatial heterogeneity of soil hydraulic properties, is simulated by combining physically based models for microwave emission and for dynamics of soil water. The scaling theory is used for the spatial variability of soil hydraulic parameters, the scaling parameter being represented by a histogram corresponding to a log-normal frequency distribution. The mean and the standard deviation of brightness temperatures over a corn field are calculated as a saturated soil dries progressively under clear-sky conditions. Results are presented for two values for the coefficient of variation (CV)of the scaling parameter, namely 0·45 and 0·65, which encompass the range of a few available field observations. For CV=0·45, the mean brightness temperatures are higher and the standard deviations are lower by about 2 deg K compared with those for CV = 0·65. Results of the present simulation suggest that spatial variability of hydraulic parameters might not be an important consideration for interpreting mean brightness temperatures over reasonably large (a few hectares or larger)vegetated fields, although some information about the frequency distribution of hydraulic parameters would be needed in interpreting the standard deviation of the brightness temperature.     

Model for atmospheric corrections to microwave brightness temperature data

The effects of atmospheric liquid water (cloud) and water vapor on the brightness temperature data acquired by Bhaskara-Satellite Microwave Radiometer at 19.1 and 22.235 GHz near the nadir look angle have been discussed in detail. It has been observed that the net contribution to brightness temperature data due to atmosphere is quite considerable over sea and wet land conditions. Two operational quasistatistical models have been developed for doing atmospheric corrections to brightness temperature data, one applicable under cloud-free conditions and the other under all weather conditions. The physical concepts to arrive at these quasistatistical models have been discussed. The constants of the models are estimated by the method of least squares fit by simulating 200 sets of atmospheric and ground conditions. The root mean square errors in the brightness temperature after applying atmospheric corrections are estimated to be 0.5 and 4 K under cloud-free and all weather conditions respectively. A detailed discussion on the validity and applicability of the models is also presented.     

The decorrelation time of microwave radar echoes from the sea surface†

The case is considered of a CW microwave radar looking at the sea surface at moderate angles of incidence. This is treated using the ‘facet’ concept, in which the sea surface is considered as being covered by spatially uncorrelated facets, each a small number of Bragg wavelengths across and being transported by the particle velocities in the longer sea waves. The facets are considered to have an unknown decorrelation time. In two cases simplifications allow approximate numerical values for the coherent decorrelation time of the radar return to be calculated. These are compared with measured bandwidths and decorrelation times reported in the literature. These agree adequately with the theory and indicate that the facet decorrelation time is long. However, some properly thought-out measurements of coherent decorrelation time are badly needed.     

A simple retrieval method for land surface temperature and fraction of water surface determination from satellite microwave brightness temperatures in sub-arctic areas

A strong linear relationship is found between Special Sensor Microwave/Imager (SSM/I) microwave (19 and 37 GHz) surface emissivities at horizontal and vertical polarizations over snow- and ice-free land surfaces. This allows retrieving the land surface emissivity and temperature from satellite microwave brightness temperatures after atmospheric corrections. Over the Canadian sub-arctic continental area, we show that the main factor modifying the emissivity is the fraction of water surface (FWS) within a pixel. Accordingly, a map of the fraction of water surface across the Canadian landmass is derived, given a correspondence within 6% as compared to the 1 km² Canadian National Topographic Database of water-covered areas. The microwave-derived surface temperatures are compared to synchronous in situ air and ground surface temperatures and also with independent satellite IR measurements over areas without snow or ice. Root mean square differences range between 2° and 3.5°, with mean bias error of the order of 1-3°. Better results are always obtained with the 37 GHz channel rather than with the 19 GHz channel. Over dense vegetation, the microwave-derived surface temperature is closer to the air temperature (at surface level) than to the ground temperature. The proposed simple retrieval algorithm, not sensitive to cloud cover, appears very useful for monitoring summer interannual or seasonal trends of the fraction of surface water, as well as the daily land surface temperature variation, which are very important parameters in environmental change analysis.     

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.     

The satellite-measured sea surface temperature change in the Gulf of Finland

Climate change in Baltic region and in the Gulf of Finland is an accomplished fact in human brains and in science. The purpose of this research is to retrieve quantitative level of changes for sea surface temperature (SST) of the Gulf of Finland. Two space systems National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) and Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) provided satellite data about temperature of the sea surface. SST data covers period 1981–2014 and includes 444 monthly data scenes with spatial resolution about 10 km. Data quality analysis displays high reliability of NOAA/AVHRR and Aqua/MODIS satellite information. The Gulf of Finland’s average annual SST has changed from 6.8°C in 1982 up to 8.2°C in 2014. Its mean speed of warming is about 0.04°C year^–1. The growth of the temperature was irregular, in the middle of 80th year, the temperature dropped down to 5.0°C, and then sharply increased up to 7.3°C in 1989. SST growth in the Gulf of Finland coincides with air temperature and sea temperature growth. The climate change in the Gulf of Finland has special significance due to the fragility of the northern ecosystems and high anthropogenic load.     

The relationship between brightness temperature and soil moisture Selection of frequency range for microwave remote sensing

Abstract

The analysis of brightness temperature data acquired from field and aircraft experiments demonstrates a linear relationship between soil moisture and brightness temperature. However, the analysis of brightness temperature data acquired by the Skylab radiometer demonstrates a non-linear relationship between soil moisture and brightness temperature. In view of the above and also because of recent theoretical developments for the calculation of the dielectric constant and brightness temperature under varying soil moisture profile conditions, an attempt is made to study the theoretical relationship between brightness temperature and soil moisture as a function of frequency. Through the above analysis, the appropriate microwave frequency range for soil moisture studies is recommended.     

Interpretation of Nimbus-7 37 GHz microwave brightness temperature data in semi-arid southern Africa

Abstract

Monthly 37 GHz microwave polarization difference temperatures (MPDT) derived from the Nimbus-7 scanning multichannel microwave radiometer (SMMR) for southern Africa from 1979 to 1985 are compared with rainfall and Advanced Very High Resolution Radiometer (AVHRR) normalized difference vegetation index (NDVI) data. MPDT rose sharply during a drought episode which occurred within the period included in the data. The rise was seen not only in the growing season, but also in the dry season MPDT when no actively photosynthetic, water-containing leaves are present. The results suggest that scattering of the emitted microwave radiation by dead and living vegetation is a more important factor than has previously been recognized. The sensitivity of MPDT to small quantities of dry vegetation encourages the hope that standing dead vegetation and plant litter may be remotely sensed. In the absence of vegetation, rough terrain reduced the MPDT whereas a damp surface increased it.     

The extension of the split window technique to passive microwave surface temperature assessment

The theoretical study of both land and sea surface temperature remote sensing is treated through investigating the extension to the microwave region (1-100GHz) of the split window technique, usually used in the thermal infrared region for sea surface temperature measurements. The study of land surface temperature shows that, in both regions (infrared and microwave), the influence (of atmospheric water vapor content and surface emissivity) is critical. The theory is based on the Radiative Transfer Equation, which assumed solutions can be given in both spectral regions, with respect to Wien's and Rayleigh-Jean's laws, respectively. The surface temperature determination is studied in connection with the surface emissivity in both infrared and microwave regions determined with an iterative process. Infrared data is provided by the sensor Advanced Very High Resolution Radiometer (AVHRR) and microwave data by Special Sensor Microwave/Imager (SSM/I), through the WETNET program, directed by NASA/HQS.     

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.     

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.     

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.     

Analysis of microwave brightness temperature of lunar surface and inversion of regolith layer thickness:Primary results of Chang-E 1 multi-channel radiometer observation

In China’s first lunar exploration project, Chang-E 1 (CE-1), a multi-channel microwave radiometer was aboard the satellite, with the purpose of measuring microwave brightness temperature from lunar surface and surveying the global distribution of lunar regolith layer thickness. In this paper, the primary 621 tracks of swath data measured by Chang-E 1 microwave radiometer from November 2007 to February 2008 are collected and analyzed. Using nearest neighbor interpolation based on the sun incidence angle in ...     

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.     

The effect of brightness on colour recognition under water

Abstract

Water distorts the colours of objects compared to the situation in air, and it is relevant to enquire how this affects divers' colour recognition. Twelve divers (eight in the laboratory and four in a field experiment) were required to determine the distances at which colours could be correctly identified in different types of water. Changing a target's brightness (keeping hue and saturation constant) significantly changed its recognition distance. In addition, reducing the reflectance of a target having a similar hue to that of the background reduced its recognition distance relatively more than targets with hues offset from that of the background. Consequently, classification by hue name alone was insufficient to allow an unambiguous rank ordering of the relative recognition distances of the different colours. In situ light measurements in the field study permitted the specification of the spectral characteristics of the targets and their visual background. Such data are important if a colour recognition model is to be established for situations involving gross spectral distortion.