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.     

Detection of small-scale roughness and refractive index of sea ice in passive satellite microwave remote sensing

Polar ice masses and sheets are sensitive indicators of climate change. Small-scale surface roughness significantly impacts the microwave emission of the sea ice/snow surface; however, published results of surface roughness measurements of sea ice are rare. Knowing the refractive index is important to discriminate between objects. In this study, the small-scale roughness and refractive index over sea ice are estimated with AMSR-E observations and a unique method. Consequently, the small-scale surface roughness of 0.25 cm to 0.5 cm at AMSR-E 6.9 GHz shows reasonable agreement with the results of known observations, ranging from 0.2 cm to 0.6 cm for the sea ice in the Antarctic and Arctic regions. The refractive indexes are retrieved from 1.6 to 1.8 for winter, from 1.2 to 1.4 for summer in the Arctic and the Antarctic, which are similar to those of the sea ice and results from previous studies. This research shows the physical characteristics of the sea ice edges and melting process. Accordingly, this investigation provides an effective procedure for retrieving the small-scale roughness and refractive index of sea ice and snow. Another advantage of this study is the ability to distinguish sea ice from the sea surface by their relative small-scale roughness.     

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.     

Influence of sea surface emissivity model parameters at L-band for the estimation of salinity

In order to prepare the Soil Moisture and Ocean Salinity (SMOS) mission, we present sensitivity studies on a two-scale sea surface emissivity model used to compute brightness temperatures ( T B ) from the Sea Surface Temperature (SST), the wind vector, the incidence angle and the Sea Surface Salinity (SSS). We analyse the impact of uncertainties of the model on T B at 1.4 GHz ( u 0 = 21 cm), namely we determine the influence of the parametrization of the sea surface permittivity and of the cutoff wavelength u d (the limit which separates the short scales of the wave spectrum from the large scales). Using two existing permittivity parametrizations we find differences on T B ranging from 0.4 to 1.1 K. For SST warmer than 12°C and incidence angles smaller than 35°, the difference on T B is a bias independent of SSS and weakly dependent on SST. For these small incidence angles, the choice of the cutoff wavelength does not lead to significant differences on T B . For incidence angles larger than 40°, the permittivity parametrization and the choice of u d are more critical, resulting in a variation of T B of several tenths of a Kelvin.     

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.     

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.     

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.     

Antarctic ice sheet and sea ice regional albedo and temperature change, 1981-2000, from AVHRR Polar Pathfinder data

Spring-summer (November, December, January) ice sheet and sea ice regional surface albedo, surface temperature, sea ice concentration and sea ice extent averages and trends from 1981 to 2000 have been calculated for the Antarctic area. In this research the AVHRR Polar Pathfinder 5-km EASE-Grid Composites and the combined SMMR and SSMI data sets from the National Snow and Ice Data Center (NSIDC), Boulder, Colorado have been employed. A regional analysis has been made for five longitudinal sectors around Antarctica: the Weddell Sea (WS), the Indian Ocean (IO), the Pacific Ocean (PO), the Ross Sea (RS) and the Bellingshausen-Amundsen Sea (BS). The IO and PO sectors show ice sheet albedos of 0.85 and temperatures of − 25 °C. The corresponding values in the RS and BS sectors are 0.80 and − 16 °C respectively. The sea ice albedo is about 0.60 in the RS, BS and WS sectors and 0.55 in the IO and PO sectors. The average sea ice temperature varies around − 12 °C. All the sectors show slight increasing spring-summer albedo trends and decreasing spring-summer temperature trends and similar interannual variability in albedo and surface temperature. The steepest ice sheet albedo trend of 0.0019 ± 0.0009/yr is found in the RS sector. The steepest sea ice albedo trend of 0.0044 ± 0.0017 /yr occurs in the PO sector. The steepest temperature trends for both the ice sheet and sea ice occur in the BS sector, having values of − 0.075 ± 0.040 °C/yr and − 0.107 ± 0.027 °C/yr respectively. The sea ice concentration shows slight increasing trends, the highest being in the PO sector (0.3 ± 0.12%/yr), whereas the sea ice extent trends are near zero with the exception of the RS sector (14,700 ±8600 km²/yr) and the BS sector (− 13,000 ± 6400 km²/yr).     

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.     

Studies of the Antarctic sea ice edge and ice extent from satellite and ship observations

Passive microwave-derived ice edge locations in the Antarctic are assessed against in situ observations from ships between 1989 and 2000. During the growth season (March-October), the ship data agrees with satellite data very well, with r² values of 0.99 and 0.97 for the Bootstrap and Team algorithms, respectively. During the melt season (November-February), the agreement is not so good with the passive microwave ice edge typically 1-2° of latitude south of the observations. This is due to the low concentration and saturated nature of the ice, and the r² values for this period are 0.92 and 0.80 for the Bootstrap and Team algorithms, respectively. Sensitivity studies show that such an offset in the summer ice edge location can cause significant errors in trend studies of the extent of sea ice cover in the Southern Ocean. The passive microwave ice concentration at the ice edge observed by ship varies greatly, averaging 14% for the Team algorithm and 19% for the Bootstrap. Comparisons between passive microwave data and SAR, Landsat and OLS data during the ice growth season show that while small-scale details in ice edge location are lost, the passive microwave data generally provide good and consistent representation of the higher resolution imagery.     

A new technique to sense non-Gaussian features of the sea surface from L-band bi-static GNSS reflections

We present a new technique to analyze L-band signals of the Global Navigation Satellite System (GNSS) that have rebounded off the sea surface, with the aim of retrieving information about surface roughness in the form of the effective Probability Density Function (PDF) of the slopes. Unlike earlier techniques, which parameterize the PDF (usually as normal bivariate distributions), this approach does not constrain the surface slopes' PDF to the shape of a particular analytical distribution. This may help to understand the real information content of L-band scattered signals, which is currently unclear. After validating the algorithm by means of end-to-end simulations, we have applied it to real data. The tests on real data show that the retrievals are robust, consistent with the results obtained with standard GNSS-reflection techniques, and in agreement with independent sources of information. Moreover, the retrieved slopes' PDF present non-Gaussian features, such as skewness. A more in-depth analysis to check whether the skewness is a geophysical signature or an artifact of the technique, shows that it maps with the up-/down-asymmetries introduced by surface forces. In particular, this is the first time that GNSS-reflections have sensed and identified the up- and down-wind signature on the surface, putting and end to the 180° ambiguity that was usually attributed to GNSS observations of directional roughness.     

Temporal and spatial variability of satellite sea surface temperature and ocean colour in the Japan/East Sea

Temporal and spatial variability of Sea Surface Temperature (SST) and ocean colour in the Japan/East Sea (JES) are examined during winter and spring using satellite data from Advanced Very High Resolution Radiometer (AVHRR) and Sea-viewing Wide Field of view Sensor (SeaWiFS). The timing of the spring phytoplankton bloom and the locations of the chlorophyll fronts are related to changes in the thermal fields and the locations of the temperature fronts. Daily images of SST and chlorophyll concentration show both differences and similarities of bio-optical and thermal front location, depending on region and season. Four sub-regions in the JES were defined and SST and chlorophyll values were extracted from weekly and monthly composite images to derive summary statistics. SST at the Subpolar Front increased about 7°C over a 1.5-month period from late April to early June in 1999. During this same period, elevated chlorophyll values near the Korean coast and in the southern basin decreased sharply as the phytoplankton bloom that first developed in the southern basin progressed to the front and northward. The SST/chlorophyll relationship is complex and seasonal. Near the Subpolar Front, SST and chlorophyll were positively related in April. In May, highest chlorophyll values corresponded to mixing regimes (such as areas of convergence and divergence at the edges of meanders) and, by June, SST and chlorophyll near the front were inversely related.     

Droplet: A virtual brush model to simulate Chinese calligraphy and painting

This paper proposes a virtual brush model based on droplet operation to simulate Chinese calligraphy and traditional Chinese painting in real time. Two ways of applying droplet model to virtual calligraphy and painting are discussed in detail The second droplet model is more elaborated and can produce more vivid results while being slightly more time-consuming. The novel feature of the proposed droplet virtual brush model successfully enables the simulation painting system to overcome the poor expressional ability of virtual brush based on particle system and avoids the complex evaluation of physical brush with solid model. The model, derived from the actual calligraphy and painting experience, due to the simplicity of the droplet operation and its powerful expressive ability, considerably improves the performance of the simulation system and maintains painting effect comparable with real brush by supporting special Chinese brush effect such as dry brush, feng and stroke diffusion.     

Analysis of sea ice motion and deformation using AMSR-E data from 2005 to 2007

Dynamics of Arctic sea ice, including motion and deformation, are studied utilizing data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (EOS) (AMSR-E) during 2005 and 2007. We first derive sea ice motion maps from the satellite data in a grid of 100 km?×?100 km using a two-dimensional wavelet method. These sea ice motion results are compared with those derived from buoy data from the International Arctic Buoy Programme. Secondly, it is well known that sea ice deformation can be characterized by a strain-rate tensor calculated from the ice velocity field. Two components of the strain-rate tensor quantify the divergence and the shearing of the ice field, respectively. Daily maps for both sea ice motion and strain-rate tensor, as well as monthly averages and spatial sums, are computed and analysed. Comparison of the monthly ice motion maps for May 2005 and May 2007 indicates that the anti-cyclonic Beaufort Gyre and Transpolar Drift Stream in the western Arctic are relatively stronger during 2007 than 2005. Different patterns in the spring months' sea ice deformation rates as characterized by the absolute values of the strain-rate tensor are observed when we compare the data of 2007 with those of 2005 and 2006. The sea ice deformation activities in the spring of 2007 happen earlier and are relatively stronger than that of 2005 and 2006. These results might help to explain why the sea ice extent in the summer of 2007 is unprecedentedly low.     

Application of a three-component scattering model over snow-covered first-year sea ice using polarimetric C-band SAR data

In this study we examine the utility of a three-component scattering model to quantify the sensitivity of radar incidence angle over snow-covered landfast first-year sea ice (FYI) during the late winter season. This three-component scattering model is based on (1) surface scattering contributed from the snow-covered FYI (smooth-ice (SI), rough-ice (RI), and deformed-ice (DI) types); (2) volume scattering contributed from snow layers which consist of enlarged snow grains, elevated brine volume, and preferential orientation of snow grains relative to radar look direction, as well as the underlying sea ice; and (3) double-bounce scattering contributed from ice ridges and ice fragments. This study uses RADARSAT-2 C-band polarimetric synthetic aperture radar (POLSAR) data acquired on 15 and 18 May 2009 for Hudson Bay, near Churchill, during late winter with surface air temperatures ≤?8°C at two different incidence angles (29° and 39°). The three-component scattering model is used to discriminate between snow-covered smooth, rough, and deformed FYI. The model shows enhanced discrimination at an incidence angle of 29°, compared with an incidence angle of 39°. The model is then used to quantify the sensitivity of radar incidence angle to each of the three scattering contributors. The results show that the relative fraction of surface scattering dominates for all three FYI types (SI ≈ 77.3%; RI ≈ 66.0%; and DI ≈ 61.1%) at 29° and decreases with increasing incidence angle and surface roughness. Volume scattering is found to be the second dominant mechanism (SI ≈ 19.1%, RI ≈ 32.2%, and DI ≈ 37.4% at 29° and SI ≈ 28.3%, RI ≈ 41.0%, and DI ≈ 49.5% at 39°) over snow-covered FYI and it increases with incidence angle and surface roughness. The double-bounce scattering contribution is low for all FYI types at both incidence angles.     

Learning automaton as a model to simulate and analyse learning behaviour in rats

A technique is presented for using a learning automaton as a model to simulate and analyse learning behaviour in rats, and the usefulness of this model is illustrated. This automaton was proposed as a learning machine by Tsetlin (1961) and refined by Aso and Kimura (1976). Some learning properties of such an automaton are first examined and it is shown that the automaton can be used to simulate a variety of learning behaviour, composed of several kinds of action, by the proper selection of parameters. Secondly, a mathematical model of the learning experiment carried out in our laboratory with rats is formulated as an interactive system between a learning automaton and its environment. Finally, the effectiveness of the mathematical model is discussed and proved through the simulation and analysis of learning behaviour with multiple actions in a specific rat.     

Some active and passive microwave signatures of Antarctic sea ice from mid-winter to spring 1991

Antarctic sea ice is often covered by a deep snow layer which acts as an emitter and a scatterer to microwave radiation leading to possible misinterpretations of ice signatures, particularly at high frequencies. The algorithms for ice identification, based on the observations of the Special Sensor Microwave Imager, at 19GHz (vertical and horizontal polarizations) and 37Ghz (vertical polarization), have proven to be inefficient for distinguishing new and old ice over the Antarctic Ocean. At an equivalent resolution and analysed on a weekly basis, complementary information can be obtained from active microwave measurements provided, at 5·3GHz (vertical polarization), by the Active Microwave Instrument, the scatterometer of ERS–1. Based on data obtained from the end of August to the end of November 1991, during the austral winter and spring radar backscatter is analysed as a function of the incidence angle. At low incidence angles, the derivative of the backscatter is closely related to the water concentration as derived from passive radiometry, whereas, at high incidence angles, the backscatter is mainly due to ice, as the water contribution is strongly reduced. During the whole period, stable features are apparent on the images obtained from the backscattering coefficients at 50°. On those images, higher values characterize the marginal ice zone, the polynya areas and the advected ice within the Ross Sea. At high incidence angles, the strong signatures of deformed/ rough ice depart significantly from the information classically extracted from the radiometers, the brightness temperatures as well as the derived products, polarization, spectral gradient ratios and concentration. It is therefore possible to classify the Antarctic ice cover into geographical clusters where the active microwave signatures can be attributed. to a peculiar ice type. Though those clusters are not totally identified, their stability and the coherence of their patterns show that they are related to geophysical structures. Four backscatter curves, simulating distinct behaviours over the Antarctic region, are proposed for sea water, marginal ice, first-year ice of the inner part of the pack and multi-year ice.     

The impact of measurement uncertainty and spatial variability on the accuracy of skin and subsurface regression-based sea surface temperature algorithms

An ongoing limitation of common regression-based infrared (IR) satellite sea surface temperature (SST) algorithms has been the lack of sufficient in situ skin temperature measurements for derivation of the algorithm coefficients. Since IR brightness temperatures respond to the skin temperature, use of the more numerous subsurface observations to tune the algorithms introduces uncertainty into the resulting SST products. Coincident in situ skin and subsurface SST measurements from three years of cruises are used to derive parallel skin and subsurface multichannel SST (MCSST)-type regression algorithms to determine the extent to which improved accuracy can be obtained using the skin measurements. Through use of only coincident measurements, the advantage offered by the greater volume of available subsurface observations is eliminated. Surprisingly, we find no accuracy improvement using skin SST algorithms relative to algorithms derived from the research-grade ship-borne subsurface temperature measurements used in our analysis. However, better accuracy was found relative to algorithms derived from subsurface observations whose accuracy was degraded to that of buoys. The results are robust with regard to satellite resolution, collocation criteria, geographical regions, and time of day.The accuracy differences are found to be generally consistent with the effects of: (1) increased measurement uncertainty of radiometric measurements relative to research-grade subsurface observations, and (2) differences in spatial variability between the skin SST and temperature-at-depth. The subsurface algorithms are regenerated after degrading the subsurface measurements by adding increasing levels of Gaussian white noise to determine the amplitude of the additional variability required to ensure equal accuracy between the skin and subsurface products. The required supplemental noise ranges between 0.10 and 0.17 K for all data combined and generally decreases with tighter collocation windows and higher-resolution satellite observations. Variogram analysis and filtering of the in situ measurements suggest that differences in measurement uncertainty between the infrared radiometers and the subsurface sensors can explain 0.07-0.10 K of the required noise, while differences in spatial variability with depth can account for up to 0.07-0.10 K of the residual noise. A key consequence is that spatial averages of the skin temperature over satellite footprints of 2 km or more, while potentially biased in the mean, may exhibit less variance relative to point samples of the subsurface temperature than to the actual radiometric skin temperature.     

Concurrent remote sensing of Arctic sea ice from submarine and aircraft

Abstract

In May 1987 a concurrent remote sensing study of Arctic sea ice from above and below was carried out. A submarine equipped with sidescan and upward looking sonar collaborated with two remote sensing aircraft equipped with passive microwave, synthetic aperture radar (SAR), a laser profilometer and an infrared radiometer. By careful registration of the three tracks it has been possible to find relationships between ice type, ice morphology and thickness, SAR backscatter and microwave brightness temperatures. The key to the process has been the sidescan sonar's ability to identify ice type through differences in characteristic topography. Over a heavily ridged area of mainly multiyear ice there is a strong positive correlation between SAR backscatter and ice draft or elevation. We also found that passive and active microwave complement each other in that SAR has a high contrast between open water and multiyear ice, while passive microwave has a high contrast between open water and first-year ice.