Super Cyclone Induces a Mesoscale Phytoplankton Bloom in the Bay of Bengal

Tropical cyclones when on land create havoc, but over the oceans they can trigger a very strong biological response, giving rise to phytoplankton blooms. The Super Cyclone (TC) 05B that occurred during October 25–29, 1999, in the Bay of Bengal over the tropical Indian ocean was one of the most significant tropical cyclones on record to affect India, with maximum winds of 240 km/h, and the worst since 1971. Using satellite data, it is found that this tropical super cyclone helped spawn a notable mesoscale phytoplankton bloom in the domain (17 $^{circ}$–20$^{circ} hbox{N}$; 87$^{circ}$–90 $^{circ} hbox{E}$), which persisted for over a month. The bloom spanned 440 km zonally and 330 km meridonally, enhanced the chlorophyll-$a$ concentrations to a maximum of 10 $hbox{mg/m}^{3}$ and the net primary productivity by 200%. Furthermore, a cyclonic eddy over the bloom region is revealed from an ocean general circulation model simulation, helping the bloom to last for over month.      

Multi$^{3}$Scat—A Helicopter-Based Scatterometer for Snow-Cover and Sea-Ice Investigations

A helicopter-based Doppler scatterometer (Multi$^{3}$Scat) is described. It allows simultaneous measurements of the surface radar backscatter at five different frequencies at co- and cross-polarization at incidence angles of 20$^{circ}$ –65$^{circ}$ from an altitude of 30–300 m. Video and infrared (IR) cameras simultaneously sense the surface in the scatterometers' footprint. The Multi $^{3}$Scat is calibrated using measurements carried out over corner reflectors. The stability of the Multi$^{3}$Scat's signal is found to be, on average, better than 0.5 dB. Typical signal-to-noise-ratio values for sigma-0 range between 10 and 20 dB for cross-polarization and between 15 and 25 dB for copolarization over snow and ice surfaces. The potential of the Multi$^{3}$Scat to acquire multifrequency multipolarization radar backscatter data and coincident video and IR temperature observations at different incidence angles over remote terrain such as the Arctic Ocean or the Alps is demonstrated.      

Optimizing $sigma^{0}$ Information From the Jason-2 Altimeter

A radar altimeter's normalized backscatter, $sigma^{0}$, is used in many oceanographic applications to infer values of wind speed, wind stress, rain rate, and the presence of biogenic slicks. The waveform retracker used to estimate the key geophysical variables for the altimeters on the Jason-1 and Jason-2 satellites shows increased small-scale variability since the problem is ill-conditioned. A simple empirical adjustment to $sigma^{0}$ improves the separability between various parameters and also improves the along-track profiles of $sigma^{0}$. This leads to the following: 1) more realistic wind fields; 2) better discrimination of rain events; and 3) improved comparison between the Jason-1 and Jason-2 altimeters during their tandem mission.      

Parameterization of the Land Parameter Retrieval Model for L-Band Observations Using the NAFE'05 Data Set

The Land Parameter Retrieval Model (LPRM) has been successfully applied to retrieve soil moisture from space-borne passive microwave observations at C-, X-, or Ku-band and high incidence angles (50 $^{circ}$–55$^{circ}$ ). However, LPRM had never been applied to lower angles or to L-band observations. This letter describes the parameterization and performance of LPRM using aircraft and ground data from the National Airborne Field Experiment 2005. This experiment was undertaken in November 2005 in the Goulburn River catchment, which is located in southeastern Australia. It was found that model convergence could only be achieved with a temporally dynamic roughness. The roughness was parameterized according to incidence angle and soil moisture. These findings were integrated in LPRM, resulting in one uniform parameterization for all sites. The parameterized LPRM correlated well with field observations at 5-cm depth ($r = 0.93$ based on all sites) with a negligible bias and an accuracy of 0.06 $hbox{m}^{3}cdot hbox{m}^{-3}$. These results demonstrate comparable retrieval accuracies as the official SMOS soil-moisture retrieval algorithm (L-MEB), but without the need for the ancillary data that are required by L-MEB. However, care should be taken when using the proposed dynamic roughness model as it is based on a limited data set, and a more thorough evaluation is necessary to test the validity of this new approach to a wider range of conditions.      

Satellite Observations on Cyclone-Induced Upper Ocean Cooling and Modulation of Surface Winds—A Study on Tropical Ocean Region

In this letter, we evaluate the relationships between the sea-surface temperatures (SSTs) and meteorological parameters over the Bay of Bengal region, India, using microwave satellite remote sensing data. Most of the cyclones in this region occur during the premonsoon period in April–June and are associated with SSTs greater than 26 $^{circ}hbox{C}$. We particularly analyzed the data from two recent cyclonic events: Mala that occurred in April 24, 2006 and Tropical Cyclone 01B (TC 01B) that occurred in May 11, 2003. We used two different remote sensing data sets, sea surface temperature (SST) from the Tropical Rainfall Measurement Mission and the NASA QuikSCAT ocean surface wind vectors to characterize the ocean–atmosphere interactions in cold SST regions formed in the trail of the aforementioned two cyclone events. The results from the satellite data analysis suggested the systematic weakening of wind speed over the cold patch, along the trail of the cyclone. A cooling of around 4$^{circ}$–5 $^{circ}$ was observed to be associated with the passage of cyclone Mala. Wind speed gradually increased from 2 to 9 m/s from the center to the boundary of the cold patch and showed good correlation with SST $(r = 0.97)$. These observations have been validated with another cyclone data (TC 01B) over the Bay of Bengal region that occurred during May 2003. Our results were consistent with the Wallace hypothesis that SST modulates the surface winds via stability.      

Using Passive Microwave Response to Soil Moisture Change for Soil Mapping: A Case Study for the Livingstone Creek Catchment

The 46-$hbox{km}^{2}$ Livingstone Creek Catchment in southeastern Australia was flown with a passive microwave airborne remote sensor four times throughout the three-week National Airborne Field Experiment in 2006, with a spatial resolution of $sim$200 m. Both continuous and discrete measurements of soil moisture were taken to help with interpretation of results. The catchment was experiencing extreme drought conditions leading up to the experiment, and as a result, ground cover in the catchment was minimal with many paddocks consisting of sparse dry stubble and grass. During the experiment period of November 2006, 30 mm of rainfall occurred, with the catchment going from parched dry conditions to surface wet conditions and back to dry conditions again in a short period of time. Changes in moisture responses observed by the airborne passive microwave sensor were field verified to reflect the different geology, soil, and landform elements of the catchment. Consequently, this study suggests that passive microwave remote sensing has potential as a tool to assist with soil mapping, through detecting changes in soil moisture spatial and temporal patterns.      

Approximations of the Planck Function for Models and Measurements Into the Submillimeter Range

A brightness temperature is defined as a linear function of the Planck radiance, with the linear coefficients optimized to minimize the difference between the brightness temperature and the physical temperatures of atmospheric and terrestrial emitters. Radiative transfer (RT) calculations can be accelerated by formulating the integration in terms of this brightness temperature while producing output in terms of radiance or brightness temperature. Approximation errors are $≪ 0.012$ K for RT model applications up to 400 GHz, for any upward, downward, or limb-view geometry, which is about an order of magnitude smaller than for the common brightness temperature derived from a second-order expansion of the Planck function. When products of an RT model that uses this optimized Planck approximation are compared with measurements and the measured radiance is high (equivalent brightness temperature is $≫ 170$ K), it can be advantageous to apply a complementary approximation to the measurements to benefit from error compensation between the model and the measurements. Alternatively, error compensation can be obtained if the calibration and RT equations use consistent brightness temperature approximations.      

Seismic Attenuation Estimation From Instantaneous Frequency

An approach is proposed for quality ($Q$) factor estimation from the variation of envelope peak instantaneous frequency (EPIF). For a frequency-independent $Q$ model, assuming that the propagating wavelet can be modeled by a Gaussian function with constant phase, an approximate analytic relation between $Q$ and EPIF variation is derived. Synthetic tests show that the EPIF method has higher resolution and is less sensitive to noise and interference reflection than common methods. The field test of reflection seismic data indicates that the zone of lower $Q$ -factors corresponds well to the gas reservoir.      

Improved Fraunhofer Line Discrimination Method for Vegetation Fluorescence Quantification

This letter presents a modification to the established Fraunhofer line discrimination (FLD) method for improving the accuracy of the solar-induced chlorophyll fluorescence (ChF) retrieval over terrestrial vegetation. The FLD method relies on the decoupling of reflected and ChF emitted radiation by the evaluation of measurements inside and outside the absorption bands. The improved FLD method introduces two correction coefficients that relate the values of the fluorescence and the reflectance inside and outside the absorption band. The new method uses the full spectral information around the absorption band to derive these coefficients. A sensitivity analysis has been performed to evaluate the impact of the correction coefficients on the accuracy of the ChF estimation. The new formulation has been tested for the $hbox{O}_{2}$ A-band on synthetic data obtaining lower errors in comparison to the standard FLD and has been successfully applied to real measurements at canopy level.      

Support-Based Implementation of Bayesian Data Fusion for Spatial Enhancement: Applications to ASTER Thermal Images

In this letter, a general Bayesian data fusion (BDF) approach is proposed and applied to the spatial enhancement of ASTER thermal images. This method fuses information coming from the visible or near-infrared bands (15 $times$ 15 m pixels) with the thermal infrared bands (90 $times$ 90 m pixels) by explicitly accounting for the change of support. By relying on linear multivariate regression assumptions, differences of support size for input images can be explicitly accounted for. Due to the use of locally varying variances, it also avoids producing artifacts on the fused images. Based on a set of ASTER images over the region of Lausanne, Switzerland, the advantages of this support-based approach are assessed and compared to the downscaling cokriging approach recently proposed in the literature. Results show that improvements are substantial with respect to both visual and quantitative criteria. Although the method is illustrated here with a specific case study, it is versatile enough to be applied to the spatial enhancement problem in general. It thus opens new avenues in the context of remotely sensed images.      

Dielectric-Covered Ground Reflectors in GPS Multipath Reception—Theory and Measurement

Global positioning system receivers sometimes operate under severe multipath conditions, including those which include a ground specularly reflected signal along with a direct signal. Here, such a case is discussed which involves a dielectric-covered flat ground reflector, with incident energy at 1.57542-GHz right-hand circularly polarized at elevation angles between 5$^{circ}$ and 50 $^{circ}$. The relative received powers produced by the sum of the specularly reflected and direct signals are computed from conventional theory and are measured for various thicknesses of dielectrics. Both theory and measurement show that the received powers produced by the sum of the specularly reflected and direct signals have the same behavior throughout a range of elevation angles. A snow case study shows potential for inferring snow depth by fitting the theory to the measurements.      

Extinction Behavior of Soil at 26.5 to 110 GHz

Soil electromagnetic properties at the microwave frequencies have been extensively documented in the literature. However, similar information at the higher millimeter frequencies is not available. A laboratory experiment was conducted to investigate the extinction behavior of wet and dry soil at millimeter wavelengths (26.5–110 GHz). For dry soil, the extinction coefficient increased from 0.02 to 0.6 $hbox{cm}^{-1}$ as the frequency increased from 26.5 to 110 GHz. The presence of even a small amount of water in the soil (5% by weight) reduced the penetration of millimeter wave signals into soil by a factor of ten.      

An Assessment of QuikSCAT Ku-Band Scatterometer Data for Soil Moisture Sensitivity

The QuikSCAT enhanced (2.225-km) backscattering product is investigated for sensitivity to changes in soil moisture and its potential for spatial disaggregation of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture. Specifically, an active–passive methodology based on temporal change detection is tested using data from the 2006 National Airborne Field Experiment data set. This campaign was carried out from October 29 to November 20, 2006 in a 60 km $times$ 40 km area of the Murrumbidgee catchment, southeast Australia. Temporal change detection analysis and accuracy in terms of spatial pattern distribution throughout the domain were assessed using a passive microwave airborne product derived from the Polarimetric L-band Multibeam Radiometer at 1-km spatial resolution. QuikSCAT–AMSR-E intercomparisons indicated higher correlations when using C-band observations. The greatest sensitivity to soil moisture was observed when using V-polarized backscatter measurement. While backscattering data showed adequate temporal sensitivity to changes in soil moisture due to precipitation events, the spatial agreement was complicated by the presence of irrigation and standing water (rice fields). This resulted in low Cramer's Phi values (less than 0.06), which were used as a measure of spatial correspondence in terms of change in soil moisture and backscatter. In addition, the high QuikSCAT sensor frequency and existence of noise in the observed data contributed to the observed discrepancies.      

An Automatized Frequency Analysis for Vine Plot Detection and Delineation in Remote Sensing

The availability of an automatic tool for vine plot detection, delineation, and characterization would be very useful for management purposes. An automatic and recursive process using frequency analysis (with Fourier transform and Gabor filters) has been developed to meet this need. This results in the determination of vine plot boundary determination and accurate estimation of interrow width and row orientation. To foster large-scale applications, tests and validation have been carried out on standard very high spatial resolution remotely sensed data. About 89% of vine plots are detected corresponding to more than 84% of vineyard area, and 64% of them have correct boundaries. Compared with precise on-screen measurements, vine row orientation and interrow width are estimated with an accuracy of 1$^{circ}$ and 3.3 cm, respectively.      

Slope correction for ocean radar altimetry

We develop a slope correction model to improve the accuracy of mean sea surface topography models as well as marine gravity models. The correction is greatest above ocean trenches and large seamounts where the slope of the geoid exceeds 100  \(\upmu \) rad. In extreme cases, the correction to the mean sea surface height is 40 mm and the correction to the along-track altimeter slope is 1–2  \(\upmu \) rad which maps into a 1–2 mGal gravity error. Both corrections are easily applied using existing grids of sea surface slope from satellite altimetry.     

Soft-Computing Modelling of Seismicity in the Southern Hellenic Arc

This letter investigates the possible coalition of time intervals and patterns in seismic activity during the preparation process of consecutive sizeable seismic events (i.e., $M_{S} geq 5.9$). During periods of low-level seismic activity, stress processes in the crust accumulate energy at the seismogenic area, while larger seismic events act as a decongesting mechanism that releases considerable amounts of that energy. Monthly mean seismicity rates have been introduced as a tool to monitor this energy management system and to divert this information into an adaptive neuro-fuzzy inference system. The purpose of the neuro-fuzzy model is to identify and to simulate the possible relationship between mean seismicity rates and time intervals among consecutive sizeable earthquakes. Successful training of the neuro-fuzzy model results in a real-time online processing mechanism that is capable of estimating the time interval between the latest and the next forthcoming sizeable seismic event.      

Assessing the SMOS Soil Moisture Retrieval Parameters With High-Resolution NAFE'06 Data

The spatial and temporal invariance of Soil Moisture and Ocean Salinity (SMOS) forward model parameters for soil moisture retrieval was assessed at 1-km resolution on a diurnal basis with data from the National Airborne Field Experiment 2006. The approach used was to apply the SMOS default parameters uniformly over 27 1-km validation pixels, retrieve soil moisture from the airborne observations, and then to interpret the differences between airborne and ground estimates in terms of land use, parameter variability, and sensing depth. For pastures (17 pixels) and nonirrigated crops (5 pixels), the root mean square error (rmse) was 0.03 volumetric (vol./vol.) soil moisture with a bias of 0.004 vol./vol. For pixels dominated by irrigated crops (5 pixels), the rmse was 0.10 vol./vol., and the bias was $-$0.09 vol./vol. The correlation coefficient between bias in irrigated areas and the 1-km field soil moisture variability was found to be 0.73, which suggests either 1) an increase of the soil dielectric roughness (up to about one) associated with small-scale heterogeneity of soil moisture or/and 2) a difference in sensing depth between an L-band radiometer and the in situ measurements, combined with a strong vertical gradient of soil moisture in the top 6 cm of the soil.      

Geodetic methods to determine the relativistic redshift at the level of 10$$^{}$$ in the context of international timescales: a review and practical results

The frequency stability and uncertainty of the latest generation of optical atomic clocks is now approaching the one part in \(10^{18}\) level. Comparisons between earthbound clocks at rest must account for the relativistic redshift of the clock frequencies, which is proportional to the corresponding gravity (gravitational plus centrifugal) potential difference. For contributions to international timescales, the relativistic redshift correction must be computed with respect to a conventional zero potential value in order to be consistent with the definition of Terrestrial Time. To benefit fully from the uncertainty of the optical clocks, the gravity potential must be determined with an accuracy of about \(0.1\,\hbox {m}^{2}\,\hbox {s}^{-2}\), equivalent to about 0.01 m in height. This contribution focuses on the static part of the gravity field, assuming that temporal variations are accounted for separately by appropriate reductions. Two geodetic approaches are investigated for the derivation of gravity potential values: geometric levelling and the Global Navigation Satellite Systems (GNSS)/geoid approach. Geometric levelling gives potential differences with millimetre uncertainty over shorter distances (several kilometres), but is susceptible to systematic errors at the decimetre level over large distances. The GNSS/geoid approach gives absolute gravity potential values, but with an uncertainty corresponding to about 2 cm in height. For large distances, the GNSS/geoid approach should therefore be better than geometric levelling. This is demonstrated by the results from practical investigations related to three clock sites in Germany and one in France. The estimated uncertainty for the relativistic redshift correction at each site is about \(2 \times 10^{-18}\).     

The first Australian gravimetric quasigeoid model with location-specific uncertainty estimates

We describe the computation of the first Australian quasigeoid model to include error estimates as a function of location that have been propagated from uncertainties in the EGM2008 global model, land and altimeter-derived gravity anomalies and terrain corrections. The model has been extended to include Australia’s offshore territories and maritime boundaries using newer datasets comprising an additional \({\sim }\)280,000 land gravity observations, a newer altimeter-derived marine gravity anomaly grid, and terrain corrections at \(1^{\prime \prime }\times 1^{\prime \prime }\) resolution. The error propagation uses a remove–restore approach, where the EGM2008 quasigeoid and gravity anomaly error grids are augmented by errors propagated through a modified Stokes integral from the errors in the altimeter gravity anomalies, land gravity observations and terrain corrections. The gravimetric quasigeoid errors (one sigma) are 50–60 mm across most of the Australian landmass, increasing to \({\sim }100\) mm in regions of steep horizontal gravity gradients or the mountains, and are commensurate with external estimates.     

Error analysis of the NGS’ surface gravity database

Are the National Geodetic Survey’s surface gravity data sufficient for supporting the computation of a 1 cm-accurate geoid? This paper attempts to answer this question by deriving a few measures of accuracy for this data and estimating their effects on the US geoid. We use a data set which comprises ${\sim }1.4$ million gravity observations collected in 1,489 surveys. Comparisons to GRACE-derived gravity and geoid are made to estimate the long-wavelength errors. Crossover analysis and $K$ -nearest neighbor predictions are used for estimating local gravity biases and high-frequency gravity errors, and the corresponding geoid biases and high-frequency geoid errors are evaluated. Results indicate that 244 of all 1,489 surface gravity surveys have significant biases ${>}2$  mGal, with geoid implications that reach 20 cm. Some of the biased surveys are large enough in horizontal extent to be reliably corrected by satellite-derived gravity models, but many others are not. In addition, the results suggest that the data are contaminated by high-frequency errors with an RMS of ${\sim }2.2$  mGal. This causes high-frequency geoid errors of a few centimeters in and to the west of the Rocky Mountains and in the Appalachians and a few millimeters or less everywhere else. Finally, long-wavelength ( ${>}3^{\circ }$ ) surface gravity errors on the sub-mGal level but with large horizontal extent are found. All of the south and southeast of the USA is biased by +0.3 to +0.8 mGal and the Rocky Mountains by $-0.1$ to $-0.3$  mGal. These small but extensive gravity errors lead to long-wavelength geoid errors that reach 60 cm in the interior of the USA.