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.      

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.      

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.      

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.      

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.      

Orbit Accuracy Requirement for ABYSS: The Space Station Radar Altimeter to Map Global Bathymetry

The Altimetric Bathymetry from Surface Slopes (ABYSS), which is the proposed science payload on the International Space Station (ISS), is a Johns Hopkins University Applied Physics Laboratory-developed flight-proved delay-Doppler phase-monopulse radar altimeter capable of measuring ocean surface slope in the 6–200-km half-wavelength frequency band range with an accuracy of 0.5 $muhbox{rad}$ , with autonomous gimbal control to compensate for the ISS structural motions. This measurement allows an improved mapping of the global bathymetry, enabling a wide range of scientific research works and applications. The nonrepeat ISS orbital ground track is ideal for ABYSS. This letter describes a simulation study on the effects of the Earth's gravity field and other errors, including thermal bending of the ISS, on the orbit determination of the altimeter instrument antenna phase center location, fulfilling the science objectives of ABYSS. Our study concluded that the error due to mean gravity field is no longer limiting due primarily to the recent Gravity Recovery and Climate Experiment gravity modeling and that the ABYSS/ISS radial orbit slope error budget in the presence of various force and measurement model errors is estimated at the 0.2-$mu hbox{rad}$ root-sum-squared (RSS) level, which satisfies the ABYSS orbit accuracy science requirement to provide an improved mapping of global bathymetry.      

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.      

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.      

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 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.      

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.      

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.      

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.      

Seasonal low-degree changes in terrestrial water mass load from global GNSS measurements

Large-scale mass redistribution in the terrestrial water storage (TWS) leads to changes in the low-degree spherical harmonic coefficients of the Earth’s surface mass density field. Studying these low-degree fluctuations is an important task that contributes to our understanding of continental hydrology. In this study, we use global GNSS measurements of vertical and horizontal crustal displacements that we correct for atmospheric and oceanic effects, and use a set of modified basis functions similar to Clarke et al. (Geophys J Int 171:1–10, 2007) to perform an inversion of the corrected measurements in order to recover changes in the coefficients of degree-0 (hydrological mass change), degree-1 (centre of mass shift) and degree-2 (flattening of the Earth) caused by variations in the TWS over the period January 2003–January 2015. We infer from the GNSS-derived degree-0 estimate an annual variation in total continental water mass with an amplitude of \((3.49 \pm 0.19) \times 10^{3}\) Gt and a phase of \(70^{\circ } \pm 3^{\circ }\) (implying a peak in early March), in excellent agreement with corresponding values derived from the Global Land Data Assimilation System (GLDAS) water storage model that amount to \((3.39 \pm 0.10) \times 10^{3}\) Gt and \(71^{\circ } \pm 2^{\circ }\), respectively. The degree-1 coefficients we recover from GNSS predict annual geocentre motion (i.e. the offset change between the centre of common mass and the centre of figure) caused by changes in TWS with amplitudes of \(0.69 \pm 0.07\) mm for GX, \(1.31 \pm 0.08\) mm for GY and \(2.60 \pm 0.13\) mm for GZ. These values agree with GLDAS and estimates obtained from the combination of GRACE and the output of an ocean model using the approach of Swenson et al. (J Geophys Res 113(B8), 2008) at the level of about 0.5, 0.3 and 0.9 mm for GX, GY and GZ, respectively. Corresponding degree-1 coefficients from SLR, however, generally show higher variability and predict larger amplitudes for GX and GZ. The results we obtain for the degree-2 coefficients from GNSS are slightly mixed, and the level of agreement with the other sources heavily depends on the individual coefficient being investigated. The best agreement is observed for \(T_{20}^C\) and \(T_{22}^S\), which contain the most prominent annual signals among the degree-2 coefficients, with amplitudes amounting to \((5.47 \pm 0.44) \times 10^{-3}\) and \((4.52 \pm 0.31) \times 10^{-3}\) m of equivalent water height (EWH), respectively, as inferred from GNSS. Corresponding agreement with values from SLR and GRACE is at the level of or better than \(0.4 \times 10^{-3}\) and \(0.9 \times 10^{-3}\) m of EWH for \(T_{20}^C\) and \(T_{22}^S\), respectively, while for both coefficients, GLDAS predicts smaller amplitudes. Somewhat lower agreement is obtained for the order-1 coefficients, \(T_{21}^C\) and \(T_{21}^S\), while our GNSS inversion seems unable to reliably recover \(T_{22}^C\). For all the coefficients we consider, the GNSS-derived estimates from the modified inversion approach are more consistent with the solutions from the other sources than corresponding estimates obtained from an unconstrained standard inversion.     

Effect of the processing methodology on satellite altimetry-based global mean sea level rise over the Jason-1 operating period

Determining how the global mean sea level (GMSL) evolves with time is of primary importance to understand one of the main consequences of global warming and its potential impact on populations living near coasts or in low-lying islands. Five groups are routinely providing satellite altimetry-based estimates of the GMSL over the altimetry era (since late 1992). Because each group developed its own approach to compute the GMSL time series, this leads to some differences in the GMSL interannual variability and linear trend. While over the whole high-precision altimetry time span (1993–2012), good agreement is noticed for the computed GMSL linear trend (of $3.1\pm 0.4$  mm/year), on shorter time spans (e.g., ${<}10~\hbox {years}$ ), trend differences are significantly larger than the 0.4 mm/year uncertainty. Here we investigate the sources of the trend differences, focusing on the averaging methods used to generate the GMSL. For that purpose, we consider outputs from two different groups: the Colorado University (CU) and Archiving, Validation and Interpretation of Satellite Oceanographic Data (AVISO) because associated processing of each group is largely representative of all other groups. For this investigation, we use the high-resolution MERCATOR ocean circulation model with data assimilation (version Glorys2-v1) and compute synthetic sea surface height (SSH) data by interpolating the model grids at the time and location of “true” along-track satellite altimetry measurements, focusing on the Jason-1 operating period (i.e., 2002–2009). These synthetic SSH data are then treated as “real” altimetry measurements, allowing us to test the different averaging methods used by the two processing groups for computing the GMSL: (1) averaging along-track altimetry data (as done by CU) or (2) gridding the along-track data into $2^{\circ }\times 2^{\circ }$ meshes and then geographical averaging of the gridded data (as done by AVISO). We also investigate the effect of considering or not SSH data at shallow depths $({<}120~\hbox {m})$ as well as the editing procedure. We find that the main difference comes from the averaging method with significant differences depending on latitude. In the tropics, the $2^{\circ }\times 2^{\circ }$ gridding method used by AVISO overestimates by 11 % the GMSL trend. At high latitudes (above $60^{\circ }\hbox {N}/\hbox {S}$ ), both methods underestimate the GMSL trend. Our calculation shows that the CU method (along-track averaging) and AVISO gridding process underestimate the trend in high latitudes of the northern hemisphere by 0.9 and 1.2 mm/year, respectively. While we were able to attribute the AVISO trend overestimation in the tropics to grid cells with too few data, the cause of underestimation at high latitudes remains unclear and needs further investigation.     

Contemporary deformation in the Kashmir–Himachal,Garhwal and Kumaon Himalaya: significant insights from 1995–2008 GPS time series

We present new insights on the time-averaged surface velocities, convergence and extension rates along arc-normal transects in Kumaon, Garhwal and Kashmir–Himachal regions in the Indian Himalaya from 13 years of high-precision Global Positioning System (GPS) time series (1995–2008) derived from GPS data at 14 GPS permanent and 42 campaign stations between $29.5{-}35^{\circ }\hbox {N}$ and $76{-}81^{\circ }\hbox {E}$ . The GPS surface horizontal velocities vary significantly from the Higher to Lesser Himalaya and are of the order of 30 to 48 mm/year NE in ITRF 2005 reference frame, and 17 to 2 mm/year SW in an India fixed reference frame indicating that this region is accommodating less than 2 cm/year of the India–Eurasia plate motion ( ${\sim }4~\hbox {cm/year}$ ). The total arc-normal shortening varies between ${\sim }10{-}14~\hbox {mm/year}$ along the different transects of the northwest Himalayan wedge, between the Indo-Tsangpo suture to the north and the Indo-Gangetic foreland to the south indicating high strain accumulation in the Himalayan wedge. This convergence is being accommodated differentially along the arc-normal transects; ${\sim } 5{-}10~\hbox {mm/year}$ in Lesser Himalaya and 3–4 mm/year in Higher Himalaya south of South Tibetan Detachment. Most of the convergence in the Lesser Himalaya of Garhwal and Kumaon is being accommodated just south of the Main Central Thrust fault trace, indicating high strain accumulation in this region which is also consistent with the high seismic activity in this region. In addition, for the first time an arc-normal extension of ${\sim }6~\hbox {mm/year}$ has also been observed in the Tethyan Himalaya of Kumaon. Inverse modeling of GPS-derived surface deformation rates in Garhwal and Kumaon Himalaya using a single dislocation indicate that the Main Himalayan Thrust is locked from the surface to a depth of ${\sim }15{-}20~\hbox {km}$ over a width of 110 km with associated slip rate of ${\sim }16{-}18~\hbox {mm/year}$ . These results indicate that the arc-normal rates in the Northwest Himalaya have a complex deformation pattern involving both convergence and extension, and rigorous seismo-tectonic models in the Himalaya are necessary to account for this pattern. In addition, the results also gave an estimate of co-seismic and post-seismic motion associated with the 1999 Chamoli earthquake, which is modeled to derive the slip and geometry of the rupture plane.     

Impact of ambient temperature on spring-based relative gravimeter measurements

In this paper, we investigate the impact of ambient temperature changes on the gravity reading of spring-based relative gravimeters. Controlled heating experiments using two Scintrex CG5 gravimeters allowed us to determine a linear correlation (R \(^{2}>\) 0.9) between ambient temperature and gravity variations. The relation is stable and constant for the two CG5 we used: ?5 nm/s\(^{2}/^\circ \)C. A linear relation is also seen between gravity and residual sensor temperature variations (R \(^{2}>\) 0.75), but contrary to ambient temperature, this relation is neither constant over time nor similar between the two instruments. The linear correction of ambient temperature on the controlled heating time series reduced the standard deviation at least by a factor of 2, to less than 10 nm/s\(^{2}\). The laboratory results allowed for reprocessing the data gathered on a field survey that originally aimed to characterize local hydrological heterogeneities on a karstic area. The correction of two years of monthly CG5 measurements from ambient temperature variations halved the standard deviation (from 62 to 32 nm/s\(^{2}\)) and led us to a better hydrological interpretation. Although the origin of this effect is uncertain, we suggest that an imperfect control of the sensor temperature may be involved, as well as a change of the properties of an electronic component.