Characteristic patterns of QuikScat-based wind stress and turbulent heat flux in the tropical Indian Ocean

Using QuikScat-based vector wind data for 1999-2003, surface wind stress and turbulent heat (Q) have been mapped for the tropical Indian Ocean (IO) to understand their seasonal variability. During July wind stress is enhanced by ∼ 70% in the Arabian Sea compared to that during January. The Arabian Sea experiences a large Q loss (150-200 W/m²) during the summer and winter monsoons, which is nearly 1.3 times of that in the Bay of Bengal. The southeasterlies are strengthened during the southern hemisphere winter. Empirical Orthogonal Function analysis captures different phases of monsoon-induced variability in wind stress and Q, ranging from seasonal to high-frequency perturbations. Coherency between time coefficients of EOF-1 for wind stress and Q suggests that former leads the latter with a temporal lag of 20-40 days for period > 322 days. At high frequencies (< 21 days) Q leads wind stress with a temporal lag of 2 days. Possible explanation for wind stress leading Q over an annual time scale is offered based on the marine atmospheric boundary layer physics and pre-conditioned ocean surface, while on shorter time scales (21 days) ocean thermodynamics through mixed layer processes cause Q to lead wind stress.     

Extending the MODIS 1 km ocean colour atmospheric correction to the MODIS 500 m bands and 500 m chlorophyll-a estimation towards coastal and estuarine monitoring

National and regional obligations to control and maintain water quality have led to an increase in coastal and estuarine monitoring. A potentially valuable tool is high temporal and spatial resolution satellite ocean colour data. NASA's MODIS-Terra and -Aqua can capture data at both 250 m and 500 m spatial resolutions and the existence of two sensors provides the possibility for multiple daily passes over a scene. However, no robust atmospheric correction method currently exists for these data, rendering them unusable for quantitative monitoring applications. Therefore, this paper presents an automatic and dynamic atmospheric correction approach allowing the determination of ocean colour. The algorithm is based around the standard MODIS 1 km atmospheric correction, includes cloud masking and is applicable to all of the visible 500 m bands. Comparison of the 500 m ocean colour data with the standard 1 km data shows good agreement and these results are further supported by in situ data comparisons. In addition, a novel method to produce 500 m chlorophyll-a estimates is presented. Comparisons of the 500 m estimates with the standard MODIS OC3M algorithm and to in situ data from a near-coast validation site are given.     

A class-based approach to characterizing and mapping the uncertainty of the MODIS ocean chlorophyll product

Global chlorophyll products derived from NASA's ocean color satellite programs have a nominal uncertainty of ± 35%. This metric has been hard to assess, in part because the data sets for evaluating performance do not reflect the true distribution of chlorophyll in the global ocean. A new technique is introduced that characterizes the chlorophyll uncertainty associated with distinct optical water types, and shows that for much of the open ocean the relative error is under 35%. This technique is based on a fuzzy classification of remote sensing reflectance into eight optical water types for which error statistics have been calculated. The error statistics are based on a data set of coincident MODIS Aqua satellite radiances and in situ chlorophyll measurements. The chlorophyll uncertainty is then mapped dynamically based on fuzzy memberships to the optical water types. The uncertainty maps are thus a separate, companion product to the standard MODIS chlorophyll product.     

Wind resource assessment from C-band SAR

Using accurate inputs of wind speed is crucial in wind resource assessment, as predicted power is proportional to the wind speed cubed. First, wind speeds retrieved from a series of 91 ERS-2 SAR and Envisat ASAR images, at moderate wind speeds (2-15 m s^− 1), were validated against in situ measurements from an offshore mast in the North Sea. The wind direction input, necessary for SAR wind speed retrievals, was obtained from the meteorological mast and from a local gradient analysis of wind streaks in the SAR images. A wind speed standard deviation of ∼ 1.1 m s^− 1 was found when in situ wind directions were used. The use of local gradient wind directions yielded a standard deviation of ∼ 1.3 m s^− 1. Wind speeds retrieved from three geophysical model functions (CMOD-IFR2, CMOD4, and CMOD5) were compared. The best approximation to the in situ measurements of wind speed was found for CMOD-IFR2, despite a bias on the order of − 0.3 m s^− 1. CMOD4 retrievals also underestimated the wind speed, whereas the bias on CMOD5 retrievals was negligible. Then, wind resource assessments were made from the SAR-based wind observations to show how errors in wind speed from the different SAR wind retrievals were reflected in the wind statistics. The mean wind speed, obtained for all of the 91 SAR scenes, was linked closely to the bias of SAR wind retrievals. Agreement to ± 15% of the in situ measurements was found for all the wind retrieval methods tested. The accuracy of power density estimates for the entire data set was evaluated by the standard deviation of SAR wind retrievals relative to the in situ measurements. SAR wind fields retrieved with CMOD-IFR2, using in situ wind direction inputs, exactly yielded the power density predicted from in situ measurements alone. The SAR-based wind resource assessment also corresponded well to predictions from longer time series of in situ measurements. This indicates that a reliable wind resource assessment may be achieved from a series of randomly selected SAR images. The findings presented here could be useful in future wind resource assessment based on SAR images.     

Helicoidal vortex model for wind turbine aeroelastic simulation

The vortex method has been extended to account for blade flexibility, which is a potential source of unsteadiness in the flow past a wind turbine rotor. The code has been validated previously under the assumption of rigid blades. The aerodynamics method is based on the Goldstein model, which distributes the flow vorticity on rigid helicoidal surfaces defined uniquely by the flow parameters (tip speed ratio and average power extracted by the rotor) and the blade geometry (maximum radius and root lengths). The structure is treated as a beam with degrees of freedom in bending and torsion. The high twist of the wind turbine blades is responsible for induced velocities in the plane of the rotor as well as out of plane. A modal decomposition has been shown to be the most accurate and efficient approach for an implicit coupling of the structural and aerodynamics equations. Results for a homogeneous blade are presented for a low speed of 5 m/s and yaw angles of 0°, 5° and 10° and compared with rigid blade results and experiments of the National Renewable Energy Laboratory (NREL). The nonhomogeneous NREL blade has also been modeled and results are presented for V = 8 and 10 m/s at zero yaw that include the effect of the tower on the blade loading.     

The Rayleigh lookup tables for the SeaWiFS data processing: Accounting for the effects of ocean surface roughness

In the atmospheric correction of ocean colour remote sensing, it is important to account for the effects of ocean surface roughness (wind speed) in the computation of Rayleigh radiance lookup tables, in particular, for the large solar and/or sensor zenith angles (>～60°). In the paper, both simulated and the SeaWiFS-retrieved results that demonstrate the effects of the ocean surface wind speed on the Rayleigh radiance computations for the various solar and sensor-viewing geometries as well as on the performance of atmospheric corrections are presented and discussed. An improved set of Rayleigh lookup tables, in which the Rayleigh scattering radiance is also a function of the sea surface wind speed, were generated and implemented into the SeaWiFS data processing system in May 2000.     

Sedflux 2.0: An advanced process-response model that generates three-dimensional stratigraphy

Sedflux 2.0 is the newest version of the Sedflux basin-filling model. Sedflux 2.0 provides a framework within which individual process-response models of disparate time and space resolutions communicate with one another to deliver multigrain-sized sediment load across a continental margin. Version 2.0 introduces a series of new process models, and the ability to operate in one of two modes to track the evolution of stratigraphy in either two or three dimensions. Additions to the 2D mode include the addition of models that simulate (1) erosion and deposition of sediment along a riverbed, (2) cross-shore transport due to ocean waves, and (3) turbidity currents and hyperpycnal flows. New processes in the 3D mode include (1) river channel avulsion, (2) two-dimensional diffusion due to ocean storms, and (3) two-dimensional flexure due to sediment loading. The spatial resolution of the architecture is typically 1–25 cm in the vertical and 10–100 m in the horizontal when operating in 2D mode. In 3D mode, the horizontal resolution usually extends to kilometers. In addition to fixed time steps (from days to hundreds of years), Sedflux 2.0 offers event-based time stepping as a way to conduct long-term simulations while still modeling low-frequency but high-energy events.     

Validation of SeaWiFS and MODIS aerosol products with globally distributed AERONET data

The validation of aerosol products derived from ocean color missions is required for the assessment of their uncertainties and as a diagnostic for the atmospheric correction schemes used for determining the ocean apparent optical properties. A comprehensive validation of the aerosol products obtained from the ocean color missions SeaWiFS and MODIS is presented; it relies on the field observations collected at 85 AERONET sites and is completed by preliminary results obtained with the data of the maritime AERONET component. A robust match-up selection protocol yields approximately 7000 match-ups for each sensor. The median absolute relative difference for the aerosol optical thickness τ_a increases from 20-22% at 443 nm to 45-48% in the near-infrared. The validation statistics are comparable for both sensors but MODIS results appear degraded particularly for sites located on isolated islands. The median absolute difference is approximately 0.03 at all wavelengths. Results are further analyzed for specific geographic regions or groups of sites selected to represent oceanic, continental, or desert dust conditions. Importantly, the match-up sets appear generally representative of the regional natural variability in τ_a amplitude and spectral shape, with the notable exception of high τ_a conditions that are excluded. An important finding is the underestimate by the atmospheric correction of the Ångström exponent α, with a median bias of − 0.52. This underestimate is apparent even at low α values and regularly increases with α. This discrepancy in τ_a spectral shape might result from an inappropriate set of candidate aerosol models and/or uncertainties in the calibration at the near-infrared bands. As the validation data base is expanded and updated in relation to new versions of the processing chains, this work provides a benchmark for the assessment of the aerosol products derived from the SeaWiFS and MODIS ocean color missions.     

Pure spin-angular momentum coefficients for non-scalar one-particle operators in jj-coupling

A revised program for generating the spin-angular coefficients in relativistic atomic structure calculations is presented. When compared with our previous version [G. Gaigalas, S. Fritzsche and I.P. Grant, Comput. Phys. Comm. 139 (2001) 263], the new version of the Anco program now provides these coefficients for both, scalar as well as non-scalar one-particle operators as they arise frequently in the study of transition probabilities, photoionization and electron capture processes, the alignment transfer through excited atomic states, collision strengths, and in many other investigations.The program is based on a recently developed formalism [G. Gaigalas, Z. Rudzikas and C.F. Fischer, J. Phys. B 30 (1997) 3747], which combines techniques from second quantization in coupled tensorial form, the theory of quasispin, and the use of reduced coefficients of fractional parentage, in order to derive the spin-angular coefficients for complex atomic shell structures more efficiently. By making this approach now available also for non-scalar interactions, therefore, studies on a whole field of new properties and processes are likely to become possible even for atoms and ions with a complex structure.     

Examining the consistency of products derived from various ocean color sensors in open ocean (Case 1) waters in the perspective of a multi-sensor approach

During its lifetime, a space-borne ocean color sensor provides world-wide information about important biogeochemical properties of the upper ocean every 2 to 4 days in cloudless regions. Merging simultaneous or complementary data from such sensors to obtain better spatial and temporal coverage is a recurring objective, but it can only be reached if the consistency of the sensor-specific products, as delivered by the various Space Agencies, has first been carefully examined. The goal of the present study is to provide a procedure for establishing a coherency of open ocean (Case-1 waters) data products, for which the various data processing methods are sufficiently similar. The development of the procedure includes a detailed comparison of the marine algorithms used (after atmospheric corrections) by space agencies for the production of standard products, such as the chlorophyll concentration, [Chl], and the diffuse attenuation coefficient, K_d. The MODIS-Aqua, SeaWiFS and MERIS [Chl] products agree over a wide range, between ∼ 0.1 and 3 mg m^− 3, whereas increasing divergences occur for oligotrophic waters ([Chl] (from 0.02 to 0.09 mg m^− 3). For the K_d(490) coefficient, different algorithms are in use, with differing results. Based on a semi-analytical reflectance model and hyperspectral approach, the present work proposes a harmonization of the algorithms allowing the products of the various sensors to be comparable, and ultimately, meaningfully merged (the merging procedures themselves are not examined). Additional potential products, obtained by using [Chl] as an intermediate tool, are also examined and proposed. These products include the thickness of the layer heated by the sun, the depth of the euphotic zone, and the Secchi disk depth. The physical limitations in the predictive skill of such downward extrapolations, made from information concerning only the upper layer, are stressed.     

Detecting the red tide algal blooms from satellite ocean color observations in optically complex Northeast-Asia Coastal waters

Over the last few decades, the coastal regions throughout the world have experienced incidences of algal blooms, which are harmful or otherwise toxic because of their potential threat to humans as well as marine organisms, owing to accelerated eutrophication from human activities and certain oceanic processes. Previous studies have found that correct identification of these blooms remains a great challenge with the standard bio-optical algorithms applied to satellite ocean color data in optically complex coastal waters containing high concentrations of the interfered dissolved organic and particulate inorganic materials. Here a new method called the red tide index (RI) is presented which is capable of identifying potential areas of harmful algal blooms (HABs) from SeaWiFS ocean color measurements representing the typical Case-2 water environments off the Korean and Chinese coasts. The RI method employs the water-leaving radiances (L_w), collected from in-situ radiometric measurements of three SeaWiFS bands centered at 443 nm, 510 nm and 555 nm, to achieve derivation of indices that are then related to absorbing characteristics of harmful algae (i.e., L_w at 443 nm) from which a best fit with a cubic polynomial function with correlation coefficient of R² = 0.91 is obtained providing indices of higher ranges for HABs and lower and slightly reduced ranges for turbid and non-bloom waters. Similar indices derived from the use of remote sensing reflectance (R_rs), normalized water-leaving radiance (nL_w) and combination of both are found rather inadequate to characterize the variability of the encountered bloom. In order to quantify the HABs in terms of chlorophyll (Chl), an empirical relationship is established between the RI and in-situ Chl in surface waters from about 0.4-71 mg m^− 3, which yields a Red tide index Chlorophyll Algorithm (RCA) based on an exponential function with correlation coefficient R² = 0.92. The established methods were extensively tested and compared with the performances of standard Ocean Chlorophyll 4 (OC4) algorithm and Local Chlorophyll Algorithm (LCA) using SeaWiFS images collected from typical red tide waters of Korean South Sea (KSS), East China Sea (ECS), Yellow Sea (YS) and Bohai Sea (BS) during 1999-2002. The standard spectral ratio algorithms, the OC4 and LCA, yielded large errors in Chl retrievals for coastal areas, besides providing false information about the encountered HABs in KSS, ECS, YS and BS waters. On the contrary, the RI coupled with the standard spectral ratios yielded comprehensive information about various ranges of algal blooms, while RCA Chl showing a good agreement with in-situ data led to enhanced understanding of the spatial and temporal variability of the recent HAB occurrences in high scattering and absorbing waters off the Korean and Chinese coasts.     

Spacebased estimation of moisture transport in marine atmosphere using support vector regression

An improved algorithm is developed based on support vector regression (SVR) to estimate horizonal water vapor transport integrated through the depth of the atmosphere (Θ) over the global ocean from observations of surface wind-stress vector by QuikSCAT, cloud drift wind vector derived from the Multi-angle Imaging SpectroRadiometer (MISR) and geostationary satellites, and precipitable water from the Special Sensor Microwave/Imager (SSM/I). The statistical relation is established between the input parameters (the surface wind stress, the 850 mb wind, the precipitable water, time and location) and the target data (Θ calculated from rawinsondes and reanalysis of numerical weather prediction model). The results are validated with independent daily rawinsonde observations, monthly mean reanalysis data, and through regional water balance. This study clearly demonstrates the improvement of Θ derived from satellite data using SVR over previous data sets based on linear regression and neural network. The SVR methodology reduces both mean bias and standard deviation compared with rawinsonde observations. It agrees better with observations from synoptic to seasonal time scales, and compare more favorably with the reanalysis data on seasonal variations. Only the SVR result can achieve the water balance over South America. The rationale of the advantage by SVR method and the impact of adding the upper level wind will also be discussed.     

Exploitation of aeroelastic effects for drift reduction,in an all-polymer air flow sensor

This paper presents a vibration amplitude measurement method that greatly reduces the effects of baseline resistance drift in an all-polymer piezoresistive flow sensor or microtuft. The sensor fabrication is based on flexible printed circuit board (flex-PCB) technology to enable the potential for low-cost and scalable manufacture. Drift reduction is accomplished by discriminating the flow-induced vibration (‘flutter’) amplitude of the microtuft-based sensor as a function of flow velocity. Flutter peak-to-peak amplitude is measured using a microcontroller-based custom readout circuit. The fabricated sensor with the readout circuitry demonstrated a drift error of 2.8 mV/h, which corresponds to a flow-referenced drift error of 0.2 m/s of wind velocity per hour. The sensor has a sensitivity of 14.5 mV/(m/s) with less than 1% non-linearity over the velocity range of 5–16 m/s. The proposed vibration amplitude measurement method is also applied to a sensor array with a modified structure and a reduced dimension, which demonstrated a sensitivity of 13.2 mV/(m/s) with a flow-referenced drift error of 0.03 m/s of wind velocity per hour.     

Petri net based decision system modeling in real-time scheduling and control of flexible automotive manufacturing systems

This paper presents the design and the implementation of a Petri net (PN) model for the control of a flexible manufacturing system (FMS). A flexible automotive manufacturing system used in this environment enables quick cell configuration, and the efficient operation of cells. In this paper, we attempt to propose a flexible automotive manufacturing approach for modeling and analysis of shop floor scheduling problem of FMSs using high-level PNs. Since PNs have emerged as the principal performance modeling tools for FMS, this paper provides an object-oriented Petri nets (OOPNs) approach to performance modeling and to implement efficient production control. In this study, we modeled the system as a timed marked graph (TMG), a well-known subclass of PNs, and we showed that the problem of performance evaluation can be reduced to a simple linear programming (LP) problem with m − n + 1 variables and n constraints, where m and n represent the number of places and transitions in the marked graph, respectively. The presented PN based method is illustrated by modeling a real-time scheduling and control for flexible automotive manufacturing system (FAMS) in Valeo Turkey.     

Sensitivity of the Indian Ocean circulation to phytoplankton forcing using an ocean model

Most ocean general circulation models (OGCMs) do not take into account the effect of space- and time-varying phytoplankton on solar radiation penetration, or do it in a simplistic way using a constant attenuation depth, even though one-dimensional experiments have shown potential significant effect of phytoplankton on mixed-layer dynamics. Since some ocean basins are biologically active, it is necessary for an OGCM to take water turbidity into account, even if it is not coupled with a biological model. Sensitivity experiments carried out with the Massachusetts Institute of Technology (MIT) OGCM with spatially and temporally-varying pigment concentration from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data during 1998-2003 reveal the effect of ocean turbidity on tropical Indian Ocean circulation. Variations of light-absorbing phytoplankton pigments change the vertical distribution of solar heating in the mixed layer, thereby affecting upper-ocean circulation. A simulation was performed from 1948 to 2003 with a constant minimum pigment concentration of 0.02 mg m^− 3 while another simulation was performed from September 1997 to December 2003 with variable pigment concentration, and the differences between these two simulations allow us to quantify the effects of phytoplankton on solar radiation penetration in the ocean model. Model results from a period of 6 years (1998-2003) show large seasonal variability in the strength of the meridional overturning circulation (MOC), meridional heat transports (MHT), and equatorial under current (EUC). The MOC mass transport changes by 2 to 5 Sv (1 Sv = 10⁶ m³ s^− 1) between boreal winter (January) and boreal summer (July), with a corresponding change in the MHT of ∼ 0.05 PW (1 PW = 10¹⁵ W) in boreal winter, which is close to the expected change associated with a significant climate change [Shell, K., Frouin, R., Nakamoto, S., & Somerville, R.C.J. (2003): Atmospheric response to solar radiation absorbed by phytoplankton. Journal of Geophysical Research, 108(D15), 4445. doi:10.1029/2003JD003440.]. In addition, changes in phytoplankton pigments concentration are associated with a reduction in the EUC by ∼ 3 cm s^− 1. We discuss the possible physical mechanisms behind this variability, and the necessity of including phytoplankton forcing in the OGCM.     

A computational algorithm for system modelling based on bi-dimensional finite element techniques

This paper develops a modelling methodology for studying relations defined a priori in two dimensions, z = u(x, y), for which experimental data are known. An innovation is that the methodology is based on bi-dimensional finite element techniques, in which the model’s value consists of a finite number of points, making it possible to obtain its value at any point. Its application permits obtaining representational models of the relation. A computational algorithm is presented; its program has been called Finit Trap 2D, which generates families of models. It has defined criteria for model selection based on information parameters.This scientific research technique complements those existing in scientific literature for generating mathematical models based on experimental data [Cortés M, Villacampa Y, Mateu J, Usó, JL. A new methodology for modelling highly structured systems. Environmental modelling and software 2000;15(5):461–70, S-PLUS 2000. Guide to statistics, vosl. 1–2. Mathsoft Inc.; 1999, SPSS 12.0. Guide to statistics, Mathsoft Inc.; 2003, Verdu F. Un algoritmo para la construcción múltiple de modelos matemáticos no lineales y el estudio de su estabilidad, Thesis Doctoral, Universidad de Alicante; 2001, Verdu F, Villacampa Y. A computational algorithm for the multiple generation of nonlinear mathematical models and stability study. Advances in Engineering Software 2008;39(5):430–7, Villacampa Y, Cortés M, Vives F, Usó JL, Castro MA. A new computational algorithm to construct mathematical models. In: Ecosystems and sustainable development II. Advances in ecological sciences, vol. 2, WIT Press: Southampton, Boston; 1999], and will be useful in the effort to simplify the model.It should be emphasised that representational models have been generated from bi-dimensional finite element models. This will naturally lead to their future application in processes described by partial differential equation whose coefficients are functions, A(x, y) for which only experimental data are known.     

A novel high-density dual threshold GNRFET SRAM design with improved stability

We propose a novel single-ended static random access memory (SRAM) design with nine graphene nanoribbon FETs (9-GNRFET) in this paper. Single-ended has an impact on density, delays, static noise margin (SNM) and power consumption. The proposed model is implemented in HSPICE as a library for 16 nm GNRFET technology. This HSPICE-compatible compact model provides accuracy while maintain compactness, and make possible efficient circuit level simulations of futuristic GNRFET-based SRAM cells design. Simulations at low supply voltage of 0.325 V have shown that proposed cell provides power saving 4.8 × as compared to a supply voltage of 0.7 V. The half-select free technique provides bit interleaving architecture, consisting of error-free operations with V_DD down to 325 mV. The proposed architecture implemented in 16 nm low leakage GNRFET technology presents the scalability of these cells near threshed voltage region, which can significantly reduce power consumptions with 0.21µW. The proposed SRAM cell design is based on simulations and results are verified on GNRFET HSPICE-compact model. The proposed cell verified under process variation, and is demonstrated with write-assist, the impact of geometrical liability and adaptive supply voltage scaling.     

Enhancement of an industrial finite-volume code for large-eddy-type simulation of incompressible high Reynolds number flow using near-wall modelling

We present a validation strategy for enhancement of an unstructured industrial finite-volume solver designed for steady RANS problems for large-eddy-type simulation with near-wall modelling of incompressible high Reynolds number flow. Different parts of the projection-based discretisation are investigated to ensure LES capability of the numerical method. Turbulence model parameters are calibrated by using a minimisation of least-squares functionals for first and second order statistics of the basic benchmark problems decaying homogeneous turbulence and turbulent channel flow. Then the method is applied to the flow over a backward facing step at Re_h = 37,500. Of special interest is the role of the spatial and temporal discretisation error for low order schemes. For wall-bounded flows, present results confirm existing best practice guidelines for mesh design. For free-shear layers, a sensor to quantify the resolution quality of the LES based on the resolved turbulent kinetic energy is presented and applied to the flow over a backward facing step at Re_h = 37,500.     

Detection of monsoonal phytoplankton blooms in Luzon Strait with MODIS data

The Luzon Strait experiences a seasonal surge of phytoplankton based on ocean color data. To examine the timing and position of the bloom, daily MODIS chlorophyll data (2002-2005) were acquired and analyzed. Supporting data such as MODIS SST and nLw bands, QuikSCAT wind data, river discharge, and bathymetry were also used and processed in order to investigate the possible driving forces behind the bloom occurrence. Results show that chlorophyll concentration in the Luzon Strait dramatically increases during NE monsoon reaching to approximately 2.0 mg/m³. Highest chlorophyll concentration is observed near the western slope of the Luzon Strait. The monsoonal bloom in the Luzon Strait is likely due to upwelling and can be possibly associated with the interaction of the northward flowing Luzon coastal current with the westward intrusion of Kuroshio during NE monsoon. The positive wind stress curl also contributes to this occurrence. The influence of Cagayan River is only limited within few kilometers from the river mouth.