The Use of Empirical Orthogonal Functions for Deriving Response Based Extreme Current Profiles

Author(s):  
Gus Jeans ◽  
Liam Harrington-Missin ◽  
Andrew Watson ◽  
Jon Upton

Coherent extreme current profiles are derived to reduce the over-conservatism associated with the traditional assumption that extreme currents occur at all depths through the water column simultaneously. Empirical Orthogonal Function (EOF) analysis has proven effective for derivation of coherent extreme current profiles in regions where it effectively captures the dominant characteristics of the flow regime. This is despite the questionable suitability of EOF for Current Profile Characterisation, which reduces a large current profile data set into a much smaller set of profiles for riser fatigue studies. EOF Mode 1 and 2 are used to represent six years of in-situ current profiles accounting for 97.75% of the original variance. With the assumption that depth integrated speed squared is proportional to drag on a simple riser, three sets of extreme current profiles were derived. A) Profiles associated with extreme near surface current speeds, B) Profiles associated with extreme mid-depth current speeds and C) Profiles associated with extreme drag on a riser.

2020 ◽  
Vol 177 (12) ◽  
pp. 5969-5992
Author(s):  
Siva Srinivas Kolukula ◽  
Balaji Baduru ◽  
P. L. N. Murty ◽  
J. Pavan Kumar ◽  
E. Pattabhi Rama Rao ◽  
...  

Author(s):  
Michael Binsar Lubis ◽  
Mehrdad Kimiaei ◽  
Hongwei An ◽  
Reza Azarhoush

Abstract Typical recommended current profiles for marine operations can be found in offshore engineering guidelines and standards. However, for some offshore components (e.g. risers, umbilicals, risers) typical simplified current profiles can easily lead to unrealistic and conservative results. Due to recent developments in current measuring technology, current speed for deep water location can be easily acquired. However, the current speeds are usually recorded for long periods and in many measurement points along the water column. Hence, finding the extreme current profile based on the recorded time-history data is not an easy task since it needs excessive computational efforts. To determine the overall response of an offshore system, various methods have been developed to minimize the required computational efforts in working with big number of irregular current profiles. Mode-based analysis using empirical orthogonal functions is one of these methods. Total number of the utilized modes plays an important role in the numerical complexity of the problem as well as the accuracy of the results. In this study, for a given deep water location, the effects of the reduced number of modes are investigated through response analysis of a simple vertical fixed slender structure under thousands of current profiles. It is found that the reduced-mode profile can produce a good representation of the measured current profile, however it tends to underestimate the structural response.


2020 ◽  
Author(s):  
Jonas Gliß ◽  
Augustin Mortier ◽  
Michael Schulz ◽  

<p>Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the present day modelling of aerosol optical properties has been assessed using simulated data representative for the year 2010, from 14 global aerosol models participating in the Phase III Control experiment. The model versions are close or equal to those used for CMIP6 and AerChemMIP and inform also on bias in state of the art Earth-System-Models (ESMs).<br>Modelled column optical depths (total, fine and coarse mode AOD) and Angstrom Exponents (AE) were compared both with ground based observations from the Aerosol Robotic Network (AERONET, version 3) and space based observations from the AATSR instrument. In addition, the modelled AODs were compared with MODIS (Aqua and Terra) data and a satellite AOD data-set (MERGED-FMI) merged from 12 different individual AOD products. Furthermore, for the first time, the modelled near surface scattering (under dry conditions) and absorption coefficients were evaluated against measurements made at low relative humidity at surface in-situ GAW sites. <br>The AeroCom MEDIAN and most of the participating models underestimate the optical properties investigated, relative to remote sensing observations. AERONET AOD is underestimated by 21%+/-17%. Against satellite data, the model AOD biases range from -38% (MODIS-terra) to -17% (MERGED-FMI). Correlation coefficients of model AODs with AERONET, MERGED-FMI and AATSR-SU are high (0.8-0.9) and slightly lower against the two MODIS data-sets (0.6-0.8). Investigation of fine and coarse AODs from the MEDIAN model reveals biases of -10%+/-20% and -41%+/-29% against AERONET and -13% and -24% against AATSR-SU, respectively. The differences in model bias against AERONET and AATSR-SU are in agreement with the established bias of AATSR against AERONET. These results indicate that most of the AOD bias is due to missing coarse AOD in the regions covered by these observations. Underestimates are also found when comparing the models against the surface GAW observations, showing AeroCom MEDIAN mean bias and inter-model variation of -44%+/-22% and -32%+/-34% for scattering and absorption coefficients, respectively. Dry scattering shows higher underestimation than AOD at ambient relative humidity and is in agreement with recent findings that suggest that models tend to overestimate scattering enhancement due to hygroscopic growth. <br>Considerable diversity is found among the models in the simulated near surface absorption coefficients, particularly in regions associated with dust (e.g. Sahara, Tibet), biomass burning (e.g. Amazonia, Central Australia) and biogenic emissions (e.g. Amazonia). Regions associated with high anthropogenic BC emissions such as China and India exhibit comparatively good agreement for all models. Evaluation of modelled column AEs shows an underestimation of 9%+/-24% against AERONET and -21% against AATSR-SU. This suggests that models tend to overestimate particle size, with implications for lifetime and radiative transfer calculations. An investigation of modelled emissions, burdens and lifetimes, mass-specific-extinction coefficients (MECs) and optical depths (ODs) for each species and model reveals considerable diversity in most of these parameters. Inter-model spread of aerosol species lifetime appears to be similar to that of mass extinction coefficients, suggesting that AOD uncertainties are still associated to a broad spectrum of parameterised aerosol processes.</p>


2018 ◽  
Vol 35 (5) ◽  
pp. 1077-1090 ◽  
Author(s):  
Björn Lund ◽  
Brian K. Haus ◽  
Jochen Horstmann ◽  
Hans C. Graber ◽  
Ruben Carrasco ◽  
...  

AbstractThe Lagrangian Submesoscale Experiment (LASER) involved the deployment of ~1000 biodegradable GPS-tracked Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) drifters to measure submesoscale upper-ocean currents and their potential impact on oil spills. The experiment was conducted from January to February 2016 in the Gulf of Mexico (GoM) near the mouth of the Mississippi River, an area characterized by strong submesoscale currents. A Helmholtz-Zentrum Geesthacht (HZG) marine X-band radar (MR) on board the R/V F. G. Walton Smith was used to locate fronts and eddies by their sea surface roughness signatures. The MR data were further processed to yield near-surface current maps at ~500-m resolution up to a maximum range of ~3 km. This study employs the drifter measurements to perform the first comprehensive validation of MR near-surface current maps. For a total of 4130 MR–drifter pairs, the root-mean-square error for the current speed is 4 cm and that for the current direction is 12°. The MR samples currents at a greater effective depth than the CARTHE drifters (1–5 m vs ~0.4 m). The mean MR–drifter differences are consistent with a wave- and wind-driven vertical current profile that weakens with increasing depth and rotates clockwise from the wind direction (by 0.7% of the wind speed and 15°). The technique presented here has great potential in observational oceanography, as it allows research vessels to map the horizontal flow structure, complementing the vertical profiles measured by ADCP.


2020 ◽  
Author(s):  
Chi-Hua Chung ◽  
Benjamin Fong Chao

<p>We examine the secular variations of global geomagnetic field on long temporal scales using the IGRF model given in Gauss coefficients for 1900 - 2020. We apply the Empirical Orthogonal Function (EOF) analysis to the geomagnetic field truncated at degree 6 and downward continue it to the core-mantle boundary (CMB) under the assumption of an insulating mantle. The first three EOF modes show the periods around 120, 75 and 60 years with corresponding spatial structures. These oscillational modes potentially support the manifestation of magnetic, Archimedes and Coriolis (MAC) waves in the stably stratified layer near CMB (Buffett, 2016). We also model and decompose the geomagnetic field to standing and drifting components according to trajectories of the Gauss coefficients similarly to Yukutake (2015). We then use the Complex EOF (CEOF) analysis on the drifting field. The results indicate the presence of the westward drift phenomenon but only weakly given the fact that the westward drift has only completed a fraction of a cycle during this time.</p>


2003 ◽  
Vol 21 (1) ◽  
pp. 389-397 ◽  
Author(s):  
I. Hoteit ◽  
G. Triantafyllou ◽  
G. Petihakis ◽  
J. I. Allen

Abstract. A singular evolutive extended Kalman (SEEK) filter is used to assimilate real in situ data in a water column marine ecosystem model. The biogeochemistry of the ecosystem is described by the European Regional Sea Ecosystem Model (ERSEM), while the physical forcing is described by the Princeton Ocean Model (POM). In the SEEK filter, the error statistics are parameterized by means of a suitable basis of empirical orthogonal functions (EOFs). The purpose of this contribution is to track the possibility of using data assimilation techniques for state estimation in marine ecosystem models. In the experiments, real oxygen and nitrate data are used and the results evaluated against independent chlorophyll data. These data were collected from an offshore station at three different depths for the needs of the MFSPP project. The assimilation results show a continuous decrease in the estimation error and a clear improvement in the model behavior. Key words. Oceanography: general (ocean prediction; numerical modelling) – Oceanography: biological and chemical (ecosystems and ecology)


2016 ◽  
Vol 33 (7) ◽  
pp. 1455-1471 ◽  
Author(s):  
Julian Kinzel ◽  
Karsten Fennig ◽  
Marc Schröder ◽  
Axel Andersson ◽  
Karl Bumke ◽  
...  

AbstractLatent heat fluxes (LHF) play an essential role in the global energy budget and are thus important for understanding the climate system. Satellite-based remote sensing permits a large-scale determination of LHF, which, among others, are based on near-surface specific humidity . However, the random retrieval error () remains unknown. Here, a novel approach is presented to quantify the error contributions to pixel-level of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data, version 3.2 (HOAPS, version 3.2), dataset. The methodology makes use of multiple triple collocation (MTC) analysis between 1995 and 2008 over the global ice-free oceans. Apart from satellite records, these datasets include selected ship records extracted from the Seewetteramt Hamburg (SWA) archive and the International Comprehensive Ocean–Atmosphere Data Set (ICOADS), serving as the in situ ground reference. The MTC approach permits the derivation of as the sum of model uncertainty and sensor noise , while random uncertainties due to in situ measurement errors () and collocation () are isolated concurrently. Results show an average of 1.1 ± 0.3 g kg−1, whereas the mean () is in the order of 0.5 ± 0.1 g kg−1 (0.5 ± 0.3 g kg−1). Regional analyses indicate a maximum of exceeding 1.5 g kg−1 within humidity regimes of 12–17 g kg−1, associated with the single-parameter, multilinear retrieval applied in HOAPS. Multidimensional bias analysis reveals that global maxima are located off the Arabian Peninsula.


2019 ◽  
Vol 11 (23) ◽  
pp. 2849
Author(s):  
Trung Kien Tran ◽  
Lucile Duforêt-Gaurier ◽  
Vincent Vantrepotte ◽  
Daniel Schaffer Ferreira Jorge ◽  
Xavier Mériaux ◽  
...  

Recently, different algorithms have been developed to assess near-surface particulate organic matter (POC) concentration over coastal waters. In this study, we gathered an extensive in situ dataset representing various contrasted bio-optical coastal environments at low, medium, and high latitudes, with various bulk particulate matter chemical compositions (mineral-dominated, 50% of the data set, mixed, 40%, or organic-dominated, 10%). The dataset includes 606 coincident measurements of POC concentration and remote-sensing reflectance, Rrs, with POC concentrations covering three orders of magnitude. Twelve existing algorithms have then been tested on this data set, and a new one was proposed. The results show that the performance of historical algorithms depends on the type of water, with an overall low performance observed for mineral-dominated waters. Furthermore, none of the tested algorithms provided satisfactory results over the whole POC range. A novel approach was thus developed based on a maximum band ratio of Rrs (red/blue, red/yellow or red/green ratio). Based on the standard statistical metric for the evaluation of inverse models, the new algorithm presents the best performance. The root-mean square deviation for log-transformed data (RMSDlog) is 0.25. The mean absolute percentage difference (MAPD) is 37.48%. The mean bias (MB) and median ratio (MR) values are 0.54 μg L−1 and 1.02, respectively. This algorithm replicates quite well the distribution of in situ data. The new algorithm was also tested on a matchup dataset gathering 154 coincident MERIS (MEdium Resolution Imaging Spectrometer) Rrs and in situ POC concentration sampled along the French coast. The matchup analysis showed that the performance of the new algorithm is satisfactory (RMSDlog = 0.24, MAPD = 34.16%, MR = 0.92). A regional illustration of the model performance for the Louisiana continental shelf shows that monthly mean POC concentrations derived from MERIS with the new algorithm are consistent with those derived from the 2016 algorithm of Le et al. which was specifically developed for this region.


2009 ◽  
Vol 22 (24) ◽  
pp. 6501-6514 ◽  
Author(s):  
Adam H. Monahan ◽  
John C. Fyfe ◽  
Maarten H. P. Ambaum ◽  
David B. Stephenson ◽  
Gerald R. North

Abstract Empirical orthogonal function (EOF) analysis is a powerful tool for data compression and dimensionality reduction used broadly in meteorology and oceanography. Often in the literature, EOF modes are interpreted individually, independent of other modes. In fact, it can be shown that no such attribution can generally be made. This review demonstrates that in general individual EOF modes (i) will not correspond to individual dynamical modes, (ii) will not correspond to individual kinematic degrees of freedom, (iii) will not be statistically independent of other EOF modes, and (iv) will be strongly influenced by the nonlocal requirement that modes maximize variance over the entire domain. The goal of this review is not to argue against the use of EOF analysis in meteorology and oceanography; rather, it is to demonstrate the care that must be taken in the interpretation of individual modes in order to distinguish the medium from the message.


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