3.2. Analysis of Variability of Oceanic Nino Index (ONI) through the Period (1950-2015) The data of OceanicNiñoIndex (ONI, three month running mean of ERSST.v4 SST anomalies in the Nino 3.4 region (5˚N-5˚S, 120˚W - 170˚W) had been used and analyzed through the period (1950-2015). This data ana- lyzed by time series method. Events are defined as 3 consecutive overlapping 3-month periods at or above the +0.5 anomaly for warm (El Nino) events and at or below the −0.5 anomaly for cold (La Nina) events. The thre- shold is further broken down into Weak (with a 0.5 to 0.9 SST anomaly), Moderate (1.0 to 1.4), Strong (1.5 to 1.9) and Very Strong (≥2.0) events. The results are the following:
Abstract. We use the twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover product to study the regional influence of the OceanicNiñoIndex (ONI) and Pacific Decadal Oscillation (PDO) on snow cover in British Columbia (BC). We apply a locally weighted re- gression (LOWESS) interpolation to the MODIS normalized difference snow index (NDSI) time series to detect the tim- ing and duration of snow. We confirm the general consensus from many previous in situ studies that both ONI and PDO have significant impacts on snow cover in BC. We add to this knowledge by performing seasonal and regional analy- sis using established hydrozones and explore variation in our results by elevation bins of 500 m. We calibrated our method with in situ snow water equivalent (SWE) data and found an optimal NDSI threshold of 30 for detecting continuous snow cover. We separate automatic snow weather station data into calibration (75 %) and validation (25 %) subsets and obtain mean absolute errors between the MODIS and in situ obser- vations for the start, end, and duration of 8.7, 8.9, and 13.1 d for the calibration data and 12.7, 12.6, and 16.6 d for the val- idation data, respectively. In general, the start date of snow is poorly correlated with both ONI and PDO, whereas the end date and duration are strongly negatively correlated. Re- gional patterns emerge wherein northern and southern BC are most correlated with the PDO and the ONI, respectively. These relationships are generally stronger at lower elevations
Abstract. The motion of electrically conducting sea water through Earth’s magnetic field induces secondary electro- magnetic fields. Due to its periodicity, the oceanic tidally induced magnetic field is easily distinguishable in magnetic field measurements and therefore detectable. These tidally induced signatures in the electromagnetic fields are also sen- sitive to changes in oceanic temperature and salinity distribu- tions. We investigate the impact of oceanic heat and salinity changes related to the El Niño–Southern Oscillation (ENSO) on oceanic tidally induced magnetic fields. Synthetic hydro- graphic data containing characteristic ENSO dynamics have been derived from a coupled ocean–atmosphere simulation covering a period of 50 years. The corresponding tidally induced magnetic signals have been calculated with the 3- D induction solver x3dg. By means of the OceanicNiñoIndex (ONI), based on sea surface temperature anomalies, and a corresponding Magnetic NiñoIndex (MaNI), based on anomalies in the oceanic tidally induced magnetic field at sea level, we demonstrate that evidence of developing ENSO events can be found in the oceanic magnetic fields statisti- cally 4 months earlier than in sea surface temperatures. The analysis of the spatio-temporal progression of the oceanic magnetic field anomalies offers a deeper understanding on the underlying oceanic processes and is used to test and val- idate the initial findings.
of rock fabric heterogeneities created in response to the dif- ferent tectonic/geodynamic settings. Ophiolites in orogenic settings (recording oceanic formation at spreading centres to oceanic destruction at convergent margins) are expected to gain rock fabric systematics particularly prominent for the nucleation and growth of fibrous minerals, due to the feed- back between cooling/decompression history (cd), secondary permeability (sp), polyphase deformation (pd), and fluid flux (ff). This correlation should be considered as a first step to outline the structural-metamorphic control on growth of as- bestos in ophiolites. Understanding that fibrous mineral oc- currence in natural prototype is a record of the structural- metamorphic history helps to reconstruct an analytical and methodological procedure for investigation of the rock fab- ric aimed at evaluating the asbestos hazard. Our synthesis implies that the geological-structural context of a particular geological site defines a first-order aspect to be taken into
Oceanic common bottlenose dolphins (Tursiops truncatus, referred to hereafter as oceanic bottlenose dolphin) forming inter-specific groups with pilot whales (Globicephala sp.) add additional complexity to the assessment of communication context. Description of complex interactions is improved with higher rates and types of communication. Hidden Markov models are popular in speech recognition applications (which they were originally designed for, see Zucchini et al., 2009 for review). This is a result of their flexibility in classifying sounds from observation series (Ren et al., 2009). A hidden Markov model incorporates the “stationary spectral configuration” (state), “transitions between states” (“spectral changes over time”) (Putland et al., 2018, p. 480), and the effect of underlying motivational states (Ren et al., 2009). Hidden Markov models have described the acoustic behaviour of birds (Somervuo et al., 2006; Ranjard et al., 2017), fish (Vieira et al., 2015), and mammals (Scheifele et al., 2015; Popov et al., 2017; Putland et al., 2018). In many cases hidden Markov models are deemed to outperform alternate approaches (Weisburn et al., 1993; Kogan and Margoliash, 1998; Brown & Smaragdis, 2009), due to the inclusion of spectral changes along a time sequence (Ren et al., 2009). Hidden Markov models also account and allow for variation in call frequency (Ren et al., 2009) and are thus appropriate in the varied environment of mixed species grouping. Additionally, the behavioural states and other communication forms of the individual dolphins are usually not directly observed. This renders hidden Markov models suitable for modelling contexts that could influence call use, including inferring use of multimodal signalling. The simultaneous call- (hydrophone) and mechano- (video recording) assessment with surface behavioural observations in this study facilitates an in-depth examination of dolphin social communication and behaviour. The primary aim is to examine signal use, including call behaviour (whistle and burst pulse vocalisations) and the use of multimodal communication of bottlenose dolphins. This study aims to quantify the effects of inter-species groupings on the social communication of oceanic bottlenose dolphin in Far North waters, New Zealand (NZ), using call parameters as the dependent variable. In line with the groupings and call variation observed in Far North waters (Chapter 2 and 3), the following questions are posed:
The model results (Figs. 3-8) demonstrate that flat subduction is a distinct end-member of steady-state subduction geometry characterized by a strongly curved slab with an obvious nearly-horizontal section. Intermediate cases between normal/steep and flat subduction appear to be transient and evolve towards one of the stable (normal/steep or flat) end-members. Parameters related to the development of flat subduction include slab age, oceanic crustal thickness, the initial subduction angle, thermal structure of the overriding continental lithosphere, absolute trenchward velocity of the overriding continent, rheological properties of the overriding continental crust and the asthenosphere. The effects of these parameters can be grouped into four types, with changing (1) the slab buoyancy, (2) viscous interplate coupling between the subducting and the overriding plate, (3) external kinematic conditions, and (4) rheological properties of the subduction zone. Figures 3-8 show the numerical results for evaluating the effects of variable parameters on the formation of flat subduction.
El niño nace y cada ser humano comienza su existencia naciendo, esto, se constituye para Hanna Arendt en una condición de la existencia humana. La natalidad, el hecho de que el ser humano tenga un comienzo y ese comienzo irrumpa en el tiempo produciendo un corte, nos posiciona frente a un ser radicalmente novedoso y original. Nunca nadie antes ocupó su lugar, y nunca algo volverá a ser igual después de esta irrupción.
Modern ocean basins have different types of crust, including oceanic crust, submerged continental crust, and transitions between these two types. In our reconstruction, the regions underlain by oceanic crust to which an age has been assigned are termed “open ocean” regions. The parts of the ocean basins that occupy the transitional zone between oceanic crust and the emerged continental crust are termed “shelf- slope-rise” regions. These regions typically extend from the boundary of open ocean regions to the coastline. Accord- ingly, the OES ocean bathymetry model involves the merging of open ocean regions and shelf-slope-rise regions (Fig. 1). To accomplish the merging, map-based operations such as computing distances between locations were carried out in ArcGIS 10.1, whereas local calculations such as interpola- tion and statistics were carried out in Matlab R2014a. The workflow is diagrammed in Fig. S9.
Viruses in the Oceanic Basement Viruses in the Oceanic Basement Olivia D Nigro,a Sean P Jungbluth,a,b* Huei Ting Lin,a* Chih Chiang Hsieh,a* Jaclyn A Miranda,a* Christopher R Schvarcz,a Michael S Rapp[.]
ET anomalies during the two types of El Niño years are also examined; we use NOAA’s precipitation reconstruction over land (PREC/L) data (Chen et al., 2002) (available at http:// www.esrl.noaa.gov/psd/data/gridded/data.precl.html), which is mainly based on rain gauge observations. ERA-Interim ET data (Uppala et al., 2008), obtained from the European Center for Medium-Range Weather Forecasts (ECMWF), is also employed (available at http://apps.ecmwf.int/datasets/). Compared with ERA-40 (Uppala et al., 2005), ERA-Interim has many improvements, particularly in the hydrologic cycle variables (Uppala et al., 2008). To improve the significance and robustness of the results from observations, the state-of- the-art global climate models (GCMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) (Taylor et al., 2012) are employed. Eight models, including NCAR-CCSM4, CNRM-CM5, GISS-E2H, GFDL-CM2.1, GFDL-ESM-2G, GFDL-ESM-2M, MPI-ESM-LR and Nor- ESM1-M, are selected based on the studies of Mo (2010) and Kim and Yu (2012), because these model output are considered the best ones to capture both two types of El Niño in intensity and frequency. All of these models are atmospheric-ocean coupled climate models and widely used in climate community. These model outputs are down- loaded from ESGF website (https://pcmdi9.llnl.gov/projects/ esgf-llnl/), including both historical and RCP4.5 output. All of the grid data are re-gridded into the resolution of 0.5 ◦ × 0.5 ◦ .
(POI) which is a large scale index representative of the central Pacific Ocean (Purca et al., 2000), and at the time of the sighting 19 °C SST was registered in situ, repre- senting a + 3 °C SST anomaly (Enfen, 2015). Hence, this sighting could be explained as a consequence of a warm El Niño event. Warming in the Peruvian Central Coast waters could have induced this individual to migrate south as northern Peru presented SST above its range preference, which is considered a biological impact of El Niño 2015–16 (Enfen, 2015). The occasional occurrence of certain ichthyofauna species at higher latitudes of the southeastern Pacific Ocean are usually related to warm El Niño events (Hooker, 1998; Espino, 1999). For ex- ample, the occurrence of M. tarapacana and M. mobu- lar in northern Chile has been associated with El Niño (Sielfeld et al., 2010; Bustamante et al., 2014).
NAO index. This suggests that a prototype seasonal fore- cast based on the GloSea5 NAO may be possible. For SST and NBT, there are regions that exhibit persisting significant correlations (e.g. the English Channel), which is promising. The correlation patterns for SSS are, however, quite differ- ent to those from the observed NAO. There is a general neg- ative correlation across the shelf that gets stronger with an increasing lag (Fig. 9g–i). The persistence in the NAO–SSS correlation reflects the longer-term nature of salinity anoma- lies. The difference in the SSS correlation patterns between the observed and GloSea5 NAO perhaps act as an error esti- mate to this approach, suggesting that caution and further as- sessment are needed before relying on an empirical seasonal forecast of this form for SSS. Overall, the results with the GloSea5 NAO suggest that real relationships exist between the forecast NAO and the observed NWS fields and that fur- ther improvements in the seasonal NAO forecast would de- liver higher levels of forecast skill and/or regional detail.
limit cycle oscillations, with a period that matches the real world, and hence the DAO is a good model for these features of ENSO. Nevertheless, the DAO model assumes a localized coupled problem, which is obviously an over- simplification of the situation in the Pacific. All influ- ences of the atmosphere, the earth’s rotation, and the ocean currents and dynamics are simply modeled by a non-linear, effective damping term and a somewhat ar- bitrary delay. The delay term ignores, e.g. East bound- ary reflections that could possibly be considered. The model further assumes that time scales must be related to propagation times of equatorially trapped oceanic waves in a closed basin. For the atmosphere, which has short time scales, the DAO simply assumes an instantaneous response.
at least partially revealed on young seafloor. Heat flow esti- mates from the Cocos Plate (Hutnak et al., 2008) and the Gulf of Aden (Lucazeau et al., 2008, 2010) are in marginally better agreement with model GHC. However, these sites are located on seafloor where predicted heat flow from all models is not significantly different (Fig. 5), and the Gulf of Aden might not be considered normal seafloor. The Juan de Fuca Ridge flank is geophysically well characterized, but there is strong evidence of ventilated discharge over much of the sampled area (Davis et al., 1997, 1999). The elevated heat flow in this area may reflect this discharge, persistent deep hydrother- mal circulation along faults (Nedimovic et al., 2009), heat release from hydration (Lowell and Rona, 2002), or advec- tion from younger seafloor. Heat flow on the Costa Rica Rift is probably the most important data point as it (1) samples seafloor young enough to potentially differentiate models, (2) is heavily sedimented with no evidence of thermally sig- nificant ventilated transport, and (3) is well characterized for heat flow and basement depth. CRR heat flow is higher than our preferred model GHC, which may be partly explained by thin oceanic crust. Probably, however, the mean or me- dian of heat flow in this region, which is significantly higher than predicted by model GHC, is a good indicator of litho- spheric conduction. The high heat flow in this region may be attributed to deeper hydrothermal transport as suggested by Davis et al. (2004). The Costa Rica Rift is in super- conductive state as depicted in Fig. 1. An important unan- swered question then regards the “normality” of such deeper transport in the crust. Such transport may be regarded as a process of passive hydrothermal circulation (albeit sealed from exchange with oceans) which is not included in model GHC. If this is normal for global oceanic crust, then model GHC may ultimately overestimate the effect of crustal insu- lation on lithospheric cooling.
Mismatch analysis was performed to examine the demographic history between the shallow-pelagic and deep-pelagic S. mentella populations using ARLEQUIN, and distributions were compared with a two-sample Kolmogorov–Smirnov (K–S) test. For populations at stationary demographic equilibrium, theoretical and empirical studies show that the mismatch distributions usually have multimodal, ragged or erratic distributions, while these are typically smoother or unimodal for populations that have undergone a recent expansion (Rogers & Harpending, 1992). To test the goodness-of-fit of distributions, we calculated the sum of squared deviations (SSD) and raggedness index (r) for a stepwise expansion model for the data tested by Monte Carlo Markov Chain simulations (1,000 steps) in ARLEQUIN.
With the widening of the expansion belt, the lithogenetic new oceanic crust is like a carrying pole, which car- ries two old oceanic crusts. Due to that the oceanic crust is in total submergence, the diagenesis of new oceanic crust stops the magma of the earth’s mantle from uplifting. Under the buoyancy influence of the high-density magma of the earth’s mantle, it will generate two consequences for the new oceanic crust, one is that the old oceanic crusts on the two sides of the expansion belt uplift, thus forming the upheaval of the expansion belt, which is called the oceanic ridge; the other is that the new oceanic crust body bends under stress, thus entering the phase of top mounting.
Station RPN is situated on Easter Island ∼ 350 km east from the Rano Kau Ridge in the Pacific, while station MCQ is lo- cated on Macquarie Island, which lies in the middle of the Macquarie Ridge (Duncan et al., 1998; Tapley et al., 2004). Both these volcanic islands are dominated by the presence of basalt and gabbro (Duncan and Varne, 1988; Jorg, 2005). The results of receiver function modeling (Fig. 5) suggest a crustal thickness of ∼ 12 ± 1 km and a plate thickness of 46 ± 2 km at station RPN. On the other hand, the crust is much thicker (∼ 19 ± 1 km) below the station MCQ and the observation of LAB is dubious. The negative phases seen close to 6 s and 10 s are barely above the error limit (Fig. 2). Station MCQ is directly located on the MOR, but the re- trieved Moho depth is larger than expected. This might be due to the fact that the observations are more representative of the islands. The LAB depth found below RPN is consis- tent with the results obtained earlier from S receiver func- tions (Heit et al., 2007; Li, et al., 2003). This study suggests that the numerical value corresponding to the negative dis- continuity below RPN might correspond to an oceanic LAB.