Satellite tracking and remote sensing data now allow us to ask fundamental biological questions about large- scale phenomena such as bird migration [17,38]. How- ever, as with any new technology, the new data types must be evaluated and compared to traditional methods. Not surprisingly, we found that traditional estimates of flight speed (from sequential, low-resolution locations) resulted in underestimates of the true distance traveled and translated into lower estimates of ground speed . Even in those species where we had a position every 15 or 30 minutes (e.g. some individuals of Anas platyrhynchos or Larus scoresbii), the differences between using instantaneous measures and next-location measure- ments were substantial and accompanied by a significant drop in the amount of explained variance. This indicates that deriving speed and direction from the next location is
Two steel slab samples from an industrial thick slab caster were investigated for the variation in dendrite deflection from the slab surface towards the slab centre. Both alloys have a similar composition and casts were made under the influence of electromagnetic brake ( EMBR ) . A clear change in the dendrite growth direction from surface towards the centre occurs, albeit over a wider zone, which can be correlated to changes in the fluid flow profile. Decrease in bending angle from surface towards the centre was observed. Takahashi relation needs to be revised to predict the high bending angle values. Correlating these deflection measurements with compositional analysis has been planned as a part of future activities, which would provide insight on the relation between the macro-segregation phenomenon and dendrite deflection. The transition area between downwards and upwards bending seems to be larger in the case of sample B, which fits qualitatively with the gradual increase of casting speed and the moving solid/liquid interface region.
The data are compiled and evaluated by statistics which may be applied in risk management. The seasonal variance of the forecast error is shown by comparing the forecasts with wind speed and directionmeasurements from FINO 1. Subsequently the results from FINO 1 will be contrasted with the analogous statistics obtained from FINO 2 and 3. Given the different geographical conditions the wind speed and direction forecast accuracy potentially vary between those sites. Risk analysts who are confronted with large-scale weather forecast uncertainty statistics thus might learn about the geographical variance, here demonstrated by comparing data between the Baltic (inland) Sea and the North Sea. The deviations between forecast values and measurements origin from inaccurate measurements, incorrect weather forecasts and the approximation of the vertical wind profile. The effects are superimposed and do not add a significant bias to the forecast error as can be observed in Fig. 2. The wind speed forecast error distribution in Fig. 2 also complies with general knowledge that the wind speed assimilation error resembles a Normal Distribution. Its first and second moments, the expected value and standard deviation, are the common parameters to describe the historical wind forecast uncertainty. Knowing its dependence on geographical and seasonal variation helps to estimate these parameters more appropriately. A seasonal bias and greater variance in stormy waters are common examples.
ABSTRACT. The semi-diurnal tidal range is small along the Turkish coastline, being in the order of 30 cm. Therefore, sea level changes, are largely influenced by changes in air pressure and wind parameters. In this study, meteorological changes are related to seawater level changes. İzmir Bay located in the Aegean Sea of Turkey is chosen as the application area. Sea level, wind speed and direction, and pressure data of 1999-2016 measured at Menteş Station in the Bay have been analyzed. Hourly wind speed and directionmeasurements at nearby meteorological station have been used as well in the long term wind analyses. The twenty-five-hour moving average filter is applied to eliminate the tidal effects on the sea level measurements. The reverse barometer effect that is the one cm sea level drop corresponding to the one mb pressure increase, is calculated, and the barometric pressure effect from the sea level data has also been eliminated. For the remaining data, wind surge has been performed. It has been observed the local meteorological contribution appears to be the most important in regional sea level variations. In İzmir Bay, the observed sea level variations result mainly from the combination of two elevations: astronomical tides and surges. While the former is of minor importance; being ±15 cm, the latter may reach up to 1.0 m elevation under the effect of the meteorological factors.
summertime distribution with an expected peak in the southwesterly direction. By 1300 LDT (fig. 3.20) no prominent wind flow pattern remains, although there is an increase in the frequency of wind directionmeasurements between the easterly and southeasterly directions. Trends from the 1400 LDT hour (Figure 3.22) are similar, although by this point the peaks are from the easterly and southerly wind directions. By the 1800 LDT hour (Figure 3.22), the southerly wind regime has asserted itself, although even here the margin is not so wide with a relatively even spread from 160 degrees up to 220 degrees from north. It is certainly possible that this three-step process is simply more common in June than in other months. The complex relationship between the sea breezes from the south-facing and east-facing coasts near Wilmington also creates issues when examining satellite data, explored in later sections.
The desire to improve short-term predictions of wind speed and direction has motivated the development of a spatial covariance-based predictor in a complex valued multichannel structure. Wind speed and direction are modelled as the magnitude and phase of complex time series and measure- ments from multiple geographic locations are embedded in a complex vector which is then used as input to a multi- channel Wiener prediction filter. Building on a C -linear cyclo-stationary predictor, a new widely linear filter is de- veloped and tested on hourly mean wind speed and directionmeasurements made at 13 locations in the UK over 6 years. The new predictor shows a reduction in mean squared error at all locations. Furthermore it is found that the scale of that reduction strongly depends on conditions local to the measurement site.
of the period 2000–2016. Meteorological data are available from four automatic weather stations (AWSs) surround- ing the experimental site. Blowing snow data stem from two sources: (i) a database of blowing snow occurrence and (ii) blowing snow fluxes derived from snow particles counters from winter 2010–2011 to 2015–2016. It should also be underlined that data collection continues and new measurements will follow. The paper is organized as follows. Section 2 describes the experimental site and the sensors used at each automatic weather station. Section 3 deals specifically with blowing snow data, which are introduced and discussed. Then, Sect. 4 presents an overview of the meteorological and blowing snow data set over the last seasons. Finally, Sect. 5 details the data availability.
Spurious noise (rattles, squeaks, etc) in the interior of car cabinets can be annoying, distractive and indicative of potential performance problems. Fault finding these problems can be difficult since the fault is intermittent and may not necessarily happen under test conditions. A 3 channel system that can record the fault and indicate its location within the cabinet is presented here. The system consists of a coincident microphone array that measures acoustic particle velocity along two orthogonal axes at its location. Detection and direction of noise can be obtained in real time or during post-processing using advanced signal analysis methods. Measurements inside a vehicle show that the very reflective nature of the sound-filed inside a car cabinet present a major challenge and that a combination of advance techniques from diagnostics engineering and room acoustics are required to reliably indicate the direction of the annoying sound.
To ensure a good coverage of the vertical extent of the plume during the second part of the flight focusing on in situ measurements, the aircraft typically flew at a fixed distance from the source for several plume transects perpendicular to the prevailing wind direction at different altitudes, trying to best cover the entire boundary layer. The number of legs for such a “wall” of measurements varied depending on the available flight time between 3 and 6. Additionally, depend- ing on available flight time such a wall was typically flown upwind and downwind, characterizing the inflow and outflow to the area. On one day, one additional downwind wall of measurements was located at a distance further away from the source to better characterize occurrent errors on the esti- mated fluxes. The maximum altitude extent of the plume was generally well documented; on all 4 flight days there was at least one leg, which shows no plume structures or signals at higher altitudes and therefore confines the upper limit of the plume. Due to ATC restrictions over congested areas like the LA Basin, flying below 1000 ft a.g.l. (ft above ground level, equals around 300 m a.g.l.) was not permitted. Therefore, the lowest measured leg was typically extrapolated down to the surface following the terrain (more details are given in Sect. 4.2). Altitude changes were made not faster than 150 m per minute to minimize the effect of pressure changes on the in situ sampling. This rate of change maintained the sampling cavity conditions well within acceptable tolerances, i.e., cav- ity pressure within 140.0 ± 0.04 Torr and cavity temperature within 45.0 ± 0.002 ◦ C (deviations are given in ± 1 σ ). Fig- ure 2 shows the approximate position of the three upwind (dashed lines) and five downwind (solid lines) walls flown on all 4 days.
2005). Similar results are found by other instruments on En- visat: ASAR, GOMOS, and MIPAS (Bargellini et al., 2005). A detailed investigation by ESA lead to an update of the on- board attitude control software by an optimization of the on- board orbit model in December 2003 (Bargellini et al., 2005), which lead to a major improvement of SCIAMACHY’s pointing performance. The remaining seasonal cycle derived with TRUE had an amplitude of about 220 m and a mean off- set of about 1 km. Investigation of monitoring measurements improved the knowledge about SCIAMACHY’s misalign- ment (Gottwald et al., 2007), which considerably reduced the mean offset. The current status of the pointing knowledge is described in Gottwald et al. (2010), which states the overall accuracy reached so far with 2–3 mdeg in elevation, corre- sponding to about 110–170 m in tangent height.
SPECIFICALLY DESIGNED FOR ITS USE. 3. ALWAYS keep the muzzle of the rifle pointed in a safe direction, especially during loading. With any muzzleloader, there is always the possibility of an accidental discharge while loading. It is imperative that the barrel be vertical and angled away from the face and body when pouring in a measured powder charge and while seating the projectile over the powder. 4. ALWAYS open the bolt of the rifle before loading powder and projectile in the barrel. Once the primer is loaded and the bolt closed, the rifle is ready to fire.
To measure spatial tuning in moving subjects, we implanted ferrets (n = 5) with multichan- nel tungsten electrode arrays, allowing the recording of single and multiunit activity during behavior. During neural recording, each ferret was placed in an arena, which the animal explored for water rewards while the surrounding speakers played click sounds (Fig 2a). To measure the animal’s head position, direction, and speed in the world during exploration (Fig 2b–2f), we tracked light-emitting diodes (LEDs) placed on the midline of the head (S1 Video). During exploration, click sounds were presented from speakers arranged at 30˚ intervals between ±90˚ relative to the arena center, with speaker order and inter-click interval (250–500 ms) varied pseudo-randomly. We also roved the level of clicks between 54 decibel sound pres- sure level (dB SPL) and 60 dB SPL such that absolute sound level varied both as a function of sound source level and distance between head and speaker, to reduce cues about sound loca- tion provided by absolute sound level (Fig 2g and 2h). Clicks were used as they provided instantaneous energy and thus ensured minimal movement of the animal during stimulus pre- sentation (S3 Fig). The locations (speaker angle) from which the clicks originated were used alone to estimate allocentric receptive fields and were used in conjunction with the animal’s head direction and position to measure egocentric spatial receptive fields.
The SRAS system could use a number of different types of detectors, sensitive to surface displacement or optical beam deflection, depending on the range of expected frequencies and the surface finish of the sample. For samples with strong specular reflections, the detector used is a knife edge detector, based on the principle of optical beam deflection; this is sensitive to the out-of-plane surface motion in one propagation direction. As the acoustic waves pass under the probe beam spot, it causes the beam to be deflected and if this motion is across the split photodiode we measure the presence of the propagating waves. The output of the detector is then amplified and band pass filtered and the trace is recorded on a digital oscilloscope (Lecroy, Wavemaster 64Xi).
Our data are thus in good agreement with these theoretical expectations. Considering the measurements undertaken at 6.158 K for SF F sample A (Fig. 3), although there is no angular dependence in zero field, the resistance can be smoothly increased from zero with both field angle and value of applied field, indicating a highly tuneable resistance (Fig. 4b), which may reflect the polarising influence of the field on equal spin triplets. This result demonstrates the feasibility of a field-controlled source of equal spin triplets, since it is the drainage to the triplet channel that suppresses the singlet fraction and reduces T c .
All pipes in the experimental setup are made of transparent acrylic in order to observe the flow. Test section is given as schematic in Figure 3. It consists of a pipe with prescribed lengths and diameters. Black bars stand for the measurement positions. The measurements were obtained by dual optical probe along the radial direction of the pipe at each measurement positions represented by black bars in the figure.
The ridge scan, 2 km along the south ridge, shows no turn- ing of the wind for the northeast winds (Fig. 11a). Thus, for this wind direction we observed a two-dimensional flow. On the other hand, for southwest winds there is a slight turning of the wind (the difference between the wind direction at the edges of the transect is roughly 15 ◦ , Fig. 11b). The maximum wind speed along the transect is not seen at the wind turbine location regardless of the dominant wind direction (Fig. 11). The initial data analysis of the wake measurements indi- cates a clear diurnal dependence of the wake characteristics (see Hansen et al., 2016), which may be related to the stratifi- cation. Due to the lack of temperature and heat flux measure- ments, we established an empirical relation between the pe- riod of a day and atmospheric stability. A well-formed, nar- row and long wake was pulled down the slope during late nights until early mornings when we expected stable condi- tions and reduced mixing (Figs. 12a and 13a). On the other hand, during the rest of the day under more unstable con- ditions and increased mixing, the wake was wider, shorter and lifted up (Figs. 12b and 13b). The inflow and wake of the turbine during 1 full day is well represented in Vasiljevi´c (2016b).
Geophysical logging was conducted in 16 wells in and near the North Penn Area 7 site from December 2000 through March 2002. The types of logs and well-construction data for the logged wells are listed in table 1. All digital data for logs and borehole video tapes are archived and available from the USGS Pennsylvania Water Science Center. The locations of the 16 wells and 6 wells logged earlier by USGS (MG-72 and MG-76) and by consultants to FERCO, Converse Consultants East, Inc., (MG-90, MG-135, MG-147, and MG-151) are shown in figure 4. The log suite for each of the 16 wells logged by USGS for this study is discussed individually and is fol- lowed by a discussion of multiple logs, including log correla- tion and interpretation of borehole-deviation and acoustic-tele- viewer data. Discussion of individual logs includes description of well construction and identification of (1) water-bearing zones and relative productivity of water-bearing zones, where possible, (2) direction and magnitude of borehole flow under nonpumping and pumping conditions, and (3) lithologic inter- vals that can be used for stratigraphic correlation. Use of the terms major and minor for water-bearing zones indicates mag- nitude relative to all zones of the borehole.