256 research outputs found
Kelvin Waves and Internal Bores in the Marine Boundary Layer Inversion and Their Relationship to Coastally Trapped Wind Reversals
Detailed observations of a coastally trapped disturbance, or wind reversal, on 10–11 June 1994 along the
California coast provide comprehensive documentation of its structure, based on aircraft, wind profiler, radio
acoustic sounding system, and buoy measurements. Unlike the expectations from earlier studies based on limited
data, which concluded that the deepening of the marine boundary layer (MBL) was a key factor, the 1994 data
show that the perturbation was better characterized as an upward thickening of the inversion capping the MBL.
As the event propagated over a site, the reversal in the alongshore wind direction occurred first within the
inversion and then 3–4 h later at the surface. A node in the vertical structure (defined here as the altitude of
zero vertical displacement) is found just above the inversion base, with up to 200-m upward displacements of
isentropic surfaces above the node, and 70-m downward displacements below.
Although this is a single event, it is shown that the vertical structure observed is representative of most other
coastally trapped wind reversals. This is determined by comparing a composite of the 10–11 June 1994 event,
based on measurements at seven buoys, with surface pressure perturbations calculated from aircraft data. These
results are compared to the composite of many events. In each case a weak pressure trough occurred between
2.4 and 4.0 h ahead of the surface wind reversal, and the pressure rose by 0.32–0.48 mb between the trough
and the wind reversal. The pressure rise results from the cooling caused by the inversion’s upward expansion.
The propagation and structure of the event are shown to be best characterized as a mixed Kelvin wave–bore
propagating within the inversion above the MBL, with the MBL acting as a quasi-rigid lower boundary. If the
MBL is instead assumed to respond in unison with the inversion, then the theoretically predicted intrinsic phase
speeds significantly exceed the observed intrinsic phase speed. The hybrid nature of the event is indicated by
two primary characteristics: 1) the disturbance had a much shallower slope than expected for an internal bore,
while at the same time the upward perturbation within the inversion was quasi-permanent rather than sinusoidal,
which more closely resembles a bore; and 2) the predicted phase speeds for the ‘‘solitary’’ form of nonlinear
Kelvin wave and for an internal bore are both close to the observed intrinsic phase speed
Lagrangian Reachabililty
We introduce LRT, a new Lagrangian-based ReachTube computation algorithm that
conservatively approximates the set of reachable states of a nonlinear
dynamical system. LRT makes use of the Cauchy-Green stretching factor (SF),
which is derived from an over-approximation of the gradient of the solution
flows. The SF measures the discrepancy between two states propagated by the
system solution from two initial states lying in a well-defined region, thereby
allowing LRT to compute a reachtube with a ball-overestimate in a metric where
the computed enclosure is as tight as possible. To evaluate its performance, we
implemented a prototype of LRT in C++/Matlab, and ran it on a set of
well-established benchmarks. Our results show that LRT compares very favorably
with respect to the CAPD and Flow* tools.Comment: Accepted to CAV 201
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Turbulent flow at 190 m height above London during 2006-2008: A climatology and the applicability of similarity theory
Flow and turbulence above urban terrain is more complex than above rural terrain, due to the different momentum and heat transfer characteristics that are affected by the presence of buildings (e.g. pressure variations around buildings). The applicability of similarity theory (as developed over rural terrain) is tested using observations of flow from a sonic anemometer located at 190.3 m height in London, U.K. using about 6500 h of data. Turbulence statistics—dimensionless wind speed and temperature, standard deviations and correlation coefficients for momentum and heat transfer—were analysed in three ways. First, turbulence statistics were plotted as a function only of a local stability parameter z/Λ (where Λ is the local Obukhov length and z is the height above ground); the σ_i/u_* values (i = u, v, w) for neutral conditions are 2.3, 1.85 and 1.35 respectively, similar to canonical values. Second, analysis of urban mixed-layer formulations during daytime convective conditions over London was undertaken, showing that atmospheric turbulence at high altitude over large cities might not behave dissimilarly from that over rural terrain. Third, correlation coefficients for heat and momentum were analyzed with respect to local stability. The results give confidence in using the framework of local similarity for turbulence measured over London, and perhaps other cities. However, the following caveats for our data are worth noting: (i) the terrain is reasonably flat, (ii) building heights vary little over a large area, and (iii) the sensor height is above the mean roughness sublayer depth
Integrated Spacecraft Autonomous Attitude Control (ISAAC)
The purpose of this project is to give undergraduate students an opportunity to design, manufacture, and maintain a mock spacecraft to be used as a testbed for autonomous control systems. The spacecraft is based on two previous models: the JX-01, an undergraduate built testbed, and the Asteroid Free Flyer led by NASA engineer and ERAU doctoral student, Michael Dupuis. This model includes cable improvements, Inertial Measurement Units (IMU), Light Detection and Ranging (LIDAR), and object-based state estimation to improve control stabilization. When completed, the hardware built for this project will provide undergraduates and researchers a platform with which they can test control algorithms and spacecraft component design. The results gathered from the project thus far is the building and design and controls experience between the team. After completion we will be able to obtain a properly modeled control algorithm and test it against multiple conditions. The final goal of the spacecraft is to provide the capabilities and perform experiments to test multiple methods to mitigate the effects of internal and external forces such as fuel sloshing, solar radiation, debris collision, and CG change
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Enhanced Short-Term Wind Power Forecasting and Value to Grid Operations: Preprint
The current state of the art of wind power forecasting in the 0- to 6-hour time frame has levels of uncertainty that are adding increased costs and risk on the U.S. electrical grid. It is widely recognized within the electrical grid community that improvements to these forecasts could greatly reduce the costs and risks associated with integrating higher penetrations of wind energy. The U.S. Department of Energy has sponsored a research campaign in partnership with the National Oceanic and Atmospheric Administration (NOAA) and private industry to foster improvements in wind power forecasting. The research campaign involves a three-pronged approach: 1) a 1-year field measurement campaign within two regions; 2) enhancement of NOAA's experimental 3-km High-Resolution Rapid Refresh (HRRR) model by assimilating the data from the field campaign; and 3) evaluation of the economic and reliability benefits of improved forecasts to grid operators. This paper and presentation provides an overview of the regions selected, instrumentation deployed, data quality and control, assimilation of data into HRRR, and preliminary results of HRRR performance analysis
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Assessing the accuracy of microwave radiometers and radio acoustic sounding systems for wind energy applications
To assess current remote-sensing capabilities for wind energy
applications, a remote-sensing system evaluation study, called XPIA
(eXperimental Planetary boundary layer Instrument Assessment), was held in
the spring of 2015 at NOAA's Boulder Atmospheric Observatory (BAO) facility.
Several remote-sensing platforms were evaluated to determine their
suitability for the verification and validation processes used to test the
accuracy of numerical weather prediction models.The evaluation of these platforms was performed with respect to well-defined
reference systems: the BAO's 300 m tower equipped at six levels (50, 100, 150,
200, 250, and 300 m) with 12 sonic anemometers and six temperature (T) and relative
humidity (RH) sensors; and approximately 60 radiosonde launches.In this study we first employ these reference measurements to validate
temperature profiles retrieved by two co-located microwave radiometers (MWRs) as
well as virtual temperature (Tv) measured by co-located wind profiling radars
equipped with radio acoustic sounding systems (RASSs). Results indicate a mean
absolute error (MAE) in the temperature retrieved by the microwave radiometers
below 1.5 K in the lowest 5 km of the atmosphere and a mean absolute error
in the virtual temperature measured by the radio acoustic sounding systems
below 0.8 K in the layer of the atmosphere covered by these measurements (up
to approximately 1.6–2 km). We also investigated the benefit of the
vertical velocity correction applied to the speed of sound before computing
the virtual temperature by the radio acoustic sounding systems. We find that
using this correction frequently increases the RASS error, and that it
should not be routinely applied to all data.Water vapor density (WVD) profiles measured by the MWRs were also compared with
similar measurements from the soundings, showing the capability of MWRs to
follow the vertical profile measured by the sounding and finding a mean
absolute error below 0.5 g m−3 in the lowest 5 km of the atmosphere.
However, the relative humidity profiles measured by the microwave radiometer
lack the high-resolution details available from radiosonde profiles. An
encouraging and significant finding of this study was that the coefficient
of determination between the lapse rate measured by the microwave radiometer
and the tower measurements over the tower levels between 50 and 300 m ranged
from 0.76 to 0.91, proving that these remote-sensing instruments can provide
accurate information on atmospheric stability conditions in the lower
boundary layer
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A Kalman-filter bias correction of ozone deterministic, ensemble-averaged, and probabilistic forecasts
Kalman filtering (KF) is used to postprocess numerical-model output to estimate systematic errors in surface ozone forecasts. It is implemented with a recursive algorithm that updates its estimate of future ozone-concentration bias by using past forecasts and observations. KF performance is tested for three types of ozone forecasts: deterministic, ensemble-averaged, and probabilistic forecasts. Eight photochemical models were run for 56 days during summer 2004 over northeastern USA and southern Canada as part of the International Consortium for Atmospheric Research on Transport and Transformation New England Air Quality (AQ) Study. The raw and KF-corrected predictions are compared with ozone measurements from the Aerometric Information Retrieval Now data set, which includes roughly 360 surface stations. The completeness of the data set allowed a thorough sensitivity test of key KF parameters. It is found that the KF improves forecasts of ozone-concentration magnitude and the ability to predict rare events, both for deterministic and ensemble-averaged forecasts. It also improves the ability to predict the daily maximum ozone concentration, and reduces the time lag between the forecast and observed maxima. For this case study, KF considerably improves the predictive skill of probabilistic forecasts of ozone concentration greater than thresholds of 10 to 50 ppbv, but it degrades it for thresholds of 70 to 90 ppbv. Moreover, KF considerably reduces probabilistic forecast bias. The significance of KF postprocessing and ensemble-averaging is that they are both effective for real-time AQ forecasting. KF reduces systematic errors, whereas ensemble-averaging reduces random errors. When combined they produce the best overall forecast
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Assessment of virtual towers performed with scanning wind lidars and Ka-band radars during the XPIA experiment
During the
eXperimental Planetary boundary layer Instrumentation Assessment (XPIA)
campaign, which was carried out at the Boulder Atmospheric Observatory (BAO)
in spring 2015, multiple-Doppler scanning strategies were carried out with
scanning wind lidars and Ka-band radars. Specifically, step–stare
measurements were collected simultaneously with three scanning Doppler
lidars, while two scanning Ka-band radars carried out simultaneous range
height indicator (RHI) scans. The XPIA experiment provided the unique
opportunity to compare directly virtual-tower measurements performed
simultaneously with Ka-band radars and Doppler wind lidars. Furthermore,
multiple-Doppler measurements were assessed against sonic anemometer data
acquired from the meteorological tower (met-tower) present at the BAO site and a lidar wind
profiler. This survey shows that – despite the different technologies,
measurement volumes and sampling periods used for the lidar and radar
measurements – a very good accuracy is achieved for both remote-sensing
techniques for probing horizontal wind speed and wind direction with the
virtual-tower scanning technique
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Vertical profiles of the 3-D wind velocity retrieved from multiple wind lidars performing triple range-height-indicator scans
Vertical profiles of 3-D wind velocity are retrieved from triple
range-height-indicator (RHI) scans performed with multiple simultaneous
scanning Doppler wind lidars. This test is part of the eXperimental Planetary
boundary layer Instrumentation Assessment (XPIA) campaign carried out at the
Boulder Atmospheric Observatory. The three wind velocity components are
retrieved and then compared with the data acquired through various profiling
wind lidars and high-frequency wind data obtained from sonic anemometers
installed on a 300 m meteorological tower. The results show that the
magnitude of the horizontal wind velocity and the wind direction obtained
from the triple RHI scans are generally retrieved with good accuracy.
However, poor accuracy is obtained for the evaluation of the vertical
velocity, which is mainly due to its typically smaller magnitude and to the
error propagation connected with the data retrieval procedure and accuracy in
the experimental setup
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