If the acoustic signature of an unmanned aerial vehicle (UAV) is observed as it overflies an array of ground microphones, then the projected and observed Doppler shifts in frequency of the narrowband tones generated b...
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If the acoustic signature of an unmanned aerial vehicle (UAV) is observed as it overflies an array of ground microphones, then the projected and observed Doppler shifts in frequency of the narrowband tones generated by its engine may be compared and converted into effective sound speed values. This allows 2D and 3D spatially varying atmospheric temperature and wind velocity fields to be estimated using tomography. Errors in estimating sound speed values are inversely proportional to the rate of change in the narrowband tones received on the ground. As this rate of change typically approaches zero at least twice per microphone during the UAV's overflight, errors in the time of flight estimates are typically too large to deliver useful precision to the tomographically derived temperature and wind fields. However, these errors may be reduced by one or two orders of magnitude by continuously varying the engine throttle rate, thereby making the tomographic technique potentially feasible. This is demonstrated through reconstruction of realistic simulated conditions for a weakly sheared daytime convective atmospheric boundary layer.
Underwater cables play vital roles in marine engineering because they provide power and communication connections from the shore to an increasing number of sea installations. To ensure the system is operating reliably...
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Underwater cables play vital roles in marine engineering because they provide power and communication connections from the shore to an increasing number of sea installations. To ensure the system is operating reliably and continuously, it is necessary to detect the shapes of underwater cables in real time. However, this task is difficult to accomplish because the underwater cables are located in a dynamic and complicated subsea environment, which can cause changes in position, depth, and visibility. In this report, the current development of underwater cable shape detection methods, including visual, acoustic, magnetic detection, and multisensor fusion detection, and the advantages and disadvantages are described and analyzed. Furthermore, the disadvantages of these methods are addressed, which, based on survey platforms with high cost, include a long detection period and the failure to reveal emergencies. Then, the need to construct a simple and reliable system to detect the shapes of underwater cables is highlighted, and one possible solution based on bend sensors embedded in underwater cables is discussed.
NASA's Surface Water and Ocean Topography (SWOT) satellite, scheduled for launch in 2020, will provide observations of sea surface height anomaly (SSHA) at a significantly higher spatial resolution than current sa...
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NASA's Surface Water and Ocean Topography (SWOT) satellite, scheduled for launch in 2020, will provide observations of sea surface height anomaly (SSHA) at a significantly higher spatial resolution than current satellite altimeters. This new observation type is expected to improve the ocean model mesoscale circulation. The potential improvement that SWOT will provide is investigated in this work by way of twin data assimilation experiments using the Navy Coastal Ocean Model four-dimensional variational data assimilation (NCOM-4DVAR) system in its weak constraint formulation. Simulated SWOT observations are sampled from an ocean model run (referred to as the "nature" run) using an observation-simulator program provided by the SWOT science team. The SWOT simulator provides realistic spatial coverage, resolution, and noise characteristics based on the expected performance of the actual satellite. Twin-data assimilation experiments are run for a two-month period during which simulated observations are assimilated into a separate model (known as the background model) in a series of 96-h windows. The final condition of each analysis window is used to initialize a new 96-h forecast, and each forecast is compared to the nature run to determine the impact of the assimilated data. It is demonstrated here that the simulated SWOT observations help to constrain the model mesoscale to be more consistent with the nature run than the assimilation of traditional altimeter observations alone. The findings of this study suggest that data from SWOT may have a substantial impact on improving the ocean model forecast of mesoscale features and surface ocean velocity.
The feature-based spatial verification method named for its three score components: structure, amplitude, and location (SAL) is applied to cloud data, that is, two-dimensional spatial fields of total cloud cover and s...
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The feature-based spatial verification method named for its three score components: structure, amplitude, and location (SAL) is applied to cloud data, that is, two-dimensional spatial fields of total cloud cover and spectral radiance. Model output is obtained from the German-focused Consortium for Small-Scale Modeling (COSMO-DE) forward operator Synthetic Satellite Simulator (SynSat) and compared with SEVIRI satellite data. The aim of this study is twofold: first, to assess the applicability of SAL to this kind of data and, second, to analyze the role of external object identification algorithms (OIA) and the effects of observational uncertainties on the resulting scores. A comparison of three different OIA shows that the threshold level, which is a fundamental part of all studied algorithms, induces high sensitivity and unstable behavior of object-dependent SAL scores (i.e., even very small changes in parameter values lead to large changes in the resulting scores). An in-depth statistical analysis reveals significant effects on distributional quantities commonly used in the interpretation of SAL, for example, median and interquartile distance. Two sensitivity indicators that are based on the univariate cumulative distribution functions are derived. They make it possible to assess the sensitivity of the SAL scores to threshold-level changes without computationally expensive iterative calculations of SAL for various thresholds. The mathematical structure of these indicators connects the sensitivity of the SAL scores to parameter changes with the effect of observational uncertainties. Last, the discriminating power of SAL is studied. It is shown that-for large-scale cloud data-changes in the parameters may have larger effects on the object-dependent SAL scores (i.e., the S and L2 scores) than does a complete loss of temporal collocation.
Conventional altimetry measures a one-dimensional profile of sea surface height (SSH) along the satellite track. Two-dimensional SSH can be reconstructed using mapping techniques;however, the spatial resolution is qui...
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Conventional altimetry measures a one-dimensional profile of sea surface height (SSH) along the satellite track. Two-dimensional SSH can be reconstructed using mapping techniques;however, the spatial resolution is quite coarse even when data from several altimeters are analyzed. A new satellite mission based on radar interferometry is scheduled to be launched in 2020. This mission, called Surface Water and Ocean Topography (SWOT), will measure SSH at high resolution along a wide swath, thus providing two-dimensional images of the ocean surface topography. This new capability will provide a large amount of data even though they are contaminated with instrument noise and geophysical errors. This paper presents a tool that simulates synthetic observations of SSH from the future SWOT mission using SSH from any ocean general circulation model (OGCM). SWOT-like data have been generated from a high-resolution model and analyzed to investigate the sampling and accuracy characteristics of the future SWOT data. This tool will help explore new ideas and methods for optimizing the retrieval of information from future SWOT missions.
During the summer of 2004 a network of 11 wind profiling radars (WPRs) was deployed in New England as part of the New England Air Quality Study (NEAQS). Observations from this dataset are used to determine their impac...
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During the summer of 2004 a network of 11 wind profiling radars (WPRs) was deployed in New England as part of the New England Air Quality Study (NEAQS). Observations from this dataset are used to determine their impact on numerical weather prediction (NWP) model skill at simulating coastal and offshore winds through data-denial experiments. This study is a part of the Position of Offshore Wind Energy Resources (POWER) experiment, a Department of Energy (DOE) sponsored project that uses National Oceanic and Atmospheric Administration (NOAA) models for two 1-week periods to measure the impact of the assimilation of observations from 11 inland WPRs. Model simulations with and without assimilation of the WPR data are compared at the locations of the inland WPRs, as well as against observations from an additional WPR and a high-resolution Doppler lidar (HRDL) located on board the Research Vessel Ronald H. Brown (RHB), which cruised the Gulf of Maine during the NEAQS experiment. Model evaluation in the lowest 2 km above the ground shows a positive impact of the WPR data assimilation from the initialization time through the next five to six forecast hours at the WPR locations for 12 of 15 days analyzed, when offshore winds prevailed. A smaller positive impact at the RHB ship track was also confirmed. For the remaining three days, during which time there was a cyclone event with strong onshore wind flow, the assimilation of additional observations had a negative impact on model skill. Explanations for the negative impact are offered.
Mountains along the California coastline play a critical role in the dynamics of marine atmospheric boundary layer (MBL) airflow in the vicinity of the shoreline. Large changes in the MBL topology have been known to o...
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Mountains along the California coastline play a critical role in the dynamics of marine atmospheric boundary layer (MBL) airflow in the vicinity of the shoreline. Large changes in the MBL topology have been known to occur downwind of points and capes along the western coast of the United States. Large spatial gradients in wind and temperature become established that can cause anomalous electromagnetic wave propagation. Detailed airborne measurements using the University of Wyoming King Air were conducted to study the adjustment of the MBL to the Point Arguello and Point Conception headlands. Pronounced thinning of the MBL consistent with an expansion fan occurred to the south of Point Conception on 13 June 2012. A sharp cloud edge was collocated with the near collapse of the MBL. D-value cross sections derived from differential GPS altitude measurements allow assessment of the vertical profile of the horizontal pressure gradient force and hence thermal wind forcing in response to the near collapse of the MBL. The Weather Research and Forecasting Model was run with a 1-km grid spacing to examine the atmospheric adjustment around Point Conception during this period. Results from the simulations including the vertical cross sections of the horizontal pressure gradient force were consistent with the aircraft observations. Model results suggest that divergence occurs as the flow rounds Point Conception, characteristic of an expansion fan. Wind speeds in the MBL increase coincident with the decrease in MBL thickness, and subsiding flow associated with the near collapse of the MBL is responsible for the sharp cloud edge.
Because of the drifting nature of the ground track of Jason-1 during its geodetic mission (GM), there are 1200 overlap events where the Jason-1 GM and Jason-2 tracks align perfectly (less than their altimeter footprin...
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Because of the drifting nature of the ground track of Jason-1 during its geodetic mission (GM), there are 1200 overlap events where the Jason-1 GM and Jason-2 tracks align perfectly (less than their altimeter footprint radius) over thousands of kilometers. These overlap events sample homogeneously all longitudes and all time differences (dt) ranging from a few minutes to 10 days or more. When dt is almost zero, the difference is characterized by altimeter noise and its modulation by waves. As dt increases, the rapid ocean variability is revealed. The first statistical analysis of the 1200 events yields variance maps, spectra, autocorrelation, and space-time scales that are consistent with past observations (e.g., the 3-day phase of ERS-1). This paper highlights the value of this Jason-1GM overlap dataset for more sophisticated studies of the rapid ocean variability. There are two major limitations: 1) the noise level of Jason-class altimeters prevents analyzing scales smaller than 80km and 2) short time differences also absorb a fraction of the derivative of slower signals. These findings are important if a geodetic mission is considered for Jason-2 in the coming years (e.g., when the satellite starts to exhibit aging problems): a well-chosen geodetic orbit for Jason-2 has the potential to collect a better distribution of overlap events with Jason-3. To that extent, thousands of orbits were screened to find the options that would provide good geodetic and mesoscale sampling and also maximize the overlap sampling of a tentative Jason-2 GM phase.
Latent 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...
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Latent 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 q(a). However, the q(a) random retrieval error (E-tot) remains unknown. Here, a novel approach is presented to quantify the error contributions to pixel-level q(a) 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. TheMTCapproach permits the derivation of E-tot as the sum of model uncertainty E-M and sensor noise E-N, while random uncertainties due to in situ measurement errors (E-ins) and collocation (E-C) are isolated concurrently. Results show an E-tot average of 1.1 +/- 0.3 g kg(-1), whereas the mean E-C (E-ins) 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 E-tot exceeding 1.5 g kg(-1) within humidity regimes of 12-17 g kg(-1), associated with the single-parameter, multilinear q(a) retrieval applied in HOAPS. Multidimensional bias analysis reveals that global maxima are located off the Arabian Peninsula.
Rainfall intensity displays relationships with atmospheric conditions such as surface temperature, and these relationships have implications for how the intensity of rainfall varies with climate. Here, hourly gauge me...
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Rainfall intensity displays relationships with atmospheric conditions such as surface temperature, and these relationships have implications for how the intensity of rainfall varies with climate. Here, hourly gauge measurements of rainfall over the contiguous United States (CONUS) are related to atmospheric variables taken from the North American Regional Reanalysis for the period 1979-2012. This analysis extends previous work relating the rainfall process to the environment by including a wider range of variables in univariate and bivariate quantile regressions. Known covariate relationships are used to quantify the regional contributions of different weather regimes to rainfall occurrence and to identify preferential atmospheric states for rainfall occurrence. The efficiency of different sets of regressors is evaluated, and the results show that both moisture availability and vertical instability should be taken into account, with CAPE in combination with specific humidity or dewpoint temperature being the most powerful regressors. Different regions and seasons behave differently, pointing to the challenges of constructing global or CONUS-wide models for representing the rainfall process. In particular, the relationships between environment and rainfall in the west of the United States are different from other regions, reflecting nonlocal rainfall processes. Most of the coastal and eastern United States display relatively low regional variability in the relationships between rainfall and environment.
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