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At least 73 records · Page 4

Accuracy of wind measurements using an airborne Doppler lidar

Simulated wind fields and lidar data are used to evaluate two sources of airborne wind measurement error. The system is sensitive to ground speed and track angle errors, with accuracy required of the angle to within 0.2 degrees and of the speed to within 1 knot, if the recovered wind field is to be within five percent of the correct direction and 10 percent of the correct speed. It is found that errors in recovered wind speed and direction are dependent on wind direction relative to the flight path. Recovery of accurate wind fields from nonsimultaneous sampling errors requires that the lidar data be displaced to account for advection so that the intersections are defined by air parcels rather than fixed points in space.

Carroll, J. J.↗

Some tests of flat plate photovoltaic module cell temperatures in simulated field conditions

The nominal operating cell temperature (NOCT) of solar photovoltaic (PV) modules is an important characteristic. Typically, the power output of a PV module decreases 0.5% per deg C rise in cell temperature. Several tests were run with artificial sun and wind to study the parametric dependencies of cell temperature on wind speed and direction and ambient temperature. It was found that the cell temperature is extremely sensitive to wind speed, moderately so to wind direction and rather insensitive to ambient temperature. Several suggestions are made to obtain data more typical of field conditions.

Griffith, J. S.↗

[Measurement of Speed and Direction of Ocean Surface Winds Using Quik Scat Scatterometer]

The SeaWinds on QuikSCAT scatterometer was developed by NASA JPL to measure the speed and direction of ocean surface winds. Simulations performed to estimate the performance of the instrument prior to its launch have indicated that the mid-swath accuracy is worse than that of the rest of the swath. This behavior is a general characteristic of scanning pencil beam scatterometers. For SeaWinds, the accuracy of the rest of the swath, and the size of the swath are such that the instrument meets its science requirements despite mid-swath shortcomings. However, by understanding the problem at mid-swath, we can improve the performance there as well. We discuss the underlying causes of the problem in detail and propose a new wind retrieval algorithm which improves mid-swath performance. The directional discrimination ability of the instrument varies with cross track distance wind speed, and direction. By estimating the range of likely wind directions for each measurement cell, one can optimally apply information from neighboring cells where necessary in order to reduce random wind direction errors without significantly degrading the resolution of the resultant wind field. In this manner we are able to achieve mid-swath RMS wind direction errors as low as 15 degrees for low winds and 10 degrees for moderate to high winds, while at the same time preserving high resolution structures such as cyclones and fronts.

Stiles, Bryan↗

The nature of multiple solutions for surface wind speed over the oceans from scatterometer measurements

The satellite SEASAT-A will carry a radar scatterometer in order to measure microwave backscatter from the sea surface. From pairs of radar measurements at angles separated by 90 deg in azimuth the surface wind speed and direction may be inferred, though not uniquely. The character of the solutions for wind speed and direction is displayed, as well as the nature of the ambiguities of these solutions. An economical procedure for handling such data is described, plus a criterion for the need for conventional (surface) data in order to resolve the ambiguities of solutions.

Price, J. C.↗

The Dependence of Ocean Surface Emissivity on Wind Vector as Measured with TMR

Global TMR brightness temperature observations at 18, 21, and 37 GHz have been colocated with near-simultaneous SeaWinds wind vector data as well as with a monthly SST climatological product. The combined data allow us to study the dependence of ocean surface emissivity, at each frequency, upon both wind speed and direction. Results show a clear two-branch wind speed dependence; weak and linear below 6 m/s with an abrupt increase in sensitivity above that point. Our analysis also shows that the nadir-view ocean surface emissivity depends on the angle between the wind direction and TMR's antenna polarization orientation.

Tran, N.↗

A New Objective Technique for Verifying Mesoscale Numerical Weather Prediction Models

This report presents a new objective technique to verify predictions of the sea-breeze phenomenon over east-central Florida by the Regional Atmospheric Modeling System (RAMS) mesoscale numerical weather prediction (NWP) model. The Contour Error Map (CEM) technique identifies sea-breeze transition times in objectively-analyzed grids of observed and forecast wind, verifies the forecast sea-breeze transition times against the observed times, and computes the mean post-sea breeze wind direction and speed to compare the observed and forecast winds behind the sea-breeze front. The CEM technique is superior to traditional objective verification techniques and previously-used subjective verification methodologies because: It is automated, requiring little manual intervention, It accounts for both spatial and temporal scales and variations, It accurately identifies and verifies the sea-breeze transition times, and It provides verification contour maps and simple statistical parameters for easy interpretation. The CEM uses a parallel lowpass boxcar filter and a high-order bandpass filter to identify the sea-breeze transition times in the observed and model grid points. Once the transition times are identified, CEM fits a Gaussian histogram function to the actual histogram of transition time differences between the model and observations. The fitted parameters of the Gaussian function subsequently explain the timing bias and variance of the timing differences across the valid comparison domain. Once the transition times are all identified at each grid point, the CEM computes the mean wind direction and speed during the remainder of the day for all times and grid points after the sea-breeze transition time. The CEM technique performed quite well when compared to independent meteorological assessments of the sea-breeze transition times and results from a previously published subjective evaluation. The algorithm correctly identified a forecast or observed sea-breeze occurrence or absence 93% of the time during the two- month evaluation period from July and August 2000. Nearly all failures in CEM were the result of complex precipitation features (observed or forecast) that contaminated the wind field, resulting in a false identification of a sea-breeze transition. A qualitative comparison between the CEM timing errors and the subjectively determined observed and forecast transition times indicate that the algorithm performed very well overall. Most discrepancies between the CEM results and the subjective analysis were again caused by observed or forecast areas of precipitation that led to complex wind patterns. The CEM also failed on a day when the observed sea- breeze transition affected only a very small portion of the verification domain. Based on the results of CEM, the RAMS tended to predict the onset and movement of the sea-breeze transition too early and/or quickly. The domain-wide timing biases provided by CEM indicated an early bias on 30 out of 37 days when both an observed and forecast sea breeze occurred over the same portions of the analysis domain. These results are consistent with previous subjective verifications of the RAMS sea breeze predictions. A comparison of the mean post-sea breeze winds indicate that RAMS has a positive wind-speed bias for .all days, which is also consistent with the early bias in the sea-breeze transition time since the higher wind speeds resulted in a faster inland penetration of the sea breeze compared to reality.

Case, Jonathan L.↗

NROSS scatterometer - An instrument for global oceanic wind observations

One of the instruments - the NROSS scatterometer or SCATT - to be launched on the Navy Remote Ocean Sensing System spacecraft in 1989 is discussed. To determine wind speed and direction that SCATT will measure the ocean normalized radar cross section (NRCS) by illuminating the ocean's surface with microwave pulses and measuring the return signal power. A wind retrieval algorithm is used to compute the wind speed and direction from the measured NRCS. Winds over at least 90 percent of the global, ice-free ocean will be observed at least once every two days. For NASA users, the system will retrieve winds with an accuracy of plus or minus 2 m/s or 10 percent whichever is greater, for wind speeds ranging from 3 to 30 m/s.

Li, F.↗

Seasat-A opens new phase in earth observations

The data output of the Seasat-A, the first satellite designed specifically for oceanographic observation, is described. Wave height and direction, ice distribution, surface wind speed and direction, ocean-surface temperature, and atmospheric water content will be monitored by the satellite. Imaging radar, microwave scatterometer, microwave radiometer and visual and infrared radiometer experiments are included in the Seasat-A observing program. Two types of orbits have been developed: a near-repeat cycle of three days, and a near-repeat cycle of 25 days. Both orbit types offer fine coverage (18.5 km crossing separations) of the earth. Synthetic aperture radar data on computer-compatible tapes and geophysical data records available through the Seasat-A mission are described.

Cutting, E.↗

Measurement of oceanic wind vector using satellite microwave radiometers

A feasibility study of deriving both a wind speed and direction from microwave radiometer measurements of the ocean is presented. The study was based on the Special Sensor Microwave/Imager (SSM/I) measurements in conjunction with buoy reports from the National Data Buoy Center. It was found that the SSM/I minus the buoy wind speed difference is correlated with wind direction due to a wind direction signal in the brightness temperatures. When this wind direction signal is removed the rms difference between the SSM/I and buoy winds reduces to 1.3 m/s. The wind direction signal was used to make global, low-resolution maps of the monthly mean oceanic wind vector.

Wentz, Frank J.↗

Lidar Measurements of Wind, and Cloud & Aerosol Structures using HARLIE at the WVIOP, Sept/Oct 2000

The holographic scanning lidar HARLIE made continuous measurements of aerosol and cloud one-micron backscatter and derived the horizontal wind speed and direction at cloud height over the ARM (SGP) site during the water vapor campaign WVIOP, September 17 - October 6, 2000. Whenever possible, these measurements were compared with Loran-C winds as measured by the routine launches of Vaisala radiosonde balloons scheduled by the ARM project. Taken overall, the agreement between these two types of observation is excellent, which could be taken merely as a validation of the relatively new HARLIE technique. However, the detailed comparison for a given sonde launch clearly requires that, out of the HARLIE data which are taken all the time at all altitudes, one must select those segments that match the altitude-time trajectory of the sonde. Moreover, the conical HARLIE scan at a 45 deg. elevation angle covers a wide area that is more representative of the average wind conditions above the site than the isolated track of the sonde's ascent. We suggest that the HARLIE instrument offers a more general and improved representation of the horizontal wind profile whenever there is sufficient backscatter by clouds and aerosols for lidar operation. HARLIE is a rugged and compact lidar that operates from aircraft as well as from the ground and has been used in several meteorological campaigns. As a "direct detection" lidar, HARLIE does not require the complexity of a coherent detection system. The data reduction algorithms facilitate the rapid and accurate determination of wind speed and direction at all altitudes. Wind measurements and HARLIE performance data from WVIOP 2000 and other campaigns will be presented.

Schwemmer, Geary↗

The nature of multiple solutions for surface wind speed over the oceans from scatterometer measurements

The satellite SEASAT-A will carry a radar scatterometer in order to measure microwave backscatter from the sea surface. From pairs of radar measurements at angles separated by 90 deg in azimuth the surface wind speed and direction may be inferred, though not uniquely. In this paper the character of the solutions for wind speed and direction is displayed, as well as the nature of the ambiguities of these solutions. An economical procedure for handling such data is described, plus a criterion for the need for conventional (surface) data in order to resolve the ambiguities of solutions.

Price, J. C.↗

Transition Marshall Space Flight Center Wind Profiler Splicing Algorithm to Launch Services Program Upper Winds Tool

NASAs LSP customers and the future SLS program rely on observations of upper-level winds for steering, loads, and trajectory calculations for the launch vehicles flight. On the day of launch, the 45th Weather Squadron (45 WS) Launch Weather Officers (LWOs) monitor the upper-level winds and provide forecasts to the launch team via the AMU-developed LSP Upper Winds tool for launches at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station. This tool displays wind speed and direction profiles from rawinsondes released during launch operations, the 45th Space Wing 915-MHz Doppler Radar Wind Profilers (DRWPs) and KSC 50-MHz DRWP, and output from numerical weather prediction models.The goal of this task was to splice the wind speed and direction profiles from the 45th Space Wing (45 SW) 915-MHz Doppler radar Wind Profilers (DRWPs) and KSC 50-MHz DRWP at altitudes where the wind profiles overlap to create a smooth profile. In the first version of the LSP Upper Winds tool, the top of the 915-MHz DRWP wind profile and the bottom of the 50-MHz DRWP were not spliced, sometimes creating a discontinuity in the profile. The Marshall Space Flight Center (MSFC) Natural Environments Branch (NE) created algorithms to splice the wind profiles from the two sensors to generate an archive of vertically complete wind profiles for the SLS program. The AMU worked with MSFC NE personnel to implement these algorithms in the LSP Upper Winds tool to provide a continuous spliced wind profile.The AMU transitioned the MSFC NE algorithms to interpolate and fill data gaps in the data, implement a Gaussian weighting function to produce 50-m altitude intervals in each sensor, and splice the data together from both DRWPs. They did so by porting the MSFC NE code written with MATLAB software into Microsoft Excel Visual Basic for Applications (VBA). After testing the new algorithms in stand-alone VBA modules, the AMU replaced the existing VBA code in the LSP Upper Winds tool with the new algorithms. They then tested the code in the LSP Upper Winds tool with archived data. The tool will be delivered to the 45 WS after the 50-MHz DRWP upgrade is complete and the tool is tested with real-time data. The 50-MHz DRWP upgrade is expected to be finished in October 2014.

Space launch↗

Extreme Wind Velocity Measurement System

A wind velocity measurement system employs two different principles of physics to measure wind speed: (1) the aerodynamic force imparted to a low profile, rigidly mounted cylindrical rod, and (2) the vibrating frequency of the rod as vortices are shed from the rod's cylindrical surface. A set of strain gages is used as a common sensor for both measurements, and these provide force measurements imparted by the wind on the rod. The signals generated by the strain gages are fed to processing circuitry that calculates the wind speed and direction from the signals. The force measurement is proportional to the square of the wind speed. Since it is a vector quantity, it can also be used to derive wind direction. The vortex shedding frequency is a scalar quantity and is linearly proportional to wind speed. This frequency can be calculated by analyzing the force measurements generated by the strain gages over time. Both of the wind velocity calculations can be advantageously used by the processing circuitry to generate an accurate wind velocity reading.

Jan A Zysko↗

30 WS North Base Wind Study

The 30 Weather Squadron (30 WS) is concerned about strong winds observed at their northern towers without advance warning. They state that terrain influences along the extreme northern fringes of Vandenberg Air Force Base (VAFB) make it difficult for forecasters to issue timely and accurate high wind warnings for northeasterly wind events. These events tend to occur during the winter or early spring when they are under the influence of the Great Basin high pressure weather regime. The Launch Weather Officers (LWOs) have seen these rapid wind increases in the current northern Towers 60, 70 and 71 in excess of their 35 kt operational warning threshold. For this task, the 30 WS requested the Applied Meteorology Unit (AMU) analyze data from days when these towers reported winds in excess of 35 kt and determine if there were any precursors in the observations that would allow the LWOs to better forecast and warn their operational customers for these wind events. The 30 WS provided wind tower data for the cool season (October - March) from the period January 2004-March 20 IO. The AMU decoded and evaluated the wind tower data for 66 days identified by the 30 WS as having high-wind events. Out of the 66 event days, only 30 had wind speed observations of > or =35 kt from at least one of the three northern towers. The AMU analyzed surface and upper air charts to determine the synoptic conditions for each event day along with tower peak wind speed and direction time series and wind rose charts for all 30 event days. The analysis revealed a trend on all event days in which the tower winds shifted to the northeast for a period of time before the first recorded > or =35 kt wind speed. The time periods for the 30 event days ranged from 20 minutes to several hours, with a median value of 110 minutes. This trend, if monitored, could give the 30 WS forecasters a precursor to assist in issuing an operational warning before a high wind event occurs. The AMU recommends developing a high-wind alert capability for VAFB using a local mesoscale model to forecast these wind events. The model should incorporate all of the VAFB local data sets and have a forecast capability of between 2 to 24 hours. Such a model would allow the meteorologists at VAFB to alert the operational customers of high wind events in a timely manner so protective action could be taken.

Wheeler, Mark↗

The SeaSat-A satellite scatterometer

This paper describes the methods used to develop performance requirements and design characteristics for the microwave scatterometer (SASS) ocean-surface wind sensor on the NASA SeaSat-A satellite. Wind vector measurement requirements from the SeaSat user community (wind speed and direction accuracy, resolution cell size, grid spacing, and swath width) define instrument characteristics. The resulting scatterometer is designed for 14.6 GHz using four fan beam antennas to measure wind speed and direction over a 1000-km swath width with a resolution cell size 50 x 50 km. Results show scatterometer accuracy satisfies user requirements for wind speed from 4 m/s to greater than 24 m/s for the nominal SeaSat-A orbit of 790 km altitude, 108 deg inclination, and 0.001 eccentricity.

Grantham, W. L.↗

Near-Nadiral Normalized Radar Cross Section of the SEA Surface at Ku, Ka, and W-Bands: Comparison of Measurements and Models

Understanding the relationship between wind speed and direction and the near-nadiral normalized radar cross section (NRCS) of the sea surface is important in many oceanographic and atmospheric remote sensing applications: (1) wind speed retrievals in traditional altimeter systems (2) assistance in calibration and path integrated attenuation processing for atmospheric profiling radars The desired wind speed (and direction in some cases) retrieval requires a clear understanding of the relationship between the relevant geophysical quantities and the observed NRCS Such understanding is available from existing electromagnetic models, but the presence of many such models, as well as implicit descriptions of the sea surface, motivates continued evaluation of model performance.

CloudSat↗

Project Fog Drops. Part 1: Investigations of warm fog properties

A detailed study was made of the micrometeorological and microphysical characteristics of eleven valley fogs occurring near Elmira, New York. Observations were made of temperature, dew point, wind speed and direction, dew deposition, vertical wind velocity, and net radiative flux. In fog, visibility was continuously recorded and periodic measurements were made of liquid water content and drop-size distribution. The observations were initiated in late evening and continued until the time of fog dissipation. The vertical distribution of temperature in the lowest 300 meters and cloud nucleus concentration at several heights were measured from an aircraft before fog nucleus concentrations at several heights were measured from an aircraft before fog formation. A numerical model was developed to investigate the life cycle of radiation fogs. The model predicts the temporal evolution of the vertical distributions of temperature, water vapor, and liquid water as determined by the turbulent transfer of heat and moisture. The model includes the nocturnal cooling of the earth's surface, dew formation, fog drop sedimentation, and the absorption of infrared radiation by fog.

Pilie, R. J.↗

Combined VHF Dopplar radar and airborne (CV-990) measurements of atmospheric winds on the mesoscale

Hourly measurements of wind speed and direction obtained using two wind profiling Doppler radars during two prolonged jet stream occurrences over western Pennsylvania were analyzed. In particular, the time-variant characteristics of derived shear profiles were examined. To prevent a potential loss of structural detail and retain statistical significance, data from both radars were stratified into categories based on the location data from the Penn State radar were also compared to data from Pittsburgh radiosondes. Profiler data dropouts were studied in an attempt to determine possible reasons for the apparently reduced performance of profiling radars operating beneath a jet stream. Temperature profiles for the radar site were obtained using an interpolated temperature and dewpoint temperature sounding procedure developed at Penn State. The combination of measured wind and interpolated temperature profiles allowed Richardson number profiles to be generated for the profiler sounding volume. Both Richardson number and wind shear statistics were then examined along with pilot reports of turbulence in the vicinity of the profiler.

Fairall, Christopher W.↗