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At least 127 records · Page 7

An empirical model for ocean radar backscatter and its application in inversion routine to eliminate wind speed and direction effects

Several regression models were tested to explain the wind direction dependence of the 1975 JONSWAP (Joint North Sea Wave Project) scatterometer data. The models consider the radar backscatter as a harmonic function of wind direction. The constant term accounts for the major effect of wind speed and the sinusoidal terms for the effects of direction. The fundamental accounts for the difference in upwind and downwind returns, while the second harmonic explains the upwind-crosswind difference. It is shown that a second harmonic model appears to adequately explain the angular variation. A simple inversion technique, which uses two orthogonal scattering measurements, is also described which eliminates the effect of wind speed and direction. Vertical polarization was shown to be more effective in determining both wind speed and direction than horizontal polarization.

Dome, G. J.↗

Sensitivity analysis of the effect of wind and wake characteristics on wind turbine loads in a small wind farm

Abstract. Wind turbines are designed using a set of simulations to determine the fatigue and ultimate loads, which are typically focused solely on unwaked wind turbine operation. These structural loads can be significantly influenced by the wind inflow conditions. Turbines experience altered inflow conditions when placed in the wake of upstream turbines, which can additionally influence the fatigue and ultimate loads. It is important to understand the impact of uncertainty on the resulting loads of both unwaked and waked turbines. The goal of this work is to assess which wind-inflow-related and wake-related parameters have the greatest influence on fatigue and ultimate loads during normal operation for turbines in a three-turbine wind farm. Twenty-eight wind inflow and wake parameters are screened using an elementary effects sensitivity analysis approach to identify the parameters that lead to the largest variation in the fatigue and ultimate loads of each turbine. This study uses the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine, simulated with OpenFAST and synthetically generated inflow based on the International Electrotechnical Commission (IEC) Kaimal turbulence spectrum with the IEC exponential coherence model using the NREL tool TurbSim. The focus is on sensitivity to individual parameters, though interactions between parameters are considered, and how sensitivity differs between waked and unwaked turbines. The results of this work show that for both waked and unwaked turbines, ambient turbulence in the primary wind direction and shear are the most sensitive parameters for turbine fatigue and ultimate loads. Secondary parameters of importance for all turbines are identified as yaw misalignment, streamwise integral length, and the exponent and streamwise components of the IEC coherence model. The tertiary parameters of importance differ between waked and unwaked turbines. Tertiary effects account for up to 9.0 % of the significant events for waked turbine ultimate loads and include veer, non-streamwise components of the IEC coherence model, Reynolds stresses, wind direction, air density, and several wake calibration parameters. For fatigue loads, tertiary effects account for up to 5.4 % of the significant events and include vertical turbulence standard deviation, lateral and vertical wind integral lengths, non-streamwise components of the IEC coherence model, Reynolds stresses, wind direction, and all wake calibration parameters. This information shows the increased importance of non-streamwise wind components and wake parameters in the fatigue and ultimate load sensitivity of downstream turbines.

17 WIND ENERGY↗

Trace Gases, Meteorological Parameters, and GPS data for TRACER-MAP

This dataset includes trace gas, meteorological, and GPS measurements made on Mobile Air Quality Laboratory 2 (MAQL2) for the TRACER-MAP sampling campaign. Trace gas measurements include nitric oxide (NO), nitrogen dioxide (NO2), reactive nitrogen compounds (NOy), ozone (O3), sulfur dioxide (SO2), and carbon monoxide (CO). All trace gases are in units of ppbv, excluding CO which is in ppmv. The dataset also includes the photolysis rate of NO2 (jNO2), latitude and longitude, wind speed (WS), wind direction (WD), ambient relative humidity (RH), ambient pressure (press), and ambient temperature (temp). Units for trace gases are in parts per billion (ppbv), latitude and longitude are in decimal degrees (dd), jNO2 is in per second (per sec), pressure is in millibar (mbar), relative humidity is in percent, the temperature is in degrees C, wind direction is in degrees, and wind speed is in meters per second. All data is 5 minutes averaged.

54 ENVIRONMENTAL SCIENCES↗

Direct Solar Wind Proton Access into Permanently Shadowed Lunar Polar Craters

Recent analyses of Lunar Prospector neutron spectrometer (LPNS) data have suggested that high abundances of hydrogen exist within cold traps at the lunar poles, and it has often been assumed that hydrogen-bearing volatiles sequestered in permanent shadow are topographically shielded from sputtering by solar wind protons. However, recent simulation results are presented showing that solar wind protons clearly access the floor of an idealized, shadowed lunar crater through a combination of thermal and ambipolar processes, in effect creating a plasma "miniwake". These simulations are the first to model the mini-wake environment in two spatial dimensions with a self-consistent lunar surface-plasma interaction. Progress is reported on constraining the nonzero particle fluxes and energies incident on kilometer-scale shadowed topography, such as a small crater embedded within a larger one. The importance of direct solar wind proton bombardment is discussed within the context of understanding the stability and inventory of hydrogen-bearing volatiles in shadow at the lunar poles. The support of the National Lunar Science institute, the DREAM institute, LPROPS, and the NASA Postdoctoral Program at NASA Goddard Space Flight Center administered by ORAU are gratefully acknowledged.

Zimmerman, M. I.↗

Considering Factors for Ion Concentrations in Precipitation at the Savannah River Site

Precipitation was collected from three different areas on the Savannah River Site during 2021. The precipitation was analyzed for concentrations of 29 different ions and compared with data on factors such as wind speed, wind direction, rain drop sizes, and more. The 2021 ion concentrations were also compared to the ion concentrations from previous years at the site as well as from Santee National Wildlife Refuge which is nearby. The historical ion concentrations data was gathered from the National Atmospheric Deposition Program. Scatter plots and correlation coefficients were used to identify what factors may have the greatest impact on ion concentration in rainwater. The data generally followed the same trends with a few notable outliers. There initially seemed to be a strong correlation between the mean diameter and some ion concentrations as both increased in July. However, ion concentrations in different areas were related to different wind directions, thus spatial variability must be considered. These factors, spatial variability of atmospheric particles and wind direction, impact concentrations of ions in precipitation.

54 ENVIRONMENTAL SCIENCES↗

Aircraft measurements of the microwave scattering signature of the ocean

Microwave scattering signatures of the ocean have been measured over a range of surface wind speeds from 3 m/s to 23.6 m/s using the AAFE RADSCAT scatterometer in an aircraft. Normalized scattering coefficients are presented for vertical and horizontal polarizations as a function of incidence angle (nadir to 55 deg) and radar azimuth angle (0 to 360 deg) relative to surface wind direction. For a given radar polarization, incidence angle, and azimuth angle relative to the wind direction, these scattering data exhibit a power law dependence on surface wind speed. The relation of the scattering coefficient to azimuth angle obtained during aircraft circles (antenna conical scans) is anisotropic and suggests that microwave scatterometers can be used to infer both wind speed and direction. These results have been used for the design of the Seasat-A Satellite Scatterometer (SASS) to be flown in 1978 on this first NASA oceanographic satellite.

Jones, W. L.↗

Vector wind and vector wind shear models 0 to 27 km altitude for Cape Kennedy, Florida, and Vandenberg AFB, California

The techniques are presented to derive several statistical wind models. The techniques are from the properties of the multivariate normal probability function. Assuming that the winds can be considered as bivariate normally distributed, then (1) the wind components and conditional wind components are univariate normally distributed, (2) the wind speed is Rayleigh distributed, (3) the conditional distribution of wind speed given a wind direction is Rayleigh distributed, and (4) the frequency of wind direction can be derived. All of these distributions are derived from the 5-sample parameter of wind for the bivariate normal distribution. By further assuming that the winds at two altitudes are quadravariate normally distributed, then the vector wind shear is bivariate normally distributed and the modulus of the vector wind shear is Rayleigh distributed. The conditional probability of wind component shears given a wind component is normally distributed. Examples of these and other properties of the multivariate normal probability distribution function as applied to Cape Kennedy, Florida, and Vandenberg AFB, California, wind data samples are given. A technique to develop a synthetic vector wind profile model of interest to aerospace vehicle applications is presented.

Smith, O. E.↗

Continuous sensor suite measurements of weather, energy, soil and flux at four PumpHouse sites at the East River, Colorado

The purpose of this package is to monitor energy and water fluxes using a comprehensive set of sensors integrated on a tripod set up at 4 locations at the East River watershed in Colorado in the Upper Colorado River Basin as part of the Scientific Focus Area (SFA) research led by the Lawrence Berkeley National Lab (LBNL). This is a continuous sensor suite measurements of weather, energy, soil and flux at four East River pumphouse sites (ER-PHS1, ER-PHS2, ER-PHS3 and ER-PHS4) include: (1) soil CO2 concentration, CO2 flux and heat flux from soil surface; (2) photosynthetic active radiation flux at 1 m; (3) incoming/outcoming short and long wave radiation at 1 m, and user calculated net short and long wave radiation; (4) oxygen concentration and surface infrared temperature; (5) soil volumetric water content, temperature, and electrical conductivity at 10, 30, 60, 115 cm depth 115 cm depth; (6) soil matric potential and temperature at 30 cm depth; (7) incoming short wave radiation at 3 m height; (8) rainfall precipitation; (9) lightning strikes and strike distances; (10) wind direction and speed, maximum wind gust at 3 m; (11) air temperature, vapor pressure and barometric pressure at 3 m; (12) X _axis_level and Y_axis_level_(degree), tilt of the ATMOS 41 sensor; (13) maximum rainfall rate; (14) relative humidity sensor temperature at 3 m; (15) internally calculated vapor pressure deficit at 3 m with vapor pressure, relative humidity and sensor temperature measurements; (16) user calculated vapor pressure.These datasets contain data from Oct 11 2019 to March 20, 2020, and new datasets will be updated on annual basis. Files uploaded in Excel and Word, with copies in csv and pdf format.

54 ENVIRONMENTAL SCIENCES↗

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.↗

How Does Inow Veer Affect the Veer of a Wind-Turbine Wake?

Stably stratified flow conditions often exhibit wind veer, or a change of wind direction with height. When wind turbines experience this veered flow, the resulting wake structure tends to exhibit a stretching into an ellipsoid, rather than a symmetric shape or a curled shape. Observational studies suggest that the magnitude of wake veer is less than the veer of the inflow, whereas large-eddy simulations with actuator disk models and actuator line models suggest a range of relationships between inflow veer and wake veer. Here we present a series of large-eddy simulations with a range of veer shapes, a range of magnitudes of veer, a range of wind speeds, and both rotational directions of the wind-turbine rotor investigating the effect on the wake deflection angle. These results can guide the application of wake steering in stably stratified flow.

17 WIND ENERGY↗

Deriving earth science products from SSM/I

A few of the major accomplishments during the second phase include: (1) all three Special Sensor Microwave Imagers (SSM/I's: F08, F10, and F11) have been cross-calibrated; (2) a very large, quality-controlled, collocated SSM/I and radiosonde data set has been produced; (3) the SSM/I-radiosonde and SSM/I-buoy data sets have been used to calibrate the SSM/I ocean retrieval algorithm; (4) ocean products have been produced for both F10 and F11 SSM/I for 1991-1993; (5) the SSM/I-buoy data set was used to better determine the variation of the ocean T(sub B) with wind direction; and (6) it was demonstrated that under high wind conditions, wind direction information can be obtained from individual SSM/I observations.

Wentz, Frank J.↗

Real-Time Kennedy Space Center and Cape Canaveral Air Force Station High-Resolution Model Implementation and Verification

Customer: NASA's Launch Services Program (LSP), Ground Systems Development and Operations (GSDO), and Space Launch System (SLS) programs. NASA's LSP, GSDO, SLS and other programs at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) use the daily and weekly weather forecasts issued by the 45th Weather Squadron (45 WS) as decision tools for their day-to-day and launch operations on the Eastern Range (ER). For example, to determine if they need to limit activities such as vehicle transport to the launch pad, protect people, structures or exposed launch vehicles given a threat of severe weather, or reschedule other critical operations. The 45 WS uses numerical weather prediction models as a guide for these weather forecasts, particularly the Air Force Weather Agency (AFWA) 1.67 kilometer Weather Research and Forecasting (WRF) model. Considering the 45 WS forecasters' and Launch Weather Officers' (LWO) extensive use of the AFWA model, the 45 WS proposed a task at the September 2013 Applied Meteorology Unit (AMU) Tasking Meeting requesting the AMU verify this model. Due to the lack of archived model data available from AFWA, verification is not yet possible. Instead, the AMU proposed to implement and verify the performance of an ER version of the AMU high-resolution WRF Environmental Modeling System (EMS) model (Watson 2013) in real-time. The tasking group agreed to this proposal; therefore the AMU implemented the WRF-EMS model on the second of two NASA AMU modeling clusters. The model was set up with a triple-nested grid configuration over KSC/CCAFS based on previous AMU work (Watson 2013). The outer domain (D01) has 12-kilometer grid spacing, the middle domain (D02) has 4-kilometer grid spacing, and the inner domain (D03) has 1.33-kilometer grid spacing. The model runs a 12-hour forecast every hour, D01 and D02 domain outputs are available once an hour and D03 is every 15 minutes during the forecast period. The AMU assessed the WRF-EMS 1.33-kilometer domain model performance for the 2014 warm season (May-September). Verification statistics were computed using the Model Evaluation Tools, which compared the model forecasts to observations. The mean error values were close to 0 and the root mean square error values were less than 1.8 for mean sea-level pressure (millibars), temperature (degrees Kelvin), dewpoint temperature (degrees Kelvin), and wind speed (per millisecond), all very small differences between the forecast and observations considering the normal magnitudes of the parameters. The precipitation forecast verification results showed consistent under-forecasting of the precipitation object size. This could be an artifact of calculating the statistics for each hour rather than for the entire 12-hour period. The AMU will continue to generate verification statistics for the 1.33-kilometer WRF-EMS domain as data become available in future cool and warm seasons. More data will produce more robust statistics and reveal a more accurate assessment of model performance. Once the formal task was complete, the AMU conducted additional work to better understand the wind direction results. The results were stratified diurnally and by wind speed to determine what effects the stratifications would have on the model wind direction verification statistics. The results are summarized in the addendum at the end of this report. In addition to verifying the model's performance, the AMU also made the output available in the Advanced Weather Interactive Processing System II (AWIPS II). This allows the 45 WS and AMU staff to customize the model output display on the AMU and Range Weather Operations AWIPS II client computers and conduct real-time subjective analyses. In the future, the AMU will implement an updated version of the WRF-EMS model that incorporates local data assimilation. This model will also run in real-time and be made available in AWIPS II.

Numerical Weather Prediction↗

Calibration of Instruments for Measuring Wind Velocity and Direction

Signal Corps wind equipment AN/GMQ-1 consisting of a 3-cup anemometer and wind vane was calibrated for wind velocities from 1 to 200 miles per hour. Cup-shaft failure prevented calibration at higher wind velocities. The action of the wind vane was checked and found to have very poor directional accuracy below a velocity of 8 miles per hour. After shaft failure was reported to the Signal Corps, the cup rotors were redesigned by strengthening the shafts for better operation at high velocities. The anemometer with the redesigned cup rotors was recalibrated, but cup-shaft failure occurred again at a wind velocity of approximately 220 miles per hour. In the course of this calibration two standard generators were checked for signal output variation, and a wind-speed meter was calibrated for use with each of the redesigned cup rotors. The variation of pressure coefficient with air-flow direction at four orifices on a disk-shaped pitot head was obtained for wind velocities of 37.79 53.6, and 98.9 miles per hour. A pitot-static tube mounted in the nose of a vane was calibrated up to a dynamic pressure of 155 pounds per square foot, or approximately 256 miles per hour,

Vogler, Raymond D.↗

NNSS Soils Monitoring: Plutonium Valley (CAU 366) FY2019

Desert Research Institute (DRI) conducted a field assessment of the potential for radionuclide-contaminated soil to be transported from the Plutonium Valley Dispersion Sites Contamination Area (CA) because of both wind and storm water runoff. This activity supported U.S. Department of Energy (DOE) Environmental Management Nevada Program (EM NV) efforts to establish post-closure monitoring plans for the Plutonium Valley Dispersion Sites Corrective Action Unit (CAU) 366. The DRI task was intended to identify the likely mechanism(s) of transport and determine the meteorological conditions that might cause the movement of radionuclide-contaminated soils. The emphasis of the work was on collecting sediment transported by channelized storm runoff and measuring airborne dust concentrations and associated wind conditions. These data will facilitate an appropriate post-closure monitoring program. In 2011, DRI installed meteorological monitoring stations north and south of the Plutonium Valley CA—known as Pu Valley North and Pu Valley South, respectively—as well as a fluvial sediment sampling station within the CA. Since installation, temperature, wind speed, wind direction, relative humidity, precipitation, solar radiation, barometric pressure, soil temperature, volumetric soil moisture content, and airborne particulate concentrations have been collected at both meteorological stations. The maximum, minimum, and average or total (as appropriate) for each of these parameters were recorded for each 10-minute interval. The sediment sampling station included an automatically activated sampling pump with collection bottles for suspended sediment, which was activated when sufficient flow was present in the channel, and passive traps for bedload material that was transported down the channel during runoff events. This report presents data collected from these stations during fiscal year (FY) 2019. During the FY2019 (October 1, 2018, through September 30, 2019) reporting period, the warmest month was July and the coldest month was February. Monthly total solar radiation was highest in June or July (depending on the station) and lowest in December. Monthly mean wind speeds were highest during February. At the Pu Valley North station, winds were commonly northerly, northwesterly, and southerly. At the Pu Valley South station, the wind direction was more variable and winds frequently came from most directions, excluding westerly and northwesterly winds. Winds above 15.0 miles per hour (mph) (24.1 kilometers per hour [km/hr]) were frequently southerly at both stations, and less-frequent strong winds were northerly (at the Pu Valley South station) or northwesterly (at the Pu Valley North station). Monthly average relative humidity ranged from 18 percent in August to 62 percent in January and February. Monthly total precipitation ranged from zero at both stations in September to 2.23 inches (in) (56.6 millimeters [mm]) during February at the Pu Valley South station and 2.09 in (53.1 mm) during March at the Pu Valley North station. From October 1, 2018, through September 30, 2019, the total precipitation was 8.23 in (209 mm) and 8.15 in (207 mm) at the Pu Valley South and Pu Valley North stations, respectively. The largest daily precipitation totals of 1.46 in (37.1 mm) and 1.14 in (29.0 mm) occurred at the Pu Valley South and Pu Valley North stations, respectively, on March 6, 2019. However, the ISCO autosampler was not activated during any storm event in FY2019 because the channel water depth measurements were insufficient for suspended sediment sample collection. Additionally, because no significant flow through the channel was indicated, no bedload samples were collected. Light breezes of 0.0 mph to 5.0 mph (0.0 km/hr to 8.0 km/hr) occurred most frequently (approximately 55 percent to 57 percent of the time). The frequency of occurrence diminished exponentially as the wind speed increased such that winds in excess of 25.0 mph (40.2 km/hr) occurred less than 0.01 percent of the time. Winds in excess of 15.0 mph (24.1 km/hr) were most commonly southerly, which is likely controlled by the topography of the valley because topographic highs define the east and west sides of the valley and converge toward the north.The concentrations of PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 micrometers [μm]) and PM10 (particulate matter with an aerodynamic diameter ≤10 μm) in the air generally increase as wind speed increases. However, the particle profiler at the Pu Valley South station regularly malfunctioned, which resulted in poor data quality and a limited period of record within FY2019. Therefore, discussion of the annual dust observations is mostly limited to the Pu Valley North station. At the Pu Valley North station, significant increases in windblown dust concentrations were observed when wind speeds exceeded 15.0 mph (24.1 km/hr), especially during southerly winds. When all wind speeds were considered, high dust concentrations at the Pu Valley North station were frequently associated with northerly, northwesterly, or southerly winds. The majority of PM10 transport at the Pu Valley North station occurred when winds were blowing northerly and northwesterly because of the high frequency of winds up to 15.0 mph (24.1 km/hr). The ratio of PM10 to PM2.5 is a qualitative indicator of the proximity of dust sources to the observation point and the values of the PM10 to PM2.5 ratio tend to be higher nearer to the source. The PM10 to PM2.5 ratio increased from 1.2 to 2.8 with higher wind speeds at the Pu Valley North station. This increase suggests that some locally sourced PM10 was present in the air when local winds exceeded 15.0 mph (24.1 km/hr). Local dust suspension is interpreted during major dust events when peaks in the PM10 to PM2.5 ratio occur simultaneously with the maximum wind speed and the peak PM10 concentration. Analysis of the five major dust events in FY2019 revealed that northerly winds were dominant in three events and southerly winds were dominant in two events. Local suspension of dust within Plutonium Valley is suspected to have occurred during two of the five major events (April 9, 2019, and September 28 to 29, 2019), and a nonlocal source of dust is presumed for the three other major dust events (October 14, 2018; May 16, 2019; and September 2, 2019). The three suspected regional dust transport events exhibited winds that typically did not exceed the 15.0 mph (24.1 km/hr) wind speed threshold for local dust transport and featured PM10 to PM2.5 ratios that indicate large-scale regional dust transport. Similar event characteristics (e.g., wind speed and PM10 concentration) were observed at air monitoring stations approximately 70 mi (113 km) to the northwest within the Tonopah Test Range (TTR). Therefore, these three regional events may not reflect transport from the Plutonium Valley CA. Routine monitoring of meteorological and hydrologic parameters at Plutonium Valley has been discontinued at the request of EM NV, effective at the conclusion of FY2019. Environmental data acquisition has been completed, and both Pu Valley North and Pu Valley South meteorological stations within Plutonium Valley as well as the ISCO autosampler station within the CA were removed on October 14, 2019.

54 ENVIRONMENTAL SCIENCES↗

An Update to the Warm-Season Convective Wind Climatology of KSC/CCAFS

Total of 1100 convective events in the 17-year warm-season climatology at KSC/CCAFS. July and August typically are the peak of convective events, May being the minimum. Warning and non-warning level convective winds are more likely to occur in the late afternoon (1900-2000Z). Southwesterly flow regimes and wind directions produce the strongest winds. Storms moving from southwesterly direction tend to produce more warning level winds than those moving from the northerly and easterly directions.

Lupo, Kevin↗

Comparison of electro-thermal performance of advanced cooling techniques for electric vehicle motors

Permanent magnet synchronous motors are commonly used in the powertrain of electric vehicles because of their high power and torque densities. Attempts to increase power and torque densities beyond the state-of-the-art often suffer from thermal limitations of the adopted winding-wire insulation class. In this paper, overall effectiveness of four different cooling technologies, namely conventional stator jacket cooling, embedded circular and rectangular cooling channels within stator core, and direct winding heat exchangers have been studied numerically. Here, by realizing temperature dependent magnetic and material properties, winding and core losses, a two-way coupling algorithm has been utilized to study the detailed electro-magnetic and thermal performance of BMW i3 motor with aforementioned cooling techniques. The numerical results illustrated that the direct winding heat exchangers approach provides better electro-thermal performance in comparison to the other cooling techniques analyzed. On the contrary, embedded rectangular and circular channel in stator core adversely affect the electro-magnetic performance and overall efficiency of the motor, despite their superior thermal performance compared to the jacket cooling

42 ENGINEERING↗

Seasat-A - An ocean observation satellite

Mission details, onboard equipment, and measurements to be taken are described for the Seasat-A global ocean monitoring satellite. The satellite is designed for mapping the global ocean geoid, charting ice fields and leads, precision measurement of sea surface topography, global monitoring of wave height and wave directional spectra, surface winds and wind direction, current patterns, and ocean temperature. Data handling subsystems, a compressed pulse radar altimeter, coherent synthetic aperture imaging radar, microwave wind scatterometer, scanning visible/IR radiometer, scanning multispectral (5 freq) microwave radiometer mounted on the satellite are described briefly.

Williams, F. L.↗

Mars atmospheric circulation - Aspects from Viking Landers

Winds measured by the two Viking Landers have been filtered and then compared with predictions from the general circulation model and to Orbiter observations of clouds and surface phenomena that indicate wind direction. This was done to determine the degree to which filtered winds may represent aspects of the general circulation. Excellent agreement was found between wind direction data from Lander 1 and the model predictions and Orbiter observations. For Lander 2, agreement was generally good, but there were periods of disagreement which indicate that the filtering did not remove other extraneous effects. It is concluded that Lander 1 gives a good representation of the general circulation at 22.5 deg N latitude but that Lander 2 is suspect. Most wind data from Lander 1 have yet to be analyzed. It appears that when analyzed these Lander 1 data (covering 3.5 Mars years) can provide information about interannual variations in the general circulation at the Lander latitude.

Ryan, J. A.↗