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TRAINING MANUAL NUMBER ONE :

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PREPARED FOR THE OFFICE OF METEOROLOGY NATIONAL WEATHER SERVICE fe no BY THE PROGRAM FOR REGIONAL OBSERVING AND FORECASTING SERVICES ENVIRONMENTAL RESEARCH LABORATORIES NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION PROFILER TRAINING MANUAL #1 Principles of Wind Profiler Operation

Developed for the National Weather Service Office of Meteorology J 1 o s Lb: jul < r I? -J Douglas W. van de Kamp SIS. DOT OHMUMBT Profiler Program NOAA/ERL Boulder, Colorado

(yw Poc, , c March 1988 55. 2 ■■ W NOTICE

Mention of a commercial company or product does not constitute an endorsement by NOAA Environmental Research Laboratories. NOAA does not authorize, for publicity or advertising, the use of any information from this publication concerning proprietary products or the tests of such products.

11 Author's Preface

In the past decade, wind profilers have evolved from individual atmospheric research systems to a 30-site demonstration network which will be installed in the central United States by mid 1990, called the Wind Profiler Demonstration Network (WPDN).

Although the research community has been observing wind profiler data for over five years, we have not explored all their uses, This manual is the first in a series of four manuals and videotapes summarizing our current experience with the operation, quality control, and meteorological use of wind profiler data.

I would like to thank Tom Schlatter of the Program for Regional Observing and Fore­ casting Services (PROFS) and Fred Zbar, Brian Smith, Dan Smith, Joe Schaefer, Andy Edman, and Larry Dunn of the National Weather Service for their constructive reviews and comments. Thanks also to the Wind Profiler Research group of the Wave Propaga­ tion Laboratory for supplying the profiler data presented in this manual.

- Ill

Contents

1. Introduction and Short History of Wind Profilers ...... 1 1.1. What is a Wind Profiler?...... 1 1.2. From Early Research Systems to the Present Development of a 30-Station Demonstration Network...... 1 1.3. Description and Uses of Wind Profiler Data...... 2 1.4. Advantages and Disadvantages of the Wind Profilers...... 6

2. Principles of Operation ...... 8 2.1. System Hardware ...... 8 2.1.1. Transmitter and power supply ...... 8 2.1.2. Antenna...... 9 2.1.3. Receiver and computer...... 10 2.2. Antenna Configuration...... 11 2.2.1. Number of beams needed ...... 11 2.2.2. Pointing angles of each beam ...... 12 2.2.3. How a phased array works...... 13 2.3. Use of Atmospheric Turbulence as a Measure of the Mean Wind ...... 15 2.3.1. Scales of turbulence ...... 15 2.3.2. Doppler shift...... 15 2.4. The Doppler Signal Spectrum and Its Uses ...... 15 2.4.1. Returned power estimate...... 16 2.4.2. Radial velocity estimate...... 16 2.4.3. Spectral width estimate...... 17 2.5. From Radial Components to Horizontal Winds...... 17

3. Accuracy and Limitations of Wind Profiler Data ...... 20 3.1. Assumption of Uniformity of the Wind Field Across All Beams ...... 20 3.2. Increased Signal-to-noise Ratio by Time-averaging ...... 21 3.3. Internal Electronic Noise...... 21 3.4. External Electronic Noise ...... 21 3.5. Side Lobes...... 23 3.6. Precipitation and Vertical Velocity Correction...... 23 3.7. Effect of Aircraft on the Data...... 24 3.8. Expected Accuracy...... 24 3.8.1. Profiler vs. rawinsonde ...... 24 3.8.2. Profiler vs. lidar ...... 25 3.8.3. Profiler vs. profiler ...... 25

4. Practical Information on the 30-Station Demonstration Network ...... 27 4.1. Location of Profiling Sites...... 27 4.2. Products, Schedules, and Communications ...... 27 4.3. Effects of Minimizing Satellite Interference ...... 28 4.4. The Hub...... 30

V 4.5. Expected Height Coverage...... 31 4.6. Mean Time Between Failure (MTBF)...... 31 4.7. Mean Time To Repair...... 32 4.8. Hub Failure...... 32

5. References...... 33

Appendix A. A Detailed Look at the Doppler Signal Spectrum...... 35

Appendix B. Examples of Wind Profiler Data...... 40

VI 1. Introduction and Short History of Wind Profilers

1.1. What is a Wind Profiler? A wind profiler is a Doppler radar used to measure the atmospheric winds above a profiler site. Typical operation of a wind profiler produces a vertical profile of the winds every hour from near the Earth's surface to above the tropopause.

The WPDN wind profilers are designed to operate reliably and unattended in nearly all weather conditions. To achieve this reliability, they have a minimum number of moving parts; therefore a fixed beam antenna is used. Obtaining wind profiles consistently to the tropopause in nearly all weather conditions requires the use of a relatively long wavelength radar. Typical NWS weather radars that have been operational for the past 30 years operate with wavelengths of 10 cm or less and require cloud or precipitation particles to act as reflectors. Wind profilers are relatively low-power, highly sensitive clear-air radars, operating with wavelengths from 33 cm to 6 meters. The radars detect fluctuations in atmospheric density, caused by the turbulent mixing of volumes of air with slightly different temperature and moisture content. The resulting fluctuations of the index of refraction are used as a tracer of the mean wind in the clear air. Although re­ ferred to as clear-air radars, wind profilers are capable of operating in the presence of clouds and precipitation.

1.2. From Early Research Systems to the Present Development of a 30-Station Demonstration Network Early radars (1920's-30's) were used primarily for upper atmospheric research con­ cerning the ionosphere. World War II sped the development and use of short wave­ length radars. It was not until the late 1960's and early 1970's that the potential for us­ ing sensitive clear-air radars to study the lower atmosphere became apparent. Chad­ wick and Gossard (1983) give an excellent account of the developments in clear-air radars.

In the late 1970’s, the Aeronomy Laboratory of the Environmental Research Laborato­ ries (ERL) in Boulder, Colorado, built and tested a very high frequency (VHF) 50-mega­ hertz (MHz) radar near Platteville, Colorado. This radar was a scaled-down prototype of a Mesosphere-Stratosphere-Troposphere (MST) research radar built and operated near Poker Flat, Alaska.

In 1980, the Wave Propagation Laboratory (WPL) of ERL began operation of the Platteville radar jointly with the Aeronomy Laboratory to measure tropospheric winds. This system operated for several years and produced coarse vertical resolution wind profiles. From the mid 1980's, a small network of five wind profilers have been operat­ ing in Colorado (Strauch et al.. 1984) (Fig. 1). These profilers routinely produced hourly wind profiles of high vertical resolution.

l - f

In 1984, ERL formed the Profiler Technology Transfer Group within WPL to develop, de­ ploy, and operate a demonstration network of 30 wind profilers in the central United States (Fig. 2, Table 1). The individual site locations or number of sites may vary slightly from those listed. The National Weather Service (NWS) will assess the utility of the network in an operational setting from 1990 through 1992. This network is expected to be the precursor of a national network.

1.3. Description and Uses of Wind Profiler Data The standard data sets will be high-quality, hourly averaged wind profiles, similar to those in Fig. 3. These hourly profiles will have been subjected to quality control checks which are designed to identify and flag nearly all incorrect wind vectors.

For the past four years, the Denver Weather Service Forecast Office (WSFO) has had access to the Colorado experimental wind profiler network and has found profiler data very useful in forecasting winter storms, in that they provide useful information about the hourly changes in the strength and depth of storm systems. The utility of profiler data is just as great during the summertime with the ability to track short-wave troughs that

- 2 - Fig. 2. Location of wind profiler demonstration network sites to be operational by mid 1990. Numbers correspond to the site numbers listed in Table 1.

- 3 - Table 1. Planned location of wind profiler sites and nearest town.

Site Nearby Town State Lat. (N) Long. (W) Elev. No. (°. ’■ ”) r. ”) (ft.)

1 Platteville CO 4010 48 104 43 10 5000 2 Lathrop MO 3934 48 94 10 12 300 3 Fairbury NE 40 06 00 97 20 24 1420 4 Hillsboro KS 3818 33 97 17 44 1465 5 White Sands MR NM 32 24 00 106 21 00 4025 6 Haviland KS 3739 08 99 05 28 2125 7 Neodesha KS 3722 48 95 38 05 835 8 Lamont OK 36 41 28 97 28 57 1005 9 Vici OK 3604 19 99 13 03 1930 10 Haskell OK 35 48 28 95 46 54 695 11 Purcell OK 3458 47 97 31 07 1085 12 Conway MO 3731 24 92 42 09 1280 13 Slater IA 41 54 03 93 41 57 1035 14 Neligh NE 4212 26 97 47 37 1720 15 Winchester IL 39 49 49 90 28 36 160 16 Blue River Wl 4313 46 90 31 42 740 17 Wolcott IN 40 48 36 87 03 00 695 18 Bloomfield MO 36 53 02 89 58 19 425

20 Wood Lake MN 4440 18 95 26 54 1045 21 DeQueen AR 3403 00 94 14 13 415 22 Okolona MS 3405 23 88 51 52 410 23 Winnfield LA 31 53 50 92 46 57 305 24 Palestine TX 31 46 45 95 42 48 455 25 Jayton TX 3301 00 100 58 48 2320 26 Tucumcari NM 3505 03 103 36 33 4070 27 Granada CO 3754 06 102 25 02 3830 28 McCook NE 40 05 09 100 39 13 2625 29 Merriman NE 42 54 20 101 41 41 3250 30 Rock Springs WY 41 32 56 109 07 25 6845 31 Aztec NM 3650 28 107 54 24 6240

June 1988

- 4 - 14 45 13 12 40 11 35 L

10 SM / a a i 4,4 & y.

9 to — 30 evoba

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8 -O .

m — 25 T - <5 7 I HG H- E I H 20 6 u312 i 1111§ i m m x 5 15 4

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2 SITE Et.EVflTipN T x: 1 22

86/09/L 1 FLEMING 86/09/10 10:00:00 ■._ k\i_ W1j_ 22:00:00 i., > 1B0 IB0-75 75-58 50-25 25-10 10-2.5 <2.5 GMT 4 GMT SPEED I N KNOTS

Fig. 3. High-quality hourly wind profiles measured by the Fleming, Colorado, research profiler during a trough passage. may enhance convection. Training Manuals No. 3 and 4 deal exclusively with using profiler data in cool-season and convective forecasting.

Although our experience with wind profilers has generally been confined to Colorado, it is expected that they will be equally useful in other climatic regions.

In the future, wind profiler data will be examined for initializing National Meteorological Center (NMC) high-resolution models.

Real-time wind profiler data may help airlines improve their operations with more effi­ cient routing (Carlson and Sundararaman, 1982) and better timing of take-offs and landings. Regions of clear-air turbulence (CAT) may be forecast more accurately in the future with wind profiler data (Hocking, 1983). The Denver Air Route Traffic Control Center (ARTCC) at Longmont has been receiving wind profiler data since 1983.

- 5 - They find profiler data valuable in their metering and spacing of aircraft into the airport (Foss and Hinkelman, 1984).

Atmospheric research using wind profilers is expected to continue with vigor. WPL has built a small transportable wind profiler. It is expected that small, low-power systems will become popular for boundary layer and lower troposphere research studies, such as pollution transport.

1.4. Advantages and Disadvantages of the Wind Profilers

Advantages of the network wind profilers over rawinsondes—

• Provide hourly averaged wind profiles every hour.

• Measure winds almost directly above each site.

• Operate reliably and unattended in nearly all weather conditions.

• Provide temporal and spatial density of soundings needed to compute derived fields for the first time.

Disadvantages of the network wind profilers—

• Provide no wind measurements in the first 500 meters (1,600 feet) of the atmos­ phere.

• Cannot measure winds during periods of strong local convection or nonuniform pre­ cipitation.

• Are sensitive to nearby radio interference.

Wind profilers cannot replace the radiosonde at this time or in the near future. The radiosonde measures a profile of temperature and moisture, something the wind profiler cannot do.

If funds become available, and additional research is completed, radiometers may be installed at the wind profiler sites. These will generate smoothed profiles (compared to the radiosonde) of temperature and moisture above each site. Geopotential heights can be derived from the radiometer measurement of virtual temperature profiles. Measure­ ments of the 500-mb pressure height are at least as accurate as the radiosonde (Hogg et al. 1983). The radiometer also accurately measures the total integrated amounts (but not the vertical distribution) of liquid and water vapor above each instrument. Even these data cannot replace the radiosonde; they can only supplement them.

- 6 - Review Topics for Section 1

The reader should know:

• what a wind profiler is

• several possible uses of wind profiler data

• several advantages and/or disadvantages of wind profilers and radiosondes.

- 7 - 2. Principles of Operation

The network will contain 30 wind profilers operating on a frequency of 404.37 MHz (wavelength = 74 cm). These ultrahigh frequency (UHF) profilers are being built by the Unisys Corporation, Great Neck, New York. A typical site is presented in Fig. 4.

Fig. 4. Typical 404-MHz demonstration wind profiler network site. Sketch courtesy of Unisys Corporation, Great Neck, New York.

2.7. System Hardware

2.1.1. Transmitter and power supply

Each system will operate on standard 115/230 volt, 50-60 Hz commercial power. Profiler sites will typically be located in rural areas. No backup generator or uninterrup­ tible power supply (UPS) will be used; therefore downtime due to occasional power fail­ ures is to be expected. Each site will use power line filters and transient suppressors for lightning protection. The equipment is designed to automatically restart after a power failure, as long as a hardware failure has not occurred.

The commercially built wind profilers are specified to operate with 6 months’ mean time between failure (MTBF). To meet this requirement, Unisys will use a low-voltage solid

- 8 - state transmitter, capable of producing approximately 16 kilowatts of peak power, or ap­ proximately 1,500 watts of average power. The average power is defined as the peak power multiplied by the percent of time that the transmitter is actually transmitting.

Timing in a wind profiling system is measured in millionths of a second (microseconds). The transmitter sends out pulses that last 1 2/3 or 6 2/3 microseconds, which corre­ spond to different height resolution modes. These two resolution modes are 250 m or 1,000 m respectively, and are a function of the volumes in the atmosphere being illumi­ nated by the transmitted pulse from the radar* (Fig. 5). The pulse repetition period (the time between pulses) is approximately 100 or 150 microseconds, corresponding to 10,000 or approximately 6,500 pulses per second, depending on the resolution mode.

Fig. 5. Relationship of the pulse width to resolution volume and gate spacing. 250-m resolution mode shown.

2.1.2. Antenna The purpose of the antenna is to direct the transmitted energy in a known, confined di­ rection. The demonstration network wind profilers will use a coaxial collinear (COCO) antenna. Each antenna is constructed relatively inexpensively from nearly standard co­ axial cables. This antenna technique was developed for use at 50 MHz with MST radars (Balsley and Ecklund, 1972) and has been adapted for the 404-MHz radars. The maximum possible height coverage of a wind profiler is determined to a great ex­ tent by atmospheric conditions, but is also related to the radar's wavelength and its

* In order for the wind profilers to meet frequency allocation (bandwidth) con­ straints, the 1 2/3 microsecond pulse length (width) has been increased to 2 1/3 microseconds (in the low mode). This decreases the height resolution from 250 to 350 m. The 250-m spacing between sample heights will remain the same.

- 9 - power-aperture product, defined below. The Next Generation Weather Radars (NEX- RAD) operate with short wavelengths (10 cm) that will routinely measure winds only in the first 3-5 km (up to approximately 500 mb) of the atmosphere (the reason for this will be discussed later). The network wind profilers operate with longer wavelengths (74 cm) and routinely measure winds throughout the troposphere (above 500 m).

The power-aperture product of a radar is defined as the average transmitted power multiplied by the size, or aperture, of the antenna. Typical tropospheric wind profilers need a power-aperture product of > 105 watt meter2 (Wm2) The network 404-MHz profilers will transmit approximately 1,500 watts average power through a 12 m x 12 m antenna array to give a power-aperture product of about 2.2 x 105 Wm2.

The significant factors that determine the physical size of an antenna array, at a par­ ticular frequency, are the required beam width and costs. Generally, the smaller (cheaper) an antenna array gets, the wider its beam width. Correspondingly, as an ar­ ray gets larger (more expensive), its beam width gets narrower. The network sites are specified to have antenna beam widths <5°, much larger than typical NWS radars (1°).

2.1.3. Receiver and computer

After the transmitted energy is radiated by the antenna, it is scattered by the atmos­ phere in all directions. A very small portion of the radiated energy is scattered back to the antenna and fed to the receiver.

Winds are measured by the profiler every 250 m (approximately 800 ft) in the vertical from a minimum height of 500 m (1,600 ft) above ground level (AGL) to a maximum height of 16.25 km AGL (approximately 53,000 ft or about 100 mb). See Fig, 6. The profilers operate in two separate modes: a low mode or a high mode. The low mode measures winds from 500 m above the ground to a maximum of 9.25 km AGL. The high mode measures winds from 7.5 km to a maximum of 16.25 km AGL. To sample these higher altitudes a longer pulse (increased power) is needed. From section 2.1.1, recall that the resolution volume is a function of the pulse length. Therefore, with the longer pulse in the high mode, less resolution is attained (1,000 m compared to 250 m in the low mode). Winds measured by the profiler are an average within each resolution volume, centered every 250 m vertically. The reason for the minimum sample height limitation of 500 m will be discussed in section 3.3.

To measure winds, a profiler emits a pulse of energy. The data processor then waits a specific amount of time for that pulse to travel up into the atmosphere, scatter, and re­ turn to the antenna/receiving system. In reality, the transmitted pulse travels on forever, and the atmosphere scatters a small amount of energy from the pulse continually back to the antenna. The receiver limits the bandwidth of the returned signal and separates it

- 10 - into its Doppler components for further processing. To measure winds at different alti­ tudes, fixed delays are used that correspond to the times needed for the pulse to make a round trip to each point along the beam and back. The computer processes all the time-dependent, pulse-to-pulse information that is later averaged.

16.25 - - - Gate 36

-i Z Gate spacing 250 m z T

13 Height resolution 1000 m

£ ■X a> HIGH MODE £> 9.25 - - Gate 36 —

o cn 0) > o 7.50 Gate 1 15 5o> ~A a> Z __ Gate spacing 250 m X Z 1

Z zj: Height resolution 250 m Z t

LOW MODE

0.50 4- Gate 1 -

Fig. 6. Height coverage, gate spacing (atmospheric sample heights), and height resolu­ tion of the network wind profilers.

2.2. Antenna Configuration

2.2.1. Number of beams needed

Any measured horizontal wind speed and direction (a vector) can be broken into its Cartesian {U and V) components as in Fig. 7. If there is zero vertical velocity of the scatterers, or (more correctly) the actual vertical motions average to zero over the sampling period, the minimum number of beams that a wind profiler can have is two, one to measure the north/south component of the wind, and one to measure the east/ west component. In reality, the atmosphere contains three dimensional motions: U, V, 40

30

20

10

-40 -30 -20 -10 0 10 20 30 40

-10--

-20

Fig, 7. An example of the north/south and east/west components of a typical wind speed and direction measurement (35 kt @ 250°; east component -32,9 kt, north component —12 kt). and lN. Therefore, a third beam is required to measure the associated vertical motions. However, it must still be assumed that the wind velocities (horizontal as well as vertical) are homogeneous in the vicinity of the profiler to compute a valid wind profile.

2.2.2. Pointing angles of each beam

For simplicity in the following sections, the two orthogonal (perpendicular) antenna beams are described as pointing directly east and north (measuring the U and V com­ ponents of the wind, respectively). See Fig. 8. In reality they could point in any orthogo­ nal directions. Pointing directions do in fact vary depending on the longitude of the net­ work sites (discussed further in section 4.3).

N

Fig. 8. Plan view of wind profiler beam orientation.

12 - The two orthogonal antenna beams point at an elevation angle of 75° above the hori­ zon*. (This is very high when compared to standard scanning weather radars.) The third beam of the antenna points vertically. The orientation of the three beams is shown in Fig. 9. The 75° elevation angle was chosen as a compromise between several op­ posing factors relating to, for example, accuracy, height resolution and transmitter power. These are discussed further by Strauch et al. (1984).

Fig. 9. Perspective view of wind profiler beam orientation.

2.2.3. How a phased array works

The COCO antenna used in the profiler network is made up of many individual radiating elements, Each element is similar to a standard dipole antenna. By placing many of these dipole elements parallel and orthogonal to each other (Fig, 4), a large-aperture antenna array is built. Figure 10 illustrates this idea with a small vertical-beam antenna array. It generates a vertical beam because the transmitted pulse arrives at each one of the individual radiating elements (represented by the triangles) at the same time, in phase. When each element of the antenna radiates its energy in phase, the pulse of energy propagates vertically away from the antenna, The beamwidth of the radar is de­ fined by the angular width for which the radiated energy is coherent (in phase). Most of the energy outside the main beam is incoherent (out of phase). Side lobes develop where small amounts of this energy outside the main beam become coherent.

* The antenna elevation angle of 75° is used throughout the text and figures in this manual. This elevation angle has been changed slightly to simplify the antenna construction. The actual elevation angle is now 73.7°.

- 13 - The two oblique beams (north and east) are produced by changing the feed cable lengths (Fig. 11). Now the transmitted pulse arrives at each one of the individual ele­ ments at a slightly different time (out of phase), so that it ripples across the array. A coherent pulse of energy is produced that moves away from the radar at an elevation angle of 75°.

To transmitter

Fig. 10. Simple four-element vertically pointing antenna. Equal length feed cables are used to produce the vertical beam.

2.3. Use of Atmospheric Turbulence as a Measure of the Mean Wind

2.3.1. Scales of turbulence

Wind profiling radars reflect their energy off fluctuations in the radio refractive index, created by turbulence. Wind profiling radars are sensitive to scales of turbulence that equal half the radar wavelength. At 404 MHz, one wavelength equals 74 cm. Therefore the radar is sensitive to turbulent eddies with spatial dimensions near 37 cm that cause fluctuations in the radio refractive index.

In the boundary layer, essentially all scales of turbulence exist from 1-cm wavelengths on up. Air density decreases with height such that normally the atmosphere cannot physically support small-scale turbulence in the upper troposphere. This is why the NEXRAD radars (10-cm wavelength) will not routinely measure winds above about 5 km. They require turbulent eddies with spatial dimensions near 5 cm that may not exist above 3-5 km.

14 - 7

To transmitter

Fig. 11. Simple four-element antenna pointing at 75° elevation angle. Unequal length feed cables are used to produce the oblique beam.

2.3.2. Doppler shift

To measure the wind velocity, we assume that the fluctuations in the radio refractive index are carried along in the mean wind flow. By using the Doppler shift principle, we can detect the motion of these fluctuations.

The radar transmits a very stable pulse at 404.37 MHz. This pulse of energy travels up into the atmosphere, which continually scatters a small amount of energy back to the antenna as the pulse encounters fluctuations in the radio refractive index. Because these fluctuations are embedded in the mean wind flow, a slight Doppler shift of the 404.37-MHz signal is produced. By measuring the shift in frequency of the returned sig­ nal, the mean wind speed is estimated.

The radar pulse travels through the atmosphere at the speed of light. To measure winds at different altitudes, fixed delays are used that correspond to the times needed for the pulse to make a round trip to each point along the beam and back. 2.4. The Doppler Signal Spectrum and Its Uses The radar pulse is illuminating (in electrical terms) a volume of the atmosphere as it travels away. This volume is a function of the height resolution of the wind profiler (250 or 1,000 meters). Within each volume, air is moving at various speeds due to shear and turbulence. These processes therefore cause a spreading out of the signal spec­ trum that is reflected back to the radar. The spectrum approximates a normal (Gauss-

15 - w

CD TD

(/> C 0 *o

-v^~ f ~V (-23.3 m/s) (23.3 m/s) Radial velocity

Fig. 12. Typical Doppler signal spectrum. ian) distribution. A typical spectrum is shown in Fig. 12. The horizontal axis represents the measured radial velocity from -V to V (a maximum of about ±23 m/s). The vertical axis represents the strength of the signal (returned power). A typical spectrum contains noise (/V) that is spread over all Doppler frequencies (±V) as well as signal from the scatterers (S). The mean background noise level is represented by N. W is the width of the signal spectrum. A more detailed look at the Doppler signal spectrum is pre­ sented in Appendix A.

2.4.1. Returned power estimate

The returned power is represented by the area above the noise level, labeled S in Fig. 12. It is the amount of signal (energy) reflected back to the radar from the atmosphere at a given height. The returned power is inversely related to the square of the measure­ ment height in the atmosphere.

The returned power is caused by gradients in atmospheric moisture and temperature on the scale of tens of centimeters. Wind profilers operate best in an “active" atmosphere with abundant water vapor. They operate less effectively in a dry, quiet, stable atmos­ phere.

2.4.2. Radial velocity estimate

The velocity at the center of the weighted area S is taken as the best estimate of the radial wind velocity at that height (resolution volume). The radial velocity estimate, rep­ resented by the vector Vr in Fig. 12, is used to compute the horizontal wind at a given height.

- 16 - 2.4.3. Spectral width estimate

This is a measure of the width of the velocity spectrum (the spread in velocity values), represented by W in Fig. 12. More precisely, W is the standard deviation of the veloci­ ties in the signal spectrum. Shear and turbulence contribute to the spreading out of the signal spectrum within each resolution volume as do pulse width, beam width, and an­ tenna pointing angle. The correlation of enhanced spectral widths to reports of clear-air turbulence may be studied using the demonstration network.

2.5. From Radial Components to Horizontal Winds The radial velocities measured in each beam by the profiler are related to the actual U, V, and W components of the wind as follows: Vre = U cos 75° + W sin 75° Vrn = V cos 75° + W sin 75° V„ = W where V„, Vr„, and Kr2 are radial velocities measured in the east, north, and zenith di­ rections, respectively. It can be seen that the measured radial velocity in the oblique beams is relatively small when compared to the horizontal wind. This relationship is il­ lustrated in Fig. 13. For example, with an east wind (with no vertical motion) at 20 m/s (about 39 kt) the radial component of the wind is equal to 20 m/s x cos 75° + 0 m/s x sin 75°, or approximately 5 m/s (10 kt). Ultimately the individual U, V, and W compo­ nents of the wind are combined to produce a speed and direction at each height.

Fig. 13. Relationship of the oblique beam radial velocity to the actual horizontal wind component.

Unlike the two oblique beams, the vertical beam results in a direct measurement of the vertical component only. Horizontal winds have no effect on the W component, assum­ ing the pointing of the beam is perfectly vertical. (The actual pointing accuracy speci­ fied for each beam is ±0.5°.)

- 17 - Solving for U and V in the equations above requires dividing each side by cos 75°, with the following results:

Vre W sin 75° cos 75° cos 75°

Vrn _ y + W sin 75° cos 75° + cos 75°

By definition 1/cos 9 = sec 0 and sin 9/cos 0 = tan 0. Therefore, the equations may be rewritten as:

U = Vre sec 75° - W tan 75° V = Vrn sec 75° - W tan 75°

The wind speed is given by Ju2 + V72. The wind direction, relative to a due east or west wind, is given by arctan {V/U).

As an example, compute the wind speed and direction given that the measured radial component toward the east equals 8.03 kt (-4.1 m/s), the radial velocity toward the north equals 2.61 kt (-1.3 m/s) and a downward (negative) vertical motion measured at 0.5 kt (26 cm/s).

Solution:

U = Vre sec 75° - W tan 75° = 8.03 kt x sec 75° - (-0.5 kt) x tan 75° = 31.02 kt + 1.87 kt = 32.89 kt

V= Vrn sec 75° - W tan 75° = 2.61 kt x sec 75° - (-0.5 kt) x tan 75° = 10.08 kt + 1.87 kt = 11.95 kt The wind speed = Ju2 + V~

= 35 kt The wind direction = arctan {V/U) = 20° from a due east or west wind.

Because both horizontal components are positive, the wind is blowing toward the north­ east. Therefore the wind is from the southwest at 250° (270°-20°). Compare the hori­ zontal components measured here (31.02 and 10.08 kt), with those illustrated in Fig. 7

- 18 - for the same wind speed and direction. The differences are due to the added vertical motion in this example.

Review Topics for Section 2

The reader should know:

• how many antenna beams are used to measure the wind at each profiler site in the demonstration network

• what assumptions have to be made to compute a valid wind measurement

• what scatters (reflects) UHF radar energy in the clear air

• what a typical Doppler signal spectrum looks like, and be able to identify the area used to estimate the wind velocity

- 19 - 3. Accuracy and Limitations of Wind Profiler Data

3.1. Assumption of Uniformity of the Wind Field Across All Beams

Recall that the north/south and east/west components of the horizontal winds are meas­ ured using beam elevations of 75°. This causes a separation between the two meas­ urement volumes equal to 0.38 times the height of the volumes. This concept is illus­ trated in Fig. 14. As an example, winds measured at 10 km (33,000 feet or about 250 mb) have their sample volumes horizontally separated by 3.8 km (2.4 miles).

An assumption of horizontal homogeneity of the wind field across all beams has to be made. This is fine for relatively long averaging times, such as one hour. Problems arise with short averaging periods (minutes), because small variations in the instantaneous wind may exist over distances as short as 0.38 H (see Fig. 14). Such variations could easily be caused by convection.

s

Fig. 14. Diagram of beam separation.

The demonstration network wind profilers cannot measure representative winds in a strongly convective environment. The atmospheric motions (wind and precipitation) are not uniform in space or time over a profiler during convection. This violates the as­ sumptions needed to measure winds with a fixed-beam Doppler radar. An example of this type of failure is shown in Appendix B.

- 20 - 3.2. Increased Signal-to-Noise Ratio by Time-averaging Atmospheric signals measured by the wind profiler are extremely weak. By a combina­ tion of pulse-to-pulse averaging and subsequent group averaging, the signal-to-noise ra­ tio is greatly improved.

The radar pulses an average of about 8,000 times per second. Data are taken for about 2 minutes in each beam direction (north, east, and vertical). Therefore the wind profile data for one beam include an average of nearly 1 million pulses. Each 6 minutes a complete wind profile is produced using all three beams and both resolution modes.

3.3. Internal Electronic Noise The wind profiler transmits on a frequency of 404.37 MHz. The data processing system attempts to extract the very weak atmospheric signals at a center frequency of 404.37 MHz ±62 Hz. The 62-Hz tolerance is the maximum unambiguous Doppler shift of the transmitted signal due to the wind velocity (corresponding to a maximum horizontal wind velocity of approximately 175 kt).

To measure the wind at a minimum height of 500 meters, the receiver must recover within several millionths of a second after the transmitted pulse. This is no small feat, considering the peak pulse power of the transmitter is about 16 kW with the receiver and data system attempting to measure atmospheric signals at power levels io15 times weaker, both using the same antenna.

The transmission of pulses sets up transient currents in the COCO antenna array. Re­ turned signals cannot be detected until these transient currents dissipate. The time re­ quired for this dissipation prevents the detection of returns below a certain height based on the system design; for the demonstration network, this height is 500 m.

The duration of the transient currents may be affected by equipment aging, minor hard­ ware problems, or changing environmental conditions. Typically the transient currents (or "ringing" of the transmitted pulse) cause a spike in the Doppler signal spectrum at or near the 0 velocity point. Special processing reduces this spike as much as possi­ ble, but cannot eliminate it without other undesirable effects. Several examples of this problem are illustrated in Appendix B.

3.4. External Electronic Noise This type of interference is usually random in nature, caused by local radio transmis­ sions. If the interference is truly random (noncoherent), it will only add to the back­ ground noise level that the radar is operating in. In Fig. 12, the signal-to-noise ratio is favorable, in that the atmospheric velocity spectrum rises well above the average noise level (the dashed line). If the noise level increases, it can cover up a weak atmos­ pheric signal. In this case a loss of data will show up in the weaker signal-to-noise ratio

- 21 - regions of the atmosphere, i.e., upper sample heights of each mode and in the core of jet streams where turbulence is minimal.

Significant errors may be produced by local radio interference if the incoming signal is stable (coherent) with respect to frequency and time. Coherent interference may be generated by nearby radio communications, but at a frequency of 404 MHz, the impact on the network is expected to be minimal.

If an interference source is coherent with time, it will produce a signal spectrum similar to that in Fig. 15. The energy from the interference source is confined to a narrow band of frequencies, contrasting to the previous example of random frequency interfer­ ence that only added to the background noise level. The data processing system lo­ cates the peak of the signal spectrum. The selected spectrum is then used to compute the estimate of the wind velocity. As the example shows, an erroneous wind vector will be computed. These usually occur in the weaker signal-to-noise ratio regions of the at­ mosphere. Coherent interference typically affects several sample heights in the same time-averaging period. The bad wind vectors are usually grouped together, all with the same speed and direction. An example is shown in Appendix B.

w

Fig. 15. Typical Doppler signal spectrum with a signal spike caused by coherent interference.

The quality control procedures operating in the Hub computer system flag most individ­ ual bad wind vectors. The procedures depend on continuity of the atmospheric flow, with limits based on the expected shear (both vertically and temporally from the same site, or from adjacent wind profiler sites). In the case of coherent interference, where several bad wind vectors are grouped together, the quality control procedures may fail and not flag them as being bad. Training Manual No. 2 describes in greater detail the quality control procedures operating in the Hub.

- 22 - 3.5. Side Lobes Side lobes refer to a response to energy scattered back to the antenna from directions outside the main beam. If backscattered energy in a side lobe becomes relatively strong, problems can occur.

The main beam power level is approximately 300 times stronger than the strongest side lobe power level. Even so, very strong signals in a side lobe, caused by aircraft, a strong convective cell or a precipitation shaft, can obscure the weak clear-air returns of the main beam. Because the profiler picks the strongest signal to compute its estimate of the wind velocity, velocities measured in a side lobe can be erroneous.

Ground clutter is usually seen in a side lobe of the radar. Special processing is used to reduce it as much as possible.

3.6. Precipitation and Vertical Velocity Correction

The strength of the reflected signal due to precipitation depends partly on the radar wavelength. At 404 MHz, any precipitation greater than light rain or snow will dominate over the clear-air signal. Cloud droplets actually enhance the reflected signal, thereby benefitting the profilers in weak signal conditions.

The dominance of the precipitation signal over the clear-air signal is no problem, given that the precipitation is uniform over the three beams of the wind profiler. We assume that the precipitation is carried horizontally by the wind in the same way as fluctuations in the refractive index are carried in the clear air. During precipitation, the vertical beam measures the fall velocity of the precipitation particles. This value is then used to cor­ rect the measurements made by the two oblique beams (due to the additional vertical component measured by each) to give the mean horizontal air motion.

Profiler measurements are vulnerable to errors in the horizontal winds caused by the relatively small vertical motions more typical of the clear-air. Each wind profiler meas­ ures the vertical motion (W) above the site. Again the assumption of homogeneity across all beams has to be made to correct properly for vertical motion.

Recall from Section 2.5. the relationship between radial velocities and the actual wind: Vre = U cos 75° + W sin 75° Vrn = V cos 75° + W sin 75° V„ = W where Vre, Vrn, and Vrz are radial velocity measurements in the east, north, and zenith directions, respectively.

A large component of any vertical motion (W sin 75°) is measured in the oblique beams. An example in section 2.5.2 illustrated the radial velocity estimate in a 20 m/s

- 23 - horizontal wind. We will expand on this with the addition of a 1 m/s downward motion of the air. Now the radial velocity estimate would be approximately equal to 6 m/s (20 m/s x cos 75° + 1 m/s x sin 75°). If no correction for the vertical velocity were made, the horizontal wind estimate would be —24 m/s (46 kt), nearly 20% in error. Consider the much larger effect of heavy stratiform rain (5-7 m/s fall velocities) on the oblique beams.

In cases of large W, it is obvious that W must be measured and its effects accounted for in the hourly horizontal wind estimate. In cases of small W (about ±15 cm/s or less), the correction should not be made, i.e., W sin 75° is ignored. The uncertainty of the vertical measurement was found (in Colorado) to equal approximately ±20 cm/s (Strauch et al.. 1986a). Therefore, any attempt to correct for smaller vertical motions just adds noise to the horizontal wind estimate.

3.7. Effect of Aircraft on the Data Aircraft flying through the main beam or a side lobe override the weak clear-air signal. They produce a random wind velocity estimate, high power return, and wide spectral width in the Doppler signal spectrum. The errors are produced only in the radar resolu­ tion volume(s) equal to the range of the aircraft from the profiler. Nearby automobile traffic in a side lobe can produce the same effects. Typically, random bad wind esti­ mates are removed before the hourly averaged wind is computed (discussed further in Section 4.4.).

3.8. Expected Accuracy One goal in designing the wind profilers in the Colorado network was to provide vertical profiles of the horizontal wind with accuracy of orthogonal components to better than 1 m/s (1.9 kt) (Strauch et al., 1984). This same accuracy is expected from the wind profilers in the 30-site demonstration network.

Determining the accuracy of wind profilers is not necessarily straightforward. Different sounding methods use different spatial and temporal averaging techniques and will likely provide some inherent variation of measurements. In addition, there is the natural vari­ ability of the atmosphere in space and time.

3.8.1. Profiler vs. rawinsonde

The first comparisons were carried out against standard NWS rawinsondes. Root-mean- square (rms) differences of wind speed were found to be 2-3 m/s (Kessler et al., 1985; Strauch et al., 1986a). The hourly wind profile closest to the time of rawinsonde launch was used in the comparison. Note that the measuring techniques are totally different. The radiosonde is tracked from the ground as it ascends and is carried many kilome­ ters downwind. The profiler measures the wind moving through the three spatially sepa­ rated volumes, located nearly overhead.

- 24 - Any standard used for comparison has errors associated with it. In this case the func­ tional precision of the rawinsonde wind speed is approximately 3.1 m/s (Hoehne, 1980). The data for this rawinsonde study were obtained over a 50-week period during 1978-1979. Once each week, two identical rawinsondes were flown on a single balloon train (vertically separated by 5 m). Each sonde was tracked by a separate, independ­ ent NWS ground station. Comparisons were then performed using the two data sets from each flight.

3.8.2. Profiler vs. lidar

Winds were compared between the WPL 915-MHz wind profiler and the WPL Doppler lidar, collocated at the Denver, Colorado, NWS Forecast Office. The rms differences of wind speed were found to be approximately 3.3 m/s (Lawrence et al., 1986).

The lidar uses a CO2 laser to measure the Doppler signal spectrum. The laser beam backscatter is caused by naturally occurring particulate matter carried along in the mean flow of the atmosphere. The primary difference between the two measurement devices is their resolution (sample) volumes. Although the same pulse durations were used, the beamwidths were very different: 2.5° for the profiler and 0.005° for the lidar. Thus, at a height of 10 km, the beamwidths are about 400 m and 1 m, respectively.

3.8.3. Profiler vs. profiler

Wind observations from two identical, collocated profilers were compared. The rms dif­ ferences of wind speed were found to be about 1.7 m/s without vertical velocity correc­ tion and about 1.3 rn/s with vertical correction (Strauch et al., 1986b).

The Platteville 405-MHz prototype profiler was built to produce five beam-pointing direc­ tions (east, north, west, south, and zenith) (Law, 1986). By using different pairs of an­ tennas (east/north or west/south), two independent wind profiles were produced each hour. Vertical velocity measurements were made using the zenith beam. When using wind data from all available heights, an rms difference of about 1.3 m/s was measured. When using wind data with the highest signal-to-noise ratios (generally from the lower troposphere), an rms difference of about 0.9 m/s was measured. The WPDN wind profilers have a much larger power-aperture product (greater sensitivity) than the profiler used in this study. Therefore the higher signal-to-noise ratios will extend to the upper troposphere, corresponding to increased accuracy at these heights (approxi­ mately 1 m/s).

- 25 - Review Topics for Section 3

The reader should know:

• several types of errors that may be visable in the data

• why the vertical velocity measurement is important

• several problems related to determining the accuracy of wind profilers

- 26 - 4. Practical Information on the 30-Station Demonstration Network

4.1. Location of Profiling Sites

The wind profilers are designed to provide continuous data to complement the twice- daily rawinsonde data. The network should be operational by mid 1990; it will be used to enhance mesoscale research and as a model for a proposed national network for the NWS.

The profilers are generally located between existing NWS upper air radiosonde sites. With this arrangement, higher density spatial data are available twice daily using the radiosonde and profiler networks. In support of atmospheric research, e.g., the STORM (STormscale Operational and Research Meteorology) program, seven profilers are more closely spaced in an inner network located in Oklahoma and Kansas. The inner network spacing is approximately 200 km, while the outer spacing is about 450 km.

The ideal profiler site would be located in a quiet rural area, in a slight bowl or depres­ sion of the Earth's surface (to minimize radio interference and ground clutter), away from aircraft flight corridors, but on a little-traveled year-round road close to commercial power and phone service.

4.2. Products. Schedules, and Communications

Each profiler measures a vertical profile of the atmosphere every 6 minutes. Data in a profile, referred to as the spectral moments, consist of the returned power, radial veloc­ ity, and spectral width estimates for each height, beam position, and resolution mode. These data are transmitted over dedicated phone lines or satellite links to the central Hub computer at the end of each 6-minute averaging period.

At each profiler site hourly averaged spectral moments are produced and transmitted through the Geostationary Operational Environmental Satellite (GOES) back to the net­ work Hub. This hourly averaged profile is used as a backup for the 6-minute data transmitted by phone lines or communication satellites. In the event of a power failure during an averaging period, degraded spectral moments are produced using the avail­ able data. The profiler system is designed to recover fully after a power failure.

The Hub computer system computes each wind profile. These profiles are then trans­ mitted to Suitland, Maryland, where they are placed on the NWS Gateway for distribu­ tion. The standard data sets available are high-quality, hourly averaged wind profiles. The averaging period is from one hour mark to the next hour mark, with the profiles available to the user by 20 minutes past the hour. Each profile is time-stamped with the ending time of the averaging period, i.e., the 0100 GMT profile is averaged between 0000 and 0100 GMT, with the profile available by 0120 GMT.

- 27 - In the future, 30-minute averaged wind profi'es may be available every 12 minutes from each site. This will depend upon communications availability and the development of quality control procedures.

4.3. Effects of Minimizing Satellite Interference It has been determined that the wind profilers may cause radio interference to certain satellites. The affected satellites use uplink frequencies near the profiler transmitter's output frequency. Polar-orbiting satellites are more susceptible to interference than the geostationary satellites.

The affected polar-orbiting satellites (at the time of this writing) are NOAA 9 and 10, plus three Soviet satellites. The operational geostationary satellites affected are GOES East and West. All seven satellites carry sensitive receivers used to locate low-power emergency beacons from downed aircraft and ships in distress. This system is called SARSAT (Search and Rescue Satellite-Aided Tracking). The profilers may interfere with the satellite's ability to detect the weak signals from these beacons.

To minimize the possibility of interference, the transmitter at each profiler site will be turned off whenever any of the five polar-orbiting satellites are scheduled to pass within a cone of ±30° from the vertical (Fig. 16). With five satellites, this will occur an aver­ age of four or five times daily (varying between two and seven times) for each

Fig. 16. Relationship of a wind profiler's inhibit cone to the polar-orbiting satellites.

- 28 - site in the demonstration network. Orbital periods of the satellites are 102-105 minutes at a height of 800-1,000 km. Orbital speeds are greater than 7 km/s. Therefore the maximum time to traverse the “inhibit" cone is less than 3 minutes. Figure 17 illustrates the horizontal extent (-1,000 km) of the inhibit cone at orbital heights for several profiler sites.

Inhibiting the transmitter will have little impact on the hourly averaged wind profiles. Less than 24 minutes will be lost every 24 hours for any given profiler. The worst case will be multiple passes, when the inhibit times are contiguous.

A different approach is used to minimize interference toward the operational geostation­ ary satellites, located at 75° and 135° west longitude. The wind profilers will be ori­ ented in azimuth so their antenna beams will generally point away from the satellites (see Fig. 17), thereby minimizing the radiated energy toward the satellites. The different azimuth pointing angle of each profiler is accounted for in the trigonometry used to cal­ culate the winds. No effect on the profiles will be seen under normal conditions. Errors related to a bad wind estimate in one or more of the components (described in Appen­ dix B) will be displayed differently depending on the site's azimuthal orientation. For ex­ ample, toward the eastern edge of the demonstration network, errors related to the most northward pointing beam will appear to be from the northwest (or southeast).

Fig. 17. Horizontal extent of several transmitter inhibit cones, at a height of 900 km. are shown by the circles. Small lines radiating from each site represent the approximate azimuth pointing directions of the oblique beams.

- 29 - 4.4. The Hub

The central computer system is known as the Hub. It handles data ingest, archiving, quality control, product generation, distribution of profiler data, and the scheduling of transmitter inhibit times for high-elevation satellite passes.

Hourly wind profiles are generated at the Hub from the 6-minute spectral moments us­ ing a simple version of the random sample consensus method (Fischler and Bolles, 1981). This algorithm examines the velocity estimates obtained during the previous hour (maximum of 10) for each range gate and determines the largest subset of values that fall within a certain velocity window of each other. (An example of this procedure is presented in the next paragraph.) Typically the radial velocity window, for the oblique beams, is about 3 m/s. In terms of horizontal wind velocity, the window is about 10 m/s (-20 kt). This allows for normal atmospheric variation during each hour. If the largest subset is four or more, those individual velocity estimates are then averaged to form the hourly average. If the largest subset is less than four, the data are rejected for that range gate and no wind component is computed for that height. If there is more than one subset with the same (largest) number of values, then the subset closest to the end of the hour is used. The individual returned power and spectral width estimates are averaged together for the corresponding velocity estimates that passed the consensus test. At each measurement height, the horizontal wind speed and direction is computed from the three wind components that passed the consensus test.

Typical horizontal wind velocities measured every 6 minutes by the profiler are pre­ sented in Table 2. The data are from the same beam and height over a 1-h period. The random sample consensus algorithm examines each velocity estimate, looking for the largest number of other estimates that are within ±5 m/s. The ±5 m/s window is centered on each of the 10 individual velocity estimates. In this case, sample 6 has no other velocity estimates within ±5 m/s. The procedure does compare the velocity esti­ mate to itself, therefore the minimum consensus number is one. Samples 4 and 8 are each within 5 m/s of the other, therefore each has a consensus value of two (itself plus one other) assigned to the velocity value. This process continues for all 10 velocity es­ timates. The velocity estimate with the largest number of velocity estimates within the consensus window is assumed to be the best estimate to compute the hourly average from. Those velocity estimates within the consensus window are then averaged to form the hourly average. Estimates number 2, 3, and 7 all have the same largest consensus number (7). Estimate 7 is chosen because it is closest to the end of the hour. (In this case it would not make a difference which subset was chosen, since each subset con­ tained identical velocity estimates.) The hourly average assigned to this beam and height position would equal 16.1 m/s. Vertical data are processed in a similar manner, except the velocity window is smaller (-±1.5 m/s).

- 30 - Table 2. Example of the random sample consensus method to obtain an hourly average.

Sample number (one every 6 minutes) 1 2 3 4 5 6 7 8 9 10

Horizontal velocity 12.5 15.3 14.8 -21.5 18.4 35.5 16.3 -25.0 17.9 17.6 estimate (m/s)

Number of 4 7 7 2 6 1 7 2 6 6 velocity estimates within ±5 m/s

Estimates that 12.5 15.3 14.8 — 18.4 — 16.3 — 17.9 17.6 pass consensus

Consensus average 16.1 m/s

The random sample consensus algorithm is very effective in detecting atmospheric sig­ nals, while rejecting random outliers in the data. These outliers can be caused by scat­ tering from aircraft, brief radio interference from other transmitters, or random estimates of the wind velocities in regions of the atmosphere where the signal-to-noise ratio is low.

The consensus algorithm operates at each profiler site (for the hourly GOES transmis­ sion) and at the Hub. Higher-level quality control is performed at the Hub in the form of vertical and temporal continuity checks. The radial components are ultimately combined at the Hub to produce a wind profile.

4.5. Expected Height Coverage The profilers are designed to measure winds from 500 m AGL to a maximum height of 16.25 km AGL. The actual maximum height of reliable data will vary with time, depend­ ing on atmospheric conditions. The profilers are designed so that missing data of 3 hours or more at or below 13 km (approximately 43,000 ft or about 170 mb) should not occur more than 10% of the time in any one month.

4.6. Mean Time Between Failure (MTBF) Each wind profiler is designed to operate an average of six months between failures. These are hardware failures at the site, not related to commercial power or communi­ cation failures. With 30 sites, slightly more than one failure per week in the network is expected. If the antenna fails to switch properly, it defaults to operate in the vertical mode only.

31 Profiler sites are typically located in rural areas. Such areas tend to lose power first and have it restored last. Backup power is not available for the profilers.

4.7. Mean Time To Repair Once a profiler has failed, service personnel will be notified. It may take several days for a technician to respond depending on workload, priority, weather conditions, etc. The mean time to repair is designed to be one hour, once a technician arrives at the site,

4.8. Hub Failure Hub failures involve the loss of all profiler network data. Preventive maintenance on the Hub computer system is performed once per month at scheduled times, usually lasting several hours. The Hub will be down during preventive maintenance.

Review Topics for Section 4

The reader should know:

• how often consensus-averaged wind profiles are generated

• the approximate expected height coverage and mean time between failure for the wind profilers

• several reasons for the possible loss of data from a specific site or the entire net­ work

- 32 - 5. References

Balsley, B.B., and W.L. Ecklund, 1972: A portable coaxial collinear antenna. IEEE Trans, on Antennas and Propagation. AP-20, 513-516,

Carlson, H.C., Jr., and N. Sundararaman, 1982: Real-time jetstream tracking: national benefit from an ST radar network for measuring atmospheric motions. Bull. Amer. Meteor. Soc., 63, 1019-1026.

Chadwick, R.B., and E.E. Gossard, 1983: Radar remote sensing of the clear atmos­ phere-review and applications. Proc. IEEE. 71, 738-753.

Fischler, M.A., and R.C. Bolles, 1981: Random sample consensus: A paradigm for model fitting with application to image analysis and automated cartography. Com- mun. Assoc. Comput. Mach., 24, 381-395.

Foss, F., and J.W. Hinkelman, Jr., 1984: Denver ARTCC evaluation of PROFS meso- scale weather products. Joint report of PROFS and FAA. 23 pp. and 4 appendices.

Hildebrand, P.H., and R.S. Sekhon, 1974: Objective determination of the noise level in Doppler spectra. J. Appl. Meteor.. 13, 808-811.

Hocking, W.K., 1983: On the extraction of atmospheric turbulence parameters from ra­ dar backscatter Doppler spectra—I. Theory, J. Atmos. Terr. Phys.. 45, 89-102.

Hoehne, W.E., 1980: Precision of National Weather Service upper air measurements. NOAA Tech. Memo. NWS T&ED-16, 23 pp.

Hogg. D.C., M.T. Decker, F.O. Guiraud, K.B. Earnshaw, D.A. Merritt, K.P. Moran, W.B. Sweezy, R.G. Strauch, E.R. Westwater, and C.G. Little, 1983: An automatic profiler of the temperature, wind and humidity in the troposphere. J. Appl. Meteoroi. 22, 807-831.

Kessler, E., M. Eilts, and K. Thomas, 1985: A look at profiler performance. 1985 Work­ shop on Technical and Scientific Aspects of MST Radar: Session on Weather Analy­ sis and Forecasting Applications, Aguadilla, Puerto Rico, Oct. 21-25.

Law, D.C., 1986: WPL second generation 405 MHz wind profiler. 23rd Conference on Radar Meteorology/Conference on Cloud Physics, Snowmass, Colo., Sept. 22-26, AMS, Boston, Mass., 3, JP394-396.

Lawrence, T.R., B.F. Weber, M.J. Post, R.M. Hardesty, R.A. Richter, N.L. Abshire, and F.F. Hall. Jr., 1986: A comparison of Doppler lidar, rawinsonde, and 915-MHz UHF wind profiler measurements of tropospheric winds. NOAA Technical Memorandum, ERL WPL-130, Boulder. Colo.

- 33 - Strauch, R.G., B.L. Weber, A.S. Frisch, C.G. Little, D.A, Merritt, K.P. Moran, and D.C. Welsh, 1986a: The precision and relative accuracy of wind profiler measurements. J. Atmos. Ocean. Tech., 4, 563-571.

Strauch, R.G., A.S. Frisch, D.A. Merritt, K.P. Moran, B.L. Weber, and D.C. Welsh, 1986b: Precision of UHF (405 MHz) wind profiler measurements. Preprints, 23rd Conf. on Radar Meteorol., Snowmass, Colo., Sept. 22-26, AMS, Boston, Mass., 1, 52-54.

Strauch, R.G., D.A. Merritt, K.P. Moran, K.B. Earnshaw, and D. van de Kamp, 1984: The Colorado wind-profiling network. J. Atmos. Ocean. Tech., 1, 37-49.

- 34 - Appendix A. A Detailed Look at the Doppler Signal Spectrum

A typical spectrum from the high mode, oblique beam is shown is Fig. A-1 (identical to Fig. 12). The spectrum contains 128 individual spectral points between -V and V. The radial velocity resolution is therefore 0.36 m/s (a range of 46.6 m/s with 128 spectral points). This results in a horizontal velocity resolution of 1.4 m/s (2.7 kt) per spectral point in the north/south and east/west components of the wind. Shear and turbulence within each resolution volume typically spread the velocity values over many spectral points.

Fig. A-1. Typical Doppler signal spectrum, ±V represents the maximum unambiguous radial velocity_of the scatterers, N is the average noise level, S the signal power, Vr the mean radial velocity, W the radial width of the signal spectrum, and Vi to V2 the interval in which the signal exists.

Every 1-2 seconds (depending on the mode and beam) an individual spectrum is pro­ duced for each of the 36 heights in a resolution mode and beam-pointing direction. About 16,000 radar pulses are averaged to produce an individual spectrum. Fifteen to 88 of these spectra are then averaged (1-2 min) to produce a final spectrum for each height, resolution mode, and beam direction. The returned signal power (S), radial ve­ locity (Vr), and the width (W) are computed from this final spectrum.

The first step in computing S, Vn and W of each spectrum is to separate the signal from the noise. The mean noise level (N) is found by applying an objective technique (Hildebrand and Sekhon, 1974) to the spectrum. The signal spectrum (S) is isolated by locating the peak value of the spectrum and including all those contiguous spectral points (\/i to V2 in Fig. A-1) that exceed the noise level. The mean noise level is then subtracted from each of the spectral points in the interval V-j to V2. The resulting spec­ trum, shown in Fig. A-2, is used to compute S, Vr, and W.

- 35 - Radial velocity

Fig. A-2. Typical Doppler signal spectrum with the mean noise level N subtracted from the signal.

The returned signal power S, in decibels (dB), is defined as the area under the curve given by

Vl 5 = j A(v) dv

V'l where A(v) is the amplitude of the signal at each velocity V. Typical returned power values are shown in Table A-1.

The radial velocity Vr, in m/s, is defined as the center of the weighted area S given by v2 Vr = 1/5 J V A{v) dv . V\

Radial velocity estimates from the oblique beams are converted to horizontal velocities using the known beam elevation angle and trigonometry. Typical horizontal and vertical wind components are shown in Table A-1.

The spectral width W is the standard deviation, in m/s, of the velocities in the signal spectrum. The standard deviation (W) is equal to the positive square root of the vari­ ance of the velocities in the signal spectrum. The variance W2 of the spectrum is given by

W2 = 1/5 J (V - Vr)2 A(v) dv Vl

Typical horizontal and vertical spectral widths W for the three wind components are shown in Table A-1.

- 36 - Table A-1. Typical profile of orthogonal wind component data giving N, S, V, and W for each height and beam position in the low mode (high resolution).

East Component

Height N S V W AGL Noise Power Velocity Width km dB dB m/s m/s

0.50 24.67 53.85 1.88 3.47 0.75 20.52 48.72 4.58 3.21 1.00 21.23 49.93 6.36 2.35 1.25 22.73 54.86 6.73 2.07 1.50 24.12 56.67 5.68 3.78 1.75 23.63 56.34 9.07 2.28 2.00 21.88 55.05 9.80 2.07 2.25 22.56 58.30 14.09 2.05 2.50 22.23 55.27 16.02 2.16 2.75 21.91 52.25 16.95 2.44 3.00 21.93 52.02 17.44 1.88 3.25 21.42 48.49 17.90 1.92 3.50 20.47 41.46 20.39 2.08 3.75 20.86 44.12 21.89 1.92 4.00 20.48 40.74 23.31 1.64 4.25 20.62 39.83 23.57 1.64 4.50 20.19 37.27 27.29 2.20 4.75 20.61 36.59 30.44 1.84 5.00 20.02 34.08 35.92 2.52 5.25 20.05 29.35 37.88 2.96 5.50 20.43 25.94 38.44 1.45 5.75 20.18 25.20 39.13 2.36 6.00 19.86 22.93 34.79 0.56 6.25 19.95 25.05 30.07 1.34 6.50 20.12 25.32 32.12 1.89 6.75 20.05 24.88 31.82 1.24 7.00 20.32 24.75 30.91 1.79 7.25 20.41 24.16 31.05 2.32 7.50 20.38 24.03 31.32 2.07 7.75 20.29 23.77 33.19 2.12 8.00 20.15 23.12 33.72 1.97 8.25 20.07 22.39 34.09 2.15 8.50 19.95 22.19 32.43 2.32 8.75 19.88 21.55 30.19 1.43 9.00 18.83 29.83 29.37 1.21 9.25 19.97 20.15 27.87 1.57

37 - Table A-1. (Continued)

North Component

Height N S V W AGL Noise Power Velocity Width km dB dB m/s m/s

0.50 26.74 49.87 2.81 3.78 0.75 19.10 35.07 3.87 3.12 1.00 23.33 38.10 4.04 3.04 1.25 20.81 45.42 -0.14 2.76 1.50 23.76 51.50 -1.76 2.16 1.75 21.46 54.02 -3.19 2.06 2.00 21.94 53.82 -4.09 2.24 2.25 22.68 53.62 -0.89 2.58 2.50 21.93 49.80 -0.17 2.32 2.75 22.95 52.61 -2.86 2.21 3.00 22.39 54.03 -3.20 2.13 3.25 20.97 47.73 -3.80 1.94 3.50 20.42 40.44 -4.78 2.42 3.75 20.91 44.54 -6.03 2.37 4.00 20.22 39.37 -6.76 2.50 4.25 20.38 39.74 -5.67 2.35 4.50 20.52 35.70 -3.82 2.36 4.75 20.06 32.51 -1.61 2.24 5,00 19.86 31.97 -0.57 3.51 5.25 19.75 28.66 -4.37 3.12 5.50 19.99 28.19 -3.77 3.16 5.75 19.75 26.04 -0.40 1.76 6.00 19.68 29.28 -3.81 3.21 6.25 20.04 20.77 -3.35 3.05 6.50 20.15 20.12 -1.25 2.89 6.75 19.85 24.25 0.18 2.54 7,00 19.93 25.37 -0.83 3.13 7.25 19.81 25.02 2.03 3.32 7.50 20.09 23.22 3.76 2.97 7.75 20.00 23.42 5.45 2.03 8.00 19.95 22.91 6.32 1.09 8.25 19.78 22.18 6.55 2.75 8.50 19.83 19.12 57.32 0.03 8.75 19.87 20.03 -15.89 3.54 9.00 19.88 21.54 4.19 3.28 9.25 19.92 20.21 3.93 2.98

38 - Table A-1, (Continued)

Vertical Component

Height N 5 V7 W AGL Noise Power Velocity Width km dB dB m/s m/s

0.50 30.48 43.92 -0.02 5.68 0.75 25.64 55.98 0.13 2.78 1.00 23.02 60.16 -0.10 2.16 1.25 22.16 51.02 -0.06 1.74 1.50 22.02 53.08 -0.11 2.42 1.75 21.32 61.20 0.06 2.59 2.00 21.32 63.46 -0.02 2.81 2.25 21.00 56.91 0.00 2.80 2.50 20.53 45.09 -0.10 2.13 2.75 21.39 40.92 0.06 2.39 3.00 21.33 52.49 -0.03 1.60 3.25 21.70 52.92 -0.11 1.57 3.50 21.56 43.11 -0.13 2.34 3.75 21.85 35.65 -0.22 3.73 4.00 21.60 38.74 -0.15 2.68 4.25 21.74 41.09 0.03 1.71 4.50 21.14 37.18 -0.08 1.57 4.75 20.67 33.41 0.17 1.54 5.00 20.99 37.19 -0.15 2.21 5.25 20.86 34.96 -0.06 3.56 5.50 20.98 31.29 -0.11 1.96 5.75 21.01 25.27 -0.16 1.00 6.00 20.67 28.66 -0.20 0.82 6.25 21.02 31.39 -0.26 2.50 6.50 20.32 30.54 -0.32 1.75 6.75 20.12 29.88 -0.21 2.02 7.00 19.89 38.71 -5.87 3.87 7.25 19.94 43.12 -4.18 5.32 7.50 20.03 32.98 -9.35 4.02 7.75 20.05 27.32 0.03 2.15 8.00 19.93 27.12 0.08 2.02 8.25 19.92 26.83 0.04 1.97 8.50 19.67 27.05 -0.10 1.54 8.75 19.78 26.15 -0.03 2.25 9.00 19.82 25.62 0.03 2.32 9.25 19.91 25.12 0.05 2.27

- 39 - Appendix B. Examples of Wind Profiler Data

Many of the following illustrations are worst-case situations. They are from research wind profilers, with little or no quality control of the data. Similar gross errors are pro­ duced by the network wind profilers, but quality control procedures operating at the Hub identify and flag most of them. Training Manuals No. 3 and 4 discuss the meteorologi­ cal interpretation of wind profiler data in a forecasting environment.

Weakening atmospheric power returns are evident in Fig. B-1. The strongest signals near 300 mb occur between 0300 and 0900 GMT in the southwesterly flow. Following the trough line passage, the flow turns northerly and the atmospheric power returns de­ crease to the point of causing large areas of missing wind data. The decrease in re­ turned power is due to the advection of drier, more stable air (little turbulence). To overcome this problem, the WPDN wind profilers have a greater power-aperture product (sensitivity) to detect weaker signals. Notice also the missing profile at 1700 GMT and the two bad wind estimates in the 2300 GMT profile.

C/3 5 ®

aI UJ I

Fig. B-1. Example of weakening atmospheric power returns with time.

- 40 - An example of attempting to measure winds in a convective environment is shown in Fig. B-2. Low-level easterly upslope flow is evident at 2100 and 2200 GMT. In the verti­ cal velocities and returned power (not shown here) for this time period, precipitation is not apparent. This is not to say precipitation did not occur, only that for the part of the hour used to estimate the wind, no precipitation occurred. The hourly average wind data plotted may have come from the first half of the hour, with rain causing too much variability in the second half of the hour to meet the consensus requirements.

50

45

40

35 _1 W

25 gX w — 20 I

15

10

5

Fig. B-2. Hourly wind profiles influenced by thunderstorms.

Initial convection started about 2300 GMT. The 0°C isotherm (melting level) is located near 4.5 km. Below this level, large errors due to the nonuniformity of vertical (fall) ve­ locities of raindrops can be seen in the 0000 GMT profile.

The 0100 GMT profile is a true representation of the atmosphere. Vertical velocities dur­ ing this period (not shown) are very small. Notice the relatively deep easterly flow.

Deep convection began near 0200 GMT. The strong northeast winds in the lowest lev­ els are in error. The nonuniformity of the atmosphere in this region violates the assump­ tions needed to calculate valid wind vectors. Recall that the profiler antenna beams pointing north and east are at an elevation angle of 75°. They are measuring the fall velocity of the rain plus the actual air motion, at levels below 4.5 km in the figure.

- 41 - At 0300 GMT the measured vertical velocities are beginning to meet the minimum con­ sensus (representativeness) constraints and an attempt to correct for them is being made. The attempt fails because of the differences in space and time (nonuniformity) of the measurements.

The convection decreased to stratiform rain, lasting up to 0700 GMT. With the return of homogeneity to the atmosphere across all beams, valid wind profiles can once again be measured. In the period of stratiform rain (0500 and 0600 GMT profiles), measured fall velocities of 6-7 m/s just above the surface extending to -4.5 km were properly corrected for (except the first few gates of the 0600 GMT profile). Above the melting layer and extending to 8 km, fall velocities for snow of 1-2 m/s were properly corrected for between 0400 and 0700 GMT.

Ground clutter will typically show up as an error over time at the same height (range), illustrated in Fig. B-3. By examining the velocity vector in error, it can usually be deter­ mined which component (antenna beam) is causing the problem. Errors caused by the north/south antenna beam will show up as bad estimates of the north/south wind com­ ponent (usually very high or near zero velocity). Likewise, east/west errors will show up in the east/west component of the wind. Errors lying on the diagonal (as in Fig. B-3) are usually caused by bad vertical velocity estimates, used to correct the horizontal wind estimate. This type of error can also be caused by bad estimates of both the north/south and east/west winds.

In Fig. B-4 we see several examples of interference (internal or external to the sys­ tem). The errors generated are similar to ground clutter, except that they extend over multiple heights (ranges).

Interference typically shows up as a group of bad wind vectors having the same speed and direction, or as an abrupt loss of wind data. Regions of the atmosphere for which the signal-to-noise ratio is low (upper sample heights of each mode and the core of jet streams) are most affected. In the 1000-1200 GMT profiles, interference has contami­ nated both wind components, resulting in high-speed diagonal wind vectors. Notice that all other high-speed wind vectors in error are nearly east or west. This is caused by interference contamination only in the east/west component; the north/south component is still correct.

- 42 - -120 -XT' <0^ <0^ ^ ~^rr~r7 500 ^ ^ ^ ^ ^ <0^ ^ ^ <0^ ------^------£6444 00 $>sSv-- '=*-'S^J—- ^s^ -— ------>—— 'S Niki-----s^—* ^----- V>)>V — ----- Wv — ^ i i i ^'0u_ Vkx_ W_ ^ ^ ^ \k- ^ V -=0 S*- SO_ Nil---- \o--- Vu_ --- 15 -Vi— 5 ^- ^ ^j/ 600 '. -o^ J -O 07 E -»> _k S ^ _ — V-- 'k— < s/ y 2 UJ 5 4 s N \ 3tr —— m t- ^ / »£/ 4& <^v V 4< /V/; X LU I o “ 700 Jj { K f z t 03 3 a 10 X ✓ LU W'Y\ \ jj I l VI 4 4" ■ y*f f•', 850 u 'SHE flEVilTiDN'

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Fig. B-3. Example of large errors due to ground clutter. MSL

above

kft

HEIGHT

Fig. B-4. Hourly wind profiles contaminated by interference.

- 43 - —155

- 50

- 45

- 40 to 35 29

30 « £ 25 |

lD I 20

15

10

- 5

Hd 06:00:m a_ V_ -X— 18:00:00 GMT ■75 15-50 50 25 05-10 10-2.5 GMT SPEED IN KNOTS 'L

Fig. B-5. Upper tropospheric flow influenced by nearby thunderstorms.

In Fig. B-5, a weak trough passage is shown that enhanced local convection. Two large convective cells developed on a north/south line directly upwind of the wind profiler site. The individual cells were located approximately 100 km apart. They propa­ gated eastward past the site, one located 50 km north and the other 50 km south. As the mean upper tropospheric flow encountered each thunderstorm, it was forced to separate and pass around the two storms. The combined accelerated flow between the cells is apparent in the 0000 GMT profile. This profile is not representative of the synop­ tic-scale atmosphere, but is representative of the subsynoptic or local atmosphere above the site.

Figures B-6, B-7, and B-8 illustrate the temporal and spatial difference of a trough pas­ sage, as measured by the Platteville, Fleming, and Flagler. Colorado, wind profilers (Fig. 1). Identical time and height coverage are displayed in each figure. Several types of errors are evident, and will be discussed below. West to southwesterly flow pre­ cedes the stronger upper-level northerly flow at each profiler site. The trough line is sharply defined in the Fleming profiles. The westward tilt with height of the horizontal shear zone is evident at each site.

- 44 - 40

35

30 2c7> I GO JS 5 25 ^ 3c h- oX 20 ^ oX

15

- 10

Fig. B-6. Hourly wind profiles measured by the Platteville. Colorado, research profiler during a trough passage. Errors are discussed in the text.

Fig. B-7. Same as Fig. B-6, except profiles are from the Fleming, Colorado, research win d profiler.

- 45 - 40

X 20 03 X

15

10

Fig. B-8. Same as Fig. B-6, except profiles are from the Flagler, Colorado, research wind profiler.

With three sites, the orientation and propagation speed of the trough line (or other sig­ nificant feature) can be found. The transition from southwesterly or westerly flow to northwesterly flow at the 500 and 400 mb levels is identified by the circles in each fig­ ure. At Platteville both transitions occur at 0400 GMT, Fleming 0700 and 1000 GMT, and Flagler 1100 and 1200 GMT. Given their order in time with respect to location (Plat­ teville first, Fleming second. Flagler third), the trough line lies in a northeast-southwest direction. The actual orientation can be found by examining the time difference between sites. At 400 mb, the transition to northwesterly flow at Flagler occurs 8 hours later than at Platteville. The transition at Fleming occurs 6 hours later than Platteville. Therefore the trough line traveled 3/4 of the distance between Platteville and Flagler in 6 hours (the time between Platteville and Fleming), and the remaining 1/4 of the distance in 2 hours (the time between Fleming and Flagler). The resulting trough line orientation is shown in Fig. B-9. The eastward component of the trough’s propagation (at 400 mb) is approximately 150 km in 6 hours, or 25 km/hr (-16 mi/hr).

A similar analysis can be done at the 500-mb level. Notice that at Fleming the trough passage at 500 mb is 3 hours earlier than at 400 mb. At Flagler the trough passage is only one hour earlier at the lower level. Therefore the 500-mb trough line is oriented more northeast-southwest, compared to the 400-mb trough line shown in Fig. B-9. Overall the trough appears to be more intense toward the north, given the stronger shear zone and increasing westward tilt with height.

- 46 - /

Fig. B-9. Trough line orientation at 400 mb (dashed line) from Figs. B-6, B-7, and B-8.

The data presented in Figs. B-6, B-7, and B-8 are from profilers operating on a fre­ quency of 50 MHz, using large 50-m x 50-m antennas. Transient currents (discussed in section 3.3) in the COCO antenna array severely limit the minimum height of these radars. Errors or missing data related to these transient currents are evident below 4 km in each of the three figures. Transient currents are expected to cause similar inter­ mittent problems in the first few sample heights of the WPDN.

Many times only one component of the three used to compute the wind vector is in er­ ror, as is the case in Fig. B-6. The errors in the first sample height are caused by bad estimates of the east/west component of the wind, while the north/south components are correct. In Fig. B-8, many of the first two sample heights are contaminated by tran­ sient currents. The east/west components may be correct in some cases, while the north/south components are in error.

- 47 - The low wind speed errors evident near the northerly jet in Fig. B-6 are related to re­ gions of weak signal returns. The atmosphere in this region is relatively stable (minimal moisture and turbulence), providing weak signal returns. In these conditions, weak inter­ nal signals to the profiler or ground clutter may obscure the clear-air signal, resulting in near zero velocity component estimates of the wind.

In Fig. B-8, errors due to ground clutter are evident at a height of 4.5 km (between the arrows). Quality control procedures operating at the Hub flag most individual bad wind vectors. The procedures may fail to flag bad data where errors are consistent in height or time.

In the future, 30-minute averaged wind profiles may be available every 12 minutes from each site in the WPDN. This will depend upon further development of quality control procedures and communications availability. Figure B-10 illustrates this high temporal data during a frontal passage. Low-level easterly flow is apparent ahead of the actual surface cold front, with light northeasterly to stronger westerly winds aloft. The frontal passage near the surface is seen about 0700 GMT with cold northerly flow deepening with time. A weak signature of the surface front passage is seen in the mid-levels. For one 12-minute averaging period, 0712 GMT, the winds veer slightly at all heights above 4 km. The 0724 GMT profile exhibits a return to west-southwest flow, similar to the 0700 GMT profile. Also note the three missing data points at a height of approximately 3.0, 3.15, and 3.3 km in the 0724 GMT profile. Slight variations of the wind field that are consistent in height and/or missing data over several heights suggest a nonuniform flow field, usually caused by vertical motions. This is consistent with strong fronts and gravity waves (including lee waves).

- 48 - Fig. B-10. High-quality 12-minute wind profiles measured by the Denver, Colorado, re­ search profiler during a frontal passage.

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