ARM TR-044

> Radar Wind Profiler and RASS (RWP915) Handbook
>
> January 2005
>
> R. Coulter
>
> Work supported by the U.S. Department of Energy,
>
> Office of Science, Office of Biological and Environmental Research

# Contents {#contents .Heading-Front}

[1. General Overview 1](#general-overview)

[2. Contacts 1](#contacts)

[3. Deployment Locations and History
1](#deployment-locations-and-history)

[4. Near-Real-Time Data Plots 1](#near-real-time-data-plots)

[5. Data Description and Examples 2](#data-description-and-examples)

[6. Data Quality 11](#data-quality)

[7. Instrument Details 14](#instrument-details)

**Figures**

[1. 3](#__RefHeading___Toc104108457)

[2. 4](#__RefHeading___Toc104108458)

[3. 5](#__RefHeading___Toc104108459)

[4. 9](#__RefHeading___Toc104108460)

[5. 10](#__RefHeading___Toc104108461)

# General Overview

The 915 MHz radar wind profiler/radio acoustic sounding system
(RWP/RASS) measures wind profiles and backscattered signal strength
between (nominally) 0.1 km and 5 km and virtual temperature profiles
between 0.1 km and 2.5 km. It operates by transmitting electromagnetic
energy into the atmosphere and measuring the strength and frequency of
backscattered energy. Virtual temperatures are recovered by transmitting
an acoustic signal vertically and measuring the electromagnetic energy
scattered from the acoustic wavefront. Because the propagation speed of
the acoustic wave is proportional to the square root of the virtual
temperature of the air, the virtual temperature can be recovered by
measuring the Doppler shift of the scattered electromagnetic wave.

# Contacts

## Mentor

Richard L. Coulter\
Environmental Research Division\
Argonne National Laboratory\
Argonne, IL 60439\
Phone: 630-252-5833

Fax: 630-252-5498\
E-mail: [rlcoulter@anl.gov](mailto:rl_coulter@anl.gov)

## Instrument Distributor

Vaisala Corporation\
194 South Taylor Avenue\
Louisville, CO 80307\
Phone: 303-499-1701\
Fax: 303-499-1767

# Deployment Locations and History

-   Southern Great Plains

    1.  Central Facility: Operating since November 1992.

    2.  Intermediate Facility 1 (Beaumont, KS): Operating since
        September 1996

    3.  Intermediate Facility 2 (Medicine Lodge, KS): Operating since
        September 1996

    4.  Intermediate Facility 3 (Meeker, OK): Operating since September
        1996

-   North Slope of Alaska (Barrow): Operating since April 2001

-   Tropical Western Pacific: Operated in cooperation with the National
    Oceanic and Atmospheric Administration (NOAA) Aeronomy Laboratory.

# Near-Real-Time Data Plots

See the [General Quick
Looks](http://www.nsdl.arm.gov/Visualization/rwp/frame.htm).

# Data Description and Examples

***[Wind Profile Data]{.underline}***

The data produced by this instrument come in three forms: raw spectra,
moments, and time-averaged profiles.

-   The spectra are the most basic form of data produced by the present
    version of this instrument. The method by which the spectra are
    obtained are discussed below in section 7.1.2. They display the
    energy content of the scattered signal over the range of Doppler
    shifts observed from each pointing direction and power level of the
    wind profiler. There is a single spectrum for each range gate,
    pointing direction, and power level. The spectrum represents an
    average of several (e.g., 60) individual spectra obtained over
    several seconds (e.g., 30).

-   The moments data are calculated directly from the spectral data and
    represent, basically, the spectrum as a whole. They are calculated
    by integrating across the Doppler frequency domain. At each range
    gate, pointing direction and power level 4 quantities are
    calculated:

    1.  Mean Doppler Shift: The first moment of the spectrum, f~D~
        calculated roughly as:

> $\begin{array}{r}
> \overline{f_{D}} = \sum_{i = f_{1}}^{f_{2}}{f_{i}S(f_{i})}\sum_{i = f_{1}}^{f_{2}}{S(f_{i})} \\
> c = v_{r} + \text{20}\text{.}\text{05}\sqrt{T_{v}}
> \end{array}$
>
> where S(f) is the power at frequency f and f1 and f2 are the maximum
> and minimum frequencies, chosen about a mid-point frequency associated
> with the maximum signal power level.

2.  Doppler width: The width of the spectrum, V~D~, calculated as

> $V_{D} = 2\sqrt{\sum_{i = f_{1}}^{f_{2}}\left( \left( f_{i} - \overline{f_{D}} \right)^{2}S(f_{i}) \right)\sum_{i = f_{1}}^{f_{2}}{S(f_{i})}}$

3.  Noise Level: This value is calculated using methods defined by
    Hildebrand and Sekhon (1974), based on the assumption of a Gaussian
    noise spectrum such that the variance of the spectral points should
    be equal to the square of their mean value divided by the number of
    spectral averages. Using this fact, the signal region is separated
    from the noise region and helps to define f~1~ and f~2~ above.

4.  Signal-to-Noise Ratio (SNR): This value is calculated from the ratio
    of S(f) to the noise level determined above.

This data can be very useful in determining atmospheric structure on
time scales as fine as a few minutes. Figure 1 shows the SNR and
vertical velocity moments for a 24-hour period (note that the vertical
velocity definition is such that positive is upward in this figure).
Note in the vertical velocities and the SNR ratios are affected by
rainfall (large downward motion associated with energy scattered from
falling rainfall rather than atmospheric structure) at about 0300 and
0700 Local Standard Time (LST).

![](media/image1.png){width="3.0680555555555555in"
height="2.9694444444444446in"}![](media/image2.png){width="3.0680555555555555in"
height="2.9805555555555556in"}

![](media/image3.png){width="3.09375in"
height="3.046527777777778in"}![](media/image4.png){width="3.09375in"
height="3.178472222222222in"}

[]{#__RefHeading___Toc104108457 .anchor}Figure 1.

-   The time-averaged profiles consist of values calculated over a
    user-defined time period (usually 1 hour for ARM data normally
    calculated using consensus averaging (see section 7.1.2) to
    eliminate values at times and heights with unacceptable data. These
    quantities include, for each height, the wind speed and direction,
    the radial wind speed along each transmit direction, and the SNR
    ratio along each transmit direction. A 24-hour period of profiler
    winds at high and low powers is often portrayed using wind barbs, as
    shown in Figure 2:

![](media/image5.png){width="3.0083333333333333in"
height="3.057638888888889in"}![](media/image6.png){width="3.0083333333333333in"
height="3.057638888888889in"}

[]{#__RefHeading___Toc104108458 .anchor}Figure 2.

***[Virtual Temperature Profile Data]{.underline}***

RASS data is similar in format to the wind data, consisting of spectral,
moments, and consensus-averaged data files. The RASS normally operates
only during the first 10 minutes of the hour. There are a few
differences in the data:

-   The spectral data is determined in the same manner as is the wind
    profile spectral data. However, because the speed of sound is
    considerably larger than normal atmospheric wind velocities, the
    size of the fast Fourier transform necessary to cover both large and
    small Doppler shifts is relatively large (2048 points nominally). To
    save space, only selected points around zero (atmospheric motion)
    and around 340 m/s (the speed of sound) are saved. There is a single
    spectrum for each range gate. Because there is only a single power
    level and pointing direction (vertical), there is normally only one
    spectrum per range gate. The spectrum represents an average of
    several individual spectra obtained over several seconds (e.g., 30)
    similar to the wind analysis; however, because of the large number
    of points, only about 10 -- 15 spectra per time interval are
    averaged.

-   The moments data are processed much the same as the wind speed data;
    however there are two signal sources to consider. Because the true
    velocity of the propagating sound wave, *c*, depends on the motion
    of the atmosphere, i.e.,

> $c = v_{r} + \text{20}\text{.}\text{05}\sqrt{T_{v}}$
>
> where v~r~ is the air speed along the direction of the sound and T~v~
> is the virtual temperature, it is sometimes necessary to compensate
> for this motion when calculating T~v~. Even though the vertical motion
> (the direction of the propagating sound wave) is usually small, there
> are situations where it is important, such as convective conditions
> (vertical velocities on the order of 5 m/s at times) and orographic
> forcing. Unfortunately there are also occasions where the use of the
> corrected value is not propitious, such as during precipitation, when
> detected descending motion is not due to air motion. Thus, moments
> similar to those calculated for the wind profiles are determined for
> both the vertical air motion and the vertically moving sound pulse.

-   The time-averaged wind profiles are, once again, calculated in a
    manner similar to the time-averaged wind profile estimates. However,
    the calculated virtual temperature (in degrees Celsius) is produced
    with and without a correction for the sensed vertical atmospheric
    motion. A 24-hour display of virtual temperatures is often
    displayed, as shown below in Figure 3. Note that each "hour" value,
    while depicted as "filling" an entire hour, is in fact
    representative only of the first 10 minutes of that hour unless the
    profiler is configured to operate RASS for longer, or different,
    time periods.

![](media/image7.png){width="4.997916666666667in"
height="5.004861111111111in"}

[]{#__RefHeading___Toc104108459 .anchor}Figure 3.

## Data File Contents

***[Wind Profile Data]{.underline}***

-   Spectral Data At each height, beam pointing direction, and power
    level:

    1.  Spectral amplitude (at each bin of fast Fourier transform).

-   Moments Data At each beam pointing direction and power level: At
    each range gate:

    1.  Mean Doppler shift (in % of Niquist frequency)

    2.  Spectral width (in % of Niquist frequency)

    3.  SNR level (in Db)

    4.  Noise Level (in Db).

-   Average Data At each power level: At each height:

    1.  Wind Speed (m/s)

    2.  Wind Direction (deg relative to true north)

    3.  For each beam pointing direction:

    -   Radial wind speed (positive = toward the antenna)

    -   Number of moments that passed consensus criteria

    -   Average SNR ratio.

***[Virtual Temperature Profile Data]{.underline}***

-   Spectral Data At each height:

    1.  Spectral amplitude (at selected bins of fast Fourier transform).

-   Moments Data At each range gate:

1.  Mean Doppler shift of vertical atmospheric motion (in % of Niquist
    frequency)

2.  Spectral width of vertical atmospheric motion (in % of Niquist
    frequency)

3.  Noise Level of atmospheric portion of spectrum (in Db)

4.  SNR Level of atmospheric portion of spectrum (in Db)

5.  Mean Doppler shift of acoustic signal (in % of Niquist frequency)

6.  Spectral width of acoustic signal (in % of Niquist frequency)

7.  Noise Level of acoustic signal portion of spectrum (in Db)

8.  SNR Level of acoustic signal portion of spectrum (in Db).

-   Average Data At each height:

1.  Virtual Temperature (deg C)

2.  Corrected (for vertical motion) Virtual Temperature (deg C)

3.  Vertical Wind Speed (m/s, positive upward)

4.  Number of moments that passed consensus criteria for:

    -   Uncorrected virtual temperature

    -   Corrected virtual temperature

    -   Vertical motion.

5.  SNR Ratio (dB) for:

    -   Uncorrected virtual temperature

    -   Corrected virtual temperature

    -   Vertical motion.

Additional information may be found at [915 RWP Data Object
Design](http://science.arm.gov/tool/dod/showdod.php?Inst=915rwp) file
for ARM netCDF file header descriptions.

### Primary Variables and Expected Uncertainty

The Primary quantities measured with the system are the intensity and
Doppler frequency of backscattered radiation. The wind speed is
determined from the Doppler frequency of energy scattered from
refractive index fluctuations (caused primarily by moisture fluctuations
but also, to a lesser extent, by temperature fluctuations) embedded
within the atmosphere; the virtual temperature is determined from the
Doppler frequency of microwave energy scattered from acoustic energy
propagating through the atmosphere.

#### Definition of Uncertainty

The primary observed quantities are Doppler frequency and signal
Amplitude. Note that the observed quantities above are not the principal
quantities of interest to most scientists. The derived quantities of
most interest to scientists are the wind speed, wind direction, vertical
wind speed, and virtual temperature as a function of height. The
accuracies of these quantities, while dependent upon the accuracy of the
frequency measurement, are also affected by atmospheric effects and vary
considerably according to conditions. The wind speed is derived from
measurements from, normally, five beams. Because the individual
components are not collocated in space, horizontal homogeneity is
assumed to derive the wind vector at a single height. Furthermore, the
data are sampled at equal time intervals along each transmit direction.
Thus, the vertical beam is sampled at larger height intervals than are
the tilted beams (by 1/(sin(elevation angle)). This difference is
approximately 3%, which can be significant at large ranges. For example,
at a nominal height of 1000 meters (tilted beams), the vertical beam
information is derived from 1035 meters, which can be significant in
some situations

-   Nominal accuracy for wind speed: 1 m/s

-   Nominal accuracy for radial wind components along the pointing
    direction of the transmitter (e.g., vertical velocity): 0.5 m/s

-   Nominal accuracy for wind dir: 3 deg

-   Nominal accuracy for virtual temp: 0.5 K.

The above figures are the result of more than 1 year of daily and
multi-daily comparisons with winds derived from the balloon borne
sounding system at the central facility of the Southern Great Plains
Cloud and Radiation Testbed (CART) site.

### Secondary/Underlying Variables

This section is not applicable to this instrument.

### Diagnostic Variables

This section is not applicable to this instrument.

### Data Quality Flags

No flags are applied during data ingest of the consensus-averaged winds
and virtual temperatures. However, the data are examined regularly by
the instrument mentor and maintained; files are created and maintained
by the Data Quality Office (DQO) on a monthly basis for each of the
instruments that determine locations (temporally and spatially) where
data should be eliminated based on a brute force, multi-pass comparison
with data from neighboring points (above, below, before, and after).
This routine eliminates most of the questionable data; however, there
are several situations that defy straightforward objective analysis
routines. However, most of these situations can be delineated by
subjective analysis. This is done monthly by the instrument mentor. The
primary situations that can create seemingly good, but actually
erroneous data include:

-   Precipitation: Both rain and snow are excellent sources of scatter
    of electromagnetic radiation; thus they have the potential to
    provide considerable increases in the effective range for useful
    data. However, precipitation is generally possessed of a
    heterogeneous spatial distribution on the scale of the separation of
    the transmitted beams. This can lead to significant errors in
    estimates of the true wind speed. Rainfall is more amenable to
    objective analysis detection because it usually has a large downward
    velocity in comparison to atmospheric motion. Snow, on the other
    hand, has quite small terminal velocities. Figure 4 shows these
    effects.

![](media/image8.png){width="3.042361111111111in"
height="2.9916666666666667in"}![](media/image9.png){width="3.170138888888889in"
height="3.035416666666667in"}

[]{#__RefHeading___Toc104108460 .anchor}Figure 4.

> Note that the data around 2200 hours LST is obviously strongly
> affected by the precipitation (region of dark red extending to all
> heights between 20 and 18 hours before 18 LST) observed in the SNR
> profile. However, the precipitation around 0600 and 1000 hours is
> largely "thrown out" by the consensus-averaging requirements and the
> precipitation around 1600 hours has no obvious detrimental effect on
> the calculated wind profile.

-   Birds: The effects of birds, particularly migrating birds, is both
    difficult to detect and significant. The profiler is sensitive not
    only to the motion of the bird itself, but to the motion of its
    wings. During migrating seasons (fall and spring), nighttime winds
    from the north (fall) and south (spring) are often affected by these
    effects. The birds generally fly along the direction of the wind and
    increase the detected wind speed by 5 m/s or more (Coulter and
    Holdridge, 1996; Pekour and Coulter, 1998). Figure 5 shows the low
    (bottom) and high (top) power winds (left) and SNR (right) that are
    affected by migrating birds. Note the obvious wind direction shift
    near 2000 hours LST for roughly a 5-hour period. In this case, the
    winds were light enough that the birds flew north anyway. In cases
    when the winds are directly along the direction of the birds'
    desired direction of flight, the evidence is quite difficult to
    determine using the wind barb plot alone. Note the "random-type"
    strong reflections around 0.7 km on the low power SNR. These are
    characteristic of migrating bird signals. Note also that the
    signature for the high power returns is considerably different from
    the low power returns because of the considerably longer transmit
    pulse duration used. Finally, note that in this case, the high-power
    winds are more affected at lower altitudes than are the low-power
    winds. Obviously, purely objective analysis is difficult in these
    cases.

> ![](media/image10.png){width="3.0680555555555555in"
> height="3.025in"}![](media/image11.png){width="3.0680555555555555in"
> height="3.013888888888889in"}![](media/image12.png){width="3.0680555555555555in"
> height="3.035416666666667in"}![](media/image13.png){width="3.0680555555555555in"
> height="2.9368055555555554in"}

[]{#__RefHeading___Toc104108461 .anchor}Figure 5.

-   60-Hz noise: When 60-Hz noise gets directly into the analyzed
    Doppler signal it is detected approximately as a Doppler shift
    associated with a radial wind speed of 10 m/s. Because the niquist
    frequency for winds is often near 10 m/s, the noise signal is
    sometimes aliased back into the spectrum as well. Depending on which
    antenna beam is affected, very large deviations in wind speed can
    occur. Some of these are easily removed, but some provide consistent
    values not totally removed by some objective analysis routines. In
    addition, it reduces the range of accessible data (see above).

### Dimension Variables

This section is not applicable to this instrument.

## Annotated Examples

This section is not applicable to this instrument.

## User Notes and Known Problems

**Update: Problem with the 915 RWPs at the Intermediate Facilities
(6/22/00)**

A noise peak in the spectra of the intermediate facility profilers
located at +- 60 Hz from 0 was reported beginning back in 04-09-1997.
This was a relatively serious problem because it effectively raised the
minimum detectable signal level from -22 dB to -16 dB, a factor of 4. We
still do not know the true cause of the problem, except that it appeared
to be a 60-Hz noise problem. However, actions taken at Beaumont,
including adjusting, but not changing, the configuration of the ground
wires has considerably reduced the occurrences of "bad" accepted data
due to 60-Hz noise (75% approximately) and reduced the minimum
detectable SNR level to about -20 to -21 dB. At Medicine Lodge,
maintenance on the phase shifter assembly in December 1999 apparently
changed the configuration in some minor way so that it also is reporting
much less "bad" data and has a minimum SNR level near -20 dB. In both
cases, however, the minimum SNR level is due to the 60-Hz noise. At
Meeker, the problem has never been quite so severe and has a minimum SNR
value near -19 to -20 dB.

## Frequently Asked Questions

**Why don't the profiler values of winds and/or temperature agree with
values from the radiosonde balloon-borne sounding system (BBSS)?\
**

-   The RWP provides values averaged over (nominally) 1 hour while the
    BBSS obtains only a grab sample at one instant in time at each
    height.

-   The balloon from the BBSS travels with the mean wind; hence it is
    not collocated with measurements from the RWP.

-   The RWP values are volume averages over (nominally) 60-240 meters in
    height by 9 degrees horizontally.

-   The BBSS measures temperature, the RWP measures virtual temperature.

-   The RWP may be detecting birds rather than the true wind.

# Data Quality

## Data Quality Health and Status

The following links go to current data quality health and status
results:

-   [DQ HandS](http://dq.arm.gov/) (Data Quality Health and Status)

-   [NCVweb](http://dq.arm.gov/ncvweb/ncvweb.cgi) for interactive data
    plotting use.

The tables and graphs shown contain the techniques used by ARM's data
quality analysts, instrument mentors, and site scientists to monitor and
diagnose data quality.

## Data Reviews by Instrument Mentor

-   **Quality Control (QC) frequency**: Daily

-   **QC delay**: Instantaneous; daily

-   **QC type**: Min/max flags, graphical plots, comparisons

-   **Inputs**: Raw data

-   **Outputs**: Summary reports

-   **Reference**:

Data QC procedures for this system are mature.

1.  Data Flags:

> A procedure has been in place and operating for several years that
> produces a parallel data stream to the ".a2" data, which consists of
> consensus-averaged wind and temperature profiles produced by the wind
> profiler. These data are unchanged from the original data but have an
> additional data field consisting of flags referring to data that are
> questionable. The flags are determined based on differences between
> successive wind or temperature variables. Comparisons are made both in
> time and space and both forward and backward (i.e., comparisons with
> previous and successive values at a given height as well as
> comparisons with values above and below at a given time.) If the
> values exceed defined limits they are flagged.

2.  Comparison with radiosonde data:

> Every routine launch of radiosondes by the BBSS is used to compare
> wind speed, wind direction, and virtual temperature between BBSS and
> the 50-MHz and 915- MHz profilers at the Central Facility. The
> approach taken is to compare all values of "good" profiler values with
> BBSS values averaged over nearly the same height interval. The
> differences are used to produce the mean, standard deviation, maximum,
> minimum, and number of values. These data are appended to a file that
> dates back to June 20, 1995. Summary plots of these data are inspected
> to determine degraded system performance (see Coulter and Lesht,
> "[Results of an Automated Comparison Between Winds and Virtual
> Temperatures from Radiosonde and
> Profilers](http://www.arm.gov/publications/proceedings/conf06/abstracts/coul2_96.pdf)"
> (PDF Document) in *Proceedings of the Sixth Atmospheric Radiation
> Measurement (ARM) Science Team Meeting*, CONF-9603149, San Antonio
> March 4-7, 1996, U.S. Department of Energy, pp. 59-60). The statistics
> of the differences are inspected daily.

3.  Comparison between 915-MHz and 50-MHz profilers:

> a\) A Quality Measurement Experiment (QME) operates routinely to
> produce a virtual wind profile derived from both the 915-MHz and
> 50-MHz radar wind profilers.
>
> b\) Portions of the wind profiles from the two instruments, using
> high-power data from the 915-MHz profiler and low-power data from the
> 50-MHz wind profiler, are compared in a manner similar to that used
> with BBSS and RWPs. Profiles of mean speed, direction, difference in u
> component, difference in v component, and difference in w component
> are appended to a file dating to January 1997. In addition, a
> statistical analysis on the differences paralleling the differences
> used for the BBSS is done over comparable height intervals and
> appended to a file beginning January, 1996. These differences are
> primarily intended to look for the influence of birds on 915-MHz radar
> performance. The statistics of the differences are inspected daily.

4.  50-MHz beam strength comparison:\
    \
    A comparison among output power for the three beams of the 50-MHz
    wind profiler is carried out daily by averaging the difference
    between returned signal strength in the lowest few acceptable range
    gates. Large differences appearing consistently are an indication of
    transmit problems. The differences are inspected daily.

5.  Estimated maximum height of return:

> The daily data from both 915-MHz and 50-MHz wind and temperature
> profilers are used to determine the maximum height attained in at
> least 25%, 50%, and 75% of the profiles during each 24-hour period.
> These data are appended to a file (for each site) beginning January
> 25, 1993 (915 - CF), March 24, 1994 (50 - CF), and January 1, 1997
> (915 - Intermediate facilities). These data are plotted occasionally
> to determine trends that might indicate hardware problems.

6.  Vertical time section perusal:\
    \
    Approximately every 5 days, the wind and temperature fields over a
    5-day period are plotted for both 50-MHz and 915-MHz profilers and
    visually inspected for consistency, both within each system and in
    comparison between the two instruments. These plots are printed and
    stored in notebooks.

7.  Daily inspection:

> Vertical time sections of hourly averaged wind and temperature over a
> 24-hour period are inspected daily for system consistency and
> operation via data placed at a Web site. (The displays for the 915-MHz
> system at intermediate facility #1 is available on the Web at
> <http://www.atmos.anl.gov/ABLE>).

## Data Assessments by Site Scientist/DQO

All DQO and most Site Scientist techniques for checking have been
incorporated within [DQ HandS](http://dq.arm.gov/) and can be viewed
there.

## Value-Added Products and QMEs

Many of the scientific needs of the ARM Program are met through the
analysis and processing of existing data products into "value-added"
products or VAPs. Despite extensive instrumentation deployed at the ARM
CART sites, there will always be quantities of interest that are either
impractical or impossible to measure directly or routinely. Physical
models using ARM instrument data as inputs are implemented as VAPs and
can help fill some of the unmet measurement needs of the program.
Conversely, ARM produces some VAPs, not to fill unmet measurement needs,
but to improve the quality of existing measurements. In addition, when
more than one measurement is available, ARM also produces "best
estimate" VAPs. A special class of VAP, called a QME, does not output
geophysical parameters of scientific interest. Rather, a QME adds value
to the input datastreams by providing for continuous assessment of the
quality of the input data based on internal consistency checks,
comparisons between independent similar measurements, or comparisons
between measurement with modeled results, etc. For more information see:

-   [VAPs and QMEs](http://www.arm.gov/data/vaps_all.php)

-   Combined 915-, 50-MHz Temperature Profile

-   Combined 915-, 50-MHz profiler, microwave radiometer (MWR), other
    sources Temp Profile

-   Sitewide Advective tendencies

-   Sitewide divergence Calculation.

# Instrument Details

## Detailed Description

### List of Components

The 915-MHz radar wind profiler is manufactured by Radian Corp. It
consists of a single-phased microstrip antenna array consisting of nine
"panels" (most systems have only four panels). The antenna is
approximately 4 m square and is oriented in a horizontal plane so the
"in-phase" beam travels vertically.

Other components in the system include four stationary acoustic sources
located at the corners of the antenna, a mobile acoustic source, a
receiver, an interface module, and a computer for data analysis and
processing.

### System Configuration and Measurement Methods

The radar wind profilers operate by transmitting in two different
vertical planes and receiving backscattered energy from refractive index
fluctuations that are moving with the mean wind. By sampling in the
vertical direction and in two tilted planes, the three components of
motion can be determined. The system consists of a single-phased array
antenna that transmits alternately along five pointing directions: one
vertical, two in the north-south vertical plane (one south of vertical,
one north of vertical), and two in the east-west vertical plane (one
east of vertical, one west of vertical). The non-vertical beams are
tilted at about 14 degrees from vertical.

Radial components of motion along each pointing direction are determined
sequentially. It takes, nominally, 30-45 seconds (dwell time) to
determine the radial components from a single pointing direction. Thus,
at the SGP CART site the system cycles through five beams (South, North,
East, West, and vertical) at low power, and then cycles the five beams
again at a high power (longer pulse length) setting. Then the whole
process is repeated. About five minutes elapse before the system returns
to the beginning of its sequence. Within an averaging interval, the
estimates from each beam-power combination are saved (11-12 in a 1-hour
period); these values are examined and compared at the end of the period
to determine the consensus-averaged radial components of motion.

Briefly, consensus averaging consists of determining if a certain
percentage (e.g., 50%) of the values fall within a certain range of each
other (e.g., 2 m/s). If they do, those values are averaged to produce
the radial wind estimate. The radial values are then combined to produce
the wind profile. The results of this averaging process are what are
reported in the ".a2" data files produced by the ARM data system.
Included in these files are height, speed, direction, radial components,
\# values in consensus, and SNR.

During a single time period during which the system operates in a single
pointing direction (dwell time), the data that is produced in the ".a1"
and ".a0" files is created. The system transmits pulses at about 1-10
kHz rate into the atmosphere. The backscatter from each transmit pulse
is sampled at, for example, a 1-MHz rate. This results in 1 sample every
150 minutes? in range. The samples at each range gate are averaged
together (time domain integration) over some number (e.g., 100) of
pulses to produce a phase value for input into a FFT. After (e.g., 64)
values are produced, the FFT is performed (one for each range gate).
This process takes on the order of 1 second. A number (about 30) of
these spectra are then averaged together during the dwell time. At the
end of the dwell time we have produced a single averaged spectrum from
each range gate along the designated pointing direction. The spectra
themselves are placed in the ".a0" data files.

The spectra are analyzed by the system before moving to the next
pointing direction. This analysis produces estimates of the SNR, the
noise, the mean velocity (proportional to frequency), and the first
moment (spectral width) at each range gate. This is the information that
is stored in the ".a1" data files. Both the ".a1" and ".a0" data files
thus have information at about (dwell time) intervals; however, the data
sequences among pointing directions and output powers.

A note of warning about the mean values in the ".a1" files. The values
are in % of full scale times 100, where full scale is the nyquist
velocity of the spectrum. Thus, velocity estimates are determined by
multiplying the "mdf" column times the "oband" or "vband" values
(described in the metadata) and dividing by 10,000.

RASS operation is essentially the same, except that the averaging time
is about 10 minutes and only a single pointing direction (vertical) is
used. Also, the atmosphere is "seeded" with a sound wave; the index of
refraction changes created by the sound wave are the signal source. To
sample both the sound wave (speed about 340 m/s) and the atmosphere (to
remove air velocity from temperature estimates) a larger FFT is required
(2048 points). This requires a smaller number of points for each time
domain integration and increases the processor time required to
calculate the FFT. The ".a0" files again are spectra; however, only a
portion of the spectra are reported, namely a region near 0 Doppler
shift to account for atmospheric motions and a region around the
expected speed of sound. The ".a1" files now consist of moments and
widths from both the atmospheric portion of the spectrum and from the
acoustic portion (the main contributor to the temperature calculation).
The ".a2" files consist of profiles of temperature and number of
consensus values.

In normal operation, temperature profiles are determined during the
first 10 minutes of every hour and the wind profile is averaged over the
remaining 50 minutes.

### Specifications

-   **Frequency**: 915 MHz

-   **Maximum Range**: 3 km 5 km

-   **Range Gate**: .06-1 km

-   **Pulse Length**: 60, 100, 200, 400 m

-   **\# Spectra/Ave Spectrum**: 1-100

-   **\# Pulse/Time Domain Integration**: 1-1000.

## Theory of Operation

This section is not applicable to this instrument.

## Calibration

### Theory

This section is not applicable to this instrument.

### Procedures

This section is not applicable to this instrument.

### History

This section is not applicable to this instrument.

## Operation and Maintenance

### User Manual

This section is not applicable to this instrument.

### Routine and Corrective Maintenance Documentation

This section is not applicable to this instrument.

### Software Documentation

ARM netCDF file header descriptions may be found at [915 RWP Data Object
Design](http://science.arm.gov/tool/dod/showdod.php?Inst=915rwp).

### Additional Documentation

**Update: Problem with the 915 RWPs at the Intermediate Facilities
(6/22/00)**

A noise peak in the spectra of the intermediate facility profilers
located at +- 60 Hz from 0 was reported beginning back in 04-09-1997.
This was a relatively serious problem because it effectively raised the
minimum detectable signal level from -22 dB to -16 dB, a factor of 4. We
still do not know the true cause of the problem, except that it appeared
to be a 60-Hz noise problem. However, actions taken at Beaumont,
including adjusting, but not changing, the configuration of the ground
wires, has considerably reduced the occurrences of "bad" accepted data
due to 60-Hz noise (75% approximately) and reduced the minimum
detectable SNR level to about -20 to -21 dB. At Medicine Lodge,
maintenance on the phase shifter assembly in December 1999 apparently
changed the configuration in some minor way so that it also is reporting
much less "bad" data and has a minimum SNR level near -20 dB. In both
cases, however, the minimum SNR level is due to the 60-Hz noise. At
Meeker, the problem has never been quite so severe and has a minimum SNR
value near -19 to -20 dB. Thus, for practical purposes, the problem has
been resolved.

See the [Preventative Maintenance Procedure Summaries for the
RWP915](http://www.db.arm.gov/emp-bin/MDS/ListPM.pl?instrument=915 RWP)
at the Southern Great Plains (SGP) site.

A.  **Calibrations and Related Performance Checks**

####  {#section .unnumbered}

1.  **What are factory recommended calibration procedures? (Identify
    NIST traceability.)\
    **

> The only true calibration procedures are carried out during the
> Acceptance Test Plan (ATP) that is performed immediately before the
> instruments are put into service. These are/were carried out by Radian
> personnel and the instrument mentor. They include the following:

-   Output Power: Measured at the output of the final
    amplifier/preamplifier, including both forward and reflected power
    measurements (3990 W and \>500 W for 50 MHz and 915 MHz,
    respectively).

-   Center Frequency: Transmit frequency (49.8 MHz and 915 MHz for 50rwp
    and 915rwp, respectively) is measured using a signal generator input
    to the receiver.

-   Doppler Direction: Using a special control parameter file, small
    signal frequency differences are analyzed to determine the
    appropriate sign of the analyzed frequency difference.

-   Dynamic Range: A signal generator with variable attenuator is used
    as input to the system to establish a dynamic range of at least 55
    dB.

-   System Sensitivity: Signal generator is used to establish a minimum
    detectable level of at least -127 dBm.

-   Range Verification: A delay line is used to establish range accuracy
    of +/- 30 m. All the above procedures are detailed in the ATP,
    Chapter 3, pages 3-9 through 3-26.

> **2. What are the factory recommended performance checks?\
> **
>
> As detailed in the ATP (Chapter 4), these include visual inspection,
> system power, timing, data transfer, antenna integrity, and RASS
> operation verification. Additional performance checks are detailed on
> page 100 of the system manual supplied by Radian and include:

-   Control lights

-   Date and time accuracy

-   Data display operating

-   Final amplifier current stationary

-   Appropriate antenna rotation

-   Data appearance

-   SNR levels unchanged.

3.  **What are the mentor calibration procedures?**

> There are no "mentor calibration procedures" other than comparison of
> data with other available sources of data. This, however, is more of a
> QC check.
>
> **4.** **What are the mentor performance checks?**
>
> These include:

-   Regular noise level checks (done by Site Ops)

-   Regular final amplifier current checks (done by Site Ops)

-   Daily data existence (done by mentor)

-   Vertical time sections of winds and temperatures (done by mentor)

-   Continuous (daily) maximum height attained monitoring (done by
    mentor).

> **5. How are calibration and related performance checks documented?\
> **

a.  Where are procedures documented?

> ATP, system operator's manual supplied by Radian Corporation and an
> Operators manual specific to the SGP supplied by the instrument
> mentor.

b.  Have major changes to calibration procedures occurred? NO

> If so, for which components and when?

c.  Are major changes to calibration procedures expected to occur? NO

> If so, for which components and when?
>
> **6. Who implements (mentor) calibration and performance checks?\
> **

-   \_ Mentor: Site Ops for system hardware Mentor for data integrity

-   \_ Factory: Factory, Site Ops, mentor

-   \_ Site Ops: Site Ops

-   \_ Other \_\_\_\_\_\_\_\_\_:

> **7. What is standard schedule of calibrations and checks?\
> **
>
> Factory calibrations are done at time of installation and are
> recommended by the mentor for every year.
>
> Other checks are recommended for Site Ops to perform in the Operator's
> Manual (p. 7):

-   Every 3 months operating level comparison

-   Every 2 years antenna analysis (factory procedure)

-   Monthly: Frame support levels and pointing direction, RASS sources
    level, acoustic sources operating

-   Daily: Operation, data existence

-   Weekly: Data integrity.

> **8. How are the calibration and check procedures initiated (queued)?\
> **

-   [x]{.underline} Scheduled Calendar Event: Monthly change of
    temperature range appropriate and expected to maximize accuracy and
    reliability of virtual temperature profiles.

-   \_ Work Order: When data existence fails, or other problem is
    identified by the mentor.

-   \_ Data Inspection: Daily (data existence, maximum height, and
    comparison with BBSS) and weekly (vertical time sections of wind
    vectors and virtual temperature contours).

-   \_ Instrument Failure: Site Ops checks daily for operation, monthly
    for physical level and pointing direction, output levels.

-   \_ Other\_\_\_\_:

> **9. How long does it take to perform calibration and performance
> check procedures? (List separately).\
> **

-   Basic factory calibration: 1-2 days

-   System operating: 30 minutes/day

-   Data existence and daily checks: 30 minutes/day

-   Data quality: 2 hours/5 days.

> **10. Are any data affected or lost during calibration or performance
> check procedures?\
> **

-   Basic factory calibration: All data lost

-   System operating: None

-   Data existence and daily checks: None

-   Data quality: None.

-   

> **11. What are corrective procedures when calibrations and or
> performance checks fall behind schedule?**
>
> None

B.  **Calibration Data\
    **

> **1. Where are calibration data documented? (List for each
> procedure.)\
> **

-   \_ Site Data System:

-   \_ Site Ops Database - Hard Copy: ATP

-   \_ Site Ops Database - Electronic Copy: Site Ops log

-   \_ Instrument Mentor - Hard Copy: ATP

-   \_ Instrument Mentor - Electronic Copy:

-   \_ Data Logger:

-   \_ netCDF file:

-   \_ Special Archive Database:

-   \_ Special databases accessible via the WWW:

-   \_ Other: Mentor log book; profiler log book (at profiler).

> **2. Where are calibration coefficients and algorithms applied to
> convert data to geophysical units?\
> **
>
> In system operating program (POP3), applied to a1 and a2 data.

C.  **Maintenance Procedures\
    **

> **1. What are the factory recommended maintenance procedures:
> (preventive and corrective)?\
> **

-   In System Manual (p. 97)

-   Clean air filters

-   Remove dust

-   Check cables

-   Inspect antenna, fences, exterior cables, clutter screens, guys,
    anchors.

> **2. What are the mentor preventative and corrective maintenance
> procedures?\
> **
>
> In Operators Manual (p. 7). These include the following:

-   Regular noise level checks (done by Site Ops)

-   Regular final amplifier current checks (done by Site Ops)

-   Daily data existence (done by mentor)

-   Vertical time sections of winds and temperatures (done by mentor)

-   Continuous (daily) maximum height attained monitoring (done by
    mentor).

> **3. How are maintenance procedures documented?**

a.  Where are procedures documented?

    i.  In System Operators Manual (p. 97-100)

    ii. In Operators Manual (p. 7)

    iii. Site Ops log at site data system (SDS).

b.  Have major changes to maintenance procedures occurred? NO

> If so, for which components and when?

c.  Are major changes to maintenance procedures expected to occur? NO\
    If so, for which components and when?

> **4. What is the procedure schedule?\
> **

-   Daily: Check operation, verify data existence

-   Weekly: Check data quality

-   Monthly: Check system alignment, cables, output levels, antenna
    switching

-   Yearly: Repeat ATP.

> **5. How are the procedures initiated (queued)?\
> **

-   \_ Scheduled Calendar Event: Automatic change of parameter files for
    temps

-   \_ Work Order: Data nonexistence or apparent malfunction determined
    by mentor

-   [x]{.underline} Data Inspection: Regular and automatic procedure of
    mentor

-   \_ Instrument Failure:

-   [x]{.underline} Other: Site Ops standing operation: daily check of
    operation, monthly checks of hardware.

> **6. How long does it take to perform maintenance procedure?\
> **

-   System operating: 30 minutes/day

-   Data existence and daily checks: 30 minutes/day

-   Data quality: 2 hours/5 days.

> **7. Are any data affected or lost during maintenance procedure?\
> **
>
> No
>
> **8. How are potential effects to data documented?\
> **
>
> Data Quality Reports
>
> **9. What are corrective procedures when maintenance falls behind
> schedule?\
> **
>
> None
>
> **10. Where is actual maintenance work documented?\
> **

-   Site Ops log

-   Instrument mentor's personal log.

D.  **Data Integrity and Quality Inspections\
    **

> **1. What nodes or activities along the data pipeline effect (or can
> potentially affect) the data stream?\
> **

-   \_ Controller Boxes

-   \_ Microprocessors

-   \_ Data Logger

-   [x]{.underline} Communication lines/links

-   \_ Calibration Data files

-   [x]{.underline} Ingest Modules

-   \_ Others? (List).

> **2. What are current difficulties?\
> **

-   Implementation of Quality Assurance (QA) procedures by SDS

-   Ability of SDS to handle vertical-only mode of operation for data
    ingest.

> **3. List and describe any standard or non-standard data inspections
> (active or planned) under each of the following categories:\
> **

-   [x]{.underline} Data Existence check: Daily ingest of "raw"
    consensus files (active)

-   \_ Mentor QC checks (during ingest): QC delta checks (planned)

-   \_ Mentor QC checks (outside of ingest):

```{=html}
<!-- -->
```
-   Vertical time section of vector and contour plots.(active)

-   Maximum height of wind and temperature profiles/day (active)

-   Comparison with BBSS (active).

```{=html}
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```
-   \_ Within Platform Check:

-   \_ Multiple Platform Check: Comparison with BBSS

-   \_ QMEs/VAPs:

```{=html}
<!-- -->
```
-   Combine 915, 50 virtual temperature profiles (planned)

-   Establish flags for questionable data (planned)

-   Compare temps and winds with BBSS (planned).

```{=html}
<!-- -->
```
-   \_ Other automated netCDF file checks

-   \_ Other analytic tools or algorithms.

> **4. Does storage media exist on the instrument system to back up data
> and store it for delayed data ingest? Please identify media and the
> maximum period of time that the data can be backed up on the media.\
> **
>
> Yes: The hard disk can hold spectra and consensus files for
> approximately 12 days. It can hold consensus only files for 1 year. An
> optical disk can hold spectral data for 1-2 months.

## Glossary

See the [ARM Glossary](http://www.arm.gov/about/glossary.stm).

## Acronyms

See the [ARM Acronyms and
Abbreviations](http://www.arm.gov/about/acronyms.stm).

## Citable References

There are numerous references to radar wind profiling, too many to list.
A good collection can be found in the proceedings from:

-   Lower Tropospheric Profiling: Needs and Technologies. American
    Meteorol. Soc. and German Meteorolog. Soc. Boulder, Colorado,
    September 10-13, 1991.

-   Third International Symposium on Tropospheric Profiling: Needs and
    Technologies, Max-Planck-Gesellschaft zur Forderung der
    Wissenschaften, NCAR, NOAA. Hamburg, Germany, August 30 - September
    2, 1994.

A few recent papers:

-   Angevine WM and JI MacPherson. 1995. "Comparison of Wind Profiler
    and Aircraft Wind Measurements at Chebogue Point, Nova Scotia." *J.
    Atmos. and Oceanic Tech*. 12:421-426.

-   Merritt DA. 1995. "Statistical Averaging Method for Wind Profiler
    Doppler Spectra." *J. Atmos. and Oceanic Tech*. 12:985-995.

-   Nastrom GD and FD Eaton. 1995. "Variations of Winds and Turbulence
    seen by the 50-MHz Radar at White Sands Missile Range, New Mexico."
    *Journ. Appl. Meteorol*. 10:2135-2148.

-   Wilczak JM and collaborators. 1995. "Contamination of Wind Profiler
    Data by Migrating Birds: Characteristics of Corrupted Data and
    Potential Solutions." *J. Atmos. and Oceanic Tech*. 12:449-467.

-   Williams CR, WL Ecklund, and KL Gage. 1995. "Classification of
    Precipitating Clouds in the Tropics Using 915-MHz Wind Profilers."
    *J. Atmos. and Oceanic Tech*. 12:1996-1012.

A few early classic papers:

-   Ecklund WL, DA Carter, and BB Balsley. 1988. "A UHF Wind Profiler
    for the Boundary Layer: Brief Description and Initial Results." *J.
    Atmos. Oceanic Technol*. 5:432-441.

-   Ecklund WL, DA Carter, BB Balsley, PE Currier, JL Green, BL Weber,
    and KS Gage. 1990. "Field Tests of a Lower Tropospheric Wind
    Profiler." *Radio Sci*. 25:899-906.