Title: NexRad Level II Data Format
1NexRad Level II Data Format
2Background Information
- Nexrad radars measure certain physical attributes
in the three dimensional space surrounding them. - This three dimensional space is logically divided
in a number of ways that mirror the way in which
the data is physically collected. These logical
distinctions also make it easier for data
consumers to understand and manipulate the data
in meaningful ways. - The following abstractions are used to logically
subdivide the data, each will be covered in the
following slides - Volume
- Sweep
- Scan
- Ray
- Pulse Volume
3Volume
- A Volume represents the entire three dimensional
space around a radar site at a single point in
time (technically it is the span of time from
when the radar starts collecting data to when it
stops). - A Volume is the top-most organizational
construct for NexRad radar data.
4Sweep
- Volumes are divided into sweeps.
- Each sweep has a unique elevation angle.
- Sweeps get their name from the operation of a
NexRad radar. In order to scan a three
dimensional space, the radar typically begins at
the lowest elevation angle and rotates, sweeping
out 360 degrees of space (one sweep). - Next, the radar will raise its elevation angle
and perform another sweep. - This process is repeated until the entire three
dimensional space has been scanned.
5Scan
- Sweeps are themselves made up of a variable
number of scans. - Most of the time, a sweep does not collect all
of the information it needs in a single 360
degree rotation. - Greater accuracy and precision can be achieved
if each type of data is collected in its own
rotation. - Therefore, a sweep will often contain a number
of scans at the same elevation angle. - Scans can contain a single type of multiple
types of data.
6Ray
- Scans are subdivided into rays.
- Rays can be thought of as spokes on a tire.
- Typically, rays are about 1 wide, so scans
contain roughly 360 rays (be aware that scans
often rotate slightly more than 360 and will
contain more than 360 rays). - The angle of each ray is known as its azimuth.
7Pulse Volume
- Each ray is divided into pulse volumes.
- Pulse volumes act like bins, catching the data
for one block of two dimensional space. - Pulse volumes typically have depths from 250m
1000m in length. - Pulse volumes are the atomic level of radar data
and cannot be further subdivided.
8Base Features
- NexRad radars collect three different base
features - Reflectivity
- Radial Velocity
- Spectrum Width
- Radial Velocity and Spectrum Width are known as
Doppler data.
9Reflectivity
- Reflectivity it is the traditional form of data
captured by radars. It is a measure of the
strength of the echo returned by a radar pulse.
Reflectivity is measured in decibels and is
usually denoted by the letter Z. Therefore,
reflectivity values are often given units of dBz.
10Radial Velocity Spectrum Width
- Radial Velocity measures the velocity of
particles moving relative to the radar. Radial
Velocity is measured in m/s. - Spectrum Width is a measure of the variance of
the doppler signals within a pulse volume.
11Base Features
- NexRad radars collect three different base
features - Reflectivity
- Radial Velocity
- Spectrum Width
- Radial Velocity and Spectrum Width are known as
Doppler data.
12Level II Data Format
- Each file represents one Volume.
- Raw files have the .Z extension and are
compressed using the LZC compression algorithm.
13High Level Data Organization
- Files contain an initial header that is followed
by a number of packets. - Packets do not have to be the same size, but in
practice they typically are.
14Data Types
- Byte 8 bits, integer type
- Short 16 bits, integer type
- Int 32 bits, integer type
- Float 32 bits, floating type
- Unsigned Char 8 bits, integer type
- All data on disk is Big Endian
15File Header Format
16High Level Packet Organization
17Message Header Information
18Continued
19Continued
20Continued
21Data Header Information
22Continued
23Pulse Volume Information
24Data Parameters
25Environmental Attributes
26Data Frame Check Sequence
The array of data can be a mixture of
reflectivity, velocity, and spectrum width data.
If more than one type of data is present, the
data will always conform to the following
organization Reflectivity gt Velocity gt
Spectrum Width (i.e. if datax is reflectivity
data and datay is velocity data, then x lt y).
Values start at pulse volumes closest to radar
and get further from the radar as the index of
the data grows (i.e. datax is closer than
datax1). Bad values (below signal to noise
ratio) are given a value of 0 and range folded
values are given a value of 1).
27Volume Coverage Patterns
- As mentioned earlier in this presentation,
volumes contain a number of sweeps at different
elevation angles and each sweep contains a number
of scans. - Volume Coverage Patterns define the number of
sweeps, the elevation angles of those sweeps, as
well as the number and types of scans in those
sweeps. - There are six common Volume Coverage Patterns
that are used depending on atmospheric conditions
and intended research.
28Volume Coverage Pattern Categories
- Convection VCP11 and VCP12
- Shallow Precipitation VCP 21
- Clear Air VCP31, VCP32
- Multiple Pulse Frequency Dealiasing VCP 121
29VCP 11
- Used for convection, especially when close to
radar. Has the best overall volume coverage. - 16 scans in 5 minutes
30VCP 12
- Used for convection, especially at longer
ranges. Focuses on lower elevations to better
sample the lower levels of storms. - 17 scans in 4 minutes
31VCP 21
- Used for shallow precipitation. Rarely used for
convection due to sparse elevation data and long
scan time. - 11 scans in 6 minutes
32VCP 31
- Used for detecting subtle boundaries or wintry
precipitation. Uses a Long pulse - 7 scans in 10 minutes
33VCP 32
- Slow rotation speed allows for increased
sensitivity. This is the default clear air mode
as it reduces wear on the antenna. Uses a short
pulse - 7 scans in 10 minutes
34VCP 121
- Used when there are a large number of rotating
storms, tropical storms, or when better velocity
data is needed. Scans lower cuts multiple times
with varying repetitions to greatly enhance
velocity data. - 20 scans in 5.5 minutes