U.S. DEPARTMENT OF COMMERCE NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION NATIONAL METEOROLOGICAL CENTER OCEAN PRODUCTS CENTER
TECHNICAL NOTE
OPERATIONAL PROCESSING OF ERS-1 SCATTEROMETER WINDS: A DOCUMENTATION
CHRISTOPHER A. PETERS * VERA M. GERALD PETER M. WOICESHYN ** WILLIAM H. GEMMILL
SEPTEMBER 1994
OPC Contribution No. 96
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THIS IS AN INTERNALLY REVIEWED MANUSCRIPT, PRIMARILY INTENDED FOR INFORMAL EXCHANGE OF INFORMATION AMONG NMC STAFF MEMBERS
* General Sciences Corporation, Laurel, Maryland
** NASA/JPL, Pasadena, California
1. Introduction
This office note describes a new
dataset internally available at the National Meteorological Center (NMC):
surface wind vectors from the ERS-1 scatterometer. The data are processed in
real time using a NMC/NASA-JPL developed system. The system combines quality
control and data management procedures designed at NMC with vector ambiguity
removal and directional selection algorithms adapted from the United Kingdom
Meteorological Office (UK Met. Office). The scatterometer is a spaceborne
radar that measures the intensity of its backscattered radiation returned from
wind-driven ocean surface waves. Since the magnitude of the ocean roughness
is correlated with the wind at the ocean surface, the radar backscatter
measurements from the scatterometer (also called sigma naughts) can be
processed to obtain surface winds. An empirical transfer function relates the
sigma naughts to the surface wind speed. The scatterometer has three separate
antennae with which to probe the ocean surface, thus enabling it to produce a
direction for the wind as well as a speed. This ability to measure both wind
speed and direction makes the scatterometer a potentially valuable source of
satellite ocean wind data, particularly in data sparse regions of the
equatorial and southern oceans. At present, other satellite based passive
instruments (such as the SSM/I or altimeter) cannot determine a wind
direction independently. A brief overview of the ERS-1 scatterometer,
along with a more detailed description of the processing scheme and final
product follows. The programs to decode the data and perform the processing
were implemented as part of the operational job stream on September 7, 1994.
It is anticipated that numerical weather prediction (NWP) models, particularly
the NMC Global Model (AVN and MRF), will soon begin experiments aimed at
assimilating this new dataset.
2. The ERS-1 Scatterometer
The scatterometer is an
active, five cm C-band radar on board the ERS-1 satellite, which was launched
by the European Space Agency (ESA) in July 1991. The instrument has three
antennae which emit radar signals, striking the ocean surface at varying
angles. The radar power backscattered from the wind-driven wavelets on the
ocean surface is then received by the satellite and correlated with surface
wind speed. The higher the amount of back-scattered radar power received by
the satellite, the rougher the sea surface, and the higher the wind speed.
Since the magnitude of the received power for each antenna relates to wind
direction differently, having three separate measurements of backscattered
power from three different view angles makes the deduction of wind direction
possible but somewhat complex. Problems in determining the correct wind field
arise due to an incomplete understanding of the physical processes which
govern the relationships between winds, ocean waves, and the scattering of the
radar signal (Offiler, 1994). An empirically based "transfer
function" is required to convert the backscattered power received to a
wind speed and direction at a height of 10 meters above the sea surface.
Several empirical transfer functions have been derived using data from field
experiments conducted during pre- launch and post-launch periods of the ERS-1
satellite (see Attema, 1992; Stoffelen, 1992), each of which produces multiple
wind vector solutions. Further processing is necessary to statistically rank
the solutions, assigning each a probability of being "correct" in
representing the wind field. Finally, a single solution must be chosen as the
"correct" one. Outside information, such as a background surface
wind field from a numerical model, often assists in the process of deciding
which vector represents the most likely solution. With regard to
instrument resolution, the measurements of backscattered power actually
consist of a 50 km wide area average of many pulses for each wind cell
measurement. The measurement locations (cells) are separated by 25 km, giving
an effective resolution of about 50 km. The width of the swath is about 500
km, with nineteen cells across a satellite track. The polar orbital period is
roughly 101 minutes, yielding about fourteen orbits per day. The ERS-1 has a
sun synchronous circular orbit at a mean altitude of about 785 km and an
inclination of 98.5 degrees (a near-polar orbit).
3. NMC Processing
NMC has been receiving the ERS-1
scatterometer data since January, 1992 in the form of a "Fast
Delivery" (FD) product from ESA. The ESA FD product includes three
measurements of backscattered power (sigma naughts) at each measurement
location (node), along with wind speeds and directions calculated by ESA,
using their own de-aliasing and ranking procedures. The ESA processed vectors
provided by the FD product have been monitored at NMC for over two years, and
have been found to be lacking in quality. For example, in some regions winds
blowing at 180 degrees opposite to each other at adjacent points are commonly
observed, indicating that the ESA processing scheme doesn't adequately resolve
the correct direction from the available set of solutions (up to six).
Problems also arise in regions of light wind speeds, with confused, randomly
appearing flow patterns present in the FD vectors. Gemmill et al (1994)
present a more detailed evaluation of the ESA FD data, noting several
deficiencies. Thus, it was decided that NMC should develop its' own
processing scheme for ERS-1 scatterometer data, with two purposes in mind:
First, to obtain an improved set of vectors for use by operational
forecasters, and second, to upgrade the quality of the ERS-1 vectors for
assimilation into numerical models.
3.1 Data Receipt and Co-location
The ERS-1 data
arrives at NMC via the WMO GTS from ESA-ESRIN (Frascatti, Italy) in BUFR
format generally two to four hours after measurements are taken by the
scatterometer. The data are decoded from BUFR (see WMO Manual on Codes,
Volume 1, FM 94, 1988) and co-located with NMC model data four times per day.
Each processing cycle contains a window of plus or minus three hours of
scatterometer measurements, i.e. the 12Z cycle decodes data measured from 09Z
to 15Z. A delay of at least two hours usually occurs between the actual time
of measurement and the time the ERS-1 data arrive at NMC. Occasionally, this
delay may be greater, as much as six hours or more. Thus, the NMC/NASA-JPL
processing scheme must consider these delays in data arrival. Also, for the
data to be of use to NWP models, they must be made available in a timely
fashion, say within three hours of real time. These realities led to the
decision to initialize the data unpacking and co-location programs several
hours "after the fact" (i.e. the 12Z cycle begins execution around
14Z), early enough to be of use to NWP models, but late enough to capture a
reasonable amount of data. As a result, some "cut-off" of data is
inevitable before assimilating it into the NMC forecast models. One possible
remedy we have undertaken is to process twice for some cycles - an early run
to get the data ready for assimilation, and a late run to capture all the data
in its' entirety (more on this below). After decoding, measurements at
each node are co-located with fields from the NMC global model. Either a
six-hour forecast from the AVN run (first guess) or the actual analysis from
the Global Data Assimilation System (GDAS) is used to provide surface winds,
air temperature, humidity and sea surface temperature. The "early"
00Z, 06Z, and 18Z runs use a six-hour AVN first guess, while the
"late" 00Z, and both "early" and "late" 12Z runs
take advantage of the availability of the GDAS analysis in their model ingest
(see Table 1). The processing scheme makes use of these model fields for
quality control and re-ranking procedures, which shall be described below.
3.2 Quality Control Procedures
In order to
maximize accuracy of the scatterometer wind vectors and minimize unnecessary
processing of bad data, some quality control (QC) procedures have been
developed. The scatterometer is one of three operating Active Microwave
Instrument modes (AMI) operating from the ERS-1 satellite, which also
functions in a Synthetic Aperture Radar (SAR) Image mode, or in a SAR Wave
mode. Whenever the AMI switches to the Image or Wave mode, data gaps result
in the scatterometer measurements. The scatterometer data over land is
flagged, but ice is not. To identify data over ice covered regions, the NMC
processing utilizes co-located NMC model analysis values of SST equal to zero
degrees C or less as a cut off to discard the data. The ESA land flags are
used to exclude data over land during processing. Since the data come into
NMC from different satellite "view stations" around the globe, they
must be time sorted, and any duplicate reports originating from multiple
reporting stations removed. During the minimization phase, NMC only processes
triplets of sigma naughts (to ensure a directional solution). Another
condition for processing is that the "noise to signal" ratio of each
sigma naught must be less than 10 %. Each sigma naught represents a series of
radar pulses over an interval of time and distance, with the number of
"missing" pulses included in the ESA FD data. When the total number
of missing pulses from a triplet of sigma naughts exceeds fifteen, we exclude
that particular node from further processing. At this point, the data have
been quality controlled, and are ready for further processing.
3.3 Minimization and Directional Selection Procedures
The minimization and directional selection algorithms developed at the
United Kingdom Meteorological Office (UK Met Office) have been adopted as the
basis for NMC's processing software (Offiler, 1992, Woiceshyn, 1993). Most of
the major changes in the overall processing scheme developed at NMC concern
data management, the co-location of NMC field data, and the initialization and
quality control procedures described above. Changes to the wind direction
selection algorithms received from the UK Met Office were minimal, and will be
briefly decribed below. After compiling datasets containing co-located
scatterometer winds and buoy reports for one year, both statistics and case
studies indicated that vectors derived from the CMOD4 transfer function were
more accurate when compared with several other candidate transfer functions
(see Gemmill et al, NMC Technical Note; Peters et al, 1994). The CMOD4
transfer function, derived at the European Center for Medium Range Forecasting
(ECMWF), was thus chosen as NMC's "operational" empirical algorithm
for processing of scatterometer data. It was developed using ECMWF analysis
wind fields as the "sea truth" data. Details of the formulation of
CMOD4 can be found in Offiler et al, 1994. A combination of two look up
tables (LUT's) generated "off- line" from the CMOD4 transfer
function, a quadratic function, and derivatives of that function invert the
sigma naughts to wind vector solutions at each measurement node. Also
established during the minimization are probabilities for each vector solution
at each node, reflecting instrument skill in selecting the "most
likely" solution. After ranking all vectors based on their relative
probabilities, the NMC global model surface wind field is employed as
guidance. Probabilities of each vector solution as being "correct"
are modified based on estimates of likely errors (standard deviation) in both
the background meteorological wind field and the scatterometer wind solutions (Offiler,
1992). The surface six hour "first gu ess" forecast winds from the
GDAS (see Kalnay et al., 1990; Parrish and Derber, 1992), co-located with
sigma naughts in step one of the processing system, are used to modify the
probabilities. Finally, a local consistency or "buddy" check is
performed on the wind field. The buddy check consists of a five by five node
array modal filter which the entire wind vector field must pass through. This
algorithm, named Sequential Local Iterative Consistency Estimator (SLICE), was
developed at the UK Met Office by Offiler (1992), and works by iteratively
checking for local inconsistencies and repairing them. The SLICE algorithm
repeats until fewer than a threshold number of nodes have had their
probabilities re-ranked. With regard to algorithmic/numerical
differences between NMC's processing and the processing done at ESA, the ESA
processing uses tables that are discretized in 0.5 m/s increments in speed and
five degree increments in direction for finding wind vector solutions during
the minimization, while NMC uses a combination of tables, functions, and
derivatives to compute the wind vectors. The ESA processing uses an 18 to 36
hour forecast from the ECMWF for the background wind field during directional
selection, whereas NMC uses either an analysis or first guess from the AVN
model. In addition, ESA and NMC use different direction selection algorithms.
The wind direction selection (often called ambiguity removal) algorithms used
by NMC produce more meteorologically consistent wind fields than those
obtained from ESA. The processing with SLICE is the final stage of
de-aliasing, resulting in a unique wind vector existing at each node of
quality controlled scatterometer measurement. Figure 1 demonstrates an
example of the de-aliased wind vectors. Figure 2 shows a schematic chart
outlining the total NMC/NASA-JPL processing package.
4. Final Datasets : Encoding and Further Details
The NMC processed scatterometer vectors, along with the latitude, longitude,
and time of each measurement node have been encoded in BUFR, and reside on the
NAS-9000. For documentation on BUFR, see "A Guide to the WMO Code Form
FM 94 BUFR", by W. Thorpe, or the WMO Manual on Codes, WMO # 306, FM 94
BUFR. The NMC processing scheme uses NMC W3 library routine W3FI85 to encode
the vectors in BUFR. Several W3 library routines to decode from BUFR exist:
W3FI78, and W3FI88 represent the latest. The data are processed six times per
day, once for the 06Z and 18Z cycles, and twice for the 00Z and 12Z cycles.
The 00Z and 12Z cycles are processed twice in order to make an
"early" run for model assimilation and a "late" run for
fuller data capture. For each cycle, data are generally available by about
three hours "after the fact"; the 12Z scatterometer vectors, for
example, should be available by no later than 15Z. To capture all the
available data, waiting until five hours after the cycle time may be
necessary. The names of the production datasets containing NMC/NASA-JPL
processed scatterometer winds, and the times at which the programs to create
these datasets execute are given in Table 1. The NMC scatterometer wind
vector datasets contain a series of BUFR messages concatenated into a single
file. In order to decode the BUFR messages, it is necessary to know which
descriptors were used in the encoding. Descriptors are listed in Table 2.
Table 1. ERS-1 Processed Wind Datasets
Cycle
Dataset Name * Execution Begins Model 00Z Early
NMC.PROD.ERS1WNDS.BUFRT00Z 02Z AVN FG 00Z Late
NMC.PROD.ERS1WNDS.BUFRT00Z 05Z GDAS 06Z
NMC.PROD.ERS1WNDS.BUFRT06Z 11Z AVN FG 12Z Early
NMC.PROD.ERS1WNDS.BUFRT12Z 14Z GDAS 12Z Late
NMC.PROD.ERS1WNDS.BUFRT12Z 17Z GDAS 18Z
NMC.PROD.ERS1WNDS.BUFRT18Z 22Z AVN FG * Note that
all datasets reside on the NAS 9000 Table 2. List of Descriptors Used and
their Units Descriptor # Type Units
1. Year Integer --- 2. Month
Integer --- 3. Day Integer ---
4. Hour Integer --- 5. Minute
Integer --- 6. Second Integer --- 7.
Latitude Real Degrees 8. Longitude
Real Degrees (-180 to 180, Positive Eastward) 9.
Wind Speed Real meters/sec 10. Wind Direction
Real Degrees
5. Acknowledgments
We thank David Offiler of the UK
Meteorological Office, Bracknell, Berskshire, UK, for allowing the use of
several of his subroutines and functions in the NMC processing of ERS-1
scatterometer data. We are grateful for the efforts of Rachel Teboulle in
support of this work, particularly in developing the time sorting algorithm
used in the NMC processing. We thank D.B. Rao for his helpful advice and
comments. This work was supported by the Coastal Hazards program of the
National Oceanic and Atmospheric Administration, and performed in part by the
Jet Propulsion Laboratory, California Institute of Technology, under contract
with the National Aeronautic and Space Administration.
References
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Validation: Workshop Proceedings - "ERS-1 Geophysical
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Kalnay, E., M. Kanamitsu, and W. Baker, "Global numerical weather prediction at the National Meteorological Center," Bull. Amer. Met. Soc., 71, 1410-1428, 1990. Offiler, D., 1992: ERS-1 Wind Retrieval Algorithm and Ambiguity Removal, EDIPVS Project Note 9, U.K. Met Office, Bracknell, Berks, UK (Dec 17, 1992).
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