In general, work has continued on developing and evaluating algorithms designed to manage the Laser Atmospheric Wind Sounder (LAWS) lidar pulses and to compute the horizontal wind vectors from the line-of-sight (LOS) measurements. These efforts fall into three categories: Improvements to the shot management and multi-pair algorithms (SMA/MPA); observing system simulation experiments; and ground-based simulations of LAWS

Emmitt, G. D. A.

Houston, S. H.

Wood, S. A.

English

NASA Technical Reports Server

N90-12081
TITLE: LAWS Simulations - Sampling Strategies and Wind Computation
Algorithms
INVESTIGATORS: G.D. Emmitt
S.A. Wood
S.H. Houston
Simpson Weather Associates, Inc.
Charlottesville, VA 22902
(804)979-3571
ACCOMPLISHMENTS in 1987/88:
In general, work has continued on developing and evaluating
algorithms designed to manage the LAWS lidar pulses and to compute
the horizontal wind vectors from the line-of-sight (LOS) measurements.
These efforts fall into three categories: i) Improvements to the
Shot Management and Multi-Pair Algorithms (SMA/MPA); 2) Observing
System Simulation Experiments; and 3) Ground-based simulations of LAWS.
Shot Management and Multi-Pair Algorithm Improvements
Various forms of shot management have been examined. In particular,
several combinations of scan angle, scan rate and pulse repetition
frequency (PRF) were simulated and evaluated for shot coincidence and
shot density (spatial). Although it is possible to achieve shot intersec-
tions by controlling all three of the scanner/lidar parameters, mid-scan
or scan to scan variations in scan angle and scan rate have been ruled
out because of engineering considerations. However, shot timing or a
variable PRF has been kept as a viable option.
Prior to invoking a variable PRF, the Multi-Pair Algorithm (MPA) was
revised for use with a fixed PRF by improving the matching of nearest
shots to form shot pairs. MPA I used a look-up table to match shots and
did not consider the effects of the earth's rotation. MPA II includes
the change in sampled volume displacement as a function of latitude. A
comparison of MPA I, MPA II and the least squares approach for i00 x I00
km 2 areas is shown in Table i.
While the advantages of the MPA (I or II) over the least squares
approach are significant the MPA II showed modest improvement 10-50%
over the MPA I. Further improvement may be possible with an "assumed"
coincidence shot schedule yet to be developed.
?9
https://ntrs.nasa.gov/search.jsp?R=19900002765 2020-03-20T00:45:46+00:00Z
(Input:
Table i
RMSSpeedError
Gradient* and Random**Wind Field)
Least Squares
MPAI
MPAII
*U = V
O O
150-650 600-1250 1200-1450 150-1450 km
32.680(33.12) 8.963(I0.05) 11.294(9.400) 17.387(23.41)
1.241(0.988) 0.615(0.314) 0.626(0.324) 0.826(0.692)
0.890(0.761) 0.577(0.319) 0.552(0.459) 0.724(0.551)
-i du = dv = 10-5 -i -i
= 2.0 m s ' dx dy sec , Ou = Ov = 0.15 m s ,
-i
**Ow(Vertical velocity variations) = 0.05 m s , Onoise(LOS measurement
-i
uncertainty) = 1.0 m s
Observing System Simulation Experiments
Efforts to assess the potential impact of LAWS on global scale
weather forecasts are on-going in a set of GCM experiments being
conducted by SWA and NASA/GSFC. The amount of data generated by the
LAWS Simulation Model (LSM) has required modifications to the assimilation/
analysis programs that provide input to the forecast models.
Figures 1-3 show the simulated LAWS winds and their sampling related
errors using ECMWF Nature Run data as input. The along and cross track
errors are obvious in Figure 3. The absence of data near the sub-satellite
ground track is due to a cut-off for wind estimates made from shot pairs
having angular separation 175-180 ° . In simulations used as input to the
forecast impact studies, cloud fields and topography are included.
Ground-based Simulations of LAWS
During the period November 16-19, SWA conducted a series of experiments
at MSFC using the ground-based scanning CO 2 Doppler lidar. The experiments
were designed to answer some questions regarding lag-angle compensation,
optimum pulse length, single shot signal quality, and space-based lidar
shot management. Review of the data collected shows that we have enough
data to work on three of the primary objectives of those tests:
i) downwind/crosswind line-of-sight (LOS) variance comparisons;
ii) single-shot/poly-shot velocity comparisons; and
iii) LAWS sampling simulations.
80
Wecompleted the sampling simulation using i0 sequential VADs
obtained on 17 Novemberwhen the winds aloft were between 20 and 30
m s-I. This block of VADsallowed us to simulate shots taken 20 to
25 km apart (we assumedTaylor's hypothesis). The results of these
simulations were presented at the CLEO'88 meeting in April in Anaheim,
CA.
The quality of the VADs, in terms of data loss, required substantial
editing before trying to fit a sine wave to the LOSvelocities. In
Figure 4a a typical VADis shownwithout any editing. If the data losses
were easily identifiable (and unambiguous) from the velocity information,
then editing would be straightforward as it often is with other types of
sensors. In our case a positive but varying velocity is reported when the
SNRis insufficient to get a good peak detection. A low band pass filter
on the velocity data was tried but good data were often filtered out and
if a large contiguous section (% 90°) of the sine wavewas bad, then the
band pass filter performed very poorly.
Instead of using FFT's and band pass filtering we chose a method that
uses the amplitude of the signal for editing the winds. Figures 4a-c
demonstrate the method for extracting useful LOSwind information from
noisy Doppler lidar measurements. The method uses the maximumsignal
amplitude at the 90th range gate as a threshold value to be comparedwith
signal amplitude at range gates where good data are expected. Part a)
shows the signal drop-out for a VADof LOSwind velocities as a function
of lidar azimuth at range gate 22. Part b) shows the corresponding SNR
(solid line) for range gate 22 and the threshold SNR(dotted line) found at
range gate 90. The circles in part c) depict LOSwind velocities after
filtering out the noise. A sine fit to the date is also shown.
This approach is conservative in so far that it uses only the best
velocity data. While the sine fitting part of the software cannot handle
biased noise very well, it can handle a VADmadeup of very few good values
including clustering in partial sectors.
The sine fitted VADsprovided the "true" wind speeds and directions
against which shot-pair estimates of the winds could be compared. The
individual LOSmeasurements(processed through the Poly-pulse pair
processor) were paired so as to simulate the relative perspectives through
the boundary layer that would be achieved from a polar orbitor. In order
to obtain enough pairs to makea meaningful statistical statement on errors,
the shot pair estimates were grouped by angles into 12 bins. In Figures
5-7, the errors in the estimates of the U (cross track in this instance)
and V (along track) componentsas well as the total wind speed indicate
the samepattern of errors resulting from the numerical simulation.
However, the amplitude of the errors are slightly large, i.e., 3-5 m s-I
in the mid-range.
CURRENTRESEARCHANDPLANSFOR1988/89
During the next six months, efforts will be focused upon the follow-
ing three areas:
• L 81
* Develop a fully documented set of gridded wind/clouds/aerosol
fields for use in the Phase a/b LAWS feasibility and trade
studies. Included in the set would be:
Pure structures - divergence
vorticity
deformation
random (u,v,w)
Model outputs - global scale with clouds
with aerosols
regional scale with clouds
with aerosols
* Use single shot data from MSFC's (or NOAA's) ground based lidar
system to assess errors associated with incorrect height assign-
ment of LOS velocities obtained in regions of known wind shear
and aerosol gradients. Software will be developed for rapid
assimilation of backscatter data collected during the 88/89
globe missions.
* Complete the Baseline and Bracket OSSES being run at GSFC.
PUBLICATIONS
Emmitt, G.D. and J.W. Bilbro, 1987: Error analysis for horizontal wind
vector computation using line-of-sight component measurements from
a space-based Doppler lidar. Submitted to special issue of AppI. Optics.
Emmitt, G.D., 1987: Contributor to Laser Atmospheric Wind Sounder (LAWS);
Instrument Panel Report (Chairman R.J. Curran), NASA Earth Observing
System, Vol. IIg, NASA Headquarters, Washington, D.C.
Emmitt, G.D. and J.W. Bilbro, 1987: Assessment of error sources for one
component wind measurements with a space-based Doppler lidar. Paper
presented at the Optical Society's Fourth Conference on Coherent Laser
Radar: Technology and Applications, Aspen, CO, July.
Emmitt, G°D., 1987: Error analysis for total wind vector computations using
one component measurements from a space-based Doppler lidar. Optical
Society's Fourth Conference on Coherent Laser Radar: Technology and
Applications, Aspen, CO, July.
Emmitt, G.D. and S.H. Houston, 1987: Impact of a space-based Doppler lidar
wind profiler on our knowledge of hurricanes and tropical meteorology.
AMS 17th Conference on Hurricanes and Tropical Meteorology, Miami, FL,
April.
Emmitt, G.D., 1988: Direct measurement of boundary layer winds over the
oceans using a space-based Doppler Lidar Wind Sounder. AMS Third
Conference on Satellite Meteorology and Oceanography, Anaheim, CA,
February.
82
Emmitt, G.D. and S.A. Wood, 1988: Ground-basedsimulation of a space-
based Doppler lidar atmospheric wind sounder. Optical Society's
Conference on Lasers and Electro-Optics, Anaheim, CA, April.
Emmitt, G.D. and S.A. Wood, 1988:
Doppler lidar simulations.
AFGL,Hanscom,MA, June.
Subvisible cirrus in space-based
Atmospheric Transmission Conference,
83
791110 0 SO0
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Figure 2.
84
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LAWS simulation: Sampling strategies and wind computation algorithms

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