TECH LIBRARY KAFB, NM. NASA Contractor Report 3473. Improved Simulation of Aerosol, Cloud, and Density. Measurements by Shuttle Lidar. Philip B.
NASA CR 3473
c.-
NASA
Contractor
Report 3473
Improved Simulation of Aerosol, Cloud, and Density Measurements by Shuttle Lidar
Philip B. Russell, Bruce M. Morley, John M. Livingston, Gerald W. Grams, and Edward M. Patterson
CONTRACT NASl-16052 NOVEMBER 1981
TECH LIBRARY KAFB, NM
NASA
Contractor
Report 3473
Improved Simulation of Aerosol, Cloud, and Density Measurements by Shuttle Lidar
Philip B. Russell, Bruce M. Morley, and John M. Livingston SRI International Me&o Park, California Gerald W. Grams and Edward M. Patterson Georgia Institute of TechnoZogy AtZanta, Georgia
Prepared for Langley Research Center under Contract NAS l-16052
National Aeronautics and Space Administration Scientific and Technical Information Branch 1981
CONTENTS
LIST OF ILLUSTRATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Vi
LIST OF TABLES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
vii
Part I
1:
EXECUTIVE SUMMARY
INTRODUCTION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3
RESULTS...................................................
II
A. B. c. D. E.
Atmospheric Models ................................... Lidar Parameters ..................................... Other Inputs ......................................... Aerosol and Cloud Measurements at 0.53 and 1.06 urn.................................. Density, Temperature, Aerosol, and Cloud Measurements at 0.355, 0.532, and 1.064 pm...........
RECOMMENDATIONS ...........................................
III
A. B. c.
Hardware Development ................................. Further Studies ...................................... Correlative Sensors ..................................
REFERENCES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9 11 15 15 16 17 19
Part 2: ORBITING LIDAR SIMULATIONS: AEROSOL AND CLOUD MEASUREMENTS BY AN INDEPENDENT-WAVELENGTHTECHNIQUE I II III
INTRODUCTION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
23
SUMMARYOF INDEPENDENT-WAVELENGTHAEROSOL LIDAR ERROR ANALYSIS METHOD. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
25
...................................... SIMULATION PROCEDURE
31
iii
IV
1. 2. 3. 4o
40 43 44 46
Signal .......................................... Molecular Density ............................... Transmission .................................... Rmin ............................................
49
SIMULATION RESULTS........................................
49 50
....................... Signal and Background Profiles ........................................... Retrievals
A. B.
1.
Tropical, a. b.
2.
3.
Nonvolcanic,
Cloud-Free,
Volcanic,
b.
Marine ...........
Cirrus,
Nighttime (Zenith Moonlit Cloud) ............ Daytime (Zenith Sunlit Cloud) ...............
High-Latitude, Nonvolcanic, Marine .......................................... a.
Saharan ......
Nighttime (Zenith Moonlit Cloud) ............ Daytime (Zenith Sunlit Ocean) ...............
Midlatitude, a. b.
VI
33 34 39 40
Atmospheric Models ................................... Lidar Parameters ..................................... Background Lighting .................................. Error Sources ........................................
A. B. c. D.
V
33
SIMULATION INPUTS .........................................
Noctilucent
Cloud,
Nighttime (Moonlit Cloud, cos e o = 0.5) ............................... Daytime (Sunlit Cloud or Ice, cos 8, = 0.5) ...............................
50 50 53 56 56 58 60 60 62 65
SUMMARYAND CONCLUSIONS...................................
APPENDICES ATMOSPHERIC MODELS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . BACKSCATTER-TO-EXTINCTION RATIOS . . . . . . . . . . . . . . . . . . . . . . . . . .
69 99
REFERENCES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
105
A B
Part 3: ORBITING LIDAR SIMULATIONS: DENSITY, TEMPERATURE, AEROSOL AND CLOUD MEASUREMENTS BY A WAVELENGTH-COMBININGTECHNIQUE I II
INTRODUCTION..............................................
117
SOLUTION TECHNIQUE........................................
121
A. B.
Gas Density and Particle Pressure and Temperature
Backscatter Profiles Profiles ....................
iV
........
121 125
-
129
ERROR ANALYSIS ............................................
III
A. B.
Gas Density Temperature
and Particle Backscatter ................................. Profiles
Profiles
........
129 130
IV
........................... ........... SIMULATION PROCEDURE
133
V
SIMULATION INPUTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
135
. ....... ... .................. ... ..... SIMULATED PERFORMANCE
137
VI
A. B. c.
Tropical, Nonvolcanic, Cloud-Free, Saharan; Nighttime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Midlatitude, Volcanic, Cloudy, Marine; Nighttime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . High-Latitude, Nonvolcanic, Cloud-Free, Marine, Nighttime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
137 142 144
SUMMARYAND CONCLUSIONS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
149
REFERENCES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
157
VII
V
ILLUSTRATIONS Part
4
5 6 7 8 9 10
Simulation Procedure for Evaluating Lidar Measurement . . . . . . . . . . . . . . . . . ......... .......... .. and Retrieval Errors
32
Model Backscatter Mixing Ratio Profiles, Single-Shot Signal and Background Profiles for Low Latitude . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
35
Model Backscatter Mixing Ratio Profiles, Single-Shot Signal and Background Profiles for Middle Latitude . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
36
Model Backscatter Mixing Ratio Profiles, Single-Shot Signal and Background Profiles for High Latitude . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
37
Low-Latitude Nighttime Simulation Results, 1.064 and 0.532, pm, Using Conventional Density Data.................
51
Low-Latitude Daytime Simulation Results, 1.064 and 0.532 um, Using Conventional Density Data.................
54
Midlatitude Nighttime Simulation Results, 1.064 and 0.532 um, Using Conventional Density Data.................
57
Midlatitude Daytime Simulation Results, 1.064 and 0.532 pm, Using Conventional Density Data.................
59
High-Latitude Nighttime Simulation Results, 1.064 and 0.532 urn, Using Conventional Density Data.................
61
High-Latitude Daytime Simulation Results, 1.064 and 0.532 pm, Using Conventional Density Data.................
63
Part 1
2
3
Multiwavelength Analysis Procedure to Retrieve Profiles Scattering Ratio and Molecular Density....................
3
Low-Latitude Nightime Simulation Results, 1.064 and 0.532 u.m, Using Lidar Density Data Above 7 km, Conventional Density Below . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
141
Midlatitude
143
Simulation
vi
Results,
Results,
0.355
0.355
pm.......
138
Low-Latitude
Nighttime
Simulation
122
2
4
Nighttime
of
~m~~~o~~~~
5
High-Latitude
Nighttime
Simulation
Results,
0.355 urn......
6
High-Latitude Nighttime Simulation Results, 1.064 and 0.532 urn, Using Lidar Density Data Above 5 km, Conventional Density Below . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
145
147
TABLES Part
2
1
Assumed Lidar
2
Background Lighting (Zenith Upward Spectral Radiance) for a Downward-Viewing Lidar and Several Scenarios........
40
Representative lo-Uncertainties in Density Profiles Derived from Conventional Sources.........................
44
3
Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Vii
38
Part
1
EXECUTIVE SUMMARY
I$”
I
A 1979 report'
by the National
Administration's
Atmospheric
tific
that
objectives
The objectives
Lidar
could
Working
be usefully
Improving transport
stratospheric models.
(3)
Improving
atmospheric
(4)
Augmenting
(5)
Understanding
upper atmospheric
(6)
Investigating
thermospheric
(7)
Investigating relationships.
magnetospheric
the global
and cloud
activities
did
lidar
retrievals that
for
was not
fully
measurements
could
to provide
species.
aspects
vital
detailed
roles
secondary,
role
In
measurements
and resolution
thought
to be achievable
the Working
and complete
of atmospheric shuttle
backscatter
of aerosol
and measurement Thus,
in practice.
pm) to aid
Group's
calculations
lidar Also
to each objective.
profile
that
the report
However,
use of lidar (0.355
profile
(4).
In addition,
as to how well
contribute
(l)-(3)
in Objective
the accuracy
to be encountered
temperature
in Objectives
(l)-(5).
the wide variety
wavelength
of sun/weather
and resolution
explored
was the possible
Nd:YAG laser
possibly
atomic
experiments.
are likely
models.
waves.
each objective.
not include
and
data base.
defines
the accuracy
orbiting
explored
lidar.
and pollutants. chemistry
temperature
Group report'
in various
question
play
though
must have for
vapor
and mesospheric
to each of Objectives
indicates
conditions
seven scien-
by an orbiting
radiation-balance
measurements
The Working
and cloud
of water
stratospheric/tropospheric
are important
briefly
flow
the meteorological
and an important,
measurements
Group defined
are:
(2)
addition,
and Space
addressed
Defining
and (5),
pled
Aeronautics
(1)
Aerosol
cloud
INTRODUCTION
profiles
aerosol
the
aerosol
and
not at the tri-
measurements
and
measurements. 3
During under
the Working
contract
define
to NASA, began a facility
the lidar
space shuttle tives.
system
ally
simulation
be implemented
Lidar
report
thus
laid
tive
of this
study
is
tic
scenarios,
This
required
to obtain
assessments available
aerosol
Nd:YAG lidar
having
indirectly
with
corrections
profiles
and temperature
of realis-
aerosol,
cloud,
from measurements consistent
the lidar
data.
Defin-
with
the
parameters
The aerosol
and cloud
as part
at wavelength
of the study.
Subsidiary
This
to yield
were to:
l
Define the correlative sensors that could best aid the lidar achieving the objectives of the Working Group report.
l
Point out specific parameters.
l
Expose the study methods and results to the scrutiny of the scientific community, for example by publishing them in a refereed journal.
benefit additional at that
expected
addressed
implications
by the study
from the measurements
complexity wavelength.
hardware
of transmitting,
cloud,
technique
Define models
question
set of aerosol, to the assessment.
a new analysis
vertically goals
The
0.355 I.rrn (with
wavelengths).
integrated
code
l
A specific
a realistic for input
actu-
The objec-
a variety
were to be made using
are then
profiles.
could
study.
which
parameters
from longer
that
they
be used in
an error-analysis-and-simulation
backscatter
the
objec-
could
that
be retrieved
useful
both
and G.E. Facility
identifies
assessments
based on elastic
that
for
the code was to be improved
and cloud
pressure
4
could
with
scientific
the present
and resolution
to better
system.
quantitatively,
were to be made using
density
parameters
for
profiles
and temperature
technique
Group's
Group report
scientifically
at SRI;
density
yields
to assess
process
be compatible
shuttle-borne
the groundwork
and temperature
made by an orbiting
would
Space Division,
study2
the confidence
Working
the accuracy
G.E. study.
with
in a future
ition
density,
that hardware
studies
Electric
definition
and the Working
established
The Atmospheric
-
hardware
accommodations
That study
scientific
General
Group meetings,
density,
and ozone
of the necessary
was whether
in
lidar
the scientific
at 0.355
pm would warrant
detecting,
and processing
the signals
Part cloud
2 of this
analyses,
perature
(plus
formatted
for
last
Part
improved rapid
gives 3 gives
aerosol
conversion
mentioned
detailed
above.
report
Browell
previous
draft
has benefitted
and S.T.
Shipley,
results
the results
and cloud) to journal
of the aerosol of the density
analyses. manuscripts,
The remainder
and makes the recommendations This
E.V.
while
objective
results
report
of Part
mentioned
considerably who also
Th.xe
and temparts
in support 1 summarizes
are of the the
above.
from discussions
performed
and
a critical
with review
of a
version.
5
!
I-
II
A. h’
Atmospheric
Models
Atmospheric
models were developed
The models
tude bands. cirrus
and noctilucent
and tropospheric scattering 0.532,
(Saharan
and extinction
0.694,
pared
ruby
to previous
represent
middle,
of total
and high
gas density,
lati-
ozone,
and marine) coefficient
at wavelengths for
0.266,
each model.
measurements,
measurements,
The models are,
and have been com-
so as realistically
encountered
in practice.
in Appendix
A of Part
0.355,
to
The models and their 2.
Parameters
A set of lidar Facility
our own review listed
as well
low,
as mesospheric, stratospheric, Profiles of backaerosols.
lidar
are described
Lidar
profiles
and physical
the conditions
derivation
for
and 1.064 urn were computed optical
G.E.
include clouds,
based on previous
B.
BESULTS
in Table
parameters
Definition of hardware 1 of Part
was developed after careful review of the 2 report, the scientific measurement goals, and capabilities. 2.
Important
The detailed points
to note
parameters
are
here are the
following: l
Three wavelengths (1.064, 0.532, and 0.355 urn> are transmitted simultaneously, but they are obtained from a single Nd:YAG laser by harmonic generation, with no special line-narrowing, tuning, or wavelength-stability requirements.
l
Three detectors and two dichroic beamsplitters are used to measure all three wavelengths simultaneously, but detector linewidth and stability can be provided by interference filters, with no need for interferometers or other more sophisticated spectral discriminators.
7
-
0
Transmitted energies and beam divergences sati fy the preliminary eye safety guidelines* developed by G.E. 3
0
The weight, power, space, and other requirements lidar parameters are consistent with the limits ence payloads.
In sum, the lidar sophisticated Working
for than
transmitting wavelength
Definition
shuttle
emphasized
safety;
the Facility
telescope
dark
to daylite
c.
Other
as the first
in the
module
aspects
in
of
the two-wavelength report. 2 Finally, we have
Definition
Definition
report
bandwidths
(See Table
than
in assuming
for
viewing
1, Section
different
daylite
receiver
and dark por-
IV-B of Part
2).
This
pro-
radiances
sunlit
IV-C of Part
2.)
at the three
clouds,
of source
calibrating
Probable
were adapted study.
*See also
sunlit errors
lidar
upon crossing
in an aerosol
from
clouds,
each as a
2, Section
in atmospheric
transmission
and in
signal
or cloud
2.
and moonlit
were developed
(See Table
in terms of atmospheric back3 study, taking into account the and cloud
we adopted
IV-B of Part
wavelengths
angle.
and aerosol
In particular,
Section
ocean,
from a previous
range of heights
transmission
filters
lidar
(sun or moon) zenith
the received
current
and interference
Inputs
to represent function
beam stops areas.
Background
larger
considered
is necessary to maximize scientific gain consistent with eye 2 however, it implies the use of a system that automatically
changes
scatter
is less
and tripled
is more complex
by the Facility
of the earth.
cedure
system 1,2
the engineering
doubled,
system
of view and filter
tions
The transmitter
reports
Nevertheless,
as a baseline
wavelengths simul2 have not been worked out. Also, the three-
detection
followed
mission.
the Nd:YAG-pumped dye laser
system.
from
systems
shuttle
the fundamental,
taneously
fields
an early
Group and Facility
an evolutionary
8
system assumed here may be considered
suitable
system,
implied by the for shuttle sci-
layer
types
considered
a launcertainty of one-half
for
in the one-way
the particulate
optical
thickness
'c p, because
in most appreciably estimated
turbid
to an accuracy
of multiwavelength also
molecular
data
D.
be acquired
gaps.
ranging
(used
wavelengths dently,
considered
using
profiles.
with
density
backgrounds.
particle
backscatter
checked
by numerical
we have encountered
analyses --namely, (2) accounting density terms
errors for
profile
at the lidar
of atmospheric
backscatter
dominates
The results ing constituents l
losses,
backscatter particle
show that
indepen-
low,
and cloud middle,
errors
in retrieved
expressions
include lidar
the four
measurements
the backscattered (3)
determining
and (4)
by using
and also Both sources and
signal,
the total
calibrating
an atmospheric
and
and
random number generators.
in actual
location,
and doubled
of daytime
expected
(1) measuring
transmission
for
a variety
and the simulations in
above 40 km.
aerosol
from algebraic
using
of error
rms errors
analyzed
to retrieve
were conducted
were calculated
expressions
density
lidar
to fill
the fundamental
For each scenario, simulations
were
is most likely
each being
assuming
the algebraic that
only
data,
Simulations
model atmospheres,
data)
at 0.53 ---and 1.06 vrn ---
and 0.53 urn) available,
conventional
latitude
nighttime
a lidar
We
in conventional
30 km and 5 to 10 percent
--and Cloud Measurements
(1.06
backscatter
below
2.)
where most shuttle
we assumed conventional
be
the aid
B of Part
the lidar
lidar
cannot
even with
errors
of the globe
and where shuttle
from 2 to 3 percent
Aerosol
(rms)
ratios
~~ 2 0.3)
(See Appendix
to analyze
regions
Specifically,
We first
high
profiles
with
than f50 percent,
measurements.
to data-sparse
data will
those
the root-mean-square
density
appropriate
backscatter-to-extinction
media (i.e., of better
lidar
assumed that
effective
signals layer
gas in
where gas
backscatter.
useful
retrievals
can be made for
the follow-
and conditions:
By day: Vertical Saharan visible), 0.53 and 1.06 pm aerosols (at 0.53
structure of tenuous clouds (subvisible and aerosols, and boundary-layer aerosols (at both wavelengths), and strong volcanic stratospheric pm). Quantitative backscatter can be
9
determined for all of the preceding, cal depth does not exceed -0.3.
These results
were obtained
in the troposphere except
within
vertical
aerosol
opti-
and noctilucent
was 100 km in the troposphere,
mesosphere
horizontal
(below
scales
these
backscatter
if
of 0.1 to 0.5 km
-60 km),
fine-scale a transmit
energy
Horizon-
200 km in the stratosphere
and 2000 km in the upper mesosphere
aerosols) could
layers
could
on single
results
layers,
were used.
of the stronger
(sometimes
and above, cloud
of 1.0 and 0.25 km, respectively,
Vertical structure (to -85 km). lower tropospheric cirrus clouds, moreover,
resolutions
to 2.0 km in the stratosphere
the mesospheric
resolution
and lower
with
and 0.5
where resolutions
finer
particulate
By night: Vertical structure and quantitative backscatter for all of the above, plus upper tropospheric and stratospheric aerosols (at 1.06 pm) and mesospheric aerosols (at 0.53 v.m) and noctilucent clouds (at 0.53 and 1.06 urn). (Again, quantitative backscatter retrievals suffer when particulate optical depth exceeds -0.3).
l
tal
provided
be observed
shots--about
be converted
monitor
(noctilucent
or stable
and
on much
700 m apart);
to quantitative
transmit
energy
were
provided. the principal
In general, reduced
sensitivity
source
for
upper
virtue
to gas density tropospheric
errors,
Also,
1.06-urn retrievals
transmission
errors
in the stronger
pheric
wavelength backscatter
essential izontal
for
is the stronger
and vertical
source
upper
tropospheric
sols
information. 10
signals
are the dominant
stratospheric
somewhat less available
susceptible
(because
layers
to
virtue
These stronger aerosol
error
aerosol
The principal
layers.
is its
of the
of atmossignals
at useful
are
hor-
resolutions.
of uncertainty
in the gas density
in measuring
aerosols.
Although
can be made at 1.06 pm using
retrievals
are
the mesospheric
At 0.53 and 1.06 urn, errors inant
which
and quantum efficiency).
observing
1.06-urn wavelength
and nonvolcanic
retrievals. 0.53-pm
of the
at both wavelengths
nonvolcanic useful
be improved
density
are
stratospheric
retrievals
conventional
would
profile
of these information,
by better
density
the domand aero-
Density,
E.
Temperature,
--at 0.355, We next
0.532,
Aerosol,
--and Cloud Measurements
---and 1.064 vrn
considered
a lidar
having
and 1.06 pm.
An analysis
technique
that
information
from 0.355
combines
density sol
profile
and cloud
and an uncertainty contamination.
to an absolute level
density
or a level
and cloud cally
(from
and 1.06 urn to yield that
takes
density
by normalization density
density
a reference
height
pressure
of this
profile
into
account
profile
aero-
is converted
are available
to good
is used to improve
where temperature procedure
a relative
at an assumed isopycnic data
and temperature
analysis
0.53,
3) was developed
at 0.53 and 1.06 pm, and is also
to yield
the success
1 of Part
profile
where conventional
retrievals
guessed)
aerosol
integrated
or pressure
profiles.
verti-
are
The two keys to
are:
l
Returns at 0.355 pm are much more sensitive to gas backscattering than are those at 1.06 urn. (Hence, on a relative basis, 0.355 urn returns are much less sensitive to aerosol contamination, whereas 1.06 pm returns readily indicate regions where particulate contamination might be significant.)
a
Aerosol retrievals and the lidar-inferred temperature profiles are relatively insensitive to bias errors in the density profile, so that errors in absolute density normalization have very little effect on these data products. Also, this reduces the effect of some transmission errors.
Error
analysis
equations
ments and to provide check the algebraic extended
error error
to inject
procedure.
were developed
bars
In addition transmission,
included
errors
perature
or pressure,
to the four conventional
in absolute
atmospheres.
into error
cirrus
the low, clouds
Also,
simulation
the multiwavelength sources
listed
code was
in Section
II-B
we also
in the reference
(with
middle,
to
retrieval
and calibration),
short-wavelength
measurement
the above argu-
quantities.
normalization,
and in estimating
In general,
retrieved
density,
density
were run for
to quantify
the numerical
errors
from a long-wavelength Simulations
on all
expressions,
appropriate
(signal,
scatter
proffle
wavelengths--0.355,
(Figure
The relative
The lidar-derived
accuracy.
three
particle
temback-
errors). and high-latitude
(subvisible
as well
model as visible) 11
and lower errors
tropospheric
that
aerosols
were larger
measurement
errors
Hence, useful
density
conditions
posphere.
(Signal
mesosphere
if
the upper
errors
accuracies
(0.5
to 2000 km to extend sity
profiles
sphere
measurement duced errors particle tudes,
because
the smaller density
the density
absolute
tude moderate
density
volcanic
errors
of about
3 percent
profiles
retrievals
in
the nonvolcanic
stratosphere
to very
poor
density
errors
retrievals on volcanic
at these
profile.
12
of the poorer
heights.
stratospheric
both because of the insensitivity and because
to be larger
relative
accuracy
intro-
at low lati-
heights,
where A midlati-
errors.
in
the accuracy and upper
of the volcanic
place
of con-
of aerosol troposphere.
density
The impact
of such retrievals
relative
km).
profiles
aerosol
-27 amount of
model introduced
so at 0.53 Pm, where conventional
was especially
was signal
For a given
density
improved
tropo-
peak (typically
at the peak (-18
relative
significantly
ratio
aerosol
den-
aerosols
at greater
larger
relative
at most heights
tends
signal
was increased
in the upper
latitudes).
peak occurs
stratospheric
to 1.0 km in
this
stratospheric
error
yields
Use of the lidar-derived ventional
error
at the mixing
the low-latitude
in the
useful
Retrieved
to 2 percent
to -16 km at high
backscatter,
tro-
and 2.0 km in the upper
to 55 km.
nonvolcanic
of 1 to 2 percent
km at low latitudes
of 0.5
below 40 km; however,
of 0.5
However,
error.
measurements
resolutions
The limiting
and stratosphere.
upper
of 200 km provided
signals
had rms errors
were restricted
was 2000 km or less.)
resolution
useful
signal
and above.
and (cloud-free)
stratosphere,
to 2.0 percent)
daytime
measurements useful
vertical
and lower
data;
in the stratosphere
prevented
resolution
A horizontal
stratosphere.
large
also
and temperature
in conventional
the stratosphere
were run with
troposphere
density
and temperature
in
horizontal
Simulations
those
were similarly
lidar
to nighttime
than
introduced
errors
This
had led
of lidar-derived
retrievals
was minimal,
to density lidar
density
errors
nonvolcanic
For cloud-free, profiles
had rms errors
by strongly height
scattering
conditions,
of 1.2 to 2.5 K in a layer tropospheric
-8 km below the reference
aerosol height
heights
a horizontal
stratospheric
between
The major over
those
fine
vertical
obtained
pause region,
of these
by passive
of detail
In general, used to put error specific
is
bars
whenever
strong
tered.
In this
respect
sity
technique
significant
because
cloud
error or aerosol
it
for
(cloud
bars.
This
and temperature-wave
expressions
and temperature
pro-
reported
above apply
example,
increase
feature
retrieves
the user
layers
to
consid-
are encoun-
of the multiwavelength
contamination
Thus,
is their
and tropo-
stratosphere).
or aerosol)
simultaneously particle
sensors
the algebraic
and will,
in the
profiles
troposphere
density
the outstanding
is that
of -3 K
possible.
the errors
particulate
and includes
and temperature
before
validated
situations
erably
profiles,
never
on lidar-derived
important,
atmospheric
analysis
spaceborne
the tropopause
the simulations
moderate
errors
temperature
to -2 km in the upper
to a degree
This
lidar-derived
increasing
structures
the reference
(40 to 55 km).
km in the upper
defining
files.
height
(-0.5
permit
of 200 km
assumed an 8 K rms error
resolution would
bound was
The midlatitude
nadir-viewing
resolution
lower
resolution
temperature
These simulations
advantage
this
or pressure
of 2000 km (i.e.,
introduced
guessed at the reference
and on the top by a
a horizontal
resolution
aerosol
17 and 20 km.
temperature
ticle
layers
were at -40 and -55 km, respectively).
volcanic
bounded on the bottom
used here,
-5 km; the upper bound was -32 km for and -47 km for
temperature
where temperature
For the model atmospheres
was guessed.
lidar-derived
density effects
and par-
in the den-
is immediately
aware of
contamination.
13
III
A.
Hardware A major
benefits
RECOMMENDATIONS
Development conclusion
of this
can be obtained
study
by adding
is
that
considerable
measurements
scientific
at 0.355 pm.
Therefore,
we recommend that: a
A ground-based or airborne three-wavelength Nd:YAG lidar system be built to make aerosol, cloud, density, and temperature measurements, both to test the conclusions reached in this study and to aid in refining the analysis techniques by using actual data.
l
The three-wavelength Nd:YAG transmitter/detector be included in any future engineering studies lidar facility.
This
study
atmosphere, resolution
has also
aerosol
shown that,
structure
tion
stratosphere,
Vertical
This l
implies
resolution
and 2 km above,
in the mesospheric
tively.
sometimes
even subvisible
where in the troposphere, lower
can be usefully
of 0.1 km or less,
to 0.25 km or less.
in the lowest
aerosol
with
configuration of the shuttle
few kilometers
retrieved
with
from single-shot cloud
a vertical
returns.
heights
1 and 0.25 km vertical cloud
Else-
can be retrieved
of 0.5 to 1 km is useful
and noctilucent
of the
layers,
in the resolu-
respec-
that:
The shuttle lidar data recording and/or telemetry designed to preserve three simultaneous profiles with vertical resolution similar to the following:
o-5 5-18 18-30 30-40 40-75 75-85 85-90
system be for each shot,
Vertical Resolution 04 0.1 0.25 1 2 1 0.25 2 15
Most signal partly to
profiles
niques
us-')
encounter
form charge part
wh ere both
of these
l
This
l
be relatable Therefore
in the pulse-counting
regime,
in the intermediate
regime
conventional
recording
(e.g.,
overlap
analysis to other
pulse
techniques parts
with
(-1
techand nonuni-
require
that
an accuracy
each of
we recommend that:
A reliable, repeatable, and precise method4 of logging and splicing together all parts of the signal profile from 0 to 90 km be developed and tested. The method should permit determination of the ratio of signal return from any height to that from any other height to an accuracy of 0.5% or better, as well as accurate logging of the strong surface return. (The above accuracy excludes the fl statistical error inherently determined by the pulse-generation rate in the pulse-counting mode; this error can be reduced by summing many shots or expanding the size of pulse-counting range bins.)
Further
answered
difficulties The data
per pulse).
-0.5% or better.
B.
and partly
practical
of any profile
be partly
regime,
in the current
100 pulses
will
Studies
study
has raised
by further The simulation mance of:
study.
several
important
Therefore
questions
could
be
we recommend that:
program be used to evaluate
- A ground-based or airborne recommended in Section A.
that
three-wavelength
the expected lidar
perfor-
design,
as
- A two-wavelength lidar based on the alexandrite solid-state laser (X = 0.7 to 0.8.um) and second harmonic generation. Such a system would benefit from increased quantum efficiency and atmospheric backscatter at -0.75 urn as compared to 1.06 pm, while retaining many of the benefits of the more complex three-wavelength system simulated in this study. The tunability of the alexandrite laser also favors other measurements, such as water vapor by differential absorption. - A three-wavelength spaceborne lidar with increased output at the (relatively eye-safe) 0.355 Pm wavelength, to extend the upper height limit and improve the horizontal resolution of density and temperature measurements. l
16
A statistical study of existing radiosonde data be conducted to determine the rms error with which density can be estimated at the 8-km "isopycnic" layer, as a function of latitude and
season. Also, that existing and new data (from dustsondes, lidar, and satellites) be surveyed to estimate how often significant aerosol and cloud contamination occurs at this level. l
A study be conducted to explore the use of three-wavelength lidar data (with conventional density data) in the lower troposphere to estimate aerosol size distributions and backscatterto-mass conversion factors.
l
A study be conducted to determine whether the wavelengthdependence ratio Y [Z B (0.355 pm)/B (1.064 urn)] can be estimated to better thaR the flOO% a&racy assumed in this study by using - Height information height-dependence - Information
l
on Bp(0.532
previous
code be improved
- Make input understand.
parameters
easier
Correlative
random errors effects
with
set and to validate
that
for
to
the user
produce
to locate
a negative
and
inferred
signal.
of NO2 absorption.
Sensors
We recommend that conjunction
data on the expected
pm).
simulation
- Include
l
with
The existing
- Handle
c.
together of Y.
the following
the shuttle the lidar
lidar,
correlative both
sensors
be operated
to augment the scientific
in data
data:
--On the Shuttle: - A radiometer of the Earth Radiation Budget type, to measure radiative effects of aerosol and cloud layers detected by the lidar. - A cloud physics radiometer,5 to compare passively inferred cloud properties (height, phase, temperature, optical thickness) with those inferred by lidar. - A temperature profiling radiometer, to permit comparisons of lidar and passively inferred temperature profiles, and studies of aerosol and cloud effects on each. - One or more surface property sensors, such as a Coastal Zone Color Scanner or a bandsat Mapper, to study effects of aerosols and thin clouds on measured radiances and inferences.
l
Elsewhere: - Radiosondes, to measure temperature comparison to model, interpolated,
and density profiles for and lidar-derived profiles. 17
to measure - Dustsondes, aerosol profiles. - Ground-based and airborne and temperature. - In situ aerosol aerosol optical tion, shape).
stratospheric lidars,
and upper to measure
clouds,
density,
samplers (impactors, filters), to determine microproperties (size distribution, composi-
- Satellite limb-scanning aerosol radiometers to measure aerosol extinction profiles.
18
tropospheric
(such
as SAGE II),
I) --
,REFERENCES
1.
2.
Shuttle pheric
Lidar
Greco,
R.V.:
ition 3.
Appl. Evans,
Kyle,
W.E.:
sics tion,
H.L.;
Swissler,
vol.
Lidar
Multi-User
Radiometer. Amer. Meteor.
Preprints, Sot.,
Instrument
of Lidar
M.P.:
Aerosol
15, 1979, pp.
of an Airborne
R.J.;
of Atmos-
1979.
and McCormick,
22, Nov.
NASA CR-145179, Curran,
Report
System Defin-
1980.
T.J.;
18, no.
Program--Final
NASA SP-433,
and Simulation
Design
Measurements. 5.
Group.
NASA CR-3303,
Analysis
Opt.,
Research
Atmospheric
P.B.;
Error
Lidar
Working
Study.
Russell, for
4.
Atmospheric
Lidar
for
Methodology Measurements.
3783-3797.
Stratospheric
Aerosol
1977.
Barnes, Third
W.L.;
and Escoe,
Conference
June 1978, pp.
D.:
A Cloud Phy-
on Atmospheric
Radia-
107-109.
19
Part
2
ORBITING LIDAR SIMULATIONS: AEROSOL AND CLOUD MEASUREMENTS BY AN INDEPENDENT-WAVELENGTHTECHNIQUE
21
I
Previous make aerosol estimated orbital
studies
have considered
and cloud
measurements.
the measurement altitudes,
lidar
illuminations. accuracy
with
lidar
which
cloud
profiles
retrieval
are more accurate nevertheless, often
yield
particle
in the midvisible
than
visible
Other
signals.
of aerosol effects nal
and cloud
will
profiles
retrievals error
for
development
several profiles,
sources. data,
than
but also
or further
lidar
lighting
is
profiles
that
far
transmission less
accurate
lidar
conditions, that
mid-
Because studies and climatic than lidar
of these
sig-
retrieved
measurements.
of lidar
quantify
areas
parame-
in the near-infrared;
the quality
combinations
highlight
lidar
signal
rather
of simulated
not only
typical
possible.
profiles,
of shuttle
background
from the
and particle-
and radiative
to estimate
and other
of the more accurate
are also
particle
realistic
These results
that
in spite
the results
have shown the
and atmospheric
transport,
the utility
paper presents
and cloud
retrieved
formation,
is important
in judging
This sol
it
wavelengths
degradations
use the retrieved
profiles,
lidar
the near-IR,
and
profiles,
accuracy
information
various
scenarios.
yield
backscatter
to have
conditions
For example,
in gas backscattering
for
be retrieved
of realistic
often
at midvisible
signals
backscattering
crucial.
lidar
studieslm6
studies
signal-measurement
conditions
errors
no quantitative
a variety
is often
and atmospheric
return
and mass, could
between
accuracy
of these
and atmospheric
and aerosol
for
The difference
Several of lidar
to date,
such as extinction
signal
ters
accuracy
the use of an orbiting
parameters,
However,
parameters
INTRODUCTION
measurements parameters,
aero-
and retrieval
the expected require
and
early
errors
in
hardware
study.
23
We refer wavelength" the lidar though
to the simulations simulations.
This
data are analyzed
other
lidar
technique
wavelengths
to retrieve
information
is described
and the companion
analysis actual istically
24
that
techniques lidar
data
mimic
might
combines
gas density,
describes
be producing signal
data
profiles
care
in actual
even
simultaneously.
aerosol,
and cloud
paper.6
In both
to make the simulated
to techniques
and to include
in which
from two or more
in a companion
as possible
encountered
retrievals
at each wavelength,
paper we have taken
in the past,
here as "independent-
temperature,
and simulated
as similar
those
terminology
independently
wavelengths
An analysis
this
presented
error
used with
sources
measurements
that
real-
and retrievals.
II
SUMMARYOF SINGLE-WAVELENGTH
AEROSOL LIDAR ERRORANALYSIS METHOD
The error paper'
analysis
method used here and described
in a previous
is based on the scattering-ratio/normalization
calibration forms,
This method has been used,
and data analysis.
in many lidar
and the resulting
scattering
ratio,
studies.8-20
algebraic
A fundamental
that
we summarize
in varying
the analysis
method
expressions. occurs
in this
analysis
method is the
by Bp(X,z)
R(X,z)
Here,
error
quantity defined
method of lidar
+ Bg(X,z)
BP(U) =1+
I Bg(A ,z)
where BP and Bg are the particulate
, (1)
Bg(.A, z>
and gaseous
backscattering
coeffi-
respectively, at wavelength X and height z. As shown in detail 7 elsewhere, the scattering ratio is related to backscattered lidar sigcients, nal
S(h,z)
as
(z - zL)2s(x,z) R(X,z)
=
, KO>Q20 ,z,q)D(d
where ZL is Q2(,A,z,zL) and D(z)
the lidar is
the
altitude,
two-way
K(X)
transmission
can be any constant
multiple
(2)
is a calibration between
constant,
the lidar
of the atmospheric
and height
z,
density
profile.
25
In solving obtained
Eq. (2),
the backscattered
from the total
(internal
plus
detector
external)
output
background
that
the calibration
at the height
gas backscattering
V(A,z)
G(X),
so ,z) = V(x,z)
Thereafter,
signal
K(X)
z* where Eq. (2)
attains
dominates
particulate
is
obtained
calibration
procedure
the
.
(3)
is usually its
fixed
by assuming
minimum value
backscattering,
yields
be
i.e.,
(and hence can be estimated Rmin is close to unity error--see Section IV-D-4). This
must first
by subtracting
- G(A)
constant
S(h,z)
implying
with
the expression
Rmin(X),
relatively
from which
that small
R(X.,z)
in practice: (z - z~)~s(X,z)Q~(~,zI,z*)D(z*) R(X,z)
=
Rmin(X)
9
cz* - ZL)~S(~,Z*)~~(~,ZL,Z)DO
(4)
or h(z R(A,z)
- zI,z*
- ZLMX
AZ*)
=
Rmin(X) q(A,z,z*)d(z,zX)
9
(5)
where
h(z
- zL,z*
2 (z - ZL) - ZL) c * 2 (z - ZL)
s(x ,z,z*> E
(6)
so ,z) , so ,z*1
26
'
(7)
1. -
Q20 rq.,,z) q(h
,z,z*)
,
E
Q20 ,q,,z*)
(8)
D(z)
d(h,z,z*)
and E(h,z) (->
sign
is
the atmospheric
applies
obtained
Eq. (1)
below,
the aerosol
and cloud (e.g.,
factors.
quantities
however, might
and Bg(X,z)
has been
backscattering
by
optical
from Bp(h,z)
known,
these
composition, constrain
in climatic thickness,
by using
and albedo,
optical
conversion
factors
and shape distributions
in some cases knowledge usefully
(10)
.
required
particulate
As is well
when the model size,
wavelengths
from Eq. (5),
the +
lidar.
- 1-J
mass) can be derived
undefined;
viewing
= Bg(.h,z)[R(X,z)
heating widely
In Eq. (8),
particulate
studies
conversion
coefficient.
we can derive
environmental rate,
(9)
to yield Bp(bz)
In turn,
,
(downward-)
has been obtained
as described
rearranging
extinction
to an upward-
Once R(A,z)
= D(z*)
of Bp(X,z)
the possible
model can vary are
at two or more
range of optical
models. In solving obtained
Eqs.
from nearby
usually
provided
Rmin(X)
is usually
aerosol
data and other
tions , plus aerosol
and cloud
through
(lo),
meteorological
D(z)--and
data;
by a model (often
errors
S(X,z)--produce
(3)
factors.
E(X,z)--hence
improved
assumed to be unity
by using
in
outputs
these V(X,z)
usually
Q2(A,z,z~)--1s lidar
or is estimated
Errors
in the detector
hence Bg(z)--is data);
from previous
quantities
and assump-
and G(X)--hence
corresponding
errors
in R(X,z),
BP(X),
parameters
derived
from these
results.
in
and the other Conventional
27
error-propagation uncertainties
7
analysis
has shown that
in R and BP are given
the resulting
larelative
by
and
(12)
where p and p* are the absolute respectively,
6x is
gas densities
the lo-uncertainty
[These
= ( C
v+l 50 pm 2 r 0.1 l.~rn
(A-2)
50 urn 1 r 50 urn,
0 where
u = and n(r)dr
I
4.0
5.0 pm 5 r 5 50 urn
developed
collection
of tropospheric
the global
background
the Earth's
surface
as a likely
descriptor
over
0.1 Urn 5 r 55.0
is the number of particles
Toon and Pollack48
=
by oceans,
between
r and r + dr. solution
selected
we adopted
aerosol
and Fenn
(A-3)
(i.e.,
34
to represent
this
distribution
the aerosol
or marine marine
to a
Because most of
below 3 km.
of continental
of the Shettle
'
as a best-fit
heights
of the marine whether
radii
measurements
for
is covered
with
equation
aerosol
2 n(r)
this
aerosol
the ocean surface, The equation
pm
2.0
present
origin).
aerosol
is
Ni
c i=1
exp -
,
In 10 rcri J%
(A-4)
where N2 = Nl x 4.71 x 10
-4
r1 = 0.005 urn r2 = 0.3 urn bl = 0.475 T2 = 0.4. The small-particle continental
88
origin;
mode [i
= 1 in Eq. (A-4)]
the large-particle
mode [i
represents
particles
= 21 represents
of those
of
sea-spray
origin.
Although
to have different
refractive
keep refractive
index
With guidance composition sea salt
(taken
soil
as NaCl), and that
for
small
water
cally
high
relative
al . (j" show that, an accuracy
and traces
is
0.35
Mie-scattering
calculations
taken
and refractive ratios
shown.
files,
Mie-scattering indices
input
nonlinear
We modeled
The data
these
of Toon et
this
approximation is good to -7 and 10 for the imaginary part
averages
thickness rather
of scattering
are discussed
(see
of NaCl and the typi-
each combination
shown in Table
A-4.
Each combination
ratios
backscattering for
of size
and backscatter-
of these
values
were then profiles
and relative
averaging
than averaging
to the Mie calculations,
dependence
These errors
as 1.52-Oi
environments.
were made for
Our reason
calculations,
as (NH4)2S04].
than that quoted in the 60 ) and allows for a Toon et al.
multiwavelength
below.
two-thirds
as 1.525-
backscatter-to-extinction
optical
as described
taken
aerosol
to 1.06 pm.
Weighted
and used to derive midvisible
part
index
the multiwavelength
specified
is
and sulfate
NaCl and (NH4)2S04, region
to-number
[taken
of wavelength.
the wavelength
yielded
as basalt),
of sulfate
of marine
the real
the marine
somewhat less
independently
of f0.02
distribution
we modeled
caused by the deliquescence
for
of our model we
size.
(taken
particles
for
over
48
of the sea salt
humidity
indices
the two modes are likely
the purposes
pure NaCl (1.58-1.53--see
admixture
refractive
for
particles
value
that
of particle
of the soil
The latter
literature
indices,
from Toon and Pollack
index
A-4).
suggests
independent
as one-third
The refractive 0 . oo51WW Table
this
was to avoid
from
vertical
the results
proof the
the refractive errors
caused by the
and extinction
on refractive index. 61 by Bergstrom and Toon et
at some length
al . 6o The vertical the lidar
distribution
measurements
of our marine
reported
marine
had a mean height
of 0.5 km with
cruise
they
haze layer
reported.
models was based on 62 and Uthe, who noted that
by Livingston
the surface-based 22-day
aerosol
in the Atlantic
a standard
They also
deviation
noted
that
and Mediterranean of 0.3 km for elevated
layers
the below 89
3.6 km in altitude surface-based vertically
were usually
layer
typically
integrated
With marine
these
km for
The elevated
centered
at heights
of 1.5 and 2.5 km, with
that
for
the surface-based
backscatter
below
The absolute
that
maritime
tropospheric 48 The values
little values
culate
extinction
marine
aerosol
ss Ep(0.55
of latitude
and
Gaussian
have equal
peak
adjusted
50 percent
so
of column
tending
m)
midvisible
optical
optical
influence
pm> and that urn) = 0.012
is
depth for
with
the low-
a large
set
for
the requirement
of the marine
from 0.02
at low latitudes.
Ep(0.53 -1 0.167 km .
the gaseous yields
A-4)
ratios aerosol
be
and mid-latitude of time-averaged
depths
ranged
coefficient models
aerosol
summarized by Toon and 48 by Toon and Pollack to represent cases
selected to occur
in our marine
(Table
may be compared with
a total
E(0.55
90
about
of 0.4
and low-
backscatter-to-extinction
case and 0.19
continental
larger
only
properties
the high-latitude
Pollack.
the mid-
the peak value
coefficients
by combining
(X = 0.53
These values
Esg(0.55
contains
model optical
cases.
with
layer
backscattering
the midvisible
0.16 for
up to a height
These layers
the
3.6 km.
models were determined the averaged
ratio,
for
the surface-
approximately
with
mixing
of the
model
are independent
(HWHM) of 0.5 km.
backscatter
ratio
and 0.6 km for
versions.
values
one-half
a three-layer
mixing
layers
the
3.6 km.
latitude
shapes and half-width
than
2 of the main text,
backscatter version
as a result
less
we adopted
As shown in Figure
the high-latitude
for
below
in mind,
has constant
and that
accounted
backscatter
results
aerosol.
based layer
present,
to 0.17,
The midvisible
pm) at the surface Using
Rayleigh
the fact
-1 vrn) z 0.18 km
for
that
extinction
extinction
with
the parti-
each of our
Ep(0.53
pm)
coefficient
coeficient, .
(A-5)
The Koschmieder
relation, 3.91 VE(0.55
yields
a surface
meteorological
model.
As noted
logical
range is associated
described tend
as "clear."
Thus,
Cirrus
(ice layers
marine
usually
aerosol
models
the globally 48 of Toon and Pollack, they
models,
lidar,
clouds
of different
than
Figure
backscatter
canic
aerosol
model for
lists
several
properties
The properties top height
The mean midvisible , is computed
our cirrus
radiometric, size
are highly density,
aver-
mixing
height,
of these
is given
we have included
and geometrical
latitude
three
thickness
to describe
layers
in
some
in terms of mulband.
on the nonvolTable
A-5
layers.
in Table
A-5 were derived
by hT, and its
coefficient
from the corresponding
profile
Urn> = Y(0.53
as follows.
geometrical
gas backscattering
Bg(0.53
-microproshape, and
each superimposed
the corresponding
of
from cloud
than trying
ratios,
observations
distribution,
variable,
rather
models are
in-situ)
A-7 shows the cirrus
listed
cloud
than on calculations
band of the model,
state.
tiwavelength
d
our thicknesses
number density,
Since
each latitude
layer's
haze conditions,
haze conditions.
rather
crystal
orientation).
"typical"
light
values
(visual,
macroproperties,
cirrus
and Russell,
although
to our aerosol
based on empirical perties
miles) for each 64 such a meteoro-
Clouds
In contrast cloud
very
optical
aged, no-continental-influence nevertheless represent light
G.
and Collis
with
to have somewhat larger
(A-6 1
range V of 22 km (13.5 63
by Elterman
,
pm)
thickness
in the layer, of gas density
urn> D(hTAh)
,
Each by fi. Bg(0.53 D using (A-7)
91
(bl MID-LAT
0.694
m
0.532
-
0.355
---
-
(4 LOW-LAT
-
0lo’310-2 BACKSCATT’ER MIXINQ RATlO I FIGURE
A-7
CIRRUS
CLOUD
ON THE MODEL
MODEL AEROSOL
BACKSCATTER IN EACH
MIXING
LATITUDE
RATIOS BAND
Icr’
SUPERIMPOSED
I
IO IO2
-
Table
A-5
PROPERTIES OF MODEL CIRRUS CLOUD LAYERS
R(0.53
r+
pm)
Wf Visbilit$
(g m-3)
High-Latitude 9 7 4
12 10 7
sE I !---I I
I I
0.002
S
1.5 x 10-4
0.02
8
7 x 10-4
0.2
V
1.5 x 10-l
Mid-Latitude
7 x 10-5 6 x 1O-4 1 x 10-l
Low-Latitude
I
16
1.16
14
1.67
11 ---
11.00
*
Assumes
1 x 10-7
2 x 10-a
0.0004
5 x 10-5
3 x 10-7
2 x 10-7
0.008
3 x 10-4
6 x 1O-7
6 x 1O-6
0.36
2 x 10-l
intrinsic
backscatter-to-extinction
ratio,
r = 0.02
' Assumes effective
backscatter-to-extinction
ratio,
r'
T Based on BP, &, and satellite 9 Assumes
effective
where
is
Y
comparisons
See Table
particle
of lidar,
radius,
human observer,
a = 50 pm.
backscatter-to-mass
Y(0.53
v.m> = 1.30 X 10
backscattering
scattering
sr-'.
A-6.
the Rayleigh
Cloud particle specified
and previous
TV data.
= 0.05
sr -1 .
ratios
BP = Bg(0.53
-9
ratio
for
air,
2 -1 -1 m sr g
coefficients
given
.
are then derived
by: (A-8)
using
the
R and pm> x [R(0.53
urn) - l]
.
(A-9)
93
Note that
we have omitted
Eq. (A-9)
because
wavelengths
a wavelength
the size
used in this
approximation independent
that
cloud
of cirrus
descriptor particles
study.
We therefore
particle
backscatter
thicknesses
r are obtained
the cloud
the empirical
wavelengths strongly
data
because
light
multiple
cirrus
crystals study,
by multiple
particles
scattered
is very to (or
scattering
using
an effective
pulse
transmissivities.
r'
studies,
exceeds
extinction
were
(A-10)
near)
effects
sr-1
lidar
That
backscatter-to-extinction
and we have adopted
r because multiple coefficient
for
is described
analogously
to Eq. (A-10)
is,
his
scattering a given
by much These
in an approximate
way by
r'
in computing
lidar
using
-1
(A-12)
value
in our models.
tends
backscatter
by an effective
light-scattering of travel.
ratio
sr
can be
thus returning
has had success 0.05
to the
of cirrus
direction
can be described
=
as having
in comparison
forward-peaked,
Platt65
clouds
(A-11)
measurements
the original
Follow-
ratio.
.
are large
strongly
transmission
optical
to decrease coefficient. thickness,
Note that the effective Lidar
pulse
defined
as: T’ = Bpah/r'
94
and extinction
optics
,
scattering.
7, I
in his
used the geometric
backscatter-to-extinction 65 of Platt, we modeled cirrus
used in this
affected
cirrus
of
compared to the
particle
r = 0.020 Again,
is large
side
from
-r = BP Ah/i-
ing
the left
of wavelength.
Optical
where r is
from
.
(A-13)
I-
To aid
in relating the last
characteristics, descriptors
of cloud
to ground-based thickness distinctions
two columns
visibility
only
very
and latitudes
of Table
content.
can be related on the basis
visible
or subvisible A-5,
(to
subvisible,
nominally
visible.
Further,
the top layer
and physical 66 However,
set
of lidar,
density
human observer).
As
band of the model the top whereas
the bottom
layer
is
in each band is similar
to the weakest
the model layer
layers
cloud
described
is geometrically
in
by Uthe and
thicker
than
the
layer.
Cloud water
content
values
by treating
effective cient
or optical
some useful
of the large
in each latitude
are nominally
imation,
visibility
to backscatter
a ground-based
layers
scatter
A cloud's
each of our model cirrus
two cloud
measured
approximate
Nevertheless,
A-6 we classified
can be seen from Table
Russell.
A-S give
physical
and satellite TV observations acquired in many seasons 1 by Evans. These distinctions are summarized in Table A-6.
human observer,
optical
to observable
of Table
approximately.
can be developed
On the basis
layers
and water
human observers
values
as either
our model cloud
particle
can be approximately the particles
radius,
one can relate
Again,
a. particle
derived
as spheres using
from the backand assuming
the geometric
number density
optics
N and extinction
an approxcoeffi-
Ep by
N=-
EP
.
(A-14)
2na2
Cloud water
content
is given
by w=-
4 "a3 pN 3
,
(A-15)
95
Table
A-6
APPROXIMATE RELATIONSHIPS BETWEENCIRRUS CLOUD BACKSCATTER, THICKNESS, AND VISIBILITY* Particle
Backscatter 1o-6
1o-7
Coefficient
I
1o-5
Weak Cirrus Never observed visually
where p is particle water).
Combining
10
Strong Cirrus Always visible; appear
daytime may even opaque
Moonlight visible under good conditions if Ah > 1 km
TV
1.
mass density Eqs.
10-4
Daytime visible if Ah > 0.5 km
Daytime visible only if Ah > 2 km
Based on Reference
I
Medium Cirrus
Seldom detected via satellite *
-1 -1 m sr
(A-14)
backscatter-to-extinction
(0.92
-3 g cm for
and (A-15)
with
ice,
-3 for 1 g cm
the definition
of the
ratio, r E Bp/Ep
(A-16)
,
then yields
2 aP
W=--BP 3 r For ice
crystals,
this
in turn
Ng mw3>= The W values effective 96
shown in Table
particle
radius
.
(A-17)
yields 30a(pm)Bp(m
-1
A-5 were derived
a of 50 p.m.
sr
-1
)
.
(A-18)
from Eq. (A-18)
By comparison,
the
using
in-situ
an
-3
r
measurements tributing ranged
of Varley
and Brooks
most effectively approximately
from
67
showed that the particle to ice content in sampled cirrus
radius clouds
con-
10 to 100 pm.
97
Appendix
B
BACRSCATTER-TO-EXTINCTION RATIOS
The lidar particulate scatter
data
analysis
extinction profiles
profiles
BP(z)
fact,
for
Ep(z)
by a possibly
backscatter-to-extinction contributes
method assumed in this
ratio,
by dividing
study
lidar-derived
height-dependent
Y,(z).
Thus,
to the uncertainty
in particulate
the cases of practical
concern
constructs back-
model
the uncertainty
In PO where 0.01 5 rp
optical
in this
in Yp
depth
study,
r
to 6rp/rp. 5 1.0, "Yp/Yp is the d omi nant contributor In some cases this dominance results from a need to solve iteratively for BP(z) and Ep(z) profiles
that
are consistent
with
Because of the importance and (24)]
tainty tions
uncertainty
we have surveyed
means of evaluating
&rp/rp
in BP(z)--see
Eqs.
the possible
range of values Also,
Yp and the parameter
we have searched
c1 defined
[and (12),
Y as a P (and hence the uncer-
model and measured values
in any chosen model value). between
profile.
of &Yp/Yp in determining
hence the transmission-induced (201,
the model Y,(z)
of
for
correla-
by -ct
BP(C).53 pm) = Bp(1.06
,
urn)
(B-1 >
or ln[Bp(0.53
pm)/Bp(l.06
pm)1
a I
.
(B-2)
In 2 Our reason
for
investigating
mined from a lidar
this
measurement
and Yp are correlated,
knowledge
to reduce
in Yp.
Ref.
uncertainity
correlation
of Bp(0.53 of Bp(0.53 [For
is that
CL can be deter-
pm)/Bp(l.06
pm); hence,
pm)/Bp(l.06
an illustration
if
o!
pm) can be used
of this
process,
see
44.1 99
The results and B-l(c) for
of this
show model values
the various
ted versus
aerosol
strongly
and cloud
These results
on wavelength.
sured
in experiments
these
experiments,
urn> cannot
Stratospheric
described
fairly
construct
the curves
parisons,
see Appendix
for
well
the stratospheric
on model size
Yp does not
100
A-3
depend very
of Yp(0.69
vm) mea-
Since ~1 was not measured be plotted
versus
in
~1, but neverthe-
studies
have shown that
by spherical-particle in Figure
B-l(a,c).
A and Ref. with
44.)
models (For Thus,
aerosols
of the type
are
used to
a summary of such comalthough
the model results
some confidence.
aerosol,
stratospheric
measurements in Figures
These results
c is a good predictor
of
B-
indicate
of ~~(0.53
CL-< 1.5, as it is for most stratospheric aerosols. the practical value of this predictive ability is diminished
facts
each plot-
u.m) can be seen.
Yp are not available,
can be adopted
provided
study,
A, Sections
shows values
B-l(a)
Aerosols
Many comparison
l(a,c>
that
B-l(b)
Figures
urn) calculated
details
indicate
Yp(0.69
A.
(For
see Appendix
ruby lidars.
the range of Yp(0.69
stratospheric
of a.
using
less
used in this
indices, Figure
B-l.
pm) and Yp(1.06
models
value
and refractive
A-7.)
are shown in Figure
of Yp(0.53
the corresponding
distributions through
survey
that
pm),
However, by the
that: l
For the background stratospheric aerosol, CLis difficult to measure by lidar because Bp(0.53 urn) is difficult to measure. [Uncertainties in molecular density severely degrade measurements of Bp(0.53pm) at most stratospheric heights, even when using the three-wavelength analysis technique.]
l
Highly accurate particulate backscatter-to-extinction ratios not required for deriving lidar backscatter profiles in the unperturbed stratosphere, because stratospheric particulate transmission is nearly unity and thus is a small source of uncertainty in analyzing lidar data.
are
20
I I 11
I I I,
I I,,
,
I
(a)Models,
I
I
I
I
I
I
I
,
I
20
(c) Models, A=
(b) Measurements, A = 0.69 pm 0
T
n
H2SO&H20 WWF’4
I
Upper Tropospheric I
I
I
-1.0
0
1.0
0.5
2.0
a FIGURE
B-l
MODEL
AND
MEASURED
VALUES
BACKSCATTER-TO-EXTINCTION
OF PARTICULATE RATIO,
y,
(a) Model values for h = 0.53 pm, plotted versus a defined by Eq. (B-2); (b) Measured values for h = 0.69 pm. Letters indicate locations (all lower tropospheric). A = Tucson, Arizona (Refs. 68-71); S = San Francisco (Ref. 20); W = Seattle, Washington (Ref. 73); E = Hempstead, England (Ref. 74); (c) as in (a) but for X = 1.06 pm.
B.
Tropospheric
Aerosols
The most critical a is in
the troposphere,
uncertainties Here, aerosol
Unfortunately, models,
any systematic (plus
backscatter for
(excluding
well-defined
because
it
is here
error
Figures
that
sources
B-l(a,c) between
of Yp appears strength)
transmission
in analyzing
lidar
yp versus
is, those
the tropospheric
The reason a within
weak.
In fact, by loca-
predicted the marine
for that
data.
in the strato-
for
to be as well
the Saharan cases). for
than
Yp and a is very
exceed
of Yp versus
aerosol
show that,
as by a--that
Yp systematically
relationship
relationship
be measured more accurately
the correlation variation
Saharan values sphere
a well-defined
become significant
a can frequently
sphere.
tion
need for
and
the upper there
any of these
tropo-
is no groups
is 101
the large index
range and sometimes
(real
and imaginary)
strong
wavelength
in the troposphere
dependence
of refractive
as compared
to the strato-
sphere. Given this ing
Yp on the basis
the uncertainty
of aerosol
for
mean and standard Figures
this
overestimate
of the appropriate
approach
Yp, because
lar
by excluding
cal
aerosol
all
concern
in Figure
B-l(b),
which
ing model points
the mean and standard experiments
are systematically
because many of the references approximate two sets
approach
is
the central
data
extremes.
The results
values
for
Yp and larger
values
in Table
c.
cirrus
value value
include 102
would
for
nonspheri-
to calculate
data
points
this
is not possible
data
"central"
B-l(c).
points
the correspond-
be useful
the ten upper
Yp values data
in the
points.
the mean and standard
are shown in Table
particu-
absorption.
than
the measured
(1) The eight
values
and all
tropospheric
individual
plus
limited--in
An
deviation data
and lower
of
points; error
bar
Note the smaller
GY~/Y~, as compared
to the model
B-l(b).
Clouds The only
tive
lower
do not give
points
GYp/Yp, and
or moderate
However,
B-l(b):
in
lcruncer-
have smaller
B-l(b).
to calculate
shown in Figure
and (2)
of all
to in Figure
is
smaller It
B-l(a,c).
deviation
referred
little
by the measured
in Figures
points
yield
tropospheric
typically
models with
is supported
the
of data
B-l(a,b)
urban aerosols
Such particles
particles.
by calculating
set of models
absorbing
A measure of
of the mean.
may underestimate
highly
of select-
of a.
groups
shown in Table
the input
than do spherical-particle This
independent
from 19 to 37 percent
this
However,
approach
can be obtained
The results,
ranging
the alternate
location,
approach
deviation
B-l(a,c).
tainties
one can adopt
result,
cloud 0.05
adopted
multiple
value sr -'
for
Yp included
(indtzzndent
by Platt scattering
in Figures
of wavelength).
and by the authors effects.
Recently,
B-l(a,c) This
of this several
is
the
is an effecstudy
studies
to 74,75
Table
B-l
MODEL AND MEASUREDAEROSOLPARTICLE BACKSCATTER-TO-EXTINCTION RATIOS
Model Values,
(a)
Upper Troposphere [Figs.
(excluding
Bl(a,c)]
Yp(sr-l)
GYp(sr-l)
0.53
0.023
0.007
31
1.06
0.023
0.005
19
(b)
1
Saharan)
Model Values,
GYp/Yp(%)
Marine
[Figs.
and Saharan
Bl(a,c>
I
A(p)
Yp(srW1)
6Yp( sr-‘>
BYp/Yp(%)
0.53
0.054
0.020
37
1.06
0.053
0.016
32
(c) __-.
Measured Values,
[Fig.
-
set*
Yp(sr-l)
1
0.028
2
0.033
*
See text
for
have shown that cal
dies. multiple
cloud
this First,
small
scattering quantitative
Bl(b)]
Yp values
for
and fog models vary 0.06
sr -'
variation
water-droplet effects values
)\ = 0.69 urn
of sets.
single-scattering
the mean value
However,
infer
definition
water-droplet
around
Lower Troposphere,
for
by only
wavelengths
must be viewed clouds
a wide range of spheri-
are usually
must be taken
into
of BP from the lidar
about
15 percent
between 0.5
with
caution
optically account return.
and 1.06 pm.
in lidar dense,
so that
in attempting Second,
stuto
although 103
cirrus
clouds
produces that
tenuous,
strong
scattering
very
decreases
forward
effective Thus,
aspherical.
the large
are frequently
water-droplet
extinction);
the small
also,
Given the wide range of crystal
as well
as cloud
tainty
D.
in cirrus
appears
Yp must be considerably
larger
our simulations. can be seen that
particular
104
effect
can be markedly spherical
measurements
in this
orientations, that
and sizes,
the relative
than
uncer-
15 percent.
Summary of the above results,
rough measure of the relative
tion
shapes,
it
On the basis
it
scattering
the crystals
to the lidar
densities,
of the crystals
of single-scattering
study.
optical
(a multiple
variation
Yp is not applicable
size
(See the first this
circumstances,
in individual
value
we have adapted
leuncertainty paragraph should
measurements.
as a
in Yp, and hence in rp, of this
be revised
and hence this
50 percent
appendix.)
for
However,
upward or downward in
is an area for
careful
atten-
REFERENCES
1.
Evans,
W.E.:
Borne Lidar. 2.
Shipley,
Effect
J.H.;
Lawler,
April
1975.
Collis,
R.T.H.;
Lidar
in Space.
Atmospheric
Lidar
Brehm, W.F.;
Lidar Working
and J.L.
Spaceflight
53706;
Roesler,
Borne Lidar
of Aerosols
Wisconsin
and Their
of Meteorology, NASA Grant
NSG
1975.) P.B.;
Engineering,
vol.
Lidar
Multi-User
and Bowhill, 17, no.
S.A.:
1, Jan.-Feb.
Research Group,
Application.
Final
(AFGL-TR-79-0624,
Analysis
opt.,
vol.
Swissler,
Force Geophysics
T.J.;
and Simulation
18, no.
22, Nov.
Final
NASA SP-433, Design
Massachusetts.
Error
Program.
Buckley:
to Air
P.B.;
Instrument
System Defin-
1980.
Space Division,
Russell,
A.P.;
of a Shuttle
Russell,
NASA CR-3303,
Atmospheric
tem for
Odell,
(Department
(NASA CR-146134,
Optical
P.J.;
W.J.;
Heat Budget.
Hake, R.D.;
Guetter,
Distribution
Madison,
Atmospheric
Study.
Shuttle
Wiscombe,
Satellite-
23-29.
R.V.:
ition
J.T.;
The Evaluation
of Wisconsin,
1057.)
Greco,
Trauger,
J.E.;
on the Atmospheric
1978, pp.
7.
Joseph,
to Measure the Global
University
6.
1968.
E.W.;
Experiment
5.
NASA CR-96893,
and Weinman, J.A.:
F.L.;
4.
of High Cloud Cover via
S.T.;
Eloranta,
3.
Remote Probing
Report
1979.
Study of a Laser Report,
of the
General
Laboratory,
Radar SysElectric
Hanscom AFB,
1979.) and McCormick,
of Lidar
Aerosol
M.P.:
Methodology
Measurements.
for Appl.
15, 1979, pp. 3783-3797.
105
8.
Fiocco, pheric
9.
Aerosols
Res.,
vol.
Kent,
G.S.;
pheric vol. 10.
G.; and Grams, G.W.:
11.
10, May 15,
Clemesha,
Scattering
B.R.; vol.
Clemesha,
Summer 1966.
1969, pp.
of Mesos-
J. Geophys.
2453-2458.
and Wright,
R.W.:
High Altitude
Atmos-
from a Laser
Beam.
J. Atm. Terr.
Phys.,
169-181.
and Nakamura,
Y.:
Dust in the Upper Atmosphere.
237, June 9, 1972, pp. and Simonich,
B.R.;
surements,
B.R.;
of Light
29, 1967, pp.
Nature,
Radar Observations
in Norway During.the
74, no.
Clemesha,
Optical
1970-1977.
328-329.
D.M.:
Stratospheric
J. Geophys.
Res.,
vol.
Dust Mea-
83, no. C5, May 20,
1978, pp. 2403-2408. 12.
Gambling,
D.J.;
of Aerosols
Bartusek,
K.;
Below 60 km.
and Elford,
W.G.:
J. Atm. Terr.
Phys.,
A 12-Month vol.
33,
Study
1971, pp.
1403-1413. 13.
Fegley, pheric
R.W.;
and Ellis,
Dust Cloud.
Optical
H.T.:
Appl.
Opt.,
vol.
Effects 14, no.
of the 8, Aug.
1974 Stratos1975, pp.
1751-1752. 14.
Itabe,
T.;
Fujiwara,
Stratospheric Lidar
15.
Aerosol
Fernald,
16.
F.G.;
3, Jan.
McCormick, Post-Volcanic Atmos.
106
After Sot.
M.:
Temporal
Variation
the Fuego Eruption Japan,
vol.
55, no.
of the
Observed
by
6, Dec. 28,
606-612.
Measurements no.
Layer
J. Met.
in Fukuoka.
1977, pp.
M.; and Hirono,
Sci.,
and Schuster, of Stratospheric
20,
1977, pp.
M.P.;
Swissler,
Stratospheric vol.
35, July
B.G.:
Wintertime
Aerosols.
1973 Airborne
J. Geophys.
Res.,
Lidar vol.
82,
433-437. T.J.;
Chu, W.P.;
Aerosol 1978, pp.
and Fuller,
W.H.:
Decay as Measured by Lidar. 1296-1303.
J.
17.
Reiter,
R.;
tions
Jager,
H.;
Carnuth,
of the Mount St.
to July
1980.
Helens
Geophys.
W.; and Funk, Eruption
Res. Lett.,
W.:
Clouds
vol.
Lidar
Observa-
Over Mid-Europe,
May
7, December 1980, pp.
1099-1101. 18.
Russell, sol;
19.
P.B.;
Lidar
vol.
Gambling,
D.J.;
and Bartusek,
Aerosols.
Russell,
Thekakera,
M.P.:
23.
Evans,
Design
Opt.,
Russell,
ed.:
for
Spectrum,
for
Aerosol
Opt.,
vol.
Stratospheric
Aerosol
Corrections
19, no.
Mea-
and Gas Experiment
Depolarization
Appl.
518-522.
Plan--Correlative
Young,
Extinction.
at
1977.
NASA TM-80076, 1979.
Revised
J. Atmos.
3000-6100A
3, 1974, pp.
the AEM-B Satellite. A.T.:
Aerosol-Induced
E.E.:
Lidar
Sage Ground Truth
the Stratosphere
181-190.
1588-1608.
13, no.
of an Airborne
of Tropos-
of an Incident.
Solar
vol.
Implications.
Observations
and Uthe,
Aero-
163-177.
6, 1972, pp.
1979, pp.
NASA CR-145179,
P.B.,
1977, pp.
and Modeling
Measurements.
surements
24.
J.M.;
8, Aug.
Appl.
W.E.:
vol.
Stratospheric
and Thermal
Lidar
Extraterrestrial
1-A Intervals. 22.
K.:
Measurement
36, no.
vol.
1, Jan.
Env.,
Livingston,
Change:
Sci.,
34, no.
Atmos.
P.B.;
The Post-Fuego
With Radiative
Sci.,
Albedo
21.
Measurements,
J. Atmos.
pheric 20.
and Hake, R.D.:
20,
for
15 Oct.
(SAGE) on
Atmospheric
1980, pp.
3427-
3428. 25.
Noxon,
J.F.;
Whipple,
Observational Res., 26.
vol.
Hudson, RP-1010, A.L.;
E.C.;
and Hyde, R.S.:
Method and Behavior 84, no.
R.D.
ed.:
C8, 20 Aug.
and Laufer,
at Mid-Latitude.
1979, pp.
Chlorofluoromethanes
p. 31, 1977. A.H.:
(Original
Stratospheric
J. Geophys.
5047-5065. and the Stratosphere.
Reference:
J. Res. NBS, vol.
NO2 1.:
Bass,
A.M.;
80A, 1976, pp.
NASA
Ledford, 143-166.)
107
27.
Evans, Airborne
Lidar
tional,
Fiocco,
Radar in Alaska
vol.
Fiocco,
G.; and Grams, G.W.:
U.S.
Report
6919,
NASA Contract
18, 1966, pp.
Aerosols
for
SRI Interna-
NASl-14520.)
NASA
Standard
1969, pp. Atmosphere
Optical
Radar Observations
of Mesos-
J. Geophys.
2453-2458. Supplements,
Washington,
D.C.
Wu, M.-F.:
Observation
and Analysis
Technology,
the Summer 1964.
the Summer 1966.
ing Office,
1966.
U.S.
Government
Print-
20402.
Report
DOT-TST-74-7,
Lexington,
Massachusetts
Stratosphere.
of the Upper Atmosphere
34-38.
in Norway During
74,
vol.
Observations
and Sweden during
Tellus,
Res.,
31.
California.
G.; and Grams, G.W.:
pheric
30.
(Final
Photomultiplier
1978.
by Optical
29.
of a Near-Infrared
Applications.
Menlo Park,
CR-145380, 28.
Evaluation
W.E.:
of Trace
Constituents
Environmental (NTIS,
in
Research
Springfield,
the
and Virginia),
1973. 32.
Fiocco,
G.; and Grams, G.W.:
Extraterrestrial Phys., 33.
of Noctilucent
Dust and Trapped Water Molecules. 33,
vol.
Grams, G.W.;
Clouds.
J. Atmos.
Terr.
1971, pp. 815-824.
and Fiocco,
Ice Particles cent
On the Origin
G.:
Equlibrium
in the Upper Atmosphere
Cloud Formation.
J. Geophys.
Temperatures
of Spherical
and Implications
Res.,
vol.
82,
for
Noctilu-
1977, pp.
961-
966. 34.
Shettle,
E.P.;
and Their netic
Optical
Panel,
in the Atmosphere,
University
of Denmark,
NTIS,
No. N76-29817.)
Act.
P.W.:
Properties.
Wave Propagation
Propagation
108
and Fenn,
Lyngby,
Models
of the Atmospheric
Paper presented 22nd Technical 27-31 Oct. Denmark,
Aerosols
at AGARD ElectromagMeeting
on Optical
1975, The Technical 1975.
(Available
from
35.
Ivlev,
L.S.;
Substances Phys., 36.
37.
Fiocco,
9, 1973, pp.
of Small
Particles
km).
J. Atmos.
Terr.
Fogel,
G.;
Tozer,
and Beeson,
39.
40.
Implications
for
83, 1978, pp. 41.
Rosen, J.M.;
42.
32,
Hofmann,
1975, pp.
tospheric
43.
44.
J.M.;
Albedo
vol.
81,
Clouds
Rocket
Cam-
5607-5612.
from a Mesospheric 1977, pp.
in Noctilucent
3177-3178. Clouds--
J. Geophys.
Water Vapor.
and Laby,
Res.,
Res.,
vol.
Russell,
P.B.;
McCormick,
Fuller,
Woods, D.C.;
Stratospheric
J.:
Distribution.
Pepin,
vol.
Aerosol
J. Atmos.
Sci.,
82,
W.H.;
and Pinnick,
Time Variations
vol.
32, 1975, pp.
J.M.: 1977, pp. M.P.;
T.J.;
I:
of the Stratospheric
Geophys.
Correlative
from Two Sounding
Res.,
Measurements.
and Rosen,
L.R.;
of Noctilucent
Sci.,
1457-1462.
Hofmann,
J.M.;
(50-110
Model of Noctilucent
79, 1974, pp.
The Worldwide
J. Atmos.
ton,
Tempera-
1327-1337.
Measurements
of Particles
Midlatitudes.
Development
37, 1975, pp.
to Polar
D.J.;
Rosen,
Aerosol
D.J.;
Oc.
1155-1156.
II:
D.J.;
USSR Atmos.
Upper Atmosphere
Optical
vol.
Mesospheric
Hofmann,
Measurements. vol.
Res.,
The Sizes
M.:
of
77, 1972, pp. 720-725.
D.E.:
J. Geophys.
Layer.
Gadsden,
vol.
Contribution
Hummel, J.R.: Aerosol
vol.
Measurements
J. Geophys.
Sci.
Equilibrium
G.:
Spectral
Res.,
Based on Polarimetric
Acad.
in the Earth's
and Rees, M.H.:
W.F.;
paigns.
and Visconti,
Phys.,
J. Geophys.
Izv.
Phase.
Indices
1034-1043.
G.; Grams, G.W.;
tures
The Complex Refractive
S.I.:
in the Dispersed
vol.
Clouds. 38.
and Popova,
at Northern 1446-1456.
Balloon
Observations
Aerosol
Event
of the Time
of 1974-1975.
J.
1435-1440.
Swissler,
Rosen, J.M.;
T.J.;
Chu, W.P.;
Hofmann,
Grams, G.W.; and Pepin,
Measurements
Stra-
R.G.:
of the Stratospheric
D.J.;
T.J.:
McMaster,
Satellite
Aerosols.
Livingsand
109
1I:Comparison
of Measurements
borne Lidar. 45.
Bigg,
E.K.:
Bigg,
47.
E.K.:
Gras,
with
Altitude
Particle
Toon,
Aerosols vol.
for
Savoie,
vol.
32,
Aerosols Sci.,
and Their
vol.
33,
1976,
of the Stratospheric
J. Appl.
D.;
vol.
Meteor.,
vol.
18,
Ocean: Sot.,
Grams, G.W.;
Blifford,
Scattering
in
1976),
1977, pp.
79-81.
Patterson,
E.M.;
of Refraction Res.,
J. Appl.
D.A.:
Commonalities
in Measured
Having
a Soil-Derived
Component.
Saharan Aerosol
J.M.:
I.H.,
of the Input
Jr.;
Gillette,
82,
D.A.;
Measurements
Across
and Output.
Editor,
Science
D.A.;
1977, pp.
Patterson,
Bul.
Press,
and Stockton, 3153-3161.
E.M.;
of the Light Proc.
Symposium
(Garmisch-Partenkirchen,
Between 300 and 700 nm for vol.
Transport
of the Saharan Dust Layer.
Gillette,
J.
57, 1976, p. 144.
the Atmosphere
H. Bolle,
Calculations.
Characteristics vol.
Model of Atmos-
1977, pp. 2074-2082.
and Wyman, C.M.:
Properties
on Radiation
82,
Average
225-246.
Aerosols
and Prospero,
A.F.;
Transfer
and Gillette,
Am. Meteorol.
Wartburg,
A Global
Radiative
for
Res.,
the Atlantic
110
Measurement
J.B.:
15, 1976, pp.
E.M.;
Geophys.
phys.
J. Atmos.
Size Distribution.
Size Distribution
52.
of Stratospheric
C.G.:
and Pollack,
Patterson,
Aug.
Sci.,
855-860.
O.B.;
Meteor.,
51.
6, June 1981.
J. Atmos.
and Time.
and Michael,
J.L.;
pheric
50.
Particles.
Size Distributions
1979, pp.
49.
38, no.
and a.n Air-
1080-1086.
Aerosol
48.
vol
Dustsondes,
910-917.
Variations pp.
Sci.,
Stratospheric
1975, pp. 46.
J. Atmos.
made by SAM II,
FRG, 19-28
Princeton,
B.H.:
New Jersey,
Complex Index
Saharan Aerosols.
J. Geo-
53.
Patterson, Relation Res.,
54.
Optical
E.M.:
to Physical
Properties
and Chemical
86, no. C4, April
vol.
Lindberg,
J.D.;
Coefficient
and Laude,
of the Crustal
Aerosol-J. Geophys.
Characteristics.
20, 1981, pp. 3236-3246. L.S.:
Measurement
of the Absorption
Dust.
Appl.
vol.
of Atmospheric
Opt.,
13, 1974, pp.
1923-1927. 55.
Kondratyev, A.P.;
K.Ya.;
Grishechkin, V.B.;
Lipatov,
and Zhvalev,
56.
V.S.;
University,
Prospero,
J.M.;
Collins,
and Carlson,
57.
Carlson,
Res.,
T.N.;
vol.
1977, pp. 58.
59.
Cherenko, Korzov,
V.I.;
V=K=; Vasiliev,
Atmos.
0.B.;
Radiative
Pro-
Pap. 247, Colorado
Sci-
1976. Vertical
T.N.:
Equatorial
and Area1 Distribution North
Atlantic
Ocean.
77, 1972, pp. 5255-5265.
and Caverly,
Saharan Dust at Solar
V-A.;
in the GATE Area and Its
of Saharan Dust over the Western J. Geophys.
L-1.;
Ivanov,
Tolkatchev,
from Russian, Fort
Chapursky,
L-S.;
M.A.;
Aerosol
V-F.:
0.D.;
Ivlev,
Prokofyev,
Translated
perties. State
Barteneva,
R.S.:
Radiative
Wavelengths.
Characteristics
J. Geophys.
Res.,
vol.
of 82,
3141-3152.
Grams, G.W.;
Blifford,
I.H.;
Gillette,
Complex Index
of Refraction
Meteor.,
vol.
13, 1976, pp. 459-471.
Pollack,
J.B.;
Some Terrestrial
Toon,
0-B.;
D.A.;
of Airborne
and Khare,
Rocks and Glasses.
Soil
B.N.: Icarus,
and Russell,
J. Appl.
Particles.
Optical vol.
P.B.:
Properties
of
19, 1973, pp.
372-379. 60.
Toon,
O.B.;
of Several Oxide,
Pollack, Atmospheric
J.B.;
and Khare,
Aerosol
and Sodium Chloride.
B.N.:
Species: J. Geophys.
The Optical
Ammonium Sulfate, Res.,
vol.
Constants Aluminum
81, 1976, pp.
5733-5748.
111
'
61.
Bergstrom,
R.W.:
Atmospheric Atmos. 62.
Aerosol
Phys.,
Livingston, over
J.M.;
63.
and Uthe,
Elterman,
L.:
Collis,
R.T.H.;
112
Model with
Lidar
J. Atmos.
Report
6342,
SRI
N00173-77-C-
Sci.,
of Particles
Cirrus
Princeton, D.J.; Part
Reagan, J.A.;
1970. of the Atmo-
Hinkley,
Back-
Ed.
1976, pp. 72-151.
Proc.
Observations
of Cirrus
1191-1204.
Observations
of Tropical
Symp. Rad. in Atmos.,
Science
1972, pp. 242-244. D.M.:
Cirrus
AFGL-TR-78-0248,
Herman,
Measuring
Aerosol
presented
at Joint
Palo Alto,
E.D.
Lidar
Clouds.
Research
Monitoring
30, 1973, pp.
P.B.:
and Brooks, 2.
Cambridge
Research
and Gases by Elastic
Absorption,
vol.
Surface
Massachusetts, Laser
1976),
Eight
Environmental
Force
and Radiometric
and Russell,
E.E.;
Air
Bedford,
New York,
C.M.R.:
Varley,
tants,
(Final
Distributions
NRL Contract
P.B.:
Measurement
Hanscom AFB, Maine 01731, 68.
Contrib.
Aerosol
2 to 13 Kilometers.
and Differential
High-Altitude
Study,
Vertical
California;
and Russell,
Lidar
Clouds.
67.
E.E.:
318, AFCRL-70-0200,
(Springer-Verlag,
Press,
of the
pp. 223-234.
Hanscom Field,
scattering
Uthe,
Size.
and Mediterranean.
Ranges,
no.
sphere.
66.
of Particle
Vertical-Attenuation
Laboratories,
Platt,
Coefficients
1979.
Papers,
65.
1973,
Menlo Park,
Meteorological
64.
46,
Atlantic
International,
and Absorption
as a Function
vol.
the North
0141.)
Extinction
Air
Distribution
Force Geophysical
Laboratory,
1978.
B.M.:
Three Optical
Size Distributions. Conference California,
Particle
for
Remotely
AIAA Paper no. 71-1057,
on Sensing 8-10 Nov.
Methods
of Environmental 1971.
Pollu-
I
69.
Fernald,
F.G.;
Aerosol
Height
no. 70.
3, Apr.
Spinhirne, bution
72.
73.
Tenth
A.P.;
Derr, vol.
6-9 Oct. Ahlquist,
Total
vol.
D.D.;
Aerosols
11,
Distriof Aerosol
by Lidar
Technique.
pp. 426-438.
and Box, G.P.: over
Tucson,
Amer. Meteor.
Laser
Vertical
and Inference
1980,
Extinc-
Arizona
Sot.,
as
Conference
Radar Conference,
Silver
1980, p. 3. N.C.;
and Charlson,
Scatter-Backscatter
Lidar
P.M.:
V.E.: 19, no.
Pinnick, scatter Silver
of
R.J.:
Ratio.
Measurement
Appl.
Opt.,
vol.
of 11,
12, December 1972, pp. 2886-2889.
Hamilton,
Tenth
D'Souza,
Measurements.
R.G.;
Measurement
Aerosol. Estimation
from Multiwavelength
75.
T.V.;
International
Maryland,
of Atmospheric 74.
Meteor.,
B.M.:
in the Troposphere
of Tropospheric
Abstracts,
the Aerosol
and Herman,
19, no. 4, Apr.
Bruhns,
by Lidar
no.
Determination
J. Appl.
Cross Section
Index vol.
Determined
Waggoner,
J.A.;
Extinction
Meteor.,
Proparties
Spring,
by Lidar.
Reagan,
Refractive
Reagan, J.A.; tion
and Reagan, J.A.:
1972, pp. 482-489.
of Aerosol
J. Appl.
B.M.;
Distributions
J.D.;
Imaginary
71.
Herman,
Lidar
14, 15 July
Backscatter 1980, pp.
Jennings,
International
Env.,
vol.
of the Extinction
and Extinction Spring,
Atmos.
of Backscatter
S.G.;
Maryland,
of Clouds
Measurements.
Appl.
Opt.,
2310-2314.
Chylek,
P.;
Radar Conference, 6-9 Oct.
3, 1969, pp. 221-223. Coefficient
in Water Clouds. Laser
and Attenuation
and Ham, C.: Conference
Back-
Abstracts,
Am. Meteor.
Sot.,
1980, pp. 40-41.
113
Part
3
ORBITING LIDAR SIMULATIONS: DENSITY, TEMPERATURE, AEROSOL AND CLOUD MEASUREMENTS BY A WAVELENGTH-COMBININGTECHNIQUE
115
I
Part
Two of this
report
a proposed
space shuttle
techniques
and conventional
upper
tropospheric
remote
are usually logical
profiles
considerable fully
--reduces
of gridded
analysis.
the lidar
or gridded
Previous wavelength, useful
is negligible wavelength
density
which
l-4
studies
information
were less
those
from lidar
from the lidar than those
clearly
and temperature backscattering fail
in obtaining
where particulate
is a nonnegligible
from
may be of the greatest
can yield
at the lidar However, density
particulate (e.g.,
these
of
wavelength single-
or temperature
at the laser
contamination of any unusual unusual
very
in regions
of gas backscattering,
the credibility interest
single-
profiles
backscattering
fraction
when this
can jeopardize
that
measurements
compared to gas backscattering.
in regions
or wavelike
exceed
and cost-
demonstrated lidar
where particulate
shortcoming
are care-
errors
information
errors
profiles
have no means of showing This
and aerosol
entails
model density
the models
speed,
meteoro-
and time
the resulting
the quality,
backscatter
analysis.
techniques
wavelength
location
errors
analysis
from gridded
but even if
low-spectral-resolution
the atmosphere
for
in areas
particle
The alternative--using
density
experimental
relative
profiles
measurement
would be enhanced by density
provided
showed that
meteorological
profile
for
analysis
over most of the globe),
a density
cloud
retrievals
aerosols
in retrieved
and season,
of retrieving
measurements models
of error
Clearly,
It
from gridded
expense and delay, by location
effectiveness itself,
(i.e.,
expense and delay.
selected
information. stratospheric
inferred
each lidar
and cloud
independent-wavelength
density
obtaining
for
aerosol
using
source
Moreover, analysis
profiles
lidar
soundings
a leading
profiles.
simulated
and nonvolcanic
from radiosonde
in the density
INTRODUCTION
density
and they occurs. results, striations
structures). 117
DeLuisi
et a1.5
at three
wavelengths
separate
profiles
combined
with
of molecular
profile
(as in Ref.
of particulate
ter.
The effect
wavelengths
the size
aerosol
form for
of density
concentrations,
density
profile
could
technique5
that
errors
dependences,
a
cases)
for
the
and uses two of the
dependence
and temperature
be
assumes a
the wavelength-dependence populations
and
gas law to obtain
the published
wavelength
wavelength
backscatter
and the ideal
for
signals
so as to obtain
and particulate
The DeLuisi
for
lidar
angles,
backscattering,
to solve
of actual
assumed functional sol
3).
dependence
lidar
combining
nadir)
equation
form (linear
three
for
showed how the molecular
one-parameter
wavelength
(or
density
the hydrostatic
temperature specific
a technique
and two zenith
They also
extinction.
Thus,
presented
do not
paramefollow
was not
the
investigated.
caused by various
and lidar
parameters
aerocould
not be evaluated. This
paper presents
obtaining
profiles
and cloud
backscattering.
of gas density
minimum possible techniques this
sources
technique
aerosol
also
or cloud
minimizes
errors
gas backscatter), mate of these tion
determined
also
reduces
to correct After includes
for
at all
heights
the effects density
as well
as aerosol
by using
the technique of errors
normalization, or cloud
when it
strengthen
and aerosol
an estiinforma-
measurement.
(It
measurement
effects.)
we present signal
and reference
contamination
errors
the user with
cloud
the
be shown,
(to
the longer-wavelength
in lidar
which
However,
wavelength
longer-wavelength
aerosol
analysis
As will
large.
provides
somewhat by using
describing
and for
and temperature
laser
automatically
short-wavelength
profiles,
118
a short
is to make the
single-angle
understood.6
density
for
as aerosol
technique
many years,
well
from a simultaneous
errors
of this
are sufficiently
by using
and it errors
for
large
concentrations
these
goal
are fairly
produces
technique as well
to single-wavelength,
have been applied
error
but related,
and temperature,
A major
extension
that
practical
an alternate,
an error
analysis
that
profiles,
transmission
pressure
or temperature,
of the lidar
density
profile.
Finally, test
we simulate
the algebraic
the measurement error
expressions
and retrieval
process
and indicate
in order
to
the range of results
possible. For purposes primary
of illustration
wavelengths
wavelengths
for
input
are of special
we assume 1.064 and 0.355 to the retrieval
interest
calculations.
pm as the These
because:
l
They are produced by the Nd:YAG laser (plus frequency-tripling a source that is becoming increasingly popular for optics), current and proposed lidar systems (ground-, air-, and space-based).7
l
They are sufficiently separated stronger at one than the other.
a
0.355 pm, while short enough to be The tripled wavelength, strongly backscattered by gas molecules, is just long enough to avoid significant absorption by the Hartley-Huggins bands of ozone.
However,
the analysis
to any other
techniques
set of wavelengths
that
are quite with
gas backscattering
general
some or all
and could of these
is much
be applied
attributes.
119
II
A.
Gas Density Figure
indicate Step 1:
and Particle
1 illustrates
Backscatter
the solution
the following
density
surements) profile (11)
to solve
for
of Part
and its
uncertainty
tainty
typical
an assumed, of particulate
R(A39)
= 1 + [R&z)
where Y is a best-estimate at wavelength
wavelength
exponent
[,6R(X3,z)
is defined
Use the estimated R(X3,z)
ratio
ratio
using (4)
for
ratio
the con-
to (9) and
profile for
and uncer-
dependence
(and
to estimate
the
R(X3,z) R(h3,z)
for
the ratio
x3 to that gaseous
short-wavelength
by
x3
'
of particulate
at Xl,
elastic
and its is given
- ~]Y(X~,XI,Z)X~
in Section
and the measured
profile
wavelength
The estimate
scattering
[Eqs.
backscattering
scattering
GR(A3,z).
from mea-
report]. scattering
uncertainty
and a conven-
scattering
GR(A,z),
technique
Use the long-wavelength
short-wavelength
S(,hl,z)
the long-wavelength
Two of this
uncertainty)
Step -3:
profile
(model or interpolated
pc(z>
single-wavelength
with
The numbers shown
technique.
signal
profile
R(Xl,z),
ventional
Profiles
steps:
Use the long-wavelength tional
Step 2:
SOLUTION TECHNIQUE
(1)
back-
and E(X) is
backscattering.
the 8,9
III-A.] scattering
short-wavelength
ratio
signal
profile
profile
121
li ‘.!?I! SIGNAL
SIGNAL
SIGNAL :ONVENTIONALI
A3 = 0.35 pm
A2 = 0.53 pm
A, = l.OBpm
--T-
I
LIDAR
b
3
I 2 Tl DENSITY
DENSITY
FIGURE
1
MULTIWAVELENGTH OF SCATTERING Numbers
S(h3,z)
indicate
to obtain
uncertainty.
ANALYSIS PROCEDURE TO RETRIEVE RATIO AND MOLECULAR DENSITY steps described
PROFILES
in the text.
the lidar-derived
The relative
density
density
profile
profile
and I
its
is
(z - zL)2s(x3,z) D(z)
=
, Q2(+z,q)R(+)
which
follows
the symbols any height
from Eq. (2) are defined.
2, the absolute
of Part If
(2)
Two of this
absolute
density
density
profile
report,
where
p is known at
can be obtained
as
D(z) p&A
122
= pm
D(2)
.
(3)
In this
paper we usually 10
level, priori,
where the density because
The uncertainty in assuming Step 4:
Step -5:
Substitute
small
in Eqs.
and (31,
(2)
natural
level,
the lidar-derived
density
at all
p,(z)
heights
the conventional
values
elsewhere.
profile
the "composite"
density
profile.
Repeat
Step 1 using in place
uncertainty.
able profile derive
the composite
(e.g., with
of the conventional
Also,
0.53
if
the signal
rather
to gas backscattering the approximate
other
urn in Figure
lidar
simple
in Section for
< &p,(z).
Call
the resulting
profile
and its profile
wavelengths
at each other ratio
procedure
is that
strongly
and
are availdensity
wavelength
to
profiles. the ratio
on wavelength.
dependence
III-A.
the conven-
density
scattering
depends very h -4 wavelength
the uncertainty
11, use the composite
profile
the corresponding
The key to this
density
2
there.
z where 6:pL(z)
Retain
accuracy
variability
is discussed
density
pc(z)
to high
including
tional
its
example,
can be estimated
of the very
an isopycnic
uncertainty
cle
choose ^z to be an assumed isopycnic
of partiFor
of gas backscattering
yields Bg(0.355 whereas with
a typical
x-"
um)/Bg(1.064
wavelength
typically11r12
pm) = 81,
dependence
of particle
(4) backscattering,
: 0 Op(Zi>e
/
dz
(11)
zi
(12)
where Ui,ifl
is
the scale Hi,ifl
Note that
Eq. (11)
height,
f (zifl
obtained
from
- 'i)/ln[p(zi)/p(Zi*l)]
is equivalent
.
(13)
to (14)
provided
we define
p(Zi*l> ~(Zf,Zifl)
- p(Zi> .
E
(15) Use of Eq. (15)
in place
of the linear
p(Zi,Zlfl)
126
=
0.5
average
[p(Zi> + p(Zi*l>]
(16)
lr
improves
accuracy
of the scale definition
height for
critical,
Hi,ifl. g(z)
we now define
perature
when&
ifl
The choice
the interval-average
because If
significantly
Lf a linear
gravitational
is a very
slowly
a reference
can be guessed with
is an appreciable or logarithmic acceleration
varying
height
function
3! at which
an accuracy
fraction
6"P or
St,
g is not
of Z.
the pressure
or tem-
we have
= P+&,
P(q)
(17)
where
API = -E(z~,~>fXz~,z>Az~ , &zI and I,
I+1 are the indices
complete
pressure
profile
E zI - ‘i
of the lidar
(18)
,
(19)
data
heights
can then be generated
surrounding
Z.
The
using
i p(zi>
for
= P(zI)
+
C j=I+l
APj,
j-1
(20)
i > I and i
P(zi> = P(zI) +
c
APj,j+l (21)
j=I-1 for (20)
i < I. yields,
Substituting for
Eqs.
the complete
(lb),
(15),
pressure
and (17)
through
(19)
into
Eq.
profile, i
P(q)
= P + lrp(Z,ZI)
+
c j=I+l
kj,j-1
p(sj,sj-1)
s (22)
127
with
an analogous
expression
for
i < I.
Here,
rf = -i+I,a)A~I
kj,j*l
The temperature Eq. (7)
,
a reference
is convenient
2 -E(z j~zj*l)Azj,j*l
profile
is obtained
(24)
l
by substituting
Ezp e +CgPW cg pw
Eq. (22)
into
temperature
T, rather
to rewrite
Eq. (25)
kj,j-1 fj(zjszj-1) j=I+l
T(zi)
= T - p pw
where r) is obtained
+ cg
pw
by exponential
'g
than a pressure
pw P, is
l
specified,
(25)
it
as
kj,j-1
g $%ZI)
128
(23)
to yield
T(q) =
If
we have defined
+
;: j=I+l
interpolation
%
p(zj,Zj-1)
pw
’
between p1 and p1+1.
(26)
III
A.
Gas Density Applying
and Particle
standard
where we have introduced
ERRORANALYSIS
Backscatter
Profiles
error-propagation
techniques
the shorthand
notations
R, e R(Ansz)
s
y'm,n E \Y(Xmg.h*,Z) Similarly,
one obtains
from Eqs.
(2)
14 to Eq. (1) yields
(28)
.
(29)
and (3)
(30) where
with
the shorthand
notations p = pm
,
(32)
129
(33)
f Also,
= R(h,,g)
we have made use of the fact
Q2(X,~,~~)/~2(~,z,z~>
=
.
(34)
that
Q2(X,2,z>
=
exp
(35) [See Eq. (8)
of Part
Equation ante
(31)
neglects
of R3 and 1,.
positively
Two and discussion.]
This
correlated
this
covariance
through
Rl and i3 are positively fim~n(‘l)S
a negative their
correlated
term proportional
is nonzero
because
dependence
on y3 1, and also
through
their
[cf. Eq. (4) Pc(~*)S and S(X,z*) solution part.] However, an algebraic and its
extremely
complicated,
practical
cases we will
in Eq. (31)
magnitude
Eqs.
deiendence
of Part for
R3 and 6, are
(30)
and (31)
on
the covariance
turns
out
give
because
Two and Eq. (27) for
the
covariance
a slight
The simulations for 6pLIpL' and are thus conservative. shed light on the magnitude of the neglected covariance
of
term is
to be small
Because the neglected
simulate.
is negative,
to the covari-
term
overestimate in Section for
IV
practical
'
cases.
B.
Temperature
Profiles
In assessing file,
we make use of the fact
Eq. (26)
and in all
lidar-derived derived
uncertainties terms
T is independent
density
profile--particularly
the assumed isopycnic at all 130
heights
but
if
density
the parameter
in the lidar-derived that
density
the first
p occurs
temperature only
in Eq. (25).
of any constant
specified
as a ratio
in
As a result,
multiplier
of the lidar-derived /S [see Eqs.
pro-
(2) and (3)]. at the reference
in the lidarfactor [This
is
height
5 and true ';: is
temperature;
if
instead
the reference
parameter
on F/E near and above z because of the first Substituting sity
Eqs.
(3)
and (2)
by the linear
averages
into
is pressure,
term in Eq. (251.1
Eq. (26)
form in Eq. (16)
and approximating
kj,j-1
c j=I+l
den-
yields
i-l +
T depends
1
Di-1
CD;-1 + D;) + ki,i-1
(36)
where 2
I
Dj E D(sj)Q
(X~,Z~,ZL)
(Z' J - ZL) 2
=-
S(x3sZj)
.
Q2(X3sZjsZi) When pressure derive
P is
Eq. (36)
specified
at the reference except
from Eq. (25),
that
(37)
R(X3sZ-j)
height,
we still
the first
can
term is replaced
--P a . CgDif3 The primed the unprimed
relative
quantities
transmissions being that
all
thus
cancel
although Writing
defined
This
over
all
errors
by Eq. (37)
to the height
heights
except
are identical that
except
This
zi and 2.) other
in the density
ratios
those
heights
removal affect
in (Recall
because
Di and Dj equally,
in this
respect,
relative
is
Zi and zj.
occurs
(25)
in terms of primed
two-way
of errors
between
of Eqs.
Di and Dj are correlated
all
to
zi where temperature
removes the effect
at all
Eq. (36)
(38)
by Eq. (2)'
definition
zj are between
transmission
D;.defined
Q2 are referred
computed.
transmission
densities
by
and
Hence, I Di and Dj are not.
and (?6).
densities
therefore 131
simplifies
the error
by a set that
analysis
has this
by replacing
correlation
error
propagation
set of variables
to Eqs.
and (38)
removed. 14
Applying
a correlated
analysis 2
(36)
yields
(39)
where
pi
(kj,j-1
1
+ kj+l,jj2
- 0.5 pi
9
ki,+lJ2
(40)
. (41)
If
the parameter
at the reference
height
z is
temperature,
then
2
( )I K
(sT>2 +
x f p2
T+-
i if
instead
pressure
Xt \
132
is specified,
;
2cg
then
(42)
IV
To test to develop tion
the algebraic insights
procedure
the analysis ventional
SIMULATION PROCEDURE
error
and data
described flow
the simulated
TWO.
(See Figure
In Steps
1.
1 of Part
above,
we extended
The extended
retrievals,
measurements
described
software,
Two.
shown in Figure
Currently
Eq. (1).
reduction
in Part
single-wavelength
into
expressions
the simula-
procedure
follows
1 and 5, which
random errors
and retrievals
are con-
are introduced
as described
In Step 2, R(X3,z)
Two.)
and also
in Part
is computed
from
we are using -1
(44) independent
of height,
are provided dependence [Recall than
directly dependence
and cloud
errors"
in this
step
and the wavelength
models at each height.
backscattering
from size
distribution
such as Eq. (44);
from an assumption,
latitude
between Eq. (44)
aerosol
multiwavelength
The "random
step.
by the differences of the input
that
calculated
in this
for
each aerosol
and refractive
index,
the resulting
of Y can be seen in Figures
submodel
height
2 through
is
rather and
4 of Part
n?o.l
sion
In Step 3 [Eqs.
(2)
are introduced,
just
described model value
in Part for
assumed isopycnic
Two.
p(i)
random errors
and (3)],
in signal
as in the single-wavelength In addition,
to simulate
a random error
an incorrect
and transmis-
simulations is added to the
guess for
density
at the
level.
No random errors
are added in Step 4.
133
In Step 5, care tional nal,
134
density transmission,
profile
is taken
to retain
the same errors
as were used in Step 1, as well
and normalization
errors
for
Al.
in the convenas the same sig-
V
The simulations models,
lidar
signal,
conventional
in Part
Two.
SIMULATION INPUTS
shown in this
parameters,
paper use the same atmospheric
background
molecular
In addition,
lighting,
density,
and error
transmission,
sources
for
and Rmin as used
we have used
b‘u -
= 100%
(45)
Y and
(46)
as measures estimating
of the
an "isopycnic"
obtained
by inspecting
from Eq. (44), of Part
leuncertainty density,
the aerosol (46)
a collection
set of balloon-measured
files.
We recommend that data.
scattering
ratio
so Eq. (46) [Note for
However, profiles
has no effect
the discussion
temperature
profiles, hence their
just
profiles.]
density derived
and cloud
is a very
profiles,
for
before
Eq. (36)
However,
retrieved
and pressure
uncertainties
for
that
retrieved
a proset of
are independent
of F,
uncertainties.
the exception particulate
profiles
are sensitive
plus
a large
or their
A
by
using
profiles
products
obtained
and density
we note
and temperature
was
in Appendix
profiles,
pressure,
be reevaluated
(45)
and in
rms deviation
described
density
the present
on these
and their
rough estimate
temperature,
Eq. (46)
of Eq. (44) Equation
models
of model molecular
small
radiosonde
respectively.
the range of Y values,
Equation
Two.
inspecting
for
in the assumption
to this
case
backscattering
do depend on i,
and
to Eq. (46).
135
VI
Nonvolcanic,
Tropical,
A.
SIMULATED PERFORMANCE
Nighttime; --
Cloud-Free,
Saharan;
Ax a --200 km
Figure
5(a) of Part Two1 has shown the profile of 1.06-urn back. . mixing ratio (Bp/Bg =R1) obtained from a simulated nighttime
scatter retrieval
that
density
combined
profile.
analysis
That retrieval
procedure
pm scattering
the 1.06-pm is
(see Figure
ratio
profile
signal
profile
1 of this
(and its
the
The estimated
2(a).
1.06-urn profile
tion
of a height-independent
dot in Figure
2(a)
Comparison Figure
2(a)
leads
percent
of the estimate
shows that
for
to a systematic
and a systematic errors
a steeper firming
this
distribution lations,
would
tiwavelength
better
with
model in this
by using
steep
require yet,
backscatter
of R(0.355
for
data,
analysis
plus
(solid
in
Eq. (44)
This
suggests
Y that
assumes
backscattering of large
associated This
line)
urn) in the stratosphere
of a representative
measurements.
because
and (27).1
a height-dependent
inspection
to
bar on each
scenario,
one in the troposphere.
careful
(or
the dot,
troposphere.
particulate
ratio
of the assump-
(45)
the model
(27),
is shown in
the error
[See Eqs.
in the lower
dependence
and composition or,
in Y.
underestimation
and a less
Two, because Also,
(l),
proportional
from zero to twice
the aerosol
be reduced
wavelength
is directly
of Part
(dots)
overestimation
could
stratosphere,
error
Eqs.
The result
(dots)
at least
with
of scattering
Y in Eq. (44).
extends
of the assumed flO0
that
5(a)
Step 2 uses the 1.06-
paper).
uncertainty)
profile
in Figure
a conventional
Step 1 of the multiwavelength
a O-355-pm profile (44), and (45) to estimate backscatter mixing ratio) and its uncertainty. Figure
with
in the
However, sets
of size
Mie-scattering set
concalcu-
of mul-
is beyond the scope of the
137
CURRENT
-
5 a
-
10-4
10-2
1
10-a
10-l
10
pA 102
Model
,4 x 10-a
10
,5 x 10-Z 0
6x
10-d
10-2
1
BACKSCAlTER
10-l
102
MIXING
RATIO
COUNTS
AZ- km 4.0
-
103 ps-’
AT 0
-10
K 10
2.0 30 f 25 20 -Model . Retrieved
15 10 5
I
0 I
I
0.90
I
I
I
DENSITY FIGURE
2
I
1 .oo
I
I
1.10
200
(a) Backscatter
280
TEMPERATURE
RATIO
LOW-LATITUDE
240
NIGHTTIME mixing
ratio
SIMULATION profile
inferred
RESULTS, from
1.064~pm
0.355 profile
-
K
pm in Figure
5(a)
of Part Two; (b) Signal and background profiles; (c) Density profile retrieved from (a) and (b), expressed as ratio to model; (d) Temperature profile derived from (c), compared to model.
138
current
study;
quite
moreover,
useful
results
the simple
and also
Step 3 (see Figure ratio
profile
a single file
given
2(c), that
shot
2(a)
in Figure
2(b)]
by Eqs. (2)
the lidar-derived
from a 2 percent pycnic
level
in Figure dots lation
This
the conventional
density
particulate
D(z)
respectively errors
? at 42 km. was in error (because
in retrieved
high-altitude between
2(c)
profile
The error
bars
profile
D(z)
for
for
of lidar
scale
on the right
of Figure
lidar's
excellent
vertical
scenario)
, give
an excellent
Existing
spaceborne
this
heights
the 2 percent it
5 at the
among the simubetween
assumed for
comes in a height
is most strongly
profile Eq. (26)
by -+2 percent
[This
results
in signal
needed to
derived
from the relative
and an estimated
In the case shown, ?! was in error
rapidly
decrease These small
resolution
(0.5
retrieval
nadir-viewing
by +8 K, and
become independent
can be most easily 2(d).]
reference
and --3 percent at 37 and 33 km, measurement errors). However,
signal
and the errors
20 and 8 km.
tropopause
using
temperature
errors,
Notice
(see below).
shows the temperature in Figure
than
errors
This
(35).]
or less
and, moreover,
of density
profile.
and the scatter density
better
profile
retrievals
2(d)
profile
temperature also
density
error
of -1 percent
is considerably
where reduction
Figure
relative
ICY error
is shown in Figure
in the relative
bars
pro-
p at the assumed iso-
through
the uncertainty
the lidar-derived
8 and 20 km.'
improve
and (30)
Both the error
by Eq. (31).
for
[shown for
density
to the right.
guessed
mixing
profile
density
offsetting
(3),
backscatter
result
(model)
provide
method.
signal
The simulated is biased
(2),
and (45)
the lidar-derived
to the exact
only
has a relative
region
the measured
and a partially
contain
show that
the estimated
in the value
Eqs.
[See
2(c)
as given
error
(44)
the analysis
to obtain
profile
(8 km),
same height.
with
and (3).
as a ratio
in Eqs.
demonstrate
1) combines
in Figure
expressed
forms
to between fl
and f2 K
seen in the expanded errors,
km in this
combined with height
of the tropopause
sensors
of these
are unable
region
and
structure.
to perform
such
retrievals.
139
Effects barely
of the tropical
be seen in Figure
the underestimate ever,
these
effects
error.
very
calculated
aerosol ately
layers
Figure
density
5 of Part
surements lated
above.)
density profile
This
backscatter
profile
this
absolute total
2(c)]
errors
in the
are
the error of these
peak.
these for
this
tropospheric
and column backscatter
values.
require
pm retrieval
that
better
in
(because
of the small
small
backscatter measurements,
depth,
Studies
mixing because
to those
in the
significantly
the accuracy
accurate
30 km and 3
effect
optical
thickness
(Simu-
where den-
contributes
degrade
also
below
here are comparable
here can significantly exchange
heights.
to 20 km),
aerosol
region
mea-
is considerably (-8
urn
above 7 km and the
at all
the 0.53
3(b)]
largest
and extinction Hence,
data
stratosphere
region
1.064 and 0.532
can be compared with
were 2 percent
surements
140
layer
from the same signal
[Figure
Despite
is an important
stratospheric/upper
tropospheric
[Figure
density
have their
ratios).
backscatter
stratospheric
aerosol
at 1.06 urn) and immedi-
at
shows that
and lower
errors
mixing
to the
the effects
These results
rms errors
comparison
density
measurement
include
How-
from the sig-
However,
retrievals
profile
below.
density
the upper tr.oposphere
ratios,
of aerosol
but used the conventional
uses the lidar sity
and (39),
Two, which was obtained
conventional
percent
profiles.
can
presence.
3 shows results
conventional
percent)
large
in the Step 1 analysis
the lidar-derived
Figure
(30)
(-1
2(a)].
to distinguish
to extremely
layer
22 and 27 km, where
Sahara and marine
and temperature
(detected
warn of their
using
and so are hard
from Eqs.
aerosol
[see Figure
in magnitude
of the strong
density
between
urn) is greatest
below 7 km, leading
lidar-derived bars,
errors,
stratospheric
especially
are comparable
Effects
obvious
2(c),
in R(0.355
signal-measurement nal
nonvolcanic
to the
and erroneous of derived
mea-
optical
of stratospheric-
measurements
in this
region.
r
E x I ii 2
4
3.
-
20
-
15
-
10
2520 I
15-
,
-
Model Retrieved
5 a
0.532,m
-
10 -
-1.6
5-
-4
0
-6 11111 11111 lllll
IO-4
IO-2
lllll
lllll
1
III&
3 x IO-3 5-x IO-2 7 x IO-’
102
IO-3
BACKSCATTER
AZ -
MIXING
IO-’
10
103
RATIO
km
35
\\\\0.532
um
1
30 25
25
20
20
ii! 2
15
15
5 a
10
E Y I
10 i
5
1
10
100 GBplBp -
FIGURE
3
LOW-LATITUDE USING LIDAR
percent
NIGHTTIME SIMULATION RESULTS, 1.064 DENSITY DATA ABOVE 7 km, CONVENTIONAL
(a,b) Backscatter mixing ratio profiles; (c) Relative backscattering broken down by source.
uncertainty
AND 0.532 pm, DENSITY BELOW in particulate
141
Midlatitude,
B.
Figure as Figure
Volcanic,
4 of this 7 of Part
signal-measurement
However,
Two.
density
assumed isopycnic
of transmission
optical
thickness
5 percent for
errors
aerosol
the conventional
to s'imulate rate
at 8 km, with
above 20 km.
density
lidar
to the conventional
lidar
signal
errors
the normalization error
[Note
the density
sity
offset
between
the dots
to a bias larger
than 2 percent). affect
bars
than that
expected
this
this
4(c)
case,
a more accuby normal-
we have retained
type
the transmission
line.
for
20 and 30 km (where
temperature
in Figure
and the vertical
of about
However,
that
vol-
error
profile),
somewhere between
in which
error
the considerable
have been obtained
and thus are not expected
error,
difference
could
significantly
above the layers
height
and the moderate
leads is
to an
of +2 percent.
through
layers
In this
normalized
increasing
model density
at 8 km to demonstrate
does not
height.
(assumed 3 percent
profile
are less
to 44 km because
error
with
error
profile
density
retrievals that
This
the same scenario
was again
accumulate
seasonal
density
4(c)]
two cloud
for
only
an offset
Because this
izing
offset
that
Ax s --200 km
above that
increases
layer.
use of a local
absolute
results
extend
[Figure
of the upper
stratospheric
Nighttime;
exceed 3 percent
case the offset
because canic
These results
profile
layer
in this
Marine;
paper shows 0.355-urn
errors
case the lidar
Cloudy,
of bias
or
profile errors
occur.
do not include
the den-
to span the difference
They do describe
between each dot and the normalization
well
the rms
dot at 8 km, as
intended.] Figure the lidar
4(d)
shows the temperature
density
perature
profile
was guessed with
profile
obtained
downward from 44 km, where the reference an error
of +8 K.
As in Figure
integrating
downward by -8 km to become independent
temperature
guess and the larger
perature
profile
15 km),
in spite
The reason cally, 142
for
is retrieved
signal-induced
to an accuracy
of the -5 percent this
the reason
was explained is that
by integrating
pressures
density
after
of the reference
density
errors,
the tem-
of 1 to 3 K (between offset
between Eqs. derived
2(d),
tem-
error (38)
32 and
above 20 km.
and (39).
from the lidar
Physi-
density
7P
I (b)
I I
I
‘\\I
7o
\ \
60
\
40
-
Model l-4
30
*lo
20 .2 x 10-2 10
3 x IO-2 5 x IO-’ 8 x IO-’
0 IO-4
IO-2
1
BACKSCATTER
102
MIXING
0 IO-3
IO-’
RATIO
IO
COUNTS
I
I
w
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km
III I-
III
III
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