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Aug 23, 2001 - Results show the bias in altitude from multiple .... the potential bias effect from seasonal and interannual ...... Data tape documentation.

POPULAR

SUMMARY

Atmospheric Expected

Ashwin

Multiple Errors

in Antarctic

Mahesh,

Code

James

D. Spinhime,

David

P. Duda,

Edwin

from

location, atmosphere path.

scatter

This adds

such scattering

cloud

size

of the

fraction

bias

even

when

result

from

blowing

atmospheric altimetry

photons, spent

scattering

snow

near

launched

deviating

to quantify

variations

to significant

year-to-year

can

be

limited

reduce

the

number

for the GLAS

height,

that with careful

observations

similar

discusses selection

can be met.

in

the

to-and-fro

of the height biases

cloud

properties

of measurements

paper

the direct estimate

variations

that

laser

from

to a minimum.

in these

to

it is likely

mission

them

layers

the expected

in cloud

variations

This

a biased

of the

of

of the satellite's

Cloud

from

important changes

time

knowledge

them

to keep

An

elevation

travel

elevation.

Year-to-year

the surface.

The

precise

and produces

by

in 2002.

and monitor

surface

of analysis

and demonstrates

specifications

with

It is important

are present,

Sensing

Antarctica.

of

is affected

greatly

no clouds

along

thereby

methods

lead

be

and

in travel,

satellite.

measurements will

Greenland

measurements

depth.

could

but this

Also,

laser

the

will

is to measure

and back,

and to develop

elevation

conditions

over

laser

and optical

cover

Surface

the

and Remote

System

laser system

make

below

magnitude

particle

Altimeter

to the time

of the ice sheet

of

Measurements

in Geoscience

to the earth to

Part Ih Analysis

of Wisconsin-Madison

Trans.

ice sheets

is used

Altimetry.

University

of this space-borne

the satellite

on GLAS

912, GSFC/NASA

Laser

the high-latitude

Altitude

University

to IEEE

Geoscience

objective

The

Code

W. Eloranta,

Effects

912, GSFC/GEST

Hampton

For submission

The

Scattering

effective

as well

in the altitude under that

as in bias.

cloud-free can

be used.

scattering

effects

the likely

biases

and analysis

will from

of data,

Atmospheric Part II: Analysis

Multiple

Scattering

Effects

of Expected

Errors

in Antarctic

Ashwin Goddard

Earth

Sciences

NASA

Goddard

Space

Flight

University

submitted

Trans.

Ashwin

author

address

Mahesh

Mail Code

912

NASA Goddard Space Greenbelt MD 20771

Flight

Email:

@gsfc.nasa.gov

ashwin.mahesh

Center

Greenbelt

MD 20771

Center,

Greenbelt

MD 20771

Hampton

VA 23681

W. Eloranta

in Geoscience August

Corresponding

Center,

of Wisconsin-Madison,

to IEEE

Measurements

P. Duda

University,

Edwin

Altitude

D. Spinhirne

David Hampton

Altimetry.

Mahesh

and Technology

James

on GLAS

2001

Madison

W153706

and Remote

Sensing

ABSTRACT

The altimetry ing from

bias in GLAS

atmospheric

properties

over

multiple

the Antarctic

are presented.

Results

nificant

source

error

free observations, used

here,

affected

in these

in cloud

in the altitude

measurements

snow, also a source altimetry

correction.

to minimize

properties

from

height,

Altimeter

is studied Estimates

selective

analysis

bias. space,

Although over

can be met.

scattering

delay.

With

The

could

may often

careful

in the bias

would clouds

magnitude

size and optical

observations

these

changes

depth

include

selection

depth.

biases

or cloudmethod is

Interannual year-to-

in surface

near-surface

and analysis

be a sig-

of the bias

lead to significant reduce

resultof cloud

such as by the Gaussian

errors.

fraction

cloud-free

Antarctica

pulse

particle

cover

knowledge

in clouds

use of low optical

altitude

effective

to current

and interannual

of the return

the surface

or other laser altimeters

in relationship

from multiple

The

cloud

System)

of seasonal

as well as in cloud

of scattering-induced

specifications

Laser

the bias in altitude

as well as improved

are necessary

year variations vation

show

scattering Plateau.

without

by variations

variations

(Geoscience

ele-

blowing

of data, laser

1. Introduction

With increasing sound

concern

monitoring

also grown.

programs

in the expectation

decades,

A major

especially

aspect

of the Earth's potentially notably

changes

change

of polar

parison

developed lite radar

ments

errors

new methods

on existing

Earth's

polar ice sheets

GLAS

is a laser-based

2002 ments, return

and Antarctica

from

surface

as part of the Earth the mean pulse.

elevation

To permit

temperature

changes

changes

and moni-

in the mass balance

Global

to other

warming

climatic

inter-annual

could

changes,

changes

of continent-wide

methods,

in the

elevation

the ice-sheet

of the ice sheets drawbacks;

radar

have ever been attempted. and will record

which

rely on a com-

and total ice loss - that are each subject mass

balance

by airborne measurements

into snow, and relatively

observations,

of

will be observed

is to measure

regions.

by typical

to measure

measurements

focus

[2].

is limited

each contain

namely

the first estimates

methods

change

(GLAS)

to measure

accumulation

and radar penetration

over Greenland

an improvement

- total snow

stage has

a particular

surface

in turn leading

proposes

ice sheets

mass balance

altimetry

System

in the polar

of these ice sheets,

more accurate

using repeated [4]. These

are concentrated

GLAS

at an early

have been climate

and implement

[1].

Altimeter

and will provide

of ice-sheet

Recently,

slope

which

to develop

changes

of significant

in the high latitudes,

and Greenland

of two large numbers

large errors.

change

climate

signs of global

Antarctic

Laser

in sea level.

ice sheets,

in the Antarctic

The determination

surface

of climate

the mass balance

a possible

thickness

Geoscience

the need

the polar ice shelves

by measurements

in the coastal

large ice sheets

alter

around

surface

large-scale

that the early

bolstered

goal of the orbital

tor a particular

of the earth's potential

ice zones

This view has been

in recent

warming to detect

The marginal

such programs, here.

over

temporal

been

[3] and satel-

are sensitive

few airborne GLAS

lidar

have

to

to

iidar measure-

measurements

will mark

changes

in the thickness

scheduled

to be launched

of the

space.

altimeter

Observing

and atmospheric

System

of the laser's the determination

(EOS)

surface

profiler

program.

For the surface

spot will be estimated

of mass

balance

changes,

altimetry

from a centroid individual

ice-sheet

in

measureof the altitude

measurements mustbemadewith uncertaintiessmallerthan 10cm. A numberof factorsaffect the accuracyof the altitudemeasurement, including surfaceslope,atmosphericpropagationand signalnoise. A cross-overtechniquethataveragestheelevationdifferencesat selectedpointson the icesheetsis designedto reduceerrorsin orderto measureregionaliceelevationchangesto an accuracyof 1.5cm per year,the statedgoal of theice-sheetaltimetry [5].

In PartI of this paper([6] hereafterreferredto asDSE),the authorspresentedcalculationsof path delaysby cloud andaerosolscatteringfrom ananalytic double-scattering modelandMonte Carlo simulationsof lidar surfacereturns. Both methodsdemonstratedthatmultiple scatteringby optically thin polarcloudscould seriouslybiasthealtituderangingof GLAS. Forexample,if the surfaceheightweremeasuredfrom thecentroidof thereturnpulse,a thin arctic stratuscloud with an optical depthof 0.5,a meanparticle radiusof 6 microns, anda thicknessof 3 km would produce ato-and-fropathdelayof 30cm, correspondingto analtitudebiasof 15cm.

Sincethe effectof multiple scatteringis to alwaysintroducea delay,themeanheightchangewill beaffectedby the changesin cloud andaerosollayersin the atmosphere.If not corrected,seasonalandannualvariationin cloud propertiescould significantlyaffectthe determinationof changesin the surfaceheight. Surfacealtimetryis a primaryobjectiveof the GLAS mission,and multiple-scatteringinduceddelayin theobservationshasthe potentialto seriouslyunderminethis goal. Using currentknowledgeof Antarctic cloudproperties,we studytheimpactof multiplescatteringon the determinationof surfacealtitude,aswell ason theinterannualvariability of it. The useof the atmosphericlidar signalsof GLAS to eliminatesucherrorswill alsobediscussed.

2. Variability

The purpose ranging

of ice-sheet

bias would

the critical of cloud

of Cloud

altitude

on the Antarctic

observations

not be a problem

issue is to determine properties.

ple scattering-induced height.

Properties

The variability

DSE found delays,

is to measure

if polar cloud

the potential that several including

Plateau

properties

bias effect cloud

cloud

in each is now considered

depth,

in turn.

changes

were constant

from seasonal

parameters

optical

temporal

over time.

and interannual

can affect cloud

in ice thickness.

particle

the magnitude

Therefore, variability of multi-

size, and mean

cloud

A

2.1. Cloud

Occurrence

Due to the harsh conditions of polar cloud surveys

properties

[7]. Despite

rent knowledge observations

of polar

- which

weather

records

percent)

observations

of clouds

report

cent of the observations. and the coastal

entirely

skies usually

Cloud

occurrence

clouds

over

generally

cycle winter.

regardless

1. The values

fewer

stations

annual

most of the Arctic

higher

during

Greenland occurs

of the time, while of clouds,

Mean

Ocean

to over

80 percent

Antarctic wintertime

ranges

even

stations, cloud

stable

from values

- from with val-

55 and 70

values

however, occurrence

during clouds over

which

in between

10 percent

surface

40 and 60 per-

inversions

as diamond

et aI. find that in winter,

from 65 percent in the Siberian the summer,

the South

cloud

of under

dust.

observations occurrence

of the observations

Arctic.

A similar

and lower

are seen far more

in the inte-

Observations

temperature

Arctic

the

in the Arctic

[8].

known

report

located

sky observations

50 to 70 percent. range

stations

seen

ice cryslals,

Hahn

of observations

with higher

occurrence

by them

(between

the few stations

less than

of near-surface

when

cloud

the

by observ-

70 and 80 percent,

amounts

typically

of clear

is usually

over the poles.

the summer,

over Antarctica,

At coastal

high plateau.

seasonally

between

are from coastal

frequency

of Antarctica

of Arctic

of the sky filled

and smaller

over Antarctica

lead to the formation

varies

values

annual

surface

over

made

cur-

Canada.

occurrences

The mean

variations

Mean

Spitsbergen,

70 to 80 percent

spatial

and

from

summarize

of sky conditions

are typically

and northern

can be made

observations

of the fraction

clear skies are rare at the high latitudes;

clear

western

of clouds

of clouds

between

rior of the continent

Ocean

the world.

than 80% in the area around

Most surface

surface

indicate

cloud

over Greenland

et al., for example,

The observations

routine

Greenland

characteristics

of Hahn

observations

Even the most comprehensive

data from the ice sheets

of polar cloud

around

in Figure

over western

presence

from

the presence

cloud

The surveys

the globe.

stations

Hahn et al. are shown ues greater

across

are summarized

ers at various

estimates

cloudiness.

as well as their remoteness,

than elsewhere.

only sparse

this, some

of clouds

They

and Antarctic,

have been far fewer

such as Hahn et al. contain

Antarctica

poles.

in the Arctic

values

frequently

Pole ranges

from

of is over

seasonal during

the

than over

the

30 to 40 per-

cent,while in the summer,cloudsareobservedin 45 to 70 percentof the observations.On the otherhand,observationsbetween1971and1980atthe coastalSyowaStation(69 S,39 E) showa maximumin the latesummer,whennearly80 percentof observationsareof clouds,andminima in the earlysummer(53%)andwinter (60%) [9]. Hahnet

al. also determined

IAV was defined

the interannual

as the standard

deviation

1991. The interannual

variation

the Arctic

near 5 percent,

(DJF)

was usually

observations.

percent

north

ations

ranged

The most (2001,

in press,

Pole station

throughout

made

at three

much

strained

height

ground

based

obtained

angles

face-based

inversion

kilometers.

The higher

from

1982-

for land stations

in

variations

show

IAV values

the summertime

from 20

the standard

at the Antarctic

coastal

devi-

stations

and

an annual

plateau

spectral

cycle

observations

of cloud

was not specifically had a limited

et al found

with Hahn

is that of Mahesh of clouds

at South

particle

effective

base heights,

designed

et al.

to quantify

cloud

occur-

field of view, and observations

clouds

were

the year to consistently in approximately

et al.'s multi-year

record

43% of their

average.

depth

plateau,

absence

bases

surface-based

of topographical

method

layer,

Ocean

During

longwave

Mahesh

consistent

and optical

The cloud

for the period

occurrence

- 45 °, 60 °, and 75 °- throughout

direction.

roughly

of the CO2-slicing

over the poles.

for December-January-February

over the Antarctic

their spectrometer

by the relative

observations.

of clouds

the year;

of the Antarctic

cloud

over the Arctic

This study

observations,

2.2. Cloud

version

From

zenith

occurrence

10 percent

over Spitsbergen.

occurrences

near 5 percent.

study

in the same viewing

spectral

and was near

thicknesses.

viewing

cloud (JJA)

The interannual

in 1992, the authors

rence

Over

year-long [ 10,11]).

radii and optical

clouds

to 2 percent

Pole are generally

recent

in seasonal

observations

from 2 to 5 percent.

at the South

(IAV) in cloud

in June-July-August

Wintertime

of Alaska

variation

have

to determine a bimodal

and a seasonally

clouds,

visual

estimates

reference the base

points. height

distribution,

of cloud Mahesh

of clouds,

secondary

i.e. most of the clouds

with bases

are con-

et al. use a modified from longwave

with the primary

dependent

height

maximum

maximum between

spectral in the sur-

2.0 and 2.5

in the 2.0 - 2.5 km range

have

smalleroptical depths(lessthan 1),whereascloudswith basesnearthe surfaceareoftenthicker, althoughmanyof thesetoo haveoptical depthsof lessthan2.

Icecrystalprecipitationcanhavea wide rangeof optical depths,but it is commonlymuchthicker duringthe winter.Wilson et between

2.7 and

springtime, optical cally

10.7, although

the observed

depths much

2.3. Cloud particle

crystal

Curry

measured

to 1.9. Mahesh

Nearly

depths

[12]. In the Arctic

et al.'s

findings

over the Antarctic

of the continent. smaller

optical

of cloud

plateau

are opti-

95% of the clouds

at South

than 5.

size

The multiple-scattering the clouds.

from 0.015

depths

of ice crystal

as 21 have been

held view that clouds

at the coasts

seen to have optical

observations

as large

ranged

the generally

than those

were

wintertime

thicknesses

thicknesses

confirmed

thinner

Pole station

al. report

induced

et al. report

distributions

path delays

that the most comprehensive

show modal

gm [8]. Summertime

Arctic

will also depend

radii between

stratus,

on the microphysical

measurements

of wintertime

10 to 80 I.tm, and an average

on the other

hand,

have much

properties

smaller

Arctic

effective mean

of

radius

radii,

ice

of 40

ranging

from 2 to 7 microns.

In the Antarctic,

Smiley

itation

during

observed

smaller

et al. reported the wintertime

than 50 microns

particles

were

could

not reported.

time from

radiometric

composed

of small particle

cloud

particle

winter

sizes using

effective

determined

particle

rately

and only a lower

here indicated

replicator,

are optically

clouds [14].

Lubin

limit to those particle

sizes

particles in winter

Mahesh

could

A particular

ranged

thin and

between

retrieved

summer

a median

than 25 microns

mostly

the winter-

and Harper

that the mean

is given.

crystals

during

[15].

precip-

and smaller

most

1992 data, and obtained larger

However,

clouds

and estimated

radii of particles

ice crystal

of Antarctic

of 4 to 16 microns radiances,

[13].

on their particle

properties

radii from their

the effective

that cloud

of clear-sky

Pole are 12.3 and 5.6 ktm, respectively

effective

study,

observed

infrared

sizes

50 and 200 microns

and estimated

sizes on the order AVHRR

common

measured

cloud

measurements,

of 15 Iam; in their determined,

inferred

radii over the South

cloud

are between

not be reliably

Stone

profile

that the most

and et al.

particle

size

not be accu-

seasonal

pattern

10 and 20 _m,

whereasin summerlargerparticles,with effectiveradii largerthan25_tm,weredominant[10,11].

3. Results

3.1. Altitude

bias

The observations would

summarized

lead to seasonal

bias for a particular climatological

The mean

in Section

and interannual

period,

frequency

altitude

2 indicate variation

the Monte of various

cloud

bias for a given _ B=

Carlo

period

]_i]_jZk

some

in the altitude

path delay

b('l:i,hj,rk)

thickness

is the computed

"1:,cloud

tion as a function fraction,

is defined .b(x

of cloud

or interannual

(year)

to the next:

In this paper, ties reported ('1:), cloud

by Mahesh

made

altitude

from the ground

well as the entire over

using

depths,

Altitude

in 1992. these

be obtained.

the Antarctic

Plateau

altitude by the

hj, rk) cloud

biases

Carlo

equation

and mean

coverage

of cloud

frac-

cloud

heights,

can be examined

calculations

using

observations, from infrared

(1), an altitude

altitude

optical

cover and r k

for sea-

the mean bias from one season

of cloud

radii (r) derived

on cloud

F is the overall

thus obtained

the frequency

Following

cloud.

between

based

is the cloud

hj is the distribution

from Monte

particle

properties,

year can

• F.r('ri,

as the difference

include

effective

the mean

that

hj, rk)

size r, and FT('l:i,hj,rk)

bias estimates

et al.; these

properties

from DSE can be weighted

F.r('l:i,

for each transmissive

sizes.

bias. To estimate

bias for each transmissive

optical

computed

(h) and cloud

for each measurement

conditions

particle

variation,

we obtain

heights

of cloud

cloud

as:

i, hj, rk)-

particle

same variables

1:i is the distribution

sonal

altitude

h, and cloud

of those

is the distribution

ments

height

results

in polar

types.

( 1 - F) + ]_i]_j]_k where

variability

biases

Due to interannual

variability,

that are not identical

with those

optical spectral

properdepths measure-

bias can be computed

over different GLAS from

cloud

seasons

will record

as

cloud

1992; nevertheless

thesedatarepresentthe bestcombinationof severalcloud propertiesrelevantto multiple-scattering induceddelayfrom a singleobservationprogram;also,atthis time Maheshet remain

the only available

Not all clouds the GLAS

will contribute

Carlo

elevation

of the GLAS

not included calculations

dataset

mission,

in any altimetry by DSE show

estimates.

that when

transmissivity

et al. at South

Pole suggest

that this upper

ments

the year.

made during

section.

old of cloud

Figure

optical

2 shows

conditions

depth

bias in Figure

of the measurements, clear-sky further

However,

2a is primarily

expected

it was assumed

in GLAS

that the scattering-induced

by Mahesh

only those

measure-

later in a later

the lower

measurements

thresh-

using

sky

for all observations

(2a)

with little or no scatter-

of clear-sky, scattering

limit

from consideration.

peak of observations

whose

depth

75% of the clouds

as shown

are plotted

due to observations

are from clouds

obtained

by using

of the observations

biases

The large

depths

in such an approach

in 1992; histograms

(2b).

the optical

thin clouds,

to

lidar, the Monte

the use of nearly

optically

According

of less than 0.25

of the GLAS

biases

by

which

effect

comprise

is minimal.

57% For the

bias is zero, this is explored

in a later section.

cloud

obtain

the altitude

and optical cal cloud

Also,

alone

the remainder

observations,

Using

Mahesh

cases

in such cases.

is considered

altitude

numbers

altitude

by the interferometer

as well as for the cloudy ing-induced

greater

will not be penetrated

transmissivity

scattering

limit still permits

altimetry.

the scattering-induced

recorded

forward

clouds

will be made

For the geometry

or through

accurate

eliminates

thick

the plateau.

is as large as 2. The optical

conditions

more

over

with a two-way

Also, one might minimize

cloud-free

This will permit

bias; optically

clouds

to the above

during

properties

measurements

corresponding

observed

of cloud

to the altitude

lidar, and no surface

the specifications would

year-long

al.'s findings

properties

depth. thickness

obtained

by Mahesh

bias that would Consistent

in a few mostly

from radiosonde

calculations

were performed

of cloud

height,

data taken

during

particle

to radius

the year,

a typi-

used in the modeling.

only a lower

winter

Carlo

from each combination

with indications

of 1 km was

et al. determined

result,

et al., Monte

cases

bound

of thick

in particle clouds

radius

only a lower

in a number

of summer-time

limit to the optical

depth

cases. was

determined.The MonteCarlo calculationsusedto obtainthe valuesin Figure2 wererun only for thoseobservationsof clouds(approximatelythree-fourthsof the total numberof cloudsobserved) in which bothparticleradiusandopticaldepthwereknown,i.e.if only a lower limit to eitherparticle sizeor optical depthis availablethosecloudsareomittedin Figure2. Theseomittedvalues, however,areshownin Figure3, andarespecificallyindicatedasthosewith only a lower limit to optical depth(diamonds),thosewith only a lower limit to particle size(opencircles)andthose with only a lower limit to bothparticleradii andopticaldepths(filled circles)known. In these specialcases,it mustbeassumedthatthe altitudebiascorrespondingto scattering-induced delay is at leastaslargeasindicatedin Figure3. The medianvalueof the altitudebiasfor the entire year,from only the cloudobservations,is 10.8cm, andthe meanis 16.2cm. For a givenvalueof the opticaldepth,thebiasin altitudewill changedueto variationsin both particlesizeandin theheightof the cloudabovethe surface. Low cloudsscatterphotonswhich, despitethescatteredpath,still remainwithin the field of view of the instrument. Scatteringby higherclouds,which aremorecommonin the non-wintermonths(October-March),tendsto removethe scatteredpathlengthsfrom the field of view,therebybiasingthe altitude less. With increasingparticleradius,however,a cloud of a given opticaldepthwill biasthe altitude increasingly, until a limiting particlesizeis reachedat which valuethe variationin the forwardscattering peakis small. The winter altitudebiasesin Table3 (discussedin a latersection)aresmallerthan non-wintervalues;this suggeststhatthe effectof particlesizesin the non-wintermonthsis more significantthanthe fact thatin winter,cloudsoccurnearerthe surface.

3.2.

Variability

If the altitude

in altitude

bias.

bias were invariant

surements

as a result

of multiple

determine

interannual

changes

of clouds bias varies

which

cause

as well.

cloud

occurrence

sitive

to changes

delay

from one year to another, scattering

could

in elevation, by multiple

The interannual

as well as the fractional in the specific

be neglected,

could

scattering

variability cloud

microphysical

errors

introduced

since

still be fulfilled.

the objective, However,

are not constant

in bias can result cover.

More

and radiative

into altimetry

mea-

namely

since

to

the properties

from one year to the next, from changes

significantly, properties

in frequencies

the bias values

of clouds

the of

are sen-

from one year to

the next.

We examine

the interannual

stand the impact

of these

from the spectral such clouds. ability

occurrence

reports

to the next,

the averages

considers

whereas

et al. to obtain

in the estimated reported

bias using two different

In the first method,

of Mahesh

by Hahn

that would

changes

approaches

we use cloud

altitude

biases

to under-

properties

that would

obtained

result

from

biases

is then obtained

using

the inter-annual

et al.

In the second

approach,

we obtain

from

during

1992-94,

of the fraction

bias changes

approach

in altitude

variables.

measurements

and the interannual former

different

The variability

in cloud

tine synoptic

variability

of the sky covered

result

that result

from

from

the latter deals with having

variations

having

more

by clouds in the cloud

more (or fewer)

vari-

fractions.

clouds

(or less) of the sky covered

rou-

The

from

one year

by clouds

when

they are present.

3.2.1

Variability

To estimate

from

the uncertainty

consider

the average

plateau.

The average

Hahn et al. is about variation

spectral

clouds

in altimetry

interannual 5 percent,

particle

sizes,

If, on the other

If clouds

during

biases

a given

will be a corresponding record

of variations

must assume bounds

in Table

properties

average

thickness

1 will increase

optical

in bias.

°

other

delay

(or reduced)

We can assume,

10

To assess

the variation

the Antarctic Pole from

the impact

differ

from

a different

from those

seen in

correspondingly.

than those as well.

seen during There

Absent cloud

(or fewer)

seen in the 1992 dataset,

bias using data years

of this

in their optical

year the additional

or decrease

thickness

over

at the South

than those

from one year to another.

of the increased

variability

altitude

during

in the scattering-induced

properties

the winter. know

to the next we may

occurrence

occurrence

If in any given

properties

year are of different

in optical

of the interannual

in the annual

if the cloud

change

the optical

heights.

in their average

computed

cloud

during

observations

in cloud

we must additionally

and the clouds different

hand,

in summer

while it is 11 percent

measurements,

seen are negligibly

1992 the average

one year of GLAS of variability

variation

then we may well see no change year.

from

as well as the extremes

on altimetry

thicknesses,

observations

is, however,

this information,

occurrence,

for instance,

1992, there

to obtain

that any increases

no we the (or

decreases)

in cloud

obtaining clouds

occurrence

the minimum

relate

only to optically

and maximum

variability

with the most and least impact

on altitude

variability

in cloud

occurrence

(5% in summer,

thin (or alternately,

of the bias. biases

thick)

clouds,

By thus removing

(or adding)

from the 1992 data along

11% in winter),

we can obtain

thereby the

with the known

new annual

average

bias values.

The altitude

biases

are tabulated seasonal

in Table

and annual

of thin clouds, variability

average

sion's

specified

A second

altitude

biases

are viewed

to be entirely

in the altitude

are computed

expected,

the seasonal

numbers

to another being

suggest

produces

comparable

able determination of the various

up to three

that the variation

variation

in the altitude

to or greater of altitude

changes

considered

from

in Tables

The interannual

reported

interannual

of the average

for Table optical numbers

the GLAS

occurrence

mission

in the mis-

(1.5 cm).

variability

values,

in

also from Hahn

1, in this case too, the additional depth

regimes,

are shown

and the annual

in Table

in bias are now even mission

2. As one

more different

specification.

and optical

bias that is significant.

than the GLAS changes

these

in cloud

bias.

than the GLAS

of variability

or four times

altitude

of the

the addition

is larger

values

values

Conversely,

of the table)

of the extreme

and annual

the values

the change

instead

again;

increases

seen in 1992

is high;

the maximum

27% in winter)

depths

occurrence

years

As was done in obtaining

from the 1992 numbers,

These

in summer,

using

the average

cloud

bias between

the optical

of thin clouds.

reduces

1992 (last column

from

of thick clouds

the removal

clouds,

can also be made

(13%

clouds

the addition

or reduced

limit for the relative

et al.'s measurements.

would

of thick

bias from

such differences

as does

such increased

altitude

occurrence

average

biases,

or the removal

calculation

(or fewer)

by considering

1. As is expected,

seen from

annual

cloud

obtained

thickness

The values

specification,

from one year

of such variability,

will clearly

impede

the reli-

one year to the next.

Indeed,

the most advantageous

1 and 2 still produces

interannual

bias variations

sizes instead

of or in addition

of 1

to 1.5 cm.

Similar optical

assessments depth

changes.

can also be made with changes The results

in Table

in particle

1 and 2 implicitly

11

assume

that whereas

optical

to depths

from oneyearto anotheraredifferent,the particlesizesandoptical depthsarecomparable betweenthe two years.Thepotentialimpactof changesin thosecharacteristicscannotbe overlooked. However,our intentionhereis to suggestthatvariability in cloud occurrencecanmanifest itself in significantvariationsin the altitudebiasof GLAS measurements from oneyearto another.Withoutquantifyingthe potentialimpactonaltitudebiasfrom everyconceivablechange in cloud characteristics,we haveattemptedto definesomerangeof valuesto suchvariability. This effort showsthatvariationin the altitudebiascouldbe of the samemagnitudeasor larger thanthe accuracyrequirementspecifiedfor the GLAS missionitself. The determinationof surface altitudes,alreadyuncertaindueto thepresenceof clouds,mustadditionallybereconciled with year-to-yearchangesin the uncertaintyin suchmeasurements.

3.2.2.

Variability

In Section

3.2.1,

from

we obtained

cloud

occurrence

result

from variations

absence

synoptic

of clouds,

as likely

in the cloud

the cloud

rence,

The routine

by surface depths,

surface

the ones of Mahesh uniform

topography

heights.

However,

in the altitude

typical

the mere

in the previous

from one year to the next.

basis,

that would

presence

- it is the portion induced

delay

or

of the sky results

sub-section,

cloud

no variability

not

but just

An alternate

bias is to use fractional and to assume

in

approach

cover

informa-

in cloud

occur-

sizes.

and synoptic

South

reports

For this reason,

the multi-year at South

12

visual

cover

heights

knowledge

observations

observations

data, in contrast

of reference

the accurate

the visual

Pole.

cloud

the advantage

this precludes

measurements,

conditions

that contain

and without

Pole station;

the spectral

sky-cover

occurrence

information

we examined

in the altitude

et al., are made visually

unlike

cover

on a regular

observations

around

the variability

The multiple-scattering

which

cloud

bias due to variation

we determine

cloud

additional

by clouds.

variability

observers

Whereas

contains

occurrence,

or particle

line of sight.

that describes

fraction

in fractional

the interannual

optical

particular

in cloud

from changes

tion reported

variability

fractions.

that is filled

variation

to obtaining

the interannual

from one year to the next; in this section

from each observation only from

reports

in the

of cloud

are not limited

provide

to

a useful

to a

dataset

From the WMO

synoptic

as the variability of the years data

in those

1992-94.

values

values,

at South Pole station,

were obtained

The average

was 42% during

ity in these

data taken

the winter

cloud

(as measured

can be computed.

in an average

These

The variations

interannual

numbers

case we have and thick tively,

are considered

3.3.

Methods

The results

tering

from

of cloud-scattering optically

clouds,

of interannual of the plateau

that seasonal/interannual distribution,

across

clouds

at which

extremes

clouds

variabil-

in the winter

obtained in cloud

to variation

in Section fractions

in the interan-

the rest of the year; this results 0.8 cm.

of all optical

depths.

delay

is expected

of all optical

biases

3.2.1 ; this is expected,

the ranging

the altimetry available

since in this

Very (optically)

is least and largest

to be larger

thin

respec-

than when

variations

thicknesses.

cause

using

errors

altimetry

eliminating all clouds,

will be used as a "stand-alone"

properties.

then we could

that the altimetry which

measurements

on cloud

were known,

are chosen

effects

thin clouds,

estimates interior

observation

of observations

and 0.85 cm during

the 1992

bias

are small enough

effects

subsets

across

so far assume

under

correspond

we saw in section

at these

with no information

of the clouds cal depths

of changes

to reduce

fractions

months

around

(11.5%)

from changes

in the bias of approximately

the extremes

to be manifest

cover

as well

Inter-annual

larger

altitude

cover,

and non-winter

months.

is slightly

result

cloud

year period

the other

average

that would

months,

the variability

represent

presented

measurement,

the winter

than the values

distributed

and the average

in cloud

variability

are lower

clouds

or decreases

for the winter

deviation)

the seasonal

of fractional

for the three

and 52% during

Using

increases

nual bias of 0.75 cm during

fraction

by the standard

than in the rest of the year (8.1%). 3.1, the corresponding

separately

cover

months,

values

select

expected

biases,

highly however,

However, those

scattering because

layers.

variability.

Also,

it is the only way of relating

variability

we saw (in the previous

Antarctic

of thin clouds section)

does not match

the opti-

when

our discussions

of climatologies

for

they are the only available

or the Arctic.

that it can provide

13

First,

depths

Multiple-scat-

be smaller

We began

in the absence

data is still useful.

when

are small.

will understandably

cover

from the coastal

instances

from them

the total cloud

to those

if the optical

cloud

statistics

Although

the variability useful

boundaries

from

the

it is possible of the total cloud to variability.

Wenow turn our attentionto subsetsof observations

that include

only optically

cloud-free

and aerosol

profiling

provide

conditions.

The use of data from the cloud

the necessary

obtained

information

from the green

both above

and below

and a substantial

Using

optical

optical

depth

by using

channel

3 shows

ent thresholds few clouds

GLAS

method

set of observations, the seasonal

depth

depths

for such analysis enough

bias could

can

can be

is detectable

is between

to permit

then be reduced

observations.

to analyze

- 0.1, 0.5, at South

Additionally,

the lidar surface

from all the data.

optical

algorithm

I and 2,

such a determina-

by setting

biases

returns.

Both

approach

for example, calculations to Table

and one-third

threshold

to detect

could

a cloud be reduced

approaches

variability

eliminates

a significant

3. The median during

threshold

are

fraction

delays altitude

the other months;

14

from

the bias

shown

bias (0.1)

as small

as 1.5 cm a

cloud-free

observa-

is to use a more fit method

delay.

values

in paper

1

Table 4

this table is readily

with this fit is nearly

the mean

sophisticated

described

from this method;

bias obtained

very

the altitude

threshold

of the scattering-induced

obtained

Since

bias.

altitudes

The Gaussian

differ-

than 2, the bias

is lowered,

or nearly

thresholds.

several

different

in ice thickness

in altitude

using

larger

at the lowest

changes

depth

all observations.

depths

bias to such cloud-free

measurements.

smaller

depth

the bias in estimated

of scattering-induced

from

optical

bias obtained

secular

the GLAS

obtained

set to 2 is not significantly

as the optical

the interannuai

to limiting

have

lower optical

biases

with the numbers

10-15%)

of altitude

using

of the altitude

in altitude

requirements

removes

to analyze

comparable

values

the computation

tions also largely

An alternate

depth

However,

The

the GLAS

Limiting

values

Pole (approximately

correspondingly.

can be selected

1.0 and 2.0 - along

obtained

approach

subsets

and annual

with the cloud

winter,

optical

thin so that a lidar signal

are transmissive

the altitude

for acceptable

obtained

shows

optical

Cloud

on GLAS

below.

Table

(DSE),

are sufficiently

clouds

so determined,

threshold

the entire

year.

data.

channel

or

depth.

depths

From

drops

such selective

The limiting

of Antarctic

a more sophisticated

discussed

if clouds

them [16].

fraction

tion of layer optical

to obtain

thin clouds

40% smaller

are reduced

by even

in

greater

amounts.

than

1.5 cm.

3.4.

Observations

As discussed vations

At very low optical

under

above,

blowing

clouds

nation,

conditions.

of relatively

Throughout are prevalent teau creates made

namely

much

blowing

by the surface

winds,

weather

spectral snow

measurements

year is less

if we selectively

It will be especially

observations

channel

which

on GLAS

downslope

The settling

which

can disturb at South

[17].

exclude

advantageous,

are made

will permit

observation.

obser-

under

known

such a determi-

There

is, however,

Blowing

used in Mahesh

surface

winds

known

as katabatic

of cold air at the higher

elevations

loose

Visual

and recent

Pole station snow

et al. suggest

snow.

indicate

is typically

blowing

depth

of the pla-

observations

snow

not very optically

that an optical

winds

conditions thick,

in

and

of 0.1 is as thick

as the

may be.

The concern

for GLAS,

surface.

Blowing

special

operational

near-surface theless

times

snow

that even if GLAS

is not just the optical

typically

extends

altimetry

physical

a typical

value

and optical

is limited the altitude

(100 microns) thicknesses

data at 50-m

layer

is close

of the GLAS

by such scattering

depth

from the surface

GLAS

a scattering

the footprint

the 532 nm channel,

Using

to process

When

within

caused

however,

mode

layers.

remain

travel

using

over the entire

snow.

observers

up to a third of all observations

depths.

to those

plateau,

of the year.

surface

values

is not used as a stand-alone

of the Antarctic

during these

optical

The use of the atmospheric

concern,

much

large

of altitude

so that the 1064 nm channel

an additional

bias averaged

bias can be held to small

in fact, to limit the determination cloud-free

the altitude

snow conditions

the altitude

that include

depths,

measurement.

to nearly

or entirely

obtained

for the blowing

snow

15

photons

As a result,

in altimetry cloud-free

from them

particle

radius,

50-300

is needed

to the surface

included

for the snow

up to the lowest resolution

becomes

values

of the snow, but its proximity

to detect

these

thin

by it never-

the delay

in their

conditions

This means as determined

be in error.

and several Carlo

and a

scattered

calculations.

might

layer, Monte

meters,

to the

combinations

calculations

of

were per-

formedasbeforeto obtainanestimateof the altitudebiasdueto blowing snow. Figure4 shows the altitudebiasdueto blowing snowfor two differentopticaldepths(filled circlesandsquares)at severaldifferentphysicalthicknessvaluesfor the snowlayer. Also shownarethe lower biasestimatesobtainedwhenthe calculationsarerepeatedwith the Gaussianfit (correspondingopencirclesandsquares)describedin DSE. A blowing snowlayer50-100m thick with anoptical depth between0.05and0.1 will biasthealtitudesderivedby between2 and4 cm approximately;this biascanbeconsiderablyreduced(to between0.5 and1.0cm)by the useof the Gaussianfit methodto determinethe centroidof the returnpulse.

4. Summary

and

Atmospheric

multiple

ments

of surface

other similar cloud

Conclusions

interannual

altitude

space

properties

scattering

as envisioned

missions.

variations.

Using

of such clouds

variability

in altitude

measurements

visual

observers,

in altitude larger itself

However, which

altimetry

are known

Laser

of polar cloud

altitude

study

Altimeter

System

cloud

variation

(GLAS)

seasonal

properties,

The

likely

in the relevant

that the atmospheric

measureor

that most of the

have significant

is quantified.

from year-to-year

laser

indicates

of Antarctic

measurements

suggest

for precision

observations

lidar measurements completed

calculations

from observations

of the mean Antarctic

variability

in cloud

made

at the South

summer

and winter

occurrence

year-to-year

by clouds

than the accuracies is substantial;

a recently

derived

the likely

introduced

error source

and the poten-

inter-annual cloud

scattering

effects

properon

are not insignificant.

properties

the interannual

spaceborne

These

data from DSE, estimates From

a survey

on GLAS

a large

for the Geoscience

bias that will result

ties is also determined.

Using cloud

Also,

that will affect

tial impact

GLAS

is potentially

variation

in the altitude

in the path of the lidar pulse

specified

for the mission.

and a uniform

altitude

measurements

can be confined

to be under

and cloud

cloud-free

bias cannot

or optically

16

estimated

by surface

to be significant,

interannual

variability

conditions;

made

The bias and is often

in the bias

out of observations

observations

thin-cloud

bias were computed.

bias was also obtained.

be subtracted

to those

altitude

fraction

appears

Further,

Pole as well as the path delay

made.

from the satellite

this reduces

the alti-

tudebiasesa greatdeal. To overcomethe limitationsin altimetrymeasurements causedby the biasresultingfrom scatteringwithin cloud layers,ice sheetelevationsshouldthusbe determined only from cloud-freeobservations.This canbe achievedusingthe atmosphericchannelat 532 nm for cloud-detection,alongsidethe 1064nm channel'saltimetrycapability. The useof improvedwaveformanalysistechniques,moresophisticatedthanmerelyacceptedthe centroidof returnpulses,canfurtherreducethe biases. Evenwith the selectiveuseof clear-skyconditionsfor altimetrycalculations,near-surfaceblowing snowwhich occursfrequentlywill remainunaccountedfor. The proximity of the snowto the surfacemakesthis scatteringlayermorepotent(perunit optical depth)thanclouds,sincescattered,delayedphotonsremainwithin the field of view of theinstrument. An altitudebiasof 1-3 cmfrom the snowlayeraloneis likely. However,aswith clouds,the useof improvedmethodsto analyzethereturnpulsewill help in substantiallyreducingthe biasunderblowing snowconditions.

The upcomingGLAS mission,by monitoringice-sheetaltitudechangesover Antarcticaandelsewhere,is expectedto provideinformationon whetherglobalwarmingis affectinga sensitiveand importantpart of theplanet. Potentialmelting of high-latitudeice sheetsfrom warmingwill likely leadto significantrisesin sealevel,andconsequentlyto catastrophicoutcomesalongcoastlinesaroundtheworld andin manyislandnations. This papersuggeststhatthe measurement accuraciesnecessaryto permitthe requiredmonitoringareachievableunderconditionsof thin or no cloud cover. Carefulselectionof datafrom which GLAS altimetrymeasurements aremadeis thereforenecessaryto ensurethatrangingdelaydueto scatteringis accountedor correctedfor.

A factor

that has not been included

bias. The results scattering cult.

of DSE suggest

on the path delay,

In addition, These

factors

other

forms

of return

els.

Further

study

that sloped

and make

other factors

ined.

in this analysis

pulse

analysis

is necessary

surfaces

noise

and surface

to determine

how signal

17

noise,

pulse

roughness

of Gaussian to reduce

slope

the effects

of the return

the effectiveness may be required

of surface

may obscure

the determination

such as signal

may also reduce

is the effect

fitting

altimetry rough,

on the altitude of cloud

centroid have

multiple more diffi-

not been exam-

on the path delay, biases

sloped

to acceptable

surfaces

and

and lev-

advanced

waveform

analysis

of the return

pulse

may affect

the multiple

scattering-induced

alti-

tude bias.

Acknowledgments.

Part of this work 33015

and NAG5-7522.

Department National

was supported

of Energy

by USRA

The total cloud through

its Carbon

contract cover

NAS5-32484,

database

Dioxide

Laboratory.

18

of Hahn

Information

and by NASA

contracts

et al. was provided Analysis

Center

NAG5-

by the U.S.

at Oak Ridge

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vol. 19, pp. 1074-1090,

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W.

List of

Figures

Figure

1. Mean

Figure

2. Histogram

using cloud

annual

(a) includes

delay

under

obtained

observations

separately.

sky observatrions

by Monte

depth

and particle

delay

is calculable,

only a lower

Figure

in DSE.

induced

Carlo

calculations.

radius

are known.

either

because

limit to the particle

depths, The filled

to be zero.

value

obtained

by Monte

panel,

induced

Carlo

during

conditions;

In the lower

of the scattering

[6].

made

as well as cloudy

using

altitude

The pluses In other

effective

calculations,

1992.

The upper

scattering-induced only the cloudy

cases

bias from only the cloudy-

are at an optical obtained

from the Gaussian

radius

all observations

(+) represent

cases,

bias from

both the centroid

circles

bias from

only a lower

altitude

of 0.05; each of these were ues obtained

errors

from

measurements

of both clear-sky is assumed

derived

is 10.8 cm.

4. Scattering-induced

ent optical

altimetry

The median

3. Multiple-scattering

obtained

over the Arctic

from interferometer

clear sky conditions

are considered

Figure

occurrence

of scattering-induced

properties

panel

cloud

data when

only a lower

blowing

of the return depth

(open

snow. pulse,

depth circles),

Results

fit at the two optical

respectively.

21

of the return depths,

both cloud

is known

optical

squares

pulse.

are shown

induced

or both (filled

are shown

1992,

(diamonds),

or

circles).

for two differ-

as well as the Gaussian

of 0.1 and the filled

from the centroid

during

limit to the scattering

limit to the optical is known

of clouds

fit discussed

at an optical

The corresponding

as open circles

depth val-

and squares

Table1: Altitude biasvalues,andchangesin thosevaluesfrom 1992annualandseasonal averages,assumingthat average 11% in the winter)

is contained

More

clouds

year-to-year entirely

than

variation

in either

in 1992

in cloud

thick Fewer

occurrence

('r>2) clouds clouds

than

(5% in the summer,

or in thin (z