Clouds - their height and fraction

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Clouds


their height and
fraction

___________________________________________________________


Author:

Valery P. Andreev,


David B. Cline,


Christina Matthey,


Stan Otwinowski

(Univer
sity California Los Angeles, UCLA)


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August 21, 2002

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CONTENTS


INTRODU
CTION

................................
................................
................................
................................
................................
.........................

3

THE RESULTS
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..............................

3

CLOUD VARIATIONS

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................................
................................
................................
...............

7

DEPENDENCE ON OPTICA
L THICKNE
SS (ALBEDO)

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................................
...................

8

CONCLUSIONS

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..........................

12

ACKNOWLEDGEMENTS

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.......

12
















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Introduction

This note describes a stud
y of clouds distribution and their parameters, namely, height of
the cloud top. This information is of the primary interest for the EUSO simulation and
data analysis. It gives the quantitative answers on the questions of when at the earliest
an air shower

from Extreme Energy Cosmic Ray (EECR) will meet clouds and how often
it will happen,
though on average
.

The study has been performed extracting the information from the data sets of the
International Satellite Cloud Climatology Project (ISCCP).




ISCCP w
as established in 1982 as part of the
World Climate Research Programme

(WCRP) to collect and analyze satellite radiance measurements to infer the global
distribution of clouds, their properties, and

their diurnal, seasonal, and interannual
variations. Data collection began on 1 July 1983 and is planned to continue through 30
June 2002 according to ISCCP.



The organization Web site is the following:
http://isccp.giss.nasa.gov/overStatPg.html
.
More links are provided at that web site to other sources of clouds information.

The results

First of all we are interested in the fractional area covered by clouds. Figure 1 shows
annual mean value for
amount of clouds based on the measurements during 17 years.

Here is the ISCCP definition for the plotted variable:


Cloud Amount

“This variable represents the frequency of occurrence of cloudy conditions in individual
satellite image pixels, each of whic
h covers an area of about 4 to 49 square kilometers.
Comparisons to other measurements confirm that this quantity also represents fractional
areal coverage at one time for the larger 280 km grid cell areas. Clouds are detected by


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their height and fraction







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tests of infrared radiance
s in nighttime and by separate infrared and visible radiance tests
in daytime”.






Figure
1
. Mean annual total cloud amount distribution, latitude versus
longitude
.

Figure 2 shows the mean cloud top temper
ature for the same data.
Cloud top
temperature can be considered as equivalent to cloud top height above mean sea
level
. Here is the ISCCP definition of the plotted variable:

Cloud top temperature

“The satellite measures the infrared radiation emitted by
the cloudy scene, which is
assumed to be covered completely by clouds at one level. If the cloud is optically thick, it
radiates like a blackbody so that the observed emission is equivalent to the actual
temperature at the top (if the upper portion of the
cloud is tenuous, then the radiating
level will be within the cloud). If the cloud is optically thin, then the emission will appear to
be larger than that for the cloud top temperature because additional radiation is
transmitted from the warmer atmosphere
and surface below. The ISCCP parameter has


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their height and fraction







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been corrected for this effect using the measured optical thickness to determine the
transmission (daytime only)”.






Figure
2
. Mean annual cloud top temperature, latitude versus longitud
e.

The global latitude versus longitude distributions of the Figure 1 and Figure 2 give
a general view for the clouds fraction and cloud top temperature. In order to calculate
an average value or to plot the profile histogram (distribution as function of s
ingle
variable) one needs to get an access to the original data sets and extract the desired
information. Fortunately ISCCP provides such an access to the data and kindly the
reading program for those data formats. From the data archives one can download
d
ata sets.

There are several different data sets available. We have used D2 data product

-

Climatological Summary Product. The resolution is 280 km equal
-
area grid, 3 hours,
monthly. There are 6596 equal
-
area boxes in total, each 280 km across. Note the E
USO
FOV spot radius at the Earth is 220 km for the 380 km orbit altitude of the International
Space Station. We have used for the

estimates the data of the year 2001 (it turned out
the data file contains data for only 9 months of that year, January


Septe
mber).



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their height and fraction







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In Figure 3 we plot calculated by us monthly average over all the pixels (equal
-
area
boxes) for the data collected during one three
-
hour interval. We used the data taken at
night (1:30 a.m.


4:30 a.m.) to display the most suitable to the EUSO d
ata taking
conditions data set. As one can see the average cloud top height is between 3 km and 4
km. Unweighted average value is
3.6 km.




Figure
3
. Average monthly height of clouds tops. The data are for the year
2001 from Januar
y to September, nighttime.

In the same way in Figure 4 we plot calculated by us average fraction of clouds. One
can see the amount of clouds is rather stable from one month to another. Unweighted
average value is
66.5 %.

It gives an idea on amount of time

or amount of space when no
clouds are present (33.5 %).




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their height and fraction







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Figure
4
. Fraction of clouds for the year 2001 from January to September,
night
-
time.

Cloud variations

Next point is the variability of cloud parameters. Expressed as dev
iations of monthly averages from
the average over the whole 19 year time record, the ISCCP data show that month
-
to
-
month
variations in globally
-
averaged cloud properties are very small: cloud amounts vary

by
about 1
-
3%
compared to a mean value of 67.5% and

cloud top temperatures vary by about 1
-
4 K compared to
a mean value of 261.5 K.

Regional variations of cloud parameters are much bigger. In Figure 5 we plot the extracted cloud
height distribution as function of latitude. The ISCCP D2 data are provided in

72 latitudinal bands
and 144 longitudinal bands. Figure 5 shows as an example the data for September 2001, again at
nighttime. One can see substantial average height variation with several big fluctuations on top of it.



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Figure
5
. Clouds height as function of latitude in 72 bands from
-
90
degrees (lowest bin) to 90 degrees (highest bin), September 2001, night
-
time.

In the same way in Figure 6 we plot the calculated average fraction of clouds as function
of latitude. The spread is

from 40% to 90%.

Another level of variations is the seasonal variations. Distributions of total cloud amount
and cloud top temperature as function of latitude are shown in Figure 7 and Figure 8,
respectively. One can see big seasonal variations at very
low and very high latitudes.

Dependence on optical thickness (albedo)

We are also interested in the amount of clouds and their height distribution for clouds with
high optical thickness (albedo). Those clouds will affect the EUSO measurements



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their height and fraction







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Figure 6.
Fraction of clouds as function of latitude in 72 bands from
-
90
degrees (lowest bin) to 90 degrees (highest bin), September 2001, night
-
time.




















Figure 7. Seasonal variation
of total cloud amount versus
latitude.





Figur
e 8. Seasonal variation
of cloud top temperature
versus latitude




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their height and fraction







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making a sizeable attenuation of the fluorescence light or reflecting the Cherenkov light
with a

high probability.


We have estimated an average clouds fraction, height and optical thickness (albedo) for
all clouds, for clouds with average albedo greater than 15%, greater than 30% and
greater than 50 %. Those estimates are given in Table 1.




All c
louds

Albedo >15 %

Albedo > 30 %

Albedo > 50 %


Clouds fraction


%




66.5




51.7



36.4



5.0


Clouds height


km



3.6




3.6





3.2




2.4

Optical
thickness

(albedo)




5.3


(


37%)




5.4

††
(


38%)




6.5

††
(


42%)



††
12.3


(


55%)






Table 1. Average cloud fraction, height and optical thickness (albedo) f
or
different cuts on cloud albedo.

The average albedo for all clouds (without any cut) is about 37 %. It should be noticed
that the optical thickness of clouds is given at visible wavelengths (approximately 0.6
microns). Highly attenuating clouds are situa
ted at lower average altitudes. The amount
of clouds with albedo greater than 70 % is less than 1 %.

Figure 9 shows the distribution of clouds height as function of latitude for all clouds (blue
dashed line), for clouds with average albedo greater than 15%

(red dotted line) and
greater than 50 % (black filled histogram). The data are for August 2001 and can be
compared with corresponding distribution for September 2001 (Figure 5). There are
fewer fluctuations in the August data.

Figure 10 shows the distri
bution of cloud fraction as function of latitude for all clouds (blue
dashed line), for clouds with average albedo greater than 15% (red dotted line), for
clouds with average albedo greater than 30% (black solid line) and greater than 50 %
(black filled hi
stogram).



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their height and fraction







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Figure 9. Clouds height (km) versus latitude (
-
90




90

)Ⱐ 䅵gus琠 2001Ⱐ
n楧桴
-
t業攮i 䅬氠 clouds


blue dashed line, clouds with average albedo
greater than 15 %
-

red dotted line, and greater than 50 %
-

black filled
histogram.




Figure 10.

Clou
ds fraction (%) versus latitude (
-
90




90

⤬ Augus琠2001,
n楧桴
-
t業攮i 䅬氠 clouds


blue dashed line, clouds with average albedo
greater than 15 %, red dotted line, greater than 30 %
-

black solid line and
greater than 50%
-

black filled histogram.



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Conclus
ions

There is a pool of atmospheric data available on
-
line or on request. Those data can be
considered as ancillary data to the future EUSO data analysis. Atmospheric data for the

year 2001 were studied in order to extract average cloud top height and tota
l cloud
amount as well as their variations with respect to latitude.

Acknowledgements

We thank Eric Plagnol for providing us with the atmospheric data web site location and
Jim Adams for encouraging us to this study.