Atmospheric Soundings, Surface Properties, Clouds

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Atmospheric Soundings, Surface Properties, Clouds

• The Bologna Lectures
• Paul Menzel
• NOAA/NESDIS/ORA

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Relevant Material in Applications of
Meteorological Satellites CHAPTER 6 - DETECTING
CLOUDS 6.1 RTE in Cloudy Conditions 6-1 6
.2 Inferring Clear Sky Radiances in Cloudy
Conditions 6-2 6.3 Finding Clouds 6-3 CHAPTE
R 7 - SURFACE TEMPERATURE
7.2. Water Vapor Correction for SST
Determinations 7-3 7.3 Accounting for Surface
Emissivity in the Determination of
SST 7-6 7.4 Estimating Fire Size and
Temperature 7-6 CHAPTER 8 - TECHNIQUES FOR
DETERMINING ATMOSPHERIC PARAMETERS 8.1
Total Water Vapor Estimation 8-1 8.3 Cloud
Height and Effective Emissivity
Determination 8-8 8.6 Satellite Measurement of
Atmospheric Stability 8-13
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Earth emitted spectra overlaid on Planck function
envelopes
O3
CO2
H20
CO2
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Profile Retrieval from Sounder Radiances
ps I?
??sfc B?(T(ps)) ??(ps) - ? B?(T(p)) d??(p) /
dp dp .
o I1, I2, I3, .... , In are measured with
the sounder P(sfc) and T(sfc) come from ground
based conventional observations ??(p) are
calculated with physics models First guess
solution is inferred from (1) in situ radiosonde
reports, (2) model prediction, or (3) blending
of (1) and (2) Profile retrieval from
perturbing guess to match measured sounder
radiances
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Sounder Retrieval Products Direct brightness
temperatures Derived in Clear Sky 20 retrieved
temperatures (at mandatory levels) 20
geo-potential heights (at mandatory levels) 11
dewpoint temperatures (at 300 hPa and below) 3
thermal gradient winds (at 700, 500, 400 hPa) 1
total precipitable water vapor 1 surface skin
temperature 2 stability index (lifted index,
CAPE) Derived in Cloudy conditions 3 cloud
parameters (amount, cloud top pressure, and cloud
top temperature) Mandatory Levels (in
hPa) sfc 780 300 70 1000 700 250 50 950
670 200 30 920 500 150 20 850 400 100 10
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Remote Sensing Regions Windows to the atmosphere
(regions of minimal atmospheric absorption) exist
near 4 ?m and 10 ?m these are used for sensing
the temperature of the earth surface and clouds.
CO2 absorption bands at 4.3 ?m and 15 ?m are
used for temperature profile retrieval because
these gases are uniformly mixed in the atmosphere
in known portions they lend themselves to this
application. The water vapor absorption band
near 6.3 ?m is sensitive to the water vapor
concentration in the atmosphere as H20 is not
uniformly mixed in the atmosphere, measurements
in this spectral region are used to infer
moisture distribution in the atmosphere. The
ozone absorption band at 9.7 ?m reveals locations
of O3 concentration in the upper atmosphere.
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GOES Sounder Spectral Bands 14.7 to 3.7 um and
vis
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GOES Imager -- Spectral Coverage
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Comparison of GOES-8 PW with microwave retrievals
GOES Sounder total precipitable water (PW) values
compare well with co-located microwave radiometer
measurements at the CART site (Lamont, OK).
Flat first-guess trace is adjusted by sounder
radiances to capture the trend and range of total
moisture.
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Comparison of GOES-8 PW with microwave retrievals
A scatter plot comparing MWR integrated water
vapor values and GOES-8 first guess/physical
retrieval values at the CART site . RMS and bias
values for all matches are quantified in the
lower right hand corner.
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Interactive Viewing of GOES Sounder DPI Time
Series UW/Madison/CIMSS NOAA/NESDIS/ORA/ARA
D/ASPT
(de-stabilizing with time)
(example from Dec. 2, 1999)
(graph lines thick when sounding available, thin
when cloud obscured)
A new interactive web site (http//cimss.ssec.wisc
.edu/goes/realtime/gdpiviewer.html) allows users
to view time series of GOES derived product
imagery (Lifted Index (LI), Precipitable Water
(PW), and Convective Available Potential Entergy
(CAPE)) by clicking on a desired location within
the latest Derived Product Image (DPI).
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Detecting Clouds (IR) IR Window Brightness
Temperature Threshold and Difference Tests IR
tests sensitive to sfc emissivity and atm PW,
dust, and aerosols BT11 lt 270 BT11 aPW (BT11
- BT12) lt SST BT11 bPW (BT11 - BT8.6) lt SST
aPW and bPW determined from lookup table as a
function of PW BT3.9 - BT11 gt 12 indicates
daytime low cloud cover BT11 - BT12 lt 2 (rel for
scene temp) indicates high cloud BT11 - BT6.7
large neg diff for clr sky over Antarctic Plateau
winter CO2 Channel Test for High Clouds BT13.9
lt threshold (problems at high scan angle or high
terrain)
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Detecting Clouds (vis) Reflectance Threshold
Test r.87 gt 5.5 over ocean indicates cloud r.66
gt 18 over vegetated land indicates cloud Near
IR Thin Cirrus Test r1.38 gt threshold indicates
presence of thin cirrus cloud ambiguity of high
thin versus low thick cloud (resolved with
BT13.9) problems in high terrain Reflectance
Ratio Test r.87/r.66 between 0.9 and 1.1 for
cloudy regions must be ecosystem specific Snow
Test NDSI r.55-r1.6/ r.55r1.6 gt 0.4 and
r.87 gt 0.1 then snow
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1.6 µm image
0.86 µm image
11 µm image
3.9 µm image
cloud mask
Snow test (impacts choice of tests/thresholds)
VIS test (over non-snow covered areas)
11 - 12 BT test (primarily for high cloud)
13.9 µm high cloud test (sensitive in cold
regions)
3.9 - 11 BT test for low clouds
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MODIS cloud mask example (confident clear is
green, probably clear is blue, uncertain is red,
cloud is white)
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AVIRIS Movie 2
AVIRIS Image - Porto Nacional, Brazil 20-Aug-1995
224 Spectral Bands 0.4 - 2.5 mm Pixel 20m x
20m Scene 10km x 10km
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MODIS identifies cloud classes
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Clouds separate into classes when multispectral
radiance information is viewed
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Multispectral data reveals improved information
about ice / water clouds
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Cloud Composition
Contrails
Image Over Kansas - 21 April 1996
Ice Cloud
Infrared Temperature Difference - 8.6 ?m (Band
29) - 11.0 ?m (Band 31)
Contrails
Water Cloud
Infrared Temperature Difference - 11.0 ?m (Band
31) - 12.0 ?m (Band 32)
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Tri-spectral IR thermodynamic phase algorithm

• 8.6-11 vs 11-12
• when slope gt 1 then ice
• when slope lt 1 then water

ice cloud April 1996 Success
water cloud Jan 1993 TOGA/ COARE
Strabala, Menzel, and Ackerman, 1994, JAM, 2,
212-229. Baum et al, 2000, JGR, 105, 11781-11792.
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Water phase clouds with 238K lt Tc lt 253K
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RTE in Cloudy Conditions I? ? Icd (1 - ?)
Ic where cd cloud, c clear, ? cloud
fraction ?
? o Ic B?(Ts) ??(ps) ?
B?(T(p)) d?? . ?
ps
pc Icd (1-e?) B?(Ts) ??(ps)
(1-e?) ? B?(T(p)) d?? ?
ps o e? B?(T(pc)) ??(pc)
? B?(T(p)) d??
pc e? is emittance of cloud.
First two terms are from below cloud, third term
is cloud contribution, and fourth term is from
above cloud. After rearranging pc
dB? I? - I?c ?e? ? ?(p)
dp . ps
dp Techniques for dealing with clouds fall into
three categories (a) searching for cloudless
fields of view, (b) specifying cloud top pressure
and sounding down to cloud level as in the
cloudless case, and (c) employing adjacent fields
of view to determine clear sky signal from partly
cloudy observations.
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Cloud Clearing For a single layer of clouds,
radiances in one spectral band vary linearly with
those of another as cloud amount varies from one
field of view (fov) to another Clear
radiances can be inferred by extrapolating to
cloud free conditions.
clear
RCO2
x
partly cloudy
xx x
x x x
cloudy
x x
N1
N0
RIRW
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Paired field of view proceeds as follows. For a
given wavelength ?, radiances from two spatially
independent, but geographically close, fields of
view are written I?,1 ?1 I?,1cd (1 - ?1)
I?,1c , I?,2 ?2 I?,2 cd (1 - ?2)
I?,2c , If clouds are at uniform altitude,
and clear air radiance is in each FOV I?cd
I?,1cd I?,2 cd I?c I?,1c I?,2c
cd c
c ?1 (I? - I? )
?1 I?,1 - I?
? ,
cd c
c ?2 (I?
- I?) ?2 I?,2 - I? where
? is the ratio of the cloud amounts for the two
geographically independent fields of view of the
sounding radiometer. Therefore, the clear air
radiance from an area possessing broken clouds at
a uniform altitude is given by c
I? I?,1 - ? I?,2 /1 - ? where
? still needs to be determined. Given an
independent measurement of surface temperature,
Ts, and measurements Iw,1 and Iw,2 in a spectral
window channel, then ? can be determined by
? Iw,1 - Bw(Ts) / Iw,2 - Bw(Ts) and
I?c for different spectral channels can be
solved.
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Cloud Properties RTE for cloudy conditions
indicates dependence of cloud forcing (observed
minus clear sky radiance) on cloud amount (???)
and cloud top pressure (pc)
pc (I? - I?clr) ??? ? ?? dB?
. ps Higher colder
cloud or greater cloud amount produces greater
cloud forcing dense low cloud can be confused
for high thin cloud. Two unknowns require two
equations. pc can be inferred from radiance
measurements in two spectral bands where cloud
emissivity is the same. ??? is derived from the
infrared window, once pc is known. This is the
essence of the CO2 slicing technique.
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Moisture Moisture attenuation in atmospheric
windows varies linearly with optical depth.
- k? u ?? e 1 - k?
u For same atmosphere, deviation of brightness
temperature from surface temperature is a linear
function of absorbing power. Thus moisture
corrected SST can inferred by using split window
measurements and extrapolating to zero k? Ts
Tbw1 kw1 / (kw2- kw1) Tbw1 - Tbw2
. Moisture content of atmosphere inferred from
slope of linear relation.
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Early SST algorithms IRW histogram of
occurrence f of observed brightness temperatures
T f(T) fs exp -(T - Tsfc)2/2?2
instrument noise / scene variability ? produce
Gaussian distribution warm side of histogram
reveals Ts T(d2f/dT20) - ? Three point
method combinations of (Ti, fi), (Tj, fj), and
(Tk, fk) on the warm side of the histogram enable
3 equations / 3 unknowns, hence a histogram of Ts
solutions. Least squares method ln (f(T))
ln (fs) - Ts2/2?2 TsT/?2 - T2/2?2 has the
form ln (f(T)) Ao A1T A2T2 , so Ts
- A1/(2A2) .
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Histograms of infrared window brightness
temperature in cloud free and cloud contaminated
conditions
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Water Vapor Correction for SST Determinations
Water vapor correction (?T) Ts Tb ?T
ranges from 0.1 C in cold/dry to 10 K in
warm/moist atmospheres for 11 um IRW
observations. Water vapor correction is
highly dependent on wavelength. Water vapor
correction depends on viewing angle. In IRW
for small water vapor concentrations, ?w
e-Kwu 1 - Kwu so that Ts Tbw1 Kw1 /
(Kw2- Kw1) Tbw1 - Tbw2 . linear
extrapolation to moisture free atmosphere
Regression of clear sky IRW obs and collocated
buoys create current operational algorithm
TsA0A1 Tbw1 A2( Tbw1-Tbw2)A3(Tbw1-Tbw2)2 a
quadratic term helps account for occasional large
water vapor concentrations.
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Cloud Detection Several multispectral methods
have evolved to detect clouds in the area of
interest. Input data are vis, T3.9, T11, and
T12 , T11_at_?30min, and SST guess. General tests
include T11 gt 270 K ocean rarely frozen T11 gt
T12 4 K clouds affect moisture correction vis
lt 4 clouds reflect more than ocean sfc T11 -
T3.9 gt 1.5 K subpixel clouds ? T11 lt 0.3
K ?SST over 1 hr small -2 K lt SST- guess lt 5 K
?SST over days bounded
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Advantages of Geostationary SST Estimates 10
times more observations of a given
location multispectral cloud detection
supplemented by temporal persistence checks
clear sky viewing enhanced by persistence
(e.g. can wait for clouds to move
through) daily composite provides good spatial
coverage can discern diurnal excursions in
SST can track SST motions as estimates of
ocean currents
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GOES daily composite SST reveals small scale
features in oceans
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GOES detects diurnal SST excursions of 2-3 C in
calm waters
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Accounting for surface emissivity When the sea
surface emissivity is less than one, there are
two effects that must be considered (a) the
atmospheric radiation reflects from the surface,
and (b) the surface emission is reduced from that
of a blackbody. The radiative transfer can be
written ps I? ?? B?(Ts)
??(ps) ? B?(T(p))d??(p)
o
ps (1-??) ??(ps) ?
B?(T(p))d??(p)
o where ??(p) represents the transmittance down
from the atmosphere to the surface. This can be
rewritten I? ?? B?(ps)??(ps) B?(TA)1 -
????(ps) - ??(ps)2 ????(ps)2 . Note that as
the atmospheric transmittance approaches unity,
the atmospheric contribution expressed by the
second term becomes zero.
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HIS and GOES radiance observations plotted in
accordance with the radiative transfer equation
including corrections for atmospheric moisture,
non-unit emissivity of the sea surface, and
reflection of the atmospheric radiance from the
sea surface. Radiances are referenced to 880
cm-1. The intercept of the linear relationship
for each data set represents a retrieved surface
skin blackbody radiance from which the SST can be
retrieved.
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Comparison of ocean brightness temperatures
measured by a ship borne interferometer (AERI),
by an interferometer (HIS) on an aircraft at 20
km altitude, and the geostationary sounder
(GOES-8). Corrections for atmospheric absorption
of moisture, non-unit emissivity of the sea
surface, and reflection of the atmospheric
radiance from the sea surface have not been made.
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GOES 3 by 3 FOVs (30 km)
11 micron
MODIS 5 by 5 FOVs (5 km)
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5km resolution MODIS
500hPa T
30km resolution GOES
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MODIS 2000/09/05-08 Daytime 850 hPa Temperature
(K) for 4 days
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NOAA-15 AMSU-A 2000/09/05 Daytime 850 hPa
Temperature (K) for one day
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MODIS
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GOES vs. MODIS 2000/06/30 1600 UTC Total
Precipitable Water (mm)
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GOES vs. MODIS 2000/06/30 1600 UTC Total
Precipitable Water (mm)
MODIS 5 km resolution
TPW
TPW
GOES 30 km resolution
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MODIS total precipitable water vapor shows a wet
bias wrt GOES bias 1.5 mm and rms of 3 mm bias
will be removed after more validation
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MODIS 2000/09/05-08 Daytime Total Precipitable
Water (cm) values over land not shown to
facilitate comparison with AMSU
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NOAA-15 AMSU-A 2000/09/05 Daytime Total
Precipitable Water (mm)
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MODIS TPW Upper panel AMSU TPW Lower panel
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MODIS 5 km resolution
Ozone
Ozone
GOES 30 km resolution
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MODIS ozone is very close to the GOES ozone (over
North America) rms of about 10 Dobsons polar
extreme ozone values will be improved
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MODIS 2000/09/05-08 Daytime Total Ozone (Dobsons)
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Earth Probe TOMS 2000/09/05 Total Ozone (Dobsons)
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TOMS Ozone
MODIS Ozone
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Early Estimates of UW MODIS Product
Quality MODIS IR window radiances agree to
within 1 C with GOES and ER-2 MAS/SHIS Cloud
mask has demonstrated advantages of new
multispectral approach sun glint, desert, and
polar problems diminished MODIS cloud top
pressures compare well with HIRS aircraft
validation is better than 50 mb. MODIS cloud
phase determinations are revealing interesting
patterns first ever global day/night ice/water
cloud determinations validations pending. MODIS
tropospheric temperatures compare well with
AMSU rms better than 1 C, both within 2 C of
radiosonde observations MODIS total precipitable
water vapor shows a wet bias wrt GOES bias 1.5
mm and rms of 3 mm bias will be removed after
more validation. MODIS ozone is very close to
the GOES ozone (over North America) rms of
about 10 Dobsons polar extreme ozone values will
be improved