Transcript Earth Radiation Budget Observations

Earth Radiation Budget
Observations
Hai-Tien Lee
Arnold Gruber
University of Maryland College Park, CICS/ESSIC-NOAA
Robert G. Ellingson
Florida State University, Dept. of Meteorology
Istvan Laszlo
NOAA/NESDIS
NOAA/NESDIS Cooperative Research Program 3rd Annual Science Symposium
Fort Collins, CO, August 15-16, 2006
Earth Radiation Budget
Kiehl and Trenberth, 1997. Bull. Amer. Meteor. Soc., 78, 197-208.
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History
• First measurements of OLR as early as 1959 from Explorer-7
• Experiments - ERB, ERBE, ScaRaB, CERES, GERB
• First routine measurements of OLR from operational satellites
began in 1974
– NOAA scanning radiometer ( SR)- window channel ( 10-12 microns)
– Linear algorithm between window radiances and total OLR – based on
radiative calculations with model atmospheres
– Evolved a few years later to a non linear algorithm which is still in use
today - adjusted for different spectral interval
• SR data 1974-1978, AVHRR 1979-onward
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AVHRR and HIRS
OLR Algorithms and Products
Tropical AVHRR OLR Anomaly
Time/Longitude plot
1984-2003
[5S-5N]
Contour level 10Wm-2
Pastel yellow are within ±10Wm-2
El Nino
ERBE-AVHRR Daytime OLR July 1985
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Clear-sky OLR Anomaly (Jan 1998)
AVHRR OLR lacks
sensitivity to water
vapor variation,
especially the upper
tropo. humidity
(UTH).
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Multi-spectral HIRS OLR Algorithm
Ellingson et al. (1989)
OLR  a0( )   ai ( ) N i ( )
i
ai=regression coefficients
=local zenith angle
T (zt , z;, )
I (zt ;, )   B (0)T (zt ,0; ,  )   0 B (z)
dz
z

2
1
OLR     I (zt; ,  )ddd


0
N i ( ) 
0


zt

0
i
I (zt , ) f i ( )d
  cos()
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Regression Model
• Channels and spectral intervals – stepwise regression based
on 1600 Phillips soundings and radiation transfer model
HIRS Channel
Wavelength (μm)
Atmos Sensitivity
H7
13.1-13.6
Near Sfc temp
H10
7.8 – 8.5
Lower trop water
vapor
H12
6.6-6.9
Upper trop water
vapor
H3
14.3-14.7
Air temp- at 100mb
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Validation of Multi-spectral OLR Algorithms
Ellingson et al., 1994: Validation of a
Ba et al., 2003: Validation of a
technique for estimating outgoing longwave
radiation from HIRS radiance observations
J. Atmos. Ocean. Technol., 11, 357-365.
technique for estimating OLR with the
GOES sounder. J. Atmos. Ocean. Technol.,
20, 79–89.
HIRS OLR is Operational since 1998.
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HIRS OLR Climate Data Record
Equator Crossing Times for NOAA Polar Orbiters
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AVHRR OLR PC3 and Satellite Observation Time
Pingping Xie, 2006
 PC seems related to changes in satellite observations time
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Inter-satellite Calibration
Collocation:
• 1°x1° lat/lon
• ±30 minutes
Homogeneity filter:
• Std error of mean OLR < 1 Wm-2
Satellites
Bias (Wm-2)
TN
0.15
N06
1.80
N07
2.13
N08
2.03
N09
Reference
N10
0.53
N11
-5.36
N12
-2.42
N14
-5.14
N15
-3.65
N16
-3.25
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OLR Climatological Diurnal Model
OLR a0  a1COS
 ( t  t0)
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2 (t  t 0)
 a2COS
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25 Years of Monthly Mean OLR Local Time Composite
Tsaidam Basin
Western Pacific
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ERBS Non-scanner and HIRS 1985-1999
Tropical 20 NS
HIRS product is as stable
as ERBS-NS.
ERBS NS vs. HIRS
Best-fit line slope = 0.998
STD = 0.97 Wm-2
r = 0.86
Tropical Mean OLR 1984-2003
Relative to HIRS
Tropical 20 NS
ERBE SC
(ERBS)
-2.9±0.1
n=60
CERES
TRMM
-0.1±0.2
n=8
CERES
Terra X
-0.5±0.1
n=56
CERES
Aqua X
-1.0±0.2
n=25
ERBE NS
-4.4±0.1
n=170
HIRS OLR is a reliable and
traceable Transfer Standard
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HIRS-CERES 2000-2004
* CERES
Mean diff
Global avg
= 1.5 Wm-2
RMS diff
Global
= 4.0 Wm-2
ES4 from Terra-Xtrack Ed.2
STD diff
Global
= 2.8 Wm-2
Global RMS Diff = 4.0 Wm-2
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Outlook
Synergy between Operational Polar-Orbiting and
Geostationary Satellite OLR Products
NOAA/MetOp/NPOESS - HIRS, IASI, CrIS, ERBS/CERES
Geostationary
GOES-W
GOES-E
GERB
Met-8/9
FY-2C
GMS
Met-5
MTSAT
The End
Validate HIRS OLR Diurnal Model
using GOES Observations
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6
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Blue: HIRS
Red: GOES
0
Nevada
Nevada
Storm
track
Florida
Gulf of
Mexico
Yucatan
Amazo
n
Sierra
Madre
Occidental
Subtropical Oceans
GOES and GERB
OLR data provide
detailed diurnal
variation information
that we can use it to
construct and examine
the diurnal models.
This figure shows the
phase information of
the OLR diurnal
variation for the
GOES-E full disk
domain with some
typical patterns at
selected sites. The
HIRS-based diurnal
model was compared
against that of the
GOES, which acts as
a reference for error
analysis.
Andes
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