1 Detection and Determination of Channel Frequency Shift in AMSU-A Observations Cheng-Zhi Zou and Wenhui Wang IGARSS 2011, Vancouver, Canada, July 24-28, 2011 IGARSS 2011, Vancouver, Canada, July 24-28, 2011 NOAA/NESDIS/Center for Satellite Applications and Research Thanks Y. Han and Y. Chen at JCSDA for their CRTM calculation suppo
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1 Detection and Determination of Channel Frequency Shift in AMSU-A Observations Cheng-Zhi Zou and Wenhui Wang IGARSS 2011, Vancouver, Canada, July 24-28,
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Detection and Determination of Channel Frequency Shift in AMSU-A Observations
Cheng-Zhi Zou and Wenhui Wang
IGARSS 2011, Vancouver, Canada, July 24-28, 2011IGARSS 2011, Vancouver, Canada, July 24-28, 2011
NOAA/NESDIS/Center for Satellite Applications and Research
(Thanks Y. Han and Y. Chen at JCSDA for their CRTM calculation support)
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Background
Weighting functions for AMSU-A. All weighting functions are corresponding to nadir or near-nadir observations.
AMSU-A: 1998-present on NOAA-15 through NOAA-19 and MetOp-A, NASA Aqua
AMSU-A observations are being assimilated into NWP models for accurate weather prediction in most weather centers in the world
AMSU-A observations are being assimilated into climate reanalysis systems to constrain model climate
AMSU-A observations are merged with MSU by different research groups to generate atmospheric temperature time series for climate change monitoring
In all these applications, channel frequency values are specified to be
the pre-launch measurements
Bias corrections of unknown error sources are conducted before AMSU-A data are being assimilated into NWP and reanalysis models
This study identify one of these error sources using inter-satellite bias analysis method
AMSU-A Orbit Information
Satellites Launch Date LECT at lunch
NOAA-16
SEPT 2000
1400 Ascending
NOAA-15
MAY 1998
0730 Descending
NOAA-17
JUNE 2002
1000 Descending
NOAA-18
MAY 2005
1400 Ascending
MetOp-A October 2006
0930 Descending
Local Equator Crossing Time of the Descending Orbits of the NOAA and MetOp-A satellites
SNO Datasets
For polar orbiting satellites, SNO events are generally found over the polar region
Use Cao’s (2004) orbital method to find SNO events
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Schematic viewing SNO and its locations
Examples of SNO Inter-Satellite Biases
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Channel 6 of MetOp-A minus NOAA-18 Channel 6 of NOAA-15 minus NOAA-18
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k j
Radiance Error Model for SNO Matchup K and J
kkkkLk ZRRR 0,
jjjjLj ZRRR 0,
SNO Radiance Error Model
jjkkL ZZRRR 0
kj jk RRR 000
j
Remove relative mean inter-satellite biases
Remove non-uniformity in inter-satellite biases
Remove instrument temperature signals
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Effect of Calibration Non-linearity
Channel 6 of MetOp-A minus NOAA-18 Channel 6 of MetOp-A minus NOAA-18
Before Inter-Calibration After SNO Inter-Calibration
Lapse Rate Climatology
Average over the 700S The averaged lapse rate around 350 hPa being steeper in winters (July) than in summers (January).
Time series with winter values being at the negative side of the summer values when the frequency shift is positive (weighting function peaking higher than prelaunch measured), and the other way around for negative frequency shift.
NOAA-15 should have a positive frequency shift
Channel 6 Measurement
NOAA-15 Minus NOAA-18
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Pre-launch Measured Frequencies for AMSU-A Channel 6
Measured Channel Frequency (Specification =54400 for all satellites)
NOAA-15 54399.53
NOAA-16 54399.78
NOAA-18 54400.97
MetOp-A 54400.07
Frequency characteristics for AMSU-A Channel 6 from Mo [1996; 2006; 2007]. Units are in MHz.
Measured frequency differences between different satellites are within 0.5 MHz.
These errors are so small that they wouldn't result in noticeable Tb differences between satellites (0.01K)
Practically, these measured channel frequencies can be considered as the same for different satellites
The shift is a post-launch error Differences for all pairs: 0.5 MHz
Methods to Determine the Actual Channel Frequency Use NOAA Joint Center for Satellite Data Assimilation (JCSDA) Community Radiative Transfer Model (CRTM) to simulate NOAA-15 observations at its SNO sites relative to NOAA-18
Use NASA MERRA reanalysis surface data and atmospheric profiles (temperature, humidity, ozone, cloud liquid water, trace gases etc.) as inputs to the CRTM
MERRA data were interpolated into the N15-N18 SNO sites before being used by CRTM
Select different frequency shift values (df) in the simulation experiments
fm : Measured Channel Frequency Valuedf: Frequency Shift
Experimental Results
Comparisons between simulations and observed N15-N18 SNO data confirms a positive frequency shift in the NOAA-15 channel 6 relative to its measured frequency value Observed SNO time series over
the Antarctic between NOAA-15 and NOAA-18
Simulated Tb (N15, df)
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Determine the Final Channel Frequency Value
Examine Tb’, which is the Tb differences between NOAA-15 and NOAA-18 at their SNO sites when NOAA-15 Tb is adjusted by its simulated frequency shift
We expect the seasonal cycles in Tb’ disappear when df equals to the actual channel frequency shift’
The seasonal cycles can be measured by the amplitude, which should be equal to zero for df=actual channel frequency shift
)18(),15()15(' NTdfNTNTT bsbbb
dfo = 36.25±1.25MHz
fa = fm+ dfo = 54435.73±1.25 MHz
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Impact on SNO Time Series
Channel 6 of NOAA-15 vs NOAA-18Before Frequency adjustment
Channel 6 of NOAA-15 vs NOAA-18After NOAA-15 Frequency adjustment
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Method is developed to detect and determine the post-launch channel frequency shift in AMSU-A observations onboard polar orbiting satellites
NOAA-15 channel-6 frequency shift is determined
Methods are expected to be applicable to other satellites and other channels, but analysis has to be done for each channel, since all channels have different lapse rate climatology
Call for impact experiments on NWP accuracy improvement at JCSDA; if positive, we need to work on more channels
Also call for provisional parameters for future AMSU-type instruments, allowing calculating the frequency shift after launch