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THE NOAA SSU STRATOSPHERIC TEMPERATURE CLIMATE DATA RECORD
Cheng-Zhi ZouNOAA/NESDIS/Center For Satellite Applications and Research
Haifeng Qian, Lilong Zhao, Likun Wang
SPARC Temperature Trends Activity Workshop, Victoria, CanadaApril 9-10, 2015
Outline
The SSU Instrument
NOAA SSU Processing History
NOAA SSU CDR Processing Procedure
Uncertainty Analysis
Resolving Stratospheric Temperature Trend Mystery
Conclusion
The SSU Instrument
One of the TOVS instruments (MSU, HIRS, SSU) onboard NOAA TIROS-N polar-orbiting satellite series from 1978-2007
Supplied by UK Met Office
Infrared radiometer using pressure modulation technique to measure atmospheric radiation from CO2 15-mv2 band
Three cells of CO2 gas were placed in the optical path with different pressure which allowed three channels for a single CO2 band
P(peak)~P(cell)/[CO2]1/2,
SSU channel weighting functions determined by cell pressure values
Channel 1 2 3
Peak of WF 15mb 5mb 1.5mb
NOAA SSU Processing History/Summary—1978-2007
Raw SSU data and satellite orbital information were operationally processed at NOAA/NESDIS for each satellite along with other TOVS instruments and saved in operational level-1b files
Operational level-1b files were distributed to world-wide users and archived in NOAA/NCDC Comprehensive Large Array-data Stewardship System (CLASS) ; other centers may also have archives after receiving the data
Level-1c SSU radiances can be calculated from calibration coefficients stored in those level-1b files
UK Met Office conducted instrument testing and developed its version of SSU time series
Technical notes available for NOAA operational processing and UKMO instrument testing, but information for instrument calibration was insufficient and sometimes even missing
NOAA SSU Processing History/Summary– 2008-present
NOAA/NESDIS began to develop SSU temperature time series using level-1c radiances derived from operational level-1b data in 2008
STAR released its first version of SSU time series in 2011 (Wang et al. 2012) and introduced the data to SPARC group
Thompson et al. (2012) documented SSU trend differences between NOAA and Met Office versions and their difference from climate model simulations and called for re-investigation of the SSU problems
The SPARC temperature trend group organized a meeting in 2013 with participation from both NOAA
and Met Office SSU groups to discuss technical issues in SSU processing; instrument space view anomalies were identified to be missing in operational level-1b processing
STAR recalibrated the SSU level-1c radiances using improved information and developed SSU FCDR and its Version 2 SSU temperature time series in 2014 (Zou et al. 2014)
Issues in Unadjusted SSU Dataset
6
Insufficient documentation– lost or no record of many calibration parameters
Bad data from bad calibration (NOAA-7 channel 2)
Space view anomaly—directly affects level-1c radiances
Blackbody target
Gas leaking in the CO2 cell weighting function
variation
atmospheric CO2 variations
limb-effect
diurnal drift effect semi-diurnal tides
Residual biases
Global mean anomaly time series for each satellite for radiances before adjustment and merging
NOAA SSU FCDR and TCDR Processing Flow Chart
SSU recalibrated L1c swath radiances
Adjusted SSU swath radiances (L1d)
Gridded SSU Tb for individual satellites
Merged SSU time series
SSU raw counts data in L1b files
SSU Recalibration: Converting raw counts to radiancesSSU Recalibration: Converting raw counts to radiances
Radiance adjustment including cell pressure, diurnal drift, atmos CO2, limb-effect
Radiance adjustment including cell pressure, diurnal drift, atmos CO2, limb-effect
Binning adjusted swath radiances into grid cellsBinning adjusted swath radiances into grid cells
Inter-satellite bias correction; global mean bias residual used to determine space view anomaly with NOAA-6 as a reference
Inter-satellite bias correction; global mean bias residual used to determine space view anomaly with NOAA-6 as a reference
FCDR
TCDR
Need two processing cycles to complete
Recalibration to Derive Radiance FCDR
Scan and Calibration Cycle
ccec RCCSRR )(
S Slope
cR
I Intercept
ce RSCI
Calibration offset
Space view anomaly
Linear calibration conducted at each earth view position
space view anomalies were estimated using residual inter-satellite biases with known values of NOAA-6 as a reference
Physics of Cell Pressure Changes
9
SSU cell pressure
Weighting function
Measured BT
CO2 cell pressure decreasing -> weighting function peaks higher
-> because of increasing lapse rate, measured Tb increasing
-> warm bias
Cell Pressure from Gas Leaking and Its Correction Time SeriesCell Pressure from Gas Leaking and Its Correction Time Series
10
Cell pressure time series(Data from S.Kobayashi et al. 2009)
CRTM simulated brightness temperature correction time series due to cell pressure changes relative a reference close to pre-launch specification
Causes dramatic effect on time series
First-Guess Adjustment—Simple Constant Bias CorrectionFirst-Guess Adjustment—Simple Constant Bias Correction
11
Global mean time series for individual satellites after constant bias correction
Constant bias correction cannot remove satellite transition jumps
Effect of cell pressure correctionEffect of cell pressure correction
12
Global mean time series for individual satellites after cell pressure correction
Cell pressure correction dramatically removed the satellite transition jumps
Suggests cell pressure correction has good accuracy
Suggests that the NOAA-14 observations just after its start were good data
Channel 2 trend significantly lower than those from constant bias correction (grey lines)
Mismatch betweenNOAA-11 and NOAA-14 will be taken care of by diurnal drift correction
NOAA Version 2 SSU Time Series
Before Adjustment and Merging After Adjustment and Merging
SSU Version 2 Temperature Anomaly Time Series
Uncertainty Analysis on FCDRUncertainty Analysis on FCDR
14
Instrument noise was less than specification (for TIROS-N) -- good for weather application
Noise is averaged out so it does not affect CDR accuracy
Calibration uncertainty due to warm load temperature uncertainty is small
Radiometric noise (Specification, NESS107)
Radiometric noise (Actual, Pick and Brownscombe 1981)
Calibration error due to warm load temperature
Ch1 0.35 0.3 0.05
Ch2 0.70 0.5 0.05Ch3 1.75 0.6 0.05
Error Budget for the SSU FCDR and TCDR
SSU Tb differences from using different warm load temperatures
Uncertainty Analysis on TCDRUncertainty Analysis on TCDR
15
Uncertainty due to space view anomaly included those from adjustment error and those from merging
Adjustment error not known, but expected to be less than 0.1 K due to excellent matching between satellite pairs
Need to be determined in future sensitivity experiments
Matching uncertainty mainly from short overlap between NOAA-9 and NOAA-11, which was estimated to be 1.4×
Error Budget for the SSU FCDR and TCDR
SSU Tb differences from using different warm load temperatures
Adjustment uncertainty (Expected)
Matching Uncertainty from NOAA-9 and NOAA-11
Total Calibration Uncertainty
Uncertainty in global mean trend (K/Dec)
Ch1 0.1 0.1 0.14 0.05
Ch2 0.1 0.13 0.16 0.06
Ch3 0.1 0.17 0.20 0.08
El Chichón
El Chichón
El Chichón
Mt. Pinatubo
Mt. Pinatubo
Mt. Pinatubo
SSU2:-0.76K/dec
Model Mean:-0.77K/dec
SSU1:-0.69K/dec
Model Mean:-0.46K/dec
SSU3(a)
SSU2(b)
SSU1(c)
Fig. 2a Global temperature anomalies time series (K) in the period of 1979-2005 at (a) SSU3 , (b) SSU2, (c) SSU1. Note SSU1~SSU3 represent the SSU observational layers. Blue thick line represents the STAR observation. Grey lines indicate the results from CMIP5 ,Black thick line represents model ensemble mean
El ChichónMt. Pinatubo
SSU1:-0.69K/dec
Model Mean:-0.56K/dec
SSU1(c)
Only high top model
Model Mean:-0.46K/dec
SSU1:-0.69K/dec
all models
SSU1(c)
Some Trend CharacteristicsSome Trend Characteristics
NOAA Version 2 SSU dataset
Plot from Seidel et al. 2011
ConclusionConclusion
• Consistent radiance FCDR was developed through recalibration where space view anomaly was included; dataset ready for application in climate reanalyses and other consistent satellite retrievals
Version 2.0 SSU time series were developed through careful adjustment and merging; adjustment included effects from cell pressure changes, diurnal drift, atmospheric CO2 variation, and viewing angle differences
Structure trend uncertainty were estimated to be 0.05, 0.06, and 0.08 K/Dec for global mean SSU1, SSU2, and SSU3, respectively
Model simulations in CMIP5 ensemble means agree with SSU Version 2.0 within the uncertainty estimates for SSU2 and SSU3; their differences were a little larger for SSU1 but not significant
Recalibration, adjustment, and merging details were well documented in Zou et al. (2014)
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