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

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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

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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

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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

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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

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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

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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

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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)