VALIDATION OF SCIAMACHY CH4 SCIENTIFIC PRODUCTS USING GROUND-

BASED FTIR MEASUREMENTSB. Dils, M. De Mazière, C. Vigouroux, C. Frankenberg, M.

Buchwitz, A. Gloudemans, T. Blumenstock, F. Hase, I. Kramer, E. Mahieu, P. Demoulin, P. Duchatelet, J.

Mellqvist, A. Strandberg, K. Petersen, J. Notholt, R. Sussmann and T. Borsdorff

Introduction

• Validation using FTIR measurements commenced in ~2004• Since then improvements on the SCIAMACHY algorithms • Also the FTIR comparison dataset has evolved

• Hard to inter-compare results from different validation studies• Re-evaluate ‘all’ SCIAMACHY CH4 algorithms with a ‘standard’ FTIR dataset

Timeline for CH4 validation

2005, Dils et al. ACPD,5: WFMDv0.41 XCH4, IMAPv0.9 XCH4, IMLMv5.5 CH4

Covering 2003 onlyCO2 normalized XCH4 for IMAP and WFMD, total columns for IMLM Channel 6 for IMAP, Channel 8 for WFMD and IMLM

Channel 8 affected by Ice layer build-up and decontamination phasesVery limited datasets (large gaps in annual coverage)

2006, Dils et al. ACP,6: WFMDv0.5 XCH4, IMAPv1.0 XCH4, IMLMv6.3 CH4

Covering 2003 only WFMD, now also using Channel 6

Solar zenith angle (sza) dependence of WFMD dataInverse seasonality of southern hemisphere IMAP XCH4

2007, Dils et al. ACVE-3 proceeding, ESA SP-642: WFMDv1.0 XCH4

2003+2004Overall improvement of data qualitysza issue resolved

2008, Current HYMN validation effort: IMAPv4.9 XCH4, WFMDv1.0/C XCH4

2003+2004+2005Updated CH4 spectroscopy for IMAPv4.9WFMD XCH4 CO2 normalised data using carbon tracker data in stead

of a constant value ( algorithm itself remains the same (v1.0))

The contributing FTIR-NDACC network

Spatial coordinates of the ground-based FTIR stations.

Station Lat N Lon E Alt (m)

NY.ALESUND 78.91 11.88 20

KIRUNA 67.84 20.41 419

HARESTUA 60.22 10.75 580

BREMEN 53.11 8.85 27

ZUGSPITZE 47.42 10.98 2964

JUNGFRAUJOCH 46.55 7.98 3580

IZAÑA 28.30 -16.48 2367

UFTIR, http://www.nilu.no/uftir

Currently a harmonized global FTIR dataset is being developed within the HYMN project! (http://www.knmi.nl/samenw/hymn/)

Validation Issues

• Time of measurement (limited overlap small dataset)• Compared the SCIA data with a 3rd order polynomial fit through the FTIR data or • Compared Monthly averages.• Used Spatial collocation grid around location of gb station

• Large grid = Lat ± 2.5° Lon ± 10°• Small grid = Lat ± 2.5° Lon ± 5°

• Altitude of FTIR station vs ‘altitude’ of SCIA data• Conversion of total column data to effective mean volume mixing ratios (with ECMWF model data)• Assumes constant VMR with altitude! extra vmr correction using TM4 model data

• FTIR airmass vs. SCIA airmass (averaged over pixel)• gets worse with grid! (two grids allows us to assess the impact)

• Retrieval parameters, averaging kernels etc. (minor impact)

Validation Parameters

• Bias: • Weighted bias of the SCIAMACHY measurements with respect to the FTIR polynomial fit

• weighted mean [(SCIA-FTIR)/FTIR]• the corresponding weighted standard error = 3*std/sqrt(N)

Weight = 1/ (error of SCIA data point)2

• Scatter:• Weighted standard deviation around the polynomial FTIR fit, shifted with the bias, acting as the mean.

• R:• Correlation coefficient between SCIAMACHY and FTIR weighted monthly means

•FTIR stations in Europe only, thus limited variability

Evolution of CH4 quality (year 2003 data)

CH4 2003 WFMDv041 WFMDv0.5 WFMDv1.0 WFMDv1.0/C

LG Bias -6.95 ± 0.28 -3.45 ± 0.05 -2.70 ± 0.04 -1.17 ± 0.04

LG scat 8.38 1.75 1.40 1.29

LG R 0.37 0.55 0.65 0.65

LG N 9131 33958 21331 17084

IMAPv0.9 IMAPv1.1 IMAPv4.9

LG Bias 12.6 ± 0.09 -0.87 ± 0.03 -1.015 ± 0.026

LG scat 1.32 1.12 1.04

LG R 0.33 0.58 0.69

LG N 4585 20695 36238

IMLMv5.5 IMLMv6.3

LG Bias -1.88 ± 0.12 -3.00 ± 0.13

LG scat 2.59 3.16

LG R 0.23 0.60

LG N 6248 6433

Evolution of CH4 quality

Evolution of R and scat for all validated versions of SCIAMACHY CH4 algorithms

*IMLM is markedly different from IMAP and WFMD, since it does not include a dry air normalisation step (using CO2 data) and uses a different spectral window: → Needs strict cloud filtering → Less datapoints → More scatter

Now IMLM focuses on CO retrievals, IMAP (Frankenberg) now developed at SRON

Time series seasonal variation

• These plots show the weighted monthly mean and error of the SCIAMACHY data aafo time together with daily mean FTIR data.

• Months that have less than 10 data points are not shown.

Evolution of quality (IMAP,WFMD and IMLM):

*Large improvements for all algorithms*Better seasonality for IMAPv1.1 than IMAPv4.9??? (fig A)

Current status (IMAPv4.9 and WFMDv1.0/Carbon Tracker)

• More scatter in WFMD data• low values for February IMAP?

Current status

• seasonality is not that well captured •Slightly worse for IMAPv4.9?

Conclusions

• Overall, one can state that all SCIAMACHY algorithms have evolved significantly over time. Both the correlation as well as the scatter have improved with each new development. Correlation coefficients of ~0.7 and scatter values of ~1% have been obtained.

• However several issues still remain. The latest IMAP product (v4.9) seems to do a worse job at capturing the seasonality than v1.1

• An in depth validation study, using the latest HYMN harmonised date (http://www.knmi.nl/samenw/hymn) (using a ‘quasi-global’ FTIR dataset), is currently undertaken. This expanded dataset will allow a closer look at station-to-station biases in the SCIAMACHY data.