Since long time, climate modellers use ensemble approaches to calculate the ensemble median and to estimate uncertainties of climate
projections where no ground-truth is known. Following this idea, the ensemble median algorithm EMMA CH4 composes level 2 data of five
GOSAT retrievals developed by NIES, SRON, and the University of Leicester.
EMMA CH4 determines in 10x10 degree grid boxes monthly averages and selects the level 2 data of the median algorithm.

EMMA CH4, University of Bremen
Max Reuter (maximilian.reuter at iup.physik.uni-bremen.de)
Institute of Environmental Physics (IUP)
University of Bremen, FB1
Otto-Hahn-Allee 1
D-28334 Bremen
Germany
Phone: +49 (421) 218 62085
FAX: +49 (421) 218 4555
http://www.iup.uni-bremen.de/~mreuter
WFMD retrieval, University of Bremen
Oliver Schneising (oliver.schneising at iup.physik.uni-bremen.de)
NIES operational retrieval
Yoshida Yukio (yoshida.yukio at nies.go.jp)
NIES PPDF-S retrieval
Andrey Bril (andrey.bril at gmail.com)
RemoTeC full physics (FP) and proxy (PR) retrieval, SRON, KIT
Andre Butz (andre.butz at dlr.de)
Otto Hasekamp (o.p.hasekamp at sron.nl)
UoL full physics (FP) and proxy (PR) retrieval, University of Leicester
Hartmut Bösch (hb100 at leicester.ac.uk)
M. Reuter, H. Bösch, H. Bovensmann, A. Bril, M. Buchwitz, A. Butz, J. P. Burrows, C. W. O'Dell, S. Guerlet, O. Hasekamp, J. Heymann, N. Kikuchi, S. Oshchepkov, R. Parker, S. Pfeifer, O. Schneising, T. Yokota, and Y. Yoshida:
A joint effort to deliver satellite retrieved atmospheric CO2 concentrations for surface flux inversions: the ensemble median algorithm EMMA.
Atmospheric Chemistry and Physics, 13, 1771-1780, 2013
(full text, BibTeX)








v4.1.CH4 (02.07.2019)
Algorithms: SCIAMACHY WFMD v4.0, GOSAT GOSAT NIES v02.75BC, GOSAT PPDF-S v02.xx, GOSAT RemoteC-FP v2.3.8, GOSAT RemoteC-PR v2.3.9, GOSAT UOL-FP v7.2, GOSAT UOL-PR v7.2
Minimum number of algorithms used for median calculation: variable, typically number of algorithms minus two.
Remarks: Based on v3.1 but with new retrieval versions, bug fixes.
v3.1.CH4 (03.09.2018)
Algorithms: SCIAMACHY WFMD v4.0, GOSAT GOSAT NIES v02BC, GOSAT NIES v02.72, GOSAT PPDF-S v02, GOSAT RemoteC-FP v2.3.8, GOSAT RemoteC-PR v2.3.9, GOSAT UOL-FP v7.2, GOSAT UOL-PR v7.2
Minimum number of algorithms used for median calculation: variable, typically number of algorithms minus two.
Remarks: New retrieval versions, algorithm composition now variable in time allowing longer time series, new common a priori (SC4C 2018), re-structured code.
ch4_v1.2 (04.10.2016)
Algorithms: RemoTeC-FP v2.3.8, RemoTeC-PR v2.3.8, UoL-FP v2.0.2, UoL-PR v7.0, NIES v02.21
Minimum number of algorithms used for median calculation: 3 (of 5)
Remarks: Same as v1.1 but with new retrieval versions.
ch4_v1.1 (20.04.2016)
Algorithms: RemoTeC-FP v2.3.7, RemoTeC-PR v2.3.7, UoL-FP v6.0, UoL-PR v6.0, NIES v02.21
Minimum number of algorithms used for median calculation: 3 (of 5)
Remarks: Same as v1.0 but accounting for averaging kernels.
ch4_v1.0 (12.02.2016)
Algorithms: RemoTeC-FP v2.3.7, RemoTeC-PR v2.3.7, UoL-FP v6.0, UoL-PR v6.0, NIES v02.21
Minimum number of algorithms used for median calculation: 3 (of 5)
Remarks: Initial version. Ignoring averaging kernels (no adjustment for a common a priori).
Data Access
After registration, please use the following link to access the data archive:
http://www.iup.uni-bremen.de/~mreuter/emma_data/
Till now, the EMMA CH4 data set covers the period 01/2003-12/2018.
The data-format is NCDF.
Condition of Use
When using EMMA data, you agree ... ... to inform us prior to any publication where EMMA data products are planned to be used, ... to offer us co-authorship for any planned peer-reviewed publication based on EMMA data products (for non peer-reviewed publications it is sufficient if you add an appropriate acknowledgement), ... not to distribute the EMMA data products to any third party (the only exception being colleagues working in your institute, in this case you agree to inform them about the conditions listed here and that they also have to accept these conditions).
EMMA CH4 is in part funded by ESA/ESRIN (GHG CCI-II), EU C3S, and the state and the University of Bremen as well as participating institues and funding organizations. |