Transcript Folie 1

Long‐term satellite‐based datasets of atmospheric
water vapour derived within CM SAF
Martin Stengel, Marc Schröder,
Nathalie Courcoux, Karsten Fennig, Rainer Hollmann
Outline
• CM SAF overview
• CM SAF ATOVS datasets (processing, examples, validation)
• CM SAF SSM/I datasets (processing, examples, validation)
• Summary and future activities
Outline
• CM SAF overview
• CM SAF ATOVS datasets (processing, examples, validation)
• CM SAF SSM/I datasets (processing, examples, validation)
• Summary and future activities
CM SAF overview
• EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF)
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CM SAF overview
• CM SAF’s role in climate monitoring and research
CM-SAF
observation datasets
mitigation
adaptation
projection
understanding
climate trends
and variability
processes
modelling
validation /
improvement
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CM SAF overview
• The aim of the Satellite Application Facility on Climate Monitoring is to
generate, archive and distribute widely recognized high-quality satellitederived products and services relevant for climate monitoring.
• CM SAF provides medium- and long-term term cloud, radiation, water
vapour and temperature products derived from different instruments
(Schulz et al., 2009).
• CM SAF water vapour products: ATOVS, SSM/I
• CM SAF data products can be distinguished in operational monitoring
products and retrospectively produced data sets.
CM SAF overview
• Operational monitoring products are disseminated with high timeliness
(max 8 weeks after the obs.) to support operational climate monitoring
applications of national meteorological and hydrological services.
• Because of the timeliness requirement it is not possible to monitor interannual variability and trends. Bias error due to orbit shift and decay, as
well as inter-satellite biases are not corrected for the operational
products.
• For the retrospective produced data sets errors due orbit changes and
inter-satellite biases are minimized.
• In general, CM SAF humidity products have to meet the service
specifications that are defined for each products. The service
specifications compliance is assessed on a regular basis, e.g. by validation
against radiosonde observations of the GCOS Upper Air Network (GUAN).
Outline
• CM SAF overview
• CM SAF ATOVS datasets (processing, examples, validation)
• CM SAF SSM/I datasets (processing, examples, validation)
• Summary and future activities
ATOVS processing
• ATOVS instruments: HIRS/3, AMSU-A/B, MHS, HIRS/4
• CM SAF ATOVS products:
• total columnar water vapour
• layered columnar water vapour
(5 tropospheric layers)
• Time coverage: 01/01/2004 - today
• Spatial resolution: (90 km)²
• Products are available as global daily and monthly means.
• Processing system: The ATOVS level l1d data generated by the ATOVS and
AVHRR Processing Package (AAPP) are used as input for the IAPP (Lee at
al., 2000).
• Output of the Deutscher Wetterdienst Global-Modell (GME) are used as
first guess input to the retrieval.
• A Kriging routine is used to determine daily and monthly means on a
global grid from the swath based retrievals, as well as uncertainties
estimates. (Lindau and Schröder, 2010)
• Advantage: land and sea, day and night, clear-sky and cloudy regions
ATOVS processing
• Layer definitions:
Layer
Pressure [hPa]
1
300-200
2
500-300
3
700-500
4
850-700
5
Surface-850
TCWV
Surface-100
Table: Layer definitions for ATOVS water vapour and temperature products.
• Satellites and AAPP/IAPP versions used:
Product
version
300
300
310
320
320
320
Date
Computer
01.01.04 - 29.02.08
01.03.08 - 31.12.08
01.01.09 - 31.05.09
01.06.09 - 30.11.09
01.12.09 - 31.01.10
01.02.10 - now
DWD COS1
DWD COS1
ECMWF HPCF
ECMWF C1A
ECMWF C1A
ECMWF C1A
AAPP
version
5.3
5.3
5.3
6.10
6.10
6.10
IAPP
version
2.1
2.1
2.1
3.0b
3.0b
3.0b
Satellites used
NOAA-15,-16,-18
NOAA-15,-18
NOAA-15,-18
NOAA-19, MetOp
NOAA-16, -19
NOAA-16, -19, MetOp
Table: Summary of the different versions of the CM SAF ATOVS products with the corresponding
dates, software and hardware updates, as well as the updates in the satellite observations used.
ATOVS example
• Layered vertically integrated water vapour for the 5 layers. Monthly means
for July 2005.
ATOVS example
Extra daily standard deviation kgm -2
Observations per grid
TPW kgm-2
• TCWV, number of observations, extra daily standard deviation
October 2004.
ATOVS validation
• Comparison ATOVS TCWV vs. GUAN radiosondes
Fig: Time series of the bias and bias corrected RMSE
of ATOVS TPW against GUAN radiosondes.
ATOVS validation
• Comparison ATOVS LCWV vs. GUAN radiosondes
Fig: Time series of the bias (left) and bias corrected RMSE (right) of ATOVS LPW 1-5 from
ATOVS and GUAN radiosondes.
ATOVS validation
• Work done in the frame of a federate activity by Claudia Stubenrauch,
LMD
TOVS-B 1987-1995
AIRS-L2 2008/2009
(IAPP)
ocean
AIRS-L2 2003-2009
ATOVS 2008/2009
Open symbols: July
Plain symbols: January
land
Outline
• CM SAF overview
• CM SAF ATOVS datasets (processing, examples, validation)
• CM SAF SSM/I datasets (processing, examples, validation)
• Summary and future activities
CM SAF SSM/I processing
• Transition of HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes
from Satellite data; http://www.hoaps.org/) into CM-SAF
• CM SAF SSM/I product: 20-year Thematic Climate Data Record (TCDR) of
total column integrated water vapour derived from SSM/I
• Satellites used: F08, F10, F11, F13, F14, F15
• Radiance homogenization, reference sensor F11
• Statistical retrieval (Schlüssel, P. and Emery W.J., 1990)
• A Kriging routine is used to determine daily and monthly means on a
global grid from the swath based retrievals, as well as uncertainties
estimates. (Lindau and Schröder, 2010)
• Advantages: day and night, clear-sky and cloudy regions
• Disadvantage: over ocean only
CM SAF SSM/I example
• Example
Fig. EUMETSAT CM SAF SSM/I derived total column water vapour (top) and
associated variability (bottom), averaged over the time series from 1987-2006.
CM SAF SSM/I evaluation
• Evaluation against Wentz (RSS) results
(Sohn and Smith, 2003)
CM SAF SSM/I evaluation
• Evaluation against Wentz (RSS) results:
CM SAF SSM/I evaluation
• Evaluation against ATOVS results
CM SAF SSM/I application
• Comparison to NWP
CM SAF SSM/I application
• Trend analysis
Fig. Trends in total column water vapour over the ice-free ocean
determined from CM SAF SSM/I derived TCWV.
Outline
• CM SAF overview
• CM SAF ATOVS datasets (processing, examples, validation)
• CM SAF SSM/I datasets (processing, examples, validation)
• Summary and future activities
Summary and Outlook
•
CM SAF ATOVS:
• The ATOVS humidity products exhibit high quality (comparisons against
GUAN stations). Comparison against other data sets are also promising.
• Reprocessing from 1998 to now is ongoing work.
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Updated, constant retrieval system
Time period will be extended with 1998 today
Switch from GME to ERA-Interim
SNO to be used for homogenization of L1 radiances
• CM SAF SSM/I:
• Provides a highly accurate dataset enabling long-term monitoring of
TCWV over ocean
• Reprocessing will be done using improved SSM/I FCDR
• Improved satellite sensor calibration and intercalibration
• FCDR is also used in other projects, e.g. ESA DUE GlobVapour
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Possibly 1D-Var system used in the future (retrieval error estimates)*
Extension of time period covered by including SSMIS sensors*
www.cmsaf.eu
Thank you
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Li, J., W. Wolf, W. P. Menzel, W. Zhang, H.-L. Huang, and T. H. Achtor, 2000: Global soundings of the
atmosphere from ATOVS measurements: The algorithm and validation. J. Appl. Meteo., 39, 1248-1268.
Lindau R., M. Schröder, 2010, Algorithm Theoretical Basis Document: Objective analysis (Kriging) for water
vapour. CM SAF ATBD, Ref Nr. SAF/CM/DWD/ATBD/KRIGING, version 1.1, 25 June 2010.
Schulz, J. and P. Albert, H.D. Behr. D. Caprion,, H. Deneke, S. Dewitte, B. Dürr, P. Fuchs, A. Gratzki, P.
Hechler, P. et al., 2009: Operational climate monitoring from space: the EUMETSAT Satellite Application
Facility on Climate Monitoring (CM-SAF), Atmos. Chem. Phys., 9, 1-23.
Schluessel, P. and Emery W.J., 1990: Atmospheric water-vapor over oceans from SSM/I measurements,
International Journal of Remote Sensing 11/5, 753-766.
Sohn, B.J. and E.A. Smith 2003: Explaining sources of discrepancy in SSM/I water vapour algorithms.
Journal of climate, 16, 3229-3255.