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CM SAF User Workshop


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New operational Interim Climate Data Records (ICDRs) of radiation and clouds properties

The CM SAF is happy to announce the availability of the new SEVIRI-based Interim Climate Data Record (ICDR) processing
of cloud and radiation properties. The new ICDRs of clouds and radiation are replacing the previous operational products
(EDRs) and are operational continuations of parameters from the Climate Data Records (CDRs) SARAH-2 and CLAAS-2,
respectively. The products currently are provided under the status “pre-operational”.

By using the same algorithms for the generation of the new ICDRs and the corresponding CDRs, the applicability for climate
monitoring is further improved. The following table gives an overview of the products available as part of the new SEVIRI

ICDRParameterTemporal resolutionSpatial resolution
Radiation (based on
SARAH-2 methods)
SIS (Surface Incoming Surface Rad.)
SID (Surface Incoming Direct Rad.)
DNI (Direct Normalized Irradiance)
daily means,
monthly means
0.05° x 0.05°,
for monthly means
diurnal cycles: 0.25°x0.25°
Clouds (based on
CLAAS-2 methods)
CTP (Cloud Top paramters including
CTT (Cloud Top Temperature),
CTH (Cloud Top Height) and
CTP (Cloud Top Pressure)
daily means,
monthly means
monthly mean diurnal
0.05° x 0.05°,
for monthly means
diurnal cycles: 0.25°x0.25°

The new ICDR SEVIRI products are available from beginning of 2018 onwards and will be regularly delivered with a timeliness
of 5 days. The data can be ordered via the CM SAF Web User Interface under the new product group “Interim Climate Data
Records” and are available in NetCDF-4 format.
See the following websites for more details on the new SEVIRI ICDRs:

For both, the Cloud and Radiation SEVIRI ICDR the CM SAF standard package of documentations (Algorithm Theoretical
Baseline Document, Product User Manual and Validation Report) is available.

Example of usage:
As an example of usage, the monthly mean Cloud Fractional Coverage (CFC) and the Surface Incoming Solar Radiation (SIS)
for May 2018 is shown in the figures below.

ICDR SEVIRI Clouds / Radiation ICDR SEVIRI Clouds / RadiationICDR SEVIRI Clouds / Radiation Source: CM SAF

Relative anomalies Radiation / Clouds Relative anomalies Radiation / CloudsRelative anomalies Radiation / Clouds Source: CM SAF

Figure 1: Cloud fraction (top left: Monthly mean, bottom right: relative anomalies) and surface downwelling
shortwave radiation (top left: Monthly mean, bottom right: relative anomalies) for May 2018.

In Europe, compared to the climatological values, May 2018 was dominated by more clouds and less solar radiation in the
northern Mediterranean and by less clouds and more solar radiation in Central and Northern Europe as revealed by Figure 1.
Based on the new SEVIRI ICDRs and their corresponding Climate Data Records, the time series of cloud fraction and solar
radiation for the location Offenbach (Germany) is shown in Figure 2, which reveals that May 2018 was the brightest May
since 2011 in Offenbach.

Time series of SIS Time series of SISTime series of SIS Source: CM SAF

Figure 2: Time series of monthly mean cloud fraction and surface radiation in the vicinity of Offenbach, Germany
for all May months from 2004 through 2018. The CDRs cover the period 2004 to 2017, continued by the ICDR from
2018 onwards.

UP / June 2018

Release of a first aerosol product in CM SAF

The CM SAF is happy to announce the release its Climate Data Record of Aerosol Optical Depth (AOD) derived from the
Spinning Enhance Visible and InfraRed Imager (SEVIRI) sensors onboard the Meteosat Second Generation (MSG)
satellites. This record covers the period from 1 Feb 2004 to 31 Dec 2012 (Meteosat-8 and -9) and consists of daily and
monthly means of AOD.

Aerosols have many impacts on the climate on our planet: direct through the scattering and absorption of radiation, and
also indirectly through the cloud nucleation and precipitation processes. Concerning the direct effect, the most relevant
parameters are the AOD and, to a lesser extent, the single scattering albedo. In the frame of climate monitoring, the
continuous monitoring of those parameters is of prime importance to understand climate variability and change.
Monitoring aerosols is also important as they have in general an adverse effect on the retrieval of many geophysical
parameters relevant for climate as, for instance, the surface albedo.

The Land Daily Aerosol (LDA) algorithm, developed at EUMETSAT, is used to process this CDR of AOD. The
algorithm performs, on a daily basis and at full pixel scale, the inversion of the accumulated solar band observations
(0.6µm, 0.8µm and 1.6µm) to estimate simultaneously the AOD (a single value at reference wavelength of 550nm) and
the 4 Rahman-Pinty-Verstraete (RPV) parameters of the surface in the 3 bands. The algorithm performs therefore an
optimization on 13 unknowns (the AOD + 3 x 4 RPV parameters). In addition, the optimization is also done over a set of
different models of aerosol microphysics (single scattering albedo, phase function).

An example of monthly mean AOD product is shown in Figure 1

Monthly mean of AOD for June 2004 Monthly mean of AOD for June 2004Monthly mean of AOD for June 2004 Source: CM SAF

Along with the data and the uncertainty estimates, a comprehensive documentation including product user manual,
algorithm descriptions, and validation report is provided. The documents and the data record can be accessed from the
DOI landing page:

- Govaerts, Y. M., Wagner, S., Lattanzio, A., & Watts, P. (2010). Joint retrieval of surface reflectance and aerosol
optical depth from MSG/SEVIRI observations with an optimal estimation approach: 1. Theory. Journal of Geophysical
Research: Atmospheres, 115(D2).
- Wagner, S. C., Govaerts, Y. M., & Lattanzio, A. (2010). Joint retrieval of surface reflectance and aerosol optical
depth from MSG/SEVIRI observations with an optimal estimation approach: 2. Implementation and evaluation. Journal
of Geophysical Research: Atmospheres, 115(D2).
NC / Dec 2017

Release of the HOAPS 4 data record

The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite data record (HOAPS) is a completely satellite based
climatology of various flux and atmospheric parameters over the global ice free oceans. A new version (HOAPS 4) has
recently been released by CM SAF. All HOAPS variables are derived from recalibrated and intercalibrated measurements
from SSM/I and SSMIS passive microwave radiometers (Fennig et al., 2017), except for the SST, which is taken from
AVHRR measurements (Reynolds et al, 2007). The data record includes multi-satellite averages and an efficient sea ice
detection procedure. Main changes in this version are a prolonged time series, now containing data for the time period
from July 1987 until December 2014, the utilisation of an updated SSM/I and SSMIS FCDR from CM SAF, the provision
of uncertainty estimates for latent heat flux,evaporation, near surface specific humidity and near surface wind speed (Kinzel
et al., 2017) and the implementation of a 1D-Var retrieval scheme for the retrieval of total column water vapour and near
surface wind speed. Other retrieval algorithms remain unchanged compared to HOAPS 3.2 (Andersson et al., 2010). All
HOAPS products have global coverage, i.e., within ±180° longitude and ±80° latitude and are only defined over the ice-free
ocean surface. The products are available as monthly averages and 6-hourly composites on a regular latitude/longitude grid
with a spatial resolution of 0.5° x 0.5° degrees. Climatological maps are exemplarily shown in Figure 1.

HOAPS 4.0 HOAPS 4.0Figure 1 Source: CM SAF

Climatological maps of evaporation (top left),
precipitation (top right) and freshwater flux (bottom).

The maps show averages over the period 1988-2014.

HOAPS was originally developed at the Max-Planck-Institute for Meteorology (MPI-M) and the University of Hamburg (UHH),
with a first release of the HOAPS 1 in 1998. HOAPS has been successfully transferred into the operational environment at
CM SAF. With the release of HOAPS 3.1 in 2009 the processing is carried out at CM SAF while scientific improvements are
developed jointly at MPI-M, UHH and CM SAF. A subset of the HOAPS parameters is released by CM SAF
via These parameters include:
• precipitation, evaporation, freshwater budget (evaporation minus precipitation), latent heat flux,
• total column water vapour, near surface specific humidity and near surface wind speed.

Along with the data and the uncertainty estimates, a comprehensive documentation including user manual, algorithm
descriptions, reprocessing layout and extensive validation studies, are provided. The documents and the data record can
be accessed from the DOI landing page

The following parameters are accessible following the instructions given at
• Vertically integrated total (liquid and ice) water, surface net longwave radiation, sea surface temperature, sea surface
saturation specific humidity, difference in humidity, latent heat transfer coefficient, sensible heat flux.

Additional information on HOAPS is also available at

Andersson, A., Fennig, K., Klepp, C., Bakan, S., Grassl, H., and Schulz, J.: The Hamburg Ocean Atmosphere Parameters
and Fluxes from Satellite Data - HOAPS-3, Earth System Science Data, 2, 215–234, DOI:10.5194/essd-2-215-2010, 2010.
Fennig, Karsten; Schröder, Marc; Hollmann, Rainer : Fundamental Climate Data Record of Microwave Imager Radiances,
Edition 3. Satellite Application Facility on Climate Monitoring. DOI:10.5676/EUM_SAF_CM/FCDR_MWI/V003, 2017.
Kinzel, J., M. Schröder, K. Fennig, A. Andersson, R. Hollmann: Uncertainty characterization of HOAPS-3.3 latent heat
flux related parameters. Atmos. Meas. Tech. Discuss., DOI:10.5194/amt-2017-176, in review, 2017.
Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K., and Schlax, M. G.: Daily High-Resolution-Blended
Analyses for Sea Surface Temperature, J. Climate, 20, 5473–5496, DOI:10.1175/2007JCLI1824.1, 2007.
MS / Oct 2017


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