'SEVIRI Physical Retrieval' products of NWC SAF

Summary and Acknowledgements

The SPhR algorithm combines NWP data with satellite observations in order to provide information on convective environmental parameters: total and layer moisture content and atmospheric instability. These are important parameters when studying the potential for later deep convection, or in predicting the further development of already existing convective clouds.

As the SPhR product is retrieved from geostationary satellite data,

• Its temporal resolution is excellent: 15 or 5 minutes.
• Its spatial resolution is comparable to or better than that of most NWP data. The default resolution is 9 x 9 km, and at best it reaches 3 x 3 km (both resolutions are valid at nadir).
• It can only slightly improve NWP humidity profiles. However, this slight improvement might be useful and sometimes even provides the crucial missing piece of information.
• It can improve the shape of some mesoscale features, such as the exact location of a moisture boundary or local moisture gradient.
• The retrieval is possible only in cloud-free areas. Undetected clouds cause mistakes.

SPhR products could be used to validate NWP fields by checking for shifts of moisture boundaries or significant differences in values of precipitable water and instability indices.

The accuracy of SPhR products depends on the temporal and spatial resolution of the NWP data. Users are advised to use the best available resolution. This product tutorial is based on the 2012 version of the SAFNWC/MSG program package. The version 2013 (which can uses hybrid level NWP data as well) may provide better SPhR products.

The quality of the cloud mask is very important, as undetected clouds cause mistakes in the retrieval. Unfortunately, certain cloud types (e.g. water clouds smaller than pixel size or thin cirrus clouds) are particularly difficult to detect. An improvement in thin cirrus cloud detection is expected in the 2015 version of the SAFNWC/MSG program package. The Meteosat Third Generation (MTG) satellite's imager instrument (FCI) should make cloud detection more reliable. The spatial resolution will increase and there will be a new channel (NIR1.3) intended specifically for improving thin cirrus detection.

The FCI instrument will have another new channel (VIS0.9) as well, which will provide more information on low-level humidity than the current SEVIRI channels.

MTG satellites will even have an infrared sounder instrument (IRS), which will provide more accurate and reliable temperature and humidity profiles with a good temporal resolution.

 

Acknowledgements

This study was supported by the NWCSAF as a Visiting Scientist Activity. We are grateful to Marianne König from EUMETSAT for her valuable comments, and for improving the text of the product tutorial.

 

Appendix

A.1 Definition of the Thomson index

Thomson index = (K-index) - (4-layer best lifted index)

The "best lifted index" or "4-layer lifted index" is a variation of the lifted index. Initially the lifted index is determined for a few levels between the surface and 1600 m. The best (most unstable) lifted index value is then retained. This is helpful when the surface lifted index may misrepresent the actual instability (e.g. morning soundings).

http://www.teachingboxes.org/avc/content/Severe_Weather_Indices.htm

 

A.2 Definition of the Supercell Composite Parameter

This is a multiple-ingredient composite index that includes effective storm-relative helicity (ESRH, Right Supercell Motion by Bunkers et al., 2000), most unstable parcel CAPE (muCAPE), and effective bulk wind difference (EBWD). Each ingredient is normalized to supercell "threshold" values, and larger values of SCP denote greater "overlap" in the three supercell ingredients. Only positive values of SCP are displayed, which correspond to environments favoring right-moving (cyclonic) supercells.

This index is formulated as follows:
SCP = (muCAPE / 1000 J kg^-1) * (ESRH / 50 m² s^-2) * (EBWD / 20 m s^-1)

EBWD is divided by 20 m s^-1 in the range of 10-20 m s^-1. EBWD less than 10 m s^-1 is set to zero, and EBWD greater than 20 m s^-1 is set to one.

 

A.3 Data used to classify the intensity of the convective events analyzed in Section 6

To classify the storms or storm systems according to their intensity, the following data were collected about the mature phases of the convective events:

• Severe storm reports published in the news, or in the European Severe Weather database (ESWD);
• 10-min surface measurements (in Hungary): maximum wind gust and maximum rain amount;
• Radar data covering the Carpathian Basin, measured by the Hungarian radar system: rain rate (calculated from column maximum reflectivity), cloud top height (ETOPS), probability of hail, vertical integrated liquid (VIL) value (the higher the VIL the higher the hail size) and the VIL/ETOPS ratio;
• Minimum brightness temperature in the SEVIRI 10.8 µm channel;
• Radar features where present; e.g. comma echo, bow echo, weak echo region (WER) or bounded weak echo region (BWER) in vertical cross sections;
• Satellite features where present; e.g. long-lived cold rings or ice plumes, and
• Forecasters’ assessment.

 

References and useful links

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