Identify and interpret fields and derived products

Description

Giulia Panegrossi presents precipitation products and applications of the Hydrology SAF.

Length: 64 minutes

Content

Within the EUMETSAT Satellite Application Facility on support to Operational Hydrology and Water Management (H-SAF), different precipitation products have been developed. The products exploit either measurements from passive microwave (PMW) radiometers on board polar orbiting satellites, or combination of Meteosat Second Generation (MSG) IR observations with the available PMW precipitation estimates. Some of the products are currently operational (http://hsaf.meteoam.it), and are available for near-real time precipitation monitoring and hydrological applications. Others are being improved and extended to satellites that have become recently operational [i.e., the polar orbiting Core Observatory of the Global Precipitation Measurement mission, (GPM), or the NPP Advanced Technology Microwave Sounder, ATMS)] or that will be operational in the near future (i.e, Meteosat Third Generation. MTG). The H-SAF precipitation products will be presented, focusing on the strengths, weaknesses, and potentials of the current products, and future perspectives offered by the products in development will be outlined.

In this presentation some applications of H-SAF precipitation products will be shown.

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Description

Nuno Moreira reports on a flash flood event on Madeira in 2010.

Length: 36 minutes.

Content

During early morning and morning on 20th February 2010 an extreme and rare flash flood event has occurred in the Portuguese island of Madeira in the North Atlantic, causing 42 casualties, 600 homeless and an estimated loss of around 1000 millions euros. In this presentation, the synoptic environment will be presented and the precipitation producing systems affecting the island will be discussed. The analysis will be mainly performed using satellite imagery from Meteosat 9, both from singles channels and RGB images, as well as from objective estimates of rain and water vapor content. Results from following studies on the precipitation regime of this mountainous island will also be presented.

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Description

Natasa Strelec Mahovic investigates 5 years of flood events in Europe.

Length: 37 minutes.

Content

In the last decade devastating floods occurred in Europe every year taking lives and causing great damages. In this presentation synoptic situations leading to the largest floods affecting Europe in the last 5 years will be analized. The main idea is to pinpoint the similarities and differences in synoptic patterns in order to improve the forecast of such events.

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Description

Joseph Kagenyi talks about forecasting land slides in Africa.

Length: 46 minutes.

Content

The monitoring of weather characteristics over the equatorial and tropical regions is well covered with both polar and geostationary satellites hence the satellite becomes a very important instrument on severe weather monitoring and forecasting. The application of multispectral data of MSG in the monitoring the microphysics of clouds such as deep convective clouds with RGB composites provides in-depth understanding in the identification of regions where extremely active storms are located. The use of Multi sensor Precipitation estimate (MPE) also helps in the estimation total of accumulated rainfall on each region during the storm period. Such areas can easily be monitored and the possibility of excess rainfall within a day can be evaluated and such information is used to issue a warning for evacuation, or for support to the potential victims on these areas.

In short RGB composites, MPE Estimates, and the accumulated rainfall on daily basis becomes effective tools of landslide forecasting. We also add the NWP products particularly the High resolution (7 km) COSMOS data and NCEP CPC data as it gives a forecast with indications of possibly of heavy storms. However with satellite data you are able to ascertain which areas would the forecast show excess impact on the ground. The NWP products are used to help in creating accumulated rainfall values (estimates) necessary in establishing the threshold values for remote areas where station gauge data is not available.

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Description

Zuhal Akyurek reports on snow reflectance characteristics that have to be considered in snow detection from satellite data.

Content

Snow on the ground differs from most of the Earth surfaces by its high reflectance or albedo in the visible and near-infrared wavelengths (0.350 to 1 μm). For longer, the snow’s reflectance decreases significantly. In these wavelengths,snow is even less reflective than certain types of vegetation. Most of the incident radiation in these wavelengths is absorbed in the snowpack. These unique spectral characteristics are used in optical remote sensing to distinguish between snow and other types of surfaces. The numerous validation studies indicate that the satellite snow products have large snow mapping accuracy with respect to ground snow observations for cloud-free conditions, which varies between 69 and 94% in the winter seasons. The main limitation of existing optical platforms operating at a daily timescale is cloud coverage, which significantly reduces the availability of snow cover information.

In this session, algorithms used to retrieve HSAF snow products; snow mask (H31, H34) and effective snow cover area (H32, H35) from opticalsatellite data are presented. The challenges and the opportunities in retrieving snow cover mapsfrom optical data are discussed.

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Description

Ali Nadir Arslan gave an overall introduction of the H SAF products with a focus on snow detection.

Content

The operational goal of H SAF highlights the need to provide products with a reliable measure of their accuracy, so the potential users are made aware of the advantages and drawbacks of the use of the H SAF products in their operational activities. With this aim, within the H SAF, three Validation Groups have been established: one for precipitation, one for soil moisture and one for snow products.

An overview of existing and future satellite-derived snow products will be provided.

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Description

Silvia Puca gave an overall introduction of the H SAF products.

Content

In the first part of the session an introduction to the EUMETSAT HSAF project is made. The EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H SAF) started in 2005 and aims to provide remote sensing estimates of relevant hydrological parameters: instantaneous rain rate and cumulated rainfall, soil moisture at surface and in the root zone, snow cover and water equivalent. The project involves experts from 12 national meteorological and hydrological European Institutes of Austria, Belgium, Bulgaria, Finland, France, Germany, Hungary, Italy, Poland, Romania, Slovakia and Turkey, and from the European Centre for Medium-range Weather Forecast (ECMWF).

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Description

Kenan Bolat reports on H SAF snow detection product H34 that is derived from the SEVIRI instrument on-board MSG H34 differs for flat and mountainous regions.

Content

H34 is a snow mask product, which is retrieved from optical imaging radiometer Spinning Enhanced Visible and Infrared Imager (SEVIRI) mounted aboard the geostationary Meteosat Second Generation (MSG) satellite operated by EUMETSAT. MSG/SEVIRI provides continuous imaging of the earth in 12 spectral channels with a repeat cycle of 15 min. The imaging spatial resolution is 3 km at sub-satellite point and degrades to 5 km over Europe. The snow cover mapping is based on a multi-channel retrieval algorithm. It exploits the high reflectivity of snow in the visible spectrum and the low reflectivity at shorter wavelengths. The snow cover retrieval algorithm differs for flat and mountainous regions. Considering the different characteristics of snow for mountainous and flat areas, two different algorithms are used in producing the snow products for flat and mountainous areas, and then the products are merged to have a single snow product.

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Description

Niilo Siljamo reports on H SAF snow detection product H31 that is derived from the SEVIRI instrument on-board MSG.

Content

In this session, EUMETSAT HSAF snow products H31 and H34 are explained in detail.

H31 is a full disk snow mask product for flatland areas, which is retrieved from optical imaging radiometer Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the geostationary Meteosat Second Generation (MSG) satellites operated by EUMETSAT. MSG/SEVIRI provides continuous imaging of the earth in 12 spectral channels with a repeat cycle of 15 min. The imaging spatial resolution is 3 km in nadir and degrades to 5 km over Europe. The snow cover retrieval algorithm used in the product is based on empirical approach, which takes into account the highly variable nature of the snow-covered surface in satellite resolution. Validation results based on weather station observations(snow depth and the state of the ground observations) are very good.

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Description

Ali Nadir Arslan gave an introduction to microwave remote sensing covering radiometry, characteristics, microwave sensors and applications.

Content

During winter season, snow covers about 40 million km2 in the Northern hemisphere. Snow is a vital water resource in many regions of the world. Climatic changes, Earth’s energy balance, water resources are strongly affected by the presence of snow. Knowledge of the amount of snow water equivalent from year to year is essential to estimate the effects of snow melt run-off. Knowing the snow characteristics helps to improve weather forecasts, to predict water supply for hydropower stations, and to anticipate flooding. Microwave sensors such asradiometers and radars are often used because of their usability under varying conditions, factors like clouds, rain and lack of light do not affect the measurement, the large penetration depth into the surface with increasing wavelength, sensitive to liquid water. Understanding of the relationship between microwave signatures and snow is very important for retrieving desired snowpack parameters such as snow density, snow water equivalent and snow wetness.

In this session, we will present a general introduction to microwave remote sensing covering radiometry, characteristics, microwave sensors and applications. We will also provide information on algorithms used to retrieve HSAF snow products from microwave sensors.

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Description

Semih Kuter and Burak Simsek introduce the H SAF snow detection products H32 and H35 derived from polar orbiter MetOp.

Content

H35 is effective snow cover product, which is retrieved from optical imaging radiometer AVHRR mounted aboard NOAA and MetOP satellites. The third generation of AVHRR, i.e., AVHRR/3, is a multi-spectral scanning radiometer with three solar channels in the VIS/NIR region and three thermal infrared channels. It is currently onboard to NOAA-15, -18, -19 and MetOp-A, -B, -C satellites. The operational H35 is confined to the Northern Hemisphere The fractional snow cover (fSCA) value within a pixel is estimated by using the reflectance data obtained from AVHRR spectral bands. The final fSCA product has ~1 km spatial resolution and it incorporates snow cover fraction percentage from 0 to 100% as well as cloud and water classes. The product for flat/forested regions is generated by Finnish Meteorological Institute (FMI) and the product for mountainous areas is generated by Turkish State Meteorological Service (TSMS). Both products, thereafter, are merged at FMI. A full disk H35 product is an image of 8,999 rows by 35,999 columns(i.e., 324 M pixels approximately).

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Description

Niilo Siljamo reports on H SAF the daily snow mask product H32 that is derived from the AVHRR instrument on-board MetOp satellites.

Content

H32 is a global daily snow mask product, which is retrieved from the Advanced Very-High Resolution Radiometer (AVHRR) onboard the polar orbiting MetOp satellites operated by EUMETSAT. Metop/AVHRR provides daily global coverage on 5 channels. The spatial resolution is 1.1 km in nadir. The snow cover retrieval algorithm used in the product is based on empirical approach which takes into account the highly variable nature of the snowcovered surface in satellite resolution. Validation results based on weather station observations (snow depth and the state of the ground observations) are very good.

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