Celia Gouveia evaluates drought events with help of vegetation and drought indices.
Length: 32 minutes.
Currently the determination of the ecological, agricultural and environmental impacts of climatic change is considered to be a scientific priority. In the present context of climate change and increasing land degradation and desertification, the evaluation of drought impacts is crucial in determining the environmental consequences of a hypothetical change in climatic conditions.
In the last decade special attention was devoted to the development of new indices particularly suited for drought analyses, quantification and monitoring, namely the ones that are using evapotranspiration data.
On the other hand remote sensing data allows to analyse vegetation activity and to estimate different biophysical parameters such as the area index, the vegetation biomass, the net primary production and photosynthetic activity. Given the spectral properties of vegetation, vegetation indices can be calculated and used to analyse vegetation dynamics and climate impacts, namely to determine the impact of droughts.
Guadalupe Sepulcre presents indicators for drought in Europe.
Length: 45 minutes.
The European Drought Observatory (EDO) (http://edo.jrc.ec.europa.eu) is an initiative of the European Commission’s Joint Research Centre that aims to integrate drought information at European level in a platform accessible to everyone. This information consists mainly in indices based in meteorological and remote sensing data that are produced in near real time.
During this lecture, the different indicators produced operationally at EDO will be firstly introduced. Secondly, a study developed at EDO assessing the LSA-SAF Evapotranspiration (ET) product for drought monitoring in Europe will be detailed. In this analysis, two case studies will be presented; corresponding to the drought episodes of spring/summer 2007 and 2011. For these two cases, the drought indicators previously introduced (Including ET) will be compared and analyzed, considering in the analysis, different drought effects as it is the decrease of the agricultural production.
Finally, the main limitations of the ET as drought indicator will be discussed, as well as the potential for drought assessment and monitoring of other LSA-SAF products like the Land Surface Temperature (LST) and the fraction of Absorbed Photosynthetic Active Radiation (fAPAR).
Nicolas Ghilain presents products of the LSA-SAF.
Length: 45 minutes.
Water resource is a major concern for sustainable development in many semi-arid areas. Early detection of drought and monitoring water consumption by agriculture are highly important for adaptation in water use regional policy. As a crucial component of the water cycle, land evapotranspiration is a primary source of information for such water resources assessments, and remote sensing from geostationary satellites offers the possibility to monitor it over large areas at relatively high temporal and spatial resolutions. The Satellite Application Facility on Land Surface Analysis (LSA-SAF) of EUMETSAT proposes an operational evapotranspiration product based on data from the SEVIRI instrument of the Meteosat Second Generation (MSG). This SESSION will focus on the evapotranspiration process and the role of satellite-based remote sensing to its observation over land. More particularly, the strategy adopted by LSA-SAF to produce the evapotranspiration maps will be unveiled, with an overview of the quality and characteristics of the operational products. At last, some examples of the product utility in drought monitoring will be given.
Natasa Strelec Mahovic reports on the precipitation event in spring 2014 which lead to inundations in SE Europe.
Length: 35 minutes.
From the beginning, spring 2014 was very rainy in large parts of central and south-eastern Europe. The soil was already saturated with water in the beginning of May, when mid-May a huge cyclone, persisting over Bosnia and Herzegovina, Serbia and Croatia for 3 days, caused extreme precipitation. The amounts measured in Serbia and Bosnia and along Sava river in Croatia were in some areas larger than ever measured before. Catastrophic flooding left thousands of people homeless and the consequences will be visible for a long time.
Gernot Zenkl presents the types of meteorological situation that can lead to critical avalanche situations in the eastern Alps.
Length: 45 minutes.
In this presentation one could see a short overview of the interesting and challenging work as an avalanche forecaster. Gernot Zenkl has shown which types of meteorological situation can lead to critical avalanche situations in the eastern Alps. Furthermore he explained the methods we use to inform and warn the people.
Zuhal Akyurek reports on snow reflectance characteristics that have to be considered in snow detection from satellite data.
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.
Ali Nadir Arslan gave an overall introduction of the H SAF products with a focus on snow detection.
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.
Silvia Puca gave an overall introduction of the H SAF products.
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).
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.
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.
Niilo Siljamo reports on H SAF snow detection product H31 that is derived from the SEVIRI instrument on-board MSG.
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.
Ali Nadir Arslan gave an introduction to microwave remote sensing covering radiometry, characteristics, microwave sensors and applications.
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.
Semih Kuter and Burak Simsek introduce the H SAF snow detection products H32 and H35 derived from polar orbiter MetOp.
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).