Identify surface features
Alexander Toniazzo discusses the validation of H SAF snow detection products.
Information on snow properties is of critical relevance for a wide range of scientific studies and operational applications, mainly for hydrological purposes. However, ground-based monitoring of snow dynamics is a challenging task, especially over complex topography and under harsh environmental conditions. Remote sensing is a powerful resource providing snow observations at a large scale.
In this session, the validation of the products will be discussed in detail. The presentation will begin with a brief recap on the various snow product types: snow detection, Snow status (D/W), Fractional SC and SWE. Some of these products are over European areas, whereas the new products developed during CDOP3 are global products of full disk satellite products.
Following there will be a short discussion about performances and limitations of each product, based on the Operational Reviews of the last years. Validation of these products requires a great effort due to sparse availability of snow observation, especially, over extra-European areas. Therefore, new validation strategies were developed.
Matias Takala presents practical examples of how to use the H13 product (Snow Water Equivalent) will be presented using Jupyter notebook.
The Snow Water Equivalent (SWE) is a parameter that describes the water content of snow mass. If snow would melt in its place the SWE tells the depth of the resulting water layer. Spaceborne microwave radiometers are well suited for the detection of SWE. Even though the spatialresolution of radiometer data is rather coarse (tens of kilometres) a polar orbiting satellite can cover most of the globe in 24h period. Unlike optical instruments radiometer depends only on natural thermal radiation of objects and doesn’t require illumination from sun. In addition, radiometers are quite insensitive to weather phenomena. The EUMETSAT H SAF SWE products H13 and H65 are described in detail in this presentation. The products are merged products containing Finnish Meteorological Institute (FMI) contribution for flat lands and Turkish State Meteorological Service (TSMS) contribution for mountainous areas. Both products use Helsinki University of Technology (HUT) model as basis for the estimates. The FMI algorithm is a data assimilation algorithm combining ground-based snow depth measurements with spaceborne derived SWE estimates and the TSMS algorithm uses modified HUT model for mountains. The nominal resolution for H13 is 0.25° and for H65 25 km. Product H13 is provided for Europe in so called H-SAF area [25-75°N lat, 25°W-45°E long]. The upcoming product H65 will provided for Northern Hemisphere in EASE2 format. The products are validated against independent SWE snow course measurements.
In thissession, practical examples of how to use the H13 product will be presented using Jupyter notebook.
Francesco Avanzi talks about the evaluation of daily snow cover area (SCA) and snow water equivalent (SWE) data sets derived from SE-E-SEVIRI(H10) and SWE E(H13) respectively.
Increasing satellite technology offers new products for hydrological applications. The validation process is crucial for these products before they are used in operational applications. The validation of satellite data sets can be done through the direct comparison with ground truth data or a reference satellite data. Another, indirect approach consists in using these datasets in models with different complexities and assess the realism of modelled outputs (so called “Hydro Validation”). EUMETSAT H SAF project provides daily snow products on snow recognition, fractionalsnow cover, snow status and snow water equivalent over complex topographies changing from flat land to mountainous areas.
In this second part, daily snow cover area (SCA) and snow water equivalent (SWE) data sets derived from SE-E-SEVIRI(H10) and SWE E(H13), respectively, are evaluated over the mountainous terrain of the Upper Euphrates Basin. First the impact of the snow cover area product is analysed and then hydro validation of both data sets are assessed through conceptual models SRM and HBV. Moreover, since the assimilation of snow products improves snow states of the models, lead time runoff and snow state forecast performance will be presented.
Aynur Sensoy Soman discusses a blending approach to use SE-E-SEVIRI(H10) data together with Sentinel-2 and MODIS into a real-time, operational cryosphere modelling chain.
Increasing satellite technology offers new products for hydrological applications. The validation process is crucial for these products before they are used in operational applications. The validation of satellite data sets can be done through the direct comparison with ground truth data or a reference satellite data. Another, indirect approach consists in using these datasets in models with different complexities and assess the realism of modelled outputs (so called “Hydro Validation”). EUMETSAT H SAF project provides daily snow products on snow recognition, fractionalsnow cover, snow status and snow water equivalent over complex topographies changing from flat land to mountainous areas.
In this this first part, we will discuss a blending approach to use SE-E-SEVIRI(H10) data together with Sentinel 2 and MODIS into a real-time, operational cryosphere modelling chain (S3M-Italy). We will compare open-loop simulations with simulations obtained assimilating H10 data to discuss the added value of this product for real time forecasting.
Overview on the H SAF satellite derived snow products.
Reliable snow cover extent is of vital importance to have a comprehensive understanding for present and future climate, hydrological, and ecological dynamics. Development of methodologies to obtain reliable snow cover information by means of optical and microwave remote sensing (RS) has long been one of the most active research topics of the RS community. Operational snow products namely H10 (Snow detection (snow mask) by VIS/IR radiometry), H11 (dry/wet by MW radiometry), H12 (Effective snow cover by VIS/IR radiometry AVHRR), H13 (Snow Water Equivalent(SWE)by MW radiometry), H31 (Snow detection by VIS/IR radiometry), H32 (Effective snow cover by VIS/IR radiometry AVHRR) have been developed since 2008 within HSAF. Considering different characteristics of snow for mountainous and flat areas, various 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. The development of new snow products is in progress. The presentation will provide an overview of existing and future operational satellite-derived snow products of H SAF portfolio. In the last part of the presentation, there will be a short introduction of quality assessment. After a brief recap of all available operational and pre-operational products, the performances of the products and the new validation strategy using high-resolution satellite data will be discussed, with some interesting case studies of the latter.
Lecture slides (Arslan and Akyurek)...
Overview on the H SAF satellite derived precipitation products.
The EUMETSAT Satellite Application Facility for Operational Hydrology and Water Management (H SAF) provides satellite products and user services in support to Operational Hydrology, Meteorology, Risk Management and Water Management. Since 2005, H SAF science and research bridge into operations through the development and dissemination of soil moisture, precipitation and snow products based on the exploitation of primary EUMETSAT missions. During the fourth Continuous Development and Operations Phase (CDOP-4, from 2022 to 2027), H SAF products will be primarily based on the Meteosat Third Generation (MTG) and the EUMETSAT Polar System -Second Generation (EPS-SG) missions. Current products are based on the use of the full constellation of microwave (MW) radiometers for Level 2 passive microwave (MW) precipitation products and for MW/IR combined products for near-real time applications over the Meteosat Second Generation (MSG) full disk area. The presentation will provide a full overview of the current status and future development of the operational precipitation product portfolio as well as the product quality assessment strategy and results. Examples of applications for specific case studies will be also presented.
Lecture slides (Panegrossi)...
This webcast contains 2 presentations: The first is from Lourdes Bugalho who talks about the forest fire combined risk index (ICRIF) and the second presentation is from Renata Libonati about monitoring burnt areas from polar orbiting satellites.
First part:
Forest fires are one of the most devastating natural disasters that often occur in mainland Portugal during the summer, with an impact on the economy, environment and climate. The Institute of Meteorology, currently Portuguese Institute of the Sea and the Atmosphere (IPMA, Instituto Português do Mar e da Atmosfera) has long made efforts to provide daily information on the risk of forest fires. Currently, IPMA daily runs an index of forest fire risk based on FWI (Fire Weather Index), developed by the Canadian Forest Service. This new index, ICRIF (Indice Combinado de Risco de Incêndios Florestais ) combines FWI with the type and condition of vegetation, called structural risk, being the vegetation type based on CORINE 2000 (CLC2000) and the vegetation conditions based on daily observation of NDVI (Normalized Difference Vegetation Index), retrieved from the AVHRR radiometer.
Second part:
Brazilian Amazonia together with the adjacent savanna (Cerrado) presents a huge number of fire events every year. In such context, accurate information about location and extent of burned area is required and of particular interest for the scientific communities dealing with meteorological and climate models in what concerns reliable estimations of biomass burned. Accordingly, an effort has been made by the scientific community to develop thematic products of burnt areas. In such context, this presentation will provide an overview of INPE/Brazil currently efforts in monitoring burned areas. The initiative is based on the (V,W) burned index. The index uses daily reflectance obtained from the 1km MODIS Level 1B calibrated radiance from bands 2 (NIR) and 20 (MIR). An overview will be given of results obtained and operational applications will be shown.
Go to Webcast (first part from L. Bugalho) ...
Go to Webcast (second part from R. Libonati) ...
Powerpoint (first part from L. Bugalho) ...
Powerpoint (second part from R. Libonati) ...
The scope of LSA-SAF is to increase benefit from Satellite (MSG and EPS) data related to land, land-atmosphere interactions and biospherical applications.
The main purpose of the Land SAF is to increase the benefits from MSG and EPS data related to land, land-atmosphere interactions and biophysical applications, namely by developing techniques, products and algorithms that will allow a more effective use of data from the two planned EUMETSAT satellites.
Although directly designed to improve the observation of meteorological systems, the spectral characteristics, time resolution and global coverage offered by MSG and EPS allow for their use in a broad spectrum of other applications, namely within the scope of land biophysical applications.
Activities to be performed within the framework of the Land SAF shall involve the development of products that are especially relevant in the following fields of application:
» Weather forecasting and climate modelling, which require detailed information on the nature and properties of land. Highest Land SAF priority should be towards the meteorological community and, within that community, NWP has been already identified as the one that has the greatest potential of fully exploit the products;
» Environmental management and land use, which require information on land cover type and land cover changes (e.g. provided by biophysical parameters or thermal characteristics);
» Natural hazards management, which requires frequent observations of terrestrial surfaces in both the solar and thermal bands;
» Climatological applications and climate change detection.
Presentation on how to discriminate levels of dust and what are the global impacts of dust outbreaks.
Dust is a global issue with it\'s good and also less good sides. There are hundreds or even thousands of places on Earth where the dust can be lifted, nevertheless you need to have a dust source to create a dust outbreak. And these are indeed two needed ingredients for lifting dust in the air that must come together; strong surface winds (requires about 15 knots) and dust source (or hotspots). MSG satellite helps a lot to do much better hot spot climatology, and for that, product called Dust Microphisics RGB is widely used. It is derived from three MSG spectral channels. Red color corresponds to difference of channels IR12.0 and IR10.8, green color to the difference of channels IR10.8 and IR8.7 and blue color to the sole IR10.8 channel. In addition to this product Natural Color RGB is also used, but mostly for detection of dust outbreak over the ocean. In this lecture Jochen Kerkmann, from EUMETSAT, will try to describe dust source regions and dust climatology, how to detect better dust on satellite images, how to discriminate levels of dust and what are the global impacts of dust outbreaks. Also he will mention topics like synoptic patterns and diurnal cycles of dust outbrakes, cloud-dust interaction, forecasting of dust movement and will give a list of typical mesoscale phenomena that can cause dust outbreaks.
Lecture based on the detection of forest fire hot spots by satellite means, which is more important in regions with small population covered areas.
Forest fires, as a natural phenomena (e.g. ignited due to lightning), is important factor in natural living process of a forest. Nevertheless, problems occur because most of the forest fires are caused by a human action, thus are very difficult to predict in any form. Therefore this lecture is mainly based on detection of forest fire hot spots by satellite means, which is more important in regions with small population covered areas. Emphasis here is on the IR3.9 µm SEVIRI channel, which can be called window channel, but on the other hand it is close to a CO2 absorption band. The importance of this channel we can see through a Wien's law; 3.9 µm is peek wavelength of blackbody with temperature of around 750 K, which is very close to temperature of a fire flame during active phase of fire. Besides forest fire detection, in this lecture you can hear something about detection of aerosols coming from forest fires, identification of burnt areas and about Fire Risk products.
Lecture starts with explanation of Vegetation monitoring and some applications of Vegetation products, such as NDVI index, FVC index, LAI and FAPAR indices.
The new generations of sensors on board meteorological satellites (SEVIRI -MSG, ASCAT -EPS, etc. ) enabled a whole new range of products related to the properties of the surface. Applications of such products are great. Some of them are; Vegetation monitoring, Wild Fires detection, Floods and Heat waves monitoring, detection of Urban heat islands, Crop water requirements, etc.
Lecture starts with explanation of Vegetation monitoring and some applications of Vegetation products, such as NDVI index, FVC index, LAI and FAPAR indices. After that Evapotranspiration parameter and Reference evapotranspiration overview is given. And at the end Land surface temperature is observed and various applications of this product are discussed.
This one hour presentation takes focus on the characteristics of the product files that are produced and distributed by LSA SAF.
This one-hour presentation takes focus on the characteristics of the product files that are produced and distributed by LSA SAF. The structure of the files is explained and freeware tools are presented. All the relevant information is given for the obtaining LSA SAF products. More general product information is given for documentation and file structure of data. Also, this session is explaining how to use Quick visualization by means of HDFView, GIS tools for visualization and analysis (Quantum GIS, GRASS GIS and ILWIS) and tool for georeferencing LSA SAF products. At the end of presentation there are words about how to use Python scripting for building custom scripts or programs for accessing and manipulating Land SAF data.