The EUMETSAT Satellite Application Facility in support to Hydrology (H-SAF) focuses on development of new geophysical products on precipitation, soil moisture and snow parameters and the utilisation of these parameters in hydrological models, NWP models and water management. The development phase of the H-SAF started in September
2005 under the leadership of Italian Meteorological Service. The "Centro Nazionale di Meteorologia e Climatologia Aeronautica (C.N.M.C.A.)", the Italian National Weather Centre, that physically hosts the generation chain of precipitation products, carried on activities to reach the final target: development of algorithms, validation of results, implementation of operative procedure to supply the service and to monitor the service performances. The paper shows the architectural status of the H-SAF precipitation group and stress the component of operations. It is shown the full
correspondence with the EUMETSAT approved H-SAF documents, in particular the Algorithm Theoretical Design Document (ATDD), where products characteristics are referenced. Are also reported the first results, produced during the first H-SAF Workshop, held in Rome in October 2007, of validation activities performed on version 1 products, and last results of products distribution to beta-users in preparation of distributing version 2.
Remote sensing from space plays an important role to know the environment. Today a lot of human activities look at
satellite data to understand the situation and take decisions. For example the knowledge of meteorological conditions
allow to plane civil protection missions and military campaigns. We can retrieve from satellite data series of parameters
that can be used for different applications building applications to manage derived information. Decision makers have to
take resolutions based on available information asking to put in evidence only useful parameters. A possible tool could
supply pictures to visualize the situation or messages to initialize a numerical model of decision.
The present paper wants to describe a possible application, giving an efficient instrument to positively conditioning
military decision process. We simulated some possible missions and have designed an instrument to select and present
environment parameters. It is also illustrated the concept of our application and shows some examples of output. The
application is very flexible because it manages parameters retrieved from other applications. We show the integration of
different Satellite Application Facilities products, applications of Italian Meteorological Service and conventional
observations. In particular we have resolved some problems as: ingesting of user's requirements (parameters and
geographical area), the retrieving of parameters in the database and optimization of spatial resolution.
The Centro Nazionale di Meteorologia e Climatologia Aeronautica recently hosted a fellowship sponsored by Galileo
Avionica, with the intent to study and perform a simulation of Meteosat Third Generation - Lightning Imager (MTG-LI)
sensor behavior through Tropical Rainfall Measuring Mission - Lightning Imaging Sensor data (TRMM-LIS). For the
next generation of earth observation geostationary satellite, major operating agencies are planning to insert an optical
imaging mission, that continuously observes lightning pulses in the atmosphere; EUMETSAT has decided in recent
years that one of the three candidate mission to be flown on MTG is LI, a Lightning Imager. MTG-LI mission has no
Meteosat Second Generation heritage, but users need to evaluate the possible real time data output of the instrument to
agree in inserting it on MTG payload. Authors took the expected LI design from MTG Mission Requirement Document,
and reprocess real lightning dataset, acquired from space by TRMM-LIS instrument, to produce a simulated MTG-LI
lightning dataset. The simulation is performed in several run, varying Minimum Detectable Energy, taking into account
processing steps from event detection to final lightning information. A definition of the specific meteorological
requirements is given from the potential use in meteorology of lightning final information for convection estimation and
numerical cloud modeling. Study results show the range of instrument requirements relaxation which lead to minimal
reduction in the final lightning information.
At the Italian Air Force Meteorological Service a neural network model (NN) was defined in order to forecast the convective systems evolution in the Mediterranean area. This model, composed by a system of NNs, uses combination of water vapour absorption (WV) and infrared window (IR) data of Meteosat Second Generation (MSG). We realized that cloud top temperature, from IR window channel, does not give enough information to forecast the evolution of convective systems. As a consequence we introduced information about middle troposphere humidity content, from water vapor absorption band. We had preliminary results using the Meteosat rapid scan (RS) data. The use of WV and IR data from Meteosat-6 RS service, with a time sampling of 10 minutes, allowed us to track satisfactorily the evolution of convective cells and improved the detection of the beginning of the cell life. We can say that information of IR channel temperature only is not enough, for example, to evaluate the dissolving phase of the convective cell. A small decrease of the cloud top temperature (detected in the IR channel) it is not a unique indication for the beginning of that phase. It is known that, during mature phase, a convective cell may have a pulsating behaviour, so its top increases and decreases for an unknown time interval.
After having defined two main evolution phases on the base of the features deduced from IR and WV channels, a specific NN algorithm was set up for nowcasting convective cells, using first RS data and then MSG data. A statistical analysis of cross-correlation between time series of different channels was performed for different areas of the Mediterranean region. From these statistics we may conclude that the performance of the NN system is more than satisfactory. This allows us to improve the operational automatic nowcasting application with the insertion of a NN module which gives information on the evolution of convective systems. In this way the forecasters are able to evaluate the probability of an increase or decrease of the severe convective activity.
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