Task 2.6. Products and services

Sub-tasks Definition and design of added value products Definition and design of added value products Implement real and near real time added value products of observational data for EuroMISS (WP8) Implement real and near real time added value products of observational data for EuroMISS (WP8) Design a system to archive the observational data for future use Design a system to archive the observational data for future use

Objective To define, select and design the added products to be developed in 2.6. for real time and near real time data compiled at 2.2. To define, select and design the added products to be developed in 2.6. for real time and near real time data compiled at 2.2. In other words, we have to define the software that will be created to generate added value products from the real time data that is going to be compiled. In other words, we have to define the software that will be created to generate added value products from the real time data that is going to be compiled.

Input from 2.2 Data to be compiled and used: Data to be compiled and used: Currents Currents Salinity Salinity Sea Level Sea Level Temperature Temperature Waves Waves Wind Speed Wind Speed Format NetCDF Format NetCDF OpenDAP OpenDAP

Products characteristics Software to be implemented in EuroMISS, EuroDESS and ROOSes web pages. Software to be implemented in EuroMISS, EuroDESS and ROOSes web pages. Modular approach and software (i.e. java) required. Modular approach and software (i.e. java) required. Not extremely complex in order to be properly tested on project time and resources and easily transported Not extremely complex in order to be properly tested on project time and resources and easily transported

Working procedure Step 1: Interrogate the different ROOSes for required software products. A representatives of each ROOS is involved in the task. A template was prepared and distributed Step 1: Interrogate the different ROOSes for required software products. A representatives of each ROOS is involved in the task. A template was prepared and distributed Step 2: Analyze and select those products feasible to implement Step 2: Analyze and select those products feasible to implement Step 3: Produce specifications for the selected products Step 3: Produce specifications for the selected products

2.6.1.Pre-selected products (1/3) Multi-parameter alert systems. It has been expressed the need to define and implement real-time web based alert indicators based on single variables or in the combination of different physical parameters. Examples of such combinations are sea level + sea state (to prevent shore infrastructure damage) or currents + SST (for HAB). These systems should be configurable by the user and must be able to send alert messages by e- mail and sms. Multi-parameter alert systems. It has been expressed the need to define and implement real-time web based alert indicators based on single variables or in the combination of different physical parameters. Examples of such combinations are sea level + sea state (to prevent shore infrastructure damage) or currents + SST (for HAB). These systems should be configurable by the user and must be able to send alert messages by e- mail and sms. Compilation of synoptic in-situ observation data sets (e.g. temperature, salinity, waves, currents) for model validation Compilation of synoptic in-situ observation data sets (e.g. temperature, salinity, waves, currents) for model validation

2.6.1.Pre-selected products (2/3) Algorithms to automatically fill data series gaps in real time. In the case of absence of measurements, sometimes is possible to infer the data from nearby instruments data or AR methods. Algorithms to automatically fill data series gaps in real time. In the case of absence of measurements, sometimes is possible to infer the data from nearby instruments data or AR methods. Operational time filter to prepare data for model assimilation or use in drift estimation. For this kind of work, it is convenient to filter the signal, keeping only the low frequency (sub-inertial) part. An additional application of these tools is the use of the high frequency part of the signal for the detection of rapid oscillations. This will be useful, for example, for Tsunami detection systems. Operational time filter to prepare data for model assimilation or use in drift estimation. For this kind of work, it is convenient to filter the signal, keeping only the low frequency (sub-inertial) part. An additional application of these tools is the use of the high frequency part of the signal for the detection of rapid oscillations. This will be useful, for example, for Tsunami detection systems.

2.6.1.Pre-selected products (3/3) Design and implementation of common data treatment tools in order to produce statistics to be employed online for the points where measurements are available (i.e. mean currents, wave roses, etc…) and by the automatic data quality algorithms (i.e. range of possible values, jumps, etc…). Design and implementation of common data treatment tools in order to produce statistics to be employed online for the points where measurements are available (i.e. mean currents, wave roses, etc…) and by the automatic data quality algorithms (i.e. range of possible values, jumps, etc…).

Future work plan By end of March the products will be selected and the specifications finished (we have a two months delay) By end of March the products will be selected and the specifications finished (we have a two months delay) A person will be hired for two years at Puertos del Estado for this task that will be jointly carried out with CMRC. A person will be hired for two years at Puertos del Estado for this task that will be jointly carried out with CMRC.