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DRIHM ICT-Video

DRIHM presents an interesting video explaining the objectives and best practices of the project

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Project

Extreme precipitation and flooding events are among the greatest risks to human life.

International agencies like the UN or the European Commission, national government organizations, and local authorities increasingly ask for globally certified management tools to deal with extreme events of precipitation and floods. For Agencies and Governmental Authorities, it is of utmost importance to be able to issue fact-based warnings to possibly affected areas. Important prerequisites of such ability are observed data and formally sound models to supplement them; this requires distribution of certified data and certified models, and perhaps certified model outputs; this implies the necessity of a reliable access to data archives and computational technologies providing new experimental data.

The burden of such a task is heavy for the hydrometeorological community, but becomes impossible without the support of an ICT structure able to deal with the massive amount of information needed. Progress will require bringing together advances in HydroMeteorological Research (HMR) and Information and Communication Technology (ICT).

With these goals in mind, the DRIHMS project was initiated to provide a detailed analysis of the needs for such steps forward in the cooperation between HMR and ICT scientists, and to provide a foundation for the timely deployment of an e-Science environment for hydrometeorology research on extreme events, as well as on climate change impacts and adaptation. Therefore, the main objectives of the DRIHMS project have been first to better understand the mindsets of both the hydro-meteorological and the ICT communities and second to propose a way of closing perceived and existing gaps between the communities.

Both the mindsets and the gaps were identified and analyzed centered on the views expressed by outstanding scientists and policy makers in the two fields of hydrometeorology and information and communication technology. The project attempted to identify the hydrometeorological hot research areas that require a network-based and distributed approach, in terms of hydrometeorological data and software sharing. Consequently, DRIHMS derived the requirements for the establishment of a reliable hydrometeorology research grid, oriented to sound prediction, both for real time warnings and for planning. This enabled the definition of a general rationale for the hydrometeorology research grid and the evaluation of the impact on such a research community.

In particular, based on the results of the project it was possible to derive a conceptual view of an HMR e-Science environment, and the consequent architectural view.

For a complete overview of the whitepaper, follow this link.

 

Severe hydro-meteorological events are increasing in frequency and magnitude. The societal and economic implications of these events, including loss of life and property damage, are the prime motivation for DRIHM’s commitment to contribute towards the following aspects:

  • Supporting Civil Protection decision makers with reliable information about where extreme meteorological events are most likely to occur;
  • Protecting people and infrastructure from the direct impact of severe weather;
  • Targeting operational rescue activity at areas known to be at high risk.

In this context, short and medium term forecasting and management of severe hydro-meteorological events are highly topical and represent an important contribution to the procedures implemented by civil protection authorities. The peculiar nature of severe hydro-meteorological processes occurring in most small and medium-size catchments in complex orography areas, such as the Mediterranean region, make them difficult to predict. This is due to a number of reasons:

  • The complex orography produces event response times in the order of a few hours;
  • Flash floods develop rapidly during the rainy season and suddenly inundate the terminal flood plains, incorporating many historic cities;
  • Traditional warning systems based on rainfall observations and rainfall–runoff modeling cannot provide the timely predictions needed to implement the required precautionary civil protection measures;
  • Social safety demands that hydrologists reliably predict ground effects 24 hours in advance and this requires using rainfall predictions as input to rainfall–runoff models, resulting in the use of a full hydro-meteorological forecasting chain;
  • Many sources of uncertainty are associated with hydro-meteorological forecasting chains.

The predictive ability of these severe hydro-meteorological events can be improved with:

  • Coherent and comparable observations at multiple locations;
  • Denser observations in time and space;
  • Better access to data;
  • More detailed models;
  • Combination of different modeling tools and post-processing tools;

A ‘joined-up science’ multidisciplinary perspective. Therefore, a key challenge for current HMR is to develop and validate new tools and methods to meet these needs. It is an interdisciplinary endeavor, requiring collaboration between measurement scientists and agencies collecting data, meteorological scientists forecasting the weather, and hydrological and hydraulic scientists predicting runoff and flooding and public services such as national environmental and civil protection agencies. It is also an international endeavor, requiring an integrated view of events that freely cross international borders. In the recent years, the quantity and complexity of the modeling tools and datasets have increased dramatically:

  • The availability and quality of remote sensing observational data from satellites and ground-based radars (providing complete three-dimensional coverage of the atmospheric and land surface state) has vastly increased;
  • The growing use of ensemble forecasting methods that combine multiple numerical weather prediction and hydrological models to quantify the uncertainty in the forecast, has dramatically multiplied the computational costs;
  • There is increasing recognition of the need to understand the entire flood forecasting chain, from observations through to civil protection response. This calls for the deployment of complex workflows able to combine different data sets, hydro-meteorological models and local decision-making expertise in a flexible manner.

However, as suggested also by the DRIHMS project:

  • Progress in tackling this HMR challenge is slowed by the difficulty in accessing data that are scattered in different archives, different countries, and different formats;
  • Collaboration is inhibited by the need for complex weather and hydrological models with significant high performance computing requirements.

It is understandable that lack of data limits the researchers’ ability to test and further advance models, resulting in a compromise that restricts their attention to the data and models locally available. However, the benefits of comparing and combining the full range of existing datasets and tools are clear.

With these goals in mind, the DRIMH project starts.

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