Operationalizing the South-East European Multi-Hazard Early Warning Advisory System (SEE-MHEWS-A)
Sector: Government • Location: Europe and Central Asia
Source: World Bank Group
Recognizing the need to improve regional severe weather and flood forecasting to improve national early warning, participatingcountries have agreed to develop the South-East European Multi-Hazard Early Warning Advisory System (SEE-MHEWS-A). With most of theanalytical and design work completed, this project will operationalize the regional system including data exchange, multiplenumerical weather p
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | dropped |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | Recognizing the need to improve regional severe weather and flood forecasting to improve national early warning, participatingcountries have agreed to develop the South-East European Multi-Hazard Early Warning Advisory System (SEE-MHEWS-A). With most of theanalytical and design work completed, this project will operationalize the regional system including data exchange, multiplenumerical weather prediction models, and flood forecasting models for select river catchment(s). The system will be established inthe European Centre for Medium-Range Weather Forecasts’ (ECMWF) high-performance computing environment, facilitating access tocutting-edge hydrometeorological approaches and technologies, while leveraging the quality, trust and sustainability of awell-established European regional intergovernmental institution. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
