| Name / Acronym |
Full name |
Fact sheet |
Web site |
| ACTRIS | Aerosols, Clouds, and Trace gases Research InfraStructure Network |
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| BSIK TAILORING | Tailoring climate scenarios for impact assessment applications |
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| BSIK-KVR-CS2 | Monitoring and profiling with the Cabauw Experimental Site for Atmospheric Research |
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| BSIK-KVR-ME1 | Integrated observations and modelling of greenhouse gas budgets at the ecosystem level in The Netherlands |
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| BSIK-KVR-ME2 | Integrated observations and modelling of Greenhouse Gas budgets at the national level in the Netherlands |
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| ECLISE | ECLISE: Enabling CLimate Information Services for Europe |
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| ENSEMBLES | ENSEMBLES |
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| EUCLIPSE | European Union Cloud Intercomparison, Process Study & Evaluation |
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| FUTURE WEATHER LARGE SCALES | Future Weather: impacts of large-scale circulation changes |
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| HSHL05/HSRR04 | Region specific climate data for Haaglanden and Region Rotterdam |
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| KKF-01C | Climate Knowledge Facility - Tailoring (Klimaat Kennis Faciliteit - Maatwerk) |
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| NMDC LK&EV | NMDC Innovatieproject Luchtkwaliteit en Externe Veiligheid |
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| PICASSO-CENA | Sensor Synergy algorithms for CloudSat and PICASSO-CENA |
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| PROBLEMS | Properties of Broken cLouds and cloud Edges from MSG SEVIRI (PROBLEMS) |
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| REMOTE INFLUENCES | KvR-CS5: Remote Influences on European Climate |
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| SRON_AEROEFF | New techniques for satellite monitoring of the first indirect aerosol effect: synergy of Meteosat Second Generation and ground-based anchor stations. |
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| SRON_CLIMPAR | Assessment of uncertainty in MSG retrieved cloud properties to improve the interpretation of climate model-to-satellite comparisons |
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| SRON_CRAFT | Cloud radiative forcing profile and vertical energy redistribution in the atmosphere (CRAFT) |
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| SRON_DRIZZLE | The impact of drizzle on cloud lifetime: an observation strategy using joint ground and satellite remote sensing. |
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| SRON_SYNTHESIS | Synthesis of active and passive measurements for atmospheric model improvement |
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| SUNSHINE ALGORITHM | Sunshine algorithm |
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| WIRE | Weather Intelligence for Renewable Energies |
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