In order to enable the necessary break though in early warning for severe weather in a changing climate, it is essential to have timely access to a wide range of observational data originating from all kinds of instruments and observations systems. C-MetNet envisions to be the data hub facility for this purpose and is an infrastructure that is needed in support of the computational models.
C-MetNet is a data hub facility for climate and atmospheric observations, providing leading edge opportunities for data-driven discovery in climate and atmospheric sciences, as well as development of geophysical hazard early warning and adaptation services. The backbone of this geo-observation system is an extensive climate and meteorological observation network and data centre. In a 'system of systems' approach C-MetNet’s open data platform integrates KNMI’s operational meteorological and climate observation network with observations from wide and expanding range of other sources, including the Ruisdael Observatory.
Ruisdael Observatory aims to make the transition to high-resolution modelling and observations using advanced ground based techniques. This concept, developed in the Netherlands will be applied in other places, including the marine environment where large-scale developments in spatial planning related to renewable energy production warrant new and advanced observations and modelling to study the effects on the local and remote environment.
Present processes lack the ability to indicate the quality of (enormous) amounts of data and the ability to link these data and models to different spatial and temporal scales, which is essential for the improvement of the resilience to climate change. Assimilation of the observations into high-resolution model analysis systems is the most promising method to integrate and interpret the new flood of observations into an understandable and manageable representation of the state of the atmosphere and land/sea surface. Present atmospheric data are generally restricted to assimilation of sensors which comply to WMO standards of measurement siting and accuracy. The challenge for the observation quality control and assimilation systems is to handle a much larger set of observations of significantly less homogeneous quality.
The ability to link observations from a reference network with data from opportunistic sensors (e.g. car or airplane sensor data and backyard weather stations) will enable a big step forward in reliability of these spatially dense observations.
Satellite data increases in the coming 5-10 years by orders of magnitude, in quantity and quality. The next generation of European meteorological satellites will be operational from 2022 onwards. The Copernicus (EU) Sentinel satellites will provide greenhouse gas and air quality observations.
In its basic realisation the envisioned C-MetNet infrastructure provides a common and open access platform for the collection, handling and dissemination of data, providing the scientific community with a single access point for quality controlled (near) real-time observations and a repository of past observations, (geo-referenced) data-derived products and all relevant (meta data) information, such as data provenance, quality assessments and calibrations.
The design of the infrastructure integrates big data engineering approaches, enabling handling of vast amounts of data and deployment of computational algorithms close to the data.
C-MetNet provides both local and wide-area measurements and observations of a range of geophysical quantities and phenomena, including basic meteorological parameters like pressure, temperature, radiation, precipitation and wind, as well as data from advanced space-based remote sensing instruments. C-MetNet services a data-driven society with access to satellite data from the next generation of European meteorological satellites, that are operational from 2022 onwards. A unique feature of the envisioned infrastructure is that it combines multiple decades of continuous past and future observations: From reference stations at locations that were carefully chosen and maintained to remain as undisturbed as possible, with data originating from dense and heterogeneously distributed networks in areas with micro-climatic conditions such as urban centres, industrial areas, solar and wind farms.
The possibility to merge and cross-reference these different types of observations will provide a wealth of opportunities for the science of climate change impacts and adaptation strategies, including large improvements of the capabilities to model and predict extreme weather events. C-MetNet connects to national and international data infrastructures (GEOSS, INSPIRE, Copernicus, CAMS, C3S), enabling discoverability for the wider (inter)national user communities. In cooperation with SurfSara, C-MetNet enables data discoverability and usage from the national compute services at SurfSara and in the European Open Science Cloud (EOSC).