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iOBS (Improved Observation Usage in Numerical Weather Prediction)

This page contains public information about the project iOBS - Improved Observation Usage in Numerical Weather Prediction.

Phase: Execution

Project Partners

  • CSC - IT Center for Science Ltd.
  • Finnish Meteorological Institute (FMI), FI
  • Norwegian Meteorological Institute MET Norway, NO
  • Nordic e-Infrastructure Collaboration (NeIC)
  • Swedish Meteorological and Hydrological Institute (SMHI), SE

Background and Goals

This 10M NOK (50% in-kind), two-year cooperation project is planned to spend an effort equal to approximately 100 person months on improving observation usage in Numerical Weather Prediction (NWP). The iOBS initiative will accommodate an increasing amount and diversity of observation data, and provide a system of harmonised data pooling and merging. Observations from the “Internet of things” (IoT), such as intelligent cars, phones, buildings and personal weather stations (PWS), including commodity weather sensors, provide detailed information on local to hyper-local meteorological phenomena. The targeted breakthrough and measurable benefit of this project is the effective assimilation of diverse observations in regional high-resolution NWP models for the delivery of reliable and accurate weather forecasts and warnings for the benefit of operations, business and society. The basis will be the current operational NWP model, AROME-MetCoOp and/or the very recent addition of a nowcasting suite; ultra-local resolution observation network (both spatial and temporal) may be even more suitable for very high-resolution NWP models on the sub-kilometric scale, and the project results will be a valuable contribution to its on-going development.

The iOBS project contributes to improved weather forecast quality by the improved use of existing and emerging observation types in operational NWP combined with Glenna2 assisted future generation e-infrastructure: machine learning, analytics and IaaS support.

Expected Benefit

The project will improve, develop and implement timely quality control (QC) algorithms for a massive amount of private observations of surface pressure using an existing data source covering the Nordic countries. Since the Scalable Acquisition and Pre-Processing system (SAPP) is modular the QC could be added to the overall observation handling. Other emerging observation types will also be explored within the limits of the project. If successful, this will to our knowledge be for the first time private pressure observations are assimilated in an operational NWP system. There are some research on assimilation of pressure from mobile phones, e.g. at Danish Meteorological Institute (DMI), and these case studies have identified a potential increase in forecast accuracy by introducing these observations in NWP. Preliminary investigation into both mobile phone pressure data and private in-situ pressure data, shows more promise to the latter due to its stationarity. Mobile phones introduce an artificial pressure tendency when it is moving, especially vertically. Regarding private observations we will maintain the data history and protect personal information and/or sensitive data.

To summarize, the quantifiable benefits in this 2-year project include:

  • Improved NWP forecast quality from increased number of observations used in data assimilation
  • Improved QC algorithms for pre-processing private observations where machine learning approaches might help to further identify important observation errors and/or instrument malfunctions
  • Reduced cost for software maintenance and development for increased efforts in research and development
  • Improved conditions for Nordic research collaboration on both novel technologies and handling of different observation types
  • Knowledge transfer across scientific disciplines and technological solutions
  • Redundancy and flexibility by using both a cloud based research infrastructure (Glenna-2) and a proven operational infrastructure (PPI)
  • Raise awareness of benefits of public-private partnerships, e.g. our QC will inform data manufacturers about their data quality (a interest that they have already expressed)


Steering group

Meetings, 3-4 per year: iOBS steering group minutes

Please see the NeIC official website.

Reference group

Please see the NeIC official website.

Project personnel

Please see the NeIC official website.


Please see the NeIC official website.

Meetings, Weekly: Management minutes (internal).


Public documents



Governance documents: