Germany – Research and development services and related consultancy services – C3S2_361b Development of Machine Learning-based Methods for Downscaling the ERA5 Global Reanalysis to European and Arctic Regions

The main objective of the present Invitation to Tender (ITT) is to add to the regional reanalyses datasets already provided by C3S with additional Machine Learning (ML)–based products, which can enhance the existing service elements of C3S on regional reanalysis. The production element of the outcome of the present work would be a Timely Update (TU) Service for the existing Copernicus Arctic Regional Reanalysis (CARRA) and Copernicus European Regional Reanalysis (CERRA) reanalysis products (in the exact same form as it is in the present products) in a near real time fashion (5 days behind real time or so). This would include at least two basic variables (2m temperature and total precipitation amount), but possibly more variables in a consistent fashion. A desirable element of the work would be also the provision of uncertainty estimates (ensemble) to the provided variables. This work would be complemented by an outlook how in the future dynamical and ML-based methods can be used (combined) to provide regional reanalyses. ECMWF intends to award a single Framework Agreement for a period of maximum 24 months, which shall be implemented via a single Service Contract expected to commence in Q12025.