4-9 September 2022, Bonn, Germany
EMS Annual Meeting Abstracts
Vol. 19, EMS2022-254, 2022, updated on 14 Apr 2023
EMS Annual Meeting 2022
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

IMPROVER overview and updates

Stephen Moseley, Ken Mylne, Bruce Wright, Simon Jackson, Fiona Rust, Gavin Evans, Ben Ayliffe, Kat Hurst, Marcus Spelman, Ben Fitzpatrick, and Chris Sampson
Stephen Moseley et al.
  • Met Office, UK

IMPROVER (Integrated Model Post-Processing and Verification) has been developed by the Met Office as an open-source probability-based post-processing system to fully exploit our convection permitting, hourly cycling ensemble forecasts. Post-processed MOGREPS-UK model forecasts are blended with deterministic UKV model forecasts and data from the coarser resolution global ensemble, MOGREPS-G, to produce seamless probabilistic forecasts from now out to 7 days ahead. For precipitation, an extrapolation nowcast is also blended in at the start. Forecasts are converted to probabilities at the start, and all initial stages of post-processing are performed on gridded data, with site-specific forecasts extracted as a final step, helping to ensure consistency. Data are processed on a 10km global grid and on a 2km UK-centred grid.

This talk will briefly describe the post-processing sequence from raw NWP model data to fully-blended, gridded and spot forecasts as probabilities and percentiles of a broad range of meteorological diagnostics, with the application of physical and statistical post-processing techniques. The system became operational in early May 2022, and the this talk will focus on some of the work that has been undertaken in the last year to achieve this, including ensemble calibration of temperature and wind speed data at observed and non-observed sites. There will be discussion of some of the verification used to prove this system, as well as a brief look at the technical aspects of this complex system, the initial customers and collaborators and the planned future work, including the use of ECMWF forecast data to extend the range of IMPROVER out to 14 days.

How to cite: Moseley, S., Mylne, K., Wright, B., Jackson, S., Rust, F., Evans, G., Ayliffe, B., Hurst, K., Spelman, M., Fitzpatrick, B., and Sampson, C.: IMPROVER overview and updates, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-254, https://doi.org/10.5194/ems2022-254, 2022.


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