This website uses cookies. Read about how we use cookies.

Close window

20 years of UM and NWP at the Interdisciplinary Centre for Mathematical and Computational Modelling

October 2017 – Met Office scientists attend the “Twenty Years of meteo.pl” conference at the Interdisciplinary Centre for Mathematical and Computational Modelling (ICM) at the University of Warsaw, which has used the Unified Model since 1997.

The Unified Model (UM) [1] has been in operations at the Met Office since June 1991. It has also been used since 1997 for numerical weather prediction (NWP) at ICM, which is at the University of Warsaw. ICM runs the UM as a regional model centred over Poland, driven by initial and boundary conditions from global model forecasts produced at the Met Office.

Figure 1: Example forecast for cloud cover, precipitation, and lightning based on a regional UM domain run by ICM, available from http://mapy.meteo.pl.

History of global modelling at the Met Office with the UM

Prior to 2003, the global model was developed at the Met Office HQ Bracknell, UK. A lot has changed since then, the Met Office moved to Exeter in 2003 and ICM subsequently acquired expertise in building and running the UM. The Met Office is continuously investing in research and development to improve the model core, its physics, and its operational implementation. This has led to over 60 updates of the operational global model (highlights in Table 1) since the first regional UM was implemented at ICM 20 years ago. Throughout these years, incremental updates continually improved the forecast accuracy at the Met Office resulting in better input data for ICM’s regional model as well. During the summer of 2017, the Met Office increased the resolution for the global model from ~17 km to ~10 km. With this resolution, the global model is now at finer resolution than the first regional model used at ICM 20 years ago.

1997 First input data for regional modelling at ICM provided from model at Met Office
Resolution global model at Met Office:
Horizontal resolution N144 (288 x 217, ~90 km), 30 vertical levels
1998-01-28 Horizontal resolution N216 (432 x 325, ~60 km), 30 vertical levels
Cray T3E as Met Office High Performance Computer 
1999-01-29 Three-dimensional variational data assimilation [2]
2002-08-07 Non-hydrostatic dynamical core New Dynamics [3]
2004-10-05 Four-dimensional variational data assimilation [4]
2005-12-13 Horizontal resolution N320 (640 x 480, ~40 km), 50 vertical levels
2009-06-30 IBM Power6 as Met Office High Performance Computer
2009-11-10 70 vertical levels
2010-03-09 Horizontal resolution N512 (1024 x 769, ~25 km)
2011-03-16 Global Atmosphere model configuration GA 3.1 [5]
2004-10-05 Hybrid ensemble / four-dimensional variational data assimilation [6]
2012-09-17 IBM Power7 as Met Office High Performance Computer
2013-04-30 Extended Kalman Filter based land surface analysis
2014-02-04 Rose for configuration and Cylc for workflow management, UM 8.5
2014-07-15 Global Atmosphere model configuration GA 6.1 [7]
Change grid placement with introduction of dynamical core ENDGame [8]
Horizontal resolution N768 (1536 x 1152, ~17 km)
2015-08-25 Cray XC40 as Met Office High Performance Computer, UM 10.1
2016-03-15 Variational bias control for satellite radiances, UM 10.2
2017-07-11 Horizontal resolution N1280 (2560 x 1920, ~10 km), UM 10.6

Table 1: Highlights of operational updates done for the Met Office global UM since ICM started to use is for initial and boundary conditions for a local area UM domain for NWP at ICM.

ICM's use of the UM as regional model

ICM as a downstream model user, has had to adjust and update their UM version and configuration according to the updates from the operational suite from the Met Office. ICM’s current model runs at convective permitting 4 km resolution (and at 1.5 km resolution experimentally) using science settings based on Met Office evaluation and verification for high-resolution models over the UK. Running and monitoring a regional UM domain over Central/Eastern Europe enables ICM to provide valuable feedback on regional model performance in a different climate from the UK. That allows ICM not only to provide high-resolution weather forecasts (Figure 1, Figure 2) to Polish users but also to help the Met Office in assessing and understanding the quality of the UM forecasts over Poland.

Figure 2: Example weather forecast for Warsaw, based on a regional UM domain run by ICM, available from http://www.meteo.pl.

Collaboration on NWP and regional model development and evaluation

ICM also collaborates with Institute of Meteorology and Water Management IMGW, Poland’s national meteorological service, and is part of the UM Partnership, formed out of the UM operational User group in 2014. The UM Partnership embeds the collaboration between ICM and the Met Office in a global consortium, facilitating the development and deployment of the UM to partners. One of the current key collaborative activities is to develop and test regional model configurations. ICM’s NWP domain has been identified as a candidate testbed for this research activity.

During October 2017, ICM celebrates 20 years of NWP at ICM, which also marks 20 years of its use of the UM. Met Office representatives from Weather Science and Science Partnerships will be visiting our partners in Poland to congratulate, give an update on developments at the Met Office and to discuss ongoing work on regional model development and plans for the next years.

References

[1] Brown A, Milton S, Cullen M, Golding B, Mitchell J, Shelly A (2012): Unified Modeling and Prediction of Weather and Climate: A 25-Year Journey. Bulletin of the American Meteorological Society. 93. 1865–1877. http://dx.doi.org/10.1175/BAMS-D-12-00018.1

[2] Lorenc AC, Ballard SP, Bell RS, Ingleby NB, Andrews PLF, Barker DM, Bray JR, Clayton A M, Dalby T, Li D, Payne TJ, Saunders FW (2000): The Met. Office global three-dimensional variational data assimilation scheme. Quarterly Journal of the Royal Meteorological Society, 126: 2991–3012. http://dx.doi.org/10.1002/qj.49712657002

[3] Davies T, Cullen MJP, Malcolm AJ, Mawson MH, Staniforth A, White AA, Wood N (2005): A new dynamical core for the Met Office's global and regional modelling of the atmosphere. Quarterly Journal of the Royal Meteorological Society. 131: 1759–1782. http://dx.doi.org/10.1256/qj.04.101

[4] Rawlins F, Ballard SP, Bovis KJ, Clayton AM, Li D, Inverarity GW, Lorenc AC, Payne TJ (2007): The Met Office global four-dimensional variational data assimilation scheme. Quarterly Journal of the Royal Meteorological Society. 133: 347–362. http://doi.org/10.1002/qj.32

[5] Walters DN, Best MJ, Bushell AC, Copsey D, Edwards JM, Falloon PD, Harris CM, Lock AP, Manners JC, Morcrette CJ, Roberts MJ, Stratton RA, Webster S, Wilkinson JM, Willett MR, Boutle IA, Earnshaw PD, Hill PG, MacLachlan C, Martin GM, Moufouma-Okia W, Palmer MD, Petch JC, Rooney GG, Scaife AA, Williams KD (2011): The Met Office Unified Model Global Atmosphere 3.0/3.1 and JULES Global Land 3.0/3.1 configurations. Geoscientific Model Development. 4: 919-941. https://doi.org/10.5194/gmd-4-919-2011

[6] Clayton AM, Lorenc AC, Barker DM (2013): Operational implementation of a hybrid ensemble/4D-Var global data assimilation system at the Met Office. Quarterly Journal of the Royal Meteorological Society. 139: 1445–1461. https://doi.org/10.1002/qj.2054

[7] Walters D, Boutle I, Brooks M, Melvin T, Stratton R, Vosper S, Wells H, Williams K, Wood N, Allen T, Bushell A, Copsey D, Earnshaw P, Edwards J, Gross M, Hardiman S, Harris C, Heming J, Klingaman N, Levine R, Manners J, Martin G, Milton S, Mittermaier M, Morcrette C, Riddick T, Roberts M, Sanchez C, Selwood P, Stirling A, Smith C, Suri D, Tennant W, Vidale PL, Wilkinson J, Willett M, Woolnough S, Xavier P (2017): The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations. Geoscientific Model Development. 10 (4). 1487-1520. https://doi.org/10.5194/gmd-10-1487-2017

[8] Wood N, Staniforth A, White A, Allen T, Diamantakis M, Gross M, Melvin T, Smith C, Vosper S, Zerroukat M and Thuburn J (2014): An inherently mass-conserving semi-implicit semi-Lagrangian discretization of the deep-atmosphere global non-hydrostatic equations. Quarterly Journal of the Royal Meteorological Society. 140: 1505–1520. https://doi.org/10.1002/qj.2235 

Last updated:

Follow us on

Facebook, Twitter, YouTube, Instagram, Snapchat, or LinkedIn Facebook Follow @metoffice on Twitter YouTube Instagram Snapchat LinkedIn