Model Setup


The following is a technical description of how ManUniCast works behind the scenes.  A detailed understanding of this technical description is not required to use ManUniCast.

How Does ManUniCast Work?

ManUniCast uses two different, but closely related, modelling systems. The weather predictions of ManUniCast are produced by version 3.4.1 of the Advanced Research Weather Research and Forecast model (WRF-ARW; Skamarock and Klemp 2008; Skamarock et al. 2008), which is an open-source model maintained by scientists at the National Center for Atmospheric Research (NCAR) designed for use by all members of the meteorological community and freely available at Principal users of WRF-ARW include many universities worldwide, as well as the United States National Oceanic and Atmospheric Administration (NOAA).

The atmospheric composition predictions of ManUniCast are produced by version 3.4.1 of the Weather Research and Forecast Model with Chemistry (WRF-Chem; Grell et al. 2005, Fast et al., 2006) with modifications made at the University of Manchester (Archer-Nicholls et al., in prep). WRF-Chem is a fully coupled atmospheric chemistry model with meteorological predictions that are produced from the same physics as WRF-ARW. The gas-phase chemistry used is the reduced Common Reactive Intermediates (CRIv2-R5) mechanism (Watson et al., 2008) and the aerosol scheme used is the 8-bin MOSAIC module (Zaveri et al., 2008) with the addition of N2O5 heterogeneous chemistry (Bertram and Thornton, 2009). The aerosol module is coupled with cloud microphysics and radiative processes (Chapman et al., 2009), providing feedback from the chemistry module back into the meteorological fields.

Domains, Boundary Conditions, and Physical Parameterisations

The weather predictions of ManUniCast consist of two fully-interactive nested domains: the first domain (d01) covering the majority of western Europe and much of the eastern north Atlantic Ocean at a 20-km grid spacing, and the second domain (d02) – which covers the United Kingdom and Ireland (excluding the Shetland Islands) – at a 4-km grid spacing.

The composition predictions of ManUniCast are made using a single domain (dchem) covering the UK, Ireland, the North Sea, much of France and Germany and the Low Countries at a 12-km grid spacing. We only display the results for the centre of the domain (matching the spatial coverage of d02) to avoid strong influences on our forecast from the chemical boundary conditions.

All three domains have 45 vertical levels and produce forecasts, starting daily from the 1800 UTC NOAA Global Forecast System (GFS) model forecasts. Presently, the two weather domains make forecasts out to 78 hours; the air-quality domain makes a forecast out to 54 hours. The NOAA global forecast model GFS provides both the initial conditions for ManUniCast from the 1800 UTC global analysis, as well as the lateral boundary conditions at three-hour intervals. The chemical initial conditions are taken from the previous day's forecast. The chemical boundary conditions are taken from MOZART-4/MOPITT global chemistry model forecasts (Emmons et al., 2010; Chemistry emissions are taken from the UK National Atmospheric Emissions Inventory (NAEI; and TNO emissions inventory (Denier van der Gon et al., 2010). The evolution of emissions on monthly, daily, and hourly time scales is constructed from scaling factors that estimate climatological observations.

The weather and the composition predictions of ManUniCast employ as many of the same physical parameterisations as possible. ManUniCast uses the Rapid Radiative Transfer Model (RRTM) longwave radiation scheme (Mlawer et al. 1997), the shortwave radiation scheme of Dudhia (1989), the Eta Monin–Obukhov surface similarity scheme of Janjic (1990, 1994), the Noah land surface model with four soil layers (Ek et al. 2003), the boundary layer scheme of Mellor and Yamada (1974) as modified by Janjic (1990, 1994). The convective parameterisation used for the weather simulation is a modified Tiedtke scheme (Zhang et al., 2011, after Tiedtke 1989) on domain d01 and the Kain-Fritsch scheme (Kain and Fritsch 1990, 1993; Kain 2004) on the chemistry domain (dchem). The microphysics scheme of Thompson et al. (2004) is used for domains d01 and d02. For the domain dchem, the microphysics scheme directly predicts cloud droplet number, which is calculated from the model aerosol fields using activation after Abdul-Razzak and Ghan (2002) with cloud microphysics following Lin et al (1983). The weather model only uses one-way feedback between domain d01 and d02, with domain d01 providing the boundary conditions for domain d02.


The models are run daily at 0005 UTC on Redqueen, the high-performance computing cluster at the University of Manchester ( Weather forecasts are generally available by 0700 UTC and chemistry forecasts by 1300 UTC. Model output is maintained by staff of the Centre for Atmospheric Science in the School of Earth and Environmental Sciences at the University of Manchester.

Domain 1: View Map

Domain 2: View Map

Chemistry Domain: View Map


Abdul-Razzak, H., and S. J. Ghan, 2002: A parameterisation of aerosol activation: 3. Sectional representation. J. Geophys. Res., 107(D3), doi: 10.1029/2001JD000483

Archer-Nicholls, S., D. Lowe, S. R. Utembe, W. Morgan, R. A. Zaveri, J. Fast, and G. McFiggans: Night-time and Day-time Chemistry in the UK Atmosphere: Part 1. Developments of the WRF-Chem model to Enable Comparison of Day-time and Night-time Oxidation Chemistry (in prep)

Bertram, T. H., and J. A. Thornton, 2009: Toward a general parameterisation of N2O5 reactivity on aqueous particles: the competing effects of particle liquid water, nitrate and chloride. Atmos. Chem. Phys., 9, 8351-8363.

Chapman, E. G., W. I. Gustafson Jr., J. C. Barnard, S. J. Ghan, M. S. Pekour, and J. D. Fast, 2009: Coupling aerosol-cloud-radiative processes in the WRF-Chem model: Investigating the radiative impact of large point sources. Atmos. Chem. Phys., 9, 945-964.

Denier van der Gon, H. A. C., A. Visschedijk, H. van der Brugh, and R. Droge, 2010: A high resolution European emission data base for the year 2005, A contribution to UBA - Projekt PAREST: Particle Reduction Strategies, TNO report TNO-034-UT-2010-01895 RPT-ML, Utrecht.

Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 3077-3107.

Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grunmann, V. Koren, G. Gayno, and J. D. Tarpley, 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J. Geophys. Res., 108(D22), 8851.

Emmons, L. K., S. Walters, P. G. Hess, J.-F. Lamarque, G. G. Pfister, D. Fillmore, C. Granier, A. Guenther, D. Kinnison, T. Laepple, J. Orlando, X. Tie, G. Tyndall, C. Wiedinmyer, S. L. Baughcum, and S. Kloster, 2010: Description and evaluation of the Model for Ozone and Related chemical Tracers, version 4 (MOZART-4). Geosci. Model. Dev., 3(1), 43-67.

Fast J. D., W. I. Gustafson Jr., R. C. Easter, R. A. Zaveri, J. C. Barnard, E. G. Chapman, and G. A. Grell, 2006: Evolution of ozone, particulates, and aerosol direct forcing in an urban area using a new fully-coupled meteorology, chemistry, and aerosol model. J. Geophys. Res., 111, doi:10.1029/2005JD006721.

Hollingsworth, A., R. J. Engelen, C. Textor, A. Benedetti, O. Boucher, F. Chevallier, A. Dethof, H. Elbern, H. Eskes, J. Flemming, C. Granier, J. W. Kaiser, J.-J. Morcrette, P. Rayner, V.-H. Peuch, L. Rouil, M. G. Schultz, and A. J. Simmons, 2008: Toward a monitoring and forecasting system for atmospheric composition: The GEMS project. Bull. Amer. Meteor. Soc. , 89(8): 1147-1164.

Janjic., Z. I., 1990: The step-mountain coordinate: Physical package. Mon. Wea. Rev., 118, 1429-1443.

Janjic., Z. I., 1994: The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., 122, 927-945.

Kain, J. S., 2004: The Kain–Fritsch convective parameterisation: An update. J. Appl. Meteor., 43, 170-181.

Kain, J. S., and J. M. Fritsch, 1990: A one-dimensional entraining/detraining plume model and its application in convective parameterisation. J. Atmos. Sci., 47, 2784-2802.

Kain, J. S., and J. M. Fritsch, 1993: Convective parameterisation for mesoscale models: The Kain.Fritsch scheme. The Representation of Cumulus Convection in Numerical Models, Meteor. Monogr., No. 24, Amer. Meteor. Soc., 165-170.

Lin, Y.-L., R. D. Farley, and H. D. Orville, 1983: Bulk Parameterisation of the Snow Field in a Cloud Model. J. Climate Appl. Meteor., 22, 1,065-1,092.

Mellor, G. L., and T. Yamada, 1974: A hierarchy of turbulence closure models for planetary boundary layers. J. Atmos. Sci., 31, 1791-1806.

Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102(D14), 16,663-16,682.

Skamarock, W. C. and J. B. Klemp, 2008: A time-split nonhydrostatic atmospheric model for weather research and forecasting applications, J. Computational Phys., 227, 3465-3485.

Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. Duda, X.-Y. Huang, W. Wang and J. G. Powers, 2008: A Description of the Advanced Research WRF Version 3. NCAR Technical Note, NCAR/TN–475+STR.

Tiedke, M., 1989: A comprehensive mass flux scheme for cumulus parameterisation in large-scale models. Mon. Wea. Rev., 117, 1779-1800.

Thompson, G., R. M. Rasmussen, and K. Manning, 2004: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and Sensitivity Analysis. Mon. Wea. Rev., 132, 519-542.

Watson, L. A., D. E. Shallcross, S. R. Utembe, and M. E. Jenkin, 2008: A Common Representative Intermediates (CRI) mechanism for VOC degradation. Part 2: Gas phase mechanism reduction. Atmos. Environ., 42(31), 7196–7204.

Zaveri, R. A., R. C. Easter, J. D. Fast, L. K. Peters, 2008: Model for Simulating Aerosol Interactions and Chemistry (MOSAIC). J. Geophys. Res., 113(D13), doi: 10.1029/2007JD008782

Zhang, C., Y. Wang, and K. Hamilton, 2011: Improved representation of boundary layer clouds over the Southeast Pacigic in WRF-ARW using a modified Tiedtke cumulus parameterization scheme. Mon. Wea. Rev., 139, 3489-3513.