The main change to the global versions of the Unified Model in the numerical weather prediction suite was the following:

The main change to the mesoscale version of the Unified Model in the numerical weather prediction suite was the following:

The main changes to the ocean and waves models during 2000 were:

28th March Introduction of UK waters wave model forecast to T+48

13 June Introduction of baroclinic shelf seas model of NW European shelf

19th September Upgrade to FOAM

24th October Wave models move to use 10m winds.

The main changes to the Nimrod nowcasting system were as follows:

14th September A wind and pressure forecast were added to Nimrod.

Routine monitoring provides regular revisions to acceptance lists for Synops, Aircraft and Sondes. In addition, the following major changes to the system were made:

December 20 (1999) ERS2 scatterometer winds disabled

May 17 Global data assimilation spring upgrade package :

• Introduced interpolation of model background to observation time.
• Use observed rather than retrieved ATOVS radiances
• Alternate covariance model allowing longer scales in the stratosphere.

June 6 Mesoscale data assimilation spring upgrade package:

• Introduced interpolation of model background to observation time.
• Alternate covariance model providing longer horizontal length scales and shorter vertical length scales
• Improved processing of surface pressure reports including use of hourly data
• Re-tuned the latent heat nudging scheme for rainfall data
• Removed humidity bias correction for VIZ sondes.

November 14 Converted stratospheric data assimilation system to 3DVAR

A) Front end mainframe computers B) Supercomputers

2.1.1 Make and model of computer

A) IBM 9672 – R45 B) Cray T3Ea (880 PEs)

IBM 9672 – R25 Cray T3Eb (640 PEs)

(PE – Processor Element)

2.1.2 Main Storage

A) 2 Gbytes (R45) B) 128Mb per PE (T3Ea)

1 Gbyte (R25) 256Mb per PE (T3Eb)

(16 PEs on each system have 512Mb)

2.1.3 Operating system

A) OS/390 Version 2 Release 9 B) UNICOS/mk 2.0.5

2.1.4 External input/output devices

A) 1 Terabyte of online disk storage B) 1440 Gbytes (T3Ea)

LAN attached Desktop PCs, 1920 Gbytes (T3Eb)

Workstations and printers

2 line printers

1 microfiche processor

to a GRAU automated tape library system

with a capacity of 28,800 cartridges.

Sun E6500 UltraSPARC processor and 16

StorageTek 9840 cartridge drives connected

to a StorageTek Powderhorn tape library with

The workstation-based ‘Horace’ system is used for visualisation and production and is operational in the National Meteorological Centre (NMC), Bracknell, and at other major operational locations in the UK.

Each user site comprises at least one Hewlett Packard UNIX data server plus as many multi-screen workstations, printers and plotters as are necessary to meet the local requirements. Communications services via a message switch provide every type of observational data from the GTS, while an ftp server provides the imagery, rainfall and numerical weather prediction (NWP) files.

Horace can display a wide variety of information in many forms, typically a combination of observations, NWP data or imagery (radar and satellite). In addition to its powerful visualisation capability Horace provides many semi-automated facilities and production tools:

• On-Screen Analysis provides the means to analyse and display contours, streamlines or wind arrows for a range of observed or derived parameters taken from scattered observations, at any level of the atmosphere or ocean, for any area of the globe. A field of NWP data is used as background in data-sparse areas.
• Using the On-screen Field Modification software, forecasters can manipulate forecast fields (of pmsl, geopotential height, precipitation, wind, ocean temperature, salinity and currents) in time and space to produce a set of meteorologically consistent output fields.
• The significant weather application allows users to prepare standard significant-weather briefing documents for military and civil aviators.
• An automatic text generation facility provides the means of generating ‘first-guess’ products, such as shipping forecasts, based on NWP output.
• Positions of atmospheric fronts can be determined objectively from NWP data and displayed on-screen as a guide for the forecaster.
• A ‘MetWatch’ module allows each user to define criteria, against which arriving observations, text messages and NWP data will be checked and an alert or automated action initiated accordingly.
• Terminal Airfield Forecasts (TAFs) are monitored automatically in the background, so that the forecaster is alerted if the most recent observation disagrees with the current TAF.
• There is a dedicated marine routing application to support both Naval and commercial shipping.

The global data assimilation system makes use of the following observation types. The counts are typical of late October, excluding data received but not yet processed for assimilation.
 

Products from WMC Washington are used as backup in the event of a systems failure (see section 7.2.3). The WAFS Thinned GRIB products at an effective resolution of 140 km (1.25º x 1.25º degrees at the equator) are received over cable in 6 hour intervals out to T+72. Since October 1996 we have also been receiving these products over the ISCS satellite link. Fields in this format include geopotential height, temperature, relative humidity, horizontal and vertical components of wind on most of the standard pressure levels, rainfall, PMSL and absolute vorticity.

Products received from Météo France, DWD and ECMWF (including Ensemble Prediction System forecasts) are used internally for national forecasting.

Fully automated.

Both manual and automatic checks are performed in real-time for surface and upper-air data from the UK, Ireland, Netherlands, Greenland and Iceland. Checks are made for missing or late bulletins or observations, and incorrect telecommunications format. Obvious errors in an Abbreviated Heading Line are corrected before transmission onto the GTS.

All conventional observations (aircraft, surface, radiosonde and also atmospheric motion winds)  used in NWP pass through the following quality control steps:

1. Checks on the code format. These include identification of unintelligible code, and checks to ensure that the identifier, latitude, longitude and observation time all take possible values.
2. Checks for internal consistency. These include checks for impossible wind directions, excessive wind speeds, excessive wind shear (TEMP/PILOT), a hydrostatic check (TEMP), identification of inconsistency between different parts of the report (TEMP/PILOT), and a land/sea check (marine reports).
3. Checks on temporal consistency on observations from one source. These include identification of inconsistency between pressure and pressure tendency (surface reports), and a movement check (SHIP/DRIFTER).
4. Checks against the model background values. The background is a T+6 forecast in the case of the global model and a T+3 forecast in the case of the regional or mesoscale model. The check takes into account an assumed observation error, which may vary according to the source of the observation, and an assumed background error, which is redefined every six hours using a formulation that includes a synoptic-dependent component.
5. Buddy checks. Checks are performed sequentially between pairs of neighbouring observations.

Failure at step 1 is fatal, and the report will not be used. The results of all the remaining checks are combined using Bayesian probability methods (Lorenc and Hammon, 1988). Observations are assumed to have either normal (Gaussian) errors, or gross errors. The probability of gross error is updated at each step of the quality control, and where the final probability exceeds 50 per cent the observation is flagged and excluded from use in the data assimilation.

Special quality control measures are used for satellite data according to the known characteristics of the instruments. For instance, ATOVS radiance quality control includes a cloud and rain check using information from some channels to assess the validity of other channels (English et al, 2000)
 

Non-real-time monitoring of the global observing system includes:

• Automatic checking of missing and late bulletins.
• Annual monitoring checks on the transmission and reception of global data under WMO data-monitoring arrangements.
• Monitoring of the quality of marine surface data as lead centre designated by CBS. This includes the provision of monthly and near-real-time reports to national focal points, and 6-monthly reports to WMO (available on request from the Met Office, Bracknell).
• Monthly monitoring of the quality of other data types and the provision of reports to other lead centres or national focal points. This monitoring feeds back into the data assimilation by way of revisions to reject list or bias correction.

Within the NWP system, monitoring of the global observing system includes:

• Generating data coverage maps from each model run (available on the Web).
• A real-time monitoring capability that provides timeseries of observation counts, reject counts and mean/r.m.s. departures of observation from model background. Departures from the norm are highlighted to trigger more detailed analysis and action as required.

The forecasting system consists of:

1. Global atmospheric data assimilation system (3DVAR)

2. Global atmospheric forecast model

3. Mesoscale atmospheric data assimilation system (3DVAR)

4. Mesoscale atmospheric forecast model

5. Stratospheric global atmospheric data assimilation system (3DVAR)

6. Stratospheric global atmospheric forecast model

7. Transport and dispersion model

8. Nowcasting model

9. Global wave hindcast and assimilation/forecast system

10. Regional wave hindcast and forecast system

11. Mesoscale wave hindcast and forecast system

12. Mesoscale model for sea-surge.

13. Global ocean model.

 The global atmospheric model runs with 3 different data cut-off times:

• 2 hours (preliminary run);
• 3 hours (main run); and
• 7 hours (update run).

The latest update run provides initial starting conditions for both the early preliminary and main runs of the global atmospheric model. The global atmospheric model provides surface boundary conditions for the global wave and ocean models. The preliminary global provides lateral boundary conditions for the mesoscale model, and surface boundary conditions for the regional wave model. The mesoscale forecast model is run four times a day and provides surface boundary conditions for the sea-surge model and the mesoscale wave model. The global wave model system includes the assimilation of wave height and wind speed observations from the altimeter on ERS-2. The global wave model provides lateral boundary conditions for the regional wave model, which then provides lateral boundary conditions for the mesoscale wave model. The nuclear accident model is run when needed.

NB:  The global Atmosphere and wave model run out to T+144 for backup purposes only.  The preliminary global atmosphere and regional wave models run out to T+48 for backup purposes only.

7.2.2 Forecast model

Basic equations Hydrostatic primitive equations with approximations accurate on

planetary scales (White & Bromley, 1995). Fourth order accurate

advection.

Independent variables Latitude, longitude, eta, time.

Integration domain Global.

Horizontal grid Spherical latitude-longitude with poles at 90ºN and 90ºS. Resolution:

0.56º latitude, and 0.83º longitude. Variables staggered on Arakawa

B-grid.

Vertical grid 30 levels, hybrid co-ordinates (eta = A/po +B);

layer boundaries at 1.0, 0.994, 0.956, 0.905, 0.835, 0.75, 0.70,0.65,

0.60,0.55, 0.50,0.45,0.41, 0.37,0.34, 0.31, 0.29,0.26,0.21,0.19,

0.165, 0.140,0.115,0.090, 0.065, 0.040, 0.020, 0.010, 0.0005;

277,252,227, 202, 177,152,127,102, 77, 52, 30, 15, 4.6 hPa.

Integration scheme Split-explicit finite difference. Adjustment uses forward-backward

scheme, second-order accurate in space and time. Advection uses a

Horizontal diffusion Linear fourth order with coefficient K = 2.0 x 10⁷ (but linear, second

order on top level with K = 7.0 x 10⁵) for winds, liquid potential

temperature and total water content. No diffusion where co-ordinate

surfaces are too steep (near orography).

Divergence damping Nil.

Orography Grid-box mean, standard deviation and sub-grid-scale gradients (for

gravity wave surface stress) derived from US Navy 10' dataset.

Orographic roughness parameters linearly derived from standard

deviation, and from 1 km data (N.America) and 100m data (Europe).

Surface classification Sea: global SST analysis performed daily.

Land: geographical specification of vegetation and soil types that

determine surface roughness, albedo, heat capacity, and surface

Physics parametrizations:

a) Surface and soil Met Office surface exchange scheme (MOSES I), Cox et al, 1999,

which includes:

• a Penman-Monteith surface flux formulation, with a 'skin' surface temperature;
• a 4-layer coupled soil hydrology and thermodynamics model;
• an interactive canopy resistance model;
• Sea-surface roughness dependent on wind speed (Charnock constant = 0.12). Surface fluxes of heat, moisture and momentum dependent on surface roughness and local stability.

RSMC Bracknell issues products on the GTS from the global numerical forecast models using several data formats. The character-based format is GRID (FM47-IX Ext.) and the binary format is GRIB Edition 1 (FM92-X Ext.). NWP model fields are interpolated onto regular latitude-longitude grids arranged in adjacent areas to give global coverage in GTS bulletins that do not exceed the GTS size limit. The regular products from the global atmospheric and wave models are on a 2.5º x 2.5º degree resolution. WAFS bulletins from the atmospheric model in the Thinned GRIB format of 140 km (1.25º x 1.25º degrees at the equator) are available over SADIS, but these bulletins, and the rest of the bulletins making up a full forecast product, are also available over high capacity links on the GTS. Graphical products can also be produced as T.4 faxes and Computer Graphic Metafiles (CGMs). Fields from the atmospheric model include geopotential height, temperature, horizontal wind on all standard levels, vertical velocity and relative humidity on some standard levels, mean sea level pressure and precipitation. From the wave model, height, direction and period of total significant wave, swell and wind-sea are available. Forecast times include the analysed data (T+0) and at 6 or 12 hour steps out to T+120. More detailed information is available in the "List of Numerical Weather Prediction Products Available from Bracknell", published by the Met Office.

In the event of a system failure at Bracknell, model runs can be switched to another supercomputer. Backup procedures are started when it becomes apparent that delays to the current run will lead to failure to meet the output schedules. At present this occurs if there is a delay of 20 minutes to the global model output. If the delay is less than 12 hours, all the normal output is generated from the previous run. The previous T+36 becomes the new T+24, for example, and the previous T+12 becomes the new T+0. If the delay is greater than 12 hours, and the previous run was not completed, then a limited number of products based on output from Washington WMC are issued in place of the normal Bracknell output.

4. Operational techniques for application of NWP products

A set of Model Output Statistics Products is generated from NWP global model forecast data from the 00Z and 12Z runs out to 6 days ahead. Day-maximum and night-minimum temperature forecasts for 800 stations world-wide and Probability of Precipitation over 6 and 12 hour periods for 300 European stations are produced. The NWP forecast data are sent to a system called FSSSI (Forecasting for Specific Sites: System Implementation) which contains a relational database, and are then run through a set of Kalman Filters to produce the forecasts. Later, the verifying observations are extracted to the database where the Kalman Filters are updated for the new observations. The forecasts are sent to other product generating systems where the data is formatted as an end product.

5. Ensemble prediction system

The ECMWF Ensemble Prediction System (EPS) is utilised for medium range forecasting. Ensembles are also run for monthly and seasonal forecasts (see Sections 7.5 and 7.6).

Output from the EPS is post-processed to provide forecasters with numerous chart displays including spaghetti diagrams, ensemble means, individual ensemble members and clusters of members. Charts showing extra-tropical cyclone tracks in ensemble members are also available. Probability forecast information for 41 synoptic sites around the British Isles are also generated, along with a comprehensive verification system for their assessment.

A new system scans the ensemble for probabilities of severe weather (severe gales, heavy rain or snow) and issues automatic alerts to forecasters when defined probability thresholds are exceeded. This system incorporates considerable calibration and also sophisticated calculation of probabilities over regions and time windows, to assess probabilities explicitly in the form required to support the UK National Severe Weather Warning Service. The system is currently under operational trial and is expected to become fully operational in 2001.

7.3.1 Data assimilation

The data assimilation scheme for the mesoscale model is similar to that for the global model except in the following:

  Analysis variables      As global (see 7.2.1) but also includes aerosol content.

7.3.2 Forecast model

The mesoscale forecast model is identical to the global model in all respects except the following:

Vertical grid 38 levels, hybrid co-ordinates (eta = A/p0 +B);

Vertical diffusion None.

Physics parametrizations:

• a Penman-Monteith surface flux formulation, with a 'skin' surface temperature;
• a 4-layer coupled soil hydrology and thermodynamics model;
• an interactive canopy resistance model;
• a tile scheme - each land gridbox can be made up from a mixture of 8 surface types (except for those classified as land-ice). Land use characteristics are based on AVHRR vegetation maps (horizontal resolution of 25m for the UK, 1km otherwise).

f) Gravity-wave drag None.

As described in section 7.2.3, except for the following:

NWP model fields are interpolated onto regular latitude-longitude grids arranged in adjacent areas covering Europe and the North Atlantic. The regional products from the atmospheric model are currently on either a 1.25º x 1.25º or a 2.5º x 2.5º degree resolution. The regional wave model products are on a 1.25º x 1.25º degree resolution. Forecast times include the analysed data (T+0) and at 3 or 6 hour steps out to T+36. Backup procedures are started when there is a delay of 10 minutes to the regional output. If the delay is less than 6 hours, all the normal output is generated from the previous run. The previous T+36 becomes the new T+30, for example, and the previous T+12 becomes the new T+6. If the delay is greater than 12 hours, and the previous run was not completed, then products from the run 12 hours before are used.

• A set of Model Output Statistics Products is generated from NWP preliminary global model forecast data from the 00Z and 12Z runs out to 2 days ahead. Day-maximum and night-minimum temperature forecasts for 500 European stations and Probability of Precipitation over 6 and 12 hour periods for 300 European stations are produced. The NWP forecast data are sent to FSSSI (see section 7.2.4)
• A set of one-dimensional Site Specific Forecast Model (SSFM) forecasts with high resolution in the boundary layer and sub-surface are run using mesoscale model and preliminary global model data as forcing data. 800 UK and near continent sites are run 4 times per day from the mesoscale model out to T+36, and 100 world-wide sites 4 times per day from the preliminary global model also out to T+36. The data are sent to FSSSI. Initialising data for the SSFM are extracted from previous runs and sent with the forcing supercomputer to run the SSFM. The forecast output is returned to FSSSI where it is packaged and further processed into a number of products for onward dissemination. Some of the further processing includes Road Surface Temperature modelling, Automatic TAF generation software and further Model Output Statistics processing. The Road Surface Temperature model output for 600 road sites in the UK has a bias correction using an updateable Kalman Filter for those sites which report surface temperature and screen temperature regularly.

Nimrod produces analyses and forecasts of precipitation and supplementary weather parameters (including precipitation type, visibility, snow probability and lightning rate), at 5 km resolution, for the period T+0 to T+6 hours. Forecasts are produced using a combination of linear extrapolation and model wind advection, with precipitation forecasts from the mesoscale model used to introduce an element of growth/decay. In addition, analyses and forecasts of cloud amount (3-D), cloud base and cloud top height, wind speed and direction are generated. These products are generated hourly at a resolution of 15 km. The Nimrod cloud and precipitation analyses are used as inputs to the mesoscale model assimilation scheme.

A stratospheric data assimilation system has been run at the Met Office for a number of years. A research data assimilation system was started in October 1991 based on the Met Office Analysis Correction (AC) scheme. This research system was the basis for the operational stratospheric data assimilation system which was started in November 1994. In November 2000, major changes were made to the operational stratospheric suite: the AC scheme was replaced by a 3-D variational scheme; satellite radiances were assimilated instead of retrieved temperature profiles; and a daily 48-hour forecast was introduced.

Initialisation of TC's is achieved by the creation of bogus data, which are fed into the numerical forecast model. TC advisory bulletins received on the GTS from various TC warning centres are used to provide the input data to this process. The creation of TC bogus data is totally automated, but forecasters in the National Meteorological Centre (NMC) at the Met Office have the facility to over-ride the automatic system and create their own bogus data if required. Full details of the bogus technique may be found in Heming et al, 1995.

A model for medium and long-range transport and dispersion (NAME, version 4.7) is available to be run in the event of a major atmospheric release of hazardous pollutants, such as in a nuclear emergency or volcanic eruption. It can also be used for routine air pollution problems, such as episode studies and forecasting air quality. The model provides forecasts of concentrations in the boundary layer and at upper levels, as well as wet and dry deposition to the surface. It uses analysis and forecast fields from the global and mesoscale atmospheric models maintained in on-line archives. The NAME model may be run at any time in hindcast or forecast mode.

Integration domain Global or UK mesoscale, nested as required.

Dynamical input Meteorological fields from the global or UK mesoscale models.

Apart from having no data assimilation, the formulation of the regional wave model is identical to the global wave model in all respects except the following:

A new UK Waters wave model has been implemented. The wave model uses the same physics as the regional wave model, with the addition of time-varying wave-current interactions, taking surface currents from the operational storm surge model. The model is set up at 1/9 by 1/6 degree resolution covering 48-63N, 12W-13E, the same grid as the operational storm surge model. The model is run four times daily, for a 48 hour forecast under mesoscale 10m winds. A separate 5-day forecast, without currents, is run twice daily using global NWP winds.

Integration domain NW European continental shelf.

Physics

The Proudman Oceanographic Laboratory (POL) baroclinic shelf seas model (Proctor and James, 1996) covering the NW European shelf area, at 1/9 by 1/6 degree resolution between 48-63N, 12W-13E, and with 15 sigma levels in the vertical, is run using surface forcing from the mesoscale numerical weather prediction model (3-hourly average for surface heating, hourly winds and pressures). Climatological values of temperature and salinity are applied at the deep ocean boundary. Tides are forced by specifying the boundary elevation using 15 harmonic constituents. The model runs once daily, for a 24 hour hindcast followed by a 48 hour forecast. There is no data assimilation.

Integration domain NW European continental shelf.

Grid Spherical latitude-longitude from 48ºN to 63ºN, and from 12ºW to

Surface classification No sea ice. No wetting or drying.

A depth-averaged storm surge model, developed by the Proudman Oceanographic Laboratory, is run operationally on behalf of MAFF (Ministry of Agriculture, Fisheries and Food) for the Storm Tide Forecasting Service. The model is implemented on a grid at 1/9 by 1/6 degree resolution covering 48-63N, 12W-13E, and is forced at the deep ocean boundaries by 15 tidal harmonic constituents. The model is run 4 times daily, using hourly values of surface pressure and 10m winds from the mesoscale NWP model to provide a 36 hour forecast.

Extended range and experimental seasonal range forecasts (Section 7.6) are produced from the same 4-month-range, 9-member AGCM ensemble integrations forced with persisted Sea Surface Temperature (SST) anomalies. Forecasts are produced weekly on Thursdays.

The model ensemble system used for long (seasonal) range forecasts is identical to that used for extended range forecasts (Section 7.5). The seasonal forecast products are experimental and are available to National Met. Services through a password protected internet site.

1. The annual figures shown above are averages of the 12 monthly statistics running from January to December 2000. The statistics are derived according to the standard verification methods specified by the CBS.
2. All results show the average of the 00 UTC and 12 UTC values at T+24, T+72, and T+120.

New applications will be developed to meet new user requirements. Over the coming year or so we will also be exploring how best to optimise the use of Horace and the Met Office’s Windows NT visualisation and production platform, Nimbus, which is used primarily in the local weather centres and military stations around the UK. We will also be investigating the possibility of porting Horace to run on the Linux operating system.

9.2 Data assimilation.

An upgrade to the current global data assimilation system is anticipated in the early spring. Later in the year a major upgrade of the system is anticipated in order to support the new version of the modelling system. Some possible candidates for inclusion in the spring upgrade are:

• A new system for defining radiosonde bias corrections of height and relative humidity;
• Intelligent thinning of ATOVS and revised channel selection including some AMSU-B;
• To present dual scatterometer winds to 3DVAR for implicit ambiguity removal;
• To make more use of Synop reports (temperature, wind, humidity);
• To use new Satwind sources, and a more intelligent thinning;
• A revised ATOVS bias correction strategy (especially for stratosphere);
• The use of Profilers;
• The use of SSMI Total Water and second satellite; and
• Inclusion of data from NOAA-16

Upgrades to the mesoscale data assimilation system during 2001 may include:

• Inclusion of European radar data to UK weather radar composite
• Assimilation of wind profiler data, high resolution Meteosat visible wind data, AMSU radiances
• Replacement of a statistical radiosonde humidity bias correction with a real-time scheme.
• Improved consistency of analysis with boundary data from global model, by interpolation of global analysis increments to the mesoscale domain to make a first guess for the mesoscale analysis.

• The global orography will be based on the GLOBE dataset of 30-second arc resolution.
• A new dynamical formulation will be assessed and prepared for operational implementation in late 2001. The main features are semi-implicit, semi-Lagrangian advection, Charney-Phillips vertical grid, height co-ordinate, non-hydrostatic.

The resolution of some of the rainfall products will be increased to 1km. Data from more European radars will be included in the rainfall analysis. An improved gauge adjustment scheme for the radar data will introduced. A sophisticated soil moisture scheme will be incorporated into Nimrod using Nimrod and model forecasts as input. An improved version of the idealised model of convection used in the GANDOLF convective forecasting system will be introduced and the rainfall forecasts from Gandolf and Nimrod will be fully integrated.

The sources of incoming advisories for TC initialisation procedures will continue to be evaluated and changes made to ensure the use of the best input data. Tests of enhancements to the TC initialisation procedure itself are ongoing and changes will be implemented if a positive impact on TC forecasts is established.

• Improved free tropospheric turbulence parametrizations;
• Use of ensemble forecast products;
• Development of a replacement model for dispersion at all ranges.

Wave energy spectra from the ERS-2 SAR UWA observations are routinely retrieved, with global coverage, using the iterative retrieval scheme developed by Hasselman et al, at the Max Planck Institute for Meteorology, Hamburg.

Ocean Forecast models.

A 1/3 degree model of the Atlantic and arctic is being developed, with a southern boundary at 30S nested into global FOAM. Models at 1/9 degree nested into the 1/3 degree Atlantic model are also under development. Methods to assimilate altimeter sea surface height data are being developed and applied. The 1/3 degree Atlantic model is being prepared for operational implementation during second quarter 2001

The shelf seas model is being upgraded to use a hybrid vertical co-ordinate, to improve representation of the surface layers in deeper water. The new model will use a Mellor Yamada turbulent mixing scheme, in place of the present bulk Richardson number scheme, and will be applied over a wider area (40N to 60N, 20W to 13E) The revised model will use the POLCOMS formulation and code.

Bloom, S.C. , Takaka, L.L., Da Silva, A.M. and Ledvina, D., 1996, Data assimilation using incremental analysis updates. Mon. Wea. Rev., 124, 1256-1271

Cox, P.M., R.A. Betts, C.B. Bunton, R.L.H. Essery, P.R. Rowntree and J. Smith, 1999: The impact of new land surface physics on the GCM simulation of climate and climate sensitivity. Climate Dynamics 15, 183-203.

Edwards, J.M. and  Slingo A., 1996:Studies with a flexible new radiation code. Part I. Choosing a configuration for a large-scale model. Quart. J. Roy. Meteor. Soc., 122  pp.689-719

English, S.J. R. J. Renshaw, P. C. Dibben, A. J. Smith, P. J. Rayer, C. Poulsen, F. W. Saunders and J. R. Eyre, 2000: A comparison of the impact of TOVS and ATOVS satellite sounding data on the accuracy of numerical weather forecasts. Quart. J.R. Meteorol. Soc. Vol. 126 No. 569 pp2911

Gregory, D. and P.R. Rowntree, 1990: A mass-flux convection scheme with representation of cloud ensemble characteristics and stability-dependent closure. Mon. Wea. Rev., 118, pp1483-1506.

Heming, J.T.,J.C.L.Chan & A.M.Radford (June 1995). A new scheme for the initialisation of tropical cyclones in the UK Meteorological Office global model. Meteorological Applications, 2, 171-184.

Jones,C.D and Macpherson,B., 1997:  A Latent Heat Nudging scheme for the Assimilation of Precipitation Data into an operational Mesoscale Model. Meteorol. Apps, 4, 269-277

Kitchen, M., R. Brown and A. G. Davies, 1994: Real-time correction of weather radar data for the effects of bright band, range and orographic growth in widespread precipitation. Quart. J. Roy. Meteor. Soc., 120, 1231-1254

Komen, G., K. Hasselmann, and S. Hasselmann, 1984: On the existence of a fully developed windsea spectrum. J. Phys. Oceanogr., 14, pp1272-1285.

Lock, A.P., A.R. Brown, M. R. Bush, G. M. Martin  and R.N.B. Smith, 1999: A new boundary layer Mixing scheme. Part I: Scheme description and single column tests. Submitted to Mon. Wea. Rev.

Lorenc, A.C., and O.Hammon, 1988: Objective quality control of observations using Bayesian methods. Theory

and a practical implementation. Quart. J. R. Meteorol. Soc., 114, pp515-543.

Lorenc, A.C., Ballard, S.P., Bell, R.S., Ingleby, N.B., Andrews, P.L.F., Barker, D.M., Bray, J.R., Clayton, A.M., Dalby, T., Li, D., Payne, T.J. and Saunders, F.W. 2000. The Met Office Global 3-Dimensional Variational Data Assimilation. Quart. J.R. Meteorol. Soc. Vol. 126 No. 570 pp2991

Macpherson, B., Wright,B.J., Hand,W.H. and Maycock,A.J., 1996:  The impact of MOPS moisture data in the UK Meteorological Office Mesoscale Data Assimilation Scheme Mon. Wea. Rev., 124,1746-1766

Martin G. M., M. R. Bush, A.R. Brown, A. P.  Lock,  and R.N.B. Smith, 1999: A new boundary layer Mixing scheme. Part II: Tests in climate and mesoscale models. Submitted to Mon. Wea. Rev.

Morcrette, J.-J., L.D.Smith, and Y.Fouquart, 1986: Pressure and temperature dependence of the adsorption in long-wave radiation parameterisations. Beitr. Phys. Atmosph., 59, pp455-469.

Palmer, T.N., G.J. Shutts, and R. Swinbank, 1986: Alleviation of a systematic westerly bias in general circulation and numerical weather prediction models through an orographic gravity wave drag parametrization. Q. J. Roy. Meteorol. Soc., 112, pp1001-1039.

Phillips, O.M., 1958: The equilibrium range in the spectrum of wind generated waves. J. Fluid Mech., 4, pp426-434.

Pope, V.D., M.L. Gallani, P.R. Rowntree and R.A. Stratton, 2000: The impact of new physical parametrizations in the Hadley Centre climate model: HadAM3. Climate Dynamics, 16,123-146.

Proctor, R. and I. D. James (1996) A fine resolution model of the Southern North Sea. Journal of Marine Systems 8 (1996) 285-295

Slingo, A., 1989: A GCM parametrization for the short-wave radiative properties of water clouds. J. Atmos. Sci., 46, pp1419-1427.

Smith, R.N.B., 1990: A scheme for predicting layer clouds and their water contents in a general circulation model. Q. J. Roy. Meteorol. Soc., 116, pp435-460.

Snyder, R.L., F.W. Dobson, J.A. Elliot, and R.B. Long, 1981: Array measurements of atmospheric pressure fluctuations above surface gravity waves. J. Fluid Mech., 102, pp1-60.

Stratton, R.A., D.L.Harrison, and R.A.Bromley, 1990: The assimilation of altimeter observations into a global wave model. AMS 5th Conference on Satellite Meteorology and Oceanography, London, 1990, pp108-109.

SWAMP (Sea Wave Modelling Project), 1985: An intercomparison study of wind wave prediction models. Part I: Principal results and conclusions. Ocean Wave Modelling. Plenum Press, 256pp.

Thomas, J.P., 1988: Retrieval of energy spectra from measured data for assimilation into a wave model. Q.J. Roy. Meteorol. Soc., 114, pp781-800.

White, A.A and R.A.Bromley, 1995: Dynamically consistent, quasi-hydrostatic equations for global models with a complete representation of the Coriolis force. Q.J. Roy. Meteorol. Soc., 121, pp399-418.

Willmott, C.J., C.M. Rowe and Y. Mintz, 1985: Climatology of the terrestrial seasonal water cycle. J. Clim., 5, pp589-606.

Wilson, D. R. , and S. P. Ballard,  1999:A microphysically based precipitation scheme for the UK Meteorological Office Unified Model. Q.J. Roy. Meteorol. Soc., 125, pp.1607-1636.