HIRLAM6 and HIRLAMA

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HIRLAM-6 and HIRLAM-A
HIRLAM Council
Advisory Comittee
Project Leader
100
Management Group Project Leader Area
leaders System Manager
Data Assimilation algorithms
Model physics
System
(Model dynamics)
Data Assimilation observation usage
25
100
Mesoscale model
25
25
50
Heads of Research
Core group members (8)
Staff (14)
2-3
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HIRLAM ALADIN organisation
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• End of HIRLAM-6 2005
• HIRLAM Evaluation
• New Programme
• Strategy for 5-10 years
• Recent activities and results
• Data assimilation
• Observations
• Model physics
• Dynamics and LBCs
• Meso-scale modelling
• HIRLAM and ALADIN collaboration

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Evaluation of HIRLAMOct 2004 Feb 2005

• Positive views and HIRLAM essential for
  institutes but
• Some complaints and hard to beat ECMWF
• Slow to solve some long standing problems
  (winter)
• No real development of high resolution FC system
• Not enough EPS
• HIRLAM important for ECMWF
• MF and ALADIN has benefited (spectral, 3DV,
  DFI..)
• MoU with weaknesses too short time and
  ambitious
• Project has no authority
• Role of Council not clear and not decisive

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Evaluation recommendations

• Stable contractual framework
• Clearer roles for governing bodies
• Authority to Project and Management
• Need good scientists and leaders
• Dedicated Core group
• Choice of ALADIN probably good
• But could have been other alternatives
• HIRLAM brand important
• Resources on synoptic model cannot be reduced
• Additional resources and use synergy effects
• Convergence with ALADIN
• Operational collaboration

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HIRLAM-A organisation

• Better control from the Programme, more full time
• Programme Manager 100
• Core group members 100 1/member(7 or 8)
• 1 part time Scientific Secretary (perhaps)
• 4 Project leaders x 75 (at least)
• Applications (100)
• DA and observations
• Dynamics and EPS
• Physical parameterisation
• Co-operation Agreement with ALADIN, common
  research and collaboration for meso-scale
• General and open MoU for 5-10 years
• Projects may change optional projects
• Operational cooperation
• climate support

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HIRLAM long term strategy2005-2015

• General development in the environment
• Increased international cooperation and
  coordination
• Synoptic scale LAM will be needed even beyond
  2010
• Meso-scale 3-1 km models will be operational
• New demands for nesting, assimilation,
  initialisation, postprocessing and probabilistic
  forecast products
• Short range EPS developed and in use
• Earth system modelling support for chemistry,
  bio- and hydrosphere

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Meso-scale forecasting system

• Best available 2.5 km meso-scale modelling system
  operational in most of the HIRLAM countries 2010
  for parts or all of the territory and
  applicable for 1 km BECAUSE it is
• Necessary for forecasting in mountainous regions
• Needed for very-short range prediction of severe
  weather, particularly with convection
• Needed for high resolution applications, air
  quality, dispersion, disastrous releases etc.

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The meso-scale forecsting system requires

• Non-hydrostatic (non approximated equations) and
  efficient dynamics (long time steps possible)
• Advanced meso-scale physics, particularly for
  clouds and precipitation species and turbulence
  (convection mainly resolved except shallow)
• Advanced data assimilation that initialises
  particularly the moist processes (rain and
  clouds) and that can utilise many new data
  sources Takes time ..
• Probabilistic forecasting and integrated system
  for estimating the probabilities
• Transparent boundary treatment

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Synoptic scale 10 km model

• Model for regional forecasting tightly coupled to
  ECMWF (will not be done by ECMWF lt2015)
• To provide best forecasts of synoptic
  disturbances with short data cut off
• To provide a comprehensive (high resolution in
  space and time) set of forecast variables for
  applications and other models
• To provide coupling to the meso-scale model with
  high resolution in space and time
• Consistent physics with meso-scale model
• EPS may have to be at 8-10 km for long time!
• ) depends on developments at and for ECMWF,
  too

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Develop EPS for all time ranges

• First for synoptic forecasting 24-48 (-72) h
• (Almost no HIRLAM-5 and -6 resources given
  (officially)) requires more resources
• Science not really developed for short range
• Natural for Operational collaboration between
  institutes (GRID)
• Pursue in a wider European context similar work
  in several places and of operational kind,
  exchanges
• Absolutely necessary for meso-scale
• Very expensive
• Science not at all developed
• Alternative methods (probabilistic
  postprocessing, using something from EPS at
  larger scales ?)

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3D/4D VAR Tuning background and observation
statistics

• Derive more statistics
• Tune sb and so on innovation statistics
• NMC method 0.4 instead of 0.6
• Statistical balance
• Horizontal variation of sb (index field)
• Balanced Jb balance equation and omega
• Nonlinear transformation for humidity
• Pre-conditioning better

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4D-VAR feasibility tests (X Yang, N Gustafsson)
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Analysis of surface parameters

• OI SST and Ice analysis
• Ocean Sea Ice SAF data -
• New OI snow analysis implemented
• QC and bias correction (due to height
  differences)
• Tuning of 2m T och RH analysis (statistics)

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Observation Usage

• Conventional data
• radiosonde launch times
• radiosonde drift
• comparing observation availability
• blacklist
• Remote sensing data
• AMSU-A
• AMSU-B
• QuikScat
• Radar doppler winds
• GPS ZTD
• WINDPROFILER

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INM test
TVNwith ATOVS
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Forecast Model - parameterisation

• Turbulence (CBR TKE-l)
• Much attention to stable case - more mixing at
  high stability - modified - cut - smooth Ri gt1
• Increased roughness - vegetational orografical
  !
• Direction of surface stress vector
• gt filling of lows, reduce 10 m wind
• Moist conservative and moist stability version
• effect of condensation on stability
• Surface fluxes ratio roughness mom/heat

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10-metre wind direction

• All Scandinavian stations
• The bias of 10 metre wind seems to be slightly
  smaller in H636
• In Scandinavia almost zero in H636
• Rms-error very similar

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Ändring av VEG index jämnare årlig variation
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ISBA snow covering parts of fractions 3 and 4,
open land and low vegetation

• Features of the snow scheme
• move the snow from fractions 3 and 4 to
  fraction 6 every timestep
• one layer of the snow, with a thermally active
  layer lt 15 cm
• water in the snow, which can refreeze
• varying albedo and density
• mirroring of temperature profile in the ground
  to assure correct memory

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Snow scheme for forest tile
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Model dynamics and predictability

• Coupling between SL advection and physics
• Semi-Lagrangian mods for orography (T eq.) and
  interpolations
• Development of transparent boundary conditions
• Incremental Digital Filter Initialisisation/launch
  ing DFI
• Ensemble forecasts with HIRLAM
• LAMEPS
• Multi-model
• Ensemble assimilation

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Semi-Lagrangian interpolations and T eq.
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Transparent Boundary conditions
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Embedding

• Verification methods - and for meso-scale SRNWP
  Workshop(s)
• Climate system developments
• System - upgrades - Reference test RCR monitor
• Merged HIRLAM/HIRVDA
• new cvs based make system

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Trunk, head, releases, merging, andnew releases

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HIRLAM work with ALADIN in 2005

• Made experiments at 11 and 2.5 km at ECMWF from
  MF data setsd
• Interfaced HI -ALADIN coupling and initial state
• Interfaced some HIRLAM physics (conv/cond, rad,
  turb started)
• Climate generation software available
• Daily runs at DMI, SMHI
• Introduce AROME system
• Evaluate HIRLAM physics
• GP coupling and LBCs
• Develop meso-scale diagnostics

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Aladin forecast2nd of July 2003 18 UTC
ALADIN 11km
ALADIN-NH 2.5km
ALADIN 2.5km
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ALADIN at SMHI 11 km
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ALADIN NH 2.5 km
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HIRLAM and ALADIN common research

• HI physics improvements
• Physics diagnostics tools
• physics interfacing, 2005
• HIRLAM modules
• General
• Externalised surface ?
• Meso-scale 3D-VAR
• Jb, wavelets, ensemble
• 2005-2006

• Meso-scale observations
• radar winds 2005-
• reflectivity 2006 -
• GPS moisture 2005-
• Surface and SST assimilation
• IR radiances over land
• Enhancements of ALADIN NH
• Map factor, VFE, pressure gradient and orography
• Large scale coupling
• Transparent LBCs

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Summary

• Thorough preparations for new HIRLAM
• Long term MoU and strategy
• More active areas more resources
• Stronger authority and more full time
• Collaboration necessary ALADIN and operations
  and climate
• Meso-scale model emphasis
• Predictability and EPS necessary
• HIRLAM developments in DA, physics, SL, LBC,
  systems
• Active work with ALADIN and code collaboration
  and common research plan

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ALADIN NH 2.5 N Sweden-Norway
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HIRLAM ALADIN code collaboration
HIRLAM
ALADIN
III
H phys Data Ass more
Available code but not necessary
Shared code
Common code
ALADIN
IV
Shared code LAM dynamics, Pre- and post
processing, support, much AROME physics, ARPEGE
Physics, some ALADIN/AROME Data Ass., sing.
vect., much obs. processing Common code HIRLAM
physics, HIRLAM developm. In AROME physics and
Data Ass. and obs. processing
Shared code
Common code
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AROME and ALADIN components

• Turbulence CBR HIRLAM 1d
• Externalised ISBA HIRLAM tiled
• (Kain-Fritsch synoptic scale - HIRLAM)
• Town model
• Advanced cloud physics
• Radiation scheme (Morcrette, ECMWF)
• Chemical modelling

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HIRLAM components for Meso-scale

• Surface scheme ISBA, snow, soil models
• Still mainly horizontally uncoupled upper air
  flow couples but flux aggregation ?
• Tiled or untiled ? tiles still exist below 1 km
• Externalised, HIRLAM or ALADIN?b
• Turbulence scheme CBR TKE - moist
• 1D or 3D ? 1D at 3 km and 3D at 1 km?
• Interactions with cloud scheme and convection
• Shallow convection ?
• Radiation scheme slopes considered
• 3D ? - More advanced more species
• Cloud scheme more advanced and more species
• MSO/SSO
• MSO relaxed but SSO needed at 1 km