demands and expectations at smhi on the european reanalysis for observations and climate
DESCRIPTION
Demands and expectations at SMHI on the European Reanalysis for observations and climate Per Und én Tomas Landelius SMHI. WP 2.1 4D-VAR developments and radar precipitation, a year of data – MO WP 2.2 3D-VAR downscaling, most of 20 years , 25 km SMHI - PowerPoint PPT PresentationTRANSCRIPT
Demands and expectations at SMHI on the European
Reanalysis for observations and climate
Per Undén Tomas LandeliusSMHI
EURO4M
WP1 observational datasets
WP2 reanalysis and evaluation
WP 3 evaluation WP 4
management and coordination
WP 2.1 4D-VAR developments and radar precipitation, a year of data – MO
WP 2.2 3D-VAR downscaling, most of 20 years , 25 km SMHI
WP 2.3 MESAN and SAFRAN downscaling, 12-4 km, MF and SMHI
What SMHI expects from EURO4M
• Dynamical downscaling of ERA data using HIRLAM 3D/4D-VAR – Consistent data set for ~ 20 years or more
• Access to observations additional to the ECMWF archive
• 2D high resolution downscaling of HIRLAM– Using these auxiliary observations– Driven by consistent HIRLAM model fields– Consistent data set ~ 20 years or more
Expect project members to share data
User requirements at SMHI
• 1961 - onwards
• Every 3:rd hour
• 5 km (0.05°)
• Parameters for:
Evaluation of climate change models
Atmospheric environment models
Oceanographical models
Wind energy studies
Hydrological models
Surface radiation models
Observation monitoring and replacement
SMHI KOAKK 40 years for QC of observations for climate National archives of
climate data have discrepancies
Need to be re-checked
– Corrections when necessary and possible
• EERA-40 ? >SMHI KOAKK
• 125 km -> HIRLAM reanalysis 22 km ->11 km? N Europe ?
• MESAN downscaling – at 11 km
Data-assimilation system, model and analysis, unchanged through the period
Analysis product quality improves in time
Observing systems including SST/ ICE improves: Better quality, more data types, higher time frequency
Reanalysis philosophy
Intermittent data assimilation
06 UTC 12 UTC 18 UTC
(06 UTC (12 UTC3 h) 3 h) 3 h)(18 UTC
tid
ITN 4/3 2010
4 Dimensional Variational Data AssimilationIterative fitting of a Forecast trajectory to observationsOver a time window of 6 hours
SMHI expertise and resources
• HIRLAM 3D and 4D-VAR• Observation handling• Re-analysis
– ERA expertise– DAMOCLES coupled
HIRLAM/HIROMB reanalysis
• Surface parameterisation• Cloud parameterisation• Radar and satellite data
and algorithms• HARMONIE (ALADIN)
models and data assimilation 3D(4D)
• MESAN 2D-analysis• OI with anisotrophic
structure functions• Observation processing
including radar, precip, satellite and road stations
• Long operational experience
• ERA-MESAN
FoUp redov
0.0
0.3
0.6
0.9
1.2
1.5
1.8
2.1
2.4
2.7
3.0
HIRLAM ALADIN
High Resolution LimitedArea Modelling
Aire Limitee Adaption Dynamique InterNationale
Improved 2D reanalysis for Europe
• ERA-40 as first guess
• 1980 – 2004
• 00, 06, 12, and 18 UTC
• 11 km (0.1°)
ERA-MESAN
Workpackage 2.2 ERA-Interim downscaling
25 km ENSEMBLES area ? ECMWF observations conv
AMVs? HIRLAM 3D-VAR 25 km Jk ((large-scale mix)) 1989-2009 -> HIRLAM 3D-VAR 11 km
EU area MESAN downscaling
11 km T2m, Td, uv, prec, clouds
3D-VAR developments Jk
MESAN/SAFRAN developments
Snow/ orography etc Advanced features
VARAN type structure functions
Coupled surf-upper air 3D ? Validation KNMI/MO
11-4 km
125-79 km
ERA-40 / ERA Interim
ECMWF
HIRLAM
MESAN
22 km
Signatur
• HIRLAM - Large Scale Mixing, LSM Reruns from ECMWF analysis, updating first guess
• Instead: Include ECMWF information in assimilation!
• Related work done with ALADIN at Météo-France
Signatur
Vorticity, model state Short forecast, ECMWF
Constrain Vorticity
• Begin as “simple” as possible: - Vorticity only - Univariate NMC statistics from
ECMWF forecasts, interpolated to HIRLAM RCR geometry
EURO4M downscaling with HIRLAM 4D-Var
possible areas
(Per Kållberg , Per Dahlgren – SMHI)HIRLAM rotated lat-long coordinates
S.P. at -35º/20º
three resolutions: 0.2º, 0.15º and 0.1º
294*260 = 76 440 points 0.2º*0.2º (27/-31/-24.7/27.5)
an example
• one day 4D-Var 0.15º*0.15º
• LBC from ERA_Interim
• 1 January 2005 18Z 4D-Var and +12h fcst
• ~215 System Billing units on C1A
• one cycle took ~40 minutes (run on daytime Nov 17)
306x306 points 0.2 x 0.2 °
another example
• one 4D-Var 0.2º*0.2º– 2 outer loops
• LBC from ERA_Interim• +12 h forecasts• Analysis 20 mins • Forecast 5 mins • => 25 mins per cycle
– Possible to run 1D / 2h– Or 12 days / day (but depending on queues etc)
• Special Project at ECMWF? Will apply ....
65 levels inst of 60 och 10 m lowest mod lv inst of 30
Development of the MESAN 2D analysis
Anisotropic structure functions Parameterized downscaling