SMHI Regional re-analysis in WP2.2

1989-1992, 2009 April 2012

Per Undén, Tomas Landelius

Per Dahlgren, Per Kållberg

Re-analysis configuration

Large Europe-Atlantic domain HIRLAM 3D-VAR 22 km 60 levels modelling system

All GTS conventional observations from ECWMF MARS No Satellite data, but Large scale forcing J

k

Albedo and snow corrected in 2 areas plus ice cover from ERA

Run test year 2009 ”Production” 1989 – 1992 (incl). Storing and archiving problems , now solved Runs to resume now

HIRLAM adjusted albedo, used in EXP=eu3a

Large scale error Constraint Per Dahlgren, Nils Gustafsson

Jk large scale constraint

References:

Dahlgren, Per and Gustafsson, N, 2012. Assimilating Host Model Information into a Limited Area Model , Tellus A 2012, 64, 15836, DOI: 10.3402/tellusa.v64i0.15836 .

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Data sets

Output data sets3D-VAR upper air and OI surface analysis. Upper air and surface

forecast fields from that analysis.

DataSpatial resolution: 0.2 by 0.2 ° rotated.Temporal resolution: 6 hours.Grid: Rotated spherical.Format: GRIB ed 1.AvailabilityArea: North Atlantic-Europe (EEA).Time period: 1989 -2010TIMELINE: n/a, scheduled for 2013-14freely available without restrictions.

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HIRLAM GRIB fields

HIRLAM EURO4M parameters, 843 fields (of which 150 are diagnostic):

Upper air parameters on 60 levels

33 109 60 U-component of Wind 34 109 60 V-component of Wind 11 109 60 Temperature 51 109 60 Specific Humidity 76 109 60 Cloud Water 71 109 60 Total Cloud Cover 200 109 60 Turbulent Kinetic Energy 58 109 60 Cloud ice

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more

10 m parameters

33 105 10 U-component of Wind 34 105 10 V-component of Wind

2 m parameters

11 105 2 Temperature 51 105 2 Specific Humidity 140 105 2 2m Temperature over land 141 105 2 2m Spec Hum 2m over land

Soil parameters

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Step

s

Lev

els

Parameters

MARS

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Retrieve,date = 20070901/to/20070915,parameter = temperature/geopotential,type = forecast,step = 0/to/48/by,levels = 1000/850/500/200,area = -10/20/10/0

SMHI implementation of ECMWF MARS @NSC.liu.seLinux servers, discs and tape robots Co-operation and merge with ECMWF

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Reasons for using MARS Easier and cheaper archiving

Don't use lot of disk space for fields No specific filesystems and paths

General interphase and tools Inventory with metadata Extractiom of subsets Interpolations and computations

built in Device independent data storage

Data server – disk, tape, etc. Tools for supervision, scheduling,

migration etc.

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Validation

Background and analysis statistics against observations used.Statistics of analysis increments and forecast tendencies.Differences from ERA Interim analyses.

OutlookFurther validation / evaluation by 2013-2014.EURO4M and users.Improvement.Releases.

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e

e4merim

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Running all the ”production” at ECMWF– Supervising and restarting etc. 4 an/fc cycles / hour

Storing the output– Ecfs – no – Copy to disk at NSC.liu.se – uses up disk space– MARS archiving

• Performance problems• New version and new scripts and hardware• Being implemented

Issues

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Another 16 years to run and archive

– Should be ready by April 2013

– Some reservation for the 36M delivery time

Validation– Monitoring observation increments– Analysis increments, differences, mean maps etc.

Plans

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Data exchange and validation

– Define variables

– Grid resolution

– Extraction from archives

– Possible data format conversion

– Transmission of data

– External access and tools ?

Further Issues