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Overview of data impact studies within the HIRLAM community
Nils Gustafsson and Harald Schyberg
with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu Huang, Magnus Lindskog, Kirsti Salonen,
Martin Stengel, Vibeke W. Thyness, Henrik Vedel, John de Vries, Xiaohua Yang
The HIRLAM A program
Participants: Denmark, Finland, Iceland, Ireland, Netherlands, Norway, Spain, Sweden + France
5 year period 2006 - 2010 3 general targets: (1) Improved synoptic scale
forecasting system (10 km); (2) Mesoscale forecasting system (a few km); (3) Probabilistic forecasting system
Development of mesoscale forecasting system in collaboration with the ALADIN community
The HIRLAM synoptic scale forecasting system
Hydrostatic gridpoint model Semi-implicit, semi-Lagrangian, 2-time level scheme Physics: ISBA surface, CBR turbulence, Rasch-
Kristjansson & Kain-Fritch condensation and convection, Savijärvi radiation
3D-Var and 4D-Var OI surface and soil assimilation Applied at 5 – 20 km horizontal resolution A “reference” model version being continuously
updated and tested
HIRLAM 3D-Var and 4D-Var
TL and AD models based on the semi-Lagrangian, semi-implicit and spectral version of HIRLAM
Statistical balance background constraint based spectral transforms, moisture included in the balance constraints
Weak digital filter constraint Variational quality control
The HARMONIE mesoscale forecasting system
Developed jointly with the ALADIN project Non-hydrostatic model Code is based on IFS 3D-Var; 4D-Var to be developed; Aim to base
background error constraint on ensemble information
Several physics packages are available Applied at 2 – 10 km horizontal resolution To replace HIRLAM also at synoptic scale
resolutions (10 km) - 2011?
HIRLAM impact studies in connection with development of observation operators
AMSU-A over sea
AMSU-A over land and sea ice
AMSU-B
HIRS
Scatterometer winds
MODIS wind
MODIS water vapour
SEVIRI water vapour channel radiances
Radar radial winds
Radar VAD wind profiles
Wind profilers
GPS zenith delays
GPS slant delays
Limitations of HIRLAM observation usage
To some extent driven by externally funded research projects and by PhD projects; not by the need from the weather services to improve forecast quality Project have often been finished before operational implementation No instructions prepared for operational NWP groups on how to access the data and do the needed pre-processing
and with the consequence
Only AMSU-A data over sea are utilized by the reference HIRLAM system in addition to conventional observations (local implementations may have more)
Example: MODIS winds (Carlos Geijo) Two one month (January and July 2006) impact studies with MODIS winds and AMSU-A radiances over sea. HIRLAM reference RCR domain Positive impact of MODIS winds in January 2006 and also of AMSU-A in January 2006, but not from the combination – not yet understood!
Example: GPS zenith delays
From Vedel and Huang (2004):Accumulated precipitation from 0 to 12h forecast time(case study)
Several HIRLAM groups have carried out impact studies with ground-based GPS zenith delay data. Difficult to show impact with conventional forecast verification scores. Positive impact demonstated in individual precipitation forecasts The need for bias correction is an open question
Example: Radar radial windsTen-day assimilation experiment: 1-10 December, 1999
Integration area and radar sites
Observation fit statistics
Verification of time-series of +24 h wind
forecasts(against observations)
Some differences fromglobal NWP setups
Higher resolution model (and focus on shorter forecast ranges, other verification measures)
Limited area: inflow of information from lateral boundaries - impact of obs. system decreases with forecast range less representative results than global systems for same period length
Cutoff time shorter (some types of satellite data and some radiosondes arrive late)
Uses less satellite data operationally (limited resources)
relative importance of radiosonde vs satellite larger may change with development of assimilation scheme
HIRLAM impact studies for EUCOS; met.no
Extra
Studies performed at DMI and met.no, observation scenarios specified from EUCOS
Two periods: December 2004-January 05 (storms passing Northern Europe), August 2005
HIRLAM 3D-Var with AMSU+Scatt+Meteosat AMV
Temps available(a typical analysis time)
Baseline
CTR
Bas + E-ASAPs
(Rejections are due to scenario selection,but also due to thinning, QC or arrival afteranalysis cutoff)
Red=rejected
Results – all scenarios, winter period
Control Scenario(all available in-situ observations)
Baselinescenario
Add E-ASAPs
Add AIREPs
Radiosondes: Add E-ASAP to baseline (incl Mike, Ekofisk, winter)
“ScandinavianStorms”
EUCOS studies met.no; conclusions Conventional observations have large positive impact in our system TEMPs dominating factor for analysis quality in precense of satellite
data, wind more than temperature (but developments ongoing towards more use of satellite: AMSU over land, advanced sounders, …)
No significant effect of adding moisture information (could also be seen as an assimilation algorithm problem)
Aicraft data complement TEMPs (positive impact of adding aircraft in the presence of sondes), but to much larger degree in winter (by chance?)
Negative impact from EWP: revising QC and data selection did not help (more work needed?)
Significant positive impact from E-ASAP network (also excluding Mike+Ekofisk)
HIRLAM Comprehensive Impact studies (CIS) – basic ideas
Try to advance the use of remote sensing data in HIRLAM through a few coordinated “Great Leaps” with participation from several HIRLAM groups Prepare the operational utilization of all types of new data in parallel with the impact studies; Data transmission and collection, data pre-processing, bias corrections etc. Provide instructions for the other national NWP groups
HIRLAM Atlantic scale CIS – model setup
HIRLAM RCR domain
HIRLAM reference 7.2RCR domain 16 km hor. resolution60 levels4D-Var, 6 h assimilation window48 km assimilation increrments
HIRLAM Atlantic scale CIS -Experiments
BASELINE = HIRLAM reference = Radiosonde data + SYNOP + SHIP + DRIBU + AIREP + AMDAR + AMSU-A over sea
ALLINCLUSIVE = BASELINE + AMSU-A over ice and land + AMSU-B over sea + QUICKSCATT winds + AMV GEO + AMV MODIS
DENIAL 1 (exclude AMSU-A over ice and land from ALLINCLUSIVE)DENIAL 2 (exclude AMSU-B over sea from ALLINCLUSIVE)etc.
CONVENTIONAL = BASELINE – AMSU-A over sea
To be finished by Summer 2008!
HIRLAM Atlantic scale CIS -Forecast verification 1
BASELINE versus ALLINCLUSIVE
Note: Impact at +48h is much stronger, but experiments where this was seen were not completely clean (slightly differing forecast models). Will be re-run in a clean way!
Verificationarea:Europe
HIRLAM Atlantic scale CIS -Forecast verification 2
BASELINE versus ALLINCLUSIVE
AreaEurope
HIRLAM Atlantic scale CIS -Forecast verification 3
BASELINE versus ALLINCLUSIVE
Verification area:UK andIreland
Surface pressure forecast differences for one case of strong impact – 6 February 2007 12 UTC. Needs to be further analyzed, in particular with data denial experiments.
+18 h +12 h
+06 h +00 h
HIRLAM Summer time convection CIS
Select a summer month, based on data availability (radar radial wind data)European area with 10 km hor. resolution (5 km later)Observations as in the Atlantic scale CIS + Radar radial winds + Groundbased GPS zenith delays + SEVIRI cloud-free water vapor radiance data
(To be prepared during summer 2008 and to be run during autumn 2008)
Concluding remarks
HIRLAM efforts have been quite advanced in development of observation operators for new types of remote sensing data and in impact studies with these data. Operational HIRLAM applications has not had sufficient benefit from these research and development efforts. A series of Comprehensive Impact Studies (CIS) has the ambition to change this – first results are promising! The HIRLAM community is on the move to the ECMWF IFS world – one main motivation is the advanced use of remote sensing data at ECMWF
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