overview of data impact studies within the hirlam community nils gustafsson and harald schyberg with...

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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

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Page 1: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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

Page 2: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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

Page 3: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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

Page 4: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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

Page 5: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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?

Page 6: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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

Page 7: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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)

Page 8: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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!

Page 9: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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

Page 10: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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)

Page 11: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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

Page 12: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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

Page 13: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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

Page 14: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

Results – all scenarios, winter period

Control Scenario(all available in-situ observations)

Baselinescenario

Add E-ASAPs

Add AIREPs

Page 15: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

Radiosondes: Add E-ASAP to baseline (incl Mike, Ekofisk, winter)

“ScandinavianStorms”

Page 16: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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)

Page 17: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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

Page 18: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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

Page 19: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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!

Page 20: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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

Page 21: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

HIRLAM Atlantic scale CIS -Forecast verification 2

BASELINE versus ALLINCLUSIVE

AreaEurope

Page 22: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

HIRLAM Atlantic scale CIS -Forecast verification 3

BASELINE versus ALLINCLUSIVE

Verification area:UK andIreland

Page 23: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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

Page 24: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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)

Page 25: Overview of data impact studies within the HIRLAM community Nils Gustafsson and Harald Schyberg with contributions from Bjarne Amstrup, Carlos Geijo, Xiang-Yu

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