© Crown copyright Met Office Impact experiments using the Met Office global and regional model...

© Crown copyright Met Office

Impact experiments using the Met Office global and regional model

Presented by Richard Dumelow

to the WMO workshop, Geneva, 19th May 2008


Collaborators

• Keir Bovis

• Gareth Dow

• Richard Dumelow

• Bruce Ingleby

• Bruce MacPherson et al


Contents

This presentation covers the following areas:

• Space-terrestrial link

• Global data denial

• Data targeting

• Increasing the use of surface data

• Observation impact experiments in the regional models


Space-terrestrial link

Richard Dumelow


Conventional observations in baseline


Space-terrestrial runs

• Baseline with all satellite data, buoy data, GUAN and GCOS stations (BASE).

• Baseline + all other data (COMB).

• Baseline + all aircraft data (BPAIR)

• Baseline + all non-GUAN radiosonde T, v (BPGTW)

• Baseline + all non-GUAN radiosonde v


Space-terrestrial – experimental set up

• Winter and summer periods:

• Winter period: 4/12/04 -> 27/01/05.

• Summer period: 5/7/05 -> 15/9/05.

• Global and limited area (NAE) model used.

• 4D-Var in global and 3D-Var in NAE.

• 6-day forecasts from 00 UTC and 12 UTC.

• Verification against observations and COMB analysis.


North Atlantic European (NAE) area


COMB vs BASE

T+48

T+144


Winter

Summer

Northern

hemisphere RMS

error with height vs

analysis

Temperature Wind

COMB vs BASE

Global model


Temperature Wind

Winter

Summer

NAE model

RMS error with

height over

Europe vs

radiosondes

COMB vs BASE


Temperature Wind

Winter

Summer

COMB vs ALL

Global model

Northern

hemisphere RMS

error vs analysis

at 500 hPa


Temperature Wind

Winter

Summer

COMB vs ALL

NAE model

RMS error over

Europe vs

radiosondes at

500 hPa


Global data denial

Richard Dumelow


Global denial experiment

• Met Office operational system as at October last year.

• Full resolution, 4D-Var.

• Forecasts from 12UTC out to 5 days.

• Verification of standard fields against observations and ‘All data’ analysis.

• One month summer period: 24/5/07 -> 24/6/07.


Global data denial runs1. All data

2. All data – all satellite

3. All data – all radiosonde

4. All data – all aircraft

5. All data – all surface

6. All data – all conventional (satellite only)

7. All data – European wind profilers


Targeting Experiments

Keir Bovis, Gareth Dow, Richard Dumelow


Targeting experiments

• ‘Subjective’ targeting

• ‘Objective’ targeting

• ‘Real’ targeting


Subjective targeting – OSE BASE+ALL

87 Sonde Stations in Total

Verification Region


Subjective targeting – OSE BASE

17 Stations in Total (~ 1 per 10o Box)

(none in verification region)

Verification Region


Subjective targeting – OSE BASE+UPS

27 Stations in Total

(17 Baseline + 10 Upstream)


Subjective targeting – results, T+12 and

T+24 temperature

VE

RIF

VE

RIF

UP

S

VE

RIF

VE

RIF

UP

S


Subjective targeting – case study:

(ex-)Hurricane Rita

Track of Hurricane Rita

Verification Region

12Z 24th 960 hPa


Subjective targeting – case study results: T+12 MSLP forecasts for 12Z 24th Sep

• Sparse network incorrectly locates Hurricane Rita and underestimates it’s intensity

BASE+ALL

(958 hPa)

BASE

(983 hPa)

X marks NHC best estimate of

Rita’s central position (960 hPa)


Objective targeting – the main elements in observation targeting

Adapted from Doerenbecher et. al., 2004.


Objective targeting - results

Objective targeting match

or out-perform

performance at target

forecast range of

subjective approaches.


Objective targeting - results

OSE T+12 T+24 T+36 T+48

base+T36

90% 85% 60% 50%

ETKF(48)

75% 75% 70% 55%

ETKF(24)

75% 75% 75% 45%• Table shows the percentage number of forecast fields with a reduced forecast RMS error

compared to corresponding fields in OSE base+ups used as a baseline.

• Objective targeting using ETKF with shortest lead time (ETKF(24)) shows the best performance at the target forecast range 36 hours.

• Results for subjective targeting (base+T36) are improved in the short-range highlighting the variability of approach with less accurate flow analyses.

Target forecast range


The Greenland Flow Distortion Experiment (GFDex) – real targetingIan Renfrew, University of East AngliaSue Gray, University of Reading

• Targeted observations comprise dropsondes deployed from the FAAM aircraft in sensitive areas identified on targeting guidance.

• Met Office targeting guidance is produced twice a day using the Ensemble Transform Kalman Filter (ETKF) with different lead and optimisation times.

4848

3636

24482460

4848

3636

24242436

Opt Time

Lead Time

Opt Time

Lead Time

12Z00Z


GFDex targeting cases - (24 February 2007 - 10 March 2007)


GFDex OSE impact – headline results

Verification over NW Europe and UK Verification over Scandinavia

Two verification regions were identified, NW Europe (inc. UK) shown in blue and Scandinavia shown in red.


Increasing the use of surface data

Bruce Ingleby


Met Office usage of Synops to March 2008

• Global: P* (Ships P*, wind)

• Use hourly Synops (3 hour window) (2007)

• LAMs: P*, T, RH, wind, log(vis) - hourly

• LAM height limit for T, RH 200 → 500 (2003)

• Obs monitoring by station with monthly updates to rejections and pressure correction

• Improvements in resolution and land surface modeling improve O-B and make global assimilation of Synop T/RH/wind feasible


Met Office usage of Synops from 2 April 2008• Synop: P*, T, RH, wind† (6 hr window) - hourly

• dht=(stn height-model height): limit for T, RH, wind of ±500m (-500 to 250m at night)

• † Tropical and unresolved island winds omitted

• RH height adjustment of 0.01%/m

• Wind speed scaling for dht > 100 m

• Ship/Buoy: P*, wind, T, RH used hourly

• Drifting buoy still limited to P*

• Nudging of soil temperatures

• Gl/LAM usage v. similar now, Gl changes red


4D-Var June 2007, Opt 1 & 2


Ver vs Synop T: NH and SH


Observation impact experiments in the regional models

Bruce MacPherson et al


Regional model impacts

Positive impact from:

• Weather radar winds

• Cloud

• Visibility


Weather radar – VAD winds

• Currently

• assimilated 61

• rejected 26


VAD wind impact experiment3-week 24km NAE 4DVAR test, autumn 2006

CNTL

noVAD

mean

pmsl

rms

pmsl


VAD wind impact experiment • Pmsl benefit statistically significant when error bars

computed for mean difference in CNTL / noVAD errors


Cloud assimilationMOPS cloud data

• impact of nudging scheme

• significant benefit in Sc episodes (eg Feb ’06)

NO MOPS cloud

Control

rms T2mrms cloud cover

One weekUK MesTrial


Spring 2005 4D-Var VIS v

NO VIS


Summary of main results


Main results from Met Office impact studies

• The space-based system has become increasingly important.

• The conventional (ground based) observing system is an essential compliment to the space-based system.

• Upstream targeting is effective but getting a large positive impact from North Atlantic targeted observations over Europe is difficult.

• In-situ observations of surface parameters have positive impact particularly in higher resolution models.


Questions and answers

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