Performance of Global Forecast System

NCMRWF/IMD(INDIA)

Presentation for Annual performance evaluation of NCEP production suite at NCEP, Maryland, USA during 6-8 December 2011

Care-takers• NCMRWF• Data/monitoring: Munmun Das Gupta,

Indira Rani• Analysis : V S Prasad• Model/post : Saji Mohandas• Verification : Gopal Iyengar• GEFS : E N Rajagopal• IMD

• Data/monitoring: S D Kotal • Analysis/Model/Verfication : V R Durai• Co-ordinator : S.K.Roy Bhowmik

Numerical Weather Prediction System of NCMRWF

Global ObservationsData Reception

Global Data Assimilation

Forecast Models

Users

SURFACE from land stations

Upper Air RSRW/ PIBAL

SHIP

BUOY

Aircraft

Satellite

High Resolution Satellite Obsn Internet (FTP)

RTH, IMD

GTS

NCMRWF OBSERVATION PROCESSING

NKN24x7

NESDIS EUMETSAT

45mbpsproposed dedicated link

Observation quality checks & monitoring

4 times a day for 00,06,12,18 UTC

Global Analysis (GSI)

Initial state

Global Forecast Model ( 9hr Fcst – first guess )

Global Model T574L64

10day FCST

Meso-scale Data Assimilation & Model

Statistical Interpolation Model (location specific FCST)

once in a day for 00 UTC

Visuali-sation

IMD

INCOIS

Other sectors

NKN

NKN

ISRO(MT)

Model Version Horizontal Resolution

Forecast Length

Performance

GFS T382L64

GFS version 9.0.1

~35km 168 Hrs (3hr data cutoff)

4 min. for 24 hr forecast (IBM-P6 16 nodes)

GFS T574L64

GFS version 9.0.1

~23km 240 Hrs (5hr data cutoff)

9 min. for 24 hr forecast (IBM-P6 16 nodes)

GEFST190L28

Latest version20 members

~70km 240 Hrs (Not operational)

6 min. For 24 hr forecast (IBM-P6 8 nodes)

GFS Models (NCMRWF) – Current status

High Performance Computing Systems

HPC Connectivity

No of Processorsavailable

Per node memory

Processor speed

IBM Power 6

Infini Band 38x32 (NCMRWF)24x32 (IMD)

4x32 GB 4.7 Gflops

Recent developments in NCMRWF GFS system

Implementation of the T382L64 GFS from May 2010(latest versions of upgraded model and GSI)

Assimilation of additional data in T382L64 GFSThe Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) windsRainfall rates (TRMM, SSMI)NOAA19 radiancesAtmospheric Infrared Sounder (AIRS) radiancesGPSRO (COSMIC)

Implementation of the T574L64 GFS from mid-November, 2010 (July 2010 Version)

Implementation of latest NCEP version of T574L64 (from June, 2011)

The T382L64 GFS was implemented in May 2010.

The T574L64 GFS was first implemented in November 2010.

T382L64 performance was evaluated during Monsoon 2010 and was found to marginally better than the T254L64 GFS. T254L64 stopped.

T574L64 performance was evaluated during November-December 2010 and was found to better than the T382L64 GFS.

T382L64 model was run parallel to T574L64 for Monsoon 2011

The latest version of the NCEP T574L64 GFS was implemented in May 2011 and found to be better than T382L64 system

T382L64 run stopped from November 2011

End-to-end T574L64 GFS system was transferred to IMD on 15 November, 2011

Time line - NCMRWF GFS

Physics T382L64 T574L64Surface Fluxes Monin-Obukhov similarity Monin-Obukhov similarity

Turbulent Diffusion Non-local Closure scheme (Hong and Pan (1996) Non-local Closure scheme (Lock et al., 2000)

SW Radiation Based on Hou et al. 2002 –no aeroslos – invoked hourly Rapid Radiative Transfer Model (RRTM2) (Mlawer et al. 1997; Mlawer and Clough, 1998)- aerosols included– invoked hourly

LW Radiation Rapid Radiative Transfer Model (RRTM) (Mlawer et al. 1997). –no aerosols- invoked 3 hourly

Rapid Radiative Transfer Model (RRTM1) (Mlawer and Clough 1997;1998). –aerosols included-invoked hourly

Deep Convection SAS convection (Pan and Wu (1994) SAS convection (Han and Pan, 2006)

Shallow Convection Shallow convection Following Tiedtke (1983) Mass flux scheme (Han and Pan, 2010)

Large Scale Condensation

Large Scale Precipitation (Zhao and Carr ,1997; Sundqvist et al., 1989)

Large Scale Precipitation (Zhao and Carr ,1997; Sundqvist et al., 1989)

Cloud Generation Based on Xu and Randall (1996) Based on Xu and Randall (1996)

Rainfall Evaporation Kessler (1969) Kessler (1969)

Land Surface Processes NOAH LSM with 4 soil levels for temperature & moisture (Ek et al., 2003)

NOAH LSM with 4 soil levels for temperature & moisture (Ek et al., 2003)

Air-Sea Interaction Roughness length by Charnock (1955)Observed SST,Thermal roughness over the ocean is based on Zeng et al., (1998).3-layer Thermodynamic Sea-ice model (Winton, 2000)

Roughness length by Charnock (1955), Observed SST, Thermal roughness over the ocean is based on Zeng et al., (1998). 3-layer Thermodynamic Sea-ice model (Winton, 2000)

Gravity Wave Drag & mountain blocking

Based on Alpert et al. (1988) Lott and Miller (1997), Kim and Arakawa (1995), Alpert et al., (1996)

Vertical Advection Explicit Flux-Limited Positive-Definite Scheme (Yang et al., 2009)

Physical Parameterization schemes in T382L64 and T574L64

New observations assimilated Improvements in Data Assimilation system

Inclusion of METOP IASI (Infrared Atmospheric Sounding Interferometer) data

Use of variational qc

Reduction of number of AIRS (Atmospheric Infrared Sounder) water vapor channels used

Addition of background error covariance input file

Assimilating tropical storm pseudo sea-level pressure observations,

Flow dependent reweighting of background error variances

NOAA-19 HIRS/4 (High Resolution Infrared Radiation Sounder) and AMSU-a (Advanced Microwave Sounding Unit) brightness temperature,

Use of new version and coefficients for community radiative transfer model (CRTM -2.02 )

NOAA-18 SBUV/2, (Solar Backscatter Ultraviolet Spectral Radiometer) Ozone , EUMETSAT-9 atmospheric motion vectors.

Improved Tropical Cyclone Relocation

Using uniform thinning mesh for brightness temperature data.

Change in land/snow/ice skin temperature variance

Improving assimilation of GPS radial occultation data. RE-tuned observation errors.

ASCAT (Advanced Scatterometer) winds included

Korean AMDAR data and more number of Aircraft

Reports

European Wind profiler data

Differences of the T574L64 GSI Data Assimilation system compared to T382L64

Observation category Name of Observation.

Surface Land surface, Mobile, Ship, Buoy (SYNOPs)

Upper air TEMP (land and marine), PILOT (land and marine), Dropsonde, Wind profiler

Aircraft AIREP, AMDAR, TAMDAR, ACARS

Atmospheric Motion Vectors from Geo-Stationary Satellites

AMV from Meteosat-7, Meteosat-9, GOES-11, GOES-13, MTSAT-1R, MODIS (TERRA and AQUA),

Scatterometer winds ASCAT winds from METOP-A satellite,

NESDIS / POES ATOVS Sounding radiance data

1bamua, 1bamub, 1bmhs,1bhirs3, 1bhirs4

Satellite derived Ozone data NESDIS/POES, METOP-2 and AURA orbital ozone data 

Precipitation Rates NASA/TRMM (Tropical Rainfall Measuring Mission) and SSM/I precip. rates

Bending angles from GPSRO Atmospheric profiles from radio occultation data using GPS satellites

NASA/AQUA AIRS & METOP/ IASI brightness temperature data

IASI,AIRS,AMSR-E brightness temperatures

Types of observations Assimilated in GFS

Observation Type

June July August September

SYNOP 143 139 142 136

RS/RW 33 33 37 39

PILOT 31 25 22 23

AWS 544 719 552 690

ARG 195 424 308 357

BUOY 10 10 11 10

Count of different types of observations over Indian Region(received at NCMRWF at 00 UTC from 1 to 25 of months June, July,

August, and September 2011)

Data Reception: NCMRWF vs ECMWF (S-W Monsoon, 2011)(Average number of observations received in 24 hours )

RED COLOUR INDICATES LESS DATA ; BLUE COLOUR INDICATES COMPARABLE DATA

June July August

NCMRWF ECMWF NCMRWF ECMWF NCMRWF ECMWF

SYNOP/SHIP Pressure

46,118 78,390 56,734 78,481 57,607 78,574

BUOY (Drifter) 10,715 13,953 13,882 13,879 13,752 13,531

TEMP 500 hPa Geopotential

1,088 1,286 1,271 1,286 1,320 1,336

TEMP/PILOT 300 hPa Wind

1,098 1,434 1,300 1,429 1,349 1,490

AIRCRAFT winds (300-150 hPa)

58,412 1,04,987 72,842 1,02,562 72,685 1,03,059

AMV winds (400-150 hPa)

2,00,283 10,06,280 2,55,690 9,78,269 2,43,282 9,45,691

AMV winds (1000-700 hPa)

1,28,786 8,53,193 1,54,724 8,91,204 1,52,905 8,21,724

Vertical Profile of T574L64 (Dotted Line) and T382L64 (Bold Line) Analyses (Black) and First Guess (Red) Vector Wind Fits (Bias and RMSE) to RAOBS over Global for JJAS, 2011. The Right Panel graph gives the observation data counts over the region used for the comparison.

Vertical Profile of T574L64 (Dotted Line) and T382L64 (Bold Line) Analyses (Black) and First Guess (Red) Vector Wind Fits (Bias and RMSE) to RAOBS over Tropics for JJAS, 2011. The Right Panel graph gives the observation data counts over the region used for the comparison.

Vertical Profile of T574L64 (Dotted Line) and T382L64 (Bold Line) Analyses (Black) and First Guess (Red) Moisture Fits (Bias and RMSE) to RAOBS over Global for JJAS, 2011. The Right Panel graph gives the observation data counts over the region used for the comparison.

Vertical Profile of T574L64 (Dotted Line) and T382L64 (Bold Line) Analyses (Black) and First Guess (Red) Moisture Fits (Bias and RMSE) to RAOBS over Tropics for JJAS, 2011. The Right Panel graph gives the observation data counts over the region used for the comparison.

Vertical Profile of T574L64 (Dotted Line) and T382L64 (Bold Line) Analyses (Black) and First Guess (Red) Temperature Fits (Bias and RMSE) to RAOBS over Global for JJAS, 2011. The Right Panel graph gives the observation data counts over the region used for the comparison.

Vertical Profile of T574L64 (Dotted Line) and T382L64 (Bold Line) Analyses (Black) and First Guess (Red) Temperature Fits (Bias and RMSE) to RAOBS over Tropics for JJAS, 2011. The Right Panel graph gives the observation data counts over the region used for the comparison.

Global Circulation Features

NCEP

NCMRWF

Day 05 Forecast Errors 850 hPa Zonal Wind JJA 2011

Regional Circulation Features

T382

T574

ANA D03 ERR

ANA D05 ERR

T382

T574

ANA D03 ERR

T382

T574

D05 ERRANA

T382

T574

ANA D03 ERR

T382

T574

T382

T574

ANA D05 ERR

T382

T574

T382

T574

T382

T574

T382

T574

VERIFICATION AGAINST ITS OWN ANALYSIS

Models: T574, T382 and UKMO

Parameters : Zonal & Meridional Wind, Geo-potential Height, Temperature, Relative Humidity

forecast and analysis fields used are valid for 00UTC and the forecasts are based on initial condition valid for 00UTC.

computed the scores using the data at 1 degree resolution from all the models.

T382

T574

UKMO

T574

T382

UKMO

850 hPa 200 hPa

Model Day1 Day3 Day5 Day1 Day3 Day5

T382 2.9 3.0 4.3 4.6 5.9 6.7

T574 2.5 3.5 4.0 4.3 5.4 6.0

UKMO 2.1 3.8 3.5 3.0 4.3 5.1

RMSE against own analysis 850 hPa Zonal Wind

850 hPa 200 hPa

Model Day1 Day3 Day5 Day1 Day3 Day5

T382 2.6 3.3 3.7 4.1 5.0 5.5

T574 2.2 3.1 3.6 3.9 4.8 5.3

UKMO 1.9 2.7 3.2 2.7 3.7 4.3

RMSE against own analysis 850 hPa Meridonal Wind

Factors and methods used In standardized verificatlon of NWP products

 Verification agalnst analysis 

Area Northem hemisphere extratropics (90°N ‑ 20°N )(all inclusive) Tropics (20°N ‑ 20°S)(all inclusive) Southem hemisphere extratropics (20°S ‑ 90°S)(all inclusive)Grid Verifying analysis is the centre's on a latitude‑longitude grid 2.5° x 2.5°; origin (0°,0°)Variables MSL pressure, geopotential height, temperature, windsLevels Extratropics: MSL, 500 hPa, 250 hPa Tropics: 850 hPa, 250 hPaTime 24h, 48h, 72h, 96h,120h,144h,168h,192h, 216h, 240h ...Scores Mean error, root‑mean‑square error (rmse), anomaly correlation, S1 skill score, root‑mean‑square vector wind error (rmseV)

Verification against observationsThe seven networks used in verification against radiosondes consist of radiosondes stations Iying within the following geographical area:

North America 25°N ‑ 60°N  50°W ‑ 145°WEurope/North Africa 25°N ‑ 70°N  10°W ‑ 28°EAsia                                25°N ‑ 65°N  60°E ‑ 145°EAustralia/New Zealand 10°S ‑ 55°S  90°E ‑ 180°EAustralia/New Zealand 10°S ‑ 55°S 90°E ‑ 180°ETropics 20°S ‑ 20°N all longitudesN. Hemisphere Extratropics 20°N ‑ 90°N  all longitudesS.Hemisphere Extratropics  20°S ‑90°S all longitudes

    

The anomaly correlation values are comparatively higher in the T574 GFS with a gain of 1 day in the skill of the forecasts.

In the lower panel the line plot depicts the difference of the forecasts of Geopotential Height of the T574 GFS from the T382 GFS.

The difference values outside the histograms are statistically significant at 95% level of confidence.

Anomaly correlation of 10 day forecasts of 500 hPa Geopotential Height over the Northern Hemisphere from the T382 (black line) and T574 (red line) GFS

The RMSE values are comparatively lower in the T574 GFS with a gain of 1 day in the skill of the forecasts.

In the lower panel the line plot depicts the difference of the forecasts of Zonal Wind of the T574 GFS from the T382 GFS.

The difference values outside the histograms are statistically significant at 95% level of confidence.

RMSE of 10 day forecasts of 850 hPa Zonal Wind over the Regional Specialized Meteorological Centre (RSMC) region from the T382 (black line) and T574 (red line) GFS

Verification of Day 01-05 Forecast against Observations over Tropics

Root Mean Square Error (RMSE) 850 hPa winds in m/s

JUNE 2011

Model Day 1 Day 2 Day 3 Day 4 Day 5

ECMWF 3.6 3.7 4.0 4.2 4.5

UKMO 3.7 4.0 4.4 4.8 5.0

NCEP 3.8 4.2 4.5 4.8 5.0

NCMRWFT574

3.8 4.1 4.5 4.7 4.9

0

12

34

56

78

9

Jan

-05

May

-05

Sep

-05

Jan

-06

May

-06

Sep

-06

Jan

-07

May

-07

Sep

-07

Jan

-08

May

-08

Sep

-08

Jan

-09

May

-09

Sep

-09

Jan

-10

May

-10

Sep

-10

Jan

-11

May

-11

Sep

-11

RM

SE

V

T80 T254 T382 T574

Verification of Day 03 Forecasts against Radiosondes over India (2005-2011)Root Mean Square Error (RMSE) of 850 hPa winds in m/s

Monsoon Depressions

Track Errors

0

100

200

300

400

500

600

700

Day-1 Day-2 Day-3 Day-4 Day-5

Days

Err

or (i

n K

m) AVE FTE T574

FTE 11 to 12june11FTE 16 to 22june11FTE 22 to 23july11FTE 22 to 23sep11

VECTOR ERROR (Km) IN THE PREDICTED TRACK OF THE FOUR SYSTEMS DURING JJAS 2011

0

100

200

300

400

500

Day-1 Day-2 Day-3 Day-4 Day-5

Days

Err

or (i

n K

m)

T574

T382

VECTOR ERROR (Km) IN THE PRECDICTED TRACK OF THE FOUR SYSTEMS DURING JJAS 2011

050

100150200250300350400450

Day-1 Day-2 Day-3 Day-4 Day-5

Days

Erro

r in

(Km

)

UKMO

T574

T382

RAINFALL FORECAST VERIFICATION DURING MONSOON 2011:T382,T574 & UKMO

• A detailed and quantitative rainfall forecast verification has been made using the IMD's 0.5° daily rainfall data for the entire period of JJAS 2011.

Model Day-1 Day-3 Day-5

T574 0.90 0.82 0.73

T382 0.81 0.79 0.72

UKMO 0.91 0.86 0.80

UKMO

T382

T574

Seasonal (a), Monthly (b) and weekly (c) rainfall (mm) predicted by T574L64 model for Monsoon-2011 against observed and long period average (climatology). Weekly rainfall is accumulated 7-day forecast

from single initial conditions of every week.

Forecasts of rain meeting or exceeding specified thresholds

For binary (yes/no) events, an event ("yes") is defined by rainfall greater than or equal to the specified threshold; otherwise it is a non-event ("no").

The joint distribution of observed and forecasts events and non-events is shown by the categorical contingency table.

hits false alarms

misses correct rejections

OBSERVED

YES NO

YES

NOFORECAST

FORECAST YES

FORECAST NO

OBSERVED YES OBSERVED NO

0.01 1 2 3 4 50

0.2

0.4

0.6

Day-1 Rainfall Forecast

T382T574UKMO

Rainfall Threshold(cm/day)

ET

S

0.01 1 2 3 4 50

0.2

0.4

0.6

Day-3 Rainfall Forecast

Rainfall Threshold(cm/day)

ET

S

0.01 1 2 3 4 50

0.2

0.4

0.6

Day-5 Rainfall Forecast

T382T574UKMO

Rainfall Threshold (cm/day)

ET

S

0.01 1 2 3 4 50

0.2

0.4

0.6

Day-1 Rainfall Forecast

T382T574UKMO

Rainfall Threshold(cm/day)

ET

S

0.01 1 2 3 4 50

0.2

0.4

0.6

Day-3 Rainfall Forecast

Rainfall Threshold(cm/day)

ET

S

0.01 1 2 3 4 50

0.2

0.4

0.6

Day-5 Rainfall Forecast

T382T574UKMO

Rainfall Threshold (cm/day)

ET

S

ETS for the predicted rainfall during JJAS 2011

IMD GFS Verification - Areas

1) ALL-INDIA (Lon: 68 E – 98E, Lat: 9N – 37N)

2) Central India (Lon: 75E – 80E, Lat: 19 – 24N)

3) East India (Lon: 83E -88E, Lat: 20N -25N)

4) North East India (Lon: 90E – 95E, Lat: 24N -29N)

5) North West India (Lon: 75E – 80E, Lat: 25N -30N)

6) South Peninsula India (Lon: 76E - 81E, Lat: 12N- 17N)

7) West Coast of India (Lon: 70E - 75E, Lat: 13N - 18N)

ALL INDIA: Weekly Cumulative Rainfall

0

30

60

90

120

Rai

nfal

l in m

mOBS

T382(CC=0.79)

T574(CC=0.83)(Lon: 68 E – 98E, Lat: 9N – 37N)

ALL India : Weekly Cumulative Rainfall

Central- INDIA:Cumulative Rainfall

0

30

60

90

120

150

180

Rain

fall in

mm

OBS

T382(CC=0.77)

T574(CC=0.76)

NORTH WEST- INDIA:7 day cum. rain

0

30

60

90

120

150

Rain

fall in

mm

OBS

T382(CC=0.68)

T574(CC=0.80)(Lon: 90E – 95E, Lat: 24N -29N)

(Lon: 75E – 80E, Lat: 19 – 24N)

NORTH EAST- INDIA:7 day cum. rain

0

50

100

150

200

250

Rain

fall in

mm

OBS

T382 (CC=0.64)

T574(CC=0.69)

EAST- INDIA:7 DAY CUM RAINFALL

0

50

100

150

200

250

Rain

fall in

mm

OBS

T382 (CC=0.47)

T574 (CC=0.75)(Lon: 83E -88E, Lat: 20N -25N)

(Lon: 75E – 80E, Lat: 25N -30N)

WEST COAST OF INDIA:7 day Cum Rain

0

50

100

150

200

250

300

350R

ain

fall in

mm

OBS

T382(CC=0.69)

T574(CC=0.74)

SP- INDIA: 7day Cum Rain

0

20

40

60

80

100

Rain

fall in

mm

OBS

T382(CC=0.56)

T574(CC=0.71)

(Lon: 70E - 75E, Lat: 13N - 18N)

(Lon: 76E - 81E, Lat: 12N- 17N)

CC: 7 DAY CUM RAIN T382 &T574

0.3

0.4

0.5

0.6

0.7

0.8

0.9

CENTRALINDIA

NW INDIA NE INDIA EAST INDIA SP INDIA WESTCOASTINDIA

ALLINDIA

T382

T574

CC :7 Day Cumulative Rainfall of GFS T382 &T574 vs. Observation

CENTRAL INDIA

0

0.3

0.6

0.9

DAY-1 DAY-2 DAY-3 DAY-4 DAY-5

CC

IMDT382

IMDT574

East india

0

0.2

0.4

0.6

0.8

1

DAY-1 DAY-2 DAY-3 DAY-4 DAY-5

CC

IMDT382

IMDT574

NE-INDIA

0

0.2

0.4

0.6

0.8

1

DAY-1 DAY-2 DAY-3 DAY-4 DAY-5

CCIMDT382

IMDT574

WEST COAST OF INDIA

0.2

0.4

0.6

0.8

1

DAY-1 DAY-2 DAY-3 DAY-4 DAY-5

CC

IMDT382

IMDT574

SP INDIA

0

0.2

0.4

0.6

0.8

DAY-1 DAY-2 DAY-3 DAY-4 DAY-5

CC

IMDT382

IMDT574NW INDIA

0.2

0.4

0.6

0.8

1

DAY-1 DAY-2 DAY-3 DAY-4 DAY-5

CC

IMDT382

IMDT574

(Lon: 70E - 75E, Lat: 13N - 18N) (Lon: 76E - 81E, Lat: 12N- 17N)

(Lon: 83E -88E, Lat: 20N -25N) ((Lon: 75E – 80E, Lat: 19 – 24N)(Lon: 90E – 95E, Lat: 24N -29N)

(Lon: 75E – 80E, Lat: 25N -30N)

GFS T574 : 168 -72 hr F/c shows a FALSE ALARM of Cyclonic Storm over Arabian sea on 6 June 2011

Analysis of 6 June 2011

(Lon: 90E – 95E, Lat: 24N -29N)

N-EAST INDIA

-6

-4

-2

0

2

4

6

Erro

r in

deg

C

DAY-1

DAY-2

DAY-3

DAY-4

DAY-5

Error in Tmax : N-EAST INDIA

-10

-8

-6

-4

-2

0

2

4

6

1JUNE2011

7 13 19 25 1JULY2011

7 13 19 25 31 6AUG2011

12 18 24 30 5 SEP2011

11 17 23 29

Erro

r in

deg

CDAY-1

DAY-2

DAY-3

DAY-4

DAY-5

(Lon: 75E – 80E, Lat: 25N -30N)

Tmax (Top) and Tmin (bottom) over North-East India

Both Tmax and Tmin mostly under predicts in all 4 months i.e. from 1June to 30 Sep 2011

GFS T574: Daily Error in Maximum and Minimum Temperature over North-East India

MAE :for Tmin (1 June-30 September 2011)

0

1

2

3

4

5

CENTRALINDIA

EAST INDIA NE INDIA NW INDIA SP INDIA WESTCOAST OF

INDIA

Te

mp

in

de

g C

DAY-1

DAY-2

DAY-3

DAY-4

DAY-5

MAE for Tmax (1 June -30 September 2011)

0

1

2

3

4

5

CENTRALINDIA

EASTINDIA

NE INDIA NW INDIA SP INDIA WESTCOAST

OF INDIA

Tem

pera

ture

in

deg

C

DAY-1

DAY-2

DAY-3

DAY-4

DAY-5

GFS T574: Seasonal Mean Error in Maximum and Minimum Temperature over different Homogeneous regions of India

Mean Absolute Error(MAE) of Tmax (top)and Tmin (bottom)

For 1 June to 30September,2011

Conclusions• The vertical profile of T574L64 analyses and first guesses fits to

radio-sonde observation for JJAS 2011 shows improvement over T382L64 analyses.

• The RMSE values of fields of T574L64 forecasts against analyses and observations show improvements over T382L64 forecasts

Equitable Threat Square (ETS) computed for different rainfall thresholds shows that UKMO has higher skill score as compared with T382 and T574 for rainfall threshold >1.0 cm/day. For rainfall intensity of 0.01 cm/day all three models feature high ETS (>0.6) for all days forecast. T574 shows better skill score then T382 for all the rainfall intensities for all days.

The impact of more satellite data incorporated in T574L64, especially the AMVs over the tropics, is more evident in T574L64 analysis and forecasts when compared to the T382L64 system.

Future data plans (NCMRWF)

• VAD winds from Indian Doppler Weather Radar.• Oscat winds (Oceansat-2 scatterometer)• INSAT / Kalpana AMV• Precipitation rates from MADRAS-MT• GEOS Sounder data• Radiances from INSAT-3D and MT• Preparing plans for Indian Doppler Weather Radar

NCMRWF wish list

• Future NCEP upgrades in dynamics/physics?• Higher resolutions? (T764L91? T1148L91/

Semi_Lagrangian?)• Diversification ? (GEFS, Hybrid GSI-EnKF VA

system)• More diagnostics and verifications?• Sensitivity studies and physics

improvements?• Participation in National/international

compaigns/experiments? (MJOWG, MT)

IMD plans

• GFS T 574

• EPS T 382

• MME based on EPS

Thrust Area: Probabilistic Forecast of high impact weather in short to medium range time scale

Hurricane WRF ModelThe HWRF model has been implemented at the India Meteorological Department (IMD) following the Implementation Agreement (IA) between India’s Ministry of Earth Sciences (MoES) and USA’s National Oceanic and Atmospheric Administration (NOAA) with an objective to provide improved tropical cyclone prediction capability for the Bay of Bengal and Arabian Sea regions.

Under the program Dr Vijay Kumar and Dr Zhan Zhang, EMC, NCEP, USA were on deputation to IMD, New Delhi in July 2011 for technology transfer of HWRF model system and provide training on initial operating capability of HWRF model.

The basic version of the model HWRFV(3.2+) which was operational at EMC, NCEP was ported on IBM P-6/575 machine, IMD with nested domain of 27 km and 9 km horizontal resolution and 42 vertical levels with outer domain covering the area of 800x800 for NIO and inner domain 60x60 with centre of the system adjusted to the centre of the observed cyclonic storm.

HWRF model successfully tested for two Bay of Bengal TC cases JAL (4-8 Nov 2010), GIRI (21-22 Oct 2010) with vortex initialization and 6 hourly cyclic mode using the NCEP GFS data provided EMC team and also tested with IMD GFS spectral fields . The Atmospheric HWRF model was made operational (Experimental) to run real-time during the cyclone season-2011.

The Ocean Model and Coupler is to be implement for Indian Ocean region (regional MOM) in collaboration with EMC, NCEP and Indian National Centre for Ocean Information Services (INCOIS), Ministry of Earth Sciences, Hyderabad, India by April 2012. Testing of the atmospheric HWRF model for the last 5 years Cyclonic Storm formed over Arabian Sea and Bay of Bengal for 6 to 8 cases with vortex initialization and 6 hourly cycling of forecast runs for each case with total 70 to 80 runs using the initial and boundary from NCEP GFS spectral fields are expected to be completed by the end of January 2012 and a joint report will be prepared by the end of February 2012.

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