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January 14, 2018 | Author: Anonymous | Category: Math, Statistics And Probability, Statistics
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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 Data Global Observations Reception SURFACE from land stations

GTS

RTH, IMD

SHIP

Global Data Assimilation Observation quality checks & monitoring

Upper Air RSRW/ PIBAL Aircraft

Satellite

NKN

ISRO (MT)

NCMRWF OBSERVATION PROCESSING 45mbps

High Resolution Satellite Obsn NKN Internet (FTP) NESDIS

proposed dedicated link

EUMETSAT

Users

Global Model T574L64 10day FCST

IMD INCOIS

BUOY 24x7

Forecast Models

Global Analysis (GSI) Initial state

Global Forecast Model ( 9hr Fcst – first guess ) 4 times a day for 00,06,12,18 UTC

Visualisation

NKN

Meso-scale Data Assimilation & Model

Statistical Interpolation Model (location specific FCST)

once in a day for 00 UTC

Other sectors

GFS Models (NCMRWF) – Current status Model

Version

Horizontal Forecast Resolution Length

Performance

GFS T382L64

GFS version 9.0.1

~35km

168 Hrs (3hr data cutoff)

4 min. for 24 hr forecast (IBMP6 16 nodes)

GFS T574L64

GFS version 9.0.1

~23km

240 Hrs (5hr data cutoff)

9 min. for 24 hr forecast (IBMP6 16 nodes)

GEFS T190L28

Latest version 20 members

~70km

240 Hrs (Not operational)

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

High Performance Computing Systems HPC

Connectivit y

No of Processors available

Per node memory

Processor speed

IBM Infini Band Power 6

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 GFS The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) winds Rainfall rates (TRMM, SSMI) NOAA19 radiances Atmospheric Infrared Sounder (AIRS) radiances GPSRO (COSMIC)

Implementation of the T574L64 GFS from mid-November, 2010 (July 2010 Version) Implementation of latest NCEP version of T574L64 (from June, 2011)

Time line - NCMRWF GFS 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 NovemberDecember 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

Physical Parameterization schemes in T382L64 and T574L64 Physics

T382L64

T574L64

Surface 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 includedinvoked 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)

Differences of the T574L64 GSI Data Assimilation system compared to T382L64

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

Types of observations Assimilated in GFS 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 AMV from Meteosat-7, Meteosat-9, GOES-11, Geo-Stationary Satellites 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

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) 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

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 BUOY (Drifter)

46,118

78,390

56,734

78,481

57,607

78,574

10,715

13,953

13,882

13,879

13,752

13,531

TEMP 500 hPa Geopotential TEMP/PILOT 300 hPa Wind AIRCRAFT winds (300-150 hPa) AMV winds (400-150 hPa) AMV winds (1000-700 hPa)

1,088

1,286

1,271

1,286

1,320

1,336

1,098

1,434

1,300

1,429

1,349

1,490

58,412

1,04,987

72,842

1,02,562 72,685

1,03,059

2,00,283

10,06,280 2,55,690

9,78,269 2,43,282

9,45,691

1,28,786

8,53,193

8,91,204 1,52,905

8,21,724

1,54,724

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

Day 05 Forecast Errors 850 hPa Zonal Wind JJA 2011

NCMRWF

NCEP

Regional Circulation Features

ANA

T382

T574

D03 ERR

ANA

T382

T574

D05 ERR

ANA

T382

T574

D03 ERR

ANA

T382

T574

D05 ERR

ANA

T382

T574

D03 ERR

ANA

T382

T574

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.

T574

T382

UKMO

T574

T382

UKMO

RMSE against own analysis 850 hPa Zonal Wind

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 Meridonal 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

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, winds Levels Extratropics: MSL, 500 hPa, 250 hPa Tropics: 850 hPa, 250 hPa Time 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 observations The 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°W Europe/North Africa 25°N - 70°N 10°W - 28°E Asia 25°N - 65°N 60°E - 145°E Australia/New Zealand 10°S - 55°S 90°E - 180°E Australia/New Zealand 10°S - 55°S 90°E - 180°E Tropics 20°S - 20°N all longitudes N. Hemisphere Extratropics 20°N - 90°N all longitudes S.Hemisphere Extratropics 20°S -90°S all longitudes

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 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.

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

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.

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

NCMRWF 3.8 T574

4.1

4.5

4.7

4.9

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

T254

T382 T574

Sep-11

May-11

Jan-11

Sep-10

May-10

Jan-10

Sep-09

May-09

Jan-09

Sep-08

May-08

Jan-08

Sep-07

May-07

Jan-07

Sep-06

May-06

Jan-06

Sep-05

May-05

9 8 7 6 5 4 3 2 1 0 Jan-05

RMSEV

T80

Monsoon Depressions

Track Errors

700

Error (in Km)

600 500

AVE FTE T574 FTE 11to 12june11 FTE 16 to 22june11 FTE 22 to 23july11 FTE 22 to 23sep11

400 300 200 100 0 Day-1

Day-2

Day-3

Days

Day-4

Day-5

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

Error (in Km)

500 400 300

T574

200

T382

100 0 Day-1

Day-2

Day-3 Days

Day-4

Day-5

Error in (Km)

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

450 400 350 300 250 200 150 100 50 0 Day-1

UKMO T574 T382

Day-2

Day-3 Days

Day-4

Day-5

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.

UKMO

T382

T574

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

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.

OBSERVED YES

YES

NO

hits

false alarms

misses

correct rejections

OBSERVED YES

OBSERVED NO

FORECAST YES

FORECAST

NO

FORECAST NO

Day-1 Rainfall Forecast T382 T574 UKMO

0.6

ETS

0.4

0.2

0 0.01

1

2

3

4

5

4

5

Rainfall Thres hold(cm /day)

Day-3 Rainfall Forecast

0.6

ETS

0.4 0.2 0 0.01

1

2

3

Rainfall Thres hold(cm /day) Day-5 Rainfall Forecast

ETS

0.6 T382 T574 UKMO

0.4 0.2 0 0.01

1

2

3

4

Rainfall Thres hold (cm/day)

ETS for the predicted rainfall during JJAS 2011

5

IMD GFS Verification - Areas 1) 2) 3)

4) 5)

6) 7)

ALL-INDIA (Lon: 68 E – 98E, Lat: 9N – 37N) Central India (Lon: 75E – 80E, Lat: 19 – 24N) East India (Lon: 83E -88E, Lat: 20N -25N) North East India (Lon: 90E – 95E, Lat: 24N -29N) North West India (Lon: 75E – 80E, Lat: 25N -30N) South Peninsula India (Lon: 76E - 81E, Lat: 12N- 17N) West Coast of India (Lon: 70E - 75E, Lat: 13N - 18N)

ALL India : Weekly Cumulative Rainfall OBS

ALL INDIA: Weekly Cumulative Rainfall 120

T382(CC=0.79)

(Lon: 68 E – 98E, Lat: 9N – 37N)

T574(CC=0.83) Rainfall in mm

90

60

30

29

17 23

20 11 11

SE P

12 18

G 31 20 11

24 30 5

6

AU

19 25

7 13

19 JU LY 25 20 11 1

1

JU

NE

20 11 7 13

0

OBS

NORTH WEST- INDIA:7 day cum . rain 150

T382(CC=0.68)

(Lon: 90E – 95E, Lat: 24N -29N)

T574(CC=0.80)

Rainfall in mm

120 90 60 30

29

23

17

11

20 11

30

EP

24

18

12

20 11

31

G

25

19

13

7

5

S

A U 6

JU 1

1

JU

N

LY

20 11

25

19

13

7

E

20 11

0

OBS T382(CC=0.77) Central- INDIA:Cum ulative Rainfall

180

(Lon: 75E – 80E, Lat: 19 – 24N)

150

Rainfall in mm

T574(CC=0.76)

120 90 60 30

S 5

29

23

17

11

20 11

30

EP

24

18

12

20 11

G

25

19

13

7

31 A U 6

LY 1

JU

N JU 1

20 11

25

19

13

7

E

20 11

0

OBS

EAST- INDIA:7 DAY CUM RAINFALL 250

T382 (CC=0.47)

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

T574 (CC=0.75)

Rainfall in mm

200 150 100 50

29

23

17

11

20 11

30

EP

24

18

12

20 11

31

S

U 6

5

A

JU 1

1

JU

N

LY

G

25

19

13

7

20 11

25

19

13

7

E

20 11

0

OBS NORTH EAST- INDIA:7 day cum . rain

250

T382 (CC=0.64)

(Lon: 75E – 80E, Lat: 25N -30N)

Rainfall in mm

200

T574(CC=0.69)

150 100 50 0

1

N JU

E

11 20

7

13

19

25 1

L JU

Y

11 20

7

13

19

25

31 6

AU

G

11 20

12

18

24

30 5

P SE

11 20

11

17

23

29

WEST COAST OF INDIA:7 day Cum Rain 350

OBS

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

300

T382(CC=0.69)

Rainfall in mm

250

T574(CC=0.74)

200 150 100 50

29

23

17

11

20 11

30

EP

24

18

12

20 11

31

S

U 6

5

A

JU 1

1

JU

N

LY

G

25

19

13

7

20 11

25

19

13

7

E

20 11

0

OBS SP- INDIA: 7day Cum Rain

100

T382(CC=0.56)

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

T574(CC=0.71)

Rainfall in mm

80 60 40 20

29

23

17

11

11 20

24

18

12

30

E P S 5

6

A

U

L

Y

G

20 11

31

25

19

13

7

01 1 2

19

13

7

25 JU 1

1

JU

N

E

20 11

0

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

0.9

0.8

0.7

0.6

0.5

0.4

0.3 CENTRAL INDIA

NW INDIA

NE INDIA

EAST INDIA

SP INDIA

WEST COAST INDIA

ALLINDIA

1

1

IMDT382

NE-INDIA

East india

CENTRAL INDIA

IMDT382

(Lon: 90E – 95E, Lat: 24N -29N)

0.9

0.8

IMDT574

0.6

0.6

0.4

0.4

0.2

CC

CC

CC

0.6

0.2

0.3

0 DAY-1

0

DAY-2

DAY-3

DAY-4

DAY-5

0

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

DAY-1

SP INDIA

WEST COAST OF INDIA

DAY-4

DAY-5

1

IMDT574 NW INDIA (Lon: 75E – 80E, Lat: 25N -30N)

0.8

0.8

CC

CC

0.6

IMDT574 0.6

DAY-3

IMDT382

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

IMDT382

DAY-2

IMDT382 IMDT574

0.8

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

CC

IMDT574

IMDT574

0.8

1

IMDT382

((Lon: 75E – 80E, Lat: 19 – 24N)

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

0.4

0.6

0.4 0.2

0.4

0

0.2

0.2 DAY-1

DAY-2

DAY-3

DAY-4

DAY-5

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

DAY-1

DAY-2

DAY-3

DAY-4

DAY-5

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

GFS T574: Daily Error in Maximum and Minimum Temperature over North-East India (Lon: 90E – 95E, Lat: 24N -29N)

DAY-1

Error in Tmax : N-EAST INDIA

DAY-2 DAY-3

6

(Lon: 75E – 80E, Lat: 25N -30N)

DAY-4 4

DAY-5

Error in deg C

2 0 1 -2JUNE 2011 -4

7

13

19

25

1 JULY 2011

7

13

19

25

31

6 AUG 2011

12

18

24

30

5 SEP 2011

11

17

23

29

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

-6 -8 -10

N-EAST INDIA

DAY-1

6

DAY-2 DAY-3

4 Error in deg C

DAY-4 2

-6

29

23

17

11

24

18

S E 30 P 20 11 5

AU 6

12

20 11

31

G

25

19

13

7

Y JU L

-4

20 11

25

19

13

7

-2

1

E

20 11

0

JU N 1

DAY-5

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

GFS T574: Seasonal Mean Error in Maximum and Minimum Temperature over different Homogeneous regions of India DAY-1

MAE for Tm ax (1 June -30 Septem ber 2011)

DAY-2 DAY-3

5

Temperature in deg C

DAY-4 DAY-5

4 3 2

For 1 June to 30 September,2011

1 0 CENTRAL INDIA

EAST INDIA

NE INDIA

NW INDIA

SP INDIA

WEST COAST OF INDIA DAY-1

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

DAY-2 DAY-3

5

DAY-4 DAY-5

4

Temp in deg C

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

3 2 1 0 CENTRAL INDIA

EAST INDIA

NE INDIA

NW INDIA

SP INDIA

WEST COAST OF INDIA

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 Model The 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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