Performance of Global Forecast System

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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

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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

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Numerical Weather Prediction System of NCMRWF
Data Reception
Global Data Assimilation
Users
Forecast Models
Global Observations
SURFACE from land stations
Observation quality checks monitoring
Global Model T574L64 10day FCST
GTS
IMD INCOIS
RTH, IMD
SHIP
BUOY
Visuali-sation
NKN
Global Analysis (GSI) Initial state
ISRO(MT)
NKN
24x7
Upper Air RSRW/ PIBAL
Meso-scale Data Assimilation Model
NCMRWF OBSERVATION PROCESSING
Aircraft
Global Forecast Model ( 9hr Fcst
first guess )
Statistical Interpolation Model (location
specific FCST)
Satellite
45mbps
proposed dedicated link
High Resolution Satellite Obsn
Internet (FTP)
Other sectors
NKN
once in a day for 00 UTC
4 times a day for 00,06,12,18 UTC
NESDIS
EUMETSAT
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GFS Models (NCMRWF) Current status
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)
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 Connectivity No of Processors available Per node memory Processor speed
IBM Power 6 Infini Band 38x32 (NCMRWF) 24x32 (IMD) 4x32 GB 4.7 Gflops
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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)
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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 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
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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 19971998). 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)
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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
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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 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
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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
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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 June July July August 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
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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.
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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.
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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.
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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.
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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.
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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.
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Global Circulation Features
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Day 05 Forecast Errors 850 hPa Zonal Wind JJA 2011
NCMRWF
NCEP
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Regional Circulation Features
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ANA
D03 ERR
T382
T574
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ANA
D05 ERR
T382
T574
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ANA
D03 ERR
T382
T574
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ANA
D05 ERR
T382
T574
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ANA
D03 ERR
T382
T574
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ANA
D05 ERR
T382
T574
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T382
T574
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T382
T574
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T382
T574
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T382
T574
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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.

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T574
T382
UKMO
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T574
T382
UKMO
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T574
T382
UKMO
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T574
T382
UKMO
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T574
T382
UKMO
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T574
T382
UKMO
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T574
T382
UKMO
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T574
T382
UKMO
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T574
T382
UKMO
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T574
T382
UKMO
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Time Series of RMSE of D01, D03 D05 Forecasts
of Zonal Wind
D01
D03
D05
200hPa
500hPa
700hPa
850 hPa
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Time Series of RMSE of D01, D03 D05 Forecasts
of Meridional Wind
D03
D05
D01
200hPa
500hPa
700hPa
850hPa
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Time Series of RMSE of D01, D03 D05 Forecasts
of Temperature
D01
D03
D05
200hPa
500hPa
700hPa
850hPa
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Time Series of RMSE of D01, D03 D05 Forecasts
of Geop Height
D05
D03
D01
200hPa
500hPa
700hPa
850hPa
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Time Series of RMSE of D01, D03 D05 Forecasts
of RH
D03
D05
D01
200hPa
500hPa
700hPa
850hPa
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RMSE against own analysis 850 hPa Zonal Wind
850 hPa 850 hPa 850 hPa 200 hPa 200 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
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RMSE against own analysis 850 hPa Meridonal Wind
850 hPa 850 hPa 850 hPa 200 hPa 200 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
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Factors and methods used In standardized
verificatlon of NWP products   Verification
agalnst analysis   Area Northem hemisphere
extratropics (90N - 20N )(all inclusive)
Tropics (20N - 20S)(all inclusive)
Southem hemisphere extratropics (20S - 90S)(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)
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Verification against observations The seven
networks used in verification against radiosondes
consist of radiosondes stations Iying within the
following geographical area North
America 25N - 60N 50W - 145W Europe/North
Africa 25N - 70N 10W - 28E Asia
25N - 65N 60E -
145E Australia/New Zealand 10S - 55S 90E -
180E Australia/New Zealand 10S - 55S 90E -
180E Tropics 20S - 20N all longitudes N.
Hemisphere Extratropics 20N - 90N all
longitudes S.Hemisphere Extratropics 20S
-90S all longitudes
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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.
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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.
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Verification of Day 01-05 Forecast against
Observations over TropicsRoot Mean Square Error
(RMSE) 850 hPa winds in m/sJUNE 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
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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
T80
T574
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Monsoon Depressions
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Track Errors
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RAINFALL FORECAST VERIFICATION DURING MONSOON
2011T382,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.

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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
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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.
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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
NO
hits false alarms
misses correct rejections
FORECAST YES
YES
FORECAST
NO
FORECAST NO
OBSERVED NO
OBSERVED YES
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Bias

• The bias score is a measure of the agreement
  between the forecast frequency of "yes" events
  and the observed frequency of "yes" events. It is
  given by the ratio of the frequency of forecast
  events to the frequency of observed events.
• The score values range from 0 to infinity and the
  score of 1 implies a perfect forecast.
• gt1 prediction
• lt1 Underprediction

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ETS

• ETS measures the fraction of observed and/or
  forecast events that were correctly predicted,
  adjusted for hits associated with random chance
  (for example, it is easier to correctly forecast
  rain occurrence in a wet climate than in a dry
  climate).
• ETS tells us how well did the forecast "yes"
  events correspond to the observed "yes" events
  (accounting for hits due to chance)?
• ETS ranges from -1/3 to 1, 0 indicates no skill
  and 1 meaning perfect score.

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ETS
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IMD GFS Verification - Areas

• 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)

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ALL India Weekly Cumulative Rainfall
(Lon 68 E 98E, Lat 9N 37N)
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(Lon 90E 95E, Lat 24N -29N)
(Lon 75E 80E, Lat 19 24N)
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(Lon 83E -88E, Lat 20N -25N)
(Lon 75E 80E, Lat 25N -30N)
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(Lon 70E - 75E, Lat 13N - 18N)
(Lon 76E - 81E, Lat 12N- 17N)
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CC 7 Day Cumulative Rainfall of GFS T382 T574
vs. Observation
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(Lon 83E -88E, Lat 20N -25N)
((Lon 75E 80E, Lat 19 24N)
(Lon 90E 95E, Lat 24N -29N)
(Lon 70E - 75E, Lat 13N - 18N)
(Lon 76E - 81E, Lat 12N- 17N)
(Lon 75E 80E, Lat 25N -30N)
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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
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GFS T574 Daily Error in Maximum and Minimum
Temperature over North-East India
(Lon 90E 95E, Lat 24N -29N)
(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
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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 30 September,2011
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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 gt1.0 cm/day. For rainfall
  intensity of 0.01 cm/day all three models feature
  high ETS (gt0.6) 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.

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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

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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)

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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

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Hurricane WRF Model The HWRF model has been
implemented at the India Meteorological
Department (IMD) following the Implementation
Agreement (IA) between Indias Ministry of Earth
Sciences (MoES) and USAs 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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• THANKS