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Current Status and Prospects . of Drought Forecasting in South Asia . L. S. Rathore, Akhilesh Gupta and J.V. Singh. National Centre for Medium Range Weather Forecasting Department of Science & Technology Government of India. Website: www.ncmrwf.gov.in. PREDICTING DROUGHT.

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slide1

Current Status and Prospects

of Drought Forecasting in South Asia

L. S. Rathore, Akhilesh Gupta and J.V. Singh

National Centre for Medium Range Weather Forecasting

Department of Science & Technology

Government of India

Website: www.ncmrwf.gov.in

slide2

PREDICTING DROUGHT

  • Difficult for most locations
  • Anomalies last for months to decades depending upon features of global circulation
  • Big picture: Global weather patterns
  • Little picture: High Pressure
  • Tropical outlook: SST, ENSO
  • Prediction needed for too many variables
  • Long range prediction of precipitation and temperature
  • Tools: Empirical, Statistical, Climate models
information needed for drought prediction
Information needed for drought prediction
  • Onset/termination dates of rainy season
  • Precip./Temp. forecast in medium range
  • Precip./Temp forecast in extended to seasonal scale
  • Dry-spell duration and its culmination into drought

Predicting drought means predicting Precip. & Temp, the prime causatives, in all temporal ranges i.e. medium, extended and seasonal.

multi decadal changes in break days
Multi-decadal changes in Break Days

Data of past 50 years show that number of Break days are more

in July as compared to August

slide6

July Rainfall in Recent Years

Since 1991, number of years (11 out of 14 years) with less than LPA of

July rainfall was more as compared to previous decades. 2002 was

the worst year with All India rainfall 54% below normal.

first half of monsoon rainfall 1901 2004
First Half of Monsoon Rainfall: 1901-2004

Large inter-annual variability can be noticed for June-July rainfall.

Years with above normal and below normal rainfall are nearly

equally distributed

slide9

NCMRWF’s Forecast System for

Drought Prediction

  • NCMRWF has developed a Deterministic Medium-

Range Weather Forecasting System.

  • Weather forecasts up to 7 days is being produced

using Global Data Assimilation and Forecast Systems

at T80L18 and T170L28 resolutions.

  • High-Resolution Mesoscale Forecasts up to 72 hrs

using MM5 and Eta Models.

  • Extended range prediction – Experimental (monthly

scales).

* Weather based farm advisory service

slide11

GLOBAL DATA ASSIMILATION-FORECAST SYSTEM

Satellite

Aircraft

Radiosonde

Surface

observations

Pilot Balloon

GTS DATA

Ships

RTH IMD

DATA RECEPTION AT NCMRWF

DATA PROCESSING & QUALITY CONTROL

06

12

18

00

ANALYSIS

ANALYSIS

ANALYSIS

ANALYSIS

6 HR FCST

6 HR FCST

6 HR FCST

GLOBAL DATA ASSIMILATION

GLOBAL SPECTRAL MODEL

7 DAYS FORECASTS

ARCHIVAL

FORECAST DISSEMINATION TO USERS

slide12

Computing Resources at

NCMRWF

Cray SV1: 24-Processors- 1.2 GFlops per processor,

8 GB Main Memory, 800 GB Disk

DEC-ALPHA:Parallel Processing System

2- Servers AS4100 @600 MHz, Memory– 1GB each

9-Work Stations @600 MHz, Memory– 512MB each

Switch: Gigabit Ethernet Smart Switch Router

ORIGIN 200:Parallel Processing System

2- Servers: 4 CPU each @225 MHz, Memory– 1GB each

ORIGIN 200:Single CPU Servers

3- Servers @270 MHz, Memory– 512 MB each

1- Server @180 MHz, Memory– 512 MB

4- O2 WORK STATIONS:@200 MHz, Memory– 512MB each

PARAM 10000:Parallel Processing System

2- SUN Ultrasparc-II Servers (4 CPU each) @300 MHz,

Memory– 1GB each, ( Switch: MYRINET)

LOCAL AREA NETWORK:on Fast Ethernet.

4- LINUX SERVERS: (WEB, FTP, PROXY, PRINT)

Internet: 2 MBPS Leased Line

slide13

AGROMETEOROLOGICAL ADVISORY

SERVICE OF NCMRWF

NCMRWF

PREPARATION OF LOCATION SPECIFIC FORECAST

FEEDBACK FROM

AAS UNIT

Internet

FAX

PHONE

  • AAS UNITS (SAUs / ICAR institutes)

PREPARATION OF AGROMET ADVISORY BULLETIN

FARMER’s

FEEDBACK

AIR

PERSONAL

T.V.

PRINT

CONTACT

FARMER

slide14

NETWORK OF AGROMET ADVISORY

SERVICE (AAS) UNITS OF NCMRWF

dry spells in july 2004
Dry Spells in July 2004
  • Monsoon 2004- Started well and remained in good phase till 3rd week of June. As on June end;

All India rainfall was 2% below normal.

19/36 sub-divisions reported normal rainfall

9/36 subdivisions reported excess rainfall

61% of district received normal to excess rains.

  • July witnessed break conditions, which culminated into; All India rainfall of 15% below normal.

Only 19 subdivisions received normal to excess rainfall. 45% districts received normal to excess rainfall.

  • Sub-divisions like W and E Rajasthan, Gujarat, Saurashtra, H.P., West U.P., Haryana, Chandigarh & Delhi, Punjab, Jharkhand, E and W M. P., Madhya Maharashtra and Vidarbha remained deficient for several weeks.
slide17

Monsoon-2004: Drought Monitoring

Growing Concern: Expansion of

R/F Deficient Area with time

1 June-14 July

slide20

Monsoon-2004:Medium Range Forecast

(One week in advance) issued to Min. of Agri.

slide21

Monsoon-2004: Medium Range Drought Prediction

A typical bulletin of NCMRWF on MRWF of Monsoon situation issued for the week 19-25 July

  • Monsoon is once again going into a BREAK PHASE.
  • Model predictions do not indicate revival of monsoon
  • during next 5 days.
  • NE States, Sub-himalayan West Bengal and North
  • Bihar may receive widespread rains with isolated
  • heavy to very falls during next 5 days.
  • Rainfall deficiency in some of the already highly
  • distressed sub-divisions such as East and West
  • Rajasthan, Haryana, Punjab, West UP, West MP, and
  • Vidarbha, may grow further during next week.
slide23

Extended Range Prediction

  • System of NCMRWF:
  • Model Climate
  • ii) Predicted Sea Surface Temperature (SST) fields
  • iii) Ensemble Integration of the Model
  • iv) Forecast Preparation
  • v) Down Scaling
slide24

Forecast Preparation :

RAINFALL ANOMALIES

  • For each run, Area-Weighted Rainfall Anomalies
  • over 36 Meteorological Sub-Divisions in India
  • are computed
  • For each run, Area-Weighted Rainfall Anomalies
  • over 6 homogenous zones over India are computed
  • West Coast (ii) Peninsular India
  • (iii) Central East India (iv) North-East India
  • (v) North-West India (vi) Himalayan Belt
slide25

Forecast anomalies for each zone from each ensemble member runs are examined and given a category >

Excess: > 20%

Normal: between –20% to 20%

Deficient: less than -20%

Probability of prediction is computed by counting how

many runs have predicted which category of rainfall

anomaly for a zone (e.g. if 10 runs are made, and for North-East zone, 7 runs Predict excess rainfall, 2 predict normal and 1 deficient, probability of forecast is given in % as (70,20,10) or (7,2,1) as number.

If the probability of forecast for a zone exceeds 80% for

any category, sufficient confidence exists, and on the

Anomaly Map, the zone is shaded.

slide26

No Shading denotes areas where category could not be determined as the spread is quite large

slide27

Observed Rain

June 2002

(source: IMD)

Performance of NCMRWF ERP Was generally GOOD for JUNE

slide29

DOWNSCALING: ?

The ERP prepared at 1.4x1.4 degrees.

DOWNSCALING NEEDED

To generate forecast for smaller domains:

DYNAMICAL DOWNSCALING

Employing Eta Model (32x32km Grid) using the

Forecasts of the Global Model

STATISTICAL DOWNSCALING

Perfect Prog Method at monthly scale

Use Weather Generator for temporal downscaling

from monthly to daily values

doac initiative for erp iitd imd ncmrwf sac icar etc
DOAC Initiative for ERP(IITD, IMD, NCMRWF, SAC, ICAR etc.)
  • Global Ocean Atmosphere Coupled Model Products (GOACM)
  • Nested Grid high resolution Regional Climate Model (RCM)
  • Multi model Super-ensemble approach based on dynamical model products and synoptic scale signals using statistical/GIS techniques
  • Deterministic and probabilistic prediction of precipitation, surface air temperature and soil moisture
slide31

CONCLUSIONS

MRWF skillful and can play a role in indicating synthesis of drought over small spatial domains.

Outreach system (AAS) existing at 83 zones.

ERP System is under development. Evaluation of the Predictions in progress.

Generally Rainfall Prediction over Peninsula,

eastern and NE Regions good.

Role of Initial Data, SST and other predictands on seasonal forecast need to be examined further.

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