Lok Sabha Question No. 2856 (UNSTARRED), answered on 2022-08-03
Subject: Upgradation of Forecast System
Ministry: EARTH SCIENCES
Asked by: Nusrat Jahan Ruhi

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## GOVERNMENT OF INDIA MINISTRY OF EARTH SCIENCES LOKSABHA

## UNSTARRED QUESTION NO. 2856 TO BE ANSWERED ON WEDNESDAY, 3 RD AUGUST, 2022

## UPGRADATION OF FORECAST SYSTEMS

## 2856. SHRI SRAT JAHAN RUHI:

inist r of EARTH SCIENCES be pleased to state:

- and d~tails of the 'Upgradation of Forecast System' programme under Atmosphere and Climate esear~h - modelling Observing System and Services (ACROSS) scheme; (a)
- whether ,he prowamme has resulted in increased accuracy of weather forecast; (b)
- if so, the detail~ thereof and if not, the reasons therefor; and (c)
- the steps taken rbYthe Government to improve the accuracy of India Meteorological Department (IMD) f recast in the country, specially in the State of West Bengal? (d)

## ANSWER

## HE MINISTER OF STATE (INDEPENDENT CHARGE) FOR MINISTRY OF SCIENCE AND TECHNOLOGY AND EARTH SCIENCES (DR. JITENDRA SINGH)

- (it)· For mOd,erniza,ion, expansion and improvement in Weather & Climate services, various plans are und rway ~n India Meteorological Department (IMD) under the umbrella Central Sector Scheme ACRQSS. There are 4 sub-schemes of IMD under ACROSS namely, Atmospheric Observa ion ~etwork (AON), Upgradation of Forecast System (UPS), Weather & Climate Services (WC~) and Commissioning of Polarimetric Doppler Weather Radars (DWR). Main activitie of the sub-scheme Upgradation of Forecast System undertaken during 2017-21 are as follows: J · f ~

## Upgrad. tion J Forecast System (UFS)

- up*adatitn and sustenance of Communication Systems for Data and Product transmission.
- De~elopmfnt of an advanced Operational Forecast System, Delivery System for Forecast androther services.
- Conduct ~I f special campaign for improving Cyclone, Thunderstorm and Fog forecasting through p ovision of additional observations.
- Int9grated Himalayan Meteorological Programme for Western & Central Himalayas.
- Caqacity Building, Outreach, Planning and sustenance of specific process related observing SYS1ems o~er India.
- (b)-(c) Yes Sir. Dur~ the past few years, !MD has been continuously improving weather prediction services in teTs of accuracy, lead time and associated impact. The forecasts and warnings are issued bI IMl'I at the national, State and district levels. It has a network of State Meteorological Centres for better coordination with State and district level agencies. With the upgradation of observa ions a d prediction system, noticeable improvements have been made in the recent past in the s ill of rediction, especially with respect to heavy-rainfall, heat-wave, thunderstorm and cyclone.

The wea her fo ecast accuracy is verified by IMD and errors and skill scores are calculated season wise and!annually.

## Details or impJ vement in Weather Forecast Accuracy are follows:

- Proba ility f Detection (POD) for heavy rainfall warning with 24 hr lead period is 74% in 2021, hich has improved by 51% in year 2021 as compared to their skill between 2002-20. False larm Rate (FAR) and Missing Rate (MR) are 26% in 2021, which has improved by 21% ' 53% espectively in year 2021 as compared to their skill between 2002-20. (Fig.-I)
- Proba ility fDetection (POD) for heat wave warning with 24 hr lead period is 97% in 2021, which has iiproved by 15% as compared to their skill between 2014-20. False Alarm Rate (FAR and issing Rate (MR) are 2% & 3% respectively in 2021, which has improved by 63% ' 82% respectively as compared to their skill between 2014-20. (Fig.-2)
- The aflual a erage landfall point forecast errors in 2021 have been 16.4 km, 10.6 km and 19.8 km refPectiJ~elY for 24, 36 and 48 hrs against the past five year (2016-2020) average error of 31.9~, 437 km and 61.5 km based on data of 2016-2020. Considering the diameter of the centraJ regio (eye) as 10-15 km, there was almost zero error in landfall point forecasts of CYcl0r in 2 '21 upto 48 hours in advance.
- The f:Ilual average track forecast errors in 2021 have been 63 km, 91 km and 164 km respectively for 24, 48 and 72hrs lead period against the past five year (2016-2020) average error 6[77, 17 and 159 km based on data of2016-2020. (Fig.-3)
- The tjack f9recast skills compared to climatology and persistence forecast have been 75%, 82% ,nd 68 l % respectively for the 24, 48 and 72 hrs lead against the long period average (20162020) skill of 64%, 76% & 78% respectively. (Fig.-3)
- The a nual verage absolute error(AE) in intensity (wind) forecast has been 6.2 knots, 9.5 I knots and 1~8 knots (108 nautical miles per hour) respectively for 24, 48 and 72 hrs lead perio of fo ecast against the past five year(2016-2020) average error of 7.9, 11.4 and 14.1 knots. The ill in intensity forecast as compared to persistence forecast was 63.2%, 78.4% and 8 .6% against the long period average (2016-20) skill of 52.2, 72.1 and 75.1 for 24, 48 and 7 hour~ lead period. (Fig.-3)
- Proba ility lf Detection (POD) for thunderstorm warning with 24 hr lead period is 86% in 2021 rgainst 31% in 2016. (Fig.-4)
- Probapility ~f Detection (POD) for thunderstorm warning with 3 hourly nowcast during March to June 2021 has been 79%.
- (d) In order to inclease the accuracy of forecast for all states/ U.T.s of the country including West Bengal, IMD has initiated to expand and modernize its observational network with special emphasi on eJpansion of DWR network, replacement of old Radars with new ones having state of the a technology especially in the cyclone prone areas. Expansion of surface observational network is als<hone of the major thrust areas and Automatic Weather Stations and Automatic Rain Garges arc being installed across the country in order to cover all data gap areas. Apart from that, Cli.rlate Services, Aviation forecast services and Environment monitoring services are also beirlg enhJnced.

As ment oned earlier, under ACROSS Scheme, following steps are being taken to further improve he acrracy of forecast

- (i) I plemfnting the monsoon mISSIon programme which improved the prediction c pabilTes in systematic and timely manner.
- pgradation of Atmospheric Observations Network (AON) including Doppler Weather adars (DWRs), Automatic Rain Gauges (ARGs), Automatic Weather Stations (AWSs), pper 1ir, Surface and Environmental Observatories etc. (ii)
- pgradltion of Forecast System (UFS) (iii)

,

- pgraJtion of Weather & Climate Services (WCS) (iv)
- pgradLiOn ofHPC System (v)
- sage If state-of-art Coupled Atmosphere Ocean Model, and Multi-Model Ensemble Jethod .. (vi)
- (vii) dopti g a seamless forecasting strategy -The long-range forecasts (for the whole ith a yalidity period of four weeks. To follow up the extended range forecast, short to ediu~ range forecast and warnings at 36 meteorological sub-divisions levels daily four t~mes vrlid up to next five days with an outlook for subsequent two days. The short to ,ediu~ range forecast is followed by very short range forecast of severe weather up to ee h~urs (nowcast) for all the districts and 1089 cities and towns. These nowcasts are dated every three hours.
- f (viii) I suance of warning using suitable colour code to bring out the impact of the severe 1 eathe~ expected and to signal the Disaster Management about the course of action to be t ken "fith respect to impending disaster weather event. Green colour corresponds to no arning hence no action is needed, yellow colour corresponds to be watchful and get update1 information, orange colour to be alert and be prepared to take action whereas red t lour lignals to take action.
- (ix) Issuing Impact Based Forecast (IBF) which give details of what the weather will do rather than what the weather will be. It contains the details of impacts expected from the severe feathe{ elements and guidelines to general public about do's and don'ts while getting ~pose~ to severe weather. These guidelines are finalised in collaboration with National Disaster Management Authority (NOMA) and is already implemented successfully for clon , heat wave, thunderstorm and heavy rainfall.

## ANNEXURE-I

1warning skill during 2021(FAR (False Alarm Rate), MR(Missing Rate), PoD ~""UVJ"J and CSI (Critical Success Index).IMD has high skill for heavy rainfall warning upto Day 5 as POD for Day 5 is more than 50%.

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Fig 2: ia Summer months (April to June) 2021vs 2014-20 heat wave skill scores

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Fig 3: (a) track forecast errors (Ian) and (b) track forecast skill (%) during 2021 compared to long period average errors during 2016-20.

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Fig.4. for 24 hr Thunderstorm forecast by !MD during past 6 years (2016 to 2021)

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