Lok Sabha Question No. 2495 (UNSTARRED), answered on 2016-11-30
Subject: Rainfall Prediction
Ministry: EARTH SCIENCES
Asked by: M. K. RAGHAVAN

## GOVERNMENT OF INDIA

## MINISTRY OF EARTH SCIENCES LOK SABHA

## UNSTARRED QUESTION NO. 2495

## TO BE ANSWERED ON WEDNESDAY, NOVEMBER 30, 2016

## RAINFALL PREDICTION

## 2495.  SHRI M.K. RAGHAVAN:

Will the Minister of EARTH SCIENCES be pleased to state:

- (a) whether  the  country  has  received  less  rain  in  the  monsoon  of  2016  than predicted by IMD;
- (b) if  so,  the  total  rainfall  received  in  monsoon  of  2016,  State-wise,  and  the average decrease in rainfall during the last five years including this year;
- (c) whether  any  study  has  been  carried  out  on  the  decreasing  pattern  and  its impact on the nation in all fields including, agriculture, power, drinking water, etc.; and
- (d) if so, the measures being taken to update the IMD system as well as to avoid inaccurate predictions by IMD?

## ANSWER

## MINISTER OF STATE FOR MINISTRY OF SCIENCE AND TECHNOLOGY AND MINISTRY OF EARTH SCIENCES

(SHRI Y. S. CHOWDARY)

- (a) Yes  Madam.  The  seasonal  rainfall  during  the  2016  monsoon  season  (JuneSeptember) over the country as a whole was 862 mm or 3% less than its Long Period Average (LPA).India Meteorological Department (IMD) predicted monsoon season rainfall for the country as a whole  likely to be 106% of the long period average with a model error of ±4%.
- (b) Total rainfall received in monsoon of 2016, State-wise is given in Annexure-I. The  forecasted  and  realized  seasonal  rainfall  anomalies  during  the  period 2010-2016 are given in Annexure-II.
- The  Indian  Monsoon  is  found  to  be  a  stable  system.  The  all-India  monsoon rainfall (June -September) does not show any long-term trend, but it exhibits year to year variability.
- (c-d)    Rainfall  data  from  observational  network  of  IMD  for  the  period  1901-2015 showed  that  the  all-India  annual  and  monsoon  rainfall  does  not  show  any significant trend. However, there are statistically significant regional variations  of  precipitation.  Eastern  parts  of  central  India  (Chhattisgarh, eastern Madhya Pradesh, Bihar) and  Kerala  showed  decreasing  trend in monsoon rainfall, while west coast of India (north of Kerala) and interior parts of Karnataka and Maharashtra showed increasing trend in seasonal monsoon rainfall.

IMD  under  Gramin  Krishi  Mausam  Sewa  (GKMS)  scheme,  generates  district level weather forecast for the next five days for issuing Agromet Advisories and  ultimately  communicated  to  the  farming  community  in  the  country. Feedback  from  farming  community  indicates  that  the  advisories  generated based on the forecast are very much useful and as a result farmers could get high  crop  productivity  and  also  minimize  the  loss  of  crop  due  to  aberrant weather.

IMD is also providing Extended Range Forecast System (ERFS) based Agromet Advisories at fortnightly scale in collaboration with Central Research Institute for Dryland Agriculture (CRIDA)-Indian Council of Agricultural Research (ICAR) to  the  state/district  level  planners.  As  the  crop  growth  and  development  is closely  related  to  active  and  break  spells  of  monsoon  rainfall,  ERFS  based GKMS bulletin is helping in strategic agricultural planning such as selection of crop varieties, application of farm inputs, contingent crops under delayed arrival and  deficit rainfall situation etc. This enables  the planners at national/state/district  level  to  mobilize  the  resource  inputs  and  to  target affected areas for efficient implementation of contingency plan at farm level. This increases the agriculture productivity and helps farmers to enhance their risk coping capability.

IMD and Power System Operation Corporation Ltd. (POSOCO), a wholly owned subsidiary of Power Grid Corporation of India Ltd. signed a Memorandum of Understanding for optimum use of weather information / forecast in the power sector. All weather information provided by IMD shall be used by the Power System  Operators  across  the  India  for  better  management  of  Indian  Power System and for the purpose of analysis.

The Government has initiated a comprehensive modernization programme for IMD  covering  upgradation  of  (i)  observation  systems  (ii)  advanced  data assimilation tools (iii) advanced communication and IT infrastructure (iv) high performance  computing  systems  and  (v)  intensive/sophisticated  training  of IMD  personnel  to  facilitate  the  implementation  of  advanced  global/regional/ meso-scale prediction models for improving the accuracy of weather forecasts  in  all  temporal  and  spatial  scales  and  for  quick  dissemination  of weather forecast assessments/warnings to the users.

Under the National Monsoon Mission initiative, other institutions of Ministry of Earth Sciences (MoES) , Indian Institue of Tropical Meteorology (IITM) Pune, Indian  National  Centre  for  Ocean  Information  Services  (INCOIS),  Hyderabad and  National  Centre  for  Medium  Range  Weather  Forecasting  (NCMRWF), NOIDA  have  embarked  upon  to  build  a  state-of-the-art  coupled  oceanatmospheric climate model for a) improved prediction of monsoon rainfall on extended  range  to  seasonal  time  scale  (16  days  to  one  season)  and  b) improved prediction of temperature, rainfall and extreme weather events on short to medium range time scale (up to 15 days) so that forecast skill gets quantitatively improved further for operational services of IMD.

Annexure-1 STATE-WISE MONSOON RAINFALL(MM)(JUNE TO SEPTEMBER) FOR 2016

| S. NO.                        | STATES             |   ACTUAL | NORMAL % DEP.   | CAT.   |
|-------------------------------|--------------------|----------|-----------------|--------|
| 1 A & N ISLAND(UT)            | 1562.6             |   1682.5 | -7%             | N      |
| 2. ARUNACHAL                  | PRADESH 1699.1     |   1768   | -4%             | N      |
| 3. ASSAM                      | 1190.6             |   1523.4 | -22%            | D      |
| 4. MEGHALAYA                  | 1455.7             |   2786.8 | -48%            | D      |
| 5. NAGALAND                   | 972.9              |   1329.9 | -27%            | D      |
| 6. MANIPUR                    | 1355.3             |   1404.5 | -4%             | N      |
| 7. MIZORAM                    | 1475.3             |   1708.3 | -14%            | N      |
| 8. TRIPURA                    | 1187.7             |   1489.1 | -20%            | D      |
| 9. SIKKIM                     | 1821.4             |   1800.8 | 1%              | N      |
| 10. WEST BENGAL               | 1382.1             |   1390.4 | -1%             | N      |
| 11. ORISSA                    | 1030.8             |   1149.9 | -10%            | N      |
| 12. JHARKHAND                 | 1096.9             |   1091.9 | 0%              | N      |
| 13. BIHAR                     | 994.1              |   1027.6 | -3%             | N      |
| 14. UTTAR PRADESH             | 731.5              |    846.1 | -14%            | N      |
| 15. UTTARAKHAND               | 1104.2             |   1229.1 | -10%            | N      |
| 16. HARYANA                   | 332.1              |    459.8 | -28%            | D      |
| 17. CHANDIGARH(UT)            | 456.2              |    844.2 | -46%            | D      |
| 18. DELHI                     | 526.8              |    636.2 | -17%            | N      |
| 19. PUNJAB                    | 352.0              |    491.9 | -28%            | D      |
| 20. HIMACHAL                  | PRADESH 624.5      |    825.3 | -24%            | D      |
| 21. JAMMU & KASHMIR           | 481.8              |    534.6 | -10%            | N      |
| 22. RAJASTHAN                 | 535.8              |    419   | 28%             | E      |
| 23. MADHYA PRADESH            | 1131.0             |    952.3 | 19%             | N      |
| 24. GUJARAT                   | 537.0              |    672.7 | -20%            | D      |
| 25. DADRA & NAGAR HAVELI (UT) | 2732.4             |   2162.3 | 26%             | E      |
| 26. DAMAN & DIU(UT)           | 1803.4             |   1620.4 | 11%             | N      |
| 27. GOA                       | 2960.2             |   2970.3 | 0%              | N      |
| 28. MAHARASHTRA               | 1164.9             |   1007.3 | 16%             | N      |
| 29. CHHATISGARH               | 1176.0             |   1153.3 | 2%              | N      |
| 30. ANDHRA PRADESH            | 549.2              |    504.4 | 9%              | N      |
| 31. TELANGANA*                | 899.8              |    755.2 | 19%             | N      |
| 32. TAMILNADU                 | 257.8              |    317   | -19%            | N      |
| 33. PONDICHERRY(UT)           | 336.1              |    355   | -5%             | N      |
| 34. KARNATAKA                 | 710.8              |    832.2 | -15%            | N      |
| 35. KERALA                    | 1352.2             |   2039.6 | -34%            | D      |
| 36. LAKSHADWEEP(UT)           | 745.5              |    998.5 | -25%            | D      |
| COUNTRY AS A WHOLE            | COUNTRY AS A WHOLE |    862   | 887.5           |        |

## Annexure-II The forecasted and realized seasonal rainfall anomalies during the period 20102016

| Year   | Actual% departure   | Forecast % departure   |
|--------|---------------------|------------------------|
| 2      |                     | 2010 2                 |
|        | 2                   | 2011 -5                |
|        | -7                  | 2012 -4                |
| 2013   | 6                   | -2                     |
| 2014   | -12                 | -7                     |
| 2015   | -14                 | -12                    |
| 2016   | -3                  | 6                      |