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Archieval of Real Time Forecast

2023

File NameDate & Time
ERPAS_Real-Time_Forecast_20231228.ppt December 29 2023 10:27:41. hrs
ERPAS_Real-Time_Forecast_20231221.ppt December 22 2023 16:45:28. hrs
ERPAS_Real-Time_Forecast_20231214.ppt December 20 2023 08:41:06. hrs
ERPAS_Real-Time_Forecast_20231207.ppt December 08 2023 14:11:40. hrs
ERPAS_Real-Time_Forecast_20231123.ppt November 24 2023 07:09:34. hrs
ERPAS_Real-Time_Forecast_20231116.ppt November 17 2023 10:52:45. hrs
ERPAS_Real-Time_Forecast_20231109.ppt November 10 2023 07:20:59. hrs
ERPAS_Real-Time_Forecast_20231102.ppt November 03 2023 11:51:30. hrs
ERPAS_Real-Time_Forecast_20231026.ppt October 27 2023 10:13:23. hrs
ERPAS_Real-Time_Forecast_20231019.ppt October 20 2023 06:56:44. hrs
ERPAS_Real-Time_Forecast_20231012.ppt October 13 2023 06:43:34. hrs
ERPAS_Real-Time_Forecast_20231005.ppt October 06 2023 12:12:05. hrs
ERPAS_Real-Time_Forecast_20230928.ppt September 29 2023 10:55:49. hrs
ERPAS_Real-Time_Forecast_20230921.ppt September 22 2023 08:57:32. hrs
ERPAS_Real-Time_Forecast_20230914.ppt September 15 2023 12:56:53. hrs
ERPAS_Real-Time_Forecast_20230907.ppt September 15 2023 09:41:45. hrs
ERPAS_Real-Time_Forecast_20230831.ppt September 08 2023 10:39:53. hrs
ERPAS_Real-Time_Forecast_20230824.ppt September 01 2023 12:11:45. hrs
ERPAS_Real-Time_Forecast_20230817.ppt August 25 2023 09:56:24. hrs
ERPAS_Real-Time_Forecast_20230810.ppt August 18 2023 10:00:55. hrs
ERPAS_Real-Time_Forecast_20230803.ppt August 04 2023 17:27:18. hrs
ERPAS_Real-Time_Forecast_20230727.ppt August 04 2023 17:25:49. hrs
ERPAS_Real-Time_Forecast_20230720.ppt July 21 2023 13:45:47. hrs
ERPAS_Real-Time_Forecast_20230713.ppt July 17 2023 04:30:00. hrs
ERPAS_Real-Time_Forecast_20230706.ppt July 07 2023 11:09:57. hrs
ERPAS_Real-Time_Forecast_20230629.ppt June 30 2023 09:35:32. hrs
ERPAS_Real-Time_Forecast_20230622.ppt June 23 2023 06:54:21. hrs
ERPAS_Real-Time_Forecast_20230615.ppt June 16 2023 08:56:17. hrs
ERPAS_Real-Time_Forecast_20230608.ppt June 09 2023 10:45:58. hrs
ERPAS_Real-Time_Forecast_20230601.ppt June 02 2023 08:03:21. hrs
ERPAS_Real-Time_Forecast_20230525.ppt May 26 2023 07:28:22. hrs
ERPAS_Real-Time_Forecast_20230518.ppt May 19 2023 07:01:17. hrs
ERPAS_Real-Time_Forecast_20230511.ppt May 12 2023 06:09:31. hrs
ERPAS_Real-Time_Forecast_20230504.ppt May 06 2023 11:58:30. hrs
ERPAS_Real-Time_Forecast_20230426.ppt April 27 2023 07:34:21. hrs
ERPAS_Real-Time_Forecast_20230419.ppt April 20 2023 09:45:23. hrs
ERPAS_Real-Time_Forecast_20230412.ppt April 13 2023 07:08:51. hrs
ERPAS_Real-Time_Forecast_20230405.ppt April 06 2023 12:52:59. hrs
ERPAS_Real-Time_Forecast_20230329.ppt March 30 2023 10:03:01. hrs
ERPAS_Real-Time_Forecast_20230322.ppt March 23 2023 11:17:15. hrs
ERPAS_Real-Time_Forecast_20230315.ppt March 17 2023 06:33:39. hrs
ERPAS_Real-Time_Forecast_20230308.ppt March 09 2023 10:02:01. hrs
ERPAS_Real-Time_Forecast_20230301.ppt March 02 2023 12:38:12. hrs
ERPAS_Real-Time_Forecast_20230222.ppt February 23 2023 09:35:03. hrs
ERPAS_Real-Time_Forecast_20230215.ppt February 16 2023 09:37:25. hrs
ERPAS_Real-Time_Forecast_20230208.ppt February 09 2023 11:31:23. hrs
ERPAS_Real-Time_Forecast_20230125.ppt February 02 2023 10:01:07. hrs
ERPAS_Real-Time_Forecast_20230201.ppt February 02 2023 09:26:16. hrs
ERPAS_Real-Time_Forecast_20230118.ppt January 20 2023 07:11:28. hrs
ERPAS_Real-Time_Forecast_20230111.ppt January 12 2023 13:34:08. hrs
ERPAS_Real-Time_Forecast_20230104.ppt January 05 2023 13:38:44. hrs

Archieval of Real Time Forecast

2024

File NameDate & Time
ERPAS_Real-Time_Forecast_20240308.ppt March 09 2024 13:33:19. hrs
ERPAS_Real-Time_Forecast_20240301.ppt March 02 2024 10:43:38. hrs
ERPAS_Real-Time_Forecast_20240222.ppt February 23 2024 08:01:45. hrs
ERPAS_Real-Time_Forecast_20240215.ppt February 16 2024 15:50:39. hrs
ERPAS_Real-Time_Forecast_20240208.ppt February 16 2024 14:14:09. hrs
ERPAS_Real-Time_Forecast_20240201.ppt February 02 2024 17:05:17. hrs
ERPAS_Real-Time_Forecast_20240125.ppt January 30 2024 07:25:42. hrs
ERPAS_Real-Time_Forecast_20240118.ppt January 19 2024 11:05:47. hrs
ERPAS_Real-Time_Forecast_20240111.ppt January 12 2024 09:07:43. hrs
ERPAS_Real-Time_Forecast_20240104.ppt January 05 2024 13:27:18. hrs

 
 

Disclaimer: The forecasts provided on this website since 07 July 2022 are from the second generation extended range prediction system (ERPv2) developed at IITM with a multi-physics strategy (Sahai et al. 2021; Kaur et al. 2022), and are being run on an experimental basis from the monsoon season 2022. For forecasts based on ERPv1, developed by IITM and being run operationally by IMD, please visit, https://nwp.imd.gov.in/cfs_rf.php or https://mausam.imd.gov.in/imd_latest/contents/extendedrangeforecast.php

 
 

 

INTRODUCTION

Under the National Monsoon Mission (NMM) Project (Rao et al., 2019) of the Ministry of Earth Sciences (MoES), the Indian Institute of Tropical Meteorology (IITM) started ERP efforts in 2011 by adopting the Climate Forecast System (CFS) from the National Centre for Environmental Prediction (NCEP), USA. An ensemble prediction system (EPS) has been developed for the ERP by using an indigenous perturbation technique (Abhilash et al. 2013), which was later developed into a multi-model EPS. Several post-processing techniques have also been developed to improve the prediction skill of extreme weather events (Sahai et al., 2017; Ganesh et al., 2018, 2020).

The EPS has remarkable skill in delivering an outlook on the intraseasonal fluctuations within the Indian summer monsoon, Madden-Julian Oscillation, heat/cold waves, cyclogenesis, and heavy rainfall events (Abhilash et al., 2013, 2014a,b,c, 2015a,b; Sahai et al., 2013, 2015a,b, 2017; Joseph et al., 2015a,b, 2016, 2019; Mandal et al. 2019; Dey et al., 2019; Ganesh et al., 2020), and this was adapted by India Meteorological Department (IMD) for operational purposes in 2016. Henceforth, these forecasts are used for generating the agricultural bulletins every week, which proved to be beneficial for farmers in increasing crop yield and choosing cost-effective crops (Chattopadyay et al. 2018). Health bulletins are also being generated by IMD using ERP guidance. An early warning system for the probabilistic prediction of vector-borne diseases has also been developed based on the ERP using AI/ML methods (Sahai et al. 2020).

In addition to these, efforts are now underway in generating the second-generation ERP (ERPv2) with a multi-physics framework for the improved prediction of the weather systems beyond 2 weeks (Sahai et al. 2021; Kaur et al. 2021). A competent set of physics pairs based on convection (simplified Arakawa Schubert SAS (Arakawa and Schubert 1974), revised SAS with modified shallow-convection (Han and Pan 2011), and microphysics (Zhao & Carr (Zhao and Carr 1997) and Ferrier (Ferrier et al. (2002)) schemes is selected to formulate a physics-based ensemble. The system with only control runs are showing great potential in the first three week leads. Therefore, for the ERPv2, we have three initial condition perturbed ensemble members (control + two) each for six multi-physics combinations, thus totalling 18 ensembles (3 initial condition perturbation X 6 physics perturbation). The experimental forecasts based on this new system, i.e., ERPv2, are now available and updated every Thursday on a real-time basis on this website, https://www.tropmet.res.in/erpas/.