Real Time Forecast

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Verification

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Latest Verification

File NameDate & Time
Verification_MISO.ppt September 29 2014 14:57:23. hrs
Verification_spatial.ppt September 29 2014 14:49:49. hrs
Verification_anim_Aug.ppt September 29 2014 14:41:39. hrs
Verification_anim_Jul.ppt September 09 2014 16:10:58. hrs
Verification_anim_May.ppt August 13 2014 14:56:08. hrs
Verification_anim_Jun.ppt August 13 2014 14:56:05. hrs

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Archieval of Real Time Forecast

File NameDate & Time

Archieval of Forecast Verification

File NameDate & Time
Verification_20140725.ppt July 26 2014 12:24:09. hrs
Verification_20140720.ppt July 21 2014 13:07:17. hrs
Verification_20140715.ppt July 16 2014 16:28:52. hrs
Verification_20140710.ppt July 11 2014 16:58:24. hrs
Verification_20140705.ppt July 06 2014 14:07:28. hrs
Verification_20140630.ppt July 01 2014 16:52:20. hrs
Verification_20140625.ppt June 26 2014 15:57:58. hrs
Verification_20140620.ppt June 21 2014 13:42:02. hrs
Verification_20140615.ppt June 16 2014 20:07:46. hrs
FV_2013_Spatial_June_July.ppt September 10 2013 16:30:28. hrs
FV_2013_Spatial_August_September.ppt September 10 2013 16:30:28. hrs

 

MISO

The skill of prediction of the large scale low-frequency mode of MISO is evaluated by computing the correlations between the predicted and observed MISO indices MISO1 and MISO2 and is shown in Figure. The top panel shows the skill of all the initial conditions (ALL) as a function of lead-time. The middle and bottom panel plots are obtained by clustering the days in terms of the active initial conditions (ACT) and break initial conditions (BRK) respectively as mentioned in each panels. It is clear that increase in resolution has no significant impact in the prediction of large-scale MISO while GFSbc produces more skilful forecast of MISO for all initial conditions (ALL, ACT and BRK).