Match!

Real-Time Performance of a Multi-Model Ensemble-Based Extended Range Forecast System in Predicting the 2014 Monsoon Season Based on NCEP-CFSv2

Published on Nov 1, 2015in Current Science0.756
路 DOI :10.18520/cs/v109/i10/1802-1813
A. K. Sahai19
Estimated H-index: 19
(IITM: Indian Institute of Tropical Meteorology),
R. Chattopadhyay16
Estimated H-index: 16
(IITM: Indian Institute of Tropical Meteorology)
+ 5 AuthorsN. Borah9
Estimated H-index: 9
(IITM: Indian Institute of Tropical Meteorology)
Abstract
The real-time validation of any strategy to forecast the Indian summer monsoon rainfall requires comprehensive assessment of performance of the model on sub-seasonal scale. The multi-model ensemble (MME) approach based on the NCEP-CFS version 2 models, as developed and reported earlier, has been employed to forecast the 2014 monsoon season on the extended range scale with 3-4 pentad lead time (where a pentad corresponds to five-day average). The present study reports the broad performance of the MME employed on experimental basis to forecast the salient features of the real-time evolution of the 2014 monsoon season during June to September. The MME is successful in predicting both these features well in advance (3-4 pentad or 15-20 days lead time). The assessment of the model performance at pentad scale lead time shows that the weak monsoon conditions that are evident in precipitation and lower level wind anomalies are well captured as a whole up to four pentad advance lead time. The subseasonal propagation during onset and withdrawal is also evident in the forecast. Finally, the region-wise performance shows that the spatial extent of the skillful forecast encompasses central India as well as the monsoon zone for the 2014 monsoon season. Considering the natural variation in the forecast skill of extended range forecast itself as reported in earlier studies, the 2014 monsoon forecast seems to be skillful for operational purposes. For other regions (e.g. North East India), the forecast could be skillful at times, but it still requires further research on how to improve the same.
  • References (0)
  • Citations (9)
馃摉 Papers frequently viewed together
1,004 Citations
41 Citations
12 Citations
78% of Scinapse members use related papers. After signing in, all features are FREE.
References0
Newest
Cited By9
Newest
#1Ancy Thomas (C-DAC: Centre for Development of Advanced Computing)H-Index: 1
The study evaluates the Indian summer monsoon prediction skill of the Atmospheric General Circulation Model (AGCM) and the impact of sea surface temperature (SST) boundary forcing on the model performance. The National Center for Environmental Prediction's (NCEP's) T170/L42 AGCM model configured with a horizontal resolution of 75 脳 75 km, with 42 vertical levels is used for the study. The SST-rainfall relationship is examined in the coupled Climate Forecast System version 2 (CFSv2) model, as CFS...
Source
#1Ji-Woo Lee (LLNL: Lawrence Livermore National Laboratory)H-Index: 7
#2Yongkang Xue (UCLA: University of California, Los Angeles)H-Index: 48
Last. Peter J. Gleckler (LLNL: Lawrence Livermore National Laboratory)H-Index: 34
view all 8 authors...
This paper evaluates multi-decadal simulations of the UCLA version of Climate Forecast System version 2, in which the default Noah land surface model has been replaced with the Simplified Simple Biosphere Model version-2. To examine the influence of the atmosphere鈥搊cean (AO) interaction on the variability, two different simulations were conducted: one with interactive ocean component, and the other constrained by the prescribed sea surface temperature. We evaluate the mean seasonal climatology o...
2 CitationsSource
#1R. Chattopadhyay (IITM: Indian Institute of Tropical Meteorology)H-Index: 16
#2Anjali Thomas (CUSAT: Cochin University of Science and Technology)
Last. A. K. Sahai (IITM: Indian Institute of Tropical Meteorology)H-Index: 19
view all 5 authors...
In the current perception of an increase in extreme precipitation events in a developing and densely populated country like India and the demands of high resolution forecast runs are high, the present study compares the statistical skill of free runs from an operational climate model run in two horizontal resolutions in simulating the frequency and intensity of extreme rainfall events over Indian region. The operational climate model is a version of the National Center for Environmental Predicti...
Source
#1Samir Pokhrel (IITM: Indian Institute of Tropical Meteorology)H-Index: 16
#2Anupam Hazra (IITM: Indian Institute of Tropical Meteorology)H-Index: 13
Last. Suryachandra A. Rao (IITM: Indian Institute of Tropical Meteorology)H-Index: 25
view all 8 authors...
2 CitationsSource
#1S. Abhilash (IITM: Indian Institute of Tropical Meteorology)H-Index: 11
#2R. Mandal (IITM: Indian Institute of Tropical Meteorology)H-Index: 5
Last. M. Rajeevan (Government of India)H-Index: 33
view all 11 authors...
Indian summer monsoon of 2015 was deficient with prominence of short-lived (long-lived) active (break) spells. The real-time extended range forecasts disseminated by Indian Institute of Tropical Meteorology using an indigenous ensemble prediction system (EPS) based on National Center for Environmental Predictions鈥檚 climate forecast system could broadly predict these intraseasonal fluctuations at shorter time leads (i.e. up to 10 days), but failed to predict at longer leads (15鈥20 days). Consider...
1 CitationsSource
#1Reepal Shah (IITs: Indian Institutes of Technology)H-Index: 7
#2A. K. Sahai (IITM: Indian Institute of Tropical Meteorology)H-Index: 19
Last. Vimal Mishra (IITs: Indian Institutes of Technology)H-Index: 25
view all 3 authors...
Water resources and agriculture are often affected by the weather anomalies in India resulting in disproportionate damage. While short to sub-seasonal prediction systems and forecast products are available, a skilful hydrologic forecast of runoff and root-zone soil moisture that can provide timely information has been lacking in India. Using precipitation and air temperature forecasts from the Climate Forecast System聽v2聽(CFSv2), the Global Ensemble Forecast System聽(GEFSv2) and four products from...
10 CitationsSource
AbstractThis observationally based study demonstrates the importance of the delayed hydrological response of snow cover and snowmelt over the Eurasian region and Tibet for variability of Indian summer monsoon rainfall during the first two months after onset. Using snow cover fraction and snow water equivalent data during 1967鈥2003, it is demonstrated that, although the snow-albedo effect is prevalent over western Eurasia, the delayed hydrological effect is strong and persistent over the eastern ...
23 CitationsSource
#1Reepal Shah (IITs: Indian Institutes of Technology)H-Index: 7
#2A. K. Sahai (IITM: Indian Institute of Tropical Meteorology)H-Index: 19
Last. Vimal Mishra (IITs: Indian Institutes of Technology)H-Index: 25
view all 3 authors...
Water resources and agriculture are often affected by the weather anomalies in India resulting in a disproportionate damage. While short to medium range prediction systems and forecast products are available, a skilful 10 hydrologic forecast of runoff and root-zone soil moisture that can provide timely information has been lacking in India. Using precipitation and air temperature forecasts from the Climate Forecast System v2 (CFSv2), Global Ensemble Forecast System (GEFSv2) and four products fro...
1 CitationsSource
#1S. Joseph (IITM: Indian Institute of Tropical Meteorology)H-Index: 13
#2A. K. Sahai (IITM: Indian Institute of Tropical Meteorology)H-Index: 19
Last. R. Phani (IITM: Indian Institute of Tropical Meteorology)H-Index: 2
view all 10 authors...
The onset/progression phase of theIndian summer monsoon (ISM) is very crucial for the agricultural sector of the country as it has strong bearing on the sowing of kharif crops, which in turn affects overall food grain production and hence food security. The recent ISMs of 2013 and 2014 exhibited quite distinct progression phases. While 2013 had one of the fastest advancement in the last 70 years, 2014 witnessed a comparatively lethargic progression phase. The major difference was felt in the ear...
5 CitationsSource