Match!

An assessment of real‐time extended range forecast of 2013 Indian summer monsoon

Published on Aug 1, 2015in International Journal of Climatology3.601
· DOI :10.1002/joc.4178
N. Borah9
Estimated H-index: 9
(IITM: Indian Institute of Tropical Meteorology),
A. K. Sahai19
Estimated H-index: 19
(IITM: Indian Institute of Tropical Meteorology)
+ 4 AuthorsA. Kumar1
Estimated H-index: 1
(Silver Spring Networks)
Abstract
Several aspects of real-time forecast of Indian summer monsoon (ISM) in 3–4 pentad lead time (extended range) are discussed in this study to explore the operational capability of the Climate Forecast System model version 2 (CFSv2) developed by National Centre for Environmental Prediction (NCEP). 2013 summer monsoon was a near excess monsoon year in terms of seasonal mean and was a result of rich diversity of phenomena including strong intraseasonal variations and intense northward propagations over the Indian region. Eleven-member forecasts were made at every 5-day interval during the June–September monsoon season which included monsoon onset and withdrawal phases. The ensemble members were created by perturbing the initial conditions at each start time. In addition to the CFSv2 forecasts, we also carried out forecasts using the atmospheric-only component (GFSv2) forced with CFSv2-derived sea surface temperature (SST) subjected to a bias correction based on historical observations (GFSbc runs). Both the CFSv2 and GFSbc runs were able to predict the progression of ISM over the Indian region and the subsequent intraseasonal oscillations (active and break phases). The analysis for an extreme event (Uttarakhand flood) and monsoon revival (MR) towards the end of the season was also performed. Comparison between the two runs shows that active and break spells were predicted with good fidelity over the Indian region, though GFSbc outperforms CFSv2 on several occasions. Thus, improvement of the operational monsoon forecast over Indian region using NCEP CFSv2 requires better representation of air–sea interaction and mean states of ocean.
  • References (26)
  • Citations (12)
📖 Papers frequently viewed together
1,004 Citations
13 Citations
16 Citations
78% of Scinapse members use related papers. After signing in, all features are FREE.
References26
Newest
#1S. Abhilash (IITM: Indian Institute of Tropical Meteorology)H-Index: 11
#2A. K. Sahai (IITM: Indian Institute of Tropical Meteorology)H-Index: 19
Last. Bhupendra Nath Goswami (IITM: Indian Institute of Tropical Meteorology)H-Index: 46
view all 8 authors...
16 CitationsSource
#1Suranjana Saha (NOAA: National Oceanic and Atmospheric Administration)H-Index: 21
#2Shrinivas MoorthiH-Index: 14
Last. Emily BeckerH-Index: 13
view all 19 authors...
1,004 CitationsSource
#1S. Abhilash (IITM: Indian Institute of Tropical Meteorology)H-Index: 11
#2A. K. Sahai (IITM: Indian Institute of Tropical Meteorology)H-Index: 19
Last. Arun KumarH-Index: 57
view all 5 authors...
This study analyses skill of an extended range prediction system to forecast Indian Summer Monsoon Rainfall (ISMR) 3-4 pentads in advance. A series of 45-d forecast integrations starting from 1 May to 29 September at 5-d interval for 7 years from 2001 to 2007 are performed with an ensemble prediction system (EPS) in NCEP Climate Forecast System Version 1 (CFSV1) model. The sensitivity experiments with different amount of perturbation suggest that full tendency perturbation experiment on all basi...
41 CitationsSource
#1S. Abhilash (IITM: Indian Institute of Tropical Meteorology)H-Index: 11
#2A. K. Sahai (IITM: Indian Institute of Tropical Meteorology)H-Index: 19
Last. S. De (IITM: Indian Institute of Tropical Meteorology)H-Index: 7
view all 4 authors...
This study examines the phase dependant temporal and spatial error evolution and prediction of active break spells of Indian summer monsoon rainfall in an ensemble prediction system (EPS) on a pentad time scale using climate forecast system (CFS). The EPS system shows systematic wet bias (overestimation) over west coast over the Arabian Sea and Myanmar coast and dry bias (underestimation) over Indian land mass even at pentad 1 lead and these biases consistently increase up to 4 pentad lead and s...
7 CitationsSource
#1Xiouhua Fu (U.H.: University of Hawaii at Manoa)H-Index: 25
#2June-Yi Lee (U.H.: University of Hawaii at Manoa)H-Index: 31
Last. Scott J. Weaver (NOAA: National Oceanic and Atmospheric Administration)H-Index: 17
view all 7 authors...
The present study assesses the forecast skill of the Madden–Julian Oscillation (MJO) observed during the period of DYNAMO (Dynamics of the MJO)/CINDY (Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011) field campaign in the GFS (NCEP Global Forecast System), CFSv2 (NCEP Climate Forecast System version 2) and UH (University of Hawaii) models, and revealed their strength and weakness in forecasting initiation and propagation of the MJO. Overall, the models forecast bett...
62 CitationsSource
#1S. Sharmila (IITM: Indian Institute of Tropical Meteorology)H-Index: 10
#2Prasanth A. Pillai (IITM: Indian Institute of Tropical Meteorology)H-Index: 9
Last. Bhupendra Nath Goswami (IITM: Indian Institute of Tropical Meteorology)H-Index: 46
view all 9 authors...
Atmospheric dynamical mechanisms have been prevalently used to explain the characteristics of the sum- mer monsoon intraseasonal oscillation (MISO), which dictates the wet and dry spells of the monsoon rainfall. Recent studies show that ocean-atmosphere coupling has a vital role in simulating the observed amplitude and rela- tionship between precipitation and sea surface temperature (SST) at the intraseasonal scale. However it is not clear whether this role is simply 'passive' response to the at...
55 CitationsSource
#1Mathew Koll Roxy (IITM: Indian Institute of Tropical Meteorology)H-Index: 14
#2Youichi Tanimoto (Hokkaido University)H-Index: 26
Last. R. Krishnan (IITM: Indian Institute of Tropical Meteorology)H-Index: 21
view all 5 authors...
The SST-precipitation relationship in the intraseasonal variability (ISV) over the Asian monsoon region is examined using recent high quality satellite data and simulations from a state of the art coupled model, the climate forecast system version 2 (CFSv2). CFSv2 demonstrates high skill in reproducing the spatial distribution of the observed climatological mean summer monsoon precipitation along with its interannual variability, a task which has been a conundrum for many recent climate coupled ...
67 CitationsSource
#1Xiouhua FuH-Index: 25
#2June-Yi LeeH-Index: 31
Last. Frederic VitartH-Index: 37
view all 5 authors...
AbstractThe boreal summer intraseasonal oscillation (BSISO) is a dominant tropical mode with a period of 30–60 days, which offers an opportunity for intraseasonal forecasting of the Asian summer monsoon. The present study provides a preliminary, yet up-to-date, assessment of the prediction skill of the BSISO in four state-of-the-art models: the ECMWF model, the University of Hawaii (UH) model, the NCEP Climate Forecast System, version 2 (CFSv2), and version 1 for the 2008 summer (CFSv1), which i...
26 CitationsSource
#1E. Suhas (UCSD: University of California, San Diego)H-Index: 1
#2J. M. Neena (UCLA: University of California, Los Angeles)H-Index: 1
Last. Bhupendra Nath Goswami (IITM: Indian Institute of Tropical Meteorology)H-Index: 46
view all 3 authors...
The wet/dry spells of the Indian summer monsoon (ISM) rainfall are governed by northward propagating boreal summer monsoon intraseasonal oscillations (MISO). Unlike for the Madden Julian Oscillation (e.g. RMM indices, Wheeler and Hendon in Mon Weather Rev 132:1917–1932, 2004), a low dimensional real-time monitoring and forecast verification metric for the MISO is not currently available. Here, for the first time, we present a real time monitoring index developed for identifying the amplitude and...
48 CitationsSource
#1Carolyn A. ReynoldsH-Index: 22
#2Justin McLayH-Index: 11
Last. Charles R. SampsonH-Index: 20
view all 6 authors...
The performance of the U.S. Navy globalatmosphericensemble prediction systemis examinedwith a focus on tropical winds and tropical cyclone tracks. Ensembles are run at a triangular truncation of T119, T159, and T239, with 33, 17, and 9 ensemble members, respectively, to evaluate the impact of resolution versus the number of ensemble member tradeoffs on ensemble performance. Results indicate that the T159 and T239 ensemble mean tropical cyclone track errors are significantly smaller than those of...
21 CitationsSource
Cited By12
Newest
#1Parthasarathi Mukhopadhyay (IITM: Indian Institute of Tropical Meteorology)H-Index: 15
#2V. S. Prasad (National Centre for Medium Range Weather Forecasting)H-Index: 4
Last. M. Rajeevan (Government of India)H-Index: 33
view all 13 authors...
A global forecast system model at a horizontal resolution of T1534 (\({\sim }12.5\, \hbox {km}\)) has been evaluated for the monsoon seasons of 2016 and 2017 over the Indian region. It is for the first time that such a high-resolution global model is being run operationally for monsoon weather forecast. A detailed validation of the model therefore is essential. The validation of mean monsoon rainfall for the season and individual months indicates a tendency for wet bias over the land region in a...
Source
#1Amit Kumar (Wadia Institute of Himalayan Geology)H-Index: 9
#2Anil K. Gupta (IIT-KGP: Indian Institute of Technology Kharagpur)H-Index: 24
Last. A.K.L. Asthana (Wadia Institute of Himalayan Geology)H-Index: 4
view all 6 authors...
Abstract Impacts of global climate change can be seen worldwide, both on developing and developed economies. In recent years, numerous researches have been carried out by the Government and Non-Government agencies in understanding, assessing, predicting, and responding to expected processes of global climate change and recommend policies for mitigation. Extreme weather events like increased precipitation, cloudbursts, flashfloods, and avalanches in the mountainous region threaten human lives, an...
2 CitationsSource
#1S. Saranya Ganesh (Savitribai Phule Pune University)H-Index: 1
#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 8 authors...
1 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’s 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 (15–20 days). Consider...
1 CitationsSource
Indian Summer Monsoon (ISM) synoptic scale systems (low-pressure systems, LPS) are known to produce increased rainfall over central India (CI). Fidelity of the Climate Forecast System version 2 (CFSv2) at simulating the LPS and their characteristics is evaluated in this study using a feature tracking algorithm. The model is able to reproduce the clustering of LPS by monsoon intra-seasonal oscillations and the associated precipitation over eastern-central India. It is found that mean biases in ci...
5 CitationsSource
#1A. K. Sahai (IITM: Indian Institute of Tropical Meteorology)H-Index: 19
#2S. Sharmila (University of Melbourne)H-Index: 10
Last. A. K. Srivastava (India Meteorological Department)H-Index: 1
view all 9 authors...
The duration and extreme fluctuations of prolonged wet or dry spells associated with intraseasonal variability during extreme monsoon have devastating impacts on agrarian-based economy over Indian subcontinent. This study examines the potential predictability limit of intraseasonal transitions between rainy to non-rainy phases (i.e., active to break phases) or vice versa over central Indian region during extreme monsoon using very high-resolution (0.25° × 0.25°) daily rainfall datasets. The pres...
Source
#1A. K. Sahai (IITM: Indian Institute of Tropical Meteorology)H-Index: 19
#2N. Borah (IITM: Indian Institute of Tropical Meteorology)H-Index: 9
Last. S. Abhilash (CUSAT: Cochin University of Science and Technology)H-Index: 11
view all 5 authors...
If a coarse resolution dynamical model can well capture the large-scale patterns even if it has bias in smaller scales, the spatial information in smaller domains may also be retrievable. Based on this hypothesis a method has been proposed to downscale the dynamical model forecasts of monsoon intraseasonal oscillations in the extended range, and thus reduce the forecast spatial biases in smaller spatial scales. A hybrid of clustering and analog technique, used in a self organizing map (SOM)-base...
2 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 v2 (CFSv2), the Global Ensemble Forecast System (GEFSv2) and four products from...
10 CitationsSource
#1Balachandrudu Narapusetty (GSFC: Goddard Space Flight Center)H-Index: 1
#2Raghu MurtuguddeH-Index: 32
Last. Arun Kumar (NOAA: National Oceanic and Atmospheric Administration)H-Index: 57
view all 4 authors...
This paper analyzes the role of the Indian Ocean (IO) and the atmosphere biases in generating and sustaining large-scale precipitation biases over Central India (CI) during the Indian summer monsoon (ISM) in the climate forecast system version 2 (CFSv2) hindcasts that are produced by initializing the system each month from January 1982 to March 2011. The CFSv2 hindcasts are characterized by a systematic dry monsoon bias over CI that deteriorate with forecast lead-times and coexist with a wet bia...
11 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