Loading…
Interplay Between Subseasonal Rainfall and Global Predictors in Modulating Interannual to Multidecadal Predictability of the ISMR
Skillful prediction of the Indian Summer Monsoon Rainfall (ISMR) has been a bottleneck problem for more than 100 years. The low seasonal predictability is attributed primarily to the chaotic nature of the subseasonal variability. Here, we show that these subseasonal variabilities rather have signifi...
Saved in:
Published in: | Geophysical research letters 2021-01, Vol.48 (1), p.n/a |
---|---|
Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c2784-67343856ea49ffd7f2d92373813e107bd7c9951dee9ee3b8bb7d27e2f558c5533 |
---|---|
cites | cdi_FETCH-LOGICAL-c2784-67343856ea49ffd7f2d92373813e107bd7c9951dee9ee3b8bb7d27e2f558c5533 |
container_end_page | n/a |
container_issue | 1 |
container_start_page | |
container_title | Geophysical research letters |
container_volume | 48 |
creator | Saha, Subodh Kumar Konwar, Mahen Pokhrel, Samir Hazra, Anupam Chaudhari, Hemantkumar S. Rai, Archana |
description | Skillful prediction of the Indian Summer Monsoon Rainfall (ISMR) has been a bottleneck problem for more than 100 years. The low seasonal predictability is attributed primarily to the chaotic nature of the subseasonal variability. Here, we show that these subseasonal variabilities rather have significant predictable contributions to the seasonal ISMR, varying on the interannual to multidecadal timescale. The subseasonal modes being the building blocks of the monsoon, their net linear contribution may approximate the predictability limit of the ISMR. It is estimated that an average of about 76% (R ∼ 0.87) of the ISMR variance predictable around the 1960s is decreased to about 64% (R ∼ 0.79) in the recent past four decades. It is suggested that improvements in the simulation of subseasonal, particularly the synoptic variability will be key to further improve the seasonal ISMR forecast skill.
Plain Language Summary
Skillful prediction of seasonal (June‐to‐September) Indian Summer Monsoon Rainfall (ISMR) has been always a big challenge for the forecasters due to its complex nature of feedback. From the perspective of seasonal prediction, the subseasonal variability of the monsoon rainfall is primarily considered as noise (e.g., Webster et al., 1998). However, using 118 years of observed rainfall data, we show that subseasonal modes of monsoon (i.e., synoptic, supersynoptic, and intraseasonal oscillation) linked with the primary global predictors, contribute significantly to the seasonal anomaly of the ISMR. The complex association of subseasonal modes with the global predictors, which vary on interannual to the multidecadal timescale, shapes the predictability of the ISMR. As a result, the prediction of seasonal ISMR is more accurate in some decades than the others. It is estimated that an average of about 76% (R ∼ 0.87) of the interannual ISMR variance was predictable around the 1960s and that has now decreased to about 64% (R ∼ 0.79) in the past four decades. It is suggested that a better understanding of the mechanisms of subseasonal modes and consequently their reasonable simulation (space‐time statistics, particularly the synoptic variability) is the key to further improve the seasonal ISMR forecast.
Key Points
The subseasonal variability, generally considered as noise, is found to have a significant predictable contribution to the seasonal Indian Summer Monsoon Rainfall (ISMR)
The synoptic variability contributes a maximum to the ISMR predictability follo |
doi_str_mv | 10.1029/2020GL091458 |
format | article |
fullrecord | <record><control><sourceid>wiley_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1029_2020GL091458</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>GRL61704</sourcerecordid><originalsourceid>FETCH-LOGICAL-c2784-67343856ea49ffd7f2d92373813e107bd7c9951dee9ee3b8bb7d27e2f558c5533</originalsourceid><addsrcrecordid>eNp9kEFLxDAUhIMouK7e_AH5AVZfkrZpjrpoXeii7Oq5pM2rRmK6NC1Lj_5zqyvoydMbHt_MwBByzuCSAVdXHDjkBSgWJ9kBmTEVx1EGIA_JDEBNmsv0mJyE8AYAAgSbkY-l77HbOj3SG-x3iJ5uhiqgDq3Xjq619Y12jmpvaO7aavo9dmhs3bddoNbTVWsGp3vrX-h3lPZ-mKC-pavB9dZgrc2vSVfW2X6kbUP7V6TLzWp9So6mhoBnP3dOnu9unxb3UfGQLxfXRVRzmcVRKkUssiRFHaumMbLhRnEhRcYEMpCVkbVSCTOIClFUWVVJwyXyJkmyOkmEmJOLfW7dtSF02JTbzr7rbiwZlF_zlX_nm3C-x3fW4fgvW-brImUSYvEJNhxyxg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Interplay Between Subseasonal Rainfall and Global Predictors in Modulating Interannual to Multidecadal Predictability of the ISMR</title><source>Wiley-Blackwell AGU Digital Archive</source><creator>Saha, Subodh Kumar ; Konwar, Mahen ; Pokhrel, Samir ; Hazra, Anupam ; Chaudhari, Hemantkumar S. ; Rai, Archana</creator><creatorcontrib>Saha, Subodh Kumar ; Konwar, Mahen ; Pokhrel, Samir ; Hazra, Anupam ; Chaudhari, Hemantkumar S. ; Rai, Archana</creatorcontrib><description>Skillful prediction of the Indian Summer Monsoon Rainfall (ISMR) has been a bottleneck problem for more than 100 years. The low seasonal predictability is attributed primarily to the chaotic nature of the subseasonal variability. Here, we show that these subseasonal variabilities rather have significant predictable contributions to the seasonal ISMR, varying on the interannual to multidecadal timescale. The subseasonal modes being the building blocks of the monsoon, their net linear contribution may approximate the predictability limit of the ISMR. It is estimated that an average of about 76% (R ∼ 0.87) of the ISMR variance predictable around the 1960s is decreased to about 64% (R ∼ 0.79) in the recent past four decades. It is suggested that improvements in the simulation of subseasonal, particularly the synoptic variability will be key to further improve the seasonal ISMR forecast skill.
Plain Language Summary
Skillful prediction of seasonal (June‐to‐September) Indian Summer Monsoon Rainfall (ISMR) has been always a big challenge for the forecasters due to its complex nature of feedback. From the perspective of seasonal prediction, the subseasonal variability of the monsoon rainfall is primarily considered as noise (e.g., Webster et al., 1998). However, using 118 years of observed rainfall data, we show that subseasonal modes of monsoon (i.e., synoptic, supersynoptic, and intraseasonal oscillation) linked with the primary global predictors, contribute significantly to the seasonal anomaly of the ISMR. The complex association of subseasonal modes with the global predictors, which vary on interannual to the multidecadal timescale, shapes the predictability of the ISMR. As a result, the prediction of seasonal ISMR is more accurate in some decades than the others. It is estimated that an average of about 76% (R ∼ 0.87) of the interannual ISMR variance was predictable around the 1960s and that has now decreased to about 64% (R ∼ 0.79) in the past four decades. It is suggested that a better understanding of the mechanisms of subseasonal modes and consequently their reasonable simulation (space‐time statistics, particularly the synoptic variability) is the key to further improve the seasonal ISMR forecast.
Key Points
The subseasonal variability, generally considered as noise, is found to have a significant predictable contribution to the seasonal Indian Summer Monsoon Rainfall (ISMR)
The synoptic variability contributes a maximum to the ISMR predictability followed by supersynoptic and Monsoon Intraseasonal Oscillations
A complex phase relationship between predictors and subseasonal variance modulates the ISMR predictability on decadal to multidecadal timescale</description><identifier>ISSN: 0094-8276</identifier><identifier>EISSN: 1944-8007</identifier><identifier>DOI: 10.1029/2020GL091458</identifier><language>eng</language><ispartof>Geophysical research letters, 2021-01, Vol.48 (1), p.n/a</ispartof><rights>2020. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2784-67343856ea49ffd7f2d92373813e107bd7c9951dee9ee3b8bb7d27e2f558c5533</citedby><cites>FETCH-LOGICAL-c2784-67343856ea49ffd7f2d92373813e107bd7c9951dee9ee3b8bb7d27e2f558c5533</cites><orcidid>0000-0002-6925-1890 ; 0000-0001-7816-4425 ; 0000-0001-7489-5394 ; 0000-0003-3011-2428 ; 0000-0002-8658-9412</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2020GL091458$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2020GL091458$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,777,781,11495,27905,27906,46449,46873</link.rule.ids></links><search><creatorcontrib>Saha, Subodh Kumar</creatorcontrib><creatorcontrib>Konwar, Mahen</creatorcontrib><creatorcontrib>Pokhrel, Samir</creatorcontrib><creatorcontrib>Hazra, Anupam</creatorcontrib><creatorcontrib>Chaudhari, Hemantkumar S.</creatorcontrib><creatorcontrib>Rai, Archana</creatorcontrib><title>Interplay Between Subseasonal Rainfall and Global Predictors in Modulating Interannual to Multidecadal Predictability of the ISMR</title><title>Geophysical research letters</title><description>Skillful prediction of the Indian Summer Monsoon Rainfall (ISMR) has been a bottleneck problem for more than 100 years. The low seasonal predictability is attributed primarily to the chaotic nature of the subseasonal variability. Here, we show that these subseasonal variabilities rather have significant predictable contributions to the seasonal ISMR, varying on the interannual to multidecadal timescale. The subseasonal modes being the building blocks of the monsoon, their net linear contribution may approximate the predictability limit of the ISMR. It is estimated that an average of about 76% (R ∼ 0.87) of the ISMR variance predictable around the 1960s is decreased to about 64% (R ∼ 0.79) in the recent past four decades. It is suggested that improvements in the simulation of subseasonal, particularly the synoptic variability will be key to further improve the seasonal ISMR forecast skill.
Plain Language Summary
Skillful prediction of seasonal (June‐to‐September) Indian Summer Monsoon Rainfall (ISMR) has been always a big challenge for the forecasters due to its complex nature of feedback. From the perspective of seasonal prediction, the subseasonal variability of the monsoon rainfall is primarily considered as noise (e.g., Webster et al., 1998). However, using 118 years of observed rainfall data, we show that subseasonal modes of monsoon (i.e., synoptic, supersynoptic, and intraseasonal oscillation) linked with the primary global predictors, contribute significantly to the seasonal anomaly of the ISMR. The complex association of subseasonal modes with the global predictors, which vary on interannual to the multidecadal timescale, shapes the predictability of the ISMR. As a result, the prediction of seasonal ISMR is more accurate in some decades than the others. It is estimated that an average of about 76% (R ∼ 0.87) of the interannual ISMR variance was predictable around the 1960s and that has now decreased to about 64% (R ∼ 0.79) in the past four decades. It is suggested that a better understanding of the mechanisms of subseasonal modes and consequently their reasonable simulation (space‐time statistics, particularly the synoptic variability) is the key to further improve the seasonal ISMR forecast.
Key Points
The subseasonal variability, generally considered as noise, is found to have a significant predictable contribution to the seasonal Indian Summer Monsoon Rainfall (ISMR)
The synoptic variability contributes a maximum to the ISMR predictability followed by supersynoptic and Monsoon Intraseasonal Oscillations
A complex phase relationship between predictors and subseasonal variance modulates the ISMR predictability on decadal to multidecadal timescale</description><issn>0094-8276</issn><issn>1944-8007</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kEFLxDAUhIMouK7e_AH5AVZfkrZpjrpoXeii7Oq5pM2rRmK6NC1Lj_5zqyvoydMbHt_MwBByzuCSAVdXHDjkBSgWJ9kBmTEVx1EGIA_JDEBNmsv0mJyE8AYAAgSbkY-l77HbOj3SG-x3iJ5uhiqgDq3Xjq619Y12jmpvaO7aavo9dmhs3bddoNbTVWsGp3vrX-h3lPZ-mKC-pavB9dZgrc2vSVfW2X6kbUP7V6TLzWp9So6mhoBnP3dOnu9unxb3UfGQLxfXRVRzmcVRKkUssiRFHaumMbLhRnEhRcYEMpCVkbVSCTOIClFUWVVJwyXyJkmyOkmEmJOLfW7dtSF02JTbzr7rbiwZlF_zlX_nm3C-x3fW4fgvW-brImUSYvEJNhxyxg</recordid><startdate>20210116</startdate><enddate>20210116</enddate><creator>Saha, Subodh Kumar</creator><creator>Konwar, Mahen</creator><creator>Pokhrel, Samir</creator><creator>Hazra, Anupam</creator><creator>Chaudhari, Hemantkumar S.</creator><creator>Rai, Archana</creator><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-6925-1890</orcidid><orcidid>https://orcid.org/0000-0001-7816-4425</orcidid><orcidid>https://orcid.org/0000-0001-7489-5394</orcidid><orcidid>https://orcid.org/0000-0003-3011-2428</orcidid><orcidid>https://orcid.org/0000-0002-8658-9412</orcidid></search><sort><creationdate>20210116</creationdate><title>Interplay Between Subseasonal Rainfall and Global Predictors in Modulating Interannual to Multidecadal Predictability of the ISMR</title><author>Saha, Subodh Kumar ; Konwar, Mahen ; Pokhrel, Samir ; Hazra, Anupam ; Chaudhari, Hemantkumar S. ; Rai, Archana</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2784-67343856ea49ffd7f2d92373813e107bd7c9951dee9ee3b8bb7d27e2f558c5533</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Saha, Subodh Kumar</creatorcontrib><creatorcontrib>Konwar, Mahen</creatorcontrib><creatorcontrib>Pokhrel, Samir</creatorcontrib><creatorcontrib>Hazra, Anupam</creatorcontrib><creatorcontrib>Chaudhari, Hemantkumar S.</creatorcontrib><creatorcontrib>Rai, Archana</creatorcontrib><collection>CrossRef</collection><jtitle>Geophysical research letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Saha, Subodh Kumar</au><au>Konwar, Mahen</au><au>Pokhrel, Samir</au><au>Hazra, Anupam</au><au>Chaudhari, Hemantkumar S.</au><au>Rai, Archana</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Interplay Between Subseasonal Rainfall and Global Predictors in Modulating Interannual to Multidecadal Predictability of the ISMR</atitle><jtitle>Geophysical research letters</jtitle><date>2021-01-16</date><risdate>2021</risdate><volume>48</volume><issue>1</issue><epage>n/a</epage><issn>0094-8276</issn><eissn>1944-8007</eissn><abstract>Skillful prediction of the Indian Summer Monsoon Rainfall (ISMR) has been a bottleneck problem for more than 100 years. The low seasonal predictability is attributed primarily to the chaotic nature of the subseasonal variability. Here, we show that these subseasonal variabilities rather have significant predictable contributions to the seasonal ISMR, varying on the interannual to multidecadal timescale. The subseasonal modes being the building blocks of the monsoon, their net linear contribution may approximate the predictability limit of the ISMR. It is estimated that an average of about 76% (R ∼ 0.87) of the ISMR variance predictable around the 1960s is decreased to about 64% (R ∼ 0.79) in the recent past four decades. It is suggested that improvements in the simulation of subseasonal, particularly the synoptic variability will be key to further improve the seasonal ISMR forecast skill.
Plain Language Summary
Skillful prediction of seasonal (June‐to‐September) Indian Summer Monsoon Rainfall (ISMR) has been always a big challenge for the forecasters due to its complex nature of feedback. From the perspective of seasonal prediction, the subseasonal variability of the monsoon rainfall is primarily considered as noise (e.g., Webster et al., 1998). However, using 118 years of observed rainfall data, we show that subseasonal modes of monsoon (i.e., synoptic, supersynoptic, and intraseasonal oscillation) linked with the primary global predictors, contribute significantly to the seasonal anomaly of the ISMR. The complex association of subseasonal modes with the global predictors, which vary on interannual to the multidecadal timescale, shapes the predictability of the ISMR. As a result, the prediction of seasonal ISMR is more accurate in some decades than the others. It is estimated that an average of about 76% (R ∼ 0.87) of the interannual ISMR variance was predictable around the 1960s and that has now decreased to about 64% (R ∼ 0.79) in the past four decades. It is suggested that a better understanding of the mechanisms of subseasonal modes and consequently their reasonable simulation (space‐time statistics, particularly the synoptic variability) is the key to further improve the seasonal ISMR forecast.
Key Points
The subseasonal variability, generally considered as noise, is found to have a significant predictable contribution to the seasonal Indian Summer Monsoon Rainfall (ISMR)
The synoptic variability contributes a maximum to the ISMR predictability followed by supersynoptic and Monsoon Intraseasonal Oscillations
A complex phase relationship between predictors and subseasonal variance modulates the ISMR predictability on decadal to multidecadal timescale</abstract><doi>10.1029/2020GL091458</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-6925-1890</orcidid><orcidid>https://orcid.org/0000-0001-7816-4425</orcidid><orcidid>https://orcid.org/0000-0001-7489-5394</orcidid><orcidid>https://orcid.org/0000-0003-3011-2428</orcidid><orcidid>https://orcid.org/0000-0002-8658-9412</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0094-8276 |
ispartof | Geophysical research letters, 2021-01, Vol.48 (1), p.n/a |
issn | 0094-8276 1944-8007 |
language | eng |
recordid | cdi_crossref_primary_10_1029_2020GL091458 |
source | Wiley-Blackwell AGU Digital Archive |
title | Interplay Between Subseasonal Rainfall and Global Predictors in Modulating Interannual to Multidecadal Predictability of the ISMR |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T02%3A44%3A41IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-wiley_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Interplay%20Between%20Subseasonal%20Rainfall%20and%20Global%20Predictors%20in%20Modulating%20Interannual%20to%20Multidecadal%20Predictability%20of%20the%20ISMR&rft.jtitle=Geophysical%20research%20letters&rft.au=Saha,%20Subodh%20Kumar&rft.date=2021-01-16&rft.volume=48&rft.issue=1&rft.epage=n/a&rft.issn=0094-8276&rft.eissn=1944-8007&rft_id=info:doi/10.1029/2020GL091458&rft_dat=%3Cwiley_cross%3EGRL61704%3C/wiley_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c2784-67343856ea49ffd7f2d92373813e107bd7c9951dee9ee3b8bb7d27e2f558c5533%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |