Diverse skill of seasonal dynamical models in forecasting South Asian monsoon precipitation and the influence of ENSO and IOD
The South Asia Seasonal Climate Outlook Forum (SASCOF) issues seasonal tercile precipitation forecasts to provide advance warning of anomalously dry or wet monsoon seasons in South Asia. To increase objectivity of the SASCOF seasonal outlook, the World Meteorological Organisation recommends using a...
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description | The South Asia Seasonal Climate Outlook Forum (SASCOF) issues seasonal tercile precipitation forecasts to provide advance warning of anomalously dry or wet monsoon seasons in South Asia. To increase objectivity of the SASCOF seasonal outlook, the World Meteorological Organisation recommends using a multi-model ensemble combining the most skilful dynamical seasonal models for the region. We assess the skill of 12 dynamical models at forecasting seasonal precipitation totals for 1993–2016 for the southwest (June–July–August–September) and northeast (October–November–December) monsoon seasons at regional and national levels for Afghanistan, Bangladesh, Nepal, and Pakistan, using identical forecast periods, hindcast initialisation months and domain used at the SASCOF. All models demonstrate positive skill when regionally-averaged, especially for the southwest monsoon season, noting considerable spatial differences. Models exhibit highest skill where correlation between observed precipitation and El Niño Southern Oscillation (ENSO) is highest, e.g., central/north India and Nepal during the southwest monsoon, and Afghanistan and north Pakistan during the northeast monsoon. Model skill is especially low in northwest India and northeast of South Asia during the southwest monsoon, e.g., Bangladesh (despite high precipitation totals) coinciding with a weak ENSO teleconnection. The Indian Ocean Dipole teleconnection is less pronounced in the southwest monsoon season, whereas the spatial pattern for the northeast monsoon closely resembles that of ENSO. Due to high variability in model skill, we recommend basing the SASCOF forecast on a multi-model ensemble of all models but discounting poorly performing models at the national level. |
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All models demonstrate positive skill when regionally-averaged, especially for the southwest monsoon season, noting considerable spatial differences. Models exhibit highest skill where correlation between observed precipitation and El Niño Southern Oscillation (ENSO) is highest, e.g., central/north India and Nepal during the southwest monsoon, and Afghanistan and north Pakistan during the northeast monsoon. Model skill is especially low in northwest India and northeast of South Asia during the southwest monsoon, e.g., Bangladesh (despite high precipitation totals) coinciding with a weak ENSO teleconnection. The Indian Ocean Dipole teleconnection is less pronounced in the southwest monsoon season, whereas the spatial pattern for the northeast monsoon closely resembles that of ENSO. Due to high variability in model skill, we recommend basing the SASCOF forecast on a multi-model ensemble of all models but discounting poorly performing models at the national level.</description><identifier>ISSN: 0930-7575</identifier><identifier>EISSN: 1432-0894</identifier><identifier>DOI: 10.1007/s00382-023-06770-2</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Afghanistan ; Bangladesh ; climate ; Climate models ; Climatology ; Dipoles ; Dynamic models ; Earth and Environmental Science ; Earth Sciences ; El Nino ; El Nino phenomena ; El Nino-Southern Oscillation event ; Ensemble forecasting ; Environmental aspects ; Geophysics/Geodesy ; India ; Indian Ocean ; Methods ; Modelling ; Monsoon forecasting ; Monsoon precipitation ; monsoon season ; Monsoons ; Nepal ; Oceanography ; Pakistan ; Precipitation ; Precipitation (Meteorology) ; Precipitation forecasting ; Seasonal precipitation ; Seasons ; South Asian monsoon ; Southern Oscillation ; Southwest monsoon ; Spatial variations ; Teleconnections ; Weather forecasting ; Wind</subject><ispartof>Climate dynamics, 2023-10, Vol.61 (7-8), p.3857-3874</ispartof><rights>Crown 2023</rights><rights>COPYRIGHT 2023 Springer</rights><rights>Crown 2023. 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E.</creatorcontrib><creatorcontrib>Srinivasan, G.</creatorcontrib><creatorcontrib>Pai, D. S.</creatorcontrib><title>Diverse skill of seasonal dynamical models in forecasting South Asian monsoon precipitation and the influence of ENSO and IOD</title><title>Climate dynamics</title><addtitle>Clim Dyn</addtitle><description>The South Asia Seasonal Climate Outlook Forum (SASCOF) issues seasonal tercile precipitation forecasts to provide advance warning of anomalously dry or wet monsoon seasons in South Asia. To increase objectivity of the SASCOF seasonal outlook, the World Meteorological Organisation recommends using a multi-model ensemble combining the most skilful dynamical seasonal models for the region. We assess the skill of 12 dynamical models at forecasting seasonal precipitation totals for 1993–2016 for the southwest (June–July–August–September) and northeast (October–November–December) monsoon seasons at regional and national levels for Afghanistan, Bangladesh, Nepal, and Pakistan, using identical forecast periods, hindcast initialisation months and domain used at the SASCOF. All models demonstrate positive skill when regionally-averaged, especially for the southwest monsoon season, noting considerable spatial differences. Models exhibit highest skill where correlation between observed precipitation and El Niño Southern Oscillation (ENSO) is highest, e.g., central/north India and Nepal during the southwest monsoon, and Afghanistan and north Pakistan during the northeast monsoon. Model skill is especially low in northwest India and northeast of South Asia during the southwest monsoon, e.g., Bangladesh (despite high precipitation totals) coinciding with a weak ENSO teleconnection. The Indian Ocean Dipole teleconnection is less pronounced in the southwest monsoon season, whereas the spatial pattern for the northeast monsoon closely resembles that of ENSO. Due to high variability in model skill, we recommend basing the SASCOF forecast on a multi-model ensemble of all models but discounting poorly performing models at the national level.</description><subject>Afghanistan</subject><subject>Bangladesh</subject><subject>climate</subject><subject>Climate models</subject><subject>Climatology</subject><subject>Dipoles</subject><subject>Dynamic models</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>El Nino</subject><subject>El Nino phenomena</subject><subject>El Nino-Southern Oscillation event</subject><subject>Ensemble forecasting</subject><subject>Environmental aspects</subject><subject>Geophysics/Geodesy</subject><subject>India</subject><subject>Indian Ocean</subject><subject>Methods</subject><subject>Modelling</subject><subject>Monsoon forecasting</subject><subject>Monsoon precipitation</subject><subject>monsoon season</subject><subject>Monsoons</subject><subject>Nepal</subject><subject>Oceanography</subject><subject>Pakistan</subject><subject>Precipitation</subject><subject>Precipitation (Meteorology)</subject><subject>Precipitation forecasting</subject><subject>Seasonal precipitation</subject><subject>Seasons</subject><subject>South Asian monsoon</subject><subject>Southern Oscillation</subject><subject>Southwest monsoon</subject><subject>Spatial variations</subject><subject>Teleconnections</subject><subject>Weather forecasting</subject><subject>Wind</subject><issn>0930-7575</issn><issn>1432-0894</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kk1v1DAQhiMEEkvhD3CKhITgkHZiJ3ZyXLUFVqq6Egtny3Emuy5ee8k4FT3w3_E2SLAckA-ej-cdaUZvlr0u4bwEkBcEwBtWAOMFCCmhYE-yRVnxVGra6mm2gJZDIWtZP89eEN0BlJWQbJH9vLL3OBLm9M06l4chJ9QUvHZ5_-D13poU7UOPjnLr8yGMaDRF67f5Jkxxly_Jap8ITyH4_JDa9mCjjjZl2vd53GESDm5Cb_A4__p2s37srNZXL7Nng3aEr37_Z9nXD9dfLj8VN-uPq8vlTWFqgFj0UrRVKxsczIDN0IMoeSs6wLIzGmXXs66rhJHQSQbY1rqVRvS84T30bZWis-zdPPcwhu8TUlR7Swad0x7DRIqXNWfAWdUm9M0_6F2YxnQPUqypRVmDaEWizmdqqx2qtF-Iozbp9ZhOFjwONtWXUjAoOYej4P2JIDERf8StnojUavP5lH37F7tD7eKOgpuON6VTkM2gGQPRiIM6jHavxwdVgjr6Qs2-UMkX6tEXiiURn0WUYL_F8c-C_1H9AhA-uWo</recordid><startdate>20231001</startdate><enddate>20231001</enddate><creator>Stacey, J.</creator><creator>Salmon, K.</creator><creator>Janes, T.</creator><creator>Colman, A.</creator><creator>Colledge, F.</creator><creator>Bett, P. 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E.</au><au>Srinivasan, G.</au><au>Pai, D. S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Diverse skill of seasonal dynamical models in forecasting South Asian monsoon precipitation and the influence of ENSO and IOD</atitle><jtitle>Climate dynamics</jtitle><stitle>Clim Dyn</stitle><date>2023-10-01</date><risdate>2023</risdate><volume>61</volume><issue>7-8</issue><spage>3857</spage><epage>3874</epage><pages>3857-3874</pages><issn>0930-7575</issn><eissn>1432-0894</eissn><abstract>The South Asia Seasonal Climate Outlook Forum (SASCOF) issues seasonal tercile precipitation forecasts to provide advance warning of anomalously dry or wet monsoon seasons in South Asia. To increase objectivity of the SASCOF seasonal outlook, the World Meteorological Organisation recommends using a multi-model ensemble combining the most skilful dynamical seasonal models for the region. We assess the skill of 12 dynamical models at forecasting seasonal precipitation totals for 1993–2016 for the southwest (June–July–August–September) and northeast (October–November–December) monsoon seasons at regional and national levels for Afghanistan, Bangladesh, Nepal, and Pakistan, using identical forecast periods, hindcast initialisation months and domain used at the SASCOF. All models demonstrate positive skill when regionally-averaged, especially for the southwest monsoon season, noting considerable spatial differences. Models exhibit highest skill where correlation between observed precipitation and El Niño Southern Oscillation (ENSO) is highest, e.g., central/north India and Nepal during the southwest monsoon, and Afghanistan and north Pakistan during the northeast monsoon. Model skill is especially low in northwest India and northeast of South Asia during the southwest monsoon, e.g., Bangladesh (despite high precipitation totals) coinciding with a weak ENSO teleconnection. The Indian Ocean Dipole teleconnection is less pronounced in the southwest monsoon season, whereas the spatial pattern for the northeast monsoon closely resembles that of ENSO. Due to high variability in model skill, we recommend basing the SASCOF forecast on a multi-model ensemble of all models but discounting poorly performing models at the national level.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00382-023-06770-2</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0002-4452-491X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Afghanistan Bangladesh climate Climate models Climatology Dipoles Dynamic models Earth and Environmental Science Earth Sciences El Nino El Nino phenomena El Nino-Southern Oscillation event Ensemble forecasting Environmental aspects Geophysics/Geodesy India Indian Ocean Methods Modelling Monsoon forecasting Monsoon precipitation monsoon season Monsoons Nepal Oceanography Pakistan Precipitation Precipitation (Meteorology) Precipitation forecasting Seasonal precipitation Seasons South Asian monsoon Southern Oscillation Southwest monsoon Spatial variations Teleconnections Weather forecasting Wind |
title | Diverse skill of seasonal dynamical models in forecasting South Asian monsoon precipitation and the influence of ENSO and IOD |
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