Dynamic Downscaling the South Asian Summer Monsoon From a Global Reanalysis Using a Regional Coupled Ocean‐Atmosphere Model

In this study, we present the results of a regional model (regional spectral model‐regional ocean model [(RSM‐ROMS]) simulation of the South Asian Summer Monsoon (SASM). The RSM‐ROMS integration is carried out at 20 km grid spacing over a period of 25 years (1986–2010). The simulation is forced by g...

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Veröffentlicht in:Journal of geophysical research. Atmospheres 2022-11, Vol.127 (22), p.n/a
Hauptverfasser: Misra, Vasubandhu, Jayasankar, C. B., Mishra, A. K., Mitra, A., Murugavel, P.
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container_title Journal of geophysical research. Atmospheres
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creator Misra, Vasubandhu
Jayasankar, C. B.
Mishra, A. K.
Mitra, A.
Murugavel, P.
description In this study, we present the results of a regional model (regional spectral model‐regional ocean model [(RSM‐ROMS]) simulation of the South Asian Summer Monsoon (SASM). The RSM‐ROMS integration is carried out at 20 km grid spacing over a period of 25 years (1986–2010). The simulation is forced by global atmospheric and oceanic reanalysis. The RSM‐ROMS simulation shows a realistic alignment of the simulated rainfall along the orographic features of the domain. Furthermore, the RSM‐ROMS simulates the observed feature of convection over continental SASM region being more vigorous with dominance of mixed warm and cold phase hydrometeors in contrast to the dominance of the warm rain process in the neighboring tropical oceans. Similarly, the upper ocean features of contrasting mixed layer and thermocline depths between the northern and equatorial Indian Ocean are also simulated in the RSM‐ROMS. Intra‐Seasonal Oscillation (ISO) of the SASM at 10–20 and 20–70 days are also simulated in the RSM‐ROMS with many of its features verifying with observations. For example, the 20–70 days ISO are of higher amplitude and its meridional propagation is slower in Bay of Bengal compared to that over Arabian Sea. Additionally, RSM‐ROMS shows 12.3 Monsoon Low Pressure Systems (LPSs) per season that is comparable to 14.6 per season from observations. Furthermore, the observed intraseasonal contrasts of LPS between the wet and dry spells of ISO is also reproduced in the RSM‐ROMS. Plain Language Summary The South Asian Summer Monsoon (SASM) climate represents a complex mix of variations across many spatio‐temporal scales over a region with unique topographic and bathymetric features. As a result, the simulation of the SASM climate offers a stiff challenge to numerical climate models. In this study, we evaluate the added value of a regional coupled ocean‐atmosphere model in downscaling the SASM climate from a 2.5° × 2.5° global atmospheric reanalysis and 0.5° × 0.5° global ocean reanalysis to 20 km grid spacing. The regional model demonstrates significant skill in capturing the observed features of the intra‐seasonal oscillations of the SASM besides displaying reasonable fidelity of simulating and improving the mean climate of the SASM. Furthermore, at 20 km grid spacing, the regional model simulates the seasonal and intraseasonal activity of the monsoon low pressure systems that is comparable to observations. Therefore, the regional model at 20 km grid spacing of this study clearly
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B. ; Mishra, A. K. ; Mitra, A. ; Murugavel, P.</creator><creatorcontrib>Misra, Vasubandhu ; Jayasankar, C. B. ; Mishra, A. K. ; Mitra, A. ; Murugavel, P.</creatorcontrib><description>In this study, we present the results of a regional model (regional spectral model‐regional ocean model [(RSM‐ROMS]) simulation of the South Asian Summer Monsoon (SASM). The RSM‐ROMS integration is carried out at 20 km grid spacing over a period of 25 years (1986–2010). The simulation is forced by global atmospheric and oceanic reanalysis. The RSM‐ROMS simulation shows a realistic alignment of the simulated rainfall along the orographic features of the domain. Furthermore, the RSM‐ROMS simulates the observed feature of convection over continental SASM region being more vigorous with dominance of mixed warm and cold phase hydrometeors in contrast to the dominance of the warm rain process in the neighboring tropical oceans. Similarly, the upper ocean features of contrasting mixed layer and thermocline depths between the northern and equatorial Indian Ocean are also simulated in the RSM‐ROMS. Intra‐Seasonal Oscillation (ISO) of the SASM at 10–20 and 20–70 days are also simulated in the RSM‐ROMS with many of its features verifying with observations. For example, the 20–70 days ISO are of higher amplitude and its meridional propagation is slower in Bay of Bengal compared to that over Arabian Sea. Additionally, RSM‐ROMS shows 12.3 Monsoon Low Pressure Systems (LPSs) per season that is comparable to 14.6 per season from observations. Furthermore, the observed intraseasonal contrasts of LPS between the wet and dry spells of ISO is also reproduced in the RSM‐ROMS. Plain Language Summary The South Asian Summer Monsoon (SASM) climate represents a complex mix of variations across many spatio‐temporal scales over a region with unique topographic and bathymetric features. As a result, the simulation of the SASM climate offers a stiff challenge to numerical climate models. In this study, we evaluate the added value of a regional coupled ocean‐atmosphere model in downscaling the SASM climate from a 2.5° × 2.5° global atmospheric reanalysis and 0.5° × 0.5° global ocean reanalysis to 20 km grid spacing. The regional model demonstrates significant skill in capturing the observed features of the intra‐seasonal oscillations of the SASM besides displaying reasonable fidelity of simulating and improving the mean climate of the SASM. Furthermore, at 20 km grid spacing, the regional model simulates the seasonal and intraseasonal activity of the monsoon low pressure systems that is comparable to observations. Therefore, the regional model at 20 km grid spacing of this study clearly demonstrates its added value to its driving global reanalysis in the simulation of the SASM climate, and its intra‐seasonal variations. The regional model simulation also demonstrates its fidelity from the verification of the seasonal and intra‐seasonal variability of the monsoon low pressure systems of the SASM. Key Points The regional climate model displays a verifiable intraseasonal variability of precipitation The regional climate model simulates the observed unique feature of intraseasonal variations of the monsoon low pressure systems The regional climate model shows the observed contrast of convection with warm rain process dominating over ocean compared to that over land</description><identifier>ISSN: 2169-897X</identifier><identifier>EISSN: 2169-8996</identifier><identifier>DOI: 10.1029/2022JD037490</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Accuracy ; Atmosphere ; atmosphere‐ocean coupling ; Atmospheric models ; Climate ; Climate models ; Convection ; Dominance ; Dry spells ; Geophysics ; Hydrometeors ; intraseasonal oscillations ; Lipopolysaccharides ; Low pressure ; Low pressure systems ; Mixed layer ; Mixed layer depth ; Modelling ; monsoon ; Monsoon climates ; Monsoons ; Ocean models ; Oceans ; Oscillations ; Pressure ; Rainfall ; Rainfall simulators ; regional climate modeling ; Seasonal variability ; Seasonal variation ; Seasonal variations ; Seasons ; Simulated rainfall ; Simulation ; Summer ; Summer climates ; Summer monsoon ; Thermocline ; Upper ocean ; Wind</subject><ispartof>Journal of geophysical research. Atmospheres, 2022-11, Vol.127 (22), p.n/a</ispartof><rights>2022. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3454-e69c3f46c4caf4636363b1b1f93f668ac075995ad0809a9ca4d4eae03ac6fd793</citedby><cites>FETCH-LOGICAL-c3454-e69c3f46c4caf4636363b1b1f93f668ac075995ad0809a9ca4d4eae03ac6fd793</cites><orcidid>0000-0001-5926-6653 ; 0000-0002-1345-6280 ; 0000-0002-7882-5868</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%2F2022JD037490$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2022JD037490$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1416,1432,27923,27924,45573,45574,46408,46832</link.rule.ids></links><search><creatorcontrib>Misra, Vasubandhu</creatorcontrib><creatorcontrib>Jayasankar, C. B.</creatorcontrib><creatorcontrib>Mishra, A. K.</creatorcontrib><creatorcontrib>Mitra, A.</creatorcontrib><creatorcontrib>Murugavel, P.</creatorcontrib><title>Dynamic Downscaling the South Asian Summer Monsoon From a Global Reanalysis Using a Regional Coupled Ocean‐Atmosphere Model</title><title>Journal of geophysical research. Atmospheres</title><description>In this study, we present the results of a regional model (regional spectral model‐regional ocean model [(RSM‐ROMS]) simulation of the South Asian Summer Monsoon (SASM). The RSM‐ROMS integration is carried out at 20 km grid spacing over a period of 25 years (1986–2010). The simulation is forced by global atmospheric and oceanic reanalysis. The RSM‐ROMS simulation shows a realistic alignment of the simulated rainfall along the orographic features of the domain. Furthermore, the RSM‐ROMS simulates the observed feature of convection over continental SASM region being more vigorous with dominance of mixed warm and cold phase hydrometeors in contrast to the dominance of the warm rain process in the neighboring tropical oceans. Similarly, the upper ocean features of contrasting mixed layer and thermocline depths between the northern and equatorial Indian Ocean are also simulated in the RSM‐ROMS. Intra‐Seasonal Oscillation (ISO) of the SASM at 10–20 and 20–70 days are also simulated in the RSM‐ROMS with many of its features verifying with observations. For example, the 20–70 days ISO are of higher amplitude and its meridional propagation is slower in Bay of Bengal compared to that over Arabian Sea. Additionally, RSM‐ROMS shows 12.3 Monsoon Low Pressure Systems (LPSs) per season that is comparable to 14.6 per season from observations. Furthermore, the observed intraseasonal contrasts of LPS between the wet and dry spells of ISO is also reproduced in the RSM‐ROMS. Plain Language Summary The South Asian Summer Monsoon (SASM) climate represents a complex mix of variations across many spatio‐temporal scales over a region with unique topographic and bathymetric features. As a result, the simulation of the SASM climate offers a stiff challenge to numerical climate models. In this study, we evaluate the added value of a regional coupled ocean‐atmosphere model in downscaling the SASM climate from a 2.5° × 2.5° global atmospheric reanalysis and 0.5° × 0.5° global ocean reanalysis to 20 km grid spacing. The regional model demonstrates significant skill in capturing the observed features of the intra‐seasonal oscillations of the SASM besides displaying reasonable fidelity of simulating and improving the mean climate of the SASM. Furthermore, at 20 km grid spacing, the regional model simulates the seasonal and intraseasonal activity of the monsoon low pressure systems that is comparable to observations. Therefore, the regional model at 20 km grid spacing of this study clearly demonstrates its added value to its driving global reanalysis in the simulation of the SASM climate, and its intra‐seasonal variations. The regional model simulation also demonstrates its fidelity from the verification of the seasonal and intra‐seasonal variability of the monsoon low pressure systems of the SASM. Key Points The regional climate model displays a verifiable intraseasonal variability of precipitation The regional climate model simulates the observed unique feature of intraseasonal variations of the monsoon low pressure systems The regional climate model shows the observed contrast of convection with warm rain process dominating over ocean compared to that over land</description><subject>Accuracy</subject><subject>Atmosphere</subject><subject>atmosphere‐ocean coupling</subject><subject>Atmospheric models</subject><subject>Climate</subject><subject>Climate models</subject><subject>Convection</subject><subject>Dominance</subject><subject>Dry spells</subject><subject>Geophysics</subject><subject>Hydrometeors</subject><subject>intraseasonal oscillations</subject><subject>Lipopolysaccharides</subject><subject>Low pressure</subject><subject>Low pressure systems</subject><subject>Mixed layer</subject><subject>Mixed layer depth</subject><subject>Modelling</subject><subject>monsoon</subject><subject>Monsoon climates</subject><subject>Monsoons</subject><subject>Ocean models</subject><subject>Oceans</subject><subject>Oscillations</subject><subject>Pressure</subject><subject>Rainfall</subject><subject>Rainfall simulators</subject><subject>regional climate modeling</subject><subject>Seasonal variability</subject><subject>Seasonal variation</subject><subject>Seasonal variations</subject><subject>Seasons</subject><subject>Simulated rainfall</subject><subject>Simulation</subject><subject>Summer</subject><subject>Summer climates</subject><subject>Summer monsoon</subject><subject>Thermocline</subject><subject>Upper ocean</subject><subject>Wind</subject><issn>2169-897X</issn><issn>2169-8996</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9kM9Kw0AQxoMoWGpvPsCCV6Ob7ObPHktjq6VSaC14C9PNpk3ZZONuQslB8BF8Rp_EDRXx5MzhG4bffMyM41x7-M7DPrv3se_PE0wiyvCZM_C9kLkxY-H5bx29XjojYw7YRowJDejAeU-6CsqCo0QdK8NBFtUONXuB1qpt9mhsCqjQui1LodGzqoxSFZpqVSJAM6m2INFKQAWyM4VBG9NPg23tCmWbaKLaWooMLbmFvj4-x02pTL0XWlizTMgr5yIHacToR4fOZvrwMnl0F8vZ02S8cHm_pStCxklOQ045WCF9br2tlzOSh2EMHEcBYwFk9iwGjAPNqACBCfAwzyJGhs7NybfW6q0VpkkPqtV2Q5P6EcUB8SOfWOr2RHGtjNEiT2tdlKC71MNp_-P0748tTk74sZCi-5dN57NVEsTEo-QbR9B-qA</recordid><startdate>20221127</startdate><enddate>20221127</enddate><creator>Misra, Vasubandhu</creator><creator>Jayasankar, C. 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K.</creatorcontrib><creatorcontrib>Mitra, A.</creatorcontrib><creatorcontrib>Murugavel, P.</creatorcontrib><collection>CrossRef</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Journal of geophysical research. Atmospheres</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Misra, Vasubandhu</au><au>Jayasankar, C. B.</au><au>Mishra, A. K.</au><au>Mitra, A.</au><au>Murugavel, P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dynamic Downscaling the South Asian Summer Monsoon From a Global Reanalysis Using a Regional Coupled Ocean‐Atmosphere Model</atitle><jtitle>Journal of geophysical research. Atmospheres</jtitle><date>2022-11-27</date><risdate>2022</risdate><volume>127</volume><issue>22</issue><epage>n/a</epage><issn>2169-897X</issn><eissn>2169-8996</eissn><abstract>In this study, we present the results of a regional model (regional spectral model‐regional ocean model [(RSM‐ROMS]) simulation of the South Asian Summer Monsoon (SASM). The RSM‐ROMS integration is carried out at 20 km grid spacing over a period of 25 years (1986–2010). The simulation is forced by global atmospheric and oceanic reanalysis. The RSM‐ROMS simulation shows a realistic alignment of the simulated rainfall along the orographic features of the domain. Furthermore, the RSM‐ROMS simulates the observed feature of convection over continental SASM region being more vigorous with dominance of mixed warm and cold phase hydrometeors in contrast to the dominance of the warm rain process in the neighboring tropical oceans. Similarly, the upper ocean features of contrasting mixed layer and thermocline depths between the northern and equatorial Indian Ocean are also simulated in the RSM‐ROMS. Intra‐Seasonal Oscillation (ISO) of the SASM at 10–20 and 20–70 days are also simulated in the RSM‐ROMS with many of its features verifying with observations. For example, the 20–70 days ISO are of higher amplitude and its meridional propagation is slower in Bay of Bengal compared to that over Arabian Sea. Additionally, RSM‐ROMS shows 12.3 Monsoon Low Pressure Systems (LPSs) per season that is comparable to 14.6 per season from observations. Furthermore, the observed intraseasonal contrasts of LPS between the wet and dry spells of ISO is also reproduced in the RSM‐ROMS. Plain Language Summary The South Asian Summer Monsoon (SASM) climate represents a complex mix of variations across many spatio‐temporal scales over a region with unique topographic and bathymetric features. As a result, the simulation of the SASM climate offers a stiff challenge to numerical climate models. In this study, we evaluate the added value of a regional coupled ocean‐atmosphere model in downscaling the SASM climate from a 2.5° × 2.5° global atmospheric reanalysis and 0.5° × 0.5° global ocean reanalysis to 20 km grid spacing. The regional model demonstrates significant skill in capturing the observed features of the intra‐seasonal oscillations of the SASM besides displaying reasonable fidelity of simulating and improving the mean climate of the SASM. Furthermore, at 20 km grid spacing, the regional model simulates the seasonal and intraseasonal activity of the monsoon low pressure systems that is comparable to observations. Therefore, the regional model at 20 km grid spacing of this study clearly demonstrates its added value to its driving global reanalysis in the simulation of the SASM climate, and its intra‐seasonal variations. The regional model simulation also demonstrates its fidelity from the verification of the seasonal and intra‐seasonal variability of the monsoon low pressure systems of the SASM. Key Points The regional climate model displays a verifiable intraseasonal variability of precipitation The regional climate model simulates the observed unique feature of intraseasonal variations of the monsoon low pressure systems The regional climate model shows the observed contrast of convection with warm rain process dominating over ocean compared to that over land</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2022JD037490</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0001-5926-6653</orcidid><orcidid>https://orcid.org/0000-0002-1345-6280</orcidid><orcidid>https://orcid.org/0000-0002-7882-5868</orcidid><oa>free_for_read</oa></addata></record>
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subjects Accuracy
Atmosphere
atmosphere‐ocean coupling
Atmospheric models
Climate
Climate models
Convection
Dominance
Dry spells
Geophysics
Hydrometeors
intraseasonal oscillations
Lipopolysaccharides
Low pressure
Low pressure systems
Mixed layer
Mixed layer depth
Modelling
monsoon
Monsoon climates
Monsoons
Ocean models
Oceans
Oscillations
Pressure
Rainfall
Rainfall simulators
regional climate modeling
Seasonal variability
Seasonal variation
Seasonal variations
Seasons
Simulated rainfall
Simulation
Summer
Summer climates
Summer monsoon
Thermocline
Upper ocean
Wind
title Dynamic Downscaling the South Asian Summer Monsoon From a Global Reanalysis Using a Regional Coupled Ocean‐Atmosphere Model
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