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MONSOON MISSION: A Targeted Activity to Improve Monsoon Prediction across Scales

In spite of the summer monsoon’s importance in determining the life and economy of an agriculture-dependent country like India, committed efforts toward improving its prediction and simulation have been limited. Hence, a focused mission mode program Monsoon Mission (MM) was founded in 2012 to spur p...

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Published in:Bulletin of the American Meteorological Society 2019-12, Vol.100 (12), p.2509-2532
Main Authors: Rao, Suryachandra A., Goswami, B. N., Sahai, A. K., Rajagopal, E. N., Mukhopadhyay, P., Rajeevan, M., Nayak, S., Rathore, L. S., S. S. C., Shenoi, Ramesesh, K. J., Nanjundiah, R. S., Ravichandran, M., Mitra, A. K., Pai, D. S., Bhowmik, S. K. R., Hazra, A., Mahapatra, S., Saha, S. K., Chaudhari, H. S., Joseseph, S., Sreeeenivas, P., Pokhrel, S., Pillai, P. A., Chattopadhyay, R., Deshpande, M., Krishna, R. P. M., Das, Renu S., Prasad, V. S., Abhilash, S., Panickal, S., Krishnan, R., Kumar, S., Ramu, D. A., Reddy, S. S., Arora, A., Goswami, T., Rai, A., Srivastava, A., Pradhan, M., Tirkey, S., Ganai, M., Mandal, R., Dey, A., Sarkar, S., Malviya, S., Dhakate, A., Salunke, K., Maini, Parvinder
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container_end_page 2532
container_issue 12
container_start_page 2509
container_title Bulletin of the American Meteorological Society
container_volume 100
creator Rao, Suryachandra A.
Goswami, B. N.
Sahai, A. K.
Rajagopal, E. N.
Mukhopadhyay, P.
Rajeevan, M.
Nayak, S.
Rathore, L. S.
S. S. C., Shenoi
Ramesesh, K. J.
Nanjundiah, R. S.
Ravichandran, M.
Mitra, A. K.
Pai, D. S.
Bhowmik, S. K. R.
Hazra, A.
Mahapatra, S.
Saha, S. K.
Chaudhari, H. S.
Joseseph, S.
Sreeeenivas, P.
Pokhrel, S.
Pillai, P. A.
Chattopadhyay, R.
Deshpande, M.
Krishna, R. P. M.
Das, Renu S.
Prasad, V. S.
Abhilash, S.
Panickal, S.
Krishnan, R.
Kumar, S.
Ramu, D. A.
Reddy, S. S.
Arora, A.
Goswami, T.
Rai, A.
Srivastava, A.
Pradhan, M.
Tirkey, S.
Ganai, M.
Mandal, R.
Dey, A.
Sarkar, S.
Malviya, S.
Dhakate, A.
Salunke, K.
Maini, Parvinder
description In spite of the summer monsoon’s importance in determining the life and economy of an agriculture-dependent country like India, committed efforts toward improving its prediction and simulation have been limited. Hence, a focused mission mode program Monsoon Mission (MM) was founded in 2012 to spur progress in this direction. This article explains the efforts made by the Earth System Science Organization (ESSO), Ministry of Earth Sciences (MoES), Government of India, in implementing MM to develop a dynamical prediction framework to improve monsoon prediction. Climate Forecast System, version 2 (CFSv2), and the Met Office Unified Model (UM) were chosen as the base models. The efforts in this program have resulted in 1) unparalleled skill of 0.63 for seasonal prediction of the Indian monsoon (for the period 1981–2010) in a high-resolution (~38 km) seasonal prediction system, relative to present-generation seasonal prediction models; 2) extended-range predictions by a CFS-based grand multimodel ensemble (MME) prediction system; and 3) a gain of 2-day lead time from very high-resolution (12.5 km) Global Forecast System (GFS)-based short-range predictions up to 10 days. These prediction skills are on par with other global leading weather and climate centers, and are better in some areas. Several developmental activities like coupled data assimilation, changes in convective parameterization, cloud microphysics schemes, and parameterization of land surface processes (including snow and sea ice) led to the improvements such as reducing the strong model biases in the Indian summer monsoon simulation and elsewhere in the tropics.
doi_str_mv 10.1175/bams-d-17-0330.1
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N.</au><au>Sahai, A. K.</au><au>Rajagopal, E. N.</au><au>Mukhopadhyay, P.</au><au>Rajeevan, M.</au><au>Nayak, S.</au><au>Rathore, L. S.</au><au>S. S. C., Shenoi</au><au>Ramesesh, K. J.</au><au>Nanjundiah, R. S.</au><au>Ravichandran, M.</au><au>Mitra, A. K.</au><au>Pai, D. S.</au><au>Bhowmik, S. K. R.</au><au>Hazra, A.</au><au>Mahapatra, S.</au><au>Saha, S. K.</au><au>Chaudhari, H. S.</au><au>Joseseph, S.</au><au>Sreeeenivas, P.</au><au>Pokhrel, S.</au><au>Pillai, P. A.</au><au>Chattopadhyay, R.</au><au>Deshpande, M.</au><au>Krishna, R. P. M.</au><au>Das, Renu S.</au><au>Prasad, V. S.</au><au>Abhilash, S.</au><au>Panickal, S.</au><au>Krishnan, R.</au><au>Kumar, S.</au><au>Ramu, D. A.</au><au>Reddy, S. S.</au><au>Arora, A.</au><au>Goswami, T.</au><au>Rai, A.</au><au>Srivastava, A.</au><au>Pradhan, M.</au><au>Tirkey, S.</au><au>Ganai, M.</au><au>Mandal, R.</au><au>Dey, A.</au><au>Sarkar, S.</au><au>Malviya, S.</au><au>Dhakate, A.</au><au>Salunke, K.</au><au>Maini, Parvinder</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MONSOON MISSION: A Targeted Activity to Improve Monsoon Prediction across Scales</atitle><jtitle>Bulletin of the American Meteorological Society</jtitle><date>2019-12-01</date><risdate>2019</risdate><volume>100</volume><issue>12</issue><spage>2509</spage><epage>2532</epage><pages>2509-2532</pages><issn>0003-0007</issn><eissn>1520-0477</eissn><abstract>In spite of the summer monsoon’s importance in determining the life and economy of an agriculture-dependent country like India, committed efforts toward improving its prediction and simulation have been limited. Hence, a focused mission mode program Monsoon Mission (MM) was founded in 2012 to spur progress in this direction. This article explains the efforts made by the Earth System Science Organization (ESSO), Ministry of Earth Sciences (MoES), Government of India, in implementing MM to develop a dynamical prediction framework to improve monsoon prediction. Climate Forecast System, version 2 (CFSv2), and the Met Office Unified Model (UM) were chosen as the base models. The efforts in this program have resulted in 1) unparalleled skill of 0.63 for seasonal prediction of the Indian monsoon (for the period 1981–2010) in a high-resolution (~38 km) seasonal prediction system, relative to present-generation seasonal prediction models; 2) extended-range predictions by a CFS-based grand multimodel ensemble (MME) prediction system; and 3) a gain of 2-day lead time from very high-resolution (12.5 km) Global Forecast System (GFS)-based short-range predictions up to 10 days. These prediction skills are on par with other global leading weather and climate centers, and are better in some areas. Several developmental activities like coupled data assimilation, changes in convective parameterization, cloud microphysics schemes, and parameterization of land surface processes (including snow and sea ice) led to the improvements such as reducing the strong model biases in the Indian summer monsoon simulation and elsewhere in the tropics.</abstract><cop>Boston</cop><pub>American Meteorological Society</pub><doi>10.1175/bams-d-17-0330.1</doi><tpages>24</tpages><oa>free_for_read</oa></addata></record>
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identifier ISSN: 0003-0007
ispartof Bulletin of the American Meteorological Society, 2019-12, Vol.100 (12), p.2509-2532
issn 0003-0007
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language eng
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source JSTOR Archival Journals and Primary Sources Collection
subjects Agriculture
Agronomy
Climate
Climate system
Cloud microphysics
Computer simulation
Data assimilation
Data collection
Earth
Earth sciences
General circulation models
High resolution
Lead time
Mathematical models
Microphysics
Monsoon climates
Monsoon forecasting
Monsoons
Organizations
Parameterization
Prediction models
R&D
Rain
Research & development
Resolution
Sea ice
Simulation
Success
Summer
Summer monsoon
Tropical environments
Variance analysis
Weather forecasting
Wind
title MONSOON MISSION: A Targeted Activity to Improve Monsoon Prediction across Scales
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