%0 Book Section
%@nexthigherunit 8JMKD3MGPCW/46KUATE
%3 grimm_south2.pdf
%4 sid.inpe.br/plutao/2021/06.16.16.55
%A Grimm, Alice Marlene,
%A Dominguez, Francina,
%A Cavalcanti, Iracema Fonseca de Albuquerque,
%A Cavazos, Tereza,
%A Gan, Manoel Alonso,
%A Dias, Pedro Leite da Silva,
%A Fu, Rong,
%A Cunningham, Christopher,
%A Hu, Huancui,
%A Barreiro, Marcelo,
%B The Multiscale Global Monsoon System
%@secondarytype PRE LI
%C Geneva
%D 2021
%E Chih-Pei, Chang,
%E Kyung-Ja, Ha,
%E Johnson, Richard H.,
%E Kim, Daehyum,
%E Lau, Gabriel N. C.,
%E Wang, Bin,
%F lattes: 3214369697732376 5 GrimmDCCGDFCHB:2021:ChLiCy
%I World Scientific Publishing
%K monção, Estação Chuvosa, América do Sul, América do Norte.
%P 49-66
%T South and North American Monsoons: Characteristics, Life Cycle, Variability, Modeling, and Prediction
%U https://www.worldscientific.com/worldscibooks/10.1142/11723
%V 11
%X The American monsoons are important components of the global monsoon system. Since the annual precipitation over most of South America is mainly concentrated in the summer monsoon season, the economy, agriculture, water/energy resources and, consequently, the livelihoods of the great majority of population are heavily dependent on the South American monsoon (SAM). On the other hand, the North American monsoon (NAM) is the predominant influence on the boreal summer climate of the Southwestern United States and Northwestern Mexico, providing between 40% and 80% of the total precipitation in this region. This chapter summarizes the weather and climatic aspects of the American monsoons, using observational and modeling studies, with focus on their life cycles, mutual influence, variability on a wide range of temporal scales, extreme events, modeling, and prediction. Ongoing and future projections of climatic changes are also addressed. SAM and NAM are the result of land/atmosphere/ocean coupling and characterized by multi-scale interactions that are not completely known or understood. Many challenges still remain to improve understanding and prediction.
%@area MET
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress iracema.cavalcanti@gmail.com
%@electronicmailaddress
%@electronicmailaddress manoel.gan@inpe.br
%@group
%@group
%@group DIMNT-CGCT-INPE-MCTI-GOV-BR
%@group
%@group DIPTC-CGCT-INPE-MCTI-GOV-BR
%@usergroup lattes
%@isbn 9789811216619
%@resumeid
%@resumeid
%@resumeid 8JMKD3MGP5W/3C9JHDE
%@resumeid
%@resumeid 8JMKD3MGP5W/3C9JHNM
%@affiliation Universidade Federal do Paraná (UFPR)
%@affiliation University of Illinois
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Centro de Investigación Cientifica y de Educación Superior de Ensenada
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Universidade de São Paulo (USP)
%@affiliation Centro de Investigación Cientifica y de Educación Superior de Ensenada
%@affiliation University of Texas
%@affiliation University of California
%@affiliation Universidad de la Republica
%@versiontype publisher
%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
%2 sid.inpe.br/plutao/2021/06.16.16.55.45