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Multivariate intraseasonal rainfall index applied to South America.
- Source :
- Meteorological Applications; Oct2019, Vol. 26 Issue 4, p521-527, 7p
- Publication Year :
- 2019
-
Abstract
- The intraseasonal variability over South America is investigated using a multivariate index based on maximum covariance analysis (MCA). This technique identifies the correlation patterns of two different data sets. The Climate Prediction Center (CPC) grid precipitation over South America and the tropical means (15°N–15°S) of outgoing long wave radiation (OLR) and zonal wind component at 850 and 200 hPa (National Oceanic and Atmospheric Administration (NOAA) and National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis, respectively) are used in the study. The MCA was applied to these data sets and a Multivariate Intraseasonal Rainfall Index for South America for South America (MIRI.SA) was constructed based on the phase and amplitude vectorial projections of the first two modes. Composites of selected cases when the amplitude was above a threshold are discussed for different phases of the Madden–Julian Oscillation (MJO). Phases (8+1) and (4+5) present strong convection anomalies over the maritime continent and South America, but with opposite signs. These patterns represent the dominant mode of precipitation over South America. Phases (2+3) and (6+7) are transient and related to the secondary mode of precipitation over South America. A space‐phase diagram calculated using the MIRI.SA index at different lags represents the positive precipitation locations over both South America and the Equatorial Pacific. The construction of this diagram in near real time could be used for monitoring precipitation extremes over different areas of South America. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13504827
- Volume :
- 26
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Meteorological Applications
- Publication Type :
- Academic Journal
- Accession number :
- 139114713
- Full Text :
- https://doi.org/10.1002/met.1780