The relationship between precipitation and large-flow is important to understand and characterize in the climate system. We examine statistical relationships
between the Tropical Rainfall Measurement Mission (TRMM) 3B42 gridded precipitation and large-scale
ow variables in the Tropics for 2000{2007. These variables
include NCEP/NCAR Re-analysis sea surface temperatures (SSTs), vertical temperature pro files, omega, and moist static energy, as well as Atmospheric Infrared Sounder
(AIRS) vertical temperatures and QuikSCAT surface divergence. We perform correlation analysis, empirical orthogonal function analysis, and logistic regression analysis
on monthly, pentad, daily and near-instantaneous time scales. Logistic regression
analysis is able to incorporate the non-linear nature of precipitation in the relation-
ship. Flow variables are interpolated to the 0.25 degrees TRMM 3B42 grid and examined
separately for each month to o set the effects of the seasonal cycle.
January correlations of NCEP/NCAR Re-analysis SSTs and TRMM 3B42 precipitation have a coherent area of positive correlations in the Western and Central
Tropical Pacific on all time scales. These areas correspond with the South Pacific
Convergence Zone (SPCZ) and the Inter Tropical Convergence Zone (ITCZ). 500mb
omega is negatively correlated with TRMM 3B42 precipitation across the Tropics on
all time scales. QuikSCAT divergence correlations with precipitation have a band of weak and noisy correlations along the ITCZ on monthly time scales in January. Moist
static energy, calculated from NCEP/NCAR Re-analysis has a large area of negative
correlations with precipitation in the Central Tropical Pacific on all four time scales.
The first few Empirical Orthogonal Functions (EOFs) of vertical temperature
profiles in the Tropical Pacific have similar structure on monthly, pentad, and daily
timescales. Logistic regression fit coefficients are large for SST and precipitation in
four regions located across the Tropical Pacific. These areas show clear thresholded
behavior. Logistic regression results for other variables and precipitation are less
clear. The results from SST and precipitation logistic regression analysis indicate the
potential usefulness of logistic regression as a non-linear statistic relating precipitation
and certain
ow variables.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2010-05-7653 |
| Date | 2010 May 1900 |
| Creators | Borg, Kyle |
| Contributors | Saravanan, R. |
| Source Sets | Texas A and M University |
| Language | English |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | application/pdf |
Page generated in 0.0017 seconds