Subregional Winter Precipitation Variability
in the US Southwest
JD
1Department
1
Tamerius
& AC
1
Comrie
of Geography and Regional Development, University of Arizona, USA
Intra-seasonal Variability
Principal Components Analysis
Overview
Detailed data analyses demonstrate that occasionally subregions within the Southwest US
have anomalously dry/wet winters that do not correlate with surrounding subregions.
Principal components analysis (with varimax rotation) was performed to examine the different
modes of variation. The first four components were retained for further analysis.
•Why do subregions that are consistently highly-correlated during the winter, occasionally
deviate from each other?
•Are these deviations produced through stochastic and/or deterministic processes?
December 1998
January 2000
Principal Component 1
Principal Component 2
•The seasonal timing of winter precipitation was
examined by dividing the average monthly
precipitation for each pixel by its average seasonal
precipitation. The mean over each nested subregion
was then calculated.
•Allows us to examine how changes in atmospheric
Component Loadings
circulation and other atmospheric variables that vary
intraseasonally, affect the distribution of precipitation.
Principal Component 3
Principal Component 4
December
January
February
March
Avg Monthly PPT/
Seasonal PPT
Region 3
Max: 0.24
Region 2
Study Area
The study area consists of the US Southwest where complex topography
coupled with atmospheric processes create variable winter precipitation. It
is theorized that variations in macro- and meso-scale circulation may
augment or diminish the effects of orography causing inconsistent relative
distribution of precipitation at the subregional scale.
Topography
November
Region 1
Average Winter Precipitation
Min: 0.16
Regionalization and Subregionalization
Data
Monthly precipitation for the winters (November-March) from 1896-2004 are examined.
Corresponding atmospheric variables will be used in future analysis.
Precipitation Data: Parameter Elevation-Regressions on Independent Slopes Model (PRISM)
*The resolution of the PRISM data was reduced from 4km to 32km to due to computational limits.
Atmospheric Data: North American Regional Reanalysis (NARR)
Average Winter Precipitation
PRISM w/ Reduced Resolution
NARR Average January 500mb
Geopotential Heights
A “maximum loading” method was applied to
delineate regions that loaded most heavily on
individual components. Every
pixel was
Region 3
assigned a value that corresponded to the
principal component that it loaded highest on.
The maximum loading method succeeded
in
Region 2
delineating regions that were highly
correlated with one another. However, to
enable the examination
of subregional
Region
1
precipitation variability, a PCA was carried out
on each region to delineate subregions.
Region This
4
process repeated again to obtain 44 highly
correlated “nested” subregions within the
study area. These subregions will be the
lenses through which subregional winter
precipitation variability is examined.
Subregions
Regions
Conclusion
•Using PCA on monthly anomalies, the Southwest US
“Nested” Subregions
has been partitioned into 44 highly correlated subregions
and are used to investigate subregional winter
precipitation variability.
•Although anomalies in adjacent subregions for any given
month are frequently correlated, occasionally they
deviate.
•The goal of these analyses is to determine if these
deviations occur systematically or are relatively random.
•If they are systematic, the key atmospheric variables that
cause the deviations will be determined.
•Viewing the intraseasonality of precipitation at the
subregional level exploits the macro-scale atmospheric
processes that evolve over a winter.
•The data suggests that these macro-scale processes
may affect the subregional distribution of precipitation.
•Future conclusions may aid subregional winter climate
prediction and provide insight into past and future climate
variability at the subregional level.
Contact Information: jamest@email.arizona.edu