Effects of atmospheric teleconnections on seasonal precipitation in mountainous regions of the southwestern U.S.: A case study in northern New Mexico

Details Effects of atmospheric teleconnections on seasonal precipitation in mountainous regions of the southwestern U.S.: A case study in northern New Mexico Effects of atmospheric teleconnections on seasonal precipitation in mountainous regions of the southwestern U.S.: A case study in northern New Mexico

Dec 2005

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005georl..3223701g&link_type=abstract

Geophysical Research Letters, Volume 32, Issue 23, CiteID L23701

Mathematics

Logic

4

Global Change: Regional Climate Change, Global Change: Water Cycles (1836), Hydrology: Precipitation (3354), Atmospheric Processes: Climate Change And Variability (1616, 1635, 3309, 4215, 4513), Atmospheric Processes: Mesoscale Meteorology

Scientific paper

This study uses instrument records and geostatistical modeling to examine hydrologically important temporal and spatial patterns of seasonal precipitation associated with the El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) in a mountainous region of northern New Mexico. PDO is the more dominant factor, compared to ENSO, with a larger influence on winter and spring precipitation (wetter for high PDO, drier for low PDO). Extreme ENSO effects are not significant during the high PDO years, but during low PDO years El Niño strongly dampens winter and spring precipitation anomalies. Elevation modulates ENSO and PDO effects on winter anomalies, but does not seem to for other seasons. For a wetter-than-normal winter, the anomalies are larger at higher elevations, and are positive. For a drier-than-normal winter, the anomalies are larger at lower elevations, and are negative. For neutral ENSO, summer precipitation is predictable but spatially variable, indicating different local climates. High-resolution mapping brings out hydrologically important patterns of precipitation anomalies that would otherwise be blurred by spatial averaging.

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