S74
Re-examination of Northeast United States Drought Trends and Characteristics

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Sunday, 17 January 2010
Exhibit Hall B2 (GWCC)
Marcus D. Walter, SOARS/Cornell University, Ithaca, NY

Drought or dry periods can have devastating societal and environmental impacts. For the northeastern United States, increases in dry periods could negatively impact the 54 million people who live in the region and depend upon the regional water resources. Because of climate change and the fluctuating precipitation patterns, drought/dry periods are expected to increase in the northeastern United States.

In this study we use Principle Component Analysis (PCA), Extreme Value Theory (EVT), and other statistical techniques to diagnose trends, characteristics, and possible causality of summer drought/dry periods for this region. The Palmer Drought Severity Index (PDSI), a widely employed and popular drought index, is used for the first part of the study. An independently developed dry period index, based on evaporation estimates and precipitation data, is used for the second part of the study.

Early results from the PCA performed on the PDSI data show a drying trend, spatially and temporally, for the northeastern United States, with the most intense drying visible over Pennsylvania. Results also show that there may be significant antecedent and seasonal correlations between the PDSI dataset and global weather and climate indices, such as land and sea surface temperatures and global surface wind fields.

This analysis is an important step in understanding the seasonal and sub-seasonal drought/dry period occurrences in the Northeast. It also provides insight into how these events are related to climate change and climate indices, and it improves the assessment and understanding of changes in drought/dry periods in this region.

Figure caption: First principle component (PC) time series from the Principle Component Analysis performed on the Palmer Drought Severity Index data for the northeastern United States. Positive PC values correspond to moist conditions and negative PC values correspond to dry conditions. This time series, which explains close to 50% of the variance of the original PDSI dataset, shows an overall drying trend for the Northeast.