Extended Abstract (180K)6.2
Identifying time-lag relationships between vegetation condition and climate to produce vegetation outlook maps and monitor drought
Tsegaye Tadesse, National Drought Mitigation Center, University of Nebraska, Lincoln, NE; and B. D. Wardlow and J. H. Ryu
The complexities of drought characteristics, as well as, the highly variable temporal and spatial relationships of climate-vegetation interactions make the prediction of drought and its impacts on vegetation very challenging. Improvements in short-, medium-, and long-range climate predictions enhance our capability to monitor vegetation conditions and develop better drought early warning and knowledge-based decision support systems. Recent advances in remote sensing observations, improvements in the spatial and temporal coverage of weather stations, and improved computational capabilities and statistical analysis techniques have enhanced our capabilities to monitor drought and project its impact on vegetation conditions over large geographic areas. However, before more accurate drought forecasts can be made, a better understanding of how long it takes for a vegetation to respond after a precipitation event is needed. In addition, determining how this precipitation-vegetation response relationship varies both geographically and across the growing season is a fundamental research question to improving drought monitoring and prediction.
The goal of this study was to identify the time-lag relationships between vegetation conditions and the preceding climate and oceanic conditions. The relationship between vegetation conditions, as observed from satellite over a 16-year period (1989-2005), and several climate and oceanic indices were investigated associated with spatial and temporal variations using several statistical analysis techniques including Empirical Orthogonal Function (EOF) for spatial pattern of vegetation condition and Principal Components Analysis (PCA) for temporal persistence between indices (e.g. from 2-weeks to 52-weeks). These relationships were analyzed across the growing season at two-week intervals. Satellite-derived vegetation index (VI) data, which has proven useful for large-area vegetation condition monitoring over the past decade, was used to derive the general vegetation conditions over multi-year time series. Two commonly used climate-based drought indices, the Standardized Precipitation Index (SPI) and the Palmer Drought Severity Index (PDSI) represented the climate conditions for a series of time-lagged periods prior to the satellite-observed vegetation conditions. Eight oceanic indices that included the Southern Oscillation Index (SOI), Multivariate El Niņo and Southern Oscillation Index (MEI), Pacific Decadal Oscillation (PDO), Atlantic Multi-decadal Oscillation (AMO), Pacific/North American index (PNA), North Atlantic Oscillation index (NAO), Madden-Julian Oscillation (MJO), and Sea Surface Temperature anomalies (SST) were also evaluated to investigate the strength of the teleconnection between the ocean, continental climate patterns, and vegetation response. This study was performed based on more than 1400 stations over a 15-state region in the central U.S.
In this paper, we present initial results of the statistical analysis and techniques that have been used to identify the time-lag relationships between the climate/ocean condition and vegetation response over the central U.S. The correlation of the climate and vegetation response for each ecosystem in the 15 state-region, the time lag period in which highest correlation observed, and the importance of these relationships to produce the vegetation outlook maps to monitor drought will be discussed.
Session 6, Drought Assessment And Prediction, Part II
Tuesday, 22 January 2008, 3:30 PM-5:30 PM, 223
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