The predictability of autumn soil moisture levels on the Canadian Prairies

Autor: E.A. Ripley, V. Wittrock
Rok vydání: 1999
Předmět:
Zdroj: International Journal of Climatology. 19:271-289
ISSN: 1097-0088
0899-8418
DOI: 10.1002/(sici)1097-0088(19990315)19:3<271::aid-joc362>3.0.co;2-g
Popis: This paper examines time and space patterns of autumn soil moisture for the south-eastern Canadian Prairie provinces and looks for potential teleconnections between these patterns and remote forcing. A unique 35-year dataset of annually-measured (in the autumn) soil moisture at 35 sites was subjected to principal component analysis. The dataset comprised gravimetric soil water contents at depths of 15, 30, 46 and 76 cm. For the composite of all soil depths, the first three principal components explained 34, 10 and 8% respectively, of the total variance. The first component, reflecting moisture changes over the entire study area, is the only one likely to be related to large-scale remote forcing and to be potentially predictable. The remaining components, related to moisture gradients within the study area, are probably either random fluctuations or responses to smaller-scale, less-remote forcing, as well as being less amenable to prediction. Analysis of the time-series amplitudes of the first mode showed significant correlations with several teleconnection indices; these were the North Pacific sea surface temperature (NPSST), the East Pacific pattern, and several indices of Arctic temperature anomalies. The highest correlations were found with the NPSST index, with early summer NPSST anomalies appearing mainly to influence autumn soil moisture, particularly the deeper layers. Although the magnitudes of the correlations were low, the results of this study contribute towards a better understanding of soil moisture variations and their potential predictors on the eastern Canadian Prairies. This may be useful for predictions of the succeeding year's crop and forage yields, as well as spring runoff and summer streamflow.
Databáze: OpenAIRE
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