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Article << Previous     |     Next >>   Contents Vol 18(4)

Natural variability of the Keetch–Byram Drought Index in the Hawaiian Islands

Klaus Dolling A C, Pao-Shin Chu A, Francis Fujioka B

A Department of Meteorology, School of Ocean and Earth Science and Technology, University of Hawaii, Honolulu, HI 96822, USA.
B USDA Forest Service, Pacific Southwest Research Station, 4955 Canyon Crest Drive, Riverside, CA 92507, USA.
C Corresponding author. Email: dolling@hawaii.edu
 
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Abstract

The Hawaiian Islands experience damaging wildfires on a yearly basis. Soil moisture or lack thereof influences the amount and flammability of vegetation. Incorporating daily maximum temperatures and daily rainfall amounts, the Keetch–Byram Drought Index (KBDI) estimates the amount of soil moisture by tracking daily maximum temperatures and rainfall. A previous study found a strong link between the KBDI and total area burned on the four main Hawaiian Islands. The present paper further examines the natural variability of the KBDI. The times of year at which the KBDI is highest, representing the highest fire danger, are found at each of the 27 stations on the island chain. Spectral analysis is applied to investigate the variability of the KBDI on longer time scales. Windward and leeward stations are shown to have different sensitivities to large-scale climatic fluctuations. An El Niño signal displays a strong relationship with leeward stations, when examined with a band-pass filter and with a composite of standardized anomalies. Departure patterns of atmospheric circulations and sea surface temperatures over the North Pacific are investigated for composites of extremely high KBDI values when fire risk is high. The winter, spring, and fall show anomalous surface anticyclonic circulations, surface divergence, and subsidence over the islands for the upper quartile of KBDI. The winter, spring, and fall composites of equatorial sea surface temperatures for the upper quartile of KBDI are investigated for possible links to atmospheric circulations. These analyses are an effort to allow fire managers some lead time in predicting future fire risks.

   
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