Abby G. Frazier

and 15 more

Drought is a prominent feature of Hawaii’s climate, however, the biological, ecological, cultural, and socioeconomic impacts of drought in Hawaii are not well understood. This paper provides a comprehensive synthesis of impacts of past droughts in Hawaii that we integrate with a geospatial analysis of drought characteristics (duration, frequency, severity, and geographic extent) using a newly developed 93-year (1920-2012) gridded Standardized Precipitation Index (SPI) dataset. The synthesis examines past droughts classified into five categories: meteorological, agricultural, hydrological, ecological, and socioeconomic drought. Results show that drought duration, magnitude, and frequency have all increased significantly, consistent with trends found in other Pacific Islands. Most droughts, though not all, were associated with El Nino events, and the two worst droughts in the past century were 1998-2002 and 2007-2012. The most severe drought in the record (2007-2012) had the greatest impacts on Hawaii Island, whereas the islands of Oahu and Kauai experienced more severe drought conditions during the 1998-2002 event. Both droughts exerted a large and quantifiable impact on the agricultural sector, and although anecdotal evidence points to strong impacts on ecological and socioeconomic sectors, more research is needed to understand drought impacts to these sectors. This synthesis is an example of how coupling quantitative SPI analysis with economic and ecological impacts can provide the historical context needed to better understand future drought projections, and will contribute to more effective policy and management of natural, cultural, hydrological, and agricultural resources.

Han Tseng

and 8 more

Cloud water interception (CWI) is not captured by conventional rain gauges and not well characterized, but could have ecohydrological significance in systems such as tropical montane cloud forests. Quantifying CWI is necessary to assess the impacts of climate and land cover changes in places such as Hawai‘i. CWI can be estimated from wind speed, cloud liquid water content (LWC), and vegetation characteristics with an empirical model. Cloud microphysics sensors measure LWC accurately, but are expensive and often designed only for use on aircraft. LWC can be estimated by fog gauges, but poorly constrained catch efficiency and spurious rain catch can cause large errors. Visibility is related to LWC, but the relationship is non-linear and depends on the (usually unknown) drop size distribution. This study is part of a project aimed at mapping CWI across the Hawaiian Islands. Earlier analyses found disagreement between LWC estimated from fog gauge and visibility observations at the project field sites. In this study, we experimented with a novel in situ observation platform and cross disciplinary collaboration to compare cloud microphysics observations with those commonly used in cloud forest studies. Field missions took place from April to July 2018 at the summit of Mt. Ka‘ala (1,200 m) on O‘ahu Island. We built a pickup truck-mounted mobile weather station that can be assembled in the field, with weather-sensitive processing modules inside the cab. A total of 10 instruments were deployed: Phase Doppler Interferometer, Cloud Droplet Probe, fog gauge, visibility sensor, rain gauge, wind monitor, camera, water isotope sampler, UAV atmospheric sensor, and Aerosol Spectrometer. A nearby long-term station provides climate and canopy water balance data. Analyses found a strong relationship between visibility and LWC in dense fog. The fog gauge showed weak correlations due to coarse resolution and false rain catch, but had a reasonable catch efficiency. The start of fog catch lagged compared to the nearby station possibly due to screen surface wetting. Concurrent with other analyses, one goal is to calibrate the fog gauge and visibility sensor for long-term LWC monitoring. The mobile platform was effective for short-term deployment of airborne sensors. We hope to repeat the experiment in the future on O‘ahu and other islands.