2020 – Hawaiʻi Climate Data Portal /climate-data-portal Sat, 14 Oct 2023 00:42:20 +0000 en-US hourly 1 https://wordpress.org/?v=6.3.1 /climate-data-portal/wp-content/uploads/2021/04/cropped-HCDP_No_Text_Color_Transparent-32x32.png 2020 – Hawaiʻi Climate Data Portal /climate-data-portal 32 32 188107989 Hawaiian summer rainfall: Two distinguishing variability regimes /climate-data-portal/hawaiian-summer-rainfall-two-distinguishing-variability-regimes/ /climate-data-portal/hawaiian-summer-rainfall-two-distinguishing-variability-regimes/#respond Tue, 31 Aug 2021 00:51:22 +0000 /climate-data-portal/?p=1332 Contributed by Xiao Luo: luoxiao.rf@gmail.com

Surrounded by the subtropical Pacific Ocean and immersed in persistent trade winds, the Hawaiian Islands experience distinct seasonality in rainfall: a wet winter from November to April and a dry summer from May to October. Summer precipitation in Hawai‘i accounts for 40% of the annual total and provides important water sources. However, our knowledge about its variability remains limited. In this study we show that statewide Hawai’i summer rainfall (HSR) variability exhibits two distinct regimes: quasi-biennial (QB, ~2 years) and interdecadal (~30-40 years). 

Figure. 1 The time series and spectrum of statewide Hawai‘i summer rainfall (HSR) anomalies from 1920 to 2012. (a) The time series of HSR (color bar) and its interdecadal component (>7 years period component, black solid line). The black dashed line indicates the linear trend in HSR during 1920-2012. (b) The power spectrum of HSR, the blue (red) dashed line indicates the 95% (90%) confidence bounds. (c) The quasi-biennial component of the normalized HSR and the quasi-biennial component of Oceanic Niño Index (ONI) from December to the next February.

The QB variation is linked to alternating occurrences of the Western North Pacific (WNP) cyclone and anticyclone in successive years. The cyclone-induced southwest anomalies generate moisture convergence and ascending motion that favors abundant rainfall. The turn-about from the cyclone to anticyclone is associated with the intrinsic biennial component of El Nino-Southern Oscillation and involves a positive feedback between atmospheric Rossby waves and the underlying dipolar sea surface temperature anomalies. 

Figure 2 Seasonal evolution of regressions on the (a-d) QB HSR index and (e-h) QB ONI on the quasi-biennial time scale. (a-d) Regressions on QB HSR index during 1920-2012 in (a) MJJA(0), (b) SOND(0), (c) JFMA(0), and (d) MJJA(1). Regressions in (a-d) correspond to rainfall anomaly of 20 mm/month on QB time scale. (e-h) are the same as in (a-d), except that the regressions are based on QB ONI during 1960-2012. Regressed fields are precipitation anomalies over land (in units of mm/month), SST anomalies over ocean (in units of °C), and 850 hPa wind anomalies (arrows) in units of m/s. 

The interdecadal variation of HSR is largely modulated by the Pacific Decadal Oscillation through affecting upstream low-level humidity that affects topographic rainfall. With the updated data to 2019 from the 10 representative stations, this study shows the long-term summer rainfall trend is quite weak during 1920-2019. This first description of the major physical drivers of summer rainfall variability provides key information for seasonal rainfall prediction in Hawai‘i. A deeper understanding of summer rainfall variability and the major drivers can help develop appropriate variability-based climate divisions that characterize the State’s spatial and temporal variability.

This work has been published in Geophysical Research Letters, 

Authors: Xiao Luo, Bin Wang, Abby G. Frazier, and Thomas W. Giambelluca

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Fire and Rain: The Legacy of Hurricane Lane in Hawaiʻi /climate-data-portal/fire-and-rain-the-legacy-of-hurricane-lane-in-hawai%ca%bbi/ /climate-data-portal/fire-and-rain-the-legacy-of-hurricane-lane-in-hawai%ca%bbi/#respond Mon, 16 Aug 2021 19:39:51 +0000 /climate-data-portal/?p=1306 By Alison D. Nugent, Ryan J. Longman, Clay Trauernicht, Mathew P. Lucas, Henry F. Diaz, and Thomas W. Giambelluca. Click to read the publication.

“Hurricane Lane, which struck the Hawaiian islands on 22–25 August 2018, presented a textbook example of the compounding hazards that can be produced by a single storm. Over a four-day period, the island of Hawaiʻi received an average 17 inches of rainfall. One location received 57 inches, making Hurricane Lane the wettest tropical storm ever recorded in the state and the second wettest ever recorded in the US.

At the same time, three wildfires on the island of Maui and one on Oʻahu burned nearly 3,000 acres of abandoned agricultural land. All of these fires occurred on the drier, leeward slopes of the islands, driven by hot summer weather, preexisting drought, and high winds around the periphery of the hurricane.

The simultaneous occurrence of rain-driven flooding and landslides, high-intensity winds, and multiple fires complicated emergency response. These compound hazards highlight the need to improve anticipation and preparation for complex climate- and weather-related phenomena.

In Hawaiʻi, hurricanes rarely make landfall due to persistent vertical wind shear over the islands. When hurricanes occur near Hawaiʻi, however, the geography of the islands can exacerbate the hazards. The nearly 746 miles of coastline make much of the state susceptible to coastal flooding, and the mountainous topography can intensify rainfall and wind speeds. In addition, the steep mountainous terrain can enhance flash flooding and trigger landslides.

The center of Hurricane Lane did not pass closer than 140 miles from the island of Hawaiʻi. Nevertheless, the prolonged, torrential rains associated with the hurricane’s large scale and slow speed resulted in flooding, mudslides, and landslides across many parts of the island and other parts of the state.

Hurricane Lane provides a unique case study of how atmospheric conditions associated with hurricanes can contribute to both record rainfall and increased fire risk at the same time. While heavy rain is a familiar feature of tropical storms, the strong convection near the storm center is also associated with, or perhaps compensated by, descending air around the storm’s periphery. This subsiding air is warm and dry, and together with intense storm-driven winds, it can increase the risk of fire hazard in the periphery of a hurricane, especially if preexisting conditions predispose the area to fire.

On Maui and Oʻahu, nonnative, fire-prone grass- and shrublands accounted for more than 85 percent of the area burned. A previous weather pattern of wet months followed by dry months led to a surplus of dead, dry grass that fueled the fires.

The immediate causes of the Maui fires remain unknown, but the Honolulu Fire Department attributed the Oʻahu fire to arcing from electrical lines caused by high winds. Altogether, more than 100 county firefighters were required to contain and extinguish the blazes. The strong, erratic winds associated with the hurricane grounded helicopters, which are a critical resource for fire suppression in Hawaiʻi’s steep terrain. The deputy fire chief on Maui described firefighting conditions as “some of the most adverse the Maui Fire Department has faced in recent history.”

The Hawaiian islands suffered considerable damage. The wildfires in west Maui destroyed 21 structures and 30 vehicles and forced the evacuation of 100 homes and the relocation of a hurricane shelter. On Hawaiʻi island, severe flooding and landslides led to road closures across the island, and torrential rains damaged 30 businesses and 152 homes and forced more than 100 people to evacuate. Altogether, the hurricane caused one death and an estimated US$250 million in property damage.” ()

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Long-Term, Gridded Standardized Precipitation Index for Hawai‘i /climate-data-portal/long-term-gridded-standardized-precipitation-index-for-hawai/ /climate-data-portal/long-term-gridded-standardized-precipitation-index-for-hawai/#respond Mon, 19 Jul 2021 17:32:56 +0000 /climate-data-portal/?p=937 Percent area drought time series (2000–2012) for the State of Hawai‘i for: (a) monthly aggregated U.S. Drought Monitor; and (b) gridded SPI-3 converted to USDM categories.

to read the publication by Matthew Lucas.

Spatially explicit, wall-to-wall rainfall data provide foundational climatic information but alone are inadequate for characterizing meteorological, hydrological, agricultural, or ecological drought. The Standardized Precipitation Index (SPI) is one of the most widely used indicators of drought and defines localized conditions of both drought and excess rainfall based on period-specific (e.g., 1-month, 6-month, 12-month) accumulated precipitation relative to multi-year averages. A 93-year (1920–2012), high-resolution (250 m) gridded dataset of monthly rainfall available for the State of Hawai‘i was used to derive gridded, monthly SPI values for 1-, 3-, 6-, 9-, 12-, 24-, 36-, 48-, and 60-month intervals. Gridded SPI data were validated against independent, station-based calculations of SPI provided by the National Weather Service. The gridded SPI product was also compared with the U.S. Drought Monitor during the overlapping period. This SPI product provides several advantages over currently available drought indices for Hawai‘i in that it has statewide coverage over a long historical period at high spatial resolution to capture fine-scale climatic gradients and monitor changes in local drought severity.

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