A paper describing these methods was recently published in the Journal of Hydrometeorology ().

These methods are currently being used to produce the monthly rainfall maps that are available for visualization and download in the Hawai‘i Climate Data Portal.

This study presents results from an ensemble of regional climate model simulations (periods 1996–2005 and 2026–2035) that are used to examine the effects of both anthropogenic forcing and natural variability associated with the Pacific Decadal Oscillation (PDO) on near-term climate projections for the Hawaiian Islands. The Community Earth System Model Large Ensemble (CESM-LE) is used in conjunction with the Weather Research and Forecasting (WRF) model for downscaling. The climate responses to the PDO and anthropogenic forcing are isolated and analyzed separately. In response to anthropogenic forcing, significant increases in surface air temperature, of ~0.8 K, are projected at low elevations. Stronger warming, of up to 1.3 K, is seen at higher elevation areas. Future climate simulations show significant increases in wet season rainfall, of ~10–20%, along the windward slopes of Big Island and Maui. Rainfall patterns during the positive PDO phase are projected to reverse in sign, leading to drier conditions, by ~10–30%, at many locations. Future climate simulations show daily rainfall extremes will increase, by up to ~10–15%, at many locations. Daily temperature extremes are also projected to increase significantly, by up to 1.4 K. Overall, results indicate that natural variability will continue to contribute to uncertainty in near-term rainfall projections for the Hawaiian Islands, masking the forced signal.

Seasonal WRF output needed to reproduce key results are available at . Daily WRF output is provided at .

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

“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.” ()

The aerosol emissions from Kilauea volcano are affecting Hawai’i rainfall locally. Based on the analyses from 2014-2017, the days with high emissions have on  average 8 mm/day less rainfall downstream of the Kilauea. Read the to learn more

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.

This research explores the relationship between 4-types of atmospheric disturbances and their contributions to daily rainfall on O‘ahu Hawai‘i.  On average, atmospheric disturbances account for 29% of the annual and 41% of the seasonal (Nov – April) rainfall on O‘ahu Hawai‘i. Cold, fronts are the most common disturbance type, and fronts that cross over the island are shown to bring significantly more rainfall than the fronts that track to the north of the Island chain. Understanding the relative contributions of disturbances to wet-season RF as well as the spatial distribution of RF during these events is important in the context of a changing climate in which disturbances are expected to become less frequent and more intense. This work has been published in the American Meteorological Society Journal, “Monthly Weather Review”.

Schematics showing six types of synoptic patterns that produce rainfall in Hawai‘i: (a) crossing fronts (CR), (b) noncrossing
fronts (NC), (c) upper-level low pressure systems (UL), (d) kona low storms (KL), (e) tropical cyclones (TC), and (f) nondisturbances
(ND). The 500-hPa isobars are indicated with solid black lines and the wind direction is indicated by the arrow.

Frequency of occurrence for each disturbance type from 1 Oct 1990 to 31 Sep 2010.

Percentage of rainfall that has occurred for each disturbance category over (left) the 20 water years and
(right) wet seasons that have occurred between 1990 and 2010.

An exploratory analysis found that atmospheric predictor variables selected through statistical methods can lead to more accurate rainfall projections when compared to the previous predictor set used in statistical downscaling for rainfall projections in Hawaiʻi. This figure shows the skill of a linear model in projecting rainfall for 1980 to 2007 using the previous predictor set (blue bars) and using a predictor set selected through our predictor selection process (orange bars). Zero represents no skill and 1 represents perfect skill. A shift towards increased skill is apparent for the selected predictor set.