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- Author or Editor: Yinphan Tsang x
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Abstract
High temporal and spatial resolution precipitation datasets are essential for hydrological and flood modeling to assist water resource management and emergency responses, particularly for small watersheds, such as those in Hawai‘i in the United States. Unfortunately, fine temporal (subdaily) and spatial (<1 km) resolutions of rainfall datasets are not always readily available for applications. Radar provides indirect measurements of the rain rate over a large spatial extent with a reasonable temporal resolution, while rain gauges provide “ground truth.” There are potential advantages to combining the two, which have not been fully explored in tropical islands. In this study, we applied kriging with external drift (KED) to integrate hourly gauge and radar rainfall into a 250 m × 250 m gridded dataset for the tropical island of O‘ahu. The results were validated with leave-one-out cross validation for 18 severe storm events, including five different storm types (e.g., tropical cyclone, cold front, upper-level trough, kona low, and a mix of upper-level trough and kona low), and different rainfall structures (e.g., stratiform and convective). KED-merged rainfall estimates outperformed both the radar-only and gauge-only datasets by 1) reducing the error from radar rainfall and 2) improving the underestimation issues from gauge rainfall, especially during convective rainfall. We confirmed the KED method can be used to merge radar with gauge data to generate reliable rainfall estimates, particularly for storm events, on mountainous tropical islands. In addition, KED rainfall estimates were consistently more accurate in depicting spatial distribution and maximum rainfall value within various storm types and rainfall structures.
Significance Statement
The results of this study show the effectiveness of utilizing kriging with external drift (KED) in merging gauge and radar rainfall data to produce highly accurate, reliable rainfall estimates in mountainous tropical regions, such as O‘ahu. The validated KED dataset, with its high temporal and spatial resolutions, offers a valuable resource for various types of rainfall-related research, particularly for extreme weather response and rainfall intensity analyses in Hawai’i. Our findings improve the accuracy of rainfall estimates and contribute to a deeper understanding of the performance of various rainfall estimation methods under different storm types and rainfall structures in a mountainous tropical setting.
Abstract
High temporal and spatial resolution precipitation datasets are essential for hydrological and flood modeling to assist water resource management and emergency responses, particularly for small watersheds, such as those in Hawai‘i in the United States. Unfortunately, fine temporal (subdaily) and spatial (<1 km) resolutions of rainfall datasets are not always readily available for applications. Radar provides indirect measurements of the rain rate over a large spatial extent with a reasonable temporal resolution, while rain gauges provide “ground truth.” There are potential advantages to combining the two, which have not been fully explored in tropical islands. In this study, we applied kriging with external drift (KED) to integrate hourly gauge and radar rainfall into a 250 m × 250 m gridded dataset for the tropical island of O‘ahu. The results were validated with leave-one-out cross validation for 18 severe storm events, including five different storm types (e.g., tropical cyclone, cold front, upper-level trough, kona low, and a mix of upper-level trough and kona low), and different rainfall structures (e.g., stratiform and convective). KED-merged rainfall estimates outperformed both the radar-only and gauge-only datasets by 1) reducing the error from radar rainfall and 2) improving the underestimation issues from gauge rainfall, especially during convective rainfall. We confirmed the KED method can be used to merge radar with gauge data to generate reliable rainfall estimates, particularly for storm events, on mountainous tropical islands. In addition, KED rainfall estimates were consistently more accurate in depicting spatial distribution and maximum rainfall value within various storm types and rainfall structures.
Significance Statement
The results of this study show the effectiveness of utilizing kriging with external drift (KED) in merging gauge and radar rainfall data to produce highly accurate, reliable rainfall estimates in mountainous tropical regions, such as O‘ahu. The validated KED dataset, with its high temporal and spatial resolutions, offers a valuable resource for various types of rainfall-related research, particularly for extreme weather response and rainfall intensity analyses in Hawai’i. Our findings improve the accuracy of rainfall estimates and contribute to a deeper understanding of the performance of various rainfall estimation methods under different storm types and rainfall structures in a mountainous tropical setting.
Abstract
The northeasterly facing, windward side of the Island of Kaua‘i (part of the State of Hawai‘i, United States) is prone to heavy rainfall events due to its topographical features and geographical location. Persistent northeasterly trade winds, coupled with steep changes in elevation, create an ideal environment for orographic precipitation. In addition, due to Kaua‘i’s 22°N latitude, the island often experiences midlatitude weather features such as kona lows, upper-level lows, and cold fronts that frequently result in high rainfall and river discharge conditions. This work uses data from river gauges in Halele‘a to understand the seasonality and impacts of the main atmospheric disturbances on two rivers in the region. The seasonality study showed that the majority of extreme flooding events occurred during the cool season and were predominantly caused by cold fronts and upper-level troughs. The historical analysis used atmospheric disturbance cases to determine that kona lows were likely to cause high streamflow in both studied Halele‘a rivers, and upper-level lows had an approximately equal probability of causing high streamflow or not. The findings that come from this project can provide context to atmospheric disturbances in Halele‘a and help community members identify and anticipate the types of events that may contribute to flooding.
Significance Statement
The north shore of the Island of Kaua‘i is prone to extreme rainfall and flooding due to interactions between the typical wind patterns and the nearby mountain range. A majority of flooding events occur during the cool season (October–April) because most of the weather events that produce extreme rainfall occur during these months. Here, we examined the top 50 flooding events in two of Kaua‘i’s north shore rivers and found that cold fronts and upper-level low pressure systems are often responsible for flooding. Additionally, any kona low is likely to cause high streamflow. This study increases the understanding of flood causes and likelihood in northern Kaua‘i.
Abstract
The northeasterly facing, windward side of the Island of Kaua‘i (part of the State of Hawai‘i, United States) is prone to heavy rainfall events due to its topographical features and geographical location. Persistent northeasterly trade winds, coupled with steep changes in elevation, create an ideal environment for orographic precipitation. In addition, due to Kaua‘i’s 22°N latitude, the island often experiences midlatitude weather features such as kona lows, upper-level lows, and cold fronts that frequently result in high rainfall and river discharge conditions. This work uses data from river gauges in Halele‘a to understand the seasonality and impacts of the main atmospheric disturbances on two rivers in the region. The seasonality study showed that the majority of extreme flooding events occurred during the cool season and were predominantly caused by cold fronts and upper-level troughs. The historical analysis used atmospheric disturbance cases to determine that kona lows were likely to cause high streamflow in both studied Halele‘a rivers, and upper-level lows had an approximately equal probability of causing high streamflow or not. The findings that come from this project can provide context to atmospheric disturbances in Halele‘a and help community members identify and anticipate the types of events that may contribute to flooding.
Significance Statement
The north shore of the Island of Kaua‘i is prone to extreme rainfall and flooding due to interactions between the typical wind patterns and the nearby mountain range. A majority of flooding events occur during the cool season (October–April) because most of the weather events that produce extreme rainfall occur during these months. Here, we examined the top 50 flooding events in two of Kaua‘i’s north shore rivers and found that cold fronts and upper-level low pressure systems are often responsible for flooding. Additionally, any kona low is likely to cause high streamflow. This study increases the understanding of flood causes and likelihood in northern Kaua‘i.
