Characterization of Lightning Occurrence in Alaska Using Various Weather Indices for Lightning Forecasting

Farukh, MA; Hayasaka, Hiroshi; Kimura, Keiji

doi:10.20965/jdr.2011.p0343

Cited by 11 publications

(17 citation statements)

References 17 publications

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“…ARs combined with ROS events (Crawford et al., 2020; Guan et al., 2016) can lead to substantial flooding (McCabe et al., 2007). Outside South Coastal, precipitation falls mainly in summer–mid fall in the form of frontal systems and convective storms, with convective storms especially common in the Interior in June and July (Farukh et al., 2011; Papineau & Holloway, 2011; Shulski & Wendler, 2007).…”

Section: Study Areamentioning

confidence: 99%

Identification of Seasonal Streamflow Regimes and Streamflow Drivers for Daily and Peak Flows in Alaska

Curran

Biles

2021

Water Resources Research

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Alaska is among northern high‐latitude regions where accelerated climate change is expected to impact streamflow properties, including seasonality and primary flow drivers. Evaluating changes to streamflow, including flood characteristics, across this large and diverse environment can be improved by identifying the distribution and influence of flow drivers. Using metrics of mean monthly streamflow data from 253 streamgages, seasonal flow regimes were clustered to guide identification of seasonal flow drivers and form hydrologic groups for identification of peak‐flow populations. Nine seasonally distinct subclasses described variability within three classes dominated by (mostly fall) rainfall, (spring) snowmelt, and (summer) high‐elevation melt. The most glacierized basins exclusively grouped into high‐elevation melt subclasses, and less glacierized basins sometimes exhibited seasonal patterns aligned with rainfall‐dominated and snowmelt‐dominated regimes. Peak‐flow populations varied by subclass from dominant rainfall or dominant snowmelt to mixed rainfall–snowmelt or mixed rainfall, snowmelt, and high‐elevation melt. Within subclasses, rainfall generated higher mean peak flows (relative to mean annual flow) than snowmelt or high‐elevation melt. Seasonal flow regimes showed clear but complex associations with basin characteristics, primarily elevation and winter temperature, and with geographic location. These dependencies provided elevation‐based analogies for changes associated with warming and insights for seasonal flow regime prediction and hydrologic region delineation. These results provide a spatially comprehensive perspective on seasonal streamflow drivers across Alaska from historical data and serve as an important historical basis for analysis.

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Section: Study Areamentioning

confidence: 99%

Identification of Seasonal Streamflow Regimes and Streamflow Drivers for Daily and Peak Flows in Alaska

Curran

Biles

2021

Water Resources Research

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“…The Alaska Lightning Detection Network was originally developed in the 1970s and has been upgraded multiple times over the intervening years. Studies have shown that the detection efficiency of the ALDN increased from 40 %-80 % to 80 %-90 % after sensors were upgraded to Vaisala Impact ES sensors in 2012 (Bieniek et al, 2020;Farukh et al, 2011). A further upgrade to a completely new set of time-of-arrival sensors (operated by TOA Systems, Inc.) was made after 2012 (Bieniek et al, 2020).…”

Section: Aldn Datamentioning

confidence: 99%

The WGLC global gridded lightning climatology and time series

Kaplan

Lau

2021

Earth Syst. Sci. Data

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Abstract. Lightning is an important atmospheric phenomenon and has wide-ranging influence on the Earth system, but few long-term observational datasets of lightning occurrence and distribution are currently freely available. Here, we analyze global lightning activity over the second decade of the 21st century using a new global, high-resolution gridded time series and climatology of lightning stroke density based on raw data from the World Wide Lightning Location Network (WWLLN). While the total number of strokes detected increases from 2010–2014, an adjustment for detection efficiency reduces this artificial trend. The global distribution of lightning shows the well-known pattern of greatest density over the three tropical terrestrial regions of the Americas, Africa, and the Maritime Continent, but we also noticed substantial temporal variability over the 11 years of record, with more lightning in the tropics from 2012–2015 and increasing lightning in the midlatitudes of the Northern Hemisphere from 2016–2020. Although the total number of strokes detected globally was constant, mean stroke power decreases significantly from a peak in 2013 to the lowest levels on record in 2020. Evaluation with independent observational networks shows that while the WWLLN does not capture peak seasonal lightning densities, it does represent the majority of powerful lightning strokes. The resulting gridded lightning dataset (Kaplan and Lau, 2021a, https://doi.org/10.5281/zenodo.4774528) is freely available and will be useful for a range of studies in climate, Earth system, and natural hazards research, including direct use as input data to models and as evaluation data for independent simulations of lightning occurrence.

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“…To place the WGLC in the context of other widely used lightning data, we compared our gridded fields with two datasets based on ground-based detection networks and one from spaceborne remote sensing. We used raw stroke count data from the Alaska Lightning Detection Network (ALDN; Fronterhouse, 2012) for the years 2012-2019 and a gridded product based on https://doi.org/10.5194/essd-2021-89 Studies have shown that the detection efficiency of the ALDN increased from 40-80% to 80-90% after sensors were upgraded to Vaisala Impact ES sensors in 2012 (Bieniek et al, 2020;Farukh et al, 2011). A further upgrade to a completely new set of time-of-arrival sensors (operated by TOA Systems, Inc.) was made after 2012 (Bieniek et al, 2020 Coordination Center, 2021) from the beginning of the period for which the TOA-based sensor network was operational (2012-2019).…”

Section: Comparison With Independent Observations Of Lightning Occurrmentioning

confidence: 99%

The WGLC global gridded lightning climatology and timeseries

Kaplan¹,

Lau²

2021

Preprint

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Abstract. Lightning is one of the most important atmospheric phenomena and has wide ranging influence on the Earth System, but few long-term observational datasets of lightning occurrence and distribution are currently freely available. Here we analyze global lightning activity over the second decade of the 21st century using a new global, high-resolution gridded timeseries and climatology of lightning stroke density based on raw data from the World-Wide Lightning Location Network (WWLLN). While the total number of strokes detected increases from 2010–2014, an adjustment for detection efficiency reduces this artificial trend. The global distribution of lightning shows the well-known pattern of greatest density over the three tropical terrestrial regions of the Americas, Africa, and the Maritime Continent, but we also noticed substantial temporal variability over the 11 years of record, with more lightning in the tropics from 2012–2015 and increasing lightning in the mid-latitudes of the Northern Hemisphere from 2016–2020. Although the total number of strokes detected globally was constant, mean stroke power decreases significantly from a peak in 2013 to the lowest levels on record in 2020. Evaluation with independent observational networks shows that while the WWLLN does not capture peak seasonal lightning densities, it does represent the majority of powerful lightning strokes. The resulting gridded lightning dataset (Kaplan and Lau, 2019, https://doi.org/10.1594/PANGAEA.904253) is freely available and will be useful for a range of studies in climate, earth system, and natural hazards research, including direct use as input data to models and as evaluation data for independent simulations of lightning occurrence.

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Characterization of Lightning Occurrence in Alaska Using Various Weather Indices for Lightning Forecasting

Cited by 11 publications

References 17 publications

Identification of Seasonal Streamflow Regimes and Streamflow Drivers for Daily and Peak Flows in Alaska

Identification of Seasonal Streamflow Regimes and Streamflow Drivers for Daily and Peak Flows in Alaska

The WGLC global gridded lightning climatology and time series

The WGLC global gridded lightning climatology and timeseries

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