Nonstationary influence of the North Atlantic tropical cyclones on the spatio‐temporal variability of the eastern United States precipitation extremes

Dhakal, Nirajan; Jain, Shaleen

doi:10.1002/joc.6409

Cited by 6 publications

(2 citation statements)

References 62 publications

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“…In addition to this, it was observed that seasonal modes of AMF dates have weakened over time for a number of sites along the coastal region with the emergence of significant modes during late spring and early summer (May-June) as well as fall season (mid-September-November). The reason for the emergence of seasonality modes during the month of November along the coastal sites might be due to an increase in the heavy precipitation trends associated with tropical cyclones in the North Atlantic basins over the last 30 years [26,[40][41][42][43]. Similarly, the emergence of modes during the months of May and early June might be due to the emergence of extreme precipitation seasonality modes during late spring and early summer season for the latest time period as shown by Dhakal et al [25].…”

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confidence: 87%

Changing River Flood Timing in the Northeastern and Upper Midwest United States: Weakening of Seasonality over Time?

Dhakal

Palmer

2020

Water

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Climate change is likely to impact precipitation as well as snow accumulation and melt in the Northeastern and Upper Midwest United States, ultimately affecting the quantity and seasonal distribution of streamflow. The objective of this study is to analyze seasonality of long-term daily annual maximum streamflow (AMF) records and its changes for 158 sites in Northeastern and Upper Midwest Unites States. A comprehensive circular statistical approach comprising a kernel density method was used to assess the seasonality of AMF. Temporal changes were analyzed by separating the AMF records into two 30-year sub-periods (1951–1980 and 1981–2010). Results for temporal change in seasonality showed mixed pattern/trend across the stations. While for majority of stations, the distribution of AMF timing is strongly unimodal (concentrated around spring season) for the period 1951–1980, the seasonal modes have weakened during the period 1981–2010 for several stations along the coastal region with simultaneous emergence of multiple modes indicating changes of seasonality therein. The fresh statistical approach based on non-parametric circular density estimates reduces some of the limitations of previous studies to detect and model event timing distributions with multiple seasons and addresses issues of non-stationarity in the data records of extreme events.

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confidence: 87%

Changing River Flood Timing in the Northeastern and Upper Midwest United States: Weakening of Seasonality over Time?

Dhakal

Palmer

2020

Water

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“…By not accounting for these patterns, current methods for hydrologic design of infrastructure, such as flood frequency analysis and regional regression, are poorly suited for considering risk from nonstationarity of extreme events (Wright et al, 2019). In addition, extreme flooding events are increasingly being attributed to hurricanes (Dhakal & Jain, 2019), which presents challenges for flood frequency statistics in coastal regions. Therefore, alternative approaches to flood frequency are needed to consider the influence of peak flows from climate enlarged hurricanes.…”

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confidence: 99%

Transposing flood risk from extreme rainfall events: A case study of Hurricane Harvey

Regier

Naughton

McDonald

2021

J Flood Risk Management

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Hurricane Harvey produced unprecedented flooding that altered flood frequency statistics near Houston, Texas. While Harvey could have made landfall elsewhere along the Gulf coast, traditional flood frequency methodologies only consider the risk of Harvey in the region that it hit. This may be a shortcoming of flood frequency methodologies as the intensity of Harvey was greater due to climate change; therefore, Harvey may be more indicative of future hurricanes than other historical observations. To that end, this study investigates what effect Harvey would have had on flood frequency statistics if it had made landfall elsewhere. To do so, a Monte Carlo simulation was used to shift Harvey's rainfall within alternative landfall locations. This rainfall was then applied to synthetic unit hydrographs to estimate peak flows that were applied in Log Pearson III and Regional Flood Frequency Analyses. Log Pearson III analyses with simulated Harvey streamflows produced median 100‐year peak flows that were 17%–66% higher than analyses that only used historical records. A regional flood frequency analysis in the central coastal geomorphologic region of Texas showed that predictive equations, based upon basin area and shape factor, had an average increase of 30.2% in the 100‐year peak discharge.

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Comparison of on-site versus NOAA’s extreme precipitation intensity-duration-frequency estimates for six forest headwater catchments across the continental United States

Mukherjee

Amatya

Jalowska

et al. 2023

Stoch Environ Res Risk Assess

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Urgency of Precipitation Intensity-Duration-Frequency (IDF) estimation using the most recent data has grown significantly due to recent intense precipitation and cloud burst circumstances impacting infrastructure caused by climate change. Given the continually available digitized up-to-date, long-term, and fine resolution precipitation dataset from the United States Department of Agriculture Forest Service’s (USDAFS) Experimental Forests and Ranges (EF) rain gauge stations, it is both important and relevant to develop precipitation IDF from onsite dataset (Onsite-IDF) that incorporates the most recent time period, aiding in the design, and planning of forest road-stream crossing structures (RSCS) in headwaters to maintain resilient forest ecosystems. Here we developed Onsite-IDFs for hourly and sub-hourly duration, and 25-yr, 50-yr, and 100-yr design return intervals (RIs) from annual maxima series (AMS) of precipitation intensities (PIs) modeled by applying Generalized Extreme Value (GEV) analysis and L-moment based parameter estimation methodology at six USDAFS EFs and compared them with precipitation IDFs obtained from the National Oceanic and Atmospheric Administration Atlas 14 (NOAA-Atlas14). A regional frequency analysis (RFA) was performed for EFs where data from multiple precipitation gauges are available. NOAA’s station-based precipitation IDFs were estimated for comparison using RFA (NOAA-RFA) at one of the EFs where NOAA-Atlas14 precipitation IDFs are unavailable. Onsite-IDFs were then evaluated against the PIs from NOAA-Atlas14 and NOAA-RFA by comparing their relative differences and storm frequencies. Results show considerable relative differences between the Onsite- and NOAA-Atlas14 (or NOAA-RFA) IDFs at these EFs, some of which are strongly dependent on the storm durations and elevation of precipitation gauges, particularly in steep, forested sites of H. J. Andrews (HJA) and Coweeta Hydrological Laboratory (CHL) EFs. At the higher elevation gauge of HJA EF, NOAA-RFA based precipitation IDFs underestimate PI of 25-yr, 50-yr, and 100-yr RIs by considerable amounts for 12-h and 24-h duration storm events relative to the Onsite-IDFs. At the low-gradient Santee (SAN) EF, the PIs of 3- to 24-h storm events with 100-yr frequency (or RI) from NOAA-Atlas14 gauges are found to be equivalent to PIs of more frequent storm events (25–50-yr RI) as estimated from the onsite dataset. Our results recommend use of the Onsite-IDF estimates for the estimation of design storm peak discharge rates at the higher elevation catchments of HJA, CHL, and SAN EF locations, particularly for longer duration events, where NOAA-based precipitation IDFs underestimate the PIs relative to the Onsite-IDFs. This underscores the importance of long-term high resolution EF data for new applications including ecological restorations and indicates that planning and design teams should use as much local data as possible or account for potential PI inconsistencies or underestimations if local data are unavailable.

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Nonstationary influence of the North Atlantic tropical cyclones on the spatio‐temporal variability of the eastern United States precipitation extremes

Cited by 6 publications

References 62 publications

Changing River Flood Timing in the Northeastern and Upper Midwest United States: Weakening of Seasonality over Time?

Changing River Flood Timing in the Northeastern and Upper Midwest United States: Weakening of Seasonality over Time?

Transposing flood risk from extreme rainfall events: A case study of Hurricane Harvey

Comparison of on-site versus NOAA’s extreme precipitation intensity-duration-frequency estimates for six forest headwater catchments across the continental United States

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