Spatiotemporal Variability of Tropical Cyclone Precipitation Using a High-Resolution, Gridded (0.25° × 0.25°) Dataset for the Eastern United States, 1948–2015

Abstract

Tropical cyclones (TCs) are an important source of precipitation for much of the eastern United States. However, our understanding of the spatiotemporal variability of tropical cyclone precipitation (TCP) and the connections to large-scale atmospheric circulation is limited by irregularly distributed rain gauges and short records of satellite measurements. To address this, we developed a new gridded (0.25° × 0.25°) publicly available dataset of TCP (1948–2015; Tropical Cyclone Precipitation Dataset, or TCPDat) using TC tracks to identify TCP within an existing gridded precipitation dataset. TCPDat was used to characterize total June–November TCP and percentage contribution to total June–November precipitation. TCP totals and contributions had maxima on the Louisiana, North Carolina, and Texas coasts, substantially decreasing farther inland at rates of approximately 6.2–6.7 mm km−1. Few statistically significant trends were discovered in either TCP totals or percentage contribution. TCP is positively related to an index of the position and strength of the western flank of the North Atlantic subtropical high (NASH), with the strongest correlations concentrated in the southeastern United States. Weaker inverse correlations between TCP and El Niño–Southern Oscillation are seen throughout the study site. Ultimately, spatial variations of TCP are more closely linked to variations in the NASH flank position or strength than to the ENSO index. The TCP dataset developed in this study is an important step in understanding hurricane–climate interactions and the impacts of TCs on communities, water resources, and ecosystems in the eastern United States.

Increasing Tropical Cyclone Precipitation Exposures over the Continental U.S.

“…We summarize changes at the local, state, and national levels to inform mitigation and adaptation strategies. annual TCP days (SI 3) and durations of TCP events (SI 4) which, together, contribute to the increases in total and extreme TC in Fig 1 . Our results generally agree with the spatial patterns shown in previous studies [23][24][25] , although our analysis provides more detailed spatial patterns and is based on a longer time series.…”

Assessment of Satellite Precipitation Data Sets for High Variability and Rapid Evolution of Typhoon Precipitation Events in the Philippines

“…Additionally, the variability distribution and magnitude of rainfall induced by typhoon is closely linked with the rapid evolution of typhoon in time and location. The limited interpretation of the variability typhoon precipitation events is due to the irregular and limited distribution of rain gauge stations (Bregy et al., 2020). Hence, the near‐real‐time and high temporal‐spatial resolution of SPDs are necessary to be carried out in this study.…”

Tropical cyclone precipitation regimes since 1750 and the Great Suppression of 1843–1876 along coastal North Carolina, USA

“…We collected tree‐ring data at five sites in coastal North Carolina (Figure 1), the region that receives the most TCP in the United States both as an absolute and percentage of annual precipitation (Knight and Davis, 2007; Nogueira and Keim, 2011; Bregy et al ., 2020). We obtained all longleaf pine samples from trees located on sandy Carolina Bay rims.…”

“…We matched TCs that tracked through the rain field at 6z, 12z, 18z, and next‐day 0z with current‐day precipitation. Our method is designed to isolate TCP amounts and is comparable to what other studies (e.g., Knight and Davis, 2007; Bregy et al ., 2020) have employed. That said, it is not possible to fully isolate TCP from other rainfall sources (e.g., convective or frontal) on the day(s) TCs tracked through the study area and non‐TCP rainfall may be included on some days.…”

“…However, we did not focus on the atmospheric steering mechanism(s) that would potentially explain multi-decadal phases of either above-or below-average TCP, whether there was a larger geographical signature to the wet/dry phases, or if the Great Suppression TCP amounts would remain unmatched using a near-century longer reconstruction period. Here, we use an expanded regional chronology based on combining updated tree-ring data from Knapp et al (2016) We collected tree-ring data at five sites in coastal North Carolina (Figure 1), the region that receives the most TCP in the United States both as an absolute and percentage of annual precipitation (Knight and Davis, 2007;Nogueira and Keim, 2011;Bregy et al, 2020). We obtained all longleaf pine samples from trees located on sandy Carolina Bay rims.…”