Characterizing Long Island's Extreme Precipitation and Its Relationship to Tropical Cyclones

被引:2
|
作者
Reed, Austin T. [1 ,2 ]
Stansfield, Alyssa M. [2 ]
Reed, Kevin A. [2 ]
机构
[1] George Mason Univ, Dept Atmospher Ocean & Earth Sci, Fairfax, VA 22030 USA
[2] SUNY Stony Brook, Sch Marine & Atmospher Sci, Stony Brook, NY 11790 USA
基金
美国国家航空航天局;
关键词
precipitation; extreme; tropical; cyclone; Long Island; resolution; UNITED-STATES; HIGH-RESOLUTION; EVENTS; MODEL; RAINFALL; SIMULATION; INDEXES; RUNOFF;
D O I
10.3390/atmos13071070
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Since extreme precipitation impacts society on small scales (i.e., a few kilometers and smaller, it is worthwhile to explore extreme precipitation trends in localized regions, such as Long Island (LI), New York. Its coastal location makes it vulnerable to various extreme events, such as tropical cyclones (TCs). This work aimed to quantify the extreme precipitation events on LI that are caused by TCs, as well as the percentage of TCs passing close to LI that cause extreme precipitation events. Both gauge-based and satellite-based precipitation datasets of varying resolutions (DAYMET, IMERG, and CPC) were used to understand the impact of dataset selection. Results are shown for the common time period of 2001-2020, as well as the full time periods of each dataset. DAYMET shows the highest percentage of extreme precipitation events linked to TCs for 2001-2020 (a maximum of 7.2%) and the highest number of TCs that caused extreme precipitation events (36.5%), with IMERG showing similar results. For the full and common time periods, the highest percentage of extreme precipitation events caused by TCs was found in eastern LI. TC-related extreme precipitation averaged over LI varied year to year, and amounts were dependent on the resolution of the observational dataset, but most datasets showed an increasing trend in the last 19 years that is larger than the trend in mean precipitation. Current infrastructure in the region is likely inadequately prepared for future impacts from TC-related extreme precipitation events in such a population-dense region.
引用
收藏
页数:14
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