High-Impact Extratropical Cyclones along the Northeast Coast of the United States in a Long Coupled Climate Model Simulation

被引:5
作者
Catalano, Arielle J. [1 ,5 ]
Broccoli, Anthony J. [1 ,2 ]
Kapnick, Sarah B. [3 ]
Janoski, Tyler P. [4 ]
机构
[1] Rutgers State Univ, Dept Environm Sci, New Brunswick, NJ 08901 USA
[2] Rutgers State Univ, Inst Earth Ocean & Atmospher Sci, New Brunswick, NJ USA
[3] Geophys Fluid Dynam Lab, Princeton, NJ USA
[4] Columbia Univ, Dept Earth & Environm Sci, New York, NY USA
[5] Portland State Univ, Dept Geog, Portland, OR 97207 USA
基金
美国国家科学基金会;
关键词
Atmospheric circulation; Extratropical cyclones; Risk assessment; General circulation models; Model evaluation; performance; HEMISPHERE WINTER; VARIABILITY; REANALYSIS; TRACKING; WIND;
D O I
10.1175/JCLI-D-18-0376.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
High-impact extratropical cyclones (ETCs) cause considerable damage along the northeast coast of the United States through strong winds and inundation, but these relatively rare events are difficult to analyze owing to limited historical records. Using a 1505-yr simulation from the GFDL FLOR coupled model, statistical analyses of extreme events are performed including exceedance probability computations to compare estimates from shorter segments to estimates that could be obtained from a record of considerable length. The most extreme events possess characteristics including exceptionally low central pressure, hurricane-force winds, and a large surge potential, which would greatly impact nearby regions. Return level estimates of metrics of ETC intensity using shorter, historical-length segments of the FLOR simulation are underestimated compared to levels determined using the full simulation. This indicates that if the underlying distributions of observed ETC metrics are similar to those of the 1505-yr FLOR distributions, the actual frequency of extreme ETC events could also be underestimated. Comparisons between FLOR and reanalysis products suggest that not all features of simulated high-impact ETCs are representative of observations. Spatial track densities are similar, but FLOR exhibits a negative bias in central pressure and a positive bias in wind speed, particularly for more intense events. Although the existence of these model biases precludes the quantitative use of model-derived return statistics as a substitute for those derived from shorter observational records, this work suggests that statistics from future models of higher fidelity could be used to better constrain the probability of extreme ETC events and their impacts.
引用
收藏
页码:2131 / 2143
页数:13
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