scholarly journals Atmospheric Circulation Patterns Associated with Extreme United States Floods Identified via Machine Learning

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Katherine E. Schlef ◽  
Hamid Moradkhani ◽  
Upmanu Lall
Keyword(s):  
United States ◽  
Machine Learning ◽  
Atmospheric Circulation ◽  
Atmospheric Circulation Patterns ◽  
Circulation Patterns

scholarly journals Avalanche extremes and atmospheric circulation patterns

2001 ◽  
Vol 32 ◽  
pp. 135-140 ◽  
Author(s):  
K.W. Birkeland ◽  
C. J. Mock ◽  
J. J. Shinker
Keyword(s):  
United States ◽  
Atmospheric Circulation ◽  
Snow Water Equivalent ◽  
Hazard Index ◽  
Western United States ◽  
Atmospheric Circulation Patterns ◽  
Avalanche Hazard ◽  
Circulation Patterns ◽  
Jackson Hole ◽  
Exact Position

AbstractAvalanche forecasters can better anticipate avalanche extremes if they understand the relationships between those extremes and atmospheric circulation patterns. We investigated the relationship between extreme avalanche days and atmospheric circulation patterns at four sites in the western United States: Bridger Bowl, Montana; Jackson Hole, Wyoming; Alta, Utah; and Taos, New Mexico. For each site, we calculated a daily avalanche hazard index based on the number and size of avalanches, and we defined abnormal avalanche events as the top 10% of days with recorded avalanche activity. We assessed the influence of different variables on avalanche extremes, and found that high snow water equivalent and high snowfall correspond most closely to days of high avalanche hazard. Composite-anomaly maps of 500 hPa heights during those avalanche extremes clearly illustrate that spatial patterns of anomalous troughing prevail, though the exact position of the troughing varies between sites. These patterns can be explained by the topography of the western United States, and the low-elevation pathways for moisture that exist to the west of each of the sites. The methods developed for this research can be applied to other sites with long-term climate and avalanche databases to further our understanding of the spatial distribution of atmospheric patterns associated with extreme avalanche days.

scholarly journals Dominant Modes of Moisture Flux Anomalies over North America

2005 ◽  
Vol 6 (2) ◽  
pp. 194-209 ◽  
Author(s):  
Francina Dominguez ◽  
Praveen Kumar
Keyword(s):  
United States ◽  
North America ◽  
Atmospheric Circulation ◽  
Moisture Flux ◽  
Eof Analysis ◽  
Anomaly Field ◽  
Atmospheric Circulation Patterns ◽  
Circulation Patterns ◽  
Complex Eof ◽  
Precipitation Events

Abstract This study investigates the principal modes of seasonal moisture flux transport over North America, analyzing their possible dependence on large-scale atmospheric circulation patterns. It uses 23 yr (1979–2001) of 6-hourly data from the NCEP–NCAR reanalysis I project. Complex empirical orthogonal function (complex-EOF) analysis is implemented on the vertically integrated and seasonally averaged moisture flux, to identify the dominant modes. For every season, the characteristic spatial pattern of the two most dominant modes is compared to the geopotential height anomaly field and precipitation anomaly field using correlation analysis. The two dominant winter modes capture the variability in the moisture flux field associated with extreme precipitation events over the western coast of the United States. The first winter mode captures 52% of the variability of the season and is related to the strong ENSO events of 1982/83 and 1997/98 (El Niño) and 1989 (La Niña). The second winter mode captures anomalous high moisture flux over the southwest related to the east Pacific teleconnection pattern. The intense moisture transport associated with high-precipitation events in the central United States (including the 1993 flood) is captured by summer mode 1, while the second mode of the summer season captures the moisture flux variability related to the 1983 and 1988 droughts. The results show that these summer flood and drought events are characterized by very different moisture flux anomalies and are not the positive and negative phases of a given mode. The use of complex-EOF analysis captures extreme hydrologic events as characteristic modes of interannual variability and allows a better understanding of the atmospheric circulation patterns associated with these events.

From Causative Mechanisms of Extreme Events to a Place-based Assessment of Flash Flood Hazard and Vulnerability in the Continental United States

2020 ◽  
Author(s):  
Hamid Moradkhani ◽  
Sepideh Khajehei ◽  
Ali Ahmadalipour ◽  
Hamed Moftakhari ◽  
Wanyun Shao
Keyword(s):  
United States ◽  
Atmospheric Circulation ◽  
Extreme Events ◽  
Flash Flood ◽  
Flood Hazard ◽  
Flash Floods ◽  
Extreme Floods ◽  
Atmospheric Circulation Patterns ◽  
Continental Scale ◽  
Circulation Patterns

<p>Flash floods impose extensive damage and disruption to societies, and they are among the deadliest natural hazards worldwide. Flooding is an on-going global-scale socio-economic risk that is likely to increase in the future under climate change and human development. This risk has led to a variety of studies on the natural and anthropogenic causes of floods. Also, the massive socioeconomic impacts engendered by extreme floods is clear motivation for improved understanding of flood drivers. This presentation is two-fold: first, I demonstrate a machine learning approach to perform clustering of reanalysis data to identify synoptic-scale atmospheric circulation patterns associated with extreme floods across the Continental United States (CONUS). We subsequently assess the flood characteristics (e.g., frequency, spatial domain, event size, and seasonality) specific to each circulation pattern. Focusing on atmospheric circulation patterns leading to extreme rainfall, which is a major factor in nearly all except snowmelt-driven extreme floods, can be especially used to inform continental-scale modeling and forecasting effort. Considering that flash flood is mainly initiated by intense rainfall, and due to its rapid onset, taking action for effective response is challenging. Therefore, building resilience to flash floods require understanding of the socio-economic characteristics of the societies and their vulnerability to these extreme events. The second part of this presentation provides a comprehensive assessment of socio-economic vulnerability (SEV) to flash floods, investigates the main characteristics of flash flood hazard and accordingly a SEV index is developed at the county level across the CONUS. The coincidence of SEV and flash flood hazard are investigated to identify the critical and non-critical regions. The results indicate the resemblance and heterogeneity of flash flood spatial clustering and vulnerability of the regions over the CONUS. We show how identifying these spatial patterns will assist policy makers reach informed and effective decisions for planning and allocating resources.</p>

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