Extreme snow events along the coast of the northeast United States: Potential changes due to global warming

2020 ◽  
pp. 1-46
Author(s):  
Guoxing Chen ◽  
Wei-Chyung Wang ◽  
Chao-Tzuen Cheng ◽  
Huang-Hsiung Hsu
Keyword(s):  
United States ◽  
New York ◽  
Global Warming ◽  
Snow Water Equivalent ◽  
Vertical Motion ◽  
Economic Activities ◽  
Northeast United States ◽  
The North ◽  
Snow Water ◽  
Mean Climate

AbstractWinter extreme snowstorm events along the coast of the northeast United States incur significant impacts on social and economic activities, and their potential changes under global warming are of great concern. Here, we adopted the pseudo global warming approach to investigate the responses of 93 events identified in our previous observational analysis. The study was conducted by contrasting two sets of WRF simulations for each event: the first set driven by ERA-Interim reanalysis and the second set by ERA data superimposed with mean-climate changes simulated from HiRAM historical (1980–2004) and future (2075–2099; RCP8.5) runs. Results reveal that the warming together with increased moisture tends to decrease the snowfall along the coast but increase the rainfall throughout the region. For example, the number of events having daily snow-water-equivalent larger than 10 mm day-1 at Boston, New York City, Philadelphia and Washington D.C. is decreased by 47, 46, 30 and 33%, respectively. The compensating changes in snowfall and rainfall lead to total precipitation increased in 3 southern cities but decreased in Boston. In addition, the southwestward shift of regional precipitation distribution is in coherence with the enhancement/reduction of upward vertical motion in the south/north and the movement of cyclone centers (westward in 58% of events and southward in 72%). Finally, perhaps more adversely, because of the northward retreat of the 0°C and the expansion of near-freezing zone, the number of events with mixed rain-snow and freezing precipitations in the north (especially the inland area) is increased.

scholarly journals Response of snowpack to +2°C global warming in Hokkaido, Japan

2019 ◽  
Vol 66 (255) ◽  
pp. 83-96
Author(s):  
Yuta Katsuyama ◽  
Masaru Inatsu ◽  
Tatsuo Shirakawa
Keyword(s):  
Global Warming ◽  
Model Evaluation ◽  
Snow Water Equivalent ◽  
Large Decrease ◽  
Present Climate ◽  
Model Driven ◽  
The North ◽  
Snow Water ◽  
Forced Simulation ◽  
Moderate Bias

AbstractThe response of snowpack to a +2°C global warming relative to the present climate was estimated in Hokkaido, Japan, using a physical snowpack model driven by dynamically downscaled (DDS) data, after model evaluation. The evaluation revealed that the snowpack model successfully reproduced the height of snow cover (HS), snow water equivalent (SWE) and snow-covered days (SCDs), but had a moderate bias in the thickness ratios of melt form (MF) and hoar category (HC). The DDS-forced simulation predicted that the seasonal-maximum HS and SWE would decrease by 30–40% in the southwestern and eastern parts of Hokkaido due to a large decrease in snowfall during the accumulation period, and that the HS and SWE in the north would decrease, albeit not significantly due to uncertain atmospheric forcing. The number of SCDs in Hokkaido was predicted to decline by ~30 d. Additionally, ~50% of snowpack thickness during a season would be MF in most areas, whereas HC would be <50% all over Hokkaido.

Mafias on the Move

2011 ◽  
Author(s):  
Federico Varese
Keyword(s):  
United States ◽  
New York ◽  
Organized Crime ◽  
The United States ◽  
The West ◽  
Market Expansion ◽  
The North ◽  
Economic Transformations ◽  
At Will

Organized crime is spreading like a global virus as mobs take advantage of open borders to establish local franchises at will. That at least is the fear, inspired by stories of Russian mobsters in New York, Chinese triads in London, and Italian mafias throughout the West. As this book explains, the truth is more complicated. The author has spent years researching mafia groups in Italy, Russia, the United States, and China, and argues that mafiosi often find themselves abroad against their will, rather than through a strategic plan to colonize new territories. Once there, they do not always succeed in establishing themselves. The book spells out the conditions that lead to their long-term success, namely sudden market expansion that is neither exploited by local rivals nor blocked by authorities. Ultimately the inability of the state to govern economic transformations gives mafias their opportunity. In a series of matched comparisons, the book charts the attempts of the Calabrese 'Ndrangheta to move to the north of Italy, and shows how the Sicilian mafia expanded to early twentieth-century New York, but failed around the same time to find a niche in Argentina. The book explains why the Russian mafia failed to penetrate Rome but succeeded in Hungary. A pioneering chapter on China examines the challenges that triads from Taiwan and Hong Kong find in branching out to the mainland. This book is both a compelling read and a sober assessment of the risks posed by globalization and immigration for the spread of mafias.

scholarly journals Climatology and Meteorological Evolution of Major Wildfire Events over the Northeast United States

2013 ◽  
Vol 28 (1) ◽  
pp. 175-193 ◽  
Author(s):  
Joseph B. Pollina ◽  
Brian A. Colle ◽  
Joseph J. Charney
Keyword(s):  
United States ◽  
Coastal Plain ◽  
Large Scale ◽  
Trajectory Analysis ◽  
Synoptic Pattern ◽  
Pressure System ◽  
Northeast United States ◽  
The North ◽  
North American Regional Reanalysis ◽  
Regional Reanalysis

Abstract This study presents a spatial and temporal climatology of major wildfire events, defined as &gt;100 acres burned (&gt;40.47 ha, where 1 ha = 2.47 acre), in the northeast United States from 1999 to 2009 and the meteorological conditions associated with these events. The northeast United States is divided into two regions: region 1 is centered over the higher terrain of the northeast United States and region 2 is primarily over the coastal plain. About 59% of all wildfire events in these two regions occur in April and May, with ~76% in region 1 and ~53% in region 2. There is large interannual variability in wildfire frequency, with some years having 4–5 times more fire events than other years. The synoptic flow patterns associated with northeast United States wildfires are classified using the North American Regional Reanalysis. The most common synoptic pattern for region 1 is a surface high pressure system centered over the northern Appalachians, which occurred in approximately 46% of all events. For region 2, the prehigh anticyclone type extending from southeast Canada and the Great Lakes to the northeast United States is the most common pattern, occurring in about 46% of all events. A trajectory analysis highlights the influence of large-scale subsidence and decreasing relative humidity during the events, with the prehigh pattern showing the strongest subsidence and downslope drying in the lee of the Appalachians.

Avalanche Fatalities during Atmospheric River Events in the Western United States

2017 ◽  
Vol 18 (5) ◽  
pp. 1359-1374 ◽  
Author(s):  
Benjamin J. Hatchett ◽  
Susan Burak ◽  
Jonathan J. Rutz ◽  
Nina S. Oakley ◽  
Edward H. Bair ◽  
...  
Keyword(s):  
United States ◽  
Water Vapor ◽  
Snow Water Equivalent ◽  
Vapor Transport ◽  
Western United States ◽  
Snow Avalanche ◽  
Water Vapor Transport ◽  
Atmospheric Rivers ◽  
Avalanche Forecasting ◽  
Snow Water

Abstract The occurrence of atmospheric rivers (ARs) in association with avalanche fatalities is evaluated in the conterminous western United States between 1998 and 2014 using archived avalanche reports, atmospheric reanalysis products, an existing AR catalog, and weather station observations. AR conditions were present during or preceding 105 unique avalanche incidents resulting in 123 fatalities, thus comprising 31% of western U.S. avalanche fatalities. Coastal snow avalanche climates had the highest percentage of avalanche fatalities coinciding with AR conditions (31%–65%), followed by intermountain (25%–46%) and continental snow avalanche climates (&lt;25%). Ratios of avalanche deaths during AR conditions to total AR days increased with distance from the coast. Frequent heavy to extreme precipitation (85th–99th percentile) during ARs favored critical snowpack loading rates with mean snow water equivalent increases of 46 mm. Results demonstrate that there exists regional consistency between snow avalanche climates, derived AR contributions to cool season precipitation, and percentages of avalanche fatalities during ARs. The intensity of water vapor transport and topographic corridors favoring inland water vapor transport may be used to help identify periods of increased avalanche hazard in intermountain and continental snow avalanche climates prior to AR landfall. Several recently developed AR forecast tools applicable to avalanche forecasting are highlighted.

scholarly journals Simulation of Snow Water Equivalent (SWE) Using Thermodynamic Snow Models in Québec, Canada

2009 ◽  
Vol 10 (6) ◽  
pp. 1447-1463 ◽  
Author(s):  
A. Langlois ◽  
J. Kohn ◽  
A. Royer ◽  
P. Cliche ◽  
L. Brucker ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Meteorological Data ◽  
Regional Scale ◽  
Correlation Coefficients ◽  
Reanalysis Data ◽  
Regional Variability ◽  
The North ◽  
Snow Water ◽  
Regional Reanalysis

Abstract Snow cover plays a key role in the climate system by influencing the transfer of energy and mass between the soil and the atmosphere. In particular, snow water equivalent (SWE) is of primary importance for climatological and hydrological processes and is a good indicator of climate variability and change. Efforts to quantify SWE over land from spaceborne passive microwave measurements have been conducted since the 1980s, but a more suitable method has yet to be developed for hemispheric-scale studies. Tools such as snow thermodynamic models allow for a better understanding of the snow cover and can potentially significantly improve existing snow products at the regional scale. In this study, the use of three snow models [SNOWPACK, CROCUS, and Snow Thermal Model (SNTHERM)] driven by local and reanalysis meteorological data for the simulation of SWE is investigated temporally through three winter seasons and spatially over intensively sampled sites across northern Québec. Results show that the SWE simulations are in agreement with ground measurements through three complete winter seasons (2004/05, 2005/06, and 2007/08) in southern Québec, with higher error for 2007/08. The correlation coefficients between measured and predicted SWE values ranged between 0.72 and 0.99 for the three models and three seasons evaluated in southern Québec. In subarctic regions, predicted SWE driven with the North American Regional Reanalysis (NARR) data fall within the range of measured regional variability. NARR data allow snow models to be used regionally, and this paper represents a first step for the regionalization of thermodynamic multilayered snow models driven by reanalysis data for improved global SWE evolution retrievals.

Spatial Variability in Seasonal Snowpack Trends across the Rio Grande Headwaters (1984–2017)

2020 ◽  
Vol 21 (11) ◽  
pp. 2713-2733 ◽  
Author(s):  
Graham A. Sexstone ◽  
Colin A. Penn ◽  
Glen E. Liston ◽  
Kelly E. Gleason ◽  
C. David Moeser ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Forest Canopy ◽  
Snow Water Equivalent ◽  
Rio Grande ◽  
Winter Precipitation ◽  
Time Step ◽  
The North ◽  
Spatial Coverage ◽  
Snow Water ◽  
Snowpack Properties

AbstractThis study evaluated the spatial variability of trends in simulated snowpack properties across the Rio Grande headwaters of Colorado using the SnowModel snow evolution modeling system. SnowModel simulations were performed using a grid resolution of 100 m and 3-hourly time step over a 34-yr period (1984–2017). Atmospheric forcing was provided by phase 2 of the North American Land Data Assimilation System, and the simulations accounted for temporal changes in forest canopy from bark beetle and wildfire disturbances. Annual summary values of simulated snowpack properties [snow metrics; e.g., peak snow water equivalent (SWE), snowmelt rate and timing, and snow sublimation] were used to compute trends across the domain. Trends in simulated snow metrics varied depending on elevation, aspect, and land cover. Statistically significant trends did not occur evenly within the basin, and some areas were more sensitive than others. In addition, there were distinct trend differences between the different snow metrics. Upward trends in mean winter air temperature were 0.3°C decade−1, and downward trends in winter precipitation were −52 mm decade−1. Middle elevation zones, coincident with the greatest volumetric snow water storage, exhibited the greatest sensitivity to changes in peak SWE and snowmelt rate. Across the Rio Grande headwaters, snowmelt rates decreased by 20% decade−1, peak SWE decreased by 14% decade−1, and total snowmelt quantity decreased by 13% decade−1. These snow trends are in general agreement with widespread snow declines that have been reported for this region. This study further quantifies these snow declines and provides trend information for additional snow variables across a greater spatial coverage at finer spatial resolution.

scholarly journals Spatiotemporal Characteristics of Snowpack Density in the Mountainous Regions of the Western United States

2008 ◽  
Vol 9 (6) ◽  
pp. 1416-1426 ◽  
Author(s):  
Naoki Mizukami ◽  
Sanja Perica
Keyword(s):  
United States ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Western United States ◽  
Densification Rate ◽  
Snow Density ◽  
Mountainous Regions ◽  
Spatiotemporal Characteristics ◽  
Snow Water

Abstract Snow density is calculated as a ratio of snow water equivalent to snow depth. Until the late 1990s, there were no continuous simultaneous measurements of snow water equivalent and snow depth covering large areas. Because of that, spatiotemporal characteristics of snowpack density could not be well described. Since then, the Natural Resources Conservation Service (NRCS) has been collecting both types of data daily throughout the winter season at snowpack telemetry (SNOTEL) sites located in the mountainous areas of the western United States. This new dataset provided an opportunity to examine the spatiotemporal characteristics of snowpack density. The analysis of approximately seven years of data showed that at a given location and throughout the winter season, year-to-year snowpack density changes are significantly smaller than corresponding snow depth and snow water equivalent changes. As a result, reliable climatological estimates of snow density could be obtained from relatively short records. Snow density magnitudes and densification rates (i.e., rates at which snow densities change in time) were found to be location dependent. During early and midwinter, the densification rate is correlated with density. Starting in early or mid-March, however, snowpack density increases by approximately 2.0 kg m−3 day−1 regardless of location. Cluster analysis was used to obtain qualitative information on spatial patterns of snowpack density and densification rates. Four clusters were identified, each with a distinct density magnitude and densification rate. The most significant physiographic factor that discriminates between clusters was proximity to a large water body. Within individual mountain ranges, snowpack density characteristics were primarily dependent on elevation.

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