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Mini Dragon Group (ages 6-7)

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Eric Sysoev
Eric Sysoev

Snowfall - Season 1 UPD


FX has been bullish on the project from the start, applying for a series tax credit in the fall of 2015 when it was still in the pilot stage. In December 2015, just as the pilot, written by Singelton and Ed Amadio, was being delivered to the network, Snowfall was approved for a $4.9 million tax credit toward its first season.




Snowfall - Season 1



Although trends in mean snowfall totals are an important indicator of changes in climate, it can be argued that the most influential snowfall years are those with extremely large or extremely small amounts of snowfall. High-extreme snowfall years are often accompanied by high-impact snowstorms that cause hazardous transportation conditions (Changnon and Changnon 2006). Also, the resulting snowpack can lead to flooding during the spring, especially if heavy rain accelerates melt (Todhunter 2001). Ski resorts and other winter recreation businesses can benefit in these years from deep and long-lasting snowpacks, and snowmelt can also fill downstream reservoirs. On the other hand, low-extreme snowfall years can lead to serious water shortages in regions dependent on deep snowpacks as a water reservoir (Mote et al. 2005); winter wheat can be vulnerable to winter frosts without a snow cover (Landau et al. 2000); and the winter frost wave may reach deeper into the soil in northern climates and damage tree roots without an insulating blanket of snow (Sutinen et al. 1999). Society benefits directly from a lack of snow by reductions in transportation hazards, roof and building damage, and snow-removal costs (Changnon et al. 2008). Extreme snowfall years have a large impact on the spatiotemporal distribution of the seasonal snowpack, greatly influencing the climate system (Dery and Brown 2007). The frequency of extreme snowfall years of either type can also be a sensitive indicator of climate change.


Low snowfall years and changes in the seasonal cycle of mountain snowpacks in the west during the late 1990s and early 2000s have been examined because of their impacts on water resources (Mote et al. 2005; Mote 2003; Regonda et al. 2005). High snowfall years such as those of the late 1970s in the north-central and northeastern United States have been studied extensively (Harnack 1980; Namias 1978). Likewise, the synoptic meteorological bases of many individual major snowstorms and their impacts have been closely examined (Kocin and Uccellini 2005a,b; Changnon and Changnon 2006). However, there has been no systematic examination of the temporal variability of high- or low-extreme snowfall years in the United States. Using a homogeneous subset of snowfall records, referenced to the same long base period, this study examined national and regional trends in extreme snowfall years, and the relationships of extreme snowfall years to temperature, precipitation, and El Niño and La Niña events.


The station snowfall data used in this study are from the National Weather Service Cooperative Observer Network (COOP). A substantial portion of the data prior to 1948 was keyed in the past decade as part of the Climate Database Modernization Program (Kunkel et al. 2005). There are a number of issues with these snowfall data that potentially affect any long-term analyses of extremes (Kunkel et al. 2007). Changes in station location, observer, and measurement practices over time can have a substantial effect on the homogeneity of individual time series. Therefore, a set of 440 long-term snowfall records specifically identified as sufficiently homogeneous for trends analysis were used for this study. The creation of this data subset will be described briefly; a more extensive discussion can be found in Kunkel et al. (2009a).


The record of extreme snowfall occurrences was examined using two approaches. First, winter-centered annual values for the percentage of the conterminous United States with high-extreme and low-extreme snowfall totals were calculated using an area-weighted approach. Within each 1 latitude by 1 longitude grid cell, the number of stations with snowfall exceeding an extreme threshold was counted and then a fraction was calculated based on the total number of stations with data in that grid cell. The gridcell fractions were then added together and divided by the number of grid cells with station snowfall data in that year in order to calculate the U.S. fraction, expressed as a percentage. For regional time series, a more direct approach was used since spatial variations in station density were not as great on a regional scale. The number of stations reporting an extreme snowfall amount for a given year and region was divided by the total number of stations with snowfall data for that year in that region. These time series were constructed for the nine standard regions established by the National Climatic Data Center (NCDC; Table 1). The use of the NCDC standard regions facilitates comparisons with regional temperature and precipitation time series already derived for these same regions from the time-of-observation bias-corrected climate division dataset (Karl et al. 1986). The nine NCDC regions are routinely used to summarize data in climate monitoring activities. Although not ideal in terms of a consistent climate across each region and not defined in terms of snowfall observations, they are sufficiently large to provide meaningful regional patterns in the continental United States, without resorting to a large number of smaller regions. These regions have been used in a number of recent studies documenting observed changes in climate including heavy precipitation (Karl and Knight 1998) and frost days (Easterling 2002). The regional analyses provide a spatially averaged view of the data that is complementary to the detailed station-by-station results, which reveal local detail. Statistical analysis of results is also more robust for regional time series than for station time series, an important consideration when analyzing extremes.


The national and regional time series were subjected to trend analysis. Although annual-to-decadal-scale variability are dominant features of these time series, as will be seen, the long-term trend is also of interest because of documented long-trends in temperature and precipitation in many regions. Given the obvious connection of snowfall to temperature and precipitation, it is of interest to examine whether any long-term snowfall extreme trends are consistent with observed trends in temperature and precipitation. Tests of the various regional time series indicated that in many cases the data distributions were not normal. Therefore, the nonparametric Kendall test was used to determine trend magnitude and statistical significance.


Some of the stations in the vicinity of the Great Lakes exhibit deviations considerably different than nearby areas (e.g., Figs. 3b,c,e). This may be due to lake-effect snowfall, a local phenomenon that may behave differently than large-scale synoptic forcing of snowfall events. Lake-effect snowfall has been studied separately and these results appear in Kunkel et al. (2009b).


Scatterplots for the Southwest (Figs. 6 and 7), generally representative of the other regions, show relatively high scatter and a somewhat nonlinear nature of the relationship between extreme frequencies and temperature and precipitation. This accounts for the relatively low amount of variance explained by regressions. Multiple regression analysis results in a significant improvement. A stepwise multiple regression relating temperature and precipitation with the Southwest high-extreme snowfall year percentages explains 53% of the variance. Temperature and precipitation together explain 39% of the variance of the Southwest low-extreme snowfall year percentages.


Strong El Niño events are associated with increased percentages of stations with low-extreme snowfall years in several regions, and in the United States as a whole (Table 4). This is quite evident from a visual inspection of Fig. 2b where all 6 El Niño events show low-extreme percentages above 10%. The U.S. result is significant at p


Strong La Niña events did not have an overall impact on the national high and low snowfall extremes percentages, but some regions did have a strong response (Table 4). In the Northwest, low-extreme snowfall years were significantly (p


Given the sensitivity of extreme snowfall seasons to temperature, and the signs of recent trends observed since 1950, it is likely that the increasing frequency of low-extreme snowfall years and decreasing frequency of high-extreme snowfall years are at least partially a consequence of the general warming that has occurred over that time period. 041b061a72


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