Snowfall and snowpack are essential sources for irrigation and drinking water in many regions of the world. On global average, more than one third of irrigation water in the world is from snowmelt [Steppuhn, 1981]. Changes in snowfall and snowpack can influence regional water supply [e.g., Dettinger and Cayan, 1995]. In addition, the timing and rate of snowmelt runoff is often critical to spring flood development [e.g., McCabe and Clark, 2005; Regonda et al., 2005; Stewart et al., 2005]. From climate perspective, snow cover and snowpack significantly affect energy budget and water exchange at the surface and influence regional and global weather and climate [e.g., Groisman et al., 1994; Hu and Feng, 2002].
 In the recent decades, snow and snow-driven hydrology over the North America has changed considerably accompanied with warming of the surface temperatures. The strong warming in the 1980s corresponded to large decline of snow cover in the North America [Karl et al., 1993; Frei et al., 1999; Mote, 2003; Mote et al., 2005]. From analysis of the snow cover in the North America in 1900–1994, Frei et al.  found that the snow cover in March has been decreasing since the 1950s. The decline of snow cover is particularly noticeable in the western United States (U.S.). This change has been attributed to increase of winter and spring temperatures, as elaborated by Mote et al.  and Stewart et al. . They showed that, in the past 50 years, dates of peak snow accumulation and peak snowmelt runoff have occurred 10–40 days earlier than in the years before. In accordance, spring snowpack has decreased by about 11%. Groisman et al. [2001, 2004] also found from station observations substantial decrease of snow cover in March and earlier ending dates of the last snowfall since 1950 in the western and northern U.S.
 In addition to influencing snowpack and snowmelt, temperature increase, particularly in the cold season, may also have affected the precipitation that falls as snow, or the winter snowfall/precipitation (S/P) ratio. Changes from solid to liquid form of precipitation could be critical because such changes could influence the snowpack and snow cover, which affect the available snow for spring melt. Lack of adequate spring melt would yield shortage and interruption of stream flows and lead to hydrological droughts in late spring and summer. Some evidence of changes of S/P ratio in the recent decades has been shown by Huntington et al.  and Knowles et al. . Huntington et al.  found that in the New England area the S/P ratio decreased in 1949–2000. Knowles et al.  showed a pronounced decrease of snowfall and S/P ratio in the western U.S. A study of snowfall in Illinois by Heim and Angel  also showed decreased snowfall and fewer snow days in the 1980s and 1990s, compared to the 1950–1970. In addition, the central U.S. have suffered frequent “snow droughts” in the past years, providing an evidence of decreasing snowfall in the central U.S.
 The relationship between changes of the S/P ratio and temperature is complex and varies in regions. For example, Huntington et al.  found the S/P ratio was weakly correlated with the surface air temperature, while Knowles et al.  showed a strong nonlinear relationship between S/P and the surface air temperature. According to this relationship, the decrease of S/P was associated with a moderate increase of winter wet-day minimum temperatures (0–3°C) during 1949–2004. In addition, the strong decrease in snowfall occurred when winter wet-day minimum temperatures, averaged over their study period, were warmer than −5°C.
 The change of the surface air temperature in the U.S. is not uniform. During the second half of the 20th century, a strong warming trend was observed in the western and the northern U.S. Warming in the eastern U.S. was weak, however, and changed to cooling in the southeast U.S. [Easterling, 2002; Feng and Hu, 2004; Groisman et al., 2004]. These varying trends of surface air temperatures could have different impacts on the snowfall and S/P ratio across the U.S. As an example, Huntington et al.  showed strong heterogeneous change of S/P in the New England area. Because the previous studies [Huntington et al., 2004; Knowles et al., 2006] analyzed the changes of snowfall and S/P ratio and the impacts of temperature for a few parts of the U.S. it remains important from both hydrological and climatic perspectives that we examine and understand the snowfall and S/P changes for the contiguous U.S.
 The focus of this study is to provide a detailed description of spatial variations of snowfall and the S/P ratio in the contiguous U.S. Details of the data sources and methods used in the analyses are in section 2. Trends in winter snowfall and S/P ratio are analyzed and presented in section 3. Impacts of temperature on monthly and seasonal changes of the S/P ratio also are examined in section 3. The possible effects of decreasing S/P on water resources and surface moisture fluxes are discussed in section 4. Section 5 contains conclusions.
2. Data and Methods
 Daily maximum and minimum surface air temperatures, precipitation, and snowfall were obtained for this study from the U.S. Historical Climatology Network (USHCN [Easterling et al., 1999]). The data set contains 1221 cooperative stations that have high-quality long-term observations. These observation data have been subjected to quality control which includes homogeneity testing and adjustments to assure their reliability.
 In this study, the liquid water equivalent of daily snowfall was determined following that described by Huntington et al.  and Knowles et al. . When nonzero snowfall was recorded at a station on a given day, the total liquid of precipitation was used as snowfall water equivalent, S, for that day. Possible biases resulting from using this method to measure the snowfall water equivalent are discussed by Huntington et al.  and Knowles et al. . For example, under mixed snow-rain conditions, use of total liquid of precipitation as S could result in a (positive) bias toward more “recorded snowfall” than the actual snowfall. However, as elaborated by Knowles et al.  and Yang et al. , the catch efficiency of precipitation gauges is typically lower for snowfall than for rainfall, especially in windy conditions. The undercatch of snowfall by the precipitation gauge will underestimate S. This negative bias, to some extent, may counter the previous positive bias and yield a small net bias. A more rigorous treatment of these effects was not possible at this time because of the absence of snowfall catch efficiency data and data flags for precipitation types at individual stations. These data limitations should be reminded in interpretations of the analysis results.
 This study focuses on the winter season, defined as November–March. To screen out the USHCN stations that have a large amount of missing values or little snowfall, the following four criteria were applied to each station. (1) If a winter month has missing precipitation (or snowfall) observations for more than 5 days that month was removed from the analysis. (2) If a winter has missing precipitation or snowfall observations for more than 10 days either clustered in one month or scattered in different months, that winter is considered having inadequate observations and was removed from the analysis. (3) Stations that contain more than 50% of winters of inadequate data in any 10-year period during 1949–2005 were excluded from this study. (4) Stations south of 37°N were excluded because most of them, except a few in mountainous areas of Arizona and New Mexico, have very little snowfall. (Inclusion of the stations in Arizona and New Mexico has little impact on the results of this study.) A similar set of criteria was used to screen the daily maximum and minimum surface air temperatures. These screenings ensure that the data used are sufficient to describe snowfall variations in the study period. There are 374 stations whose data met these sets of criteria for snowfall and temperature. These stations are fairly evenly distributed across the contiguous U.S., except in Montana and Wyoming (see Figure 1). Observations of precipitation, snowfall, maximum and minimum temperatures at those stations were used in our analyses.
 Data of 1949–2005 at each station were complied for snowfall water equivalent (S), total precipitation (P), S/P ratio, and the maximum and minimum surface air temperatures for wet (rainfall or snowfall) days, for each month and each winter. Daily (as well as monthly and winter) average air temperature was calculated as the arithmetic mean of the maximum and minimum air temperatures.
 Kendall's tau slope estimator [Sen, 1968; Gilbert, 1987] was used to evaluate the trends of the variables at each station. This slope estimator is a nonparametric method assuming no a priori distribution of variations in the data, and has been used frequently for trend analysis in environmental and climate studies [e.g., Hu et al., 2005; Huntington et al., 2004]. Correlation analysis and regression also were used to analyze variations of the S/P ratio and its relationship with temperatures.
3.1. Seasonal and Monthly Variations
 Figure 1 shows the trend of the S/P ratio in 1949–2005. While the spatial features of the trend in the New England area and the western U.S. are similar to that shown by Huntington et al.  and Knowles et al. , the areas showing coherent decrease of the S/P ratio are in the Pacific Northwest and the north-central U.S. In areas outside of these two boxes the trends are mixed with some stations showing increased S/P and others showing decreased S/P ratio. Among the 374 stations, 287 have decreased S/P. Among the 287, 135 stations show strong decreasing trend (significant at 95% confidence level). Meanwhile, the S/P ratio showed increase at 87 stations, of which 20 show strong increase (significant at 95% confidence level). On average, the contiguous U.S. has been experiencing strong decreases in the S/P ratio, a result suggesting that the precipitation has been falling as rain more often than snow in the last 5 decades.
 Changes of either or both types of precipitation (snowfall and rainfall) influence the S/P ratio. Thus, to better understand how the changes of S or P, or both, have influenced the S/P trend, we show in Figure 2 the long-term trends of S and P during 1949–2005. Compared to Figure 1, most of the stations show decreasing S in regions of negative S/P trend, a result suggesting that the decreased S/P ratio is primarily related to decreased amount of snowfall. The relationship between S/P and P is not as coherent as for S/P and S, however, and it is less geographically consistent. For example, over the Pacific Northwest, the S has been decreasing and P also decreasing at most of the stations. Because the averaged S in that region over the winter months has been decreasing at a large rate of −8.62% per decade, significant at 99% confidence level, the large decrease of S has caused the significant decreasing of S/P in the Pacific Northwest (Table 1). In the central U.S., the S has been decreasing but P increasing at most of the stations. The regional averaged S has been decreasing at −3.41% per decade but P increasing at 3.72% per decade (Table 1). These decreasing S and increasing P explain the strong decrease of the S/P ratio in the central U.S. In the eastern U.S., both S and P show weak decrease at a rate that has caused no net change of the S/P ratio (Table 1). These changes of S, P, and the S/P ratio shown in Figures 1 and 2 and Table 1 indicate different causes for the observed decreasing trend of the S/P ratio across the contiguous U.S.
|Wet-day temperature, °C/10yr||−0.08||−0.09||0.62c||0.28||0.66b||0.30c|
|Wet-day temperature, °C/10yr||0.08||0.35||0.97c||0.10||0.97c||0.52b|
|Wet-day temperature, °C/10yr||0.35||0.09||−0.23||−0.11||0.28||0.09|
|Wet-day temperature, °C/10yr||0.09||0.25||0.43||0.16||0.63c||0.36c|
 While there are on average many more stations with decreasing S/P than the number of stations with increasing S/P ratio (Table 2) for each winter month (November–March) in the contiguous U.S., the number of stations with decreasing S/P varies in different months (Table 2). Inspecting Table 2 we find that the month of March has the most stations showing decreasing S/P and the month of January has the fewest stations with decreasing S/P. The S/P decreased at 319 (85%) stations in March, of which 150 show significant decreasing trend. In contrast, S/P decreased at only 213 (57%) stations in January and increased at 161 stations. Moreover, the number of stations with significant decreasing S/P in January is about one half of the number of stations in March, albeit that number is still the second highest among all the winter months. On the other hand, the stations with significant increasing trend in January are 13 times (26 versus 2) as many as the stations in March (Table 2). The averaged S/P ratio over the contiguous U.S. also shows strongest decrease in March and weakest in January (Table 1). The overall strong decrease of the S/P ratio in March and weak decrease of S/P in January are consistent with the observed decreasing snowpack and snow cover in March and April and weak or no change in January in North America since 1950 [Frei et al., 1999].
|Negative trend||247 (70)||246 (54)||213 (72)||218 (43)||319 (150)||287 (135)|
|Positive trend||127 (16)||128 (19)||161 (26)||156 (11)||55 (2)||87 (20)|
 The trends of the S/P ratio at each station across the contiguous U.S. for January and March are shown in Figure 3. In the Pacific Northwest the S/P ratio has been decreasing substantially in both months. In the central and eastern U.S., the S/P trends are quite different between January and March, however. In the central U.S. and in January (Figure 3a), stations with increasing S/P trend are blended with stations of decreasing trend. Together they give a weak decrease of S/P for the region. In the eastern U.S., especially in the Ohio Valley, the S/P ratio has been increasing at a majority of the stations. The averaged January S/P is a positive 1.46% per decade (Table 1). In contrast, much stronger decreasing trends of S/P are shown in March in the central U.S. (Figure 3b). The averaged S/P is −4.5% per decade, significant at 99% confidence level. In the eastern U.S., decreasing S/P in March replaced weak increase of S/P in January at majority of the stations, yielding an average decrease S/P for the region.
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