The close relationship between air and ground temperatures has been used to reconstruct paleoclimate conditions from ground temperatures. Unfortunately, the presence of snow decouples air and ground temperatures and obscures their relationship. The objective of this paper is to investigate the role that snowpack conditions play in affecting the relationship between air and soil temperatures. The annual thermal offset between mean annual soil and air temperatures is examined over a 12 year period (1990–2002) at Fargo, ND, using observed soil temperatures along with simulations from a physically based snowpack model. Early season snow cover does not necessarily lead to large thermal offsets. These snowpacks, while low in density, also tended to be shallow and therefore do not provide much thermal insulation. Winter snowpacks explain a greater portion of the annual thermal offset. While denser than fall snowpacks, the extra depth and longer persistence leads to superior insulation of the ground.

A one-dimensional snowpack model, a unique airmass identification scheme, and surface weather observations are used to investigate large ablation events in the central Appalachian Mountains of North America. Data from cooperative observing stations are used to identify large ablation events within a 1° latitude × 1° longitude grid box that covers the majority of the Lycoming Creek basin in northern Pennsylvania. All 1-day ablation events greater than or equal to 7.6 cm (3 in.) are identified for the period of 1950 through 2001. Seventy-one events are identified, and these days are matched with a daily airmass type derived using the Spatial Synoptic Classification technique. Average meteorological characteristics on ablation days of each airmass type are calculated in an effort to understand the diverse meteorological influences that led to the large ablation events. A one-dimensional mass and energy balance snowpack model (“SNTHERM”) is used to calculate surface/atmosphere energy fluxes responsible for ablation under each airmass type. Results indicate that large ablation events take place under diverse airmass/synoptic conditions in the central Appalachians. Five airmass types account for the 71 large ablation events over the 52-yr period. Forty-three of the events occurred under “moist” airmass types and 28 under “dry” airmass conditions. Large ablation events under dry airmass types are driven primarily by daytime net radiation receipt, especially net solar radiation. These events tend to occur early and late in the snow cover season when solar radiation receipt is highest and are characterized by relatively clear skies, warm daytime temperatures, and low dewpoint temperatures. Moist airmass types are characterized by cloudy, windy conditions with higher dewpoint temperatures and often with liquid precipitation. During these events sensible heat flux is most often the dominant energy flux to the snowpack during ablation episodes. However, in many cases there is also a significant input of energy to the snowpack associated with condensation. Combinations of high sensible and latent heat fluxes often result in extreme ablation episodes, similar to those witnessed in this area in January 1996.

Abstract:Snow cover is found across extensive areas of the northern hemisphere during the winter and early spring seasons. Meltwater provided by this snow cover can be an important source of freshwater for agriculture, domestic uses and hydroelectric power. Rapid ablation of the snowpack, however, can also pose environmental hazards such as¯ooding.The ability to forecast meltwater quantities is dependent upon a knowledge of the factors in¯uencing the snowmelt process. This paper employs a hybrid modelling and synoptic climatological approach to investigate the relationships between synoptic weather patterns, surface energy¯uxes and midwinter snowmelt in the northern Great Plains. The ®rst objective of this study is to identify distinct synoptic patterns that are associated with days where signi®cant snow cover ablation occurred. The second objective is to evaluate the relationships between synoptic-scale weather patterns, snow surface energy transfers and snowmelt. A case study of 21 February 1975 is used to illustrate these relationships. Unlike the other synoptic-type studies, which rely on empirically derived energy¯ux data from single index sites, this study employs a physically based snowpack model to generate estimates of energy¯uxes. The use of modelled¯uxes instead of measured values allows for a more spatially extensive analysis as surface¯uxes over the entire study region can be analysed in conjunction with the prevailing synoptic-scale weather patterns.Three major synoptic types, characterized by the presence of a midlatitude cyclone, are associated with large midwinter snowmelt episodes in the northern Great Plains. The case study illustrates how variations in temperature, humidity, cloud cover and wind speeds associated with such cyclonic storms can play a major role in aecting snow surface±atmosphere energy exchanges. As expected, elevated wind speeds and stronger temperature and humidity gradients signi®cantly increased the transfers of sensible and latent heat between the snow surface and the atmosphere. Increased cloud cover near the low pressure centre reduced incoming solar radiation but through counter radiation also reduced the loss of long-wave radiation. #

The Northern Great Plains is a region where variations in seasonal snow accumulation can have a dramatic affect on regional hydrology. In the past, one of the problems in studying snow hydrology has been obtaining information of sufficiently high temporal and spatial resolution on the water content of the snowpack. This project used a hybrid climatology of snow water equivalent (SWE) that incorporated both model and observed data. This climatology has a long time series (49 years) and a high spatial resolution (1°× 1°) sufficient for use in a climatic analysis.The long and complete time series of SWE generated in this project allowed for a comprehensive analysis of the meteorological and climate forcing mechanisms that influence the amount of SWE. The five largest (high SWE) and five smallest SWE (low SWE) accumulations on 1 March were examined. High SWE years received greater snowfall and fewer accumulated melting degree days throughout the season. Large SWE accumulations at the end of the season, however, were not always associated with deep snowpacks early in the season. Also, all five high SWE years had above normal snowfall in February. Years with small or no SWE had below-average snowfall but greater than average accumulated melting degree days.A synoptic analysis examined both atmospheric circulation and air mass frequencies to assess impacts on ablation and snowfall. A distinct difference in the frequency of different air mass during high SWE versus low SWE years was evident. High SWE years were characterized by substantially greater intrusions of the coldest and driest air mass type (dry polar). Low SWE years, in contrast, had a greater frequency of more moderate air masses (dry moderate and moist moderate). In years with above average SWE, negative departures in November-December-January-February composite 700 hPa field were evident across the continental USA and indicate a greater frequency of troughing across the study area. Low SWE years were characterized by a ridging pattern that reduced the likelihood of precipitation and may have aided in the intrusion of more moderate air masses.

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