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Snow field
About: Snow field is a research topic. Over the lifetime, 1517 publications have been published within this topic receiving 45608 citations. The topic is also known as: snowfield.
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TL;DR: In this paper, a two-dimensional, time-dependent cloud model was used to simulate a moderate intensity thunderstorm for the High Plains region, where six forms of water substance (water vapor, cloud water, cloud ice, rain, snow and hail) were simulated.
Abstract: A two-dimensional, time-dependent cloud model has been used to simulate a moderate intensity thunderstorm for the High Plains region. Six forms of water substance (water vapor, cloud water, cloud ice, rain, snow and hail, i.e., graupel) are simulated. The model utilizes the “bulk water” microphysical parameterization technique to represent the precipitation fields which are all assumed to follow exponential size distribution functions. Autoconversion concepts are used to parameterize the collision-coalescence and collision-aggregation processes. Accretion processes involving the various forms of liquid and solid hydrometeors are simulated in this model. The transformation of cloud ice to snow through autoconversion (aggregation) and Bergeron process and subsequent accretional growth or aggregation to form hail are simulated. Hail is also produced by various contact mechanisms and via probabilistic freezing of raindrops. Evaporation (sublimation) is considered for all precipitation particles outsi...
3,300 citations
01 Jan 2007
TL;DR: Contributing Authors: J.H. Box, D.O. Robinson, Ian Joughin, S. Smith, and D.W. Walsh.
Abstract: Contributing Authors: J. Box (USA), D. Bromwich (USA), R. Brown (Canada), J.G. Cogley (Canada), J. Comiso (USA), M. Dyurgerov (Sweden, USA), B. Fitzharris (New Zealand), O. Frauenfeld (USA, Austria), H. Fricker (USA), G. H. Gudmundsson (UK, Iceland), C. Haas (Germany), J.O. Hagen (Norway), C. Harris (UK), L. Hinzman (USA), R. Hock (Sweden), M. Hoelzle (Switzerland), P. Huybrechts (Belgium), K. Isaksen (Norway), P. Jansson (Sweden), A. Jenkins (UK), Ian Joughin (USA), C. Kottmeier (Germany), R. Kwok (USA), S. Laxon (UK), S. Liu (China), D. MacAyeal (USA), H. Melling (Canada), A. Ohmura (Switzerland), A. Payne (UK), T. Prowse (Canada), B.H. Raup (USA), C. Raymond (USA), E. Rignot (USA), I. Rigor (USA), D. Robinson (USA), D. Rothrock (USA), S.C. Scherrer (Switzerland), S. Smith (Canada), O. Solomina (Russian Federation), D. Vaughan (UK), J. Walsh (USA), A. Worby (Australia), T. Yamada (Japan), L. Zhao (China)
962 citations
TL;DR: In this article, the influence of seasonal snow cover on seasonally frozen ground has received relatively little attention and further study is needed, and further studies are needed to evaluate the impact of seasonal cover on the ground thermal regime.
Abstract: [1] The presence of seasonal snow cover during the cold season of the annual air temperature cycle has significant influence on the ground thermal regime in cold regions. Snow has high albedo and emissivity that cool the snow surface, high absorptivity that tends to warm the snow surface, low thermal conductivity so that a snow layer acts as an insulator, and high latent heat due to snowmelt that is a heat sink. The overall impact of snow cover on the ground thermal regime depends on the timing, duration, accumulation, and melting processes of seasonal snow cover; density, structure, and thickness of seasonal snow cover; and interactions of snow cover with micrometeorological conditions, local microrelief, vegetation, and the geographical locations. Over different timescales either the cooling or warming impact of seasonal snow cover may dominate. In the continuous permafrost regions, impact of seasonal snow cover can result in an increase of the mean annual ground and permafrost surface temperature by several degrees, whereas in discontinuous and sporadic permafrost regions the absence of seasonal snow cover may be a key factor for permafrost development. In seasonally frozen ground regions, snow cover can substantially reduce the seasonal freezing depth. However, the influence of seasonal snow cover on seasonally frozen ground has received relatively little attention, and further study is needed. Ground surface temperatures, reconstructed from deep borehole temperature gradients, have increased by up to 4°C in the past centuries and have been widely used as evidence of paleoclimate change. However, changes in air temperature alone cannot account for the changes in ground temperatures. Changes in seasonal snow conditions might have significantly contributed to the ground surface temperature increase. The influence of seasonal snow cover on soil temperature, soil freezing and thawing processes, and permafrost has considerable impact on carbon exchange between the atmosphere and the ground and on the hydrological cycle in cold regions/cold seasons.
852 citations
TL;DR: In this paper, the sensitivity of the global climate system to interannual variability of he Eurasian snow cover has been investigated with numerical models and it was found that heavy than normal Eurasian cover in spring leads to a “poor” monsoon over Southeast Asia.
Abstract: The sensitivity of the global climate system to interannual variability of he Eurasian snow cover has been investigated with numerical models. It was found that heavier than normal Eurasian snow cover in spring leads to a “poor” monsoon over Southeast Asia thereby verifying an idea over 100 years old. The poor monsoon was characterized by reduced rainfall over India and Burma, reduced wind stress over the Indian Ocean, lower than normal temperatures on the Asian land mass and in the overlying atmospheric column, reduced tropical jet, increased soil moisture, and other features associated with poor monsoons. Lighter than normal snow cover led to a “good” monsoon with atmospheric anomalies like those described above but of opposite sign. Remote responses from the snow field perturbation include readjustment of the Northern Hemispheric mass field in midlatitude, an equatorially symmetric response of the tropical geopotential height and temperature field and weak, but significant, perturbations in the surface wind stress and heat flux in the tropical Pacific.
The physics responsible for the regional response involves all elements of both the surface heat budget and heat budget of the full atmospheric column. In essence, the snow, soil and atmospheric moisture all act to keep the land and overlying atmospheric column colder than normal during a heavy snow simulation thus reducing the land–ocean temperature contrast needed to initiate the monsoon. The remote responses are driven by heating anomalies associated with both large scale air-sea interactions and precipitation events.
The model winds from the heavy snow experiment were used to drive an ocean model. The SST field in that model developed a weak El Nino in the equatorial Pacific. A coupled ocean-atmosphere model simulation perturbed only by anomalous Eurasian snow cover was also run and it developed a much stranger El Nino in the Pacific. The coupled system clearly amplified the wind stress anomaly associated with the poor monsoon. These results show the important role of an evolving (not specified) sea surface temperature in numerical experiments and the real climate system. Our general results also demonstrate the importance of land processes in global climate dynamics and their possible role as one of the factors that could trigger ENSO events.
686 citations
TL;DR: In this article, the authors compared the accuracy of the three products, namely, SMMR, NOAA/NESDIS and USAFGWC, and concluded that the results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes.
Abstract: Snow covers about 40 million km2 of the land area of the Northern Hemisphere during the winter season. The accumulation and depletion of snow is dynamically coupled with global hydrological and climatological processes. Snow covered area and snow water equivalent are two essential measurements. Snow cover maps are produced routinely by the National Environmental Satellite Data and Information Service of the National Oceanic and Atmospheric Administration (NOAA/NESDIS) and by the US Air Force Global Weather Center (USAFGWC). The snow covered area reported by these two groups sometimes differs by several million km2, Preliminary analysis is performed to evaluate the accuracy of these products. Microwave radiation penetrating through clouds and snowpacks could provide depth and water equivalent information about snow fields. Based on theoretical calculations, snow covered area and snow water equivalent retrieval algorithms have been developed. Snow cover maps for the Northern Hemisphere have been derived from Nimbus-7 SMMR data for a period of six years (1978–1984). Intercomparisons of SMMR, NOAA/NESDIS and USAFGWC snow maps have been conducted to evaluate and assess the accuracy of SMMR derived snow maps. The total snow covered area derived from SMMR is usually about 10% less than the other two products. This is because passive microwave sensors cannot detect shallow, dry snow which is less than 5 cm in depth. The major geographic regions in which the differences among these three products are the greatest are in central Asia and western China. Future study is required to determine the absolute accuracy of each product. Preliminary snow water equivalent maps have also been produced. Comparisons are made between retrieved snow water equivalent over large area and available snow depth measurements. The results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes. Heavily forested and mountainous areas tend to mask out the microwave snow signatures and thus comparisons with measured water equivalent are poorer in those areas.
650 citations