Impacts of snow on soil temperature observed across the circumpolar north

NASA Astrophysics Data System (ADS)

Zhang, Yu; Sherstiukov, Artem B.; Qian, Budong; Kokelj, Steven V.; Lantz, Trevor C.

2018-04-01

Climate warming has significant impacts on permafrost, infrastructure and soil organic carbon at the northern high latitudes. These impacts are mainly driven by changes in soil temperature (TS). Snow insulation can cause significant differences between TS and air temperature (TA), and our understanding about this effect through space and time is currently limited. In this study, we compiled soil and air temperature observations (measured at about 0.2 m depth and 2 m height, respectively) at 588 sites from climate stations and boreholes across the northern high latitudes. Analysis of this circumpolar dataset demonstrates the large offset between mean TS and TA in the low arctic and northern boreal regions. The offset decreases both northward and southward due to changes in snow conditions. Correlation analysis shows that the coupling between annual TS and TA is weaker, and the response of annual TS to changes in TA is smaller in boreal regions than in the arctic and the northern temperate regions. Consequently, the inter-annual variation and the increasing trends of annual TS are smaller than that of TA in boreal regions. The systematic and significant differences in the relationship between TS and TA across the circumpolar north is important for understanding and assessing the impacts of climate change and for reconstruction of historical climate based on ground temperature profiles for the northern high latitudes.

Influence of snow temperature on avalanche impact pressure

NASA Astrophysics Data System (ADS)

Sovilla, Betty; Koehler, Anselm; Steinkogler, Walter; Fischer, Jan-Thomas

2015-04-01

The properties of the snow entrained by an avalanche during its motion (density, temperature) significantly affect flow dynamics and can determine whether the flowing material forms granules or maintains its original fine-grained structure. In general, a cold and light snow cover typically fluidizes, while warmer and more cohesive snow may form a granular denser layer in a flowing avalanche. This structural difference has a fundamental influence not only in the mobility of the flow but also on the impact pressure of avalanches. Using measurements of impact pressure, velocity, density and snow temperature performed at the Swiss Vallée de la Sionne full-scale test site, we show that, impact pressure fundamentally changes with snow temperature. A transition threshold of about -2°C is determined, the same temperature at which snow granulation starts. On the one hand warm avalanches, characterized by temperatures larger than -2°C, move as a plug and exert impact pressures linearly proportional to the avalanche depth. For Froude numbers larger than 1, an additional square-velocity dependent contribution cannot be neglected. On the other hand cold avalanches, characterized by a temperature smaller than -2°C, move as dense sheared flows, or completely dilute powder clouds and exert impact pressures, which are mainly proportional to the square of the flow velocity. For these avalanches the impact pressures strongly depend on density variations within the flow. We suggest that the proposed temperature threshold can be used as a criterion to define the transition between the impact pressures exerted by warm and cold avalanches, thus offering a new way to elude the notorious difficulties in defining the differences between wet and dry flow, respectively.

Sensitivity of Support Vector Machine Predictions of Passive Microwave Brightness Temperature Over Snow-covered Terrain in High Mountain Asia

NASA Astrophysics Data System (ADS)

Ahmad, J. A.; Forman, B. A.

2017-12-01

High Mountain Asia (HMA) serves as a water supply source for over 1.3 billion people, primarily in south-east Asia. Most of this water originates as snow (or ice) that melts during the summer months and contributes to the run-off downstream. In spite of its critical role, there is still considerable uncertainty regarding the total amount of snow in HMA and its spatial and temporal variation. In this study, the NASA Land Information Systems (LIS) is used to model the hydrologic cycle over the Indus basin. In addition, the ability of support vector machines (SVM), a machine learning technique, to predict passive microwave brightness temperatures at a specific frequency and polarization as a function of LIS-derived land surface model output is explored in a sensitivity analysis. Multi-frequency, multi-polarization passive microwave brightness temperatures as measured by the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) over the Indus basin are used as training targets during the SVM training process. Normalized sensitivity coefficients (NSC) are then computed to assess the sensitivity of a well-trained SVM to each LIS-derived state variable. Preliminary results conform with the known first-order physics. For example, input states directly linked to physical temperature like snow temperature, air temperature, and vegetation temperature have positive NSC's whereas input states that increase volume scattering such as snow water equivalent or snow density yield negative NSC's. Air temperature exhibits the largest sensitivity coefficients due to its inherent, high-frequency variability. Adherence of this machine learning algorithm to the first-order physics bodes well for its potential use in LIS as the observation operator within a radiance data assimilation system aimed at improving regional- and continental-scale snow estimates.

Snow cover and temperature relationships in North America and Eurasia

NASA Technical Reports Server (NTRS)

Foster, J.; Owe, M.; Rango, A.

1983-01-01

In this study the snow cover extent during the autumn months in both North America and Eurasia has been related to the ensuing winter temperature as measured at several locations near the center of each continent. The relationship between autumn snow cover and the ensuing winter temperatures was found to be much better for Eurasia than for North America. For Eurasia the average snow cover extent during the autumn explained as much as 52 percent of the variance in the winter (December-February) temperatures compared to only 12 percent for North America. However, when the average winter snow cover was correlated with the average winter temperature it was found that the relationship was better for North America than for Eurasia. As much as 46 percent of the variance in the winter temperature was explained by the winter snow cover in North America compared to only 12 percent in Eurasia.

Spatiotemporal Variability and in Snow Phenology over Eurasian Continent druing 1966-2012

NASA Astrophysics Data System (ADS)

Zhong, X.; Zhang, T.; Wang, K.; Zheng, L.; Wang, H.

2016-12-01

Snow cover is a key part of the cryosphere, which is a critical component of the global climate system. Snow cover phenology critically effects on the surface energy budget, the surface albedo and hydrological processes. In this study, the climatology and spatiotemporal variability of snow cover phenology were investigated using the long-term (1966-2012) ground-based measurements of daily snow depth from 1103 stations across the Eurasian Continent. The results showed that the distributions of the first date, last date, snow cover duration and number of snow cover days generally represented the latitudinal zonality over the Eurasian Continent, and there were significant elevation gradient patterns in the Tibetan Plateau. The first date of snow cover delayed by about 1.2 day decade-1, the last date of snow cover advanced with the rate of -1.2 day decade-1, snow cover duration and number of snow cover days shortened by about 2.7and 0.6 day decade-1, respectively, from 1966 through 2012. Compared with precipitation, the correlation between snow cover phenology and air temperature was more significant. The changes in snow cover duration were mainly controlled by the changes of air temperature in autumn and spring. The shortened number of snow cover days was affected by rising temperature during the cold season except for the air temperature in autumn and spring.

Modeling the Physical Multi-Phase Interactions of HNO3 Between Snow and Air on the Antarctic Plateau (Dome C) and coast (Halley)

NASA Astrophysics Data System (ADS)

Chan, Hoi Ga; Frey, Markus M.; King, Martin D.

2017-04-01

Nitrogen oxides (NOx = NO + NO2) emissions from nitrate (NO3-) photolysis in snow affect the oxidising capacity of the lower troposphere especially in remote regions of the high latitudes with low pollution levels. The porous structure of snowpack allows the exchange of gases with the atmosphere driven by physicochemical processes, and hence, snow can act as both source and sink of atmospheric chemical trace gases. Current models are limited by poor process understanding and often require tuning parameters. Here, two multi-phase physical models were developed from first principles constrained by observed atmospheric nitrate, HNO3, to describe the air-snow interaction of nitrate. Similar to most of the previous approaches, the first model assumes that below a threshold temperature, To, the air-snow grain interface is pure ice and above To, a disordered interface (DI) emerges assumed to be covering the entire grain surface. The second model assumes that Air-Ice interactions dominate over the entire temperature range below melting and that only above the eutectic temperature, liquid is present in the form of micropockets in grooves. The models are validated with available year-round observations of nitrate in snow and air at a cold site on the Antarctica Plateau (Dome C, 75°06'S, 123°33'E, 3233 m a.s.l.) and at a relatively warm site on the Antarctica coast (Halley, 75°35'S, 26°39'E, 35 m a.s.l). The first model agrees reasonably well with observations at Dome C (Cv(RMSE) = 1.34), but performs poorly at Halley (Cv(RMSE) = 89.28) while the second model reproduces with good agreement observations at both sites without any tuning (Cv(RMSE) = 0.84 at both sites). It is therefore suggested that air-snow interactions of nitrate in the winter are determined by non-equilibrium surface adsorption and co-condensation on ice coupled with solid-state diffusion inside the grain. In summer, however, the air-snow exchange of nitrate is mainly driven by solvation into liquid

Snow Micro-Structure Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Micah Johnson, Andrew Slaughter

PIKA is a MOOSE-based application for modeling micro-structure evolution of seasonal snow. The model will be useful for environmental, atmospheric, and climate scientists. Possible applications include application to energy balance models, ice sheet modeling, and avalanche forecasting. The model implements physics from published, peer-reviewed articles. The main purpose is to foster university and laboratory collaboration to build a larger multi-scale snow model using MOOSE. The main feature of the code is that it is implemented using the MOOSE framework, thus making features such as multiphysics coupling, adaptive mesh refinement, and parallel scalability native to the application. PIKA implements three equations:more » the phase-field equation for tracking the evolution of the ice-air interface within seasonal snow at the grain-scale; the heat equation for computing the temperature of both the ice and air within the snow; and the mass transport equation for monitoring the diffusion of water vapor in the pore space of the snow.« less

Modification of Soil Temperature and Moisture Budgets by Snow Processes

NASA Astrophysics Data System (ADS)

Feng, X.; Houser, P.

2006-12-01

Snow cover significantly influences the land surface energy and surface moisture budgets. Snow thermally insulates the soil column from large and rapid temperature fluctuations, and snow melting provides an important source for surface runoff and soil moisture. Therefore, it is important to accurately understand and predict the energy and moisture exchange between surface and subsurface associated with snow accumulation and ablation. The objective of this study is to understand the impact of land surface model soil layering treatment on the realistic simulation of soil temperature and soil moisture. We seek to understand how many soil layers are required to fully take into account soil thermodynamic properties and hydrological process while also honoring efficient calculation and inexpensive computation? This work attempts to address this question using field measurements from the Cold Land Processes Field Experiment (CLPX). In addition, to gain a better understanding of surface heat and surface moisture transfer process between land surface and deep soil involved in snow processes, numerical simulations were performed at several Meso-Cell Study Areas (MSAs) of CLPX using the Center for Ocean-Land-Atmosphere (COLA) Simplified Version of the Simple Biosphere Model (SSiB). Measurements of soil temperature and soil moisture were analyzed at several CLPX sites with different vegetation and soil features. The monthly mean vertical profile of soil temperature during October 2002 to July 2003 at North Park Illinois River exhibits a large near surface variation (<5 cm), reveals a significant transition zone from 5 cm to 25 cm, and becomes uniform beyond 25cm. This result shows us that three soil layers are reasonable in solving the vertical variation of soil temperature at these study sites. With 6 soil layers, SSiB also captures the vertical variation of soil temperature during entire winter season, featuring with six soil layers, but the bare soil temperature is

Future Change of Snow Water Equivalent over Japan

NASA Astrophysics Data System (ADS)

Hara, M.; Kawase, H.; Kimura, F.; Fujita, M.; Ma, X.

2012-12-01

Western side of Honshu Island and Hokkaido Island in Japan are ones of the heaviest snowfall areas in the world. Although a heavy snowfall often brings disaster, snow is one of the major sources for agriculture, industrial, and house-use in Japan. Even during the winter, the monthly mean of the surface air temperature often exceeds 0 C in large parts of the heavy snow areas along the Sea of Japan. Thus, snow cover may be seriously reduced in these areas as a result of the global warming, which is caused by an increase in greenhouse gases. The change in seasonal march of snow water equivalent, e.g., snowmelt season and amount will strongly influence to social-economic activities. We performed a series of numerical experiments including present and future climate simulations and much-snow and less-snow cases using a regional climate model. Pseudo-Global-Warming (PGW) method (Kimura and Kitoh, 2008) is applied for the future climate simulations. MIROC 3.2 medres 2070s output under IPCC SRES A2 scenario and 1990s output under 20c3m scenario used for PGW method. The precipitation, snow depth, and surface air temperature of the hindcast simulations show good agreement with the AMeDAS station data. In much-snow cases, The decreasing rate of maximum total snow water equivalent over Japan due to climate change was 49%. Main cause of the decrease of the total snow water equivalent is the air temperature rise due to global climate change. The difference in the precipitation amount between the present and the future simulations is small.

Concentrations of Reactive Trace Gases In The Interstitial Air of Surface Snow

NASA Astrophysics Data System (ADS)

Jacobi, H.-W.; Honrath, R. E.; Peterson, M. C.; Lu, Y.; Dibb, J. E.; Arsenault, M. A.; Swanson, A. L.; Blake, N. J.; Bales, R. C.; Schrems, O.

Several measurements at Arctic and Antarctic sites have demonstrated that unexpected photochemical reactions occur in irradiated surface snow influencing the composi- tion of the boundary layer over snow-covered areas. The results of these reactions are probably most obvious in the interstitial air of the surface snow since it constitutes the interface between the surface snow and the boundary layer. Therefore, measurements of concentrations of nitrogen oxide and dioxide, nitrous acid, formaldehyde, hydro- gen peroxide, formic acid, acetic acid, and other organic compounds were performed in the interstitial air of the surface snow of the Greenland ice sheet. Concentrations were measured at variable depths between - 10 cm and - 50 cm during the summer field season in 2000 at the Summit Environmental Observatory. At shallow depths, the system NO-NO2-O3 exhibits large deviations from the calculated photostationary state. Using steady-state analyses applied to OH-HO2-CH3O2 cycling indicated the presence of high concentrations of OH and peroxy radicals in the firn air. Maximum concentrations calculated for a depth of - 10 cm are in the order of 6 105 molecules cm-3 and 1.4 * 107 molecules cm-3 for OH and HO2, respectively, although radia- tion levels at - 10 cm are reduced by approximately 50 % compared to levels above the snow surface. By far the most important OH source is the photolysis of HONO while the photolysis of ozone contributes less than 2 % to the overall production of OH in the firn air.

Snow as an accumulator of air pollutants

Treesearch

Robert T. Brown

1976-01-01

Using simple analytical techniques, the amounts of air pollutants accumulated in winter snow were determined and the results correlated with lichen survival on trees. Pollutants measured were particulate matter, sulfate, and chloride. An inverse relationship was found between amounts of each of these pollutants and the abundance of various lichens.

Air-snow interaction of nitrogen species in the polar regions

NASA Astrophysics Data System (ADS)

Cutting Thakur, Roseline; Thamban, Meloth

2017-04-01

The previous studies in the polar regions have frequently compared ion concentration of nitrogen species in snow and aerosol, neglecting to discuss the fact that snow could also scavenge chemical compounds in the gas phase. Further, Peroxyacetyl nitrate (PAN(g)) which is a reactive nitrogen oxide and constitutes ˜90% of the total NOy in the higher altitudes has very scarce measurements in Antarctica and higher altitude areas. The present study reports the interaction of gaseous PAN(g) and HNO3(g)species with NO3- in aerosols and surface snow, in different meteorological conditions at both Antarctic and Arctic regions. Trace gases were sampled through the denuder tubes followed by a Teflon filter to collect the aerosol species and analyzed through the Ion Chromatography technique. Simultaneous snow measurements were also carried out near the air sampling site, close to the Polar Indian research stations. Samples were collected over a period of 15 days in January-February, 2014 in Larsemann Hills, East Antarctica, and 9 days during April, 2012 in Ny- Ålesund, Arctic. Obervations suggest that during high temperature, high radiation and high humidity conditions HNO3(g) concentration decrease with a simultaneous increase in aerosol NO3- [NO3- (A)] in both the regions. It implies that HNO3(g) converts to NO3-(A) probably through the reaction with sea-salt aerosols leading to the formation NO3- in aerosols. Further, the NO3- aerosol-snow interaction is also strong in these conditions. Such associations suggested that, dry deposition of nitrate aerosol could be a source of snow nitrate [NO3- (S)]. Further, a decrease of PAN(g)concentration with a simultaneous increase in NO3-(A) suggested that PAN(g) undergoes photolytic conversion to form NO2(g) and HNO3(g), which may further hydrolyze to form NO3-(A) due to high humidity conditions. However, this mechanism was not dominant during low temperature and low radiation conditions in both the regions, rather a direct gaseous

THE INFLUENCE OF THE SPATIAL DISTRIBUTION OF SNOW ON BASIN-AVERAGED SNOWMELT. (R824784)

EPA Science Inventory

Spatial variability in snow accumulation and melt owing to topographic effects on solar radiation, snow drifting, air temperature and precipitation is important in determining the timing of snowmelt releases. Precipitation and temperature effects related to topography affect snow...

Arctic tundra shrub invasion and soot deposition: Consequences for spring snowmelt and near-surface air temperatures

NASA Astrophysics Data System (ADS)

Strack, John E.

Invasive shrubs and soot pollution both have the potential to alter the surface energy balance and timing of snow melt in the Arctic. Shrubs reduce the amount of snow lost to sublimation on the tundra during the winter leading to a deeper end-of-winter snowpack. The shrubs also enhance the absorption of energy by the snowpack during the melt season, by converting incoming solar radiation to longwave radiation and sensible heat. This results in a faster rate of snow melt, warmer near-surface air temperatures, and a deeper boundary layer. Soot deposition lowers the albedo of the snow allowing it to more effectively absorb incoming solar radiation and thus melt faster. This study uses the Colorado State University Regional Atmospheric Modeling System version 4.4 (CSU-RAMS 4.4), equipped with an enhanced snow model, to investigate the effects of shrub encroachment and soot deposition on the atmosphere and snowpack in the Kuparuk Basin of Alaska during the May-June melt period. The results of the simulations suggest that a complete invasion of the tundra by shrubs leads to a 1.5 degree C warming of 2-m air temperatures, 17 watts per meter square increase in surface sensible heat flux, and a 108 m increase in boundary layer depth during the melt period. The snow free-date also occurred 11 days earlier despite having a larger initial snowpack. The results also show that a decrease in the snow albedo of 0.1, due to soot pollution, caused the snow-free date to occur five days earlier. The soot pollution caused a 0.5 degree C warming of 2-m air temperatures and a 2 watts per meter square increase in surface sensible heat flux. In addition, the boundary layer averaged 25 m deeper in the polluted snow simulation.

Effects of different temperature treatments on biological ice nuclei in snow samples

NASA Astrophysics Data System (ADS)

Hara, Kazutaka; Maki, Teruya; Kakikawa, Makiko; Kobayashi, Fumihisa; Matsuki, Atsushi

2016-09-01

The heat tolerance of biological ice nucleation activity (INA) depends on their types. Different temperature treatments may cause varying degrees of inactivation on biological ice nuclei (IN) in precipitation samples. In this study, we measured IN concentration and bacterial INA in snow samples using a drop freezing assay, and compared the results for unheated snow and snow treated at 40 °C and 90 °C. At a measured temperature of -7 °C, the concentration of IN in untreated snow was 100-570 L-1, whereas the concentration in snow treated at 40 °C and 90 °C was 31-270 L-1 and 2.5-14 L-1, respectively. In the present study, heat sensitive IN inactivated by heating at 40 °C were predominant, and ranged 23-78% of IN at -7 °C compared with untreated samples. Ice nucleation active Pseudomonas strains were also isolated from the snow samples, and heating at 40 °C and 90 °C inactivated these microorganisms. Consequently, different temperature treatments induced varying degrees of inactivation on IN in snow samples. Differences in the concentration of IN across a range of treatment temperatures might reflect the abundance of different heat sensitive biological IN components.

The Development of Snow Properties and Its Effect on Trafficability.

DTIC Science & Technology

1980-04-01

preferred to the horizontally applied NRC snow hardness tester. Hence the latter does not enter into graphical representation of the snow cover...depth was broken or cracked during vehicle passage. With the air temperature at 0°C, snow density was meassured in the trace of the right track: TABLE I

Does Temperature Modify the Effects of Rain and Snow Precipitation on Road Traffic Injuries?

PubMed

Lee, Won-Kyung; Lee, Hye-Ah; Hwang, Seung-sik; Kim, Ho; Lim, Youn-Hee; Hong, Yun-Chul; Ha, Eun-Hee; Park, Hyesook

2015-01-01

There are few data on the interaction between temperature and snow and rain precipitation, although they could interact in their effects on road traffic injuries. The integrated database of the Korea Road Traffic Authority was used to calculate the daily frequency of road traffic injuries in Seoul. Weather data included rain and snow precipitation, temperature, pressure, and fog from May 2007 to December 2011. Precipitation of rain and snow were divided into nine and six temperature range categories, respectively. The interactive effects of temperature and rain and snow precipitation on road traffic injuries were analyzed using a generalized additive model with a Poisson distribution. The risk of road traffic injuries during snow increased when the temperature was below freezing. Road traffic injuries increased by 6.6% when it was snowing and above 0 °C, whereas they increased by 15% when it was snowing and at or below 0 °C. In terms of heavy rain precipitation, moderate temperatures were related to an increased prevalence of injuries. When the temperature was 0-20 °C, we found a 12% increase in road traffic injuries, whereas it increased by 8.5% and 6.8% when it was <0 °C and >20 °C, respectively. The interactive effect was consistent across the traffic accident subtypes. The effect of adverse weather conditions on road traffic injuries differed depending on the temperature. More road traffic injuries were related to rain precipitation when the temperature was moderate and to snow when it was below freezing.

Does Temperature Modify the Effects of Rain and Snow Precipitation on Road Traffic Injuries?

PubMed Central

Lee, Won-Kyung; Lee, Hye-Ah; Hwang, Seung-sik; Kim, Ho; Lim, Youn-Hee; Hong, Yun-Chul; Ha, Eun-Hee; Park, Hyesook

2015-01-01

Background There are few data on the interaction between temperature and snow and rain precipitation, although they could interact in their effects on road traffic injuries. Methods The integrated database of the Korea Road Traffic Authority was used to calculate the daily frequency of road traffic injuries in Seoul. Weather data included rain and snow precipitation, temperature, pressure, and fog from May 2007 to December 2011. Precipitation of rain and snow were divided into nine and six temperature range categories, respectively. The interactive effects of temperature and rain and snow precipitation on road traffic injuries were analyzed using a generalized additive model with a Poisson distribution. Results The risk of road traffic injuries during snow increased when the temperature was below freezing. Road traffic injuries increased by 6.6% when it was snowing and above 0°C, whereas they increased by 15% when it was snowing and at or below 0°C. In terms of heavy rain precipitation, moderate temperatures were related to an increased prevalence of injuries. When the temperature was 0–20°C, we found a 12% increase in road traffic injuries, whereas it increased by 8.5% and 6.8% when it was <0°C and >20°C, respectively. The interactive effect was consistent across the traffic accident subtypes. Conclusions The effect of adverse weather conditions on road traffic injuries differed depending on the temperature. More road traffic injuries were related to rain precipitation when the temperature was moderate and to snow when it was below freezing. PMID:26073021

Temperature inversions and cold-air pools study in Picos de Europa surroundings

NASA Astrophysics Data System (ADS)

Iglesias González, Miguel; Yagüe, Carlos; Maqueda, Gregorio

2017-04-01

Using surface temperature data from dataloggers located at the bottom of four different high-altitude (2000 m MSL) glaciokarstic depressions in Picos de Europa (Cantabrian Cordillera, Spain) from January 2012 to September 2016, we have analyzed the evolution of more than 200 different cold-air pools events according to different geomorphologic parameters. The ski-view determinates the cold-air pool occurrence and the temperature range, and the depression's depth is a very important factor in the permanent cold-air pools (PCAP) formation. Depending on the structure of the thermal curve, we classified all cold-air pools in each depression by using a conceptual model with eight different modes. With wind and relative humidity data, supplied by a weather station situated near the depressions, and NCAR-NCEP reanalysis data, we have characterized them at mesoscale and synoptic scale. If the ski-view is small enough, we can have undisturbed cold-air pools even though disturbed wind conditions. Snow-covered and non-snow-covered events were measured during the campaign, which allow us to recognize its influence on the temperature inversions. We also identified and analyze several permanent cold-air pools events where December minimum temperature record of -30,6°C in the Iberian Peninsula was measured. We also make a deep analyze of the Iberian Peninsula historical minimal temperature record of -32,7°C, which was measured on February 2016. Finally we use and test a simplified three-layer radiative model to describe and verify the influence of different geomorphologic factors in the cooling process of all the cold-air pools.

Evaluation of MODIS Land Surface Temperature with In Situ Snow Surface Temperature from CREST-SAFE

NASA Astrophysics Data System (ADS)

Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Munoz, J.; Khanbilvardi, R.; Yu, Y.

2016-12-01

This paper presents the procedure and results of a temperature-based validation approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) product provided by the National Aeronautics and Space Administration (NASA) Terra and Aqua Earth Observing System satellites using in situ LST observations recorded at the Cooperative Remote Sensing Science and Technology Center - Snow Analysis and Field Experiment (CREST-SAFE) during the years of 2013 (January-April) and 2014 (February-April). A total of 314 day and night clear-sky thermal images, acquired by the Terra and Aqua satellites, were processed and compared to ground-truth data from CREST-SAFE with a frequency of one measurement every 3 min. Additionally, this investigation incorporated supplementary analyses using meteorological CREST-SAFE in situ variables (i.e. wind speed, cloud cover, incoming solar radiation) to study their effects on in situ snow surface temperature (T-skin) and T-air. Furthermore, a single pixel (1km2) and several spatially averaged pixels were used for satellite LST validation by increasing the MODIS window size to 5x5, 9x9, and 25x25 windows for comparison. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and nighttime values. Results indicate that, although all the data sets (Terra and Aqua, diurnal and nocturnal) showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C), both suggesting that MODIS LST retrievals are reliable for similar land cover classes and atmospheric conditions. Results from the CREST-SAFE in situ variables' analyses indicate that T-air is commonly higher than T-skin, and that a lack of cloud cover results in: lower T-skin and higher T-air minus T-skin difference (T-diff). Additionally, the study revealed that T-diff is inversely proportional to cloud cover, wind speed, and incoming solar radiation. Increasing the MODIS window size

Temporal Changes in the Observed Relationship between Cloud Cover and Surface Air Temperature.

NASA Astrophysics Data System (ADS)

Sun, Bomin; Groisman, Pavel Ya.; Bradley, Raymond S.; Keimig, Frank T.

2000-12-01

The relationship between cloud cover and near-surface air temperature and its decadal changes are examined using the hourly synoptic data for the past four to six decades from five regions of the Northern Hemisphere: Canada, the United States, the former Soviet Union, China, and tropical islands of the western Pacific. The authors define the normalized cloud cover-surface air temperature relationship, NOCET or dT/dCL, as a temperature anomaly with a unit (one-tenth) deviation of total cloud cover from its average value. Then mean monthly NOCET time series (night- and daytime, separately) are area-averaged and parameterized as functions of surface air humidity and snow cover. The day- and nighttime NOCET variations are strongly anticorrelated with changes in surface humidity. Furthermore, the daytime NOCET changes are positively correlated to changes in snow cover extent. The regionally averaged nighttime NOCET varies from 0.05 K tenth1 in the wet Tropics to 1.0 K tenth1 at midlatitudes in winter. The daytime regional NOCET ranges from 0.4 K tenth1 in the Tropics to 0.7 K tenth1 at midlatitudes in winter.The authors found a general strengthening of a daytime surface cooling during the post-World War II period associated with cloud cover over the United States and China, but a minor reduction of this cooling in higher latitudes. Furthermore, since the 1970s, a prominent increase in atmospheric humidity has significantly weakened the effectiveness of the surface warming (best seen at nighttime) associated with cloud cover.The authors apportion the spatiotemporal field of interactions between total cloud cover and surface air temperature into a bivariate relationship (described by two equations, one for daytime and one for nighttime) with surface air humidity and snow cover and two constant factors. These factors are invariant in space and time domains. It is speculated that they may represent empirical estimates of the overall cloud cover effect on the surface air

Evolution of the Specific Surface Area of Snow in a High Temperature Gradient Metamorphism

NASA Astrophysics Data System (ADS)

Wang, X.; Baker, I.

2014-12-01

The structural evolution of low-density snow under a high temperature gradient over a short period usually takes place in the surface layers during diurnal recrystallization or on a clear, cold night. To relate snow microstructures with their thermal properties, we combined X-ray computed microtomography (micro-CT) observations with numerical simulations. Different types of snow were tested over a large range of TGs (100 K m-1- 500 K m-1). The Specific Surface Area (SSA) was used to characterize the temperature gradient metamorphism (TGM). The magnitude of the temperature gradient and the initial snow type both influence the evolution of SSA. The SSA evolution under TGM was dominated by grain growth and the formation of complex surfaces. Fresh snow experienced a logarithmic decrease of SSA with time, a feature been observed previously by others [Calonne et al., 2014; Schneebeli and Sokratov, 2004; Taillandier et al., 2007]. However, for initial rounded and connected snow structures, the SSA will increase during TGM. Understanding the SSA increase is important in order to predict the enhanced uptake of chemical species by snow or increase in snow albedo. Calonne, N., F. Flin, C. Geindreau, B. Lesaffre, and S. Rolland du Roscoat (2014), Study of a temperature gradient metamorphism of snow from 3-D images: time evolution of microstructures, physical properties and their associated anisotropy, The Cryosphere Discussions, 8, 1407-1451, doi:10.5194/tcd-8-1407-2014. Schneebeli, M., and S. A. Sokratov (2004), Tomography of temperature gradient metamorphism of snow and associated changes in heat conductivity, Hydrological Processes, 18(18), 3655-3665, doi:10.1002/hyp.5800. Taillandier, A. S., F. Domine, W. R. Simpson, M. Sturm, and T. A. Douglas (2007), Rate of decrease of the specific surface area of dry snow: Isothermal and temperature gradient conditions, Journal of Geophysical Research: Earth Surface (2003-2012), 112(F3), doi: 10.1029/2006JF000514.

Snow and ice control at extreme temperatures.

DOT National Transportation Integrated Search

2011-04-25

As expected, most state and provincial DOTs that we spoke with are using traditional methods to prevent and : remove snow and ice at very low temperatures. In addition to a review of current research, we spoke with six winter : maintenance profession...

Interannual variability of March snow mass over Northern Eurasia and its relation to the concurrent and preceding surface air temperature, precipitation and atmospheric circulation

NASA Astrophysics Data System (ADS)

Ye, Kunhui

2018-06-01

The interannual variability of March snow water equivalent (SWE) in Northern Eurasia and its influencing factors are studied. The surface air temperature (SAT) and precipitation are the dominant factors for the snow accumulation in northern Europe and the remaining region, respectively. The strongest contribution of SAT to snow accumulation is mainly found in those months with moderate mean SAT. The strongest contribution of precipitation is not collocated with the climatological maxima in precipitation. The leading mode of March SWE variability is obtained and characterized by a spatial dipole. Anomalies in atmospheric water vapor divergence, storm activity and the associated atmospheric circulation can explain many of the associated precipitation and SAT features. Anomalies in autumn Arctic sea ice concentration (SIC) over the Barents Sea and Kara Sea (B/K Sea) and a dipole pattern of November snow cover (SC) in Eurasia are also observed. The atmospheric circulation anomalies that resemble a negative phase of North Atlantic Oscillation (NAO)/Arctic Oscillation (AO) are strongly projected onto the wintertime atmospheric circulation. Both observations and model experiment support that the autumn B/K Sea SIC has some impacts on the autumn and AO/NAO-like wintertime atmospheric circulation patterns. The dipole pattern of November Eurasian SC seems to be strongly forced by the autumn B/K Sea SIC and its feedback to the atmospheric circulation is important. Therefore, the impacts of autumn B/K Sea SIC on the autumn/wintertime atmospheric circulation and thus the March SWE variability may be modulated by both constructive and destructive interference of autumn Eurasian SC.

Long-term analyses of snow dynamics within the french Alps on the 1900-2100 period. Analyses of historical snow water equivalent observations, modelisations and projections of a hundred of snow courses.

NASA Astrophysics Data System (ADS)

Mathevet, T.; Joel, G.; Gottardi, F.; Nemoz, B.

2017-12-01

The aim of this communication is to present analyses of climate variability and change on snow water equivalent (SWE) observations, reconstructions (1900-2016) and scenarii (2020-2100) of a hundred of snow courses dissiminated within the french Alps. This issue became particularly important since a decade, in regions where snow variability had a large impact on water resources availability, poor snow conditions in ski resorts and artificial snow production. As a water resources manager in french mountainuous regions, EDF (french hydropower company) has developed and managed a hydrometeorological network since 1950. A recent data rescue research allowed to digitize long term SWE manual measurments of a hundred of snow courses within the french Alps. EDF have been operating an automatic SWE sensors network, complementary to the snow course network. Based on numerous SWE observations time-series and snow accumulation and melt model (Garavaglia et al., 2017), continuous daily historical SWE time-series have been reconstructed within the 1950-2016 period. These reconstructions have been extented to 1900 using 20 CR reanalyses (ANATEM method, Kuentz et al., 2015) and up to 2100 using GIEC Climate Change scenarii. Considering various mountainous areas within the french Alps, this communication focuses on : (1) long term (1900-2016) analyses of variability and trend of total precipitation, air temperature, snow water equivalent, snow line altitude, snow season length , (2) long term variability of hydrological regime of snow dominated watersheds and (3) future trends (2020 -2100) using GIEC Climate Change scenarii. Comparing historical period (1950-1984) to recent period (1984-2016), quantitative results within a region in the north Alps (Maurienne) shows an increase of air temperature by 1.2 °C, an increase of snow line height by 200m, a reduction of SWE by 200 mm/year and a reduction of snow season length by 15 days. These analyses will be extended from north to south

Drought and Snow: Analysis of Drivers, Processes and Impacts of Streamflow Droughts in Snow-Dominated Regions

NASA Astrophysics Data System (ADS)

Van Loon, Anne; Laaha, Gregor; Van Lanen, Henny; Parajka, Juraj; Fleig, Anne; Ploum, Stefan

2016-04-01

Around the world, drought events with severe socio-economic impacts seem to have a link with winter snowpack. That is the case for the current California drought, but analysing historical archives and drought impact databases for the US and Europe we found many impacts that can be attributed to snowpack anomalies. Agriculture and electricity production (hydropower) were found to be the sectors that are most affected by drought related to snow. In this study, we investigated the processes underlying hydrological drought in snow-dominated regions. We found that drought drivers are different in different regions. In Norway, more than 90% of spring streamflow droughts were preceded by below-average winter precipitation, while both winter air temperature and spring weather were indifferent. In Austria, however, spring streamflow droughts could only be explained by a combination of factors. For most events, winter and spring air temperatures were above average (70% and 65% of events, respectively), and winter and spring precipitation was below average (75% and 80%). Because snow storage results from complex interactions between precipitation and temperature and these variables vary strongly with altitude, snow-related drought drivers have a large spatial variability. The weather input is subsequently modified by land properties. Multiple linear regression between drought severity variables and a large number of catchment characteristics for 44 catchments in Austria showed that storage influences both drought duration and deficit volume. The seasonal storage of water in snow and glaciers was found to be a statistically important variable explaining streamflow drought deficit. Our drought impact analysis in Europe also showed that 40% of the selected drought impacts was caused by a combination of snow-related and other drought types. For example, the combination of a winter drought with a preceding or subsequent summer drought was reported to have a large effect on

Drought and Snow: Analysis of Drivers, Processes and Impacts of Streamflow Droughts in Snow-Dominated Regions

NASA Astrophysics Data System (ADS)

Van Loon, A.; Laaha, G.; Van Lanen, H.; Parajka, J.; Fleig, A. K.; Ploum, S.

2015-12-01

Around the world, drought events with severe socio-economic impacts seem to have a link with winter snowpack. That is the case for the current California drought, but analysing historical archives and drought impact databases for the US and Europe we found many impacts that can be attributed to snowpack anomalies. Agriculture and electricity production (hydropower) were found to be the sectors that are most affected by drought related to snow. In this study, we investigated the processes underlying hydrological drought in snow-dominated regions. We found that drought drivers are different in different regions. In Norway, more than 90% of spring streamflow droughts were preceded by below-average winter precipitation, while both winter air temperature and spring weather were indifferent. In Austria, however, spring streamflow droughts could only be explained by a combination of factors. For most events, winter and spring air temperatures were above average (70% and 65% of events, respectively), and winter and spring precipitation was below average (75% and 80%). Because snow storage results from complex interactions between precipitation and temperature and these variables vary strongly with altitude, snow-related drought drivers have a large spatial variability. The weather input is subsequently modified by land properties. Multiple linear regression between drought severity variables and a large number of catchment characteristics for 44 catchments in Austria showed that storage influences both drought duration and deficit volume. The seasonal storage of water in snow and glaciers was found to be a statistically important variable explaining streamflow drought deficit. Our drought impact analysis in Europe also showed that 40% of the selected drought impacts was caused by a combination of snow-related and other drought types. For example, the combination of a winter drought with a preceding or subsequent summer drought was reported to have a large effect on

Idiosyncratic Responses of High Arctic Plants to Changing Snow Regimes

PubMed Central

Rumpf, Sabine B.; Semenchuk, Philipp R.; Dullinger, Stefan; Cooper, Elisabeth J.

2014-01-01

The Arctic is one of the ecosystems most affected by climate change; in particular, winter temperatures and precipitation are predicted to increase with consequent changes to snow cover depth and duration. Whether the snow-free period will be shortened or prolonged depends on the extent and temporal patterns of the temperature and precipitation rise; resulting changes will likely affect plant growth with cascading effects throughout the ecosystem. We experimentally manipulated snow regimes using snow fences and shoveling and assessed aboveground size of eight common high arctic plant species weekly throughout the summer. We demonstrated that plant growth responded to snow regime, and that air temperature sum during the snow free period was the best predictor for plant size. The majority of our studied species showed periodic growth; increases in plant size stopped after certain cumulative temperatures were obtained. Plants in early snow-free treatments without additional spring warming were smaller than controls. Response to deeper snow with later melt-out varied between species and categorizing responses by growth forms or habitat associations did not reveal generic trends. We therefore stress the importance of examining responses at the species level, since generalized predictions of aboveground growth responses to changing snow regimes cannot be made. PMID:24523859

Idiosyncratic responses of high Arctic plants to changing snow regimes.

PubMed

Rumpf, Sabine B; Semenchuk, Philipp R; Dullinger, Stefan; Cooper, Elisabeth J

2014-01-01

The Arctic is one of the ecosystems most affected by climate change; in particular, winter temperatures and precipitation are predicted to increase with consequent changes to snow cover depth and duration. Whether the snow-free period will be shortened or prolonged depends on the extent and temporal patterns of the temperature and precipitation rise; resulting changes will likely affect plant growth with cascading effects throughout the ecosystem. We experimentally manipulated snow regimes using snow fences and shoveling and assessed aboveground size of eight common high arctic plant species weekly throughout the summer. We demonstrated that plant growth responded to snow regime, and that air temperature sum during the snow free period was the best predictor for plant size. The majority of our studied species showed periodic growth; increases in plant size stopped after certain cumulative temperatures were obtained. Plants in early snow-free treatments without additional spring warming were smaller than controls. Response to deeper snow with later melt-out varied between species and categorizing responses by growth forms or habitat associations did not reveal generic trends. We therefore stress the importance of examining responses at the species level, since generalized predictions of aboveground growth responses to changing snow regimes cannot be made.

Quantifying Temperature Effects on Snow, Plant and Streamflow Dynamics in Headwater Catchments

NASA Astrophysics Data System (ADS)

Wainwright, H. M.; Sarah, T.; Siirila-Woodburn, E. R.; Newcomer, M. E.; Williams, K. H.; Hubbard, S. S.; Enquist, B. J.; Steltzer, H.; Carroll, R. W. H.

2017-12-01

Quantifying Temperature Effects on Snow, Plant and Streamflow Dynamics in Headwater Catchments Snow-dominated headwater catchments are critical for water resource throughout the world; particularly in Western US. Under climate change, temperature increases are expected to be amplified in mountainous regions. We use a data-driven approach to better understand the coupling among inter-annual variability in temperature, snow and plant community dynamics and stream discharge. We apply data mining methods (e.g., principal component analysis, random forest) to historical spatiotemporal datasets, including the SNOTEL data, Landsat-based normalized difference vegetation index (NDVI) and airborne LiDAR-based snow distribution. Although both snow distribution and NDVI are extremely heterogeneous spatially, the inter-annual variability and temporal responses are spatially consistent, providing an opportunity to quantify the effect of temperature in the catchment-scale. We demonstrate our approach in the East River Watershed of the Upper Colorado River Basin, including Rocky Mountain Biological Laboratory, where the changes in plant communities and their dynamics have been extensively documented. Results indicate that temperature - particularly spring temperature - has a significant control not only on the timing of snowmelt, plant NDVI and peak flow but also on the magnitude of peak NDVI, peak flow and annual discharge. Monthly temperature in spring explains the variability of snowmelt by the equivalent standard deviation of 3.4-4.4 days, and total discharge by 10-11%. In addition, the high correlation among June temperature, peak NDVI and annual discharge suggests a primary role of spring evapotranspiration on plant community phenology, productivity, and streamflow volume. On the other hand, summer monsoon precipitation does not contribute significantly to annual discharge, further emphasizing the importance of snowmelt. This approach is mostly based on a set of datasets

Diffusion of volatile organics through porous snow: impact of surface adsorption and grain boundaries

NASA Astrophysics Data System (ADS)

Bartels-Rausch, T.; Wren, S. N.; Schreiber, S.; Riche, F.; Schneebeli, M.; Ammann, M.

2013-03-01

Release of trace gases from surface snow on Earth drives atmospheric chemistry, especially in the polar regions. The gas-phase diffusion of methanol and of acetone through the interstitial air of snow was investigated in a well-controlled laboratory study in the temperature range of 223 to 263 K. The aim of this study was to evaluate how the structure of the snowpack, the interaction of the trace gases with the snow surface, and the grain boundaries influence the diffusion on timescales up to 1 h. The diffusive loss of these two volatile organics into packed snow samples was measured using a chemical ionization mass spectrometer. The structure of the snow was analyzed by means of X-ray computed micro-tomography. The observed diffusion profiles could be well described based on gas-phase diffusion and the known structure of the snow sample at temperatures ≥ 253 K. At colder temperatures surface interactions start to dominate the diffusive transport. Parameterizing these interactions in terms of adsorption to the solid ice surface, i.e. using temperature dependent air-ice partitioning coefficients, better described the observed diffusion profiles than the use of air-liquid partitioning coefficients. No changes in the diffusive fluxes were observed by increasing the number of grain boundaries in the snow sample by a factor of 7, indicating that for these volatile organic trace gases, uptake into grain boundaries does not play a role on the timescale of diffusion through porous surface snow. In conclusion, we have shown that the diffusivity can be predicted when the structure of the snowpack and the partitioning of the trace gas to solid ice is known.

Diffusion of volatile organics through porous snow: impact of surface adsorption and grain boundaries

NASA Astrophysics Data System (ADS)

Bartels-Rausch, T.; Wren, S. N.; Schreiber, S.; Riche, F.; Schneebeli, M.; Ammann, M.

2013-07-01

Release of trace gases from surface snow on earth drives atmospheric chemistry, especially in the polar regions. The gas-phase diffusion of methanol and of acetone through the interstitial air of snow was investigated in a well-controlled laboratory study in the temperature range of 223 to 263 K. The aim of this study was to evaluate how the structure of the snowpack, the interaction of the trace gases with the snow surface, and the grain boundaries influence the diffusion on timescales up to 1 h. The diffusive loss of these two volatile organics into packed snow samples was measured using a chemical ionization mass spectrometer. The structure of the snow was analysed by means of X-ray-computed micro-tomography. The observed diffusion profiles could be well described based on gas-phase diffusion and the known structure of the snow sample at temperatures ≥ 253 K. At colder temperatures, surface interactions start to dominate the diffusive transport. Parameterizing these interactions in terms of adsorption to the solid ice surface, i.e. using temperature-dependent air-ice partitioning coefficients, better described the observed diffusion profiles than the use of air-liquid partitioning coefficients. No changes in the diffusive fluxes were observed by increasing the number of grain boundaries in the snow sample by a factor of 7, indicating that for these volatile organic trace gases, uptake into grain boundaries does not play a role on the timescale of diffusion through porous surface snow. For this, a snow sample with an artificially high amount of ice grains was produced and the grain boundary surface measured using thin sections. In conclusion, we have shown that the diffusivity can be predicted when the structure of the snowpack and the partitioning of the trace gas to solid ice is known.

Recent increase in snow-melt area in the Greenland Ice sheet as an indicator of the effect of reduced surface albedo by snow impurities

NASA Astrophysics Data System (ADS)

Rikiishi, K.

2008-12-01

Recent rapid decline of cryosphere including mountain glaciers, sea ice, and seasonal snow cover tends to be associated with global warming. However, positive feedback is likely to operate between the cryosphere and air temperature, and then it may not be so simple to decide the cause-and-effect relation between them. The theory of heat budget for snow surface tells us that sensible heat transfer from the air to the snow by atmospheric warming by 1°C is about 10 W/m2, which is comparable with heat supply introduced by reduction of the snow surface albedo by only 0.02. Since snow impurities such as black carbon and soil- origin dusts have been accumulated every year on the snow surface in snow-melting season, it is very important to examine whether the snow-melting on the ice sheets, mountain glaciers, and sea ice is caused by global warming or by accumulated snow impurities originated from atmospheric pollutants. In this paper we analyze the dataset of snow-melt area in the Greenland ice sheet for the years 1979 - 2007 (available from the National Snow and Ice Data Center), which is reduced empirically from the satellite micro-wave observations by SMMR and SMM/I. It has been found that, seasonally, the snow-melt area extends most significantly from the second half of June to the first half of July when the sun is highest and sunshine duration is longest, while it doesn't extend any more from the second half of July to the first half of August when the air temperature is highest. This fact may imply that sensible heat required for snow-melting comes from the solar radiation rather than from the atmosphere. As for the interannual variation of snow-melt area, on the other hand, we have found that the growth rate of snow-melt area gradually increases from July, to August, and to the first half of September as the impurities come out to and accumulated at the snow surface. However, the growth rate is almost zero in June and the second half of September when fresh snow

The Breathing Snowpack: Pressure-induced Vapor Flux of Temperate Snow

NASA Astrophysics Data System (ADS)

Drake, S. A.; Selker, J. S.; Higgins, C. W.

2017-12-01

As surface air pressure increases, hydrostatic compression of the air column forces atmospheric air into snowpack pore space. Likewise, as surface air pressure decreases, the atmospheric air column decompresses and saturated air exits the snow. Alternating influx and efflux of air can be thought of as a "breathing" process that produces an upward vapor flux when air above the snow is not saturated. The impact of pressure-induced vapor exchange is assumed to be small and is thus ignored in model parameterizations of surface processes over snow. Rationale for disregarding this process is that large amplitude pressure changes as caused by synoptic weather patterns are too infrequent to credibly impact vapor flux. The amplitude of high frequency pressure changes is assumed to be too small to affect vapor flux, however, the basis for this hypothesis relies on pressure measurements collected over an agricultural field (rather than snow). Resolution of the impact of pressure changes on vapor flux over seasonal cycles depends on an accurate representation of the magnitude of pressure changes caused by changes in wind as a function of the frequency of pressure changes. High precision in situ pressure measurements in a temperature snowpack allowed us to compute the spectra of pressure changes vs. wind forcing. Using a simplified model for vapor exchange we then computed the frequency of pressure changes that maximize vapor exchange. We examine and evaluate the seasonal impact of pressure-induced vapor exchange relative to other snow ablation processes.

Observations of Precipitation Size and Fall Speed Characteristics within Coexisting Rain and Wet Snow

NASA Technical Reports Server (NTRS)

Yuter, Sandra E.; Kingsmill, David E.; Nance, Louisa B.; Loeffler-Mang, Martin

2006-01-01

Ground-based measurements of particle size and fall speed distributions using a Particle Size and Velocity (PARSIVEL) disdrometer are compa red among samples obtained in mixed precipitation (rain and wet snow) and rain in the Oregon Cascade Mountains and in dry snow in the Rock y Mountains of Colorado. Coexisting rain and snow particles are distinguished using a classification method based on their size and fall sp eed properties. The bimodal distribution of the particles' joint fall speed-size characteristics at air temperatures from 0.5 to 0 C suggests that wet-snow particles quickly make a transition to rain once mel ting has progressed sufficiently. As air temperatures increase to 1.5 C, the reduction in the number of very large aggregates with a diame ter > 10 mm coincides with the appearance of rain particles larger than 6 mm. In this setting. very large raindrops appear to be the result of aggregates melting with minimal breakup rather than formation by c oalescence. In contrast to dry snow and rain, the fall speed for wet snow has a much weaker correlation between increasing size and increasing fall speed. Wet snow has a larger standard deviation of fall spee d (120%-230% relative to dry snow) for a given particle size. The ave rage fall speed for observed wet-snow particles with a diameter great er than or equal to 2.4 mm is 2 m/s with a standard deviation of 0.8 m/s. The large standard deviation is likely related to the coexistence of particles of similar physical size with different percentages of melting. These results suggest that different particle sizes are not required for aggregation since wet-snow particles of the same size can have different fall speeds. Given the large standard deviation of fa ll speeds in wet snow, the collision efficiency for wet snow is likely larger than that of dry snow. For particle sizes between 1 and 10 mm in diameter within mixed precipitation, rain constituted I % of the particles by volume within the isothermal layer

Competing roles of air temperature and summer precipitation events on proglacial stream discharges in Chhota Shigri Glacier catchment, Indian Himalaya

NASA Astrophysics Data System (ADS)

AL, R.

2016-12-01

It has been widely recognized that western Himalayan region depends heavily on glacier and snow melt for its water needs. This is true especially for the Chenab sub-basin and more generally for other sub-catchments of the mighty Indus catering to the water demands of millions of stake holders who depend on this water resource. However, there are very few studies available to understand high altitude glaciated catchments, the climatic controls over their flow regimes, and their dependency on glacier mass balances, mainly because of poor access. Hence, the proglacial stream discharges from Chhota Shigri Glacier, a representative glacier of western Himalayan region has been analyzed for understanding the impact of rising air temperatures and highly variable summer precipitation events on discharges that are sourced majorly from snow melt and glacier wastage. This study, for the first time attempts to understand the factors influencing the interannual, subseasonal, and the diurnal variability observed in this representative catchment over four ablation seasons (2010-2013), by monitoring solar radiation, air temperature, summer precipitation, albedo and transient snow cover. The proglacial discharge is governed by air temperatures and albedo-enhancing summer precipitation events, which also enhances transient snow cover. While, the positive mass balance years gave rise to lesser proglacial discharges in comparison to negative mass balance years, lesser winter accumulation was compensated by the lower ablation resulting summer snowfall events in some years. While rising summer air temperatures give rise to glacier wastage, the role of melting transient snow cover on stream discharge is highly significant, especially for positive mass balance years. The pronounced interannual variations and the decreased proglacial discharge in comparison to 1980s suggest that Chhota Shigri Glacier is possibly wasting its way to reach equilibrium to the changed climatic conditions of the

Arctic tundra shrub invasion and soot deposition: Consequences for spring snowmelt and near-surface air temperatures

NASA Astrophysics Data System (ADS)

Strack, John E.; Pielke, Roger A.; Liston, Glen E.

2007-12-01

Invasive shrubs and soot pollution both have the potential to alter the surface energy balance and timing of snow melt in the Arctic. Shrubs reduce the amount of snow lost to sublimation on the tundra during the winter leading to a deeper end-of-winter snowpack. The shrubs also enhance the absorption of energy by the snowpack during the melt season by converting incoming solar radiation to longwave radiation and sensible heat. Soot deposition lowers the albedo of the snow, allowing it to more effectively absorb incoming solar radiation and thus melt faster. This study uses the Colorado State University Regional Atmospheric Modeling System version 4.4 (CSU-RAMS 4.4), equipped with an enhanced snow model, to investigate the effects of shrub encroachment and soot deposition on the atmosphere and snowpack in the Kuparuk Basin of Alaska during the May-June melt period. The results of the simulations suggest that a complete invasion of the tundra by shrubs leads to a 2.2°C warming of 3 m air temperatures and a 108 m increase in boundary layer depth during the melt period. The snow-free date also occurred 11 d earlier despite having a larger initial snowpack. The results also show that a decrease in the snow albedo of 0.1, owing to soot pollution, caused the snow-free date to occur 5 d earlier. The soot pollution caused a 1.0°C warming of 3 m air temperatures and a 25 m average deepening of the boundary layer.

Calculation of new snow densities from sub-daily automated snow measurements

NASA Astrophysics Data System (ADS)

Helfricht, Kay; Hartl, Lea; Koch, Roland; Marty, Christoph; Lehning, Michael; Olefs, Marc

2017-04-01

:10 approximation (i.e. 100 kgm-3), which is mainly based on daily values in the Alps. Variations in new snow density could not be explained in a satisfactory manner using meteorological data measured at the same location. Likewise, some of the tested parametrizations of new snow density, which primarily use air temperature as a proxy, result in median new snow densities close to the ones from automated measurements, but show only a low correlation between calculated and measured new snow densities. The case study on the influence of snow settling on HN resulted on average in an underestimation of HN by 17%, which corresponds to 2-3% of the cumulated HN from the previous 24 hours. Therefore, the mean hourly new snow densities may be overestimated by 14%. The analysis in this study is especially limited with respect to the meteorological influence on the HS measurement using ultra-sonic rangers. Nevertheless, the reasonable mean values encourage calculating new snow densities from standard hydro-meteorological measurements using more precise observation devices such as optical snow depth sensors and more sensitive scales for SWE measurements also on sub-daily time-scales.

Snow and glaciers in the tropics: the importance of snowfall level and snow line altitude in the Peruvian Cordilleras

NASA Astrophysics Data System (ADS)

Schauwecker, Simone; Rohrer, Mario; Huggel, Christian; Salzmann, Nadine; Montoya, Nilton; Endries, Jason; Perry, Baker

2016-04-01

The snow line altitude, defined as the line separating snow from ice or firn surfaces, is among the most important parameters in the glacier mass and energy balance of tropical glaciers, since it determines net shortwave radiation via surface albedo. Therefore, hydroglaciological models require estimations of the melting layer during precipitation events, as well as parameterisations of the transient snow line. Typically, the height of the melting layer is implemented by simple air temperature extrapolation techniques, using data from nearby meteorological stations and constant lapse rates. Nonetheless, in the Peruvian mountain ranges, stations at the height of glacier tongues (>5000 m asl.) are scarce and the extrapolation techniques must use data from distant and much lower elevated stations, which need prior careful validation. Thus, reliable snowfall level and snow line altitude estimates from multiple data sets are necessary. Here, we assemble and analyse data from multiple sources (remote sensing, in-situ station data, reanalysis data) in order to assess their applicability in estimating both, the melting layer and snow line altitude. We especially focus on the potential of radar bright band data from TRMM and CloudSat satellite data for its use as a proxy for the snow/rain transition height. As expected for tropical regions, the seasonal and regional variability in the snow line altitude is comparatively low. During the course of the dry season, Landsat satellite as well as webcam images show that the transient snow line is generally increasing, interrupted by light snowfall or graupel events with low precipitation amounts and fast decay rates. We show limitations and possibilities of different data sources as well as their applicability to validate temperature extrapolation methods. Further on, we analyse the implications of the relatively low variability in seasonal snow line altitude on local glacier mass balance gradients. We show that the snow line

Snow: a reliable indicator for global warming in the future?

NASA Astrophysics Data System (ADS)

Jacobi, H.-W.

2012-03-01

The cryosphere consists of water in the solid form at the Earth's surface and includes, among others, snow, sea ice, glaciers and ice sheets. Since the 1990s the cryosphere and its components have often been considered as indicators of global warming because rising temperatures can enhance the melting of solid water (e.g. Barry et al 1993, Goodison and Walker 1993, Armstrong and Brun 2008). Changes in the cryosphere are often easier to recognize than a global temperature rise of a couple of degrees: many locals and tourists have hands-on experience in changes in the extent of glaciers or the duration of winter snow cover on the Eurasian and North American continents. On a more scientific basis, the last IPCC report left no doubt: the amount of snow and ice on Earth is decreasing (Lemke et al 2007). Available data showed clearly decreasing trends in the sea ice and frozen ground extent of the Northern Hemisphere (NH) and the global glacier mass balance. However, the trend in the snow cover extent (SCE) of the NH was much more ambiguous; a result that has since been confirmed by the online available up-to-date analysis of the SCE performed by the Rutgers University Global Snow Lab (climate.rutgers.edu/snowcover/). The behavior of snow is not the result of a simple cause-and-effect relationship between air temperature and snow. It is instead related to a rather complex interplay between external meteorological parameters and internal processes in the snowpack. While air temperature is of course a crucial parameter for snow and its melting, precipitation and radiation are also important. Further physical properties like snow grain size and the amount of absorbing impurities in the snow determine the fraction of absorbed radiation. While all these parameters affect the energy budget of the snowpack, each of these variables can dominate depending on the season or, more generally, on environmental conditions. As a result, the reduction in SCE in spring and summer in the

Diffusion of nitrogen oxides and oxygenated volatile organic compounds through snow

NASA Astrophysics Data System (ADS)

Bartels-Rausch, T.; Ammann, M.; Schneebeli, M.; Riche, F.; Wren, S. N.

2013-12-01

Release of trace gases from surface snow on Earth drives atmospheric chemistry, especially in the Polar Regions. The exchange of atmospheric trace gases between snow or firn and atmosphere can also determine how these species are incorporated into glacial ice, which serves as archive. At low wind conditions, such fluxes between the porous surface snow and the overlaying atmosphere are driven by diffusion through the interstitial air. Here we present results from two laboratory studies where we looked at how the structure of the snowpack, the interaction of the trace gases with the snow surface, and the grain boundaries influence the diffusion of NO, NO2, HONO, methanol, and acetone on time scales up to 1 h. The diffusion through a snow sample was the direct observable of the experiments. Results for different snow types are presented, the structures of which were analysed by means of X-ray computed micro-tomography. Grain boundary content was quantified in one sample using a stereological method. The observed diffusion profiles were very well reproduced in simulations based on gas-phase diffusion and the known structure of the snow sample at temperatures above 253 K. At colder temperatures surface interactions start to dominate the diffusion. Parameterizing these in terms of adsorption to the solid ice surface gave much better agreement to the observations than the use of air - liquid partitioning coefficients. This is a central result as field and modelling studies have indicated that the partitioning to liquid water might describe the diffusion through snow much better even at cold temperatures. This will be discussed using our recent results from surface sensitive spectroscopy experiments. No changes in the diffusion was observed by increasing the number of grain boundaries in the snow sample by a factor of 7.

A room temperature operating cryogenic cell for in vivo monitoring of dry snow metamorphism by X-ray microtomography

NASA Astrophysics Data System (ADS)

Calonne, N.; Flin, F.; Lesaffre, B.; Dufour, A.; Roulle, J.; Puglièse, P.; Philip, A.; Lahoucine, F.; Rolland du Roscoat, S.; Geindreau, C.

2013-12-01

Three-dimensional (3D) images of snow offer the possibility of studying snow metamorphism at the grain scale by analysing the time evolution of its complex microstructure. Such images are also particularly useful for providing physical effective properties of snow arising in macroscopic models. In the last 15 years, several experiments have been developed in order to get 3D images of snow by X-ray microtomography. Up to now, two different approaches have been used: a static and an in vivo approach. The static method consists in imaging a snow sample whose structural evolution has been stopped by impregnation and/or very cold temperature conditions. The sample is placed in a cryogenic cell that can operate at the ambient temperature of the tomograph room (e.g. Brzoska et al., 1999, Coléou et al., 2001). The in vivo technique uses a non impregnated sample which continues to undergo structural evolutions and is put in a cell that controls the temperature conditions at the boundaries of the sample. This kind of cell requires a cold environnement and the whole tomographic acquisition process takes place in a cold room (e.g. Schneebeli and Sokratov, 2004, Pinzer and Schneebeli, 2009). The 2nd approach has the major advantage to provide the time evolution of the microstructure of a same snow sample but requires a dedicated cold-room tomographic scanner, whereas the static method can be used with any tomographic scanner operating at ambient conditions. We developed a new in vivo cryogenic cell which benefits from the advantages of each of the above methods: it (1) allows to follow the evolution of the same sample with time and (2) is usable with a wide panel of tomographic scanners provided with large cabin sizes, which has many advantages in terms of speed, resolution, and availability of new technologies. The thermal insulation between the snow sample and the outside is ensured by a double wall vacuum system of thermal conductivity of about 0.0015 Wm-1K-1. An air

Air and ground temperatures along elevation and continentality gradients in Southern Norway

NASA Astrophysics Data System (ADS)

Farbrot, Herman; Hipp, Tobias; Etzelmüller, Bernd; Humlum, Ole; Isaksen, Ketil; Strand Ødegârd, Rune

2010-05-01

The modern southern boundary for Scandinavian permafrost is located in the mountains of Southern Norway. Permafrost and seasonal frost are considered key components of the cryosphere, and the climate-permafrost relation has acquired added importance with the increasing awareness and concern of rising air temperatures. The three-year research project CRYOLINK ("Permafrost and seasonal frost in southern Norway") aims at improving knowledge on past and present ground temperatures, seasonal frost, and distribution of mountain permafrost in Southern Norway by addressing the fundamental problem of heat transfer between the atmosphere and the ground surface. Hence, several shallow boreholes have been drilled, and a monitoring program to measure air and ground temperatures was started August 2008. The borehole areas (Juvvass, Jetta and Tron) are situated along a west-east transect and, hence, a continentality gradient, and each area provides boreholes at different elevations. Here we present the first year of air and ground temperatures from these sites and discuss the influence of air temperature and ground surface charcteristics (snow conditions, sediments/bedrock, vegetation) on ground temperatures.

Field observations of the electrostatic charges of blowing snow in Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Omiya, S.; Sato, A.

2011-12-01

An electrostatic charge of blowing snow may be a contributing factor in the formation of a snow drift and a snow cornice, and changing of the trajectory of own motion. However, detailed electrification characteristics of blowing snow are not known as there are few reports of charge measurements. We carried out field observations of the electrostatic charges of blowing snow in Tobetsu, Hokkaido, Japan in the mid winter of 2011. An anemovane and a thermohygrometer were used for the meteorological observation. Charge-to-mass ratios of blowing snow were obtained by a Faraday-cage, an electrometer and an electric balance. In this observation period, the air temperature during the blowing snow event was -6.5 to -0.5 degree Celsius. The measured charges in this observation were consistent with the previous studies in sign, which is negative, but they were smaller than the previous one. In most cases, the measured values increased with the temperature decrease, which corresponds with previous studies. However, some results contradicted the tendency, and the maximum value was obtained on the day of the highest air temperature of -0.5 degree Celsius. This discrepancy may be explained from the difference of the snow surface condition on observation day. The day when the maximum value was obtained, the snow surface was covered with old snow, and hard. On the other hand, in many other cases, the snow surface was covered with the fresh snow, and soft. Blowing snow particles on the hard surface can travel longer distance than on the soft one. Therefore, it can be surmised that the hard surface makes the blowing snow particles accumulate a lot of negative charges due to a large number of collisions to the surface. This can be supported by the results of the wind tunnel experiments by Omiya and Sato (2011). By this field observation, it was newly suggested that the electrostatic charge of blowing snow are influenced greatly by the difference of the snow surface condition. REFERENCE

Blowing Snow Sublimation at a High Altitude Alpine Site and Effects on the Surface Boundary Layer

NASA Astrophysics Data System (ADS)

Vionnet, V.; Guyomarc'h, G.; Sicart, J. E.; Deliot, Y.; Naaim-Bouvet, F.; Bellot, H.; Merzisen, H.

2017-12-01

In alpine terrain, wind-induced snow transport strongly influences the spatial and temporal variability of the snow cover. During their transport, blown snow particles undergo sublimation with an intensity depending on atmospheric conditions (air temperature and humidity). The mass loss due to blowing snow sublimation is a source of uncertainty for the mass balance of the alpine snowpack. Additionally, blowing snow sublimation modifies humidity and temperature in the surface boundary layer. To better quantify these effects in alpine terrain, a dedicated measurement setup has been deployed at the experimental site of Col du Lac Blanc (2720 m a.s.l., French Alps, Cryobs-Clim network) since winter 2015/2016. It consists in three vertical masts measuring the near-surface vertical profiles (0.2-5 m) of wind speed, air temperature and humidity and blowing snow fluxes and size distribution. Observations collected during blowing snow events without concurrent snowfall show only a slight increase in relative humidity (10-20%) and near-surface saturation is never observed. Estimation of blowing snow sublimation rates are then obtained from these measurements. They range between 0 and 5 mmSWE day-1 for blowing snow events without snowfall in agreement with previous studies in different environments (North American prairies, Antarctica). Finally, an estimation of the mass loss due to blowing snow sublimation at our experimental site is proposed for two consecutive winters. Future use of the database collected in this study includes the evaluation of blowing snow models in alpine terrain.

Global Snow-Cover Evolution from Twenty Years of Satellite Passive Microwave Data

USGS Publications Warehouse

Mognard, N.M.; Kouraev, A.V.; Josberger, E.G.

2003-01-01

Starting in 1979 with the SMMR (Scanning Multichannel Microwave Radiometer) instrument onboard the satellite NIMBUS-7 and continuing since 1987 with the SSMI (Special Sensor Microwave Imager) instrument on board the DMSP (Defence Meteorological Satellite Program) series, more then twenty years of satellite passive microwave data are now available. This dataset has been processed to analyse the evolution of the global snow cover. This work is part of the AICSEX project from the 5th Framework Programme of the European Community. The spatio-temporal evolution of the satellite-derived yearly snow maximum extent and the timing of the spring snow melt were estimated and analysed over the Northern Hemisphere. Significant differences between the evolution of the yearly maximum snow extent in Eurasia and in North America were found. A positive correlation between the maximum yearly snow cover extent and the ENSO index was obtained. High interannual spatio-temporal variability characterises the timing of snow melt in the spring. Twenty-year trends in the timing of spring snow melt have been computed and compared with spring air temperature trends for the same period and the same area. In most parts of Eurasia and in the central and western parts of North America the tendency has been for earlier snow melt. In northeastern Canada, a large area of positive trends, where snow melt timing starts later than in the early 1980s, corresponds to a region of positive trends of spring air temperature observed over the same period.

Measurement of the spectral absorption of liquid water in melting snow with an imaging spectrometer

NASA Technical Reports Server (NTRS)

Green, Robert O.; Dozier, Jeff

1995-01-01

Melting of the snowpack is a critical parameter that drives aspects of the hydrology in regions of the earth where snow accumulates seasonally. New techniques for measurement of snow melt over regional scales offer the potential to improve monitoring and modeling of snow-driven hydrological processes. We present the results of measuring the spectral absorption of liquid water in a melting snowpack with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS data were acquired over Mammoth Mountain, in east central California on 21 May 1994 at 18:35 UTC. The air temperature at 2926 m on Mammoth Mountain at site A was measured at 15-minute intervals during the day preceding the AVIRIS data acquisition. At this elevation, the air temperature did not drop below freezing the night of May 20 and had risen to 6 degrees Celsius by the time of the overflight on May 21. These temperature conditions support the presence of melting snow at the surface as the AVIRIS data were acquired.

Incorporating Cold-Air Pooling into Downscaled Climate Models Increases Potential Refugia for Snow-Dependent Species within the Sierra Nevada Ecoregion, CA

PubMed Central

Curtis, Jennifer A.; Flint, Lorraine E.; Flint, Alan L.; Lundquist, Jessica D.; Hudgens, Brian; Boydston, Erin E.; Young, Julie K.

2014-01-01

We present a unique water-balance approach for modeling snowpack under historic, current and future climates throughout the Sierra Nevada Ecoregion. Our methodology uses a finer scale (270 m) than previous regional studies and incorporates cold-air pooling, an atmospheric process that sustains cooler temperatures in topographic depressions thereby mitigating snowmelt. Our results are intended to support management and conservation of snow-dependent species, which requires characterization of suitable habitat under current and future climates. We use the wolverine (Gulo gulo) as an example species and investigate potential habitat based on the depth and extent of spring snowpack within four National Park units with proposed wolverine reintroduction programs. Our estimates of change in spring snowpack conditions under current and future climates are consistent with recent studies that generally predict declining snowpack. However, model development at a finer scale and incorporation of cold-air pooling increased the persistence of April 1st snowpack. More specifically, incorporation of cold-air pooling into future climate projections increased April 1st snowpack by 6.5% when spatially averaged over the study region and the trajectory of declining April 1st snowpack reverses at mid-elevations where snow pack losses are mitigated by topographic shading and cold-air pooling. Under future climates with sustained or increased precipitation, our results indicate a high likelihood for the persistence of late spring snowpack at elevations above approximately 2,800 m and identify potential climate refugia sites for snow-dependent species at mid-elevations, where significant topographic shading and cold-air pooling potential exist. PMID:25188379

Incorporating cold-air pooling into downscaled climate models increases potential refugia for snow-dependent species within the Sierra Nevada Ecoregion, CA

USGS Publications Warehouse

Curtis, Jennifer A.; Flint, Lorraine E.; Flint, Alan L.; Lundquist, Jessica D.; Hudgens, Brian; Boydston, Erin E.; Young, Julie K.

2014-01-01

We present a unique water-balance approach for modeling snowpack under historic, current and future climates throughout the Sierra Nevada Ecoregion. Our methodology uses a finer scale (270 m) than previous regional studies and incorporates cold-air pooling, an atmospheric process that sustains cooler temperatures in topographic depressions thereby mitigating snowmelt. Our results are intended to support management and conservation of snow-dependent species, which requires characterization of suitable habitat under current and future climates. We use the wolverine (Gulo gulo) as an example species and investigate potential habitat based on the depth and extent of spring snowpack within four National Park units with proposed wolverine reintroduction programs. Our estimates of change in spring snowpack conditions under current and future climates are consistent with recent studies that generally predict declining snowpack. However, model development at a finer scale and incorporation of cold-air pooling increased the persistence of April 1st snowpack. More specifically, incorporation of cold-air pooling into future climate projections increased April 1st snowpack by 6.5% when spatially averaged over the study region and the trajectory of declining April 1st snowpack reverses at mid-elevations where snow pack losses are mitigated by topographic shading and cold-air pooling. Under future climates with sustained or increased precipitation, our results indicate a high likelihood for the persistence of late spring snowpack at elevations above approximately 2,800 m and identify potential climate refugia sites for snow-dependent species at mid-elevations, where significant topographic shading and cold-air pooling potential exist.

Research on Using the Naturally Cold Air and the Snow for Data Center Air-conditioning, and Humidity Control

NASA Astrophysics Data System (ADS)

Tsuda, Kunikazu; Tano, Shunichi; Ichino, Junko

To lower power consumption has becomes a worldwide concern. It is also becoming a bigger area in Computer Systems, such as reflected by the growing use of software-as-a-service and cloud computing whose market has increased since 2000, at the same time, the number of data centers that accumulates and manages the computer has increased rapidly. Power consumption at data centers is accounts for a big share of the entire IT power usage, and is still rapidly increasing. This research focuses on the air-conditioning that occupies accounts for the biggest portion of electric power consumption by data centers, and proposes to develop a technique to lower the power consumption by applying the natural cool air and the snow for control temperature and humidity. We verify those effectiveness of this approach by the experiment. Furthermore, we also examine the extent to which energy reduction is possible when a data center is located in Hokkaido.

Air and Ground Surface Temperature Relations in a Mountainous Basin, Wolf Creek, Yukon Territory

NASA Astrophysics Data System (ADS)

Roadhouse, Emily A.

The links between climate and permafrost are well known, but the precise nature of the relationship between air and ground temperatures remains poorly understood, particularly in complex mountain environments. Although previous studies indicate that elevation and potential incoming solar radiation (PISR) are the two leading factors contributing to the existence of permafrost at a given location, additional factors may also contribute significantly to the existence of mountain permafrost, including vegetation cover, snow accumulation and the degree to which individual mountain landscapes are prone to air temperature inversions. Current mountain permafrost models consider only elevation and aspect, and have not been able to deal with inversion effects in a systematic fashion. This thesis explores the relationship between air and ground surface temperatures and the presence of surface-based inversions at 27 sites within the Wolf Creek basin and surrounding area between 2001 and 2006, as a first step in developing an improved permafrost distribution TTOP model. The TTOP model describes the relationship between the mean annual air temperature and the temperature at the top of permafrost in terms of the surface and thermal offsets (Smith and Riseborough, 2002). Key components of this model are n-factors which relate air and ground climate by establishing the ratio between air and surface freezing (winter) and thawing (summer) degree-days, thus summarizing the surface energy balance on a seasonal basis. Here we examine (1) surface offsets and (2) freezing and thawing n-factor variability at a number of sites through altitudinal treeline in the southern Yukon. Thawing n-factors (nt) measured at individual sites remained relatively constant from one year to the next and may be related to land cover. During the winter, the insulating effect of a thick snow cover results in higher surface temperatures, while thin snow cover results in low surface temperatures more closely

Siberia snow depth climatology derived from SSM/I data using a combined dynamic and static algorithm

USGS Publications Warehouse

Grippa, M.; Mognard, N.; Le, Toan T.; Josberger, E.G.

2004-01-01

One of the major challenges in determining snow depth (SD) from passive microwave measurements is to take into account the spatiotemporal variations of the snow grain size. Static algorithms based on a constant snow grain size cannot provide accurate estimates of snow pack thickness, particularly over large regions where the snow pack is subjected to big spatial temperature variations. A recent dynamic algorithm that accounts for the dependence of the microwave scattering on the snow grain size has been developed to estimate snow depth from the Special Sensor Microwave/Imager (SSM/I) over the Northern Great Plains (NGP) in the US. In this paper, we develop a combined dynamic and static algorithm to estimate snow depth from 13 years of SSM/I observations over Central Siberia. This region is characterised by extremely cold surface air temperatures and by the presence of permafrost that significantly affects the ground temperature. The dynamic algorithm is implemented to take into account these effects and it yields accurate snow depths early in the winter, when thin snowpacks combine with cold air temperatures to generate rapid crystal growth. However, it is not applicable later in the winter when the grain size growth slows. Combining the dynamic algorithm to a static algorithm, with a temporally constant but spatially varying coefficient, we obtain reasonable snow depth estimates throughout the entire snow season. Validation is carried out by comparing the satellite snow depth monthly averages to monthly climatological data. We show that the location of the snow depth maxima and minima is improved when applying the combined algorithm, since its dynamic portion explicitly incorporate the thermal gradient through the snowpack. The results obtained are presented and evaluated for five different vegetation zones of Central Siberia. Comparison with in situ measurements is also shown and discussed. ?? 2004 Elsevier Inc. All rights reserved.

Work of Breathing into Snow in the Presence versus Absence of an Artificial Air Pocket Affects Hypoxia and Hypercapnia of a Victim Covered with Avalanche Snow: A Randomized Double Blind Crossover Study.

PubMed

Roubík, Karel; Sieger, Ladislav; Sykora, Karel

2015-01-01

Presence of an air pocket and its size play an important role in survival of victims buried in the avalanche snow. Even small air pockets facilitate breathing. We hypothesize that the size of the air pocket significantly affects the airflow resistance and work of breathing. The aims of the study are (1) to investigate the effect of the presence of an air pocket on gas exchange and work of breathing in subjects breathing into the simulated avalanche snow and (2) to test whether it is possible to breathe with no air pocket. The prospective interventional double-blinded study involved 12 male volunteers, from which 10 completed the whole protocol. Each volunteer underwent two phases of the experiment in a random order: phase "AP"--breathing into the snow with a one-liter air pocket, and phase "NP"--breathing into the snow with no air pocket. Physiological parameters, fractions of oxygen and carbon dioxide in the airways and work of breathing expressed as pressure-time product were recorded continuously. The main finding of the study is that it is possible to breath in the avalanche snow even with no air pocket (0 L volume), but breathing under this condition is associated with significantly increased work of breathing. The significant differences were initially observed for end-tidal values of the respiratory gases (EtO2 and EtCO2) and peripheral oxygen saturation (SpO2) between AP and NP phases, whereas significant differences in inspiratory fractions occurred much later (for FIO2) or never (for FICO2). The limiting factor in no air pocket conditions is excessive increase in work of breathing that induces increase in metabolism accompanied by higher oxygen consumption and carbon dioxide production. The presence of even a small air pocket reduces significantly the work of breathing.

The Kühtai data set: 25 years of lysimetric, snow pillow, and meteorological measurements

PubMed Central

Kirnbauer, R.; Parajka, J.; Schöber, J.; Blöschl, G.

2017-01-01

Abstract Snow measurements at the Kühtai station in Tirol, Austria, (1920 m.a.s.l.) are described. The data set includes snow water equivalent from a 10 m2 snow pillow, snow melt outflow from a 10 m2 snow lysimeter placed at the same location as the pillow, meteorological data (precipitation, incoming shortwave radiation, reflected shortwave radiation, air temperature, relative air humidity, and wind speed), and other data (snow depths, snow temperatures at seven heights) from the period October 1990 to May 2015. All data have been quality checked, and gaps in the meteorological data have been filled in. The data set is unique in that all data are available at a temporal resolution of 15 min over a period of 25 years with minimal changes in the experimental setup. The data set can therefore be used to analyze snow pack processes over a long‐time period, including their extremes and long‐term changes, in an Alpine climate. Analyses may benefit from the combined measurement of snow water equivalent, lysimeter outflow, and precipitation at a wind‐sheltered alpine site. An example use of data shows the temporal variability of daily and 1 April snow water equivalent observed at the Kühtai site. The results indicate that the snow water equivalent maximum varies between 200 and more than 500 mm w.e., but there is no statistically significant temporal trend in the period 1990–2015. PMID:28931957

Are We Biologically Safe with Snow Precipitation? A Case Study in Beijing

PubMed Central

Shen, Fangxia; Yao, Maosheng

2013-01-01

In this study, the bacterial and fungal abundances, diversities, conductance levels as well as total organic carbon (TOC) were investigated in the snow samples collected from five different snow occurrences in Beijing between January and March, 2010. The collected snow samples were melted and cultured at three different temperatures (4, 26 and 37°C). The culturable bacterial concentrations were manually counted and the resulting colony forming units (CFUs) at 26°C were further studied using V3 region of 16 S rRNA gene-targeted polymerase chain reaction -denaturing gradient gel electrophoresis (PCR-DGGE). The clone library was constructed after the liquid culturing of snow samples at 26°C. And microscopic method was employed to investigate the fungal diversity in the samples. In addition, outdoor air samples were also collected using mixed cellulose ester (MCE) filters and compared with snow samples with respect to described characteristics. The results revealed that snow samples had bacterial concentrations as much as 16000 CFU/ml for those cultured at 26°C, and the conductance levels ranged from 5.6×10−6 to 2.4×10−5 S. PCR-DGGE, sequencing and microscopic analysis revealed remarkable bacterial and fungal diversity differences between the snow samples and the outdoor air samples. In addition, DGGE banding profiles for the snow samples collected were also shown distinctly different from one another. Absent from the outdoor air, certain human, plant, and insect fungal pathogens were found in the snow samples. By calculation, culturable bacteria accounted for an average of 3.38% (±1.96%) of TOC for the snow samples, and 0.01% for that of outdoor air samples. The results here suggest that snow precipitations are important sources of fungal pathogens and ice nucleators, thus could affect local climate, human health and agriculture security. PMID:23762327

Are we biologically safe with snow precipitation? A case study in beijing.

PubMed

Shen, Fangxia; Yao, Maosheng

2013-01-01

In this study, the bacterial and fungal abundances, diversities, conductance levels as well as total organic carbon (TOC) were investigated in the snow samples collected from five different snow occurrences in Beijing between January and March, 2010. The collected snow samples were melted and cultured at three different temperatures (4, 26 and 37°C). The culturable bacterial concentrations were manually counted and the resulting colony forming units (CFUs) at 26°C were further studied using V3 region of 16 S rRNA gene-targeted polymerase chain reaction -denaturing gradient gel electrophoresis (PCR-DGGE). The clone library was constructed after the liquid culturing of snow samples at 26°C. And microscopic method was employed to investigate the fungal diversity in the samples. In addition, outdoor air samples were also collected using mixed cellulose ester (MCE) filters and compared with snow samples with respect to described characteristics. The results revealed that snow samples had bacterial concentrations as much as 16000 CFU/ml for those cultured at 26°C, and the conductance levels ranged from 5.6×10(-6) to 2.4×10(-5) S. PCR-DGGE, sequencing and microscopic analysis revealed remarkable bacterial and fungal diversity differences between the snow samples and the outdoor air samples. In addition, DGGE banding profiles for the snow samples collected were also shown distinctly different from one another. Absent from the outdoor air, certain human, plant, and insect fungal pathogens were found in the snow samples. By calculation, culturable bacteria accounted for an average of 3.38% (±1.96%) of TOC for the snow samples, and 0.01% for that of outdoor air samples. The results here suggest that snow precipitations are important sources of fungal pathogens and ice nucleators, thus could affect local climate, human health and agriculture security.

Time-Lapse Micro-Tomography Measurements and Determination of Effective Transport Properties of Snow Metamorphism Under Advective Conditions

NASA Astrophysics Data System (ADS)

Ebner, P. P.; Grimm, S.; Steen-Larsen, H. C.; Schneebeli, M.; Steinfeld, A.

2014-12-01

The metamorphism of snow under advective air flow, with and without temperature gradient, was never experimentally investigated. We developed a new sample holder where metamorphism under advective conditions can be observed and measured using time-lapse micro-tomography [1]. Long-term experiments were performed and direct pore-level simulation (DPLS) [2,3] was directly applied on the extracted 3D digital geometry of the snow to calculate the effective transport properties by solving the governing fluid flow equations. The results showed no effect of isothermal advection, compared to rates typical for isothermal metamorphism. Appling a temperature gradient, the results showed increased snow metamorphism compared to rates typical for temperature gradient metamorphism. However, for both cases a change in the isotopic composition in the air as well as in the snow sample could be observed. These measurements could be influential to better understand snow-air exchange processes relevant for atmospheric chemistry and isotopic composition. REFERENCES[1] Ebner P. P., Grimm S., Schneebeli M., and Steinfeld A.: An instrumented sample holder for time-lapse micro-tomography measurements of snow under advective airflow. Geoscientific Instrumentation, Methods and Data Systems 4(2014), 353-373. [2] Zermatten E., Haussener S., Schneebeli M., and Steinfeld A.: Tomography-based determination of permeability and Dupuit-Forchheimer coefficient of characteristic snow samples. Journal of Glaciology 57(2011), 811-816. [3] Zermatten E., Schneebeli M., Arakawa H., and Steinfeld A.: Tomography-based determination of porosity, specific area and permeability of snow and comparison with measurements. Cold Regions Science and Technology 97 (2014), 33-40. Fig. 1: 3-D surface rendering of a refrozen wet snow sample with fluid flow streamline.

Wind slab formation in snow: experimental setup and first results

NASA Astrophysics Data System (ADS)

Sommer, Christian; Lehning, Michael; Fierz, Charles

2016-04-01

The formation of wind-hardened surface layers, also known as wind slabs or wind crusts, is studied. Better knowledge about which processes and parameters are important will lead to an improved understanding of the mass balances in polar and alpine areas. It will also improve snow-cover models (i.e. SNOWPACK) as well as the forecast of avalanche danger. A ring-shaped wind tunnel has been built and instrumented. The facility is ring-shaped to simulate an infinitely long snow surface (infinite fetch). A SnowMicroPen (SMP) is used to measure the snow hardness. Other sensors measure environmental conditions such as wind velocity, air temperature, air humidity, the temperature of the snow and of the snow surface. A camera is used to detect drifting particles and to measure the Specific Surface Area (SSA) at the snow surface via near-infrared photography. First experiments indicate that mechanical fragmentation followed by sintering is the most efficient process to harden the surface. The hardness increased rapidly during drifting snow events, but only slowly or not at all when the wind speed was kept below the threshold for drifting snow. With drifting, the penetration resistance increased from the original 0.07 N to around 0.3 N in about an hour. Without drifting, a slow, further increase in resistance was observed. In about six hours, the hardness of the top 1-2 cm increased to 0.5 N. During this eight-hour experiment consisting of about two hours with intermittent drifting and six hours without drifting, the density at the surface increased from 66 kg/m3 to around 170 kg/m3. In the unaffected region close to the ground, the density increased from 100 kg/m3 to 110 kg/m3.

Snow multivariable data assimilation for hydrological predictions in mountain areas

NASA Astrophysics Data System (ADS)

Piazzi, Gaia; Campo, Lorenzo; Gabellani, Simone; Rudari, Roberto; Castelli, Fabio; Cremonese, Edoardo; Morra di Cella, Umberto; Stevenin, Hervé; Ratto, Sara Maria

2016-04-01

The seasonal presence of snow on alpine catchments strongly impacts both surface energy balance and water resource. Thus, the knowledge of the snowpack dynamics is of critical importance for several applications, such as water resource management, floods prediction and hydroelectric power production. Several independent data sources provide information about snowpack state: ground-based measurements, satellite data and physical models. Although all these data types are reliable, each of them is affected by specific flaws and errors (respectively dependency on local conditions, sensor biases and limitations, initialization and poor quality forcing data). Moreover, there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine observational and modeled information to obtain the most likely estimate of snowpack state. Indeed, by combining all the available sources of information, the implementation of DA schemes can quantify and reduce the uncertainties of the estimations. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model, strengthened by a robust multivariable data assimilation algorithm. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity, relative air humidity, precipitation and incident solar radiation) to provide a complete estimate of snowpack state. The implementation of an Ensemble Kalman Filter (EnKF) scheme enables to assimilate simultaneously ground

Validation of snow characteristics and snow albedo feedback in the Canadian Regional Climate Model simulations over North America

NASA Astrophysics Data System (ADS)

Fang, B.; Sushama, L.; Diro, G. T.

2015-12-01

Snow characteristics and snow albedo feedback (SAF) over North America, as simulated by the fifth-generation Canadian Regional Climate Model (CRCM5), when driven by ERA-40/ERA-Interim, CanESM2 and MPI-ESM-LR at the lateral boundaries, are analyzed in this study. Validation of snow characteristics is performed by comparing simulations against available observations from MODIS, ISCCP and CMC. Results show that the model is able to represent the main spatial distribution of snow characteristics with some overestimation in snow mass and snow depth over the Canadian high Arctic. Some overestimation in surface albedo is also noted for the boreal region which is believed to be related to the snow unloading parameterization, as well as the overestimation of snow albedo. SAF is assessed both in seasonal and climate change contexts when possible. The strength of SAF is quantified as the amount of additional net shortwave radiation at the top of the atmosphere as surface albedo decreases in association with a 1°C increase in surface temperature. Following Qu and Hall (2007), this is expressed as the product of the variation in planetary albedo with surface albedo and the change in surface albedo for 1°C change in surface air temperature during the season, which in turn is determined by the strength of the snow cover and snowpack metamorphosis feedback loops. Analysis of the latter term in the seasonal cycle suggests that for CRCM5 simulations, the snow cover feedback loop is more dominant compared to the snowpack metamorphosis feedback loop, whereas for MODIS, the two feedback loops have more or less similar strength. Moreover, the SAF strength in the climate change context appears to be weaker than in the seasonal cycle and is sensitive to the driving GCM and the RCP scenario.

The influence of air temperature inversions on snowmelt and glacier mass-balance simulations, Ammassalik island, SE Greenland

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mernild, Sebastian Haugard; Liston, Glen

2009-01-01

In many applications, a realistic description of air temperature inversions is essential for accurate snow and glacier ice melt, and glacier mass-balance simulations. A physically based snow-evolution modeling system (SnowModel) was used to simulate eight years (1998/99 to 2005/06) of snow accumulation and snow and glacier ice ablation from numerous small coastal marginal glaciers on the SW-part of Ammassalik Island in SE Greenland. These glaciers are regularly influenced by inversions and sea breezes associated with the adjacent relatively low temperature and frequently ice-choked fjords and ocean. To account for the influence of these inversions on the spatiotemporal variation of airmore » temperature and snow and glacier melt rates, temperature inversion routines were added to MircoMet, the meteorological distribution sub-model used in SnowModel. The inversions were observed and modeled to occur during 84% of the simulation period. Modeled inversions were defined not to occur during days with strong winds and high precipitation rates due to the potential of inversion break-up. Field observations showed inversions to extend from sea level to approximately 300 m a.s.l., and this inversion level was prescribed in the model simulations. Simulations with and without the inversion routines were compared. The inversion model produced air temperature distributions with warmer lower elevation areas and cooler higher elevation areas than without inversion routines due to the use of cold sea-breeze base temperature data from underneath the inversion. This yielded an up to 2 weeks earlier snowmelt in the lower areas and up to 1 to 3 weeks later snowmelt in the higher elevation areas of the simulation domain. Averaged mean annual modeled surface mass-balance for all glaciers (mainly located above the inversion layer) was -720 {+-} 620 mm w.eq. y{sup -1} for inversion simulations, and -880 {+-} 620 mm w.eq. y{sup -1} without the inversion routines, a difference of 160 mm w

Estimate of temperature change due to ice and snow accretion in the boreal forest regions

NASA Astrophysics Data System (ADS)

Sugiura, K.; Nagai, S.; Suzuki, R.; Eicken, H.; Maximov, T. C.

2016-12-01

Previous research has demonstrated that there is a wide difference between the surface albedo in winter/spring in snow-covered forest regions in various global climate models. If the forest is covered with snow, the surface albedo would increase. In this study, we carried out field observations to monitor the frequency of ice and snow accretion in the boreal forest regions. The time-lapse digital camera was set up on each side of the observation towers at the site located to the north of Fairbanks (USA) and at the site located to the north of Yakutsk (Russia). It was confirmed that both forests were not necessarily covered with snow without a break from the start of continuous snow cover until the end. In addition, the boreal forest at the Yakutsk site is covered with snow in comparison with the boreal forest at the Fairbanks site for a long term such as for about five month. Using a one-dimensional mathematics model about the energy flow including atmospheric multiple scattering, we estimated temperature change due to ice and snow accretion in the boreal forest regions. The result show that the mean surface temperature rises approximately 0.5 [oC] when the boreal forest is not covered with snow. In this presentation, we discuss the snow albedo parameterization in the boreal forest regions and the one-dimensional mathematics model to provide a basis for a better understanding of the role of snow in the climate system.

Meteorological and snow distribution data in the Izas Experimental Catchment (Spanish Pyrenees) from 2011 to 2017

NASA Astrophysics Data System (ADS)

Revuelto, Jesús; Azorin-Molina, Cesar; Alonso-González, Esteban; Sanmiguel-Vallelado, Alba; Navarro-Serrano, Francisco; Rico, Ibai; López-Moreno, Juan Ignacio

2017-12-01

This work describes the snow and meteorological data set available for the Izas Experimental Catchment in the Central Spanish Pyrenees, from the 2011 to 2017 snow seasons. The experimental site is located on the southern side of the Pyrenees between 2000 and 2300 m above sea level, covering an area of 55 ha. The site is a good example of a subalpine environment in which the evolution of snow accumulation and melt are of major importance in many mountain processes. The climatic data set consists of (i) continuous meteorological variables acquired from an automatic weather station (AWS), (ii) detailed information on snow depth distribution collected with a terrestrial laser scanner (TLS, lidar technology) for certain dates across the snow season (between three and six TLS surveys per snow season) and (iii) time-lapse images showing the evolution of the snow-covered area (SCA). The meteorological variables acquired at the AWS are precipitation, air temperature, incoming and reflected solar radiation, infrared surface temperature, relative humidity, wind speed and direction, atmospheric air pressure, surface temperature (snow or soil surface), and soil temperature; all were taken at 10 min intervals. Snow depth distribution was measured during 23 field campaigns using a TLS, and daily information on the SCA was also retrieved from time-lapse photography. The data set (https://doi.org/10.5281/zenodo.848277) is valuable since it provides high-spatial-resolution information on the snow depth and snow cover, which is particularly useful when combined with meteorological variables to simulate snow energy and mass balance. This information has already been analyzed in various scientific studies on snow pack dynamics and its interaction with the local climatology or topographical characteristics. However, the database generated has great potential for understanding other environmental processes from a

The Effect of Climate Change on Snow Pack at Sleepers River, Vermont, USA

NASA Astrophysics Data System (ADS)

Shanley, J. B.; Chalmers, A.; Denner, J.; Clark, S.

2017-12-01

Sleepers River Research Watershed, a U.S. Geological Survey Water, Energy, and Biogeochemical Budgets (WEBB) site in northeastern Vermont, has a 58-year record (since 1959) of snow depth and snow water equivalence (SWE), one of the longest continuous records in eastern North America. Snow measurements occur weekly during the winter at the watershed using an Adirondack type snow tube sampler. Sleepers River averages about 1100 mm of precipitation annually of which 20 to 30 percent falls as snow. Snow cover typically persists from December to April. Length of snow cover and snow depth vary with elevation, aspect, and cover type. Sites include open field, and hardwood and conifer stand clearings from 225 to 630 meters elevation. We evaluated changes in snow depth, snow cover duration, and SWE relative to elevation, soil frost depth, air temperature, total precipitation, and the El Niño - Southern Oscillation (ENSO) cycle. Overall, warmer winter temperatures have resulted in more midwinter thaws, more rain during the winter, and more variable soil frost depth. Trends in snowpack amount and duration were compared to winter-spring streamflow center-of-mass to evaluate if shifts in the snow pack regime were leading to earlier snowmelt.

Measurement of the Spectral Absorption of Liquid Water in Melting Snow With an Imaging Spectrometer

NASA Technical Reports Server (NTRS)

Green, Robert O.; Dozier, Jeff

1995-01-01

Melting of the snowpack is a critical parameter that drives aspects of the hydrology in regions of the Earth where snow accumulates seasonally. New techniques for measurement of snow melt over regional scales offer the potential to improve monitoring and modeling of snow-driven hydrological processes. In this paper we present the results of measuring the spectral absorption of liquid water in a melting snowpack with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS data were acquired over Mammoth Mountain, in east central California on 21 May 1994 at 18:35 UTC. The air temperature at 2926 m on Mammoth Mountain at site A was measured at 15-minute intervals during the day preceding the AVIRIS data acquisition. At this elevation. the air temperature did not drop below freezing the night of the May 20 and had risen to 6 degrees Celsius by the time of the overflight on May 21. These temperature conditions support the presence of melting snow at the surface as the AVIRIS data were acquired.

Effects of multilayer snow scheme on the simulation of snow: Offline Noah and coupled with NCEP CFSv2

NASA Astrophysics Data System (ADS)

Saha, Subodh Kumar; Sujith, K.; Pokhrel, Samir; Chaudhari, Hemantkumar S.; Hazra, Anupam

2017-03-01

The Noah version 2.7.1 is a moderately complex land surface model (LSM), with a single layer snowpack, combined with vegetation and underlying soil layer. Many previous studies have pointed out biases in the simulation of snow, which may hinder the skill of a forecasting system coupled with the Noah. In order to improve the simulation of snow by the Noah, a multilayer snow scheme (up to a maximum of six layers) is introduced. As Noah is the land surface component of the Climate Forecast System version 2 (CFSv2) of the National Centers for Environmental Prediction (NCEP), the modified Noah is also coupled with the CFSv2. The offline LSM shows large improvements in the simulation of snow depth, snow water equivalent (SWE), and snow cover area during snow season (October to June). CFSv2 with the modified Noah reveals a dramatic improvements in the simulation of snow depth and 2 m air temperature and moderate improvements in SWE. As suggested in the previous diagnostic and sensitivity study, improvements in the simulation of snow by CFSv2 have lead to the reduction in dry bias over the Indian subcontinent (by a maximum of 2 mm d-1). The multilayer snow scheme shows promising results in the simulation of snow as well as Indian summer monsoon rainfall and hence this development may be the part of the future version of the CFS.

CREST-SAFE: Snow LST validation, wetness profiler creation, and depth/SWE product development

NASA Astrophysics Data System (ADS)

Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Khanbilvardi, R.; Munoz Barreto, J.; Yu, Y.

2017-12-01

CREST-SAFE: Snow LST validation, wetness profiler creation, and depth/SWE product development The Field Snow Research Station (also referred to as Snow Analysis and Field Experiment, SAFE) is operated by the NOAA Center for Earth System Sciences and Remote Sensing Technologies (CREST) in the City University of New York (CUNY). The field station is located within the premises of the Caribou Municipal Airport (46°52'59'' N, 68°01'07'' W) and in close proximity to the National Weather Service (NWS) Regional Forecast Office. The station was established in 2010 to support studies in snow physics and snow remote sensing. The Visible Infrared Imager Radiometer Suite (VIIRS) Land Surface Temperature (LST) Environmental Data Record (EDR) and Moderate Resolution Imaging Spectroradiometer (MODIS) LST product (provided by the Terra and Aqua Earth Observing System satellites) were validated using in situ LST (T-skin) and near-surface air temperature (T-air) observations recorded at CREST-SAFE for the winters of 2013 and 2014. Results indicate that T-air correlates better than T-skin with VIIRS LST data and that the accuracy of nighttime LST retrievals is considerably better than that of daytime. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and night-time values. Results indicate that, although all the data sets showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C). Additionally, we created a liquid water content (LWC)-profiling instrument using time-domain reflectometry (TDR) at CREST-SAFE and tested it during the snow melt period (February-April) immediately after installation in 2014. Results displayed high agreement when compared to LWC estimates obtained using empirical formulas developed in previous studies, and minor improvement over wet snow LWC estimates. Lastly, to improve on global snow cover mapping, a snow product capable of estimating snow depth and snow water

Snow multivariable data assimilation for hydrological predictions in Alpine sites

NASA Astrophysics Data System (ADS)

Piazzi, Gaia; Thirel, Guillaume; Campo, Lorenzo; Gabellani, Simone; Stevenin, Hervè

2017-04-01

Snowpack dynamics (snow accumulation and ablation) strongly impacts on hydrological processes in Alpine areas. During the winter season the presence of snow cover (snow accumulation) reduces the drainage in the basin with a resulting lower watershed time of concentration in case of possible rainfall events. Moreover, the release of the significant water volume stored in winter (snowmelt) considerably contributes to the total discharge during the melting period. Therefore when modeling hydrological processes in snow-dominated catchments the quality of predictions deeply depends on how the model succeeds in catching snowpack dynamics. The integration of a hydrological model with a snow module allows improving predictions of river discharges. Besides the well-known modeling limitations (uncertainty in parameterizations; possible errors affecting both meteorological forcing data and initial conditions; approximations in boundary conditions), there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine several independent snow-related data sources (model simulations, ground-based measurements and remote sensed observations) in order to obtain the most likely estimate of snowpack state. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model strengthened by a multivariable DA framework for hydrological purposes. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity

Snow crystal imaging using scanning electron microscopy: III. Glacier ice, snow and biota

USGS Publications Warehouse

Rango, A.; Wergin, W.P.; Erbe, E.F.; Josberger, E.G.

2000-01-01

Low-temperature scanning electron microscopy (SEM) was used to observe metamorphosed snow, glacial firn, and glacial ice obtained from South Cascade Glacier in Washington State, USA. Biotic samples consisting of algae (Chlamydomonas nivalis) and ice worms (a species of oligochaetes) were also collected and imaged. In the field, the snow and biological samples were mounted on copper plates, cooled in liquid nitrogen, and stored in dry shipping containers which maintain a temperature of -196??C. The firn and glacier ice samples were obtained by extracting horizontal ice cores, 8 mm in diameter, at different levels from larger standard glaciological (vertical) ice cores 7.5 cm in diameter. These samples were cooled in liquid nitrogen and placed in cryotubes, were stored in the same dry shipping container, and sent to the SEM facility. In the laboratory, the samples were sputter coated with platinum and imaged by a low-temperature SEM. To image the firn and glacier ice samples, the cores were fractured in liquid nitrogen, attached to a specimen holder, and then imaged. While light microscope images of snow and ice are difficult to interpret because of internal reflection and refraction, the SEM images provide a clear and unique view of the surface of the samples because they are generated from electrons emitted or reflected only from the surface of the sample. In addition, the SEM has a great depth of field with a wide range of magnifying capabilities. The resulting images clearly show the individual grains of the seasonal snowpack and the bonding between the snow grains. Images of firn show individual ice crystals, the bonding between the crystals, and connected air spaces. Images of glacier ice show a crystal structure on a scale of 1-2 mm which is considerably smaller than the expected crystal size. Microscopic air bubbles, less than 15 ??m in diameter, clearly marked the boundaries between these crystal-like features. The life forms associated with the glacier were

Snow depth on Arctic and Antarctic sea ice derived from autonomous (Snow Buoy) measurements

NASA Astrophysics Data System (ADS)

Nicolaus, Marcel; Arndt, Stefanie; Hendricks, Stefan; Heygster, Georg; Huntemann, Marcus; Katlein, Christian; Langevin, Danielle; Rossmann, Leonard; Schwegmann, Sandra

2016-04-01

The snow cover on sea ice received more and more attention in recent sea ice studies and model simulations, because its physical properties dominate many sea ice and upper ocean processes. In particular; the temporal and spatial distribution of snow depth is of crucial importance for the energy and mass budgets of sea ice, as well as for the interaction with the atmosphere and the oceanic freshwater budget. Snow depth is also a crucial parameter for sea ice thickness retrieval algorithms from satellite altimetry data. Recent time series of Arctic sea ice volume only use monthly snow depth climatology, which cannot take into account annual changes of the snow depth and its properties. For Antarctic sea ice, no such climatology is available. With a few exceptions, snow depth on sea ice is determined from manual in-situ measurements with very limited coverage of space and time. Hence the need for more consistent observational data sets of snow depth on sea ice is frequently highlighted. Here, we present time series measurements of snow depths on Antarctic and Arctic sea ice, recorded by an innovative and affordable platform. This Snow Buoy is optimized to autonomously monitor the evolution of snow depth on sea ice and will allow new insights into its seasonality. In addition, the instruments report air temperature and atmospheric pressure directly into different international networks, e.g. the Global Telecommunication System (GTS) and the International Arctic Buoy Programme (IABP). We introduce the Snow Buoy concept together with technical specifications and results on data quality, reliability, and performance of the units. We highlight the findings from four buoys, which simultaneously drifted through the Weddell Sea for more than 1.5 years, revealing unique information on characteristic regional and seasonal differences. Finally, results from seven snow buoys co-deployed on Arctic sea ice throughout the winter season 2015/16 suggest the great importance of local

Characterization of Air and Ground Temperature Relationships within the CMIP5 Historical and Future Climate Simulations

NASA Astrophysics Data System (ADS)

García-García, A.; Cuesta-Valero, F. J.; Beltrami, H.; Smerdon, J. E.

2017-12-01

The relationships between air and ground surface temperatures across North America are examined in the historical and future projection simulations from 32 General Circulation Models (GCMs) included in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The covariability between surface air (2 m) and ground surface temperatures (10 cm) is affected by simulated snow cover, vegetation cover and precipitation through changes in soil moisture at the surface. At high latitudes, the differences between air and ground surface temperatures, for all CMIP5 simulations, are related to the insulating effect of snow cover and soil freezing phenomena. At low latitudes, the differences between the two temperatures, for the majority of simulations, are inversely proportional to leaf area index and precipitation, likely due to induced-changes in latent and sensible heat fluxes at the ground surface. Our results show that the transport of energy across the air-ground interface differs from observations and among GCM simulations, by amounts that depend on the components of the land-surface models that they include. The large variability among GCMs and the marked dependency of the results on the choice of the land-surface model, illustrate the need for improving the representation of processes controlling the coupling of the lower atmosphere and the land surface in GCMs as a means of reducing the variability in their representation of weather and climate phenomena, with potentially important implications for positive climate feedbacks such as permafrost and soil carbon stability.

Global warming in the context of 2000 years of Australian alpine temperature and snow cover.

PubMed

McGowan, Hamish; Callow, John Nikolaus; Soderholm, Joshua; McGrath, Gavan; Campbell, Micheline; Zhao, Jian-Xin

2018-03-13

Annual resolution reconstructions of alpine temperatures are rare, particularly for the Southern Hemisphere, while no snow cover reconstructions exist. These records are essential to place in context the impact of anthropogenic global warming against historical major natural climate events such as the Roman Warm Period (RWP), Medieval Climate Anomaly (MCA) and Little Ice Age (LIA). Here we show for a marginal alpine region of Australia using a carbon isotope speleothem reconstruction, warming over the past five decades has experienced equivalent magnitude of temperature change and snow cover decline to the RWP and MCA. The current rate of warming is unmatched for the past 2000 years and seasonal snow cover is at a minimum. On scales of several decades, mean maximum temperatures have undergone considerable change ≈ ± 0.8 °C highlighting local scale susceptibility to rapid temperature change, evidence of which is often masked in regional to hemisphere scale temperature reconstructions.

A New Operational Snow Retrieval Algorithm Applied to Historical AMSR-E Brightness Temperatures

NASA Technical Reports Server (NTRS)

Tedesco, Marco; Jeyaratnam, Jeyavinoth

2016-01-01

Snow is a key element of the water and energy cycles and the knowledge of spatio-temporal distribution of snow depth and snow water equivalent (SWE) is fundamental for hydrological and climatological applications. SWE and snow depth estimates can be obtained from spaceborne microwave brightness temperatures at global scale and high temporal resolution (daily). In this regard, the data recorded by the Advanced Microwave Scanning Radiometer-Earth Orbiting System (EOS) (AMSR-E) onboard the National Aeronautics and Space Administration's (NASA) AQUA spacecraft have been used to generate operational estimates of SWE and snow depth, complementing estimates generated with other microwave sensors flying on other platforms. In this study, we report the results concerning the development and assessment of a new operational algorithm applied to historical AMSR-E data. The new algorithm here proposed makes use of climatological data, electromagnetic modeling and artificial neural networks for estimating snow depth as well as a spatio-temporal dynamic density scheme to convert snow depth to SWE. The outputs of the new algorithm are compared with those of the current AMSR-E operational algorithm as well as in-situ measurements and other operational snow products, specifically the Canadian Meteorological Center (CMC) and GlobSnow datasets. Our results show that the AMSR-E algorithm here proposed generally performs better than the operational one and addresses some major issues identified in the spatial distribution of snow depth fields associated with the evolution of effective grain size.

Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations.

PubMed

Wang, Tao; Peng, Shushi; Krinner, Gerhard; Ryder, James; Li, Yue; Dantec-Nédélec, Sarah; Ottlé, Catherine

2015-01-01

Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation) into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms) and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique) improve the simulation accuracy of mean seasonal (October throughout May) snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the magnitude of

Snow cover distribution over elevation zones in a mountainous catchment

NASA Astrophysics Data System (ADS)

Panagoulia, D.; Panagopoulos, Y.

2009-04-01

A good understanding of the elevetional distribution of snow cover is necessary to predict the timing and volume of runoff. In a complex mountainous terrain the snow cover distribution within a watershed is highly variable in time and space and is dependent on elevation, slope, aspect, vegetation type, surface roughness, radiation load, and energy exchange at the snow-air interface. Decreases in snowpack due to climate change could disrupt the downstream urban and agricultural water supplies, while increases could lead to seasonal flooding. Solar and longwave radiation are dominant energy inputs driving the ablation process. Turbulent energy exchange at the snow cover surface is important during the snow season. The evaporation of blowing and drifting snow is strongly dependent upon wind speed. Much of the spatial heterogeneity of snow cover is the result of snow redistribution by wind. Elevation is important in determining temperature and precipitation gradients along hillslopes, while the temperature gradients determine where precipitation falls as rain and snow and contribute to variable melt rates within the hillslope. Under these premises, the snow accumulation and ablation (SAA) model of the US National Weather Service (US NWS) was applied to implement the snow cover extent over elevation zones of a mountainous catchment (the Mesochora catchment in Western-Central Greece), taking also into account the indirectly included processes of sublimation, interception, and snow redistribution. The catchment hydrology is controlled by snowfall and snowmelt and the simulated discharge was computed from the soil moisture accounting (SMA) model of the US NWS and compared to the measured discharge. The elevationally distributed snow cover extent presented different patterns with different time of maximization, extinction and return during the year, producing different timing of discharge that is a crucial factor for the control and management of water resources systems.

Effect of Climate Change on Soil Temperature in Swedish Boreal Forests

PubMed Central

Jungqvist, Gunnar; Oni, Stephen K.; Teutschbein, Claudia; Futter, Martyn N.

2014-01-01

Complex non-linear relationships exist between air and soil temperature responses to climate change. Despite its influence on hydrological and biogeochemical processes, soil temperature has received less attention in climate impact studies. Here we present and apply an empirical soil temperature model to four forest sites along a climatic gradient of Sweden. Future air and soil temperature were projected using an ensemble of regional climate models. Annual average air and soil temperatures were projected to increase, but complex dynamics were projected on a seasonal scale. Future changes in winter soil temperature were strongly dependent on projected snow cover. At the northernmost site, winter soil temperatures changed very little due to insulating effects of snow cover but southern sites with little or no snow cover showed the largest projected winter soil warming. Projected soil warming was greatest in the spring (up to 4°C) in the north, suggesting earlier snowmelt, extension of growing season length and possible northward shifts in the boreal biome. This showed that the projected effects of climate change on soil temperature in snow dominated regions are complex and general assumptions of future soil temperature responses to climate change based on air temperature alone are inadequate and should be avoided in boreal regions. PMID:24747938

Effect of climate change on soil temperature in Swedish boreal forests.

PubMed

Jungqvist, Gunnar; Oni, Stephen K; Teutschbein, Claudia; Futter, Martyn N

2014-01-01

Complex non-linear relationships exist between air and soil temperature responses to climate change. Despite its influence on hydrological and biogeochemical processes, soil temperature has received less attention in climate impact studies. Here we present and apply an empirical soil temperature model to four forest sites along a climatic gradient of Sweden. Future air and soil temperature were projected using an ensemble of regional climate models. Annual average air and soil temperatures were projected to increase, but complex dynamics were projected on a seasonal scale. Future changes in winter soil temperature were strongly dependent on projected snow cover. At the northernmost site, winter soil temperatures changed very little due to insulating effects of snow cover but southern sites with little or no snow cover showed the largest projected winter soil warming. Projected soil warming was greatest in the spring (up to 4°C) in the north, suggesting earlier snowmelt, extension of growing season length and possible northward shifts in the boreal biome. This showed that the projected effects of climate change on soil temperature in snow dominated regions are complex and general assumptions of future soil temperature responses to climate change based on air temperature alone are inadequate and should be avoided in boreal regions.

Estimating the Longwave Radiation Underneath the Forest Canopy in Snow-dominated Setting

NASA Astrophysics Data System (ADS)

Zhou, Y.; Kumar, M.; Link, T. E.

2017-12-01

Forest canopies alter incoming longwave radiation at the land surface, thus influencing snow cover energetics. The snow surface receives longwave radiation from the sky as well as from surrounding vegetation. The longwave radiation from trees is determined by its skin temperature, which shows significant heterogeneity depending on its position and morphometric attributes. Here our goal is to derive an effective tree temperature that can be used to estimate the longwave radiation received by the land surface pixel. To this end, we implement these three steps: 1) derive a relation between tree trunk surface temperature and the incident longwave radiation, shortwave radiation, and air temperature; 2) develop an inverse model to calculate the effective temperature by establishing a relationship between the effective temperature and the actual tree temperature; and 3) estimate the effective temperature using widely measured variables, such as solar radiation and forest density. Data used to derive aforementioned relations were obtained at the University of Idaho Experimental Forest, in northern Idaho. Tree skin temperature, incoming longwave radiation, solar radiation received by the tree surface, and air temperature were measured at an isolated tree and a tree within a homogeneous forest stand. Longwave radiation received by the land surface and the sky view factors were also measured at the same two locations. The calculated effective temperature was then compared with the measured tree trunk surface temperature. Additional longwave radiation measurements with pyrgeometer arrays were conducted under forests with different densities to evaluate the relationship between effective temperature and forest density. Our preliminary results show that when exposed to direct shortwave radiation, the tree surface temperature shows a significant difference from the air temperature. Under cloudy or shaded conditions, the tree surface temperature closely follows the air temperature

Analysis of snow-cap pollution for air quality assessment in the vicinity of an oil refinery.

PubMed

Krastinyte, Viktorija; Baltrenaite, Edita; Lietuvninkas, Arvydas

2013-01-01

Snow-cap can be used as a simple and effective indicator of industrial air pollution. In this study snow-cap samples were collected from 11 sites located in the vicinity of an oil refinery in Mazeikiai, a region in the north-west of Lithuania, in the winter of 2011. Analysis of snowmelt water and snow-dust was used to determine anthropogenic pollutants such as: sulphates and chlorides, nitrites, nitrates, ammonium nitrogen, total carbon, total nitrogen; heavy metals: lead (Pb), copper (Cu), chromium (Cr), cadmium (Cd). Concentrations of heavy metals in snow-dust were detected thousands of times higher than those in the snowmelt water. In this study, analysis of heavy metal concentration was conducted considering different distances and the wind direction within the impact zone of the oil refinery. The sequence of heavy metals according to their mean concentrations in the snow-dust samples was the following: Pb > Cr > Cu > Cd. Heavy metals highly correlated among each other. The load of snow-dust was evaluated to determine the pollution level in the study area. The highest daily load of snow-dust was 45.81 +/- 12.35 mg/m2 in the north-western direction from the oil refinery. According to classification of the daily load of snow-dust a lower than medium-risk level of pollution was determined in the vicinity of the oil refinery.

Photovoltaic cell electrical heating system for removing snow on panel including verification.

PubMed

Weiss, Agnes; Weiss, Helmut

2017-11-16

Small photovoltaic plants in private ownership are typically rated at 5 kW (peak). The panels are mounted on roofs at a decline angle of 20° to 45°. In winter time, a dense layer of snow at a width of e.g., 10 cm keeps off solar radiation from the photovoltaic cells for weeks under continental climate conditions. Practically, no energy is produced over the time of snow coverage. Only until outside air temperature has risen high enough for a rather long-time interval to allow partial melting of snow; the snow layer rushes down in an avalanche. Following this proposal, snow removal can be arranged electrically at an extremely positive energy balance in a fast way. A photovoltaic cell is a large junction area diode inside with a threshold voltage of about 0.6 to 0.7 V (depending on temperature). This forward voltage drop created by an externally driven current through the modules can be efficiently used to provide well-distributed heat dissipation at the cell and further on at the glass surface of the whole panel. The adhesion of snow on glass is widely reduced through this heating in case a thin water film can be produced by this external short time heating. Laboratory experiments provided a temperature increase through rated panel current of more than 10 °C within about 10 min. This heating can initiate the avalanche for snow removal on intention as described before provided the clamping effect on snow at the edge of the panel frame is overcome by an additional heating foil. Basics of internal cell heat production, heating thermal effects in time course, thermographic measurements on temperature distribution, power circuit opportunities including battery storage elements and snow-removal under practical conditions are described.

Sensitivity of Alpine Snow and Streamflow Regimes to Climate Changes

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Marks, D. G.; Bernhardt, M.

2014-12-01

Understanding the sensitivity of hydrological processes to climate change in alpine areas with snow dominated regimes is of paramount importance as alpine basins show both high runoff efficiency associated with the melt of the seasonal snowpack and great sensitivity of snow processes to temperature change. In this study, meteorological data measured in a selection of alpine headwaters basins including Reynolds Mountain East, Idaho, USA, Wolf Creek, Yukon in Canada, and Zugspitze Mountain, Germany with climates ranging from arctic to continental temperate were used to study the snow and streamflow sensitivity to climate change. All research sites have detailed multi-decadal meteorological and snow measurements. The Cold Regions Hydrological Modelling platform (CRHM) was used to create a model representing a typical alpine headwater basin discretized into hydrological response units with physically based representations of snow redistribution by wind, complex terrain snowmelt energetics and runoff processes in alpine tundra. The sensitivity of snow hydrology to climate change was investigated by changing air temperature and precipitation using weather generating methods based on the change factors obtained from different climate model projections for future and current periods. The basin mean and spatial variability of peak snow water equivalent, sublimation loss, duration of snow season, snowmelt rates, streamflow peak, and basin discharge were assessed under varying climate scenarios and the most sensitive hydrological mechanisms to the changes in the different alpine climates were detected. The results show that snow hydrology in colder alpine climates is more resilient to warming than that in warmer climates, but that compensatory factors to warming such as reduced blowing snow sublimation loss and reduced melt rate should also be assessed when considering climate change impacts on alpine hydrology.

A conceptual snow model with an analytic resolution of the heat and phase change equations

NASA Astrophysics Data System (ADS)

Riboust, Philippe; Le Moine, Nicolas; Thirel, Guillaume; Ribstein, Pierre

2017-04-01

Compared to degree-day snow models, physically-based snow models resolve more processes in an attempt to achieve a better representation of reality. Often these physically-based models resolve the heat transport equations in snow using a vertical discretization of the snowpack. The snowpack is decomposed into several layers in which the mechanical and thermal states of the snow are calculated. A higher number of layers in the snowpack allow for better accuracy but it also tends to increase the computational costs. In order to develop a snow model that estimates the temperature profile of snow with a lower computational cost, we used an analytical decomposition of the vertical profile using eigenfunctions (i.e. trigonometric functions adapted to the specific boundary conditions). The mass transfer of snow melt has also been estimated using an analytical conceptualization of runoff fingering and matrix flow. As external meteorological forcing, the model uses solar and atmospheric radiation, air temperature, atmospheric humidity and precipitations. It has been tested and calibrated at point scale at two different stations in the Alps: Col de Porte (France, 1325 m) and Weissfluhjoch (Switzerland, 2540 m). A sensitivity analysis of model parameters and model inputs will be presented together with a comparison with measured snow surface temperature, SWE, snow depth, temperature profile and snow melt data. The snow model is created in order to be ultimately coupled with hydrological models for rainfall-runoff modeling in mountainous areas. We hope to create a model faster than physically-based models but capable to estimate more physical processes than degree-day snow models. This should help to build a more reliable snow model capable of being easily calibrated by remote sensing and in situ observation or to assimilate these data for forecasting purposes.

Air- ice-snow interaction in the Northern Hemisphere under different stability conditions

NASA Astrophysics Data System (ADS)

Repina, Irina; Chechin, Dmitry; Artamonov, Arseny

2013-04-01

The traditional parameterizations of the atmospheric boundary layer are based on similarity theory and the coefficients of turbulent transfer, describing the atmospheric-surface interaction and the diffusion of impurities in the operational models of air pollution, weather forecasting and climate change. Major drawbacks of these parameterizations is that they are not applicable for the extreme conditions of stratification and currents over complex surfaces (such as sea ice, marginal ice zone or stormy sea). These problem could not be overcome within the framework of classical theory, i.e, by rectifying similarity functions or through the introduction of amendments to the traditional turbulent closure schemes. Lack of knowledge on the structure of the surface air layer and the exchange of momentum, heat and moisture between the rippling water surface and the atmosphere at different atmospheric stratifications is at present the major obstacle which impede proper functioning of the operational global and regional weather prediction models and expert models of climate and climate change. This is especially important for the polar regions, where in winter time the development of strong stable boundary layer in the presence of polynyas and leads usually occur. Experimental studies of atmosphere-ice-snow interaction under different stability conditions are presented. Strong stable and unstable conditions are discussed. Parametrizations of turbulent heat and gas exchange at the atmosphere ocean interface are developed. The dependence of the exchange coefficients and aerodynamic roughness on the atmospheric stratification over the snow and ice surface is experimentally confirmed. The drag coefficient is reduced with increasing stability. The behavior of the roughness parameter is simple. This result was obtained in the Arctic from the measurements over hummocked surface. The value of the roughness in the Arctic is much less than that observed over the snow in the middle and

Climate Sensitivity to Realistic Solar Heating of Snow and Ice

NASA Astrophysics Data System (ADS)

Flanner, M.; Zender, C. S.

2004-12-01

Snow and ice-covered surfaces are highly reflective and play an integral role in the planetary radiation budget. However, GCMs typically prescribe snow reflection and absorption based on minimal knowledge of snow physical characteristics. We performed climate sensitivity simulations with the NCAR CCSM including a new physically-based multi-layer snow radiative transfer model. The model predicts the effects of vertically resolved heating, absorbing aerosol, and snowpack transparency on snowpack evolution and climate. These processes significantly reduce the model's near-infrared albedo bias over deep snowpacks. While the current CCSM implementation prescribes all solar radiative absorption to occur in the top 2 cm of snow, we estimate that about 65% occurs beneath this level. Accounting for the vertical distribution of snowpack heating and more realistic reflectance significantly alters snowpack depth, surface albedo, and surface air temperature over Northern Hemisphere regions. Implications for the strength of the ice-albedo feedback will be discussed.

Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations

PubMed Central

Wang, Tao; Peng, Shushi; Krinner, Gerhard; Ryder, James; Li, Yue; Dantec-Nédélec, Sarah; Ottlé, Catherine

2015-01-01

Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation) into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms) and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique) improve the simulation accuracy of mean seasonal (October throughout May) snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the magnitude of

Ice core evidence of rapid air temperature increases since 1960 in alpine areas of the Wind River Range, Wyoming, United States

USGS Publications Warehouse

Naftz, D.L.; Susong, D.D.; Schuster, P.F.; Cecil, L.D.; Dettinger, M.D.; Michel, R.L.; Kendall, C.

2002-01-01

Site-specific transfer functions relating delta oxygen 18 (δ18O) values in snow to the average air temperature (TA) during storms on Upper Fremont Glacier (UFG) were used in conjunction with δ18O records from UFG ice cores to reconstruct long-term trends in air temperature from alpine areas in the Wind River Range, Wyoming. Transfer functions were determined by using data collected from four seasonal snowpacks (1989-1990, 1997-1998, 1998-1999, and 1999-2000). The timing and amount of each storm was determined from an automated snowpack telemetry (SNOTEL) site, 22 km northeast of UFG, and ~1060 m in elevation below UFG. Statistically significant and positive correlations between δ18O values in the snow and TA were consistently found in three of the four seasonal snowpacks. The snowpack with the poor correlation was deposited in 1997-1998 during the 1997-1998 El Nino Southern Oscillation (ENSO). An ultrasonic snow-depth sensor installed on UFG provided valuable insights into site-specific storms and postdepositional processes that occur on UFG. The timing of storms recorded at the UFG and Cold Springs SNOTEL sites were similar; however, selected storms did not correlate. Snow from storms occurring after mid-October and followed by high winds was most susceptible to redeposition of snow. This removal of lower temperature snowfall could potentially bias the δ18O values preserved in ice core records to environmental conditions reflecting higher air temperatures and lower wind speeds. Transfer functions derived from seasonal snow cover on UFG were used to reconstruct TA values from δ18O values determined from two ice cores collected from UFG. Reconstructed air temperatures from the ice core data indicate an increase in TA of ~3.5oC from the mid-1960s to the early 1990s in the alpine areas of northwestern Wyoming. Reconstructed TA from the ice core records between the end of the Little Ice Age (LIA), mid-1800s, and the early 1990s indicate a TA increase of ~55oC. The

Process-level model evaluation: a snow and heat transfer metric

NASA Astrophysics Data System (ADS)

Slater, Andrew G.; Lawrence, David M.; Koven, Charles D.

2017-04-01

Land models require evaluation in order to understand results and guide future development. Examining functional relationships between model variables can provide insight into the ability of models to capture fundamental processes and aid in minimizing uncertainties or deficiencies in model forcing. This study quantifies the proficiency of land models to appropriately transfer heat from the soil through a snowpack to the atmosphere during the cooling season (Northern Hemisphere: October-March). Using the basic physics of heat diffusion, we investigate the relationship between seasonal amplitudes of soil versus air temperatures due to insulation from seasonal snow. Observations demonstrate the anticipated exponential relationship of attenuated soil temperature amplitude with increasing snow depth and indicate that the marginal influence of snow insulation diminishes beyond an effective snow depth of about 50 cm. A snow and heat transfer metric (SHTM) is developed to quantify model skill compared to observations. Land models within the CMIP5 experiment vary widely in SHTM scores, and deficiencies can often be traced to model structural weaknesses. The SHTM value for individual models is stable over 150 years of climate, 1850-2005, indicating that the metric is insensitive to climate forcing and can be used to evaluate each model's representation of the insulation process.

Process-level model evaluation: a snow and heat transfer metric

DOE PAGES

Slater, Andrew G.; Lawrence, David M.; Koven, Charles D.

2017-04-20

Land models require evaluation in order to understand results and guide future development. Examining functional relationships between model variables can provide insight into the ability of models to capture fundamental processes and aid in minimizing uncertainties or deficiencies in model forcing. This study quantifies the proficiency of land models to appropriately transfer heat from the soil through a snowpack to the atmosphere during the cooling season (Northern Hemisphere: October–March). Using the basic physics of heat diffusion, we investigate the relationship between seasonal amplitudes of soil versus air temperatures due to insulation from seasonal snow. Observations demonstrate the anticipated exponential relationshipmore » of attenuated soil temperature amplitude with increasing snow depth and indicate that the marginal influence of snow insulation diminishes beyond an effective snow depth of about 50 cm. A snow and heat transfer metric (SHTM) is developed to quantify model skill compared to observations. Land models within the CMIP5 experiment vary widely in SHTM scores, and deficiencies can often be traced to model structural weaknesses. The SHTM value for individual models is stable over 150 years of climate, 1850–2005, indicating that the metric is insensitive to climate forcing and can be used to evaluate each model's representation of the insulation process.« less

Process-level model evaluation: a snow and heat transfer metric

DOE Office of Scientific and Technical Information (OSTI.GOV)

Slater, Andrew G.; Lawrence, David M.; Koven, Charles D.

Land models require evaluation in order to understand results and guide future development. Examining functional relationships between model variables can provide insight into the ability of models to capture fundamental processes and aid in minimizing uncertainties or deficiencies in model forcing. This study quantifies the proficiency of land models to appropriately transfer heat from the soil through a snowpack to the atmosphere during the cooling season (Northern Hemisphere: October–March). Using the basic physics of heat diffusion, we investigate the relationship between seasonal amplitudes of soil versus air temperatures due to insulation from seasonal snow. Observations demonstrate the anticipated exponential relationshipmore » of attenuated soil temperature amplitude with increasing snow depth and indicate that the marginal influence of snow insulation diminishes beyond an effective snow depth of about 50 cm. A snow and heat transfer metric (SHTM) is developed to quantify model skill compared to observations. Land models within the CMIP5 experiment vary widely in SHTM scores, and deficiencies can often be traced to model structural weaknesses. The SHTM value for individual models is stable over 150 years of climate, 1850–2005, indicating that the metric is insensitive to climate forcing and can be used to evaluate each model's representation of the insulation process.« less

Trace elements and common ions in southeastern Idaho snow: Regional air pollutant tracers for source area emissions

USGS Publications Warehouse

Abbott, M.; Einerson, J.; Schuster, P.; Susong, D.; Taylor, Howard E.; ,

2004-01-01

Snow sampling and analysis methods which produce accurate and ultra-low measurements of trace elements and common ion concentration in southeastern Idaho snow, were developed. Snow samples were collected over two winters to assess trace elements and common ion concentrations in air pollutant fallout across the southeastern Idaho. The area apportionment of apportionment of fallout concentrations measured at downwind location were investigated using pattern recognition and multivariate statistical technical techniques. Results show a high level of contribution from phosphates processing facilities located outside Pocatello in the southern portion of the Eastern Snake River Plain, and no obvious source area profiles other than at Pocatello.

Spatiotemporal variations in the difference between satellite-observed daily maximum land surface temperature and station-based daily maximum near-surface air temperature

NASA Astrophysics Data System (ADS)

Lian, Xu; Zeng, Zhenzhong; Yao, Yitong; Peng, Shushi; Wang, Kaicun; Piao, Shilong

2017-02-01

There is an increasing demand to integrate land surface temperature (LST) into climate research due to its global coverage, which requires a comprehensive knowledge of its distinctive characteristics compared to near-surface air temperature (Tair). Using satellite observations and in situ station-based data sets, we conducted a global-scale assessment of the spatial and seasonal variations in the difference between daily maximum LST and daily maximum Tair (δT, LST - Tair) during 2003-2014. Spatially, LST is generally higher than Tair over arid and sparsely vegetated regions in the middle-low latitudes, but LST is lower than Tair in tropical rainforests due to strong evaporative cooling, and in the high-latitude regions due to snow-induced radiative cooling. Seasonally, δT is negative in tropical regions throughout the year, while it displays a pronounced seasonality in both the midlatitudes and boreal regions. The seasonality in the midlatitudes is a result of the asynchronous responses of LST and Tair to the seasonal cycle of radiation and vegetation abundance, whereas in the boreal regions, seasonality is mainly caused by the change in snow cover. Our study identified substantial spatial heterogeneity and seasonality in δT, as well as its determinant environmental drivers, and thus provides a useful reference for monitoring near-surface air temperature changes using remote sensing, particularly in remote regions.

Understanding Montane Snow Water Equivalent Response to Climate Change and Variability

NASA Astrophysics Data System (ADS)

Huning, L. S.; AghaKouchak, A.

2017-12-01

Large populations worldwide rely on the seasonal snowpack for the majority of their water resources. Warming temperatures and other hydrometeorological changes impact the timing, distribution, and amount of montane snow water equivalent (SWE). Therefore, developing an improved understanding of the historical response to changing atmospheric drivers across snow-dominated mountainous regions has significant societal value related to water resources management and environmental hazards (i.e. flooding and droughts) for a future warming climate. Utilizing multi-decadal snow data sets and a probabilistic risk model over mountain ranges such as the Sierra Nevada (USA), the response of snowpack characteristics (e.g. SWE/snowfall, peak SWE, day of peak SWE, melt rate, etc.) to unit changes in hydrometeorological quantities (e.g. air temperature, humidity, winds, etc.) is quantified. The likelihood that the amount of SWE will exceed specified amounts (e.g. long-term peak SWE value) is presented for a range of climatic conditions. This study compares hydrologic response of montane SWE across windward and leeward basins, elevational bands, and regions of differing physiographic characteristics to understand how projected global warming such as a unit increase in air temperature or changes in other hydrometeorological quantities impact SWE at different spatial scales (i.e. basin-wide and range-wide). It provides insight that can be used to understand vulnerabilities of the seasonal snowpack to changes in climatic and atmospheric conditions.

Changing Snow Cover and Stream Discharge in the Western United States - Wind River Range, Wyoming

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Foster, James L.; DiGirolamo, Nicolo E.; Barton, Jonathan S.; Riggs, George A.

2011-01-01

Earlier onset of springtime weather has been documented in the western United States over at least the last 50 years. Because the majority (>70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack has important implications for the management of water resources. We studied ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover products, 40 years of stream discharge and meteorological station data and 30 years of snow-water equivalent (SWE) SNOw Telemetry (SNOTEL) data in the Wind River Range (WRR), Wyoming. Results show increasing air temperatures for.the 40-year study period. Discharge from streams in WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades. Changes in streamflow may be related to increasing air temperatures which are probably contributing to a reduction in snow cover, although no trend of either increasingly lower streamflow or earlier snowmelt was observed within the decade of the 2000s. And SWE on 1 April does not show an expected downward trend from 1980 to 2009. The extent of snow cover derived from the lowest-elevation zone of the WRR study area is strongly correlated (r=0.91) with stream discharge on 1 May during the decade of the 2000s. The strong relationship between snow cover and streamflow indicates that MODIS snow-cover maps can be used to improve management of water resources in the drought-prone western U.S.

Atmospheric mercury speciation and mercury in snow over time at Alert, Canada

NASA Astrophysics Data System (ADS)

Steffen, A.; Bottenheim, J.; Cole, A.; Ebinghaus, R.; Lawson, G.; Leaitch, W. R.

2014-03-01

Ten years of atmospheric mercury speciation data and 14 years of mercury in snow data from Alert, Nunavut, Canada, are examined. The speciation data, collected from 2002 to 2011, includes gaseous elemental mercury (GEM), particulate mercury (PHg) and reactive gaseous mercury (RGM). During the winter-spring period of atmospheric mercury depletion events (AMDEs), when GEM is close to being completely depleted from the air, the concentration of both PHg and RGM rise significantly. During this period, the median concentrations for PHg is 28.2 pgm-3 and RGM is 23.9 pgm-3, from March to June, in comparison to the annual median concentrations of 11.3 and 3.2 pgm-3 for PHg and RGM, respectively. In each of the ten years of sampling, the concentration of PHg increases steadily from January through March and is higher than the concentration of RGM. This pattern begins to change in April when the levels of PHg peak and RGM begin to increase. In May, the high PHg and low RGM concentration regime observed in the early spring undergoes a transition to a regime with higher RGM and much lower PHg concentrations. The higher RGM concentration continues into June. The transition is driven by the atmospheric conditions of air temperature and particle availability. Firstly, a high ratio of the concentrations of PHg to RGM is reported at low temperatures which suggests that oxidized gaseous mercury partitions to available particles to form PHg. Prior to the transition, the median air temperature is -24.8 °C and after the transition the median air temperature is -5.8 °C. Secondly, the high PHg concentrations occur in the spring when high particle concentrations are present. The high particle concentrations are principally due to Arctic haze and sea salts. In the snow, the concentrations of mercury peak in May for all years. Springtime deposition of total mercury to the snow at Alert peaks in May when atmospheric conditions favour higher levels of RGM. Therefore, the conditions in the

Monitoring snow cover variability (2000-2014) in the Hengduan Mountains based on cloud-removed MODIS products with an adaptive spatio-temporal weighted method

NASA Astrophysics Data System (ADS)

Li, Xinghua; Fu, Wenxuan; Shen, Huanfeng; Huang, Chunlin; Zhang, Liangpei

2017-08-01

Monitoring the variability of snow cover is necessary and meaningful because snow cover is closely connected with climate and ecological change. In this work, 500 m resolution MODIS daily snow cover products from 2000 to 2014 were adopted to analyze the status in Hengduan Mountains. In order to solve the spatial discontinuity caused by clouds in the products, we propose an adaptive spatio-temporal weighted method (ASTWM), which is based on the initial result of a Terra and Aqua combination. This novel method simultaneously considers the temporal and spatial correlations of the snow cover. The simulated experiments indicate that ASTWM removes clouds completely, with a robust overall accuracy (OA) of above 93% under different cloud fractions. The spatio-temporal variability of snow cover in the Hengduan Mountains was investigated with two indices: snow cover days (SCD) and snow fraction. The results reveal that the annual SCD gradually increases and the coefficient of variation (CV) decreases with elevation. The pixel-wise trends of SCD first rise and then drop in most areas. Moreover, intense intra-annual variability of the snow fraction occurs from October to March, during which time there is abundant snow cover. The inter-annual variability, which mainly occurs in high elevation areas, shows an increasing trend before 2004/2005 and a decreasing trend after 2004/2005. In addition, the snow fraction responds to the two climate factors of air temperature and precipitation. For the intra-annual variability, when the air temperature and precipitation decrease, the snow cover increases. Besides, precipitation plays a more important role in the inter-annual variability of snow cover than temperature.

Downscaling of snow depth and river discharge in Japan by the Pseudo-Global-Warming Method

NASA Astrophysics Data System (ADS)

Kimura, F.; Ma, X.; Hara, M.; Advanced Atmosphere-Ocean-Land Modeling Program

2010-12-01

Although a heavy snowfall often brings disaster, snow cover is one of the major water resources in Japan. Even during the winter, the monthly mean of the surface air temperature often exceeds 0 deg. in large parts of the heavy snow areas along the Sea of Japan. Thus, snow cover may be seriously reduced in these areas as a result of global warming, which is caused by an increase in greenhouse gases. This study estimates the impact of global warming on the snow depth in Japan during early winter. Some dynamical downscaling experiments are conducted by the Pseudo-Global-Warming method for the future projection of snow cover. By the hindcast runs, precipitation, snow depth, and surface air temperature show good agreement with the AMeDAS station data observed in a High-Snow-Cover (HSC) year and a Low-Snow-Cover (LSC) yea. Pseudo-Global-Warming runs for these years indicate that the decreasing ratios of the snow water are more significant in the areas whose altitude is less than 1500 m. The increase of the air temperature is one of the major factors for the decrease in snow water, since the present mean air temperature in most of these areas is near 0 deg. even in winter. On the other hand, the change in the aerial-mean precipitation due to global warming is less than 15% in both years. To evaluate the impact of the reduction of snow cover to water resource, a hydrological simulation is also made for the Agano River basin, which locates in Niigata and Fukushima Prefectures. The Agano River drains into the Sea of Japan and is the second largest river in Japan with annual discharge of about 12.9 billion m3. A hind cast experiment is carried out for the two decades from 1980 to 1999. The average correlation coefficient of 0.79 for the monthly mean discharge in the winter season indicates that the interannual variation of the river discharge could be reproduced and that the method is useful for climate change study. Then the hydrological response to the future global warming

Snow observations in Mount Lebanon (2011-2016)

NASA Astrophysics Data System (ADS)

Fayad, Abbas; Gascoin, Simon; Faour, Ghaleb; Fanise, Pascal; Drapeau, Laurent; Somma, Janine; Fadel, Ali; Bitar, Ahmad Al; Escadafal, Richard

2017-08-01

We present a unique meteorological and snow observational dataset in Mount Lebanon, a mountainous region with a Mediterranean climate, where snowmelt is an essential water resource. The study region covers the recharge area of three karstic river basins (total area of 1092 km2 and an elevation up to 3088 m). The dataset consists of (1) continuous meteorological and snow height observations, (2) snowpack field measurements, and (3) medium-resolution satellite snow cover data. The continuous meteorological measurements at three automatic weather stations (MZA, 2296 m; LAQ, 1840 m; and CED, 2834 m a.s.l.) include surface air temperature and humidity, precipitation, wind speed and direction, incoming and reflected shortwave irradiance, and snow height, at 30 min intervals for the snow seasons (November-June) between 2011 and 2016 for MZA and between 2014 and 2016 for CED and LAQ. Precipitation data were filtered and corrected for Geonor undercatch. Observations of snow height (HS), snow water equivalent, and snow density were collected at 30 snow courses located at elevations between 1300 and 2900 m a.s.l. during the two snow seasons of 2014-2016 with an average revisit time of 11 days. Daily gap-free snow cover extent (SCA) and snow cover duration (SCD) maps derived from MODIS snow products are provided for the same period (2011-2016). We used the dataset to characterize mean snow height, snow water equivalent (SWE), and density for the first time in Mount Lebanon. Snow seasonal variability was characterized with high HS and SWE variance and a relatively high snow density mean equal to 467 kg m-3. We find that the relationship between snow depth and snow density is specific to the Mediterranean climate. The current model explained 34 % of the variability in the entire dataset (all regions between 1300 and 2900 m a.s.l.) and 62 % for high mountain regions (elevation 2200-2900 m a.s.l.). The dataset is suitable for the investigation of snow dynamics and for the forcing

Simulations of a Canadian snowpack brightness temperatures using SURFEX-Crocus for Snow Water Equivalent (SWE) retrievals

NASA Astrophysics Data System (ADS)

Larue, Fanny; Royer, Alain; De Sève, Danielle; Langlois, Alexandre; Roy, Alexandre; Saint-Jean-Rondeau, Olivier

2016-04-01

In Quebec, the water associated to snowmelt represents 30% of the annual electricity production so that the snow cover evaluation in real time is of primary interest. The key variable is snow water equivalent (SWE) which describes the evolution of a global seasonal snow cover. However, the sparse distribution of meteorological stations in northern Québec generates great uncertainty in the extrapolation of SWE. On the contrary, the spatial and temporal coverage of satellite data offer a source of information with a high potential when considered as an alternative to the poor spatial distribution of in-situ information. Thus, this project aims to improve the prediction of SWE by assimilation of satellite passive microwave brightness temperatures (Tb) observations, independently of any ground observations. The snowpack evolution is simulated by the French snow model SURFEX-Crocus, driven by the Canadian atmospheric model GEM with a spatial resolution of 10 km. The bias of the atmospheric model and the impact of initialization errors on the simulated SWE were quantified from our ground measurements. To assimilate satellite observations, the multi-layered snow model is first coupled with a radiative transfer model using the Dense Media Radiative transfer theory (the DMRT-ML model) to estimate the microwave snow emission of the simulated snowpack. In order to retrieve simulated Tb in frequencies of interest (i.e. sensitive to snow dielectric properties), the snow microstructure needs to be well parameterized. It was shown in previous studies that the specific surface area (SSA) of snow grains is a well-defined parameter to describe the size and the shape of snow grains and which allows reproducible field measurements. SURFEX-Crocus estimates a SSA for each simulated snow layer, however, the snow microstructure in DMRT-ML is defined per layer by monodisperse optical radius of grain (~ 1/SSA) and by the stickiness which is not known. It thus becomes necessary to introduce

Snow specific surface area simulation using the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS)

NASA Astrophysics Data System (ADS)

Roy, A.; Royer, A.; Montpetit, B.; Bartlett, P. A.; Langlois, A.

2012-12-01

Snow grain size is a key parameter for modeling microwave snow emission properties and the surface energy balance because of its influence on the snow albedo, thermal conductivity and diffusivity. A model of the specific surface area (SSA) of snow was implemented in the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS) version 3.4. This offline multilayer model (CLASS-SSA) simulates the decrease of SSA based on snow age, snow temperature and the temperature gradient under dry snow conditions, whereas it considers the liquid water content for wet snow metamorphism. We compare the model with ground-based measurements from several sites (alpine, Arctic and sub-Arctic) with different types of snow. The model provides simulated SSA in good agreement with measurements with an overall point-to-point comparison RMSE of 8.1 m2 kg-1, and a RMSE of 4.9 m2 kg-1 for the snowpack average SSA. The model, however, is limited under wet conditions due to the single-layer nature of the CLASS model, leading to a single liquid water content value for the whole snowpack. The SSA simulations are of great interest for satellite passive microwave brightness temperature assimilations, snow mass balance retrievals and surface energy balance calculations with associated climate feedbacks.

Coupling of snow and permafrost processes using the Basic Modeling Interface (BMI)

NASA Astrophysics Data System (ADS)

Wang, K.; Overeem, I.; Jafarov, E. E.; Piper, M.; Stewart, S.; Clow, G. D.; Schaefer, K. M.

2017-12-01

We developed a permafrost modeling tool based by implementing the Kudryavtsev empirical permafrost active layer depth model (the so-called "Ku" component). The model is specifically set up to have a basic model interface (BMI), which enhances the potential coupling to other earth surface processes model components. This model is accessible through the Web Modeling Tool in Community Surface Dynamics Modeling System (CSDMS). The Kudryavtsev model has been applied for entire Alaska to model permafrost distribution at high spatial resolution and model predictions have been verified by Circumpolar Active Layer Monitoring (CALM) in-situ observations. The Ku component uses monthly meteorological forcing, including air temperature, snow depth, and snow density, and predicts active layer thickness (ALT) and temperature on the top of permafrost (TTOP), which are important factors in snow-hydrological processes. BMI provides an easy approach to couple the models with each other. Here, we provide a case of coupling the Ku component to snow process components, including the Snow-Degree-Day (SDD) method and Snow-Energy-Balance (SEB) method, which are existing components in the hydrological model TOPOFLOW. The work flow is (1) get variables from meteorology component, set the values to snow process component, and advance the snow process component, (2) get variables from meteorology and snow component, provide these to the Ku component and advance, (3) get variables from snow process component, set the values to meteorology component, and advance the meteorology component. The next phase is to couple the permafrost component with fully BMI-compliant TOPOFLOW hydrological model, which could provide a useful tool to investigate the permafrost hydrological effect.

Evolution of the snow area index of the subarctic snowpack in central Alaska over a whole season. consequences for the air to snow transfer of pollutants.

PubMed

Taillandier, A S; Domine, F; Simpson, W R; Sturm, M; Douglas, T A; Severin, K

2006-12-15

The detailed physical characteristics of the subarctic snowpack must be known to quantify the exchange of adsorbed pollutants between the atmosphere and the snow cover. For the first time, the combined evolutions of specific surface area (SSA), snow stratigraphy, temperature, and density were monitored throughout winter in central Alaska. We define the snow area index (SAI) as the vertically integrated surface area of snow crystals, and this variable is used to quantify pollutants' adsorption. Intense metamorphism generated by strong temperature gradients formed a thick depth hoar layer with low SSA (90 cm(2) g-1) and density (200 kg m(-3)), resulting in a low SAI. After snowpack buildup in autumn, the winter SAI remained around 1000 m(2)/m(2) of ground, much lower than the SAI of the Arctic snowpack, 2500 m(2) m-(2). With the example of PCBs 28 and 180, we calculate that the subarctic snowpack is a smaller reservoir of adsorbed pollutants than the Arctic snowpack and less efficiently transfers adsorbed pollutants from the atmosphere to ecosystems. The difference is greater for the more volatile PCB 28. With climate change, snowpack structure will be modified, and the snowpack's ability to transfer adsorbed pollutants from the atmosphere to ecosystems may be reduced, especially for the more volatile pollutants.

Timing of wet snow avalanche activity: An analysis from Glacier National Park, Montana, USA.

USGS Publications Warehouse

Peitzsch, Erich H.; Hendrikx, Jordy; Fagre, Daniel B.

2012-01-01

Wet snow avalanches pose a problem for annual spring road opening operations along the Going-to-the-Sun Road (GTSR) in Glacier National Park, Montana, USA. A suite of meteorological metrics and snow observations has been used to forecast for wet slab and glide avalanche activity. However, the timing of spring wet slab and glide avalanches is a difficult process to forecast and requires new capabilities. For the 2011 and 2012 spring seasons we tested a previously developed classification tree model which had been trained on data from 2003-2010. For 2011, this model yielded a 91% predictive rate for avalanche days. For 2012, the model failed to capture any of the avalanche days observed. We then investigated these misclassified avalanche days in the 2012 season by comparing them to the misclassified days from the original dataset from which the model was trained. Results showed no significant difference in air temperature variables between this year and the original training data set for these misclassified days. This indicates that 2012 was characterized by avalanche days most similar to those that the model struggled with in the original training data. The original classification tree model showed air temperature to be a significant variable in wet avalanche activity which implies that subsequent movement of meltwater through the snowpack is also important. To further understand the timing of water flow we installed two lysimeters in fall 2011 before snow accumulation. Water flow showed a moderate correlation with air temperature later in the season and no synchronous pattern associated with wet slab and glide avalanche activity. We also characterized snowpack structure as the snowpack transitioned from a dry to a wet snowpack throughout the spring. This helped to assess potential failure layers of wet snow avalanches and the timing of avalanches compared to water moving through the snowpack. These tools (classification tree model and lysimeter data), combined with

A comparison study of two snow models using data from different Alpine sites

NASA Astrophysics Data System (ADS)

Piazzi, Gaia; Riboust, Philippe; Campo, Lorenzo; Cremonese, Edoardo; Gabellani, Simone; Le Moine, Nicolas; Morra di Cella, Umberto; Ribstein, Pierre; Thirel, Guillaume

2017-04-01

exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity, relative air humidity, precipitation and incident solar radiation) to provide an estimation of the snowpack state. In this study, no DA is used. For more details on the DA scheme, please see EGU2017-7777. Observed data supplied by meteorological stations located in three experimental Alpine sites are used: Col de Porte (1325 m, France); Torgnon (2160 m, Italy); Weissfluhjoch (2540 m, Switzerland). Performances of the two models are compared through evaluations of snow mass, snow depth, albedo and surface temperature simulations in order to better understand and pinpoint limits and potentialities of the analyzed schemes and the impact of different parameterizations on models simulations.

An electrostatic charge measurement of blowing snow particles focusing on collision frequency to the snow surface

NASA Astrophysics Data System (ADS)

Omiya, S.; Sato, A.

2010-12-01

the fixed fetch (12m). The number of collisions of particle was converted from the wind velocity using an equation obtained by Kosugi et al. (2004). Blowing snow particles tend to accumulate negative charges gradually with increase of the number of collisions to the snow surface. As a result, it is demonstrated that the gaps between the field values and the wind tunnel ones were due to difference of the collision frequency of snow particles. Assuming a logarithmic relationship as first approximation between the measured charges and the number of collisions, the charge-to-mass ratios will reach roughly the same value which was obtained in the field with several hundreds collisions. For instance, fetch is needed roughly 200m for blowing snow particles to gain -30 μC/kg under the following conditions: air temperature -20 degrees Celsius, wind velocity 7m/s and hard snow surface. REFERENCE: Kosugi et al., (2004): Dependence of drifting snow saltation length on snow surface hardness. Cold Reg. Sci. Technol., 39, 133-139.

Validation of snow line estimations using MODIS images for the Elqui River basin, Chile

NASA Astrophysics Data System (ADS)

Vasquez, Nicolas; Lagos, Miguel; Vargas, Ximena

2015-04-01

Precipitation events in North-Central Chile are very important because the region has a Mediterranean climate, with a humid period, and an extensive dry one. Separation between solid and liquid precipitation (snow line) in each event is important information that allow to estimate 1) the available snow covered area for snow-melt forecasting, during the dry season (the only resource of water in this period) and 2) the area affected by rain for flood modelling and infrastructure design. In this work, snow line was estimated with a meteorological approach, considering precipitation, temperature, relative humidity and dew point information at a daily scale from 2004 to 2010 and hourly from 2010 to 2013. In both periods, different meteorological stations are considered due to the implementation of new stations in the study area, covering from 1000 to 3000 (m.a.s.l) approximately, with snow and rain meteorological stations. The methodology exposed in this research is based in vertical variation of dew point and temperature due to more stability variations compared to vertical relative humidity behavior. The results calculated from meteorological data are compared with MODIS images, considering three criteria: (1) the median altitude of the minimum specific fractional snow covered area (FSCA), (2) the mean elevation of pixels with a FSCA<10% and (3) the snow line estimation via snow covered area and hypsometric curve. Historically in Chile, snow line has been studied considering few specific precipitation and temperature observations, or estimations of zero isotherms from upper air soundings. A comparison between these estimations and the results validated through MOD10A1/MYD10A1 products was made in order to identify tendencies and/or variations of the snow line at an annually scale.

Spatial Relationships Between Snow Contaminant Content, Grain Size, and Surface Temperature in Multi-spectral Remote Sensing Data of Mt. Rainier, WA

NASA Astrophysics Data System (ADS)

Kay, J. E.; Hansen, G.; Gillespie, A.; Pettit, E.

2002-12-01

Relating cryosphere change to climate change requires estimation of radiative fluxes on snow-covered surfaces. The distribution of, and relationship between, snow-pack properties that affect radiative balance can be estimated with high-resolution remote-sensing data. MODIS/ASTER airborne simulator (MASTER) data were collected at Mt. Rainier to reveal spatial patterns of, and correlations between, snow contaminant content, grain size, and temperature. The visible and near-infrared (VNIR: 11 bands, 0.4-1.0 μm) and the short-wave infrared (SWIR: 14 bands, 1.6-2.4 μm) data are processed to bi-directional reflectance (BDR) and albedo, by removing atmospheric effects and by normalizing to Solar irradiance and incidence angle. VNIR BDR and albedo are used as a proxy for snow contaminant content. Physical and optical grain size are estimated by comparing SWIR BDR and albedo to modeled and measured spectra, and ground-truth measurements. The thermal infrared data (TIR: 10 bands, 8-13 μm) are processed to temperature by removing emissivity and atmospheric effects. In combination, the VNIR, SWIR, and TIR data reveal a distinct pattern of contaminants, grain size, and temperature related to a recent snowfall and the end-of-the-summer melting season. At lower elevations, the surface accumulation of dirty lag deposits resulted in snow with very low visible albedo (20-30 %), large physical and optical grain radii (500-1500 μm, 200 μm), and temperatures near the melting point. At higher elevations, the recent snowfall left snow with low contaminant content, and a higher visible albedo (60-90 %). However, a region near the summit with smaller physical and optical grain radii (400 μm, 100 μm), and temperatures below the melting point, is distinguished from a middle elevation region with grain sizes and temperatures similar to the lower region. Contaminants reduce VNIR albedo and significantly enhance absorption of incoming solar radiation. The spatial correlation between

Observational Evidence of Changes in Soil Temperatures across Eurasian Continent

NASA Astrophysics Data System (ADS)

Zhang, T.

2015-12-01

Soil temperature is one of the key climate change indicators and plays an important role in plant growth, agriculture, carbon cycle and ecosystems as a whole. In this study, variability and changes in ground surface and soil temperatures up to 3.20 m were investigated based on data and information obtained from hydrometeorological stations across Eurasian continent since the early 1950s. Ground surface and soil temperatures were measured daily by using the same standard method and by the trained professionals across Eurasian continent, which makes the dataset unique and comparable over a large study region. Using the daily soil temperature profiles, soil seasonal freeze depth was also obtained through linear interpolation. Preliminary results show that soil temperatures at various depths have increased dramatically, almost twice as much as air temperature increase over the same period. Regionally, soil temperature increase was more dramatically in high northern latitudes than mid/lower latitude regions. Air temperature changes alone may not be able to fully explain the magnitude of changes in soil temperatures. Further study indicates that snow cover establishment started later in autumn and snow cover disappearance occurred earlier in spring, while winter snow depth became thicker with a decreasing trend of snow density. Changes in snow cover conditions may play an important role in changes of soil temperatures over the Eurasian continent.

Why on the snow? Winter emergence strategies of snow-active Chironomidae (Diptera) in Poland.

PubMed

Soszyńska-Maj, Agnieszka; Paasivirta, Lauri; Giłka, Wojciech

2016-10-01

A long-term study of adult non-biting midges (Chironomidae) active in winter on the snow in mountain areas and lowlands in Poland yielded 35 species. The lowland and mountain communities differed significantly in their specific composition. The mountain assemblage was found to be more diverse and abundant, with a substantial contribution from the subfamily Diamesinae, whereas Orthocladiinae predominated in the lowlands. Orthocladius wetterensis Brundin was the most characteristic and superdominant species in the winter-active chironomid communities in both areas. Only a few specimens and species of snow-active chironomids were recorded in late autumn and early winter. The abundance of chironomids peaked in late February in the mountain and lowland areas with an additional peak in the mountain areas in early April. However, this second peak of activity consisted mainly of Orthocladiinae, as Diamesinae emerged earliest in the season. Most snow-active species emerged in mid- and late winter, but their seasonal patterns differed between the 2 regions as a result of the different species composition and the duration of snow cover in these regions. Spearman's rank correlation coefficient tests yielded positive results between each season and the number of chironomid individuals recorded in the mountain area. A positive correlation between air temperature, rising to +3.5 °C, and the number of specimens recorded on the snow in the mountain community was statistically significant. The winter emergence and mate-searching strategies of chironomids are discussed in the light of global warming, and a brief compilation of most important published data on the phenomena studied is provided. © 2015 Institute of Zoology, Chinese Academy of Sciences.

Sensitivity of snow process simulations to precipitation-phase transition method in forested and open areas

NASA Astrophysics Data System (ADS)

Lundberg, A.; Gustafsson, D.

2009-04-01

Modeling of forest snow processes is complicated and especially problematic seems to be the separation of precipitation phase in climates where a large part of the precipitation falls at temperatures near zero degrees Celsius. When the precipitation is classified as snow, the tree crowns can carry an order of magnitude more canopy storage as compared to when the precipitation is classified as rain, and snow in the trees also alters the albedo of the forest while rain does not. Many different schemes for the precipitation phase separation are used by various snow models. Some models use just one air temperature threshold (TR/S) below which all precipitation is assumed to be snow and above which all precipitation is classified as rain. A more common approach for forest snow models is to use two temperature thresholds. The snow fraction (SF) is then set to one below the snow threshold (TS) and to zero above the rain threshold (TR) and SF is assumed to decrease linearly between these two thresholds. Also more sophisticated schemes exist, but three seems to be a lack of agreement on how the precipitation phase separations should be performed. The aim with this study is to use a hydrological model including canopy snow processes to illustrate the sensitivity for different formulations of the precipitation phase separation on a) the simulated maximum snow pack storage b) the interception evaporation loss and c) snow melt runoff. In other words, to investigate of the choice of precipitation phase separation has an impact on the simulated wintertime water balance. Simulations are made for sites in different climates and for both open fields and forest sites in different regions of Sweden from north to south. In general, precipitation phase separation methods that classified snowfall at higher temperatures resulted in a larger proportion of the precipitation lost by interception evaporation as a result of the increased interception capacity. However, the maximum snow

The Snow Must Go On: Ground Ice Encasement, Snow Compaction and Absence of Snow Differently Cause Soil Hypoxia, CO2 Accumulation and Tree Seedling Damage in Boreal Forest

PubMed Central

Vuosku, Jaana; Ovaskainen, Anu; Stark, Sari; Rautio, Pasi

2016-01-01

At high latitudes, the climate has warmed at twice the rate of the global average with most changes observed in autumn, winter and spring. Increasing winter temperatures and wide temperature fluctuations are leading to more frequent rain-on-snow events and freeze-thaw cycles causing snow compaction and formation of ice layers in the snowpack, thus creating ice encasement (IE). By decreasing the snowpack insulation capacity and restricting soil-atmosphere gas exchange, modification of the snow properties may lead to colder soil but also to hypoxia and accumulation of trace gases in the subnivean environment. To test the effects of these overwintering conditions changes on plant winter survival and growth, we established a snow manipulation experiment in a coniferous forest in Northern Finland with Norway spruce and Scots pine seedlings. In addition to ambient conditions and prevention of IE, we applied three snow manipulation levels: IE created by artificial rain-on-snow events, snow compaction and complete snow removal. Snow removal led to deeper soil frost during winter, but no clear effect of IE or snow compaction done in early winter was observed on soil temperature. Hypoxia and accumulation of CO2 were highest in the IE plots but, more importantly, the duration of CO2 concentration above 5% was 17 days in IE plots compared to 0 days in ambient plots. IE was the most damaging winter condition for both species, decreasing the proportion of healthy seedlings by 47% for spruce and 76% for pine compared to ambient conditions. Seedlings in all three treatments tended to grow less than seedlings in ambient conditions but only IE had a significant effect on spruce growth. Our results demonstrate a negative impact of winter climate change on boreal forest regeneration and productivity. Changing snow conditions may thus partially mitigate the positive effect of increasing growing season temperatures on boreal forest productivity. PMID:27254100

The Snow Must Go On: Ground Ice Encasement, Snow Compaction and Absence of Snow Differently Cause Soil Hypoxia, CO2 Accumulation and Tree Seedling Damage in Boreal Forest.

PubMed

Martz, Françoise; Vuosku, Jaana; Ovaskainen, Anu; Stark, Sari; Rautio, Pasi

2016-01-01

At high latitudes, the climate has warmed at twice the rate of the global average with most changes observed in autumn, winter and spring. Increasing winter temperatures and wide temperature fluctuations are leading to more frequent rain-on-snow events and freeze-thaw cycles causing snow compaction and formation of ice layers in the snowpack, thus creating ice encasement (IE). By decreasing the snowpack insulation capacity and restricting soil-atmosphere gas exchange, modification of the snow properties may lead to colder soil but also to hypoxia and accumulation of trace gases in the subnivean environment. To test the effects of these overwintering conditions changes on plant winter survival and growth, we established a snow manipulation experiment in a coniferous forest in Northern Finland with Norway spruce and Scots pine seedlings. In addition to ambient conditions and prevention of IE, we applied three snow manipulation levels: IE created by artificial rain-on-snow events, snow compaction and complete snow removal. Snow removal led to deeper soil frost during winter, but no clear effect of IE or snow compaction done in early winter was observed on soil temperature. Hypoxia and accumulation of CO2 were highest in the IE plots but, more importantly, the duration of CO2 concentration above 5% was 17 days in IE plots compared to 0 days in ambient plots. IE was the most damaging winter condition for both species, decreasing the proportion of healthy seedlings by 47% for spruce and 76% for pine compared to ambient conditions. Seedlings in all three treatments tended to grow less than seedlings in ambient conditions but only IE had a significant effect on spruce growth. Our results demonstrate a negative impact of winter climate change on boreal forest regeneration and productivity. Changing snow conditions may thus partially mitigate the positive effect of increasing growing season temperatures on boreal forest productivity.

Snowpack displacement measured by terrestrial radar interferometry as precursor for wet snow avalanches

NASA Astrophysics Data System (ADS)

Caduff, Rafael; Wiesmann, Andreas; Bühler, Yves

2016-04-01

Wet snow and full depth gliding avalanches commonly occur on slopes during springtime when air temperatures rise above 0°C for longer time. The increase in the liquid water content changes the mechanical properties of the snow pack. Until now, forecasts of wet snow avalanches are mainly done using weather data such as air and snow temperatures and incoming solar radiation. Even tough some wet snow avalanche events are indicated before the release by the formation of visible signs such as extension cracks or compressional bulges in the snow pack, a large number of wet snow avalanches are released without any previously visible signs. Continuous monitoring of critical slopes by terrestrial radar interferometry improves the scale of reception of differential movement into the range of millimetres per hour. Therefore, from a terrestrial and remote observation location, information on the mechanical state of the snow pack can be gathered on a slope wide scale. Recent campaigns in the Swiss Alps showed the potential of snow deformation measurements with a portable, interferometric real aperture radar operating at 17.2 GHz (1.76 cm wavelength). Common error sources for the radar interferometric measurement of snow pack displacements are decorrelation of the snow pack at different conditions, the influence of atmospheric disturbances on the interferometric phase and transition effects from cold/dry snow to warm/wet snow. Therefore, a critical assessment of those parameters has to be considered in order to reduce phase noise effects and retrieve accurate displacement measurements. The most recent campaign in spring 2015 took place in Davos Dorf/GR, Switzerland and its objective was to observe snow glide activity on the Dorfberg slope. A validation campaign using total station measurements showed good agreement to the radar interferometric line of sight displacement measurements in the range of 0.5 mm/h. The refinement of the method led to the detection of numerous gliding

Using Air Temperature to Quantitatively Predict the MODIS Fractional Snow Cover Retrieval Errors over the Continental US (CONUS)

NASA Technical Reports Server (NTRS)

Dong, Jiarui; Ek, Mike; Hall, Dorothy K.; Peters-Lidard, Christa; Cosgrove, Brian; Miller, Jeff; Riggs, George A.; Xia, Youlong

2013-01-01

In the middle to high latitude and alpine regions, the seasonal snow pack can dominate the surface energy and water budgets due to its high albedo, low thermal conductivity, high emissivity, considerable spatial and temporal variability, and ability to store and then later release a winters cumulative snowfall (Cohen, 1994; Hall, 1998). With this in mind, the snow drought across the U.S. has raised questions about impacts on water supply, ski resorts and agriculture. Knowledge of various snow pack properties is crucial for short-term weather forecasts, climate change prediction, and hydrologic forecasting for producing reliable daily to seasonal forecasts. One potential source of this information is the multi-institution North American Land Data Assimilation System (NLDAS) project (Mitchell et al., 2004). Real-time NLDAS products are used for drought monitoring to support the National Integrated Drought Information System (NIDIS) and as initial conditions for a future NCEP drought forecast system. Additionally, efforts are currently underway to assimilate remotely-sensed estimates of land-surface states such as snowpack information into NLDAS. It is believed that this assimilation will not only produce improved snowpack states that better represent snow evolving conditions, but will directly improve the monitoring of drought.

Effects of open-air temperature on air temperature inside biological safety cabinet.

PubMed

Umemura, Masayuki; Shigeno, Katsuro; Yamamura, Keiko; Osada, Takashi; Soda, Midori; Yamada, Kiyofumi; Ando, Yuichi; Wakiya, Yoshifumi

2011-02-14

In Japan, biological safety cabinets (BSCs) are normally used by medical staff while handling antineoplastic agents. We have also set up a class II B2 BSC at the Division of Chemotherapy for Outpatients. The air temperature inside this BSC, however, decreases in winter. We assumed that this decrease is caused by the intake of open-air. Therefore, we investigated the effects of low open-air temperature on the BSC temperature and the time of admixtures of antineoplastic agents. The studies were conducted from January 1 to March 31, 2008. The outdoor air temperature was measured in the shade near the intake nozzle of the BSC and was compared with the BSC temperature. The correlation between the outdoor air temperature and the BSC temperature, the dissolution time of cyclophosphamide (CPA) and gemcitabine (GEM), and accurate weight measurement of epirubicin (EPI) solution were investigated for low and normal BSC temperatures. The BSC temperature was correlated with the open-air temperature for open-air temperatures of 5-20°C (p < 0.0001). The dissolution of CPA and GEM at these temperatures was significantly delayed as compared to that at 25°C (p < 0.01 and p < 0.0001, respectively). The weight measurement of EPI solution using a syringe method lacks accuracy because of its high coefficient of viscosity at low temperatures (p < 0.01). These results suggest that the BSC temperature decreases below room temperature in winter when air is drawn from outdoors. We showed that the BSC temperature affects the dissolution rate of antineoplastic agents. Further, we suggested that the BSC temperature drop might delay the affair of the admixtures of antineoplastic agents and increase the waiting time of outpatients for chemotherapy.

A coupled melt-freeze temperature index approach in a one-layer model to predict bulk volumetric liquid water content dynamics in snow

NASA Astrophysics Data System (ADS)

Avanzi, Francesco; Yamaguchi, Satoru; Hirashima, Hiroyuki; De Michele, Carlo

2016-04-01

Liquid water in snow rules runoff dynamics and wet snow avalanches release. Moreover, it affects snow viscosity and snow albedo. As a result, measuring and modeling liquid water dynamics in snow have important implications for many scientific applications. However, measurements are usually challenging, while modeling is difficult due to an overlap of mechanical, thermal and hydraulic processes. Here, we evaluate the use of a simple one-layer one-dimensional model to predict hourly time-series of bulk volumetric liquid water content in seasonal snow. The model considers both a simple temperature-index approach (melt only) and a coupled melt-freeze temperature-index approach that is able to reconstruct melt-freeze dynamics. Performance of this approach is evaluated at three sites in Japan. These sites (Nagaoka, Shinjo and Sapporo) present multi-year time-series of snow and meteorological data, vertical profiles of snow physical properties and snow melt lysimeters data. These data-sets are an interesting opportunity to test this application in different climatic conditions, as sites span a wide latitudinal range and are subjected to different snow conditions during the season. When melt-freeze dynamics are included in the model, results show that median absolute differences between observations and predictions of bulk volumetric liquid water content are consistently lower than 1 vol%. Moreover, the model is able to predict an observed dry condition of the snowpack in 80% of observed cases at a non-calibration site, where parameters from calibration sites are transferred. Overall, the analysis show that a coupled melt-freeze temperature-index approach may be a valid solution to predict average wetness conditions of a snow cover at local scale.

Evaluation of snow cover and snow depth on the Qinghai-Tibetan Plateau derived from passive microwave remote sensing

NASA Astrophysics Data System (ADS)

Dai, Liyun; Che, Tao; Ding, Yongjian; Hao, Xiaohua

2017-08-01

Snow cover on the Qinghai-Tibetan Plateau (QTP) plays a significant role in the global climate system and is an important water resource for rivers in the high-elevation region of Asia. At present, passive microwave (PMW) remote sensing data are the only efficient way to monitor temporal and spatial variations in snow depth at large scale. However, existing snow depth products show the largest uncertainties across the QTP. In this study, MODIS fractional snow cover product, point, line and intense sampling data are synthesized to evaluate the accuracy of snow cover and snow depth derived from PMW remote sensing data and to analyze the possible causes of uncertainties. The results show that the accuracy of snow cover extents varies spatially and depends on the fraction of snow cover. Based on the assumption that grids with MODIS snow cover fraction > 10 % are regarded as snow cover, the overall accuracy in snow cover is 66.7 %, overestimation error is 56.1 %, underestimation error is 21.1 %, commission error is 27.6 % and omission error is 47.4 %. The commission and overestimation errors of snow cover primarily occur in the northwest and southeast areas with low ground temperature. Omission error primarily occurs in cold desert areas with shallow snow, and underestimation error mainly occurs in glacier and lake areas. With the increase of snow cover fraction, the overestimation error decreases and the omission error increases. A comparison between snow depths measured in field experiments, measured at meteorological stations and estimated across the QTP shows that agreement between observation and retrieval improves with an increasing number of observation points in a PMW grid. The misclassification and errors between observed and retrieved snow depth are associated with the relatively coarse resolution of PMW remote sensing, ground temperature, snow characteristics and topography. To accurately understand the variation in snow depth across the QTP, new algorithms

Climate warming enhances snow avalanche risk in the Western Himalayas

PubMed Central

Ballesteros-Cánovas, J. A.; Trappmann, D.; Madrigal-González, J.; Eckert, N.; Stoffel, M.

2018-01-01

Ongoing climate warming has been demonstrated to impact the cryosphere in the Indian Himalayas, with substantial consequences for the risk of disasters, human well-being, and terrestrial ecosystems. Here, we present evidence that the warming observed in recent decades has been accompanied by increased snow avalanche frequency in the Western Indian Himalayas. Using dendrogeomorphic techniques, we reconstruct the longest time series (150 y) of the occurrence and runout distances of snow avalanches that is currently available for the Himalayas. We apply a generalized linear autoregressive moving average model to demonstrate linkages between climate warming and the observed increase in the incidence of snow avalanches. Warming air temperatures in winter and early spring have indeed favored the wetting of snow and the formation of wet snow avalanches, which are now able to reach down to subalpine slopes, where they have high potential to cause damage. These findings contradict the intuitive notion that warming results in less snow, and thus lower avalanche activity, and have major implications for the Western Himalayan region, an area where human pressure is constantly increasing. Specifically, increasing traffic on a steadily expanding road network is calling for an immediate design of risk mitigation strategies and disaster risk policies to enhance climate change adaption in the wider study region. PMID:29535224

Simulating Snow in Canadian Boreal Environments with CLASS for ESM-SnowMIP

NASA Astrophysics Data System (ADS)

Wang, L.; Bartlett, P. A.; Derksen, C.; Ireson, A. M.; Essery, R.

2017-12-01

The ability of land surface schemes to provide realistic simulations of snow cover is necessary for accurate representation of energy and water balances in climate models. Historically, this has been particularly challenging in boreal forests, where poor treatment of both snow masking by forests and vegetation-snow interaction has resulted in biases in simulated albedo and snowpack properties, with subsequent effects on both regional temperatures and the snow albedo feedback in coupled simulations. The SnowMIP (Snow Model Intercomparison Project) series of experiments or `MIPs' was initiated in order to provide assessments of the performance of various snow- and land-surface-models at selected locations, in order to understand the primary factors affecting model performance. Here we present preliminary results of simulations conducted for the third such MIP, ESM-SnowMIP (Earth System Model - Snow Model Intercomparison Project), using the Canadian Land Surface Scheme (CLASS) at boreal forest sites in central Saskatchewan. We assess the ability of our latest model version (CLASS 3.6.2) to simulate observed snowpack properties (snow water equivalent, density and depth) and above-canopy albedo over 13 winters. We also examine the sensitivity of these simulations to climate forcing at local and regional scales.

Heterocyclic Aromatics in Petroleum Coke, Snow, Lake Sediments, and Air Samples from the Athabasca Oil Sands Region.

PubMed

Manzano, Carlos A; Marvin, Chris; Muir, Derek; Harner, Tom; Martin, Jonathan; Zhang, Yifeng

2017-05-16

The aromatic fractions of snow, lake sediment, and air samples collected during 2011-2014 in the Athabasca oil sands region were analyzed using two-dimensional gas chromatography following a nontargeted approach. Commonly monitored aromatics (parent and alkylated-polycyclic aromatic hydrocarbons and dibenzothiophenes) were excluded from the analysis, focusing mainly on other heterocyclic aromatics. The unknowns detected were classified into isomeric groups and tentatively identified using mass spectral libraries. Relative concentrations of heterocyclic aromatics were estimated and were found to decrease with distance from a reference site near the center of the developments and with increasing depth of sediments. The same heterocyclic aromatics identified in snow, lake sediments, and air were observed in extracts of delayed petroleum coke, with similar distributions. This suggests that petroleum coke particles are a potential source of heterocyclic aromatics to the local environment, but other oil sands sources must also be considered. Although the signals of these heterocyclic aromatics diminished with distance, some were detected at large distances (>100 km) in snow and surface lake sediments, suggesting that the impact of industry can extend >50 km. The list of heterocyclic aromatics and the mass spectral library generated in this study can be used for future source apportionment studies.

GPM Pre-Launch Algorithm Development for Physically-Based Falling Snow Retrievals

NASA Technical Reports Server (NTRS)

Jackson, Gail Skofronick; Tokay, Ali; Kramer, Anne W.; Hudak, David

2008-01-01

In this work we compare and correlate the long time series (Nov.-March) neasurements of precipitation rate from the Parsivels and 2DVD to the passive (89, 150, 183+/-1, +/-3, +/-7 GHz) observations of NOAA's AMSU-B radiometer. There are approximately 5-8 AMSU-B overpass views of the CARE site a day. We separate the comparisons into categories of no precipitation, liquid rain and falling snow precipitation. Scatterplots between the Parsivel snowfall rates and AMSU-B brightness temperatures (TBs) did not show an exploitable relationship for retrievals. We further compared and contrasted brightness temperatures to other surface measurements such as temperature and relative humidity with equally unsatisfying results. We found that there are similar TBs (especially at 89 and 150 GHz) for cases with falling snow and for non-precipitating cases. The comparisons indicate that surface emissivity contributions to the satellite observed TB over land can add uncertainty in detecting and estimating falling snow. The newest results show that the cloud icc scattering signal in the AMSU-B data call be detected by computing clear air TBs based on CARE radiosonde data and a rough estimate of surface emissivity. That is the differences in computed TI3 and AMSU-B TB for precipitating and nonprecipitating cases are unique such that the precipitating versus lon-precipitating cases can be identified. These results require that the radiosonde releases are within an hour of the AMSU-B data and allow for three surface types: no snow on the ground, less than 5 cm snow on the ground, and greater than 5 cm on the ground (as given by ground station data). Forest fraction and measured emissivities were combined to calculate the surface emissivities. The above work and future work to incorporate knowledge about falling snow retrievals into the framework of the expected GPM Bayesian retrievals will be described during this presentation.

Understanding atmospheric mercury speciation and mercury in snow over time at Alert, Canada

NASA Astrophysics Data System (ADS)

Steffen, A.; Bottenheim, J.; Cole, A.; Ebinghaus, R.; Lawson, G.; Leaitch, W. R.

2013-06-01

Ten years of atmospheric mercury speciation data and 14 yr of mercury in snow data from Alert, Nunavut, Canada are examined. The speciation data, collected from 2002 to 2011, includes gaseous elemental mercury (GEM), particulate mercury (PHg) and reactive gaseous mercury (RGM). During the winter-spring period of atmospheric mercury depletion events (AMDEs), when GEM is close to being completely depleted from the air, the concentrations of PHg and RGM rise significantly. During this period, the median concentrations for PHg is 28.2 pg m-3 and RGM is 23.9 pg m-3 from March to June in comparison to the annual median concentrations of 11.3 and 3.2 -3 for PHg and RGM, respectively. In each of the ten years of sampling, PHg increases steadily from January through March and is higher than RGM. This pattern begins to change in April with very high levels of PHg and increasing RGM. In May, RGM transitions to be significantly higher than PHg and continues into June whereas PHg sharply drops down. The transition is thought to be driven by a combination of air temperature and particle availability. Firstly, the ratio of PHg to RGM is favoured by low temperatures suggesting that oxidized mercury may partition to available particles to form PHg. Prior to the transition, the median air temperature is -24.8 °C and after the transition the median air temperature is -5.8 °C. Secondly, high aerosol levels in the spring are a strong driver for the high PHg concentrations. In February through April, partitioning of oxidized mercury to produce PHg was favoured by increased concentrations of particles that are principally the result of Arctic Haze and some sea salts. In the snow, the concentrations of mercury peak in May for all years. The highest deposition of mercury to the snow in the spring at Alert is during and after the transition of PHg to RGM in the atmosphere.

Observation of Snow cover glide on Sub-Alpine Coniferous Forests in Mount Zao, Northeastern Japan

NASA Astrophysics Data System (ADS)

Sasaki, A.; Suzuki, K.

2017-12-01

This is the study to clarify the snow cover glide behavior in the sub-alpine coniferous forests on Mount Zao, Northeastern Japan, in the winter of 2014-2015. We installed the glide-meter which is sled type, and measured the glide motion on the slope of Abies mariesii forest and its surrounding slope. In addition, we observed the air temperature, snow depth, density of snow, and snow temperature to discuss relationship between weather conditions and glide occurrence. The snow cover of the 2014-15 winter started on November 13th and disappeared on April 21st. The maximum snow depth was 242 cm thick, it was recorded at February 1st. The snow cover glide in the surrounding slope was occurred first at February 10th, although maximum snow depth recorded on February 1st. The glide motion in the surrounding slope is continuing and its velocity was 0.4 cm per day. The glide in the surrounding slope stopped at March 16th. The cumulative amount of the glide was 21.1 cm. The snow cover glide in the A. mariesii forest was even later occurred first at February 21st. The glide motion of it was intermittent and extremely small. On sub-alpine zone of Mount Zao, snow cover glide intensity is estimated to be 289 kg/m2 on March when snow water equivalent is maximum. At same period, maximum snow cover glide intensity is estimated to be about 1000 kg/m2 at very steep slopes where the slope angle is about 35 degree. Although potential of snow cover glide is enough high, the snow cover glide is suppressed by stem of A. mariesii trees, in the sub-alpine coniferous forest.

Survival of rapidly fluctuating natural low winter temperatures by High Arctic soil invertebrates.

PubMed

Convey, Peter; Abbandonato, Holly; Bergan, Frode; Beumer, Larissa Teresa; Biersma, Elisabeth Machteld; Bråthen, Vegard Sandøy; D'Imperio, Ludovica; Jensen, Christina Kjellerup; Nilsen, Solveig; Paquin, Karolina; Stenkewitz, Ute; Svoen, Mildrid Elvik; Winkler, Judith; Müller, Eike; Coulson, Stephen James

2015-12-01

The extreme polar environment creates challenges for its resident invertebrate communities and the stress tolerance of some of these animals has been examined over many years. However, although it is well appreciated that standard air temperature records often fail to describe accurately conditions experienced at microhabitat level, few studies have explicitly set out to link field conditions experienced by natural multispecies communities with the more detailed laboratory ecophysiological studies of a small number of 'representative' species. This is particularly the case during winter, when snow cover may insulate terrestrial habitats from extreme air temperature fluctuations. Further, climate projections suggest large changes in precipitation will occur in the polar regions, with the greatest changes expected during the winter period and, hence, implications for the insulation of overwintering microhabitats. To assess survival of natural High Arctic soil invertebrate communities contained in soil and vegetation cores to natural winter temperature variations, the overwintering temperatures they experienced were manipulated by deploying cores in locations with varying snow accumulation: No Snow, Shallow Snow (30 cm) and Deep Snow (120 cm). Air temperatures during the winter period fluctuated frequently between +3 and -24 °C, and the No Snow soil temperatures reflected this variation closely, with the extreme minimum being slightly lower. Under 30 cm of snow, soil temperatures varied less and did not decrease below -12 °C. Those under deep snow were even more stable and did not decline below -2 °C. Despite these striking differences in winter thermal regimes, there were no clear differences in survival of the invertebrate fauna between treatments, including oribatid, prostigmatid and mesostigmatid mites, Araneae, Collembola, Nematocera larvae or Coleoptera. This indicates widespread tolerance, previously undocumented for the Araneae, Nematocera or Coleoptera, of

The snowmaker: nature identical snow production in the laboratory

NASA Astrophysics Data System (ADS)

Schleef, S.; Jaggi, M.; Loewe, H.; Schneebeli, M.

2013-12-01

Using natural snow for laboratory experiments can be tricky due to shortage of winter periods and snowfall, difficulties of sample casting and transport, and the great variability of natural snow due to the varying conditions of crystal growth in the clouds. This hinders repeatable laboratory experiments with reproducible specimen and microstructural characteristics. To minimize experimental uncertainties we designed an improved machine called snowmaker, which enables us to produce nature-identical snow in a cold laboratory under well defined conditions. The snowmaker is based on well-known principles: warm humid air from a heated water basin is advected into a cold nucleation chamber where the vapor resublimates on stretched Nylon wires. Crystals are automatically harvested by a motor driven brush rack and collected in a box, thereby several kilograms of snow can be produced per day with minimum maintenance. The excess vapor is collected in a moisture trap to avoid frost in the laboratory. The entire construction is designed as a rolling, modular assembly system which can easily carried out of the laboratory for defrosting. In addition to previous attempts we focus on the reproducibility of the samples and the comparison to natural snow down to the microscale. We show that the settings of water temperature and cold laboratory temperature facilitates the production of different crystal shapes like dendrites and needles in a reproducible way. Besides photography, we analyzed the microstructure of snowmaker crystals in aggregated specimen by X-ray microtomography. Depending on the settings we can create reproducible samples with density of 50-170 kg/m3 and specific surface areas of 50-80 mm-1. We briefly touch similarities between artificial and natural snow samples with respect to crystal habit, microstructural parameters and short-time metamorphism.

On the formation of glide-snow avalanches

NASA Astrophysics Data System (ADS)

Mitterer, C.; Schweizer, J.

2012-12-01

On steep slopes the full snowpack can glide on the ground; tension cracks may open and eventually the slope may fail as a glide-snow avalanche. Due to their large mass they have considerable destructive potential. Glide-snow avalanches typically occur when the snow-soil interface is moist or wet so that basal friction is reduced. The occurrence, however, of glide cracks and their evolution to glide avalanches are still poorly understood. Consequently, glides are difficult to predict as (i) not all cracks develop into an avalanche, and (ii) for those that do, the time between crack opening and avalanche event might vary from hours to weeks - or on the other hand be so short that there is no warning at all by crack opening. To improve our understanding we monitored several slopes and related glide snow activity to meteorological data. In addition, we explored conditions that favor the formation of a thin wet basal snowpack layer with a physical-based model representing water and heat flux at the snow-soil interface. The statistical analyses revealed that glide-snow avalanche activity might be associated to an early season and a spring condition. While early season conditions tend to have warm and dry autumns followed by heavy snowfalls, spring conditions showed good agreement with increasing air temperature. The model indicates that energy (summer heat) stored in the ground might be sufficient to melt snow at the bottom of the snowpack. Due to capillary forces, water will rise for a few centimeters into the snowpack and thereby reduce friction at the interface. Alternatively, we demonstrate that also in the absence of melt water production at the bottom of the snowpack water may accumulate in the bottom layer due to an upward flux into the snowpack if a dry snowpack overlies a wet soil. The particular conditions that are obviously required at the snow-soil interface explain the strong winter-to-winter variations in snow gliding.

Normalized-Difference Snow Index (NDSI)

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.

2010-01-01

The Normalized-Difference Snow Index (NDSI) has a long history. 'The use of ratioing visible (VIS) and near-infrared (NIR) or short-wave infrared (SWIR) channels to separate snow and clouds was documented in the literature beginning in the mid-1970s. A considerable amount of work on this subject was conducted at, and published by, the Air Force Geophysics Laboratory (AFGL). The objective of the AFGL work was to discriminate snow cover from cloud cover using an automated algorithm to improve global cloud analyses. Later, automated methods that relied on the VIS/NIR ratio were refined substantially using satellite data In this section we provide a brief history of the use of the NDSI for mapping snow cover.

Minimum Temperatures, Diurnal Temperature Ranges and Temperature Inversions in Limestone Sinkholes of Different Sizes and Shapes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whiteman, Charles D.; Haiden, Thomas S.; Pospichal, Bernhard

2004-08-01

Air temperature data from five enclosed limestone sinkholes of various sizes and shapes on the 1300 m MSL Duerrenstein Plateau near Lunz, Austria have been analyzed to determine the effect of sinkhole geometry on temperature minima, diurnal temperature ranges, temperature inversion strengths and vertical temperature gradients. Data were analyzed for a non-snow-covered October night and for a snow-covered December night when the temperature fell as low as -28.5°C. Surprisingly, temperatures were similar in two sinkholes with very different drainage areas and depths. A three-layer model was used to show that the sky-view factor is the most important topographic parameter controllingmore » cooling for basins in this size range and that the cooling slows when net longwave radiation at the floor of the sinkhole is nearly balanced by the ground heat flux.« less

Comparison of Satellite-Derived and In-Situ Observations of Ice and Snow Surface Temperatures over Greenland

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Box, Jason E.; Casey, Kimberly A.; Hook, Simon J.; Shuman, Christopher A.; Steffen, Konrad

2008-01-01

The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

Decadal trend of precipitation and temperature patterns and impacts on snow-related variables in a semiarid region, Sierra Nevada, Spain.

NASA Astrophysics Data System (ADS)

José Pérez-Palazón, María; Pimentel, Rafael; Herrero, Javier; José Polo, María

2016-04-01

In the current context of global change, mountainous areas constitute singular locations in which these changes can be traced. Early detection of significant shifts of snow state variables in semiarid regions can help assess climate variability impacts and future snow dynamics in northern latitudes. The Sierra Nevada mountain range, in southern Spain, is a representative example of snow areas in Mediterranean-climate regions and both monitoring and modelling efforts have been performed to assess this variability and its significant scales. This work presents a decadal trend analysis throughout the 50-yr period 1960-2010 performed on some snow-related variables over Sierra Nevada, in Spain, which is included in the global climate change observatories network around the world. The study area comprises 4583 km2 distributed throughout the five head basins influenced by these mountains, with altitude values ranging from 140 to 3479 m.a.s.l., just 40 km from the Mediterranean coastline. Meteorological variables obtained from 44 weather stations from the National Meteorological Agency were studied and further used as input to the distributed hydrological model WiMMed (Polo et al., 2010), operational at the study area, to obtain selected snow variables. Decadal trends were obtained, together with their statistical significance, over the following variables, averaged over the whole study area: (1) annual precipitation; (2) annual snowfall; annual (3) mean, (4) maximum and (5) minimum daily temperature; annual (6) mean and (7) maximum daily fraction of snow covered areas; (8) annual number of days with snow cover; (9) mean and (10) maximum daily snow water equivalent; (11) annual number of extreme precipitation events; and (12) mean intensity of the annual extreme precipitation events. These variables were also studied over each of the five regions associated to each basin in the range. Globally decreasing decadal trends were obtained for all the meteorological variables

Testing Snow Melt Algorithms in High Relief Topography Using Calibrated Enhanced-Resolution Brightness Temperatures, Hunza River Basin, Pakistan

NASA Astrophysics Data System (ADS)

Ramage, J. M.; Brodzik, M. J.; Hardman, M.; Troy, T. J.

2017-12-01

Snow is a vital part of the terrestrial hydrological cycle, a crucial resource for people and ecosystems. In mountainous regions snow is extensive, variable, and challenging to document. Snow melt timing and duration are important factors affecting the transfer of snow mass to soil moisture and runoff. Passive microwave brightness temperature (Tb) changes at 36 and 18 GHz are a sensitive way to detect snow melt onset due to their sensitivity to the abrupt change in emissivity. They are widely used on large icefields and high latitude watersheds. The coarse resolution ( 25 km) of historically available data has precluded effective use in high relief, heterogeneous regions, and gaps between swaths also create temporal data gaps at lower latitudes. New enhanced resolution data products generated from a scatterometer image reconstruction for radiometer (rSIR) technique are available at the original frequencies. We use these Calibrated Enhanced-resolution Brightness (CETB) Temperatures Earth System Data Records (ESDR) to evaluate existing snow melt detection algorithms that have been used in other environments, including the cross polarized gradient ratio (XPGR) and the diurnal amplitude variations (DAV) approaches. We use the 36/37 GHz (3.125 km resolution) and 18/19 GHz (6.25 km resolution) vertically and horizontally polarized datasets from the Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Radiometer for EOS (AMSR-E) and evaluate them for use in this high relief environment. The new data are used to assess glacier and snow melt records in the Hunza River Basin [area 13,000 sq. km, located at 36N, 74E], a tributary to the Upper Indus Basin, Pakistan. We compare the melt timing results visually and quantitatively to the corresponding EASE-Grid 2.0 25-km dataset, SRTM topography, and surface temperatures from station and reanalysis data. The new dataset is coarser than the topography, but is able to differentiate signals of melt/refreeze timing for

A Physical Based Formula for Calculating the Critical Stress of Snow Movement

NASA Astrophysics Data System (ADS)

He, S.; Ohara, N.

2016-12-01

In snow redistribution modeling, one of the most important parameters is the critical stress of snow movement, which is difficult to estimate from field data because it is influenced by various factors. In this study, a new formula for calculating critical stress of snow movement was derived based on the ice particle sintering process modeling and the moment balance of a snow particle. Through this formula, the influences of snow particle size, air temperature, and deposited time on the critical stress were explicitly taken into consideration. It was found that some of the model parameters were sensitive to the critical stress estimation through the sensitivity analysis using Sobol's method. The two sensitive parameters of the sintering process modeling were determined by a calibration-validation procedure using the observed snow flux data via FlowCapt. Based on the snow flux and metrological data observed at the ISAW stations (http://www.iav.ch), it was shown that the results of this formula were able to describe very well the evolution of the minimum friction wind speed required for the snow motion. This new formula suggested that when the snow just reaches the surface, the smaller snowflake can move easier than the larger particles. However, smaller snow particles require more force to move as the sintering between the snowflakes progresses. This implied that compact snow with small snow particles may be harder to erode by wind although smaller particles may have a higher chance to be suspended once they take off.

Spatiotemporal Variations in the Difference between Satellite-observed Land Surface Temperature and Station-based Near-surface Air Temperature

NASA Astrophysics Data System (ADS)

Lian, X.

2016-12-01

There is an increasing demand to integrate land surface temperature (LST) into climate research due to its global coverage, which requires a comprehensive knowledge of its distinctive characteristics compared to near-surface air temperature ( ). Using satellite observations and in-situ station-based datasets, we conducted a global-scale assessment of the spatial, seasonal, and interannual variations in the difference between daytime maximum LST and daytime maximum ( , LST - ) during 2003-2014. Spatially, LST is generally higher than over arid and sparsely vegetated regions in the mid-low latitudes, but LST is lower than in the tropical rainforests due to strong evaporative cooling, and in the high-latitude regions due to snow-induced radiative cooling. Seasonally, is negative in tropical regions throughout the year, while it displays a pronounced seasonality in both the mid-latitudes and boreal regions. The seasonality in the mid-latitudes is a result of the asynchronous responses of LST and to the seasonal cycle of radiation and vegetation abundance, whereas in the boreal regions, seasonality is mainly caused by the change in snow cover. At an interannual scale, only a small proportion of the land surface displays a statistically significant trend (P <0.05) due to the short time span of current measurements. Our study identified substantial spatial heterogeneity and seasonality in , as well as its determinant environmental drivers, and thus provides a useful reference for monitoring near-surface temperature changes using remote sensing, particularly in remote regions.

Are there evidences of altitudinal effects of air temperature trends in the European Alps 1820-2013?

NASA Astrophysics Data System (ADS)

Schoener, W.; Auer, I.; Chimani, B.; Garnekind, M.; Haslinger, K.

2013-12-01

We use the HISTALP data set (www.zamg.ac.at/histalp) in order to assess the elevation dependency of air temperature trends within the European Alps. The evidence of altitudinal effects of the climate warming (with higher sensitivity of high mountain regions to warming) is a key statement, or at least key hypothesis, in many studies. The high relevance of such statement resp. hypothesis is obvious if one consider the impacts resulting from such fact, such as snow- and glacier melting and related effects for mountain hydrology. The HISTALP data set stands out with respect to its series lengths and its high level of homogenisation. Interestingly, the HISTALP temperature data show no clear altitudinal dependency of warming or cooling trends within the period 1820-2013. Additionally, a rather homogenous temporal trend could be observed within the entire Greater Alpine Region (GAR). Because HISTALP include also air pressure and vapour pressure series, we could compare our measured air temperatures with mean-column air temperatures, computed by the barometric formula, which were derived from the independently measured air pressure data (using vapour pressure to account for the atmospheric water content) at low resp. high elevations. Computed mean column temperatures are in good agreement with observed temperatures, indicating generally homogenous temporal temperature trend behaviour at different elevations. Our finding contradicts several results from climate modelling attempts and also other studies investigating Alpine temperature trends. We conclude that, whereas modelling results are still limited in the assessment of altitudinal effect of temperature trends from missing atmospheric processes captured by the models, the difference of the trend behaviour compared to other analyses of instrumental air temperatures comes from the seasonal base taken as the basis for trend estimation. It appears that opposite trend in spring and autumn for the period 1980

Drivers and environmental responses to the changing annual snow cycle of northern Alaska

USGS Publications Warehouse

Cox, Christopher J.; Stone, Robert S.; Douglas, David C.; Stanitski, Diane; Divoky, George J.; Dutton, Geoff S.; Sweeney, Colm; George, J. Craig; Longenecker, David U.

2017-01-01

On the North Slope of Alaska, earlier spring snowmelt and later onset of autumn snow accumulation are tied to atmospheric dynamics and sea ice conditions, and result in environmental responses.Linkages between atmospheric, ecological and biogeochemical variables in the changing Arctic are analyzed using long-term measurements near Utqiaġvik (formerly Barrow), Alaska. Two key variables are the date when snow disappears in spring, as determined primarily by atmospheric dynamics, precipitation, air temperature, winter snow accumulation and cloud cover, as well as the date of onset of snowpack in autumn that is additionally influenced by ocean temperature and sea ice extent. In 2015 and 2016 the snow melted early at Utqiaġvik due mainly to anomalous warmth during May of both years attributed to atmospheric circulation patterns, with 2016 having the record earliest snowmelt. These years are discussed in the context of a 115-year snowmelt record at Utqiaġvik with a trend toward earlier melting since the mid- 1970s (-2.86 days/decade, 1975-2016). At nearby Cooper Island, where a colony of seabirds, Black Guillemots, have been monitored since 1975, timing of egg laying is correlated with Utqiaġvik snowmelt with 2015 and 2016 being the earliest years in the 42-year record. Ice-out at a nearby freshwater lagoon is also correlated with Utqiaġvik snowmelt. The date when snow begins to accumulate in autumn at Utqiaġvik shows a trend towards later dates (+4.6 days/decade, 1975-2016), with 2016 the latest on record. The relationships between the lengthening snow-free season and regional phenology, soil temperatures, fluxes of gases from the tundra, and to regional sea ice conditions are discussed. Better understanding of these interactions is needed to predict the annual snow cycles in the region at seasonal to decadal scales, and to anticipate coupled environmental responses.

Seasonal Snow Extent and Snow Volume in South America Using SSM/I Passive Microwave Data

NASA Technical Reports Server (NTRS)

Foster, James L.; Chang, A. T. C.; Hall, D. K.; Kelly, R.; Houser, Paul (Technical Monitor)

2001-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Special Sensor Microwave Imagers (SSM/I) on board Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1992-1998, both snow cover extent and snow depth (snow mass) were investigated during the winter months (May-August) in the Patagonia region of Argentina. Since above normal temperatures in this region are typically above freezing, the coldest winter month was found to be not only the month having the most extensive snow cover but also the month having the deepest snows. For the seven-year period of this study, the average snow cover extent (May-August) was about 0.46 million sq km and the average monthly snow mass was about 1.18 x 10(exp 13) kg. July 1992 was the month having the greatest snow extent (nearly 0.8 million sq km) and snow mass (approximately 2.6 x 10(exp 13) kg).

Crowdsourcing urban air temperatures from smartphone battery temperatures

NASA Astrophysics Data System (ADS)

Overeem, Aart; Robinson, James C. R.; Leijnse, Hidde; Steeneveld, Gert-Jan; Horn, Berthold K. P.; Uijlenhoet, Remko

2014-05-01

Accurate air temperature observations in urban areas are important for meteorology and energy demand planning. They are indispensable to study the urban heat island effect and the adverse effects of high temperatures on human health. However, the availability of temperature observations in cities is often limited. Here we show that relatively accurate air temperature information for the urban canopy layer can be obtained from an alternative, nowadays omnipresent source: smartphones. In this study, battery temperatures were collected by an Android application for smartphones. It has been shown that a straightforward heat transfer model can be employed to estimate daily mean air temperatures from smartphone battery temperatures for eight major cities around the world. The results demonstrate the enormous potential of this crowdsourcing application for real-time temperature monitoring in densely populated areas. Battery temperature data were collected by users of an Android application for cell phones (opensignal.com). The application automatically sends battery temperature data to a server for storage. In this study, battery temperatures are averaged in space and time to obtain daily averaged battery temperatures for each city separately. A regression model, which can be related to a physical model, is employed to retrieve daily air temperatures from battery temperatures. The model is calibrated with observed air temperatures from a meteorological station of an airport located in or near the city. Time series of air temperatures are obtained for each city for a period of several months, where 50% of the data is for independent verification. The methodology has been applied to Buenos Aires, London, Los Angeles, Paris, Mexico City, Moscow, Rome, and Sao Paulo. The evolution of the retrieved air temperatures often correspond well with the observed ones. The mean absolute error of daily air temperatures is less than 2 degrees Celsius, and the bias is within 1 degree

Shrub canopies influence soil temperatures but not nutrient dynamics: An experimental test of tundra snow-shrub interactions.

PubMed

Myers-Smith, Isla H; Hik, David S

2013-10-01

Shrubs are the largest plant life form in tundra ecosystems; therefore, any changes in the abundance of shrubs will feedback to influence biodiversity, ecosystem function, and climate. The snow-shrub hypothesis asserts that shrub canopies trap snow and insulate soils in winter, increasing the rates of nutrient cycling to create a positive feedback to shrub expansion. However, previous work has not been able to separate the abiotic from the biotic influences of shrub canopies. We conducted a 3-year factorial experiment to determine the influences of canopies on soil temperatures and nutrient cycling parameters by removing ∼0.5 m high willow (Salix spp.) and birch (Betula glandulosa) shrubs, creating artificial shrub canopies and comparing these manipulations to nearby open tundra and shrub patches. Soil temperatures were 4-5°C warmer in January, and 2°C cooler in July under shrub cover. Natural shrub plots had 14-33 cm more snow in January than adjacent open tundra plots. Snow cover and soil temperatures were similar in the manipulated plots when compared with the respective unmanipulated treatments, indicating that shrub canopy cover was a dominant factor influencing the soil thermal regime. Conversely, we found no strong evidence of increased soil decomposition, CO2 fluxes, or nitrate or ammonia adsorbtion under artificial shrub canopy treatments when compared with unmanipulated open tundra. Our results suggest that the abiotic influences of shrub canopy cover alone on nutrient dynamics are weaker than previously asserted.

CO2 flux over young and snow-covered Arctic pack ice in winter and spring

NASA Astrophysics Data System (ADS)

Nomura, Daiki; Granskog, Mats A.; Fransson, Agneta; Chierici, Melissa; Silyakova, Anna; Ohshima, Kay I.; Cohen, Lana; Delille, Bruno; Hudson, Stephen R.; Dieckmann, Gerhard S.

2018-06-01

Rare CO2 flux measurements from Arctic pack ice show that two types of ice contribute to the release of CO2 from the ice to the atmosphere during winter and spring: young, thin ice with a thin layer of snow and older (several weeks), thicker ice with thick snow cover. Young, thin sea ice is characterized by high salinity and high porosity, and snow-covered thick ice remains relatively warm ( > -7.5 °C) due to the insulating snow cover despite air temperatures as low as -40 °C. Therefore, brine volume fractions of these two ice types are high enough to provide favorable conditions for gas exchange between sea ice and the atmosphere even in mid-winter. Although the potential CO2 flux from sea ice decreased due to the presence of the snow, the snow surface is still a CO2 source to the atmosphere for low snow density and thin snow conditions. We found that young sea ice that is formed in leads without snow cover produces CO2 fluxes an order of magnitude higher than those in snow-covered older ice (+1.0 ± 0.6 mmol C m-2 day-1 for young ice and +0.2 ± 0.2 mmol C m-2 day-1 for older ice).

Macroscopic modeling of heat and water vapor transfer with phase change in dry snow based on an upscaling method: Influence of air convection

NASA Astrophysics Data System (ADS)

Calonne, N.; Geindreau, C.; Flin, F.

2015-12-01

At the microscopic scale, i.e., pore scale, dry snow metamorphism is mainly driven by the heat and water vapor transfer and the sublimation-deposition process at the ice-air interface. Up to now, the description of these phenomena at the macroscopic scale, i.e., snow layer scale, in the snowpack models has been proposed in a phenomenological way. Here we used an upscaling method, namely, the homogenization of multiple-scale expansions, to derive theoretically the macroscopic equivalent modeling of heat and vapor transfer through a snow layer from the physics at the pore scale. The physical phenomena under consideration are steady state air flow, heat transfer by conduction and convection, water vapor transfer by diffusion and convection, and phase change (sublimation and deposition). We derived three different macroscopic models depending on the intensity of the air flow considered at the pore scale, i.e., on the order of magnitude of the pore Reynolds number and the Péclet numbers: (A) pure diffusion, (B) diffusion and moderate convection (Darcy's law), and (C) strong convection (nonlinear flow). The formulation of the models includes the exact expression of the macroscopic properties (effective thermal conductivity, effective vapor diffusion coefficient, and intrinsic permeability) and of the macroscopic source terms of heat and vapor arising from the phase change at the pore scale. Such definitions can be used to compute macroscopic snow properties from 3-D descriptions of snow microstructures. Finally, we illustrated the precision and the robustness of the proposed macroscopic models through 2-D numerical simulations.

Snow hydrology in a general circulation model

NASA Technical Reports Server (NTRS)

Marshall, Susan; Roads, John O.; Glatzmaier, Gary

1994-01-01

A snow hydrology has been implemented in an atmospheric general circulation model (GCM). The snow hydrology consists of parameterizations of snowfall and snow cover fraction, a prognostic calculation of snow temperature, and a model of the snow mass and hydrologic budgets. Previously, only snow albedo had been included by a specified snow line. A 3-year GCM simulation with this now more complete surface hydrology is compared to a previous GCM control run with the specified snow line, as well as with observations. In particular, the authors discuss comparisons of the atmospheric and surface hydrologic budgets and the surface energy budget for U.S. and Canadian areas. The new snow hydrology changes the annual cycle of the surface moisture and energy budgets in the model. There is a noticeable shift in the runoff maximum from winter in the control run to spring in the snow hydrology run. A substantial amount of GCM winter precipitation is now stored in the seasonal snowpack. Snow cover also acts as an important insulating layer between the atmosphere and the ground. Wintertime soil temperatures are much higher in the snow hydrology experiment than in the control experiment. Seasonal snow cover is important for dampening large fluctuations in GCM continental skin temperature during the Northern Hemisphere winter. Snow depths and snow extent show good agreement with observations over North America. The geographic distribution of maximum depths is not as well simulated by the model due, in part, to the coarse resolution of the model. The patterns of runoff are qualitatively and quantitatively similar to observed patterns of streamflow averaged over the continental United States. The seasonal cycles of precipitation and evaporation are also reasonably well simulated by the model, although their magnitudes are larger than is observed. This is due, in part, to a cold bias in this model, which results in a dry model atmosphere and enhances the hydrologic cycle everywhere.

Altitude-dependent influence of snow cover on alpine land surface phenology

NASA Astrophysics Data System (ADS)

Xie, Jing; Kneubühler, Mathias; Garonna, Irene; Notarnicola, Claudia; De Gregorio, Ludovica; De Jong, Rogier; Chimani, Barbara; Schaepman, Michael E.

2017-05-01

Snow cover impacts alpine land surface phenology in various ways, but our knowledge about the effect of snow cover on alpine land surface phenology is still limited. We studied this relationship in the European Alps using satellite-derived metrics of snow cover phenology (SCP), namely, first snow fall, last snow day, and snow cover duration (SCD), in combination with land surface phenology (LSP), namely, start of season (SOS), end of season, and length of season (LOS) for the period of 2003-2014. We tested the dependency of interannual differences (Δ) of SCP and LSP metrics with altitude (up to 3000 m above sea level) for seven natural vegetation types, four main climatic subregions, and four terrain expositions. We found that 25.3% of all pixels showed significant (p < 0.05) correlation between ΔSCD and ΔSOS and 15.3% between ΔSCD and ΔLOS across the entire study area. Correlations between ΔSCD and ΔSOS as well as ΔSCD and ΔLOS are more pronounced in the northern subregions of the Alps, at high altitudes, and on north and west facing terrain—or more generally, in regions with longer SCD. We conclude that snow cover has a greater effect on alpine phenology at higher than at lower altitudes, which may be attributed to the coupled influence of snow cover with underground conditions and air temperature. Alpine ecosystems may therefore be particularly sensitive to future change of snow cover at high altitudes under climate warming scenarios.

High frequency acoustic reflections from an air-snow interface

NASA Astrophysics Data System (ADS)

Courville, Z.; Albert, D. G.; Lieb-Lappen, R.; Fegyveresi, J. M.

2016-12-01

High frequency wave propagation methods can be used to determine in situ near surface micro-pore geometry parameters in real Earth materials including snow. To this end, we have been developing a portable ultrasonic transducer rig to make measurements of acoustic reflections from a variety of natural porous media. Fresh natural snow, in particular, is a difficult material to characterize, as any mechanical interaction is likely to damage the fragile pores and grain bonds. Because acoustic waves are sensitive to the porous material properties, they potentially can be used to measure snow properties in a non-destructive manner. Such methods have already been demonstrated on cohesive porous materials including manufactured foams, porous metals, and sintered glass beads. We conducted high frequency, oblique-angle and near vertical reflection measurements on snow samples in a cold room. We then compare the acoustically derived snow physical parameters, including porosity, with values determined from micro-computed tomography (μCT) and with standard (but destructive) laboratory measurements. Preliminary results using a manufactured open cell foam following previous work by Fellah et al., (2003) shows very good agreement between values of porosity determined from the acoustic measurements and the values determined from μCT image analysis and gravimetric determination. Similarly, preliminary results comparing acoustic measurements of natural, dry snow samples prepared in the laboratory show good agreement between acoustically-derived porosity values and porosity values derived through independent means. Fellah, Z.E.A., S. Berger, W. Lauriks, C. Depollier, C. Aristegui, and J.Y. Chapelon, (2003b), Measuring the porosity and tortuosity of porous materials via reflected waves at oblique incidence, J. Acous. Soc. Am., 113, 2424-2433.

Snow in Time for the Solstice

NASA Technical Reports Server (NTRS)

2004-01-01

In mid-December, the weather in eastern North America cooperated with the calendar, and a wintry blast from the Arctic delivered freezing cold air, blustery winds, and snow just in time for the Winter Solstice on December 21' the Northern Hemisphere's longest night of the year and the official start of winter. This image was captured by the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) on December 20, 2004, the day after an Arctic storm dove down into the United States, bringing snow to New England (upper right of top image); the coastal mid-Atlantic, including Washington, D.C.; and the southern Appalachian Mountains in Tennessee and North Carolina. Over the Atlantic Ocean (image right), the fierce Arctic winds were raking the clouds into rows, like a gardener getting ready to plant the seeds of winter. The detailed close-up at the bottom of this image pair shows the cloud and snow patterns around Lake Ontario, illustrating the occurrence of 'lake-effect snow.' Areas in western upstate New York often get as much as fifteen feet or more of snow each year as cold air from Canada and the Arctic sweeps down over the relatively warm waters of Lakes Ontario and Erie. Cold air plus moisture from the lakes equals heavy snow. Since the wind generally blows from west to east, it is the 'downwind' cities like Buffalo and Rochester that receive the heaping helpings of snowfall, while cities on the upwind side of the lake, such as Toronto, receive much less. Unlike storms that begin with specific low-pressure systems in the Pacific Ocean and march eastward across the Pacific Northwest, the Rockies, the Great Plains, and sometimes the East, the lake-effect snows aren't tied to a specific atmospheric disturbance. They are more a function of geography, which means that the lakes can keep fueling snow storms for as long as they remain ice-free in early winter, as well as when they begin to thaw in late winter and early spring. Image courtesy the SeaWiFS Project, NASA

A model of the planetary boundary layer over a snow surface

NASA Technical Reports Server (NTRS)

Halberstam, I.; Melendez, R.

1979-01-01

A model of the planetary boundary layer over a snow surface has been developed. It contains the vertical heat exchange processes due to radiation, conduction, and atmospheric turbulence. Parametrization of the boundary layer is based on similarity functions developed by Hoffert and Sud (1976), which involve a dimensionless variable, dependent on boundary-layer height and a localized Monin-Obukhov length. The model also contains the atmospheric surface layer and the snowpack itself, where snowmelt and snow evaporation are calculated. The results indicate a strong dependence of surface temperatures, especially at night, on the bursts of turbulence which result from the frictional damping of surface-layer winds during periods of high stability, as described by Businger (1973). The model also shows the cooling and drying effect of the snow on the atmosphere, which may be the mechanism for air mass transformation in sub-Arctic regions.

Effects of soot-induced snow albedo change on snowpack and hydrological cycle in western U.S. based on WRF chemistry and regional climate simulations

NASA Astrophysics Data System (ADS)

Qian, Y.; Gustafson, W. I.; Leung, R.; Ghan, S. J.

2008-12-01

Radiative forcing induced by soot on snow is an important anthropogenic forcing affecting the global climate. In this study we simulated the deposition of soot aerosol on snow and the resulting impact on snowpack and the hydrological cycle in the western United States. A yearlong simulation was performed using the chemistry version of the Weather Research and Forecasting model (WRF-Chem) to determine the soot deposition, followed by three simulations using WRF in meteorology-only mode, with and without the soot-induced snow albedo perturbations. The chemistry simulation shows large spatial variability in soot deposition that reflects the localized emissions and the influence of the complex terrain. The soot-induced snow albedo perturbations increase the surface net solar radiation flux during late winter to early spring, increase the surface air temperature, and reduce the snow accumulation and spring snowmelt. These effects are stronger over the central Rockies and southern Alberta, where soot deposition and snowpack overlap the most. The indirect forcing of soot accelerates snowmelt and alters stream flows, including a trend toward earlier melt dates in the western United States. The soot-induced albedo reduction initiates a positive feedback process whereby dirty snow absorbs more solar radiation, heating the surface and warming the air. This warming causes reduced snow depth and fraction, which further reduces the regional surface albedo for the snow covered regions. For a doubled snow albedo perturbation, the change to surface energy and temperature is around 50-80%, however, snowpack reduction is nonlinearly accelerated.

Radiative transfer model of snow for bare ice regions

NASA Astrophysics Data System (ADS)

Tanikawa, T.; Aoki, T.; Niwano, M.; Hosaka, M.; Shimada, R.; Hori, M.; Yamaguchi, S.

2016-12-01

Modeling a radiative transfer (RT) for coupled atmosphere-snow-bare ice systems is of fundamental importance for remote sensing applications to monitor snow and bare ice regions in the Greenland ice sheet and for accurate climate change predictions by regional and global climate models. Recently, the RT model for atmosphere-snow system was implemented for our regional and global climate models. However, the bare ice region where recently it has been expanded on the Greenland ice sheet due to the global warming, has not been implemented for these models, implying that this region leads miscalculations in these climate models. Thus, the RT model of snow for bare ice regions is needed for accurate climate change predictions. We developed the RT model for coupled atmosphere-snow-bare ice systems, and conducted a sensitivity analysis of the RT model to know the effect of snow, bare ice and geometry parameters on the spectral radiant quantities. The RT model considers snow and bare-ice inherent optical properties (IOPs), including snow grain size, air bubble size and its concentration and bare ice thickness. The conventional light scattering theory, Mie theory, was used for IOP calculations. Monte Carlo method was used for the multiple scattering. The sensitivity analyses showed that spectral albedo for the bare ice increased with increasing the concentration of the air bubble in the bare ice for visible wavelengths because the air bubble is scatterer with no absorption. For near infrared wavelengths, spectral albedo has no dependence on the air bubble due to the strong light absorption by ice. When increasing solar zenith angle, the spectral albedo were increased for all wavelengths. This is the similar trend with spectral snow albedo. Cloud cover influenced the bare ice spectral albedo by covering direct radiation into diffuse radiation. The purely diffuse radiation has an effective solar zenith angle near 50°. Converting direct into diffuse radiation reduces the

From the clouds to the ground - snow precipitation patterns vs. snow accumulation patterns

NASA Astrophysics Data System (ADS)

Gerber, Franziska; Besic, Nikola; Mott, Rebecca; Gabella, Marco; Germann, Urs; Bühler, Yves; Marty, Mauro; Berne, Alexis; Lehning, Michael

2017-04-01

Knowledge about snow distribution and snow accumulation patterns is important and valuable for different applications such as the prediction of seasonal water resources or avalanche forecasting. Furthermore, accumulated snow on the ground is an important ground truth for validating meteorological and climatological model predictions of precipitation in high mountains and polar regions. Snow accumulation patterns are determined by many different processes from ice crystal nucleation in clouds to snow redistribution by wind and avalanches. In between, snow precipitation undergoes different dynamical and microphysical processes, such as ice crystal growth, aggregation and riming, which determine the growth of individual particles and thereby influence the intensity and structure of the snowfall event. In alpine terrain the interaction of different processes and the topography (e.g. lifting condensation and low level cloud formation, which may result in a seeder-feeder effect) may lead to orographic enhancement of precipitation. Furthermore, the redistribution of snow particles in the air by wind results in preferential deposition of precipitation. Even though orographic enhancement is addressed in numerous studies, the relative importance of micro-physical and dynamically induced mechanisms on local snowfall amounts and especially snow accumulation patterns is hardly known. To better understand the relative importance of different processes on snow precipitation and accumulation we analyze snowfall and snow accumulation between January and March 2016 in Davos (Switzerland). We compare MeteoSwiss operational weather radar measurements on Weissfluhgipfel to a spatially continuous snow accumulation map derived from airborne digital sensing (ADS) snow height for the area of Dischma valley in the vicinity of the weather radar. Additionally, we include snow height measurements from automatic snow stations close to the weather radar. Large-scale radar snow accumulation

Comparison of AMSR-E and SSM/I snow parameter retrievals over the Ob river basin

USGS Publications Warehouse

Mognard, N.M.; Grippa, M.; LeToan, T.; Kelly, R.E.J.; Chang, A.T.C.; Josberger, E.G.

2004-01-01

Passive microwave observations from the Advanced Microwave Scanning Radiometer - EOS (AMSR-E) and from the Special Sensor Microwave Imager (SSM/I) are used to analyse the evolution of the snow pack in the Ob river basin during the snow season of 2002-03. The Ob river is the biggest Russian river with respect to its watershed area (2 975 000 km2). The Ob originates in the Altai mountains and flows northward across the vast West Siberian lowland towards the Arctic Ocean. The majority of snow cover is contained in the lowlands rather than in mountainous regions and persists for six months or more. During the snow season, surface air temperatures are very cold. Therefore, the combination of cold dry snow and large areas of uniform topography is ideal for snowpack extent and water equivalent retrievals from passive microwave observations. The thermal gradient through the snow pack is estimated and used to model the growth of the snow grain size and to compute the evolution of the passive microwave derived snow depth over the region. A comparison between the AMSR-E and SSM/I estimates is performed and the differences between the snow parameters from the two satellite instruments are analysed.

[Characteristics of evaporation over broadleaved Korean pine forest in Changbai Mountains, Northeast China during snow cover period in winter].

PubMed

Li, Hui-dong; Guan, De-xin; Wang, An-zhi; Wu, Jia-Bing; Jin, Chang-jie; ShiI, Ting-ting

2013-04-01

Based on the measurement data of water vapor flux by open-path eddy covariance system and of the micrometeorological factors in broad-leaved Korean pine forest in Changbai Mountains during the snow cover period from 2002 to 2005, this paper analyzed the dynamics of snow cover evaporation and the relationships between the evaporation and meteorological factors. The energy balanced ratio during the snow cover period was 79. 9% , and the latent heat flux accounted for 21. 4% of net radiation. The diurnal variation of the evaporation presented a single-peak curve, and the evaporation rate during snow-melting period was higher than that during stable snow cover period. The half-hour evaporation presented liner relationship with net radiation and quadratic relationship with air temperature. The daily evaporation presented quadratic relationship with net radiation and exponential relationship with air temperature. The daily evaporation presented a dynamic trend of decreasing-stable-increasing, with the maximum at increasing stage and the minimum at stable stage. The maximum value of the daily evaporation was 0.73 mm d-1, and the minimum value was 0. 004 mm d-1. During the snow cover periods of 2002-2003, 2003-2004 and 2004-2005, the annual evaporation was 27.6, 25.5, and 22.9 mm, accounting for 37.9% , 19.5% , and 30. 0% of the precipitation in the same periods, respectively. The mean value of the daily evaporation in the three periods was 0. 17, 0. 19, and 0. 17 mm d-1, respectively.

MODIS Snow and Ice Production

NASA Technical Reports Server (NTRS)

Hall, Dorthoy K.; Hoser, Paul (Technical Monitor)

2002-01-01

Daily, global snow cover maps, and sea ice cover and sea ice surface temperature (IST) maps are derived from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS), are available at no cost through the National Snow and Ice Data Center (NSIDC). Included on this CD-ROM are samples of the MODIS snow and ice products. In addition, an animation, done by the Scientific Visualization studio at Goddard Space Flight Center, is also included.

Snow distribution and heat flow in the taiga

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sturm, M.

1992-05-01

The trees of the taiga intercept falling snow and cause it to become distributed in an uneven fashion. Around aspen and birch, cone-shaped accumulations form. Beneath large spruce trees, the snow cover is depleted, forming a bowl-shaped depression called a tree well. Small spruce trees become covered with snow, creating cavities that funnel cold air to the snow/ground interface. The depletion of snow under large spruce trees results in greater heat loss from the ground. A finite difference model suggests that heat flow from tree wells can be more than twice that of undisturbed snow. In forested watersheds, this increasemore » can be a significant percentage of the total winter energy exchange.« less

Spatiotemporal variability of snow depth across the Eurasian continent from 1966 to 2012

NASA Astrophysics Data System (ADS)

Zhong, Xinyue; Zhang, Tingjun; Kang, Shichang; Wang, Kang; Zheng, Lei; Hu, Yuantao; Wang, Huijuan

2018-01-01

Snow depth is one of the key physical parameters for understanding land surface energy balance, soil thermal regime, water cycle, and assessing water resources from local community to regional industrial water supply. Previous studies by using in situ data are mostly site specific; data from satellite remote sensing may cover a large area or global scale, but uncertainties remain large. The primary objective of this study is to investigate spatial variability and temporal change in snow depth across the Eurasian continent. Data used include long-term (1966-2012) ground-based measurements from 1814 stations. Spatially, long-term (1971-2000) mean annual snow depths of >20 cm were recorded in northeastern European Russia, the Yenisei River basin, Kamchatka Peninsula, and Sakhalin. Annual mean and maximum snow depth increased by 0.2 and 0.6 cm decade-1 from 1966 through 2012. Seasonally, monthly mean snow depth decreased in autumn and increased in winter and spring over the study period. Regionally, snow depth significantly increased in areas north of 50° N. Compared with air temperature, snowfall had greater influence on snow depth during November through March across the former Soviet Union. This study provides a baseline for snow depth climatology and changes across the Eurasian continent, which would significantly help to better understanding climate system and climate changes on regional, hemispheric, or even global scales.

Photochemical degradation of PCBs in snow.

PubMed

Matykiewiczová, Nina; Klánová, Jana; Klán, Petr

2007-12-15

This work represents the first laboratory study known to the authors describing photochemical behavior of persistent organic pollutants in snow at environmentally relevant concentrations. The snow samples were prepared by shock freezing of the corresponding aqueous solutions in liquid nitrogen and were UV-irradiated in a photochemical cold chamber reactor at -25 degrees C, in which simultaneous monitoring of snow-air exchange processeswas also possible. The main photodegradation pathway of two model snow contaminants, PCB-7 and PCB-153 (c approximately 100 ng kg(-1)), was found to be reductive dehalogenation. Possible involvement of the water molecules of snow in this reaction has been excluded by performing the photolyses in D2O snow. Instead, trace amounts of volatile organic compounds have been proposed to be the major source of hydrogen atom in the reduction, and this hypothesis was confirmed by the experiments with deuterated organic cocontaminants, such as d6-ethanol or d8-tetrahydrofuran. It is argued that bimolecular photoreduction of PCBs was more efficient or feasible than any other phototransformations under the experimental conditions used, including the coupling reactions. The photodegradation of PCBs, however, competed with a desorption process responsible for the pollutant loss from the snow samples, especially in case of lower molecular-mass congeners. Organic compounds, apparently largely located or photoproduced on the surface of snow crystals, had a predisposition to be released to the air but, at the same time, to react with other species in the gas phase. It is concluded that physicochemical properties of the contaminants and trace co-contaminants, their location and local concentrations in the matrix, and the wavelength and intensity of radiation are the most important factors in the evaluation of organic contaminants' lifetime in snow. Based on the results, it has been estimated that the average lifetime of PCBs in surface snow, connected

Saharan dust particles in snow samples of Alps and Apennines during an exceptional event of transboundary air pollution.

PubMed

Telloli, Chiara; Chicca, Milvia; Pepi, Salvatore; Vaccaro, Carmela

2017-12-21

Southern European countries are often affected in summer by transboundary air pollution from Saharan dust. However, very few studies deal with Saharan dust pollution at high altitudes in winter. In Italy, the exceptional event occurred on February 19, 2014, colored in red the entire mountain range (Alps and Apennines) and allowed to characterize the particulate matter deposited on snow from a morphological and chemical point of view. Snow samples were collected after this event in four areas in the Alps and one in the Apennines. The particulate matter of the melted snow samples was analyzed by scanning electron microscopy with energy dispersive X-ray spectrometry (SEM-EDS) and by inductively coupled plasma mass spectrometry (ICP-MS). These analyses confirmed the presence of Saharan dust particle components in all areas with similar percentages, supported also by the positive correlations between Mg-Ca, Al-Ca, Al-Mg, and Al-K in all samples.

Variation in Rising Limb of Colorado River Snowmelt Runoff Hydrograph Controlled by Dust Radiative Forcing in Snow

NASA Astrophysics Data System (ADS)

Painter, Thomas H.; Skiles, S. McKenzie; Deems, Jeffrey S.; Brandt, W. Tyler; Dozier, Jeff

2018-01-01

Common practice and conventional wisdom hold that fluctuations in air temperature control interannual variability in snowmelt and subsequent river runoff. However, recent observations in the Upper Colorado River Basin confirm that net solar radiation and by extension radiative forcing by dust deposited on snow cover exerts the primary forcing on snowmelt. We show that the variation in the shape of the rising limb of the annual hydrograph is controlled by variability in dust radiative forcing and surprisingly is independent of variations in winter and spring air temperatures. These observations suggest that hydroclimatic modeling must be improved to account for aerosol forcings of the water cycle. Anthropogenic climate change will likely reduce total snow accumulations and cause snowmelt runoff to occur earlier. However, dust radiative forcing of snowmelt is likely consuming important adaptive capacity that would allow human and natural systems to be more resilient to changing hydroclimatic conditions.

MODIS Snow and Sea Ice Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.

2004-01-01

In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow and sea ice products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and Ice Data Center at various resolutions and on different grids useful for different communities Snow products include binary snow cover, snow albedo, and in the near future, fraction of snow in a 5OO-m pixel. Sea ice products include ice extent determined with two different algorithms, and sea ice surface temperature. The algorithms used to develop these products are described. Both the snow and sea ice products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.

Snow model design for operational purposes

NASA Astrophysics Data System (ADS)

Kolberg, Sjur

2017-04-01

A parsimonious distributed energy balance snow model intended for operational use is evaluated using discharge, snow covered area and grain size; the latter two as observed from the MODIS sensor. The snow model is an improvement of the existing GamSnow model, which is a part of the Enki modelling framework. Core requirements for the new version have been: 1. Reduction of calibration freedom, motivated by previous experience of non-identifiable parameters in the existing version 2. Improvement of process representation based on recent advances in physically based snow modelling 3. Limiting the sensitivity to forcing data which are poorly known over the spatial domain of interest (often in mountainous areas) 4. Preference for observable states, and the ability to improve from updates. The albedo calculation is completely revised, now based on grain size through an emulation of the SNICAR model (Flanner and Zender, 2006; Gardener and Sharp, 2010). The number of calibration parameters in the albedo model is reduced from 6 to 2. The wind function governing turbulent energy fluxes has been reduced from 2 to 1 parameter. Following Raleigh et al (2011), snow surface radiant temperature is split from the top layer thermodynamic temperature, using bias-corrected wet-bulb temperature to model the former. Analyses are ongoing, and the poster will bring evaluation results from 16 years of MODIS observations and more than 25 catchments in southern Norway.

Improved quantification of mountain snowpack properties using observations from Unmanned Air Vehicles (UAVs)

NASA Astrophysics Data System (ADS)

Shea, J. M.; Harder, P.; Pomeroy, J. W.; Kraaijenbrink, P. D. A.

2017-12-01

Mountain snowpacks represent a critical seasonal reservoir of water for downstream needs, and snowmelt is a significant component of mountain hydrological budgets. Ground-based point measurements are unable to describe the full spatial variability of snow accumulation and melt rates, and repeat Unmanned Air Vehicle (UAV) surveys provide an unparalleled opportunity to measure snow accumulation, redistribution and melt in alpine environments. This study presents results from a UAV-based observation campaign conducted at the Fortress Mountain Snow Laboratory in the Canadian Rockies in 2017. Seven survey flights were conducted between April (maximum snow accumulation) and mid-July (bare ground) to collect imagery with both an RGB camera and thermal infrared imager with the sensefly eBee RTK platform. UAV imagery are processed with structure from motion techniques, and orthoimages, digital elevation models, and surface temperature maps are validated against concurrent ground observations of snow depth, snow water equivalent, and snow surface temperature. We examine the seasonal evolution of snow depth and snow surface temperature, and explore the spatial covariances of these variables with respect to topographic factors and snow ablation rates. Our results have direct implications for scaling snow ablation calculations and model resolution and discretization.

Polarization signatures and brightness temperatures caused by horizontally oriented snow particles at microwave bands: Effects of atmospheric absorption

NASA Astrophysics Data System (ADS)

Xie, Xinxin; Crewell, Susanne; Löhnert, Ulrich; Simmer, Clemens; Miao, Jungang

2015-06-01

This study analyzes the effects of atmospheric absorption and emission on the polarization difference (PD) and brightness temperature (TB) generated by horizontally oriented snow particles. A three-layer plane-parallel atmosphere model is used in conjunction with a simplified radiative transfer (RT) scheme to illustrate the combined effects of dichroic and nondichroic media on microwave signatures observed by ground-based and spaceborne sensors. Based on idealized scenarios which encompass a dichroic snow layer and adjacent nondichroic layers composed of supercooled liquid water (SCLW) droplets and water vapor, we demonstrate that the presence of atmospheric absorption/emission enhances TB and damps PD when observed from the ground. From a spaceborne perspective, however, TB can be reduced or enhanced by an absorbing/emitting layer above the snow layer, while a strong absorbing/emitting layer below the dichroic snow layer may even enhance PD. The induced PD and TB, which rely on snow microphysical assumptions, can vary up to 2 K and 10 K, respectively, due to the temperature-dependent absorption of SCLW. RT calculations based on 223 snowfall profiles selected from European Centre for Medium-Range Weather Forecasts data sets indicate that the existence of SCLW has a noticeable impact on PD and TB at three window frequencies (150 GHz, 243 GHz, and 664 GHz) during snowfall. Our results imply that while polarimetric channels at the three window channels have the potential for snowfall characterization, accurate information on liquid water is required to correctly interpret the polarimetric observations.

Finland Validation of the New Blended Snow Product

NASA Technical Reports Server (NTRS)

Kim, E. J.; Casey, K. A.; Hallikainen, M. T.; Foster, J. L.; Hall, D. K.; Riggs, G. A.

2008-01-01

As part of an ongoing effort to validate satellite remote sensing snow products for the recentlydeveloped U.S. Air Force Weather Agency (AFWA) - NASA blended snow product, Satellite and in-situ data for snow extent and snow water equivalent (SWE) are evaluated in Finland for the 2006-2007 snow season Finnish Meteorological Institute (FMI) daily weather station data and Finnish Environment Institute (SYKE) bi-monthly snow course data are used as ground truth. Initial comparison results display positive agreement between the AFWA NASA Snow Algorithm (ANSA) snow extent and SWE maps and in situ data, with discrepancies in accordance with known AMSR-E and MODIS snow mapping limitations. Future ANSA product improvement plans include additional validation and inclusion of fractional snow cover in the ANSA data product. Furthermore, the AMSR-E 19 GHz (horizontal channel) with the difference between ascending and descending satellite passes (Diurnal Amplitude Variations, DAV) will be used to detect the onset of melt, and QuikSCAT scatterometer data (14 GHz) will be used to map areas of actively melting snow.

Snow Water Equivalent Retrieval By Markov Chain Monte Carlo Based on Memls and Hut Snow Emission Model

NASA Astrophysics Data System (ADS)

Pan, J.; Durand, M. T.; Vanderjagt, B. J.

2014-12-01

The Markov chain Monte Carlo (MCMC) method had been proved to be successful in snow water equivalent retrieval based on synthetic point-scale passive microwave brightness temperature (TB) observations. This method needs only general prior information about distribution of snow parameters, and could estimate layered snow properties, including the thickness, temperature, density and snow grain size (or exponential correlation length) of each layer. In this study, the multi-layer HUT (Helsinki University of Technology) model and the MEMLS (Microwave Emission Model of Layered Snowpacks) will be used as observation models to assimilate the observed TB into snow parameter prediction. Previous studies had shown that the multi-layer HUT model tends to underestimate TB at 37 GHz for deep snow, while the MEMLS does not show sensitivity of model bias to snow depth. Therefore, results using HUT model and MEMLS will be compared to see how the observation model will influence the retrieval of snow parameters. The radiometric measurements at 10.65, 18.7, 36.5 and 90 GHz at Sodankyla, Finland will be used as MCMC input, and the statistics of all snow property measurement will be used to calculate the prior information. 43 dry snowpits with complete measurements of all snow parameters will be used for validation. The entire dataset are from NorSREx (Nordic Snow Radar Experiment) experiments carried out by Juha Lemmetyinen, Anna Kontu and Jouni Pulliainen in FMI in 2009-2011 winters, and continued two more winters from 2011 to Spring of 2013. Besides the snow thickness and snow density that are directly related to snow water equivalent, other parameters will be compared with observations, too. For thin snow, the previous studies showed that influence of underlying soil is considerable, especially when the soil is half frozen with part of unfrozen liquid water and part of ice. Therefore, this study will also try to employ a simple frozen soil permittivity model to improve the

Towards Understanding the Timing and Frequency of Rain-on-Snow (ROS) Events in Alaska

NASA Astrophysics Data System (ADS)

Pan, C.; Kirchner, P. B.; Kimball, J. S.; Kim, Y.; Kamp, U.

2017-12-01

Rain-on-snow (ROS) events affect ecosystem processes at multiple spatial and temporal scales including hydrology, carbon cycling, wildlife movement and human transportation and result in marked changes to snowpack processes including enhanced snow melt, surface albedo and energy balance. Changes in the surface structure of the snowpack are visible through optical remote sensing and changes in the relative content and distribution of water, air and ice in the snowpack are detectable using passive microwave remote sensing. This project aims to develop ROS products to elucidate changes in frequency and distribution in ROS events using satellite data products derived from both optical and passive microwave satellite records. To detect ROS events, we use downscaled brightness temperature measurements derived from vertical and horizontal polarizations at 19 and 37 GHz from the Advanced Microwave Scanning Radiometer (AMSR-E/2) passive microwave satellites. Preliminary results indicate an overall classification accuracy of 77.6% relative to in situ weather observations including surface air temperature, precipitation, and snow depth. ROS events are spatially distributed largely to elevations below 500 m and occur most frequently on northern to western aspects in addition to southeastern. Regional ROS hot spots occur in southwest Alaska characterized by warmer climates and transient snowcover. The seasonal timing of ROS events indicates increasing frequency during the fall and spring months.

The AMSR2 Satellite-based Microwave Snow Algorithm (SMSA) to estimate regional to global snow depth and snow water equivalent

NASA Astrophysics Data System (ADS)

Kelly, R. E. J.; Saberi, N.; Li, Q.

2017-12-01

With moderate to high spatial resolution (<1 km) regional to global snow water equivalent (SWE) observation approaches yet to be fully scoped and developed, the long-term satellite passive microwave record remains an important tool for cryosphere-climate diagnostics. A new satellite microwave remote sensing approach is described for estimating snow depth (SD) and snow water equivalent (SWE). The algorithm, called the Satellite-based Microwave Snow Algorithm (SMSA), uses Advanced Microwave Scanning Radiometer - 2 (AMSR2) observations aboard the Global Change Observation Mission - Water mission launched by the Japan Aerospace Exploration Agency in 2012. The approach is unique since it leverages observed brightness temperatures (Tb) with static ancillary data to parameterize a physically-based retrieval without requiring parameter constraints from in situ snow depth observations or historical snow depth climatology. After screening snow from non-snow surface targets (water bodies [including freeze/thaw state], rainfall, high altitude plateau regions [e.g. Tibetan plateau]), moderate and shallow snow depths are estimated by minimizing the difference between Dense Media Radiative Transfer model estimates (Tsang et al., 2000; Picard et al., 2011) and AMSR2 Tb observations to retrieve SWE and SD. Parameterization of the model combines a parsimonious snow grain size and density approach originally developed by Kelly et al. (2003). Evaluation of the SMSA performance is achieved using in situ snow depth data from a variety of standard and experiment data sources. Results presented from winter seasons 2012-13 to 2016-17 illustrate the improved performance of the new approach in comparison with the baseline AMSR2 algorithm estimates and approach the performance of the model assimilation-based approach of GlobSnow. Given the variation in estimation power of SWE by different land surface/climate models and selected satellite-derived passive microwave approaches, SMSA provides

A tentative record of the last 1,000 years of Greenland temperature from occluded air in the GISP2 ice core

NASA Astrophysics Data System (ADS)

Kobashi, T.; Severinghaus, J. P.; Barnola, J.; Kawamura, K.; Beaudette, R.

2005-12-01

Ice borehole temperature inversion has been used to reconstruct Greenland surface temperature during the last millennium (Dahl-Jensen et al, Science, 1998). However, this technique does not preserve high frequencies because of diffusion of heat in the ice. Here, we present a tentative reconstruction of the past 1,000 years of central Greenland temperature using nitrogen and argon isotopes from occluded air in the GISP2 ice core. This technique preserves decadal-to-centennial-scale temperature variations and complements the borehole technique. Nitrogen and argon isotopes in the porous snow layer (~80m) experience two isotopic fractionations by gravitation and temperature gradients (ΔT) between the top and bottom of the snow layer. The simultaneous analysis of argon and nitrogen isotopes allows us to separate these two effects, and obtain a history of ΔT in the layer. To a first approximation, ΔT change on decadal to centennial time scales is a surface temperature history because the heat conductivity of snow is much smaller than that of ice, and the heat capacity of the ice sheet is quite large. The preliminary ΔT history (20-year interval) shows a Medieval Warm Period in the 11th to 12th centuries and the Little Ice Age in the 15th to 19th centuries. Furthermore, the record shows a clear similarity with the Be-10 record (a proxy for solar activity) with Wolf, Sporer, Maunder, and Dalton minima clearly seen in the cold periods. This finding is consistent with the hypothesis that solar activity influenced Greenland temperature during the past 1000 years.

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing in the Wind River Range, Wyoming

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Foster, James L.; DiGirolamo, Nicolo E.; Riggs, George A.

2010-01-01

MODIS-derived snow cover measured on 30 April in any given year explains approximately 89 % of the variance in stream discharge for maximum monthly streamflow in that year. Observed changes in streamflow appear to be related to increasing maximum air temperatures over the last four decades causing lower spring snow-cover extent. The majority (>70%) of the water supply in the western United States comes from snowmelt, thus analysis of the declining spring snowpack (and resulting declining stream discharge) has important implications for streamflow management in the drought-prone western U.S.

Experimental measurement and modeling of snow accumulation and snowmelt in a mountain microcatchment

NASA Astrophysics Data System (ADS)

Danko, Michal; Krajčí, Pavel; Hlavčo, Jozef; Kostka, Zdeněk; Holko, Ladislav

2016-04-01

Fieldwork is a very useful source of data in all geosciences. This naturally applies also to the snow hydrology. Snow accumulation and snowmelt are spatially very heterogeneous especially in non-forested, mountain environments. Direct field measurements provide the most accurate information about it. Quantification and understanding of processes, that cause these spatial differences are crucial in prediction and modelling of runoff volumes in spring snowmelt period. This study presents possibilities of detailed measurement and modeling of snow cover characteristics in a mountain experimental microcatchment located in northern part of Slovakia in Western Tatra mountains. Catchment area is 0.059 km2 and mean altitude is 1500 m a.s.l. Measurement network consists of 27 snow poles, 3 small snow lysimeters, discharge measurement device and standard automatic weather station. Snow depth and snow water equivalent (SWE) were measured twice a month near the snow poles. These measurements were used to estimate spatial differences in accumulation of SWE. Snowmelt outflow was measured by small snow lysimeters. Measurements were performed in winter 2014/2015. Snow water equivalent variability was very high in such a small area. Differences between particular measuring points reached 600 mm in time of maximum SWE. The results indicated good performance of a snow lysimeter in case of snowmelt timing identification. Increase of snowmelt measured by the snow lysimeter had the same timing as increase in discharge at catchment's outlet and the same timing as the increase in air temperature above the freezing point. Measured data were afterwards used in distributed rainfall-runoff model MIKE-SHE. Several methods were used for spatial distribution of precipitation and snow water equivalent. The model was able to simulate snow water equivalent and snowmelt timing in daily step reasonably well. Simulated discharges were slightly overestimated in later spring.

Measured Black Carbon Deposition on the Sierra Nevada Snow Pack and Implication for Snow Pack Retreat

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hadley, O.L.; Corrigan, C.E.; Kirchstetter, T.W.

2010-01-12

Modeling studies show that the darkening of snow and ice by black carbon deposition is a major factor for the rapid disappearance of arctic sea ice, mountain glaciers and snow packs. This study provides one of the first direct measurements for the efficient removal of black carbon from the atmosphere by snow and its subsequent deposition to the snow packs of California. The early melting of the snow packs in the Sierras is one of the contributing factors to the severe water problems in California. BC concentrations in falling snow were measured at two mountain locations and in rain atmore » a coastal site. All three stations reveal large BC concentrations in precipitation, ranging from 1.7 ng/g to 12.9 ng/g. The BC concentrations in the air after the snow fall were negligible suggesting an extremely efficient removal of BC by snow. The data suggest that below cloud scavenging, rather than ice nuclei, was the dominant source of BC in the snow. A five-year comparison of BC, dust, and total fine aerosol mass concentrations at multiple sites reveals that the measurements made at the sampling sites were representative of large scale deposition in the Sierra Nevada. The relative concentration of iron and calcium in the mountain aerosol indicates that one-quarter to one-third of the BC may have been transported from Asia.« less

Brilliant Colours from a White Snow Cover

ERIC Educational Resources Information Center

Vollmer, Michael; Shaw, Joseph A

2013-01-01

Surprisingly colourful views are possible from sparkling white snow. It is well known that similarly colourful features can exist in the sky whenever appropriate ice crystals are around. However, the transition of light reflection and refraction from ice crystals in the air to reflection and refraction from those in snow on the ground is not…

Synchronous NDVI and Surface Air Temperature Trends in Newfoundland: 1982 to 2003

NASA Technical Reports Server (NTRS)

Neigh, C. S. R.; Tucker, C. J.; Townshend, J. R. G.

2007-01-01

The northern regions of the earth are currently experiencing rapid change in temperature and precipitation. This region contains -40% of carbon stored in the world's soil which has accumulated from the last ice age (over 10,000 years ago). The carbon has remained to this point due to reduced decomposition from the short growing seasons and subfreezing temperatures. The influence of climate upon plant growth can have significant consequences to the carbon cycle balance in this region and could potentially alter and release this long term store of carbon to the atmosphere, resulting in a negative feedback enhancing climate warming. These changes have the potential to alter ecosystems processes, which impact human well being. This paper investigated a global satellite record of increases in vegetation growth from 1982 to 2003 developed at GSFC. It was found that, Newfoundland's vegetation growth during the 1990s exceeded global measurements. A number of potential causes were investigated to understand the mechanistic environmental drivers that could alter the productivity of this ecosystem. Possible drivers of change included: human influence of land use change on vegetation cover; changes in precipitation; temperature; cloud cover; snow cover; and growing season length. We found that humans had a minimal influence on vegetation growth in Newfoundland. Less than 6% of the island was logged during the investigation. We found a strong correlation of vegetation growth to a lengthening of the growing season of -9 and -17 days from 1982-1990 and 1991-1999. A distinct drop in plant growth and air temperature was found in 1990 to 1991 from the volcanic eruption of Mt. Pinatubo that reduced global surface air temperatures. These results document the influences of air temperature upon northern forest plant growth and the cooling effects of major volcanic eruptions in this ecological system.

Effects of soot-induced snow albedo change on snowpack and hydrological cycle in western United States based on Weather Research and Forecasting chemistry and regional climate simulations

NASA Astrophysics Data System (ADS)

Qian, Yun; Gustafson, William I.; Leung, L. Ruby; Ghan, Steven J.

2009-02-01

Radiative forcing induced by soot on snow is an important anthropogenic forcing affecting the global climate. In this study we simulated the deposition of soot aerosol on snow and the resulting impact on snowpack and the hydrological cycle in the western United States. A year-long simulation was performed using the chemistry version of the Weather Research and Forecasting model (WRF-Chem) to determine the soot deposition, followed by three simulations using WRF in meteorology-only mode, with and without the soot-induced snow albedo perturbations. The chemistry simulation shows large spatial variability in soot deposition that reflects the localized emissions and the influence of the complex terrain. The soot-induced snow albedo perturbations increase the surface net solar radiation flux during late winter to early spring, increase the surface air temperature, and reduce the snow accumulation and spring snowmelt. These effects are stronger over the central Rockies and southern Alberta, where soot deposition and snowpack overlap the most. The indirect forcing of soot accelerates snowmelt and alters stream flows, including a trend toward earlier melt dates in the western United States. The soot-induced albedo reduction initiates a positive feedback process whereby dirty snow absorbs more solar radiation, heating the surface and warming the air. This warming causes reduced snow depth and fraction, which further reduces the regional surface albedo for the snow-covered regions. For a doubled snow albedo perturbation, the change to surface energy and temperature is around 50-80%; however, snowpack reduction is nonlinearly accelerated.

A satellite snow depth multi-year average derived from SSM/I for the high latitude regions

USGS Publications Warehouse

Biancamaria, S.; Mognard, N.M.; Boone, A.; Grippa, M.; Josberger, E.G.

2008-01-01

The hydrological cycle for high latitude regions is inherently linked with the seasonal snowpack. Thus, accurately monitoring the snow depth and the associated aerial coverage are critical issues for monitoring the global climate system. Passive microwave satellite measurements provide an optimal means to monitor the snowpack over the arctic region. While the temporal evolution of snow extent can be observed globally from microwave radiometers, the determination of the corresponding snow depth is more difficult. A dynamic algorithm that accounts for the dependence of the microwave scattering on the snow grain size has been developed to estimate snow depth from Special Sensor Microwave/Imager (SSM/I) brightness temperatures and was validated over the U.S. Great Plains and Western Siberia. The purpose of this study is to assess the dynamic algorithm performance over the entire high latitude (land) region by computing a snow depth multi-year field for the time period 1987-1995. This multi-year average is compared to the Global Soil Wetness Project-Phase2 (GSWP2) snow depth computed from several state-of-the-art land surface schemes and averaged over the same time period. The multi-year average obtained by the dynamic algorithm is in good agreement with the GSWP2 snow depth field (the correlation coefficient for January is 0.55). The static algorithm, which assumes a constant snow grain size in space and time does not correlate with the GSWP2 snow depth field (the correlation coefficient with GSWP2 data for January is - 0.03), but exhibits a very high anti-correlation with the NCEP average January air temperature field (correlation coefficient - 0.77), the deepest satellite snow pack being located in the coldest regions, where the snow grain size may be significantly larger than the average value used in the static algorithm. The dynamic algorithm performs better over Eurasia (with a correlation coefficient with GSWP2 snow depth equal to 0.65) than over North America

Impacts of Synoptic Weather Patterns on Snow Albedo at Sites in New England

NASA Astrophysics Data System (ADS)

Adolph, A. C.; Albert, M. R.; Lazarcik, J.; Dibb, J. E.; Amante, J.; Price, A. N.

2015-12-01

Winter snow in the northeastern United States has changed over the last several decades, resulting in shallower snow packs, fewer days of snow cover and increasing precipitation falling as rain in the winter. In addition to these changes which cause reductions in surface albedo, increasing winter temperatures also lead to more rapid snow grain growth, resulting in decreased snow reflectivity. We present in-situ measurements and analyses to test the sensitivity of seasonal snow albedo to varying weather conditions at sites in New England. In particular, we investigate the impact of temperature on snow albedo through melt and grain growth, the impact of precipitation event frequency on albedo through snow "freshening," and the impact of storm path on snow structure and snow albedo. Over three winter seasons between 2013 and 2015, in-situ snow characterization measurements were made at three non-forested sites across New Hampshire. These near-daily measurements include spectrally resolved albedo, snow optical grain size determined through contact spectroscopy, snow depth, snow density and local meteorological parameters. Combining this information with storm tracks derived from HYSPLIT modeling, we quantify the current sensitivity of northeastern US snow albedo to temperature as well as precipitation type, frequency and path. Our analysis shows that southerly winter storms result in snow with a significantly lower albedo than storms which come from across the continental US or the Atlantic Ocean. Interannual variability in temperature and statewide spatial variability in snowfall rates at our sites show the relative importance of snowfall amount and temperatures in albedo evolution over the course of the winter.

Soot climate forcing via snow and ice albedos.

PubMed

Hansen, James; Nazarenko, Larissa

2004-01-13

Plausible estimates for the effect of soot on snow and ice albedos (1.5% in the Arctic and 3% in Northern Hemisphere land areas) yield a climate forcing of +0.3 W/m(2) in the Northern Hemisphere. The "efficacy" of this forcing is approximately 2, i.e., for a given forcing it is twice as effective as CO(2) in altering global surface air temperature. This indirect soot forcing may have contributed to global warming of the past century, including the trend toward early springs in the Northern Hemisphere, thinning Arctic sea ice, and melting land ice and permafrost. If, as we suggest, melting ice and sea level rise define the level of dangerous anthropogenic interference with the climate system, then reducing soot emissions, thus restoring snow albedos to pristine high values, would have the double benefit of reducing global warming and raising the global temperature level at which dangerous anthropogenic interference occurs. However, soot contributions to climate change do not alter the conclusion that anthropogenic greenhouse gases have been the main cause of recent global warming and will be the predominant climate forcing in the future.

On the influence of recrystallization on snow fabric and microstructure: study of a snow profile in Central East Antarctica

NASA Astrophysics Data System (ADS)

Calonne, Neige; Schneebeli, Martin; Montagnat, Maurine; Matzl, Margret

2016-04-01

Temperature gradient metamorphism affects the Antarctic snowpack up to 5 meters depth, which lead to a recrystallization of the ice grains by sublimation of ice and deposition of water vapor. By this way, it is well known that the snow microstructure evolves (geometrical changes). Also, a recent study shows an evolution of the snow fabric, based on a cold laboratory experiment. Both fabric and microstructure are required to better understand mechanical behavior and densification of snow, firn and ice, given polar climatology. The fabric of firn and ice has been extensively investigated, but the publications by Stephenson (1967, 1968) are to our knowledge the only ones describing the snow fabric in Antarctica. In this context, our work focuses on snow microstructure and fabric in the first meters depth of the Antarctic ice sheet, where temperature gradients driven recrystallization occurs. Accurate details of the snow microstructure are observed using micro-computed tomography. Snow fabrics were measured at various depths from thin sections of impregnated snow with an Automatic Ice Texture Analyzer (AITA). A definite relationship between microstructure and fabric is found and highlights the influence of metamorphism on both properties. Our results also show that the metamorphism enhances the differences between the snow layers properties. Our work stresses the significant and complex evolution of snow properties in the upper meters of the ice sheet and opens the question of how these layer properties will evolve at depth and may influence the densification.

Crowdsourcing urban air temperatures from smartphone battery temperatures

NASA Astrophysics Data System (ADS)

Overeem, A.; Robinson, J. C. R.; Leijnse, H.; Steeneveld, G. J.; Horn, B. K. P.; Uijlenhoet, R.

2013-08-01

Accurate air temperature observations in urban areas are important for meteorology and energy demand planning. They are indispensable to study the urban heat island effect and the adverse effects of high temperatures on human health. However, the availability of temperature observations in cities is often limited. Here we show that relatively accurate air temperature information for the urban canopy layer can be obtained from an alternative, nowadays omnipresent source: smartphones. In this study, battery temperatures were collected by an Android application for smartphones. A straightforward heat transfer model is employed to estimate daily mean air temperatures from smartphone battery temperatures for eight major cities around the world. The results demonstrate the enormous potential of this crowdsourcing application for real-time temperature monitoring in densely populated areas.

Climate Change Across Seasons Experiment (CCASE): A new method for simulating future climate in seasonally snow-covered ecosystems.

PubMed

Templer, Pamela H; Reinmann, Andrew B; Sanders-DeMott, Rebecca; Sorensen, Patrick O; Juice, Stephanie M; Bowles, Francis; Sofen, Laura E; Harrison, Jamie L; Halm, Ian; Rustad, Lindsey; Martin, Mary E; Grant, Nicholas

2017-01-01

Climate models project an increase in mean annual air temperatures and a reduction in the depth and duration of winter snowpack for many mid and high latitude and high elevation seasonally snow-covered ecosystems over the next century. The combined effects of these changes in climate will lead to warmer soils in the growing season and increased frequency of soil freeze-thaw cycles (FTCs) in winter due to the loss of a continuous, insulating snowpack. Previous experiments have warmed soils or removed snow via shoveling or with shelters to mimic projected declines in the winter snowpack. To our knowledge, no experiment has examined the interactive effects of declining snowpack and increased frequency of soil FTCs, combined with soil warming in the snow-free season on terrestrial ecosystems. In addition, none have mimicked directly the projected increase in soil FTC frequency in tall statured forests that is expected as a result of a loss of insulating snow in winter. We established the Climate Change Across Seasons Experiment (CCASE) at Hubbard Brook Experimental Forest in the White Mountains of New Hampshire in 2012 to assess the combined effects of these changes in climate on a variety of pedoclimate conditions, biogeochemical processes, and ecology of northern hardwood forests. This paper demonstrates the feasibility of creating soil FTC events in a tall statured ecosystem in winter to simulate the projected increase in soil FTC frequency over the next century and combines this projected change in winter climate with ecosystem warming throughout the snow-free season. Together, this experiment provides a new and more comprehensive approach for climate change experiments that can be adopted in other seasonally snow-covered ecosystems to simulate expected changes resulting from global air temperature rise.

Climate Change Across Seasons Experiment (CCASE): A new method for simulating future climate in seasonally snow-covered ecosystems

PubMed Central

Templer, Pamela H.; Reinmann, Andrew B.; Sanders-DeMott, Rebecca; Sorensen, Patrick O.; Juice, Stephanie M.; Bowles, Francis; Sofen, Laura E.; Harrison, Jamie L.; Halm, Ian; Rustad, Lindsey; Martin, Mary E.; Grant, Nicholas

2017-01-01

Climate models project an increase in mean annual air temperatures and a reduction in the depth and duration of winter snowpack for many mid and high latitude and high elevation seasonally snow-covered ecosystems over the next century. The combined effects of these changes in climate will lead to warmer soils in the growing season and increased frequency of soil freeze-thaw cycles (FTCs) in winter due to the loss of a continuous, insulating snowpack. Previous experiments have warmed soils or removed snow via shoveling or with shelters to mimic projected declines in the winter snowpack. To our knowledge, no experiment has examined the interactive effects of declining snowpack and increased frequency of soil FTCs, combined with soil warming in the snow-free season on terrestrial ecosystems. In addition, none have mimicked directly the projected increase in soil FTC frequency in tall statured forests that is expected as a result of a loss of insulating snow in winter. We established the Climate Change Across Seasons Experiment (CCASE) at Hubbard Brook Experimental Forest in the White Mountains of New Hampshire in 2012 to assess the combined effects of these changes in climate on a variety of pedoclimate conditions, biogeochemical processes, and ecology of northern hardwood forests. This paper demonstrates the feasibility of creating soil FTC events in a tall statured ecosystem in winter to simulate the projected increase in soil FTC frequency over the next century and combines this projected change in winter climate with ecosystem warming throughout the snow-free season. Together, this experiment provides a new and more comprehensive approach for climate change experiments that can be adopted in other seasonally snow-covered ecosystems to simulate expected changes resulting from global air temperature rise. PMID:28207766

Sulfur dioxide reactions on ice surfaces: Implications for dry deposition to snow

Treesearch

Martha H. Conklin; Richard A. Sommerfeld; S. Kay Laird; John E. Villinski

1993-01-01

Controlled exposure of ice to a reactive gas, SO2, demonstrated the importance of the chemical composition of the ice surface on the accumulation of acidity in snow. In a series of bench-scale continuous-flow column experiments run at four temperatures (-1, -8, -30 and -60°C), SO2 was shown to dissolve and to react with other species in the ice-air interfacial region...

MELIFT - A new device for accurate measurements in a snow rich environment

NASA Astrophysics Data System (ADS)

Dorninger, M.

2012-04-01

A deep snow pack, remote locations, no external power supply and very low temperatures are often the main ingredients when it comes to the deployment of meteorological stations in mountainous terrain. The accurate position of the sensor related to the snow surface is normally not known. A new device called METLIFT overcomes the problems. WMO recommends a height between 1.2 m and 2 m above ground level for the measurement of air temperature and humidity. The height above ground level is specified to take care of the possible strong vertical temperature and humidity gradients at the lowest layers in the atmosphere. Especially in snow rich and remote locations it may be hardly possible to follow this advice. Therefore most of the meteorological stations in mountainous terrain are situated at mountain tops where strong winds will blow off the snow or in valleys where a daily inspection of the sensors is possible. In other unpopulated mountainous areas, e.g. basins, plateaus, the distance of the sensor to the snow surface is not known or the sensor will be snow-covered. A new device was developed to guarantee the sensor height above surface within the WMO limits in harsh and remote environments. An ultrasonic snow height sensor measures the distance to the snow surface. If it exceeds certain limits due to snow accumulation or snow melt the lift adapts its height accordingly. The prototype of METLIFT has been installed in Lower Austria at an altitude of 1000m. The lift is 6 m high and can pull out for another 4 m. Sensor arms are mounted every meter to allow the connection of additional sensors or to measure a profile of a certain parameter of the lowest 5 m above surface. Sensors can be added easily since cable wiring is provided to each sensor arm. Horizontal winds are measured at 7 m height above surface. METLIFT is independent of external power supply. Three lead gel accumulators recharged by three solar panels provide the energy necessary for the sensors, the data

Snow micro-structure at Kongsvegen glacier, Svalbard

NASA Astrophysics Data System (ADS)

Bilgeri, F.; Karner, F.; Steinkogler, W.; Fromm, R.; Obleitner, F.; Kohler, J.

2012-04-01

Measurements of physical snow properties have been performed at several sites at Kongsvegen glacier, which is a key Arctic glacier in western Spitzbergen (79N, 13E). The data were collected at six locations along the flow line of the glacier at different elevations (161 to 741m asl.) and describe snow that was deposited during winter 2010/11. We basically consider the vertical profiles of snow temperature, density, hardness, grain size and crystal shapes derived from standard stratigraphic methods (snow pits)and measurements using advanced instruments like Snow Micropen® and NIR imagery. Some parameters were measured repeatedly and with different instruments which proves a high quality as well as long-term and spatial representativeness of the data. The general snow conditions at the end of winter are characterized by a linear increase of snow depth and water equivalent with elevation. Snow hardness also increases with elevation while density remains remarkably constant. At most sites the snow temperature, density, hardness and grain size increase from the surface towards the snow-ice interface. The surface and the bottom layers stand out by specific changes in snow signature (crystal types) and delineate the bulk of the snow pack which itself features a rather complex layering. Comparison of the high-resolution profiles measured at different elevations at the glacier suggests some principal correlations of the signatures of hardness, grain size and crystal type. Thus, some major features (e.g. particularly hard layers) can be traced along the glacier, but the high-resolution layering can not straightforwardly be related from one site to the other. This basically reflects a locally different history of the snow pack in terms of precipitation events and post-depositional snow metamorphism. The issue is investigated more quantitatively by enhanced statistical processing of the observed signatures and simulation of the history of individual layers. These studies are

Snow depth and snow cover retrieval from FengYun3B microwave radiation imagery based on a snow passive microwave unmixing method in Northeast China

NASA Astrophysics Data System (ADS)

Gu, Lingjia; Ren, Ruizhi; Zhao, Kai; Li, Xiaofeng

2014-01-01

The precision of snow parameter retrieval is unsatisfactory for current practical demands. The primary reason is because of the problem of mixed pixels that are caused by low spatial resolution of satellite passive microwave data. A snow passive microwave unmixing method is proposed in this paper, based on land cover type data and the antenna gain function of passive microwaves. The land cover type of Northeast China is partitioned into grass, farmland, bare soil, forest, and water body types. The component brightness temperatures (CBT), namely unmixed data, with 1 km data resolution are obtained using the proposed unmixing method. The snow depth determined by the CBT and three snow depth retrieval algorithms are validated through field measurements taken in forest and farmland areas of Northeast China in January 2012 and 2013. The results show that the overall of the retrieval precision of the snow depth is improved by 17% in farmland areas and 10% in forest areas when using the CBT in comparison with the mixed pixels. The snow cover results based on the CBT are compared with existing MODIS snow cover products. The results demonstrate that more snow cover information can be obtained with up to 86% accuracy.

[Characteristics of chemical pollution of snow cover in Aktobe areas].

PubMed

Iskakov, A Zh

2010-01-01

The paper gives data on the nature of snow cover pollution in the urbanized areas in relation to the remoteness from the basic sources of ambient air pollution. The total snow content of carcinogens has been estimated.

Snow in Italy

NASA Image and Video Library

2012-02-24

NASA image acquired February 24, 2012 By late February, 2012, the great European cold wave had begun to loosen its frigid grip, but significant snow still remained in the region. The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite captured this true-color image of snow in Italy on February 24 at 12:35 UTC (1:30 p.m. local time). In the north of the image, bright white clouds blanket the region in a broad arc. Snow, which tends to be generally less bright that clouds, covers the Alps in the north of Italy. The Apennine Mountains, which form the backbone of the Italian peninsula, also carry a blanket of snow. Although clouds and snow can, at times, be distinguished visually in a true-color image, sometimes they can appear very similar. When it is important to clearly define snow from cloud, false color images are often helpful. Rome, which can be seen as a gray smudge on the southwestern coast of the peninsula, recorded highs of a spring-like 50°F the day this image was captured, but earlier in the month the temperatures dove as low as 26°F on February 5. During that cold snap a rare intense snowfall blanketed Rome, causing the closure of the Colosseum, the Roman Forum and the Palatine Hill due to concerns of the risk of icy footing for tourists, and roads became impassible. Further north, temperatures plummeted to −21 °C (−6 °F) on 7 February. On February 11, news media reported over 2 meters (6.5 feet) of snow had fallen in Urbino, a walled town situated on a high sloping hillside on the eastern side of the Apennine Mountains. That same snowfall cut access to many remote towns in the Apennines, blocking roads and trapping some people in the homes. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA�

Monitoring snow cover and its effect on runoff regime in the Jizera Mountains

NASA Astrophysics Data System (ADS)

Kulasova, Alena

2015-04-01

The Jizera Mountains in the northern Bohemia are known by its rich snow cover. Winter precipitation represents usually a half of the precipitation in the hydrological year. Gradual snow accumulation and melt depends on the course of the particular winter period, the topography of the catchments and the type of vegetation. During winter the snow depth, and especially the snow water equivalent, are affected by the changing character of the falling precipitation, air and soil temperatures and the wind. More rapid snowmelt occurs more on the slopes without forest oriented to the South, while a gradual snowmelt occurs on the locations turned to the North and in forest. Melting snow recharges groundwater and affects water quality in an important way. In case of extreme situation the snowmelt monitoring is important from the point of view of flood protection of communities and property. Therefore the immediate information on the amount of water in snow is necessary. The way to get this information is the continuous monitoring of the snow depth and snow water equivalent. In the Jizera Mountains a regular monitoring of snow cover has been going on since the end of the 19th century. In the 80s of the last century the Jizera Mountains were affected by the increased fallout of pollutants in the air. There followed a gradual dieback of the forest cover and cutting down the upper part of the ridges. In order to get data for the quantification of runoff regime changes in the changing natural environment, the Czech Hydrometeorological Institute (CHMI) founded in the upper part of the Mountains several experimental catchments. One of the activities of the employees of the experimental basis is the regular measurement of snow cover at selected sites from 1982 up to now. At the same time snow cover is being observed using snow pillows, where its mass is monitored with the help of pressure sensors. In order to improve the reliability of the continuous measurement of the snow water

Experimental Investigation of Concrete Runway Snow Melting Utilizing Heat Pipe Technology

PubMed Central

Su, Xin; Ye, Qing; Fu, Jianfeng

2018-01-01

A full scale snow melting system with heat pipe technology is built in this work, which avoids the negative effects on concrete structure and environment caused by traditional deicing chemicals. The snow melting, ice-freezing performance and temperature distribution characteristics of heat pipe concrete runway were discussed by the outdoor experiments. The results show that the temperature of the concrete pavement is greatly improved with the heat pipe system. The environment temperature and embedded depth of heat pipe play a dominant role among the decision variables of the snow melting system. Heat pipe snow melting pavement melts the snow completely and avoids freezing at any time when the environment temperature is below freezing point, which is secure enough for planes take-off and landing. Besides, the exportation and recovery of geothermal energy indicate that this system can run for a long time. This paper will be useful for the design and application of the heat pipe used in the runway snow melting. PMID:29551957

Experimental Investigation of Concrete Runway Snow Melting Utilizing Heat Pipe Technology.

PubMed

Chen, Fengchen; Su, Xin; Ye, Qing; Fu, Jianfeng

2018-01-01

A full scale snow melting system with heat pipe technology is built in this work, which avoids the negative effects on concrete structure and environment caused by traditional deicing chemicals. The snow melting, ice-freezing performance and temperature distribution characteristics of heat pipe concrete runway were discussed by the outdoor experiments. The results show that the temperature of the concrete pavement is greatly improved with the heat pipe system. The environment temperature and embedded depth of heat pipe play a dominant role among the decision variables of the snow melting system. Heat pipe snow melting pavement melts the snow completely and avoids freezing at any time when the environment temperature is below freezing point, which is secure enough for planes take-off and landing. Besides, the exportation and recovery of geothermal energy indicate that this system can run for a long time. This paper will be useful for the design and application of the heat pipe used in the runway snow melting.

Forward-looking Assimilation of MODIS-derived Snow Covered Area into a Land Surface Model

NASA Technical Reports Server (NTRS)

Zaitchik, Benjamin F.; Rodell, Matthew

2008-01-01

Snow cover over land has a significant impact on the surface radiation budget, turbulent energy fluxes to the atmosphere, and local hydrological fluxes. For this reason, inaccuracies in the representation of snow covered area (SCA) within a land surface model (LSM) can lead to substantial errors in both offline and coupled simulations. Data assimilation algorithms have the potential to address this problem. However, the assimilation of SCA observations is complicated by an information deficit in the observation SCA indicates only the presence or absence of snow, and not snow volume and by the fact that assimilated SCA observations can introduce inconsistencies with atmospheric forcing data, leading to non-physical artifacts in the local water balance. In this paper we present a novel assimilation algorithm that introduces MODIS SCA observations to the Noah LSM in global, uncoupled simulations. The algorithm utilizes observations from up to 72 hours ahead of the model simulation in order to correct against emerging errors in the simulation of snow cover while preserving the local hydrologic balance. This is accomplished by using future snow observations to adjust air temperature and, when necessary, precipitation within the LSM. In global, offline integrations, this new assimilation algorithm provided improved simulation of SCA and snow water equivalent relative to open loop integrations and integrations that used an earlier SCA assimilation algorithm. These improvements, in turn, influenced the simulation of surface water and energy fluxes both during the snow season and, in some regions, on into the following spring.

The Role of Snow Thickness over Arctic Winter Sea Ice in the Survival and Dispersal of Brine-Derived Microbes

NASA Astrophysics Data System (ADS)

Deming, J. W.; Ewert, M.; Bowman, J. S.

2013-12-01

The brines of polar winter sea ice are inhabited by significant densities of microbes (Bacteria and Archaea) that experience a range of extreme conditions depending on location in, and age of, the ice. Newly formed sea ice in winter expels microbes (and organic exudates) onto the surface of the ice, where they can be wicked into frost flowers or into freshly deposited snow, resulting in populations at the ice-air and air-snow interfaces characterized by even more extreme conditions. The influence of snow thickness over the ice on the fate of these microbes, and their potential for dispersal or mediation of exchanges with other components of the ice-snow system, is not well known. Examination of in situ temperature data from the Mass Balance Observatory (MBO) offshore of Barrow, Alaska, during the winter of 2011 allowed recognition of an hierarchy of fluctuation regimes in temperature and (by calculation) brine salinity, where the most stable conditions were encountered within the sea ice and the least stable highest in the snow cover, where temperature fluctuations were significantly more energetic as determined by an analysis of power spectral density. A prior analysis of snow thickness near the MBO had already revealed significant ablation events, potentially associated with bacterial mortality, that would have exposed the saline (microbe-rich) snow layer to wind-based dispersal. To better understand the survival of marine bacteria under these dynamic and extreme conditions, we conducted laboratory experiments with Arctic bacterial isolates, subjecting them to simulations of the freezing regimes documented at the MBS. The impact of the fluctuation regime was shown to be species-specific, with the organism of narrower temperature and salinity growth ranges suffering 30-50% mortality (which could be partially relieved by providing protection against salt-shock). This isolate, the psychrophilic marine bacterium Colwellia psychrerythraea strain 34H (temperature range

Improving the Performance of Temperature Index Snowmelt Model of SWAT by Using MODIS Land Surface Temperature Data

PubMed Central

Yang, Yan; Onishi, Takeo; Hiramatsu, Ken

2014-01-01

Simulation results of the widely used temperature index snowmelt model are greatly influenced by input air temperature data. Spatially sparse air temperature data remain the main factor inducing uncertainties and errors in that model, which limits its applications. Thus, to solve this problem, we created new air temperature data using linear regression relationships that can be formulated based on MODIS land surface temperature data. The Soil Water Assessment Tool model, which includes an improved temperature index snowmelt module, was chosen to test the newly created data. By evaluating simulation performance for daily snowmelt in three test basins of the Amur River, performance of the newly created data was assessed. The coefficient of determination (R 2) and Nash-Sutcliffe efficiency (NSE) were used for evaluation. The results indicate that MODIS land surface temperature data can be used as a new source for air temperature data creation. This will improve snow simulation using the temperature index model in an area with sparse air temperature observations. PMID:25165746

Toward mountains without permanent snow and ice

NASA Astrophysics Data System (ADS)

Huss, M.; Bookhagen, B.; Huggel, C.; Jacobsen, D.; Bradley, R. S.; Clague, J. J.; Vuille, M.; Buytaert, W.; Cayan, D. R.; Greenwood, G.; Mark, B. G.; Milner, A. M.; Weingartner, R.; Winder, M.

2017-05-01

The cryosphere in mountain regions is rapidly declining, a trend that is expected to accelerate over the next several decades due to anthropogenic climate change. A cascade of effects will result, extending from mountains to lowlands with associated impacts on human livelihood, economy, and ecosystems. With rising air temperatures and increased radiative forcing, glaciers will become smaller and, in some cases, disappear, the area of frozen ground will diminish, the ratio of snow to rainfall will decrease, and the timing and magnitude of both maximum and minimum streamflow will change. These changes will affect erosion rates, sediment, and nutrient flux, and the biogeochemistry of rivers and proglacial lakes, all of which influence water quality, aquatic habitat, and biotic communities. Changes in the length of the growing season will allow low-elevation plants and animals to expand their ranges upward. Slope failures due to thawing alpine permafrost, and outburst floods from glacier- and moraine-dammed lakes will threaten downstream populations. Societies even well beyond the mountains depend on meltwater from glaciers and snow for drinking water supplies, irrigation, mining, hydropower, agriculture, and recreation. Here, we review and, where possible, quantify the impacts of anticipated climate change on the alpine cryosphere, hydrosphere, and biosphere, and consider the implications for adaptation to a future of mountains without permanent snow and ice.

Ultra-Wideband Radiometry Remote Sensing of Polar Ice Sheet Temperature Profile, Sea Ice and Terrestrial Snow Thickness: Forward Modeling and Data Analysis

NASA Astrophysics Data System (ADS)

Tsang, L.; Tan, S.; Sanamzadeh, M.; Johnson, J. T.; Jezek, K. C.; Durand, M. T.

2017-12-01

The recent development of an ultra-wideband software defined radiometer (UWBRAD) operating over the unprotected spectrum of 0.5 2.0 GHz using radio-frequency interference suppression techniques offers new methodologies for remote sensing of the polar ice sheets, sea ice, and terrestrial snow. The instrument was initially designed for remote sensing of the intragalcial temperature profile of the ice sheet, where a frequency dependent penetration depth yields a frequency dependent brightness temperature (Tb) spectrum that can be linked back to the temperature profile of the ice sheet. The instrument was tested during a short flight over Northwest Greenland in September, 2016. Measurements were successfully made over the different snow facies characteristic of Greenland including the ablation, wet snow and percolation facies, and ended just west of Camp Century during the approach to the dry snow zone. Wide-band emission spectra collected during the flight have been processed and analyzed. Results show that the spectra are highly sensitive to the facies type with scattering from ice lenses being the dominant reason for low Tbs in the percolation zone. Inversion of Tb to physical temperature at depth was conducted on the measurements near Camp Century, achieving a -1.7K ten-meter error compared to borehole measurements. However, there is a relatively large uncertainty in the lower part possibly due to the large scattering near the surface. Wideband radiometry may also be applicable to sea ice and terrestrial snow thickness retrieval. Modeling studies suggest that the UWBRAD spectra reduce ambiguities inherent in other sea ice thickness retrievals by utilizing coherent wave interferences that appear in the Tb spectrum. When applied to a lossless medium such as terrestrial snow, this coherent oscillation turns out to be the single key signature that can be used to link back to snow thickness. In this paper, we report our forward modeling findings in support of instrument

Response of Arctic Snow and Sea Ice Extents to Melt Season Atmospheric Forcing Across the Land-Ocean Boundary

NASA Astrophysics Data System (ADS)

Bliss, A. C.; Anderson, M. R.

2011-12-01

Little research has gone into studying the concurrent variations in the annual loss of continental snow cover and sea ice extent across the land-ocean boundary, however, the analysis of these data averaged spatially over three study regions located in North America and Eastern and Western Russia, reveals a distinct difference in the response of anomalous snow and sea ice conditions to the atmospheric forcing. This study compares the monthly continental snow cover and sea ice extent loss in the Arctic, during the melt season months (May-August) for the period 1979-2007, with regional atmospheric conditions known to influence summer melt including: mean sea level pressures, 925 hPa air temperatures, and mean 2 m U and V wind vectors from NCEP/DOE Reanalysis 2. The monthly hemispheric snow cover extent data used are from the Rutgers University Global Snow Lab and sea ice extents for this study are derived from the monthly passive microwave satellite Bootstrap algorithm sea ice concentrations available from the National Snow and Ice Data Center. Three case study years (1985, 1996, and 2007) are used to compare the direct response of monthly anomalous sea ice and snow cover areal extents to monthly mean atmospheric forcing averaged spatially over the extent of each study region. This comparison is then expanded for all summer months over the 29 year study period where the monthly persistence of sea ice and snow cover extent anomalies and changes in the sea ice and snow conditions under differing atmospheric conditions are explored further. The monthly anomalous atmospheric conditions are classified into four categories including: warmer temperatures with higher pressures, warmer temperatures with lower pressures, cooler temperatures with higher pressures, and cooler temperatures with lower pressures. Analysis of the atmospheric conditions surrounding anomalous loss of snow and ice cover over the independent study regions indicates that conditions of warmer temperatures

NOAA's National Snow Analyses

NASA Astrophysics Data System (ADS)

Carroll, T. R.; Cline, D. W.; Olheiser, C. M.; Rost, A. A.; Nilsson, A. O.; Fall, G. M.; Li, L.; Bovitz, C. T.

2005-12-01

NOAA's National Operational Hydrologic Remote Sensing Center (NOHRSC) routinely ingests all of the electronically available, real-time, ground-based, snow data; airborne snow water equivalent data; satellite areal extent of snow cover information; and numerical weather prediction (NWP) model forcings for the coterminous U.S. The NWP model forcings are physically downscaled from their native 13 km2 spatial resolution to a 1 km2 resolution for the CONUS. The downscaled NWP forcings drive an energy-and-mass-balance snow accumulation and ablation model at a 1 km2 spatial resolution and at a 1 hour temporal resolution for the country. The ground-based, airborne, and satellite snow observations are assimilated into the snow model's simulated state variables using a Newtonian nudging technique. The principle advantages of the assimilation technique are: (1) approximate balance is maintained in the snow model, (2) physical processes are easily accommodated in the model, and (3) asynoptic data are incorporated at the appropriate times. The snow model is reinitialized with the assimilated snow observations to generate a variety of snow products that combine to form NOAA's NOHRSC National Snow Analyses (NSA). The NOHRSC NSA incorporate all of the available information necessary and available to produce a "best estimate" of real-time snow cover conditions at 1 km2 spatial resolution and 1 hour temporal resolution for the country. The NOHRSC NSA consist of a variety of daily, operational, products that characterize real-time snowpack conditions including: snow water equivalent, snow depth, surface and internal snowpack temperatures, surface and blowing snow sublimation, and snowmelt for the CONUS. The products are generated and distributed in a variety of formats including: interactive maps, time-series, alphanumeric products (e.g., mean areal snow water equivalent on a hydrologic basin-by-basin basis), text and map discussions, map animations, and quantitative gridded products

Potential for Monitoring Snow Cover in Boreal Forests by Combining MODIS Snow Cover and AMSR-E SWE Maps

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.; Foster, James L.

2009-01-01

through the seasons. A blended snow product, the Air Force Weather Agency and NASA (ANSA) snow algorithm and product has recently been developed. The ANSA algorithm blends the MODIS snow cover and AMSR-E SWE products into a single snow product that has been shown to improve the performance of snow cover mapping. In this study components of the ANSA snow algorithm are used along with additional MODIS data to monitor daily changes in snow cover over the period of 1 February to 30 June 2008.

Comparison between AVHRR surface temperature data and in-situ weather station temperatures over the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Rezvanbehbahani, S.; Csatho, B. M.; Comiso, J. C.; Babonis, G. S.

2011-12-01

Advanced Very-High Resolution Radiometer (AVHRR) images have been exhaustively used to measure surface temperature time series of the Greenland Ice sheet. The purpose of this study is to assess the accuracy of monthly average ice sheet surface temperatures, derived from thermal infrared AVHRR satellite imagery on a 6.25 km grid. In-situ temperature data sets are from the Greenland Collection Network (GC-Net). GC-Net stations comprise sensors monitoring air temperature at 1 and 2 meter above the snow surface, gathered at every 60 seconds and monthly averaged to match the AVHRR temporal resolution. Our preliminary results confirm the good agreement between satellite and in-situ temperature measurements reported by previous studies. However, some large discrepancies still exist. While AVHRR provides ice surface temperature, in-situ stations measure air temperatures at different elevations above the snow surface. Since most in-situ data on ice sheets are collected by Automatic Weather Station (AWS) instruments, it is important to characterize the difference between surface and air temperatures. Therefore, we compared and analyzed average monthly AVHRR ice surface temperatures using data collected in 2002. Differences between these temperatures correlate with in-situ temperatures and GC-Net station elevations, with increasing differences at lower elevations and higher temperatures. The Summit Station (3199 m above sea level) and the Swiss Camp (1176 m above sea level) results were compared as high altitude and low altitude stations for 2002, respectively. Our results show that AVHRR derived temperatures were 0.5°K warmer than AWS temperature at the Summit Station, while this difference was 2.8°K in the opposite direction for the Swiss Camp with surface temperatures being lower than air temperatures. The positive bias of 0.5°K at the high altitude Summit Station (surface warmer than air) is within the retrieval error of AVHRR temperatures and might be in part due to

The Infrared Sensor Suite for SnowEx 2017

NASA Technical Reports Server (NTRS)

Hall, D. K.; Chickadel, C. C.; Crawford, C. J.; DeMarco, E. L.; Jennings, D. E.; Jhabvala, M. D.; Kim, E. J.; Lundquist, J. D.; Lunsford, A. W.

2017-01-01

SnowEx is a winter airborne and field campaign designed to measure snow-water equivalent in forested landscapes. A major focus of Year 1 (2016-17) of NASA's SnowEx campaign will be an extensive field program involving dozens of participants from U.S. government agencies and from many universities and institutions, both domestic and foreign. Along with other instruments, two infrared (IR) sensors will be flown on a Naval Research Laboratory P-3 aircraft. Surface temperature is a critical input to hydrologic models and will be measured during the SnowEx mission. A Quantum Well Infrared Photodetector (QWIP) IR imaging camera system will be flown along with a KT-15 remote thermometer to aid in the calibration of the IR image data. Together, these instruments will measure surface temperature of snow and ice targets to an expected accuracy of less than 1C.

Role of snow and cold environment in the fate and effects of nanoparticles and select organic pollutants from gasoline engine exhaust.

PubMed

Nazarenko, Yevgen; Kurien, Uday; Nepotchatykh, Oleg; Rangel-Alvarado, Rodrigo B; Ariya, Parisa A

2016-02-01

Exposure to vehicle exhaust can drive up to 70 % of excess lifetime cancer incidences due to air pollution in urban environments. Little is known about how exhaust-derived particles and organic pollutants, implicated in adverse health effects, are affected by freezing ambient temperatures and the presence of snow. Airborne particles and (semi)volatile organic constituents in dilute exhaust were studied in a novel low-temperature environmental chamber system containing natural urban snow under controlled cold environmental conditions. The presence of snow altered the aerosol size distributions of dilute exhaust in the 10 nm to 10 μm range and decreased the number density of the nanoparticulate (<100 nm) fraction of exhaust aerosols, yet increased the 100-150 nm fraction. Upon 1 hour exhaust exposure, the total organic carbon increased in the natural snow from 0.218 ± 0.014 to 0.539 ± 0.009 mg L(-1), and over 40 additional (semi)volatile organic compounds and a large number of exhaust-derived carbonaceous and likely organic particles were identified. The concentrations of benzene, toluene, ethylbenzene, and xylenes (BTEX) increased from near the detection limit to 52.48, 379.5, 242.7, and 238.1 μg kg(-1) (± 10 %), respectively, indicating the absorption of exhaust-derived toxic organic compounds by snow. The alteration of exhaust aerosol size distributions at freezing temperatures and in the presence of snow, accompanied by changes of the organic pollutant content in snow, has potential to alter health effects of human exposure to vehicle exhaust.

A Distributed Snow Evolution Modeling System (SnowModel)

NASA Astrophysics Data System (ADS)

Liston, G. E.; Elder, K.

2004-12-01

A spatially distributed snow-evolution modeling system (SnowModel) has been specifically designed to be applicable over a wide range of snow landscapes, climates, and conditions. To reach this goal, SnowModel is composed of four sub-models: MicroMet defines the meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowMass simulates snow depth and water-equivalent evolution, and SnowTran-3D accounts for snow redistribution by wind. While other distributed snow models exist, SnowModel is unique in that it includes a well-tested blowing-snow sub-model (SnowTran-3D) for application in windy arctic, alpine, and prairie environments where snowdrifts are common. These environments comprise 68% of the seasonally snow-covered Northern Hemisphere land surface. SnowModel also accounts for snow processes occurring in forested environments (e.g., canopy interception related processes). SnowModel is designed to simulate snow-related physical processes occurring at spatial scales of 5-m and greater, and temporal scales of 1-hour and greater. These include: accumulation from precipitation; wind redistribution and sublimation; loading, unloading, and sublimation within forest canopies; snow-density evolution; and snowpack ripening and melt. To enhance its wide applicability, SnowModel includes the physical calculations required to simulate snow evolution within each of the global snow classes defined by Sturm et al. (1995), e.g., tundra, taiga, alpine, prairie, maritime, and ephemeral snow covers. The three, 25-km by 25-km, Cold Land Processes Experiment (CLPX) mesoscale study areas (MSAs: Fraser, North Park, and Rabbit Ears) are used as SnowModel simulation examples to highlight model strengths, weaknesses, and features in forested, semi-forested, alpine, and shrubland environments.

Monitoring of soil and air-rock temperatures in the Western Massif of the Picos de Europa (Spain)

NASA Astrophysics Data System (ADS)

Ruiz-Fernández, Jesús; Vieira, Gonçalo; García, Cristina

2013-04-01

In this paper we study the ground thermal regime and air-rock interface in the Western Massif of the Picos de Europa (Cantabrian Range, Spain). This calcareous massif is highly affected by karstification processes. Quaternary glaciers, fluvio-torrential processes and present-day periglacial processes also contribute to explain the landforms present in this massif. Up to 9 dataloggers were installed during 6 years in different sites in terms of altitude, orientation, slope and geomorpolohical setting recording temperatures every two hours. The number of freeze-thaw cycles in the soil(between 0 and 16) was controlled by the depth of the snow cover. The temperatures in the interface rock-air showed between 30-60 cycles, reaching 119 and 130 during the year 2007-2008. Extreme minimum temperatures in the soil oscillate between 0.3 and -6.3, while in the rocky walls the loggers recorded temperatures between -7.3 and -14.3°C. Monitoring of soil temperatures around the ice patch - the only one in the massif today - resulted in slightly negative mean annual temperatures. These conditions may reveal the existence of sporadic permafrost on debris that cover the ice patch. Both the buried ice and the permafrost are in disequilibrium with the current environmental conditions of the massif.

High Lapse Rates in AIRS Retrieved Temperatures in Cold Air Outbreaks

NASA Technical Reports Server (NTRS)

Fetzer, Eric J.; Kahn, Brian; Olsen, Edward T.; Fishbein, Evan

2004-01-01

The Atmospheric Infrared Sounder (AIRS) experiment, on NASA's Aqua spacecraft, uses a combination of infrared and microwave observations to retrieve cloud and surface properties, plus temperature and water vapor profiles comparable to radiosondes throughout the troposphere, for cloud cover up to 70%. The high spectral resolution of AIRS provides sensitivity to important information about the near-surface atmosphere and underlying surface. A preliminary analysis of AIRS temperature retrievals taken during January 2003 reveals extensive areas of superadiabatic lapse rates in the lowest kilometer of the atmosphere. These areas are found predominantly east of North America over the Gulf Stream, and, off East Asia over the Kuroshio Current. Accompanying the high lapse rates are low air temperatures, large sea-air temperature differences, and low relative humidities. Imagery from a Visible / Near Infrared instrument on the AIRS experiment shows accompanying clouds. These lines of evidence all point to shallow convection in the bottom layer of a cold air mass overlying warm water, with overturning driven by heat flow from ocean to atmosphere. An examination of operational radiosondes at six coastal stations in Japan shows AIRS to be oversensitive to lower tropospheric lapse rates due to systematically warm near-surface air temperatures. The bias in near-surface air temperature is seen to be independent of sea surface temperature, however. AIRS is therefore sensitive to air-sea temperature difference, but with a warm atmospheric bias. A regression fit to radiosondes is used to correct AIRS near-surface retrieved temperatures, and thereby obtain an estimate of the true atmosphere-ocean thermal contrast in five subtropical regions across the north Pacific. Moving eastward, we show a systematic shift in this air-sea temperature differences toward more isothermal conditions. These results, while preliminary, have implications for our understanding of heat flow from ocean to

Large scale snow water status monitoring: comparison of different snow water products in the upper Colorado basins

USGS Publications Warehouse

Artan, G.A.; Verdin, J.P.; Lietzow, R.

2013-01-01

We illustrate the ability to monitor the status of snowpack over large areas by using a~spatially distributed snow accumulation and ablation model in the Upper Colorado Basin. The model was forced with precipitation fields from the National Weather Service (NWS) Multi-sensor Precipitation Estimator (MPE) and the Tropical Rainfall Measuring Mission (TRMM) datasets; remaining meteorological model input data was from NOAA's Global Forecast System (GFS) model output fields. The simulated snow water equivalent (SWE) was compared to SWEs from the Snow Data Assimilation System (SNODAS) and SNOwpack TELemetry system (SNOTEL) over a~region of the Western United States that covers parts of the Upper Colorado Basin. We also compared the SWE product estimated from the Special Sensor Microwave Imager (SSM/I) and Scanning Multichannel Microwave Radiometer (SMMR) to the SNODAS and SNOTEL SWE datasets. Agreement between the spatial distribution of the simulated SWE with both SNODAS and SNOTEL was high for the two model runs for the entire snow accumulation period. Model-simulated SWEs, both with MPE and TRMM, were significantly correlated spatially on average with the SNODAS (r = 0.81 and r = 0.54; d.f. = 543) and the SNOTEL SWE (r = 0.85 and r = 0.55; d.f. = 543), when monthly basinwide simulated average SWE the correlation was also highly significant (r = 0.95 and r = 0.73; d.f. = 12). The SWE estimated from the passive microwave imagery was not correlated either with the SNODAS SWE or (r = 0.14, d.f. = 7) SNOTEL-reported SWE values (r = 0.08, d.f. = 7). The agreement between modeled SWE and the SWE recorded by SNODAS and SNOTEL weakened during the snowmelt period due to an underestimation bias of the air temperature that was used as model input forcing.

L-Band Brightness Temperature Variations at Dome C and Snow Metamorphism at the Surface

NASA Technical Reports Server (NTRS)

Brucker, Ludovic; Dinnat, Emmanuel; Picard, Ghislain; Champollion, Nicolas

2014-01-01

The Antarctic Plateau is a promising site to monitor microwave radiometers' drift, and to inter-calibrate microwave radiometers, especially 1.4 GigaHertz (L-band) radiometers on board the Soil Moisture and Ocean Salinity (SMOS), and AquariusSAC-D missions. The Plateau is a thick ice cover, thermally stable in depth, with large dimensions, and relatively low heterogeneities. In addition, its high latitude location in the Southern Hemisphere enables frequent observations by polar-orbiting satellites, and no contaminations by radio frequency interference. At Dome C (75S, 123E), on the Antarctic Plateau, the substantial amount of in-situ snow measurements available allows us to interpret variations in space-borne microwave brightness temperature (TB) (e.g. Macelloni et al., 2007, 2013, Brucker et al., 2011, Champollion et al., 2013). However, to analyze the observations from the Aquarius radiometers, whose sensitivity is 0.15 K, the stability of the snow layers near the surface that are most susceptible to rapidly change needs to be precisely assessed. This study focuses on the spatial and temporal variations of the Aquarius TB over the Antarctic Plateau, and at Dome C in particular, to highlight the impact of snow surface metamorphism on the TB observations at L-band.

Aquarius Brightness Temperature Variations at Dome C and Snow Metamorphism at the Surface. [29

NASA Technical Reports Server (NTRS)

Brucker, Ludovic; Dinnat, Emmanuel Phillippe; Picard, Ghislain; Champollion, Nicolas

2014-01-01

The Antarctic Plateau is a promising site to monitor microwave radiometers' drift, and to inter-calibrate microwave radiometers, especially 1.4 GHz (L-band) radiometers on board the Soil Moisture and Ocean Salinity (SMOS), and AquariusSAC-D missions. The Plateau is a thick ice cover, thermally stable in depth, with large dimensions, and relatively low heterogeneities. In addition, its high latitude location in the Southern Hemisphere enables frequent observations by polar-orbiting satellites, and no contaminations by radio frequency interference. At Dome C (75S, 123E), on the Antarctic Plateau, the substantial amount of in-situ snow measurements available allows us to interpret variations in space-borne microwave brightness temperature (TB) (e.g. Macelloni et al., 2007, 2013, Brucker et al., 2011, Champollion et al., 2013). However, to analyze the observations from the Aquarius radiometers, whose sensitivity is 0.15 K, the stability of the snow layers near the surface that are most susceptible to rapidly change needs to be precisely assessed. This study focuses on the spatial and temporal variations of the Aquarius TB over the Antarctic Plateau, and at Dome C in particular, to highlight the impact of snow surface metamorphism on the TB observations at L-band.

Long-term record of atmospheric and snow surface nitrate from Dome C (Central Antarctica)

NASA Astrophysics Data System (ADS)

Traversi, Rita; Becagli, Silvia; Brogioni, Marco; Caiazzo, Laura; Ciardini, Virginia; Giardi, Fabio; Legrand, Michel; Macelloni, Giovanni; Petkov, Boyan; Preunkert, Suzanne; Scarchilli, Claudio; Severi, Mirko; Vitale, Vito; Udisti, Roberto

2017-04-01

Nitrate is the end product of the oxidation of atmospheric nitrogen oxides and one of the most abundant ions present in polar ice and snow, mainly as nitric acid in present-climate conditions. Nitrate stratigraphies from snow and ice layers have the potential to provide records of past changes in atmospheric composition, including atmospheric NOx cycling and oxidative capacity, as well as past solar activity or major variations in Earth's magnetic field. Nevertheless, in order to exploit such a potential, chemical concentrations in the air, snow, firn and ice core need to be correlated. Hence, the knowledge of the link between atmosphere and snow composition at the time of deposition is basic to reconstruct past climate and past atmospheric chemical composition. The extent of such knowledge depends on whether the species of interest are gaseous or in the condensed phase, and if they are reversible and/or irreversibly deposited to snow. In order to provide a contribution to their air-to-snow exchange in the Antarctic plateau, as well as to the understanding of dominant sources and sinks of nitrate, we present here nitrate records in atmospheric aerosol and surface snow sampled at high resolution, all year-round, at Dome C along 9 years (November 2004 - November 2013). This represents the longest and most highly resolved record from continental Antarctica, where continuous and long-term atmosphere and snow samplings are particularly difficult due to the extreme meteorological conditions and, at the same time, need of extra-care in avoiding contamination due to the low level of ion concentrations. Results confirm, on a larger statistical data set with respect to previous observations, nitrate seasonal pattern with summer maxima both for aerosol and surface snow, in-phase with UV solar irradiance. Such a temporal pattern is likely a combination of nitrate sources and post-depositional processes that enhance during summer. Moreover, a case study of synoptic analysis for

Space-time analysis of snow cover change in the Romanian Carpathians (2001-2016)

NASA Astrophysics Data System (ADS)

Micu, Dana; Cosmin Sandric, Ionut

2017-04-01

Snow cover is recognized as an essential climate variable, highly sensitive to the ongoing climate warming, which plays an important role in regulating mountain ecosystems. Evidence from the existing weather stations located above 800 m over the last 50 years points out that the climate of the Romanian Carpathians is visibly changing, showing an ongoing and consistent warming process. Quantifying and attributing the changes in snow cover on various spatial and temporal scales have a great environmental and socio-economic importance for this mountain region. The study is revealing the inter-seasonal changes in the timing and distribution of snow cover across the Romanian Carpathians, by combining gridded snow data (CARPATCLIM dataset, 1961-2010) and remote sensing data (2001-2016) in specific space-time assessment at regional scale. The geostatistical approach applied in this study, based on a GIS hotspot analysis, takes advantage of all the dimensions in the datasets, in order to understand the space-time trends in this climate variable at monthly time-scale. The MODIS AQUA and TERRA images available from 2001 to 2016 have been processed using ArcGIS for Desktop and Python programming language. All the images were masked out with the Carpathians boundary. Only the pixels with snow have been retained for analysis. The regional trends in snow cover distribution and timing have been analysed using Space-Time cube with ArcGIS for Desktop, according with Esri documentation using the Mann-Kendall trend test on every location with data as an independent bin time-series test. The study aimed also to assess the location of emerging hotspots of snow cover change in Carpathians. These hotspots have been calculated using Getis-Ord Gi* statistic for each bin using Hot Spot Analysis implemented in ArcGIS for Desktop. On regional scale, snow cover appear highly sensitive to the decreasing trends in air temperatures and land surface temperatures, combined with the decrease in

Future change in seasonal march of snow water equivalent due to global climate change

NASA Astrophysics Data System (ADS)

Hara, M.; Kawase, H.; Ma, X.; Wakazuki, Y.; Fujita, M.; Kimura, F.

2012-04-01

Western side of Honshu Island in Japan is one of the heaviest snowfall areas in the world, although the location is relatively lower latitude than other heavy snowfall areas. Snowfall is one of major source for agriculture, industrial, and house-use in Japan. The change in seasonal march of snow water equivalent, e.g., snowmelt season and amount will strongly influence to social-economic activities (ex. Ma et al., 2011). We performed the four numerical experiments including present and future climate simulations and much-snow and less-snow cases using a regional climate model. Pseudo-Global-Warming (PGW) method (Kimura and Kitoh, 2008) is applied for the future climate simulations. NCEP/NCAR reanalysis is used for initial and boundary conditions in present climate simulation and PGW method. MIROC 3.2 medres 2070s output under IPCC SRES A2 scenario and 1990s output under 20c3m scenario used for PGW method. In much-snow cases, Maximum total snow water equivalent over Japan, which is mostly observed in early February, is 49 G ton in the present simulation, the one decreased 26 G ton in the future simulation. The decreasing rate of snow water equivalent due to climate change was 49%. Main cause of the decrease of the total snow water equivalent is strongly affected by the air temperature rise due to global climate change. The difference in present and future precipitation amount is little.

Estimating Snow Water Storage in North America Using CLM4, DART, and Snow Radiance Data Assimilation

NASA Technical Reports Server (NTRS)

Kwon, Yonghwan; Yang, Zong-Liang; Zhao, Long; Hoar, Timothy J.; Toure, Ally M.; Rodell, Matthew

2016-01-01

This paper addresses continental-scale snow estimates in North America using a recently developed snow radiance assimilation (RA) system. A series of RA experiments with the ensemble adjustment Kalman filter are conducted by assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature T(sub B) at 18.7- and 36.5-GHz vertical polarization channels. The overall RA performance in estimating snow depth for North America is improved by simultaneously updating the Community Land Model, version 4 (CLM4), snow/soil states and radiative transfer model (RTM) parameters involved in predicting T(sub B) based on their correlations with the prior T(sub B) (i.e., rule-based RA), although degradations are also observed. The RA system exhibits a more mixed performance for snow cover fraction estimates. Compared to the open-loop run (0.171m RMSE), the overall snow depth estimates are improved by 1.6% (0.168m RMSE) in the rule-based RA whereas the default RA (without a rule) results in a degradation of 3.6% (0.177mRMSE). Significant improvement of the snow depth estimates in the rule-based RA as observed for tundra snow class (11.5%, p < 0.05) and bare soil land-cover type (13.5%, p < 0.05). However, the overall improvement is not significant (p = 0.135) because snow estimates are degraded or marginally improved for other snow classes and land covers, especially the taiga snow class and forest land cover (7.1% and 7.3% degradations, respectively). The current RA system needs to be further refined to enhance snow estimates for various snow types and forested regions.

The value of snow cover

NASA Astrophysics Data System (ADS)

Sokratov, S. A.

2009-04-01

Snow is the natural resource, like soil and water. It has specific properties which allow its use not just for skiing but also for houses cooling in summer (Swedish experience), for air fields construction (Arctic and Antarctic), for dams (north of Russia), for buildings (not only snow-houses of some Polar peoples but artistic hotel attracting tourists in Sweden), and as art material (Sapporo snow festival, Finnish events), etc. "Adjustment" of snow distribution and amount is not only rather common practice (avalanche-protection constructions keeping snow on slopes) but also the practice with long history. So-called "snow irrigation" was used in Russia since XIX century to protect winter crop. What is now named "artificial snow production", is part of much larger pattern. What makes it special—it is unavoidable in present climate and economy situation. 5% of national income in Austria is winter tourism. 50% of the economy in Savoy relay on winter tourism. In terms of money this can be less, but in terms of jobs and income involved this would be even more considerable in Switzerland. As an example—the population of Davos is 14000 in Summer and 50000 in Winter. Skiing is growing business. In present time you can find ski slopes in Turkey and Lebanon. To keep a cite suitable for attracting tourists you need certain amount of sunny days and certain amount of snow. The snow cannons are often the only way to keep a place running. On the other hand, more artificial snow does not necessary attract more tourists, while heavy natural snowfall does attract them. Artificial snow making is costly and requires infrastructure (ponds and electric lines) with very narrow range of weather conditions. Related companies are searching for alternatives and one of them can be "weather regulation" by distribution of some chemical components in clouds. It did not happen yet, but can happen soon. The consequences of such interference in Nature is hardly known. The ski tourism is not the

Air temperature recordings in infant incubators.

PubMed Central

Aynsley-Green, A; Roberton, N R; Rolfe, P

1975-01-01

Air temperatures were continuously recorded inside four incubators with proportional heating control and six incubators with on/off heating cycles, during routine use. The air temperatures in the former were constant throughout, with a gradient between the roof and above-mattress air temperature not exceeding 1 degree C. In contrast, the recordings from the latter models showed a regular cyclical oscillation, the duration of the cycle varying from 14 to 44 minutes. Each incubator had a characteristic profile. The roof air temperature could vary by as much as 7-1 degrees C and the above-mattress air temperature by as much as 2-6 degrees C during the cycle. The oscillation persisted in the air temperatures recorded inside an open-ended hemicylindrical heat shield when used inside these incubators, but was markedly reduced inside a closed-ended heat shield, Carbon dioxide concentration did not increase significantly inside the latter. Images FIG. 1 FIG. 2 PMID:1147654

Rain-on-snow Events in Southwestern British Columbia: A Long-term Analysis of Meteorological Conditions and Snowpack Response

NASA Astrophysics Data System (ADS)

Trubilowicz, J. W.; Moore, D.

2015-12-01

Snowpack dynamics and runoff generation in coastal mountain regions are complicated by rain-on-snow (ROS) events. During major ROS events associated with warm, moist air and strong winds, turbulent heat fluxes can produce substantial melt to supplement rainfall, but previous studies suggest this may not be true for smaller, more frequent events. The internal temperature and water content of the snowpack are also expected to influence runoff generation during ROS events: a cold snowpack with no liquid water content will have the ability to store significant amounts of rainfall, whereas a 'ripe' snowpack may begin to melt and generate outflow with little rain input. However, it is not well understood how antecedent snowpack conditions and energy fluxes differ between ROS events that cause large runoff events and those that do not, in large part because major flood-producing ROS events occur infrequently, and thus are often not sampled during short-term research projects. To generate greater understanding of runoff generation over the spectrum of ROS magnitudes and frequencies, we analyzed data from Automated Snow Pillow (ASP) sites, which record hourly air temperature, precipitation and snowpack water equivalent and offer up to several decades of data at each site. We supplemented the ASP data with output from the North American Regional Reanalysis (NARR) product to support point scale snow modeling for 335 ROS event records from six ASP sites in southwestern BC from 2003 to 2013. Our analysis reconstructed the weather conditions, surface energy exchanges, internal mass and energy states of the snowpack, and generation of snow melt and water available for runoff (WAR) for each ROS event. Results indicate that WAR generation during large events is largely independent of the snowpack conditions, but for smaller events, the antecedent snow conditions play a significant role in either damping or enhancing WAR generation.

The ASMEx snow slab experiment: snow microwave radiative transfer (SMRT) model evaluation

NASA Astrophysics Data System (ADS)

Sandells, Melody; Löwe, Henning; Picard, Ghislain; Dumont, Marie; Essery, Richard; Floury, Nicolas; Kontu, Anna; Lemmetyinen, Juha; Maslanka, William; Mätzler, Christian; Morin, Samuel; Wiesmann, Andreas

2017-04-01

A major uncertainty in snow microwave modelling to date has been the treatment of the snow microstructure. Although observations of microstructural parameters such as the optical grain diameter, specific surface area and correlation length have improved drastically over the last few years, scale factors have been used to derive the parameters needed in microwave emission models from these observations. Previous work has shown that a major difference between electromagnetic models of scattering coefficients is due to the specific snow microstructure models used. The snow microwave radiative transfer model (SMRT) is a new model developed to advance understanding of the role of microstructure and isolate different assumptions in existing microwave models that collectively hinder interpretation of model intercomparison studies. SMRT is implemented in Python and is modular, thus allows switching between different representations in its various components. Here, the role of microstructure is examined with the Improved Born Approximation electromagnetic model. The model is evaluated against scattering and absorption coefficients derived from radiometer measurements of snow slabs taken as part of the Arctic Snow Microstructure Experiment (ASMEx), which took place in Sodankylä, Finland over two seasons. Microtomography observations of slab samples were used to determine parameters for five microstructure models: spherical, exponential, sticky hard sphere, Teubner-Strey and Gaussian random field. SMRT brightness temperature simulations are also compared with radiometric observations of the snow slabs over a reflector plate and an absorber substrate. Agreement between simulations and observations is generally good except for slabs that are highly anisotropic.

Snow Cover, Snowmelt Timing and Stream Power in the Wind River Range, Wyoming

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Foster, James L.; DiGirolamo, Nicolo E.; Riggs, George A.

2011-01-01

Earlier onset of springtime weather, including earlier snowmelt, has been documented in the western United States over at least the last 50 years. Because the majority (is greater than 70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for the management of streamflow. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work, such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud-gap-filled (CGF) map products and 30 years of discharge and meteorological station data are studied. Streamflow data from streams in WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period as a whole. The extent of snow-cover (percent of basin covered) derived from the lowest elevation zone (2500-3000 m) of the WRR, using MODIS CGF snow-cover maps, is strongly correlated with maximum monthly discharge on 30 April, where Spearman's Rank correlation, rs,=0.89 for the decade of the 2000s. We also investigated stream power for Bull Lake Creek above Bull Lake; and found a trend (significant at the 90% confidence level) toward reduced stream power from 1970 to 2009. Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature

Temperature signal in suspended sediment export from an Alpine catchment

NASA Astrophysics Data System (ADS)

Costa, Anna; Molnar, Peter; Stutenbecker, Laura; Bakker, Maarten; Silva, Tiago A.; Schlunegger, Fritz; Lane, Stuart N.; Loizeau, Jean-Luc; Girardclos, Stéphanie

2018-01-01

Suspended sediment export from large Alpine catchments ( > 1000 km2) over decadal timescales is sensitive to a number of factors, including long-term variations in climate, the activation-deactivation of different sediment sources (proglacial areas, hillslopes, etc.), transport through the fluvial system, and potential anthropogenic impacts on the sediment flux (e.g. through impoundments and flow regulation). Here, we report on a marked increase in suspended sediment concentrations observed near the outlet of the upper Rhône River Basin in the mid-1980s. This increase coincides with a statistically significant step-like increase in basin-wide mean air temperature. We explore the possible explanations of the suspended sediment rise in terms of changes in water discharge (transport capacity), and the activation of different potential sources of fine sediment (sediment supply) in the catchment by hydroclimatic forcing. Time series of precipitation and temperature-driven snowmelt, snow cover, and ice melt simulated with a spatially distributed degree-day model, together with erosive rainfall on snow-free surfaces, are tested to explore possible reasons for the rise in suspended sediment concentration. We show that the abrupt change in air temperature reduced snow cover and the contribution of snowmelt, and enhanced ice melt. The results of statistical tests show that the onset of increased ice melt was likely to play a dominant role in the suspended sediment concentration rise in the mid-1980s. Temperature-driven enhanced melting of glaciers, which cover about 10 % of the catchment surface, can increase suspended sediment yields through an increased contribution of sediment-rich glacial meltwater, increased sediment availability due to glacier recession, and increased runoff from sediment-rich proglacial areas. The reduced extent and duration of snow cover in the catchment are also potential contributors to the rise in suspended sediment concentration through

Distribution and variability of total mercury in snow cover-a case study from a semi-urban site in Poznań, Poland.

PubMed

Siudek, Patrycja

2016-12-01

In the present paper, the inter-seasonal Hg variability in snow cover was examined based on multivariate statistical analysis of chemical and meteorological data. Samples of freshly fallen snow cover were collected at the semi-urban site in Poznań (central Poland), during 3-month field measurements in winter 2013. It was showed that concentrations of atmospherically deposited Hg were highly variable in snow cover, from 0.43 to 12.5 ng L -1 , with a mean value of 4.62 ng L -1 . The highest Hg concentration in snow cover coincided with local intensification of fossil fuel burning, indicating large contribution from various anthropogenic sources such as commercial and domestic heating, power generation plants, and traffic-related pollution. Moreover, the variability of Hg in collected snow samples was associated with long-range transport of pollutants, nocturnal inversion layer, low boundary layer height, and relatively low air temperature. For three snow episodes, Hg concentration in snow cover was attributed to southerly advection, suggesting significant contribution from the highly polluted region of Poland (Upper Silesia) and major European industrial hotspots. However, the peak Hg concentration was measured in samples collected during predominant N to NE advection of polluted air masses and after a relatively longer period without precipitation. Such significant contribution to the higher Hg accumulation in snow cover was associated with intensive emission from anthropogenic sources (coal combustion) and atmospheric conditions in this area. These results suggest that further measurements are needed to determine how the Hg transformation paths in snow cover change in response to longer/shorter duration of snow cover occurrence and to determine the interactions between mercury and absorbing carbonaceous aerosols in the light of climate change.

GPS interferometric reflectometry for ground-based remote sensing of snow depth and density

NASA Astrophysics Data System (ADS)

Nievinski, F. G.; Larson, K. M.; Gutmann, E. D.; Zavorotny, V.; Williams, M. W.

2011-12-01

GPS interferometric reflectometry (GPS-IR) is a method that exploits multipath for ground-based remote sensing in the surroundings of a GPS antenna. It operates on L-band, leveraging hundreds of conventional GPS sites existing in the U.S., with a typical footprint of 30-meter radius. Multipath is the coherent interference of line-of-sight and reflected signals; as the two go in and out of phase, the power recorded by a GPS interferometer goes through peaks and troughs that can be related to land surface characteristics, such as soil moisture and snow depth. GPS-IR has been demonstrated to be capable of retrieving snow depth during extended periods at various locations, as validated by comparisons with a continuously-operating terrestrial scanning laser, an airborne LIDAR campaign, manual stake surveys, and ultrasonic depth sensors. Here we explore the possibility of retrieving snow density, too. This will determine the feasibility and limitations of GPS-IR for monitoring of snow water equivalent (SWE). Data were collected at Niwot Ridge LTER in Colorado, at a 3,500-m altitude alpine tundra site. Niwot receives around 1,000 mm of precipitation per year and has a mean annual air temperature of -3.8°C. Snow density and temperature is measured in 10-cm vertical increments at snowpits dug approximately every week. A continuously-operating GPS system established in 2009 allows for measurement of the snowpack several times a day at multiple azimuths as satellites rise and set. The typical peak snow depth at the GPS site is 1.5 m, with a peak depth during the study period of 1.7 m in 2009/2010 and 2.5 m in 2010/2011; density ranged 200-600 kg/m3. We employ a forward/inverse model originally developed for snow depth and recently extended to account for layering to study both synthetic and real observations. We present comparisons of density estimates obtained using GPS-IR observations to snowpit field data, focusing initially on dry snow. In addition, we explore the

Projections for Changes in Natural and Technical Snow Reliability of a Major Turkish Ski Resort by Using RegCM4.3.5

NASA Astrophysics Data System (ADS)

Ozturk, Tugba; Cenk Demiroglu, O.; Tufan Turp, M.; Türkeş, Murat; Kurnaz, M. Levent

2014-05-01

Climate change has been and increasingly will be a major threat to the ski tourism industry whose survival is highly dependent on existence of snow cover of sufficient depth and duration. The common knowledge requires that in order for a ski resort to be viable, it has to perform operations for at least 100 days in seven out of ten winters. For this matter, it is now even more usual for the ski resorts to adapt to this issue by technical snowmaking. In this study, projected future changes for the period of 2010-2040, 2040-2070, and 2070-2100 in air temperature, relative humidity, and snow depth climatology and variability with respect to the control period of 1970-2000 were assessed for the domain of a major ski resort in Turkey. Regional Climate Model (RegCM4.3.5) of ICTP (International Centre for Theoretical Physics) was used for projections of future and present climate conditions. HadGEM2 global climate model of the Met Office Hadley Centre, MPI-ESM-MR of the Max Planck Institute for Meteorology, GFDL-ESM2M of the National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory were downscaled to 10 km for the resort and its surrounding region. Both the projections and the downscaling were realized according to the RCP4.5 and the RCP8.5 emission scenarios of the IPCC. The outputs on snow depth were used for a count of the changes on snow cover duration sufficient for skiing actitivies, signaling natural snow-reliability, whereas the outputs on air temperature and relative humidity were utilized for determination of wet-bulb temperatures. The latter measure was used to interpret the changes in the snowmaking capacity, in other words; technical snow-reliability, of the resort. This work was supported by the BU Reasearch Fund under the project number 7362. One of the authors (MLK) was partially supported by Mercator-IPC Fellowship Program.

Evaluation of distributed hydrologic impacts of temperature-index and energy-based snow models

USDA-ARS?s Scientific Manuscript database

Proper characterizations of snow melt and accumulation processes in the snow-dominated mountain environment are needed to understand and predict spatiotemporal distribution of water cycle components. Two commonly used strategies in modeling of snow accumulation and melt are the full energy based and...

John Snow: the first hired gun?

PubMed

Lilienfeld, D E

2000-07-01

The 1854 English cholera outbreak led to reform of Victorian public health legislation, including the Nuisances Removal and Diseases Prevention Act. The reforms threatened the closure of many factories whose fumes were considered hazardous to the public's health. The second witness to appear before the Parliamentary committee considering the reforms was Dr. John Snow. Snow testified on behalf of the manufacturers threatened by the reforms. He stated that the fumes from such establishments were not hazardous. He contended that the workers in these factories did not become ill as a result of their exposures, and therefore these fumes could not be a hazard to the general public's health. Snow also presented data from the 1854 cholera outbreak as the basis for his belief that epidemic diseases were transmitted by water, not air. Although the data concerned cholera, Snow extended the inference to all epidemic diseases. When the committee's report was published, The Lancet chastised Snow in a stinging editorial. Parliament subsequently revised the bill in favor of the manufacturers and passed it into law. The implications of this particular episode in the history of epidemiology are discussed.

Controlled-Temperature Hot-Air Gun

NASA Technical Reports Server (NTRS)

Munoz, M. C.

1986-01-01

Materials that find applications in wind tunnels first tested in laboratory. Hot-Air Gun differs from commercial units in that flow rate and temperature monitored and controlled. With typical compressed-airsupply pressure of 25 to 38 psi (170 to 260 kPa), flow rate and maximum temperature are 34 stdft3/min (0.96 stdm3/min) and 1,090 degrees F (590 degrees C), respectively. Resembling elaborate but carefully regulated hot-air gun, setup used to apply blasts of air temperatures above 1,500 degrees F (815 degrees C) to test specimens.

A distributed snow-evolution modeling system (SnowModel)

Treesearch

Glen E. Liston; Kelly Elder

2006-01-01

SnowModel is a spatially distributed snow-evolution modeling system designed for application in landscapes, climates, and conditions where snow occurs. It is an aggregation of four submodels: MicroMet defines meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowPack simulates snow depth and water-equivalent evolution, and SnowTran-3D...

Evaluation of the most suitable threshold value for modelling snow glacier melt through T- index approach: the case study of Forni Glacier (Italian Alps)

NASA Astrophysics Data System (ADS)

Senese, Antonella; Maugeri, Maurizio; Vuillermoz, Elisa; Smiraglia, Claudio; Diolaiuti, Guglielmina

2014-05-01

Glacier melt occurs whenever the surface temperature is null (273.15 K) and the net energy budget is positive. These conditions can be assessed by analyzing meteorological and energy data acquired by a supraglacial Automatic Weather Station (AWS). In the case this latter is not present at the glacier surface the assessment of actual melting conditions and the evaluation of melt amount is difficult and degree-day (also named T-index) models are applied. These approaches require the choice of a correct temperature threshold. In fact, melt does not necessarily occur at daily air temperatures higher than 273.15 K, since it is determined by the energy budget which in turn is only indirectly affected by air temperature. This is the case of the late spring period when ablation processes start at the glacier surface thus progressively reducing snow thickness. In this study, to detect the most indicative air temperature threshold witnessing melt conditions in the April-June period, we analyzed air temperature data recorded from 2006 to 2012 by a supraglacial AWS (at 2631 m a.s.l.) on the ablation tongue of the Forni Glacier (Italy), and by a weather station located nearby the studied glacier (at Bormio, 1225 m a.s.l.). Moreover we evaluated the glacier energy budget (which gives the actual melt, Senese et al., 2012) and the snow water equivalent values during this time-frame. Then the ablation amount was estimated both from the surface energy balance (MEB from supraglacial AWS data) and from degree-day method (MT-INDEX, in this latter case applying the mean tropospheric lapse rate to temperature data acquired at Bormio changing the air temperature threshold) and the results were compared. We found that the mean tropospheric lapse rate permits a good and reliable reconstruction of daily glacier air temperature conditions and the major uncertainty in the computation of snow melt from degree-day models is driven by the choice of an appropriate air temperature threshold. Then

Spring snow albedo feedback in daily data over Russia: Comparing in-situ measurements with reanalysis products.

NASA Astrophysics Data System (ADS)

Wegmann, M.; Zolina, O.; Jacobi, H. W.

2016-12-01

Global warming is enhanced at high northern latitudes where the Arctic surface air temperature has risen at twice the rate of the global average in recent decades - a feature called Arctic amplification. This recent Arctic warming signal likely results from several factors such as the albedo feedback due to a diminishing cryosphere, enhanced poleward atmospheric and oceanic heat transport, and changes in humidity. Surface albedo feedback is stating that the additional amount of shortwave radiation at the top of the atmosphere decreases with decreasing surface albedo whereas surface air temperature increases with decreasing surface albedo. It is considered a positive feedback in that an initial warming perturbation than kicks off a strengthening warming. Looking at the Northern Hemisphere with its large landmasses, snow albedo feedback is especially strong since most of these landmasses experience snow cover during boreal wintertime. Unfortunately, so far there remains a lack of reliable observational data over large parts of the cryosphere. Satellite products cover large parts of the NH, however lack high temporal resolution and have problems with large solar zenith angles as well as over complex terrain (eg. Wang et al. 2014). Our analysis focuses at the Russian territory where we utilize in-situ radiation and snow depth measurements. We found 50 stations which measure both variables on a daily basis for the period 2000-2013. Since Hall (2004) found that 50% of the notal NH snow albedo feedback caused by global warming occurs during NH spring, we focus on the transition period of March to June (MAMJ). Thackeray & Fletcher 2006 compared albedo feedback processes CMIP3 and CMIP5 model families and found while the models represent the feedback process accurately, there are still inherent biases and outdated parameterizations. Therefore we use the daily observations and state of the art reanalysis products to 1) evaluate reanalysis and model products in respect to

Near-surface temperature inversion during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

NASA Astrophysics Data System (ADS)

Adolph, Alden C.; Albert, Mary R.; Hall, Dorothy K.

2018-03-01

As rapid warming of the Arctic occurs, it is imperative that climate indicators such as temperature be monitored over large areas to understand and predict the effects of climate changes. Temperatures are traditionally tracked using in situ 2 m air temperatures and can also be assessed using remote sensing techniques. Remote sensing is especially valuable over the Greenland Ice Sheet, where few ground-based air temperature measurements exist. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and the temperature of the actual snow surface (referred to as skin temperature) can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign extending from 8 June to 18 July 2015, near Summit Station in Greenland, to study surface temperature using the following measurements: skin temperature measured by an infrared (IR) sensor, 2 m air temperature measured by a National Oceanic and Atmospheric Administration (NOAA) meteorological station, and a Moderate Resolution Imaging Spectroradiometer (MODIS) surface temperature product. Our data indicate that 2 m air temperature is often significantly higher than snow skin temperature measured in situ, and this finding may account for apparent biases in previous studies of MODIS products that used 2 m air temperature for validation. This inversion is present during our study period when incoming solar radiation and wind speed are both low. As compared to our in situ IR skin temperature measurements, after additional cloud masking, the MOD/MYD11 Collection 6 surface temperature standard product has an RMSE of 1.0 °C and a mean bias of -0.4 °C, spanning a range of temperatures from -35 to -5 °C (RMSE = 1.6 °C and mean bias = -0.7 °C prior to cloud masking). For our study area and time series, MODIS surface temperature products agree with skin

Observed Trends in West Coast Atmospheric River Temperatures

NASA Astrophysics Data System (ADS)

Gonzales, K. R.; Swain, D. L.; Barnes, E. A.; Diffenbaugh, N. S.

2017-12-01

Understanding the changing characteristics of atmospheric rivers (ARs) in a warming climate is critical in light of their importance in generating precipitation and creating the potential for flood and geophysical hazards. Numerous changes to the characteristics of ARs under the influence of a changing climate have been documented or hypothesized; one simple hypothesis is that AR precipitation will occur at increasingly warm temperatures, potentially altering the critical rain/snow balance in snowpack-dependent watersheds and causing precipitation at higher elevations to fall as rain rather than snow. Not only would warmer, primarily rain-producing ARs greatly affect snow accumulation, but they might also increase the intensity of runoff, the potential for flooding, and the occurrence of rain-on-snow events. Since the West Coast of North America relies heavily on ARs as a source of precipitation and snowpack accumulation, these regions may be profoundly affected by changes in AR temperatures and associated impacts. Using a catalog of ARs encompassing 1979-2014 and ERA-Interim reanalysis, we assess whether detectable trends exist in cool season AR temperatures over the Pacific Coast states of California, Oregon, and Washington. We define AR temperature by the mean temperature of the air mass between 1000 hPa and 750 hPa, and compare AR temperature trends to background temperature trends over the same period. We find overall AR warming over this period and particularly robust warming in March ARs coincident with an apparent poleward shift in March AR frequency. Further analysis suggests that warmer ARs have higher rates of warming than cooler ARs. AR temperature trends generally scale with background temperature trends, although some regions exhibit a near one-to-one relationship while others are largely uncorrelated. The observed warming of ARs making landfall on the West Coast may have potentially significant implications for rain vs. snow at higher elevations, the

Effects of wintertime atmospheric river landfalls on surface air temperatures in the Western US: Analyses and model evaluation

NASA Astrophysics Data System (ADS)

Kim, J.; Guan, B.; Waliser, D. E.; Ferraro, R.

2016-12-01

Landfalling atmospheric rivers (ARs) affect the wintertime surface air temperatures as shown in earlier studies. The AR-related surface air temperatures can exert significant influence on the hydrology in the US Pacific coast region especially through rainfall-snowfall partitioning and the snowpack in high elevation watersheds as they are directly related with the freezing-level altitudes. These effects of temperature perturbations can in turn affect hydrologic events of various time scales such as flash flooding by the combined effects of rainfall and snowmelt, and the warm season runoff from melting snowpack, especially in conjunction with the AR effects on winter precipitation and rain-on-snow events in WUS. Thus, understanding the effects of AR landfalls on the surface temperatures and examining the capability of climate models in simulating these effects are an important practical concern for WUS. This study aims to understand the effects of AR landfalls on the characteristics of surface air temperatures in WUS, especially seasonal means and PDFs and to evaluate the fidelity of model data produced in the NASA downscaling experiment for the 10 winters from Nov. 1999 to Mar. 2010 using an AR-landfall chronology based on the vertically-integrated water vapor flux calculated from the MERRA2 reanalysis. Model skill is measured using metrics including regional means, a skill score based on correlations and mean-square errors, the similarity between two PDF shapes, and Taylor diagrams. Results show that the AR landfalls are related with higher surface air temperatures in WUS, especially in inland regions. The AR landfalls also reduce the range of surface air temperature PDF, largely by reducing the events in the lower temperature range. The shift in the surface air temperature PDF is consistent with the positive anomalies in the winter-mean temperature. Model data from the NASA downscaling experiment reproduce the AR effects on the temperature PDF, at least

Hydrologic response across a snow persistence gradient on the west and east slopes of the Rocky Mountains in Colorado

NASA Astrophysics Data System (ADS)

Richard, G. A.; Hammond, J. C.; Kampf, S. K.; Moore, C. D.; Eurich, A.

2017-12-01

Snowpack trend analyses and modeling studies suggest that lower elevation snowpacks in mountain regions are most sensitive to drought and warming temperatures, however, in Colorado, most snow monitoring occurs in the high elevations where snow lasts throughout the winter and most streamflow monitoring occurs at lower elevations. The lack of combined snow and streamflow monitoring in watersheds along the transition from intermittent to persistent snow creates a gap in our understanding of snowmelt and runoff within the intermittent-persistent snow transition. Expanded hydrologic monitoring that spans the gradient of snow conditions in Colorado can help improve streamflow prediction and inform land and water managers. This study established hydrologic monitoring watersheds in intermittent, transitional, and persistent snow zones on the east slope and west slope of the Rocky Mountains in Colorado, and uses this monitoring network to improve understanding of how snow accumulation and melt affect soil moisture and streamflow generation under different snow conditions. We monitored six small watersheds (three west slope, three east slope) (0.8 to 3.9 km2) that drain intermittent, transitional, and persistent snow zones. At each site, we measured: streamflow, snow depth, soil moisture, precipitation, air temperature, and snow water equivalent (SWE). In our first season of monitoring, the west slope persistent and transitional sites had more mid-winter melt and infiltration, shorter snowpack duration, and lower peak SWE than the east slope sites. Snow cover remained at the east slope persistent site into June, whereas much of the snow at the persistent site on the west slope had already melted by early June. The difference in soil water input likely has consequences for streamflow response that we will continue to examine in future years. At the west slope intermittent site, the stream did not flow during the entire first year of monitoring, while at the east slope

X-ray computed microtomography of sea ice - comment on "A review of air-ice chemical and physical interactions (AICI): liquids, quasi-liquids, and solids in snow" by Bartels-Rausch et al. (2014)

NASA Astrophysics Data System (ADS)

Obbard, R. W.

2015-07-01

This comment addresses a statement made in "A review of air-ice chemical and physical interactions (AICI): liquids, quasi-liquids, and solids in snow" by Bartels-Rausch et al. (Atmos. Chem. Phys., 14, 1587-1633, doi:10.5194/acp-14-1587-2014, 2014). Here we rebut the assertion that X-ray computed microtomography of sea ice fails to reveal liquid brine inclusions by discussing the phases present at the analysis temperature.

Seasonal Snow Extent and Snow Mass in South America Using SMMR and SSM/I Passive Microwave Data (1979-2003)

NASA Technical Reports Server (NTRS)

Foster, J. L.; Hall, D. K.; Chiu, L.; Kelly, R. E.; Powell, H.; Chiu, L.

2007-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-satellite and the Special Sensor Microwave Imagers (SSM/I) on board Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2003, both snow cover extent and snow depth (snow mass) were investigated during coldest months (May-September), primarily in the Patagonia area of Argentina and in Chile. Most of the seasonal snow in South America is in the Patagonia region of Argentina. Since winter temperatures in this region are often above freezing, the coldest winter month was found to be the month having the most extensive snow cover and also usually the month having the deepest snow cover as well. Sharp year-to-year differences were recorded using the passive microwave observations. The average snow cover extent for July, the month with the greatest average snow extent during the 25-year period of record, is 320,700 km(exp 2). In July of 1984, the average monthly snow cover was 701,250 km(exp 2) - the most extensive coverage observed between 1979 and 2003. However, in July of 1989, snow cover extent was only 120 km(exp 2). The 25-year period of record shows a sinusoidal like pattern, though there appears to be no obvious trend in either increasing or decreasing snow extent or snow mass between 1979 and 2003.

The layered evolution of fabric and microstructure of snow at Point Barnola, Central East Antarctica

NASA Astrophysics Data System (ADS)

Calonne, Neige; Montagnat, Maurine; Matzl, Margret; Schneebeli, Martin

2017-02-01

Snow fabric, defined as the distribution of the c-axis orientations of the ice crystals in snow, is poorly known. So far, only one study exits that measured snow fabric based on a statistically representative technique. This recent study has revealed the impact of temperature gradient metamorphism on the evolution of fabric in natural snow, based on cold laboratory experiments. On polar ice sheets, snow properties are currently investigated regarding their strong variability in time and space, notably because of their potential influence on firn processes and consequently on ice core analysis. Here, we present measurements of fabric and microstructure of snow from Point Barnola, East Antarctica (close to Dome C). We analyzed a snow profile from 0 to 3 m depth, where temperature gradients occur. The main contributions of the paper are (1) a detailed characterization of snow in the upper meters of the ice sheet, especially by providing data on snow fabric, and (2) the study of a fundamental snow process, never observed up to now in a natural snowpack, namely the role of temperature gradient metamorphism on the evolution of the snow fabric. Snow samples were scanned by micro-tomography to measure continuous profiles of microstructural properties (density, specific surface area and pore thickness). Fabric analysis was performed using an automatic ice texture analyzer on 77 representative thin sections cut out from the samples. Different types of snow fabric could be identified and persist at depth. Snow fabric is significantly correlated with snow microstructure, pointing to the simultaneous influence of temperature gradient metamorphism on both properties. We propose a mechanism based on preferential grain growth to explain the fabric evolution under temperature gradients. Our work opens the question of how such a layered profile of fabric and microstructure evolves at depth and further influences the physical and mechanical properties of snow and firn. More generally

Snow water equivalent mapping in Norway

NASA Astrophysics Data System (ADS)

Tveito, O. E.; Udnæs, H.-C.; Engeset, R.; Førland, E. J.; Isaksen, K.; Mengistu, Z.

2003-04-01

In high latitude area snow covers the ground large parts of the year. Information about the water volume as snow is of major importance in many respects. Flood forecasters at NVE need it in order to assess possible flood risks. Hydropower producers need it to plan the most efficient production of the water in their reservoirs, traders to estimate the potential energy available for the market. Meteorologists on their side use the information as boundary conditions in weather forecasting models. The Norwegian meteorological institute has provided snow accumulation maps for Norway for more than 50 years. These maps are now produced twice a month in the winter season. They show the accumulated precipitation in the winter season from the day the permanent snow cover is established. They do however not take melting into account, and do therefore not give a good description of the actual snow amounts during and after periods with snowmelt. Due to an increased need for a direct measure of water volumes as snow cover, met.no and NVE initialized a joint project in order to establish maps of the actual snow cover expressed in water equivalents. The project utilizes recent developments in the use of GIS in spatial modeling. Daily precipitation and temperature are distributed in space by using objective spatial interpolation methods. The interpolation considers topographical and other geographical parameters as well as weather type information. A degree-day model is used at each modeling point to calculate snow-accumulation and snowmelt. The maps represent a spatial scale of 1x1 km2. The modeled snow reservoir is validated by snow pillow values as well traditional snow depth observations. Preliminary results show that the new snow modeling approach reproduces the snow water equivalent well. The spatial approach also opens for a wide use in the terms of areal analysis.

Retrieval of air temperatures from crowd-sourced battery temperatures of cell phones

NASA Astrophysics Data System (ADS)

Overeem, Aart; Robinson, James; Leijnse, Hidde; Uijlenhoet, Remko; Steeneveld, Gert-Jan; Horn, Berthold K. P.

2013-04-01

Accurate air temperature observations are important for urban meteorology, for example to study the urban heat island and adverse effects of high temperatures on human health. The number of available temperature observations is often relatively limited. A new development is presented to derive temperature information for the urban canopy from an alternative source: cell phones. Battery temperature data were collected by users of an Android application for cell phones (opensignal.com). The application automatically sends battery temperature data to a server for storage. In this study, battery temperatures are averaged in space and time to obtain daily averaged battery temperatures for each city separately. A regression model, which can be related to a physical model, is employed to retrieve daily air temperatures from battery temperatures. The model is calibrated with observed air temperatures from a meteorological station of an airport located in or near the city. Time series of air temperatures are obtained for each city for a period of several months, where 50% of the data is for independent verification. Results are presented for Buenos Aires, London, Los Angeles, Paris, Mexico City, Moscow, Rome, and Sao Paulo. The evolution of the retrieved air temperatures often correspond well with the observed ones. The mean absolute error of daily air temperatures is less than 2 degrees Celsius, and the bias is within 1 degree Celsius. This shows that monitoring air temperatures employing an Android application holds great promise. Since 75% of the world's population has a cell phone, 20% of the land surface of the earth has cellular telephone coverage, and 500 million devices use the Android operating system, there is a huge potential for measuring air temperatures employing cell phones. This could eventually lead to real-time world-wide temperature maps.

Early snow melts and biomass burning over Eastern Eurasia and their impacts on the air quality in Northern Japan

NASA Astrophysics Data System (ADS)

Yasunari, T. J.; daSilva, A.; Akiyama, M.; Hayasaki, M.; Murao, N.; Kim, K. M.

2016-12-01

We investigated monthly characteristics including a couple of large biomass burnings (BB) in Eastern Eurasia during 2003 and 2014, and the smoke impacts on Northern Japan. The new re-analyses data including the aerosol data assimilation, called MERRA-2, which was produced by the NASA's Global Modeling and Assimilation Office (GMAO), the monthly mean MODIS snow cover fraction (SCF) data (MOD10CM; further re-gridded), and the observations on PM2.5, elemental carbon (EC), and organic carbon (OC) in Sapporo city (Hokkaido, Japan), were used in our analyses. For the MERRA-2 and MODIS SCF data, we calculated 12-year climatology for each month and these anomalies from the climatology on the focused variables. Three-month means of the anomalies for the last three months until the BB months were calculated except for the SCF. For the SCF, the three-month mean anomalies until the one month before the BB months were also calculated. Here we start especially focusing on the identified fire months with the MERRA-2 data (May 2003, April 2008, and July 2014) in terms of these smoke impacts on the air qualities in Northern Japan (i.e., Hokkaido). We identified two types of biomass burning patterns within these three months. For the BBs in May 2003 and April 2008, the main BB areas were seen in the eastern part of the Lake Baikal. In July 2014, the main BB area was in the Sakha Republic and close to the Arctic region. Then, the MERRA-2 data overestimated the observations (EC, OC, and PM2.5) in Sapporo (Hokkaido, Japan) during the smoke transports, but the elevated timings were well reproduced. For all the three BB cases, abnormally reduced SCF were seen by the one month before the Eurasian BB generations (i.e., earlier than the BB generations). The positive and negative anomalies of 2-m temperature and surface soil wetness, covering the three-month until the BB months, were identified. These suggest that early snow-melting anomalies for these three years could make the following BB

A Blended Global Snow Product using Visible, Passive Microwave and Scatterometer Satellite Data

NASA Technical Reports Server (NTRS)

Foster, James L.; Hall, Dorothy K.; Eylander, John B.; Riggs, George A.; Nghiem, Son V.; Tedesco, Marco; Kim, Edward; Montesano, Paul M.; Kelly, Richard E. J.; Casey, Kimberly A.;

Snowscape Ecology: Linking Snow Properties to Wildlife Movements and Demography

NASA Astrophysics Data System (ADS)

Prugh, L.; Verbyla, D.; van de Kerk, M.; Mahoney, P.; Sivy, K. J.; Liston, G. E.; Nolin, A. W.

2017-12-01

Snow enshrouds up to one third of the global land mass annually and exerts a major influence on animals that reside in these "snowscapes," (landscapes covered in snow). Dynamic snowscapes may have especially strong effects in arctic and boreal regions where dry snow persists for much of the year. Changes in temperature and hydrology are transforming northern regions, with profound implications for wildlife that are not well understood. We report initial findings from a NASA ABoVE project examining effects of snow properties on Dall sheep (Ovis dalli dalli). We used the MODSCAG snow fraction product to map spring snowline elevations and snow-off dates from 2000-2015 throughout the global range of Dall sheep in Alaska and northwestern Canada. We found a negative effect of spring snow cover on Dall sheep recruitment that increased with latitude. Using meteorological data and a daily freeze/thaw status product derived from passive microwave remote sensing from 1983-2012, we found that sheep survival rates increased in years with higher temperatures, less winter precipitation, fewer spring freeze-thaw events, and more winter freeze-thaw events. To examine the effects of snow depth and density on sheep movements, we used location data from GPS-collared sheep and a snowpack evolution model (SnowModel). We found that sheep selected for shallow, fluffy snow at high elevations, but they selected for denser snow as depth increased. Our field measurements identified a critical snow density threshold of 329 (± 18 SE) kg/m3 to support the weight of Dall sheep. Thus, sheep may require areas of shallow, fluffy snow for foraging, while relying on hard-packed snow for winter travel. These findings highlight the importance of multiple snowscape properties on wildlife movements and demography. The integrated study of snow properties and ecological processes, which we call snowscape ecology, will greatly improve global change forecasting.

Seasonal Snow Extent and Snow Mass in South America using SMMR and SSM/I Passive Microwave Data (1979-2006)

NASA Technical Reports Server (NTRS)

Foster, J. L.; Hall, D. K.; Kelly, R. E. J.; Chiu, L.

2008-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite and the Special Sensor Microwave Imagers (SSM/I) onboard Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2006, both snow cover extent and snow water equivalent (snow mass) were investigated during the coldest months (May-September), primarily in the Patagonia area of Argentina and in the Andes of Chile, Argentina and Bolivia, where most of the seasonal snow is found. Since winter temperatures in this region are often above freezing, the coldest winter month was found to be the month having the most extensive snow cover and usually the month having the deepest snow cover as well. Sharp year-to-year differences were recorded using the passive microwave observations. The average snow cover extent for July, the month with the greatest average extent during the 28-year period of record, is 321,674 km(exp 2). In July of 1984, the average monthly snow cover extent was 701,250 km(exp 2) the most extensive coverage observed between 1979 and 2006. However, in July of 1989, snow cover extent was only 120,000 km(exp 2). The 28-year period of record shows a sinusoidal like pattern for both snow cover and snow mass, though neither trend is significant at the 95% level.

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures for Falling Snow Events

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail; Johnson, Benjamin T.

2011-01-01

Physically based passive microwave precipitation retrieval algorithms require a set of relationships between satellite -observed brightness temperatures (TBs) and the physical state of the underlying atmosphere and surface. These relationships are nonlinear, such that inversions are ill ]posed especially over variable land surfaces. In order to elucidate these relationships, this work presents a theoretical analysis using TB weighting functions to quantify the percentage influence of the TB resulting from absorption, emission, and/or reflection from the surface, as well as from frozen hydrometeors in clouds, from atmospheric water vapor, and from other contributors. The percentage analysis was also compared to Jacobians. The results are presented for frequencies from 10 to 874 GHz, for individual snow profiles, and for averages over three cloud-resolving model simulations of falling snow. The bulk structure (e.g., ice water path and cloud depth) of the underlying cloud scene was found to affect the resultant TB and percentages, producing different values for blizzard, lake effect, and synoptic snow events. The slant path at a 53 viewing angle increases the hydrometeor contributions relative to nadir viewing channels. Jacobians provide the magnitude and direction of change in the TB values due to a change in the underlying scene; however, the percentage analysis provides detailed information on how that change affected contributions to the TB from the surface, hydrometeors, and water vapor. The TB percentage information presented in this paper provides information about the relative contributions to the TB and supplies key pieces of information required to develop and improve precipitation retrievals over land surfaces.

A modified force-restore approach to modeling snow-surface heat fluxes

Treesearch

Charles H. Luce; David G. Tarboton

2001-01-01

Accurate modeling of the energy balance of a snowpack requires good estimates of the snow surface temperature. The snow surface temperature allows a balance between atmospheric heat fluxes and the conductive flux into the snowpack. While the dependency of atmospheric fluxes on surface temperature is reasonably well understood and parameterized, conduction of heat from...

Evaluation of an improved intermediate complexity snow scheme in the ORCHIDEE land surface model

NASA Astrophysics Data System (ADS)

Wang, Tao; Ottlé, Catherine; Boone, Aaron; Ciais, Philippe; Brun, Eric; Morin, Samuel; Krinner, Gerhard; Piao, Shilong; Peng, Shushi

2013-06-01

Snow plays an important role in land surface models (LSM) for climate and model applied over Fran studies, but its current treatment as a single layer of constant density and thermal conductivity in ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) induces significant deficiencies. The intermediate complexity snow scheme ISBA-ES (Interaction between Soil, Biosphere and Atmosphere-Explicit Snow) that includes key snow processes has been adapted and implemented into ORCHIDEE, referred to here as ORCHIDEE-ES. In this study, the adapted scheme is evaluated against the observations from the alpine site Col de Porte (CDP) with a continuous 18 year data set and from sites distributed in northern Eurasia. At CDP, the comparisons of snow depth, snow water equivalent, surface temperature, snow albedo, and snowmelt runoff reveal that the improved scheme in ORCHIDEE is capable of simulating the internal snow processes better than the original one. Preliminary sensitivity tests indicate that snow albedo parameterization is the main cause for the large difference in snow-related variables but not for soil temperature simulated by the two models. The ability of the ORCHIDEE-ES to better simulate snow thermal conductivity mainly results in differences in soil temperatures. These are confirmed by performing sensitivity analysis of ORCHIDEE-ES parameters using the Morris method. These features can enable us to more realistically investigate interactions between snow and soil thermal regimes (and related soil carbon decomposition). When the two models are compared over sites located in northern Eurasia from 1979 to 1993, snow-related variables and 20 cm soil temperature are better reproduced by ORCHIDEE-ES than ORCHIDEE, revealing a more accurate representation of spatio-temporal variability.

Changing snow cover in tundra ecosystems tips the Arctic carbon balance

NASA Astrophysics Data System (ADS)

Zona, D.; Hufkens, K.; Gioli, B.; Kalhori, A. A. M.; Oechel, W. C.

2014-12-01

The Arctic environment has witnessed important changes due to global warming, resulting in increased surface air temperatures and rain events which both exacerbate snow cover deterioration (Semmens et al, 2013; Rennert et al, 2009; White et al, 2007; Min et al, 2008; Sharp et al, 2013; Schaeffer et al, 2013). Snow cover duration is declining by almost 20% per decade, a far higher rate than model estimates (Derksen and Brown, 2012). Concomitant with increasing temperatures and decreasing snow cover duration, the length of the arctic growing season is reported to have increased by 1.1 - 4.9 days per decade since 1951 (Menzel et al, 2006), and, plant productivity and CO2 uptake from arctic vegetation are strongly influenced by changes in growing season length (Myneni et al., 1997; Schaefer et al., 2005; Euskirchen et al., 2006). Based on more than a decade of eddy flux measurements in Arctic tundra ecosystems across the North slope of Alaska, and remotely sensed snow cover data, we show that earlier snow melt in the spring increase C uptake while an extended snow free period in autumn is associated with a higher C loss. Here we present the impacts of changes in snow cover dynamics between spring and autumn in arctic tundra ecosystems on the carbon dynamics and net C balance of the Alaskan Arctic. ReferencesDerksen, C., Brown R. (2012) Geophys. Res. Lett., doi:10.1029/2012GL053387 Euskirchen, E.S., et al. (2006) Glob. Change Biol., 12, 731-750. Menzel, A., et al. 2006. Glob. Change Biol., 12, 1969-1976. Min SK, Zhang X, Zweirs F (2008) Science 320: 518-520. Rennert K J, Roe G, Putkonen J and Bitz C M (2009) J. Clim. 22 2302-15. Schaefer, K., Denning A.S., Leonard O. (2005) Global Biogeochem. Cycles, 19, GB3017. Schaeffer, S. M., Sharp, E., Schimel, J. P. & Welker, J. M. (2013). Soil- plant N processes in a High Arctic ecosystem, NW Greenland are altered by long-term experimental warming and higher rainfall. Glob. Change Biol., 11, 3529-39. doi: 10.1111/gcb.12318

Potential genotoxic effects of melted snow from an urban area revealed by the Allium cepa test.

PubMed

Blagojević, Jelena; Stamenković, Gorana; Vujosević, Mladen

2009-09-01

The presence of well-known atmospheric pollutants is regularly screened for in large towns but knowledge about the effects of mixtures of different pollutants and especially their genotoxic potential is largely missing. Since falling snow collects pollutants from the air, melted snow samples could be suitable for evaluating potential genotoxicity. For this purpose the Allium cepa anaphase-telophase test was used to analyse melted snow samples from Belgrade, the capital city of Serbia. Samples of snow were taken at two sites, characterized by differences in pollution intensity, in three successive years. At the more polluted site the analyses showed a very high degree of both toxicity and genotoxicity in the first year of the study corresponding to the effects of the known mutagen used as the positive control. At the other site the situation was much better but not without warning signals. The results showed that standard analyses for the presence of certain contaminants in the air do not give an accurate picture of the possible consequences of urban air pollution because the genotoxic potential remains hidden. The A. cepa test has been demonstrated to be very convenient for evaluation of air pollution through analyses of melted snow samples.

Unusually Low Snow Cover in the U.S.

NASA Technical Reports Server (NTRS)

2002-01-01

New maps of snow cover produced by NASA's Terra satellite show that this year's snow line stayed farther north than normal. When combined with land surface temperature measurements, the observations confirm earlier National Oceanic and Atmospheric Administration reports that the United States was unusually warm and dry this past winter. The above map shows snow cover over the continental United States from February 2002 and is based on data acquired by the Moderate-Resolution Imaging Spectroradiometer (MODIS). The amount of land covered by snow during this period was much lower than usual. With the exception of the western mountain ranges and the Great Lakes region, the country was mostly snow free. The solid red line marks the average location of the monthly snow extent; white areas are snow-covered ground. Snow was mapped at approximately 5 kilometer pixel resolution on a daily basis and then combined, or composited, every eight days. If a pixel was at least 50 percent snow covered during all of the eight-day periods that month, it was mapped as snow covered for the whole month. For more information, images, and animations, read: Terra Satellite Data Confirm Unusually Warm, Dry U.S. Winter Image by Robert Simmon, based on data from the MODIS Snow/Ice Global Mapping Project

Acoustic Wave Propagation in Snow Based on a Biot-Type Porous Model

NASA Astrophysics Data System (ADS)

Sidler, R.

2014-12-01

Despite the fact that acoustic methods are inexpensive, robust and simple, the application of seismic waves to snow has been sparse. This might be due to the strong attenuation inherent to snow that prevents large scale seismic applications or due to the somewhat counterintuitive acoustic behavior of snow as a porous material. Such materials support a second kind of compressional wave that can be measured in fresh snow and which has a decreasing wave velocity with increasing density of snow. To investigate wave propagation in snow we construct a Biot-type porous model of snow as a function of porosity based on the assumptions that the solid frame is build of ice, the pore space is filled with a mix of air, or air and water, and empirical relationships for the tortuosity, the permeability, the bulk, and the shear modulus.We use this reduced model to investigate compressional and shear wave velocities of snow as a function of porosity and to asses the consequences of liquid water in the snowpack on acoustic wave propagation by solving Biot's differential equations with plain wave solutions. We find that the fast compressional wave velocity increases significantly with increasing density, but also that the fast compressional wave velocity might be even lower than the slow compressional wave velocity for very light snow. By using compressional and shear strength criteria and solving Biot's differential equations with a pseudo-spectral approach we evaluate snow failure due to acoustic waves in a heterogeneous snowpack, which we think is an important mechanism in triggering avalanches by explosives as well as by skiers. Finally, we developed a low cost seismic acquisition device to assess the theoretically obtained wave velocities in the field and to explore the possibility of an inexpensive tool to remotely gather snow water equivalent.

Snow stratigraphic heterogeneity within ground-based passive microwave radiometer footprints: implications for emission modelling

NASA Astrophysics Data System (ADS)

Sandells, M.; Rutter, N.; Derksen, C.; Langlois, A.; Lemmetyinen, J.; Montpetit, B.; Pulliainen, J. T.; Royer, A.; Toose, P.

2012-12-01

Remote sensing of snow mass remains a challenging area of research. Scattering of electromagnetic radiation is sensitive to snow mass, but is also affected by contrasts in the dielectric properties of the snow. Although the argument that errors from simple algorithms average out at large scales has been used to justify current retrieval methods, it is not obvious why this should be the case. This hypothesis needs to be tested more rigorously. A ground-based field experiment was carried out to assess the impact of sub-footprint snow heterogeneity on microwave brightness temperature, in Churchill, Canada in winter in early 2010. Passive microwave measurements of snow were made using sled-mounted radiometers at 75cm intervals over a 5m transect. Measurements were made at horizontal and vertical polarizations at frequencies of 19 and 37 GHz. Snow beneath the radiometer footprints was subsequently excavated, creating a snow trench wall along the centrepoints of adjacent footprints. The trench wall was carefully smoothed and photographed with a near-infrared camera in order to determine the positions of stratigraphic snow layer boundaries. Three one-dimensional vertical profiles of snowpack properties (density and snow specific surface area) were taken at 75cm, 185cm and 355cm from the left hand side of the trench. These profile measurements were used to derive snow density and grain size for each of the layers identified from the NIR image. Microwave brightness temperatures for the 2-dimensional map of snow properties was simulated with the Helsinki University of Technology (HUT) model at 1cm intervals horizontally across the trench. Where each of five ice lenses was identified in the snow stratigraphy, a decrease in brightness temperature was simulated. However, the median brightness temperature simulated across the trench was substantially higher than the observations, of the order of tens of Kelvin, dependent on frequency and polarization. In order to understand and

Effects of snow grain shape on climate simulations: sensitivity tests with the Norwegian Earth System Model

NASA Astrophysics Data System (ADS)

Räisänen, Petri; Makkonen, Risto; Kirkevåg, Alf; Debernard, Jens B.

2017-12-01

Snow consists of non-spherical grains of various shapes and sizes. Still, in radiative transfer calculations, snow grains are often treated as spherical. This also applies to the computation of snow albedo in the Snow, Ice, and Aerosol Radiation (SNICAR) model and in the Los Alamos sea ice model, version 4 (CICE4), both of which are employed in the Community Earth System Model and in the Norwegian Earth System Model (NorESM). In this study, we evaluate the effect of snow grain shape on climate simulated by NorESM in a slab ocean configuration of the model. An experiment with spherical snow grains (SPH) is compared with another (NONSPH) in which the snow shortwave single-scattering properties are based on a combination of three non-spherical snow grain shapes optimized using measurements of angular scattering by blowing snow. The key difference between these treatments is that the asymmetry parameter is smaller in the non-spherical case (0.77-0.78 in the visible region) than in the spherical case ( ≈ 0.89). Therefore, for the same effective snow grain size (or equivalently, the same specific projected area), the snow broadband albedo is higher when assuming non-spherical rather than spherical snow grains, typically by 0.02-0.03. Considering the spherical case as the baseline, this results in an instantaneous negative change in net shortwave radiation with a global-mean top-of-the-model value of ca. -0.22 W m-2. Although this global-mean radiative effect is rather modest, the impacts on the climate simulated by NorESM are substantial. The global annual-mean 2 m air temperature in NONSPH is 1.17 K lower than in SPH, with substantially larger differences at high latitudes. The climatic response is amplified by strong snow and sea ice feedbacks. It is further demonstrated that the effect of snow grain shape could be largely offset by adjusting the snow grain size. When assuming non-spherical snow grains with the parameterized grain size increased by ca. 70 %, the

Snow control on active layer and permafrost in steep alpine rock walls (Aiguille du Midi, 3842 m a.s.l, Mont Blanc massif)

NASA Astrophysics Data System (ADS)

Magnin, Florence; Westermann, Sebastian; Pogliotti, Paolo; Ravanel, Ludovic; Deline, Philip

2016-04-01

Permafrost degradation through the thickening of the active layer and the rising temperature at depth is a crucial process of rock wall stability. The ongoing increase in rock falls observed during hot periods in mid-latitude mountain ranges is regarded as a result of permafrost degradation. However, the short-term thermal dynamics of alpine rock walls are misunderstood since they result of complex processes related to the interaction of local climate variables, heterogeneous snow cover and heat transfers. As a consequence steady-state and long-term changes that can be approached with simpler process mainly related to air temperature, solar radiations and heat conduction were the most common dynamics to be studied so far. The effect of snow on the bedrock surface temperature is increasingly investigated and has already been demonstrated to be an essential factor of permafrost distribution. Nevertheless, its effect on the year-to-year changes of the active layer thickness and of the permafrost temperature in steep alpine bedrock has not been investigated yet, partly due to the lack of appropriate data. We explore the role of snow accumulations on the active layer and permafrost thermal regime of steep rock walls of a high-elevated site, the Aiguille du Midi (AdM, 3842 m a.s.l, Mont Blanc massif, Western European Alps) by mean of a multi-methods approach. We first analyse six years of temperature records in three 10-m-deep boreholes. Then we describe the snow accumulation patterns on two rock faces by means of automatically processed camera records. Finally, sensitivity analyses of the active layer thickness and permafrost temperature towards timing and magnitude of snow accumulations are performed using the numerical permafrost model CryoGrid 3. The energy balance module is forced with local meteorological measurements on the AdM S face and validated with surface temperature measurements at the weather station location. The heat conduction scheme is calibrated with

Comparison of Snow Mass Estimates from a Prototype Passive Microwave Snow Algorithm, a Revised Algorithm and a Snow Depth Climatology

NASA Technical Reports Server (NTRS)

Foster, J. L.; Chang, A. T. C.; Hall, D. K.

1997-01-01

While it is recognized that no single snow algorithm is capable of producing accurate global estimates of snow depth, for research purposes it is useful to test an algorithm's performance in different climatic areas in order to see how it responds to a variety of snow conditions. This study is one of the first to develop separate passive microwave snow algorithms for North America and Eurasia by including parameters that consider the effects of variations in forest cover and crystal size on microwave brightness temperature. A new algorithm (GSFC 1996) is compared to a prototype algorithm (Chang et al., 1987) and to a snow depth climatology (SDC), which for this study is considered to be a standard reference or baseline. It is shown that the GSFC 1996 algorithm compares much more favorably to the SDC than does the Chang et al. (1987) algorithm. For example, in North America in February there is a 15% difference between the GSFC 198-96 Algorithm and the SDC, but with the Chang et al. (1987) algorithm the difference is greater than 50%. In Eurasia, also in February, there is only a 1.3% difference between the GSFC 1996 algorithm and the SDC, whereas with the Chang et al. (1987) algorithm the difference is about 20%. As expected, differences tend to be less when the snow cover extent is greater, particularly for Eurasia. The GSFC 1996 algorithm performs better in North America in each month than dose the Chang et al. (1987) algorithm. This is also the case in Eurasia, except in April and May when the Chang et al.(1987) algorithms is in closer accord to the SDC than is GSFC 1996 algorithm.

Improved Snow Mapping Accuracy with Revised MODIS Snow Algorithm

NASA Technical Reports Server (NTRS)

Riggs, George; Hall, Dorothy K.

2012-01-01

The MODIS snow cover products have been used in over 225 published studies. From those reports, and our ongoing analysis, we have learned about the accuracy and errors in the snow products. Revisions have been made in the algorithms to improve the accuracy of snow cover detection in Collection 6 (C6), the next processing/reprocessing of the MODIS data archive planned to start in September 2012. Our objective in the C6 revision of the MODIS snow-cover algorithms and products is to maximize the capability to detect snow cover while minimizing snow detection errors of commission and omission. While the basic snow detection algorithm will not change, new screens will be applied to alleviate snow detection commission and omission errors, and only the fractional snow cover (FSC) will be output (the binary snow cover area (SCA) map will no longer be included).

Laser-filamentation-induced condensation and snow formation in a cloud chamber.

PubMed

Ju, Jingjing; Liu, Jiansheng; Wang, Cheng; Sun, Haiyi; Wang, Wentao; Ge, Xiaochun; Li, Chuang; Chin, See Leang; Li, Ruxin; Xu, Zhizhan

2012-04-01

Using 1 kHz, 9 mJ femtosecond laser pulses, we demonstrate laser-filamentation-induced spectacular snow formation in a cloud chamber. An intense updraft of warm moist air is generated owing to the continuous heating by the high-repetition filamentation. As it encounters the cold air above, water condensation and large-sized particles spread unevenly across the whole cloud chamber via convection and cyclone like action on a macroscopic scale. This indicates that high-repetition filamentation plays a significant role in macroscopic laser-induced water condensation and snow formation.

Long-term variability in Northern Hemisphere snow cover and associations with warmer winters

USGS Publications Warehouse

McCabe, Gregory J.; Wolock, David M.

2010-01-01

A monthly snow accumulation and melt model is used with gridded monthly temperature and precipitation data for the Northern Hemisphere to generate time series of March snow-covered area (SCA) for the period 1905 through 2002. The time series of estimated SCA for March is verified by comparison with previously published time series of SCA for the Northern Hemisphere. The time series of estimated Northern Hemisphere March SCA shows a substantial decrease since about 1970, and this decrease corresponds to an increase in mean winter Northern Hemisphere temperature. The increase in winter temperature has caused a decrease in the fraction of precipitation that occurs as snow and an increase in snowmelt for some parts of the Northern Hemisphere, particularly the mid-latitudes, thus reducing snow packs and March SCA. In addition, the increase in winter temperature and the decreases in SCA appear to be associated with a contraction of the circumpolar vortex and a poleward movement of storm tracks, resulting in decreased precipitation (and snow) in the low- to mid-latitudes and an increase in precipitation (and snow) in high latitudes. If Northern Hemisphere winter temperatures continue to warm as they have since the 1970s, then March SCA will likely continue to decrease.

Long-term variability in Northern Hemisphere snow cover and associations with warmer winters

USGS Publications Warehouse

McCabe, G.J.; Wolock, D.M.

2010-01-01

A monthly snow accumulation and melt model is used with gridded monthly temperature and precipitation data for the Northern Hemisphere to generate time series of March snow-covered area (SCA) for the period 1905 through 2002. The time series of estimated SCA for March is verified by comparison with previously published time series of SCA for the Northern Hemisphere. The time series of estimated Northern Hemisphere March SCA shows a substantial decrease since about 1970, and this decrease corresponds to an increase in mean winter Northern Hemisphere temperature. The increase in winter temperature has caused a decrease in the fraction of precipitation that occurs as snow and an increase in snowmelt for some parts of the Northern Hemisphere, particularly the mid-latitudes, thus reducing snow packs and March SCA. In addition, the increase in winter temperature and the decreases in SCA appear to be associated with a contraction of the circumpolar vortex and a poleward movement of storm tracks, resulting in decreased precipitation (and snow) in the low- to mid-latitudes and an increase in precipitation (and snow) in high latitudes. If Northern Hemisphere winter temperatures continue to warm as they have since the 1970s, then March SCA will likely continue to decrease. ?? 2009 Springer Science+Business Media B.V.

Effects of air temperature and discharge on Upper Mississippi River summer water temperatures

USGS Publications Warehouse

Gray, Brian R.; Robertson, Dale M.; Rogala, James T.

2018-01-01

Recent interest in the potential effects of climate change has prompted studies of air temperature and precipitation associations with water temperatures in rivers and streams. We examined associations between summer surface water temperatures and both air temperature and discharge for 5 reaches of the Upper Mississippi River during 1994–2011. Water–air temperature associations at a given reach approximated 1:1 when estimated under an assumption of reach independence but declined to approximately 1:2 when water temperatures were permitted to covary among reaches and were also adjusted for upstream air temperatures. Estimated water temperature–discharge associations were weak. An apparently novel feature of this study is that of addressing changes in associations between water and air temperatures when both are correlated among reaches.

Satellite Snow-Cover Mapping: A Brief Review

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.

1995-01-01

Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow

Field measurements and modeling of wave propagation and subsequent weak layer failure in snow due to explosive loading

NASA Astrophysics Data System (ADS)

Simioni, Stephan; Sidler, Rolf; Dual, Jürg; Schweizer, Jürg

2015-04-01

Avalanche control by explosives is among the key temporary preventive measures. Yet, little is known about the mechanism involved in releasing avalanches by the effect of an explosion. Here, we test the hypothesis that the stress induced by acoustic waves exceeds the strength of weak snow layers. Consequently the snow fails and the onset of rapid crack propagation might finally lead to the release of a snow slab avalanche. We performed experiments with explosive charges over a snowpack. We installed microphones above the snowpack to measure near-surface air pressure and accelerometers within three snow pits. We also recorded pit walls of each pit with high speed cameras to detect weak layer failure. Empirical relationships and a priori information from ice and air were used to characterize a porous layered model from density measurements of snow profiles in the snow pits. This model was used to perform two-dimensional numerical simulations of wave propagation in Biot-type porous material. Locations of snow failure were identified in the simulation by comparing the axial and deviatoric stress field of the simulation to the corresponding snow strength. The identified snow failure locations corresponded well with the observed failure locations in the experiment. The acceleration measured in the snowpack best correlated with the modeled acceleration of the fluid relative to the ice frame. Even though the near field of the explosion is expected to be governed by non-linear effects as for example the observed supersonic wave propagation in the air above the snow surface, the results of the linear poroelastic simulation fit well with the measured air pressure and snowpack accelerations. The results of this comparison are an important step towards quantifying the effectiveness of avalanche control by explosives.

Role of snow in the fate of gaseous and particulate exhaust pollutants from gasoline-powered vehicles.

PubMed

Nazarenko, Yevgen; Fournier, Sébastien; Kurien, Uday; Rangel-Alvarado, Rodrigo Benjamin; Nepotchatykh, Oleg; Seers, Patrice; Ariya, Parisa A

2017-04-01

Little is known about pollution in urban snow and how aerosol and gaseous air pollutants interact with the urban snowpack. Here we investigate interactions of exhaust pollution with snow at low ambient temperature using fresh snow in a temperature-controlled chamber. A gasoline-powered engine from a modern light duty vehicle generated the exhaust and was operated in homogeneous and stratified engine regimes. We determined that, within a timescale of 30 min, snow takes up from the exhaust a large mass of organic pollutants and aerosol particles, which were observed by electron microscopy, mass spectrometry and aerosol sizers. Specifically, the concentration of total organic carbon in the exposed snow increased from 0.948 ± 0.009 to 1.828 ± 0.001 mg/L (homogeneous engine regime) and from 0.275 ± 0.005 to 0.514 ± 0.008 mg/L (stratified engine regime). The concentrations of benzene, toluene and 13 out of 16 measured polycyclic aromatic hydrocarbons (PAHs), particularly naphthalene, benz[a]anthracene, chrysene and benzo[a]pyrene in snow increased upon exposure from near the detection limit to 0.529 ± 0.058, 1.840 ± 0.200, 0.176 ± 0.020, 0.020 ± 0.005, 0.025 ± 0.005 and 0.028 ± 0.005 ng/kg, respectively, for the homogeneous regime. After contact with snow, 50-400 nm particles were present with higher relative abundance compared to the smaller nanoparticles (<50 nm), for the homogeneous regime. The lowering of temperature from 25 ± 1 °C to (-8) - (-10) ± 1 °C decreased the median mode diameter of the exhaust aerosol particles from 69 nm to 57 nm (p < 0.1) and addition of snow to 51 nm (p < 0.1) for the stratified regime, but increased it from 20 nm to 27 nm (p < 0.1) for the homogeneous regime. Future studies should focus on cycling of exhaust-derived pollutants between the atmosphere and cryosphere. The role of the effects we discovered should be evaluated as part of assessment of pollutant loads and exposures in

Annual Soil Temperature Wave at Four Depths in Southwestern Wisconsin

Treesearch

Richard S. Sartz

1967-01-01

Soil temperature was measured for a year on a southeast-facing slope of 25 percent, latitude 43 degrees 50 minutes N. The spring-summer cover was unmowed alfalfa-bluegrass meadow, the fall-winter cover, meadow stubble. Snow cover was light or absent. The soil was Fayette silt loam, valley phase. The annual temperature wave at all depths followed the air temperature...

Spatiotemporal changes of snow cover over the Tibetan plateau based on cloud-removed moderate resolution imaging spectroradiometer fractional snow cover product from 2001 to 2011

NASA Astrophysics Data System (ADS)

Tang, Zhiguang; Wang, Jian; Li, Hongyi; Yan, Lili

2013-01-01

Snow cover changes over the Tibetan plateau (TP) are examined using moderate resolution imaging spectroradiometer (MODIS) daily fractional snow cover (FSC) data from 2001 to 2011 as well as in situ temperature data. First, the accuracy of the MODIS FSC data under clear sky conditions is evaluated by comparing with Landsat 30-m observations. Then we describe a cloud-gap-filled (CGF) method using cubic spline interpolation algorithm to fill in data gaps caused by clouds. Finally, the spatial and temporal changes of snow cover are analyzed on the basis of the MODIS-derived snow-covered area and snow-covered days (SCD) data. Results show that the mean absolute error of MODIS FSC data under clear sky condition is about 0.098 over the TP. The CGF method is efficient in cloud reduction (overall mean absolute error of the retrieved FSC data is 0.092). There is a very high inter-annual and intra-seasonal variability of snow cover in the 11 years. The higher snow cover corresponds well with the huge mountains. The accumulation and melt periods of snow cover vary in different elevation zones. About 34.14% (5.56% with a significant decline) and 24.75% (3.9% with a significant increase) of the study area presents declining and increasing trend in SCD, respectively. The inter-annual fluctuation of snow cover can be explained by the high negative correlations observed between the snow cover and the in situ temperature, especially in some elevations of February, April, May, August, and September.

A Comparison of Sea Ice Type, Sea Ice Temperature, and Snow Thickness Distributions in the Arctic Seasonal Ice Zones with the DMSP SSM/I

NASA Technical Reports Server (NTRS)

St.Germain, Karen; Cavalieri, Donald J.; Markus, Thorsten

1997-01-01

Global climate studies have shown that sea ice is a critical component in the global climate system through its effect on the ocean and atmosphere, and on the earth's radiation balance. Polar energy studies have further shown that the distribution of thin ice and open water largely controls the distribution of surface heat exchange between the ocean and atmosphere within the winter Arctic ice pack. The thickness of the ice, the depth of snow on the ice, and the temperature profile of the snow/ice composite are all important parameters in calculating surface heat fluxes. In recent years, researchers have used various combinations of DMSP SSMI channels to independently estimate the thin ice type (which is related to ice thickness), the thin ice temperature, and the depth of snow on the ice. In each case validation efforts provided encouraging results, but taken individually each algorithm gives only one piece of the information necessary to compute the energy fluxes through the ice and snow. In this paper we present a comparison of the results from each of these algorithms to provide a more comprehensive picture of the seasonal ice zone using passive microwave observations.

Objective Characterization of Snow Microstructure for Microwave Emission Modeling

NASA Technical Reports Server (NTRS)

Durand, Michael; Kim, Edward J.; Molotch, Noah P.; Margulis, Steven A.; Courville, Zoe; Malzler, Christian

2012-01-01

Passive microwave (PM) measurements are sensitive to the presence and quantity of snow, a fact that has long been used to monitor snowcover from space. In order to estimate total snow water equivalent (SWE) within PM footprints (on the order of approx 100 sq km), it is prerequisite to understand snow microwave emission at the point scale and how microwave radiation integrates spatially; the former is the topic of this paper. Snow microstructure is one of the fundamental controls on the propagation of microwave radiation through snow. Our goal in this study is to evaluate the prospects for driving the Microwave Emission Model of Layered Snowpacks with objective measurements of snow specific surface area to reproduce measured brightness temperatures when forced with objective measurements of snow specific surface area (S). This eliminates the need to treat the grain size as a free-fit parameter.

Air temperature gradient in large industrial hall

NASA Astrophysics Data System (ADS)

Karpuk, Michał; Pełech, Aleksander; Przydróżny, Edward; Walaszczyk, Juliusz; Szczęśniak, Sylwia

2017-11-01

In the rooms with dominant sensible heat load, volume airflow depends on many factors incl. pre-established temperature difference between exhaust and supply airflow. As the temperature difference is getting higher, airflow volume drops down, consequently, the cost of AHU is reduced. In high industrial halls with air exhaust grids located under the ceiling additional temperature gradient above working zone should be taken into consideration. In this regard, experimental research of the vertical air temperature gradient in high industrial halls were carried out for the case of mixing ventilation system The paper presents the results of air temperature distribution measurements in high technological hall (mechanically ventilated) under significant sensible heat load conditions. The supply airflow was delivered to the hall with the help of the swirl diffusers while exhaust grids were located under the hall ceiling. Basing on the air temperature distribution measurements performed on the seven pre-established levels, air temperature gradient in the area between 2.0 and 7.0 m above the floor was calculated and analysed.

Snow cover retrieval over Rhone and Po river basins from MODIS optical satellite data (2000-2009).

NASA Astrophysics Data System (ADS)

Dedieu, Jean-Pierre, ,, Dr.; Boos, Alain; Kiage, Wiliam; Pellegrini, Matteo

2010-05-01

retrieve (i) Fractional Snow cover at sub-pixel scale, and (ii) maximum snow cover. All products were retrieved at 8-days over a complete time period of 10 years (2000-2009), giving 500 images for each river basin. Digital Model Elevation was given by NASA/SRTM database at 90-m resolution and used (i) for illumination versus topography correction on snow cover, (ii) geometric rectification of images. Geographic projection is WGS84, UTM 32. Fractional Snow cover mapping was derived from the NDSI linear regression method (Salomonson et al., 2004). Cloud mask was given by MODIS-NASA library (radiometric threshold) and completed by inverse slope regression to avoid lowlands fog confusing with thin snow cover (Po river basin). Maximum Snow Cover mapping was retrieved from the NSIDC database classification (Hall et al., 2001). Validation step was processed using comparison between MODIS Snow maps outputs and meteorological data provided by network of 87 meteorological stations: temperature, precipitation, snow depth measurement. A 0.92 correlation was observed for snow/non snow cover and can be considered as quite satisfactory, given the radiometric problems encountered in mountainous areas, particularly in snowmelt season. The 10-years time period results indicates a main difference between (i) regular snow accumulation and depletion in Rhone and (ii) the high temporal and spatial variability of snow cover for Po. Then, a high sensitivity to low variation of air temperature, often close to 1° C was observed. This is the case in particular for the beginning and the end of the winter season. The regional snow cover depletion is both influenced by thermal positives anomalies (e.g. 2000 and 2006), and the general trend of rising atmospheric temperatures since the late 1980s, particularly for Po river basin. Results will be combined with two hydrological models: Topkapi and Fest.

MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.

2010-01-01

Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

Remote Sensing of Snow Cover. Section; Snow Extent

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Frei, Allan; Drey, Stephen J.

2012-01-01

Snow was easily identified in the first image obtained from the Television Infrared Operational Satellite-1 (TIROS-1) weather satellite in 1960 because the high albedo of snow presents a good contrast with most other natural surfaces. Subsequently, the National Oceanic and Atmospheric Administration (NOAA) began to map snow using satellite-borne instruments in 1966. Snow plays an important role in the Earth s energy balance, causing more solar radiation to be reflected back into space as compared to most snow-free surfaces. Seasonal snow cover also provides a critical water resource through meltwater emanating from rivers that originate from high-mountain areas such as the Tibetan Plateau. Meltwater from mountain snow packs flows to some of the world s most densely-populated areas such as Southeast Asia, benefiting over 1 billion people (Immerzeel et al., 2010). In this section, we provide a brief overview of the remote sensing of snow cover using visible and near-infrared (VNIR) and passive-microwave (PM) data. Snow can be mapped using the microwave part of the electromagnetic spectrum, even in darkness and through cloud cover, but at a coarser spatial resolution than when using VNIR data. Fusing VNIR and PM algorithms to produce a blended product offers synergistic benefits. Snow-water equivalent (SWE), snow extent, and melt onset are important parameters for climate models and for the initialization of atmospheric forecasts at daily and seasonal time scales. Snowmelt data are also needed as input to hydrological models to improve flood control and irrigation management.

Transport of intercepted snow from trees during snow storms

Treesearch

David H. Miller

1966-01-01

Five principal processes by which intercepted snow in trees is removed during snow storms are described and evaluated as far as data permit: vapor flux from melt water, vapor flux from bodies of snow, stem flow and dripping of melt water, sliding of bodies of intercepted snow from branches, and wind erosion and transport of intercepted snow. Further research is...

Multi-parameter monitoring of the construction and evolution of a snow bridge over a crevasse on an Alpine glacier

NASA Astrophysics Data System (ADS)

Ravanel, Ludovic; Malet, Emmanuel; Batoux, Philippe

2017-04-01

Snow bridges that form over the crevasses of the Alpine glaciers allow mountaineers and skiers to cross them easily but constitute an important danger in case of rupture. Between 2008 and 2014, 37 injured persons and 13 deaths related to falls into crevasse were recorded (i.e. an average of two deaths per year) on the glaciers of the French side of the Mont Blanc massif - out of the famous Vallée Blanche ski route, which however embodies an important part of the aid related to falls into crevasses. To understand the construction and evolution of these fragile structures, instrumentation was set up on the Glacier du Géant, at 3450 m a.s.l., near the Aiguille du Midi (3842 m a.s.l.), on the French side of the Mont Blanc massif, close to a crevasse whose bridge had recently collapsed over a length of 37 m. The maximum width of the crevasse in this area is 6 m. At the top of a 7-m-high pole - to prevent future snowfalls -, sensors have been installed in September 2016 to measure different snow and weather parameters: air temperature, wind speed and direction, snow height. An automatic camera surveys the crevasse and the snow bridge geometry. Several other sensors monitor the temperature of snow and air in the crevasse. In addition, an extensometer was installed into the crevasse to measure the evolution of its width. The results of the first 6 months of survey are presented, including the formation of the bridge in mid-November, during a period of snowfall associated with a strong wind. Although the instrumentation is well suited to the high mountain conditions, its maintenance is delicate due to the strong instability of the environment (glacier movements and extreme weather conditions, primarily) but the results of this work will bring new glaciological knowledges which should participate in a better safety on glaciers.

Granulation of snow: From tumbler experiments to discrete element simulations

NASA Astrophysics Data System (ADS)

Steinkogler, Walter; Gaume, Johan; Löwe, Henning; Sovilla, Betty; Lehning, Michael

2015-06-01

It is well known that snow avalanches exhibit granulation phenomena, i.e., the formation of large and apparently stable snow granules during the flow. The size distribution of the granules has an influence on flow behavior which, in turn, affects runout distances and avalanche velocities. The underlying mechanisms of granule formation are notoriously difficult to investigate within large-scale field experiments, due to limitations in the scope for measuring temperatures, velocities, and size distributions. To address this issue we present experiments with a concrete tumbler, which provide an appropriate means to investigate granule formation of snow. In a set of experiments at constant rotation velocity with varying temperatures and water content, we demonstrate that temperature has a major impact on the formation of granules. The experiments showed that granules only formed when the snow temperature exceeded -1∘C. No evolution in the granule size was observed at colder temperatures. Depending on the conditions, different granulation regimes are obtained, which are qualitatively classified according to their persistence and size distribution. The potential of granulation of snow in a tumbler is further demonstrated by showing that generic features of the experiments can be reproduced by cohesive discrete element simulations. The proposed discrete element model mimics the competition between cohesive forces, which promote aggregation, and impact forces, which induce fragmentation, and supports the interpretation of the granule regime classification obtained from the tumbler experiments. Generalizations, implications for flow dynamics, and experimental and model limitations as well as suggestions for future work are discussed.

Distributed snow modeling suitable for use with operational data for the American River watershed.

NASA Astrophysics Data System (ADS)

Shamir, E.; Georgakakos, K. P.

2004-12-01

The mountainous terrain of the American River watershed (~4300 km2) at the Western slope of the Northern Sierra Nevada is subject to significant variability in the atmospheric forcing that controls the snow accumulation and ablations processes (i.e., precipitation, surface temperature, and radiation). For a hydrologic model that attempts to predict both short- and long-term streamflow discharges, a plausible description of the seasonal and intermittent winter snow pack accumulation and ablation is crucial. At present the NWS-CNRFC operational snow model is implemented in a semi distributed manner (modeling unit of about 100-1000 km2) and therefore lump distinct spatial variability of snow processes. In this study we attempt to account for the precipitation, temperature, and radiation spatial variability by constructing a distributed snow accumulation and melting model suitable for use with commonly available sparse data. An adaptation of the NWS-Snow17 energy and mass balance that is used operationally at the NWS River Forecast Centers is implemented at 1 km2 grid cells with distributed input and model parameters. The input to the model (i.e., precipitation and surface temperature) is interpolated from observed point data. The surface temperature was interpolated over the basin based on adiabatic lapse rates using topographic information whereas the precipitation was interpolated based on maps of climatic mean annual rainfall distribution acquired from PRISM. The model parameters that control the melting rate due to radiation were interpolated based on aspect. The study was conducted for the entire American basin for the snow seasons of 1999-2000. Validation of the Snow Water Equivalent (SWE) prediction is done by comparing to observation from 12 snow Sensors. The Snow Cover Area (SCA) prediction was evaluated by comparing to remotely sensed 500m daily snow cover derived from MODIS. The results that the distribution of snow over the area is well captured and the

14 CFR 23.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Carburetor air temperature controls. 23... Powerplant Powerplant Controls and Accessories § 23.1157 Carburetor air temperature controls. There must be a separate carburetor air temperature control for each engine. ...

14 CFR 23.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Carburetor air temperature controls. 23... Powerplant Powerplant Controls and Accessories § 23.1157 Carburetor air temperature controls. There must be a separate carburetor air temperature control for each engine. ...

14 CFR 23.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Carburetor air temperature controls. 23... Powerplant Powerplant Controls and Accessories § 23.1157 Carburetor air temperature controls. There must be a separate carburetor air temperature control for each engine. ...

14 CFR 23.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Carburetor air temperature controls. 23... Powerplant Powerplant Controls and Accessories § 23.1157 Carburetor air temperature controls. There must be a separate carburetor air temperature control for each engine. ...

14 CFR 23.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Carburetor air temperature controls. 23... Powerplant Powerplant Controls and Accessories § 23.1157 Carburetor air temperature controls. There must be a separate carburetor air temperature control for each engine. ...

The seasonal cycle of snow cover, sea ice and surface albedo

NASA Technical Reports Server (NTRS)

Robock, A.

1980-01-01

The paper examines satellite data used to construct mean snow cover caps for the Northern Hemisphere. The zonally averaged snow cover from these maps is used to calculate the seasonal cycle of zonally averaged surface albedo. The effects of meltwater on the surface, solar zenith angle, and cloudiness are parameterized and included in the calculations of snow and ice albedo. The data allows a calculation of surface albedo for any land or ocean 10 deg latitude band as a function of surface temperature ice and snow cover; the correct determination of the ice boundary is more important than the snow boundary for accurately simulating the ice and snow albedo feedback.

European In-Situ Snow Measurements: Practices and Purposes.

PubMed

Pirazzini, Roberta; Leppänen, Leena; Picard, Ghislain; Lopez-Moreno, Juan Ignacio; Marty, Christoph; Macelloni, Giovanni; Kontu, Anna; von Lerber, Annakaisa; Tanis, Cemal Melih; Schneebeli, Martin; de Rosnay, Patricia; Arslan, Ali Nadir

2018-06-22

In-situ snow measurements conducted by European institutions for operational, research, and energy business applications were surveyed in the framework of the European Cooperation in Science and Technology (COST) Action ES1404, called "A European network for a harmonised monitoring of snow for the benefit of climate change scenarios, hydrology, and numerical weather prediction". Here we present the results of this survey, which was answered by 125 participants from 99 operational and research institutions, belonging to 38 European countries. The typologies of environments where the snow measurements are performed range from mountain to low elevated plains, including forests, bogs, tundra, urban areas, glaciers, lake ice, and sea ice. Of the respondents, 93% measure snow macrophysical parameters, such as snow presence, snow depth (HS), snow water equivalent (SWE), and snow density. These describe the bulk characteristics of the whole snowpack or of a snow layer, and they are the primary snow properties that are needed for most operational applications (such as hydrological monitoring, avalanche forecast, and weather forecast). In most cases, these measurements are done with manual methods, although for snow presence, HS, and SWE, automatized methods are also applied by some respondents. Parameters characterizing precipitating and suspended snow (such as the height of new snow, precipitation intensity, flux of drifting/blowing snow, and particle size distribution), some of which are crucial for the operational services, are measured by 74% of the respondents. Parameters characterizing the snow microstructural properties (such as the snow grain size and shape, and specific surface area), the snow electromagnetic properties (such as albedo, brightness temperature, and backscatter), and the snow composition (such as impurities and isotopes) are measured by 41%, 26%, and 13% of the respondents, respectively, mostly for research applications. The results of this survey

[Psycrophilic organisms in snow and ice].

PubMed

Kohshima, S

2000-12-01

Psychrophilic and psycrotrophic organisms are important in global ecology as a large proportion of our planet is cold. Two-third of sea-water covering more than 70% of Earth is cold deep sea water with temperature around 2 degrees C, and more than 90% of freshwater is in polar ice-sheets and mountain glaciers. Though biological activity in snow and ice had been believed to be extremely limited, various specialized biotic communities were recently discovered at glaciers of various part of the world. The glacier is relatively simple and closed ecosystem with special biotic community containing various psychrophilic and psycrotrophic organisms. Since psychrophilic organisms was discovered in the deep ice-core recovered from the antarctic ice-sheet and a lake beneath it, snow and ice environments in Mars and Europa are attracting a great deal of scientific attention as possible extraterrestrial habitats of life. This paper briefly reviews the results of the studies on ecology of psychrophilic organisms living in snow and ice environments and their physiological and biochemical adaptation to low temperature.

Comparing different snow products to assess spatio-temporal snow cover patterns in the Central Taurus Mountains, Turkey

NASA Astrophysics Data System (ADS)

Sturm, K.; Helmschrot, J.

2013-12-01

differs notably during snow accumulation and ablation periods, the highest deviations occurring in December, April, and May. The highest SCA inconsistencies are observed in the low and mid altitudes, whereas the higher elevations are snow-covered very early in the snow season as modeled by J2000. During these periods, J2000 simulates a significantly larger SCA than MODIS. The analysis of individual time steps suggests that the J2000 daily model does capture individual snow events, whereas the MODIS products fail to do so due to their temporal resolution. Furthermore, acquisition time and inner-daily melt and re-freezing effects may affect SCA estimates from MODIS data. In other cases, differences can clearly be associated to insufficient model input data, primarily due to limited spatial precipitation and temperature data. Our study indicates that individual products might provide inconsistent information on temporal and spatial snow cover. We recommend considering a combined analysis of different snow products in order to provide reliable information on snow cover dynamics, in particular in eastern Mediterranean high-altitude environments.

New Perspectives on Blowing Snow Transport, Sublimation, and Layer Thermodynamic Structure over Antarctica

NASA Technical Reports Server (NTRS)

Palm, Steve; Kayetha, Vinay; Yang, Yuekui; Pauly, Rebecca M.

2017-01-01

Blowing snow over Antarctica is a widespread and frequent event. Satellite remote sensing using lidar has shown that blowing snow occurs over 70% of the time over large areas of Antarctica in winter. The transport and sublimation of blowing snow are important terms in the ice sheet mass balance equation and the latter is also an important part of the hydrological cycle. Until now the only way to estimate the magnitude of these processes was through model parameterization. We present a technique that uses direct satellite observations of blowing snow and model (MERRA-2) temperature and humidity fields to compute both transport and sublimation of blowing snow over Antarctica for the period 2006 to 2016. The results show a larger annual continent-wide integrated sublimation than current published estimates and a significant transport of snow from continent to ocean. The talk will also include the lidar backscatter structure of blowing snow layers that often reach heights of 200 to 300 m as well as the first dropsonde measurements of temperature, moisture and wind through blowing snow layers.

Dynamics of Phase Transitions in a Snow Mass Containing Water-Soluble Salt Particles

NASA Astrophysics Data System (ADS)

Zelenko, V. L.; Heifets, L. I.; Orlov, Yu. N.; Voskresenskiy, N. M.

2018-07-01

A macrokinetic approach is used to describe the dynamics of phase transitions in a snow mass containing water-soluble salt particles. Equations are derived that describe the rate of salt granule dissolution and the change in the phase composition and temperature of a snow mass under the conditions of heat transfer with an isothermal surface. An experimental setup that models the change in the state of a snow mass placed on an isothermal surface is created to verify theoretical conclusions. Experimental observations of the change in temperature of the snow mass are compared to theoretical calculations. The mathematical model that is developed can be used to predict the state of a snow mass on roads treated with a deicing agent, or to analyze the state of snow masses containing water-soluble salt inclusions and resting on mountain slopes.

Modelling the snowmelt and the snow water equivalent by creating a simplified energy balance conceptual snow model

NASA Astrophysics Data System (ADS)

Riboust, Philippe; Thirel, Guillaume; Le Moine, Nicolas; Ribstein, Pierre

2016-04-01

A better knowledge of the accumulated snow on the watersheds will help flood forecasting centres and hydro-power companies to predict the amount of water released during spring snowmelt. Since precipitations gauges are sparse at high elevations and integrative measurements of the snow accumulated on watershed surface are hard to obtain, using snow models is an adequate way to estimate snow water equivalent (SWE) on watersheds. In addition to short term prediction, simulating accurately SWE with snow models should have many advantages. Validating the snow module on both SWE and snowmelt should give a more reliable model for climate change studies or regionalization for ungauged watersheds. The aim of this study is to create a new snow module, which has a structure that allows the use of measured snow data for calibration or assimilation. Energy balance modelling seems to be the logical choice for designing a model in which internal variables, such as SWE, could be compared to observations. Physical models are complex, needing high computational resources and many different types of inputs that are not widely measured at meteorological stations. At the opposite, simple conceptual degree-day models offer to simulate snowmelt using only temperature and precipitation as inputs with fast computing. Its major drawback is to be empirical, i.e. not taking into account all of the processes of the energy balance, which makes this kind of model more difficult to use when willing to compare SWE to observed measurements. In order to reach our objectives, we created a snow model structured by a simplified energy balance where each of the processes is empirically parameterized in order to be calculated using only temperature, precipitation and cloud cover variables. This model's structure is similar to the one created by M.T. Walter (2005), where parameterizations from the literature were used to compute all of the processes of the energy balance. The conductive fluxes into the

A Comprehensive Snow Density Model for Integrating Lidar-Derived Snow Depth Data into Spatial Snow Modeling

NASA Astrophysics Data System (ADS)

Marks, D. G.; Kormos, P.; Johnson, M.; Bormann, K. J.; Hedrick, A. R.; Havens, S.; Robertson, M.; Painter, T. H.

2017-12-01

Lidar-derived snow depths when combined with modeled or estimated snow density can provide reliable estimates of the distribution of SWE over large mountain areas. Application of this approach is transforming western snow hydrology. We present a comprehensive approach toward modeling bulk snow density that is reliable over a vast range of weather and snow conditions. The method is applied and evaluated over mountainous regions of California, Idaho, Oregon and Colorado in the western US. Simulated and measured snow density are compared at fourteen validation sites across the western US where measurements of snow mass (SWE) and depth are co-located. Fitting statistics for ten sites from three mountain catchments (two in Idaho, one in California) show an average Nash-Sutcliff model efficiency coefficient of 0.83, and mean bias of 4 kg m-3. Results illustrate issues associated with monitoring snow depth and SWE and show the effectiveness of the model, with a small mean bias across a range of snow and climate conditions in the west.

Snow Ecology

NASA Astrophysics Data System (ADS)

Jones, H. G.; Pomeroy, J. W.; Walker, D. A.; Hoham, R. W.

2001-01-01

In this volume, a multidisciplinary group of acknowledged experts fully intergrate the physical, chemical, and biological sciences to provide a complete understanding of the interrelationships between snow structure and life. This volume opens a new perspecitve on snow cover as a habitat for organisms under extreme environmental conditions and as a key factor in the ecology of much of the Earth's surface. The contributors describe the fundamental physical and small-scale chemical processes that characterize the evolution of snow and their influence on the life cycles of true snow organisms and the biota of cold regions with extended snow cover. The book further expands on the role of snow in the biosphere by the study of the relationship between snow and climate and the paleo-ecological evidence for the influence of past snow regimes on plant communities. Snow Ecology will form a main textbook on advanced courses in biology, ecology, geography, environmental science, and earth science where an important component is devoted to the study of the cryosphere. It will also be useful as a reference text for graduate students, researchers, and professionals at academic institutions and in government and nongovernmental agencies with environmental concerns.

40 CFR 91.309 - Engine intake air temperature measurement.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 20 2014-07-01 2013-07-01 true Engine intake air temperature... Provisions § 91.309 Engine intake air temperature measurement. (a) Engine intake air temperature measurement... the supply system or in the air stream entering the engine. (b) The temperature measurements must be...

40 CFR 91.309 - Engine intake air temperature measurement.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 21 2012-07-01 2012-07-01 false Engine intake air temperature... Provisions § 91.309 Engine intake air temperature measurement. (a) Engine intake air temperature measurement... the supply system or in the air stream entering the engine. (b) The temperature measurements must be...

40 CFR 91.309 - Engine intake air temperature measurement.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 21 2013-07-01 2013-07-01 false Engine intake air temperature... Provisions § 91.309 Engine intake air temperature measurement. (a) Engine intake air temperature measurement... the supply system or in the air stream entering the engine. (b) The temperature measurements must be...

40 CFR 91.309 - Engine intake air temperature measurement.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 20 2011-07-01 2011-07-01 false Engine intake air temperature... Provisions § 91.309 Engine intake air temperature measurement. (a) Engine intake air temperature measurement... the supply system or in the air stream entering the engine. (b) The temperature measurements must be...

14 CFR 29.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Carburetor air temperature controls. 29.1157 Section 29.1157 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF... Accessories § 29.1157 Carburetor air temperature controls. There must be a separate carburetor air temperature...

14 CFR 25.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2012 CFR

2012-01-01

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14 CFR 29.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2011 CFR

2011-01-01

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14 CFR 25.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2011 CFR

2011-01-01

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14 CFR 29.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2010 CFR

2010-01-01

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14 CFR 25.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2010 CFR

2010-01-01

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14 CFR 29.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2014 CFR

2014-01-01

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14 CFR 29.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2013 CFR

2013-01-01

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14 CFR 25.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2013 CFR

2013-01-01

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14 CFR 25.1157 - Carburetor air temperature controls.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Carburetor air temperature controls. 25.1157 Section 25.1157 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF... Accessories § 25.1157 Carburetor air temperature controls. There must be a separate carburetor air temperature...

Time budgets of Snow Geese Chen caerulescens and Ross's Geese Chen rossii in mixed flocks: Implications of body size, ambient temperature and family associations

USGS Publications Warehouse

Jonsson, J.E.; Afton, A.D.

2009-01-01

Body size affects foraging and forage intake rates directly via energetic processes and indirectly through interactions with social status and social behaviour. Ambient temperature has a relatively greater effect on the energetics of smaller species, which also generally are more vulnerable to predator attacks than are larger species. We examined variability in an index of intake rates and an index of alertness in Lesser Snow Geese Chen caerulescens caerulescens and Ross's Geese Chen rossii wintering in southwest Louisiana. Specifically we examined variation in these response variables that could be attributed to species, age, family size and ambient temperature. We hypothesized that the smaller Ross's Geese would spend relatively more time feeding, exhibit relatively higher peck rates, spend more time alert or raise their heads up from feeding more frequently, and would respond to declining temperatures by increasing their proportion of time spent feeding. As predicted, we found that Ross's Geese spent more time feeding than did Snow Geese and had slightly higher peck rates than Snow Geese in one of two winters. Ross's Geese spent more time alert than did Snow Geese in one winter, but alert rates differed by family size, independent of species, in contrast to our prediction. In one winter, time spent foraging and walking was inversely related to average daily temperature, but both varied independently of species. Effects of age and family size on time budgets were generally independent of species and in accordance with previous studies. We conclude that body size is a key variable influencing time spent feeding in Ross's Geese, which may require a high time spent feeding at the expense of other activities. ?? 2008 The Authors.

Validation of A One-Dimensional Snow-Land Surface Model at the Sleepers River Watershed

NASA Astrophysics Data System (ADS)

Sun, Wen-Yih; Chern, Jiun-Dar

A one-dimensional land surface model, based on conservations of heat and water substance inside the soil and snow, is presented. To validate the model, a stand-alone experiment is carried out with five years of meteorological and hydrological observations collected from the NOAA-ARS Cooperative Snow Research Project (1966-1974) at the Sleepers River watershed in Danville, Vermont, U.S.A. The numerical results show that the model is capable of reproducing the observed soil temperature at different depths during the winter as well as a rapid increase of soil temperature after snow melts in the spring. The model also simulates the density, temperature, thickness, and equivalent water depth of snow reasonably well. The numerical results are sensitive to the fresh snow density and the soil properties used in the model, which affect the heat exchange between the snowpack and the soil.

Total mercury and methylmercury in high altitude surface snow from the French Alps.

PubMed

Marusczak, Nicolas; Larose, Catherine; Dommergue, Aurélien; Yumvihoze, Emmanuel; Lean, David; Nedjai, Rachid; Ferrari, Christophe

2011-09-01

Surface snow samples were collected weekly from the 31st of December 2008 to the 21st of June 2009 from Lake Bramant in the French Alps. Total mercury (THg), total dissolved mercury (THgD), methylmercury (MeHg) and particle distributions in surface snow were analyzed. Results showed that THg concentrations, MeHg concentrations and particle load increased with snow surface temperature, which is an indicator of rising temperatures as the season progresses. Significant correlations between MeHg and snow surface temperature and MeHg and total particles greater than 10 μm were observed. This suggests that the MeHg found in the snow originates from atmospheric deposition processes rather than in situ snowpack sources. This study suggests that an important post-winter atmospheric deposition of MeHg and THg occurs on summital zones of the French Alps and it is likely that this contamination originates from the surrounding valleys. Copyright © 2011 Elsevier B.V. All rights reserved.

Measuring spatiotemporal variation in snow optical grain size under a subalpine forest canopy using contact spectroscopy

NASA Astrophysics Data System (ADS)

Molotch, Noah P.; Barnard, David M.; Burns, Sean P.; Painter, Thomas H.

2016-09-01

The distribution of forest cover exerts strong controls on the spatiotemporal distribution of snow accumulation and snowmelt. The physical processes that govern these controls are poorly understood given a lack of detailed measurements of snow states. In this study, we address one of many measurement gaps by using contact spectroscopy to measure snow optical grain size at high spatial resolution in trenches dug between tree boles in a subalpine forest. Trenches were collocated with continuous measurements of snow depth and vertical profiles of snow temperature and supplemented with manual measurements of snow temperature, geometric grain size, grain type, and density from trench walls. There was a distinct difference in snow optical grain size between winter and spring periods. In winter and early spring, when facetted snow crystal types were dominant, snow optical grain size was 6% larger in canopy gaps versus under canopy positions; a difference that was smaller than the measurement uncertainty. By midspring, the magnitude of snow optical grain size differences increased dramatically and patterns of snow optical grain size became highly directional with 34% larger snow grains in areas south versus north of trees. In winter, snow temperature gradients were up to 5-15°C m-1 greater under the canopy due to shallower snow accumulation. However, in canopy gaps, snow depths were greater in fall and early winter and therefore more significant kinetic growth metamorphism occurred relative to under canopy positions, resulting in larger snow grains in canopy gaps. Our findings illustrate the novelty of our method of measuring snow optical grain size, allowing for future studies to advance the understanding of how forest and meteorological conditions interact to impact snowpack evolution.

Improving representation of canopy temperatures for modeling subcanopy incoming longwave radiation to the snow surface

NASA Astrophysics Data System (ADS)

Webster, Clare; Rutter, Nick; Jonas, Tobias

2017-09-01

A comprehensive analysis of canopy surface temperatures was conducted around a small and large gap at a forested alpine site in the Swiss Alps during the 2015 and 2016 snowmelt seasons (March-April). Canopy surface temperatures within the small gap were within 2-3°C of measured reference air temperature. Vertical and horizontal variations in canopy surface temperatures were greatest around the large gap, varying up to 18°C above measured reference air temperature during clear-sky days. Nighttime canopy surface temperatures around the study site were up to 3°C cooler than reference air temperature. These measurements were used to develop a simple parameterization for correcting reference air temperature for elevated canopy surface temperatures during (1) nighttime conditions (subcanopy shortwave radiation is 0 W m-2) and (2) periods of increased subcanopy shortwave radiation >400 W m-2 representing penetration of shortwave radiation through the canopy. Subcanopy shortwave and longwave radiation collected at a single point in the subcanopy over a 24 h clear-sky period was used to calculate a nighttime bulk offset of 3°C for scenario 1 and develop a multiple linear regression model for scenario 2 using reference air temperature and subcanopy shortwave radiation to predict canopy surface temperature with a root-mean-square error (RMSE) of 0.7°C. Outside of these two scenarios, reference air temperature was used to predict subcanopy incoming longwave radiation. Modeling at 20 radiometer locations throughout two snowmelt seasons using these parameterizations reduced the mean bias and RMSE to below 10 W m s-2 at all locations.

Meteorological Modeling of Wintertime Cold Air Pool Stagnation Episodes in the Uintah and Salt Lake Basins

NASA Astrophysics Data System (ADS)

Crosman, E.; Horel, J.; Blaylock, B. K.; Foster, C.

2014-12-01

High wintertime ozone concentrations in rural areas associated with oil and gas development and high particulate concentrations in urban areas have become topics of increasing concern in the Western United States, as both primary and secondary pollutants become trapped within stable wintertime boundary layers. While persistent cold air pools that enable such poor wintertime air quality are typically associated with high pressure aloft and light winds, the complex physical processes that contribute to the formation, maintenance, and decay of persistent wintertime temperature inversions are only partially understood. In addition, obtaining sufficiently accurate numerical weather forecasts and meteorological simulations of cold air pools for input into chemical models remains a challenge. This study examines the meteorological processes associated with several wintertime pollution episodes in Utah's Uintah and Salt Lake Basins using numerical Weather Research and Forecasting model simulations and observations collected from the Persistent Cold Air Pool and Uintah Basin Ozone Studies. The temperature, vertical structure, and winds within these cold air pools was found to vary as a function of snow cover, snow albedo, land use, cloud cover, large-scale synoptic flow, and episode duration. We evaluate the sensitivity of key atmospheric features such as stability, planetary boundary layer depth, local wind flow patterns and transport mechanisms to variations in surface forcing, clouds, and synoptic flow. Finally, noted deficiencies in the meteorological models of cold air pools and modifications to the model snow and microphysics treatment that have resulted in improved cold pool simulations will be presented.

High-resolution LIDAR and ground observations of snow cover in a complex forested terrain in the Sierra Nevada - implications for optical remote sensing of seasonal snow.

NASA Astrophysics Data System (ADS)

Kostadinov, T. S.; Harpold, A.; Hill, R.; McGwire, K.

2017-12-01

Seasonal snow cover is a key component of the hydrologic regime in many regions of the world, especially those in temperate latitudes with mountainous terrain and dry summers. Such regions support large human populations which depend on the mountain snowpack for their water supplies. It is thus important to quantify snow cover accurately and continuously in these regions. Optical remote-sensing methods are able to detect snow and leverage space-borne spectroradiometers with global coverage such as MODIS to produce global snow cover maps. However, snow is harder to detect accurately in mountainous forested terrain, where topography influences retrieval algorithms, and importantly - forest canopies complicate radiative transfer and obfuscate the snow. Current satellite snow cover algorithms assume that fractional snow-covered area (fSCA) under the canopy is the same as the fSCA in the visible portion of the pixel. In-situ observations and first principles considerations indicate otherwise, therefore there is a need for improvement of the under-canopy correction of snow cover. Here, we leverage multiple LIDAR overflights and in-situ observations with a distributed fiber-optic temperature sensor (DTS) to quantify snow cover under canopy as opposed to gap areas at the Sagehen Experimental Forest in the Northern Sierra Nevada, California, USA. Snow-off LIDAR overflights from 2014 are used to create a baseline high-resolution digital elevation model and classify pixels at 1 m resolution as canopy-covered or gap. Low canopy pixels are excluded from the analysis. Snow-on LIDAR overflights conducted by the Airborne Snow Observatory in 2016 are then used to classify all pixels as snow-covered or not and quantify fSCA under canopies vs. in gap areas over the Sagehen watershed. DTS observations are classified as snow-covered or not based on diel temperature fluctuations and used as validation for the LIDAR observations. LIDAR- and DTS-derived fSCA is also compared with

A Warming Surface but a Cooling Top of Atmosphere Associated with Warm, Moist Air Mass Advection over the Ice and Snow Covered Arctic

NASA Astrophysics Data System (ADS)

Sedlar, J.

2015-12-01

Atmospheric advection of heat and moisture from lower latitudes to the high-latitude Arctic is a critical component of Earth's energy cycle. Large-scale advective events have been shown to make up a significant portion of the moist static energy budget of the Arctic atmosphere, even though such events are typically infrequent. The transport of heat and moisture over surfaces covered by ice and snow results in dynamic changes to the boundary layer structure, stability and turbulence, as well as to diabatic processes such as cloud distribution, microphysics and subsequent radiative effects. Recent studies have identified advection into the Arctic as a key mechanism for modulating the melt and freeze of snow and sea ice, via modification to all-sky longwave radiation. This paper examines the radiative impact during summer of such Arctic advective events at the top of the atmosphere (TOA), considering also the important role they play for the surface energy budget. Using infrared sounder measurements from the AIRS satellite, the summer frequency of significantly stable and moist advective events from 2003-2014 are characterized; justification of AIRS profiles over the Arctic are made using radiosoundings during a 3-month transect (ACSE) across the Eastern Arctic basin. One such event was observed within the East Siberian Sea in August 2014 during ACSE, providing in situ verification on the robustness and capability of AIRS to monitor advective cases. Results will highlight the important surface warming aspect of stable, moist instrusions. However a paradox emerges as such events also result in a cooling at the TOA evident on monthly mean TOA radiation. Thus such events have a climatic importance over ice and snow covered surfaces across the Arctic. ERA-Interim reanalyses are examined to provide a longer term perspective on the frequency of such events as well as providing capability to estimate meridional fluxes of moist static energy.

Changes in Andes snow cover from MODIS data, 2000-2016

NASA Astrophysics Data System (ADS)

Saavedra, Freddy A.; Kampf, Stephanie K.; Fassnacht, Steven R.; Sibold, Jason S.

2018-03-01

The Andes span a length of 7000 km and are important for sustaining regional water supplies. Snow variability across this region has not been studied in detail due to sparse and unevenly distributed instrumental climate data. We calculated snow persistence (SP) as the fraction of time with snow cover for each year between 2000 and 2016 from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors (500 m, 8-day maximum snow cover extent). This analysis is conducted between 8 and 36° S due to high frequency of cloud (> 30 % of the time) south and north of this range. We ran Mann-Kendall and Theil-Sens analyses to identify areas with significant changes in SP and snowline (the line at lower elevation where SP = 20 %). We evaluated how these trends relate to temperature and precipitation from Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) and University of Delaware datasets and climate indices as El Niño-Southern Oscillation (ENSO), Southern Annular Mode (SAM), and Pacific Decadal Oscillation (PDO). Areas north of 29° S have limited snow cover, and few trends in snow persistence were detected. A large area (34 370 km2) with persistent snow cover between 29 and 36° S experienced a significant loss of snow cover (2-5 fewer days of snow year-1). Snow loss was more pronounced (62 % of the area with significant trends) on the east side of the Andes. We also found a significant increase in the elevation of the snowline at 10-30 m year-1 south of 29-30° S. Decreasing SP correlates with decreasing precipitation and increasing temperature, and the magnitudes of these correlations vary with latitude and elevation. ENSO climate indices better predicted SP conditions north of 31° S, whereas the SAM better predicted SP south of 31° S.

24. EXTERIOR VIEW, SHOWING AIRPLANES IN VERY DEEP SNOW. Photographic ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

24. EXTERIOR VIEW, SHOWING AIRPLANES IN VERY DEEP SNOW. Photographic copy of historic photograph. July-Dec. 1948 OAMA (original print located at Ogden Air Logistics Center, Hill Air Force Base, Utah). Photographer unknown. - Hill Field, Airplane Repair Hangars No. 1-No. 4, 5875 Southgate Avenue, Layton, Davis County, UT

Early results from NASA's SnowEx campaign

NASA Astrophysics Data System (ADS)

Kim, Edward; Gatebe, Charles; Hall, Dorothy; Misakonis, Amy; Elder, Kelly; Marshall, Hans Peter; Hiemstra, Chris; Brucker, Ludovic; Crawford, Chris; Kang, Do Hyuk; De Marco, Eugenia; Beckley, Matt; Entin, Jared

2017-04-01

. Snow simply varies too much. Thus, the snow community consensus is that a multi-sensor approach is needed to adequately address global snow, combined with modeling and data assimilation. What remains at issue, then, is how best to combine and use the various sensors in an optimal way. That requires field measurements. NASA's SnowEx airborne campaign is designed to do exactly that. A list of core sensors is as follows. All are from NASA unless otherwise noted. • Radar (volume scattering): European Space Agency's SnowSAR, operated by MetaSensing • Lidar & hyperspectral imager: Airborne Snow Observatory (ASO) • Passive microwave: Airborne Earth Science Microwave Imaging Radiometer (AESMIR) • Bi-directional Reflectance Function (BRDF): the Cloud Absorption Radiometer (CAR) • Thermal Infrared imager • Thermal infrared non-imager from U. Washington • Video camera The ASO suite flew on a King Air, and the other sensors flew on a Navy P-3. In addition, two NASA radars flew on G-III aircraft to test more experimental retrieval techniques: • InSAR altimetry: Glacier and Ice Surface Topography Interferometer (GLISTIN-A) • Radar phase delay: Uninhabited Aerial Vehicle Synthetic Aperture Radar, (UAVSAR)

Snow as a habitat for microorganisms

NASA Technical Reports Server (NTRS)

Hoham, Ronald W.

1989-01-01

There are three major habitats involving ice and snow, and the microorganisms studied from these habitats are most eukaryotic. Sea ice is inhabited by algae called diatoms, glacial ice has sparse populations of green algai cal desmids, and the temporary and permanent snows in mountainous regions and high latitudes are inhabited mostly by green algal flagellates. The life cycle of green algal flagellates is summarized by discussing the effects of light, temperature, nutrients, and snow melts. Specific examples of optimal conditions and environmental effects for various snow algae are given. It is not likely that the eukaryotic snow algae presented are candidated for life on the planet Mars. Evolutionally, eukaryotic cells as know on Earth may not have had the opportunity to develop on Mars (if life evolved at all on Mars) since eukaryotes did not appear on Earth until almost two billion years after the first prokaryotic organisms. However, the snow/ice ecosystems on Earth present themselves as extreme habitats were there is evidence of prokaryotic life (eubacteria and cyanbacteria) of which literally nothing is known. Any future surveillances of extant and/or extinct life on Mars should include probes (if not landing sites) to investigate sites of concentrations of ice water. The possibility of signs of life in Martian polar regions should not be overlooked.

Developing an A Priori Database for Passive Microwave Snow Water Retrievals Over Ocean

NASA Astrophysics Data System (ADS)

Yin, Mengtao; Liu, Guosheng

2017-12-01

A physically optimized a priori database is developed for Global Precipitation Measurement Microwave Imager (GMI) snow water retrievals over ocean. The initial snow water content profiles are derived from CloudSat Cloud Profiling Radar (CPR) measurements. A radiative transfer model in which the single-scattering properties of nonspherical snowflakes are based on the discrete dipole approximate results is employed to simulate brightness temperatures and their gradients. Snow water content profiles are then optimized through a one-dimensional variational (1D-Var) method. The standard deviations of the difference between observed and simulated brightness temperatures are in a similar magnitude to the observation errors defined for observation error covariance matrix after the 1D-Var optimization, indicating that this variational method is successful. This optimized database is applied in a Bayesian retrieval snow water algorithm. The retrieval results indicated that the 1D-Var approach has a positive impact on the GMI retrieved snow water content profiles by improving the physical consistency between snow water content profiles and observed brightness temperatures. Global distribution of snow water contents retrieved from the a priori database is compared with CloudSat CPR estimates. Results showed that the two estimates have a similar pattern of global distribution, and the difference of their global means is small. In addition, we investigate the impact of using physical parameters to subset the database on snow water retrievals. It is shown that using total precipitable water to subset the database with 1D-Var optimization is beneficial for snow water retrievals.

Observed Differences between North American Snow Extent and Snow Depth Variability

NASA Astrophysics Data System (ADS)

Ge, Y.; Gong, G.

2006-12-01

Snow extent and snow depth are two related characteristics of a snowpack, but they need not be mutually consistent. Differences between these two variables at local scales are readily apparent. However at larger scales which interact with atmospheric circulation and climate, snow extent is typically the variable used, while snow depth is often assumed to be minor and/or mutually consistent compared to snow extent, though this is rarely verified. In this study, a new regional/continental-scale gridded dataset derived from field observations is utilized to quantitatively evaluate the relationship between snow extent and snow depth over North America. Various statistical methods are applied to assess the mutual consistency of monthly snow depth vs. snow extent, including correlations, composites and principal components. Results indicate that snow depth variations are significant in their own rights, and that depth and extent anomalies are largely unrelated, especially over broad high latitude regions north of the snowline. In the vicinity of the snowline, where precipitation and ablation can affect both snow extent and snow depth, the two variables vary concurrently, especially in autumn and spring. It is also found that deeper winter snow translates into larger snow-covered area in the subsequent spring/summer season, which suggests a possible influence of winter snow depth on summer climate. The observed lack of mutual consistency at continental/regional scales suggests that snowpack depth variations may be of sufficiently large magnitude, spatial scope and temporal duration to influence regional-hemispheric climate, in a manner unrelated to the more extensively studied snow extent variations.