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Atmosphere
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Modeling and Measuring Snow Processes across Scales
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Modeling and Measuring Snow Processes across Scales

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (15 November 2020) | Viewed by 31211

Special Issue Editor

Prof. Dr. Jorge F. Carrasco

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Guest Editor
Centro de Investigación Gaia Antártica, University of Magallanes, Manuel Bulnes 01855, Punta Arenas, Chile
Interests: atmosphere-cryosphere interaction; climate variability and change in polar regions and high mountains; synoptic meteorology and forecasting
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Snowfall and snow cover play a very important role in the climate system, modifying the global energy budget because of its high albedo. Snowmelt is also an important component of the hydrologic process in many mountainous environments as well as in polar regions. The increase in surface temperatures has relevant cryospheric consequences for polar and high-elevation regions, where snow is a dominant climatic feature. Higher temperatures may result in shifting from solid to liquid precipitation, earlier snowmelt, reducing snow cover extent, and shortening of the snow cover duration. Although much progress has been made in understanding and predicting snow precipitation and snow cover changes and their multiple consequences, many aspects, such as snow monitoring and modeling and the impact of snow changes on ecosystems and society, remain open research topics that require further understanding.

This Special Issue of Atmosphere aims to capture the state of the art of modeling and measuring snow processes, including, among other aspects, snow accumulation and spatial distribution, snow transport, snow–vegetation interactions, snow cover and melting, snowfall, and snowpack in mountains and polar regions. Studies focusing on analyzing and predicting changes in snow processes and the ecological and societal impacts during the 21st century due to climate change will also be welcome.

Dr. Jorge F. Carrasco
Guest Editor

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Keywords


  • Snowfall
  • Snowpack
  • Snow cover
  • Snowmelt
  • Modeling snow processes
  • Snow change impacts
  • Snow polar regions
  • Snow mountains regions

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Published Papers (9 papers)

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Research

19 pages, 5803 KiB  
Article
Snow Processes and Climate Sensitivity in an Arid Mountain Region, Northern Chile
by Francisco Jara, Miguel Lagos-Zúñiga, Rodrigo Fuster, Cristian Mattar and James McPhee
Atmosphere 2021, 12(4), 520; https://doi.org/10.3390/atmos12040520 - 20 Apr 2021
Cited by 8 | Viewed by 4299
Abstract
Seasonal snow and glaciers in arid mountain regions are essential in sustaining human populations, economic activity, and ecosystems, especially in their role as reservoirs. However, they are threatened by global atmospheric changes, in particular by variations in air temperature and their effects on [...] Read more.
Seasonal snow and glaciers in arid mountain regions are essential in sustaining human populations, economic activity, and ecosystems, especially in their role as reservoirs. However, they are threatened by global atmospheric changes, in particular by variations in air temperature and their effects on precipitation phase, snow dynamics and mass balance. In arid environments, small variations in snow mass and energy balance can produce large changes in the amount of available water. This paper provides insights into the impact of global warming on the mass balance of the seasonal snowpack in the mountainous Copiapó river basin in northern Chile. A dataset from an experimental station was combined with reanalysis data to run a physically based snow model at site and catchment scales. The basin received an average annual precipitation of approximately 130 mm from 2001 to 2016, with sublimation losses higher than 70% of the snowpack. Blowing snow sublimation presented an orographic gradient resultant from the decreasing air temperature and windy environment in higher elevations. Under warmer climates, the snowpack will remain insensitive in high elevations (>4000 m a.s.l.), but liquid precipitation will increase at lower heights. Full article
(This article belongs to the Special Issue Modeling and Measuring Snow Processes across Scales)
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14 pages, 4326 KiB  
Article
Seasonal Estimates and Uncertainties of Snow Accumulation from CloudSat Precipitation Retrievals
by George Duffy, Fraser King, Ralf Bennartz and Christopher G. Fletcher
Atmosphere 2021, 12(3), 363; https://doi.org/10.3390/atmos12030363 - 10 Mar 2021
Cited by 5 | Viewed by 2429
Abstract
CloudSat is often the only measurement of snowfall rate available at high latitudes, making it a valuable tool for understanding snow climatology. The capability of CloudSat to provide information on seasonal and subseasonal time scales, however, has yet to be explored. In this [...] Read more.
CloudSat is often the only measurement of snowfall rate available at high latitudes, making it a valuable tool for understanding snow climatology. The capability of CloudSat to provide information on seasonal and subseasonal time scales, however, has yet to be explored. In this study, we use subsampled reanalysis estimates to predict the uncertainties of CloudSat snow water equivalent (SWE) accumulation measurements at various space and time resolutions. An idealized/simulated subsampling model predicts that CloudSat may provide seasonal SWE estimates with median percent errors below 50% at spatial scales as small as 2° × 2°. By converting these predictions to percent differences, we can evaluate CloudSat snowfall accumulations against a blend of gridded SWE measurements during frozen time periods. Our predictions are in good agreement with results. The 25th, 50th, and 75th percentiles of the percent differences between the two measurements all match predicted values within eight percentage points. We interpret these results to suggest that CloudSat snowfall estimates are in sufficient agreement with other, thoroughly vetted, gridded SWE products. This implies that CloudSat may provide useful estimates of snow accumulation over remote regions within seasonal time scales. Full article
(This article belongs to the Special Issue Modeling and Measuring Snow Processes across Scales)
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22 pages, 5428 KiB  
Article
Validation of CloudSat-CPR Derived Precipitation Occurrence and Phase Estimates across Canada
by Rithwik Kodamana and Christopher G. Fletcher
Atmosphere 2021, 12(3), 295; https://doi.org/10.3390/atmos12030295 - 25 Feb 2021
Cited by 8 | Viewed by 2879
Abstract
Snowfall affects the terrestrial climate system at high latitudes through its impacts on local meteorology, freshwater resources and energy balance. Precise snowfall monitoring is essential for cold countries such as Canada, and particularly in temperature-sensitive regions such as the Arctic; however, its size [...] Read more.
Snowfall affects the terrestrial climate system at high latitudes through its impacts on local meteorology, freshwater resources and energy balance. Precise snowfall monitoring is essential for cold countries such as Canada, and particularly in temperature-sensitive regions such as the Arctic; however, its size and remote location means the precipitation gauge network there is sparse. While satellite remote sensing of snowfall from instruments such as CloudSat-CPR offers a potential solution, satellite detection of precipitation phase has not been systematically evaluated across Canada. In this study, CloudSat-based precipitation occurrence and phase retrievals were validated at 26 stations across Canada maintained by Environment and Climate Change Canada (ECCC). Probability of Detection (POD), defined as the percentage agreement between coincident CloudSat and human-observed present weather information for precipitation (solid, liquid or no precipitation), and False Alarm Ratio (FAR) were used as the primary metrics for validation. The mean POD (FAR) for precipitation occurrence across Canada is 65.5% ± 4.3 (31.4% ± 5.1) and for no precipitation is 90.6% ± 1.4 (11% ± 2.5). The results show lower rates of detection under cloudier skies, in the presence of (freezing) drizzle and for lighter snowfall, which may be explained by a large number of false-positives due to CloudSat-CPR’s high instrumental sensitivity. When CloudSat correctly detects the occurrence of precipitation, it shows uniformly high POD (>80%) and low FAR (<10%) for classifying the phase of precipitation. Large databases of coincident ground and satellite measurements allow us to provide a new estimate of around 9% for the frequency of virga events, a factor of two smaller than a previous estimate for the Arctic. The results from this study show that CloudSat has useful accuracy in detecting precipitation occurrence and very high accuracy at classifying precipitation phase, over diverse climate zones across Canada. As such, there is significant potential for satellite monitoring of snowfall in remote, cold regions. Full article
(This article belongs to the Special Issue Modeling and Measuring Snow Processes across Scales)
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32 pages, 54597 KiB  
Article
Arctic Snow Isotope Hydrology: A Comparative Snow-Water Vapor Study
by Pertti Ala-aho, Jeffrey M. Welker, Hannah Bailey, Stine Højlund Pedersen, Ben Kopec, Eric Klein, Moein Mellat, Kaisa-Riikka Mustonen, Kashif Noor and Hannu Marttila
Atmosphere 2021, 12(2), 150; https://doi.org/10.3390/atmos12020150 - 25 Jan 2021
Cited by 14 | Viewed by 5721
Abstract
The Arctic’s winter water cycle is rapidly changing, with implications for snow moisture sources and transport processes. Stable isotope values (δ18O, δ2H, d-excess) of the Arctic snowpack have potential to provide proxy records of these processes, yet it [...] Read more.
The Arctic’s winter water cycle is rapidly changing, with implications for snow moisture sources and transport processes. Stable isotope values (δ18O, δ2H, d-excess) of the Arctic snowpack have potential to provide proxy records of these processes, yet it is unclear how well the isotope values of individual snowfall events are preserved within snow profiles. Here, we present water isotope data from multiple taiga and tundra snow profiles sampled in Arctic Alaska and Finland, respectively, during winter 2018–2019. We compare the snowpack isotope stratigraphy with meteoric water isotopes (vapor and precipitation) during snowfall days, and combine our measurements with satellite observations and reanalysis data. Our analyses indicate that synoptic-scale atmospheric circulation and regional sea ice coverage are key drivers of the source, amount, and isotopic composition of Arctic snowpacks. We find that the western Arctic tundra snowpack profiles in Alaska preserved the isotope values for the most recent storm; however, post depositional processes modified the remaining isotope profiles. The overall seasonal evolution in the vapor isotope values were better preserved in taiga snow isotope profiles in the eastern Arctic, where there is significantly less wind-driven redistribution than in the open Alaskan tundra. We demonstrate the potential of the seasonal snowpack to provide a useful proxy for Arctic winter-time moisture sources and propose future analyses. Full article
(This article belongs to the Special Issue Modeling and Measuring Snow Processes across Scales)
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16 pages, 3752 KiB  
Article
Local Weather Conditions Create Structural Differences between Shallow Firn Columns at Summit, Greenland and WAIS Divide, Antarctica
by Ian E. McDowell, Mary R. Albert, Stephanie A. Lieblappen and Kaitlin M. Keegan
Atmosphere 2020, 11(12), 1370; https://doi.org/10.3390/atmos11121370 - 17 Dec 2020
Cited by 2 | Viewed by 3252
Abstract
Understanding how physical characteristics of polar firn vary with depth assists in interpreting paleoclimate records and predicting meltwater infiltration and storage in the firn column. Spatial heterogeneities in firn structure arise from variable surface climate conditions that create differences in firn grain growth [...] Read more.
Understanding how physical characteristics of polar firn vary with depth assists in interpreting paleoclimate records and predicting meltwater infiltration and storage in the firn column. Spatial heterogeneities in firn structure arise from variable surface climate conditions that create differences in firn grain growth and packing arrangements. Commonly, estimates of how these properties change with depth are made by modeling profiles using long-term estimates of air temperature and accumulation rate. Here, we compare surface meteorology and firn density and permeability in the depth range of 3.5–11 m of the firn column from cores collected at Summit, Greenland and WAIS Divide, Antarctica, two sites with the same average accumulation rate and mean annual air temperature. We show that firn at WAIS Divide is consistently denser than firn at Summit. However, the difference in bulk permeability of the two profiles is less statistically significant. We argue that differences in local weather conditions, such as mean summer temperatures, daily temperature variations, and yearly wind speeds, create the density discrepancies. Our results are consistent with previous results showing density is not a good indicator of firn permeability within the shallow firn column. Future modeling efforts should account for these weather variables when estimating firn structure with depth. Full article
(This article belongs to the Special Issue Modeling and Measuring Snow Processes across Scales)
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15 pages, 6967 KiB  
Article
Transition from a Subaerial to a Subnival Permafrost Temperature Regime Following Increased Snow Cover (Livingston Island, Maritime Antarctic)
by Miguel Ramos, Gonçalo Vieira, Miguel Angel de Pablo, Antonio Molina and Juan Javier Jimenez
Atmosphere 2020, 11(12), 1332; https://doi.org/10.3390/atmos11121332 - 8 Dec 2020
Cited by 11 | Viewed by 2716
Abstract
The Antarctic Peninsula (AP) region has been one of the regions on Earth with strongest warming since 1950. However, the northwest of the AP showed a cooling from 2000 to 2015, which had local consequences with an increase in snow accumulation and a [...] Read more.
The Antarctic Peninsula (AP) region has been one of the regions on Earth with strongest warming since 1950. However, the northwest of the AP showed a cooling from 2000 to 2015, which had local consequences with an increase in snow accumulation and a deceleration in the loss of mass from glaciers. In this paper, we studied the effects of increased snow accumulation in the permafrost thermal regime in two boreholes (PG1 and PG2) in Livingston Island, South Shetlands Archipelago, from 2009 to 2015. The two boreholes located c. 300 m apart but at similar elevation showed different snow accumulation, with PG2 becoming completely covered with snow all year long, while the other remained mostly snow free during the summer. The analysis of the thermal regimes and of the estimated soil surface energy exchange during the study period showed the effects of snow insulation in reducing the active layer thickness. These effects were especially relevant in PG2, which transitioned from a subaerial to a subnival regime. There, permafrost aggraded from below, with the active layer completely disappearing and the efficiency of thermal insulation by the snowpack prevailing in the thermal regime. This situation may be used as an analogue for the transition from a periglacial to a subglacial environment in longer periods of cooling in the paleoenvironmental record. Full article
(This article belongs to the Special Issue Modeling and Measuring Snow Processes across Scales)
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21 pages, 5741 KiB  
Article
Case Study of a Heavy Snowstorm Associated with an Extratropical Cyclone Featuring a Back-Bent Warm Front Structure
by Yu Zhao, Liang Fu, Cheng-Fang Yang and Xiang-Fu Chen
Atmosphere 2020, 11(12), 1272; https://doi.org/10.3390/atmos11121272 - 25 Nov 2020
Cited by 6 | Viewed by 2734
Abstract
An extreme snowstorm event that occurred over Heilongjiang and Jilin Provinces on 24–26 November 2013 was related to a cyclone characterized by a back-bent occluded front structure. This study investigates the structure of the back-bent occluded front and snowfall mechanism using multiple observations [...] Read more.
An extreme snowstorm event that occurred over Heilongjiang and Jilin Provinces on 24–26 November 2013 was related to a cyclone characterized by a back-bent occluded front structure. This study investigates the structure of the back-bent occluded front and snowfall mechanism using multiple observations and NCEP/NCAR 1° × 1° reanalysis data in concert with the HYSPLIT model. The main results show that the extreme event was more synoptically governed by the outbreak of the polar vortex and moisture anomaly of the East Sea. The cyclone occurred just ahead of the 500-hPa merged deep trough, and then developed under the effect of the positive vorticity advection ahead of the 500-hPa trough and intense divergence of the upper-level jet. The south-southwest wind strengthened obviously after the merger of the southern and northern branch troughs, which was the main reason behind the cyclone moving northward. The moisture mainly originated from the Sea of Japan, insofar as that dry and cold air in the lower troposphere over the western mainland moistened obviously as it turned southward and passed over the Bohai Sea and the Sea of Japan, supplying abundant moisture for the snowstorm event. The intensity of moisture transport depended on the location and intensity of the cyclone. When the cyclone developed, the dry air continuously intruded into the cyclone’s center, and made a conveyor belt of warm air wrap around it. The dry air gradually changed from descending to ascending motion as it moved ahead of the westerly trough, while the moist air in the northern part of the cyclone moved to the west and south and incorporated into the south of the cyclone center. Warm and moist air was lifted and arrived in the northwestern part of the cyclone after the occluded front’s formation. Frontogenesis within the comma head was enhanced evidently owing to the rotation and deformation. The convergence between the southeast and northeast winds resulted in intense frontogenesis, leading to the enhancement of the front-scale ascent. Strong ascent formed in the comma head of the cyclone, which resulted in intense snowfall. Full article
(This article belongs to the Special Issue Modeling and Measuring Snow Processes across Scales)
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19 pages, 6413 KiB  
Article
Analyzing Precipitation Changes in the Northern Tip of the Antarctic Peninsula during the 1970–2019 Period
by Jorge F. Carrasco and Raúl R. Cordero
Atmosphere 2020, 11(12), 1270; https://doi.org/10.3390/atmos11121270 - 24 Nov 2020
Cited by 14 | Viewed by 2769
Abstract
Five decades of precipitation data are available from the Chilean Antarctic weather stations located in the northern tip of the Antarctic Peninsula. Data include daily accumulation and type of precipitation registered at the time of the observation at the Meteorological Antarctic Center located [...] Read more.
Five decades of precipitation data are available from the Chilean Antarctic weather stations located in the northern tip of the Antarctic Peninsula. Data include daily accumulation and type of precipitation registered at the time of the observation at the Meteorological Antarctic Center located at Base Eduardo Frei Montalva, King George Island. This information allowed us to analyze not only the precipitation accumulation changes (always questionable in cold and windy regions) but also changes in precipitation days and precipitation phases (rain versus snow). The expo nential filter was applied to the monthly data to obtain decadal-like changes. The analysis revealed an overall increase in precipitation from 1970 to the early-1990s 60 ± 7 mm (10 year)−1 (p < 0.05) and 31 ± 4 mm (10 year)−1 (p < 0.05) and a negative trend between 1991 and 1999 with decreasing precipitation of −95 ± 9 mm (10 year)−1 (p < 0.05). On the other hand, while an increase in precipitation events also took place from 1970 to the early-1990s, there was a decreasing trend in precipitation events during the 2010s. This implies that the positive trend in precipitation accumulation registered during this period is due to the increasing extreme precipitation events. The precipitation type analysis shows an increase (decrease) in snow (rain) events from around the mid-1990s to mid-2010s during the summer season. These opposite trends were related to the summer cooling affecting the AP region. Full article
(This article belongs to the Special Issue Modeling and Measuring Snow Processes across Scales)
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18 pages, 3483 KiB  
Article
Quantifying the Changing Nature of the Winter Season Precipitation Phase from 1849 to 2017 in Downtown Toronto (Canada)
by Micah J. Hewer and William A. Gough
Atmosphere 2020, 11(8), 867; https://doi.org/10.3390/atmos11080867 - 16 Aug 2020
Cited by 5 | Viewed by 3360
Abstract
One hundred and sixty–nine years of weather station data were analyzed to quantify the changing nature of the winter season precipitation phase in the downtown area of Toronto (Canada). The precipitation variables examined were rainfall, snowfall water equivalent, total precipitation, rain days, snow [...] Read more.
One hundred and sixty–nine years of weather station data were analyzed to quantify the changing nature of the winter season precipitation phase in the downtown area of Toronto (Canada). The precipitation variables examined were rainfall, snowfall water equivalent, total precipitation, rain days, snow days, and precipitation days. From these precipitation variables, three precipitation phase metrics were constructed for further analysis: the fraction of total precipitation that fell as snow, the fraction of precipitation days that recorded snow, and finally, the precipitation phase index (PPI) derived from comparing the rainfall to the snowfall water equivalent. Snowfall and snow days were decreasing at the most significant rate over this time period, and although rain days were increasing, total precipitation and precipitation days were also decreasing at a statistically significant rate. All three precipitation phase metrics suggest that winters are becoming less snowy in Toronto’s urban center. We also looked at trends and changes in average winter season temperatures to explore correlations between warming temperatures and changes in the winter season precipitation phase. Of the three precipitation phase metrics considered, the ratio of snow days to precipitation days recorded the strongest time series trend and the strongest correlation with warming temperatures. Full article
(This article belongs to the Special Issue Modeling and Measuring Snow Processes across Scales)
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