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A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description
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| Zeitschriftentitel: | Journal of Geophysical Research: Oceans |
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| Personen und Körperschaften: | , , , , , , , |
| In: | Journal of Geophysical Research: Oceans, 125, 2020, 10 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
American Geophysical Union (AGU)
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| Schlagwörter: |
| author_facet |
Liston, Glen E. Itkin, Polona Stroeve, Julienne Tschudi, Mark Stewart, J. Scott Pedersen, Stine H. Reinking, Adele K. Elder, Kelly Liston, Glen E. Itkin, Polona Stroeve, Julienne Tschudi, Mark Stewart, J. Scott Pedersen, Stine H. Reinking, Adele K. Elder, Kelly |
|---|---|
| author |
Liston, Glen E. Itkin, Polona Stroeve, Julienne Tschudi, Mark Stewart, J. Scott Pedersen, Stine H. Reinking, Adele K. Elder, Kelly |
| spellingShingle |
Liston, Glen E. Itkin, Polona Stroeve, Julienne Tschudi, Mark Stewart, J. Scott Pedersen, Stine H. Reinking, Adele K. Elder, Kelly Journal of Geophysical Research: Oceans A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description Earth and Planetary Sciences (miscellaneous) Space and Planetary Science Geochemistry and Petrology Geophysics Oceanography |
| author_sort |
liston, glen e. |
| spelling |
Liston, Glen E. Itkin, Polona Stroeve, Julienne Tschudi, Mark Stewart, J. Scott Pedersen, Stine H. Reinking, Adele K. Elder, Kelly 2169-9275 2169-9291 American Geophysical Union (AGU) Earth and Planetary Sciences (miscellaneous) Space and Planetary Science Geochemistry and Petrology Geophysics Oceanography http://dx.doi.org/10.1029/2019jc015913 <jats:title>Abstract</jats:title><jats:p>A Lagrangian snow‐evolution model (SnowModel‐LG) was used to produce daily, pan‐Arctic, snow‐on‐sea‐ice, snow property distributions on a 25 × 25‐km grid, from 1 August 1980 through 31 July 2018 (38 years). The model was forced with NASA's Modern Era Retrospective‐Analysis for Research and Applications‐Version 2 (MERRA‐2) and European Centre for Medium‐Range Weather Forecasts (ECMWF) ReAnalysis‐5th Generation (ERA5) atmospheric reanalyses, and National Snow and Ice Data Center (NSIDC) sea ice parcel concentration and trajectory data sets (approximately 61,000, 14 × 14‐km parcels). The simulations performed full surface and internal energy and mass balances within a multilayer snowpack evolution system. Processes and features accounted for included rainfall, snowfall, sublimation from static‐surfaces and blowing‐snow, snow melt, snow density evolution, snow temperature profiles, energy and mass transfers within the snowpack, superimposed ice, and ice dynamics. The simulations produced horizontal snow spatial structures that likely exist in the natural system but have not been revealed in previous studies spanning these spatial and temporal domains. Blowing‐snow sublimation made a significant contribution to the snowpack mass budget. The superimposed ice layer was minimal and decreased over the last four decades. Snow carryover to the next accumulation season was minimal and sensitive to the melt‐season atmospheric forcing (e.g., the average summer melt period was 3 weeks or 50% longer with ERA5 forcing than MERRA‐2 forcing). Observed ice dynamics controlled the ice parcel age (in days), and ice age exerted a first‐order control on snow property evolution.</jats:p> A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description Journal of Geophysical Research: Oceans |
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| title |
A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description |
| title_unstemmed |
A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description |
| title_full |
A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description |
| title_fullStr |
A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description |
| title_full_unstemmed |
A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description |
| title_short |
A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description |
| title_sort |
a lagrangian snow‐evolution system for sea‐ice applications (snowmodel‐lg): part i—model description |
| topic |
Earth and Planetary Sciences (miscellaneous) Space and Planetary Science Geochemistry and Petrology Geophysics Oceanography |
| url |
http://dx.doi.org/10.1029/2019jc015913 |
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2020 |
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|
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<jats:title>Abstract</jats:title><jats:p>A Lagrangian snow‐evolution model (SnowModel‐LG) was used to produce daily, pan‐Arctic, snow‐on‐sea‐ice, snow property distributions on a 25 × 25‐km grid, from 1 August 1980 through 31 July 2018 (38 years). The model was forced with NASA's Modern Era Retrospective‐Analysis for Research and Applications‐Version 2 (MERRA‐2) and European Centre for Medium‐Range Weather Forecasts (ECMWF) ReAnalysis‐5th Generation (ERA5) atmospheric reanalyses, and National Snow and Ice Data Center (NSIDC) sea ice parcel concentration and trajectory data sets (approximately 61,000, 14 × 14‐km parcels). The simulations performed full surface and internal energy and mass balances within a multilayer snowpack evolution system. Processes and features accounted for included rainfall, snowfall, sublimation from static‐surfaces and blowing‐snow, snow melt, snow density evolution, snow temperature profiles, energy and mass transfers within the snowpack, superimposed ice, and ice dynamics. The simulations produced horizontal snow spatial structures that likely exist in the natural system but have not been revealed in previous studies spanning these spatial and temporal domains. Blowing‐snow sublimation made a significant contribution to the snowpack mass budget. The superimposed ice layer was minimal and decreased over the last four decades. Snow carryover to the next accumulation season was minimal and sensitive to the melt‐season atmospheric forcing (e.g., the average summer melt period was 3 weeks or 50% longer with ERA5 forcing than MERRA‐2 forcing). Observed ice dynamics controlled the ice parcel age (in days), and ice age exerted a first‐order control on snow property evolution.</jats:p> |
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| author | Liston, Glen E., Itkin, Polona, Stroeve, Julienne, Tschudi, Mark, Stewart, J. Scott, Pedersen, Stine H., Reinking, Adele K., Elder, Kelly |
| author_facet | Liston, Glen E., Itkin, Polona, Stroeve, Julienne, Tschudi, Mark, Stewart, J. Scott, Pedersen, Stine H., Reinking, Adele K., Elder, Kelly, Liston, Glen E., Itkin, Polona, Stroeve, Julienne, Tschudi, Mark, Stewart, J. Scott, Pedersen, Stine H., Reinking, Adele K., Elder, Kelly |
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| description | <jats:title>Abstract</jats:title><jats:p>A Lagrangian snow‐evolution model (SnowModel‐LG) was used to produce daily, pan‐Arctic, snow‐on‐sea‐ice, snow property distributions on a 25 × 25‐km grid, from 1 August 1980 through 31 July 2018 (38 years). The model was forced with NASA's Modern Era Retrospective‐Analysis for Research and Applications‐Version 2 (MERRA‐2) and European Centre for Medium‐Range Weather Forecasts (ECMWF) ReAnalysis‐5th Generation (ERA5) atmospheric reanalyses, and National Snow and Ice Data Center (NSIDC) sea ice parcel concentration and trajectory data sets (approximately 61,000, 14 × 14‐km parcels). The simulations performed full surface and internal energy and mass balances within a multilayer snowpack evolution system. Processes and features accounted for included rainfall, snowfall, sublimation from static‐surfaces and blowing‐snow, snow melt, snow density evolution, snow temperature profiles, energy and mass transfers within the snowpack, superimposed ice, and ice dynamics. The simulations produced horizontal snow spatial structures that likely exist in the natural system but have not been revealed in previous studies spanning these spatial and temporal domains. Blowing‐snow sublimation made a significant contribution to the snowpack mass budget. The superimposed ice layer was minimal and decreased over the last four decades. Snow carryover to the next accumulation season was minimal and sensitive to the melt‐season atmospheric forcing (e.g., the average summer melt period was 3 weeks or 50% longer with ERA5 forcing than MERRA‐2 forcing). Observed ice dynamics controlled the ice parcel age (in days), and ice age exerted a first‐order control on snow property evolution.</jats:p> |
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| institution | DE-Gla1, DE-Zi4, DE-15, DE-Pl11, DE-Rs1, DE-105, DE-14, DE-Ch1, DE-L229, DE-D275, DE-Bn3, DE-Brt1, DE-Zwi2, DE-D161 |
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| spelling | Liston, Glen E. Itkin, Polona Stroeve, Julienne Tschudi, Mark Stewart, J. Scott Pedersen, Stine H. Reinking, Adele K. Elder, Kelly 2169-9275 2169-9291 American Geophysical Union (AGU) Earth and Planetary Sciences (miscellaneous) Space and Planetary Science Geochemistry and Petrology Geophysics Oceanography http://dx.doi.org/10.1029/2019jc015913 <jats:title>Abstract</jats:title><jats:p>A Lagrangian snow‐evolution model (SnowModel‐LG) was used to produce daily, pan‐Arctic, snow‐on‐sea‐ice, snow property distributions on a 25 × 25‐km grid, from 1 August 1980 through 31 July 2018 (38 years). The model was forced with NASA's Modern Era Retrospective‐Analysis for Research and Applications‐Version 2 (MERRA‐2) and European Centre for Medium‐Range Weather Forecasts (ECMWF) ReAnalysis‐5th Generation (ERA5) atmospheric reanalyses, and National Snow and Ice Data Center (NSIDC) sea ice parcel concentration and trajectory data sets (approximately 61,000, 14 × 14‐km parcels). The simulations performed full surface and internal energy and mass balances within a multilayer snowpack evolution system. Processes and features accounted for included rainfall, snowfall, sublimation from static‐surfaces and blowing‐snow, snow melt, snow density evolution, snow temperature profiles, energy and mass transfers within the snowpack, superimposed ice, and ice dynamics. The simulations produced horizontal snow spatial structures that likely exist in the natural system but have not been revealed in previous studies spanning these spatial and temporal domains. Blowing‐snow sublimation made a significant contribution to the snowpack mass budget. The superimposed ice layer was minimal and decreased over the last four decades. Snow carryover to the next accumulation season was minimal and sensitive to the melt‐season atmospheric forcing (e.g., the average summer melt period was 3 weeks or 50% longer with ERA5 forcing than MERRA‐2 forcing). Observed ice dynamics controlled the ice parcel age (in days), and ice age exerted a first‐order control on snow property evolution.</jats:p> A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description Journal of Geophysical Research: Oceans |
| spellingShingle | Liston, Glen E., Itkin, Polona, Stroeve, Julienne, Tschudi, Mark, Stewart, J. Scott, Pedersen, Stine H., Reinking, Adele K., Elder, Kelly, Journal of Geophysical Research: Oceans, A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description, Earth and Planetary Sciences (miscellaneous), Space and Planetary Science, Geochemistry and Petrology, Geophysics, Oceanography |
| title | A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description |
| title_full | A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description |
| title_fullStr | A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description |
| title_full_unstemmed | A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description |
| title_short | A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description |
| title_sort | a lagrangian snow‐evolution system for sea‐ice applications (snowmodel‐lg): part i—model description |
| title_unstemmed | A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description |
| topic | Earth and Planetary Sciences (miscellaneous), Space and Planetary Science, Geochemistry and Petrology, Geophysics, Oceanography |
| url | http://dx.doi.org/10.1029/2019jc015913 |