Measuring the Impact of a New Snow Model Using Surface Energy Budget Process Relationships
Abstract Energy exchange at the snow‐atmosphere interface in winter is important for the evolution of temperature at the surface and within the snow, preconditioning the snowpack for melt during spring. This study illustrates a set of diagnostic tools that are useful for evaluating the energy exchan...
Published in: | Journal of Advances in Modeling Earth Systems |
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American Geophysical Union (AGU)
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ftdoajarticles:oai:doaj.org/article:0aab5bf6477a47f181f838056da6b688 2023-05-15T15:00:30+02:00 Measuring the Impact of a New Snow Model Using Surface Energy Budget Process Relationships Jonathan J. Day Gabriele Arduini Irina Sandu Linus Magnusson Anton Beljaars Gianpaolo Balsamo Mark Rodwell David Richardson 2020-12-01T00:00:00Z https://doi.org/10.1029/2020MS002144 https://doaj.org/article/0aab5bf6477a47f181f838056da6b688 EN eng American Geophysical Union (AGU) https://doi.org/10.1029/2020MS002144 https://doaj.org/toc/1942-2466 1942-2466 doi:10.1029/2020MS002144 https://doaj.org/article/0aab5bf6477a47f181f838056da6b688 Journal of Advances in Modeling Earth Systems, Vol 12, Iss 12, Pp n/a-n/a (2020) multi‐layer snow Arctic snow modelling forecast diagnostics Greenland atmosphere‐land coupling Physical geography GB3-5030 Oceanography GC1-1581 article 2020 ftdoajarticles https://doi.org/10.1029/2020MS002144 2022-12-31T12:56:19Z Abstract Energy exchange at the snow‐atmosphere interface in winter is important for the evolution of temperature at the surface and within the snow, preconditioning the snowpack for melt during spring. This study illustrates a set of diagnostic tools that are useful for evaluating the energy exchange at the Earth's surface in an Earth System Model, from a process‐based perspective, using in situ observations. In particular, a new way to measure model improvement using the response of the surface temperature and other surface energy budget (SEB) terms to radiative forcing is presented. These process‐oriented diagnostics also provide a measure of the coupling strength between the incoming radiation and the various terms in the SEB, which can be used to ensure that improvements in predictions of user‐relevant properties, such as 2 m temperature, are happening for the right reasons. Correctly capturing such process relationships is a necessary step toward achieving more skilful weather forecasts and climate projections. These diagnostic techniques are applied to assess the impact of a new multi‐layer snow scheme in the European Centre for Medium‐Range Weather Forecasts'‐Integrated Forecast System at two high‐Arctic sites (Summit, Greenland and Sodankylä, Finland). A previous study showed that it will enhance 2 m temperature forecast skill across the Northern Hemisphere in boreal winter compared to forecasts with the single layer model, reducing a warm bias. In this study we use the diagnostics to show that the bias is improved for the right reasons. Article in Journal/Newspaper Arctic Greenland Sodankylä Directory of Open Access Journals: DOAJ Articles Arctic Greenland Sodankylä ENVELOPE(26.600,26.600,67.417,67.417) Journal of Advances in Modeling Earth Systems 12 12 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
multi‐layer snow Arctic snow modelling forecast diagnostics Greenland atmosphere‐land coupling Physical geography GB3-5030 Oceanography GC1-1581 |
spellingShingle |
multi‐layer snow Arctic snow modelling forecast diagnostics Greenland atmosphere‐land coupling Physical geography GB3-5030 Oceanography GC1-1581 Jonathan J. Day Gabriele Arduini Irina Sandu Linus Magnusson Anton Beljaars Gianpaolo Balsamo Mark Rodwell David Richardson Measuring the Impact of a New Snow Model Using Surface Energy Budget Process Relationships |
topic_facet |
multi‐layer snow Arctic snow modelling forecast diagnostics Greenland atmosphere‐land coupling Physical geography GB3-5030 Oceanography GC1-1581 |
description |
Abstract Energy exchange at the snow‐atmosphere interface in winter is important for the evolution of temperature at the surface and within the snow, preconditioning the snowpack for melt during spring. This study illustrates a set of diagnostic tools that are useful for evaluating the energy exchange at the Earth's surface in an Earth System Model, from a process‐based perspective, using in situ observations. In particular, a new way to measure model improvement using the response of the surface temperature and other surface energy budget (SEB) terms to radiative forcing is presented. These process‐oriented diagnostics also provide a measure of the coupling strength between the incoming radiation and the various terms in the SEB, which can be used to ensure that improvements in predictions of user‐relevant properties, such as 2 m temperature, are happening for the right reasons. Correctly capturing such process relationships is a necessary step toward achieving more skilful weather forecasts and climate projections. These diagnostic techniques are applied to assess the impact of a new multi‐layer snow scheme in the European Centre for Medium‐Range Weather Forecasts'‐Integrated Forecast System at two high‐Arctic sites (Summit, Greenland and Sodankylä, Finland). A previous study showed that it will enhance 2 m temperature forecast skill across the Northern Hemisphere in boreal winter compared to forecasts with the single layer model, reducing a warm bias. In this study we use the diagnostics to show that the bias is improved for the right reasons. |
format |
Article in Journal/Newspaper |
author |
Jonathan J. Day Gabriele Arduini Irina Sandu Linus Magnusson Anton Beljaars Gianpaolo Balsamo Mark Rodwell David Richardson |
author_facet |
Jonathan J. Day Gabriele Arduini Irina Sandu Linus Magnusson Anton Beljaars Gianpaolo Balsamo Mark Rodwell David Richardson |
author_sort |
Jonathan J. Day |
title |
Measuring the Impact of a New Snow Model Using Surface Energy Budget Process Relationships |
title_short |
Measuring the Impact of a New Snow Model Using Surface Energy Budget Process Relationships |
title_full |
Measuring the Impact of a New Snow Model Using Surface Energy Budget Process Relationships |
title_fullStr |
Measuring the Impact of a New Snow Model Using Surface Energy Budget Process Relationships |
title_full_unstemmed |
Measuring the Impact of a New Snow Model Using Surface Energy Budget Process Relationships |
title_sort |
measuring the impact of a new snow model using surface energy budget process relationships |
publisher |
American Geophysical Union (AGU) |
publishDate |
2020 |
url |
https://doi.org/10.1029/2020MS002144 https://doaj.org/article/0aab5bf6477a47f181f838056da6b688 |
long_lat |
ENVELOPE(26.600,26.600,67.417,67.417) |
geographic |
Arctic Greenland Sodankylä |
geographic_facet |
Arctic Greenland Sodankylä |
genre |
Arctic Greenland Sodankylä |
genre_facet |
Arctic Greenland Sodankylä |
op_source |
Journal of Advances in Modeling Earth Systems, Vol 12, Iss 12, Pp n/a-n/a (2020) |
op_relation |
https://doi.org/10.1029/2020MS002144 https://doaj.org/toc/1942-2466 1942-2466 doi:10.1029/2020MS002144 https://doaj.org/article/0aab5bf6477a47f181f838056da6b688 |
op_doi |
https://doi.org/10.1029/2020MS002144 |
container_title |
Journal of Advances in Modeling Earth Systems |
container_volume |
12 |
container_issue |
12 |
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1766332600281989120 |