Surface energy balance on the Antarctic plateau as measured with an automatic weather station during 2014
AWS data during 2014 collected at PANDA-N station, on the East Antarctica Plateau, are analysed. Net Short Wave Radiation (QSWR), net Long Wave Radiation (QLWR), sensible (QH), latent (QL) and subsurface or ground (QG) heat fluxes are computed. Annual averages for QSWR, QLWR, QH, QL and QG of 19.65,...
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ftarcticportal:oai:generic.eprints.org:2685 2023-12-10T09:39:00+01:00 Surface energy balance on the Antarctic plateau as measured with an automatic weather station during 2014 Minghu, Ding Agrawal, Anubha Heil, Petra Diyi, Yang 2019-06 application/pdf http://library.arcticportal.org/2685/ http://library.arcticportal.org/2685/1/A1902002.pdf en eng Polar Research Institute of China - PRIC http://library.arcticportal.org/2685/1/A1902002.pdf Minghu, Ding and Agrawal, Anubha and Heil, Petra and Diyi, Yang (2019) Surface energy balance on the Antarctic plateau as measured with an automatic weather station during 2014. Advances in Polar Science, 30 (2). pp. 93-105. Energy Article PeerReviewed 2019 ftarcticportal 2023-11-15T23:54:41Z AWS data during 2014 collected at PANDA-N station, on the East Antarctica Plateau, are analysed. Net Short Wave Radiation (QSWR), net Long Wave Radiation (QLWR), sensible (QH), latent (QL) and subsurface or ground (QG) heat fluxes are computed. Annual averages for QSWR, QLWR, QH, QL and QG of 19.65, −49.16, 26.40, −0.77 and 3.86 W·m−2 were derived based on an albedo value of 0.8. QSWR and QH are the major sources of heat gain to the surface and QLWR is the major component of heat loss from the surface. An iterative method is used to estimate surface temperature in this paper; surface temperature of snow/ice is gradually increased or decreased, thereby changing longwave radiation, sensible, latent and subsurface heat fluxes, so that the net energy balance becomes zero. Mass loss due to sublimation at PANDA-N station for 2014 is estimated to be 12.18 mm w.e.·a−1; and mass gain due to water vapour deposition is estimated to be 3.58 mm w.e.·a−1. Thus the net mass loss due to sublimation/deposition is 8.6 mm w.e.·a−1. This study computes surface energy fluxes using a model, instead of direct measurements. Also there are missing data especially for wind speed, though 2 m air temperature data is almost continuously available throughout the year. The uncertainties of albedo, wind speed and turbulent fluxes cause the most probable error in monthly values of QLWR, QH, QL, QG and surface temperature of about ±4%, ±20%, ±50%, ±11% and ±0.74 K respectively. Article in Journal/Newspaper Advances in Polar Science Antarc* Antarctic Antarctica East Antarctica Polar Science Polar Science Arctic Portal Library Antarctic The Antarctic East Antarctica |
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language |
English |
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Energy |
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Energy Minghu, Ding Agrawal, Anubha Heil, Petra Diyi, Yang Surface energy balance on the Antarctic plateau as measured with an automatic weather station during 2014 |
topic_facet |
Energy |
description |
AWS data during 2014 collected at PANDA-N station, on the East Antarctica Plateau, are analysed. Net Short Wave Radiation (QSWR), net Long Wave Radiation (QLWR), sensible (QH), latent (QL) and subsurface or ground (QG) heat fluxes are computed. Annual averages for QSWR, QLWR, QH, QL and QG of 19.65, −49.16, 26.40, −0.77 and 3.86 W·m−2 were derived based on an albedo value of 0.8. QSWR and QH are the major sources of heat gain to the surface and QLWR is the major component of heat loss from the surface. An iterative method is used to estimate surface temperature in this paper; surface temperature of snow/ice is gradually increased or decreased, thereby changing longwave radiation, sensible, latent and subsurface heat fluxes, so that the net energy balance becomes zero. Mass loss due to sublimation at PANDA-N station for 2014 is estimated to be 12.18 mm w.e.·a−1; and mass gain due to water vapour deposition is estimated to be 3.58 mm w.e.·a−1. Thus the net mass loss due to sublimation/deposition is 8.6 mm w.e.·a−1. This study computes surface energy fluxes using a model, instead of direct measurements. Also there are missing data especially for wind speed, though 2 m air temperature data is almost continuously available throughout the year. The uncertainties of albedo, wind speed and turbulent fluxes cause the most probable error in monthly values of QLWR, QH, QL, QG and surface temperature of about ±4%, ±20%, ±50%, ±11% and ±0.74 K respectively. |
format |
Article in Journal/Newspaper |
author |
Minghu, Ding Agrawal, Anubha Heil, Petra Diyi, Yang |
author_facet |
Minghu, Ding Agrawal, Anubha Heil, Petra Diyi, Yang |
author_sort |
Minghu, Ding |
title |
Surface energy balance on the Antarctic plateau as measured with an automatic weather station during 2014 |
title_short |
Surface energy balance on the Antarctic plateau as measured with an automatic weather station during 2014 |
title_full |
Surface energy balance on the Antarctic plateau as measured with an automatic weather station during 2014 |
title_fullStr |
Surface energy balance on the Antarctic plateau as measured with an automatic weather station during 2014 |
title_full_unstemmed |
Surface energy balance on the Antarctic plateau as measured with an automatic weather station during 2014 |
title_sort |
surface energy balance on the antarctic plateau as measured with an automatic weather station during 2014 |
publisher |
Polar Research Institute of China - PRIC |
publishDate |
2019 |
url |
http://library.arcticportal.org/2685/ http://library.arcticportal.org/2685/1/A1902002.pdf |
geographic |
Antarctic The Antarctic East Antarctica |
geographic_facet |
Antarctic The Antarctic East Antarctica |
genre |
Advances in Polar Science Antarc* Antarctic Antarctica East Antarctica Polar Science Polar Science |
genre_facet |
Advances in Polar Science Antarc* Antarctic Antarctica East Antarctica Polar Science Polar Science |
op_relation |
http://library.arcticportal.org/2685/1/A1902002.pdf Minghu, Ding and Agrawal, Anubha and Heil, Petra and Diyi, Yang (2019) Surface energy balance on the Antarctic plateau as measured with an automatic weather station during 2014. Advances in Polar Science, 30 (2). pp. 93-105. |
_version_ |
1784893016116297728 |