Accounting for Clouds in Sea Ice Models
Over sea ice in winter, the clouds, the surface layer air temperature, and the longwave radiation are closely coupled. This report uses archived data from the Russian North Pole (NP) drifting stations and recent data from Ice Station Weddell (ISW) to investigate this coupling. Both Arctic and Antarc...
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ftdtic:ADA358288 2023-05-15T13:37:12+02:00 Accounting for Clouds in Sea Ice Models Makshtas, Aleksandr P. Andreas, Edgar L. Svyashchennikov, Pavel N. Timachev, Valery F. COLD REGIONS RESEARCH AND ENGINEERING LAB HANOVER NH 1998-12 text/html http://www.dtic.mil/docs/citations/ADA358288 http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA358288 en eng http://www.dtic.mil/docs/citations/ADA358288 APPROVED FOR PUBLIC RELEASE DTIC AND NTIS Meteorology *WEATHER FORECASTING *CLOUD COVER *SEA ICE ALGORITHMS ATMOSPHERIC TEMPERATURE SURFACE TEMPERATURE ANTARCTIC REGIONS ARCTIC REGIONS PE61102A Text 1998 ftdtic 2016-02-20T01:03:53Z Over sea ice in winter, the clouds, the surface layer air temperature, and the longwave radiation are closely coupled. This report uses archived data from the Russian North Pole (NP) drifting stations and recent data from Ice Station Weddell (ISW) to investigate this coupling. Both Arctic and Antarctic distributions of total cloud amount are U shaped; that is, observed cloud amounts are typically either 0-2 tenths or 8-10 tenths in the polar regions. These data obey beta distributions; roughly 70 station years of observations from the NP stations yielded fitting parameters for each winter month. Although surface layer air temperature and total cloud amount are correlated, it is not straightforward to predict one from the other, because temperature is normally distributed while cloud amount has a U shaped distribution. Nevertheless, the report presents a statistical algorithm that can predict total cloud amount in winter from surface layer temperature alone and, as required, produces a distribution of cloud amounts that is U shaped. Because sea ice models usually need cloud data to estimate incoming longwave radiation, this algorithm may be useful for estimating cloud amounts and, thus, for computing the surface heat budget where no visual cloud observations are available but temperature is measured from the Arctic buoy network or from automatic weather stations, for example. The incoming longwave radiation in sea ice models is generally highly parameterized. The report evaluates five common parameterizations using data from NP-25 and ISW. The formula for estimating incoming longwave radiation that Koenig-Langlo and Augstein developed using both Arctic and Antarctic data has the best properties but does depend nonlinearly on total cloud amount. This nonlinearity is crucial since cloud distributions are U shaped, while common sources of cloud data tabulate only mean monthly values. Text Antarc* Antarctic Arctic North Pole Russian North Sea ice Defense Technical Information Center: DTIC Technical Reports database Antarctic Arctic North Pole Weddell |
institution |
Open Polar |
collection |
Defense Technical Information Center: DTIC Technical Reports database |
op_collection_id |
ftdtic |
language |
English |
topic |
Meteorology *WEATHER FORECASTING *CLOUD COVER *SEA ICE ALGORITHMS ATMOSPHERIC TEMPERATURE SURFACE TEMPERATURE ANTARCTIC REGIONS ARCTIC REGIONS PE61102A |
spellingShingle |
Meteorology *WEATHER FORECASTING *CLOUD COVER *SEA ICE ALGORITHMS ATMOSPHERIC TEMPERATURE SURFACE TEMPERATURE ANTARCTIC REGIONS ARCTIC REGIONS PE61102A Makshtas, Aleksandr P. Andreas, Edgar L. Svyashchennikov, Pavel N. Timachev, Valery F. Accounting for Clouds in Sea Ice Models |
topic_facet |
Meteorology *WEATHER FORECASTING *CLOUD COVER *SEA ICE ALGORITHMS ATMOSPHERIC TEMPERATURE SURFACE TEMPERATURE ANTARCTIC REGIONS ARCTIC REGIONS PE61102A |
description |
Over sea ice in winter, the clouds, the surface layer air temperature, and the longwave radiation are closely coupled. This report uses archived data from the Russian North Pole (NP) drifting stations and recent data from Ice Station Weddell (ISW) to investigate this coupling. Both Arctic and Antarctic distributions of total cloud amount are U shaped; that is, observed cloud amounts are typically either 0-2 tenths or 8-10 tenths in the polar regions. These data obey beta distributions; roughly 70 station years of observations from the NP stations yielded fitting parameters for each winter month. Although surface layer air temperature and total cloud amount are correlated, it is not straightforward to predict one from the other, because temperature is normally distributed while cloud amount has a U shaped distribution. Nevertheless, the report presents a statistical algorithm that can predict total cloud amount in winter from surface layer temperature alone and, as required, produces a distribution of cloud amounts that is U shaped. Because sea ice models usually need cloud data to estimate incoming longwave radiation, this algorithm may be useful for estimating cloud amounts and, thus, for computing the surface heat budget where no visual cloud observations are available but temperature is measured from the Arctic buoy network or from automatic weather stations, for example. The incoming longwave radiation in sea ice models is generally highly parameterized. The report evaluates five common parameterizations using data from NP-25 and ISW. The formula for estimating incoming longwave radiation that Koenig-Langlo and Augstein developed using both Arctic and Antarctic data has the best properties but does depend nonlinearly on total cloud amount. This nonlinearity is crucial since cloud distributions are U shaped, while common sources of cloud data tabulate only mean monthly values. |
author2 |
COLD REGIONS RESEARCH AND ENGINEERING LAB HANOVER NH |
format |
Text |
author |
Makshtas, Aleksandr P. Andreas, Edgar L. Svyashchennikov, Pavel N. Timachev, Valery F. |
author_facet |
Makshtas, Aleksandr P. Andreas, Edgar L. Svyashchennikov, Pavel N. Timachev, Valery F. |
author_sort |
Makshtas, Aleksandr P. |
title |
Accounting for Clouds in Sea Ice Models |
title_short |
Accounting for Clouds in Sea Ice Models |
title_full |
Accounting for Clouds in Sea Ice Models |
title_fullStr |
Accounting for Clouds in Sea Ice Models |
title_full_unstemmed |
Accounting for Clouds in Sea Ice Models |
title_sort |
accounting for clouds in sea ice models |
publishDate |
1998 |
url |
http://www.dtic.mil/docs/citations/ADA358288 http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA358288 |
geographic |
Antarctic Arctic North Pole Weddell |
geographic_facet |
Antarctic Arctic North Pole Weddell |
genre |
Antarc* Antarctic Arctic North Pole Russian North Sea ice |
genre_facet |
Antarc* Antarctic Arctic North Pole Russian North Sea ice |
op_source |
DTIC AND NTIS |
op_relation |
http://www.dtic.mil/docs/citations/ADA358288 |
op_rights |
APPROVED FOR PUBLIC RELEASE |
_version_ |
1766089254916587520 |