Spatial and temporal variability of satellite‐derived cloud and surface characteristics during FIRE‐ACE

Maslanik, James A; Key, Jeffrey R.; Fowler, Charles W.; Nguyen, Tri-Thanh; Wang, X.a

doi:10.1029/2000jd900284

Cited by 47 publications

(50 citation statements)

References 24 publications

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“…The wintertime mean of C APP-x agrees with C pyr based on the results shown in the top panel of Fig. 5, but C APP-x overestimates cloud cover relative to C pyr during the short summer, contrary to expectations based on Meier et al (1997), but consistent with the results of Maslanik et al (2001). Table 2 shows trends computed from the visual and pyrgeometer time series.…”

Section: B Seasonal Cyclessupporting

confidence: 69%

Cloud Cover over the South Pole from Visual Observations, Satellite Retrievals, and Surface-Based Infrared Radiation Measurements

2007

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Estimates of cloud cover over the South Pole are presented from five different data sources: routine visual observations ; C vis ), surface-based spectral infrared (IR) data (2001; C PAERI ), surface-based broadband IR data (1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003); C pyr ), the Extended Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder (APP-x) dataset (1994-99; C APP-x ), and the International Satellite Cloud Climatology Project (ISCCP) dataset (1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003); C ISCCP ). The seasonal cycle of cloud cover is found to range from 45%-50% during the short summer to a relatively constant 55%-65% during the winter. Relationships between C pyr and 2-m temperature, 10-m wind speed and direction, and longwave radiation are investigated. It is shown that clouds warm the surface in all seasons, 0.5-1 K during summer and 3-4 K during winter. The annual longwave cloud radiative forcing is 18 W m Ϫ2 for downwelling radiation and 10 W m Ϫ2 for net radiation. The cloud cover datasets are intercompared during the time periods in which they overlap. The nighttime bias of C vis is worse than previously suspected, by approximately Ϫ20%; C ISCCP shows some skill during the polar day, while C APP-x shows some skill at night. The polar cloud masks for the satellite data reviewed here are not yet accurate enough to reliably derive surface or cloud properties over the East Antarctic Plateau. The best surface-based source of cloud cover in terms of the combination of accuracy and length of record is determined to be C pyr . The use of the C pyr dataset for further tests of satellite retrievals and for tests of polar models is recommended.

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Section: B Seasonal Cyclessupporting

confidence: 69%

Cloud Cover over the South Pole from Visual Observations, Satellite Retrievals, and Surface-Based Infrared Radiation Measurements

2007

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“…The APP-x data have been validated with in situ data from the Surface Heat Budget of the Arctic Ocean (SHEBA) field experiment (Maslanik et al, 2001), the Collaborative Interdisciplinary Cryospheric Experiment (C-ICE), and the Canadian Arctic Shelf Exchange Study (CASES) (Howell et al, 2006). APP-x data have also been used to assess trends and spatio-temporal variability in surface parameters for Arctic regions (Wang and Key, 2003;Wang and Key, 2005b).…”

Section: Multi-year Sea-ice Conditions In the Northwestmentioning

confidence: 99%

“…APP-x data have also been used to assess trends and spatio-temporal variability in surface parameters for Arctic regions (Wang and Key, 2003;Wang and Key, 2005b). Maslanik et al (2001) note that the APP-x data set can be used to observe coupled relationships between surface state conditions and atmospheric forcings at a relatively fine spatio-temporal resolution. However, Key et al (1997) caution that the satellite-derived surface parameters at high latitudes may still result in some added uncertainty.…”

Section: Multi-year Sea-ice Conditions In the Northwestmentioning

confidence: 99%

Multi‐year sea‐ice conditions in the western Canadian arctic archipelago region of the northwest passage: 1968–2006

et al. 2008

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Numerous studies have reported decreases in Arctic sea-ice cover over the past several decades and General Circulation Model (GCM) simulations continue to predict future decreases. These decreases -particularly in thick perennial or multi-year ice (MYI) -have led to considerable speculation about a more accessible Northwest Passage (NWP) as a transit route through the Canadian Arctic Archipelago (CAA RÉSUMÉ [Traduit par la rédaction] De nombreuses études ont signalé des diminutions dans la couverture de glace de mer arctique au cours des dernières décennies et les simulations des modèles de circulation générale (MCG) continuent de prévoir d'autres diminutions. Ces diminutions -en particulier dans la glace de plusieurs années épaisse et pérenne -ont vivement laissé miroiter la possibilité d'un passage du Nord-Ouest (PNO) plus accessible en tant que route pour traverser l'archipel Arctique canadien (AAC). Les archives numériques du Service canadien des glaces (ANSCG) permettent d'étudier l'importation/exportation et la croissance sur place de la glace de plusieurs années dans les segments du PNO situés dans l'ouest de l'AAC de 1968 à 2006. Cette analyse montre que les conditions de glace de plusieurs années dans les segments du PNO situés dans l'ouest de l'AAC sont restées assez stables parce que les régions de Franklin et du détroit de M'Clintock agissent continuellement comme un mécanisme de drain à siphon pour la glace de plusieurs années. Les résultats montrent aussi qu'en plus de la région des îles de la Reine-Élisabeth, l'ouest du détroit de Parry et le détroit de M'Clintock

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“…Progress toward improving retrievals has been made and several useful datasets over the Arctic Ocean are now available (Key 2000;Maslanik et al 2001;Schweiger et al 1999). The Radiative Transfer for the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) Polar Pathfinder (TPP) dataset (Schweiger et al 2002) is derived from the High Resolution Infrared Radiation Sounder (HIRS) and Microwave Sounding Unit (MSU) instruments aboard the National Oceanic and Atmospheric Administration (NOAA) polar-orbiting platforms and is available for the period 1980-2004.…”

Section: Datasetsmentioning

confidence: 99%

Relationships between Arctic Sea Ice and Clouds during Autumn

et al. 2008

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The connection between sea ice variability and cloud cover over the Arctic seas during autumn is investigated by analyzing the 40-yr ECMWF Re-Analysis (ERA-40) products and the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) Polar Pathfinder satellite datasets. It is found that cloud cover variability near the sea ice margins is strongly linked to sea ice variability. Sea ice retreat is linked to a decrease in low-level cloud amount and a simultaneous increase in midlevel clouds. This pattern is apparent in both data sources. Changes in cloud cover can be explained by changes in the atmospheric temperature structure and an increase in near-surface temperatures resulting from the removal of sea ice. The subsequent decrease in static stability and deepening of the atmospheric boundary layer apparently contribute to the rise in cloud level. The radiative effect of this change is relatively small, as the direct radiative effects of cloud cover changes are compensated for by changes in the temperature and humidity profiles associated with varying ice conditions.

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Spatial and temporal variability of satellite‐derived cloud and surface characteristics during FIRE‐ACE

Cited by 47 publications

References 24 publications

Cloud Cover over the South Pole from Visual Observations, Satellite Retrievals, and Surface-Based Infrared Radiation Measurements

Cloud Cover over the South Pole from Visual Observations, Satellite Retrievals, and Surface-Based Infrared Radiation Measurements

Multi‐year sea‐ice conditions in the western Canadian arctic archipelago region of the northwest passage: 1968–2006

Relationships between Arctic Sea Ice and Clouds during Autumn

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