Trends in satellite-derived cloud and surface properties for 1982 to 1999 show that the Arctic has warmed and become cloudier in spring and summer but has cooled and become less cloudy in winter. The increase in spring cloud amount radiatively balances changes in surface temperature and albedo, but during summer, fall, and winter, cloud forcing has tended toward increased cooling. This implies that, if seasonal cloud amounts were not changing, surface warming would be even greater than that observed. Strong correlations with the Arctic Oscillation indicate that the rise in surface temperature and changes in cloud amount are related to large-scale circulation rather than to local processes.
With broad spectral coverage and high spatial and temporal resolutions, satellite sensors can provide the data needed for the analysis of spatial and temporal variations of climate parameters in data-sparse regions such as the Arctic and Antarctic. The newly available Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder (APP) dataset was used to retrieve cloud fraction, cloud optical depth, cloud particle phase and size, cloud-top pressure and temperature, surface skin temperature, surface broadband albedo, radiative fluxes, and cloud forcing over the Arctic Ocean and surrounding landmasses for the 18-yr period from 1982 to 1999. In the Arctic, Greenland is the coldest region with the highest surface albedo, while northeastern Russia has the highest surface temperature in summer. Arctic annual mean cloud coverage is about 70%, with the largest cloudiness occurring in September and the lowest cloudiness occurring in April. On annual average, Arctic cloud visible optical depth is about 5–6. Arctic precipitable water is near 0.2 cm in winter and 1.5 cm in summer. The largest downwelling shortwave radiative flux at the surface occurs in June; the largest upwelling shortwave radiative flux occurs in May. The largest downwelling and upwelling longwave radiative fluxes as well as the net all-wave radiative flux occur in July, with the largest loss of longwave radiation from the surface in April.
Over the past 20 yr, some Arctic surface and cloud properties have changed significantly. Results of an analysis of satellite data show that the Arctic has warmed and become cloudier in spring and summer but has cooled and become less cloudy in winter. The annual rate of surface temperature change is 0.057°C for the Arctic region north of 60°N. The surface broadband albedo has decreased significantly in autumn, especially over the Arctic Ocean, indicating a later freeze-up and snowfall. The surface albedo has decreased at an annual rate of −0.15% (absolute). Cloud fraction has decreased at an annual rate of −0.6% (absolute) in winter and increased at annual rates of 0.32% and 0.16% in spring and summer, respectively. On an annual time scale, there is no trend in cloud fraction. During spring and summer, changes in sea ice albedo that result from surface warming tend to modulate the radiative effect of increasing cloud cover. On an annual time scale, the all-wave cloud forcing at the surface has decreased at an annual rate of –0.335 W m−2, indicating an increased cooling by clouds. There are large correlations between surface temperature anomalies and climate indices such as the Arctic Oscillation (AO) index for some areas, implying linkages between global climate change and Arctic climate change.
In this study, six Arctic sea ice thickness products are compared: the AVHRR Polar Pathfinder-extended (APP-x), ICESat, CryoSat-2, SMOS, NASA IceBridge aircraft flights, and the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS). The satellite products are based on three different retrieval methods: an energy budget approach, measurements of ice freeboard, and the relationship between passive microwave brightness temperatures and thin ice thickness. Inter-comparisons are done for the periods of overlap from 2003 to 2013. Results show that ICESat sea ice is thicker than APP-x and PIOMAS overall, particularly along the north coast of Greenland and Canadian Archipelago. The relative differences of APP-x and PIOMAS with ICESat are −0.48 m and −0.31 m, respectively. APP-x underestimates thickness relative to CryoSat-2, with a mean difference of −0.19 m. The biases for APP-x, PIOMAS, and CryoSat-2 relative to IceBridge thicknesses are 0.18 m, 0.18 m, and 0.29 m. The mean difference between SMOS and CryoSat-2 for 0~1 m thick ice is 0.13 m in March and −0.24 m in October. All satellite-retrieved ice thickness products and PIOMAS overestimate the thickness of thin ice (1 m or less) compared to IceBridge for which SMOS has the smallest bias (0.26 m). The spatial correlation between the datasets indicates that APP-x and PIOMAS are the most similar, followed by APP-x and CryoSat-2.
With recent, dramatic changes in Arctic sea ice and the Antarctic ice sheets, the importance of monitoring the climate of the polar regions has never been greater. While many individual global satellite products exist, the AVHRR Polar Pathfinder products provide a comprehensive set of variables that can be used to study trends and interactions within the Arctic and Antarctic climate systems. This paper describes the AVHRR Polar Pathfinder (APP), which is a fundamental climate data record that provides channel reflectances and brightness temperatures, and the AVHRR Polar Pathfinder—Extended (APP-x), which is a thematic climate data record that builds on APP to provide information on surface and cloud properties and radiative fluxes. Both datasets cover the period from 1982 through the present, twice daily, over both polar regions. APP-x has been used in the study of trends in surface properties, cloud cover, and radiative fluxes, interactions between clouds and sea ice, and the role of land surface changes in summer warming.
16 December 2010 in Journal of Geophysical Research: Oceans