Satellite-derived Arctic Climate Characteristics and Recent Trends

Satellite sensors can provide the data needed for the analysis of spatial and temporal patterns 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) data has been extended to create a comprehensive data set, called APP-x, containing cloud fraction, cloud optical depth, cloud particle phase and size, cloud top pressure and temperature, surface temperature and broadband albedo, radiation fluxes and cloud forcing over the Arctic and Antarctic for the 19-year period 1982-2000.

The APP-x data show that the annual mean cloud coverage in the Arctic is about 70%, with a maximum in September and a minimum in April. Arctic cloud optical depth averages about 5 ~ 6. The largest downwelling shortwave radiation flux at the surface occurs in June; the largest upwelling shortwave flux occurs in May. The largest downwelling and upwelling longwave and net radiation fluxes occur in July, with the largest loss of longwave radiation from the surface in April.

Over the past 20 years, the Arctic has warmed and become cloudier in spring and summer, but has cooled and become less cloudy in winter. The decadal rate of annual surface temperature change is 0.57^oC for the area north of 60^oN. The surface broadband albedo has decreased significantly in autumn, indicating a later freeze-up and snowfall. Surface albedo has decreased at a decadal rate of -1.5% (absolute). Cloud fraction has decreased at a decadal rate of 6% (absolute) in winter, and increased at decadal rates of 3.2% and 1.6% 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, net cloud forcing at the surface has decreased at a decadal rate of -3.35 W/m², 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.