ALBERT

Description: Monthly surface temperatures in the Arctic and Antarctic regions have been derived from the 11.5 micrometer thermal infrared channel of the Nimbus 7 temperature humidity infrared radiometer (THIR) for a whole year in 1979 and for a winter and a summer month from 1980 through 1985. The data set shows interannual variability and provides spatial details that allow identification of temperature patterns over sea ice and ice sheet surfaces. For example, the coldest spot in the southern hemisphere is observed to be consistently in the Antarctic plateau in the southern hemisphere, while that in the northern hemisphere is usually located in Greenland, or one of three other general areas: Siberia, the central Arctic, or the Canadian Archipelago. Also, in the southern hemisphere, the amplitude of the seasonal fluctuation of ice sheet temperatures is about 3 times that of sea ice, while in the northern hemisphere, the corresponding fluctuations for the two surfaces are about the same. The main sources of error in the retrieval are cloud and other atmospheric effects. These were minimized by first choosing the highest radiance value from the set of measurements during the day taken within a 30 km by 30 km grid of each daily map. Then the difference of daily maps was taken and where the difference is greater than a certain threshold (which in this case is 12 C), the data element is deleted. Overall, the monthly maps derived from the resulting daily maps are spatially and temporally consistent, are coherent with the topograph y of the Antarctic continent and the location of the sea ice edge, and are in qualitative agreement with climatological data. Quantitatively, THIR data are in good agreement with Antarctic ice sheet surface air temperature station data with a correlation coefficient of 0.997 and a standard deviation of 2.0 C. The absolute values are not as good over the sea ice edges, but a comparison with Russian 2-m drift station temperatures shows very high correlation (with correlation coefficient at 0.998) and a standard deviation of 1.1 C. Overall, the rms error is estimated to be from 1 to 2 C, depending on the surface, while the average bias when compared with in situ data is less than 2 C.