Analysis of merged SMMR-SSMI time series of Arctic and Antarctic sea ice parameters 1978-1995
Analysis of merged SMMR-SSMI time series of Arctic and Antarctic sea ice parameters 1978-1995
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DOI：
10.1029/96gl04021
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发表时间：
1997-02-15
影响因子：
5.2
通讯作者：
Miles, MW
中科院分区：
文献类型：
--
作者：
Bjorgo, E;Johannessen, OM;Miles, MW
调查全球海冰覆盖最一致的方法是卫星被动微波传感器，因为这些传感器不受光照和云层的影响。Nimbus 7扫描多通道。微波辐射计(SMMR)和国防气象卫星计划(DMSP)特殊传感器微波成像仪(SSMI)提供了1978年至今全球海冰覆盖的信息。这两台仪器在1987年7月和8月的6周重叠期内同时飞行，从而实现了两个传感器的相互比较。通过使用西北遥感实验(NORSEX)算法，对亮度温度进行了仪器漂移和校准差异的校正，以产生月平均北极和南极海冰面积和海冰面积的连续时间序列，该算法将亮度温度与冰浓度联系起来。对时间序列的统计分析估计，在16.8年的观测期内，北极冰盖面积和冰盖面积的减少分别为4.5%和5.7%。根据对SMMR和SSMI数据的分析，这里建立的总体趋势有助于更好地定义和加强早先关于冰盖减少的断言。这些结果与GCM模拟结果一致，GCM模拟结果表明，在全球变暖的情况下，海冰覆盖面积正在消退。
The most consistent means of investigating the global sea ice cover is by satellite passive microwave sensors, as these are independent of illumination and cloud cover. The Nimbus 7 Scanning Multichannel. Microwave Radiometer (SMMR) and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Imager (SSMI) provide information on the global sea ice cover from 1978 to present. The two instruments flew simultaneously during a 6-week overlap period in July and August 1987, thus enabling intercomparison of the two sensors. Brightness temperatures are corrected for instrument drift and calibration differences in order to produce continuous time series of monthly averaged Arctic and Antarctic sea ice extent and sea ice area through the use of the NOr-wegian Remote Sensing EXperiment (NORSEX) algorithm, which relates brightness temperatures to ice concentration. Statistical analysis on the time series estimates the decreases in Arctic ice extent and ice area to be 4.5% and 5.7%, respectively, during the 16.8-year observation period. The overall trends established here serve to better define and strengthen earlier assertions of a reduced ice cover, based on analysis of SMMR and SSMI data taken separately. These results are consistent with GCM simulations that suggest retreat of the sea ice cover under global warming scenarios.