| Summary: | under noll grader och snö och regn är vanligt förekommande, vilket bl.a. skapar hala vägar och behov av A new Polar Platform Systems (PPS) Cloud Mask (CM) test sequence is required for improving cloud detection during Arctic winter conditions. This study introduces a test sequence, called Ice Night Sea (INS), that to a greater extent successfully detects clouds over ice surfaces and which is less sensitive to cloud free misclassification.The test sequence uses a combination of Numerical Weather Prediction (NWP) fields and Advanced Very High Resolution Radiometer (AVHRR) satellite data. Only the infrared (IR) AVHRR channels can be exploited during night conditions. Training target data from winter 2001-2002, collected over a large area north of the Atmospheric Radiation Measurement (ARM) site at Barrow, Alaska, were used to assess the general atmospheric state of the Arctic and to perform a qualitative validation of CM test sequences. Results clearly show that the atmospheric conditions during Arctic winter severely hamper cloud detection efforts. Very cold surface temperatures and immense surface temperature inversions lead to a diminished separability between surfaces and clouds. One particular problem is that the IR brightness temperatures for the shortest wavelength (3.7μm - henceforth T37) are strongly affected by noise. The use of an IR noise filter was shown to improve results significantly. In addition, the problem of misclassifying cracks in the pack ice as Cirrus clouds was basically solved by using a dedicated filter using the local variance of T37.Using an inverse version of a typical daytime Cirrus test (based on just two IR channels and normally applied successfully outside the Arctic region), it is shown that we can detect a substantial part of the warmsemi-transparent clouds commonly found in the Arctic. Running the test sequences on training target data revealed an improvement in correct cloud free target classification of around 30% but only a marginal improvement for cloudy training targets. ...
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