# Skill Scores SEV/OCA vs. ACTRIS from 20250707 to 20250720 # Legend: # Ntot = Total number of points used for computation of skill scores # For Parameter=Cloud Mask --> POD_1 = Probability Of Detection for clear-sky (from 0=WORST value to 1=BEST value, -999=no statistic) # POD_2 = Probability Of Detection for clouds (from 0=WORST value to 1=BEST value, -999=no statistic) # FAR_1 = False Alarm Rate for clear-sky (from 0=BEST value to 1=WORST value, -999=no statistic) # FAR_2 = False Alarm Rate for clouds (from 0=BEST value to 1=WORST value, -999=no statistic) # HR = Hit Rate for cloud detection (from 0=WORST value to 1=BEST value, -999=no statistic) # For Parameter=Cloud Phase --> POD_1 = Probability Of Detection for water clouds (from 0=WORST value to 1=BEST value, -999=no statistic) # POD_2 = Probability Of Detection for ice clouds (from 0=WORST value to 1=BEST value, -999=no statistic) # FAR_1 = False Alarm Rate for water clouds (from 0=BEST value to 1=WORST value, -999=no statistic) # FAR_2 = False Alarm Rate for ice clouds (from 0=BEST value to 1=WORST value, -999=no statistic) # HR = Hit Rate for cloud phase (from 0=WORST value to 1=BEST value, -999=no statistic) # For Parameter=N. of Layers--> POD_1 = Probability Of Detection for single layer (from 0=WORST value to 1=BEST value, -999=no statistic) # POD_2 = Probability Of Detection for 2-layers (from 0=WORST value to 1=BEST value, -999=no statistic) # FAR_1 = False Alarm Rate for single layer (from 0=BEST value to 1=WORST value, -999=no statistic) # FAR_2 = False Alarm Rate for 2-layers (from 0=BEST value to 1=WORST value, -999=no statistic) # HR = Hit Rate single vs. 2-layers (from 0=WORST value to 1=BEST value, -999=no statistic) # # Parameter Ntot POD_1 POD_2 FAR_1 FAR_2 HR Cloud_Mask 18433 0.7341 1.0000 0.0000 0.4066 0.8084 Cloud_Phase_SL 4091 0.9398 0.5170 0.6415 0.0324 0.6113 Cloud_Phase_2L_BotWat 1774 1.0000 -999.0000 0.5000 -999.0000 0.5000 Cloud_Phase_2L_TopIce 811 -999.0000 1.0000 -999.0000 0.0284 0.9716 N_layers 7696 0.9276 0.2175 0.0674 0.7953 0.8716