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Because of a lack of regular, direct measurements, limited information is available about the frequency and the spatial and temporal distribution of icing conditions aloft, including supercooled large drops (SLD). Research aircraft provide in situ observations of these conditions, but the sample set is small and can be biased. Surface observations of freezing fog and freezing precipitation provide additional insight, but cannot be used alone to assess the presence of icing aloft. Climatologies based solely on such observations can underestimate their presence in areas where subfreezing temperatures are uncommon. Other techniques can be used in an effort to reduce some of these biases and limitations. Expanding upon results for North America reported in Part I, the frequencies of icing and SLD over Europe and Asia are inferred here using 1) surface weather observations in conjunction with vertical profiles of temperature and moisture and 2) model reanalyses of temperature and moisture. Icing maxima and minima are found to migrate seasonally, both geographically and in the vertical, and to vary in their intensity. They are linked to the location of common storm tracks and other forcing, such as that associated with sloped terrain. After establishing reasonable consistency between the methods over data rich regions, the model analyses are used to examine icing frequencies over the remainder of the globe. [ABSTRACT FROM AUTHOR]

The accuracy and precision are determined of cloud liquid water path (LWP) retrievals from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat-8 using 1 yr of LWP retrievals from microwave radiometer (MWR) measurements of two CloudNET stations in northern Europe. The MWR retrievals of LWP have a precision that is superior to current satellite remote sensing techniques, which justifies their use as validation data. The Cloud Physical Properties (CPP) algorithm of the Satellite Application Facility on Climate Monitoring (CM-SAF) is used to retrieve LWP from SEVIRI reflectances at 0.6 and 1.6 μm. The results show large differences in the accuracy and precision of LWP retrievals from SEVIRI between summer and winter. During summer, the instantaneous LWP retrievals from SEVIRI agree well with those from the MWRs. The accuracy is better than 5 g m-2 and the precision is better than 30 g m-2, which is similar to the precision of LWP retrievals from MWR. The added value of the 15-min sampling frequency of Meteosat-8 becomes evident in the validation of the daily median and diurnal variations in LWP retrievals from SEVIRI. The daily median LWP values from SEVIRI and MWR are highly correlated (correlation > 0.95) and have a precision better than 15 g m-2. In addition, SEVIRI and MWR reveal similar diurnal variations in retrieved LWP values. The peak LWP values occur around noon. During winter, SEVIRI generally overestimates the instantaneous LWP values from MWR, the accuracy drops to about 10 g m2, and the precision to about 30 g m-2. The most likely reason for these lower accuracies is the shortcoming of CPP, and similar one-dimensional retrieval algorithms, to model inhomogeneous clouds. It is suggested that neglecting cloud inhomogeneities leads to a significant overestimation of LWP retrievals from SEVIRI over northern Europe during winter. [ABSTRACT FROM AUTHOR]