Abstract. The spatio-temporal variability of integrated water vapour (IWV) on small scales of less than 10 km and hours is assessed with data from the 2 months of the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP) 2 ) Observational Prototype Experiment (HOPE). The statistical intercomparison of the unique set of observations during HOPE (microwave radiometer (MWR), Global Positioning System (GPS), sun photometer, radiosondes, Raman lidar, infrared and near-infrared Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellites Aqua and Terra) measuring close together reveals a good agreement in terms of random differences (standard deviation ≤ 1 kg m −2 ) and correlation coefficient (≥ 0.98). The exception is MODIS, which appears to suffer from insufficient cloud filtering.For a case study during HOPE featuring a typical boundary layer development, the IWV variability in time and space on scales of less than 10 km and less than 1 h is investigated in detail. For this purpose, the measurements are complemented by simulations with the novel ICOsahedral Nonhydrostatic modelling framework (ICON), which for this study has a horizontal resolution of 156 m. These runs show that differences in space of 3-4 km or time of 10-15 min induce IWV variabilities on the order of 0.4 kg m −2 . This model finding is confirmed by observed time series from two MWRs approximately 3 km apart with a comparable temporal resolution of a few seconds.Standard deviations of IWV derived from MWR measurements reveal a high variability (> 1 kg m −2 ) even at very short time scales of a few minutes. These cannot be captured by the temporally lower-resolved instruments and by operational numerical weather prediction models such as COSMO-DE (an application of the Consortium for Small-scale Modelling covering Germany) of Deutscher Wetterdienst, which is included in the comparison. However, for time scales larger than 1 h, a sampling resolution of 15 min is sufficient to capture the mean standard deviation of IWV. The present study shows that instrument sampling plays a major role when climatological information, in particular the mean diurnal cycle of IWV, is determined.

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The spatio-temporal variability of integrated water vapour (IWV) on small-scales of less than 10 km and hours is assessed with data from the two months of the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE). The statistical intercomparison of the unique set of observations during HOPE (microwave radiometer (MWR), Global Positioning System (GPS), sunphotometer, radiosondes, Raman Lidar, infrared and near infrared Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellites Aqua and Terra) measuring close together reveals a good agreement in terms of standard deviation (≤ 1 kg m−2) and correlation coefficient (≥ 0.98). The exception is MODIS, which appears to suffer from insufficient cloud filtering. \ud \ud For a case study during HOPE featuring a typical boundary layer development, the IWV variability in time and space on scales of less than 10 km and less than 1 h is investigated in detail. For this purpose, the measurements are complemented by simulations with the novel ICOsahedral Non-hydrostatic modelling framework (ICON) which for this study has a horizontal resolution of 156 m. These runs show that differences in space of 3–4 km or time of 10–15 min induce IWV variabilities in the order of 4 kg m−2. This model finding is confirmed by observed time series from two MWRs approximately 3 km apart with a comparable temporal resolution of a few seconds.\ud \ud Standard deviations of IWV derived from MWR measurements reveal a high variability (> 1 kg m−2) even at very short time scales of a few minutes. These cannot be captured by the temporally lower resolved instruments and by operational numerical weather prediction models such as COSMO-DE (an application of the Consortium for Small-scale Modelling covering Germany) of Deutscher Wetterdienst, which is included in the comparison. However, for time scales larger than 1 h, a sampling resolution of 15 min is sufficient to capture the mean standard deviation of IWV. The present study shows that instrument sampling plays a major role when climatological information, in particular the mean diurnal cycle of IWV, is determined

The present study evaluates the global numerical weather prediction model GME with respect to frozen particles, both ice and snow, focusing on the performance of a diagnostic versus a prognostic precipitation scheme. As a reference, CloudSat Cloud Profiling Radar observations are utilized – the so far only near-globally available data set which vertically resolves clouds. Both the observation-to-model and the model-to-observation approach are applied and compared to each other. For the latter, the radar simulator QuickBeam is utilized. Criteria are applied to further improve the comparability between model and observations. The two model versions are statistically evaluated for a four-month period. <br><br> The comparison reveals that the prognostic scheme reproduces the shape of the CloudSat frequency distributions for both ice water content (IWC) and reflectivity factor well, while the diagnostic scheme produces no large IWCs or reflectivity factors because snow falls out instantaneously. However, the prognostic scheme overestimates the occurrence of high ice water paths (IWP), especially in the mid-latitudes. Sensitivity tests show that an increased fall speed of snow successfully reduces IWP. Both approaches capture the general features, but for details, the two together deliver the largest informational content. In case of limited resources, the model-to-observation approach is preferred. Finally, the results indicate that the lack of IWC in most global circulation models might be attributed to the use of diagnostic precipitation schemes, i.e., the lack of snow aloft. <br><br> Based on its good performance the prognostic scheme went into operational mode in February 2010. The adjusted snow fall speed went operational in December 2010. However, continual improvements of the ice microphysics are necessary, which can be assessed by the proposed evaluation technique