Assessment of small-scale integrated water vapour variability during HOPE

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. 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. 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.