Abstract
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.
Highlights
Water vapour is the most effective greenhouse gas (Kiehl and Trenberth, 1997) and an important part of the hydrological cycle, so that the exact knowledge on atmospheric moisture is absolutely essential for both numerical weather prediction (NWP; e.g. Weckwerth et al, 1999) and climate modelling (e.g. Bony et al, 2006)
Kahn et al (2011) compare the integrated water vapour (IWV) variability in NWP and climate models with those directly observed by Atmospheric InfraRed Sounder (AIRS) observations and airborne measurements with a focus on stratocumulus regions over ocean
We first investigate the instrument performance during the whole period of HD(CP)2 Observational Prototype Experiment (HOPE) before we analyse whether the small-scale temporal IWV variability (< 1 h) revealed in the case study is typical for the complete HOPE period
Summary
Water vapour is the most effective greenhouse gas (Kiehl and Trenberth, 1997) and an important part of the hydrological cycle, so that the exact knowledge on atmospheric moisture is absolutely essential for both numerical weather prediction (NWP; e.g. Weckwerth et al, 1999) and climate modelling (e.g. Bony et al, 2006). Water vapour is the most effective greenhouse gas (Kiehl and Trenberth, 1997) and an important part of the hydrological cycle, so that the exact knowledge on atmospheric moisture is absolutely essential for both numerical weather prediction Weckwerth et al, 1999) and climate modelling Water vapour has been investigated in several field campaigns such as the HYdrological cycle in the Mediterranean EXperiment (HyMeX; Drobinski et al, 2014) and the Convective and Orographically-induced Precipitation Study (COPS; Wulfmeyer et al, 2011). There is still need for research about its role in various atmospheric processes. The interaction between atmospheric humidity and convec-. S. Steinke et al.: Assessment of small-scale integrated water vapour variability
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