Assessment of small-scale integrated water vapour variability during HOPE

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.

Ground-based lidar and microwave radiometry synergy for high vertical resolution absolute humidity profiling

“…The values are small in all situations and lie inside the GPS uncertainty of 1-2 kg m −2 (Gendt et al, 2004) and the MWR product of ∼ 0.5-1 kg m −2 (Steinke et al, 2015). While the only-MWR case presents a negative bias of ∼ 0.5 kg m −2 , the inclusion of the RL in the RL+MWR case corrects this bias, reducing it 1 order of magnitude.…”

“…Note that this flexible framework allows the retrieval of temperature once corresponding RL and MWR data are available. The method was applied to the 2-month dataset collected during HOPE (HD(CP) 2 Observational Prototype Experiment), where a multitude of groundbased remote sensing instruments for the investigation of boundary layer and cloud processes were operated (Steinke et al, 2015;Behrendt et al, 2015;Foth et al, 2015). Here we focus on clear sky cases and absolute humidity profiles.…”

Accomplishments of the MUSICA project to provide accurate, long-term, global and high-resolution observations of tropospheric {H<sub>2</sub>O,<i>δ</i>D} pairs – a review

“…A main characteristic of tropospheric humidity is the high short-term and small-scale variability, which make intercomparison studies difficult. Concerning temporal variability, Steinke et al (2015) reported good correlation of integrated water vapour (IWV) observations and simulations made within 3 h (see their Fig. 7).…”

“…Spatial variability can be estimated by spacebased observations or by models. Steinke et al (2015) used ICON simulations and estimated the scatter for humidity encountered at a distance of 10 km to be about 4 % (right column in their Fig. 4 using an IWV of 12 kg m −2 from their Fig.…”

Vertical distributions of aerosol optical properties during the spring 2016 ARIAs airborne campaign in the North China Plain

“…The DFM-09 radiosonde is a lightweight weather radiosonde that measures temperature (at a resolution of 0.1 • C with an accuracy of 0.2 • C), pressure (at a resolution of 0.1 hPa with an accuracy of 0.5 hPa), RH (at a resolution of 1 % with an accuracy of 2 %), and wind speed (accuracy = 0.2 m s −1 ) (Navas-Guzmán et al, 2014). RH is measured by a thin-film capacitance sensor, and its uncertainties and errors depend on temperature and GPS location (Steinke et al, 2015). Data acquisition and processing were performed at the Graw ground station located at the Xingtai supersite using the Grawmet software.…”