ALBERT

Description: The past two decades have witnessed an explosion of DNA sequencing technologies that provide unprecedented insights into genome sequences—the blueprints of life on Earth. Although initially driven by biomedical research, this revolution offers exciting opportunities in Earth sciences. Analyzing genomes and other biomolecules ("omic" methods) within environmental samples provides new vistas of microbial geochemistry. However, the massive amount of data produced can be hard to decipher, and the resources and infrastructure to train and support geoscientists in omics approaches are lacking. This article summarizes some of the opportunities and challenges in the applications of omic approaches to geochemical problems.

Description: Initial objectives and design of the Benchmark campaign organized within the European COST Action ES1206 (2013-2017) are described in the paper. This campaign has aimed at supporting the development and validation of advanced GNSS tropospheric products, in particular high-resolution and ultra-fast zenith total delays (ZTD) and tropospheric gradients derived from a dense permanent network. A complex dataset was collected for the 8-week period when several extreme heavy precipitation episodes occurred in central Europe which caused severe river floods in this area. An initial processing of data sets from Global Navigation Satellite System (GNSS) and numerical weather models (NWM) provided independently estimated reference parameters – zenith tropospheric delays and tropospheric horizontal gradients. Their provision gave an overview about the product similarities and complementarities and thus a potential for improving a synergy in their optimal exploitations in future. Reference GNSS and NWM results were inter-compared and visually analysed using animated maps. ZTDs from two reference GNSS solutions compared to global ERA-Interim re-analysis resulted in the accuracy at the 10-millimeter level in terms of RMS (with a negligible overall bias), comparisons to global GFS forecast showed accuracy at the 12-millimeter level with the overall bias of -5 mm and, finally, comparisons to mesoscale ALADIN-CZ forecast resulted in the accuracy at the 8-milllimetre level with a negligible total bias. The comparison of horizontal tropospheric gradients from GNSS and NWM data demonstrated a very good agreement among independent solutions with negligible biases and the accuracy of about 0.5 mm. Visual comparisons of maps of zenith wet delays and tropospheric horizontal gradients showed very promising results for future exploitations of advanced GNSS tropospheric products in meteorological applications such as severe weather event monitoring and weather nowcasting. The GNSS products revealed a capability of providing more detailed structures in atmosphere than the state-of-the-art numerical weather models are able to capture. Initial study on contribution of hydrometeors (e.g. cloud water, ice or snow) to GNSS signal delays during severe weather reached up to 17 mm in zenith path delay and suggested to carefully account them within the functional model. The reference products will be further exploited in various specific studies using the Benchmark dataset. It is thus going to play a key role in these highly inter-disciplinary developments towards better mutual benefits from advanced GNSS and meteorological products.

Description: 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.

Description: Within the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) there is a need for an assessment of the uncertainty in the integrated water vapour (IWV) in the atmosphere estimated from ground-based global navigation satellite system (GNSS) observations. All relevant error sources in GNSS-derived IWV are therefore essential to be investigated. We present two approaches, a statistical and a theoretical analysis, for the assessment of the uncertainty of the IWV. The method is valuable for all applications of GNSS IWV data in atmospheric research and weather forecast. It will be implemented to the GNSS IWV data stream for GRUAN in order to assign a specific uncertainty to each data point. In addition, specific recommendations are made to GRUAN on hardware, software, and data processing practices to minimise the IWV uncertainty. By combining the uncertainties associated with the input variables in the estimations of the IWV, we calculated the IWV uncertainties for several GRUAN sites with different weather conditions. The results show a similar relative importance of all uncertainty contributions where the uncertainties in the zenith total delay (ZTD) dominate the error budget of the IWV, contributing over 75 % of the total IWV uncertainty. The impact of the uncertainty associated with the conversion factor between the IWV and the zenith wet delay (ZWD) is proportional to the amount of water vapour and increases slightly for moist weather conditions. The GRUAN GNSS IWV uncertainty data will provide a quantified confidence to be used for the validation of other measurement techniques.

Description: Water vapor plays an important role in meteorological applications; GeoForschungsZentrum (GFZ) therefore developed a tomographic system to derive 3-D distributions of the tropospheric water vapor above Germany using GPS data from about 300 ground stations. Input data for the tomographic reconstructions are generated by the Earth Parameter and Orbit determination System (EPOS) software of the GFZ, which provides zenith total delay (ZTD), integrated water vapor (IWV) and slant total delay (STD) data operationally with a temporal resolution of 2.5 min (STD) and 15 min (ZTD, IWV). The water vapor distribution in the atmosphere is derived by tomographic reconstruction techniques. The quality of the solution is dependent on many factors such as the spatial coverage of the atmosphere with slant paths, the spatial distribution of their intersections and the accuracy of the input observations. Independent observations are required to validate the tomographic reconstructions and to get precise information on the accuracy of the derived 3-D water vapor fields. To determine the quality of the GPS tomography, more than 8000 vertical water vapor profiles at 13 German radiosonde stations were used for the comparison. The radiosondes were launched twice a day (at 00:00 UTC and 12:00 UTC) in 2007. In this paper, parameters of the entire profiles such as the wet refractivity, and the zenith wet delay have been compared. Before the validation the temporal and spatial distribution of the slant paths, serving as a basis for tomographic reconstruction, as well as their angular distribution were studied. The mean wet refractivity differences between tomography and radiosonde data for all points vary from −1.3 to 0.3, and the root mean square is within the range of 6.5–9. About 32% of 6803 profiles match well, 23% match badly and 45% are difficult to classify as they match only in parts.

Description: Slant-integrated water vapor (SIWV) data derived from GPS STDs (slant total delays), which provide the spatial information on tropospheric water vapor, have a high potential for assimilation to weather models or for nowcasting or reconstruction of the 3-D humidity field with tomographic techniques. Therefore, the accuracy of GPS STD is important, and independent observations are needed to estimate the quality of GPS STD. In 2012 the GFZ (German Research Centre for Geosciences) started to operate a microwave radiometer in the vicinity of the Potsdam GPS station. The water vapor content along the line of sight between a ground station and a GPS satellite can be derived from GPS data and directly measured by a water vapor radiometer (WVR) at the same time. In this study we present the validation results of SIWV observed by a ground-based GPS receiver and a WVR. The validation covers 184 days of data with dry and wet humidity conditions. SIWV data from GPS and WVR generally show good agreement with a mean bias of −0.4 kg m−2 and an rms (root mean square) of 3.15 kg m−2. The differences in SIWV show an elevation dependent on an rms of 7.13 kg m−2 below 15° but of 1.76 kg m−2 above 15°. Nevertheless, this elevation dependence is not observed regarding relative deviations. The relation between the differences and possible influencing factors (elevation angles, pressure, temperature and relative humidity) are analyzed in this study. Besides the elevation, dependencies between the atmospheric humidity conditions, temperature and the differences in SIWV are found.

Description: Ground based GPS zenith path delay (ZPD) measurements are well established as a powerful tool for integrated water vapor (IWV) observation. The International GNSS Service (IGS) provides ZPD data of currently more than 300 globally distributed GPS stations. To derive IWV from these data, meteorological information (ground pressure and mean temperature above the station) are needed. Only a limited number of IGS stations is equipped with meteorological ground sensors up to now. Thus, meteorological data for IWV conversion are usually derived from nearby ground meteorological observations (ground pressure) and meteorological analyses (mean temperature). In this paper we demonstrate for the first time the applicability of ground pressure data from ECMWF meteorological analysis fields in this context. Beside simplified data handling (no single station data and quality control) this approach allows for IWV derivation if nearby meteorological stations are not available. Using ECMWF ground pressure and mean temperature data the new IGS 5-min ZPD data set has been converted to IWV for the first time. We present initial results from selected stations with ground meteorological sensors including pressure and temperature comparisons between ECMWF and local measurements. The GPS IWV is generally validated by comparison with ECMWF IWV. The ECMWF derived station meteorological data are compared with local measurements at all accordingly equipped stations. Based on this comparison, the mean error (in terms of standard deviation) introduced by time interpolation of the 6-hourly ECMWF data is estimated below 0.2 mm IWV.

Description: Within the Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN) there is a need for an assessment of the uncertainty in the Integrated Water Vapour (IWV) in the atmosphere estimated from ground-based GNSS observations. All relevant error sources in GNSS-derived IWV is therefore essential to be investigated. We present two approaches, a statistical and a theoretical analysis, for the assessment of the uncertainty of the IWV. It will be implemented to the GNSS IWV data stream for GRUAN in order to obtain a specific uncertainty for each data point. In addition, specific recommendations are made to GRUAN on hardware, software, and data processing practices to minimize the IWV uncertainty. By combining the uncertainties associated with the input variables in the estimations of the IWV, we calculated the IWV uncertainties for several GRUAN sites with different weather conditions. The results show a similar relative importance of all uncertainty contributions where the uncertainties in the Zenith Total Delay (ZTD) dominate the error budget of the IWV contributing with over 75 % to the total IWV uncertainty. The impact of the uncertainty associated with the conversion factor between the IWV and the Zenith Wet Delay (ZWD) is proportional to the amount of water vapour and increases slightly for moist weather conditions. The GRUAN GNSS IWV uncertainty data will provide a quantified confidence to be used for the validation of other measurement techniques, taking the uncertainty into account from diurnal to decadal time scales.

Description: 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.