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Austria depends significantly on high quality, highly resolved weather forecasts, especially due to its complex orography, manifold landscapes and special meteorologically induced natural hazards in the alpine area and its important economic branches agriculture and tourism, which are strongly impacted by weather. The success of these forecasts is determined by a precise definition of the current state of the 3D atmosphere with highly resolved measurements due to the nonlinear nature of atmospheric processes. Radio occultation methods investigate the bending of a radio signal on its way through the atmosphere by measuring the Doppler shift between a global navigation satellite system (GNSS) and a low earth orbit satellite (LEO) and their precise positions. The bending and refraction of the signal depend on atmospheric properties like ionisation of the upper atmosphere and moisture and temperature in lower levels. So, these properties can be indirectly estimated by the bending with a high vertical resolution on the meter scale in the upper levels, where conventional observations (aircraft and radio soundings) are relatively scarce. The observation number of public financed probes dropped down recently by aging and breakdown of the LEO satellites, while on contrary a huge number of recently commercially launched and maintained satellites of the Spire Inc increased the amount of radio occultation data drastically. In addition to atmospheric monitoring, the occultation method can be used for the initialisation of numerical weather prediction models, as it was already shown for some global models (Arpège, GME, ECMWF-IFS), but also limited area models (WRF). Especially, in the latter case with higher model resolutions the definition of the observation operator simulating the measured parameter is rather crucial to succeed. Within the scope of this project, the new occultation measurements of Spire Inc will be assimilated for the first time into the numerical weather prediction system of ZAMG named AROME over Austria. To achieve this aim, data pre-processing is necessary (derivation of the bending angle, quality check by passive assimilation and first guess departure checks). For the time being, a 2D observation operator for bending angle is available in the AROME code, which was developed for coarser resolutions. Within the project, it will be investigated, how it can be improved and adapted to higher resolutions and which steps would be necessary to reach this goal. The possible impact of the new observations on the model performance will be estimated by case studies and a longer test period using intercomparison to a reference run without radio occultation assimilation. Finally the potential of an operational application of the data within the AROME system will be envisaged. (abridged text)
Sentinel-1 satellites with their Synthetic Aperture Radar sensors will make it possible to measure soil moisture in hitherto unreached spatial resolution an requires new approaches in efficient dealing with Big Data. This new data source will be used to create soil moisture products like the Soil Water Index (SWI), whereas the innovative combination with already established satellite sensors (e.g. ASCAT, ERS, SMOS) will result in a product being the new benchmark with regard to spatio-temporal resolution and accuracy. Due to the high resolution of the SWI product based on Sentinel-1 data, it will be feasibly for the first time to meaningful run the weather forecast model AROME with explicit convection in combination with soil moisture data assimilation. The expected positive impact on precipitation forecast quality will be verified within several case studies. At the end of the project, two main outcomes are expected: i) a high-quality soil moisture data set and an ii) improved severe weather forecast.
The collocation method was used to compute water vapor fields for the Upper Rhine Graben (URG) region from GNSS zenith total delays (ZTDs) and InSAR double difference slant delays (ddSTDs). Furthermore, mean temperature from ERA data was used for the conversion of GNSS ZTDs into IWV. The input data are hourly GNSS tropospheric parameters from the GURN (GNSS Upper Rhine Graben network) network for 4 different seasons in the period 2016-2018, as well as ddSTDs for 168 InSAR acquisition epochs of the Sentinel 1A+B satellites. In total, our dataset includes 2D fields of integrated water vapor (IWV) and zenith total delays (ZTDs) as well as 3D 'tomographic' products in form of refractivity fields. For 4 specific seasonal periods, also hourly water vapor density fields are provided by exploiting the relations between IWV and water vapor density in the collocation scheme. The tropospheric fields are provided for the horizontal WRF grid of data assimilation subset of this joint data collection, whereas the 3D fields are computed up to 8 km height for 16 equally distributed layers.
Convection-permitting simulations with the Weather Research and Forecasting Modeling System (WRF) were carried out in order to provide improved water vapor fields for the Upper Rhine Valley in the border region of Germany, Switzerland and France. Hourly ERA5 reanalysis data served as input for three different simulations with (1) open loop, (2) assimilation of GNSS ZTD, InSAR ZTD and synoptic station data and (3) assimilation of tomography ZTD fields. The three-dimensional variation data assimilation (3D-VAR) configuration with hourly resolution was used. The simulations were performed for four events, one in each season (April 11-22, 2016, July 13-23, 2018, October 16-31, 2018, January 6-21, 2017). Surface pressure, temperature (2m) and integrated water vapor are provided in 2D as well as pressure, temperature and water vapor density for each of the 72 vertical levels (3D).
The provided dataset consists of double differential slant delays and absolute zenith wet delays in the region of the Upper Rhine Graben. Basis is the SLC data from Sentinel 1A+B satellites provided by the Copernicus program. 169 scenes were processed which had been acquired between April 2015 and July 2019, including data of four specific study events (11 – 22 Apr 2016, 13 – 24 Jul 2018, 16 – 31 Oct 2018, 06 – 21 Jan 2017). Interferometric processing was performed using the software SNAP, continued by a Persistent Scatterer Interferometric SAR (PS-InSAR) processing, using the program StaMPS. The first product are double differential slant delays which represent the phase delay in radiant in the satellites line of sight between the master acquisition (17 Mar 2012) and each acquisition-date respectively. Further processing uses ERA5 zenith wet delay (ZWD) and mean temperature to infer absolute zenith wet delays. A mean value is subtracted for each scene, resulting in an absolute value correction. In addition, long wavelength components are corrected by fitting the trend over the scene for each date to a 2D polynomial approximation from the ERA5 data, as those parts cannot reliably be estimated solely from the SAR data. The final product for every scene is the integrated water vapor (IWV) in kg/m² for each acquisition date at the distributed PS-points – on average about 50 points per square kilometer.
The ground-based global navigation satellite system (GNSS) technic was employed to retrieve the integrated water vapor (IWV) at 66 stations of the GNSS Upper Rhine Graben network (GURN). The GNSS IWV dataset is synchronous with the associated InSAR dataset, with 219 days available during the period March 2015 – July 2019. GNSS zenith total delay (ZTD) estimates are calculated every one hour and then converted to IWV with additional meteorological parameters from ERA5. The GNSS IWV of all the stations are saved in daily files in the second version of the Solution (Software/Technique) Independent Exchange (SINEX) format for TROpospheric parameters. GNSS station information is given in the file headers. In addition, the associated meteorological parameters from ERA5 are also provided, such as station pressure and weighted mean temperature.
Different observation and modeling techniques were used to derive integrated water vapor (IWV) fields for the Upper Rhine Graben in the border region of Germany, Switzerland, and France. The dataset features 1) point-scale IWV and zenith total delay (ZTD) derived for 66 stations of the global navigation satellite system (GNSS) Upper Rhine Graben network (GURN), 2) area-distributed IWV and differential slant path delays from space-borne Interferometric synthetic aperture radar (InSAR) observations, 3) IWV, ZTD, refractivity (3D), and water vapor density (3D) from tomography, obtained by collocation of GNSS and InSAR products, and 4) IWV, precipitation and water vapor density (3D) simulated with the Weather Research and Forecasting Modeling system (WRF) with free run (open-loop) and three-dimensional variational data-assimilation (3D-VAR) configuration. All data products cover 4 seasonal epochs (11 – 22 Apr 2016, 13 – 24 Jul 2018, 16 – 31 Oct 2018, 06 – 21 Jan 2017). GNSS, InSAR, and tomography data are additionally available for the period Jan 2015 – Jun 2019.
Objective: ACOBAR will develop an observing system for the interior of the Arctic Ocean based on underwater acoustic methods including tomography, data transmission and communication to/from underwater platforms, and navigation of gliders. ACOBAR offers alternative methods to the ARGO system, which cannot be used in ice-covered seas, based on platforms located under the sea ice. Data collection and transmission from the water column, the seafloor and the subseafloor will be possible in ice-covered seas. ACOBAR will contribute to filling gaps in the global ocean observing system and thereby support the development of GEOSS. ACOBAR will implement field experiments with acoustic sources and receivers in the Fram Strait and the Arctic Ocean. Acoustic tomography will be used to obtain integrated 3-D fields of temperature, transports and heat fluxes. Long-range acoustic navigation commands will be tested to operate gliders. Data transmission from fixed moorings via acoustic modems to the surface for downloading from ships or for satellite transmission will be implemented. The existing array of acoustic sources from ice-tethered platforms in the Arctic Ocean will be tested for tomographic measurements of water mass properties. Data from tomography arrays and other underwater platforms will be disseminated to users with near real-time capability, including assimilation in ocean models. ACOBAR will extend and improve methods for underwater data collection that are presently tested in DAMOCLES IP. The acoustic technologies in ACOBAR aim to be used for transmission of multidisciplinary data from underwater observatories under development in ESONET NoE. Transfer of technology and know-how from USA to Europe will take place, with exchange of scientists, workshops and meetings between scientists, engineers and students. The consortium consists of 9 partners, of which three are SMEs and six are research and educational institutions.
Data assimilation aims to blend incomplete and inaccurate data with physics-based dynamical models. In the Earth's radiation belts, it is used to reconstruct electron phase space density, and it has become an increasingly important tool for validating our current understanding of radiation belt dynamics, identifying new physical processes, and predicting the near-Earth hazardous radiation environment. The dataset presents the electron flux reconstructed by assimilating electron flux measurements of the following spacecraft into the 3D Versatile Electron Radiation Belt model (VERB; Shprits et al., 2008, Subbotin and Shprits, 2009): 1. Van Allen Probes Magnetic Electron Ion Spectrometer (MagEIS; Blake et al., 2013) and Relativistic Electron Proton Telescope (REPT; Baker et al., 2013), and 2. Geostationary Operational Environmental Satellites (GOES) Magnetospheric Electron Detector (MAGED; Hanser, 2011), and Energetic Proton, Electron, and Alpha Detector (EPEAD; Onsager et al., 1996, Hanser, 2011). The method employs a split-operator Kalman filter (Shprits et al., 2013). The dataset contains electron flux for the period from 01 October 2012 00:00 UT to 01 October 2016 00:00 UT, organized in monthly files for selected values of electron energies (0.5 MeV, 1 MeV, and 2 MeV) and equatorial pitch angles (20 degree, 50 degree, and 70 degree).
The mission of World Data Center for Climate (WDCC) is to provide central support for the German and European climate research community. The WDCC is member of the ISC's World Data System. Emphasis is on development and implementation of best practice methods for Earth System data management. Data for and from climate research are collected, stored and disseminated. The WDCC is restricted to data products. Cooperations exist with thematically corresponding data centres of, e.g., earth observation, meteorology, oceanography, paleo climate and environmental sciences. The services of WDCC are also available to external users at cost price. A special service for the direct integration of research data in scientific publications has been developed. The editorial process at WDCC ensures the quality of metadata and research data in collaboration with the data producers. A citation code and a digital identifier (DOI) are provided and registered together with citation information at the DOI registration agency DataCite.
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