Beschreibung: The Regional Research Network „Water in Central Asia“ (CAWa) funded by the German Federal Foreign Office consists of 19 remotely operated multi-parameter stations (ROMPS) in Central Asia. These stations were installed by the German Research Centre for Geosciences (GFZ) in Potsdam, Germany in close cooperation with the Central-Asian Institute for Applied Geosciences (CAIAG) in Bishkek, Kyrgyzstan, the national hydrometeorological services in Uzbekistan and Tajikistan, the Ulugh Beg Astronomical Institute in Tashkent, Uzbekistan, and the Kabul Polytechnic University, Afghanistan. The primary objective of these stations is to support the establishment of a reliable data basis of meteorological and hydrological data especially in remote areas with extreme climate conditions in Central Asia for applications in climate and water monitoring. Up to now, ten years of data are provided for an area of scarce station distribution and with limited open access data which can be used for a wide range of scientific or engineering applications. This dataset provides different types of raw hydrometeorological data such as air temperature, relative humidity, air pressure, wind speed and direction, precipitation, solar radiation, soil moisture and soil temperature as well as snow parameters and river discharge information for selected sites. The data has not undergone any quality control mechanism and should, therefore, be seen as raw data. A visual inspection of the data set has been made and some errors and quality degradation are listed in Zech et al. (2020) but does not claim to be complete. A quality control is strongly recommended by the authors before using the data. Each station data has its own storage directory at the data dissemination server named with the abbreviation (4-letter code) of the station. The data is sampled with a 5-minute interval and stored in hourly files separated by the type of data. These files are then archived as monthly files named with the station abbreviation, type of data, year and month. After one year, these monthly files are further archived to a yearly file. A detailed description for the stations is provided by the Station Exposure Descriptions. Further information about the dataset can be found in Zech et al. (2020). All data is compiled as ASCII data in two different formats which are explained in the documents GITW-SSP-FMT-GFZ-003.pdf (for the stations ALAI, ALA6, and SARY) and CAWA-SSP-FMT-GFZ-006.pdf (for all other stations). Monthly, the data will be dynamically extended as long as data can be acquired from the stations. Additionally, the near real-time data can be displayed and downloaded without any registration from the Sensor Data Storage System (SDSS) hosted at the Central-Asian Institute for Applied Geosciences (CAIAG) in Bishkek, Kyrgyzstan.

Beschreibung: Interannual to decadal sea level trends are indicators of climate variability and change. A major source of global and regional sea level data is satellite radar altimetry, which relies on precise knowledge of the satellite's orbit. Here, we assess the error budget of the radial orbit component for the TOPEX/Poseidon mission for the period 1993 to 2004 from a set of different orbit solutions. Upper bound errors for seasonal, interannual (5 years), and decadal periods are estimated on global and regional scales based on radial orbit differences from three state-of-the-art orbit solutions provided by different research teams (GFZ, GSFC, and GRGS). The global mean sea level error related to the orbit is of the order of 7 mm (more than 10 % of the sea level variability) with negligible contributions on the annual and decadal time scale. In contrast, the orbit related error of the interannual trend is 0.1 mm/year (18 % of the corresponding sea level variability) and might hamper the estimation of an acceleration of the global mean sea level rise. For regional scales, the gridded orbit related error is up to 11 mm and for about half the ocean the orbit error accounts for at least 10 % of the observed sea level variability. The seasonal orbit error amounts to 10 % of the observed seasonal sea level signal in the Southern Ocean. At interannual and decadal time scales, the orbit related trend uncertainties reach regionally more than 1 mm/year. The interannual trend errors account for 10 % of the observed sea level signal in the Tropical Atlantic and the south-eastern Pacific. For decadal scales, the orbit related trend errors are prominent in a couple of regions including: South Atlantic, western North Atlantic, central Pacific, South Australian Basin, and Mediterranean Sea. Based on a set of test orbits calculated at GFZ, the sources of the observed orbit related errors are further investigated. Main contributors on all time scales are uncertainties in Earth’s time variable gravity field models and on annual to interannual time scales discrepancies of the tracking station sub-networks, i.e., SLR and DORIS.

Beschreibung: The data set provides GFZ VER11 orbits of altimetry satellites ERS-1 (August 1, 1991 - July 5, 1996), ERS-2 (May 13, 1995 - February 27, 2006), Envisat (April 12, 2002 - April 8, 2012), Jason-1 (January 13, 2002 - July 5, 2013) and Jason-2 (July 5, 2008 - April 5, 2015) TOPEX/Poseidon (September 23, 1992 - October 8, 2005), derived at the time spans given at Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences within the Sea Level phase 2 project of the European Space Agency (ESA) Climate Change Initiative using "Earth Parameter and Orbit System - Orbit Computation (EPOS-OC)" software and the Altimeter Database and processing System (ADS, http://adsc.gfz-potsdam.de/ads/) developed at GFZ. The orbits were computed in the same (ITRF2008) terrestrial reference frame for all satellites using common, most precise models and standards available and described below. The ERS-1 orbit is computed using satellite laser ranging (SLR) and altimeter crossover data, while the ERS-2 orbit is derived using additionally Precise Range And Range-rate Equipment (PRARE) measurements. The Envisat, TOPEX/Poseidon, Jason-1 and Jason-2 orbits are based on Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) and SLR observations. The orbit files are available in the Extended Standard Product 3 Orbit Format (SP3-c, ftp://igscb.jpl.nasa.gov/igscb/data/format/sp3c.txt) Files are gzip-compressed. File names are given as sate_YYYYMMDD_SP3C.gz, where "sate" is the abbreviation (ENVI, ERS1, ERS2, JAS1, JAS2, TOPX) of the satellite name, YYYY stands for 4-digit year, MM stands for month and DD stands for day of the beginning of the file. More details on these orbits are provided in Rudenko et al. (2017)

Beschreibung: New, precise, consistent orbits (VER11) of altimetry satellites ERS-1, ERS-2, TOPEX/Poseidon, Envisat, Jason-1, and Jason-2 have been recently derived at the GFZ German Research Centre for Geosciences in the extended ITRF2008 terrestrial reference frame using improved models and covering the time span 1991–2015. These orbits show improved quality, as compared with GFZ previous (VER6) orbits derived in 2013. Improved macromodels reduce root mean square (RMS) fits of satellite laser ranging (SLR) observations by 2.6%, 6.9%, and 7% for TOPEX/Poseidon, Jason-1, and Jason-2, respectively. Applying Vienna Mapping Functions 1 instead of Hopfield model for tropospheric correction of Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) observations reduces RMS fits of SLR observations by 2%–2.4% and those of DORIS observations by 2.6% for Envisat and Jason satellites. Using satellite true attitude instead of models improves Jason-1 SLR RMS fits by 41% from July 2012 until July 2013. The VER11 orbits indicate the mean values of the SLR RMS fits between 1.2 and 2.1 cm for the different missions. The internal orbit consistency in the radial direction is between 0.5 and 1.9 cm. The global mean sea level trend for the period 1993–2014 from TOPEX, Jason-1, and Jason-2 is 2.8 and 3.0 mm/year using GFZ VER6 and VER11 orbits, respectively. Regionally, the decadal trends from GFZ VER11 and external orbits vary in the order of 1 mm/year.

Beschreibung: There are a large number of geophysical processes affecting sea level dynamics and coastal erosion in the Baltic Sea region. These processes operate on a large range of spatial and temporal scales and are observed in many other coastal regions worldwide. This, along with the outstanding number of long data records, makes the Baltic Sea a unique laboratory for advancing our knowledge on interactions between processes steering sea level and erosion in a climate change context. Processes contributing to sea level dynamics and coastal erosion in the Baltic Sea include the still ongoing viscoelastic response of the Earth to the last deglaciation, contributions from global and North Atlantic mean sea level changes, or contributions from wind waves affecting erosion and sediment transport along the subsiding southern Baltic Sea coast. Other examples are storm surges, seiches, or meteotsunamis which primarily contribute to sea level extremes. Such processes have undergone considerable variation and change in the past. For example, over approximately the past 50 years, the Baltic absolute (geocentric) mean sea level has risen at a rate slightly larger than the global average. In the northern parts of the Baltic Sea, due to vertical land movements, relative mean sea level has decreased. Sea level extremes are strongly linked to variability and changes in large-scale atmospheric circulation. The patterns and mechanisms contributing to erosion and accretion strongly depend on hydrodynamic conditions and their variability. For large parts of the sedimentary shores of the Baltic Sea, the wave climate and the angle at which the waves approach the nearshore region are the dominant factors, and coastline changes are highly sensitive to even small variations in these driving forces. Consequently, processes contributing to Baltic sea level dynamics and coastline change are expected to vary and to change in the future, leaving their imprint on future Baltic sea level and coastline change and variability. Because of the large number of contributing processes, their relevance for understanding global figures, and the outstanding data availability, global sea level research and research on coastline changes may greatly benefit from research undertaken in the Baltic Sea.