The 2008 DGFI Realization of the ITRS: DTRF2008 (data)

The DTRF2008 is a realization of the International Terrestrial Reference System ITRS. The DTRF2008 consists of station positions and velocities of global distributed observing stations of the space geodetic observation techniques VLBI, SLR, GPS and DORIS. The DTRF2008 was released in May 2010 and includes the observation data of the techniques up to and including 2008. The observation data are processed and submitted by the corresponding international services: IGS (International GNSS Service, http://igscb.jpl.nasa.gov) IVS (International VLBI Service, http://ivscc.gsfc.nasa.gov) ILRS (International Laser Ranging Service, http://ilrs.gsfc.nasa.gov) IDS (International DORIS Service, http://ids-doris.org). The DTRF2008 is an independent ITRS realization, which is computed on the basis of the same input data as the ITRF2008 (IGN, Paris). Both realizations differ with respect to their computation strategies: while the ITRF2008 is based on the combination of solutions, the DTRF2008 is computed by the combination of normal equations. The DTRF2008 comprises the coordinates of 559 GPS-, 106 VLBI-, 122 SLR- and 132 DORIS-stations. The reference epoch is 1.1.2005, 0h UTC. The Earth Orientation Parameters (EOP) - that means the coordinates of the terrestrial and the celestial pole, UT1-UTC and the Length of Day (LOD) - were simultaneously estimated with the station coordinates. The EOP time series cover the period of 1983 to 2008. The station names are the official IERS indications: cdp numbers or 4-character IDs and DOMES numbers (http://itrf.ensg.ign.fr/doc_ITRF/iers_sta_list.txt). The solution is available in different file formats (SINEX and SSC), see below. A detailed description of the solution is given by Seitz M. et al. (2012). The results of a comparison of DTRF2008 and ITRF2008 is given by Seitz M. et al. (2013). More information as well as residual time series of the station positions can be made available by request.

Shoreline change on nine reef islands over a seven-decade period

Atoll islands are subject to a variety of processes that influence their geomorphological development. Analysis of historical shoreline changes using remotely sensed images has become an efficient approach to both quantify past changes and estimate future island response. However, the detection of long-term changes in beach width is challenging mainly for two reasons: first, data availability is limited for many remote Pacific islands. Second, beach environments are highly dynamic and strongly influenced by seasonal or episodic shoreline oscillations. Consequently, remote-sensing studies on beach morphodynamics of atoll islands deal with dynamic features covered by a low sampling frequency. Here we present a study of beach dynamics for nine islands on Takú Atoll, Papua New Guinea, over a seven-decade period. A considerable chronological gap between aerial photographs and satellite images was addressed by applying a new method that reweighted positions of the beach limit by identifying "outlier" shoreline positions. On top of natural beach variability observed along the reweighted beach sections, we found that one third of the analyzed islands show a statistically significant decrease in reweighted beach width since 1943. The total loss of beach area for all islands corresponds to 44% of the initial beach area. Variable shoreline trajectories suggest that changes in beach width on Takú Atoll are dependent on local control (that is, human activity and longshore sediment transport). Our results show that remote imagery with a low sampling frequency may be sufficient to characterize prominent morphological changes in planform beach configuration of reef islands.

Mass balance and acceleration of the Greenland ice sheet

Within the last decade, the Greenland ice sheet (GrIS) and its surroundings have experienced record high surface temperatures (Mote, 2007, doi:10.1029/2007GL031976; Box et al., 2010), ice sheet melt extent (Fettweis et al., 2011, doi:10.5194/tc-5-359-2011) and record-low summer sea-ice extent (Nghiem et al., 2007, doi:10.1029/2007GL031138). Using three independent data sets, we derive, for the first time, consistent ice-mass trends and temporal variations within seven major drainage basins from gravity fields from the Gravity Recovery and Climate Experiment (GRACE; Tapley et al., 2004, doi:10.1029/2004GL019920), surface-ice velocities from Inteferometric Synthetic Aperture Radar (InSAR; Rignot and Kanagaratnam, 2006, doi:10.1126/science.1121381) together with output of the regional atmospheric climate modelling (RACMO2/ GR; Ettema et al., 2009, doi:10.1029/2009GL038110), and surface-elevation changes from the Ice, cloud and land elevation satellite (ICESat; Sorensen et al., 2011, doi:10.5194/tc-5-173-2011). We show that changing ice discharge (D), surface melting and subsequent run-off (M/R) and precipitation (P) all contribute, in a complex and regionally variable interplay, to the increasingly negative mass balance of the GrIS observed within the last decade. Interannual variability in P along the northwest and west coasts of the GrIS largely explains the apparent regional mass loss increase during 2002-2010, and obscures increasing M/R and D since the 1990s. In winter 2002/2003 and 2008/2009, accumulation anomalies in the east and southeast temporarily outweighed the losses by M/R and D that prevailed during 2003-2008, and after summer 2010. Overall, for all basins of the GrIS, the decadal variability of anomalies in P, M/R and D between 1958 and 2010 (w.r.t. 1961-1990) was significantly exceeded by the regional trends observed during the GRACE period (2002-2011).

Analysis of temporal microbial properties from experimental plots of the Jena experiment (2003-2014)

The study was carried out on the main plots (Main Experiment) of a large grassland biodiversity experiment, the Jena Experiment. In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. This data set consists of standard deviation (SD), mean and stability (stab) of soil microbial basal respiration (µl O2/h/g dry soil) and microbial biomass carbon (µg C/g dry soil). Data were derived by taking soil samples and measuring basal and substrate-induced microbial respiration with an oxygen-consumption apparatus. Samples for calculating the temporal stability were taken every year in May/June from 2003 to 2014, except in 2005. Oxygen consumption of soil microorganisms in fresh soil equivalent to 3.5 g dry weight was measured at 22°C over a period of 24 h. Basal respiration (µlO2/g dry soil/h) was calculated as mean of the oxygen consumption rates of hours 14 to 24 after the start of measurements. Substrate- induced respiration was determined by adding D-glucose to saturate catabolic enzymes of microorganisms according to preliminary studies (4 mg g-1 dry soil solved in 400 µl deionized water). Maximum initial respiratory response (µl O2/g dry soil/h) was calculated as mean of the lowest three oxygen consumption values within the first 10 h after glucose addition. Microbial biomass carbon (µg C/g dry soil) was calculated as 38 × Maximum initial respiratory response according to prelimiray studies.