AGB Phase Transition in Globular Clusters: A Tool for Dating Starbursts

A new method to detect and study young star clusters is presented. This is based on the knowledge that the light of stellar populations with ages between ∼ 200 Myr and ∼ 1/2 Gyr is dominated by very red, bright AGB stars. Star clusters undergoing this so-called ‘AGB phase transition’ are featured by very red V-K colours, like those of Magellanic Clouds clusters, while optical colours like B-V remain blue typical for young populations. The best channel for detecting star clusters in this age range is therefore the near IR. From the theoretical side, SSP models including properly the contribution of the bright AGB are required (Maraston, 1998). Using this strategy, we succesfully detected the AGB phase transition among the clusters of the merger remnant galaxy NGC 7252 (see Maraston etal., 2001). This revised version was published online in September 2006 with corrections to the Cover Date.     

A New SPT-Based Method for Estimating Axial Capacity of Driven Piles in Glacial Deposits

Geotechnical and Geological Engineering - This paper proposes a new design method for the axial capacity of driven piles in glacial deposits with the standard penetration test (SPT) based on a...     

C‐band SAR backscatter characteristics of Arctic sea and land ice during winter

Abstract

Synthetic Aperture Radar (SAR) data has become an important tool for studies of polar regions, due to high spatial resolution even during the polar night and under cloudy skies. We have studied the temporal variation of sea and land ice backscatter of twenty‐four SAR images from the European Remote Sensing satellite (ERS‐1) covering an area in Lady Ann Strait and Jones Sound, Nunavut, from January to March 1992. The presence of fast ice in Jones Sound and glaciers and ice caps on the surrounding islands provides an ideal setting for temporal backscatter studies of ice surfaces. Sample regions for eight different ice types were selected and the temporal backscatter variation was studied. The observed backscatter values for each ice type characterize the radar signatures of the ice surfaces. This time series of twenty‐four SAR images over a 3‐month period provides new insights into the degree of temporal variability of each surface. Ice caps exhibit the highest backscatter value of ‐3.9 dB with high temporal variability. Valley glacier ice backscatter values decrease with decreasing altitude, and are temporally the most stable, with standard deviations of 0.08–0.10 dB over the 90‐day period.

First‐year ice and lead ice show a negative trend in backscatter values in time and a positive correlation of up to 0.59 with air temperature over the 90‐day period. For first‐year ice and lead ice, episodes of large temperature fluctuations (±12°C) are associated with rapid changes in backscatter values (±2 dB). We attribute the backscatter increase to a temperature‐induced increase in brine volume at the base of the snow pack. Multi‐year ice, conglomerate ice and shore ice are relatively stable over the 3‐month period, with a backscatter variation of only a few dBs. An observed lag time of up to three days between backscatter increase/decrease and air temperature can be attributed to the insulation effect of the snow cover over sea ice. The net range of the backscatter values observed on the most temporally stable surface, valley glacier ice, of about 0.30 dB indicates that the ERS‐1 SAR instrument exceeds the 1 dB calibration accuracy specified for the Alaska SAR Facility processor for the three winter months.     

Projected climate change impact on Baltic Sea cyanobacteria

Compared to other phytoplankton groups, nitrogen-fixing cyanobacteria generally prefer high water temperatures for growth and are therefore expected to benefit from global warming. We use a coupled biological-physical model with an advanced cyanobacteria life cycle model to compare the abundance of cyanobacteria in the Baltic Sea during two different time periods (1969–1998; 2069–2098). For the latter, we find prolonged growth and a more than twofold increase in the climatologically (30 years) averaged cyanobacteria biomass and nitrogen fixation. Additional sensitivity experiments indicate that the biological-physical feedback mechanism through light absorption becomes more important with global warming. In general, we find a nonlinear response of cyanobacteria to changes in the atmospheric forcing fields as a result of life-cycle related feedback mechanisms. Overall, the sensitivity of the cyanobacteria-driven system suggests that biological-physical and life-cycle related feedback mechanisms are important and must therefore be included in future projection studies.     

The Compatibility of Flare Temperatures Observed with AIA,GOES, and RHESSI

We test the compatibility and biases of multi-thermal flare DEM (differential emission measure) peak temperatures determined with AIA with those determined by GOES and RHESSI using the isothermal assumption. In a set of 149 M- and X-class flares observed during the first two years of the SDO mission, AIA finds DEM peak temperatures at the time of the peak GOES 1?–?8 Å flux to have an average of T _p=12.0±2.9 MK and Gaussian DEM widths of log₁₀(σ _T )=0.50±0.13. From GOES observations of the same 149 events, a mean temperature of T _p=15.6±2.4 MK is inferred, which is systematically higher by a factor of T _GOES/T _AIA=1.4±0.4. We demonstrate that this discrepancy results from the isothermal assumption in the inversion of the GOES filter ratio. From isothermal fits to photon spectra at energies of ?≈6?–?12 keV of 61 of these events, RHESSI finds the temperature to be higher still by a factor of T _RHESSI/T _AIA=1.9±1.0. We find that this is partly a consequence of the isothermal assumption. However, RHESSI is not sensitive to the low-temperature range of the DEM peak, and thus RHESSI samples only the high-temperature tail of the DEM function. This can also contribute to the discrepancy between AIA and RHESSI temperatures. The higher flare temperatures found by GOES and RHESSI imply correspondingly lower emission measures. We conclude that self-consistent flare DEM temperatures and emission measures require simultaneous fitting of EUV (AIA) and soft X-ray (GOES and RHESSI) fluxes.