Shells of Paphia undulata (Bivalvia) from the South China Sea as potential proxy archives of the East Asian summer monsoon: a sclerochronological calibration study

The climate of the South China Sea is dominated by the East Asian monsoon (EAM) system. Existing paleoclimate reconstructions offered an excellent insight into longer-term EAM variations. However, due to a lack of appropriate high-resolution paleoclimate data, relatively little is known about the frequency and strength of EAM extremes during the Holocene. To evaluate and establish a potential proxy archive for past variations of the EAM on shorter time-scales, we have carried out a calibration study on shells of the bivalve mollusk, Paphia undulata (Born 1778) from Daya Bay, China. This species has a short lifespan (3 years). Shells grow uninterruptedly between February/March and mid-November and are formed near oxygen isotopic (δ¹⁸O) equilibrium with the ambient environment. Shell growth patterns, δ¹⁸O_shell and δ¹³C_shell values, can be used to estimate the relative amount of precipitation and terrestrial runoff. Therefore, shells of this species can provide reliable, sub-seasonally resolved data on past East Asian summer monsoon strengths. The feasibility of this method has been tested with two Holocene shells from sediment cores taken from the nearby Beibu Gulf. A rather peculiar finding is that shell growth of P. undulata seems to be largely uncoupled to measured local environmental variables. Growth rates are negatively correlated to seawater temperature and chlorophyll a levels and positively to salinity. It is hypothesized here that extraordinary fast shell growth in early spring (February/March; low temperature and primary productivity) are facilitated by preserved energy resources, ensuring that the bivalve quickly reaches the predation window and the required size for reproduction.     

Single-frequency single-site VTEC retrieval using the NeQuick2 ray tracer for obliquity factor determination

A single-frequency single-site GPS/Galileo algorithm for retrieval of absolute total electron content is implemented. A single-layer approximation of the ionosphere is used for data modeling. In addition to a standard mapping function, the NeQuick model (version 2) of the ionosphere is now applied to derive improved mapping functions. This model is very attractive for this purpose, because it implements a ray tracer. We compare the new algorithm with the old one using an effective global height of the ionosphere of 450 km. Combined IGS IONEX gridded data sets serve as reference data. On global average, we find a small improvement of 1 % in precision (standard deviation) of the NeQuick2 mapping method versus the conventional approach on global average. A site-by-site comparison indicates an improvement in the precision for 34 % of the 44 sites under investigation. The level of improvement for these stations is 0.5 TECU on average. No improvement was observed for 41 % of the sites. Further comparisons of the single (code ranges and carrier phases) versus dual-frequency (carrier phases only) single site algorithm show that dual-frequency VTEC estimation is more accurate for the majority of the stations, but only in the range of 0.3 TECU (2.6 %) in average.     

Using a Sodar to Measure Optical Turbulence and Wind Speed for the Thirty Meter Telescope Site Testing. Part I: Reproducibility

In this two-part study, we investigate the usefulness of Sodars as part of a large instrument suite for the study of high mountains in the site selection process of the Thirty Meter Telescope (TMT). In this first part, we describe the reproducibility of the measurements and the comparability of results from different sites for data taken with two complementary Sodar models: the XFAS and SFAS models manufactured by Scintec Inc. To this end, a cross-calibration campaign was conducted on two of the sites comparing both the wind speeds and the optical turbulence measurements of the different units. The specific set-up conditions and the low atmospheric pressure require us to make a compromise between the amount of data available for statistics and the quality of the data. For the comparison of the wind speed, results from the same models show a systematic difference of 12 and 9% for the XFAS and SFAS, respectively. The scatter between individual measurements, which includes instrumental, set-up and statistical fluctuation contributions, was found to be 21 and 23%. For optical turbulence, the respective values are 6 and 3% for the systematic difference and 46 and 67% for the scatter. These results show that Sodars can be useful tools for astronomical site testing for projects such as the TMT.     

Using a Sodar to Measure Optical Turbulence and Wind Speed for the Thirty Meter Telescope Site Testing. Part II: Comparison with Independent Instruments

In the second part of this study, we compare both the wind speed and turbulence given by the Sodars with independent sets of measurements. In the case of the wind speed we compare the lowest Sodar data bin with a sonic anemometer located on a 7-m tower. The agreement between the two instruments was convincing with a regression slope near unity. The integrated turbulence measurements of the Sodars are compared with those obtained with a combined multi-aperture scintillation sensor and differential image motion monitor (MASS/DIMM) unit. It was found that the Sodars are indeed capable of quantitatively measuring optical turbulence, and agree with the MASS/DIMM measurements with a correlation coefficient of approximately 80% and a regression slope within 10% of unity. Additional acoustic noise in the Sodar data was identified using this comparison and removed from the data.     

Probabilistic assessment of regional climate change in Southwest Germany by ensemble dressing

Since single-integration climate models only provide one possible realization of climate variability, ensembles are a promising way to estimate the uncertainty in climate modeling. A statistical model is presented that extracts information from an ensemble of regional climate simulations to estimate probability distributions of future temperature change in Southwest Germany in the following two decades. The method used here is related to kernel dressing which has been extended to a multivariate approach in order to estimate the temporal autocovariance in the ensemble system. It has been applied to annual and seasonal mean temperatures given by ensembles of the coupled general circulation model ECHAM5/MPI-OM as well as the regional climate simulations using the COSMO-CLM model. The results are interpreted in terms of the bivariate probability density of mean and trend within the period 2011–2030 with respect to 1961–1990. Throughout the study region one can observe an average increase in annual mean temperature of approximately +0.6K and a corresponding trend of +0.15K/20a. While the increase in 20-year mean temperature is virtually certain, the 20-year trend still shows a 20% chance for negative values. This indicates that the natural variability of the climate system, as far as it is reflected by the ensemble system, can produce negative trends even in the presence of longer-term warming. Winter temperatures are clearly more affected and for both quantities we observe a north-to-south pattern where the increase in the very southern part is less intense.     

Detection of surface change in complex topography using terrestrial laser scanning: application to the Illgraben debris‐flow channel

Detection of surface change is a fundamental task in geomorphology. Terrestrial laser scanners are increasingly used for monitoring surface change resulting from a variety of geomorphic processes, as they allow the rapid generation of high‐resolution digital elevation models. Irrespective of instrument specifics, survey design or data processing, such data are subject to a finite level of ambiguity in position measurement, a consideration of which must be taken into account when deriving change. The propagation of errors is crucial in change detection because even very small uncertainties in elevation can produce large uncertainties in volume when extrapolated over an area of interest. In this study we propose a methodology to detect surface change and to quantify the resultant volumetric errors in areas of complex topography such as channels, where data from multiple scan stations must be combined. We find that a commonly proposed source of error – laser point elongation at low incidence angles – has a negligible effect on the quality of the final registered point cloud. Instead, ambiguities in elevation inherent to registered datasets have a strong effect on our ability to detect and measure surface change. Similarly, we find that changes in surface roughness between surveys also reduce our ability to detect change. Explicit consideration of these ambiguities, when propagated through to volume calculations, allows us to detect volume change of 87 ± 5 m³, over an area of ～ ?4900 m², due to passage of a debris flow down a 300 m reach of the Illgraben channel in Switzerland. Copyright © 2011 John Wiley & Sons, Ltd.     

High resolution regional climate model simulations for Germany: part I—validation

A five-member ensemble of regional climate model (RCM) simulations for Europe, with a high resolution nest over Germany, is analysed in a two-part paper: Part I (the current paper) presents the performance of the models for the control period, and Part II presents results for near future climate changes. Two different RCMs, CLM and WRF, were used to dynamically downscale simulations with the ECHAM5 and CCCma3 global climate models (GCMs), as well as the ERA40-reanalysis for validation purposes. Three realisations of ECHAM5 and one with CCCma3 were downscaled with CLM, and additionally one realisation of ECHAM5 with WRF. An approach of double nesting was used, first to an approximately 50 km resolution for entire Europe and then to a domain of approximately 7 km covering Germany and its near surroundings. Comparisons of the fine nest simulations are made to earlier high resolution simulations for the region with the RCM REMO for two ECHAM5 realisations. Biases from the GCMs are generally carried over to the RCMs, which can then reduce or worsen the biases. The bias of the coarse nest is carried over to the fine nest but does not change in amplitude, i.e. the fine nest does not add additional mean bias to the simulations. The spatial pattern of the wet bias over central Europe is similar for all CLM simulations, and leads to a stronger bias in the fine nest simulations compared to that of WRF and REMO. The wet bias in the CLM model is found to be due to a too frequent drizzle, but for higher intensities the distributions are well simulated with both CLM and WRF at the 50 and 7 km resolutions. Also the spatial distributions are close to high resolution gridded observations. The REMO model has low biases in the domain averages over Germany and no drizzle problem, but has a shift in the mean precipitation patterns and a strong overestimation of higher intensities. The GCMs perform well in simulating the intensity distribution of precipitation at their own resolution, but the RCMs add value to the distributions when compared to observations at the fine nest resolution.     

Alpine snow cover in a changing climate: a regional climate model perspective

An analysis is presented of an ensemble of regional climate model (RCM) experiments from the ENSEMBLES project in terms of mean winter snow water equivalent (SWE), the seasonal evolution of snow cover, and the duration of the continuous snow cover season in the European Alps. Two sets of simulations are considered, one driven by GCMs assuming the SRES A1B greenhouse gas scenario for the period 1951–2099, and the other by the ERA-40 reanalysis for the recent past. The simulated SWE for Switzerland for the winters 1971–2000 is validated against an observational data set derived from daily snow depth measurements. Model validation shows that the RCMs are capable of simulating the general spatial and seasonal variability of Alpine snow cover, but generally underestimate snow at elevations below 1,000 m and overestimate snow above 1,500 m. Model biases in snow cover can partly be related to biases in the atmospheric forcing. The analysis of climate projections for the twenty first century reveals high inter-model agreement on the following points: The strongest relative reduction in winter mean SWE is found below 1,500 m, amounting to 40–80 % by mid century relative to 1971–2000 and depending upon the model considered. At these elevations, mean winter temperatures are close to the melting point. At higher elevations the decrease of mean winter SWE is less pronounced but still a robust feature. For instance, at elevations of 2,000–2,500 m, SWE reductions amount to 10–60 % by mid century and to 30–80 % by the end of the century. The duration of the continuous snow cover season shows an asymmetric reduction with strongest shortening in springtime when ablation is the dominant factor for changes in SWE. We also find a substantial ensemble-mean reduction of snow reliability relevant to winter tourism at elevations below about 1,800 m by mid century, and at elevations below about 2,000 m by the end of the century.     

Evidence for the 22-year-cycle in the longitudinal distribution of sunspots

It was shown in an earlier paper that preferred hemispheres of solar activity alternate with the 22-year magnetic cycle, when analyzed in the 27.0 day Bartels rotation. Using data which cover the time between 1818 and 1983 we trace back this result to 1880 (cycle 12). Before 1880 no significant correlations are found.