The Herschel-PACS photometer calibration

This paper provides an overview of the PACS photometer flux calibration concept, in particular for the principal observation mode, the scan map. The absolute flux calibration is tied to the photospheric models of five fiducial stellar standards (α Boo, α Cet, α Tau, β And, γ Dra). The data processing steps to arrive at a consistent and homogeneous calibration are outlined. In the current state the relative photometric accuracy is ～2 % in all bands. Starting from the present calibration status, the characterization and correction for instrumental effects affecting the relative calibration accuracy is described and an outlook for the final achievable calibration numbers is given. After including all the correction for the instrumental effects, the relative photometric calibration accuracy (repeatability) will be as good as 0.5 % in the blue and green band and 2 % in the red band. This excellent calibration starts to reveal possible inconsistencies between the models of the K-type and the M-type stellar calibrators. The absolute calibration accuracy is therefore mainly limited by the 5 % uncertainty of the celestial standard models in all three bands. The PACS bolometer response was extremely stable over the entire Herschel mission and a single, time-independent response calibration file is sufficient for the processing and calibration of the science observations. The dedicated measurements of the internal calibration sources were needed only to characterize secondary effects. No aging effects of the bolometer or the filters have been found. Also, we found no signs of filter leaks. The PACS photometric system is very well characterized with a constant energy spectrum νF _ν = λF _λ = const as a reference. Colour corrections for a wide range of sources SEDs are determined and tabulated.     

Sensitivity of simulated temperature,precipitation, and global radiation to different WRF configurations over the Carpathian Basin for regional climate applications

In this study, the Weather Research and Forecasting (WRF) model is used to produce short-term regional climate simulations with several configurations for the Carpathian Basin region. The goal is to evaluate the performance of the model and analyze its sensitivity to different physical and dynamical settings, and input data. Fifteen experiments were conducted with WRF at 10 km resolution for the year 2013. The simulations differ in terms of configuration options such as the parameterization schemes, the hydrostatic and non-hydrostatic dynamical cores, the initial and boundary conditions (ERA5 and ERA-Interim reanalyses), the number of vertical levels, and the length of the spin-up period. E-OBS dataset 2 m temperature, total precipitation, and global radiation are used for validation. Temperature underestimation reaches 4–7 °C for some experiments and can be reduced by certain physics scheme combinations. The cold bias in winter and spring is mainly caused by excessive snowfall and too persistent snow cover, as revealed by comparison with satellite-based observations and a test simulation without snow on the surface. Annual precipitation is overestimated by 0.6–3.8 mm day⁻¹, with biases mainly accumulating in the period driven by large-scale weather processes. Downward shortwave radiation is underestimated all year except in the months dominated by locally forced phenomena (May to August) when a positive bias prevails. The incorporation of downward shortwave radiation to the validation variables increased the understanding of underlying problems with the parameterization schemes and highlighted false model error compensations.

     

Robust and fast reconstruction of complex roofs with active sampling from 3D point clouds

This article proposes a novel method for the 3D reconstruction of LoD2 buildings from LiDAR data. We propose an active sampling strategy which applies a cascade of filters focusing on promising samples at an early stage, thus avoiding the pitfalls of RANSAC‐based approaches. Filters are based on prior knowledge represented by (nonparametric) density distributions. In our approach samples are pairs of surflets—3D points together with normal vectors derived from a plane approximation of their neighborhood. Surflet pairs provide parameters for model candidates such as azimuth, inclination and ridge height, as well as parameters estimating internal precision and consistency. This provides a ranking of roof model candidates and leads to a small number of promising hypotheses. Building footprints are derived in a preprocessing step using machine learning methods, in particular support vector machines.     

Alteration and chemical U-Th-total Pb dating of heterogeneous high-uranium zircon from a pegmatite from the Aduiskii massif,middle Urals,Russia

Mineralogy and Petrology - The U-Th-Pb isotope system in the accessory mineral zircon may be disturbed, as for instance by the secondary loss of radiogenic lead. The recognition of such alteration...     

Exploring the application of a flood risk management Serious Game platform

Based on the experience gained with SeCom2.0, we will explain the impact of game-based learning and provide an overview of the current use of Serious Games in teaching flood risk management in Germany. SeCom2.0 is a collaborative learning platform, which deals with a flood situation in Cologne. The use of Serious Games in flood risk management is still limited due to many factors. The article will give a deeper insight into the SeCom2.0 project, explaining the pedagogical design and the development. We will cover the pitfalls and possible suggestions for further development to facilitate wider use of such games by adapting the settings to local conditions. This article will also describe how a Serious Game can support lifelong learning for students and employees involved in flood risk management. The key components, design patterns and structure of or SeCom2.0 are described, along with ideas to implement selected topics in flood risk management in an engaging gaming environment.     

Air-sea fluxes: 25 years of progress

During the past quarter century the study of air-sea interaction has evolved from a small branch of marine climatology to play a key role in the modelling of the coupled system of ocean and atmosphere. Knowledge of air- sea fluxes has grown, based on Monin-Obukhov similarity theory for surface boundary layers and on direct and indirect techniques of measuring the fluxes. This has been the basis for providing boundary conditions needed to couple atmospheric and oceanic circulation models that are used to forecast weather and climate. An overview of current understanding is followed by a discussion of parameterisation schemes and a chronicle of some of the experimental work that has tested theories and quantified their conclusions.     

Sea surface wind stress and drag coefficients: The hexos results

Turbulent fluxes have been measured in the atmospheric surface layer from a boom extending upwind from the Dutch offshore research platform Meetpost Noordwijk (MPN) during HEXMAX (Humidity Exchange over the Sea Main Experiment) in October–November, 1986. We started out to study eddy flux of water vapour, but discrepancies among simultaneous measurements made with three different anemometers led us to develop methods to correct eddy correlation measurements of wind stress for flow distortion by nearby objects. We then found excellent agreement among the corrected wind stress data sets from the three anemometers on the MPN boom and with eddy correlation measurements from a mast on a tripod. Inertial-dissipation techniques gave reliable estimates of wind stress from turbulence spectra, both at MPN and at a nearby ship. The data cover a range of wave ages and the results yield new insights into the variation of sea surface wind stress with sea state; two alternative formulas are given for the nondimensional surface roughness as a function of wave age.     

Addressing sources of uncertainty in runoff projections for a data scarce catchment in the Ecuadorian Andes

Future climate projections from general circulation models (GCMs) predict an acceleration of the global hydrological cycle throughout the 21st century in response to human-induced rise in temperatures. However, projections of GCMs are too coarse in resolution to be used in local studies of climate change impacts. To cope with this problem, downscaling methods have been developed that transform climate projections into high resolution datasets to drive impact models such as rainfall-runoff models. Generally, the range of changes simulated by different GCMs is considered to be the major source of variability in the results of such studies. However, the cascade of uncertainty in runoff projections is further elongated by differences between impact models, especially where robust calibration is hampered by the scarcity of data. Here, we address the relative importance of these different sources of uncertainty in a poorly monitored headwater catchment of the Ecuadorian Andes. Therefore, we force 7 hydrological models with downscaled outputs of 8 GCMs driven by the A1B and A2 emission scenarios over the 21st century. Results indicate a likely increase in annual runoff by 2100 with a large variability between the different combinations of a climate model with a hydrological model. Differences between GCM projections introduce a gradually increasing relative uncertainty throughout the 21st century. Meanwhile, structural differences between applied hydrological models still contribute to a third of the total uncertainty in late 21st century runoff projections and differences between the two emission scenarios are marginal.