Identifying sensitivities for cirrus modelling using a two-moment two-mode bulk microphysics scheme

Cirrus cloud genesis is an inherently multiscale and non-linear problem. The synoptic scale provides the environment, the mesoscale determines the forcing and the actual nucleation events occur on a microscopic scale. This makes the parameterisation in numerical weather prediction models a challenging task. In order to improve the prediction of cirrus clouds and ice supersaturation formation in the German Weather Service (DWD) model chain, the controlling physical processes are investigated and parameterised in a new cloud ice microphysics scheme

Detecting instruction effects. Deciding between covariance analytical and change-score approach

The article focuses on estimating effects in nonrandomized studies with two outcome measurement occasions and one predictor variable. Given such a design, the analysis approach can be to include the measurement at the previous time point as a predictor in the regression model (ANCOVA), or to predict the change-score of the outcome variable (CHANGE). Researchers demonstrated that both approaches can result in different conclusions regarding the reported effect. Current recommendations on when to apply which approach are, in part, contradictory. In addition, they lack direct reference to the educational and instructional research contexts, since they do not consider latent variable models in which variables are measured without measurement error. This contribution assists researchers in making decisions regarding their analysis model. Using an underlying hypothetical data-generating model, we identify for which kind of data-generating scenario (i.e., under which assumptions) the defined true effect equals the estimated regression coefficients of the ANCOVA and the CHANGE approach. We give empirical examples from instructional research and discuss which approach is more appropriate, respectively. (DIPF/Orig.

Evaluation of Item Response Theory Models for Nonignorable Omissions

When competence tests are administered, subjects frequently omit items. These missing responses pose a threat to correctly estimating the proficiency level. Newer model-based approaches aim to take nonignorable missing data processes into account by incorporating a latent missing propensity into the measurement model. Two assumptions are typically made when using these models: (1) The missing propensity is unidimensional and (2) the missing propensity and the ability are bivariate normally distributed. These assumptions may, however, be violated in real data sets and could, thus, pose a threat to the validity of this approach. The present study focuses on modeling competencies in various domains, using data from a school sample (N = 15,396) and an adult sample (N = 7,256) from the National Educational Panel Study. Our interest was to investigate whether violations of unidimensionality and the normal distribution assumption severely affect the performance of the model-based approach in terms of differences in ability estimates. We propose a model with a competence dimension, a unidimensional missing propensity and a distributional assumption more flexible than a multivariate normal. Using this model for ability estimation results in different ability estimates compared with a model ignoring missing responses. Implications for ability estimation in large-scale assessments are discussed

Nukleation von Wolkeneis und atmosphärische Eisübersättigung in numerischen Wettervorhersagemodellen

Cirrus cloud genesis is a multiscale problem. This makes the parameterization in numerical weather prediction models a challenging task. In order to improve the prediction of cirrus clouds and ice supersaturation formation in the German Weather Service (DWD) model chain, the controlling physical processes are investigated and parameterised in a new cloud ice microphysics scheme. Scale dependencies of the ice microphysical scheme were assessed by conducting simulations with an idealised and realistic regional Consortium for Small-Scale Modeling (COSMO) model setup and a global model (GME). The developed two-moment two-mode cloud ice scheme includes state-of-the-art parameterisations for the two main ice creating processes, homogeneous and heterogeneous nucleation. Homogeneous freezing of supercooled liquid aerosols is triggered in regions with high atmospheric ice supersaturations (145-160 %) and high cooling rates. Heterogeneous nucleation depends mostly on the existence of sufficient ice nuclei in the atmosphere and occurs at lower ice supersaturations. The larger heterogeneously nucleated ice crystals can deplete ice supersaturation and inhibit subsequent homogenenous freezing. In order to avoid an overestimation of heterogeneous nucleation, cloud ice sedimentation and a prognostic budget variable for activated ice nuclei are introduced. A consistent treatment of the depositional growth of the two ice particle modes and the larger snowflakes using a relaxation timescale method was applied which ensures a physical representation for depleting ice supersaturation. Comparisons between the operational and the new cloud ice microphysics scheme in the GME revealed that the location of cirrus clouds is dominated by the model dynamics whereas the cirrus cloud structures strongly differed for the different schemes. Especially a reduction in the ice water content between 9 and 11 km was observed when using the new cloud ice scheme. This change is an improvement as demonstrated by a comparison with the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) ice water content product. Further comparisons of the GME with the Integrated Forecast System (IFS) model of the European Centre for Medium-Range Weather Forecasts (ECMWF) show a clear improvement of the ice supersaturation distribution with the new two-moment cloud ice scheme. In-cloud ice supersaturation is correctly captured, which is compliant with in-situ measurements. This is a more physical description then in the IFS model, where in-cloud ice saturation is assumed.Die Entstehung von Zirren geschieht auf mehreren Skalen, was eine Herausforderung für die Parametrisierung in Numerischen Wettervorhersagemodellen darstellt. Um die Vorhersage von Zirren und Eisübersättigung in der Modellkette des Deutschen Wetterdienstes (DWD) zu verbessern, werden die kontrollierenden mikrophysikalischen Prozesse untersucht und in einem neuen Wolkeneismikrophysikschema parametrisiert. Die Skalenabhängigkeit des Eismikrophysikschemas wird anhand von idealisierten, sowie reellen Modelläufen mit dem Regionalmodell (COSMO) und dem Globalmodell (GME) ermittelt. Die Entwicklung des 2-Momenten 2-Moden Wolkeneisschemas beinhaltet neuartige Parametrisierungen der zwei Hauptentstehungsprozesse von Wolkeneispartikeln, homogenes und heterogenes Gefrieren. Homogene Nukleation von flüssigen Aerosolen wird in Regionen mit hohen atmosphärischen Eisübersättigungen (145-160 %) und hohen Kühlraten ausgelöst. Heterogenes Gefrieren ist abhängig von der Existenz von Eiskernen und erfolgt bereits bei niedrigen Eisübersättigungen. Die größeren heterogen gefrorenen Eispartikel können eine vorhandene Eisübersättigung abbauen und somit das Einsetzen von homogener Nukleation verhindern. Um eine Überschätzung von heterogen nukleirtem Eis zu verhindern, wurden Wolkeneissedimentation und eine prognostische Bilanzgleichung für aktivierte Eiskerne eingeführt. Eine Relaxations-Zeitskalen-Methode für das Depositionswachstum der 2-Eismoden und der größeren Schneeflocken erlaubt eine konsistente Behandlung für den Abbau der Eisübersättigung. Ein Vergleich zwischen dem GME unter Verwendung des operationellen und dem neuen Wolkeneisnukleationsschema zeigte, dass die Entstehungsposition der Zirren von der Dynamik des Modells dominiert wird und gleich bleibt, während die innere Struktur der Eiswolken sich stark unterscheidet. Insbesondere wurde eine Verringerung des Eiswassergehaltes zwischen 9 und 11 km beobachtet. Dies stellt gemäß Auswertungen mit dem Wolkeneiswasser Produkt des CALIPSO(Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations), eine Verbesserung gegenüber dem operationellen Schema dar. Weitere Vergleiche mit dem IFS (Integrated Forecast System) Modell des europäischen Zentrums für mittelfristige Wettervorhersage zeigten klare Verbesserungen hinsichtlich der Verteilung von Eisübersättigung mit dem neuen 2-Momenten Wolkeneisschema. Besonders erlaubt die Verwendung des neuen Schemas auch die Erfassung der Eisübersättigung innerhalb von Wolken, die mit direkten Messungen übereinstimmt. Hingegen dem IFS, dem eine Annahme der Sättigung innerhalb von Wolken zu Grunde liegt, kann somit mit dem neuen Wolkeneisschema eine physikalischere Beschreibung der Eisübersättigung erreicht werden

A semiparametric approach for item response function estimation to detect item misfit

When scaling data using item response theory, valid statements based on the measurement model are only permissible if the model fits the data. Most item fit statistics used to assess the fit between observed item responses and the item responses predicted by the measurement model show significant weaknesses, such as the dependence of fit statistics on sample size and number of items. In order to assess the size of misfit and to thus use the fit statistic as an effect size, dependencies on properties of the data set are undesirable. The present study describes a new approach and empirically tests it for consistency. We developed an estimator of the distance between the predicted item response functions (IRFs) and the true IRFs by semiparametric adaptation of IRFs. For the semiparametric adaptation, the approach of extended basis functions due to Ramsay and Silverman (2005) is used. The IRF is defined as the sum of a linear term and a more flexible term constructed via basis function expansions. The group lasso method is applied as a regularization of the flexible term, and determines whether all parameters of the basis functions are fixed at zero or freely estimated. Thus, the method serves as a selection criterion for items that should be adjusted semiparametrically. The distance between the predicted and semiparametrically adjusted IRF of misfitting items can then be determined by describing the fitting items by the parametric form of the IRF and the misfitting items by the semiparametric approach. In a simulation study, we demonstrated that the proposed method delivers satisfactory results in large samples (i.e., N ≥ 1,000). (DIPF/Orig.

Dental histology of late Miocene hipparionins compared with extant Equus, and its implications for Equidae life history

Hipparionins were a dominant element of the late Miocene faunas of Europe; however, their biology and ecology remain incompletely understood. In this paper, we explore the pace of life history of different-sized hipparionin horses, using dental histology, and compare it with extant equids. In doing so we consider (i) the size diversity of hipparionins, (ii) their generally smaller size compared to extant equids, and (iii) the allometric coupling between size and life history. In particular, we reconstruct the dental growth in lower first/second molars and in later-formed lower third molars for three hipparionin taxa: two dwarf species (Hipparion periafricanum and H. gromovae), and a larger species (H. concudense). We also analyze dental growth in an extant zebra (Equus quagga) for comparative purposes. Our results reveal that, within each species, there are differences in enamel growth parameters between the first/second molars and third molars. These results illustrate the differences in the developmental timing of these teeth and the existence of a relationship between dental growth parameters with somatic growth. We also find that hipparionin teeth grow at slower rates and tend to erupt later in time than in extant Equus. Dwarf hipparionins, moreover, exhibit lower enamel extension rates than the larger species, but similar formation and eruption times. Considering the link between dental development and life history, these results suggest a slower pace of growth of selected hipparionins compared to extant equids, and a further slower life history than expected for their size in the two dwarf forms

The role of relatedness in the motivation and vitality of university students in online classes during social distancing

As part of the social distancing measures for preventing the spread of COVID-19, many university courses were moved online. There is an assumption that online teaching limits opportunities for fostering interpersonal relationships and students’ satisfaction of the basic need for relatedness – reflected by experiencing meaningful interpersonal connections and belonging – which are considered important prerequisites for student motivation and vitality. In educational settings, an important factor affecting students’ relatedness satisfaction is the teachers’ behavior. Although research suggests that relatedness satisfaction may be impaired in online education settings, to date no study has assessed how university lecturers’ relatedness support might be associated with student relatedness satisfaction and therefore, student motivation and vitality. This study tested this mediating relationship using data collected during the early days of the COVID-19 pandemic. The study also investigated whether the relations were moderated by a high affiliation motive which reflects a dispositional wish for positive and warm relationships. The possible importance of the communication channel selected by the lecturers (video chat yes/no) and the format of a class (lecture/seminar) were also investigated. In a sample of N = 337 students, we tested our hypotheses using structural equation model (SEM). Results confirmed mediation, but not moderation. The use of video chat (video call) seems to facilitate the provision of relatedness support but our data did not show that the format of a class was associated with relatedness. Our findings indicate that both teaching behavior and the technical format used to deliver lectures play important roles in student experiences with online classes. The results are discussed in light of other research conducted during the pandemic. (DIPF/Orig.

Wie digital ist die Berufsschule?: Eine Analyse anhand von Online-Berichtsheften

Das BMBF-Forschungsprojekt DiBBLok1 untersucht Gelingensbedingungen des Einsatzes von digitalen Medien in Lernorten der beruflichen Bildung. Der Lernort Berufsschule wird dabei in Hinblick auf seinen Anteil an der Lernortkooperation untersucht. In diesem Beitrag wird am Beispiel des Online-Berichtshefts BLok (Online-Berichtsheft zur Stärkung der Lernortkooperation) der Frage nachgegangen, welche Berufsschulen dieses Tool deutschlandweit bereits einsetzen, in welchem Umfang dies geschieht und welche Faktoren dabei einflussgebend sind. Entsprechende quantitative Daten wurden im Rahmen des Projekts DiBBLok nach rund zehn Jahren Praxiseinsatz von BLok erstmalig erhoben. Sie geben Aufschluss über den aktuellen Stand der Strukturdaten in Bezug auf den Standort der Berufsschule, den Umfang an angemeldeten Berufsschulehrenden und Auszubildenden sowie der Verbreitung über die Jahre hinweg. Eine quantitative Analyse der Nutzungsweisen wird im Projekt noch folgen.[... aus der Zusammenfassung

Insular giant leporid matured later than predicted by scaling

The island syndrome describes morphological, behavioral, and life history traits that evolve in parallel in endemic insular organisms. A basic axiom of the island syndrome is that insular endemics slow down their pace of life. Although this is already confirmed for insular dwarfs, a slow life history in giants may not be adaptive, but merely a consequence of increasing body size.We tested this question in the fossil insular giant leporid Nuralagus rex. Using bone histology, we constructed both a continental extant taxon model derived from experimentally fluorochrome-labeled Lepus europaeus to calibrate life history events, and a growth model for the insular taxon. N. rex grew extremely slowly and delayed maturity well beyond predictions from continental phylogenetically corrected scaling models. Our results support the life history axiom of the island syndrome as generality for insular mammals, regardless of whether they have evolved into dwarfs or giants

Palaeohistology reveals a slow pace of life for the dwarfed Sicilian elephant

Altres ajuts: CERCA Programme/Generalitat de CatalunyaThe 1-m-tall dwarf elephant Palaeoloxodon falconeri from the Pleistocene of Sicily (Italy) is an extreme example of insular dwarfism and epitomizes the Island Rule. Based on scaling of life-history (LH) traits with body mass, P. falconeri is widely considered to be 'r-selected' by truncation of the growth period, associated with an early onset of reproduction and an abbreviated lifespan. These conjectures are, however, at odds with predictions from LH models for adaptive shifts in body size on islands. To settle the LH strategy of P. falconeri, we used bone, molar, and tusk histology to infer growth rates, age at first reproduction, and longevity. Our results from all approaches are congruent and provide evidence that the insular dwarf elephant grew at very slow rates over an extended period; attained maturity at the age of 15 years; and had a minimum lifespan of 68 years. This surpasses not only the values predicted from body mass but even those of both its giant sister taxon (P. antiquus) and its large mainland cousin (L. africana). The suite of LH traits of P. falconeri is consistent with the LH data hitherto inferred for other dwarfed insular mammals. P. falconeri, thus, not only epitomizes the Island Rule but it can also be viewed as a paradigm of evolutionary change towards a slow LH that accompanies the process of dwarfing in insular mammals