Hans Ertel Center for Weather Research

Hamburg, Germany

Hans Ertel Center for Weather Research

Hamburg, Germany
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Naumann A.K.,Max Planck Institute for Meteorology | Seifert A.,Hans Ertel Center for Weather Research
Journal of the Atmospheric Sciences | Year: 2016

In this paper, the evolution of the raindrop size distribution (RSD) is investigated for two isolated shallow cumulus clouds that are modeled with large-eddy simulations. For a two-moment bulk rain microphysics scheme that assumes the RSD to follow a gamma distribution, it is shown that the evolution of the rainwater content of an individual shallow cumulus cloud-in particular, its subcloud-layer rainwater amount and its surface precipitation rate-is highly sensitive to the choice of the shape parameter of the gamma distribution. To further investigate the shape of the RSD, a Lagrangian drop model is used to represent warm rain microphysics without a priori assumptions on the RSD. It is found that the shape parameter is highly variable in space and time and that existing closure equations, which are established from idealized studies of more heavily precipitating cases, are not appropriate for shallow cumulus. Although a relation of the shape parameter to the mean raindrop diameter is also found for individual shallow cumulus clouds, this relation differs already for the two clouds considered. It is therefore doubtful whether a two-moment scheme with a diagnostic parameterization of the shape parameter (i.e., a local closure in space and time) can be sufficient, especially when being applied across different cloud regimes. A three-moment bulk rain microphysics scheme is able to capture the general development of the relation of the shape parameter to the mean raindrop diameter for the two simulated clouds but misses some relevant features. © 2016 American Meteorological Society.

Seifert A.,Hans Ertel Center for Weather Research | Heus T.,Max Planck Institute for Meteorology
Atmospheric Chemistry and Physics | Year: 2013

Trade wind cumulus clouds often organize in along-wind cloud streets and across-wind mesoscale arcs. We present a benchmark large-eddy simulation which resolves the individual clouds as well as the mesoscale organization on scales of O(10 km). Different methods to quantify organization of cloud fields are applied and discussed. Using perturbed physics large-eddy simulation experiments, the processes leading to the formation of cloud clusters and the mesoscale arcs are revealed. We find that both cold pools as well as the sub-cloud layer moisture field are crucial to understand the organization of precipitating shallow convection. Further sensitivity studies show that microphysical assumptions can have a pronounced impact on the onset of cloud organization. © 2013 Author(s).

Naumann A.K.,Max Planck Institute for Meteorology | Seifert A.,Hans Ertel Center for Weather Research | Mellado J.P.,Max Planck Institute for Meteorology
Geoscientific Model Development | Year: 2013

We introduce a probability density function (PDF)-based scheme to parameterize cloud fraction, average liquid water and liquid water flux in large-scale models, that is developed from and tested against large-eddy simulations and observational data. Because the tails of the PDFs are crucial for an appropriate parameterization of cloud properties, we use a double-Gaussian distribution that is able to represent the observed, skewed PDFs properly. Introducing two closure equations, the resulting parameterization relies on the first three moments of the subgrid variability of temperature and moisture as input parameters. The parameterization is found to be superior to a single-Gaussian approach in diagnosing the cloud fraction and average liquid water profiles. A priori testing also suggests improved accuracy compared to existing double-Gaussian closures. Furthermore, we find that the error of the new parameterization is smallest for a horizontal resolution of about 5-20 km and also depends on the appearance of mesoscale structures that are accompanied by higher rain rates. In combination with simple autoconversion schemes that only depend on the liquid water, the error introduced by the new parameterization is orders of magnitude smaller than the difference between various autoconversion schemes. For the liquid water flux, we introduce a parameterization that is depending on the skewness of the subgrid variability of temperature and moisture and that reproduces the profiles of the liquid water flux well. © 2013 Author(s).

Heus T.,Max Planck Institute for Meteorology | Seifert A.,Hans Ertel Center for Weather Research
Geoscientific Model Development | Year: 2013

This paper presents a method for feature tracking of fields of shallow cumulus convection in large eddy simulations (LES) by connecting the projected cloud cover in space and time, and by accounting for splitting and merging of cloud objects. Existing methods tend to be either imprecise or, when using the full three-dimensional (3-D) spatial field, prohibitively expensive for large data sets. Compared to those 3-D methods, the current method reduces the memory footprint by up to a factor 100, while retaining most of the precision by correcting for splitting and merging events between different clouds. The precision of the algorithm is further enhanced by taking the vertical extent of the cloud into account. Furthermore, rain and subcloud thermals are also tracked, and links between clouds, their rain, and their subcloud thermals are made. The method compares well with results from the literature. Resolution and domain dependencies are also discussed. For the current simulations, the cloud size distribution converges for clouds larger than an effective resolution of 6 times the horizontal grid spacing, and smaller than about 20% of the horizontal domain size. © 2013 Author(s).

Miltenberger A.K.,ETH Zurich | Seifert A.,Hans Ertel Center for Weather Research | Joos H.,ETH Zurich | Wernli H.,ETH Zurich
Quarterly Journal of the Royal Meteorological Society | Year: 2015

The precipitation produced by orographic clouds is the result of the interaction between nonlinear dynamical and microphysical processes. Focusing on warm-phase stable clouds, we propose that the precipitation efficiency is essentially controlled by the bulk Damköhler number of the system, i.e. the ratio of the characteristic advective to the microphysical time-scale of the cloud. These time-scales are investigated thoroughly for single air parcels along temporally highly resolved trajectories from quasi-two-dimensional numerical simulations with vertical Froude numbers between 0.38 and 2.31. Based on these results, analytical formulations for the Damköhler number of single parcels and for a bulk Damköhler number for the entire cloud are developed, which depend only on the far upstream flow properties and the cloud droplet number density. Relating the bulk Damköhler numbers to the precipitation efficiencies from the numerical simulations results in a unique scaling relation between the two non-dimensional numbers: no precipitation is observed for very small Damköhler numbers, while for large Damköhler numbers the precipitation efficiency asymptotically approaches a maximum value of about 0.8. For intermediate Damköhler numbers, the precipitation efficiency depends strongly on the microphysical properties of the clouds. © 2015 Royal Meteorological Society.

Wapler K.,Hans Ertel Center for Weather Research | Wapler K.,German Weather Service | James P.,German Weather Service
Atmospheric Research | Year: 2015

The occurrence and characteristics of thunderstorms in Central Europe are examined in relation to the predominant synoptic conditions as derived from an automatic classification of synoptic patterns. Lightning strokes measured by a lightning detection network, human thunderstorm observations at weather stations and convective cells derived from radar reflectivity are used. The analysis reveals conditions favourable for thunderstorm development and highlights regions affected under different flow regimes. Additionally, the cell-based analysis shows that different synoptic conditions are typically associated with specific cell characteristics, such as the direction and speed of movement or cell sizes and severity. These relationships can be explained meaningfully via a description of the synoptic-meteorological characteristics of each of the standard weather patterns. As such these results may support a better understanding of thunderstorm formation as well as improve forecasters' situational awareness. © 2014 Elsevier B.V.

Haslehner M.,Hans Ertel Center for Weather Research | Janjic T.,Hans Ertel Center for Weather Research | Craig G.C.,Ludwig Maximilians University of Munich
Quarterly Journal of the Royal Meteorological Society | Year: 2016

Convective-scale applications require data assimilation methods that can cope with nonlinear dynamics and the stochastic nature of convection. For this application, the particle filter is a promising data assimilation method because it estimates the probability density function (PDF) of the atmospheric state and not only its first two moments. However, in order to represent PDFs with a small number of particles, the particle filter is usually combined with another data assimilation technique. In this article we investigate a hybrid algorithm, the nudging proposal particle filter, which combines the sequential importance resampling particle filter with nudging. Analytic and experimental results on an idealized, nonlinear, one-dimensional model are used to show that there exists a combination of the two methods such that the nudging proposal particle filter outperforms both of its components. In this article, a stochastic cloud model, represented through a birth-death process, serves as a first test model for the filter. The transition probability density can be calculated exactly for this model, thus providing insight into its contribution to the selection of particles during resampling. The functioning mechanism of the nudging proposal particle filter in its simplest form is investigated and the impact of the model parameters on the filter's behaviour highlighted. © 2016 Royal Meteorological Society.

Lange H.,Ludwig Maximilians University of Munich | Janjic T.,Hans Ertel Center for Weather Research
Monthly Weather Review | Year: 2016

Aircraft observations of wind and temperature collected by airport surveillance radars [Mode-S Enhanced Surveillance (Mode-S EHS)] were assimilated in the Consortium for Small-Scale Modeling Kilometre-scale Ensemble Data Assimilation (COSMO-KENDA), which couples an ensemble Kalman filter to a 40-member ensemble of the convection permitting COSMO-DE model. The number of observing aircrafts in Mode-S EHS was about 15 times larger than in the AMDAR system. In the comparison of both aircraft observation systems, a similar observation error standard deviation was diagnosed for wind. For temperature, a larger error was diagnosed for Mode-S EHS. With the high density of Mode-S EHS observations, a reduction of temperature and wind error in forecasts of 1 and 3 hours was found mainly in the flight level and less near the surface. The amount of Mode-S EHS data was reduced by random thinning to test the effect of a varying observation density. With the current data assimilation setup, a saturation of the forecast error reduction was apparent when more than 50% of the Mode-S EHS data were assimilated. Forecast kinetic energy spectra indicated that the reduction in error is related to analysis updates on all scales resolved by COSMO-DE. © 2016 American Meteorological Society.

Zeng Y.,Ludwig Maximilians University of Munich | Janjic T.,Hans Ertel Center for Weather Research
Quarterly Journal of the Royal Meteorological Society | Year: 2016

Numerical discretization schemes have a long history of incorporating the most important conservation properties of the continuous system in order to improve the prediction of the nonlinear flow. The question arises whether data assimilation algorithms should follow a similar approach. To address this issue, we explore the conservation properties during data assimilation using perfect model experiments with a 2D shallow-water model preserving important properties of the true nonlinear flow. The data assimilation scheme used here is the Local Ensemble Transform Kalman Filter with varying observed variables, inflation, localization radius and thinning interval. It is found that, during the assimilation, the total energy of the analysis ensemble mean converges with time towards the nature run value. However, enstrophy, divergence and the energy spectra are strongly affected by the data assimilation settings. Having in mind that the conservation of both the kinetic energy and enstrophy by the momentum advection schemes in the case of non-divergent flow prevents a systematic and unrealistic energy cascade towards the high wave numbers, we test the effects on the prediction depending on the type of error in the initial condition. During the assimilation, we assess the downward nonlinear energy cascade through a scalar, domain-averaged noise measure. We show that the accumulated noise during assimilation and the error of analysis are good indicators of the quality of the prediction. © 2016 Royal Meteorological Society.

Wapler K.,Hans Ertel Center for Weather Research
Meteorology and Atmospheric Physics | Year: 2013

A 6-year analysis (including data of 36 million strokes) of the spatial and temporal occurrence of lightning strokes in Germany and neighbouring areas is presented. The analysis on a high-resolution grid with spatial resolution of 1 km allows assessing the local risk of lightning and studying local effects, e.g. the influence of orography on the occurrence of thunderstorms. The analysis reveals spatial and temporal patterns: the highest number of lightning strokes occurs in the pre-alpine region of southern Germany, further local maxima exists in low mountain ranges. The lowest number of lightning strokes is present in areas of the North Sea and Baltic Sea. Despite a high year-to-year variability of lightning rates, on average a clear annual cycle (maximum June to August) and diurnal cycle (maximum in the afternoon) are present. In addition to this well-known annual and diurnal pattern, the analysis shows that those are intertwined: the diurnal cycle has an annual cycle, visible in the time of daily maximum which occurs later in the afternoon in summer compared to spring and autumn. Furthermore, the annual cycle of lightning is varying geographically, e.g. offshore and coastal regions show a lower amplitude of the annual cycle and a later maximum (autumn) compared to inland (mountainous) regions. In addition, the annual and diurnal cycles of lightning attributes are analysed. The analysis reveals rising height of inner-cloud lightning during the year with a maximum in late summer. © 2013 Springer-Verlag Wien.

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