Efficient approximation of the incomplete gamma function for use in cloud model applications

This paper describes an approximation to the lower incomplete gamma function γ<i><sub>l</sub>(a,x)</i> which has been obtained by nonlinear curve fitting. It comprises a fixed number of terms and yields moderate accuracy (the absolute approximation error of the corresponding normalized incomplete gamma function <i>P</i> is smaller than 0.02 in the range 0.9 ≤ <i>a</i> ≤ 45 and <i>x</i>≥0). Monotonicity and asymptotic behaviour of the original incomplete gamma function is preserved. <br><br> While providing a slight to moderate performance gain on scalar machines (depending on whether <i>a</i> stays the same for subsequent function evaluations or not) compared to established and more accurate methods based on series- or continued fraction expansions with a variable number of terms, a big advantage over these more accurate methods is the applicability on vector CPUs. Here the fixed number of terms enables proper and efficient vectorization. The fixed number of terms might be also beneficial on massively parallel machines to avoid load imbalances, caused by a possibly vastly different number of terms in series expansions to reach convergence at different grid points. For many cloud microphysical applications, the provided moderate accuracy should be enough. However, on scalar machines and if <i>a</i> is the same for subsequent function evaluations, the most efficient method to evaluate incomplete gamma functions is perhaps interpolation of pre-computed regular lookup tables (most simple example: equidistant tables)

On the analytic approximation of bulk collision rates of non-spherical hydrometeors

Analytic approximations of the binary collision rates of hydrometeors are derived for use in bulk microphysical parameterizations. Special attention is given to non-spherical hydrometeors like raindrops and snowflakes. The terminal fall velocity of these particles cannot be sufficiently well approximated by power-law relations which are used in most microphysical parameterizations, and therefore an improved formulation is needed. The analytic approximations of the bulk collision rates given in this paper are an alternative to look-up tables and can replace the Wisner approximation, which is used in many atmospheric models. © 2014 Author (s)

Generation of an Object-based Nowcasting Ensemble

Presentación realizada en la 3rd European Nowcasting Conference, celebrada en la sede central de AEMET en Madrid del 24 al 26 de abril de 2019

Development of a probabilistic precipitation-nowcastingapproach at DWD

Presentación realizada en la 3rd European Nowcasting Conference, celebrada en la sede central de AEMET en Madrid del 24 al 26 de abril de 2019

Saharan Dust Event Impacts on Cloud Formation and Radiation over Western Europe

We investigated the impact of mineral dust particles on clouds, radiation and atmospheric state during a strong Saharan dust event over Europe in May 2008, applying a comprehensive online-coupled regional model framework that explicitly treats particle-microphysics and chemical composition. Sophisticated parameterizations for aerosol activation and ice nucleation, together with two-moment cloud microphysics are used to calculate the interaction of the different particles with clouds depending on their physical and chemical properties. The impact of dust on cloud droplet number concentration was found to be low, with just a slight increase in cloud droplet number concentration for both uncoated and coated dust. For temperatures lower than the level of homogeneous freezing, no significant impact of dust on the number and mass concentration of ice crystals was found, though the concentration of frozen dust particles reached up to 100 l-1 during the ice nucleation events. Mineral dust particles were found to have the largest impact on clouds in a temperature range between freezing level and the level of homogeneous freezing, where they determined the number concentration of ice crystals due to efficient heterogeneous freezing of the dust particles and modified the glaciation of mixed phase clouds. Our simulations show that during the dust events, ice crystals concentrations were increased twofold in this temperature range (compared to if dust interactions are neglected). This had a significant impact on the cloud optical properties, causing a reduction in the incoming short-wave radiation at the surface up to -75Wm-2. Including the direct interaction of dust with radiation caused an additional reduction in the incoming short-wave radiation by 40 to 80Wm-2, and the incoming long-wave radiation at the surface was increased significantly in the order of +10Wm-2. The strong radiative forcings associated with dust caused a reduction in surface temperature in the order of -0.2 to -0.5K for most parts of France, Germany, and Italy during the dust event. The maximum difference in surface temperature was found in the East of France, the Benelux, and Western Germany with up to -1 K. This magnitude of temperature change was sufficient to explain a systematic bias in numerical weather forecasts during the period of the dust event

Assimilation of 3D radar reflectivities with an ensemble Kalman filter on the convective scale

An ensemble data assimilation system for 3D radar reflectivity data is introduced for the convection-permitting numerical weather prediction model of the COnsortium for Small-scale MOdelling (COSMO) based on the Kilometre-scale ENsemble Data Assimilation system (KENDA), developed by Deutscher Wetterdienst and its partners. KENDA provides a state-of-the-art ensemble data assimilation system on the convective scale for operational data assimilation and forecasting based on the Local Ensemble Transform Kalman Filter (LETKF). In this study, the Efficient Modular VOlume RADar Operator is applied for the assimilation of radar reflectivity data to improve short-term predictions of precipitation. Both deterministic and ensemble forecasts have been carried out. A case-study shows that the assimilation of 3D radar reflectivity data clearly improves precipitation location in the analysis and significantly improves forecasts for lead times up to 4 h, as quantified by the Brier Score and the Continuous Ranked Probability Score. The influence of different update rates on the noise in terms of surface pressure tendencies and on the forecast quality in general is investigated. The results suggest that, while high update rates produce better analyses, forecasts with lead times of above 1 h benefit from less frequent updates. For a period of seven consecutive days, assimilation of radar reflectivity based on the LETKF is compared to that of DWD's current operational radar assimilation scheme based on latent heat nudging (LHN). It is found that the LETKF competes with LHN, although it is still in an experimental phase

The impact of mineral dust on cloud formation during the Saharan dust event in April 2014 over Europe

A regional modeling study on the impact of desert dust on cloud formation is presented for a major Saharan dust outbreak over Europe from 2 to 5 April 2014. The dust event coincided with an extensive and dense cirrus cloud layer, suggesting an influence of dust on atmospheric ice nucleation. Using interactive simulation with the regional dust model COSMO-MUSCAT, we investigate cloud and precipitation representation in the model and test the sensitivity of cloud parameters to dust–cloud and dust–radiation interactions of the simulated dust plume. We evaluate model results with ground-based and spaceborne remote sensing measurements of aerosol and cloud properties, as well as the in situ measurements obtained during the ML-CIRRUS aircraft campaign. A run of the model with single-moment bulk microphysics without online dust feedback considerably underestimated cirrus cloud cover over Germany in the comparison with infrared satellite imagery. This was also reflected in simulated upper-tropospheric ice water content (IWC), which accounted for only 20&thinsp;% of the observed values. The interactive dust simulation with COSMO-MUSCAT, including a two-moment bulk microphysics scheme and dust–cloud as well as dust–radiation feedback, in contrast, led to significant improvements. The modeled cirrus cloud cover and IWC were by at least a factor of 2 higher in the relevant altitudes compared to the noninteractive model run. We attributed these improvements mainly to enhanced deposition freezing in response to the high mineral dust concentrations. This was corroborated further in a significant decrease in ice particle radii towards more realistic values, compared to in situ measurements from the ML-CIRRUS aircraft campaign. By testing different empirical ice nucleation parameterizations, we further demonstrate that remaining uncertainties in the ice-nucleating properties of mineral dust affect the model performance at least as significantly as including the online representation of the mineral dust distribution. Dust–radiation interactions played a secondary role for cirrus cloud formation, but contributed to a more realistic representation of precipitation by suppressing moist convection in southern Germany. In addition, a too-low specific humidity in the 7 to 10&thinsp;km altitude range in the boundary conditions was identified as one of the main reasons for misrepresentation of cirrus clouds in this model study.</p

Національно-демократичні об'єднання та політичні партії в Україні кінця XIX - початку XX століття

Deep brain stimulation (DBS) has become increasingly important for the treatment and relief of neurological disorders such as Parkinson's disease, tremor, dystonia and psychiatric illness. As DBS implantations and any other stereotactic and functional surgical procedure require accurate, precise and safe targeting of the brain structure, the technical aids for preoperative planning, intervention and postoperative follow-up have become increasingly important. The aim of this paper was to give and overview, from a biomedical engineering perspective, of a typical implantation procedure and current supporting techniques. Furthermore, emerging technical aids not yet clinically established are presented. This includes the state-of-the-art of neuroimaging and navigation, patient-specific simulation of DBS electric field, optical methods for intracerebral guidance, movement pattern analysis, intraoperative data visualisation and trends related to new stimulation devices. As DBS surgery already today is an important technology intensive domain, an "intuitive visualisation" interface for improving management of these data in relation to surgery is suggested

Shape abnormalities of the caudate nucleus correlate with poorer gait and balance : results from a subset of the ladis study

Objective Functional deficits seen in several neurodegenerative disorders have been linked with dysfunction in frontostriatal circuits and with associated shape alterations in striatal structures. The severity of visible white matter hyperintensities (WMHs) on magnetic resonance imaging has been found to correlate with poorer performance on measures of gait and balance. This study aimed to determine whether striatal volume and shape changes were correlated with gait dysfunction. Methods Magnetic resonance imaging scans and clinical gait/balance data (scores from the Short Physical Performance Battery [SPPB]) were sourced from 66 subjects in the previously published LADIS trial, performed in nondisabled individuals older than age 65 years with WMHs at study entry. Data were obtained at study entry and at 3-year follow-up. Caudate nuclei and putamina were manually traced using a previously published method and volumes calculated. The relationships between volume and physical performance on the SPPB were investigated with shape analysis using the spherical harmonic shape description toolkit. Results There was no correlation between the severity of WMHs and striatal volumes. Caudate nuclei volume correlated with performance on the SPPB at baseline but not at follow-up, with subsequent shape analysis showing left caudate changes occurred in areas corresponding to inputs of the dorsolateral prefrontal, premotor, and motor cortex. There was no correlation between putamen volumes and performance on the SPPB. Conclusion Disruption in frontostriatal circuits may play a role in mediating poorer physical performance in individuals with WMHs. Striatal volume and shape changes may be suitable biomarkers for functional changes in this population