100 research outputs found
Improving the Analog Ensemble Wind Speed Forecasts for Rare Events
Abstract
An analog-based ensemble technique, the analog ensemble (AnEn), has been applied successfully to generate probabilistic predictions of meteorological variables, wind and solar power, energy demand, and the optimal bidding in the day-ahead energy market. The AnEn method uses a historical time series of past forecasts from a meteorological model or other prediction systems and observations of the quantity to be predicted. For each forecast lead time, the ensemble set of predictions is a set of observations from the past. These observations are those concurrent with the past forecasts at the same lead time, chosen across the past runs most similar to the current forecast. Recent applications have demonstrated that the AnEn introduces a conditional negative bias when predicting events in the right tail of the forecast distribution of wind speed, particularly when the training dataset is short. This underestimation increases when the predicted event occurs less frequently in the available historical data. A new bias correction for the AnEn using wind observations from more than 500 U.S. stations is tested to reduce the AnEn's underestimation of rare events. It is shown that the conditional negative bias introduced by the AnEn in its standard application is significantly reduced by our novel approach. Also, the overall probabilistic AnEn performances improve when predicting wind speed higher than 10 m s−1 as demonstrated by lower values of the continuous ranked probability score. These improvements can be attributed to an increased reliability achieved by introducing the proposed bias correction algorithm
POST-PROCESSING OF ALADIN WIND SPEED PREDICTIONS WITH AN ANALOG-BASED METHOD
In this paper, different post-processing methods are described and evaluated for deterministic and probabilistic point-based 10-m wind speed forecast over Croatia. These methods are applied to forecasts of operational high-resolution dynamical adaptation model (DADA) run with 2 km horizontal resolution to address the following question: which point-based post-processing method is the best suited for wind forecasting in the operational suite at DHMZ (Meteorological
and Hydrological Service of Croatia).
The verification procedure includes several metrics computed considering wind speed as continuous, categorical and probabilistic predictand. Those metrics were used to optimize the configuration,
and to test both the deterministic and probabilistic prediction performance. This study shows that deterministic analog-based predictions (AnEn) improve the correlation between predictions and measurements while reducing forecast error better than using Kalman
filter based predictions (KF), even though KF shows better bias reduction. The best results are achieved when forecasting the mean of analog ensemble or the Kalman filter of the mean of analog ensemble. Probabilistic AnEn predictions are properly dispersive, while having better resolution, discrimination and skill than forecast generated via logistic regression. These results encourage the potential use of AnEn in an operational environment at the location of
meteorological stations, as well as at wind farm s
Bayesian Exploration of Multivariate Orographic Precipitation Sensitivity for Moist Stable and Neutral Flows
Abstract
Recent idealized studies examined the sensitivity of topographically forced rain and snowfall to changes in mountain geometry and upwind sounding in moist stable and neutral environments. These studies were restricted by necessity to small ensembles of carefully chosen simulations. Research presented here extends earlier studies by utilizing a Bayesian Markov chain Monte Carlo (MCMC) algorithm to create a large ensemble of simulations, all of which produce precipitation concentrated on the upwind slope of an idealized Gaussian bell-shaped mountain. MCMC-based probabilistic analysis yields information about the combinations of sounding and mountain geometry favorable for upslope rain, as well as the sensitivity of orographic precipitation to changes in mountain geometry and upwind sounding. Exploration of the multivariate sensitivity of rainfall to changes in parameters also reveals a nonunique solution: multiple combinations of flow, topography, and environment produce similar surface rainfall amount and distribution. Finally, the results also divulge that the nonunique solutions have different sensitivity profiles, and that changes in observation uncertainty also alter model sensitivity to input parameters
The first-in-class alkylating deacetylase inhibitor molecule tinostamustine shows antitumor effects and is synergistic with radiotherapy in preclinical models of glioblastoma
Background: The use of alkylating agents such as temozolomide in association with radiotherapy (RT) is the
therapeutic standard of glioblastoma (GBM). This regimen modestly prolongs overall survival, also if, in light of
the still dismal prognosis, further improvements are desperately needed, especially in the patients with O6-
methylguanine-DNA-methyltransferase (MGMT) unmethylated tumors, in which the benefit of standard treatment
is less. Tinostamustine (EDO-S101) is a first-in-class alkylating deacetylase inhibitor (AK-DACi) molecule that fuses
the DNA damaging effect of bendamustine with the fully functional pan-histone deacetylase (HDAC) inhibitor,
vorinostat, in a completely new chemical entity.
Methods: Tinostamustine has been tested in models of GBM by using 13 GBM cell lines and seven patient-derived
GBM proliferating/stem cell lines in vitro. U87MG and U251MG (MGMT negative), as well as T98G (MGMT positive),
were subcutaneously injected in nude mice, whereas luciferase positive U251MG cells and patient-derived GBM stem
cell line (CSCs-5) were evaluated the orthotopic intra-brain in vivo experiments.
Results: We demonstrated that tinostamustine possesses stronger antiproliferative and pro-apoptotic effects than
those observed for vorinostat and bendamustine alone and similar to their combination and irrespective of MGMT
expression. In addition, we observed a stronger radio-sensitization of single treatment and temozolomide used as
control due to reduced expression and increased time of disappearance of γH2AX indicative of reduced signal and
DNA repair. This was associated with higher caspase-3 activation and reduction of RT-mediated autophagy. In vivo,
tinostamustine increased time-to-progression (TTP) and this was additive/synergistic to RT. Tinostamustine had
significant therapeutic activity with suppression of tumor growth and prolongation of DFS (disease-free survival) and
OS (overall survival) in orthotopic intra-brain models that was superior to bendamustine, RT and temozolomide and
showing stronger radio sensitivity.
Conclusions: Our data suggest that tinostamustine deserves further investigation in patients with glioblastoma
Challenges in Developing Better Observational Constraints and Models for Aerosols : Emerging Ideas for Design and Use of Future Observing Systems
No abstract availabl
On the Impact of the Assimilation of Nacelle Winds and Yaw Angles With WRF-FDDA and WRF-DART for Short-Term Wind Energy Predictions
Investigating Networked Music Performances in Pedagogical Scenarios for the InterMUSIC Project
With the big improvement of digital communication networks, Networked Music Performances (NMP) received a great interest from music live performance and music recording industry. The positive impact of NMP in pedagogical appli- cations, instead, has been only preliminary explored. Within the InterMUSIC project, we aim to investigate NMP from a pedagogical perspective, that has considerable differences with respect to music performances, and to develop tools to improve distance learning experiences. In this paper, we introduce a conceptual framework designed to be the foundation for all the experiments conducted in the project. We also present two preliminary experiments that investigate the sense of presence of geographically-distant musicians in a distance learning scenario. We discuss the comments provided by the musicians as a set of requirements and guidelines for future experiments
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