相关论文: Microburst nowcasting applications of GOES

Machine learning models have been employed to perform either physics-free data-driven or hybrid dynamical downscaling of climate data. Most of these implementations operate over relatively small downscaling factors because of the challenge…

Active wind noise detection and suppression techniques are a new and essential paradigm for enhancing ASR-based functionality with smart glasses, in addition to other wearable and smart devices in the broader IoT (Internet of things). In…

Project GRAND presents the results of a search for coincident high-energy gamma ray events in the direction and at the time of nine Gamma Ray Bursts (GRBs) detected by BATSE. A gamma ray has a non-negligible hadron production cross section;…

We demonstrate thermodynamic profile estimation with data obtained using the MicroPulse DIAL such that the retrieval is entirely self contained. The only external input is surface meteorological variables obtained from a weather station…

Motivated by the need for ubiquitous and reliable communications in post-disaster emergency management systems (EMSs), we hereby present a novel and efficient stochastic geometry (SG) framework. This mathematical model is specifically…

In this paper we quantify the performances of an automated weather forecast system implemented on the Large Binocular Telescope (LBT) site at Mt. Graham (Arizona) in forecasting the main atmospheric parameters close to the ground. The…

Measuring the resistance fluctuations of gas sensors provides new opportunities to enhance the selectivity and sensitivity of the sensor. Taking advantage of this possibility requires special low-noise measurement hardware and software to…

As climate change intensifies, the shift to cleaner energy sources becomes increasingly urgent. With wind energy production set to accelerate, reliable wind probabilistic forecasts are essential to ensure its efficient use. However, since…

The Atacama Desert has long been established as an excellent site for submillimeter observations. Yet identifying potentially optimal locations for a new facility within this region can require long field campaigns that rely on the…

This paper proposes a novel prediction-free two-stage coordinated dispatch framework for the real-time dispatch of grid-connected microgrid with generalized energy storages (GES). The proposed framework explicitly addresses grid awareness,…

Accurate geolocation is essential for the reliable use of GEDI LiDAR data in footprint-scale applications such as aboveground biomass modeling, data fusion, and ecosystem monitoring. However, residual geolocation errors arising from both…

Atmospheric retrievals are essential tools for interpreting exoplanet transmission and eclipse spectra, enabling quantitative constraints on the chemical composition, aerosol properties, and thermal structure of planetary atmospheres. The…

Adaptive Optics at mid-IR wavelengths has long been seen as either not necessary or easy. The impact of atmospheric turbulence on the performance of 8-10 meter class telescopes in the mid-IR is relatively small compared to other performance…

Predictions of the uncertainty associated with extreme events are a vital component of any prediction system for such events. Consequently, the prediction system ought to be probabilistic in nature, with the predictions taking the form of…

Out-of-distribution (OOD) detection is essential for deploying deep learning models in open-world environments. Existing approaches, such as energy-based scoring and gradient-projection methods, typically rely on high-dimensional…

We quantify the scientific potential for exoplanet imaging with the Mid-infrared E-ELT Imager and Spectrograph (METIS) foreseen as one of the instruments of the European Extremely Large Telescope (E-ELT). We focus on two main science cases:…

In this paper, we propose a data-driven energy storage system (ESS)-based method to enhance the online small-signal stability monitoring of power networks with high penetration of intermittent wind power. To accurately estimate inter-area…

Super-resolving the coarse outputs of global climate simulations, termed downscaling, is crucial in making political and social decisions on systems requiring long-term climate change projections. Existing fast super-resolution techniques,…

We present large-eddy-simulation (LES) modeling approaches for the simulation of atmospheric boundary layer turbulence that are of direct relevance to wind energy production. In this paper, we study a GABLS benchmark problem using…

Understanding the behaviour of the confined fast ions is important in both current and future fusion experiments. These ions play a key role in heating the plasma and will be crucial for achieving conditions for burning plasma in next-step…