相关论文: Atmospheric pressure loading for routine data anal…
We present an approach that uses a deep learning model, in particular, a MultiLayer Perceptron (MLP), for estimating the missing values of a variable in multivariate time series data. We focus on filling a long continuous gap (e.g.,…
In air pollution studies, dispersion models provide estimates of concentration at grid level covering the entire spatial domain, and are then calibrated against measurements from monitoring stations. However, these different data sources…
Energetic electrons accelerated at coronal reconnection sites during solar flares precipitate into the lower solar atmosphere, generating nonthermal emissions and regulating energy deposition. However, how their transport and precipitation…
This paper presents the fifth part of the Very Long Baseline Array (VLBA) Calibrator Survey (VCS), containing 569 sources not observed previously with very long baseline interferometry in geodetic or absolute astrometry programs. This…
Rayleigh Brillouin (RB) scattering profiles for air have been recorded for the temperature range from 255 to 340 K and the pressure range from 640 to 3300 mbar, covering the conditions relevant for the Earth's atmosphere and for planned…
Electricity load forecasting for buildings and campuses is becoming increasingly important as the penetration of distributed energy resources (DERs) grows. Efficient operation and dispatch of DERs require reasonably accurate predictions of…
Radio-loud active galactic nuclei (AGNs), hosting powerful relativistic jet outflows, provide an excellent laboratory for studying jet physics. Very long baseline interferometry (VLBI) enables high-resolution imaging on milli-arcsecond…
We present a regime-switching vector-autoregressive method for very-short-term wind speed forecasting at multiple locations with regimes based on large-scale meteorological phenomena. Statistical methods short-term wind forecasting…
Precipitation plays a critical role in the Earth's hydrological cycle, directly affecting ecosystems, agriculture, and water resource management. Accurate precipitation estimation and prediction are crucial for understanding climate…
Near-surface air temperature is a key physical property of the Earth's surface. Although weather stations offer continuous monitoring and satellites provide broad spatial coverage, no single data source offers seamless data in a…
Building an accurate load forecasting model with minimal underpredictions is vital to prevent any undesired power outages due to underproduction of electricity. However, the power consumption patterns of the residential sector contain…
Weak lensing observations have the potential to be even more powerful than cosmic microwave background (CMB) observations in constraining cosmological parameters. However, the practical limits to weak lensing observations are not known.…
The next-generation, broadband geodetic very long baseline interferometry system, named VGOS, is developing its global network, and VGOS networks with a small size of 3--7 stations have already made broadband observations from 2017 to 2019.…
Cool clouds are expected to be destroyed and incorporated into hot supernova-driven galactic winds. The mass-loading of a wind by the cool medium modifies the bulk velocity, temperature, density, entropy, and abundance profiles of the hot…
Rainfall-induced landslides pose a growing risk worldwide as climate change intensifies extreme rainfall events. To provide sufficient evacuation time, landslide early warning systems (LEWS) for real-time disaster monitoring must estimate…
Numerical weather forecasting using high-resolution physical models often requires extensive computational resources on supercomputers, which diminishes their wide usage in most real-life applications. As a remedy, applying deep learning…
Interspacecraft ranging is crucial for the suppression of laser frequency noise via time-delay interferometry (TDI). So far, the effects of on-board delays and ambiguities on the LISA ranging observables were neglected in LISA modelling and…
Unpredictability of renewable energy sources coupled with the complexity of those methods used for various purposes in this area calls for the development of robust methods such as DL models within the renewable energy domain. Given the…
A new technique has been developed to remove the ionosphere's distorting effects from low frequency VLBI data. By fitting dispersive and non-dispersive components to the phases of multi-frequency data, the ionosphere can be effectively…
Real-time air pollution monitoring is a valuable tool for public health and environmental surveillance. In recent years, there has been a dramatic increase in air pollution forecasting and monitoring research using artificial neural…