相关论文: Downscaling Microwave Brightness Temperatures Usin…
In this study, a novel machine learning algorithm is presented for disaggregation of satellite soil moisture (SM) based on self-regularized regressive models (SRRM) using high-resolution correlated information from auxiliary sources. It…
A novel algorithm is developed to downscale soil moisture (SM), obtained at satellite scales of 10-40 km by utilizing its temporal correlations to historical auxiliary data at finer scales. Including such correlations drastically reduces…
In this study, a machine learning algorithm is used for disaggregation of SMAP brightness temperatures (T$_{\textrm{B}}$) from 36km to 9km. It uses image segmentation to cluster the study region based on meteorological and land cover…
We study super-resolution imaging theoretically using a distant n-mode interferometer in the microwave regime for passive remote sensing, used e.g., for satellites like the "soil moisture and ocean salinity (SMOS)" mission to observe the…
Sea surface temperature (SST) is an essential climate variable that can be measured via ground truth, remote sensing, or hybrid model methodologies. Here, we celebrate SST surveillance progress via the application of a few relevant…
We present a microwave-frequency method for measuring polar Kerr effect and spontaneous time-reversal symmetry breaking (TRSB) in unconventional superconductors. While this experiment is motivated by work performed in the near infrared…
Resistive RAM (RRAM) devices are candidates for neuromorphic computing devices in which the functionality lies in the formation and reversible rupture and gap-closing of conducting filaments in insulating layers. To explore the thermal…
We investigate theoretically the ultimate resolution that can be achieved with passive remote sensing in the microwave regime used e.g.~on board of satellites observing Earth, such as the Soil Moisture and Ocean Salinity (SMOS) mission. We…
A light-beam-assisted temperature-control system operating within a temperature range from 77 to 180 K is developed for investigating the absorption of electromagnetic waves by high-temperature superconductors in the vicinity of…
We construct a simple analytical model to study the effects of cosmic strings on the microwave background radiation. Our model is based on counting random multiple impulses inflicted on photon trajectories by the string network between the…
The key challenge in multispectral radiation thermometry is accurately measuring emissivity. Traditional constrained optimization methods often fail to meet practical requirements in terms of precision, efficiency, and noise resistance.…
Over the past decade, the gravitational lensing of the Cosmic Microwave Background (CMB) has become a powerful tool for probing the matter distribution in the Universe. The standard technique used to reconstruct the CMB lensing signal…
We introduce a novel method for reconstructing surface temperatures through occluding forest vegetation by combining signal processing and machine learning. Our goal is to enable fully automated aerial wildfire monitoring using autonomous…
Deep learning, particularly convolutional neural networks for image recognition, has been recently used in meteorology. One of the promising applications is developing a statistical surrogate model that converts the output images of…
High-resolution soil moisture (SM) observations are critical for agricultural monitoring, forestry management, and hazard prediction, yet current satellite passive microwave missions cannot directly provide retrievals at tens-of-meter…
Weak gravitational lensing of the cosmic microwave background (CMB) carries imprints of the physics operating at redshifts much lower than that of recombination and serves as an important probe of cosmological structure formation, dark…
We present a signal-foreground separation algorithm for filtering observational data to extract spectral distortions of the cosmic microwave background (CMB). Our linear method, called the least response method (LRM), is based on the idea…
The temperature gradient of microwave background radiation (CMBR) is calculated in the Self Consistent Model. An expected values for Hubble parameter have been presented in two different cases. In the first case the temperature is treated…
Solar small scale microwave bursts (SMBs), including microwave dot, spike, and narrow band type III bursts, are characterized with very short timescales, narrow frequency bandwidth, and very high brightness temperatures. Based on…
Spectral Spatial Fluctuations (SSF) of the Cosmic Microwave Background Radiation (CMBR) temperature are considered as a result of an interaction of primordial atoms and molecules with CMBR in proto-objects moving with peculiar velocities…