Results 61 to 70 of about 641,092 (210)
Aerosol‐Cloud Interactions: Overcoming a Barrier to Projecting Near‐Term Climate Evolution and Risk
Abstract Aerosol‐cloud interactions (ACI) are a major source of uncertainty in climate science, critically affecting our ability to project near‐term climate evolution and assess societal risks. These interactions influence effective radiative forcing, cloud dynamics, and precipitation patterns, yet remain insufficiently constrained due to limitations ...
Ulas Im +40 more
wiley +1 more source
Exploiting radar polarimetry for nowcasting thunderstorm hazards using deep learning [PDF]
This work presents the importance of polarimetric variables as an additional data source for nowcasting thunderstorm hazards using an existing neural network architecture with recurrent-convolutional layers.
N. Rombeek, J. Leinonen, U. Hamann
doaj +1 more source
Perspectives on Systematic Cloud Microphysics Scheme Development With Machine Learning
Abstract Cloud microphysics—the collection of processes that govern the small‐scale formation, evolution, and interactions of liquid droplets and ice crystals in clouds and precipitation—remains a major source of uncertainty in weather and climate models.
Kara D. Lamb +9 more
wiley +1 more source
Weather Radar Polarimetry–Trends Toward Operational Applications
This is a version of a speech presented at the 27th Conference on Radar Meteorology. Relative advantages of polarimetry are contrasted with the advantages accrued by the introduction of radar into meteorology and by the addition of Doppler measurements ...
Dušan S. Zrnić
core +1 more source
We investigated the use of C-band RADARSAT Constellation Mission (RCM) synthetic aperture radar (SAR) for retrieval of ocean surface wind speeds by using four new channels (right circular transmit, vertical receive (RV); right circular transmit ...
He Fang +7 more
doaj +1 more source
Polarimetric SAR data's inherent complex‐valued nature demands algorithms that work directly with complex representations, yet most deep‐learning approaches sidestep this by converting to the real domain. We implement and evaluate complex‐valued convolutional autoencoders that compress and accurately reconstruct full‐polarimetric SAR signals—preserving
Quentin Gabot +4 more
wiley +1 more source
Results of Dual-Polarimetric Airborne Passive Radar
Polarimetry in remote sensing applications has emerged as a valuable technique for enhancing the information content of Synthetic Aperture Radar (SAR) images. Passive radar exploits existing illuminators of opportunity, e.g.
Markiton, Philipp M., Cristallini, Diego
core +1 more source
Single-Pass Bistatic SAR Interferometry Using Fixed-Receiver Configurations: Theory and Experimental Validation [PDF]
In this paper, bistatic interferometry using fixed-receiver configurations is addressed both theoretically and experimentally. The analytical expressions for interferometric phase and height sensitivity are derived, and a full interferometric processing ...
Mallorqui, Jordi J. +5 more
core +1 more source
Space-borne polarimetric SAR sensors or the golden age of radar polarimetry
SAR Polarimetry represents an active area of research in Active Earth Remote Sensing. This interest is clearly supported by the fact that nowadays there exists, or there will exist in a very next future, a non negligible quantity of launched ...
Pottier E.
doaj +1 more source
This paper presents a multistatic, frequency‐ and polarimetry‐adaptive autofocus algorithm (F‐Pol) for SAR imaging of moving targets undergoing complex, six‐degrees‐of‐freedom (6‐DoF) motion. Building on Localised Threshold Sharpness (LTS), the method exploits agreement across frequency sub‐bands and polarisation channels to improve pulse‐by‐pulse ...
Anmol Rattan, Daniel Andre, Mark Finnis
wiley +1 more source

