A novel technique is used to estimate derivatives of ice effective radius with respect to height near convective cloud tops ( /) from airborne shortwave reflectance measurements and lidar. Values of / are about -6 m/km for cloud tops below the homogeneous freezing level, increasing to near 0 m/km above the estimated level of neutral buoyancy. Retrieved / compares well with previously documented remote sensing and in situ estimates. Effective radii decrease with increasing cloud top height, while cloud top extinction increases. This is consistent with weaker size sorting in high, dense cloud tops above the level of neutral buoyancy where fewer large particles are present, and with stronger size sorting in lower cloud tops that are less dense. The results also confirm that cloud-top trends of effective radius can generally be used as surrogates for trends with height within convective cloud tops. These results provide valuable observational targets for model evaluation.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5880042 | PMC |
| http://dx.doi.org/10.1002/2016GL068548 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Polarity transitions of narrow bipolar events in thundercloud tops reaching the lower stratosphere.
Nat Commun
August 2024
CAS Key Laboratory of Geospace Environment, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, China.
Blue corona discharges are often generated in thunderclouds penetrating into the stratosphere and are the optical manifestation of narrow bipolar events (NBEs) observed in radio signals. While their production appears to depend on convection, the cause and nature of such discharges are not well known. Here we show the observations by a lightning detection array of unusual amounts of 982 NBEs during a tropical storm on the coastline of China.
View Article and Find Full Text PDFHybMED: A Hybrid Neural Network Training Processor With Multi-Sparsity Exploitation for Internet of Medical Things.
IEEE Trans Biomed Circuits Syst
October 2024
Cloud-based training and edge-based inference modes for Artificial Intelligence of Medical Things (AIoMT) applications suffer from accuracy degradation due to physiological signal variations among patients. On-chip learning can overcome this issue by online adaptation of neural network parameters for user-specific tasks. However, existing on-chip learning processors have limitations in terms of versatility, resource utilization, and energy efficiency.
View Article and Find Full Text PDFPossible Effects of Volcanic Eruptions on the Modern Atmosphere of Venus.
Space Sci Rev
April 2024
School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287-1404 USA.
This work reviews possible signatures and potential detectability of present-day volcanically emitted material in the atmosphere of Venus. We first discuss the expected composition of volcanic gases at present time, addressing how this is related to mantle composition and atmospheric pressure. Sulfur dioxide, often used as a marker of volcanic activity in Earth's atmosphere, has been observed since late 1970s to exhibit variability at the Venus' cloud tops at time scales from hours to decades; however, this variability may be associated with solely atmospheric processes.
View Article and Find Full Text PDFImaging of 3 bright terrestrial gamma-ray flashes by the atmosphere-space interactions monitor and their parent thunderstorms.
Sci Rep
March 2024
Department of Physics and Technology, University of Bergen, Bergen, Norway.
The Atmosphere-Space Interactions Monitor (ASIM) on the International Space Station (ISS) includes an instrument designed to geolocate Terrestrial Gamma-ray Flashes (TGF) produced by thunderstorms. It does so with a coded aperture system shadowing the pixelated Low Energy Detector of the Modular X- and Gamma-ray Sensor (MXGS). Additionally, it locates associated lightning flashes with the Modular Multispectral Imaging Array (MMIA).
View Article and Find Full Text PDFIndividual tree segmentation of airborne and UAV LiDAR point clouds based on the watershed and optimized connection center evolution clustering.
Ecol Evol
July 2023
State Key Laboratory of Remote Sensing Science, Beijing Engineering Research Center for Global Land Remote Sensing Products Beijing Normal University Beijing China.
Light detection and ranging (LiDAR) data can provide 3D structural information of objects and are ideal for extracting individual tree parameters, and individual tree segmentation (ITS) is a vital step for this purpose. Various ITS methods have been emerging from airborne LiDAR scanning (ALS) or unmanned aerial vehicle LiDAR scanning (ULS) data. Here, we propose a new individual tree segmentation method, which couples the classical and efficient watershed algorithm (WS) and the newly developed connection center evolution (CCE) clustering algorithm in pattern recognition.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!