1,305 research outputs found
Multi-satellite altimetry and GOCE geoid based surface and subsurface currents in the Mediterranean Sea
Peer ReviewedPostprint (published version
Final report on studies of space/time variability of marine boundary layer characteristics
August 1990.Appendix A originally presented as Melanie A. Wetzel's dissertation (Colorado State University, 1990) under the title: Investigation of a remote sensing technique for droplet-effective radius.Includes bibliographical references.ONR Contract no. N00014-86-C-0459
Dynamical modeling of marine boundary layer convection
April 1987.Includes bibliographical references.Sponsored by NSF ATM-8510664.Sponsored by ONR N00014-84-C-0591.Sponsored by NOAA NA-85-RAH05045
Satellite Climatology of Tropical Cyclone with Concentric Eyewalls
An objective method is developed to identify concentric eyewalls (CEs) for tropical cyclones (TCs) using passive microwave satellite imagery from 1997 to 2014 in the western North Pacific (WNP) and Atlantic (ATL) basin. There are 91 (33) TCs and 113 (50) cases with CE identified in the WNP (ATL). Three CE structural change types are classified as follows: a CE with the inner eyewall dissipated in an eyewall replacement cycle (ERC, 51 and 56% in the WNP and ATL), a CE with the outer eyewall dissipated first and the no eyewall replacement cycle (NRC, 27 and 29% in the WNP and ATL), and a CE structure that is maintained for an extended period (CEM, 23 and 15% in the WNP and ATL). The moat size and outer eyewall width in the WNP (ATL) basin are approximately 20–50% (15–25%) larger in the CEM cases than that in the ERC and NRC cases. Our analysis suggests that the ERC cases are more likely dominated by the internal dynamics, whereas the NRC cases are heavily influenced by the environment condition, and both the internal and environmental conditions are important in the CEM cases. A good correlation of the annual CE TC number and the Oceanic Niño index is found (0.77) in WNP basin, with most of the CE TCs occurring in the warm episodes. In contrast, the El Niño/Southern Oscillation (ENSO) may not influence on the CE formation in the ATL basin. After the CE formation, however, the unfavorable environment that is created by ENSO may reduce the TC intensity quickly during warm episode. The variabilities of structural changes in the WNP basin are larger than that in the ATL basin
A Simple Model for Cavity Enhanced Slow Lights in Vertical Cavity Surface Emission Lasers
We develop a simple model for the slow lights in Vertical Cavity Surface
Emission Lasers (VCSELs), with the combination of cavity and population
pulsation effects. The dependences of probe signal power, injection bias
current and wavelength detuning for the group delays are demonstrated
numerically and experimentally. Up to 65 ps group delays and up to 10 GHz
modulation frequency can be achieved in the room temperature at the wavelength
of 1.3 m. The most significant feature of our VCSEL device is that the
length of active region is only several m long. Based on the experimental
parameters of quantum dot VCSEL structures, we show that the resonance effect
of laser cavity plays a significant role to enhance the group delays
A Deep Learning Approach to Radar-based QPE
In this study, we propose a volume-to-point framework for quantitative
precipitation estimation (QPE) based on the Quantitative Precipitation
Estimation and Segregation Using Multiple Sensor (QPESUMS) Mosaic Radar data
set. With a data volume consisting of the time series of gridded radar
reflectivities over the Taiwan area, we used machine learning algorithms to
establish a statistical model for QPE in weather stations. The model extracts
spatial and temporal features from the input data volume and then associates
these features with the location-specific precipitations. In contrast to QPE
methods based on the Z-R relation, we leverage the machine learning algorithms
to automatically detect the evolution and movement of weather systems and
associate these patterns to a location with specific topographic attributes.
Specifically, we evaluated this framework with the hourly precipitation data of
45 weather stations in Taipei during 2013-2016. In comparison to the
operational QPE scheme used by the Central Weather Bureau, the volume-to-point
framework performed comparably well in general cases and excelled in detecting
heavy-rainfall events. By using the current results as the reference benchmark,
the proposed method can integrate the heterogeneous data sources and
potentially improve the forecast in extreme precipitation scenarios.Comment: 22 pages, 11 figures. Published in Earth and Space Scienc
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