Zobrazeno 1 - 10
of 24
pro vyhledávání: '"TING-CHI WU"'
Autor:
Ting-Chi Wu, 吳婷琦
97
Meteorological fields are necessary input for air quality modeling. Wind field is responsible for pollutant transport and turbulent mixing in the troposphere. In this work we studied the impact of analysis nudging of meteorological variables
Meteorological fields are necessary input for air quality modeling. Wind field is responsible for pollutant transport and turbulent mixing in the troposphere. In this work we studied the impact of analysis nudging of meteorological variables
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/e88j5p
Autor:
Steven J. Fletcher, Milija Zupanski, Michael R. Goodliff, Anton J. Kliewer, Andrew S. Jones, John M. Forsythe, Ting-Chi Wu, Md. Jakir Hossen, Senne Van Loon
Publikováno v:
Monthly Weather Review. 151:761-774
In this paper we present the derivation of two new forms of the Kalman filter equations; the first is for a pure lognormally distributed random variable, while the second set of Kalman filter equations will be for a combination of Gaussian and lognor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4e504f556cefee45ed3c48472953a989
https://doi.org/10.1175/mwr-d-22-0072.1
https://doi.org/10.1175/mwr-d-22-0072.1
Autor:
Lewis Grasso, Daniel Bikos, Jack Dostalek, Ting-Chi Wu, Kyle Hilburn, Ed Szoke, Jorel Torres, Jon W. Zeitler, Bill Line, Ariel E. Cohen
Publikováno v:
E-Journal of Severe Storms Meteorology. 15:1-24
Thunderstorms formed in the afternoon of 17 April 2019 over northern Mexico. Satellite data are used to highlight several features associated with convective preconditioning over portions of Coahuila, Mexico. Satellite imagery was used to identify tw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4eaf0dd153221df450ddbb49a72c929e
https://doi.org/10.55599/ejssm.v15i2.76
https://doi.org/10.55599/ejssm.v15i2.76
Autor:
John F. Dostalek, Lewis D. Grasso, Yoo-Jeong Noh, Ting-Chi Wu, Jon W. Zeitler, Harry G. Weinman, Ariel E. Cohen, Daniel T. Lindsey
Publikováno v:
E-Journal of Severe Storms Meteorology. 16:1-19
A clear sky, daytime retrieval of low-level precipitable water vapor based on the single-layer approximation to the radiative transfer equation applied to three longwave window channels is described. The algorithm, which simultaneously retrieves skin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::88596a4a6a4665aa87d484855aeec073
https://doi.org/10.55599/ejssm.v16i2.79
https://doi.org/10.55599/ejssm.v16i2.79
Autor:
John M. Forsythe, Kennard B. Kasper, Jorel Torres, Emily Berndt, Dan Bikos, Harry G. Weinman, Lewis D. Grasso, John F. Dostalek, Curtis J. Seaman, Heather Q. Cronk, Ting-Chi Wu, Steven D. Miller
Publikováno v:
Atmospheric Measurement Techniques, Vol 14, Pp 1615-1634 (2021)
On 16–17 February 2020, dust within a Saharan Air Layer (SAL) from western Africa moved over the eastern Atlantic Ocean. Satellite imagery and products from ABI on GOES-16, VIIRS on NOAA-20, and CALIOP on CALIPSO along with retrieved values of laye
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b37e33a491ac87e873ead607813228e1
https://doi.org/10.5194/amt-14-1615-2021
https://doi.org/10.5194/amt-14-1615-2021
Data assimilation plays a critical role in the advancement of numerical weather prediction (NWP) via ingesting information of atmospheric observations from various platforms. As more and more observations become available, it is important to quantify
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::97f7658844e23972c96de5c6337dabfc
https://doi.org/10.5194/egusphere-egu22-10704
https://doi.org/10.5194/egusphere-egu22-10704
Autor:
Yi Wang, Sonia M. Kreidenweis, Jun Wang, Jennifer Bukowski, Jack F. Dostalek, Jeffrey S. Reid, Susan C. van den Heever, Ting-Chi Wu, Annette L. Walker, Steven D. Miller, Milija Zupanski, Xiaoguang Xu, Christine Chiu, Jeremy E. Solbrig, Louie Grasso, Qijing Bian
Publikováno v:
Atmospheric Measurement Techniques. 12:5101-5118
Lofted mineral dust over data-sparse regions presents considerable challenges to satellite-based remote sensing methods and numerical weather prediction alike. The Southwest Asia domain is replete with such examples, with its diverse array of dust so
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb75b5c1099b48f9760174ffe85e7084
https://doi.org/10.5194/amt-12-5101-2019
https://doi.org/10.5194/amt-12-5101-2019
Imagery from the GOES series has been a key element of U.S. operational weather forecasting for four decades. While GOES observations are used extensively by human forecasters for situational aware...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c53d97dc0baf1a1ad1bfa60ab1afa33
https://doi.org/10.1002/essoar.10504858.1
https://doi.org/10.1002/essoar.10504858.1
Autor:
Lewis D. Grasso, Christian D. Kummerow, Wesley Berg, James Fluke, Milija Zupanski, Richard Schulte, Ting-Chi Wu, Philip T. Partain, Heather Q. Cronk, A. Kliewer, Steven M. Miller
Unlike large, expensive, and high-risk operational satellites, small/cube satellites (SmallSats) are a small, inexpensive, and a low-risk type of satellite. As a NOAA Cooperative Institute with specialties in satellite data processing and data assimi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::73e7d203f19400a728dd0336309f6cc4
https://doi.org/10.5194/egusphere-egu2020-1949
https://doi.org/10.5194/egusphere-egu2020-1949
Autor:
Christopher W. O'Dell, Lewis D. Grasso, Ting-Chi Wu, Yoo-Jeong Noh, Fanyou Kong, Daniel T. Lindsey
Publikováno v:
Monthly Weather Review. 146:3927-3944
In preparation for all-sky satellite radiance assimilation, the Community Radiative Transfer Model (CRTM), version 2.1.3, was used to produce Geostationary Operational Environmental Satellite-12/13 (GOES-12/13) imagery near 3.9 μm. For the current s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b390da76120041e4bee96b5502cfaa0f
https://doi.org/10.1175/mwr-d-17-0342.1
https://doi.org/10.1175/mwr-d-17-0342.1