Multi-Parameter Neural Network for Altimeter Tropical Cyclone Wind Speed Estimation
نویسندگان
چکیده
منابع مشابه
The Research on Ocean Surface Wind Speed Retrieval by Neural Network Algorithm for HY2 Altimeter
The neural network algorithm in this paper is applied to the ocean surface wind speed retrievals. Firstly, the Ku band backscattering coefficient (σKu) is considered as the input parameter to retrieve the wind speed and the retrieval precision reaches 1 m/s (root mean square error) for HY2 altimeter. Secondly, by introducing the Ku-band significant wave height (swhku), C-band backscattering coe...
متن کاملTropical Cyclone Wind Estimation Using Synthetic Aperture Radar
We have investigated various SAR images of tropical cyclones, which were acquired by the SAR aboard the satellites ENVISAT and RADARSAT-1 at different polarizations and incidence angles, using a similar approach as suggested by Horstmann et al., 2005 [1]. The resulting SAR-retrieved wind fields are compared to results of high-resolution numerical models as well as in situ measurements collected...
متن کاملReexamination of Tropical Cyclone Wind–Pressure Relationships
Tropical cyclone wind–pressure relationships are reexamined using 15 yr of minimum sea level pressure estimates, numerical analysis fields, and best-track intensities. Minimum sea level pressure is estimated from aircraft reconnaissance or measured from dropwindsondes, and maximum wind speeds are interpolated from best-track maximum 1-min wind speed estimates. The aircraft data were collected p...
متن کاملTropical Cyclone Heat Potential By using an Artificial Neural Network
The neural network is traditionally used to refer to a network or circuit of biological neurons. The modern usage of the term often refers to artificial neural networks, which are composed of artificial neurons or nodes. Thus the term may refer to either biological neural networks, made up of real biological neurons, or artificial neural networks, for solving artificial intelligence problems. T...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IOP Conference Series: Earth and Environmental Science
سال: 2021
ISSN: 1755-1307,1755-1315
DOI: 10.1088/1755-1315/682/1/012020