Zobrazeno 1 - 10
of 14 267
pro vyhledávání: '"Numerical weather prediction"'
Autor:
Yu Fujimoto, Masamichi Ohba, Yujiro Tanno, Daisuke Nohara, Yuki Kanno, Akihisa Kaneko, Yasuhiro Hayashi, Yuki Itoda, Wataru Wayama
Publikováno v:
Big Earth Data, Pp 1-23 (2024)
Wind power is crucial for achieving carbon neutrality, but its output can vary due to local wind conditions. The spatio-temporal behavior of wind power generation connected to the power grid can have a significant impact on system operations. To asse
Externí odkaz:
https://doaj.org/article/3cc3431c64a34601be0ce3ed812fe376
Autor:
Lifeng ZHANG
Publikováno v:
暴雨灾害, Vol 43, Iss 3, Pp 243-254 (2024)
Heavy rainfall is an important weather that causes flood disasters, and it is also one of the most important natural disasters in our country. With development of the high-resolution numerical models, numerical weather prediction has been the main me
Externí odkaz:
https://doaj.org/article/6bb87e4492144a7f9091482631e69227
Publikováno v:
Earth and Space Science, Vol 11, Iss 10, Pp n/a-n/a (2024)
Abstract A new technology for remote measurements of marine surface pressure has been proposed, employing a V‐band differential absorption radar and a radiometric temperature sounder to calculate the total column atmospheric mass. Observing System
Externí odkaz:
https://doaj.org/article/0dbda285b50c42bfac07524f932999d8
Autor:
Bachir Annane, Lewis J. Gramer
Publikováno v:
Frontiers in Earth Science, Vol 12 (2024)
This study examines the influence of NASA Cyclone Global Navigation Satellite System (CyGNSS) Level 2-derived 10 m (near-surface) wind speed over the ocean on analyses and forecasts within the NOAA operational Hurricane Analysis and Forecast System (
Externí odkaz:
https://doaj.org/article/b297becd667042e39026177a57d71b3a
Publikováno v:
Frontiers in Earth Science, Vol 12 (2024)
Tropical cyclones models have long used nesting to achieve higher resolution of the inner core than was feasible for entire model domains. These high resolution nests have been shown to better capture storm structures and improve forecast accuracy. T
Externí odkaz:
https://doaj.org/article/37c045188ea444e2a20962a61db219a9
Autor:
Andrew M. Thomas, Stephen Noble
Publikováno v:
Frontiers in Earth Science, Vol 12 (2024)
To convert lightning indices generated by numerical weather prediction experiments into binary lightning hazard, a machine-learning tool was developed. This tool, consisting of parallel multilayer perceptron classifiers, was trained on an ensemble of
Externí odkaz:
https://doaj.org/article/46c0cd688dc7443cbb5523d3a58a994b
Autor:
Toshiyuki Ishibashi
Publikováno v:
Earth and Space Science, Vol 11, Iss 9, Pp n/a-n/a (2024)
Abstract Atmospheric state analysis is a difficult scientific problem but essential for atmospheric sciences. Data assimilation can generate accurate analyses by integrating information on the atmospheric state using probability density functions (PD
Externí odkaz:
https://doaj.org/article/e74ef53f25d2480281731fc755ca450e
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 17, Pp n/a-n/a (2024)
Abstract In Numerical Weather Prediction (NWP) models, such as the Weather Research and Forecasting (WRF) model, parameter uncertainty in physics parameterization schemes significantly impacts model output. Our study adopts a Bayesian probabilistic a
Externí odkaz:
https://doaj.org/article/e51459fc02f242aab4b9e477adf40815
Publikováno v:
Weather and Climate Extremes, Vol 45, Iss , Pp 100694- (2024)
This study suggests a methodology for probabilistic forecasts of the extreme heat events in East Asia based on an operational global ensemble prediction used by the Korea Meteorological Administration (KMA). It focuses on the medium range of up to 11
Externí odkaz:
https://doaj.org/article/912e561f97bf48008e6c85a42d7c649e