Zobrazeno 1 - 10
of 46
pro vyhledávání: '"YUANFU XIE"'
Publikováno v:
Atmospheric and Oceanic Science Letters, Vol 11, Iss 4, Pp 352-357 (2018)
The Ensemble Transformation (ET) method and its variation ET-based Sensitivity (ETS) method have been used in adaptive observation studies. However, the solution of the ensemble transformation matrix in the ET and ETS methods is not unique. A general
Externí odkaz:
https://doaj.org/article/461e9d6944364b3ca7b095148dd3c041
Publikováno v:
Atmosphere, Vol 13, Iss 1, p 127 (2022)
The combination of techniques that incorporate observational data may improve numerical weather prediction forecasts; thus, in this study, the methodology and potential value of one such combination were investigated. A series of experiments on a sin
Externí odkaz:
https://doaj.org/article/b78fd760d033479688d5e32a4db14fcf
Autor:
Yuanfu Xie
Publikováno v:
Atmosphere, Vol 10, Iss 4, p 179 (2019)
Z-grid finite volume models conserve all-scalar quantities as well as energy and potential enstrophy and yield better dispersion relations for shallow water equations than other finite volume models, such as C-grid and C-D grid models; however, they
Externí odkaz:
https://doaj.org/article/c85f2e9e2a8e4ebf94641b898527198c
Publikováno v:
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 65, Iss 0, Pp 1-22 (2013)
An Observing System Simulation Experiment (OSSE) system has been implemented at the National Oceanographic and Atmospheric Administration Earth Systems Research Laboratory in the US as part of an international Joint OSSE effort. The setup of the OSSE
Externí odkaz:
https://doaj.org/article/27c649135c61457dbfe11935fafab7a2
Autor:
Hongli Fu, Jinkun Yang, Wei Li, Xinrong Wu, Guijun Han, Yuanfu Xie, Shaoqing Zhang, Xuefeng Zhang, Yingzhi Cao, Xiaoshuang Zhang
Publikováno v:
Advances in Meteorology, Vol 2017 (2017)
This study addresses how to maintain oceanic mixing along potential density surface in ocean data assimilation (ODA). It is well known that the oceanic mixing across the potential density surface is much weaker than that along the potential density s
Externí odkaz:
https://doaj.org/article/3c30ebbb48964032b9f4abf2d77b4450
Publikováno v:
Advances in Meteorology, Vol 2016 (2016)
Extracting multiple-scale observational information is critical for accurately reconstructing the structure of mesoscale circulation systems such as typhoon. The Space and Time Mesoscale Analysis System (STMAS) with multigrid data assimilation develo
Externí odkaz:
https://doaj.org/article/417f507d26e6420cbae3da38c7ff47e8
Publikováno v:
Advances in Meteorology, Vol 2015 (2015)
Externí odkaz:
https://doaj.org/article/dc193d63c5484609bb5129a92ee53b1a
Autor:
Yuanfu Xie, Zilong Qin
Publikováno v:
Journal of Meteorological Research. 35:775-788
High-resolution global non-hydrostatic gridded dynamic models have drawn significant attention in recent years in conjunction with the rising demand for improving weather forecasting and climate predictions. By far it is still challenging to build a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c628798fce27bbe6f430d964bf67721
https://doi.org/10.1007/s13351-021-0202-3
https://doi.org/10.1007/s13351-021-0202-3
Publikováno v:
Weather and Forecasting.
This paper reports the assimilation of cloud optical depth datasets into a variational data assimilation system to improve cloud ice, cloud water, rain, snow, and graupel analysis in extreme weather events for improving forecasts. A cloud optical dep
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09e743676271272748a514bb77051caf
https://doi.org/10.1175/waf-d-20-0238.1
https://doi.org/10.1175/waf-d-20-0238.1
Autor:
Yuanfu Xie
In order to provide multiple choices of dynamic cores for the next generation global numerical prediction system at Chinese Meteorological Administration (CMA), a Z-grid based dynamic core is under development. Among other important features of a Z-g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed42bae377006e3c2c39adc07457f64f
https://doi.org/10.5194/egusphere-egu2020-21150
https://doi.org/10.5194/egusphere-egu2020-21150
