Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Liao-Fan Lin"'
Autor:
Stanley G. Benjamin, Tatiana G. Smirnova, Eric P. James, Liao-Fan Lin, Ming Hu, David D. Turner, Siwei He
Publikováno v:
Journal of Hydrometeorology. 23:825-845
Initialization methods are needed for geophysical components of Earth system prediction models. These methods are needed from medium-range to decadal predictions and also for short-range Earth system forecasts in support of safety (e.g., severe weath
Autor:
LIAO-FAN LIN1, ZHAOXIA PU1 zhaoxia.pu@utah.edu
Publikováno v:
Monthly Weather Review. Jul2020, Vol. 148 Issue 7, p2863-2888. 26p.
Autor:
LIAO-FAN LIN1 liaofan.lin@utah.edu, ZHAOXIA PU1
Publikováno v:
Monthly Weather Review. Dec2019, Vol. 147 Issue 12, p4345-4366. 22p.
Publikováno v:
Journal of Hydrometeorology.
Satellite and model precipitation such as the Global Precipitation Measurement (GPM) data are valuable in hydrometeorological applications. This study investigates the performance of various satellite and model precipitation products in Taiwan from 2
Publikováno v:
Journal of Hydrometeorology. 19:2007-2020
Hydrological applications rely on the availability and quality of precipitation products, especially model- and satellite-based products for use in areas without ground measurements. It is known that the quality of model- and satellite-based precipit
Autor:
Zhaoxia Pu, Liao-Fan Lin
Publikováno v:
Journal of Applied Meteorology and Climatology. 57:2507-2529
This study characterizes the spatial and temporal variability of the background error covariance between the land surface soil moisture and atmospheric states for a better understanding of the potentials of assimilating satellite soil moisture data u
Autor:
LIAO-FAN LIN1 liaofan.lin@gatech.edu, EBTEHAJ, ARDESHIR M.2, FLORES, ALEJANDRO N.3, BASTOLA, SATISH1, BRAS, RAFAEL L.1
Publikováno v:
Monthly Weather Review. Dec2017, Vol. 145 Issue 12, p4997-5014. 18p.
Publikováno v:
Monthly Weather Review. 145:4997-5014
This paper presents a framework that enables simultaneous assimilation of satellite precipitation and soil moisture observations into the coupled Weather Research and Forecasting (WRF) and Noah land surface model through variational approaches. The a
Publikováno v:
Water Resources Research. 53:1309-1335
This study characterizes the space-time structure of soil moisture background error covariance and paves the way for the development of a soil moisture variational data assimilation system for the Noah land surface model coupled to the Weather Resear
Publikováno v:
Journal of Hydrometeorology. 16:811-829
The objective of this study is to develop a framework for dynamically downscaling spaceborne precipitation products using the Weather Research and Forecasting (WRF) Model with four-dimensional variational data assimilation (4D-Var). Numerical experim