Sensitivity of WRF simulations with the YSU PBL scheme to the lowest model level height for a sea fog event over the Yellow Sea

Y Yang, XM Hu, S Gao, Y Wang - Atmospheric Research, 2019 - Elsevier
The lowest model level is the interface of energy and mass exchanging between the surface
and planetary boundary layer (PBL). Previous studies mostly examined the role of the lowest …

A comparison between 3DVAR and EnKF for data assimilation effects on the Yellow Sea fog forecast

X Gao, S Gao, Y Yang - Atmosphere, 2018 - mdpi.com
The data assimilation method to improve the sea fog forecast over the Yellow Sea is usually
three-dimensional variational assimilation (3DVAR), whereas ensemble Kalman filter …

A revised method with a temperature constraint for assimilating satellite-derived humidity in forecasting sea fog over the Yellow Sea

X Gao, S Gao, Z Li, Y Wang - Frontiers in Earth Science, 2023 - frontiersin.org
Numerical forecast of sea fog is very challenging work because of its high sensitivity to
model initial conditions. For better depicting the humidity structure of the marine atmospheric …

An Online Assimilation Method to Improve the Numerical Forecast of Sea Fog Using Microwave Radiometer‐Retrieved Cloud Water Path

X Gao, X Bao, S Ma, Q Chen… - Journal of Geophysical …, 2024 - Wiley Online Library
Numerical forecast of the sea fog is sensitive to the initial moist stratification within the
marine atmospheric boundary layer (MABL). This study develops an online assimilation …

Impact of Feature-Dependent Static Background Error Covariances for Satellite-Derived Humidity Assimilation on Analyses and Forecasts of Multiple Sea Fog Cases …

Y Yang, S Gao, Y Wang, H Shi - Remote Sensing, 2022 - mdpi.com
Assimilation of satellite-derived humidity with a homogenous static background error
covariance (B) matrix computed over the entire computational domain (Full-B) tends to …

A new observation operator for the assimilation of satellite-derived relative humidity: Methodology and experiments with three sea fog cases over the Yellow Sea

Y Yang, Y Wang, S Gao, X Yuan - Journal of Meteorological Research, 2021 - Springer
Assimilation of satellite-derived relative humidity (Satellite-RH) is capable of improving sea
fog forecasts by saturating the background in the observed foggy areas. Previous studies …

Impact of Multivariate Background Error Covariance on the WRF‐3DVAR Assimilation for the Yellow Sea Fog Modeling

X Gao, S Gao - Advances in Meteorology, 2020 - Wiley Online Library
Numerical modeling of sea fog is highly sensitive to initial conditions, especially to moisture
in the marine atmospheric boundary layer (MABL). Data assimilation plays a vital role in the …

[PDF][PDF] Related articles that may interest you

J WANG, J YANG, HL REN, J LI, Q BAO… - Journal of …, 2021 - researchgate.net
Assimilation of satellite-derived relative humidity (Satellite-RH) is capable of improving sea
fog forecasts by saturating the background in the observed foggy areas. Previous studies …

Improvements of Sea Fog Forecasting Based on CMA-TYM

B Huang, J Zhang, Y Cao, X Gao, S Ma… - Frontiers in Earth …, 2022 - frontiersin.org
Based on the operational version of the China Meteorological Administration Typhoon
Model (CMA-TYM, formerly known as GRAPES_TYM), a series of numerical tests are …