Biblio
Filters: Author is Yiguo Wang [Clear All Filters]
A downscaling-merging method for high-resolution daily precipitation estimation. Journal of Hydrology 581, (2019).
Downscaling satellite-derived daily precipitation products with an integrated framework. International Journal of Climatology (2018).doi:10.1002/joc.5879
Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian climate prediction model. Tellus. Series A, Dynamic meteorology and oceanography 68:32437, (2016).
Seasonal to decadal predictions of regional Arctic sea ice by assimilating sea surface temperature in the Norwegian Climate Prediction Model. Climate Dynamics (2020).doi:10.1007/s00382-020-05196-4
Seasonal predictability of Kiremt rainfall in coupled general circulation models. Environmental Research Letters 12, (2017).
The mean state and variability of the North Atlantic circulation: A perspective from ocean reanalyses. Journal of Geophysical Research (JGR): Oceans 124, (2019).
Basin Interactions and predictability. Interacting Climates of Ocean Basins (2020).
Impact of ocean and sea ice initialisation on seasonal prediction skill in the Arctic. Journal of Advances in Modeling Earth Systems 11, (2019). Abstract
Propagation of Thermohaline Anomalies and their predictive potential along the Atlantic water pathway. Journal of Climate (2021).doi:https://doi.org/10.1175/JCLI-D-20-1007.1
Impact of snow initialization in subseasonal-to-seasonal winter forecasts with the Norwegian Climate Prediction Model. Journal of Geophysical Research (JGR): Atmospheres 124, (2019). Abstract
Assimilation of lidar signals: Application to aerosol forecasting in the western Mediterranean basin. Atmospheric Chemistry and Physics (ACP) 14, (2014).
Seasonal predictions initialised by assimilating sea surface temperature observations with the EnKF. Climate Dynamics 19, (2019).
Modelling and assimilation of lidar signals over Greater Paris during the MEGAPOLI summer campaign. Atmospheric Chemistry and Physics 14, 3511–3532 (2014).
Alleviating the bias induced by the linear analysis update with an isopycnal ocean model. Quarterly Journal of the Royal Meteorological Society 142, (2016). Abstract
Assimilation of ground versus lidar observations for PM$_{10}$ forecasting. Atmospheric Chemistry and Physics 13, 269–283 (2013).
Optimising assimilation of hydrographic profiles into isopycnal ocean models with ensemble data assimilation. Ocean Modelling 114, (2017).
