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Yiguo Wang
Bjerknes Centre for Climate Research
12Publications
7H-index
149Citations
Publications 12
Newest
#1Yiguo Wang (Bjerknes Centre for Climate Research)H-Index: 7
#2Francois Counillon (Bjerknes Centre for Climate Research)H-Index: 14
Last.Yu. Guz (Bjerknes Centre for Climate Research)H-Index: 122
view all 8 authors...
This study demonstrates that assimilating SST with an advanced data assimilation method yields prediction skill level with the best state-of-the-art systems. We employ the Norwegian Climate Prediction Model (NorCPM)—a fully-coupled forecasting system—to assimilate SST observations with the ensemble Kalman filter. Predictions of NorCPM are compared to predictions from the North American Multimodel Ensemble (NMME) project. The global prediction skill of NorCPM at 6- and 12-month lead times is high...
Source
#1Fei Li (NILU: Norwegian Institute for Air Research)H-Index: 10
#2Yvan J. Orsolini (NILU: Norwegian Institute for Air Research)H-Index: 21
Last.Yiguo Wang (Remote Sensing Center)H-Index: 7
view all 6 authors...
Source
#1Fengrui Chen (Henan University)H-Index: 7
#2Yu. Guz (Remote Sensing Center)H-Index: 122
Last.Xi Li (WHU: Wuhan University)
view all 5 authors...
Source
#1Anny CazenaveH-Index: 60
#2Benoit MeyssignacH-Index: 22
Last.Bert Wouters (UU: Utrecht University)H-Index: 33
view all 90 authors...
Global mean sea level is an integral of changes occurring in the climate system in response to unforced climate variability as well as natural and anthropogenic forcing factors. Its temporal evolution allows changes (e.g., acceleration) to be detected in one or more components. Study of the sea-level budget provides constraints on missing or poorly known contributions, such as the unsurveyed deep ocean or the still uncertain land water component. In the context of the World Climate Research Prog...
50 CitationsSource
#1Stephanie Gleixner (Geophysical Institute, University of Bergen)H-Index: 3
#2Noel Keenlyside (Geophysical Institute, University of Bergen)H-Index: 40
Last.Ellen Viste (Geophysical Institute, University of Bergen)H-Index: 6
view all 6 authors...
The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June–September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985–2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no mo...
6 CitationsSource
#1Yiguo Wang (Bjerknes Centre for Climate Research)H-Index: 7
#2Francois Counillon (Bjerknes Centre for Climate Research)H-Index: 14
Last.Mao-Lin Shen (Geophysical Institute, University of Bergen)H-Index: 9
view all 6 authors...
Abstract Hydrographic profiles are crucial observational datasets for constraining ocean models and their vertical structure. In this study, we investigate a key implementation setup for optimising their assimilation into isopycnal ocean models. For this purpose, we use the Norwegian Climate Prediction Model (NorCPM), which is a fully-coupled climate prediction system based on the Norwegian Earth System Model and the ensemble Kalman filter. First, we revisit whether it is more accurate to assimi...
7 CitationsSource
#1Francois Counillon (Bjerknes Centre for Climate Research)H-Index: 14
#2Noel Keenlyside (Bjerknes Centre for Climate Research)H-Index: 40
Last.Mats Bentsen (Bjerknes Centre for Climate Research)H-Index: 31
view all 7 authors...
We document a pilot stochastic re-analysis computed by assimilating sea surface temperature (SST) anomalies into the ocean component of the coupled Norwegian Climate Prediction Model (NorCPM) for the period 1950–2010 (doi: 10.11582/2016.00002 ). NorCPM is based on the Norwegian Earth System Model and uses the ensemble Kalman filter for data assimilation (DA). Here, we assimilate SST from the stochastic HadISST2 historical reconstruction. The accuracy, reliability and drift are investigated using...
17 CitationsSource
#1Yiguo Wang (Bjerknes Centre for Climate Research)H-Index: 7
#2Francois Counillon (Bjerknes Centre for Climate Research)H-Index: 14
Last.L. Bertino (Bjerknes Centre for Climate Research)H-Index: 1
view all 3 authors...
8 CitationsSource
#1Lin Wu (CNRS: Centre national de la recherche scientifique)H-Index: 4
#2Grégoire Broquet (CNRS: Centre national de la recherche scientifique)H-Index: 12
Last.Yiguo Wang (CNRS: Centre national de la recherche scientifique)H-Index: 7
view all 8 authors...
1 CitationsSource
#1Yiguo Wang (Remote Sensing Center)H-Index: 7
#2Karine Sartelet (ENPC: École des ponts ParisTech)H-Index: 24
Last.François Dulac (CNRS: Centre national de la recherche scientifique)H-Index: 34
view all 35 authors...
This paper presents a new application of assim- ilating lidar signals to aerosol forecasting. It aims at in- vestigating the impact of a ground-based lidar network on the analysis and short-term forecasts of aerosols through a case study in the Mediterranean basin. To do so, we em- ploy a data assimilation (DA) algorithm based on the opti- mal interpolation method developed in the POLAIR3D chem- istry transport model (CTM) of the POLYPHEMUS air qual- ity modelling platform. We assimilate hourly ...
23 CitationsSource
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