A5078364306- Climate variability and models
- Meteorological Phenomena and Simulations
- Oceanographic and Atmospheric Processes
- Hydrological Forecasting Using AI
- Energy Load and Power Forecasting
- Complex Systems and Time Series Analysis
- Tropical and Extratropical Cyclones Research
- Atmospheric and Environmental Gas Dynamics
- Geological and Geophysical Studies
- Environmental Changes in China
- Fault Detection and Control Systems
- Geophysics and Gravity Measurements
- Remote Sensing and Land Use
- Atmospheric Ozone and Climate
- Geomagnetism and Paleomagnetism Studies
- Environmental and Agricultural Sciences
- Plant Water Relations and Carbon Dynamics
Inner Mongolia University
2022-2023
NOAA Geophysical Fluid Dynamics Laboratory
2020
Nanjing University of Information Science and Technology
2015-2020
University Corporation for Atmospheric Research
2020
National Oceanic and Atmospheric Administration
2020
Hainan Meteorology Administration
2020
National Centre for Atmospheric Science
2018-2020
University of Reading
2018-2020
Abstract In the summer of 2018, Northeast Asia experienced a heatwave event that broke existing high-temperature records in several locations Japan, Korean Peninsula, and northeastern China. At same time, an unusually strong Madden–Julian oscillation (MJO) was observed to stay over western Pacific warm pool. Based on reanalysis diagnosis, numerical experiments, assessments real-time forecast data from two subseasonal-to-seasonal (S2S) models, we discovered importance MJO generation this...
Abstract The response of the Madden‐Julian oscillation (MJO) to ocean feedbacks is studied with coupled and uncoupled simulations four general circulation models (GCMs). Monthly mean sea surface temperature (SST) from each model prescribed its respective simulation, ensure identical SST mean‐state low‐frequency variability between simulation pairs. Consistent previous studies, coupling improves model's ability propagate MJO convection beyond Maritime Continent. Analysis moist static energy...
Abstract The oceanic feedback to the atmospheric boreal summer intraseasonal oscillation (BSISO) is examined by diagnosing sea surface temperature (SST) modification of fluxes and moist static energy on scales. SST variability affects latent heat (LH) sensible (SH) fluxes, through its influence air‐sea moisture gradients ( ∆q ∆T , respectively). According bulk formula decomposition, LH mainly determined wind‐driven flux perturbations, while SH more sensitive thermodynamic perturbations....
Abstract We investigated the characteristics and mechanisms of subseasonal precipitation variability in North China during rainy season (June–September). Two dominant intraseasonal modes with periods 8–20 30–60 days were identified via spectral analysis. Together, they explain 62.8% total variability. Nearly all persistent heavy rainfall events observed concurrently enhanced positive phases biweekly or/and 30–60-day modes. To elucidate origins these two variabilities, we performed moisture...
Abstract. The effect of air–sea coupling on simulated boreal summer intraseasonal oscillation (BSISO) is examined using atmosphere–ocean-mixed-layer coupled (SPCAM3-KPP, referred to as SPK throughout) and uncoupled configurations the superparameterized (SP) Community Atmospheric Model, version 3 (SPCAM3, SPA throughout). configuration constrained either observed ocean mean state or from SP with a dynamic (SPCCSM3), understand mean-state biases BSISO. All overestimate subtropical rainfall its...
Abstract Northward‐propagating convection associated with intraseasonal oscillation (ISO) over the South China Sea (SCS) is closely linked to evolution of East rainy season. In this study, we quantitatively examined contribution air‐sea coupling northward propagation SCS based on observational diagnosis and model experiments. While oceanic feedback plays a limited role in Indian Ocean western Pacific ISO, its positive effect ISO much larger nearly comparable that atmospheric internal...
Abstract. The effect of air-sea coupling on the simulated boreal summer intraseasonal oscillation (BSISO) is examined using atmosphere—ocean-mixed-layer coupled (SPCAM3-KPP) and uncoupled configurations Super-Parameterized (SP) Community Atmospheric Model, version 3 (SPCAM3). configuration constrained to either observed ocean mean state or from SP with a dynamic (SPCCSM3), understand biases BSISO in latter. All overestimate subtropical rainfall its variance. simulate realistic northward...