Lei Bi

All‐sky <scp>FY4B</scp> ‐ <scp>GIIRS</scp> infrared hyperspectral satellite data assimilation in the <scp>CMA</scp> ‐ <scp>GFS 4DVar</scp> system. Part <scp>II</scp> : Evaluation

Optimizing Ice Cloud Representations with a Mixed Super-ellipsoidal Scheme using Polarized Radiance Observations

All‐sky <scp>FY4B</scp> ‐GIIRS infrared hyperspectral satellite data assimilation in the <scp>CMA‐GFS</scp> 4DVar system. Part I: Implementation

Scattering-physics-constrained neural network framework for retrieving dust microphysical properties from scattering matrix measurements

Evaluation of Ice Crystal Scattering Models Using Polarimetric Observations

PhySCAT‐Net: A Physics‐Informed Deep Learning Framework for Optimizing Hydrometeor Bulk Scattering Properties Using Satellite Observations

AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE

Efficient Forward Radar Operator Simulations in Melting Layer Scenarios and Evaluations of Melting Layer Scheme in ZJU‐AERO Based on Ground‐Based and Spaceborne Radar Observations

Chlorophyll-a Variation Trends in Marginal Seas: Assessing the Impact of Global warming and Anthropogenic Activities Using Time Series Satellite Data (1998–2020)

Global Polarized Radiance of Ice Clouds in the Visible and Near-Infrared Bands and Optimal Ice Crystal Model Parameters

Application of Deep Learning to Enhance the Computation of Phase Matrices of Nonspherical Atmospheric Particles Across All Size Parameters

Monitoring rapidly evolving dust storms in Northern China from a constellation of GEO and LEO hyperspectral infrared sounders

How machine learning approaches are useful in computing the optical properties of non-spherical particles across a broad range of size parameters?

Uncertainties in laboratory-measured shortwave refractive indices of mineral dust aerosols and derived optical properties: a theoretical assessment

Modeling of Melting Layer in Cross‐Platforms Radar Observation Operator ZJU‐AERO: Multi‐Stage Melting Particle Model, Scattering Computation, and Bulk Parameterization

ZJU-AERO V0.5: an Accurate and Efficient Radar Operator designed for CMA-GFS/MESO with the capability to simulate non-spherical hydrometeors

Inhomogeneous Sea‐Salt Aerosols—A New Strengthening Mechanism for the Western North Pacific Subtropical High

AI-NAOS: An AI-Based Nonspherical Aerosol Optical Scheme for Chemical Weather Model GRAPES_Meso5.1/CUACE

ZJU-AERO V0.5: An Accurate and Efficient Radar Operator Designed for CMA-GFS/MESO with Capability of Simulating Non-spherical Hydrometeors

Single‐Scattering Properties of Encapsulated Fractal Black Carbon Particles Computed Using the Invariant Imbedding T‐Matrix Method and Deep Learning Approaches

Assimilating <scp>FY3D‐MWRI</scp> 23.<scp>8 GHz</scp> observations in the <scp>CMA‐GFS 4DVAR</scp> system based on a pseudo <scp>All‐Sky</scp> data assimilation method

Flexible implementation of the particle shape and internal inhomogeneity in the invariant imbedding T-matrix method.

Quantifying the coherent backscatter enhancement of non-spherical particles with discrete dipole approximation.

The uncertainties in the laboratory-measured short-wave refractive indices of mineral dust aerosols and the derived optical properties: A theoretical assessment

Distinct linear polarization of core-shell particles at near-backscattering directions.

The Liver Tumor Segmentation Benchmark (LiTS)

The Inhomogeneity Effect of Sea Salt Aerosols on the TOA Polarized Radiance at the Scattering Angles Ranging From 170° to 175°

More or Less: How Do Inhomogeneous Sea‐Salt Aerosols Affect the Precipitation of Landfalling Tropical Cyclones?

Lidar Ratio-Depolarization Ratio Relations of Atmospheric Dust Aerosols: The Super-Spheroid Model and High Spectral Resolution Lidar Observations.

Sea Surface Salinity Inversion Model for Changjiang Estuary and Adjoining Sea Area with SMAP and MODIS Data Based on Machine Learning and Preliminary Application