A5011787930- Meteorological Phenomena and Simulations
- Precipitation Measurement and Analysis
- Climate variability and models
- Hydrology and Watershed Management Studies
- Cryospheric studies and observations
- Soil Moisture and Remote Sensing
- Hydrological Forecasting Using AI
- Flood Risk Assessment and Management
- Hydrology and Drought Analysis
- Geophysics and Gravity Measurements
- Climate change and permafrost
- Environmental DNA in Biodiversity Studies
- Scientific Computing and Data Management
- Geographic Information Systems Studies
- Ocean Waves and Remote Sensing
- Fluid Dynamics Simulations and Interactions
- Microbial Community Ecology and Physiology
- Geological Modeling and Analysis
- Environmental Changes in China
- Groundwater flow and contamination studies
- Spectroscopy Techniques in Biomedical and Chemical Research
- Advanced Computational Techniques and Applications
- Environmental Monitoring and Data Management
- Environmental and Agricultural Sciences
- Coastal and Marine Dynamics
Institute of Geology and Geophysics
2025
Chinese Academy of Sciences
2025
Powerchina Huadong Engineering Corporation (China)
2024
PowerChina (China)
2024
NSF National Center for Atmospheric Research
2022-2024
NSF NCAR Climate and Global Dynamics Laboratory
2023-2024
University of Saskatchewan
2019-2024
Chongqing Emergency Medical Center
2024
Chongqing University
2024
Canmore Museum and Geoscience Centre
2020-2024
The goal of this commentary is to critically evaluate the use popular performance metrics in hydrologic modeling. We focus on Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta (KGE) metrics, which are both widely used research practice around world. Our specific objectives are: (a) provide tools that quantify sampling uncertainty metrics; (b) across a large sample catchments; (c) prescribe further is, needed improve estimation, interpretation, large-sample analysis demonstrates there...
Abstract The goal of this study is to quantitatively intercompare the standard products Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) and its successor, Global Measurement (GPM) mission Integrated Retrievals for GPM (IMERG), with a dense gauge network over midlatitude Ganjiang River basin in southeast China. In general, direct comparisons TMPA 3B42V7, 3B42RT, Day-1 IMERG estimates observations an extended period rainy season (from May through...
As the largest and oldest well-preserved impact structure on Moon, South Pole-Aitken (SPA) basin lunar farside is critical for understanding early solar system dynamics history, but accurately determining its age remains challenging. Crater-counting chronology Apollo sample studies propose various SPA-forming ages, which require validation by in situ sampling of SPA basin. Here, we present petrology, geochemistry norite clasts from that were returned Chang'e-6. These norites have highly...
The performance of Day-1 Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) and its predecessor, Tropical Rainfall Measuring Mission (TRMM) Multisatellite Analysis 3B42 Version 7 (3B42V7), was cross-evaluated using data from best-available hourly gauge network over Tibetan Plateau (TP). Analyses three-hourly rainfall estimates in warm season 2014 reveal that IMERG shows appreciably better correlations lower errors than 3B42V7, though with...
Abstract Accurate estimation of precipitation from satellites at high spatiotemporal scales over the Tibetan Plateau (TP) remains a challenge. In this study, we proposed general framework for blending multiple satellite data using dynamic Bayesian model averaging (BMA) algorithm. The blended experiment was performed daily 0.25° grid scale 2007–2012 among Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT and 3B42V7, Climate Prediction Center...
The performance of the latest released Integrated Multi-satellitE Retrievals for GPM mission (IMERG) version 5 (IMERG v5) and TRMM Multisatellite Precipitation Analysis 3B42 7 (3B42 v7) are evaluated compared at multiple temporal scales over a semi-humid to humid climate transition area (Huaihe River basin) from 2015 2017. impacts rainfall rate, latitude elevation on precipitation detection skills also investigated. Results indicate that both satellite estimates showed high Pearson...
Abstract. Precipitation estimates with fine quality and spatio-temporal resolutions play significant roles in understanding the global regional cycles of water, carbon, energy. Satellite-based precipitation products are capable detecting spatial patterns temporal variations at resolutions, which is particularly useful over poorly gauged regions. However, satellite-based indirect precipitation, inherently containing seasonal systematic biases random errors. In this study, focusing on...
Abstract Gridded meteorological estimates are essential for many applications. Most existing datasets deterministic and have limitations in representing the inherent uncertainties from both data methodology used to create gridded products. We develop Ensemble Meteorological Dataset Planet Earth (EM-Earth) precipitation, mean daily temperature, temperature range, dewpoint at 0.1° spatial resolution over global land areas 1950 2019. EM-Earth provides hourly/daily estimates, probabilistic (25...
Abstract Meteorological forcing is a major source of uncertainty in hydrological modeling. The recent development probabilistic large‐domain meteorological data sets enables convenient characterization, which however rarely explored research. This study analyzes how uncertainties affect modeling 289 representative cryosphere basins by the Structure for Unifying Multiple Modeling Alternatives (SUMMA) and mizuRoute models with precipitation air temperature ensembles from Ensemble Data set...
Triple collocation (TC) is a novel method for quantifying the uncertainties of three data sets with mutually independent errors and has been widely used over different geographical fields. Researches in recent years report that TC shows potential merging multiple from sources, while TC-based not precipitation. Using formulation, this study merges precipitation Climate Prediction Center's morphing technique (CMORPH), Precipitation Estimation Remotely Sensed Information using Artificial Neural...
The United States Natural Resources Conservation Service (NRCS) Runoff Curve Number (CN) is the most widely used rainfall-runoff modeling method. hydrologic soil group (HSG), land use/cover, surface condition and antecedent moisture jointly determine CN value. This study aims to update previous global map using recently available geospatial remote sensing data. Based on conventional Department of Agriculture (USDA) National Engineering Handbook Section 4 (NEH-4) standard lookup tables, newly...
Abstract Satellite remote sensing is able to provide information on global rain and snow, but challenges remain in accurate estimation of precipitation rates, particularly snow retrieval. In this work, the deep neural network (DNN) applied estimate rates high latitudes. The reference data for DNN training are provided by two spaceborne radars onboard Global Precipitation Measurement (GPM) Core Observatory CloudSat. Passive microwave from GPM Microwave Imager (GMI), infrared MODerate...
Abstract. Station-based serially complete datasets (SCDs) of precipitation and temperature observations are important for hydrometeorological studies. Motivated by the lack station North America, this study seeks to develop an SCD from 1979 2018 data. The new America (SCDNA) includes daily precipitation, minimum (Tmin), maximum (Tmax) data 27 276 stations. Raw meteorological were obtained Global Historical Climate Network Daily (GHCN-D), Surface Summary Day (GSOD), Environment Change...