What is he best known for?
The fields of study he is best known for:
- Statistics
- Ecology
- Meteorology
Ming Pan mainly investigates Climatology, Data assimilation, Meteorology, Precipitation and Atmospheric sciences.
Ming Pan combines subjects such as Quantitative precipitation forecast, Tropical and subtropical dry broadleaf forests, Snow cover and Scale with his study of Climatology.
The various areas that Ming Pan examines in his Data assimilation study include Streamflow, Surface runoff, Ensemble Kalman filter, Water cycle and Bowen ratio.
His work in Meteorology tackles topics such as Remote sensing which are related to areas like Water balance and Kalman filter.
His Precipitation research is multidisciplinary, incorporating perspectives in Tropical savanna climate and Tropical ecology.
Ming Pan has researched Atmospheric sciences in several fields, including Hydrology, Hydrology, Evapotranspiration and Vegetation, Normalized Difference Vegetation Index.
His most cited work include:
- The multi‐institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system (916 citations)
- Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling (248 citations)
- Multi-decadal trends in global terrestrial evapotranspiration and its components (217 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Remote sensing, Climatology, Meteorology, Water content and Precipitation.
As a part of the same scientific study, Ming Pan usually deals with the Remote sensing, concentrating on Evapotranspiration and frequently concerns with Water balance, Water cycle, Atmospheric sciences and Eddy covariance.
His work deals with themes such as Streamflow and Climate model, which intersect with Climatology.
His study in Data assimilation and Climate Forecast System is carried out as part of his studies in Meteorology.
His study explores the link between Water content and topics such as Radiometer that cross with problems in Vegetation.
His research in Precipitation intersects with topics in Scale and Scale.
He most often published in these fields:
- Remote sensing (31.11%)
- Climatology (30.00%)
- Meteorology (22.22%)
What were the highlights of his more recent work (between 2019-2021)?
- Climatology (30.00%)
- Remote sensing (31.11%)
- Flood myth (6.11%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Climatology, Remote sensing, Flood myth, Streamflow and Evapotranspiration.
His Climatology research incorporates themes from Climate change and GCM transcription factors.
The Remote sensing research Ming Pan does as part of his general Remote sensing study is frequently linked to other disciplines of science, such as Set, therefore creating a link between diverse domains of science.
The Streamflow study combines topics in areas such as Meteorology, Precipitation and Calibration.
His studies deal with areas such as Discharge and Surface runoff as well as Meteorology.
His Precipitation research includes elements of Global warming and Atmospheric sciences.
Between 2019 and 2021, his most popular works were:
- A Global Drought and Flood Catalogue from 1950 to 2016 (15 citations)
- Global Estimates of Reach‐Level Bankfull River Width Leveraging Big Data Geospatial Analysis (11 citations)
- Quantifying irrigation cooling benefits to maize yield in the US Midwest (11 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Ecology
- Climate change
The scientist’s investigation covers issues in Remote sensing, Precipitation, Streamflow, Climatology and High resolution.
His work carried out in the field of Remote sensing brings together such families of science as Percentile, Spatial heterogeneity, Grid cell and Soil moisture index.
Ming Pan has researched Precipitation in several fields, including Calibration, Pearson product-moment correlation coefficient, Atmospheric sciences, Data assimilation and Irrigation scheduling.
His Streamflow research incorporates elements of Radar, PERSIANN, Calibration and Scale.
His Climatology research includes themes of Cross-validation, Hydrology and Catchment scale.
In his study, Watershed is strongly linked to Water resources, which falls under the umbrella field of Cross-validation.
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