What is he best known for?
The fields of study he is best known for:
- Meteorology
- Remote sensing
- Hydrology
His scientific interests lie mostly in Water content, Meteorology, Remote sensing, Data assimilation and Climatology.
His Water content research is multidisciplinary, relying on both Scatterometer, C band, Soil science and Annual cycle.
His Scatterometer research incorporates themes from Hydrology, Atmospheric sciences and Moisture.
The Numerical weather prediction research Clément Albergel does as part of his general Meteorology study is frequently linked to other disciplines of science, such as Interpolation and Extended Kalman filter, therefore creating a link between diverse domains of science.
His research investigates the link between Numerical weather prediction and topics such as Soil water that cross with problems in Flood forecasting, Earth observation and In situ.
Clément Albergel has included themes like Hydrometeorology, Albedo, Snow, Snowpack and Climate model in his Climatology study.
His most cited work include:
- ESA CCI Soil Moisture for improved Earth system understanding : State-of-the art and future directions (360 citations)
- ERA-Interim/Land: a global land surface reanalysis data set (326 citations)
- Evaluation of the ESA CCI soil moisture product using ground-based observations (322 citations)
What are the main themes of his work throughout his whole career to date?
Clément Albergel mainly focuses on Water content, Data assimilation, Remote sensing, Climatology and Leaf area index.
The various areas that Clément Albergel examines in his Water content study include Soil science, Soil water, Meteorology and Atmospheric sciences.
His study in the field of Numerical weather prediction is also linked to topics like Product and Data set.
His Data assimilation study incorporates themes from Snow and Evapotranspiration.
The study incorporates disciplines such as Scatterometer, Earth observation and Brightness temperature in addition to Remote sensing.
His Climatology research integrates issues from Atmospheric model, Hydrology, Precipitation and Water cycle.
He most often published in these fields:
- Water content (59.86%)
- Data assimilation (36.05%)
- Remote sensing (34.69%)
What were the highlights of his more recent work (between 2019-2021)?
- Water content (59.86%)
- Climatology (27.89%)
- Remote sensing (34.69%)
In recent papers he was focusing on the following fields of study:
His main research concerns Water content, Climatology, Remote sensing, Data assimilation and Soil water.
His Water content research includes elements of Surface runoff, Atmospheric sciences, Flash flood and Soil horizon.
His work on Numerical weather prediction as part of general Climatology research is frequently linked to Leaf area index, Scale and Elevation, thereby connecting diverse disciplines of science.
The Data assimilation study combines topics in areas such as Snow and Evapotranspiration.
His Soil water study is related to the wider topic of Soil science.
His Soil science study integrates concerns from other disciplines, such as Scatterometer and Change detection.
Between 2019 and 2021, his most popular works were:
- Validation practices for satellite soil moisture retrievals: what are (the) errors? (21 citations)
- Challenges for drought assessment in the Mediterranean region under future climate scenarios (13 citations)
- SMOS brightness temperature forward modelling and long term monitoring at ECMWF (9 citations)
In his most recent research, the most cited papers focused on:
- Meteorology
- Remote sensing
- Hydrology
The scientist’s investigation covers issues in Water content, Leaf area index, Climatology, Remote sensing and Atmospheric model.
Clément Albergel has researched Water content in several fields, including Soil science, Soil water and Change detection.
Leaf area index is connected with Vegetation type, Atmospheric sciences, Evapotranspiration, Data assimilation and Soil horizon in his research.
His study in Brightness temperature extends to Climatology with its themes.
Clément Albergel studies Remote sensing, namely Synthetic aperture radar.
His Atmospheric model study frequently links to other fields, such as Weather and climate.
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