What is he best known for?
The fields of study he is best known for:
- Meteorology
- Atmosphere
- Troposphere
Fabrizio Sassi mainly investigates Atmospheric sciences, Climatology, Climate model, Stratosphere and Troposphere.
His Climate model investigation overlaps with other disciplines such as Atmosphere, Forcing and Meteorology.
His study in Meteorology is interdisciplinary in nature, drawing from both Internal wave and Geophysics.
Stratosphere is a component of his Quasi-biennial oscillation, Brewer-Dobson circulation, Polar vortex and Sudden stratospheric warming studies.
The various areas that Fabrizio Sassi examines in his Troposphere study include Atmospheric circulation, Convection and Mesosphere.
His Mesosphere research is multidisciplinary, relying on both Meteorological reanalysis and Chemical transport model.
His most cited work include:
- Simulation of secular trends in the middle atmosphere, 1950–2003 (556 citations)
- Recent developments in gravity‐wave effects in climate models and the global distribution of gravity‐wave momentum flux from observations and models (335 citations)
- Sensitivity of chemical tracers to meteorological parameters in the MOZART-3 chemical transport model (328 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Atmospheric sciences, Atmosphere, Stratosphere, Climatology and Climate model.
His Atmospheric sciences research incorporates themes from Ionosphere and Thermosphere.
In Atmosphere, he works on issues like Altitude, which are connected to Latitude.
His Stratosphere study frequently draws connections between adjacent fields such as Aeronomy.
In the field of Climatology, his study on Northern Hemisphere, Extratropical cyclone, Middle latitudes and Brewer-Dobson circulation overlaps with subjects such as Earth's magnetic field.
The concepts of his Troposphere study are interwoven with issues in Atmospheric circulation, Equator and Convection.
He most often published in these fields:
- Atmospheric sciences (77.38%)
- Atmosphere (46.43%)
- Stratosphere (44.05%)
What were the highlights of his more recent work (between 2017-2021)?
- Atmospheric sciences (77.38%)
- Ionosphere (20.24%)
- Thermosphere (32.14%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Atmospheric sciences, Ionosphere, Thermosphere, Atmosphere and Atmospheric model.
His work on Stratopause as part of general Atmospheric sciences research is often related to Climate model, thus linking different fields of science.
Fabrizio Sassi integrates Climate model and Sudden stratospheric warming in his research.
His work in the fields of Ionosphere, such as D region, overlaps with other areas such as Sounding rocket and Radio wave.
His Atmosphere research incorporates elements of Computational physics and Altitude.
His Altitude research is multidisciplinary, incorporating elements of Baroclinity, Forcing, Northern Hemisphere and Space weather.
Between 2017 and 2021, his most popular works were:
- Impact of non-migrating tides on the low latitude ionosphere during a sudden stratospheric warming event in January 2010 (10 citations)
- Simulations of the Boreal Winter Upper Mesosphere and Lower Thermosphere with Meteorological Specifications in SD-WACCM-X (7 citations)
- Whole Atmosphere Coupling on Intraseasonal and Interseasonal Time Scales: A Potential Source of Increased Predictive Capability (6 citations)
In his most recent research, the most cited papers focused on:
- Meteorology
- Atmosphere
- Troposphere
The scientist’s investigation covers issues in Atmosphere, Atmospheric sciences, Climate model, Sudden stratospheric warming and Coupling.
As part of his studies on Atmosphere, he frequently links adjacent subjects like Stratosphere.
His work deals with themes such as TEC, Total electron content, Ionosphere and Atmospheric model, which intersect with Atmospheric sciences.
He integrates Climate model with Data assimilation in his study.
His Coupling research spans across into fields like Predictive capability, Potential source and Computational physics.
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