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Related Concept Videos

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The radiation pressure applied by an electromagnetic wave on a perfectly absorbing surface equals the energy density of the wave. The wave's momentum also gets transferred to the surface when an electromagnetic wave is entirely absorbed by it. The rate at which momentum is transmitted to an absorbing surface perpendicular to the propagation direction equals the force on the surface.
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The average temperature of Earth is the subject of much current discussion. Earth is in radiative contact with both the Sun and dark space; it receives almost all its energy from the radiation of the Sun and reflects some of it into outer space. Dark space is very cold, about 3 K, so Earth radiates energy into it. For instance, heat transfer occurs from soil and grasses, the rate of which can be so rapid that frost can occur on clear summer evenings, even in warm latitudes.
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Related Experiment Video

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Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information
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Remote sensing algorithm for retrieving global-scale sea surface solar irradiance.

Saber Aradpour1, Zhiqiang Deng2

  • 1Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA, USA.

Environmental Monitoring and Assessment
|October 21, 2023
PubMed
Summary
This summary is machine-generated.

A new remote sensing algorithm, the LSU model, accurately retrieves sea surface solar irradiance (SR) using XGBoost. It identifies key atmospheric and oceanic factors, offering globally applicable, high-resolution SR data.

Keywords:
Remote sensingSinkSolar irradianceSourceXGBoost model

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Area of Science:

  • Oceanography
  • Atmospheric Science
  • Remote Sensing

Background:

  • Accurate sea surface solar irradiance (SR) data is crucial for various applications.
  • Existing models may lack accuracy or global applicability.

Purpose of the Study:

  • To develop and validate a novel remote sensing (RS) algorithm for retrieving instantaneous sea surface solar irradiance (SR).
  • To identify key factors influencing SR and assess the model's global applicability.

Main Methods:

  • Utilized the XGBoost (XGB) package in RStudio for algorithm development.
  • Incorporated nine key RS parameters including photosynthetically available radiation (PAR), instantaneous PAR (iPAR), water leaving reflectance, angstrom, aerosol optical thickness (aot_869), and latitude.
  • Trained the LSU model using available RS data and ground-truth solar irradiance data.

Main Results:

  • The LSU model identified PAR, iPAR, latitude, and aot_869 as the most influential parameters.
  • Aerosol optical thickness (aot_869) was the primary atmospheric factor, while PAR, iPAR, and latitude were key oceanic factors.
  • The LSU model demonstrated superior accuracy and a fine resolution (1x1 km) compared to existing SR models.

Conclusions:

  • The LSU model is scientifically sound, incorporating major SR source and sink factors.
  • The model is technically accurate and globally applicable for retrieving instantaneous SR data.
  • This algorithm provides a valuable tool for obtaining global-scale SR data on demand.