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Earth System Modeling , Observations and Data Assimilation
Submission Deadline: Jul. 15, 2020

This special issue currently is open for paper submission and guest editor application.

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Lead Guest Editor
Muhammed Eltahan
Forschungszentrum Jülich, Institute of Bio- and Geosciences (IBG-3), Jülich, Germany
Guest Editor
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Guidelines for Submission
Manuscripts can be submitted until the expiry of the deadline. Submissions must be previously unpublished and may not be under consideration elsewhere.
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Published Papers
The special issue currently is open for paper submission. Potential authors are humbly requested to submit an electronic copy of their complete manuscript by clicking here.

Special Issue Flyer (PDF)

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Special Issue

Introduction
Earth system models can be used on different types of studies on weather and climate scale. They in global and regional scale have a lot of challenges and open Challenges issues regarding modeling different physical and chemical process such Precipitation, transpiration, Dust storms, and water and energy budget in order to improve numerical model capabilities. Many innovative methods had been used in order to improve existing modeling system performance. One of these methods is data assimilation for the different types of ground and remote sensing observations. Different type of Algorithms from least square approach till the Kalman filters and their families had been developed but still not all of them are well presented and investigated on different temporal and spatial scales on the earth system.
Due to very huge amount and different types of the available ground and remote sensing observations, new innovative approaches had been initiated such applying artificial intelligence (AI) specially , deep learning algorithms to either build new data driven models or enhance the existing numerical models by modifying/replacing some internal implemented physical schemes with new one based on different AI approaches.
In this special issue, different types of work related to any type of earth modeling either numerical or data driven models are welcomed using any kind of ground/remote sensing observation in order to study different physics on weather or climate scale.

Aims and Scope:

  1. Earth system modeling
  2. Data Assimilation
  3. Observations and Remote Sensing
  4. Deep learning for Earth system modeling
  5. Weather and Climate temporal Scale
  6. Global and Regional Scale events
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