Showcasing model performance across space and time using single diagrams-Reference-Cited by-同舟云学术

Showcasing model performance across space and time using single diagrams

Published:2023-02 Issue: Volume:181 Page:102150
ISSN:1463-5003
Container-title:Ocean Modelling
language:en
Short-container-title:Ocean Modelling

Author:

Paul Arya^ORCID,M. Afroosa,Baduru Balaji,Paul Biswamoy

Publisher

Elsevier BV

Subject

Atmospheric Science,Geotechnical Engineering and Engineering Geology,Computer Science (miscellaneous),Oceanography

Reference20 articles.

1. Madden-julian oscillation winds excite an intraseasonal see-saw of ocean mass that affects Earth’s polar motion;Afroosa;Commun. Earth Environ.,2021

2. Ensemble based regional ocean data assimilation system for the Indian Ocean: Implementation and evaluation;Baduru;Ocean Model.,2019

3. The Spectral Diagram as a new tool for model assessment in the frequency domain: Application to a global ocean general circulation model with tides;Calim Costa;Comput. Geosci.,2022

4. The ERA-interim reanalysis: Configuration and performance of the data assimilation system;Dee;Q. J. R. Meteorol. Soc.,2011

5. High-resolution operational ocean forecast and reanalysis system for the Indian ocean;Francis;Bull. Am. Meteorol. Soc.,2020

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1. Enhancing the Performance of Machine Learning and Deep Learning-Based Flood Susceptibility Models by Integrating Grey Wolf Optimizer (GWO) Algorithm;Remote Sensing;2024-07-16

2. A new diagram for performance evaluation of complex models;Stochastic Environmental Research and Risk Assessment;2024-03-02

3. The MJO-driven Indo-Pacific barotropic see-saw;Deep Sea Research Part I: Oceanographic Research Papers;2023-09

4. Prediction of groundwater level variations using deep learning methods and GMS numerical model;Earth Science Informatics;2023-08-31