Impact of Data Assimilation Frequency and Observation Location in Thermal Effluent Modeling for Coastal Waters
Abstract This study investigates the application of data assimilation (DA) using the Ensemble Kalman Filter (EnKF) to address the uncertainties associated with modeling the thermal effluents discharged from power and desalination plants into a shallow, tidal bay. A two‐dimensional hydrodynamic model...
Saved in:
Main Authors: | N. Alsulaiman, M. vanReeuwijk, M. D. Piggott |
---|---|
Format: | Article |
Language: | English |
Published: |
American Geophysical Union (AGU)
2025-07-01
|
Series: | Earth and Space Science |
Subjects: | |
Online Access: | https://doi.org/10.1029/2024EA004099 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Application of Ensemble Kalman Filter With Covariance Localization in Data Assimilation of Radiation Belt Electrons
by: Yuan Lei, et al.
Published: (2025-06-01) -
Assimilation of temporal-spatial leaf area index into the CERES-Wheat model with ensemble Kalman filter and uncertainty assessment for improving winter wheat yield estimation
by: He LI, et al.
Published: (2017-10-01) -
Kalman filtering assimilated machine learning methods significantly improve the prediction performance of water quality parameters
by: Zhenyu Gao, et al.
Published: (2025-12-01) -
Improving Soil Moisture Estimation by Integrating Remote Sensing Data into HYDRUS-1D Using an Ensemble Kalman Filter Approach
by: Yule Sun, et al.
Published: (2025-06-01) -
A Model‐Independent Strategy for the Targeted Observation Analysis and Its Application in ENSO Prediction
by: Weixun Rao, et al.
Published: (2025-07-01)