Identification

Title

Improving climate bias and variability via CNN‐based state‐dependent model‐error corrections

Abstract

We develop an approach to correct biases in the atmospheric component of the Community Earth System Model using convolutional neural networks (CNNs) to create a corrective model parameterization for online bias reduction. By predicting systematic nudging increments derived from nudging toward the ERA5‐reanalysis, our method dynamically adjusts the model state, outperforming traditional corrections based on climatological increments alone. Our results show significant root mean squared error improvements across all state variables, with land precipitation biases reduced by 25%–35%, seasonally dependent. Notably, we observe an improvement to the Madden‐Julian Oscillation (MJO), where the CNN‐corrected model successfully propagates the MJO across the maritime continent, a challenge for many current climate models. This advancement underscores the potential of using CNNs for real‐time model correction, providing a robust framework for improving climate simulations. This advancement highlights the potential of CNNs for real‐time model correction, improving climate simulations and bridging observed and simulated dynamics.

Resource type

document

Resource locator

Unique resource identifier

code

https://n2t.net/ark:/85065/d7dz0dqw

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

Resource Type

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Temporal reference

Temporal extent

Begin position

End position

Dataset reference date

date type

publication

effective date

2025-03-28T00:00:00Z

Frequency of update

Quality and validity

Lineage

Conformity

Data format

name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

<span style="font-family:Arial;font-size:10pt;font-style:normal;" data-sheets-root="1">Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</span>

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact