OOIR: Observatory of International Research

Papers

(The H4-Index of Journal of Advances in Modeling Earth Systems is 34. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)

Article	Citations
The GFDL Earth System Model Version 4.1 (GFDL‐ESM 4.1): Overall Coupled Model Description and Simulation Characteristics	350
WeatherBench: A Benchmark Data Set for Data‐Driven Weather Forecasting	194
An Unprecedented Set of High‐Resolution Earth System Simulations for Understanding Multiscale Interactions in Climate Variability and Change	132
CMIP6 Simulations With the CMCC Earth System Model (CMCC‐ESM2)	115
Data‐Driven Medium‐Range Weather Prediction With a Resnet Pretrained on Climate Simulations: A New Model for WeatherBench	79
Description and Climate Simulation Performance of CAS‐ESM Version 2	69
Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0	67
Sub‐Seasonal Forecasting With a Large Ensemble of Deep‐Learning Weather Prediction Models	67
Machine Learning for Model Error Inference and Correction	64
Representation of Plant Hydraulics in the Noah‐MP Land Surface Model: Model Development and Multiscale Evaluation	61
ENSO and Pacific Decadal Variability in the Community Earth System Model Version 2	59
An Introduction to the E3SM Special Collection: Goals, Science Drivers, Development, and Analysis	58
Mean Squared Error, Deconstructed	58
The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation	52
Simulations With the Marine Biogeochemistry Library (MARBL)	52
CMIP6 Historical Simulations (1850–2014) With GISS‐E2.1	52
Machine Learning the Warm Rain Process	46
Potential and Limitations of Machine Learning for Modeling Warm‐Rain Cloud Microphysical Processes	46
A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts	44
Performance of the Taiwan Earth System Model in Simulating Climate Variability Compared With Observations and CMIP6 Model Simulations	44
Machine Learning Emulation of Gravity Wave Drag in Numerical Weather Forecasting	43
Are Terrestrial Biosphere Models Fit for Simulating the Global Land Carbon Sink?	43
Stochastic‐Deep Learning Parameterization of Ocean Momentum Forcing	43
Convection‐Permitting Simulations With the E3SM Global Atmosphere Model	42
Evaluation of CMIP6 Global Climate Models for Simulating Land Surface Energy and Water Fluxes During 1979–2014	42

Deep Learning for Improving Numerical Weather Prediction of Heavy Rainfall	39
Data‐Driven Super‐Parameterization Using Deep Learning: Experimentation With Multiscale Lorenz 96 Systems and Transfer Learning	39
Global Prediction of Soil Saturated Hydraulic Conductivity Using Random Forest in a Covariate‐Based GeoTransfer Function (CoGTF) Framework	38
LGM Paleoclimate Constraints Inform Cloud Parameterizations and Equilibrium Climate Sensitivity in CESM2	37
Process‐Based Climate Model Development Harnessing Machine Learning: I. A Calibration Tool for Parameterization Improvement	36
Accelerating Radiation Computations for Dynamical Models With Targeted Machine Learning and Code Optimization	35
Correcting Coarse‐Grid Weather and Climate Models by Machine Learning From Global Storm‐Resolving Simulations	35
The German Climate Forecast System: GCFS	34
Improved Quantification of Ocean Carbon Uptake by Using Machine Learning to Merge Global Models and pCO₂ Data	34
Urban Morphological Parameters of the Main Cities in China and Their Application in the WRF Model	34
One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global Models	34