ICESEE

ICESEE (ICE ShEet state and parameter Estimator) is a data assimilation software framework designed for coupling with ice sheet models such as ISSM, Icepack, and idealized models like Lorenz-96. It provides a modular, extensible platform for applying ensemble-based data assimilation techniques in glaciological modeling and beyond.

What is ICESEE?

ICESEE (ICE ShEet state and parameter Estimator) is a scalable ensemble-based data assimilation framework designed for coupling with ice-sheet, climate, and geophysical models such as ISSM, Icepack, and idealized systems like Lorenz-96.

ICESEE provides a modular and extensible scientific computing infrastructure for ensemble forecasting, uncertainty quantification, parameter estimation, and hybrid physics–AI workflows in large-scale environmental modeling.

The framework supports:

Ensemble-based data assimilation methods
Distributed-memory HPC execution
Cloud-enabled scientific workflows
Cross-language model coupling
AI-enhanced scientific computing and machine learning integration

Getting Started

To get started with ICESEE:

For Cluster installation and runs, see ICESEE-Spack or ICESEE-Containers and for cloud runs, see ICESEE-GHUB

AI/ML Integration

ICESEE is being extended with scientific machine learning and AI-enhanced workflows to support next-generation hybrid physics–AI modeling and scalable intelligent simulation systems.

Current and planned AI/ML capabilities include:

Machine learning–based parameter estimation
Neural-network observation operators
AI-enhanced ensemble initialization
Adaptive covariance and inflation tuning
Surrogate forward models for accelerated simulations
Intelligent workflow automation and HPC optimization
AI-assisted diagnostics and parameter tuning

The AI/ML framework is designed to integrate seamlessly with existing ensemble-based data assimilation workflows while maintaining compatibility with distributed HPC environments and scientific modeling systems.

Supported Models

icepack: PDE-based modeling with Firedrake
issm: Finite-element ice sheet modeling (via MATLAB interface)
lorenz96: Idealized nonlinear DA benchmarking
flowline_model: Simple ice flow simulation

Documentation

Explore the Wiki to find:

Configuration and setup tips
How to implement new models
How to extend or modify filters
Debugging common issues

Key Features

Modular ensemble-based data assimilation framework
Cross-language scientific model coupling
Scalable HPC and distributed-memory workflows
HDF5/NetCDF-based scientific data pipelines
Containerized and cloud-enabled execution
AI/ML-ready scientific workflow infrastructure
Extensible APIs for integrating external models
Support for uncertainty quantification and ensemble forecasting

Future Directions

Integration of scientific machine learning workflows into data assimilation pipelines
Development of neural surrogate models for accelerated ice-sheet simulations
AI-enhanced parameter estimation and adaptive ensemble tuning
Integration with AWS and cloud-native scientific computing environments
Expansion of distributed HPC workflows for large-scale ensemble forecasting
Incorporation into the GHUB online ice-sheet platform
Intelligent workflow orchestration and automated HPC diagnostics

For questions or contributions, please open an issue or pull request on the GitHub repository or contact me at bkyanjo3@gatech.edu

ICESEE is distributed as free and open-source software under a BSD-style license (see LICENSE). All external dependencies, including ISSM, Icepack, and other coupled models, are governed by their own licenses, which are independent of and do not impose restrictions on the ICESEE license.

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