Climate Model Simulation Crashes
Donated on 6/17/2013
Given Latin hypercube samples of 18 climate model input parameter values, predict climate model simulation crashes and determine the parameter value combinations that cause the failures.
Dataset Characteristics
Multivariate
Subject Area
Climate and Environment
Associated Tasks
Classification
Feature Type
Real
# Instances
540
# Features
-
Dataset Information
Additional Information
This dataset contains records of simulation crashes encountered during climate model uncertainty quantification (UQ) ensembles. Ensemble members were constructed using a Latin hypercube method in LLNL's UQ Pipeline software system to sample the uncertainties of 18 model parameters within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). Three separate Latin hypercube ensembles were conducted, each containing 180 ensemble members. 46 out of the 540 simulations failed for numerical reasons at combinations of parameter values. The goal is to use classification to predict simulation outcomes (fail or succeed) from input parameter values, and to use sensitivity analysis and feature selection to determine the causes of simulation crashes. Further details about the data and methods are given in the publication 'Failure Analysis of Parameter-Induced Simulation Crashes in Climate Models,' Geoscientific Model Development (doi:10.5194/gmdd-6-585-2013).
Has Missing Values?
No
Variables Table
Variable Name | Role | Type | Description | Units | Missing Values |
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0 to 10 of 18
Additional Variable Information
The goal is to predict climate model simulation outcomes (column 21, fail or succeed) given scaled values of climate model input parameters (columns 3-20). Column 1: Latin hypercube study ID (study 1 to study 3) Column 2: simulation ID (run 1 to run 180) Columns 3-20: values of 18 climate model parameters scaled in the interval [0, 1] Column 21: simulation outcome (0 = failure, 1 = success)
Dataset Files
File | Size |
---|---|
pop_failures.dat | 244.3 KB |
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset climate_model_simulation_crashes = fetch_ucirepo(id=252) # data (as pandas dataframes) X = climate_model_simulation_crashes.data.features y = climate_model_simulation_crashes.data.targets # metadata print(climate_model_simulation_crashes.metadata) # variable information print(climate_model_simulation_crashes.variables)
Lucas, D., Klein, R., Tannahill, J., Ivanova, D., Brandon, S., Domyancic, D., Zhang, Y., D., D., & D. , D. (2013). Climate Model Simulation Crashes [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5HG71.
Creators
D. Lucas
R. Klein
J. Tannahill
D. Ivanova
S. Brandon
D. Domyancic
Y. Zhang
D. D.
D. D.
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.