Greenhouse Gas Observing Network
Donated on 4/15/2015
Design an observing network to monitor emissions of a greenhouse gas (GHG) in California given time series of synthetic observations and tracers from weather model simulations.
Dataset Characteristics
Multivariate, Time-Series
Subject Area
Climate and Environment
Associated Tasks
Regression
Feature Type
Real
# Instances
2921
# Features
5232
Dataset Information
Additional Information
This data set contains time series of greenhouse gas (GHG) concentrations at 2921 grid cells in California created using simulations of the Weather Research and Forecast model with Chemistry (WRF-Chem). Each grid cell covers an area of 12 km by 12 km, and there is one data file per grid cell. Each file contains 16 time series of GHG concentrations. The data points in the time series are spaced 6 hours apart (4 samples per day) over the period May 10 – July 31, 2010. The first 15 rows are time series of GHG tracers released from 14 distinct spatial regions in California and one outside of California. The last row corresponds to the time series of “synthetic GHG observations†generated with EDGAR emissions of HFC-134a scaled by a factor 0.7 and with noise added. Using this data, the goals are to (1) use inverse methods to determine the optimal values of the weights in the weighted sum of 15 tracers that best matches the synthetic observations, (2) and use optimization methods to determine the best locations to observe GHGs to constrain the inversion. We used a Bayesian method for (1) and genetic algorithms for (2). Further details about the data and methods are given in the publication 'Designing optimal greenhouse gas observing networks that consider performance and cost,' Geoscientific Instrumentation Methods and Data Systems.
Has Missing Values?
No
Variable Information
Each file in the data set is labeled ghg.gid.siteWXYZ.dat, where WXYZ is an integer location ID described in our manuscript. At each location, Rows 1-15: GHG concentrations of tracers emitted from regions 1-15 Row 16: GHG concentrations of synthetic observations Columns 1-327: GHG concentrations every 6 hours from May 10 – July 31, 2010. All GHG concentrations are in units of parts per trillion.
Reviews
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset greenhouse_gas_observing_network = fetch_ucirepo(id=328) # data (as pandas dataframes) X = greenhouse_gas_observing_network.data.features y = greenhouse_gas_observing_network.data.targets # metadata print(greenhouse_gas_observing_network.metadata) # variable information print(greenhouse_gas_observing_network.variables)
Lucas,D.. (2015). Greenhouse Gas Observing Network. UCI Machine Learning Repository. https://doi.org/10.24432/C5JK5M.
@misc{misc_greenhouse_gas_observing_network_328,
author = {Lucas,D.},
title = {{Greenhouse Gas Observing Network}},
year = {2015},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5JK5M}
}Creators
D. Lucas
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.