Energy Justice Analysis of Climate Data with ClimRR

Sam Foreman

Continued Analysis

August 7, 2023

import matplotlib.pyplot as plt
import geopandas as gpd

from typing import Optional
from enrich.style import STYLES
from rich.theme import Theme
from rich.console import Console

from ClimRR import (
    set_plot_style,
    get_logger,
    DEFAULT_CRS,
)
from ClimRR.data import (
    load_shapefile,
    load_csvs,
    load_counties,
    load_chicago_data
)

set_plot_style()
theme = Theme(STYLES)
log = get_logger('ClimRR')
console = Console(theme=theme, log_path=False, markup=True)

/Users/samforeman/miniconda3/envs/ClimRR/lib/python3.11/site-packages/pyproj/__init__.py:91: UserWarning: Valid PROJ data directory not found. Either set the path using the environmental variable PROJ_DATA (PROJ 9.1+) | PROJ_LIB (PROJ<9.1) or with `pyproj.datadir.set_data_dir`.
  warnings.warn(str(err))

shape = load_shapefile()
data = load_csvs(shape)
chidata = load_chicago_data(shape.crs)

data['FireWeatherIndex_Wildfire'].shape=(62834, 35)

data['HeatingDegreeDays'].shape=(62834, 10)

data['AnnualTemperatureMinimum'].shape=(62834, 18)

data['SeasonalTemperatureMaximum'].shape=(62834, 27)

data['ConsecutiveDayswithNoPrecipitation'].shape=(55896, 19)

data['SeasonalTemperatureMinimum'].shape=(62834, 27)

data['WindSpeed'].shape=(62834, 18)

data['AnnualTemperatureMaximum'].shape=(62834, 18)

data['Precipitation_inches_AnnualTotal'].shape=(55896, 18)

counties = load_counties(shape.crs)

illinois = counties[counties["ste_name"] == "['Illinois']"]
wind_il = data["WindSpeed"].overlay(illinois, how='intersection')

fig, ax = plt.subplots(figsize=(10, 7))
wind_il.plot(ax=ax, column='hist', legend=True)
ax.set_axis_off()
plt.show()

console.log("\n".join(list(data.keys())))

[07:00:13] FireWeatherIndex_Wildfire                                                         
           HeatingDegreeDays                                                                 
           AnnualTemperatureMinimum                                                          
           SeasonalTemperatureMaximum                                                        
           ConsecutiveDayswithNoPrecipitation                                                
           SeasonalTemperatureMinimum                                                        
           WindSpeed                                                                         
           AnnualTemperatureMaximum                                                          
           Precipitation_inches_AnnualTotal

def get_state(
        state: str,
        counties: Optional[gpd.GeoDataFrame] = None,
) -> gpd.GeoDataFrame:
    counties = load_counties(DEFAULT_CRS) if counties is None else counties
    assert counties is not None and isinstance(counties, gpd.GeoDataFrame)
    assert counties.crs == DEFAULT_CRS
    return counties[counties["ste_name"] == f"['{state}']"]


def get_variable_for_state(
        data: gpd.GeoDataFrame,
        state: gpd.GeoDataFrame,
) -> gpd.GeoDataFrame:
    """Returns `data.overlay(state, how='intersection')`"""
    return data.overlay(state, how='intersection')

california = get_state('California', counties=counties)

fig, ax = plt.subplots(figsize=(10, 7))
ax = california.plot(ax=ax)
ax.set_axis_off()

cali_temp_max = get_variable_for_state(
    data["SeasonalTemperatureMaximum"],
    california
)

fig, ax = plt.subplots(figsize=(16, 7), nrows=2, ncols=3, sharey='row', sharex='col')
ax = ax.flatten()
ax0 = cali_temp_max.plot(ax=ax[0], column='hist_winter', legend=True)
ax0.set_title('Winter [Historical]')
ax0.set_axis_off()
ax1 = cali_temp_max.plot(ax=ax[1], column='rcp85_midc_winter', legend=True)
ax1.set_axis_off()
ax1.set_title('Winter [RCP85: Mid-Century]')
ax2 = cali_temp_max.plot(ax=ax[2], column='rcp85_endc_winter', legend=True)
ax2.set_axis_off()
ax2.set_title('Winter [RCP85: End-Century]')

ax3 = cali_temp_max.plot(ax=ax[3], column='hist_summer', legend=True)
ax3.set_title('Summer [Historical]')
ax3.set_axis_off()
ax4 = cali_temp_max.plot(ax=ax[4], column='rcp85_mid_summer', legend=True)
ax4.set_axis_off()
ax4.set_title('Summer [RCP85: Mid-Century]')
ax5 = cali_temp_max.plot(ax=ax[5], column='rcp85_end_summer', legend=True)
ax5.set_axis_off()
ax5.set_title('Summer [RCP85: End-Century]')
plt.tight_layout()

Citation

BibTeX citation:

@online{foreman2023,
  author = {Foreman, Sam},
  title = {Energy {Justice} {Analysis} of {Climate} {Data} with
    {ClimRR}},
  date = {2023-08-07},
  url = {https://saforem2.github.io/climate-analysis},
  langid = {en}
}

For attribution, please cite this work as:

Foreman, Sam. 2023. “Energy Justice Analysis of Climate Data with ClimRR.” Intro to HPC Bootcamp @ NERSC: ClimRR. August 7, 2023. https://saforem2.github.io/climate-analysis.