Wolfram for Environmental Science | Things to Try

Make edits and run any piece of code by clicking inside the code and pressing
+
.

Access & Analyze Weather and Climate Data

Retrieve temperature data for a provided location over a specified temporal range:
Run
In[]:=
min=WeatherData
Champaign
CITY
,"MinTemperature",
Wed 1 Jan 2025
,
Thu 1 Jan 2026
,"Day";​​max=WeatherData
Champaign
CITY
,"MaxTemperature",
Wed 1 Jan 2025
,
Thu 1 Jan 2026
,"Day";
Make a time series plot of the data:
Run
In[]:=
DateListPlot​​{min,max},Joined->True,Filling->{1->{2}},​​PlotLegends->SwatchLegend
,
,{"Min °C","Max °C"}
Out[]=
Min °C
Max °C
Import atmospheric
CO
2
concentration data from NOAA as a Tabular object:
Run
In[]:=
noaaCO2Data=CastColumns[Import["https://gml.noaa.gov/webdata/ccgg/trends/co2/co2_mm_mlo.csv","Tabular"],{"year"->"Integer16","Month"->"Integer8"}]
Out[]=
Tabular
Row count: 818
Column count: 8

Plot a time series of atmospheric
CO
2
concentration:
Run
In[]:=
featurekeelingCurve=DateListPlotTake[Normal[Dataset[​​TransformColumns[​​noaaCO2Data,​​"date"->Function[DateObject[{#year,#month},"Month"]]][​​All,{"date","average"}]][All,{#date,#average}&]],-60],

Out[]=

Make Maps and Access Remote Sensing Services

Map global ecological regions such as terrestrial biomes:
Run
In[]:=
biomes=
chaparral biome
BIOME
->
,
desert or dune biome
BIOME
->
,
forest biome
BIOME
->
,
mountain biome
BIOME
->
,
rainforest biome
BIOME
->
,
savanna or grassland biome
BIOME
->
,
taiga biome
BIOME
->
,
tundra biome
BIOME
->
,
scrub forest biome
BIOME
->
;​​​​GeoGraphics[​​{GeoStyling[#〚2〛],EntityValue[#〚1〛,"Polygon"]}&/@biomes,​​GeoBackground->Transparent,ImageSize->450]
Out[]=
Plot a relief map of Illinois:
Run
In[]:=
GeoGraphics
Illinois, United States
ADMINISTRATIVE DIVISION
,GeoBackground->"ReliefMap",GeoZoomLevel->8
Out[]=
Map land cover using ESA data:
Run
In[]:=
LegendedGeoGraphics
Illinois, United States
ADMINISTRATIVE DIVISION
,​​GeoServer->
StringTemplate[
]
,GeoZoomLevel->8,​​SwatchLegend​​
,
,
,
,
,
,
,
,
,
,
,​​{"Tree cover","Shrubland","Grassland","Cropland","Built-up","Bare / sparse vegetation","Snow and ice","Permanent water bodies","Herbaceous wetland","Mangroves","Moss and lichen"},​​LegendLayout->{"Column",1}
Out[]=
Tree cover
Shrubland
Grassland
Cropland
Built-up
Bare / sparse vegetation
Snow and ice
Permanent water bodies
Herbaceous wetland
Mangroves
Moss and lichen

Model Environmental and Ecological Processes

Define a classic Lotka-Volterra predator-prey model:
Run
lotkaVolterra[{xInit_,yInit_},{a_,b_,c_,d_}]:={(*preypopulation*)x'[t]==a*x[t]-b*x[t]*y[t],​​(*predatorpopulation*)y'[t]==-c*y[t]+d*x[t]*y[t],​​(*Initialconditions*)x[0]==xInit,y[0]==yInit}​​​​sys=lotkaVolterra[{10,5},{1.5,1,3,1}];​​​​(*Previewthesystemofdifferentialequations:*)​​Column[sys]