Claremont: An Operation Healthy Air Data Story

The data collection period was July – August 2017.

Goal: Does air temperature differ when comparing a backyard, front yard, and neighboring park? To examine this, we looked at three air temperature sensors (called iButtons) in Montclair. Each sensor had been located about 2 meters (~ 7 feet) high in a tree. Here are the sensor numbers and information about the trees each sensor was located in:

  • Sensor # 35: in a backyard. Tree species: Tangelo, 8 feet average tree canopy radius and about 15 feet high.
  • Sensor # 45: in a park (cemetery). Tree species: Plum/cheery tree, 8.6 feet average tree canopy radius and about 16 feet high.
  • Sensor # 47: in the frontyard/street. Tree species: Coast live oak, 24 feet average tree canopy radius and about 35 feet high.

Figure 1.
Upper Left (A): Satellite image of neighborhood in Montclair with locations of sensors.
Upper Right (B): Locations of sensors in Montclair.
Bottom (C): Map from ESMC web site of same neighborhood in Montclair with locations of sensors. HabitatNetwork maps ( of the same neighborhood with the sensor locations.

How does the air temperature vary across the different sensors? Do you have any predictions? For example, do you think backyards or front yards would be cooler during the day? What about night time? What about differences between trees along a road with asphalt which heats up during the sunny day compared to no asphalt?

(Tip while using the ESMC Data Explorer: On the left side you can choose which of the three campaigns you wish to learn about. Get more tips in our “How to Use ESMC iButton Data Explorer” blog.)

Figure 2.

Using the ESMC data tool (top figure), we were able to select a narrow range of dates (to more clearly see the patterns) and look at how air temperature (on the y axis) changed across several days (time is on the x axis).

What patterns do you see? The first most obvious pattern, to me, is how air temperature changes over a 24-hour period, with a high temperature peak between 1 and 4 pm. Air temperature tends to drop thereafter with it being most cool around 5 am.

The sensor that tends to be the hottest during the day is # 37 (located in the medium size tangelo tree in the backyard)—which is 4-8 degrees F hotter than either of the other two trees. The other two trees have similar daytime air temperatures.

However, the coolest location at nighttime is the cemetery park (by 2-6 degrees F). One possible reason may be that the park is surrounded by trees and not asphalt or buildings which themselves tend to radiate out heat at night.

This is just one snapshot comparison across some sensors which has revealed interesting patterns. We are interested in hearing from you about what you find and what questions you might have. Let us know, and we can post your questions/findings! Send your findings and questions to

How to Use ESMC iButton Data Explorer

Dr. Lorena Castro who is part of the research team at University of Iowa led by Dr. Jun Wang developed a website where users can explore the air temperature data from our Operation Healthy Air study. The site has a lot of great features. For instance, you will be able to compare the air temperature from up to six different sensors as well as against a high-resolution air temperature forecast model. You can compare backyards to front yards, streets to city parks or schools, nighttime to daytime, as well as data across days. This post is to give you some tips on how to effectively use the tool. For clarity, the iButton is the name of the air temperature sensor we used in OHA.

First, choose the campaign you are interested in on the left-hand side:

Campaign 1 – Long Beach (June 2017)

Campaign 2 – Inland Empire (July-August 10th, 2017)

Campaign 3 – Inland Empire (August 15th-Sept 30th2017)

After selecting a campaign, you can click on the sensors you interested in displaying.

You can visualize up to 6 sensors at the same time by scrolling down and selecting “More than one button.”

You can add weather forecasted data for that location by clicking “Model data.”

You can also change the range of dates you want to display. Helpful tip: by keeping a narrower timeframe, you get to see many patterns more clearly.

Learn more about the other tools available through the California real time ESMC site developed by the University of Iowa by exploring other tabs at the top of the website.