What is MaRTy?
MaRTy is a mobile biometeorological instrument platform that was designed to measure pedestrian thermal comfort. It is a weather device that measures the many factors that contribute to how hot it feels, especially during extreme heat events. Though we typically use air temperature to measure heat, there is another metric that plays an even bigger role in how hot it feels: mean radiant temperature (MRT). MRT is a metric that tells us the total heat load a person would experience in a given location based on the incoming radiation, and it is what MaRTy is named after. To measure MRT, MaRTy has three net radiometers that measure radiation from six directions. MaRTy also measures air temperature, humidity, wind speed and direction, plus it records the GPS coordinates. The ability to measure MRT in real time at various outdoor locations without computer modeling is what makes MaRTy an incredibly useful tool.
MaRTy was developed at Arizona State University in response to a lack of instrumentation that could accurately capture the thermal load—or total stress due to heat—on the human body. MRT is distinct from, though highly related to, the two most common metrics used to measure the Urban Heat Island Effect (UHI): air and land surface temperature. Land surface and air temperatures are useful metrics for large-scale urban heat mitigation plans, however, they have some critical limitations. To implement cooling solutions in cities that target improving the comfort of pedestrians, we must study urban heat on the hyper-local scale.
Both urbanization and climate change are increasing the intensity of extreme heat events. We cannot control when we will have heat waves, but we can control how we build our cities, and urban planners have the ability to reduce the temperature that pedestrians experience during extreme heat events. MaRTy is a tool that informs us on how the built environment can exacerbate heat, the effectiveness of heat mitigation technologies and strategies, and the value of cool spaces on extremely hot day.
Illustration by Fiona McLaughlin
How Does Mean Radiant Temperature Work?
Using MaRTy, MRT is calculated from the combination of radiative inputs from six directions to produce a measurement of the thermal heat load. This calculation is specific to the exact location where MaRTy stands, giving it the ability to capture fine-scale thermal variations between sites. In other words, MRT can distinguish the temperature differences that humans feel depending on a variety of factors, like how sunny or shady it is or how hot the ground beneath them is.
Though we feel a significant difference between the shade and the sun on a hot day, the air temperature might not change very much between the two locations. This is because air temperature is not measuring radiation, and incoming radiation has a very strong influence on the temperature that humans feel. For example, on a cold day, if the sun is shining on your skin, it will make your skin feel warm despite the low air temperature. By measuring incoming radiation from all directions, we are able to get a more accurate picture of how much stress due to heat a person will experience in a specific location.
The air temperature, relative humidity, and wind speed are not a part of the MRT equation, but they are still important metrics to know because they affect our thermoregulation. While radiation is always the dominant factor influencing human comfort in a hot, dry climate like Sacramento, it is especially dominant on days with low windspeeds and low relative humidity (which is typically the case on the hottest days of the year). For an overview of the physical processes behind radiative inputs, air temperature, relative humidity, and wind speed and how they contribute to human thermal comfort, visit this page.
Feels Like Temperature vs Thermal Heat Load
In this graph, we see MRT taken at a transit station in June in the full sun and in the shade. Measurements were taken between 1:00-2:00pm and 3:00-4:00pm. As the sun gets more intense throughout the day, MRT goes up in the sun. The shade, however, blocks most incoming radiation and remains relatively constant despite the increased heat. This demonstrates how powerful the shade can be at reducing the incoming radiation and therefore thermal heat load.
You may notice from the graph that the MRT readings may seem surprisingly high at 40◦C (104◦F) and 70◦C (158◦F), and it is important to understand that this is not a reflection of what the temperature feels like.
Thermoregulation is the human body's process of keeping its core temperature within certain boundaries despite the outside environment. MRT is not a feels like temperature of the location, it is measuring the factor that has the strongest influence on how the human body will thermoregulate. This is why we say MRT measures the thermal heat load. Upon receiving an incoming heat load, the human body will thermoregulate in an attempt to feel more comfortable. A feels like temperature of a given location would account for this thermoregulation process, which differs drastically from person to person based on a variety of factors. MRT, the other metrics measured by MaRTy, and information from passersby collected by heat comfort surveys can be added to a heat index called the Physiologically Equivalent Temperature (PET) to give us an estimate of the feels like temperature based on the human body's thermoregulation process.
Measuring Shade
On its own, MRT cannot determine the relative radiation contributions from nearby surfaces and objects. MaRTy will give you a lower MRT value if you move it from the sun to the shade, but it cannot tell you that the change is due to the shade. In the existing MaRTy literature, MRT data is often combined with fisheye photos of the sky from each collection site. These photos can make great visuals to pair with data. They are either taken with a fisheye lens on a camera pointed directly upwards or generated from Google Street View. If studying the effects of shade on heat discomfort, we can plug the fisheye photos into a computer program that separates the pixels into sky and non-sky, creating a simple fraction for the amount of visible sky in a location called Sky View Factor (SVF). This is a great way to measure the amount of available shade in a location.
Image from Middel et al 2018: Sky View Factor footprints for urban climate modeling. https://doi.org/10.1016/j.uclim.2018.05.004
