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Looking 50 Years in the Future with NASA Earth Scientists

Looking 50 Years in the Future with NASA Earth Scientists

In the 50 years since the first Earth Day, the view from space has revolutionized our understanding of Earth’s interconnected atmosphere, oceans, freshwater, ice, land, ecosystems and climate that have helped find solutions to environmental challenges.

If NASA’s Earth science has changed this much in 50 years, what will it look like in 50 more years?

We asked some researchers what they thought. Here are their answers, in their own words.


Mahta Moghaddam is a professor of electrical and computer engineering at the University of Southern California. She’s building a system that helps sensors sync their measurements.

I am interested in creating new ways to observe the Earth. In particular, my team and I are building and expanding a system that will allow scientists to better study soil moisture. Soil moisture plays a vital role in the water and energy cycle and drives climate and weather patterns. When soil is wet and there is enough solar radiation, water can evaporate and form clouds, which precipitate back to Earth. Soil also feeds us – it nourishes our crops and sustains life on Earth. It’s one of the foundations of life! We need to characterize and study soil in order to feed billions of people now and in the future.


Our novel tool aims to observe changes in soil moisture using sensors that talk to each other and make decisions in real time. For instance, if one sensor in a crop field notes that soil is dry in a plot, it could corroborate it with other sensors in the area and then notify a resource manager or decision maker that an area needs water. Or if a sensor in another location senses that soil moisture is changing quickly due to rain or freeze/thaw activity, it could send a command to launch a drone or even to notify satellites to start observing a larger region. We live in one big, connected world, and can and will use many different scales of observations – local to global – from point-scale in-situ sensors to the scales that can be covered by drones, airplanes, and satellites. In just a few years from now, we might see much more vastly automated systems, with some touching not only Earth observations, but other parts of our lives, like drone deliveries of medical tests and supplies.


Odele Coddington is a scientist at the Laboratory for Atmospheric and Space Physics at the University of Colorado, Boulder. She’s building an instrument to measure how much solar energy Earth reflects back into space.

My research is focused on the Earth system response to the Sun’s energy. I spend half of my time thinking about the amount and variability of the Sun’s energy, also known as the solar irradiance. I’m particularly interested in the solar spectral irradiance, which is the study of the individual wavelengths of the Sun’s energy, like infrared and ultraviolet. On a bright, clear day, we feel the Sun’s warmth because the visible and infrared radiation penetrate Earth’s atmosphere to reach the surface. Without the Sun, we would not be able to survive. Although we’ve been monitoring solar irradiance for over 40 years, there is still much to learn about the Sun’s variability. Continuing to measure the solar irradiance 50 years from now will be as important as it is today.


I spend the other half of my time thinking about the many processes driven by the Sun’s energy both within the atmosphere and at the surface. I’m excited to build an instrument that will measure the integrated signal of these processes in the reflected solar and the emitted thermal radiation. This is my first foray into designing instrumentation and it has been so invigorating scientifically. My team is developing advanced technology that will measure Earth’s outgoing radiation at high spatial resolution and accuracy. Our instrument will be small from the onset, as opposed to reducing the size and mass of existing technology. In the future, a constellation of these instruments, launched on miniaturized spacecraft that are more flexible to implement in space, will give us more eyes in the sky for a better understanding of how processes such as clouds, wildfires and ice sheet melting, for instance, alter Earth’s outgoing energy.


Sujay Kumar is a research physical scientist at NASA’s Goddard Space Flight Center. He works on the Land Information System.

Broadly, I study the water cycle, and specifically the variability of its components. I lead the development of a modeling system called the Land Information System that isolates the land and tries to understand all the processes that move water through the landscape. We have conceptual models of land surface processes, and then we try to constrain them with satellite data to improve our understanding. The outputs are used for weather and climate modeling, water management, agricultural management and some hazard applications.


I think non-traditional and distributed platforms will become more the norm in the future. So that could be things like CubeSats and small sats that are relatively cheaper and quicker than large satellites in terms of how much time it takes to design and launch. One of the advantages is that because they are distributed, you’re not relying on a single satellite and there will be more coverage. I also think we’ll be using data from other “signals of opportunity” such as mobile phones and crowd-sourced platforms. People have figured out ways to, for example, retrieve Earth science measurements from GPS signals.

I feel like in the future we will be designing our sensors and satellites to be adaptive in terms of what the observational needs on the ground are. Say a fire or flood happens, then we will tell the satellite to look over there more intensely, more frequently so that we can benefit. Big data is a buzzword, but it’s becoming a reality. We are going to have a new mission call NISAR that’s going to collect so much data that we really have to rethink how traditional modeling systems will work. The analogy I think of is the development of a self-driving car, which is purely data driven, using tons and tons of data to train the model that drives the car. We could possibly see similar things in Earth science.

Hear from more NASA scientists on what they think the future will bring for Earth science: 

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