One thing about cloud scientists: They never have their heads in the clouds. They are as grounded as trees. They hold steady to deep investigations of their subject, those mutable gatherings of water droplets and ice particles that the rest of us might only see as bunnies, lions, and camels.
Take Ann Fridlind, for instance, an atmospheric scientist at NASA’s Goddard Institute for Space Studies (NASA GISS) in Manhattan. Over the course of a 15-year career, she has studied an alphabet of natural phenomena related to the billows, towers, funnels, and streaks that interrupt solar radiation and give us precipitation: the mysteries of warm and cold stratiform clouds, deep convection outflow, ice-containing stratus clouds, uncertainty parameters in satellite measurements, cloud types in the Arctic, deep convection clouds, and the near-surface clouds that gather in the planetary boundary layer.
These days, Fridlind is helping develop the next generation of atmospheric models. “Probably the rest of my career I’ll be working in the climate models program,” she said. “It’s where clouds present the biggest challenge.”
Fridlind has cast a wide model net, working on the setup and operation for streamlining NASA’s coupled ocean-atmosphere ModelE single column model, taking part in GWEX model intercomparison projects, and developing observation-based case studies that test the implementation of two-moment microphysics. (That’s a parameterization scheme intended to improve the way clouds and precipitation are represented in mesoscale models of the atmosphere.)
Questions You Always Wanted to Ask
Before adding global modeling work to her career to-do list, Fridlind was busy with smaller-scale cloud studies, often supported by the Atmospheric System Research program of the U.S. Department of Energy (DOE). Her latest ASR grant uses a multi-scale analysis of long-term data sets with the intention of improving how warm and mixed-phase clouds are simulated in general circulation models (GCM).
She will use NASA’s ModelE as a testbed, but adds that the resulting techniques and procedures will be applicable to any GCM. Meanwhile, Fridlind will mine shallow-cloud statistics from the DOE’s Atmospheric Radiation Measurement (ARM) Facility, especially archived data from ARM observation sites in Alaska, Oklahoma, and the Azores.
Shallow clouds, after all, have radiative impacts on a global scale. Their processes determine most of the cloud water content, and in turn drive the magnitude of global cloud radiative feedback—the coupling of clouds and surface temperatures.
As part of this project, Fridlind and colleagues from Pennsylvania State University and the Brookhaven National Laboratory are using data from ARM’s North Slope of Alaska atmospheric observatory to study cloud types in the Arctic, with ModelE as a testbed for ice nucleation.
“In ice clouds, ice crystal properties are important in general,” she said. “We don’t look at the shape of a cloud and think it looks like a bunny. But we do look at the shape of the crystals inside,” in search of ice crystal properties like size, shape, mass, surface characteristics, and evolution.
The ice-crystal work has already spun off one paper (on single-crystal images) with Fridlind as lead author; a second is on the way this year, she said.
The Alaska study is another example of the way Fridlind works: combining real-world ground and air observations to evaluate the computer-based simulations of GCMs.
That dual appreciation of modeling and observations comes in part from the campaigns Fridlind has taken part in: the Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE, in Key West, Florida); the Mixed-Phase Arctic Cloud Experiment (M-PACE, in Deadhorse, Alaska); the Tropical Warm Pool – International Cloud Experiment (TWP-ICE) and High-Altitude Ice Crystals-High Ice Water Content study (HAIC-HIWC)—both out of Darwin, Australia); and most recently the Observations of Aerosols above Clouds and their Interactions (ORACLES, in Walvis Bay, Namibia).
“There is no better way to immerse oneself in what is known and not known about the cloud system being studied than through the daily experience of the science team’s decisions about what to target,” she said, that and the exciting “quick looks at observations that are completely brand new, and unexpected in some cases.”
Being there—sometimes way out there—makes a difference. “Attending experiments for days on end, side-by-side with investigators who are running instruments, is the best opportunity to develop a relationship of trust with your data sources,” said Fridlind, “and to ask questions you always wanted to ask about instrument performance and scientific objectives. There is so much to learn and plenty of time to do that.”
Getting Here from There
How do you get from a childhood in Tucson, Arizona, to chatting with cloud scientists in Walvis Bay, Namibia?
Fridlind can explain, beginning with an early memory of her Tucson upbringing: “I went to the most wonderful school there,” she said, including a final four years at nationally ranked University High School. “I can’t say enough how important that is.”
Then there were the people who inspired and influenced her early on. Her mother taught history and English, and her father was an architect who had majored in math. A great aunt taught mathematics at Brooklyn College; one grandmother was a geophysicist.
“I got the math gene on both sides,” said Fridlind, explaining one set of inclinations that sent her into the clouds. “I like to say I speak English and math.”
At Stanford University (BS 1992, BA 1992) she majored in both civil engineering and economics, driven by an interest in global development. That included classroom time studying the factors behind famine while at the university’s now-disbanded Food Research Institute.
After graduation, with jobs in the early 1990s hard to come by, Fridlind spent the next three years as an environmental consultant (1992 to 1995), mostly with Louis Berger and Associates in the global firm’s New Jersey office. Such consultancy is not “an uncommon route to atmospheric science,” she said, and her work as a land-atmosphere modeler sharpened her appetite for studies to come. It was a realm of the quotidian: simulations of effluent, building heating systems, and hospital incinerators.
Fridlind returned to graduate school after considering three potential paths: law, economics, and earth science. The third won the race. “I thought it was a better fit,” said Fridlind, of a pursuit in which the quantitative is king, numbers rule, and to most problems “there is an answer.”
Super-Cooled Liquid Clouds
At Stanford, during her 1996 to 2002 studies with mentor Mark Jacobson and others, Fridlind also fully embraced what she had missed as a consultant: the thrill of research, especially the kind packed with practical meaning for the world. Instead of finishing the doctorate fast—her first plan—Fridlind delved into chemistry, along with more fluid mechanics and hydrology.
Her dissertation was on atmospheric aerosols. “Before the ink was dry,” she said of her degree, she was on a plane to Florida for the joint NASA-ARM CRYSTAL-FACE campaign in Key West as a NASA-Ames postdoc looking at clouds related to tropical convection.
At NASA-Ames, the brilliant and energetic Fridlind became a “fresh-out”—a first-year full-time hire “fresh out” of graduate school. In 2005, during a NASA reorganization that made it easier to move around, she went to NASA GISS, making it all the easier to someday go over to the global modeling side of the business.
In models, it is clouds—shallow, middle, and high—that remain one of the enduring challenges to getting things right. How will surface temperatures respond to an anticipated doubling of atmospheric carbon dioxide? How will clouds respond, then factor into climate sensitivity?
Climate models are continually being improved, said Fridlind. For example, improving the representation of super-cooled liquid clouds at high latitudes is a focus of her current ASR-funded project (Multi-Scale Observational Analysis and Modeling to Improve GCM Simulation of Global Shallow Cloud Processes and Feedbacks).
Climate model simulations that agree better with observations of super-cooled liquid water at high latitudes have substantially higher climate sensitivities than models that don’t, she said. That is, such simulations predict that rising CO2 will lead to more warming than most commonly estimated.
“We are focusing our model development on matching observations of super-cooled liquid at ARM’s North Slope of Alaska site, in a region where predicted super-cooled liquid is known to correlate with predicted climate sensitivity,” said Fridlind. “Understanding Earth’s climate sensitivity well is a ‘holy grail’ for climate scientists.”
Meanwhile, the same sentiment applies to her early schooling, her path to the clouds, and to her present work, she said: “I am very grateful.”
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This work was supported by the U.S. Department of Energy’s Office of Science, Office of Biological and Environmental Research as part of the Atmospheric System Research Program.