This year, Kaighin McColl published a paper on global distribution and dynamics of surface soil moisture, based on NASA’s SMAP satellite. We decided to ask him a couple of questions about him and his research.
Q: Where are you from, where are you based, and what are your current research interests?
I’m Australian, but moved to Boston about five years ago to start my PhD at MIT. After graduating in September, I’m now a postdoctoral fellow at Harvard’s Department of Earth and Planetary Sciences. I’m interested in turbulent exchanges of water, heat, momentum and scalars between the land and atmosphere, which control the occurrence and severity of droughts, floods and heatwaves (among other things). The turbulent fluxes are often tightly coupled and not well-represented in weather and climate models. To study this system, I use high-resolution simulations of turbulent flows (including the atmosphere) and field observations. I also use and develop satellite observations of soil moisture and vegetation.
Q: What is the take home message of your paper?
Precipitation causes the land surface to get wet. But it can go the other way: a wet land surface can cause rainfall to occur. Evaporation of water from the land surface adds water to the lower atmosphere, which can prime it for rainfall. This leads to feedbacks: rain adds water to the land surface, which is pumped back into the atmosphere, which causes more rain, and so on. Feedbacks like this can prolong droughts, heatwaves and floods, but are poorly represented in weather and climate models. For feedbacks to occur, the land surface has to hold on to water from the atmosphere for a while: if rainwater drains rapidly out of the soil layer, for instance, there’s no time for land-atmosphere feedbacks to take hold. So to identify regions where land-atmosphere feedbacks have the potential to occur, we need to estimate how long the land surface holds on to precipitation (roughly, the ‘memory’ of the storage). Our study maps surface soil moisture memory globally. More broadly, it shows that, while surface soil moisture is a tiny storage in the global water budget (<0.001% of global freshwater by volume), it plays a significant role in the water cycle, retaining a median 14% of precipitation falling on land after three days.
Q: It’s quite extraordinary to publish in such a high impact journal as a student. How did you decide to give it a shot, and how did you experience the publication process compared to “normal” journals?
It was a team effort and I’ve been fortunate to work with very talented colleagues. My Ph.D. advisor, Dara Entekhabi, had the idea that positive increments in the soil moisture time series were an untapped and interesting source of hydrologic information. A few of us in the Entekhabi group (including Hamed Alemohammad and Alex Konings) kicked around ideas about possible applications with Dara for about a year. I’d been thinking about connections between positive increments and soil moisture memory, and we eventually agreed on this as a central storyline for the paper. Ruzbeh Akbar joined the group shortly after and contributed a lot of the data analyses that went in to the paper. The publication process at Nature Geoscience was pretty smooth. We had great reviewers who were thorough and constructive. The editorial decision to send a submitted manuscript out to review depends on a lot of factors beyond your control. We were fortunate to have some luck there.
Q: A common point of criticism on microwave remote sensing soil moisture products is that it’s mainly a measure of moisture in the top centimeters at most. If one is interested in ‘real’ soil moisture, or root zone soil moisture, what can they learn from your paper?
SMAP provides a product with a nominal depth of 5-cm, so we were careful to make the paper about surface soil moisture (SSM) rather than root-zone soil moisture (RZSM). RZSM and SSM can behave differently, and RZSM memory will typically be longer than SSM memory. That being said, in many cases, SSM and RZSM are correlated and SSM observations include information on RZSM, particularly at the large scales of interest in this study. In our paper, we demonstrate analytically that previous estimates of soil moisture memory are likely overestimated, due to a property of the memory metric used. This applies to previous estimates of both SSM and RZSM memory.
Q: In your analysis you masked out areas with a vegetation cover above a certain density. Unfortunately, these areas the ones where information on soil moisture is crucial for food security and ecosystem function. What would you need to also include these areas in your analysis?
The SMAP mission is conservative and masks out regions where vegetation density is greater than 5 kg/m2. Soil moisture retrievals are still performed in regions with less dense vegetation, including many agricultural regions. One possible approach to overcome both the limitations you mention — not seeing RZSM or seeing through dense vegetation — is moving from L-band (used by SMAP) to P-band, a lower frequency band of microwave radiation. These observations see through denser vegetation, and can see deeper into the soil profile.
[END] – Interviewed by Tim van Emmerik
This interview is part of the new YHS Research “Hylights” series to showcase interesting and outstanding work by early career scientists. Selection criteria are not set in stone, but reasons to select work can include e.g. novelty and relevance of findings, fun of reading, unique collaborations, media coverage and generated controversy. Selected work will be provided with a short layman summary, and a short written or video interview with the (first) author(s). Tips can be sent to young email@example.com or firstname.lastname@example.org.