Luke A Parsons

Current Research:

As a research scientist, I am:

1) Studying humid heat and air pollution impacts on human health and labor productivity and how global warming and global emissions reductions will impact future labor, the economy, and human health.

2) Studying the combined effects of deforestation/reforestation, agroforestry, and climate change on temperatures, labor, and human health and well-being.

3) Using climate model simulations and paleoclimate data assimilation to study the dynamics of pre-instrumental drought in locations such as Southwestern North America.

To read more about my current research, see the Research link, check out my CV, or visit my Google Scholar profile.

Recent Research:

Working in hot and potentially humid conditions creates health and well-being risks that will increase as the planet warms. It has been proposed that workers could adapt to increasing temperatures by moving labor from midday to cooler hours. I use reanalysis data to show that in the current climate approximately one third of global heavy labor losses in the workday could be recovered by moving labor from the hottest hours of the day. However, using climate model (CMIP6) projections, I show that this particular workshift adaptation potential is lost as early morning heat exposure rises to unsafe levels for continuous work, with worker productivity losses accelerating under higher global warming levels. These findings emphasize the importance of finding alternative adaptation mechanisms to keep workers safe, as well as the importance of limiting global warming (Nature Communications, 2021).

In follow-up research, I use data from a newer, lab-controlled study (Foster et al., 2021) that relates temperature+humidity to human work capacity to study the impact of  heat exposure and recent climate change on labor productivity. I find that globally, humid heat may currently be associated with over 650 billion hours of annual lost labor (148 million full time equivalent jobs lost). This updated estimate is over 400 billion hours more than previous estimates. For context, this difference in estimated labor loss is comparable to losses caused by the COVID-19 pandemic. Over the last four decades, global heat-related labor losses increased by at least 9% (>60 billion hours annually using the new empirical model) highlighting that relatively small changes in climate (<0.5oC) can have large impacts on global labor and the economy (Environmental Research Letters, 2022).

If you want to hear to an audio summary of the work described above, please listen to my recording on acaudio.com.

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Humid heat exposure from climate change already impacts populations in low-latitude countries, and future global warming will have substantial negative consequences for the health and well-being of some of the most vulnerable communities in the tropics. Additionally, tropical deforestation causes immediate local increases in land surface temperatures. In recent work, we examined the labor and mortality consequences of deforestation and climate change in Berau Regency Indonesia (Lancet Planetary Health, 2021). In follow-up work, we show that recent (21st century) deforestation across the tropics has already created significant increases in unsafe working conditions due to humid heat exposure for almost 5 millions people, including several million outdoor workers. Future warming will exacerbate these impacts. (One Earth, 2021).

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Understanding past climate variability is important for contextualizing climate change as well as for testing the ability of climate models to simulate the climate system before global warming. However, reconstructing past climate variability remains a complex task because pre-instrumental paleoclimate proxy records, such as tree rings, corals, ice cores, and sediment cores, are geographically sparse and are not perfect recorders of climate information. Exactly how to extrapolate information from paleoclimate proxies to other locations and climate variables remains an outstanding issue. Traditionally, information about how one location varies with another location or variable (covariance) is derived from one climate model or from one instrumental data source. In a recently published paper, I find that reconstructions using covariance estimated from combinations of multiple climate models produces less error than reconstructions that use just one climate model (Earth and Space Science, 2021).

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In the latest climate model simulations (CMIP6 models, which are used in the Intergovernmental Panel on Climate Change report, or IPCC AR6), I find that most models agree that as the globe warms in the 21st century, much of Amazonia will receive less rainfall and will rapidly heat up. In these model projections under unabated global warming, recent particularly hot droughts become common by the middle of the 21st century. Importantly, reducing greenhouse gas emissions appears to decrease the magnitude of future rainfall trends in the region and decreases the severity of particularly hot years. However, these results as they relate to rainfall changes should be interpreted with caution for two reasons: 1) many CMIP6 models show considerable rainfall biases in the American tropics, 2) These simulated changes in the Amazon are associated with model-projected future changes in the tropical Pacific Ocean (ENSO), and climate models traditionally struggle to reproduce observed trends in the tropical Pacific (Earth's Future, 2020)

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Using CMIP5 and CMIP6 pre-industrial control simulations and instrumental data, I examined the regions associated with unforced and forced climate variability and change. There is very little unforced  (natural, internal) climate variability in regions of deep convections in the tropics. By contrast, forced climate variability (short-lived cooling from volcanic eruptions) and climate change (warming from greenhouse gases) show strong signals in these regions in the tropics (Geophysical Research Letters, 2020)

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Using the CMIP5 piControl and past1000 as well as new Last Millennium Reanalysis reconstructions I created using each of the 10 CMIP5 past1000 simulations, I studied the regions associated with interdecadal, global-mean temperature variability in the pre-instrumental era (Journal of Geophysical Research-Atmospheres, 2019)

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Using the NCAR CESM Last Millennium Ensemble and other Earth System Model simulations, I studied the continuum of ocean-atmosphere conditions that coincide with multi-year drought in Southwestern North America as well as the ocean-atmosphere trajectories of these events  (Journal of Climate, 2018; Journal of Geophysical Research-Atmospheres, 2019).