User Profile: Dr. John Fasullo

Who uses NASA Earth science data? Dr. John Fasullo, to track changes in Earth’s climate.

Dr. John Fasullo, Project Scientist, National Center for Atmospheric Research

Dr. John Fasullo in Jamaica pointing out NASA’s ability to determine global mean sea level to within 1mm given the complicating effects of tides, waves, and sampling challenges. Image courtesy of Dr. John Fasullo.

Research interests: Climate variability and change with a focus on the energy and water cycles.

Current research: Earth’s climate is changing, and NASA has the numbers to prove it. According to data from the Global Climate Change website based on studies by NASA’s Goddard Institute for Space Studies (GISS), the National Oceanic and Atmospheric Administration, and the University of East Anglia, global mean surface temperature has risen about 0.78˚C (about 1.4˚F) since 1880 (with 9 of the 10 warmest years ever recorded occurring since 2000) and Arctic ice reached its lowest extent ever recorded in the satellite era on September 16, 2012.

As also noted on the Global Climate Change website, global mean sea level is rising about 3.4 mm per year. This is why a drop in global mean sea level of roughly 7 mm during 2010 and 2011 was an unexpected event, and an event well-suited to Dr. John Fasullo’s research interests.

Fasullo uses NASA Earth observing data to characterize Earth’s climate and test various theories about the effects of climate change on Earth processes, particularly effects on the energy and water cycles. Changes in global mean sea level are indicative of variability of both cycles due to the ocean’s large role distributing global heat and moisture. If global sea level falls, such as in 2010-2011, this means that water was prevented from entering the ocean. For Fasullo, this raised the obvious question: Where did this water go and where was it stored?

Much of the data used by Fasullo for monitoring global mean sea level come from Earth observing missions. These include the joint NASA/German Aerospace Center Gravity Recovery and Climate Experiment (GRACE) satellite mission, which studied Earth’s gravity field, and the joint NASA/French Space Agency (cnes) TOPEX/Poseidon mission and Jason series of satellite missions, which study ocean surface topography.

Fasullo also relies on climate models. These models use complex algorithms and high power computers to analyze Earth observing data collected over many years by satellite, airborne, and ground-based instruments. Models such as the Goddard Earth Observing System Model, Version 5 (GEOS-5), NCAR’s Community Earth System Model version 1 (CESM1), and the World Climate Research Programme’s Coupled Model Intercomparison Project Phase 5 (CMIP5) attempt to simulate and predict climate responses to events, such as an increase in carbon dioxide (CO2) or a volcanic eruption. These models are constantly checked against data collected by Earth observing missions and real-world events to ensure that their projections accurately reflect actual environmental responses.

These models sometimes are found to contain biases. Along with monitoring global mean sea level, Fasullo also looks at these biases. In one recent study, Fasullo and his colleagues identified major differences in how some climate models simulate clouds, which are notoriously difficult to simulate due to their complexity. Not only are clouds difficult to track and detect, they also differ in microphysical properties. These microphysical properties include the condensation nuclei around which water vapor adheres to form clouds and water droplets. As a result, cloud processes in models are more general than exact, which can lead to different models returning different simulations of environmental conditions.

In order to minimize potential model bias, Fasullo and his colleagues developed an approach to look at the environment in which clouds occur, rather than the clouds themselves. This approach relies on relative humidity, which is easily tracked and measured in the atmosphere by instruments aboard satellites, such as the Clouds and the Earth’s Radiant Energy System (CERES) instrument aboard the Tropical Rainfall Measuring Mission (TRMM), which ended in 2015, and Terra, Aqua, and Suomi NPP satellites.

Data products used:

  • GRACE gravity field measurements, available through the Physical Oceanography Distributed Active Archive Center (PO.DAAC)
  • Sea Level Rise from Satellite Altimetry data available through the Global Climate Change portal
  • Various products from TRMM, which are available through the Precipitation Measurement Missions (PMM) portal
  • Various data sets from the Global Precipitation Climatology Project (GPCP), which is part of the Mesoscale Atmospheric Processes Laboratory located at NASA’s Goddard Space Flight Center
  • Various cloud and flux data sets produced from data collected by the CERES instrument

Research findings: So where did water go that did not end up in the ocean in 2010-2011? The answers found by Fasullo and his colleagues involve several contributing factors that occurred over an 18 month period, among which were La Niña conditions in the Eastern Pacific Ocean (that is, cooler than normal ocean water, which is the opposite of El Niño conditions) and the unique nature of Australia’s rivers. The end result was a rare combination of climatic factors that led to historically heavy rainfall in Australia that was prevented from flowing into the ocean long enough to cause a drop in global sea levels.

During 2010-2011, La Niña conditions transported moisture from east to west, resulting in heavier than normal rainfall in the western Pacific Ocean. Meanwhile, an atmospheric circulation pattern called the Indian Ocean Dipole, or IOD, had entered a negative phase. A negative IOD phase is characterized by warmer than normal water in the eastern Indian Ocean and cooler than normal water in the western Indian Ocean. This negative IOD led to heavier than normal precipitation in the western Pacific, especially over Australia. In addition, another atmospheric circulation pattern called the Southern Annular Mode (SAM) had entered a negative phase and was drawing moisture and storm systems from the western Pacific southward. These factors led to the heaviest rainfall ever recorded in many parts of Australia.

Over most land regions, this excess water would simply drain into the ocean. However, Australia has two unique characteristics that prevent water from easily running to the sea. When rain falls in Australia, particularly in the eastern part of the continent, it runs inland and is collected in basins that trap water. This type of basin is called an endorheic basin. The only way water leaves an endorheic basin is through evaporation or slow seepage. Compounding this, Australia also has very low runoff ratios due to its large expanse of desert. These areas with very low runoff are called arheic, and also prevent moisture from easily escaping.

Fasullo and his colleagues found that these factors led to heavier than normal precipitation falling on an area that trapped this water and prevented it from flowing easily to the sea, leading to a decrease in global mean sea level. Fasullo’s research also found that simply having La Niña conditions in place is not enough to cause such a large decrease in global mean sea level; a number of other climate factors (such as the negative phase of the IOD and the SAM) also need to be present to cause substantially heavier than normal precipitation to fall in areas that prevent this water from running into the sea, such as in Australia.

In their work on minimizing model biases through the use of the cloud/relative humidity relationship, Fasullo found that the tropics and subtropics both show seasonal variations in relative humidity that correlate strongly with the formation of clouds and the warming projected by models in response to increases in CO2 in the 21st century. Adjusting climate models to use observed variations in relative humidity gathered from Earth observing satellites that can sense moisture in the troposphere should help lower model biases and enable these models to make better predictions of future climate trends.

Read about the research:

Fasullo, J.T., Lawrence, D. & Swenson, S. (2016). Are GRACE-era terrestrial water trends driven by anthropogenic climate change? Advances in Meteorology, 2016. doi:10.1155/2016/4830603

Fasullo, J.T., Boening, C., Landerer, F.W. & Nerem, R.S. (2013). Australia's unique influence on global sea level in 2010-2011. Geophysical Research Letters, 40(16). doi:10.1002/grl.50834

Fasullo, J.T. & Trenberth, K.E. (2012). A less cloudy future: The role of subtropical subsidence in climate sensitivity. Science, 338(6108). doi:10.1126/science.1227465

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