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AOSC Seminar by Dr. Lesley Ott, 3/11/2021

AOSC Seminar

Dr. Lesley Ott



Title: Toward integrated seasonal predictions of land and ocean carbon flux: lessons learned from NASA’s subseasonal-to-seasonal predictions



Seasonal forecasts made by coupled atmosphere-ocean general circulation models (GCMs) are increasingly able to provide skillful forecasts of climate anomalies. At some modeling centers, the capabilities of these models are being expanded to represent carbon-climate feedbacks including ocean biogeochemistry (OB), terrestrial biosphere (TB) interactions, and fires. Here, we examine whether land and ocean carbon flux anomalies that occurred over the past 10 years could have been predicted. This period included both El Nino and La Nina episodes, which are predictable several months in advance, and a wealth of remote sensing data to evaluate performance. We explore this topic using NASA’s Goddard Earth Observing System (GEOS) model, which routinely produces an ensemble of seasonal climate forecasts, and a suite of offline dynamical and statistical models that estimate carbon flux processes. Using GEOS forecast fields from 2007-16 to force flux model hindcasts shows that these models are able to reproduce significant features observed by satellites. Specifically, OB hindcasts are able to predict anomalies in chlorophyll distributions with lead times of 3-4 months. Statistical fire forecasts driven by ocean climate indices are able to predict burned area in the tropics with lead times of 3-12 months. The ability of TB hindcasts to reproduce land flux anomalies is controlled by the skill of the climate forecast. Application of a bias correction to address substantial errors in the seasonal forecast meteorology greatly improves TB predictions, supporting skillful forecasts out to 3 months. Though TB predictions display skill in reproducing estimates produced by the same TB model driven by observed meteorology, predictions from different models can also disagree with each other, highlighting the need for multi-model approaches and for continued model development to improve the reliability of forecasts. While seasonal forecasting remains an active area of research, these results demonstrate that forecasts of carbon flux processes can support a variety of applications, allowing scientists to understand carbon-climate feedbacks as they happen and to capitalize on more flexible satellite technologies that allow areas of interest to be targeted with lead times of weeks to months.



Dr. Ott received her Ph.D. in Atmospheric and Oceanic Science (AOSC) from the University of Maryland, College Park, in 2006, after also receiving her MS and BS degrees from UMD.  She joined the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center in 2006, as a NASA post-doctoral fellow, and in 2011, as a civil servant. Her research focuses on understanding how small scale atmospheric processes affect atmospheric composition and our understanding of the carbon cycle.  She currently leads the carbon cycle modeling group in the GMAO, including projects that aim to i) integrate land, ocean, and atmospheric models to better understand carbon flux, ii) support NASA’s OCO and GeoCarb satellite missions, and iii) use models to evaluate the benefit of future space-based CO2 and CH4 missions. She previously served on the panel for the 2017 Decadal Survey for Earth Science, which helps NASA determine measurement priorities over the next decade.  Recently, she has been busy tracking COVID19 impacts on CO2 and helping to plan an international workshop on greenhouse gas remote sensing to be held later in the spring.


Contact: Ken Pickering

AOSC Seminar

Pre-seminar refreshment: N/A
Seminar: 3:30-4:30pm, Zoom
Meet-the-Speaker: 4:30-5:00pm, Zoom [For AOSC Students only]

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