Project Funding: 2014 - 2017

NRA: 2013 NASA: Carbon Cycle Science   

Funded by NASA

Abstract:
One of the biggest sources of uncertainty in the climate of the 21st Century arises from potentially strong but poorly understood carbon-climate feedback. Under rising CO2, some coupled climate models develop persistent drought over the Amazon, which transforms high-carbon forests to low-carbon savannas releasing enormous amounts of CO2. We propose to test a more realistic model of drought stress and resilience in tropical forests against a wealth of experimental and satellite data, implement the new parameterization in the open-source Community Earth System Model, and use it to explore this 'tropical terrestrial tipping point' under several 21st Century warming scenarios. The proposed research is responsive to Element 3.1.1 in the solicitation, and directly addresses goals and objectives of both NASA and DOE. Carbon, water, and energy cycling in tropical forests typically have naive representation in coupled Earth System models. Simulated precipitation is distributed over large grid cells and results in light rain rates that are easily intercepted by the canopy. By contrast, real precipitation falls in torrential convective downpours over smaller areas in organized squall lines, quickly saturating canopy storage to infiltrate soils or run off. Land-surface schemes in many climate models were developed with temperate forests in mind, and fail to sustain transpiration and photosynthesis during extended tropical dry seasons. In climate models that simulate photosynthesis, net carbon uptake occurs during the rainy season with net release under severe stress during the dry season. Some Amazon sites exhibit opposite seasonal cycles. It is unreasonable that such naive models can be expected to correctly predict the strength or thresholds for positive carbon-climate feedback under enhanced evaporative demand in a high-CO2 world. Experimental data have shown that some tropical forests are very well adapted to strong seasonal drought as well as to periods of longer-lasting drought associated with El Nino conditions. Multiyear records of carbon, water, and energy fluxes across a huge precipitation gradient in the Amazon reveal tremendous variations in drought resilience. In the wet northwest, drought is very rare and photosynthesis may be light limited by persistent clouds. Seasonal drought increases to the southeast, where drought-tolerant forests give way to savanna ecosystems. Throughfall exclusion experiments performed in two locations show that a forest ecosystem more frequently exposed to drought was more resilient to severe chronic drought that might be experienced under global warming scenarios. These observations point to the need for more nuanced representation of drought impacts on tropical carbon cycles in Earth System models. We propose to use data from the two multiyear throughfall exclusion experiments to tune a new drought resilience parameterization based on accessibility of deep soil moisture. The research will be conducted using two ecosystem models, the Community Land Model (CLM4) and the Simple Biosphere Model (SiB4). Drought resilience will be scaled across tropical forests using climatological mean precipitation, dry season length, and the variance of annual precipitation during the GPCP record. We will evaluate the new scheme across gradients in observed precipitation and episodic drought in 2005 and 2010. We will use simulations of the MERRA reanalysis period (1979-present) to predict pan-tropical LAI, fPAR, GPP, ecosystem respiration, and chlorophyll fluorescence on a 0.5 degree grid. These will be evaluated against AVHRR NDVI (1982-present), MODIS LAI/fPAR (2000-present), and chlorophyll fluorescence (2007-present), with special attention to drought stress and resilience. Finally, we will incorporate the improved ecosystem model in a multiscale ('superparameterized') version of the Community Earth System Model to quantify carbon-climate feedback in tropical forests under several climate change scenarios.

Publications:

Baker, I. T., Sellers, P. J., Denning, A. S., Medina, I., Kraus, P., Haynes, K. D., Biraud, S. C. 2017. Closing the scale gap between land surface parameterizations and GCMs with a new scheme, SiB3-Bins. Journal of Advances in Modeling Earth Systems. 9(1), 691-711. DOI: 10.1002/2016MS000764

Haynes, K. D., Baker, I. T., Denning, A. S., Stockli, R., Schaefer, K., Lokupitiya, E. Y., Haynes, J. M. 2019. Representing Grasslands Using Dynamic Prognostic Phenology Based on Biological Growth Stages: 1. Implementation in the Simple Biosphere Model (SiB4). Journal of Advances in Modeling Earth Systems. 11(12), 4423-4439. DOI: 10.1029/2018MS001540

Haynes, K. D., Baker, I. T., Denning, A. S., Wolf, S., Wohlfahrt, G., Kiely, G., Minaya, R. C., Haynes, J. M. 2019. Representing Grasslands Using Dynamic Prognostic Phenology Based on Biological Growth Stages: Part 2. Carbon Cycling. Journal of Advances in Modeling Earth Systems. 11(12), 4440-4465. DOI: 10.1029/2018MS001541

Haynes, K., I. Baker, and S. Denning. 2020. Simple Biosphere Model version 4.2 (SiB4) technical description. Mountain Scholar, Colorado State University, Fort Collins, CO, USA. https://hdl.handle.net/10217/200691

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)

• Tropical Terrestrial Tipping Point   --   (Ian Baker, Katherine Haynes, Scott Denning, Don Dazlich, David Randall, Anna Harper)   [abstract]

More details may be found in the following project profile(s):

• NASA Terrestrial Ecology (TE) Project Profile