RUBISCO SFA

Government-funded user facilities provide prestigious opportunities for academic, government, and industry researchers to enhance and accelerate their science at little to no cost. The U.S. Department of Energy, Office of Science, manages multiple user facilities dedicated to energy and environmental research. Through a competitive, peer-reviewed proposal process, scientists can collaborate with us to study biological and environmental functions, as well as matter and energy, at varying spatial and temporal scales.

In this session, participants will learn about:

• the role of user facilities in furthering national priorities such as energy security and predictive understanding of environmental processes,
• the expertise and instrumentation available at user facilities,
• examples of frontier-expanding energy and environmental research,
• numerous opportunities for collaborating with user facilities, and
• useful tips for submitting successful proposals.

Principal investigators, early career scientists, post-doctoral researchers, and graduate students from academic institutions, government laboratories, non-profits, and industry are invited to participate. Virtual and in-person speakers will include a mix of representatives from the Department of Energy and individual user facilities, as well as former and current researchers who regularly submit successful proposals. This is an exciting opportunity to start new collaborations, learn from experts how to navigate the proposal process, and help the science community push the boundaries of energy and environmental research.

Type:
Town Hall

Primary Contact:
Linda Isakson (Pacific Northwest National Laboratory)

Conveners:
Rolanda Jundt (Pacific Northwest National Laboratory)
David Gilbert (Lawrence Berkeley National Laboratory)

Moderator:
Linda Isakson (Pacific Northwest National Laboratory)

Presenters:
Paquita Zuidema (University of Miami)
Davinia Salvachua (National Renewable Energy Laboratory Golden)
Mikayla Borton (Colorado State University)
Sharlene Weatherwax (Department of Energy, Office of Science)
Jeffrey Blanchard (University of Massachusetts Amherst)

The DOE Atmospheric Radiation Measurement (ARM) user facility will be relocating the third ARM Mobility Facility (AMF3) to the Southeastern United States (SEUS) for a five year deployment starting in the fall of 2022. The AMF3 SEUS site science team is working with ARM and the larger scientific community to guide the siting of the new deployment to address critical science focal areas spanning five cross-cutting topics: convective cloud initiation, deep convective cloud processes, aerosol controls on cloud condensation nuclei, aerosol direct impacts on radiation, and land-atmosphere two-way interactions. This campaign will enable a wide range of observational, analysis, and modeling studies to characterize the relationships between local and regional weather patterns and surface processes across a patchwork of natural, managed, and anthropogenic landscapes in the SEUS region. The target audience for this town hall includes: the atmospheric and terrestrial ecosystem science communities, program managers across funding agencies (DOE BER/ESS, NASA, NSF, USDA), and SEUS partners and users of other related measurement networks (e.g. NEON). The goals of the proposed town hall are to present and solicit feedback on: scientific goals of the SEUS deployment, siting maps that meet operational and scientific requirements, and targeted field campaigns.

Type:
Town Hall

Primary Contact:
Chongai Kuang (Brookhaven National Laboratory)

Presenters:
Scott E. Giangrande (Brookhaven National Laboratory)
Shawn Serbin (Brookhaven National Laboratory)

Sections:
Hydrology
Global Environmental Change
Earth and Planetary Surface Processes
Biogeosciences
Atmospheric Sciences

Cross-Listed:
H - Hydrology
GC - Global Environmental Change
EP - Earth and Planetary Surface Processes
B - Biogeosciences
A - Atmospheric Sciences

DOE research in MultiSector Dynamics (MSD) is transforming the way scientists explore complex landscapes and the multi-scale interactions involving human and natural systems, sectors, and the influences and stressors that shape their evolution. Accompanying data, modeling, and analysis frameworks are reaching across traditional research domains in ways that have given rise to a new and emerging interdisciplinary field and community-of-practice. This Town Hall explores DOE’s role in MSD research, the implications for insights into topics ranging from coastal science and integrated hydro-terrestrial modeling to global and regional Earth system predictability, and DOE’s foundational role in the creation of this new field.

Type:
Town Hall

Primary Contact:
Robert Vallario (Department of Energy)

Presenters:
Gerald L. Geernaert (Department of Energy)
Xujing Davis (U.S. Department of Energy)
Patrick M. Reed (Cornell University)
Dave Judi (Pacific Northwest National Laboratory)
Jennie Rice (Pacific Northwest National Laboratory)
Jennifer F. Morris (Massachusetts Institute of Technology)

Section:
Town Halls

Sections:
Science and Society
Natural Hazards
Hydrology
Global Environmental Change
Biogeosciences

Cross-Listed:
SY - Science and Society
NH - Natural Hazards
H - Hydrology
GC - Global Environmental Change
B - Biogeosciences

The status of soil moisture across a national scale is of interest to a broad range of interests, including meteorologists, hydrologists, climatologists, agriculturalists, and geophysicists. A new initiative, the National Coordinated Soil Moisture Monitoring Network, was developed to provide a framework for national scale soil moisture monitoring activities, with a focus on utility and resilience. Papers are called for on all aspects of soil moisture science, including in situ monitoring, remote sensing, and modeling. Soil moisture is an essential climate and agricultural variable, impacting many applications, therefore also of interest are studies using large-scale soil moisture estimates, as this will help to guide the development of the network.

Type:
Poster

Primary Convener:
Michael H. Cosh (USDA Agricultural Research Service)

Conveners:
Todd G. Caldwell (U.S. Geological Survey)

Chairs:
Michael H. Cosh (USDA Agricultural Research Service)
Todd G. Caldwell (U.S. Geological Survey)

OSPA Liaison:
Michael H. Cosh (USDA Agricultural Research Service)

Index Terms:
1847 Modeling
1848 Monitoring networks
1855 Remote sensing
1866 Soil moisture

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Soils - SWIRL

Cross-Listed:
A - Atmospheric Sciences

Soil moisture is an important variable for studying global hydrological processes. Existing gridded soil moisture datasets are from data assimilation products, remote sensing, and land surface models, which are subject to considerable bias due to satellite data retrieval and modeling errors. In recent years, there has been much interest in upscaling in situ observations of ecosystem variables (e.g. evapotranspiration, gross primary productivity) to generate gridded datasets using machine learning methods. Such procedure can be similarly applied to develop upscaled gridded soil moisture datasets, which will have different error sources than existing gridded soil moisture products, and can serve as a useful alternative for data cross-checking, model evaluation, and empirical analysis. In this research, global soil moisture observations are assembled from the International Soil Moisture Network, FLUXNET, and the Canadian Global Water Futures. Random forest models are fitted between soil moisture at different depths and a variety of predictors (meteorological conditions, vegetation, soil properties, land cover, and topography), for each ecosystem type and snow/non-snow/growing/non-growing seasons. In the next step, the models will be applied with global gridded meteorological, vegetation, soil, land cover, and topography datasets to obtain global gridded long-term soil moisture product.

Authors:
Yaoping Wang (University of Tennessee)
Jiafu Mao (Oak Ridge National Laboratory)
Mingzhou Jin (University of Tennessee)
Forrest M. Hoffman (Oak Ridge National Laboratory)

Earth system models are effective tools to assess LULCC impacts in a changing climate by incorporating a broad range of relevant processes, such as the transitions between natural and managed land use types, urbanization, and ecosystem dynamics following disturbances. While they have paved the way toward elucidating the role of LULCC in modulating biogeophysical and biogeochemical feedbacks in the Earth system, they are yet to be improved by integrating with observations and data-assimilated Earth system records. We seek contributions on, but not limited to, quantifying the effects of LULCC on water/carbon/nutrient cycling, the water-food-energy nexus, and regional and the global climate using Earth system records and/or models. Studies on developing Earth system records and projections (e.g., the Land Use Model Intercomparison Project), high-resolution modeling of individual processes, validation and verification tools, and coupling frameworks that advance scientific understanding and improve fidelity of Earth system models, are strongly encouraged.

Type:
Oral

Primary Convener:
Dan Li (Boston University)

Conveners:
Edouard Davin (ETH Swiss Federal Institute of Technology Zurich)
Yanyan Cheng (Pacific Northwest National Laboratory)

Chairs:
Edouard Davin (ETH Swiss Federal Institute of Technology Zurich)
Yanyan Cheng (Pacific Northwest National Laboratory)
Dan Li (Boston University)

OSPA Liaison:Yanyan Cheng (Pacific Northwest National Laboratory)

Atmospheric mineral dust originating from Africa contains micronutrients that fertilize both surface marine ecosystem in Atlantic Ocean and tropical forest in Amazonia. However, the mechanism of land use and land cover change (LULCC) impacts on such nutrient transport pathway remain poorly understood. In this presentation, we use the Community Earth System Model (CESM) to investigate how large-scale deforestation affects the dust transport and deposition in the tropics. We find that surface biophysical changes (i.e., albedo increase, evapotranspiration and surface roughness decline) that accompany deforestation produce a warmer, drier and windier surface environment, which enhances the long-range dust transport from North Africa to the Amazon. Tropics-wide deforestation weakens Hadley circulation (HC) through reducing the surface latent heating that weakens the vertical velocity in deep tropics. The weakened upward branch of HC tends to force the tropical air poleward and this shift of more stable air tends to increase subtropical static stability. Such atmospheric perturbation is related to the poleward expansion of HC that leads to the increase of local surface air pressure in North Africa. Local northeasterly winds increase accordingly and make the dust in North Africa more easily to be transported across the tropical North Atlantic Ocean. We estimate that the annual atmospheric phosphorus deposition from dust thereby increases by about 26±25% in the Amazon. Our results exemplify how LULCC can modify the tropical nutrient transport, the change of which may have important implications for the long-term changes in productivity and biodiversity of tropical ecosystems.

Authors:
Yue Li (University of California Irvine)
James T. Randerson (University of California Irvine)
Natalie Mahowald (Cornell University)
Peter Lawrence (National Center for Atmospheric Research)

The mortality and economic losses caused by floods are increasing. In fact, the top 10 costliest floods since 1900 are all occurred over the past thirty years. On the one hand, this is the result of economy development, but on the other hand the hydrological cycle was largely intensified by climate change and human activities, particularly land use change. Disentangling these effects on flood risk change is very challenging due to the compound nature of the driving factors. Using the best available long-term historical climate forcing and a land surface model that is capable of representing the hydrological effects of land use, here we attempted to compare the effects on flood risk between climate change and land use. Results showed that over the past 110 years, climate change’s effects were mixed, strong, and widespread, while land use’s contributions were dominantly increase, modest, and restricted to the areas with large land use changes. However, when we aggregated their effects over large regions (e.g., major river basins), flood risk increase from land use may surpass that from climate change, as climate change’s effects offset from locations to locations within regions. This suggests that we have to reduce large-scale deforestation to avoid the catastrophic consequence of floods from the compounding effects of climate change and large-scale deforestation.

Authors:
Xitian Cai (Lawrence Berkeley National Laboratory)
William J. Riley (Lawrence Berkeley National Laboratory)
Zhenzhong Zeng (Princeton University)

Predictions of future atmospheric CO₂ levels are influenced by global carbon and nutrient cycles, climate interactions, and feedbacks to the Earth system. Relevant processes operate at different spatial and temporal scales and vary across terrestrial, coastal, and marine ecosystems. Uncertain biogeochemical feedbacks may be altered by anthropogenic disturbance agents, including tropospheric O₃, acceleration of nutrient and hydrological cycles, eutrophication, acidification, land cover/land use change, and potential climate intervention strategies. This session focuses on integrated understanding of feedback mechanisms that improve Earth system predictability, methods for evaluating and benchmarking process representations in Earth system models, approaches for constraining future climate projections (e.g., emergent constraints), and novel applications of artificial intelligence and machine learning for improving predictive understanding of global biogeochemical cycles.

Type:
Poster

Primary Convener:
Forrest M. Hoffman (Oak Ridge National Laboratory)

Conveners:
Cheryl S. Harrison (University of Texas Rio Grande Valley)
Cheng-En Yang (University of Tennessee)

Chairs:
Forrest M. Hoffman (Oak Ridge National Laboratory)
Cheryl S. Harrison (University of Texas Rio Grande Valley)
Cheng-En Yang (University of Tennessee)

OSPA Liaison:
Cheryl S. Harrison (University of Texas Rio Grande Valley)

Index Terms:
0428 Carbon cycling
0439 Ecosystems, structure and dynamics
1615 Biogeochemical cycles, processes, and modeling
1622 Earth system modeling

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Climate - SWIRL

Cross-Listed:
OS - Ocean Sciences
GC - Global Environmental Change

Co-Sponsored:
ESA: Ecological Society of America

Countries have long been making efforts by reducing emissions of greenhouse gases to mitigate climate change. In the agreements of the United Nations Framework Convention on Climate Change, involved countries have committed to reduction targets. However, carbon (C) sink by natural ecosystems has been difficult to quantify. Using a transient traceability framework, we quantified country-level C sequestration potential by natural terrestrial ecosystems by the middle of the 21$^^st century based on simulations of 12 CMIP5 Earth System Models under RCP8.5. The top 20 countries that have the highest C sequestration potential has the potential to sequester 62 Pg C by the middle of this century. Among the top 20 countries, Russia, Canada, United States, China, and Brazil sequester the most. The dominant forces to drive carbon sequestration are changes in net primary production and C residence time. Our results highlight that model-based estimates of land C sequestration may potentially offset a substantial proportion of greenhouse-gas emissions, especially for countries with a large change in NPP and long inherent residence time.

Authors:
Lifen Jiang (Northern Arizona University)
Junyi Liang (China Agricultural University)
Xingjie Lu (Northern Arizona University)
Enqing Hou (Northern Arizona University)
Forrest M. Hoffman (Oak Ridge National Laboratory)
Yiqi Luo (Northern Arizona University)

Boreal river systems play a crucial role in high latitude change as they carry the highest terrestrial input of all aquatic flow to the sea. This includes a massive dissolved organic flux, injected directly to the climatologically sensitive Arctic Ocean. The dissolved organics imply chemical functional groups that interact with coastal and open ocean biophysical properties such as light attenuation, surface tension, trace metal chelation and aerosol formation. We have performed reduced kinetic modeling for organic matter evolution along an idealized Siberian river. We studied reactivity, networking and fate for the major macromolecular groups based on their diverse structures: sugar, lipids, proteins, heteropolycondensate and humic substance are all considered. We found that along the stream course, chemical reactivity is slow relative to the coastal or open ocean, but mixing at tributary nodes plays a dominant role. Concentrations for the various carbon compounds stagger at connecting points based specifically on sourcing from the different Arctic sub-ecosystems: taiga, tundra, woodland, peat, bog and others. Even so, photochemical and microbial losses contribute to the final mix and along coastlines biophysical impacts are extreme. For example the chromophoric dissolved organic matter or CDOM attenuates at a one versus ten meter e-fold depending on upstream ecology. Soil-runoff and deltaic (pre- versus post-) processing also exert discrimination on the functional distribution and aquatic chemical influence. Further investigation is necessary and ongoing, through an increase in the number of connection points dictating dilution and mixing. And we are hoping to investigate the interaction of humics as flocculants with mineral particles, since they are capable of removing turbidity as ionic strength rises in the plume.

Authors:
Amadini Mendis Jayasinghe (New Mexico Tech)
Scott Elliott (Los Alamos National Laboratory)
Anastasia Piliouras (Los Alamos National Laboratory)
Jaclyn L. Clement-Kinney (Los Alamos National Laboratory)
Georgina Gibson (University of Alaska Fairbanks)
Nicole Jeffery (Los Alamos National Laboratory)
Forrest M. Hoffman (Oak Ridge National Laboratory)
Jitendra Kumar (Oak Ridge National Laboratory)
Oliver W. Wingenter (New Mexico Tech)

Terrestrial ecosystems take up about one-third of total anthropogenic carbon emissions, providing a check on rising atmospheric CO₂ concentration. While increases in CO₂ fertilization and water use efficiency increase vegetation productivity under rising atmospheric CO₂ levels, rising surface temperature often leads to a reduction in available soil moisture and an increase in plant respiration. This results in varying spatial and temporal responses of net biome production (NBP) and the strength of the land carbon sink. The latest generation of Earth system models and observations have shown that the increase in vegetation productivity could reach a tipping point beyond which the respiration losses could be higher than photosynthetic capacity, as the surface temperatures get higher than the optimum growing temperature of plants. However, the impacts of future climate on extremes in NBP is unknown. We investigated NBP extremes in the Community Earth System Model (CESM2) from 1850 through 2100 and attributed the NBP extremes to individual and compound effects of climate drivers. Preliminary results showed a net increase in the frequency of negative extremes in NBP, with anomalous reductions in soil moisture as the most dominant climate driver. We found increased variability in vegetation growth due to rising CO₂ emissions through the study of extremes in NBP. A larger increase in the frequency and intensity of negative extremes in NBP than positive extremes in NBP indicates persistent extremes-driven reductions in vegetation growth in the future, and this imbalance could lead to a net reduction in terrestrial carbon uptake capacity and carbon storage when ecosystem respiration exceeds photosynthesis. The consequences of declining NBP and increasing negative extremes in NBP may result in global reduction in plant productivity and crop yield, even as the demand for vegetation is increasing due to rising demand for food, fiber, fuel, and building material.

Authors:
Bharat Sharma (Northeastern University)
Forrest M. Hoffman (Oak Ridge National Laboratory)
Jitendra Kumar (Oak Ridge National Laboratory)
Auroop R. Ganguly (Northeastern University)

Better representation of biogeochemistry–climate feedbacks and ecosystem processes in Earth system models (ESMs) is essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century and beyond. Model–data comparison and integration activities are required to inform improvement of land carbon cycle models and the design of new measurement campaigns aimed at reducing uncertainties associated with key land surface processes. The International Land Model Benchmarking (ILAMB) Package was designed to facilitate systematic and comprehensive model–data comparison and improve understanding of factors influencing model fidelity. We used ILAMB to benchmark and intercompare terrestrial carbon cycle models coupled within ESMs used to conduct historical simulations for the Fifth and Sixth Phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). Results indicate that the suite of CMIP6 land models exhibits better performance than the suite of CMIP5 land models in comparison with observations for a variety of biogeochemical, hydrological, and energy-related variables. These improvements are partially attributed to reductions of biases in temperature, precipitation, and incoming radiation, suggesting that free-running atmosphere models in these ESMs also improved; however, biases in some regions increased. An analysis of forcing variables, prognostic land variables, and relationships from variable-to-variable comparisons indicate an overall improvement in most CMIP6 models, with relationships for some models exhibiting the greatest improvement in ILAMB scores, suggesting that improved model process representation in some models, and likely increased model complexity, contributed to improved model performance. We further analyze the degree to which the range of model uncertainties may have been reduced for CMIP6 land models as compared with CMIP5 land models.

Authors:
Forrest M. Hoffman (Oak Ridge National Laboratory)
Nathan Collier (Oak Ridge National Laboratory)
Mingquan Mu (University of California Irvine)
Cheng-En Yang (University of Tennessee)
Charles D. Koven (Lawrence Berkeley National Laboratory)
David M. Lawrence (National Center for Atmospheric Research)
Gretchen Keppel-Aleks (University of Michigan Ann Arbor)
Min Xu (Oak Ridge National Laboratory)
Qing Zhu (Lawrence Berkeley National Laboratory)
Weiwei Fu (University of California Irvine)
Jiafu Mao (Oak Ridge National Laboratory)
Hyungjun Kim (University of Tokyo)
J. Keith Moore (University of California Irvine)
William J. Riley (Lawrence Berkeley National Laboratory)
James T. Randerson (University of California Irvine)

The Community Land Model (CLM5) is widely used by the Earth System Modeling research community to study many aspects of the role of land in climate and weather. In particular, the omodel is frequently used to understand and predict global and regional land carbon stock trajectories, water state trends, and carbon-water interactions and water use efficiency trends. Recent work has demonstrated high uncertainty due to forcing, structural, and parametric uncertainties. Prior efforts to assess CLM parametric uncertainty have been hampered by computational constraints or code limitations, necessarily limited to selected parameters related to specific processes. Here, we present a new community effort to conduct a comprehensive tiered exploration of parameter sensitivity and uncertainty; the CLM5 Parameter Perturbation Ensemble project (CLM5PPE). We have identified 200+ model parameters across processes that control energy, water, carbon, and nitrogen interactions. Phase 1 of the CLM5PPE involves one-at-a-time high/low parameter perturbations for all 200+ parameters on a sparse grid (~250 grid cells) that reasonably captures the main features of global higher-resolution simulations. Each simulation is checked for reasonableness (e.g., vegetation survivability rates). Each parameter perturbation is also run with environmental perturbations (CO₂, climate, N-deposition) that span historical and projected values. A set of 50 parameters are selected for further evaluation with the criteria for selection based on their importance in determining the mean, variability, and responses to environmental perturbations for a range of key land climate variables. Phase 2 uses these parameters to run a Latin hypercube sparse-grid 2500-member perturbed parameter ensemble, again repeated for each environmental perturbation. In Phase 3, ~200 best performing parameter sets will be used to run an ensemble of historical and projection period 2° resolution simulations to provide a realistic and comprehensive assessment of parametric uncertainty. All data output from this project as well as the scripting infrastructure to automate parameter perturbations, generate large ensembles, and assess model performance will also be made available to facilitate further parameter exploration of this and future versions of CLM.

Authors:
David M. Lawrence (National Center for Atmospheric Research)
Katie Dagon (National Center for Atmospheric Research)
Daniel Kennedy (National Center for Atmospheric Research)
Rosemary A. Fisher (National Center for Atmospheric Research)
Benjamin Sanderson (National Center for Atmospheric Research)
Keith W. Oleson (National Center for Atmospheric Research)
Forrest M. Hoffman (Oak Ridge National Laboratory)
Nathan Collier (Oak Ridge National Laboratory)
Danica L. Lombardozzi (National Center for Atmospheric Research)
William R. Wieder (National Center for Atmospheric Research)
Charles D. Koven (Lawrence Berkeley National Laboratory)
Sean C. Swenson (National Center for Atmospheric Research)

Anthropogenic and natural fires are an important component of the Earth system. Geographic location, fuel type, seasonality and intensity of fire largely determine the sign and magnitude of feedbacks on the Earth system. The aim of this session is to explore links between fire, vegetation, climate, air quality, and humans from the local to the global scale and determine how these interactions will change in a warming world. We encourage abstracts that explore the interactions of fires with the terrestrial biosphere and atmosphere using remote sensing, in situ observations, modeling, or an integrated approach with an emphasis on (1) impacts of fire on weather and climate, atmospheric chemistry and air quality, (2) the role of fires in the carbon cycle and ecosystem functioning, (3) the influence of humans on fire (and vice versa), and (4) the changing nature of fire over millennia, and predictions for the future.

Type:
Oral

Primary Convener:
Catherine M. Dieleman (University of Guelph)

Conveners:
Mika Tosca (School of the Art Institute of Chicago)
Jessica L. McCarty (Miami University Oxford)
Brendan M. Rogers (University of California Irvine)

Chairs:
Mika Tosca (School of the Art Institute of Chicago)
Brendan M. Rogers (University of California Irvine)
Jessica L. McCarty (Miami University Oxford)

OSPA Liaison:
Jessica L. McCarty (Miami University Oxford)

Neighborhoods:
1. Science Nexus

SWIRLs and Tracks:
Extreme Events & Hazards - SWIRL

Cross-Listed:
B - Biogeosciences

Africa contains some of the most vulnerable ecosystems to fires. Successful seasonal prediction of fire activity over these fire-prone regions remains a challenge and relies heavily on in-depth understanding of various driving mechanisms underlying fire evolution. Here, we assess the seasonal environmental drivers and predictability of African fire using the analytical framework of Stepwise Generalized Equilibrium Feedback Assessment (SGEFA) and machine learning techniques (MLTs). The impacts of sea-surface temperature, soil moisture, and leaf area index are quantified and found to dominate the fire seasonal variability by regulating regional burning condition and fuel supply. Compared with previously-identified atmospheric and socioeconomic predictors, these slowly evolving oceanic and terrestrial predictors are further identified to determine the seasonal predictability of fire activity in Africa. Our combined SGEFA-MLT approach achieves skillful prediction of African fire one month in advance and can be generalized to provide seasonal estimates of regional and global fire risk.

Authors:
Jiafu Mao (Oak Ridge National Laboratory)
Yan Yu (University of Wisconsin Madison)
Peter E. Thornton (Oak Ridge National Laboratory)
Michael Notaro (University of Wisconsin Madison)
Stan Wullschleger (Oak Ridge National Laboratory)
Xiaoying Shi (Oak Ridge National Laboratory)
Forrest M. Hoffman (Oak Ridge National Laboratory)
Yaoping Wang (University of Tennessee)

As of this writing in April 2020, scientists in many countries are working under stay-at-home orders. Although the AmeriFlux network has strong virtual connectivity and ecosystem flux research continues apace, 2020 brings a field (and education) season like no other. Therefore, in addition to popular AmeriFlux town hall activities, this year we are adding new activities. For the former, come learn about opportunities for 2021 and news of the network. We will wrap up the first theme year, on Methane, and launch the next. Celebrate successes, like honors to colleagues, funding opportunities, and new data products. Join a conversation with other flux scientists and chart priorities for the AmeriFlux Management Project (AMP). New for this year, we’ll launch activities for mentoring, connecting, and collaborating—which can take place locally or virtually, designed for people at different career levels, experience with fluxes, and locations across the Americas and world. These will include regional mini-workshops and facilitating peer-to-peer mentoring. The town hall will feature short, structured interactions to strengthen and celebrate our connections. This town hall is hosted by AMP and attracts a broad audience of ecologists and Earth scientists, early career and senior, from around the world. See you there!

Type:
Town Hall

Primary Contact:
Margaret S. Torn (Lawrence Berkeley National Laboratory)

Presenters:
Deb Agarwal (LBNL)
Margaret S. Torn (Lawrence Berkeley National Laboratory)
Sébastien Biraud (Lawrence Berkeley National Laboratory)
Trevor F. Keenan (Lawrence Berkeley National Laboratory)
Dario Papale (University of Tuscia)
Daniel B. Stover (Department of Energy Germantown)

Sections:
Hydrology
Global Environmental Change
General
Cryosphere
Biogeosciences
Atmospheric Sciences

Cross-Listed:
H - Hydrology
GC - Global Environmental Change
C - Cryosphere
B - Biogeosciences
A - Atmospheric Sciences

Coastal systems are a highly dynamic component of the Earth system, developed from a near balance between land-aquatic interfaces and strongly influenced by natural, anthropogenic and variable weather and climatic drivers. While coastal systems play a critical role in biogeochemical cycling with the potential to provide major feedbacks to the Earth system, they are inadequately captured in process, ecosystem, regional, sectoral, and Earth system models. DOE has recently launched three new efforts that will examine coastal processes/activities in the mid-Atlantic, Alaskan and Great Lakes regions. The goal of this session is to highlight ongoing developments using a coupled model-experimental approach related to DOE’s strategic research priorities. Additionally, this town hall will enable a community dialog to explore potential linkages to other community efforts and encourage coastal research collaborations.

Type:
Town Hall

Primary Contact:
Daniel B. Stover (Department of Energy Germantown)

Moderators:
Renu Joseph (US Department of Energy)
Paul E. Bayer (Department of Energy Germantown)
Robert Vallario (Department of Energy)
Jennifer S. Arrigo (Department of Energy Washington DC)

Presenter:
Daniel B. Stover (Department of Energy Germantown)

Sections:
Hydrology
Global Environmental Change
General
Biogeosciences

Cross-Listed:
OS - Ocean Sciences
H - Hydrology
GC - Global Environmental Change
B - Biogeosciences

Predictions of future atmospheric CO₂ levels are influenced by global carbon and nutrient cycles, climate interactions, and feedbacks to the Earth system. Relevant processes operate at different spatial and temporal scales and vary across terrestrial, coastal, and marine ecosystems. Uncertain biogeochemical feedbacks may be altered by anthropogenic disturbance agents, including tropospheric O₃, acceleration of nutrient and hydrological cycles, eutrophication, acidification, land cover/land use change, and potential climate intervention strategies. This session focuses on integrated understanding of feedback mechanisms that improve Earth system predictability, methods for evaluating and benchmarking process representations in Earth system models, approaches for constraining future climate projections (e.g., emergent constraints), and novel applications of artificial intelligence and machine learning for improving predictive understanding of global biogeochemical cycles.

Type:
Oral

Primary Convener:
Forrest M. Hoffman (Oak Ridge National Laboratory)

Conveners:
Cheryl S. Harrison (University of Texas Rio Grande Valley)
Cheng-En Yang (University of Tennessee)

Chairs:
Forrest M. Hoffman (Oak Ridge National Laboratory)
Cheryl S. Harrison (University of Texas Rio Grande Valley)
Cheng-En Yang (University of Tennessee)

OSPA Liaison:
Cheryl S. Harrison (University of Texas Rio Grande Valley)

Index Terms:
0428 Carbon cycling
0439 Ecosystems, structure and dynamics
1615 Biogeochemical cycles, processes, and modeling
1622 Earth system modeling

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Climate - SWIRL

Cross-Listed:
OS - Ocean Sciences
GC - Global Environmental Change

Co-Sponsored:
ESA: Ecological Society of America

In the oceans, inflow of anthropogenic carbon dioxide through air sea gas exchange triggers a series adjustments in bicarbonate and carbonate ion concentrations that causes the pH to decline and net storage in dissolved inorganic carbon (DIC) to be more than a factor of 10 smaller than what would be expected if DIC adjusted directly in proportion to the overlying changes in atmospheric CO₂ mole fraction. This effect, known as the Revelle factor, is implicitly built into all state-of-the-art ocean biogeochemistry models through equations that represent the different forms of DIC as a function of temperature, alkalinity, pressure, salinity and the concentration of several other ions. On land, in contrast, carbon storage is often closely regulated by the initial response of gross primary production (GPP) to different forms of global change. The distribution of turnover times in downstream pools (as well as their sensitivity to climate) can modify rates of carbon storage in important ways, yet the donor pool structure of many models means that downstream adjustments to inflows do not offer as much resistance to carbon storage as compared to what occurs in the oceans by means of changes in carbonate chemistry. Here we describe several processes that operate on individual plant, community, stand, and ecosystem levels that may limit carbon storage in terrestrial ecosystems, yet are not well represented in models. These include downregulation of CO₂ fertilization effects on net primary production relative to effects on gross primary production, adjustments in tree mortality as a function of tree biomass, changes in stand-level fire disturbance as a function biomass accumulation in live, coarse woody debris, and litter pools, and limits to carbon storage in soils posed by fixed number of binding sites to clay and mineral surfaces in soils. We highlight some of these limits using analysis of earth system models from the 6th Coupled Model Intercomparison Project (CMIP6) and through analysis of global fire and soil carbon age datasets.

Authors:
James T. Randerson (University of California Irvine)
Jonathan Wang (University of California Irvine)
Stijn Hantson (University of California Irvine)
Zheng Shi (University of California Irvine)
Nicole Hemming-Schroeder (University of California Irvine)
Yue Li (University of California Irvine)
Paul A. Levine (University of California Irvine)

Terrestrial photosynthesis is the largest flux of carbon between the atmosphere and the Earth’s surface and is 10 times greater than carbon emissions from fossil fuel burning and land use change combined. Photosynthesis also connects the carbon cycle to water and nutrient cycles. As such, it is important to reliably simulate photosynthetic processes to accurately project future global change. Photosynthesis in land surface models (LSMs) is dependent on photosynthetic capacity, which is closely coupled to the enzymatic content of plant leaves. Most LSMs parameterize photosynthetic capacity using plant functional type-specific parameters, while others simulate it using soil nutrient-dependent values of leaf nutrient content. However, recent theoretical developments suggest that photosynthetic capacity acclimates to optimize photosynthesis primarily to aboveground climate. A key tenet of this optimization is that photosynthesis is maximized at the lowest possible nutrient use to build photosynthetic enzymes, such as Rubisco. Quantifications of this theory offer a simpler, yet more dynamic formulation for LSMs. Here, we integrated this optimization theory into the E3SM LSM (ELM) and simulated future photosynthesis under the RCP 8.5 climate scenario. In our simulation, we found that optimal acclimation resulted in an increase in global photosynthesis in 2100 as compared to present day, primarily as a result of CO₂ fertilization. Interestingly, we also simulated a decrease in Rubisco-based nitrogen, which occurred in response to both elevated CO₂ and elevated temperature. While the increase in photosynthesis is commonly observed in other LSM simulations, the reduction in leaf nitrogen is not. This effect is likely to alter simulated carbon-nitrogen interactions, possibly even reducing simulated nitrogen limitation of future productivity.

Authors:
Nicholas G. Smith (Texas Tech University)
Trevor F. Keenan (Lawrence Berkeley National Laboratory)
Qing Zhu (Lawrence Berkeley National Laboratory)
William J. Riley (Lawrence Berkeley National Laboratory)

The importance of carbon (C)-nutrient interactions to the prediction of future C uptake has long been recognized. Many ESMs in CMIP6 (the Coupled Model Intercomparison Project phase 6) are now including nitrogen (N) cycle and C-N interactions. However, only a few models in CMIP6 have developed the capability to include phosphorus (P) cycle processes and C-N-P interactions. The Energy Exascale Earth System Model (E3SM) land model (ELM) version 1 is one of the few that has this capability. Here we provide a comprehensive global scale evaluation of ELM v1. Using the International Land Model Benchmarking (ILAMB) system we show that the implementation of P cycle dynamics is critical to improving model simulated biomass, leaf area index (LAI), and global net C balance. The evaluation of model sensitivity to a step increase of CO₂ with free-air CO₂ enrichment (FACE) observational data suggests that ELM v1 is able to capture the field observed responses for photosynthesis, growth, LAI and vegetation C stocks. The good agreement between model simulations and FACE observations is mainly due to the introduction of a non-structural carbon pool in ELM v1. Model simulations showed that global C sources and sinks are significantly affected by P limitation, as the historical CO₂ fertilization effect was reduced by 20% and C emission due to land use and land cover change was 11% lower when P limitation was considered. Our study suggests that introduction of C-N-P coupling and a non-structural carbon pool will likely have substantial consequences for projections of future C uptake.

Authors:
Xiaojuan Yang (Oak Ridge National Laboratory)
Peter E. Thornton (Oak Ridge National Laboratory)
Daniel M. Ricciuto (Oak Ridge National Laboratory)
Forrest M. Hoffman (Oak Ridge National Laboratory)

This Town Hall will introduce the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign, wherein the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Program will deploy its second Mobile Facility (AMF2) to the Upper Gunnison Basin’s East River Watershed, located in the Elk Mountain range of the Colorado Rocky Mountains between September 2021 and June 2023. The AMF2 atmospheric observatory will use a suite of 3-dozen instruments to measure precipitation, aerosols, radiation, clouds, winds, temperature, humidity, and surface fluxes throughout the campaign.

As an integrated field laboratory, SAIL will be collocated, and work in close concert with the DOE Subsurface Biogeochemistry Research (SBR) program’s Watershed Function Scientific Focus Area (SFA), which is investigating surface and subsurface hydrology, biology, and chemistry in the same watershed. Together, these observations will quantify and characterize the major hydrological and atmospheric processes and their interactions that impact water and energy balances in the atmosphere-through-bedrock continuum within the East River Watershed.

The target audience includes the mountain research community including atmospheric scientists, hydrologists, snow scientists, and process and Earth System modelers, program managers (DOE BER, NASA, NSF, NOAA). The primary goal of this Town Hall is to engage and foster collaborations with the audience, so we will discuss the SAIL campaign observations, the process studies that the data can enable, and how the campaign can be used to confront and benchmark a wide range of models. We will also allocate significant time to discuss the potential science that SAIL data can enable, community data needs and interests, and opportunities for community participation and agency collaborations with the campaign.

Type:
Town Hall

Primary Contact:
Daniel Feldman (Lawrence Berkeley National Laboratory)

Presenters:
V. Chandrasekar (Colorado State University)
Allison C. Aiken (Los Alamos National Laboratory)
Jiwen Fan (Pacific Northwest National Laboratory)
Kenneth H. Williams (Lawrence Berkeley National Laboratory)
Jeffrey S. Deems (National Snow and Ice Data Center)
David Gochis (NCAR)
L. Ruby Leung (Pacific Northwest National Laboratory)

Sections:
Hydrology
Global Environmental Change
Cryosphere
Atmospheric Sciences

Cross-Listed:
H - Hydrology
GC - Global Environmental Change
C - Cryosphere
A - Atmospheric Sciences

Methane is a potent greenhouse gas with a shorter atmospheric lifetime than CO₂ but a stronger warming potential molecule for molecule. Concentrations of CH₄ continue to increase, making it a critical component of pathways to mitigate climate change. This session highlights bottom-up and top-down integration of measurements and model simulations of methane sources and sinks. Examples of relevant topics include wetland and freshwater emissions, sources from the agriculture and energy sectors, and inverse modeling and atmospheric isotopes. The session also invites research on inter-annual and decadal scale trends and variability. The research presented will contribute to an updated global methane budget being developed under the umbrella of the Global Carbon Project and to IPCC AR6 carbon budgets.

Type:
Poster

Primary Convener:
Robert B. Jackson (Stanford University)

Conveners:
Marielle Saunois (LSCE Laboratoire des Sciences du Climat et de l'Environnement)
Benjamin Poulter (NASA GSFC)
Josep Gili Canadell (CSIRO)

Chairs:
Robert B. Jackson (Stanford University)
Marielle Saunois (LSCE Laboratoire des Sciences du Climat et de l'Environnement)

OSPA Liaison:
Benjamin Poulter (NASA GSFC)

Index Terms:
0414 Biogeochemical cycles, processes, and modeling
0426 Biosphere/atmosphere interactions
0475 Permafrost, cryosphere, and high-latitude processes
0497 Wetlands

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Climate - SWIRL

Cross-Listed:
GC - Global Environmental Change

Trans-Disciplinary:
GC - Global Environmental Change

Co-Organized:
Global Environmental Change

Wetlands are responsible for ~30% of global methane (CH₄) emissions and introduce some of the largest uncertainties in the global CH₄ budget. Comparison of CH₄ emissions simulated by land surface models show that uncertainties arise from differences in model parameterization and wetland extents. Data-driven upscaling may help constrain model uncertainties by providing independent emissions estimates. Although eddy covariance flux measurements of carbon dioxide have been upscaled to estimate global gross primary production, similar products for CH₄ fluxes are lacking. To address this gap, we use data from 47 FLUXNET-CH₄ freshwater wetland sites with machine learning to 1) evaluate data-driven model performance in predicting global CH₄ fluxes; 2) identify useful classes of predictors and important single predictors from a large suite of remote sensing, climatic, topographic, and biometeorological covariates; and 3) predict monthly CH₄ emissions from freshwater wetlands at regional to global scales.

Globally, the model performed well (R² = 0.6, MAE = 26.2 nmol m⁻² s⁻¹, Bias = 1.6 nmol m⁻² s⁻¹). Normalized errors were largest at swamps (n = 6), four of which are distinctive tropical sites, and smallest at marshes (n = 10). Mean seasonal cycles were reproduced well (R² > 0.7) at two-thirds of sites, although interannual anomalies were not accurately reproduced. Gridded climatology and tower-measured biometeorology were the most useful covariate classes for predicting CH₄ fluxes, land cover (including inundation and vegetation cover) was intermediate; and soil, relief, and vegetation greenness were least useful. The most important individual predictors included nighttime land surface temperature, potential radiation, enhanced vegetation index, air temperature, and latent heat flux. Several static predictors were also useful, including percent agricultural land use and slope. Preliminary estimates of average (2001–2012) annual CH₄ emissions scaled by wetland area were 151 Tg CH₄ globally, in close agreement with recent bottom-up model estimates (Saunois et al. 2020), with 96 Tg (~64%) from the tropics, and 31 Tg (~21%) from &ht;45°N, in agreement with a recent northern upscaling effort (31–38 Tg; Peltola et al. 2019). We acknowledge the FLUXNET-CH₄ contributors for the data provided in these analyses.

Authors:
Gavin McNicol (Stanford University)
Etienne Fluet-chouinard (Stanford University)
Sara Knox (Stanford University)
Zutao Yang (Stanford University)
Zhen Zhang (University of Maryland)
Tuula Aalto (Finnish Meteorological Institute)
Sheel Bansal (U.S. Geological Survey)
Mathias Goeckede (Max Planck Institute for Biogeochemistry)
Jinxun Liu (U.S. Geological Survey)
Joe Melton (Environment and Climate Change Canada)
Andrew D. Richardson (Northern Arizona University)
William J. Riley (Lawrence Berkeley National Laboratory)
Rodrigo Vargas (University of Delaware)
Jeremy Irvin (Stanford University)
Sharon Zhou (Stanford University)
Andrew Ng (Stanford University)
Bejamin Poulter (NASA Goddard Space Flight Center)
Robert B. Jackson (Stanford University)

Scientists, practitioners and communities have accelerated their engagement and collaboration to produce decision-relevant and actionable science. In this session, we explore (1) how scientists build and strengthen partnerships with community members and other stakeholders; (2) how these novel and truly collaborative partnerships lead to decision-relevant tools, resources, or knowledge; and 3) co-production of knowledge where multiple types of knowledge, including Indigenous Knowledge and western scientific disciplines are combined. We invite on-the-ground stories and experiences, successes and challenges, and best practices that illustrate relationship-building, increased collaborative capacity, and the successful co-production of actionable science including federal, state, local, university, Indigenous and extension partners, to name a few. Through this collective sharing, we can harness characteristics of effective and transformative partnerships to better understand community needs and deliver stakeholder-driven and decision-relevant science. Together, we continue progress toward interdisciplinary and transformative science that is actionable and equitable.

Type:
Oral

Primary Convener:
Melissa Varga (Union of Concerned Scientists)

Conveners:
Julian Reyes (AAAS Science and Technology Policy Fellowship)
Colleen Strawhacker (National Science Foundation)
Elisabeth K. Larson (NASA)

Chairs:
Melissa Varga (Union of Concerned Scientists)
Julian Reyes (AAAS Science and Technology Policy Fellowship)
Colleen Strawhacker (National Science Foundation)
Elisabeth K. Larson (NASA)

OSPA Liaison:
Colleen Strawhacker (National Science Foundation)

Index Terms:
0299 General or miscellaneous
1630 Impacts of global change
6349 General or miscellaneous
6620 Science policy

Neighborhoods:
1. Science Nexus

SWIRLs and Tracks:
Science Communication - SWIRL

Permafrost shifts, changing riverine flow, and alterations in snow, rain, and evapo-transpiration processes all impact the high latitude regions of the globe and are strongly affecting the stakeholder communities that reside in, and rely on, this land. Two projects focused on examining the coupled human-physical system, capturing changes, and producing collaborative science that will assist Arctic communities better adapt, and mitigate these changes, are described herein. The “Interdisciplinary Research for Arctic Coastal Environments” (InteRFACE) project, funded by the Department of Energy, focuses on how coupled, multi-scale feedbacks among land processes, such as permafrost, snow, and water, and human systems, such as transportation and resource availability, will impact the trajectory of change across the Arctic coastal interface. InteRFACE brings together multiple DOE funding streams, researchers at several US National Labs, and scientists from the University of Alaska Fairbanks. The NOAA “Experimental Framework for Testing the National Water Model: Operationalizing the Use of Snow Remote Sensing in Alaska” project seeks to evaluate the National Water Model for Alaska, and operationalize the use of the system for improved river prediction and forecasting. This project is a collaboration between the University of Alaska Fairbanks, the National Center for Atmospheric Research, and the New Mexico Consortium. Research results, with a focus on the collaborative partnerships, will be described and shared.

Authors:
Katrina E. Bennett (Los Alamos National Laboratory)
Joel C. Rowland (Los Alamos National Laboratory)
Aubrey L. Dugger (National Center for Atmospheric Research)
Vladimir A. Alexeev (University of Alaska Fairbanks)
Alec P. Bennett (University of Alaska Fairbanks)
Bob Bolton (University of Alaska Fairbanks)
Diana L. Bull (Sandia National Laboratories)
Jessica E. Cherry (National Weather Service)
Ethan Coon (Oak Ridge National Laboratory)
Carl Dierking (University of Alaska Fairbanks)
Hajo Eicken (University of Alaska Fairbanks)
Meredydd Evans (Pacific Northwest National Laboratory)
Forrest M. Hoffman (Oak Ridge National Laboratory)
Benjamin M. Jones (U.S. Geological Survey)
Nicole Jeffery (Los Alamos National Laboratory)
Jitendra Kumar (Oak Ridge National Laboratory)
Olivia A. Lee (University of Alaska Fairbanks)
Emily Niebuhr (National Weather Service)
Anastasia Piliouras (Los Alamos National Laboratory)
Jon Schwenk (Los Alamos National Laboratory)
Kurt Solander (University of California Irvine)
David P. Streubel (National Weather Service)

The US Global Change Research Program (USGCRP) is celebrating 30 years of advancing global change science and understanding. This town hall, hosted by the USGCRP Interagency Working Group on Integrated Observations (ObsIWG), will highlight advances in observational capabilities and agency research efforts over the past 30 years that are relevant to climate and global change, focusing on interagency coordinated observational activities. A discussion period will follow allowing for the community to engage with members of the ObsIWG about opportunities for enhanced coordination of future observational efforts.

Type:
Town Hall

Primary Contact:
Diane Stanitski (NOAA ESRL Global Monitoring Laboratory)

Moderators:
Diane Stanitski (NOAA)
Sally A. McFarlane (Department of Energy Germantown)
Barry L. Lefer (University of Houston)
Monika Kopacz (NOAA)

Presenters:
James H. Crawford (NASA Langley Research Center)
Olga V. Kalashnikova (Jet Propulsion Laboratory, California Institute of Technology)
Gregory J. Frost (Chemical Sciences Laboratory)
Ravan Ahmadov (NOAA ESRL/CSL)
Jessica L. McCarty (Miami University Oxford)
Carlos R. Mechoso (UCLA)
Chris W. Fairall (NOAA Boulder)
Christopher S. Bretherton (Vulcan, Inc.)
Yangang Liu (Brookhaven National Laboratory)
Rene Garreaud (University of Chile)

Sections:
Ocean Sciences
Global Environmental Change
General
Atmospheric Sciences

Cross-Listed:
OS - Ocean Sciences
GC - Global Environmental Change
A - Atmospheric Sciences

Understanding of the physical-mechanisms underlying water, carbon, and nutrient cycling at the land-atmosphere interface rely on our perception of the climate-soil-vegetation interactions. For instance, land-use changes, ecosystem management, and climate variability alter the functionality of the Critical Zone, with potential implications for water resources, primary productivity, carbon sequestration, and land-atmosphere interaction. Despite the advances over the past decades, characterizing the effect of natural/human disturbances still necessitates a fundamental understanding of the interactions between hydrological, physical, and biogeochemical processes across spatiotemporal scales and biomes. Here, we solicit contributions aimed at building a mechanistic understanding of such interactions under different land-use changes, ecosystem management strategies, and climate forcings, through theoretical, modeling, experimental, and data analysis approaches. We welcome contributions that investigate fundamental and applied questions ranging from water and nutrient cycles to ecosystem productivity, water-carbon coupling to climate-soil-vegetation coevolution, plant water, and nutrient use efficiencies, ecological optimality, mineral-water interactions, and soil-carbon sequestration.

Type:
Oral

Primary Convener:
Salvatore Calabrese (Texas A&M University)

Conveners:
Guta Wakbulcho Abeshu (University of Houston)
Binayak Mohanty (Texas A&M University)
Hong-Yi Li (University of Houston)
William J. Riley (Lawrence Berkeley National Laboratory)

Chairs:
Salvatore Calabrese (Texas A&M University)
Binayak Mohanty (Texas A&M University)
Hong-Yi Li (University of Houston)
Guta Wakbulcho Abeshu (University of Houston)

OSPA Liaison:
Binayak Mohanty (Texas A&M University)

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Soils - SWIRL

Cross-Listed:
EP - Earth and Planetary Surface Processes
B - Biogeosciences

Trans-Disciplinary:
B - Biogeosciences

Phenology is an integrative and sensitive indicator of ecosystem health and function that responds to climate, water and nutrient availability, disturbance, and environmental change. Understanding phenological responses to environmental change across spatial and temporal scales is critical for forecasting shifts in species activity and associated changes in biogeochemical cycling, landscape dynamics, and ecological processes. This session features recent advances in characterizing the spatio-temporal patterns in vegetation phenology using a variety of methods (e.g., satellite, drones, webcams, in situ measurements); determining underlying mechanistic processes; developing accurate model representations of vegetation phenology; and investigating phenological implications to key land surface processes and society.

Type:
Poster

Primary Convener:
Jitendra Kumar (Oak Ridge National Laboratory)

Conveners:
William Walter Hargrove (USDA Forest Service)
Min Chen (Pacific Northwest National Laboratory)
Jin Wu (Brookhaven National Laboratory)

Index Terms:
0414 Biogeochemical cycles, processes, and modeling
0439 Ecosystems, structure and dynamics
0466 Modeling
0480 Remote sensing

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Climate - SWIRL

Cross-Listed:
IN - Earth and Space Science Informatics
GC - Global Environmental Change

A wide range of processes influence the response of terrestrial carbon fluxes (NEE, GPP, TER, fires, lateral export) to changes in land and atmospheric moisture availability. Of equal importance is the role of the vegetation and soils in regulating land-atmosphere moisture fluxes (precipitation, ET), which in turn feeds back to the water cycle and the climate system.

This session encourages contributions exploring carbon-water interactions at various spatial and temporal scales, covering all types of biomes (boreal, temperate and tropical forests, grasslands, wetlands). Contributions might include for example 1) investigating the effect of nonlinearities in the response of ecosystems to weather and climate, 2) disentangling the impact of co-varying, drought-driven changes in soil moisture, vapour pressure deficit, or temperature, 3) using in-situ or satellite observations to evaluate or improve models, 4) developing new representations of plant and ecosystem response to stress (e.g. through plant hydraulics, optimality approaches, etc.).

Type:
Oral

Primary Convener:
Vincent Humphrey (California Institute of Technology)

Conveners:
Vincent Humphrey (California Institute of Technology)
Kimberly A. Novick (Indiana University Bloomington)
Ana Bastos (Ludwig Maximilians University of Munich)
Markus Reichstein (Max Planck Institute for Biogeochemistry)

Chairs:
Kimberly A. Novick (Indiana University Bloomington)
Ana Bastos (Ludwig Maximilians University of Munich)
Markus Reichstein (Max Planck Institute for Biogeochemistry)
Vincent Humphrey (California Institute of Technology)

OSPA Liaison:
Vincent Humphrey (California Institute of Technology)

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Soils - SWIRL

Cross-Listed:
A - Atmospheric Sciences

Trans-Disciplinary:
H - Hydrology
GC - Global Environmental Change

The terrestrial carbon and water cycles are primarily driven by photosynthesis and transpiration that are both regulated by plant stomatal conductance. Such a physiological link not only determines ecosystem functioning, but also modulates flux exchanges between the biosphere and the atmosphere. The relationship between water losses via transpiration relative to carbon gains via photosynthesis can be estimated by plant water-use efficiency (WUE), a metric that involves multiple definitions across leaf to ecosystem scales. Despite its various functional forms, forest WUE trends inferred from different approaches ubiquitously increase in recent decades. Although several mechanisms have been proposed to explain rising forest WUE at seasonal time scales, none of them have examined the intra-seasonal variability of WUE and its impacts on long-term WUE trends. Here, we analyze the statistical distribution of sub-seasonal WUE at 33 eddy covariance sites with at least 10 years of measurements to investigate the effects of short-term WUE variability. Our random-forest variable importance analysis suggests that recent increases in site-specific WUE observations are strongly correlated with the corresponding trends inferred from its 95^th percentile. Further, our results demonstrate that seasonal mean WUE correlates well (r = 0.75 to 0.89) with the number of most active hours (i.e., cumulated hours when WUE exceeds a site-specific percentile), highlighting the importance of short-term favorable microclimatic conditions. Collectively, our findings suggest that a proper representation of seasonal cycles in WUE is needed to mechanistically explain recent increases in WUE observations and improve estimates in terrestrial carbon and water cycles.

Authors:
Kuang-Yu Chang (Lawrence Berkeley National Laboratory)
William J. Riley (Lawrence Berkeley National Laboratory)

Phenology is an integrative and sensitive indicator of ecosystem health and function that responds to climate, water and nutrient availability, disturbance, and environmental change. Understanding phenological responses to environmental change across spatial and temporal scales is critical for forecasting shifts in species activity and associated changes in biogeochemical cycling, landscape dynamics, and ecological processes. This session features recent advances in characterizing the spatio-temporal patterns in vegetation phenology using a variety of methods (e.g., satellite, drones, webcams, in situ measurements); determining underlying mechanistic processes; developing accurate model representations of vegetation phenology; and investigating phenological implications to key land surface processes and society.

Type:
Poster

Primary Convener:
Jitendra Kumar (Oak Ridge National Laboratory)

Conveners:
William Walter Hargrove (USDA Forest Service)
Min Chen (Pacific Northwest National Laboratory)
Jin Wu (Brookhaven National Laboratory)

Index Terms:
0414 Biogeochemical cycles, processes, and modeling
0439 Ecosystems, structure and dynamics
0466 Modeling
0480 Remote sensing

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Climate - SWIRL

Cross-Listed:
IN - Earth and Space Science Informatics
GC - Global Environmental Change

Understanding of the physical-mechanisms underlying water, carbon, and nutrient cycling at the land-atmosphere interface rely on our perception of the climate-soil-vegetation interactions. For instance, land-use changes, ecosystem management, and climate variability alter the functionality of the Critical Zone, with potential implications for water resources, primary productivity, carbon sequestration, and land-atmosphere interaction. Despite the advances over the past decades, characterizing the effect of natural/human disturbances still necessitates a fundamental understanding of the interactions between hydrological, physical, and biogeochemical processes across spatiotemporal scales and biomes. Here, we solicit contributions aimed at building a mechanistic understanding of such interactions under different land-use changes, ecosystem management strategies, and climate forcings, through theoretical, modeling, experimental, and data analysis approaches. We welcome contributions that investigate fundamental and applied questions ranging from water and nutrient cycles to ecosystem productivity, water-carbon coupling to climate-soil-vegetation coevolution, plant water, and nutrient use efficiencies, ecological optimality, mineral-water interactions, and soil-carbon sequestration.

Type:
eLightning

Primary Convener:
Salvatore Calabrese (Texas A&M University)

Conveners:
Binayak Mohanty (Texas A&M University)
Hong-Yi Li (University of Houston)
Guta Wakbulcho Abeshu (University of Houston)
William J. Riley (Lawrence Berkeley National Laboratory)

Chairs:
Binayak Mohanty (Texas A&M University)
Guta Wakbulcho Abeshu (University of Houston)
Salvatore Calabrese (Texas A&M University)

OSPA Liaison:
Hong-Yi Li (University of Houston)

Index Terms:
0414 Biogeochemical cycles, processes, and modeling
1807 Climate impacts
1813 Eco-hydrology
1834 Human impacts

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Soils - SWIRL

Cross-Listed:
EP - Earth and Planetary Surface Processes
B - Biogeosciences

Trans-Disciplinary:
B - Biogeosciences

Co-Organized:
Biogeosciences

Understanding of the physical-mechanisms underlying water, carbon, and nutrient cycling at the land-atmosphere interface rely on our perception of the climate-soil-vegetation interactions. For instance, land-use changes, ecosystem management, and climate variability alter the functionality of the Critical Zone, with potential implications for water resources, primary productivity, carbon sequestration, and land-atmosphere interaction. Despite the advances over the past decades, characterizing the effect of natural/human disturbances still necessitates a fundamental understanding of the interactions between hydrological, physical, and biogeochemical processes across spatiotemporal scales and biomes. Here, we solicit contributions aimed at building a mechanistic understanding of such interactions under different land-use changes, ecosystem management strategies, and climate forcings, through theoretical, modeling, experimental, and data analysis approaches. We welcome contributions that investigate fundamental and applied questions ranging from water and nutrient cycles to ecosystem productivity, water-carbon coupling to climate-soil-vegetation coevolution, plant water, and nutrient use efficiencies, ecological optimality, mineral-water interactions, and soil-carbon sequestration.

Type:
eLightning

Primary Convener:
Salvatore Calabrese (Texas A&M University)

Conveners:
Binayak Mohanty (Texas A&M University)
Hong-Yi Li (University of Houston)
Guta Wakbulcho Abeshu (University of Houston)
William J. Riley (Lawrence Berkeley National Laboratory)

Chairs:
Binayak Mohanty (Texas A&M University)
Guta Wakbulcho Abeshu (University of Houston)
Salvatore Calabrese (Texas A&M University)

OSPA Liaison:
Hong-Yi Li (University of Houston)

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Soils - SWIRL

Cross-Listed:
EP - Earth and Planetary Surface Processes
B - Biogeosciences

Trans-Disciplinary:
B - Biogeosciences

Co-Organized:
Biogeosciences

Snow properties in seasonal and perennial snow environments vary over many orders of spatial and temporal magnitude and at a wide range of scales. Large variations in bulk properties, such as snow depth, snow water equivalent, and impurity content can occur over distances less than 100 meters and time scales of minutes to hours, complicating measurement and modeling efforts. Topography and vegetation combine with variability in precipitation, wind, and melt to create a complex distribution of snow properties across the landscape and through time. This session will focus on studies which quantify spatial and temporal variations in snow and snow-related processes at medium to large scales for a wide range of problems, including snow hydrology, snow avalanches, and remote sensing or modeling efforts.

Type:
Poster

Primary Convener:
Jeffrey S. Deems (National Snow and Ice Data Center)

Conveners:
Jesus Revuelto (Instituto Pirenaico de Ecología)
Hans-Peter Marshall (Boise State University)
Ernesto Trujillo (USDA-ARS)

Chairs:
Jeffrey S. Deems (University of Colorado)
Jesus Revuelto (Instituto Pirenaico de Ecología)

OSPA Liaison:
Jesus Revuelto (Instituto Pirenaico de Ecología)

Index Terms:
0736 Snow
0740 Snowmelt
0742 Avalanches
1863 Snow and ice

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Earth Processes - SWIRL

Cross-Listed:
H - Hydrology
GC - Global Environmental Change

Land surface snow processes, which are challenging to simulate in Earth system models, are of critical importance in northern high-latitude regions, where they influence many other biogeophysical and biogeochemical processes. Capturing them in models is particularly difficult because of highly heterogeneous surface properties and lack of reliable data in remote and harsh regions. Here we present an offline land surface simulation using the Energy Exascale Earth System Model (E3SM) Land Model (ELM) over northern high-latitudes (>=60°N) at a half-degree spatial resolution. Results are evaluated using the ILAMB package and the NCAR Land Diagnosis Tool (as shown on https://elm-ngee-webserver.ornl.gov/). For assessing snow processes and their consequences on plant phenology, we derived DOYs (day of year) of snow melt and ground cover of 1998-2019 from northern hemisphere daily snow cover products by the US National Ice Center’s Interactive Multi-sensor Snow and Ice Mapping System (USNIC-IMS).

USNIC-IMS data showed that earlier snow melt occurred in 2000-2010 (from DOY ~160 to ~150), but then began to reverse (DOY ~155 in last 3 years), with large spatial-temporal variations. Combined with slightly earlier ground snow-cover since around 2010, yearly snow-free period increased from ~115 to 130 days around 2010 and then dropped to ~120 days in recent years. Remarkably, offline ELM simulations, with GSWP3v2 forcing, exhibited those trends., and simulated yearly-averaged 2.4+/-3.0 days earlier snow-cover and 6.4+/-3.4 days earlier melt, and thus 6.6+/-3.9 days longer snow-free season, compared to the observations.

Model-data discrepancies may be caused by model forcing or snow algorithms or both, which partially contributed to vegetation phenological shifts (and to spatiotemporal LAI mismatches) in some Arctic regions identified by two Diagnosis Tools. For example, severe under-estimation of LAI (and thus SOM) and phenological shifts apparently exist in Northeastern Siberian Russia and Northeastern Canada. Those biases could be a consequence of late snow melt and a short snow-free season due to heavy or extended winter snowfall. Our study demonstrates that data integration, model development and fidelity assessments are critical to further improve ELM performance in the pan-Arctic.

Authors:
Fengming Yuan (Oak Ridge National Laboratory)
Daniel M. Ricciuto (Oak Ridge National Laboratory)
Min Xu (Oak Ridge National Laboratory)
Nathan Collier (Oak Ridge National Laboratory)
Xiaoying Shi (Oak Ridge National Laboratory)
Dali Wang (Oak Ridge National Laboratory)
Forrest M. Hoffman (Oak Ridge National Laboratory)
Peter E. Thornton (Oak Ridge National Laboratory)
Stan Wullschleger (Oak Ridge National Laboratory)

Intensive evaluation and analyses of climate models creates a foundation for understanding climate variability. There has been an explosion of observing systems on existing and many new platforms and new climate model approaches such as machine learning to parameterizations. These advances are leading to significant challenges to process, integrate and assimilate multiple model and observational data from different sources – due to huge volumes, vast ranges of spatial and temporal scales, as well as inconsistencies in data formats, structures, and metadata. Increasingly, data organizations are integrating data into the cloud that enables scientists to access, analyze, share data and collaborating on research papers in the cloud. Scientists are rethinking how they will leverage this new environment to analyze their model and observational data in the future. Developers need to reach across infrastructure boundaries transparently with scalable solutions, while effectively moving processing and analysis, but not control, away from users and closer to the data. This session seeks to present recent advances and works in progress including but not limited to: a) novel architectures or use-cases that support seamless access and processing of large climate datasets, e.g. CMIP, Obs4MIPs, and CREATE; b) latest status of integrating data into ESGF or similar repository systems; c) tools and services for inter-comparisons of climate models; d) large data processing methods borrowed from optimization, machine learning and semantics; e) data fusion techniques for large observational data sets acquired by Microwave, Infrared, Active, Passive and other multi and hyper-spectral sensors (such as LIDAR, SAR, Radiometers, Ceilometers).

Type:
Oral

Primary Convener:
Suhung Shen (NASA Goddard Space Flight Center and George Mason University)

Conveners:
Christian Page (CERFACS)
Milton Halem (University of Maryland Baltimore County)
David J. Meyer (NASA Goddard Space Flight Center)

Chairs:
Christian Page (CERFACS)
Suhung Shen (NASA Goddard Space Flight Center and George Mason University)
Milton Halem (University of Maryland Baltimore County)

OSPA Liaison:
Suhung Shen (NASA Goddard Space Flight Center and George Mason University)

Index Terms:
3360 Remote sensing
1626 Global climate models
1920 Emerging informatics technologies
1932 High-performance computing

Neighborhoods:
1. Science Nexus

SWIRLs and Tracks:
Data & Rising Technologies - SWIRL

Cross-Listed:
OS - Ocean Sciences
GC - Global Environmental Change
B - Biogeosciences
A - Atmospheric Sciences

A Land Model Testbed (LMT), designed to provide a computational framework for systematically assessing model fidelity and supporting rapid development of complex multiscale models, offers a general-purpose workflow for conducting large ensemble simulations of multiple land surface models, post-processing large volumes of model output, and evaluating model results.

It leverages existing tools for launching model simulations and the International Land Model Benchmarking (ILAMB) package for assessing model fidelity through comparison with best-available observational datasets.

Increased complexity and proliferation of uncertain parameters in process representations in land surface models has driven the need for frequent and intensive testing and evaluating of models to quantify uncertainties and optimize parameters such that results are consistent with observations.

The LMT described here meets these needs by providing tools to run thousands of ensemble simulations simultaneously on high performance computing resources, like the Summit supercomputer at the Oak Ridge Leadership Computing Facility, as well as cloud environments like Amazon Web Services, post-processing outputs, automating execution of an enhanced version of ILAMB with site-specific benchmarks and multivariate functional relationships, and by offering ensemble diagnostics and a customizable dashboard for displaying model performance metrics and associated graphics.

We envision the LMT capabilities will serve as a foundational computational resource for a proposed modeling and synthesis center focused on terrestrial multiscale model-data integration.

Authors:
Sarat Sreepathi (Oak Ridge National Laboratory)
Min Xu (Oak Ridge National Laboratory)
Nathan Collier (Oak Ridge National Laboratory)
Jitendra Kumar (Oak Ridge National Laboratory)
Jiafu Mao (Oak Ridge National Laboratory)
Forrest M. Hoffman (Oak Ridge National Laboratory)

Terrestrial ecosystems are experiencing chronic increases in water stress with global change. In particular, more frequent and intense drought events can lead to down-regulation of vegetation physiological processes, increases of biotic stress (e.g. bark beetles), and even mortality. Plant hydraulic traits play a key role in vegetation drought responses because they modulate plant water transport systems and can influence both short- and long-term plant ecophysiological processes. However, studies of vegetation drought responses and plant hydraulics are still challenging given the complexity and limited cross-scale observations in plant physiology, functional diversity, and spatial environmental heterogeneity. This session aims to highlight advances in observing plant hydrodynamics and responses to drought from tissue, individual to ecosystem and landscape scales and integration of these diverse data streams to improve modeling of vegetation drought stress and plant hydraulics. Studies from both natural and agricultural ecosystems are welcomed.

Type:
Oral

Primary Convener:
Xiangtao Xu (Cornell University)

Conveners:
Anna T. Trugman (University of Utah)
Leander D.L. Anderegg (University of California Berkeley)
William Anderegg (University of Utah)

Chairs:
Xiangtao Xu (Cornell University)
Anna T. Trugman (University of Utah)

OSPA Liaison:
Leander D.L. Anderegg (University of California Berkeley)

Index Terms:
0439 Ecosystems, structure and dynamics
0466 Modeling
0476 Plant ecology
0480 Remote sensing

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Earth Processes - SWIRL

Cross-Listed:
H - Hydrology
GC - Global Environmental Change

Vegetation growth is affected not only by the concurrent climate, but also its status in the past and the associated lagged responses. Favorable climate in the past may stimulate vegetation growth to surpass the ecosystem carrying capacity, leave an ecosystem vulnerable to climate stresses. This phenomenon, known as structural overshoot, can greatly contribute to worldwide drought stress and forest mortality, but the magnitude of the impact is poorly known due to the dynamic nature of overshoot and complex influencing timescales. Here we use a dynamic statistical learning approach to identify and characterize ecosystem structural overshoot globally, and quantify the associated drought impacts. When applied to satellite observation of terrestrial vegetation during 1981–2015, we find that structural overshoot contributed to 33.9% of the drought. Overshoot droughts occur more frequently in mid-latitude semi-arid or dry sub-humid regions, with higher impacts in boreal ecosystems. The fraction of droughts related to overshoot is strongly associated with biodiversity, with mean annual temperature, vegetation coverage, and aridity as secondary factors. These overshoot droughts are not only more likely to happen in warmer months, leading to higher risks of compound extreme drought and heat, but also causing faster vegetation decline compared to normal droughts, contributing to the development of flash drought, and causing large impact on ecosystem stability. Although the overall overshoot numbers have decreased over the past 35 years, the hotspots regions still exist, especially in vulnerable ecosystems where drought has become more prevalent.

Authors:
Yao Zhang (Lawrence Berkeley National Laboratory)
Trevor F. Keenan (Lawrence Berkeley National Laboratory)
Sha Zhou (Columbia University)

This session highlights water cycle research that describes the linkages between the ocean, atmosphere, and land hydrology. Contributions are invited on all aspects of water cycle research including analyses undertaken using in situ and spaceborne observations from current (e.g., GO-SHIP, Argo, SMAP, SMOS, GRACE-FO, GPM, GCOM-W), past (e.g., Aquarius, TRMM, GRACE), and future (e.g., SWOT, CIMR) satellite missions, estimates based on numerical models, data assimilation systems, as well as climate model projections and theoretical contributions. We particularly welcome studies that consider multiple realms (the ocean, atmosphere, land surface and subsurface), and provide compelling evidence for linkages between these, describing coherent water cycle variability and change. We welcome global and regional assessments across these interfaces, and contributions that demonstrate what needs to be observed to ensure that long-term changes in the water cycle are accurately quantified.

Type:
Oral

Primary Convener:
Paul James Durack (Lawrence Livermore National Laboratory)

Conveners:
John T. Reager (NASA Jet Propulsion Laboratory)
Nadya Vinogradova Shiffer (NASA Headquarters)

Chairs:
Paul James Durack (Lawrence Livermore National Laboratory)
John T. Reager (NASA Jet Propulsion Laboratory)
Nadya Vinogradova Shiffer (NASA Headquarters)
Francis H. Lambert (University of Exeter)

OSPA Liaison:
Paul James Durack (Lawrence Livermore National Laboratory)

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Extreme Events & Hazards - SWIRL
Climate - SWIRL

Cross-Listed:
OS - Ocean Sciences
H - Hydrology
C - Cryosphere
A - Atmospheric Sciences

Co-Sponsored:
EGU: European Geosciences Union
AMS: American Meteorological Society

Trans-Disciplinary:
OS - Ocean Sciences
H - Hydrology
C - Cryosphere
A - Atmospheric Sciences

Global warming is expected to change surface water availability (precipitation minus evapotranspiration, P−E) and hence freshwater resources. However, the influence of land-atmosphere feedbacks on future P−E changes and the underlying mechanisms remain unclear. Here we demonstrate that soil moisture (SM) strongly impacts future P−E changes, especially in drylands, through regulating evapotranspiration and atmospheric moisture inflow. To do so, we use transient simulations from general circulation models, both with and without long-term SM changes, along with empirical statistical models of SM-atmosphere feedbacks. We find a consistent negative SM feedback on P−E, which may offset up to ~60% of the decline in dryland P−E that is otherwise expected to occur. The negative feedback is not caused by atmospheric thermodynamic responses, i.e., temperature and humidity changes, to declining SM, but rather by SM-related regulation of atmospheric circulation and vertical ascent that enhance moisture transport towards drylands. This SM effect is a large source of uncertainty in projected dryland P−E changes, underscoring the need to better constrain future SM changes and improve representation of SM-atmosphere processes in models.

Authors:
Sha Zhou (Columbia University)
Park Williams (Columbia University)
Benjamin R. Lintner (Rutgers University)
Alexis M. Berg (Rutgers University)
Yao Zhang (Lawrence Berkeley National Laboratory)
Trevor F. Keenan (Lawrence Berkeley National Laboratory)
Benjamin Cook (NASA-GISS)
Stefan Hagemann (Heimholtz-Zentrum Geesthacht)
Sonia I. Seneviratne (ETH Zurich)
Pierre Gentine (Columbia University)

The Environmental Systems Science (ESS) program, in the US Department of Energy’s Office of Science, supports fundamental research needed to unravel the coupled physical, chemical, and biological processes that control the structure and functioning of terrestrial ecosystems and integrated watersheds across critical spatial and temporal scales. The goal is to advance robust, predictive understanding of these systems for use in Earth system, ecosystem and reactive transport models. Comprised of Terrestrial Ecosystem System Science (TES) and Subsurface Biogeochemical Research (SBR), the interdisciplinary research community supported by ESS addresses these complex questions using a systems approach, combining iterative model-driven experimentation and observation, new measurements, field studies, manipulative studies, and state of the art models. At this Town Hall, Program Managers will provide updates on the ESS portfolios and strategies, including linkages to other programs within Biological and Environmental Research (BER) at DOE and across other federal agencies. Finally, programmatic priorities for funding opportunities will be described, including both scientific and infrastructure needs. Significant time for discussion and questions will follow these brief presentations.

Type:
Town Hall

Primary Contact:
Jennifer S. Arrigo (Department of Energy Germantown)

Moderator:
Jennifer S. Arrigo (Department of Energy Germantown)

Presenters:
Gerald L. Geernaert (Department of Energy)
Daniel B. Stover (Department of Energy Germantown)
Paul E. Bayer (Department of Energy Germantown)

Sections:
Hydrology
Global Environmental Change
General
Biogeosciences

Cross-Listed:
H - Hydrology
GC - Global Environmental Change
Biogeosciences

Climate change is unfolding faster in the high northern latitudes than anywhere else on Earth. These changes are impacting ecological processes directly, through warmer temperatures and changing precipitation, and indirectly, though increasing frequency of climate-driven disturbances such as wildfire, outbreaks of pests and pathogens, and permafrost thaw. Although some ecosystems are resistant or resilient to these changes, many are shifting to new states, altering the function of the Arctic-boreal region. This session invites contributions in terrestrial ecology and carbon cycle science that provide conceptual, regional, or global insights into the resilience and vulnerability of the Arctic-boreal region, including its wildlife and ecosystem services, to changing climate. Contributions may address any geographic area of this region. We welcome studies that use in situ, airborne, and satellite remote sensing observations, and models, or some combination thereof, to conceptualize, detect, predict or forecast the changing function of this region in the earth system.

Type:
eLightning

Primary Convener:
Abhishek Chatterjee (NASA Goddard Space Flight Center)

Conveners:
Peter C. Griffith (NASA/GSFC)
Michelle C. Mack (Northern Arizona University)
Natalie Boelman (Lamont-Doherty Earth Observatory)
Scott J. Goetz (Northern Arizona University)

Chairs:
Peter C. Griffith (NASA/GSFC)
Natalie Boelman (Lamont-Doherty Earth Observatory)
Michelle C. Mack (Northern Arizona University)

OSPA Liaison:
Elisabeth K. Larson (NASA)

Index Terms:
0414 Biogeochemical cycles, processes, and modeling
0428 Carbon cycling
0439 Ecosystems, structure and dynamics
0475 Permafrost, cryosphere, and high-latitude processes

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Climate - SWIRL

Cross-Listed:
GC - Global Environmental Change
A - Atmospheric Sciences

Trans-Disciplinary:
GC - Global Environmental Change
A - Atmospheric Sciences

Co-Organized:
Global Environmental Change
Atmospheric Sciences

The Arctic is undergoing rapid changes in climate, vegetation composition and productivity. To understand the impacts of climate change on the function of Arctic tundra ecosystems, it is crucial to understand vegetation distribution and heterogeneity across large spatial scales. Knowledge of the environmental drivers controlling current vegetation composition and distribution is necessary for modeling potential shifts under a warming climate.

Our study was focused on three watersheds in the Seward Peninsula of Alaska, where field surveys were conducted as part of the US DOE’s NGEE-Arctic project. Using airborne hyperspectral imagery from NASA AVIRIS-NG, we developed a Deep Neural Network-based classifier to create a high resolution (5m) map of Arctic tundra plant communities with an accuracy exceeding 80%. Analysis of landscape patterns, using area and aggregation based metrics, show Alder-Willow Shrub and Tussock-Lichen Tundra communities occupy a greater proportion of the landscape and are more clumped together compared to Mesic Graminoid Herb Meadow and Sedge-Willow-Dryas Tundra communities.

We also developed an Environmental Niche Model to understand the relative importance of various environmental drivers in determining the presence/absence of plant communities. Preliminary results show that microtopography (e.g elevation) and soil moisture are the primary drivers of vegetation distribution at the landscape scale. Keystone species, like nitrogen-fixing Alder shrubs, also influence the nutrient availability and vegetation communities in their hydrologically connected downslope neighborhood. High resolution maps of plant communities will provide a better representation of above-ground trait variability in Earth System Models, and will provide data for model parameterization, benchmarking and validation. Insights from niche modeling could improve our understanding of mechanisms and environmental drivers of vegetation distribution and succession.

Authors:
Venkata Shashank Konduri (Northeastern University)
Jitendra Kumar (Oak Ridge National Laboratory)
Forrest M. Hoffman (Oak Ridge National Laboratory)
Verity G. Salmon (Oak Ridge National Laboratory)
Colleen Iversen (Oak Ridge National Laboratory)
Amy Breen (University of Alaska Fairbanks)
William W. Hargrove (USDA Forest Service)

Our understanding of energy, water, and greenhouse gas cycling within the earth system is grounded in in-situ observations. Globally, hundreds of eddy-covariance flux sites, as well as aircraft, measure exchanges of energy and greenhouse gases between ecosystems and the atmosphere.

Many flux sites contribute to regional networks and the global FLUXNET, which provides globally synthesized and comprehensive datasets. Such joint efforts serve as the foundation for studying energy, water, and greenhouse gas cycling from local to global and from diel to decadal scales.

This session focuses on the current state and future perspectives of flux measurements, synthesis, and modeling through collaborations and partnerships. We welcome contributions that improve our understanding through theories, instrumentation, models, datasets, and applications. Submissions that integrate different data types, GHGs, regions or scales are particularly encouraged, as well as new developments that improve the quality, interoperability, and reproducibility of data and tools.

Type:
Oral

Primary Convener:
Gilberto Pastorello (Lawrence Berkeley National Laboratory)

Conveners:
David Durden (National Ecological Observatory Network)
Housen Chu (Lawrence Berkeley National Laboratory)
Dario Papale (University of Tuscia)

Chairs:
Gilberto Pastorello (Lawrence Berkeley National Lab)
Housen Chu (Lawrence Berkeley National Laboratory)

OSPA Liaison:
Housen Chu (Lawrence Berkeley National Laboratory)

Index Terms:
0414 Biogeochemical cycles, processes, and modeling
0426 Biosphere/atmosphere interactions
0428 Carbon cycling
0438 Diel, seasonal, and annual cycles

Neighborhoods:
3. Earth Covering

Cross-Listed:
IN - Earth and Space Science Informatics
H - Hydrology
GC - Global Environmental Change
A - Atmospheric Sciences

As a major pathway for ecosystems to lose water, evapotranspiration (ET) is an essential process that affects the water cycle and land-atmosphere feedback in the earth system. Elevated CO₂ significantly affects ecosystems, by increasing photosynthesis and/or reducing stomatal conductance, which affects both ET and carbon assimilation. These direct and indirect effects have been quantified by model simulations, however are rarely constrained with ecosystem level direct, and long-term observations. Here we analyzed the high-frequency eddy covariance (EC) based observations at 80 sites from Fluxnet and AmeriFlux that have more than 10 years of observations to quantify the effects of CO₂ on ET, and water use efficiency (WUE). We investigated the drivers of trends and interannual variation of WUE at all sites. Results indicate that among all sites, the majority of sites did not have a significant trend of ET over time; at the same time, 25 sites showed a significant increase in the ET over time and 11 sites have a significant ET decrease over time. As for the WUE, we found a significant increase trend in WUE at 26 sites. We also found that while net radiation, gross primary production, and soil water content contributed most for the interannual variation of ET for most sites, the elevated CO₂ also played a significant role in regulating the long-term trends of ET at most sites.

Authors:
Xinchen Lu (University of California Berkeley)
Trevor F. Keenan (Lawrence Berkeley National Laboratory)

Greenhouse gas emission inventories, climate mitigation planning, forest carbon sequestration and Payment for Ecosystem Services (PES) programs, cap-and-trade systems, self-reporting programs, and their associated Monitoring, Reporting and Verification (MRV) frameworks depend upon data that are accurate, systematic, practical, and transparent. For carbon, there are multiple MRV frameworks in existence, reflecting a diversity of spatial scales, governing bodies, and relevant policies. Given the scientific challenges, policy importance, and breadth of activities occurring around the world, this session will focus on advances in research and applications, including decision support and policy, that align or address stakeholder needs through the measuring, modeling, and monitoring of strategic carbon pools. This session will also feature a panel of Stakeholders representing Local, State, and National Government Agencies and NGOs.

Type:
Poster

Primary Convener:
Peter C. Griffith (NASA Goddard Space Flight Center)

Conveners:
George C. Hurtt (University of Maryland)
Molly Elizabeth Brown (University of Maryland)

Chairs:
Peter C. Griffith (NASA Goddard Space Flight Center)
George C. Hurtt (University of Maryland)

OSPA Liaison:
Molly Elizabeth Brown (University of Maryland)

Index Terms:
0414 Biogeochemical cycles, processes, and modeling
0428 Carbon cycling
0466 Modeling
0480 Remote sensing

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Climate - SWIRL

Cross-Listed:
A - Atmospheric Sciences

Agroecosystems play a vital role in regional and global carbon cycles. Quantifying the carbon budget of agroecosystems remains a challenge mainly due to the complex impacts of human management on the carbon cycle of agroecosystems. Model-data fusion is a promising approach to accurately quantify the carbon budget of agroecosystems given more and more observations become available from satellite remote sensing. Here we present a model-data fusion system to quantify the carbon budget of the U.S. Midwestern agroecosystem. We first evaluated the performance of an advanced agroecosystem model, ecosys, in simulating carbon budget over the U.S. Midwestern. We conducted model simulations and evaluations at 7 cropland eddy-covariance sites in the U.S. Midwestern. The site-level simulations show that ecosys model captured both the magnitude and seasonal patterns of carbon fluxes (i.e. GPP, NEE, Reco), LAI, and dynamic of plant carbon allocation processes with high accuracy. We then scaled the simulations up to the 293 counties across three I-states (i.e. Illinois, Indiana, and Iowa). We constrained the model with a novel NIRv-based remotely sensed GPP product and crop yield data from USDA National Agricultural Statistics Service in the even years during 2001 and 2018, and evaluated the model performance in the odd years during the same period. The results show that the constrained ecosys model reproduced the spatial distribution and interannual variability of corn and soybean yield in the three I-states. The responses of the carbon cycle processes to the environmental variability obtained from the constrained model simulations were consistent with the observed ones, revealing the applicability of the constrained ecosys model in simulating the impacts of future climate change on the carbon cycle of the U.S. Midwestern agroecosystems. We finally quantified the carbon budget of the U.S. Midwestern agroecosystems at county scale using the constrained ecosys model under both historic and future climate conditions.

Authors:
Wang Zhou (University of Illinois Urbana-Champaign)
Kaiyu Guan (University of Illinois Urbana-Champaign)
Bin Peng (University of Illinois Urbana-Champaign)
Jinyun Tang (Lawrence Berkeley National Laboratory)
Zhenong Jin (University of Minnesota)
Chongya Jiang (University of Illinois Urbana-Champaign)
Robert F. Grant (University of Alberta)
Symon Mezbahuddin (University of Alberta)

Emergent patterns in both models and observations repeatedly hint at simpler aggregate responses within the complexity of the terrestrial carbon cycle; knowledge of these can accelerate our capacity to advance understanding of the terrestrial biosphere and to eliminate plausible but inaccurate representations. We are entering an era of high dimensional and increasingly informative Earth observations with more power to inform models, but the power of these new observations is just being tapped. This session will focus on the identification of modes and function emerging from terrestrial ecosystem carbon models and observations, with the aim to advance fundamental understanding of terrestrial carbon cycling. We welcome submissions highlighting recent progress on a range of themes spanning from emergent behavior in biospheric process models, model emulation and optimal model complexity theory to corresponding emergent patterns in satellite and aircraft observations, in-situ measurements, global in-situ datasets and terrestrial carbon cycle model-data fusion analyses.

Type:
Poster

Primary Convener:
Alexandra G. Konings (Stanford University)

Conveners:
A. Anthony Bloom (Jet Propulsion Laboratory, California Institute of Technology)
Nicholas Parazoo (Jet Propulsion Laboratory, California Institute of Technology)

Chairs:
Alexandra G. Konings (Stanford University)
A. Anthony Bloom (Jet Propulsion Laboratory, California Institute of Technology)
Nicholas Parazoo (Jet Propulsion Laboratory, California Institute of Technology)

OSPA Liaison:
Alexandra G. Konings (Stanford University)

Index Terms:
0428 Carbon cycling
0430 Computational methods and data processing
0466 Modeling
0480 Remote sensing

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Climate - SWIRL

Terrestrial ecosystems take up about 1/3 of anthropogenic emissions and serve as a critical carbon sink to mitigate climate change. The size of ecosystem carbon sink is dependent on the availability of exogenous (e.g. light, water and nutrient) and endogenous (e.g. carbohydrate, mycorrhizal) resources to ecosystems and how ecosystems use these resources. Ecosystems loose carbohydrate via respiration to provide metabolic energy to maintain the function and growth of living organisms in plants and soil. The carbon accumulated per unit carbon cost for an ecosystem (denoted as carbon cost efficiency, which is an extension of the commonly used carbon use efficiency by considering heterotrophic respiration) thus places a critical constraint on the potential carbon sink strength. In this study, we used a global network of eddy covariance measurements (~212 sites) to quantify the carbon cost efficiency of various ecosystems. We found strong relationships between carbon cost efficiency and environmental factors, soil and remotely-sensed vegetation status across flux sites, which allows for global inference of the potential of terrestrial ecosystems to offset future emissions.

Authors:
Xiangzhong Luo (Lawrence Berkeley National Laboratory)
Trevor F. Keenan (Lawrence Berkeley National Laboratory)
Housen Chu (Lawrence Berkeley National Laboratory)

Tropical forests comprise the most biologically diverse terrestrial ecosystems, cycle more carbon and water than any other biome, and play critical roles in regulating the global and regional climate systems. A better understanding of tropical forest processes is required to advance our understanding of the Earth system and to develop improved Earth System Models (ESMs). This session will focus on research in tropical forests including modeling, remote sensing and ground-based results. Processes to be highlighted include the response of tropical forest ecosystems to:

• global change pressures, such as land use change/changing demographics/increased atmospheric CO₂/altered rainfall/warming,
• extreme weather events (e.g., drought, heat waves, and extreme rainfall),
• climate variability (e.g., El Niño), and
• role of biodiversity, biogeochemistry (including soil fertility, nutrient limitation, soil respiration, and carbon sequestration), and phenology in modulating these processes.

We encourage submissions that consider tropical forest responses to global change from a wide range of perspectives.

Invited Speakers

1. Prof. Carlos A Nobre (http://www.nasonline.org/member-directory/members/20035943.html)
2. Prof. Andreas Huth (https://www.ufz.de/index.php?en=36559)

Type:
Poster

Primary Convener:
Robinson I. Negron Juarez (Lawrence Berkeley National Laboratory)

Conveners:
Yilin Fang (Battelle, Pacific Northwest National Laboratory)
Cynthia Wright (Oak Ridge National Lab)
Jessica Needham (Lawrence Berkeley National Laboratory)

Chairs:
Robinson I. Negron Juarez (Lawrence Berkeley National Lab)
Yilin Fang (Battelle, Pacific Northwest National Laboratory)
Cynthia Wright (Oak Ridge National Lab)
Jessica Needham (Lawrence Berkeley National Laboratory)

OSPA Liaison:
Jessica Needham (Lawrence Berkeley National Laboratory)

Index Terms:
3305 Climate change and variability
3337 Global climate models
0414 Biogeochemical cycles, processes, and modeling
0426 Biosphere/atmosphere interactions

Neighborhoods:
3. Earth Covering

Vegetation phenology is an integrated and sensitive indicator of ecosystem function that responds to disturbance, seasonality, variability and extremes in weather and climate. Phenology modulates surface energy balance and hydrological processes at the landscape scale. Knowledge of tropical forest phenology, however, is limited because highly diverse communities of tree species exhibit a variety of often-subtle phenological patterns. Heterogeneous tropical forests also exhibit highly variable and heterogeneous responses to biotic and abiotic stressors. While satellite remote sensing is commonly used to study vegetation phenology, frequent cloud cover, smoke from fires, and sensor artifacts complicate the study of tropical phenology. Widely used satellite platforms like MODIS and Landsat suffer from limitations of coarse spatial resolution or low temporal repeat frequency. We used satellite remote sensing data from two platforms: a) Sentinel-2 MultiSpectral Instrument operated by European Space Agency; and b) VENμS, a cooperative Earth observation program of Israel and France using a minisatellite that combines high spatial resolution and frequent repeats for selected study areas.

We focused our analysis at a series of sites across a gradient of wet and dry tropical forests and varying land use, from evergreen tropical forests, to savannas, to grasslands and croplands, and where both Sentinel-2 and VENμS imagery were available. We developed Normalized Difference Red Edge Index (NDRE) time series from both platforms, which showed greater dynamic range than the frequently used Normalized Difference vegetation Index (NDVI) from MODIS. Analyses of high spatio-temporal resolution data help reveal the dominant phenological patterns in heterogeneous tropical vegetation, despite frequent occultation from clouds and smoke. Preliminary analysis shows varying phenological responses during wet vs dry seasons across broadleaf evergreen forest, savannas and grasslands.

Authors:
Jitendra Kumar (Oak Ridge National Laboratory)
Morgan Steckler (University of Tennessee)
William W. Hargrove (USDA Forest Service)
Forrest M. Hoffman (Oak Ridge National Laboratory)

Climate change and land-use intensification have presented humanity with great challenges in maintaining food security and environmental sustainability. Cropland carbon sequestration achieved through conservative management practices is promising for enhancing soil organic carbon (SOC) and health, reducing greenhouse gas (GHG) emissions, and finally mitigating climate change. Improved modeling and monitoring capacities to track SOC changes and GHG emissions at granular scales are urgently needed in both academia and industry. We invite submissions focusing on: (1) developing scalable and cost-effective monitoring capacities to track SOC changes and GHG emissions; (2) synthesis of multi-source observations to infer cropland SOC changes and GHG emissions, including those from near-surface/airborne/satellite remote sensing, ground surveys, long-term agricultural experiments, and intensive sensor networks; (3) multi-scale process-based modeling of crop, management, environmental, and economic aspects of the agricultural system; and (4) systematic model-data integration to support decision-making for improved farming practice, policy design, and economic returns.

Type:
Poster

Primary Convener:
Bin Peng (University of Illinois at Urbana Champaign)

Conveners:
Zhenong Jin (University of Minnesota-Twin Cities)
Jinyun Tang (Lawrence Berkeley National Laboratory)
Kaiyu Guan (University of Illinois at Urbana Champaign)

Chairs:
Bin Peng (University of Illinois at Urbana Champaign)
Zhenong Jin (University of Minnesota-Twin Cities)
Jinyun Tang (Lawrence Berkeley National Laboratory)
Kaiyu Guan (University of Illinois at Urbana Champaign)

OSPA Liaison:
Bin Peng (University of Illinois at Urbana Champaign)

Index Terms:
0402 Agricultural systems
0428 Carbon cycling
1615 Biogeochemical cycles, processes, and modeling
1640 Remote sensing

Neighborhoods:
3. Earth Covering

SWIRLs and Tracks:
Natural Resources - SWIRL

Cross-Listed:
B - Biogeosciences

Predicting the consequences of manipulating genotype (G) and agronomic management (M) on agricultural ecosystem performances under future environmental (E) conditions remains a challenge. Crop modelling has the potential to enable society to assess the efficacy of G × M technologies to mitigate and adapt crop production systems to climate change. Despite recent achievements, dedicated research to develop and improve modelling capabilities from gene to global scales is needed to provide guidance on designing G × M adaptation strategies with full consideration of their impacts on both crop productivity and ecosystem sustainability under varying climatic conditions. Opportunities to advance the multiscale crop modelling framework include representing crop genetic traits, interfacing crop models with large-scale models, improving the representation of physiological responses to climate change and management practices, closing data gaps and harnessing multisource data to improve model predictability and enable identification of emergent relationships. A fundamental challenge in multiscale prediction is the balance between process details required to assess the intervention and predictability of the system at the scales feasible to measure the impact. An advanced multiscale crop modelling framework will enable a gene-to-farm design of resilient and sustainable crop production systems under a changing climate at regional-to-global scales.

Authors:
Bin Peng (University of Illinois Urbana-Champaign)
Kaiyu Guan (University of Illinois Urbana-Champaign)
Jinyun Tang (Lawrence Berkeley National Laboratory)
Elizabeth A. Ainsworth (University of Illinois Urbana-Champaign)
Senthold Asseng (University of Florida)
Carl Bernacchi (University of Illinois Urbana-Champaign)
Mark Cooper (University of Queensland)
Evan H. DeLucia (University of Illinois Urbana-Champaign)
Joshua W. Elliott (University of Chicago)
Frank Ewert (University of Bonn)
Robert F. Grant (University of Alberta)
David I. Gustafson (Independent Scientist)
Graeme L. Hammer (University of Queensland)
Zhenong Jin (University of Minnesota)
James W. Jones (Professor)
Hyungsuk Kimm (University of Illinois Urbana-Champaign)
David M. Lawrence (National Center for Atmospheric Research)
Yan Li (Beijing Normal University)
Danica L. Lombardozzi (National Center for Atmospheric Research)
Amy Marshall-Colon (University of Illinois Urbana-Champaign)
Carlos D. Messina (Corteva AgriScience)
Donald R. Ort (University of Illinois Urbana-Champaign)
James Schnable (University of Nebraska Lincoln)
C. Eduardo Vallejos (University of Florida)
Alex Wu (University of Queensland)
Xinyou Yin (Wageningen University)
Wang Zhou (University of Illinois Urbana-Champaign)

Emergent patterns in both models and observations repeatedly hint at simpler aggregate responses within the complexity of the terrestrial carbon cycle; knowledge of these can accelerate our capacity to advance understanding of the terrestrial biosphere and to eliminate plausible but inaccurate representations. We are entering an era of high dimensional and increasingly informative Earth observations with more power to inform models, but the power of these new observations is just being tapped. This session will focus on the identification of modes and function emerging from terrestrial ecosystem carbon models and observations, with the aim to advance fundamental understanding of terrestrial carbon cycling. We welcome submissions highlighting recent progress on a range of themes spanning from emergent behavior in biospheric process models, model emulation and optimal model complexity theory to corresponding emergent patterns in satellite and aircraft observations, in-situ measurements, global in-situ datasets and terrestrial carbon cycle model-data fusion analyses.

Type:
Oral

Primary Convener:
Alexandra G. Konings (Stanford University)

Conveners:
A. Anthony Bloom (Jet Propulsion Laboratory, California Institute of Technology)
Nicholas Parazoo (Jet Propulsion Laboratory, California Institute of Technology)

Chairs:
Alexandra G. Konings (Stanford University)
A. Anthony Bloom (Jet Propulsion Laboratory, California Institute of Technology)
Nicholas Parazoo (Jet Propulsion Laboratory, California Institute of Technology)

OSPA Liaison:
Alexandra G. Konings (Stanford University)

Neighborhoods:
3. Earth Covering

Terrestrial biosphere models (TBMs) are integral tools to study ecosystem–atmosphere carbon exchange. However, TBMs diverge markedly in their carbon flux estimates, limiting our ability to forecast climate change impacts on the terrestrial carbon cycle. Model evaluation has routinely focused on locally optimized processes and functional relationships, yet the space–time variability in carbon flux estimates at regional to continental scales has remained divergent as ever. Here, we leverage atmospheric CO₂ observations to explore emergent patterns in the divergence among TBM estimates of gross primary productivity (GPP) and net ecosystem exchange (NEE) over North America. To do so, we evaluate a suite of diagnostic, prognostic, and machine-learning TBMs and solar-induced fluorescence (SIF) data products based on how well their regional patterns explain the variability in biospheric CO₂ drawdown.

Models with GPP and NEE estimates that effectively reproduce atmospheric CO₂ variability (as is indicated by R² values) share a strong growing-season sink in the Midwest US croplands, whereas the remaining models tend to place most growing-season uptake in forests. The difference in model explanatory power depends mainly on how well models represent the seasonal cycle of the growing-season cropland sink, rather than the partition of fluxes across biomes. Our results suggest that improving model representation of cropland processes that govern the seasonality of fluxes, such as phenology and carbon allocation, is a priority for robust quantification of North American carbon exchange.

Authors:
Wu Sun (Carnegie Institution for Science)
Yuanyuan Fang (Carnegie Institution for Science)
Xiangzhong Luo (Lawrence Berkeley National Laboratory)
Yoichi Shiga (Universities Space Research Association)
Yao Zhang (Lawrence Berkeley National Laboratory)
Arlyn E. Andrews (NOAA)
Kirk W. Thoning (NOAA)
Joshua Fisher (NASA Jet Propulsion Laboratory)
Trevor F. Keenan (Lawrence Berkeley National Laboratory)
Anna Michalak (Carnegie Institution for Science)

Global photosynthesis results in the single largest flux of carbon dioxide between the atmosphere and the biosphere. Long-term changes in photosynthesis could therefore provide a strong feedback to climate change through changing the growth rate of atmospheric CO₂. Global photosynthesis cannot be observed, however, and must therefore be inferred through emergent dynamics in multiple proxies. But the historic sensitivity of global photosynthesis derived from such proxies spans an order of magnitude, leading to large uncertainty in estimates of both the historic and expected future changes in photosynthesis. Here, we examine the various proxies of long-term photosynthetic change, and show that they can be reconciled by combining known plant physiology with emergent dynamics of the global carbon cycle. The results suggest that global photosynthesis has increased due to elevated CO₂, but with a much lower sensitivity that that implied by some proxies, and a higher sensitivity than that inferred from remote-sensing based estimates.

Authors:
Trevor F. Keenan (Lawrence Berkeley National Laboratory)
Xiangzhong Luo (Lawrence Berkeley National Laboratory)
Martin G. De Kauwe (University of New South Wales)
Belinda Medlyn (Western Sydney University)
I. Colin Prentice (Imperial College London)
Benjamin Stocker (Imperial College London)
Cesar Terrer (Imperial College London)
Han Wang (Tsinghua University)
Yao Zhang (Lawrence Berkeley National Laboratory)
Sha Zhou (Columbia University)

Tropical forests comprise the most biologically diverse terrestrial ecosystems, cycle more carbon and water than any other biome, and play critical roles in regulating the global and regional climate systems. A better understanding of tropical forest processes is required to advance our understanding of the Earth system and to develop improved Earth System Models (ESMs). This session will focus on research in tropical forests including modeling, remote sensing and ground-based results. Processes to be highlighted include the response of tropical forest ecosystems to:

• global change pressures, such as land use change/changing demographics/increased atmospheric CO₂/altered rainfall/warming,
• extreme weather events (e.g., drought, heat waves, and extreme rainfall),
• climate variability (e.g., El Niño), and
• role of biodiversity, biogeochemistry (including soil fertility, nutrient limitation, soil respiration, and carbon sequestration), and phenology in modulating these processes.

We encourage submissions that consider tropical forest responses to global change from a wide range of perspectives.

Invited Speakers

1. Prof. Carlos A Nobre (http://www.nasonline.org/member-directory/members/20035943.html)
2. Prof. Andreas Huth (https://www.ufz.de/index.php?en=36559)

Type:
Poster

Primary Convener:
Robinson I. Negron Juarez (Lawrence Berkeley National Laboratory)

Conveners:
Yilin Fang (Battelle, Pacific Northwest National Laboratory)
Cynthia Wright (Oak Ridge National Lab)
Jessica Needham (Lawrence Berkeley National Laboratory)

Chairs:
Robinson I. Negron Juarez (Lawrence Berkeley National Lab)
Yilin Fang (Battelle, Pacific Northwest National Laboratory)
Cynthia Wright (Oak Ridge National Lab)
Jessica Needham (Lawrence Berkeley National Laboratory)

OSPA Liaison:
Jessica Needham (Lawrence Berkeley National Laboratory)

Index Terms:
3305 Climate change and variability
3337 Global climate models
0414 Biogeochemical cycles, processes, and modeling
0426 Biosphere/atmosphere interactions

Neighborhoods:
3. Earth Covering

Tropical forests are a crucial carbon sink to rising atmospheric CO₂; however, they could be experiencing a tipping point. Their ability to remove carbon from the atmosphere is decreasing due to continuous deforestation from human practices and tree mortality from frequent climatic extremes. Therefore, it is very important to study the vulnerability of tropical forests to climate change. Compared with changes in mean climates, the ecosystem resilience is more sensitive to changes in climate variability. El Niño-Southern Oscillation (ENSO) is the most important mode of climate variability on interannual to decadal time scales and exerts extensive impacts on Earth’s climate and ecosystems through prominent teleconnections. It significantly affects the intensity and occurrence of extreme events worldwide. Despite the inter-model discrepancies in the projected changes of ENSO properties itself, the frequency and intensity of strong/extreme ENSO events tend to increase in the future as well as the strength of ENSO impacts and teleconnections over continental regions. It leads to increased interannual variability (IAV) in temperature, precipitation and radiation and wildfire frequency. Thus, an ENSO event of a given strength could produce more extreme impacts and induce more stress on global ecosystems. In this study, we will investigate the vulnerability of tropical forests to the projected increases of ENSO-induced extremes and their responses to global climate by analyzing multi-model results from the CMIP6 archive. We will delineate the ENSO induced effects from the trends of mean climates by comparing the model results on the ENSO years with those on the normal years. Initial results showed that the ENSO-induced extremes have great impacts on tropical forests and the enhanced IAV induced by ENSO will increase vulnerability of tropical forests, especially for those forests in locations that do not currently experience strong IAV.

Authors:
Min Xu (Oak Ridge National Laboratory)
Salil Mahajan (Oak Ridge National Laboratory)
Forrest M. Hoffman (Oak Ridge National Laboratory)