GEOG Researchers Selected to Lead Multiple NASA Carbon Monitoring System Projects

Multiple GEOG researchers were selected to lead and continue multiple projects through NASA ROSES 2020 A.6 Carbon Monitoring System. Principle investigators include Professor and Research Director George Hurtt, Science Team Leader of NASA Carbon Monitoring System, Associate Research Professor John Armston, Associate Research Professor Varaprasad Bandaru, Reem A. Hannun, NASA/UMBC Assistant Research Scientist, Lesley E. Ott, NASA Research Meteorologist and Benjamin Poulter, NASA Research Scientist, both Adjunct Professors in GEOG. In addition to these PIs, multiple members of the department are involved including: Research Professor Molly Brown, Research Assistant Professor Louise Chini, Professor Ralph Dubayah, Professor Matthew Hansen, Research Professor R. César Izaurralde, Assistant Research Professor Curtis Jones, Assistant Research Professor Hao Tang, Incoming Postdoc Lei Ma, Graduate Research Assistant Quan Shen, and Postdoc Zhen Zhang. 

These projects leverage several years of collaboration between GEOG and NASA GSFC on carbon-cycle science and applications as driven by stakeholder needs.

George Hurtt notes,  “With these new projects, GEOG is poised to help lead and continue to the next generation of scientific capabilities needed to support stakeholder needs for data on carbon.” He adds on, “The breadth, and depth, of contributions to this topic in the department and with our partners is incredible, and is inspiring for the future.”

Additional selected PIs had the following comments.

Varaprasad Bandaru comments on his project saying, “Given the recent developments and the attention in the agricultural carbon markets to promote climate friendly agriculture and the need for a reliable monitoring system, our CMS project is timely, and is expected to provide high resolution baseline cropland carbon estimates for the U.S and Canada with required accuracy for operational use, and would support a large stakeholder community.”

 “Support from CMS has been incredibly important in building our modeling and observational tools. Over the past 10 years, we’ve seen these products grow from ideas into mature datasets with the quality needed to support decision-making at a range of scales,” expressed Lesley Ott on the support CMS has given. 

Benjamin Poulter comments on his selected project saying, “Blue’ carbon stored by coastal ecosystems plays an increasingly important role in climate adaptation and mitigation. Our CMS project, BLUEFLUX, provides us with an exciting opportunity to combine field and aircraft measurements of carbon dioxide and methane fluxes with satellite remote sensing to develop blue-carbon products for a variety of stakeholders engaged with coastal restoration and management.” 

Similarly, Reem Hannun says, “Our work with CMS will allow us to synthesize some unique and exciting datasets and models to better support Maryland’s state greenhouse gas budget and associated forest management efforts. Although I’m new to the CMS community, I look forward to our collaboration with GEOG given their long-standing expertise in the field of carbon monitoring and stakeholder partnership.” 

Abstracts for all projects can be found below. GEOG participants are marked in bold font. For more information on these projects and the NASA Carbon Monitoring System, please visit the NASA CMS Website. 

High-Resolution Forest Carbon Monitoring and Modeling: Continued Prototype Development and Deployment to National and Global Scales and Science Team Lead

PI: George Hurtt

Participants: Louise Chini, Ralph Dubayah, Matthew Hansen, Nancy Harris, Nathan Hultman, Andrew Lister, Lei Ma, Jarlath O’Neil-Dunne, Alexander Rudee, Quan Shen, Hao Tang, Elliott Campbell, Abhishek Chatterjee, Susan Cook-Patton, Chris David, Grant Domke, Erik Fisher, Valeria Morales, Ramakrishna Nemani, Lesley Ott, Benjamin Poulter, Edil Sepulveda Carlo, and Debjani Singh

NASA has recognized the urgent need for CMS/MRV research through its initiation of the Carbon Monitoring System (CMS) program. The University of Maryland, working with NASA centers, the USFS, and commercial entities has led research efforts in Phase I and Phase II that have laid the basic groundwork of our approach to MRV. Beginning with two counties in MD, projects have used wall-to-wall airborne lidar coverage, high resolution optical imagery, and in-situ field data collection to produce high-resolution bottom-up maps of carbon stocks for Sonoma County, CA, the entire state of MD, and the 11 state RGGI+ region (MD, DE, PA, MA, CT, RI, NH, VT, NJ, NY, ME). These same data have also been used to drive a prognostic ecosystem model to predict carbon fluxes for connecting to atmospheric assessments, and to provide estimates of future carbon sequestration potential needed for climate mitigation planning. Our work has demonstrated the value of this approach for both science and stakeholders and suggests logical follow-on activities that should be undertaken towards the realization of operational MRV systems that are responsive to local, national and international interests. The overall goal of this project is the continued development, and geographic expansion, of our approach to high-resolution forest carbon monitoring and modeling. In particular, we seek to continue development and deployment of our approach to the national, and global scales, harnessing newly available orbital remote sensing from NASA (GEDI, ICESat-2, Landsat). In the process, we will both deepen and expand our stakeholder engagement including key governmental and non-governmental organizations. We believe this build-out is the logical next step, and critical toward the development of a national CMS that includes high-resolution forest carbon monitoring.

Savanna-Bio: Biomass estimation with new spaceborne missions for MRV in Dry Forests and Savannas

PI: John Armston

Participants: Laura Duncanson, Paul Siqueira, Konrad Wessels, Rajashekar Gopalakrishnan, Sean Healey, Laven Naidoo, Stuart Phinn, and Peter Scarth 

This proposal addresses the key objective of NASA's CMS to develop accurate and precise Monitoring Reporting and Verification (MRV) systems required by stakeholders, by reducing the uncertainty in biomass estimates and derived change products. While tropical Dry Forests and Shrublands (or "Savannas") have lower biomass densities (below 60 Mg/ha) than Tropical Rainforests and Moist Forests, they are expansive, covering more than 20% of the earth and representing the third highest total carbon stock by ecosystem. A very large portion of the world's population, most of which live in less economically developed countries, are directly dependent on local savanna ecosystem services (e.g. fuelwood and grazing). Despite the obvious global importance of savannas, remote sensing efforts have been skewed towards moist tropical forested environments. Due the structural heterogeneity of savannas and the very sparse field data available for the parameterization of current lidar and SAR-based models, the error of biomass estimation in these ecosystems is very high (relative RMSE 50-100%), precluding the accurate monitoring for MRV of biomass changes due forest degradation, regrowth, debushing, bush encroachment and mitigating activities, e.g. restoration and afforestation. The overall goal of this research is to use the billions of measurements made by the new spaceborne lidar data from NASA's GEDI (launched December, 2018) and ICESat-2 (launched September, 2018) to improve the accuracy of SAR-based models, with a view to the upcoming NASA/ISRO NISAR mission. To achieve this goal our research objectives are to: (i) develop GEDI and ICESat-2 biomass models representative of savanna ecosystems; (ii) produce prototype multi-date aboveground biomass maps for international pilot sites (India, South Africa and Australia) using coincident GEDI, ICESat-2, and spaceborne SAR data (ALOS PALSAR2, Sentinel1); (iii) use independent airborne lidar and field data to validate the products and evaluate the uncertainty of prototype aboveground biomass estimates from 1 ha to 1 km2 scales; and (iv) work with existing in-country partners to prototype products for biomass gains and losses that do not constitute land cover changes but are desired inputs to national carbon accounting systems, international reporting obligations, emissions trading and mitigating activities. By focusing on quantifying change at the lower end of the biomass range where SAR is most sensitive (20-80 Mg/ha), we will improve the accuracy of lower magnitude biomass change estimation, such as regrowth and degradation, not only in savannas, but for other biomes as well. The project will leverage the international experience of the PI and Co-PI's in savannas and their existing networks of collaborators/users, as well as existing airborne lidar and biomass field data. By developing prototype products for new pilot areas in India, South Africa and Australia, the project will expand the capability, impact and societal relevance of the CMS program towards its global aspirations.

Improving, Evaluating and Extending Satellite-Based High Resolution Cropland Carbon Monitoring System 

PI: Varaprasad Bandaru

Participants: Molly Brown, Craig Daughtry, George Hurtt, Curtis Jones, Benjamin Runkle, Rajat Bindlish, Michael Cosh, Elliott Campbell, Roberto Izaurralde, Tyson Ochsner and Debjani Singh. 

Croplands have the potential to stabilize atmospheric CO2 and mitigate climate change but also contribute to global warming through greenhouse gas emissions. A recent State of the Carbon (C) Cycle Report (SOCCR2) highlighted the significance of accounting spatial  variability of impacts of land use and land management practices in agriculture to improve the estimates of net carbon balance on croplands. Considering the need for a comprehensive CO2 monitoring system of agricultural lands to support C management policies and programs, with support from the NASA Carbon Monitoring System (CMS) program, a prototype of a high-resolution cropland carbon monitoring system (CCMS v.1.0) was developed. This system integrates satellite remote sensing-based crop inputs (i.e. crop phenological metrics and crop type maps) and intermediate state variables (e.g. crop type leaf area index) with the Environmental Policy Integrated Climate (EPIC) agroecosystem model to generate estimates of net C balances at 500 m resolution. 

The implementation of the CCMS framework over U.S corn, soybean and winter wheat systems grown in 2012 (drought year) and 2015 (normal year) provided insights on agroecosystem C dynamics that vary with changes in management, crop type, and weather conditions. Further, it revealed a few sources of uncertainty in the CCMS estimates and indicated the importance of understanding and quantifying long-term trends. To address some identified uncertainties in the current framework, and to provide improved and extended products, we propose to continue our CMS work with four major objectives. In the first objective, we will enhance the CCMS v1.0 through assimilating SMAP based Thermal Hydraulic disaggregation of Soil Moisture (THySM) high-resolution soil moisture (1km) product using a robust ensemble propagation approach, and by integrating Landsat and Sentinel based spatially resolved 30 m tillage maps. To ensure the quality of the CCMS products to use in the state and regional carbon and climate related programs, in the second objective, we will conduct an evaluation study in five pilot regions (located in Maryland, Arkansas, Oklahoma, Iowa, and Manitoba) representing major cropping systems in the U.S and Canada. We will collect extensive in-situ data to adjust crop parameters to reflect crop specific dynamics and local conditions, and to understand the performance of improved CCMS framework (CCMS v2.0) to estimate C and N2O fluxes at local scale. In the third objective, we will deploy the CCMS v2.0 framework over U.S and Canada croplands to estimate seasonal and annual C fluxes and N2O emissions at 500m spatial resolution under major cropping systems (i.e. corn, soybean, winter wheat, spring wheat, rice, cotton and canola) for a five year-period (2017-2021). Further, we will quantify the uncertainty in the CCMS products using observed data from USDA long-term agroecosystem research (USDA-LTAR), USDA-GRACEnet, Agriculture and Agri-Food Canada flux sites, and AmeriFlux sites, as well as reported country yield statistics. In order to improve usability and obtain feedback on our CMS products, in our fourth objective we will work closely with USDA regional climate hubs, the Maryland state government, the Arkansas NRCS, and Agriculture and Agri-food Canada, and will integrate CCMS products in their conservation and climate change mitigation programs. 

The proposed project directly contributes to the NASA CMS solicited research topic on “Studies that build upon, extend, evaluate and/or improve the existing CMS products for biomass and flux”. Ultimately, the proposed work will advance C and N2O monitoring capability on croplands and the products developed under this project are expected to contribute to the national and international programs targeting greenhouse gas reduction and climate friendly agriculture. Further, the data products will help in developing carbon markets, and improve national inventories and C budget reporting.

Linking Forest Biomass and Carbon Exchange Using LiDAR-Derived Forest Structure and Airborne Flux Observations

PI: Reem Hannun

Participants: Thomas Hanisco, George Hurtt, Elliott Campbell, Stephen Kawa, and Glenn Wolf

A robust carbon monitoring system (CMS) requires a comprehensive understanding of terrestrial carbon stocks and the underlying processes that connect vegetation metabolism to biomass change and integrated carbon flux. Terrestrial biosphere models that predict carbon storage and exchange typically have large uncertainties. In addition, discrepancies persist between biosphere- and atmosphere-based methods to quantify the terrestrial carbon budget.

We propose to quantify the relationship between forested biomass and net ecosystem exchange (NEE) using previously acquired remote sensing maps of forested structure and direct flux observations and to use these results to evaluate the Ecosystem Demography (ED) biophysical process model. Our research plan entails two main objectives, focused on closing the gap between biosphere and atmosphere-based approaches for quantifying carbon exchange:

1. We will employ a novel combination of datasets to constrain the relationship between biomass and NEE over forested sites in Maryland. This work will combine high-resolution LiDAR-derived forest structure measurements (Dubayah, CMS 2011) with in-situ fluxes of CO2, CH4, sensible heat, and latent heat acquired from the Carbon Airborne Flux Experiment (CARAFE) (Kawa, CMS 2015) to explore questions at the flux-biomass interface: How does NEE vary with forest biomass and canopy height? How do meteorological parameters such as evapotranspiration, photosynthetically active radiation, and temperature influence the observed relationship?
2. We will use observation-based constraints to evaluate the Ecosystem Demography (ED) biophysical process model, a current CMS prototype (Hurtt, CMS 2016) that projects forest carbon sequestration potential. The ED model is initialized with LiDAR canopy height measurements, and we will extract model-estimated NEE and other relevant output to assess the degree to which the model does, or does not, capture observed relationships. This will enable us to refine underlying model processes that link forest biomass and carbon flux, better quantify the uncertainties in the ED carbon storage projections, and identify future measurement priorities.

This work directly targets several CMS goals by synergizing previous CMS activities, including remote sensing maps of forest biomass, model projections of forest carbon storage, and airborne flux measurements. This work will further refine remote-sensing methods for carbon stocks and fluxes by providing an independent evaluation to reduce uncertainty in the current ED data products. We will engage stakeholders from the Maryland Department of Environment and Department of Natural Resources to identify uncertainties and target validation efforts to benefit the state’s Regional Greenhouse Gas Initiative. With the advent of global forest structure measurements from satellites such as GEDI, direct validation of ED will establish reliability in biomass approaches to carbon flux as model-assisted prototypes scale up to global applications.

GEOS-Carb IV: Delivering low-latency carbon flux and concentration datasets in support of NASA’s Carbon Monitoring System

PI: Lesley E. Ott

Participants: Lionel Arteaga, Nikolay Balashov, Joanna Joiner, Tomohiro Oda, Benjamin Poulter, Cecile Rousseaux, Brad Weir, Abhishek Chatterjee, George Collatz, George Hurtt, and Eleanor Stokes

Since its 2010 inception, GSFC-based modeling teams have continuously provided complete and physically consistent set of global flux and atmospheric concentration data products to CMS. The proposed work will draw on the unique capabilities of NASA’s Goddard Earth Observing System (GEOS) models and data assimilation system and consists of two main components: (i) production and refinement of observationally constrained ‘bottom-up’ atmosphere-ocean and atmosphere-land biosphere fluxes, and fossil fuel emissions; and (ii) production of global carbon analyses that incorporate multiple satellite and in situ datasets. A central theme has been the use of meteorological forcing provided by NASA’s Modern Era Retrospective-analysis for Research and Applications, Version 2 (MERRA-2) to produce a consistent picture of the interactions between weather, climate, and carbon.

The activities proposed here have two overarching goals: 1) to reduce the latency of flux and concentration datasets and 2) to implement refinements in retrospective products that incorporate additional observations and improve quantification of uncertainties. COVID-19 provided a powerful example of the growing demand for low latency information about the carbon cycle. The GEOS-Carb system contributed to international and national efforts to track human emission reductions from space using components developed during earlier phases of the project: gap-filled analyses of carbon concentrations, an observationally-informed flux package, and a novel anomaly detection technique. Products were delivered to dashboards coordinated by NASA and international space agencies with ~2 month latency, providing the first quantification of recent changes in carbon dioxide concentrations. Despite this success, efforts to separate human emissions changes from natural variability were limited by the lack of year-specific information about land fluxes. We propose to address this limitation by making modifications to GEOS-Carb land fluxes that incorporate reflectance information available in near real time and integrate GMAO’s existing fire radiative power based fire emissions, which reduce latency over burned area approaches. This will feed into low latency carbon dioxide analyses, supporting preliminary attribution of atmospheric anomalies in support of carbon monitoring. 

We also plan to extend and improve flux estimates to cover the 20-year period from 2003-2022. GEOS-Carb land flux estimates have been provided by a model that assumes an approximate balance between respiration and primary production. We plan to incorporate lessons learned from recently released estimates of gross primary production based on surface reflectances to improve the ability to simulate interannual and daily variability. Ocean flux estimates will be further constrained through incorporation of new data on the exports of carbon from surface to deep ocean and will incorporate updated uncertainty estimates. We plan to continue to provide updates to our nighttime lights based fossil fuel emissions inventory. In addition to improvements in bottom-up flux estimates, will also exploit the unique ability of GEOS to run with multiple subgrid physical parameterizations to refine transport uncertainty estimates. Ocean and land fluxes and fossil fuel emissions will be used together in the GEOS constituent data assimilation system (CoDAS) to provide the most complete, data-driven picture of atmospheric greenhouse gases over the past 20 years. GEOS-Carb products and system development will continue to support a wide range of stakeholders, including NASA science teams; state and federal government agencies; and international efforts aimed at constraining carbon budgets.

Blue Carbon Prototype Products for Mangrove Methane and Carbon Dioxide Fluxes (BLUEFLUX)

PI: Benjamin Poulter

Participants: Zhen Zhang 

Mangrove forests provide a range of ecosystem services that include habitat for biodiversity, food and fiber for local communities, and structural protection from shoreline erosion and flooding. However, a variety of drivers that include coastal development and aquaculture, sea level rise, and an increase in hurricanes are leading to rapid losses of mangroves around the world. In response, government and non-governmental organizations are actively working to restore and protect the world’s remaining mangroves using science to understand demography and growth, and then applying these findings to inform conservation management and planning.

Recent scientific advances, partly supported by NASA’s Carbon Monitoring System (CMS), have led to novel datasets that describe historical distributions and changes in mangrove area, mangrove canopy height, aboveground biomass and carbon stocks. Carbon has emerged as the ‘currency’ for mangrove ecosystem restoration, as seen by the role of ‘blue carbon’ (including mangroves, as well as tidal marshes, kelp forests, and coral reefs) in the United Nations Sustainable Development Goals (SDG 14). Mangroves are one of the most carbon rich ecosystems in the world and have tremendous potential to sequester carbon from the atmosphere, thereby partly offsetting industrial emissions while at the same time providing a conservation funding mechanism. To enable these efforts, we need to 1) better understand blue carbon fluxes, in addition to stocks, 2) quantify how carbon dioxide (CO2) and methane (CH4) are exchanged between mangrove ecosystems the atmosphere and the ocean, and 3) determine how these fluxes are affected by disturbance history, and 4) what the net radiative effect of the two gases are in the context of climate mitigation.

Our proposed project, BLUEFLUX, will quantify blue carbon fluxes by developing a prototype, daily-gridded (500 m) CO2 and CH4 flux product for the Caribbean region for the time period 2000-present day. We address CMS 2020 relevance through “the accounting of blue carbon ecosystems (quantification and change - e.g. regional/global extent and temporal distribution)”. A data-driven upscaling methodology, using machine learning, will be applied to existing NASA remote-sensing products based on a synthesis of existing ground observations and the acquisition of new airborne eddy covariance measurements over southern Florida. Over ten-site years of mangrove eddy covariance and chamber data will be standardized to contribute to an environmental response function analysis. These measurements will be combined with six aircraft deployments, carried out over southern Florida to quantify CO2 and CH4 fluxes for a gradient of mangrove types, disturbance histories, tidal stage, and season, to fill gaps in the ground-observing network.

Our team includes experts in trace-gas field measurements and data synthesis from Yale University, the NASA Goddard Space Flight Center (GSFC) CARbon Airborne Flux Experiment group (CARAFE), and remote sensing and modeling experts from East Carolina University and NASA GSFC. Over the past decade, the team has established relationships with a diverse group of stakeholders in Florida and throughout the Caribbean, for example with the Everglades National Park, ELTI (Empowering People to Restore and Conserve Tropical Forests), the Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV), and the Center for International Forestry (CIFOR). The upscaled carbon flux product will be used to provide information to i) complete the greenhouse gas budgets of mangrove ecosystems in the region and at project scale, ii) inform stakeholders on how these fluxes have changed over time, and iii) quantify the net radiative forcing of mangrove ecosystems across a matrix of disturbance histories from hurricanes to better inform climate mitigation activities.