Exploring New Multi-Instrument Approaches To Observing Terrestrial Ecosystems And The Carbon Cycle From Space

Abstract:

In October 2015, we held a five-day workshop at the Keck Institute for Space Studies, bringing together experts on terrestrial ecology and the carbon cycle, remote sensing, in-situ networks, modeling, and systems engineering. The goals of the workshop were to:

1) Identify grand challenges in terrestrial ecology and carbon cycle science and outline how new multi-instrument remote sensing products can enable revolutionary advancements towards unlocking those challenges

2) Collaborate on using existing airborne, space-based, and ground-based measurements to highlight and quantify those potential advancements

3) Explore how multi-instrument data products can reduce key parameter and structural uncertainties in terrestrial biosphere models

The more general themes of the workshop were framed around the potential, that in a few years time, we could see co-flight of suite of sensors aboard the International Space Station providing simultaneous observations of ecosystem structure, functioning, and composition. These include two instruments recently selected by the NASA Earth Venture Instrument program, GEDI, a LiDAR which will measure the 3D structure and biomass of forests, and ECOSTRESS, a thermal radiometer, which will estimate evapotranspiration and plant water stress. These also include two proposed instruments, OCO-3, capable of targeted mapping of solar-induced fluorescence and column CO2, and an imaging spectrometer, which would provide near-global maps of plant biodiversity and plant canopy biochemistry. The workshop sought to break down the ‘stovepiping’, that can arise from the traditionally contingency-adverse systems engineering approach to mission planning, by developing a broader strategy that would combine data products from multiple sensors to address carbon cycle grand challenge questions that no single sensor can address alone. We will present highlights from the workshop, as well as results from the discussion of observation needs, potential data products, and plans for future work.