B. Poulter | USGS Science

USGS2025

A U.S. scientific community vision for sustained earth observations of greenhouse gases to support local to global action

Managing carbon stocks in the land, ocean, and atmosphere under changing climate requires a globally-integrated view of carbon cycle processes at local and regional scales. The growing Earth Observation (EO) record is the backbone of this multi-scale system, providing local information with discrete coverage from surface measurements and regional information at global scale from satellites. Carbon flux information, anchored by inverse estimates from spaceborne Greenhouse Gas (GHG) concentrations, provides an important top-down view of carbon emissions and sinks, but currently lacks global continuity at assessment and management scales (< 100 km). Partial-column data can help separate signals in the boundary layer from the overlying atmosphere, providing an opportunity to enhance surface sensitivity and bring flux resolution down from that of column-integrated data (100–500 km). Based on a workshop held in September 2024, the carbon cycle community envisions a carbon observation system leveraging GHG partial columns in the lower and upper troposphere to weave together information across scales from surface and satellite EO data, and integration of top- down/bottom-up analyses to link process understanding to global assessment.

AGU Advances↗

USGS2013

Simulating boreal forest carbon dynamics after stand-replacing fire disturbance: insights from a global process-based vegetation model

Stand-replacing fires are the dominant fire type in North American boreal forests. They leave a historical legacy of a mosaic landscape of different aged forest cohorts. This forest age dynamics must be included in vegetation models to accurately quantify the role of fire in the historical and current regional forest carbon balance. The present study adapted the global process-based vegetation model ORCHIDEE to simulate the CO 2 emissions from boreal forest fire and the subsequent recovery after a stand-replacing fire; the model represents postfire new cohort establishment, forest stand structure and the self-thinning process. Simulation results are evaluated against observations of three clusters of postfire forest chronosequences in Canada and Alaska. The variables evaluated include: fire carbon emissions, CO 2 fluxes (gross primary production, total ecosystem respiration and net ecosystem exchange), leaf area index, and biometric measurements (aboveground biomass carbon, forest floor carbon, woody debris carbon, stand individual density, stand basal area, and mean diameter at breast height). When forced by local climate and the atmospheric CO 2 history at each chronosequence site, the model simulations generally match the observed CO 2 fluxes and carbon stock data well, with model-measurement mean square root of deviation comparable with the measurement accuracy (for CO 2 flux ~100 g C m −2 yr −1 , for biomass carbon ~1000 g C m −2 and for soil carbon ~2000 g C m −2 ). We find that the current postfire forest carbon sink at the evaluation sites, as observed by chronosequence methods, is mainly due to a combination of historical CO 2 increase and forest succession. Climate change and variability during this period offsets some of these expected carbon gains. The negative impacts of climate were a likely consequence of increasing water stress caused by significant temperature increases that were not matched by concurrent increases in precipitation. Our simulation results demonstrate that a global vegetation model such as ORCHIDEE is able to capture the essential ecosystem processes in fire-disturbed boreal forests and produces satisfactory results in terms of both carbon fluxes and carbon-stock evolution after fire. This makes the model suitable for regional simulations in boreal regions where fire regimes play a key role in the ecosystem carbon balance.

Biogeosciences↗