Surface, aircraft, and satellite measurements indicate pervasive cold season CO2 emissions across Arctic regions, consistent with a hyperactive biosphere and increased metabolism in plants and soils. A key remaining question is whether cold season sources will become large enough to permanently shift the Arctic into a net carbon source. Polar orbiting GHG satellites provide robust estimation of regional carbon budgets but lack sufficient spatial coverage and repeat frequency to track sink-to-source transitions in the early cold season. Mission concepts such as the Arctic Observing Mission (AOM) advocate for flying imaging spectrometers in highly elliptical orbits (HEO) over the Arctic to address sampling limitations. We perform retrieval and flux inversion simulation experiments using the AURORA mission concept, leveraging a Panchromatic imaging Fourier Transform Spectrometer (PanFTS) in HEO. AURORA simulations demonstrate the benefits of increased CO2 sampling for detecting spatial gradients in cold season efflux and improved monitoring of rapid Arctic change.

Phytoplankton primary production is a crucial component of Arctic Ocean (AO) biogeochemistry, playing a pivotal role in the carbon cycling by supporting higher trophic levels and removing atmospheric carbon dioxide. The advent of satellite observations measuring chlorophyll a concentration (Chl_ a) has yielded unprecedented insights into the distribution of AO phytoplankton, enhancing our ability to assess oceanic productivity. However, the optical properties of AO waters differ significantly from those of lower‐latitude waters, and standard Chl_a algorithms perform poorly in the AO. In particular, Chl_a retrievals are challenged by interferences from other marine constituents including higher pigment packaging and higher proportion of light absorption by colored dissolved organic matter. To derive phytoplankton-originating signature as well as mitigate those effects, solar-induced chlorophyll fluorescence (SIF) emerges as a valuable tool for acquiring physiological insights into the direct photosynthetic processes in the AO. In this study, we leverage satellite-based SIF measurements to assess their correlation with a set of predictive factors influencing phytoplankton photosynthesis. We extend the temporal coverage of AO SIF data to cover the period 2004 - 2020. This novel dataset offers a pathway to monitor the physiological interactions of phytoplankton with changes in climate, promising to significantly improve our understanding of the Arctic water’s productivity. The application of this data is expected to provide insights into how phytoplankton respond to shifts in environmental changes, contributing to a more nuanced understanding of their role in High-Latitude Northern Oceans ecosystems.

Flash droughts– the rapid drying of land and intensification of drought conditions - have devasting impacts to natural resources, food supplies, and the economy. Less is currently known about the drivers of flash droughts and their impact to landscape carbon losses. We leverage carbon and water cycle data from NASA OCO-2 and SMAP missions to determine the net impact of flash drought events in the U.S. on the carbon sinks. On average, pre-onset carbon uptake fully offsets post-onset losses, creating a carbon neutral biosphere over a +/- 3 month period surrounding flash drought onset. This contrasts with ecosystem models, which underestimate pre-onset uptake and overestimate post-onset loss. Furthermore, spaceborne observations of solar induced fluorescence (SIF) provide a reliable indicator of flash droughts at lead times of 2-3 months, due to feedbacks between vegetation growth and soil water loss. This study is expected to improve understanding and prediction of flash droughts.

Across temperate North America, interannual variability (IAV) in gross primary production (GPP) and net ecosystem exchange (NEE), and their relationship with environmental drivers, are poorly understood. Here, we examine IAV in GPP and NEE and their relationship to environmental drivers using two state-of-the-science flux products: NEE constrained by surface and space-based atmospheric CO2 measurements over 2010–2015 and satellite up-scaled GPP from FluxSat over 2001-2017. We show that the arid western half of temperate North America provides a larger contribution to IAV in GPP (104% of east) and NEE (127% of east) than the eastern half, in spite of smaller magnitude of annual mean GPP and NEE. This occurs because anomalies in western ecosystems are temporally coherent across the growing season leading to an amplification of GPP and NEE. In contrast, IAV in GPP and NEE in eastern ecosystems are dominated by seasonal compensation effects, associated with opposite responses to temperature anomalies in spring and summer. Terrestrial biosphere models in the MsTMIP ensemble generally capture these differences between eastern and western temperate North America, although there is considerable spread between models.

Top-down estimates of CO2 fluxes are typically constrained by either surface-based or space-based CO2 observations. Both of these measurement types have spatial and temporal gaps in observational coverage that can lead to biases in inferred fluxes. Assimilating both surface-based and space-based measurements concurrently in a flux inversion framework improves observational coverage and reduces sampling biases. This study examines the consistency of flux constraints provided by these different observations and the potential to combine them by performing a series of six-year (2010–2015) CO2 flux inversions. Flux inversions are performed assimilating surface-based measurements from the in situ and flask network, measurements from the Total Carbon Column Observing Network (TCCON), and space-based measurements from the Greenhouse Gases Observing Satellite (GOSAT), or all three datasets combined. Combining the datasets results in more precise flux estimates for sub-continental regions relative to any of the datasets alone. Combining the datasets also improves the accuracy of the posterior fluxes, based on reduced root-mean-square differences between posterior-flux-simulated CO2 and aircraft-based CO2 over midlatitude regions (0.35–0.50~ppm) in comparison to GOSAT (0.39–0.57~ppm), TCCON (0.52–0.63~ppm), or in situ and flask measurements (0.45–0.53~ppm) alone. These results suggest that surface-based and GOSAT measurements give complementary constraints on CO2 fluxes in the northern extratropics and can be combined in flux inversions to improve observational coverage. This stands in contrast with many earlier attempts to combine these datasets and suggests that improvements in the NASA Atmospheric CO2 Observations from Space (ACOS) retrieval algorithm have significantly improved the consistency of space-based and surface-based flux constraints.

The boreal forest plays an important role in the global carbon cycle but has remained a significant source of uncertainty. Remote sensing can help us better understand the boreal forest’s role in the global carbon cycle. A faint light signal emitted by plant’s photosynthetic machinery, known as solar-induced chlorophyll fluorescence (SIF), is a promising remotely sensed proxy for carbon uptake, also known as gross primary productivity (GPP), due to its connection to photosynthesis and its strong relationship with GPP when observed by satellite. However, SIF and GPP are fundamentally different quantities that describe distinct, but related, physiological processes. The relationship between SIF and GPP is therefore complicated by both physical and ecophysiological controls. In particular, the dynamics of the SIF/GPP relationship are poorly understood under varying viewing directions and light conditions. This is further complicated in evergreen systems where canopy clumping and the presence of needles create a unique radiative environment. We use a combination of tower-based SIF and GPP measurements from a boreal forest field site compared with a coupled biochemical-radiative transfer model to understand illumination effects on the SIF/GPP relationship. We find that GPP is amplified under cloudy sky conditions in both measurements and model results. SIF on the other hand, shows no significant difference between sunny or cloudy sky conditions in modeled results, but does show a difference in measurements. We suggest that these differences may be due to viewing geometry effects that are important for SIF under sunny sky conditions or the presence of clumping. Accounting for the differences in the SIF/GPP relationship therefore is critical for the utility of SIF as a proxy for GPP. In summation, our results provide insight into how we can use remote sensing as a tool to understand photosynthesis in the boreal forest.

Solar-Induced Chlorophyll Fluorescence (SIF) is a powerful proxy for gross primary productivity (GPP) in Boreal ecosystems. However, SIF and GPP are fundamentally different quantities that describe distinct, but related, physiological processes. Recent work has highlighted non-linearities between SIF and GPP at finer spatial (leaf- to canopy- level) and temporal (half-hourly) scales. Therefore, questions have arisen about when, where, and why SIF is a good proxy for GPP and what the potential sources for divergence between the two are. The goal of this study is to answer two specific questions: 1) At what temporal scale is SIF a good proxy for GPP and 2) What are the predominant physical and ecophysiological drivers of nonlinearity between SIF and GPP in boreal ecosystems? We collected tower-based measurements of SIF (and other common vegetation indices) with PhotoSpec (a custom spectrometer system) and eddy-covariance GPP data at a 30-minute resolution at the Southern Old Black Spruce Site (SOBS) in Saskatchewan, CA. We applied a combination of statistical and machine learning approaches to disentangle the influence of structural/illumination effects and ecophysiological variations on the SIF signal. Our results show that at a high temporal resolution (half-hourly), SIF and GPP are predominantly dependent on photosynthetically active radiation (PAR). Therefore, the non-linear light response of GPP drives non-linearity between SIF and GPP. Additionally, canopy structure and illumination effects become important to the SIF signal at high temporal resolutions. At the seasonal timescale, SIF and GPP exhibit co-varying responses to PAR, even when accounting for changes in canopy structure. We attribute changes in the light responses of SIF and GPP to sustained photoprotection over winter which co-varies with changes in temperature. Finally, we show that the relationship between SIF and GPP has a seasonal dependence caused by small differences between the light use efficiencies of fluorescence and photosynthesis. Accounting for this seasonally variable relationship will improve the use of SIF as a proxy for GPP.

Solar-Induced chlorophyll Fluorescence (SIF) provides a powerful proxy for determining forest gross primary production (GPP), particularly in evergreen ecosystems where traditional measures of greenness fail. The dynamics of the SIF/GPP relationship, however, are poorly understood under varying viewing directions and light conditions. This is, in large part, due to challenges in measuring SIF at the spatiotemporal scale that is necessary to understand these effects. Therefore, the aim of this work is to utilize high-temporal and spatial resolution SIF measurements to better constrain the response of SIF to ambient canopy illumination and viewing geometry. We use a PhotoSpec instrument and eddy covariance measurements to explore the SIF/GPP relationship under various viewing directions and light conditions during the 2019 and 2020 growing seasons at the Old Black Spruce site in Saskatchewan, Canada. PhotoSpec is a tower-based 2-D scanning spectrometer system capable of taking Fraunhofer-line based SIF retrievals in the red and far-red wavelength ranges with a 0.7 degree field of view at a ~30 second time resolution. Measured SIF and GPP are combined with SCOPE modelling results to provide a mechanistic understanding of the physical and ecophysiological drivers for the SIF/GPP relationship in the Boreal Forest. Our results show that viewing direction and solar zenith/azimuth angles are important for the SIF signal under direct light conditions, but not under diffuse. Furthermore, the SIF/GPP relationship changes under direct and diffuse light conditions at a 30 minute, daily, and monthly resolution. Our ability to use SIF as a proxy for GPP depends on a quantitative understanding of radiative transfer within the canopy and how scanning geometry impacts SIF measurements. These results provide an important insight into these relationships in the Boreal forest, a region where GPP has been traditionally difficult to track using remote sensing.

The ACT-America Earth Venture mission conducted five airborne campaigns across four seasons from 2016-2019, to study the transport and fluxes of Greenhouse gases across the eastern United States (US). Unprecedented spatial sampling of atmospheric tracers (CO2, CO, and COS) related to biospheric processes offers opportunities to improve our qualitative and quantitative understanding of seasonal and spatial patterns of biospheric carbon uptake. Here, we examine co-variation of boundary layer enhancements of CO2, CO, and COS across three diverse regions: the crop-dominated Midwest, evergreen-dominated South, and deciduous broadleaf-dominated Northeast. To understand the biogeochemical processes controlling these tracers, we compare the observed co-variation to simulated co-variation resulting from model- and satellite- constrained surface carbon fluxes. We found indication of a common terrestrial biogenic sink of CO2 and COS and secondary production of CO from biogenic sources in summer throughout the eastern US. Stomatal conductance likely drives fluxes through diffusion of CO2 and COS into leaves and emission of biogenic volatile organic compounds into the atmosphere. ACT-America airborne campaigns filled a critical sampling gap in the southern US, providing information about seasonal carbon uptake in southern temperate forests, and demanding a deeper investigation of underlying biological processes and climate sensitivities. Satellite- constrained carbon fluxes capture much of the observed seasonal and spatial variability, but underestimate the magnitude of net CO2 and COS depletion in the Southeast, indicating a stronger than expected net sink in late summer.

Since the 1960s, carbon cycling in the high-latitude northern forest (HLNF) has experienced dramatic changes: most of the forest is greening and net carbon uptake from the atmosphere has increased. During the same time period, the COseasonal cycle amplitude (SCA) has almost doubled. Disentangling complex processes that drive these changes has been challenging. In this study, we substitute spatial sensitivity to temperature for time to quantify the impact of temperature increase on Gross Primary Production (GPP), total ecosystem respiration (TER), the fraction of Photosynthetic Active Radiation (fPAR), and the resulted contribution of these changes in amplifying the COSCA over the HLNF since 1960s. We use the spatial heterogeneity of GPP inferred from solar-induced chlorophyll Fluorescence in combination with net ecosystem exchange (NEE) inferred from column COobservations made between 2015 and 2017 from NASA’s Orbiting Carbon Observatory -2. We find that three quarters of the spatial variations in GPP and in the fPAR absorbed by the HLNF can be explained by the spatial variation in the growing season mean temperature (GSMT). The long term hindcast captures both the magnitude and spatial variability of the trends in observed fPAR. We estimate that between 1960 and 2010, the increase in GSMT enhanced both GPP and the SCA of NEE by ~20%. The calculated enhancement of NEE due to increase in GSMT contributes 56–72% of the trend in the CO SCA at high latitudes, much larger than simulations by most biogeochemical models.