Interpreting seasonal changes in the carbon balance of southern Amazonia using measurements of XCO<sub>2</sub> and chlorophyll fluorescence from GOSAT

Parazoo, Nicholas C.; Bowman, K. W.; Frankenberg, Christian; Lee, Jung-Eun; Fisher, Joshua B.; Worden, J.; Jones, Dylan B. A.; Berry, Joseph A.; Collatz, G. J.; Baker, Ian; Jung, Martin; Liu, Junjie; Osterman, G. B.; O’Dell, Chris; Sparks, Athena; Butz, A.; Guerlet, Sandrine; Yoshida, Yukio; Chen, Huilin; Gerbig, Christoph

doi:10.1002/grl.50452

Cited by 97 publications

(94 citation statements)

References 44 publications

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“…We simulate atmospheric CO 2 using the Goddard Earth Observing System Chemistry global tracer model (GEOS-Chem) (14) forced by assimilated meteorological fields and surface CO 2 flux from land, ocean, and fossil fuel sources. Monthly CO 2 output is sampled during midday (10-18 LST), averaged across all Alaskan land grid points (55°N to 72°N, 170°W to 140°W), and binned vertically into the ML and FT. We run CO 2 experiments based on two configurations of the Community Land Model, version 4.5 (CLM4.5) (15)(16)(17).…”

Section: Methodsmentioning

confidence: 99%

Detecting regional patterns of changing CO ₂ flux in Alaska

Parazoo

Commane

Wofsy

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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With rapid changes in climate and the seasonal amplitude of carbon dioxide (CO 2 ) in the Arctic, it is critical that we detect and quantify the underlying processes controlling the changing amplitude of CO 2 to better predict carbon cycle feedbacks in the Arctic climate system. We use satellite and airborne observations of atmospheric CO 2 with climatically forced CO 2 flux simulations to assess the detectability of Alaskan carbon cycle signals as future warming evolves. We find that current satellite remote sensing technologies can detect changing uptake accurately during the growing season but lack sufficient cold season coverage and near-surface sensitivity to constrain annual carbon balance changes at regional scale. Airborne strategies that target regular vertical profile measurements within continental interiors are more sensitive to regional flux deeper into the cold season but currently lack sufficient spatial coverage throughout the entire cold season. Thus, the current CO 2 observing network is unlikely to detect potentially large CO 2 sources associated with deep permafrost thaw and cold season respiration expected over the next 50 y. Although continuity of current observations is vital, strategies and technologies focused on cold season measurements (active remote sensing, aircraft, and tall towers) and systematic sampling of vertical profiles across continental interiors over the full annual cycle are required to detect the onset of carbon release from thawing permafrost.carbon cycle | permafrost thaw | climate | Earth system models | remote sensing T he future trajectory of carbon balance in the Arctic-Boreal Zone (ABZ) is of global importance because of the vast quantities of carbon sequestered in permafrost soils (1). Climate warming threatens to increase permafrost thaw and release soil carbon back to the atmosphere as a positive feedback promoting additional warming (2). It is unclear whether the observed intensification of the northern high-latitude carbon cycle is dominated by plant productivity or microbial decomposition, both of which seem to be increasing (3-6). Although warming temperatures and C/N fertilization promote greening and higher summer productivity during the short, intense growing season, these same factors also drive increased emissions during the long cold season (3-5).Detecting changes in ABZ carbon balance requires sustained observations over the full annual cycle. In the last decade, researchers have recognized the importance of year-round landatmosphere CO 2 flux observations (3-5). Synthesis studies of these data show that increasing growing season uptake has been offset by stronger winter respiration. Measurements of atmospheric CO 2 collected from in situ and remote sensing instruments provide spatially and temporally integrated constraints of net CO 2 exchange on regional to pan-Arctic scales. In situ observations have been limited primarily to a small network of surface towers and infrequent, short duration airborne campaigns designed primarily to detect the pan-Ar...

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Section: Methodsmentioning

confidence: 99%

Detecting regional patterns of changing CO ₂ flux in Alaska

Parazoo

Commane

Wofsy

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…The first global maps of SIF were derived using data from the Greenhouse Gases Observing Satellite (GOSAT) (20)(21)(22)(23). Despite the complicated photosynthesis-SIF relationships and the convolution of the signal with canopy structure (16), SIF retrievals showed high correlations with data-driven GPP estimates at global and annual scales (21,22), as well as intriguing patterns of seasonal drought response in Amazonia (24,25). Recently, a global SIF data set with better spatial and temporal sampling than that from GOSAT was produced using spectra from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument onboard the MetOp-A platform (26) (see SI Appendix, SIF Retrievals).…”

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confidence: 99%

Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence

Guanter

Zhang

Jung

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

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Photosynthesis is the process by which plants harvest sunlight to produce sugars from carbon dioxide and water. It is the primary source of energy for all life on Earth; hence it is important to understand how this process responds to climate change and human impact. However, model-based estimates of gross primary production (GPP, output from photosynthesis) are highly uncertain, in particular over heavily managed agricultural areas. Recent advances in spectroscopy enable the space-based monitoring of sun-induced chlorophyll fluorescence (SIF) from terrestrial plants.Here we demonstrate that spaceborne SIF retrievals provide a direct measure of the GPP of cropland and grassland ecosystems. Such a strong link with crop photosynthesis is not evident for traditional remotely sensed vegetation indices, nor for more complex carbon cycle models. We use SIF observations to provide a global perspective on agricultural productivity. Our SIF-based crop GPP estimates are 50-75% higher than results from state-ofthe-art carbon cycle models over, for example, the US Corn Belt and the Indo-Gangetic Plain, implying that current models severely underestimate the role of management. Our results indicate that SIF data can help us improve our global models for more accurate projections of agricultural productivity and climate impact on crop yields. Extension of our approach to other ecosystems, along with increased observational capabilities for SIF in the near future, holds the prospect of reducing uncertainties in the modeling of the current and future carbon cycle.crop productivity | carbon fluxes | Earth observation | carbon modeling | spaceborne spectroscopy T he rapidly growing demand for food and biofuels constitutes one of the greatest challenges for humanity in coming decades (1). It is estimated that we must double world food production by 2050 to meet increasing demand (2), but the once rapid growth seen in the "green revolution" has stalled, and even past advances are threatened by climate change (3-5). Much of past yield improvement has focused on increases in the harvest index and resistance to pests. However, all else being equal, the quantity of photosynthesis places an upper limit on the supply of food and fuels from our agricultural systems.Ironically, we currently have very limited ability to assess photosynthesis of the breadbaskets of the world. Agricultural production inventories provide important information about crop productivity and yields (6-8), but these are difficult to compare between regions and lag actual production. Carbon cycle models, based on either process-oriented biogeochemistry or semiempirical data-driven approaches, have been used to understand the controls and variations of global gross primary production (GPP, equivalent to ecosystem gross photosynthesis) (9) and to investigate the climate impact on crop yields (10). However, uncertainty associated with inaccurate input data and much simplified process descriptions based on the plant functional type concept severely challenge the applicat...

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“…GOSAT observations provide new insight into fluxes in regions that are poorly sampled by in situ observations, regions like tropical Asia (Basu et al, 2014) and the southern Amazon (Parazoo et al, 2013). These studies also identify a number of common challenges.…”

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confidence: 96%

“…A number of studies use GOSAT observations to estimate surface fluxes, and these studies report numerous successes and challenges that could apply to OCO-2 (e.g., Takagi et al, 2011;Basu et al, 2013;Guerlet et al, 2013;Maksyutov et al, 2013;Parazoo et al, 2013;Saeki et al, 2013;Basu et al, 2014;Deng et al, 2014;Houweling et al, 2015). GOSAT observations provide new insight into fluxes in regions that are poorly sampled by in situ observations, regions like tropical Asia (Basu et al, 2014) and the southern Amazon (Parazoo et al, 2013).…”

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Characterizing biospheric carbon balance using CO<sub>2</sub> observations from the OCO-2 satellite

Miller¹,

Michalak²,

Yadav³

et al. 2017

Preprint

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Abstract.NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite launched in summer of 2014. Its observations could allow scientists to constrain CO 2 fluxes across regions or continents that were previously difficult to monitor. This study explores an initial step toward that goal; we evaluate the extent to which current OCO-2 observations can detect patterns in biospheric CO 2 fluxes and constrain monthly CO 2 budgets. Our goal is to guide top-down, inverse modeling studies and identify areas 5 for future improvement. We find that uncertainties and biases in the individual OCO-2 observations are comparable to the atmospheric signal from biospheric fluxes, particularly during northern hemisphere winter when biospheric fluxes are small. A series of top-down experiments indicate how these errors affect our ability to constrain monthly biospheric CO 2 budgets. We are able to constrain budgets for between two and four global regions using OCO-2 observations, depending on the month, and we can constrain CO 2 budgets at the regional level (i.e., smaller than seven global biomes) in only a handful of cases (16% of 10 all regions and months). The potential of the OCO-2 observations, however, is greater than these results might imply. A set of synthetic data experiments suggests that observation or retrieval errors have a salient effect. Advances in retrieval algorithms and to a lesser extent atmospheric transport modeling will improve the results. In the interim, top-down studies that use current satellite observations are best-equipped to constrain the biospheric carbon balance across only continental or hemispheric regions.

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Interpreting seasonal changes in the carbon balance of southern Amazonia using measurements of XCO₂ and chlorophyll fluorescence from GOSAT

Cited by 97 publications

References 44 publications

Detecting regional patterns of changing CO ₂ flux in Alaska

Detecting regional patterns of changing CO ₂ flux in Alaska

Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence

Characterizing biospheric carbon balance using CO<sub>2</sub> observations from the OCO-2 satellite

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Interpreting seasonal changes in the carbon balance of southern Amazonia using measurements of XCO2 and chlorophyll fluorescence from GOSAT

Cited by 97 publications

References 44 publications

Detecting regional patterns of changing CO 2 flux in Alaska

Detecting regional patterns of changing CO 2 flux in Alaska

Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence

Characterizing biospheric carbon balance using CO&lt;sub&gt;2&lt;/sub&gt; observations from the OCO-2 satellite

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Interpreting seasonal changes in the carbon balance of southern Amazonia using measurements of XCO₂ and chlorophyll fluorescence from GOSAT

Detecting regional patterns of changing CO ₂ flux in Alaska

Detecting regional patterns of changing CO ₂ flux in Alaska

Characterizing biospheric carbon balance using CO<sub>2</sub> observations from the OCO-2 satellite