The Orbiting Carbon Observatory‐2 (OCO‐2) collects solar‐induced chlorophyll fluorescence (SIF) at high spatial resolution along orbits (
SIF¯oco2_orbit), but its discontinuous spatial coverage ...precludes its full potential for understanding the mechanistic SIF‐photosynthesis relationship. This study developed a spatially contiguous global OCO‐2 SIF product at 0.05° and 16‐day resolutions (
SIF¯oco2_005) using machine learning constrained by physiological understandings. This was achieved by stratifying biomes and times for training and predictions, which accounts for varying plant physiological properties in space and time.
SIF¯oco2_005 accurately preserved the spatiotemporal variations of
SIF¯oco2_orbit across the globe. Validation of
SIF¯oco2_005 with Chlorophyll Fluorescence Imaging Spectrometer airborne measurements revealed striking consistency (R2 = 0.72; regression slope = 0.96). Further, without time and biome stratification, (1)
SIF¯oco2_005 of croplands, deciduous temperate, and needleleaf forests would be underestimated during the peak season, (2)
SIF¯oco2_005 of needleleaf forests would be overestimated during autumn, and (3) the capability of
SIF¯oco2_005 to detect drought would be diminished.
Plain Language Summary
Newly available observations of solar‐induced chlorophyll fluorescence (SIF) from satellite sensors represent a major step toward quantifying photosynthesis globally in real time. However, existing satellite SIF records are restricted to low spatial resolutions, sparse data acquisition, or both. These limitations impede the full capability of SIF for improving our understanding of dynamics of photosynthesis and its response to environmental changes (particularly in heterogeneous landscapes) to better support carbon source/sink attribution and verification. This study developed a novel high‐resolution time series of spatially contiguous SIF for the globe, leveraging NASA's Orbiting Carbon Observatory‐2 measurements. We combined machine learning algorithms with known physiological constraints for this effort. Comparison with independent airborne SIF measurements revealed strong consistency, confirming the high quality of this new SIF data set. The high‐resolution and global contiguous coverage of this data set will greatly enhance the synergy between satellite SIF and photosynthesis measured on the ground at consistent spatial scales. Potential applications with this data set include advancing dynamic drought monitoring and mitigation, informing agricultural planning and yield estimation in a more spatially explicit way, and providing a benchmark for upcoming satellite missions with SIF capabilities at higher spatial resolutions.
Key Points
A spatially contiguous global OCO‐2 SIF data set at 0.05° and 16‐day resolutions (
SIF¯oco2_005) was developed using machine learning and physiological constraints
SIF¯oco2_005 successfully preserves the spatiotemporal variability of the original OCO‐2 SIF retrievals, captures water stress, and reduces noise
SIF¯oco2_005 is highly consistent with independent airborne measurements, demonstrating the effectiveness and validity of the prediction framework
Quantifying gross primary production (GPP) remains a major challenge in global carbon cycle research. Spaceborne monitoring of solar-induced chlorophyll fluorescence (SIF), an integrative ...photosynthetic signal of molecular origin, can assist in terrestrial GPP monitoring. However, the extent to which SIF tracks spatiotemporal variations in GPP remains unresolved. Orbiting Carbon Observatory-2 (OCO-2)'s SIF data acquisition and fine spatial resolution permit direct validation against ground and airborne observations. Empirical orthogonal function analysis shows consistent spatiotemporal correspondence between OCO-2 SIF and GPP globally. A linear SIF-GPP relationship is also obtained at eddy-flux sites covering diverse biomes, setting the stage for future investigations of the robustness of such a relationship across more biomes. Our findings support the central importance of high-quality satellite SIF for studying terrestrial carbon cycle dynamics.
NASA's Orbiting Carbon Observatory-2 (OCO-2) mission was motivated by the need to diagnose how the increasing concentration of atmospheric carbon dioxide (CO
) is altering the productivity of the ...biosphere and the uptake of CO
by the oceans. Launched on 2 July 2014, OCO-2 provides retrievals of the column-averaged CO
dry-air mole fraction (Formula: see text) as well as the fluorescence from chlorophyll in terrestrial plants. The seasonal pattern of uptake by the terrestrial biosphere is recorded in fluorescence and the drawdown of Formula: see text during summer. Launched just before one of the most intense El Niños of the past century, OCO-2 measurements of Formula: see text and fluorescence record the impact of the large change in ocean temperature and rainfall on uptake and release of CO
by the oceans and biosphere.
Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and ...global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5° × 0.5°. We also show some significant differences between fluorescence and coincident normalized difference vegetation indices (NDVI) retrievals.
Global retrieval of solar induced fluorescence emitted by terrestrial vegetation can provide an unprecedented measure for photosynthetic efficiency. The GOSAT (JAXA, launched Feb. 2009) and OCO‐2 ...(NASA, to be launched 2013) satellites record high‐resolution spectra in the O2 A‐band region, overlapping part of the chlorophyll fluorescence spectrum. We show that fluorescence cannot be unambiguously discriminated from atmospheric scattering effects using O2 absorption lines. This can cause systematic biases in retrieved scattering parameters (aerosol optical thickness, aerosol height, surface pressure, surface albedo) if fluorescence is neglected. Hence, we demonstrate an efficient alternative fluorescence least‐squares retrieval method based solely on strong Fraunhofer lines in the vicinity of the O2 A‐band, disentangling fluorescence from scattering effects. Not only does the Fraunhofer line fit produce a more accurate estimate of fluorescence emission, but it also allows improved retrievals of atmospheric aerosols from the O2 A‐band.
Diagnosing land‐atmosphere fluxes of carbon‐dioxide (CO2) and methane (CH4) is essential for evaluating carbon‐climate feedbacks. Greenhouse gas satellite missions aim to fill data gaps in regions ...like the humid tropics but obtain very few valid measurements due to cloud contamination. We examined data yields from the Orbiting Carbon Observatory alongside Sentinel‐2 cloud statistics. We find that the main contribution to low data yields are frequent shallow cumulus clouds. In the Amazon, the success rate in obtaining valid measurements vary from 0.1% to 1.0%. By far the lowest yields occur in the wet season, consistent with Sentinel‐2 cloud patterns. We find that increasing the spatial resolution of observations to ∼200 m would increase yields by 2–3 orders of magnitude and allow regular measurements in the wet season. Thus, the key to effective tropical greenhouse gas observations lies in regularly acquiring high‐spatial resolution data.
Plain Language Summary
Our research looks at how well satellites are able to observe greenhouse gases such as carbon dioxide and methane in tropical areas, which is important for understanding climate change. We find that these satellites often cannot make good measurements in places like the Amazon rainforest due to clouds. By using space‐based instruments that can peek in between clouds (requiring about ∼200 m spatial resolution), we would get much more frequent information, even during the rainy season. Our study shows that high‐spatial resolution is needed to regularly observe greenhouse gases in the tropics.
Key Points
Data yields of current remotely sensed greenhouse gas (GHG) missions in the humid tropics are often below 1%
Shallow cumulus clouds cause most of the low data yields, esp. in the wet season
Finer spatial resolution (∼200 m) can overcome the data sparsity in the tropics
Global monitoring of sun-induced chlorophyll fluorescence (SIF) is improving our knowledge about the photosynthetic functioning of terrestrial ecosystems. The feasibility of SIF retrievals from ...spaceborne atmospheric spectrometers has been demonstrated by a number of studies in the last years. In this work, we investigate the potential of the upcoming TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite mission for SIF retrieval. TROPOMI will sample the 675–775 nm spectral window with a spectral resolution of 0.5 nm and a pixel size of 7 km × 7 km. We use an extensive set of simulated TROPOMI data in order to assess the uncertainty of single SIF retrievals and subsequent spatio-temporal composites. Our results illustrate the enormous improvement in SIF monitoring achievable with TROPOMI with respect to comparable spectrometers currently in-flight, such as the Global Ozone Monitoring Experiment-2 (GOME-2) instrument. We find that TROPOMI can reduce global uncertainties in SIF mapping by more than a factor of 2 with respect to GOME-2, which comes together with an approximately 5-fold improvement in spatial sampling. Finally, we discuss the potential of TROPOMI to map other important vegetation parameters at a global scale with moderate spatial resolution and short revisit time. Those include leaf photosynthetic pigments and proxies for canopy structure, which will complement SIF retrievals for a self-contained description of vegetation condition and functioning.
With the advent of dedicated greenhouse gas space-borne spectrometers sporting high resolution spectra in the O2 A-band spectral region (755-774 nm), the retrieval of chlorophyll fluorescence has ...become feasible on a global scale. If unaccounted for, however, fluorescence can indirectly perturb the greenhouse gas retrievals as it perturbs the oxygen absorption features. As atmospheric CO2 measurements are used to invert net fluxes at the land-atmosphere interface, a bias caused by fluorescence can be crucial as it will spatially correlate with the fluxes to be inverted. Avoiding a bias and retrieving fluorescence accurately will provide additional constraints on both the net and gross fluxes in the global carbon cycle. We show that chlorophyll fluorescence, if neglected, systematically interferes with full-physics multi-band XCO2 retrievals using the O2 A-band. Systematic biases in XCO2 can amount to +1 ppm if fluorescence constitutes 1% to the continuum level radiance. We show that this bias can be largely eliminated by simultaneously fitting fluorescence in a full-physics based retrieval. If fluorescence is the primary target, a dedicated but very simple retrieval based purely on Fraunhofer lines is shown to be more accurate and very robust even in the presence of large scattering optical depths. We find that about 80% of the surface fluorescence is retained at the top-of-atmosphere, even for cloud optical thicknesses around 2-5. We further show that small instrument modifications to future O2 A-band spectrometer spectral ranges can result in largely reduced random errors in chlorophyll fluorescence, paving the way towards a more dedicated instrument exploiting solar absorption features only.
This work describes the NASA Atmospheric CO2 Observations from Space (ACOS) XCO2 retrieval algorithm, and its performance on highly realistic, simulated observations. These tests, restricted to ...observations over land, are used to evaluate retrieval errors in the face of realistic clouds and aerosols, polarized non-Lambertian surfaces, imperfect meteorology, and uncorrelated instrument noise. We find that post-retrieval filters are essential to eliminate the poorest retrievals, which arise primarily due to imperfect cloud screening. The remaining retrievals have RMS errors of approximately 1 ppm. Modeled instrument noise, based on the Greenhouse Gases Observing SATellite (GOSAT) in-flight performance, accounts for less than half the total error in these retrievals. A small fraction of unfiltered clouds, particularly thin cirrus, lead to a small positive bias of ~0.3 ppm. Overall, systematic errors due to imperfect characterization of clouds and aerosols dominate the error budget, while errors due to other simplifying assumptions, in particular those related to the prior meteorological fields, appear small.
Simulations of carbon fluxes with terrestrial biosphere models still exhibit significant uncertainties, in part due to the uncertainty in model parameter values. With the advent of satellite ...measurements of solar induced chlorophyll fluorescence (SIF), there exists a novel pathway for constraining simulated carbon fluxes and parameter values. We investigate the utility of SIF in constraining gross primary productivity (GPP). As a first test we assess whether SIF simulations are sensitive to important parameters in a biosphere model. SIF measurements at the wavelength of 755 nm are simulated by the Carbon-Cycle Data Assimilation System (CCDAS) which has been augmented by the fluorescence component of the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model. Idealized sensitivity tests of the SCOPE model stand-alone indicate strong sensitivity of GPP to the carboxylation capacity (Vcmax) and of SIF to the chlorophyll AB content (Cab) and incoming short wave radiation. Low sensitivity is found for SIF to Vcmax, however the relationship is subtle, with increased sensitivity under high radiation conditions and lower Vcmax ranges. CCDAS simulates well the patterns of satellite-measured SIF suggesting the combined model is capable of ingesting the data. CCDAS supports the idealized sensitivity tests of SCOPE, with SIF exhibiting sensitivity to Cab and incoming radiation, both of which are treated as perfectly known in previous CCDAS versions. These results demonstrate the need for careful consideration of Cab and incoming radiation when interpreting SIF and the limitations of utilizing SIF to constrain Vcmax in the present set-up in the CCDAS system.
PDF
