Abstract. Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GCP-CH4-2019 (Saunois et al., 2020) and from the Global Carbon Project.

Chlorophyll a fluorescence (ChlF) has been used for decades to study the organization, functioning, and physiology of photosynthesis at the leaf and subcellular levels. ChlF is now measurable from remote sensing platforms. This provides a new optical means to track photosynthesis and gross primary productivity of terrestrial ecosystems. Importantly, the spatiotemporal and methodological context of the new applications is dramatically different compared with most of the available ChlF literature, which raises a number of important considerations. Although we have a good mechanistic understanding of the processes that control the ChlF signal over the short term, the seasonal link between ChlF and photosynthesis remains obscure. Additionally, while the current understanding of in vivo ChlF is based on pulse amplitude-modulated (PAM) measurements, remote sensing applications are based on the measurement of the passive solar-induced chlorophyll fluorescence (SIF), which entails important differences and new challenges that remain to be solved. In this review we introduce and revisit the physical, physiological, and methodological factors that control the leaf-level ChlF signal in the context of the new remote sensing applications. Specifically, we present the basis of photosynthetic acclimation and its optical signals, we introduce the physical and physiological basis of ChlF from the molecular to the leaf level and beyond, and we introduce and compare PAM and SIF methodology. Finally, we evaluate and identify the challenges that still remain to be answered in order to consolidate our mechanistic understanding of the remotely sensed SIF signal.

[1] Our ability to close the Earth's carbon budget and predict feedbacks in a warming climate depends critically on knowing where, when and how carbon dioxide is exchanged between the land and atmosphere. Terrestrial gross primary production (GPP) constitutes the largest flux component in the global carbon budget, however significant uncertainties remain in GPP estimates and its seasonality. Empirically, we show that global spaceborne observations of solar induced chlorophyll fluorescence -occurring during photosynthesis -exhibit a strong linear correlation with GPP. We found that the fluorescence emission even without any additional climatic or model information has the same or better predictive skill in estimating GPP as those derived from traditional remotely-sensed vegetation indices using ancillary data and model assumptions. In boreal summer the generally strong linear correlation between fluorescence and GPP models weakens, attributable to discrepancies in savannas/ croplands (18-48% higher fluorescence-based GPP derived by simple linear scaling), and high-latitude needleleaf forests (28-32% lower fluorescence). Our results demonstrate that retrievals of chlorophyll fluorescence provide direct global observational constraints for GPP and open an entirely new viewpoint on the global carbon cycle. We anticipate that global fluorescence data in combination with consolidated plant physiological fluorescence models will be a step-change in carbon cycle research and enable an unprecedented robustness in the understanding of the current and future carbon cycle. Citation: Frankenberg, C., et al.

Abstract. The global methane (CH 4 ) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH 4 over the past decade. Emissions and concentrations of CH 4 are continuing to increase, making CH 4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH 4 sources that overlap geographically, and from the destruction of CH 4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (∼ biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). . Top-down inversions consistently infer lower emissions in China (∼ 58 Tg CH 4 yr −1 , range 51-72, −14 %) and higher emissions in Africa (86 Tg CH 4 yr −1 , range 73-108, +19 %) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models.The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30-40 % on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions.

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...

Abstract. 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.

INTRODUCTION The influence of El Niño on climate is accompanied by large changes to the carbon cycle, and El Niño–induced variability in the carbon cycle has been attributed mainly to the tropical continents. However, owing to a dearth of observations in the tropics, tropical carbon fluxes are poorly quantified, and considerable debate exists over the dominant mechanisms (e.g., plant growth, respiration, fire) and regions (e.g., humid versus semiarid tropics) on the net carbon balance. RATIONALE The launch of the Orbiting Carbon Observatory-2 (OCO-2) shortly before the 2015–2016 El Niño, the second strongest since the 1950s, has provided an opportunity to understand how tropical land carbon fluxes respond to the warm and dry climate characteristics of El Niño conditions. The El Niño events may also provide a natural experiment to study the response of tropical land carbon fluxes to future climate changes, because anomalously warm and dry tropical environments typical of El Niño are expected to be more frequent under most emission scenarios. RESULTS The tropical regions of three continents (South America, Asia, and Africa) had heterogeneous responses to the 2015–2016 El Niño, in terms of both climate drivers and the carbon cycle. The annual mean precipitation over tropical South America and tropical Asia was lower by 3.0σ and 2.8σ, respectively, in 2015 relative to the 2011 La Niña year. Tropical Africa, on the other hand, had near equal precipitation and the same number of dry months between 2015 and 2011; however, surface temperatures were higher by 1.6σ, dominated by the positive anomaly over its eastern and southern regions. In response to the warmer and drier climate anomaly in 2015, the pantropical biosphere released 2.5 ± 0.34 gigatons more carbon into the atmosphere than in 2011, which accounts for 83.3% of the global total 3.0–gigatons of carbon (gigatons C) net biosphere flux differences and 92.6% of the atmospheric CO 2 growth-rate differences between 2015 and 2011. It indicates that the tropical land biosphere flux anomaly was the driver of the highest atmospheric CO 2 growth rate in 2015. The three tropical continents had an approximately even contribution to the pantropical net carbon flux anomaly in 2015, but had diverse dominant processes: gross primary production (GPP) reduced carbon uptake (0.9 ± 0.96 gigatons C) in tropical South America, fire increased carbon release (0.4 ± 0.08 gigatons C) in tropical Asia, and respiration increased carbon release (0.6 ± 1.01 gigatons C) in Africa. We found that most of the excess carbon release in 2015 was associated with either extremely low precipitation or high temperatures, or both. CONCLUSION Our results indicate that the global El Niño effect is a superposition of regionally specific effects. The heterogeneous climate forcing and carbon response over the three tropical continents to the 2015–2016 El Niño challenges previous studies that suggested that a single dominant process determines carbon cycle interannual variability, which could also be due to previous disturbance and soil and vegetation structure. The similarity between the 2015 tropical climate anomaly and the projected climate changes imply that the role of the tropical land as a buffer for fossil fuel emissions may be reduced in the future. The heterogeneous response may reflect differences in temperature and rainfall anomalies, but intrinsic differences in vegetation species, soils, and prior disturbance may contribute as well. A synergistic use of multiple satellite observations and a long time series of spatially resolved fluxes derived from sustained satellite observations will enable tests of these hypotheses, allow for a more process-based understanding, and, ultimately, aid improved carbon-climate model projections. Diverse climate driver anomalies and carbon cycle responses to the 2015–2016 El Niño over the three tropical continents. Schematic of climate anomaly patterns over the three tropical continents and the anomalies of the net carbon flux and its dominant constituent flux (i.e., GPP, respiration, and fire) relative to the 2011 La Niña during the 2015–2016 El Niño. GtC, gigatons C.

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