Influence of El Niño on atmospheric CO2 over the tropical Pacific Ocean: Findings from NASA's OCO-2 mission

Characterizing the regional XCO2 variability and its association with ENSO over India inferred from GOSAT and OCO-2 satellite observations

India is primarily concerned with comprehending regional carbon source-sink response in the context of changes in atmospheric CO2 concentrations or anthropogenic emissions. Recent advancements in high-resolution satellite's fine-scale XCO2 measurements provide an opportunity to understand unprecedented details of source-sink activity on a regional scale. In this study, we investigated the long-term variations of XCO2 concentration and growth rates as well as its covarying relationship with ENSO and regional climate parameters (temperature, precipitation, soil moisture, and NDVI) over India from 2010 to 2021 using GOSAT and OCO-2 retrievals. The results show since the launch of OCO-2 in 2014, the number of monthly high-quality XCO2 soundings over India has grown nearly 100-fold compared to GOSAT, launched in 2009. Also, the discrepancy in XCO2 increase of 2.54(2.43) ppm/yr was observed in GOSAT (OCO-2) retrieval during an overlapping measurement period (2015-2021). Additionally, wavelet analysis indicated that the OCO-2 retrieval is able to capture a better frequency of local-scale XCO2 variability compared to GOSAT, owing to its high-resolution cloud-free XCO2 soundings, providing more well-defined regional-scale source-sink features. Furthermore, dominant spatial pattern of XCO2 variability observed over south and southeast of India in both satellites, with XCO2 semi-annual and annual variability more distinctly present in OCO-2 compared to GOSAT. A cross-correlation analysis suggested GOSAT XCO2 growth rate positively correlates with ENSO in different homogeneous monsoon regions of India, with ENSO leading the GOSAT XCO2 growth rate in all homogeneous regions by 3-9 months. The South Peninsular region sensitive to ENSO changes, especially during 2015-2016 ENSO event, where a decrease in CO2 uptake was observed is closely linked with precipitation, soil moisture, and temperature anomalies. However, regional climate parameters show a low correlation with XCO2 growth since CO2 is a long-lived well-mixed gas primarily having an imprint of large-scale transport in column CO2.

A multi-satellite framework to rapidly evaluate extreme biosphere cascades: The Western US 2021 drought and heatwave

The increasing frequency and intensity of climate extremes and complex ecosystem responses motivate the need for integrated observational studies at low latency to determine biosphere responses and carbon-climate feedbacks. Here, we develop a satellite-based rapid attribution workflow and demonstrate its use at a 1-2-month latency to attribute drivers of the carbon cycle feedbacks during the 2020-2021 Western US drought and heatwave. In the first half of 2021, concurrent negative photosynthesis anomalies and large positive column CO2 anomalies were detected with satellites. Using a simple atmospheric mass balance approach, we estimate a surface carbon efflux anomaly of 132 TgC in June 2021, a magnitude corroborated independently with a dynamic global vegetation model. Integrated satellite observations of hydrologic processes, representing the soil-plant-atmosphere continuum (SPAC), show that these surface carbon flux anomalies are largely due to substantial reductions in photosynthesis because of a spatially widespread moisture-deficit propagation through the SPAC between 2020 and 2021. A causal model indicates deep soil moisture stores partially drove photosynthesis, maintaining its values in 2020 and driving its declines throughout 2021. The causal model also suggests legacy effects may have amplified photosynthesis deficits in 2021 beyond the direct effects of environmental forcing. The integrated, observation framework presented here provides a valuable first assessment of a biosphere extreme response and an independent testbed for improving drought propagation and mechanisms in models. The rapid identification of extreme carbon anomalies and hotspots can also aid mitigation and adaptation decisions.

Low frequency changes in CO2 concentration in East Asia related to Pacific decadal oscillation and Atlantic multi-decadal oscillation for mid-summer and early fall

The climatological seasonal maximum and minimum CO₂ concentrations in East Asia for 1987-2020 have been recorded at April and August, respectively. We found that the CO₂ concentration in East Asia during July, August, and September (JAS) is lower than normal before the late 1990s and after the early 2010s (Low_CO₂ period), and higher than normal from the late 1990s to the early 2010s (High_CO₂ period). The low-frequency variability of CO₂ concentration in East Asia during JAS correlates with both Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO)-related sea surface temperatures (SSTs). We analyzed atmospheric and oceanic conditions during JAS between the two periods, finding that precipitation in East Asia decreased during JAS in High_CO₂ period than that in Low_CO₂ period, possibly due to PDO and AMO-related SST forcing, which decreases vegetation's photosynthetic activity. This may lead to a higher CO₂ concentration than normal in East Asia in High_CO₂ period through reduced uptake of CO₂ from the atmosphere. This implies that terrestrial vegetation activity influenced by remote SST forcings should be monitored to better understand regional carbon cycles in East Asia.

The carbon sink of the Coral Sea, the world's second largest marginal sea, weakened during 2006-2018

The latest reports show that the ocean absorbs approximately 26 % of anthropogenic CO₂ and that the carbon sink of the global ocean (air-sea CO₂ flux) is continually increasing, while variations in different marginal seas are complicated. The Coral Sea, the second largest marginal sea in the world, is characterized by a generally oligotrophic basin and borders the biodiversity hotspot of Great Barrier Reef. In this study, we proposed a semianalytical method and reconstructed the first high-resolution satellite-based pCO₂ and air-sea CO₂ flux dataset from 2006 to 2018 for the Coral Sea. This dataset performed well in the basin (RMSE<10 μatm, R² > 0.72) and coral reef areas (RMSE<12 μatm, R² > 0.8) based on validation by a massive independent dataset. We found that sea surface pCO₂ is increasing (1.8 to 2.7 μatm/year) under the forcing of increasing atmospheric CO₂, and the pCO₂ growth rate in water is faster than that in the atmosphere. The combination of increasing sea surface pCO₂, high pCO₂ seawater from coral reef areas, and the low depletion capacity of the oligotrophic basin led to a gradual weakening of the carbon sink in the Coral Sea, with the 2016 carbon sink being 52 % of that in 2006. This weakening was more pronounced after strong El Niño events (e.g., 2007, 2010, and 2016), with the corresponding high SST and low wind speed further weakening the carbon sink. This understanding of the long-term change in the Coral Sea provides new insight on the carbonate system variation and carbon sink capacity evolution in seawater under increasing atmospheric CO₂.

Robust algorithm for precise XCO2 retrieval using single observation of IPDA LIDAR

CO₂ column-weighted dry-air mixing ratio (X_CO2) products with high precision and spatial resolution are essential for inverting CO₂ fluxes and promoting our understanding of global climate change. Compared with passive remote sensing methods, IPDA LIDAR, as an active remote sensing technique, offers many advantages in measuring X_CO2. However, a significant random error in IPDA LIDAR measurements causes X_CO2 values calculated directly from LIDAR signals to be unqualified as the final X_CO2 products. Hence, we propose an efficient particle filter-based inversion of CO₂ for single observation (EPICSO) algorithm to precisely retrieve the X_CO2 of every LIDAR observation while preserving the high spatial resolution of LIDAR measurements. The EPICSO algorithm adopts the sliding average results as the first estimate of the local X_CO2; subsequently, it estimates the difference between two adjacent X_CO2 points and calculates the posterior probability of X_CO2 based on particle filter theory. To evaluate the performance of the EPICSO algorithm numerically, we perform an EPICSO to process pseudo-observation data. The simulation results show that the results retrieved by the EPICSO algorithm satisfy the required high precision and that the algorithm is robust to a significant amount of random errors. In addition, we utilize LIDAR observation data from actual experiments in Hebei, China, to validate the performance of the EPICSO algorithm. The results retrieved by the EPICSO algorithm are more consistent with the actual local X_CO2 than those of the conventional method, indicating that the EPICSO algorithm is efficient and practical for retrieving X_CO2 with high precision and spatial resolution.

A high concentration CO2 pool over the Indo-Pacific Warm Pool

Anthropogenic emissions have produced significant amount of carbon dioxide (CO₂) in the atmosphere since the beginning of the industrial revolution. High levels of atmospheric CO₂ increases global temperature as CO₂ absorbs outgoing longwave radiation and re-emits. Though a well-mixed greenhouse gas, CO₂ concentration is not uniform in the atmosphere across different altitudes and latitudes. Here, we uncover a region of high CO₂ concentration (i.e. CO₂ pool) in the middle troposphere (500-300 hPa) over the Indo-Pacific Warm Pool (IPWP, 40° E-140° W, 25° S-25° N), in which the CO₂ concentration is higher than that of other regions in the same latitude band (20° N-20° S), by using CO₂ satellite measurements for the period 2002-2017. This CO₂ pool extends from the western Pacific to the eastern Indian Ocean. Much of the CO₂ pool is over the western Pacific Ocean (74.87%), and the remaining lies over the eastern Indian Ocean (25.13%). The rising branch of Walker circulation acts as a "CO₂ Chimney" that constantly transports CO₂ released from the natural, human-induced and ocean outgassing processes to the middle and upper troposphere. The CO₂ pool evolves throughout the year with an average annual trend of about 2.17 ppm yr^-1, as estimated for the period 2003-2016. Our analysis further reveals that La Niña (El Niño) events strengthen (weaken) the CO₂ pool in the mid-troposphere. The radiative forcing for the CO₂ pool suggests more warming in the region and is a grave concern for global warming and climate change.

Role of space station instruments for improving tropical carbon flux estimates using atmospheric data

The tropics is the nexus for many of the remaining gaps in our knowledge of environmental science, including the carbon cycle and atmospheric chemistry, with dire consequences for our ability to describe the Earth system response to a warming world. Difficulties associated with accessibility, coordinated funding models and economic instabilities preclude the establishment of a dense pan-tropical ground-based atmospheric measurement network that would otherwise help to describe the evolving state of tropical ecosystems and the associated biosphere-atmosphere fluxes on decadal timescales. The growing number of relevant sensors aboard sun-synchronous polar orbiters provide invaluable information over the remote tropics, but a large fraction of the data collected along their orbits is from higher latitudes. The International Space Station (ISS), which is in a low-inclination, precessing orbit, has already demonstrated value as a proving ground for Earth observing atmospheric sensors and as a testbed for new technology. Because low-inclination orbits spend more time collecting data over the tropics, we argue that the ISS and its successors, offer key opportunities to host new Earth-observing atmospheric sensors that can lead to a step change in our understanding of tropical carbon fluxes.

Seasonal and annual variations of CO2 and CH4 at Shadnagar, a semi-urban site

Carbon dioxide (CO₂) and methane (CH₄) are the most important greenhouse gases (GHGs) due to their significant role in anthropogenic global climate change. The spatio-temporal variations of their concentration are characterized by the terrestrial biosphere, seasonal weather patterns and anthropogenic emissions. Hence, to understand the variability in regional surface GHG fluxes, high precision GHGs measurements were initiated by the National Remote Sensing Center (NRSC) of India. We report continuous CO₂ and CH₄measurements during 2014 to 2017 for the first time from Shadnagar, a suburban site in India. Annual mean CO₂ and CH₄ concentrations are 399.56 ± 5.46 ppm and 1.929 ± 0.09 ppm, respectively, for 2017. After the strong El Niño of 2015-2016, an abnormal rise in CO₂ growth rate of 5.5 ppm year^-1 was observed in 2017 at the study site, compared to 3.03 ppm year^-1 at Mauna Loa. Thus, the repercussion of the El Niño effect diminishes the net uptake by the terrestrial biosphere accompanied by increased soil respiration. Seasonal tracer to tracer correlation between CO₂ and CH₄ was also analyzed to characterize the possible source-sink relationship between the species. We compared CO₂ and CH₄ concentrations to simulations from an atmospheric chemistry transport model (ACTM). The seasonal phases of CH₄ were well captured by the ACTM, whereas the seasonal cycle amplitude of CO₂ was underestimated by about 30%.

Attribution of Space-Time Variability in Global-Ocean Dissolved Inorganic Carbon

The inventory and variability of oceanic dissolved inorganic carbon (DIC) is driven by the interplay of physical, chemical, and biological processes. Quantifying the spatiotemporal variability of these drivers is crucial for a mechanistic understanding of the ocean carbon sink and its future trajectory. Here, we use the Estimating the Circulation and Climate of the Ocean-Darwin ocean biogeochemistry state estimate to generate a global-ocean, data-constrained DIC budget and investigate how spatial and seasonal-to-interannual variability in three-dimensional circulation, air-sea CO₂ flux, and biological processes have modulated the ocean sink for 1995-2018. Our results demonstrate substantial compensation between budget terms, resulting in distinct upper-ocean carbon regimes. For example, boundary current regions have strong contributions from vertical diffusion while equatorial regions exhibit compensation between upwelling and biological processes. When integrated across the full ocean depth, the 24-year DIC mass increase of 64 Pg C (2.7 Pg C year^-1) primarily tracks the anthropogenic CO₂ growth rate, with biological processes providing a small contribution of 2% (1.4 Pg C). In the upper 100 m, which stores roughly 13% (8.1 Pg C) of the global increase, we find that circulation provides the largest DIC gain (6.3 Pg C year^-1) and biological processes are the largest loss (8.6 Pg C year^-1). Interannual variability is dominated by vertical advection in equatorial regions, with the 1997-1998 El Niño-Southern Oscillation causing the largest year-to-year change in upper-ocean DIC (2.1 Pg C). Our results provide a novel, data-constrained framework for an improved mechanistic understanding of natural and anthropogenic perturbations to the ocean sink.

Seasonal Variations of Solar-Induced Fluorescence, Precipitation, and Carbon Dioxide Over the Amazon

Previous studies suggested that the Amazon, the largest rainforest on Earth, changes from a CO₂ sink to a CO₂ source during the dry/fire season. However, the biospheric contributions to atmospheric CO₂ are not well understood during the two main seasons, the dry/fire season and the wet season. In this article, we utilize Orbiting Carbon Observatory 2 (OCO-2) Solar-Induced Fluorescence (SIF) to explore photosynthetic activity during the different seasons. The spatiotemporal variability of OCO-2 SIF, OCO-2 CO₂, precipitation, and burned area are investigated over the Amazon from September 2014 to December 2019. Averaging over the entire Amazon region, we found a positive temporal correlation (0.94) between OCO-2 SIF and Global Precipitation Climatology Project precipitation and a negative temporal correlation (-0.64) between OCO-2 SIF and OCO-2 CO₂, consistent with the fact that precipitation enhances photosynthesis, which results in higher values for SIF and rate of removal of CO₂ from the atmosphere above the Amazon region. We also observed seasonality in the spatial variability of these variables within the Amazon region. During the dry/fire (August-October) season, low SIF values, low precipitation, high vapor pressure deficit (VPD), large burned areas, and high atmospheric CO₂ are mainly found over the southern Amazon region. In contrast, during the wet season (January-March), high SIF values, high precipitation, low VPD, smaller burned areas, and low CO₂ are found over both the central and southern Amazon regions. The seasonal difference in SIF suggests that photosynthetic activity is reduced during the dry/fire season relative to the wet season as a result of low precipitation and high VPD, especially over the southern Amazon region, which will contribute to more CO₂ in the atmosphere during the dry/fire season.

On the Detection of COVID-Driven Changes in Atmospheric Carbon Dioxide

We assess the detectability of COVID-like emissions reductions in global atmospheric CO2 concentrations using a suite of large ensembles conducted with an Earth system model. We find a unique fingerprint of COVID in the simulated growth rate of CO2 sampled at the locations of surface measurement sites. Negative anomalies in growth rates persist from January 2020 through December 2021, reaching a maximum in February 2021. However, this fingerprint is not formally detectable unless we force the model with unrealistically large emissions reductions (2 or 4 times the observed reductions). Internal variability and carbon-concentration feedbacks obscure the detectability of short-term emission reductions in atmospheric CO2. COVID-driven changes in the simulated, column-averaged dry air mole fractions of CO2 are eclipsed by large internal variability. Carbon-concentration feedbacks begin to operate almost immediately after the emissions reduction; these feedbacks reduce the emissions-driven signal in the atmosphere carbon reservoir and further confound signal detection.

Regional impacts of COVID-19 on carbon dioxide detected worldwide from space

Activity reductions in early 2020 due to the coronavirus disease 2019 pandemic led to unprecedented decreases in carbon dioxide (CO₂) emissions. Despite their record size, the resulting atmospheric signals are smaller than and obscured by climate variability in atmospheric transport and biospheric fluxes, notably that related to the 2019–2020 Indian Ocean Dipole. Monitoring CO₂ anomalies and distinguishing human and climatic causes thus remain a new frontier in Earth system science. We show that the impact of short-term regional changes in fossil fuel emissions on CO₂ concentrations was observable from space. Starting in February and continuing through May, column CO₂ over many of the world’s largest emitting regions was 0.14 to 0.62 parts per million less than expected in a pandemic-free scenario, consistent with reductions of 3 to 13% in annual global emissions. Current spaceborne technologies are therefore approaching levels of accuracy and precision needed to support climate mitigation strategies with future missions expected to meet those needs.

No evidence for global decrease in CO2 concentration during the first wave of COVID-19 pandemic

Numerous studies have reported that CO₂ emissions have decreased because of global lockdown during the first wave of the COVID-19 pandemic. However, previous estimates of the global CO₂ concentration before and after the outbreak of the COVID-19 pandemic are limited because they are based on energy consumption statistics or local specific in-situ observations. The aim of the study was to explore objective evidence for various previous studies that have claimed the global CO₂ concentration decreased during the first wave of the COVID-19 pandemic. There are two ways to measure the global CO₂ concentration: from the top-down using satellites and the bottom-up using ground stations. We implemented the time-series analysis by comparing the before and after the inflection point (first wave of COVID-19) with the long-term CO₂ concentration data obtained from World Meteorological Organization Global Atmosphere Watch (WMO GAW) and Greenhouse Gases Observing Satellite (GOSAT). Measurements from the GOSAT and GAW global monitoring stations show that the CO₂ concentrations in Europe, China, and the USA have continuously risen in March and April 2020 compared with the same months in 2019. These data confirm that the global lockdown during the first wave of the COVID-19 pandemic did not change the vertical CO₂ profile at the global level from the ground surface to the upper layer of the atmosphere. The results of this study provide an important foundation for the international community to explore policy directions to mitigate climate change in the upcoming post-COVID-19 period.

Comparative Evaluation of Top-Down GOSAT XCO2 vs. Bottom-Up National Reports in the European Countries

Submitting national inventory reports (NIRs) on emissions of greenhouse gases (GHGs) is obligatory for parties of the United Nations Framework Convention on Climate Change (UNFCCC). The NIR forms the basis for monitoring individual countries’ progress on mitigating climate change. Countries prepare NIRs using the default bottom–up methodology of the Intergovernmental Panel on Climate Change (IPCC), as approved by the Kyoto protocol. We provide tangible evidence of the discrepancy between official bottom–up NIR reporting (unit: tons) versus top–down XCO2 reporting (unit: ppm) within the European continent, as measured by the Greenhouse Gases Observing Satellite (GOSAT). Bottom–up NIR (annual growth rate of CO2 emission from 2010 to 2016: −1.55%) does not show meaningful correlation (geographically weighted regression coefficient = −0.001, R2 = 0.024) to top–down GOSAT XCO2 (annual growth rate: 0.59%) in the European countries. The top five countries within the European continent on carbon emissions in NIR do not match the top five countries on GOSAT XCO2 concentrations. NIR exhibits anthropogenic carbon-generating activity within country boundaries, whereas satellite signals reveal the trans-boundary movement of natural and anthropogenic carbon. Although bottom–up NIR reporting has already gained worldwide recognition as a method to track national follow-up for treaty obligations, the single approach based on bottom–up did not present background atmospheric CO2 density derived from the air mass movement between the countries. In conclusion, we suggest an integrated measuring, reporting, and verification (MRV) approach using top–down observation in combination with bottom–up NIR that can provide sufficient countrywide objective evidence for national follow-up activities.

Interannual Variability of Air-Sea Exchange of Mercury in the Global Ocean: The "Seesaw Effect" in the Equatorial Pacific and Contributions to the Atmosphere

Air-sea exchange of gaseous elemental mercury (Hg(0)) is influenced by different meteorological factors and the availability of Hg in seawater. Here, we use the MITgcm ocean model to explore the interannual variability of this flux and the influence of oceanographic and atmospheric dynamics. We apply the GEOS-Chem model to further simulate the potential impact of the evasion variability on the atmospheric Hg levels. We find a latitudinal pattern in Hg(0) evasion with a relatively small variability in mid-latitudes (3.1-6.7%) and a large one in the high latitudes and Equator (>10%). Different factors dominate the patterns in the equatorial (wind speed), mid- (oceanic flow and temperature), and high-latitudinal (sea-ice, temperature, and dynamic processes) oceans. A seesaw pattern of Hg(0) evasion anomaly (±5-20%) in the equatorial Pacific is found from November to next January between El Niño and La Niña years, owing to the anomalies in wind speed, temperature, and vertical mixing. Higher atmospheric Hg level (2%-5%) are simulated for Hg(0) evasion fluxes with three-month lag, associated with the suppression of upwelling in the beginning of the El Niño event. Despite of the uncertainties, this study elucidates the spatial patterns of the interannual variability of the ocean Hg(0) evasion flux and its potential impact on atmospheric Hg levels.

Influence of atmospheric parameters on human mortality data at different geographical levels

Human mortality data are often modeled using a demographic approach as a function of time. This approach does not present an adequate fit model for the number of deaths with great variability. For this reason, additional information (social, economic and environmental) is required for complementing and improving demographic modelling. This article evaluated the association between human mortality data (segregated by age and sex) with meteorological and air pollutant covariates at three geographical levels: country, macro-climate regions and county. The modelling was based on a generalized linear modelling framework and takes into account the common characteristic of overdispersion in human mortality data through the application of negative binomial distribution. The proposed approach improved the dynamic behavior of the Farrington-like model (basic demographic model) and took into account the extreme meteorological and natural air pollution events. Notably, the proposed modelling worked well in cases where the amount of data was scarce.

Observations of greenhouse gases as climate indicators

Humans have significantly altered the energy balance of the Earth's climate system mainly not only by extracting and burning fossil fuels but also by altering the biosphere and using halocarbons. The 3rd US National Climate Assessment pointed to a need for a system of indicators of climate and global change based on long-term data that could be used to support assessments and this led to the development of the National Climate Indicators System (NCIS). Here we identify a representative set of key atmospheric indicators of changes in atmospheric radiative forcing due to greenhouse gases (GHGs), and we evaluate atmospheric composition measurements, including non-CO₂ GHGs for use as climate change indicators in support of the US National Climate Assessment. GHG abundances and their changes over time can provide valuable information on the success of climate mitigation policies, as well as insights into possible carbon-climate feedback processes that may ultimately affect the success of those policies. To ensure that reliable information for assessing GHG emission changes can be provided on policy-relevant scales, expanded observational efforts are needed. Furthermore, the ability to detect trends resulting from changing emissions requires a commitment to supporting long-term observations. Long-term measurements of greenhouse gases, aerosols, and clouds and related climate indicators used with a dimming/brightening index could provide a foundation for quantifying forcing and its attribution and reducing error in existing indicators that do not account for complicated cloud processes.

CO2 Concentration, A Critical Factor Influencing the Relationship between Solar-induced Chlorophyll Fluorescence and Gross Primary Productivity

The uncertainty of carbon fluxes of the terrestrial ecosystem is the highest among all flux components, calling for more accurate and efficient means to monitor land sinks. Gross primary productivity (GPP) is a key index to estimate the terrestrial ecosystem carbon flux, which describes the total amount of organic carbon fixed by green plants through photosynthesis. In recent years, the solar-induced chlorophyll fluorescence (SIF), which is a probe for vegetation photosynthesis and can quickly reflect the state of vegetation growth, emerges as a novel and promising proxy to estimate GPP. The launch of Orbiting Carbon Observatory 2 (OCO-2) further makes it possible to estimate GPP at a finer spatial resolution compared with Greenhouse Gases Observing Satellite (GOSAT), Global Ozone Monitoring Experiment-2 (GOME-2) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). However, whether the relationship between GPP and SIF is linear or non-linear has always been controversial. In this research, we proposed a new model to estimate GPP using SIF and the atmospheric CO2 concentration from OCO-2 as critical driven factors simultaneously (SIF-CO2-GPP model). Evidences from all sites show that the introduction of the atmospheric CO2 concentration improves accuracies of estimated GPP. Compared with the SIF-CO2-GPP linear model, we found the SIF-GPP model overestimated GPP in summer and autumn but underestimated it in spring and winter. A series of simulation experiments based on SCOPE (Soil-Canopy Observation of Photosynthesis and Energy) was carried out to figure out the possible mechanism of improved estimates of GPP due to the introduction of atmospheric CO2 concentrations. These experiments also demonstrate that there could be a non-linear relationship between SIF and GPP at half an hour timescale. Moreover, such relationships vary with CO2 concentration. As OCO-2 is capable of providing SIF and XCO2 products with identical spatial and temporal scales, the SIF-CO2-GPP linear model would be implemented conveniently to monitor GPP using remotely sensed data. With the help of OCO-3 and its successors, the proposed SIF-CO2-GPP linear model would play a significant role in monitoring GPP accurately in large geographical extents.

Dynamics of atmospheric carbon dioxide over different land cover types in India

This study presents an analysis of high-resolution space borne retrievals of the column-averaged dry-air mole fraction of carbon dioxide [Formula: see text] and the role of vegetation in controlling atmospheric CO₂ dynamics over the Indian region. Nadir and glint mode [Formula: see text] retrievals from the Orbiting Carbon Observatory-2 (OCO-2) spectrometer for the period September 2014-July 2017 are studied with satellite-derived normalized difference vegetation index (NDVI) and rainfall over different land cover types. The atmospheric [Formula: see text] variability shows a strong negative correlation with satellite-derived NDVI. Higher rainfall favours the vegetative growth and photosynthetic activity, thus lowers atmospheric [Formula: see text] concentration. The mean monthly [Formula: see text] over terrestrial region of India is observed as 400.18 ± 3.85 ppm with seasonal variations over different land cover types. The correlation of [Formula: see text] with NDVI over mixed forest and deciduous broadleaf forest types was estimated as - 0.86, - 0.76 (p < 0.01), respectively. The study could also highlight strong seasonal [Formula: see text] variability at higher latitudinal zones of India. It is significant to note that space-based observations indicate that atmospheric carbon dioxide levels have surpassed a significant milestone of 400 ppm in recent times. The study provides significant inputs towards improving our understanding of terrestrial biogeochemical carbon cycle over India.

Enhanced North American carbon uptake associated with El Niño

Long-term atmospheric CO₂ mole fraction and δ¹³CO₂ observations over North America document persistent responses to the El Niño-Southern Oscillation. We estimate these responses corresponded to 0.61 (0.45 to 0.79) PgC year^-1 more North American carbon uptake during El Niño than during La Niña between 2007 and 2015, partially offsetting increases of net tropical biosphere-to-atmosphere carbon flux around El Niño. Anomalies in derived North American net ecosystem exchange (NEE) display strong but opposite correlations with surface air temperature between seasons, while their correlation with water availability was more constant throughout the year, such that water availability is the dominant control on annual NEE variability over North America. These results suggest that increased water availability and favorable temperature conditions (warmer spring and cooler summer) caused enhanced carbon uptake over North America near and during El Niño.

Observing Changes in Ocean Carbonate Chemistry: Our Autonomous Future

PURPOSE OF REVIEW

We summarize recent progress on autonomous observations of ocean carbonate chemistry and the development of a network of sensors capable of observing carbonate processes at multiple temporal and spatial scales.

RECENT FINDINGS

The development of versatile pH sensors suitable for both deployment on autonomous vehicles and in compact, fixed ecosystem observatories has been a major development in the field. The initial large-scale deployment of profiling floats equipped with these new pH sensors in the Southern Ocean has demonstrated the feasibility of a global autonomous open-ocean carbonate observing system.

SUMMARY

Our developing network of autonomous carbonate observations is currently targeted at surface ocean CO₂ fluxes and compact ecosystem observatories. New integration of developed sensors on gliders and surface vehicles will increase our coastal and regional observational capability. Most autonomous platforms observe a single carbonate parameter, which leaves us reliant on the use of empirical relationships to constrain the rest of the carbonate system. Sensors now in development promise the ability to observe multiple carbonate system parameters from a range of vehicles in the near future.

The impact of the 2015/2016 El Niño on global photosynthesis using satellite remote sensing

The El Niño-Southern Oscillation exerts a large influence on global climate regimes and on the global carbon cycle. Although El Niño is known to be associated with a reduction of the global total land carbon sink, results based on prognostic models or measurements disagree over the relative contribution of photosynthesis to the reduced sink. Here, we provide an independent remote sensing-based analysis on the impact of the 2015-2016 El Niño on global photosynthesis using six global satellite-based photosynthesis products and a global solar-induced fluorescence (SIF) dataset. An ensemble of satellite-based photosynthesis products showed a negative anomaly of -0.7 ± 1.2 PgC in 2015, but a slight positive anomaly of 0.05 ± 0.89 PgC in 2016, which when combined with observations of the growth rate of atmospheric carbon dioxide concentrations suggests that the reduction of the land residual sink was likely dominated by photosynthesis in 2015 but by respiration in 2016. The six satellite-based products unanimously identified a major photosynthesis reduction of -1.1 ± 0.52 PgC from savannahs in 2015 and 2016, followed by a highly uncertain reduction of -0.22 ± 0.98 PgC from rainforests. Vegetation in the Northern Hemisphere enhanced photosynthesis before and after the peak El Niño, especially in grasslands (0.33 ± 0.13 PgC). The patterns of satellite-based photosynthesis ensemble mean were corroborated by SIF, except in rainforests and South America, where the anomalies of satellite-based photosynthesis products also diverged the most. We found the inter-model variation of photosynthesis estimates was strongly related to the discrepancy between moisture forcings for models. These results highlight the importance of considering multiple photosynthesis proxies when assessing responses to climatic anomalies.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

Impact of the 2015/2016 El Niño on the terrestrial carbon cycle constrained by bottom-up and top-down approaches

Evaluating the response of the land carbon sink to the anomalies in temperature and drought imposed by El Niño events provides insights into the present-day carbon cycle and its climate-driven variability. It is also a necessary step to build confidence in terrestrial ecosystems models' response to the warming and drying stresses expected in the future over many continents, and particularly in the tropics. Here we present an in-depth analysis of the response of the terrestrial carbon cycle to the 2015/2016 El Niño that imposed extreme warming and dry conditions in the tropics and other sensitive regions. First, we provide a synthesis of the spatio-temporal evolution of anomalies in net land–atmosphere CO₂ fluxes estimated by two in situ measurements based on atmospheric inversions and 16 land-surface models (LSMs) from TRENDYv6. Simulated changes in ecosystem productivity, decomposition rates and fire emissions are also investigated. Inversions and LSMs generally agree on the decrease and subsequent recovery of the land sink in response to the onset, peak and demise of El Niño conditions and point to the decreased strength of the land carbon sink: by 0.4–0.7 PgC yr⁻¹ (inversions) and by 1.0 PgC yr⁻¹ (LSMs) during 2015/2016. LSM simulations indicate that a decrease in productivity, rather than increase in respiration, dominated the net biome productivity anomalies in response to ENSO throughout the tropics, mainly associated with prolonged drought conditions.

This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.

Observing carbon cycle-climate feedbacks from space

The impact of human emissions of carbon dioxide and methane on climate is an accepted central concern for current society. It is increasingly evident that atmospheric concentrations of carbon dioxide and methane are not simply a function of emissions but that there are myriad feedbacks forced by changes in climate that affect atmospheric concentrations. If these feedbacks change with changing climate, which is likely, then the effect of the human enterprise on climate will change. Quantifying, understanding, and articulating the feedbacks within the carbon-climate system at the process level are crucial if we are to employ Earth system models to inform effective mitigation regimes that would lead to a stable climate. Recent advances using space-based, more highly resolved measurements of carbon exchange and its component processes-photosynthesis, respiration, and biomass burning-suggest that remote sensing can add key spatial and process resolution to the existing in situ systems needed to provide enhanced understanding and advancements in Earth system models. Information about emissions and feedbacks from a long-term carbon-climate observing system is essential to better stewardship of the planet.

Enhanced response of global wetland methane emissions to the 2015-2016 El Niño-Southern Oscillation event

Wetlands are thought to be the major contributor to interannual variability in the growth rate of atmospheric methane (CH4) with anomalies driven by the influence of the El Niño-Southern Oscillation (ENSO). Yet it remains unclear whether (i) the increase in total global CH4 emissions during El Niño versus La Niña events is from wetlands and (ii) how large the contribution of wetland CH4 emissions is to the interannual variability of atmospheric CH4. We used a terrestrial ecosystem model that includes permafrost and wetland dynamics to estimate CH4 emissions, forced by three separate meteorological reanalyses and one gridded observational climate dataset, to simulate the spatio-temporal dynamics of wetland CH4 emissions from 1980-2016. The simulations show that while wetland CH4 responds with negative annual anomalies during the El Niño events, the instantaneous growth rate of wetland CH4 emissions exhibits complex phase dynamics. We find that wetland CH4 instantaneous growth rates were declined at the onset of the 2015-2016 El Niño event but then increased to a record-high at later stages of the El Niño event (January through May 2016). We also find evidence for a step increase of CH4 emissions by 7.8±1.6 Tg CH4 yr-1 during 2007-2014 compared to the average of 2000-2006 from simulations using meteorological reanalyses, which is equivalent to a ~3.5 ppb yr-1 rise in CH4 concentrations. The step increase is mainly caused by the expansion of wetland area in the tropics (30°S-30°N) due to an enhancement of tropical precipitation as indicated by the suite of the meteorological reanalyses. Our study highlights the role of wetlands, and the complex temporal phasing with ENSO, in driving the variability and trends of atmospheric CH4 concentrations. In addition, the need to account for uncertainty in meteorological forcings is highlighted in addressing the interannual variability and decadal-scale trends of wetland CH4 fluxes.

The Orbiting Carbon Observatory-2 early science investigations of regional carbon dioxide fluxes

NASA's Orbiting Carbon Observatory-2 (OCO-2) mission was motivated by the need to diagnose how the increasing concentration of atmospheric carbon dioxide (CO2) is altering the productivity of the biosphere and the uptake of CO2 by the oceans. Launched on 2 July 2014, OCO-2 provides retrievals of the column-averaged CO2 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 CO2 by the oceans and biosphere.