Investigating bias in the application of curve fitting programs to atmospheric time series

The decomposition of an atmospheric time series into its constituent parts is an essential tool for identifying and isolating variations of interest from a data set, and is widely used to obtain information about sources, sinks and trends in climatically important gases. Such procedures involve fitting appropriate mathematical functions to the data. However, it has been demonstrated that the application of such curve fitting procedures can introduce bias, and thus influence the scientific interpretation of the data sets. We investigate the potential for bias associated with the application of three curve fitting programs, known as HPspline, CCGCRV and STL, using multi-year records of CO2, CH4 and O3 data from three atmospheric monitoring field stations. These three curve fitting programs are widely used within the greenhouse gas measurement community to analyse atmospheric time series, but have not previously been compared extensively. The programs were rigorously tested for their ability to accurately represent the salient features of atmospheric time series, their ability to cope with outliers and gaps in the data, and for sensitivity to the values used for the input parameters needed for each program. We find that the programs can produce significantly different curve fits, and these curve fits can be dependent on the input parameters selected. There are notable differences between the results produced by the three programs for many of the decomposed components of the time series, such as the representation of seasonal cycle characteristics and the long-term (multi-year) growth rate. The programs also vary significantly in their response to gaps and outliers in the time series. Overall, we found that none of the three programs were superior, and that each program had its strengths and weaknesses. Thus, we provide a list of recommendations on the appropriate use of these three curve fitting programs for certain types of data sets, and for certain types of analyses and applications. In addition, we recommend that sensitivity tests are performed in any study using curve fitting programs, to ensure that results are not unduly influenced by the input smoothing parameters chosen. Our findings also have implications for previous studies that have relied on a single curve fitting program to interpret atmospheric time series measurements. This is demonstrated by using two other curve fitting programs to replicate work in Piao et al. (2008) on zero-crossing analyses of atmospheric CO2 seasonal cycles to investigate terrestrial biosphere changes. We highlight the importance of using more than one program, to ensure results are consistent, reproducible, and free from bias

New applications of continuous atmospheric O2 measurements: meridional transects across the Atlantic Ocean, and improved quantification of fossil fuel‐derived CO2

High precision, continuous measurements of atmospheric O2 and CO2 are a valuable tool for gaining insight into carbon cycle processes, and for separating land biospheric, oceanic and fossil fuel fluxes of CO2. This thesis presents a new atmospheric O2 and CO2 measurement system that has been deployed on board a commercial container ship, travelling continuously between Germany (~55°N) and Argentina (~35°S). These data are the first ongoing atmospheric O2 measurements across the Atlantic Ocean, closing a gap in the global atmospheric O2 network. The Atlantic meridional transects of atmospheric O2 and CO2 display latitudinally‐varying seasonality. The annual mean latitudinal gradient in APO (Atmospheric Potential Oxygen; a tracer derived from O2 and CO2 measurements) does not show a pronounced bulge at the equator, in contrast to observations across the Pacific Ocean. Atmospheric O2 and CO2 measurements from Norfolk, UK are used to demonstrate a novel method for quantifying fossil fuel derived CO2 (ffCO2), using APO data. This APO ffCO2 quantification method is more precise than the frequently‐used CO tracer method, owing to a smaller range of APO:CO2 fossil fuel emission ratios compared to the CO:CO2 range. A sensitivity analysis of the fossil fuel emission ratios also indicates that the APO method is very likely more accurate than the CO method, and can therefore be used independently of 14CO2 measurements (unlike the CO method), which are costly and highly unreliable in many UK regions, owing to nuclear power plant influences. These new applications of atmospheric O2 measurements have significant future potential. The shipboard data can be used to test and improve global climate model estimates of meridional oceanic heat and carbon transport in the Atlantic. Using APO to quantify ffCO2 has significant policy relevance, with the potential to provide more accurate and more precise top‐down verification of fossil fuel emissions

In situ measurements of atmospheric O2 and CO2 reveal an unexpected O2 signal over the tropical Atlantic Ocean

We present the first meridional transects of atmospheric O2 and CO2 over the Atlantic Ocean. We combine these measurements into the tracer atmospheric potential oxygen (APO), which is a measure of the oceanic contribution to atmospheric O2 variations. Our new in situ measurement system, deployed on board a commercial container ship during 2015, performs as well as or better than existing similar measurement systems. The data show small short-term variability (hours to days), a step-change corresponding to the position of the Intertropical Convergence Zone (ITCZ), and seasonal cycles that vary with latitude. In contrast to data from the Pacific Ocean and to previous modeling studies, our Atlantic Ocean APO data show no significant bulge in the tropics. This difference cannot be accounted for by interannual variability in the position of the ITCZ or the Atlantic Meridional Mode Index and appears to be a persistent feature of the Atlantic Ocean system. Modeled APO using the TM3 atmospheric transport model does exhibit a significant bulge over the Atlantic and overestimates the interhemispheric gradient in APO over the Atlantic Ocean. These results indicate that either there are inaccuracies in the oceanic flux data products in the equatorial Atlantic Ocean region, or that there are atmospheric transport inaccuracies in the model, or a combination of both. Our shipboard O2 and CO2 measurements are ongoing and will reveal the long-term nature of equatorial APO outgassing over the Atlantic as more data become available

Diurnal variability of atmospheric O-2, CO2, and their exchange ratio above a boreal forest in southern Finland

The exchange ratio (ER) between atmospheric O(2 )and CO2 is a useful tracer for better understanding the carbon budget on global and local scales. The variability of ER (in mol O(2 )per mol CO2) between terrestrial ecosystems is not well known, and there is no consensus on how to derive the ER signal of an ecosystem, as there are different approaches available, either based on concentration (ERatmos) or flux measurements (ERforest). In this study we measured atmospheric O-2 and CO2 concentrations at two heights (23 and 125 m) above the boreal forest in Hyytiala, Finland. Such measurements of O-2 are unique and enable us to potentially identify which forest carbon loss and production mechanisms dominate over various hours of the day. We found that the ERatmos signal at 23 m not only represents the diurnal cycle of the forest exchange but also includes other factors, including entrainment of air masses in the atmospheric boundary layer before midday, with different thermodynamic and atmospheric composition characteristics. To derive ERforest, we infer O(2 )fluxes using multiple theoretical and observation-based micro-meteorological formulations to determine the most suitable approach. Our resulting ERforest shows a distinct difference in behaviour between daytime (0.92 +/- 0.17 mol mol(-1)) and nighttime (1.03 +/- 0.05 mol mol(-1)). These insights demonstrate the diurnal variability of different ER signals above a boreal forest, and we also confirmed that the signals of ERatmos and ERforest cannot be used interchangeably. Therefore, we recommend measurements on multiple vertical levels to derive O-2 and CO2 fluxes for the ERforest signal instead of a single level time series of the concentrations for the ERatmos signal. We show that ERforest can be further split into specific signals for respiration (1.03 +/-; 0.05 mol mol-1) and photosynthesis (0.96 +/- 0.12 molmol(-1)). This estimation allows us to separate the net ecosystem exchange (NEE) into gross primary production (GPP) and total ecosystem respiration (TER), giving comparable results to the more commonly used eddy covariance approach. Our study shows the potential of using atmospheric O-2 as an alternative and complementary method to gain new insights into the different CO2 signals that contribute to the forest carbon budget.Peer reviewe

Novel quantification of regional fossil fuel CO2 reductions during COVID-19 lockdowns using atmospheric oxygen measurements

It is not currently possible to quantify regional-scale fossil fuel carbon dioxide (ffCO2) emissions with high accuracy in near real time. Existing atmospheric methods for separating ffCO2 from large natural carbon dioxide variations are constrained by sampling limitations, so that estimates of regional changes in ffCO2 emissions, such as those occurring in response to coronavirus disease 2019 (COVID-19) lockdowns, rely on indirect activity data. We present a method for quantifying regional signals of ffCO2 based on continuous atmospheric measurements of oxygen and carbon dioxide combined into the tracer "atmospheric potential oxygen"(APO). We detect and quantify ffCO2 reductions during 2020-2021 caused by the two U.K. COVID-19 lockdowns individually using APO data from Weybourne Atmospheric Observatory in the United Kingdom and a machine learning algorithm. Our APO-based assessment has near-real-time potential and provides high-frequency information that is in good agreement with the spread of ffCO2 emissions reductions from three independent lower-frequency U.K. estimates

A surface ocean CO2 reference network, SOCONET and associated marine boundary layer CO2 measurements

The Surface Ocean CO2 NETwork (SOCONET) and atmospheric Marine Boundary Layer (MBL) CO2 measurements from ships and buoys focus on the operational aspects of measurements of CO2 in both the ocean surface and atmospheric MBLs. The goal is to provide accurate pCO2 data to within 2 micro atmosphere (μatm) for surface ocean and 0.2 parts per million (ppm) for MBL measurements following rigorous best practices, calibration and intercomparison procedures. Platforms and data will be tracked in near real-time and final quality-controlled data will be provided to the community within a year. The network, involving partners worldwide, will aid in production of important products such as maps of monthly resolved surface ocean CO2 and air-sea CO2 flux measurements. These products and other derivatives using surface ocean and MBL CO2 data, such as surface ocean pH maps and MBL CO2 maps, will be of high value for policy assessments and socio-economic decisions regarding the role of the ocean in sequestering anthropogenic CO2 and how this uptake is impacting ocean health by ocean acidification. SOCONET has an open ocean emphasis but will work with regional (coastal) networks. It will liaise with intergovernmental science organizations such as Global Atmosphere Watch (GAW), and the joint committee for and ocean and marine meteorology (JCOMM). Here we describe the details of this emerging network and its proposed operations and practices

Rising atmospheric methane: 2007-2014 growth and isotopic shift

From 2007 to 2013, the globally averaged mole fraction of methane in the atmosphere increased by 5.7±1.2ppb yr$^{-1}$. Simultaneously, $\delta^{13}$C$_\text{CH4}$ (a measure of the $^{13}$C/$^{12}$C isotope ratio in methane) has shifted to significantly more negative values since 2007. Growth was extreme in 2014, at 12.5±0.4ppb, with a further shift to more negative values being observed at most latitudes. The isotopic evidence presented here suggests that the methane rise was dominated by significant increases in biogenic methane emissions, particularly in the tropics, for example, from expansion of tropical wetlands in years with strongly positive rainfall anomalies or emissions from increased agricultural sources such as ruminants and rice paddies. Changes in the removal rate of methane by the OH radical have not been seen in other tracers of atmospheric chemistry and do not appear to explain short-term variations in methane. Fossil fuel emissions may also have grown, but the sustained shift to more $^{13}$C-depleted values and its significant interannual variability, and the tropical and Southern Hemisphere loci of post-2007 growth, both indicate that fossil fuel emissions have not been the dominant factor driving the increase. A major cause of increased tropical wetland and tropical agricultural methane emissions, the likely major contributors to growth, may be their responses to meteorological change.This work was supported by the UK Natural Environment Research Council projects NE/N016211/1 The Global Methane Budget, NE/M005836/1 Methane at the edge, NE/K006045/1 The Southern Methane Anomaly and NE/I028874/1 MAMM. We thank the UK Meteorological Office for flask collection and hosting the continuous measurement at Ascension, the Ascension Island Government for essential support, and Thumeka Mkololo for flask collection in Cape Tow

Global Carbon Budget 2018

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use and land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2008–2017), EFF was 9.4±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.7±0.02 GtC yr−1, SOCEAN 2.4±0.5 GtC yr−1, and SLAND 3.2±0.8 GtC yr−1, with a budget imbalance BIM of 0.5 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr−1. Also for 2017, ELUC was 1.4±0.7 GtC yr−1, GATM was 4.6±0.2 GtC yr−1, SOCEAN was 2.5±0.5 GtC yr−1, and SLAND was 3.8±0.8 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018

Global Carbon Budget 2018

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use and land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2008–2017), EFF was 9.4±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.7±0.02 GtC yr−1, SOCEAN 2.4±0.5 GtC yr−1, and SLAND 3.2±0.8 GtC yr−1, with a budget imbalance BIM of 0.5 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr−1. Also for 2017, ELUC was 1.4±0.7 GtC yr−1, GATM was 4.6±0.2 GtC yr−1, SOCEAN was 2.5±0.5 GtC yr−1, and SLAND was 3.8±0.8 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018