Variability of the Global Ocean Carbon Sink (1998 through 2011)

In this thesis a newly developed 2–step neural network approach is used to reconstruct basin–wide monthly maps of the sea surface partial pressure of CO2 (pCO2) at a resolution of 1��1� for both the Atlantic Ocean from 1998 through 2007 and the global ocean from 1998 through 2011. From those, air–sea CO2 flux maps are computed using a standard gas exchange parameterization and high–resolution wind speeds. Observations form the basis of the studies conducted in this thesis. The neural network estimates benefit from a continuous improvement of the observations, i.e., the Surface Ocean CO2 Atlas (SOCAT) database. Additionally, bottle samples were collected along the UK–Caribbean line to investigate the variability of the sea surface pCO2 and its drivers. The neural network derived pCO2 estimates fit the observed pCO2 data with a root mean square error (RMSE) of about 10 �atm in the Atlantic Ocean from 1998 through 2007 and about 12 �atm in the global ocean from 1998 through 2011, with almost no bias in both studies. A check against independent pCO2 data reveals a larger RMSE, in particular in regions with strong pCO2 variability and gradients. Temporal mean contemporary flux estimates for the Atlantic Ocean (–0.45�0.15 Pg C � y

Drive and Motion Design In Material Handling Equipment

Drives account in many cases up to one third of the costs of material handling equipment. This fact justifies a closer look to important drive and motion issues. Typical design criteria for drives are energy and power consumption, wear, heat and noise generation. Engineering design activities start with the generation of the system configuration, that is to make appropriate topological decisions where to locate the drives in the equipment structure. These decisions define to a great extent the functional quality of the mechanical structure and the distribution of forces in the power train. For early design stages an elasto-kinetic model is developed, which is later enhanced by a more detailed simulation model. Another important issue is the definition of high quality motion profiles defined by selected velocity-time relationships

The 2015-2016 El Nino and the Response of the Carbon Cycle: Findings from NASA's OCO-2 Mission

The El Nino Southern Oscillation (ENSO) is the most important mode of tropical climate variability on interannual to decadal time scales. Correlations between atmospheric CO2 growth rate and ENSO activity are relatively well known but the magnitude of this correlation, the contribution from tropical marine vs. terrestrial flux components, and the causal mechanisms, are poorly constrained in space and time. The launch of NASA's Orbiting Carbon Observatory-2 (OCO-2) mission in July 2014 was rather timely given the development of strong ENSO conditions over the tropical Pacific Ocean in 2015-2016. In this presentation, we will discuss how the high-density observations from OCO-2 provided us with a novel dataset to resolve the linkages between El Nino and atmospheric CO2. Along with information from in situ observations of CO2 from NOAA's Tropical Atmosphere Ocean (TAO) project and atmospheric CO2 from the Scripps CO2 Program, and other remote-sensing missions, we are able to piece together the time dependent response of atmospheric CO2 concentrations over the Tropics. Our findings confirm the hypothesis from studies following the 1997-1998 El Nino event that an early reduction in CO2 outgassing from the tropical Pacific Ocean is later reversed by enhanced net CO2 emissions from the terrestrial biosphere. This implies that a component of the interannual variability (IAV) in the growth rate of atmospheric CO2, which has typically been used to constrain the climate sensitivity of tropical land carbon fluxes, is strongly influenced and modified by ocean fluxes during the early phase of the ENSO event. Our analyses shed further light on the understanding of the marine vs. terrestrial partitioning of tropical carbon fluxes during El Nino events, their relative contributions to the global atmospheric CO2 growth rate, and provide clues about the sensitivity of the carbon cycle to climate forcing on interannual time scales

An assessment of the Atlantic and Arctic sea–air CO2 fluxes, 1990–2009

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biogeosciences 10 (2013): 607-627, doi:10.5194/bg-10-607-2013.The Atlantic and Arctic Oceans are critical components of the global carbon cycle. Here we quantify the net sea–air CO2 flux, for the first time, across different methodologies for consistent time and space scales for the Atlantic and Arctic basins. We present the long-term mean, seasonal cycle, interannual variability and trends in sea–air CO2 flux for the period 1990 to 2009, and assign an uncertainty to each. We use regional cuts from global observations and modeling products, specifically a pCO2-based CO2 flux climatology, flux estimates from the inversion of oceanic and atmospheric data, and results from six ocean biogeochemical models. Additionally, we use basin-wide flux estimates from surface ocean pCO2 observations based on two distinct methodologies. Our estimate of the contemporary sea–air flux of CO2 (sum of anthropogenic and natural components) by the Atlantic between 40° S and 79° N is −0.49 ± 0.05 Pg C yr−1, and by the Arctic it is −0.12 ± 0.06 Pg C yr−1, leading to a combined sea–air flux of −0.61 ± 0.06 Pg C yr−1 for the two decades (negative reflects ocean uptake). We do find broad agreement amongst methodologies with respect to the seasonal cycle in the subtropics of both hemispheres, but not elsewhere. Agreement with respect to detailed signals of interannual variability is poor, and correlations to the North Atlantic Oscillation are weaker in the North Atlantic and Arctic than in the equatorial region and southern subtropics. Linear trends for 1995 to 2009 indicate increased uptake and generally correspond between methodologies in the North Atlantic, but there is disagreement amongst methodologies in the equatorial region and southern subtropics.U. Schuster has been supported by EU grants IP 511176-2 (CARBOOCEAN), 212196 (COCOS), and 264879 (CARBOCHANGE), and UK NERC grant NE/H017046/1 (UKOARP). G. A. McKinley and A. Fay thank NASA for support (NNX08AR68G, NNX11AF53G). P. Landsch¨utzer has been supported by EU grant 238366 (GREENCYCLESII). N. Metzl acknowledges the French national funding program LEFE/INSU. Support for N. Gruber has been provided by EU grants 264879 (CARBOCHANGE) and 283080 (GEO-CARBON) S. Doney acknowledges support from NOAA (NOAA-NA07OAR4310098). T. Takahashi is supported by NOAA (NAO80AR4320754)

Global Carbon Budget 2015

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere 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 a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (E-FF) are based on energy statistics and cement production data, while emissions from land-use change (E-LUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (G(ATM)) is computed from the annual changes in concentration. The mean ocean CO2 sink (S-OCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in S-OCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (S-LAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen-carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as +/- 1 sigma, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (20052014), E-FF was 9.0 +/- 0.5 GtC yr(-1) E-LUC was 0.9 +/- 0.5 GtC yr(-1), GATM was 4.4 +/- 0.1 GtC yr(-1), S-OCEAN was 2.6 +/- 0.5 GtC yr(-1), and S LAND was 3.0 +/- 0.8 GtC yr(-1). For the year 2014 alone, E FF grew to 9.8 +/- 0.5 GtC yr(-1), 0.6% above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2% yr(-1) that took place during 2005-2014. Also, for 2014, E-LUC was 1.1 +/- 0.5 GtC yr(-1), G(ATM) was 3.9 +/- 0.2 GtC yr(-1), S-OCEAN was 2.9 +/- 0.5 GtC yr(-1), and S-LAND was 4.1 +/- 0.9 GtC yr(-1). G(ATM) was lower in 2014 compared to the past decade (2005-2014), reflecting a larger S-LAND for that year. The global atmospheric CO2 concentration reached 397.15 +/- 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in E-FF will be near or slightly below zero, with a projection of 0.6 [ range of 1.6 to C 0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of E-FF and assumed constant E LUC for 2015, cumulative emissions of CO2 will reach about 555 +/- 55 GtC (2035 +/- 205 GtCO(2)) for 1870-2015, about 75% from E FF and 25% from E LUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quere et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi: 10.3334/CDIAC/GCP_2015)

Assessing recent trends in high-latitude Southern Hemisphere surface climate

Understanding the causes of recent climatic trends and variability in the high-latitude Southern Hemisphere is hampered by a short instrumental record. Here, we analyse recent atmosphere, surface ocean and sea-ice observations in this region and assess their trends in the context of palaeoclimate records and climate model simulations. Over the 36-year satellite era, significant linear trends in annual mean sea-ice extent, surface temperature and sea-level pressure are superimposed on large interannual to decadal variability. However, most observed trends are not unusual when compared with Antarctic paleoclimate records of the past two centuries. With the exception of the positive trend in the Southern Annular Mode, climate model simulations that include anthropogenic forcing are not compatible with the observed trends. This suggests that natural variability likely overwhelms the forced response in the observations, but the models may not fully represent this natural variability or may overestimate the magnitude of the forced response

A novel sea surface pCO2-product for the global coastal ocean resolving trends over the 1982–2020 period

In recent years, advancements in machine learning based interpolation methods have enabled the production of high-resolution maps of sea surface partial pressure of CO2 (pCO2) derived from observations extracted from databases such as the Surface Ocean CO2 Atlas (SOCAT). These pCO2-products now allow quantifying the oceanic air-sea CO2 exchange based on observations. However, most of them do not yet explicitly include the coastal ocean. Instead, they simply extend the open ocean values onto the nearshore shallow waters, or their spatial resolution is simply so coarse that they do not accurately capture the highly heterogeneous spatiotemporal pCO2 dynamics of coastal zones. Until today, only one global pCO2-product was specifically designed for the coastal ocean (Laruelle et al. 2017). This product however has shortcomings because it only provides a climatology covering a relatively short period (1998–2015), thus hindering its application to the evaluation of the interannual variability and the long-term trends of the coastal air-sea CO2 exchange, a temporal evolution that is still poorly understood and highly debated. Here we aim at closing this knowledge gap and update the coastal product of Laruelle et al. (2017) to investigate the longest global monthly time series available for the coastal ocean from 1982 to 2020. The method remains based on a 2-step Self Organizing Maps and Feed Forward Network method adapted for coastal regions, but we include additional environmental predictors and use a larger pool of training and validation data with ~ 18 million direct observations extracted from the latest release of the SOCAT database. Our study reveals that the coastal ocean has been acting as an atmospheric CO2 sink of -0.4 Pg C yr-1 (-0.2 Pg C yr-1 with a narrower coastal domain) on average since 1982, and the intensity of this sink has increased at a rate of 0.1 Pg C yr-1 decade-1 (0.03 Pg C yr-1 decade-1 with a narrower coastal domain) over time. Our results also show that the temporal trend in the air-sea pCO2 gradient plays a significant role in the decadal evolution of the coastal CO2 sink, along with wind speed and sea-ice coverage changes that can also play an important role in some regions, particularly at high latitudes. This new reconstructed coastal pCO2-product (Roobaert et al. 2023, https://www.ncei.noaa.gov/archive/accession/0279118) allows establishing regional carbon budgets requiring high-resolution coastal flux estimates and provides new constraints for closing the global carbon cycle.info:eu-repo/semantics/publishe

Global high-resolution monthly pCO(2) climatology for the coastal ocean derived from neural network interpolation

In spite of the recent strong increase in the number of measurements of the partial pressure of CO2 in the surface ocean (pCO(2)), the air-sea CO2 balance of the continental shelf seas remains poorly quantified. This is a consequence of these regions remaining strongly under-sampled in both time and space and of surface p CO2 exhibiting much higher temporal and spatial variability in these regions compared to the open ocean. Here, we use a modified version of a two-step artificial neural network method (SOM-FFN; Landschutzer et al., 2013) to interpolate the p CO2 data along the continental margins with a spatial resolution of 0.25 ffi and with monthly resolution from 1998 to 2015. The most important modifications compared to the original SOM-FFN method are (i) the much higher spatial resolution and (ii) the inclusion of sea ice and wind speed as predictors of p CO2. The SOM-FFN is first trained with p CO2 measurements extracted from the SO-CATv4 database. Then, the validity of our interpolation, in both space and time, is assessed by comparing the generated pCO(2) field with independent data extracted from the LD-VEO2015 database. The new coastal pCO(2) product confirms a previously suggested general meridional trend of the annual mean pCO(2) in all the continental shelves with high values in the tropics and dropping to values beneath those of the atmosphere at higher latitudes. The monthly resolution of our data product permits us to reveal significant differences in the seasonality of pCO(2) across the ocean basins. The shelves of the western and northern Pacific, as well as the shelves in the temperate northern Atlantic, display particularly pronounced seasonal variations in pCO(2); while the shelves in the south-eastern Atlantic and in the southern Pacific reveal a much smaller seasonality. The calculation of temperature normalized pCO(2) for several latitudes in different oceanic basins confirms that the seasonality in shelf pCO(2) cannot solely be explained by temperature-induced changes in solubility but are also the result of seasonal changes in circulation, mixing and biological productivity. Our results also reveal that the amplitudes of both thermal and nonthermal seasonal variations in pCO(2) are significantly larger at high latitudes. Finally, because this product's spatial extent includes parts of the open ocean as well, it can be readily merged with existing global open-ocean products to produce a true global perspective of the spatial and temporal variability of surface ocean pCO(2)

Surface Ocean CO2 Atlas (SOCAT) gridded data products

As a response to public demand for a well-documented, quality controlled, publically available, global surface ocean carbon dioxide (CO2) data set, the international marine carbon science community developed the Surface Ocean CO2 Atlas (SOCAT). The first SOCAT product is a collection of 6.3 million quality controlled surface CO2 data from the global oceans and coastal seas, spanning four decades (1968–2007). The SOCAT gridded data presented here is the second data product to come from the SOCAT project. Recognizing that some groups may have trouble working with millions of measurements, the SOCAT gridded product was generated to provide a robust, regularly spaced CO2 fugacity (fCO2) product with minimal spatial and temporal interpolation, which should be easier to work with for many applications. Gridded SOCAT is rich with information that has not been fully explored yet (e.g., regional differences in the seasonal cycles), but also contains biases and limitations that the user needs to recognize and address (e.g., local influences on values in some coastal regions)