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The analysis of observed atmospheric trace-gas mole fractions to infer surface sources and sinks of chemical species relies heavily on simulated atmospheric transport. The chemical transport models (CTMs) used in flux-inversion models are commonly configured to reproduce the atmospheric transport of a general circulation model (GCM) as closely as possible. CTMs generally have the dual advantages of computational efficiency and improved tracer conservation compared to their parent GCMs, but they usually simplify the representations of important processes. This is especially the case for high-frequency vertical motions associated with diffusion and convection. Using common-flux experiments, we quantify the importance of parameterized vertical processes for explaining systematic differences in tracer transport between two commonly used CTMs. We find that differences in modeled column-average CO2 are strongly correlated with the differences in the models' convection. The parameterization of diffusion is more important near the surface due to its role in representing planetary-boundary-layer (PBL) mixing. Accordingly, simulated near-surface in situ measurements are more strongly impacted by this process than are simulated total-column averages. Both diffusive and convective vertical mixing tend to ventilate the lower atmosphere, so near-surface measurements may only constrain the net vertical mixing and not the balance between these two processes. Remote-sensing-based retrievals of total-column CO2, with their increased sensitivity to convection, may provide important new constraints on parameterized vertical motions.

Accurate accounting of emissions and removals of CO2 is critical for the planning and verification of emission reduction targets in support of the Paris Agreement. Here, we present a pilot dataset of country-specific net carbon exchange (NCE; fossil plus terrestrial ecosystem fluxes) and terrestrial carbon stock changes aimed at informing countries' carbon budgets. These estimates are based on “top-down” NCE outputs from the v10 Orbiting Carbon Observatory (OCO-2) modeling intercomparison project (MIP), wherein an ensemble of inverse modeling groups conducted standardized experiments assimilating OCO-2 column-averaged dry-air mole fraction (XCO2) retrievals (ACOS v10), in situ CO2 measurements or combinations of these data. The v10 OCO-2 MIP NCE estimates are combined with “bottom-up” estimates of fossil fuel emissions and lateral carbon fluxes to estimate changes in terrestrial carbon stocks, which are impacted by anthropogenic and natural drivers. These flux and stock change estimates are reported annually (2015–2020) as both a global 1∘ × 1∘ gridded dataset and a country-level dataset and are available for download from the Committee on Earth Observation Satellites' (CEOS) website: https://doi.org/10.48588/npf6-sw92 (Byrne et al., 2022). Across the v10 OCO-2 MIP experiments, we obtain increases in the ensemble median terrestrial carbon stocks of 3.29–4.58 Pg CO2 yr−1 (0.90–1.25 Pg C yr−1). This is a result of broad increases in terrestrial carbon stocks across the northern extratropics, while the tropics generally have stock losses but with considerable regional variability and differences between v10 OCO-2 MIP experiments. We discuss the state of the science for tracking emissions and removals using top-down methods, including current limitations and future developments towards top-down monitoring and verification systems.

We evaluate terrestrial net ecosystem-atmosphere exchange (NEE) of CO2 from nine global inversion systems that inferred fluxes from four CO2 observational sources. We use 98 flights in the central ...

The Orbiting Carbon Observatory 2 (OCO-2) satellite has been provided information to estimate carbon dioxide (CO2) fluxes at global and regional scales since 2014 through the combination of CO2 retrievals with top-down atmospheric inversion methods. Column average CO2 dry air mole fraction retrievals has been constantly improved. A bias correction has been applied in the OCO-2 version 9 retrievals compared to the previous OCO-2 version 7r improving data accuracy and coverage. We study an ensemble of ten atmospheric inversions all characterized by different transport models, data assimilation algorithm and prior fluxes using first OCO-2 v7 in 2015-2016 and then OCO-2 version 9 land observations for the longer period 2015- 2018. Inversions assimilating in situ (IS) measurements have been also used to provide a baseline against which to compare the satellite-driven results. The times series at different scales (going from global to regional scales) of the models emissions are analyzed and compared to each experiments using either OCO-2 or IS data. We then evaluate the inversion ensemble based on dataset from TCCON, aircraft, and in-situ observations, all independent from assimilated data. While we find a similar constraint of global total carbon emissions between the ensemble spread using IS and both OCO-2 retrievals, differences between the two retrieval versions appear over regional scales and particularly in tropical Africa. A difference in the carbon budget between v7 and v9 is found over this region which seems to show the impact of corrections applied in retrievals. However, the lack of data in the tropics limits our conclusions and the estimation of carbon emissions over tropical Africa require further analysis.

The ability of current global models to simulate the transport of CO2 by mid-latitude, synoptic-scale weather systems (i.e. CO2 weather) is important for inverse estimates of ...

International audience; We use 148 airborne vertical profiles of CO2 for frontal cases from the summer 2016 Atmospheric Carbon and Transport—America (ACT America) campaign to evaluate the skill of 10 global CO2 in situ inversion models from the version 7 Orbiting Carbon Observatory-2 (OCO 2) Model Intercomparison Project (MIP). Model errors (model posterior—observed CO2 dry air mole fractions) were categorized by region (Mid Atlantic, Midwest, and South), frontal sector (warm or cold), and transport model (predominantly Tracer Model 5 (TM5) and Goddard Earth Observing System—Chemistry [GEOS Chem]). All inversions assimilated the same CO2 observations. Overall, the median inversion profiles reproduce the general structures of the observations (enhanced/depleted low level CO2 in warm/cold sectors), but 1) they underestimate the magnitude of the warm/cold sector mole fraction difference, and 2) the spread among individual inversions can be quite large (>5 ppm). Uniquely in the Mid Atlantic, inversion biases segregated according to atmospheric transport model, where TM5 inversions biases were -3 to -4 ppm in warm sectors, while those of GEOS Chem were +2 to +3 ppm in cold sectors. The large spread among the mean posterior CO2 profiles is not explained by the different atmospheric transport models. These results show that the inversion systems themselves are the dominant cause of this spread, and that the aircraft campaign data are clearly able to identify these large biases. Future controlled experiments should identify which inversions best reproduce mid latitude CO2 mole fractions, and how inversion system components are linked to system performance.

Attention to emotional stimuli has been associated with psychological health among adults and youth. In this study, we examined 2 putative functional psychophysiological correlates of attention to emotional information in a community sample of 135 youth (Mage^12 years, 7 months; SDage^1 year, 1 month; 50% girls). After measuring resting respiratory sinus arrhythmia (RSA), participants completed a 1,500 ms emotional faces dot probe task with eye tracking. We examined pupil dilation during angry, sad, and happy trials and predicted that lower resting RSA and greater pupil dilation would be associated with relatively greater attention to negative stimuli. Results partially confirmed our hypothesis. Lower resting RSA was associated with relatively greater attention to sad faces. Lower resting RSA was also associated with relatively greater attention to angry faces when pupil dilation was lower. RSA may be an important functional correlate of attention that should be explored further in future research.Keywords: adolescents; attention bias; vagal tone; pupil dilation; respiratory sinus arrhythmia; heart rate variabilityAttention to emotional information has been associated with psychological health in both youth and adults. For example, biased attention toward sad stimuli has been associated with depression, whereas biased attention toward angry stimuli has been associated with anxiety (Mathews & MacLeod, 2005; Mogg & Bradley, 2005). Biased attentional patterns may be an important marker of future psychopathology (e.g., Joormann, Talbot, & Gotlib, 2007); thus, understanding them has important implications for the assessment, prevention, and treatment of psychopathology. One way to better understand these attentional patterns is to examine whether they are associated with functional physiological processes involved in emotion. Surprisingly, little research has been devoted to this topic, especially among youth. This study examines two possible psychophysiological correlates of attention to emotional information among youth: pupil dilation and respiratory sinus arrhythmia (RSA).RESEARCH ON ATTENTION TO EMOTIONAL STIMULI IN ADULTS AND YOUTHDifferent tasks have been used to evaluate possible attention biases, with the two most common being an emotional Stroop task and an attentional probe method (Mathews & MacLeod, 2005). Emotional Stroop tasks compare the response latency of naming the colors of emotionally valenced words compared to neutral ones. Biases are inferred when color naming takes longer on emotional words compared to neutral words. Attentional probe methods briefly present stimuli (typically emotional and neutral words) on a computer screen and then assess how rapidly participants can find a probe that replaces one of the stimuli. Individuals respond faster to a probe that is presented in an attended rather than unattended area of a display; thus, attention is inferred based on reaction time (RT; Mathews & MacLeod, 2005; Mogg & Bradley, 2005).ADULTSResearch examining clinically depressed or anxious adults has generated considerable evidence, suggesting that both of these disorders are associated with biased attention related to emotional information (Mathews & MacLeod, 2005; Mogg & Bradley, 2005). Specifically, depressive disorders have generally been associated with attention to sad stimuli, whereas anxiety disorders have been associated with a bias toward or away from threat or angry stimuli, depending on the amount of time the stimulus is presented (Mathews & MacLeod, 2005).Interestingly, the bias toward sad stimuli often seen with depressive disorders is only present when the stimulus is presented for a fairly long time (1,000 ms or longer; Mathews & MacLeod, 2005). In their review, Gotlib and Joormann (2010) concluded that although depressed individuals may not automatically orient their attention toward negative information, once this negative information has become the focus of their attention, they may have greater difficulty disengaging from it. …

This study analyzes seasonal and spatial patterns of column carbon dioxide (CO2) over North America, calculated from aircraft and tall tower measurements from the NOAA Global Greenhouse Gas Reference Network from 2004 to 2014. Consistent with expectations, gradients between the eight regions studied are larger below 2 km than above 5 km. The 11-year mean CO2 dry mole fraction (XCO2) in the column below ∼ 330 hPa ( ∼ 8 km above sea level) from NOAA's CO2 data assimilation model, CarbonTracker (CT2015), demonstrates good agreement with those calculated from calibrated measurements on aircraft and towers. Total column XCO2 was attained by combining modeled CO2 above 330 hPa from CT2015 with the measurements. We find large spatial gradients of total column XCO2 from June to August, with north and northeast regions having ∼ 3 ppm stronger summer drawdown (peak-to-valley amplitude in seasonal cycle) than the south and southwest regions. The long-term averaged spatial gradients of total column XCO2 across North America show a smooth pattern that mainly reflects the large-scale circulation. We have conducted a CarbonTracker experiment to investigate the impact of Eurasian long-range transport. The result suggests that the large summertime Eurasian boreal flux contributes about half of the north–south column XCO2 gradient across North America. Our results confirm that continental-scale total column XCO2 gradients simulated by CarbonTracker are realistic and can be used to evaluate the credibility of some spatial patterns from satellite retrievals, such as the long-term average of growing-season spatial patterns from satellite retrievals reported for Europe which show a larger spatial difference ( ∼ 6 ppm) and scattered hot spots.

The Orbiting Carbon Observatory-2 has been on orbit since 2014, and its global coverage holds the potential to reveal new information about the carbon cycle through the use of top-down atmospheric inversion methods combined with column average CO2 retrievals. We employ a large ensemble of atmospheric inversions utilizing different transport models, data assimilation techniques and prior flux distributions in order to quantify the satellite-informed fluxes from OCO-2 Version 7r land observations and their uncertainties at continental scales. Additionally, we use in situ measurements to provide a baseline against which to compare the satellite-constrained results. We find that within ensemble spread, in situ observations and satellite retrievals constrain a similar global total carbon sink of 3.7 ± 0.5 PgC, and 1.5 ± 0.6 PgC per year for global land, for the 2015–2016 annual mean. This agreement breaks down on smaller regions, and we discuss the differences between the experiments. Of particular interest is the difference between the different assimilation constraints in the tropics, with the largest differences occurring in tropical Africa, which could be an indication of the global perturbation from the 2015–2016 El Niño. Evaluation of posterior concentrations using TCCON and aircraft observations gives some limited insight into the quality of the different assimilation constraints, but the lack of such data in the tropics inhibits our ability to make strong conclusions there.

Despite its importance to the climate system, the ocean meridional heat transport is still poorly quantified. We identify a strong link between the northern hemisphere deficit in atmospheric potential oxygen (APO = O $$_2$$ + 1.1 $$\times$$ CO $$_2$$ ) and the asymmetry in meridional heat transport between northern and southern hemispheres. The recent aircraft observations from the HIPPO campaign reveal a northern APO deficit in the tropospheric column of $$-$$ 10.4 $$\pm$$ 1.0 per meg, double the value at the surface and more representative of large-scale air–sea fluxes. The global northward ocean heat transport asymmetry necessary to explain the observed APO deficit is about 0.7–1.1 PW, which corresponds to the upper range of estimates from hydrographic sections and atmospheric reanalyses.

We show that transport differences between two commonly used global chemical transport models, GEOS‐Chem and TM5, lead to systematic space‐time differences in modeled distributions of carbon dioxide and sulfur hexafluoride. The distribution of differences suggests inconsistencies between the transport simulated by the models, most likely due to the representation of vertical motion. We further demonstrate that these transport differences result in systematic differences in surface CO2 flux estimated by a collection of global atmospheric inverse models using TM5 and GEOS‐Chem and constrained by in situ and satellite observations. While the impact on inferred surface fluxes is most easily illustrated in the magnitude of the seasonal cycle of surface CO2 exchange, it is the annual carbon budgets that are particularly relevant for carbon cycle science and policy. We show that inverse model flux estimates for large zonal bands can have systematic biases of up to 1.7 PgC/year due to large‐scale transport uncertainty. These uncertainties will propagate directly into analysis of the annual meridional CO2 flux gradient between the tropics and northern midlatitudes, a key metric for understanding the location, and more importantly the processes, responsible for the annual global carbon sink. The research suggests that variability among transport models remains the largest source of uncertainty across global flux inversion systems and highlights the importance both of using model ensembles and of using independent constraints to evaluate simulated transport., Key Points There are systematic differences in transport between two commonly used chemical transport models, TM5 and GEOS‐ChemThese systematic differences lead to significant and meaningful posterior flux uncertainties in atmospheric CO2 flux inversions

Observation Package (ObsPack) is a framework designed to bring together atmospheric greenhouse gas observations from a variety of sampling platforms, prepare them with specific applications in mind, and package and distribute them in a self-consistent and well-documented product. Data products created using the ObsPack framework (called "ObsPack products") are intended to support carbon cycle modeling studies and represent a next generation of value-added greenhouse gas observation products modeled after the cooperative GLOBALVIEW products introduced in 1996. Depending on intended use, ObsPack products may include data in their original form reformatted using the ObsPack framework or may contain derived data consisting of averages, subsets, or smoothed representations of original data. All products include extensive ancillary information (metadata) intended to help ensure the data are used appropriately, their calibration and quality assurance history are clearly described, and that individuals responsible for the measurements (data providers or principal investigators (PIs)) are properly acknowledged for their work. ObsPack products are made freely available using a distribution strategy designed to improve communication between data providers and product users. The strategy includes a data usage policy that requires users to directly communicate with data providers and an automated e-mail notification system triggered when a product is accessed. ObsPack products will be assigned a unique digital object identifier (DOI) to ensure each product can be unambiguously identified in scientific literature. Here we describe the ObsPack framework and its potential role in supporting the evolving needs of both data providers and product users.

Atmospheric transport model errors are a major contributor to uncertainty in CO2 inverse flux estimates. Our study compares CO2 mole fraction observations from the North American Carbon Program Mid-Continental Intensive (MCI) field campaign and modeled mole fractions from two atmospheric transport models: the global Transport Model 5 from NOAA's CarbonTracker system and the mesoscale Weather Research and Forecasting model. Both models are coupled to identical CO2 fluxes and lateral boundary conditions from CarbonTracker (CT2009 release). Statistical analyses were performed for two periods of 2007 using observed daily daytime average mole fractions of CO2 to test the ability of these models to reproduce the observations and to infer possible causes of the discrepancies. TM5-CT2009 overestimates midsummer planetary boundary layer CO2 for sites in the U.S. corn belt by 10 ppm. Weather Research and Forecasting (WRF)-CT2009 estimates diverge from the observations with similar magnitudes, but the signs of the differences vary from site to site. The modeled mole fractions are highly correlated with the observed seasonal cycle (r ≥ 0.7) but less correlated in the growing season, where weather-related changes in CO2 dominate the observed variability. Spatial correlations in residuals from TM5-CT2009 are higher than WRF-CT2009 perhaps due to TM5's coarse horizontal resolution and shallow vertical mixing. Vertical mixing appears to have influenced CO2 residuals from both models. TM5-CT2009 has relatively weak vertical mixing near the surface limiting the connection between local CO2 surface fluxes and boundary layer. WRF-CT2009 has stronger vertical mixing that may increase the connections between local surface fluxes and the boundary layer.

Geoengineering the climate by increasing the Earth's reflectivity has been suggested. In this Perspective, the detectability of various methods is investigated. Although satellite observations can detect large changes in albedo, smaller increases caused by some methods of geoengineering are indistinguishable from natural variability. This raises the question of how such schemes would be managed if their impacts can not be quantified.

Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding of land-atmosphere carbon exchange to larger regions. The North American Carbon Program (NACP) Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal model intercomparison and evaluation effort focused on improving the diagnosis and attribution of carbon exchange at regional and global scales. MsTMIP builds upon current and past synthesis activities, and has a unique framework designed to isolate, interpret, and inform understanding of how model structural differences impact estimates of carbon uptake and release. Here we provide an overview of the MsTMIP effort and describe how the MsTMIP experimental design enables the assessment and quantification of TBM structural uncertainty. Model structure refers to the types of processes considered (e.g. nutrient cycling, disturbance, lateral transport of carbon), and how these processes are represented (e.g. photosynthetic formulation, temperature sensitivity, respiration) in the models. By prescribing a common experimental protocol with standard spin-up procedures and driver data sets, we isolate any biases and variability in TBM estimates of regional and global carbon budgets resulting from differences in the models themselves (i.e. model structure) and model-specific parameter values. An initial intercomparison of model structural differences is represented using hierarchical cluster diagrams (a.k.a. dendrograms), which highlight similarities and differences in how models account for carbon cycle, vegetation, energy, and nitrogen cycle dynamics. We show that, despite the standardized protocol used to derive initial conditions, models show a high degree of variation for GPP, total living biomass, and total soil carbon, underscoring the influence of differences in model structure and parameterization on model estimates.

Atmospheric CO2 inversions estimate surface carbon fluxes from an optimal fit to atmospheric CO2 measurements, usually including prior constraints on the flux estimates. Eleven sets of carbon flux estimates are compared, generated by different inversions systems that vary in their inversions methods, choice of atmospheric data, transport model and prior information. The inversions were run for at least 5 yr in the period between 1990 and 2010. Mean fluxes for 2001–2004, seasonal cycles, interannual variability and trends are compared for the tropics and northern and southern extra-tropics, and separately for land and ocean. Some continental/basin-scale subdivisions are also considered where the atmospheric network is denser. Four-year mean fluxes are reasonably consistent across inversions at global/latitudinal scale, with a large total (land plus ocean) carbon uptake in the north (−3.4 Pg C yr−1 (±0.5 Pg C yr−1 standard deviation), with slightly more uptake over land than over ocean), a significant although more variable source over the tropics (1.6 ± 0.9 Pg C yr−1) and a compensatory sink of similar magnitude in the south (−1.4 ± 0.5 Pg C yr−1) corresponding mainly to an ocean sink. Largest differences across inversions occur in the balance between tropical land sources and southern land sinks. Interannual variability (IAV) in carbon fluxes is larger for land than ocean regions (standard deviation around 1.06 versus 0.33 Pg C yr−1 for the 1996–2007 period), with much higher consistency among the inversions for the land. While the tropical land explains most of the IAV (standard deviation ~ 0.65 Pg C yr−1), the northern and southern land also contribute (standard deviation ~ 0.39 Pg C yr−1). Most inversions tend to indicate an increase of the northern land carbon uptake from late 1990s to 2008 (around 0.1 Pg C yr−1, predominantly in North Asia. The mean seasonal cycle appears to be well constrained by the atmospheric data over the northern land (at the continental scale), but still highly dependent on the prior flux seasonality over the ocean. Finally we provide recommendations to interpret the regional fluxes, along with the uncertainty estimates.

Quantifying oceanic anthropogenic carbon uptake by monitoring interior dissolved inorganic carbon (DIC) concentrations is complicated by the influence of natural variability. The "eMLR method" aims to address this issue by using empirical regression fits of the data instead of the data themselves, inferring the change in anthropogenic carbon in time by difference between predictions generated by the regressions at each time. The advantages of the method are that it provides in principle a means to filter out natural variability, which theoretically becomes the regression residuals, and a way to deal with sparsely and unevenly distributed data. The degree to which these advantages are realized in practice is unclear, however. The ability of the eMLR method to recover the anthropogenic carbon signal is tested here using a global circulation and biogeochemistry model in which the true signal is known. Results show that regression model selection is particularly important when the observational network changes in time. When the observational network is fixed, the likelihood that co-located systematic misfits between the empirical model and the underlying, yet unknown, true model cancel is greater, improving eMLR results. Changing the observational network modifies how the spatio-temporal variance pattern is captured by the respective datasets, resulting in empirical models that are dynamically or regionally inconsistent, leading to systematic errors. In consequence, the use of regression formulae that change in time to represent systematically best-fit models at all times does not guarantee the best estimates of anthropogenic carbon change if the spatial distributions of the stations emphasize hydrographic features differently in time. Other factors, such as a balanced and representative station coverage, vertical continuity of the regression formulae consistent with the hydrographic context and resiliency of the spatial distribution of the residual field can be used to help guide model selection. The characteristic spatial scales of the modes of inter-annual to decadal variability in relation to the size of the North Atlantic, in concert with the station coverage available, place practical limits on the ability of eMLR to fully account for natural variability. Due to its statistical nature, eMLR only efficiently removes the natural variability whose spatial scales are smaller than the system analyzed.

To investigate the effect of additional CO2 observations in the Siberia region on the Asian and global surface CO2 flux analyses, two experiments using different observation dataset were performed. One experiment was conducted using a data set that includes additional observations of Siberian tower measurements (Japan-Russia Siberian Tall Tower Inland Observation Network: JR-STATION), and the other experiment was conducted using a data set without the above additional observations. The results show that the global balance of the sources and sinks of surface CO2 fluxes was maintained for both experiments with and without the additional observations. While the magnitude of the optimized surface CO2 flux uptake in Siberia decreased, the magnitude of the optimized surface CO2 flux uptake in the other regions (e.g., Europe) of the Northern Hemisphere (NH) increased for the experiment with the additional observations. This change was mostly caused by changes in the magnitudes of surface CO2 flux in June and July. The observation impact measured by uncertainty reduction and self-sensitivity tests shows that additional observations provide useful information on the estimated surface CO2 flux. It is expected that the Siberian observations play an important role in estimating surface CO2 flux in the NH in the future.

We develop an approach for estimating net ecosystem exchange (NEE) using inventory-based information over North America (NA) for a recent 7-year period (ca. 2000–2006). The approach notably retains information on the spatial distribution of NEE, or the vertical exchange between land and atmosphere of all non-fossil fuel sources and sinks of CO2, while accounting for lateral transfers of forest and crop products as well as their eventual emissions. The total NEE estimate of a � 327 ± 252 TgC yr � 1 sink for NA was driven primarily by CO2 uptake in the Forest Lands sector (� 248 TgC yr � 1 ), largely in the Northwest and Southeast regions of the US, and in the Crop Lands sector (� 297 TgC yr � 1 ), predominantly in the Midwest US states. These sinks are counteracted by the carbon source estimated for the Other Lands sector (+218 TgC yr � 1 ), where much of the forest and crop products are assumed to be returned to the atmosphere (through livestock and human consumption). The ecosystems of Mexico are estimated to be a small net source (+18 TgC yr � 1 ) due to land use change between 1993 and 2002. We compare these inventorybased estimates with results from a suite of terrestrial biosphere and atmospheric inversion models, where the mean continental-scale NEE estimate for each ensemble is � 511 TgC yr � 1 and � 931 TgC yr � 1 , respectively. In the modeling approaches, all sectors, including Other Lands, were generally estimated to be a carbon sink, driven in part by assumed CO2 fertilization and/or lack of consideration of carbon sources from disturbances and product emissions. Additional fluxes not measured by the inventories, although highly uncertain, could add an additional � 239 TgC yr � 1 to the inventory-based NA sink estimate, thus suggesting some convergence with the modeling approaches.

We show here an updated estimate of the net land carbon sink (NLS) as a function of time from 1960 to 2007 calculated from the difference between fossil fuel emissions, the observed atmospheric growth rate, and the ocean uptake obtained by recent ocean model simulations forced with reanalysis wind stress and heat and water fluxes. Except for interannual variability, the net land carbon sink appears to have been relatively constant at a mean value of −0.27 Pg C yr−1 between 1960 and 1988, at which time it increased abruptly by −0.88 (−0.77 to −1.04) Pg C yr−1 to a new relatively constant mean of −1.15 Pg C yr−1 between 1989 and 2003/7 (the sign convention is negative out of the atmosphere). This result is detectable at the 99% level using a t-test. The land use source (LU) is relatively constant over this entire time interval. While the LU estimate is highly uncertain, this does imply that most of the change in the net land carbon sink must be due to an abrupt increase in the land sink, LS = NLS – LU, in response to some as yet unknown combination of biogeochemical and climate forcing. A regional synthesis and assessment of the land carbon sources and sinks over the post 1988/1989 period reveals broad agreement that the Northern Hemisphere land is a major sink of atmospheric CO2, but there remain major discrepancies with regard to the sign and magnitude of the net flux to and from tropical land., Biogeosciences, 7 (8), ISSN:1726-4170

We present carbon dioxide (CO2) estimates from the Tropospheric Emission Spectrometer (TES) on the EOS-Aura satellite launched in 2004. For observations between 40° S and 45° N, we find about 1 degree of freedom with peak sensitivity at 511 hPa. The estimated error is ~10 ppm for a single target and 1.3–2.3 ppm for monthly averages on spatial scales of 20°×30°. Monthly spatially-averaged TES data from 2005–2008 processed with a uniform initial guess and prior are compared to CONTRAIL aircraft data over the Pacific ocean, aircraft data at the Southern Great Plains (SGP) ARM site in the southern US, and the Mauna Loa and Samoa surface stations. Comparisons to Mauna Loa data show a correlation of 0.92, a standard deviation of 1.3 ppm, a predicted error of 1.2 ppm, and a ~2% low bias, which is subsequently corrected. Comparisons to SGP aircraft data over land show a correlation of 0.67 and a standard deviation of 2.3 ppm. TES data between 40° S and 45° N for 2006–2007 are compared to surface flask data, GLOBALVIEW, the Atmospheric Infrared Sounder (AIRS), and CarbonTracker. Comparison to GLOBALVIEW-CO2 ocean surface sites shows a correlation of 0.60 which drops when TES is offset in latitude, longitude, or time. At these same locations, TES shows a 0.62 and 0.67 correlation to CarbonTracker at the surface and 5 km, respectively. We also conducted an observing system simulation experiment to assess the potential utility of the TES data for inverse modeling of CO2 fluxes. We find that if biases in the data and model are well characterized, the averaged data have the potential to provide sufficient information to significantly reduce uncertainty on annual estimates of regional CO2 sources and sinks. Averaged pseudo-data at 10°×10° reduced uncertainty in flux estimates by as much as 70% for some tropical regions.

We present an estimate of net ecosystem exchange (NEE) of CO2 in Europe for the years 2001-2007. It is derived with a data assimilation that uses a large set of atmospheric CO2 mole fraction observations (∼70 000) to guide relatively simple descriptions of terrestrial and oceanic net exchange, while fossil fuel and fire emissions are prescribed. Weekly terrestrial sources and sinks are optimized (i.e., a flux inversion) for a set of 18 large ecosystems across Europe in which prescribed climate, weather, and surface characteristics introduce finer scale gradients. We find that the terrestrial biosphere in Europe absorbed a net average of -165 Tg C yr-1 over the period considered. This uptake is predominantly in non-EU countries, and is found in the northern coniferous (-94 Tg C yr-1) and mixed forests (-30 Tg C yr-1) as well as the forest/field complexes of eastern Europe (-85 Tg C yr-1). An optimistic uncertainty estimate derived using three biosphere models suggests the uptake to be in a range of -122 to -258 Tg C yr-1, while a more conservative estimate derived from the a-posteriori covariance estimates is -165±437 Tg C yr-1. Note, however, that uncertainties are hard to estimate given the nature of the system and are likely to be significantly larger than this. Interannual variability in NEE includes a reduction in uptake due to the 2003 drought followed by 3 years of more than average uptake. The largest anomaly of NEE occurred in 2005 concurrent with increased seasonal cycles of observed CO2. We speculate these changes to result from the strong negative phase of the North Atlantic Oscillation in 2005 that lead to favorable summer growth conditions, and altered horizontal and vertical mixing in the atmosphere. All our results are available through http://www.carbontracker.eu. © 2009 Blackwell Publishing Ltd.

Population models in ecology are rarely validated by comparing their pre- dictions to long-term observations of changes in population size. We have used a variety of analytical tools to examine a 45-year time series of annual censuses of Alpine ibex (Capra ibex) in the Gran Paradiso National Park in northwestern Italy. This ibex population grew from about 3300 to almost 5000 individuals in the 1980s during a decade of anom- alously mild winters, and then began to decline in the 1990s. By 1997, the population size had returned to previous levels. Adult survival apparently increased and adult sex ratio may have changed to slightly favor males during the increase in population density. Yearly changes in total population were correlated with seasonal average snow depth and population density over the 39 years for which climate data were available. Our results show that the ibex population size was limited by both density dependence and deep snow. A model based on these factors fit to the first 19 years of data was used to forecast subsequent changes in total population based on initial population size and yearly snow depth. The model was able to predict the increase and subsequent decline in total population size over the final 20 years of the study but failed to reproduce population levels after the eruption. Our results suggest that the 1980s episode of population growth was primarily driven by increased adult survival, rather than increased recruitment.

A blind comparison with data is made with a model for the coherence time of broadband sound (133 Hz, 17-Hz bandwidth) at 3709 km. Coherence time is limited by changes in the ocean because the acoustic instruments are fixed to the Earth on the bottom of the sea with time bases maintained by atomic clocks. Although the modeled coherence time depends a bit on the difficult problem of correctly modeling relative signal-to-noise ratios, normalized correlation coefficients of the broadband signals for the data (model) are 0.90 (0.83), 0.72 (0.59), and 0.51 (0.36) at lags of 2, 4.1, and 6.2 min, respectively. In all these cases, observed coherence times are a bit longer than modeled. The temporal evolution of the model is based on the linear dispersion relation for internal waves. Acoustic propagation is modeled with the parabolic approximation and the sound-speed insensitive operator.

Bathythermometric observations from standard National Oceanographic Data Center data sets are used to show evidence of Rossby waves in the northeast Pacific Ocean following several E1 Nino-Southern Oscillation events between 1968 and 1991. Observations of a westward propagating warm anomaly following the 1982-1983 El Nino are consistent with evidence from ocean models and satellite observations that coastally trapped Kelvin waves of tropical origin excite Rossby waves in the northeast Pacific. Observed Rossby wave phase speeds are about 1.6 cm s -1 higher than those predicted by linear shallow-water theory. At midlatitudes, observed waves are more than 1.5 times faster than theory. Phase speeds of Rossby waves in a 1/8° resolution nonlinear primitive equation model exceed standard linear theory, but only by about 0.1 cm s -1 , despite the fact that the model should replicate mechanisms that have recently been proposed to explain the observed anomalously fast phase speeds.

Ecosystems are important and dynamic components of the global carbon cycle, and terrestrial biospheric models (TBMs) are crucial tools in further understanding of how terrestrial carbon is stored and exchanged with the atmosphere across a variety of spatial and temporal scales. Improving TBM skills, and quantifying and reducing their estimation uncertainties, pose significant challenges. The Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal multi-scale and multi-model intercomparison effort set up to tackle these challenges. The MsTMIP protocol prescribes standardized environmental driver data that are shared among model teams to facilitate model–model and model–observation comparisons. This paper describes the global and North American environmental driver data sets prepared for the MsTMIP activity to both support their use in MsTMIP and make these data, along with the processes used in selecting/processing these data, accessible to a broader audience. Based on project needs and lessons learned from past model intercomparison activities, we compiled climate, atmospheric CO2 concentrations, nitrogen deposition, land use and land cover change (LULCC), C3 / C4 grasses fractions, major crops, phenology and soil data into a standard format for global (0.5° × 0.5° resolution) and regional (North American: 0.25° × 0.25° resolution) simulations. In order to meet the needs of MsTMIP, improvements were made to several of the original environmental data sets, by improving the quality, and/or changing their spatial and temporal coverage, and resolution. The resulting standardized model driver data sets are being used by over 20 different models participating in MsTMIP. The data are archived at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov) to provide long-term data management and distribution.

Diagnostic carbon cycle models produce estimates of net ecosystem production (NEP, the balance of net primary production and heterotrophic respiration) by integrating information from (i) satellite-based observations of land surface vegetation characteristics; (ii) distributed meteorological data; and (iii) eddy covariance flux tower observations of net ecosystem exchange (NEE) (used in model parameterization). However, a full bottom-up accounting of NEE (the vertical carbon flux) that is suitable for integration with atmosphere-based inversion modeling also includes emissions from decomposition/respiration of harvested forest and agricultural products, CO2 evasion from streams and rivers, and biomass burning. Here, we produce a daily time step NEE for North America for the year 2004 that includes NEP as well as the additional emissions. This NEE product was run in the forward mode through the CarbonTracker inversion setup to evaluate its consistency with CO2 concentration observations. The year 2004 was climatologically favorable for NEP over North America and the continental total was estimated at 1730 ± 370 TgC yr(-1) (a carbon sink). Harvested product emissions (316 ± 80 TgC yr(-1) ), river/stream evasion (158 ± 50 TgC yr(-1) ), and fire emissions (142 ± 45 TgC yr(-1) ) counteracted a large proportion (35%) of the NEP sink. Geographic areas with strong carbon sinks included Midwest US croplands, and forested regions of the Northeast, Southeast, and Pacific Northwest. The forward mode run with CarbonTracker produced good agreement between observed and simulated wintertime CO2 concentrations aggregated over eight measurement sites around North America, but overestimates of summertime concentrations that suggested an underestimation of summertime carbon uptake. As terrestrial NEP is the dominant offset to fossil fuel emission over North America, a good understanding of its spatial and temporal variation - as well as the fate of the carbon it sequesters ─ is needed for a comprehensive view of the carbon cycle.

[1] Although boundary layer processes are important in climate, weather and air quality, boundary layer climatology has received little attention, partly for lack of observational data sets. We analyze boundary layer climatology over Europe and the continental U.S. using a measure of boundary layer height based on the bulk Richardson number. Seasonal and diurnal variations during 1981–2005 are estimated from radiosonde observations, a reanalysis that assimilates observations, and two contemporary climate models that do not. Data limitations in vertical profiles introduce height uncertainties that can exceed 50% for shallow boundary layers (

COMMENTARY Common but differentiated IBI Prize Essay LETTERS I BOOKS I POLICY FORUM I EDUCATION FORUM I PERSPECTIVES LETTERS edited by Jennifer Sills Iconic CO 2 Time Series at Risk THE STEADY RISE IN ATMOSPHERIC LONG- lived greenhouse gas concentrations is the main driver of contemporary climate change. The Mauna Loa CO 2 time series (1, 2), started by C. D. Keeling in 1958 and maintained today by the Scripps Institution of Oceanography and the Earth System Research Laboratory (ESRL) of NOAA, is iconic evidence of the effect of human- caused fossil fuel and land-use change emis- sions on the atmospheric increase of CO 2 . The continuity of such records depends criti- cally on having stable funding, which is chal- lenging to maintain in the context of 3- to 4-year research grant funding cycles (3), and LEAH R. GERBER Faculty of Ecology, Evolution, and Environmental Sciences, School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA. E-mail: leah.gerber@asu.edu References 1. Associated Press, The New York Times, 6 July 2012, p. A7 (www.nytimes.com/2012/07/06/ world/europe/south-korea-whaling-plan-criticized.html). 2. S. Herman, Voice of America, 24 July 2012 (www.voanews.com/content/south-korea-still- considering-resumption-of-whaling/1444081.html). 3. L. R. Gerber, L. Morissette, K. Kaschner, D. Pauly, Science 323, 880 (2009). 4. R. Black, BBC News, 5 July 2012 (www.bbc.co.uk/news/science-environment-18719512). is currently threatened by the fi nancial crisis. The ESRL Global Monitoring Division maintains a network of about 100 surface and aircraft sites worldwide at which whole air samples are collected approximately every week for analysis of CO 2 , CH 4 , CO, halocar- bons, and many other chemical species (4). This is complemented by high-frequency measurements at the Mauna Loa, Barrow, American Samoa, and South Pole obser- vatories, and about 10 North American tall towers. The success of the NOAA program has inspired similar efforts in Europe (5), China (6), India (7), and Brazil (8), with the United Nations World Meteorological Orga- nization providing guidance and precision requirements through the Global Atmosphere Watch program (9), but no funding. 31 AUGUST 2012 Downloaded from www.sciencemag.org on August 17, 2015 AT THE RECENT INTERNATIONAL WHALING COMMISSION’S ANNUAL meeting in Panama, South Korean offi cials announced their plan to initiate a “scientifi c whaling” program (1). This announcement came as a surprise given the general sentiment that the global demand for whale meat is declining. After weeks of international outcry, on 17 July, South Korea reversed their decision to hunt whales for research, but the issue is not dead (2). South Korea claimed that the goal of the scientifi c whaling pro- gram is to study the types and amounts of fi sh whales eat, given confl ict with fi sher- ies. Yet, it is well established in the scien- tifi c literature that there are many ways to study whale diet without killing them (3). Decades of fruitless negotiation between pro- and anti-whaling nations suggests a broken system, wrought with loopholes that allow unsustainable whal- ing to continue. Within this broken system, there is no incentive to reduce whaling, as the recent announcement by South Korea shows. Whaling groups are unwilling to compromise by allowing a sustainable harvest of whales, so unsustainable (scientifi c) whaling continues. To ensure a future of both whales and whalers, we must har- ness the passion and value that people place on living whales, with- out telling people what to do or force one set of values on others. We need novel, out-of-the-box approaches to effective management and conservation of whales. We must compromise to ensure reduc- tions in whales being killed, better oversight of countries that har- vest them, and limited whaling that does not threaten the persis- tence of whales. For those who believe that whaling is unethical, I challenge you to put forward alternative ideas to a global moratorium that fosters the “loophole” of scientifi c whaling. With new plans to develop scientifi c whaling programs (4), the current global moratorium is clearly bro- ken. Scientists, conservation advocates, resource managers, and the public must work together to develop new approaches to ensure the persistence of whales in our oceans. The data collected by NOAA and its worldwide partners have been used not only to demonstrate the unassailable rise of atmo- spheric greenhouse gas concentrations, but also to infer the magnitudes, locations, and times of surface-atmosphere exchange of those gases based on small concentration gradients between sites (10). Important fi nd- ings from analysis of these records include the detection of a signifi cant terrestrial car- bon sink at northern mid-latitudes (11) and subsequent research aimed at identifying the mechanisms by which that sink must operate. Long-term, high-quality, atmospheric mea- surements are crucial for quantifying trends in greenhouse gas fl uxes and attributing them to fossil fuel emissions, changes in land-use and management, or the response of natural VOL 337 SCIENCE www.sciencemag.org Published by AAAS CREDIT: LEAH GERBER/ ARIZONA STATE UNIVERSITY The Scientifi c Whaling Loophole

Understanding of carbon exchange between terrestrial ecosystems and the atmosphere can be improved through direct observations and experiments, as well as through modeling activities. Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding to much larger terrestrial regions. Although models vary in their specific goals and approaches, their central role within carbon cycle science is to provide a better understanding of the mechanisms currently controlling carbon exchange. Recently, the North American Carbon Program (NACP) organized several interim-synthesis activities to evaluate and inter-compare models and observations at local to continental scales for the years 2000-2005. Here, we compare the results from the TBMs collected as part of the regional and continental interim-synthesis (RCIS) activities. The primary objective of this work is to synthesize and compare the 19 participating TBMs to assess current understanding of the terrestrial carbon cycle in North America. Thus, the RCIS focuses on model simulations available from analyses that have been completed by ongoing NACP projects and other recently published studies. The TBM flux estimates are compared and evaluated over different spatial (1{sup o} x 1{sup o} and spatially aggregated to different regions) and temporal (monthly and annually) scales. The range inmore » model estimates of net ecosystem productivity (NEP) for North America is much narrower than estimates of productivity or respiration, with estimates of NEP varying between -0.7 and 2.2 PgC yr{sup -1}, while gross primary productivity and heterotrophic respiration vary between 12.2 and 32.9 PgC yr{sup -1} and 5.6 and 13.2 PgC yr{sup -1}, respectively. The range in estimates from the models appears to be driven by a combination of factors, including the representation of photosynthesis, the source and of environmental driver data and the temporal variability of those data, as well as whether nutrient limitation is considered in soil carbon decomposition. The disagreement in current estimates of carbon flux across North America, including whether North America is a net biospheric carbon source or sink, highlights the need for further analysis through the use of model runs following a common simulation protocol, in order to isolate the influences of model formulation, structure, and assumptions on flux estimates.« less

This synthesis discusses the emissions of carbon dioxide from fossil-fuel combustion and cement production. While much is known about these emissions, there is still much that is unknown about the details surrounding these emissions. This synthesis explores our knowledge of these emissions in terms of why there is concern about them; how they are calculated; the major global efforts on inventorying them; their global, regional, and national totals at different spatial and temporal scales; how they are distributed on global grids (i.e., maps); how they are transported in models; and the uncertainties associated with these different aspects of the emissions. The magnitude of emissions from the combustion of fossil fuels has been almost continuously increasing with time since fossil fuels were first used by humans. Despite events in some nations specifically designed to reduce emissions, or which have had emissions reduction as a byproduct of other events, global total emissions continue their general increase with time. Global total fossil-fuel carbon dioxide emissions are known to within 10 % uncertainty (95 % confidence interval). Uncertainty on individual national total fossil-fuel carbon dioxide emissions range from a few percent to more than 50 %. This manuscript concludes that carbon dioxide emissions from fossil-fuel combustion continue to increase with time and that while much is known about the overall characteristics of these emissions, much is still to be learned about the detailed characteristics of these emissions.

[1] For over 20 years, atmospheric measurements of CO2 dry air mole fractions have been used to derive estimates of CO2 surface fluxes. Historically, only a few research laboratories made these measurements. Today, many laboratories are making CO2 observations using a variety of analysis techniques and, in some instances, using different calibration scales. As a result, the risk of biases in individual CO2 mole fraction records, or even in complete monitoring networks, has increased over the last decades. Ongoing experiments comparing independent, well-calibrated measurements of atmospheric CO2 show that biases can and do exist between measurement records. Biases in measurements create artificial spatial and temporal CO2 gradients, which are then interpreted by an inversion system, leading to erroneous flux estimates. Here we evaluate the impact of a constant bias introduced into the National Oceanic and Atmospheric Administration (NOAA) quasi-continuous measurement record at the Park Falls, Wisconsin (LEF), tall tower site on CarbonTracker flux estimates. We derive a linear relationship between the magnitude of the introduced bias at LEF and the CarbonTracker surface flux responses. Temperate North American net flux estimates are most sensitive to a bias at LEF in our CarbonTracker inversion, and its linear response rate is 68 Tg C yr−1 (∼10% of the estimated North American annual terrestrial uptake) for every 1 ppm of bias in the LEF record. This sensitivity increases when (1) measurement biases approached assumed model errors and (2) fewer other measurement records are available to anchor the flux estimates despite the presence of bias in one record. Flux estimate errors are also calculated beyond North America. For example, biospheric uptake in Europe and boreal Eurasia combined increases by 25 Tg C yr−1 per ppm CO2 to partially compensate for changes in the North American flux totals. These results illustrate the importance of well-calibrated, high-precision CO2 dry air mole fraction measurements, as well as the value of an effective strategy for detecting bias in measurements. This study stresses the need for a monitoring network with the necessary density to anchor regional, continental, and hemispheric fluxes more tightly and to lessen the impact of potentially undetected biases in observational networks operated by different national and international research programs.

As the U.S. and the International Community come to grips with anthropogenic climate change, it will be necessary to develop accurate techniques with global span for remote measurement of emissions and uptake of greenhouse gases (GHGs), with special emphasis on carbon dioxide.1 2 Presently, techniques exist for in situ and local remote measurements. The first steps towards expansion of these techniques to span the world are only now being taken with the launch of satellites with the capability to accurately measure column abundances of selected GHGs, including carbon dioxide. These satellite sensors do not directly measure emissions and uptake. The satellite data, appropriately filtered and processed, provide only one necessary, but not sufficient, input for the determination of emission and uptake rates. Optimal filtering and processing is a challenge in itself. But these data must be further combined with output from data-assimilation models of atmospheric structure and flows in order to infer emission and uptake rates for relevant points and regions. In addition, it is likely that substantially more accurate determinations would be possible given the addition of data from a sparse network of in situ and/or upward-looking remote GHG sensors. We will present the most promising approaches we've found for combining satellite, in situ, fixed remote sensing, and other potentially available data with atmospheric data-assimilation and backward-dispersion models for the purpose of determination of point and regional GHG emission and uptake rates. We anticipate that the first application of these techniques will be to GHG management for the U.S. Subsequent application may be to confirmation of compliance of other nations with future international GHG agreements.

[1] In the paper ‘‘Using altimetry to help explain patchy changes in hydrographic carbon measurements’’ by K. B. Rodgers et al. (Journal of Geophysical Research, 114, C09013, doi:10.1029/2008JC005183, 2009) the twelfth affiliation should read ‘‘CSIC, Vigo, Spain’’ not ‘‘CSIC, Madrid, Spain.’’ In addition, the address for F. F. Perez and A. F. Rios should read ‘‘CSIC, Eduardo Cabello, 6, Vigo E-32606, Spain’’ not ‘‘CSIC, Serrano 117, Madrid E-28006, Spain.’’ JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 114, C12099, doi:10.1029/2009JC005835, 2009 Click Here for Full Article

We synthesize estimates of the contemporary net air-sea CO2 flux on the basis of an inversion of interior ocean carbon observations using a suite of 10 ocean general circulation models (Mikaloff Fletcher et al., 2006, 2007) and compare them to estimates based on a new climatology of the air-sea difference of the partial pressure of CO2 (pCO2) (Takahashi et al., 2008). These two independent flux estimates reveal a consistent description of the regional distribution of annual mean sources and sinks of atmospheric CO2 for the decade of the 1990s and the early 2000s with differences at the regional level of generally less than 0.1 Pg C a−1. This distribution is characterized by outgassing in the tropics, uptake in midlatitudes, and comparatively small fluxes in thehigh latitudes. Both estimates point toward a small (∼ −0.3 Pg C a−1) contemporary CO2 sink in the Southern Ocean (south of 44°S), a result of the near cancellation between a substantial outgassing of natural CO2 and a strong uptake of anthropogenic CO2. A notable exception in the generally good agreement between the two estimates exists within the Southern Ocean: the ocean inversion suggests a relatively uniform uptake, while the pCO2-based estimate suggests strong uptake in the region between 58°S and 44°S, and a source in the region south of 58°S. Globally and for a nominal period between 1995 and 2000, the contemporary net air-sea flux of CO2 is estimated to be −1.7 ± 0.4 Pg C a−1 (inversion) and −1.4 ± 0.7 Pg C a−1 (pCO2-climatology), respectively, consisting of an outgassing flux of river-derived carbon of ∼+0.5 Pg C a−1, and an uptake flux of anthropogenic carbon of −2.2 ± 0.3 Pg C a−1 (inversion) and −1.9 ± 0.7 Pg C a−1 (pCO2-climatology). The two flux estimates also imply a consistent description of the contemporary meridional transport of carbon with southward ocean transport throughout most of the Atlantic basin, and strong equatorward convergence in the Indo-Pacific basins. Both transport estimates suggest a small hemispheric asymmetry with a southward transport of between −0.2 and −0.3 Pg C a−1 across the equator. While the convergence of these two independent estimates is encouraging and suggests that it is now possible to provide relatively tight constraints for the net air-sea CO2 fluxes at the regional basis, both studies are limited by their lack of consideration of long-term changes in the ocean carbon cycle, such as the recent possible stalling in the expected growth of the Southern Ocean carbon sink.

20 páginas, 1 apéndice, 10 figuras.-- Keith B. Rodgers ... et al., Here we use observations and ocean models to identify mechanisms driving large 11 seasonal to interannual variations in dissolved inorganic carbon (DIC) and dissolved 12 oxygen (O2) in the upper ocean. We begin with observations linking variations in upper 13 ocean DIC and O2 inventories with changes in the physical state of the ocean. Models are 14 subsequently used to address the extent to which the relationships derived from 15 short-timescale (6 months to 2 years) repeat measurements are representative of variations 16 over larger spatial and temporal scales. The main new result is that convergence and 17 divergence (column stretching) attributed to baroclinic Rossby waves can make a 18 first-order contribution to DIC and O2 variability in the upper ocean. This results in a close 19 correspondence between natural variations in DIC and O2 column inventory variations 20 and sea surface height (SSH) variations over much of the ocean. Oceanic Rossby wave 21 activity is an intrinsic part of the natural variability in the climate system and is elevated 22 even in the absence of significant interannual variability in climate mode indices. The 23 close correspondence between SSH and both DIC and O2 column inventories for many 24 regions suggests that SSH changes (inferred from satellite altimetry) may prove useful in 25 reducing uncertainty in separating natural and anthropogenic DIC signals (using 26 measurements from Climate Variability and Predictability’s CO2/Repeat Hydrography 27 program).

[1] To date, no formal validation of the new ionosphere nowcast system, United States–Total Electron Content (US-TEC), at the Space Environment Center in Boulder, Colorado, has been published. This paper therefore lays part of the validation groundwork by comparing solutions from Magic, the analysis version of US-TEC, with total electron content (TEC) data from the Fast Onboard Recording of Transient Events (FORTE) satellite. The Magic system uses ground-based GPS observations to reproduce a four-dimensional model of the electron density in the ionosphere. From this model, the TEC between any two points at any time can be obtained. The FORTE satellite, on the other hand, detects the arrival time versus frequency of a broadband signal from a transmitter at Los Alamos. The FORTE-observed group delay provides the TEC along the line of sight between the transmitter and the satellite. These FORTE line-of-sight observations can be compared with TEC values over the same lines of sight in the Magic model. A root-mean-square error (RMSE) calculation statistically compares 178 lines of sight. The RMSE indicates a statistical error of 2.87 total electron content units (1 TECU = 1016 el/m2) between FORTE and Magic, using the current operational GPS station list in US-TEC. How much FORTE and Magic individually contribute to this error remains indeterminable, although the errors are expected to be unique to either system and uncorrelated. Individual contributions of each method to the RMSE are estimated by eliminating observations most affected by raypath bending in FORTE and by varying the number of stations in Magic.

IPCC TAR 1.4 ± 0.7 1.7 ± 0.5 T3L1 1.3 ± 1.4 1.5 ± 1.4 T3L2 1.5 ± 1.0 1.3 ± 1.0 Bopp O2/N2 1.7 ± 0.9 ( 1.2 ± 0.9) 1.9 ± 0.9 ( 2.3 ± 0.7) Keeling O2/N2 1.7 ± 0.8 ( 1.3 ± 0.8) 1.4 ± 0.6 ( 1.9 ± 0.6) Joint 1.1 ± 0.2 2.1 ± 0.1 0.4 ± 0.2 1.7 ± 0.2 Gloor inverse 1.9 ± 0.3 ( 1.7 ± 0.3) 0.4 ± 0.3 1.5 ± 0.4 ( 1.8 ± 0.4) McNeil CFCs 1.5 ± 0.4 ( 2.0 ± 0.4) Matsumoto OCMIP 1.7 ± 0.2 ( 2.2 ± 0.2) Tak99 k u 2.1 Tak02 k u 1.6 Tak02 k u 2.3 MOM3 forward 2.2 ± 0.2 0.4 ± 0.1 1.7 ± 0.2 Estimates have been corrected so that river carbon flow is manifested as a land sink and a preindustrial ocean source of 0.45 PgC yr 1 (see auxiliary material). Contemporary air-sea fluxes (Fcontemp = Fpreindust + Fanthro) have been scaled to the 1992–1996 period by assuming the anthropogenic component is proportional to the atmospheric concentration perturbation, but air-land fluxes are not scaled. Original estimates, uncorrected for river carbon and unscaled in time, are given in parentheses. ‘‘IPCC-TAR 90s’’ is the estimate of Prentice et al. [2001] for the 1990s; ‘‘T3L1’’ and ‘‘T3L2’’ are the TransCom3 control inversions for level 1 [Gurney et al., 2002] and level 2 [Gurney et al., 2004], respectively, both for the period 1992–1996. ‘‘BoppO2/N2’’ and ‘‘Keeling O2/N2’’ represent the oxygen analyses of Bopp et al. [2002] for the period 1990–1996 and Keeling and Garcia [2002] for the 1990s, respectively. ‘‘Joint’’ is the current joint inversion for the period 1992–1996. ‘‘Gloor inverse’’ is the previous ocean inversion of Gloor et al. [2003] scaled to 1992–1996, a result nearly identical to that of McNeil et al. [2003] from CFC analysis. ‘‘Matsumoto OCMIP’’ is the summary of forward ocean carbon cycle simulations [Orr et al., 2001], as reported by Matsumoto et al. [2004], also scaled to 1992–1996. ‘‘Tak99’’ and ‘‘Tak02’’ represent estimates based on the DpCO2 analyses of Takahashi et al. [1999, 2002] respectively, using quadratic (‘‘k u’’ [Wanninkhof, 1992]) and cubic (‘‘k u’’ [Wanninkhof and McGillis, 1999]) gas transfer velocity parameterizations. ‘‘MOM3 Forward’’ are the 1992–1996 fluxes from OCMIP2 biotic simulations for the five models of the MOM3 suite used in the present study (see Table 1 of Jacobson et al. [2007]). For the period of the 1990s. Air-sea fluxes scaled to 1992–1996 by assuming that the anthropogenic flux is proportional to the atmospheric CO2 perturbation. For the period 1990–1996. Includes 0.45 ± 0.18 PgC yr 1 to account for river carbon fluxes (see auxiliary material). For the period 1990–1991. GLOBAL BIOGEOCHEMICAL CYCLES, VOL. 21, GB2025, doi:10.1029/2007GB003012, 2007 Click Here for Full Article

[1] The 14CO2 released into the stratosphere during bomb testing in the early 1960s provides a global constraint on air-sea gas exchange of soluble atmospheric gases like CO2. Using the most complete database of dissolved inorganic radiocarbon, DI14C, available to date and a suite of ocean general circulation models in an inverse mode we recalculate the ocean inventory of bomb-produced DI14C in the global ocean and confirm that there is a 25% decrease from previous estimates using older DI14C data sets. Additionally, we find a 33% lower globally averaged gas transfer velocity for CO2 compared to previous estimates (Wanninkhof, 1992) using the NCEP/NCAR Reanalysis 1 1954–2000 where the global mean winds are 6.9 m s−1. Unlike some earlier ocean radiocarbon studies, the implied gas transfer velocity finally closes the gap between small-scale deliberate tracer studies and global-scale estimates. Additionally, the total inventory of bomb-produced radiocarbon in the ocean is now in agreement with global budgets based on radiocarbon measurements made in the stratosphere and troposphere. Using the implied relationship between wind speed and gas transfer velocity ks = 0.27〈u102〉(Sc/660)−0.5 and standard partial pressure difference climatology of CO2 we obtain an net air-sea flux estimate of 1.3 ± 0.5 PgCyr−1 for 1995. After accounting for the carbon transferred from rivers to the deep ocean, our estimate of oceanic uptake (1.8 ± 0.5 PgCyr−1) compares well with estimates based on ocean inventories, ocean transport inversions using ocean concentration data, and model simulations.