scholarly journals Does atmospheric CO<sub>2</sub> seasonality play an important role in governing the air-sea flux of CO<sub>2</sub>?

2012 ◽  
Vol 9 (6) ◽  
pp. 2311-2323 ◽  
Author(s):  
P. R. Halloran
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Seasonal Cycle ◽  
Co2 Flux ◽  
Atmospheric Co2 ◽  
Seasonal Cycles ◽  
Earth System ◽  
Model Simulations ◽  
Anthropogenic Co2 ◽  
The Impact

Abstract. The amplitude, phase, and form of the seasonal cycle of atmospheric CO2 concentrations varies on many time and space scales (Peters et al., 2007). Intra-annual CO2 variation is primarily driven by seasonal uptake and release of CO2 by the terrestrial biosphere (Machta et al., 1977; Buchwitz et al., 2007), with a small (Cadule et al., 2010; Heimann et al., 1998), but potentially changing (Gorgues et al., 2010) contribution from the ocean. Variability in the magnitude, spatial distribution, and seasonal drivers of terrestrial net primary productivity (NPP) will be induced by, amongst other factors, anthropogenic CO2 release (Keeling et al., 1996), land-use change (Zimov et al., 1999) and planetary orbital variability, and will lead to changes in CO2atm seasonality. Despite CO2atm seasonality being a dynamic and prominent feature of the Earth System, its potential to drive changes in the air-sea flux of CO2 has not previously (to the best of my knowledge) been explored. It is important that we investigate the impact of CO2atm seasonality change, and the potential for carbon-cycle feedbacks to operate through the modification of the CO2atm seasonal cycle, because the decision had been made to prescribe CO2atm concentrations (rather than emissions) within model simulations for the fifth IPCC climate assessment (Taylor et al., 2009). In this study I undertake ocean-model simulations within which different magnitude CO2atm seasonal cycles are prescribed. These simulations allow me to examine the effect of a change in CO2atm seasonal cycle magnitude on the air-sea CO2 flux. I then use an off-line model to isolate the drivers of the identified air-sea CO2 flux change, and propose mechanisms by which this change may come about. Three mechanisms are identified by which co-variability of the seasonal cycles in atmospheric CO2 concentration, and seasonality in sea-ice extent, wind-speed and ocean temperature, could potentially lead to changes in the air-sea flux of CO2 at mid-to-high latitudes. The sea-ice driven mechanism responds to an increase in CO2atm seasonality by pumping CO2 into the ocean, the wind-speed and solubility-driven mechanisms, by releasing CO2 from the ocean (in a relative sense). The relative importance of the mechanisms will be determined by, amongst other variables, the seasonal extent of sea-ice. To capture the described feedbacks within earth system models, CO2atm concentrations must be allowed to evolve freely, forced only by anthropogenic emissions rather than prescribed CO2atm concentrations; however, time-integrated ocean simulations imply that the cumulative net air-sea flux could be at most equivalent to a few ppm CO2atm. The findings presented here suggest that, at least under pre-industrial conditions, the prescription of CO2atm concentrations rather than emissions within simulations will have little impact on the marine anthropogenic CO2 sink.

scholarly journals Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models

2019 ◽  
Vol 16 (19) ◽  
pp. 3883-3910 ◽  
Author(s):  
Lina Teckentrup ◽  
Sandy P. Harrison ◽  
Stijn Hantson ◽  
Angelika Heil ◽  
Joe R. Melton ◽  
...  
Keyword(s):  
Land Use ◽  
Co2 Concentration ◽  
Fire Regimes ◽  
Atmospheric Co2 ◽  
Anthropogenic Factors ◽  
Burned Area ◽  
Earth System ◽  
Atmospheric Co2 Concentration ◽  
Fire Models ◽  
The Impact

Abstract. Understanding how fire regimes change over time is of major importance for understanding their future impact on the Earth system, including society. Large differences in simulated burned area between fire models show that there is substantial uncertainty associated with modelling global change impacts on fire regimes. We draw here on sensitivity simulations made by seven global dynamic vegetation models participating in the Fire Model Intercomparison Project (FireMIP) to understand how differences in models translate into differences in fire regime projections. The sensitivity experiments isolate the impact of the individual drivers on simulated burned area, which are prescribed in the simulations. Specifically these drivers are atmospheric CO2 concentration, population density, land-use change, lightning and climate. The seven models capture spatial patterns in burned area. However, they show considerable differences in the burned area trends since 1921. We analyse the trajectories of differences between the sensitivity and reference simulation to improve our understanding of what drives the global trends in burned area. Where it is possible, we link the inter-model differences to model assumptions. Overall, these analyses reveal that the largest uncertainties in simulating global historical burned area are related to the representation of anthropogenic ignitions and suppression and effects of land use on vegetation and fire. In line with previous studies this highlights the need to improve our understanding and model representation of the relationship between human activities and fire to improve our abilities to model fire within Earth system model applications. Only two models show a strong response to atmospheric CO2 concentration. The effects of changes in atmospheric CO2 concentration on fire are complex and quantitative information of how fuel loads and how flammability changes due to this factor is missing. The response to lightning on global scale is low. The response of burned area to climate is spatially heterogeneous and has a strong inter-annual variation. Climate is therefore likely more important than the other factors for short-term variations and extremes in burned area. This study provides a basis to understand the uncertainties in global fire modelling. Both improvements in process understanding and observational constraints reduce uncertainties in modelling burned area trends.

scholarly journals Effects of snow grain shape on climate simulations: sensitivity tests with the Norwegian Earth System Model

2017 ◽  
Vol 11 (6) ◽  
pp. 2919-2942 ◽  
Author(s):  
Petri Räisänen ◽  
Risto Makkonen ◽  
Alf Kirkevåg ◽  
Jens B. Debernard
Keyword(s):  
Grain Size ◽  
Sea Ice ◽  
Grain Shape ◽  
Earth System Model ◽  
System Model ◽  
Blowing Snow ◽  
Earth System ◽  
Spherical Case ◽  
The Impact ◽  
Global Mean

Abstract. Snow consists of non-spherical grains of various shapes and sizes. Still, in radiative transfer calculations, snow grains are often treated as spherical. This also applies to the computation of snow albedo in the Snow, Ice, and Aerosol Radiation (SNICAR) model and in the Los Alamos sea ice model, version 4 (CICE4), both of which are employed in the Community Earth System Model and in the Norwegian Earth System Model (NorESM). In this study, we evaluate the effect of snow grain shape on climate simulated by NorESM in a slab ocean configuration of the model. An experiment with spherical snow grains (SPH) is compared with another (NONSPH) in which the snow shortwave single-scattering properties are based on a combination of three non-spherical snow grain shapes optimized using measurements of angular scattering by blowing snow. The key difference between these treatments is that the asymmetry parameter is smaller in the non-spherical case (0.77–0.78 in the visible region) than in the spherical case ( ≈  0.89). Therefore, for the same effective snow grain size (or equivalently, the same specific projected area), the snow broadband albedo is higher when assuming non-spherical rather than spherical snow grains, typically by 0.02–0.03. Considering the spherical case as the baseline, this results in an instantaneous negative change in net shortwave radiation with a global-mean top-of-the-model value of ca. −0.22 W m−2. Although this global-mean radiative effect is rather modest, the impacts on the climate simulated by NorESM are substantial. The global annual-mean 2 m air temperature in NONSPH is 1.17 K lower than in SPH, with substantially larger differences at high latitudes. The climatic response is amplified by strong snow and sea ice feedbacks. It is further demonstrated that the effect of snow grain shape could be largely offset by adjusting the snow grain size. When assuming non-spherical snow grains with the parameterized grain size increased by ca. 70 %, the climatic differences to the SPH experiment become very small. Finally, the impact of assumed snow grain shape on the radiative effects of absorbing aerosols in snow is discussed.

scholarly journals Assessing the impact of late Pleistocene megafaunal extinctions on global vegetation and climate

2013 ◽  
Vol 9 (4) ◽  
pp. 1761-1771 ◽  
Author(s):  
M.-O. Brault ◽  
L. A. Mysak ◽  
H. D. Matthews ◽  
C. T. Simmons
Keyword(s):  
Large Scale ◽  
Surface Albedo ◽  
Climate Model ◽  
Rapid Expansion ◽  
Atmospheric Co2 ◽  
Earth System ◽  
Global Mean Temperature ◽  
Pleistocene Climate ◽  
Global Vegetation ◽  
The Impact

Abstract. The end of the Pleistocene was a turning point for the Earth system as climate gradually emerged from millennia of severe glaciation in the Northern Hemisphere. The deglacial climate change coincided with an unprecedented decline in many species of Pleistocene megafauna, including the near-total eradication of the woolly mammoth. Due to an herbivorous diet that presumably involved large-scale tree grazing, the mammoth extinction has been associated with the rapid expansion of dwarf deciduous trees in Siberia and Beringia, thus potentially contributing to the changing climate of the period. In this study, we use the University of Victoria Earth System Climate Model (UVic ESCM) to simulate the possible effects of these extinctions on climate during the latest deglacial period. We have explored various hypothetical scenarios of forest expansion in the northern high latitudes, quantifying the biogeophysical effects in terms of changes in surface albedo and air temperature. These scenarios include a Maximum Impact Scenario (MIS) which simulates the greatest possible post-extinction reforestation in the model, and sensitivity tests which investigate the timing of extinction, the fraction of trees grazed by mammoths, and the southern extent of mammoth habitats. We also show the results of a simulation with free atmospheric CO2-carbon cycle interactions. For the MIS, we obtained a surface albedo increase and global warming of 0.006 and 0.175 °C, respectively. Less extreme scenarios produced smaller global mean temperature changes, though local warming in some locations exceeded 0.3 °C even in the more realistic extinction scenarios. In the free CO2 simulation, the biogeophysical-induced warming was amplified by a biogeochemical effect, whereby the replacement of high-latitude tundra with shrub forest led to a release of soil carbon to the atmosphere and a small atmospheric CO2 increase. Overall, our results suggest the potential for a small, though non-trivial, effect of megafaunal extinctions on Pleistocene climate.

scholarly journals Modelling the seasonal variability of the Antarctic Slope Current

Ocean Science ◽  
2011 ◽  
Vol 7 (4) ◽  
pp. 455-470 ◽  
Author(s):  
P. Mathiot ◽  
H. Goosse ◽  
T. Fichefet ◽  
B. Barnier ◽  
H. Gallée
Keyword(s):  
Wind Speed ◽  
Mass Transport ◽  
Sea Ice ◽  
Seasonal Cycle ◽  
Water Mass ◽  
Atmospheric Forcing ◽  
Sensitivity Experiments ◽  
The Mean ◽  
Antarctic Slope Current ◽  
The Antarctic

Abstract. One of the main features of the oceanic circulation along Antarctica is the Antarctic Slope Current (ASC). This circumpolar current flows westwards and contributes to communication between the three major oceanic basins around Antarctica. The ASC is not very well known due to remote location and the presence of sea ice during several months, allowing in situ studies only during summertime. Moreover, only few modelling studies of this current have been carried out. Here, we investigate the sensitivity of this simulated current to four different resolutions in a coupled ocean-sea ice model and to two different atmospheric forcing sets. Two series of simulations are conducted. For the first series, global model configurations are run at coarse (2°) to eddy-permitting (0.25°) resolutions with the same atmospheric forcing. For the second series, simulations with two different atmospheric forcings are performed using a regional circumpolar configuration (south of 30° S) at 0.5° resolution. The first atmospheric forcing is based on a global atmospheric reanalysis and satellite data, while the second is based on a downscaling of the global atmospheric reanalysis by a regional atmospheric model calibrated to Antarctic meteorological conditions. Sensitivity experiments to resolution indicate that a minimum model resolution of 0.5° is needed to capture the dynamics of the ASC in terms of water mass transport and recirculation. Sensitivity experiments to atmospheric forcing fields shows that the wind speed along the Antarctic coast strongly controls the water mass transport and the seasonal cycle of the ASC. An increase in annual mean of easterlies by about 30 % leads to an increase in the mean ASC transport by about 40 %. Similar effects are obtained on the seasonal cycle: using a wind forcing field with a larger seasonal cycle (+30 %) increases by more than 30 % the amplitude of the seasonal cycle of the ASC. To confirm the importance of wind seasonal cycle, a simulation without wind speed seasonal cycle is carried out. This simulation shows a decrease by more than 50 % of the amplitude of the ASC transport seasonal cycle without changing the mean value of ASC transport.

scholarly journals Terrestrial carbon sink observed from space: variation of growth rates and seasonal cycle amplitudes in response to interannual surface temperature variability

2014 ◽  
Vol 14 (1) ◽  
pp. 133-141 ◽  
Author(s):  
O. Schneising ◽  
M. Reuter ◽  
M. Buchwitz ◽  
J. Heymann ◽  
H. Bovensmann ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Growth Rates ◽  
Seasonal Cycle ◽  
Temperature Anomaly ◽  
Carbon Sink ◽  
Atmospheric Co2 ◽  
Climate Feedback ◽  
Terrestrial Carbon ◽  
Terrestrial Carbon Sink ◽  
The Impact

Abstract. The terrestrial biosphere is currently acting as a net carbon sink on the global scale, exhibiting significant interannual variability in strength. To reliably predict the future strength of the land sink and its role in atmospheric CO2 growth, the underlying biogeochemical processes and their response to a changing climate need to be well understood. In particular, better knowledge of the impact of key climate variables such as temperature or precipitation on the biospheric carbon reservoir is essential. It is demonstrated using nearly a decade of SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) nadir measurements that years with higher temperatures during the growing season can be robustly associated with larger growth rates in atmospheric CO2 and smaller seasonal cycle amplitudes for northern mid-latitudes. We find linear relationships between warming and CO2 growth as well as seasonal cycle amplitude at the 98% significance level. This suggests that the terrestrial carbon sink is less efficient at higher temperatures during the analysed time period. Unless the biosphere has the ability to adapt its carbon storage under warming conditions in the longer term, such a temperature response entails the risk of potential future sink saturation via a positive carbon-climate feedback. Quantitatively, the covariation between the annual CO2 growth rates derived from SCIAMACHY data and warm season surface temperature anomaly amounts to 1.25 ± 0.32 ppm yr−1 K−1 for the Northern Hemisphere, where the bulk of the terrestrial carbon sink is located. In comparison, this relationship is less pronounced in the Southern Hemisphere. The covariation of the seasonal cycle amplitudes retrieved from satellite measurements and temperature anomaly is −1.30 ± 0.31 ppm K−1 for the north temperate zone. These estimates are consistent with those from the CarbonTracker data assimilated CO2 data product, indicating that the temperature dependence of the model surface fluxes is realistic.

scholarly journals Consistent evaluation of ACOS-GOSAT, BESD-SCIAMACHY, CarbonTracker, and MACC through comparisons to TCCON

2016 ◽  
Vol 9 (2) ◽  
pp. 683-709 ◽  
Author(s):  
Susan Kulawik ◽  
Debra Wunch ◽  
Christopher O'Dell ◽  
Christian Frankenberg ◽  
Maximilian Reuter ◽  
...  
Keyword(s):  
Mole Fraction ◽  
Seasonal Cycle ◽  
Atmospheric Co2 ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Cycle Phase ◽  
Data Set ◽  
Single Observation ◽  
Cycle Amplitude ◽  
The Impact

Abstract. Consistent validation of satellite CO2 estimates is a prerequisite for using multiple satellite CO2 measurements for joint flux inversion, and for establishing an accurate long-term atmospheric CO2 data record. Harmonizing satellite CO2 measurements is particularly important since the differences in instruments, observing geometries, sampling strategies, etc. imbue different measurement characteristics in the various satellite CO2 data products. We focus on validating model and satellite observation attributes that impact flux estimates and CO2 assimilation, including accurate error estimates, correlated and random errors, overall biases, biases by season and latitude, the impact of coincidence criteria, validation of seasonal cycle phase and amplitude, yearly growth, and daily variability. We evaluate dry-air mole fraction (XCO2) for Greenhouse gases Observing SATellite (GOSAT) (Atmospheric CO2 Observations from Space, ACOS b3.5) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) (Bremen Optimal Estimation DOAS, BESD v2.00.08) as well as the CarbonTracker (CT2013b) simulated CO2 mole fraction fields and the Monitoring Atmospheric Composition and Climate (MACC) CO2 inversion system (v13.1) and compare these to Total Carbon Column Observing Network (TCCON) observations (GGG2012/2014). We find standard deviations of 0.9, 0.9, 1.7, and 2.1 ppm vs. TCCON for CT2013b, MACC, GOSAT, and SCIAMACHY, respectively, with the single observation errors 1.9 and 0.9 times the predicted errors for GOSAT and SCIAMACHY, respectively. We quantify how satellite error drops with data averaging by interpreting according to error2 = a2 + b2/n (with n being the number of observations averaged, a the systematic (correlated) errors, and b the random (uncorrelated) errors). a and b are estimated by satellites, coincidence criteria, and hemisphere. Biases at individual stations have year-to-year variability of  ∼  0.3 ppm, with biases larger than the TCCON-predicted bias uncertainty of 0.4 ppm at many stations. We find that GOSAT and CT2013b underpredict the seasonal cycle amplitude in the Northern Hemisphere (NH) between 46 and 53° N, MACC overpredicts between 26 and 37° N, and CT2013b underpredicts the seasonal cycle amplitude in the Southern Hemisphere (SH). The seasonal cycle phase indicates whether a data set or model lags another data set in time. We find that the GOSAT measurements improve the seasonal cycle phase substantially over the prior while SCIAMACHY measurements improve the phase significantly for just two of seven sites. The models reproduce the measured seasonal cycle phase well except for at Lauder_125HR (CT2013b) and Darwin (MACC). We compare the variability within 1 day between TCCON and models in JJA; there is correlation between 0.2 and 0.8 in the NH, with models showing 10–50 % the variability of TCCON at different stations and CT2013b showing more variability than MACC. This paper highlights findings that provide inputs to estimate flux errors in model assimilations, and places where models and satellites need further investigation, e.g., the SH for models and 45–67° N for GOSAT and CT2013b.

scholarly journals An estimate of monthly global emissions of anthropogenic CO2: Impact on the seasonal cycle of atmospheric CO2

2008 ◽  
Vol 113 (G1) ◽  
pp. n/a-n/a ◽  
Author(s):  
D. J. Erickson ◽  
R. T. Mills ◽  
J. Gregg ◽  
T. J. Blasing ◽  
F. M. Hoffman ◽  
...  
Keyword(s):  
Seasonal Cycle ◽  
Atmospheric Co2 ◽  
Anthropogenic Co2 ◽  
Global Emissions

scholarly journals A remote sensing technique for global monitoring of power plant CO<sub>2</sub> emissions from space and related applications

2010 ◽  
Vol 3 (4) ◽  
pp. 781-811 ◽  
Author(s):  
H. Bovensmann ◽  
M. Buchwitz ◽  
J. P. Burrows ◽  
M. Reuter ◽  
T. Krings ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Wind Speed ◽  
Power Plant ◽  
Co2 Emissions ◽  
Kyoto Protocol ◽  
Inverse Modeling ◽  
Point Sources ◽  
Atmospheric Co2 ◽  
Independent Verification ◽  
Anthropogenic Co2

Abstract. Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas (GHG) causing global warming. The atmospheric CO2 concentration increased by more than 30% since pre-industrial times – primarily due to burning of fossil fuels – and still continues to increase. Reporting of CO2 emissions is required by the Kyoto protocol. Independent verification of reported emissions, which are typially not directly measured, by methods such as inverse modeling of measured atmospheric CO2 concentrations is currently not possible globally due to lack of appropriate observations. Existing satellite instruments such as SCIAMACHY/ENVISAT and TANSO/GOSAT focus on advancing our understanding of natural CO2 sources and sinks. The obvious next step for future generation satellites is to also constrain anthropogenic CO2 emissions. Here we present a promising satellite remote sensing concept based on spectroscopic measurements of reflected solar radiation and show, using power plants as an example, that strong localized CO2 point sources can be detected and their emissions quantified. This requires mapping the atmospheric CO2 column distribution at a spatial resolution of 2×2 km2 with a precision of 0.5% (2 ppm) or better. We indicate that this can be achieved with existing technology. For a single satellite in sun-synchronous orbit with a swath width of 500 km, each power plant (PP) is overflown every 6 days or more frequent. Based on the MODIS cloud mask data product we conservatively estimate that typically 20 sufficiently cloud free overpasses per PP can be achieved every year. We found that for typical wind speeds in the range of 2–6 m/s the statistical uncertainty of the retrieved PP CO2 emission due to instrument noise is in the range 1.6–4.8 MtCO2/yr for single overpasses. This corresponds to 12–36% of the emission of a mid-size PP (13 MtCO2/yr). We have also determined the sensitivity to parameters which may result in systematic errors such as atmospheric transport and aerosol related parameters. We found that the emission error depends linearly on wind speed, i.e., a 10% wind speed error results in a 10% emission error, and that neglecting enhanced aerosol concentrations in the PP plume may result in errors in the range 0.2–2.5 MtCO2/yr, depending on PP aerosol emission. The discussed concept has the potential to contribute to an independent verification of reported anthropogenic CO2 emissions and therefore could be an important component of a future global anthropogenic GHG emission monitoring system. This is of relevance in the context of Kyoto protocol follow-on agreements but also allows detection and monitoring of a variety of other strong natural and anthropogenic CO2 and CH4 emitters. The investigated instrument is not limited to these applications as it has been specified to also deliver the data needed for global regional-scale CO2 and CH4 surface flux inverse modeling.

scholarly journals Spatial distributions of <i>X</i><sub>CO<sub>2</sub></sub> seasonal cycle amplitude and phase over northern high-latitude regions

2021 ◽  
Vol 21 (22) ◽  
pp. 16661-16687
Author(s):  
Nicole Jacobs ◽  
William R. Simpson ◽  
Kelly A. Graham ◽  
Christopher Holmes ◽  
Frank Hase ◽  
...  
Keyword(s):  
High Latitude ◽  
Seasonal Cycle ◽  
Atmospheric Transport ◽  
Co2 Flux ◽  
Latitudinal Gradients ◽  
Seasonal Cycles ◽  
Spatial Distributions ◽  
Surface Contact ◽  
Northern High Latitude ◽  
Data Coverage

Abstract. Satellite-based observations of atmospheric carbon dioxide (CO2) provide measurements in remote regions, such as the biologically sensitive but undersampled northern high latitudes, and are progressing toward true global data coverage. Recent improvements in satellite retrievals of total column-averaged dry air mole fractions of CO2 (XCO2) from the NASA Orbiting Carbon Observatory 2 (OCO-2) have allowed for unprecedented data coverage of northern high-latitude regions, while maintaining acceptable accuracy and consistency relative to ground-based observations, and finally providing sufficient data in spring and autumn for analysis of satellite-observed XCO2 seasonal cycles across a majority of terrestrial northern high-latitude regions. Here, we present an analysis of XCO2 seasonal cycles calculated from OCO-2 data for temperate, boreal, and tundra regions, subdivided into 5∘ latitude by 20∘ longitude zones. We quantify the seasonal cycle amplitudes (SCAs) and the annual half drawdown day (HDD). OCO-2 SCAs are in good agreement with ground-based observations at five high-latitude sites, and OCO-2 SCAs show very close agreement with SCAs calculated for model estimates of XCO2 from the Copernicus Atmosphere Monitoring Services (CAMS) global inversion-optimized greenhouse gas flux model v19r1 and the CarbonTracker2019 model (CT2019B). Model estimates of XCO2 from the GEOS-Chem CO2 simulation version 12.7.2 with underlying biospheric fluxes from CarbonTracker2019 (GC-CT2019) yield SCAs of larger magnitude and spread over a larger range than those from CAMS, CT2019B, or OCO-2; however, GC-CT2019 SCAs still exhibit a very similar spatial distribution across northern high-latitude regions to that from CAMS, CT2019B, and OCO-2. Zones in the Asian boreal forest were found to have exceptionally large SCA and early HDD, and both OCO-2 data and model estimates yield a distinct longitudinal gradient of increasing SCA from west to east across the Eurasian continent. In northern high-latitude regions, spanning latitudes from 47 to 72∘ N, longitudinal gradients in both SCA and HDD are at least as pronounced as latitudinal gradients, suggesting a role for global atmospheric transport patterns in defining spatial distributions of XCO2 seasonality across these regions. GEOS-Chem surface contact tracers show that the largest XCO2 SCAs occur in areas with the greatest contact with land surfaces, integrated over 15–30 d. The correlation of XCO2 SCA with these land surface contact tracers is stronger than the correlation of XCO2 SCA with the SCA of CO2 fluxes or the total annual CO2 flux within each 5∘ latitude by 20∘ longitude zone. This indicates that accumulation of terrestrial CO2 flux during atmospheric transport is a major driver of regional variations in XCO2 SCA.

scholarly journals Seasonality of sea ice controls interannual variability of summertime Ω<sub>A</sub> at the ice shelf in the Eastern Weddell Sea – an ocean acidification sensitivity study

2015 ◽  
Vol 12 (2) ◽  
pp. 1653-1687 ◽  
Author(s):  
A. Weeber ◽  
S. Swart ◽  
P. M. S. Monteiro
Keyword(s):  
Surface Water ◽  
Sea Ice ◽  
Primary Production ◽  
Interannual Variability ◽  
Mixed Layer ◽  
Seasonal Cycle ◽  
Weddell Sea ◽  
Ice Shelf ◽  
Saturation State ◽  
Anthropogenic Co2

Abstract. Increasing anthropogenic CO2 is decreasing surface water aragonite saturation state (ΩA), a growing concern for calcifying Euthecosome pteropods and its wider impact on Antarctic ecosystems. However, our understanding of the seasonal cycle and interannual variability of this vulnerable ecosystem remains limited. This study examines surface water ΩA from four consecutive summers in the Eastern Weddell Gyre (EWG) ice shelf region, and investigates the drivers and the role played by the seasonal cycle in the interannual variability of ΩA. Interannual variability in the seasonal phasing and the rate of summer sea ice thaw was found to be the primary factor explaining interannual variability in surface water ΩA. In "optimal" summers when summer sea ice thaw began in late November/early December (2008/2009 and 2010/2011), the summertime increase in ΩA was found to be 1.02, approximately double that from summers when sea ice thaw was delayed to late December (2009/2010 and 2011/2012). We propose that the two critical climate (physical-biogeochemical) sensitivities for ΩA are the timing and the rate of sea ice thaw, which has a direct impact on the mixed layer and the resulting onset and persistence of phytoplankton blooms. The strength of summertime carbonate saturation depends on seasonal changes of sea ice, stratification and primary production. The sensitivity of surface water biogeochemistry in this region to interannual changes in mixed layer – sea ice processes, suggests that future trends in climate and the seasonal cycle of sea ice, combined with rapidly increasing anthropogenic CO2 will likely be a concern for the Antarctic ice shelf ecosystem within the next few decades. If in the future, primary production is reduced and CO2 increased, our results suggest that in the EWG summertime surface water aragonite undersaturation will emerge by the middle of this century.

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