Abstract: Combined measurements of δ18O, δ17O, and δD in ice cores, leading to d excess and 17O excess, are expected to provide new constraints on the water cycle and past climates. We explore different processes, both in the source regions and during the poleward transport, that could explain the 17O excess increase by 20 per meg observed from the Last Glacial Maximum (LGM) to Early Holocene (EH) at the Vostok station. Using a single-column model over tropical and subtropical oceans, we show that the relative humidity at the surface is the main factor controlling 17O excess in source regions. Then, using a Rayleigh-type model, we show that the 17O excess signal from the source region is preserved in the polar snowfall, contrary to d excess. Evaporative recharge over mid and high latitudes and δ18O seasonality in polar regions can also affect the Vostok 17O excess but cannot account for most of the 20 per meg deglacial increase from LGM to EH. On the other hand, a decrease of the relative humidity at the surface (rhs) by 8 to 22% would explain the observed change in 17O excess. Such a change would not necessarily be incompatible with a nearly unchanged boundary layer relative humidity, if the surface thermodynamic disequilibrium decreased by 4C. Such a change in rhs would affect source and polar temperatures reconstructions from δ18O and d excess measurements, strengthening the interest of 17O excess measurements to better constrain such changes.

Abstract: We demonstrate the effect of an ecosystem differentiated insulation by snow on the soil thermal regime and on the terrestrial soil carbon distribution in the pan-Arctic area. This is done by means of a sensitivity study performed with the land surface model ORCHIDEE, which furthermore provides a first quantification of this effect. Based on field campaigns reporting higher thermal conductivities and densities for the tundra snowpack than for taiga snow, two distributions of near-equilibrium soil carbon stocks are computed, one relying on uniform snow thermal properties and the other using ecosystem-differentiated snow thermal properties. Those modeled distributions strongly depend on soil temperature through decomposition processes. Considering higher insulation by snow in taiga areas induces warmer soil temperatures by up to 12 K in winter at 50 cm depth. This warmer soil signal persists over summer with a temperature difference of up to 4 K at 50 cm depth, especially in areas exhibiting a thick, enduring snow cover. These thermal changes have implications on the modeled soil carbon stocks, which are reduced by 8% in the pan-Arctic continental area when the vegetation-induced variations of snow thermal properties are accounted for. This is the result of diverse and spatially heterogeneous ecosystem processes: where higher soil temperatures lift nitrogen limitation on plant productivity, tree plant functional types thrive whereas light limitation and enhanced water stress are the new constrains on lower vegetation, resulting in a reduced net productivity at the pan-Arctic scale. Concomitantly, higher soil temperatures yield increased respiration rates (+22% over the study area) and result in reduced permafrost extent and deeper active layers which expose greater volumes of soil to microbial decomposition. The three effects combine to produce lower soil carbon stocks in the pan-Arctic terrestrial area. Our study highlights the role of snow in combination with vegetation in shaping the distribution of soil carbon and permafrost at high latitudes.

Abstract: Seasonal and interannual variability in atmospheric carbon dioxide (CO2) concentrations was simulated using fluxes from fossil fuel, ocean and terrestrial biogeochemical models, and a tracer transport model with time-varying winds. The atmospheric CO2 variability resulting from these surface fluxes was compared to observations from 89 GLOBALVIEW monitoring stations. At northern hemisphere stations, the model simulations captured most of the observed seasonal cycle in atmospheric CO2, with the land tracer accounting for the majority of the signal. The ocean tracer was 3–6 months out of phase with the observed cycle at these stations and had a seasonal amplitude only ~10% on average of observed. Model and observed interannual CO2 growth anomalies were only moderately well correlated in the northern hemisphere (R ~ 0.4–0.8), and more poorly correlated in the southern hemisphere (R < 0.6). Land dominated the interannual variability (IAV) in the northern hemisphere, and biomass burning in particular accounted for much of the strong positive CO2 growth anomaly observed during the 1997–1998 El Nio event. The signals in atmospheric CO2 from the terrestrial biosphere extended throughout the southern hemisphere, but oceanic fluxes also exerted a strong influence there, accounting for roughly half of the IAV at many extratropical stations. However, the modeled ocean tracer was generally uncorrelated with observations in either hemisphere from 1979–2004, except during the weak El Nio/post-Pinatubo period of the early 1990s. During that time, model results suggested that the ocean may have accounted for 20–25% of the observed slowdown in the atmospheric CO2 growth rate.

Abstract: Interannually varying net carbon exchange fluxes from the TransCom 3 Level 2 Atmospheric Inversion Intercomparison Experiment are presented for the 1980 to 2005 time period. The fluxes represent the model mean, net carbon exchange for 11 land and 11 ocean regions after subtraction of fossil fuel CO2 emissions. Both aggregated regional totals and the individual regional estimates are accompanied by a model uncertainty and model spread. We find that interannual variability is larger on the land than the ocean, with total land exchange correlated to the timing of both El Nio/Southern Oscillation (ENSO) as well as the eruption of Mt. Pinatubo. The post-Pinatubo negative flux anomaly is evident across much of the tropical and northern extratropical land regions. In the oceans, the tropics tend to exhibit the greatest level of interannual variability, while on land, the interannual variability is slightly greater in the tropics and northern extratropics. The interannual variation in carbon flux estimates aggregated by land and ocean across latitudinal bands remains consistent across eight different CO2 observing networks. The interannual variation in carbon flux estimates for individual flux regions remains mostly consistent across the individual observing networks. At all scales, there is considerable consistency in the interannual variations among the 13 participating model groups. Finally, consistent with other studies using different techniques, we find a considerable positive net carbon flux anomaly in the tropical land during the period of the large ENSO in 1997/1998 which is evident in the Tropical Asia, Temperate Asia, Northern African, and Southern Africa land regions. Negative anomalies are estimated for the East Pacific Ocean and South Pacific Ocean regions. Earlier ENSO events of the 1980s are most evident in southern land positive flux anomalies.

Abstract: This paper demonstrates an inversion of surface CO2 fluxes using concentrations derived from assimilation of satellite radiances. Radiances come from the Atmospheric Infrared Sounder (AIRS) and are assimilated within the system of the European Centre for Medium-Range Weather Forecasts. We evaluate the quality of the inverted fluxes by comparing simulated concentrations with independent airborne measurements. As a benchmark we use an inversion based on surface flask measurements and another using only the global concentration trend. We show that the AIRS-based inversion is able to improve the match to the independent data compared to the prior estimate but that it usually performs worse than either the flask-based or trend-based inversion.