A reassessment of the discrepancies in the annual variation of δD-H₂O in the tropical lower stratosphere between the MIPAS and ACE-FTS satellite data sets

The annual variation of δD in the tropical lower stratosphere is a critical indicator for the relative importance of different processes contributing to the transport of water vapour through the cold tropical tropopause region into the stratosphere. Distinct observational discrepancies of the δD annual variation were visible in the works of Steinwagner et al. (2010) and Randel et al. (2012). Steinwagner et al. (2010) analysed MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) observations retrieved with the IMK/IAA (Institut für Meteorologie und Klimaforschung in Karlsruhe, Germany, in collaboration with the Instituto de Astrofísica de Andalucía in Granada, Spain) processor, while Randel et al. (2012) focused on ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. Here we reassess the discrepancies based on newer MIPAS (IMK/IAA) and ACE-FTS data sets, also showing for completeness results from SMR (Sub-Millimetre Radiometer) observations and a ECHAM/MESSy (European Centre for Medium-Range Weather Forecasts Hamburg and Modular Earth Submodel System) Atmospheric Chemistry (EMAC) simulation (Eichinger et al., 2015b). Similar to the old analyses, the MIPAS data set yields a pronounced annual variation (maximum about 75 ‰), while that derived from the ACE-FTS data set is rather weak (maximum about 25 ‰). While all data sets exhibit the phase progression typical for the tape recorder, the annual maximum in the ACE-FTS data set precedes that in the MIPAS data set by 2 to 3 months. We critically consider several possible reasons for the observed discrepancies, focusing primarily on the MIPAS data set. We show that the δD annual variation in the MIPAS data up to an altitude of 40 hPa is substantially impacted by a “start altitude effect”, i.e. dependency between the lowermost altitude where MIPAS retrievals are possible and retrieved data at higher altitudes. In itself this effect does not explain the differences with the ACE-FTS data. In addition, there is a mismatch in the vertical resolution of the MIPAS HDO and H2O data (being consistently better for HDO), which actually results in an artificial tape-recorder-like signal in δD. Considering these MIPAS characteristics largely removes any discrepancies between the MIPAS and ACE-FTS data sets and shows that the MIPAS data are consistent with a δD tape recorder signal with an amplitude of about 25 ‰ in the lowermost stratosphere

An Analysis of Soil Respiration across Northern Hemisphere Temperate Ecosystems

Over two-thirds of terrestrial carbon is stored belowground and a significant amount of atmospheric CO₂ is respired by roots and microbes in soils. For this analysis, soil respiration (Rs) data were assembled from 31 AmeriFlux and CarboEurope sites representing deciduous broadleaf, evergreen needleleaf, grasslands, mixed deciduous/evergreen and woodland/savanna ecosystem types. Lowest to highest rates of soil respiration averaged over the growing season were grassland and woodland/savanna &lt deciduous broadleaf forests &lt evergreen needleleaf, mixed deciduous/evergreen forests with growing season soil respiration significantly different between forested and non-forested biomes (p &lt 0.001). Timing of peak respiration rates during the growing season varied from March/April in grasslands to July-September for all other biomes. Biomes with overall strongest relationship between soil respiration and soil temperature were from the deciduous and mixed forests (R⁲ ≥ 0.65). Maximum soil respiration was weakly related to maximum fine root biomass (R⁲ = 0.28) and positively related to the previous years' annual litterfall (R⁲ = 0.46). Published rates of annual soil respiration were linearly related to LAI and fine root carbon (R⁲ = 0.48, 0.47), as well as net primary production (NPP) (R⁲ = 0.44). At 10 sites, maximum growing season Rs was weakly correlated with annual GPP estimated from eddy covariance towersites (R⁲ = 0.29; p &lt 0.05), and annual soil respiration and total growing season Rs were not correlated with annual GPP (p &gt 0.1). Yet, previous studies indicate correlations on shorter time scales within site (e.g., weekly, monthly). Estimates of annual GPP from the Biome-BGC model were strongly correlated with observed annual estimates of soil respiration for six sites (R⁲ = 0.84; p &lt 0.01). Correlations from observations of Rs with NPP, LAI, fine root biomass and litterfall relate above and belowground inputs to labile pools that are available for decomposition. Our results suggest that simple empirical relationships with temperature and/or moisture that may be robust at individual sites may not be adequate to characterize soil CO₂ effluxes across space and time, agreeing with other multi-site studies. Information is needed on the timing and phenological controls of substrate availability (e.g., fine roots, LAI) and inputs (e.g., root turnover, litterfall) to improve our ability to accurately quantify the relationships between soil CO₂ effluxes and carbon substrate storage