ERA-interim reanalysis debiased at FLUXNET sites

(preliminary) Exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 sites registered and up to 250 of them sharing data (Free Fair Use dataset). Many modelling groups use the FLUXNET dataset for evaluating ecosystem model's performances but it requires uninterrupted time series for the meteorological variables used as input. Because original in-situ data often contain gaps, from very short (few hours) up to relatively long (some months), we develop a new and robust method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-interim) and high temporal resolution spanning from 1989 to today. These data are however not measured at site level and for this reason a method to downscale and correct the ERA-interim data is needed. We apply this method on the level 4 data (L4) from the LaThuile collection, freely available after registration under a Fair-Use policy. The performances of the developed method vary across sites and are also function of the meteorological variable. On average overall sites, the bias correction leads to cancel from 10% to 36% of the initial mismatch between in-situ and ERA-interim data, depending of the meteorological variable considered. In comparison to the internal variability of the in-situ data, the root mean square error (RMSE) between the in-situ data and the un-biased ERA-I data remains relatively large (on average overall sites, from 27% to 76% of the standard deviation of in-situ data, depending of the meteorological variable considered). The performance of the method remains low for the Wind Speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations.

Landfast sea-ice and platelet-layer thickness and conductivity of Atka Bay, Antarctica, December 2012

Ice shelves strongly impact coastal Antarctic sea-ice and the associated ecosystem through the formation of a sub-sea-ice platelet layer. Although progress has been made in determining and understanding its spatio-temporal variability based on point measurements, an investigation of this phenomenon on a larger scale remains a challenge due to logistical constraints and a lack of suitable methodology. In this study, we applied a laterally-constrained Marquardt-Levenberg inversion to a unique multi-frequency electromagnetic (EM) induction sounding dataset obtained on the landfast sea ice of Atka Bay, eastern Weddell Sea, in 2012. In addition to consistent fast-ice thickness and -conductivities along > 100 km transects; we present the first comprehensive, high resolution platelet-layer thickness and -conductivity dataset recorded on Antarctic sea ice. The reliability of the algorithm was confirmed by using synthetic data, and the inverted platelet-layer thicknesses agreed within the data uncertainty to drill-hole measurements. Ice-volume fractions were calculated from platelet-layer conductivities, revealing that an older and thicker platelet layer is denser and more compacted than a loosely attached, young platelet layer. The overall platelet-layer volume below Atka Bay fast ice suggests that the contribution of ocean/ice-shelf interaction to sea-ice volume in this region is even higher than previously thought. This study also implies that multi-frequency EM induction sounding is an effective approach in determining platelet layer volume on a larger scale than previously feasible. When applied to airborne multi-frequency EM, this method could provide a step towards an Antarctic-wide quantification of ocean/ice-shelf interaction.

Analysis of spatial microbial properties from experimental plots of the Jena experiment (September 2010)

The study was carried out on the main plots (Main Experiment) of a large grassland biodiversity experiment, the Jena Experiment. In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. This data set consists of standard deviation (SD), mean and stability (stab) of soil microbial basal respiration (µl O2/h/g dry soil) and microbial biomass carbon (µg C/g dry soil). Data were derived by taking soil samples and measuring basal and substrate-induced microbial respiration with an oxygen-consumption apparatus. Samples for calculating the spatial stability of soil microbial properties were taken on the 20th of September in 2010. Oxygen consumption of soil microorganisms in fresh soil equivalent to 3.5 g dry weight was measured at 22°C over a period of 24 h. Basal respiration (µlO2/g dry soil/h) was calculated as mean of the oxygen consumption rates of hours 14 to 24 after the start of measurements. Substrate- induced respiration was determined by adding D-glucose to saturate catabolic enzymes of microorganisms according to preliminary studies (4 mg g-1 dry soil solved in 400 µl deionized water). Maximum initial respiratory response (µl O2/g dry soil/ h) was calculated as mean of the lowest three oxygen consumption values within the first 10 h after glucose addition. Microbial biomass carbon (µg C/g dry soil) was calculated as 38 × Maximum initial respiratory response according to prelimiray studies.

Analysis of temporal microbial properties from experimental plots of the Jena experiment (2003-2014)

The study was carried out on the main plots (Main Experiment) of a large grassland biodiversity experiment, the Jena Experiment. In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. This data set consists of standard deviation (SD), mean and stability (stab) of soil microbial basal respiration (µl O2/h/g dry soil) and microbial biomass carbon (µg C/g dry soil). Data were derived by taking soil samples and measuring basal and substrate-induced microbial respiration with an oxygen-consumption apparatus. Samples for calculating the temporal stability were taken every year in May/June from 2003 to 2014, except in 2005. Oxygen consumption of soil microorganisms in fresh soil equivalent to 3.5 g dry weight was measured at 22°C over a period of 24 h. Basal respiration (µlO2/g dry soil/h) was calculated as mean of the oxygen consumption rates of hours 14 to 24 after the start of measurements. Substrate- induced respiration was determined by adding D-glucose to saturate catabolic enzymes of microorganisms according to preliminary studies (4 mg g-1 dry soil solved in 400 µl deionized water). Maximum initial respiratory response (µl O2/g dry soil/h) was calculated as mean of the lowest three oxygen consumption values within the first 10 h after glucose addition. Microbial biomass carbon (µg C/g dry soil) was calculated as 38 × Maximum initial respiratory response according to prelimiray studies.

Compilation of planktonic foraminiferal census counts from the Southern Hemisphere Oceans

We present an improved database of planktonic foraminiferal census counts from the Southern Hemisphere Oceans (SHO) from 15°S to 64°S. The SHO database combines 3 existing databases. Using this SHO database, we investigated dissolution biases that might affect faunal census counts. We suggest a depth/[DCO3]2- threshold of ~3800 m/[DCO3]2- = ~-10 to -5 µmol/kg for the Pacific and Indian Oceans, and ~4000 m/[DCO3]2- = ~0 to 10 µmol/kg for the Atlantic Ocean, under which core-top assemblages can be affected by dissolution and are less reliable for paleo-sea surface temperature (SST) reconstructions. We removed all core-tops beyond these thresholds from the SHO database. This database has 598 core-tops and is able to reconstruct past SST variations from 2° to 25.5°C, with a root mean square error of 1.00°C, for annual temperatures. To inspect dissolution affects SST reconstruction quality, we tested the data base with two "leave-one-out" tests, with and without the deep core-tops. We used this database to reconstruct Summer SST (SSST) over the last 20 ka, using the Modern Analog Technique method, on the Southeast Pacific core MD07-3100. This was compared to the SSST reconstructed using the 3 databases used to compile the SHO database. Thus showing that the reconstruction using the SHO database is more reliable, as its dissimilarity values are the lowest. The most important aspect here is the importance of a bias-free, geographic-rich, database. We leave this dataset open-ended to future additions; the new core-tops must be carefully selected, with their chronological frameworks, and evidence of dissolution assessed.

Diatom abundance in surface sediments of the Southern Ocean

Based on the quantitative analysis of diatom assemblages preserved in 274 surface sediment samples recovered in the Pacific, Atlantic and western Indian sectors of the Southern Ocean we have defined a new reference database for quantitative estimation of late-middle Pleistocene Antarctic sea ice fields using the transfer function technique. The Detrended Canonical Analysis (DCA) of the diatom data set points to a unimodal distribution of the diatom assemblages. Canonical Correspondence Analysis (CCA) indicates that winter sea ice (WSI) but also summer sea surface temperature (SSST) represent the most prominent environmental variables that control the spatial species distribution. To test the applicability of transfer functions for sea ice reconstruction in terms of concentration and occurrence probability we applied four different methods, the Imbrie and Kipp Method (IKM), the Modern Analog Technique (MAT), Weighted Averaging (WA), and Weighted Averaging Partial Least Squares (WAPLS), using logarithm-transformed diatom data and satellite-derived (1981-2010) sea ice data as a reference. The best performance for IKM results was obtained using a subset of 172 samples with 28 diatom taxa/taxa groups, quadratic regression and a three-factor model (IKM-D172/28/3q) resulting in root mean square errors of prediction (RMSEP) of 7.27% and 11.4% for WSI and summer sea ice (SSI) concentration, respectively. MAT estimates were calculated with different numbers of analogs (4, 6) using a 274-sample/28-taxa reference data set (MAT-D274/28/4an, -6an) resulting in RMSEP's ranging from 5.52% (4an) to 5.91% (6an) for WSI as well as 8.93% (4an) to 9.05% (6an) for SSI. WA and WAPLS performed less well with the D274 data set, compared to MAT, achieving WSI concentration RMSEP's of 9.91% with WA and 11.29% with WAPLS, recommending the use of IKM and MAT. The application of IKM and MAT to surface sediment data revealed strong relations to the satellite-derived winter and summer sea ice field. Sea ice reconstructions performed on an Atlantic- and a Pacific Southern Ocean sediment core, both documenting sea ice variability over the past 150,000 years (MIS 1 - MIS 6), resulted in similar glacial/interglacial trends of IKM and MAT-based sea-ice estimates. On the average, however, IKM estimates display smaller WSI and slightly higher SSI concentration and probability at lower variability in comparison with MAT. This pattern is a result of different estimation techniques with integration of WSI and SSI signals in one single factor assemblage by applying IKM and selecting specific single samples, thus keeping close to the original diatom database and included variability, by MAT. In contrast to the estimation of WSI, reconstructions of past SSI variability remains weaker. Combined with diatom-based estimates, the abundance and flux pattern of biogenic opal represents an additional indication for the WSI and SSI extent.