G-force measurements at Mount Nyiragongo

To evaluate the mechanical stress on the volcanic edifice that results from lava lake level variations, we deployed a self-recording, differential capacitance (MEMS Inertial Sensor STMicroelectronics LIS3LV02DQ), 3-axis X6-1A accelerometer (Gulf Coast Data Concepts, LLC) at a distance of ~100m from the center of the Nyiragongo lava lake on freshly erupted lava flows. The device range was used in high (12-bit) resolution mode, which corresponds to a sensitivity of about 1 mg. The device was set to high-sensitivity mode with four additional bits to improve resolution, yet with a much lower signal-noise ratio. Once in position, the accelerometer continuously recorded data for three-day periods in June 2010. The system was oriented so that the X- and Y-axes form a plain parallel to the lava lake. During data collection, we did not attempt to calibrate the precision of the angle because relative G-force measurements were required instead of absolute G-force measurements. To distinguish the tiny accelerations caused by temperature differentials of the atmosphere, from the forces caused by magma movements, the temperature of the X6-1A device was continuously recorded. Temperature variations were corrected for by applying a de-correlation method to the recorded signal. Data was collected at 20 Hz, regrouped into batches that cover 1 hour per observation and associated with one averaged temperature measurement. This method was reproducible because diurnal temperature variations were the main cause for heating and cooling.

Artificial oxygen fluxes measured by the eddy correlation method using stirring-sensitive oxygen microsensor and oxygen optodes in a flume experiment

In the last decade, the aquatic eddy correlation (EC) technique has proven to be a powerful approach for non-invasive measurements of oxygen fluxes across the sediment water interface. Fundamental to the EC approach is the correlation of turbulent velocity and oxygen concentration fluctuations measured with high frequencies in the same sampling volume. Oxygen concentrations are commonly measured with fast responding electrochemical microsensors. However, due to their own oxygen consumption, electrochemical microsensors are sensitive to changes of the diffusive boundary layer surrounding the probe and thus to changes in the ambient flow velocity. The so-called stirring sensitivity of microsensors constitutes an inherent correlation of flow velocity and oxygen sensing and thus an artificial flux which can confound the benthic flux determination. To assess the artificial flux we measured the correlation between the turbulent flow velocity and the signal of oxygen microsensors in a sealed annular flume without any oxygen sinks and sources. Experiments revealed significant correlations, even for sensors designed to have low stirring sensitivities of ~0.7%. The artificial fluxes depended on ambient flow conditions and, counter intuitively, increased at higher velocities because of the nonlinear contribution of turbulent velocity fluctuations. The measured artificial fluxes ranged from 2 - 70 mmol m**-2 d**-1 for weak and very strong turbulent flow, respectively. Further, the stirring sensitivity depended on the sensor orientation towards the flow. Optical microsensors (optodes) that should not exhibit a stirring sensitivity were tested in parallel and did not show any significant correlation between O2 signals and turbulent flow. In conclusion, EC data obtained with electrochemical sensors can be affected by artificial flux and we recommend using optical microsensors in future EC-studies. Flume experiments were conducted in February 2013 at the Institute for Environmental Sciences, University of Koblenz-Landau Landau. Experiments were performed in a closed oval-shaped acrylic glass flume with cross-sectional width of 4 cm and height of 10 cm and total length of 54 cm. The fluid flow was induced by a propeller driven by a motor and mean flow velocities of up to 20 cm s-1 were generated by applying voltages between 0 V and 4 V DC. The flume was completely sealed with an acrylic glass cover. Oxygen sensors were inserted through rubber seal fittings and allowed positioning the sensors with inclinations to the main flow direction of ~60°, ~95° and ~135°. A Clark type electrochemical O2 microsensor with a low stirring sensitivity (0.7%) was tested and a fast-responding needle-type O2 optode (PyroScience GmbH, Germany) was used as reference as optodes should not be stirring sensitive. Instantaneous three-dimensional flow velocities were measured at 7.4 Hz using stereoscopic particle image velocimetry (PIV). The velocity at the sensor tip was extracted. The correlation of the fluctuating O2 sensor signals and the fluctuating velocities was quantified with a cross-correlation analysis. A significant cross-correlation is equivalent to a significant artificial flux. For a total of 18 experiments the flow velocity was adjusted between 1.7 and 19.2 cm s**-1, and 3 different orientations of the electrochemical sensor were tested with inclination angles of ~60°, ~95° and ~135° with respect to the main flow direction. In experiments 16-18, wavelike flow was induced, whereas in all other experiments the motor was driven by constant voltages. In 7 experiments, O2 was additionally measured by optodes. Although performed simultaneously with the electrochemical sensor, optode measurements are listed as separate experiments (denoted by the attached 'op' in the filename), because the velocity time series was extracted at the optode tip, located at a different position in the flume.

Airborne hyperspectral image data of Heron Reef, Australia

This airborne hyperspectral (19 bands) image data of Heron Reef, Great Barrier Reef, Australia is derived from Compact Airborne Spectrographic Imager (CASI) data acquired on 1st and 3rd of July 2002, latitude -23.45, longitude 151.92. Processing and correction to at-surface data was completed by Karen Joyce (Joyce, 2004). Raw imagery consisted several images corresponding to the number of flight paths taken to cover the entire Heron Reef. Spatial resolution is one meter. Radiometric corrections converted the at-sensor digital number values to at surface spectral radiance values using sensor specific calibration coefficients and CSIRO's c-WomBat-c atmospheric correction software. Geometric corrections were done using field collected coordinates of features identified in the image. Projection used was Universal Transverse Mercator Zone 56 South and Datum used was WGS 84. Image data is in TIFF format.

Multi-sensor global compilation of mid-Holocene sea surface temperatures, based on Mg/Ca and alkenone palaeothermometry and reconstructions obtained using planktonic foraminifera and organic-walled dinoflagellate cyst

We present and examine a multi-sensor global compilation of mid-Holocene (MH) sea surface temperatures (SST), based on Mg/Ca and alkenone palaeothermometry and reconstructions obtained using planktonic foraminifera and organic-walled dinoflagellate cyst census counts. We assess the uncertainties originating from using different methodologies and evaluate the potential of MH SST reconstructions as a benchmark for climate-model simulations. The comparison between different analytical approaches (time frame, baseline climate) shows the choice of time window for the MH has a negligible effect on the reconstructed SST pattern, but the choice of baseline climate affects both the magnitude and spatial pattern of the reconstructed SSTs. Comparison of the SST reconstructions made using different sensors shows significant discrepancies at a regional scale, with uncertainties often exceeding the reconstructed SST anomaly. Apparent patterns in SST may largely be a reflection of the use of different sensors in different regions. Overall, the uncertainties associated with the SST reconstructions are generally larger than the MH anomalies. Thus, the SST data currently available cannot serve as a target for benchmarking model simulations.

Photosynthetically Active Radiation (PAR) measurements from a Biospherical Instrument Inc. QCR-2150 surface PAR sensor mounted on a sensor mast during the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set provides continuous measurements made with a Biospherical Instrument Inc. QCR-2150 surface PAR sensor mounted on a sensor mast at the stern of the ship (ca. 8m above deck) and time synchronized with the CTD recording unit. The sensor consists of a cosine collector and was also utilized to correct the CTD PAR sensor data. The dark was computed as the lowest 0.01% voltage of the signal that was found to be very stable (0.00965V) for all the legs except for the 2nd leg of the polar circle where there was no complete night (the manufacturer dark was 0.0097V). The manufacturer calibration slope from 12/ 2012 was used to transform the data to scientific units.

Properties of seawater and particulate matter (fluorescence) from a WETLabs Eco-FL sensor mounted on the continuous surface water sampling system during the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set provides continuous measurements made with a WETLabs Eco-FL sensor mounted on the flowthrough system between June 4th, 2011 and March 30th, 2012. Data was recorded approximately every 10s. Two issues affected the data: 1. Periods when the water 0.2µm filtered water were used as blanks and 2. Periods where fluorescence was affected by non-photochemical quenching (NPQ, chlorophyll fluorescence is reduced when cells are exposed to light, e.g. Falkowski and Raven, 1997). Median data and their standard deviation were binned to 5min bins with period of light/dark indicated by an added variable (so that NPQ affected data could be neglected if the user so chooses). Data was first calibrated using HPLC data collected on the Tara (there were 36 data within 30min of each other). Fewer were available when there was no evident NPQ and the resulting scale factor was 0.0106 mg Chl m-3/count. To increase the calibration match-ups we used the AC-S data which provided a robust estimate of Chlorophyll (e.g. Boss et al., 2013). Scale factor computed over a much larger range of values than HPLC was 0.0088 mg Chl m-3/count (compared to 0.0079 mg Chl m-3/count based on manufacturer). In the archived data the fluorometer data is merged with the TSG, raw data is provided as well as manufacturer calibration constants, blank computed from filtered measurements and chlorophyll calibrated using the AC-S. For a full description of the processing of the Eco-FL please see Taillandier, 2015.

Properties of seawater (partial pressure of carbon dioxide (pCO2)) from a ProOceanus CO2-Pro sensor mounted on the continuous surface water sampling system during the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set provides continuous measurements of partial pressure of carbon dioxide (pCO2), using a ProOceanus CO2-Pro instrument mounted on the flowthrough system. This automatic sensor is fitted with an equilibrator made of gas permeable silicone membrane and an internal detection loop with a non-dispersive infrared detector of PPSystems SBA-4 CO2 analyzer. A zero-CO2 baseline is provided for the subsequent measurements circulating the internal gas through a CO2 absorption chamber containing soda lime or Ascarite. The frequency of this automatic zero point calibration was set to be 24 hours. All data recorded during zeroing processes were discarded with the 15-minute data after each calibration. The output of CO2-Pro is the mole fraction of CO2 in the measured water and the pCO2 is obtained using the measured total pressure of the internal wet gas. The fugacity of CO2 (fCO2) in the surface seawater, whose difference with the atmospheric CO2 fugacity is proportional to the air-sea CO2 fluxes, is obtained by correcting the pCO2 for non-ideal CO2 gas concentration according to Weiss (1974). The fCO2 computed using CO2-Pro measurements was corrected to the sea surface condition by considering the temperature effect on fCO2 (Takahashi et al., 1993). The surface seawater observations that were initially estimated with a 15 seconds frequency were averaged every 5-min cycle. The performance of CO2-Pro was adjusted by comparing the sensor outputs against the thermodynamic carbonate calculation of pCO2 using the carbonic system constants of Millero et al. (2006) from the determinations of total inorganic carbon (CT ) and total alkalinity (AT ) in discrete samples collected at sea surface. AT was determined using an automated open cell potentiometric titration (Haraldsson et al. 1997). CT was determined with an automated coulometric titration (Johnson et al. 1985; 1987), using the MIDSOMMA system (Mintrop, 2005). fCO2 data are flagged according to the WOCE guidelines following Pierrot et al. (2009) identifying recommended values and questionable measurements giving additional information about the reasons of the questionability.