Downwelling solar irradiance, upwelling solar radiance, sky leaving radiance, and cloud cover observed during ARCHEMHAB study (on Maria S. Merian Leg MSM21/3) from 2012-07-26 to 2012-08-10

The need to obtain ocean color essential climate variables (OC-ECVs) using hyperspectral technology has gained increased interest in recent years. Assessing ocean color on a large scale in high latitude environments using satellite remote sensing is constrained by polar environmental conditions. Nevertheless, on a small scale we can assess ocean color using above-water and in-water remote sensing. Unfortunately, above-water remote sensing can only determine apparent optical properties leaving the sea surface and is susceptible to near surface environmental conditions for example sky and sunglint. Consequently, we have to rely on accurate in-water remote sensing as it can provide both synoptic inherent and apparent optical properties of seawater. We use normalized water leaving radiance LWN or the equivalent remote sensing reflectance RRS from 27 stations to compare the differences in above-water and in-water OC-ECVs. Analysis of above-water and in-water RRS spectra provided very good match-ups (R2 > 0.97, MSE<1.8*10**-7) for all stations. The unbiased percent differences (UPD) between above-water and in-water approaches were determined at common OC-ECVs spectral bands (410, 440, 490, 510 and 555) nm and the classic band ratio (490/555) nm. The spectral average UPD ranged (5 - 110) % and band ratio UPD ranged (0 - 12) %, the latter showing that the 5% uncertainty threshold for ocean color radiometric products is attainable. UPD analysis of these stations West of Greenland, Labrador Sea, Denmark Strait and West of Iceland also suggests that the differences observed are likely a result of environmental and instrumental perturbations.

Crete fault scarp point cloud data

This paper assesses the along strike variation of active bedrock fault scarps using long range terrestrial laser scanning (t-LiDAR) data in order to determine the distribution behaviour of scarp height and the subsequently calculate long term throw-rates. Five faults on Cretewhich display spectacular limestone fault scarps have been studied using high resolution digital elevation model (HRDEM) data. We scanned several hundred square metres of the fault system including the footwall, fault scarp and hanging wall of the investigated fault segment. The vertical displacement and the dip of the scarp were extracted every metre along the strike of the detected fault segment based on the processed HRDEM. The scarp variability was analysed by using statistical and morphological methods. The analysis was done in a geographical information system (GIS) environment. Results show a normal distribution for the scanned fault scarp's vertical displacement. Based on these facts, the mean value of height was chosen to define the authentic vertical displacement. Consequently the scarp can be divided into above, below and within the range of mean (within one standard deviation) and quantify the modifications of vertical displacement. Therefore, the fault segment can be subdivided into areas which are influenced by external modification like erosion and sedimentation processes. Moreover, to describe and measure the variability of vertical displacement along strike the fault, the semi-variance was calculated with the variogram method. This method is used to determine how much influence the external processes have had on the vertical displacement. By combining of morphological and statistical results, the fault can be subdivided into areas with high external influences and areas with authentic fault scarps, which have little or no external influences. This subdivision is necessary for long term throw-rate calculations, because without this differentiation the calculated rates would be misleading and the activity of a fault would be incorrectly assessed with significant implications for seismic hazard assessment since fault slip rate data govern the earthquake recurrence. Furthermore, by using this workflow areas with minimal external influences can be determined, not only for throw-rate calculations, but also for determining samples sites for absolute dating techniques such as cosmogenic nuclide dating. The main outcomes of this study include: i) there is no direct correlation between the fault's mean vertical displacement and dip (R² less than 0.31); ii) without subdividing the scanned scarp into areas with differing amounts of external influences, the along strike variability of vertical displacement is ±35%; iii) when the scanned scarp is subdivided the variation of the vertical displacement of the authentic scarp (exposed by earthquakes only) is in a range of ±6% (the varies depending on the fault from 7 to 12%); iv) the calculation of the long term throw-rate (since 13 ka) for four scarps in Crete using the authentic vertical displacement is 0.35 ± 0.04 mm/yr at Kastelli 1, 0.31 ± 0.01 mm/yr at Kastelli 2, 0.85 ± 0.06 mm/yr at the Asomatos fault (Sellia) and 0.55 ± 0.05 mm/yr at the Lastros fault.

Stable Water Isotopologue data collected during HCCT-2010

Cloud samples for the isotopic analysis were collected in the framework of the Hill Cap Cloud Thuringia 2010 (HCCT-2010) campaign on Schmücke (50° 39'N/ 10° 46'E, 937 m a.s.l.; Germany) in September and October 2010 with a three-stage Caltech Active Strand Cloudwater Collector (CASCC) during 13 different cloud events with a temporal resolution of 1 to 3 hours. In a first step, we ensured that no additional fractionation occurred during sampling with the CASCC. The d values of the three sizes classes of the CASCC (4 µm to 16 µm, 16 µm to 22 µm and >22 µm) did not differ significantly, revealing that the cloud droplets of different sizes quickly equilibrate their delta value with the one of the surrounding vapor. delta values in the cloud droplets varied from -77 per mil to -15 per mil in d2H and from -12.1 per mil to -3.9 per mil in d18O and were fitted by d2H =7.8*d18O +13*10**-3. delta values decreased with temperature as well as towards the end of the campaign, representing a seasonal trend which is known from d values in precipitation. The deuterium excess of the cloud samples was generally higher than the Local Meteoric Water Line of the closest GNIP (Global Network of Isotopes in Precipitation) station. Rain decreases its deuterium excess during falling through an unsaturated air column, while the cloud droplets conserve the deuterium excess of the initial evaporation and thus have been found to be a good indicator for the airmass source region: higher deuterium excess was measured for polar air masses and lower deuterium excess for Mediterranean air masses. Changes in d values during one cloud event were up to 3.6 per mil (d2H) and 0.23 per mil (d18O), except for frontal passages, which were associated with increases of ~6 per mil per hour (d2H) and ~0.6 per mil per hour (d18O). Using a box model, we showed that the influence of condensation only was able to explain the variation in the isotope signal of two cloud passages. Consequently, we deduced that the water vapor "feeding" the cloud advected the measured changes. A trajectory analysis and moisture source diagnostic revealed that it is very likely that the variations were either related to rain out along the trajectories or to meteorological changes in the moisture source region. This was the first study using stable water isotopologues in cloud water manifesting their potential in the context of atmospheric water vapor circulation.

Platinum-group element abundances in background samples and the K-T boundary interval from DSDP Hole 91-596 (Table 2)

New data on Ru/Ir abundance ratios are presented for nonmarine (Hell Creek, Montana; Frenchman River, Saskatchewan) and marine Cretaceous-Tertiary boundary sites (Brazos River, Texas; Beloc, Haiti; DSDP 577 and DSDP 596). The Ru/Ir ratio varies from 0.5 to 1 within 4000 km of Chicxulub and increases to 2-3 at paleodistances (65 Ma) of up to 12,000 km from the impact site. For CI chondrites, Ru/Ir = 1.5. A ballistic model of ejecta cloud cooling and expansion, which employs the available vapor-pressure versus temperature data for Ru and It, predicts qualitatively similar global variation in the Ru/Ir ratio but by only a factor of 1.5. We infer that several other factors, such as remobilization of PGE during diagenesis, preferential oxidation of Ru, condensation kinetics and atmospheric chemical and circulation processes, may account for the observed larger Ru/Ir variation.

Mesocosm experiment Cape Verde 2012: Environmental conditions (PAR, cloud cover, pump)

Two 7-day mesocosm experiments were conducted in October 2012 at the Instituto Nacional de Desenvolvimento das Pescas (INDP), Mindelo, Cape Verde. Surface water was collected at night before the start of the respective experiment with RV Islândia south of São Vicente (16°44.4'N, 25°09.4'W) and transported to shore using four 600L food safe intermediate bulk containers. Sixteen mesocosm bags were distributed in four flow-through water baths and shaded with blue, transparent lids to approximately 20% of surface irradiation. Mesocosm bags were filled from the containers by gravity, using a submerged hose to minimize bubbles. The accurate volume inside the individual bags was calculated after addition of 1.5 mmol silicate and measuring the resulting silicate concentration. The volume ranged from 105.5 to 145 L. The experimental manipulation comprised addition of different amounts of inorganic N and P. In the first experiment, the P supply was changed at constant N supply in thirteen of the sixteen units, while in the second experiment the N supply was changed at constant P supply in twelve of the sixteen units. In addition to this, "cornerpoints" were chosen that were repeated during both experiments. Four cornerpoints should have been repeated, but setting the nutrient levels in one mesocosm was not succesfull and therefore this mesocosm also was set at the center point conditions. Experimental treatments were evenly distributed between the four water baths. Initial sampling of the mesocosms on day 1 of each run was conducted between 9:45 and 11:30. After nutrient manipulation, sampling was conducted on a daily basis between 09:00 and 10:30 for days 2 to 8.