Underway optical chlorophyll-a and turbidity data were collected along the cruise track with Sea-Bird Scientific ECO FLNTU sensors installed within two autonomous measurement containers, as part of the "Reinseewassersystem" (RSWS). The containers measure alternatingly. While one container is measuring, the other one is being cleaned. The boxes switched generally every 12 hours. The water inlet for the RSWS is at about 6.5 m below sea surface. Observed chlorophyll-a and turbidity data were both quality controlled. Analysis of the chlorophyll-a and turbidity data during parallel operation of the sensors in the two boxes showed significant differences between the sensors. The sensors were aligned resulting in consistent chlorophyll-a and turbidity time series. The corrected chlorophyll-a data were calibrated based on chlorophyll-a values from discrete water samples taken from a RSWS water outlet in the hangar. Samples were frozen and measured fluorometrically in the lab. The time series was separated into two sections, coastal and open ocean, which were calibrated independently. The turbidity time series was also compared to suspended particulate matter from water samples, however, correlation was low and therefore the comparison not used for calibrating turbidity. The calibrated chlorophyll-a time series and corrected turbidity time series were compared against Globcolour CHL1 and TSM products, respectively. Details on all quality control steps, the calibration, and the comparison with satellite data can be found in the data processing report. The data set user should keep in mind that some parts of the time series are likely affected by non-photochemical quenching, see data processing report. It was out of the scope of the quality control to flag or correct non-photochemical quenching. The resulting data set contains the original data and corresponding quality flags achieved by the quality control algorithm as well as the calibrated chlorophyll-a and corrected turbidity data with corresponding quality flags. The data source is given through the name of the active container. The data set contains data during transit time and station work. We recommend to use ship's speed to filter for only transit data.
Underway optical chlorophyll-a and turbidity data were collected along the cruise track with Sea-Bird Scientific ECO FLNTU sensors installed within two autonomous measurement systems, called self-cleaning monitoring boxes (SMBs). The SMBs measure alternatingly. While one box is measuring, the other one is being cleaned. The water inlet for the SMBs is at about 4 m below sea surface. Observed chlorophyll-a and turbidity data were both quality controlled and the chlorophyll-a data was additionally calibrated using chlorophyll-a reference data from discrete water samples taken from the CTD water sampler at 10 m depth. Sample chlorophyll-a was determined spectrophotometrically following Jeffrey and Humphrey (1975) as in EPA Method 446. Note that the ship crossed various biogeochemical provinces leading to high variability in the data and, additionally, non-photochemical quenching effects can be observed making it difficult to robustly calibrate the data. A comparison of the calibrated chlorophyll-a with satellite data using the GlobColour CHL1 and CHL2 products is additionally provided. Details on all quality control steps, the calibration, and the comparison with satellite data can be found in the data processing report. The resulting data set contains the original data, the calibrated data (in case of chlorophyll-a) and corresponding quality flags achieved by the quality control algorithm. The data source is given through the name of the active SMB. The data set contains data during transit time and station work. We recommend to use ship's speed to filter for only transit data.
The effects of a phytoplankton bloom and photobleaching on colored dissolved organic matter (CDOM) in the sea-surface microlayer (SML) and the underlying water (ULW) were studied in a month-long mesocosm study, in May and June of 2023, at the Institute for Chemistry and Biology of the Marine Environment (ICBM) in Wilhelmshaven, Germany. The mesocosm study was conducted by the DFG research group BASS (Biogeochemical processes and Air–sea exchange in the Sea-Surface microlayer, Bibi et al., 2025) in the Sea Surface Facility (SURF) of the ICBM. The facility contains an 8 m × 1.5 m × 0.8 m large outdoor basin with a retractable roof, which was closed at night and during rain events. The basin was filled with North Sea water from the adjacent Jade Bay. Homogeneity of the ULW in the basin was achieved by constant mixing of the water column. The daily SML and ULW samples were collected alternating in the morning, about 1 h after sunrise, and in the afternoon, about 10 h after sunrise. The alternation of sampling times intended to capture a potential effect of sun-exposure duration on DOM transformations and elucidated the day and night variability of the layers. The SML was collected via glass plate sampling (Cunliffe and Wurl, 2014). The ULW was sampled via a submerged tube and a connected syringe suction system in 0.4 m depth. The removed sample volume was refilled with Jade Bay water every day. SML and ULW samples were filtered through pre-flushed 0.7 µm Whatman GF/F and 0.2 nucleopore filters into clear 40 ml SUPELCO bottles. These bottles were acid-washed twice and combusted at 500 °C for 5 h. The samples were stored dark and at 4 °C and measured within a few months of the study. FDOM was measured using a Aqualog fluorescence spectrometer (Horiba Scientific, Japan) with 10 seconds integration time and high gain of the CCD (charge-coupled device) sensor within an excitation range from 240 to 500 nm, and an emission range from 209.15 to 618.53 nm. The Aqualog measures fluorescence as well as absorption. The resulting data includes an excitation-emission-matrix (EEM) of the blank (MilliQ Starna cuvette), an EEM of the sample, and the absorption values of the sample. The raw exported Aqualog data was corrected for errors and lamp shifts. The corrected EEM data is then decomposed by PARAFAC (Murphy et al., 2013) for its underlying fluorophore components. Before running the PARAFAC routine, the corrected data needed to undergo a correction process by subtracting the blank from the sample EEM and canceling the influences of the inner-filter effect (IFE, Parker & Rees, 1962; Kothawala et al., 2013). The fluorescence intensity of the IFE-corrected EEM is calibrated by using the Raman scatter peak of water (Lawaetz & Stedmon, 2009). For PARAFAC the corrected data was processed using the drEEM and NWAY toolbox (version 0.6.5; Murphy et al., 2013) in MATLAB (R2020b). A 4-component model was validated with the validation style S4C6T3 for the split half analysis with nonnegativity constraints and 1-8e as the convergence criteria with 50 random starts and a maximum number of 2500 iterations. The resulting final model had a core consistency of 82.04 and the explained percentage was 99.54%. Furthermore, four fluorescence indices were calculated from the corrected EEM data (HIX – Humification index, Zsolnay et al., 1999; BIX – Biological index, Huguet et al., 2009; REPIX – Recently produced index, Parlanti et al., 2000, Drozdowska et al., 2015; ARIX, Murphy, 2025).
Reference measurements of surface waters were collected during two RV Otzum cruises along the river Elbe in 2012 and 2013 (Ot2012_05: 21.-24.05.; Ot2013_05: 27.-30.05.2013). Temperature [°C], salinity, turbidity [NTU], and chlorophyll from fluorescence [µg/L] were measured by a PocketFerrybox System (values given to the time of sampling). Water samples were taken from the outlet of the system. Suspended particular matter (SPM) and chlorophyll a (Chl a) were filtered onboard on glas fibre filters (GFF, 47mm, 0,7 µm) and frozen at -25°C and -80°C immediately after sampling. Values were determined in the lab after the cruise within 2 months, for SPM via gravimetric analysis (IOCC recommendations) and for Chl a according to EPA Method 445. Water clarity and color were observed using a white Secchi disc with a diameter of 30 cm and a Forel-Ule color scale. The Secchi depth (SD) was recorded as a relative measure of water clarity at each in situ station during day time. At half SD the apparent color of the water above the submerged Secchi disc was determined using the Forel-Ule color scale. A Forel-Ule color scale is a classic tool used to differentiate the percieved color of water based on a scale from 1 (indigo blue) to 21 (cola brown). The measurements were conducted as recommended in literature (Garaba and Zielinski, 2015; Wernand, 2011; Wernand and van der Woerd, 2010). Measurements were part of the project DOMsense (01.11.2011 - 31.05.2014, KF2866501DF1)
Im Teilvorhaben 3 wird im Modul 5 (Flächendeckendes satellitengestütztes Monitoring der Wachstumsreaktion) ein satellitenbasiertes räumliches Monitoring der Wachstumsreaktion der Bäume für die Testgebiete entwickelt. Als Wachstumsreaktion wird die Veränderung des Saftflusses sowie des Dickenwachstums als Reaktion auf extreme Hitze- und Trockenperioden definiert. Beide Variablen werden mittels DHC-Stationen in situ gemessen und durch die Kombination mit Satellitendaten in die Fläche überführt. Als Prädiktoren werden neuartige Daten der spektral hochaufgelösten ECOSTRESS (IR hyperspektral), OCO-3 und DESIS (Hyperspektralsensor) herangezogen, die alle auf der ISS installiert und damit optimal für eine solche Datenkombination geeignet sind. Die Daten der punktuellen DHC-Stationen werden verwendet, um maschinelle Lernmodelle auf der Basis der spektral hochaufgelösten neuen Fernerkundungsdaten unter normalen und extremen Klimabedingungen zu trainieren. Die Modelle können auf das Prädiktorgitter angewendet werden, sodass die Zielvariablen räumlich modelliert werden können. Aufgrund der schlechten zeitlichen Auflösung werden diese Daten wiederum als Prädiktoren verwendet, um die Zielvariablen auf konventionelle, zeitlich höher aufgelöste (Sentinel, MODIS) und Kronen auflösende Systeme (Planet) zu transferieren. Damit ist ein räumliches Monitoring unter verschiedenen Klimabedingungen möglich. ECOSTRESS liefert gegitterte Prädiktorvariablen zur Verdunstung, zum Evaporative Stress Index sowie zur Water Use Efficiency in 30 bis 70 m Auflösung, die mit DHC-Messungen des Saftflusses kombiniert werden. OCO-3 liefert Informationen zur fotosynthetischen Aktivität (SIF: solar-induced chlorophyll fluorescence) in etwa 2 km Auflösung, die mit den DHC-Messungen zum Dickenwachstum kombiniert werden. DESIS liefert hyperspektrale Daten in 30 m Auflösung und wird v.a. für die Erhöhung der räumlichen Auflösung der OCO-3 Daten verwendet.
Gletscher sind bedeutende Speicher organischen Kohlenstoffs (OC) und tragen zum Kohlenstofffluss vom Festland zum Meer bei. Aufgrund des Klimawandels wird eine Intensivierung dieser Flüsse erwartet. Der Export von OC aus Gletschern wurde weltweit in verschiedenen Regionen quantifiziert, trotzdem liegen keine vergleichbaren Daten für Island vor, obwohl sich dort die größte europäische außerpolare Eiskappe befindet. Um die globalen Prognosen der glazialen Kohlenstofffreisetzung zu verbessern, ist es das Ziel dieses Pilotprojektes, den Export von gelöstem und partikulärem organischen Kohlenstoff (DOC, POC) aus Islands Gletschern erstmalig zu quantifizieren und neue Kooperationen mit isländischen Wissenschaftler/innen für gemeinsame zukünftige Forschungsprojekte aufzubauen. Hierzu werden 4 Feldkampagnen zu unterschiedlichen Jahreszeiten sowie Treffen mit isländischen Kollegen/innen durchgeführt. In jeder Feldkampagne werden von 23 Gletschern der Eiskappen Vatnajökull, Langjökull, Hofsjökull, Myrdalsjökull und Snaeellsjökull Eisproben entnommen, um die biogeochemische Diversität des glazialen OC zu charakterisieren sowie dessen Export in Verbindung mit Massenbilanzen zu quantifizieren. In Gletscherbächen werden Wasserproben entnommen, um den Austrag von OC direkt am Gletschertor zu bestimmen sowie die Kohlenstoffflüsse entlang von 6 Gletscherbächen mit unterschiedlicher Länge (2 km bis 130 km) beginnend am Gletschertor bis zur Mündung zu untersuchen. Wie sich der Gletscherrückgang langfristig auf ein Gletscherbachökosystem auswirkt, wird durch die taxonomische Bestimmung von Makroinvertebraten im Vergleich zur Bestimmung von Prof. Gíslason aus dem Jahre 1997 beurteilt. Gleichzeitig werden in diesem Gletscherbach Wasserproben zum eDNA-Barcoding entnommen, um eine rasche und gering invasive Methode zur laufenden Beobachtung des zukünftigen Einflusses der Gletscherrückgang zu entwickeln. Vor Ort werden Wassertemperatur, elektr. Leitfähigkeit, pH-Wert, gelöster Sauerstoff, Trübung und Chlorophyll alpha gemessen. Innovative Labormethoden (HPLC, DNA-Barcoding, Picarro, GC, TOC) werden zur Analyse des OC im Eis und Wasser (DOC, DIC, POC, Fluoreszenz, Absorption), der Nährstoffe (P-PO4, N-NO3, N-NO2, N-NH4), stabiler Isotope (18O, 2H), Chlorophyll alpha, CO2 und aquatischen Organismen eingesetzt. Die Anwendung statistischer Methoden (Faktorenanalyse, Hauptkomponentenanalyse) basierend auf Anregungs- und Emissionsmatrizen erlauben die Quellen des OC im Gletschereis sowie -schmelzwasser zu bestimmen und die räumliche Vielfalt des OC zu erklären. Das gewonnene Wissen wird zur Verbesserung globaler Prognosen glazialer Kohlenstofffreisetzung beitragen sowie einen intensiven Einblick in das glaziale Ökosystem geben. Für die antragstellenden Nachwuchswissenschaftler/innen entstehen vielversprechende Kooperationen mit isländischen Wissenschaftlern/innen, fokussierend auf die zeitlichen sowie räuml. Aspekte der glazialen Kohlenstoffflüsse sowie das Ökosystem Gletscher
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