Das aktuelle Klima der Erde verändert sich schneller, als von den meisten wissenschaftlichen Prognosen vorhergesagt wurde. Dabei erwärmen sich die Polargebiete schnellsten von allen Regionen der Erde. Die Polargebiete haben auch starke globale Auswirkungen auf das Erdklima und beeinflussen daher das Leben und die Lebensgrundlagen auf der ganzen Welt. Trotz der großen Fortschritte der Polarforschung der letzten Jahre gibt es nach wie vor schlecht verstandene Prozesse; einer davon ist die Aerosol-Wolke-Klima-Wechselwirkung, die daher auch nicht zufriedenstellend modelliert werden können. Wolken und deren Wechselwirkungen im Klimasystem sind eine der schwierigsten Komponenten bei der Modellierung, insbesondere in den Polarregionen, da es dort besonders schwierig ist, qualitativ hochwertige Messungen zu erhalten. Die Verfügbarkeit hochwertiger Messungen ist daher von entscheidender Bedeutung, um die zugrunde liegenden Prozesse zu verstehen und in Modelle integrieren zu können. Im ersten Teil des hier vorgeschlagenen Projekts schlagen wir, d.h. TROPOS, vor, die bestehenden Aerosolmessungen an der Neumayer III-Station um in-situ Wolkenkondensationskern- (CCN) und Eiskeim- (INP) Messungen zu erweitern für einen Zeitraum von fast zwei Jahren. Die erfassten Daten wie Anzahl der Konzentrationen, Hygroskopizität, INP-Gefrierspektren usw. werden mit meteorologischen Informationen (z.B. Rückwärtstrajektorien) und Informationen über die chemische Zusammensetzung der vorherrschenden Aerosolpartikel verknüpft, um Quellen für INP und CCN über den gesamten Jahreszyklus zu identifizieren. In einem optionalen dritten Jahr wollen wir die Ergebnisse der südlichen Hemisphäre mit den TROPOS-Langzeitmessungen des CCN und INP aus der Arktis (Villum Research Station) vergleichen, welche uns im Rahmen dieses Projekts von DFG-finanzierten TR 172, AC3, Projekt B04 zur Verfügung stehen werden. Ein Ergebnis des beantragten Projekts wird ein tieferes Verständnis dafür sein, welche Prozesse die CCN- und INP-Population in hohen Breiten dominieren. Die im Rahmen des vorliegenden Projekts gesammelten quantitativen Informationen über CCN und INP in hohen Breiten werden öffentlich zugänglich veröffentlicht, z.B. für die Evaluierung globaler Modelle und Satellitenretrievals.
During cruise HE644 (joint campaign of MS FRITZ REUTER and RV HEINCKE), Lagrangian surface drifters (Meyerjürgens et al., 2019; Deyle et al., 2024) were deployed from MS FRITZ REUTER, following the near-surface water motion, therefore allowing for observations within a moving water mass over extended periods with minimal disturbance to the surrounding water. Coordinates of the drifter position were transmitted by a GPS satellite tracker (inReach® Messenger from Garmin Ltd.) at two-minute intervals. Position data was processed after Deyle et al. (2024) and is available on minutely resolution in this dataset. For original trajectories see "<DOI>". In addition, the drifters were equipped with (down to 1.75 m depth) instrument chains including temperature and lightweight CTD (conductivity, temperature, depth) sensors. Depth in water was only recorded by RBRbrevio³ sensors, for others the depth was measured during sensor chain preparation and saved in the data array as fixed depth. The in situ temperature was recorded at up to six different depths using RBRsolo³, RBRbrevio³ (both sample frequency 1-2 Hz) and Aqua TROLL® 100 sensors (sample frequency 1 min-1). Conductivity was measured at up to three different depths, using RBRbrevio³ and Aqua TROLL® 100 sensors. RBR sensors were calibrated to a measurement uncertainty of ± 0.002 °C and ± 0.003 mS cm-1, whereas the TROLL sensors have a measurement uncertainty of ± 0.1 °C and ± 0.5%. For details on the sensor data processing see the appropriate processing report.
Derzeitige radar-basierte Nowcastingverfahren basieren auf der Annahme, dass die zeitliche Entwicklung von Hagelereignissen in erster Linie durch Advektionsvorgänge gesteuert ist; die relevanten physikalischen Prozesse, die für die Entstehung und das Größenwachstum von Hagel entscheidend sind, bleiben dabei unberücksichtigt. In Verbindung mit der komplexen internen Struktur und Dynamik von Hagelstürmen ergeben sich daraus große Unsicherheiten bei der Vorhersage der Hagelgrößenverteilung und der von Hagel betroffenen Fläche am Boden. Das Ziel des Projekts LIFT (Large Hail Formation and Trajectories) ist es, die Hagelentstehung und Hageltrajektorien besser zu verstehen, um daraus als wichtige Komponenten eines physikalisch-basierten Nowcastings erstmals ein radar-basiertes Verfahren für das Hagelwachstums zu entwickeln. Zu diesem Zweck wird im Rahmen von LIFT eine Messkampagne Süddeutschland durchgeführt, wo die größte Hagelwahrscheinlichkeit in Deutschland auf vielfältige Beobachtungssysteme trifft, die im Rahmen der Messkampagne Swabian MOSES mit einem dichten Netzwerk betrieben werden. Zum ersten Mal werden im Rahmen von LIFT moderne Radargeräte, In-situ Messgeräte, Fotogrammetrie und numerische Modellierung synergistisch kombiniert und ein umfassender Datensatz zur Rekonstruktion der zeitlichen Entwicklung des Hagelwachstums erstellt. Betroffene Bürger werden aktiv in die Messaktivitäten mit einbezogen und aufgerufen, Hagelkörnern einschließlich ihrer Haupteigenschaften in die WarnWetter App des DWD zu melden. Die Messkampagne mit ihrem mobilen und flexiblen Konzept beinhaltet die Anwendung neuer, innovativer Messtechniken, darunter Lagrangesche Trajektorien mittels kleiner Messsysteme, die in die Wolken eingebracht werden, und dronengesteuerte Luftbildaufnahmen zur Bestimmung der Hagelspektren. Aus Fernerkundungsdaten gewonnene Signaturen von Hagelereignissen liefern Informationen über die Charakteristika der Hagelereignisse und werden mittels numerischer Simulationen sorgfältig auf Messungenauigkeiten und Sensitivitäten bzgl. atmosphärischer Umgebungsvariablen evaluiert. Indikatoren für die Hagelentstehung und das Hagelwachstum werden aus Beobachtungsdaten und Simulationen identifiziert, und liefern die Grundlage für ein beobachtungs-basiertes Hagelwachstumsmodell. Schließlich wird dieses Multi-Parameter Hagelwachstumsmodell mit den bestimmten Hageltrajektorien und Schmelzprozessen kombiniert, um zu bestimmen, welche Prozesse am wichtigsten sind für das Nowcasting von Hagel. Das Projekt LIFT liefert damit einen wichtigen Betrag für zukünftige radar-basierte Hagelwarnsysteme mit einer verbesserten Vorhersagezeit und Vorhersagequalität.
During cruise HE644 (joint campaign of MS FRITZ REUTER and RV HEINCKE), Lagrangian surface drifters (Meyerjürgens et al., 2019; Deyle et al., 2024) were deployed from MS FRITZ REUTER, following the near-surface water motion, therefore allowing for observations within a moving water mass over extended periods with minimal disturbance to the surrounding water. Coordinates of the drifter position were transmitted by a GPS satellite tracker (inReach® Messenger from Garmin Ltd.) at two-minute intervals. Position data was processed after Deyle et al. (2024) and is available on minutely resolution in this dataset. For original trajectories see "<DOI>". In addition, the drifters were equipped with (down to 1.75 m depth) instrument chains including temperature and lightweight CTD (conductivity, temperature, depth) sensors. Depth in water was only recorded by RBRbrevio³ sensors, for others the depth was measured during sensor chain preparation and saved in the data array as fixed depth. The in situ temperature was recorded at up to six different depths using RBRsolo³, RBRbrevio³ (both sample frequency 1-2 Hz) and Aqua TROLL® 100 sensors (sample frequency 1 min-1). Conductivity was measured at up to three different depths, using RBRbrevio³ and Aqua TROLL® 100 sensors. RBR sensors were calibrated to a measurement uncertainty of ± 0.002 °C and ± 0.003 mS cm-1, whereas the TROLL sensors have a measurement uncertainty of ± 0.1 °C and ± 0.5%. For details on the sensor data processing see the appropriate processing report.
During cruise HE644 (joint campaign of MS FRITZ REUTER and RV HEINCKE), Lagrangian surface drifters (Meyerjürgens et al., 2019; Deyle et al., 2024) were deployed from MS FRITZ REUTER, following the near-surface water motion, therefore allowing for observations within a moving water mass over extended periods with minimal disturbance to the surrounding water. Coordinates of the drifter position were transmitted by a GPS satellite tracker (inReach® Messenger from Garmin Ltd.) at two-minute intervals. Position data was processed after Deyle et al. (2024) and is available on minutely resolution in this dataset. For original trajectories see "<DOI>". In addition, the drifters were equipped with (down to 1.75 m depth) instrument chains including temperature and lightweight CTD (conductivity, temperature, depth) sensors. Depth in water was only recorded by RBRbrevio³ sensors, for others the depth was measured during sensor chain preparation and saved in the data array as fixed depth. The in situ temperature was recorded at up to six different depths using RBRsolo³, RBRbrevio³ (both sample frequency 1-2 Hz) and Aqua TROLL® 100 sensors (sample frequency 1 min-1). Conductivity was measured at up to three different depths, using RBRbrevio³ and Aqua TROLL® 100 sensors. RBR sensors were calibrated to a measurement uncertainty of ± 0.002 °C and ± 0.003 mS cm-1, whereas the TROLL sensors have a measurement uncertainty of ± 0.1 °C and ± 0.5%. For details on the sensor data processing see the appropriate processing report.
During cruise HE644 (joint campaign of MS FRITZ REUTER and RV HEINCKE), Lagrangian surface drifters (Meyerjürgens et al., 2019; Deyle et al., 2024) were deployed from MS FRITZ REUTER, following the near-surface water motion, therefore allowing for observations within a moving water mass over extended periods with minimal disturbance to the surrounding water. Coordinates of the drifter position were transmitted by a GPS satellite tracker (inReach® Messenger from Garmin Ltd.) at two-minute intervals. Position data was processed after Deyle et al. (2024) and is available on minutely resolution in this dataset. For original trajectories see "<DOI>". In addition, the drifters were equipped with (down to 1.75 m depth) instrument chains including temperature and lightweight CTD (conductivity, temperature, depth) sensors. Depth in water was only recorded by RBRbrevio³ sensors, for others the depth was measured during sensor chain preparation and saved in the data array as fixed depth. The in situ temperature was recorded at up to six different depths using RBRsolo³, RBRbrevio³ (both sample frequency 1-2 Hz) and Aqua TROLL® 100 sensors (sample frequency 1 min-1). Conductivity was measured at up to three different depths, using RBRbrevio³ and Aqua TROLL® 100 sensors. RBR sensors were calibrated to a measurement uncertainty of ± 0.002 °C and ± 0.003 mS cm-1, whereas the TROLL sensors have a measurement uncertainty of ± 0.1 °C and ± 0.5%. For details on the sensor data processing see the appropriate processing report.
During cruise HE644 (joint campaign of MS FRITZ REUTER and RV HEINCKE), Lagrangian surface drifters (Meyerjürgens et al., 2019; Deyle et al., 2024) were deployed from MS FRITZ REUTER, following the near-surface water motion, therefore allowing for observations within a moving water mass over extended periods with minimal disturbance to the surrounding water. Coordinates of the drifter position were transmitted by a GPS satellite tracker (inReach® Messenger from Garmin Ltd.) at two-minute intervals. Position data was processed after Deyle et al. (2024) and is available on minutely resolution in this dataset. For original trajectories see "<DOI>". In addition, the drifters were equipped with (down to 1.75 m depth) instrument chains including temperature and lightweight CTD (conductivity, temperature, depth) sensors. Depth in water was only recorded by RBRbrevio³ sensors, for others the depth was measured during sensor chain preparation and saved in the data array as fixed depth. The in situ temperature was recorded at up to six different depths using RBRsolo³, RBRbrevio³ (both sample frequency 1-2 Hz) and Aqua TROLL® 100 sensors (sample frequency 1 min-1). Conductivity was measured at up to three different depths, using RBRbrevio³ and Aqua TROLL® 100 sensors. RBR sensors were calibrated to a measurement uncertainty of ± 0.002 °C and ± 0.003 mS cm-1, whereas the TROLL sensors have a measurement uncertainty of ± 0.1 °C and ± 0.5%. For details on the sensor data processing see the appropriate processing report.
During cruise HE644 (joint campaign of MS FRITZ REUTER and RV HEINCKE), Lagrangian surface drifters (Meyerjürgens et al., 2019; Deyle et al., 2024) were deployed from MS FRITZ REUTER, following the near-surface water motion, therefore allowing for observations within a moving water mass over extended periods with minimal disturbance to the surrounding water. Coordinates of the drifter position were transmitted by a GPS satellite tracker (inReach® Messenger from Garmin Ltd.) at two-minute intervals. Position data was processed after Deyle et al. (2024) and is available on minutely resolution in this dataset. For original trajectories see "<DOI>". In addition, the drifters were equipped with (down to 1.75 m depth) instrument chains including temperature and lightweight CTD (conductivity, temperature, depth) sensors. Depth in water was only recorded by RBRbrevio³ sensors, for others the depth was measured during sensor chain preparation and saved in the data array as fixed depth. The in situ temperature was recorded at up to six different depths using RBRsolo³, RBRbrevio³ (both sample frequency 1-2 Hz) and Aqua TROLL® 100 sensors (sample frequency 1 min-1). Conductivity was measured at up to three different depths, using RBRbrevio³ and Aqua TROLL® 100 sensors. RBR sensors were calibrated to a measurement uncertainty of ± 0.002 °C and ± 0.003 mS cm-1, whereas the TROLL sensors have a measurement uncertainty of ± 0.1 °C and ± 0.5%. For details on the sensor data processing see the appropriate processing report.
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.
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