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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Comparison of temperature variability and trends in Svalbard and Franz Joseph Land

Renberg, Johanna January 2022 (has links)
Arctic warming is assumed to be four times the global warming. A published study by Ivanov et al. (2019) shows that the annual average temperature of Franz Joseph Land (the world’s northernmost island region, a Russian territory) has increased by 5.2 °C from 2000-2017. This result supported the idea of determining whether Svalbard (Norwegian territory) is experiencing similar warming. Svalbard has historically been an attractive research center for examining climate change in the Arctic. Due to easier accessibility, the vast majority of weather stations have been located on the western part of the main island, Spitsbergen, which does not provide a representative picture of the entire archipelago. Therefore, this project has focused on eastern Spitsbergen. Data from six stations have been processed to analyze the temperature changes based on linear regression (the same method as at Franz Joseph Land). As eastern Spitsbergen has never been a priority, only short datasets are available, with the longest one dating from 2009. Because of this, no statistically significant result could be elucidated. Instead, data from Longyearbyen, which is located southwest were implemented, allowing analysis over the same period as Franz Joseph Land (2000-2017). This result suggested a temperature increase of 5.6 °C for the same period, with a statistical significance of P = 0.13, as well as that the winters are extra vulnerable to warming. The stations from eastern Spitsbergen’s local variability were also examined, which showed that the local climate varies although the stations are relatively close. Among others, Pyramiden seemed to be most affected by the lapse rate feedback, meaning a significant strong warming at the surface.
2

Arctic low-level mixed-phase clouds and their complex interactions with aerosol and radiation: Remote sensing of the Arctic troposphere with the shipborne supersite OCEANET-Atmosphere

Griesche, Hannes Jascha 28 June 2022 (has links)
In the course of this thesis, Arctic low-level mixed-phase clouds and their interaction with aerosol and radiation have been investigated. To do so, measurements with the shipborne remote sensing supersite OCEANET-Atmosphere were conducted during the PS106 expedition in the Arctic summer 2017. OCEANET-Atmosphere comprises among other instruments a multiwavelength polarization lidar PollyXT and a microwave radiometer HATPRO. For PS106 the OCEANET-Atmosphere facility was complemented for the first time with a motion-stabilized vertically pointing Doppler cloud radar Mira-35. The cloud radar Doppler velocity was corrected for the ship’s vertical movement. The stabilization and the correction enabled, e.g., the derivation of eddy dissipation rates from the Doppler velocities. A data set of cloud microphysical and macrophysical properties was derived by applying the synergistic Cloudnet algorithm to the combined measurements of cloud radar, lidar, and microwave radiometer. Within this thesis, the set of the Cloudnet retrievals was improved to account for the complex structure of the Arctic cloud system. A new detection approach for the frequently observed low-level stratus clouds was developed based on the lidar signal-to-noise ratio. These clouds, which were below the lowest range gate of the cloud radar were observed during 50 % of the observational time. A new approach for the continuous determination of the ice crystal effective radius was introduced. This new retrieval made the data set suitable to perform high-resolved radiative transfer simulations. The retrieved data set was utilized to derive the first temperature relationship for heterogeneous ice formation in Arctic mixed-phase clouds. A strong dependence of the surface coupling state for high subzero ice-formation temperatures was found. For an ice-formation temperature above -15 °C, surface-coupled ice-containing clouds occur more frequently by a factor of 5 in numbers of observed clouds and by a factor of 2 in frequency of occurrence. Possible causes of the observed effect were discussed by sensitivity studies and a literature survey. Instrumental and methodological effects, and previously published similar observations of an increased ice occurrence at such high subzero temperatures have been ruled out as a possible explanation. The most likely cause of the observed effect was attributed to a larger reservoir of biogenic ice-nucleating particles in the surface-coupled marine boundary layer. This larger reservoir led to a higher freezing efficiency in these clouds which had at least their base in that layer. Finally, the importance of the detailed classification of the low-level clouds was highlighted by the evaluation of radiative transfer simulations. A difference in the cloud radiative effect of up to 100 W m-2 was calculated when these clouds were considered.:1 Introduction 2 Arctic — Amplified climate change 2.1 The Arctic climate system 2.2 Cloud radiation budget 2.3 Arctic mixed-phase clouds 2.4 Heterogeneous ice formation in Arctic mixed-phase clouds — constraints and previous findings 2.5 Motivating research questions 3 Data set — Applied instrumentation, processing, and retrievals 3.1 Introduction to ground-based active remote sensing of aerosol and clouds 3.1.1 Lidar principle 3.1.2 Radio Detection and Ranging — Radar 3.2 The Arctic expedition PS106 3.3 Instrumentation 3.3.1 The OCEANET-Atmosphere observatory 3.3.2 Other instruments used in this study 3.4 Data processing and synergistic retrievals 3.4.1 Correction of vertical-stare cloud radar observations for ship motion 3.4.2 Retrieval of eddy dissipation rate from Doppler radar spectra 3.4.3 Cloud macro- and microphysical properties from instrument-synergies 3.5 Summary of the data processing for PS106 4 Cloud and aerosol observations during PS106 4.1 Meteorological conditions during PS106 4.2 Case studies 4.3 Cloud and aerosol statistics during PS106 4.4 Discussion of the observational data sets 5 Contrasting surface-coupling effects on heterogeneous ice formation 5.1 Methodology 5.1.1 Ice-containing cloud analysis 5.1.2 Surface-coupling state 5.2 Results: influence of surface coupling on heterogeneous ice formation temperature 5.3 Discussion of the observed surface-coupling effects 5.3.1 Methodological and instrumental effects 5.3.2 Possible causes for increased ice occurrence in surface-coupled clouds 6 Application of the data set in collaborative studies and radiative transfer simulations within (AC)3 6.1 Radiative transfer simulations and cloud radiative effect 6.2 LLS treatment for improved radiative transfer simulations 6.3 Discussion 7 Summary and outlook Appendices A Determination of a volume depolarization threshold forlidar-based ice detection Bibliography / Im Rahmen dieser Arbeit wurden niedrige arktische Mischphasenwolken und ihre Wechselwirkung mit Aerosolen und Strahlung untersucht. Dazu wurden Messungen mit der schiffsgestützten Fernerkundungs-Supersite OCEANET-Atmosphere während der PS106-Expedition im arktischen Sommer 2017 durchgeführt. OCEANET-Atmosphere vereint, u.a., ein Multiwellenlängen-Polarisations-Lidar PollyXT und ein Mikrowellen-Radiometer HATPRO. Für PS106 wurde OCEANET-Atmosphere erstmalig um ein stabilisiertes, vertikal ausgerichtetes Doppler-Wolkenradar Mira-35 erweitert. Die Doppler-Geschwindigkeit wurde in Bezug auf die Vertikalbewegung des Schiffes korrigiert. Dank Stabilisierung und Korrektur war, z.B., die Ableitung von Wirbeldissipationsraten aus den Doppler-Geschwindigkeiten möglich. Unter Anwendung des synergetischen Cloudnet-Algorithmus wurde aus den kombinierten Wolkenradar, Lidar und Mikrowellenradiometer Messungen ein Datensatz der mikro- und makrophysikalischen Wolkeneigenschaften für PS106 erstellt. Im Rahmen dieser Arbeit wurde Cloudnet verbessert, um der komplexen Struktur der arktischen Wolken Rechnung zu tragen. Ein neuer Ansatz zur Erkennung der häufig beobachteten niedrigen Stratuswolken wurde entwickelt, basierend auf dem Lidar-Signal-zu-Rausch-Verhältnis. Diese Wolken, die unterhalb des untersten Höhenlevels des Wolkenradars auftraten, wurden während 50% der Beobachtungszeit identifiziert. Ein neuer Ansatz für die kontinuierliche Bestimmung des effektiven Radius der Eiskristalle wurde eingeführt. Dank dieser neuen Methode eignet sich der erstellte Datensatz für die Durchführung von Strahlungstransfersimulationen. Zum ersten Mal wurde eine Temperaturbeziehung für heterogene Eisbildung in arktischen Mischphasenwolken in Abhängigkeit ihres Oberflächen-Kopplungsstatus abgeleitet. Bei Temperaturen über -15°C war die relative Häufigkeit von Eis beinhaltenden Wolken doppelt so hoch und die Anzahl fünf Mal höher wenn sie mxit der Oberfläche gekoppelt waren, als bei entkoppelte Wolken. Mögliche Ursachen für den beobachteten Effekt wurden anhand von Sensitivitätsstudien und einer Literaturanalyse diskutiert. Instrumentelle und methodische Effekte sowie früher veröffentlichte ähnliche Beobachtungen konnten als mögliche Erklärung ausgeschlossen werden. Die wahrscheinlichste Ursache für den beobachteten Effekt wurde auf ein größeres Reservoir an biogenen Eiskristallisationskeimen in der oberflächengekoppelten marinen Grenzschicht zurückgeführt. Dieses größere Reservoir hat zu einer höheren Gefriereffizienz in Wolken geführt, die zumindest ihre Basis in dieser Schicht hatten. Die Bedeutung der detaillierten Klassifizierung von tiefliegenden Wolken auf Strahlungstransfersimulationen wurde hervorgehoben. Der simulierte Effekt der Wolken auf den Strahlungshaushalt unterschied sich bis zu 100 W m-2, unter Berücksichtigung dieser Wolken.:1 Introduction 2 Arctic — Amplified climate change 2.1 The Arctic climate system 2.2 Cloud radiation budget 2.3 Arctic mixed-phase clouds 2.4 Heterogeneous ice formation in Arctic mixed-phase clouds — constraints and previous findings 2.5 Motivating research questions 3 Data set — Applied instrumentation, processing, and retrievals 3.1 Introduction to ground-based active remote sensing of aerosol and clouds 3.1.1 Lidar principle 3.1.2 Radio Detection and Ranging — Radar 3.2 The Arctic expedition PS106 3.3 Instrumentation 3.3.1 The OCEANET-Atmosphere observatory 3.3.2 Other instruments used in this study 3.4 Data processing and synergistic retrievals 3.4.1 Correction of vertical-stare cloud radar observations for ship motion 3.4.2 Retrieval of eddy dissipation rate from Doppler radar spectra 3.4.3 Cloud macro- and microphysical properties from instrument-synergies 3.5 Summary of the data processing for PS106 4 Cloud and aerosol observations during PS106 4.1 Meteorological conditions during PS106 4.2 Case studies 4.3 Cloud and aerosol statistics during PS106 4.4 Discussion of the observational data sets 5 Contrasting surface-coupling effects on heterogeneous ice formation 5.1 Methodology 5.1.1 Ice-containing cloud analysis 5.1.2 Surface-coupling state 5.2 Results: influence of surface coupling on heterogeneous ice formation temperature 5.3 Discussion of the observed surface-coupling effects 5.3.1 Methodological and instrumental effects 5.3.2 Possible causes for increased ice occurrence in surface-coupled clouds 6 Application of the data set in collaborative studies and radiative transfer simulations within (AC)3 6.1 Radiative transfer simulations and cloud radiative effect 6.2 LLS treatment for improved radiative transfer simulations 6.3 Discussion 7 Summary and outlook Appendices A Determination of a volume depolarization threshold forlidar-based ice detection Bibliography
3

Isotope-based source apportionment of black carbon aerosols in the Eurasian Arctic

Winiger, Patrik January 2016 (has links)
Aerosols change the Earth's energy balance. Black carbon (BC) aerosols are a product of incomplete combustion of fossil fuels and biomass burning and cause a net warming through aerosol radiation interactions (ari) and aerosol cloud interactions (aci). BC aerosols have potentially strong implications on the Arctic climate, yet the net global climate effect of BC is very uncertain. Best estimates assume a net warming effect, roughly half to that of CO2. However, the time scales during which CO2 emissions affect the global climate are on the order of hundreds of years, while BC is a short-lived climate pollutant (SLCP) with atmospheric life times of days to weeks. Climate models or atmospheric transport models struggle to emulate the seasonality and amplitude of BC concentrations in the Arctic, which are low in summer and high in winter/spring during the so called Arctic haze season. The high uncertainties regarding BC's climate impact are not only related to ari and aci, but also due to model parameterizations of BC lifetime and transport, and the highly uncertain estimates of global and regional BC emissions. Given the high uncertainties in technology-based emission inventories (EI), there is a need for an observation-based assessment of sources of BC in the atmosphere. We study short-term and long-term observations of elemental carbon (EC), the mass-based analog of optically-defined BC. EC aerosol concentrations and carbon-isotope-based (δ13C and ∆14C) sources were constrained (top-down) for three Arctic receptor sites in Abisko (northern Sweden), Tiksi (East Siberian Russia), and Zeppelin (on Svalbard, Norway). The radiocarbon (∆14C) signature allows to draw conclusion on the EC sources (fossil fuels vs. biomass burning) with high accuracy (&lt;5% variation). Stable carbon isotopic fingerprints (δ13C) give qualitative information of the consumed fuel type, i.e. coal, C3-plants (wood), liquid fossil fuels (diesel) or gas flaring (methane and non-methane hydrocarbons). These fingerprints can be used in conjunction with Bayesian statistics, to estimate quantitative source contributions of the sources. Finally, our observations were compared to predictions from a state of the art atmospheric transport model (coupled to BC emissions), conducted by our collaborators at NILU (Norwegian Institute for Air Research). Observed BC concentrations showed a high seasonality throughout the year, with elevated concentrations in the winter, at all sites. The highest concentrations were measured on Svalbard during a short campaign (Jan-Mar 2009) focusing on BC pollution events. Long-term observations showed that Svalbard (2013) had overall the lowest annual BC concentrations, followed by Abisko (2012) and Tiksi (2013). Isotope constraints on BC combustion sources exhibited a high seasonality and big amplitude all across the Eurasian Arctic. Uniform seasonal trends were observed in all three year-round studies, showing fractions of biomass burning of 60-70% in summer and 10-40% in winter. Europe was the major source region (&gt;80%) for BC emissions arriving at Abisko and the main sources were liquid fossil fuels and biomass burning (wood). The model agreed very well with the Abisko observations, showing good model skill and relatively well constrained sources in the European regions of the EI. However, for the Svalbard and East Siberian Arctic observatories the model-observation agreement was not as good. Here, Russia, Europe and China were the major contributors to the mostly liquid fossil and biomass burning BC emissions. This showed that the EI still needs to be improved, especially in regions where emissions are high but observations are scarce (low ratio of observations to emitted pollutant quantity). Strategies for BC mitigation in the (Eurasian) Arctic are probably most efficient, if fossil fuel (diesel) emissions are tackled during winter and spring periods, all across Eurasia. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Manuscript. Paper 3: Manuscript.</p>
4

Introduction of the Transregional Collaborative Research Center TR 172: Arctic Amplification

Wendisch, Manfred, Brückner, Marlen, Burrows, John P., Crewell, Susanne, Dethloff, Klaus, Ebell, Kerstin, Lüpkes, Christof, Macke, Andreas, Notholt, Justus, Quaas, Johannes, Rinke, Annette, Tegen, Ina 13 November 2017 (has links)
A new German research consortium is investigating the causes and effects of the rapid rise of near-surface air temperatures in the Artic. Within the last 25 years a remarkable increase of the Arctic near-surface air temperature exceeding the global warming by a factor of two to three has been observed. The phenomenon is commonly referred to as Arctic Amplification. The warming results in rather drastic changes of a variety of climate parameters. For example, the Arctic sea ice has declined significantly. This ice retreat has been well identified by satellite measurements. However, coupled regional and global climate models still fail to reproduce it adequately; they tend to systematically underestimate the observed sea ice decline. This model observation difference implies that the underlying physical processes and feedback mechanisms are not appropriately represented in Arctic climate models. Thus, the predictions of these models are also likely to be inadequate. It is mandatory to identify the origin of this disagreement. / Ein neu geschaffenes deutsches Forschungskonsortium untersucht die Ursachen und Effekte des rapiden Anstiegs der bodennahen Lufttemperatur in der Arktis. Innerhalb der letzten 25 Jahre wurde ein bemerkenswerter Anstieg der Bodenlufttemperatur in der Arktis beobachtet, welcher die globale Erwärmung um den Faktor 2 bis 3 übersteigt. Dieses Phänomen wird als arktische Verstärkung bezeichnet. Diese Erwärmung resultiert vielmehr in einer drastischen Änderung einer Vielzahl von Klimarparametern. Beispielsweise ist das arktische Meereis deutlich zurückgegangen. Dieser Eisrückgang wurde durch Satellitenbeobachtungen gut beobachtet. Dagegen haben regionale und globale Klimamodelle immer noch Probleme, den Rückgang entsprechend zu reproduzieren. Sie tendieren dazu, den Meereisrückgang systematisch zu unterschätzen. Die Unterschiede zwischen Modell und Beobachtungen legen nahe, dass die grundlegenden physikalischen Prozesse und Rückkopplungsmechanismen nicht entsprechend in arktischen Klimamodellen repräsentiert werden. Somit sind wahrscheinlich auch die Vorhersagen der Modelle unzureichend. Es ist notwendig, den Ursprung dieser Unstimmigkeit zu identifizieren.

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