ALBERT

Note: Dissertation, Universität Potsdam, 2019 , Table of Contents Abstract Zusammenfassung Abbreviations 1 Introduction 1.1 Scientific Background and Motivation 1.1.1 Arctic Tundra Vegetation 1.1.2 Remote Sensing of Arctic Tundra Vegetation 1.1.3 Hyperspectral Remote Sensing of Arctic Vegetation 1.2 Aims and Objectives 1.3 Study Area and Data 1.3.1 Toolik Lake Research Natural Area 1.3.2 In-situ Canopy-level Spectral Data 1.3.3 True-colour Digital Photographs 1.3.4 Leaf-level Photosynthetic Pigment Data 1.3.5 Airborne AISA Imagery 1.3.6 Simulated EnMAP and Sentinel-2 Reflectance Spectra 1.3.7 Simulated EnMAP Imagery 1.4 Thesis Structure and Author Contributions 1.4.1 Chapter 2 -A Phenological Approach to Spectral Differentiation of Low-Arctic Tundra Vegetation Communities, North Slope Alaska 1.4.2 Chapter 3 -Monitoring Pigment-driven Vegetation Changes in a Low Arctic Tundra Ecosystem Using Digital Cameras 1.4.3 Implications of Litter and Non-vascular Components on Multiscale Hyperspectral Data in a low-Arctic Ecosystem 2 A Phenological Approach to Spectral Differentiation of Low Arctic Tundra Vegetation Communities, North Slope Alaska 2.1 Abstract 2.2 Introduction 2.3 Materials and Methods 2.3.1 Study Site and Low Arctic Vegetation Types 2.3.2 Ground-Based Data and Sampling Protocol 2.3.3 EnMAP and Sentinel-2 Surface Reflectance Simulation 2.3.4 Stable Wavelength Identification Using the InStability Index 2.4 Results 2.4.1 Spectral Characteristics by Phenological Phase 2.4.2 InStability Index and Wavelength Selection of Ground-based Spectra 2.4.3 InStability Index and Wavelength Selection of Simulated Satellite Reflectance Spectra 2.5 Discussion 2.5.1 Phenological Phase and Wavelength Stability of Ground-based Spectra 2.5.2 Phenological Phase and Wavelength Stability of Satellite Resampled Spectra 2.5.3 Influence of Spatial Scale 2.6 Conclusions 2.7 Acknowledgements 2.8 Supplementary Material 2.8.1 Data Publication 3 Monitoring Pigment-driven Vegetation Changes in a Low Arctic Tundra Ecosystem Using Digital Cameras 3.1 Abstract 3.2 Introduction 3.3 Methods 3.3.1 Study Site 3.3.2 Digital Photographs 3.3.3 Field-based Spectral Data 3.3.4 Vegetation Pigment Concentration 3.3.5 Data Analyses 3.4 Results 3.4.1 RGB Indices as a Surrogate for Pigment-driven Spectral Indices 3.4.2 RGB Indices as a Surrogate for Leaf-level Pigment concentration 3.5 Discussion 3.6 Conclusions 3.7 Supplementary Material 3.7.1 Data Publication 4 Implications of Litter and Non-vascular Components on Multiscale Hyperspectral Data in a Low Arctic Ecosystem 4.1 Abstract 4.2 Introduction 4.3 Materials and Methods 4.3.1 Study Site 4.4 Remote Sensing Data 4.4.1 Ground-based Image Spectroscopy Data 4.4.2 Airborne AISA Hyperspectral Data 4.4.3 EnMAP Simulation 4.4.4 Spectral Comparison by Wavelength 4.4.5 Linear Mixture Analysis 4.5 Results 4.5.1 Spatial Scaling of Spectral Signals 4.6 Discussion 4.7 Conclusions 4.8 Acknowledgements 5 Synthesis and Discussion 5.1 Phenological Phase: does phenology influence the spectral variability of dominant low Arctic vegetation communities? 5.2 Vegetation Colour: How does canopy-level vegetation colour relate to phenological changes in leaf-level photosynthetic pigment concentration? 5.3 Intrinsic Ecosystem Components: How does spatial aggregation of high spectral resolution data influence low Arctic tundra vegetation signals? 5.4 Key Innovations 5.5 Limitations and Technical Considerations 5.6 Outlook: Opportunities for Future Research 6 References Acknowledgements

Note: Dissertation, Universität Potsdam, 2020 , CONTENTS 1 Introduction 1.1 Context: A rapidly changing Arctic 1.1.1 Documentation of recent changes in the Arctic 1.1.2 Research relevance 1.1.3 Objective: Svalbard as a hotspot for climate change 1.2 Physical Background 1.2.1 Radiation and surface energy balance 1.2.2 Peculiarities of the Arctic climate system 1.2.3 Role of atmospheric circulation 1.3 The regional setup on Svalbard 2 data and methods 2.1 Data description 2.1.1 Era-Interim atmospheric reanalysis 2.1.2 Svalbard Station Meteorology 2.1.3 Sea Ice Extent 2.1.4 Ocean data products 2.1.5 FLEXTRA Trajectories 2.2 Statistical Methods 2.2.1 Trend estimation 2.2.2 Correlation 2.2.3 Coefficient of Determination 3 state of surface climate parameters: pan-svalbard differences 3.1 Motivation 3.2 Surface air temperature 3.2.1 Annual cycle 3.2.2 Annual temperature range 3.2.3 Long-term trends 3.3 Fjord Sea Ice coverage 3.3.1 Climatology 3.3.2 Sea ice cover trends 3.3.3 Regional classification across Svalbard 3.3.4 Drivers of regional differences 3.4 Discussion and Conclusion 3.5 Current state of climate projections for the Svalbard region 4 Air mass back trajectories 4.1 Methodology 4.2 Winter 4.2.1 Source Regions of Ny-Ålesund Air 4.2.2 Circulation changes 4.2.3 Quantification of Advective Warming 4.3 Summer 4.3.1 Source Regions of Ny-Ålesund Air 4.3.2 Circulation changes 4.3.3 Quantification of advective cooling 4.3.4 Observational Case Study: May/June 2017 4.4 Discussion and Conclusion 5 Changing drivers of the arctic near surface temperature budget 5.1 Winter 5.2 Summer 5.3 Summary 6 Summary and conclusion A Details on calculations A.1 SLP composite Index A.2 Derivation of coefficient of determination A.3 Temperature effect of changing source regions over time B Supplementary figures Bibliography

Note: Dissertation, Universität Potsdam, 2020 , Table of contents Abstract Kurzfassung Table of contents Chapter 1: Introduction 1.1 The challenge of proxy uncertainties 1.2 Aims and approaches 1.3 Thesis outline and author's contributions Chapter 2: Comparing methods for analysing time scale dependent correlations in irregularly sampled time series data 2.1 Abstract 2.2 Introduction 2.3 Methods 2.3.1 Time scale dependency 2.3.2 Irregularity 2.3.3 Surrogate data 2.3.3.1 Construction of surrogate signals 2.3.3.2 Construction of irregular sampling 2.3.4 Evaluation of the estimation methods 2.4 Results 2.4.1 Correlation of red signal - white noise time series 2.4.2 Correlation of white signal - white noise time series 2.5 Discussion 2.5.1 Effect of irregularity and non-simultaneousness in sampling 2.5.2 Choosing the best method 2.5.2.1 Handling irregularity 2.5.2.2 Accounting for time scale dependency 2.5.3 Example application to observed proxy records 2.6 Conclusion 2.7 Computer code availability 2.8 Acknowledgements 2.9 Appendix 2-A. Significance test for time scale dependent correlation estimates Chapter 3: Empirical estimate of the signal content of Holocene temperature proxy records 3.1 Abstract 3.2 Introduction 3.3 Data 3.3,1 Proxy records 3.3.2 Climate model simulations 3.4 Method 3.4.1 Approach and assumptions 3.4.2 Spatial correlation structure of model vs. reanalysis data 3.4.3 Processing steps 3.4.3.1 Estimation of the spatial correlation structure 3.4.3.2 Estimation of the SNRs 3.5 Results 3.5.1 Spatial correlation structure and correlation decay length 3.5.2 SNR estimates 3.6 Discussion 3.6.1 Spatial correlation structure of model simulations 3.6.2 Finite number of proxy records 3.6.3 Proxy-specific recording of climate variables 3.6.4 Time uncertainty and non-climatic components of the proxy signal 3.6.5 Implications and future steps forward 3.7 Conclusion 3.8 Code availability 3.9 Data availability 3.10 Acknowledgements Chapter 4: Testing the consistency of Holocene and Last Glacial Maximum spatial correlations in temperature proxy records 4.1 Abstract 4.2 Introduction 4.3 Data 4.4 Method 4.4.1 Approach and assumptions 4.4.2 Holocene and LGM spatial correlation structure from climate model simulation 4.4.3 Effect of changes in climate variability on the predicted correlations 4.4.4 Effect of changes in time uncertainty on the predicted correlations 4.4.S Estimating the surrogate-based LGM spatial correlation and accounting for parameter uncertainty 4.5 Results 4.6 Discussion 4.6.1 Proxy-specific recording and finite number of records 4.6.2 Time uncertainty of proxy records 4.6.3 Contrary behaviour of U K'37 records 4.6.4 Spatial correlation structure and orbital trends 4.7 Conclusion 4.8 Acknowledgements 4.9 Appendix 4-A. Deriving the effect of a different signal variance on the correlation Chapter 5: Synthesis 5.1 Irregular sampling and time scale dependent correlations 5.2 Spatial correlation structure of proxy records 5.3 Consistency of spatial correlations for different climate states 5.4 Signal content of proxy records 5.5 Concluding remarks and Outlook Chapter A: Supplement of Chapter 3 - Empirical estimate of the signal content of Holocene temperature proxy records A.1 Supplementary Figures A.2 Supplementary Tables Chapter B: Supplement of Chapter 4 - Testing the consistency of Holocene and Last Glacial Maximum spatial correlations of temperature proxy records 8.1 Supplementary Figures 8.2 Supplementary Tables References Danksagung Eidesstattliche Erklärung

Note: Dissertation, Universität Potsdam, 2019 , TABLE OF CONTENTS Abstract Zusammenfassung Table of contents List of figures List of tables List of abbreviations 1 Introduction 1.1 Scientific background and motivation 1.1.1 Permafrost degradation 1.1.2 Snow cover 1.1.3 Vegetation phenology 1.2 Remote sensing of rapid changes 1.2.1 SAR remote sensing 1.2.2 TerraSar-X 1.3 Data and methods 1.4 Aims and objectives 1.5 Study areas and data 1.6 Thesis structure and author contributions 1.6.1 Chapter 2 – Monitoring inter-and intra-seasonal dynamics of rapidly degrading ice-rich permafrost riverbanks in the Lena Delta with TerraSAR-X time series 1.6.2 Chapter 3 – TerraSAR-X time series fill a gap in spaceborne snowmelt monitoring of small Arctic catchments 1.6.3 Chapter 4 – Estimation of Arctic tundra vegetation phenology with TerraSAR-X 2 Monitoring inter-and intra-seasonal dynamics of rapidly degrading ice-rich permafrost riverbanks in the Lena Delta with TerraSAR-X time series 2.1 Abstract 2.2 Introduction 2.3 Study area 2.4 Data and methods 2.4.1 SAR data and processing 2.4.2 Automated cliff-top line extraction from SAR data 2.4.3 Quantification of cliff-top erosion with the Digital Shoreline Analysis System 2.4.4 Cliff top mapping from optical satellite data 2.4.5 In-situ observations of cliff top erosion 2.4.6 Climate data 2.4.7 Statistical data analysis 2.5 Results 2.5.1 TSX erosion versus in-situ and optical datasets 2.5.2 Inter-and intra-annual cliff-top erosion and climate data 2.5.3 Backscatter time series 2.6 Discussion 2.6.1 Inter-annual dynamics of cliff-top erosion 2.6.2 Intra-annual dynamics of cliff-top erosion 2.6.3 Backscatter dynamics of tundra and cliff surfaces 2.7 Conclusions 2.8 Acknowledgments 3 TerraSAR-X time series fill a gap in spaceborne snowmelt monitoring of small Arctic catchments 3.1 Abstract 3.2 Introduction 3.3 Study area 3.4 Data and methods 3.4.1 SAR satellite data 3.4.2 Optical satellite data 3.4.3 In-situ time-lapse camera data 3.4.4 Snow Cover Extent from TerraSAR-X 3.4.5 Snow Cover Extent from Landsat 8 3.4.6 Accuracy assessment of TerraSAR-X Snow Cover Extent 3.4.7 Fractional Snow Cover time series analysis 3.5 Results 3.5.1 Evaluation of TSX Snow Cover Extent 3.5.2 Time series of Fractional Snow Cover in all catchments 3.5.3 Time series of Fractional SnowCover in small catchments 3.6 Discussion 3.6.1 Spatiotemporal monitoring of snowmelt dynamics using TSX 3.6.2 Technical considerations for using TSX for wet snow detection 3.7 Conclusions 3.8 Acknowledgements 3.9 Appendix 4 Relationships between X-Band SAR and vegetation phenology in a low Arctic ecosystem 4.1 Abstract 4.2 Introduction 4.3 Study area 4.4 Data and methods 4.4.1 In-situ time-lapse phenological cameras 4.4.2 Time-lapse image analysis 4.4.3 SAR satellite data 4.4.4 Backscatter and coherence time series 4.4.5 In-situ vegetation and climate data 4.5 Results 4.5.1 Phenocams 4.5.2 Backscatter dynamics 4.5.3 Coherence dynamics 4.6 Climate data 4.7 Backscatter and vegetation height 4.8 Discussion 4.9 Conclusion 4.10 Acknowledgments 5 Synthesis 5.1 Rapid permafrost disturbance 5.2 Snowmelt dynamics 5.3 Arctic tundra vegetation phenology 5.4 Seasonality and complementarity of TSX 5.5 Limitations and technical considerations 5.6 Key findings and outlook References Acknowledgements

Note: Dissertation, Universität Potsdam, 2019 , Table of Contents Abstract Zusammenfassung 1 Introduction 1.1 Scientific background 1.1.1 Permafrost - terrestrial and subsea 1.1.2 Subsea permafrost distribution 1.1.3 Relevance in the context of a changing Arctic 1.1.4 Influences on subsea permafrost 1.2 Hypotheses and objectives 1.3 Thesis organization 2 Detection of subsea permafrost degradation rates 2.1 An overview of geophysical methods and studies in subsea permafrost 2.2 Geophysical objectives 2.3 Passive seismic techniques 2.3.1 H/V passive seismics 2.3.2 Passive seismic interferometry 2.4 Instrument design & marine tests on Sylt 2.5 Arctic feasibility test site around Muostakh Island 2.6 Arctic deployment for wide area detection around Muostakh Island 3 Modelling of subsea permafrost degradation processes 3.1 An overview on subsea permafrost modelling 3.2 Salt distribution- mechanisms beyond diffusional transport 3.3 Open questions in salt transport and permafrost degradation 3.4 Modelling objectives 3.5 Study sites 3.5.1 Primary study site: Cape Mamontov Klyk 3.5.2 Secondary study sites: Buor Khaya & Muostakh Island 3.6 Developing a model for subsea permafrost 3.6.1 Thermal regime of the subsurface: governing equations of conductive heat transfer 3.6.2 Model definitions: concentration and thaw depth 3.6.3 Saline effect on the state of permafrost 3.6.4 Salt transport: governing equation & parameterizations 3.6.5 Modelling approach 3.6.6 Model testing 3. 7 Results: Influence of model parameters on subsea permafrost degradation 3.8 Discussion and implications 3.8.1 Modelled inundation parameters 3.8.2 Further factors affecting subsea permafrost degradation 3.8.3 Implications 4 From local to regional scale: Amending sparsely distributed temperature records 4.1 An overview of borehole temperature reconstruction . 4.2 On the transferability of ground to air temperatures . 4.3 Reconstruction objectives 4.4 Borehole sites and climate 4.5 Borehole temperatures 4.6 Inversion method 4.6.1 Forward model 4.6.2 Optimization 4.6.3 Sensitivity analysis 4.7 Results and discussion of the reconstruction from the permafrost boreholes 4.7.1 Recoverable period 4.7.2 Optimization 4.7.3 Surface temperature reconstructions and fit 4.7.4 Inversion method's impact on character of solution & sensitivity to temperature history parameterization 4.8 Discussion of spatial differences and implications 4.8.1 Comparison to other temperature data 4.8.2 Site differences 4.8.3 Methodological considerations 4.8.4 Implications 5 Conclusion and outlook 5.1 Outlook Appendices A Modelling tests for H/V method configuration Bibliography Acknowledgements

Note: Dissertation, Universität Potsdam, 2018 , Table of Content I. Abstract II. Deutsche Zusammenfassung 0 Preface 1 Scientific Background 1.1 Paleoenvironmental changes since the gLGM in arid Central Asia and north-western High Asia 1.1.1 Paleoclimatic changes 1.1.2 Lake level fluctuations following climatic changes 1.1.3 Inferred terrestrial vegetation responses to environmental changes and possible human impact 1.2 The role of proxy records in tracing environmental changes 1.2.1 Archives and Proxies investigated in environmental studies in Central Asia 1.2.2 Limnological systems as environmental archives 1.2.3 The multiproxy approach as a tool to decipher environmental change 1.3 Study area 1.4 Material and Method Overview 1.4.1 Field based sampling 1.4.2 Outline of material and methods 1.5 Aim and objectives ofthis thesis 1.6 Thesis outline 1.7 Contribution of the authors 1.7.1 Manuscript I - published 1.7.2 Manuscript II - published 1.7.3 Manuscript III - published 1.7.4 Manuscript IV - in preparation 2 Manuscript I Climatic and limnological changes at Lake Karakul (Tajikistan) during the last ~29 cal ka 2.1 Abstract 2.2 Introduction 2.3 Study Area 2.4 Material and methods 2.4.1 Fieldwork 2.4.2 Laboratory analysis 2.5 Results 2.5.1 Age-depth relationship in core KK12-1 2.5.2 TIC, TOC, TOC/TN, δ18Ocarb and δ13CCarb 2.5.3 Grain-size distribution and results ofend-member modelling 2.5.4 XRF data 2.5.5 Ordination results of sediment parameters 2.6 Discussion 2.6.1 Paleoenvironmental indicators from sediment variables 2.6.2 Implications ofthe Lake Karakul sediment record 2.6.3 Linking lake internal development to climate change 2.7 Conclusions 2.8 Acknowledgements 2.9 Data availability 3 Manuscript II Aquatic macrophyte dynamics in Lake Karakul (Eastern Pamir) over the last 29 cal ka revealed by sedimentary ancient DNA and geochemical analyses of macrofossil remains 3.1 Abstract 3.2 Introduction 3.3 Material and Methods 3.3.1 Sample acquisition and treatment 3.3.2 Genetic approach 3.3.3 Elemental isotopic analyses ofaquatic macrophyte remains 3.4 Results 3.4.1 Macrophyte records along lake depth transects in Lake Karakul 3.4.2 Submerged plant content 3.4.3 Ancient DNA analyses 3.4.4 C, N, δ13C and δ15N of Stuckenia cf. pamirica remains 3.5 Discussion 3.5.1 Assessment of aDNA and chemical aquatic macrophyte data as proxies for the macrophyte composition and the paleo-productivity 3.5.2 Changes of past submerged plant composition and productivity and potential drivers 3.6 Conclusions 3.7 Acknowledgements 3.8 Data Availability 4 Manuscript III Radiocarbon and optical stimulated luminescence dating of sediments from Lake Karakul, Tajikistan 4.1 Abstract 4.2 Introduction 4.3 Regional setting 4.4 Methods 4.4.1 Collection and correlation of cores 4.4.2 Radiocarbon dating 4.4.3 Optically stimulated luminescence (OSL) dating 4.4.4 Establishment ofage-depth model 4.4.5 Investigation of exposed lake sediments 4.5 Results 4.6 Discussion 4.6.1 Recovered sediments and correlation ofcores from Lake Karakul 4.6.2 Age-depth model, and assessment of radiocarbon and OSL age data 4.6.3 Significance ofexposed sediments at section KK13-S1 4.6.4 Implications ofthe chronological data 4.7 Conclusion 4.8 Acknowledgements 5 Manuscript IV Vegetation change in the Eastern Pamir Mountains inferred from Lake Karakul pollen spectra of the last 28 ka 5.1 Abstract 5.2 Introduction 5.3 Study site 5.4 Material and Methods 5.4.1 Sediment cores and chronology 5.4.2 Pollen sample preparation and pollen analyses 5.4.3 Pollen data treatment 5.5 Results 5.5.1 Composite core (KK12-1/2; 27.6 cal ka BP to present) 5.5.2 Short core TAJ-Kar-08-lB 5.6 Discussion 5.6.1 Interpretation of pollen data 5.6.2 Terrestrial vegetation change in the Eastern Pamir Mountains in response to past climate change 5.7 Conclusions 5.8 Acknowledgements 5.9 Data Availability 6 Synthesis 6.1 Proxy evaluation 6.1.1 Age-depth relationship 6.1.2 Limnological proxies 6.1.3 Terrestrial proxies 6.2 The potential of Lake Karakul as archive for long term environmental change in the Eastern Pamir 6.3 Climate and moisture availability changes over time - inferred from sedimentary proxies 6.4 Assessment ofthe aquatic macrophyte composition and paleoproductivity within Lake Karakul 6.5 Inferred terrestrial vegetation changes as responds to climatic changes over the last 28 cal ka 6.6 Comparison inferred regional vegetation, lake internal and lake external variations and changes in climate reconstructed in other studies 6.6.1 Pre- gLGM and global Last Glacial Maximum (27.6 to 19 cal ka BP) 6.6.2 Late glacial 6.6.3 Early to middle Holocene 6.6.4 Middle to late Holocene 6.7 Outlook 7 Appendix 7.1 Supplementary information for Manuscript I 7.2 Supplementary information for Manuscript II 7.3 Supplementary information for Manuscript III 8 References Danksagung Eldesstattliche Erklärung