The Arctic continues to be a 'hot spot' for climate change. There is an active debate in the scientific community whether and how changes in the Arctic climate system also affect the weather and climate in the mid-latitudes. Representing the Arctic properly in models is a major part of the research done in this area. From the perspective of numerical weather prediction (NWP) models, it has been shown that a better representation of the atmospheric state of the Arctic does not only lead to improved medium-range forecasts for the Arctic region but also for the mid-latitudes. Thus, an improved understanding and representation of atmospheric processes in the Arctic is essential to improve the forecast quality of NWP models. One important puzzle piece in the Arctic system are clouds. Due to their small spatial scale, cloud processes are parameterized in global NWP models. The basis for these parameterizations are measurements and more complex models of the physical processes, which need to be parameterized. Cirrus play an important part in the radiative budget of the Arctic atmosphere. Their interaction with solar and terrestrial radiation is one of these complex processes that need to be parameterized. However, due to the remoteness of the Arctic there are insufficient measurements available to allow these parameterizations to be tailored to the Arctic. Therefore, this thesis explores the influence of Arctic cirrus on the radiative budget in the Arctic using new airborne measurements from an aircraft campaign in spring 2022. In detail, during two measurement flights in the central Arctic over sea ice in April 2022, one measurement section was flown below and one above an isolated cirrus. Furthermore, the measurements are used to evaluate the representation of Arctic cirrus in the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF), specifically in the radiation scheme ecRad, using sensitivity studies.:Chapter 1: Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Radiative Effect of Arctic Cirrus . . . . . . . . . . . . . . . . . . . . . 1 1.1.1 Surface and Top-of-Atmosphere Radiative Effect . . . . . . . . 4 1.1.2 Ice Crystal Shape . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2 Formation, Microphysical and Radiative Properties of Cirrus . . . . . 6 1.3 Representation of Cirrus in Numerical Weather Prediction Models . . 9 1.3.1 Simplified Radiative Transfer . . . . . . . . . . . . . . . . . . 9 1.3.2 Ice Optics Parameterizations . . . . . . . . . . . . . . . . . . . 10 1.4 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Chapter 2: Fundamentals of Radiative Transfer . . . . . . . . . . . . . 13 2.1 Radiometric Quantities . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.2 Particle Optical Properties . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2.1 Particle Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2.2 Optical Cross Sections . . . . . . . . . . . . . . . . . . . . . . 16 2.2.3 Single-scattering Albedo . . . . . . . . . . . . . . . . . . . . . 17 2.2.4 Scattering Phase Function . . . . . . . . . . . . . . . . . . . . 17 2.2.5 Asymmetry Parameter . . . . . . . . . . . . . . . . . . . . . . 19 2.3 Cloud Microphysical Properties . . . . . . . . . . . . . . . . . . . . . 19 2.4 Bulk Optical Properties . . . . . . . . . . . . . . . . . . . . . . . . . 20 2.5 Effective Radius . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.6 Radiative Transfer Equation . . . . . . . . . . . . . . . . . . . . . . . 23 2.6.1 General Formulation . . . . . . . . . . . . . . . . . . . . . . . 23 2.6.2 Considering the RTE in Global Models . . . . . . . . . . . . . 24 2.7 Radiative Transfer in the IFS - ecRad . . . . . . . . . . . . . . . . . . 25 2.8 Ice Optics Parameterizations . . . . . . . . . . . . . . . . . . . . . . . 25 2.9 Parameterization of the Ice Effective Radius . . . . . . . . . . . . . . 29 2.10 Cloud Radiative Effect . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Chapter 3: Airborne Measurements during HALO–(AC)3 . . . . . . . 33 3.1 The HALO–(AC)3 Campaign . . . . . . . . . . . . . . . . . . . . . . 333.2 Aircraft and Instrumentation . . . . . . . . . . . . . . . . . . . . . . 33 3.2.1 Irradiance Measurements . . . . . . . . . . . . . . . . . . . . . 34 3.2.2 Radar and Lidar . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.3 VarCloud Microphysical Retrieval . . . . . . . . . . . . . . . . . . . . 38 3.4 Case Studies of Arctic Cirrus . . . . . . . . . . . . . . . . . . . . . . 39 3.4.1 Radar and Lidar Measurements . . . . . . . . . . . . . . . . . 42 3.4.2 BACARDI Measurements . . . . . . . . . . . . . . . . . . . . 43 Chapter 4: Radiative Transfer Simulations . . . . . . . . . . . . . . . . 47 4.1 ecRad and IFS Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 4.1.1 Surface Albedo Parameterization . . . . . . . . . . . . . . . . 49 4.1.2 Ice Optics Parameterizations . . . . . . . . . . . . . . . . . . . 49 4.2 Sensitivity Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 4.3 libRadtran Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 Chapter 5: Comparison of Model and Measurement Results . . . . . 53 5.1 Macro- and Microphysical Representation of Arctic Cirrus in the IFS 53 5.2 Solar Irradiances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5.2.1 Solar Downward Irradiance Above Cloud . . . . . . . . . . . . 57 5.2.2 Solar Transmissivity Below Cloud . . . . . . . . . . . . . . . . 58 5.2.3 Sea Ice Albedo Influence . . . . . . . . . . . . . . . . . . . . . 59 5.2.4 Three-dimensional Effects . . . . . . . . . . . . . . . . . . . . 61 5.2.5 Aerosol Particles . . . . . . . . . . . . . . . . . . . . . . . . . 61 5.2.6 Ice Optics Parameterizations . . . . . . . . . . . . . . . . . . . 63 5.2.7 Ice Effective Radius Parameterization . . . . . . . . . . . . . . 64 5.2.8 IWC and reff,ice Input . . . . . . . . . . . . . . . . . . . . . . . 67 5.3 Terrestrial Irradiances . . . . . . . . . . . . . . . . . . . . . . . . . . 72 5.3.1 Cloud Base Temperature and Emissivity . . . . . . . . . . . . 74 5.3.2 Water Vapor Concentration . . . . . . . . . . . . . . . . . . . 75 5.3.3 Three-dimensional Effects and Aerosol Particles . . . . . . . . 77 5.3.4 Ice Optics Parameterizations . . . . . . . . . . . . . . . . . . . 77 5.3.5 IWC and reff,ice Input . . . . . . . . . . . . . . . . . . . . . . . 79 5.4 Cloud Radiative Effect . . . . . . . . . . . . . . . . . . . . . . . . . . 81 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Appendix A: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87A.1 ecRad Settings Overview . . . . . . . . . . . . . . . . . . . . . . . . . 87 A.2 Additional Figures - Terrestrial Irradiance . . . . . . . . . . . . . . . 91 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 List of Symbols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119

Remote sensing is a powerful tool for studying the marine environment; however, many images are contaminated by sun glint, the specular reflection of light from the water surface. Improved radiative transfer modelling could lead to better methods for estimating and correcting sunglint. This thesis explores the effect of using detailed numerical models of the sea surface when investigating the transfer of light through the atmosphere-ocean system. New numerical realisations that model both the shape and slope of the sea surface have been created; these contrast with existing radiative transfer models, where the air-water interface has slope but not elevation. Surface realisations including features on a scale from 3 mm to 200 m were created by a Fourier synthesis method, using up to date spectra of the wind-blown sea surface. The surfaces had mean square slopes and elevation variances in line with those of observed seas, for wind speeds up to 15 m/s. Ray-tracing using the new surfaces gave estimates of reflected radiance that were similar to those made using slope statistics methods, but significantly different in 41% of cases tested. The mean difference in the reflected radiance at these points was 19%, median 7%. Elevation-based surfaces give increased sideways scattering and reduced forward scattering of light incident on the sea surface. The elevation-based models have been applied to estimate pixel-pixel variation in ocean colour imagery and to simulate scenes viewed by three types of sensor. The simulations correctly estimated the size and position of the glint zone. Simulations of two ocean colour images gave a lower peak reflectance than the original values, but higher reflectance at the edge of the glint zone. The use of the simulation to test glint correction methods has been demonstrated, as have global Monte Carlo techniques for investigating sensitivity and uncertainty in sun glint correction. This work has shown that elevation-based sea surface models can be created and tested using readily-available computer hardware. The new model can be used to simulate glint in a variety of situations, giving a tool for testing glint correction methods. It could also be used for glint correction directly, by predicting the level of sun glint in a given set of conditions.

Tropical forests, which provide important ecosystem functions and services, are increasingly threatened by anthropogenic pressures. This has resulted in an urgent need to understand tree species diversity of those forests. Where knowledge of that diversity is largely from the botanical surveys and local ecological studies, data must inevitably be up-scaled from point observations to the landscape and regional level if a holistic perspective is required. This thesis explores aspects of the spatio-temporal heterogeneity of canopy reflectance patterns over the forests of French Guiana, in order to assess whether this information could help defining an ecologically consistent forest typology. To gain insight into both the spatial and temporal heterogeneity of French Guiana’s forests, instrumental artefacts affecting the satellite data first had to be addressed. Data used in this study represent the spectral response of forest canopies, and the way in which such data are captured makes them susceptible to the ‘bi-directional reflectance distribution function’ (BRDF). BRDF indicates that objects do not reflect light in equal proportions in all directions (isotropically). Thus, forest canopies will reflect light anisotropically depending on factors including canopy roughness, leaf optical properties and inclination, and the position of the sun relative to the sensor. The second chapter of this thesis examines how BRDF affects the canopy reflectance of forests in French Guiana, and how not correcting for BRDF affects spectral classifications of those forests. When monthly reflectance data corrected for the artefact are examined, these suggest seasonally-occurring changes in forest structure or spectral properties of French Guiana’s forests. The third chapter of this thesis thus examines temporal effects of BRDF, and used cross-regional comparisons and plot-level radiative transfer modelling to seek to understand the drivers of the monthly variation of the forests’ canopy reflectance. For the latter, the Discrete Anisotropic Radiative Transfer (DART) model was used along with aerial laser scanning (ALS) observations over different forest structures, indicating that the observed variation in reflectance (and derivatives known as vegetation indices) could not be explained by monthly variations in solar direction. At the regional scale, it was also demonstrated that forests in the Guiana Shield possess temporal variation distinct from forests in central Africa or northern Borneo, forests also lying just above the Equator. Had the observed temporal variation in vegetation indices been the result of BRDF, it would have been expected that the forests in the three zones would have similar patterns of variation, which they did not. Central African forests appear to have their greening synchronized with rainfall, whereas forests in the Guianas appear synchronized with the availability of solar radiation. Further analysis of the vegetation index time-series of observations also indicated that different types of forests in French Guiana possess distinct patterns of temporal variation, suggesting that tropical forest types can be discriminated on the basis of their respective “temporal signatures.” That was exploited in the fourth chapter of the thesis, which maps forests in French Guiana based on their combined spatio-temporal canopy reflectance patterns and by so doing presents a novel way of addressing forest typology, based on ecologically meaningful information. The thesis presented demonstrates that it is possible to adequately address remote sensing data artefacts to examine patterns of spatial and temporal variation in tropical forests. It has shown that phenological patterns of tropical rainforests can be deduced from remote sensing data, and that forest types can be mapped based on spatio-temporal canopy reflectance patterns. It is thus an important contribution to understand the ecology of tropical forests in French Guiana and to improve the toolbox of scientists dealing with the identification of spatio-temporal patterns observable in forests at the landscape level.

Tropical forests, which provide important ecosystem functions and services, are increasingly threatened by anthropogenic pressures. This has resulted in an urgent need to understand tree species diversity of those forests. Where knowledge of that diversity is largely from the botanical surveys and local ecological studies, data must inevitably be up-scaled from point observations to the landscape and regional level if a holistic perspective is required. This thesis explores aspects of the spatio-temporal heterogeneity of canopy reflectance patterns over the forests of French Guiana, in order to assess whether this information could help defining an ecologically consistent forest typology. To gain insight into both the spatial and temporal heterogeneity of French Guiana’s forests, instrumental artefacts affecting the satellite data first had to be addressed. Data used in this study represent the spectral response of forest canopies, and the way in which such data are captured makes them susceptible to the ‘bi-directional reflectance distribution function’ (BRDF). BRDF indicates that objects do not reflect light in equal proportions in all directions (isotropically). Thus, forest canopies will reflect light anisotropically depending on factors including canopy roughness, leaf optical properties and inclination, and the position of the sun relative to the sensor. The second chapter of this thesis examines how BRDF affects the canopy reflectance of forests in French Guiana, and how not correcting for BRDF affects spectral classifications of those forests. When monthly reflectance data corrected for the artefact are examined, these suggest seasonally-occurring changes in forest structure or spectral properties of French Guiana’s forests. The third chapter of this thesis thus examines temporal effects of BRDF, and used cross-regional comparisons and plot-level radiative transfer modelling to seek to understand the drivers of the monthly variation of the forests’ canopy reflectance. For the latter, the Discrete Anisotropic Radiative Transfer (DART) model was used along with aerial laser scanning (ALS) observations over different forest structures, indicating that the observed variation in reflectance (and derivatives known as vegetation indices) could not be explained by monthly variations in solar direction. At the regional scale, it was also demonstrated that forests in the Guiana Shield possess temporal variation distinct from forests in central Africa or northern Borneo, forests also lying just above the Equator. Had the observed temporal variation in vegetation indices been the result of BRDF, it would have been expected that the forests in the three zones would have similar patterns of variation, which they did not. Central African forests appear to have their greening synchronized with rainfall, whereas forests in the Guianas appear synchronized with the availability of solar radiation. Further analysis of the vegetation index time-series of observations also indicated that different types of forests in French Guiana possess distinct patterns of temporal variation, suggesting that tropical forest types can be discriminated on the basis of their respective “temporal signatures.” That was exploited in the fourth chapter of the thesis, which maps forests in French Guiana based on their combined spatio-temporal canopy reflectance patterns and by so doing presents a novel way of addressing forest typology, based on ecologically meaningful information. The thesis presented demonstrates that it is possible to adequately address remote sensing data artefacts to examine patterns of spatial and temporal variation in tropical forests. It has shown that phenological patterns of tropical rainforests can be deduced from remote sensing data, and that forest types can be mapped based on spatio-temporal canopy reflectance patterns. It is thus an important contribution to understand the ecology of tropical forests in French Guiana and to improve the toolbox of scientists dealing with the identification of spatio-temporal patterns observable in forests at the landscape level.