This dissertation deals with spectral measurements of solar radiation in the visible and near infrared wavelength range. The data were collected during a field campaign on the Cape Verde Islands in January / February 2008 within the DFG research group SAMUM 2 (Saharan Mineral Dust Experiment). During this campaign airborne measurements of upward radiances and irradiances were performed over aerosol layers. Since the Cape Verde Islands are in the advection area of air masses from the Sahara region northeast of the islands and from regions with bush fires from the southeast, the sampled aerosol mainly consists of mineral dust, biomass burning smoke or a mixture of both. These radiation measurements and airborne lidar measurements of aerosol extinction coefficients were used to calculate the dust radiative forcing at the top of atmosphere with an one-dimensional radiative transfer model. This required the spectral surface albedo and aerosol optical properties, determined by model retrievals. The dependence of the calculated dust radiative forcing on the aerosol optical thickness was used to distinguish between aerosol distributions with mineral dust only or mixed with biomass burning smoke. This mainly model-based method was compared with another mainly measurement-based method, which requires the net radiation at the flight altitude and its dependence on the aerosol optical thickness to distinguish between the different aerosol distributions. The mainly model-based method shows no differences between the calculated radiative forcings of aerosols mainly consisting of mineral dust and those mixed with biomass burning smoke due to high uncertainties. In contrast to the mainly model-based method, the mainly measurement-based method shows clear differences between aerosols with and without biomass burning smoke. Thus the mainly measurement-based method is the preferred method, because it omits the retrieval of the aerosol optical properties, which leads to high uncertainties, in contrast to the mainly model-based method.

Despite large efforts and decades of research, the scientific understanding of how aerosols impact climate by modulating microphysical cloud properties is still low and associated radiative forcing estimates (RFaci ) vary with a wide spread. But since anthropogenically forced aerosol-cloud interactions (ACI) are considered to oppose parts of the global warming, it is crucial to know their contribution to the total radiative forcing in order to improve climate predictions. To obtain a better understanding and quantification of ACI and the associated radiative effect it as been suggested to use concurrent measurements and observationally constrained model simulations. In this dissertation a joint satellite-reanalysis approach is introduced, bridging the gap between climate models and satellite observations in a bottom-up approach. This methodology involves an observationally constrained aerosol model, refined and concurrent multi-component satellite retrievals, a state-of-the-art aerosol activation parameteriza- tion as well as radiative transfer model. This methodology is shown here to be useful for a quantitative as well as qualitative analysis of ACI and for estimating RFaci . As a result, a 10-year long climatology of cloud condensation nuclei (CCN) (particles from which cloud droplets form) is produced and evaluated. It is the first of its kind providing 3-D CCN concentrations of global coverage for various supersaturations and aerosol species and offering the opportunity to be used for evaluation in models and ACI studies. Further, the distribution and variability of the resulting cloud droplet numbers and their susceptibility to changes in aerosols is explored and compared to previous estimates. In this context, an analysis by cloud regime has been proven useful. Last but not least, the computation and analysis of the present-day regime-based RFaci represents the final conclusion of the bottom-up methodology. Overall, this thesis provides a comprehensive assessment of interactions and uncertainties related to aerosols, clouds and radiation in regimes of liquid water clouds and helps to improve the level of scientific understanding.

(English)Ozone is one of the most important greenhouse gases in terms of radiative forcing, as aresult of increasing in its precursor emissions since pre-industrial times. Until recently,the ozone radiative forcing calculations were entirely model based, exhibiting high uncertaintiesand a large spread in model values, as shown in the Intergovernmental Panelon Climate Change, Assessment Report 5. Satellite sounders operating in the infrarednow offer the possibility to infer directly the longwave radiative effect (LWRE) of ozone.The hyperspectral measurements allow to retrieve a vertical profile of ozone, and also thevertical distribution of the LWRE, apart from its column integrated value. The separationbetween troposphere and stratosphere allows to better constrain model estimates ofozone radiative forcing, but also support the predictions for its future evolution.In this thesis, a new method for calculating the ozone LWRE is presented, by exploitingthe measurements of the Infrared Atmospheric Sounding Interferometer on board theMetop satellites. The method is based on the calculation of the Instantaneous RadiativeKernel (IRK), which implies the angular integration of the radiance (inthe 9.6 μm band) at the top of the atmosphere using a Gaussian Quadrature. This quantityis transformed into a radiative flux density (the LWRE) by multiplicationwith the ozone profile retrieved by FORLI, for each atmospheric scene. The LWRE calculationmethod is applied to IASI non-cloudy scenes, for day and night, for the periodof 01/10/2007 to 31/12/2016. The results are analyzed separately for the total column ofozone, and for its tropospheric and stratospheric components; they are compared to estimationsdetermined independently from the TES (Tropospheric Emission Spectrometer)measurements on-board Aura, and from three state-of the-art chemistry-climate models.The discussion of the results is focused then on the spatial and temporal variability ofthe LWRE in the troposphere and stratosphere, as well as the on the trends over 9 yearsof measurements.(French)L’ozone est actuellement l’un des gaz à effet de serre les plus importants en terme de forçage radiatif ;sa contribution est liée à l’augmentation des émissions de ses précurseurs depuis l’époque préindustrielle. Jusqu’à récemment, le calcul du forçage radiatif de l’ozone était entièrement basé sur des modèles et était sujet à de grandes incertitudes, qui se révèlent notamment par la large gamme des valeurs calculées et intégrées dans le Cinquième Rapport d’Évaluation du Groupe d’experts intergouvernemental sur l’évolution du climat (GIEC). Les sondeurs embarqués sur des satellites et travaillant dans le domaine de l’infrarouge thermique donnent aujourd’hui la possibilité de directement mesurer l’effet radiatif de l’ozone au niveau de la radiation infrarouge sortante. La possibilité qu’offrent les mesures hyperspectrales pour restituer un profil vertical d’ozone permet par ailleurs de fournir la distribution verticale du forçage radiatif, au-delà se valeur intégrée sur la colonne atmosphérique. La séparation entre la troposphère et la stratosphère est importante en particulier pour contraindre les estimations des modèles mais aussi pour prédire l’évolution future du forçage radiatif. Dans cette thèse, nous présentons une méthode de calcul de l’effet radiatif de l’ozone qui exploite les mesures de l’Interféromètre Atmosphérique de Sondage dans l’Infrarouge (IASI) à bord des satellites Metop en orbite polaire. La méthode se base sur le calcul, pour chaque mesure de IASI, d’une grandeur appelée Instantaneous Radiative Kernel (IRK), impliquant l’intégration angulaire de la radiance (dans la bande d’absorption d’ozone centrée à 9.6µm) au sommet de l’atmosphère via une quadrature de Gauss. Cette quantité est transformée en une densité de flux radiatif (appelée Longwave Radiative Effect, LWRE) par multiplication par le profil d’ozone restitué par le logiciel FORLI, pour la scène atmosphérique en question. La méthode du calcul du LWRE est appliquée aux scènes non nuageuses de IASI, de jour comme de nuit, pour la période du 01/10/2007 au 31/12/2016. Les résultats sont analysés séparément pour la colonne totale d’ozone mais également pour ses composantes troposphériques et stratosphériques ;ils sont comparés aux estimations déterminées de façon indépendantes des mesures de l’instrument TES (Tropospheric Emission Spectrometer) sur AURA. La discussion de nos résultats se focalise ensuite sur la variabilité spatiale et temporelle du LWRE dans la troposphère et la stratosphère ;des résultats préliminaires concernant les tendances sur les 9 années de mesures sont fournis. Le manuscrit est structuré en différentes parties. Après une série de chapitres introductifs décrivant les bases nécessaires à ce travail, nous présentons l’instrument IASI et l’algorithme FORLI dédié à la restitution des concentrations d’ozone. La méthode de calcul du LWRE, au centre de notre travail de recherche, est décrite avec ses fondements mathématiques dans un chapitre dédié. Les distributions spatiales et verticales du LWRE, ainsi que son évolution temporelle sur 9 ans, d’une part pour l’effet radiatif de l’ozone total et d’autre part pour sa contribution troposphérique/stratosphérique sont discutées dans les derniers chapitres, qui incluent également une brève comparaison des estimations du LWRE par trois modèles de chimie-climat différents. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

The optimum ordering strategies for the coded V-BLAST system with capacity achieving temporal codes on each stream are studied in this thesis. Mathematical representations of the optimum detection ordering strategies for the coded V-BLAST under instantaneous rate allocation (IRA), uniform power/rate allocation (URA), instantaneous power allocation(IPA) and instantaneous power/rate allocation (IPRA) are derived. For two transmit antennas, it is shown that the optimum detection strategies are based on the per-stream before-processing channel gains. Based on approximations of the per-stream capacity equation, closed-form expressions of the optimal ordering strategy under the IRA at low and high signal to noise ratio (SNR) are derived. Necessary optimality conditions under the IRA are given. Thresholds for the low, intermediate and high SNR regimes in the 2-Tx-antenna system under the IPRA are determined, and the SNR gain of the ordering is studied for each regime. Performances of simple suboptimal ordering strategies are analysed, some of which perform very close to the optimum one.

We consider a variety of types of vertex sequences, which are defined in terms of a requirement that the next vertex in the sequence must meet. For example, let S = (v1, v2, …, vk ) be a sequence of distinct vertices in a graph G such that every vertex vi in S dominates at least one vertex in V that is not dominated by any of the vertices preceding it in the sequence S. Such a sequence of maximal length is called a dominating sequence since the set {v1, v2, …, vk } must be a dominating set of G. In this paper we survey the literature on dominating and other related sequences, and propose for future study several new types of vertex sequences, which suggest the beginning of a theory of vertex sequences in graphs.

It is often desirable to study simulated turbulent flows at steady state even if the flow has no inherent source of turbulence kinetic energy. Doing so requires a numerical forcing scheme and various methods have been studied extensively for turbulence that is isotropic and homogeneous in three dimensions. A review of these existing schemes is used to form a framework for more general forcing methods. In this framework, the problem of developing a forcing scheme in Fourier space is abstracted into the two problems of (1) prescribing the spectrum of the input power and (2) specifying a force that has the desired characteristics and that adds energy to the flow with the correct spectrum. The framework is used to construct three forcing schemes for horizontally homogeneous and isotropic, vertically stratified turbulence. These schemes are implemented in large-eddy simulations and their characteristics analyzed. Which method is “best” depends on the purpose of the simulations, but the framework for specifying forcing schemes enables a systematic approach for identifying a method appropriate for a particular application.

No description available.

No description available.

As the world becomes more globalised, user equipment such as smartphones and Internet of Things devices require increasingly more data, which increases the demand for wireless data traffic. Hence, the acceleration of next-generational networks (5G and beyond) focuses mainly on increasing the bitrate and decreasing the latency. A crucial technology for 5G and beyond is the massive MIMO. In a massive MIMO system, a detector processes the received signals from multiple antennas to decode the transmitted data and extract useful information. This has been implemented in many ways, and one of the most used algorithms is the Zero Forcing (ZF) algorithm. This thesis presents a novel parallel design to accelerate the ZF algorithm using the Cholesky decomposition. This is implemented on a GPU, written in the CUDA programming language, and compared to the existing state-of-the-art implementations regarding latency and throughput. The implementation is also validated from a MATLAB implementation. This research demonstrates promising performance using GPUs for massive MIMO detection algorithms. Our approach achieves a significant speedup factor of 350 in comparison to a serial version of the implementation. The throughput achieved is 160 times greater than a comparable GPU-based approach. Despite this, our approach reaches a 2.4 times lower throughput than a solution that employed application-specific hardware. Given the promising results, we advocate for continued research in this area to further optimise detection algorithms and enhance their performance on GPUs, to potentially achieve even higher throughput and lower latency. / <p>Our examiner Mahdi wants to wait six months before the thesis is published. </p>

Watershed models are powerful tools for simulating different scenarios to understand the impact of management practices and are used to support and guide decision-making. However, there are often challenges and limitations to using watershed models in some areas of watershed modeling; 1) model calibration in the areas with data limitations; 2) acquiring complete weather data that accurately reflect watershed model responses; 3) accurate representation of manure operation in watershed models. This dissertation addresses each of the aforementioned challenges using new approaches and tools in three studies with the main objective of achieving a better prediction of water quality and quantity and enhancing watershed models. Chapter 2 presents a method (multi-basin calibration (MBC)) to estimate watershed model parameters that lack long-term streamflow records. In the MBC method, first, the Soil and Water Assessment Tool (SWAT) models are initialized individually for several similar neighboring watersheds with a short period of measured streamflow. Then, we aggregate the simulated and observed flows from each initialization with short histories to generate a combined observed-simulated streamflow record that is longer than the initial length of each individual member in order to increase the information content. The Nash-Sutcliffe efficiency (NSE) from this merged time series was used as the basis for calibrating using a differential evolution algorithm. To evaluate the MBC, SWAT models for three newly instrumented USGS gages in Lake Champlain Basin of Vermont, USA, were compared to the commonly used similarity-based regionalization (SBR) approach. Results demonstrate that short periods of hydrological measurement from multiple locations in a basin can represent a system similar to long-term measurements. Chapter 3 develops a method to generate a complete weather data time series with the integration of multiple Global Historical Climatology Network (GHCN) stations and to assess the benefit of much higher density, lower reliability precipitation measurements from private citizens collected by the Community Collaborative Rain, Hail, and Snow (CoCoRaHS) network data that was integrated into the GHCN. To evaluate the performance of the methodology, generated weather data is used to force the Soil and Water Assessment Tool (SWAT) models of 21 United States Department of Agriculture (USDA)-Agricultural Research Service (ARS)-Natural Resource Conservation Service (NRCS)-Conservation Effects Assessment Project (CEAP) watersheds to simulate daily streamflow. The results demonstrated that integration of multiple GHCN stations including higher-density, but perhaps lower-quality weather data can enhance model performance. A comparison with published SWAT model results further corroborated improved model performance using newly combined GHCN data. Chapter 4 develops a hybrid SWAT model, SWAT-Dairy, to accurately represent the impact of manure operation on nutrient transport. The SWAT-Dairy model incorporates process-based livestock routines, developed in the R platform, which quantify daily manure production, stored manure, daily total nitrogen (N) and phosphorus (P), organic and mineral N and P, and dynamic manure nutrient fractions based on animal characteristics, feed characteristics, and environmental conditions. Outputs are then used in SWAT to simulate the impact of livestock manure production. The new model, with simulated manure application management, is applied to a farm in the Little Otter Creek Basin in Vermont, US. Subbasin- and farm-level N and P losses from manure management using the new model were compared for different feed management scenarios. / Doctor of Philosophy / In the past few decades, watershed management has become more challenging due to rapid population growth, climate change, and agricultural practices. In order to achieve better watershed management strategies, it is essential to understand the complex interaction between different biological, physical, and chemical processes occurring in the watershed. Watershed models are useful tools that help scientists and engineers to understand and predict how climate and land-use changes and agricultural management practices affect different components of a watershed system. While watershed models have many advantages, they are often limited by challenges and obstacles, such as model parameter estimations in the areas with limited measured streamflow data, acquiring complete and accurate weather data, and explicit representation of animal management impacts on water quality in manure applications. This dissertation addresses the challenges mentioned earlier by developing new approaches and methods that improve water quality and quantity using watershed models. A long record of measured streamflow data is necessary for watershed models to accurately represent watershed systems and estimate the parameters that cannot be directly measured. However, many watersheds worldwide are not monitored or are newly instrumented with a short period of recorded data. Chapter 2 introduces a new approach (multi basin calibration (MBC)) that integrates short periods of recorded data from several watersheds to provide a similar representation of the watershed system as long-term records. MBC was compared with a commonly used method that requires long recorded streamflow data from a neighboring watershed. The results showed that MBC improved model results and captured hydrological processes better for the watershed with a short period of recorded data than the traditionally used method. Obtaining accurate weather data for a watershed model can also be challenging since land-based weather stations often contain missing data. In recent years, hydrological modelers and researchers have access to the much higher density of weather measurements from private citizens that collect data with inexpensive equipment. However, no study has evaluated the benefits of using much higher-density data from private citizens for watershed modeling. Chapter 3 presents a new methodology to acquire complete weather data time series with the integration of all weather stations, including higher density private citizen-based measurements. Then the weather data were used to force watershed models of 21 watersheds across the United States. The results showed that the new methodology provides weather data that reflect the watershed model response with satisfactory performance ratings in 18 out of 21 watersheds. Lastly, chapter 4 develops a dairy model and integrates it into one of the most commonly used watershed models, the Soil and Water Assessment Tool (SWAT), to investigate how different farm management scenarios impact manure production and nutrient contents as well as their consequent effect on water quality during manure application on farm fields.