Clouds have a large impact on the Earth’s radiation and energy budget and play consequently a crucial role in prediction of climate change. At the same time, they are highly variable in time and space. To study and distinguish the different influences of clouds on the climate system it is useful to separate clouds into individual cloud regimes. In this thesis a new cloud classification and their response to disturbed cloud droplet number concentration is presented. Liquid water clouds at cloud scale are separated on the basis of cloud properties derived from combined A-Train satellite measurements involving the MODIS measurements onboard Aqua, the CloudSat cloud radar and the CALIPSO cloud lidar. Using the combined MODIS and CALIPSO cloud-top phase discrimination, liquid water clouds are identified. The high resolved vertical measurements of the CALIPSO lidar provide three cloud base height classes and the spatial variability of cloud top height within a 20 km footprint as an inhomogeneity parameter from which two cloud inhomogeneity classes are defined resulting in a total of six liquid cloud classes. The classification smoothly disentangles marine and continental clouds as well as stratiform and cumuliform clouds in different latitudes at the high spatial resolution of about 20 km. Analyzing the cloud droplet effective radius reff , cloud optical thickness τc , adiabatic liquid water path Lad, adiabatic cloud droplet number concentration Nc,ad and cloud geometrical thickness Hthick,CC derived from collocated combined MODIS, CloudSat and CALIPSO measurements shows a useful discrimination between cloud regimes. Further separations between non precipitating and precipitating clouds using the CloudSat precipitation flag as well as between three classes of free tropospheric relative humidity from a meteorological reanalysis above cloud top are made to investigate adjustments to aerosol-cloud interactions for individual cloud regimes. For this, the cloud liquid water path response, cloud thickness response, and cloud fraction response to perturbed cloud droplet concentration is analyzed. All sensitivities depend on the chosen cloud or environmental parameter indicating the importance of analyzing aerosol-cloud interactions for particular cloud regimes since similar clouds with similar cloud parameter responses are grouped together helping to identify individual behavior of these cloud regimes to perturbations in cloud droplet number concentration.

The practical handling and analysis of satellite data is outlined using the programming language Python. The limb sounding technique of the SABER instrument on board of the TIMED satellite delivers vertical profiles of kinematic temperature from the stratosphere (∼30 km) up to the lower thermosphere (∼120 km). The procedure may be summarised as follow: In the first step the level 2 data for one month are extracted from the netCDF format and arranged into a new altitude-latitude grid for the ascending and descending orbits. The longitudinal structure is rearranged applying the decomposition into zonal harmonics. Various cross sections of the data give a good overview of the thermal structure and dynamics of the atmosphere up to 120 km. The monthly values of the zonal averaged temperature are compared to the available data from stratospheric reanalyses up to 60 km as well as the initialized background climatology of general circulation models for the middle atmosphere. / In diesem Artikel soll der praktische Umgang mit Satellitendaten und deren Auswertung unter Verwendung der Programmiersprache Python skizziert werden. Auf der Basis der Horizontsondierungen des SABER Instruments auf dem TIMED Satelliten werden vertikale Profile wie die kinetischen Temperatur von der Stratosphäre (∼30 km) bis zur unteren Thermosphäre (∼120 km) gewonnen. Die Arbeitsschritte bei der Analyse lassen sich wie folgt gliedern: Als erstes werden die Level 2 Produkte eines Monats aus dem netCDF Format extrahiert und an ein neues Höhen-Breiten Gitter für jeden auf- und absteigenden Orbit angepasst. Die Längenstruktur wird mit Hilfe einer Zerlegung in harmonische Funktionen regularisiert. Diverse Querschnitte der Daten geben ein guten Überblick über die thermischen Struktur und Dynamik der Atmosphäre bis 120 km. Die Monatswerte des Zonalmittels der Temperatur werden mit denen aus operationellen Reanalysedaten (∼60 km) sowie der Hintergrundklimatologie von Zirkulationsmodellen der mittleren Atmosphäre verglichen.

Philosophiae Doctor - PhD / Wetlands are highly productive systems that act as habitats for a variety of flora and fauna. Despite their ecohydrological significance, wetland ecosystems are under severe threat as a result of environmental changes (e.g. the changing temperature and rainfall), as well as pressure from anthropogenic land use activities (e.g. agriculture, rural-urban development and dam construction). Such changes result in severe disturbances in the hydrology, plant species composition, spatial distribution, productivity and diversity of wetlands, as well as their ability to offer critical ecosystem goods and services. However, wetland degradation varies considerably from place to place, with severe degradation occurring particularly in developing regions, such as sub-Saharan Africa, where Land Use and Land Cover changes impact on wetland ecosystems by affecting the diversity of plant species, productivity, as well as the wetland hydrology.

The capabilities of a number of remote-sensing techniques for biophysical mapping in the subarctic have been examined at Pen Island in northwestern Ontario. After a two week field reconnaissance, colour infrared aerial photography was studied and a detailed biophysical map of the area was produced. Using this knowledge LANDSAT satellite data of the site were investigated. In a visual analysis of the data, the majority of the units identified in the airphoto interpretation were detected, and these were distinguished primarily by their spectral characteristics. Digital analysis of the satellite data using the Bendix MAD system allowed many of the classes of the earlier studies to be delineated and also permitted the classification to be readily extended beyond the original site. In both LANDSAT analyses specific biophysical units could be mapped from the satellite data but could not be identified without the airphoto interpretation. / Thesis / Master of Science (MSc)

Infrastructural investments are crucial drivers for promoting growth and activating virtuous cycles of development. Their allocation processes and their socio-economic impact are themes of fundamental importance for development economics. The first two chapters of this thesis employ quasi-experimental methods to analyze the Road Sector Development Programme (RSDP), a large-scale infrastructural investment project implemented in Ethiopia between 1998-2016. The first chapter investigates whether road investment decisions have been influenced by ethnic favoritism mechanisms benefiting the Tigray People’s Liberation Front (TPLF), the dominant component of the Ethiopian People’s Revolutionary Democratic Front (EPRDF). We find evidence of a significant misallocation of public resources towards areas inhabited by the Tigray ethnicity with respect to a suitable control group. The second chapter looks at the impact of the increase in market access due to the RSDP on the productivity of formal and informal Ethiopian firms. Given the important role of informality in Sub-Saharan Africa, it is paramount to disentangle their reaction to productivity shocks from that of formal enterprises. We detect an increase in productivity for formal firms and a decrease in the likelihood of a firm being informal, compatible with the “entry into informality” of less productive formal enterprises and with the presence of informal “survivalist” firms at lower tiers of the productivity distribution. The third chapter employs near-real time satellite data to assess the economic and environmental impact of the Covid-19 contagion containment measures enacted by a selected group of Arab countries, therefore bringing to prominence the use of large, granular, and publicly available datasets for informing crisis response.

Visualization is the process of constructing methods, which are able to synthesize interesting and informative images from data sets, to simplify the process of interpreting the data. In this thesis a new approach to construct meteorological visualization methods using neural network technology is described. The methods are trained with examples instead of explicitely designing the appearance of the visualization. This approach is exemplified using two applications. In the fist the problem to compute an image of the sky for dynamic weather, that is taking account of the current weather state, is addressed. It is a complicated problem to tie the appearance of the sky to a weather state. The method is trained with weather data sets and images of the sky to be able to synthesize a sky image for arbitrary weather conditions. The method has been trained with various kinds of weather and images data. The results show that this is a possible method to construct weather visaualizations, but more work remains in characterizing the weather state and further refinement is required before the full potential of the method can be explored. This approach would make it possible to synthesize sky images of dynamic weather using a fast and efficient empirical method. In the second application the problem of computing synthetic satellite images form numerical forecast data sets is addressed. In this case a mode is trained with preclassified satellite images and forecast data sets to be able to synthesize a satellite image representing arbitrary conditions. The resulting method makes it possible to visualize data sets from numerical weather simulations using synthetic satellite images, but could also be the basis for algorithms based on a preliminary cloud classification. / Report code: LiU-Tek-Lic-2004:66.

Obtaining an accurate estimate of a land-cover classifier's performance over a wide geographic area is a challenging problem due to the need to generate the ground truth that covers the entire area that may be thousands of square kilometers in size. The current best approach constructs a testing dataset by drawing samples randomly from the entire area --- with a human supplying the true label for each such sample --- with the hope that the selections thus made statistically capture all of the data diversity in the area. A major shortcoming of this approach is that it is difficult for a human to ensure that the information provided by the next data element chosen by the random sampler is non-redundant with respect to the data already collected. In order to reduce the annotation burden, it makes sense to remove any redundancies from the entire dataset before presenting its samples to a human for annotation. This dissertation presents a framework that uses a combination of clustering and compression to create a concise-set representation of the land-cover data for a large geographic area. Whereas clustering is achieved by applying Locality Sensitive Hashing (LSH) to the data elements, compression is achieved through choosing a single data element to represent a given cluster. This framework reduces the annotation burden on the human and makes it more likely that the human would persevere during the annotation stage. We validate our framework experimentally by comparing it with the traditional random sampling approach using WorldView2 satellite imagery.

Understanding the quality of the air we breathe is critical in quantifying the impact that atmospheric chemistry has on health. Poor air quality increases the risk of heart and lung diseases as well as having a detrimental effect on climate, ecology and the built environment. The burning of fossil fuels and plant matter (biomass burning) creates large quantities of gases and particulate matter that impact air quality and the air we breathe. Biomass burning is estimated to contribute 400 Tg of non-methane organic compounds, 40 Tg of methane and 7.1 Tg of nitrogen oxides to the atmosphere each year. This thesis aims to better understand the role of biomass burning on air quality and tropospheric chemistry. The in depth analysis presented here addresses of the impact of boreal biomass burning in North America on air quality, in particular, carbon monoxide (CO) and ozone (O3). By using a number of different modelling techniques along with data collected from a field campaign and satellites the transport and chemistry of biomass burning emissions were analysed and quantified. The first research chapter of the thesis used the GEOS-Chem atmospheric chemistry transport model to interpret aircraft measurements of CO in biomass burning outflow taken during the 2011 BORTAS-B campaign over Canada. The model has some skill reproducing the observed variability, but has a positive bias for observations < 100 ppb and a negative bias for observations > 300 ppb. It was found that observed CO variations are largely due to fires over Ontario, with smaller and less variable contributions from fossil fuel combustion from eastern Asia and NE North America. To help interpret observed variations of CO an effective physical age of emissions (¯A) metric was developed. It was found that during BORTAS-B the age of emissions intercepted over Halifax, Nova Scotia is typically 4–11 days, and on occasion as young as two days. The analysis shows that ¯A is typically 1–5 days older than the associated photochemical ages inferred from co-located measurements of different hydrocarbons. It is argued that a robust observed relationship between CO and black carbon aerosol during BORTAS-B (r² > 0.7), form the basis of indirect evidence that aerosols co-emitted with gases during pyrolysis markedly slowed down the plume photochemistry during BORTAS-B with respect to photochemistry at the same latitude and altitude in clear skies. The second research chapter focuses on O3 production downwind from boreal biomass burning. Using the GEOS-Chem model, the O3 chemistry within a biomass burning plume from a fire on 17 July 2011 in mid-Canada was examined. The model shows a significant positive bias (~20 ppb) in reproducingO3 mixing ratios over North America for July 2011 when compared to observations. Reducing NO emissions from lightning and fossil fuel by 50% and 54% respectively reduced this bias to ~10 ppb. The cause of the remaining bias is uncertain. Using a novel technique with the model, the centre of the biomass burning plume was tracked and O3 concentrations and chemistry was extracted from the centre of the plume. The biomass burning enhanced O3 concentrations throughout the plume by between 1 – 20 ppb when compared with the same plume path with no biomass burning. The plume was characterised as being NOx-rich for the initial four days of transport. The sensitivity of the O3 chemistry to different emissions was calculated and it was found that the O3 is initially highly sensitive to NO emissions from biomass burning and then to NO emissions from fossil fuels as it travels across an urban area surrounding Quebec City. The O3 net production was found to initially decrease with an increase in NO but increase further downwind. The final research chapter of the thesis uses long-term satellite observations to evaluate natural variability in CO concentrations over the North Atlantic. 15 years of MOPITT CO column observations were used along with modelled CO from the GEOS-Chem model. The model was evaluated against the MOPITT overpass and shows a negative bias of between -8% and -24% over the northern mid-latitudes with the largest bias seen in spring. The model has a large positive bias (8% – 40%) over the Amazon,West Africa and Indonesia through all seasons. Using Empirical Orthogonal Function (EOF) analysis on the MOPITT and GEOS-Chem CO columns shows the largest mode of variability seen in the North Atlantic to be the oxidation of methane for winter and spring, biomass burning during summer and fossil fuel combustion from East Asia during autumn.

To predict the performance of an electro-optical sensor system (EO-system) requires taking the weather situation into consideration. The possibility to use weather data from satellites instead of ground – and flight stations has been investigated. Nearly 170 satellites (about 10% of the functional satellites in orbit) were found to have atmosphere and weather monitoring. A method to select satellite data has been created based on three criteria: (1) the satellite should have a least one payload that measure a weather parameter for EO-system, (2) it should be possible to download data, free of charge, from the specified payload and (3) the satellite should cover geographical areas of interest for a potential user. The investigated performance property is the range, which is affected by many weather parameters, and focus has been on aerosols. The mean value for the aerosol extinction coefficient, for day- and nighttime conditions in December 2016, from the satellite CALIPSO’s lidar instrument Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) has been downloaded from www.earthdata.nasa.gov and implemented in a new developed application to predict the range for an EO-system. In the satellite data, from December 2016, it could be seen that the presence of aerosols, on a global scale, appears below 5 km and that the concentration of aerosols for nighttime condition is higher in local areas. For the test wavelength band of 0.9–2.5 µm, the application showed that the aerosol impact reduced the range by nearly 87%, if the EO-system was in a layer with aerosols. The application for the range prediction of EO-systems is on an early stage and need further development, especially its weather and scene parameters, to become a successful tool for a potential user in the future. / Att förutsäga prestandan hos ett elektro-optiskt sensorsystem (EO-system) kräver att man tar hänsyn till bland annat förhållandet i atmosfären. Möjligheten att använda väderdata från satelliter istället för mark- och flygstationer har undersökts. Det hittades nästan 170 satelliter (cirka 10% av de fungerande satelliterna i omloppsbana) med inriktning på atmosfär- och väderövervakning. En metod för att välja ut satellitdata har skapats som baseras på tre kriterier: (1) satelliten ska ha minst ett instrument som mäter en väderparameter för EO-system, (2) man ska, från internet, kunna ladda ner mätdata från det specifika instrumentet och (3) satelliten ska passera över ett område som är av intresse för en potentiell användare. Den prestandaegenskap som har undersökts är räckvidden, som påverkas av flera väderparametrar, där fokus har legat på inverkan från aerosoler. Medelvärdet för extinktionskoefficienten av aerosoler, för dag och natt i december 2016, från satelliten CALIPSO’s lidarinstrument Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) laddades ner från www.earthdata.nasa.gov och användes i en nyutvecklad applikation för att förutsäga räckvidden hos ett EO-system. Från satellitens mätningar i december 2016 kunde man se att förekomsten av aerosoler mestadels befann sig, globalt sett, uppdelat i olika lager under 5 km höjd och att koncentrationen av aerosoler är högre på natten i lokala områden. Applikationens beräkningar visade att förekomsten av aerosoler påverkade räckvidden för exempel våglängdsbandet 0.9–2.5 µm med en försämring upp till 87% när EO-systemet befann sig i ett skikt av aerosoler. Applikationen för att förutsäga räckvidden hos EO-system är i dess begynnelse och kräver vidareutveckling av både väder- och scenparametrar för att det ska bli ett framgångsrikt verktyg.

Dados de gravimetria e de altimetria por satélite foram usados como subsídio à análise morfoestrutural na região da Bacia de Pelotas-RS. Na abordagem gravimétrica foi usado o modelo geopotencial EGM2008 através das anomalias Bouguer e na abordagem batimétrica foi usado o modelo global DTU10BAT. Através dos mapas de anomalias Bouguer e perfis gravimétricos gerados, verificou-se que as anomalias Bouguer aumentam positivamente da costa em direção às maiores profundidades oceânicas, o que caracteriza um progressivo afinamento crustal associado à deriva continental. O comportamento das anomalias Bouguer obtidas por dados satelitais evidenciaram a presença de uma ruptura conhecida como Charneira Albo-aptiana na plataforma continental. A incidência de valores de anomalias significativamente positivas na região do Baixo de Mostardas sugere a presença de uma massa de maior densidade nesta região. A resolução dos dados gravimétricos utilizados não permitiu evidenciar a presença de paleocanais na região, sendo necessária uma maior resolução espacial, associada a outros métodos de investigação. O uso de dados de altimetria por satélite (modelo DTU10BAT) permitiu a análise batimétrica da plataforma continental e a investigação da configuração morfológica da região, que foi dividida em três faixas: Torres- Farol Solidão, Farol Solidão-Farol da Conceição e Farol da Conceição-Farol Sarita. Foi gerado um modelo teórico e comparado com o modelo DTU10BAT na geração do mapa de anomalias batimétricas. Os eixos de anomalias batimétricas negativas identificados estão frequentemente associados à direção de paleodrenagens, assim como as anomalias positivas tem relação com linhas de paleoestabilizações do nível do mar ou altos estruturais. Foi definida uma sequência de descontinuidades na altura do Farol da Conceição que apresentou expressiva coincidência com paleocanais delineados na mesma região através de outros estudos. Todos os dados foram processados e integrados em um sistema de informações geográficas. Os dados gravimétricos e batimétricos oriundos de missões satelitais são uma grande ferramenta nos estudos regionais para áreas que envolvam aplicações geológicas e mesmo oceanográficas. / Data from satellite altimetry and gravity were used to the morphostructural analysis in the Pelotas Basin-RS region. The EGM2008 geopotential model through the Bouguer anomalies was used in the gravimetric approach and the DTU10BAT global model was used in the bathymetric approach. Through the Bouguer anomalies maps and the gravimetric profiles that were generated, it was observed that Bouguer anomalies increase positively from coast towards to the major ocean depths, what characterizes a progressive crustal thinning associated with the continental drift. The behavior of the Bouguer anomalies obtained from satellite data showed the presence of a rupture, known as Charneira Albo-Aptiana, on the continental shelf. The incidence of significant positive anomalies values on the Baixo de Mostardas region suggests the presence of a higher-density mass in this region. Because of the resolution of the gravimetric data used in this research was not enough, it was not possible to show the presence of paleochannels in the region, requiring a greater spatial resolution data, associated with other methods of investigation. The use of satellite altimetric data (model DTU10BAT) allowed the bathymetric analysis of the continental shelf and the research of morphological configuration of the region, which was divided into three areas: Torres- Solidão Lighthouse, Solidão Lighthouse-Conceição Lighthouse and Conceição Lighthouse-Sarita Lighthouse. A theoretical model was generated and it was compared with the DTU10BAT model in the generation of the bathymetric anomalies map. The axes of negative bathymetric anomalies identified are often associated with the direction of paleochannels, as well as the positive anomalies are related to lines of sea level paleostabilizations or structural highs. It was defined a sequence of discontinuities at the Conceição Lighthouse proximities which presented a significant coincidence with paleochannels that were delineated in the same region through other studies. The data were processed and integrated in a geographic information system. Gravimetric and bathymetric data from satellite missions are an important tool in regional studies for areas that involve geological and oceanographic applications.