Soil biogenic emissions of nitric oxide from arid and semi-arid ecosystems

The biogenic production of NO in the soil accounts for between 10% and 40% of the global total. A large degree of the uncertainty in the estimation of the biogenic emissions stems from a shortage of measurements in arid regions, which comprise 40% of the earth’s land surface area. This study examined the emission of NO from three ecosystems in southern Africa which cover an aridity gradient from semi-arid savannas in South Africa to the hyper-arid Namib Desert in Namibia. A laboratory method was used to determine the release of NO as a function of the soil moisture and the soil temperature. Various methods were used to up-scale the net potential NO emissions determined in the laboratory to the vegetation patch, landscape or regional level. The importance of landscape, vegetation and climatic characteristics is emphasized. The first study occurred in a semi-arid savanna region in South Africa, where soils were sampled from 4 landscape positions in the Kruger National Park. The maximum NO emission occurred at soil moisture contents of 10%-20% water filled pore space (WFPS). The highest net potential NO emissions came from the low lying landscape positions, which have the largest nitrogen (N) stocks and the largest input of N. Net potential NO fluxes obtained in the laboratory were converted in field fluxes for the period 2003-2005, for the four landscape positions, using soil moisture and temperature data obtained in situ at the Kruger National Park Flux Tower Site. The NO emissions ranged from 1.5-8.5 kg ha-1 a-1. The field fluxes were up-scaled to a regional basis using geographic information system (GIS) based techniques, this indicated that the highest NO emissions occurred from the Midslope positions due to their large geographical extent in the research area. Total emissions ranged from 20x103 kg in 2004 to 34x103 kg in 2003 for the 56000 ha Skukuza land type. The second study occurred in an arid savanna ecosystem in the Kalahari, Botswana. In this study I collected soils from four differing vegetation patch types including: Pan, Annual Grassland, Perennial Grassland and Bush Encroached patches. The maximum net potential NO fluxes ranged from 0.27 ng m-2 s-1 in the Pan patches to 2.95 ng m-2 s-1 in the Perennial Grassland patches. The net potential NO emissions were up-scaled for the year December 2005-November 2006. This was done using 1) the net potential NO emissions determined in the laboratory, 2) the vegetation patch distribution obtained from LANDSAT NDVI measurements 3) estimated soil moisture contents obtained from ENVISAT ASAR measurements and 4) soil surface temperature measurements using MODIS 8 day land surface temperature measurements. This up-scaling procedure gave NO fluxes which ranged from 1.8 g ha-1 month-1 in the winter months (June and July) to 323 g ha-1 month-1 in the summer months (January-March). Differences occurred between the vegetation patches where the highest NO fluxes occurred in the Perennial Grassland patches and the lowest in the Pan patches. Over the course of the year the mean up-scaled NO emission for the studied region was 0.54 kg ha-1 a-1 and accounts for a loss of approximately 7.4% of the estimated N input to the region. The third study occurred in the hyper-arid Namib Desert in Namibia. Soils were sampled from three ecosystems; Dunes, Gravel Plains and the Riparian zone of the Kuiseb River. The net potential NO flux measured in the laboratory was used to estimate the NO flux for the Namib Desert for 2006 using modelled soil moisture and temperature data from the European Centre for Medium Range Weather Forecasts (ECMWF) operational model on a 36km x 35km spatial resolution. The maximum net potential NO production occurred at low soil moisture contents (<10%WFPS) and the optimal temperature was 25°C in the Dune and Riparian ecosystems and 35°C in the Gravel Plain Ecosystems. The maximum net potential NO fluxes ranged from 3.0 ng m-2 s-1 in the Riparian ecosystem to 6.2 ng m-2 s-1 in the Gravel Plains ecosystem. Up-scaling the net potential NO flux gave NO fluxes of up to 0.062 kg ha-1 a-1 in the Dune ecosystem and 0.544 kg h-1 a-1 in the Gravel Plain ecosystem. From these studies it is shown that NO is emitted ubiquitously from terrestrial ecosystems, as such the NO emission potential from deserts and scrublands should be taken into account in the global NO models. The emission of NO is influenced by various factors such as landscape, vegetation and climate. This study looks at the potential emissions from certain arid and semi-arid environments in southern Africa and other parts of the world and discusses some of the important factors controlling the emission of NO from the soil.

Radar based improvements and diagnosis of the convective capabilities of the cosmo-2 model

In the last few years the resolution of numerical weather prediction (nwp) became higher and higher with the progresses of technology and knowledge. As a consequence, a great number of initial data became fundamental for a correct initialization of the models. The potential of radar observations has long been recognized for improving the initial conditions of high-resolution nwp models, while operational application becomes more frequent. The fact that many nwp centres have recently taken into operations convection-permitting forecast models, many of which assimilate radar data, emphasizes the need for an approach to providing quality information which is needed in order to avoid that radar errors degrade the model's initial conditions and, therefore, its forecasts. Environmental risks can can be related with various causes: meteorological, seismical, hydrological/hydraulic. Flash floods have horizontal dimension of 1-20 Km and can be inserted in mesoscale gamma subscale, this scale can be modeled only with nwp model with the highest resolution as the COSMO-2 model. One of the problems of modeling extreme convective events is related with the atmospheric initial conditions, in fact the scale dimension for the assimilation of atmospheric condition in an high resolution model is about 10 Km, a value too high for a correct representation of convection initial conditions. Assimilation of radar data with his resolution of about of Km every 5 or 10 minutes can be a solution for this problem. In this contribution a pragmatic and empirical approach to deriving a radar data quality description is proposed to be used in radar data assimilation and more specifically for the latent heat nudging (lhn) scheme. Later the the nvective capabilities of the cosmo-2 model are investigated through some case studies. Finally, this work shows some preliminary experiments of coupling of a high resolution meteorological model with an Hydrological one.

Scenari finanziari e portafogli ottimi: modelli di previsione e strategie per l'asset allocation tattica

Le scelte di asset allocation costituiscono un problema ricorrente per ogni investitore. Quest’ultimo è continuamente impegnato a combinare diverse asset class per giungere ad un investimento coerente con le proprie preferenze. L’esigenza di supportare gli asset manager nello svolgimento delle proprie mansioni ha alimentato nel tempo una vasta letteratura che ha proposto numerose strategie e modelli di portfolio construction. Questa tesi tenta di fornire una rassegna di alcuni modelli innovativi di previsione e di alcune strategie nell’ambito dell’asset allocation tattica, per poi valutarne i risvolti pratici. In primis verificheremo la sussistenza di eventuali relazioni tra la dinamica di alcune variabili macroeconomiche ed i mercati finanziari. Lo scopo è quello di individuare un modello econometrico capace di orientare le strategie dei gestori nella costruzione dei propri portafogli di investimento. L’analisi prende in considerazione il mercato americano, durante un periodo caratterizzato da rapide trasformazioni economiche e da un’elevata volatilità dei prezzi azionari. In secondo luogo verrà esaminata la validità delle strategie di trading momentum e contrarian nei mercati futures, in particolare quelli dell’Eurozona, che ben si prestano all’implementazione delle stesse, grazie all’assenza di vincoli sulle operazioni di shorting ed ai ridotti costi di transazione. Dall’indagine emerge che entrambe le anomalie si presentano con carattere di stabilità. I rendimenti anomali permangono anche qualora vengano utilizzati i tradizionali modelli di asset pricing, quali il CAPM, il modello di Fama e French e quello di Carhart. Infine, utilizzando l’approccio EGARCH-M, verranno formulate previsioni sulla volatilità dei rendimenti dei titoli appartenenti al Dow Jones. Quest’ultime saranno poi utilizzate come input per determinare le views da inserire nel modello di Black e Litterman. I risultati ottenuti, evidenziano, per diversi valori dello scalare tau, extra rendimenti medi del new combined vector superiori al vettore degli extra rendimenti di equilibrio di mercato, seppur con livelli più elevati di rischio.

Digital marketing: le nuove opportunità di business per le aziende nell'era del web 2.0

L’elaborato ha lo scopo di presentare le nuove opportunità di business offerte dal Web. Il rivoluzionario cambiamento che la pervasività della Rete e tutte le attività correlate stanno portando, ha posto le aziende davanti ad un diverso modo di relazionarsi con i propri consumatori, che sono sempre più informati, consapevoli ed esigenti, e con la concorrenza. La sfida da accettare per rimanere competitivi sul mercato è significativa e il mutamento in rapido sviluppo: gli aspetti che contraddistinguono questo nuovo paradigma digitale sono, infatti, velocità, mutevolezza, ma al tempo stesso misurabilità, ponderabilità, previsione. Grazie agli strumenti tecnologici a disposizione e alle dinamiche proprie dei diversi spazi web (siti, social network, blog, forum) è possibile tracciare più facilmente, rispetto al passato, l’impatto di iniziative, lanci di prodotto, promozioni e pubblicità, misurandone il ritorno sull’investimento, oltre che la percezione dell’utente finale. Un approccio datacentrico al marketing, attraverso analisi di monitoraggio della rete, permette quindi al brand investimenti più mirati e ponderati sulla base di stime e previsioni. Tra le più significative strategie di marketing digitale sono citate: social advertising, keyword advertising, digital PR, social media, email marketing e molte altre. Sono riportate anche due case history: una come ottimo esempio di co-creation in cui il brand ha coinvolto direttamente il pubblico nel processo di produzione del prodotto, affidando ai fan della Pagina Facebook ufficiale la scelta dei gusti degli yogurt da mettere in vendita. La seconda, caso internazionale di lead generation, ha permesso al brand di misurare la conversione dei visitatori del sito (previa compilazione di popin) in reali acquirenti, collegando i dati di traffico del sito a quelli delle vendite. Esempio di come online e offline comunichino strettamente.

Dynamik diabatischer Rossby-Wellen

Diabatische Rossby-Wellen (DRWs) sind zyklonale Wirbel in der unteren Troposphäre, welche sich durch einen thermodynamisch-dynamischen Mechanismus kontinuierlich regenerieren und dabei schnell propagieren können. Vorangehende Untersuchungen schreiben derartigen zyklonalen Wirbeln das Potential zu, unter Wechselwirkung mit einer Anomalie an der Tropopause eine rapide Zyklonenintensivierung und folglich extreme Wetterereignisse hervorrufen zu können. DRWs wurden bisher meist in idealisierten Studien untersucht, woraus sich noch einige offene Fragen zu diesem Phänomen, besonders in realen Modelldaten, ergeben.rnrnIm Mittelpunkt dieser Arbeit steht die Fallstudie einer DRW, die im Dezember 2005 über dem Nordatlantik auftrat. Der Lebenszyklus des Systems ist über mehrere Tage und durch verschiedene Phasen verfolgbar und resultiert in einer explosiven Druckvertiefung. Zur Untersuchung der Fallstudie wurde mit operationellen Daten eines Globalmodelles sowie mit den Resultaten eines feinskaligeren Regionalmodelles gearbeitet, auf welche unterschiedliche Analysewerkzeuge angewendet wurden. rnrnDie eingehende Untersuchung der Propagationsphase der DRW bekräftigte das Vorhandensein von genügend Feuchte und Baroklinität als essentiell für den Propagationsmechanismus und die Intensität der DRW. Während der Propagationsphase arbeitet der selbsterhaltende DRW-Mechanismus unabhängig von einer von den Wellen an der Tropopause ausgehenden Anregung. Sensitivitätsstudien mit dem Regionalmodell, in denen die Umgebungsbedingungen der DRW lokal modifiziert wurden, ergaben, dass die Propagation einen relativ robusten Ablauf darstellt. Dementsprechend war in den vier untersuchten operationellen Vorhersagen die Propagationsphase gut wiedergegeben, während die rapide Intensivierung, wie sie gemäß den Analysen aufgetreten ist, von zwei der Vorhersagen verfehlt wurde.rnrnBei der Untersuchung der Intensivierungsphase stellten sich die Position und die zeitliche Abstimmung der Bewegung der Anomalie an der Tropopause relativ zur DRW in der unteren Troposphäre sowie die Stärke der Systeme als entscheidende Einflussfaktoren heraus. In den Entwicklungen der Sensitivitätssimulationen deutete sich an, dass ein unabhängig von der DRW an geeigneter Position entstandener zyklonaler Wirbel konstruktiver zu einer starken Zyklonenintensivierung beitragen kann als die DRW.rnrnIm zweiten Teil der Arbeit wurde ein Datensatz über die Nordhemisphäre für die Jahre 2004-2008 hinsichtlich des geographischen Vorkommens und der Intensivierung von DRWs untersucht. DRWs ereigneten sich in diesem Zeitraum über dem Atlantik (255 DRWs) halb so oft wie über dem Pazifik (515 DRWs). Ihre Entstehungsgebiete befanden sich über den Ostteilen der Kontinente und den Westhälften der Ozeane. Die Zugbahnen folgten größtenteils der baroklinen Zone der mittleren Breiten. Von den erfassten DRWs intensivierten sich im Atlanik 16% zu explosiven Tiefdruckgebieten, über dem Pazifik liegt der Anteil mit 11% etwas niedriger. Damit tragen DRWs zu etwa 20% der sich explosiv intensivierenden außertropischen Zyklonen bei.

Merkmalsbezogene Verifikation hochaufgelöster Niederschlagsvorhersagen für Deutschland

Die Verifikation bewertet die Güte von quantitativen Niederschlagsvorhersagen(QNV) gegenüber Beobachtungen und liefert Hinweise auf systematische Modellfehler. Mit Hilfe der merkmals-bezogenen Technik SAL werden simulierte Niederschlagsverteilungen hinsichtlich (S)truktur, (A)mplitude und (L)ocation analysiert. Seit einigen Jahren werden numerische Wettervorhersagemodelle benutzt, mit Gitterpunktabständen, die es erlauben, hochreichende Konvektion ohne Parametrisierung zu simulieren. Es stellt sich jetzt die Frage, ob diese Modelle bessere Vorhersagen liefern. Der hoch aufgelöste stündliche Beobachtungsdatensatz, der in dieser Arbeit verwendet wird, ist eine Kombination von Radar- und Stationsmessungen. Zum einem wird damit am Beispiel der deutschen COSMO-Modelle gezeigt, dass die Modelle der neuesten Generation eine bessere Simulation des mittleren Tagesgangs aufweisen, wenn auch mit zu geringen Maximum und etwas zu spätem Auftreten. Im Gegensatz dazu liefern die Modelle der alten Generation ein zu starkes Maximum, welches erheblich zu früh auftritt. Zum anderen wird mit dem neuartigen Modell eine bessere Simulation der räumlichen Verteilung des Niederschlags, durch eine deutliche Minimierung der Luv-/Lee Proble-matik, erreicht. Um diese subjektiven Bewertungen zu quantifizieren, wurden tägliche QNVs von vier Modellen für Deutschland in einem Achtjahreszeitraum durch SAL sowie klassischen Maßen untersucht. Die höher aufgelösten Modelle simulieren realistischere Niederschlagsverteilungen(besser in S), aber bei den anderen Komponenten tritt kaum ein Unterschied auf. Ein weiterer Aspekt ist, dass das Modell mit der gröbsten Auf-lösung(ECMWF) durch den RMSE deutlich am besten bewertet wird. Darin zeigt sich das Problem des ‚Double Penalty’. Die Zusammenfassung der drei Komponenten von SAL liefert das Resultat, dass vor allem im Sommer das am feinsten aufgelöste Modell (COSMO-DE) am besten abschneidet. Hauptsächlich kommt das durch eine realistischere Struktur zustande, so dass SAL hilfreiche Informationen liefert und die subjektive Bewertung bestätigt. rnIm Jahr 2007 fanden die Projekte COPS und MAP D-PHASE statt und boten die Möglich-keit, 19 Modelle aus drei Modellkategorien hinsichtlich ihrer Vorhersageleistung in Südwestdeutschland für Akkumulationszeiträume von 6 und 12 Stunden miteinander zu vergleichen. Als Ergebnisse besonders hervorzuheben sind, dass (i) je kleiner der Gitter-punktabstand der Modelle ist, desto realistischer sind die simulierten Niederschlags-verteilungen; (ii) bei der Niederschlagsmenge wird in den hoch aufgelösten Modellen weniger Niederschlag, d.h. meist zu wenig, simuliert und (iii) die Ortskomponente wird von allen Modellen am schlechtesten simuliert. Die Analyse der Vorhersageleistung dieser Modelltypen für konvektive Situationen zeigt deutliche Unterschiede. Bei Hochdrucklagen sind die Modelle ohne Konvektionsparametrisierung nicht in der Lage diese zu simulieren, wohingegen die Modelle mit Konvektionsparametrisierung die richtige Menge, aber zu flächige Strukturen realisieren. Für konvektive Ereignisse im Zusammenhang mit Fronten sind beide Modelltypen in der Lage die Niederschlagsverteilung zu simulieren, wobei die hoch aufgelösten Modelle realistischere Felder liefern. Diese wetterlagenbezogene Unter-suchung wird noch systematischer unter Verwendung der konvektiven Zeitskala durchge-führt. Eine erstmalig für Deutschland erstellte Klimatologie zeigt einen einer Potenzfunktion folgenden Abfall der Häufigkeit dieser Zeitskala zu größeren Werten hin auf. Die SAL Ergebnisse sind für beide Bereiche dramatisch unterschiedlich. Für kleine Werte der konvektiven Zeitskala sind sie gut, dagegen werden bei großen Werten die Struktur sowie die Amplitude deutlich überschätzt. rnFür zeitlich sehr hoch aufgelöste Niederschlagsvorhersagen gewinnt der Einfluss der zeitlichen Fehler immer mehr an Bedeutung. Durch die Optimierung/Minimierung der L Komponente von SAL innerhalb eines Zeitfensters(+/-3h) mit dem Beobachtungszeit-punkt im Zentrum ist es möglich diese zu bestimmen. Es wird gezeigt, dass bei optimalem Zeitversatz die Struktur und Amplitude der QNVs für das COSMO-DE besser werden und damit die grundsätzliche Fähigkeit des Modells die Niederschlagsverteilung realistischer zu simulieren, besser gezeigt werden kann.

Studio e ricostruzione delle distribuzioni granulometriche interne al grano in motori a propellente solido

The main purposes of this essay were to investigate in detail the burning rate anomaly phenomenon, also known as "Hump Effect", in solid rocket motors casted in mandrel and the mechanisms at the base of it, as well as the developing of a numeric code, in Matlab environment, in order to obtain a forecasting tool to generate concentration and orientation maps of the particles within the grain. The importance of these analysis is due to the fact that the forecasts of ballistics curves in new motors have to be improved in order to reduce the amount of experimental tests needed for the characterization of their ballistic behavior. This graduate work is divided into two parts. The first one is about bidimensional and tridimensional simulations on z9 motor casting process. The simulations have been carried out respectively with Fluent and Flow 3D. The second one is about the analysis of fluid dynamic data and the developing of numeric codes which give information about the concentration and orientation of particles within the grain based on fluid strain rate information which are extrapolated from CFD software.

Assimilation of data from conventional and non conventional networks through a LETKF scheme in the COSMO model

The present work studies a km-scale data assimilation scheme based on a LETKF developed for the COSMO model. The aim is to evaluate the impact of the assimilation of two different types of data: temperature, humidity, pressure and wind data from conventional networks (SYNOP, TEMP, AIREP reports) and 3d reflectivity from radar volume. A 3-hourly continuous assimilation cycle has been implemented over an Italian domain, based on a 20 member ensemble, with boundary conditions provided from ECMWF ENS. Three different experiments have been run for evaluating the performance of the assimilation on one week in October 2014 during which Genova flood and Parma flood took place: a control run of the data assimilation cycle with assimilation of data from conventional networks only, a second run in which the SPPT scheme is activated into the COSMO model, a third run in which also reflectivity volumes from meteorological radar are assimilated. Objective evaluation of the experiments has been carried out both on case studies and on the entire week: check of the analysis increments, computing the Desroziers statistics for SYNOP, TEMP, AIREP and RADAR, over the Italian domain, verification of the analyses against data not assimilated (temperature at the lowest model level objectively verified against SYNOP data), and objective verification of the deterministic forecasts initialised with the KENDA analyses for each of the three experiments.

Indigenous knowledge related to climate variability and change: insights from droughts in semi-arid areas of former Makueni District, Kenya

This article describes the indigenous knowledge (IK) that agro-pastoralists in larger Makueni District, Kenya hold and how they use it to monitor, mitigate and adapt to drought. It examines ways of integrating IK into formal monitoring, how to enhance its value and acceptability. Data was collected through target interviews, group discussions and questionnaires covering 127 households in eight villages. Daily rainfall data from 1961–2003 were analysed. Results show that agro-pastoralists hold IK on indicators of rainfall variability; they believe in IK efficacy and they rely on them. Because agro-pastoralists consult additional sources, the authors interpret that IK forms a basic knowledge frame within which agro-pastoralists position and interpret meteorological forecasts. Only a few agro-pastoralists adapt their practices in anticipation of IK-based forecasts partly due to the conditioning of the actors to the high rainfall variability characteristic of the area and partly due to lack of resources. Non-drought factors such as poverty, inadequate resources and lack of preparedness expose agro-pastoralists to drought impacts and limit their adaptive capacity. These factors need to be understood and effectively addressed to increase agro-pastoralists’ decision options and the influence of IK-based forecasts on their decision-making patterns. The limited intergenerational transfer of IK currently threatens its existence in the longer term. One way to ensure its continued existence and use is to integrate IK into the education curriculum and to link IK with formal climate change research through the participation of the local people. However, further studies are necessary to address the reliability and validity of the identified IK indicators of climate variability and change.

Divorce and Family Support in Later Life: Emerging Concerns.

Two patterns are among the most important considerations in planning services for the elderly of the future: (1) the current role of family members in supporting older adults and (2) the present high rate of divorce. Thus far, these patterns may not have significantly affected each other. However, if forecasts of increasing service demands by older adults are correct, service planners must consider what resources will be available to the elderly of the future. In this article, literature from a variety of areas is reviewed focusing on one question: How will the currently high rate of divorce affect the family support system of older adults in the future? Current divorce and remarriage patterns could undermine this support system of the elderly. Possible short-and long-term effects of the demands and emotional consequences of divorce are discussed within this context, and implications for public policy are suggested.

Formation of Exchange Rates on the Russian Market: Dynamics and Modelling

Galina Kovaleva. The Formation of the Exchange Rate on the Russian Market: Dynamics and Modelling. The Russian financial market is fast becoming one of the major sectors of the Russian economy. Assets have been increasing steadily, while new market segments and new financial market instruments have emerged. Kovaleva attempted to isolate the factors influencing exchange rates, determine patterns in the dynamic changes to the rouble/dollar exchange rate, construct models of the processes, and on the basis of these activities make forecasts. She studied the significance of economic indicators influencing the rouble/dollar exchange rate at different times, and developed multi-factor econometric models. In order to reveal the inner structure of the financial indicators and to work out ex-post forecasts for different time intervals, she carried out a series of calculations with the aim of constructing trend-cyclical (TC) and harmonic models, and Box and Jenkins models. She found that: 1. The Russian financial market is dependant on the rouble/dollar exchange rate. Its dynamics are formed under the influence of the short-term state treasury notes and government bonds markets, interbank loans, the rouble/DM exchange rate, the inflation rate, and the DM/dollar exchange rate. The exchange rate is influenced by sales on the Moscow Interbank Currency Exchange and the mechanism of those sales. 2. The TC model makes it possible to conduct an in-depth study of the structure of the processes and to make forecasts of the dynamic changes to currency indicators. 3. The Russian market is increasingly influenced by the world currency market and its prospects are of crucial interest for the world financial community.

First middle-atmospheric zonal wind profile measurements with a new ground-based microwave Doppler-spectro-radiometer

We report on the wind radiometer WIRA, a new ground-based microwave Doppler-spectro-radiometer specifically designed for the measurement of middle-atmospheric horizontal wind by observing ozone emission spectra at 142.17504 GHz. Currently, wind speeds in five levels between 30 and 79 km can be retrieved which makes WIRA the first instrument able to continuously measure horizontal wind in this altitude range. For an integration time of one day the measurement error on each level lies at around 25 m s−1. With a planned upgrade this value is expected to be reduced by a factor of 2 in the near future. On the altitude levels where our measurement can be compared to wind data from the European Centre for Medium-Range Weather Forecasts (ECMWF) very good agreement in the long-term statistics as well as in short time structures with a duration of a few days has been found. WIRA uses a passive double sideband heterodyne receiver together with a digital Fourier transform spectrometer for the data acquisition. A big advantage of the radiometric approach is that such instruments can also operate under adverse weather conditions and thus provide a continuous time series for the given location. The optics enables the instrument to scan a wide range of azimuth angles including the directions east, west, north, and south for zonal and meridional wind measurements. The design of the radiometer is fairly compact and its calibration does not rely on liquid nitrogen which makes it transportable and suitable for campaign use. WIRA is conceived in a way that it can be operated remotely and does hardly require any maintenance. In the present paper, a description of the instrument is given, and the techniques used for the wind retrieval based on the determination of the Doppler shift of the measured atmospheric ozone emission spectra are outlined. Their reliability was tested using Monte Carlo simulations. Finally, a time series of 11 months of zonal wind measurements over Bern (46°57′ N, 7°26′ E) is presented and compared to ECMWF wind data.

Evaluation of flood risk in response to climate variability

Standard procedures for forecasting flood risk (Bulletin 17B) assume annual maximum flood (AMF) series are stationary, meaning the distribution of flood flows is not significantly affected by climatic trends/cycles, or anthropogenic activities within the watershed. Historical flood events are therefore considered representative of future flood occurrences, and the risk associated with a given flood magnitude is modeled as constant over time. However, in light of increasing evidence to the contrary, this assumption should be reconsidered, especially as the existence of nonstationarity in AMF series can have significant impacts on planning and management of water resources and relevant infrastructure. Research presented in this thesis quantifies the degree of nonstationarity evident in AMF series for unimpaired watersheds throughout the contiguous U.S., identifies meteorological, climatic, and anthropogenic causes of this nonstationarity, and proposes an extension of the Bulletin 17B methodology which yields forecasts of flood risk that reflect climatic influences on flood magnitude. To appropriately forecast flood risk, it is necessary to consider the driving causes of nonstationarity in AMF series. Herein, large-scale climate patterns—including El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO)—are identified as influencing factors on flood magnitude at numerous stations across the U.S. Strong relationships between flood magnitude and associated precipitation series were also observed for the majority of sites analyzed in the Upper Midwest and Northeastern regions of the U.S. Although relationships between flood magnitude and associated temperature series are not apparent, results do indicate that temperature is highly correlated with the timing of flood peaks. Despite consideration of watersheds classified as unimpaired, analyses also suggest that identified change-points in AMF series are due to dam construction, and other types of regulation and diversion. Although not explored herein, trends in AMF series are also likely to be partially explained by changes in land use and land cover over time. Results obtained herein suggest that improved forecasts of flood risk may be obtained using a simple modification of the Bulletin 17B framework, wherein the mean and standard deviation of the log-transformed flows are modeled as functions of climate indices associated with oceanic-atmospheric patterns (e.g. AMO, ENSO, NAO, and PDO) with lead times between 3 and 9 months. Herein, one-year ahead forecasts of the mean and standard deviation, and subsequently flood risk, are obtained by applying site specific multivariate regression models, which reflect the phase and intensity of a given climate pattern, as well as possible impacts of coupling of the climate cycles. These forecasts of flood risk are compared with forecasts derived using the existing Bulletin 17B model; large differences in the one-year ahead forecasts are observed in some locations. The increased knowledge of the inherent structure of AMF series and an improved understanding of physical and/or climatic causes of nonstationarity gained from this research should serve as insight for the formulation of a physical-casual based statistical model, incorporating both climatic variations and human impacts, for flood risk over longer planning horizons (e.g., 10-, 50, 100-years) necessary for water resources design, planning, and management.

Towards greater accuracy in individual-tree mortality regression

Background mortality is an essential component of any forest growth and yield model. Forecasts of mortality contribute largely to the variability and accuracy of model predictions at the tree, stand and forest level. In the present study, I implement and evaluate state-of-the-art techniques to increase the accuracy of individual tree mortality models, similar to those used in many of the current variants of the Forest Vegetation Simulator, using data from North Idaho and Montana. The first technique addresses methods to correct for bias induced by measurement error typically present in competition variables. The second implements survival regression and evaluates its performance against the traditional logistic regression approach. I selected the regression calibration (RC) algorithm as a good candidate for addressing the measurement error problem. Two logistic regression models for each species were fitted, one ignoring the measurement error, which is the “naïve” approach, and the other applying RC. The models fitted with RC outperformed the naïve models in terms of discrimination when the competition variable was found to be statistically significant. The effect of RC was more obvious where measurement error variance was large and for more shade-intolerant species. The process of model fitting and variable selection revealed that past emphasis on DBH as a predictor variable for mortality, while producing models with strong metrics of fit, may make models less generalizable. The evaluation of the error variance estimator developed by Stage and Wykoff (1998), and core to the implementation of RC, in different spatial patterns and diameter distributions, revealed that the Stage and Wykoff estimate notably overestimated the true variance in all simulated stands, but those that are clustered. Results show a systematic bias even when all the assumptions made by the authors are guaranteed. I argue that this is the result of the Poisson-based estimate ignoring the overlapping area of potential plots around a tree. Effects, especially in the application phase, of the variance estimate justify suggested future efforts of improving the accuracy of the variance estimate. The second technique implemented and evaluated is a survival regression model that accounts for the time dependent nature of variables, such as diameter and competition variables, and the interval-censored nature of data collected from remeasured plots. The performance of the model is compared with the traditional logistic regression model as a tool to predict individual tree mortality. Validation of both approaches shows that the survival regression approach discriminates better between dead and alive trees for all species. In conclusion, I showed that the proposed techniques do increase the accuracy of individual tree mortality models, and are a promising first step towards the next generation of background mortality models. I have also identified the next steps to undertake in order to advance mortality models further.

Topographic and meteorological influences on spatial scaling of heavy convective rainfall in mountainous regions

Characterizing the spatial scaling and dynamics of convective precipitation in mountainous terrain and the development of downscaling methods to transfer precipitation fields from one scale to another is the overall motivation for this research. Substantial progress has been made on characterizing the space-time organization of Midwestern convective systems and tropical rainfall, which has led to the development of statistical/dynamical downscaling models. Space-time analysis and downscaling of orographic precipitation has received less attention due to the complexities of topographic influences. This study uses multiscale statistical analysis to investigate the spatial scaling of organized thunderstorms that produce heavy rainfall and flooding in mountainous regions. Focus is placed on the eastern and western slopes of the Appalachian region and the Front Range of the Rocky Mountains. Parameter estimates are analyzed over time and attention is given to linking changes in the multiscale parameters with meteorological forcings and orographic influences on the rainfall. Influences of geographic regions and predominant orographic controls on trends in multiscale properties of precipitation are investigated. Spatial resolutions from 1 km to 50 km are considered. This range of spatial scales is needed to bridge typical scale gaps between distributed hydrologic models and numerical weather prediction (NWP) forecasts and attempts to address the open research problem of scaling organized thunderstorms and convection in mountainous terrain down to 1-4 km scales.