Exploiting ground-based measurements of the Global Positioning System for numerical weather prediction

Data assimilation provides an initial atmospheric state, called the analysis, for Numerical Weather Prediction (NWP). This analysis consists of pressure, temperature, wind, and humidity on a three-dimensional NWP model grid. Data assimilation blends meteorological observations with the NWP model in a statistically optimal way. The objective of this thesis is to describe methodological development carried out in order to allow data assimilation of ground-based measurements of the Global Positioning System (GPS) into the High Resolution Limited Area Model (HIRLAM) NWP system. Geodetic processing produces observations of tropospheric delay. These observations can be processed either for vertical columns at each GPS receiver station, or for the individual propagation paths of the microwave signals. These alternative processing methods result in Zenith Total Delay (ZTD) and Slant Delay (SD) observations, respectively. ZTD and SD observations are of use in the analysis of atmospheric humidity. A method is introduced for estimation of the horizontal error covariance of ZTD observations. The method makes use of observation minus model background (OmB) sequences of ZTD and conventional observations. It is demonstrated that the ZTD observation error covariance is relatively large in station separations shorter than 200 km, but non-zero covariances also appear at considerably larger station separations. The relatively low density of radiosonde observing stations limits the ability of the proposed estimation method to resolve the shortest length-scales of error covariance. SD observations are shown to contain a statistically significant signal on the asymmetry of the atmospheric humidity field. However, the asymmetric component of SD is found to be nearly always smaller than the standard deviation of the SD observation error. SD observation modelling is described in detail, and other issues relating to SD data assimilation are also discussed. These include the determination of error statistics, the tuning of observation quality control and allowing the taking into account of local observation error correlation. The experiments made show that the data assimilation system is able to retrieve the asymmetric information content of hypothetical SD observations at a single receiver station. Moreover, the impact of real SD observations on humidity analysis is comparable to that of other observing systems.

Studies on orographic effects in a numerical weather prediction model

Numerical models, used for atmospheric research, weather prediction and climate simulation, describe the state of the atmosphere over the heterogeneous surface of the Earth. Several fundamental properties of atmospheric models depend on orography, i.e. on the average elevation of land over a model area. The higher is the models' resolution, the more the details of orography directly influence the simulated atmospheric processes. This sets new requirements for the accuracy of the model formulations with respect to the spatially varying orography. Orography is always averaged, representing the surface elevation within the horizontal resolution of the model. In order to remove the smallest scales and steepest slopes, the continuous spectrum of orography is normally filtered (truncated) even more, typically beyond a few gridlengths of the model. This means, that in the numerical weather prediction (NWP) models, there will always be subgridscale orography effects, which cannot be explicitly resolved by numerical integration of the basic equations, but require parametrization. In the subgrid-scale, different physical processes contribute in different scales. The parametrized processes interact with the resolved-scale processes and with each other. This study contributes to building of a consistent, scale-dependent system of orography-related parametrizations for the High Resolution Limited Area Model (HIRLAM). The system comprises schemes for handling the effects of mesoscale (MSO) and small-scale (SSO) orographic effects on the simulated flow and a scheme of orographic effects on the surface-level radiation fluxes. Representation of orography, scale-dependencies of the simulated processes and interactions between the parametrized and resolved processes are discussed. From the high-resolution digital elevation data, orographic parameters are derived for both momentum and radiation flux parametrizations. Tools for diagnostics and validation are developed and presented. The parametrization schemes applied, developed and validated in this study, are currently being implemented into the reference version of HIRLAM.

Diagnostic Tests Based on Quantile Residuals for Nonlinear Time Series Models

This thesis studies quantile residuals and uses different methodologies to develop test statistics that are applicable in evaluating linear and nonlinear time series models based on continuous distributions. Models based on mixtures of distributions are of special interest because it turns out that for those models traditional residuals, often referred to as Pearson's residuals, are not appropriate. As such models have become more and more popular in practice, especially with financial time series data there is a need for reliable diagnostic tools that can be used to evaluate them. The aim of the thesis is to show how such diagnostic tools can be obtained and used in model evaluation. The quantile residuals considered here are defined in such a way that, when the model is correctly specified and its parameters are consistently estimated, they are approximately independent with standard normal distribution. All the tests derived in the thesis are pure significance type tests and are theoretically sound in that they properly take the uncertainty caused by parameter estimation into account. -- In Chapter 2 a general framework based on the likelihood function and smooth functions of univariate quantile residuals is derived that can be used to obtain misspecification tests for various purposes. Three easy-to-use tests aimed at detecting non-normality, autocorrelation, and conditional heteroscedasticity in quantile residuals are formulated. It also turns out that these tests can be interpreted as Lagrange Multiplier or score tests so that they are asymptotically optimal against local alternatives. Chapter 3 extends the concept of quantile residuals to multivariate models. The framework of Chapter 2 is generalized and tests aimed at detecting non-normality, serial correlation, and conditional heteroscedasticity in multivariate quantile residuals are derived based on it. Score test interpretations are obtained for the serial correlation and conditional heteroscedasticity tests and in a rather restricted special case for the normality test. In Chapter 4 the tests are constructed using the empirical distribution function of quantile residuals. So-called Khmaladze s martingale transformation is applied in order to eliminate the uncertainty caused by parameter estimation. Various test statistics are considered so that critical bounds for histogram type plots as well as Quantile-Quantile and Probability-Probability type plots of quantile residuals are obtained. Chapters 2, 3, and 4 contain simulations and empirical examples which illustrate the finite sample size and power properties of the derived tests and also how the tests and related graphical tools based on residuals are applied in practice.

Generalised regression estimation for domain class frequencies

This study examines the properties of Generalised Regression (GREG) estimators for domain class frequencies and proportions. The family of GREG estimators forms the class of design-based model-assisted estimators. All GREG estimators utilise auxiliary information via modelling. The classic GREG estimator with a linear fixed effects assisting model (GREG-lin) is one example. But when estimating class frequencies, the study variable is binary or polytomous. Therefore logistic-type assisting models (e.g. logistic or probit model) should be preferred over the linear one. However, other GREG estimators than GREG-lin are rarely used, and knowledge about their properties is limited. This study examines the properties of L-GREG estimators, which are GREG estimators with fixed-effects logistic-type models. Three research questions are addressed. First, I study whether and when L-GREG estimators are more accurate than GREG-lin. Theoretical results and Monte Carlo experiments which cover both equal and unequal probability sampling designs and a wide variety of model formulations show that in standard situations, the difference between L-GREG and GREG-lin is small. But in the case of a strong assisting model, two interesting situations arise: if the domain sample size is reasonably large, L-GREG is more accurate than GREG-lin, and if the domain sample size is very small, estimation of assisting model parameters may be inaccurate, resulting in bias for L-GREG. Second, I study variance estimation for the L-GREG estimators. The standard variance estimator (S) for all GREG estimators resembles the Sen-Yates-Grundy variance estimator, but it is a double sum of prediction errors, not of the observed values of the study variable. Monte Carlo experiments show that S underestimates the variance of L-GREG especially if the domain sample size is minor, or if the assisting model is strong. Third, since the standard variance estimator S often fails for the L-GREG estimators, I propose a new augmented variance estimator (A). The difference between S and the new estimator A is that the latter takes into account the difference between the sample fit model and the census fit model. In Monte Carlo experiments, the new estimator A outperformed the standard estimator S in terms of bias, root mean square error and coverage rate. Thus the new estimator provides a good alternative to the standard estimator.

Towards a Dynamic Communication Model: A Useful Tool in Relationship Communication

In order to bring insight into the emerging concept of relationship communication, concepts from two research traditions will be combined in this paper. Based on those concepts a new model, the dynamic relationship communication model, will be presented. Instead of a company perspective focusing on the integration of outgoing messages such as advertising, public relations and sales activities, it is suggested that the focus should be on factors integrated by the receiver. Such factors can be historical, future, external and internal factors. Thus, the model put a strong focus on the receiver in the communication process. The dynamic communication model is illustrated empirically using it as a tool on 78 short stories about communication. The empirical findings show that relationship communication occurs in some cases; in some cases it does not occur. The model is a useful tool in displaying relationship communication and how it differs from other communication. The importance of the time dimension, historical and future factors, in relationship communications is discussed. The possibility of reducing communications costs by the notion of relationship communication is discussed in managerial implications.

Understorey vegetation as an indicator of forest site potential in Southern Finland.

The relationship between site characteristics and understorey vegetation composition was analysed with quantitative methods, especially from the viewpoint of site quality estimation. Theoretical models were applied to an empirical data set collected from the upland forests of southern Finland comprising 104 sites dominated by Scots pine (Pinus sylvestris L.), and 165 sites dominated by Norway spruce (Picea abies (L.) Karsten). Site index H100 was used as an independent measure of site quality. A new model for the estimation of site quality at sites with a known understorey vegetation composition was introduced. It is based on the application of Bayes' theorem to the density function of site quality within the study area combined with the species-specific presence-absence response curves. The resulting posterior probability density function may be used for calculating an estimate for the site variable. Using this method, a jackknife estimate of site index H100 was calculated separately for pine- and spruce-dominated sites. The results indicated that the cross-validation root mean squared error (RMSEcv) of the estimates improved from 2.98 m down to 2.34 m relative to the "null" model (standard deviation of the sample distribution) in pine-dominated forests. In spruce-dominated forests RMSEcv decreased from 3.94 m down to 3.16 m. In order to assess these results, four other estimation methods based on understorey vegetation composition were applied to the same data set. The results showed that none of the methods was clearly superior to the others. In pine-dominated forests, RMSEcv varied between 2.34 and 2.47 m, and the corresponding range for spruce-dominated forests was from 3.13 to 3.57 m.

Cox-2, tenascin, CRP, and ingraft chimerism in a model of post-transplant obliterative bronchiolitis

Chronic rejection in the form of obliterative bronchiolitis (OB) is the major cause of death 5 years after lung transplantation. The exact mechanism of OB remains unclear. This study focused on the role of cyclo-oxygenase (COX) -2, tenascin, and C-reactive protein (CRP) expression, and the occurrence of ingraft chimerism (= cells from two genetically distinct individuals in a same individual) in post-transplant OB development. In our porcine model, OB developed invariably in allografts, while autografts stayed patent. The histological changes were similar to those seen in human OB. In order to delay or prevent obliteration, animals were medicated according to certain protocol. In the beginning of the bronchial allograft reaction, COX-2 induction occurred in airway epithelial cells prior to luminal obliteration. COX-2 expression in macrophages and fibroblasts paralleled the onset of inflammation and fibroblast proliferation. This study demonstrated for the first time, that COX-2 expression is associated with the early stage of post- transplant obliterative airway disease. Tenascin expression in the respiratory epithelium appeared to be predictive of histologic features observed in human OB, and influx of immune cells. Expression in the bronchial wall and in the early obliterative lesions coincided with the onset of onset of fibroblast and inflammatory cell proliferation in the early stage of OB and was predictive of further influx of inflammatory and immune cells. CRP expression in the bronchial wall coincided with the remodelling process. High grade of bronchial wall CRP staining intensity predicted inflammation, accelerated fibroproliferation, and luminal obliteration, which are all features of OB. In the early obliterative plaque, majority of cells expressed CRP, but in mature, collagen-rich plaque, expression declined. Local CRP expression might be a response to inflammation and it might promote the development of OB. Early appearance of chimeric (= recipient-derived) cells in the graft airway epithelium predicted epithelial cell injury and obliteration of the bronchial lumen, which both are features of OB. Chimeric cells appeared in the airway epithelium after repair following transplantation-induced ischemic injury. Ingraft chimerism might be a mechanism to repair alloimmune-mediated tissue injury and to protect allografts from rejection after transplantation. The results of this study indicate, that COX-2, tenascin, CRP, and ingraft chimerism have a role in OB development. These findings increase the understanding of the mechanisms of OB, which may be beneficial in further development of diagnostic options.

Temperature-Sensitive Src-Transformed Mdck Cells nn 3d Cultures as a Model of Malignant Transformation of Epithelial Cells

The equilibrium between cell proliferation, differentiation, and apoptosis is crucial for maintaining homeostasis in epithelial tissues. In order for the epithelium to function properly, individual cells must gain normal structural and functional polarity. The junctional proteins have an important role both in binding the cells together and in taking part in cell signaling. Cadherins form adherens junctions. Cadherins initiate the polarization process by first recognizing and binding the neighboring cells together, and then guiding the formation of tight junctions. Tight junctions form a barrier in dividing the plasma membranes to apical and basolateral membrane domains. In glandular tissues, single layered and polarized epithelium is folded into tubes or spheres, in which the basal side of the epithelial layer faces the outer basal membrane, and the apical side the lumen. In carcinogenesis, the differentiated architecture of an epithelial layer is disrupted. Filling of the luminal space is a hallmark of early epithelial tumors in tubular and glandular structures. In order for the transformed tumor cells to populate the lumen, enhanced proliferation as well as inhibition of apoptosis is required. Most advances in cancer biology have been achieved by using two-dimensional (2D) cell culture models, in which the cells are cultured on flat surfaces as monolayers. However, the 2D cultures are limited in their capacity to recapitulate the structural and functional features of tubular structures and to represent cell growth and differentiation in vivo. The development of three-dimensional (3D) cell culture methods enables the cells to grow and to be studied in a more natural environment. Despite the wide use of 2D cell culture models and the development of novel 3D culture methods, it is not clear how the change of the dimensionality of culture conditions alters the polarization and transformation process and the molecular mechanisms behind them. Src is a well-known oncogene. It is found in focal and adherens junctions of cultured cells. Active src disrupts cell-cell junctions and interferes with cell-matrix binding. It promotes cell motility and survival. Src transformation in 2D disrupts adherens junctions and the fibroblastic phenotype of the cells. In 3D, the adherens junctions are weakened, and in glandular structures, the lumen is filled with nonpolarized vital cells. Madin-Darby canine kidney (MDCK) cells are an epithelial cell type commonly used as a model for cell polarization. Its-src-transformed variants are useful model systems for analyzing the changes in cell morphology, and they play a role in src-induced malignant transformation. This study investigates src-transformed cells in 3D cell cultures as a model for malignant transformation. The following questions were posed. Firstly: What is the role of the composition and stiffness of the extracellular matrix (ECM) on the polarization and transformation of ts v-src MDCK cells in 3D cell cultures? Secondly: How do the culture conditions affect gene expression? What is the effect of v-src transformation in 2D and in 3D cell models? How does the shift from 2D to 3D affect cell polarity and gene expression? Thirdly: What is the role of survivin and its regulator phosphatase and tensin homolog protein (PTEN) in cell polarization and transformation, and in determining cell fate? How does their expression correlate with impaired mitochondrial function in transformed cells? In order to answer the above questions, novel methods of culturing and monitoring cells had to be created: novel 3D methods of culturing epithelial cells were engineered, enabling real time monitoring of a polarization and transformation process, and functional testing of 3D cell cultures. Novel 3D cell culture models and imaging techniques were created for the study. Attention was focused especially on confocal microscopy and live-cell imaging. Src-transformation disturbed the polarization of the epithelium by disrupting cell adhesion, and sensitized the cells to their environment. With active src, the morphology of the cell cluster depended on the composition and stiffness of the matrix. Gene expression studies revealed a broader impact of src transformation than mere continuous activity of src-kinase. In 2D cultures, src transformation altered the expression of immunological, actin cytoskeleton and extracellular matrix (ECM). In 3D, the genes regulating cell division, inhibition of apoptosis, cell metabolism, mitochondrial function, actin cytoskeleton and mechano-sensing proteins were altered. Surprisingly, changing the culture conditions from 2D to 3D affected also gene expression considerably. The microarray hit survivin, an inhibitor of apoptosis, played a crucial role in the survival and proliferation of src-transformed cells.

Sensitivity of wetland methane emissions to model assumptions: application and model testing against site observations

Abstract. Methane emissions from natural wetlands and rice paddies constitute a large proportion of atmospheric methane, but the magnitude and year-to-year variation of these methane sources is still unpredictable. Here we describe and evaluate the integration of a methane biogeochemical model (CLM4Me; Riley et al., 2011) into the Community Land Model 4.0 (CLM4CN) in order to better explain spatial and temporal variations in methane emissions. We test new functions for soil pH and redox potential that impact microbial methane production in soils. We also constrain aerenchyma in plants in always-inundated areas in order to better represent wetland vegetation. Satellite inundated fraction is explicitly prescribed in the model because there are large differences between simulated fractional inundation and satellite observations. A rice paddy module is also incorporated into the model, where the fraction of land used for rice production is explicitly prescribed. The model is evaluated at the site level with vegetation cover and water table prescribed from measurements. Explicit site level evaluations of simulated methane emissions are quite different than evaluating the grid cell averaged emissions against available measurements. Using a baseline set of parameter values, our model-estimated average global wetland emissions for the period 1993–2004 were 256 Tg CH4 yr−1, and rice paddy emissions in the year 2000 were 42 Tg CH4 yr−1. Tropical wetlands contributed 201 Tg CH4 yr−1, or 78 % of the global wetland flux. Northern latitude (>50 N) systems contributed 12 Tg CH4 yr−1. We expect this latter number may be an underestimate due to the low high-latitude inundated area captured by satellites and unrealistically low high-latitude productivity and soil carbon predicted by CLM4. Sensitivity analysis showed a large range (150–346 Tg CH4 yr−1) in predicted global methane emissions. The large range was sensitive to: (1) the amount of methane transported through aerenchyma, (2) soil pH (± 100 Tg CH4 yr−1), and (3) redox inhibition (± 45 Tg CH4 yr−1).