Reverse Engineering tools: development and experimentation of innovative methods for physical and geometrical data integration and post-processing

In recent years, the use of Reverse Engineering systems has got a considerable interest for a wide number of applications. Therefore, many research activities are focused on accuracy and precision of the acquired data and post processing phase improvements. In this context, this PhD Thesis deals with the definition of two novel methods for data post processing and data fusion between physical and geometrical information. In particular a technique has been defined for error definition in 3D points’ coordinates acquired by an optical triangulation laser scanner, with the aim to identify adequate correction arrays to apply under different acquisition parameters and operative conditions. Systematic error in data acquired is thus compensated, in order to increase accuracy value. Moreover, the definition of a 3D thermogram is examined. Object geometrical information and its thermal properties, coming from a thermographic inspection, are combined in order to have a temperature value for each recognizable point. Data acquired by an optical triangulation laser scanner are also used to normalize temperature values and make thermal data independent from thermal-camera point of view.

Palaeo wind system reconstruction of the last glacial period over Europe, using high resolution proxy data and model-data-comparison

The atmosphere is a global influence on the movement of heat and humidity between the continents, and thus significantly affects climate variability. Information about atmospheric circulation are of major importance for the understanding of different climatic conditions. Dust deposits from maar lakes and dry maars from the Eifel Volcanic Field (Germany) are therefore used as proxy data for the reconstruction of past aeolian dynamics.rnrnIn this thesis past two sediment cores from the Eifel region are examined: the core SM3 from Lake Schalkenmehren and the core DE3 from the Dehner dry maar. Both cores contain the tephra of the Laacher See eruption, which is dated to 12,900 before present. Taken together the cores cover the last 60,000 years: SM3 the Holocene and DE3 the marine isotope stages MIS-3 and MIS-2, respectively. The frequencies of glacial dust storm events and their paleo wind direction are detected by high resolution grain size and provenance analysis of the lake sediments. Therefore two different methods are applied: geochemical measurements of the sediment using µXRF-scanning and the particle analysis method RADIUS (rapid particle analysis of digital images by ultra-high-resolution scanning of thin sections).rnIt is shown that single dust layers in the lake sediment are characterized by an increased content of aeolian transported carbonate particles. The limestone-bearing Eifel-North-South zone is the most likely source for the carbonate rich aeolian dust in the lake sediments of the Dehner dry maar. The dry maar is located on the western side of the Eifel-North-South zone. Thus, carbonate rich aeolian sediment is most likely to be transported towards the Dehner dry maar within easterly winds. A methodology is developed which limits the detection to the aeolian transported carbonate particles in the sediment, the RADIUS-carbonate module.rnrnIn summary, during the marine isotope stage MIS-3 the storm frequency and the east wind frequency are both increased in comparison to MIS-2. These results leads to the suggestion that atmospheric circulation was affected by more turbulent conditions during MIS-3 in comparison to the more stable atmospheric circulation during the full glacial conditions of MIS-2.rnThe results of the investigations of the dust records are finally evaluated in relation a study of atmospheric general circulation models for a comprehensive interpretation. Here, AGCM experiments (ECHAM3 and ECHAM4) with different prescribed SST patterns are used to develop a synoptic interpretation of long-persisting east wind conditions and of east wind storm events, which are suggested to lead to an enhanced accumulation of sediment being transported by easterly winds to the proxy site of the Dehner dry maar.rnrnThe basic observations made on the proxy record are also illustrated in the 10 m-wind vectors in the different model experiments under glacial conditions with different prescribed sea surface temperature patterns. Furthermore, the analysis of long-persisting east wind conditions in the AGCM data shows a stronger seasonality under glacial conditions: all the different experiments are characterized by an increase of the relative importance of the LEWIC during spring and summer. The different glacial experiments consistently show a shift from a long-lasting high over the Baltic Sea towards the NW, directly above the Scandinavian Ice Sheet, together with contemporary enhanced westerly circulation over the North Atlantic.rnrnThis thesis is a comprehensive analysis of atmospheric circulation patterns during the last glacial period. It has been possible to reconstruct important elements of the glacial paleo climate in Central Europe. While the proxy data from sediment cores lead to a binary signal of the wind direction changes (east versus west wind), a synoptic interpretation using atmospheric circulation models is successful. This shows a possible distribution of high and low pressure areas and thus the direction and strength of wind fields which have the capacity to transport dust. In conclusion, the combination of numerical models, to enhance understanding of processes in the climate system, with proxy data from the environmental record is the key to a comprehensive approach to paleo climatic reconstruction.rn

Overview of data assimilation methods

We present the data assimilation approach, which provides a framework for combining observations and model simulations of the climate system, and has led to a new field of applications for paleoclimatology. The three subsequent articles explore specific applications in more detail.

A model-data comparison of Holocene timberline changes in the Swiss Alps reveals past and future drivers of mountain forest dynamics

Mountain vegetation is strongly affected by temperature and is expected to shift upwards with climate change. Dynamic vegetation models are often used to assess the impact of climate on vegetation and model output can be compared with paleobotanical data as a reality check. Recent paleoecological studies have revealed regional variation in the upward shift of timberlines in the Northern and Central European Alps in response to rapid warming at the Younger Dryas/Preboreal transition ca. 11700years ago, probably caused by a climatic gradient across the Alps. This contrasts with previous studies that successfully simulated the early Holocene afforestation in the (warmer) Central Alps with a chironomid-inferred temperature reconstruction from the (colder) Northern Alps. We use LandClim, a dynamic landscape vegetation model to simulate mountain forests under different temperature, soil and precipitation scenarios around Iffigsee (2065m a.s.l.) a lake in the Northwestern Swiss Alps, and compare the model output with the paleobotanical records. The model clearly overestimates the upward shift of timberline in a climate scenario that applies chironomid-inferred July-temperature anomalies to all months. However, forest establishment at 9800 cal. BP at Iffigsee is successfully simulated with lower moisture availability and monthly temperatures corrected for stronger seasonality during the early Holocene. The model-data comparison reveals a contraction in the realized niche of Abies alba due to the prominent role of anthropogenic disturbance after ca. 5000 cal. BP, which has important implications for species distribution models (SDMs) that rely on equilibrium with climate and niche stability. Under future climate projections, LandClim indicates a rapid upward shift of mountain vegetation belts by ca. 500m and treeline positions of ca. 2500m a.s.l. by the end of this century. Resulting biodiversity losses in the alpine vegetation belt might be mitigated with low-impact pastoralism to preserve species-rich alpine meadows.

Marine Isotope Stage (MIS) 11 results of model data with Community Climate System Model version 3 including the Dynamic Global Vegetation Model (CCSM3-DGVM) in NetCDF format at global and regional scale

The climate of Marine Isotope Stage (MIS) 11, the interglacial roughly 400,000 years ago, is investigated for four time slices, 416, 410, 400, and 394 ka. The overall picture is that MIS 11 was a relatively warm interglacial in comparison to preindustrial, with Northern Hemisphere (NH) summer temperatures early in MIS 11 (416-410 ka) warmer than preindustrial, though winters were cooler. Later in MIS 11, especially around 400 ka, conditions were cooler in the NH summer, mainly in the high latitudes. Climate changes simulated by the models were mainly driven by insolation changes, with the exception of two local feedbacks that amplify climate changes. Here, the NH high latitudes, where reductions in sea ice cover lead to a winter warming early in MIS 11, as well as the tropics, where monsoon changes lead to stronger climate variations than one would expect on the basis of latitudinal mean insolation change alone, are especially prominent. The results support a northward expansion of trees at the expense of grasses in the high northern latitudes early during MIS 11, especially in northern Asia and North America.

On the effects of circulation, sediment resuspension and biological incorporation by diatoms in an ocean model of aluminium, link to model data

The distribution of dissolved aluminium in the West Atlantic Ocean shows a mirror image with that of dissolved silicic acid, hinting at intricate interactions between the ocean cycling of Al and Si. The marine biogeochemistry of Al is of interest because of its potential impact on diatom opal remineralisation, hence Si availability. Furthermore, the dissolved Al concentration at the surface ocean has been used as a tracer for dust input, dust being the most important source of the bio-essential trace element iron to the ocean. Previously, the dissolved concentration of Al was simulated reasonably well with only a dust source, and scavenging by adsorption on settling biogenic debris as the only removal process. Here we explore the impacts of (i) a sediment source of Al in the Northern Hemisphere (especially north of ~ 40° N), (ii) the imposed velocity field, and (iii) biological incorporation of Al on the modelled Al distribution in the ocean. The sediment source clearly improves the model results, and using a different velocity field shows the importance of advection on the simulated Al distribution. Biological incorporation appears to be a potentially important removal process. However, conclusive independent data to constrain the Al / Si incorporation ratio by growing diatoms are missing. Therefore, this study does not provide a definitive answer to the question of the relative importance of Al removal by incorporation compared to removal by adsorptive scavenging.

Improving probabilistic flood forecasting through a data assimilation scheme based on genetic programming

Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.

Description of atmospheric conditions at the Pierre Auger Observatory using the Global Data Assimilation System (GDAS)

Atmospheric conditions at the site of a cosmic ray observatory must be known for reconstructing observed extensive air showers. The Global Data Assimilation System (GDAS) is a global atmospheric model predicated on meteorological measurements and numerical weather predictions. GDAS provides altitude-dependent profiles of the main state variables of the atmosphere like temperature, pressure, and humidity. The original data and their application to the air shower reconstruction of the Pierre Auger Observatory are described. By comparisons with radiosonde and weather station measurements obtained on-site in Malargue and averaged monthly models, the utility of the GDAS data is shown. (C) 2012 Elsevier B.V. All rights reserved.

A scaleless data model for direct and progressive spatial query processing

A progressive spatial query retrieves spatial data based on previous queries (e.g., to fetch data in a more restricted area with higher resolution). A direct query, on the other side, is defined as an isolated window query. A multi-resolution spatial database system should support both progressive queries and traditional direct queries. It is conceptually challenging to support both types of query at the same time, as direct queries favour location-based data clustering, whereas progressive queries require fragmented data clustered by resolutions. Two new scaleless data structures are proposed in this paper. Experimental results using both synthetic and real world datasets demonstrate that the query processing time based on the new multiresolution approaches is comparable and often better than multi-representation data structures for both types of queries.

Data assimilation for precipitation nowcasting using Bayesian inference

This work introduces a new variational Bayes data assimilation method for the stochastic estimation of precipitation dynamics using radar observations for short term probabilistic forecasting (nowcasting). A previously developed spatial rainfall model based on the decomposition of the observed precipitation field using a basis function expansion captures the precipitation intensity from radar images as a set of ‘rain cells’. The prior distributions for the basis function parameters are carefully chosen to have a conjugate structure for the precipitation field model to allow a novel variational Bayes method to be applied to estimate the posterior distributions in closed form, based on solving an optimisation problem, in a spirit similar to 3D VAR analysis, but seeking approximations to the posterior distribution rather than simply the most probable state. A hierarchical Kalman filter is used to estimate the advection field based on the assimilated precipitation fields at two times. The model is applied to tracking precipitation dynamics in a realistic setting, using UK Met Office radar data from both a summer convective event and a winter frontal event. The performance of the model is assessed both traditionally and using probabilistic measures of fit based on ROC curves. The model is shown to provide very good assimilation characteristics, and promising forecast skill. Improvements to the forecasting scheme are discussed

Bayesian data assimilation

This thesis addresses data assimilation, which typically refers to the estimation of the state of a physical system given a model and observations, and its application to short-term precipitation forecasting. A general introduction to data assimilation is given, both from a deterministic and' stochastic point of view. Data assimilation algorithms are reviewed, in the static case (when no dynamics are involved), then in the dynamic case. A double experiment on two non-linear models, the Lorenz 63 and the Lorenz 96 models, is run and the comparative performance of the methods is discussed in terms of quality of the assimilation, robustness "in the non-linear regime and computational time. Following the general review and analysis, data assimilation is discussed in the particular context of very short-term rainfall forecasting (nowcasting) using radar images. An extended Bayesian precipitation nowcasting model is introduced. The model is stochastic in nature and relies on the spatial decomposition of the rainfall field into rain "cells". Radar observations are assimilated using a Variational Bayesian method in which the true posterior distribution of the parameters is approximated by a more tractable distribution. The motion of the cells is captured by a 20 Gaussian process. The model is tested on two precipitation events, the first dominated by convective showers, the second by precipitation fronts. Several deterministic and probabilistic validation methods are applied and the model is shown to retain reasonable prediction skill at up to 3 hours lead time. Extensions to the model are discussed.

A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle

Acknowledgements. This work was mainly funded by the EU FP7 CARBONES project (contracts FP7-SPACE-2009-1-242316), with also a small contribution from GEOCARBON project (ENV.2011.4.1.1-1-283080). This work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program; DE-FG02-04ER63917 and DE-FG02-04ER63911), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), GreenGrass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia, USCCC. We acknowledge the financial support to the eddy covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Université Laval and Environment Canada and US Department of Energy and the database development and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, University of California-Berkeley, University of Virginia. Philippe Ciais acknowledges support from the European Research Council through Synergy grant ERC-2013-SyG-610028 “IMBALANCE-P”. The authors wish to thank M. Jung for providing access to the GPP MTE data, which were downloaded from the GEOCARBON data portal (https://www.bgc-jena.mpg.de/geodb/projects/Data.php). The authors are also grateful to computing support and resources provided at LSCE and to the overall ORCHIDEE project that coordinate the development of the code (http://labex.ipsl.fr/orchidee/index.php/about-the-team).