Multiscale Synthesis Research Articles

The North American Carbon Program Multi-scale Synthesis and Terrestrial Model Intercomparison Project – Part 2: Environmental driver data

Abstract. Ecosystems are important and dynamic components of the global carbon cycle, and terrestrial biospheric models (TBMs) are crucial tools in further understanding of how terrestrial carbon is stored and exchanged with the atmosphere across a variety of spatial and temporal scales. Improving TBM skills, and quantifying and reducing their estimation uncertainties, pose significant challenges. The Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal multi-scale and multi-model intercomparison effort set up to tackle these challenges. The MsTMIP protocol prescribes standardized environmental driver data that are shared among model teams to facilitate model–model and model–observation comparisons. This paper describes the global and North American environmental driver data sets prepared for the MsTMIP activity to both support their use in MsTMIP and make these data, along with the processes used in selecting/processing these data, accessible to a broader audience. Based on project needs and lessons learned from past model intercomparison activities, we compiled climate, atmospheric CO2 concentrations, nitrogen deposition, land use and land cover change (LULCC), C3 / C4 grasses fractions, major crops, phenology and soil data into a standard format for global (0.5° × 0.5° resolution) and regional (North American: 0.25° × 0.25° resolution) simulations. In order to meet the needs of MsTMIP, improvements were made to several of the original environmental data sets, by improving the quality, and/or changing their spatial and temporal coverage, and resolution. The resulting standardized model driver data sets are being used by over 20 different models participating in MsTMIP. The data are archived at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov) to provide long-term data management and distribution.

Modeling and Monitoring Terrestrial Primary Production in a Changing Global Environment: Toward a Multiscale Synthesis of Observation and Simulation

There is a critical need to monitor and predict terrestrial primary production, the key indicator of ecosystem functioning, in a changing global environment. Here we provide a brief review of three major approaches to monitoring and predicting terrestrial primary production: (1) ground-based field measurements, (2) satellite-based observations, and (3) process-based ecosystem modelling. Much uncertainty exists in the multi-approach estimations of terrestrial gross primary production (GPP) and net primary production (NPP). To improve the capacity of model simulation and prediction, it is essential to evaluate ecosystem models against ground and satellite-based measurements and observations. As a case, we have shown the performance of the dynamic land ecosystem model (DLEM) at various scales from site to region to global. We also discuss how terrestrial primary production might respond to climate change and increasing atmospheric CO2and uncertainties associated with model and data. Further progress in monitoring and predicting terrestrial primary production requires a multiscale synthesis of observations and model simulations. In the Anthropocene era in which human activity has indeed changed the Earth’s biosphere, therefore, it is essential to incorporate the socioeconomic component into terrestrial ecosystem models for accurately estimating and predicting terrestrial primary production in a changing global environment.

The North American Carbon Program Multi-Scale Synthesis and Terrestrial Model Intercomparison Project – Part 1: Overview and experimental design

Abstract. Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding of land–atmosphere carbon exchange to larger regions. The North American Carbon Program (NACP) Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal model intercomparison and evaluation effort focused on improving the diagnosis and attribution of carbon exchange at regional and global scales. MsTMIP builds upon current and past synthesis activities, and has a unique framework designed to isolate, interpret, and inform understanding of how model structural differences impact estimates of carbon uptake and release. Here we provide an overview of the MsTMIP effort and describe how the MsTMIP experimental design enables the assessment and quantification of TBM structural uncertainty. Model structure refers to the types of processes considered (e.g., nutrient cycling, disturbance, lateral transport of carbon), and how these processes are represented (e.g., photosynthetic formulation, temperature sensitivity, respiration) in the models. By prescribing a common experimental protocol with standard spin-up procedures and driver data sets, we isolate any biases and variability in TBM estimates of regional and global carbon budgets resulting from differences in the models themselves (i.e., model structure) and model-specific parameter values. An initial intercomparison of model structural differences is represented using hierarchical cluster diagrams (a.k.a. dendrograms), which highlight similarities and differences in how models account for carbon cycle, vegetation, energy, and nitrogen cycle dynamics. We show that, despite the standardized protocol used to derive initial conditions, models show a high degree of variation for GPP, total living biomass, and total soil carbon, underscoring the influence of differences in model structure and parameterization on model estimates.

Multiscale phase screen synthesis based on local principal component analysis

Motivated by the increasing importance of adaptive optics (AO) systems for improving the real resolution of large ground telescopes, and by the need of testing the AO system performance in realistic working conditions, in this paper we address the problem of simulating the turbulence effect on ground telescope observations at high resolution. The procedure presented here generalizes the multiscale stochastic approach introduced in our earlier paper [Appl. Opt. 50, 4124 (2011)], with respect to the previous solution, a relevant computational time reduction is obtained by exploiting a local spatial principal component analysis (PCA) representation of the turbulence. Furthermore, the turbulence at low resolution is modeled as a moving average (MA) process, while previously [Appl. Opt. 50, 4124 (2011)] the wind velocity was restricted to be directed along one of the two spatial axes, the use of such MA model allows the turbulence to evolve indifferently in all the directions. In our simulations, the proposed procedure reproduces the theoretical statistical characteristics of the turbulent phase with good accuracy.

Multirate diversity strategy of fractal modulation

Previous analyses of fractal modulation were carried out mostly from a signle perspective or a subband, but the analyses from the perspective of multiscale synthesis have not been found yet; while multiscale synthesis is just the essence of the mutlirate diversity which is the most important characteristic of fractal modulation. As for the mutlirate diversity of fractal modulation, previous studies only dealt with the general outspread of its concept, lacked the thorough and intensive quantitative comparison and analysis. In light of the above fact, from the perspective of multiscale synthesis, in this paper we provide a comprehensive analysis of the multirate diversity of fractal modulation and corresponding quantitative analysis. The results show that mutlirate diversity, which is a fusion of frequency diversity and time diversity, pays an acceptable price in spectral efficiency in exchange for a significant improvement in bit error rate. It makes fractal modulation particularly suitable for the channels whose bandwidth and duration parameters are unknown or cannot be predicted to the transmitter. Surely it is clearly of great significance for reliable communications. Moreover, we also attain the ability to flexibly make various rate-bandwidth tradeoffs between the transmitter and the receiver, to freely select the reception time and to expediently control the total bandwidth. Furthermore, the acquisitions or improvements of these fine features could provide support of the technical feasibility for the electromagnetic spectrum control technology in a complex electromagnetic environment.

Controlled Multiscale Synthesis of Porous Coordination Polymer in Nano/Micro Regimes

A simple and straightforward method combines microwave-assisted solvothermal conditions with the coordination modulation method to achieve the size-controlled formation of the porous coordination polymer (PCP), [Cu3(btc)2] (where btc represents benzene-1,3,5-tricarboxylate) in the nano/micro regimes. The addition of a monocarboxylic acid modulator to the reaction mixture greatly influenced the morphology of the resulting sample, through competitive coordination interactions during the crystal formation process. By adjusting the concentration of dodecanoic acid additive, we could subtly control the nucleation rate of a [Cu3(btc)2] framework and, thus, the resulting crystal size. Homogeneous nanocrystals of the PCP with sizes ranging from few tenths of nanometers up to few micrometers could be successfully obtained in a controlled manner. X-ray diffractions and gas sorption measurements revealed highly crystalline particles with large pore volumes. Moreover, variations in the sorption profiles could be corr...

Integrated multiscale product and process control of polymeric coating curing

In automotive coating manufacturing, control of curing of thin films of wet paint on vehicle panels is always a very challenging operational task. This is especially true when both process efficiency and product quality need to be controlled simultaneously. The challenges in this task are multiple. First, coating quality is not measurable online and its characterization is multiscale in length and time. Second, coating curing is a multistage process where heat and mass transfer and polymerization take place also in multiscale of length and time, most of which are not measurable online either. In this paper, we introduce an integrated multiscale product and process control (IMPPC) scheme that can be used to control effectively the reactive drying process. By resorting to this scheme, a set of advanced methodologies for multiscale modeling, model simplification, and multiscale controller synthesis can be seamlessly integrated to construct a high-performance control system. It is demonstrated that this control system has extraordinary performance on set-point tracking and disturbance rejection. Most importantly, it offers unique opportunities to achieve all-time on-aim control of both coating quality and process performance covering a wide range of time and length scales.

Schooling behaviour and environmental forcing in relation to anchoveta distribution: An analysis across multiple spatial scales

The Peruvian anchovy or anchoveta ( Engraulis ringens) supports the highest worldwide fishery landings and varies in space and time over many scales. Here we present the first comprehensive sub-mesocale study of anchoveta distribution in relation to the environment. During November 2004, we conducted a behavioural ecology survey off central Peru and used a series of observational and sampling tools including SST and CO 2 sensors, Niskin bottles, CTD probes, zooplankton sampling, stomach content analysis, echo-sounder, multibeam sonar, and bird observations. The sub-mesoscale survey areas were chosen from mesoscale acoustic surveys. A routine coast-wide (∼2000 km) acoustic survey performed just after the sub-mesoscale surveys, provided information at an even larger population scale. The availability of nearly concurrent sub-mesoscale, mesoscale and coast-wide information on anchoveta distribution allowed for a unique multi-scale synthesis. At the sub-mesoscale (100s m to km) physical processes (internal waves and frontogenesis) concentrated plankton into patches and determined anchoveta spatial distribution. At the mesoscale (10s km) location relative to the zone of active upwelling (and age of the upwelled water) and the depth of the oxycline had strong impacts on the anchoveta. Finally, over 100s km the size of the productive area, as defined by the upwelled cold coastal waters, was the determining factor. We propose a conceptual view of the relative importance of social behaviour and environmental (biotic and abiotic) processes on the spatial distribution of anchoveta. Our ecological space has two y-axis; one based on self-organization (social behaviour), and the other based on the environmental processes. At scales from the individual (10s cm), to the nucleus (m), social behaviour (e.g. the need to school) drives spatial organization. At scales larger than the school, environmental forces are the main driver of fish distribution. The conceptual ecosystem models presented in this paper may provide the final links needed to develop accurate forecasts of the spatial distribution of anchoveta over multiple scales.

Multi-scale Texture Synthesis

Multi-scale Texture Synthesis

Extending natural textures with multi-scale synthesis

This paper presents a texture synthesis algorithm that was designed for the tile-less generation of large images of arbitrary size from small sample images. The synthesised texture shows features that are visually similar to the sample over a wide frequency range. The development of the algorithm aimed at achieving high quality results for a large range of natural textures, incorporation of the original samples in the synthesis product, ease of use and good texturing speed even with input sample data two magnitudes larger than used by previous techniques. Like other algorithms we utilise an implicit texture model by copying arbitrary shaped texture patches from the sample to the destination over a multi-scale image pyramid. Our method combines the advantages of different previous techniques with respect to quality. A mixture of exhaustive searching, massive parallel computing and the well-known LBG-algorithm ensures a good balance between texturing quality and speed.

Algorithmic shape modeling with subdivision surfaces

We present methods for synthesizing 3D shape features on subdivision surfaces using multi-scale procedural techniques. Multi-scale synthesis is a powerful approach for creating surfaces with different levels of detail. Our methods can also blend multiple example multi-resolution surfaces, including procedurally defined surfaces as well as captured models.

Geographic Scaling Issues in Integrated Assessments of Climate Change

Geographic scale matters in integrated assessments of global climate change issues, but incorporating a variety of scales and cross-scale dynamics in integrated assessment modeling requires confronting a number of conceptual and operational challenges, including upscaling, downscaling, tracing out cross-scale relationships, and multi-scale synthesis.

Texture synthesis via a noncausal nonparametric multiscale Markov random field

Our noncausal, nonparametric, multiscale, Markov random field (MRF) model is capable of synthesizing and capturing the characteristics of a wide variety of textures, from the highly structured to the stochastic. We use a multiscale synthesis algorithm incorporating local annealing to obtain larger realizations of texture visually indistinguishable from the training texture.